Repository: marcotcr/lime Branch: master Commit: fd7eb2e6f760 Files: 63 Total size: 39.2 MB Directory structure: gitextract_jwcrr_g_/ ├── .gitignore ├── .travis.yml ├── CONTRIBUTING.md ├── LICENSE ├── MANIFEST.in ├── README.md ├── benchmark/ │ ├── __init__.py │ ├── table_perf.py │ └── text_perf.py ├── binder/ │ └── environment.yml ├── citation.bib ├── doc/ │ ├── blog_post.md │ ├── conf.py │ ├── index.rst │ ├── lime.rst │ └── notebooks/ │ ├── Latin Hypercube Sampling.ipynb │ ├── Lime - basic usage, two class case.ipynb │ ├── Lime - multiclass.ipynb │ ├── Lime with Recurrent Neural Networks.ipynb │ ├── Submodular Pick examples.ipynb │ ├── Tutorial - Faces and GradBoost.ipynb │ ├── Tutorial - Image Classification Keras.ipynb │ ├── Tutorial - MNIST and RF.ipynb │ ├── Tutorial - continuous and categorical features.ipynb │ ├── Tutorial - images - Pytorch.ipynb │ ├── Tutorial - images.ipynb │ ├── Tutorial_H2O_continuous_and_cat.ipynb │ ├── Using lime for regression.ipynb │ └── data/ │ ├── adult.csv │ ├── co2_data.csv │ ├── imagenet_class_index.json │ └── mushroom_data.csv ├── lime/ │ ├── __init__.py │ ├── bundle.js │ ├── discretize.py │ ├── exceptions.py │ ├── explanation.py │ ├── js/ │ │ ├── bar_chart.js │ │ ├── explanation.js │ │ ├── main.js │ │ ├── predict_proba.js │ │ └── predicted_value.js │ ├── lime_base.py │ ├── lime_image.py │ ├── lime_tabular.py │ ├── lime_text.py │ ├── package.json │ ├── style.css │ ├── submodular_pick.py │ ├── test_table.html │ ├── tests/ │ │ ├── __init__.py │ │ ├── test_discretize.py │ │ ├── test_generic_utils.py │ │ ├── test_lime_tabular.py │ │ ├── test_lime_text.py │ │ └── test_scikit_image.py │ ├── utils/ │ │ ├── __init__.py │ │ └── generic_utils.py │ ├── webpack.config.js │ └── wrappers/ │ ├── __init__.py │ └── scikit_image.py ├── setup.cfg └── setup.py ================================================ FILE CONTENTS ================================================ ================================================ FILE: .gitignore ================================================ # Compiled python modules. *.pyc # Setuptools distribution folder. /dist/ /lime/node_modules # Python egg metadata, regenerated from source files by setuptools. /*.egg-info # Unit test / coverage reports .cache # Created by https://www.gitignore.io/api/pycharm ### PyCharm ### # Covers JetBrains IDEs: IntelliJ, RubyMine, PhpStorm, AppCode, PyCharm, CLion, Android Studio and Webstorm # Reference: https://intellij-support.jetbrains.com/hc/en-us/articles/206544839 # User-specific stuff: .idea/workspace.xml .idea/tasks.xml .idea/dictionaries .idea/vcs.xml .idea/jsLibraryMappings.xml # Sensitive or high-churn files: .idea/dataSources.ids .idea/dataSources.xml .idea/dataSources.local.xml .idea/sqlDataSources.xml .idea/dynamic.xml .idea/uiDesigner.xml # Gradle: .idea/gradle.xml .idea/libraries # Mongo Explorer plugin: .idea/mongoSettings.xml ## File-based project format: *.iws ## Plugin-specific files: # IntelliJ /out/ # mpeltonen/sbt-idea plugin .idea_modules/ # JIRA plugin atlassian-ide-plugin.xml # Crashlytics plugin (for Android Studio and IntelliJ) com_crashlytics_export_strings.xml crashlytics.properties crashlytics-build.properties fabric.properties ### PyCharm Patch ### # Comment Reason: https://github.com/joeblau/gitignore.io/issues/186#issuecomment-215987721 # *.iml # modules.xml # .idea/misc.xml # *.ipr # Pycharm .idea ================================================ FILE: .travis.yml ================================================ dist: xenial sudo: false language: python cache: pip python: - "3.6" - "3.7" # command to install dependencies install: - python -m pip install -U pip - python -m pip install -e .[dev] # command to run tests script: - pytest lime - flake8 lime ================================================ FILE: CONTRIBUTING.md ================================================ ## Contributing I am delighted when people want to contribute to LIME. Here are a few things to keep in mind before sending in a pull request: * We are now using flake8 as a style guide enforcer (I plan on adding eslint for javascript soon). Make sure your code passes the default flake8 execution. * There must be a really good reason to change the external interfaces - I want to avoid breaking previous code as much as possible. * If you are adding a new feature, please let me know the use case and the rationale behind how you did it (unless it's obvious) If you want to contribute but don't know where to start, take a look at the [issues page](https://github.com/marcotcr/lime/issues), or at the list below. # Roadmap Here are a few high level features I want to incorporate in LIME. If you want to work incrementally in any of these, feel free to start a branch. 1. Creating meaningful tests that we can run before merging things. Right now I run the example notebooks and the few tests we have. 2. Creating a wrapper that computes explanations for a particular dataset, and suggests instances for the user to look at (similar to what we did in [the paper](http://arxiv.org/abs/1602.04938)) 3. Making LIME work with images in a reasonable time. The explanations we used in the paper took a few minutes, which is too slow. 4. Thinking through what is needed to use LIME in regression problems. An obvious problem is that features with different scales make it really hard to interpret. 5. Figuring out better alternatives to discretizing the data for tabular data. Discretizing is definitely more interpretable, but we may just want to treat features as continuous. 6. Figuring out better ways to sample around a data point for tabular data. One example is sampling columns from the training set assuming independence, or some form of conditional sampling. ================================================ FILE: LICENSE ================================================ Copyright (c) 2016, Marco Tulio Correia Ribeiro All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. ================================================ FILE: MANIFEST.in ================================================ include lime/*.js include LICENSE ================================================ FILE: README.md ================================================ # lime [![Build Status](https://travis-ci.org/marcotcr/lime.svg?branch=master)](https://travis-ci.org/marcotcr/lime) [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/marcotcr/lime/master) This project is about explaining what machine learning classifiers (or models) are doing. At the moment, we support explaining individual predictions for text classifiers or classifiers that act on tables (numpy arrays of numerical or categorical data) or images, with a package called lime (short for local interpretable model-agnostic explanations). Lime is based on the work presented in [this paper](https://arxiv.org/abs/1602.04938) ([bibtex here for citation](https://github.com/marcotcr/lime/blob/master/citation.bib)). Here is a link to the promo video: KDD promo video Our plan is to add more packages that help users understand and interact meaningfully with machine learning. Lime is able to explain any black box classifier, with two or more classes. All we require is that the classifier implements a function that takes in raw text or a numpy array and outputs a probability for each class. Support for scikit-learn classifiers is built-in. ## Installation The lime package is on [PyPI](https://pypi.python.org/pypi/lime). Simply run: ```sh pip install lime ``` Or clone the repository and run: ```sh pip install . ``` We dropped python2 support in `0.2.0`, `0.1.1.37` was the last version before that. ## Screenshots Below are some screenshots of lime explanations. These are generated in html, and can be easily produced and embedded in ipython notebooks. We also support visualizations using matplotlib, although they don't look as nice as these ones. #### Two class case, text Negative (blue) words indicate atheism, while positive (orange) words indicate christian. The way to interpret the weights by applying them to the prediction probabilities. For example, if we remove the words Host and NNTP from the document, we expect the classifier to predict atheism with probability 0.58 - 0.14 - 0.11 = 0.31. ![twoclass](doc/images/twoclass.png) #### Multiclass case ![multiclass](doc/images/multiclass.png) #### Tabular data ![tabular](doc/images/tabular.png) #### Images (explaining prediction of 'Cat' in pros and cons) ## Tutorials and API For example usage for text classifiers, take a look at the following two tutorials (generated from ipython notebooks): - [Basic usage, two class. We explain random forest classifiers.](https://marcotcr.github.io/lime/tutorials/Lime%20-%20basic%20usage%2C%20two%20class%20case.html) - [Multiclass case](https://marcotcr.github.io/lime/tutorials/Lime%20-%20multiclass.html) For classifiers that use numerical or categorical data, take a look at the following tutorial (this is newer, so please let me know if you find something wrong): - [Tabular data](https://marcotcr.github.io/lime/tutorials/Tutorial%20-%20continuous%20and%20categorical%20features.html) - [Tabular data with H2O models](https://marcotcr.github.io/lime/tutorials/Tutorial_H2O_continuous_and_cat.html) - [Latin Hypercube Sampling](doc/notebooks/Latin%20Hypercube%20Sampling.ipynb) For image classifiers: - [Images - basic](https://marcotcr.github.io/lime/tutorials/Tutorial%20-%20images.html) - [Images - Faces](https://github.com/marcotcr/lime/blob/master/doc/notebooks/Tutorial%20-%20Faces%20and%20GradBoost.ipynb) - [Images with Keras](https://github.com/marcotcr/lime/blob/master/doc/notebooks/Tutorial%20-%20Image%20Classification%20Keras.ipynb) - [MNIST with random forests](https://github.com/marcotcr/lime/blob/master/doc/notebooks/Tutorial%20-%20MNIST%20and%20RF.ipynb) - [Images with PyTorch](https://github.com/marcotcr/lime/blob/master/doc/notebooks/Tutorial%20-%20images%20-%20Pytorch.ipynb) For regression: - [Simple regression](https://marcotcr.github.io/lime/tutorials/Using%2Blime%2Bfor%2Bregression.html) Submodular Pick: - [Submodular Pick](https://github.com/marcotcr/lime/tree/master/doc/notebooks/Submodular%20Pick%20examples.ipynb) The raw (non-html) notebooks for these tutorials are available [here](https://github.com/marcotcr/lime/tree/master/doc/notebooks). The API reference is available [here](https://lime-ml.readthedocs.io/en/latest/). ## What are explanations? Intuitively, an explanation is a local linear approximation of the model's behaviour. While the model may be very complex globally, it is easier to approximate it around the vicinity of a particular instance. While treating the model as a black box, we perturb the instance we want to explain and learn a sparse linear model around it, as an explanation. The figure below illustrates the intuition for this procedure. The model's decision function is represented by the blue/pink background, and is clearly nonlinear. The bright red cross is the instance being explained (let's call it X). We sample instances around X, and weight them according to their proximity to X (weight here is indicated by size). We then learn a linear model (dashed line) that approximates the model well in the vicinity of X, but not necessarily globally. For more information, [read our paper](https://arxiv.org/abs/1602.04938), or take a look at [this blog post](https://www.oreilly.com/learning/introduction-to-local-interpretable-model-agnostic-explanations-lime). ## Contributing Please read [this](CONTRIBUTING.md). ================================================ FILE: benchmark/__init__.py ================================================ ================================================ FILE: benchmark/table_perf.py ================================================ """ A helper script for evaluating performance of changes to the tabular explainer, in this case different implementations and methods for distance calculation. """ import time from sklearn.ensemble import RandomForestClassifier from sklearn.datasets import make_classification from lime.lime_tabular import LimeTabularExplainer def interpret_data(X, y, func): explainer = LimeTabularExplainer(X, discretize_continuous=False, kernel_width=3) times, scores = [], [] for r_idx in range(100): start_time = time.time() explanation = explainer.explain_instance(X[r_idx, :], func) times.append(time.time() - start_time) scores.append(explanation.score) print('...') return times, scores if __name__ == '__main__': X_raw, y_raw = make_classification(n_classes=2, n_features=1000, n_samples=1000) clf = RandomForestClassifier() clf.fit(X_raw, y_raw) y_hat = clf.predict_proba(X_raw) times, scores = interpret_data(X_raw, y_hat, clf.predict_proba) print('%9.4fs %9.4fs %9.4fs' % (min(times), sum(times) / len(times), max(times))) print('%9.4f %9.4f% 9.4f' % (min(scores), sum(scores) / len(scores), max(scores))) ================================================ FILE: benchmark/text_perf.py ================================================ import time import sklearn import sklearn.ensemble import sklearn.metrics from sklearn.datasets import fetch_20newsgroups from sklearn.pipeline import make_pipeline from lime.lime_text import LimeTextExplainer def interpret_data(X, y, func, class_names): explainer = LimeTextExplainer(class_names=class_names) times, scores = [], [] for r_idx in range(10): start_time = time.time() exp = explainer.explain_instance(newsgroups_test.data[r_idx], func, num_features=6) times.append(time.time() - start_time) scores.append(exp.score) print('...') return times, scores if __name__ == '__main__': categories = ['alt.atheism', 'soc.religion.christian'] newsgroups_train = fetch_20newsgroups(subset='train', categories=categories) newsgroups_test = fetch_20newsgroups(subset='test', categories=categories) class_names = ['atheism', 'christian'] vectorizer = sklearn.feature_extraction.text.TfidfVectorizer(lowercase=False) train_vectors = vectorizer.fit_transform(newsgroups_train.data) test_vectors = vectorizer.transform(newsgroups_test.data) rf = sklearn.ensemble.RandomForestClassifier(n_estimators=500) rf.fit(train_vectors, newsgroups_train.target) pred = rf.predict(test_vectors) sklearn.metrics.f1_score(newsgroups_test.target, pred, average='binary') c = make_pipeline(vectorizer, rf) interpret_data(train_vectors, newsgroups_train.target, c.predict_proba, class_names) ================================================ FILE: binder/environment.yml ================================================ name: lime-dev channels: - conda-forge dependencies: - python=3.7.* # lime install dependencies - matplotlib - numpy - scipy - scikit-learn - scikit-image - pyDOE2 # for testing - flake8 - pytest # for examples - jupyter - pandas - keras - pytorch::pytorch-cpu - tensorflow - h2oai::h2o - py-xgboost - pip: # lime source code - -e .. ================================================ FILE: citation.bib ================================================ @inproceedings{lime, author = {Marco Tulio Ribeiro and Sameer Singh and Carlos Guestrin}, title = {"Why Should {I} Trust You?": Explaining the Predictions of Any Classifier}, booktitle = {Proceedings of the 22nd {ACM} {SIGKDD} International Conference on Knowledge Discovery and Data Mining, San Francisco, CA, USA, August 13-17, 2016}, pages = {1135--1144}, year = {2016}, } ================================================ FILE: doc/blog_post.md ================================================ # LIME - Local Interpretable Model-Agnostic Explanations In this post, we'll talk about the method for explaining the predictions of any classifier described in [this paper](http://arxiv.org/pdf/1602.04938v1.pdf), and implemented in [this open source package](https://github.com/marcotcr/lime). # Motivation: why do we want to understand predictions? Machine learning is a buzzword these days. With computers beating professionals in games like [Go](https://deepmind.com/alpha-go.html), many people have started asking if machines would also make for better [drivers](https://www.google.com/selfdrivingcar/), or even doctors. Many of the state of the art machine learning models are functionally black boxes, as it is nearly impossible to get a feeling for its inner workings. This brings us to a question of trust: do I trust that a certain prediction from the model is correct? Or do I even trust that the model is making reasonable predictions in general? While the stakes are low in a Go game, they are much higher if a computer is replacing my doctor, or deciding if I am a suspect of terrorism ([Person of Interest](http://www.imdb.com/title/tt1839578/), anyone?). Perhaps more commonly, if a company is replacing some system with one based on machine learning, it has to trust that the machine learning model will behave reasonably well. It seems intuitive that explaining the rationale behind individual predictions would make us better positioned to trust or mistrust the prediction, or the classifier as a whole. Even if we can't necesseraly understand how the model behaves on all cases, it may be possible (and indeed it is in most cases) to understand how it behaves in particular cases. Finally, a word on accuracy. If you have had experience with machine learning, I bet you are thinking something along the lines of: "of course I know my model is going to perform well in the real world, I have really high cross validation accuracy! Why do I need to understand it's predictions when I know it gets it right 99% of the time?". As anyone who has used machine learning in the real world (not only in a static dataset) can attest, accuracy on cross validation can be very misleading. Sometimes data that shouldn't be available leaks into the training data accidentaly. Sometimes the way you gather data introduces correlations that will not exist in the real world, which the model exploits. Many other tricky problems can give us a false understanding of performance, even in [doing A/B tests](http://www.exp-platform.com/documents/puzzlingoutcomesincontrolledexperiments.pdf). I am not saying you shouldn't measure accuracy, but simply that it should not be your only metric for assessing trust. # Lime: A couple of examples. First, we give an example from text classification. The famous [20 newsgroups dataset](http://qwone.com/~jason/20Newsgroups/) is a benchmark in the field, and has been used to compare different models in several papers. We take two classes that are suposedly harder to distinguish, due to the fact that they share many words: Christianity and Atheism. Training a random forest with 500 trees, we get a test set accuracy of 92.4%, which is surprisingly high. If accuracy was our only measure of trust, we would definitely trust this algorithm. Below is an explanation for an arbitrary instance in the test set, generated using [the lime package](https://github.com/marcotcr/lime). ![alt text](https://raw.githubusercontent.com/marcotcr/lime/master/doc/images/twoclass.png "Explanation") This is a case where the classifier predicts the instance correctly, but for the wrong reasons. A little further exploration shows us that the word "Posting" (part of the email header) appears in 21.6% of the examples in the training set, only two times in the class 'Christianity'. This is repeated on the test set, where it appears in almost 20% of the examples, only twice in 'Christianity'. This kind of quirk in the dataset makes the problem much easier than it is in the real world, where this classifier would **not** be able to distinguish between christianity and atheism documents. This is hard to see just by looking at accuracy or raw data, but easy once explanations are provided. Such insights become common once you understand what models are actually doing, leading to models that generalize much better. Note further how interpretable the explanations are: they correspond to a very sparse linear model (with only 6 features). Even though the underlying classifier is a complicated random forest, in the neighborhood of this example it behaves roughly as a linear model. Sure nenough, if we remove the words "Host" and "NNTP" from the example, the "atheism" prediction probability becomes close to 0.57 - 0.14 - 0.12 = 0.31. Below is an image from our paper, where we explain Google's [Inception neural network](https://github.com/google/inception) on some arbitary images. In this case, we keep as explanations the parts of the image that are most positive towards a certain class. In this case, the classifier predicts Electric Guitar even though the image contains an acoustic guitar. The explanation reveals why it would confuse the two: the fretboard is very similar. Getting explanations for image classifiers is something that is not yet available in the lime package, but we are working on it. ![alt text](https://raw.githubusercontent.com/marcotcr/lime/master/doc/images/image_from_paper.png "Explanation") # Lime: how we get explanations Lime is short for Local Interpretable Model-Agnostic Explanations. Each part of the name reflects something that we desire in explanations. **Local** refers to local fidelity - i.e., we want the explanation to really reflect the behaviour of the classifier "around" the instance being predicted. This explanation is useless unless it is **interpretable** - that is, unless a human can make sense of it. Lime is able to explain any model without needing to 'peak' into it, so it is **model-agnostic**. We now give a high level overview of how lime works. For more details, check out our [pre-print](http://arxiv.org/pdf/1602.04938v1.pdf). First, a word about **interpretability**. Some classifiers use representations that are not intuitive to users at all (e.g. word embeddings). Lime explains those classifiers in terms of interpretable representations (words), even if that is not the representation actually used by the classifier. Further, lime takes human limitations into account: i.e. the explanations are not too long. Right now, our package supports explanations that are sparse linear models (as presented before), although we are working on other representations. In order to be **model-agnostic**, lime can't peak into the model. In order to figure out what parts of the interpretable input are contributing to the prediction, we perturb the input around its neighborhood and see how the model's predictions behave. We then weight these perturbed data points by their proximity to the original example, and learn an interpretable model on those and the associated predictions. For example, if we are trying to explain the prediction for the sentence "I hate this movie", we will perturb the sentence and get predictions on sentences such as "I hate movie", "I this movie", "I movie", "I hate", etc. Even if the original classifier takes many more words into account globally, it is reasonable to expect that around this example only the word "hate" will be relevant. Note that if the classifier uses some uninterpretable representation such as word embeddings, this still works: we just represent the perturbed sentences with word embeddings, and the explanation will still be in terms of words such as "hate" or "movie". An illustration of this process is given below. The original model's decision function is represented by the blue/pink background, and is clearly nonlinear. The bright red cross is the instance being explained (let's call it X). We sample perturbed instances around X, and weight them according to their proximity to X (weight here is represented by size). We get original model's prediction on these perturbed instances, and then learn a linear model (dashed line) that approximates the model well in the vicinity of X. Note that the explanation in this case is not faithful globally, but it is faithful locally around X. ![alt text](https://raw.githubusercontent.com/marcotcr/lime/master/doc/images/lime.png "Intuition") # Conclusion I hope I've convinced you that understanding individual predictions from classifiers is an important problem. Having explanations lets you make an informed decision about how much you trust the prediction or the model as a whole, and provides insights that can be used to improve the model. If you're interested in going more in-depth into how lime works, and the kinds of experiments we did to validate the usefulness of such explanations, [here is a link to our pre-print paper](http://arxiv.org/pdf/1602.04938v1.pdf). If you are interested in trying lime for text classifiers, make sure you check out our [python package](https://github.com/marcotcr/lime/). Installation is as simple as typing: ```pip install lime``` The package is very easy to use. It is particulary easy to explain scikit-learn classifiers. In the github page we also link to a few tutorials, such as [this one](http://marcotcr.github.io/lime/tutorials/Lime%20-%20basic%20usage%2C%20two%20class%20case.html), with examples from scikit-learn. ================================================ FILE: doc/conf.py ================================================ # -*- coding: utf-8 -*- # # lime documentation build configuration file, created by # sphinx-quickstart on Fri Mar 18 16:20:40 2016. # # This file is execfile()d with the current directory set to its # containing dir. # # Note that not all possible configuration values are present in this # autogenerated file. # # All configuration values have a default; values that are commented out # serve to show the default. import sys import os # If extensions (or modules to document with autodoc) are in another directory, # add these directories to sys.path here. If the directory is relative to the # documentation root, use os.path.abspath to make it absolute, like shown here. #sys.path.insert(0, os.path.abspath('.')) curr_path = os.path.dirname(os.path.abspath(os.path.expanduser(__file__))) libpath = os.path.join(curr_path, '../') sys.path.insert(0, libpath) sys.path.insert(0, curr_path) import mock MOCK_MODULES = ['numpy', 'scipy', 'scipy.sparse', 'scipy.special', 'scipy.stats', 'scipy.stats.distributions', 'sklearn', 'sklearn.preprocessing', 'sklearn.linear_model', 'matplotlib', 'sklearn.datasets', 'sklearn.ensemble', 'sklearn.cross_validation', 'sklearn.feature_extraction', 'sklearn.feature_extraction.text', 'sklearn.metrics', 'sklearn.naive_bayes', 'sklearn.pipeline', 'sklearn.utils', 'pyDOE2',] # for mod_name in MOCK_MODULES: # sys.modules[mod_name] = mock.Mock() import scipy import scipy.stats import scipy.stats.distributions import lime import lime.lime_text import lime.lime_tabular import lime.explanation import lime.lime_base import lime.submodular_pick # -- General configuration ------------------------------------------------ # If your documentation needs a minimal Sphinx version, state it here. #needs_sphinx = '1.0' # Add any Sphinx extension module names here, as strings. They can be # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom # ones. extensions = [ 'sphinx.ext.autodoc', 'sphinx.ext.mathjax', 'sphinx.ext.napoleon', ] # Add any paths that contain templates here, relative to this directory. templates_path = ['_templates'] # The suffix(es) of source filenames. # You can specify multiple suffix as a list of string: # source_suffix = ['.rst', '.md'] source_suffix = '.rst' # The encoding of source files. #source_encoding = 'utf-8-sig' # The master toctree document. master_doc = 'index' # General information about the project. project = u'lime' copyright = u'2016, Marco Tulio Ribeiro' author = u'Marco Tulio Ribeiro' # The version info for the project you're documenting, acts as replacement for # |version| and |release|, also used in various other places throughout the # built documents. # # The short X.Y version. version = u'0.1' # The full version, including alpha/beta/rc tags. release = u'0.1' # The language for content autogenerated by Sphinx. Refer to documentation # for a list of supported languages. # # This is also used if you do content translation via gettext catalogs. # Usually you set "language" from the command line for these cases. language = None # There are two options for replacing |today|: either, you set today to some # non-false value, then it is used: #today = '' # Else, today_fmt is used as the format for a strftime call. #today_fmt = '%B %d, %Y' # List of patterns, relative to source directory, that match files and # directories to ignore when looking for source files. exclude_patterns = ['_build'] # The reST default role (used for this markup: `text`) to use for all # documents. #default_role = None # If true, '()' will be appended to :func: etc. cross-reference text. #add_function_parentheses = True # If true, the current module name will be prepended to all description # unit titles (such as .. function::). #add_module_names = True # If true, sectionauthor and moduleauthor directives will be shown in the # output. They are ignored by default. #show_authors = False # The name of the Pygments (syntax highlighting) style to use. pygments_style = 'sphinx' # A list of ignored prefixes for module index sorting. #modindex_common_prefix = [] # If true, keep warnings as "system message" paragraphs in the built documents. #keep_warnings = False # If true, `todo` and `todoList` produce output, else they produce nothing. todo_include_todos = False # -- Options for HTML output ---------------------------------------------- # The theme to use for HTML and HTML Help pages. See the documentation for # a list of builtin themes. html_theme = 'default' # Theme options are theme-specific and customize the look and feel of a theme # further. For a list of options available for each theme, see the # documentation. #html_theme_options = {} # Add any paths that contain custom themes here, relative to this directory. #html_theme_path = [] # The name for this set of Sphinx documents. If None, it defaults to # " v documentation". #html_title = None # A shorter title for the navigation bar. Default is the same as html_title. #html_short_title = None # The name of an image file (relative to this directory) to place at the top # of the sidebar. #html_logo = None # The name of an image file (relative to this directory) to use as a favicon of # the docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32 # pixels large. #html_favicon = None # Add any paths that contain custom static files (such as style sheets) here, # relative to this directory. They are copied after the builtin static files, # so a file named "default.css" will overwrite the builtin "default.css". html_static_path = ['_static'] # Add any extra paths that contain custom files (such as robots.txt or # .htaccess) here, relative to this directory. These files are copied # directly to the root of the documentation. #html_extra_path = [] # If not '', a 'Last updated on:' timestamp is inserted at every page bottom, # using the given strftime format. #html_last_updated_fmt = '%b %d, %Y' # If true, SmartyPants will be used to convert quotes and dashes to # typographically correct entities. #html_use_smartypants = True # Custom sidebar templates, maps document names to template names. #html_sidebars = {} # Additional templates that should be rendered to pages, maps page names to # template names. #html_additional_pages = {} # If false, no module index is generated. #html_domain_indices = True # If false, no index is generated. #html_use_index = True # If true, the index is split into individual pages for each letter. #html_split_index = False # If true, links to the reST sources are added to the pages. #html_show_sourcelink = True # If true, "Created using Sphinx" is shown in the HTML footer. Default is True. #html_show_sphinx = True # If true, "(C) Copyright ..." is shown in the HTML footer. Default is True. #html_show_copyright = True # If true, an OpenSearch description file will be output, and all pages will # contain a tag referring to it. The value of this option must be the # base URL from which the finished HTML is served. #html_use_opensearch = '' # This is the file name suffix for HTML files (e.g. ".xhtml"). #html_file_suffix = None # Language to be used for generating the HTML full-text search index. # Sphinx supports the following languages: # 'da', 'de', 'en', 'es', 'fi', 'fr', 'hu', 'it', 'ja' # 'nl', 'no', 'pt', 'ro', 'ru', 'sv', 'tr' #html_search_language = 'en' # A dictionary with options for the search language support, empty by default. # Now only 'ja' uses this config value #html_search_options = {'type': 'default'} # The name of a javascript file (relative to the configuration directory) that # implements a search results scorer. If empty, the default will be used. #html_search_scorer = 'scorer.js' # Output file base name for HTML help builder. htmlhelp_basename = 'limedoc' # -- Options for LaTeX output --------------------------------------------- latex_elements = { # The paper size ('letterpaper' or 'a4paper'). #'papersize': 'letterpaper', # The font size ('10pt', '11pt' or '12pt'). #'pointsize': '10pt', # Additional stuff for the LaTeX preamble. #'preamble': '', # Latex figure (float) alignment #'figure_align': 'htbp', } # Grouping the document tree into LaTeX files. List of tuples # (source start file, target name, title, # author, documentclass [howto, manual, or own class]). latex_documents = [ (master_doc, 'lime.tex', u'lime Documentation', u'Marco Tulio Ribeiro', 'manual'), ] # The name of an image file (relative to this directory) to place at the top of # the title page. #latex_logo = None # For "manual" documents, if this is true, then toplevel headings are parts, # not chapters. #latex_use_parts = False # If true, show page references after internal links. #latex_show_pagerefs = False # If true, show URL addresses after external links. #latex_show_urls = False # Documents to append as an appendix to all manuals. #latex_appendices = [] # If false, no module index is generated. #latex_domain_indices = True # -- Options for manual page output --------------------------------------- # One entry per manual page. List of tuples # (source start file, name, description, authors, manual section). man_pages = [ (master_doc, 'lime', u'lime Documentation', [author], 1) ] # If true, show URL addresses after external links. #man_show_urls = False # -- Options for Texinfo output ------------------------------------------- # Grouping the document tree into Texinfo files. List of tuples # (source start file, target name, title, author, # dir menu entry, description, category) texinfo_documents = [ (master_doc, 'lime', u'lime Documentation', author, 'lime', 'One line description of project.', 'Miscellaneous'), ] autoclass_content = 'both' # Documents to append as an appendix to all manuals. #texinfo_appendices = [] # If false, no module index is generated. #texinfo_domain_indices = True # How to display URL addresses: 'footnote', 'no', or 'inline'. #texinfo_show_urls = 'footnote' # If true, do not generate a @detailmenu in the "Top" node's menu. #texinfo_no_detailmenu = False ================================================ FILE: doc/index.rst ================================================ .. lime documentation master file, created by sphinx-quickstart on Fri Mar 18 16:20:40 2016. You can adapt this file completely to your liking, but it should at least contain the root `toctree` directive. Local Interpretable Model-Agnostic Explanations (lime) ================================ In this page, you can find the Python API reference for the lime package (local interpretable model-agnostic explanations). For tutorials and more information, visit `the github page `_. .. toctree:: :maxdepth: 2 lime Indices and tables ================== * :ref:`genindex` * :ref:`modindex` * :ref:`search` ================================================ FILE: doc/lime.rst ================================================ lime package ============ Subpackages ----------- .. toctree:: lime.tests Submodules ---------- lime\.discretize module ----------------------- .. automodule:: lime.discretize :members: :undoc-members: :show-inheritance: lime\.exceptions module ----------------------- .. automodule:: lime.exceptions :members: :undoc-members: :show-inheritance: lime\.explanation module ------------------------ .. automodule:: lime.explanation :members: :undoc-members: :show-inheritance: lime\.lime\_base module ----------------------- .. automodule:: lime.lime_base :members: :undoc-members: :show-inheritance: lime\.lime\_image module ------------------------ .. automodule:: lime.lime_image :members: :undoc-members: :show-inheritance: lime\.lime\_tabular module -------------------------- .. automodule:: lime.lime_tabular :members: :undoc-members: :show-inheritance: lime\.lime\_text module ----------------------- .. automodule:: lime.lime_text :members: :undoc-members: :show-inheritance: lime\.submodular\_pick module ----------------------- .. automodule:: lime.submodular_pick :members: :undoc-members: :show-inheritance: Module contents --------------- .. automodule:: lime :members: :undoc-members: :show-inheritance: ================================================ FILE: doc/notebooks/Latin Hypercube Sampling.ipynb ================================================ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Latin Hypercube Sampling \n", "This notebooks walks through [Latin Hypercube Sampling](https://en.wikipedia.org/wiki/Latin_hypercube_sampling) (LHS) and explains how it differs from the standard [Gaussian Random Sampling](https://en.wikipedia.org/wiki/Normal_distribution) implemented in LIME.\n", "\n", "Standard Gaussian random sampling draws samples from a standard normal distribution Probability Density Function (PDF), $\\mathcal{N}(0,1)$. In practice, if we sample from $\\mathcal{N}(0,1)$ many times, we will begin to obtain enough samples to \"understand\" the space from which we are sampling.\n", "\n", "Some black-box models are computationally expensive, and in high dimensions, we require more samples from the standard normal distribution. We thus introduce a quasi-random process to reduce the needed number of sampled points while not losing our \"understanding\" of the space. LHS is a quasi-random process. LHS samples from a n-dimensional CDF (a n-dimensional hypercube) and places points spread out in the space. It is somewhat analogous to the problem of placing non-attacking rooks on a chessboard. The points are placed to sample all of the features in such a way that the points are distributed across the CDF. We then use a point percentile function (PPF) to go from the CDF to the PDF so we can do the same computations LIME does to the Gaussian points. \n", "\n", "This notebook walks through some examples of both sampling methods and shows how using LHS can save one run time." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# imports \n", "from lime import lime_tabular\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import matplotlib.patches as mpatches \n", "from pyDOE2 import lhs\n", "from scipy.stats.distributions import norm\n", "\n", "np.random.seed(1) # for repeatability " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Visualizing the differnce between Gaussian sampling and LHS\n", "\n", "Let us consider a toy problem with $n=2$ features (for the ease of visualizing). We can compare what the sampled points for Gaussian sampling and LHS will look like. We compare these plots for $s = 25$ samples (to build intuition)." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "n = 2 # number of features\n", "s = 25 # number of samples\n", "\n", "gauss_data = np.random.normal(0,1,n*s).reshape(s,n) # how lime generates the values\n", "lhs_data = lhs(n,s) # lhs generated data" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# visualizing the results in the cdf\n", "means = np.zeros(n)\n", "stdvs = np.array([1]*n)\n", "gaus_cdf = np.zeros((s,n))\n", "for i in range(n):\n", " gaus_cdf[:,i] = norm(loc=means[i], scale=stdvs[i]).cdf(gauss_data[:,i])\n", " \n", " \n", "fig, (ax1, ax2) = plt.subplots(1, 2,sharey=True)\n", "\n", "ax1.scatter(gaus_cdf[:,0],gaus_cdf[:,1],color='tab:blue',label='Gaussian Sampling (cdf)')\n", "ax1.set_xlabel('feature 1')\n", "ax1.set_ylabel('feature 2')\n", "ax1.legend(shadow=True,fancybox=True)\n", "\n", "ax2.scatter(lhs_data[:,0], lhs_data[:,1],color='tab:orange',label='LHS (cdf)')\n", "ax2.set_xlabel('feature 1')\n", "ax2.legend(shadow=True, fancybox=True)\n", "\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# visualizing the the distribution of points in the pdf\n", "# transformation lhs from cdf to pdf\n", "means = np.zeros(n)\n", "stdvs = np.array([1]*n)\n", "for i in range(n):\n", " lhs_data[:, i] = norm(loc=means[i], scale=stdvs[i]).ppf(lhs_data[:, i]) \n", "\n", "fig, (ax1, ax2) = plt.subplots(1, 2,sharey=True)\n", "\n", "ax1.scatter(gauss_data[:,0],gauss_data[:,1],color='tab:blue',label='Gaussian Sampling (pdf)')\n", "ax1.set_xlabel('feature 1')\n", "ax1.set_ylabel('feature 2')\n", "ax1.legend(shadow=True,fancybox=True)\n", "\n", "ax2.scatter(lhs_data[:,0], lhs_data[:,1],color='tab:orange',label='LHS (pdf)')\n", "ax2.set_xlabel('feature 1')\n", "ax2.legend(shadow=True, fancybox=True)\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Intuitively, it appears that the LHS method, since the points are better distributed through the space, would require fewer points to be generated. In both the CDF and PDF, we see LHS spreads out over the space more than the Gaussian sampling approach. \n", "\n", "Let us test this on the [Iris](https://en.wikipedia.org/wiki/Iris_flower_data_set) dataset. " ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "# imports for the iris data set and model\n", "from sklearn.neural_network import MLPClassifier\n", "from sklearn.datasets import load_iris\n", "from sklearn.model_selection import train_test_split\n", "from sklearn.metrics import accuracy_score" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "model accuracy score: 0.9333333333333333\n" ] } ], "source": [ "# train a black box model on the data set\n", "np.random.seed(1)\n", "iris = load_iris()\n", "train, test, labels_train, labels_test = train_test_split(iris.data, iris.target, train_size=0.80)\n", "clf = MLPClassifier(solver='lbfgs', alpha=1e-5,hidden_layer_sizes=(11,6), random_state=1)\n", "clf.fit(train, labels_train)\n", "print('model accuracy score: ',accuracy_score(labels_test, clf.predict(test)))\n", "\n", "# point to explain\n", "test_instance = test[8]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now that we have a pretty good black-box model, let's compare the top weight (as predicted by LIME). First, we will do it for just one run and fix the number of samples at $s = 5000$, which is the default number of samples." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " \n", " \n", "
\n", " \n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# gaussian sampling for LIME\n", "explainer = lime_tabular.LimeTabularExplainer(train,10,feature_names=iris.feature_names,class_names=iris.target_names,discretize_continuous=False)\n", "exp = explainer.explain_instance(test_instance,clf.predict_proba,num_features=1,top_labels=1,num_samples=5000,model_regressor=None,sampling_method='gauss')\n", "exp.show_in_notebook()" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " \n", " \n", "
\n", " \n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# LHS sampling for LIME\n", "explainer = lime_tabular.LimeTabularExplainer(train,10,feature_names=iris.feature_names,class_names=iris.target_names,discretize_continuous=False)\n", "exp = explainer.explain_instance(test_instance,clf.predict_proba,num_features=1,top_labels=1,num_samples=5000,model_regressor=None,sampling_method='lhs')\n", "exp.show_in_notebook()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Notice that in both cases, we obtain the same explanation! Now we can test this and see what happens when we change the number of samples. " ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "max_samples = 5000\n", "\n", "samp = []\n", "weight_gauss = []\n", "weight_lhs = []\n", "\n", "for i in range(10,max_samples+1):\n", " \n", " # gaussian random sampling explanation\n", " explainer_gauss = lime_tabular.LimeTabularExplainer(train,i,feature_names=iris.feature_names,class_names=iris.target_names,discretize_continuous=False)\n", " exp_gauss = explainer.explain_instance(test_instance,clf.predict_proba,num_features=1,top_labels=1,num_samples=i,model_regressor=None,sampling_method='gauss')\n", " _gauss = list(exp_gauss.local_exp.values())[0][0][1]\n", " \n", " # lhs random sampling explanation\n", " explainer_lhs = lime_tabular.LimeTabularExplainer(train,i,feature_names=iris.feature_names,class_names=iris.target_names,discretize_continuous=False)\n", " exp_lhs = explainer.explain_instance(test_instance,clf.predict_proba,num_features=1,top_labels=1,num_samples=i,model_regressor=None,sampling_method='lhs')\n", " _lhs = list(exp_lhs.local_exp.values())[0][0][1]\n", " \n", " # appending the data\n", " samp.append(i)\n", " weight_gauss.append(_gauss)\n", " weight_lhs.append(_lhs) " ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# plotting the data generated in the previous step\n", "plt.figure(1,[10,7])\n", "plt.plot(samp,weight_gauss,color='tab:blue',label='Gaussian Sampling')\n", "plt.plot(samp,weight_lhs,color='tab:orange',label='LHS')\n", "plt.xlabel('number of samples')\n", "plt.ylabel('top explanation weight')\n", "plt.title('Comparing the Convergence of the Explanation')\n", "plt.legend()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can see that both sampling methods converge to the same top weight. These results extend to all other weights as well, as LHS does not introduce bias. \n", "\n", "For LHS, we have consistently less varied results and faster convergence. Utilizing LHS, one could reduce the number of samples to increase the speed of explanations without losing any information or reliability. " ] } ], "metadata": { "kernelspec": { "display_name": "limeenv", "language": "python", "name": "limeenv" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.3" } }, "nbformat": 4, "nbformat_minor": 4 } ================================================ FILE: doc/notebooks/Lime - basic usage, two class case.ipynb ================================================ { "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import lime\n", "import sklearn\n", "import sklearn.ensemble\n", "import sklearn.metrics" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Fetching data, training a classifier" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For this tutorial, we'll be using the [20 newsgroups dataset](http://scikit-learn.org/stable/datasets/#the-20-newsgroups-text-dataset). In particular, for simplicity, we'll use a 2-class subset: atheism and christianity." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "from sklearn.datasets import fetch_20newsgroups\n", "categories = ['alt.atheism', 'soc.religion.christian']\n", "newsgroups_train = fetch_20newsgroups(subset='train', categories=categories)\n", "newsgroups_test = fetch_20newsgroups(subset='test', categories=categories)\n", "class_names = ['atheism', 'christian']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's use the tfidf vectorizer, commonly used for text." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "vectorizer = sklearn.feature_extraction.text.TfidfVectorizer(lowercase=False)\n", "train_vectors = vectorizer.fit_transform(newsgroups_train.data)\n", "test_vectors = vectorizer.transform(newsgroups_test.data)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now, let's say we want to use random forests for classification. It's usually hard to understand what random forests are doing, especially with many trees." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini',\n", " max_depth=None, max_features='auto', max_leaf_nodes=None,\n", " min_samples_leaf=1, min_samples_split=2,\n", " min_weight_fraction_leaf=0.0, n_estimators=500, n_jobs=1,\n", " oob_score=False, random_state=None, verbose=0,\n", " warm_start=False)" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "rf = sklearn.ensemble.RandomForestClassifier(n_estimators=500)\n", "rf.fit(train_vectors, newsgroups_train.target)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.92093023255813955" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pred = rf.predict(test_vectors)\n", "sklearn.metrics.f1_score(newsgroups_test.target, pred, average='binary')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We see that this classifier achieves a very high F score. [The sklearn guide to 20 newsgroups](http://scikit-learn.org/stable/datasets/#filtering-text-for-more-realistic-training) indicates that Multinomial Naive Bayes overfits this dataset by learning irrelevant stuff, such as headers. Let's see if random forests do the same." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Explaining predictions using lime" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Lime explainers assume that classifiers act on raw text, but sklearn classifiers act on vectorized representation of texts. For this purpose, we use sklearn's pipeline, and implement ````predict_proba```` on raw_text lists." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "from sklearn.pipeline import make_pipeline\n", "c = make_pipeline(vectorizer, rf)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[[ 0.274 0.726]]\n" ] } ], "source": [ "print(c.predict_proba([newsgroups_test.data[0]]))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we create an explainer object. We pass the ````class_names```` as an argument for prettier display." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "from lime.lime_text import LimeTextExplainer\n", "explainer = LimeTextExplainer(class_names=class_names)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We then generate an explanation with at most 6 features for an arbitrary document in the test set." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Document id: 83\n", "Probability(christian) = 0.414\n", "True class: atheism\n" ] } ], "source": [ "idx = 83\n", "exp = explainer.explain_instance(newsgroups_test.data[idx], c.predict_proba, num_features=6)\n", "print('Document id: %d' % idx)\n", "print('Probability(christian) =', c.predict_proba([newsgroups_test.data[idx]])[0, 1])\n", "print('True class: %s' % class_names[newsgroups_test.target[idx]])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The classifier got this example right (it predicted atheism). \n", "The explanation is presented below as a list of weighted features. " ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[(u'Posting', -0.15748303818990594),\n", " (u'Host', -0.13220892468795911),\n", " (u'NNTP', -0.097422972255878093),\n", " (u'edu', -0.051080418945152584),\n", " (u'have', -0.010616558305370854),\n", " (u'There', -0.0099743822272458232)]" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "exp.as_list()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "These weighted features are a linear model, which approximates the behaviour of the random forest classifier in the vicinity of the test example. Roughly, if we remove 'Posting' and 'Host' from the document , the prediction should move towards the opposite class (Christianity) by about 0.27 (the sum of the weights for both features). Let's see if this is the case." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Original prediction: 0.414\n", "Prediction removing some features: 0.684\n", "Difference: 0.27\n" ] } ], "source": [ "print('Original prediction:', rf.predict_proba(test_vectors[idx])[0, 1])\n", "tmp = test_vectors[idx].copy()\n", "tmp[0, vectorizer.vocabulary_['Posting']] = 0\n", "tmp[0, vectorizer.vocabulary_['Host']] = 0\n", "print('Prediction removing some features:', rf.predict_proba(tmp)[0, 1])\n", "print('Difference:', rf.predict_proba(tmp)[0, 1] - rf.predict_proba(test_vectors[idx])[0, 1])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Pretty close! \n", "The words that explain the model around this document seem very arbitrary - not much to do with either Christianity or Atheism. \n", "In fact, these are words that appear in the email headers (you will see this clearly soon), which make distinguishing between the classes much easier." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Visualizing explanations" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The explanations can be returned as a matplotlib barplot:" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "image/png": 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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "%matplotlib inline\n", "fig = exp.as_pyplot_figure()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The explanations can also be exported as an html page (which we can render here in this notebook), using D3.js to render graphs. \n" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
\n", " \n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "exp.show_in_notebook(text=False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Alternatively, we can save the fully contained html page to a file:" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "exp.save_to_file('/tmp/oi.html')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Finally, we can also include a visualization of the original document, with the words in the explanations highlighted. Notice how the words that affect the classifier the most are all in the email header." ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
\n", " \n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "exp.show_in_notebook(text=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "That's it for this tutorial. Random forests were just an example, this explainer works for any classifier you may want to use, as long as it implements ````predict_proba````." ] } ], "metadata": { "kernelspec": { "display_name": "lime3", "language": "python", "name": "lime3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.7" } }, "nbformat": 4, "nbformat_minor": 1 } ================================================ FILE: doc/notebooks/Lime - multiclass.ipynb ================================================ { "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import lime\n", "import sklearn\n", "import sklearn.ensemble\n", "import sklearn.metrics" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Fetching data, training a classifier" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In the [previous tutorial](http://marcotcr.github.io/lime-ml/tutorials/Lime%20-%20basic%20usage%2C%20two%20class%20case.html), we looked at lime in the two class case. In this tutorial, we will use the [20 newsgroups dataset](http://scikit-learn.org/stable/datasets/#the-20-newsgroups-text-dataset) again, but this time using all of the classes." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "from sklearn.datasets import fetch_20newsgroups\n", "newsgroups_train = fetch_20newsgroups(subset='train')\n", "newsgroups_test = fetch_20newsgroups(subset='test')\n", "# making class names shorter\n", "class_names = [x.split('.')[-1] if 'misc' not in x else '.'.join(x.split('.')[-2:]) for x in newsgroups_train.target_names]\n", "class_names[3] = 'pc.hardware'\n", "class_names[4] = 'mac.hardware'" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "atheism,graphics,ms-windows.misc,pc.hardware,mac.hardware,x,misc.forsale,autos,motorcycles,baseball,hockey,crypt,electronics,med,space,christian,guns,mideast,politics.misc,religion.misc\n" ] } ], "source": [ "print(','.join(class_names))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Again, let's use the tfidf vectorizer, commonly used for text." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "vectorizer = sklearn.feature_extraction.text.TfidfVectorizer(lowercase=False)\n", "train_vectors = vectorizer.fit_transform(newsgroups_train.data)\n", "test_vectors = vectorizer.transform(newsgroups_test.data)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This time we will use Multinomial Naive Bayes for classification, so that we can make reference to [this document](http://scikit-learn.org/stable/datasets/#filtering-text-for-more-realistic-training)." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "MultinomialNB(alpha=0.01, class_prior=None, fit_prior=True)" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from sklearn.naive_bayes import MultinomialNB\n", "nb = MultinomialNB(alpha=.01)\n", "nb.fit(train_vectors, newsgroups_train.target)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.83501841939981736" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pred = nb.predict(test_vectors)\n", "sklearn.metrics.f1_score(newsgroups_test.target, pred, average='weighted')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We see that this classifier achieves a very high F1 score. [The sklearn guide to 20 newsgroups](http://scikit-learn.org/stable/datasets/#filtering-text-for-more-realistic-training) indicates that Multinomial Naive Bayes overfits this dataset by learning irrelevant stuff, such as headers, by looking at the features with highest coefficients for the model in general. We now use lime to explain individual predictions instead." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Explaining predictions using lime" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "from sklearn.pipeline import make_pipeline\n", "c = make_pipeline(vectorizer, nb)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[[ 0.001 0.01 0.003 0.047 0.006 0.002 0.003 0.521 0.022 0.008\n", " 0.025 0. 0.331 0.003 0.006 0. 0.003 0. 0.001 0.009]]\n" ] } ], "source": [ "print(c.predict_proba([newsgroups_test.data[0]]).round(3))" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "from lime.lime_text import LimeTextExplainer\n", "explainer = LimeTextExplainer(class_names=class_names)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Previously, we used the default parameter for label when generating explanation, which works well in the binary case. \n", "For the multiclass case, we have to determine for which labels we will get explanations, via the 'labels' parameter. \n", "Below, we generate explanations for labels 0 and 17." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Document id: 1340\n", "Predicted class = atheism\n", "True class: atheism\n" ] } ], "source": [ "idx = 1340\n", "exp = explainer.explain_instance(newsgroups_test.data[idx], c.predict_proba, num_features=6, labels=[0, 17])\n", "print('Document id: %d' % idx)\n", "print('Predicted class =', class_names[nb.predict(test_vectors[idx]).reshape(1, -1)[0, 0]])\n", "print('True class: %s' % class_names[newsgroups_test.target[idx]])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now, we can see the explanations for different labels. Notice that the positive and negative signs are with respect to a particular label - so that words that are negative towards class 0 may be positive towards class 15, and vice versa." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Explanation for class atheism\n", "(u'Caused', 0.26601045845449439)\n", "(u'Rice', 0.13658462676578711)\n", "(u'Genocide', 0.13519771973974065)\n", "(u'owlnet', -0.092585962025604027)\n", "(u'certainty', -0.088001257903975866)\n", "(u'Semitic', -0.085734572813977061)\n", "\n", "Explanation for class mideast\n", "(u'fsu', -0.056622666266163954)\n", "(u'Luther', -0.051897643027619206)\n", "(u'Theism', -0.049640283384298073)\n", "(u'jews', 0.037819200983811155)\n", "(u'Caused', -0.037513316854574666)\n", "(u'Genocide', 0.027357407069969929)\n" ] } ], "source": [ "print('Explanation for class %s' % class_names[0])\n", "print('\\n'.join(map(str, exp.as_list(label=0))))\n", "print()\n", "print('Explanation for class %s' % class_names[17])\n", "print('\\n'.join(map(str, exp.as_list(label=17))))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Another alternative is to ask LIME to generate labels for the top K classes. This is shown below with K=2. \n", "To see which labels have explanations, use the ````available_labels```` function." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[0, 15]\n" ] } ], "source": [ "exp = explainer.explain_instance(newsgroups_test.data[idx], c.predict_proba, num_features=6, top_labels=2)\n", "print(exp.available_labels())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now let's see some the visualization of the explanations. Notice that for each class, the words on the right side on the line are positive, and the words on the left side are negative. Thus, 'Caused' is positive for atheism, but negative for christian." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
\n", " \n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "exp.show_in_notebook(text=False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We notice that the classifier is using reasonable words (such as 'Genocide', 'Luther', 'Semitic', etc), as well as unreasonable ones ('Rice', 'owlnet'). Let's zoom in and just look at the explanations for class 'Atheism'." ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
\n", " \n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "exp.show_in_notebook(text=newsgroups_test.data[idx], labels=(0,))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Looking at this example demonstrates that there can be useful signal in the header or quotes that would generalize - i.e., the Subject line. There is also signal that would not generalize (e.g. email addresses and institution names)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Explaining predictions without headers, quotes and footers" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Finally, we follow the [suggestion of removing headers, footers and quotes](http://scikit-learn.org/stable/datasets/#filtering-text-for-more-realistic-training), and explain the same example with the new data." ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "newsgroups_train = fetch_20newsgroups(subset='train', remove=('headers', 'footers', 'quotes'))\n", "newsgroups_test = fetch_20newsgroups(subset='test', remove=('headers', 'footers', 'quotes'))\n", "train_vectors = vectorizer.fit_transform(newsgroups_train.data)\n", "test_vectors = vectorizer.transform(newsgroups_test.data)\n", "nb = MultinomialNB(alpha=.01)\n", "nb.fit(train_vectors, newsgroups_train.target)\n", "c = make_pipeline(vectorizer, nb)\n", "explainer = LimeTextExplainer(class_names=class_names)" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[15, 17]\n" ] } ], "source": [ "exp = explainer.explain_instance(newsgroups_test.data[idx], c.predict_proba, num_features=6, top_labels=2)\n", "print(exp.available_labels())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Notice how different the explanations are for the classifier without headers, footers and quotes. The prediction changes, but so do the reasons." ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
\n", " \n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "exp.show_in_notebook(text=False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's see the explanation with the text for the top class (christian):" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
\n", " \n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "exp.show_in_notebook(text=newsgroups_test.data[idx], labels=(15,))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Notice how short the text became after removing all of that information. One begins to wonder if this version of the dataset is still useful, or if it is better to find another dataset altogether. Could a reasonable classifier detect that this document belongs to the class atheism?\n", "\n", "Anyway, I hope this illustrated how to use LIME to explain arbitrary classifiers in the multiclass case!" ] } ], "metadata": { "kernelspec": { "display_name": "lime3", "language": "python", "name": "lime3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.7" } }, "nbformat": 4, "nbformat_minor": 1 } ================================================ FILE: doc/notebooks/Lime with Recurrent Neural Networks.ipynb ================================================ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# This network demonstrates how to use LIME with recurrent neural networks.\n", "\n", "This focuses on keras-style \"stateless\" recurrent neural networks. These networks expect input with a shape `(n_samples, n_timesteps, n_features)` as opposed to the more normal `(n_samples, n_features)` input that most other machine learning algorithms expect. \n", "\n", "To explain the neural network models, we use a variant on the `TabularExplainer` that takes care of reshaping data appropriately." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Using Theano backend.\n" ] } ], "source": [ "# Imports\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import pandas as pd\n", "\n", "from keras.models import Sequential\n", "from keras.layers import LSTM, Dropout, Dense\n", "from keras.optimizers import Adam\n", "from keras.utils import to_categorical\n", "\n", "from sklearn.preprocessing import MinMaxScaler\n", "from sklearn.metrics import classification_report\n", "\n", "from lime import lime_tabular\n", "\n", "%matplotlib inline" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Data\n", "\n", "We will use the $CO_2$ dataset, which measures the concentration of $CO_2$ above Mauna Loa every week since about 1960. The classification task will be deciding if the concentration is rising - this is a problem that needs recurrency to solve (since the answer comes from the derivative), and is less trivial than it sounds because there is noise in the data. \n", "\n", "The data is included in the `data` subdirectory here, where I've added a column for the detrended data that ends up being useful for the network, as we shall see shortly." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "df = pd.read_csv('data/co2_data.csv', index_col=0, parse_dates=True)" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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lUN/eja5cAZbF8erOepxxbEXAhd/Y0Y28xV3lQGCHA9nWsC8vnzdAR0AMNFGv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JF0HJd3vSNHjs+NjAvU7USJUCJI07i4prqG5+bLpSQqQIpH7v/SCeQZ2WFZ4/Y9C4mTwrXvdTiQ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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, (left, right) = plt.subplots(nrows=1, ncols=2, figsize=(13, 5))\n", "df[['co2']].plot(ax=left)\n", "df[['co2_detrended']].plot(ax=right)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Reshaping the dataset to be appropriate for the model" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def reshape_data(seq, n_timesteps):\n", " N = len(seq) - n_timesteps - 1\n", " nf = seq.shape[1]\n", " if N <= 0:\n", " raise ValueError('I need more data!')\n", " new_seq = np.zeros((N, n_timesteps, nf))\n", " for i in range(N):\n", " new_seq[i, :, :] = seq[i:i+n_timesteps]\n", " return new_seq" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(2270, 12, 2) (2270, 2)\n" ] } ], "source": [ "N_TIMESTEPS = 12 # Use 1 year of lookback\n", "data_columns = ['co2', 'co2_detrended']\n", "target_columns = ['rising']\n", "\n", "scaler = MinMaxScaler(feature_range=(-1, 1))\n", "X_original = scaler.fit_transform(df[data_columns].values)\n", "X = reshape_data(X_original, n_timesteps=N_TIMESTEPS)\n", "y = to_categorical((df[target_columns].values[N_TIMESTEPS:-1]).astype(int))\n", "\n", "# Train on the first 2000, and test on the last 276 samples\n", "X_train = X[:2000]\n", "y_train = y[:2000]\n", "X_test = X[2000:]\n", "y_test = y[2000:]\n", "print(X.shape, y.shape)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Define the model" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": true }, "outputs": [], "source": [ "model = Sequential()\n", "model.add(LSTM(32, input_shape=(N_TIMESTEPS, len(data_columns))))\n", "model.add(Dropout(0.2))\n", "model.add(Dense(2, activation='softmax'))\n", "\n", "optimizer = Adam(lr=1e-4)\n", "model.compile(loss='binary_crossentropy', optimizer=optimizer)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Train on 2000 samples, validate on 270 samples\n", "Epoch 1/500\n", "0s - loss: 0.7026 - val_loss: 0.6739\n", "Epoch 2/500\n", "0s - loss: 0.6883 - val_loss: 0.6651\n", "Epoch 3/500\n", "0s - loss: 0.6748 - val_loss: 0.6558\n", "Epoch 4/500\n", "0s - loss: 0.6636 - val_loss: 0.6457\n", "Epoch 5/500\n", "0s - loss: 0.6485 - val_loss: 0.6352\n", "Epoch 6/500\n", "0s - loss: 0.6335 - val_loss: 0.6236\n", "Epoch 7/500\n", "0s - loss: 0.6172 - val_loss: 0.6108\n", "Epoch 8/500\n", "0s - loss: 0.6013 - val_loss: 0.5964\n", "Epoch 9/500\n", "0s - loss: 0.5822 - val_loss: 0.5806\n", "Epoch 10/500\n", "0s - loss: 0.5621 - val_loss: 0.5633\n", "Epoch 11/500\n", "0s - loss: 0.5402 - val_loss: 0.5441\n", "Epoch 12/500\n", "0s - loss: 0.5149 - val_loss: 0.5234\n", "Epoch 13/500\n", "0s - loss: 0.4914 - val_loss: 0.5013\n", "Epoch 14/500\n", "0s - loss: 0.4668 - val_loss: 0.4788\n", "Epoch 15/500\n", "0s - loss: 0.4444 - val_loss: 0.4574\n", "Epoch 16/500\n", "0s - loss: 0.4219 - val_loss: 0.4365\n", "Epoch 17/500\n", "0s - loss: 0.4034 - val_loss: 0.4176\n", "Epoch 18/500\n", "0s - loss: 0.3851 - val_loss: 0.4012\n", "Epoch 19/500\n", "0s - loss: 0.3705 - val_loss: 0.3861\n", "Epoch 20/500\n", "0s - loss: 0.3584 - val_loss: 0.3719\n", "Epoch 21/500\n", "0s - loss: 0.3448 - val_loss: 0.3596\n", "Epoch 22/500\n", "0s - loss: 0.3343 - val_loss: 0.3485\n", "Epoch 23/500\n", "0s - loss: 0.3242 - val_loss: 0.3385\n", "Epoch 24/500\n", "0s - loss: 0.3151 - val_loss: 0.3292\n", "Epoch 25/500\n", "0s - loss: 0.3059 - val_loss: 0.3208\n", "Epoch 26/500\n", "0s - loss: 0.2989 - val_loss: 0.3128\n", "Epoch 27/500\n", "0s - loss: 0.2929 - val_loss: 0.3053\n", "Epoch 28/500\n", "0s - loss: 0.2831 - val_loss: 0.2987\n", "Epoch 29/500\n", "0s - loss: 0.2792 - val_loss: 0.2929\n", "Epoch 30/500\n", "0s - loss: 0.2749 - val_loss: 0.2872\n", "Epoch 31/500\n", "0s - loss: 0.2661 - val_loss: 0.2828\n", "Epoch 32/500\n", "0s - loss: 0.2667 - val_loss: 0.2783\n", "Epoch 33/500\n", "0s - loss: 0.2594 - val_loss: 0.2738\n", "Epoch 34/500\n", "0s - loss: 0.2566 - val_loss: 0.2703\n", "Epoch 35/500\n", "0s - loss: 0.2540 - val_loss: 0.2670\n", "Epoch 36/500\n", "0s - loss: 0.2509 - val_loss: 0.2641\n", "Epoch 37/500\n", "0s - loss: 0.2480 - val_loss: 0.2611\n", "Epoch 38/500\n", "0s - loss: 0.2466 - val_loss: 0.2593\n", "Epoch 39/500\n", "0s - loss: 0.2454 - val_loss: 0.2572\n", "Epoch 40/500\n", "0s - loss: 0.2433 - val_loss: 0.2554\n", "Epoch 41/500\n", "0s - loss: 0.2411 - val_loss: 0.2536\n", "Epoch 42/500\n", "0s - loss: 0.2401 - val_loss: 0.2521\n", "Epoch 43/500\n", "0s - loss: 0.2371 - val_loss: 0.2505\n", "Epoch 44/500\n", "0s - loss: 0.2378 - val_loss: 0.2494\n", "Epoch 45/500\n", "0s - loss: 0.2354 - val_loss: 0.2489\n", "Epoch 46/500\n", "0s - loss: 0.2306 - val_loss: 0.2474\n", "Epoch 47/500\n", "0s - loss: 0.2355 - val_loss: 0.2460\n", "Epoch 48/500\n", "0s - loss: 0.2331 - val_loss: 0.2452\n", "Epoch 49/500\n", "0s - loss: 0.2273 - val_loss: 0.2448\n", "Epoch 50/500\n", "0s - loss: 0.2295 - val_loss: 0.2445\n", "Epoch 51/500\n", "0s - loss: 0.2261 - val_loss: 0.2439\n", "Epoch 52/500\n", "0s - loss: 0.2251 - val_loss: 0.2430\n", "Epoch 53/500\n", "0s - loss: 0.2273 - val_loss: 0.2432\n", "Epoch 54/500\n", "0s - loss: 0.2237 - val_loss: 0.2425\n", "Epoch 55/500\n", "0s - loss: 0.2199 - val_loss: 0.2418\n", "Epoch 56/500\n", "0s - loss: 0.2238 - val_loss: 0.2415\n", "Epoch 57/500\n", "0s - loss: 0.2207 - val_loss: 0.2416\n", "Epoch 58/500\n", "0s - loss: 0.2202 - val_loss: 0.2411\n", "Epoch 59/500\n", "0s - loss: 0.2186 - val_loss: 0.2416\n", "Epoch 60/500\n", "0s - loss: 0.2208 - val_loss: 0.2413\n", "Epoch 61/500\n", "0s - loss: 0.2184 - val_loss: 0.2408\n", "Epoch 62/500\n", "0s - loss: 0.2170 - val_loss: 0.2417\n", "Epoch 63/500\n", "0s - loss: 0.2174 - val_loss: 0.2409\n", "Epoch 64/500\n", 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0.2445\n", "Epoch 81/500\n", "0s - loss: 0.2049 - val_loss: 0.2434\n", "Epoch 82/500\n", "0s - loss: 0.2053 - val_loss: 0.2425\n", "Epoch 83/500\n", "0s - loss: 0.2037 - val_loss: 0.2434\n", "Epoch 84/500\n", "0s - loss: 0.2059 - val_loss: 0.2444\n", "Epoch 85/500\n", "0s - loss: 0.2040 - val_loss: 0.2437\n", "Epoch 86/500\n", "0s - loss: 0.2040 - val_loss: 0.2428\n", "Epoch 87/500\n", "0s - loss: 0.2026 - val_loss: 0.2417\n", "Epoch 88/500\n", "0s - loss: 0.2028 - val_loss: 0.2438\n", "Epoch 89/500\n", "0s - loss: 0.2036 - val_loss: 0.2427\n", "Epoch 90/500\n", "0s - loss: 0.1975 - val_loss: 0.2441\n", "Epoch 91/500\n", "0s - loss: 0.2016 - val_loss: 0.2438\n", "Epoch 92/500\n", "0s - loss: 0.2012 - val_loss: 0.2424\n", "Epoch 93/500\n", "0s - loss: 0.2024 - val_loss: 0.2439\n", "Epoch 94/500\n", "0s - loss: 0.2000 - val_loss: 0.2458\n", "Epoch 95/500\n", "0s - loss: 0.1994 - val_loss: 0.2450\n", "Epoch 96/500\n", "0s - loss: 0.1988 - val_loss: 0.2438\n", "Epoch 97/500\n", "0s - loss: 0.1998 - val_loss: 0.2461\n", "Epoch 98/500\n", "0s - loss: 0.1978 - val_loss: 0.2449\n", "Epoch 99/500\n", "0s - loss: 0.2007 - val_loss: 0.2446\n", "Epoch 100/500\n", "0s - loss: 0.1967 - val_loss: 0.2453\n", "Epoch 101/500\n", "0s - loss: 0.1957 - val_loss: 0.2444\n", "Epoch 102/500\n", "0s - loss: 0.1984 - val_loss: 0.2445\n", "Epoch 103/500\n", "0s - loss: 0.2028 - val_loss: 0.2444\n", "Epoch 104/500\n", "0s - loss: 0.1985 - val_loss: 0.2477\n", "Epoch 105/500\n", "0s - loss: 0.2001 - val_loss: 0.2440\n", "Epoch 106/500\n", "0s - loss: 0.1988 - val_loss: 0.2451\n", "Epoch 107/500\n", "0s - loss: 0.2002 - val_loss: 0.2472\n", "Epoch 108/500\n", "0s - loss: 0.1984 - val_loss: 0.2471\n", "Epoch 109/500\n", "0s - loss: 0.1949 - val_loss: 0.2460\n", "Epoch 110/500\n", "0s - loss: 0.1985 - val_loss: 0.2456\n", "Epoch 111/500\n", "0s - loss: 0.1959 - val_loss: 0.2459\n", "Epoch 112/500\n", "0s - loss: 0.1968 - val_loss: 0.2445\n", "Epoch 113/500\n", "0s - loss: 0.1987 - val_loss: 0.2453\n", "Epoch 114/500\n", "0s - loss: 0.1967 - val_loss: 0.2440\n", "Epoch 115/500\n", "0s - loss: 0.1954 - val_loss: 0.2423\n", "Epoch 116/500\n", "0s - loss: 0.1959 - val_loss: 0.2436\n", "Epoch 117/500\n", "0s - loss: 0.1998 - val_loss: 0.2446\n", "Epoch 118/500\n", "0s - loss: 0.1999 - val_loss: 0.2441\n", "Epoch 119/500\n", "0s - loss: 0.1958 - val_loss: 0.2438\n", "Epoch 120/500\n", "0s - loss: 0.1967 - val_loss: 0.2429\n", "Epoch 121/500\n", "0s - loss: 0.1971 - val_loss: 0.2443\n", "Epoch 122/500\n", "0s - loss: 0.1962 - val_loss: 0.2428\n", "Epoch 123/500\n", "0s - loss: 0.1977 - val_loss: 0.2451\n", "Epoch 124/500\n", "0s - loss: 0.1983 - val_loss: 0.2430\n", "Epoch 125/500\n", "0s - loss: 0.1952 - val_loss: 0.2425\n", "Epoch 126/500\n", "0s - loss: 0.1932 - val_loss: 0.2429\n", "Epoch 127/500\n", "0s - loss: 0.1957 - val_loss: 0.2417\n", "Epoch 128/500\n", "0s - loss: 0.1946 - val_loss: 0.2429\n", "Epoch 129/500\n", "0s - loss: 0.1942 - val_loss: 0.2426\n", "Epoch 130/500\n", "0s - loss: 0.1917 - val_loss: 0.2420\n", "Epoch 131/500\n", "0s - loss: 0.1933 - val_loss: 0.2411\n", "Epoch 132/500\n", "0s - loss: 0.1962 - val_loss: 0.2402\n", "Epoch 133/500\n", "0s - loss: 0.1952 - val_loss: 0.2439\n", "Epoch 134/500\n", "0s - loss: 0.1935 - val_loss: 0.2412\n", "Epoch 135/500\n", "0s - loss: 0.1991 - val_loss: 0.2411\n", "Epoch 136/500\n", "0s - loss: 0.1925 - val_loss: 0.2399\n", "Epoch 137/500\n", "0s - loss: 0.1949 - val_loss: 0.2417\n", "Epoch 138/500\n", "0s - loss: 0.1930 - val_loss: 0.2406\n", "Epoch 139/500\n", "0s - loss: 0.1934 - val_loss: 0.2411\n", "Epoch 140/500\n", "0s - loss: 0.1918 - val_loss: 0.2408\n", "Epoch 141/500\n", "0s - loss: 0.1924 - val_loss: 0.2427\n", "Epoch 142/500\n", "0s - loss: 0.1931 - val_loss: 0.2409\n", "Epoch 143/500\n", "0s - loss: 0.1966 - val_loss: 0.2400\n", "Epoch 144/500\n", "0s - loss: 0.1933 - val_loss: 0.2408\n", "Epoch 145/500\n", "0s - loss: 0.1966 - val_loss: 0.2391\n", "Epoch 146/500\n", "0s - loss: 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0.2284\n", "Epoch 260/500\n", "0s - loss: 0.1898 - val_loss: 0.2289\n", "Epoch 261/500\n", "0s - loss: 0.1887 - val_loss: 0.2296\n", "Epoch 262/500\n", "0s - loss: 0.1904 - val_loss: 0.2283\n", "Epoch 263/500\n", "0s - loss: 0.1916 - val_loss: 0.2280\n", "Epoch 264/500\n", "0s - loss: 0.1893 - val_loss: 0.2298\n", "Epoch 265/500\n", "0s - loss: 0.1874 - val_loss: 0.2290\n", "Epoch 266/500\n", "0s - loss: 0.1892 - val_loss: 0.2276\n", "Epoch 267/500\n", "0s - loss: 0.1873 - val_loss: 0.2291\n", "Epoch 268/500\n", "0s - loss: 0.1848 - val_loss: 0.2286\n", "Epoch 269/500\n", "0s - loss: 0.1894 - val_loss: 0.2283\n", "Epoch 270/500\n", "0s - loss: 0.1925 - val_loss: 0.2276\n", "Epoch 271/500\n", "0s - loss: 0.1880 - val_loss: 0.2283\n", "Epoch 272/500\n", "0s - loss: 0.1898 - val_loss: 0.2277\n", "Epoch 273/500\n", "0s - loss: 0.1898 - val_loss: 0.2284\n", "Epoch 274/500\n", "0s - loss: 0.1894 - val_loss: 0.2306\n", "Epoch 275/500\n", "0s - loss: 0.1890 - val_loss: 0.2268\n", "Epoch 276/500\n", "0s - loss: 0.1876 - val_loss: 0.2283\n", "Epoch 277/500\n", "0s - loss: 0.1886 - val_loss: 0.2283\n", "Epoch 278/500\n", "0s - loss: 0.1876 - val_loss: 0.2285\n", "Epoch 279/500\n", "0s - loss: 0.1892 - val_loss: 0.2274\n", "Epoch 280/500\n", "0s - loss: 0.1856 - val_loss: 0.2287\n", "Epoch 281/500\n", "0s - loss: 0.1892 - val_loss: 0.2293\n", "Epoch 282/500\n", "0s - loss: 0.1892 - val_loss: 0.2286\n", "Epoch 283/500\n", "0s - loss: 0.1873 - val_loss: 0.2297\n", "Epoch 284/500\n", "0s - loss: 0.1855 - val_loss: 0.2285\n", "Epoch 285/500\n", "0s - loss: 0.1906 - val_loss: 0.2274\n", "Epoch 286/500\n", "0s - loss: 0.1889 - val_loss: 0.2275\n", "Epoch 287/500\n", "0s - loss: 0.1887 - val_loss: 0.2281\n", "Epoch 288/500\n", "0s - loss: 0.1879 - val_loss: 0.2278\n", "Epoch 289/500\n", "0s - loss: 0.1858 - val_loss: 0.2270\n", "Epoch 290/500\n", "0s - loss: 0.1884 - val_loss: 0.2299\n", "Epoch 291/500\n", "0s - loss: 0.1865 - val_loss: 0.2281\n", "Epoch 292/500\n", "0s - loss: 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0.2269\n", "Epoch 309/500\n", "0s - loss: 0.1896 - val_loss: 0.2297\n", "Epoch 310/500\n", "0s - loss: 0.1871 - val_loss: 0.2281\n", "Epoch 311/500\n", "0s - loss: 0.1862 - val_loss: 0.2268\n", "Epoch 312/500\n", "0s - loss: 0.1859 - val_loss: 0.2279\n", "Epoch 313/500\n", "0s - loss: 0.1870 - val_loss: 0.2272\n", "Epoch 314/500\n", "0s - loss: 0.1881 - val_loss: 0.2272\n", "Epoch 315/500\n", "0s - loss: 0.1891 - val_loss: 0.2276\n", "Epoch 316/500\n", "0s - loss: 0.1887 - val_loss: 0.2265\n", "Epoch 317/500\n", "0s - loss: 0.1887 - val_loss: 0.2288\n", "Epoch 318/500\n", "0s - loss: 0.1890 - val_loss: 0.2279\n", "Epoch 319/500\n", "0s - loss: 0.1876 - val_loss: 0.2293\n", "Epoch 320/500\n", "0s - loss: 0.1859 - val_loss: 0.2272\n", "Epoch 321/500\n", "0s - loss: 0.1916 - val_loss: 0.2277\n", "Epoch 322/500\n", "0s - loss: 0.1867 - val_loss: 0.2260\n", "Epoch 323/500\n", "0s - loss: 0.1906 - val_loss: 0.2275\n", "Epoch 324/500\n" ] }, { "name": "stdout", "output_type": "stream", 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422/500\n", "0s - loss: 0.1857 - val_loss: 0.2280\n", "Epoch 423/500\n", "0s - loss: 0.1862 - val_loss: 0.2275\n", "Epoch 424/500\n", "0s - loss: 0.1874 - val_loss: 0.2301\n", "Epoch 425/500\n", "0s - loss: 0.1895 - val_loss: 0.2284\n", "Epoch 426/500\n", "0s - loss: 0.1829 - val_loss: 0.2272\n", "Epoch 427/500\n", "0s - loss: 0.1873 - val_loss: 0.2288\n", "Epoch 428/500\n", "0s - loss: 0.1867 - val_loss: 0.2280\n", "Epoch 429/500\n", "0s - loss: 0.1870 - val_loss: 0.2268\n", "Epoch 430/500\n", "0s - loss: 0.1855 - val_loss: 0.2274\n", "Epoch 431/500\n", "0s - loss: 0.1865 - val_loss: 0.2278\n", "Epoch 432/500\n", "0s - loss: 0.1850 - val_loss: 0.2279\n", "Epoch 433/500\n", "0s - loss: 0.1864 - val_loss: 0.2289\n", "Epoch 434/500\n", "0s - loss: 0.1846 - val_loss: 0.2277\n", "Epoch 435/500\n", "0s - loss: 0.1816 - val_loss: 0.2277\n", "Epoch 436/500\n", "0s - loss: 0.1846 - val_loss: 0.2276\n", "Epoch 437/500\n", "0s - loss: 0.1842 - val_loss: 0.2284\n", "Epoch 438/500\n", "0s - loss: 0.1875 - val_loss: 0.2265\n", "Epoch 439/500\n", "0s - loss: 0.1872 - val_loss: 0.2287\n", "Epoch 440/500\n", "0s - loss: 0.1837 - val_loss: 0.2267\n", "Epoch 441/500\n", "0s - loss: 0.1869 - val_loss: 0.2264\n", "Epoch 442/500\n", "0s - loss: 0.1884 - val_loss: 0.2282\n", "Epoch 443/500\n", "0s - loss: 0.1863 - val_loss: 0.2291\n", "Epoch 444/500\n", "0s - loss: 0.1854 - val_loss: 0.2277\n", "Epoch 445/500\n", "0s - loss: 0.1842 - val_loss: 0.2275\n", "Epoch 446/500\n", "0s - loss: 0.1853 - val_loss: 0.2287\n", "Epoch 447/500\n", "0s - loss: 0.1850 - val_loss: 0.2283\n", "Epoch 448/500\n", "0s - loss: 0.1847 - val_loss: 0.2285\n", "Epoch 449/500\n", "0s - loss: 0.1866 - val_loss: 0.2272\n", "Epoch 450/500\n", "0s - loss: 0.1834 - val_loss: 0.2270\n", "Epoch 451/500\n", "0s - loss: 0.1857 - val_loss: 0.2297\n", "Epoch 452/500\n", "0s - loss: 0.1843 - val_loss: 0.2272\n", "Epoch 453/500\n", "0s - loss: 0.1849 - val_loss: 0.2276\n", "Epoch 454/500\n", "0s - loss: 0.1845 - val_loss: 0.2270\n", "Epoch 455/500\n", "0s - loss: 0.1857 - val_loss: 0.2266\n", "Epoch 456/500\n", "0s - loss: 0.1856 - val_loss: 0.2292\n", "Epoch 457/500\n", "0s - loss: 0.1842 - val_loss: 0.2289\n", "Epoch 458/500\n", "0s - loss: 0.1845 - val_loss: 0.2272\n", "Epoch 459/500\n", "0s - loss: 0.1851 - val_loss: 0.2269\n", "Epoch 460/500\n", "0s - loss: 0.1857 - val_loss: 0.2284\n", "Epoch 461/500\n", "0s - loss: 0.1841 - val_loss: 0.2278\n", "Epoch 462/500\n", "0s - loss: 0.1807 - val_loss: 0.2285\n", "Epoch 463/500\n", "0s - loss: 0.1838 - val_loss: 0.2263\n", "Epoch 464/500\n", "0s - loss: 0.1862 - val_loss: 0.2274\n", "Epoch 465/500\n", "0s - loss: 0.1829 - val_loss: 0.2281\n", "Epoch 466/500\n", "0s - loss: 0.1867 - val_loss: 0.2278\n", "Epoch 467/500\n", "0s - loss: 0.1865 - val_loss: 0.2279\n", "Epoch 468/500\n", "0s - loss: 0.1857 - val_loss: 0.2295\n", "Epoch 469/500\n", "0s - loss: 0.1877 - val_loss: 0.2282\n", "Epoch 470/500\n", "0s - loss: 0.1862 - val_loss: 0.2280\n", "Epoch 471/500\n", "0s - loss: 0.1863 - val_loss: 0.2304\n", "Epoch 472/500\n", "0s - loss: 0.1848 - val_loss: 0.2285\n", "Epoch 473/500\n", "0s - loss: 0.1872 - val_loss: 0.2279\n", "Epoch 474/500\n", "0s - loss: 0.1849 - val_loss: 0.2309\n", "Epoch 475/500\n", "0s - loss: 0.1851 - val_loss: 0.2287\n", "Epoch 476/500\n", "0s - loss: 0.1850 - val_loss: 0.2293\n", "Epoch 477/500\n", "0s - loss: 0.1852 - val_loss: 0.2293\n", "Epoch 478/500\n", "0s - loss: 0.1851 - val_loss: 0.2283\n", "Epoch 479/500\n", "0s - loss: 0.1857 - val_loss: 0.2279\n", "Epoch 480/500\n", "0s - loss: 0.1856 - val_loss: 0.2278\n", "Epoch 481/500\n", "0s - loss: 0.1850 - val_loss: 0.2309\n", "Epoch 482/500\n", "0s - loss: 0.1870 - val_loss: 0.2279\n", "Epoch 483/500\n", "0s - loss: 0.1805 - val_loss: 0.2288\n", "Epoch 484/500\n", "0s - loss: 0.1851 - val_loss: 0.2273\n", "Epoch 485/500\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "0s - loss: 0.1908 - val_loss: 0.2294\n", "Epoch 486/500\n", "0s - loss: 0.1812 - val_loss: 0.2276\n", "Epoch 487/500\n", "0s - loss: 0.1837 - val_loss: 0.2296\n", "Epoch 488/500\n", "0s - loss: 0.1836 - val_loss: 0.2288\n", "Epoch 489/500\n", "0s - loss: 0.1854 - val_loss: 0.2290\n", "Epoch 490/500\n", "0s - loss: 0.1875 - val_loss: 0.2272\n", "Epoch 491/500\n", "0s - loss: 0.1839 - val_loss: 0.2285\n", "Epoch 492/500\n", "0s - loss: 0.1849 - val_loss: 0.2308\n", "Epoch 493/500\n", "0s - loss: 0.1846 - val_loss: 0.2289\n", "Epoch 494/500\n", "0s - loss: 0.1867 - val_loss: 0.2291\n", "Epoch 495/500\n", "0s - loss: 0.1867 - val_loss: 0.2276\n", "Epoch 496/500\n", "0s - loss: 0.1864 - val_loss: 0.2297\n", "Epoch 497/500\n", "0s - loss: 0.1845 - val_loss: 0.2307\n", "Epoch 498/500\n", "0s - loss: 0.1855 - val_loss: 0.2289\n", "Epoch 499/500\n", "0s - loss: 0.1852 - val_loss: 0.2301\n", "Epoch 500/500\n", "0s - loss: 0.1830 - val_loss: 0.2298\n" ] }, { "data": { "text/plain": [ "" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model.fit(X_train, y_train, batch_size=100, epochs=500,\n", " validation_data=(X_test, y_test),\n", " verbose=2)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " precision recall f1-score support\n", "\n", " 0 0.83 0.92 0.87 100\n", " 1 0.95 0.89 0.92 170\n", "\n", "avg / total 0.90 0.90 0.90 270\n", "\n" ] } ], "source": [ "y_pred = np.argmax(model.predict(X_test), axis=1)\n", "y_true = np.argmax(y_test, axis=1)\n", "print(classification_report(y_true, y_pred))" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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RWQTPuWdIv9du2oVQpe4V1E3NRB5/Ne/kn0oot0jRFKYUN5g/R0s+91RDrI7n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\nmY9ZtqWU3AC9RdXIHuO1VnV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/d7j7KU0SOVVv3FE7+R37OfmlM2GdOTWw03jOfRCkb6rW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\nPB3N514H7akVeerbsDtxpzdxKWkvYlTnnu1KSkn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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.plot(y_true, lw=3, alpha=0.3, label='Truth')\n", "plt.plot(y_pred, '--', label='Predictions')\n", "plt.legend(loc='best')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Explain the model with LIME:" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "explainer = lime_tabular.RecurrentTabularExplainer(X_train, training_labels=y_train, feature_names=data_columns,\n", " discretize_continuous=True,\n", " class_names=['Falling', 'Rising'],\n", " discretizer='decile')" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " \n", " \n", "
\n", " \n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "exp = explainer.explain_instance(X_test[50], model.predict, num_features=10, labels=(1,))\n", "exp.show_in_notebook()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can see that the most important features are the de-trended $CO_2$ concentration several timesteps in the past. In particular, we see that if that feature is low in the recent past, then the concentration is now probably rising. " ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.5.2" } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: doc/notebooks/Submodular Pick examples.ipynb ================================================ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# SP LIME\n", "\n", "## Regression explainer with boston housing prices dataset" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ ".. _boston_dataset:\n", "\n", "Boston house prices dataset\n", "---------------------------\n", "\n", "**Data Set Characteristics:** \n", "\n", " :Number of Instances: 506 \n", "\n", " :Number of Attributes: 13 numeric/categorical predictive. Median Value (attribute 14) is usually the target.\n", "\n", " :Attribute Information (in order):\n", " - CRIM per capita crime rate by town\n", " - ZN proportion of residential land zoned for lots over 25,000 sq.ft.\n", " - INDUS proportion of non-retail business acres per town\n", " - CHAS Charles River dummy variable (= 1 if tract bounds river; 0 otherwise)\n", " - NOX nitric oxides concentration (parts per 10 million)\n", " - RM average number of rooms per dwelling\n", " - AGE proportion of owner-occupied units built prior to 1940\n", " - DIS weighted distances to five Boston employment centres\n", " - RAD index of accessibility to radial highways\n", " - TAX full-value property-tax rate per $10,000\n", " - PTRATIO pupil-teacher ratio by town\n", " - B 1000(Bk - 0.63)^2 where Bk is the proportion of blacks by town\n", " - LSTAT % lower status of the population\n", " - MEDV Median value of owner-occupied homes in $1000's\n", "\n", " :Missing Attribute Values: None\n", "\n", " :Creator: Harrison, D. and Rubinfeld, D.L.\n", "\n", "This is a copy of UCI ML housing dataset.\n", "https://archive.ics.uci.edu/ml/machine-learning-databases/housing/\n", "\n", "\n", "This dataset was taken from the StatLib library which is maintained at Carnegie Mellon University.\n", "\n", "The Boston house-price data of Harrison, D. and Rubinfeld, D.L. 'Hedonic\n", "prices and the demand for clean air', J. Environ. Economics & Management,\n", "vol.5, 81-102, 1978. Used in Belsley, Kuh & Welsch, 'Regression diagnostics\n", "...', Wiley, 1980. N.B. Various transformations are used in the table on\n", "pages 244-261 of the latter.\n", "\n", "The Boston house-price data has been used in many machine learning papers that address regression\n", "problems. \n", " \n", ".. topic:: References\n", "\n", " - Belsley, Kuh & Welsch, 'Regression diagnostics: Identifying Influential Data and Sources of Collinearity', Wiley, 1980. 244-261.\n", " - Quinlan,R. (1993). Combining Instance-Based and Model-Based Learning. In Proceedings on the Tenth International Conference of Machine Learning, 236-243, University of Massachusetts, Amherst. Morgan Kaufmann.\n", "\n", "Random Forest R^2 Score: 0.881\n", "Linear Regression R^2 Score: 0.593\n" ] } ], "source": [ "from sklearn.datasets import load_boston\n", "import sklearn.ensemble\n", "import sklearn.linear_model\n", "import sklearn.model_selection\n", "import numpy as np\n", "from sklearn.metrics import r2_score\n", "np.random.seed(1)\n", "\n", "#load example dataset\n", "boston = load_boston()\n", "\n", "#print a description of the variables\n", "print(boston.DESCR)\n", "\n", "#train a regressor\n", "rf = sklearn.ensemble.RandomForestRegressor(n_estimators=1000)\n", "train, test, labels_train, labels_test = sklearn.model_selection.train_test_split(boston.data, boston.target, train_size=0.80, test_size=0.20)\n", "rf.fit(train, labels_train);\n", "\n", "#train a linear regressor\n", "lr = sklearn.linear_model.LinearRegression()\n", "lr.fit(train,labels_train)\n", "\n", "#print the R^2 score of the random forest\n", "print(\"Random Forest R^2 Score: \" +str(round(r2_score(rf.predict(test),labels_test),3)))\n", "print(\"Linear Regression R^2 Score: \" +str(round(r2_score(lr.predict(test),labels_test),3)))" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "# import lime tools\n", "import lime\n", "import lime.lime_tabular\n", "\n", "# generate an \"explainer\" object\n", "categorical_features = np.argwhere(np.array([len(set(boston.data[:,x])) for x in range(boston.data.shape[1])]) <= 10).flatten()\n", "explainer = lime.lime_tabular.LimeTabularExplainer(train, feature_names=boston.feature_names, class_names=['price'], categorical_features=categorical_features, verbose=False, mode='regression',discretize_continuous=False)" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "#generate an explanation\n", "i = 13\n", "exp = explainer.explain_instance(test[i], rf.predict, num_features=14)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "%matplotlib inline\n", "fig = exp.as_pyplot_figure();" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Input feature names: \n", "['CRIM' 'ZN' 'INDUS' 'CHAS' 'NOX' 'RM' 'AGE' 'DIS' 'RAD' 'TAX' 'PTRATIO'\n", " 'B' 'LSTAT']\n", "\n", "\n", "Input feature values: \n", "[4.3790e-02 8.0000e+01 3.3700e+00 0.0000e+00 3.9800e-01 5.7870e+00\n", " 3.1100e+01 6.6115e+00 4.0000e+00 3.3700e+02 1.6100e+01 3.9690e+02\n", " 1.0240e+01]\n", "\n", "\n", "Predicted: \n", "20.161599999999957\n" ] } ], "source": [ "print(\"Input feature names: \")\n", "print(boston.feature_names)\n", "print('\\n')\n", "\n", "print(\"Input feature values: \")\n", "print(test[i])\n", "print('\\n')\n", "\n", "print(\"Predicted: \")\n", "print(rf.predict(test)[i])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# SP-LIME pick step\n", "\n", "### Maximize the 'coverage' function:\n", "\n", "$c(V,W,I) = \\sum_{j=1}^{d^{\\prime}}{\\mathbb{1}_{[\\exists i \\in V : W_{ij}>0]}I_j}$\n", "\n", "$W = \\text{Explanation Matrix, } n\\times d^{\\prime}$\n", "\n", "$V = \\text{Set of chosen explanations}$\n", "\n", "$I = \\text{Global feature importance vector, } I_j = \\sqrt{\\sum_i{|W_{ij}|}}$" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "import lime" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "import warnings\n", "from lime import submodular_pick\n", "sp_obj = submodular_pick.SubmodularPick(explainer, train, rf.predict, sample_size=20, num_features=14, num_exps_desired=5)" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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\n", 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\n", 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\n", 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"text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "im=W.hist('NOX',bins=20)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Text explainer using the newsgroups" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/mnt/c/Users/marcotcr/work/lime/python3env/lib/python3.6/re.py:212: FutureWarning: split() requires a non-empty pattern match.\n", " return _compile(pattern, flags).split(string, maxsplit)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Document id: 83\n", "Probability(christian) = 0.442\n", "True class: atheism\n" ] } ], "source": [ "# run the text explainer example notebook, up to single explanation\n", "import sklearn\n", "import numpy as np\n", "import sklearn\n", "import sklearn.ensemble\n", "import sklearn.metrics\n", "\n", "from sklearn.datasets import fetch_20newsgroups\n", "categories = ['alt.atheism', 'soc.religion.christian']\n", "newsgroups_train = fetch_20newsgroups(subset='train', categories=categories)\n", "newsgroups_test = fetch_20newsgroups(subset='test', categories=categories)\n", "class_names = ['atheism', 'christian']\n", "\n", "vectorizer = sklearn.feature_extraction.text.TfidfVectorizer(lowercase=False)\n", "train_vectors = vectorizer.fit_transform(newsgroups_train.data)\n", "test_vectors = vectorizer.transform(newsgroups_test.data)\n", "\n", "rf = sklearn.ensemble.RandomForestClassifier(n_estimators=500)\n", "rf.fit(train_vectors, newsgroups_train.target)\n", "\n", "pred = rf.predict(test_vectors)\n", "sklearn.metrics.f1_score(newsgroups_test.target, pred, average='binary')\n", "\n", "from lime import lime_text\n", "from sklearn.pipeline import make_pipeline\n", "c = make_pipeline(vectorizer, rf)\n", "\n", "from lime.lime_text import LimeTextExplainer\n", "explainer = LimeTextExplainer(class_names=class_names)\n", "\n", "idx = 83\n", "exp = explainer.explain_instance(newsgroups_test.data[idx], c.predict_proba, num_features=6)\n", "print('Document id: %d' % idx)\n", "print('Probability(christian) =', c.predict_proba([newsgroups_test.data[idx]])[0,1])\n", "print('True class: %s' % class_names[newsgroups_test.target[idx]])" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/mnt/c/Users/marcotcr/work/lime/python3env/lib/python3.6/re.py:212: FutureWarning: split() requires a non-empty pattern match.\n", " return _compile(pattern, flags).split(string, maxsplit)\n", "/mnt/c/Users/marcotcr/work/lime/python3env/lib/python3.6/re.py:212: FutureWarning: split() requires a non-empty pattern match.\n", " return _compile(pattern, flags).split(string, maxsplit)\n" ] } ], "source": [ "sp_obj = submodular_pick.SubmodularPick(explainer, newsgroups_test.data, c.predict_proba, sample_size=2, num_features=6,num_exps_desired=2)" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "[exp.as_pyplot_figure(label=exp.available_labels()[0]) for exp in sp_obj.sp_explanations];" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/mnt/c/Users/marcotcr/work/lime/python3env/lib/python3.6/site-packages/sklearn/ensemble/forest.py:246: FutureWarning: The default value of n_estimators will change from 10 in version 0.20 to 100 in 0.22.\n", " \"10 in version 0.20 to 100 in 0.22.\", FutureWarning)\n" ] }, { "data": { "text/plain": [ "0.9333333333333333" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from sklearn.datasets import load_iris\n", "iris=load_iris()\n", "from sklearn.model_selection import train_test_split as tts\n", "Xtrain,Xtest,ytrain,ytest=tts(iris.data,iris.target,test_size=.2)\n", "from sklearn.ensemble import RandomForestClassifier\n", "rf=RandomForestClassifier()\n", "rf.fit(Xtrain,ytrain)\n", "rf.score(Xtest,ytest)" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": [ "explainer = lime.lime_tabular.LimeTabularExplainer(Xtrain, \n", " feature_names=iris.feature_names,\n", " class_names=iris.target_names, \n", " verbose=False, \n", " mode='classification',\n", " discretize_continuous=False)" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[0, 2, 1]" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "exp=explainer.explain_instance(Xtrain[i],rf.predict_proba,top_labels=3)\n", "exp.available_labels()" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [], "source": [ "sp_obj = submodular_pick.SubmodularPick(data=Xtrain,explainer=explainer,num_exps_desired=5,predict_fn=rf.predict_proba, sample_size=20, num_features=4, top_labels=3)" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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exp numberpetal length (cm)petal width (cm)sepal length (cm)sepal width (cm)
setosa0-0.410513-0.049033-0.0036350.010532
setosa1-0.416660-0.0387740.013522-0.000206
setosa2-0.249963-0.023399-0.0014910.000962
setosa3-0.423744-0.0531670.006401-0.001301
setosa4-0.255049-0.0376260.0026710.002027
versicolor00.254472-0.0429480.029553-0.013252
versicolor10.261545-0.0548800.024067-0.001325
versicolor2-0.026307-0.2285080.0114490.008821
versicolor30.282608-0.0346690.028875-0.001872
versicolor4-0.009620-0.164904-0.015407-0.008737
virginica00.1560410.091980-0.0259190.002720
virginica10.1551150.093654-0.0375890.001530
virginica20.2762700.251906-0.009958-0.009783
virginica30.1411360.087837-0.0352770.003173
virginica40.2646690.2025300.0127360.006710
\n", "
" ], "text/plain": [ " exp number petal length (cm) petal width (cm) \\\n", "setosa 0 -0.410513 -0.049033 \n", "setosa 1 -0.416660 -0.038774 \n", "setosa 2 -0.249963 -0.023399 \n", "setosa 3 -0.423744 -0.053167 \n", "setosa 4 -0.255049 -0.037626 \n", "versicolor 0 0.254472 -0.042948 \n", "versicolor 1 0.261545 -0.054880 \n", "versicolor 2 -0.026307 -0.228508 \n", "versicolor 3 0.282608 -0.034669 \n", "versicolor 4 -0.009620 -0.164904 \n", "virginica 0 0.156041 0.091980 \n", "virginica 1 0.155115 0.093654 \n", "virginica 2 0.276270 0.251906 \n", "virginica 3 0.141136 0.087837 \n", "virginica 4 0.264669 0.202530 \n", "\n", " sepal length (cm) sepal width (cm) \n", "setosa -0.003635 0.010532 \n", "setosa 0.013522 -0.000206 \n", "setosa -0.001491 0.000962 \n", "setosa 0.006401 -0.001301 \n", "setosa 0.002671 0.002027 \n", "versicolor 0.029553 -0.013252 \n", "versicolor 0.024067 -0.001325 \n", "versicolor 0.011449 0.008821 \n", "versicolor 0.028875 -0.001872 \n", "versicolor -0.015407 -0.008737 \n", "virginica -0.025919 0.002720 \n", "virginica -0.037589 0.001530 \n", "virginica -0.009958 -0.009783 \n", "virginica -0.035277 0.003173 \n", "virginica 0.012736 0.006710 " ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import pandas as pd\n", "df=pd.DataFrame({})\n", "for this_label in range(3):\n", " dfl=[]\n", " for i,exp in enumerate(sp_obj.sp_explanations):\n", " l=exp.as_list(label=this_label)\n", " l.append((\"exp number\",i))\n", " dfl.append(dict(l))\n", " dftest=pd.DataFrame(dfl)\n", " df=df.append(pd.DataFrame(dfl,index=[iris.target_names[this_label] for i in range(len(sp_obj.sp_explanations))]))\n", "df" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] } ], "metadata": { "anaconda-cloud": {}, "kernelspec": { "display_name": "lime3", "language": "python", "name": "lime3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.7" } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: doc/notebooks/Tutorial - Faces and GradBoost.ipynb ================================================ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Overview\n", "The notebook shows how the ```lime_image``` tools can be applied to a slightly larger dataset like the Olivetti Faces. The dataset is very low resolution and allows quite a bit of rapid-iteration." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": false }, "outputs": [], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "from skimage.color import gray2rgb, rgb2gray # since the code wants color images\n", "from skimage.util.montage import montage2d # to make a nice montage of the images" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": false }, "outputs": [], "source": [ "from sklearn.datasets import fetch_olivetti_faces\n", "faces = fetch_olivetti_faces()\n", "# make each image color so lime_image works correctly\n", "X_vec = np.stack([gray2rgb(iimg) for iimg in faces.data.reshape((-1, 64, 64))],0)\n", "y_vec = faces.target.astype(np.uint8)" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(-0.5, 1279.5, 1279.5, -0.5)" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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dlMvlhHnPZDJYWVkRvUinh3acWIcpPzyDuVzubwdzinygQKoaXmY+FnC7YAKA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\nvr7egiq3mNC1V5xpt4coRXqRSER+v1+bm5tmWyAcAGUU5WD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AtXB1H2x+ADgblg1MGoi0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\nhy8Bc1AAzHn0WdZf5PVCgVT0Q1RjxuNxLS0taWdnR3/913+t4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Jvuw5AB7vn8/Ny6UnDW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+9sqVKxaMAHqxbWhvPVjnM5GUQJzhM/k+WQjOBgEbv4MvglVNp9P2DJFNehLEyy/+b6+PFEhF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\nKiqViu2x09NTra+vK5VKaX19XS0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xeCR4XVxcRKlUQqFQwM7OjsgGkYJjMpnQ2dkp5Vju\nR7Xxj8oJlPWiHq7NZkN3dzcmJyfhdDqFGqPaJ74zNZlU7RjfM9eSdokVLbUrmyOxGXTr9XrR6Wxt\nbYXf70c4HBafRNvEEir31f3oohqc0G5yj/A8MWmgnjAATE9Pw+/3o1arIRwON8i4FYtFxONx2dcc\nH26z2dDW1gaHw9GgKHE/usZzTjlGIsYGg0E6vdk4Rd/KRjae7UwmI01HRBw1Gg28Xi/sdjvcbrcE\ndOVyGeVyWTjeuVwOxWIRa2trkixxb6t+xmazyTlXkWJ1j6tn69f5MDVYYxzAykxnZyd0ugPFjbt3\n78JgMCAWi0mj0f7+QRNTJBIRbeaJiQk5awxUOS7c5XIJlYuAA+0xbfD6+rog5aySFItFGAwGHDp0\nCLdu3WpQGeEeI7qvAj3cY2rsoK6BCo7o9Xr09vYCAB566CEsLS3JGHQCFNx7H+f6RAWpTU1NGBsb\nky645eVlCRRJrAeAzs5O0XhjMMVuepYKUqmUlDmZdTLr7uvrk4V+/PHH8frrr0uzA3kshUJBuEvc\naCyXqcRjGn1mfLlcTkpGFOCnYbFYLAiFQsjlcvD7/fjCF76AiYkJFAoFmek8PDwsGbDKG1X5XSpy\nRuSKDS3cbOStceNxWpJKnD506BB2dnbQ3t4ujSl0NpxxrqJo96NtarMNAOFSqWUFfr9a3vzKV76C\nv//7vwcADAwMQKM5EL6Ox+NYW1tDOBwW/hf5fXTipH5wXzC7ZJZNRwEAzz77rPDpVlZWAAAvvPAC\n3n77bdy4cUMcbiAQkDVlAKSiOurhpnOp1WoN0kF8TyrSx0CZgaDBYJD57zTKer0e5XK5Ya8wIFCN\nBvnWwD1eIhtRgHsBGx0q76e5uRlPP/00Xn31ValOcAIRB2SQt6Zm69RqtVqtEhySzL+2toZSqYTV\n1VXk83lZIxpxs9mMSCQiHfYnT57ExYsXZQIT1Q6IDhKNVKsmauDFPc2vqZQINVBX0TieD51Oh+ef\nfx4rKyvo6+tDoVBAPB7H/v4+LBYLJicnZYAGAx7up8HBQUFSNjY2sLCwgGKxCI1GIzQjJgXf/OY3\nUavV8OGHH6KzsxPxeByLi4v4/Oc/j+985ztwu93Y2tpCPB6XhgSqLVSrVeGP2u32hnGsasNMLpfD\nwsKC8M3ItyOfmqhmU1OTBLZNTU3CF2bJXn1eBlD8bLPZLDQjNaBVtSo3NzeRzWZlbzJouF+9gsht\nNBqFzWaDz+cThYN0Oi3UoVQqJfbC6XTKGmxvb4uawPT0NJZ+NQKY+42I4vr6OqLRKEKhEFZXV5HL\n5WQPMMhhoMM/3EusnDmdTrS1tYm8IINWPj/RaTbksNmPtpnVtXq9jt7eXvm9tD08Zww2GJjYbDaZ\nHMepPwQW2LCTy+WwtLSEVColqjNqI09vby9u3ryJZDIpI07X19exuLgoNBDyb4kUx2IxEZfnxCGb\nzSaJAdUUpqenBaVlcGoymVCpVJDL5RAIBBAIBLCwsAAA0qSkqki0t7ejqalJRPxpD+9PPtfX17G8\nvCx7lM2U1J7Wag9oa9FoVJJE+pRIJIJAICAIarVaxcrKCra2DsY3swGR1SOuk1qhoo3jfi8UCtLb\nAADFYhF7e3sIh8NYXFyEy+USvirvpbm5GblcTqqzm5ubsieNRiPi8ThWVlbg9/sRDAZl5DOTZyrh\n3L59G9lsVt5FU1MTvF6vyE2+9957on5Sr9cxNTUlcouMRVg9rtfrCAQCcLvd0muiAiH3gw7ZbBaJ\nREIkAWk/qI1aKBT+l1rQ/9f1iQpSmVnUajVcvXpVtPM0Gg1u3rwpAeStW7dgt9tx6NAh9Pb2SuZB\nR8IAlaRvvV4Pn88nEDwlgs6ePSucmUAggM3NTSQSCZTLZckAl5eXpcmE87yHhoYQCoWkFMQMJ5FI\nYHV1VaQxtra20NbWBqvVCofDIY0HVqsVTqdTNqfBYJCObU6kYLBULBbhdDobSr4kfANoQOPovMmt\notGkoWWJADgIaij50tnZKf9+8+ZNaDQHDR5tbW3SlUlEgUgRjRBRVyI1DMBojHU6HXp6ev4Xj3Jv\nb08mSi0tLcFqtYpzuXTpEmKxGGq1mqAsL7zwAnK5HAwGA6LRKHw+n7zHbDbbUPpsb2/HyMhIA8ep\ntbUVly9fxujoKG7cuAG73S6z0VUSO5UZVAqGTqcTHiMdM5F+cqJ2dw8m7VCWRS2pWSwW6Y43GAw4\nefIk1tfXYbPZMDk5CavVivn5eRQKBeF/ulwu4Qu73W7hzLGTfXV1VZw933NrayucTidMJhM6OjrQ\n3d0NjUaDl19+GePj45ifn0e9fsDdqtcP+FbRaBQmkwnVahXZbFYMIx34oUOH0N/f31B6m5ubQzqd\nRiaTEZ5Uc3MzvF4vnE4nmpub5RwMDg4iEAg0aABbLBYMDw9LYJJOp8WJcJLc3t6e/D6iyXRq/Pdi\nsdggbUY7YLfbJcgyGAx4/vnn8bd/+7dYX19HV1eXjH4lKra6uir7+R/+4R9QLpdx/vx52O12bG1t\nob+/H7lcDs3NzZienpbGTODACbOLPRAIYGBgANFoFIcPH8bo6CjK5bIgoPF4HF6vF+3t7ahUKkgk\nEshms9DpdMjlcsjn8xJ48JnZ+LmysoJCoSBJgcPhQDgclvLr7u4ustmsrCUbqiKRiIz5ZXOXOhKW\nE5rYjMo1J82EKhnFYhELCwvIZrMSlKlUlXw+LyACKxc6nQ5bW1vo6OgQZKper8Pn84lskCqVxqCc\ngUatVpMhKFarFUePHpUmJAIEVDFxOBx48803MTo6ilgsJt3K1WoVFotFAlsiXvQL5DmSLmC32+Fy\nueTns9msnBOWqNlg2NLSIiM+AUji6nA40NTUhHQ6jfX1dZjNZgQCAeF0MhgxmUxIp9MolUoIh8Mi\nkcfENZVKYX19HVNTUzKhj1W29vZ2AAeI+WuvvYaxsTGZjKjVaiWApJReOBwW1RX2MrBxTm0cI0If\nj8exvb2NTCYjyDKHexCsKJfLYlM6Ozuh0WgkgCZqzD1Cm8l3woSWdhiAJMlEAnn2ucdo38PhMMrl\nMubm5sQHRiIRoWrx62z4JL+ayDUDPp/PB5vNJsE5B4EUCgWMj4+LMs729rb0amg0GiwvL2NlZQXh\ncBiTk5MNVRyq9AwPD8Nms6FUKsHn80kjFvcrG4wJTjCOiMfjsiepVcwGMe5h2urFxUVJGBlTkPNP\nW0D/PTs7i3g8ju7ubrS3t8t481qtJvtiYWEB8/Pzwkmn75qfnxda4srKioAcH/f6RAWpp06dgl6v\nx+3bt9HX1wefzyfl1I6ODqytrSGTyQiCwcNitVobtPJoDPR6PUZHR+H1emG1WuWAm81mFItFTE5O\n4siRIzhx4oQ4yO3tbXR2dgrq1N/fL4EO9Tl5uHt6emTMaUtLi0hTaLVaOJ1OyZQookuEJJVKIRqN\noq+vD6dPn0Y8HofVakVHR4foDVLWxkctvyQAACAASURBVGq1YnZ2VrKYer0Oj8cjc869Xq90llO4\nP5vNIpfLIZvNCiJAw8aM+VOf+hRqtRocDgd8Ph9++ctf4tixY3Kfu7u7mJmZETUBv9+Phx9+GN/7\n3vekU5Kl0o2NDdy5c0dkdVjGczqdGBgYQDwex97eHhYWFtDd3Y1Tp07B7/ejXq/j7t27GB0dxc2b\nN+F0OoV7dPToUWxubiIWi+HP/uzPMD4+jp6eHvh8PpRKJXR2diIUCiEQCODmzZvSoW02m2E2m3H6\n9GkJtNip/Nhjj+Hf/u3fRPuRMiHlchkOhwN37twRftnCwgIymYwQ6L1eL9xuN7xeL/x+f4P80vr6\nOrLZrDS0EHUymUxiYOx2O3p7e2GxWESlYHx8HB6PR762srKClZUVZLNZkRQjgk+UW6vVIpvNolwu\ni5C+RqOB2+1GKBSC1WoVFOfSpUt46qmnxFnU63VxiHq9XtaeTqhSqSCZTKJUKqFUKom0V7Vahd1u\nx/b2tgwmUA3/yMgIPB4PHA6H6Ma2trZiZWUFiUQCXV1d8Hq9uHHjBnp7e9HU1CSl9+XlZWSzWZkd\n/uGHH0Kj0QjC7/V60dPTg46ODnGg2WxWSr8MlJksWSwWOJ1OtLa2yrnWaDT4xje+gf/5n/8R2kJX\nVxcmJiYkITGbzSiVSvjZz36GBx98EG1tbQgGg3j//feFNvLpT38apVIJi4uL4uiplfwv//IvCIVC\neO655zAwMIBUKoVIJIJ0Oi1lymAwKMgrGyatVqtw7lQqD98rHTt1Nt1uNwA0oFFEQCg/VCgUkMlk\nsL29LTaUlRwiICaTCX6/X+Z5A/eoAqyakOaQSCTEvrLMx6pOrVaTCXLUi+Wac8/VajVROqDSicrj\nZkBLxIiceNouBq6UsGMQTGfPBG10dBTr6+sIBoNSOeI5JY3BaDTC4/FIkMaAmLZVTfRVlQzuET47\nAyYi5vzdXEedTid0DybQ+/v7CAaD8Pl8Ug0hxUBdU+CeNuzm5qYkI0QC+e8srT/77LN47733EA6H\npRzOIIQd6gwMCZZw33P9CQYxCOJ7o9Qjg0om3wQgmpqa8NOf/hTHjx9vqCzyPXNtqTCxsbGBZDIp\na9zd3S3SguVyWXRfVfoBkypq5AL3uKLRaBRms1mUFRYWFoTywGEKfH4K/zPAUsXxCTJQfcLr9SIY\nDMJgMDRIL+7tHeiuO51O3L59G4ODg5icnGxQW6E6DJvuKJvHSi6VJtRzTvSciDFlKImErq+vS58E\ng+GOjg5sbm7C5XIJEkpf19bWhu7ubuFQq7QyUpdIeZqZmRHZQtoQ8shrtZqop/zyl79EpVKBz+cT\nDvzHuT5RQSqlEfr6+hq4Y+yoY6BIHcF6vS4lAfK0GPjQAKyursrBMhgMkuU2NzfD5/NhY2MDL730\nEt59913k83n4fL4GLhEDDt4PYX2O0GPwYLPZcOHCBSQSCdTrdeE0cYPu7+/D7XZDq9XKdKzd3V08\n+eST+Kd/+ifEYjE8++yzaG1txerqKjY3N+UAe71ezMzMCJ+rVCqJNAaNCHCABlBAn/ImXNdgMCgo\nicViwfXr13H27FmcPn0a169fx5/8yZ9gbm5OiOHRaFS4OKVSCYlEAm+88QacTqegS11dXWKsarUa\nlpaWGgI08m542E0mE3p7e/HjH/8Yjz/+ODQaDaampgRRdTqdiMfjGB4eFlSSzR8nTpzA9773PUQi\nEemQnpycxOOPP46rV6+Kg6MM0OLiopSqWVpjOenxxx/Ht771LXHsra2tmJmZET1Qg8Eg0l8sO5F7\npdFoBKFgWSmZTArNg8aKEjV+v1/QmaWlJbmXvb09dHV1IRwOA4Cg1SaTCU6nE5VKRZAGtSRmNBpx\n5MgR6e41mUwIh8OwWq2C7rDD9sEHH8Tc3BwOHTokpXWn0wmbzYa1tTUMDQ1JeZHJAYM4GjDSSNTG\nkWAwiDfeeENKXWo5uFarIRAISEBLbtWRI0fw5ptvolQq4YEHHhBqyNraGo4fP47W1lYptxOJIVpH\n/V2WXEkF4fcAB+hdIBCA3+8X1GNmZgbHjh1DU9OB9NzIyAh6e3tRr9fx3nvvYWVlRYJ0jUaD+fl5\nXLhwAe+++y4cDgcA4MyZMyJTxbId9XlDoZBIwLhcLrz66qv4m7/5G/zpn/4pXC6XdLlztClL7isr\nK8JlJCLMBJolSJ5p2jU6UzoslQpE+8jhI62trbDZbFL+ZdDHJIQjeAEIesTSORE1lgQpHaSqiJCD\nyj2yubmJ1tZWGXKyuLgoDre5uVkm3qmKCgxwqS3MIDKZTKKnpwfAvfHM5KSyUYXIG+lVDK49Ho8E\n5uTQZzIZqY7xDG1tHcyqp51mJYhUGdJ4WDolEkifwsCPZWOLxYJEIiGOn87dbreLpiqpGQaDQQId\nnjW+R7UphdUZ7htWaAwGA7a3t2VU9t7engAvrBTSd7Fsvrd3MCiBIAJ1Yplw7OzsSEOhRqMRniUD\nW/JtSbHiRCOu+9jYmHCMVV6+2rnPIIg6v0x8yVNlIs0yPgCxf1artWGvcL3oB6j7Wq/XpTm1WCzK\npEE16VKVW/j++X6pE0o7y0SE9oi+kRQGABJw1uv3pMR0ugM5ueXlZfh8PqGvqZUL2jXeLz+XyQf9\nPPcYdbY5zY6ULsYWrIJxXfjeSFGgegr3EM8mEzidTifADRMo7n+DwQC73Y729nbE43GRR/y41ycq\nSGUZu6mpSaY8NTc3I5VK4erVq3A6nYJeFAoF+T6OYaxWq4jH49KkVK/XRbLD6/VicHAQwWAQuVxO\niN1sEuAG293dRTqdBnAQOCwvL0Ov14sAN/XL7Ha7GDBu0kwmIxpslUoFt2/fltJcT0+PbMD19XUR\nlbZarWhpaUEqlYLVaoVer0cmk8Hg4CCam5vx/vvvY3l5GcA9aRoiUwyUGVR0d3fDZDLJlCiKp9MY\nLSwsYGBgAI8++iiOHz+O2dlZnD59Gq+//jreffddybBZas9kMigUCsLfSaVSsNlsUi4GDjJjlkOJ\nCjBwoDatXq/H8PAwfD4fdnd38cgjj8But+Pb3/42zp07h4GBAczNzSGfz4sxy+fzUtb9u7/7O2g0\nGkGd+vv70dzcjBdffBHRaFTKm8xeOfTAZrPB5XIJ529/fx+nT58WriiFtjc3N9HW1ga/34+dnR1c\nvnwZKysrggxQA5FcSgCCjoVCIVgsFty9exebm5vSXcy9lc1mEQ6HEQgEcPjwYczPz8Nms4mGK50V\n9U3599ramgSTNptNAh3gIMDlfiSthaLiLNn5fD7s7OwIb+qll17Chx9+iEgkIoEpy4p0/pSTYXMF\nBZ3J26WTWl1dbUjclpaWkEwm4XQ6EQ6HBeGtVquy/oODg0gmk3C5XDh8+DAMBgOSyaQ0T12/fh2x\nWExKyXwml8slpX6+j66uLkSjUaytrcl6c2xtqVRCd3c3IpEI3G43rl+/jlOnTuGVV17B4cOHUSwW\nMT8/j9XVVRw7dgyhUAjf/OY34fV68fLLL+PSpUvIZrOShBC5cjgcuHDhgvwOcsgvX76Mvb09nDp1\nCt/4xjfwr//6r/jggw8wPDwsnD+/3y988OXlZXnGeDyOUqmEWq0mQSHLekxe1KYh8j+JUiYSCSws\nLIjOJdfbbDbDZrNhe3sbTqdTAiOWps1mM+LxOObn50UQnaXkjY0NQfu45izj84zVajUkk0lsbW2J\nrd3b25MEweVyYXZ2VgI/Onm1uYq8XH69paUFXq9XgjkVyXW5XMJ5JLrKe2WiRPvt9XqFc8qJfa2t\nrejs7EQqlZIBH2yiWl9fl+5sOmNyUilFxWDZYDCgUqmgVCrJfbpcLjmXLFMzEGKgm0wm4fF4YDab\nRbBdtVekXXk8HjidTmmAoQ7zxsaGvEMiY+TyUvf06NGjSKVSDdxZ6o2aTCbEYjHcvXtXEjaPx4Nk\nMimfzeY/PgeDeiZkDAYLhYLYTo1GIzQANmsCEB/GZk3awVwuJ+X3/v5+9PT0SEmfF0EFTipkYkB/\nQh41gywmcyoYQfkq8n3z+bxoLHP92tvbxTYzoSG6TpoLKRvqntvf35cy/OHDhyWJq9cP1GOYEJJH\nfPnyZZRKJZw5c0aaBI1GIzY3N4Umw4okk1EmrqysnT59GlarVRoDSRugxBinaNIHTE1NCfWRdKSN\njQ243W6xCWys0mq1Yq+ZOHNENatUOp0OLpdLqsKkUXzc6xMVpDJbAyDBklarlSw8FovhwQcfRKlU\ngsfjgdvtFt6kw+HA9vY2BgcHpZOU3L50Oo3p6WmYzWb88Ic/xMjICI4ePSo8UzWrvnXrFhKJhKC1\nBoMBd+7cQTAYlDIBOXZra2tSEt3a2sLhw4cxMzODVCoFo9GIQqEgDq1WqyEajaKnpwd+vx9LS0sY\nGhoSjqpOp5MmoeHhYdRqNVy6dAkLCwu4ffs2HnjgAXz5y1/G9evXhYu4t7cHt9sNh8MhATODPcoB\nzc7OIhAI4I//+I8xOTmJK1eu4B//8R/x1a9+FYFAQHg3Fy5cgM1mQzabRalUwssvv4zLly9jaWlJ\nyq6rq6vQarV46qmnpOTh8XiECM6ShMvlwpUrV2AymfAXf/EX+M53voNsNosHHnhAjOhrr70mDTiX\nLl1CIpGQ0tpbb72FUqmEUCiEo0ePIpFIQKfTibMngkxk9OjRo3jttdeE0zQ+Po5yuYxHH30UkUgE\nhw4dEgfe19eH8fFxtLS0oKenR/g1HR0dqFQqmJycxK1bt3Dr1i089dRTePbZZ3H9+nUZV0ouLx2Z\nwWDA3NycdLDq9XosLS3B4XDgj/7oj7C4uIh0Oo3z58/jmWeekbI1+YbUXlxcXEQgEMC3v/1tRCIR\nydSJDjEgoDM1m83CT6QY+srKCjY2NjA0NCRJAdGtkZER1Go1DA0NNTQolctlJBIJCTp/+tOfwmaz\nYXh4WBIcCoNzdGkgEEBXVxeuX78ufMEbN26gqalJAvGTJ0/C4XAI4kJReaJ9Op1O1oIB6s2bN2Gz\n2fCNb3wDly9fRrVaRSaTEWSJlIDd3V1MT0+LE8vlcojFYjh+/Dg8Hg9KpRJ+/vOf4+GHH8bhw4eF\n+pJMJnHx4sUGgfCJiQl4PB4UCgUsLCwIsmIymSQIImUkHo/D5/Oht7cX8XhcnF82m8X58+clyKzV\nDkYpMon0er0idr+5uYn5+Xk8+OCDsFqtuHbtmpyN7e1tQdaYPAOQyUoc89zU1ISRkRFMTU1hb28P\nhUIBJ0+exM2bN5FIJKTDmJUBBhmsMjU1NaG3txcXL15EPp/H6OhoQ8MebTE/n82WRArdbjdu3LiB\n3d1dQYKWl5eF5sGEiiVfi8WC1dVVvPXWW4Lw5fN5mM1mHDt2DEajET09PaIIoHbfe71e1Ot12Gw2\nzM3N4a233hLEnvuxp6dHuP8sVzPgsFqtWFlZQSaTQVdXF4LBIH72s59hfX0d3d3dMtKY6CzRbAb5\nDB4sFgu6urpw8eJFrKysCNpK+gHXi2VdcquJ5F27dg27u7t49913RSlmbGxM+LXU1FQDNiodrK6u\nore3F9///vcFxCGl4NChQwgGg2hqapL9w3srlUpC2RoZGcGVK1ekOZkT6UKhEGw22//i0dPGrKys\nIBAI4Cc/+Yn0Ojz66KOYnp7G8ePHpU9DnZDHqW/xeFySd6LlpL309/fD7XZLWVsFA3Z3d2G325FM\nJhGNRnH37l1otVpB0zlAgFUHnglWJ9fX16HT6XD9+nW43W68/vrrcLvdmJmZwVNPPQWz2Sygx8bG\nhlR8yCkm4HTixAn85Cc/kapDJBLBxMQEHnjgAXR0dEiVi+h2MBiU/ROLxQRxLxQKiEQi6Ovrw87O\njgxb4KQuvnOiqV6vF5VKBYuLi8KFP3r0KILBIC5evIjJyUmEw+EGmbjNzU1JjsfGxrCwsIDZ2Vnp\neaAeN9FqBvQq5YD/PzQ0hB/+8Ie4dOmSxD2kUTEJJO3i41yfqCCVCA/LWcw+A4EA3nvvPcmePB4P\ntFotOjo6ANzjAPHPI488gl/84heSiZ44cUJ4K0NDQ1JqYsmKnC4GQswYdDod0uk0IpGIdDaS2+l2\nu6Uc0tx8MDP45MmTaG1tRWtrq3TADQ0NSbBAziAnQrEsUqlUEA6HG3gg8XgctVoNbW1teOaZZ3Dm\nzBkEAgFBrJaWlqQ5hIeXAUAoFML8/LyUdwcHB5FKpeDz+fDMM8/gww8/xOrqKkKhkJROzp07h/Hx\ncQmG0uk0stksOjs70d3d3aAs4HA4ZG0B4M///M9x8uRJeDwe6T7t6OhArVbDnTt3cPz4cRlb2dfX\nB5PJhHfeeQdOpxP5fB43b95EuVxGLpeDy+XCk08+iVu3bgmywYyeHGI2hRCF0Wq16OzslCyUXaD9\n/f3Y2NhAPB4XeRuW+xYXF/GZz3xGOu7r9TpisZhwkZ9//nk899xzCIVCIt589+5dSQjURi12sy8s\nLEiGy+aTkZERbGxs4K233sLy8rJImZBjRQrAZz/7WQSDQfzzP/8zbDabNNBxOgk5dpy05fF4BL3g\nQIJkMilNTNlsFpFIRIw/g62enh5Bujc3N5HJZLCxsYGHHnoIP/jBD+D3+3HixAlxFi6XSxJArhMb\n6Lq6uqTJkKjs8ePHBQH2er0A7o2fdTgciEajDZJT+XwemUwGPT096O7uhk6nQzgcRi6Xw97eHmKx\nmCgh0CFRRou/p1gsYnV1FY8++ihOnjwJAIjH41LlsNlsKBaL6OzslJJhc3OzoKGkMeTzeTmTqVQK\nzz33XIN6wvPPP49f/OIX6OzsRCwWk9LdkSNH4PF4YLVaJbgn4rO0tCS6jURnyVenJBedNRs8u7q6\nANyrnJDG0t7eLhSlWq2GSCQiyI06uYbVptbWVumMZuBFtMdqtWJ0dBSlUkmUHNxuNzwej4yVJY3D\n5/NJwxMDv97eXmkKKxQKaGtrkwYmACIur9VqYTKZMDAwAIvFgkKhgJWVFUFkOa7YbDY3TA/SaDSC\nlKlKInx+cgur1YNRv36/XyhWTLy53tTEZnmYwYHH45GzFAqFGoJNvi9SHlhJYcMdubxsAqW6Bc8f\nP7ulpQW5XA67u7vo6OjAM888I8/GHgGTySR7muuulm1pP1988UU5F6RuMJEkHYFyUi0tLWhpaZFe\nDLPZjMceewwAROyeSJw68pp/yGnlZz/33HOCrBH1TyQSwqlXJb+45kNDQ3A6naJ2QwUPu90uVDb6\nbpUqwaCZ61ypVKR0z6lRTA643zmUhO8hlUrJ+X744YdRKpXwqU99SqaEsWxP9JhxBCusra2tyGQy\n+NKXviS+nPxg1f4wud/a2sLo6Cja2tpkvxEtnZmZgd1ul8Q4EAhIJdZmswG4V6XweDzY3d3FkSNH\nYDAYpHGaKhX3vyv6NPZ/eDweVKtVBINBtLS04KGHHkJ/f7+gp/v7+9KwTfqJzWaT+Ie8+UwmI1Wv\nubk5oSO5XC7cunWrQTbr/7o+UUEqN7rBcDCNyOfzCeI0MDAgULxOp0MoFJKSIjtcydGx2+34whe+\ngPHxcSl7sPQEAO3t7cLDoMEgUdvlcom8DAnIzP6ISrGUSwK/Kn8zPDyMjo4OKXeQz6NKljgcDkGZ\narUDLbuXX35ZnOX+/r3ZvA8++KCUd65cuSIIr16vlxI2jeXGxgYGBwcxPz8vz+HxeOD1ejExMYF6\nvY5PfepT0vnOMZobGxuwWCwYGRnB4OAg5ubm5ECqc623t7fxe7/3e7h9+3aDSsBf/dVfYXFxEWtr\na7h16xYKhQI6OjrQ3t6Ozc1NjI2NSUDNcqbD4ZAynMvlEg0+loSHh4elzEl+00svvYSNjQ14vV4h\ng58+fRrf+ta3MDY2hjt37kiZ2G63IxgMYmBgQMpnNCyDg4Mwm80YGBiQUjK5zcViEV/96lel5HP5\n8mXhcNEBGAwHI1FbW1ulOeLOnTsy7tDj8cBut4uuXF9fH86dOye8Kpbk19fXEYlE4PP5oNPpMDk5\nia997WtS2tXr9cLvJMLFrP3cuXM4f/68JFuFQgFHjx7FmTNncOrUKUFZd3Z20NLSgs3NTXzxi18U\n9IEyS11dXXKmvvSlLyEej0u3tcViEbSTiDMpMZzdHIvFUK1W0dnZCZvNBqPRiL6+PgmsgXs6qww6\nVM4aZYfC4bAoJ7z//vvCpaMaAdFnBpmf+cxn8Oabb0pp3OPxYGRkBJVKBb29vbh27RrMZjP8fr+g\na01NTRgYGBBuO7l3DE7UsuaxY8ek4ZDNRlarFUNDQ5idncUjjzyCpaUluS/aAnL96Mh53hkkDg4O\nYmFhAcvLy2hqasJDDz0k/E3uWUrfAfecl9/vF6kt0o/IPWYZkwkQufIMVFidcjgcGB0dlQoPy5YA\nJHAl6suLQSADjFqtJp3jnMvOs0SOJYM01a6T58qZ7js7OxIwWq1WQclVP8CGIoPBIDJNbM7inmTA\nwYCBCA/Xv62tDTabDaurq1IlOnLkiJTmGSharVahjRFd8vv9KBaL0hw3NTUFi8WCvr4+SdIZWKv8\nSwZK9CdnzpyRkdoqzYiABhVMVMk7vkPyCFk1CIVCwl0cGhpCU1OT3Lc6Krq1tVUad9n46/F4pGzN\naorJZJLqgYri0u+xjK7X69HZ2SlrfO7cOUE+2SjEi2eJ79zr9YqvYcOg2lTFhjWiuPy9XAfKqdFm\ncK3ZVEV6FfcegYdCoSB0EdLquL5cez43v87Ame+JyjsEs0jDY8JTqVTkHbFBmvz4lpYWLCwsYGho\nCHNzcxIz2Gw2bG1tST8EfzeTC9JiqD27traGiYkJCehPnDgBvV4viaDZbEb4V5Mys9ks7t69K0om\nRE8JvrAyxrXm18llJvrd09Mj2riHDx+G1+uV80t78nGvT1SQyrILy+MM6ngQ6QRZSqHhJH+Oh4MI\nJJ0WycEMLlmWVbsVSZQmWkrnANwTwKZjJ4JKbolaPiVPiUaQFAEaI2Z/DBSq1SrcbjeCwaDA7js7\nOyIB1dTUBJfLhcXFRXHcJpNJRJBJWWAAtL+/j6effhoXLlzA4uKiOGAiICyh7e3tCR+RSBhnpJPb\nYjQapYRGXuLk5KQ4N66Jy+XC1atXEQwG8elPfxpLS0uS3Xq9XkFgAQj/7oknnpAAme+3Wq1KEMeS\nFflN9XodbrdbECqWtmq1Gn7rt34L3/3ud/HlL39ZOkdNJpO8U1IMtFot5ufn0d3djSNHjogDZ3JD\nRItNRktLS9KtzOCM5XciFCS5f+5zn8N///d/i3PV6e7ppBqNRikrkqdL1J77jbI25O1qNBohp/M+\nyRGk4yD9g0ZaTYZ4nyyxAQdNQFw/GnieNZYqaZyBg05y7n02sLFqoNFocPr0aUQikQYEuqmpSfY+\njT/XRKPR4NOf/nSDbFJLSwt6e3slSFheXha+YFNTEwYHBxs6fImqdnR0YGhoCDdv3sT+/r4gNmxs\nee6556S5UKvV4tlnnxVkjwgSEy0ixJQUqtfrgszzPNIwDw8PY2JiAqurqzh8+DCAe9OWeF75fnQ6\nHbq7u7G0tCTouc1mExSSvD+WVjs6OgTdo11iV7RqN0jnYeBLp0Y7xPcEoMEJcy8RceTZ1el0otrA\n+7yfJ8jmDSIofD9E/Xi2edbJH+b38mutra2yr4B7E39UegP/TbW9Op1OqE2RSEQ+k0AFE3nuP9pS\n7mmbzSbyT0SFyJ8lr5xIHO+LqJRGo5FG1La2Nvh8PgEZADSAJ/xZrh/3gU53IGNHOTkVTVXL7Lxa\nW1sFJGEgz25+IresLPL5VWlCNjqq751oXmtrqwRaBFjUIJXv2GKxSEc6NTh3dnbEtjIR4Jrz4hpS\nQpJUDFJ/1P3Ni2sCQOzZ4OCg6OTSt/F7yZ0n7YmJAdFBJvk7OztwOp2yN4gcEiBSS93cz4xBuOak\nj5DCQm4+kWtVoYHPRp/W1dUlmsYtLS0SA6jrQf41145oPRMZdW+xsqgCPoxFdnZ2hIpG+ggbKYkY\nq+ebz602TfHMcPQp7RORZ8YtahL6f12fqCCVh5ILqQokq6UEAHJg+LJVo7W+vi4lRjXwBA6yNB5m\nOhMeEG5a9XAzc6Pj5aYl2ZpZLQAJgHd3dyUYYVOHGhCpjQ7AgTFg5srMSF0LckJomNSpGqosCrla\nzc3N+OxnP4vl5WXhG9KoFItF4Tu2tbXJyEZmi+l0GocOHZJ5yHQ8ExMTaGpqQnd3tzgUotg6nQ7P\nPvss/vqv/xovvPACjh07Jg6WjpvrqtVqEYvFcOTIEUxNTWFubg6RSERQyXA4LM+m1WqRTqeRy+Uw\nNjaGRCIhPCD1nTudTnR3d+P8+fN4+umnZXY7yxvMsgHI2tM50PAwUeHz8uCqnaTsMFf3h0odeeGF\nFxCNRhGNRoWLx2YL6hfyswCI9AqDWuoVcr+y05UBmrrHGeANDQ2JwWagpcqqsJyk1WoRDAYxMzMj\npXOeCaLSdFYul0ucJHWE+Zx0AuSosjFnY2NDSs5seGEgyLOl1WoRiUSkm5XINgMHBkNE7IhWEA3m\n5zOpOHXqFNxuN+7evQu9Xi8lLcpR8bn5949//GN8/vOfx87Ojug68rl3d3exvLyMiYkJfOYzn0E+\nn5eGQ3IyWZY8fvw4xsfHcf78eZw8efJ/fS6/b35+HgMDAw2BA2XRjEYjHA6HBDgMHnm/wL1xndzr\nTCQpcM4RoyrtiFQDTqPinuHnM7Dl3qMmLve0amv5zuikKQZO+gcDB94z1UWYZHOf0TbyvHH/c+35\njLxH3gedMW0uAQnVL/D3MilmIwudNwNL2kqVH2m1WtHZ2SmB5P0la6vVitXVVdEeZuMZE38GK8Vi\nUZw69zYvPj+RRV7qOnMN1DVhsshAgTQj/ju/d2dnRxQQGLCr9omNMNxLvBj0qPeqckO5r4hyMyin\nT+UeZ9c6be39iYaKDqufcf/F8j4n+rFRzW63w+FwiI2lLjOlz8gXZ/MSn432W+U3q++WZ0a9VzbR\nci358/xZnoWdnR2hlKnvUNUOh4Ff+QAAIABJREFUZeDodDrl3RHUoV1h3KGuFX9Xc3OzqONwzVWp\nMnW/MthVlRCYPJJywudW94C69jzfRqNRtGxplxiDUKru/mf9v65PVJBKx8cggc6KF9FNZm2Uf7JY\nLMjn82hubhYdOL3+QG+VKIfb7RaYm0ETXxqNpLrR6XR4GDY2NlAqlQRip9NgIEHDRYP4wQcfSEec\nWv7h56+trYkRJ0rG30mJDH4dgIgO0+HRGNO5q06A68hMmJuZwRqDYZW7Q54XtVxZ3q1UKvj5z38u\ntAF2jNpsNpHkoHE8fPgwLl26BI/Hg76+PrS3twvyzfVhwwQFhwOBgGh3ptNpGceWyWRw+/ZtAMCR\nI0cko+NnZrNZGaFLEeympia8+uqraG9vx4kTJ0SWSavVihQMy6bqwQUg6B4Dfe4hr9cr74glYjaE\n0Ggz2zUajfD5fNI8Q0PLDmnuaRorvmcA0pyhBincf7xHNvKxkYh7lDxHOgm+a5PJJPuDyRo7i/lM\nahWBGb7qMIkaazQaKdcxYCYHeH9/XzJxomZEUZh5k0PId682gLD8z+5SjmpkRzpROQZNzc3NKJfL\nUh7nFCOVnkMRa2b8pVIJp0+flg5oTjSq1e4NschmsxgdHZVgjqVsim6Tfzg6OiqUlzfeeAM2mw39\n/f3o6+uDTqdDoVCA3W4XRQ9ePJ9sriFCz6RPDRLV4I0UBDoqdmfzPTHQ4BpyzYl+EX1Ry5oAJCFS\nUU1eDIxpP9m8x4AFuDffnEhesViUQIpnQn121SEzQFZtH4N4FeFpamqSjngV6eS6cE3oF0hjUpMu\n7kV+JjU1yeWkw1efHYAksqwukS/Id7q3tyf9E0zcCGSoyDBwD01Wg2v13TFIYyBE/jnBAgYi6j0y\nKOa7Jcqq+gKuvVpO58/fH7RyPZnkc125Z2kn6TfZnMZmnPuf7de9b34W3zPvi/fc1NTUoOPKz2Ms\nQOSWQSA/V626qs+vBqb8HO5RAHIfTGYoF0YVF9oedT8xuKVfoR1R14Cfz/umHef9EJklest/o21W\nASvVHvNZVF+l7g11PdX9pvoR7jcCD0Scd3d3hfqirhWb0er1gwEwrAp83OsTFaTSEBLtVI0gpyIw\nQNVoDqZQ6XQ69Pb2Cv/TYDDggw8+wFNPPYXV1VUxgqlUSvheW1tbCAaDqNcPmmVY5mK2oGYtm5ub\nMoLM7/ejUqng1q1bMoKPzR/Nzc3IZDKoVCro6OiAyWRCsVjErVu30NvbC4/HI0ZuY2MDwMFEDKfT\nidXVVZTLZQkqADTwZXjRAFF/kUGy3W7H4uKi6K/ye2/cuCEBk1rKY1MYAORyOQSDQXkGo9GIhYUF\nOVxarRZjY2MoFAoSyLHRixqLZrMZ1WoVX/nKV/CXf/mX2N7extWrV2Ua0B/8wR+I0D75T/v7+9J0\n43A4sLe3B5/Ph+npadErHBoaEoTL5/Phzp07KBaLMh1sYmICg4ODKBaLOHHiBF555RV0dHRAq9Ui\nlUoBgEjysLTNwJ4SV0Qx6URojGlk1FIqAwAA0nVL2adsNoutrS0sLS0JCklOETmLNIhEGelE+HXV\n+LPkr9FokMlkYDKZkM1msbm5KclCW1sbxsfHBbF1OByCmLMsRVRgf38fiUQCsVgM4V816fH9sjRG\nA6fus7a2NhHZXltbE1WH7e1t9Pf34/r167BYLKLNSZSQ66TSMliSYhMY9+D9JSgigKr0DmXd2ICl\n0+lkIhCRZzZqqcgg153vmvSViYmJBi4bBwBwRDE1iSl7Mz09jdHRUczOziIUCkkFhnw3am9qNBoJ\ngohAplIpCexUR3W/81GREjoflqU57YhnlwkAf577hs6NvMOFhQUEg8FfyyPjz9CBcQ/wdzLYrNVq\n0mxGpFgFEegQuZe02gNpHSpRMNBQgyQiS3zPtFPZbFYQdGpiM2Aj+s5gjg6Ue0rVsuXzqeeMQRHf\nnfr8asMW79ViseDQoUO4ffu2cFtZiaF2MpvUDAaDBEp8LgY4qg0HIPJNTHr4fVxPNRAiBYrrqu4X\nJorcZ7lcTgKX+98374MUFv48cG9sNc8i1zudTov6AH0RAy6+d/430Uw16FPvk8oATKDJj1XHlubz\neeRyObS0tEgpn6gifRpR1r29g2EHlOLj1/i991cE2MTEz6KfZFKg7hHaPtKB1PfHSilHFadSKeFB\n37x5E2fOnJHET6228b+JQDKxUXnXDM4JotAuq+eRP3s/Gs1nuH8PM9Dk56q2nu87FArJlC7er5ok\nM4msVquYnp6GVquV4SIf5/pEBakULKaT4kIT4lfJ6izBsUFoa2sL2WwWFosFg4ODwn/i5q3VDrT9\n2KlKFIGajGyE4cEnp/D69etIJBIYHR0FANEppSHa29tDPB5HIBCAzWZD+Ffj52q1mtwnJ5KwVEUE\ngUHm7u6ulLJpgLk5aRgookxeks1mk5KeRqNBMpmUzbe3t4eBgQGZv0uH3tPTI06G6gQ0FszsmEnX\najVpXOKmXV5exuLiojTisCS0t7cn0zfYZNDc3IxwOAyfz4doNCq8IB5WOp29vXsDEoxGI0KhkKCj\nqh5hPB7HBx98AI/Hg7a2NuEhffDBB1L2IdJKSgWfhwaDouPUqFxfXxf0kn94eLkPGaSm02lpBFM7\n6NX30tXVhampKenWrVarwqUmSqDuL2bmQOP8ZDZqbW1t4b333sP+/j4eeughpFIpKX/+/Oc/x4sv\nviiGjcgcy/t0pnQQwIERjUaj8Hq9DSgKgxT1+9kwNz8/j/fffx9f+MIXZFTehQsX8P777+MP//AP\nUa8faCASFWV2zo5RVZCcCPivQxdVB0y0lw2M165dw8jIiDRfFAoFLC0t4bHHHsPc3Jw0RWi12gbn\nw2RIpztoKiGH22g0ijYhpzmtrq6KQ04kEvjlL38Ji8WCcDgsU8WMRiNu3bolCFpbWxuy2SxisRj8\nfr8EHmrZtbm5WfSJ+ZxqwKYGidwjdAx0/Azi2PjDPUNEiRfPEgMVjrUcGxtrqOSo752C3QAaeJZE\nR1VtVXa5AxCEXkXUSF3guaUzp01TESnaeAZUlUoFU1NTuHLlCr7+9a8jn8/LYBKXyyVTpKjWwJIt\nEWYGtMViUTiH95c3ue7UASWfk81P3H/AvQCQ72VtbU0GHvB3sjoAQMaAEpFSUU71d6qoINeKWsKr\nq6tCxbpz547QgxgEEc1n1Y9rSJukjmVW3zH3HN8Vk1ai7Gy8VZ+VFRR1kAYvvkMi17SBfD6eabVC\nqVYCqBk8NzeHhYUFPPTQQ0gkEkgkEmKjNRpNAyJer9dlj9FnUgJOpUYxIVKrkDwrPE8clJLNZoV+\nU61WMT4+jlAoJPuWVSa1yqauOZN3vpNoNCpnjzZIte08CyqirAaz+/sHzYAceqCeG/V9qtQN+lSu\nt/qZfHf1el2UEbRarfgL3iOlsoji8ncT2WUyVi6XpeHz/8/1iQpSVSkolgTp6FgaJ/LBJhaiTsxe\nSE5WpRXUgJJBG2WF1O5dlfe3u3sw8u7q1at4/vnnG/hVpVJJXjaNbKFQQHt7uxgzu90uosUffvih\nyEjwADKj1Gg0iEQimJ6eRn9/f0MHLw84RdWz2az8WywWw8TEhGitJhIJtLe348aNGyiXyyKPQxHj\nnZ0dLC4uCp+MwWp/fz/m5+dhMpmkq5yGlk6H70GrPZD9IiLHDQxA1pQGiEaJB40lYDZ5zc3NiVwT\n3zX/ZpbKi8kDlQ64dkRbTSYTzGaziBpzWgd5pGoAxb20vLws+roqikpDy2CN89Q1mgNR7f/4j/+A\n2+3G2bNnkUgkUKvVsLi4iNdeew2/8zu/I2un1+tlKhqdPINDoiN8B0SiaPzoNGq1mqgfAJBOT6vV\ninPnzklDAsuCRLsBCNK2sbEhARxlvRh402nfv99IJWlra4Pb7cbjjz8uXNUrV64gHA6jq6tLkA6K\n+5dKJeGmMWMnp5UZ++zsLD71qU9J8sCgjIaYDo9OZ3p6GoFAQM6vRqNBLpfDRx99hGAwiFqthkKh\nIMbY5/NJgA7cC3qTySQikYi8WyaL6XQaq6urglgS6T58+LDwLukgNRoNxsbG4PF4kMvloNVqRWh+\nZmZGJLSow7i5uQmn04mJiQlZw/sRRaI8DL64v2mrpqenpTlyf39fJN7Ui0kskTwii+VyGSsrK+L4\n1TVhIMxzx+56yjft7x9MsZmbm5P/ZwCjlj65l3nmCSbwnDFgU5MglddHpLtWq6G/vx82mw3z8/PI\nZrPQ6XTY2toSLqdahVCbxDY2NhoSmPCvBiGoz8u/eb/cX3wullWZMFerVeTzeczPzzeUPHmuuMbV\nahW5XA4bGxuyxnwX1NxkgMi9x/vQaDQiM3T9+nUsLy/jmWeeQSaTwdtvvy2SQjabTRBT3qdacaHN\nYABH+3E/qsnzxmCN6hb5fB7pdFoaxSYnJ2X0MzmK1GxVqRVcl83NTdGQZnKoBqhMnnheSNug7c3l\ncqJlu7u7K0oHbPLke2awxM9MpVJChVH/jXZcPR9MCsh7z+VyuHjxIjQajUix3bhxA5ubmxgcHJQE\nVr0fNWkslUoy0YsBvNFoFOSfjcUq6MF3xorvzs6O2N1CodBQYWKQen814P4Eln6B54OfVa/fm24G\nNI7ZjUaj0geyt7eH8fFxuFwuea8M8vl+OVhiZmZGzry6vv/X9YkKUoF7sDVwD0VUg0eigjQiLP+X\ny2URkWYG4fV6G0pKdNaqTiMPEjUS1Q77q1evoq+vT5BWAIIMcdTf2tqajJxTNyQRXpaiP/roI3zu\nc5+Tsg6NtF5/oLNYLBYlwGlpaRFjxnvn51NWBgBGR0exu7sLnU6H5eVluFwunDx5UiQn8vm8GAh2\n0ZMjSfSLDtzn8zWgHSxnM8tkMM6/GcCy8WVgYACbm5sIhUJYWFiQqUXr6+syW5iTjThXmUaVDWYq\n/420BArJl0olrK+vS/bOhqJkMonwr8bOhcNhrK6uNuwPVfaI97+4uIhz584hGo0iHA5LUMmyMw8n\np26QklCpVESkfnt7G9FoFENDQ6hWq/iN3/gN+P1+LC8vy0QQABLAMZhn+VQNzFSUg4kW34XL5RLD\nRurA/v4+vF6vTMkiR5UlSCJTDIK5tqurqzh16hTK5TL8fn9DKY33w8YQOlUqD1AT0eFwCPfbaDSK\nXBHpNnxO/s1mBJ1Oh6NHj+LSpUvyrCy9qkgCnTGTC74fcgmJnLz00kvScZ5IJOQs0onz9xJ14e8n\nisCAhBJakUhEEAQir7VaTaoirNYwaAqHwzJiNBQKIZlMYnZ2VigzZrNZptWMj4/L5B41aOGaq0Fc\nKpWSwGl5eRlLv5rmxUoOA+Z6vS4Jnxqw8LyzAkGawP2JOEvWTL5Vzngmk4HD4cDS0pJQWigZx+oN\n7QCDMn4uES5+nhpYqsE0KQtMHnU6HZxOJ9ra2hCLxYQ2wb1Iu0kKDt8VE9KtrS2RzGGjjZoQcG+r\nDpbVOAYei4uLQuUKh8OYnp5GMpkUOgdBBXWtCWaoCCl9gGrT1LIpn4fNVLVaDUePHkUoFMLy8jIy\nmQxGR0dRr9eFJsIEm8MBVBtFe0NbrII9vBfuf6Ka/Oy1tTXcuHEDtVoNhw4dQj6fF+nG8K+aWHkm\nyVVU99v29sG4UKpiqGgeE0smeGyyZGDG93337l1Jik0mk9hq2j1W+Yj2sUcklUoJDUs938A9LinX\niQkBg/eWlhZ89rOfRblcRjqdxvb2Ns6cOSPSbaTMsJpoNBol6SIVqFwuN9jmnp4eVCoV6R3heefF\nteTasWm4Wq3izp07gpQzyaft4R7i/uE68xwxmbg/+eX/82yVSiUUi0VoNBrMzMwIsJNOp9HV1SXn\nihUGFSAsl8uYmJhAS0tLQ/Xl41yfqCB1ZmZGBGPVkvji4qIYXr4MOjReFBsnkTuVSkk3p16vF7H1\nsbExkSXhS6AhZOBYr9elHPHEE08Id5JckXq9jnA4jHK5LHw8Gi2dTifNSi6XC/l8HpVKBT09PeII\n9Hq9dMoBgNfrRVdXlzhTGngimDQybISic0gkEqKrRqfI7l0G6ZlMRiZxkNpgtVqFZP+f//mfshYk\npev1epHNoHFmYKp2fJfLZRk/yiSAqE9PTw+uXLkio/6sVmtDScjpdGJ6eloaQJhVAmjgETOQJieS\nQRyzXJZd+DwazT3pGD4zL/5/JpPB8PAwpqamxICpPDUVISA/ltms2+2WJMNsNksJh2gnRfD5+dy3\nzc3NMm+ee0B1WEQhGJwR5SCqyGY7lrOI5tMA8T5UjhrXkklAOBwWQ0/+Fg0iAAk8iJiQ+0zeZywW\nEwdSLpdlv5DPqb5HJk80qPl8Hq2trRgeHpbGkvvLsbzntrY2cfJUR8jlcpIwabVa4RnTmTEQopNe\nW1uT80bEkAMN+MzVahXLy8sYGBhAsViUe1BLekTQWJVhElyr1WR4RT6fl/fJZIxjRff39zE3Nyco\nicr34j6r1+tScvZ6vVhcXBTUkvQmnlueDTpmNXDjnuUa7OzsIJlMCh9X3W/cn2xAYUm4q6sLDodD\nyvykQBDx5Pcx4VRRRqJ4RBj5vQyM1USMoulcD1aXWlpaEIlEBEVjUM53o+4ZBuIqRWx8fBwXL17E\nb/7mbzaU2Rkgs/qzv78vk3jY7KTX66WaFY1GEYvF0NbWJgEPeY3qfl1fX0c0GhWfoTaucD/TttAe\nMJEhss4zZDabsby8LA2MqmKLWulR91m5XMbOzo6skVqpUcvAasmdARilhU6fPi0jSyuVCsbGxhrk\nsfieKedGRJg8cdpgFS3ne+KZoci9WuJWudX0STzPPLPAPR4n0UBSwagows8B7iVFBHpYCSFCqQJg\n7e3tsFqtDTJuXGsmOaRbbGxsNCQ5tKEcMkSaHPtmGFjzUkv0pNMxyGYlYGlpCZVKBf39/eL3NjY2\npMGKa8u9Rd/Mz7+/UkI/Q99lt9vFVyeTSSQSCZhMJoyNjQkYwViKa8EKHe2caq8/7vWJClI54pJI\nCg8EpyeRmM1NTyO6s7MjPMRKpSJ8VBpPonq8eEAZFJKszAPMUh0zM5abaIir1SrS6TRMJpNM06Cx\nXFtbQ1tbG1ZXV4VfsrOzg2AwKKVaGmkaP0rRMLghwsWSGktTfE42LLW2tkqzhtFoFAe8u7uLTCYD\nq9UqBGdOhAmFQuLgiZDt7e3h0UcflaCDpSCWRG02W8OMd/L+mMkxQOU6rK+vi8zUysqKrDcNgE6n\nw49+9CPpziR/lO93e3sb2WxW5tozaKNUF5MXSoQwYK/XD/iRXq8XoVBIUFi1Q7NWO2jOoCIAgzWi\nCyqXSa/XC9+RP8umjGq1Kiii0WgUFKmvr08MHnCPG6qWGnn/6n0BkN/PIIOGmCV8joplAKKicwz2\nnU6nGFhVM7JareLs2bPQarW4fPkyurq6Gji4wD3uVDKZBACpVPCMseuVvN+lpSVxMj6frwF1Z/DB\nkhdR9+PHj4vTvD8J43ln9r69vS1IIM8SNT5ZctPr9bBYLJKYqTqSKj/u0KFD2NjYEF6W2rRGri2D\nKXLcqHfMRIu6t1RYoL0gutjV1dUwfYfP1tbWJtJvvCc1aKIuInAQ0HR2diKdTguSThSTQQ33D3+e\nSQidKaWLyIenTVEdMJNS7kOi2Xq9XkaCOp3Ohik+/HfuWwY9DJKYHPFvldPJn9VoNKIWwa59cvt4\nFhhgFAoFkSVisskqA9Ub1OCbyZt6/Trkj6gghwAQWGhubsb6+jpu3ryJUqkEq9Uq/87gngmnSsNi\nxYbceD6vGqzybFN27f5mMiJ9HR0dDRURPptaslb9k0qh+P73v49z587JZ6tnn+9H3b88A1Rh0ev1\nIjNG1E8t4avrrO41JiYMjO4Pltj7wf1LW8f75vCVlZUVCey5h7gfeP+0L6yqcT3K5bIkRioPmBUH\ndQ/z39SmKVVZgT6Qdo5Bqcpx55AeqowAB8kQg1RWA7l3eJ/0nbVaDYcPH8bW1pY0W3u9XtEIZ5zC\nvaBWlFXKCs/S/fudduJ+O8jYyeVyCYpPX87nZ+zBfbO5uSl8YVWz++Nen6ggdXBwUDYhDzedpNFo\nxOzsLKLRaEMDUD6fl4yOQR4N2+rqKlKpFNrb2wWJUWF4ZqYsFxFpoYGl3E6xWMRHH32EQ4cO4ezZ\ns6IUMDg4iGg0Ki9sfHxcEN0333xTpg8FAgGUy2WMjo4KPE+dwnQ6jf7+frS2tuLChQuS3bHsr9Fo\nsLKyIhk4S0oWiwXlclmCFq4ZgxMGzDzMDodDjCSREZXLw6CqWCzCYrHAbrcLmvfBBx8I6kBjysCI\nzV88tMViERMTEzIxis0G1WpVgq1KpYJyuYze3l5B3xio1ut1QZ/J+yNNAYBwZYEDhM9oNAoXc35+\nHouLiygWiwiHww3oE1FK4ADt7OjowK1btySpUQ03AwCWAVnmpbNhYEBEhM1l8Xhcxpja7XZp7jKb\nzZLJV6tV4QurTRjkAy79akwqjSIHWNDAWywWcYbFYlGM3O7uroyvZfB0P2+QndFEp4hUqOXPZDKJ\nXC4nZU1ylTnNiA17pN3QedRqNQQCATidTkFg1QCUKBSbG1XZNuBeE086nZb3S8oEuVMk/9N5cIhA\nrXYwLpPfqxpQouetra1YWFhAe3u7cLXUTvFcLifrwfOgNv+wW91kMiGdTss437W1NSnFVyoVHD9+\nXCoXbIRkMklKgVrupwNXER6WI+12u2jQstxbq9VEnodOkAkSnTrXk8mwGtBxvdVgl3uL/85z6HQ6\nJRHiuaDDZvDDc8LghEkC94QKLLBJZWdnB9lsFv/+7/+O1tZW9Pf3i/Nvb2/H3NycvPNisSjBiMVi\nwbFjx2Cz2RoGQjCAY3f7/YES14OVAlak6EP4/bSdFP9n4sCf43rx+TjWmL5KBThIOWBwQZtLwIPr\nSE1bNuqYzWasra1JJzz3qEajkVK4ynXn76Idq9fv8dv5vnj+KVKvUmy4Pi0tLTJIhAHL/RxHBjtM\nKFgFqNVqQtFQfyefm+go/+RyuYbeAd4f9znRe66r+jfRPQaC9fpBc9PU1BS6u7sbBO7vP1v8OcYL\n7MEwGAxIJBLY398XsX0mLdzHTJyY8O3u7uLOnTuiAKDVHugwnz17FocOHRLQQ0X+VQUJrVYrPQqM\nM/h1riOpifcnKkwKfx2lhZcaoPLfuHasuqnUSfXnGRMwDtrZ2cHMzIwACNwLH/f6RAWpV65cgclk\ngsvlkgBnb28PkUgEKysrDdqfKvRNI8rJHGzQ6ezsxNramgSyDCx46Ph7FhcXcf36dTz22GOoVCoi\nU8OMxmAw4Nq1a5icnGy4x3q9jmQyiXQ6jWq1KgL+LI309PRgYGAAGo1GZC/40llmnpycFMUBcj3o\nQHko1N9LJ8yDw9KmWvJpajoYf1apVMR47OzsCNqmotJEffP5vGia8mByfR544AFotVppiiCKxSCC\nuqputxsAcOrUKSSTSSwsLGBkZETKijywr7/+uhwCSliRV0luEptJZmdnxbiT6qHVHkhg6PUHAu4t\nLS3IZDJIJBISNC8uLgrFgo6Lh3pubg4ulws+nw+5XE4CJtUZxeNx6S6nsaDUlt1ul7ITmxl4j8zA\nS6WSBMKhUEiMHuVkVM5etVpFuVxGMpmUMid5SMzaSb1Ip9OCSmq1B8MOuP/8fj/29vakS1uVgVpd\nXcXIyAjK5bKISxPVpRFNp9Mol8tSDeC5Ag6qHKVSCalUCnt7e4Iul0olQdC9Xq9whRlkMzvf3t5G\nJBJBe3s7Ll++LIE7cA9hy+VyiMViACDrxeRFp9M1UFvIuaYsVrVaRW9vr1RI1GaCer2O7373u9Bq\nteju7pamhba2NkQiEeh0OqTTabz99tsIBAJ44oknhE4RDocRi8VE5q23txebm5uYnp5GpVLBE088\nAb1ej3Q6DafTKUEI7RdwgLQT6Qca9Q5Vjh4AScz1ej06OjpEQUJN1BicEfHhPuS55ffodAcDIuL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D6fqtVqkwaupaVF6XTaqs2JLjs6OmyeealU0le/+lUzaEQ9pDnYRNvb29ZLE12Y2/ifHm+k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\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AW14usDn7cte7VCpZUSnt8VxbRcahqanJ2Ff8LmeBvSXgdSU2rA93A3nBycmJ9W4+Pj5W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PYBMVwd3dQ9k1+KX8wzvjnQDWYPc5c4B9+Ek31mIfuig867Szs6O7d+/qS1/60idqnPpUSVDB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\nVmQbrOXW1pZmZ2e1vb2tF154QbVaTQsLCwoEAjaUoFwuq1qtqru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uxWJRExMTphPGTrKP\ntKIKh8Pq6+sze0IwxVkgcPP5fOrs7LQMBT5uYGDAAj4CGCQPPDf1PfgjiCh8Ememvb3d7lixWKzK\nqP5Pr0cKpAaDQf3bv/2bAQ8a5XKB0IEC9JhghOC9t7fX2hD19vZqdXXVjBNggO/nkNXX1+tv//Zv\n9eMf/9iodUnGPBEpEzWiM4IVQ8eCGLm9vV3JZNIu7tHRkUUppK1wnF/96le1sbFhlZ6wL4FAwNhk\njAAdDzhgHGRSLRScuI3BOWzS+QhRij1gKnBCVOASEbM2XATpvJcbhS4I1QcGBmwsnVspTXoSQHh8\nfGws7sTEhH76058aG+Lz+ar0WKSPiJZpnk6QcXR0ZA226cVJ0MH6IifweDyWHk6n0/qzP/sz/fa3\nv9Ubb7xhQvJQKGSVlI2Njdb7Eq2VJPvsPp9PkUhEs7OzBrBxsF5vpdG0OxMdhpDPQqoFoEEaBeBA\nkIShkVQV9WazWTP6yWTSzuDOzo4xYe5YvOPjYxP/w9TC2HV3dyuXy5nzZb3pRsALdiocDmttbc3u\nB5X9SFvYSzRt6Bt7e3s1Njamn/70p/rGN75hII7gx80e8H0wnJz32tpavfDCC1pYWKhKcaFnY6IW\nKXQctFvoAEBgTCkpae7M008/rX/5l3/RF7/4RXm9XrtbTU1Nli6sra1VKBSyLgikhSnwZN0JXgHg\n7DuOH7kCzDMBDueO9eXnwUofHx+brIfzhTP1+/2m13Rb+PHetP0BVEiVYhX0+BQ78jN5f0A9vV8J\ncjkXVMwD+Pr6+ozFIUUJOKRtlNtZAHmVy/CQxr5w4YJGR0ergBQAAXuJTpi1LBQKBnbYazItnDX3\nvBE0ALyxcchjRkZGPkUMACzYm7OzM2PI+dnIXwBogGPuPH4NEobz0NnZaa2xhoeHbR/4hcSLAmMY\nQbe1UmNjo6XACaL53BTy4vNchoz16evrs+4u9PblZ0iyrgiuVMBtT1RbW2t9c/k5BLYUK2Kv3WJb\n2GjpfCAGRAk/Q5IBupqaGg0ODtrakIEFPAK0AK5oQgHcnEWmlI2Njdl7YHvR+bL3FG15PB5j+lkf\n2riRhcS/IhnkfLt+FZa3vb3dgiWelWfEhrHOSCtcYDkwMGAEEdlG9gxCjWl7+CsICsgmqXq4ArYD\nvAHJ91lfjxRIRU+DEactDkaNIptoNGqAb3x8XJKsqp2iCNKXR0dHFs1zENEclctlzc7Oam5uzoxV\nOBw2Q8fkDCLweDxuxQ5cCgwQB+n4+Fj9/f1WAUs7Ey4ZqdSWlhal02n98pe/1GOPPWZpLiIx2BqM\nN0YIp8DhYZ02NzetiIp1IxIlZUiFJRcNQ8+zYqQ9nkq7FNdpuiNAYStg5lx2g2fA6BB1YhwoaBsY\nGDCghcElDcU+8nsikTBGqbW11dhGnCdAsaGhQTs7O5qamrIIEnaa/X7uuee0s7Oju3fvWlUvhpUi\nCjpHAORJZboG2ufz6emnn9bq6qrp8jijLhjlolMVWygUdO3aNc3Ozto+w4agiS6VSgqFQrp9+7Z1\nGeD3mpoajYyMaHFx0XrCktZsaWkx5pOiDlp4dXV1mb6RPrQwcYj4GxsbdXZ2png8bn1VXaaBNbh6\n9apWV1cViURsPTgvGHKpoi2Dndze3tbPf/5z/dVf/ZXdc/SRFMjAEqEdZD05B5Ks8II2YwShgA7u\nLm2tuJ/PPPPMp9qlwZTTL3B4eFj3799XJBKRpCrQVC6XrYCMdeWs48BgJmktlM1mLX3HfcFJE8zw\ns/k31hrAgJNmH5qbmxWPx23fuQMAHbqJuNPkCLx5D+RJBKvcD2wTthgHxl3o6+sztsVlfQnCCJTo\nEBIKhcyBw4S7NonPy7q4zhPAD6hyNaquJEA6H4nM2YMh4xzATEMmcI94NtafveO5JFl7OUmmyXe1\nk6VSyRrsezyVftlIm9gvmE1YRjdF74Jc9hvGDtaR808wx98BLG72hnZzAFMKaVlz1o7/39vbs5Qu\n94v952zhu/h87C+2jcyaS2LwOV0gyC80mBAsZDypPkdmRzYIECedA033bnR1denSpUvG2nKeAYwu\nKUAxHcwmz8z34bc4H6wt7CjZRHAJrccIXgCMZKMAiQB37h5BvCs3oDdxW1ubMbcEN+wZfi+fz2tq\nakrRaNQq7rHBbgtOzgoBswuoy+WyTc/ivQCsbrDG50SeA6HyWV+PFEiFcYnH41aF7YrCYV3Ozs6n\nBGHkEfxTcFEsFi3ycvUz9D0tlyuTrfL5vG7cuGHpNQoRgsGg9SykSXU+n1c8HrdWSTBfGFD0eTQq\nhq3ivWFHKATZ39/X9PS0tccB1HHBiI64BDhe1gPATLPeg4MDvf/+++rr6zPmgZS8O7mC6Budnps+\n5/JhODHQRHYYWfSQsVhMu7u7Wl5e1vj4uEXy7s8FFNPag+pKJBXxeNyKEjAiyCtoc4N+a3d3V+Fw\n2D4760pKk/Qn/4dRZhIVICUajapUKumVV16xCmSMnCQLQNg/mtWTetvf35ff79fIyIixhTh50vUw\n32iN+fvrr7+uL33pSzZal6phgCitm2iFA5CDFS2Xy5qcnFSxWDS9NMVtBDf7+/u25pFIxAzL2dmZ\nstmsgSsYHBq+w14T0OBw3fRZMBjUxMSEOUp+Ll0nMJb0wi2Xy8as/eQnP9EPfvADcxKkmmhGDVMo\nybSSOJnT01MlEgmb5uRmVrhjkmw/wuGwSUxee+01STJ7cHp6appDxtzSlYNCSow2Qzjq6upMtwlL\n49oVKoBpuUaPWRwEAMRlOHAOnDnuHKygqwnnLrW0tGh3d9cawHNv2U+a5ZfLZRtNyT0GIOE4+YUz\nooE4DhYpEkCOKuGRkRHLugA6CLrQ8a+srOjSpUvm3HHIgBXuCD2JkWnAanIv0L7idMkiIR1gMAfZ\nMYq7WC+emTXmnEgVUEpmjMCOzBVrt7e3p93dXSuGgwRgrwFkpNQfljQQ9CId4cXdcaVA2D9XekBq\nn3ODfQNMsc/5fN6KL7nLnFd3DQBFqVTKgpS6usrwEAAgQTWkCWeE+wWLDhsLccAsedZFkoEi7pMr\n/aLdH5pPCJz9/X0DQkiAuHc+n8/67aKPXlhYMOkAe8x94i4g/6EtHC2V+Ax+v9+GWyB1c1+w5Uy+\npNXT/v6+jZ6laAryhaCQ74d5pUUX9xfpxfb2tv2bKyErFos2zYoghIxWMpm0O+qCTJck8fv9dpfA\nJTwzUzbdwQ6upAubRDcTpgd+1tcjBVJJ8bJIpJOpeEU3QgT45JNPGjt0eHhoUSRsFDpVDLgb1eAk\nj4+Ptbq6atOePB6PVcLiPImuR0ZGND8/ryeeeMKE60y1gn2UZO2Q3BfVuZLM2H/44Yf2mdBgkToD\nfGMQaPcBYCEikyq6kqOjI/X29mpmZkaxWEynp6fq6emxiwbAIJVOFwIq4t30I5Gaq/Gi0TIXr1gs\nmjN7/PHH9ctf/tKm9+BAML5MdymVSia+pwoZsTq6J/diEiHSOqWvr8/WEQPEfjL+laieCJJ0C61S\nzs7O9Prrr5vR5BkoZgBEABIKhYJpenmRukmlUqbtIq3kGkcMI86EfQ0EAnr77bc1NjZmz42jkM5l\nBRRI8Fkxyq4zpMMCRgkHjhOgQtxlPDBkPp/PHHJdXZ1VlZN+AwC6Gj+YR7eqmeeGHSENx/PTmQLj\nms/nP1WRzO+JRELlclnt7e1V7Brp8Pb2dusD6WrbXADksif0jnTZFAqRCN4AcThhPi9fDzOCjAQA\nACiTZMWRLvPA/YSFwTkjsUGLC2jgzLojKNGfA6RLpZJVILe3t5tEg+eigOjg4EDRaFRPPfWUfSae\nj8wKTC6M6sHBgTY2NqynMJOGIpGITk9PtbS0pMPDQ5vYRkW8Kx2CcSGAom8qewjji6SI1mQuS7O/\nv6+NjQ3V19erp6dH8/PzmpiYkKQqZhfwz8QvN2NDwAu4wq5xFmDBdnZ2tLu7q+HhYQs+kTsUCgWb\nLDg4OKjZ2VkNDw8rFAqZfwKsAdI6Ozut5+fDgJK1csmS1dVVDf13LQa2niCT7geJREJbW1uKRCJV\nHSFcNpU9HBkZ0dbWlp0pzhpnz2U0CSzdCUp8b21trWKxmFXIc5dptcV9wZ9AwHDeOc8AVjdTwLqg\nlcVmuew6/88Zd9PyDLDAj2ezWUtzo9HEf0HyEHRsb29bT1PqIeiH6/FU2kZubW2Zz8NuuNkKCh1p\ne+Y+E/uBf8YOuFmHVCplwNP1udlsVl6v17pHcFex20hgGE3d1tam9vZ2m4rH+2P/8QdgK4gmdy8g\naPz+ylCgvr4++x58OOcLmQhn/bO+HimQChiDTTo5OTE9GXqmcrlsRVHRaNTajyCKPjg4sAiNQif0\nJxgtt6edJK2vrxvbhCPo7Oy0iIaLduvWLZVKJW1tbdkMXZqHAy5xNABMDjoXigtYX1+v+fl5lctl\nTU9P69lnnzVAAMDgAsKUUQTEAevp6dH6+roWFha0tbWlYDCo69eva21tTYuLi4pGoxoaGrJUEEMB\niNA/+ugjXb9+3YAojEg+n7dIta2tzbSPgCWv16toNKqZmRkdHR1pfn5e4+PjSiQS+vjjj9XT06NQ\nKGTMrzvtJZ1Oa3V1VR9//LFeeuklS7PQRJhUIoC9q6vLHGcwGLRenRg3UhZHR0f2XIjKMX4YAlJf\nRLFcfthHpAv0jJMqoPzo6EiDg4MGxBCOE0lzkQlm3FQ/jgHjReAFKGAiDsDXTS/D3EnnUTgtyGAw\nWlpaqkA5AM1t68I6SOfMs5vGZ404m6StMpmMuru7DSADemkXRfAIwyzJWBtSU9wBF6ThQGC5vF6v\nacxLpZJJS7xerwYHB63XJS3OAIk0hmeKC+vkOgxJtkfsx+bmpjlDdIUExu50OdgLSRYAMXDATaPx\n3i4Lz7oDkglQSZ9y9vg+1ozAEe0X7NTBwYFlEhYWFtTU1GRsey6Xq2IWsT10BYEt4jy499zv91tQ\nxljeZDJpPW9ramq0u7tr/V3dEY8EHthTsiSk38k0uQVRkmwtDg8PdXZ2plgsps3NTfu67e1tS0vm\n83ltbW2ZpAbQ4LLTAGMKUcrlslVIk3ImEGJ/6EnMHVhZWbHe3FKlmwEyFdb17OzMWi9he9An0tOb\nymqauEOYYBP4tb29bW3u6BOdTqdNQnPz5k0L5gkCVlZWTNfKnXMZNgrnVldXrcm9m16G+ebu0Zs2\nGo1qfHxchULB+gyPjIyY/SbAx2ey35A52JKDgwMrksXmsUbYTvaedYO9xMeVy2Wtr6/bHUDTDDFC\nENLY2Gi+vlyu9D+HzECniS0DqLqjxre3ty07d3BwYL2SacXnZlKxXdxZAjDAG3Yd/wFzi99BrsL9\n4HzSS3l0dFSHh4eanZ21fu2MQuXMuuvv1ji0tbWpu7u7KujkbmCPAPW5XM6mbeEHV1dXLaO5vb2t\n1tZWkwwAUt1nwVf9X5vuR7sHO0MKgMKG1dVVzczMqLGxUf39/ZqentbBwYGy2axefvll6wTw4MED\njY6OWqREGgTg5EaB//RP/2TMAk4TQEuEubi4qPn5eeupOj09bYblG9/4htLptILBoN5++20NDAxo\naGjI0gFHR0fm4NxD/utf/9oAy8zMjK5du2YXsKGhwYAifR5dR7y4uChJpjcEgPb19SmRSFibjWQy\nqffff1/j4+NmcDisTK3CuZEi5TMD/KniSyQSVvHI1JxEIqH19XV9+ctftsbpuVxOMzMzSiaT1ngb\njR4FK1tbW5aycSuzm5ubjUWFUb1//74xPKQmMHqwDAcHBwoEAopEIlW6PFLFsCLFYtGcIY7j448/\n1nPPPWfGHFaE6BtmZXh42KJ4QAKOuqamxlImbpsuN+UPYMJwe71eLS4ufmpuNeCGND4gjU4FOD3m\nvcOM4vxcnZPrTDGSd+7c0YsvvqjT01NjC3EUyFCIlLe2ttTf32+szr1799TT06Pu7m4LDLLZbNUk\nMVc/htHO5XL64IMPqphe5B4EB+wJmrSPP/5YjY2NGhoaUkNDg9bX140pGxkZsUpX0m08C58DB/L/\nlL4ic8FaElAATBcXF9XV1aWamhrdu3fPpB0EfJxz9pM0JVkLwAOgDGaMAiU+g/t1OHGvt6Kbv3fv\nng4ODvTee++publZzz77rKUamUA2ODhoch6AF905APqwlNw3UucEC5yLbDZrLOA777yje/fumXaz\nvb1dkrSxsaGOjg41NDTYFKFEIlHV0B3QQpEStQPsAewzQKe9vV23bt3SrVu3qgrNtra2zA5xpo6P\nj+2euUECzCl/JuAiRU/QRaEZ/we4qaur061bt/Tuu+8aGcCoWXp183W1tbVaXV21zhAAPiRKgUBA\ng4OD2tjYMB/m6gMBSzs7O5b5e/DggXWfSSaTyucrY7qZ9jM4OGja5tXVVdXU1BjbDZsLGNzY2NDg\n4KB1nCgWi8ZmE5jwOVOplKanp63ojOAVEPTcc89ZDQSdIthn7r4r53LlAgQG+BX3brrrxoANAvyj\noyN7Rs40kgU3qwhgJU3uZl89Hk+VzpJnCgQC6u/v169+9Svdvn1bwWBQ4XBYHk9l2l48Htfo6Kg6\nOjrsbC0vL6u9vb0qY0DHHoJZgnGGaHCXeSbOulTJuLz33nvW6om2WoeHh/rggw/U09Oj8fHxqnGy\nSB1gvul/C5jl75Bk2COYb+4ho9ORUWYyGW1vbyuXy6m/v1+SLFOUzWbtjIM18ENkdj7r65ECqa4O\niMtBF80nXQAAIABJREFUWv2dd96xEYscRiKUnp4eA6F37twx+n51ddVGNJKeHR4eNuDCZSNVDyXO\naMHd3V3duXPHokmMYWNjo7LZrEZGRhSNRhWJRLS0tKSdnR2VSpXJLMPDw1Z1Sv9PQEShUNBHH31k\nKXRS3xgadKvxeFzt7e020SSVSimTyVh7H4wJVYarq6va3d21RtvMPP744481OjpqDLOrIcN4crln\nZ2cNfAFODg8PbaIQjpjgoKGhQffu3bO+eES5i4uL2tvbU09PT9VEF9IYvCepEZwnrbIODw/15ptv\nqlyu6I2Hh4d19+5dW4crV67YtJlsNmtghgiRCkc3TVoul/XjH//YWLpisajV1VU9+eSTxli6aVGY\ny+npaXV3d9vovdraWpsB39vbK7+/MjqWdA3vW1tbawacvSVFXSqVNDMzY30X3WbWMA7T09MaGRlR\nU1OTlpaWTPtE9Sg9UHEGpDbdghCCEEmWJsLguXO90VOyD3fu3JHH47GRsDCIKysrVYMvXIcDGwhI\nBKT/3d/9XVUxGq1k2H/XiGOYmRJ3//59G8axvb1tumqPx2PFYDgHt8gBJhyZAMYW4PXOO+/oy1/+\nctWdI6h97733dHR0pKefflrd3d2qra21aWRDQ0NW2JHNZu0sSbKfwX5ztpExwRITyPC8BIlkXLxe\nr55++mlNT0/rG9/4hrxer+7fv2/MzlNPPaWRkRHT5yMnwWnDvPL83AH+7qZO0dHBoJRKJevLSzs9\nqQI6pqamDCDC8rhZHwCz1+tVKpWy1GQ+nzfQjGMn5e/xVFoGMjmO2oOBgQGVSqWq0ZEAasC1C7IB\n6PgEzpXLggHMWaPx8XFjYUdHR1Uul7W8vGyAo7m5WePj41Xpe8AT4NkFI64kCCYbJg07m81mFYvF\nrF1ZXV2dfvWrX2ljY8NYPc4kAwB8Pp+WlpY0MjKi+vp6bW5uanV11Xr4YusCgYCuXbtmTDhnHuCN\nbeHP165dU319vcnDIpGIhoaGJJ23XsJ2Im/Bh5DJcQOFcrmimff7Kx0mpHOZ28PsWyAQUDqd1vLy\nsj7++GN1dHTY+PJPPvlEkUhEU1NTFli5QT5AEbBKWz9ageXzlW4Srt2HtCiVSnrmmWesjRv6/HA4\nrHA4bLItN0PDOSsUCpYV5HPACHM+WB9Xf4sPgCm+fv263n77bdXU1Ghzc9MGpTzxxBNqbm62AT7Y\nKnw9vpgMSCaT0dramp555hkLTF22ns9HoLmxsaG5uTlls1lruUg/8u3tbV2+fFmSrO8sWMGtJSFr\n4+q6/6fXIwVSudD5fN6mGC0tLenOnTt22Bk7xkxhogvGKCYSCTU1NSmZTCqTyRhQg1FtbGxUJBKx\ndIKbIsVxMjN5fn6+im1hVCSGgdRLPB7X3bt3FQgEbKQcFHt9fb2CwaCuXr1qM8bdqkEuEIVL6KI+\n+eQTA8rS+UxjDgmVtPTl47Pv7+8rkUiYI+WgYsS5rHQDgLljkgrGzwVbVH/z2ZPJpIaGhsyxkj4h\nEic1e3h4aNq7YrFSyIaujyiXy9DU1GSGZWZmRouLi6qpqbE2Qxg5j8ejyclJpVIpFQoFbW5umhFh\nrCIFEEwbIyBxtUEAN/pYYrwxfJKUyWSUTCZ1enqqGzdumJ5tZWXFUq3FYtGApCv5wKjDApEOdwsn\nYEMlVRk9wN7m5qb+/d//Xb/zO7+j1tZW5XI5ra+vWwq9ra3NWmcRaLm6Mxcg+/1+ayAOawwQdLtW\nwGru7e1VpcOZUV4sFvXgwQNdunTJgL2kKn0o+1VTU6NYLFaliYUtgo1rbm7W5uamBXSnp6c29tJl\n1La2tsxGkOZPpVKmUaeS/+EiGVeHyTpL0srKiskH4vG43alkMqnj42NtbGyoVKr0F1xdXbX0Goaa\nvqLsLSlYl8kj2Ma5oyPmLNOyDcDIv3NWJycnzflcvXrVnoXvY6Ib95R7Lsm03zA9Dw/iYE8ISnDM\nONmBgQG1t7crkUjY+YKBpQMGhW2ka122aO2/J3zF43Fjm7EXyKgkWVrz5Zdf1sLCQhUDBqileTn9\nW9G+YvtdnaurvXSLmEh9Y2PJjBBonJ6eWiHa6uqqpaxh/glODw8PLVPFHeOcMekNaQL7SFU/KXIa\n/ZOGf/7553Xv3j1lMhkLKun7yb3BHjG1CxvE/S4UCrYn0nmhK7IHqsUhB9jnkZERDf33RDn35TKH\ngFw+B9/PCxYPiQef2dWCu2l+ArPHHntMmUxGL7/8svn02tpaPf/88/L5fLaOblYERh2/zvN3dXVp\nZ2fHPocrJcIuUkfh8Xj00ksvWSaQvabgCTkOkiv8FOQHoJygjuI1yAUIA94XsMw6FYuVgRQHBwdK\nJBJKpVKWhSOYZ9/Q6bo+nMCrv79f//Vf/6UXX3zRsql0wEBWxJrn83m9+OKLamtrMzIrFArp2rVr\nVdrVVCplJJ0LsDkv3CV3//+n1yMFUnGKGIZoNKqTkxOb/gO1TTsijB4bKcmMpd/vt2kv6Le8Xq8+\n/vhjXb9+vUq7huPAqJM+pHGvS/EDOtDJogFLJpNW6QqQaW5utk4EkvS5z33OjJkr6Pf5fNbaBQ2q\nJIsicUb8O9S7OzMY3RhVwFtbWxbZ40hcXdba2lpVEQegndSkdC7Edi/mwcGB6aYw3KR9lpeXDSC6\n6UyYBq/Xq7W1tapCHJgeJBPvvvtu1fQdjBeaL0mKx+Oqr69XNBo19gUQlUqlLBXh9Xqt5ygRMJ8N\nZ02RWz5fGXO3vr5uYAHmkcrb9fV10+4RYZL+KJfLNkWFlC7GGAPPLwKTuro6a1lTKBSsyhhxPUb1\nk08+kc/nUzQaNY0V6eDe3l4rMCPT8HDKm0ICtMScYdhRN81PcZ1UqarNZDKqq6sMU3CdD5E0khBa\nrRH0odW8ceNGFYtHNwemJhWLRWP9Dg8Pq/TCGFfOL/pGv9+v27dv23qj052YmFBHR4dV1rpaRQIP\n91xzp+PxuK0f4ANnnslkbA2QYBwfHysajdrgA1gg2jJh8CXZecNOkcIkdYpTAky6hSOsN9kk9/z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wHS9vZ2DQ0NVUlWXC0wf6ajBOt+enpqfpOvI8AisPR4PKZBRmqGjAfGns/e0NBgHUgIopAO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\n1tYqmUzq0qVLxlnL5/P67LPP1NHRYbxV514ASIDPx7nc3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DxuSg6sPcEwZww6wMbGhlUl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\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Pep96AvcZGe8ryTI1vCMXDFKc4mbJGArC3x8dHalQKKivr0+VSsVGLsOu0UcZp815IEPF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uHxjgMmZX9/X/F4XA8ePNCHPvQhff3rX1dXV5cBkMPDQ5MQwAB7vSWsVW9vr+bn521NYPMBG4wn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tWF/fP7/dYE5ESsx8fH7d4zfY6EAjuwsbFhEmkkC/B0/X6/FhYW1NTUpEAgoPb2dtPAxS5y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\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yIZPJwO12izsGS9Rkia1WqyQlu7u7uHfvHp544omWyUPHjh1DJpOB0WiEz+eTPQRASnFc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2t7c1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Hf2hzc1MnTpywbAnFOoWFherq6jJwjSNE9+kWvySTSVVXV2vfvn06cuSIzp07Z9eMPQPY0Y/6\n7NmzOnLkiM01Z92LiopUUVGhBx54wEAaL/SHsGSkRsli3XfffTp69KiGh4dVVlZmgSBMYX5+vsbG\nxuzzKNTjPrAzLS0teuCBByyztLi4aK2RKKgBvJeUlJid8Hq9ampqMnkKwAQZx8bGhu69914D+DB1\n7Pt9+/YpHA7b7+ETefaxWMzmy6ONTafTNklvamrKAke3IAqNazgc1o9+9CM9/vjj5ovQvwOmIZhc\nm012gpT37u6u5ubmdPXqVWPrKQolq8X7YVbPnz+ve++9154zPieTySgej+v1119XNBq1bApaf1eW\ngA9kVO3p06e1sLCgwsJCKywEJ6DtxQYiueIz2TcrKysWkCIDpEiS6+OPx+PRpUuX9NJLL2lhYUHF\nxcVqamqy8bbcO8+OQFCSFSTv7u6a9r+oqEif+MQnJGlPoTF2c3V11ewyAVxlZaW++tWvamJiwuRu\n+DKCMjKK7/X1vgKpREYcrJ6eHsViMdOkSbnFJu2dSCT26HAooKDBsZtuI/pAX7O6umrAbd++fXr7\n7bdN2E11eiqVUnV1tUpLS40Bq6urUyaTUTgc3lMIgjF0W14QwUO/d3R0mN61uLhY8/PzKi0ttQIl\nCq9GRkasRREHgP6sk//VM5Xm9js7OzbffmlpyQ5LMBhUV1eXzdytqqoyg86BYD1pBI9DRJvLjN+F\nhQVzXvv27TMnEgwGLZ0SjUYN7LiibyLMqqoq9fb26vXXX7fDIkkrKys6d+6cWlpa1NzcrLGxMWu3\nBTu+u7trDhrnD1ghIueaWltbDTByz/wbrMrOzo4uXryoUCikpqYmAz08M5hDt/G71+vV6OioRf8e\nj8cYs7q6OmvbAxCm9dDW1pYFHACo1dVV6zqBQyeFwvejs15ZWbFJZrTPYk1hrtkn6XTaWj9ReOiy\ntJKsOriiokKhUMiYXhjpZDKp2tpadXR0aGFhQQUFBYpEInY/kgwMUKiH8URPmE6ntbCwoLvvvlvR\naNSCNK7v6tWr9gzRfVLRj1SitbVVBw4cMH1pd3e3pqamrMVXNBrV8PCwjh49qrq6OkWjUdPHkcYk\nJeVeNywmQdTw8LCCwaBKS0uVSCRs6lk0GtXExIQikYiWl5c1PT0tKQc0Kisr9+iVWX9Sn9gBUtXr\n6+v69a9/rf3790vSnhY+m5ubeuyxx0xXCZuEzjMWi9k4SrThbt9O2FrkK7u7u3t6OXo8Hk1MTNj+\nAJCcOHFCLS0t5lT5PXTGZAIoSmpoaFBjY6OuXLmiUChkQImgn3VGF816Y4OvL6iqqqpSbW2tseIu\nOwOJALvJuURDd/DgQSUSCcViMWPxrmdgU6mU3njjDXV1dZk2GjaO80WnCVevix+i5RU9Qjc2NqzA\nq7+/37TAZLQAHO+8844kmdQFlpfArbi4WJ/+9KcNIHOPFA2hzYQswF4jjSotLbUR2ewVBiTs7Ozo\nu9/9rh566CFVVlZahi8Wi+ntt99WOp1WQ0ODysvLDfi6AAnQRwHv6OioUqmUfv3rX+uP/uiPDNAg\nx2K9SJ9zH9QikMp2pQzus+Ye0HZiqwKBgAYGBnT27FkLHAgKJFn2CWlHNps1kErGFMCJnrm2ttYy\ndmhrKZoF0C8uLlp2s66uTh/72Mc0OzuraDRqoJbiQYAagI/zT4ADM721tWXFnV1dXZZqR7OOTeLz\naPn2wgsvWFEf9+5mQygYe/rpp+X1evV7v/d7ysvLs/68aJg9Ho9mZmZMh+uekaqqKkmyqn/OnNfr\n1cGDB219kES4wSt77r283lcgVZIZ+HQ6rQ996EN6+umnLUUcCoWUyWSMrWxsbDS2DMMiySorYRcB\nBhjB6upqM6ykQHDi9OWjki6VShnVLsnSa6QY0WmgtSKtGA6HTa9YVlamyclJY6g4JFTzDQ8P76lG\nJ0rDqOAQKyoqtLS0pImJCUvL0jKHQouysjINDAyosrLSRvjhIEjruKkOSdbwnVQ3kSOgNRgMKhwO\nG9NM/9iioiKrDiR9jHFADE+qGSN18OBBiyolGVM8MjIiSWYIQqGQjbWVpFAoZKzP8vKytWYKh8Mm\n73CbTuMYXRaONc5kcs333377bRPll5aW2nNHJ5tO50bBdXV1WRssnCpRKBPA+H0MCUCxrq5ODz30\nkH76059aGiYSiSiZTForI5yV1+s1sFJQkBsz297ebv14XXaJyWKsPdot9vmBAwespydnymUsNjc3\nNTc3Z9pbmKmysjIrwOns7FRra6vNNOe63GpggCdgjD02Pj6u3//939eXv/xlffvb39bc3Jxdw8bG\nhoaGhuwZdXZ2qq6uTg0NDSorK1MsFjMdZDAY1MbGhoHdSCRie/q+++7bM42FYhq6JXA+Xd0y2mKY\nMvSvAwMDqqqqsmKbhoYGK97EKcE2k25EsiJpDyh1q8sJFn74wx/qb//2byXJAmUCzLa2NmN+cHg4\ne5hJl8GANUN/3NjYaH16KW6UrmWOpGujR9HPkmIkS8QaYgc4i+w5+gIjDSEwBESgfXUrgAE/gEAq\n3LGpsDHIOHDyrr2VZJ1AuN54PG7sPL9DAZzX67VsBn9getEMwyqRmUDehcafgiiX3QOMI09yu3NQ\nme71enXp0iVVV1crnU7r5Zdf1gMPPGB2lTHTaPwANGVlZQaiYHuRCNAiyC3EIUMAGCIFS+D1/e9/\nX3/8x3+sYDBoWalbbrlFN954oz0bN6vGcJPNzU0jNBoaGlRXV6d4PG6ABRkK8hxYT2RX+ObS0lLr\n/1leXq6Ojg6TpVVXV9uehBmVZPpWwGc4HFZjY6OBLs4RzC7nnBdnBADHvUFmNDU1WVEn94s0BBDG\nGWZPb21tqbm5WX6/3wqasTOc1bNnz2p2dlbd3d3GclLIlM3mxj6fOHHCrovvWllZMdkWGtrS0lKV\nl5crGAzqd37nd4zJZ024Vu6XbjZuUSN+CTlZJpMrymS/EBRBMvC7/D/vYcgGhZG0qCJgorXfe3m9\nr0CqW2VMcQotWebm5pTJ5Kq5g8Gg9Tpz276weLBcy8vLpuFDI1ZdXa0rV67o1ltvtQ2fn59vRuD+\n++/Xt771LQ0ODury5ctaXFxULBazQiBSZrBarnyAgqZwOGw9RrmHG264QR6PxxjebDbXONct3JCu\nNeHGsKdSKYv+w+GwCgsLdeLEiT3tjZaWlmyilhupYehg6kgDEklx/egsKysrDXCgYeQw19fXq6am\nRktLS2ZQNjc398x/xlAi8IZBY+pUVVWVmpqaND8/r3379mlxcdEiSUl2AOh9ub29rZaWFk1NTSkS\niexJu8DukYom5QS7inPlUANYcKwAj1QqpenpaUvBAGJc0Aorcf1oVlLuMKYAI7Ryly5dUnd3t+66\n6y6Vl5fr3LlzGhsb0+5ubrRdOBz+b0AHRgiHX1ZWZmCVSlHkJUxzolqaYoDW1lZ1dHQoGAxqaWlJ\nP/zhDw0gYoSYYkOPXwI4HCAFEGVlZQZieUbRaFQbGxsGSgGoDBXwer06fvy4IpGIjh07pgceeECX\nLl3S6dOn7XnjoGjMPzg4qOrqasXjcdXW1ioUCtmAiN3dXZNUdHV1WXqYoiXYFByLu7/dlK0LdNgT\nDNEIhUImtbh69artXVKbFAQBjiiacQEwTCL2gMI2F7DB/uDo0M/iGN2uJh7PtT6ksEC0hZK0R5uW\nyWQMOLp6Zbeamc8C0MHuA9hhYCQZaKaI1AWyABJsphvUATwBeHl5eRodHVVPT48k2e8DCgCrBFpM\ndSNo4/PYv8h3sEvpdNqCE57tr371K/tu9gXrDqtOYEl1Mz/n+nw+n+0tng86UVLZiUTCvruoqMgY\nemzOz3/+cz344IN2lqkixz55PB6TAASDQVtzr9drQ164HqQ0FIUB6l3mnPQ5fawJqGtqaux66+rq\n7OwAkDgb+EH+3x3hTCEzEiGyePgs7AP7jj1AFszj8ViWDTvsEhr4f9hjae+IX86s+yzcrijBYFCz\ns7MKhUKmywXwuy3UCCaw2xRdsQerqqr2MNN8JwVsBCXszaeeekpVVVXq6OiwwIqhLQRDdHvhegiW\nIDSwu5wv2G+GDSAb4H55EejzomUfDC2svNs/GmaeloUE35L2XBP7I5VKWeaHICabzerHP/6xPvSh\nD+m9vN5XIBWDX1RUpJ6eHouogsGglpeXNTMzY3qaQCBgmxcHIsnYLlJlFBWVl5dbixe3ophoGkYW\no1haWqr6+nrNzc1pe3tbly5dUnNzsxkmnBFsEhtrZ2dHiUTCegniyJi1K8mYCJhAVwDOfbA5l5aW\nbENROY0YXtIe0IsTLCoqsr6NsLduuw82H5sxPz9f0WhUx44d05UrVxSPx+0Aw6jiIGE3+SyMJFNv\nVlZWrOIbTRai7YKCApuJfb3xcUH65uamIpGIWltbtbm5qcbGRmuflEwm93QjQFPqtrvifjEA7sGj\nny0vDu3kf/Vu5WesJy+XeeL5M/JWkqXDSdPm5eVpeXnZCgBvvPFG0z9euXJFfr/fdM0NDQ32XEgT\ncR7cIgFJxhTDoADEYIoolvL7/Vbt/cQTT2hubk6//e1vTT7R0dGhlZUVLS0t6cqVKwoEAtYfkTS2\nx+Oxwh13z6M7BYiRQZBkjv3mm2+2oK2jo0PV1dV67bXX9hTowJCcP39e/f39lnaiXyFngjWHtWbi\ni8t4uQVxGGmuj84S7n7DbuTl5SkcDuvMmTPq6emRz+dTX1+f7SXOFgESbBfPCYBAARvngSCZNB0a\nWUA9MglsD4UvABQ0v7BL7HHADYDbBVcMAaCP5ltvvWVgEu0y4NvtlJBMJi29DdhD2+myZK4kBWmU\nK6kiY0NQDJg4e/asuru7DRCShSFLwjOEAYd4YI1JW+MbOHsAWYAPZ+Sf/umfDHBd31YqmUya7QBo\nEKy7gSxMHesEOANcw3DxjFKplH7wgx+YPrmwsFArKyuKRCK2lu5+wgdwTwAI1w9gv0lJc32uNIOA\nNplM6pe//KVdK59ZUlJiBX1uoOVKYAiM+V2Cb+wIexAGEqabzgWS9kg1nn76aZ06dWqP/eQ586wI\nAtgnyA0Aqa4tB6BTCM378aVkS5955hk99thjeyROFEojo4INhYxwA1ECNncMLeDOlWXg99g7b7/9\ntu69915JsmcFIOY7IEAIqMnSsbb8ncCBrMj13QoImsrKyvT888/btdPmC10sz5h2h6wVtRB0/3AD\nIc4wgJ3uGwBz9n9paal+8Ytf6L2+3lcglQ1z+PBhdXd3q6CgQOFwWE1NTaqvr7eCIETmbsEC6Ugq\nrdELptNpVVdXWwHG9PS07rzzTovg0bAcPnzYIj6AalVVlQmG19bWjM11Gx2T7nQ3IsYS40FVNvcI\nGHaZAVcXhMHgvUtLS1bEVFdXp1gsZsCWyBiNGzpBQAbgm4PM3zF2Pp9PR48e1Q9+8APrSkAqYmho\nSO3t7aqqqlIgELDDhKPD0FG9vr29bS1GSEUiZSACY52IVjkY0rXJLOjuqBQdGBhQZ2enra3bYNwt\njuHg4fABBDDIiMUp/Nra2tLCwoKam5s1PT1tz5rer4zr297eNmkGjM/Ozo5JIEiBUc0u5RzPoUOH\nVFxcrHg8bnv11ltv1fDwsCTZqFScCX1DYS1geABFRLPr6+vWnoVMwebmphYXF3Xrrbcao4xcRMrp\nvD73uc/pS1/6koqKinTLLbfoO9/5jvx+v1W/4sDpMEHHBtK+AMGVlRUrhOEswsIFAgFtb2+rtbVV\nExMTlr52ZSZusQSs9Llz5xQIBNTc3Kzx8XEDQgAzSbaPSYnxuW6qDjYTB5VIJPYEE25gy993d3dV\nUVGhSCSi4uJiY/7RJvO7jDskhcye397Ojc6lMpnAOC8vT6FQSBcuXFA2m9XExITpqiVZwEwfQ2QU\n7rkFIF4fsPAzWCHuP5vNWjXxiy++aPf6wgsv6LHHHjOWCaDPmQEgsi4ABIrAYPlhX2CrOYsU6ZB+\ndIHVxsaGLl++rJaWlj1gkkAQNhn7RxBOQAMLzD0DfqlH4P5pko9doxgIO4+zdzMKOGi+G1sBaGBo\nh6vxppoaILC7u6tEIqELFy5YG7RsNquvfOUr+vWvf62HH37YbKUkk16xxwk4KcSVZP7B1dqSckWH\nyzQxMhvz8/Pyer1qb283vTMBL/eHHSJAIQgB9KZSuZGt2BxApJuFS6fTth7YbldG8PLLL+uRRx6x\n9Xb1qS44Yj0Bx4WFhbZvYILLysoMgAEkWUuyeewnV36HLInAhHXAb/Bv/Bx7S9Ea+58zga8muMzP\nz9f3vvc9lZaWqq6uzp6dyyizZgSZPL+8vGstNnkukFKce84RWmTOP4Eeemqe2fLysuEnt4Ucgau7\n3i7ZQBDAnnBtInuCAJVgIZFI7JFa/J9e7yuQyua98cYbTb/DzysrK/cI0HHSLDhaEteQe71eVVVV\nGd2dyWSsmbqrQ83Ly9ONN95o7zt69KgBHTRvMA7ZbNYmk9DTk8hakrEuFG8QYUr6b3+HCcBYw6i4\nqVm+z+/3q6SkxCo+MRwAVCJTmCxStq6GxGVTd3ZyjbUPHz68x4AizAeAXb582dhPClMAZhwqngXa\nWK/Xq5KSEkUiEZ04cWKPE9zY2FBjY6MBRfdFVJmXl5uiQyVuNps1BoveqYBb9giG0A0QuE+X4UTb\niBZseHhYfX19Bv6p1uWam5qarPLeZbIAvJlMxgDq0tKSSS5KSkp02223mQPGeEajUdtPfr9f0WhU\niUTCuifA7tTV1amqqsoMDiL9vLxc83G0z2i/CgsLFYvFNDAwYCwkTi6VSqmhocFS37fccou8Xq+u\nXr2qxsZGVVdXW+ub5eVlS92TEoUtAbCQrVhZWVE8Hjftc2Njo6qqqhSJRDQ+Pm7Zjng8bsMXMJau\n9joajWpkZESHDh1SbW2t+vv77Wyyl9BkUvSBYXeZCwqPABE8b9ce4HDYN5LU3Nxs8pOJiQkLoCgu\nwGHjVACCm5ubWl5e1tLSkgULjAcGsCNPSSaTGh8ft96wrANdQNB5A07ISnAeCJw5+2gIKXZDmkLQ\n/MYbb+xJD05PT2t2dlZNTU22FgTQBNc4SNYeEMX3uan13d1dK5Di/Zy5VCplzx7H+corr+jDH/6w\nPVN3/ekHCjvstjpijVyNMWAGMApQ2d3dtXoFbKqb3gX04uhJa3ON2BFem5ubprWFHXXPP+x1JpPR\n//pf/2uPhpmC31deeUUf/OAHzS/RtiudTlvlOvp1JgPhR+gkAVBygy9qEZC0udMM8U8U5PKZ2H4Y\ncAAZz4s+mwQMtD6iXy+EEFklWEHsK99RV1enX/3qV9ZpQJL5abeNotuaD7KI64XhZT3danL2KoRU\nfX39HqYZHOEWGWEj8dXYIlfuQKCHveA84Zcl7elIMDIyYp1NfvzjH+vTn/60nSW+e3Nz09rA4T8J\noGDSOWeBQMCIFQqZqHOAzSSAevLJJ+2ZSNKPfvQjffaznzW7OD09rUAgYAwo9+FO1eJMcwbdug2f\nz2edG3i5gzRgq9/L630FUouLi1VbW2tj4dLptO655x7Nzs5aLy/YGDYNwFWSbTBe7oF3v4NUC4cs\nPz83ZxqjdvDgQf3d3/2dbr75ZqP92Rxuz08+F4DkGmUOItcaCoWsuS+bk/SFy+xIe1OR3Bdp1WAw\naC0pMJrMSnd1hehwaXSeTCbN2MIgoFepra3VsWPHLB1AnzcYjdnZWXm9XtNPudXtfKYk29ykiObn\n53XixAnT0wGs3Yk8rrMCRGBoFhcXTTfZ2NhoTY5d54NDd1OfsHw7OzsGJmDUioqK1NraqsXFRWMh\niKBx8CsrKwYWp6amVFBQYClwom+cABowNL2VlZXWwgw2eW1tzQoKNjY2tLi4qM7OTmP5MUwEQYBi\nmGKMAhE+TgnmGgnGkSNHFA6H1dfXZ1E08gB0VfTapFUbz5T0LeklgDDPyuPxmHOFLQRo19TU2L5M\nJpPav3+/pW1xTG5Rg8uQ4SBmZmYUDAYtrU2BC9E+PStdoAlQcWUmrAtSH/oEu2cLxyjlDO/nP/95\nZbO5Yosf/vCHCgaDKi8vt8bYsC+AI9Y2FotZg/b19XUrXKSzBJKilZUVfelLX9LPf/5za/2Fk2VE\nIqzF7u6uFVy6lcIE6kgX3EwI+4eCDPpMumnPkpISPfnkk/rSl75k90+KD1aF8wNw8Xq9FowApt0A\nmvPOuQJ8u32FeRUWFmphYUFNTU3Wy9V9DyDQ7SiAZhm2D/tOGh6mCQ08o3y5FgAUYCcSiZj20wUz\n7DHsJ+tCVsXv91uWAXnB1lau8fvS0pLZLPZUYWGhPvWpT2loaEjV1dVqa2vT888/b4AX38Y+dUkE\nF6gDTFwNNzYNeUk8HldDQ4OmpqbMBhcUFOgLX/iCvva1r1lgi64QcIQtIHgmYwO4Q5dPECjJiJCi\noiLzDQBfNxuWl5en1157TQMDA9YmkuchyUAckjX+H0YP0oXUNfddVFSk5eXlPR1WXJ1vfn6+Lly4\noM7OTiuuZE9TJ0DAj3/Gd3JOCGDYWwTmFCJh71966aX/Fgy5nT04z5wfQDbrxJqAEVzfxnlnLQnQ\nOBuBQEDvvPOOZQ08nlwR4IULF6yne0FBbjoath87DEiFtIMUY/1ZC7JGdMSYnp7eo3X/v3m9r0Dq\n448/LumakcxkMtq3b5/Onj2rtrY2S8u4ujJ+RoQraQ/A432SzNGSTgYMYnik3IFBR8gDxKny+QAY\nNi+HjzQ+n+myRn6/X2+88YbuvvtuO/wFBQU2e5nr4174jPX1dX3yk59UX1+f/vqv/9oE3KQIXW0m\nDm1ubs5YQXSyXCdGhlTeDTfcIK83NzDhe9/7nk6cOGGghypWDrLbaJp0hCSLHt2WODTcvt5Z4VTd\n9eeZue9JJpN6+OGHVVNTo2effVZSTn4Bu4jehzQfThvHgnaXStTi4mLV19fbNd5///0GKN99913r\ngUq0yB6MRqP2PHCkrJ3bcgngj6ErLi7WzMyMAoGAabsw2ENDQ3r44YdVVlam6upqk6bgfEjp4/x4\ndm5w5PF4LNVE2xSag7tO4erVqzp48KCdiXvuuUf79+9XZWWl/v3f/12PP/64Dh8+rMrKSgtscIAw\nkmQNCAwBnBTxuG14MI4AgGw2148UfRPP2g3oMLwdHR0aGRnRvn37DAChf3NT4awJgGxxcdGKydAu\nMzLVLSRkDW655RYNDg4qHo9bMEBVfGtrq5599lnt37/fil1gsdxWU5FIxFjTsrIyNTY2GijFEWI3\n3nzzTf3lX/6l6ULPnj1rQIGuHGSIAK+xWMwAWSaT6/VIlw83NV5cXGyjOqPRqMrLy/Xb3/7WgimX\nFfL5fPr617+u++67Tz09PXtsG0EdGQ9YVVi3SCRizJsLSK5nmNCtk+ZEw5bNZrW4uGiMusv88UyL\ni4st8MPpu8BBkgUrkqyRfyAQsPHIOzu5UcD33XefnnrqKRs7zaCSaDRqFdCAAfYkGmn+zj0EAgE7\n+7BQ+fm5tlz9/f366U9/KumadGl3d1ePP/64vvjFL2p0dNSGxCwsLFiGgg402PK1tbU9KVxsDAEb\nbDoMF2Covb1d5eXl+tM//VM98sgj5j/q6+v105/+VJ/4xCfs3OCf3EyfW2iDnIqMTiaTsQwm3w8p\nAnkTj8e1u7urxsZGWxdsw5NPPim/36/PfOYze6QrtBJzg83rWyxJuXZv+FNssMugNjY2GnEg5UAm\nbenW1tasrRU4ATsNmwlIZB8y8pl1QApCsEYgf/z4cb3zzjsaGBjQ0NCQyUG4N0kGpAHbSIGQg7jk\nCoE26+PaWmwd1wBzTjbY3b/nz5/X4cOHNTMzY/UEjJXl8woLCxWPxw18IyFw15ACajAI/cp7e3tV\nVlamSCRi4Pq9vPJc5/7/+usDH/jAqs/nK7/tttuMfauoqLA5vfTbJBJwwSqLzN+la8AHJw8LymSP\nZ599VlevXrWWLL/7u79ro9+IYF0jTFqG/7oOAGAAcGVzSzIji/FlYz733HNaXFxUXl6eDhw4oObm\nZuuBFwwGjXGQZMBZkm1m7tONJDmIOBnu3+vN9cfEMT///POamJiw6TtPPPHEnkICGCsAE3pLUvKA\njLy8PDuYrAWGg2vCuCSTST311FMWoXq9Xj388MO6/fbbTaeD0cCAontETuDqc2CAABHStbY5GGsO\n4e7uri5evKjTp08rPz9fN9xwgyYmJvRXf/VX5ux5v1ucAAOLEXcF5ltbW8ZAUczFXiToIRodGRnR\nSy+9pOLiYqu+P3DggO0TNLg8z8LCQnPu3C8g1d3jrDNrALj0eHL98dbX1/Uv//Ivqq6uNobh1Vdf\n1RNPPGEpL7f4BSYPZtLtuenucbRlZAVIw7LvdnZ2FIlE9Ktf/WqP3vree+81TSkyBNeg0+ZJku1j\nDLG7p9z9D6NDhiQej2tpaUmpVEpf+9rXrAfw2tqa7r//fisI9Pl81lyeDAIV365O0Q2Ccdju3uL5\nMN1maWlJzz77rPx+vxoaGvSTn/zE9sQNN9yg++67T7W1taaTdwNN1+m4wd31f2fN2R/YJxwiwwD+\n4R/+QQcPHtRHPvIRGwhBexzpWh9dVxoAw+ICF76fNDxBAvtkdXVV4XBYIyMjunDhgoG1np4effrT\nn7YG6gS0sER8B/fI916fZWHN2aMUqFKwSYAyMjKi0dFR5eXl6ejRo3rwwQdVUVFhGnP2O9/vSj9c\nx+teG98LcUJAmUgktL29rZmZGS0uLuqll14yZrmrq0uf/OQnrRE+gZarW3SfNS98hJtiZm/T0YM2\nXltbWwqHw5qYmNCZM2fMFhcWFur222/X7bffroaGBusU4BInrv+8/uXaGPYYa0jsk5cAACAASURB\nVIBOHZZ7cXFRiURCr732mpaXl3Xrrbfq5MmTNpWQ583nIXtwQae7v9xr4lnjL6knYK9tbGzoN7/5\njcmJBgYGdPz4ccsO0SmC9eY63Pt09dGuTeWsY0/JgK2urhqTevny5T11LYWFhfrgBz+oY8eOKRQK\nWVCDDXHt2PXX4l4TayPJADx2hsB8fX1d4XBY//zP/6z29nY99thjlsGBEce34Dvc7+B7wBLcL2eb\nLClZGjqVxGIxnTlzRlNTU5qYmPifN9B1r//5Tv8ffUWjUYvoSR25hsTVhrksKsbddSo8GP5I1wwy\nTq2mpkahUEhXr161pvc4YzY2rCMzb+lPyXsBRzCPkiyNDvOCcXQjs8LCwv9N3pvHxnleV+NnZjgk\nh+RwOPsMZzgc7qQoUZZEW5alyLHk2HGzuGmbvU3jJkgdOCjSNkCTAC2Soi36AQWKIEHQdEnS1nGN\nFHWaOqlrO27iWAu1WNRCiuLOGXL2nbOSs31/sOfqoZof6v73g78BBCUyOfPO+z7Pfe4995xzcfbs\nWRFZJBIJWYhqNU1lPaF+vu4N4FyM/JsqPX5WvX7XX89isWB9fV2Sq8nJyX2oiqowJZJFBENF9Jiw\n8vu1tbWJgwLfhxuA1IaPfexj4rU6NjYmI1T5PUlYJx2Dfq/k/qpBk3w6Fgm0JSOKxbYReWrHjx8X\n3mC5XEZ/fz/a2toEqeBB3dLSIlxMiogA7Pt8BiedTidtfTU4qER1WpDFYjFUKhXx4uQ6ZGHAa1YP\ncRVVURF9NfCpf9i6UZOOlpYWLC0tIZvN4sUXX4Tdbt/3vkSF+fkUuqloIHDXhJ7PhxZn6sGr0WiE\nF+3z+QQl7u3tFRqGKhziM1IpIExE1c/mfub/V/c5r4nXQCrL7u7uvpaY1WrdV+AxMVbvGX9fDe5M\nlNWESkVm1SKB6217extbW1siimPCwRjB78RnxOfH7/aLKEDqn3s7R2rMU6+pra1Npvyohc6991ZN\nGtXXvfQMlcOp2pPxnrFzwKKFyaHaAVPjl3rd/Dw1YVET93t/n2b7Km+up6cHLS0tYjiv3i8+A96D\ne++pet7wd/k79547TLZ4z4iMM6ZarVaJT/eeY3ypa5gJk9plUK+pra0NNptN7Bf5Pq2trejt7YXJ\nZJL13Gw2pRjhWlfXBveW+j1/0d9cl+ozYpzn9fI73BuL1QSc18CfVYV/6nO5d1+o94vrnd1Dvh+L\nTIIz6ppVC9lf9N3UNa/eJzV28jkBkIKcIBK7JioVpLe3d5/YU92b/Ew1Ybx3Tdy7h9XXvVxxxgzV\nheLe9c2/1fdUCzC1k8nny3yHxZ0ai7u7u2UE9lt9va2S1Hw+L1wlIjZsWfHQZFXBhA64G0zUDagG\nBh68qp9mS8ueMj4ej4uvHFvDbA2oLR9atJjNZhiNRkFC2Dqi9xlbntxI5CIykDMJA7BvFjsnNlG5\nyQ2tEs0pBiG6eu9m/kWVoprocHIF1c68v+TJ3csb5L3nuFObzQaz2Swtdr4nEzS2o3hI8D3VjaQi\nkQwwvHb1nvN3aKdltVplNKSK4lmt1n1K/7a2NuHsqhU7NzST7Y2NDQwMDOyrslW0lO/P78zWMdt+\nVP/y3jLJ4vPmIcaCRa/XY3JyUgqOdDotSAFbxmrSqypq1aSV16r+m3qIMMHWaDRCK2HyFIlEZJoT\nDxKuLSYZ5N729PTAbDbL/Hpyllj48Dup3/ne5JnflVzyarWKcDgse5iFCQtQrg3ufbUoUxOM/6+E\nhwkzv1uj0YDdbpe2HxEI+ofyGrnOiN6ryf+9SZJaSDCm8DOZ7JP/qNVqxQSc64n3kocovz/tfVTk\nXN3HagJzr5CG94fxgIgIkRJVXKkiNfcmvSpipiL0KuLE5FO9Nu5zFo5sRfJ1LxKuInXcdyp6q34n\n9ffUg1G9j2rMZyzgXlZbp2rioNFo9sUb3i81KeL/5vdnUdls3uVZq0UGFdDkNKqFm6pAV4sf9Y+q\nYVDj+b0JF72TaQem1e7RifgsyR3l92QrXf18NTnhd1L3kvrd1e+gxiDeY4IM/Dl+rtpB4dr5RUWQ\nutZVtFwV6KrdDPU9iFAzZ1Dvo/ps1UJAXfNqDL13HapJNM8E0m/Us5JDJVRwgvFBo9HIPr1336n7\nS70fKpKqPg/yzlXkGYDsA56hajdS/Rz1HqjFgboe7u1IM26x0AQghedbfb2tklRaTbCdwUOThygP\nUgpc+HPqQ1UDvfo3k0Py3KiaJC9ka2tLTHhbWlqkbc/2juq7yU3AxJFJC8eS8t+JCHPhMPg3Go19\nI+Z4SAHA9va2JLTcDKzSeACRcqAuSLZZ6ZGotgs0mru+bWzTMNFcXl6WjUX0iciTGqhoOUEPOXrP\nqveXBwUTNvJ7+J25sR9++GHodDokEgm5Ft5zJiYq9xWAIH2891wLnI3daDRk/ahCLt4btp04Clcl\n3JOHp/7hc+P/V4MA27QU/fDfudlVJJoHV7PZxPDwMJrNvRnykUhEUD21a8Ckh8GQdAs14Nx7EPAa\ngb3DkkUDJ6tRCHfz5k0Z+cl7yO/KFwM+Ez5OQVHFhjwM1CDLgMw9x6Szr69PihK9fs9STq/Xi7k1\nOxFE2pmosq3IJIPfj2uJyTf/jXuOv8N7wOeWy+WQTCalOKhUKtKOJLeWLXNy3u49PPhe9x4gqvKe\n921wcBD1eh2zs7Nyb+jPTGse9fDm3/xeaoxR1zF/hhzQew8bfs69ohYecCo6x3iiJkr3JqZqIsz3\npaiL18U9AEDWPg81NTbzfdVODN+fhy//qIkl2/vkRvO73IsIM8bwd/n+FCSqz5LrhdQU9bur3ZpG\noyGxn59DwRr3r9oFoYiXSTSvS0WK1USDf9Qi496f4/flvaKegZ/P/cPknOcHY6Z6j1Rwh8W7uq7V\nJIX7imtEjRHqfVLfT+WX8t/4N69ddV5R45fqUEGPYxZv3DPq2q3X65KMqzzNe7mm6s+rMZ6fzWvj\nnud1cr2pZ4DasVLFX+qz4NpgR0Hdi+q9vPfz1Z/ltQLYt7dIv1LPU177vSCGWqSpe+YXxRNShlSR\n+L2IrQr4qIXF//R6Wwmn1DF33ITxeFymRWk0GkGZSFZmO4uoIA9dqiVp1s9pJtvb2/vQQKJ25XIZ\n6+vruP/++4XQfvPmTZkYBUA4mWpbWK/fG0/W09OD69evi88oP5sVHgMIx99xMWi1WnEc2N7ehsPh\nwO7uLoLB4D60hAvV5XIB2FuIHo9HELdisYh6fc/WJBKJyIFYLBZFVepyudDR0YFoNCo8SJvNJm1c\nJomrq6vCp2EgJw+LSQ8AsVDZ3NyERrPn20eyu1Z713OQVlJsybA1lUwmkUwmMTo6Kj9748YNsRqi\noESv3zOSrlb3PPwajT3/w52dHSFxJxIJdHR0yNhalVfo9XrlnnV2dsqwAaopmZjQ05XXz0KGYgWu\nz1gsBo1Gg3A4LOrtlpYWuS8q2soRiGz781lSfEMxWLlcFtstojFcmyaTSVT8DBaNRkNUzfF4XOgn\ntVoNRqMRyWRS+Em01TIajQiFQoJM8KDZ3d1FIpGQg5ZBn4p1Fi7cJ0wguWdVpLVWq8Hj8UgSzQLk\nzp07gqwyuU+n0wiHw7JWWLXr9Xr4/X5RdnNP8Lp4zZubm0in01JA0TliZ2cHVqt1X4LLsbahUAhO\npxONRkP8BmltxvjRbDZlqhDXAv8N2I8mMmiTo87iwmQySWE4MTGB+fl5AJBxhOwYMS6wIOPvEw2+\nF/ECIAejWiCq6A+RPOAuRYXPkD/DQ5UHGHAXLVOTZ/WAJwKt0dzl4qrPlL/f3t6OVColVAAVSVTf\nVxWdqp+tfld+NzX5UxNDFohqi5N7VvUb5t7gzzMBoI2XmrCpCSO/J3mHFNAw6aAYiQkWbZpUFb/6\n4p7j9aiIF/83i2omH7xPFM/wpSKLLH54TlLYRKT+FyXhvL9MOLieCLQwSVbX370JCoEbdgl4XXwm\n6u+ra1BNpNRCi4mfmhARkOEzIRDCMb/1+p4w2WKxSMdGjW8qWMUkVu06qgkm8w9eL5NRnmMqV139\nThxCwrOC64LfjfZO7LDx+ajrV9WQqCi0WkwaDAYkEglBbVmMqM9H3SP3vlQUX33e/B6MDVyL6p7l\n8+EQgrf6elslqY3GXR+vRqOBO3fuwGazifUEvShpRzE8PIyenh5BeVRbkNXVVYTDYVSrVZm4weRI\nrQwIWxsMBvG9XF9fRyKREBSVoyOBu/YLRqNx38HANnw8Hhc1HA9Ng8Eggq9MJgOr1QqXy4VKpYKe\nnh5EIhFJIiqVClZWVtDV1SWjYfV6Pa5duyazfv1+P9xuNzQajfj1GY1GbG5uYm1tTUQ3NptNvnO5\nXMbCwgIKhQIcDod8Hq2Ums0m0uk0AoGAWCQtLy+js7NTEsCNjQ309PQgk8mI6r+zsxNLS0uwWq1Y\nWlqSytdgMMiUL71eD7vdDq/XK/w/JrNMMoPBIMLhMIrFokxgikQisFgsuH37NnZ3d2GxWJBKpSSI\nlEolbGxswGw2IxAIiIE6AFHT045mZGQE9XpdFNXq887lclhcXBS0MxQKiViqpaUFc3Nz+0ycScmI\nRCIwGo1YW1sTdJI8TavVCp1ubwby4OCgqEnVYQk8zJaWlkSNTtFPKpVCpVJBpVLByMiIJDoTExNI\nJpNobW1FIpFALBZDMBiEXq+XMby85/QEJrKp1Wpht9sFYeFaC4fDYpVCtXxPTw/6+/uFIkPutFar\nlYRvZWXlv9EymLSPjY2h2WzKdBNVBAhA9nF3dzdaW1vlucbjceTzeVgsFgwPD8thDewheZ2dnYhE\nIojH4wiFQiiVShgdHUV3dzcGBwfFEm1+fl46A11dXUJ1YLKp0+mwsLAgiXm9XsfGxgbq9Tp6e3vh\n9XplH/CAyGQyKJVKCAaDmJ2dhcPhkMKPxQ09Eev1uoyJJbKaSqVgNBqRy+UQi8XgcrlgsViE3kCE\nhoJRlTZRrVYloY7FYsLf5X7i8yXfWavVioKeSRhRRvUwVNE54C4SyiSScZIHNdd/Op3ex4Nj7M3l\ncrBarQiFQtBqtcLn5mGsHsz3ouRMHPjduJdVJTifr9rtYYHE2M5io7+/X4prrm1eD0cI8yzo7u4W\nhw9SIzjlsFKpYH19fZ/IjYIYcqzJcWccIDeXSaPaCWAywMJPbTnznnPNqYi6as/F5IVr12g0SnJe\nq9WEF87kiOuE78vPZLJDtF2rvTtLngiiWoQyYeJ1cHogO1O9vb3Qavd0HXTOYFKfz+fl/biuSBlS\nkVqOEmYHUEX0eX10J2AhcuzYMSn2u7q6xKVle3sbJpNJfq9YLApgwL2h8ssBiHsMu6EszvgMeJ7y\nGk0mE6rVKiYmJlAsFnH9+nV4PB4577ku9Xq9DMZR+crMMbivCATxGbEgzuVyInpU7yMpWSxO+X1U\nBJ7rQv2+ajeOa7PZbIq/Ou+PWojQSYT83LfyelslqURPdTod0uk0gD300ufzweFwiHfjjRs3hEdZ\nq9WQSqWg0+nkECO/1Ol0YmBgAAMDA6IGTafTou4HIGjRxsYGJiYmAACvvvoqHn74YdjtdhQKBbhc\nLhQKBUSjUUEsk8kkbt++jVOnTkkg4WeyOu/v74fVaoXb7ZZgsb29jdXVVbhcrv/GTzIYDNjY2BC/\nTafTie7ublQqFRw5cgQ3b97Eu971LrS1teHWrVvSIi2VStjc3JQWKu2dpqenJVkmmnTp0iU0m03x\n9ezs7EQymYRWq8X3v/99HD16FMePH5dAlUgkMDk5ifPnz4vlSDQaxcGDB2XD+nw+tLS0wGq1CpJm\ns9nE97C1tRULCwvC8QT2gi5bs+VyGW+88QaOHj2KkZERabeqk2e4cfL5PMbGxoRbyCA4PDyMO3fu\nYHx8HC6XS9rx7e3tWFtbw/r6OgYGBuSQtVgsyGQy8r0ffPBBDA4Oin2RTqeDy+XC66+/LuT427dv\n4/Tp00LxaGvbG/awurqKlpYW9Pf3w2Kx7Ks02d72+/1yoAKQ+1IsFpFIJMSX0+FwYGJiAs1mExcu\nXMDZs2dx9epVLC4uitckCwEVxX3/+98v6KpGs6fyvXXrFpaXl9FsNuWzent7MT8/L4fk7OysKHE7\nOjpk7fFgbjQawsPO5/MA9g4RVvmdnZ1wu93o6+sT4UY0GkUwGERvb68gewyA9DmkT63RaITb7ZYC\nJhaLYW5uDocOHZLDLpPJCJpP5B4Aent70d7ejiNHjghaQe4pLWHoL0zUnEgInSJ8Ph9GR0eRSCRg\nMBhw/fp1SSSIPDOBpBMHk52xsTGMj4+jra1NhFKzs7Pwer2yxni4t7a24tixY9BqtQiFQujs7EQg\nEMDm5iYSicS+Q5wFS19fH3w+HwwGA2KxGJaWlhCPx5FMJgWl5X6zWCzS/kskEhJPm80mxsbGpNtC\nNTyTCFo0AZCuDifX8SCPRqOIRCKiaFcPQqvVKtdBRbDX68XNmzdhsVgwPj4ubVuOeWRyE4vFZG2S\nS83ilYdgJpOR0dGM2UzCyT8lz56Hbl9fH/R6PRwOhxRT3d3d2N3dRTQaRalUkmRA1T5wLXAtJhIJ\nbG5uymATcl7ZOmdRwW6A3+/HjRs30NnZienpaXEd4PPgtCeOamXsamm5q0Rvb2+X9jZ9LoG7vEN+\nfxaOvH5V9EthUywWw+bmJux2u4AVtB9iYkrwhALSavWu7R7V6yyWeN/1er1oKBjLqdHo6+vbt04I\nKMViMSnOWTB1d3fDYrHAbrfDarVCr9djeXkZW1tbInBlp1Cn08HhcEgRkU6n0Wg0RFQ7PDwMnU6H\nVCol+8NisSCbzYpdHL8XXTCcTif6+/vh8XhkHQeDQayvr8uQDr7a29vhdDpRrVb3TYir1+sy7ObY\nsWOIx+Ow2WzI5XLI5/Oijue+0+l08Pl8GB8fx+DgoDzHzc1N0cdwrbW2tsLlcgnotLOzI922RqMh\nDkQ8ryORCKLRqOQNzHeI3mq1WuEyM1FXry2TyQjCywKU3GvuPRZYR44cect53dsqSaXpLdGHcrmM\nvr4+VCoVbG1tSVDx+/0YGRmBRqPBiy++CIfDgePHj6OzsxMXLlxAJpMR9V00GsX09LS0nxqNPTHF\nt7/9bUne9Ho9yuUyAoEAfvCDH+DIkSM4dOgQCoUCQqGQ2GzQHy6dTqOvrw+dnZ148MEHBeW9evUq\nGo0GrFYruru7USwWsb29LRVfX18fBgcHMTw8jH//93/Hu971LhiNRiwvL0vgIN/T5/PJQmeS5na7\nZUxcKBSS5MJisSCRSODy5cvo7u5GrVbD+vo6/uVf/gU7OzvweDyyyAOBANra2kS5Hg6HYTAY8Hd/\n93fY3d3FQw89hGKxiNnZWTk819fXZdKI2+1GrVbDfffdh/X1dRSLRdy8eVPGafb394tJdb1eh9/v\nh9/vx9TUFK5evQqdTieHdzweR1tbG15++WUcPHgQ9913n1hrRCIRaDQaxONxEQIMDQ0Jary1tYXW\n1lasr68LKjwwMIByuSzDB5gsezweXLhwQT6PQdZms+Hf/u3fkEqlxAj/Rz/6kQQTBt9GowGLxYIH\nH3wQo6Oj0u6/fPmymGl7vV4RwKXTafh8PoyNjeHIkSOYmZmRpLRSqchkqkajsS/gLS8vIxqNStJQ\nq9WwubkpB1axWMTZs2fR0tKCixcvYmVlRZSYr732GorFovimAoDb7cb3v/99nDx5EufPn983/aha\nreI73/kO3ve+96Gvr0+SH1b+wB4q3NfXhzfeeAOf/vSnxX+PCZ3f7xc6DEf+OZ1OTE1N4fLly0gk\nEnKo7+zsIBwOo1AoCG+W73Xr1i0xv6Zt09DQEHQ6HV544QWYTCacOnUKWq0WV69elUQOAFZXV9He\n3o5AICCo/uHDhzE1NSU2a/TtrNX2Jmp1dHTg4sWLOHv2LDQaDQKBAFpaWuB2u+F0OjE8PIzd3V28\n9NJLGB0dhdPpxObmpvCwx8fHodFocPjwYXR3d8u4ZFqobW9vC2rDWMb7xfGJHNLAFmK5XBaUHQAi\nkQicTqckD6Qk0FifLU/+jNrubm9vRzweh91ux+joKKxWq/CgDQaDILxcBypHT6vd8zseHx8Xm7B4\nPC6CNyJatAojgsokhqMse3t7MTExAYfDgXg8LkhsIpFApVKRhFZF13U6HWw2G0ZGRsTzNBAICNLP\nhJ/cZSZMpOGUSiWYTCYZId3Z2YlYLCaxSavVil1etVpFZ2enJGakjJDiobpF2Gw2OSdY9JFzS1V/\nOp2Gy+WCwWDA4OCgdJz4+fF4XJJzdfgIE87e3l5Jkmu1Pbu8aDQq/F+irPSh1en2RKAsnIxGo6D1\n09PTgvaxE0Z/2Gq1Kv6+Go0GZrMZ/f39GB0dFcrA8vIywuEw0um0tLw7Ojr2uawYDAYpYumeMjEx\nAZPJJC4mRHLZFeJ9YyeMlCu73S7vS84zPxcAPB6PCBuJdhoMBoRCIXR1dWFsbExoDbQqtFqt4krD\nzhGnjun1erhcLuE5k16Wz+eRz+f3aSXoksAOB7CXsObzeSmkGF+MRqMUx6SJLC0toaOjA319fbLm\nI5EIpqenJQFkYUgxablcljyjXC7LVCvu80wmI7ZifO9YLCYg1fLyshSNpPqwC8LhPcPDwzKieXFx\nUawpVcScFCjeg2QyKc+QtMO38tJ95Stf+V+mgv//fT377LNfKhaLbT09PYLMbG5u4vz587h16xaK\nxSIikQjS6TQ2NjYk2JVKJSSTSXg8HphMJknutra20NnZiWeffRZvvvkmlpeXZUJILBbDI488Iq2z\nwcFBPP3001hYWMD09DQuXryIP/qjP8IDDzyAf/zHf8TS0hI0Gg2WlpYA7G2So0eP4m//9m8RCoVw\n4cIFtLXtjaaMx+MIBoPo6OjArVu38LOf/QzJZBJXr15FNBqFzWbD4uIiyuUy7ty5I9XJ2NgYgD3Y\nPRQK4dKlS5iZmYFGo0E6nUY0GsX6+jpqtb3JMkwCWNV2dnYilUohkUjg4MGDmJmZkYk2ly5dEmGJ\nz+fDyMgIbt26BQD4whe+IC4FLS0t+M3f/E185Stfwfe+9z0EAgF4PB68+eaboqZ/5zvfieeeew6B\nQACzs7PY3t5GV1cXAoEAtra2cPLkSayvr+PatWsAgNdeew1erxcWiwUXL14UM2uDwYAvfelLePHF\nF3HmzBncvHkTf/zHf4zjx48jEongpZdeQiaTkdGWTqcTJ06cwNe//nWEQiHcvHlT2rjr6+uIx+Po\n6+vD6uoqLl68iJ2dHVy4cEEmcKytrcHn80mwph8veXvPPPMMvva1r+E73/kOtre3cfz4cczMzKCt\nrQ0OhwMPPPAA/s//+T9IpVK4dOkSAEgbNhqN4uGHH0YwGMSdO3dgNpvxwgsvYGxsDFqtFj/72c9g\nNBqF+N7a2orLly/jySefRCaTwZ07d/Dmm28K2gUABw4cwNzcHFpbW4Xnubm5iWaziZmZGUxMTKBS\nqSCZTGJiYgKvv/46stks9Ho9fv7zn6OrqwuZTAajo6Pw+XyCzIyMjMBms+Hll1/Gpz/9afz4xz/G\nc889h3/4h3/AnTt3EAqFEAwGBW09e/YsvvWtb2F9fR2zs7MIBoOC3pdKJSwsLODChQsoFAq4fPmy\nIAFbW1swm83Y2tqCz+dDOByGXq/HfffdJ23YN954AwMDA9ja2sLk5CS8Xi/u3LmDlZUVcUFgAWm1\nWjE4OCjCwUQigcHBQSwvL2N8fByhUAgnTpzAq6++Kv/+iU98Aq+88gqcTicKhQJ6enpw8OBBSb7O\nnTuH8+fPIxgM4sqVKwiFQlhYWECtVkM0GoXBYEA8HodGo5F24vr6Oubn53H58mVcuXIFP/nJTwQB\nGR8fRy6Xg8/nw7Vr18RNotFoCKK5vb2NjY0N5PN5XLhwAdeuXYPf78fBgwdRLBYxOTmJZDKJqakp\nuN1uoXKwhTk2NiYI3X/+53+iUCigu7sbsVgM6+vr+2x6fD4fnE6nDDxgqzCVSiESiSCRSIg4gskQ\n7dro1cyukTrIYnFxEVtbWwD20M61tTVYrdZ9Ldxjx47BYrEI+k8UkRQVFVGkeM/tduPIkSMwm81o\nbW3F1tYWIpGItMW1Wi02NjawtbUl6DMLJCL5ra2tGBoakmsn/3ttbQ0AsLKyImgTKRqkb/n9fhGz\nRiIRBINBjI+PCzVrYWEBADA+Po65uTmEw2EpCml0Pj09DYfDgUgkIm1pdt84oYwoLNF9dr7MZjMM\nBgPC4TACgYA8L4PBIAghX0Q2C4WCWAUWCgUcP34cuVxOuipEyZaXl2GxWLC7uyuCxlKphMHBQfT3\n9wsdJpVKoVQqobu7G1arFT09PZifn5cODhMxTsYjMufxeGA2mxEKhYSqRG/NtbU14cOTdsIk+sSJ\nE7Db7Whvb0cymcT6+rp0H/R6PW7fvo3V1VWhc62trYllJLuJIyMj0trmgIRbt24hHA7jwoULCAQC\nqFQqOHbsmGhDmMySLgRAOif9/f3o6OjAjRs3pDiLx+MC8rCjQr1FsVjE8PAwCoUC0um0xAB2X8fG\nxlCpVHDq1CkEAgEcOXJELB2z2SxCoRBcLpe03qempnDu3DkZr8tOnsfjkQ5yR0cHQqEQjh07tu+e\nk+awuLgotBwAEs8dDgempqZEs0DqFJH61tZW6cySDkDklhSO/7LQ/OpbyeveVkgqUQez2Qy73Y56\nvY61tTWMjo5KNUFktV6vo6enR4yr/X4/Ojo68M1vfhOf+tSnsLCwIC3oiYkJ5HI5HDp0CP/xH/+B\ner2OxcVFfPzjH5d2SiqVQjAYRDQaxbFjx/Dqq6/iIx/5CLa2tvC+970PqVQKuVxOuI4HDhxAPp/H\nwYMHcfLkSaytrWFubg4Wi0Xa4M3m3hQgikyAvTbvxYsXodVqcevWLTz22GP40Y9+hNbWVjzyyCN4\n9dVXYTKZ5OA1GAyo1WoYGRmRTUoLCKJwU1NT+Mu//Et89KMfFdS2VqthOlgoOQAAIABJREFUenpa\nqi62IGq1GlZWVlAsFgUNee6559De3o7HHnsMP/7xj/HUU0/hhRdewMGDB5HL5VAoFNDb24v+/n70\n9/fje9/7Hp566inEYjHEYjGEw2GxdWJC3dHRAY/HA7/fj1KpJFOjTCYTPv7xj+Pzn/88WlpacP78\neVFanz9/Ho888ghu3LiBtrY2TE1NAdgLxqOjo/B4PPjTP/1TfP7zn5dihY4KPCCbzSb8fr+MpQSA\nmZkZQaP/7M/+DGfOnEFvby/OnTuHo0eP4rHHHsPVq1fx5S9/GS+99BIefPBBoYC4XC74fD709fXh\n3Llz+NznPict20AgIChbs9mU1ntXVxecTif0ej1efvllOVyfeeYZfOpTn0JXVxeGhobQbDYFrfb7\n/RgaGto3rKLRaAh9oVaryUSUwcFB4RGzMMtmszh79qzwDEdGRiQZmJ6exrVr16Q9Fg6H8bnPfQ6H\nDx/GhQsXMDMzg6GhIfT19Un7qdHYm1ozPj6OQqGAD3/4w2htbcXGxoYcTGwB8XCkWp8t/Wq1it/9\n3d/FZz7zGUFf3G43Pv3pT+Ppp5+G3W7H0aNH5YBiW7G/v1+CMKef9PX1we124+tf/zo++clPSlDd\n3d2F3+9HuVyGz+dDqVTC8ePHcf36dbz++uv42Mc+JvxBiisASHt8fHxc7rk6JrKzsxMejwezs7P4\n3Oc+h1qthjt37mB4eBh6vV6oI/QRTKVSCIfDuHTpEtrb23H79m00Gg3YbLZ9Lhncc16vF21tbZie\nnkapVJIJVzQiV50JVM7o6OjoPnP2++67D263WzizZrNZUD1ykIk+ki/fbDZFMFkul3H48GFpnzoc\nDthsNkk0gb2ieWBgAB0dHUilUhgYGBCqCdcHJ9tR2OhwOARh6urqQjqdFmoBJz81Gg0MDw8jl8sJ\nTYuomSoc5H7I5/OSMObzefj9fjQaDUEJOfSFaxLYS3rT6bSAAH6/X7pNJ06cEM6hy+XC6urqf7Nr\nGhgYgM/nk0EPfBYWiwUPPPAANjc3odfrYbVa0Ww20dfXJ7xMonMcWep2uyWZOHbsGLa2toTm5fP5\n9mkImKBZLBYRlwaDQZTLZUxOTiIUCiEej8Nqtco9t1qtWF5eli5FPB5HKpVCR0cHhoeHUavVEIlE\n8OSTT2J7e1vWrsVikWKdLfzBwUFpV586dUo6RAMDA4hGo0gmkzLGnAUEx5lTuLm2tiYocTKZFG1A\noVBAMBjE/fffv496QEW52+2G0WjExsaG0F0SiYTww9n5JG+bIINWq4XZbEa9XpfJUO3t7Xj44YcR\nDocxPDwse4zAlGorRh7q2NgYCoUCPB6PtMMnJyeRSqWwuroqiTGFx6TGdXV1YWBgABqNBjabTdDt\nZrMp0wYB4OjRo1IUUeDd09ODoaEhHDx4ENlsFq2trfjEJz4hYuRoNCpAg81mk66J3+9Hs9mExWJB\nMBhEKpWS58eEe3h4GFtbWzAajSiXyxgbG4PRaBSRMf2MKZ72+XyIxWKSOwDA5uYmLBaLrJn/Z9X9\nhUIBJpMJiUQCR44cgUajwZkzZ2AwGCTYE54ndJ3L5XDp0iV87GMfE+5fpVKBz+eD1WqVA+7QoUMA\ngF/6pV/C3Nwcjh49igsXLgh/dGRkBD//+c9lqseTTz6JUCiE9fV14f6QWD84OIhGo4Hvfve7+O53\nvyuK9HPnzuHpp5+WlgEAETKYzWZYLBb09vZKZZzNZvH888+jXC7DbrfjL/7iL3DmzBnU63U8/vjj\nIjjipiQZn+rZ5eVlDA0NQavVCjfW4/GgWCyKaMLtdqOtrQ1jY2PY3NyE3+/H1tYWVldXpe2+vLyM\nBx98EIcPHxZBF1EZbl6Hw4HJyUlUKhWcO3cOzzzzDEKhEFpaWnDjxg2cPn0a3d3dKJfLiEaj0Ol0\nOHDgABwOB8bGxmSM3be//W189rOfRalUgtvtxpUrVxCLxeB0OvHUU08hm81ia2sL8Xhchg8YDAYM\nDAzIeFaTyYTNzU10dnbi8uXLksyziq7X6yJqmZ6eluD4T//0T/i1X/s1dHV1wWKxCLozOTkpZHui\nHNFoVA75Q4cOoVgs4vnnn8dzzz2HO3fuoK2tDSsrK7DZbILirKysoL29HVNTU2hra8NnP/tZpNNp\n+P1+/M3f/A2++MUvSnvT4/FIAM5kMnA6nVLhU3hmtVpFOMQDlGMlp6amEAwGhctaq9WkyucBmUgk\nMDo6Kq3gUqkEr9eL3d1dvPbaa/jqV7+Kw4cPS4suGAwiFArJwcXRmS+++CK+9rWvYWZmBn6/H+Fw\nWAj/1WoVsVgMwJ6YcGxsDC0tLRgcHMS3vvUtfPnLX4bJZEIoFEKttjf+9Ktf/SpaW1tx9OhRabNr\nNBoUCgUUi0UMDg6KYKBQKGB2dhYf+tCHoNfr5VlwL+7s7CCZTMoIU1XMeOzYMXzrW9+C1+vF1tYW\nqtUqpqamBO04ceIEEomE+KgSxWppaREE/+zZs3KI3bhxA0888YRwoqvVKlKplFAeBgcHceHCBeHa\nEq1ha79SqcBqtcLn84nJPwUM+Xwe9Xpd3EvUgSIARBxDqsDo6ChKpZII9OgIYDabBWXa2dkRtIZD\nDSYmJoRv+s53vhMABCGjkI1xlveyvb0dDocDJpNJEEq2++jSoY5SpLCQnEtyxE+fPi1t3DNnzgjy\nQyoGOx68J9VqFR0dHfD5fDCZTCIi7evrEzFNNpuF3W4XriWwn7/pdrtlMAfv36FDh9Bs7lnBeTwe\n9PT0IJ/Po6enR1rRTNYoHHG73SiVShgfHxdrIsYlWsSRx0zOIAW7J06cEESK97xQKGB0dFT4fxaL\nRRBXCg4nJyeFN93S0oIPfOADgqxSrJNMJmVUKwAMDAygWq3C6XTCYrGIQIfoMgEBn88n3Q5VYV8o\nFNDV1QW9Xg+v1yuuDo899pjQ7ZgcxuNxSfhJReCZUyqV8J73vEfQ91OnTqFavTtml4JG1SmCdBOb\nzSaFfmdnpxQjzWZTkrZMJiPJKdXspIIRFWVSyFY8Ozy9vb3I5XL71PF8H7bZGWePHDkiFmbVahXD\nw8NyxlCQVi6X4XA4RBuRSCRgsVj2iSDZDeHzUi0GW1tbYbFYJAYQZCLPl8h3vV6HzWYTp4larSbI\nuMfjgU6nw+nTp0WYyHHYTFSJwrNoJ7JK7jjvVbPZxOOPPy4dv2KxiP7+foTDYUGRVXeE/+n1tkpS\nGYRGR0dF4ed2u0Vg09XVJWp/ImPkT7Hl9eijj2JnZwcWi0VU1rVaTUbY6XQ6HD58WPhRXEjNZhMu\nlwsPPvigIKGtra3S8hgZGRFEi9ZYZ86cQSwWE/L6r/zKr6BcLqO3txdGoxGpVArFYlEQolqtJjPC\nuaioAK3X6xgZGZHA3tHRIYiBw+GA1+sVdSl5aQcOHBCx2NDQkAR18qS6u7uFE6TVanHgwAF0d3cL\nIT2Xy8Hv94vCnxYnpET4/f59PMdqtYqVlRU8++yzwhva2dmB0WiEy+WC1WpFOByWNhbvQaFQgNVq\nlb9HR0fx8ssvY2RkBENDQxgbGxOVLNHhoaEhEcyRL5ZKpfB7v/d7YkNE+sd73vMeOBwOJBIJsd9q\nbW0VxaTZbEahUEAgEMDY2BiCwaCINajgpHpdo9HA6/XCZDJJkKjX68hkMvjzP/9zmblN1N/n88Fi\nsYgdlUajEY7m5uam2B0xENGnE4DYVo2NjYkwQPWfpCo4kUjAbDYLj4oB/c6dOzh48CB6enoQDAZF\nKU/rGSJLTN452s5kMiGVSuHDH/6wdBLy+TxsNhvcbve+UcSBQADvfve7kUwmxU3i2rVrMm6S7gys\nrDljPhaLoaurS/hgTPx4WA8PD4tYi0mm2WyG2+0WFJGjBll49fT04B3veIe8N1ug5IiS+mM2m3H2\n7Fm0t7fjwoUL+OlPfyp2T5VKRXicZrMZPp9PDlnyEKvVKqLRKA4cOCB7U6PRYHJyUvh/RBLtdruI\nVWiXdfny5X1+wsAeckurN5vNJmuQ4h+6LTBJYnsNALLZrMQQonlUChPtLBaLKJfL8v3ID6Woxmq1\niq0br12v10tCQjEY4xSvI5/Py5rmfHaNZm+GOYszJqSdnZ37uG1MFqlmpgCGHDkKtHK5HJxOpxyc\n/P7pdBo6nQ5Op1Ps/JiQs3PBOGm32yUJItrZ0tIi64oWa0TBOHyChSp5eMAeN5b2bmxNM2ngz5LP\nm8/nYTKZsLOzg0QiIW4zpIeQp0itBUWXNpsN6XRa+Ma8L0zEiApy8AzXITnPOt2e7ZnX6xXqDJPT\nnZ0dQfk2NjYkLvBz9Xq9OJtQYMrChMkmAQImVOzccT0Xi0VJ0HkWcC2YTCYcPHhQFOK8Z+ykZDIZ\neQYqN1dNolgwsq1us9mQzWblvHY4HCiXyyI2JP+bk5L4fIgQM2kkbYb7kfFRo9GIgLi1dW+0rd/v\nh1a7562dSCQE+KFDB508KICm8I/Pn3xz5gd8dk6nU2gYpLnwLFCdHlg8cTw1RYG5XA6NRkMK5J2d\nHdjtdkxMTEh85/qn5R2FrIy/7BiRMsiChsJhAGLl2d7ejnK5jIGBAfkuqrf2//R6W5n5k4TfbDaR\nTCblwfX398NsNstBSGLy8vIyBgcHBbYH9gIoE0ej0Sg2QG1tbXC73ejt7YXD4cDQ0JB8FgVOHR0d\n+MlPfiIPyuVyweVyyXzxZDKJSCSC3d1dXL9+HR/84Acl6ACQljD5XSaTCYcOHcLExARcLpcgBW63\nG5ubmzh58qTw1Vjh8Xr6+/vh9/sleJM0Xi6XsbKygkOHDqGnp2ef4CEQCIiasqOjA4lEQnh4bIGz\ndUYkkQjN6OiotIz8fr8obPv6+sQqqlar4dy5c7LxuKkeffRRnDt3Dq2trbDb7RgbG4PH4xFrEpLi\nGaycTifcbjcSiQTsdruIw3idHEHLAoOtyOeff15suniwP/roo8LD6+jowNjYGCYnJ2G320X13NPT\nI9WiyWSCy+USJbjdbkdLSwtcLhdsNpu0pfv6+iTJrtfreP7559HX1ye2W7u7u3j88cdx7do19PT0\nwOVyYXR0VFoxTFqowu7q6oLdbsfQ0JAEZrX44qutrU3EcKqVCP9WE8KpqSmsrKxIu7K3txcejwde\nr1fQq/HxcUnAHQ6HCHqcTqdYpBmNRvT19cHhcMjIX470DIfDeOSRR/YR6pm412o19PT0SBuVqFV7\nezsGBgZEULaxsSEoOG2+xsbGUCqVYLPZ0N/fD5vNJm3WWm3P2HtxcRHT09OYnJyUg4z/jfuBo06B\nPYHL+Pi48Mn0ej0OHDggz4DK4kQigdOnTyMSiYitG8drkuM3OTkpLgJMBNn+YxHkcDiE80lxAVEL\ni8UiVjbAXbSSKKHH4xGEe2dnR4pXTlQjX4/3gwc+OylU6+bzeWmj6/V62Gw2uFwuEavV6/V9hz+R\nI9XDma1PItGqvRNRRbZCDQYDTCaT7A9SbXp7e4WGxCKVcRqAcOO5F+hfrdfrMTg4KH6XRFqpDOf3\nZ5uWimRaAZJC0dPTI2ADEUmitG1tbXA6nfus2MjPZ6JOYQ/RWK5v3nM1qaCIkffbarXKz9MvlYd4\nZ2enWCpyb5DX2dvbKzGcQh12PJrNpghpmGTSz5kvKuN5r5mkca/yrKGDAFFRJm+0cmL7Wx0QQ1RR\npfColmaMFXwGLPYJyhDBZxeRNJdisQiHwyFWYKpwjveQ78lElnGLCLNq48T1rFqZUYCnjk8l+MIO\nFdd2uVyW31c9hfV6vWgD4vG43Hci+ru7u3Luk1rCPaqOX2bho/qyE4nms6BOgd+ZRQH/G4tTFizc\nk+y4MfchMEXRGrtd0WhUOk8EllicqAUpcx4AUowQEKTjCJ2D1Of2P73eVkkqAKmKdDodDh06JNwI\ntshJMt/Z2YHX68W5c+f2ecfRn3NpaUkSNr/fD5/PB6PRKHydWCyGgYGBffN4m80mPv/5z6NaraKn\npwfNZlNGnlKJTRuhUqkkFTIh8JaWFoyOjoqvKhceq7lmswmTyQSj0Yg33ngDgUBADj1usvn5eZjN\nZql0AQg6ygOnq6sLly9flsVFuwqn04nbt2+L3RX9Htn+o0BicnJSFjaT+Q984AM4d+6c8FSYwKdS\nKQQCAdTre9Nz3vve9wr6Q77K4OAgAAgCzcOHqkgiARaLBc888ww6OjqktcEql+plBnO2UsPhMJrN\nJq5cuYL3vve9+7hmbNVfv35dqnneD342K9NUKoWPfOQjgjoyeD311FN48cUXZXgBE4BCoSDPcXZ2\nFo8++qigr9zIfr9fxl4CewGX1bTRaBSaSqVSwe///u+LIpWBgW3DfD4vfFD+oaCE3YVwOCyoBgA5\nhK5cuYJoNCrXzQDGNUlvU4/HAwC4//77BbVZW1tDa2srrFarrNHd3V1RqwOQiV6kUNRqNTzxxBMi\nZOQ6IsLHQMvihe9D1wBe3/LyMkqlkohLuF7Id6pUKuju7sabb765jzfW0tKCnp4ezM7OCmLB4EzL\nJI1mz9NwYWEBFGHywOUemJmZEW5lpVKRzyUV5MqVK4IysntCXiRROR50ROcYF4iukqLErgIRbSaG\nvE46NDDZ5kHPtjHt1pj0MfFigsW1zj1EtJ1xhQkEkyoedmazGV6vVw5tdhSIthBFJGhAHjQ/i78/\nODgo651xju1v1VNTHWFsMpngdruFt8rWP4VZjCfqZC0WkL29vfsQf6rqmdhyvZbLZXEjoPUOE1iV\n68r1xfYrr4HvQ/SZHQFSaljg8bBnAqAmrPV6XVAqPm+TyQSPxyP7jUUUi08iZ0Sjub6YGHZ0dMDt\ndkuCCkCun/GBv881DEBsvphAEXWmV7i6NrlX29vbYTQapZAmgk+bvVqtJgk+KQMschwOh8QkcvX7\n+vrkd1UPVxUhZ7LLYr+zsxNWq1UcaWjzR+QdgFjUEUFlwcHrIjLN+Eouslo40o+Y70fknk4O9Dvn\nnmL8IVeTHTd+XwI9tIpi4clCgmuN94tIPzs6tPjj/WHew+KCz4fAA1v3pAxR3EYbq1KpJFQcrm2+\nF7uTBLBo96XVaqWrSAoSHUHe6utt1+7nTWw2m2LiToN0s9kMs9ksCMKbb76JsbEx2VxckBQyvPji\ni7Db7XA4HNJ2oYrd7/cjHo9jZ2dvOg2wVz2oqtLz588LTYBIVjKZxB/+4R/it3/7t6W9xJGqFErl\ncjk8//zzQpYm2sr3nZ6exm/8xm9I+7Wjo0MSF4/Hg2AwKEkTk2DVq+7ixYs4evSotFi4oVpbW1Eo\nFPDSSy/h0KFD4utGKxOdTofR0VHxnmTVxkPs/vvvh1arRTgcRjweFzU4BVe/8zu/I0MBWlpahCd5\n9epVPPHEE1hZWZGpTSwsiH4MDw/D6XSKITkP51AohPe+972oVqvY3NzEm2++KYFje3sbmUwGHR0d\nePrpp9FoNBCJRFCtVjE3N4dms4loNIqPfvSjuH37NhYXF+U78ZDJZDLw+Xw4ceKECEbUNlepVMKZ\nM2fQ0tKCZDIppH7ys3K5HD75yU9Co9FgcXEROp1OlKJzc3P40Ic+hBdeeGHfzHAefDabTZSdiUQC\nmUxGEOhMJoORkREAexYmsVhM+Ek8DJkMEGUrl8v46U9/iqmpKXlOJ0+ehMPhQCqVkgMDgFTZ9CTN\nZrMYHR3F2toayuUyDAYDfvmXfxk7OzuYmZnB0tKSIAOlUgmBQABf+tKXhD9cr9dx584dmbrz0EMP\n4dKlSwiHw/J5Ki+UbUcAogJmJU+R1ezsrAR4oka0l6rValhaWsL4+LggeUzOiNR+73vfwxNPPCFJ\nF1t/4XAYFosFIyMjKJVK2Nragk6nk+BN4drt27fR2dkJvV4v7bRwOCwWY5lMBgsLC6J0Z4ueIgUm\nvjxIyLOmhU0ymZTRtOSPNptN4VvzD4sfJgb5fB79/f1yaJZKJXR0dGB1dRV9fX1SfDF5Vu156CVN\n+xmiKiz6KJBgXFETjcXFRTgcDin4mQAQ3V9bWxNeJ4UuKq0gl8vJ+mOySF4xi2sWXuwO1et1uV+M\n8yrK1dXVhdXVVRHRqYUn3yeZTCKRSOw7AygsUdcdCzuqwvkdG40GotEo+vv75b7yOkOhEOx2OwBI\njAUghVQ2m0U2mxUks9FoIJvNSqeKdAuu266uLnnWu7t7kwUBiIsDUXOr1YrZ2VmhWLANzYSLTgmJ\nREI6C0wcmHTHYjF0dHTIfWXyw2fDYRWqiKe1tRVLS0ti96d28Uj5ItJPBJ+JHQtStUPEwoWfzQQ+\nlUohFovJeuYZ19nZiWw2i83NTUGB+erq6kKpVJLBDCwIGHP5/qQl8FkzyWMiTOQ6k8lIV43tej5X\ng8Eg6D4AodbQlov0I4oUiSZvb2+LxoRriQgrnQ6Y8EajUbn2cDgsZxR/nsUUk2J6DZNyxnOM92Rn\nZ0eKMf7hmqGPKuMVlfrZbBYajQbBYBAOhwPAXRSb653OFBQoci+91dfbKklli4rwMs2YySdhm4aV\nvd/vRyaTQTqdFv/FTCYjNi3333+/oBHValXax0zmGMi5uVhhVat7U6qmp6exurqK9fV1hEIhUdID\nwPz8PObn53H48GFJqLa3t3H9+nU89thjGB4eFjI/W1E0Pu/v7xfbCZ/Ph5WVFbkWtkpCoZAkueRm\nsRqfmJjA7u6uGPWqC250dFQqIE4oIUme908lsPN+8kAgr4mJUjAYFF+0dDqNP//zP8eFCxfwzW9+\nUzbGN77xDZw+fRqf+tSnRPE+PDwshwmnubDlSh9SFYHS6XTwer0olUriTUveHMUyly9fxszMDD74\nwQ9KJfrss8/i3e9+N06fPo2rV68KRYQHWF9fn9hfhUIh4eMSBWfbgnSLWCyG3t5eBAIBERo1m038\n1V/9FV566SX89V//tfhgfuMb38BnPvMZPP7447h9+7Yc3FyrfX19UlxwfQKQ9ccDh0GBaDdR893d\nXdy4cQN6vR5vvPEG5ufnMTAwIIfOn/zJn+Dpp58WRTYFAgzUAKR6JhJit9sRjUalzQ0Ax44dEw/I\n27dvo1qtinXW/Pw8bt++jampKUGm/vmf/xkPPfQQTp48iddee01sWJg4jIyMwGKxYG5uDsDd+fNE\nzADA4XAIp5UcU7YSKVzjuFyOjDUYDCgWi5LkPfnkkxJkuT9oEM7kjjxPBnweJul0WiyW1OK2Wq0i\nHA5jc3MT169fF7pKJpPBD37wA5jNZhw9ehQnT56U31ODNhN8JkJsu6VSKfHcJdLItixFG0QCeZ94\nqNTre+OOzWYzkskk+vr6JGYRbWMHihw28kFpz8SpX/RgVNuNzWYTq6ur4lNNlJsHXDgcFtV5LpeT\ndjEPP+4n+kwyAVN5q/RUJTrLuMNOjcPhECQzGo1K94pTuhKJhHD5mBjTro12S3zx8xn7WRQBkBY1\nUT/ufzp2cN1otVpRylMXwASLv0uBKtFaPn+uWbXoY2eEySCwxzWOxWLwer1YX1+H1+uVIjAUCgnA\nweRTTVay2az4j6oIJgDpUhGVrFarUqgQMef/ZgFHzmwkEoHJZBJLR+5bFjJEKzn6m/+dBT9deNh5\nJJKottJpD2m320WDQDvEQCAgnU5+HnnSRJi3t7eRzWb33ZdSqSRrSKWrMB4zBgHYNzGNg0dY5Obz\neUFC+fNcl0wQ1aKMojSeIdSFMDZwPba07A0quXjxItbW1qTgXltbwzve8Q4BTYhyUxjIe0Z/Xd5z\ndnRrtZpwswneqecKz3sOlqAYjhM1yb/l9RJNZc5ESyvmWKoo8a2+3lZJKnkRXGRs05DX0draKlXd\nzZs3YbPZ8MYbb6BQKODo0aMyl/3v//7v8dRTT2FychLA3ckgbMFwQXKjEapvNPZGovp8PhSLRSwv\nL8umOXz4sKidL1++jNdffx2HDh2SKpZ+fOl0Gq+88gpWV1dFxMVKZ3t7W6o78mB5OAKQlqfb7UY+\nn5cKl5yhZrOJH/3oRxgbG8P6+jqi0ahY6XR0dOA73/kOPvShD6G3t1c4OXzx0OEBRvFHvV7fN42F\n1TJ9YU0mEw4cOACtVovZ2Vn09fXhq1/9qngE5vN5sQS6cOGCoLesSHmYqfwYCrNoYcSBB5x/TAuj\niYkJHDx4EOVyGa+88gquX7+OBx98ENVqFcFgUPh358+fh1arxejoqPC/OLWKKFMqlUIoFBJPWaPR\nCADSdicakEwmEQwGsbu7i/vuuw9erxdXr14FAHzxi1/E9evXpfV58uRJXL16FblcTu632jbu7u6G\n3W6XGfX5fB7ZbFYmmBG9I2LBaj2fz4u/5vT0NF555RUMDQ1Jp+H69evo7u7GF77wBcRisX3FGxMg\nADIljcVCW1sbVldXRc3KxGl3dxexWAzZbBYejwdTU1Oyty5fvoxjx46hUqlIwWKxWHDt2jXcvHlT\n/P94YNrtdqHoUCHPtiJRHL64Blm1sz1HNHBnZwcbGxsSTCnqeP3119HX1wen0ylOG0SdeaCpCU93\ndzfy+bxwD6vVPfN2iiGGhoYkWTQYDJient6noJ2fn0ehUMD09DR8Ph96enqQzWal6K3X65iZmUF/\nf7/s9UwmIy1/ikCJLPMQYlxj7AH2BprQj9btdst/p7LXZDLJQcIEkZ2Q7e1tSd74OY1GQ5TMbOUy\nhjJhiMfjIjC8cuUKNjY2UC6XBWViYuzz+ST5o7qabVMmD7xW8l3VZJCdBna+OGmn0dgTAXIgA3B3\nhnqtVpNWL9+/Vtvz92QMpfsKcBfB5Zpj0sRuk9pS5v+nQwW9YImCxuNxHDhwQMSPKtWLSTi/Cwsh\nJkf5fF5U5kTLiJTydzhC9tatW5ibm4PX65VnVCgUxN6ISTeFt/QIJhWCz7pSqeDnP/85+vr65HN5\nL/m9CVw0m00Eg0HcunULExMT0u27desWTp48KToPxnEmLOys8bMJ7DBJZReLlBEWafze1WoViUQC\ntVoNa2trWFpa2mfwT3SVBZuKzDNBZCHGV61WE1GumqwbDAZB1NW8pQGZAAAgAElEQVREnt3alZUV\nXLx4ESaTCZFIRNT3x48fl7OL+4lFGL8DOwQtLS2IRCJC61A7kwD2dR3otJPL5WR4A/2NT58+Ld9T\nTeiZEKvFCJNvilhpQcaODUEqUgO0Wq04EFy9ehXpdFpyCgJEfJ7cG6QnMEFmF5pnzP9GOPW2SlJ7\nenpkgwOQIENOR7FYhNFoRFtbG06ePIlXXnkFLpcL0WgUGxsb0tL7rd/6LUEZiVCwuqAwIhQKSaXH\nJJacyEwmg/Pnz+PgwYNYWVkR/hDVnJw6Qy+4ubk5Qb+YpD300EP7rD2IqN68eVOCRiqVkqBEX0ku\nLlbhVPjyEHM6nYhEItjY2EAoFJJgBgCHDx9GIBDAwMCABC/grv8sk0SOJ2QV5XA4EAgEYLFYUCgU\nBJ2kmXmzuTfOkmIgzqqfm5vD8ePHsbKyIip8WpJUKhXZwDzIW1tbEYlExCuQjgVM1q9cuSI8L+Bu\ne6de3/M4pLPBSy+9hDt37uwjlGcyGeHGMgnp6urCzZs3Reii0+lEIcpWF8cj0og7EAiIyTf9HI1G\nI4aGhrC5uYmtrS0sLy/D6/XK+EWj0QiPxyOCvUqlgt7eXmmxhcNhbG9vIxQKSfAij4tKXibodFIo\nlUoyjvG+++7DrVu3YDab4fF4ZIBDKpXC8PCw3D+6DLCNSWoE3SCIgtEzs9ncU0i/+uqr6O/vx/b2\ntowGzmaz6OzsRH9/PxKJBK5cuYL5+XlRa3MEol6vF/SHSPnq6qoIkdh2Y8HAip50FooiaEjO52Y0\nGrG+vo719XUJpKT7dHR0IJvNwmw272thZjIZRCIRoe9wndHmq1KpIB6PC/LLBJ9UB1IO6EJAm7Dd\n3V1BG65evSoiMwr2WltbMTY2htnZWeHckn5BBJ2HOYB9xSMPEapoybGcm5sTJJUoXm9vr/ChWZSo\nqCULZlVwx/cm75T/xp9na9T/X9PD3vnOd2JmZgaZTEb2bG9vr6D3RL7IKeRhyvHS5GVyX21vb8Pt\ndgv6wo4RxwFzDTSbTaytrWFzc1MOy0Zjz6uXojTGRiKVvHauDx7cTBpV0QrjpyqsYiJMxJXJN4Ul\njAOMgXwPcgCJkLJbUq/X0dHRIdQFrVYrSRqpByxWCBSQfnH79m0poEmRstls+0Q1vOfsBql8ykaj\nga2tLfldcpp5DqjJCicO3n///ZibmxM7P04oGxwclDOFxTsTJnaACDzwXlDDkM/nYTAYBFxi8cdn\nzhhktVplhCkLCHb/6vU6vF4vCoWCPBs+22w2K44hXA9arVYKLra7ee6pwio+c04vjMfjcgaR5jU2\nNgav1ytCMiZk3C+839yvOp0Om5ub0Gg0MiJZRdbVJNlut+M973mPWG3WajUpigwGw757qiaDqmaF\nsYQFNOMsObXcm/zOAASYY/ycm5tDMpmUeNvS0iLDYng/ib6qYB4RVrVAeCuvt1WSSlQAgFgiNRoN\nxGIxjI2NSTs6Ho+jWq3i0UcfxczMjHj0tba2ypjKwcFBScBaWlqkTdjV1SVTSjY3N8V2IZFIYGxs\nDLdv38bIyAg6Ozvx8ssvw+l0iqcoEQGioh6PR4zrw+Ewzpw5I4plWvYw6LEKGx8fR7ValZYxoXqN\nRiMbmOgaeYjNZlMU8sePH5dxpDyA8/m8iLb0er3wgXhIsuVGjibfv9FoCCrEBGp7exsf/OAHMTMz\ng1KphLa2NqkUg8EgarU9L0B6rsZiMbhcLiwsLAg/hm3r3d1dMbCmur9UKsnkIaIPamI4OzsLl8sl\nnL6dnb253LS26ezslKTM7/dL8KzVaoLQsp3WaDTw/ve/H5cuXRJhWyQSEbFANpvF8vIyPB6PFDQM\nzvl8Hjdu3MDu7q7wp4jgDA8Po6enB/F4XCYgMTjTz3ZjY0MsT6iOZaFENDUSiQhyXSqV0NXVhc3N\nTQQCAXk/KkzJzSVi2GzuTZ/K5/Ni0eR0OuH3+6UwyOVyCIVCyGQywgfkOpydnRXB1ODgIK5cuQKr\n1YpKpSIjZ8nzM5vNyGazooylwCcYDIrrBlEWv9+PXC4nHCfOg2ZQdbvdKJfLCIfD8Hg8WFxchNfr\nlX1IXu7g4KAUp1tbW6jVatjY2JACjibmsVhMDjiNRoPe3l5cv35dBDnch+Rgkh9HYQaTSIvFIoiK\nygMHIAksESWixkTMm80mFhYWxKmC8+F5YBCxIApEz1IiWyoHmd/hkUceEX4yebNMaFiE8eBisspE\nhnuN7WiHwyFiVKJMTLJ2d3dl0g0nsd13333QaDQyIYmtSCai3Es8jHkoMgnQarVYXV3FsWPHhJ/M\nZIU/x2KfXaxisYgzZ87I2mGixy4TYxmFYeyUqAkt6QRbW1s4dOiQPCNVlMQYznvFOHvmzBlsbW3J\n7HPePyb33I9EvdUEHYAc4uyoGY1GiVe8BnIf6/U9L0w6OWi1Wjz55JPSwWLSy3tGgQ3jHBFbJhNc\ny7SRI9rHF+9Na2urCCyJJv7qr/6qJEbAnkMGaQYqn5f2Zkx6+R50JeA6ZELE59ZsNsUeikIyDu/Q\n6/V47LHHJFklh5mdFdXdgd9d7cSwC8Y1R4SSrW61WGN8572t1famw/n9fonRjGfqGuGz5Xuw2GBr\nnveXZwavr9FoyOhUVfDU1taG4eHhfcUs6ShMTrlGCHjws7mvmb/w++XzeaRSKZkgxb3Je0Tnm2az\niZGREXR0dCASiYjFH439y+Wy+K6qVAPeA4If/xvRFPA2G4v69a9//Uvt7e1tRCfIoerq6pKJFxyH\nNz8/L5YcNJpmQra8vCx2KVtbW9jd3RXrolqtJkEwGo0ik8mIhQpbUgxCgUBAZmizQjaZTDIphPPO\nOTqO5vc8lLLZrBiUs5IzGAy4du0ams0mbt68ua/FSVSJCEaxWJR5yWx90hoiEonA7/cLx4TXQzSz\nVCoJIZ3epel0Wlqw4XBYktfe3l4xec5ms7h58yaSyaQcoNlsVqbG8GCjtyX5Ue3t7VhYWJA2GlHi\ndDqNkZERqaI3NzfFzsTr9QrnjPzYtbU1UWXT3w2ADAioVqtYX18Xo3RW0bQJYdJOgrcq2uBIWSLJ\nDodD+HKZTAZ2ux1Xr17FysqKCDKMRiOCwaDM0GarhyRyJmcMFqz2jx07hsXFRQm+CwsLknC6XC5R\n9JMbXCwWEQ6Hkc1m5d/K5TJSqZR8Ll0PmDzZ7XZJJDlpZH5+HhaLBfF4HLlcDoFAQO4LkR7SWUj3\nyOfziMViiEQisg44jajRaAhNgt6EwB4aSOQsnU7LYcU9RI50pVKR9lKpVBLOLNXu7e3tMl6VhUil\nUsHNmzelsnc4HDLKNRAIyNhIcipjsZiY8q+ursLpdGJra0vQEYokiPaQZkET/1wuBwD70Ot0Oi3F\nA43WGaSJELOVzsOkUCggFosJf4vJMNEPiuYoAOLeJ19RPdANBgO8Xq8cqmpSxuKdhwmfFQBJhkg7\nKJfL6OnpkSSKCBwRT76YPBL9MxqNIjgl4kwrP/L2mByzXcjDkUVIf3+/CBkByM/znvD+8ABvaWmB\n0+mEx+MR83XSCdTDX+XB8jCmSjmXyyESicgI2u7u7n3+k1S6E7UiYkbUiHx2DkzhfWarnmuevE/G\nH7awKZpim5dIKjUB1WpVkpvt7W1B6IxGIwYGBsQSL5PJyDolR5LPjOtevQekE9ntdkmuifRxnfEe\nkx5B5HF4eBhdXV3S3iZSyxfXFhXgXD8szkmTYzFFf051PTJBNZlMUpzxjHK73ejp6ZE1pLbkud/4\nHtwfXGc7OzsynbFer0s3lvuJiT7jJq9ne3tbEj2K0+jZy/Wl3me2upnM8tkDkGtkJ0SldrCAZ0xv\nbW1FLBZDZ2cnAoGA2DQyGWVySKCFtAfuHa5TIqWMocwZuL6ZBDMHINjDs4CdP4q2GXP4YmFAFFWj\n0ew7E4LBIH7913/9/72xqEQTzGaz3BCNRoNAICAVr8ViEWU60QlW893d3Ugmk4IYra6uolqtolAo\nYHV1Ff39/TK+j63yzs5ORKNRmYNOiyC2yLPZLBYXF+F0OkWMwgMpEonAYrGIaEqn0+2bna2KdLhw\ntVqtiLt2d3eldanT6aQty83JFk4wGESzuecRp/K2iNS0tLRIwsR2g1arhV6/N67P5XIhk8kgHA4L\nmsoD1uVyIZlMwmKxIBqNijl7LBaTIM+Nws2ysbEhnBYe0JxiUq/XsbS0JK16h8OB1dVVmVK0vr4O\ns9ksrdXd3V0JsOS1FYtFLC4u4tixY0gkEsLHUoVP9XpdWtJMXvV6vSj8KaxbXl6WthE3JRHoYrGI\nrq4uaZO+/vrr2NjYEL9Ltu/ZTuRkHc5j3t7eFnuZjY0NmVbS3t6OxcVFWT/b29vi/sD3BSDuCVwX\njcaeubLVakU8HpcCqlqtilsCkRK+L1vRVGiaTCbcunVLkByi4RRkcd1Qlc/nG4lEhHjP70JeZyqV\nEo9DvV4vST45SyzQiEKTL0dVOqktHo8HiUQC4+Pj8t2i0agkGkS0aTDNvcYko9lsigk3RT480Km0\nbTb3LN/YleCho/KumChQyERXB5vNJhzvWq2GwcFBGVJRqVRw48YNEYIwgG9sbMDtdkOn00lBzAKA\nSTD3Mw+ZXC4nnQPuKSJlvKe0wjKbzSgWi4hGo0ilUpJk8DACICgWEQ41dgKQcc5E01SeoSpKIRK2\n8V+jb4mKZbNZQcCICvLAVV/ch6RebW9vw263SyJF43E1AeJ18L/Nz8+jq6tLuLAcAgBA4haTdlXJ\nT6QnEokAgPheqwp7APLZlcqeJzcTbsZO1S5qZ2dHpuwwQVfvNeOQylHl2kmn0wKMEMFTkXMiZ9Vq\nVc60K1euYGBgAAsLC3C5XOKqQhCD9AI+cyZf6rnDGJPNZoWryOfCvcF4Tq/UixcvwufzYW5uDgaD\nQZIaJtaVSkWKEVLViGLyWjY3N2WITaFQEGca3u977xWLfVVQ3Nvbi9nZWeEbc/+oxYwqMuTZT64y\nnyevnzx23nMAUvTodDqh6qTTaXR3d2NtbU2smlRetUqp4DmlulCw+GWHVKUf0MqSQkg6FnH/lstl\nDA4O4vDhw9L+57Nua2uTz+V6ZEcKuDsdijEyk8lAp9OJloU5jLrPuG+tVive/e53Y21tDdFoFABE\nTKzRaORsUWkHal5E8OitvN5WSSo39NbWFgAIckEk1el0ytxgNegwOJBbyAqLdg/FYhFmsxmzs7PS\niidiwoVAxAu4ayZOaJ3KVIom3G43bt++LfZEhw8fxrlz53D9+nXMzc1hdXVVLGmIwDJxVf3mVDEF\nPVyZ2PDQUqs98uq4OQAIygnsKaaJnpCfm8vlEA6HZfpUNBpFLBaT9jLpBkS9OJ2Fm1mj0eDAgQOi\nZtZoNFhaWpKWTiKRQDweB7DXQlxbWxN0lYgBKRpsoTKxJlLFoKoqETs7O7G2tobh4WG0te3NOg+H\nw9KqbzT2rF6WlpbQ3t4uvDEicRTNkN9HKyC2DSnaymazogInmpdMJrG6uopgMAiv14sTJ07g1KlT\nuHbtGt7xjnfghz/8IbxeL374wx8iGo1ia2tLPAiXl5fFu9VgMAj6wESZL3JV2fpje4sFTFdXlwR9\nnW5vnr3X65V21K1bt6QFT6SQB7fBYMD6+rp8L+AuF9BsNgtvlSI2FhRU53NoxR/8wR8IQn7q1Clc\nuHABo6Oj+PGPfyyDBP71X/9VqDCcHBSPxwXxp2eq1WqVJI3CtkajIchVsVjE5uamBF0WXlwnFEbw\nUKDanBQeigjJHSVfkWuKLf/d3d1986jpNcq9SdeBarWKwcFBdHd3i83MqVOn5BlxrTSbTaysrEgy\nzkMxmUzC6/UKOkcUhy1SIpZ8PrTfInqztLSESCQCr9crLWi32y1onsFgkAScyQm5gjygyIXnxB41\nYeIBB+xNcltYWBB0yeFw4Pjx49KGXFpakoKZtkgHDhyA0WgUZIyJYktLC7a2tmStswDnQUvElmuS\n9JtQKCRUKSb5FPeRl0rqBFF89Ttw71PPEA6H4f8vm0FeI7sJLEp5IDPG1mo1zM7O7iso6KTAe8ck\nm4c/E3t+VybufCZMgNiapciP2odSqYRXXnkFsVgMVqsV8/PzMJlMuH79Og4dOiRUGYIEbLfyj1ar\nlXHIfA7UN9AVhgkOJ+HxcxcWFrC6ugqz2YzXX39d9tEDDzyA3t5e4Scytqu0ACadlUpFOkRcayxk\nq9WqmMuTV0k0mUr5QCCAUCgk186O4v8l78x+4z6vu/8dDofbcDYOZ+WQw1WUKMmyU9nO4iwG0iC5\nCAq0aPsP5KpXvSrQv6Q3LZCb3hVICrRIFydIk9aIHduyLEsiLXEnh7NzZrgNOdt7MfkcPsM371u/\nl686gOBEIue3PM9zzvd8z/ecw/hw5FYuo+hqcdFOw8rSvxw21211BpDknFUqFa2vr9v3lkolxeNx\nra2t2TmhCJHv4Lyy72BRAXb1et38E++tXq/r2bNnyuVy2tzc1Ne//nV5vf2x4aOjo/rxj39sdQwU\nvXEt7p+9wxmD3QXssj4MXCBrQh9VfO3JyYkVgsbjceVyOS0vLyuZTFqPY7KoLoOLbfP5fP9PAFV6\nxdL9f/d3f/fXPp9vlLY5gDPYHQCIdN2uCqE4zMv+/v5AayHSu9DVzWbTACrGhUgehgJQSYpiZGRE\n09PTWl5e1te+9jWl02mbYw1YovF7IBDQ/fv3FY/HLb0p9XVtGCuiLFLNAAT+DSE3DhqQnsvl5PFc\nzzgnKnJTJJJM70l/TZxNvV432YQkSwW4YvRarWZBADO6YZdwIPR5gzUMBoOam5tTNBo1dhSnTGug\neDyuw8NDS7kR6VerVfl8PhUKBZMpEPGHw2E9ePBAb7/9tlKplKamphSNRq1au9frj7JdXV21XnVM\niKLZeKvVsj6ipKBOT0+tpRYHnsIljNnKyoq+853vaGVlRZOTk3rvvfckSR9//LHW19fVarX0+PFj\nA5hHR0e2fxC0kzKm1RLvDWNDqzV0ZTA+MOAzMzM2GID/4vBjsZhNnKG5dqVSsb0kXY/KvLy8tH3o\nVoICFjHel5eXymazSiQS+uM//mP5fD598MEH+qd/+ifFYjH9+7//u/x+v54+fWqRdbfbtd6PAFK3\nFQvZCtKqkszowQyjMS8UCuZsYZoATXNzc8YKkQqjmvb8/NwMJ0YWPThOE+dOoAWzHI1GjQFmv2Mz\nms2mnj17ZppkGEXYpUajoefPnxsLB1AiRUiLNdhU13GQNaJnba/XLxzK5XL6zW9+o8ePH1uwkU6n\n9f7775tEBweKVhJHQroQQFWv1+26jGmVZLrfsbEx1Wo1bW9va39/34iARCKhXC5nrcpoEI6W7eHD\nh1ZIBUML47S3t2fXp9sBKViXAbq66g+T+PWvf63PPvvMbPBbb71lU4VmZ2d1cHCg7e1tff7559Yx\nA/AC8GNtnz17ZusTCoUslQqIgAWGVSJowCf88pe/1MHBgUlFHj9+LElW+AX4J9ACOJGGpiURZw1b\nzO9gpyuVij777DPrHsN0N+wbQf7e3p75KrcTASCa/fz48WO7P0Z1MqgAMEWgVigU9OGHH+rjjz9W\nrVZTIBCw/f/w4UN1u1198MEHqlQqqlarlrUj5YufYQ0KhYLto2Qyac9BdoRiPZjZi4sLra+v6+Dg\nQB9//LEKhYIFgwzaYT+yp9DFunYDkMwa4RfctUZCRhDSarV0eHioZ8+e6fHjx3rvvfesMBTp1aef\nfmraWPoqY28uLy+tdRPvm3MISGUkcbfbNTlVu91vA5nNZnXv3j2boAmQXVhYMHviShxudpRgvd1A\nA9zjEm6uVpxswNOnT/XixQs9evRIGxsbVqyH/LBer5uGHRsL/sHOs/8++eQTeTwe/cVf/MX/vHS/\ndN2rFCMISwETGAgEBsYQopti1vji4qKBUhgNtJIAMnRVOFCiFpg/aG+YWUnW+sfn89mElUqloouL\nCxWLRR0dHZlBlvpGIRKJGBWPTg820+/3KxAI2OZrt9tWUOTxeJTNZnVycqLt7W1Fo1ET7sOiMnfc\nnSwUCoVMIwlIJXJH7+imElzGFaE2AId+oUdHR8YW/Pa3v7UqeUnGlnq9XtMEd7tdmwaFFqdardpm\nR4pB42yXBaLwibZVx8fHevr0qXZ3d02TBYCXrifSoAftdrsDM53ZB/zhHm7dumXvsN1uWwRM5wf6\nnDabTf3gBz8whgQHSN/WZDJpBo2eoPSzBEDTy5GAAsME8+YK4Il6KfaD9UMXxKhg0sWxWMxANc4R\nNhItHCkenvfw8FCpVMr020hYcIQMW6jX69bCjWbmP/zhD3V0dKR0Om0Ar1KpWDAEm+o6U9J1tGTi\nfDF+dWtry56V9zEzM2PTiRiBCON6fn5uxSkEJWjskJKQBm00GvY7ACNS9TDypM8Aj8+fP7eerbBB\nrAuaeAKT3d1d66PJeSCtOz09bWsjyfYOMgR6ceIQGJ5xdXWlxcVFG+2Ktp49l8/ntbGxoQcPHpgM\ngsIaWD5AEftE6rdWS6fTJqfinQcCAb399tv6/ve/b/pmMh68V95FNBrV9773PbO1bjEUDPjm5qYx\nfJxXdMqcQ545Ho/rL//yL03aQu9PhjJUq1WTK0WjUQuo3GI0gmHOOyylx9MfzDA9PW32HA09vWOR\nNuzs7Bi79I1vfEP5fF4PHz5UrVbTv/zLv6harWr+d1MLCQYAnADXg4MDszGsN6AVOQe2vtVq6a23\n3rKsBT2d0U0jFTs+PrbiKvYsmkpAIHUQbgEZwQIV5Px7q9UfMPLnf/7n1pouFArZnu31ekqn03r7\n7beNpCgWi5bRAJwTFLHvsSWcd7ewD+BFl4nDw0M9ffrUzgXSI2xGu902GQL2HXkfew57dXx8bNfq\ndDrGnuPP6WTAvdNTN51OK5vN6sGDB/L7/TZQwO/3K5PJmO0k2wP7S/AKTuBeePdIXAjKpX6QMjMz\nYyA0EAgYRsCXX15eam1tTdFoVNVq1YgW9x7ctDtnhRHcXLtUKll9CR0FICrW1tbsnsLhsGUdXJvs\nFoW6Ewzd6+/s7AxkEr7M55UCqRhYNFIcahr6cwjQa1WrVSv4oBUDonUMY7vd1szMjBXN8G8c8pOT\nE6s4xukmk8kBzQtsTzab1cuXLweAF6kV0lqSTCOTTCb17NkzhcNhnZycmCyBSjvSKYAINDSdTsdY\nR3SBfr9fyWTSJmKNjY0pkUgYezkzM2MsJOnsp0+fmq4HEA7bd3V1ZZsc5+EWBJHCRSOKKBu2D1DF\nIaLYgogSAAEoJfJ008+np6daWFjQ8fGxIpGIjo6OLPoNhUKqVCp2kNH0YvDQh5I2p50WIBY2gaIY\n6bptD0CMlluwFKSMKIBotVoDLYdKpZJdD2bA7/eb9uji4sLYYFK5+/v79u6Ibs/PzxUMBo2VJljC\nEJJSm5yc1PPnz007BUsK8MVgttttFQoFawXD1BbWHENNEFMsFhWJRHRycqJ0Om2yEzSP3W7XRvcy\nMabZ7LcvQ/vt9Xq1t7enaDSqer1uDrFYLA4wOJLM8Ur98an0O+QdMemESShkHXCKPEs+n1csFpPf\n7zfWEube1apNTU2Z7tfVVcFCZDIZK3j0eDyqVqsqFovWJxg95NjYmOmXWV8MOOnhUqlkKT7YX/b5\nxMSEBZYYda/Xa1W/rB362Lt376pQKFhhGZo+QBiAORqN2pQ7AIbbHgfduXtekH5Q2IKtouUXRTXY\nSFhLniUQCFgbOrffKNpBJDv8PgEpgQtnBRsHM4t0g6EJ0rWEicCs0WiYBAOmGpAq9Qt63MER2E3e\nCwW4ZFgALVTBLywsWNu+cDisxcVF+Xw+ffOb39TDhw8HZEv4IPwUZ5ZphTh12srRxcDtXeum3SnO\nogsAe4zsF2QM1+IP93N4eDgAMl32zbWH+BzSuD5ff9ofY6dpv+X1epVIJCzDw15B04pPxF5Qk4Es\nABvAGE23EwQ+8e233zZZG3sf+VmlUlG9XlelUjE9NgXPPDOZBAaodLv99nsHBweamZkZaCHGXhwf\nH9fs7KzeeOMNXV31e4IT4JAppFCWQI6hEhAW7HP8tXSd9if4Ojo6suLQbrerSCRi7xVdOWQWUqBI\nJKKFhQXLimDrOdME0Zw1ejTje7B7y8vLOjw8NCkUfpPJXdgmMiluey7s+sTEhMrlsr1jGHjYWYIx\nyJYv83mlQKp03c+NA0E/Tw4fjZ0pFhkaGlKxWLQ0CfoxwM7p6akqlYptprGxMat2x2BidAEbTDdB\nB8cmzeVympycNI0nxRKk7nDm9Xpd9Xp9gGWBTYNBYVwnrAFgjs2LcZufn9fJyYkikYj8fr+lVgHC\nsB+JRMKcDKAgkUjo6dOnxkw2m01zTrAvCNg9Ho/y+bwmJycNRAwN9adf7e7uyuPxWA9PUg1IJLgm\nTgxdKZpXIlqv16twOGypcFitRCKhUqlkabVPP/3UdGdPnz6VJGWzWWOIpL6GN5/PmwMdGxuzoQAw\n7hQmSX1jEgqFJPUdBUzmzfY/7Ll8Pq+VlRWtr69bkZHLnAAgSHvTSSKRSJiuFV2UW5kLe7e5ualA\nIGCFa+yFeDxuvWzdwQO8b9rwUIDF9CDADIyoJAOnOJZCoaCTkxMDgqTCJBlTT9snuikcHx/b3uQc\nnp6eKpVKGXNYLBaNscO5kppnP7i6MJz+2Vl/tODQ0JASiYTOzs4UCoVsyhoBFDosAIrH47GAiH6b\nFFLR/sg19rC5sLynp6eamppSIBCwbgi0bKMAMZVKGSOCrWFP1ut1m1jFbGy/32+ZFZidYrFoDoI/\n3W7X7IjbHo40qtfbH5FI9iAUCqlUKsnj8djACIIR9Kuu1o41pSsB4GD+d9P56KrAO8Gh4sxhara2\ntozNOT09tb6bnBMcG4CKwI5155zB1mFPyHxQnAQbWigUrKvGxMSEtdmTZLb28vLSnC8BJy3VJJlT\nJeVLMao7nhPARTu1tbU1y7hxX9gFZGMTExM2CpcgADYTVqeNMpkAACAASURBVBzgQvr36upKc3Nz\n1vaOwNPVSHI+19fXrWCu2+2a7Q4Gg2aLWV/eKwDbbSvmpqABoQBvQGAwGLTM0PT0tPb3943tZIQq\nfgom022FBFg6PT217AaSFYLT6elpY+k4Q66tBeTCLjL1ijoI9MP4a8A3gSj7gABP6gcnaNK5Hlk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1IyCqB4x/itRCKhly9f2j6cmJgY0PoTJIEHKNCkMBw/TZBNFjqVStmEwy/zeaVAqitGvrq6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\nEGKAA7rOZrNpRZmvX7+2dSj92AHnZzyDvb099fT0mAP08OFDnZ+f6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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "%matplotlib inline\n", "fig, ax1 = plt.subplots(1,1, figsize = (8,8))\n", "ax1.imshow(montage2d(X_vec[:,:,:,0]), cmap='gray', interpolation = 'none')\n", "ax1.set_title('All Faces')\n", "ax1.axis('off')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Setup a Pipeline\n", "Here we make a pipeline for processing the images where basically we flatten the image back to 1d vectors and then use a RandomForest Classifier" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [], "source": [ "from sklearn.pipeline import Pipeline\n", "from sklearn.ensemble import RandomForestClassifier\n", "from sklearn.ensemble import GradientBoostingClassifier\n", "from sklearn.preprocessing import Normalizer\n", "from sklearn.decomposition import PCA\n", "\n", "class PipeStep(object):\n", " \"\"\"\n", " Wrapper for turning functions into pipeline transforms (no-fitting)\n", " \"\"\"\n", " def __init__(self, step_func):\n", " self._step_func=step_func\n", " def fit(self,*args):\n", " return self\n", " def transform(self,X):\n", " return self._step_func(X)\n", "\n", "makegray_step = PipeStep(lambda img_list: [rgb2gray(img) for img in img_list])\n", "flatten_step = PipeStep(lambda img_list: [img.ravel() for img in img_list])\n", "\n", "simple_rf_pipeline = Pipeline([\n", " ('Make Gray', makegray_step),\n", " ('Flatten Image', flatten_step),\n", " ('Normalize', Normalizer()),\n", " ('PCA', PCA(25)),\n", " ('XGBoost', GradientBoostingClassifier())\n", " ])" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [], "source": [ "from sklearn.model_selection import train_test_split\n", "X_train, X_test, y_train, y_test = train_test_split(X_vec, y_vec,\n", " train_size=0.70)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "Pipeline(steps=[('Make Gray', <__main__.PipeStep object at 0x00000268D6B12080>), ('Flatten Image', <__main__.PipeStep object at 0x00000268D6B09CC0>), ('Normalize', Normalizer(copy=True, norm='l2')), ('PCA', PCA(copy=True, iterated_power='auto', n_components=25, random_state=None,\n", " svd_solver='auto', tol=0.0...=100, presort='auto', random_state=None,\n", " subsample=1.0, verbose=0, warm_start=False))])" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "simple_rf_pipeline.fit(X_train, y_train)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Scoring the Model\n", "We show the scoring of the model on the test data to see how well it works\n" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " precision recall f1-score support\n", "\n", " 0 0.50 0.25 0.33 4\n", " 1 0.50 1.00 0.67 2\n", " 2 0.00 0.00 0.00 3\n", " 3 0.00 0.00 0.00 2\n", " 4 1.00 0.33 0.50 3\n", " 5 0.25 1.00 0.40 1\n", " 6 0.33 0.25 0.29 4\n", " 7 0.00 0.00 0.00 3\n", " 8 1.00 0.25 0.40 4\n", " 9 1.00 0.33 0.50 3\n", " 10 1.00 0.67 0.80 3\n", " 11 1.00 0.33 0.50 3\n", " 12 0.25 0.50 0.33 2\n", " 13 1.00 1.00 1.00 2\n", " 14 1.00 0.40 0.57 5\n", " 15 0.50 0.20 0.29 5\n", " 16 0.50 0.50 0.50 4\n", " 17 0.50 0.33 0.40 3\n", " 18 0.67 1.00 0.80 2\n", " 19 1.00 0.75 0.86 4\n", " 20 0.23 1.00 0.38 3\n", " 21 0.00 0.00 0.00 1\n", " 22 0.12 0.50 0.20 2\n", " 23 0.40 0.50 0.44 4\n", " 24 0.67 0.67 0.67 3\n", " 25 1.00 0.40 0.57 5\n", " 26 1.00 1.00 1.00 2\n", " 27 1.00 1.00 1.00 3\n", " 28 0.00 0.00 0.00 0\n", " 29 0.67 0.67 0.67 3\n", " 30 0.67 0.50 0.57 4\n", " 31 0.38 1.00 0.55 3\n", " 32 1.00 0.75 0.86 4\n", " 33 1.00 0.33 0.50 3\n", " 34 0.50 0.33 0.40 3\n", " 35 0.50 0.33 0.40 3\n", " 36 0.75 0.75 0.75 4\n", " 37 0.00 0.00 0.00 2\n", " 38 1.00 0.75 0.86 4\n", " 39 0.50 1.00 0.67 2\n", "\n", "avg / total 0.65 0.51 0.52 120\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "c:\\IntelPython35\\envs\\tf-gpu-backup\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n", "c:\\IntelPython35\\envs\\tf-gpu-backup\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] } ], "source": [ "# compute on remaining test data\n", "pipe_pred_test = simple_rf_pipeline.predict(X_test)\n", "pipe_pred_prop = simple_rf_pipeline.predict_proba(X_test)\n", "from sklearn.metrics import classification_report\n", "print(classification_report(y_true=y_test, y_pred = pipe_pred_test))" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": false }, "outputs": [], "source": [ "%load_ext autoreload\n", "%autoreload 2\n", "import os,sys\n", "try:\n", " import lime\n", "except:\n", " sys.path.append(os.path.join('..', '..')) # add the current directory\n", " import lime" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from lime.wrappers.scikit_image import SegmentationAlgorithm\n", "explainer = lime_image.LimeImageExplainer(verbose = False)\n", "segmenter = SegmentationAlgorithm('slic', n_segments=100, compactness=1, sigma=1)" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": false, "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Wall time: 11.2 s\n" ] } ], "source": [ "%%time\n", "explanation = explainer.explain_instance(X_test[0], \n", " classifier_fn = simple_rf_pipeline.predict_proba, \n", " top_labels=6, hide_color=0, num_samples=10000, segmentation_fn=segmenter)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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csXXnEWuk174KHfWyowwNlXV0fLxaR72rGBuLOnrwYL6Orrgnl0IIIYQQYvWi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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from skimage.color import label2rgb\n", "temp, mask = explanation.get_image_and_mask(y_test[0], positive_only=True, num_features=5, hide_rest=False)\n", "fig, (ax1, ax2) = plt.subplots(1,2, figsize = (8, 4))\n", "ax1.imshow(label2rgb(mask,temp, bg_label = 0), interpolation = 'nearest')\n", "ax1.set_title('Positive Regions for {}'.format(y_test[0]))\n", "temp, mask = explanation.get_image_and_mask(y_test[0], positive_only=False, num_features=10, hide_rest=False)\n", "ax2.imshow(label2rgb(3-mask,temp, bg_label = 0), interpolation = 'nearest')\n", "ax2.set_title('Positive/Negative Regions for {}'.format(y_test[0]))" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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2rpk9aoR67lD67Tozu8HMPmNmD2hI9wgzO8vMLi9tutTM3mtmpzakPaO0eYuZvdrMDgn3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PbZ3TVdAOzPUo46++D7Df4zeKha3J/voLLzu51suQ+WNVPiGfO8k6FlftD67bMwRglUy6kDNcae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\nUeb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T6/W6Tk9Pp4HhqI/llAbXsnFdkdPT09OUL/IjAp1K5OXXaSSdRpF5G3wbBeTNrKLl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\n9pUB133a0VB5WC6X0y7lp34dEBUhy8Hpza3N1w77iHR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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# now show them for each class\n", "fig, m_axs = plt.subplots(2,6, figsize = (12,4))\n", "for i, (c_ax, gt_ax) in zip(explanation.top_labels, m_axs.T):\n", " temp, mask = explanation.get_image_and_mask(i, positive_only=True, num_features=5, hide_rest=False, min_weight=0.01)\n", " c_ax.imshow(label2rgb(mask,temp, bg_label = 0), interpolation = 'nearest')\n", " c_ax.set_title('Positive for {}\\nScore:{:2.2f}%'.format(i, 100*pipe_pred_prop[0, i]))\n", " c_ax.axis('off')\n", " face_id = np.random.choice(np.where(y_train==i)[0])\n", " gt_ax.imshow(X_train[face_id])\n", " gt_ax.set_title('Example of {}'.format(i))\n", " gt_ax.axis('off')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Gaining Insight\n", "Can we find an explanation for a classification the algorithm got wrong" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Using #70 where the label was 11 and the pipeline predicted 17\n" ] } ], "source": [ "wrong_idx = np.random.choice(np.where(pipe_pred_test!=y_test)[0])\n", "\n", "print('Using #{} where the label was {} and the pipeline predicted {}'.format(wrong_idx, y_test[wrong_idx], pipe_pred_test[wrong_idx]))" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Wall time: 8.75 s\n" ] } ], "source": [ "%%time\n", "explanation = explainer.explain_instance(X_test[wrong_idx], \n", " classifier_fn = simple_rf_pipeline.predict_proba, \n", " top_labels=6, hide_color=0, num_samples=10000, segmentation_fn=segmenter)" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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9IvuJ+wUqL75fzHiz4+ew4h3mxjYJL9bB8ypv+LCijP9ExPN0hhG3Xz9vBMYh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5AAAg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OPG6cKYMu3iTuI4MlMyxTpmiTA01c72xG2s3Oj+nqsNNoXl9eXk5p8RcXF2tbV/BR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\njgmejIt4tgXcZTZb0s17k4A5dG/enxlwzURmtqX1f0b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FQqFQKBQG8H/X4pBP\nWZKxSgAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# now show them for each class\n", "fig, m_axs = plt.subplots(2,6, figsize = (12,4))\n", "for i, (c_ax, gt_ax) in zip(explanation.top_labels, m_axs.T):\n", " temp, mask = explanation.get_image_and_mask(i, positive_only=True, num_features=5, hide_rest=False, min_weight=0.01)\n", " c_ax.imshow(label2rgb(mask,temp, bg_label = 0), interpolation = 'nearest')\n", " c_ax.set_title('Positive for {}\\nScore:{:2.2f}%'.format(i, 100*pipe_pred_prop[wrong_idx, i]))\n", " c_ax.axis('off')\n", " face_id = np.random.choice(np.where(y_train==i)[0])\n", " gt_ax.imshow(X_train[face_id])\n", " gt_ax.set_title('Example of {}'.format(i))\n", " gt_ax.axis('off')" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "tf-backup", "language": "python", "name": "tf-backup" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.5.2" } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: doc/notebooks/Tutorial - Image Classification Keras.ipynb ================================================ { "cells": [ { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "LgSzX-nVxwkV" }, "source": [ "Here is a simpler example of the use of LIME for image classification by using Keras (v2 or greater)" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 54 }, "colab_type": "code", "id": "_KS7nU0axwkY", "outputId": "21a4f2b5-120c-40bd-8ea1-b73edd8bce0a" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Notebook run using keras: 2.4.3\n" ] } ], "source": [ "import os\n", "import keras\n", "from keras.applications import inception_v3 as inc_net\n", "from keras.preprocessing import image\n", "from keras.applications.imagenet_utils import decode_predictions\n", "from skimage.io import imread\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline\n", "import numpy as np\n", "print('Notebook run using keras:', keras.__version__)" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "w-eyXVAHxwkj" }, "source": [ "# Using Inception\n", "Here we create a standard InceptionV3 pretrained model and use it on images by first preprocessing them with the preprocessing tools" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 74 }, "colab_type": "code", "id": "GF8hPe1Rxwkl", "outputId": "fdbae3ad-ddfc-409c-bd3d-3ed8ead94a25" }, "outputs": [], "source": [ "inet_model = inc_net.InceptionV3()" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "colab": {}, "colab_type": "code", "id": "GaQ0zT5Txwks" }, "outputs": [], "source": [ "def transform_img_fn(path_list):\n", " out = []\n", " for img_path in path_list:\n", " img = image.load_img(img_path, target_size=(299, 299))\n", " x = image.img_to_array(img)\n", " x = np.expand_dims(x, axis=0)\n", " x = inc_net.preprocess_input(x)\n", " out.append(x)\n", " return np.vstack(out)" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "26Le95e5xwk1" }, "source": [ "## Let's see the top 5 prediction for some image" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 398 }, "colab_type": "code", "id": "3sxO8vzlxwk2", "outputId": "82b2b75b-6bd8-4fab-ea2c-5b365806fb9e", "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "('n02133161', 'American_black_bear', 0.6371605)\n", "('n02105056', 'groenendael', 0.03181805)\n", "('n02104365', 'schipperke', 0.029944215)\n", "('n01883070', 'wombat', 0.028509509)\n", "('n01877812', 'wallaby', 0.025093526)\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "images = transform_img_fn([os.path.join('data','cat_mouse.jpg')])\n", "# I'm dividing by 2 and adding 0.5 because of how this Inception represents images\n", "plt.imshow(images[0] / 2 + 0.5)\n", "preds = inet_model.predict(images)\n", "for x in decode_predictions(preds)[0]:\n", " print(x)" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "collapsed": true, "id": "_MCRFeNJxwk9" }, "source": [ "## Explanation\n", "Now let's get an explanation" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 54 }, "colab_type": "code", "id": "aP6LjonHxwlA", "outputId": "07b6f31d-5207-4cf8-e75f-500fb3f8c939" }, "outputs": [], "source": [ "%load_ext autoreload\n", "%autoreload 2\n", "import os,sys\n", "try:\n", " import lime\n", "except:\n", " sys.path.append(os.path.join('..', '..')) # add the current directory\n", " import lime\n", "from lime import lime_image" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "colab": {}, "colab_type": "code", "id": "2b7ow1YtxwlH" }, "outputs": [], "source": [ "explainer = lime_image.LimeImageExplainer()" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "3ADfGCzxxwlO" }, "source": [ "hide_color is the color for a superpixel turned OFF. Alternatively, if it is NONE, the superpixel will be replaced by the average of its pixels. Here, we set it to 0 (in the representation used by inception model, 0 means gray)" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 104, "referenced_widgets": [ "1fb1b32b563b4cf2bc565e4f150d5886", "17bb7656e07842dda40e13da228550c8", "3b0b05ed4a1e4a7492bad6d208b005a1", "30f68d0a496d4e97a5f9e59b6fce9f5e", "bfe238fe53be4860b53021934755f0b1", "f7d2484df9f24bceafc1910e361bc03f", "059e79101bc04a6dac3d6c8065d5f960", "e8a5f1d84d784fe7b75b1b965aec3fb8" ] }, "colab_type": "code", "id": "1L0lWZ8yxwlQ", "outputId": "ee3a3678-bf31-46ba-dec4-e098c9c55eaa" }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "faa50bde7a254cb7986a81274c778be0", "version_major": 2, "version_minor": 0 }, "text/plain": [ "HBox(children=(IntProgress(value=0, max=1000), HTML(value='')))" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "CPU times: user 13min 8s, sys: 1min 12s, total: 14min 21s\n", "Wall time: 38.9 s\n" ] } ], "source": [ "%%time\n", "# Hide color is the color for a superpixel turned OFF. Alternatively, if it is NONE, the superpixel will be replaced by the average of its pixels\n", "explanation = explainer.explain_instance(images[0].astype('double'), inet_model.predict, top_labels=5, hide_color=0, num_samples=1000)" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "5XAf25PNxwlY" }, "source": [ "Image classifiers are a bit slow. Notice that an explanation on my Surface Book dGPU took 1min 12s" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "uWl908SyxwlZ" }, "source": [ "### Now let's see the explanation for the top class ( Black Bear)" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "WXMdU3hwxwla" }, "source": [ "We can see the top 5 superpixels that are most positive towards the class with the rest of the image hidden" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "colab": {}, "colab_type": "code", "id": "rgs3IwZnxwlc" }, "outputs": [], "source": [ "from skimage.segmentation import mark_boundaries" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 287 }, "colab_type": "code", "id": "5LJMsp3Oxwlk", "outputId": "64b82262-8a45-4232-e844-2e15c5fc2d09" }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "temp, mask = explanation.get_image_and_mask(explanation.top_labels[0], positive_only=True, num_features=5, hide_rest=True)\n", "plt.imshow(mark_boundaries(temp / 2 + 0.5, mask))" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "aAFdw9oJxwlr" }, "source": [ "Or with the rest of the image present:" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 287 }, "colab_type": "code", "id": "-6eei5uQxwls", "outputId": "a9f29754-15aa-43a9-a64d-493f1f01dea2" }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "temp, mask = explanation.get_image_and_mask(explanation.top_labels[0], positive_only=True, num_features=5, hide_rest=False)\n", "plt.imshow(mark_boundaries(temp / 2 + 0.5, mask))\n" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "y7aoh_OExwl0" }, "source": [ "We can also see the 'pros and cons' (pros in green, cons in red)" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 287 }, "colab_type": "code", "id": "jHow3M4Oxwl1", "outputId": "7cc10571-84aa-4e8f-d6cc-80a56cf7d054" }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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otdyntUb0QvTlHHHNoDtZd+FIKxVQdMqjjCOEmVoWAlMpSDFTU6LYDmU0TUMTjWkOmkY1R+8LO9ky1bAikEiqiaIq0xQY9yd2boNTDlJDyYJefG9oBJxbiMFSEmI0tIh4i649dj8Tc+I7+EIGLAu0VAiFK/Y43kBPARyZGSgc2RNhha0bOnoUhnM2y3tqjRIjShm8f5oiCj00fDxSr+8RdWLQhm3XYXyHtTtEK2LYo7zG1j22aZxozt1z2NueFy9vMM3XdNqQp4SzinYqWOugJVKFgS03u6fYDB1u2tKq40wiYnroOhoa151hWsaaDTUJrttgbIffOCTMKKPItVJLxHRbpsM1tRRSHHG7m6S4pAMWT1ydcV6JtQFNYqRgmHmOCwYsnryW5RqFiUsKFQVUMoXAjKVjoGNYXV9TWbgqR0cj0UjMzHj8WnJ0mNVhZyKs2K2tZdqKo65OswToRltRw5HMBkthXlODkRMPqFzgcO/T/V4TQaC1Ruc8OWbIBZRiOo1Y7wg1EC7vMXQbSlYor6mhkHNedgFbqanhtOMQJ5ooQlmidCMyhQmtFbkKumRcv6GWTFEJJXZxeOMxZJpappnaEGWouuH7npASVskCywWsboQQGHYL41prJZeKUoYYIyEUWlpY9VYht6V0WVrFKIMzHtEGWz2TmUAKITWc7sm1ME+ZNEaGbkNKlZQKIKQaULagVI+2msFuSDEQQiDEI9fzzEXbkRtYUXzBp30b38HnrwmAJRCZmchEPBqPkMns2aPJVASDZ8cFjh6hsuWCj+EzAJimI7RCaYLSnqY9UhI5jWjjybPAzYY2T3Dz8afBG45xRo6aKZ5Q4igyMZfERX8D9MwtueZwdYaWE1M1hOsT2oBVO2iGrvfc2Ow473uc6hhuWFQJ5BKpomhYtPWEknHOkYuQJWP7DusteAW5go7kkvEousFzORlUmalNaAK/5UP/MP+Mv0vPFScmKic0liXUGxSOSOLISzRuMNAj9ExMTBwwePQKxRU9e+4RaVQSCktPj6UjrdQkLJA+cLXWAgKGnrIoSSgE9kyAxmOYOBAwFAKRhqdnpmIxZGZmCooT97nPBWdAYMuGzDWFhMO/T/97zQSBaQrIKt5wShFDIswT4i3WOk4hgBL0CAaHMpoQT8xxyXqOpxNNFHmudEZDhsN0wvUWEYW1PVY1amxUZ3HiKDLjjMWIIjbBVIgaJCW6XqhNU0rCKQ2tkGxD1UTJBtcPhJhRRpNLxmhPToFaAqVlmsAUM713GK1Jqi7Zt1SqEpSqzPGERZHThO4UqRSm2LhMI4WJWhRea/YP7tNiRW06zh/bEBN0aHRziCgKlUzklB6QrwOb4TH+7U/6Jr6br2BHQ+NJRCYCkYTBceKaicLAQGEmE3Gco9lS6fhkvvyfe0c/9uPfRUhXbDcdRnpySMylkKThtWLMhXNXcOGci96i9QLRnTlHthPjvnDoI2fFsfEzpffIlOk7RdfPtHmDHieurmbU2Oi0pd9sOdtccGYfw+stxltKOrFRliknEgrnOoIxWFGkcSZUhevPCHUio7lZHWJ7krJo55hKRCfF7//orwbgr/FVfCpfCoCi4nAMZAqOCUXGcH9l/g2GDodamRMInDgSOSF4HBdsuQUEGjcoXKJxaDZoFJ4NcIlii+FirTcMTMwMPEVmInONZ2DLlmtOBCIHMoodnpmKYOmoVAbOgAR4zhBGXsZzgdvsEAK3uYlh5P25+mumizCVTGnLrhfnuDDejUWAkzK96Wgxk2MihLDQL3UhjXJe1Ho5BnLOzOOJlBL9xmOswhjLOE3knJYysQjGKDplmcIITq1KLtDaYoxhfzgQQqDWihGA+kq9vVZENE0pYs6IMpRSqL+sDyPmhLYGlCzwTTRKG4xVOKPW7yfEeaLWjNaKUjItN1Is7I8HvLdIKzgDOU2UlYDMOVGLQmtLbm1VyJlFLYcmzHkZJ+DoUStIXWB+T89uZcDbqnirZDIWh13LUwA/+L/9+Yffx6Lofbe8k5xJuZJTJcfEeJwI0zUpxqUenheNRyiZWBctR2sNaiM5wz4XEEcxBttZvMsYK0TG5R3lQqvjouwTwXvLFGdyLswl0WqEuhB9YYpQFr4opUKMMyEt2oxWMrWkpRhXMvM8LxUbeeU9mZXveBvfuxb2Fs1dZkZW3WpBYVZUIBgimQrsmVct3wLxM2DpaTgMGxwXtFVDoFiI5Y4zHBssHrVQvfTcRtOTgUTC4leAnx++C8FSscwEEnHVIhYsmg1bMnmlKBcivRIw60gqFfvaRwLQRMitIFZTIzitacKSeys4XB+pLaL1Iuudx4zWeqmrC0wx0FLCOotTO/aH+1i1MLq6GYadx1QQbWhVqCLofoNLBUkJbx3WOXJMqMHR9z1SGy3Ni6RVKUzTpFrQTpjnI9p3dMM5KWeUUqSUyKU95BSy0msmp5AmNC1ooxispVDpN7c5HZ/BKJAKtRyISUOzVKmc5j29LKU24xVWd7SsqKYSYsFoQISQCiUlOn3OH3rLtzyc157NQ45foWgIHVs8npmGAAfuAwWLZebETH5IKs0tPLyX1hqpM6DQRoj7EylDKjOxHSEe8VmhQyCWS/xmx0kswQxIHJEa0TUTUmHob3KsR1rnMe1Jdt1I3VaK3rI/FsoYUTqT1cihnlBxT22KqwcP6GJCl9Oi9YhQQ+E0jRzGK8bjxMXNDcQjkYKtigdZ86Td0RlLKYV9viZG+/B7FeAH+FPcYk/HFkeHsGXixXW3BzAUFB2OxB7B8IAD19wnEXBs8VxguInnbFXrRe7zHlh1A2Cpa81AcxPFdql4rBxAJKE5o+fql0mEyyoMXmoHGk8gI4BmQ8cWxYG8Xn9kpOI4MjOw40kuEIRL5rVK8KvbayIICBBjxGpNzRlrLcfxtIiItKKpAqXh7cBcJoxThCmirSFMAW/NigoaYRqpKWP9gNdQtWCbUNNEMQZdhdoytWp8W5RjVQuyyjeqKZSSQDTWW5SCkGZ0tdTphNNmUS2mQKcMIZzQ2qNEyLVQdUMpT4gT2mhs39HEoJwm1JHBOQbniSpiO4869fitZd7fYz/vEfGkKKSUkGrYOEPKAWPAqw6jHdoFmjbMuXJ53BOnicFZ/t23LJXYH+Yv8RJ3aVR29EAmoFYiqeBxJEYES6NDA4URA8wcyRz4S/yH/PHf/fUA/JP/6/toNtNJRz84mgjH6yObThFmgzRFLgZTMnW6JtmOlx68G2m3SfKAWk9sOkOzBu8sKEWTHdS89FR4y8ZW4mi4eVOTNgotkdYpxBhO6Ug8nZj2e3bNcLP3zGmmGUeSTMvC6bBHt8rpWHElEXShJEEsBNvTS8fO7QitEFN5uPYagmYgre5UqJzINAyJiYZhZASETE/POYmZyJ4Tl2QKZzyJ4FloxWHl6D0DHXbNzw0QCGy4hWWLxhG4RnHOgKERgYznAo0HCpc8WIU+Pdcc8ZxTmcgYPBc0Nmj26KVOg6VD06+IpkeADQMTmvZ+XP01EQQaDaMUNRdKKYsKcC2xpRKp1UATkEitcJhmnPGEOdMkc7jcU6oi5IAyetGhayFLQZdF6un7jlTKovOq7aGkWMHDZhYRoTcduWX6jaekvCgVrcOI0Du7wvGMN5bxcGRz82yBjLktzTRNmKdEN2wpVQghYf2CWIZugzdtCXZWEVMhlEybAikfOc2L+kv7DUYVSpwINeKV4M0FfrNZ6vJaUGKY48w8jSgpxPhKZrdA/iVvNOsrPuOMmQOsNedEoKwk4Q5P5UTCkIlkNIpXdstQI53RmLbU5cUZtpsdpWbsTlP2I4PdIvMR0zxjuSS/oFBynzIZ2GryjRvcuHmLjdtQM9wYbhFrxnYW3a44xj3Z9Gy2huQgqSPVCblGwukupwcHYpjYbXckOqpxiLZYEQqazhmgYUwFyaSUabrivWWcTzQjON3RqOSyKCj/Fn+emTsrYirrWowrhz+vjTmQMRQKM4nXc4GikWkkNBrIzGR6hISwQbNw9xu6tcpwIiGrEmDR/RuWhqm0ioOFxDWXnCMYujVR25GpnBA6zrH0QEfPjmlVHE44Gic0PY7FoT23iMxsWHqFNmxW3Per22uGE5jHiRQWuN9KJee8CoiW5py5ROaSELd0x03TBLIECu/9kiaoZcHX9Ucbs3SftUZOFUWl1IRRSxkQwPtFkNRkuV4phVaWXArKGoxZRUIr3G9UQki01thsNuRaaApiDgsvQMN4Sy4V6zuM82v1w2Lty0KfTIwzIEu/RC7M80RuFfSCimgFJQ1FXUUu3cN+CiWGuua/KU+UGsk1P5zLJTe1q2p96RVYclBWJqASCFSWfPmw1rcXeNrj6EkU/lu+eJ3PpRpjREFppDmSakH00kWoRGNUj9E9VI20iraaFGZS2WOl4ZVicB0lFIwYSsp0usOJW3ZR8SBLMDZW44ctoEg1YRp03iK1keoiN1bOE1IEwCjLxdk5Q9fjXIdaOZql52Mpu1YKVaCiqetczUwUGjNpFeRkGplCZhH9zCgmhLCKcco6H4KhZ2BLwawdAW6VEgv9GgCW7r9AR49DkcnUdZZlTRMripE9MxNLj6ChYZnIVDQFDXgsWzwdjoGO84dcBhgaFc8FZ9xeg8UGjaOnZ8NNNgwIr6CfX2mvDSRQK11vyGlpDKqlUcpSg7WDYa5LrIyHkWBmvOlRtZFqoNZMrBkxlpwyvfZ4VZnSiWos3lliTFjXo+cKDbwzaLvktihZUELOaKtQxuGsZ44nUk10xqKUIUtDL+QFxnqKKNLLfcmiSGtL8Mv9BlUUTQypJDaD4fy855gDylRyKeSkGOeRKZ4I87Ps43NMQXCSaVi8VlgjaJ3JRUh6wmDIMeF7T2ZgngohjATJGB0fzmck4dnSA4ZMITGyBJ2K4LngCW4xMxHYo7leNeodIHR0ZCxp/UbpGGgUNrstSjROG+qcyVJJecRaD82zeWzH9eWLjNOMGWdunz3GqSZ225sM3RkeB9Vxa3NGbx5DWcs0HfH9gE49Se9R9ohShSyNOp8Y4548dbQCu/Pb+GFDjAFOI4hijImuP2NrPG57wVUMHHPAu8qY99QszKrRO4uyHaYdmUPiL/8fX8kf/YQ/DcD38LVsgQMTS+Fu6Z/ssVhk1ecXHIYLNkS23Kehyfi17yKubMpA5RYbApmOxhlnRByFsCoBIJI5cBdN48SBZ/glQDMwcMZT3GVmxy0GPEf2gKdnRyNi6FH0nNNzRU9iAm7xGB/MORfMFCZGLnkv0OHZAjc4vZ8g8JpAAktHX6KkTKWRNQwbvzC6IRLWfoDWGlogxplIJra01IZzJddE7x01JuYyorVZst2XWeTjiPUdqgr9Zlg73DzOe5pU8ioC0i2jSltlqYs4SNOI82HZxRtoLYtgqDW0saRUaMZgnEcri7Ee63swiq5zOG85jAe0bujOrjVsRyiZcb7L1I7EGFCqkmsjhchgLEoXpnJgjBNRRe6F57mer7h7uKIJGLtZ2O5cyPX4cD6PHBACS3f/cjqAADMVx5aGx7DFcYuOx/A8yTlP4tAMXCzwmoFzbvJX+SZaiuQ5oHJi3o+M9+6gZoh3LonzNaok7rzrhL55i30442fedpft408s2gk5R+VKDTBOcHbrnK3ZMo1HxvnI2eCROZFbAtmgxHN1qOwPJ+ackLGjTksFxjRDSJUpJOa0B7MItWYSvVkqCVprUqtMYSSGQk4w5sohLULbFAL3p/u0WPjOv/8lfMsP/2GEibK6fsZR0Gx5HI/HApaMBW7SYdlQyVzwGIoLNvQUDgT2COBR9Eu4pqejg3XfHzBsyByZOazPGtnRcUKTWPoVxiVhJWCYGXE4OjqOTCuSWBDEwhWc0/MUjRtsGNjQc5OnMFg2a6OUQXNGx4mr9+l/rwkkgAjTHDmOM7vdGSlmYoHaFDUlagNlF4hHFuIqvNEK5jQtLH5ZlVVK0yuz6M9jRGthMJaGouaK65ZmH601tImcLSkWXGdoSijOQyr4vud0OjCXyNBvkSbEsrQDzykjSpNEsE0tB1akpW6O0li3QZSFUvCD5uLigqv9NdpDawnbCUU0uQVyzRjTMfTnnO96wl1HypE5J86845j2DLsNsUZivmKfMjo5uvj6UBwAACAASURBVOGD6LoO73rmcI+cXkECIy/xBK+jER4eDpIRejZ4LOc8QULwCAGDrE2sliWA9PRo9NoCI3zS7/kS/hf+HL9xOf6Bf/zD30idA7FdwaGnqJu8/Zl/TFEDP/JDP0VUMx/0C/d48kPeyLl3/PhPvp3f86m3eer8FtOoeU/c0513tClw+XzAnBVe/69+NrfW8f+D//W/ZBoi016Ic8XVhJ8abugpJTFPl+TYkfMDcjV0cov9TnFKd0hnA1YsGYWUyhyu8bOnmnMuTxMPxgNqnhnbhPWar3jLX+V7+BpmIoqlz1Dh8WxQnDBUIpmb3GDDbmVMPJqBLXtOjGt6oElMZAp7Rjo6bvMEl9xZhWuJzMzlKsy6zRs5krjHPXqEjJAwVCyVW0SOJDwezc/zi9xiw4YdOyo9mpFIxw1G7q6cRY9G2DOj2bH0DggnMobAnvArve6hvSaCwHIajMFteuYYIAmhVsY5sd0O6FKgNlznmaZAXnvZRRoioJKglcIohVGaEGdEgVVLs0UpEdt3iNLotpyUU1tGs/Spa1XR0jBiqceIFkMoid1wThVoomiy5Ma990vPgrUgbSnOtIoRQzQVbR1iPbVAZy23b19wuN4j0vCd0Pc9IUS0roQ44zsLrXGjv81T245iNA9euOJSTuxLwZkeJYZcCqd4xRwiMSoep3LTbrDaE2yl8UrrtF8bViqWROW45rMGw4Yba2V76Ug39JwY2XGTgds07hC4YmDAc0Yk80N8K4aJH+NP84l8A7/1k7+OH/2B/wxpA9Vb3vXMHX7bR/8G/u73/VPee+c+H//xv4H+sY/gh/7Hn2J87zt4+nd+FD/0PT/P7Q8PjM83nvzIHUNo/KN3vZNP/E0fzmd89sI9fBlv5U1c8CX/xlc+/C5/5Xv/Y64K3O4t+TDikhDmhkknYuk4jQ514x73npn5g5/3Tfzg3/k6ymBw4UB1O3KOKHOB6XpSnZD5SG2N09VItoo/+7c/i6c/PayVgBnDIrBe8vGMXpmATFqz8oE73MOiVzZhZuJET4djw9XaqvOAyhN4Eo7necAZF1wRGDkSuUKw3GM5u+BFXuIWPXsyiRcxeG7RMXPk7byTD+dDOHGXI5mB13GfuwxsmFlasTUbrkn0DDQygZmOHTOayMgBxb+1BvBfzV4TQaDWugg5FJj1YJGQA+rlTr+ccKZbRCdKUQuUthzcodXSU6BqXQ4hUZbKeqBGmNhstqRqiTmzHTparNAUu80Z0zRRc1ogZCwUyWyHcyjgrSPVsghxxGCspbVlnMZ6OtfIqUCc0crQiiwtv8ZS26LzLyWxHTYcro9osxxYMk0TfT8wxYCoBLWgpUFpnG1uoupM3mwZ40x1CmFAcMS0MNp67ZIsLEd0dd3AKQtf+Sk/9MtmNPPyYVhh7XcrFHo8hYDgmNadyWBRaAqNDGy5oLHoASqN5VCLjkyiPaybQ2rClCZau8lf//7/mbd+0cfyfz7zc/SSOeTGM++4z7kZOMgZLz5zh4963Rv46be/B9Vvecf/9A5aK4wp8IvFLadNAM9zh9vc5Jv5Og5MHLnLt33ef/Uvt5Zy5tN/1zfyV/7GF2PLogHcbTzzYeZwOtBC5TBN0DSn6xObbcdIwGDQWDSgacjq4moRfzMyE4lYIgZFITEzYnC49fMbei65xCA4PAnDSGFPoHJcw7JQsJzY827u8yY+hPRwBxc6CpbKNdMivEJ4N88xYBAiV9zlcR5fjzmp6zVLMnOXK+waBjSOmYZhw5Fn3u+cvSqnDf/L2s2bF+33/q6PQ4yQkqCbYqozXRVSbUhnUKnhh5668hsxVfzQEadrNt4vB0sI9N4TpnEp+bVM5zparWgE7wteb+i1p+pCqZXBOOZcMM5SVKVKZcsGYxVFEtlUnO3pveXlk4HMsEVbj2qaajVKDKVVnN/SROO6Hms1hcLFxU1SmSmMKF258dgNtFTec/0cdb5ivH4OaYYn3J6P+dCPpciW+w9e5D3XL0B/wVg2dHT833d/hgfzfWJd1Ihvev0n8IYPfpw8X/Kpv/kVie/38sfZoHiKj6Bn4B5X/D88R6TgEDo2KBRX3F/pL8UTPIbjMXa8Ye2Zu6RnB2vvWeTE0u+u+BTeyjd9yxfzevNG/tb//k+4vveAj/m4N/Leu4V3/dSP0zvPnCJeGSgTrRb8U7c4Lzteur7iav+AVDJPPv4EpoHVllyXXPdHfupt/AF+B0vXBSg6zrkg0tjQY1Gcc8F9Lhkp3KLyPA94A09zjyO36HkjhufZ8y38jX9ujX3XX/9mnnjyNo2Jd//SO/myf//bAfh6PhPP69nSOGPLixw45waZhnBCcw9LYaBxSeYSy2/ktzPzgB7PFQ/w9GzZYunXM5kaBeEWTyK8yNv4Gb6W7/z/rPsv+vJ/h7/4rT/AJ3/Sm/nEf/238fV/6r/hv+dLeQd3+Nf4aK448KV8I1/DH+GDuOAuRz6Sj2CDIrLlkis0Bo/DkNlROVLXeoFwk1u8l0s+ly/nLb/j4/kH//Afva219uZfOY7XBDG45NSVNGW8aKRlemUYfIfrBjqxbDabhyKP1hq+c9RU2O12zDEsx11ZzxgDTZYjp/p+IKeE0hqz1rlt11OV0FjKgwCd97SaiXEh+5ouNNWQBp222Ar5lCmiKFoorRFjJOeIEbM0FVm7qLxkUdcZ79DWcJovyWWiKcVgzKLxvrxPThFjDE52yPEez6czQtVQoPMbnBK21nL78adxZ7fo2xmterwe8NYxTS8ynhKPdzf40Z/+VgC+mz9I4JLAESGyW7oxqEwEHjByInAJjCROjFySuWLPHeABV7xEW0uHe14iMBEYmWkceYFP4a0AfOjTH8Vf+76/zb0XnuX+g2d59y8+y9v+4d+nSeWFOy8AMB731Cb43ZZN8dx56TnG6UDKAecNh8OBB/tr7t+7S42B/eHAJ3/Mm7nkLnd5wLx28r3A81T27HmRF3mOn+WnGbnmmvu8mweA5e28k2d4noENf4+387O8m7fwW/g6/j2+ga8C4As/609Sy8C9+3B9BV/9zUtT1J/hb6JpfBnfTgO+hu/gi/nP+Y/4M2vTzoILniFxYsaw4z7vXZUEkYlET48g65gDe/ZUZn6Mn+Cf8ixfy3fy+V/wB/jcP/KZAHzVf/qFADz7tl/gsz7hE7h58xaXalnbX8C38xf4fj6Pr+ZL+UZ+/+97M3+O7+GtfBvfwHfzWfwnvIOZz+ALueYuwnK60BbDzJHIgWe5w5HIz/JTfC5fzu/97R8P6X3rBF4T6QC1sekXCFzKwmfrJoQQkH4gxJkQEsY5Ukp0vWOKCakwz2t+3oT5NGJ6S82BWgXs0j5ZayXXTOccJa5EoxFizOy8J+S0nEuolzp1o4Ash486MaRU0KYDFGOIbOzwsHLwymnFYM1y6MlS3gREU2tAG4U2jt5qxnkRADkD56pD37jJfjqgpXAIMze7gf+XuTcPti09y/t+37iGPZzpjt1qSa0JkRYghgAGHGYMtplCYaocJmHHqRRhEBVsCKQcTOzgcqoIReyAQhkcMpSTqiTGjsvBQGyCbBCqGKOW1KhbUrfuvX3Hc84+e+81fWP++NY9goKGsoGqXqeq+wz3DHsN3/C+z/N7lFK0dgmixqeMzIbKrggXbtY/WPbdBWEK5KbCqpr/891/hfC5H5yLgRGNJRLmTUG5zA2GBavZve7R6Fl7XtOzIdEyUBBcGkFHRzXDNWouAPhL/+G3sV6/H4Gi321xKWKrA9bVkvPzhyzbBckHRl8YeaLRDGdneOcIAnx0WEz5OAQOlwuUkEzTxF50vJsP8jk8QyQzsccjaYEBh6IiMHHOhn6GeAoqtpxyzFW6ufJxwUOu8iQdIy/yG5e32f7BKR99/wsMsSNmxX/8Pf8+wkz8nb9ZVgV/gb/Bt/3Vz+VI32A/bvnJv/7fA/D3+V7OOMXNdZSP8oAbCA45wRM5p+MaB2QmLGs8p+zQ/HX+JgB/7qu+iDv3P8y7f63AtW7dfcDTN27wts9c8ehOzxuvPcHp+2/xjm/5WtL5Fnv9Ou/5l+/hza8/4dozb+Rrvrxi33V84ie+gR9/1//Of8r3A1CxJKD5i7yTn+AH8ES+gx/hx3knE55v578FKEK6aXjFx+9VsR24cnKUv/JPfWFZlktF7wcOjCUjiRli9GhdwCAgQUbq1QI/OULXFfKvEBgBWafiIdAabRXCZRaVJSeHki1SJFTTYJUsNGJrkEIQBTiZcTFwuKwRqZh8al0zhYhuKnRdgRFIs5wFSgIrFyQFQkkqsyYCzcKAKj4FoScknkUtWJqW3u2pRGSxlIR1y+bhPbbDlq7red3JMatFjUYSUss+WOr1EZvzjmdf+nWGsWPynm7c4SfN0697PW977Ws4riXOe97+qaXA9t/xJ3kjn0fLmgHYsWPHIwBu0gKRO9xlYE1GcoJiwSHdrFLPKMTc237EBd9BeUg+963P4HXGkDg93dEuaoacMVkgxUQ3eGpjsUYhM/SxiHSqqmG327FYNHg3YqQqJpcsyFJQa8N+1yOU5AO3X+bTeBMVDQXxVfDjRWdXs6WnoaahYqLgN0GxYYMkziadltKYK0i1K9zgkGvAkr/HTwHwlX/mqxF+xxNvvMGzz36Im0cHHF05ZvT3eNQFrl9d0J8HUrQsr3f89N95NwB//ls/j//5Z36FH+W7eCc/BsBP8t10VHzP/NC/4zu/keFOwLsP88EXN6yFJbmJJ555I7c+eoftdsfJ0SF0jhzh6OkTFoPHHgse3t8is2TrJCF2nBxcxY0TDYbXP3XIS/f2vP7Tn+Rv/9j/xjd/xRdzdzvyxmdey0+8638B4L/8ke/jB7/vRwD4mi/6AoYMx9WKBxdn/NKvvvv33A68KlYCOWcGV6Ai+4sNi+WScRyxdUOKgVrqYiV+3AfGE2NkmgYUFFWfcyiVL52FhTwcWFdLUogoLTHGEOJAmouNUhQ+fU4JHwpNJpNxwaOlRcREkDNhOFO+mjJELinIUkp8CFhTCEXSGIxVRBJVbRn9QIiOVbUmu0geHGpdIWQkiYSqWqrJk5sRKXVRyOkC8xBG0I8enzxSBnzoySiiE6QAbuzZ93tWqkKrj8t8DTV7ztAoBgyegEayoiXNxlaBQyNIKCoMCjH/t/SgExqH5Dv4Yb7/276Wf/xrzxHHHpVhkBmhBdMwsl6vOH+wQVYUFWN2CDQLWyNzJsZE3E8Ypdnv97RNhRbqkq2QKWTpG9ev8/CssBAlEGfl3sTAAUcIMmecsmSFx9HTcUBLZMHIdrbZgGdiJHLMCY4dgkDPyIrAfT50eY7uP3oJPfWYaolBkaThve95jqtPnxA6gbxmePDyQ64fGkg1X/91n4c9atk+PAPgnfwY3/yNX83/8D/+Ax7xMj/A/3r5s1++9ZDwUsfd6S59nzluNIOOTLceENxIO3mmTcc47Thpj/GP9nB1zcN7G+RomBaK7fYR14+PGAZP9plqLbjY9Vy9fshHP3iLL/6kT0RUp7zhjU8z9ZZv+lNfzvoNJ4x3P8w3fct/wPnDczwb2rQgaIX8uKD0dx2vikEAyrgdhom6WaCswpoFIiRM1TIMHQJNZQyZSM4aFQTHiwNCcETnsVIgRam9WiMIoQgl7KKCISBiJoQJaypUVZFSRopEKqMIOkmkLDJk530hEVcWoTRjKtx/rRQISWUUYWYT7seJqqkJUVHXBfpJDjRKMvkdfhw4aCyf8NSbef+HnmNlNGsUumrJQbAjYlpNGpbs3Ja1WtMagxQeIzTbrue82+KmSPaGoCNSVYRzx+n9jjOxwZ4cYque33jv3+Ltn/G9GJZoJgLDDAdZEDBIPArJROCIhi33sVy/FMU4IoYa8GzJfCM/yFuefC2L9n2l++LHsrWM0NQtwTlCgilM+DFgq9JWEzJipOJ8s8FWFUkpoo8crYsUWCLo9juGqWO1OuCoXfLw0SOELbdjwaBPmFkSUyTOAUFmYETNvY9TOqq54LmjZyJQUaNhHgQNPYIlgg/zAfRM1/n3Pv0zEUSEXPKxjzzP4cEBt164DcPEg+fv0TSKd//S8xzZJc+9PPEG9XoevXyKv31KKyRf9eWfzc/9k1/lhWdf4q1PXeO5W2UA+KIv/TROX9xx9Yrj4fYO2WWWStE7B2PEHVX0t+5SNxXDuOPayQ0OFmvoz3nx+Y+R515EOvVIJbl95w5XTm6QQmKzS1zsHcPtM9qq5ejKIVdv3uT0rOP2vY/yuiuHbF54hBygGxPnH3vA6595Mw/Pt4iLDVMcX/HZe1VsB06OD/OXfcnns1gs6IYJW0msLG0o4RJVVXHR9YUhQEJrjRKCFDzj2LNYrUlDj4wZoRONUhhl8QQaa1nVC4yocHlAygITXdqaLhQlt5SSadbR51wky6vVahbi9AijEVXFcnVU8OWLhrpuSRFU1SCVQYjiCzBaYlqDzAnkRI1ivWh5w80rvHTvpcK59yMcVlykyNn5fWSOiOTQ1YKjRc3VZsXZmLl71nPn9Iwwbdnu7zOSMbpFuMzZ2YYf/aF/yE/zzRzMDaqv4scvz+k/4utQ3KBjxURBVGcmWiR29pRFagyKloPZRqy4IPH1/DU+/7M+nWnziFu7jqKMiNTWkILAh4g1kmEqqDdFsemuDxr6sWO9PiQFwcXZhiQyBwcHbLfbgo8XgqaqEJpLXsOyWRVStEuoSvJbt+/yqbwGicYRL3kIBs0OTyZjL19R8cjl+d5QMwGopuGCC2qaeXsAz/JhPvXNb6LrOtbHh2z2HVVVcbI64NHZQ2prQSSGGKmqitj1qMrgJ4dtFxATfXfOwi6ZRqgWmiAFN177Gj76gec4WZb6jkQwTh3jEGnbmpwzh6tD7p7dL92t5KmWa566fh0/7rjz8C7PfNKn8OJHXobk2XcdV69cmbdQFSIJVG05O91wfHSEG0aWyyVSGGLsaA8O2J2NBOHwQiKd5+T4mF03USOpXnPEe3/tvVxs96/e7kCm9L1jjGV5HiLOeWxdYYyhGztcdAhRHHgllCSgrcHWDd0wFax1pUGWvbxAoU0BhMQYGaaeqm0QPiOUJKmETYKsJaOYIVJa4/1EVZnCL3Qzrz9BDpmLi4tSLNSGnCMhFbFnEql0A6y6jCRzOTIOjl23pV0dsttuyCFATITkcN4TpolhvyO4keRmPl0o9OKuv+Bis2HszvBTz9h3GCWphWaJ4Ed/6B8ChecuZ63Z4+Mf804UxcUeGJnYzYJUOctTBdBQAKKlM51ZMswDAEB31jP6gVaXVmdKiX4/zNJcSQiFfze6iZQjKReT0XLeym13O5LIKK3px44QAikljDFM3rPf7xnHkcZWICVT8IRcBvjXX13zr7jNyDgPAMV95/FYLAsWDHRMDLOstiEDDW0pKqPZUx7GAxYUsmKZ7CYfqJqiOYnBFaCsG1HWMExjSUXK0O97pDCMfaRdr3DBM+w7olJEITnbnXMxDkgpeeH9H0IhOH14xr6bLuE4VVVdJmW9fP8epn7cjWoYJocbBybveN0b38LZdsuUApNz1HXD5vyCqqrYdXtcDOy2Ha2t6MeCHhda4VMmy4rJOXweSUkQOocxDXdu32KYRrpacvelW1yxi1d8/l4V2wEpJVW7AAE6gdaWKY2ITJkHhGa9WiByLn38VaHzhskRs6K2XN6Ira3QWoMsD3ldF53A8mDJ1O2Q1iCMYYwRu65YyZqLsS9LWK1Y6UOEzDMePIOXSGWIPqCbCh8ScvLYpsa0NbFEDhaHH5mqMtRZ4EJBjb/p6dcyXlzwcNuBv6Cxmb7fUMcTqipQC4kIFlKkFhqlFuxGS7+5y50XX6LPUynW2YbjqFiKiaO5G/ErfB2fT41HcYrkl3kHiTUtjgkY+RgDCyQNE4aAQFOKl5HrfAPf/buuxWe8/ZPpLjaIdIEWlmkcikvSBWpVcN39MHB8siZ0O7QuqUi1bRimkc3gsKa4N2Mq83MIHl1Zggtsthcslwu0Ncho6J1HEcv2bOY4qlmU9H7u8UausKQmIOgY5mEso1DUVDzkIQccEojsGZmYMLOer6Kdq/c7bvGINz35FEp6gkuYypJDZAodOzLjbuDg6gkfO31Ao2vS5JmYCCLizzxj15Fjom0M+7yDHJj2W+LgmdyeoCu0NuhUVKx1XTNOAaU1u33PRMRt9jRtxRQLdfl8e4EPgQcXtyF5khD4fmS5XBBiZOhHkoDRTcgoGVKkWS4Ywp5q1ExjYpg6XE5MYyb5ESklu33pUIV+YHFxxjCNxez2CserYhAQCKy1JO9opKGui3+rHAXgmXPGaE3MBfIpRcaNI1oZpJTUxjD284xD5vBgCS4UCyyC6B3WWpRSjCmgpST6wBgH6jn9KOTHAaYFdBLDHGcmDBhx6Tl4bAeWAnRV4UOgqSRSlpwDgkeoUqteL1Z87NE9kgwM/Z7oI8qYgkFze9LoMVVpdjWtwlaaHAK7iwhx4qBuCjXGT8imopGSr/7On+UX+cq5MGbRQEOFp58xlAGBmZf9boZQLIk8geGAgQd8E9/Nz77r77ILE8++532gDe/9l/+cyW3p93ukyDS2IThPUmWgfnwYY+m6jpAySmgOD5dsTjegFS45hr6nsRbnPONmw5WTY0Y/MnRD0Xs4ByKR03xOs8SqmhBKfoJSijc/cZXnX35IIMzgz2LoXVLPGkdJT4+ZW5iF0F9WDGGugIQZ0nVr7owYY8hpIqbE0I3UdYWPgXEc0JVl++iMz/qcP8F7f/XXUHMsHUiGcSQLgbEG5zNKCJp2gQ9FmWp0RSKXhxVBKxfYtqLrz0pQq9EIF0EJxsGhdDH2SqGY/MAw+UKX0qrkbc4Wcxc82mqCjyzrmlprLoaBtm2Zcvl9WcDQTcQk0VbjnS/Pjky4bsQPPdduXOf00fkrPn+vikGgTBeZSlcgM1MKICQ5xjI4zJl6MmZcjuQsMFWFcwGhEsk7UJbaarSQmEXDsO04ODgogh/7OKWnLJmVUri+p61XIBJpmqiMRSqIrgBBJu/QWiKUJIuMqmoSgtE7ZLJIpckxI2KmbVuySKj5d9RGgFf4GLnYnjGoEe+3HJ2sSb5nOw3EbsuiMVhXUnSSTKRYIaJkCgN9DwsNK6UJZslhk6jHjm94Z1HCldZZj+EmYjYDrTgg0ZPmZhk0SJ7gHfzXv+uU/+c/8F9xeOz44Aef5bc++EH2Z6dM8QJpFJ/xOX+Cs0ePePY338eiakCX140A5mxEJTU+RFqlCFNAZEHKkpw8MpfBcZgCbbssmgskTdPwuAZlbF3ckm1ZwmupURmyFAzeY2xZDbzEhjdxjUxkzQEjHoNgw46KBoslEGfpc4FymRkCUghKHzdWkTLn+y1WaBrZ4KeSdblaLxn3Eylk/vn/88scrZaEcSJKQUwF3WWVYUyeSkiClOx25zz9hie4/eI9qtowutJFWjQrpK148fYdVIzUywX7vkOZCqUVxLKFsloyTKWwKpQukOsUSVi2uw7vI4dX1jhX+Bc5Z16+d5/1lSuc7vaoINjlyI0rJ/h9RxKZbt/T2IZunGiawrFYHh9x/+EpmldeCrwqCoNXr1zJX/91X4VEYKQqEdKmQDysLtCPwv8vDEJSKtDREKgtkDyNUlijEFKzbqpLzl9tLDGWopaWhpAiQXissmSfQUV655G65MJUxhD8QFaa6CLSVqA1aIWtK7z3rA8PCAmkbWjqJbY2aF0ulJSSG2vDODoOj8t+7fT8jOy3XDs8BFsCOu8+uEBNkoZMlpHqQLO6/hoOTMv20cSLDz9IcIG2agmjows9qbugipFv/Ms/B8Av8GcR3KTjgKssOaJh4g4dWyYMsOAL+W/44b/2o2iTuXfnNvXqGD/0PDq/T3yw43YaOX/xNznv96ztghwiTd3SDSPbzXnJWSQWFaYsqI0YSgsWlblx7SqPHj1CKQMp0g+epq6Z4lRMX7oiTCWN2VpzyYUUcxI0ORazVV0XjHtTESaHi2UAeeHuA15HYREIxKwTqGZbbSEnZUp+gmNiMYNSHZE1KzyR5+Ys3KevX6Xr9mhtaJQproAYMHVFipnRB7RSlEXP7P2PAalMEZNpQUwQXEl5UmZBHEcwAjeMnJyccL69QFhdEHe6tI+HbqRtlzz5utfysec/TAiOpmlKnWVynFw9xLlQADqTm+PmJUnlAlF1DpcyRllEKu30Vd0yqoibpuKiVRIpBFaUOlh2AZcjxij86GlqxaN+fPUWBuWM9qqqiqwleS48lRivYb5xSgExhFCqtboUcAylEEgqEpeqKfs5rTVW6Zk4BDF5QiyzwmXUmSwcA2PUpVmp3JjltPg0kbMnRlfSfp27XFEopYgpzYOTL1FZokSBAdRCca1ZgPCQhkIVMoV5L6zEWss0OPxUNA/BTUwhFk2DUigqlm1FszyirUtrVPtCNfq73/05AHwJ/4gtjg2JHYnCrc+zcj0ycZW/+oN/DSsd9577ME4m9ucP2D96wOmtW/RyZPvii0xTKfhNwdP5gXvnD9mfX6CEQM+qSK0lSgmUKizGymq0FHTDnsWiKYXSEC6vJTzuvEAUXGoqpBCkGGdis7hMiA7RYRtDDqU4XFVlywQfB6UqSnwnFFpSPaPUH5N35fyWSDQYEv5yAHjN8UGJuJ9pUyFFqtrSti3eBaboWdctpExVVTz11FNlElKaaSgCJzeMs3BN46ZAZiRlh5AJlKSfSn5l8IkcUwHPzsXSHCIvvfQSQgiMLnSskBPrxZph7EkpMQxDCZSZ+Rp+nIghz0pUS1vVjN6hs2AfHXJmZQCkGIslf+rx3uNCSdV27uNA3ld8/v7In+h/m0MIhFIECg3aJAGjp9YKu2xBSIzRGK2odUkkjjLTNA392KOVxdQNKEne91hbRsxUEL7UusbMltzsIiKU/VcOHiklvR9QQiNyQVKp2hJiprILkAplLDKDqSzaFpdiURNahJIoWMIjlwAAIABJREFUI8kahMiFiIwgxYmHmx3kTPKJRgpkJUlolKyprMbamqAt2RiUbahyQGGQ48RBewBqSRMGlGxRKM73j5j2iX3I/Oz3fjEAOyoqAo4THIIFcW6tHfLl/ADLuqZ3jtNxixw9cXLs7j8idENx8u0fMbpApatSMY+ZSmqMVdRtW7oBQiJcxtoapSWLGcN2cHCAMYajkyvEDE1lqLQizjee1GUWcs5R1zWoXK6RlMU45EKZVbUog4jzDGFk9CNLa5BK8dqjdhYPRTyxJEZRMgAGRiwaS4VCoeZtgCAiyLyfu7zx6glPHh0Ac/1BqFn8FfAucHJ8DfN4q6hAyIDJgvZwjdaKWtdoW3InVssD8BliwMWAcgndtsSUqZoakQRZlpqBUgapJdLoAsSRAhFLDLpQgM74AFEGsJrsHauDZakhiJrgS6dEa81mv0PlkkplTEUyZavsYoAsybl4YWII2LolijLRtabCMINg0x8TbVgI8SKwo5CbQ875M4QQx8DfB14PvAj8uZzzK1clyhhApXTZGzaG7DJyfjFy3ifmXKS5OQZ0Cvgxkq3k+PAKw7gFY8jCoGqFVQZEom1a5DyThVBc9M2qxkdHDBFypqkW4ASKQqaREgQKo8r7XsZi2hSSpajncExNihJtBE2tQCdaa5iE4+p6QRodRsC+O2VMp1RNpl4fFQNSVqjlVayHGDelJbSuOVgrrFjghoRcrllMlqVMpHGknx5y3k2c3mv44Z/6vwH4W3wZP8E7OOIaWxwJxSlL/uRvc6t967d+O7c++gu85bVvwKqK9/36/8fh8RF3H93j9PwB4oWBatGykC3TVPIclJFk6TFZEdyErBQHiwXnpxu6seNT3vbJvPDsc9i6zNQiBu5tPgY+Uh+uWK8sbirEp91+pHMDSEHMaf58mXd23R6tFcZIsiipD36aqG2FrBQXgyNEeHnT8wZqoAyQe7rZG6FwOARmtvwWA5dAscTyfh5yrV1g1IS0JWlKa83VKyc8eHSfJBUyJc7OH+FIDNNIu1wwpIzsRz7y3PMM3YA5NIRxIrfFr7FslgCcHB7R9yP7qaepLConpAnooEGXsNeQJFcOW+LoGMZiTtNVw3qx5mx3wXIpqLQmuMQzn/YZPPuh56hUyXc8vnrAwwenZO2p6rKtFELMQTdlcJkmR20qYiwy+cZW5FiA5bKSKJ1xLmArXfibk+f3Ov4oVgJfmHN++2/ba3wf8Is55zcDvzh//PseaV6GW6vRys5Qy6ILU6q0O9K89BaxwEKzToxjT9ftqHRdtgOiEFhzzlS2IfhEjCWuXOTycCulcFOgrmuUrRBSIlUhF9V1gVR20zjjzkq7yhgz98VBW4OQFqk1LgRSCkipWa0WVFZgZUYbqBYNTma8SnhRkGZK2lmR2KERVFqxahJXDlfU7WGhEjUt2ZdZKyfHZtqDqTlpr/LDP/ULAPxlvpaeYypO2NLiOcCjeC+Ob+c7+Yuzc+5nfuZv88SVq4h1xd3bHyMRuXf3Fnma8ENP0kXws9/vy3JRRqxRrGzDelVx/dohJkcapTg6WnFjccDm3hl2vWKahgLsEFAvWpLM2Kqi6wdiLuEpISek0ShZ6E3G2Pl1Cdq2gTQXCYWhtk0pEsqy5Ztc4OXN40DtEvHtKBz+DDzmOQYSlnouBhbBV0TwxPEBbVuzXC4gJ4ahJ8bAgwcPCD5hdMG7oQSkkhq93+85NIrrn/g6vvRrvoLP/+Iv4dH5OQeLFUrC8ckhWST2fVfCVfzIYV3juw6ty2QzTCUjU5NRCbZnW6y1aCWoq4J/nYaR1lRF4yHL9uC5D3yQha1RQgKlzVgtW2KMNM2ibBOEwBp7udU9XK3oXcmkXNVLDusFSguapubgYA1kDq8esRv63/f5++PoDnw18AXz+38P+GfAX/n9vkEAWkhklugsCcKABpkE477D1i1h6kmTZ8wJGQVKxkJbVwXsSXBo25CkJleKJCGFTCULJlxLSGgmF7C2YQqRnBJaBoKRTHGkkRXOe6rKoLIkukzwJbirVH1VofXJgrcuDH2F0Q0XfaA9VJACT994HWe7B2yNQ48HbJXHLirMYNnmPffOHiGGngMB0wrGYGjqY8aQ6dDIxnPn1pZ1bfmzX/9Dl+fpe/iPEIxMtNxh4F9zm4r7eMCi2bOlLAzLiP8VX/KnmeJDxrsf4dGDhxghSd4xzYlAiTJIdl3PzUXDjetPMwwdvZu1hFGwrBuEK5EZZMHZ+Tl1ZVgvTzjfbOjcnpOTE1YHhwzDyOhCqSFIUDqzatd87O4po0/YHFivDpmmibHvWa4sKUbiGAgxgyrdlqoyfPisLB6f5GCe8wMTBYWai7KAzOMIT4tjpMLOsA94+WzLG24eMcYBJQ0HBwdFDCRKDWlwnqauON9siDGyaGvy5Ph3v+KreM8v/zN+/vmPkZXmias3ca5839RNxCSQqrhBZYrEMLG6doycyvaiqatCms4JdCaE0uePSiC1QKaMjI4gwQiNlYYpBo4OV3T7PTGlQscaPFlmVssWJQrXkslzcnREUnMuhRC87U1Ps9/uSc7TDXuO2hYUhG5Ctw0pTFy/eowbHa90/GEHgQz8vCjlzJ/MOb8LuJ5zvjt//R5w/ff6RiHEX4LCPFouF+SYiuhGlGBJl0oxzhhDCpHZqI/JpVjV9RsWtp6r8kUD571n0S7I2RN8xBpT2nZSYrSkGyaqqmLse5SQ+LlAWBlLEAmRBcYYxhRwk0cx6xPk4+KYIQtFUgoopqPoXTEyKclKKYRIZAlZC6rQMoiBHCNh60FZ6D1xO6CFZ2IH/QFxOZA8TFmhkufh3T3f8Of/MwD+C74Pi+Eue3p61hyxYUskcciC27yMoUazZseOgY5f5d181md/HgvrcWFi2O1ZVDVu6BnHkRQjUhbFkdaatm5YHx/SdVtSjKzqNUYo/NCX/aYAqRTnuz2ro8MZ/R1Ytw1mWeGB4Ca0LtyH09NTrlw9ngeYDrJHpMR6dVTEWzkjRS7dnlxEvzkllJZzkfXjRayJkRtc5SFn8wBnULP/oFB04kzZ8eh5S+AYeDMnfOTuKa+7tqQyhn4aWC2W9F2HNgYfMsMwEGO8NKW99ZlP5pd+/p8iZzXktRvH3LlzB2s1IoPUkn4oWPymbYuhSiniVHIOHq9Yja0IzqMqgzGSsR/IWrBqGsZ+JPhQWi0i42dgrXOlPrXvOhZti58mqkojUmbXdWitOThYFVz+40Ts5QI3upKqDTR16YqN00hlKj7p7Z/Ce//ff0Hd1qUO8grHH3YQ+Lyc8x0hxDXgnwohnvvtX8w5Z/Hbr+jv/Nq7gHcB3Lh+Lc+fu6y2pxhL8S5zmRGQsoAQ6d04V+cD2guSgqY2xJTod1vsosbaCpElKWaMLdVRay2omSBsJCEUarCyLVprREhoJUg+YWuDnxJCz7gzP2FDjQsBWWmqymBs2UqklCDG0ibLgSl4JjxtdVhktXuHaSu8EughUWXJtu+oDwXnAULc8wWf/I6Pn5zPhu/iu2Yd/MAZLxNwjHheoi+dAjR5dtTtuSAR6ekuI6gX65bzB2e08w0pUglN0VozhUBMcW6dVlRVxfZ8R1VrUpiBKSlTWU0eI1kXWo6xdRlo6wbhE1efuIbrB24/fFhYj7KwIpfLJeM00TYN0+g5WC/oJ0+Mmc1mQ8qBHBNSS0TKiJRRWpEfuzqz4M2vucbztx/MyK2akpZQrEWOPEdtSE44YKLHYJkYivCMisfBIS892POGKxXWzPkSzB2JVDIctNZopYhZcPTETexHPoo2ll2/4/bt2xhrmZxHSSALVKXISRBjxtQVYRrxYySk4hrd7zqMtkhZHsy+H1ktW/qxZ+wH+n5AIliuFkzTRF1rkoO+74vGpKrw/ciibRn8RM7Q1hYtFWN0rNsF4ziiTMkuVBlCyGit2A89lS4+Fmk0927d5cmbT3C2OWccX9lA9IcaBHLOd+b/PxBC/B/AZwL3hRA3c853hRA3gQd/4A9KGalLbqCRkhhdSe4VGaUtyU+IrFlrwcU4IGLpqfocWQiolIRQlneQSvcgRpTMGGvxOWCMgiDIsbgDO9dTtxUyG0glY7DgzTzLqlwgpSM+K1RtSzsx5hIqqiVCJnwYZ0Z/ZLm0uCSRSvHC7hY3Dk+QlcI9+ghnu1NumQW20wTlcLuOb/0LPwnA9/OfcM6W/4lv4IAjYplXcVzQz4S6B7w80+7iZTPMoHiBDij4r549zDAQgF/6+Z/nk97yNh5dnDGMO3IoLby6rgsTIcJysUQry+aiZ3NxhqotKpYagG6KDjGFwNmmR1sLZK6sDtheXNCNnt75EuzatkTvOT+/4GB1SHTl79z0E0ZXaJOxIbPbb5GqiIAqa0EKck7IeaDPLkAsgNhhXr7eZ+Qmt2Y2X00k0lKivnsG9vSXODJQ3KPsf9/CFQDe+uQVnJtIIl+uLCGTc9EEVMrwpjd9Au/5V+/hN/7Fu/FxYvSBum3Y7ndYOcfXK0OKCZky49AzdT1tW0JvUow0dU1MGWXsbGOfUBiquhiQKmNLa7WpStKWm1itGkAi01iyLzN0w57ja9c4P7+grioqrXAx0SqFFAckKVgfHzG5Eb/t6L0npEhdV6ybRcnQ8J52vWL38Iyu3xXozu9T/vu3LgwKIRZCiNXj94EvA54Ffg74lvmffQvwD/7gH1ZadimXHq1WlkqVmTkOA8onYvRshy2RTJKCKQaUKtQf7z1CQorhUlsw9D2QmcJAFqViGmMEYZAhsVKaGBwxZqKLcwGxaNyHsYRGewtaSsLkSLHITrVSCDIpudJ+NIL1MnK4snRDUWyNfccYM+LiEW6/R3jH1J8zes/9/YZ7ub586S9wC88Wx44zHvAiH+Aet7nF85zzUV7mLmdMDFyw5YKBnh2PeMRDLLCixSIYGecwkY+P+O/70LOs2wqrisCqtS02a7Lzl2lI+90OrxL91DMMA492e85dpJ88p5sLzruBum3ZdR0uRB5u9my6ofg4suDu2X32fYfPidVifamXkNqyWB9jTM3UeYTSLNrqksPQ9yM5KQQfl4TXtkIqjTJmRoI8vj3sPPAJLAaITBRykULh5vrA4+MTbl7lQzzi33nNDWIWRPHxr7pxmmdSjRSKxWLBb7zvN1k1a/zQzUVSwTiOVFVF33e0lcU7RwyBMUSMtTSLGp0EhBI1H1LRHohMYWFYWxSJIc6E6cJzTCnR2grb1HM0neXGyRotPAfLmvV6jQ89B8uKg6PSiVitFmglkDbT1Iqze/foLjas1ysWqwW2rZFzC1RQXLKu2zPstggNQhZw7isdf5juwHXgV4QQ/xp4D/B/5Zz/CfAjwJcKIZ4HvmT++A88xnFkvVpydnGBMGLeq2msNiDBVpooJNqAC5FpikzucR5rRMRSSNRZUAnJsiqKLHQxIBeJaKG7j25imiasLLOS1BkhI8oaYsyzoCSTRkUglhgvUxFdhuRwcU8IPVZlWqs4bJc0OaKVYDtcMLkdfrdhPySmNKAYEM0J1fKApW0ZxwKm+Aa+nh7HwxKlwiMelPYjHkfHOT179pQUPEg4dlzgCIz01LTomRS8YzvHUkvezmcB8La3fAIX51tcLMvV0joyCGmoqyXTGAgRRBIYWZRmRmqcLwU+YxuykLjZ3+BTZhh6alsRBXjnMLrBWo0SEq0lIZWQGJEEhwcHxBhQ1pSbMCawhf9YW0MMI3GOb4vO40aPlAIXHNNvK2QJQBdXAQKBxjDOYRx7ejT6dwwD2kje+uQVxqnnqdc8UZb8sjwNyuhSe5o8MSfOtjvaOWOynxLWtPTTSMoCNxVqs/ex/G4psbJg72LI+JyY5pk4yUxMJZ5NKUOiqCJFhn23o10u5ph7Wc6djBzUS+IwkKRCSUOOCSsgTEVnweCoq4rJj0SpEEmx35fsycNlQ8oORIHujONUWug5YqoiZpJGY4RE5kQWfwwxZDnnjwCf8nt8/hT44n+jHyYFWhfyjG1rcszYpmLY7i8vbtz3pFAYe6SIUhJrikZ+kpFWFZtmyBBEJsaJStVMPhOzY1XXBF8uvNYSlzPeDdS2IbhIu1jSubHASr0jh1jUYjKCFhATIk1IIVk3NXVV2obHN0+QaHadZ8sGJRMP7r+Ii3tMtSY1FTeufjKf/cyXcefslO39xHEog0Ah1C55kY8CUFPPM/2ejokELFhzxgPcTNopeUIjAsWLfJQlx1gWXOeYYQ6/WLHgJle5+6Hf4hNe+1p253usKTf6NIyQM3cfnjIFT0wllk1WihOjuetGgpR03jOeFev08XqBj5mUc0G0i7IVE0pCBCtaMjO0pW2wdUsOkQcP7tEuWvwuUtctzjkO5ILNZk+70JAStbWlQChEsWVnIOffka3YsriUCRugZAab2SAU0VQYFrN3Etw4EIVlPwQ+eutlQor4caJuWpyPRSOgNVZC343zAywoMLQ4ZxmWGsrR8QESxabfEzw0Zla25kySkmpRYux3uy2yrsGN1G3FbtdhbcmL0AksJfxGWI1OsDALYu9ZrFY82G44Ojqi2w987Vf/GX79V3+d+w8ekEKG4PnE17yOl08fsh123FyviQcrhn2HjwKRdKE8xcBRe8x+v0NlR4qe45Ml+32P9xFbfXz1+bsev3+jh/WP6ciX8kdxuSx/XGkdx5EkCg7sscQ0xgg5Mo492hrGabpMC87BM/XDLJl0aFMhRVFtQeEWZFXCRIS186Cg2fUdScB+2JPz7A9WxUmYBKUgKCWLxQI5m2ik1Ewu0neBs7MNwzAWHsHCsu3PSWIEUZh9uWo4rFclzTeWASthuMWLc9xkPc9oYV7olijKM84omxNVZhcEYX7zBCY8HR0TExu2ZDIbNoiZL9CNE3VVlXnUaMYw4me3ZJxDXfppxMVAmvfMOQmiD5fn2pMIObHf96Xn74sKMFKKrVqXwDMpJTFmpn6g7/vSS5+mSwfiMI1lWTzLYqUUl9elyMH95cc3n3yCpw7WQIn0lkim+a0MBqVLsGJJILBjh0DyNAuef7AtRbfKFj6DEGhlLqXKo5su77FyHhLxsURZa5Io1nCfytby4PCQbT8weodzDqM1x0dHCCHwLl4akWKMaFP8KcM4En24lD6PYxmgvPdkAV1XAmgfS5n7vkdIyQee+xDaKuqmoa5rrh0d8/LtO+y6PdaWrEghBE1dY20JnPWTo54NQ3VdMwWP0ZJdt0dKeelTeKXjVeEiLFpzweRK9HiMnhgCWUkWTcs4dGQpUEHR9XvIkRgT2nBpxujcgNaa2lhciEidkWaGQ2jFGIsP3fiIUxIjDT5ByAEtI+iKbrxgsWyghyghKQFJIlIJ/Tg8PmAY91TalN6x1gx9ZHd+wXSxJdgOdTVx8vTIfr9k409ZJUtVNejmgGGYGIfMzStlEPhp3sWf5st5wEMMlohDo5hwSBLD3B0f5iCKIjquZj4gSCx7zlmyIiM44JDb3KeeHXUAjgRC0lSWGANV23C+21OZijoL1ocrFtlw3u04OTnmU65e5T3ve5a9K0v7QGaz29I0Fi0kKcHR8SH37j/EyNKefZzS1HlPKxXHx8fsxwk7ToxjT6AIcZIys2W2AF0jCWKirkv13yVBDh6yZLO5YEyBK21N1SQ+dvqAN3GFiQF3KQ2GnmHeJEh6JiSGpyjyW0TRc+SYkVkSfen2VFVFHCZUtSB6hzLl3IsIeSz244lcCpQ+8MLtl6hthQsTua4YRUKOAz5ltIDsA0ZpvIuMObLbFLhqzIG2bYqfQumiPBTQzQOhPba4WNrDRgl0teCF519kSqVmsRCaR/tTOhlplUYTebi/YFkv2fc7rLUslgYxRkxaMI4D66NDggpYZTBh4mKzx1ZFY/lKx6tiEMgpgS8WUN1YXJhKBkBKTD6AzAiTmbqCs/LRY2WRp/qUmfY7DhcHoKH3HY1sGX2PkDUKgU62aLqVKOBQMS+AfI9aLZhiIAx7hFB4l/FpKJbZKSGELj31FNl0F0yT5+YVzRRLxLa/2BD3OyqdcCrANGHsmiB7XCx59VFNfOTsNuf37qJSz0p+vEjjKMvQqyyRCD7CR+ZdfgmmdLjZLltm3jCHZ4LAM7BmhUaxY8sFHS0GDQxEnuAqDx485I03b9L5gcOrJyw9tG3DUzeeolkdcnF2l4PmiM2DMxYrza7refqtb+Y33/d+KmOxQpKSK735SrEbe9Sm2LEvNjuklVTGkrLj4OCIHCLn290szS4pzkoXg5ZMiZhB5IgUEpmhaisSghwyMoNqatpG0Q0lqnuxaEg58ORhw53NI27QIFFYLAZBP2+bSjx3sRm9xIbrYQH4WXGaqSpF9hGpBePo0HXFbtOXiUECIZNnKaIUAlKiqeoSa54ybVMTO49MAiNlMRN5TxaCRb3CD13hRHT+stXdLmqEKoOp25d7VyhFcJ7FYoHvHTF5pISpmxiGCRdK4XTYXDBKy8lrnoTNhqQTQwSZE30cUE2Fd54peYauo64WHK8XpFRWd0ZGQoocHLYoJdjf2/+u5+7x8arYDjC71LQSRTI6j5TM/rCcMylMCJHRWoIIpDyVRF6gNTVN07Dd7YFS/KmqAnoQogBFiIGciwMux+JENE1LcAWKKZSkmYs3KZUZo3ACyp9ojEKIsiesK1Oiz2rB5AaUEWhbYTXELiBFw3JVUdklXdfh/YSPWzYXD8hTh7bV5UuXGFoOeC2v5S73WLCYqTmWx9GYAVeMIHPFvMai0dTULFkiKPUEhUJS4q4NBjNf3g/fvctqvWTZrqi14eDkmLpa4nPgmTc/A03N8mBF0yy4dnIVhWC1WGKMmV1txRCDekxsLk6/EB2NrViuVwghcM7RLhZlCbpalmq5ECgtZmdgRcix/Jx6JkDlouDLc8Bs27ZM01R0G6LcDyKXtu/NdYXHz2uiSM8wy4YtDZZ6HgaeYImWikXbkGMqLr7Zvpxz2XqKHDG2rAqqqvwtinx5/VNOiDkQRAnLODqsspDKdqeu6yI9V4oQy334eEtKSpAyMZf7qDz8ohQKlYSUiM7N2waHlYpVs+Dk5Ihl07JeLDlYrdFa8+jRA3x0hYSUI3VdE2Iiy+LtNlJw8+SEN9x8DVIIlCkF2qaqqW1FSwlLDfwx6QT+qI5Mxkc/23AF5IwWAu8dVmb200jOnqyhv9hTac04jRhjuBh3/P/MvWmsrVl61/dbwzvu4czn3KmmntyFwR2nDTa2HLAdjG0RIRJHKCiOA0jIRBApSkxQIkeKUEbIF2RhGQLBjiUIShSFOECIbTnQVuKmsV09uOeu6rpVdzrjnt5xDfnwrL3PrXZX7IAj1S7duufuc84+e5/9rrWe5//8h7A/xy/PKYuawfWMRuNGkSR3zomZBZFZbugHDX5DWdS4dUtWl4JKxwCDQ3kjXgLB4jpHUeRYq9k/mGKM4qCe4RK33xrIrcYTMLZnrzpiEnKGjSYvj3j57h0W8QpV1jx7+/M0myv2pnPKzPL3/8+/xPf/vv8ARceMmp/l7/G7+AgexzkdG1qWrJKHjqGh3xFnlqwxCRjr6NnjkAvOk+W2uOpMKGmfe+O/87u/l/tnLzCdH7C4XPHWlz/Dyf4xpy++xNnxEsqCz3/uNR599Q2IAeUdOiJx5G7Er1cYnZFlGc3YMStrSlWjteLm6oZJXRFwPHr8pmQyDLlMEdpeDDFHh1WaXBl67+n6keBH6rpiaiuyQrHqBvDi1DO6XgxijMXk0I0DIdNc0vMikTUDOQaHY8GSOTUtPZKckPH24oZ7e4EQI74TU1OdyFzzyZS26dm0G4q8ou8jJkIAvAoYo5lEy9BLHz2ERhSfvUNbwafGYSDPDUOU0XZelqxXjfgkGkNR5Vid0W8G1uuWvFAUWUGuLYM1uBi52fSSXD2ZMrrIwzefYJTwAmymKTNF6Bw+KtRsRm1zLhcrFBlucYNKdvmb0vHmoiGPnizXtG3LOPS87/iOTB+IzPKCy/brJxO/NyoBkChx5yUuzAp5JwSRbIrWXQBDY8QWTGtN37TozLJcLwHPur3BGJGlxijWUDqztG2L8156Vzw2r8myAlPXDN2ICbKL932/A3IChn50aA1GC+hT5Bn9ONAHl9iMnhhHKW9DUh16MQp1Y0ael9w7uQNBoqfn05qimJAVe+zNZwBEHK/wCiec4lFccsOMPUpqSvIdRXZ70rfJXDMQdlZaa9YodCqRMxQqOerI0Oy//s/+S77td38HXltCElV94P2v8uCVFxiCYrp/hIqBV155hXXXg5Fod6Nhvr+306JroGtaskws3eTEztg72Edrixs81gpRq2ka4eTPpnRDx+gGNk0jJ7wRbMEHCInJGEIgM4rNqiFGuR6qoiSEwKZrRUWXvAffZJWA0kCV/nMEbHIgHtLml20nIsMAWiXRzyDXgwsUuXgTNJsNo3N03u0MSYOSPy4GopL8R2MMg3dMK9lEFEg4rg+s12IIanOFtobr9Qp0ZIxb5Z6iHwduFle4ztE2siBNZnl2fcP5csUQoOmFu7IDsmNk9I7NZkM0mtn+jBgcdZ6hokZ7uc5DkoG3XU8fgzBEgRWBVb+hKqfvuvbeE5tAjAHvOly/wQ8tvu8AxRiFs47KUVpjTJZKK02d1Uzymk3XorRl07WUec6iWTF6Qz92tH2D1wGvZAMYu14sx6NcWG3byqTAWJwLjC6Q55YhKLLCkueWTBsmdck0zykKCUXtmw3t6NCxocwrppmGuKGyEw6PTnFpql1mNXk9Y38yFxVZNsdmE+bFjDvFGR//yj/kVRxf5DXucp8LLplySotLgaGCF4yMdHS4RInVaYogomboaagpIS0Si+Hb+AgPueIv//h/R57NuHy85GC6z/HBIdWk5t7LLzM7vU9WGW5urqAb+OrnvszgHVfNSgRUPvL08goVNUqLJt1k0g83TUdWl2yGlpv1RjzzosGQEYO0Y8aqtJkHVKbI8wIfIz4q7tzIFxzOAAAgAElEQVQ5pczFbizLZMJjraGcyPSBaHBxFLxIC5mobXtePD0EYEItzj8MdAypYtIpq0DGYV+9uCbPC6q8Yu2kNJ9MJgQPtkgRb5lGZZZgFFqJQCygcCHSOUHutd6agDiyOpegHJuLJ6XRDGPEu7QYPfRuJGrQyqK8IpiEL5Exq/fIswytLVnyoEBL8G4cAp2LqARihmHbjmhRArrI1Fnef3LMnaMDXj65w97xPoXNuH9yxnxaglFCBc8qVs2aYRhYDgMvvfLiu66/98QmoNAMzmPLSuy9FfTjhlwrRi/hFjFYXBgZcbRDy2pzLck6vse1N/hoOL+6wnrDs5trEfoMI23fQW4ZRk8XR0YCrQ60CpTOUDrS9CuilvmvGGDkKB1wbo3OPJnRNMMKlGVvss/doymvnFRs1IriqGDv7ikP7nyA1fCE88VjTD2wdg85v7xgEx2LZkVkYDqfykUTNdP5EQeZ4Xs/8cf5BT7GwFc5433skVFTYym5xzEWRZVSgiyKjhGFTZVCRkbFgGbBOWfc5dv4Ln6Af5W/xc/xkz/xMzw4e0BA8+D+PclnsJasKhm8Y7NYc/HGI3oGsqrgD3zfH+Rbv/07aG56Rg1VXTOOHqs1wcVk3x6ZTGYi+7aW6JSYiA49wViysqKsJmyWPUPvaVo5lWNI2Y0xMqlynj05pyoMXdfifUAZQ9sLHbwqSlzw4vCkFDYU+DayaEbefCYci54xkaYcOVZ4CjgMOS0dR5TMKbi+bHjr5pIf+pM/jCktQzfg/IAKIzo6xm4kjA4/BiZlRa4VIXEU8kRtHpwjqEC0sN60eKNYDGuiM6yaFtASjxI8OkSCl9d7eXON9546y4DA4B3XN2taP9KMPcMoobdWG7QJzOYV1ihGLxOvvCiY1jVVXjCfHNB5RR8cT1Yrnq3WfPrtr3J1dcXj66XYjEXNPJvwoDpgrjJihC5oinLG629+9V3X33tiEwDEusuAR37pIBLhrmuE8TQ6VARj5OIzJsO7ARU9oGmanmEQYYgxmuvrC2KUnTTE2/BQk4JGTaJZjuOINblUCuO4myX7ZHLa+4AyVsZDyDxblzmVzYl1mWzKMkxR4Iyj8S1tt2AcN9wsntK0S4Z+w9hv2HQb2mHDxgmF1I6KTvf8zM/9GD/PZ/gcn2RgxMOuny8p0VhyMiZUlOQERjSaA2o+yO/g+/j9fDPfyIf4MJaagj0ALq+uuLh+wnK9gtzC4Mi1pTI5h3uHFEXBg3v3xQBkteYzn/4cj958RJbEWzerJVpDVVUiiEmU38E5lDKoCEVmUE4MWodh4Pz8HOdcasEiXmkwBpI3hLVWLN1RNE2TkqGj6P6VPL5QdnOKLMcWBgJcNB330us6YpaIURKdLkkKkko0Mibj1WLHrwD4b//KX5O4u26AqOkTtTfPLWUlCrut8UiMkahUkh/3ycEAxjQKjF4mB+tmI7yDcSAqITG55FKsrSEq2Ui01tR1zbSqxbMCIceNvShlpc2VCYq1lrzK0UZaYjcGlDLCUvSC+FtjON4/4MH9O6giYz6dsOp6Vm1D50bGGCDZ5RFb+nZgUt+C0V97e08AgyEEtI2MwdM7yRQMfqAfVDJZCHjXyqx12FBkRgwibc2yEw5/bQLBKZrNSF5J8Mi6XTEr9hn6ARNBhxLnOmyRSznXd2grslKjYIigtCZTyGnkPU4b8bo3gWbYUGi4+8ILfOnR6xyWB1QHc2o9xY8NN083jLqjXS9oG8j06+xPDlDRsVheoSYF+/U+A44n/dtCxrl+i8AT/vrf/yF+6u4f5Pf9C/8mxxxyj1OesOKUQx7hOCDnkD0cihk1d3mVkZFP8et8kk9xxRMir4GkH/DT3GPyH/8UH+Wb+Z9TCOfP/PX/kWW7QRnNF778BV7+4Id4ev2Ubj1y/uQpn/z4L7P0LUPbMFSKybRER7heLiEqmn6kyEtWGxEuHe3N2Cx77r90h8LmrMcOBsPB8RFllnO+WNB1LUWWyyw/84xhEKFWEP8+qzQuePw4MC0mXNwsyArL5vKSqqg437TcZcYZNYGB+0yYUjIAKjVeHZ6ehhyLw5GTc8WSkklqkxqOjudiaT8rGdqOqq5FUFVlrJfSYnajbAxFUdD0PRdXl6AVJmiG0Se/xIhRGu9HovJEpxm0+CAYnYJaCBRGTEmbvmMYxQ1o9GtMwkPGGJgUJU0f6NZr6rpGFzk6BvKyZHG1ELOaeYXrG/LcElTkctVg+8DlzRprHHv7c7roGC8HPB2Tg0Mu+g0fffllnq1XnM0Koo88XW/edf29JzYBnfp9Pwqyqq3CBc+mXUrf6AMqy2EcKPIc33WETNOsVxR1jht7YjCMQ0um1jRmZK+eyRy/Ewfb3vdEXeCcw0cHpSz4cRzJJhWhH2WMgyOzBZGM6eF9fLMiz+FQ1WzcSJEVVGj6YYWpK4gWb+B89DSuo4sdlc8JcUVVvg9TalSrmdQlujAUuiCrFOv2GmUrGCztsGZ+eErbiQLugiseMCcw0NEyYw/NiKbiFV5mzYov8zqv8yXOeSuBYqIs9FgUjo5LNpzzv/Kr3OfDfDPfys/+yR/c/c7/wo/95/zSz/0Dzu7e4b/68f+CP/Mn/jSfePOzu8+fHs7JbYktDWadUVclbrWk6bpk4jFwuVgxszntquPt5SPuvvAAHTzT4wMuHz/luJ5woSPRB/qhRRvxebTKYnNPlpVoHF3XEz20yiXQMJBXFVtvzJGQOv5IwNKy2dGFFWIyIhWUo0ZylY/ZE6Zmej2+8WzajtmsxgVFcML00xiUivTjgEEqvcYJGK0joJNXZYQYEupiAmPw1EVJ6zrRbyhxZDaJHem8AufQVUapNSE6tCqIYaAqKnzXEvqOPK+JJOORzjHfq9G5pt6v6VeesXeUZUXTLxl8YFZXzM4mtJsNr3z4Qzx8/SHjuoVCMSnnnJY1h3cPGL1jPqsoBliNMtl51/X327WQ/3lvor5q2AaTBm+YzfZS+dnTD2sGv4Hgd7LLqi4ZXQCVEYWKRkh6+m5o8AhFsx17rClxXnzknY/iqecD0VpWbYMuMtqhJxrN0KzIi0i7WvDyN76fUBwSM0NRlRBaLpcLTDnjtD6ljw3n3Yrl5kr61OgpskPODr6RsizZsy9yfHSfLJvy0t37fPjlu+xN93jSXLIKS0wVOTo4JY8ldb3PJ98QC7G3eIP3UbHgGmiYccqGKz7DL/NrfJZ/wsc4500KcvKEmztaFJGaOqkMFJHAktf5Jf4OM6bssc89HvBjf+E/4if/5k+SVzKl+PG/8RMcssf/xT/lb/MzfOdHP8oLkz3sRKi7y+WSPgFV+rnLJqtzLpc3nNy9x9j17B0d8mu/8homszRDv3NxLsuSse8JzvPGkwucC0It9g6TFXISplJ6HD3ROS7WEgNXpfd0JDAwIhCb/FeQkxF3Zb+YjmYp2jxyg1iUrdqGsiwgCPaDMtSTPSKaqA0/8id+GKVICdNGRoYh4J2MCbUGbbYtpCdG6EePMja5VKtEHQ44JxMYjNrxDvI8Z3Q9AXGtLoylLCtc8Mzme6iosTbncrGkuW6pdI61sNo0bJqBSTnnzukZ3dDz9ttPuV5s+Oyvfp7rqxVlPaMqaqZ5jc5ylk3LshtoNiO/urzmMipu+ne3GHuP5A4cxT/y/d+DyfSO690NPTp6ej/S9yMaJT7srpNybBhRGYzeYbVitVlS2RKLwmZCEsptRj05YAjS38/rGT6KLXn0gcJmeGtw6fPr9ZrprGI+nVBNc0xRUtT7lBPFvKx42jzmd568n/P+GcezU6KC6+Ztbpolq9WGNy8ecnDvjJce3OegvE9uB+7md7FZxWeuXuOjH/rdlG7CxvX8whd+gbvHD1DjwF65R3SK66Xn5OSAShle+9Qv8eXXr/jzf1aMQ7+Hl/kYb5MBG8AyUpKjdg4D6jnfPZ9GXRIkKiacgWniIlosHSMVOZrI7+V7+Fl+ljMKnjHyS/waD/ksf5Q/yg9857/EJz71Gm0/0LY9FRU9o3jl0aOBM+7wkLeZ1znHR0fEUTGfVTRrkR+/+L5X+Me//PF3vOezImfVD9w9OeD6esW0nqBxPFtuOGTGFSsm2rIJjrvMGRnQ6GQuCmZnLBoxZHQ49plzww0FGRUFSxoiEl+21dBVRpMbmwzYJBux6zpUtGSZwTnp7zWGIXiMUgxBWoE8z+n7kSK37O/v8/TZxQ5r2uoQthz9LYailCJH1K/tEJI4aSQzhtxKypCPigJLVRVcbpZEoJrUnJQFi7ah7QbODg5YL1fUc4ngM0oLb6Ew9H3LwWyKyTPU4PAxUmY1VssY8qLtOb1zl4+/9vmvmzvwnmgHBIgR0YZWihA9ZWVgiDgM1nr6tieEiN1SflUkRo3VGd73lGVNHAXo88Eznc4IIdIOHSGNoXxUyV+upzC56MqnMqZq25ZpPZHZv3aY3HC4P6Pte/reoKczqsxSmIEQHWPKMOjcyHKzpumanWpM2Yy8sNigKKNlDAPdxnHZrDixJct+iVKR6CIH8zPOJmeMw8D55UOGMDIvM2zmKaaG/+l/+085qGp+/rt/lByLoaDA41K0aI5lZExjQ5/SeCRzOOxceUcUsMEn2Y3wFhp6phj+AT8LwA2OAsVXeEhIyT1/7x//Ix6cnvDsZkGGZcQhvEsH6f9PeMJ97rJsHgOPv/btBc55mTPe4CkP2Octblj18viPz685mM1YbdbMZzK33+oeNgml7+kpyOnpKamTx9CISZtgz0hFucMDRoadCZnDUWABR1VmFIXFqMg4psfue5QyEAP6uZJZ9CzpYxCxWMqzGIaRzWaTchgkki7GmJiPMW0AQnyTnIGMcezTZiHegCQQcN33zGdzutUKZUsKmzGqyND19Fqo1VqLwraa1Iz9wKACpY90zlOqkohMbWLvmFTCcr24WjIvNfNJzX5dsTq/eNf1955oB5SCpht2xiBBi6njZhwh+tS3KYzNdiQKZSyFNRTWwBjRXlEVJTE4qnIqwQ8YRuWxNmMENkNDH5yUeCqijfSA20lA5iKmGZkdV3zLh+5Q2Q2zqiDLNbnWvPrSizRZWvzNDc5tOCgKRtXTDw3FZI+yyFitG24WG7F5QnQQ+/WUR4/f4lMPP8eXLl5PWPacojpD7R1z5+SDqEyRuYzeBx5femLnKCfH6PwIkLK4oadKciLJa4zolDioEnPAEZP2QNx4DZLs6wFDSUOH3qoMccwomVAwZY7D86f5N1gQ+IspobjtZVJhsel5Q580DRZLRs4Fl5xxxIe4zwc445v4IB/hVY6Y8RJ36BiYUrNh4B7z3Xs/oeB6taKoKs5v1skiJXLCnANqTtljSsVIR0jtgFQ5lpaWHtH6L2m5YUNEUZLjEWlyzYQGWfAueQismw6txJ5s9GGn8990DS5ECcT1tws7y2QSIt4CIyjoh0Fs7IMQyp6vBpSKVGWRSFYhkaGkMiDxAoJzYlaqNJvVCmUty+WSusrQRNBiF972njy3NM6xWDagLNZFsmqCNYYsZROMwRBGxdMnVyzXHXVd82TR8uTJiounF/j47n4C74lNgBipMo0bZIE36wVKR6xRMr4LguL6XhJalFLYTIQhgw+QGUmA6TaoPKdpOrAZPmiUylivW5S7Hf1FxK7cRUeWG+qywgQ43De8+NIUq/f59GXOVx+tyG3HyazC+YYQFTfNwDTmNKs1bhM4DhNeVHt4F5lmJaDpGkvfOHxX8GzT8+jiGZU6ZX11xbNnn+SN13+VSanI6oxJuccklpiQsTc/xhbQjiNl8Bzs1+RoVPT83f/9LzFIvAM9LTZZbI/pRNZYJANYWgNBA4RV6AlYDCWWAkNNSUBGWp5Il1B2Eg+/p+GcL9Ax8GP8OS4XKw6ZsU35yZOuQcTfipaWY464YsGEPQKSFbhhw5wJjoGCItmhzrFkyTB9Sk3NBINf99RYCgoUhjF5A/iUMCS24nkyFR0IO36AT1WBIkvfJw5L465NAtibVAmZl/SoOHZoIlVWkCtB9XVKrJLqQKFNWtxOdAAB4UqEQPJr1ElunRqxBAqGQJJKa0KQjaQucrYh6yqCSjZrW1GR1UbES0FTaiv4iE6tS5IqkykxfOlF0lyUJZlONvrDgNeBeirai3XbUGUFZDllXVNX1bsuv/fGJgCocCvC2AqJlJJZsjIWH8SEMeLRVgIrQhhEoeVG0FHSXw2QKZpenGDzrKKcTIhREaIYi1Z5gS1KtClQSBJQOa0YlKOPnvHyGW8+/DzXfYfPA3lWUhZTmrGlGTbQNNRqTuZ7vA4czGa8fHCXajLH6glH82MKXeDGhovrhqcX51wvL3n26JInTxdcuXOuF2tO61NGpfjq9TOe6Mh0bwqqxg4Fx6cvcPfgRTIX8G6kD46WngMqMia7vjgghT+onbeOStWB1AI68RcjnkCzOz99WsiacWdj2ifJluMRn+Me97nHCS/zgA0dFsvIQE+POPzY3Vz+MY/RKB7yBMiZMGNIX23RbGhwDLRskgjIIuRsqV4qyvRvGBDvRpWezYCjoGRFQwAsOdvwUeEoSuRYwFOQYciS7djImpbMGLpuEHNTFJOiZDabkRtZbLcckogmkhktkmcliULbMh/YbSIgoz75E35jO+DlWtaJydCnqDplND7IvH8r8d/yVXKbs9msMUGTq4xFKzRrHaHIStphoB8js/khm3VP0/S0rXg0nBwfMa1qtIrcOzwljoFx9LgYaLqOm8V7XUVIMluIURZ0iGglGQFKGSHxKEGlt7utUopoxKPeWpvuk6AQrYTu6/3IcrmQN0nJODAQkw22kj9olJbgEZNVdCNkAaamIugesglVnTOp5zRNQ11V7B0difGGM8RgqCeHzA5POJkfk2UlRZZTlTkxONbLK7pmwWa1Zhw9q35gWI1sVkuccyyvrlndLFhcLzFlLiYkKpBVmoO9KVop1uvl7ve0oEUlObFLBpsKk2jE4ssQ0/JRaSHEBAY6Al06IYHdprE1LBGCUsBg+UH+bdY0TDihoaFOqsQxNRvb793+LYM5Ye31OBYs2CT345aWgoKMjClTRsZdpqDD0dEni1SFT0QoUUbKVKCnp6GlpNpVA/Kc5eduVZWkiYiQhxRVmhBoSPZnlkkKq12tF5J54D3dKDbiGkVubmGy7cKW15fi2J7LT4TtePs2688onTId4k6xuP2cUpLEpJXGaNEFbB/fR8kzVOk6FRdkSwiOLHkuZlqe22azoajK5AotkwfXDyKBJrC4uebO8Ql933O5kXwq/fXDh9Jrew/cYhSpblHlZIUFk+MzC1YiwDOd4dzI4FrZV+OwQ/eVk0Rb7RVWWXqnyataOuayIERL60WZFUPAK02Zl0SnKIzhYG8fEx2lMVx3I15lTF4+45vun3JY7VFnMAyST7hY3KCdpi8POH5wl4MHH+AiHrKafAN79z7EpN7jQ3dewXqFUhBWFlV71sMVl48+yaff+gyf+ief5cuvbTh/9oQ3r7/Ck6vP8WTxFd54+gmuVmsODg4YTMHpbJ/9u3MaHbGlbE4AP8wf4zv4ENvgzSFd+IIFSH/s06kf8NzhhIKMnn5XvitUWkTJnxEQUXOeeuzIv8a/jmXCDT1DGsrJ4hPNvmwqIyUZJTkRzzfwKiM9ipGMjBP28XgyCno6SgouucFSsmaDRhyMNRktbVrggQlTBhxNilcDzUBkINLjyMmomDESWdMlE5ZIkQJZLQUdXYJPHb337E1qqixHDZFhFPWisPksUQU65/FKE4OImVyQBR4Hh4seFaPE2D/n0LMd/+02ixCJaSxorWWal1itGb2AtFqD8lFkyqlNCMTkUWhY9a2YjZSV4DAhihlOaj8qY/DRyXMcB6wWEH3sR4Z1Q9v0EnWnA/3QsF9mvLh/gDWOm+7rKwjlnX9P3MTGarVYMvZD+qXqFORgMbWcCNYYrFH0/YjzkagMuhC6JUZTTadU9RzvIFMlQyvBDFVR0vcjKI32GhcNGOjwNO0KVSiqiWZmK46KQ/anE1oVuHs0IWvX9ItHdFe/zvs/8BFsPceXmsndB0xOz8j25jhajJpyuVpxYOa4lWPz+Jqr9pqLy0s0OdoUHBhLv1zg+44mWp4+fVu8CLVns3zKevWQheq5Or/ieJ6zuXFkeUlZTamqCQAPeYM3cVTMU4dPOjnFX2fA7fpgEHnslNluji49fcEeB5C2A5emCg6HRae4L8ef499LAaCGhgbxN8jp6BC3B0VGgU0Th8c8QpOxpGXFihUjBTVFCgx1aCom7LNPRYlF6haHQ+oROd2XLFjRUjFlwgQJGJFAkAKTGpaBKj2u+DEa1rRYYE7NHjXSxcspvGk6UIqF6whGUZicdnQMcZSQz2QPFkmaf8A5j1MRHcUPwSbKudY65Vbqd7QK241AuA4CQroQ0Npgo5HYcB2xRnyhgF2LYoy8ZwORzdCI43Jmd/kGPnhCVJQmg6SyzeuSLK9oGnEiUkqBh64fWS+WRAXL5Q2TosBk5l1X33tjE1ASOppbyYG3VjM0kh03DB3NZkkYerT34EbKrMaHkTF6fAyUZUVVz1hv1oxh2JmCeBdS+m2HtjnGKQpbMkbJeA+ZZTotmRxMOL435+xOyfwoMrWKtr/h5TsVdV6xjs+4HN/ktLZMpoesxg3n7YqbvkHVM2KZ8YXLN3i0eoMn/Tl5f0nTPYTukjh0mKDxNmOiK45fuE9vG2I2cnn5GTbdApPlDASePv4CX/nkr/DFL/8CJ5MXOChK6umc0Qd+8A/8WX6UP8O3841cMNIzUFJyxHHK4RtSHWBSmyAX5gWXWAoGPB/hI/xOfldaxNImSMdKmhVoXOqzJeKr59/lR+jomDBhTK3EVuBsE01XevLIDdccccyKNcuUhdDQcc2CQKCjJcNww5IBR0jeBwZLx5BegWJEJiFLrjlHNtERjyT5iUpwTBKiMfkwS32ikr/AgkfcIHQxT2EMfXCsmpYYFYN3nK8WNMMoVuHJPzJGOXl759NBJCrWzIhjo/dxFz0Pt5UAsDvVb2XXoikQZ6FAH0bGscMFlTQAty3FbFLhtrHpWhN0ZEwuzCFK9qHRImM2WlMXJbmxdO3A1XLFZDJh07b04ygYWmaJyQF6/+SAPM8x9vZg+Nrbe2ITiEE87AkOYxWDHzB4dBgpS7GqLusSU4nsMysKfBzASBvROTEYqaqa3FoZD9kMXWSpJ1PkVkMpsc7KGPJ6AjZjOp9JxVGfYrKMKljGZsndu3fJTUmwHdEccb2pyDimygSEe7J4xMa1dK7h2fVTnFvh8pFlv8DFQBZB9S2VcjxbntNt1thJyXRWMt+vyV3GYj1wsX7Gsl/ihw2L5obHjz5DtJovrXsau0fXLBMQBV/lNf4OHydPgJqU55ZjTqiYpr5abNpMemsDgWcp/+ULfIHX+DVe5hWuWfCH+EOplxY6rE+LSSoKT0DRMyZhzkCWkn1CYiRsuQricSDTh2vOeYkH2DS2XLCkoGSTKomejktudqd3SK9DHlXATpsmGmMCBAUAzNmksBGNZs6cCRMyMhyRjjZdTVmakqR/bYU40Qsb1Dl8EKGPMUqi5lVAG5LXQYZOXJRtOtGYhFPbRmDnPvUcl+B5nGAbKa5TmC5agbXYZCunjJbglfTtLoBNzMNJEqWZJIkyyCYyRE9RFPSDo9lsePXVb2A5jpAs0DvnWG02ZHXOqlnS9SMxM5xfX3B+vdgpI7/e7T2xCWxtpLYlGUgkeWYtfd+TZTleB8Ywoq2i6TZUUwGWYowUhaSu2Ewn8NDSDyNFUeKCTBmMMYxaaKFllYtkOUr/lmUZTy/OybKMQokHXAyaTbch+hLFSFWXeNvAmJHbgsF1rJsNl1fPGMYWpyJ2DLRty6ZvUONIXkGWK3Rhcbbi7uFd5tMJ1gaMkjHRsDqnWT2lt2uarmXj11TVEU82K56sh6TwWwFwwj7iHRR2KrmBgcc8gTQis0lWC3IaZWR4HN/NdydUPuMNXkej+TJfTm487EBF4RN4LFKd5Bhq6jSMdOSU1NS76YCg3/q5nxmpqVBERjyWkpaWA47o6MnImaYNq2fcxaZJVaJxDCgCzW4gOuzwD3ENMmySdkAchlViLshzaBJLcHcLYjFvTGJPaskdsM+V8Vvzla2KcYvwG2PQEWxmBQ9ILs3bzz+/CWxvWyDQJ9Bx+zUhCIi5/VkxpmmOVrRtuxtfhyA6hc4FmmRkIuNJWRPKGpbO8bFfew2A3nuuk6OztRabSx6kc456b4ayCm1vwfOvd3tPMAYhUtscR2TwUqYGraUF0IbgO4IL2Bx8hCLXWFOgVMDaghgV9XzC0DmyEqwdadzA6MDmpUSQact8Mkenvrme1xKNHQxj7ymPeuyguRpb8hiITx5i9yueqYZX77+fCY63rs/JO88LxZyx3/B0/Ravv/3rZMqyv3/KdHqXqCKhGWg2PX6xYPbCHU7zSMxOmNiMV1WHGs7xzcDkNGdS1/jhMVdXV1xdNxzPXuGDH/omlCpYLC/ZeIeeigz0V/gSIw0NC9rEFcgTSz6kk9QRUp99a0+u0XyMj6XeG76L7+JjfIwv8SV+D7+Hj/NxstQCxHTeucQYtBS0rHGASo/d0mHSyR+RXEDLlCvWbOh4yJt0DBgMHQ0FGSsWlGi6FBbSI0nHjkCVyv02ZQpGoKZgJNIz7HgR280gpJ+9zx7XLBGbUdkgbs/r21uICqLkSAxOTlSip7YF/ShYkfdyfxgdeWHFaSiFgMQgNmXWWHx0sqGkClPIQbcTA5leybPcypLlSQTa2EOiEwMYLSQkR9htGOtNl4hgihxD4+R90ARuEGPUGSViu27YJKxk3DR806sf5OFbb3EyrVATWN6sMKFk07UY/f9PAtFv661pB/rBY3Qu9hkqUpYFeW4BQ11lRC8CEKJPTK6SqpxR5DUxWGxWUZQ1WV5jTUWR14xhJBpNHxybtiNETVFOhZY7+04AACAASURBVJt9uk8xyXh6/ZRHC8P09AzVZDx9tOLiouNaGWKumOztc3pwl19//ZN87skjnvY9gxvZLJfMCsNhVaNcR2Wm5LbATOcUR2fke8fcrK9QsabMFesxUhzc4/0vvp8XXijZKw/IvASh7Jdz5lbz4v1XmM7vMUaRmz579ow//J0/AsCcCY95xmKnDlBcconH74JHfHIcKsh2c3S/K7YFfvtFfnE3zvsEn8CmsdqWXGR3+L9NrYG4DdtESIpoZkwSthBw9ECgSo804vm9fIdUZUK6Ta2EzDHkK0YKJDtykjIGTQL9dFrQjpGj59iFgj/k6TmASa9hu9n1DAmfuL0FHbHapKBOOcWHvpcR9M7QVhODYmh7olYMw+08TfwibkeDIHZiMYGF268BdlUEaKk2klmqbBCS+5BrJcSg9H0uyHRmO6IEdhjLSKDCUKZlKj4JWarSRiBSp/fojJJPfvaL+C5wvWxoNl2aQERymzEM7/F2wHuPziwB8YEzSpNn0k8NQ4fNPH3niYwpAtsmnzsLWlMUFcrYFHApPZLNhTqqTYZzAa0MRSEBkAGVEnktN+sVk3nNcnNDyCPMToh9z4BiM6w4qU/JlMVR49o1m7DgrfO38dZDZtBBkWuD9jD2PdqDqmrMbMpoDMpIebherwl4muiJtkCRM8+PiD7iXeTq2Q3R5Eyrfeq6xjnPer2m729HO0ssJ2lZzJjsCDMjycMf2PLlhQwkC2frx7fdECTkJKQWIOwm/8COA3D72H2C3NQu+MMkcG/7daDT42omqU15lVeJRNodWUhK+I6Omppsq/ak240thedoEvzokoFKwCbcQKNo6dm2LSoBiSY9v+004PlcQkDyE6KQfDIjNOAtoy/ibxdx2iiUAp5rCUi/WVnQAGpX8j9PEnqeEwC3lHQQHGBMLs0hOkjfZ5TGaNEfiHaZHbAbcIkkbVKlJglJS5YJlN2+fo0D9tAsx57zTcdVN9L0HcZkKVDlvR4+ohVeBfp+oKzkrY1uRCtFH0YJAs0cSuXJdnxKkVmq6T7aTGj7jkltk5BDMdWKzgWCjRSqTAi4pqxmEsRZa6xV3Kw6sr2caAve/9IZ9+/coeIZRwffyJeaL2BsQV9m1MWU2LZ8oNrj9W7F9aYhHyrmZclmeUCmZ+wf7+N6x93pGZf5DU3fYY8fUGcv8fjqCUr1HBy/wNhuaKJholuOJ/uMww0utoyqY5Yf4MJIs2o5KEvYP0O5Wwnov8xH+at8iQ0tFSUBh0cAvZi2AXHBkSjxrSPOdnFsJcBj0tCZdKKq1OHH54hEQGoNDAMdGSWWLCESnhl1etTAQE/BlI5Ncj8q+B/46R2BaUOHJ7LPnIZFQvqF4jylZpHK/TGhAAUZLUPyEZQFIZCnTAhaeja0TCmZYJISQuqMkcABBSSgMLNWfiNKiROwlgBTWdQRHcBzy/2PSomrz+jJrcY5l7IL/K70f55EtCUKbVmHzrl3TBuMMeKH4R2Z0SgCOmq0gjGIGjBEj4+QW4FEFTI2rJD8xZ6RAmnNxgTYigo0Y6DHE2mI5FjucUzLpWzV7chDFkyNofWBrwNhAL+FSkAp9TeUUs+UUp9+7r5DpdT/oZT6Yvr7IN2vlFJ/WSn1JaXUJ5VS/+Jv9vjATmhhM3mWLgjFsh9bjMlo254QRNBhs1LagTIFWkTEBCQqsrISZqG1Ek/uIj5oiRTXVrQJKmC1/JyiKDCZuMTYrEAXhnpScu+uJg810cMeBctVy+AixmTs2ZKu71FBgTJkRSmutL1jOpng3ICtxGp7jCNNHBmCMBvXiyVohR8UQ29o/UheWZzvIUSq+ohx6Lm+FonqfDIl5or//h/+RQDe4C3ucwcgjery3fz/+RNwW9pvcwqA3cfbE1e+Lu5K9pDKcZDNYQswDglHUAkwNDvwkdRSBFSqNMpk8Clax5wJ0+d+rmbBNS/yMlOmgKJnYE2XSvxbrcP2e7ZjwS2+EeEdr0t4DZYuEaG2I0+VLmurNdH53WkcRicgm/fiSq0VGP2Ocn4L6OVpri72X7cAX7rOd9ftNmjkNwKBt9ODkIC9gNpZ3WmtdwxEnw7pwbnd65cWJ+wqMpGDD+lA80nrkWzSEdao8Chi4nyM1Mw5Ysbae2b/L+f9b6Ud+JvA933NfX8e+PkY4weBn0//Bvh+4IPpz58CfuK38Piyw2qPVgMxDLg4MPhewBidYXROWeVklVB5q709DqZ3yOoD8nqP2eyAarZPltdUszna1EzLPQ5m+0yLKZN8yqSYUpUKY6AyhmldEa30uweHe1zdXPKJz3+SUOd8ZhWZndRkoyNzhsX523zhi5+nshVnk7tgrOgTSkd1cAdbzFknn/5hcFxsrnhz8waPzj+NbmWObvMTrDE8fvaUy/UFKjqePXMYUzAMS2KMTDljvHGM3Zf57Buf4cnihrOT9/FD3/ujADziKY94exdEolLJGBND4PkTXz4b0dxqCrbaQpWmBluK8VZsVKDJgDx12zlFMi3JU2cv/TyQJgWiYhRMYmBFn6b/nhkF00Qk2noejHi+yFdY0yGchECTGAK3RXRkTHhBJFKmSYQsfthSoMdUt8w5AGTEOaWgwPKYG+4ezCmVoixL+b5U3rsYODk8wkcnNuba7nr3bbmvlCzW6NmBf+9sDZ67bp/7s71vOznIjN1hCtvvbUfH8Z0zei/+iGPaoEryHY5jyXYb+dYZokcs1fvUAkSEPbllhIjhCrzJYzocAXjCJT0NU8xuM/96t9+0HYgx/iOl1Mtfc/cfBn5/+vingF8E/sN0/09HOdr/b6XUvlLqbozx64nMn/sZIlfVQPAemyzACUhPagLjECn2NT6WnBwekZV7+JALFJV2XUmryZjNMtrVmjIv6NqRMW21XmkJzagL9vantGGDqaYUylDGgdguebR4navmMe66wXQF9f6CPTNj5QdJly1nHEz3WfoNbr3m9PAVciyr9Zoni3OK3JJPCo7tHl94+BTcGwxdw/JG89L+fdxywehGTDVndf0GnQ8sVoFqalOWgvgkMN6wXo707hYY+xJvsmRDj0vjppA6xttTHm5Py9vR2js/v8UCskQs2vbVfRL2BCBLYN2YxngGEljnkRrC7JQLYv3tqKlZs2FCQUuPY+SEOdc0aYAnysMFK0a6nRrRJdxhS2U2mGQiYul2ASoGhaghx0Rp8mnDkGVgE94gk5TcSlDKqmsxNiezGWEYyazl6cUlk7JgDF4MRVQKvEljNFH+SUlO8rrYtgDPMwSfrwRgWyFIqwHsMANJKRKTV43i0aNHKKUYtlMCNJExne5x5/8g1Y3c1+PSRry9P+64IDmGU465ywtsWHDIMR/jY6l6EzP2kmyXx/C1t39WYPDsuYX9BDhLH98HHj73dW+l+37DTSn1p5RSn1BKfaIfxl16bZZlWJtR5hV7e/uUVUFeWIqiZhw7ppN9lDVM85LCSkhmjFE88ZObLYieACUgYFHVaK2ZzWY7daLs+o6jg2MyY1F9wDVrNt2CspqgbGDYrFmNC3I0x9U+GItOEWcAJojFmSFiY0HrOtbjGmtz9GSP4A1tc0G37qjLikJ5Dmc1p/sz8myPyaQiBssYB0aXM7UVk6KkHwKzuqC2Cre6Raq3ZbFKyL3f9fl61+8/X06z+8xtkQm3M/ntI6nUT96evuUOQATBEEKqM7Ybi4R2yvhqSJ8ntQQSkVZjkbAUlcaP2ymFAJTy3Dwjc+ZpvHc74CtS27EVGgHp+eY7pqJOgOEWJPPATZIgh4S655lEhW2dpLOsoKwq/Ogkbn4790/CHbk2b4VqISVUP+8X8Nw1/A58AH4jRrADCzVSrmj13BRB7rot/6UdiLvfM2yJzylAL0Gg2zpQUJstk/Of8gkaBn6Jj1FQpAmDp085lu92++eeDsRtaOD/9+/7qzHGb4kxfkuRWyZVjhu7dLJZlA6sVktGN5KpnN6P5OWBXKzVIaSMAq8ysFZssa2lKieyiLOc0Ssyo6kyDSoyjj2TaYlzjk1zzbysCUOLHQbKSclevU/m9jgrSi7aG966fsTms1/EZxkffOF3sNKBRXfN6f4DXn3lJU5mh1wv3mBtOorpnJjNePrG2zTDwOmLH+SP/St/nJdPvpVve/+3E7qBpuupybl3cJ8XHpzxA9/9R1isr7BjyX5+l+nJ+zg6e5mgSuYndzl58QEHx7eVwA1XRAZyLEM6PbN0gm5PRPdc2be9UGBLD/ZsqTU+neOeQJ46SSEGFQRGJtTpNL69QEXJL1uRS1QlcTIS5YJnxAINTQpLiewzQzOSodLC1kRccikauM8LdHj22UvbgE6zDoVnIOxky7LQ+mQu0jEwYUKfXrdsTLe3VSvCpw984AOM48joHcFqmmZNDA5ts0QYSyQnIwteotbtjgastBaT0ec2gnT9Au+UEQNSwab7Rzcg0YMBE43Yh8c0DdPbpSeBKVl67VLT6LTl3tYD28pO/hZ0pGbCFvZ9xgUaxRt8JQ1qXVJ9iP/SwG+/gOipUuouQPr7Wbr/beCF577uQbrvN725wSfWk0R9jX2PyTRZlrMZO/K8oC5KprM5WktIprVW0Fwtog+TYqck3aWgqiqJFouBoi6YTGoZI1oNwcvfMeB1oo0WOUo1dLam1DMOpiVBy5AtFJp1kN5ba8hCwen+PqvNiqubC9brZ6xuJPd+eXXB2HTU0zvkWc3BfsHh7JDBDTSbJeu+ZYgje9MjBq/IiprCVjx++gxb1nin6UJAW0Oz6vlv/oo4/AjaLpLZrV+ALM6R5wEluD1dtifL7X0xgXvZ7j6xKRNHHzmwTBoNCsy2JRBt24btx7AFB31qHRwQydI0u6Bg2Fl9sft6ATXl+W5Hh884T62G3Gom5BQJZQi7EeitTLimoUly4dvx134tQqthGJhNptzc3BBcGtOlCnDoHfV0it+Re0hVgphzDMOwk7bD7en+tZ4B8bnv3962n5dQ03falG1vMl4MO17AkCqq51/fNm59+zvbvsaYZkEADWsCkRyzY14W6X3dVokZ0BDeUVF97e2fdRP4u8APp49/GPhfnrv/30pTgm8DFr8ZHnB7UxDlAuuHTiSTWrzwpnklIaGZISsm9IMneIXOdKJ6WmyKiopRyBjOOXRQzPamYKW8iwp8bugYKauCwnsePnkD7XpcCLRjjhrmDK8PhGvF2aqiUzmf/+qnafuCh5eP+PLlWzx5ds6enfDS3n38YFhdrejzQP/kdfKN4a7qCeef5XJ8xrd8+MOcHdxn3+5jfGTYXNA9+grH8ylvrjZ4nVPO9ikm+xyennG9uGa9PCd4xcXTBbkq+ff/nf8EAINlAMbktrMF+rY8gK+dkW9hI5P65y26Hgg7vr7Yg2VJ728T2cjvLsz43PfB7bhxy1BUKPbYQ6eLUCcoMsfg0zkNcMBeylY0u3Ggwe5aCmHAZQl/sGx9CTZpY9h6B4hZyLDLXRTM/fY1G2PIlFw3g/NcXl5KG5OyEyXjQrFer8mytBE+x/p7HuDbLuavXejbTWH7NdvKAW4rBKGqK3zYTmyEIizCodQZpOVnEjdiu2nD1iHS72o5m3r7wFYTwm7rE7N1h0oYyXYrlQ2l4P9h7k1jJMuy+77fvW+NF1vumbVXdfW+chbOkBpTpEgNOSZlUoZsQ4QhwrYAG4L8RV4AG/BuGJANyDZg2AZkWZANGLQJUdTQNHeOhyJnema6p6f3raq79srKyi32eOu9/nDvjfcyOnualr7UTRQyK+LFi3g33j33nP/5n/9Zo8N0UVvxyfGZwKAQ4lcxIOCGEOIu8J8Cfxv4NSHEXwduAf+KPfy3gZ8HrgMz4F//rPODc7VAqwpfC5LQZkqFTxAY8K/V77IWrxP7XbqdPqU2dNB+r0NRVIbO6ZsFkmWmqSYiJ/QDWi3TerrVihCBxA9arIQZaTYjpCT0NEM9oXgwpdRzfvzFL0E2p9RTDvSQ8f5d3r7+Bmf6GwymY9ptTTopKX2jK5jEEbEIONMP6KzBlVbASCnSwT3OPf3nefPVN+l6ApV3yKKQM+sRw3nGJLuFL+eg19nsPsbs4BblLKWqJuzv3yHfmyN1DeYYrr2HooXCtOEKLCwY2B26sumjCiz9VC7iSldhiF38JuUnbEJJ2BDB8fANHdWEEbWHYW4aoyXgdjJHIoqIbbrKfI42CUa5qGLKhMD6BAUlEp8ZGTGmUCYkJLJMuMqGAwU5fsPImQInYd/H4xaHYK8LKoSAXlIYj1DAJJ3SimNkbgG0MDQ5ewlJHDKazBY0X89y7+dpvjAKnm2MUhTFCVDQqQs5qnGe54v72K4Z811okDYNiNIo4Twy95kdLqIWYJ9B+iubAaoWIUFBtcB2aHwr7jVtWnj4TJmQWo9MW1RgzA9RFOHPlh345U956mdOOVYDf/OzznnaUHZCizJFKUPQUMr0IFT46EpTVLaaS5jKwyAISefpomFkURTWukum6QBdlUSBJK9K4rYhtwSURF7ASqfD3mBKNFPshyn9/gbZ8SElJZ2tTfIPX8dbCQmGM0bzgsPhANELyMjptFbRKmU09PC9kEQGVONjcqWJg4BcdkmLFDUf4GceQRXS8yOmqqK7ssJqP2JQFNCOiKMuK0kHoVKydIAuUkqlWItaHBYDqnlNFnLMOSMeqogtvVQtlqlZMM4jCAhxZBu3iCMCUgqLMit7LnOOjAzT8ry0hsPcjC4cqLn7yqb+zM5lblrPAlqe5bk5kRITrvTpUFnkG1jErO4zu1Ags2HI1NYYOM/DBDDm3ArFsTUAa72EajQjDAN8X6OEWYRZnhGHUd1l2u7ywpNoXTFN54azUZYEgYeqoNDFCVd/sWgb3oG9z2sKcp6jtULYxd7kCUANljWDAheiue9FU/twwoZJhc0GuDl2oKp7Xtowzp07I8OnpE+XOYcW8HVgqm8TtKdDd48EbVggCKRA+mJhZQN8IuGRhB6tIKQTdfGTDtqTeH5IGEX4fkjUSghaRocgiVsE0igSe2iEMs0hwqhFWVVE7YAgbrG+3kL6GRfPnoMnV9ne6VFmOUVU0l29wL27u6yvvURr9TIrm+v0t9e5cXQdLQJayRopisoTtAnZXrvC8c1d3nnjBxzcvc9rb9xmMO3wuSe+QjX1Sas5yZkNMmIuXT7DetKlDHt4rYjJ4A6x7NGWgmp+RD44oBX7nNtYxRuM2FjxGE2MNtwLXMYoB5po3jECK7tEXemtkdcCs8SLxU0mGzCTERqtbOMOad3vWpeQRcbBhRF6gR3UygN1XYHrjWiO07huQV061ivQTJiTMmdOisCjR5cI07tgzHQRAbsbvk0LUPTo2jClsmGJATj7xJxhhaPRjG67vXDZ03lOWGEFWjW+F56oCnSknqJUlFb3T9uaXlUZb8EsYHVCL6BJCXaUYTc8ZcRqpJJQudoCUyCESyNqAwq6+33ZANhGbfabc4bCDMeRcN9MjfeIBfhnmAGmA9Mm3YWBMPUWcgGsnjYeCSMAmlIr0jQly3MrAW76AQhtdv4wjGmFBvirLJVYSvB8nygI6SRGysn1pHfpwsiPbONJo1pcKWWai/qKfiDoEjMVAR45goh+vIoWMd2NDr4KmCqB55swIhQ+SdBhns8odEAYGkOEFyFFQOwF7N7fZVTmtHseZ+Iee4MHpNUU7Yd4QZt5WTJXMaNRiq89+lFiEeYKzxf4fsjGxhYtPyaQAf/ev/sPANikS60g7C2svPmya61AwLrmwWJBQZ0qdAy0Cpf0M/uPO6a0+7gjqkDNFlTUHgE4zIGFjmBlsQQj/hlxxNECgfDt7WoqCFNmjBcpSOcIewtvQlKQ4eFxxBGuAVnRcGuN8VFs02Y8nZpWZtZVF55x7UulFrUXhlJuDIAnDImnxpH0AuVXZWVSgnBi0bvfTaMAZsG776Gu5Wze2U5lXC6MgJtTcAtbLHZpt+Dd99n08tzcu2RrEwFSKLp0OWKw8N4cAzOzGo6fNh4NIyAAz1A2W602cRyjpSawu730PNMaOk+J4xi1KNYwHVqVzvE9gVQFqjJuj/DAk4Yx1m636bTbRpykq5GBot3zuDU4QkvBjpfgZXNm0zlqcEgcRJw9f46LT66S65I46hCvdHl252mSMMEvFEK0qcI2oipYXd+gLFL8S5fZPL/NjWuv8e79jKfOr1OoDGZTgs0tDnKPu2XJ3v4BpT4iLcdsh108GZPOj9lZv8Ra+ykGx1PyWc5Od4N/9L/9xwAcYSrswOgKRhgJ69CmCU+mA4UF+MzO6eMqABWxTdQ5r8DDKQZre35s2k9aP+GT/ANlY06B63+oLWhlWqBV9ibFvm+XBEFFi5iYkJiQDgkVmRUfM21VpkwxEmbRIqPg21xDQLC4sZ1vkpMzo2STVXw8yrJC+h4ZiqwqKapykfuXErKsIPBCYtspWCmDMegGX0BXmkB6ZicXctHFenGrNhiCJv0vLFpRL/6FoIs1GIEFEktlmuSZZKaJ2Z3hrqgzIP5iEVd4OPanM77aSr4aw9CiZbES2OfYSObZoiyFJiUnIP4hfMFHxAhopZBamaKgVoxSZuePow4kLUgSjJJwSODb3Z6SwPcRgUTKFogAGUYUWpHlU5QuEa0QP/IXpZsy8JnNUqoi5O2bI+4xpy99RsM9/FLijff5+N7bHBf3OE4ryqjL2ubj5MWEajhlvbvBU8ElRBQzLMfcne/z2Noxzzyd8Oy5i2xvneenv/Y1zkwjPnj7j3hnlONXmvvZlHvHxxxKzcPBEbdGH7PW8en6Lfpnt/D9gomnOPfEFp//wgs8f+YsX7r6HL1gm72jkr/9X/wNXud1fFtGqqlIrfynZyW33HClRIU1FmD6CqQY8c+U3CLJpo3InAyFYLrIJAeLBS8t/wAgxG+4op7djRyAp4hp4eFxwABXVWhSlx6Otzi2PMKUwu7jgtQKhVaUePiL86bkOAw9X1RC6gXduQJmGPXo1oJGbdqHOyAvCAxmYjYES91VJa5ttxGcVkbhRyjCyEdJbVSAMdLglT4pJ66U+SerOs5XnEzFLnZzBUILsrK0GYFaC1JYX67OsdQEIJfybWIwTdDQZBJMuDBhYjMmBoUxaePKzqUJFWdkFiw8fTwSRsDNptaaw6OHRFFMXmYgNUVpHJ9WnNDu9o2b73kopRepGiVgnmUUhZVyAlqt2BA/woBSVQSBQAQ+ma4ogXZ/haKoiOKYMs+IZYuk1YcwRISCspygS00xHJHlinCWMR5MKCOPrCgQcYtUZQTxlFjtc2azpC0DQt2itbXBLD0k9z0O5ynjdIIf5vhRTqfnsdINyWfGMa88gYwC2t2EsOsxKkcIFdFut/Finxd+9Gn+g//ElGAosGIdWHafAZIMv15bIo5bKOYVbhcxXHOzzF16EHuTOX2+ZozqbsBgIfdlvIPAAofua6u1BhWr9Oixgm9rDTwCZszwCXBS4hUVCQk+IYGtTHA3oTuvQ8zrakcPR5Mtya2ZqCypSHHA0eK122xRKkVRVeR5YRZtqakW8b2irPI6ZlYmVndMU63rRiOImt2nlMZVCYe4Poj1z0leZv1YYBemCxnc65pgLZys6wAIGgbi5FKxJKbG447dmS9qLmpuhwvBfth4RIyAEVyodGn6sCtFq52AJwl8n7id4AUGsMkzhScDwiCu67mVRggPhakIDHzj6kVRhNbKSD3LEi2Niu40nVGUJaIEAg/fD2l3WoTtdby4Bdr088lViRAFSoZ0wshkHzyjed8OE4o0J9VzVlbg0tkeohR4UUjpa/yWT+VLBuMByAlUc5QsCOOArt9F5ZJKTtCeJE5a+FHIuPQZlRlSS4Kkjddpk9c8Enx8W4vvLeK8lJQZMysjVheXeNYgGC5A7dK7hVO3MJO4vL/bhZr/d7tJk2UQWDQ/sLuNo/wafeHMypvXRUs+Pn2rf+BkymZMFs+7m9/Rk3MrKWaeNzhDQrIIA9wSM+GM6YgUW45Bk3gT2ptf+mKRAozjeDEXWmuzWwsBrpS4oQeglK5BPiRtEhwq31zEjrTVzPMDuN4QzeN048ddv/se3HGeBUKbhKzl3836EPe4Z41x00C40LDJH1kej4SeANoqtQpFp9cxrZVKAYEwdGAt8aKQ2Isopc17V0a+SeUmTi4pqaqS8XSEBCLPCFJFoaTSJUmvwzwdI8qMztYq03FK7MfMvTmrT16mLVo8dmEVf+zBvT3uP9jl0tY2RSF4vLdDuZIynt3GEz3ObG6QlhPK+SGvvp9zZqXNetJhp/MB0z2fnZ2Eff8Ko+kcNX6f/kYPnc8ZDofsbD9BencIxV2Os3u0gi0ubF5kMJvx4OERqy3JRAvWSslHe7tcPv9sPU3kFJQUuN3I7JRGaEPjhCnNDeLidGH3eZM9MJTS2mF3foC2sa1T9alBQ5caNMu9sOlFJ0disANTa7DJFje5ZVuja0wbUEVmewq0MN2Cc3JW6DNgancq4+EYfoNaxMGOK5+TM0HRpsXYCo06inFll4TxGjwmDEmskTJeikdVmBjc+FIFoW82Gikgkj65qshzhzNBi8jG2fUCduAnfLJAy3lTTWZmc8FG1jiZAKBOD7KECThvwlyR4QK4ugHnZzSNsROJgdqLCvCJiRap1sByRlKLEZ02Hg1PAE1epURJTJbPySqFDgIqIZEiJIo7eJU2BG8MkON8syDwCDwfqRXpbI6UklY7Jgp8ktjH9yWtbo9CVXhhxc72eSKZ0IlabK2tEyRGx02pnJg2BRXdMic8vEM1/IitMKbf2SQMuvhKcDi4gfRjJsdTzncucOf2hDuHGdOxoNcOUEqxNx+gyjHn19tEs5zs+JjZZJ9IdigGh3T1nKDq4Ksuvp/z4N4D8uEhvXaXaTZnVOZ8MD4iaMUMD28vZskU3JobO7OVZh0iAgSO4BtQqwhpaxhyyzA0LUpMww+DfxtdABcmLMegTqHIDIGpgatTVc7VzUipyNhjtGY9SgAAIABJREFUlzVWMBqHlc1EVMQkGNFRE82H+MyYUqcTjaZgkxpcWLqwq56rKElJ7fEm7i0XC00RWgdaYhqV+ARoayICPCI8WnbPyy13QNpink4QsdFbQSlNy5bzuoXu/nbeiQuuHEjXLNV2n705mn0bzSyapWg4Eq4Yq6LO+2u6tO3fdUm4sHPXJbHgrmwYbXNcRMiLfI4Jc6QtR3belfdpiiI8Mp6AJop9RAhCxkRxB5KYwPOI4jZhkJAEbUogihNUVYBWlJWGQqB1wXQyJ/A0VaqQQUDU7YKvSaKEdi/k3M6TVKuX2V67yNvvvUp3fRVdztHpIXsfP2C00qU4zvBbAV95IeX+G/eYvv91+k/8q6i2oF9sk5b3+Hi2x0uzS6x4ikIrklZFW3TJOmvIUcXKYwOO9+ZU3Qu0Zh263W2q7GNuFj6Xd9aRxw85c7nDvWpOknU43Hufh/cETz37o+zdnICqOLe1zrV712m1E8qyrmF3fABDIzUu4xRtc8TY9FtpWXlmAYRACyPt7cqFA7sbK+vKQ717NQk6zijkVrtP4KTJSut6Goa6YRaaVudzu1h6tqzY6AjqRUmyQWQqaxR85lbcvGh4Hm73AxbJUCOtxdKicOw6B7l5i1RbYT+dmZfALjQrmmIVfopSAzkRASUTooWn4/wMaXdwsdjtm0vcyXuZz3wypncjs6lOZ4TrEEvb62Lx2xnvCVMcdVqc8O4EYybWz6u/K2GNkdGM/AEdYgbMcDAlQOhLVPkok4Wk0QJUCFRlmjPmeb5QYAkjnyAyaZ08zw2IY9M2WgiUsJzxIKDTbdNqtcjLAj/ymU2ntKKIw2HO8WAfIVc5c/Eirc4qUkvT/bcXI1RBOjzgcPcGx5MO/fU5m8Emw2pOoTSoEaNSUXBIlVdUfoiolBE29TvE7RVyKcmqmLkWCC8g6QUEfgIyJJY9+nHCRmcNP+rQCXuE/iqlLiiFptQ+UlWsttt0ui2i2KfSBasn4ru6INhlpJ2WoDMKemEUtKXpusLjGjR0JavNn6ZL60KCJsDldsSWTeC1aS8MSGAzCi3aBEQ4xcMOfbsUqxPvC4I2bTSCLl3A7Yz2foBPLKb689TDLYzKouXS7mnixJV5i/h6Sm67E3u2C5AxMoU1GQJtuyLXef/mvLuF3ozfm0ZgOXZ3JN/T9B2ahq5pZNx1OdWk+rOcxAEWawe9uG4anosDh30BUaPE/rTxSBgBcAIMgiAI8QLTO96otmpms5mRhgarnGoMRFEaZyrPc4LQI8sK2z9ekXQT078tSciKgt2H9xkcjrmz95C40yZsJbT6fXqeZiUSbK5uo3SGV47ZP76Ft7JKuAofH4/Ihw9Jy4r78+sIGTJKh8zLgiSOCDyfTOWsrm0z91tkaYzyfdrtDoPsCC8UHE0UUdCDStHvr5J01mn5MSv9TaQX0+6sI72IPB/QaUmqrCKoBN2wQ7+/emKe/MUN2Nx5TpKC3DEOLDSOZIkj/Lg90rmiTaFO99MEsbDH5ta99BeLzfzkGKXf1Jb5RkS0aDNlboMX0w7d7Kxmf3MeRnMhn6yEdMRls/SqxaepsxduERWLxeF0EevF6wwaQI8Ww+mcPC/Iy9J6EO49a8JSPU8nKdengWunPd+csyYhqgn2uefdPDZ/u89kvjsb9hLQVI9arBv7v5o8pMksVtSOTKagVAqtHnHGoNYQhxGRDPCET8tv0Wn16SU9POEbvoAUlnkliMI2ZQFeYLjhwhMUlelI5IchSI2uMuZlxsaWR5XlDIs7VJMRd777dW7OPkSVhxxWkjOjj3hhWxF6FS9depEs6/Pq7TdRQ0lwdpN/69kNnmKXJ9qKw/1dBvd3+Xh4jbvH17k53CeJt+itbPHwsKLwBTf2HuJ1zrFz6QrffuMV4jgmXT1La2uLQhVMtaLIfG4eHeP7HTbWn+XcpQt0O2uo/fcp7n+X8PANntKHRLszjm+9u5inhMjGtQ44q4EldwM59V+QtimnYEKKtouhbkleswydIvHyTuQWmxtGxEORoThmTEld4hoT2w4IZvkeM6RLi5SUY8YMmDIixXQVisgoiImZ2gYiTdajy0iYhe12N0efUazQs7UGBjz0kcxJbSET1sQJG3VjP6cJEdbpEgLxIuypSDDK1AqPlPnCIDS9pOb/m8bRzf1yatBdS8XJNO3yTo2d8fqvZlhk/nJ8jcIGU+7cBaVliRhsJ2yFaKnxWiGFMFwJCabjkTqJVTTHI2EEpCdQSkPlE3pGCUYqjV9p4jihlbTxrXio1po0TZG+h64qhNQI6REEPtKXxLE5Nq1yumHIyvo2Zy+1UWXFl888Rql9dt//gDIPUelNKj9BH7/PxJ9z4eIGv/KzP4Vo9yFSHBz0OMg0Z7aeoe+v0xpXdJTifNSh4pij6T2EqkjiDQIvI4g2WFu/wNqZS1TpiOF8nyyHM6tnaXciphqGpRGSPpzcZ3B4lye3z/Jjl5/kiviYf+7KDs89eYELLz1G9+w6R3sfMBWC3/7f/yMAhkyY4LhlrlinRrCbcbwbLlwwzPJysZjcjeY8iCZNuMkSdOd1P6WF5Pp0bKghyTCdkHIrB+5hWoFNmdOlS0iEEy71FwSkGlWPaaExDcTc+wYNo1SnIc0iGzPGx3VKkrYIKsDt/c47cW3UDHvSvXdKhzaFxTVMR+TMeh2uBrI2sssgodvN3WPu87lxcpeuFq/37I/7fLUsmvlumpRphdN3qH2UpjE2DVoNLJpRMmOOlIIyL5BCm96bWAAdkOrT04Nmvh+BoZWmUqA8sajNbrfbeJ4giiIbKjQqwYRzm8zfgW+UhKPASZIbVqEUmuF4hPA8tEjpBSWXV/rc3bvBpLpPIH1CGTBCItMUAp/uRkw/eZJIb0HU5+h4DLHGX9Vc7a9yxV9BtHp0vR5aZaACOu0V1jsblNpD+4qd5AyMNLEMCWNN6XlM5wpltQ4Gk9R8Rik5KxO6YUlPSjr+KmHcI8pCJg9v4rd9Kh2jA7M4e3SIMI0/XG7a3WTNhd9ctM0btbL7EXwylm0uuOZ5TuICJ8uJnasd2BvXaRQ6XUDnpTQ9DQ/PdizybSbD0WjNN+qIQOZ/WHfawIJ1Os25x+aoukT65PWUFIR2rzTkJSfQmRHa17j3dkGIPmV+mim/5fl1x57cvT+JDzQNQnNOm8al+Z05roX7Xl3mxPNMSzUpBUHgE0UhnoCWF9jna60DYCF6epq4iRuPhBEQUiJlRDfpIiXEUQKeQgUBUkMozAUjBWVl+OHCVmN4npFtiuPY0IlFZa4qnbPRDplkU17/8GPixGctyvjC57eZPPT5OHuT++OXOV7Z5nuHGhmEfP+d7yNm9/jClT/HQRURn3uWiyvPUqb7lPP3+epLZ3g+1BQ3X+OJY59Y71OkGWUxxK9gXswZTg5ZXWvz/o1XWQ8VvpdxOQnozirC8SH9wCfPRqyngqvhkEm2j5yPmYZdXskVv/fxIUfpKmtXv8L6zpMMp0eEtlX21CAgjJkudspmHO3y+/Wu4SA2QY2t191s3HGhbfLRdHebYKCJ0GvRC0XFPkeUVKRk1t02Lq8R/3Q7KIyYERNRURDg0SIiY0aIRFHSsc3MYgJLPcYuRpfn94ltKhKM4QcWXkAtsGIWVw0w6sYCM3rMOXoR5bumrRpNbBn9TUO4HKc3fzfnfXEPLxkK2Xi8uYsvG4vmMB7PyePNuSRCmJQmWLkyIdGVsnyZgJ/7pZ+nGwREtoOXL8HXAt+qaM2LnE8bj4YRALqdPp6QBFGbNE3xfNMppixtAkwKhPRt/4CMqjA00CI31XdOYkx6oNIUH4GOIipdsrXZpuWF5Nt9qlLy1HBOS/lMx3Aw0/T9itVZyu7DXapWQCvUDEWbMgMvSphXXdLJjKK7ycXuFBlUzO68RR9BXknKdI6vFWU2p1Ax5TTDH8+Zi5S2F+D5HZ7aTOh6HbIsoxpWFMMSL1snKGJmZcpw7HGkBJPpIb5XUeQ9MlUg/YxekHP/lf8BjwhJbG9etVjQy7uOGy737MC15k7T5APUQqJNluBJtNph7i5/7dJxavEdehYClDblZvL6RhLGxK1GbagkIiS16Ldb4DEhLSJcTWRiW6FLsDKZdSGxh2CN7iIWBhd/126y+UxGMcEBhq6Lc0FhFZvNMbbkbJHyaxq95kJ3c1M1nmt6S+Y9awHQ5bH8PX3ScMhFBWf9GoNlLGTNEEjf1FG48uaiLPjD3/8jpkWBrwXK1jtoIfG1IQs98p6A1kBZ4QsjdZUkCaqSKCUJohZREFDmBVk2p6oKq/arUKpECI8it62kbOyzutZnbW2Fo+MZuchIS4+dsx0ioZGR4N/4y7/EKz/4Br2gw8d713h2Q/Fc+BEb/S6v3RWsbKzx2M4WKgI/09y88z7X3vkB6ID88b/IoNhiN+5yf3dKtC0ZBQX5tKBMBZ9/+nE61ZR49YDPr7do65KN9JCWn9Dq+1z78A5v3H0Lb2WbpBUwTvr40VmCpE8lC3y5yns3PuL28ICnXvoR+mfXKaMWYz8k5RiB0xOoTtxqdZxqtAPcjpnY9N1pyPYymHUaOt183qStjGlxz2v7Xu4WmzOjoCIiIMHIXOfkxJY156i0itLKkZrYOCJixARX2OzksWfMTiDfCsN4HDMlszl8R+EBYck5YhF6hItd3ngXpQXThPUGjKZijYE08/fOGLq5a+7QTepwEx9w83ri/uYkH6N5jub34Dyw+v8sXH+JIPRNHQylWoTCxjDAbDKl0pppmRFEEZXS5OWcrCxoxa1PSKQ1xyNBFhLCxMqtuIMWAf3uKnGvR+CFqEqTCYUvrG6gJ0nnU3zfCGOBxNMK6du8qAxo9zscPdynLHM6co1xeky0vsV/+53f4t/52i9yWE74WfkY3rknuPXeu5xbe4K07PNz/8LPkn30LqItCFtd/A+P+N7D79Ou9gm8Ff77v/MbbP/4E/zLX/08+dEzvLz3gMubFxnefhN9JeAn2kNWOxEyHpAVKfejqxw9PAaVsb6Zko1mnL2yw+G1ETpUvDnd58nh43w43Wc4PuLqxnmGgxkfpQ/ZnA/JvPtIsQqPbTMpXEgwYZU+KcMFBQWau4yh6rqbKbXpok167DNazPmn7UbuuZMAY32jmwDDEVkkrkeeoxCb3Uwt3HVDYMrwwbZBl7Rp4VOwygoz5pQWNHSFMC1ajBkt2I8ugDH0ZrNT5rjyKWPgzPvktiVaYOFAQ112IKoRIVN4hGhKUjKixhJwOQqNJiS0Jdb1Aq0JQyf3+WVMwD3WnMvlrMyyoXCjapzbuP9mtxdSkpeuLFoudBNQBhhXaIQ2aykOQsoqhdJHC02ZF3iyTiMvj0fCExBCUGnFLEsJgtBUAyoBlSLyAwLfx5cBkR8sijxcvzehNGEYGotpyXVZnuKFAWu9Lp6qmE4zdJrDcJ9h8YB+0qPf3aEqj5BTQd7Zwl/v0W09QVANKNICqRI2oxAvCfF0THfrAn47pqymdFb7rF3p8FMXrvLCiubJMMebHNHvJKhOiyDyGFRj7g2naNoUWjKpBOuJhx+tUMYlcRIRRQGdToduGCPKgNFkzNHwgPl8TqYKZpOMqT9mPJ0gg5i/91v/OcDClXYusnNr3Z7d3OFdHZpHjQU0f582lmPY5k0v7Pu6Y3wrMOrIL05rwNT/S1wH4YyciBiNJienQ5sBA0zDDVexGOKYgMZQ+DZyN+/lpMlMIxR/4R/UKbzaLXeP+TalajIbavFb2bACBMXS4qgzBUv3aWOxn5aRcYZ3OaZvnve0cy6f24F/zWIm87iHL08Cf03JM1f2PJpPCUSAZ4F2KSWqfNRLiRFESQvPDxECko5JGWlp3J0yr1BFjipKpFbgGWJnWVZ4nmdaTFca6Xm044jbt29TTeYEgUcsJjzpK7h1nyfOfpn/9zs/4I9ee8B9WvzgD36diyuSd157h6gTkk8f8msv32D/W/+Yt957Be+5n2bcGRKvrKL8Ducf2+DFZy6jDseIqUcr3mH33pQg6PL6zT/k7XCNQ/kEx0dzNsItnnniBTKvR6kVOk3xV84SrQRMphVJ5PHs0y8QbJ7n5uE+D2YTju7cYD5+gCh6rLfXeWrjSd679RabvTa3HxwQlq5gaIpE2yo+lgIDE7G7RGIANo1WfmIXW96ZpL19PZr6da5BiViw/hzXHbD/V4vP4VJdRp/A9CpwfQQMBOhCDPP5S6t84AqEQ0KMulFGZbEKs9Drhml181JTKRjYygEHBmaWoiyoC2ucJ+ET2k9jmn3mC8zAGBY3D8tVfMtAXhMLaO7yy8Dfciiml37cPLuQIQjMol0WMimVCXkdFuB2/kobPQTDCRDkqqKoKtKiJIoC8rL4hDFZHo+IETD13FI4FBuCIFjov3sI8CQyMB2AAmlcUGEpw0EckZe5qTiUkm7cZjaZsxl6iNInCXw+dymgnwT4OkcxZRxMmQ+HPN32SQpJNhmj0pwX+5LN7Q0685wyrZhWKVG7QxAXxP2IVtzj3s37/On33+Ta0YiP9j7i5YMRt+7lxF5EHGlu3LvFS1cuc2ElAekRdbrEXoxAM5+V6HjKwfiQMJrx0Z09Pnj7BrN7+wi/4vGN84RiwnAe4GceK0mbXJYQVMx3d/m//o9/380Y2YIOc3InaaabfJtvbkpznTbqG1V+Yidzu2J9jtrvMP/z7CKqef3u/Z0GkQtb2rQX5c+OrejZkMLlzo2xMvmOk6Qa17Kr5jQ4fkMtslZ7Jd6iZqBOxZXWD3Ay324hNkHRJsvQjeWUoSueWs4SNI/5NJzAeXGOqVnPVbUQRl1ucvJp/QvcsU4kxRMSX0r8MGCeFwgNnVZyKlDpxqNhBCz3v5Uk4JkUSJ7n+EGEH4UooShVZawhmnw2tzoCgkopsrLg7NkdsnzOXGVs9XusdNrMul0OkgmRaBN6MVERceNOzFvph6g056/99L/E+vo2l86cYXhvxGxynecuaUqZcK4/5ICCce4jkj4TBHEgODg64qGYc3+yz+pKh0mwyduD60zlEYO8YDqe8Nbeuzz19I9wda3DdHKAl0OoY3bncx4Mb1LMQ46qfdR8hTfe/Uc8dr5kZXOPfmeTc2d/jI2VZ3jx7Dn20pBKnOVPXv0NfunyM0g/Yz59AECLjMjmkutuwp8En+aWnDtrLLBlV9YZgHoxnA5euWOboKCj/rrdszYmdc+DwN7upqrNFBi1aJPYDkKO5lwj/AVO96CZu3e5jR6dJUNVkVuj4NJshlCTIywfoJkZcUbR1WRiOQ9NQ3nyWk7WAzTnqqm9ePKWPpk9aD7u5stRih17Q0rjvje7JDcX/2JHl3Uo0GyA0jw2tc1WRSg5mgxp/RBg8JEwAgJBlhdUErQMofIIfJ8syygq04Skqip0pQzIgQESBQo/9Ej6HdJsQr/fpdP2WYvnnN32WJ18iLr3Bp30LQ6vfYs/vXmL46Mh73zzO4Rbm/zWWx/xapZzbf1F3vAe5/XdA7JUceOffJs//XDItdsfowdjZr3LvHV3zurGOc6vPs4b9+6TBWe4X80ZtEOCEK5ceYl4PuN3f/3r7Kc533j5VbQXc8HXMD/iw4fX+NWv/4/8/ve/xcblDUYix1NDVjbW4dwag1bGUXuV69mQQWdMtHKJb7z+Ax589DaqjPndgw+59NhTPPHFL/Pbv/VfMgDqshtl91qDERgPwGDmnt2lq8aN2FwMNfDmmHrBQphjGRRrouHNMEIszuv6JUpchyMH4o2YW067ICKy7EfTp1Ba/UAnYXby3MsgnCYjbRguaBOibYzvgD1BXW/vjFZNSXamzqVQHdOh3pVPU+NZXtSnGdXmcU2mYXO492gKoLj16zwBl/5bFjttKiCXyho+pZBCgzLHF9pobeRFSiR9Ej+g+CG+wCNiBKDT6YAQREFIVVVMJ3M8TyB9ibRdXvKiosorROBTzjOUFggJQs3xA0FWzNFRx8h8+0foUiDFEB1J1no9krDPJB/w2ObT5KOU8/Eaadjm5vg+qhzQUQlqBOOtHqNKk6mHpDLjlTvHaD1kXgUIb4qnTPPo+ThFV4rI67DWT6iqnKNoj/X+ee7vf8Dd/SO6vVWKlsfe7od0VEmWFRyNP+JomHN3OCZLR6jUpyIn6SZUQpId3uDbb7xCnmiC+YR5obj24B3m4iFrUUT/zGXAqAEsA33CQoDOBa8XrxnNWNTtYKrxnNMeWN453WhW1jUzEvXRxjAV5MwocAVEJl0XUdpio4ltWAKKYwZIAkwdX4Vpsi0WpcrC+gPGTQ8WbrzxPlzNpNP6M2ajalyTmx+n0euoPu4anf/krsuxFt0VnbaIS4slNJuAOIPQnKNmzO+8iKaxWQ4llpucnhYGuJ3feApu/q3wizD/c2G1lJJpVRB8Og78iBgBKVGVxPMCpO8RRCGh74PWqNLwz7J5StAoh9S+R6lLqnRkqvNikKLijDxAVIp04JNPDnjcP89+Z4wfp5x77jEy5fOXf/oXeOu1b7P5peeYBCNuvPkqYXCeXVKO/JwbrRfYeOzzTHffZLv/5xlNb3Pu+a8xL3LW+yskQR9R5QwODrh1DDu98+xnOfdmI474kP7Zx2nLC3z7+79Hv7fOeiE41z9HZ/0iG+t9SpGz1V3hjY9vEwwekpIi5Rn8ss31998jm+Tcmd8nHAyY3tfM3zvg2v3fZLW1xe1ccvbseQAmVLaQpi6wAXfjm6XR3PGXF/ZyTOv+73jry+PUm3bJ1QVtQT5jDoyCcWHd7Wzx2fq0rcJgSIuE3CIcxoiZVyZEdonXqTnT9LSuehQI5o1WZs3QyNUCNMMd99ul4kxoAE0jeRobsHn9LsxxPR6a4cryfDXPsRxinEgtak4AeE0vAPhEY5O6m3JNn3fnkdKjLBWeJ5ilczpRTLuVfOL7dOORMAJKmyKnqtAUeUVe5eRVjvSMs5umGVQKXVZ4toV0pRRJ6NOJEuKgpJplbO8knF9rcfXSKk9e3uKpC+dRwVneuHaLv/fuu5xd22RFbeHtfIHtao37RwNG+/ucXd/h4vbjXF71+YOHJSubfXS0xtqDGaP5ET/6zI+TZIL+eM7No5AkSuiGffpCU97+PkoL4sER8wdv4Y17HLz3TVKmiNynFbRZO/sUj1/9Gc5d/TJ4GV4+pywUaTrgeH2VG7fvkquEvVvvcLE/oF2EzEZH5L7GS4esru8g5xVsbPHB3rf43r1XF3OXEONZtp5rKuqwckeagZPEoOXRRLkVtcCnywosL4jlwiL3vIch5Bi40oB9gdU9MuU8AVucQVj5Us8u+T59OnQWxqeiIiJmRkpsNRGc0nFzwdUU52DhwjdDGGndf/e4U/kJGvMDNEA+ceK8zTlrgnjNfgAnPSJ9Yj6bu3/zOTdqnKFewG4sk3uWEf5lb0FKSRB4C2HUvlXTqipFHNY4w2njkTACQgq0NDRhT5r+b17oMc9S0qzA9308zyOvckphe9Fojaai5ys6FcyqnHHmMdIRvd4angyYpVNe2X+Ne/6YbD1hms7ZVRM6YcLKhaf57pvf4M1rt5kzJGydpRefx+9sULW3GKZTvNYFQrnC+x/u8oUvvsh07Sz3773NtJjT62/Qb60ximCeHxDILn2hONc/Q1YpEpXgyzZKw9raGvtqTpIkrHY22Vp7hq4P270rlIOK3toq66svoosOaytf5ekf+Utsds8Sr1Rc+bGnWNk+Sze5zDQ9Zm+0RzEbLOYuW7jVerGIa6z7ZCXcp41l8K8m/RQnnnd/Nxlyboc2aLs6cVYPjzn5AoIrUDzgITEJqRVHnTLlkIcoKts00yz3wvo4BsCrswsOjZA2S+A+w7KL7Xouuh6NUGc3jCvv8INafVk1Xuuur27WUu/izexL03NoegyneQfLYGHTQEhrhIBFc1S3oN1ji/O4HgnaFt5hhHjKss4olGVJ4EckccJ8ZkLnTxufaQSEEH9fCPFQCPF247H/TAhxTwjxuv33843n/kMhxHUhxAdCiJ/7rPMvPojwKEoJIkDriiLPicMWnufjCdOFCAyRIhCSJPTpd7r0NwO2z4T81LMJz3RTblzfZ/f1m3zjvev8w+sPGRchP3H1Fxjuj/nua9+gG/ukwEtf+RIvPvmTfD5sk/eucvvmdwhaCZcvPcX1j97j5svfQcuS7fwBk+u/y+3xIc9/+at84ZkfZaLH7Fa3uT+9Tzf3qdQO3zt6me2oRE5THuu8RKQ7TLIWoyrjQTVjX+VU1YRuK6SkTRI8wdb2k7SSx9hsv8TFtWepxBZ3pOJ71z/g7KWXKHXJbKuNPNdls/Msf3zj1/nc+ld451bd7b2pY28YdyGur5/PJ3PUNcnIvb7ezZZ/QsLFzmdulvrH7Y4aRwxyO6Q50ukZRlY70C2PmJCKlE3WmDAnJKBFSIxneYROaVja1uacCFGMYSmp2X217DkYLUI3AuITaUAnx2XvuMZOfLIIq/nYaV7BMg6zvOiXn3d/n5YlWD7OKRybv9UnMIEmh2AZNIQaT6iqCiEEs3SGH4V4/4zZgX8AfO2Ux/87rfWP2H+/DSCEeBb4q8Bz9jX/kxDCO+W1J4ZJcxiXRWgIvJDQj0xLKFVXC/q+j+/7BFISeJJKtmn5MEtLRBBwdXWNy72H7M0OybyATjdiu7fDmd4l4ngblU0JA81KHDLXklE6QMUbyEGCJwSz8QFClsRqTBL4qDxntd/lz22/wPv3r6M6ZwnjdTrdFTqyy8NyznFR4AcSUcxZDztsrrY4s/04WVYwmoCSHsfjOZP5AdPZiLidMBpmDEuP8WjO+x+8wazc58btD7hzcI+HD66TH2VM8xlhsMV8nDI+3EepAoqHXDj/BMXwJKPPsw5zYMUlHVDWdEdPFgNx4vWn7U7LOII7dtmrcIvG6fg5roBGL3Zep4Kc21JjgWBqqwvN5zfvuUIPU8ojiQht/O/jip/M53cEJmcqanagyXQ4MTVpz22qLZpHXYACAAAgAElEQVSeQvOamtfe9CROVmOeZPadFlp9Gh7QPO/ycacBhE1voOnuL+MBQRDgeR6e59FutxbyYc22alVRsLa2znyeLaTWTxufaQS01v8EOPqs4+z4JeD/1FpnWusbmBblX/qsF7n20KFvNeuCAE/7SC2MkEhRUmY5QhmpsUIV9FY7TI8+5pkzkpHyGA4i3v74PpF3lT+4c593dm8yKDQb5y6T9M8yPy5phW26m6soL4JZxe7N+9wfHbH65DpKevjhId3DnPVU0QlXubN/m6Ho8cVf/Bp3bn3EOx+8QuX38ESPNI7orKwicw/lB0yUYvPyc1y+vElW5Vx5/DnWVwS//91fY7h/wPd+8MeU+RxGESEj3vuj3+Hrf/gPIRC8c+cVHhx9k3brHvnD97l//S2++Ye/wY13vsdsMme9s4I+VBAMeefey8zVtcXcufZfmro/QGDTgs7Jbd7oyxJXUGvgub/dgnKEnOYN3NS9cyi6qcozBT9u4ZSLfH9BhwSJIiBiToHC4yf4KhWmd4EjBE2ZImCxY0tOhhzucwUNj8OEPOXiupz+TjP1mS3aclWL3X75es1c1rF+8/qbWMRpYYE7pjmaXsLyOZrHNEOE5uuUTfc1d3shahpw0yjM53Pba7E+vqhK/Dji4dEhMgzYPx7waeOfBRP4t4UQb9pwwQnhnQPuNI65ax/7oUM7tFMotCrJ5+kiHirLcnHxwvcIpI+iogzgy49t8tZuSa+YEYwKXnvrA14tJ5w7u8Zoeot3bnyLe4Oc9249QOY9vrB+iWI6INWC2VATS4+f/+rf4qn+CxTFHd58bY/N7gy9odm50oFCE+ojjnaP+ejjaxxMMv7k7jV+753XGN25zQc3PkDMRqwGAbFc562Zz0xdRZPz/v1dphV4YZub++8yOrjHixceIww013ff5pf/xq+gxIBcQ6fsUxaCVHlsX1zlzOMryHzO+YtnURPNut/jqMiYDiPeHP86ctzIL1Nr0bm/XQERnKSpfjayzydeszyaQibLXoZj4Rm3PyKywiFHDBcLNLNswX/M14loUeEvaMWF9SRKckobCGTMMQoFzWakGYWlQbsF24z9HdDnmm645bgM7rlrbRoE99t5RadhKc35PG1Ol0OwZYOwfJ7mcS5rYVqt+ydqA5RSlGVJnueUZdloliIXorxgvGaALMsWtHpHMDpt/NMagf8ZuAr8CLAL/J3/vycQQvybQohXhRCvpvOMOIkR0hZueD5lNce33WUNm8pEuAjN5tYa48GQtwcVh3eGRMLjrQ/fItVzHnzwBl+68gu0wpiVMKYaj1GzGefOXOTG4T2mYcHR4JhxOebS5Sd46/p3afklV1cu4ScJN8oCVVb0+jsk+Sqfe6bPdw/f5mrsMzq4z/X9Gdu6YqA0utzl4hMrXLv9kDBSvHdnly9c3aKNYPfuh7zyzu/xhTN9fvL5z3Mu3uDOrbsUM4izFdISRBBSiSmtzipb61c4u645Gj6gTDTb5xXV1OP5519kNBmyuhMTxevM96d0NluLeTQNSeWJXQvqdFkz3l12cZsx8XIKsRkWNI9t3vzNAp7YtjsP7bumZFSYYp2EFibHr/ARFKRsss4exzzBc6yyakt8A7tTmyUd2aoA12HZxf9Ou8CxIVyqzsxHiGmy4tnQwkMu8gsnZcKa11eHD7UxqWsM6sW7LNHePMdy9uK04+qw5mSJsmgYHCkFZVmaZqju8zV2f2GLiySGNOcaqy7qOZrUY6XxLND4aeOfyghorfe01pXWWgH/C7XLfw+40Dj0vH3stHP8Xa31F7XWX2y1YvIsQyKIo8iQhqLIeAdlhe/7VFWFLz2SMKDIcvrthGCaEgUBH+0dI/sJpZRUkc/x+JDhrELEPYJ2wk7/cQiOmWUzokpRVAN2zqyxuXGW44M5gUjo9tfY2tlEKslUpARyk+52B0SbbrLGjz33OQ4HNygG7/OlH/mLFFpRehF5EVGU1/D8Lfxcs1vO2Tn7OHujY66uXqG7fZlCwPjwmPF8xkTP2dze4O7+PVr9gLIsGY2H7B09RMiSKO6RDh/ghWfQYsbalRV203sEFLT1Gh4tkrV+PY/2xm32C2i6/u6Y5lhGspvG4TQAq/n4abuah0dKSmwViiqaXkm5kBdzufsOXSQBz/MiQ46s3FdIbDsZGSPkgD5TLm5255OUXfc5mi518/HmgjvtseWagqaKsrt6pzDgRlNj4dN2+OZ381mjBggb57MuvVvMDhNwoKDTDmxiBs326svSYpU2TVY/bfxTGQEhxJnGf/9FwGUOfhP4q0KISAhxBXgC+N5nnlAKZKWJpU86m1qPQFAJcyGeLwlinyQO0eSsJj5KVvT7HlzcILr6OK+OJ9wThxwPHvJHH/8Gq224+sST3Di4S2u7T2/jedbPr/P8k0+z1emws/0sW53H8WTEw+qYWTGlKGccyjGx2uBC0mXrwlP88bW7rCXbvH7jAbfe/RZ+HiHaT5CNp4ynOW+++jIPjvZg1uPLj/849959n95Wiy/96Ff4K1/5ab71g+v88QcfklbwQM/JgpSzWy+wE1+mV0I/WKfT3+D60QfcO8wN1dPvks/HjAb7XHvl/6a1HrAfeLz3iumnOJo0XXdJauk5bvhLxS/GSNSuc3MRNRf5afn/Jl6wfFMbmU7T2ExgRC9rBWLjhickgGbCDEVJiE+B4iIXeZ+3OOKAIXP2OGLA1PIJNE5IxPAHYhwPTsKin0JlgUC3+N3ndbiFo1TXisXLVOiaFSgQi+KieiggsMIkJ6//h7n2zblszrH7u/meNTho+JJB0BAUVcr8KyuqqlpQhgWmUKiZPjTh9MnsgVKKSquF5/Bp48+SIvxV4GXgKSHEXSHEXwf+GyHEW0KIN4G/APwtAK31O8CvAe8Cvwv8Ta316UoGJ9+DIAhRClZ6PeLQiIuGoZn8Mjfxjx+GRFFkWouFEXEeoNp9ZkXG0d095vua4XCA9+A2ycpZXv/t32SlmPHGrT/h4fFNjidTzrTWOZzexw88dvcPGB28w97+LncPB7x57X1iL6EcHOC1BNPyDoezklt7H3Ht41tsrKZMjr/Ph6/9Pzy/8xN8fHjM6uoaf+Uv/TLD8XVuHN7mhUtf4Y+/9036/Sv4K+fJZEZ/peCLX/wy3TMXmI0K+juXuDP8kK21M2ytbzMYjunEq+xP9tl9OCBNUy6shlx96XMo8WWyOwes+DHPP/skB0cFGbPF3BUUth1IsLjVnMx1Taap41z3+HIcvJz7Xnw3p7i9BiD0FtkIn4iIkMA68j4efbrEBFRkxESEFnQrMOrH++zZXVaRkhMS4Ep6ndyZUTJO0eQLMrT7ZCYt6ARN6h+BWLRVc0vctTVvnsHHudq1+94EDM31QkRoW6GJE/PXDBtOAweXMw4n7vdTvDDjORnSnNvJXSPZyMb4QgjTZMcK6Ehp2qejjBfgeR5Cu2ybMQaSmnPwaePPkh34Za31Ga11oLU+r7X+X7XWf01r/YLW+kWt9S9qrXcbx/9XWuurWuuntNa/81nnt7OB9D0jGlJqfASh51NpRRj4tPyQwPMYjUasr/dpexmqrLg1GLPRXqEza1HdPebZc210PkWtP0G+e4yUazylznO4u0+SdBhP91EiZegrVla3SA9u8ZPP//Mcj+8xrPY4HHwEccL6ucd47/A6wYV1km6L1779Fq2NDpcuvMhma4erW5/nO6++ipiV9C+t8/LLL9OJ2twaX+OD8QMCcobZdW5nAj/ZQSdbbOxss//GhxzlQ1TZ5sbh23hr22RVyNHxQ9qzmKyouDW9htQeTz77HFfOPE1QKoaH24xHD/D66zy5/jP4jY3exZJ1nb+JYZsxp9HO8xY35ien/5NUYmkzDM241UfSIqRN3BAZrchIScktfGf28AFj5hSAJMRnlTUSEioUHdqkaEK6lGS0SOjQQaKI8dA2WyBQRECBKRLyMC3VTDu0miFhVAwd6FfhYVqb+7ZuobSPGX69I1mb1KQzA6eFEwLBnCkr9O281QbDAaRubmq33n0vnw7EnWZU3efRlWmDrpRJ70Z46EqjNQihKcuKvCioKtN+XWnq9ullhdLKegwVPvXid8VGp41HgjEIAi0ckAO+kEjpL+STK88jDhJaQqPLY+6PYLcYIc6sc/iDl2llY7YvtIj9C7zw5NNsJNtMh0e04xY/9yv/Gs8eDrj94AP0Zsibd7/FjXf+a64dDVhthaSrJWv4dNOIzY1VprOPeeqZFf7gnVf5zofvIiYhT1/aYW1UsKsqLj31Odhc4xd+9mskeBzdvoNXTGjJgjKd86t/8PeZTjPGgz2u3fgu9+5/m5WgzeuvX2P17BXC44rf+eav4nspn//cz3D/o3cZDm5z/eEbFOkR/jSl26qQwWUOZ8dk+ZRLF3dQox06saKsxuzee30xc7Ht7OPbVJu5VZdrAsxwbjKcvBGbHAJ3M1cWXPMXwJi5iTJypjbl5l6PJQA3K/E8C8iVVIyYcMwQn4AeXRJaZBzxOFfwiWiREBOQ0CEmYhWfHjE+gTUhKVucwcfs7gZwrGzVoUdIbK9SW+ShFgZxLn4zxPEWAYK2BoATc+KGe9VP8pMIBIElT7nrbnoDy2Xcp4GG7vdyBgFqcNZ8HwKnhGw8IiuQUmpatofDCa+jsfMLjLfQbXdBBgtEw5efTtd5JIyAEDatIQRS+AhhF39lLZnSSA0r6322z68zKxRhBULmfPkn/gL3xxNW+gkP0iM+9/QzbLTOoeMWIR4dL/z/qHvvMMfu6v7/dZt6l2ak6TM7dXu112Vt3G0wxlQTwBAICSUETEkCIYQSCAlP6BBaQgjGECAGbFwwttfd611vX+/ubJneizTq9bbfH1ea0YwX8n2e3z+bj555pJF070e6+pzzOeV93ofmdVtxxjMkF+bYsG43kuBlavw/CLlDjM+foySX2LJxPVmjgKlqSIpEMZVF1iskc2UE7NgdIcqJWTw2F06vh4OD03jlRmINHnLlAnYcpOcztHlbKCl2KqqO4JRQc2nyxQwNASeiAoGGLUT8MumyxpFzR2hoDONRbGhZCUckgqqVKWkKhw6f4shLz+L0yiQKRfKaiEYJ2S5gc64AP2qce9bOVMtbrzXnWc7pr4X9WudYjXKz+P6FujPUmHC15b1utZlrLM9dv8hXavGs8t9iFeKso5GnyDwJCqgI6LiwU6GEgoADN16CuGlGRKCLIAkWsHABVlxhJfipUqsRAKobyQqE+kKkH7VRY0Ra6wbV20RyNZ5S69pQP8w1t7U7e/28a+HbazMK9VmF2q2W4akdY2VW1NXxH9HqsbGMJxAspVCpVCwODk1fRiD+oXFxKAGsoiCH22LiUXUTSRCRBBFBVCz+wUqB2WSS44NJ0jmN6aUEkgl7J6ZRSRLp6EUqpXhRL9J25ZVs7OpiY3cPdz/1YxpuuBpJDONRl3jx+H1saX8TLenz7J35PuXEDNOzh4jnMkTDrYi0MT89wat2XkYuZxKfHGIplyFXKHPLjlcwrA0zdOIAojZBbMCL121S0jIkVYFCMUfX5u2k0tNohoSeSvC2m/+G4mKSUzP7KGUyNK2LoZWa6QpuYvTYQSRflra2KJevv4FOOcCucB8jI6eYzx7gzPxjJBclTMHB+s5eBsJXs73vJnZ337587USs4hyL5ruGgGfNorLGhWCq9e8TgRpLj/WcTs0CMKv2xUoaz1IWlsKwXIUaH4CEtWDt1RClCwdNhFGw00AzMywQwo8D8OOglWachOinkR1EGWOO64kwyhka8XOIOIvkaMeDjIgbBQ+uqv0AJQrLArMCJv5D2QJLCfpwV22Yl+/g9RkEFZ17+TVhQuh1tRT1EOSawls76t2D+j4Ea3+DesugPpZgBStrVOk1Xghj+UgFq89gsVxe+T1rbENq2dpEqzOtznGsHheFEgBAkChrKkhgSlZqQxJAMzVEpZpDNUxS6SV27Grnpkuux9fcSF/WpOSAyfQclZ5GbIkUslhCcXSwof1qfHqJdHwJX8FBtNhBPtdAtpzEa7yCoO8GVJdIOZPgxcGnUTQFl8PGtoHL2RjtorN5JzmfQtFup2X7OpxKGFc+SUqM82fv/AgHnhtkZCxOOCwTa2qit2cjc6Mn6W3zo5gmwdZOnjjwPHpKYFPDbkyHwvjkKTqbRTzRMGPnHJSTKbZtvYS3v/ZqAv4oWzZfSTyfYq54FkV2MHz+KKfPjtLd0sXinMDjTz/PmRMjy5fNElQDrbowa6bi2qDTheIBtf+lqlDbkPDiwF3tASBSy5uvFPBUlst2V9p+1jB6KjUidGs+uebToqNgR0fAg48O+tAxsOFGRiSIDTcqT3OORxjhdX8X4Qcc5Z2f6uYkU/z8N5/kMz94PefIsJ1WmnCxniBRPDhwEcCFHztgq9okK3UOtdBgzXyvZQmS5JeVpVytLlztGplWC3PBslTnSVArMLIU70qR0doCovrru6JQXh4QXOsirHUVarWTK2p8pcALTBTsy3NJSFaAXZKRRQlRXsloOHH+UWvgolACtainYIqIgoymWV2GZElZzn9KioJitxH0+PA1hlmKx3GpNrqb3Vy9fhNpJAzBwVgly1JpGK9XYiIzRzlXYmLsNH3bOpFNGYoehidOYgu3IJRlMrkhcnM5RodPUqlIGJUKdiNIxkxTNBfoaG5AsAm4GmMYJuQqIqKh4LP5KU+nqSSLxIUw67yNiFoFXYRW31YGmptwihpGZgiHu4TiMlA1jXIpjqvBjU92kVDTtHV2Yfc2kSx4OD89xETeiSJ7EFAQRZn1fS30xzQy2UWm5odoDDmIBTuWr10tUl0jAYXVvm19VmDVNWeloWlt4alVqK+JSYESLjyUqiU4tfOujZ7XOPxWz7tCViIgWYsQo9qByEmWJB6CmAhEiRHAyTOcAODDX7mS5uZW3vRhL4Ko84FPbCGZmicca+emP+3jacbx08BzTOHAV7VO1Cq5aC1QJy2jBa3PtbJL1zzj2sKvpefM5UfGsgJYO+oDiLVja/GYtW7BH4sFrGUjupBbsRKb0bHXdYiqP59FiW4NzTRQdSuLpmrV7ty116pVk39oXBR9B6j6MQJWlsAh2UCUKFTKFuOQYVCqlFEUCZfbR7PmxtfWyaQwjGnvYGF2gkZnG0MvPYc7FKI0m8QbdFE+O4NaTCOGU1zf18rhMzpjxiRbehu5f9/j+MoBNl2ykYXhcW7Y8yfMTKWI2N2UEm7GiinMTIatfVdiOiTsooFilpHnfGzvDvLM4O/Zfv0WPK4yr9n+Gn764H/jVnz09jRzduER8sXzLGh2tl/3RjK6g7OJ+5mfmaO7I8iBY0/hVhR27mhh55bLeP/f/y19G1xkZ2NMzDyEXvGSyBRojrUixGx86KqPc3R0lOTi8wTDNnzhFSS2Wt3JtKowrkXC1UY9KnDtArXcCTsmFax25pZrUOvZp2MhE9W6OSzDesV0deBAq7IS1dh7amShGQpkKeNGJkuRDFnCuOkizL3s5Vs/eRsfXbyMWGMPimcah6RTbPViTxjoriLuFg/i4hLrAhE+87Orub0i8P7xGNscGV74eBaALsIskqt2PBKriMHaJ5CWTXYrviFVrQUr1Vlr1ApUd/5qeLWafxcEAdFrYGQvDLy6EIlrTYjrMy7m8nUxVv2/VrnWK1Ur5bnaDakp+9r5ZURMs/YNLDmSqjkSq2rTyo5oXDhDcFFYArWhKMpyztMwwG5zYuoGFc3qPiSKIJRVkqk0LW4PU9MjeNo7GRmeZi4/TUNjDFUoky7H0Y0i5/KTJHQDMxgkqXhISS48Ng9HziVJJc6z49o9zI+OoEsmi9klosEeDF0mkZ+hYrPjDLVQVpw4ygb5RJzJBY1YW4zW6HoWRieZTBwl2r6eSDSGT3fjFDMcHjrEQk5nKV+hUkxzXjmKzbQzOTqGqlRoiUYJeXyUdRei4eTXz/+U3kY7YlFCsWXpbe7G7vVhyDJlDSanUrx4bpB9+09gJDVy6RRqfqWJyMtr417OjAMvjwfU+731vnOtY7BJjU58pQch1FOM1yLxlhVSolQNG4rUPG+NCjWeQxGw4USjggQ0IHMve/nHb7+ZdHaJolrtI2HmqGgJsvESTn+YpXSK48efYypRRHTJXNqzGWdzCNWuEGoMc9mbowCMkqCBSNWiqSx/3vrvDjVLwKyKolGlPF9RAPVjFdPPCjRjlRuwli1o+f1cODC49vm1QckLBSlrz9csg7Vgr9rv46jiNVYUi0l5uevTxZ4iNEGRZUTTinbanC5skg27zUZZreDyuwl4/KjlPEK2xNDgKN//1cPouTKf/N4XOZ9JoigSh57dS17WKZ2Nc/78eZwRiSktxb4nTvLs5BAZQyMcDRFtsHNjdA8PPvRNIo4YDjnMkwd/R0dblKVKhbOHR0mli4hIjP1uL7grGKUA+w49yHd++l1GMrMcG3uBT73vA9iFMvm8Tm/7ALpTY346g8pubM5LKJVKHHn4MI/H74bAEgNN29jUei1L+SJt/iC5cp7zB07Q2tFExcwwOjLP8ZNHSA4v4FcV5o5Os7DwNIde+Abu5CNIuXMEdQfX9F6xfOksnJmKvLzr1ARcwGq7IS7vhLCyqGpdgQXM5brAGi6/XM3D1/oDCtXsg4UQlJaBPbUUnCV0MrWOBRaK0MSFDQ0TDZVmOjCRyDDNBjq49Bub+dw330rEG2Qsd4aupg5KzilmMmeJ56fo77ySUKSR5u4QV297Ez2bLiVktzGzOMEtm17NrvUDjI8kiPUEOHbkP3jn313CKNM04sWHo4oWNKGKItCp+f8sk6dJVSwlgCyvAHLq2XtrBB/1Cba1Qrrip682++upxeuPq1kJa3+T2rE1foZ65Vw7f40wtb5oq6YUylXMpnX++shITQ1feFwUSkAQBCSzyiUny+imhiBqoGvYFQWKGnY0ooEgG9d10dUT4tYru7C1bMTf4mNjwE6f04diE2hRKmhiitLgaXwtPQyEgjiVNHuf24vTGSWbzGGzaZwpJSjkssykVY6fmaBUKTOcWSSXStJ+xQB2swBakoI4x0svjXL8xF5mRzPcev2lnHrsMS7pdvPbR5/jzOhxJGeUwdwoI0MZykWBmbnztEUG0IJ2NvXswjnTQHNLBEkvE/VF2dbUhaE4mR4/jexoYGEhy9wLcaKtMlrZINIVpFTUwC7icLlJlwxOnp6l54pt3PDK65hhGZuFCwMndiScVfN8peuPTq1B2EoQq94UraDhwIZUbfihIOJAxIcNN67q+1e4/VeYeSwQUP1SNNCwL+9yIs104MKBGzt9tLALP9PMcp45nuYEfeuiuF1wZmwvhUIFr6ORga6diLIDp9HJyeEDZEppMsUUzxx+grHcMM1hO7JaYN/gC+iBEOlUjtdt3c73HvkVgViE937pSoKIdNOAFxWp+smMapZDAAI00kgDetU8VtEQxdWouhohRw2mK0lW6ROshv2uBRbVRs1MX81ktELGUhN+8QLiJyEttyWvvWet0ql3+Wqt0updCKtEW1n+HPUK50LjolECHo/H0ryiWdXGIMkigqliEwVE06S5Mcx0fJ7xzCLdA10sxScQFYG2HV3MLFVw2kOoBHH47PQ2b2L0zFlkySAU82FKKgUpC4qCy+GnWEgi2k1KaplcMk9FWyTgkvEEPeQ9ErLTjVeyYRZMHB4Y6O+hWCzSFG5HokxUdJJRR4g4bUxnh6jkSmzatgFREbCXk4RcDVBIEIo0sKPrcmx2J0vpBBVT54Ydt2Fk59EEG91tnZhmlqDPxGF309TswmXPocjg9gpkU2nS2QrTCy7KPhfJCgyOTPDzh+4CoIiJQGU5M1BbkJbuty1f49ULzqgGBS30nNU7oLYT1dwErSr4VvDQws8L1WIgyw6o1QxQ3XUi+LFjEEGmkzDNyAgoRPAABu/66O3c8pYN/NU/7mYpZRniTsHE0AUcTplCGSSPl7aGGxENGJ4+R3rJRHY5mByaJ6vYkXBQLpZ49LGHWbeuDd0VolTKIisiak7lJZY4xCROFJw4MbEaj1rXAFKkCeLGRLcafdaV2K5l8anFB0zTxDQMWvpDq1//I8G2tdf8QiXJa4Wzvu6h/vwr96stj5W06GpwUq1Qa4Vs9f9AitA0TQzd2lvQQTEFDAOciojboeCJubAFvYzPTzAjTeP0Odg3fYy+gEm5MsfRp56nTTnAn975RkwNWjsv57W3Xk97WSCt6vR3rKOzoZ1yKU46nyOVcLFzQwMBZxDR7mZTWydeHZ4cfY716zeyMHaW8YkhZrNJHJfuZE/nJioFga2X9hMJ9+DwJsgsTtPZ0U1nIMTJZ7/NTbe/iZ2+dt57c4ywYCe9dBSbXSCXFfGEPJQny1TUaXqa1vOt+7+CqDkIaBKjgydJzmVouGI9ra1tbAi62TnQSae7jeHDWda1D5CdCuGINfLS2cc5NnaAlpDEhoFLGP6fd9GEhzxW8w1rV7A88j5CCBfgyrN2o1rFoUgZC6prR8TAajJapESNl6C2m9lRlvfAWn9DGZkGnDiBMBJTJMkCMxTY9vkWbvv+HuLEueIrnbR/KcLG7buJ9rTzgff/klIuSz41R14MoOgO4ulJjh59GEwnzpiMVCmyOKYhZqKcOj1Ck89LJjlLOOLF7RC5sn0nPf4wT784yJWX7kQuCCiyg/d8fjN/8ukmLnlnOxmK1W7I5apj4EJDp41O7DZroxGE6o4rQq3MpSb41Am5IBrMnUuuytOv9eMvNNbu0vVxm/phr6b7apTv9Tu4iVmlV6tFMlaUx9r/a5ZCDe3xxyyA2rgolIAVkbEuiySIVCoVTFPHMDREUyYYCZIvlxBsMpV8AcQ8BhKKu4gjX6CpqwM1FqDZJeNWs5RKw+iRdvob28lLGebSM3TE2mkMBtiyaQOpdIaMVsFnC1NQVXyBLvp8bbhSZTSPyFJxCqFcADnBuW2zdPwAACAASURBVDPP4Ao6UBSFfDHHM/sfoyvWyVRhmnxpjpyQR5EbSQsGZV1DUC6lvb8d0+mhxbOJfGqUfUd+icMGS8UM9z/5JEUjy9D0Wbq2RAg43JQ9InYpAE4HsdhmMuoSvV0NbNywjXQ+ic8eQEbE4wyhlTMUyks88MLvMVq6OMciLlxoVShvNcdClAC1mkG5miCqX1gO7HXmrAU2suLJGk4cOHAgI1fTU5ZwWNgBqjUEAlG82KkQRiSOyg2va+KW13m49oMR/KEgpqLwrn9cT1fnAK5YEEHI0hmw8ePf/gJvpIlssUzE5wKXQND0s23rDaiJOGk1g5Lz43YoaAikFmfxtm4ln0miaVZVIkIZSXewwS2giDaw2RAFELwSpiYhBCxRzVFYFoNStW36A+xFM9ZUAZpmFZ8vrKDvqmW5pmmAsNKfYe3+X2/i1/5fCwaqv8FqNieg2rl5xZKDFfxB7XXLu19d+LU2w1BvCRr/j4rg4lACWI0V5WofdcVmw2WzY9psOGSJ2YkpmgQRd0sMt+lhvqCRfOlF8imDV73ydfhbHcjRS9g38yTX3HApHtHH6TOHKPoiFlZgMY9QkignykRdfpLxYY6eniK8LkDUYxLuDZO2RRlNn2VsLoNUVrC5GkmXDEJOgSPDR5AiIZodXiiojGgucqEoMxOz+KNbkIUQx1/8PdFd13PP3ofZ0DJAk7OZLf6b0eUMmewwu7fcQcDbxsFz99DbtIGBLZdiajEMXSaIk9Ojp1iKFzkrzpHUNF7xmo/zjg+9i96mnZjhElkzTTi4ntnKOUybyeT0S9w9+AIACXJALWVnAgpPcAYbPmqIQrGKB7AWjEGJMk6oEpJYRbUVTDRMKqjkqtZAhQq1HHMJi7pMR8NLhDGSjKETxeqD0NDXyIY9t7LeE+K5A7+kLCZxhztYv+tq0qkZJmfGyZspJk7+GG9DB33rrmZDbDfbem+iqJY5tn8/9nKMhRNj7L7+Zvpbd2Gzu+ju3MLjD/wbH3z/3chON0Ozo8zMTpBA48XxEgcHn+LE4f2YikI2mUDVy4juC6+zGpWZVYprKcyVklxWkW+s1OuLiIYMy7uvNS7UpehCO3T9jg6rlUS9RVDPVVA7V30WwGCFq6H2Hsv3XzluBe9gKe5aUPiPuS4XhRIQBAFFtqGpulU9JZkUjQpOl0y+VMDtCjKVnWTkicOofRFSk0Ok/Q0Ioo/7/vNenA1O1FOzhOzr+f35n3J44jwHFl9iqHyYSM7O0+cPcf31VxDesI7jp/bjjRTo63JRzo8iKOMUy2fwRmOs9zYizU0gyhJmxUGh4EKSZtmw7nr++74vE/O2synax849vUQCAtu6t+E1gkQaNpDMp7EpDUiajy9/8YP0bHwHIxPDzCQXuXLn28mWE5SkIQoVhUROZXzv74i4bdx559/w5+/8FuuaN9Jic9OAjcpCnG985+/Y+9h9nJkapOMdb+JTX/1X/K5GIku9PP38Y2xp20Kv0sfn7n49b/7XV1GgQi0WLlGmnQDddcxutdRSbZEoCKjVCgEfDuyIyDjQEDAR0aGa/LOEpkgZsZrgE5GYZpE73jfAN3/0Hq788g4AhsfPsP/pJzi2uETrpi4mhk+TTo/wnS+9l5KeZzI7ymvv+BIyXu5/7HuMpQVkscyJkV+S0ZMcOjfHZz70Ta5/xZUUnRM4+oN0Nih8+KarMCoFPvTJt9AR7sIT9BIcn+HA+d8i2xfJzCbp6I0C0yxOZtm06Sp8AZm33rWBj37yplVrrUIFQZBRZOdy9Z11bymEGmFnvTVgmiaYGghWjKVWu1AT2rVWwIWwGBdK+V0oFXghaPeFwF61Qmijyrx8oTlWn+8Pj4tCCVC90HabbZkNRZBEVF2jrKtktAL9nZ0oFY2h/YPMFAqkFtN0N62jUYry8M9+z/Y9t1LQVdQSCBWT6YnTmNixNQTRizIHnj9NajaNP9hOoayxe+fbyJcKBO0h5s8dIxT1kpVGyC0OMpdZIJ3Ikc6P4msZ4MmDD9EccZBUUvglL/vvvQ+nrw+n0oGBwGx6CqeW58z4OHLZ4MbX/hVLyVnMrEC0wU960aSruwu33ECpnGZ24RSSaCOZTOL22MmlJmmPtiNpBexeN5lSgUJxiXQ+h6YvMPjb+zh64jihUDOqIlOUTQRFoSUkIeYkkmMn+OBnrgOgjIkHJ2kqHGPQurx1i3JloZiY1bSflfvXMKooO6tKT6vLS6907ZHR8WHjPX++g6DLw9nUGNOZBW55bxdqWSOdLpFdzNDd3UMJCPtC+F1BpAq4ykWyi4O4ve0IlTznB/fi7t6OITiYK5xDTeY4dPI4eTnC9Pw85ewRenYMcN8LoyxpCtP5BGETnn7gIFuuaKEz0IAn5MTudpG3jVCopImEGzE1CBZV/E4nrV0D3HnXa1ctN0W2USpZxKg1Pj5rGZrLlsBann9DYDmIWEGrkrleOBZwIRjxhYS8fvde6ypc6Nz1sYSV33Gl5Ls+RlGvnFbCvRceF4USEIRqJkAQsNntVrtxRaJUrFAxdLyijXSqhGFWIJli8PAst7zyDTS1bqSnv5XEgQQtbb2UHRINwXaabU4aXGH8dj+aoBL2e5nLTOCTBZzOKIHAAEeHDqKrTbzlpgf463cf5Zb+u1BsOfLeg9z1+m/xkb/4Mv/ynvtJF2YoVZJs3n4zHf51hCN+XnPtjWizRSLhRsaTCRq9Vg/Dk2fO0tm/g5RoYzJ+mM1brybiiDKbHkb2uiglNJo6oxQKJQbWbcUs5Rk+naE90kg2a3DZ+j3MTCfQKnZETaeim5SdHhzGDJnUJE5nA06/G1UtEc8tMTe1hN/XzPqefmYnVtKGJjrpOuKR5etct+xcuLAjLNcFOqo8gDZsVfSAUO3qC7V+gjV2gkWKoCtIgoyNNO5wGU1QKSd0RIeJyykzeOYs7Z2dzC7MU0TBUD0ISplSOsdApx9F9mFqc+x99kncPheJSgaxkicdH+H+3/+Gii4S8jSSK6Y4cOIJbDYo6gITSxkeffAgieb1ON02UuUUU8lF7LJCjgzNHWEOPfUMBb+T9f2XIMgChllacyFUJEnANHUkSVgVB7DWo/CyXoCCJGAaKz0Nmmh62W6/cv1fDgqqz+3XH1MvuC//nV4OKlohINGXhV9khUF5BRWwko68UCqyflwcsGEETAMEpdpkxBQxcxoFUUM1VXKFLGGPjxuvu4Zjzz1LYHcrN22+hscT44xk43zq05+klJwkVVokLDXSc/MeFudUkiNTdPVfyrnkS5Q1FTXYzjU9u7jn0SHe94Z/sqb+/j/B0FnwtvOmT3/Beu7v3wI2J4wv8NH/fBB48GWfuH8H/OzAv/Dnt34RgJL3H7j1irdx5yc+xK2yj6+/+DH++a/uZr3rXRx98TM8/ZTMlv7trG/bzQO/2UesZ4Jrr/kTnnj+QaJDBsV8nBeVFMlCDldbJ32N/Tzzu1/jDQXQZAdOh4/xmSE29+8kPT7D0HMjGJs7GJ9/hFtv/RKv/vNred2/XkPhjELqh2fxIpOtinitDt9qJqJTwUClhAa4kClTwaSCGw8plmgkyiyLy/vRO/kTfszP2UkvccrABI2dXWy6YhcVcZLjU0dItpTxL4QI+GQ6enawlDrMwdEEmXyZW3btopAexe+L8LsTT5CaOM1Aw04K0TIzC8coKWka3TZefcvVGLYW+nyTjC6MkF0oIpRnsbUaTJzJsGfPZt723rdy52c6eOi5e8jkc0RDMeJpA7/sIdwUoVLWuemaazkzeQSxvcy+l55hKa5zya3rOPhQtfDKMEEWMSo6kqRgGGUMQ1jmsoTV7gCAqZnL0qIAKeLLa0FBQa32SKi5XTWBrGVl1nIY1iuKtbs2rFYK9e+rWQn11oaGuVz6XV/LUX/8HxsXiSUgIMs2NBMEQcJld+IMuQkF/bS0xWhZt4mSbHDgydM8O3iGMz/6AV/7/X/yu3vuoj+yDt0r89+PP0TydI7zqVFGnj3AfQ/8CLnbx8LUKI2NIUrlMnPzp9k7e5T3vaFKjvzBN0IpD40DIEvw5U9bz6cDMJcHQYZbd8Kt2+HG7S/73G/d/Ynlx4PHTjA2OUubuMTJxFnKyQovjLzIudEzjMZHKS2lOTZ6nCeOHkSSJPo6u5icOINuT9K97VJ27djDydPn6Oq/DL8p84sH7+HNb34PmVyCUKQHmxCiuyeGMxambctVtA94cTQ4uTZ2PXu//ilOJhaIx0WWfCW++LOPkUVjO35cOBCq8Xyqgr6NFhRcOKtLx4aNChWyZJGxkSNPhAAKClaRsAcFmUmm2FQFETmaQpwdOkvItgG/rYmegJdQyMNCxmB2dARZchNwBWmQ3AhZ6Om6ClnRmZ48iL91I642Ly8NnkBxOXEIYa7d+HbSSTtPPfMwUj7FTDpFNLyOZCbB9OlFsjmNSNTk2tvc+JecSLJJMaeTWCyy6wo7Hr+POW2SsmDw1OnHEEU4cGwf8dkEZ8/EKS6OL/9Wpm6CblXdqaqKqupV/god01zp+rOSHTARRCzuL6wsSalaaFUTcGDZhaoJZ31wrlZ5WIvkw8uzCvBy122tkqi/r7lrUrX+YSXwuzqg+L8pgYvEEgDZvgJsMUwdXZLQU4soAT9Dw/spVwB9EW+qQr5sw3Z0kPXbr+YHX/wBb3vLG8kUpvnbP/s4bqfA4NTj5BuzjBx4lqaNHUjDC2za1kwikaU08yL0AZ/9S2gC7EEwShDrgtEx+Ou74NhDYFYgn4fuZkCG7BLceQ20tkAuDrEOcDXBRz8HwMxigZCriRMLo2y2N9DY0IKi6EScIt0tXVy1YxP3PzxDUTbZGVvHvOAnmZ+gqaWJXEYlX/TiKzoZP/wib7n9Tv5ix1a+d/ogHV07aehSiHhdLBw6zVNTEwjSErauIN1NvczOqkS3XMI/f/XN/OqLD/GBz7+OTLrC7pt72Lp5A0e//NvqVa2ZsunqH2yiiSQZkuQRqunAWvWdReBpYEfkQfbRQoAzzPL+L27n783dXH9zNx3RK9k3Emd07EW8Pifx4gidW9sozSzgb+wgM1Qm0tzDXGqc6dnzDGzeTqswQ6ejhUZXhD2b13Nk6Di6JvPV/7ib9Ru2Mp08icO+FUeuwNz8NDldY+PlG7musYlf/uwRrrttC6IukJnX8SgKDlFkfi5IOjCPnowyVxhCL5YZ0SfID3uINYSR8oskbSbv/NwbOP7UUTzeKbL5oiXspr5G6FfW5KqGn5KAoFqC5UKkSI37Z+WmVLswwYr/vnZnrxUA1Zv3awOJ9ajOCwX7oFaIZC4L/NqApFQXs6h9Dg2NC42LxhKop0gC0JJZ2puj2DSDcnKJSFcrmr1EpLGVcotJ83X9tEW7ecf7Pki6YuLwe3nw0Sc4ND7EupZr2RzrpKetgeFj55hQ4ckThxFkiUN7H7Mm/ex3QHRBvAS5NJw6BlNDcOZpCIbALkNbEyg+WN8CXQ7wu6HLDU29YLNDKQ2f+AAA//6Zx5ByeQZau9h56zZC3k5mhw5SPPUipUoBiGEPhtD0Is5IKw6c+HQvkqwhhDxIWgGfEOZ1V72Tp196npKrnUJqmp5YFK/Nx/zUCGKkEa/Hw1QuTzlTZnL4HAUtTaaQ55WX38zDL/yKpmiAYmqaqckl5jND/Nfjn+MD397A3T/6AMNzB3jL3+/hjjsjAJxklhAOmokSJoQN+zL+vFLNSxcp46SCF4G7vnAnHW0DuJt8zGcF7vn575A1DZe3hNsWZEOkk4DDjtcToVTUsDWAPxgkVS4SagkzOHWczdFexk7v51e/e5hLr3sNuYqGy+0nm87g9OfwaiHy2QSG5iE9P4dZdNDS0czMhEZnVwvTE+dJFotkC3kQFDLpEvlkGjVvUhFUSloBURTZGe2mLxKhpJk43Cq6bEMr51BsNhRFQpZXYgH18YC19PzL7oBew1iCUc3ELL+nKnz1DVzrU4P1RUY1MBBcGHFYO9cf4ii4cNDPXCX0a4OK/ydShCDgcDjQDZBlEYfbQbpSpNPvxe0IkjWKLCwmMF0xzF4P177ieh74zcP82w9+SMsV2xkfnECuKEyND5ObOc+5Ugpv803s3LCDDU1NOGMChWSeNkeUf/38EWvKr95lpX0Wz0FFhAefggd/A/Mm2HLglEAoQlmB9BzsvBp0J0gSTJ+GcgkUGSorZaQ53yKyWGbvvY/Tf3k/ppClvX8DsZYov/jV3ag2mZhbwBUIMBGfRA45sQGS04Uoqex53ZvQ7WWWlpbYO3QIxWEn1tNLX6yXuXODTI8PY/eUcMkCTz36NBPMYZhlGgJehpNLTC2doim0ie6eDux2J6opUsoYKLJG25arUWUTW7aI6nbyvk9fDVgluD004sOOC4MQTYSxo6HiQiGEk04kHLj4xqfu4RNv/wyf/LNvMTyyxIJ6FLvdRqXiIz6X4PrNr0YzBMSASWOgi2KqhE+3Y6dMKpMlVRrnmWPn2LB5OzpZfvjr/6a7sxm57GBza5DBiXPMLi0heGRkUwCHTlowmZ3I8+LhQ1TEFFJW5tT8ORyqgt/bjKGKlLUCihZkcS6JLLkI+RxctfUOGjZcSlktgc0FpWYkVGRBRDEUTKqUXIKELIsr7Lx1zT7rMwSGIGMK0EUEFQVpjelvreLV5cA1l6D+9bU79lqhlpYVzcs7PK0cJ1AfPqy9Vn9fU0A1whjtAuXOK5/1IhiCIKCpVZbUioor5OfGXRs4MrTIYiWPIDdYsdBGGJ2f42vffIwlux25PMu3//0zfPgLP8RulLl9903ce/fd/PKhb/ObX/wTTw3+krHpfbz+9tcgNPVx+U0fsyZ813UwvwTxOCSLcGoIPBLccDMYRZhahF1bARFcRfB3QmIavncv/Pl3oaENklkYW4CmAHzkbQB859/+hc0DNxH1NPCDb36dfUeO8G9P/oBAU5KA4aE0Ncevn3uc3q4Yb33bX7IwkyReOM/i6SOcnR6GygQPPv9bkHSSi3HymRjpYpZnnnmaojSLzhLTozMIWZUGb4TxoUl+95tfcHLpBKemn+Ghh59geOoEV2x/O6KSwZZY5PjoMRZmDH69/9t8/vPvZHJ6AVOH7/3jM7zjXQN43uVlgkU6ifE+7uDnfINuYvw7X+b1XE4njZjM4aTEe7mCO9gEQE5IMT0xx/nJI0hJB7ZiE0fmz2BkA2xqvZZTp2boarscTTSQXTIvHH+RpXkTW6uf0+NDbL98K6mRcW59xV9w5Y3vYsPuVzEQW8crXnETfjFGtlhCLfu4pu21nDuTZdclbtYNOEiVBa7p+2tE08M3XvVpJM3Nns5XMpdeQvR5cXicNIW2cnKuRDr9JF3dJtHeCPbwIm3tzfgbDDwxxep1ISuYAkh15DX1YKFV7cF1HcPQ8RHGYLWPfqHdt77cd+1OXM/tUHu9nuy1/ry1x/DyNONauPCFdnuhqgZELnKiUQSrhFiWBAxRwqGXGZvOonhhfGSQZPI84tw0XqnCXR/7HM6cysKRY2zd8mpi4S7+7ZcfxiuG+ad7voA91ECvpKH4BMpJNxNLLn7ylZ9xWexGa66PvxvkICxOA3kwx2FjA7R44dwgdG8ARzMsLsH2rZCKQ9QLUpd1/Gc/CJoEugwOBRDhaz8F4HU33MLw9CgtTa2IWoz163bR2hpgaCjDrGMCW8Qk4A3x6IH7OPKTe2gMt9PbfT0lLcn6YAtlXyOTo+P4tAp/cv1fohcmOfXSSdq617F5w1uZOjdDRdZA1unZ3Edv22be9b47GZ6ZQcnbsVV0du64kYNP/xfZ+QrziszQ8ZNoeS9XN+9i9myJYKMTmRgAd//oDAP9N3GaORoJ8CIv8UO+RzP9PMKTZMmjoBGnhL1KE/rLap8ZdXyMG191K33RPtqCnSRTRfyxNkpqBo9vPU3hGGaxzNDCCZrDrTgVGwGfweRUAbtfZk/fLvxhO9/77g/Y/+R9vDR5kEQ2RzjsRK+ohD1udDnHm958Bz0DJeyRRcyin5P7Mvzooe/y+X/4Je/7xb04lB2otjiSAqaappIrMZ4+z2/v+RlqpoSYEIkqKrFGG6lgEJdfINzgt8qhTKqM1lZgUJIkFEVCEMxlvEqtilCxWdj+45xFqhZGWUt3paCnxjJUb87XRr2CWFtRWN/v4EJBvLXnqbcm6nkeTKzy5fpz1zpAXfTugOWb6SiiVVKcnJ8nr1eQJScOWaJInuC6drpad7Mgx7n2kp0MrGui0SmgqLC1bx1lbAx4fHT2+9EqEuWSSLkoEwn3kE1OkCZvTWaIEG2GbBIO7QNHAHxe6OuBO14NLgMmF2F8FtIZkF3w2FFwmvDGa8Fjg7FRKFZAzcPf/Mvy9+ho7CBPCYetGZe3yGPPH2QuryNLOi6/gKAZ5ASQEyWu3rqN48MPU0pM0drRjt4p86uHv4XNnqUp0gK+IO+49SO0NnTiDHaQXRinozmKPa0Tz2XJZ1PYJJn1PZdhpnNUKLAkw72P/g6PV8Hus6EoOuVKmuTCEmLTTl7zulfiijSya/suAP7nkZ9iCytcTj9nOEcL7cAiE8wgkUNEJkY7URrQkPgv9i9/12i0hScefgFNtjM3lyGVy3F8/1Ok42nEcgpEOy2hBjSbTq6cB6GCWiwyOjVOfDGOO7aeUqXI4kKekpplatCBw9NOrpDGGfGw49LbcPtsFEslHHYXU0MCS+Mit796M5s7Q/xo79c4O/QEc7PTZDQTuyRRSipU5ApaxUXTJpV0UmdbZBPT8yoO0UNI8hKfK6HrJoIsWES2poGqVpl66tp41ayA5RZf+gqZZ4Is6hq04No4QP1Yu6vXozdhJauw1k24UOVhbdS7G/V8BvWBwtqtlj34Q+OiyQ6Ioog75MMjK6TjafLlPLKi4Pe5cI4ZDJ/cy2STm/zhIttu34zX3871V95C8okX+eE9X2Zg/WtpWb+J8VP7+dA3jvPgI//Eq2/5+7oZPgSvfiVkXgC3BKIELxkwcwhC68ATgPFFaG6B20OgpSDihlQGTs3D8DR0NFsKIp6CQBNMLqz6Di8+/xMaVBuRvhhbRy+nI+zlwVNP42oI0L1RoknZwtL0eRZeGmH4muN0Ne2kkssS2uglqDTQrDuJXn4VpaLMj3/+HTra+ijJcO7MUyxl47T3DNDZ1Ybx0jR2vcjS3GG+9q2j3HzbzSzOzFNKzNLitvPQk0/haMjSv7mPZx46ya5Lm7n/3q+QTM1zxe7b2LrnDm7jdzxwy9u4k2vowM40GU5zigzjNBIlxiWsI8Apfk8IPwG6+BRByiT4V57i1PQLLKWTeL0NTKeSfOC2V/Hj5x+l0dvHsVMH0F1Z7t9/kG6pSMPVDgbK7SxOxtk00M74xAw/+ve/pj3YzfVv3sreZ5/nkhuCjB6e4ra3vZsHfn8ve597msZ2N1//2V24E3bMRIScluVT3/4e//yFD9HW2UvU9zSmOs3MTILGDh+5eInMqQBNnV1kAkNcu/G9HDo/TyJxkFCbj2L6LFv7/Agd/VQKTzI/X6SclTEqKsgiqqpjGNZatNls1Y7YllLQ1siQE5H8cl3/yzsb16L8tcf1O/daN0Cs1gTUnqsdAyvsRfVxhQvRyNUEv6YUVshIWMYoXNzZAaxIrYhIUdcpVFTKqSWSiwtsWNeLzaHQ2tXGpst20ejrJqO7aegMkErH8UTdDMQuYX7yPA88coo33/FBgDUKAHjHnVBYAtkJhTTE02C3wVwSnArMzkF2EQpJUFTIFmB8HjQVrtgDDh2CfpB0MBXIFKChcdUUC04bTUE/sqmQyxUQzAoNoTDprABmOzPT89ibvBS1JLbIenoHnFQKRfz5AOlJg02tfUyODSIqHkxDJuTycPb8C5w5e4KALcK5w0OMnT5LVl9AsWVwSl4MSUfV7eTVMrLiJZOsUF5IEDQd6GoZr+CllC2wafsmHK4AAX+EV66/FhGBt7OFaSYoUULGg0YSExsRvIxxFIAOwuQoMsIg44yQZYnPcw1dLX2EYi5MSha7kpBDdDgQiypFtYjXlyTgTvHdf3kEWXBQqWRwO32cH5nEG1DIVNI0xjrYd+gw548OoaR8dHY7OHF2mmuvuAMpn2dmZoJyskwlC5l8Hrvi4H/uuxfFqKDYvORzFbSyhmTzY+YVYpEoC6kCi+VxXHqA/S8d5dmnf0smp+JyyEwNjVNYTHLi1DCd6/sJtfqxeUREUbZ6/AkCYpVhqFKpAAYIJqYp4PY6V/3WOmpdnyRr/KGo/9oAXr2loCCj1fnrFwr21R+3FmRUz1VYz7C8mj35/wBYCAEkj5N8PoOo6BhyCT3oJ4vA/hPPsm5rC1Nqha9/8AukfRmuuvx2dnS9iZNnR5mYOkUs5mfPhgjXXX8pvxl+hie//36e/eHHrXN/5C+gpROOvgCJJFTSkDagKwSCC3QFfnIPNDTB1QPgL1mmftQDrY1wyW5wLIIsWinC7Cy89TbYfRn84GervsbwaJGRiSSiZDCkLTHrVJg9O8GWK27Ea7TRtGeAvs4e3vXhd5NIT1EYdyHJjdz3+L08u/c3zOkxZMGDbsS56qbbKC8t0D2WYJFZljJHuCI+jjQyhXl2jMG5aQK2ddz8xs9TLCxSTJWIVySuubqP2DonusPH7IkZOvsbmZqZ4rkD+8iXSxw/fxywSlMXyaCTZTc9RHCwlyn2E+cEg3iROM7DlBBRybGEQSceKgT4B57is395L7/62lkUv53GfjtHjhxhOrHILVdehWKTUJMxLl2/nTve8FrS5TnKJRndKNLR1kyrL4ZmipyfOMi6lm6aGpzsP/MsetzP+ZNP8tzxB/nIx/6Brf2X8dmPfo+p+ALbN/QyPz3N/vt/SqOrDTWVY/q8ykD/ZUycmGL4pMpiHHZf2o3pU5k4Os3M3FmCHolQk52SQ+LsmVFmFnIsLU0wO3set9+J1y/j9ytVN8BEMPRlsTYMMA0RWYFQ84qoWK3RZK5hGegpugAAIABJREFUGxvYUJfMe7nw1z9e6yaIiDhZ3WNxraDXWwG1UV+GvLrz9IpLUTtjravXHwMMXRRKwDQNDLVCJOhFLVew+21ITjvlQo6yBPPnigTmZvnY5z+K09bEueQcf/PP78UnlAh7dRoX48QCbSza40QqDVz73u9y1bu/ZJ38xBlo84JqQGMUPEEIe2A4bgm0oVppwP33W1bBUtny+V0mSBUYTYI7CNfugalxiLpBmwLN6rj+yMOWIvjRPV/m3Te9FUfEwd0/+SbawhxuTWbjpgFOHHqSXz/wE+79n6+S1c6gGwHGZsfoa48wOjNOINCOzenDKxvEdBt9113DvscfJRMfQvc14hx3UCjZGPK5qWRVSnawG25mDJEffv9vOXRsEF3X8UlZjv/+CcaWxknnRL75jUeZX1jAlA3KRXA4PUyMneSOD17FI8zwCGMsonIfz1Jgcvn3aKaRRdL4CTLESdy4aKSBEZZox817uGz5vcXFJZ7Ye4ait4XNTWH2HX2Olo4BEnGN7FyBm2/rRVgSyRezLORMwgGd8bNzGEmR0YlFdNXgqz/5Ab2dUSTFQUJLsP/4c/zn979PU/s2Dhx/mA3r24gvZrj1zlex8fJunjvwHGXDhjca4ej557C7PBQLJudOz5DPzfLSY2O0X/oXlFWZYHcMj6Sgpkqk4xqCGGB0JI1h9xDwugk1h9EdFmTYBHo29aMbYBMFaqzjzW1BElNWv4UB2rCapGu008tpTrFMVMoKw/Ba/35tBqH2nnbaL5D0W9tG7uUVhWsDjdbcL68TWOkP/f+j74AgCG2CIDwpCMJpQRBOCYJwV/X5kCAIjwmCcL56H6w+LwiC8E1BEIYEQTghCMKO/30OCQUDUzcoZbLY3Q4kU6NYTmNUiiyUJlFFG7ZCCZui8syBR1EXJsi6/dgrfrpaejEdXrRUnMb24MqJP/OP0GSHs1OQTIKeh3QJymUwddjSDJpgBfhOjUEOKGQhYoeyAGoZAi5QHVZKULBBKg2RPvjwtwALOvCVb34EZBtDaoZsdoT+lh3YXAJatoS70U5pcZzX3/ge+oO7cXhEBkeOINsDBHovIdbcA7qHaCyM1xGkffMO5mbSTA+Nk3bD4cOnSKdUHKILMewj44R4pYRgqIjJFFo+j7MsopkSLlHiPW++i0pBpFSKY5NiOOxeZodEdFuWnhZo61pPf/+G5Us0SIoAEiECALyRDtxE0CjRSAcidn7MeZJk8eKjgkGpijgEuG33bXjtEp78FFMLcyTys3hdAcpanoW4TKDjSl59+ZtJL5VRiwYzoyUCMYPJzDQDTf0kC3H+5/f3IplZjp49TL5k0OkN097bTYMNchmdiLMXHDpdm65ge/922nvbWJoaQxRM3F4/mXyGxfgEzVEPyUUXdtXJU/d/Ha/LiZqeZ0mVMUWBQsHAdBapVDTUhElifpGAzSTojGAzdGRJYXZ8jOauJlyybBUfYVBWMpTy1o4rU0ZExomNFxmpgqjB2oVX2obV7+ZrXYCaUFst1tdhcT2sxh+uTSFeCD68stvXwEgrc1mKocYvYc36h8b/iyWgAR8zTXMDcBnwAUEQNgCfAPaaptkL7K3+D/BKoLf69x7gu//bBAKgmyJFzcQQVJbmCnhtJbrat+AR7VY7K7OXoOMVqOkk16zbxe6r38KTg0/gjfQw5lSYXEjSbGvm9ps+Be/9U3jDa+DgPigkoMMLgQDkElAqQsQJ7W1QNqG5CYKNIDjghUOQd4DDA+uiEOu1YgRSxcIOdLdB72WgBmDkMABPPP0kiUyZ8cJZvv7lT9LcuZtd6/tZ37ETRffiEyNs2rmHe3/+XW7b/F6UecguDtMS2Up6McGxw/txShL+/4+59wyPq7zW/n97Zvb00WjURqMuq9uSbMu9V2wwxqZXU0JJCBBIAgkhHUhCwslJTkgCSSih9w62MTYu2LjKsmXZsnpvoxlN72Xv98PIxhBy3vP+/+cD67p0zcwe6Zmt2bPWPGute923KY2VV19F9ZxV7H7zWbTGdobHGll2wSwiGhVT581iIjhK+QULWDHtAuIJJUOhMILCxIq6NUzICVzJGL94+2lyzVnMri/jyWcewDPhoWp+LXqtCTG2FM+AF9fIKLMxn33/t+HBjoKLKcRCDjYqCBPnGPvIpBiAmczCwQDNnCCBhqpzasr6CPgNaZTkzkCnyEChDSAqBXqC/bz20XMYbRnoEgI2i5XEmMjEkIry0lww56AyROlv20kgGSOpl1DGQoz1alAqA+w5+AlXrb+N86+9GWNRMZ6ggoHWdirriijIrCbkt5NISIQ8Iua0dIrLqskrSGfVVVdxx50/IxZzkWcuojg7FyksU1tdSPxUmJr6qehtMlNr5+L3S2RZDEhKAVERJxKJ4x1ykllhJpGUUcoK7J0SwuS2O4YWkTgNlNJFEzFUZEyqFp+Z6vsyOOjLCMBzOwmXsvgsE/KXgUf/LsU4twagRpxkjlZ/BYHIv8KWv8r+J9Lko7IsN03e9wOngXxgI/Dc5K89B5wZ2t4IPC+n7CCQLgiC7b97DUFIpQQBv59ELIno8ZNMGrAVFRCQJbzDoyhVMkcOfIw47sCrFohl6WlvP0XvaAc23TQs+mLuuPup1II+L2TnwegI6CxQUwNyFLKLoa4CIgLEYym0n8UEWgmmzoFxH+hjUJwJXf0QiYAtB3KyAAE0GphSBgVWyCkBwCjFSHO5cYyNMq9hGYeO7CTDnMNFl6zjlmuuQplrYmDiOKWlWWSV1OMfGmH+nJW0Dw4SS0qYtBHirlHqpszFMeEi4AuTSMaQFTInd3ZhsWZTYMlATJgQiOMbt6M1CphyMjGmu8jMsbHpik0kw05EhYDBYKCosBKDRo3LOcqCeReSZh4jmYxTWVdKoTWPhE6gES9LqDl7DT6mhxgST3IEHz7U6IgQo5NObmIqTRzCQ4IicvARQXdOpVmvziSpiuLzDTOluoYTTYewZliwpGnITS+mcagDS7qNSDLEzPnF2B1jjI8EkEIJAioFQ24nXfvHqKvJQ6XRkgzFyM3KIhYP4Rwc4aXNL1JX08D2LS8zo6IBdUYWsXiQObPmYjZbyLIaCatiaGXo7T7NcGCAD95/EZOoYHhsBFfEj1oBOZZSrv3mA2SarKyes4Ro1E88HidmjKBQiehMacSiEvGEAlWJESGlfEcyLpyVgzchY8HEbtqRkCeHglQkkdGg+Ren/e/6/hISfkbgnI7B/6sliJMgOcmj+EUMwRfBS/9LNQFBEEqAmcAhwCrL8pkh9jHAOnk/H85JMGFo8tiX1/qmIAiNgiA0en0+5GQSUa1FozWAQUMgYqev6zOiIRdXbLgTlUVG8AYoVmtxjvTgsg9RVTSbjo7d7OjYT0/Hkc8X3/opfLANhBB02aGlD1RmkH0wMZ5yfpcXtFqYmg/uOIhOWDkb/FEY9cPUual3R61JtRNlGSJKcExAXjF0dgBQsfg8bA3TKNZbGXX3MauiHq9mjI+3vcMTe57EN9FKJBElYjZxvPkQ+QVVbP7kQ0xFozzxwt9RJXM476JNGHLy+NYD69i+68+oCCDr1Dz209/jyfChtFg43nQMo6WBqELmeM8o3p4oaxdeg8dh59Z/PIAiCUo5Dd+Yl1hMS3ZWOUN943T3tBLxxVFLRt5+82+I+nS6jqdGavdOko6csS2k6hxPsgUTOkRU6IAKllPLNHLIRSKJAiUzJynFAKYvXYMkhbEYNIx4BzjVGmdCE0KpFlFZZBSY8IYcDB2J8MYHhygtrEEQEyQMIeTxPuRwlIM7PBw92kuyXUIU42QWzkWvdbN/aDfuwRNkTCvkgqUz+eeH7xIbHyM3N4+Bzh7s/UMMdDkpsRVxuHOUkQEN9aU1fPj8TvKN5QwO+PG77cQkif0nPubJl36HUt1HSG+ltHI2S8+/mYHmUTZuWIBaF8FaZsCWY6J32zDpajUySgRlnJgitfOJoqCQUjSIpJMGwAQuVKiIE/8XxN+52/svH5eQ0GBEc44wyLk7gXNxAl9OJ84wE69m6eQu4wwKMaX78DlV2f/i7IAgCEbgLeC7siz7zn1OTk1Z/D+FMlmW/yHL8mxZlmenmdLQqpS47COotUa0+TpM7X6q02xk5VdwaOQ4frcTVf0UtPXnkcCDmAjy9vNvIwtq5i1awHe++xhccinMmgu2LNDGYFpJKmn3RcHrSjFjhxIgGsCUBWY9KARYtQgKqmHIA4X5UFmbqhlE4hBSpwBG4+MwrxxycmEiCTMXAJAcOMaNm37KD7/7BKEJIxFUbP5oK4JKwt7XwYzqjShUSvKLpzFo38GyeXO5ZsO1BNrc3Pzt9YQ1cW66fz27W/5OeUYVR9r3csw+REiKU7fyFsbCMSITMQYbm+ls3E+ouYdgzE7dihqkhJn1c5eS6BskzVdKcWEdJXEj+oq5iOZprFx/G2pzjGRcQygcRwqFKcrNA5X4hWux4dt53P7o4i8ce45jREkikySCwOt8zBn2AQVKREoA+PFf7mZ8ohlVKImsLmDD4tvJNnu5omExhdpsEgkVo0NjuHsgt1qNWakkGnKTpshEkYwyFBknEpe4+L58lq9aQOWi2VSVlHJo5wvYcrNxd3Vz5e33sOOt5+gedZA9y0bCKRLFzc1X34484MFabCQ2rsCQVPOjX6/hlb89xaJFRbgNcaLROL6AElkVIdOST35BNoI5wvYnX6a3aSsdjW+zclEGGRV5ZBdno1PrOP9Xy1IkKaokarWccpNJQFEueZygj9nUTuoapHLv+KSU2ZkxnnPFSM760FcU+o7ST5TP5wPOhQSn0gj12fXODSBnag87+BQjEillBAEFArFJLQIJ6axYzP/v7oAgCCKpAPCSLMtvTx62n9nmT96eQc4MA4Xn/HnB5LF/a7IsE4lHyDabKa+vI+IPU5RdgL46j5rZM+gebyfblEtZVTW67DIEtYGTwz1suvQSMpTpOMcmCR7StaBUpDgCIhGI+MHrAeTUbSiS2tKnT6IEBRVo9aBXgF4DoWRqslClgXE36PQgREAQITsd+kZAoYZzIvfelu6z901KJSeG96FS+Ok/9hm2sAmrsZ64Sqa5byd23zBHuloJB5R09PSxa+9+2kZPsOa85fSPj1KSbiaBQI5Bh8YQANQkHBJjg33kFdVz/qrLKZ+1iI7OIRgzsm3fRwQidpwTHiLaCaLOYcToBK1HPkVQBjndcgCNqEdliBP2R7DmFXG04yDn1y46e86rLq9Eq9Mx3H/u5i1lqQ+0yMP8lbv4BudzMSqMRICuyc3eb+56DIvRgqRQE466ePrVx0kgYC1aiDHHgifmw2JUo83LRVIKGPU2quZNR69LjXBrRZFqax1SKMjJrjZef28zfQ4X5owskDMIJkPEJQllMsmQsxO3w0PXQB9qcxZvvP86dzx0OzIuRvwC8eAE7aO9GBIyamWS6UtnohGiZGSKJJIycb8HQ7aOpCKOKAUYGfYQlmKYctOJxyYADVJYQqFKw5AmolRIxONJlMqUGwJ4CaMkgQEjfkLISGc/DSmYrmKS3fnL37xfLBCeed7FBKpzUqtzA0UKXRj7wtb+3FRCRiYdPRFkcsk6i0NUoURG4kouRoGKxFe0Gc+1/0l3QACeBk7LsvyHc556H7hx8v6NwHvnHL9hskswH/CekzZ89UkoFSgUkEjEOfzZVipLy8ldU427LYKnpwNjVMGoewiVI4LOOUQ8EiU9EkJXnk1WTQOXr70Vbr4RXG5wjEMwnCrubT8O/X0Q8ENcSFUg9Wmpb/mSgpRzS0CmFZJKuHweyCYIuMA1mPL1sgIoKALZApY6WLgWGmYBcO0PayjKM/LDe5cy9wIDhtpFXDhjFYsX2PC44sQL1fzj/ecRE+kUl+QhmQT2HuvkzcaXuPCCm5mRV0Xl9Frczj7qs5fQ4pmgInsV5y28FXdvgv985r+4adN9rP3mGhzxGC9v38bHOz9C1msZ7NtDhagmszKPuul1VBTMRYOLEV0horODYUcvweQQUtKLTp/FTdf+iFH3IGIwwGctW1l1ZRabrrby0I/ewBfR4hgPM3OjiRt/voDrf7KER568n60MsoUBADKp5xn+SC8xPuIEgUkY9l2/3oRn3I7H4cRaUYHodVM6u5idh3fQO3CUdFOC1uMdzFpkozK7lHt/fA27tnWyYPEq3FEnkaSWXNsFSJF0ZlXkce26FVx54QoC2gDXXnwvQsJIU08zwyNe3O4o5fW1aPItZElZ9AzamZtdzYYLvsOMmdmMRWSGHG76R0PoiyvZvuMFhDCYMwzcc8X9jHZ4aXWMUVVsRV1tZEpdAdkZVpLZFbzz2gkGe/zoC0Q0kojZYECpFDGl6xAFAwqVgEJQMMgwl7MBLQaCJEjH+KVPs0QBBV8YHz5T1/8yvFePjjQMTGXGV1b/U3/7eZfhrE+eDRRgwUIc8BOklvrJZmASAZG3eX9yh/Lv24PwP9sJLAKuB1YKgnB88mcd8FvgPEEQOoHVk48BtgA9QBfwJHDH/+0FZFlGo9ERkBJoZA2nOvs4NtDPiFpguGcU0pTkZucQGenGOK2CJbPWoBENqIwyt629O7VIcpJTL5kAlQqiMQjFQKMDpQCyBDoNEEtVIv1+KCyA2nKIRUCpBa8ALhec7oS2AUhIMOQEJNApoKwM0rMB+Mtzd5KIyygkL4OuEZSKLHa8+1fG40lGPF5uvuESeodiaNIHsVnSkQLpWA0leH0DJL1JTFmV9HS6KC8qRVCr8DiClGVns23by9g7T1CYW4fPcYQ339rMxICDgXEX9pAat0Oiu2cEMRqi2TWIPeAkElKis0qs37AJZ8zFlIwaXN4YolJGVkpkmbPZ37iNjtFhNq26lBWXrcHr0ODwh7n0srlcefElOFr8ZOXoGezvp3rWbD5r/pDLbp539hp9k++xhzHe5xQAhyfpteSQG/tEBHdEYrBngLTMNIryp7Bjx2bcvjhevw+zNowcM6NI+NhzeC+xqJ1+7yhKvYg2HGGgrQ1TVhF+WUIRGuHO7/0GZ/8wu3d8wMdbd9NzpAVdmhJiCvxOB0Pd4ySVbnSVBoJpShweJ1MqalE6E3iCTlRxPQpxHL3Cgj63FKVGx4hnhIBfBjGG3y5gVBs48OlJHG4fO7e0sW59Rap4mJWDMghJg4QvGkNSCESiAaSEhCRLjOHAQQAnLtQoztK9n2tzmf2Fx2dy8+Q5O0hIjQ1nU4Q4qRT15Q4BwPSzxdvPdxfnQo/DhBBQosE8WQ8QUaFmJtUkkL6SbuzL9j/pDuyTZVmQZbleluUZkz9bZFmekGV5lSzLFbIsr5Zl2TX5+7Isy3fKslwmy3KdLMuN/7fXEIQUh5tGB4mkTJbNhGsixgXFJk4OHCTbrGHE4yV75mJ27XiLPIOKke5eVpat/nyRDgccOQEZelDIoDWB1gCiAkJBIJnK61RJkDSQiEIyCu/tgG17YXQA2oZhSj6sWg91s0CIp2oAkh7WXAj5ZQA89uJtDEltrFl9GUPhDrLqbCxZU8zKdfPp6W3idKOTmCvB4pnz8J88TZQwJB1E42PolEnUCS/9x/ay+YP9HDp6jCxNBod2NbLllU8oSNdwYqCH1pFT/PKHr/HGfz2BURFhvL+f+RkK5GiImZVmoi4VA81daKIq2ns6WTHvMh74+YPEhrqYt/o8xHg/g2N2Kgw5DPb10Xx4P7U50+jubmbb9oOMDPjIshVy+Xl1OMInKV6+kerSeZSU57Jv9xtE40m8niEWXGw6+xYvuS4Fk/7RT88H4LpfLcaoU9B32oE3FGekx4HGLNDZNUieKZ9Y1IQyqCKsjmCL+Igps2nraqN+ZQEu3xDjjkGKAxosFgtedx+J4ACSuZzzrlpBffZ87r/378y60EalXk/Q4WPg0BBjHROYRQMuhYkMMcCDf/kdM+dfypt/fZpEPIoyYESVKSIpFPTs62PaBigozSG3wEp2sRpNNMDR432UVy6icsGldBxvwyL70Vo0ZGVpKCquxK/wIEkJyqZZCceDrFsy7wvEI+3so5MuwkgsuvaLMBgBeIsP0cFkzSBF7/4KT2NAnGzqpRxPRxItQWZRiUySRSwm/ayiY0pg/TinySV9MgSc4RpI0b8KyJSQhRIVCbyc5CQp8dUYzbRMVgjU8AW8wL/a1wIxqBAEDEYFmekW9GYdbc3HKNKnEdWpKKpfyqjXhawO8tLbj7Dlk+088IuNLLr0at75cPfni4wPQn4mhBNQNh+CHjCkQVRKEYGYDGDQgTuYqgu4QuBzQmk11MwCVzJFNeaNg0ZKjQm7hqGkHGZeCCVz4XAz/P4R7t70JL/9xifceuGvycuYh70/xA1rHyXo8qEVMlEYRJ5ubGL77v0c90RI6gL0HQlwum2QvlCcaBI+3vsSlXkCWaF0+oIurrtzMSWLM9HHi9AG41x96WX856N3sHDdLFQylFnTGVcPY6sykpOtY3x+JgPdAh6/SJm1ipff+AP6rClcsukh9mx+EbPehKvXx5AqTDRoIFOpRSN7efzD7VROyeDKe9YyLWc2g94Qx06/S4UQw+4cxdsrkmO2oYsrqarIZfncVOrzt8dvpWF6Pffcv5hI3M6lP16M3xWidNocookkaVoFGpUPrS1JVrKQRcuno9Y7WTlzOa7mLiIhmdPHOtjzVif+IQWJ8TEUIzkIyRzmzK9j/uw68uun4EqMc/W1K6msW8aG29PQqWyYrToWNszg9vtu4/d330NepkTI7sI5YMLtdvDCiw+jztRzUW0Ooz0hKudb6djmYN7MGk5/3IcQ89AzYkfSS4T6S9iw8ZccO7AVla+birn5OF0BEkYLQ04X6ZladFoz5VkmwiEfFeV5tMfHqJ1ZgMWa0iJsx4NjEjD12cspkpo0DKhJ6TNJpGDFU5iCAogj0UsHWeQAERKkFCLKmYVECJFMJMDHIL6zUnKQylUVjOFBIs4ZSngFEkpkdOiYyyoEEgQII6MgQphy0idTCwkjKtRo/tuE4GsRBGRZRtRqCIdDyFKCcDCI09nPzhOn8AXshO0++vv7SU/PQaH0o8hfwLj/NJ3dn32+SFouKI2gVEE8nhoOEgRQq1OpQSQCgiIVEPwB0KkhEQa1mKIXy8yAHDU0D6WoxawFkGkBqw30OjBqUsXDO3+Qah5PmnXaAnSihnRzJolkjBVL1+HscqOPh/F4O8nTm5EVWtJzwR+SsVgsXLB8DZWLcpG1QepqVjHaMsTe9qOkq/IIecP0DjkoyTXgcCfILa5G0iVQavRkZ4vYrFVccv16hnYfRucK0tt+nIZFi9Hn6CnIzWTI0cyaDZuQMkKkp6WjnIihllzUXbicpEpFRoaEZ9CFWh8jraIQjS4H0ZDNWGgUWVTRcvokJVXTyLFmMjLRzer1V7LxrhwSRj2CykRpSQ42Wz46g8zuLU2M+z2o0lQkAjrya/IRYgrSjDr67V70KhNF2QXkWzL57KNeTp+ws3PXR6izRMY8LtbOn0M4XcszLz9OHCXBWIK2U60kggksWg/9dhnHYJjDOw8z7pigtasTTyKD6hw9kkamNK8Ipc7Cohn1aLVaFt12K0LEDyolt1yygLFhN3ZXmFhURg6FiSUTlK+cyiM//h46MYehsW70NgUaUUYZj6KPgqSKoAlIRNUisXCETGsGepUSSVSi1QvMu6ySbz9yE/KXtvY+gueAhWKTWg4q4kAaaTzDawwzfrYEKCCgx8JJ+slAi4iJQUbQof9Sn1+JmjPTDMJZ5z5DL3oBaziTaIhoyCITPxFkdKgRmUM93+MuNPwbSSa+JkEgmZRx+d3EJQmtXsUUWykGQw6f7jyMTaflppWXk2HSoS7QkWnJJlvU4J2YIKz4nEGW0gxIU6eAPoFREE1gsqR2BIIiVfEvKYJEJJXfJ6OQVwgoYEkDTK2Atl64cCqcagP7aShoAKUtBSNOSjDigUcfgK0vnX3Z99/4JeODI7icR7jw/Ft59cXXWLJsNTMWnMfitZdgd9oxuRTkTcsm26pn9FQ7yaw8hpomyCwv4NMtL5NRl03PyWPMXLCE0uVWSvOhPH0VN1+wkR1Pvcec+uWoYwJF6cuJJPz87Pb32PH8IW7748P0nR5jqP1TJlpHWbx8Od1d+4iJ4DkVoWx5BkF1nOH+KGmxJH1eD6vPX0Nc6yDginDy0NvU5ldQXZBB0D9ExCxRVGriwPa99E/0kpVp4f1db1OeW83OU9toat1Lm+s03pCL8KiO2llTEUmwdE4Fy2bUEY6M0nygBWWJimP72tm44EKe/+BZAnEVgx4fF1xeQjA2yCyLmjRRSXZaMTPzp3HB8rlEvCJT8iqx2tQcaepkf8cJnG1Kjp84QXZWkEUlDWToZbZ98Hd0hTdyrKmRTd+/kXjCx/N/fg+TOJ3N+7cQM5iRkmHW3no3HmWEqTWVDDVN0NPlQKXWMt7ew6/vvY5A2Et43I3THUQOK5AiKkqrc+ke8dDpGGHC5SHLbMI10ovD4WC4z4VGGyHhdxFPtJy9/jPXfI68TCKTEnlL2SBdVFPHXGrIxHyW4iul5BjHhAUffpQYuJ1VeJEmOYDO4AAUKCZlZtewkjMoAwVgQsv3+RGFlCCQUowyoiSGj1FkishAQsWbvMG9/JJ158x7fNm+FkFAqVSQlWUhFpdxR2Sy7aDSCJw4doSoMUZbwEOaoYjTR48QVHsxGzNIDHkIDk0WA6+YDckkeINwvAtKp6a2/54xeOiOycKgAkZHQQ9EwxCWQBJSI2ERP8TcoBChpAGsxdDjBm0B5GUBKpBVsGY+/OI/4MJNZ8998z/szDuvnhff3M5nn7yNQq/i0zc+IWdwnMhgB35XGNy5OH0B5pSuwiupeGPHu6QVZxFNTFB5aSlqyYt7JMjrL7yFjgL+8h/baW1y408zUzNrFu998A7X33QlR7p3YI0s5LKF5fz0D3dy2TcamDa7DI/DDdoYUVfY0FC+AAAgAElEQVQn0yunsPfwcfQGkdETExSUZFA3o4LWYzupKijl0LEeSovn0HyihT53gFvueZDmrgiyJYo+qkEtgk4lkKPSo45mUltcSdt4D4yKVJimEhpLcvzUGJkWiVJbGt4JHw1FGSimNKAI6njo++8Q7w2Qo5URTRVozVZsRUlu+dUqxieG+OTl7fS2nCYYUhNwefjn4Q8IEeT8RStRxq1UTF9BQa6ZHKWG9BoFttJKptdvJK6TCUcd7G47xZN/+A2ZljQOvPsq9kSC+rpcrr9hJt6xccxiFINRx2BXDwsX5qLPj1O1qgKP/jjZJXHKazXs6jtOYZGJulV1FJbkEREkbKU1tBzpo79pL5JfBMnERDhAQU4mcY9MUb2FjHw9QTmIYzz77PVPKLQAZGNGhxIJeVK+BTQo6KAFCynArAY1ajQkiJCBiBYBPyHsdFLNciyImDByRiY+hTxIlQM/ZT8V5KNBQQKwYeZhfsMEcSSglHzcBEgSRyaJmwhGZIYJ8B/8hh3nEMJ82b4WQUCtUeMecxIMB0iOD6FMNxAIulm9eA673jzAG3tfxTXiRY7pCQfcOENBxGQWkfgk6OWNRog6wJINeSVw4iDEfKAxQtMIZJrAoIGOdjAYIBwFkx6M5pQmtXMEctVQkAuuEQh6YcUq8PpTz8cSIHw1IcNN1yzkJ9f9mv3HduKKRFGJCWqnVHKws43B2CjqdLjr/t8Rdwm8uuMtRL0KlUKNwWJAkVDRMdGGUq1HYXVz9TcXEoj089nAHva07mJgvIW6ebVkZ82jfWKEgeMGFl+Wjy/pQZGl4dof3EjQmSAma7Dl5nB44BNa2k+jtng52dlLlikdRzKM2z6AMXsmgVgA/7iHjlNjvP3H10krrWTXkVcREyK/+tl38LbGSUoi7nASXWYmgkbHsYExvn/+LYy5BwlqtDhDMXQGA0PDw7gdE5zq2423eA4H9j3H0Q86+PTQ63gDPgJhLW3hw2Sla8ioXUzPySTfvefnpE83s+Kau8mTEuw6soeEnMAi5vPuR++zrbGNWMhBbdlG3LFMTAqJN/7zr7jjbtpajhNSBJg281Je3PE+xdk63DIUZeQQLxF5a/e7qIlROmUGzriLqDbKgWEHaaYpfPjiIez9CcpN1UyMBhBFLwpUuFweCsw2aucXIqqVzJ8zh9O7w4yM9ZBIhqmvmsHRU6NEklESfhlvIM78hTPwdDmx5RuZtiyfLF1qYC1EEgEVs5hBjCQCkEsuOdjooJ+jtKEkTowoetRoMGFGhQc7x2mmi0FchInzOQ7vXNx/lCgiVmQU5JNFgCglpPNPnkVGQQGZFGObbNzKBHHyE36IEQ3/yW+4ho3/1v++FkEgEomgN+SgUsRRKNJoPNHI0Z5G1KgZGxpifnEl7iTIiTQsWisNGjOHOpopy6/6fBFtGiyYA6oAKPWQWwuZZmg5DPYAOBxQX5UiDLn5KhhyQ98w+L3Q1AtjfjAIkJGZSiWsMyF/Smq3oFICKmg8Ca2nvnDuz76yH1FXx773+7HIJhQhBcuvvYZkhpLLzr8IYTiNb953HZl5JZhEAYMpQNg/wKk2B2OOceIDETQKA/Xla9m94wQLFi1lwu9n8fxl+CN2Dp94ltqpOoYb7Tz6+HeJKkVQ9eHs9bE2fzr1yxayatEycnMWU2ddTmFRCRPDGs6fMw0x08Bs2zxmL2/g1gvvQKtXgWaCNKuKtz/azkTXaYoKywkNuTBIq7nqoisQRBWBwAgbLruGPafHad57mPcHt5BVZkDweqgvLWNR/Touu/Iyrjz/RrTaMnZ/+ApFoo2l11zM2GeHyTBqsC3RsPfTbUybtZjx5nbuvvhSjrTsxDPaz1tb/0ylrZ7MpBulGON46y7GPINsf/Z90tL1ZGTFmLlkNjnaPNplOwMtTQTCAc6rO58nfvRjTo+fxFaVw4x5S8hNGGjd2Un3CR+RRBxBDKGPaDl49DgzLEtRRiSWr8vFHxnBICxFqZKZ8OYQFPx4ww4+fuMgvpCfSCyGPTTGVtfL9LT1Y9IoOLS/lZw8K3pjOnZ7kO6DHp598AB7tjYyOhwgHhumuCI1YFWAkhIy6Ob0WTWgQew4GEOPRJwoWeRN9vZVuEnQg0CIIEc5QQd9zGYBIpavBPYoUTKXKvIpwIGTH/AQD/MUnTSTIEGUCP2k4DjmSXnZW7iLw+wjk0wa6fy3/ve1CAIKAYKxIIqECo1Gh1pvpr3pFIVTyskriTN34fnkGLPQmGLkWQo50n4QpQKyTecsoklCWwsY86DKBsEYHGuG04MpDIBancISKEToaYYMDchh8HpBqwY5DvlFMDIEi1al6ghFhaAUU4HA5wa3M0VKco499Ugqwh7Z+SSxkRGU6iQfbG1EDurxpEXQmCSczhOMDQ0wu34B+oSZaCSIYiBA9dRiwl4VQkyiftp6rOZSDrXsY6C7g6GBVmIBDzW2Oj7YuYUNV1zB3578B0OnDnPV+d9GKfZx+3X30dJ0iFWLVhHWJGnsOcYDt72Ew9vI9Gk3UpiWTfPpt6nIK2PeijUEJoKYMzJxTowSn+hhzdK1HDq9n5suvg8p6mHalBpErQZfLI7drSHuHaTGZiG3ZCpqV5QNC65mLBpkSnE1jfv28PzOfxLzi4RdIb5z569QjUX41UNP0X7YTnZeLgpDCEnUc9+3/4x9rBOb2UDvUA/WqVZieYWsveQbRAIJwskksWSCDJ3I1JI6nnruSbxqByqtBtdElPqGRUQjISqm1DHuaeJE02ckI0EC/ji24kxy1Bl4h0bISLOS8IaRvCGODvWTq7HiHBwmHo0SisSonWclJzMLoyWdREJCUJjIyjLQPWhHUgRIy7bS3XMS2RtAq5PRaI2Mjw2jFmViQTdV88xfuPai0kxNcWosRiZBmHECRCb7+KCYzPDHmUCPhgABBAREtGiRkImimWQDVqJiPeu+4JBfHkF+mddJEORWbqONTvLIo4suVMAwI2Sjp5oiFjKf5VzEAKOTzh/FztC/97//Dz77v24yMsGYE0FU4/TaQZKZO72B9ub3CKp0ODvauXj5eUwMdSJqYnTb3dg9gzSsn/b5IgoJPt4Fn2yHzTugJhNmFsGFq8BqAVFINW7X3wu5+VBgAtmaAhFVmSHqSyEJ86zg80F1dQp9KCdhzAfDfgi6YMZCrrmtAoBZtWZu/cHj3P+9q/lg+ydkJP243E7aGz8iSIx6cxn2kTgzy0uR3CpOd/YjB/P52VW/pzy7hM6xPop01UyxrWDWwmuQJDeVZgMWXYSQvQ2XT8mJwWbmzKvjkg2Xsrw0i1kLbuKiG/+ArmAWDWsu4Laf3c1vHvs1pz59lWylwKMf3Ua6lM9ly1Yy7vUzvbIM/0Qv7/a/R0ahGaQghbZyVq68gXgwygyNEmttHj/6xc34lALENVjTNTzywA9ZUVOL3TlMpaYBTVEax4YO8odvPcZzL77FitkXsshWiinNT2ZuHr966Ts4xF4G0w1cdcXF1Jmr8QybkO0h/rn5PXwZZpSGPBRigqO7glgynTy3dwc5KnCOxtGaLOgtCXqHwKUcYP9nh/FGfXS37ufNTw9iKWuguzdJZ/MhXnvzHbqG40SEANMLcrni0ukszKzj+IFuBh1B9r19nN+tX82LrzzLwvp1OD1h0jJtKHx6RrpD9B3qJFNvYkppESQFspSZiD4dGVYVvR12DGYDCYWePJsGsyUHz7gHpdJC+6HPvwB8xDm1z8v9dz4DQAdB3uNjtIiTRB6p2UA1InH85GPCixcTeiL4WcQyYAw9auIk6aGZDDJR40GLGuVkb18xiQ44oxGdTzpjGPmAJzjKQRKMU0shcWT8hBlmjG3sZC87CeLkcZ7DRYAAX/zyOte+HkFASlI7tQJ/3IVBZ0RvkYhHs6heOI20+FR8US+PPv9rEhYTjfubUeDjvPMa2Pza0c8X2X8CcrWfP9ar4NgADPRBGqkhoLwp8PyPoboIYmYo00BxNsy/AHJKIexLkYnoM1IcAkmgZzBFRFJbDBdfCsB0SxHX3lrHLX+6m4MHdtNyqAlvmo+PuzvIC5hImGOMx+wkJQUhlYBGWcC3NtxKTnYWG1esZ17DFJTpQxSoMvjevTeyeev77H3lDWSVTPtQgCAqfv/nVzDbCmmoX05p2UK6hnfy5r42jnz8EHu2vMDs/AXccNUVnG79jKAyxgPffI7AeAma3iiR3AEOeZo5bW+isHwtZWXF1HksrLvwBtyBDLRmI9f/7DZsOQKPvfUCr9/3CHOvmMuq0nQcoQnuuu0H3L7xCtpig7z4p0Za27rJFvN484XXMVlncLLzY3odJzBYipiduYiCdBUR5wj9E0O8+8lrPPiXh3n18HZylRYOtrbS3jNK0NDB0dOfEbeIHN/agqtXQ8I1yMKrLsYTDZBMRKkoq+aipWW4BgL0HW3CmicypSCLFReuYcm8jXjcEzT1dnP9ihU0b36No/s303HExwstu3np4Ef85K9/Ym6OzGtbP2QwLqJQSLy84zWiUpjhXXbUaQJHB45jq7Qx1udA1JsZHRxgzBNnPBhkilZN8/4jOIcTeH0h2gaG6Tlhx+9JkJf+OQ+guUZk/aYVPMePAbCh4VIqKGchm9mCQBIlKhRIzKOOmcwF1ExnGjGiLOA8trKVEUaxkqopnKSTrbxDFz7UxFGjRZpsDabkRiUSwAquopM3yaAKAS9h1MRQ4ySIhJYarMjoCOKlHi0h+jCg4YsjY1+0r0UQUKpUnGpupbyilqBqmKqpNgIde9l8Yhe9TS1UFc7AkqZlsKeDqdWzySkuo73Hg+tkHyvWp3IytPpUAe+M/eXp1K1RmxIUUWtgfyNETWDNT5GFhjTgCUK6JaUzUFQDrgHI1kFIgqpicNpB6wbgnt9fwROfPo4zI4n/00Ge/o+XCfmjtNkDeCOjbLrhLuZfuQirspTWt+0c3t+CbjRCt7ONtLxSXP4+0koSvLnrGCPxEE5HnJ/96WGObx3j7289gjAWJXjcjafxM3708F/55IU/se9QK309bgh6uOr62+ltDlFgnYZbbEQXNvHyD59n8ZwlfNT4DMn0KH/4w2aObwsxv3YhUl+MjkEfTcd7SJhqaN39CeuWVHDT9FmsW5JPVCwkppOYMX81Cd8II1Ejfsconx7qpMf5LnOmL8cdGOC9d97h2it/wdIZSwjEHaQXpuN2tHP91XczoRUZ6B3DVGyjJmc63b2tlM5IY0XGRaQZJtiwej7pljhNLR1kK7KZN3cG7+95BH1xIfffeAPOd/cghD04pTH6x/185/f3sWTOLMIxDz1DLnYe3s/0+tl81rgFVXEIhcVGxtQMwoMhfNE4ysUOShQlPPzKDdRnT2NK6UqefOU3tLUeZsaGNcxqyEWtSSNtjpLpdbPIE3P5cMtThP1J2rZtYcUFM9H6JEbbj1K9fCnuUASzScnQaIB0oxlrvpFllyxByFFSeU0Bq789i6rcYkabWrmRlCL1KFFMWHibV9jCX9Gjw4BABAktRYwxRpQ4XkZZxCw6OMBM5iAj0IkTJpmF3IQwTWINJSIwiTxIEqeSXLIx08kp0imil14OcggjObTSjYSSOAkuJo/5ZHMnV/NPdpIEapiG8yuk6s/Y1yIISFISvV5Pz1gnImrU6jQqFi0EnZo/PfAgosGCNc+CFDWxt3EHM6ctYM3l5zN3zkw8cVdqEUENWV/x7wiq1DSgIgnpWakx4ddegrEWsA+nCgteB6BMTRf2tEEwAeMBmAilCEXLUvht58Rh+ppb2Ln/AKb6Wah0ClqOdVDTUII6Q8Hf/vQ4Pr2C6668hGf/+SgWVTY/+/7VtB10IylESjOqycut4JnHH8Ng0FFUVUGhtZIj7YfJzE1j1uwL2NcbJGvuDF587jHu+O63sBaqObBzBw6/nR9e82tuuusnWGur6GzxMmPRHL535c3UzJ3HmBQhUxXhlQ9+x1O/eZkP9j5I3bLVDLUepmWom48+ehMpruDZV94kFjZSUzyVaESBLxZnRmUWsTQTEyEXJZYSppeVsXD+TTR3tNDc2URMDPK97z6MQtRwaNduVswuo91rp2ugBV80AVlK+gaDWGwFKGQJIaSidFodD3/7ScSMMmJhLT1N7QiqChbmT0FXOJtnX/0zeeUVPPCjOxDSjOjjaiIhJzkxI6u+eTeZmQZsGUYKi6ZiUouoFDGaG5uIJ3V4FRoWr70cs87CG68eo8s1xsmDLXQM72P+yivJQMuM5TVElT7UsQQaTZCZVSXUTq1gJBDnSNtpqsuyuPf7P2Xtuk2Ysk2o9TlE8KJDnZInj8VRigqMRiP2nl5M+TFmFmaz44mjaNNFMqfkMnVxJgC/53YWcjF2xnEwhIxEMYUwiewrwEo/Ttwk2UcjV3MRhznEII7JZqJIHml4saPEgICSfPIxoEWNQBFmxggQIcIw46hRokVBlB4cjGLATC0laEgyTg7rWMvl3MZp9pCNgTFG0KD9V9+YtK9FEFDI4JNCWMJjBCJhkmE7beEWFIKKkus24oppeOXl3RjjSt56/DAuQ5Qj7zfzwo5DnNrv52jnS9DWBwfs/7p4SAaTMaUm7AZWieAuht/+BeImmFUNpoJU0LWfgIoyiMmw+2nwjaXWmJMiTXr9mX4WVFm46xv3oiwKMq04jW5xL9Mz0rA3BklfaGPHy9vYPXCACW0LPkUGf9nWRO3yHMxaPyIKDMoIy2+dS4V+LsK4g1C6g+9//7sUKeZw6sM3uWylhdy8OLfedAkza67j0ftexTHQzc7TTfQde5ubr7gaUY6xsmoRnS1/ItZQzqeP/4NjWzq4oW4muz87zNPv3MHGJb/lrqvuZVb+bL49axMVlVMwmUNUOAT0JidGUy71tRbMmDndGcQUV+Ia76Kh4RI8I02YlDZMhgBjwwoK8jMxpKt59NHf8N3HbmLHsS7Om30zu3p20/TJ37jqksv54/zLaD61jdbufWgMCqbPseHWiCT9AVqPf4zXHuP8ZfPx29N58v4f88QT/8W7L/2dH/7uSUyxCKvrG8gxmvnWXT/lycf/hBiXiYYCCGY1kcFxJrwTjNvHCAey2P7zf1I5fwYP3/IIpbpZ1Po1/GD5PRzY+hF/fO4hqqqKONp0AMfwSWSLzILy2YTCflraj9JQq+PyDTczRDuZMTXLFp+HnIxTUmDgscdfoO/kCEaFnsIpJrKSJsprF6LRR0kGYfcrvQB8+s5pDn7YSuu+CQASiLzKE7zPU7jJZAaVnKSHEkrpZg+1LEBGZgIvcyjjD3wAiPhxECNKHhacTDCBHQMyZgqRiU3SlMAQPpIIk52BfoJE2cTNNOOkhmLKyCZMkPlM4RDt7KSfGjLZzD4qKKKPMbK+7ojBuAzpei29IzGUiXFGnDG6hvtQOEX0Qhp+Xz/WIisejR85KbH9j5tR4mJqXSEVxWXMqrju3y+eW5RqF1bUQNIEL/eBSoBbroC77oBsNYy2QUEJHDqckh4LjcDN34WHHgS3C468mzpPO/z26X8SGh7GZJW5dsNthEIabvvFfRjkfGry0snU2cjNyGH7yUOUC2ZMvd2UW6dQV72MdTfOJhmsYssn29nVtIVTjcfQKLJIxI6zfm0FbYoo66+/ncrqIjLzYhzd9ztef+sfFKZn4vQ7kdLzuP5bl9A/3kgmIVavuIgt721l0z0/5+eP3Eb2hZfhnujjwovX0t//Ngfeupvrr/kxv33nJZ5+7ja8ooVlV8xm3DnAnj0tvHHyI3LTi/Cb47QftpNUJTHmqDg81MZfP3qIFQXnU9NgpeczBw/+5OccavmQBUurKLVayK+tp9ZWw9CQhpNvfkI8p5BRXwAp4iKkHadrooem/h483gku2LiAjHAGWbpsnnm1k+LcUt779DDHRt2svOJi0vPSse+fYONF1xG0WLj3qlsY93tpaFhDwu/ixcOvYs2oRq0UcY0e5FvfvIVn//afXPaDjVz+nTVc9L1HONbejiiK3Hn5t1DmmTnVpKC2PIPkSIJSg41IRM3pgRNEJpIsmm9k0fRl3P3YM7ijMWIGF32tnzJnppWoM4KqIE4yJnLNdy6nr/MkJVekMdjqR6/5agT+MU5yBb8gh2KGcfAAdzKfBiqoZ5g47/E03+AWBCBCgDAu6rAgk6SeHPSoiQEBogwxwXymEiRCACZHg2Wi+LmGdbzJU1zLtSynFoEIo/ThZQIXLkaJkkst+RgYwc0IUUopRA148f9bF/laBAEBmZ4hH6MhNxct/RbBsJNANIhBo2bLRx+jSdMi6DVUZdvYsWM7FTXlaDVKkkIApyfAxbeks/qaehrun/Kvi+fkQJYWFCGorgK9EbKtMGM1rJ4NpmzQaUFnTGEN9h6HD3elHk+bAubP20LPPvUQJVkzsZY2oEzqSbisBDwRuvtG2fDtm9EqZUw2C939IWprS3ErXCy6cS37dx1ibMJFTloNvd5mpFM6Kupmcs1VlyBHkhTl59IrHENlkMg1l6M0WsgzW3Aa4qi6OhC8Ekoxgwd/eS23fuObRBJe5i6+mYKay1H5xzl2ejdRg4Y9O7fTMGMZwbCKU137ENPzee69p4grPCxYfjEKJBact56wpORoy3FKy4sZ8fTw8jv78TrGmVm1gMw8LWPDMeKyyJ3feYKDW44zv+I8YvpB/vHx82SRR+/gIKec7XSPnqQyq5Zv/eTXPPnsa5SXlNLbJhBOGpATStK0OfR0dhFOSrg8MXK0Jm5Zm8Pupg6ev+dZ9DY1J/4Pc28ZHuXV9X3/RjLJxN1dISEhBJIQILi7a5HitFCKu0NpS2mhUIoVdwoUdw0hBAnEE2LEXWeSmYw+H+CuXL2v67me4/3wdn3a597nXivHHHuvc2fttf7/pMcYq/QozCWcPHuZ6poK4p7Eo6hQU16eTXlpHrKSarBQYmoqwFynI7zbIKK7ebB01mZaODgye+pc3pVnUNdcxo21X5NVVsuWVduxMvNDptHTa+hmOrqFU19vQE5lNUW1cqyknhiJ6rn4ywVEQmMkZh4Eh0fi1toVnUpHZamC54/vYmKgQlCvQ6gSIjT/UPK76F+q40VUcZpT1NNEDTK28B3zGUUDxQjQk08t5cRgjT151KFEjIoP99setKKQYqQIkSBgMaGUk4/0I27h/2ADShDzlteE0J08SoklmQbq8cMbCUrAGBnV1FGBCQLcCcQfW2SUfgQi+/fyj3ACzSoNJYXvCQ5w5cyTX8goLEdXqKCwphErt2qePrxJc1MtFnIF7+SxeLubkp5fwMwxn2Iu1BF7XUPG9SrqTjUx5kAgczf3+0P5sUMfqgt7dIOhodA2+EPdwE974LttMH8DdO8Gvi7QbQSEhYFQBfIGWPYdKBp/V3U5/iKfz55H6osEugzoT6nuFtFhHnQJH4CbWoyPNJJFS+dw/OhB7EqldA5pTfb79+jtpJw8vJVxk4dyPeEkoxYNR1ZXhWefQM799IjG7EZ+O3iPg98dZmzX8RTEFXDj4XPKavVMX7oMa3MLKlLywdKU9KozlKbm8jx2B6lvruE5rBVubdti0qihUSvHz6c3R369zdO4eEqMS+gX5oKu2YZyZQH5FfX8cPwM519kUVtfRX2snKiwtoyaNYwGWTUSG2cqM2poYRdCtbyS80dn49utEYm7EX4aJ/wdfHiW+gIzW2OuH31E0ssHeEe4cOfqHVp36UhpQz4tfYyxszfC3dwJVWEhg7v2wN7cG0M3Y9KU7+nZZzqOFlp2HP+Oqnwt/m0CsRN/iDEojct4ePEARSTwzfpfqC+opKqmGnMzE7xa+eFgaIi7qZD60iIeX8+ktjGevHQ5fWZ5UJybS6WsmN6Tx/Pk/EMSlNlIHaxYs+BHpq0JQhTuQF7RPYSWCmwtjDgV8xi9iZaXNVdp0ckIlcSMyDZtacoqZUrASByNLenUdRzRA3vy6uciLO1d0BsqAdjOnr+s3xeUUsQ7bvGMAXTCABE7uMhseuKGCBMMuUcupghpQEkYPgTgjSkm3OIpNjggQowfrugQY4iCwXT9WI8oRACMZwBPyUGNCmusqCERb6TYoUWMBcdYTBlNFFHC9+xiBesoRI0dQgRo8PvIJv2/yT/CCYjEIKutwFgqwVTniLGZDY1SEcZiEQ8e3qOmvBZvRxFSF3cqK/JxCY5CWWeBXqBCJ9BRWSanqKEEISosrE3YvfrmXw1UVYGR4Yf8f4kh2LtBfiz424PYDK4cApHFB0SiZ/cgP/1D3gFNEPsWIqMBEMjVLFk9g8HjRlBVWIPEy59uvYdz49aPKDTGBHXoxqOLjwhwtkdrpaJRVUO3bt3xszJF5lCPhbUJXlY2tHT0p1X7IORlGmYMnMLgTuMwcrQEhZaLu3bQ1Axje85EpNNS2/gSoYU9X6zfwpQxc3mTHUejoBpze09MGoRk3E/m5IEdKA3rmTh9Jp4tQ3E2ECKvb0JrIsFIYoc+rYLGBh3qhgIsXa3xD/BBZ2BI296d8Q1tRWnyW2ysW3AjdRct3X1BJMTVx5w2oV0pySvndfwdnAMiUUiUdAqNwsBUQV35KzxCAsnPq8DG2hMdMjRyKXJNA6YyC8wEFgQFdyAlL4vgyCi2rz6InbUZ6bUGRIb48+P+rfiL7fGN7kCzqYSGpDKkiNAYKpDpZYRHdKRl6/ZIbUU0WtYjFwjxsTIkVWeOo3ckXu0deBGTRZBPB1o5OmLoJsXVz4fATlE0lIkQWhohljQzYkYfxLXgINdSUttIZGcbor3boNfkoapuxNu2Nf7WLjgGSLgfd5SnZ67RafoQ9NZCrtz/iaeZCTh28cPew4rmKi2+3T5gKoz6LJou0z9gCWRTRd7HZJxfOMwLqmiDO7Hk4YItbpjjjxv5lNGMDgOs6YUzgo+RfynSj6iBcioxpgdj2MklOuGLED0ioIhymqhGgAFPiMPoY7mwLWa4Y8xR7mOFOZXkUk41MR+vKi2wQIsYk388NTnQqpWOIlAAACAASURBVJUtNx/GEdalJxW6QgyFQqrr6wgol2LjYc2LkwXkFOXQUFXDxfPHaadQ0qfnYnLyq3/XkV1Yw/4RL/+u/NtDH+oCrGwgIQl62EFVBShNwawS3qdCqAcMGgkrd0OPzh9Kifdshd6dIT6GCas/oceoNgQIbNBK5ERXO2Ou96DgZR4iNGw6uQQT+XvcA30Ryirw92jD4OljuHTxIgGh/libqZjYfxQuGk/OXzlPzbO33HuSRLU8kf4zx9PazZdXTzLYn3saVaaEbae+4V12KpfvXmbMp2PYtGwT5eXlqOMleAe7svPqKWJTYgkwMMPfM5hj35xk4oCp3LjyA82NGgQ6KUXZsYiwoe34cCqLdJxc/wSZTsqNO08QKOVsP/kTh7dtw8KwieiWwwnxbs+5Zxu5ff8FDRnG7Iz5ibljJoCzmlMXVlFZU0qjYTPyUi1ObsbcOP8Ej6GNHL29l9vxj0Cop1apQy3U4WjlSL1ZHhp5OeP69uL666Os/m41Vx+uY/W3t/G19CFdVMHGT7+grk7Nz1cPEuTbCndvN5xsvfhs+Rf0HT4SJxN7pDVa5kZO48qjSrp1GMDcnd1YM3AKbcP8eFP6kLzst4z69AuEjRU8Syli+fpFaIsLuX79MW16tCKsZwjv34qRFRaiFlhQXNrIl5N3sWN7Z95m3UfooKOxsAKZRkCPTVPY+uMC1k4ehkBohHeYDfVZxRS8f42peTM+ZmYsOTkWpWEDukojYlKfAmCLlLWsQ4khzdTxknTccEaHFR3pghLV78uxN4bI0eKFFzuYRRF5NNOMM+5kkEYl9cxlJtaoP0KZgxhTHLEknwq0JCNHhwh7KqigH72RoeAmO7nCY1KowBQVCmTk04gWDeX/9GQhtUaNlVtLjIRmxD++QGSHjtTXSTAUNlFsZ05zczM3Yl/g7O9MU5WMuduXYTJiECO7RHLo1tK/K1z/IYmDX9b80Vf/HhqrwNYdnj/8UGnoGADRfaD9WNg8G07u+/BucTE8SoAV3/4+/eTmE3w+/ARKJwkxj6/hOqgjhs+qMRWWkngrlQ7BBuQlZKJPKmftvFVcOHibDdPXYmVvh6WjDaYGphgJTXmelMHL2BTM2rZjYs+hhEZ3wtXOkXGDu2Ed3IKBXUejaFFDi1ZRZD4qQ6yNIDf1BuW5pez++RLde47myuWNWDvU0iwGnbGUxwevUlAuYMbaXVw9eh0bOxPkzWrqNFpuPk7g2OZr7JmxlHbRzpjqtNg6WiC1scCksg4Tq3BKVUVM/XwAxUmvqFZYITLRYWDqgLowk3Gj5hPoYEdhw3PQVSMSqMgvbqakoppGLShqBKAwxcKqEnVTA252ltjZeXH6zs9kvi/mbfFLhnQZw/B+Pfl1x69sWXqdR3d/IfvlG2TvyhnQvx1GhpXMmDMfjYWeyvJy2kmCGT9xIJYCEY72drTyakG/2eHMX7MBpRF4Sj04cns/NVUlHD60AQuXdjyMe0yFTsdXZ4+ilWuQFRfibGaNtrGJ2Ngqli3ehHsbMeZ1HpRqU3n46jRKsTlKgRHWVoYkZDXj5mlOSEAbPD1tCejdF62mivKXpSia1RjpXamT6XiRlMfpdQ8oSysg0DuI6JYRAFShYCMbCMEOCySUUshbkvBAgxgZ2X/C2t3IIw5wi2RSmcde+hOGE0aY0IAhEp5wnd3sR4cDa5lBB9rygidU0cg2vsEUA8xoxgoLKoBj3OYZr9nCcRzxIApfQvFEC9TyARr/xMechv9N/hFOQCQQ4OrlgUJcSXWdjPu/PUFipKKDTwQpGYk0qav59uRKjE0tcTK3RVsKL3+9h4ORC5dfHOWz1aF/Vbj+K9BVgtj6jz6ZBgJaQMYLsPeAk7tBVw0rzkBe9gcykdICOLkRarPgxklo/JBg8dW30wnqAEn3NqDWSTEyNeHKvUv0HjGI2lIls1dsx9TJiHYdO1OY/YKsxAS279hLfOZjvP2CsRT6ItMLKC7Lw8BaSee+nuj09Xi49CIswJrE7HjEDu1pUlVx+9JXhLUaRXXTc0I6dKG6oQpLGy/6t/YmJNSUWw9uY2PqilwpIjE9heRXidg5WCGQNKPKS6BzVCBaAxGV5eBo6UqdooF1s4ejdI5k9oQBCBqamNR1FMbGxuiaDNBmvqSpwZ745+/wdRqBUiZHp9FjUJ+FocqBhuZiFKpGHrzMRKeywcbKBEd7FzQqLdZ25tQkp/LpiDmYmNsg0WmwMhbiILWn8H0ROhSkvSolty4dfY05r/K07F47n67dx7BxwTx8zCwIbe3LFwu24GXrDZkqiqugR8dJJBfnk5abh5GZNUlJKXTw9+fw/iPo6+twzVHjZ+eF1kBJkxJa+URQlF+As4Upenk6q1Zt4875E8hlKmoVcsxTcymX52JpYU3C7be0DI4iIakaj5ABOFrZkZ1XQ8Gbt+iMpKQml9BkaMCvp+9j4+xAdkoOKo2WosRSBkzvjouDLQYGWiQG7phbWaPU/3FjsHzf55hijRU6ltETT8zZRwJbuMTRfwkmZlP1e1XAr7xEixgVEiyxJQA3ZjOGVF6ykQOYYQwYIUNDBjGACQpUOGKBEmfaY44blqQSTz6FPCaWh6QBIgw/hgTDGPFv998/wgnodTpcsppxdvNBWFmEwrgegVqLi6sdQcFeGArM+G7tBaqr5dw/nUxB+Ruc7EzwGeCOt5kn1Qb5XH56gcU7B/2hVGgHkxf88TxxDfh0hgsx0Okz8AkFL8cPYwu/g2EzYfEWENVD8EjYsvP3m4HEtFiOHDzPz6/voHKtxa5Cxtpvv+HwyY3YOFgQl3qF8mdaKkxlRPcaQXRXHyYsGM3AKW259uwETSYVNJdVY+vRxJvydwR4WpJ8Jx5LSxtcDdpw5+4Rbp7YhYG0jqA+sylveIdGb0X7Qb4oTcswstPQ49M2DOg0ETvvIBqbSog0nsn4foMJNvLH3iYADy8nJkxYiMrIjZT4TIJbtMVcKGDCmFHU+QpZMcmZ/PIqvOxFaKpeImrQEebhS5OHFMsAT8483MHzF69xN7LEVaLDOcCHzi7t0Qe406DRY2tnSV1tMwq9KdPmTMDOwJlOXZyZP/Y8An8r+kWsY9qYSeSkFTNiwmCyshIJdguhV9dgli7+lvmfD8dQlM3Km9vJqq2gztCKE2efcWrXVc6fOM+AaaOYs2YWkqpqdlxfQGXucwxLHFDWNFOmMaddaBRfr/uRVzduY9F7IAqZLzKFGp+A3uRWvcZAp6WgQEznqJb0G+VB566Dyaqq4Mdpxxi6dh3rD0wkL6cQj2Bb6hqy+H5wT+av/Ro/Txce3Sqkt60tuhoRAaEijKxdqbZW8+WsJVRnCFkybyTr1yxlfseFlJXLiAr3R6IvYdT40XSb0uP3JWbbJOExSWTRzClKSfj4FQaY/C/BRD8sGUgwk/jAX1FEA6dJxhIzjvCAYgp4h55wWpNLORpE2CIhgwxC6I+KIg7zHFsMKUJON0bgiT+eiPiezbTGn0H4ABJG050Ubv/b/fePcAJmlqaUaDVUVMm4kf4eTx83rI1EdI4eTXFlDYGdOtLGwwaJsYxJnw+hNL0ZoYGIgvpijEzNsLA3JP7FJZTFTfzwZDwT1/xfOFBH94b+n4HXh6McJ1fAoY8sxmO3g8TyQ8HRRzl7JJ1XWanU5Odia2SGma0DbjaWPIu7ilonZuzCL3F18MLD0Aif0HbIK+twMbAgviiHViYONNXIOHPuLsXKBgJjmjCVmrO4/zwO/7aNBpUJ1mJXuoW0wsZJREtTZy5fP4udsyn3zt/BwtIEIwtrOgUsQy+wpCa/AmWjiveaSuoqdAS1cSU1KYdta04j1svxaudAXbWQtFv3UBrpWLB5FvHXXzIkoi+JxUXcefQOKwcfMrNKKc/NxMvIntLSSrJLS9FYllKcn4O3jTNWynp8e49EU5VHYIsApFopVVVanO09wEiEnZ0FRmI1Egch584dwcPPDq3cjlat/Dnx1VlUAi1mlhY4hrcmNuk0hQVQU/eO8ROjmTRnFG069mfMpEg6eNtSm1HB+q+WI6s0hiYrzEytUevlFBbXkpdRQMHLAjZ+d40lj+YycfJSOg+ZwdTPNyCvV1D//Am2Vp4Ymonwb9UaMTpyMyvwbx/CwiGDqZNX4ePQhaRXObzPaURSqCIptQhnZ388fR3RaQW4+4vY/M0UypRFtA4JAGNr0t6mUSuDVT/04VnGSybPGcqy5VsRCA1pFFVgXFCLrUcLlJV/HPMvxt34vR3Hc+6S8pdl9+0PH+g6u+FLFnVcI5lC/opTUUcuownnYx4sEsqppBwJKgwQ4IoZ+TzFGiecESKgjiqqyOQhSeTwhCt40gF7WtKMAY1YMYypfMrGf7sd/hFOQFYn5+yjw9RW5tLC14SSjFyqpTbYe3ZgcvBwHCttGbq2G0q1jBmzl/BbzBFGbF5IemIi1UIximYFCpUT0e27s6DzKY5vSvjPBs/d+etzt/Gw5SOnys0TcHkdf2ZxXbGiO9U5FdQ1aCgvTOZNiSUbJmxiypqt3E1O4Plvv1GkrCY7L4Okpz8SEd6KAV06kXonnoDOIZS8q2PVxC8xKDFm9pUntGw9nM7T1pBY+IS4ikSeF7/F2asDxk1teVH9DiuVC4+uXiMlO5XOnUfRUFzF/I19SU65gsDUiLjfGvCVGFFeWIpW6EFAx0DW713NzzeWkXrmGTa+pvj4O6Ov0zOy+2D6tXNCaWWEvLQO01oVZ9If4SwWoJa6o61opoP1YMb0G0FeVh6DJk5EYyHg5vN6On3SF7+gluSr6jF3tkSkrCMwuB2JaYlUvkpHlR/Ehcv7iPTpTJiHP68qz2Eg17B8ZRdGduxMWUk6omYxaVezGb5xJFl5yaQmpPH1pvm42LozNmIGbdq4ogkQ0yM4lMzMN9QalJGQ9IqUV9ncfXODhNfpTFzUi5MnLhC34g59loVhZCklIT0RowZDHsdV0c6vHarmRtQ6AwreFvPl11PJfH8VCxc3rr4+Q7fIaBxcdZhjRKq2Gn+VPcUiG4RCXwrKSglr05Uph45gI7akWalGeu0FrnbmDGz/KcXlOsxNKvFsE8nVe09w9TOmsKkMA+8gku/+jNTsD96BZ+cy/7bUFh7x/b3dqX9/AEoQMIQP/8I+5CXn+e33d65RiohifLAmCAtsgDZ0RIYWHRJaEIIEM96QgAuteE46SsT0IpSpjCKOMnRUcZgz5NHIFyzgHcnU/dMDgzoEfP/VLpR6FXpHa8orCvmu+yeM+aQt8raGSINMyDkUg4NTC3bE78bY0Jfcqme06SXBoMAAlVLID8u3MWb4qv/aZv+xH8qBN347BZyD/xjo9wkcS/rLu1u3PmD1wj34OnkgvCpAkXMfkbiU5JsHwQJic9Po03sWN3KPcvTidS7G3KO2uolRg9YQZhWBcXE1OnMxDl69EErfEh93j3HDfFk/dSfCsgRSiiq5fS+Wm7s+o+ntYaRBzQwf2IcJX4xGpzTAsLmZ5QuPky57gGfgfQ5diKPrlCjaukUSPrATeZUiSt+8ZuecPXQNELBq5AqEmTJqZRZYWdtS1KBm69lbuJs4oBXa8/ReHpMXfUqouJEBPQfQZXAUEX7tCfRqxdn7d9G2UGFhrWNsUCDaeA1+1hY8j03GNcCWPZeWI9SpaRvgT7uOQ1izZCVR4aGsOrCcrGcy5kwfzMAhW9l57jhfL9tBbn4Cd5+9oTC7nJ9+OYFnO2emzJnF3ssriG1W0KbfJQI9DSjMaSSltA59k4IOLaLx8fShtZ8xrTvpqS2t5+CpFTyMe8rdvbepy7vN/jtb2bTyR5zbWDJl3DRCRTZsmr6L54+y+P7LU5RoUsBUR0zWNSZvm4GyQIKdi5T+nw0gcHJPVNXpFLy5iJVESaBAgX8bR2SiOtysgnmkSqc8/wWHbn5FYe0DDOw8yXizmy0bJ9OhQ3sc6qzYtG4vb3SlRPq3pMfIUHxCzJi2MpTfHu0FPrDen9i7AVXZH5uvQ0BnADLJwoYP8aoDLGbURy7fvnQA4DQlHOM69tiTQCP2CJEgwgdTtnKAho/EY1/QFwkSGlFRjheJPGA+/bBCgQ1SvudrcqniAucJ4s/gG3+Vf4QTUGpUHH7wK0KFDh9Pb1ycrQnuNAEnW0dKVTpin99gVJ8x6HRN1BbJsTFTEvvbA2pq6mh8k476PxZKfpA1eyaxb/e6359vnPmAtNKkV//HeeMHfvDYZx4fQ+rgxG/vXrBq+wPeZD+nddsu7F50Bys7AXbO5gh1xkT1HohaJCGr8CFJx/dxL/EmLYd153FiAmWl7zhy6Ai9w8diayjATGuEqY0X3gFuWNtKsLUxY1j36aSefUVxUy23DsZy9/VDcpsakYrUmJQV8e6xhrMXfuTE1kl0mjaPtqEDyf71HPVpMqKcg3HqMBDT1kF8e/MF8kYFrj6RRIe3xFOsw83ZgUhPQ0riVZw4fJe0glT6TF2Eh9QWpWkDxQ0V6Er1FObmotQ2fUBDdgmkXq1A06hgxrBxaKsl+Dj7oPGyIivnBQoUeLkEERUxDX2DFBs3Q6qVMtSNeozMK9DoxFh7aqgry8LWwp7k1zkM6RuCV1gnHt46QJVKxrvi95y8fJO8mHukxTXzyaTPKK8qplbTRGZhLTWVdew9/ivmWPDr41ss3z2XK6cv8f3xE4yc2JZ+gyN51lxKYXMOd6/dxdnDjLwsyH9fiqetL0FWZRiaGqDDgvQbGTQ2i3GwM6dOp8HI2oPKogKadQaYGZihrSxFaCDBQKLj3oOnaMUaZGWmPH8lINjOhKd3bjB5UHeqqitwlXjSN3oQVcmFRHVqT3FDIat3b2PcmmjWbl6OT0Qwjc2Gf1tTR+jLc9KYQgdm8N3v/bd49nt7HhMRI6A9PVCjQ4AEJ8QYIMXoI638WW6gRU0VTUgR44Q/1Qi5SwoVNHCHRyiQ4YUGAfl/+zv+RwR/JlX4/0taBgfou61yZ5DrCB7eeEle9QW8vHoSHumPd54ltYN9STlxinlf/srUcRMQmhVweP/T/2c77ccGM7LPKBZ/uvb3vmGL2nFp+ytmLRvOvm8uMqRjEIZR/pz77hLr920irIMx4hJv9u9dzP5vT3Dh4H6KmvNxDArArLqBRHkhY5fs5bfPJhIyrxe/7diBY1MbWvaQ8i5Zh3V7A1Ku5xLaPop6sYxiXTFeIlvc3TrTPbQjbxriUCSWYxKlZuuEA3i0N6KtXwtCu4zAzrsFjS/fceDOdxgL1AzoMIfE9CzcfFUI0kyJiLBFJ3LiWWIRpkH+pMU/YeLYdew8toTJIz9j++kF5N+r5vzh8yjE9UzeugFfuZh7L14T1CmAinwpDhZVHPwtjq6tutB9pCeVlTWYmTvTZognp77eR3snF2qt2lErfoC5pSHdO3XByDyY8tdVWLdwx0D2mqSXOubN/wozIw2/3PgNR5WQHafXMsWzHQ7DOnD9XBH9u3fhxfVjOPm1I6YoFr8WXgiEOjQCA9ZPPk7vqdZkPVAROdgBT3t7QgZFcu/xDcxEeirzdWg1NShlzUhsnWgZ3p8fJ/7E4PEGqD3s6BHWgz6RS5k6rx8eLfxJjnnOtaNHmb56Di4RHrSyas3jpw9QC7Wc3XCQ1ac3UZBsRvsevri5asiNScYgQIrOypQDn11l2NA2CGyk9O3XlReJWRz85jYjWnQjsoeIy4+fcv5iEdH9ffjhq6MEOaoZtXI6sbEF2Ig92fD9AgoL3uDt0pFC28NUp+nRp9awdVs6ny3ohEIl5c6DV7x9cQc7s3AAZtCP89yjjr9+kFbwBVv5kfG0JJlsrGjPMc6zjo285Cy1yBECi/mSfIwxoRAJYn7hJkuYRBHFdMWKJWzHgXAeCF6+1uv1f6VH4h9yEtAIdIi1BghESly1Tfh7dySr/iX3nt+m7YQvqX6di2mbFtwtPkdIWPjfHMCsjR3/jea/SqeIjjTL/+r0Lm3/QJC075uLfLt1GhE9wrGrqeXArXUEWDpw9/5zKuXF2HtLuZtSgoePhBEzp5Px9Almbi4sXXqS79cu5llaIXWN1ViadmDIiDFEhbbFVC3FQidn7fIt5FaXUV/XiLFGwOs3bygtz0bY2EBxSTpljYa8zc5h5sLZNGlUOBu2w8bej+837eHmgwOEew1mYof5WLv64x06hLqSd0RM7odcISG7oZbO7VxoF+CPtKaAny9vwKJMS2LcLawNLOiirEEsqiX+6isas9/h7m/BpZvnWLl5GdU5GWRmVGEq0hHopaW5REZaagn1Rcnkluh491bHyImruHjoIsVlSoQaNRpBBYV5Deg8rTEWSrl7KxadZQ03nu7FVKSiIrUIhZUSgaoZO/cAMlOy+HL+AH7ZuYeC3Ldc/fU+W9ZuoOFtKcMGTiIvK4G5uyZz4cBtpszpghQ1/bpPJrv6GaqKSuJe59FYVo2Z3hGlkSGiogqubd9PtVBGXYMFtSWl6EVCTh46RVVCJcbGGkYPCif2ZSHG5s1oS8o4e+0y7cOj8PF15drLxxib2VJrVMCt9EdIFWbcjYtFamOFk5khDnIdSTWpdOo8kLepyWjUjTh5SJi/bTt7467xvsgLnV6IX3AwUr2AmLwq1HUGCMWWWBoqKS3TkfzuLZGRkZjZ2SJWSanQaXHv4oHeUEFZSgY2JkY8e/hH0PA97393ADM2DgNgDFZs5UcATpFOe0J4SQymGGP8EaLMBR0hOLGJveSThRNehBCNKc00IcQIUypwoScdsPqnZwzqmlVU11YQE38Viy7WVNdrEdXWY2Nnx9HUA2iL9ZTmF7Jq2zr6Du/+t/n71sb+L1r/Lr4ebbH1U/P5jMEAzF3dn9FTPoCSdJvpTr66jFtP4+k2aSYGGhF9HTyY2qovoTIJAyMmUyxL4aWtBy0CrZCXaCl6m4Aq8TD9/QzoEh6O1/MKFo5pj9y4jpevbzB4wTRa+gdw6NYF2nhaEdbKFStbFxrVhlQ1vMMltC+pCa+wtdeiS9Xj1LKcVq5hCKvS2PXTAg6sXo5duy706taTdJWYo5f2sGvxCgzLTDi5YC5PZG8Q6yDxfTwJaS8pt1FjbCRhxfe70Flb4WYjIcG/HXpNPiXlTwl3tkZoH83KlStYPHMJrQJtCPSU8qYyD1mDAZV1WhzEagw1fmSdieNYzA8MmDiLtg6OuDuZU1lhjlTSxPP4/fTv0YLdS1Yxqk1XhnhE8eupvaTff8HNpweozJDw3c5fiKtMoTmrksKyJsYsHU2+2JI1qz8hpFU/2nVuyU/fr2HY0AE0xKUyb+0Sflh/k6iOkzn/5CTN73WM6TkVQZoJ4/r3Jy+7gpq0ZrbNWsfKNV+SlXePL6YexMvdC5W+hquvf2Tzka9JTowh3LM7Z+J/pmf7aPRWpiyd+SlxsYlk/KYi7v41HByDsGp+h4m8nNCeoWz+ajayuly0plLWHPqJQN9ANh3cRLWinFpNFRZSESPGh3HjUDWP4x8zfl4E46Z/gpm/LfPmTsXbPQhHoRi1iQ6h8glDhs3j6t1bqMvlVFYVMdhxCCdXLsVM4Ey3RYOxdbJEYi7iafwZAO6S/vsaPbD2EgBn+QBk8/Dmzg/9vEYBCJBgiRtG1CNCRw71mGOOljiSeMU+TjCTOZhhjhgDknnPAJaj/BOK8b/Kf8NK7CYQCB4KBII0gUCQKhAI5n/sXy8QCIr/haT0f+asEAgE2QKBIFMgEPT5v9nQIUDbqESrLUDTaECYyohPXAbiaqpB+PAeIaNaMXzYJIZ06UGN0R8/2Jofhv5Fzzcn5/ze3nJi1t/sxL0+i69UiqmzIVuOLeFVfCrtvNozbV8kNbJKiu+VMfGLMVgINVQaN7P04k/k6eSU+3qRe/chXy/cjIeBJcuH7cJ5UACK1hEMHPcjhjpLIsJDMfPvT8LlN1jbS3lvq2P2/M84dvwxA3qMITcnnzv3niMv1+PiIsDBrTNrZo1hYNginie+xtrZhT5tT2PpLcKt31wGh3QgrdqI4d0WcezpWTLjnvLT+Hn0W9yHZL0NEdMXMbTHBroOHk29fS++2b8K4+J6qtIaeCcvJyjMmTGj+zF2cDfmDV7J7jPPWLFvExmHtmEfbE5U/54UljdzJ66WQxs3Y+Viw6ljP/I0ppRVy2bw856zFF4r48sDQ9n/4Aozxx5i+tg1uOgG0b9TOCv7b2DPyZss33+UM8+eYe/vwoHEXxjQtg/jBoSyY/JcuvWZi0lQa4rlSaScOIqVADZv3EJLRwtykWGkcUNWUEJgCz/Mm6tY8FkHlk7bgibTnUFtt3Mv/jq9RgRhZtaffRd+ZMuqSUhbDmT6yNXYap15b1dA4kMxr5Of4d1aw+m7x1n/6ReMmrieeb0W0Ld9ED52XUjNrmVCv5lMm/8lUjslUmEGLhI/BrZdS8WzFETFPdFIRPjUOHHi5jdY5xdwc+VFdOomWlo4sfjzdXSKCuWTSaEsXN4FgdSB0+cP8SI2nlu33+BhLWP0AA9UajklSjX1OSm0DepAwosa7AL1bI+7wOg58zCw1vEuMZmZo7tRhg5fzV/BP9f+NJMBM1x/f/bAgBX9dhCGKQZAP8yxwYitLCceOSH0QkEjw+hGLU3UUsg8ZmGGGUIaKCQBW+yRUcfj/49AoxpgkV6vDwTaA58LBILAj2M//JmkFODj2FggCOgL7BEIBP/+LAIYGRrwPr+KTV8+IkmZgKyhBgcbK8R1hly6lkjM4/tcux0LOg2ZBWm/zysvygbg2rXPAVg24effx8rK/h4IsaKWW8+ySErMQNmookHVRNfxo5EodGhR0KZbO06e382S+V9x6ewlAoN9sXfy5fGd0/h2HUefjn7E3DyHzKiZQL8I8r+9xMHDKzi88xL5gmri9p8gtFd33qc30VZvxqBBLbBxMcG+hTcNOi1aQymVskJkDRpe3I1n694L5KenIy/LIqn4PWdizuMTEEXK2wsozBRc0u83/QAAIABJREFU/3k6237ZSmt/CwaGh1KBPa4NOmLevOKHYycxtrNCLjfn9Mn5DI0aTH21iAgfNU9un6HxfR25OVVUl6XTqV0ndm9aRdc2s1m3/ywWNp5UFlUS0d8dF2dw8jbE2MyGe3czuf4kjieVWmIS0vDv2oXb8TGsXb+Yb3aOYOnEaTQXJFGaVo9raBh7j87FySUCe3crMJRS3JjLrZhXTJ03lbBWTuwbOJOA1p0pqK3AwFyKSY0WMwMpLUwsyEx8w5RlC9my6CGjxi+gZVQ3XFsHMGjpZM6cPsq+019SWtHAi5dZhLfpyKplCzl79wZm5o48ScrjfVMc935YyrqZm1FW6NE0iXmfkcmmDbcJ6+fFnss/UVCWi0hvQGNOEq4+/khFCozdfPE2C6ai0YT7d2/gb9edG7d+QiIU0TrwUzIbqpj/+Sr0zc00qcTkvWxg+vzPwVZDqFcwli7O6KhE31iGMNCS6toKzt3J4eyNdAYNGoS3ny9+bXw4ePNnEm4VYWzTwPvECsysrHGNDiYsPJo3b57hbW+OedR4Ms/MAODywws0FldgIzJh2qYPtwj5qHHCExPcsUfMzX/5mnejExG0pS+DMAHqUJBPBWqamM16mpDynCw0iDH7D2yE/w0rcaler0/42JYB6YDLf5gyBDij1+ub9Xp9Hh8oyiP+kw2BQICuTE5mTikluW8Qasx4XpBOU2k1wybO5M2lX7jy6BLGQisycv64iw0P7cgnq4Kwtnb9m85di299aOT9QYq8eMkGHsU/pLJEjVrdiMTBhD0H9tFUpkXfACr7Glq2CsHdWYiwUs+IrmPRaQwQNyipEVRRpxIQZu+NZRCEebZk16mt1MuMWPztKmLvJPLpT6u59DiB3DsXqEuQoCloxNvNhb3HNyFTKGlQ1CEVNGHv5czYWe1QN93EwcmStynVSHViHh3byqC2nyGXy5EIHQkbEk2HNu0orRDRZegXWDg4IRdKUDQ20DVkCBtXbWL1z/MZEt6R4IhRqGt1+AcEYZSTx/N7sWS/vU1oeBROI4ax/9JNNEoD3spzKXn1ipTcFAwEWvqOC6e52JictHd4WPkyf/Q4fvvmCw7t3MVX+ybgoRaAIpcurf0ZNKA1rl16IxDW066zGyFd/RHq9RhamlCRmYah2J49+xfSZrAzYnsfJizozp6NG5HXpiEyMSakW0cqamswkogJ8GrN6vUTufn2IRnleUgqdTh7eFOTeIsNJ47RVJrBqkVfk5fagIe7MR4OHpjoDaipL2fJlEFYK3QsmrcQ39bWeGgtMBBJsDZRUmuZy6hoL24fziA+24BAV1+C3DuAjR6xvRR/T3sS3hcydOhQggN9SBdLyUlvoqGmiOSipzg4m3A5PpmGwqcIxRIiuneib99gitPKqZU3MGXCfKpq5Sho4u6JX6kSKpk6YjAdO7akXCEnJuYZj7LiKMx/RkVGBWJ7S8xMbVi44Qvi77/nfW4iekU9JUoZxmoHAobPJiPjPjEPbzJ33lo823VG2Czn2O31vMo/ySUeEkMaxWgYMdvvL2v8MBfxxpVAWmKOiMEMpJlqAmjPYEZRTwEtsCGTZJYRyL+T/6eYgEAg8ATaAPEfu+YKBIIkgUBwSCAQWH3scwEK/zStiP/sNNAiYurkacxYP5D57bvi7GzI0PBAqksraCyMYWL3Q0TqIvFx9cBH/4EefNF3IVjWl2MnkXLu5jHGLPk3Jrz+CIa6Wg1k146vUKtVlJTmIa1X4OLvihgph7bu5faDB4hrLdHp6mgf4cPL2kTu//oLQ0cMJ77+GmvGDce/pTudQz8hIesVKz5bxKrV61m4eS9hHlL2P7kL1lbsfvKO7bdSqPbwISEhFTuVmGaRHLG6jrevKhgUMYwWNVJUz5KolhjRxnUY48Z0Zf+BBL5YOJjB0f14ciGRcrUXP5/ZghvWbN05hcKKQq6cusrw3kEsXjSHOas/YceyQ0ycuw03M1eMAgz4+tRFciQKpLZGuPj3J6ekkKz6B0wMtaXzYF9++vkcQpUQqdaQ1MJszIw8kdoXs3L7ViJ7dmZKoC9LFyxixhfzaIoRoc1won/PIdy6k8GUBVtIy9Oyc0UeLkat8DbrjmdYMaWvUwnv3pGQqAhSi8r59ccExCbufL7tKgtXraAmqxa5gxfvmkvQW7qiMdRydW8MVakazETZDO7bn11HThGf9prchBqGRXegSh9NF69PWLFsBBJjB3p5+JGtkfMk/gJXbt3Awy6CW2fSOZd0DtcxQ7A3ssE1yIGT6zdzMuU5Zt46JozewPXr32Ji1QO1Wsb+XYtwFERSWviU45eOM2j4RJzMtPSY3weNmZYla5Zj2xTMrKkzeV8XQr/WKzj9226UdVJ0WhFzvtrFzpXfse2nvbTp1BeBupry3GzmfvEt5cZGjPKxRmxeSXFmHdNn98Ej2obG3DqGTx/IsWOHeXz5HgpROQMWHsI6pwqBvRilzogWLSKYPySER6nryH59H0tXL+7dvcyVWy9Y8N0UALp3k+ATHMEPu/847WqpIpF4CqikGjGBBNACUxYyHi21KDDGDAdKSSWRfx88/6+dgEAgMAUuAF/q9foG4GfABwgFSoHt/62uj/pmCgSCVwKB4JWspg4X2xC8vO159NyQ7d9cAuEwrryp5kLMO6InDOf7PftY0vtzQsdFs2RyH8ytvCirs6VFywHgXkmrcGeux3zAgB8d9XcAhU17RwNw6uQepOblNDalMX/dQvKKn3L9dgYpmc34tpZSVtpMtNAXTZmWqpzXDJrQn+9OH2LuoG3IHF2Z/clGUjMfkJuZzcB5o1GKlUybM4onFQqy9v3C2R8vEh7ljru7CbkvnpIVW8GMwVPo1XUE5XViTh+JYfrulbR0cGTZxpPE3Y5n78WD3Nt7mRnrxyNtFLFj7yF6zRhDzokfkYpBXVLK0H498PAOwj7MjhatBzJryXiUehMOXD7J1J6jWf7DHAZOmoC72oAVPSfh7exJqUzF+BEbiGo3gq+TVLg5haFMyeJlSg0JcYUMGzAJR62IHV8940VMKpsez+GFh4rNN68iE6pw8W1FXWkV6jBbajNMqVXX0aCuY/cPc2lU6tlxYCGzOh9EbiPDRmjMuyfp3L54lHkjRvIs9T5jPu3A0k0LSY2R421lhI2RMxER/lhHh5OWVoS7nwlXXr3lqzNf8+XmMbi3bkGPIa3YvGkSW+YPR+JgyrSJP6Olii17L1L7tpF6VSmvC7J5X/KC2Wu/IcqhNZUHEihLN6WypIrLSS8wEFkQGGKMTl9Br75rGTEtglWLv2bE5E95XfeO6oZqPhncnR8OLiGjoY62wd1QNgm4uPEnit7lsu/ALmITNxObc56KCh0dIsbi6NCDorIy8kprOXPiCK2Do2gqykTgasOvd0+TlZiK2NucQyvWc2DxRgyTbNm98ib5BRoKKmNpaRzJs3uvUaULefHqMVeePiDK1Z6t32/mu92rWPnLXWRNjvTtOoOu7boyePgIcnPyGND7E7wiDWkyl/Lk9UMamv9IPqpAyR0KCMGPIUwgg1J2sQdngviWpbjhQDKvKEdEAbf+7V78r5yAQCAw4IMDOKnX6y8C6PX6cr1er9Xr9TrgAH8c+YsBtz9Nd/3Y9xfR6/X79Xp9O71e305qacTJB79QXwoWIeaYz7Djjkc8k0dOJGKcIYumTWXRbF8CfCOZO2YSzqM70Np7LA3uLbmadAkjI2+CzAeRVPSQqV+Gog+wpvcEd9w7/WEvKfPDj2ep9KZ7h3BCvcaz59T3SDSe3Lx+C7PUVKTiaByDSsgJtuDIidskl5WgMzPC1riGRdNHkvI0kZn7FmKr0tIlchQLt5/j4E8byM99j6XECYGBBcMGR2DcUEuzqQhrQ0McDCw5fvE0cfdOEX+pgOHjB7IneDaXYq6SJSgg1FnIvHWDaPTw5ef1PzK8dVcWT11F9v6HjB31GZ937MqT3DpElSKiP2lDmbIMXz8PerZrwdlP5lBbGcuM3fPYvmg/mYXF1Nop+ebcFixq6/G38qasNgE7Ew9iDp/ATith2ewJLO7bkU0/TGKAdyRt+3bj5Yv9TBgbzJrQNgRE+1L9OJeZw8YQe+MpyFWUXs5ky8PvcfQNQS1TUOvpzZFHW9m/5QLN2nTKS5qRmnuQkPGcZSt20mP8QJLycugU5IeRvQKpTIXCUUW1/AVhXSbzPrMY72BTPNwjSHoQR6RnO1ZPPkB5QS7hPaMpyE5n1rT5LNo4j6rGbATYo7BUMWXlNNIzU9j/63AuJJRz/t4RVi79gYEbN/DVDz/z6YRvGTqiK15mngiNPXh75Ud0iWk0qgSEDGvg+PEDtGkZyq51BaisLBk/cgoXTu9g2JhxGAssKKtMY8gn4Ry+dJlh3WYyu8tkhMZ6rD0M8OuuJOnqPjoMs8Ta3pdN8z7h0uU88t4+ZMb0udw8HIfEPJjl323g2uv9DBjTllCnRgQ1TThbRaL2KmZt34GM37QHeX0tuvoqesz6HIVGxZIv9/L8zA1KY8+y/9wBXldrufXrK3T1eezevYW8+Gas3G1xoyVPnv6RYpxCBW94Slvc0SOkiBwiGYMzdiShJ4p2HOI4etLY+C8FTP9PTkAgEAiAX4B0vV7//Z/6nf702jD4vVriCjBWIBAYCgQCL8APePGfbGjUOhS1ORg5WfHs2X3EzVoclE3cf5ZM726jOBt7G62lISNHjEVZaYTIoBmfID/izmyjoq4Cv4BWGFt7oDOwwCsqiCZJIRpjARrJHzaiAtqz4+pKNm46zpB5SzApl2Nn4k521kvSkp/zSFnN08tXqVM2cuO3V0yaEEbV+zccWf0zLR2D8OkQhMjOjNLKCpJyqxk9fA69p0Rx81kOlaUKHt+/g5urEHFzESoTHSJja6zsdUQHd6TkwVNCXXzRiXQ0F5fiFRmOnVxCn1YtKdDLSE1IwsWnBV99P5e3infsfHqWoVPnM2/ZfrzdQkh4nsKDh/GE+vniau/IqrWrcWsTRv/IdnTv1YtqrZqb705johGjTajH1Kctnu27k/gmgcuPziBuSqcs6x6zFiyn+7TFjFq0ivcvniEJ7URjfj7P0y2R2vqjtelI6s0EvEK90KGjR/cuGDt7M3nUWB5e/Q1VcyPmZu7IG3JRNZdy8MRBNA2pONoZcP/RTYQaLSqFFYnvkunuE8TpmMcYSxtwCfGirqSW/8PcW0ZXea773r+ZzNiccXd3gyAJmkAghKDFKU4LFPdSoECBUqBQrEgpFHfXAIGgSSCEJIS4u7tPTeb5sPZZe61z9j7jfc8Y7zt6fXqee4znuT/9/rdc1mNgOHsurqUmIwV3S2eeX4wm6moslTm5dKkJeX8uHrmWOnPmfI+FuZjol1H8uGcH89Yv5dTBxySmx4OmBZ/vwabFO5G1q9G/hz+xGTF8SU9C9j6JMmUzh46ewcykk8cJRZQXf6FLKUEh0+TS4QtYWthw4thMSnOqKGvopKXBhO2rv8NIzQFjt/7Y2zji6tLOh4QbSI0zkaU14epqiaW+HrkvXtIkESDXbsJE15Jjp4+T8zkZsb0cSzs9ZHJN5I1CspqqSCy+R5e+I01dHXSr52DcJmTcOi9qC9MRyGqpE9bi2dsEA6GIIF9bBg9zRSJVw8zcCC2dWtq7y1GvlXP/1GsAqstr0LFQA+V/BhRdYR8C1MmlG2OcaeQLLziHNro08xZtBMhRUUAt1f8Sjfj/WgSAgcBsIPR/cQfuEwgEaQKBIBUYCqwBUKlUGcBNIBN4BixTqVRd/6cJVF1KzDRt8PZ2Q1/hispIDzuBAZ69vFCWC9CQV+IbOpwOcyH6ZiICevWloDibDQe2oiuRUlaRg7q+NsadYipfpDBkcG866jvxcLf45xw9AzxYPfYfhRXaWhrRUzdAq1uGoNOeI3/uIyUrjgg/N4xNdOkV5IyVgx+Llx1AKuygvKEUgU4zmmrdOFvZc/N2FPM3jiHu2hPkMi2+pOehqaZBIeoEumqjVq9CWw2kom6mr9rE3nO3URlpcvr2br4eM4ftm5cSunQZtiIz3NzNmekbzqvEB7hbeRH1KgZvI29sfP0x7G7EuPcMaiWFdNsY0d4lQdfUEvWKOuI+vabAAprq2shLSsTU2pLXD+7h6dgXbT0HHJz7oKipYerIGXg4hWDr6kH6u7NcubybSfPWMnzq1/y4cQEpr5+QfHM/yUkZFJVkMnL4bL7fNwlNlRodQiUJCVnUVatRlpRNfVMZApUAIyMjhngHcuXKDSw8B2ElMsdC04v2Rn2qyip4ev0shhJNGhVtmBqaY+6pTVNxFUXdNnhZmhD6bW/kWp1UVNejKVFS152BshN0dEQU5yQhcaijILuFpGcZSCuaSf18Hj0NH9qzTXFSM6atEPLKPyOVFXLy8l068lPJ//ySxk4J8vIGlm/YyNZV++jXN5g5W4+TWVhHd14TDvYhaAkMKJUlYCAtw9fVB1VdIQITDaQCJUkVSbRXNePrOZyps1ezacM5xk0dy4xpy7HWG4CWixXaarq0tEsxdujJwNAwejp54NRDGxkierh609amQL/Lim07ItFQWeGoaQmd1bgYQ0F3A1lZaeiodNEW9yAh/i0hA8IQtFTSd0w4ckkLhsYWNLcp0TbRwdbHgZmLnQDQkmkQkxnDy0f/2XXLFmcMMeZPTlLHR8IYiht2rGMNupjykXvooI0+6nwh5v9eBFQqVaxKpRKoVCr/f3UHqlSq2SqVyu8/xsepVKqqf/nmF5VK5aJSqTxUKtXT/9P/AdRRITdzJS7lFcHhQ3i2/TE//nGYXuMHkxIpYui0sZjbuZLYmIqdWje7d23n2PGTvEy9h7pAjbS4anwsXXDwNMM8qC/njz0kwMsKR71/eCb3XlvG2hVLOHthDUdO/0D6u2jK21sxMNDDq7eK8bauzFwzjWtP0qlMqkWs1UWjrpDLp8/wzdh1iExNiQjfyNv3D3l37iSHbp5k04LvifCZQNiYkRwKsiVAuxttTTX0XS3pF9GfGSOnUFrohLmihtjDe0n82MYgKxNW79+JRqMhcUnZSPqHc/PxZ2xmBaNV20R2VhKO4X0x6u5G3lXD0j9OMHvqAFZP+4bz0c8pSW/ApqOFVb/cJD7+M2kd8XS+eczM0TN4cexPlq7+leUHf0XyKZfrn98yZ90u3sU+oaKjjFPHT+E25FsWz1xJhKsGR368S1VqBbElbTjpWaCvJ6L29ReGDQ7hzbZLpOUnkpdbSrtaB0/iM1AVmmJu5UJnTS0n5+/l2o4EJoSMICG3iqqMAgqiXtOZ0kJqcip+wz1wdLBlVsRw+loEcO7XT9RW2lCTcQOpqoF7hzOhy4FuoYqS5g5OHr7G3G9mIm2RkHA1ibLKEhwDdJi/LgQ3Rz0WLp3Pmr0BzO7nRlVHJxG/jqKroQwft17I5W2sn7OHvjO+wW/wKIzkPenX24XU3Bounj7CgMF9aMi5zaaJx1j1a19yi1MJ7eqP0tib53G3KO1Mxt3NnmHOk+hlFoTI0AaloRH6xj2YOmU906bPQSFowNbNGbf+/ni4W3Jz6Vn0FHK2fr+Zyw+fExo0jD3nplCvyuK7CavIy5fw9EIuBz79hkqhy64VOznRmMKZ7am0SAp49TgTe20Lyj9IqWmt4mFCLh7ZJZia6/LhVSHSWgmdze3Epr4kvbQSgPgnTbiJzbD3/09utLFjAP6oyOYsUSziN8axnv0cYDhBTGUz0dxBhYBKKv/vReD/DzPQMSUnJxZZYglmqk5cx49DYaBFbfI7/jz5KzkFH1CTq5Ow/wKBY/qhJ+vE1qaM479H4+I+HA0NA24XPeRSVApHj15m3pTRdBe1MnL4NLYcGY+fizsDJwdi5SkgIf0uzTIpY1d8hUxbxqiwqegEmHPnRgwLR/XDSMeSgFGDeHDkCk0dOex/fpf6vGyq79zAvF1Ih58ZwspWXr6JY+yBrbj2cmX+2TcU6Goz3qSRRwcTGehpxEQXPaZpdlFT387i2E8s6G3CiWtnWbp9Id/tOs2i3QdIStvNoOCBHF1zlAEjxqIu1Ke6uoKEikxu3LrPh4xYAgcNJrO5Ehtbc0wsNGnVcyIqcgvzxy1EINVAz9WXssZOvMPDuPB4Cy218KY+ltEBEWw7t44OXSnJT69h0suX+JcnefPuKfpOhnTWNWEqUcMnwJ21F+4Q1C8Mu6kb8XBxZdi6kyQpPzB41FCmhvTj8/NHNFfmk/v+Bf4eHsQkfWbYpJ6Y22qy95eDVDQ6sv/6G4w0tKjIKObRw0zimooZHLCGvA8KaruaKMzJpzylCX2RDTt//4rBAYMozH+LQKiBPLOb1VsWYSLRZsuaNUzSDGVy2E4GurjgH76AD7nnqP+sz53GG8SnZSD/qE2tUMacsZMZMqQ37zMfcD1uP2IvE9JL3mFmokn2m0esHGePb4Qdvx1/hMJOCBZdGBgZ4jJyEMMHzaY0NxIX9wCUsnY8PYZz4PgKvlS8RkPHlvz8SnKunCSpqYiGfCXzx60kNHg1reoaBA6xY/2ybXTJ84k8/R4DE180SjSQtGjzKOoEPcv1kXZ1oazJx9TKGFPzqYz3H8ec6cvIzXhKeVEFQfP7MyAsmKt37hM6PBBVQE90VV6ETvdCWiJFX1cDK9kQBniOZdocdwCeXy2jNBWCx3oAUEsG17mGAHuqKWcto1nBV6TwhDya0MIDJXIMMKLrv2h3/j/tbyECbR2dCFFxYN9V3iZUYWOlgyK/laqaGhbODsXTuT8d5VJmz5pIQvwLlNIOCktU+Pjp012ri5GTPjoSKYLsAuxF7pRmV2NtbU1+WjkKDbh+MYrYyCKcbXuhK9JmYOgALu48hwHGtCiasXF35vVfyTR0SqlStHLj2DVMNMxR69Kh5nky3qE+qKxaGblpO91VTeTryokvrufciydcvBLFpuNHmDX3OzR07Vgzw47XBfm8OHOWxLIOZF1SfOy7cLQKQGUi5X1CNMMnDsMvxJSyeh2e3o1m3Y8b+JyQRFp6Dt0CY7KLyrEUmdIukdKuaOdzfjKKxk76RUSgUhbSld9CYJ9pWOr3Ilnair/7YGri4zFTiVEoWrDIbeHw9d8QFLdQWV6DhYYBYmk17bXVqBnZ061dwbF9qwkdO4LmRi0+vn9L3IeP3Dm/l+y8N+SfOc7xZfsQ+xfhPMwGFy0lAl0hHZUGDAoIprW7CqMqJcNCJ6Bb3MCxA0uYFDyEtm4ZO9auovRzI8amhjTUfqRfeChiNUPkGuV0vayn4GQShdlpjBvvSruGC30CbXnz6AJN8ma+OXiAi6+TmLRuN5t/3MSzw/dYPm0yqg51tHRMmdZ7IjePHObKrRu0d3ZQUlPJYHcdPNwHUp9VxMsPT3Fx7UNJTgVSKaiZCOjRz536ukKSkvIwNzbBW+zN4nXHefs5hUZZBw1VRRy7dIib746y+YcbmIsMKCrPpEu7m1U/HOHQ3n34+fmRU5yFja0OpblpLP3uBzKKP2NkZ46uri7vPr+mW0sXXztPiuqq6DfhWyo7JRTHvMPaoz8Hf1tA2vtatA30KM6VcvLub6Rnv0TfQQ8rPV2uHJmCmTyHkoRCYp4nIlHUYqgnpl0i5Y+Dt9Fo0/k3Xt49+keszFi+oZ56nnGfBtRYwwVWsR5b/NClE1t0aaCdJsoRYPBfoQeA+vbt2/+/5Pv/kW36cd328B6OnH15g04NGWL7Do4tPsTmyIvkZmfS2F7P47e3kYoKGDsmhJSMTjqlTcgaYPCAITw9+hBnH3t+vxiJfw8t+ribMn75L1QW1YCojozoFCQNzYydPwtZYR0Zea/ZuPEUB26uw9hGn9SnWfzyUzDmWj5U61ZgauxFbkkGMY/KKNQuJ+rRWyaFD2Ln+u1oqWnTfOotCnklCWdfUKF6i7ljHfnlMSgt3cnFkZisdOZt246PnhoH8z7SqlDHTd+QmMpqfpo9l4JaCXWdKZgb6PL79jdEZ+5hfvgqBCIBQfpGrJ23i0xJAVFPb/PdpK2klr1Ao1NCf10VnjYB+IxaiI+nMY52Xmwauw1jtyoCQhdTUfWG0D7TMRkymOnDx5H18hXu/Z1pNpQTl1WFoLiF7LybjDXsQ5FQg47UVCx9reirUcnFFzEURF5lyeY/2HT0KhtnpBPW/wavKm7TYVFJ2LjRaKiqMbPTQVYrIq6iHCcDTXIk7ZRnJnL07FZ6TJrLoZs/MXZIDzo0tZBWJ3Lu5GV+OL+X3s7u/Lb/ZworXuKk0CRwgDVvjx1FbmFLXs576loF7Nmynvcfskh+cYbPhfFMmTeeGvV2eg6fQE5qPKmp6TgMMSH93XsyGtORNAgwHWZCZ5kFMyd8y+LN2xnStx/N0kyERlrkyQ3p5dgPKztNmko/oOeqyRCvRXgOcODJl21otppxbX8il+OP8/ziK7KykpGqmpgeMpeYj6U8SjvIhLlzqTRtYe7EoRSU16Im1eP+lfPcuBqDhpYxr97GYO2gg56WAb18Azm99zqzf97PtBH9MHPTwEphwIPnH+jjbYFdgCNlJfl8KSlCWt6GjlyNiqIm/Acacvh2NBq+xiybu5AB/r68/XSfO1czAJg4vYaL/EgPYignmfN44c4ubuNDIakc5y7b6aKJWdzgMb4MxhADtDCgk4vUIWI447i740XV9u3bT/2v/P0tdgJisRAbQ33aqwV0qyRUxTeRJq0kzEWOlrYz8gYlYrERasZWVHS009RYikwiRaVSMXpsKJt37iUrPQvvAXo0NrVwIzmWdw8fER8ViaWVN0Mi+mNlb8z7d2dIzc1FbmRIZnoFXjbh5JZVYefoQ3RcJVdjYxBUCHnx9DkR4925lXeHiqhIxMJWTp1+T22+Gg465ix5d5CO/AZsNOT0CvQk6vYbxI5a6Fp48O5DOkJDISFTVtJzUhhioRqWMneUPdyp7WrBwq8vf1z9k4ZmOepiEQ8+XMVIbET/IkHxAAAgAElEQVR0RjJCS0uce42lsL6A5KxUbK37ENN4DWG7GGfTPny95g7+Izdw+NBm4t/noZJo4e5rTNjQIaiMTWiWl1JYn0ZlZjq5SXEM8Q2nvtKC6JfPcAywoUC7kC6ZETV2PjyLSiFP1IG8S0JDtzGm+pY0CcQoW1o58N08zKzcsXfU4eTGGBzNvXmW8pSOJiVFOV/ILqpCZFFAcbWEqROnY2nrh1QI3VI55loqcqsk3L2WQEZJAb16jWGgQoWL5QBevn+AtaaCZrEQa+1Meo6exer1Bxg6cRYpGW+x7tDCSASRH58x+eeluAd4MWH4NxS8/cA3G2eRGC0n7mwUQX1D6KxvZ/lPyymv68LQ1pjz95+zfNIsWtur0NCW4aQRxN3jz6hqK6C5zoLSxlLqKprQFBrTLNdCT1uftrwychrSsBZp4Gc3mDEjR6KuKcbJtz8pb94xKDyM3UsOkXElhqCvBmFhZsSPy/fw3Zqf+WXnNFJSXnD/4T2+fMpGIGwhL13BuPAZVLbWMm2CH5UV2Uye9Bsf3xQSl5yCoYU+JcoyiooSEenr8Cn+JUb9nTh88CQqU3f09WwprqwkN+M2Mtm/NxC1wYe9LKSIJ6xkNQXEoKCLzfzJtJ//ERCnjRmeeHCTM3RjgIQkQtmBEg2q/yMh6b+yv8VOYMdvP213622Pl48dRoammIjruHz2FldOplKuzMPW1ZYvOXl0V3Th7e7N57g8zAxMEWjK6D9oKDpWXty+doHJg0KZOGElBg1JOIZPws7GnT9PncEhtCdrvv0JsVgfGystevsOoa02gbjMTNpKshkeOoioF8/QdBWR8qkceycblFIQNafzKi2VIa4D2LF2PJbmCjYdfcnKAWFomwnRDVHD3tyW9x8q0Nd0wNbGnegXMaz4bgt7ervxMLWMTvUOvNU7EHn2oiGzlIy7yegaqVGe2IafkzFif2cOLT9Jbu5jdm/ah0IF9bJ0xvmNYuSMVRzduZqqTjl19TJU6XEoZVX4a1myf/sazD28GTXHnRunnvDxyzO2Tv6DnNgYjJ318HcPQWSjx5UvJzi15T7nzx1AKVWSWlWNh6SGJfuv8PHJR/IKU+jloIPAy4matiImjluL2NyY+WO3sfCHw7jotjA1bAl+/v6cuHiC5NwUUr4kcOzXW3SmP+bEuUfsnz6dHOypqk6in7I3zu6mmMiLEGn5UJAXh6WGDiWqdJbuOMPDe29Qt3FAX30IToFCKpSt6Ni6MCxwApO++QrrEHvENfWE9VvMzbN/cffTeb4e9QPRe3Yybs/X5FfmY2htjKeLPTOGrUFV1Uq7ehEf357F1sELAyd9Hpx/yq97rvMm8wylCVl8aZRhZqrA1ccedUNbqlrbaK59yZI55zl2/SAW5gbsWHcOTf1MsiuqCe83n+jqQ+Q1vGfaiKl0d7eT8SkXfR1X1JXVJL5Jok1cT3t1HVNmjOfblREU5zRS0ZLDmvWHGDqvD7PCRXSZinFy68c3W9fw8shzumxl2LSZsOLrNTTld7Pj4Dl8bJrRVLri2FFNfOUbgnx7svrSTZYtXMedl4aEBvwjYc6ZOzzDl/kcAuAGnlhTiCepTAn5x6XfdbRI5iE7WE0x3URylg8kYYQRs5nLkR2n/747AYEc4j7EUNVRgGN3B1ND17N43WxSymKxNTJh0MBheJtbMsArkJT4F/T0HYGBs4hgBw9uXnpLB00c33UdmamKo6e+Z9vuLwwy8CHt42fmR0xCrSqNow+WIu1UY1DgCApbG0gtLUZblouepRstBhog0uHTrTRWbJ6Mhm4OLcWpnDwRy6NbxQhtApBndhFdoI1ApWL8xJF0CvXoPciJHEUXPgHG/LrrDLUVJSi0JfywewOfjfSJa6mmLa+ZvoEzOPv9BtTaKpCZluNoqM7SjfsoEtVwdNVmrHt2MXhQGKWFCiz0xLx+EUu7UM7uwztRqQupTq7Dw7aG/uET+W7bdgauXEydTIRcJwqnFicivM0xsRRh7BeKRAmPT9yhXlLImeh7uOmbcu7eKUpTO7GulRN1N4phS/excd4kqqqzcfJzpKQ0F7FChlRYB10C1n4/AUNPN8pbsxC7ezPzzAxePIqml5sjD34vpYenKTX5sdgPW8Hqzbt4JjVAqyENLSNPvvtzPTFv7vDX+zw2n/gdM8+eDP1pFZraDiS2fMYpQJ3ff3uIjU8QeuI+XL25nshFa3i6/TgD+g4l9lUGJSodwkIDWLZtNy0JSpxNhCz85TK3fruETqM+DdJWkhJTMbVIpVHURVlzEd2G+swesYVV32yj/5gQqhRZWDt5ILT3p4e9HE11IUZifQrSiyireopKoIVK2wBV5icape1Ymthhrjae6u5Kdt1ZzME5UXwT8hdNxtYEDZzAyEkL2PfLCuzCtDD21aa+rI3aSl12Lwlm5be/YuNmxKuoOEqb63iy8yqz1z1HTU1FQ7ucq/d/oe+PffD2cqFF1MCwaat5nPSOn1b1ZMWun9H3MOPbHdE06yqJSn5FH3sxuflJ/Dz/H3Uv66ingXJ2cfGfzPQgkK+4DEDQQkMAdFCnPz0wph8iOmmjmzJKaKWd9yT+7+D9h/0tREBDoImTtTmKNhliS29+Ov4HBWmpWDl4kZwaT1pWNvr6+qzcvJxQ94G4u9rx5k0BEyZMxkhkyI37uymvKaesqBAfHys+5MfzriOTfqN6MXLxd2R/yqCjup6Xb5/RqK1i757NlJUY0ixtJUDahbSsBidDGxyD9XgQeRtVuw4bZsxgmIEFV6P34zLIlyZnN17ff4VSoMa8yfNIKcqiQ6pLxud4fDynMG3CdC5sv0JXcRM9DDWxUmvFycGGPqNGolDEoSM252VmOTkNnfyw8Rr+PV3RE1vhM9wcHbEuKFRMWTGNTrGc0BHf8vn9J7pqknB1M0Nf0IWqyR+b3r1Y5TeIxgoptkFOWHt6UqQmpbixGfXGVq4knMLPzoHwOcvQ7egg8cML2iXt2OgaIVVrZNnPC8j78IGEmEfoy7ow1hahrStAommCRMOQ2ro20IRgYz++XbWUL7lFaNgboivoYtbykdTWSkGjjogR81E265Icc5BhfTxwdrQlYOhI9u2azrKh7uQkVKHfDst2ryBslCMBVv6YOgh4deIerbVGCBRCTB2saMgrQ9DWjWhgKCuP7sXOzoLkWx+w8XHEUs+ENwkJJJan0WvIREyN7Qhz703fAb3Izq7E23cgx49F8+VLHE2SdrTEHZR1ZNA/3IyrF25Tnd+MQKcR7Zxk3j/NQs9ME4WGKQNcXFBX00BOK1KtSga5mNNRJUFTU0GVsBpdNXUqUuroFMj5mJVAdUYmkc//5M2jD8xa/g0KhYJGZRH27raotBWg5452gxRfmz4sXjyfx0nPqW2vY/3GcXSp2hEoxXy4+wK1LhG5ubUM6z+WK6c3sXjSbCKGTqe6owQXHQsiny+nJhVaK2QYWeuze97df/Iho508qqinjDYkAKTyhcMsBuDj6Wa2Mpk0cnDGkQpqUaFAGwOkVCICtDD5b/n7exwHftq+XWwPbr69QGiMnacJVtYmhPWYT5tUk5SXl6kVtlFankVa2Rd8fTwpeFXLm8a3DHAaSW7uc0LDpjN6zNdINDV4EHeAkupoSsuqEMgraZCZYWRnR0NbGqOCp1JfK+SbeWtAtxfNqiYy8pMZP2wOkceeEPv8EyJdQyztw3hw6QG3Yl5xac9lXtw5zp/XI1FT1LH3u03suHuShpJEKorrqH/fwMK941i48Dv+PHoPhZYKg96BiF9lc3nPSVx0rHmVWs7miL6YGw/BsLuSwq5y3vx5jW1bD2Hb6s71vGeEe2rzIekz+vqdGNdZMHx8OHnvOhjsrU2dgYSX9/9iwcnTJOck42XZTXpNCqV1crQsA9m59BLHV/TDYNgGAnv3ISJsCjJzS4TaHQhstenrH86rqFiOPbpLblo84fY+4NeKhZGculwpCydvJvruK8rbPyF0sMKvVzDLZi/g+5mLsC5XYKKux8vM97wvzUBcn49U2MCZW2W0GXbRefcQXx7c4fDZdEwlTZgO/4bMqlfsWXCMA/d24qTmyu+3L/HXL5cRmgmJvnSGNnUlRUmFmDtMJFXyB0MGz+XJb3/xIHI6xkbuPE99gLbQhqqOIm6cXYCOsy6TV+8m6XESRvomPLxyGf+IcBaHT6FVIcVI248/D+xl6MCvqW7LwVSjmcqmRlaPX8ytZ/FM/EqHjpZO7kdfY96kLWSkP2akcx+Ch//AzQ+XKCjrpKulnfKOHIZbenLr5TskHTW0VzayetMCutQaqGjKoOhtBloWpqyfPZ9tM9ex+8Rhxvdzwi5oOM+j79PbRcya7d8SMngMUlUrtgYBqFuZ8CnzET8vOUhCTCTNVbVkd1Vg4dyLhqJ0WkXmZL97h5ufK0L9ZuYNPU50gg23ouTsXiUjJ+Ykiyb8ThyjieQkEtYzg1X0+5fVPZRMQsnAiXc4cJEudpDEa2SUI6eKVrSI25H49z0OiERa9OgbhJq6Ns3SGpSdagj0VNyNOklXuxxzRxG9uh1BTUlzDXQITQga2wdDsQ4Pr55F3VCLvIbPKBQiSr6k053ZRsE7FeX5VSR+iqGpOgtTPS3Uu+vZsecXqsrqmb1qEk/uHeV5Yjrq8i4a1GvRdOoiu0IdQ20VvW1b2DQngGCxiJSKJMz9zWnMj0Ku3sma6/d4+eQZvv1HU1vWRk5uLUd+uUOHngHnIy/QVa3kzYM4Fv5+k2kTA/iQ105xaxH9flhO7L7DxDx8jrSjnO9X7CAn9Qv1Kbn061DH1aAH3ZIushOzCRs7HXlFEf3CejFi1RYEDe1oiT1Rtqpw8fQhJjKS9uJ2JJ1NPHh6mKSccyTnF3Dm1T6O7j6IubUVPXxtKMnKpL1OiqSzGzd/HwrTqzG3d+Hr4z9hKDTCSOXKp+pm1K10MTZypKK0gRHBo7l78A8unL+KyridntNnIxfo0CxpwkLeTW93d+I/5rFyYhBFSfmcivqIsbs3v+6ZxobLl1i3bBENFW2YeJuj29HJuLkTEbQLObngW44v34imnj8yZRZ9g3vwdMePaLRoU9veSlT6HQztrXidnoSZqSuWQjMa6puok8lQx4Dctmfom+hibKVB75BepKWnkJOfR3FeBoZCayLGBtLalE1rhYKIoClkl0gRe3ribG5LC+oU10ix1xqMRF0LoUCTqMJEvj32PQITA149vk7oiIlUt9bTy9yOa3/eRyCTInmXw9njkRSUF6FCBx1TY9If5iAx8iW7sxojkTcY26GFAQMHz0AuNmGsVxC3o37DysKIdjV1qjrkZD4q5+6nS8hb9amor0LUpeLUyQ0YaznQUl2DrEubjXO306lQ43NaLLHvLvHpXT0uw20pFogACGM46zmE4F/6Gn7k2H/JlD99aCYPCRroYstHHv+3/P0tREClBW/uxhL5/Dm5mdGsH7OO+qRGTpy6RGr1U/z6zKe6RUhnvQFDQifj59MDn97uFEU1sufnYUgbVRxau42rcWtprtZiwbQl2OjXY2aoRkFmMQIbNUozM5j6bQJudg4YWuYyKdyMIU5ilFVFOLj4U5wehX6XLX9t+oo7idEcfXCSDHkFtv39eH/vKPt+2I5QR0pWWwMzNgwnueY26t2GjF+4ivTyHJ5ee46ZwhS5qpUPORkEi03xsdVHJ8gLF29DXPrrkPIhnf7bpxK0aCTKkmx+PfKMlJRXjF65nkWb/iJi8jQG+Phh5eaEmqUYZ7fJ9B8+HlFxHR5Tg1m5YhyxSXFkZZSx99cb9PYfzcePL1BJmyk2yqWm3ZVebT0ImTaIs68OYWLggJmxM7LuZgYFhnLx/B32/rQNz97+HLi8E12RGeNnHCQwVJ8PcX9w8OBuDu66g8rKko3HzrFs2VDmrllA7PXjuPrZ0V4rpn/IQNz6z8LBywixsxNBQ0by+4vnpGYWU9omx9LJlIWrZhP9JoGDOxbhMLAXOV/ikEk0SNRN48r7L7TpyjBuNqay7jEr7m9jQb9+SIQQuGACU7YdIac4i7DwUMztBexdfhgNqTbJLz+zPGgxIdMmcvfMFdobNNFPSeR21HPOb72HnpERX4UvJmToOIIHO2Hh0QvrbiFLFm2nWl7MqmnR1DZXEjFhNq3SSgYELcBSryf9fD3R6Cpn+887sBWZo9umz85rn7i/dw5r5u3FY3xPmqsK0dEyxFFsRmNrNSMX+rBnzyxO37zH2K++xjYwHGMjc/RU5ly/dAG5iy9RSw5SWdVKu7QWQ61m7P10efr7flRNaeQUaZCdXYWxujWJcbEMHNib/LYMjCxCSfpSjKZ1GuUlbVgZOUG3gJqOf9zsh40xBSCUGf9kJ4jlXPmX96fMYT8LucRW/InAi94cI57X/5bd/+/2t6g2bG9vqpoyK5yZ835iyAhffjwykNFe62hq06e25QnjQ3chVKlAoGTQyCEEDhUR5BROfnkVfYeHUJr/hK3zL/Dy416uRCfxy7JzxDw9xd77P2Nr4cmvW/ciz4Y5W+cwZ/ksRrv5cjO7gT0Lt7Fh12y2LDnA+qND8aoIZM32A9yKP8nxU1Es2hZK2XMBMRc3ETT9O17WRXH2p0R+2DWdFmUaNRI19JM7kRW0YRbcH5Vch4fvoxk+qQ8ufe0ZOWQsP+9chaWrNZmHPjD8+4msnHeMh49+QcvKmgkhy7l6dyt2uv6UKgo4eeAvQkKGMml2P9xNZpKdEMVvhw+z7aejvLp0jCXHTnH77h6m+gTzsbueft4eXLx7AneZCFMjY5wHzqegVcqJQ6uJmD+fIa5hdMu02Hrla4Jsv6M+Zinmw35ky+YfmbbBgvTYOgJ6D0NaG0te0ghmhNWj128ef+xdysEjFzh3dBfho+ZRW5BA1aN87nTKcDN344/jG/nu8ExWz5jHb4u2Yes7An07JU5BocTGvSM6KpKEZzWMW2mCFiIe/Z7L00+pGBt08vTwfrqtg1i7cRfvz80i3sOCniZuWHX0oLstmlnTfsFvjguRh/LYf3YNReVFDPSZzv1P3xPsvBFfu2YKLYQYtPgQMbAngeMG8u2y8fjq9OXtx+vcTy5g1EhvDA07sbINY2bAQtb9OYzpfb/ievpDbAT9sdLXIFmZhbqyClOpD6+zLuLnNo1lo9dx/v6vvIl7x6Jvh9JSY4uaqIsWaTlhfReQX5iCX49BuBoMQFNXjS6VErdxjgx2lLJz22siP0ex7+v1/PhgL3JpG3Wlbxgdso8tP00iPrKer8YEYNq3m0m9t6LVnk5KSRmCVCVdIy3IL3iAtcV8zpzbwpP9f5GQ38iECSv/yUiPnnq49+3i1unO/5ajz6wggKOUKSuwE9owEEda0KSTQmayhV2C7X/fasMKlYKpi9cyNMKP3r56mDja4ug2jGsp0TQ3w56rv7PnziHWHtlLv/4ODHb2wdDNEQ9fD3acPsSEsCX49LFHqTLk8fNHJH2OI6cthc7KFmKef8JQ2BcjZyMOTp2KtKGdgpZ04i/8RdiY8ZRJUrh/dStWms74r1/JiV+/w8LZm1F9w7lx7haRh3ey+deLvIt9jG1+AcruWvy9B2OgckNWUY62hjYnXj5Bw8AAAxsVOnoyStPTOLjiKnWNVQQNHEhdYxvX/njC6P5hXF61gUnTp5JXlY2gq5OU+GjuRR/B2lgfsYEB1mZ2pLeU0KhsRNrSgq5EjlFfH/yCvFBXAxtzYzRcA/mS+4HKyiQ09QUY9J6JvpMb0ppydISVDDfVJTb1BVraEmoa22lrLsdUU4Hj4AX89eACSj0JRTUNqDQlvIy+Q5DbIEIGtiDXHImXkxa6mta0yBpp0BBx/9FzzG1t6DlrNCIdCX3NNajLe4eB2JTIA1f5/vBJZq8eh5mFFS+fRpPw9jXff9WP7Iw3qJuq8emREiWGbP5lGRpqdYT3GYxFUiSXHh4hcNJ2tKMv8fL6PWTq6qw5vJOktNM0vlKw8dRUlNVFTIiYj6GeiBDLYLx8Xcj4EE9hWTq6og7evU5ATySjsb2e2jY5ijZtqqKz8HB2p6JIgraeDvIWOXll6diaWJOfUE7u52wmDfsBhawONQ0FD15F0ammSUVNHYkpb3G07MJGrKBB4o6TvzNZLSWkxH5BrNBAQyCksDSDxIIYnr07Q05lJiMGOuNqbUNXhwp3017EPrzPg6tXUGgI0TA0Q1NTm8EyY7Q09anKaCK9pQBnN1dURgNIKinkfuFHyiXZ6FnZ8svu9Tg6irhecI/K+n9vT2Zur4mhlzX+oY7/Nh7Jsn8+B3CU8uYG7IT/KLDThBQ5FYTRj5/Z/t/y97cQAQtje3atH4+1hQp5azcxp+IY/7UntspG5I0leIpKMZZpMGqEGz283ckrU6FlI6dBWIqooYXxYwbSpagmoSKfcSHjOfFiNmW1idgZDyTuQQzB4WKmbhrN4/fPGersg7f3GAb1H0Cr/ntciy14kP+anMYqYqN+pbTLG1tjT+oVUsJ9B/NXwidOPLxCp6UEP0s3BAhJyH5BbXoJtqXerPrhKN9+Nxtt91r6RgSyb8cuOhoUBPUM4ePFt1Rl5GPd0sF1niNRt2fe3n00Jemgqd7Kql0zqVFUUSGvoTolC7rqySx+xuOTj3iR+hgtHzscJwyjrD6L98kPOH9pL3qally/eJyEnC8sPb6amtp89l5cjqmdGwZ2fXDSsKQrYDDemtZkpFTxJv4cS+esQGIlw0epjbOuBvJ6BdpKfVZOXoyzjYii7HpcffzxMXJnzb4dDPIWsmztNswNNBg7LoTY5BgeXIvERFHCyB/WUVVfgLKpmYA509l+YQmHLm/ms/wh3oG1DBmlRWWJATtPr8a51oXla93oEzYYRU0rK0/+QODUKXj+vI9LPx+hS98e084AVK3q6Bl2cXzNYaavWEKfybp4Ke1QCrx4lhaLjpkWS5Yd5OjpgwyasYBx5rPJbvqCjqsCI5keg8wi0DURsWf3DgoKyymsTELLtp6GinJW/R7Gvrl32HR1D+auInT01FFpaxDsPYZumT4d7a2IdLTwNfQkOf8Ft+Ie0H+oO7N6hyPXldCZm02Id08+SZ/hERKCl5s1s74ZwZBBU8j7HMPkidsZ4vMj2rr6zPlmGK8lEnSrwcXeh6amdIyFOky//pj3GbfY//B3HnxfTJp6NeVN0Zg01TPdL4A2mRhpuwAHRxMczJ0QpTcSGb+d/sFeAISNsUCvpy0BFpZ0NTX+GzujOc4RlnJ0/z/yCWwN/+EF2MVPmGKAJkaIETOGCf8tf38LESiuKERBN5YWdti49cMjaBqDJg4kPu4NclkzRn1Ho2+tRKdVyL03N9l75BR52UXIatrR1TDAbbAv074KRimzJ7/sLY2lteQUl6OlW07km2Sc+/oiLOtkw6GTFFcXMmxsBDYDZCwfvgzfkCn0UO9LW8ZHmiUSQicNpUOijZWXLWUSGVt/jMClQI1xDn2wDxiDCj3sbDyZ1N+LRmUZlcIE1JXmtMmayXsfg5uHB82WQvRbc6iubaKHTX+2bLmEtLIQWVs12pIyXt09R2ZODpo22phau2JkKqawJJlJQ6bR1mKAtm43nZciKUyvREczj0PbIihJ08RMT43XBa95Xfacho5q9CUadEhlLJr8LdEfP/Dq2ipkbanUfcomImQJB+4sJDvmATsOr8XH1ofyHkPYsfUgCjUFJkojzj+5ztge3/HicTZBvUbhN2YQ5nqgFNlxZ/9FUlJK+OXYbnI6avHo/xVbto5GURxJUnEBptZ9mbt0NSMHjEDc0YNpbqcRdw5HrD6egODxFFTmsmHTdVzMHVnr6EZqXA7Shy38dP4Ch6/MZfLGr1i6ujeL9r3k0FB3WnJzWTB/NdamLuiquSC3M8In2JjS6LsYd5Rx4XM0v27ZQWlxHb59Qsj7WEZtXR03H0fi7OtLdlo+hy+c4eqH9dzeFo+uhjdrx/1CcPh4fF2cyX+Xw9zgbfgO9SM1K4pJgatokbbSP8CdEJfBDA6ciJOrFZP7DUFfx5s84rh45hi63Qa49rfk4vVLzBwxmq0/r2R26GgmL3XC01zEqb+W02fYONpkLZj2VCPy/io2H97A9XW72TzlDWV0EmTtTFl6G49P/0lrUyOHd47EzskGLStjsswrqHkXg9jEC22RFk1SLW49zQK1diJGTeTYyROo6/iwqtcAZApbQpYPY9vFr/+Nn2eLYlnx/b/3QcwhnnfkUEE5B4niMff+W/7+FiJgYmSCgbiLJdu/R9dJm8f7L1GW1I1EUkO9wITXZ66i1NHhr2M3SIytwc5AxOW9RxEaKilpLsFX24sGaSefLmwmKKw/29cfwt+4B1rtmnQrCmjMq2fivLmcvLWPoeNm8fT6Y1LelKGwFaFlqYu5mQ77f36HUClE36CJOzfOUltfwsxhfnzVdzzuQ934anwY3y7ezYY9k2lQ1hA850dOn35GVUsRgSuakReloyH1oGef0RhVy3H62ob1v+7EDhnXc5KxxYnIknhu533Bbt44HNV80JR0U5vWQnZqEeXo4eApJnBgCJ3ocD4mg6qadEzb1NExEnHm5XvcbANISXzO7NmbcRF30YE9ai32fMp9QF/bPoTMPcXuixeZv2YlAyNsGGfvjp1vMB5hAyj98oKbV9cTfXE/I0aMJMI9DNSk9BkWTHtLJe8jb1FRUExOdgFHLr2jW2BI0Ogx2Lg6UV5RgJFZKwl5lqgknZx79ZHKyg8M692bnsFuiEwaaK2pZZBPH9yVxkzbMpuxngPY/sckpk89z9Q/DnLs/F98+JLG0+uHUOsQs2HyPt6/LKO6rZiBc4/TXPiMsFmL0TZWw1rfltJ3j3kff5fw8TOZtHkpjVH3SW7JYlT4Nxz64wShEyPYumovMxZ/TXZqPBqabeR8eI6gbCAXXx/j8YUXHLyyCD09W5QtNXw9eQpXX/1AYkoqeTVtJBbexFRuROM7PF8AACAASURBVIdSQmdXF8EDQ7nz9i2ymhpeFpfz9HUUw4dNIeFdCZsPHGXD13vo6yWkX2AoTgHuHFxyB/c+PTi98xVSrWoEygJGuEfQe0w4/Xxm893ICex/8BPmXTpcv3Wefb/vpKBJxt03F5kxdC0pTVGsmLEJD4eJSAVatFZXMHPaXIa5jmfGN99gZx1Mpc5dpIpU3n/OwNBQyPP4B8jqqnHVCf4nO7OPm7Nm+Mr/jSm3/0gY+p/BwqVN/1txr3/a3yJOYOOGDduX7vqGyz/dYstv/bAJdCZi5DxEBqZ0VSYyyEOTLpE1rVWp2Pib4Gbrg6FrN6IWMTO/6UN9uyklzzOQeaijKzJigONI2iSVDJ49hbu3ThMxejqWAiuy2ot48PoSgS5DETVVUK5bhaW2KUeW7eRW3EPELnr0GTiXJ7cO8PLxXf5cd4nq4mpcpw7nVWwrEYP1sR/pTHluF949rRk6ayJjuwSkN+kwIDAMm176hI8cRGGWkqrqLMxaXtDqOYKbN3bQL3A8ayes5869S1R0FLFi7g40Pxag1kuMuloHaSktZFYUExDQk/a2CsLH9Cc57h3j5i9E16wn72IvETFgHAFVyXyozKai0oCvxs0lLeMWGhrG2Ok7YG7vjYfrUI7tncPmzb9QWpnL2MVr2LtlDeFjlqBnoM6Hj7G0UYpFZytupj3R1TTDLWggS3btZNyM0cS+fc2js78TF/eRRw/u4+pmiIayhUBLTzz9HBiw8ns8HUzp6zoIL/sg8qpUrJlxCgvXntS0lLJq1Xo+nd1JYnU0Y40jUDV3oKCBc09XYyNRkH3nPVI3S55f2sayH77l8YPrdJnp47/IjfmTfiTI1Iff1vxMmV8LWg1d5NRkIOwQY+UTwvN7P2PlYcXTW6fw8u5NTUUK3y4aR5/+y3Fz8qBKXENBVzYVaRmMCdhAo00T+bmfCBswlX5953A+8lesNb3QMqpAz7AHLVUpCI0aifq9GZcIHxQie9bPu0TUh1U01imxl5qzZM18cnKyefjyCjNWbmL+0BnIVBK2XV6CkbU9hjIRlfV1nEk4hLmVOf0DVzBz3GCCxy7j/OvtDOj5LVtPjWLWVxHkvo/n97v30fdpR01eQVRNC09uHcF39Hh+HD6ET1WZhPdayvkHa2lWtmIo6kF920cCh9izacd9hk4NYJDbNJ7H/cGJvW0Ua/RCJDakxvA1iUluDPD9z94CIWT8G2Mlaks4uevo3zdOQKitSWFZDq4RjhRV1JKd1sSb1x8x0dLD3MacdeceUa+Uoe3miYGynseRD9DV6ELDWJfKMil1ze1ou5hgYqKNibY+Fpa9SMnLpLZWQm97T8R6NljbiKn/UoqHVQC65mb0FPcg48E1Ht88Q5G2CAdPOzxNLPmc84pp01ciqWzk5KldyE1NGBqyCPfONBzE7kikYGgu4tKTC8i0mzAMDObBuXeEDB3HkydP0TYxQCqRMaCfA/iP5tyJHYx3ckGoY8DHmJv0CPSjrTSbm58vM3LdDgoqilAaCqlqqiI/o5Enz+/S1NJMh5kmSiNILkrBoK2d2sRPyJQt1OnIcBR60MtmCAaaTihaxORnV+Dq5Ut1czNNTU24aXmjb25JyPAFxCYmsXrOXrwdA6iuqMHCLpCWzha8xszEQsOW+KpU1MzsMTfQYe/Wn2mRdyDprmHihPUUlrTgadUTTTUbzHv5U1qRi72dEXKFiiqZCQNCwkkrKGT4nKH8cmAiC1cvYs/eOZib6uFhYUunWIjTwGASyrsxM3XFysWGr6YPxa1CwYaZe/9He+cdHVW1N+znZCbT0nvvpBICBAIhQEB6EwREQQUBsVBExIYiiiIXFVREBAQRRIogvVfpgYQktPTee5lkZjKTqd8fcL/P976X9/2++73XsJZ51jprdvactc6zfie/39pnn2RvTDU1PP/8ZBbPWU9W9g02n3iOjMZ85r0zj6qDSj5Ztpoo72ieGNOfQDcbnH0CqFJXY7Q4UZqfx0vTR7BrzwVUFgM38m7i69SfC1uO4BPgg9Ezj3jHeBrbTGCRYNKV09U3AWVxIy7uIZjVbbQ1WLBqhylTppKce4XMpF+xmCy0yXRoNBbKqaXCWEKdXo+zk5SLKb+BuZGM/LOERT2FqrkOtRrmLV2Mld6KSnM7Z8/spXfsBIa/HoeXQwhN2mYGDw6jTKmh96ShvLlgJGG+USiwIz/3EhZrI/bqBu5kNpB69zxBXj4U5jehNitZvvhrYmKnEusRxsxZEzC0udAjJI6o4ESmjXiCZo0KV+cYxG0i3nr2xiPz6+ONbyORPnrj3cdiJLBj58/Lxw+bQm55Bm3lTrj7+XL11Bky7xfjHS0h7XA2PRK8qC/WkJWs5ur+E6xZtYmCzDQibFqol7YQETqOSmMxQd0H8NXKTxGJG2hS1xCkdqU89Th3TRqmTJ6Dn8SZw7f2M2jSMwz06U+1TRNisQ6LwhutWcHJ43uI6O5Pg7+FmpZmPlt1gnNHplO+I43sKBespUHoNY3UFNaAVStJyfkEu4ko07bw8pyVhPn0R+wrIe1uCtVVlfTpO5yomET2L1rK7C9+Yf0nKwmMsKFBa6S+pg5z223EbjZEeHTlzrkidh85SkNdPSe2/4zRVYFcr2DPjkOsWbYekVbFqiNHWbRkL7d1Oqxk9dSX7mfzB/tYt+s9uriHo29OJv6J8RhNMrLrkrDROnLqmyVcUe4iNmQwu09sxsnoiLlZSc+Jc9h9ejX6SiMR0c68MCiWb7dc5tMlbzNy8RhCfWyZOe05Tl2+xCtT1/Pu6hk4SG3w6+ZLhERCglSMwaLhk3lvY/Ct5CmngYR6tXHiZBNd7QJAaod/93BeWZbA6xNfo0efqbj5h3AqtZ5VP23EzS6G5JyDBPUawsGd64nxC6apvJXJT31Ir8lRlGQXI7eLJqvmBndTM/BzdMbg50ZU925Ee/vwREIvCvIthEa6U3f5J44W7eKtV5fh6ebBqq1fM3R0InU5ZfSI6ElxcRVn80+x+s0VNKv03Ck/h1toN86dPMKmry6yZus7OFkVkisqpySzCFeFnB6xE9i6bzkirYilC78g2D+CWwUnOHk1BXGKCr2PnhP3TxPgbyI0IJqGKyWcWr6bCLs8HBOiKKq4S1zkAJLVGbg5mfC3d6N/+DTyCq7h5GmNtbuRySPmUlOsJSTGizWrDjAmfjBGxwBqqq9x6VIj7nIz08YPY0vSTURCFSXtBi4X3iYtpYwuPQTmjz3FhiOvU5w1k4G97/yn3Hr+m9dwMUj4vf5HUn8teXxHAlYYienmhpteRJ2qjACdH18v3YLeKofasgY+Wr0Wg1aKn5sbMpt2Xvp4Hn27duW1N9fh6xGNqMSKckkFNeoSHCxOyPQiXNoDyE/LQamXI46Kw9pBTFHmaX46upX+ITFcuHKJpiYdmhojT0xairenK2dP72bwiG7cupXJ20+MwNdXz1e/vkSjqp45v3zJleuHGN41Bo2jlKYmHX0CwtAVyJE5OmDrKScnP49la1/hxIHv2PnxWYb2nItRouTKyWbGT5/HyjXz8Lb1QWqMpujMMW7e3onMNZbLp+/y+qJvGRwdgq2tO9pqI29Mn0NjbTGNqlzmLnmDniNnkC+zQZxay4ntI1BUJpGry6VZKyG74hK/nb6Ko3881e0e6H3cOXz7HEv+9gFtpnKqRCF4+kZy8to+jPVG+o8bTkpRDesPvMWz4xegNtVTr2zgkz0ncLa14qM1i3AQtWArMrBj+3d88PIGLmcfQGklQq/QEn6vmWZVG79ll2OUQl2bJ+Gu7tzHBd+oGSz7+XuEuDH42gIiOR6mGCKlnmz/7TpPL3yNmXOm8+vHKxn7ZiLVDWa+3vA2y6av4NCdDFy9e9NqpSMhYBTbDh3ASSYwvt+bTH92HiI3ObqraTTLlZxMOsvzLy7HJzyW3QeX0XfcXBY/s4z8vAzq2+twc3Ylq7iMlOTD3CzahLdnNHZ6KGox82vKcXJz7pB9cx8evaIRiYQHrxrbTbS2nMFeI+LL6T+wf99+ZFI7LLYi7ramoGwrIyUjH6WliHV7k3Cwd6K+qJm6lhIaGytZvPgnpq9/nrCn5xDS7EOEewi/31xN1p7zaFrk5GtK+Wnba5Q236KorJHMtApO31jL7KlzKbufzYdLp/PhrnncvnuWqkYt4TE6PLoEsOX094Q6KHD2qOfU+u951qzDw0dAJyjYefU9WhpkvP/adgCWbXjwFqCocRUAu97cxPLFa8i7efG/yL/HAJPZyLnfdzBs2HSC4npQKhTwzto3kbg54hnam19/vsiVM+fRGAROHCukJqWQIouB15cuIKleSlNBAzYGGN13MTW1DSQECTS2NnMvt57g+B603LlPXFUbw/2mExDuhUGsoMpOh65bHGIra64nfY1/hAMDJvWlorqendt28tmeA2RXVKMtPECIq4lcQwXeti5Yu4uw0hpQydr4+fBVjl3dwoyF3xPs3x1l3R0WTprIvFlfMuOtOXx/5Bf01m0MfGMUDoN6YcloIXBYDKH2LuikChzVCuorRPSPj+Opl8NZ+umbqLMzeXb4JFrFMiytrtSUZyKxd2LLtr/RWNPO0BmzCHMJoclexdr3luPu1oe6/Eac3BUk3zvH6mULEYuD8ezpi29YJOqr+2mz1pF2IgtDeyvjBz/N7aNHsAv1x0vuxcmbv9Gkb0ShCcbkKbD4zVkU1ArcL5ASIBOYM3slyef2UqrMpclkRtVcx4KN90lLvUivwCDkZjvuHf0ETb0be/YsoQ3oP9CWMGUtlbdPoFGX8PlzQ3HsmsiIyCAkSjPLP/2GS46NbPnyJPvWHuWVgb1pUCqoSq3m+PoNuLn7M2nck3RR+1FpKCGr5CDXa34nsy6FWU9/SuXuQ/QPiib6qWD6uPlQk1nN4TOfsepv77PzymaqsUVfB9qWXOa98gnH96fg4OKKwWDg5MmfCHP0pspYg52XP4E2LuiBoNBIpHIZJeW2VLYrqbfIiYyM4En//ng425Ny8yCpxeUYTdYEu8Wx+Pt48vOr0ajqEBQi8nLVjJ4VycYtJ9l1fBsNodao/TT4OI5mUPgArh87jH2TiLocJRKxiHKrViICnPEMCuNS0h6a7du5nnadiS8+i61EjtLaTIiNPd72LbQpY5n94jpi3JdhMmlJVlszd9F7qNt0CI3lzB351v/OpRXzHrwFCHZ5H8wPti1bd/0TbO2lj8y/x6IICCYzM6e/z4GzuylLz6XNxwv/vl1oKGvBThKMfXEx4+JH4WMr4GW2oUJvpDw/h96hQbS0lvDU6Cfxs/OgsOoi3RN6Yu8RhFKkpFtPZ4JDwxjVy4tuUb0weroSGtQFi0MwZdUX+GL929jfb6G9Ukl2ZT4eMjukgi1OCjlFudWoW0W42/fmTFo+izasRGgX8FI4EywPIsjHEd8QOTaO0Rz+dQf3S85RmlqIg0TEh0sW0kVeRrxDHW4qHZvWL6NYpyd4yFDKs+/S7mamtDyf4oJGQkODsW/3wM3oQpm6DFefAK6kpKHUVjG4ewwRDn6s+2AJ1doSBDsV93UN3Mu6ibohC1MV1Fm1cvn2GUqrJdjJxCybswgrowZzax59ug5i7HNziIgIxdbemfy6Zu4r8/nk/Qs0phfiFRrEud9S0NSpqG4roWcXL554YSzYGRGblMya8wHllRWMGTuZ0pK9eEgd8ZbDtaKvmTR5FOkZedi2qhi6cC5GRTdEd5vZsn8DT3i40S5WER03knfmLyF0/HJyc29gcDEwbOgMxDXZpF48ylMzhpOVXc7oCfOQy0zEBw2mrkJCo7KCbV9sZNWOg2TuP0K7pxgPJylihRmZpxuvzPoC/4DuJJ9LIqJ7XyTmILoGJpLo3psuzoHYiNoIspfR1lbH+P5vMHL4FL47Mp92O+ibMBqFsxQnhS0NrY2Y1TaYsGBQ2GM2WlOWcR93s4TdSdsIjY6hVWaD0tSGWqXDaC5DEAlYLBa6+w2jR1QUnnYu2JiNdImKwV9hy4vPvUh039GcT9+PtKoNZ0UAS15eTUuLhCsX8/hy1WY83SJwKqvk9u1mmjVasspLKUxPx6RTczn7DG0SEb4yDwb3ieW366nU1jRy8eRhfPztGDd6DnYBFprLBfQGHd7u8XgL/2fpsFmM+9/tlDsPdjSuunaSNrXTf8q7v/NYFIFWrZqPP19J3KA4QqNiuL/vCLlXr6AzNWGtuo7bLD+eTJxL+IA+9Av24v0PZ6OptGH6uAQSfMWE9YuhXpXHk/qJuIjskcUNpKymHLl3DO0qFXe79idHL2Kfcg3JN05QnZWJZ7U/rcevMmrZXCYMmIG53EhthR6ZUskXm1ey8IWnGTl4BgOjR/PG4svE9YthVGJX9AYvCloLGdhnLD0C4lny5TwExU2cpD64lGeRW1LDWx9Po6jCEV29iZzmetYt+hDnHV+S8+N8Lt87xM6LSXw0ZxX16jq+/dunaF39mTn/S5buXs3sjwbj18sOJ0sPkoqTiAgbj3O0mZ4h3biXdojwqKFopXLCRe7MXvQEuTfuowkMxclJj1xRy9o72/n448k0FGuoTjtGcnY5wbY+yD2tmD3+OUR2Kvbl7+bVua+x4Y3vGJYYirVRhWAuJ8Q5liP7T9JcVMSz/YJ4Y9VUzO0GzqYcQesZga6+Fr+QRLZtW8/wiRvx62XPwKmzELQSrix/i+6v9uPHIzvo1Wcxl3NvcK+5lgXDnqDg4GbObj6Fv3d/egXY8fryBYRLnDBIdRy4+wWbT37CjDEL6Bcfhe9cXwSZI1NXT2Hkoid56YuNBOhjuHf7HF7BHgyfEY08MJS1u5cwbcRL6C0Cilobkgpv0WXQKBaOfYvJwXNQiyQ01zfz7YG3+WTFOt546hva6jToKEXXbEXWmTKQGMnLayGl6Q656RdQuFvh4RqIRmrD7bvnOHtoL9m6bKrzVPjJo6mpVzPFexzmLJg64T3ktk7MfvY1BnafRoS1G88+/zoNogoOXfkebzcfxoz6gPSUFMbPH8TSBW/xRJwfp4qPYjKrySm1cPajg7SnipjabxxfLT1Ezu0GIqSRzJ0ZRpxDNJdSUxDpxWjbK5j77HzWrp5PeHcnQn1HobKUYlBVUau7zcubl/DSemde2TWabX/4R6E+scsA+Py9ZHxNj15j8LEoAu06Lf7dHaisTudOzh7c5c401Nbw+VtfUlahpzE9CU1zOyYrE6EJPbB2t6On2szPxy4RO2AmTZVK2ht0nC8+g5U4gNNHf2Taa28wfvx4vA1aCs5/yamCS1z9bR866gmO6U6BqYztV+qZvvhbXAdH4qxowzbKnjJjMz+88w2/7N7Onq0r8Y+O4sKlDXgXOdBl9ELaNALiVhlZpZVcTbmG6m4pOouR/JTfSXj/C5x1IrJOn+K5Twaj9wgj7V4NK48tRhjSjRkfbOfpPkOZZNHzwZcf0WfKTDZtO0zm4X3s2bcYPys/PKRduX7uDNrQFrIyDdxuqkCn0eFkbMNGbo/JXUR1YTUam670Swjl6YHd6aEIwkoncP1+BotHvI2/RUzZ1RsEdInkgy82YpAIKBtVHN97ivqqdnZ9tYOYHv25tOcY2lwT5XfKCXLvRh0qfj21gamvzMBRbsOLU+ezZu8iMlUq7u0/zf4PPuJefhmjxzzFb1/OQmQTzKHblzFY+/Lu9qtYyRv59PmJpKWepYdfHD0mfsbqtNs4SOvZc+wUyTfW0nf2JK6fLYEgD27mXee5sEUU5rXw9LyxNOFI6r4z6NTwwjPzqbycwY2UZOIGDuWLt09zd4eExPED+O3qKiKD/HlyzOu0KHOYs+wVam5mINjYUtFuz7CZCbSpTdy7m4HZ25Z+Q4K5l/s7gsmeN795D1dPLwaPGUp/+2iWv7GOWe/GkvN7CT6uOryCommnDrm1Pc26SjQaDZoyI2JbKUKDgfgJs3nr/eUcv36CsopK9v++l3qdMz6JUSgCwnAM88LZzgW1tpV3l07gVuVNFr+ziORdW6lSazE1O1JjqOGLl3bz7RufMCAinhZrOySeXYgI68WwkGGs+X4zkU+FUlbTRkFyFr3Dw1j9WU8mjR1NSHAYIS5ObP5hN452jtwpSMOqQcKgfrMIsPmPuxYvWP5gA9MRc0VM6tL6TzLvAY9FEfDy8qchqQBdthXFKS20CtmMfDKR+1WZ+Mhc2bVVg5dEQ+r1W4waN5p8QzaD17xMDW04B4SydfuvGC1mosdM4dzZA9y+X0d1cQO30u7wzcF9DE1YRGNNHn4qb7qGPkOxph6zROCD1X2wWN1g1do5TJu3EuW1diLNXQkf2Zdwd0e6u9jTrjDSoACF1oNuPok426rRWoxUbv6JZ8fG8dGKn/HuFkGzVsKhzRvIrLhNdUMr+/eU88Krz1F0pBoPO2v0tr6s3L4YVV4jGg8J549uYkQfP9btWUbimMnIbWTE9h1A6u2r2PrZ0ZiWQ2JkAIHBkXw0fzNrNq0gNrA3RZdOIO/3IsVFGdzKLyCs+2BMZOBtEnFm+09s+vk9th2/yLTpn1Cnd6KblwMX7l7E2cGNCa+MQ1utpEc/BX9b/Bbfnz1AryEjmPvhj7g5Ssi+ewkvG1eOXD5DSamGzKIUQoOC2fvTDyCX8cu1ZPZuukxzvYqxr36Ep1cICYHRFP64mcuXNnNyWx7W+S10FwSWLPuOgvJTZJ06Rb1bAAf2reCljW+z5JN52Pezp1XZiHp/JbvXvY+XrQvl9Xo8rF1Y910S6XWphDt6EhhsS+Gha9S1llPZoGbD5vXc3HmBrJxrNHgKfLVhLs4uEVyqyMbg54xRU8vpg+txc27hwObFPBU3BWeVEbWmmO2/fsXiqbOxbQOVTIUFO2Q+rvgFhhOrdcezhw+lZUbUpbWoTbb0UESARYy+0UzigBjQS7EVV3Lyyj7CgodRlpVBbnoyH334G25agScHTeTMpgUY8vNRa1sRa9rpGRULunoUVh4ED+pDgk8C1Y5mZCI7juRuRuPjx7m8axw7thZ1jYl+vcNpk+jx9Q8l7UIKdgGuTJv9GtVKLebAXuy4fAGl0oqS+nyObF+FwWCDSK/g3U+msXnXd/hII/ni1Lv0e0uCsT2TiKFxZDXswMHTjvaiR68x+FgUgarKMryd/ekhN3B19xVMxRqaGmowqPJpaRNxesVY6iUmWlvqqGnMZdc7N/l+9w6CFQqO/PYFEweNwk3hT0llCSN7DyTePpzSwmTiI+MYEOjMmp++QuLgjdbVk+by86Rf2oWtCMYMWoSNbQD+nu7UV98BX1fahvgxauQ0JKYAWkrNDHpmPHFdohj/5vOknPuZ12cPxEqsw7VnAlf2p1HcqqSppJiqwkbCfEVcqUpjzY/HCW6pZ9/+LVyuvY6lwhG75CqGT1mIf/xIMmvg5dmf8vl3H9JNGsIT3t1orWqltiSdkc9PwSyTU18no6W8hcBQe+4UJhNk50ZFYx4ege6olWUU3M8h4+J9fHv3Ia0om/yGZn5c9hlNOisiBrtxr6YK21ApvfvMpLG+gm4B0fy27gyWe2KiHQcyaOo8XCI8aBOsCXQWETNiPDlFFXg5OlGdUYWNWkxVhp6efi4sXfwOhgYT8aNf53rSDxy98yNNhiJcpAJii4T7UWYqZTXE9bVj3MenqH1qNK6hchJHzCE1V8+1s8dRePfEwyTGYNXK0PCu9My1wVZigL5BvL1wL3MShtMgayYz6w5ZyalEPjGNTV8eoMEiYsuSpXRxcKWhrJytv92m6ZYKe4MVOQ3XKddkMbTPGPz9I9l6eieHLqYxr/dE1vx6nIsXz5KtvYfIokDkbqD45nV8etlTmH6QCksma35ch61YTpujLVGJJuqL23G29UTX6MCYcTNxdLLB1jEQPQIyuYXPhi9jw3ffgZWW7j0CsZM6cujnRbgEOLF/z1WSrjdRL9YjEgSa6tooLWikRVtHTW0+DqG98Bk8GZGQB3I/ou2nMum9JRRkZWJtHcbqX6fSL3Em3+5ahE6mpl+XYQS4epKdfQOFvYwTVzOgwMLGFX/DWQ3vTX2RdsGIqqWFDV8cwlnlhdLFzMWkA3z2yj6qS7T0FY9AqfInwNjG/ru6R+bfY1EERBJr7E1SEidM5Pn3vsanz2Ba85sIiI6goOYukWOeRmZQ4S53osXeSKCnLR5NegYGdsfBNoCfU3/Bxz8UkaSFXGUpZrUKa507BosJs5OMQT0SUGDG1qIgzDMRudqOKYlvEd8nHjdM0NKAjcER25ok6i5fpuB+KgkjE3l304/ERYVgI5dSo8ymjWqmT5mFQichfFQcagcRMpMEi8KKiCAf7GPH4WvpisTKhdeefh57XRuXzx6itamBIS8u4PfLpzC6u1B1P4NeE4fjoPPC19mLtq52uOkDaAIkYi3ZV+4R4OdIS2sjXvIu2NvakfDaTNIr7qBtqiLCK5DwSAdaWl3JzsumrBEkzjKuZ6XzwpiXURY3YyUzUt9SwJGbu/D0DuJg+hEGB/VkyYo3uJB+nfnznqNVsKO0thQ3hSPtYjPGljbsnL2wl1qQRMVQU6Ymv7mZBYu+orHeiF9gb5JupiJBirpJT2ZhOkVp57h++jQ3N+0kNDyY05e2c2rnCkSVFhQqE+b2Gzj4OlFvsjAiqDvHt+VwLPkAM7fsxdU2nPTMGu7e2okowIBcZouLoCUsIICMS9/h6hfCoUNXeXLsVN6f+SxZ925iaKpl6murqWttwtUxEIUgQ2dxJspzEmZjJc+NGoNGJ2d4zwn4DnBD2dLCQJ8+lNdXIQuMwMVZgmdwDxxkwQT7dEUtErASjDRIxZg1Epoba+nlZcvprIt4egQhtfFAJWojTN9Eq9yDhCFPkVF+GNeAcMRo6NljMJnZjZy/vokBz/ZHZrZgUlkQWzlRqW5FLmmmPO8mYrMVNnJ3agsbkFis0XnrKFfLUFhk3LtQwoltR8muu0x7iQr7wbuUGgAAD2FJREFUJjmhvWLxDhqIjSPcqs5Foapj9KszGD1kHN7dBhA7IQFVZQM+QW5IXW1R2NtQUl+N2liIt2MgfuER6CwN3E7fRJB/KK+//v+xIemfgcVg4WRrMR/+sJZEH4GSjExU9qXEBY+gUdXK5hv7EEk88LC44UsAn67Yg9hRSqbQxvnbVxG7tLHub18zMLCd6wc+oslOygtjJ5KRXsBP28+jNBsROZfipFJzLyeTAt1tIgKGUFtRQ52slbGTvuNM8m5EZgNOunq6uzpz5eB+9t3ZSVj3OD5b/zmhIUMoKEsloIsnlcY6pg99h8RBgzl+6Axe/t4MHJzI5BGLCE3ohUbbwi91KaQnl5Jfn4VXTG9WH1mNzGLk5v5fWLd5K+VnU/l65a+cr9qC471iQiP60ic6GhuFN2XKRuS59YQ6RrP//dV8u+kHMkq0lLVmUGksZ+PGDdQmlePkpOLcsV9ICB+FnVzBL2sOc+PqSZ6duoSD362g9EwFMi8JZrGO7KQGPl93iHPpKTgqZPQbH0jmtT1ER4aQ3pCMqbmZFR+9g17ZjJNPMCIfDU22ag5sySNx8ADCB7qy7r2ZvPjMUmJ8xnD39xOsW/oB/caNJz6hC7HP9kNe1sC4oaPRlpby3dnbrJoXT3k1bM08x4w3RxPi14+4Kd3wVOnY8/liXGNccPXQ8eOVddxXpaJv01ClaEGmTOHLn76mreYK8za+h3OwDyOnj0IoT+bGpcM8kzAKO1sXvCLcyK3MpTBzNwaUvPXiXhImP0/QM6+w9fwmjI3tFOaWEj90FvNf2M7B7J0YaszEdxmDtDyPKQNfRoKZupJqCnfpMCKlzbqNqF49eXXyAhRttRjLztHLvZ2pU/YRHDMNeaAP3x3aSDepCLU0D5V1C5PD/fBQOOEd7U99ZRFSKwv2GhkhNh4888wKfi9QsmHTt5TWXMTarKah6R6lOcf5/fQHvLrkcw6ePM6hvTfIuXcL/z7DMBgMuAZGsef2anoo++C/NoMArYCnwYGxc9+j4PYlbDw86OrVjTBZPH69fbl7K4co0wjS14n5+chUtiSv53DeCpLyzhMcP528mmuPzL/Hogg42TlAWgNii4w2qTWLZi/APaQrxXcrGD3gBeR1DogtLfQfOhRjaQ4HT61Ham0F+noURhNFWiVvvjSMhjwXwvoMJSf3PrV29hgMzfSOdMHOs5CVCyqQ2fojNbrw9gsfk52fQ0b6QXr37IWlohyZiwOp+XX0fWIixUlXGDPtJdrzjIisrSjJqSclJQmddypZ1wuRt7bx6cczsDiJcI1yx6Kp5t6Z69y5vJvSzVupU1XhYgPDJ75GW00xGo2K28fOMXX6G0wcF8+Tk2bz+sptfPDVe7hkt+A7YCwmKxcU9kGcvXqRkEob4pa+y3OrVzD77ffoK+5ORV06Cpk7dmIJw54dQEmDBXGbmIiYbqhNNZjlAsNmTafVyo8Bg16k2ahg3YefYY8TIrGEIXFd2bB6Jtdu/M7wiZN4bsxz3LtQQlz/59HLbNiz9yKX7/6CVtSOl5s7jhJHesTGM/zpXlhktbSV6Xl63kxaJBpi+sWi95IzYNHrqFsk9BC74CWdhtOAEZw6s5IzxyyUN52hMn4ou3Z9iUgr4uiqPSQ3NrHUP4pxw59n4vzPqBBVI20yk3OxgYZbhTRV5pCadQGNQoocKQf2/EY/f1fcg/qTmnwZO68EgoICOHr1AtJ2GSkp92nMS0LTWE9gmD/2vpEcOruMlNIbNOvUFJfYMKLnII4l/YSlrpx+GgW9QntzrvgcXp7uhHXtSWZpOmED/ejVJRKpVIRRpWTLjzvRtLSw8v1rjBn+HCKtHRpnM7XaZAJDfLjfmEqT7j4ODn5cOrqbi8ZMymT1GFv0NOVaoTVa4eLqTruVNYKrgI9TVzx9gql3bcHewQN9tS1ZSXmU1yfx6YL32XH/A37L30BeRTM6cug7chbZty7TnlZKQxcNK6rLePu9Twhw8sKsq6GgoRA3pRdPj5qGlYMJfV4ln36+nanjphIut0GvdEdqMpF8uwUnsT1JF7ZS2HL3kfn3WBSBxqYW3GJC8HCwpVbZxIFftyOxltOmbUItb8Pe05ZKkwVjhZKEObNxjvAiNC6GzLIKpM7eBEjsUQt6VC1lhHh1IaxLAIcP/0K7HhQBPogUUi7u30q3IYMI7BpBYGAgBYWXcQ2MRltWwPXr16k3lUKrHJHYhFeoD3KRE87+7bjaBBCT0JMTyam0t+ppteiR27uic1fRmtWEl4crMudgBJk1v1/LodfzE6lQZeLkFoadozVmWxWtDU0MGD6C1vRCYnsPYqBCQuqhXYTF9ubVeR/x009/w0vigMqYTdqxDOZ+t5o5CyfzzdpltEut6B/Tl++/+wU3qRsmGwEv13Ck7h7Y2og4t/cSVgpbKgsa+GXVt6zesY3Jc0ajldZRWt5CbGQ87QYlbWhJz7jNrNdf5ObFO2Rn3ebzlSupyE9lRN8p3L10HmsrFwzqMvxkDoT6d8E/LBYvr650TQiktqgKsdwKQSRm7zc7qLqZiVzcSn5zBl0iR/H6kulcun4AiyKQlRtf5tvdWyn+7RfsistpyW7EMzIAP7MWef9hFFibaLdoCHcKp1rQUp6sROHsSE/XCNxlXhhNxUR2jyUspg8yncBLL0zivSV78HR3INJNj8LYiMWowc9NgoeTEwpXN5Jun2fj+nfwcfMlK/kmhnotxQ1K5DJPaupSabIYCIp+kozyPPzkBlqtmxGkIhpqspFYLOQV52IrkmDWi3DzcKco5yLVNbfQG/WUNxSD2oJIFs6Rcxvo4eTCmuNfI7G44+49mOTsG+i1YLZSM6R/T5C049fVj15xvbCqr8enrycxYX6Yy5rRt2kwWdlTozZiJ3fHqLegN2jQqtvwtLNBKuiQOTgxKDyc9Lu1pN/Zj42VCE//Puzdew6NRkugt5ihUYNptNFT01jL+IA4/F18yGnM4OmFw0nJq2T/qc04uLpiK/fCyWxNQUnmI/PvsSgCzi5OjOk3CpXJyBNhwUSPnIyduzvHTh/HpFLSbNTz/rszyDVVcjf7MsOCAriedZi3nppLTkkx0d3iqWg1YbKVcTEtlTaRiiB3O8J8gpC5iXCpisHF14HAqH70iOxDakoLNRX3Wf79O1RJ6xjy1FhcDa4YJDpiuk3gXnURJlkRPeMHUVd+l74xQ0nP+4G3ptzg7I8p2Njak9gaSLfgfuzZthadUI7e4EBpWhJWSiU1VeUUNF9jf+pnhIcOJ0BjQdymY9SYBMa9uICBb05i+tx3iHDTog7oQbryAnmm29hVezL/nc/Y89kqPoyJ4+Wh/dFaGVH7uPPpvPm0GWvRtjSSX3kB36gqCrObmDlhNPevX8HDxZYPD3/N6jdHMTxUSpRHCF9uWElO6e+ICxVEB8Ryp7yeQycP0NyejY9gIFPVyq+7PmXIgGjC+vswxPN1ukd15/Lvd9n54z6qik4hNtizcMoy1v18nJpGE4f37WDSC7NIGNkfw4EbiJvVzFs7g4VzoujXbSQ3Tp1hyotrab6cQqJ3NCUuKubPWsiirz+jx9TnqPUSYWxrQ9tSSerpS/TxkTF/eX+6JCaSrMzHRuyBlXUPTl++TK8xM7AJCqNroImS2gz2X9zC+dxGugZGInL0RCrvSUrxFX45/wNR4fH4uPngYRuFnaKFZoMLvtZ2yKxjUbZb8ek3r/HD2Z308hjEzWP7Sb3UhIvMkztZh/HW9SPcXUZBYzmJ/QZzv7yRyD5deGX5GM6cOUhms4oKjZZz144gay9EbRKTlV7DgJ4T6NWrFz3DEpAYiqmvzWfYsKcx1KhJybiIVmohLfcmPjJXcqpucbciGVtfbzxtPege2o0nw6fRr8dADC1iWu644qH1JyxgDHfSNrL91g5GD3uGvv2HkjDLi75zxtB/fCxFjVkkl9zi1ZSFpF1OoSG3gVZfez746klupp7G7Cjm3ecXkRgyFJGphbExU7mR0cSoIbMemX+PxRqDgiDUAxqgoaNd/oArnT7/HY+bU6fPf02AxWJx+8fOx6IIAAiCkPrPFkHsKDp9/nseN6dOn3+Nx+JxoJNOOuk4OotAJ538xXmcisB/Wuygg+n0+e953Jw6ff4FHps5gU466aRjeJxGAp100kkH0OFFQBCEUYIg5AqCUCAIwpIOcigRBOG+IAh3BEFIfdjnLAjCOUEQ8h9+PnpVhv8Zh58EQagTBCHjD33/1EF4wLqHMbsnCELsn+SzXBCEyodxuiMIwpg/fPf+Q59cQRBG/ht8/ARBuCgIQpYgCJmCILzxsL8jY/Qopw6L07+ExWLpsAMQAYVAMCAB7gJRHeBRArj+Q9+XwJKH7SXAF/9mh0QgFsj47xyAMcApQADigeQ/yWc58PY/OTfq4b2TAkEP76nof9jHC4h92LYD8h5etyNj9CinDovTv3J09EigD1BgsViKLBaLHvgVmNDBTn9nAvDzw/bPwFP/zotZLJYrQNM/dD/KYQKww/KAm4CjIAhef4LPo5gA/GqxWNotFksxUMCDe/s/6VNtsVjSH7ZVQDbgQ8fG6FFOj+LfHqd/hY4uAj7wH/ZMruC/DuK/CwtwVhCENEEQXnnY52GxWKoftmsAjw7wepRDR8ZtwcPh9U9/eET6U30EQQgEegLJPCYx+gcneAzi9H9LRxeBx4UBFoslFhgNzBcEIfGPX1oejOU69DXK4+AAbARCgB5ANfDVny0gCIItcABYZLFY/sOaWR0Vo3/i1OFx+n+ho4tAJeD3h599H/b9qVgslsqHn3XAIR4M0Wr/Pnx8+Fn3Z3v9Fw4dEjeLxVJrsVhMFovFDGzh/wxl/xQfQRCseZBsuywWy8GH3R0ao3/m1NFx+n+lo4vALSBUEIQgQRAkwFTg6J8pIAiCjSAIdn9vAyOAjIceLz487UXgyJ/p9ZBHORwFZjycAY8HWv4wJP638Q/P1BN5EKe/+0wVBEEqCEIQEAqk/A9fWwC2AtkWi+XrP3zVYTF6lFNHxulfoqNnJnkwi5vHg5nSpR1w/WAezNjeBTL/7gC4ABeAfOA84Pxv9tjDg6GjgQfPii89yoEHM97fP4zZfaD3n+Tzy8Pr3ePBL7TXH85f+tAnFxj9b/AZwIOh/j3gzsNjTAfH6FFOHRanf+Xo/IvBTjr5i9PRjwOddNJJB9NZBDrp5C9OZxHopJO/OJ1FoJNO/uJ0FoFOOvmL01kEOunkL05nEeikk784nUWgk07+4vwvMTj0/LRpX6oAAAAASUVORK5CYII=\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "temp, mask = explanation.get_image_and_mask(explanation.top_labels[0], positive_only=False, num_features=10, hide_rest=False)\n", "plt.imshow(mark_boundaries(temp / 2 + 0.5, mask))" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "e5FIt55txwl9" }, "source": [ "Or the pros and cons that have weight at least 0.1" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 287 }, "colab_type": "code", "id": "ExFQHJw_xwl-", "outputId": "2b7e3bfd-5c66-42ef-eaf7-60506b25dbe3" }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "temp, mask = explanation.get_image_and_mask(explanation.top_labels[0], positive_only=False, num_features=1000, hide_rest=False, min_weight=0.1)\n", "plt.imshow(mark_boundaries(temp / 2 + 0.5, mask))" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "R2W22gjS1oiJ" }, "source": [ "Alternatively, we can also plot explanation weights onto a heatmap visualization. The colorbar shows the values of the weights." ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 287 }, "colab_type": "code", "id": "qXBM71Bo1UPc", "outputId": "9f32237b-eb29-4355-a0a3-96163c2360c5" }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "#Select the same class explained on the figures above.\n", "ind = explanation.top_labels[0]\n", "\n", "#Map each explanation weight to the corresponding superpixel\n", "dict_heatmap = dict(explanation.local_exp[ind])\n", "heatmap = np.vectorize(dict_heatmap.get)(explanation.segments) \n", "\n", "#Plot. The visualization makes more sense if a symmetrical colorbar is used.\n", "plt.imshow(heatmap, cmap = 'RdBu', vmin = -heatmap.max(), vmax = heatmap.max())\n", "plt.colorbar()" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "YaQK8BZexwmG" }, "source": [ "### Let's see the explanation for the second highest prediction" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "ClAt2PowxwmH" }, "source": [ "Most positive towards wombat:" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 287 }, "colab_type": "code", "id": "cROfKjUMxwmI", "outputId": "37bfe983-d4bc-45b2-bca2-964b91f1258f" }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 15, "metadata": { "tags": [] }, "output_type": "execute_result" }, { "data": { "image/png": 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5iIATZk0DCDkl1BWOQSELhDqwMotoM6Me1dTe4UVoNbNz5268D2zaNCZoQkX59/OF8/5N+J6XvJfXv/5/cMEFz+LHfiZT+c9y683CI055P1dffhWvef0S43gs3/GcL7JlS+YP37uZn//t9+/zOot1+x5c3P/+99ezzjpr/zsOOKAIIfKSl5zDTV89no9/4kmk5Pd6/RnPeAc//wvX8L9+KfKAB57C2972jbWGiCghxFU59n3hPve5nYc++P/w//7kmO3bxEID78kxk1JCBARP0yqnPG7GC56/gVtvSHzlyoSvPD/785vYurXhdb+8m+3brD5gNKpoZw11qMgp4kNllYQomiLeeSYpoQpOBDGnwboQRRBxiAMPeO9pm4g6RyqrFwlayEWBnBlXI1Ala8JKERKVq2lTS4Uwqka0uSUDY19RVQG/5JnumZFaZTwKhOCIuaHyIx70YOGv3rqbrPcF4Ks3JF73C3vYuFGp/Jhbb1jmqCOOYKl2RBQfMyuTFY5+wISzP3DzZxYUwOa/6zf0Cw64V+PZzz6PE0+4hRuvO5PTTvscn/7041cZgmc84wJuvvkrfPazNeedn3n1q2/k4Q//MgArK8ts3XrCfj/j5JOv5KlP/RjnnPNitm8/cq/XTzzxOpaWJtxyy7E8+cmf4MuXOnbvrsi5IbbgXcIFwTmxtJ0qPmUu+XzgyktaxlVAnCfUNf/PK2Zs37WHNitoSxAsRg8VihCqMU0byeI49bGP5NOf+SxtjHjvIEFSJbcZnLnrXaogZxvoOSkqDlVFRFC1MmQRKQZKzHgAoQrMYoM4T86JIEYktilCCLikpASTZoVxrBmPa7JP7N4zZTQaMa5rlpeXufqa3TzzKSOc7qDyjuRgVI244xbYMBozHtXMmpamVbLCtrZB2obrLm32+ZsMxOCAHpde+kgm0yPYvvOpuPRInvzkT/WvbdlyG5//3DX81E/W5Jx54xsDr3nNbi688F1cdun7edGL3sFJJ1217nGdy5x22qc55ZTLOeOMd3LCCddz0klX8e3f/slV+5188pV8zwvfznTPOZx55rlceOG38q3flnj0o63H3wlkTeQUSSnTNtEGmROCc3gfmDYtTRNpm5bZJCLaxfgmLpoKERg1M20bqwjUxOcvvtRSds7hOi8A8M5b/aBY7jCrMqprxktLZM2oQKksKoPf0dUdZoU2Z5JaBSMioGZcLO2oJLEORs2Kc1bZuLtpWGkavHe4IMzahpQyu3ftRkRwPuDEEyOkpExnM5ImJnHG7slutu/ewWRlxnSygp9NaNuG8dK+hXsGT2BAj61bT2D3buERj34zF/7Hi3n+6X9PzsqnPvVtvOQl/8Cv/Mputm2ryk2vvPWtwnjkEIlcf73ntf/fuTz+cWMEQZzF0NdedzLj0W7e9g838nOvnfAzPwH/+3eFZz7zg4i0HHfchXzxi0/n2msfwUMecjXbt6/wy68ds7JyE097xj/ysQ97vnRZJnhPSpngKyPiyqBKmkitUo9G1gKsAinjUyKVTsBKhKUNG9izsgcvtu5AjPZ+0xGwWB9ng1ycIwMUY2A6BDZwxTna2KJqVKBz1nq86A1IyTDYcQVBSDEjhfsHwAkheFZmM6q6tgyFh5AdM5QmRmoRnFjmYdY2jKoKbSBLZkk8bUwIjiRQBfNQMqDecfvu3VReWRqNcKrE6Wyfv/vACQxYhSOO2MkPvvI83v+eVxJ3XMe3P+99XHHFw/D+A3zPGQGPgJhEd1VVtDESfMA7x6iquc+mTThgvGmZWUx8yyNvZef2ii9erKTCij3+sYk3/sUKHzzf8epXe37oh1q+6+mnsWvHRfzB73muu0pwwdlM6IW6EnKbmKy01urrPSoWp1MIu1S6e2vnqQKoOnLOZIEYo82yOeOcIzYt4oJReCnZDK5Cq8lm/xBoUwKUynlUzLW2088gNvhjTITgUdWe8AOsXsDZWgdOIIjHqaPVBE5BxQZ0zjQx4eySEpxjPK7ZPZuRs7LkAjErSayUuXKBKngqL1YKnSKjqgZnHsjGumIymaAhIN4xmUwZq0OcEmr4ym27Bk5gwP4holy/9WauuuxKlsKR7L5zxNOf/j5eduYYr4o4G4QpJowDE2KMbNh0BJPpFFdXtJMpcc8KOMenPzkmq0l7pZgYj0Z86dKWH/9vI758hSN45c1/GfnSZRdx0adqcB7xCSX3A0vVm1vuUz+Dm5EQUgItBT7OeXP1cwIJZJSl8ZjW+15yPOeME2f9AQ7EechKFssDCPSko10PKTOs2uc4R87WeNRlGHIu7y2egJbnThyoHavynraNkG2/Tq9ASjjhcKQYSa3xBY3aMmlOxMIFQLyQybStUteOEMz4SrA26eygGtVMG/NUgvOIBMa1I1QAu9b9zQcjMAAwQY6jj97G859/Lmf/U8vll93Bt3/bI3jbXz2V8/9jhUsuvwm8kJL13tvAc0AElJXJCnVdcfv27SxvXMZ7R5o0SM54ESYx0cYW7xTJmUu+GEhJ8U6I4vjMhTUpt1TiyJoYjWrLy7tMThkhMGtanHeIOAsHHDjvjWBrbZ3BOgRUPYgjxhk7pyu0bcQjOMlUoaKuK8Q5YozEaDl7SNTOIVg9gAmPQBZz4DuPWXNGxGoF5l70gsiIKjiHZi0ZBjtmzNGMhJMStmREi5FRRcjUoSI2Ee8CQTyTtmVDPULVgXgmTUsQz8bxEpPJFOcErTNBKo7YuBHvzCMaV2Pu2LmLto3kCvJMCXHfQiiDETjMceKJ13Hiiddx55138KUvfZE3vF55wx9XPPO7dnPEfY5h19bAV2+bEYIjabl5cYX70jIQzJ9NORMnxmbHNhLKbNimiPOOSox4i20qbDukZLMjWYk5IxJxleXlRK2YJraJhBFiOCArVaiYtA2hUkLlca4qIiElPVe8lqSZII6AUNWBUVUxWZmhUpoEVYnYTBuQUjFo10Yz5OKRdANWpfMOSi1AgaoWP4KiWeB6r0DVKgMdYt8RxSGk8hfBuA1xVHVlRk8cHlsrwRVCcRQCKSWadko9CrRtSxsjVV2R2hYNDpVMO5mwcVQxQZnESCtKnfadAxiMwGGMLVtu48UvPodf/IXdfORjcPkVRnKJT3z4ox/lWc86nQ2bjmRUL+H8bnLb9gy4iJXFeCdlVm3ZuGkT7WRGnLa44BiPx0wnEcGhKRIqTzNr8ZS/VU3lA9EbQy44sipV8LSzaMQcgqYiEqoCUZEuW6fOYncnSOqq75RQBWKMaKuoKCMfGIXKRnKClM1weOdoi6ZARshiMX9WI9jEgRR235WSIc2Ao3f9O/TPi2FwCN55okZyVsQZP+CyyZuJ0BsASzk6ZjGCywRfE+MMUSE50zVIORMQI/5yJrWpF/PXnMlNS86B7DDOAqgEqnHN9tkepu2+PYEhRXgYo64bNm/eyRcuyVz2pdwTZ04dkhJv+pPXs2vnDrwLNG2LYimzFKPNkhmCr6iriuA9s+mUpY0b2DXdw57JhN1Ng68rfAh4Zy56vbTE0oYl6lFlXrjL5ip76+hLSWkmDUkVV9cQoW0ibWoRydTBI87It9GoImZlZdLQZmWWLMe/YXnE5k0bcN7i+SYmpk1DmzK7mhnqjbFvkhX8em9zoXUbGqMPNqNnsbjc5MlL5MA8PFj0BqyYyIxBLKImmXmGoHKe4K3IqA8hsppxEDtmkzLTUk8g3qEi1tiULfNR+wrK4iniHeICs5kRpmQlTSNNE00/QSDFho3jilDte6gPRmBAf9OL2vJc4qxA6LZbb+JTn/4UKUdCCEZQlX5747OkEGTeCLOUWd64gelsxqxtmE6ntDExbUp6KltV/EozoYkRxbT/xRlRpsXlnsZIypnpZIXJbIY435fvOieEqkK8kHIkxWQNP1IScDkzWVkhxdiPs6SZNidmbSRlExWdxoZp21r9gGqZ5yGqNfb0ELEBSjEKC4Nfy3t7vgD6YwHWmkwJObJxIjGXmbvUCiBQlwyDOGeREbmkGI3IjGWVpJQte1EFb6nDNjFtWpxzVvSkagurOPNqQFnasGRG5muM9MEIHMZYXl7hT/9U+NxnbYhZ5lvRlGhiZBpbds320GpGc8aJ7+PlUu1iM+2sQVNCNHHnrbdx1OYjUbWOuz0rKyjKynTCtJkRm5Y9K1OaaTQ323k0W148UdYDwNYQTDlB5UgKGSkDucFVDl856lFtmQpV2tQUHQAl5zLbit3epiScaHOy5cdSoum0A7wjkRBvYY4Wg4PYMbyzZiBxQi7DO2fzmmDuEeSc+xoA733Z37IKOEGdkXtZTVREnfELiikf+2J46yqAgFPFYzUKs5xoS/PSLEYcjmOPvS9JKDyNMmlbVmZTpA7M4oxpE0ki7FjZxSxm9rEQGDAYgcMWIiaauW0bzKZ9PsxiVFGk9iSU7dvupJnNiF1GwHnqqsKJI3hPFQJevKW4UiK1DaO6ZjQal1SdYzZrCFUFalVxS+MlfLBVgUVsEZB5LJ4I3qruYskROu/6zjsRIcWEqPEE3jsrTBJbYDTlhAq0bWsqw85Sac47xJvRcf2gW4zrtbQtd2G99BV+zpUmoVIu7JzgnCv8yPxxh6yltXkhzahK8ZjsmManWmVhN4urmnHRbOXJwXmC90XdyLyQalRTVRXbt+8khJpUSE0nNt23ObG0NDbj4BxRlZggxsEIDFgDVeETn3gyZ56pnHyy9qmsLrWVU0QEdu3awe5dO/qbFJS2aa0SLzjq4Fge12xYtkrBJrbUdcWRRx5FTuYCZ4W2afBiKUbN2WS8FNo22k1Y6u6tDtdRhxrnAkmVJkfUQVeKm9uMRBhXI+MHREqXnw2wnIyvmA9QY+rNc0l4HxAnVFUoA7JU+jkBzThfPIiY+pnWynpdOWYXPBg6Y9B5B8Wf6md3264mXELnPWhfmqzF0wLjRFCxZdNTQnKiKsZqGhtCCOyZTC1MyhlVoU2JEALjjctMpw3BCaEK9jslU1lu28EIDFgHN998HNu2PZXTTrMOvdzf6CaM4VxH1qVeultw4D31qCbGaHX5ROogbAg1XoWbb72FjZs2Uo9GZDIueJwLtK0JeaomcuEZNGVzgTG2PCcT/dDSeDOurV6gq8pz3mY3ESMv22iLjcYYmcya3hCIN7c7arTORWeuvQjEti2lwBYSKMVwxDSPvaXr6jdYGbQZg5TMK+hm/75uog+8XUkhzolDRRAvVE7wbiGsUCsndqVGAbGKxSxCQyY5+x5SvIZdKytkEaIkUGUkgTYmZrOGdtqCC+zYOSEnS1MGb+FWTHsLr9Cf7YDDFjk72rbijW9SfKDk/Y2gs8U5EjE2fU1AzqnPj8/aZl62mwGMrd+wNKJCWB6NUVVmTWODWpXl8ZKlIAXqUUWMDSlFCwm8Q7xHPUQykWSDRcE768cHLYuCRKZtS/CWhnMls8BiG692M64N6phNfrzyjiq4kpIEmBN7dB2BdiSrS6DU5GdApJiFefagw1qSUESIMS0c25wcJ87ER7L2ZrX3IsS25Zz6Woe2eAiVL23KwLSdAuYBOGdbZzExGo05/vjjmcVEzjCbNXRjvw9R1sFQJzDAsJbtFqyhppBgvqpxwardJMIoVKiz4pzUJggVbWyoQmCclWuuuoK2mQFCGxPeKeq7Gc8hki2eF09TlgynxPnB20waXFVWEFJjtzUhzpPynHCrnaNVQUmlS1Cpx55RPUJWpvhSO2DVPuCdo8kLBU8lY4GU2dvRcwFdlO+cuekd8bdefYCl/eakYVdS3DcV5Vw8K8VpVyCkJZQxbgPoQw/vHUHEeiA0EwS0kKCUsuMgnphaMkorGAnrg6V0YzLxk8nM0ppfo0dov56AiLxFRG4VkUsWth0tIueJyJXl71Flu4jIH4vIV0TkYhF5wtd7Dw44ONi+/Uim0xFa3EcRCL4QZ/0s1s18RpLZ7GPklcZsRS1dq6wIo7qiEovr+9RbSuzatYsNGzdS1yNy0pLiavrZNZWYunN9FSPTYj8zlvhZrU+/icZbzJoZfRGjU1zwTGNjHEbX7SdCirFP2+Gsc1AWcmfOuz5mt0HcMf/z2X1tlWC3Ped5J6G9x9KffdUgZm8ShZx0jiCFXCzGtqpqnPPQ1wVkJHfehUM049zcwzCrx5QAACAASURBVFGUiNJqJgGTyW727NwOTslO8KMxoQ7ElEqL8/r4esKBvwGeu2bba4APqurJwAfLc4DnASeX/2cBf/Z1HH/AQcTFFz+GnTu38IOvKmx0yYuj1rbrXWneUZtFKfF5zLE0yBip1cZMm7vKP2FcVdSFU5DSM9+mxO133sEsNhanRiuAyVCYf0Cs0MZa6wRfBaR0CnaEnfdWWZhyZjQam9KPc1Rl9vTOHNzaueJtQN/QI7BhaQk02+dIx31QPqdrBbYwxxYfNQ+mm+07LBqEzkD0hqL0Ddhr8x6BNmXqpaXe4HWelytlxs5ZaGQ1AkVxWISo4MSTk/bnmXK2xieRPtMSc0vTRmZNw/ZdO2mnDU6cLba6D+zXCKjqR4BtazafAfxtefy3wIsWtv+dGv4DOFJE7re/zxhwcJHSEi95qTIaW3+6E0+oKityKaTXXDmnuMXi+qKUWGJ157wV5JTimOCUDUtjbJ1fZzNhhsmsZaVtiDmzvLzEqArzm95ofVAtysCZTqgj5YwrpFu/iJBaJiBn29+L0DQzPA7nHG2M5GwDSFRwElhZmVCXGoAY0zwt1x9P50x/V9QD/bae7NN5eKB99qRLD3ZegH0fldxnX6bTiYUuRdVYtfRdxEhsWzOkJV2bynVuyczKb9EJpCBG1HrnOPqozTzkWx7Jgx56Cg866SQUsd/Ie7IIld+3nNs3Swweq6o3lcc3A8eWx8cD1y/sd0PZthdE5CwRuUhELlpZWfkmT2PA3YG3ve3l3Oc+j+HXfuMYjtzsqKrKGOvSRtvG0jlYRDRyabxpYkMWG/Ba2mIrH3rxDSk6/Db4upLaXCrmAISVyQriXCnNdZaVQEzDzznr51crxBFxeF/hvJSZzdKVwnxA+SrQtA1tbK2y0JncWIzRGHrnEG+DnzQfxF1WAKBTALbQgH6fxRl7EZ1REHHmzhfkhf2sKMj2tcpLC3UWG5FSWSSVYnTNpGjXKNFzB67LLqhSVzVLS0s4ES677FKuu/56rr36GjtPsTBMYSFzsTfucnZAu6TnN/6+v1DVU1X11OXlfUsfDTiwePjDv8zznvc+Pv3p0/i+70scf5xDkyn5mKRXUcZJ1svfMd4pJXIZNF2+m9Ihl1Iyd1dgw3hMJeAFfKn5F9Ei+w2j8RJNSkbkLaTUnARyTLjCVbhuoGRryEkxmcpQF5fTDSTFh4qmSWSBI47YTC51CeqE2KkCiVugPOycUMvtG3k5zzYskmrzWoA5Fj2DtJCKy137sGqROVswOtKpDHV9Ca54DF1YMvdEuhJGEYeoZQlElaqu6PiOyZ4psYlsu/0OW1MxpZJZcTiUlOM+74Fv1gjc0rn55e+tZfuNwAMX9ntA2TbgPyFOPPFyPv+Zd/ED33sJpz7xH/jtX9/F9dc7pNSgL8a3wF4Ms7Xumsue2sRsYj0CEpyJflQBJVOPHD5I34jjxFJeLOTdJ9NpP6C7yrhQBZqc6Hh5EUr9vGNUj41Mq6t5qFKq/GZtwyy2Npiy6REoFGEQMxSj8bgnBbtZ3pca/rZtSTn1bvlaLgBW8wHd88XwoGylW/SjI0jnaUTtvYAuFOne67pwaH7weQGjWmOSosTYMpnNWNk9oWliua6+v17OOVuSHUX83d9K/C7glcBvl7/vXNj+kyLyT8C3ATsWwoYB/wkwGs14whM+i6ry7xd8hD9+Q6bygdOfVSMSiNrivFX+WdpM+0zA4ozXlcIqQqgrSPS9+JX3BOdp4oyMLaqxYcMSs2lj7bIi1k7rPdNmNq/Vd0Xfu4QbUSBqwomz1FiR7co5Ic4Gv7fNJsOVMgSYNi04oYmJ2DQWlojQtq1lQBy0sbEuPE19/G3uvlgX5QLL3xmB7nt3IUHvtTjXZwdWpQ/dPOORi5djc78UTsPER8Q5YuqaoOxaSOmAdMXwheAgY6XUhajM5ZpETUULwc4rUrKfOaN1RS0102bfasP7NQIi8o/A04D7iMgNwOuwwf82Eflh4DqgE59/L3A68BVgBXjV/o4/4MDD+8Txx1/PaDRly5aLef0bLgd1fPjDWDqqMOWKxeqZMmOVWnqQVQbABsFcm8+UfwRKPb5kQJQ61Kj3TGcNsWmtJ0ADTbJilpQjdVXj6Npri5ZfkdNKsS3NOA6NkRRtkPrgSSqm4VdktlJu+9keZ7UBTbJBTxl6phxsg7EKRaizFBn5UhIck/YeUJfiWwwBFtOCXX1AZwA69B2GnQvfvZeuEMlSfqrd9S9FTphRTTmbTkOp3AQlJe17Frq1EYHei6iriiCetm2s4av7DWOi3c/9sV8joKqv2MdLz1xnXwV+Yn/HHHDP4cgjt/PSl/4Tf/e3t7N9O7zzXMc112K99ilRVzWUWDZrsj74wo6bEXD9DDfPk89LZDsJLg+FHHTEtiVnx2hcM2saYhsZ1bWVDHuHtpEcjcgDIxEpFYEpRpyY6IgJeNhN7rxDihxQViU2Dbo0YlTVHLExcMf2O0vqMhG8N/2DrCRSz9x71xXkWIejqs223otVBJJKOXBJ0a25lmtJQVU1wlG7DMbqMGFefShzQ1BIyJx1lTehOaPi+tdiqazsDLDxDdpzI+YwzfmQGCNVEDYuj2n27LaGKoTgvK2o7Pw+S4eHsuF7OTZv3kFdr1DXiS1bMrt2gMcEOT2u7wA0bcxyIztngp9ryLNuMFnRmr0W29Zq7oFuCS5XyKi6CrZAZ1Zim23V3VlD5TwbRmNCWZ23KSKgWuKCrOaCOxHG1YgqVH3xjAKajID0wZPbRDNr+kHWtpEKoRZrSXayIOCB9AYu5Vx6BOaNR6gVSdl3zHu1DK81AItZgUVSs7tenSxYvz/0A3tthqGrKSjefslQLByve1G7rVqKOq32wYyfMB57NtT1/PgZgliWZV8YjMC9HNdddyJnn/1Knnjq0/ixH1c2biz6d7nMT93MpLa0lwlgWIPMItO91t3tnFcrMPLmQZQ73gdPPRrTzMwRTbFTznUlX6+9AGnWXJSApZ/lVNWUcQozXoUwJ+qL9remRGwjk8mEB9z//mWh0DKIspb0Zi7fsxu05q10hkFYPWvbQC0lwws5r8Vy6sXwoGPwLWW3d+1AxwF0KT/HfMB1YcmqPCRdyGD/HAueh9oZ+67bs5xfxyMIto7BdDqj9qEXLkmaaGJj6tD7wGAEDlGIKCeeeN1+97vvfW/lgQ+8nu/6rg/zi6/13HyLtdEiJrPdZiu/zblwApjyjvOeKlR7lcqCEXOarVy4Iwgpg8MXMcw2mopPcJ6N4zFeoR5XjAqbX408TjLBO6pQlapD6/jr+AHnhOlsiiiE0LX9mjVQJ8ymDSrCbbfc1A9M7x0NmUYTbYq2UAjapy69eCofrHcAbB0F7WZo6yysvMd5K8LpuIJF9t8vMO2dUVivQaczBKO6tvBJ7fO041B07t6bFFnHN8wroXz32M1/hxCCGTQxg5uLh7B952527Z4ymTSlTDmTneKqwL5NwNBAdEhgNJrx3d/9fhbLMXJW3v9vWzn55Odx5ZUnc/zxN/LEJ17EJz7xFJ785I/zqU89ibatePGLz+Ef/v4Wc+FxpQ7fGdnmrJikk/dyTrAVOKPNXt6hsWPEu1V1pJ9DExmTw1bqygb3ZNYwtuVwcB5GwRbknOREamOv7OOyKwuDWJecCH0NPb0hCqCm0NPl1V0h+rJCo4mgoZ8NVdXCDymKRWWmFUcvnWaFR74M2m49AcE5LTX79jzlbEZnwc03Y9BxA5mF2p5V+6xNFaayXFn5plBEWrXfR3p+xLyNhF+sSiw2uARDVivgnBnO1uTFkprBJdnA7/oZci6Kzl8DgxE4BPCKV/wjl116C69+dWCyZ8X6y3HcsU346Z8+lzPPrPn4xxpe+pIZv/KrV/LSlza89rVXsXnzM/iTN97KH/0h/OmbPLt20OsEZlWCBDLJimM0WZTZFaf0KTMb5J1L672jbdsSB4vNSipUoWbjhiXLV2tGvCkBxaJFkEuokXOiqivUOZwEfM7EmPBV6Hv0LeVmJF/t63k+XUGLEXNiZFjMiZXptNzowtKGZdqprc1HyY/HsspPzlg3XhH+MgOTjTuwXmq0yJBZtoPeuCxmR1TpCcQOc85kddjknCst1+bqW/O1lArIuReSFz4DsVWPo3ZCp4spSe37APpCpPI5rWZG3vceWl+QVMjGfWEwAocAlpdX2Lkzct21glARC7HlfeD3fi/ze787Kf32wg+9aor3jp/6qRXOOuvd/Nmf2cx5w/VK8EaqIQ6Ps0J+7MZNWRHJfXi6eEMLpQdeistfctRdfGqttom2acmtLQpSV95aXHOidoEjNtiyZBO1WDo1La4o+4iYZJidg2K9dtZLIJWlEruqwc7pzkUBKBZdfu8dKUPTtniBpo1IVVp3XeleCELti1IvZtycdoRc4fEXXH+3MMg7VSGrlOzIUXttcfZf6wn0/Qb2om3vyQb6v6u9je7zpV/5qNuxk1Vf5BVTURZCiiBJLHoFUrw2xdZa3AcGTuAQgc2ikdg21kjjymq7ybrzUlq4MdWUcv7Pn1ngKOJBTeRCoLTWay/20X9GXj3DrJrZCnsei6oOpRqPlPBqcW4QWx8vpkTbzGXE2mwVeKgpBXmBpcoKjIILBBcsJQYLM5ade0yRpm2IbWsqOb1hmrf+5kxZWFRpZw25iG1YDYOiydYLCEUl2TqMzbupXOj1EdvWuI7gQ+9Oz3mA0n/QMXLsXTzVYS2HEpzvQyhxrpT+0XtXaw0A2YRVF38DKSm/4pStyU6Yceq+k3eClOvoncM5+I1fX31OixiMwCECKdZfy0/WNq2l0OpQFqgEyFTBblbJ0K2imWIss4I14FifPSVYNreaUtgCC7FsP+uVXD1S0m7g1ZqFxImp9ZKZzlYIwW66VFSI0IR3njZFkISTjPNi6wh0kuPQS4xB16dgsuNttAaYmKO1L5eQxVJ8XcFMpnaVLSkOtFlxeKR0F3YD0GVH8M6MgZT1BICR8xy5vBEvNmDXegRdKbFzbtXs3zH2i9do0SOATvV4YTViuorBIpBa/klHeqqyvLxk8XwhA7vZPGCrENWhskVZimaB67IJ4jji6KOgqDShyhOeEPmd303c//j/ss97azAChwi65bFjkfnuSk2baDXuHbNsbbZSWn4Lm+y6/H+39La3DrU16SyYu709H0CnhWeeg3Ol1diHvqilk9tu2paVlQmxjcUbyTar5VzWBygNRGU2m2sK5j5utvOBeZXiohsrxdWxG15KbK7Mm4y6eTqLRf6C4vz8u+WUiUXNlyLS2WbzpLz48j3ncTasjfcXlilbE5uvh5RSn3pV5tLkWp4rpUKTjgS0pdO6Wv9VXARCmyIx2ZoKrlRoukJY5py5Y/ud9rk58/KXw3kfzJxx5gPZtm3LPu+tgRM4ROCdIzhTjrVBa2RRm21BUOlu4BLni4AXZ0tjeys8UTVJq+4GZGFWW7u23noNMoKWnL2VBE9nM7SsupvU1tsDTxuzqQdlExXtKndjGwvRKIQiOV5VFXGWrBqQrvpA1/l815NonS5fKpkNESPQtFt+vAiJ5Gipzk4c2BSRHLjck22WS1d0NsEHX0jMSLca06K7vjjLO+dK66+uOc8117CQrGvTjItrGnaeQvf6dDrt3995B1bPZGKlLKyCbKshFIMoymw2w/uK8dhxxosc7/jn/8Ltt9+HnTuP2Oe9NRiBQwXOZnLvhKTSx5MdoT/Pk5cmHGyNgJyizfqt9dPnUl3mOk29no2393c97evNboqx/SF42qLvD0LMFqRYNKEEPOBK266SQqaua1vdByWLgFNSUxbe9N7ShsVa2CC3VJ32Ap/mMtu5zdNyrjDfuV/mu6uicdZjUKS9bKUjWyrcYWk71AhFQciayFFx3vcz/GI83qEbzGtj+cV9F6+bl9LoUyzYIqO/yG/owvG7z85FpUlEEO+477GZ8ThzzbVd81YJJQS8V15wumkxeloe+4TNrKycwdatJ+731hqMwKECse48zZmUdFVaafEm7WYwVUqsb0y5Zy7qIQszT2cA1t68uubYPU+AZRhSanuhkE7S24k3LgBTuq1qz3QyYzoDJKGVlfKKc8wmMwKeto1IsNy5FDJPU9d8MyfQbBiZgahHNdOpqSBbeCM05Xy6fgARLVkMkzATLKMQQsC1bUkdZlAl+MAsdd6FeVYWurhVA3zttVn18yw8X+wy7JqDtHyP7v3ddbemICFG3etad30GCozqxF/8pbJxI7zsZcJtt9n38cFKv3/2f3qe9KRn0kX4d9xxDNdeu38DAIMROCRwzjkv5oEP/GvqjZk9d1gxiZYCk7U57MVB3W2z6kDBFuHu78X566xOCe7TMKCQ7TZbXhr1BF7bZsQrIgnnTCos5oRkqOoacYqXQNupE1VFSbdbQcgHHFOCE2J2ZNc1zwAlfHeuMw7WtBOClC5AG8y2hkG3PoLpF6oHTd2ZW6gUNVGFwKxtoesczKbhn3Te8GMpytVLjXWPpSdT976Oi887gwysa6ztmkvfIbjoIfiFTAjACScIJ530YLZt28L551/O+98f2bABnvQky2R85jPP4zOfOfnrvqcWMRiBQwC7d2/k9NMbzviemr/7O7ElvNKcTFt7k/Z/F91nSihJt239mWzRGCy6qx0hZzNrLspBgg8BtO21B33Jodd1jarVMngPXjwp2gw98p4wqmljponRXPSOLY8JmOsKSllzwFYhc73uYeWL2lApjMmpy3jYGUsZ9F1ZrsM4he66VC5YuNI1/5TpuuNKvhbZtzYDsPd+5resrRlYlPharwCpv8zMw7Juv7e8Rbjyyodz4YXfCjyXE07YSttW/Mu/3HUJz8EIHALQUvLaZpOsSgrBeyTLwj6r88ZayCQpd7V2S3wJLJJZi95D997FY3RNNqrZ9PmKizudzqhKlV/WLk43EYzC8ZGz0uSGDdXI6gREqbzJhgXniBIZjQOpzVQS0GRcuRcTCVWwElm1EmVLydnpazLtwpRTt653777Pi3nKuQuk8kZRRczOlDSbeSOZ1HMN62FtQdDi9dv377Z3uLaPo/e/iSww/QBV5Xj5y4Vrr30WV1xxav+OrVtP2M8xv34MKcJDACsry7znPc/nIQ92jOsRTjtFmgXCClYR1QJF49dSi7kjkvaagXSVKs6qeHRVSLFAhJWagpTmqT/U4vkgZZXh2YzUJuMPijGR0t3nECZNY1kCZ3UH41FtLn02+ewQQtHuzySNVusv2nMHdVWZTqEsipgWubNusJbPtVRkspLjLMQcSaRCFpbvS+EX7AvPK+7Wme3XXpu9mP9VKU5WvW+xpmD+nvnv0nVuiggPf7jwyU8ey0te8hyuvPI0VPdnTL45DEbgEICqcOONx/Mj/+0Ijtlig6ZbqaZHIfuc2LJd3QzeqdE4WT/+X4u1s5xFAdLPsLbWve3T5dOtAtEMQxsbUhGxGFVWNz+btox8IHhv6sBS2l6bWc/ee+9pmrZ4EUrb2mpGy8sb+3OxtHgR3ciZNra4or6rYj2QUtb060hP81yKRHkZhF0BT3DeNEtKs5CI9FLe3Xjb17Xqti/G/Nbdt7eX0O231itYPO5i1gDg1FPhn/9Z+MAHXskXvnAaOR+4oToYgUMEN998HDfe+AD+4A9avO+abfbeL2sutQI2u8Wihb88Hu3TLV3vJu9nNyjsdjd7lfi5fL4rZanWkKP9QOoKa4BS+tvSNi0p5bI8uLB5w6ZSPVfEMdWMwWi0ZKXAMdOUxTOcODRL7+0kTagsKu5YRiTFSPC+76zrmqW6UZ2lK/hRq1qUEiLJ/NiwWqJ78fF6DH5/7deRGev+LkqUrU0xdtuqCn7pl5QLLgj83d9VbN36bNp23+sF3F0YOIFDCO95z/N52cuu4OGPaLj0Ml+Ucew11e6mkhIPU8Zg0fRfU/3WYe+Zad4dt24BkVgLq/cOFVPiTam1EtaSGtOsaIAsggs2U8ec8KEip0jTtFRVoGkagvckJ0zbxlYYKi55cAFQ2tms93JiMiESKYUzWY0/6MaxLwO5c+nNeyjlw6qoGGE478IzAVCrC3C9HdiXUVwMmZybVw6uvVb7IhXXC7UW933hC+F1r1P+5E9+lB07Nvdc0IHG4AkcQsjZ8cAHKj/yw0oIvlToWQy66LaKL91naFm512LiteSW3Yirn0tx99djtaWk9VJOqCwW1NAz713pbquZNqe+yQmEUBXdACl1+0XRqFsSLBdpMs3dCshd27DrJ2lVLRJg9lwciHf4wi10KT/nTVW4K6fuPljwhczUXpC0k+iS0mC01vCtLRpa+3e9uoG94/69sZaD8V649NJHsWfPBnJ294gBgMEIHHI499wzWd4ojCohlzRax4R3N2InYtktqW081/qzf7fvnOCaNxF1x+xc2bnOn5Bz54qn+c0spjEIuV+PIGeHJkfb2sIlVV2RSmeg6oL0F0WOuzTVJLVy2OBCz2/APBSZZzNM6agUSxtnoNY34JzfqzOyq923PgIzBt3/7jp18ftaLA5s16+zuHecv55RWMTiuoMAmzfDKafAq171SP71X19A09Rf381wN2EwAocYbr31vjzz2Vt42jMTXk2gc18FKSLSNxlN29hvg72JrW6bGQVW7bP4vu5xN6BSyeEjnZKNhROue38pa3XeNANMxdiKiEJVW9wuOvciyufP19qjVwECEOcYVwtCmpgHEEuWIqstL96t7deVIveufF8KVJY3VxNZ7T5n37n/vb/72ozK4m+wmDFY79p1rx93HLz1rcrZZz+ST33qTGaz0dd7K9xtGIzAIYZduzZxySWP4n/8jDJamq/6a8FwtyCmFgZ/nv5ae0uvvknn2xarBdcrIFr73HWlB+ZI9xJanSBHJhNRJk1L05qmgPOeadvYugCVx9emmdct/oVa/799gwSL+n2iJI0L5wKhFAKxitszNz+lvJfBU117Pcr30fU1Fdaiu07d48XrsuqoHVG6zvbOizr5ZHjBC+CTn3zyPeb+r8VgBA5BXHTRqRx37AN42En0JWauTwu6fv3AniSDPmZf/L9KtmthG6x/Qy/+7UMPncfdav2tOG9kWxMTiC0AqiW/n5LF+a2WFY8zzKYtIhbna06k3GDDP5Edq5h7EWuh7oyXZtMbKCuIG//RLym+DnsP89oc3ft7dt2B3Uy/XqzfDeDuIOtxBN3z9UjAxWPu2SPccgscddSdX+snP6AYjMAhiBgD3jv+8I9zP3su3sx9rUDpPFx7I3ez/HphxNo4d+3fRezl6pb/MSXaki1wojg1lV9fOgZzsorBUV2bNuGmjYgTWw05WI98JULlfFEDnPcSqKaSCShrIuQi5KlqCsismXnnaZK9vmM3gHNX58D612Dt952/ttqAri0iWms41xocEeGzn1Xe/GZ4wQv+lW7dwnsagxE4hCFgWQJnZbbee2slLRr863EEXwuLsS7Mu+jWHmM9o9KlF1XL4Pcd417Ui4oS0NLyRmJUYpusbDdZYVFd17bkWDm2r4IJjTpPKMKinddiklkLsXdH0pXP6s/PrY6/fakfMLIzLZCRrucfWDNzr/2/9jru65ruyztYvNbdtje/WbjiihlPecq/49z6qwQdSAxG4BCGYgRYLimAbsUcWxrc1vtbZP/3ev86Lv4iM76W/Fqc7boB2xkA731RM5ur4iJCGzNRBXWQRNm+axehDuRoLbtOoF2ZEdtooQLFaKRE6uTBzKXpib0k1hdBLpLh/ffByqml6x/IeD/nRrrOPxMeKUVNhQ/oVzdi9fLja8OjtYZyb+9g39d28e+igb3mGnjSk5Tf/M2P84hHnE8IX1si/O7Gfo2AiLxFRG4VkUsWtv2KiNwoIp8v/09feO21IvIVEblcRL77QJ34gAWCaqHIRcSZIq8Iayepjhxbzy1d3GfxRl38uzjou+fdMTvD0B8HIwB9Wf5Ky8Bx3ojMDctLxDYVjgCqouUfUzTpMHGEUJGdw3lvDVNSSpNXdQza0O0UizqTICImEML8nFeTdN1CpQvejbAX4bevUGrttVsvJFi7/3rhRbe9aeBDH1J27vwkT3vah7gn8fV4An8DPHed7X+kqo8r/98LICLfAnwv8Mjynj8VkX0vgjbgboFz85AAuvX21k9NLWJf7u3aSsG1N/bquoLOJZde5MS6jGWhyUnLgpiJqgqlIMdR+cqIf83UwVYGisUbCL5CNZFUaVNeNdvbeaopGS0OMsy1DyGU1mSrAnTe5LiFtTO7fM3rsigqsl5I0L22drbfF6m69vHi+7vjve51wjHHXMJoNNvrdz5Q2K8RUNWPANu+zuOdAfyTqs5U9RpsifLT7sL5DfhasPqcBfd17vrmrMS4KN45d5PXYnFgdK5uF1Ysvn/xZp0z5Pb+to1F6rto98WSp0cY1yO8QFXVzGaJlB0nPOQkQqhKp6OdV2xbRLElxDvmXhRxq/Py3nfVdKVfoBQs5VIb0ImXSkkTareakO49k68dxN3jxc9b3G+9UGHxWHv9RF/D61q7TVW56SahqiY8/OFf3mu/A4W7wgn8pIhcXMKFo8q244HrF/a5oWwbcABQ6mlW3cRdL/1ibL+vuLQ/zn6eL2JxcKwKDaD0EShkm/lN4FSZTCf9vjG1xNiy9catpKxkp6bvh8XzjlIBqBnN1hCkOaN5bpC6Qd99f6AnCrvHUEKQwpeIzvddy+Kvxb5m7sVt623fH74WOdid0w/9UGY02sAXvvDYb/j43yy+WSPwZ8BJwOOAm4A/+EYPICJnichFInLRysrKN3kahzlEqHygcr7cULDo4i6ST4tu7b4Ptz7rvd5sZiTdHL4IdHpnTUMpJ3Ky9QFcx/qnhBMlayQ1LdEJRx53LEsbN/TfxRVuwYswqiqcE6rg6TIDAKLSD/Su0Kd7LYRAKqnC/H/Ze+8oy+7qzvfzO/nmUDl3jupudSu0RCuBAiAhGytqngAAIABJREFUyRLYgDFOGB4YM8bjt8ZjP683jzEez2JsL6/xwh6cnsfPFjbGBAkESEgClIXUakkdq3PlXDffe+Lv/XHurbpVXdUtEwQN9V2rVtU99+Q6v332b+/v/u4A/CA8B1GXOr+YYVye0w/qMZYGIWq5F7H8nlzs3jbfy5WMiECQSEje9jb4yldW7xHww8D3ZASklJNSSl+G5Vd/zaLLPwr0Na3aW1+20j7+Skp5tZTy6mg0+r2cxk89JPUHXIgFtlvzW3q10la48GFcKa/dvN3FBwALPQkaHHwahqLO1ReKgmVZYfMSRcOMxuns7KJSKFKt2WGFn64h68FOv+Fq1zsoNejHoefDAr24katvnPdStqNc8BAWrqhp3SX3cpkBaHgauq6x0KZg2ZRo+fYr35uLG4aFuANwxx1w//1Qq1kAbNt2nF27Xrvo9j8IfE+lxEKILinleP3jfUAjc/Ag8IAQ4k+BbmAz8ML3fZZrWAUCFAWvXozDIt1lyUPZ6JzTSBeuuKeLBLUueJBlSEVUGx4GjThCY2DWXXVFoCoKyADHdUEE6JrAlxAxokxPTILi4cmAYqW6MPgb0wEFpa5iHAY8w2sRCBlmEgLZ0BFYOn8PFYpkSDmu35VGkxKEqH9u9GdoLry6MCAaj0dRRZSZ2fxCOnE1rBRbuBQWjxdgaPDcc9dRLsfYuvUEb3vbQ5hmaAxfe23X69rf94JLGgEhxGeBW4BWIcQI8F+AW4QQVxIayHPA/wEgpTwihPgccBTwgI9KKS/WGn0N3ycajUnVunvuiEYDzKW1AReLYK+U2lrpgW58rypKmOpDwfX8sMGH0rQfCYZuQL26T1FUNEVBVRRcx0WP6ZSKeWrlEpql4QQ+qq6EbcVlgC99FC0sD/bcAKH6aI225YGy4L+qKPX+e3X57XqK0nXdheYiiLDVmBR16bC6eEmYCWxE58Nra2zfbAz6BnqwIhYzzx5cuKfLswINrJQtuJQxaBwrm1X4678NePllgaZ5rF9/ll//SJV3v7uFSiWKadoLxUW9vSMLXIKhof7vW3XokkZASvneFRb/7UXW/0PgD7+fk1rD60NDjQcaJbxhqk4uF9qUoXrv8jddMy5wceueA00PtBByIV/v+T5ChoPW80KtAkQ9uCcUbNdBFZCIxUMPXIbRf6lAJpVC0yM4tg1SopsGQlFwqjVUVSCliiLqxkQTSCHQTQ3H9dG0xdJpX4Y+h2BRCKXhhSz2VwhpxQ159rDisWEIGlOJRU8gvF91gygE588PY1mR+oAO7/GlBn9j2ev+P0pJtQqf+IRAiOe4884iUh7m5YMqzzw1z8+/75+49rq9jI3tZ/fuV3n88ZeoVGze9z5JT89tPP30gdd9rJWwpix0GUMg0DUN35dITYQPeF3Ao/kZbDybi1V0l0hb1RuWamrYckzWRT6VhQh/2AY9kI0OOUp9hhBOE+pDBSkFpUoZRRFoio6qqliWCZ6kWJynrb2d/Pw8qmHgay7CDxAq6Koe7kQD4fmg+hjRBJ5towiJt+Bt6Ni+jyb0ev1AaIxEY3ALsUBSEo0KI9HwAljwDMLLX2GOLwNy8wW2Xd1NqVymWq7ie4viLM3Eq2bF5hX/VyvEY5qX1WqCT30qXPbgg0coFATjY6ACf/InGtt3HOLjHz/Dx/9DiWMnwLYVrr02YO/eUxc1ApFIFc/TLipTtmYELmMIEXrGXtCgvS6WxCJWd/lXm/eHD/ZiXKExZ26g0QV4qb6hbFqvYSgAGZ6TJxU0Gbb5UhQNEQjcmo0MfMq1Cm4QYGoKETVK4NhYloFpmCiBQJgW5fkS67ZnOHd6GsM0cG0PXQsVjVVNAc8JFYIa8QhJqLAsl7r1y69Zrbd2D79j4Rqa70Wjx58fuAT4SyuaV5kSLL+nKx27sf3y9Rs4dqz+vZQIVcWXksNHBB/6UKGhiVo/vuCFF1an4fT2DtPb+wDr1/fz4IP3rLreWu3AZQ6hhGK5CmIhf84SLyAM2L2ufYmGelAjGh40upfX3/SNIiVR/wldalVVUNV6Xz8BmhJ2Qtbq7bFVVSURj6LpGtF4nHKlimWaGEKgA7FYhGgiQXu/wcYdEX7jYw47dib4zd/Kkeky+YX3Oew40E4sYaKqCoaqYZoGpqGjCPB9b2HQLuiPCJZQiJdkQQJZFyMNKxZXWkeIsLYgkAHDR4ZQ9LpXUf9+Of36YnyDcCq1/PPKRmDJOcBCoDT0NOoKUTL8/jOfkbzlLQ+xffuxC47d3z/Effd9gY9/3OaVVwZpb59a9f++ZgR+IuCH0XpNW2hf1Zwua3ZVV5q3qmqoGKwpClHDIGKYRAwDrc62CxqpOMIWYFKyQE2WEHZD8sKfIABfhhoDuqpiGhqapmLGLFTTJNGeIdnWiit9zFiEWEuE1oEot92R54ufL/Lnf6zQ2nIbn/qTAhH9Lv75n1y627fwR787y5U3t7Lj2i76difYtDdFV28SM2ISjxvELB1UQUDYjCRsVd4YqGKRVq2G4qI1z1uY1iyXCltIFYY3iVrNZfNVW0FhoZqx2fVfSWBkOZbGaC7ULFyRSaiEhkhRw3hEwwNQhEAVCk8/aTAxXqW7e+yCbbPZOTKZHLmc4MMf1gmCz696bmvTgcsZIpyPK4oGCviOQ0N1ePmcc7UHdKGLsWw0v6iLdAQBmmngOy5ShvX7Xt19XlAVXsHLEGJRqDRAoiBQVY1q1UYoKrqiUyoXiJsxFE2lrb2VG67P8R8+PMPDD9/DyZNhP73BwR0AlEop7r//C3R1zfL+9/icHk7xwnd7aE9aDE2WmZzME43rzE4XMWyJDaAsNvEAFgJ6QoAqBYqqYKk6ZduuG4nmdZdmQhp/y3qspUFOWlh+CW9geXaluT9h83YrpWIDuSjr7nmLvSEbAWHbcXnH3YI//MNx9u9/nlwuTa1m0dk5QU/PKN/4BlSrUC4HfOAD1RX//7BmBC5rKIqK0HSEcJH4C91tYWUq8Gouq5RyIQioqsqi+GYQinkIQldf1v1suTA5XnyDaZqG73vhQyvC2n6JQNV1vMDHrQZEIgZ21Q3bmxsKW3fq/NZvDjEyfAVf+MJNDA/3XXB+jmPgOAZSwk3Xlnn7m4t8e4fKI09toiPhkBk1aG+P4x72mRkqhZwCRaDUOxmF9ykMCgZBWIfQ1t5KV3cHB188HF7vRQJ6DZx8dRDTMrAri4U9y2MsK/3dHDhsnkZcEH9o9kCWTE1YMGhLjxfue2RE8MlPnmPXrrN85jMWUhr87u/mmJhQefllhVpVBRn2ZPRX+P/DmhG4rCGlrEuJhy54qFN/8TRggzew9CGtl+DKIGzw0UizNaYTIqTcKoRz1AbppkFCEkLBdd2FY0QiFooiqFQq6EYUWX8IhabiujVSSZMr98JHPuTwzUc/gOdpq+a6fV8lCBTm5zNMjg+wa/dhRkt3IqIjJOM2nRtj7F6/iZSY4WV3iNnJEp67lJqyOHhACcDFpyRrSOkTBPWsAYsGcfmbGsApuLR1Zxk7M3XBAF7pPjff7+Z9Lw8WXsqTCJevvJ4QYRD3zBmF06cl+bxDd7fNAw+ohHat7uU0IqarYM0IXNYIC2uECMBd1N0DQIJQw7RhI+DXTKdVVZUgCAOJYUXuIsXW9/16oE8HIXC8sBegWtfpRyx6CiGdN1hMEyqhgfB9Hw0Vz3ERqiTb2k61UsGxS1y/P8LP/2KSp5++85Ly2lu2DLJ+/TkAstl5jg/tZVPXLqpVj9dOTBPLGmxevwU3sJmrmAS+pDhTxQm8OoVZ1IN5gBZeq12qMHveqzc7WTpfb2D5gNUUhVRLnLEzUxd98zejoVe4EgnrYmjEcJbHb1acNohFevhjjzWvG8Y7Qs8ulKHzV+HtrRmByxSOY0AAWr3/HqqC7zo0yCyNFNNyckvjTdeg+IaBxPChUVUNTQ3FPIQQeIHE94O6FFfobYjGfLvuISxMEQjQNAUhwxRgIpFASXgIVFJpiy29GW6+w+emm3OUigN898W3vi557ePHt7FlyyBbt55ACDg7vJ75WgklkkVIwZ6BTZwcH0UkTHo2d1KpTJDs1ZifzDM/4uMGom4IAoSURJNxzIzO7FBxScpv+T1qJgcJIfADKOQKdTJWI1W6ctehxu/mUuyV0oXLt1naVflCr6HBZ5D1jEuzUWhst5DqFWrotdVjCP5FbM9aduAyxRe+cD+plMr6TRIRBOiWhqk3CCENF1eBOq+/OR3WmE8KZNg12PMgCGsBlLpngB8yAT0/JARpmo6oc/uFIkAGiHqDEJBoQiWdtch0KLR26dxyu8nP/KxCS1uU296qct97SvT17+fhh3+L7zx5P5XK6ysaq1SifO5zP8eJE1sBUBWNqdlhXj78NBHTxIonmCtOYugamqmQWW/Rsx16ek3i8cgCl0JRBIpUqJYdsp1JpNdIgzamRCu59Yt/+56H6zpEYnr9u6VTiAu3XSrZvrwXYWN587qrTUUa/7OGp9ZYp3nQL99XECy2nBcLxnplrHkClyk8TyOXv5r77n+ZT/1RGL0OZEMGG9JJi0LBblLkWXy7NBR5G204NEVBFdQJBwqBDEU4fT8AVak/eOA6PkhRz0qAZmjEYzq1qsPWrfDx366hmyAUF0PrQhVp7rztRRSxg2JxgKNHt35P1yqlWPAaIlED/CoJFDJ6lMmZAp1trShSoBsqrR0GvqKQ1ltxaw6lQ1O4rsudt9/CI488BX5AIppCUUdDNiTQiPpfaAiaBnoQEHgqesRClJwVznFlAhZcnBjU+BxqMfhLpgHN6yn1cvGGMWnO0Czf10JsQ14oJbcS1ozAZQopBcePb+MDv3aQ55+VPPJNB9f1aHTf3bk9wcGXHWpuOIB9v5n3HubRvcAPq/SQaNriQ6WoCopQ0fx6T0Ppo6oGhqbh+gGKqqCbCjuuMNB0hdycwpe+XObc+QN897vXAFCtRvA8jURiF+VyDM/73h+1m2/+Njt3nqAwfQ9eZSeGMUEm0UJGM8nNnyCS7aVUcHGwMRICu6JDTDKwo4Whk3koCvbfuoNHHnuKQML05DyhdFHDJV881kpv1gbtSDUjoLj1+7/64Pr31A001m+kDlfLOPh11aYLpwuLWYTX51FciLXpwGWMkZFeHn/8Hv767xRuu1Wim+EbXUHht39nkmxfAhEo9Re8ukgcAhzPR1dC+qyQEEiB54PnS1w3oFK18X0fz2/4zWJBNTjwfW5/q85DX5b8zu9084Fft+joCgd+Pp8in0/hOAZBoJDPp74vAwAwPNzH4cMHODKyg7IfxQsUsi1dtHafZWLOZnT8BEPnT2PoGo5dpeY4KIaKFDYtHVGMmM7nn/gK8WwUhGD8zER9kCkXj7wvDGaBEqiohosZWxzgy1u4NaPZkDS/nZdj+ZRhuRew/NyWD/DVuArNqcnm46yENSNwmeP48W1885v38Om/8PmXzwa0d4KiSP7yf0WJRuMLc0FZ59OGrifoqiAgVM0xDT0U+tR0AsJWYoEI1YIVEUbQHc9FCp8gUIinNH7pl1wef/wdnD11Bz0tb2Fqspvjx7f9wK9vw4Yz3HPPg8Asdulp+tprtLdN0a89z+nhk7h+ieJ8hWTaIBnTwVZpa+1F1STJpMmevb1s3tWGdF00Q0H64NXCgGijVVo4QMKflYg8jfvn1SQ49SxJU1BuJQOwGl6vl7ASz2P553DRhQ1PVsxGXGRWsDYd+AnA4OAWzp37T9x558M8/NXXuP5qjZlZj8/82Si/+AuSodFmrrvEimkoPtQqoRColD5qoIJQcAFfSvxAoiqLb6ZGL4OoAf/x4wqe8zaOH9+GlIK5uSwnT26+aKXa94rz5wc4fPgKnnvuOvbseYVNPX/J+p5xDj6/lfLZdvR4lcBX8aLj5N04ViRKLJolZqhoeoSWgc20dM3wyrEjBGoZTVfr3o67QCVeno5rxsIAU6BWdCi7DkEgMQw9nH5x6QG7UqT/Yt+vzhdYziqUhO3bVhY8XTKlWZw5XIA1T+AnAI3A2bFj22nrMHjrXZJPfsLj5lsCfvED4YOi1CW6hRAYEQ0jomOoGtSVCAIRzv+jUQvLMNBUFUmd4lqvIkrG4nR3avze77uARnMDzR+GAYCQLPToo7cjpWDDhjOUyr18+ak0X3hVZbpWpOrWmMtVcAIbxy2gmBUq81PY0qa1q4c5d5Z8ZQyhBsSiMayEQFHDwqiwWxIL5KmLzqMF1Mo1XNtDVQSGoS8J/K3GBVieElxt3eXrLceSGMECdVlZoG03n3vDuK0WmFyONSPwE4Tjx7fxrW/dx59/Gp54XPDssyr/+q8Wih4gFdDUUOFHCoHUgpDb36AJCzBNg8B3iUUtNE2tcwFg/1X7UDWFdCZCS0fLj+Ta0pl5Jl2XnPMaT50wGZ4aYSI3i6aHqc+MmSQWMdE1g762LvSaxNMqDBeOkq9O4gc+hi6wonpYJ1Hv0SCEupAKXG2wSBmSozzXw7U9BBKvzpCEpU1amt/o/16S0KXWWWnqsTyw2djP62EiLpz/Jc9sDZcVTpzYyneefCfv/6UNHDpk8H//rkd/V4R0NE42ptO5PsG+vQbtyQBL15E+CEXF8zwqtSqeG+B7AZlUEkPXcQNJpDtFMhFB6Da33upRKCQoFJJv2DV1d49x021fYmICvvaYQJ1XcN0aTjWgUq7Sv0kSSWkUvAquUDg89jKBVuPI4GvUqi65gsTO5YhkDGJRA3xoZFM9zwtFWRYCcytrEAgg8AJ03cCKmAvbwFJFombyTvPfDSbmvwerxRoES0lGzUSh5cIxrycGsRYT+AnEiRNbGRzcwr59B9m+/Rh/9TejzM6IUJPPqmFqvRRzJf7bJx2mJ6tUbQdF1cKAVxDgOA6qHj4a8WSEkdEZsu1R7n1Hlauv3cqXv7yOc+fWvWHX86Y3Pc3J4TTCrzJb7UQTQE1HI4BAUq3o5EpV7JxKoM3jOQ4FtczsuEPCiuMXqniBxsC6NiZciTlcpFbzCMLQaChKsjCAF4+7vJJQBBLd1DBMQbniXpBOXD6dWO4JLGRnLlGwtFrAceG7pn2v5nFccO5i5cYzsGYEfmIhpeCll67i6NEdRCJLy0ht2+TWWx/jf376KB/9cAw3iFGtBASeT61aQwCe7QKSeJuJotZ40x0+b71jK6+8sndBEvuNwObNJ1m//hzKhODP/tFiqjBBSsvglAIwNWolj5z00C0NoUqqtQKmNEgpUfRYitmag6YKXAVS6TTljINpzOC5oUwZASENWDTuW4Mp2BiATQNMaBimSkBtgXQVbrOURrwanRhYqCVYqQipeVnj86qQNJ2zvMC4rCYltxLWjMBPOKrVCNVq5ILlDz10NzccgDffPsvg2RjrB6Z57XASRekhn5tDSoWsjHPVjTqxSBTPL1GRL7PnTUfY2Jnmi1+8j7m57A/9/E+e3MwTT7yZAzc+woZunakZjdbeUYbGE7SKDHnFI63HET5UvBFS0ShZ0nTHdjPdUyU/fIxoKoHqCCIRgWkF6KoGiov0Q/ajpgt8P6TlLuojLKvtR6G1JUFrb5Kp4WmktBdk1lajAcOFMuaN9Zq3ac5QLK8DaN7vAi5hRJqPq6qLFOPVsBYT+CnF9dc/y6uv3czd97TTkimS7Myy95atvO9X7yGzxeS2+6/nyhs2cv3+Au2dE4zakr/9fA8PfL6H3t4RentH3rBz1XSXv/lSimeOQNWBjHktnmPwrtvmSMVa2NS1k5rnIiwN1dSIWF3M2TpVewhNdwk0FSvhhAFQxSaSVDF0FaGoUC+FhpUDagsDOAgY2JRlYEdHWG7d9BZeLa23UuQfLqw+bPxeadCvlF1oHtCrZRUW96vUA4drZKE1NGHLlkEOHHiaG298ksHjB/jgr6kMjyeZLeQ5dOwlolaGialppOZxdOh6Dp9PYXguXRmd3//YELWataJ38cPA7t2vcutbHmNw0qY9nuZjP+vy4OPnePfbVR47tIV4Io3VNo/rFbHzNYr5GjPOPOfPn6Y8NYOeNzFqLi0ZE9s00Q3ItMYxdS1shqouNi8J35yLSs3Nb1td1/GNGrZRBNnIAizrzCzC3gUXSwU29ts8JWg+1nLCz0r7Wb7dStTixrqetzKXoRlr04GfQgwObuH8+QGee+461m16lH/8YozpXI7u3g4q7jiu45FKdGLFWgl0i2y6xObeUQxVJRETfOUrdy3IgP2woWkemuZz8w6bhGpgV7N0thlMFiVj4+dpT0ZxRYJ4VGd01EFGFKzAgXSFpJehvW0fp57+FomIgVu1KRdsYpZB1FKpOgqeG+AGzTX/oRFY4sYLAQTEExE8u4ofeGFfQ0WABBUVv97tqJEBuNhcfKlrXtc0YGXCz0r1BM0ip8szECsFBtdShGtYAiEkO3Yc5aljBXZf9XWe+LaKXdVRrYBCtcRkeYZkQpDIJGhr60D1HKKGhlPt5sTpHv7ly9vJZOZQlEtLcv0gMDi4hVOnNqEW7ycd7eSWA9Ns67P59XcP8v98bJbzYzZHTpSwTA2lalIbi2D5CVTTp6NnP+dyHrbt4iPRgjzdbSYD6/vo7IuTTBlYuo6uqCgiJA8tdnVeLLsWSDRNo70rhSG1cMCLUEORpgBhAysy9liZLNTgYl2Q7F9hf8uXNS9vGJbl6UqQK8YlmrFmBH7KEI1WuPnmbzNX9PjT/1dh6JyNaYEqTLrjBaTjkugymS+MYPvzmMKlWC1x6GCRsl3iyGCAFwxx1dVPo6o//A5zpVKcz372vUxNtbNjx1H+8aH9tFjQ1Qbr+30MVUN6KsUZhVS0Bd/XcGUFvZzgyMnzvPTS05SqLgoKcxNzVHN5Riem6VzXRfeWDmIZE02rNx2V1KcHDQHVxcYkekRwdvQ8XkBdQwFMVUPTVRR96aBcPtAbWGkwd7W3snP31sVcxApBxOXbLn/7N7YLZeCXFheFGgQXv8drRuCnDEGgUC7HCGo+82NVPOHQl8iyqbvG//mREX71/hxTE9MgPMbGjuPqLh42JdvHFAqWoXHlnjGuuvo5brzxyTfsnOfnM3zpSz/Dpu5xEmYCAFVRiUfamB0pMHauhhlPsHFTN6puUB5Xyc1NkogZJNMWjpAUciUKxRo1O0cgahgRlWTKIp4wEQ09gWCxmWo47hQURWDFBKWiQKgmvuOiqzoD6ztp62hBN9Ul8/Bmg3Ax0o4QAmEpeMbFqxGXb9M8nVhJSn7xs7zgfFbCmhH4KYPjGAwN9fPBd8/xX//zNJ7q8eLwIK3pPAM9Pgf2CvQAyk4eQ7fIK6Ok4jYtrRlEoCP8OH/6D+sYmlK44orDmKZ96YP+gJDNzvGWG87w3vcOAuAFHmMzExDoBI5KKe/jemVe/e4IBdGFp8RR4xaK1LArNWwfjFiGqeka5ZqHikCLqGAKNF1FApn2bNgMVUoUEUpzJdIGtUKAsG1cUUYqgmjaYOPV6yjbRURsdbd/tTRf47tMWyvl6oUiJcvf8ssDi8vZieGy5TwBQRAs6kquhksaASFEnxDiCSHEUSHEESHEb9aXZ4UQjwohTtZ/Z+rLhRDifwohTgkhXhVC7LvUMdbwxkFVfdLpHG2ZgJsO2PzB75bpHrA4N9LOA1/cwB///UaseAvFUhXNiqHWDO66rsr6gXFyuXnybpGzIw7feUFFN8ps3nzyDTv3117bxeRkB5lsw/AINNPCl5JqLU/UVDG0Vnra1zF+7hDSrqBrKma0hcAX6DEDLSWo2h7VUhXfqRLRArKJOJamYuo65XyB7v424lELRVNC9UThUS17+GqoWmTqOtm2GGfOT6D4LkooyxSe0TIWIaxsACBsFhPJtFLKF1lsqLq4TfN2y8k/zb8X6cjLGYthDAgEyO8vJuABvy2l3AFcB3xUCLED+M/AY1LKzcBj9c8Abwc2138+BPzl6zjGGt5ABIHCP3/NpObA1bvn+dj7c7S2F5mYquHYaVJGB8LRmZ4bR/oRZACZVBvFSoGJmQl8U/IvX5KUSo2H7I3D008fYGysi5MnNwHgOi5ORRKNJBCoGIZCz8aNrO/bTDRqYmoRTNNAFxp9Pe2YFZ10JosUAa3tXSAFiaiOUASJhImua7i1GpGUhST0EFw7bEGm6AaBamBFBZ19LRRH5hCqRjIaWdAmaGCloOAF3wHr17VTmS+u+J5ePsVo9g4aqcBGl2ilLgO3lIjUOMrChxVxSSMgpRyXUh6s/10EjgE9wL3A/66v9r+Bn6n/fS/wDzLEc0BaCNF1qeOs4Y2B4xg88cSbuWJdB3/3r+0AXLl1lj/4j+Ns6M7zsfceYX13he72OKVKmWLN45Hne3nyYEAQREhlkng1hbgJkUiNrq7xN/T8T57czD/8wy8yM9OKEAJDi6CrJsIU+J7PieNHKHllUplWLFUyOTLMxMxoWBehR9m8/To2dHdzzfadpJNtJFNZlJhKNBnFiGmgBVTKHl4kVFxSVQ1FaAjA9V1010GPGOQKNhrgB17IyhOLQblLpecagzoIArSoh9K0ynKjcbGovgBM3VhCGQ5FYC6MDwTfz3RgyUGFWAfsBZ4HOqSUjSdgAuio/90DDDdtNlJftnxfHxJCvCiEeLFSqfx7TmMN3ye2bj3BFduH+OgvTDE83Muzz17P0PktvPudRbZutPn5e8b5lXcNEzcEm3qmWd85wLauK9AjEQxTBQ86u7OouvojOf9G7ULgB+TH85QLJaKRNs4N5UhY/SR0HU1YZI1uiqUynlOjaJeZmZnk0KFnsCMT5BIK0Wg7HQPbscuSq6/fiqa5RGIK77z3XrySQypqhAIkvoOHgvAdAt/FiEYozFcRcZUAqDg2QixSf1ca+CspAwcyIBZpZcveLYhlHaBhZYGRZs6AoqpsXr9hWRGRXFJluNBj+geRIhRCxIF/Az4upSwsO7F6aPX1Q0r5V1LKq6WUV0ejr09+eg0/WEgJp05t4pFH7uChh+7m+PHlggCRAAAgAElEQVStqKpPIlHk+r3zKMJlftqkaAteOXcYQ2goRkBERolG2ijkM7z88t4fybkfPLiPQi5BRHikWg2CsqSzrZXrbhng/MnDnD7zJOOVSYSqE6gGQpE4hRqaArZf5tgzrzB+8hBzE8dpb/FJdaTo6O8g05rB3KpgF2s4noemKShChyCsOUimM5SrHtKWVOeqCBnqMdx+6w1h8VH9xl7sTd7s1s/pNaxUgobbfmFWQV3YZjlBSErJuaFzRBTqgcyQc+BTbx9XbzK72Jh1ZbwuIyCE0AkNwD9JKb9QXzzZcPPrvxu9j0eB5qZyvfVla/gxQaGQpFyO8vLLe3nyyRuBUN//7Nn1uK7Oa6/t4sknb2Rdn49u6RzY+TRXbr2Cvm0b0aNZonoLtYpCLD7Pnj2v/Eiu4corD9HWbnPNgStIxixKNY++9Qly/hiF6QJGRGXdvnZU4RFNgaEoFCbnsHUPPwjw8jXmZiYJvBqdPXEQPmY0jmUZjBenUU0FqYQKRJqugAhDf1XXY8O6HsyIRTlfJRIz0LwIV75lK4oEWZ+fN6fnoJFyXPpmF0JQns+TMWMoq7ypg2ApA3F5nECxJJF4lNa21BKik2Zo7Ny1Dd3UL9pzAF4HbViER/1b4JiU8k+bvnoQ+CXgv9d/f7lp+W8IIf4Z2A/km6YNa/gxwODgFh566G5Ondq0pAfg88/vp1yOcfjwFQgh+fhHXma2dJy5s1F27uzmVOFhTo4muXJjjq9+C0rFKKdObfqRXIOiBOhajf6+QYzoLejjQ4yMlYhU5xkeytMSqIxMHoNAYsZUruzZxzfOfI3JVIEN7XGUdo9UJIld1qgR4fzpEpoaIdEu0RUdw9RwgwAzYiLQKalVUKBQKnHrgdt5+CtP4jgBV2zZjk6EFwefWojBRaNRisXyEpJOGKQXS6YEhqFjVTWyHVkM06RWqy25RiEEiAAZLKUKL0BKIlmL0VPzxBWdVGuG/FwOGUii8QjDo8PUajUanZRWw+upHTgAvB94TQhxqL7s9wgH/+eEEB8AzgM/V//uYeBO4BRQAX7ldRxjDW8wVlMGPnz4CiDUI/jWY3exYcMZNm4bYXficxQqNXwmSegB77rHx/e63lBxkeUwTdi0Mc+ZiRnaWjo59OQ36d6vIGwFTTiUpi1i2SymZRJNZvA8lYgliChxvITP9GSFdKqN86MBiZjL2VNzdAwk0X2BltSpui4RS0cJFDRFR9NiCD/C4XNnsSsO0ZhF//Y+zh6dXczHi4Ct2zbz0sGXIWiw9QRR06RSq9VpxiCRKKZCZmM3YrqKamionorv+UsGe3dXB2PjUzQPYlEXfxFC4GlB2HiFGIlEnFKhgCo0IhGLicmpOrvx4pTBSxoBKeVTF9nLrSusL4GPXmq/a/jxx4kTW5mby7Jhwxlmp5P84z/+Ojfe+CTnzw9w9dUv8tWv3vUjOa94vERr6wxPPBflkaf6ePstp/mjT+YQ0kcWdfSIRUTRmTw6zbobswg7RqItjhVTUWyXowen2LT9OqxUjfVdCaxohgnnFOcGx0lmWrBVm0jEJNqjUynU2LllM1MtfazbGMWnzNkXTzJ5fo67fuFmXhk5zLnB87RWo6i6QLqCQy+/hmGqSFciA5BC4b/8X/+JP/jjT1EueqjCRyg6qb4I5XyOjGaSTEbZduUAR585QdXz6oZAMDM7R6YlRn6uCo2AnwAUBSElPV2tzJ4s4VSrjJeKJLIxyvNVpsemUYSKVAUiqDeeWWVasFZFuIaLQghJECg899x1SCn4znduAkIp8B8FVNXn3nu/jGcm+R9/IVi/WfL1F/oRusPm3hQ5p0K0zWJyuER/f5L50TyZlji5UgnVEshqht7enYyNnMdUA/yNKsNTRWSLTqFSRTdVIqZF3BQUyzaxRIQZt8J8Poc6lKB7XYb2/k4CoVGeqWKZOqm0xuxQlcCvt3YLIPAV0m0JipM5PD+gYOawrAjl/DwBEEuatLd2MzM6xUzBJ0DgukWcwIOFTIHE9yW6aaEbDnYtbDgrZKgToGk6Xe0DHNWG8Ot9I2tVm3S3yexIGEswpIKnq3jumqjIGr5HTE218/d//8tvWOnwpZBO58By+ben3kZXaxuvDToU5wzWbYzwrg8FKJok25nk2h27SCdi5GcCPMenkiviqS7p3naGzh4lqru4QZkZe4KJqXMovkdEM1E0iW5LdEtF4JNpieO6FcxEKF9W8ar07ewkGlOZGJnBtCStHRa+3WjXLpH4eI6HUHVEVCeeifOFb3+V+fli2NZNgNAkkWiKiVNj+GWbVDrF6aNjqLpBs+Pt+2GNRCQRpSHxLpCoqkJLa4KbDtyIaRogBKqq1csffBTVQCiCe+++k7e8+RaSscSq93TNCKzhknijBEReD+6++yFkoDI2NM8db7WZHZvhiS88zfYtEb7+3Y4wet+T4Zfedz9ai8W6DV24RZ+Z3AxSVbAr09x28x5qnofv1RgdnWV2ooZBglR7mol8kbG5efLzVSKmAXaZcr5EsVCmXCwxO5Kj4Axx9NVhUlmN/PgUphXF0tS63FijxTjMTcySzrSw7br1pNUYsiHwoZn4rotimNgVGzWmc+e7bqBWlqiWgqLWZccEKMJnYmSaddt7UVRAShQV2nsTbN+/jbZsyHo0LZ1U2kQIyE/6tPUkIVD5L3/8CfYcuIad29avek/XjMAaLhsIIXFdePCz81y5bZBvPdmBLSVdHUnuuuMUTsEhoilEEymkEqW7JwqaQ7wlhhuZpq0jQUdXkpHCOOmMTvfGTpKJCL5vY8XTlPIVnPw0fkUghUrVc9EVnVopINUWQVfB82pU5k3MQFCq2fjSwK4pSF1BqzdpUequvKpJaoUCqWgaqgqKqqIKFSF8hOIjaj61wKE6VyKldmBZCoal1wUGIJASKcNA4vDgKNnOBJqiIISCHtN56cVXKRRsUFRS7UlcGWBoGr4Xsh5NTWHUmebsqUFGJidWva9rRmANlw127DhKT88kd/2c5IoNx9my6Qz963tov6qHT3x6AE1x6Vq3jpnCOCdOvcypYoFyzeLlg+eYGa3Sn+0gqPnkcqMEnoPj1IibKTJdKdJtcfq71/HffusvKZdKCEUhm+jk3GgB2/XwHB/XdxjY0IY/FZButai4RaKWwczsHOWch2lZ9PT0IOtz+kw0SSqTYj7IcezUeYQnkYpElwqqbhLN6uQnZhgePsfJuXPYroem+M15ACBk4eVmipjZNHrMpK0/S8JsY9OGfr75nceR0qa1N4ZlWszPh6lJKVw++NFfplao8tV/e5CB7b2r3te1wOAaLhscObITVfXZsOEMbbEyP/e2Mb7x7U7mJ+exix6btrciNdAjEWZrc6i1GCJw6FuXxcUmbvVRY4JCzsAwbDS1wvjYLAgT17NxfIdpb5T5+TyaAmMjM5gxEy+oUam6bN6QIZEw2ZFaR1Ccp2hVybSksKcqOHEfTTcpFXML3P1SpYRI6JiWDl6AkYrgl2poEYFb9ikg8V2fQqnE1MRMqORkBOTF0vLscGqg0GolUftAxedNN99ES3uSJ594CtcPcIVLpVQFKYlGDCp5l527rqRYLNDV387sbHHV+7rmCazhssLRoztoa5umvX2K1myVtx+YoDBcxJ+vhRWNrktuMs+h0TEGEptpi8TpbEvheAGpVC+mHifa3omVShIoJnpgkC+WsAOHmlvm0Pknqc1PowkXhIIQPplMCrtUxdDB1206o1lcoRJISXe2DVyNTNKgpzVDPBEDwoHr+mFaziv7yEKoSyiDgETaIh6LEKig1kVLHUdy/Q3XExjAghrQ0s7HZb9Iqttkz/59DM4MougRJoZHiSQVirkCminp7M2yefcmbrv1Vlr7W3j+qReRMuwqvRrWjMAaLhu0ts5gWTVOn95IvuLw3GtZTnx3Azfu3cANm3aRm62Rmynw8Q/9Pjdv28Lp116FYpLZ8RLYcZxinqHTE+THpxHY9Hd3oygqEcWCkqCtN8rU1ARIhVLZQ9d9ItEkmjBQ1QjrB3YQDXo4W7b5nd/7r2zo3sah5wZxbZe3336Ad/zs3UQVC8uwEFKgqKH7Xy6XuWbPRgLXJpmKkErFWb9zK0bNIZrRKcxUOX/wBJFUFKeWxzAFQmnQhAEkrucxeWacpBXD25hg7NVBcs400sjRu7WD8rRHrehSLTi8+twRstEE2wb6+LdvfpmJ4Skmz6xO2l0zAmu4LJBK5bnvvi9y771f5oYbnuLxp5P88d+2YehRijGb9/zGB9ixfTdtuBw9eZR8tYjtu8yUJ8m2xiieLyFUwUR+hkxLEt2WSKFSKpYo25Ky7ZA0fGYnxyjOu3iBwmyxTCqeZNOm9bSkDNKdEaIxlWdPPM9nv/5F3vSmfWzftZutm7cz68+SSbdyz7vuJB6PIISKgqCzJ0M2kSK1NU0qlcLRXFo3dDMzPo5TqxBNWEghGR+fYmLuHI7jgxWgBWGj1aAuCCKkxLU92jf1URkeoW/7DjKdabychqFoODUXz1GIRQ1UxcC3BO29cYK5PEpcIPQ1nsAaLnOUSnGOHdvOqVObsB0Vt+BQs0sEGz1sJ+C7w49z8413sf/APTzz3NepVvJ07dlAa79K3qvScWWSgb4u0qbJxz72fhTHJ3/mHBs39uFMS+z8LHuvPYAMYgghmZ+tEDEs5iYK5Is2RrvOU6+c5eyUDRWHI4ee5//73AM4ZolN1+xA1xMQbUXRAqTnYRoKfgDZvn5qrs3Bbw+iq5J1/d04w/O0ruvEVn3Gz+QRUoFAYBlptqzbjeYrrN/QS0dnCwJJLG3QuyXL5v3biHelqc3a6L5GxZ+jUhXUai7RRAzTVLh+RwtvPrCRq67dwiPf/BZ+UdK7sRvvItG/tcDgGi4L+L7K6dMbue++z/PIIwZb923mTYV1PPnqs1hqjLPPv4K90aWncwubMxmCtEZtcpaMqZDzArb0ddLT3YEXCI6fP89Nd95EXE8SNVuozHwVRTMpBlXiVgxVKiQSOlHLpKOjlZnxcRJXSIz5Ir07NqKsr3F+dATcgLmpaTZsGiBrdPOtg1+nOj9Bz8YuRs9OUKo6OG6FdQPdePM2QeAzNDzJrhv38czhk/gqBI5LLG4RT0SI6hLLshBVQfv2DtRygUotj5UwKVZqRGs2M6MzFMZyZDfHOHPkFRItCXoHulEzQ1jYOIko27fu5O3vuJfP/tNfguozMzyLZWpUWFkPcs0TWMNlA8cxCHyV7Zuq7N0ywQ1XXE9Xup0+Q+eqrj1EA5Mzw4Mk00nsmkepMIkeDRhobcNxasxWJsm2wjcf+w5e3CEiYce2bWQSEQzd5/DBF5kdHsXSdKJJjZgaQbPiOH4ep+ASlGps6G8hT4XyvIPvavR2tpAbHuXId17CcadJtrWRbIlR8VyyfVlK86MkNqS55Vf3cv8v/iw9A628+NIZPL+GPVdEM3Ta+tupVaucPHuayZFxoqk0k/Pj5PIz1KoBs8NF3FmJQGHy1VGMmklXfyvjJ6fIdEVxbRe76NC2JclUOce56QJqRDJ4coRESzTURGxdYwyu4ScAjmMgUdmyQ5KIDvPM0d/ntz5wjN5NVzBdrYEV4YqerQypLqM5iw293RQnKqxLb0TxYoyfOkOQc5BylNNHT/OlJ17gxcHzvHTmGOX8aa66bjOWGUVJexTnHfbs38nQmdOktgjmR8tMF4sMnh1lXfs69ly7g/I5hzvv+CDpdT1s2vdmKiWbE6fOcMvd17JuWx9tG7qpFD1Ov3CQwadn+bNPfBq7kmd2aor+jW38xac+xdad3VRyVWo1h4mhMd79rr1cd8MuJs/NMnFuHtfxCQBFk2y5to+377uNX/7Ir7D/ht2k4iaTZ84Sj6no0sQu6mTSA7Sk0jx7+FlePHiIvo1tOK5Dbra06n1dMwJruCwQj5e4774v0tk5TdG9HYBfvudqOtpcXnnhYV4dfoXRyZOcfOIJjGiWm2+8nQPX3sXQ7Cwnxkrs3ncjWkbHTkKpXCauKUQsB1HOsX1bP/FsD2qrpH1jC4GnU6145MZH2bmjDUNP4FdUbCl5+uvPkuhqJzeVw/Ns9JhNtjXJd194gf6WbXQqvTzz1Eu0tEZx/TzSlUzPVXHGhmnbnKRYsfECDTHt8NLZI8hIjOmJSRRFYFgKB7/5LXK5WSxThUCgyLAUuH9LH9O5cdo7e3E0j2+89CTFqRzJgQRnRk+g6xrFfJlCbp7enl7Kwx5G1ceIe5QLNqhrfQfWcJkjm51jw4azvPSdPRx/5jY+/ek38cDXunj40TvQ2lqwywUqU6P0r1/PoedeZNwbp6w63HDdrbx29hvMMkWuOgWmTzIe4czELJOlWV6bOIiettHiUfp7uvHmCxzo3svWTf1s3XMN2R09FPMVDCOOrgdkeuN4ZYmVNNhzzTp6+7upTVjYqs2WzVfiRqrYnoOH5PYDu4nEPErzZY4enWL9unb6uzoY2NtJpL+Nzz3wIGcOnSHdEscwdDLtafS2LMmswrqrBlCFIAi7pzOwq4OhF3KoER0RE+TPjePGSmS7VURN4W3v2Eel4lEsVbnu2ut46cVDOI6FnvXxij6ZTPuq93bNCKzhxx5CSN70pmco5qNcce1hdl7zN7T0bWPo/Aydne9g64YtdKxrJ7uuk7Zd20konXiBw9nJY7xw4im6Wlrwz85RcHVuuv0artm6Dzeo0JdRsBWfVItGsj3gyNGX+Ll73sHA/i2IqMWrZ57j2PmzxNNJUu1RDM2gWC3y4iOP0hJL4icjuG4KzUqQSMXZuLmbsyeOc+qlGbq7W7ELCq19GbKJJLFolNbeGPF0nPU9HWzsyVCeLaHrAdG0hZCQ6AwIWnW27bkKLavS3ZHE0hV6NrUxVZ0lPzGHFConxwdpN3up5TwSMQ0rovDEd17h6v17aG9JMydzPPqNh5kt5lB0FRkI4oax6v1dMwJr+LGHlIJvf/tmXFfj3OidlMsT9EU8Ng100Nk5RXd6nq079mBFTCZLHtdfvZfS6TOcOXWOeDqBFY+Tn1AoDhVRvDS1isKmjj28551XMjI2SM0r4paruI7Kl777GC+8/Cjb2tejCgvPdxg7PEZubgTVCohoCpv2dVD1C9TmXY6dGuTEsReYPzXBqbETGNEolWKZ82dGMDMGnal2btp3BWpao7O3hd37trGtI4LtuCTSCW7Zv5vKTBW35pCJtVFzqhSKZSxMoqbgnfffQKrHQp3ViEZ0KrUqXmkKIXQombjjPpaSpnje4d0fvJW3vOU2XM1EVso4pRK5Qg1UqBYv7HLUwJoRWMOPPYSQ3HHHI6QzDpOVfTz0YA/54FWGxk7zv/7hXxjNdXB2boqR/DxfevrbtKS6uXrr9eg1QXF6lolzed5xz7vYt3899kTA+dyrzDkTTLsqaiJFS187p4cL9KxrQRcpdu3ZTM+ODsrVSbQc6IEBbpRYIoZQdI49N8bwqWEG+jfRnUwRMVTe8f5bmJ6aoiPZiYWHotiMj42xe2c3B67Zx2+/75fZGqxn17brad/ZwjPPHWF6cpoNb06yuStGf1ccr1xibtJn1j/E2/adoy3ZQvvWTlJtUWYnx6k5AY8depTc/Djjc2eIRhJU5hSqikvBL/DUo6+x6+b9bO/vZc8t/cSTFqX8NGiCD73n51e9v2tGYA0/9pBShErI5c1MnakSLUUYH78KVzikE3DNvl1Mj08wOznF5PirGJEULz3zPFPn5qnUqvSIgLnKOFo2Re50kVi6g4mxEo65GUvRyc1WmD53HjPTzdS0T14qPPHCC0SyEYbPTuLLAEuPE8u0ICerVOYqpFNpOjrbqNQ8Dh98jdNHjmLF4/Sv6yObtThw9RZaO1TSsSRpo4fOTAtX3fVOvvnkw4xVquioaIGK2l7lk38yw6/8epViuYZbDkgm2jg/lKWUL2FkBZ6tMD/jUi35jEyepBb4mBGN7Vs24gY6HS0QTUimTk2iR5M8/sRT2GWNDTt6URGkYwm2XLNn1fu7ZgTWcFnAcQxmcgXODZ6kbWeSns4pXF/HcbKcGTpL4PkE0qC/N8Pnv/oZIqkEUre4/dp72HjgAE8d/hqO45LqjBONR/mZG+/ilZdfIZmyGBnJ0adGyI/lsCIVlHicWEuWG665heqcwvZt/fzM29/Otb0H8FyD3u40dqnKwPpN/PPX/pl8xUZKn/5UBzvW9fKee+5neDZgerpMrLud/bfextHcHKfOHCFfK1Ccr9La2cbuWzaQDorccpvHBz/iYrUnsCIGuiUoo/GBX3s3p0/MkJvPERCQTOtUSkVarH4y7RrD+RxKUkEKj81926h4ecZHDvLqweep5W2MDptkNMGt910DHblV7+0aY3ANlwXOnx/ghgNP8+EPf418uZ1yNcWGk2O88ozLWLSbRDqBqAQo1XmqtRm01gHetfkGVC1ONDHAtz/7KXTVRMmXqGoVrtq/m/GTI6iVGukU3HPj1Tx56gRtbV3MzQUIRaWv5wre+2tjTOfH2Lajn6999XEqRoWujIJaNOkeGODU5/6cVGucNjPBXC6HYlvc/f7b8Z/6NxTPQAajPPDA39CW6WJkapy23jTDJ8bIZCyMtgpf+tcAb6yFU1MRYkqECnkmT+bY0i65/u6/41//R5TcaBVV9YlnYrS0RPGUWQrjRc4fmybTFaM27ZHoLlP+/9s78+i4qjvPf27tVSrVIlWVltJuSbYky1osS5Y3jAHjBbANCXASZxsmyZmE7nROp8+kO3O6M53JTCYJmXMmmWQmCWnSQAIcwGAMxjbYBu+WbMuSZe3WLpVKVSpttS9v/pBMHIKMIQGZ+H3Oeaee7nuv7vf9nvTV79733r0T0NvfhUqXjNaQSiDgIX95Gavq63n86VcWjK2cCch8Ili+/BKzs0aOnc7C4y4gJdnLg/VKvvJ1Cb3aQWg2iCISRquzUH37bXgmRzBnpvPWhWNkpThJz9Qy4G3lkrcNW1zN8Z4LRONmdMYkSssq2NfWisWUTFxSUK2zkqQL4LDk44nHMNjVPPbTx9m2bSepGVrCCj9JRj3unhNYk00480xcaOwjv2ApPSEXL7/9Jp5ogDXLCpgM9zEy1MCRjlM4l9mY9blwJBxo1BFSspKYcYU413Q7ppTNbKkLk5eXy/qsEQ4cV/MP3ytFqzWSnplJPKJGxFQ4U7OJhZIIRTw48+z4/RKjExFWlq5k86Y1NJ8dJClFzclDZxlum6Cmfi3xWITxbveCsZVNQOamR62OsmKFh9Gxz6JQfZaYVM3pjhTcIfjZEwqOvHmQIoOfdVUj9F0a5PS+BoLhcaZjboQmQUP3ZXwjQbRIFFYVkrGqhMwkI5PDF5l1j4FrDFtGEmgVOCzZnOprZNrn5ULX24SjPaj0gm/87RZOHT+ELSWDfFMRX/jqN5AykslMS2NqMk5YE6J99CRLSrI4c/Ywicsu/L4Ys74warONCfcUJ157jtH+KUx6G8GwIDoa44615Wzc1MJXHz5AU2uQtTXNfPFv3Pzkv7WzvHYSz2CUlDQtOq0Ss03JqrIN6KM2QhEFFYWFxIgS8sUY9SkYnx1la+069MogOr2aOx64A+/sNBfPXMTmUC8YX9kEZG56amvPotVEKCnqY/PG/8rKisdob+3h588vIaZOZskyO6HUZILROF/8cpiCPBNCZaGjvQOnPQtFuBeVIoE2riTQH8QdDOAPTxAiDGoDYa8HjU6PUa9HMePFNTFCUb6VlvZTqA1q/NN63GNK8hxWJkZHKMsqxGQ3YzZYqFm2HFU4iC3DzvmO4xxq2E9mvo2VayrQZKXg98fwa30kjV0iOOzjgduSWFPciVKhwGzM4suPNmDLTiY7082jjwzy5a9MEYnq+d1Td9HRo6Zq2UZiswFSTFosTgUWqx1jwoRKq8YluTAINaUlZWSVZRBUaRhSjXNwTwNLqpZiW5qOJzyIcmacAoP8nIDMJ5gTJ9Zy8FAZR972MzlpQogE92xSo1JcYnLajyPLwboqaLxYwOGGCqKSkvKMajxDYzizi0lzLEGj1TLhm2Ll8iqIR+mdFlhtS7CnWVEZLViNRqSYxJmTZ8m2paLT28hfYseZnodn1EPLWy0Y7UYctmRM6eXsO7QXEZRI1sZRWBL0DQ8xcC5KdlIWWY5MMGfj0fSi0OiIBqcRVhXjEfCrE7iS+ti1NUpRZTm/elLLbx6P8t8fS8Y3qUSphKSkMDX1A2TYsnhgp5u1q2cpXy0RD6Wg0xvAIKFOaAkGAuRXOSldV4DKpEUZlbh4/BihUII7d6/Batdjmp1BpzNisS08XZxsAjKfCBoba7hwoYoXX7yfV1+7i9ysSf7+ywmU6ggRZjm4PwVXyxX8U6OkmJOYnTEixeIEpnz0jo6T5VyCzZKOQhtDp05mKuDjypSLgvSlzCZ0qPQaTGoJ4Y0QUcfQabSopQSKhAoiCm7bdh9HL7wNoVxW1K3hiquXJIxENCYSs0pmp+Jow2FSjRnEJIhpoT/YTDgWwx+YxBVKwmjQ0HwySn1tkE/vukyOs4+Tb2nJ1mvYfnuANEcav/71I3gmdJzvG+fBbeepqzrKN7/upqxMy6RvBKVGh0ZvIK7TMOP2MdI9iGsgQo9vGKPJQHHecoqWZmFKNxFKzJKhKUFhUdPW07lgbGUTkPlEoNcH2bHjZTasfAGlupl9Rx34vNspzdej1g3SO3OeBx6pYWpsEqc5j6b2i5TmFnGps5NgYIYZdwhTYjnN55vxzLoZ9h5CGxgjvzCfHTvWo9GFUBoMrNmxHaPViE6TjEKrYaB7gOBAmOf2/YK6Oz7F337/6zz+5P/gnvu3o88wcvDQSXJSy6hfVkGqXY1F72bNqq1cPHCA6GUPQc8shcoa/sOdn0MKq7ltS5iX9jpJ0sfZVv07vvZtPds+10Pd6iidncXY7eOkWhRU5dvQKSc4ebqKX7+YxdY7c/npD4OgjFO1wt1+zQwAABe+SURBVENsLIhGryAwHaaiuBRjZIKRUR+ukRh3bt1KIp7A5RpmdkaP07mcIVffgrF9XxMQQmQLIY4IIS4LIVqFEN+YL/+uEGJYCNE0v2y75ph/FEJ0CyE6hBB3/yV+CWRkJEkglKATEsYEFBbuwTukYdzjRWGc4tjJExTZczh5qpU7Vq6jsrAQIenoHx2lumwNxVlpaJXTWLUSOcYVFKdtwNffS8CrQ6BHGgxzvukouahJiiYxPu4ixaBneXk5zvQUDu15jcOv7WXSH2DSH2J2JsyWjVtJePspLUwizWEnOdVBbGaS0tJlBENKLFkahmM+nnzlJULKGK83OLh/xyRdXYW8/PIOdqxpZ+3KAJGIhoaGVVy4UEUwqKeuMsTx/XEOnG7nldf8/POPQ1xuklhX8wt2bn6OjevdaJRmtEKL1apjJjbDcP8V9GY1FqeZUP80nsEhNCYN0XiIQdfUgnG9kUwgBvy9JEmlwGrg60KI0vlt/0uSpMr55TWA+W0PA2XAFuDnQgjln3PxZWSCQT0vv7yD4+d2Ur/eQ11dAHOSllVLNjF5RcuEJ4HFkILHO4nZaaTPO8KA9wpWk5mksI+yEgdWu4GcymUUOkvQ6FLxDIdJ15fR3tCNVR2jOH8rM7o4n75rLQVWE8RAGzHQ2nsGtBIFOg3x2SlU1iin3jrAQHCMwtIc9KmpHDnTTHpRBhFNGG9iiJ7YMM2XxvArPbz5ZiNa3WXuWNvDlppu8nNnsNuHiUYV/Pr/PUrrhbX87nefeWeasWefvZ9Jbxr16ysQ4xl86VNqcnNauOceJUU5ZzEm+VmaHyUrp5DadfUsKa9ABMOkZZpJL0lFqRUU5pRBSEWna4TZKbCFjAvG9kZmJR4FRufXZ4QQbYDzOofsAJ6RJCkM9AohuoFa4NQNX3EZmfcgGlWTljaG329m7ys7uPvuA5RVNjAwFmBCBw99uo2BERXDvVtoOjdJSfEQIrGcyrIYa2p/QOOFewiOptDn6sGeZaO8qIq+ySlKS4JsWH2GE+2pVNZUM+4+xJXuLIw2OwUrMynKc3L2XAf1mzaRU7qMtzuPMzpyiZYjr5Gy+dOsXL8GdYYRfWKGCV+IK+NjWCxWMtIziSSGMBn01K6BZ94sxmEOkJE8SjhWxMqK02g0cY4fX4dKFWPp0g46Opbidjs4fHgTCkWCHzz2Q4aHnRRm1vHKKyXs2rWHjAwXep2G5vNt1K2oxmK3kKwzkLm8AHtWChcaL+P1j1BVVsnEcJxZ4WXLhjIa2wbfM64fqE9ACJEHVAFn5oseFUI0CyF+I4Swzpc5gWtrG+L6piEjc8M0NKzi2WcfIjXVi8UyidVs4r7tFlKMyczEDFQXbsLHBf71u6d56N5mVpW/RTxRgtcbp6WpE6smi3DAh9szgdXuwGwxUrXOjdU6xZLc86iCapKtX6V/MoHNVExHXzszUQ1qbTJGWzYHX3ydmrXrsFuy0ApBLJRgadl6JJ2BkvQc9HoNKklJzfIKzA4r6jiUVBVy8KQNT383cTFN5SqBt6+Af/leiHXrDrF791Ps3v0U9977CkVFXe+cqyQJDh26i6kpM6dPr8btdvDCCw8wM2MkFokTjwXw9YzS0NbI4KgHpzMDox6ajhwl25SJ2mBCJelIztThr/kL3B0QQhiBF4C/kyRpGvgFsASoZC5TeOyDXEwhxFeEEI1CiMZAIPBBDpW5hZEkwdhYGk1NlbS2lpFIKBCzMXRBLT/+vyZ+/PtZ/unLo+TnDeBzqynMGKZixfM88UI6IWMRg9Ep/LNBypZl0tZ1jMHQJKPeIQDG+vpoPXEMnf1pEuo+MtJ+Tvu5LmKzyZSUbiVEkLAIc/r0cSypFpLUCQxpNgbHB7ncdInMYjNfu289//zQlzjz+0ZsFNN9ZZrOwTa2VBv55u4w1nAav9u/i9YRH9FQCf/27MPMhhxotX86CKgkCc6fr2bfvnsIh7UAeDw2YjEVd29Ws6JC4p8eSyHqjVC5dB0Jq56WC5cwm1JZnpFF66lm+vq7CMQiDJ9pXjCmN2QCQgg1cwbwtCRJL84JlMYkSYpLkpQAfsVcyg8wDGRfc3jWfNm7TlD6pSRJNZIk1RgMhhuRISPzDomEgrfeuo01a06StsTMXRuyqc1VUpLZhnZ+jP3RwWRs2jyspjx27xqg+dI5ypznefC2cbIzx6hcsQopfIGi3BAAG9eE+S/fmuTo26U8tCWX6ZnN2LPsFFcWkFuiobvpGLbcBJFwGE1UjSSlM3rlEm8c3Me66i1MTCs4euJtXP4WNm5fTqY9gFYfwVlkxeyc5tiBPKru2EosrsSRZqTm7tsxp0aJhow888zD7N17359MAW8yTZOf3/sn59/QZCEnR0P7+H28ffIAOrMeyRcmR1GITq8nLqlxZjnYuKEe/9AI5WWrFozljdwdEMDjQJskST+5pjzjmt12AZfm1/cCDwshtEKIfKAIOPt+9cjIfFDuvvsAsZiKnp4l9PSU8Q/fcPHVz0+inO+G7hjRkOp009ubT4pFwea1Vwgr6hiYKKKzV0P3yBgNTUH6PDbiCQVnL9rodq2id2AfqanrWLPmdnzdY/h8w8zM9qGdCKJQmoiqE3R0dODMW0pv5zm6BhvYdOd6OgZC7Hm9mbfaLjLkbaZq5UosBgMZaUautKWzpMLBdDxCLORhsLcDjS7MvZtew+tRMDVlprOz+I/OTwiJXbv2sGvXHhyOuWf/NZoIQki4R0ZQ+Ktw5kt85T8lY063MX5xgJFxDxk5TqSZEMvz8li5diOtrR2Y0v+8acjWAp8DNr3rduAPhRAtQohm4HbgmwCSJLUCzwGXgdeBr0uSFP9AV1dG5gZ49dXtnD1bS3X1ecrKWrFY4rjHcpieTqalZTnly0ycPFOPEBIatcSdqy2UF2eQmzeOIX6FfLsRb4+P0+eW0jeyjtloAQW5ndx/XwY6YxfHTxyjpqqeF58/iN1YTjgFfOEgkZkQCYOSzOws/NNxhE4iIDwkG21MjYXwDSmYnEohongchyGD5CQ1+blJuBIBpidHCHkTKM3pJCc3c/lSOadPr37P85MkwRtv3InR6Ke4uBMhJEpLL6PXB9my1cTmB+oZ6TfRP16Lp6OV8d5xms42sqliAyF/lPNHWlDEIqTYDFzxNS0Yxxu5O3Acrpkt+Q+8dp1jvg98//2+W0bmzyEU0nHu3EpycgZQKBJIEsRiKvbuvY/u7j/uCItG1dTWniVV9wyjhCgrHSc/43Fy/nOQVGc6fT276LjwNkmpkxRn6jjd4mTtqvO4HXW0eTqxOlJRGpRo1AkuHrpE/e3lNBw/Tf/IBJUVK2hs20tGUjFrltei0UisXTnJmeFaFJFT1JWUkOk8z7GfWcmrsdF4uI+s0jTuWHOa3tb37zOXJFi37ji9vflMTZnx+5MQalCkG3nqO7+k7qGlnDx8icBAgK27d3JpuI2a0gokewpD/j60Bi2heHDB75efGJT5RDMxkcLevfeRmTnC8ePrOHu29k8MAKClpZzOzmKStReYHC6kNHcapTRIT1sJVtV+igokPvPgedKSnFRWXibF8BLHfp9gVBEkHtPxo3/9Fbdt3Ikzz05ZWRFrau9GKGd49LN/g6RTERwUTMwGaHc185ktr1JV/AKmxCUKCqKsXvk0ZQWn+daj7dRlv0FK6hja1DhdrVNcuFB13fPz+5M4daoerTbM7t1P8dBDz3LmTB2hUAlTXUF2fuY+llh6CY61UFtfzOHTr3Hm/EH8yiCZOfn4fFPo1HokaeFHdWQTkPnEk5ExSmqql6GhrD9pV18lkVAQCulQKhOUl1/i1X07eOaZhwmFdOx/7Q6GevaiVBVz991HEAoNpUVFPPT5TCJTb7J6Yz3eGRcok4gG1BQUl9Le1QVJamKzUSbGxklNyyc7JQUFEjptiIEuQbDLz5iUz6keJQpFnJWF3VjiAT6zW89dq7voaP0009OmBc9r2bJ2PvvZp3E43AgBen2IaLSEDWtTUanuJ69gHG9slBNHe1BozNz7qd3kZTiwpqYSDYWIR4NcudICQUjR5i5YjzyykMwnnubmFXi9qQwP3/jjKF1dRWzdup+SkjZefnkHB15fQ3tbP+vX55CTM0Bh2ctEYloU7dtpGxpg/T3lTIT8JBsyef3Vl1CoVUh6DS3RbkqKq0hIEhqlkp3bZjHoExhNcaKqEHnKCWqLpti3bztm8xQKRYITx9eRlOTH47FdV2NV1QVsNi82m5cL/bdT5pzFn/geLW3TGEWcTn8clbaVL9/fQXibkT7XMN1dQ1RUriEWF+hC4BibwqXXk5mSvWA9sgnI/FVwIwYwM5NMIKDH7Z6biOOtt24jHNbS25uP3T5Od3ch/f25PPTQs9hsHtq9tZx4YwSHxUd23b1MM8mz//4i6+rq0arG2fPqIabccFvmesY8l8lMymRZUQKVSkJIMaREE7s2QTBooqdnCVNTZmAuKwkG9e+rd3zcTk7OAOGwFrU2j6eP2cjN3c/Kkn0cfesLBPUhthccxTu2ghUrOnFPGVmxtJrRlh5u33QXCtwsq93M6Pgpggt3CcgmIHPrcPny3CsvHR1LAQgEDBw+vIlly9rZsuV19u/fSkfHUp56ajc5OQPs3PUSX/tmKZPDOp54+jCrH7iP7Fwzh17dj84WIuqfwVoQJyulmb4ERNUtpKbOPfjmHoFP3ZUgELDy4ov34/NZF9S1EIcPb2Lp0g4CAQPFzt9xxfxVKtOfRxWbwT0ZweD14lg/SnbGANGYmtaB44z7rnDHbWX4Ax56Lp9kJOjDkpdHenLmgvXIJiBzS3HVCK6lqKgLi2WK7dtfJRAwMDiYzchIJjOzJi4PLWO0R8uGLam8uW8/aUv0ZMfsDDQPIuIqPn1fK0++oOIbXwnScjmVFEuIgwfvYvPmQwD09poZGsr6QBqFkKiouEhd3RnMFgf++L/gDcZZavsNQf8yrOZmssvSKDK+zfSMmaG2LIpLOygoniY3GsaeewdNAx30DnoIqPzogl7U8YIF65NNQOaWxmSaJhjU4/cbOHp0I4ODc23ntWtPkOUcJHOsgcMdgs9sdlOYb6NrZJoUcwrlpWru3RBmZV2Imko1afYp8hxm3jiUw22b5gwgkRAMDOR8YE1JSX5qa88Si6mQCKEzjOH1rUREf4A3ClOB76KODtA3WEFu3hkqK5v4feM2lPEunMlJGEyNJFnS0BoNjLrb0HlgzJ6xYH2yCcjcsqjVUXbseBmVKsbBg5u5ePEPE3R0dhZTvqIFu3mWR3Z6keJqlueNMzsqYTAbeWRXD/EZNa8eXE9+/gRp9gYys7vpH4aZ6WQOntpIIqGguXnFB9Y1O2tkz55dRKNqcnP7KS39GTmZxTS13o470IRGs5G1y3+KUihRq2MA3Lasi0xjN0JIROMteKTf0jF0HsntJ9gzzHBi4bsQsgnI3LLEYiouXqxAo4nQ0lL+R9tGRzN44t++iFIZZ9Omw5SXNxOKqNi+Ic63vxekx5VMukOJw6yhtLCL5557kAcffI5oZD3h8BXa2kpuqPNvIcbH7QBMTlrQ6ULk5x/ApB8n2RBEmWHBau4HBH2R+5ls7yErcwiRLBFJaAn4Yji0T5BIqEmymnmgbpaWoYYF65JNQOaWRZLEdf9Tz87ODcQRiWhQKMA/Y6G3L48773HjSPcxM5OL2eLipZd2MDqaQW9vPs7CXkzJU+Tm9tPevuzP0ieERFFRF2fO1CFJc02L++9/EYf9p1fPAIe0nwv+25kailGhC9I4Vg8X4kTVWnRGMxmGVAry26lfXcN3vvgn7/EBsgnIyFyXzMwRCgu7mZ1N4vnnP4Xb7eBb3/oxBkOAQ4cyOHKq/p0RgV56aSd1G45zqmMD3e96G/DDsH79MerqzrB//1bOnp17SbevLw+7fRwh5h4nNmiDbFzxNh6vEW9HJUuc7XRbl1G4tIM9TztpbhxjrCWX2po7gMb3rEc2ARmZ6+BypXP+fDXj43bGxtIAePLJz5Gb209Dw6p3DABgetrE0QN3EYv9Zf6sdLoQSmUcjeYP04ofPLiZoqIurNa5uQUvja0jL/kCVkOUlIoznG+qpGJFMx3Dyxgb8RCf8pOXvYKKvJcXrEc2ARmZ65BIKHC50tm27TUkSdDRsRSXKx2XK/09949GF57p54Ny6NBduFzpf9RkudZghIAC8zl6B5YyO2FgNGmaVasamZ5J4pnfZ6Acc5Fm0vLZrY0MDS08Zof87oCMzPswPm5netr0TibwcbFQn8Wrr25HkuaaA1M+M16XherqRpzOuTZ/PB4jGpnlP37JhTVlmFgwjaK8heuRMwEZmfdhctLCE0988Y9S/8Xk6p0DSRI89dRugkE9+fnd5OTMDe3pHsvikQc7qavvYstdoFBc5sknPwc8+Z7fJ5uAjMwNcLMYAMwNv97SUk4koiES0SBJgrNna8nKGkKhkJAkFXX1HQgBSiX09BRc92Ul2QRkZD5hRCKa+SaBeKePIDe3n94+K75JPTXVHYRDShASLlcWzz//qes+syCbgIzMJ5Crow9fpbc3n7ycTtzDNpqbUzDqB1AoJJpaqt73oSW5Y1BG5hOOEBKrV58mljDQ2LSemZlkPL5icvJn2LLldVasWHi4cZBNQEbmE8/y5ZdwONw4HG7uf/BpaladRaWK8aMf/QNjY2m0tZVc93i5OSAj8wmnpaUcjSZCfn4vY14lpcuG6O4uJDe3n+TkGbKyhujtzV/weNkEZGT+Cjh3biXT0yZ23bcXlSYyN8X5/FRt+fm9sgnIyNwK+P1JROJKJsbtVFef56WXdjI9beLIkduve5xsAjIyfyWMjGSyZ88ufD4rdvs4vb35180AriKbgIzMXxH9/XNDi19vKPN3I98dkJG5xZFNQEbmFkc2ARmZWxzZBGRkbnFkE5CRucURkiQttgaEEOOAH/AstpZrsCHreT9uNk2ynuuTK0mS/d2FN4UJAAghGiVJqllsHVeR9bw/N5smWc+HQ24OyMjc4sgmICNzi3MzmcAvF1vAu5D1vD83myZZz4fgpukTkJGRWRxupkxARkZmEVh0ExBCbBFCdAghuoUQ314kDX1CiBYhRJMQonG+LEUIcUgI0TX/af2INfxGCOEWQly6puw9NYg5/vd8zJqFENUfk57vCiGG5+PUJITYds22f5zX0yGEuPsj0JMthDgihLgshGgVQnxjvnwxY7SQpkWL04dCkqRFWwAl0AMUABrgIlC6CDr6ANu7yn4IfHt+/dvA//yINWwAqoFL76cB2AbsBwSwGjjzMen5LvCt99i3dP7aaYH8+Wuq/AvryQCq59eTgc75ehczRgtpWrQ4fZhlsTOBWqBbkqQrkiRFgGeAHYus6So7gN/Or/8W2PlRViZJ0tvAxA1q2AH8uzTHacAihMj4GPQsxA7gGUmSwpIk9QLdzF3bv6SeUUmSzs+vzwBtgJPFjdFCmhbiI4/Th2GxTcAJDF7z8xDXD+JHhQQcFEKcE0J8Zb4sTZKk0fl1F/DxzkF1fQ2LGbdH59Pr31zTRPpY9Qgh8oAq4Aw3SYzepQlugjjdKIttAjcL6yRJqga2Al8XQmy4dqM0l8st6m2Um0ED8AtgCVAJjAKPfdwChBBG4AXg7yRJmr5222LF6D00LXqcPgiLbQLDQPY1P2fNl32sSJI0PP/pBvYwl6KNXU0f5z/dH7eu62hYlLhJkjQmSVJckqQE8Cv+kMp+LHqEEGrm/tieliTpxfniRY3Re2la7Dh9UBbbBBqAIiFEvhBCAzwM7P04BQghkoQQyVfXgc3ApXkdX5jf7QvAwhO8f3QspGEv8Pn5HvDVwNQ1KfFHxrva1LuYi9NVPQ8LIbRCiHygCDj7F65bAI8DbZIk/eSaTYsWo4U0LWacPhSL3TPJXC9uJ3M9pd9ZhPoLmOuxvQi0XtUApAJvAl3AG0DKR6zj98yljlHm2oqPLKSBuR7v/zMfsxag5mPS8+R8fc3M/UJnXLP/d+b1dABbPwI965hL9ZuBpvll2yLHaCFNixanD7PITwzKyNziLHZzQEZGZpGRTUBG5hZHNgEZmVsc2QRkZG5xZBOQkbnFkU1ARuYWRzYBGZlbHNkEZGRucf4/k6sohWfuDJcAAAAASUVORK5CYII=\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light", "tags": [] }, "output_type": "display_data" } ], "source": [ "temp, mask = explanation.get_image_and_mask(106, positive_only=True, num_features=5, hide_rest=True)\n", "plt.imshow(mark_boundaries(temp / 2 + 0.5, mask))" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "Z2MSbZ6kxwmP" }, "source": [ "Pros and cons:" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 287 }, "colab_type": "code", "id": "6HmKJVr1xwmR", "outputId": "7d369717-cefc-461d-d01f-49389dddd177" }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 16, "metadata": { "tags": [] }, "output_type": "execute_result" }, { "data": { "image/png": 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"nbformat_minor": 1 } ================================================ FILE: doc/notebooks/Tutorial - MNIST and RF.ipynb ================================================ { "cells": [ { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "# Overview\n", "The notebook shows how the ```lime_image``` tools can be applied to a smaller dataset like mnist. The dataset is very low resolution and allows quite a bit of rapid-iteration." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "from skimage.color import gray2rgb, rgb2gray, label2rgb # since the code wants color images" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": true, "deletable": true, "editable": true }, "outputs": [], "source": [ "from sklearn.datasets import fetch_openml\n", "mnist = fetch_openml('mnist_784')\n", "# make each image color so lime_image works correctly\n", "X_vec = np.stack([gray2rgb(iimg) for iimg in mnist.data.reshape((-1, 28, 28))],0).astype(np.uint8)\n", "y_vec = mnist.target.astype(np.uint8)" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "%matplotlib inline\n", "fig, ax1 = plt.subplots(1,1)\n", "ax1.imshow(X_vec[0], interpolation = 'none')\n", "ax1.set_title('Digit: {}'.format(y_vec[0]))" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "# Setup a Pipeline\n", "Here we make a pipeline for processing the images where basically we flatten the image back to 1d vectors and then use a RandomForest Classifier" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "from sklearn.pipeline import Pipeline\n", "from sklearn.ensemble import RandomForestClassifier\n", "from sklearn.preprocessing import Normalizer\n", "\n", "class PipeStep(object):\n", " \"\"\"\n", " Wrapper for turning functions into pipeline transforms (no-fitting)\n", " \"\"\"\n", " def __init__(self, step_func):\n", " self._step_func=step_func\n", " def fit(self,*args):\n", " return self\n", " def transform(self,X):\n", " return self._step_func(X)\n", "\n", "\n", "makegray_step = PipeStep(lambda img_list: [rgb2gray(img) for img in img_list])\n", "flatten_step = PipeStep(lambda img_list: [img.ravel() for img in img_list])\n", "\n", "simple_rf_pipeline = Pipeline([\n", " ('Make Gray', makegray_step),\n", " ('Flatten Image', flatten_step),\n", " #('Normalize', Normalizer()),\n", " #('PCA', PCA(16)),\n", " ('RF', RandomForestClassifier())\n", " ])" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "from sklearn.model_selection import train_test_split\n", "\n", "X_train, X_test, y_train, y_test = train_test_split(X_vec, y_vec,\n", " train_size=0.55)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [ { "data": { "text/plain": [ "Pipeline(steps=[('Make Gray', <__main__.PipeStep object at 0x0000024B3F533A20>), ('Flatten Image', <__main__.PipeStep object at 0x0000024B3F533828>), ('RF', RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini',\n", " max_depth=None, max_features='auto', max_leaf_nodes=None,\n", " ...imators=10, n_jobs=1, oob_score=False, random_state=None,\n", " verbose=0, warm_start=False))])" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "simple_rf_pipeline.fit(X_train, y_train)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "%load_ext autoreload\n", "%autoreload 2\n", "import os,sys\n", "try:\n", " import lime\n", "except:\n", " sys.path.append(os.path.join('..', '..')) # add the current directory\n", " import lime" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": true, "deletable": true, "editable": true }, "outputs": [], "source": [ "from lime import lime_image\n", "from lime.wrappers.scikit_image import SegmentationAlgorithm\n", "explainer = lime_image.LimeImageExplainer(verbose = False)\n", "segmenter = SegmentationAlgorithm('quickshift', kernel_size=1, max_dist=200, ratio=0.2)" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": false, "deletable": true, "editable": true, "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Wall time: 3.34 s\n" ] } ], "source": [ "%%time\n", "explanation = explainer.explain_instance(X_test[0], \n", " classifier_fn = simple_rf_pipeline.predict_proba, \n", " top_labels=10, hide_color=0, num_samples=10000, segmentation_fn=segmenter)" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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RzhcjYjq53+RHGbgoH6x90P/nbG/gvjTALeUKXA28g5zXW81s/u1Inve0eHddBDw3Ip7X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\nSVIvMo9KGu9qX9C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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "\n", "temp, mask = explanation.get_image_and_mask(y_test[0], positive_only=True, num_features=10, hide_rest=False, min_weight = 0.01)\n", "fig, (ax1, ax2) = plt.subplots(1,2, figsize = (8, 4))\n", "ax1.imshow(label2rgb(mask,temp, bg_label = 0), interpolation = 'nearest')\n", "ax1.set_title('Positive Regions for {}'.format(y_test[0]))\n", "temp, mask = explanation.get_image_and_mask(y_test[0], positive_only=False, num_features=10, hide_rest=False, min_weight = 0.01)\n", "ax2.imshow(label2rgb(3-mask,temp, bg_label = 0), interpolation = 'nearest')\n", "ax2.set_title('Positive/Negative Regions for {}'.format(y_test[0]))" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [ { "data": { "image/png": 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QvWS9J9Ra+/ruv1fVoVV1ywzvWu2oqkOm3N3BS/68f2vtja21NyT58QxXKzx3FnNmS1MD\nLDL5Z9GpARaZ/C8ATfMaVdWNkjw2wzs1O6rqiKo6Isk5Sb4zyQOWbL4jyaWttSs3YF4/XFXvrapr\nklyZ4d2hUyZ333zK3V03+fODrbX/XB2vtXZJkr/LsPABC0oNqIFFJv/yv+jUgBpYZPK/OPm3evba\n3T/JbZP8TJLHLbuvZXj36b0zeq7e71Lbb+k/qmrH5Dk/keSXklyS4fMRD0nyi5n+zZLdBXL5yH1X\nJLnHlPtje1EDamCRyb/8Lzo1oAYWmfwvSP41zWv3xAwhemaSWnbfo5KcUFXPmFwmcWGSB1bVt+3l\nXaZeUXw5ybeNjN9x2b8fluTGSR7WWvv33YNV9YDsm48m+UaS24/cd7sM716xuNSAGlhk8i//i04N\nqIFFJv8Lkn+XZ69BVR2Y4fexvbO19rbW2l8svSV5dZJDkzx88pC3Zvien7SXXV+b8aK4MMnNq+qu\nS+Zw2wwf0F/q+smfN1qy3c2TPGVVX9gyrbVrMvxC8/tU1VFL9nmXDJdknLkv+2XrUwNqYJHJv/wv\nOjWgBhaZ/C9W/qu13psZ7E1VPTbDsvIPb62dMXJ/ZVgY4EOttUdMxv4ow7tS75ncbpThl4Wf1Vp7\nzWSbM5Icn6GoLk2ys7V2TlXdIsMS9ZcneWWSm2VYUv6KJPdqre03efxRSc5Lcn6GZeoPSfK0DKvx\n3T3JnVprn5lse3aS1lq7/16+1rsk+fBkH6/M8G7aL0zmf6/W2uem+uaxLagBNbDI5F/+F50aUAOL\nTP4XLP9tjkt3b/VbktOTXJPkwD1sc1qSryX59sm/K8PvS/tYhg/WX5bkjCT3WPKYozIsKHBNhneL\nTlty3wOS/MvksR/P8PmJsaXmH5LknzO8W3Vhkv+W4R2m65McvmS7s5O8b5Vf7z2S/FWSqzIsKvDW\nJEfM+//BbX43NaAGFvkm//K/6Dc1oAYW+Sb/i5V/Z5oBAACgw2eaAQAAoEPTDAAAAB2aZgAAAOjQ\nNAMAAECHphkAAAA69p/3BJLkYVWW8N4EVvyCuQXTWqt5PXepAeZM/llk88x/ogaYP8cAFtlq8u9M\nMwAAAHRomgEAAKBD0wwAAAAdmmYAAADo0DQDAABAh6YZAAAAOjTNAAAA0KFpBgAAgA5NMwAAAHRo\nmgEAAKBD0wwAAAAdmmYAAADo0DQDAABAh6YZAAAAOjTNAAAA0LH/vCfA+rrvcceNjj/4IQ9ZMXbC\nhz88uu3Pvf3tM50TbJTjOvl/yEj+k+TDIzXwdvlni5J/Fp0aYJHJ/2w50wwAAAAdmmYAAADo0DQD\nAABAh6YZAAAAOjTNAAAA0GH17G3ikSecMDr+xCc9aXR8//32WzH23UcfPbrtKeedNzp+0UUXrXJ2\nsL5O6OT/SZ387zeS/yQ5eqQGzpN/Njn5Z9GpARaZ/G8MZ5oBAACgQ9MMAAAAHZpmAAAA6NA0AwAA\nQIemGQAAADqsnr3FPOqRjxwdf/zjHz86PrZKdk9vNb1Tjj12dPxxC7hyHvP3yJEa6OW/l+mese2P\n7eR/EVeOZP7kn0WnBlhk8j8/zjQDAABAh6YZAAAAOjTNAAAA0KFpBgAAgA5NMwAAAHRYPXuTeulL\nXzo6fsxd7jI6vv/+0/1XfvrCC1eMPeLUU0e3/cIXvjDVvmEWejVwl5EamDb/F47kP0lOHakB+Wce\n5J9FpwZYZPK/+TjTDAAAAB2aZgAAAOjQNAMAAECHphkAAAA6NM0AAADQYfXsDXSrW91qdPzpT3/6\nirHv/d7vHd22pnzOsVWyk+Q+L3vZijEr5LGepsl/0q+BafRWiHzZSP4TNcD6kX8WnRpgkcn/2j20\nM37GBj2/M80AAADQoWkGAACADk0zAAAAdGiaAQAAoMNCYBvoMY95zOj4Dx177Jr3fdHOneP7PuWU\n0fEvfvGLa35OmEYv/8fOIP87O/k/Rf7ZJOSfRacGWGTyv37GFghbj8XBnGkGAACADk0zAAAAdGia\nAQAAoEPTDAAAAB2aZgAAAOjYNqtnT7tK2thKa7NyyMEHj44fdeSRa973xRdfPDr+/S960ej4lVde\nuebnhGkdPFIDR84g/8l4DbxI/tlE5J9FpwZYZPK/NrPo0Xr7WMuq2s40AwAAQIemGQAAADo0zQAA\nANChaQYAAIAOTTMAAAB0bMnVs9ey8tlGeOaznjU6vmPHjlXv46KdO0fH33H66aPjW3WFPLanZ43U\nwDT5T5KdnRo4faQG5J/NZD3zv0v+2QIcA1hkG53/4+R/QzjTDAAAAB2aZgAAAOjQNAMAAECHphkA\nAAA6NM0AAADQsSVXz94sjuishHfve997zfu+5wteMDp+9dVXr3nfMCu91SBnUQMvUANscvLPolMD\nLLL1zP85nfzfTP7X5KFreKwzzQAAANChaQYAAIAOTTMAAAB0aJoBAACgw0Jga3CHO9xhdPzGBxww\n1X4+d9llK8a++tWv7tOcYCP1auCAKWrgspH8J2qAzU/+WXRqgEUm/4vFmWYAAADo0DQDAABAh6YZ\nAAAAOjTNAAAA0KFpBgAAgA6rZ6/BAx/4wKm2//rXvz46fq8XvnDF2PXXX79Pc1ruz5/85NHxjx9x\nxIqxXbt2jW77ile8YnT8y1/+8r5PjG1hmhro5f+FI/lPZlMDT+7k/4iR/CfjNSD/9Gz2/E/z+p/I\nP9Pb7DXgGMB6mkX+z+nk/5szyP8tO/n/xU7+r5f/PXKmGQAAADo0zQAAANChaQYAAIAOTTMAAAB0\naJoBAACgY1Ovnn3GvCcwccSOHaPjtz/ssKn2c9bZZ4+O3/vyy1e9j9735Ha3u93o+JX3ve/o+D1u\nc5sVY6210W1f8pKXjI6feeaZo+Pvete7Voz1VuZma9jRqYHDpqiBszv5v3yK/Pf08n/fTv5vM5L/\nZLwGZpH/RA1sZeuZ/2le/5PxY8AsXv8T+afPMWAlNbA41jP/r58y/w8dGbt9J/8v7uT/O6bI/8md\n/P9VJ//v7uR/bGXurcaZZgAAAOjQNAMAAECHphkAAAA6NM0AAADQoWkGAACAjk2xevZmWSW755a3\nvOXo+M0PPXSq/ezcuXPNcxlbNS9Jcumlo8Onnnrq6PijHvWoFWNHHXXU6LaHH3746PjTnva00fH9\n9ttvxdjpp58+um1vxW42l14NHDpFDcwi/z2XziD/yXgNzCL/yXgNyP/WsJ75n/YgPHoMkH/WmWPA\nSmpgcWym/I/2TJ38H76O+X96J//7d/L/9m2Qf2eaAQAAoEPTDAAAAB2aZgAAAOjQNAMAAECHphkA\nAAA6NsXq2Zvd3e9+96m2v/baa0fHL7zwwllMZyq3+vu/Hx3/x/POWzF2eGc1vQMf/eipnvOpT33q\nirEdH//46La/dcEFU+2b+ZhFDcwj/3/fyf95I/lPxleUfPQM8p8kHx+pgQvkf0vo5f9hne3H8v/f\nO/k/el8ntQrTvP4n48eAWbz+J+PHAK//W4djwOo5Bmw/WzX/v9bJ/ylT5P+PZpT/3xjJ/1FbLP/O\nNAMAAECHphkAAAA6NM0AAADQoWkGAACAjmqtzXsOqar5T2IPXn6f+4yOP+95zxsd730xr37Vq0bH\n//q9792Xac1cdcYPPOig0fGjjx5fwuauv/IrK8bOP//80W1POumkVc1tI7TWet+CdbfZa+A+U9bA\nmFd18v/eTZL/noOmzP+vjOQ/Ga8B+R9s1fz/3RTHgJ/o5P/ATZT/sQDM4vU/kf+92ao14BiwkmPA\n9OR/85o2/x+cIv8v3ET5f+cq8u9MMwAAAHRomgEAAKBD0wwAAAAdmmYAAADo0DQDAABAx/7znsBW\ncPkVV4yOX3311aPjhxxyyOj4jh07Zjan9dBbuvC6664bHT/33HNHxw+/6qoVYwcccMC+TotN4IoZ\n1MBmz3/PtPm/aiT/iRrYytYz/5fu+7RmbuwYMIvX/0T+tzrHgJUcAxaH/K80bf733wb5d6YZAAAA\nOjTNAAAA0KFpBgAAgA5NMwAAAHRomgEAAKDD6tmr8Duf/vTo+NMuuWR0/Jhjjhkdf9CDHzw6fuSR\nR64Ye8Mb3zi67a5du0bHr7nmmtHxnoMPPnjV2979bncbHf/sPe85Ov7kW9xixdgf7z8etRMPO2x0\n/LWf/ewqZ8dG+HSnBi6ZogYePEX+k+SNU9TAeub/bp3837OT/1uM5D9J9h+pgcM6+f+s/G8qs8j/\nazr5/3Qn/9McAzb7638yfgzw+r91OAas5BiwOOR/pRd28v/BTv6PH8n/uZ3832OT5t+ZZgAAAOjQ\nNAMAAECHphkAAAA6NM0AAADQoWkGAACADqtnr8G73/3u0fE73elOo+MHHXTQ6PhRRx21YuylJ588\n1Vyuuuqq0fGqGh0/5JBDptr/Wp1//vmj45d0Vsh76Aye84wZ7IM9m6YGpsl/kpw8RQ1s9vwn4zVg\nhdStbT3zP80xYKvm3+v/1ucYsHqOAdvPIud//Kf65IDe9lPkfxZVMYvjyHLONAMAAECHphkAAAA6\nNM0AAADQoWkGAACADk0zAAAAdFg9ew2e+4EPjI5ff/31o+Mnnnji6PhNbnKTVY3tyaGHHjrV9rPw\nH9/4xuj4b37ykyvGPvva1673dFZYj5XzuKEPTFED0+R/T+Nj5pH/b3Ty/8mR/CfJa+dQA6yvaY4B\n2y3/07z+Jxt/DPD6vzEcA1ZyDFgc8r/SnTv5P36D878ev0HBmWYAAADo0DQDAABAh6YZAAAAOjTN\nAAAA0FGttXnPIVU1/0nM0fOOOWbF2CNOOGF021vf+taj45/+1KdGx3vf2M9deumq5rYnF+3cOTp+\n7rnnrnnf8/DO1mpez73INXDMSP6T5IQpauBTnfz3XDqD/O/cZvlv8j8XY6//yXTHAK//azfP1/9k\nsWvAMWBzcAyYD/nfHFaTf2eaAQAAoEPTDAAAAB2aZgAAAOjQNAMAAECHphkAAAA6rJ7Nf3rovCcw\nZ1bPZpFZOZVFPgZYPZtF5xjAIrN6NgAAAKyBphkAAAA6NM0AAADQoWkGAACADk0zAAAAdOw/7wkw\nH4u8SirAIvP6DwDTcaYZAAAAOjTNAAAA0KFpBgAAgA5NMwAAAHRomgEAAKDD6tkL6oyRMSuqAmx/\nY6//iWMAAPQ40wwAAAAdmmYAAADo0DQDAABAh6YZAAAAOjTNAAAA0KFpBgAAgA5NMwAAAHRomgEA\nAKBD0wwAAAAdmmYAAADo0DQDAABAh6YZAAAAOjTNAAAA0KFpBgAAgA5NMwAAAHRomgEAAKCjWmvz\nngMAAABsSs40AwAAQIemGQAAADo0zQAAANChaQYAAIAOTTMAAAB0aJoBAACgQ9MMAAAAHZpmAAAA\n6NA0AwAAQIemGQAAADo0zQAAANChaQYAAIAOTTMAAAB0aJoBAACgQ9MMAAAAHZpmAAAA6NA0AwAA\nQIemGQAAADo0zQAAANChaQYAAIAOTTMAAAB0aJoBAACgQ9MMAAAAHZpmAAAA6NA0AwAAQIemGQAA\nADo0zQAAANChaQYAAIAOTTMAAAB0aJoBAACgQ9MMAAAAHZpmAAAA6NA0AwAAQIemGQAAADo0zQAA\nANChaQYAAIAOTTMAAAB0aJoBAACgQ9MMAAAAHZpmAAAA6NA0AwAAQIemGQAAADo0zQAAANChaQYA\nAIAOTTMAAAB0aJoBAACgQ9MMAAAAHZpmAAAA6NA0AwAAQIemGQAAADo0zQAAANChad4AVfWUqtpV\nVYevYtv7TbY9fiPmtuy571xVZ1bVlVV1fVU9fKPnwPYj/yw6NcAik38WnRrYHhauaa6qJ0/CuPt2\nXVWdX1WvqqrbrNPTtslt6TxOrKon72H7eXhDku9J8vwkT0ryj+v5ZMv+H5benruez7vI5H+PNjT/\nSVJVt6mq36uqz07+L3ZW1anr/byLTA3s0YbVwMj/w/Lb49bruReZ/O/RRv8MdGhV/a+quqCqvlpV\nF1fVqVX1Xev5vItODezRRtfAbarqD6rq8kkNfKSqHr2ez7kW1dq8/l/mYxLQ05K8IMnFSQ5MclyS\nn538+66tta/N+DkryQGttf9YMvbRJJ9vrd1/ZPsbL912I1TVgUm+muTk1tpJG/Scu5KcmaFIl/rn\n1tonNmKoqmn/AAAdoUlEQVQOi0b+u3OcR/4PS/J/k+xK8vtJ/j3J7ZL8QGvtERsxh0WkBrpz3NAa\nqKo7JrnPyF2/nORuSQ5rrV2x3vNYNPLfneNG57+SfDjJdyf5P0k+leTOSZ6V5CtJ7tJau3a957GI\n1EB3jhtdA4ck+ackt07yO0kuT/KYJPdL8vjW2p+t9xymtf+8JzBH72mt/dPk76dV1ZeS/FKSn0ry\nplk+URvemVh1+De6UCZ2v7v2lVntsKpu2lr76l42u6C19iezek5WTf5vaB75f12G78v3t9aunNXz\nsmpq4IY2tAZaaxdn+AF16fYHJnltkvdpmNed/N/QRh8Djk3y/Ume2Vr73SWPuSDJ65P8WJLTZzUX\nRqmBG9roGnhGkh1J7t9a+5vJ9r+b5O+T/L9V9eettW/Oai6zsHCXZ+/BWUkqyZ12D1TVnarqLVX1\nxaq6tqo+VFUPXv7AqvqFqvrXyTZfqqp/qKqfWXL/DT7LUFU7M1z+8CNLLg85a3LfDT7LMLlc5OrJ\nDxPLn/dPq+rSyTtYu8ceVFV/W1XXVNVVVXVGVR2zpy+8qk7K8MNLS/Kbk+e/aMn996yqv6yqr0zm\n8t6q+sFl+9h9ucvxVfWaqro8ySV7et4ljz2wqm6ymm1ZN/K/gfmvqqOT/GSS/9Vau7KqblJVi/wm\n5magBuZ0DFji4UkOSfLHUz6OtZP/jc3/oZM/l785dNnkz+v2NGfWhRrY2Bo4LsOZ9r/ZPTB5c+HN\nSb4zwxnnTUXT/C13nvz5xWS4zj7Jh5L8eJJXZ7i+/yZJ3lFVP7X7QVX19CSvSPKvSZ6T5IVJ/jnJ\n0jAt/yzDc5J8NsknkjwhyROTnLJs+93elOSmSR6ydLJVdVCShyZ5yyRkqaonJTkjydVJnpvkJUnu\nkuQDtefFB96a5BczvFj8yWQ+vzjZ5/ck+dsk35vk1yf7vGOS91fVvUf29ZoMlxu9eLL93jwlybVJ\nrquqj5XPsc2L/G9s/n9s8nV+vqrel+EHpOuq6t1VdYc9PI71owbmcwxY6gkZLg9825SPY+3kf2Pz\n/48ZfvY5uap+tKpuV1X3S/IbSc5J8t49PJb1oQY2tgZukvE3h746mcf37eGx89FaW6hbkicnuT7J\njya5ZZLbJ3lsks8nuSbJbSfb/fZkux9a8tibJbkwyYVLxt6W5LxVPufhS8Y+muSskW3vN9n2+CVj\nlyR587Ltfnqy3Q8vmduXkrx22Xa3TvLlJL+7lzneIcNnK3952fjbMoT6DkvGvjPD5RtnL/sadyV5\nfzJ8Vn4V/xcfSPJfMxT9zyf5l8k+/su8c7Jdb/K/OfKf4fM7uybf93cleXSGz3JeleSCJAfOOyvb\n9aYGNkcNjDz/tyf5WpI/mXdGtvNN/jdP/pM8KMNaFruW3N6d5Kbzzsl2vqmBzVEDGd5o+EaS71o2\n/qeTr+sV887K8tuinmmuJO/LUCCXZHhX5aokj2itfW6yzYOSnNNa+9DuB7VhUYbXJbnjkksdrkxy\nWFV9/zrO9y1JHlxVN10y9tgk/95a++Dk3z+e5OZJ/qyqbrn7luHdqg9neHGYSlXdaLLft7XW/m33\neGvtsgzfs+Oq6uAlD2lJfr9NUr83rbX7ttZe3Vo7o7X2ugzvKv1rkpeVy7XXk/yvwjrnf/fjLm2t\nPaS19uettd9K8vQM73Y/ftr5MhU1sArrfQxY5qeTHBCXZm8E+V+FDcj/FzIshPSrGT5He1KS45P8\n4bRzZWpqYBXWuQZOzdBkv6WqfqiqdlTVrybZvRDqQdPOd70tatPckpyY4RLJH0lyTGvtiNba0sth\n7pDk/JHHfmLJ/clwKc01Sc6p4dcGvLqqxlYEXYvdl2Y8PEmq6mYZivnNS7Y5MsOLwNkZXgR2367I\nEPhb78Pz3nryvBeM3PeJDPlZ/qsRLt6H50mStOED/69O8m3ZjJdlbB/yvzrrmf/rMvw/vGXZ+FuS\nfDPjqwozO2pgdTbyGPCEDGdJ3rOPj2f15H911i3/VbVjMtfXt9Z+o7X2ztbayUmemeTRVfUT+zBf\nVk8NrM661UBr7aNJHpdhMbC/S/LpDFefPifD13HNPsx3XS3ywjP/0L61at4+a619soZFfR6aYWGf\nRyZ5ZlW9uLX24rXuf/IcH66qizMsxf5nGYrmwNywWG6U4UXgiRmWbV9uo1agW+viFbsXDbjFWifC\nHsn/+lht/i+d/HmDubbWdlXVFzNcqsr6UgPrY+pjQA2/l/a4DJcPXj/7KTFC/tfHavP/lAyf6XzX\nsvF3TP784SR/NaM5MU4NrI9VHwNaa39RVe9Icvck+2W48mL3GfGxRn2uFrlp3pt/S3L0yPhdltyf\nJGmtXZfhDNFbalgB921Jfq2qXt76y8ZPe/nam5M8e3IZxGOTXNxaO2fJ/RdmeGfm8621s6bcd8/n\nM3wgv/d92JXpV0fdmyOWPDfzI//rm/+PZJjv7ZcOVtUBSW4V+d8M1MDGHQN2fxzBpdmbh/yvb/5v\nk2G++2X4XOduB0z+9PP5/KmBDTgGTK4y/cjuf1fVj2f43my6xfAW9fLs1Xh3kh+oJUuqTy6H+Pkk\nO1trH5+M3eCM6OQ//xMZgntA+q7NcBnyar0pw7uST0nyE1n5O+T+KsPnMZ5fI7+6pqpuNcVzJRnO\neiU5M8lPLV11r6q+I8MlFR9ore3T5RNj86nhF53/YobP+XxkxYPYSPK/jvnPsFDGFUmeUFU3XjL+\n1Ayvy2fu436ZHTWwvjWw1OOSfKa19n9nsC9mQ/7XN/8XZHitf8yy8cdnaBjWfAaUNVMDG3cM2L3f\nI5P8lyTvbK19elb7nZVFfSer9r5Jfj1DIN5TVa/M8Fmrp2T4DMMjl2x3ZlVdluSDGS6HOCbJs5Kc\nMVkwoOcjSZ5RVb+W4Tr+K1prZ/fm11r756q6MMOS9DfODS/JSGvt6qo6MckbkvxTVf1ZhneIDs+w\nTP3fJXn2Kr7u5f5nhs98fLCqXpNhRbufn8zhucu2Xc33dbdnVdUjkrwzyWeS3C5Dw/BdSZ7YNtkv\nNN9m5H/11iX/rbX/qKr/kWHBlw9U1RszfG+fneFXO/iVO+tLDazeeh0DhgdU3TXJ3ZK8bB/mxr6R\n/9Vbr/z/YZL/nuT3qupeST6WYS2Xn8uwIOrb92GurJ4aWL11OwZU1ccynKH/TIbPNj8jw4mzE/dh\nnuuvbYIlvDfylm8t+36vVWx7xwzv5HwxwztCH0ryk8u2eVqGD91fkeEShguSvDzJwSPPuXSp+dtk\n+OzKlZP7zpqMr1hqfsljTp7c98k9zPn4DO+OfWky5wuSvD7JPffytd5hsu9fGrnv7pN9fiXD7377\n6yQ/sK/f18n2P5ZhwZd/z/BrRr44eY77zTsj2/km/5sj/0se95gMZxS+muFzzr+T5Gbzzsl2vqmB\nTVcDL5s87nvmnY1FuMn/5sl/ktsm+f0MDdN1GX5v72uT3GLeOdnONzWwqWrgjzMsHHZdhsu8X53k\nVvPOSO9Wk0kDAAAAy/hMMwAAAHRomgEAAKBD0wwAAAAdmmYAAADo0DQDAABAh6Z5wVXV+6vqrHnP\nA+ZFDbDI5J9FpwZYZPK/epr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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# now show them for each class\n", "fig, m_axs = plt.subplots(2,5, figsize = (12,6))\n", "for i, c_ax in enumerate(m_axs.flatten()):\n", " temp, mask = explanation.get_image_and_mask(i, positive_only=True, num_features=1000, hide_rest=False, min_weight = 0.01 )\n", " c_ax.imshow(label2rgb(mask,X_test[0], bg_label = 0), interpolation = 'nearest')\n", " c_ax.set_title('Positive for {}\\nActual {}'.format(i, y_test[0]))\n", " c_ax.axis('off')" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "# Gaining Insight\n", "Can we find an explanation for a classification the algorithm got wrong" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Using #9381 where the label was 8 and the pipeline predicted 9\n" ] } ], "source": [ "pipe_pred_test = simple_rf_pipeline.predict(X_test)\n", "wrong_idx = np.random.choice(np.where(pipe_pred_test!=y_test)[0])\n", "print('Using #{} where the label was {} and the pipeline predicted {}'.format(wrong_idx, y_test[wrong_idx], pipe_pred_test[wrong_idx]))" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Wall time: 2.44 s\n" ] } ], "source": [ "%%time\n", "explanation = explainer.explain_instance(X_test[wrong_idx], \n", " classifier_fn = simple_rf_pipeline.predict_proba, \n", " top_labels=10, hide_color=0, num_samples=10000, segmentation_fn=segmenter)" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [ { "data": { "image/png": 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aAQAAoEPTDAAAAB2aZgAAAOjQNAMAAECHphkAAAA6rJ69xR1zzDGj409/+tPX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\n//XTNM9QVT2lqm6sqvft4XG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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# now show them for each class\n", "fig, m_axs = plt.subplots(2,5, figsize = (12,6))\n", "for i, c_ax in enumerate(m_axs.flatten()):\n", " temp, mask = explanation.get_image_and_mask(i, positive_only=True, num_features=10, hide_rest=False, min_weight = 0.01 )\n", " c_ax.imshow(label2rgb(mask,temp, bg_label = 0), interpolation = 'nearest')\n", " c_ax.set_title('Positive for {}\\nActual {}'.format(i, y_test[wrong_idx]))\n", " c_ax.axis('off')" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true, "deletable": true, "editable": true }, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.5.2" }, "widgets": { "state": {}, "version": "1.1.2" } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: doc/notebooks/Tutorial - continuous and categorical features.ipynb ================================================ { "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import sklearn\n", "import sklearn.datasets\n", "import sklearn.ensemble\n", "import numpy as np\n", "import lime\n", "import lime.lime_tabular\n", "np.random.seed(1)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Continuous features" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Loading data, training a model" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For this part, we'll use the Iris dataset, and we'll train a random forest. " ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "iris = sklearn.datasets.load_iris()" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "train, test, labels_train, labels_test = sklearn.model_selection.train_test_split(iris.data, iris.target, train_size=0.80)\n" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "RandomForestClassifier(n_estimators=500)" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "rf = sklearn.ensemble.RandomForestClassifier(n_estimators=500)\n", "rf.fit(train, labels_train)\n" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.9666666666666667" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sklearn.metrics.accuracy_score(labels_test, rf.predict(test))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Create the explainer" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As opposed to lime_text.TextExplainer, tabular explainers need a training set. The reason for this is because we compute statistics on each feature (column). If the feature is numerical, we compute the mean and std, and discretize it into quartiles. If the feature is categorical, we compute the frequency of each value. For this tutorial, we'll only look at numerical features." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We use these computed statistics for two things:\n", "1. To scale the data, so that we can meaningfully compute distances when the attributes are not on the same scale\n", "2. To sample perturbed instances - which we do by sampling from a Normal(0,1), multiplying by the std and adding back the mean.\n" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "explainer = lime.lime_tabular.LimeTabularExplainer(train, feature_names=iris.feature_names, class_names=iris.target_names, discretize_continuous=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Explaining an instance" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Since this is a multi-class classification problem, we set the top_labels parameter, so that we only explain the top class." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "i = np.random.randint(0, test.shape[0])\n", "exp = explainer.explain_instance(test[i], rf.predict_proba, num_features=2, top_labels=1)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We now explain a single instance:" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " \n", " \n", "
\n", " \n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "exp.show_in_notebook(show_table=True, show_all=False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now, there is a lot going on here. First, note that the row we are explained is displayed on the right side, in table format. Since we had the show_all parameter set to false, only the features used in the explanation are displayed.\n", "\n", "The *value* column displays the original value for each feature.\n", "\n", "Note that LIME has discretized the features in the explanation. This is because we let discretize_continuous=True in the constructor (this is the default). Discretized features make for more intuitive explanations.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Checking the local linear approximation" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "feature_index = lambda x: iris.feature_names.index(x)" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Increasing petal width\n", "P(setosa) before: 1.0\n", "P(setosa) after: 0.482\n", "\n", "Increasing petal length\n", "P(setosa) before: 1.0\n", "P(setosa) after: 0.55\n", "\n", "Increasing both\n", "P(setosa) before: 1.0\n", "P(setosa) after: 0.032\n" ] } ], "source": [ "print('Increasing petal width')\n", "temp = test[i].copy()\n", "print('P(setosa) before:', rf.predict_proba(temp.reshape(1,-1))[0,0])\n", "temp[feature_index('petal width (cm)')] = 1.5\n", "print('P(setosa) after:', rf.predict_proba(temp.reshape(1,-1))[0,0])\n", "print ()\n", "print('Increasing petal length')\n", "temp = test[i].copy()\n", "print('P(setosa) before:', rf.predict_proba(temp.reshape(1,-1))[0,0])\n", "temp[feature_index('petal length (cm)')] = 3.5\n", "print('P(setosa) after:', rf.predict_proba(temp.reshape(1,-1))[0,0])\n", "print()\n", "print('Increasing both')\n", "temp = test[i].copy()\n", "print('P(setosa) before:', rf.predict_proba(temp.reshape(1,-1))[0,0])\n", "temp[feature_index('petal width (cm)')] = 1.5\n", "temp[feature_index('petal length (cm)')] = 3.5\n", "print('P(setosa) after:', rf.predict_proba(temp.reshape(1,-1))[0,0])\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Note that both features had the impact we thought they would. The scale at which they need to be perturbed of course depends on the scale of the feature in the training set." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We now show all features, just for completeness:" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " \n", " \n", "
\n", " \n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "exp.show_in_notebook(show_table=True, show_all=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Categorical features" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For this part, we will use the Mushroom dataset, which will be downloaded [here](http://archive.ics.uci.edu/ml/machine-learning-databases/mushroom/agaricus-lepiota.data). The task is to predict if a mushroom is edible or poisonous, based on categorical features." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Loading data" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "data = np.genfromtxt('http://archive.ics.uci.edu/ml/machine-learning-databases/mushroom/agaricus-lepiota.data', delimiter=',', dtype='\n", " \n", " \n", "
\n", " \n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "i = 137\n", "exp = explainer.explain_instance(test[i], predict_fn, num_features=5)\n", "exp.show_in_notebook()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now note that the explanations are based not only on features, but on feature-value pairs. For example, we are saying that odor=foul is indicative of a poisonous mushroom. In the context of a categorical feature, odor could take many other values (see below). Since we perturb each categorical feature drawing samples according to the original training distribution, the way to interpret this is: if odor was not foul, on average, this prediction would be 0.24 less 'poisonous'. Let's check if this is the case" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array(['almond', 'anise', 'creosote', 'fishy', 'foul', 'musty', 'none',\n", " 'pungent', 'spicy'], dtype='\n", " \n", " \n", "
\n", " \n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "np.random.seed(1)\n", "i = 1653\n", "exp = explainer.explain_instance(test[i], predict_fn, num_features=5)\n", "exp.show_in_notebook(show_all=False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Note that capital gain has very high weight. This makes sense. Now let's see an example where the person has a capital gain below the mean:" ] }, { "cell_type": "code", "execution_count": 70, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " \n", " \n", "
\n", " \n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "i = 10\n", "exp = explainer.explain_instance(test[i], predict_fn, num_features=5)\n", "exp.show_in_notebook(show_all=False)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "lime3", "language": "python", "name": "lime3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.7" } }, "nbformat": 4, "nbformat_minor": 1 } ================================================ FILE: doc/notebooks/Tutorial - images - Pytorch.ipynb ================================================ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Using Lime with Pytorch" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In this tutorial we will show how to use Lime framework with Pytorch. Specifically, we will use Lime to explain the prediction generated by one of the pretrained ImageNet models.\n", "\n", "Let's start with importing our dependencies. This code is tested with Pytorch 1.0 but should work with older versions as well." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "scrolled": true }, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "from PIL import Image\n", "import torch.nn as nn\n", "import numpy as np\n", "import os, json\n", "\n", "import torch\n", "from torchvision import models, transforms\n", "from torch.autograd import Variable\n", "import torch.nn.functional as F" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Load our test image and see how it looks." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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ne4OkM72yHCXlqc/EkJcZBoMKXGhhHDq0VuMGDreu32B3dxc/UPiuh7Ut0nfQRpJnCyLPoR/GGKspsowoStjbP8d6MafOKnpBwmKxwPNjAnfAy88f8sSffhpLhO+MQUnS/JgwkgS+xFAzTY8IIoV0BP1xQt2kDEYD0lWJ71gsLaOxwzpb4HqWJPbphSF1IegPYqbLOUUpcX3YHo0Qbecq/7Ef/WG++ewzKOVSVDUIl7g34mS1xPNc8u/C5/iOEArWtFhT48oI4TqgG772F18hK0qiMKZYr3n88cd518P7PPvM1zh/6RGCwOWzT3yaH/zge/n/vrKiyjVFuSatcoZbE/KmYKvn4YkBwhNMZ3Ou/MDDGGmZTY+JhEfUD9F516GDIEAoiRP6OJ5HvqowumaxXHLhwgUC3aIRtMYgXIe9rW1q3bBcpVy+cpm2KnEch+lqQVbmtBK0aXF8ByEleV3h1B5pUeJj0KbFdSxG1EjHkJcrAPr9Psez253q7np4Yec8TPM1vu/Tti1CwHK1Zmt7Gykl+2fOIKWkaTrTx3EclrM5k8kEay1hlJxeZ4Hrh9y6fYQKBNPplF4cM5vNTk2JAqSkFpq2aWjbhqIoCCOfsixpms4RJlDESUJZ1NSVJs9L2tYSRRG9pM/L168RxzGr1QqlXPr9Pkq5VFVJrzfAassH3v8BmqZiuVxS5SU3rl6nH3f+nizLOq0EGAwGHB8fIxTYusYBsnWK6/q4qvMFRKHPep3RNA1JFKKNJo5j8jyl1+thjCHNc3zfRwgQSqCrmslkgud59JNOLV+tVpyd7NELerjSxRiN0ZbVKuVDH/wI3/zmN9F5zbVvXWdnss14uM2k9xCzRcbLBwuuv3iEMB6f/OQ/4ORohmkFSX9EkS0Aia5bbGsx+DRaEidD8jwnSzWD/hZ1nuF7krKqcZTLZGdCvsoJ4xBHuhyfHLB/9gLXbt2ibQ21bvGlQ15UHB4eEEUBIMmzktV6huuN6fUj1uvlqSZ1f7wjhIIQAkcIjK2RVoIjSLM1jz36IZTroBzLxz/+s9TFgs898Xl2zxhuHVzjyrsu8L/99v9IPGmQUrJat50H2jT4nsPh0Q1ct3OQhYHPiy8+TxhG7Oxtka6XtLIFfRq3VpK0ypCeYpWviYYJRVERDgbMVmsaa3EwoATWWA5nJ50Q8R1u3L6BqxwwlrIuWOYprTW4rkLXDb6uCaOQLM/JqpJWgOu6FHWB6yqUpzBl55QTjiHsu0gkwoB0oG0No9GIvChAKDzfv+OIyvP8jqNRCIHjODRNQxT3ODw87vwVro899fA3uqQ/GIFb4YhOZXeVTxzHLJYrjIasKQlDH+fUcVrWmjBOSNOcIOicn4t52mkcZU0c99BNy3KxJIkHBEHEcNipspPxNnmeU1UlUjgo6dBLEgSC9TLHtjAcTDpnZGNwlUfga2QQslwsu4FkLUoqpCMpyowgCHCczuwzxiClZDDourJSr/hJHNrWp6g63wgtFGlBpSt29naZr+f0kx5lXtBUGt9x6QUJy+kCKQ2NI5DS4vsRjiN54YUX6AU9qkWGp31CMeTdlx7ljz/zeYpckxcNbSUZJEMkil4Uo6saIwxGSLCKKIyYLZZIKen1elggCHvY1lAXFWEYk5cFjuOirUFrQ1k3JMkQYQVhNMD1Ys6dvYjWDcvFgq3dbXKxJk8zHM/F81yMbtmajCiKgvUyRSqYjO9/eoJ3RO2DNZbVbIq0GtqSF77yZYb9HnVTds4roynLkiuX38XO9hl+8P0fwPMVx9OXiWKNtDWBo5j0x+yO97iwfxFfOfQjn3EvwTY1gRDoIsfBsJye4CpBXeY0TYO2BiugtZasyKmNZr5cUOqGSrdMVyvWZc66zNFYmtMIw82bN1llS6y0zBZTqrbCjQKU65D0+9StJuwn1K2mqCuE4+A4LlVVUxQldWOoGzBWoa0krzQ3bh1RV4blKuXo5JA0TZnPZ7TGsFqtWCwWFEVFWWvWeUFe1QRxQl1roijB87qnhbWC/mBEU7cURYVB0ksGCKEIw5imqQDDfDpjOp2idYsSDr4fIoVD21qMsTR1y3qdkaYlSrmURU1TtwRBxGqZdeFC6VEUFTs7eywWCxzlcXD7CEd5pGmOlA6BH91pV7bMmB3NaKsW0xhW8xWr+Yo46FGWnZd/OZ8zHAxwPUUUByini+C4ngfWdkK90aSrNRKBqxyKLGe5XIIwnX/GcwmCgDTNieMeZ8+eZ2eyQ11WXDx/AWklkR8hLWAs1miK9QpTV5i2pDUVW1sjwsCjWGe0pcGmDg+ffx86l3zm05/j+ss3+dIXvsSLL7xEXVb83b/7G4wnfaaz21R1Sl6sT8PigizLGA36JElEowuybI1AUxVrjG5ZrVZg7B1Bf3Qyw/NDlqs1WVHhhzFad8JCCEnS61M3Gtf38fwEKXxuH0wROOjGcvXqdYbDLfq9MXGc3Pd4fEdoCkAXX9UVdZ6hTMV8dkh/PCQaxERezXve8250WbCzs4vjSg6ODzm8dh0hNUkQUeQN4/4WZVmRzjMUirooSbyIJquIfJ/ewOfk5ARfClwc0tUaKxyoS+q6xgpBWVdESUylG5q6ZWtnl7wo6Pf7NFrTpCuUUpRFgW01dWnIpCBMQg6PD7ly5RH0cQPGEvkBrlQ4YdQ9kZEIbQic7gmXJIPuCVnXiNbBGEHsD1GEeFIS9L6tCSwXC4QQuK6LUqozF4wl9HyODm4jhKAqSlzXxeqWsqhxXZ+qqgkCiUJQFBV7e3udU8+usFYQxz1G/SFV2ZAkfXRr8b2QvEgp8ozhsE+WpwRegBQKP/YJgoDlYoFEUeYVrvKQCMq8QJ3G+R3HYzZbEEURSZLQlE0XymxbxsNR5wcZd9pE3OvRaotuurDh7LhzsB4fH+I4Hkop/DigaWuqqqIqO1Pt2rVrdyJFVdWZTsr1kEpQVRVpnhEEEUpI2kbTVJ02FbgB2SqjqWrcKEIisMYQ+R6yaajqCiFddG24+sJVbOsgtWJ6a8alySNYFEpYDg9f4Cd+/GN83v8Czz//PCsjGY56WNlw/ca3EKomdLsQ6Hg4IRcpqBatG/zAoVyk6KomXc1Ilyl+GBL3I5TjUBeSusk5PFoz6A05OT7C9T16SZ+maZDSoW1bSirqssLiUJY1UnrkWU2RN+zunOHocIo1Aj/4lywk2RpD0B9wcvNlPv8nf4JsNePxmJPDA7ZuDmiaOY4rCNyQv/E3fplnX3wOay1Hh8ecu7TNwa1rJPEQ0wp6yQhjDMvlnKY2rJYZSnoIK1FCITR4gcdivqJtLNEg7mL8tiGOYqpGo4RDW5X04pimqnGUYLWedfa1HzDqD3BoeeShi6xWKUopXNfDDIYU6xX721voxmCFQQhBkiRdXoMfEahuUHW5DT3C099t21IXNVJKfD9gtVoSJxIpcpRSJEnCcr3CdXzSbEUS93Fll9q6rhscpcjSlMlwhBSKaDhECEHpSKwRBL7P0eEBe7tnmM1mKM+SrlfEUQ/PC06fPgLfUyxXKYEX4rsBvTg8TYgBzw2oqoq6bHEdHyXdbsA3nfk2GnXXPi0rYtclP00Aq6qKpqrwPI80TZnNT1hmS4SjcF2X+WqJ5/nUbUsS98mKBUZLrLWnoUPLarXC9R2Op0eMhxN2d/c5ODhAa02aZwihcKVHnpX4gUvbWlzXJ12tiU+jCK7rUlVVF9evKqwxlEWBUoqmqmnKAk9KWg1lLugP99BFy/HNI3TR8ugPPIZOFWGvTxJ77J9pOHf+Ar//qT9gd7dTzwejCZXOCeKQQLu0SEK/T7nOOLu3R16uKeoMKxomg5gsTbm0v0cxrGhMS9PWCGWAmjj0iMcJJydTlGNxFayWJwwGnVBttUEIxXK5JPAHDAYDTk6OOU5XXL5yCSklR7MjkriP+C6yG98R5oOUijJPWa0WfPpTv8+7Ll9kcXKIRPO//M//mCeffIIsn/P//N4/Zzo7ZGd3cppA4lDkGuUPyWrDPCu4PZtx62RKWrc4wYh5WpFrQ9kY5usMzw8xKIaDSWfPSYVwXOK4hzEw6A3xHJ/t8TbL2RLRakLPxbQNg37C+bP7SGs4v79H4AqGScz2ZAtXKSajMUpIjG6J/YB+nHT2s7E4wqHVmr2tXQZhj53hVmf2uBZpWhwEvnTwpUvsRVw+fwldGSI3JPRCZscn2FqDbfEchyJfU5cVZVEw7g/Y39nl/N4ZHARn9vbwlURYMLqlFwYsZ1PGgyFNVRA4itUqxfdimrLh4NYhq2XKtZdeZrVaEQYeaBjEA/J1Di3URY2rFNJKqry4ow7XdY1U0B8k6LamKLukn7btEsasbUnTFVEUUdclYJCOQDkOVhiSfszlh6+wSlfcuHWTvCzo93qdX8QP6PViwqjzeWjTMhwOAViv17RtS5IkXTKY7wNgpaJpBboxhEGMUoqi6HwMgk5bWC3WZOuUdJ0TuB7Swmq1YDwagXTZ27+E52xRFwkvPbPguacP+dB7f5ybLx8yny/pDybsnbnAat2we+YK2gT4wZit3XP837/zOJ/78y8ihCRNc9CCKq24cvFdVGlBkeW4ysERktGwT+L7tHXDpfPn2N8dce7sLlvjPkoaPFdQlSmT8YCL588w6HuEgUTYhv3dCb044uHLl3j44YfZ3t7C9z22tydceugcs9kRWpcMhwm6LSnz+89TeFOhIIT4J0KIIyHE1161bCyE+JQQ4vnTz9HpciGE+EdCiBeEEE8LIT54X41QXcqypxx+5qd+gueee5ZHHnmE4XiL/+Q/+3t8/K/8HA8/+kH+6I//AM9rKbMZP/1TH+PXfuXf5dKFd9MaQd10CT51o+n1h4zGW8yXK4TrYpCMtrcpqwarXJQXUjSG/nhCqy1KusRBzHgwxnd8Rv0BkR9w8dx5Hrl0mVF/QOwFJGFE2zQgLLPZlCLLydMMXZfouqTIUkTbsjg5oSlybKupsozbN24g2oYyXbOez1jMTjg5uk2ZLlkvZ8yntynzFbcPrjNfnGCt5vLlh8iyDD8M0E3FcDDAcRxMowldn9gPGfdHSCtxHA+JIltlKBxefP4lWt3FsJPAx3c9xoMhvuugxGkSTjJia7TFcDgmiXpMRltcunSpy37MS/pJn7Io8ByfKq8RRpIuM7J1jq4bFrMZSRThOQ6+42Maw/TomPnJlCovOD48oC5zsvWa+XTKwe2bpynQirIsGY0HWDon4tWrL9HvJwwGfYzRLJdL4rjT4LTWfPmLX+JPP/MZbGtIoi5fwvM8hJLUumG+XNDoLjLiui6u57Gzv8fR0RFFUdC2lqZpKMpXMhg9kmRIHMSEoU8U+5w7ewZrBIPBPjevL7j+8pyvf/klvvn1a5Qp7A7PIGvFdDrl+PiYre093vPeH+KPP/MEv/4b/zlXrryPsjD84R/9KU989s+5fXDC4iSjLCx7uxd54YVrLJYZdW1YLQuUcDm4dUJTw8OPvJvHHvsQWVFx/cYtbh8csZivyNYp8/mcyA+YTqedqRVGDPsDBr0hcRhzdHjCyy9fw3EkbdvguF269PbOFrbV6LoiiXz6/fvPUxCvpLq+gVD4SSAF/ldr7ftPl/19YGat/aQQ4jeAkbX214UQPw/8R8DPAx8F/gdr7UffrBEf/vAH7R996p/RjyWf/8yn2B5PEF4MXp9Llx+hqGY8/s9/i6vPPMnDF4bsn9kCLyLo7/C1b73AXzz3FKPhBCE6lTOKIqw11HVNVZaYxoBU9HtDpvMZSZIwX80JQo8kjLoUaCxFURBEPkIpvMDFWkGT1sS9mNlyQWs12mratsELfMAidZeFKC14XoAj1Wm8vk+tC9I0JY5DsJZWd7n5vh9ijQRdcjJfkCQJjushHYWV4tScabGy7ZKCHJfQj3CEwnE88nXBzs4O89kR2rRIz78zIPJ1TuD5FEVF01QMkx51XdK2LXF/gFQuRVnjex69Xo/FYtH5S5qG4+PjLjejrjttJ47RuiaKIlbpsjuG1yXa1GUDVuI4Dkopev1uXWM0CJc0TYniAEN3DnFvQFU1SOUSeYqizBBC0FT1nTqCttHEvQQtNK7rUZYldVETBjFlWeO7HmVd4ScBTduyzlKCIOgEwWl4UgSK6XyGtIrxsMvKtHrnAAAgAElEQVR3aFrN5YffxY1bN5GmRVqP1kh2dges14dsDQe0teLgZsrVaxnnd6/wza88z9WrV9nfm3BmPOBv/8rf5FO/9zjX52s+8MM/Qn9nl+sHtwlcj689/WVoa1ZZSWsMceJS6YyLV/ZIhh5x4nH2wj5Pff5JjDEEXsD+zg4nx4cEvgLRkqYpjegckr0oZrFYEYcRruty7eoNRsM+Vx46x8HBAb4b4LgBQvkUZUNVG+pyjRAWz3c4f+Ys0+mUtm1I05T9vT1uHx7yX/43X/ziq17a9Lq8qaZgrf1TYPaaxa/3wpdfoBMe1lr7OWD4yszOb3IM4jjmqc/9ORcuPsR8uWaVFl2GmecRBBF/7Zf/Jo998EfpDXaQjt+ZEJHlRz76g7zrXe86VVUtnufRNN3FyLIMaR3OnnmIn/rYx/nRj36MUX+bWzcO+YWf/6v4IsK2Bl03tHVLVZTYFk4OT1jOV9RlRdKLqcoS33FRQoJuEUYgjWV6eAwtWG2pywajLW1rUcrl6OCIdF2CdciyiuWie8pKFLoyyFbgOD77O3t4bojWXcquKxWm0fiuj2lAGQlGkq8z1suUw4PbWGM4vH0Lx1VYDGm2JM1WlFWOpUE5gv6w1+XGl13evuN4hEGMMdBUDXVdcvXqSyglSNMVdV2idY3WNUoJPF92IWIFyhGk2Qrd1vT7fay1XL5yBT8M2NrZxvU9nn/hBZbrFa01ZEWOUJKiqQmTmJ39HYoqZb48AaHxQo+6rdFWo02DdASt1Uy2x9R1SZpmzGYzyrJkOBwShiGuq2haDcaihMRViiTqMijXyxXz+Zw8TVmfLNGZZhglzI+nYCz9pMd0eozRDWm6wos9gkSxyhdkeUVZKY6PK15+aY5rBhzfnDEeThBYgtAhjBQHR1cZ7/QwRjMc9uklMRfO7eO4gsce+wDnz5/HdQWe73D27EV+8P0f5htPfwtdSsqs5ukv/wXbe7uEccJ73vdeFus1jYXFOkVbQZj0Ea1LWwkWsxIlQppaIGzAmf2LPPzI+ziezVHK5fDwiOVyycsvv9zledQFBtuFJP2Qk/mMoq5YrFOqqkFIiWPu3334vfoUXu+FL2eB669a78bpsu9ACPEJIcRTQoinjk9OUK7LDz32QZQTEPWGXL78MNq0oDU3D465cfU2j37wY/zu43/CYq1ZrXOENDz3/Ne5devWHYfWdDqlqiratqXf71NVDTdv3uTJJ5/ks5/9M+qq5MpDl3jys0/gOl2FZBxGDIdDhqeJNdtbW0gr0ZWmLiswFs916ScJSZiwPRrTi/vsjnfw3QCJYntrj17Sp64aTCtwPJ+2BWMEnhvS740YDiZIozCNIQ77lIVmtcy75J9GU2QlZV50OQ9tS+JHuNLBE4o4TMBYfNfDGM16vcRxJGWZo3WN7zssFnOGwwHrdHGaG1ChXEkrwQs9ZvOTzuQpunoHKeVpinJ1x1n4SlEVp0VFZZmzWi0wp1WQ8/mcuq6ZpyvcyCOtCtZlzoUrD2GVZJmn9EdDVODxsZ/8CY6OjzmeHtPrJ8RJQKNzbh8doBynSw32XMqmy4RcpWtcv0tBDsOQyXBCnucsFt3x4zhksr3FYrHgtO8x7A+YTCaEvs9wOERayc5gi7bSiFrjKkWerbFtg5Ate2fP0OiCSqdM5yc4XkJROFg74Oh2SuxFNEVOlS155PJFDm7cpD8cEcYRX3r6K/z0x38GgLouefbZb/Lnn3uCL33pKZ559hv0+iGOFPSSAf14zC/+W7/KwfUZrgjoJyNm0y5r9KWrV8FRuL6HG0b0hlvUGpR0cVQXbSnLisVy1dWPlDXf/MYzeG5IlpZceugKH/nIR3jo4kW2JmOMbtjd2yPudVmdrYGy6jS5pD/keLqk0X95My+92fwv315o7W8Cvwnw4Q89aleLBY6wnCwWvOexDzE9mrG9vQ3S4dy5R6jzE5Re8St/62+zWN5gXTX4KLQ+dTaFCdPpjDAMSZKE4+OjLkatugrGKApYLGYgQDluVwprLU3bEAUhWZ6SJDHTxRxl1emAgarqMsHqIj+tCjSkVU1d1yAFwtUM+kOKoiCKuli8ch0CJZmMt5nNZghpkQiKvEBrw6Xzl1gtU/wwJu45lFVOXhSnVXtdxWZVlIyGW7iqZbFY4LtdeXhZluzt7RGELk1TYYxGKMFs1p37we2b+K6H5ztdglPgEsYBtjUYWlzlcunCeY5nt4lij3U6p6oqBoMBYeQSRRFN09BLhsxmXa2EtRZtuirH2WzG1s42abo61W58dna2unwSqwnDAG0ajo8Pefzxx9nf38XzXWazGcNhH627sNlysSLw/S4qE4ZdDsJpeDHyuxDudDqlrmuGwyGO8liv1/T7gocfuszR9ISdrS2Oj49RQjAedsk6496I/b09er2Y5557hsVqSRD7NHVJmeX4TkhepuRFxvlzl1jONdN5yRN/8lWEluT5FCkrzp0b89wLL6Mb+PwXvs75/fN84MM/xjPPvYAXRqgoYDGfsrU1xnMVyYUzWCloastitqAqOyEaeBGzkyVbOzHD3pA0S9na2mI5n92p1hWiK7Db251Q1zV1rRkMe8znc6QjidyAdt0ghcfOzh5ZVvD5zz+FtZb+cMyFi+cxtMzma5qqRkqHXm/QOVPTnPPnzzNr7/n6lXvyvWoKr/fClxvA+Vetdw649aZ7E12dfBT3eM+jH6SpW3TbPcGQkjzPKcqarz73DI99/OMsq5zZOuP3/+hP+IuvfhNrLdPp9E4pb9u2+L7Per3GCtPZ9sUKL3RwXEtrSpRjQDSEoU9ZF1jbgoLBoNdpD3HM1taEIAoZjIZEUcRgMEBKpwt/uT6OdAnCEIMBKaiamqQfU1QVYRxzcnLS2c1NQ9PWlLpk/+wOTqjAtbiRQoua3qjHYNxnOB4gHUXcS7B0sfauNFoy3hrRmAY/8inqjPny253K8zziuPO0v5Ie3DQVe+d2mOxMMMJS6xrP60rBm6pgPB6jtabX650WB0nKsmQ+n3dOuaJgb2/vTkXoZLyNFA67O/vUlaZt21NtpPObCNHNpeB5HkWRcfHieXzfZ7VKOTmc4bs+y/kKXbf4rkeR592ARiBM99xYzhecHB3fybeoqqrztzgOy3TJYDzg8OSQ9XKFpxyqomR7e5um6hyInnJodMWNW9d5/vnnAfB9H98NKPMK3w1wlcMg6THuj8hXNZEace3523zk0R/mQ48+hqTB9zSOU7NezxlOtrh9vOLxP/gzktEuQdjjK1/5KtdfvorveiznC44ObuM4Hq7rc/369S4a4kkObx/w8OVH+NIXnibyhyjh0E9iqnyNkhBHAQLDwc1bFHnF9RsvsVovWK1n5NmS7e0JSS+gNRVB6FFWmjSvMQaqomS5XLJer5lPT8jWKXXZ4Pshy/mCdLUmCEK2x1ucHB4TRNF9D+7vVSi83gtffhf4ldMoxI8Ay1fMjDcjSZIukUj5SLer2LNIqvUSRxlOFrd49Ic/wO/93v/OZ7/0BF/8xlc4WS2pTyfekFKe5icsybLszhwAjucilKRpa2aLKY2psdLcUZnTfInjCfzQw/Ud+sMeURLihR7CEVggy3PiJKEoS6I4xvN94iQhCMOu5t73cAOPqBd3dnQckJcZjitp6pI8T2lbTW/Y53B2zLMvPsvR8oi8ynB8RaUrrLQIR1E2NUfTE/r9/ulA7ZKXsjzFdRVh7JEVK3q9+I6DLon7XYq0EJw9c57BYISUgjRdY9Cs0jmtaLrEGjRFvrrjRyiKjDxPmc+nnDmzx8MPX76Tgdd576tOADrenUlMdN2FRV9J5ZUWqqKgF8XQGhxXsZjP2J5sIU6zBsu0xncCqrTi5rUbjPojFIpe3MeRLo50icOErfF25/toLA9dutKVO58mcHVFa2PSNGU6ndI0DQc3byGE4Nb1GxRFgRu4ZGXGOltRVOVpSrTDpfOXSPweLg7r6ZJhMmYUbXHw0gmJ3+fi2XMkYUCWVazXa+I44PyFM0RJzHt/8P0sipTZaonWhssPP8zu7j63bt0iSRIunL+ENYIXnn+RCxcu8cef+TQ3b13jiT/7DD/54z/Gx370Y/gqIZ2tSGczlDEkkcd40KcuSoa9PrEfEIcJSrpMxtvsbHcaQdta6tZghaKqWppG43vhnXkg2qbC9RT9pMdkNMbolovnzqOrhnS5Isu6CFKa5vc9uN/UfBBC/B/ATwNbQogbwN8DPsm9X/jyOF3k4QUgB/6d+2qF7WrAq6oicPqs0iWD0YTj24f4gQuuJYoV/+0//E+ZLl+idUuOVyviaMig30efZh8aYxmPx6eTpnQ1761VlHmN48J4vEWep2AlVkjKusKLHYQj0XXNal3h+SFWCqRSVGVnIkjpsM4zXN+jKivquiaKYoQQSMdlsZjRHw5YrlccHB0yHA4JgoCyyFFC4nkuVlrqJqdpGyZ7u1y/cQunsCi3m2CjNbabFlAIhoMxcRSxXi5wXZcgCmh0hTISISzbO1tUZY3WXSSji3DEFEXFyckJo+GQssqRHjz11NcZT4YoCfP5lLauCcKEXNeMJyOyLGM46jIrr157GaUUYRBhtMDaU2vQdlqE1obRqI/r+kxnB8RxTOD5WNsiANN2GkRW5ThOp+67UiGsJA4THEeCa/DciLZucaVHXWlcx6EuGxynm6REyM7Xc/3qNVAW5bpdOC6OOVwuUUYS9xKyLEMpRRB0OSEnR8eMdsbgWoSGKq+6MKgRZKsSR7rUWcXuZIvIS0jnsF4UvPvy+/GEwJEgiXGdznTpD3u4cUjcnxD24Q//7FPs9S8SJhFHJ8foSjM9mmKaLklrb+8cSil+7ud+li9/8Qv827/013jxpW9x/vxFrl+/iet2kZGtYQ9XKVbzGWd2d8izkmF/gJRQFMVpIlmXZ3HzxgF5VdLrDYkcB4E4LTyLsNayWC2pqooXnnmRra0tJpMJ8/mC7ckWIKmqrpJUVPc/mdubCgVr7S+/zl/f8cIX28U3/4P7Pvor2yERTgQ6Z3Z8hCssvispViegdviH/91/zEsvP8vu/hApDHEUkUQ9HMfvkpFESNOuCFzJ/OQIuT2mqotusOcF/bgrbjLaBSNw3JAsX7G1fYbj+Y3OGeh5lE3N7ekBrqsYbY26PH6nq5U3wlAW3ZRWWgqOVwt6vR66aShqjVtpat2SZSWjoUe6rnCNxI8Ciqom8lwW6yXjrQm3rt8iiWP6cUKedrMv1abuBBZQ6ZT+0Kc/SjpPfdOwzjVSuuRlQYshW6+Jw4CmMejTQqwsK9ja2sG6Cun56Fawu7uP4zik6QrrK6TvcZguuzBfYziezwmCgNH2Nuv1GgSUdYkvHDw/ROuG2WLKaDImjANOllOkhKzOSEY9HARl3rCcLwjcrkjpzGjntAaim07s6PCA0XjMalVjre3saKVI4qSrTlzM78w4JREI2zlAJ9tj5ospO1tjDtuaqkjZ393CNoaqqYnCLhvyxq0FnucRhjFHhwek6ZrhcNhFOOoKx/Xw/ZAkjEnTChyX4+OUdO5zbv8H6PUGRIlh0EjWqyOE1EjXoTcIKfMpjmjp+QFn3vNetgdd/chs7lCWIXlZMugHTOczRlHE/s6Eb73wNfqB5cUXv8HuuZ9BI9g/t8+LL73M/v4+Wb6mLwdsD/co0pxJ0qdsSgwCaSVl3WDaLpqmlMNkOGJvb5+jwwV5sUbMGlxPEQwi9oY9RqMJ8+kMieDw8JidnV2KsuxmaHIgGSQI720UCt8PhBAgFUEY4rkCXZY0TcFka8RXv/g5jo5eJAwFra5YL+fs7+9jTGdyRHHC7eMjHKWQFibDESdHx7ihSxL18X19x8cgpEMYJaRpRttalus1rZFky4wohOl0jnQdrBDcunnCxUvnGSQ9nn76aQajCf8/dW8ec9t61/d9njXPe977Hc883GP7TraxCwGUhBpShQqoWqlKSFsFtVVo01ZR+0dbVaqUvyo1REqTJlKUlEaFUlopiGKIBYSAbcAX7Gtzfe8998zDO+95rbXXPPSPZ98XCyXhyk2Ru6QjnfPO593redbv+f2+3893vZYON1XXpSYgSwEo64qqqZnNl7z2+uskSYItHD775nfx21/8Eq1Qt18XVqsVRVWh5DmFYdHQcnJ2Csju+unZ8aUugEaQzFMq0dI0FWVZ0u/2qIqcVgjKuqKoGoqixDBtXNdHN03yskIRKlEYo+nqFoFm0QpI8wzTNlEUWK1lc1JVVcIwvHRbWrpBUVRs0gW+38G0dDZRTBiGmLZ1OfqdX1xgGRaWYVOWNaamUhQNi8WSoshRipKg2+fg4IA0TfF9H9u2ieNECpA0nbqs6PhdNE3B1GXnXWmEnLFHEaKFMi1pqgbXdlFQSPIUx3PJsowsy+j3+6zWa1k1GDaWbqK0UNfS/p3nOWWRUxQZm2SFqQtWM0E/2KHOFYSo0VSFru/x2ifusVgv2CQRqlA42BkTRynjwYggCKDOcB2bbq9HlhX43Q62bfILv/ALPHj4DknYx9AVmqrg87/4ef6Dn/hJfuv0Syhti2gFTVXTtg3xJuXifIXn+hiGiu+6TJfSK2LWDVUjUZyWYWI5NnleEq039Ad9siLG9QOmiyk7kwNmizWbMCSJUwzDpG0EAvm6r1ZLlssFh4eH//JF+C3Xd8Sm0DTN1gKr0baChpYkk05AwzDwfIfJZMR8ccGwP6Cua9KkJM/mPImecf3mNTZxRBQnKAqYtiNv3lqQJjW+72x5AxVZWdDv95kfHeEId+soy2kdHaGaVGXNJsno9XrMpmvaSlKFsiRhd7xDWuS0Wy2+6/qoqkC0EMcxXuBSVDlxElGWJb/x5d+kLCsc16RsG8I4pqXGdWRn2fMdsjIjyWKqqqJscnb29kizhOV6TdMoVFWB7TogVCxHYzqf4doOmmGwSdLt00RnOp3TCfpoQiWMYmzb3hqF8stFLIQgyyQ/oqpyNE0qDOWkpZEThBos3yGttxJgRSGKIny/Q6/b3XISVii6wiZKyNOMPC24dfMOVSU77nm6xvM8FKHRCPn6ZlmGpkp/RVs3JPEGXZUNzqatCePN5Tk538RcuXaV6XTK+fk5aZpzsHd1yyqsiZqU5SKiN+jje5BsMjqd3qV/pN8b07QFnU6Hqi4oshxF0TAti8HAJY18vvnVD2gnAYIKXXEoNiq+63NwuIdlazx6tOb6lassl0t2bkwARUrx1wuSzXOuX7+J6wX84//r/+TrX3+fP//Df5Yf/bF/A9fS+fI/+20c22dnfJV3v/GQP/N9n2M9O8XUV9RiRZisyPKSO3fvcnZ2zny1pF3WGJaJUFqyTcY62jAcT9B1G8OwUFqd/fEe57NTkjxks0lA1fj62++ys7ePWkkaVpYVPH7wWOICHBPXkhLwD6vcj3J9h2wKLXW7hXarOoZlQxzjeD6aUQINT589wXVNFE1sdQgtlmPiNvDs6SPGwyHD8ehyNHgxnSIMDbfTI8tKmiYnzTN0XaVpW2rRcnpxxsHBIflyQblaoukGqq5RNi2GaZOlG05PT9nf3yfPJIRDNfRLTp6qCoQQVFVJK+T57nx+hm3b+B2P09kpN6/fYrmckyUbVFPF0CzyLQnpwwZjXueMxpL1t96EJElCx++QbwpUVUfVDPIkxvf7rFcRQtXQNI222kJI0djdOaCuW87OLuj3h4DshfR7PnmREEURWZYxGk0kkHWzJAi66LrOYr7Cth0Cv4eiaMzncwaDAaqqslgsaJoG6oq7d+9x/PII17Qoyg1dP8C2HdJc3tBVkmHqFp5jECXRtrKS3MjhcEgUbtAUFdu1yDYJXT+grmvyIgXDwLUliLYpU5bzBaZucLB3SF5UhAvZP1iGazbphm6/h+v6FHWDrkuq8qAXUGYljuNQ1RnF1kfRmFIyrbYSrpKGNXdvvgaNYDDQaasNruHw8sUpcbxCKLC3u8vjRw8wDIO6KuTvShHkaULbwu///u/zhS+8TbcLP/ajP4Tvu3zxi79Jt+Mzmuzwcz//K3zuh36En/4H/4i///f+J86jJZ/6xCf5zbd+hbYVKLrCs+Pn6KpBmGwosoThsE9Z1tiWy53dfVZhxGS8i1AVzk5OsVWDnfEI2zvg+PQERdV58METmlZBqyssTcc0TTzHp9vtUlY5iqbT7QQI5Z9H+v7nX98Rm4KqqvLGUxWaBoq8JNokXL91m3gtmC3m+IFDVuT4XZ+qlYo5vxPQsMYNxmRpxisfu8L9d99jvdkQbKEkZd1i+94lx9D2bKarOQdXDrl//z4oDaZtbpV4S3wvoDv0KJscRWspk1I2tHQdd+sIFKpgvVrj+i6qUNAMlfl8BkqL3+2wWM1xuza3X7nD2dk5bVWhOwaWMBCNoGpaaFrW4RJVVZlMJpRliaqqqKomm4Z5hqKZqJqGZZislyuSOMX3PGkmahocz0fd6vmrQoqO6loKnIpCsv0MXQqfTN1gOp1SlwU0OooiKArZnfd9nyhKMPRsawxrUFSdpm0p8oo7d+4Qx9KwZlo6VyZ7rFZLLmYzwjih2+0ThiGL5RrLsukFHmVZc/36TcIwvBQ+AWiKQlWW2Jb0dDRNwyaK2dkZXwJku90uiqLguQGgMF+ssSxJ1B5Ndjmfn23x6ga+I7UlbSuYzWbkmxLHtcjTBFWT+pA8TSV8Ji+wfY8P7j+nF9zg5vXrLNdPUMlYnC8ZDfbRDS4t3qDQ70rn5+nLZ/T7fa5du8ajR0/4xtff5nu/5zZvfvJ1Dg4O2Gxinh8/5/jlBdf2a37qp/4W+4c3eOutr/BX/sq/z1/4t3+I9crn6sEt/uDR71OJEtPyqJua3qDPfCZhs00NWZaxWq3QTYv377/LaDzGsg3KJGYTJYSJjuNYdDo9/r2/+Bd48OARWRjT9Xy6nR7Pnz+HuuXZ42e8+earPH7wmM5g+JHX43fEpiCEwNRtWmoUTUdrTA4OrgEKQtXZPbzCbH6O65rMlwssx0HRVFbRCqEKqanXdJbrFa2qkuQZeS0ttW2TUNYVvu9iGiar9ZpWhccvnnF44wpJFDMY9anaivPzHKE3lM22V1BWmKZBq4JmqDTUTJdTPM+h2/cRakNeZDieTVE7oCrohkZ30GM8HlPlBdFqhec71HWDUOTmpxqqrACQtKUiL2hb8L0O09k5RVGwt3vAbLbCc1yKrEQVGmVR4HoeTdPQCXoYwiAzJVloUyeX6G+JbBP0egN0XWDbBkkiHYYfvg9UFEVDERqaBgf7Q6JoI5FsKDx48IAbN27IBmBegiKYr5bUdc2jx48ZjQcYloOt6mySRHo0LJ2g18HQNaJ4fYmqn81mWLpFx/dlT0ZtaSjRDBVVNaianFW4vFShlmlDmhUIRWOxWNHUYDoO0WaDbdvAH6L627ZFEwpK2+A4LovzFwwHPcoiuRyjJplkSpzPlujrhsAfEIYhT58+RTcyHJPt2FVBUVVaBJZlAxDHCc+ePeHu7ZvEccjP/twv8oM/+Kf5iZ/4y9y8dp0kSYjjiMP9XZqm5ejpV1jZa9555xu8/+AD9vd3+f7v+y7+57/zd7h37w2+5wc/g227PDt9QtCF8WDM4mLBeDBktZ5hmQ5l2fLeBx9wcHhIUSQgqu1Ds8K0NNoGVEWhzAsW0xm+4zIOeqRxwtnZGb7vk2UZnucxn885ONwj6P7/bFOAPwzuyIuCsqrxXI+2LjFtm9PzKZtkg9f10agkD2Edo2kGolEoipJoE1NvcWS6bUgVoGmiaDpVXJJXOaqlEmUbTNPE9j3OZnNMRUerapqmvNQz2LbN8dk5nu3QIPA7HcIwpExralGiGPKsPl1P8RwXhYbx/g6LxYKizEk2G54/fUrH67EzGWHbJmfnJxi2TZyk9PuStxAtJcL7Q7RaXbf0ugMAsqxgb2dPqgnTnG4gtQhxkmBYkkvgOT5xHDOZTOj2ZCmutGBZHoomlYlFkVGWOXleomkalmVtBUYqRVGRJDlFXlEW4ZbaBL1eD60VEheva8wWc/IipdPpsAgXuP0Oim6jqDpFXdEKyIoUw7ZoKdlscoqyZjGXZq/A75LEMbPZBZ1OB13XMQwNTVMIoyVVLWlLSRoxX+RYpidl2Numb9WWlEmMrutk65SqlTCWdbjcZnTIsaRuqFy/cYiuqxwEBxwdHfFi/pKdyZ5UXk728ZxrvHix2prhPEy9w+nLp/iuQZyuaBWFNC9ZrELGwz6jyRhoePT0CTevXeWv/bWfxHV9Dnb3WK/XBL5HsglZzKYsLi74vu/5LJsw4v77b/MDf+7Pc3JxzO279/ixf+vH+F9/+h9jDHWu3dvFDXxW6wV1UdNxO2SJfBBFUUSn02Mw6OK4JoPhTTRDRxUQrRtaUWMbFmlS8ujpE3od2fBMU9mTAfA1lf5owCaPcQOfoio4Pn7+kdfid8ymIGfiyh9h72korUZWlDi+R1GV1G1DtIlp1YZWrSmzkqJs6HS71E0jEW5VRdDvXUpvG1GhmSZxGrPJNpiOlNVu0oQkN8izGs0UW9hngmqYVGVD0mYUSo4buMzXcxACVVMoa6ksLKKCkgLbtDk/P8U0bamY86U0eL2QoR9xkeM4Urrb6/WomgZF17hy5RqbjQSE5HlJVclgmrKsL/mLvU6XBoUyyxEttHVNVSg0NFxcXOA5DovlHNu00XWdqpKVwGwqDUWDYYez8ymWZUqQSVFsZ9c6umaxWobs7Oxt5+OV7FVsHZdZkhMEAYv1CsOyqAVYHR8aQVo25E2GbducnZ4wHPYlu3G1wLcC+XUEbDYbVosFQggGgx4vn7+gN+jid30Wa7mJyrwNB9uTsJeq3OpE8hzbtfBUl6KomM5n9LoD0qQAVcG2bXq9DicnJ1R1gZqJrVlKYbGYsXewz6Tao0ZQ5DWNAo8fXxDHKXfu3GF+vsYfTeh0JnQDwenZc1rVxnJsnjx5xmQ0om0g6HYQx4K0yPna177Geuxxd4gAACAASURBVCGt3fdeeYWTkyN+49f/Gb2ew+c+9zn+4O3fYTAa8PFP3OJXf+3zCNXkM2+8wSt33uQXf+k/4u/+zE8RxhHL5QKEwmI2p05L9nd36FkBaZLTtoL+oEuSxDRtQRHmgIKuOMynSwK3y7MnL7h+eHOLeBsShqutM1gSqJbLBaompzh1U1GUHx3c+sdap/8krk9/+pPtW299aRsFJ6ibEk2VAQMtEf/Ff/XvkJQrTKfFC2yyrKAsa9pacgnzSjav/MBlupgiVIGiKIxGA54/f05Z1lIEZNpURQ1otI1Eqc/Pz/A6Nt1Rl/V6SV0VKHVLU1aMBmMuVivZgY/X+L7L+fkpg2Gfui5xXRtFlwKc8XjCbDajyqutRLfE8xzZpd9s8Byb6XRKr9fDMiw01aAuM9IiJ81yPC8gTVM802U+nXF4eEiShpKVoCh0gh5FUbFYLPD9gNViQeDYKKpBnOWYptT360Ig2prOYMhyuaTb7W6ZAvVlIpMQgnAZb7kCAUHgUJRS7HV2Osf3ejiuQVVnlGWxHe3VmIZHkhRYtotpCdIkxlA11us1Ozs7W5GNj9boJJtIwlObiqoq8L0uQdBlPl9iajp5nqIbKqcXZyRJjKrKqVPTgG1JcMpoIL0NdVFjbY9G169f53x+wSaW3fSiTnEcizwvaRsVoZjUTYKmFTRVS1N3cO2r1LXDs6NTHEVBVzXKMmc06JCkG/m9qxLLsiiKiuVyyWIhSVtdP+DOnTsIIXh59ByKkL1xH2s7ualblf7kkP5kH9vpkCQJbVsxm57SCnD9Hqblc3j1NpqV8Pf+wf+AIKc/6NHULXXZbDH1BY6nEq0L2tIgCjMsU8cwa2y7xnVtHLNLi0YUxVRNQ6/fRdPg8ZMPUB2Dnck+nulSbErCVUxdVtvgWeh4On/1v/vVfzXW6T+pSwhxGZ9V1zVVKV/0thV4nS6240pQZVFRtaCpuhynaXLGXhUly+VSnjkbCRJZLFa4TkBZNNiWh2W4mKbNwcEBr9y+Q56kdHqB5PktVuRRBFmJrgos20CoYOgqq+UcXVUwNJ2D/X2qopR4q0alTCtUFBYXU/Qtdanr+hhCjipnp1PqvMBzXFzbwVR0VrMVbVVj6iZJtCHwfQLPp+/3qMuKvZ19wlWEqVsk8YYkTomjiPVyJcHTQoG6RVNt1vGG1SrEshw8LyBONjLidJtwVZblpatQNjLVbeNUQTcNyjJntV6wXk5xLI298QDPMVgu59I70kqVqK7rRPEaw9A4Ozvh7OyELJOVguM4LBYLqqoiiiI0TWOxXKPqBv3BEMeVP9fJ6TllVUmtRlGxWoZ0PKmQ3N8/RLQKo8GQbs9FKBWbJCRJN2ySkLzM6HR8jk9fkhYbGlGS5smWAJWSJjWq4pAmOYbuoqsBaWKgiT5ZIvi9t/6AKq/ZxKkUX202l3F99nbq8eEY17Iseawrq0uoSt2UvPHaqwghePDgEaBw7949bt+9e9mr+fJX3uIb37xPb7TL7/7eN5nOEuK4otsfs1wv+Nn//X9hPApQ9QpNr/A7BkHPwgoErZqj6zpXrx3SHXrs7g0xbZWyKmiFRlE1PH35gvlqSVFVXL16FU3VMU2bbrfPtcNrROsVSbxhsZixXM5wHIsoWbIMp8zDP0o/+Bdf31GbAqIBIdHoqqpC29I0DePRHgL59C2bFttyWMcb/KCDIlQGvY68GRWVMpMmoixJJdm30Tncu0FbaVLHr+jURSndhIYmkeGqiikEIi1Qq4oqK2iahiTP6LgO+5MxO8MBoq6Y9IdM+iNG3RGGMCg2JY5uMz+fE69iHGP7lNRViiRFNC0dt0Mep5iKNPF0PJ8kSmiqmts379Dzuii14OToGFO3MFQdWzexDRvXcnFMiycPnzA9u6BIM5Io4fXXP8Xrb3yGwB9u/QNyczQNC9/vEIUxipBhtIHfIU0ymrrF9wJGwzG6Ic/idZMj2oq93TF1kaFSspyd43jS42FYJqtwjWHZ9AcDWgG9fgff9wmCYAsNMWXehFCoqooXRy8JgoDHj57yy7/8T1gu14DCer3G8+TnRGtpjlIVnWFvQLiM5IixKMiLhLopmM5OZUCLrlG3LReLORfLObUiczNsVx7JAq/Dwd6+BMmmG8IwhsajSB3Wy5qzkzW+12N3Z5/9/X1M08RxrcsNrKoaXNeXR53ViqqqGA6HTHZGCKXl7PyIt7/6++RZymc//Sm+/3u/D103eeeddyVtO4qJ0oTeuM+nvuezHJ1N+cm/+l8y3r1Gqxq88/47xHlE0+ZsNkvGoy6GKcjKmKSKWUYXBF2bqqpQ1RbX0wgGOovVKTt7E4RikJYtk4M9sqrECTqUdYNuGlxM5/hBl7osydOUJI0ZT4Z8/BP3iJIlh9f26E0Ciqb4yGvxO2ZTaLaQTpA+eaGq0haMyt74EBo5d/8QYjoYDNBMiyAI0HUd29QleaeFKpfehMALGHQG1EWFazlUWUWZV7R1Q7haY1nSu3+wv4+jmFzfO0QXCuvlEs2QqHaaGts0aOuGbtAjDlOm5wuaUlDlLarQ0FWLP/Xd37sFsWjyhi8LmWFg2BiqfJtruzi6TVu1eLaDoRoUm5wyr8iSnDu37hIu17RNg67obCKZizAeTtid7PLpT34X/e4A23R4+MEjyqLBUHVu37jN0fMjHFOaf6az+SUrIYqiy+PDh2VxWZYswyXr9RJoqaqCZBMReA5tXWHZslQvy3LrhswuEWi9XodORy5eFcFiNpfKwkRKrBUh5cqtUBiMhrzx5qfQDYvlKkQ3pRy4bVviOCbPc05Pz3n/vYe8/94HTC9m0uRVtIhGxfW6NAhMy2UdJpxeLKlrlTxXaVrjUhlZVRlRPCcOp/QHkq/geUPeeus9Xr6cM10siTcronCBqkkyl+M4kjehyLbaer1GVXV2d/c5ODjYgl103njjVeqqRNXgD77+Nb7xjW/Q7/f57u/+blqhSnzaxSn3H76Paqk8ev6AVmv4vbffQjEEQc9kGZ3xzvu/i2EAtayUHjx4gO91ZBhNp8MylI7HKA5ZredskhV/9nPfT2/Yw3ZddMPC9lx2D/ZRdY0w2XD/0UOKuqJsahzPkyRvIE5jnj5/RHfUYZ0scbs2bj/4yGvxO2JTaEFWCQCI7cisvewv3Lv7MYa9AUUmA0zSTEa4WbpsxumqLNtVBJ4X0NYNjmlRZjltU2HqBrqmsjOZ4JgGoq3ZnYxoy4Ju0OH89IxXX32VT7z2Oq+/9ib7e1cxVIPlfEUYSnqN4wQowkCg8eon3uDw8BpCaPiuj6aozKZTekGPQbfHZz71GQxhsAk3mKqBikrgBli6hes42KaFY7lYho2iaKzmK3TdkEcJr0Nd1ITLCBUF27A4eXkMNVR5haVbUEuy8te//gfM53NevnyJaUkEWr8/xDRtqe7bxrj5vn/Zmf6QkLy3t4frOaiq3GhPTk44Pj4mz0vqqrlMbyqLCttyOD25QFV1mq1pq65KhJCTCt/3UVWd2WyGY1lbjDwIIWnTpmljmja2bSJES03JaDKk0+vS6Q3oD8dM9nbxAp80zYmjkqpUce0+uuoRxRmn0wWHV28w3DkgSVuWqw1e0MMLfExHp9N3Ge93CAKHxWzJ53/p16HVSfMcXRf4gYVhCjzPoaWm0+nQ60l/ixCC/f1D6rrlwYMHzOdLqqri5s3rFHnK0ycPmIyHhOECXVP54P13ee+997hx4waNkNF0N27f5P6Tb6LZNXE65WT6kLPFI56dfJNaWTAPn5PmCcv1hr39K7z5xmc4Pj6j2xmQpjmDwQjTNFmtFjTUhPGar779NRzPpjfo4wU+57NzVvEKdMH5YkZWl+xcOSBrKi4WMxTLoBI1L05eMl3NuFjOMD2LOImwPfsjr8fviOmDAEQLEiIiU5PaukUoCoZicHX/gNOXRyh2gWv3EKqy3XEjPN9hZ3eX4XBIVVXShTYcb8/DgjiUZhlVKGhKi98PyPLkskxsK4Vhv8s3339fplOXJQ0qaqOwN95ndn6Brsngk6aBfr+P63TY398niiKOj1+gKALHsojjmEePHvHGawadYEDbhqiaDEDJ85KmjrAtV+oqlJL5fE6cbOgEMmmpF3RI2hTXsmkbQdMUmKZN04Bp2NR1i+93mF7MWUUrNnlBN3BRFfBdj3fff49rN27hdxoeP/yA/f19bNvdVghLDg4OWCwWxHGC55uALPf9IKAuK+lGDEtUzcLUVfrdAU0lmE6nzOdzXFv2X65cOWBvb4/VfMFoMJKIOKFgahZV2aCIVkYB1i0tCtE6pCwyHFunyFNoSyxfbrJq1TAwZRKV45i0TUOyKpgtFtSNhqoZ6Ca89sbrpGlKFq8ZDibUfk1Z59DWTJch+7u7XLl+nSSq+cIv/x60XZpWMh+atmRk9/i9r/wO4lOfvqxIh70uk8mEvMiIQpmLoGoyafzq1X1evHjGtauH/KW/9Bd5+fwpr7/2cY6fPWZn2GO5nNMIuHLtCla3xz/90pe48+Y9dvb7xOEaMY3JqxLNEGhGwWTXI13mjMZ3OT+b0ul1uXb1Fi9evMB2ZLR9b9BnNptRFg1FXvOv/+AP8cUvfnG7qdv4gYNQTPIyp2pKnh8fcePeTc6Xc25cP0CrLfpBl7qVYjHfc1E1A8OBNP9XaJ3+k7pkdSDdikWRYerattlY8vC9+9y8eh1hbcjqmDhNqGqBrqlMzy/I0wxQaNoWwzKJ1yEogjiM8CcmVZmQbGSfQLRyYedpimUbVIVguVxj2AbZ1vnYtIJwEXHn1g6xmRBHmRwP9npkacGv//pv4DgON29eZzwZoqkGlmFIdaDXJd4kGLqObpmYmo6iynRmQ9NRVV2Gs6gqbQuj4ZjFOkTXa5T+iOEooMhzPE8hStaUdc1yHbGz41O1DQ/eu8/t27dB1xjbJpv1iqLIyPOUu7fvcH5yTtAfMByOt3ZnmaEhhGC9XjMYyIi2LNvQ741I6pSL+RzD0AmcDk1dY9sORbnB7/ms1xH3bn8c702Pd999l73xHkkUk9cxgRtg2zbj8Q7n0wsURcF1PRbzc9I0JQi61JVMPDIMg80mwrQMsqzmYn5GVQoCv0teldRNTrhZMugOqMqGvb09FqsljmfSqoKkCCmbkt29CdFqiUCG4jhuhzw3mC9zNCPli7/6u2iKT1Fa3Ll7g2+++3U6mFB3uHJ4gxfPj/B8Wc3keX5pyc61nBcv7uN6PsdHL5lOT/m+7/ksdZURrhaYus71G1e5fjAhXofouk532KPWddAVxjsjTk7OOD45ItksCHyDstgwCPqcnZ1juQ6m5bNcL0iLhPQsw3U3RKs1ve6EPNngdGzWq5BNnOMFHR49fEYrBHmVYbSCMIxkqlgFZQU7B7t87Q/eZh0uaYwS27So24aj6TlX9w9Iy5JFuGY0GpFuPnoYzHfE8eHDq66rS06gUCVOrK1avvrVr/PjP/7jWJbB2dkFTQNZuqFtm0tyT12XdLtdwtWaNE3JkxRDlT2Bxfycpi5RREtRZuiGeumzP9zbRYiWvCiwHYc0k76EyWhMmedUVUNRVDSNnISEYcitW7cIgoAwDCnSjPOLU8LtGbnb7VKWpaxOVEln/lDCHG1iptMpaZqSJjmKatK2KpqmEQQBabaRf9KUVpFpUGEYsru7KyckkYSNPH78hJOTY1zX3hqyavrdLqqqkhcpeZZwPjuXwqeqkqlKeY5lmORpIcEbQieOIpZb67SiqOimS9W2HB+f4jk+ZV7RVDVlUfC1r36V8WjEwwcPoGkRbUuyiTg7PZGGKdcjjmNOz44JV2vauoGmhbal2+ng+ZKaXRQFVVPjdzr4XZ/pYo7neRimiVAltyLoBai6QtD1qZuSqi5QlBYhGk5On2PbLZ6rMxqNEa3D9Dzjn/zyb/O3/uZPc//dY3Ym1xj0x+zt7HLv3j263T6WE9Dp9HH9gFu378osx7Yly2W/5cqVK7zx+pucn58zHA755Ouf5PzsQioJkY7ct99+G893adqaq9euYDsOo9GE47NTgl7ArVu36HR8bEcnSSK6PU+GGTsOpqZTtRl+18Xv+ti+ieMa7OwOKesa07FZLEPGO7uYtsVoNGI2u6CqC9ahtKtncYSqtOhqy3J5hqa2DPt9RsOJlEXrOnmZ0e12UDWNNE8BwZMnT1jGq4+8Dj8K4v0fAj8MXHwL4v2/B/5DYLr9sP+mbdtf3r7vvwZ+AqiB/6xt2y/8cT/Epz/9qfYrb31RjiWlQgeEoM5zRFsTrk55evZl/uHP/W0006FqIHClll3HpG4rbM8FpZV+h6LAd13qUuLWkiSTJqqquSTxyIqkwPdllFy305fe/njD/v4+y8VWEYk8bwsVWWpWJZtNSlW31FWBrQsczyVOE4l513Rc26apajTHQtEMmW6kqhiajqKoVLkMSzG1IetwTi0yev2A5XpBrzegarZNvjJDV02URqOuBIPBkCgKcTsuWZFy9OI5qqqyv78vsxR6PTRNY7VasSkS6aDcRqIprQKtQlMrOL5P11WxPRvDkPFrmqFLJ10rzVayK1+hazLNWhUKvu9iGQYvjo6k8CjbsDvexTQ8VN1G1RVsR6ctFE5PzqnaCr/jESUhdStNb1LKLAEhUigl2NnZ4fj4mNlsxiuvfIwirRFKi64LklRutpZlbRmNPig1vrvH8YuIr3z5mzx9csKbb3wXR0cn9AOfnfGI2WLKeGeCF3Q5u5hSVy07+/t84u6rOI4BbcqTxw/YxCGvfuxV6qKmaeALX/gVHj58yGuf+DijYZe6ynEsjSyPef21j2OImm7XQwgVxxvQaA4vLy6YhnOEUzOdHbFenTHs90jTnKDTYxnNcX2bOFpyZf8KZyfnKK2gNxzw4uVLOv0eUZzQ7Q7pBA6zi2Mmgy7r1RJFUamrlqKq8Wxp2EvTlHWYcOvmXY6PzmmEQpwuyCtpT/d9SbkeDEY09fb102r+2//8yx9Jp/BRjg8/Dfxt4B/9kbf/zbZt/8dvfYMQ4mPAvwt8HNgDfk0Icadt2/pf/i1aEA0CQds2IFoEgrIuKIuCbq/Hz/yNnwGVLYSj2gaq2qitTBHKSolb832f1rYllDXPaeuGwPNZFCWaIY1E3U5nKwLy2cQxtuXieZ5ssrWSflOWpeT72RY3b99iHa/RTIPpYk5Vt3/IQlQUWqFu8ekNtC1hnODZDnlaslzNsbcZgWmSYFkWVdvQ7ff4vj/1A/zmb/1TympDGIf0ej1QVIk2832idUmelQy6XbK0AFrSbENSxCTZhp3dMY7jsFqtcF2XKF5TlqWsEPKK5XKOY9vsTXbI04K8qEjLnMXRmnanwypaoeuqjHNLNoTrmOFwRJYliELIJ2na0u12t8AZhdVqRa83IM0zRCtHeZ1gSJIVLFZLorji/vuP+K5Pf3pLlWrRLYW0kPi7upKvged5l+To46MX7O7s0w06aIpgmUg9hOR0SnNS0+iMRiNevjjFdUc8vv+U0+OQ33/rGbs7A+Iop8hrHNu7DJRN05w4OaPb7RPFCVcPDrdTD4GqVFy/foPHjz7g4cOH3Lh6A1UV3Lx1A6FIxuXJ0TGjQZdlsqKpcuLlGl3NKfOIvd0rlGXNajv/r+sapayYzS7wPYOqLjBNHdsxmc4yEqWi0+ldViJpnHB8fLw1o0WcnU/RNZe7d25w/PIZZ9MZStvQthW+10M3Wlbhkv39fcoK7t495JvvvE+3M6StW3bGE8JY5nOenZ2ws7ODQBr1Ar9DnvwxS/Bbrm839+FfdP0I8HNt2+Zt2z5FYtk+81E+URXyBgIpPEo3IUdHR/jdHugGH3/tVWzTwDR1Oh2fuq4vKcDrLWBDVzWaqmYTxViGgakbtFVLXZRcPTik43mM+gPqoqTrB4TLFek2S3C9jrBtmyAILjvSmqYxXy05n02J44Qw2hDFCQcHB/R6PcaTIb3BkLaFsq5J04xNnOB5PrpuoLY6167cxHcDRKvRtJL5qOoqYRzyf/z8/8Z0fsbFNoSlbQXT6VymNp+cI5BjxYuLC6lCjFY4joVQavb2dqiqijAM2Ww2VJU0zXQ6HfI8J1quuLKzh6OblGmOYWjYjsnVq1dxPEcq7xqYTue8PD4iyxIUFVbREtT2ckqRFfklI/Ho5JRNmvH02QtM06bXG7BehyyXa168OCJJElw/4BOv3wOtkY1AtaFuCnodj7aq6PkevuNiGya+45LGGyzdoMxTaCqqIkM3FWpy6rZA0VuECqqusQ5j9vZucPqyoEgd6sLh8GCfV+6+RlPLkNl3330PVZPHzDAMieOYt956i7Ozc54/f06apvL3VTYsF2sG/dElxFZRFA4O9vjhH/5z/ODnfoDReMB8doGuqOyMJ3z1K79LtF7hWBJo47ou3W6f4WTM/Yf3OTl9iefY0NYoilRAvnj2FN/3EUKQJpIRMl8uMB0pkPpwCjIeTlisljx5/AzbcrZVncZouEuaV+Rlg2543Lz9Cn6nz8X5jFu3bmGYGoahsQljBkGfOqvouAFlWlBscnpeB89yaSv1Iy7h/3c9hf90Gw33Dz+MjePbzX2YzmhbGSHW0pAkCYquceP2LYos5+j5S+6//4GU6VYFCgLL1KnyAn0bfkrdoAkFU9Pp+sElwOPDXIP1eo1lWeR5RhiGZFlBt9tnNJqQZRLZPp/PZdfWl5tOTctoPEYoCv3BAMfx+MxnPiPTljwLIdgyBTUZtup36PQH1A3Ml2sUVBzDIVyG21QlebbPy5JWCDo9j36/y3A02EJJVK5fvy4NLrE0yPR6PRnqWmbUtfRyGIZOXiSYpoFlmWiaymq1ZDgcAC1FIaPW001Cxw+oqoosSanLisVixmQykhyDPGc4Gl2q+TRTo2krVK3FsgyCwMNxLDZpTEPLYDSkbiTExrEDXCcg6PZphcB1PQ4Orki+RFvj+C6z+YVMpyoLVos5Ki0X52cs5wuqoiSJN7iOTZFnzKYX2JaJqipUdY7jGmi6oNORPoqqbHGsAd94+xGes4toPVRFToWePHnClasHBIHHfLliPl+ws7uPbbmcnV2ws7NHmRdE65CXL19SFPK+mUwmZFlOWVQ8fvyYuqloKakKKe3+M9///Xz2s58l8HwmozF3794lT1J03cRzO9JP0YDjOKRpuh3Dtty9e4eqyLh35y43rl1jtVyiIlivQ4JAbtrT+YwsSwnXa7IoxXMcPnbvLtPpFMtymEz2sG2P8+mC0WhCUbZous3X3n6H87Mpju+zWoWSxtXv41gu3aArJz41WIZNv9vH0ExEo7A/+v+evPR3gb+OlBj8deBvAH+Zbzf34dNvtnkuIZtt29LpdD78GFBURpM9xuMdouwFooVNHGOYMu483VTohvxv1FVFHEX0O13Ojk8kpivaEAQBqsY2X2GDbbsYhkUcJQi9RdcllUhVNXTNQPN0lsslqqpQVlvDji1BHefnU+azM0bjvmym1Q2bOKbf70tbNIKLs3N6nQ5CCJq6lqnGmdyY8tKk0w2Ynp/zyiuv8PLly62RqcLQTSi34bRXDsirDb1+R8beIbMCLUujpqFuK9Ik20bTa2TZBtO06PX6PH/+Ak3TGI0mJEmMYeoSQisa1uuQaBOzNxkThiHrdShDSAwHVzNQVNlUE42grlqCwCdONZYLqUa0XI+mhsVqSeDb23CaBs/3qVvpGygbGfluWBZnZ2fcuHadD95/QJrmDIdD9K3ZKy+yLYW7wnEckiTkfHqBZpmX+P31ek2vu8t8WvCVL7/NxdmGVz92k92dfT64/5hr165SNzl5EXPn7nXicMU6jOkN+rzyysfodHoswzX93oB33nmXu3fvMZ2qzC7OuXvnFq7rkycbdnZ2ODo6YpMs2R1P2J3sUFU1u7u7vPaxe0wvTrj7ym3OTp4SxRkPH79AGD5RlpGeFrzyym1Us8Q0fZ4/eYoqFNJNwmy2wNItTN2izNZQQ7fTw9A1dF1HNC1NBfEmJY1COq5HWzRkZFimw+/89lcQQobErKZL+oMAU9cpUtmX6nbkfWdbLqfHF+S53JzCZUgSZbSNimUJ5rM/Pmnhw+vb2hTatj3/8O9CiL8P/NL2n99W7kNTN2iKgmaY3/pdEAKEKtAUh6Az4HR2X5JlbIeWgrYBx/EoSmn+cC0byzCJoxjLNBFCYNsS8WWaButwfimhzrIMRZGlV1lKFkCSJDJFeat/X87nDCYTNnFM4PU4OTplf3fCqD9gPBiwWiwpFZMkS6lyuRD8TpfUjUniDc7YYbY458qVA14ePcf1JJq7zAtE1fDy+QtpdvIDVvMlF+EZ4/EOQgiW8yWarXB+fsZkuEMcJRiGS92U1GWKYVjois1ms8HQLbTA4OmT5xiGwWuvvnGJQHN1gaFr5HlOVTdohsV0PiMM19i2PEZohpw+JEmKaRpEcYKoK7ygS1FUEvqSlDx7/pJ79z6O67o0hU9ZJNRVjaoaFGXOKopo1RrTtDg/v8AwLIyOwenplFc+9nFEI5jNFrSiIctTKSVPYhQFqqrYNhdVKgTRJtnCU/u0wubJkxOqsosipIYjjmOSJKYsCl555Q6DwWCbHD3kgw8e0u12OTk5xfe9bQNWJ3ADHj55ynR6zt7OmAcfPGIy7lMVGb7r4Loudbnh/nvv86Xf+jI/+iP/Ji+fPaP7qddxez3QNYa7h9S14MmjYxbrEz54+pjx1SFWV0VrSpRWYt3mixkFLUmcohk6R0fHvP7xT2HbJicXEkefb2LaGhzdoef6FKIiCzMs1yWJUlarFW++/knSOMN1VfZ3JpxfnLK7L/M4iqIgjmOKuqHYyEpwOOpLZF0UEYURluVg2x4nx8cfeX1/W5uCEGL3W/Icfgz4MJH6F4GfFUL8FLLReBt464/7eoqqohk2TVmi6CZNU9O2oKoaggYUBdP2aFtBXbcYhopluRy9PCfNGibjAMey0ZAmpKooZXDI+TmmWUeEkAAAIABJREFU46NUJUme0tJi2hbL5RpdswCNciOR7VHU4gcui8Vi65Yr2N3d5fT0DCGUbR+iy3q5Iug4LC7OpXahO0ZRJS1HVVWyJMYydNS2ZTo9x/E97j96j8D16HgyaMYQKp0dn4vZhdTfC5V0k9ANOkTLJePxGH3QJSpCqjrj7OwYTTPlqBIZWpPlBaLVMAwL0zSZTqcYhqQWHx2doJoGTVXQNhWebSNAkpmXC1Sh0On6qIr0kxiWg+t41JUg2oQMBj3my2NUQydNcuoadNPkzp07krmI4Pz8HMdWcV2fOEpkaC41/X6PxXSOaqkUdYWigOv5PHzwZMtOVCmqDN0w2Gy22Pw8xTYly6HYshWiKEEROpu4YHZ+wulxyHquoQi5kZVlTZrmbKIY3+/QCfr0un2mFyGqbvLOO++wszsmTVM6HRlf/+qrr1LUskHc8V1oGp4/f4mpCx4/XNDv+uiaQhRtcByH//sXP89rr3+Cz3/h1/jXvvvTuKpDmpa4ls8qzvj13/gtgn6HXunT0V1WUUQ3GNM2DXdv3yFNKjTd5nx6xkAfsJ6vOc0i6iYnKxNMVadMCqyBzjK6IKw29Dt9HMsmjzPG/RFZUdDrdmnbGkdTGXY72JqBauiswxjVNGmThKYBXddZryLKKqepQVE0PvGJV/ng/kOu37wOPP5I6/vbzX3400KIN5BHg2fAfwzQtu27QoifB94DKuA/+eMnDyBPHZJ6U5YZAE37oSlKWlRv3fwY773/RbIsJk1TDENjMBpxcjwlK2UisaEbsA2Bmc/nVHWNKCTAM0kjut0ex8fHaKrF8fExV69ex3HkmbuqC9mw1DSm0ynjyYiLiwtsw+Tk5AwNg92dHZazElMzUUwNXdUQApqyxDYMQBCtQ9mICgLs1kEzNVRVIU8yJpMJZ2dnMisS5Oi1bWVoSi1Q2oaLk1OaomAw6hOFIZ7tE6cJoMon5CYk6AUYpollmvJpbJiSLLydvS+XS3RH9glczyeMQiY7Yy6ePZdj1Tzn8dPnHB5eQTFMTMvh5dEZh9cOQVM5vZjSDXzWYUxRVFiOT922mLqGbpjkRUbZ1Ki6iVDhxs1rvDw64cqVK8yWU/KsxnVMmjpHM0wWq5jeaAfRKCymU/yBTSNaFF2i56qmkTRoU0dFRtfVTcbp6Sm94Cq/+9vfQGn7CFwUYXF4eBXf9zEMg/fefYeLiwsODw+xbZedyR57exc8f/GYoig4Pj4mimJu3brF06dPOdjdY7Zc4Hsd8izB8Vz6vk8QeCSbGEVpt5WidJ2+9/4HpOmGJ8+e0jQVn/1/qHvTGMvS+z7vOft2z92XqltrL9Xdsy+cGVIkJXJEWooRwXIEwTCiGHYAW1mcOIkdyU6cD5NEsBIIyAYBsvzJTizJlkxJUSSREk2OOJwZckjOwp6lp7ura69bdfft7Gs+nMuOgyjSBIgB6nypwsVF3ao6933v+77/3/95Pv48j956ghu3brF77SaIIntPXuVr3/hdktRnNBgjSTkiEsNVs5Isi0iSgKyrTGYBrXaNy76LauhMBxPyeo5tlVByieVshrOYo8oq7fY6i4XDg8NjnnjsEZzpiLVOh4vRgIXjUK03CMKAaqnKJBwSeAUnYjqdUiqV6fV6vPnmd3jkkUc5OTv6SBMCfN/wFJ7Lv/PGqyCl+IGLomrIog5okEOSZsyW7/GLv/SzBPGAPIM0l5jNXUplC12TEOIcWzeZzybIqoSqqwSpj6XaZElaaN7zjDgJUWSN+XxBvV5HFAV838cwTIK42DoASCsjkaio1Ot1zs/P0RUVyzBxFguq1SpCDvPlomi/1fRVF2Bh+SmYEAkLZ4lplphNlyycJfV6DeRC3kqWUit3CP2MwPcxdRkhz0miiDCOUUyV2WyBrKhEcY4kSTz7/LMcHD3g+Oy0gLFIMkkU02g0iOIAQQBJgV5/gGmVSVOZaqtGEDpIYk6r3KR3esn6xkahiy9ZxQGvwOqQS2fhOOiGjCyINOstwqBAvmm6zmQ2pdVqkUYx48EQUchZ63QZT2eUq03iKCNPYyAnXFGZfNdjrdPBGU1RRAkvd6k26pwcHtFqtKlWy/QvztE1FVXTWIQ+fjijUb3Gr//T12k3rzIajdjauM7uziPUqhJJGhGG/uo+iJyfn6+2kikHB/tMxkMMQ0PVFHRF5caNmwwGA8olG9f3ODg6QVVVnnvuWU6OHvDYrZvsbneJPIflconrOJydnSHkxf/lkx//BN2NNa7duEYQ+MwXfaq1DrrWYTQf8qU/+mfYtkTJNqk364xGAyazMddvXmc8GTKdTtBkHcsw8QIf1y3cFOdnp5RLNoPzSyqlCk9/7Gm+/trXuX7z+sqFEdFutDg8OEZEIk4jru5dZTqdMp3OsU2bg/1DKs3S6v0sMxkvaLU6TKdTrl+/Sr/fR1Lh7/7MV/8s8RRykGSSJEcSdURBJ0eEwtKILItUq9Ui4ZjmK0BpSne9g10yCRwXkYz5rOjp13WdJI2olMss3CX1Zp0gDknyBM3UiLOYRrsJkkiaZth2GTconIiqqpIDo9GIUqmEZVnMZoUcFSFFUUVERUCUUgQpxzSKgzdBEjFLBogZJ+cH+NESL1xgmCqe57C23qHVahUJQ8/Hd1wcN2O+cEnzjHKlwny5JMwSFFMmEVKyXKTV7iApKpWqzcJdsH9wnzAKyNOIG9evYJdMHnn0JpquMJ3NaK630EyLre3tovypywW+TABRLmjI3e0tBAl0s/A/+KGHokh4nsPcmaNqMmmUYuoWrAJQBYuwQKJ5nkPgzVGVIq7t+yFCpjDoTfnuOx8QhyFZGlOyDCQRKlWb4+NDBpMBcR6j6NrKIWGRZCkLZ4lVtnE9jyCOSJIcRazx1S+/yXpnD2eRc3PvSa5fv0W3u0alXGYyGqNIMpqicnBwwLe//SYnJyerBKLI0dEROzs7D7dWvu8/hMyEYcitW7dot9sPydWO4/DVr34VTTPY3d3l2rVrfP7zP8wnfuA5/upf+cv8wCefQ1FhPLzE1FVa7Sb7+/c4Pz9FViQq1aLhzHEc3n33XXq9S7Is4513bnN+dkGSpASOx8XFBVmSkqbpigxWfLBsX72CqFssvJAbjz7ObO7hejFRmHN02ENTSjTqXUyjxvvv3ScIC4qXqIg8+9wzbG130Uyp2JaYMv1hEbg7PT8jSuKH5f6Pcn3f9D5kaVJARBUJhKKmmgPCqp4hCQrj8ZRavUCsl8wSQeDRaNaol7bRJJnpeEKWJUhyoZHPsgxBEnGjAMScRqvB2ekpWZatXI0yy9kcRZcply00Tcb1i2oFFNWP5WJBmsYkSYwii/QuTynbFmcXJ3Q6HeZewVn0opggCCiXy6xvrlMqlbg4u6BcbpJnEZNxiCRWyBKRenMDRZEZTnqYFbMIyoxOcBcu3VKXk8tLrl69ymS8hDQjzXPiNC28EnGIZmq019dYLqcYlsZwPKRSrrK1u00YJaTkpCKImsLlYEhDSClXS+RJjKwruL5DGPq0220AolnA0dGQmzf3GA6HCIKAaa+qJ3EhbcmyjDQpyratVovZZIypm/iOT9mss1wu8fwQU9cIQofMT3D9BbplslwuWO+2GPUHjBcj1ssbTKbz4j5U60SBRxQFlOt1cjI26g0mo5TxxR2ubtc46N/l+Wc/hiSkuM6IgTNFVVX6/f5DKE+5UqFcqXF+3sN1XSqVWkGD8l0UpeggLZfLREFYyIQQabfbyLKIKguULZPlfMqXv/xlNje71Kplmo0a56dHHMQ+llncpxee/ySjQR+kiKeffhpNa3Jn/30EMaNi25imSS7kRFHEWrfDwfEBjUaD2WxCxdQZT31kuXjtMIlZ2+hiqBq6bqJoEYKscHzQw7IMSmWb4cWQz734Ob79zTeZTGYEUbE6Ktkm0+kYQQRZERDkBMddMpvNse0aO7sbDEfF8x3HoxRqf9yw+2Ov74uVQp5niFIOWQIC5FkCFGmu710CBdYsjlJu3rzJYjbHcxzmkzEfvHcb3/dptJp01tce1t3jOF6p3T10XWUwGNBsNrEsizxNiYMQWRfx/AXD0QW6qRXgkSTD8yIWToSp19BUmzyT0TWLtbVNZMVC1WzCCBTZoFZdw/OgUb+Krm4RhFXiuEW9/gSR3yIKWnz7jR6vv3bIg/sBh/c8jh8EiIpAuW6QiT6lusnG7jaSpqEaJcI0I0wz5kuHXADFVClVbPrDIbJUcCCu7l3HMArMW5gUxGXdNAiTmDgO0XWNVqdNkqUocqG8/94qq2SZJHFEEkdkaUKtWmE6GVOyTOIoIvIjgqWPv3SQBIH5eIKQZqiSjCIqTEcuMjrNWgd3ueDKTpfr1ze5+cgmFVsny2MQUpbLGaKQIUnQ6bZptevEcUh3vYMoilxe9lA07eH90jQF3dDonY2RhALx3mo3iaKAer2CIEZU7TKnx4dIqxL292C0h4dHzGdLer0LfvjFz9PrXaLIKrZts76+tmI6FqlCSZI4OztjPp9z584dwjDkiSee4NFHHyOKIoIgwHUdOp0WJcugUSuxtdHGMhQ0vUhXvv7aa9y/f4/ZfIIgpIzHI05PT1YMzGK1CdDv91ksHCRJomLbxf0KQyaTCZ7nMR6Pubg4ZzS+5GJwjmmpzOZjvv3tN5BVibe++xanvWMURcCPHObOhLkzRlQymu0KqRA+TOBubm7yo3/+RzjrnWGYCkmeUa6V6W7sfOTx+H2xUhAEgcBboJsG+x+8yfWbjwIaoiCRUUSeAXTNIAgCDvcPMVSNRrvBdDai2+3ieEuCKAQyTNtCEzKCuNDDiaKI7wfYJWvVKKXiOT6WWSIXBdJULOy+UYau1gj8lF7Po2w3yCKRkt2kXFWR5aKLc+AOUGQLIdWxNIs337jHg/tnnF+8SXftCkGYoakFUkyRRdIENK3KdDrn4uIeogg7W12ef9HCWRbA1PncRZUzXCem2azjeD6CUpChSrrJcDzEsixanTZHJyfUalWOT85YzJZUanVmsxmVWoXxeIima8zGS6rVJkGwLE65w4iyVUJCIEVAVTXiOKZWqUKjeAMvl0tarRYVs0DXJWFE6AcIOVTLNrpukOcFoObTn/g07soFMZ1OkRUQFZjMR/hezM6VXeK4cGaocqFRK2SwKnGUkUYhkpBjGAZR4BUeg2qbo6N9DMPiu2/fI4ltBsMenbUWpqWTZjHNRpWzwzOypMDBj8djoiihXK5iGCZ3P7zP1mZhdjo5PeKTn3yBG9evPYyCl8wScZogSRK3bt3CdZdsbTzDxdkpZAlr7RbdbhfTUJAlqFUsru50+eC9d6lUC4Vgt7tJGHo88sgj1OrbeAfLVTt2xnK5JM0zbt26weHxEaqqYpo6s1lCfzjEtAp8XRAElK0ShmGxnC+QRAk39rjsTTAMfYXTk1k6M5Io5ObNaxwdnVCrWwSxV2D0ljP8qCjtaqKKLKvIas6v/dqvYFdq+FFAksW06y1OT0//hBH4f7++LyYF8hzdVEn9Md9951WuXFlHMmqAgYhAmkGSh2xubrN0zlBVleViymQ0oGQbTOfFWYAfF8nEXBYI4mKffHl+SdmuIEsioRcWTVSKQBImxFKEbGlEYYSuV4lDBUG2uPPBIWlc5q0PzljOHAQZDFMBISUKY0BEUy1Gowmt2hq6aVMtP0alrOC5Ec7SIUtkpsuiy65k2ahSRrd7E0NvESc+XugxG2p02haBN8XU66SJQrPVIM08chJqjSZpHpHmKbIskmUZjuMSBjFpJjCZzCgZJRSpaF7yPJ8ojojjkEa1huf6iGmOVTIwNJXlbEoqRMi5zHjoPYx8O/MF9XIFMcspmxbT0ZRcLdyOdqmEN18SJSGLxYL2WhtNjjk524dUwC6VUFa/myqrXLlyjdFsTpQmuL5HnmVYhlnkP9Tik12WVqr6ZsEPUJUynuswm47Y3toiDkW8Zc529yqDYY/JuM/V3atMRws0VYKsoE0Ph0MeeewJsgwOj06QZYVHH32ce/fuUavV6Q8uiKKI3nyGLMt0u11UWWV3d5dckJjP59i2zfn5GYam0WiucX50hK4q1Gs2uiZz/84HvPiZTxV/e6fJWmcLBImvvfJHHJ/0+fin/hx+ulzxKmV6F3OuXNvl+OSQWr3KfLkkSRPqjSqR55GR01lf48MP76LrOmvtdZzZgnq1QRLmlKwybuCgCTm7jz1Jr9dDVgyGwylJEuEHEOcxQi7hBwmqJqCqBhsb2zy4v49hGWxsFZPidD7BrtTxQg/T1j/ycPy+2D4AjC/PkaSM92+/QRYvmA5WYYu82NtrkoYoiiwWRWTYMvWHwZR6vY6sKCw9Fz8KmC5nLJwlYRyxvbWDJIoIGauae44iKtiWxWQ4YTicEEY5Z6dDBpdLvvrV7zC4iLg4Cxn1c04Pfe5/OOHdty84fuBhaVcQs3X651DSryEJNpOxj+MGxcAwJFrrVc77R+hGCc2scDGcEaYCF4MhYZoj6waabvLmN8/5F7/2NeYTgSiQKFlFBDYnJYxclss5QegX+LMkZjgekWUZ29u7xFGOaVVYOB7zefFJNZvNyJKcPMsIXA9Fkgr03LQAxUoi1O0KEgJVuwgmTUZTVFkjDmJCLyQLU0zdIA4jZrOCLxGGIWQZaRJDnmOXDUq2xJVrXZIkKAJZcQq5xGQwB0FgNJ08xMlPJhOSKGI2meAsFqRxiCIJkKaULQvfcdA0BYSMs9Mer7/6NpJQYntrjyRJ2N7eJs8ktreuMbwYUS6X6XbXaTQa9E7PcFeSmOFgzMnJSQHyTbIVGi6i0WgQxzHn5+f0er0CxJqmD1H2pVKJcrm8+rldqtUqpmkiyzKf/vSnef31b1It14jDAkw7ny7wPJ+96zd59pnn8MOQIAqJ45D19RaiCIahEYY+lWpROlVVFVGSqNaKhGWt2cAwjCL3YpXon12iSzr9syH93gQJnd2d67SbmySxQBinRfw+yShZFQzTptnYYGvjOpvdPe7fO6ZWbRGsovTttRbt9TVkWSKMo2I79xGv74+VgpAR+R5f/INX+Xf/xl9HkWNqDROiJUlmIK+sOM88+UPcu3ePNDVZujG5oCArMkEUIEoZzVYFw7A4PjmjWi2T5wmL5RhVM5HEojvPdxwEFRRVo9qoIxoCEg3ysMsXv/gNNK1GFHp4fsJsssSPE+IkQ5ZlfD/nrbeLnFalUsMfXCAi4AdLfL+QzKyvb5DEKZ/51Cd58pkX+M3f/G1KmxuoqoquqDjOgoVXmJPs0jaq4XJ5ltLqCMhSQpxEqLpUtDJnDvVOjYQUrWSSSQJGyeJifI4sKcRRQqlRwfc8NEPF9DUkQcLQdbIgQhYkqpUKs6XDZOzSqNbpn/XpNJoMxxPW2+tEy4Q4K0hJhqJhmRqLhU+1bpClAtPFHKteIQx9VGLiOEaJJZKk6MLsj/rFGY5pEiYBQeqTLXLEKKdStZlMR8higWELw0IoU61YnJ85BKJPFAVFedGXKZtV5FKZL713iKLUyMUQq1JHM2sIqojjz9FMA0S4ceMGvh8wXzgcnZzjRQmZqHB22SdNY87Oz5nP59y7cw/r6SdxFg4AiZzw6quvc/XaNR559Ca2qWGqTXpnx3jLEZamY+oab33rDS4vL9jcWuORWzcI44has1iGt5tb/MRf/CkqrRa5IqFaEsNLjzzXsSwFPyri6b4XE4UZx0fn7OzssLZVlIElWaFi2lyenbO5Xi0Cc1WLXBIYOEM+9/kfYTwb8+q332Dvxi1moUe10UBOQ9SwOHuxzTKKrRB5LpotsrGxzsnJSTFR9s4oW2XkPEVWRRzHIU4/+uf/981KodWo8C+/+L+jSgkPHtxmeH6Ps9N3CcIhebJAEAWa9TaGWuHB/R7f+uYHfPF3X+M739xnOvaQRB1yhcuLMUkIYZgw6E+oNppISkE8qlSruIFLEHskQkgihJTtDl97+du8/JVvQ2ZyfNTn+KhHr3fJfLEAoZgQBEEgioq9qKZpDAaXzGYT5vM5qqLjui6iWODNLKPEsD/ijW+8xs//3H/L51/8LGXLpFKxqdUaqIoJuUyci4iiTe/cZTpKmY1TDL3OchFi6DaKoiFJEu32WpGw7HTxHZc8SQl9j7KpMxkM0GQZSRTRNY3QDWg31hBlgSAOqFaLYM71q1dIkohre9dI8pjNbmG0qlQKeGilUqNSqZBlGbIsoigCURKi6Apu6CGoObmcoeoFaEYUi/jy5sYWumYxny8wrBJZBrVaA0s3EIGqXZSSx8MRa+0OvuuRhCn1agNTM5FlFUPTESkUcgcPzhFyi/F4zGI5IU1TLvtDVFVmOp3Q7/cfdoUWSL0MWVYYjSZEcVK4IXa32djY4JOf/CTlks3e3h71ep3A86lXa+zt7SGJxfZoNBohyzL1ag1ZEIk8F7KEa9eusXfjWhEqUhR+8LOfQdV16rUGpUrBaDg+PuW8f8a9B3fwfR9dN1aBr4j9/X0uh0MmkxnNxhppItI7v0AUCl3f6fEJ1XqTo/Nj/MhDkAVkQ+LKjV0OT+8TRj61uo3vz6hWDcaTPl4UECUxSZrjLh0qdnmlyAsgy6nYZdbaHa5fvcaD+w8QM4HIDUmDhCD46CsF6aWXXvrXNtA/6vXL//AfvvQDT23zY599mlbLoN6solkWsqogZCnLucPl+RGvv/4Ko8EYS6/RaV+hf+Hw9psH7OyuQ67gOQmaViHwU3a2dmk1W8wWcyRRwgs8PN+jUrfJ8xRBFAiTkIN7LmRVPvjgnPHIJctEbLtMnMRoql4Mcst6qHKP46hoEV49liYp34PMBkFIGMRoWlH9cJwF796+zX/19/9L9m7uFXFpoFqrYRglxqMpqqKQZzCbOKSJQJal2BWLNImYz8Zoso6z8iN4SxdN1RgOhrTqTWq2TZLGyKLMyf4hZdNme2OH/nBItV0GBSRJxHOX3Lt3B0vXWDozOmtNVNUgB87Oe1z0exiGzv3792m1m6RJYdVKEXFcZ8UGTFE0AUVV0DWNxdRj79pNDh4cEoUhnc4aQp6TZhlpFK+MUymBHzKbzKlWq2iaju8HBH5AHgssHZdyyeb4+Igsh35vxGKa8OEHQxTFwA8C6o0GF71zOp02lxdnOM6czW6XyWTKYDBi6biYls2Dw2Oee/4F+v0emxtdosinUa1y8/oelxdndDotwtBnsXBod1rcuHGTLEsJPJ/h5SVRGKGIIrKYoSgKpmlw48YeN/b2gJyzs1PK5QoX55f8zv/x+/zO7/w+jz39OAkhc3eAYoAqilQrNnES4bgOQqZimhXOzwbsbF8hzyNkSSbyiq+O61IqWWiGymBwSRh6NOo1DF0l9DwkAcQ0JXRdDE3FjwIUVcf3fJqNJqenp7jOkuVihucFxHFKEPjMZnMazUbBwJAU4jhBzBRef71/8dJLL/2jP208fl9MCr/0S7/4krS8y2ef2sIfn6NtbkMq897t93npv/j7/OYXvsjv/+7v8fLLf4Tnxnx494DQFZhOfQI/Qtd0DK3CaLjk5LBP76xPjohpWiSZh+PO0XSVkl0YjsqVDlEIea7wja+fsX9/xHKeEscSqqITJTGsNHaaVii8C9BHVuQVFAVRLEqkslQstgoCckIcxziOA+TYpRLz+ZT79+/yH/9Hf4sXP/dp6o02H969h10u47gLprMZqmKQpRKSKOP7DgtnRJwEaIpIGieEro+EwHI2RxJkNFll78p1Do/uo6gaZbsgWI8HUzZ2ttm+eo3bd29z85FHmE3mGIpKu94kiWOWzpLxdErguNjlMoZZQF+2tjYRJZEoTHjk0Ue4d/AAWdFodtYIVucci+WC+WxGHKbIssKHH37A9uYmeVZMjJIsMptOyUUR0zCZTKZ019aRZQXLMDENizDwiYMYUZCoVWvMZmMss9jXC0icnow5OljSbLV55pnnqNZr+L5LrV4lCj067RYiAhsbGywWS/wg5NvfeZPnX/gk9+7fRxIF4tBDFkXyJEZVZd599zZplnJ6erJSBNgcHDxgsVhw0btgNh4zvOyjKjKT0SWz2YzHn3iUcsnG81zsconjgyOajTqeF/Lmm9/lL/xbP8ELn3iO+0d3yKWIVAiQAMs0EcSMcrlKudREyBXCsMhRqKLAfDItJLJJgdAzSybD8QBVk2i36kWreRRj6RqR55LGEbZRZD3qnTbOckmz1cJzPXzfoWyX0TSVLIM4SsjzlGqlwny2oFFv0b8c8pkffJHRYMorr5z+2ZkU/uf/6Rde+pX/8T/DPbmDO5tx9uCCX//CH/DP/7ffxp1HvPfBMSfHPQZ9F8dxUVUTQVAwLYv5fEkaCZycXHBydEHgJZyfzXCWCy57F3S364hSTMk2cd0I35EJXA1RqPL+e4e8850eWaoDOo7jU6mUieJolWSco6lFcEcQhBWQ5XvQ1QKZVtCiirSYaRan7JqmEQQBaRwiiTmO5/Le+x/w4oufZ73b5fmPv8DZ2RnNtToH+/sEvk8SJyRJjKaLtDoVZCVH0ySyJCGJEjRJwjQMFrM5vV4fWZUxaza5rDCZzsgzgbW1dYazKfvHRwiKQp7luI7LYrIgjRIM00LVdPwwYdC7RBAEqo0qggiSWrAi9/cf4LgOlm0zGi0JwhRd06nVapycnFIuVRkOpyiSQLVSgTyj1WqS5ilJGlMqWSBKZLmAKIiIyOTFnIEmS0iigGnohGFIuWKDENFoVvHDgGq1znTkc/LAZe/6dUoVG4GccqWCs5hRrVVQZIVOq4nrupyeniHLGg8OjjDMEkcnJ8XPN3Xu3rnDp37gE4SBz9paBwTY3NygPxiuLE/3OT09pd+/IAqKCVjXFOp1i5t7e3Tabe7ceZ+3336b9U6bJ554gl7vAsuwuHr9BpValZ3ru3x4/30WzoA4dUnjgklZKplMJzNMs0zgR+xs7+B7DiWrmPxq9Rau47J0nIL2ncXkecaDB/t0Oh08p9DLbcAyAAAgAElEQVToSaLMeqfDbDLh/KJHLsmsddYQBYkkjtANg3q9ytJxqFYbSLJIu9PBCwo8QL8/RJY12u0uG+tb/PpvfOvPzqTwP/zCP3jpb//Nn8CIA1RR5+5+j1/951+kUt3i/r0LhjMPTbO4fmOPp5/6GL4fMp8vaLUabHa75LmMpmjUqy1KpTqeG7CcL/kbf/2nUQ0Yj4coks7hwYDJUOAPfv9NvvKHtzk5GZPFKoZWJY5ykqTQo2dZyng8ZXd3l9lsShQVJOg8z8mydHW+UPRJqEpBFVYUjSiKMYzCIp1mMWEcEMYRURQznc145NYtdne3KZVMnnvuY3zr7W9Rsgx81yPwAyAhjFwee+w68+UYw1KRRYEw8KnYNr3e+Yr00yGIYrSaTZJl2KUSi9mCJInJhJzBbMTG2gZxmLJcLBHFgiIliQrDwYjxcMqtvT2CMMCwDebOFFmVKdtl4iRBU3Q0XWc2dwm9mKPDIzRVpWKXEXKFdr2DYRoFA1IScTwXWVYJwghV0bFtm/5giKlbNBttPDekatss5zPIYTKdUa5UiOOA8XxAFPuUKxVkRePOB0dEXrF9c12XJE3wXJcwDNjd2aXZbCDkGZpmMJsu8IOQKE4YT2boZglZkdl/cB9ZEh9i3xqtJjdu3GC5dIq+jTQjDAM+80M/yOZ6m3JJ44XnnqVWsbBLJrVahXfeeZt//I9/g0dv7SLLclHBCCN8P6Cz3qXZaVNpVrj74H2OzvdpNMusNdeYTiboRtEc5ywdlo7LeNwvGv3ykE5nnd75JZPJjEa9wcnhIevrHfIsQVZVkiQliRPyHJIkIwhClq6LJMmoukaSpPheQJKmqJpWbClkiThNiNMYSREwLbNolKo1qFYbvPPOe7jLJV975egjTQrfFweNtWqFv/Xv/21+9r/5RUKhgiQabK2v8eHdfQTD5Nqtq3R31qnWa5z1LrDtGpKgMp8sEVGwrRKVSg1VMZAxuHH9CX7oB3+UV195k3e+dURZ36ZqbqPQ5M7tC2xjG02uEfsyaQajyZiFO0WQWPX2J1TsMpe9S3Rdf+hgLPgMxkOwaa1WQ9UKmYooyquJIVlNEgpBGLNYuvQHAxaLGb/8y79E4LsoYlH2abfX8cOY2XKGWTJIM9A1m2+98S5bGzdor3VIhWIFctY7K/roVYn5comoqIxHcwaXQzwvoFVvIAvFp/HORpfJ5SWTQR/LMmh3O2glA91S2dno8txjjxdqek3j8PCQWqOKoOQs/QWarlCtlRDyhHrNZnury9WrV/D9wnn5V37qp8hzgfPLGYpik2UqimIzn4dcnM+IIon7D4558smnC7NUnLO7e4Xz84uCbSGKmIaNZtiMJnNKdhW7XCdOcqq1JoulT5LGqJqC6zoPo9jj8RQBicCNUNVipbG5uYlpmg8zGnEc44chYZQRpwLfeettTs7O+c6bb7P/4JA4TXn11de4f/8+P/7jP06zWWdzq8tjj93i/v77nJ0e8ODBfe7evUun0+Ev/NiLXLlyhe3tbcbDEWfnJ9glHcsyyMkII5+Ly3PSKGY6HTOdjYGMy4seYeTh+y4lS6XZqlCuqpQqJvsH9ylXKyxmS26/c5s0zpiPZ8jIpEnOcuEynS9JcwnVtFh6PlGaYZUrjPsDJChUh7rOwpkThCHjxQzHd1ANFTfwOD47wSgZ+JHPyXmPFz//55gtph95PH5frBR+/uf+65fk3EM167z+zW+R5ykngwHv3D+jsb1Nd7uJLEscHx/jej6TyYIwSFjMXSaTKQgppqFTq7cKI3WUsHQLeEe51EQWTaIIfu93vkIa2zzYH6AoGq7rIIgZVskiS3N0XWEyHVCr1/CcAFlWuXptl36/XzRZJQmCQEF5FgsSUp5lKIqOaVrouo5lmSRJjOPMybKc6XxOuhKvKopMEkc8//xzyLKMYtb52st/xGw2pVErJK6zacFzMCwFyQxI0whNEYnigDhJWLouSZ5TbTbIM/BcF5KEPIjp1BukUcR8MadZqVC2LbxggRMs0DSZJAzJ/ZCaVUJQCvX71pVN/KjgVCZJShIl2JZFuawR+AFxmlKrlogij831de59eJ9nnn6e2+/dx/ciyuUqvfM+cZRTsusMBlM6603Ozk5Zzlxm0xnt1hqGppGEPmHoE2UKnp9gWhaVagVRlskzGTKd1199h0ppk97FOdV6FVmREQQRTdOxSxU8x2U6LZrVPNdnOl2QZSKO5+P6PvVGnZJtE3gehq5zfHLM0im4DYdHRzz95JNcvXq1+F/PxpRMlSR02VhvMp/NePrpp5lOp6iyCOQ888wz7O3tce/uPWRFIgpDuptbSLpKmETc3f8ATRdR1Zxqpc54NKBerzAcFRg4SRaKVKkukOUJl70BaSpgmSXarQ5pHHN1d5soCjHsouKk6QaarjMaj2mud0lyIM8JHAdBEInCiBwBq2SycAvpjF2y0HSN0XhAu9Ok3mhy2R/SbnUBGU0R+fKX7//Z2T78ws//3Eu+F/LhUGQUlnjnwx6paDLxYz48OCH1I5ylSxQlVOwKkK0cggmyqqCaFppqYGgaZqk49Y/ijIODHh/eO+e7t49545sPGPRDoghkebX8F+RCg4ZAkibIskqagqioaLpBrVkjXdmvF4sFeZ5TLlfQNB1FUVFVHdOyKdl2cQ5RMsnynDBMicIML1yy1uog+iklSWHQP+XByT32bj7C1tY1Wu0KnjcEz+NaGT5502DRP2O8FCmtbxI6I7Ikx9Q16rU6tVobXSnjOS5iJuDOFqzVW4j5yvRULaHpCpoqYFnl1T5eIXRcKpaNLEkgyyyjkOW4j2kZfPD+HXTFQEBiOl7QqDUQBJnexYQcgZyELIuo1xvMlwuCKKQ/6rH0HcLEp9Ksk8uwe+Uqr7zyKp//4c8xuuhxY+cRdrZu8dSTz5IT4EZTJssZdrXDYjmjXNaJ4jnlikoQ+QSRxitfP+TBvstTT36M45Mznnn6Wd69/R5lu4zreXTW2iiaQr1aZjqd0mmvMRyPVpNBi8ODI5IkZjaZosgK1VqFZ599imu7mzz79OPYpkazVkbVRbI8w3FC0jhjNOhRsUWeeXIP0yhzedHjhec/RqfdxLZLvP32W/THYzIyRFREucpad4dvfOdVJNVD0WIsXWe2nGNVK8wWAWvrO0znC1RdRxAlVM1AN0oIokL/8oJGs0qWBahqiuOMEYUMXdZRZZUPPrhDqVRnufRQZJlK2UYmJ4oLelYmyoQZ3HtwhKJpfPjhffSyjecXk24aeASOQ56mXPQuyPIETVX58h/e+/9n+yAIwpYgCC8LgnBHEIT3BUH4T1aP1wVB+LIgCPdXX2urxwVBEP4XQRD2V2DXZ/+014jjjEqlQxjETCYT2u02H3xwD10p0Wmso+smgiARxzFnvfOHApOrV69gmgaVSoXhcMhwPML3fTJE7u8/4Py8x8XlgPF4zGw2K+AdK2aiLMsrPmCG5/ur/bH0cDlarVYL4jGwdJzCgaCqWKUSiqqiqCqlFaU3yzKq1WohOkkSsjwhTiMkJJaDPh3LZ6+Vcq0pwHLCF/7ZrwIZeQh/6Sf/Et1ujZI+p6EPeOFWjaYtsf/hXaRcYqe7RZ5lREFA4HpYRtHuTJ4iAGEQEIUhs/mSk9MLZnOH4WhG72KAJGvESU53Y4cwSrh7b78QvApglSv4frHHFQSJJC6qJ4PBiN7FGRkuUTJHVhIyfEbjcyQ5ZbEcEoYBpmaytra2wsr7DIbnfOIHnuGtt19nbb3J/tFdjk/u8bu/91scHe8ThC7r3TZR7K1WTRrd9R2mU5/tzUfZvzfA0tcw9Dqz2YLHHnuiSJ8qCoqicOXKFd55550Ck7e6l/P5HMdxVmg2D0HMEVYWLk3TabfXiOOEi8GQfn9EZ22DVmebJJE5Pu7zxS+9zG/99pfIMp0okslylV6vx80b1/n6115hPp3hOQ6L+bxIzlaaGGYZ1w/40pe/SJR6uMGSyXTKeDojy3KyOHtI2bq6s0vVLmNoGu5iSeTHqLLM4088Spz4zBcTSpUycQ5BFLN/eMDCWa5auResdVocHTxgeHFJ//KSbreLpCpIqoRtGzzz9JPsbG3ysaefQlYlcllAMzUSSSAWcvw0xqhbnAx6HJzt/2nD8OH1URKNCfB38jx/SxAEG3hTEIQvA38N+Eqe5/+dIAh/D/h7wN8F/jwFhm0P+DgF5PXjf9ILzBceY11DUWVKtoGoiDQbbYJUoFVt4nnTVQVAQlEEqtUq5XIZTdcRFsLDbrMCvBHSH44LNbqmEfkhplnCdYuVxvfOA1RVxHOLZCGr9tuiq9ICSSwOF9NCeRb4PqIk0Wq1HhqsNE1D0zQyAYSVvEUQRTzHeXgwaYkGLdPlL/8bT7FVV4lyk997/R6vf/VlBDFHE0CWSoiywPnph+yo0LJqpP4SQS+ThBnHhyfc2OvSOz8mkmLSOKG71iYDmrUm08kc0yihagZpGoOoomoVhsMp8+UxGxsd9g+OabUaNFoFdWk0mRDNfa5du4a/mKLbReKzVq7huj5WySbNPMLQxw9iZrMZIKKoFqJoMp0tscwKlq1zcVEYnpbzEYqkcOXaOp63QFEFciK2d9bJCJEEgYuLC7rdTRT5KkEYslzOyXKBe3cuuDhzGQ3OaLe3Wa64FkmacvXaHqdnxzRaTTY2NuidnVOxjWJil9SVXm6J67rsbG2zf3zGD3/usxwfHNJodiBP8N2A4XCOopp851vv8+G9O1wM+jiOh6lovPLqG5hays/8nf8Au2SytbHJG9/4Btsbm7z5zts8ODjgiSef5uSsR683w08TMFI296oMJj0sy2QyXFCt2NSrDUbDCf2LS5Ik4cqVHVxnQa1Sx1kGWCWd6WSIIGbUm7UCciNKxGFMvaZwdnbG9u4VnKXH6fEhnVaLcskiMzRm7hzd1EgyGI8GmFsavZMLVEUGTSJOEoSVwMeLQxaBS4aE1agQzucfeVL4KN6HizzP31p9vwTuUGDbfxz4J6un/RPgL66+/3Hgf82L65tAVRCE9T/5txAolW22Nzs0G2U2tzdY3+4SxzFR6OO5AYu5w9bmDuTFhGEYBkmeMHeWxHFMq9XCdXyiMEHTDRw/QNUMHn/8SYIgQhTlh22238scCOL/BZ4oknwyu7u77Ozs4LruCg8fs7a+QZ4L5HkBglUUDUXRyDLQdRNJLZwNkqSQrFYieZ4TBzGtskmzlCNFQ2pazHOP3UTIU77whd8AsZhxzVqXw5MlitLh7t0erpsioLHW7rC9sYksSaRJQp5lmKYJZMShT73aoFarEccxhmEwXSyZLzz8IGGts0EUpkynS27dfJQsy8iyjM3NzVVZrI1ll4qDVEFCAC4vB7Sa6zQbazxy62narR0k0SSORAy9ymjgEvhFu3i5qjBfDLDLOrV6uWh0EkT6/SHOMmIyniGKIqWyTZaKDPsLrl67QRQnRUNYMKc/vKRUqhJGIpORz42bj3Pt6k36ozGtVofXXvsGu7u7uI6PIAiUSzaHh4e022vMFw6GZRLHMZ/61Kfo9c4K3qUss7mxzWc/+1nSNOWNb36bt958h5df+Tq/+iu/xlde/irTxRxNU/nE88+RxAGj0Yj5csHJWQ/LsjBNkx/+zGdXrfYtynadgwcn1KpNwjTn8PgYs6Rxd/9dao0KcZqg6AaGbrFcFG7KtbU2jUaNy8tLNNWgbFeLT/oVNNgPPeI04uT0HLtSxyzXWDhLrl3bK3BwRtFdaeoa1XKF9fUO83lhw07TFEmA2Pep2ib1ss1Gq0HNsrAUjapZxpBVPMelUi1TrdlFN+xHvP4/9T4IgrALPAO8AXS+B2/N8/xCEIT26mn/b+6Hi3/lMQRB+GngpwF0VcU0NdLERzYt7u7fZTScgZQxGV8iySrtZuEqaLVa9PqXuK5Ls9kkCCMW0zmsFWSjpecync2JkwzbNDg4PCbNCmK0bmh4vl+U5wSBeCUAyeFhlNl1XQRZeniwGIYBvu8/pPgEKzRZGIbkokAeUpQmdY3ID4oDMM8jWzksdKNGrz9DDPpkgs9C2WLheHzpS3/IT/7kj5Gg8KnP/Bj/6B/897z81pT33hvjmFfJgoB+74LWE7v0L064evUq+/v7xHHMwl1QqVQ4PDhC1bWHq5dbNx9hMBjw7vvvUS5VePzxxwnCAjJi25XibxNEqtUax6Mzvv7aa9y6cZ0sCDBtmzzNqNUKUEl/cIog5BimytZ2l8FgwK2bj3Bx0QchZDZ3qJarLByXy/MerUYLIVWYT3rU2jZiTcEPQurI+F6CIBocPrjAtFQ2tjZxljMajQZHhz2ODh0arXWSJOb6Xpd79xpc9IfceOQWvf7gIduyumpYevOdt9lYW3/YcHV2dkK9WqPWaOJGF9y+fZv9ex9il0w+8cILXNnd5Lf+xW8wnU1wXAdFzfib/+G/R8myuL67hr+cUasZhZAmrxcNVXmOIEnkyLTaa2hGiVdfe4PR1OM//9mf4bW3vswkELBti+XSRRRU4gTiyGd3d5v79+9TKpWQ5WKInZycFe+R2EOUZCRBJogSjFLh4CyUeFXCOMIwNERFY03tUKtWyZJ05alYZz5bUms0yaIYkQzDMLnsnaMHJoZh4ToBJdlg3B/TqjTQRZHe4SEPbv9raJ0WBKEEfAH4T/M8XwjfQyL9MU/9Yx77f7Cg/lXvg6kpOUJG5LlEispFf0iOwGQ65tatW3heQLfbpT8ckGcCo9GYHJHxZM76+gbObEqpVDDqZodLjJJNpbHG4ekJSVh0lzmOgyQphGGIJBXbAlEUkSWJcCUHSdOU+XyOH4WoSsEbUHSNNMhxA58gjpBlGWfukWUZiqxiGBalUnFWkSgJQhJhmmbhrnQcHvTGkGkIsc/c8xkGF8R6nXdvvw+CgILIM0/donPtKf7pV76CqUo8dXOP48EdrFKd5XKOIAiMx2PanQ5+GJEhEsY5w9GM7vYal5eXPPHU44hijus5XL92FUM3i6YwzJUY1UQURe7d20fXdXTDYG9vjyDwkGSB2TgiSyJef/U1LLvEzrU1XG9Js1On37/ALCucXR6SZinuckm72UIUJerVKpf+qHAQlCpsbm4iSwYLZ44o5bz73jvs7T1GlkHv4oQo9pgvpiDE7F27wVpHY9i/pFK9QhDI5HlKo9ViNBoRzH263S71ep07H75Pd22NtbU1XMenVCo9XPmNhmOarTpJmuMsFpyfnvLv/Ns/xVqnSb1ioUjw0z/917h79w6nx2f8mz/2I+Spz3jY4+pWm/FI4GPPPEaexZye93jiiR/l6PgUwyhU7opm8i+/8jWuXdvjp/7q57n5xKO8cftlDMPi7t0HqLJK6ATEQYCsiFwO+uRixmg6pLu+yWBUWL9mzoil42Csej5EUSHPBILQo2JbRH6KVTY57Z1y9eoO+wcPkDUZS7eYzBf4CwdNUZiMxjSbTeIg5HvjMIsTNFtBkVRIBbrNLv8nc28aI1l2nuk95+5L7Bm5L7VvXVVdvS+iSHY3xSYpiaQoQSThgagxBA9gyxjYso3ByD9sA/Z4bA80FiBbhmARogRpCBmekSiRYouLyGaz2fteXdW1ZWVm5RaRsceNu55z/eNGpWhDSw8gGH2BRBYiIzKiIuOe+53ve9/nVUKhaYLV+XlKF22e/e776yu8L52CEMKkWBD+MM/zfzu9ef/utmD6vTW9/d87+0FoGvv7+8zU5+h2AvLcQSoHKYzCfz4/SxiOmEwmjCYB9116gPn5RXTTZdAvyrWlpaUCI+b7NOpNojimVmsUnIUwolIpzD5SysPJxd1GoxBFwrNSquAx5DlSFotJuVQhiVNGwzFpkjEJQnIFulboE1KZAVqRjJRlh6t+kiR4dZ9urLh8J+flDcHlA9hPdITlEIcJeu6jy4Q8TvnSP/nHuGsztFPJs89/n3F3hzAcUatVSbKYmdkGM7NNkkwRxVNTTBSzt9dibm6OVnuPKJ7gmAauZeLaBjeuXeGF559jbWWJeqVMs97EMS0WZhdwfI/6TIOZZp1KyafkuywsLHDp0iVWlo/Q2otIQodeJ0OjSpZY9Hsx5dIc9154HM+ZZWvjgI3bu5TLZWZmaoyDHpOow0Fnl4XFWfySycOPPkCahbRae/i+Q2OuhufUGPZjrl/fQNccLr97k5Jfp9mc5a233uDcPRdYXlmh0Wjw6quv0mg0qNVqhzb5U2dOc2vjNgD9fp8rV64wOztLmsb4tstPPfUxfM/hW8/8BX/1nb9kc+M64WTAxXOnuP/eiwiZEA6GGLmk22ox16jT2W8VUJlU8ublq1i2j+P6bG3v0e2NuH5rHUlROYFif7eFbfj0Dgb4js/CwgLlWpX+cEy720EzDISu886Vd9k/aNPp9/BrPl65RH8cIoTL7s4BnlfCsXQsW0fKgsQtBGy39mjON9nc3UaaYLnFZyaJUrRpLH2r1ULTNFaPrCFMi1zo5OhUak00zcJyXLr9YXHBez9Q9enxfqYPAvhd4Eqe57/xYz/6GvDL03//MvCnP3b7l6ZTiMeAwY9lRPyNh5SKOFIkCSipc9AdY1oeCwvL7O62iZKYazeuk+dF2Onu/h6GbuH7ZZaWllhbWyMIJighDmk8hUGpSFByXbf4z2oatm0jhI5hFHrxu1OIKEoOQ0+DoIiD31xfp9PpMD8/j2ma5KhDeXNh+FEICpvzYDBi0B8SJmmx5zMEQhfMLq+xevoSc8cvEeklMt0BwybPczp7ATo6jg1f+uUv8MQnnqK2NEupbBGMUlaOzjOKxlSqdV56+VVGk4DBsNhXVipVKpUSru+AlqMLKPse9VqFNJyQpTFJHHLm1EnGwxEl30fkMDszR55k3NnZZre1zySKaB3sF45I2+X69Tt8//tv88Jz2zz3vQ2+/51bXL86YditINQye1uCvR1B/0Bj2APbmIHcZjgeMZ50CKIOhpkhVchw1GO/tY2mCWYaFXb3tshlglI5SaxQUufGrW1KXhPLLLG+vs5g2Gdnp0j3yvO86KHoBdNQSkkYhty8eZNgHPLss89BLpiZmSEIAoLRmIWFBf7wD/6I/+Vf/k+MRwNqlTJKZoz6PfqDA5aWF9FzRaPqM98sKpLr124hE8XC3CIX772P/mBEmguu39zk5q07xHHGwvwiZ86cwnJM/ujf/D6VSonjJ45OCcqwslxwOdFyjp04iswzVo+sYFg6jZkZtnd3GYwDVo6sYZg2o0nA8vIqWq7R7QwYDcbkec5Bu8vc3HxByO72QQg2Nu/Q7fVRUiCzAlqzNL9Avd4oKOHDCTt7HSZpTnlmhoNOj25/yGgYsrq6RrvbY35l6X0vCu9n+/Ah4JeAt4UQb0xv+3XgXwJ/LIT4FWAT+MXpz74B/DRFuOwE+A//vifIgUGc0R6PEbaGpmfs7W1QrVZpNufpDgN008U0TU4eP0q71aHVamNYHlt3NugPXJSCYTDGsT3K5TpSSihr9Ab9Qz8CiKl89K+bgXGSIISObTuQ6ygpcUyb8XhEtVbG9zwsw+Di+Xt4443XitebCwzDZDQasVAusbfbIgpDkjChVq0QhgHzcwt84qMf5bXXXkPTAo6u1RgOPbr9AZPRBC3XeOHtF/nE00+R5yBExh//zh/x9NMf5/b6JrVGg93eDarlOUBj7fhpZJ7hlx2yJGfYHyDTCZ47yyQKcNwSg8EIx7RYXlzCsGwyJekOR/i+z82NTVzL5s7tDY6srlGZb7DdPuDE0WWsaolQ5uxvDnjp+X1GPZtYZtPQ2wTrWgspUyplH0NoKFkkK8/MNZDSZDCS3Hf/SYaDgLXjSwz7I6IkwrR8sjhHmAlhMGGmViedKA7ae5w+exShuWxtbtGcWabbHWDoEE563L6tOH7iGGfPnuWbf/F1Oq02J4+f4J133sa1bRzd4tID9/Piiy+zuHyEy1euU6o02draxvNCqtU6jz1yH2urC6wsz9Jt71AqV3n9tde456JguWYihGR+aZWf/fnPsX5rC10okiRla2cLoels3r5DpxOQSIvnfvgKTz7xCI1aiSRTVGsWdw726PQs7jl/ina7wzDooBmSC/ee4tbme6DlGJ7G2YtniYKMs2fPsDfs0Uzh2Mk13nj9ZQR1UDVUpqNrZbYP7nDP+Qv0eh0cV5AECcEgpCdHeEdKVGtzaLoiSUP293ZxnRKTUcze/gDXX0YzGoz6LcYHHeab8yghkJHO0twqlvX+yUt/76KQ5/lz/M19AoCP/Q33z4Fffd+voHgMmqYV04aksCbneV6AWtOUbr+H51iY06isyWRSdGHzGNu2ieO00Bi4paJPYBT5hGkW4boOURQRRdG0SiiES4ZhoFSx55JS/r++4iSabiHyolMchtTrtUP/Q5FUpdBNe2pcKeTR8wuzJFHEwmwT29T5yJNP8M477/DaG29x/4MPUKvVGIzGU++9w49+9CKPP/441bI7/VMo/rff+m0++9nPMh5PuH0zZHXVo1J1aO0d4HZdet0Bl+69l41b69y6sUl3MGJ5dYmDdp+lpQXiTLJ9Z5cknXDq1Cl6gz69fodGo0Frd48nP/4UW5ubVEsGpmiQJhm2VSJD59133qLb0jD1OjIdkVKMVgUWSSKxtRxsDSFcDg4kO60WSiUIPeHP/+Q1zp07wtGjJsdOniBWI6QKqDSWCMYDNCfn/D2nigQtr0a9WSaOcnKhuHjvOfb3Y6qVJmdOety8fXv6dzSoVCq0Wi0aMzUuXLhIpVLmT/7kT0mV5ODggBMnEp5++mm+/e1vk+eSYdTjzOlzBNEYpefc3NjglZde5vVXrxZlsWaz9JOXyFRCf9hjZmmNWrNM/2Cf7fY+w6Gg1b5DtV7h+eefYTKJ+PnPfZpHHn2Aq9evsNM74M0rb6G0CC23DrH3cRyzvd9ifmmOM2fvYb+9x0GnQ7U6Q6ni0kuHzNaqOIagO+jz0Q99iO5BGyTcvF0ZnQgAACAASURBVH6TWq1Cs9nkypUrOI5FnBSTgziJ6O928TyHa1evc9/9F4gineFwiNIVmi8o6SWaC2sMBj1qMzW67W06wwOU0mh1d5lfmCHLsr/7JPyx4wNBXspzMEyTYDJhMBggNA1NCJI0JYqL2LLROOH0yRna7fahuChOJZpRhLOaponQdbrdLrVpzJZSGbpuTmPoirBU27YIgjGaJkjTor9g2+7hqCcMQzKZFJLkLMOxfeQUZXW3J1EoHxUyKYi/ru2ioUjCEKEkvfYI2zb5r/7Lf4au68wvLrC9vUuuF32IJM3IcsUz3/wOzZk5/pP/+FcQ043c6dNn+fKXf4+f/4VP89jCfczNmmR5l89+9jM8883vcfTIOQQ6QRBw7Ohpzt5zmkRFvHf9Co5TRKotLi+RJhMmkzG+79KYbdAbdDl64ijrmxvFAhwHjAYjGqtHyCVIZTLqx8SRSZxH2I5OnuUYukE4SbAsi94w5L77znD9+vXClDYecfHiRc6fPcfbb73GresHvPnKW2j2mJlmBdPUcZxtHA8G/Tazc7eYX5hhttlgZr6GX9JYXFxmfXMd15rn1s07nD13EkPXioDWqajsyJEj5KrQOWxtbbG2tjbF0q1N0WvdgmzlOAyjiLfffZ3ZZoP3brzLeDggjVL8koUhDFqtFju7+yzMVtDNQmvS7ffYa7XJU40wMHnr7dexPMG999/LbGOWn/iJxwmTiIsX7+PspUvc+e1b5LrHztYG8/OztFptarUm880VOgddbNsDaVEqlbizvsvywhq1Up0sjehst1heWOStV99gcX6BMAy5cM9Fup0huuFT8xrYjsHN9Ws0ZmrYmsmDDzyASlLOnryHg70ubtkmlQorV3QHfVbXjpLFEVquWFiYo72/Rcmrcuv6LU4eP0ajUmH99q33fT5+IBYFACF0Dg6607IepMwQQkxL2KwATmganudRLlVptdrU6zP0BkPmZheYTCbstorWheNayDyjVqtgmG6RORgESCmxrIKPoGnalKJkAhqVSpU0kT/WdCy2GHfn+1JKkqQIkb2bkI2m02q1qNdqCJkRBhOWFuY4cuY0V69eBVOn3miwvLrK7dubbO/uECfZtPkZAoK33nqH3d02tXqZil+UeI8//jhf/t2v8C/+x3/GxUuPsdPq8ud//jWWF08xP7dKmg6YXWxQ9xYYjQZgKNbWVnj2h9/j+InC1SeTIqLcdV06/Q6+52HbNmEc0mg02N3YwrMr2IZHGAeoLOL+B8/y53fegXzAONbQKLZYhmExGkecu3CevYMug8mYYNzjyJGjfPwTT7G1sVmoSYMxOTkLc5d4/LGf5PiJo7z66ku8+tqL9Po2g4FOryc4qIb85Te/Sr3ms7J8jFs39jl/rsnZs6dJ4oRPfvKTXLlyBVM3+PznP89Xv/pVzp46yXA4nIqWiqbu3t4eCwtFg/mTT/8UX/7ylylZFsNxipAZvulx6vwZjqytFRoBDFr7Gzz0yMPIJKZWq3DlnWtsbbT4wQ9fJ44k8TjG83U+/uEPY9s2J46d5NXX3kbJlIceeoA4UpTdJuOgzWLjOJPhiGNLF0iSjCvvXMEve0Q26Hjs7nVJY51ATxkPeszM1KnoCwz3M1Ybp7GERbVuMh6O6eyOadRLmKbNfrtNPADlTE11xGiagaMnrN/cIlMpDz36IL1BH0+U2b3d4tjqKa7fuIptCBYWVtA1k5MnDGq+RzwMKLn++z4XPxCLQpHqQ0ErCiY4tjU16GTT0Z/AdWyU5DC7YWlpkdFkQqnkcfXqVZrN5qFMOYoKmOh4Kk+uTmPh7155XNfFsoqVXIgcpQpnZBTF0yt5ipQFMMUy/Wl0vQ25QNO16RYCNHLSOESlHlkaYxjF1W2v0+bE6TMYjs14PGZ9Y5PhaIjKi12YbpnU63UG/RFxHNNut/FLhdTWtgqR1Sc/+dOcP3+C//k3/gu8qsviYuEIrDfKtFodsizizv4dTpw8gu1oXLtxhYceuJfesE+tVubFF1/hku+zv7+P7/sMugO2hhssLi4y6A3w7DI6JlfefpePf/xj/P7v/z733vsYx09abG2NGI0MQGAaNlmSousGtg71xSY3b1yBNOOxhx9hdXmFb337GVKVEqUTGrU6j/7E4ziuR28w4rU33iaYKFbWzvPkk08i0PnLr3+NlZVHMEzJ5Xdu4dou3d4BZ86c5ZUXX+KHz3+PL37xi7z++uvk13MefvhhhMoBjU6ng+MaLCwtYts2e3s7fOixx9F1wezsDMN+wIXTZ7nv/gs4rs78bA3HNdA0CEZjaqeOEMYZJbdMo77IjSvf5S+feZat1gDHLbM463L+3lMoNEqVBn/xF9+hezDA1AWt1pBX3rxKc2YGS5ikacTq3BmCYEKt6tK4tHQ4zVIo5m3QhMA2TCIrJpYKU3PQhCAjwbEsZJ6imRUunT2CY3qMxgMWaqsEc2N0QzAajfBLJYLRBCPRON48RyJDxrspWaTje2Wavkf/zoDVxipqlHNw0EXTDAzDYmZ5kcm4z+2N/b/1/Pv/Hh+IRQEhSJVECXA8Z9oniJFZjiYK1WCSRIxGI2zHpNPpUKvm7LfbJKnk2PEjhzmOUVT0A3TNRMoc2ynKSqUyhsP+dBHIsO0SrusghGAyibCsYtG5O6rM82JcGYYhKytLh3syKYtQWKEZWJZFuTZLMBwhswTPc5BCYxJlDDa3UHl+KLBBEwXL37EPKw9d16nX66yurhaBqXrRX7nrp5ifW+a3/tff49f/m19l985NdKOAw3Y67QL/rgy2trcQZKAErf19TMui0zrg5InTGJZDvT6DqRvMzTSZhGO2trZozMyQOpKZxgLvvfse3/3Wt/nMz36Cl155k1/6pZ/llVc3+OGzG+xvH6DJFKEABH4es7++jYtEmWVqbo0769ssNVe5dmUdQ/N58qlPcObsUSy7yOIURogwEx57/H6OHV/jO9/+Lp/82c8y6nX5zne/wcL8IrmKGQx6fOuZb1Cr1fjoRz/KN77xDX76p3+a7e1tlFKkKqVSa7B/0CaOCrpVs9kkSRLWb9/CMszCKVueIYsTOq0295w/Ra1SJU4C4jAiiSJqjSbff/Z5HMum7Jg0KmXC8YBjR44yiiVSTpC5xs52m5deeoftrV32dzocWZul3W3zE85PMldrYFKi7NXo7ndxHJdgnOE5HkhJKgtWJCoHBOMkwbUtslwQDSVJHBcityjB1DVsw8EQBqQCPTFRaU5Jr7K332J+foUkSWh6VRxhoEoFdyGKJ1AWuF5x4an6TSZJgGUqSsRIqVDo3HpvhzSb4LsL/IOlTv//cQjBoSEpjuPDhmCpVGI4HJFnBdJ9d3eX5ZVFXNdlc3OT/mgEQnDixAmGw5zd3WJm7jjeX6vMpn6GcrlMkiQAh2lEhmEcotWKq3+hsbr73bIsSn6NXq/Hsv/XSm1N13Fdh1KpgsiLk92rVKamKYc4y8jzQmVo2jaGZRUN0ihCyRzLMorou1KJxcVFDEPD0EHlGRqCYkoisR0fcpt/8d/9n/zlt/6Yf/enX+FHP/oR588XvEdl5NRnZxl1usw2ZgnDQmBlmQ7N5WKEJ6MEFSWEo5DRaEStVGPr5galaoVkkpNLmKnPsb5+mwcffJCNjR3uv3ie6MAiWluGOGXc7ZNECTdfe5FBLNGBpdU1OvubDIY9JsMBWVzoO5ozC5TcMjdvXuOll14ijWKeevKjJGnAK68+T7XmoRsJl69d5v4HHmF1ZY53336FUsliMhojhKBerfLIQw/xta99jQ9/+MPcvn2bLMs4fvw4P/mhj/C973+bo0eP8urLr1D2PSzLor1fTEha/X22t+6gtBTHt+n0e7RaLe7cucP+XhuylETlnD55lPMnllhsVnn6qQf5028/z9HT97E0d5JbNza4vbkxxdZreGWTLJ+wvLLEkeUV+u0OuqY4GAc0Z2ZA6ugyJwyLShM0dF3DtAySqdxe1wSGyqjUqoU3JpOkOejkmEIjHo9xnQoWGrpZsCSa5RkMZeC6PirLMYUiShRJmKILiyROGIUhhmFDZlCzG+RJiJHqxKkikBlrJ87yhS99kXb7gN/433/4vs7HD8SioAmNZr3JQbeL55YwdItJGqEJMHSTPJdTtr9Du9MjiYv9pG6ZlCplBBLXsXBtkyTJsKwiYSfp96fThBDT0qmUiy1FZW6OcRAc5gUYhkWecyhfvttHAEEqFVqmKPs+oBDCAF1H0zQ0kRNMJyV3/RTDYEyuwHXLZFkMQsNyHLJp1VGwCAWeV5SKpZJHreYjyNGEhsozclX0O6JRjOO75JnG0x/7RS5dupd//l//p0hZhKbOLjbxbIPMDTl7zwV2dnbZ2dmjWq1hmw69cY9mtU6oBXzrmW/y0Q9/GNf3MQ0bbI1mbZ4kybhzZ5NSqcZolNOcO8ZX/82fcenYY9ilGr7Q0JczyFLiJKLXHyAFbPW7XH7pu/SCmPmVo6wu1uj1hzz7V8+Qpx9jOByTBBlJqCg5ZUaTgNm5BcIoYxz2KVUtLly6wGjQ4b1rtyj7Bo1KmVqlynPPPcfRo0f5mU99ij/7+tf5zGc+w8svv8ze3j6a1sKyLN57773DbWARchugCw3Xs7BcgzcvX+W9m9dxHId46n2JJjG+pXHkxHFGwyEl/xi2HvOhR+/hnRs32GltEowjrl+/RpIqjq7Mce7sce45d5yllTqojNPHT/PaSy9iCA3bshj0R9M+lI1uWghNQ6UpSRIRymJbLDIFnoPMU/JcIrMEjZxqxSMcj7EMg24wwtDtIsA3CKiXK0iVMx5PkGaxxTZ9C8e2MHRzqqwdo5SaqnQN5EQSRwkiB8OwWJiZ52C3y+/+9leIwvdPc/5ARNEbupYfW12m1x9i2y65Ekhkkec3GZGjFaW3bpDJBJUpbEunUi6jaYK15RVM06I3CFC5jhJFGIduauimRi4VO7t3aO+38DyPXn/M4uIySSqn1UnBVrgrgonjmCiekGSKyswijbKNriKuXb9WnNB+Fc910Q2DSKbIOCKXCsdxEEIHoSEV6AYoChSaoqgoNAS6KEadJ8/cy//1x3/I0kJ9OvNV03dEQ6YgJ2N2d7cxHZtKrY4wDVxf5+33XuR/+O9/nTjY4+zpRdyKwUG/R6lap+z6XH7zLZr1Bo7j0Gq1OHr0OK5rU61WefGVlzl27BjDfofV1VmCYUie1xGqTmt3jOXMIqWJnAQs1ur4UlIzIRy1yeKYwWhSVDlllyhNsX2PSZaxsb1DmCWYlsPNnQ6aYRJFEUqBX61Rqtax/QqlWp36TIXddpdKrXiN2xu3uPL6qzTKhdOzF8WYpkmlUuHo6hr9fp+DgwMeeOAB+v0+k3DI3t4ehmFw/tw5eu0DDlptfNdm0OtjOTYffvIJ9tt7vPTSS/iex/0XLvDoI49gMGZt7TS1qs+PvvcnTA5u4Toltg4Ev/WVZ1CuiaUJfvGzn+SzP/MRmjMuUqUIbGyvzrX3drj86psIJTAdG900UFmKkKpoksPUSFdUvEwvGIZhoBsGtm0z6PeB/LBC1RDEaUQuFL7nkcQBuoJM5XilCr3eoDAAJpOCAia0Q9APstiKaqL4nE3CEMN2qNZq9EdjdMMgTjMMTfCf/avfeV9R9B+ISgEh6I9HmI7NJIww7cLJqJsGmq6jlIYQxX7eNGxSYurNWbRpetRwHKKbkgyB63pkStLp9qk16mgqJQ4nyKyIsO/3x1SrVfb29qhUq+R5wVgUaIf6hYKwJLAMDd/SwDCplKvo169xfLFKqVRlszVGahaOaRNJBVpOJnOErtANA8M2C++EbiClIs8VmSryDws3n8MTH3uSarVKlilMYzqTzHNUrhA6CFuy2d7EcSr85v/xu9hOlVLZ46C3wyc/9Y/ZXv8hm7ffpJwbeJ6HyjKkynjyySd47q+eo5MVJKFypcaN9VuMgpTlxeNcv77Jh37yAp3eHSahTtBJaW/dZnX1CE5mokmb+qxNzSthyJwoGKP7Mxh10OezQsKdm5BLZJ5hxzFibpZypcTu7i5nP/QQnW6hTIyzlEyGpL0JYX+X1rUQvzELposWhXiLC5hIVlcWcU2Nd69cJjccVJqhV6q8/PLLfOITn+Dhhx/m8uXL+L6P781x7b0bnD13mpdeepkzJ04gpeSg3WU07LOyskS30+aec+e479JFTEOn7Foc7O3iO4J+v8WR1XPoeYqtKyq+wYNLx6nYzzCztsRTH/kwH/3Jhzm6No+ux4wnAbZToVxpMNsstBuu4aDyvPisZLKoUhyfJEsP8XxFChVIBXmmULkkjseQa+RIpFTMzc0xGgzRNB2ZK+JIoucOuqGh4gRTs/GsAoZruoXT0fc9PM8riGC2hTAFutBAN3HMwuOS5joy18gSyXAYFHF77/P4QCwKeZ4jFSBzDNsBIdB0k0QmeKUyWVLotovQTRMHH003icOo8EMEMUIruuWWM8I0TQD6wxGubZCru9WQhmkWGYKW5TCZTPC8EpZlI7Oc8Xh8GOhSNBwFcTgi1w38pQVmShZnl2ps7bZIEwFOFRuwbWe6lwSZ58hckeUZQjeJpcQ1jak1WyfNFJrpsLi6xq/92q/huBrI4spimQUHUmWSVCY896Pn+fM/+zrd/gTLqLK3f4coSSlXPPq9gEZJ4/77HkMzxjzzV1/n5LkzrCwu8fyz36dWqeK6LrouGA77NBoNbt5ap1qto5TGdnsfq+JwsD0haKecPn0fcdoliTocnTuGVxLkMkMzbexSjTBNEJaGbiRUTBMVFO+pgULPMprLRYjrkfIcYTBktlplcWYGzRAIQ+eg02Nja5eKYzOYhETjiL3RGFtA2bJZvXCBP/ijrzA3N0elUqPT6ZCrDNex+OZffJ0vfPGLPPTQA7z88suUXY/lpSU2b28QBmM2NjboHrTxbQdLV5haTnt3B9d1effdd8hlws7WTe6/9wIP3neeC5cuILOQ7c2bLNctVBqRJUN+7jM/gT97nKeeeIJqyWY4HGCaGa7vEU/l61euXEGlGRkZuYQ4S3Etk3E4IYpTTNMuRsJ5fqh/UVLD0A0MUyvG2bqGTiHEa+0fYOg6jusyGE4olStEkxChG9SaDUbDgAwdExMlFbouiOPksPHd7fVoNBqkOcg4mm4dpgChtFigHNMgnfbT3s/xgVgUlMoJwknxhuoWksL9ZmpFCVqr1VCSQ0WhZRXk4CSTTOIMwxAYRvFmJFlGKov76GjkuSCKEkaj4FB5BpBlCQh9CmY1EBQ8Bdd12d3dRUqJEDqNeoVxGDPpHTBXsbBVDNGEJNHJ0ww7LxardDpNQOTI6R/DMDVGYYBmusgkxC9XCaOQI8dO8av/9D/H9Yty09AFmjARQiOOJ4XvYmubty+vs9ceMR4H9Hv7VMtzeLaDbeh0DzrEwyGj/pB7H1zhzJkzGLbN7u4u4STGtyWOa5JmEQf9Hlvb29x78T5uXFvHsXTM2MbIy9QcnxPHjjPsdHFLEcfXyjhxC5Eb6KZOtz3Ec+pUNY80TMBKkWFCrTZPlGSMggn1WoMwliijGPNmqSrYA1lCp9ctPtCaxclTZ+n0+lQmMYPxmETlrF+5QiwznLLPo498iFvrN3jnzbeZmWmAVOgIHMfhxvXrPPDgg5w+dQrfcWk2G7xz+W3uu3iW3c1NfKOOTDNIU0xSrl+5zNqRYywuL1F2bR66/zxnjh1FqQjIMS3B/PwshgpoVGuIsstHPvIwV9d7fPdb3+DEyeMsLzZozJTo7+6ysnoSANd2YBqSm2vFlCiJY1zLZjQJgSIPpFQqoSQYukWsKZKpMM6yLBCKLFOUShWCYDQF9Bikec4kztAth5Scdn/EeDzEcRxsw0JLZBG4HEss18azTEpOnSgKiwthloEQBMMhoaZRLRU5oFXXJC+57/t8/EAsCtp0XKdPG3iZVERRVHAKLIvxaIIQAsdzicIIzTAwDJMkk1iOj44oSEa2NU1y0pC5mEqaU+KogJDEYYSUxTaiOOmZyp8dTLMwKRXZDjolu4Tve3Q6Hcq+hycDlubrqKgAeei6xjgYUq4WpKYsyciSBCkzLFNHz3P0LGS+bOCaCsPUUWrITKNO1clZni0TJwm5YZLlOa6pgcrRctARhMGE1159l+07Lfq9DrPNRXRdsrw8SyYnbG0c0B7t0Gq9ycqxT9NoNEhkxmgw5sKFS+RZwng8xPZN5uZrHDm+wv5ui1MnVonDjI3nrvHMS1v8ws98lFde+Rr1Spn1/as4j57C6nWg7NMftPH9Em9sdKm5CwgFrq/hVx12cgPPr+KWy4hskbLl4hoaZdvGq5ULrQc5s/UaUlDst4VgdvYUhi4IxwHd/pgkk4yjiJtbWwzabcLhmLXlRZZXVnBdF6UyGq5LrVYhS2OWlpYI+kNWlpcwdYVKJljLTXx7HhlHHFldoH3QQwqwbZMPXfowjmPhmYKDvTtcu3KVSRKz+Kkn6Q2GzJccxpHE9SS2Z5MkMR//xNPkuWJ2toLKQybhmOeefZaL9z7CZDRG13VkkiLMYtvW73WIZY7vuOQip16vMh5PSFKJJC8wbUphiALeqqNNhXGFv0RmGUkSkStJGMlDBJ1mCBozNWQSM+p3qVgGWVz0J8LhBKkUvu+jkphJOGFxYaHoZWiFkazfLQjOruUjbPN9n48fiEVBqRyV5URyGhOfFXNeiUSIHBOrGBNOXY4yF1imBWToOiThBNcrTurRaDCdQNjEuoVpFQvNJEgIxgXh+W6DByGmPgpJyS/KOdd1i6aOTEiVJE4yjs4IGlqAmIwQus7BOCNOAdMijiMMikkF5JiawBY5eq7wCTi5uMDK/AyD9h5C1xnHIfVSyvrr3+P4uZPUqzXKrg1AGIbEYcBkMuby5cu89MILHDm6yBBJMO6gsoi97Rt0ujsYuiCe9LBtyFVCHMXYfonZRpnWdgvTAmGYJDJjpt7koNfF910MqaGZBktmAzPc4s7VPfJBh9psFT0V9O7scE9D49bGbY4cn0USkVUhGLbpdyKadY90UIxeW8FVNNNixyoMaVGc4rglMsMlUTmW59JYmme/06Uxt8DNm+vYlo9T9snCGE3T0YSFZ7mcnK0RKkUy6DKIYl55+WWCEGwL/LJLd9AnCAIef/xx1tbW2Nq8SaXk8s7rb3DmxAoqGpPIBOIBx9bmORiMWb99i9nlI4wmCWk05vqVd7GQPPHkU4RRTL25iIpDstwikoI0SRC6zo2b61SqJSxbQ2gJjWaTmze2+MM/+AqN6hF818MQBpM4QkMwPztHt9UmyxJqM42pt8UiUzlxNC3hXRchi89znhfKWSkLXLuYVpuWKKZerm6RZTGOZZClIb5lMONVyabu3DgtEsFt20UzHLxSjVxK9luFxD9OIkplG6EbmJZFqnKiYf99n48fiEUBir6C7xVU4XzawHHMQmeQZikKyMZjXMfHdGzSTBXkFiEOo76FUJiGges4RQaEYaGbGmEwwXEcxqNB4alIkmK1zzKkyAtzk2aST8VGvu8TTDLiKKHSaOAaKTOORr0xz8bBiCSnkDmrlDSFVElMTUdlEkNI4liytLjAWtni/pNNtCTgxIkZlFK0+xNyM+LNH3yDS5/8uSLiPfZpVMoFpce2GY+HXLrvIseOLrCzu05rfxfHLhUR6KMxiozZ2Rrj0YDP/dx9DId9Mi2ibtmYhl9oK4YHHD91jN3WFhtb2+zv73Ns9SiO0HnrjbeoRyUiAe/cvkNjEmB39xjlJtIp0R7uUC6v0g9ClAnu7Dzr+/u0x+DMlTHzmLLUEcrGyHVUGJNnKY7KkWGA4xhYukClGjFdbJlRzgzcuEV/b0zXclAS8gQsyyaMJWGmELZLzXZYOXGCc0qx127R7hxQn2lgGAYvvPAjTp48yc7GFlE0pOzpHD+yzM0rb3NkcZaKLVDpmLffuMX84ml+5w++yfdfeJN7L93PlXffJAoG/JNf+jyXr1zl6pU3WKyUSMYhw3YfWwncps3RkydQmWBpZY04GlEuF/CdRx9+iI98+Eme+cYLDFtdhC7wfb9w2aIxOzvLYDSg1+tOq9gQTTfJspQoybFkRsmxCz+OmPI3ZOHedW0HU9eIB8MCHZ/EBRfD0Mkk1EoOlm6wtRfglyrkQqdcnSFJUpJUMgkVcRhSrpQYT2KCSYIUA/JcIwhjfN9HM94/T+EDsSgIQdFkyxWaISApzExJUsBUDV3H0i0yJZEqxTM90jRGoBAodNsgml7lpQQk2I5GGE/wDYecAn6So5FJ0HRjKjkuEpazNEFoCiUlmm4TJyG2bWMJgaun6Gmfxfo8KstIVEYOCJGjyRhTCVwTVDrm6NIc4WCfesmh4Y95/Ow8tuhSnnFI0wlhlGIwIU9yPGVjpzHReETZK5HrApUookmIZXnkqs/cXJONjXWSRCBlhGGZKDLWVhaJoohjR5aZX1rh6JE6t7euIWLFd7/3TZ584mOMxxCPI0pWhcGkxfysDyqkMXeCILhFffEoX/rSQ9Q9j+Wyh4ZgFEyo+AaunjLpR1iOySRLcLwKy5csdM0mSyJcy0CNR/T7fYLhiOGozySK0A2DPFckKkXoGp1el2SYk+sOu9cHZLJB7tVwTJdOp0OWpCRBWPAucwORgNAFUuhs7Gxz8/Y6SaoYhinj4Qjfdem2+7z25ss0ay41T+f0sWVsz2K7tcNMtQJCUmnM0Jyb5+c+9ylefPUy169dxTIMjpw6zcJ8g1dfeZF/9IXP8/X/+99iqRzfKzHsdAijALcWsN9VSM1ibqEMkxGzlTIi02htDalVZ+ls7uK6YErIVIZrlen3h1TcCi+/+AIXLp6n6peJkxTHtXD9MoNhgCYjVBrg2A65lIg0wTZ0cjVEomPmOoNOj34wYm5hllE8olKpMOgMmUQJul8iyaBWqzAaT0hkRpCmlKsetmXQCwJQEst1SLIM37XxjWKq5vmV930+0QLSXAAAIABJREFUfiAWBcuyePTRR7l58yYHnR5xHKFycdhjAEiyGCF0pMzQhUBOrdbAIV05SQoUmuM4h8KkSTA+hLLeJTffDY4tNBqKLE2RMp32FRSmaaFUThxOyMMJ/pJFnEymjEMd17Mwk4SSbTBXNfFtnYpfp+rlrJ4+g57F6HqGivq4VQ9NJehCEsUBlmEQZimWabF98wYrJ88U+ossR0lJGEfEqeSNN9/m6JFVNm7f4rHHHmNvb4/W/i5PP/VR3rv6Lv1OF9fxKJfqlMsVVpZWmIQBJ48fYxz0KNdchqMDVo+s0RA+3V4L16jyzW/8gGZjFdNxaZRdXKETJwqZJehCI1UmB70xulR4pkWcmYx6KZajYepgGCZZDKbTwJ0to1VinCm2TmgaSsBoNMLzPI4IjVhKTMvBMCzSROK7PqkQ2K7FwUGbRCbkuUDlcPv2Jrbn8+xrL/He9XUMy0QzcjTLQeUBuTD4d3/6ZzTqNo6uOHP0HMLwCGINcpfN9pjVhQoKjZ2dHWq1Jl/44ufpHHRpt3Y5c/IIVy+/y+e/8PMYusV4EtLZ3qBccolVSK1RpXMwoNQ4zuU33uK1pMvnf+EJ0jREKo1rN67jkGMnbUylwSSnUiqRDfvcd/wkGzt3ePpjDxTJ4RWLfn9SJEnJLosNmxyPdmuMyBWkknA4xqqWqZVrdDo9PMuhXK2gOwZC16iUywRBSBwm1BtNJklCnEjarQ6u7+H5Dl6lgNDEcUyp5JFLhaEXk6MoiohzsB2Twb8HzfnvXRSEEKvA7wMLFOqa38nz/DeFEP8t8B8B7eldfz3P829MH/PPgV8BJPBP8zx/5u96jjTNeP7554mnkWsAmsj/ml9Q/M6pb6EQa9yNf9c0DSG0Q/OUpmlFBPeP6Q3uPkYIgaYX1CXP8xiNRtNXoDGZRJTLhbZgNBoUYFaVsTLjUao2GUZDLNchD1PKlolesTA1yalZk5LvUPctNGIq+ogsCaj6Lp5loOKYXLOYTAIMTSeCQ1bEztZt7n/4UdIsoWK4jGVGrgn6wwFhFNA5aPHwww9y8+Y6d7Y2kGnGCy+8QByM8d0Svd6IT3/607zx9neLPIdc4Zd9KpUKmgVJFhLKEXu7XSrePNevdPCcBbRc59TaCuFoTM336bUPsAwTmeeEcdGMzSTIICZKUwzLQ8aSBIWmJ3i2zzhOEUJg6D4YMAxD0MG0LEIckkQrbO1Y2LgIqZFrgm5ngjQEKghxnBKjYMIkCmk255g5VabkepwejQijlO5wwPzSIhubd4gyRdQfUa96zOHT74157kevMOh3QGWUSx5zc00qtXnm5+fxaku8+PoNqo2MM6dPsLbapFHxeeDcCb7/vR/yH/yjL3Lj5joqmqA00F1wq1XivTFyEmGrlPsuXUQlMdd31jl19n6UlREc7FHxJPPVEus3bzIeCoIw4errLzKzusJb7T163TY//7nPEg9bNGbnyAYB8TilMXsaVZsjmoxJkpT5uRWUUnR7E2yvSqogUwLD9jBtm0mSEqdF5dPudvGrNWQS4bgeURgglUIJ0Ay92Ia4fpFjMpmQCw3L8QiCADPXMafp6f8giwJ/e+4DwL/O8/xf/fidhRD3AF8EzgNLwLeFEKfz/G+HxGmahmHa5GjTE75YBHJVBJ4IoZFTTBN83yfPFXledLSllJimQRiGh9XC3SlCEAR4tkGaxocGJM/3MQyr6O6aBmQCTS+2Dnd/R5qmhV1bF4UiDZ1+lKDGYxyrymKzzP7ukIVahZMLNppQzNQskBlkMUZZx3EgS2KCLKXTiwv9hWEiZSGdHkcJSThkEozQpMZwNGZprkn7YJ3NOxskWYhj6WhKMttssDj7GD/4wQ84aLWZn50hVzm/+Rv/muXlZX73916lMe8x2yxw74N+F6/p0R216d3uc+H0Y3z7z96CuMKpYycJRgfEgwG1Upm97Q2qpVqBwTd0cjQM0wAjxzQsLL9KmimCIKBcLhfyaykJ0xTbMEmlYjKJELqGZVjstjvotodru0ghSKTC0C2yVAEamuORpxmGEvRaQ8IowfY8gmGKbfv0OyP0HDr7bSzH4vaNG4UORRSEriSWoJsYpo5h6SwfqeBZBmkc0Gg0aB/0SROB3ctYnJ8lCgN63ZxaxaVeL7N5c53F5TVu3NokjhTbm/sMghi3WqI6b5LbZcI0JY5Tugc9jq7UOHP6HkzP41Of+ywMJnz1d77MRidi5uh5VC6wxyErp0qgmaysXUDIhHgML794Fcu4iUJw4fxFgvGYOEiwLQuRFRcw3bAwp4I7LRdoFBezem2GKInxfdjZ26dSrSGTFMsyGI0LmK/jTD+rUhInKck4wLIsNASO5wGQZjkSrRhX/kMtClO+4l2U+0gIcTf34W87Pgt8Nc/zGFgXQtwAHgF+9Hc9TxAEhQx4Ohm4WyUcvg4K3YAQ+ZSp+NceBcPQphWDOPy6OxPOsuwwnOVuFXKXvW9ZFppeeBgiGSHTDLdSZXS3UzvlMSrDQlAmidqUbIUlU+YrLhXfwrIMkBGuqaNyjYlMmZ1rglLs9TuYtoOYzqVNw0DXQVc5nueQhEMsDfxqFd12abfbzMzMMAqKdKC432F/r42MI6I05eyZU8w1arx39V2ajVnqNZ/3rl1mbmkGx8sJohGmrtOcrdEadQrYqT/DlTdvUrMXEKLEqD2h2ayiKxj3BxjCJAiCaaqSS5plgMAyDaQqqNdSFROiMIywrUI7kqYxIRpC5ZRKJcI4LppoGmRhjNTNQvBk6AQqL7wHUUQYxjiahmXblHQLxzNwvRJBGJIDehox6XWpexbBZIItE9CLK1MqQWYJNza3efqnnsAyNaolC8/MsUTKTK3Me5ff4ubBbVq9y/w/1L1pjGXped/3e89+zt2XurVXdXVXd3X3zLBnhhxyuAxJkZRMEZIlxY4hS46kKPESw1+DAAkQ0BCCQHa8ybEkOJClwLFhwZAcU7IoUgtFSpyFnJmenp6t1+rq2uvu9559e/Ph3Koe0rI0iRVjfL50LbfuRd+q9znP83/+y0c+8RmqjTaNWpUbN17B99Z5fGuLaq3GhfUN3nlrm95A0j/pY1R9cq3N0moLNQPVNHGDGMOoInODPNGJYsHzL9xk8wPPcu+NW7iZjkSgVdtI3SQNMwaDMY1qhTiI+OjHv0Doe9y+e4/nX3yL19+5y1/6S99PrVwp0sryYnvmByGmUdgGGIaBril0jw9BVcgzKNkWhqoQiUIfYxgFCzeNYgxDJUtShKLM5P6COEkL5a9tkSQZmibIs/+fnJe+K/fh48DfEkL8BPAyRTcxpCgYL77rx05zH777uc5yH4rsBeXMIu20GCii8C04fYxuFG1SlmUoaoENnBaSU2fm0/ZJCDEzWU1J0/xstMjzggOhqioiyzEMjSiSKIr4jiKkqjqapmBWa9zZOeaZrRVMclLPR88ikhyGA5cHGKytzBFmxYqz2ZkHrVhSlhpNPC/AcMoomkacZiwsLXDSn5D5PmEw5t69W6xqJaRqYpsG3aNdhIRKqczG6ga24fDSS99iNBkzHY+RJHzw6Q8w12yxuFDnW6+/gGkpKHpCu95g1B8hlBxbNxgdjJlvnGP/nbustuap1ptUSxaqHjMZDCmXq5imjesHCFWcEbss28H3Jhimg2FopLnEsovuypu66IrALls06w0ODo4Igymt1hxhEqPnCrrmEAYxhpDkacJkMjnjhtimiVW2SbKMMIooVcrEmYduK4ynXVLfQ3pTFhybWJNIxWbqeYSJxLRKeElGLwp48403WFlcwFxp06xUePvmDWwVHn/sA3T7I6QxxjAMtre3ac0/w3Of/hRLywvkgY/jONy4cYNmrc7V9QXeevM2/ZOA5NXbfPVrUxaXSnz+85+ntbjMxEspVepcf+Ut3rr9JTaW11HQMVGZjKag6ShqSq1mEsuMgTeiVO0wt9hGJjGN+RaKY/O0Xeb7fjDh9ddf49VXX8UxC9xrbmGeDz3zTJHhoCu40xG2ZaABvhshhYpTrmDpCrGXECfFzUxXNdBybNMGXSIVURgKx0UnksvCuFhVdPI0w7Kd93zO/2NyH34B+BmKru5ngL8H/DT/H3IfdF2XMgehaGRJULwe+eyuD5Cf+RucjgGpFEhZCIhOuwBFKZBWwzDOXJaS0DsrFkmSkOU5hmGdgZS2ZSBJUTVBlhYdS6VcY+oW5hZdN+D4aEo47PG5py8R+T5uHIKEWAoGnop39yGdmsXF88sI3cQqVchkzniao9tFHJ7neXhBghnFmJbKU1tPMNJtNFPDKjlMJjHusMtkNEYhZ21pmbzWYnVljbu377L7cIfNSxeoVR0O9nbozDcYjg+4ffcGdiMFJWEw7qIqkOeCuWqbw9sDXvz2DT589VlsUUbJJeQRpmbgmWVyqSBzQbPVRlEUxsMRWV5Y2ylIFJETZzm6ahREL9+jZBe4S57LQj9SrYIszGWEppOlKcG4XwC7CuR5hmMIbNtiMplAHDKZJrNxUTIeFViIaSjI0GPaO0ILXebLBkmUIASIahuETiY0esMJZDHe0QnfvLPHRz/6BLXSJVbOXeaN16+j3t9mrj3P1pWrJJlkaWmF3YcHDMd9vv3ySzzz5JOMByf85F/+Meplm5/80b/AL/7iP+XpuQ6rFzd58eVv89qtfQyRMRicsL48z8SPWFpa5rHHr/G7X/oNMmzyNGVlaZnueIxUNXYP9rm4tclJdx9Exus3X6NaLVMuV5nrzDMcjgmCgAvnr/DUtQ8RByHf+PrXuPHqm9x++zatVoNKucSlzYssL28yGAww7CKcVjM0lDyl6phEaYKi60xcl3ajTeiHJEmC5dikM/uBNCmAdV1RC1vCLCMM/4w7hT8u90FKefyu7/8fwG/OPv1/nfsAzHgGj+rJ6cdCiLOKcup5kL2LMqrOhCff3WXoetFiJd/1fIZhnPEgDMNgMhmRJBFQHJACtyjjeT5xKtFqFZQsxrR1du7v8sTGPHONKuMk5WSSctIbk4gMUhdd2+XS5jqWk3LS67H94BhFMSiV7IJUlYQcnJzw8ec+gUKxftU0hXfeeQc3yGk4DpOJS+iO8Uo2h9t7jCcTFjodnnzySXZ3t3nt+n2e/fCT3L71FtdfbRQkFT2hVC8TuAHB1KdaqbBUWeCP9l/lY9e+h2QKIo8olzXcqUc0MTHsckGgyRPyHILAw3JskDlpHFGtOQRhim3qJHFCnGcoMCvOGbpdQtGKO5KUoFs2QlEJ4iIvQ9M0kjxDMXUM08T3febazUIkhIbnhgSejyIlJcfE7w7RSVmp1rCaJcbDHo4h6LTnSLKUNFc47o25urJM2TIZhSmriyW++cJN7u/s8/0/8HnM5hqKBsfdHvuHA+JcZXF5jWc+/CxPNT/IJz/9aQLP4+K5VS6tLpCEY/7Pf/aP+Oxzz7J7fMjGvMOeYdK4tspyq065WSXNE3IBc/NznAxGXLn2IV775svU7Qr7oymqWeLNO3c4Pury5jt3+OTHn8Vzp6wsbmCaOnkOhl4hSVxU4SBUQRIrlEsNvu97v8DHP+YRxQFvvH6DZs1CxCG/9As/T7lc4sLmJZbX1ik5NqqmEOeQCc4cwsaui6Ea6JrNxPWRAnRVw3EKuz9VKfAhIQSK+WcoiPoP5T4IIRbflefwI8Abs4+/BPxLIcTfpwAaLwLf+pNeQwKaaZDFCXLmxSjzgvmFlKiKgqoIdFUhS4u5FKGiK3ahd4hjQAEFcmLIJZahk6cpaRrPDFwLUlSeJTPXZkmmgGXZOE4R9RYEAWHkY1o6IAvb70GfhhLjxBE/9IVPk/vHDMcjojhECaeEXspJAI0K2HbGcS9gKmv829+7yziEVrOOgodpmZBKFueqPP/K21w8v0rnyjqOLmm327zy+gM81cR1Uyp2hQf37zDuD6jUy7x1/S0OD0747Oc+zX/xX36e4eQeqmJSrZ4gkhA/T+j1PHTNgayMCCrceP5tHu88hubFmKoBqkGeQKlUI0slXpbMHKFUElmY57pBMT5Uyg6qZgIuUZggJdiOc+aEHUQpiiExDOfM4k7MZlbL0FENB9txsKTE86Zoik4cJpiaCZmkUatgKhpas47MU0SWULUF3niIJhJ68ZSqqZGmEMcxu4dHlOsNFDK8SY9Oo0J60mfUP2G9ZOINx9x48WU2L29hlhWO7z+gWanS29nhU5/8DFESsn/k4k4mxVikJrz8wtd54gNPs/fGLV79w2/RalZ46xtfZ96yGKChZ+DYNrZjYhoaD+5v4/kRG+e28JKEqqNjKoI8lxjA937vJ/F7J2gkVOp1BoMBmlpHVXX2d/cKDwSrOKxhFhFFhbcGmo6O5DOf+yy+N6Lf7/PhTzyHOxxzfHTEWzffAHJajTqOrnBpa4vltRVSBOgKbjwlVzWcGX6mqTlCpghFIoWCqllYtkZvOHiPJeE9+CkIIT4B/CFwk0eC//8R+MvAk7Mz/QD466dFQgjxP1GMEinFuPHlP/E1FEXadqmIcE+SM4356ctpqnrWMeh6AXTZdgXdsB5tIaQkzQujE1UR2JpB4LtMvQnwyEb+TM0423Koqn4WGXc6U586M0kpqddKrNYcVpycjh2zulBCtx3aKxuUG/McDHy605DD3R2S0SGGSPAyhVu7AwaRTbnW4fD4hCSKKVs6OjGkOVULPvbJD/P0xz6FWZ/DS4qZ3h8P8cddUt9HUQw+8dwH0VVJv98nlyl2SSK0IaPpHn2vV7TlrouhW6SuIOnGGLFBy5jDsapFEKtVJkwzdLNwgMqQxLlJmua4XkC91cQ0HAzLJEkKwljFerTmdX0P3/fp9/uYhk271aLdbpPPouLTXKJohf2aYVhoQiFLctIsJgg8MlmMfc1GGykFulZ0bpqmkcYBjqkRuhPS2Gd4csjw4S3KdpGx2JzrsHdywvrGefYfPCwoxK0G04lPvT3H/Yf79F2XXNeIs8LdWOaCRq3C+uZ5fvJv/Deg5Az6x+hSEocB9XaZ+fYcxw9O+Be/8MvoUlBvFAWgZtVwFcEgz3j8mSe49uRlSpbF0dExv/PV3+On/uu/Stms8taNt7l76wGmbgGC0POpOhbD/oDOfHtmxZZjOxZkhepWqiZhlBQq2CTBMDVUcYqlpYg8QleKpDKZ5Ri6ikKBeyVxxGR0gu+6HB8dcHR0gqRQE0/9iEq5SrVeZeP8Mnmes7RyjiSVeF6AooFZqvBTf+cX35OfwvvCZEUIRZqWjaYr+L5faMMBZriCOgtQVTWteDMNg1KphqLqZFkhComShDQrciM0oWAZJlEY4gUuSRKdmcOegpKF1r0wA4VirDBNkyAIzr5XuEmr6HHMetNitWXwAz/wac5d2qSztoldbhGkOcNpSPdwj9vXn6e7t02Q5OweD3l926WzvEkQp6QJjMdDEt+FNEIVKRdXWqxurtNanOdk0MewDOaaVTaWlymbNmmiIJQplZrCaNij0Wih6TlhPGDkdUkNDSGKO1oyDqlkFfbffEhNrWCZdZAqmQQpVPwoIheweWmTheUl3nx9m8FoiK6bmJaDF8SMJlNyFCzLYmmhhQBct3j/hBBYeoHVCPIzp2c/iOj1B3QWl/CDCMcp0yiVCnGXJsgpsB03COkPCv6IOxqytbU1cyFKkElIGvkIUtzeMaXUY3f7ASW7MHBZObfBcfcEUy3utMOgyFpQhMbBSZfNy1fZOzrGj2IO+kMUVQNd5fwTl/kr/+1/xfbDe+ikjI+P0BSV/d4+W1tXWJ3f4NXnb3LztZt40ZRKpYQjDDLb4cb2Hf7a3/ppFjsVxr0jeiddLly4QKXaZDh2ubT1OAe7fV78gxexFRM1F2Qz7kyWxBi6QOYJKhLb0kjSiCjVcEpl0rS4+SmKRrPZpNfrFRuELMEwCul1kmSoSIRCsRpXIclCqk6J0PNo1xtMhiMGgwHj0QR3OsJxNMoVg1evX6c/8IlCmF9qsbDYoVSr8zO/8cJ/RiYrzLQOtoMqlBlGUGjQ1VkADBR3d02frSzJyNOifcuyjDxNyJII2zDOXGhSTZs5K+WPXumPWXcCZ53Bo2JRPDYMY3RN53AU4tQcKstbWJ11MrtFpJeJZYzqqCyf38TUYby2xmg0pLJ/SGz0OOoPaTXniVOFXMZMZQapiqrkrJ5b5ns+9TEOenusn7tQuA2Vqpwc9pCpwsLSMnsHu+x3dzANQbWpsX3/IaqWU6laBG5Cdzjg6qUr1Ms1Dt54SEUtYysl0jAjlwVQiFCwTBupCo4Ojnjw4AElzcEiw9YEChkpMXVbQ9MLS7DpoEupVKJm60RKjswysiQgTxJKpkW1ZHDS7WNrBivzc2RZiqMriCzGnaY0a1Um0xHlahWBJAkDKmUH03KYq1dIkwhVVUjiEMdQEamC5/oEgUfg9jh//hy2XeLO9n16vROiKMCLxhiqxsbSIr3jI3RdcPXcMv64S1MXXFldp6zr9F2XYRyysNAmFRm/8i9/hb/5Uz/B+toSv/XbX+YTn/kkOzs7PH75WqELUFR0zUFRbfw0J4pSVtcv4E5jbo/uErkDDEVy/+47HPe6nN96nKN+mwtbmxwfHLF3awcVA9MqkeYJqqbgT4ZUyjZCJpiWjp7mLFQa3NveoVwuU7EsxuMpg+MAXdEpWQYyU4pIQ1Uj8gMMy6LZajDxJjMgt8RxzwWZEacTBKA4FZbbcxiKiudNkEQ88/FPUa60GI+n9PsDRqM+B+/cec+n8X1SFARZmiJm51RKOSMtzUzK8pw8l2i6hqIIwiDGsosKquvazFcxQ1UAmaFqBbAVhuFs7/4oMlPO5mfLLhEGs03HjBl5yoA8ZUEWl4KX5iTAOw8HPOwHNDdM3ElATSmxsLDKeDyme7SH05ynUqkiH9znSr3N4rmA3/v6H3Hr9k3iTKHZWsTRTE6O+jRqNT7xqQ9hOZIPPrlFkkTYpTolu8kzT38PpUqDN25dx3IdDntTMil55/ZbXLv2FF/53S9zZesiqZegZCrDwYQ0sXCHHouVeQzNwcw0kjjD1AUIFaGpoAgQYDlllEziVGx0q0g5qlkGWEV8XpKlKLaJbevFe2FaZ4XSdV10VUUXOY2KA2rRtsdphqZbKIqGrhrIPKNcdhgMewyGQ9bObWCXyuS5gkxC9JmFv6ZphGGAQgZ5WjBNA8FBv89keI/6XAthaizNL3P14hVeev4F9nfu8/3f/+c4OTzi9TffYG19A1C4v7NNs1Zj+dwyD3pdxuMxbuDjVMpUWk3Cbo/F9XXOXbxArqioCkxHPZQ4ZaneBF1w3BuAo6GicvPGTT745CXKLZWHO/dQJFy6sMnInRCHLq435gNPXOVkex/CHJEnpEGA601pNipoAhRFKxKhDYtgMmClVee1117jqac/hFVzSNOMNI0x1EJYZxoGYRhStm1UTTDs94iTENsqEcU5UZBgmCYxGrVGFW/QIwhCSlYNu7GIUFKUJGQ48dHKHdbmVmn5LtcUwb+688vv6TS+T4qCRJ8pIsvlMu5kiszFWQtfEJNmnnY52HZhdFHYpxU6cUPT0FSVJI1IohBNMyiXK/jhI9UlUqLpOpubm9y6dYtKtUowi6A77R5UVT1zlRZCIEWOQCdFA5kSZCp+BCg5e3uHdNoLBF7AwvwKgpSTgz2MUg1HkWh6j89/z0f45Mc+wvbuEccn/SLBqbPBT//EjzPfqTIZD7ANg1wzSBOBXrVBM3l4cIDQBP1+l5WVZXrHu9iWyfXr19F1nX6/y7Dns7p1keXlVUxXklQmmJqOaekkfoqqFTwNmaeYilmwAtMMXdVwc0GWJGSui6ap5EmCIgQyjQiCgEqtzLA7YW5hniSO8PwAIVQsx2YymSCEimpahT4hk4ik+F1kWYZTLorySa/LysoKc/Nt0kwS+UUobxIHBEHA3FwL153gu2NqJQtF1xgcj3j8sce58cqraLaJ0DX8MMT1fRY680iRc27zIl/6zd+g1azhB1MMU+X4qEen02aapfjugGA8wmo2GJ2MuXj+CkLYCLOCoVU4POhyefMi/eNjbGBjoU2ep1iOiUaDcZLR8wJubt+hZMBjV89z6cqTWJbJG69dZ/PiFpEfcLizgyVK5FlCpVQYmgTehLlmnVqlRJ7FxIGPkAphkKBnkMuED117isD3CsNXVUU1VBCgmRpxGmPYBmEYI7PCtk3TivGj7DSYegG6ZaMZKklWKIV1cyb9jnJ0Q8ELsoKJGkt6Iw/HMdGtP8Msyf9UV5oWtOKyU8KFs1ZekTwK2JjxDQr3JWeWDxEjUBGGJM1iRJ6R5GkB5qSSKArPrKtUTaPRaDAYDFheXi725rPrFIg8LUSnSVJpllGt1YmCmIXFFqOJT7fb48XnX+BHf/THuPv2Hc6trZCLvDA1lSqaXaVVNUnjKY6dUK7YNFptLKdKp9Uk8ifkWVzYtfkJWZhQq9TJhSBOMhJSjgdHTMcPmZurcfftlzi/uoSpW/hmxOXLayRJxHAhp7I4z8CdYI8yltodkmGEkQvi3EfmGZZpoAgNpI9AYBkaUTjm2LdYnO/gqIJ7d26TBH5hQy4UPL8IpV1cXubg8IjWXAfD0ZhMPfJU0FpeJ02KQjsJAjKZUyrVimRuKXl4uIemCFpzTTKZMplMKTkV8izD0Axq1RJB4DGZTPBDjySJ6A+m6Eqx3bj52k2W5pcYDYZkccZjlx/D932e/8PnyZKUsJGwefkKtqVTqpc56ncZBx6GzLEqNovtBa5ceYJf/Be/yq27O7hpxHMffg5dMdEyna3VSxwfPuSbv/s1Jvt9GnYV3VBp1uokcYiiWgzGHnmQsrt9yLVr17hzb4ePf/xjLC+d586tbS5fVHniI0/wa//q10iClMFxl5JusjLfKRy8dJ3uaFBwZ6Lib1bXTJIkpNKokaIUfo6aBnnhzIRukZARRimGac9IeEWXmyQJqZyimxpxkuD5PpoqqJRs1lZWuPNsYBW9AAAgAElEQVTggDQKaFRraMIGqaLlKfV2DYSkOzNceS/X+6YonB7KOI7PlJEq8uyQnjIU8zzHNO2ZdbuHqmqoGpA/8nE0NJUsV0AUReF0HQkKrluwHR2niKqrVqsFcWc8PsuCOO0YsiybpUgJNF2n2+3S7w9Ik/NFQE0Q47kBXbvLyvoaQRgzGIxZmGtRsQ28SR/dsEmlRpxIytUqtVqNXuxj2waOWQKp83D7IefP21jlMpqmIGXGYNBl2N2l09Z47mMfpXu4RxrFRKFPu77K7tEejbk5fut3fptrF54geTBEHPq0zRqVUpnBpE+cxdTrTSzdPKOB62qZUtnCFCXcIKRWrbJ2fguRpcg0wbFNpCwyNlXdIJOCSCoc9fuYVglTNzkZTsmzAuOxrCLxaOwVLs9BELB1aROZJQyHQ4RaWNwVLloKk8mE/sCnUqtSa9TRdIVQKUaKOHTpdDqcPHyAphWgYrszz/HhCffu36FRKZNHCbZV+GfsHx2wsrqEUHVqfsBJt8/RwS6D4y66VeMLn/okXT+i2unwS//w5zE0ldHhPt/6+u/y1JOPkfohJdvCKZksLHZw3QkVS8MfejR0FX1hnrffeJNf90Y899nv4e/+r/8bP/4jP8JitclSvcXf/u//BxYXVqhU29QadWq2Q56nZJmYBc+ayJwzMp2UAtXUmEwDcqGh2yb7Bwfs7O3ymc99lvsP93FKJRpzbbbvPijA9ZkvqWGZxFmG7lgYUkGxbPIswR9PeRDeI47T4sY0yogCH8epIoAwiAgjl/NbV9/zWXyfFAUxa9mTMzpyFEdYlVIhcOIRcel0V34mnEJDoqFYNq4XzopHSpxkhGGMpkoMXQVUgiAgIS80EXGCAEbjKfV6HcO0EYqGZVln4wSi8H2EjDCcIoTkpW+9ytrqeQbjEKvaxI2PkWpBEBl0j1DShEatSRpHVJoLaLNtRhQWBp+aqlKvN4njmCTOcMoOlVqZiTdEMXVEGCI8j6O9XSaTY/JcYNh1lJKBUy/z8h+8Sc8dUq6VaYQ6H918jGl/SrXc4sonP4IceZhJAoqgXG8UugVRWNwZps04iYkHKQpjSrU64+4xzUYHYRqMgiF+XORYSKGh67KAY6KQRmOejCKJ27HLeFMPxzAZDk7od3s4ls3CwgJ2yWY6mhJHCQKVyE9JEkmY+Zi2RaPTwJ8oxFEBHkdRhGXZdHsn6FlCmMbIXHDc7yENiR+5+D2f9cVFkmCKsCEY9Djyp8TA/Z0D8jzl/Noa7VqJim2ytrbOcbdPGLssmyr+0QOeW19m/+iYJ59+AkUVhCcTGrUaQR4QxhnjSciDnT2qpRK2JliyUjJdsPn0E0hdZ//br7JpVXnxN34bQ83ZeeFFrs4vgK7j2CWEUUa1DTzfJQ190jSnZDsgFEYTF13TMIFyySLNElzPQ0lMnvroJ8hvvM7uyYS5hVX8NKa1soaX5LTqDaaTCTv7e4zcACuTmIaENEGRkMoUp+zgRiFJlmKXymhaifLiImESEsUBew93WV1d5t72w/d8GpU//SH/KS45O/QFz2BxcRFVUQtDy1mH8G58AR4ViVMMIM2yMxs3IcTZ6rLoMtQz4PAUX/B9n9F4dOa2dMqAbLVaj0aXWeeSzkhQWZaxvb3Nr/2bX2c6nSKl5NKlS8Rxim4YDEZjtq5cpeRUsJwSpl0iySSWU6bZbM62GeFZMpWqCSzTpNVqoZs2hmmR5TnD8ZjthzvkJDTnmkwmY/I8pdfr8clPfIpKpcJcs1gZjkdTJhMXxTK5eece4yhlnApKC+cYpjqJWcXHIFAsjsYhiVbCqLW5tHWeNI2Ym29jOhpxFlFtVDFKJursTqxoRYdVrtTOxrZMFopJoeR0h4fYtsH6xiqtToMkixlPR4zcHpn06fUPCMIxceJjWiqGqRAnRaeWy5RBv4tjmYz7XWolC11IksBlrl4mnA5Y7rRJA5dGqYQhBfONFiqCdmfujJm6urpamPzqRUDKdOry6o3XSLKUpaUldF1lrtPk2gceo1Urc359hWrFxrENkjjAsQ2ckslJ95BGtYqqqpRKJZbWVinVqrTm5zBNk1atjqkU6VXtRotavYlmFAYqp7/PUwq+bdtUKhXCMDzTfSiqim6ZjFyXOAfdLiF0kzfeuUOl2sJwSrhxyMq5dVY2VslUyd2de2xsbVBulTkZdJGahlA0ckWl2e7QbLaJ4wRNFPGDvu9jmibHR0fMt+dRFZ0L5y/h2BUM9b3f/98XReHd40Gappw7d44sz84ETKePgUeRbqdfO539T39e1/WzYiKEIE3zs87iFJdI07QI+BCSSqUye1xKFEVF8pRajBXhzMT19GdPu5N79+5x/fp1XnnlFaQEPwyL1lBVMSwL3TQwTBvdcNBNC88LyJDU63Ucxyni5RQVXVWLrkXmmJZDjuS412d/f59bt24xCaZohoobjNEtHdMsiFtzrQ6aopPGSWGwsn6el6+/yW9+9Q+4czQgrzRIFYVKtUqcJJQrJQQZrVYFW4MsdNnf2UZTYDQ8YTA4wfVGuMH4LJREqMrZH3scx6QznUmaFIlEigLtdhvDtmi1WuRSohkapUoZTVMJI49avQwyZ9A/YeqO2Nm5z2QyxnXdWXq4jTseYJuCJPAwNYmtKcTeiM2NFYLpCF0tlJFxGNDtdmnW6nT7fbwwoNPp0G63+eizz6LrBoPhGN20WVvf4MqVK9y5cwtEStmxydKQrUsbTMcDxoM+83MNDA3azSoyi9CUHKFIbMvAtC1GgYvVqNIdjlhYWKBZqrLaWWR9aQVvWvh66qaNbphUG01SmaNoGuVqHSmLv8VavUmn02F9fb3Q3qTFnT2nEO1NJhMmE5d+f0ipXOPcxgXai4v83X/49xm7I/xwyj/+Jz/Hxa0L/PW/+ddQ1CJ8SCgafhIVYUZCKxijQcxCZ57jwyOEENy6dZs0SomjnGHfJYree0KU+sUvfvHP4lz/R11f/OIXv3hqfKooCtvb26iqII5TLMskyxOKfMXTgiDOSEjlchmZ54W1epbhOM6M4WeSJCmnZkuFaEp/ZNwywzAq1QquO8W2LdI0wTB0TNPAcWx0XZsBoCpBFJzNd5ZVrI0ePnxIs9mgWq2wtrqCooKma/h+QJqn6JoOEqI4JAoD0jjE1IoVVRrFDMc94igsmJlCUKm1+KVf+efkQkfRFKKsj+t26XRqWIbB9t0dlpdWaTUbZFnKndv36HSWaLWX2N0d8PobJ5z0TkiFSqtiUS+Z1KoOIk+olm10kaKrObrIiKMUIQVZmmCbJhWnhAB0RaCpOmGQMJlOZ+7aCaZuEoQhaZZQLlUQKCAFQihMXQ/TcnC9CKEU8X2WaZFnOXGYUK0UzMpqpYYiVMgVhsMejqHjjfqoMsUUGXEwJQ59nvrgY8RZxA//yA9x/cYNqvUGvf4AIWQhEtI0hKpSrVU5ODhiZ+chJ90eK8srSGA4GnLr1i0ajQYlx6JaKXH/3h1sy2A46PKRDz+DbZoMhn26J8ecW19F5hJdK9y84jwDXaNUqWCYBWYSuC4CyYOdhywvr6BbNusXLuGnOWGakwsFTjtB3SRLioQzRVXwZ7YAhiqZDLsYWrFtiMOQWqWKaegEvo8fhbz99ttcuriJqaqUbZuHDx6QZTG27TDojUmTFBSBpmhEQYBtOZRsC9txmIzHGJaNzLNCb+IFCIrfURyF/P71G4df/OIX/+mfdh7fJ5gC3zEWGLqBJAPyM+6AlI+6gVOKrGmajyTRMjvrGk6voruYCXZ080wZeUqfllIi8xyZ50RhSJ4VijJd0xBApVxmNB5/x/bjtHspwMkh3nRCo1bB86Znd1VkYa1Wr9fodY8pOyWiIKfqWBwe7GIoKoamE/oB06lHEMfUmx0aukW50uQrX/09nJLOxStlsizm4OAI1xlTqVV57cYNLl/ZZDodoxsWcS5RdYuJH6HZMI4yvvKNFwiDxzHIuXz5MmQ5lmmgzoqpqplYpkEuJVkW4E+mKFUBmcTUC26CsA0ajRqj0YjJZIrWVLHNghIeBiGqYhRJVkIwnQa02yWqlQaqqhOHU6IgJIljKpUqtm2j6zaarhOnCWHmUXJsJuMh850W/uAETVGpzs0xEPDKjddxyib/5t/9BtV2E99L0SplLFsH22LU65OkKZVaFT9wKZeqtNsd7t65j6Ir1Go1SrZDq9Vgf3+f4aCPEIKD/T100+DmjRtkskiErlarnJycsLCwgOcG5EzpjUZoVglVM5lrtdm5d78oYJ7HhUsXUTWDUq3G8WBMJAXarKtK46RYAUuBbhpnRDjX8wDIZMzywnxRONKU+nwbhMpRb0CaQ+B6JHnGW7u7LM7PEfsen3vuU9zevsP9d24TBCHqrGM+FQHGcYzMEnKRo2qCNCtChRAZcVIY9ei6ier8Z7iSLLqAR9iBqhhEWVAUguzfV08qinLmu+j5PqZtnI0BzBKh8jxHzJ7zdJ0p3uXRAIVUGsD3fer1+hmhZjwen20ibNvGnY7JZeGnHwRBIeTJJZNBl4f371GrOlQq5cILTxSeDbs7UxqNBoe725QsFZWMPPIZ+wEKglRROOn2CMKU/iikN4r4yEc/wTdfvF7gIVJjcb6DlGNsy6J/MkKKnAcPt7HLNla1wus3bxJdLMJxUDQsu4w0UqbCRlNV3j5xyeKEWrXOoN9nOp1y9epVLs81UFVBOu6j5Bkyy1ByiUxEEVkndCJ/imNqtBrLZAim02khp458Ko5JnElymbI0N8fU89E1A5ELojAtvBp0A991CT0fwzYwLAMZ5UzGMQvtOlORkqcxKysr3Lt1i+k4QmYSRTUI4oTR4Qlz88ukJOi2w2PXHkPmCdv3H7CwtMDa2ipZltHuLLC9vUtzroNME6bDER9+9iPcuHGDXOTkeQEY65pFGASsrKxgOiX2Dw4wLYfBYIDnxxz2esRpQKPRpLOwQqlU5d7dbZI8oztxubK1Rancpjcc4ycwjRI00yGOYxqVMomiI0Q0SzIzmVufY9jrz8BqSKOY/mCCYWpUqjV838ePfdrtFqPJlMDP0E2NjfV1Ej/EVE2O94+Yb85DIqkaNoksdBRZlqAIUNRijW4ZBoquMgk8Ns6vcdw9Ya6zznTiE4fRH+tn8B+63heYAnynVPoRmYizavsdLkyzj08fe5r4/G4/xjMqs1QQqGfjxinWcPo8QRCc8RiCICBJEly3CPxI08JbYDQa4TjOWSdQLpdJ05xLly4hs5QsjXj7zTdQhSSNQybDYm4tORahHxD4Lp47YTzoosoMmcZEnouiaLRac4ynHr/6r3+df/Rz/4T+wEUzbNqtBXRhoQiTsl3FcQrewOq5dUq1KkLXmFtcYHXjPGN3ytrauTP9huu6vPPOOzSaTRaWlwnzjFxVqbY6NOeXCFLBG7tHPH/jTR70hqilMqlQUAwdRQHfc4n9KbooxgmRpWSRT8kyUfOcTrOOpqbUyjqVikkQjJF5iCBjNO5Tq1YKDUme4DgGuYyJE4+bb7yMrmW0W3WSNGJuroUQgsPjI2qNJmgGGxe3aDcWCd2Ehc4y48EEy3J44uoTfPvbr3D9+mtc3LrEBz/4Qd544w2Ojo648eqNIq/DKmPpBs16g93tHSqlMs1aE8cuo6gmVrnC3NwiUSLZ2z2gVmvQ641QdRtVL4xn1zbWmZ+f53j/gIOdXaIg4P6Dezzz8Y+SqII333mbWqdNrCrkqk6UpERJTO+ki+/7xEmhawjDkFu3bhX8grTw60B1yBSLaZDjRhmTICGIM8aBT5RlRSCyWoDkqMrM6McizxTiOC9k5oZB2bbQdAWhCU5zJNIsYeqOaTereP6QxaUWS8ttWq0SUTwzi32P1/ukKDyyUSvyFDJUIdG0Rym+8O5iIGdsw0fEJl3X30VNhjzLCsrzqcJy1i38+1cO5Oi6ShQFJElEGPpImZEkEaPRCFUT5HnBDEzisGjddZUojTFMlQsb53jlpW/jTV2mkxHj0QhdU/jWyy8yGnQJXY9Br89k6qJogvn5+cKpNwiJwowrV59A1R32j6f8vX/wc6iKye3bd1FVkyjMaLXm0DSDnMLU1XEcJtMxL3/7W7z91uvs7u5w8+ZN8iQnjCJScs5vrHJ88JAXvvG7PLF1DkP6iHhEu2KixB43bt/jXnfAg+6Y1+/e4/o773Bv75BQaBjlOoapkiYBvjfF86dYhoYy0zdMJyNif4LnjlBlim2qRN4U0xSkiVewT9WcwaBXhOokIUJI1tdWMHQV09TZ3zuk3x8SRAmuH3PS67K+sUGv10NXDTbPbxF6EbVKFZmkbN+/S9UuFcVdM/jqV3+HubkO7XaHZrOJoRocHx/jlEvFoYwjPD9kMJoQxglSqFiWQxAllEoVhKqRSViYX8JxKjx4sEuawls33yQKQ+qVKuPBkMFgwNNPfYjjbpe3796hvTjPxHMJ44ggSpBCYFnOLDcym6l5BUEYYdkl/DhBMw18L0S3yoSZIFdNhm6EapXIVB0/koS5RLE1FEvDjwPCNCHMU6Si4kdF8LGuquRZRpak79Lw5CiqmHFvHHzfpXfS5XB/n9vvvEMQuGiqRNXeu/DxfVIUTlNzVBbaDeolhcVWCcdQyNIMIRUUIQoarpQgcnISUlmswBA5SRyTxDFpnGHqBmkSoVCwHFXt0cjx3V3H6XWKN+R5ThSFDIdD/MAnFzmWodOslbl8cY3NcyuzfAiVieexuLaEquqoisFvf+X3ac4tFqvTNCM4OuDrv/XvOH54zPZbu6Sxzl5/gijXOZnGtJqLONU6v/+NFzArTQzbRtVtJl6IZpY56U9oNTuYVpVcUVFMi0Z7nvFoxFKjzVNXz/ORa5ucm69xuDNAVSzCFLRSYXd+49YOYz/iV/6vf04ucv7c5z+H645wp2MuXdzg6tXLONUK0yhiMu3z4ktf599+7eu8tHfI9njMycgjNyxiwyQRGiJJCF2P8aTPaNjFVCQkIZaQzDdraFlCo+wg8uK9r1RKZFLilGvomoNl1PDGEUkYMT+/yMRLWFrbolxr02i02Nu9x+aFZSb+hChOuXT5KnGaIERGrWKTZxHnllcLO3S7ysHeMZZhU6vUmUxG1Os1jgY99EoZN03BNDl36RL5LNF5OC5Umjt7+yiGSbnWZDj1sK0Sy/Or6LnGtcvX2H2ww+3tO9TmGzz5oadYXl7F7Xqsz63zcG8fRdEwNJ35uTlsw0bmCpZdplKpECUZQZQwmHhMvZD797e5efPNIowomJDIGMVS0B0NYWgcHh9RLleKQONazk//d3+Fv/o3fpLPf+FTXNpapzNfI40mKGlIDozHY2SeYyoahmoghSCREqGZeGFCmumkiYY/TZkMffZ2jkgTyLL3vn14X2AKQkCjUUMRgtAbMd+o0GnXsU2New+7xFIFUTD9oADxFFQ0BMpME3EGQirFSCFm3Uf+XR3CdxeGP146XtjASSkxdZV6rcLG6jJf+L7v5Y+e/yaTictw6rG5cZ6L57e49+ABWCb/+ktfIlclDdtmECekd465d+cd/u+jr2BIwV/44R/kyec+RC9waSws0Ts65KA34Ed+6M/zP/8vfwddL/jspqkTRB6ubyGFQhiGBRkrSqlXWzTOXeZwd4dS2cAPJly69DibF/e4f3uMqjkoisBQJEkaMZzmNOeW+Z0/eomv/dGLXN28RL1UIfUGLGg6m+tVdKuFHtYw83O8dK/Hw2EPqbSwk5z+cZ9EE4gw4vLCEs12m0bVQQkivNCHLOPk8IjV1VVqzSZJKFFEhmlAmoaYplOMdLL4o0zyBEVo+JMxpqqx/2CbPPUpGTrSsri3vYNtl/Ajn/vbO9ilGmkc0h2O6CwscvfeDmvrK0zHE3y3kCkP3T5CVXC9Aa1WC9/3KdkmzXaH8bgAZGu1Gq7rsXN4xPLKCpppsXd4xHgwJgpiIj+gWinx5S9/hc987rO4YYSqapycnLCzs8vq8hpxHFOv1AttDjqBP6RcqRWxAsMBlWqNkm0TxjFzrTZCSBbn53BsC5kmDCdDur0+C4sbjMdj4ixheXGBwJ+Sxj5GYvKPf/ZnyZOU0WBEu9liYa7D+dUOw96QJJWUbYu9gz0Mw2Bt7RxZIrAtC9fzsKxSYXCMQhKn6KqJ5ThImWFZ793i/U/tFIQQlhDiW0KIG0KIN4UQf3v29Q0hxEtCiDtCiF8VQhizr5uzz+/Ovn/uT3uNU3flYbdPs2KysdpGy33aVYNWVZ+BjYVFuKrqxb+KQhonkD/KgjjTOLxrZHh3ETglKL170/HH/H+/o2gEfsgP//kfpN895sL5c6wuLnNl8xI6CotzHa6/+hpf+8Yf8pu//WW80ON///mf59VvvYKNDl0fS+hgWnz4o8+y1ppHlbC3e4Cm6Bzv71G2TMhTfvzHfpQ4CanVKozdMUme4fkRQtVxfY/heESSS46OewzHAfXmIlKYfOiZj5Ir8Bf/4g8jlARdAyWXBN6Uxx57DLtSRy3VedidcPvhAD9NmbhjFtoNlqtwZbEKwYh8eox/fIeDe28wGA/o9g7xQw+pKkhdRTglukHIa/d3ePXONkazTapZLG2c5/zlKxhOmf5ghOsHDHon5HFAydTIYh+Zx2hkiCzGUASWptKoVjCFxFShVioR+gEyFxwdHTEYjUCopBKmro+i2xiWQ7c3olJv0OsOijurJtAMlWazTqfTYv3cCogcXdcJgoDeyQknJydomsb+4QkpKtXWAm6YFdbyhs38/DymWVC7d3Z2+MC1pxhPfTRVZzSasLKywvlzGxiGhoLAsUrI7BH6j8xI4hBNU+ieHM9k/CmTyQR3MmE8HNE9OmZ/d480TSmXywyHI2zbwR1PkFnGydEBulAYdvukQQw5XNg4z8baOuPRCH86ZW6uxVynSS4TlpYWqDXqvHbjBqpmECYphmWT5hlJmpPLYuMg0JCZhFxhOnbfW0XgvY0PEfAZKeU1CqelzwshngV+liL34SIwpAh/YfbvUEq5CfyD2eP+xCubzf+thkmnUaNRsom9MSVd0Kg46KpE0xTEDHgUQgWpoKKiyEeH+ZS09IjJKL7jkKuqerZR+G4/yHdvNb4D3wAOD/e5fGmrWO0ZGk8/dY0LG2vINGU46HPz5g0EKWHkowCvfvtlfuWf/TKKoXNnb4dhGHBpawtDEQTDCQu1JtOjHrVahYODA4b9Ae12kw9/+BmCIDgDSfuDCf3BiN6gT6PdIklTTLvEvfs73L5znzSDF779CsPJkIF7woWtJVQjQyiFUcp0OiXKJHEOy+c2eeLa4+zsHXJvb484hVtv3yYOQ/onAyqlGs88+SEWOotEUcL5pRrnVxpUnYKJ+P9Q96Y/kqXXnd5z9z32jIzca++q6uru6r2bTTabiyiN9rGlGcg2PDAMCQZsw7YwgI35ZP0Fhg0PPCOMJI9GsABCM5aoxSRbZJPs5lK9sKu69qqsqszKPWOPuPvqDzcy2dRIUBuQB9QFCplx782MCFS+J857zvk9P1GR8bKcwrDAqnLlxj2Gcc4Prt5gpz8kFBX0ehu52kTVbWRJZzR0GQwGTMdjoiCgSFLSMOBw/4DAmyKQIwulQXCexmRZQbvdwbKsY3/Qo3mQKE6pNpo0W60yExRl6vUmQRSytLLMXGeeJy6cR1F19g8P6HQ6FEXG/FybKIp54aWXUXUTw3RozbUpcpHRaILv+4zHY8bulCfOn2dl+QSLC8v0eiMs02H93gPG4zGSUNKRkzBCyAUMzcRxSkAvokCcRthOWWDVDIOdnR2yoqAQAElEM3SazTkss4okGviTGEU2SMKUc6efIAgiZKVCa36FeqPDeBIymATML65SKAaoBkkSoVvmsT/JmXNn2d7d4f79+4RJTIZw/OHoeaWqNfATilya2SR+suNvDQpFeRyFGWX2rwA+D/zR7Py/Bn559v0vzR4zu/4F4eMr8K89BAxNxTJMsiTmcHeXhfbczEcSTEXAkIpj+TTwY2TnIIhQFOXH5haOMgJZln8MwzZ7Tx/LEkRApCiEv+ZrOVL15S//CWfOnOHq9WtcvHiB9658ly98/nU8d8TZ06f47Guvstppo1KgijlZHrF3uM2fvfstxIrO6ZOLSFKKZiqIZBxubbHcbuNUK6ydPEmcJgxGQ774xS+iaRqyKBL4EWkuMJp4rJxYo9s9YDgZkuYZr37q06wsrxH4EUmeISgiSyfn+fTnX2bouoiKSJCk3H/wCN8v7e7CwOPxzg7TKGK3P+TP33qbb763we98+auIZougsLixMWBvGLPxYIPuzhZry4sYmsSdGzeo1SrYFZvRZIhm6BjVKk6rxcVnL9NzPa7evcd7t+5y9cEmh9OQnhtgNlvMLZ2gMbeArOqMPZ/BaIhqqiCW28HAL1WSImU2mGUZWRKhqTJxXAq25ufnyyDZ77N7cEh/PEFUVJJCxLRr3L7/EGSVb3zrbQYTj3ZnmcnEZX5+fjZoFnDnzi2eufwsi4sdpuMJYeAzGY7oHhwSxzGLy0t0RwMO+yN297rUGi1c1y/FSKqKLMvoigpC6TMiyyLdbpeKU6MQJBSt5IUaloXv+zz7/HNYjo1hW8iKUjp/DacEfoo/CcjSHKGQsE0HUShoNZroho0kaxh2FbveJBMkDoYTDkdT3CBBUhWWl5cxbWu2tVWpVyusra2xtfGIve2tHzM9Sou8ROEVOf8fbB8+Mc1ZAj4AzgD/HHgAjIqiOHqqj3s7LAFbs8WXCoIwBppA72/8/UCWpIzDKVahsrI6j+v6xEkpwLE1gTiHMImJMhGEmZZcKkpdv5QfaxSytECeEZdEUcQPS+7i0biyKP4oMzgaX569xx/bbhydEwSBPIn4i69+jbXlDqNBj5defp4w8vmlX/5ZWjWHE4ttfv6nvwCzDsZaZ5HJ4ZDYHTEKPYI0xt0/wKhpTJKAeqPC2+9+l9MXznL25BL/91/8JW6UcSzSQiIAACAASURBVOnyCywtrfDo4SaNhkOSeYRxwmA4RNUVOtUGjWqT69evoUoyn/7UK9xdv81HN68ymIwQRYehB7qVY5oW4sSDLMPSFA7HQ5aWOmxsbDDXrPNoe49Tix2mdovcaqE0DMhCQnUf3U64vr7FxfMj3v3gOrkIX/vqX/BTn3odR5XIsoDD/QFzFZ3MkkjzGN0xySUd23IIU+i7Ex72HiCLBUudefI0orPQIY5DpCzDHQ0RspQ8T1HEAlFVSOOCJIlm49w+aRxy8dLTTKdT7t9/gCRJdDqd0uAngzRLiJIE1ahw5b2PQBK5ePEEiihy86MPiaIAEHEsmyzLefPrX+P8+fMc7m3Tbs3hiQJhmPLaF15jZ2+bubl59rYPUPWSP1AUBbKsYeoioR+wuLyE2Why/dY9TFHCcmy2dnfQdAPTNFE1jf39Q8IwxKpUiZKYJIlwbAsZhSRMS3/TtFQ/1ioWU3fAeDjm7JmTfP/Dq2iqjmmanDhxgm63T5CkzHWWmbgTpmnM/mEXQy+zBUEQUGQRyDh39jRFUXD16lVOnTyDZVlMPQ9ZVZBU5VhF/EmOT9R9KIoiK4riMiWu/SXgwl9328fW+N907fgQBOE3BEF4XxCE9/Ni5j4kK9SrDXw/LCfjsrJAqMkFllGOz8pymd7HSQKCRJylP7bAj9Knj9vPHUl3j70fPnYNOM4kjoahjoRXRyY1L7/yKnNzczOuHty+dxPTUTAtFc8dY+oyhlCw0mpSN3UoSifgiRxjOwbVQmCxVWUQDhF0gdZCk+byHOubj7hx5y61Rh0/Cnn7nXdwXbdkRboeaZLz6NEmXhggqRKuN+Kj61fxQg/bNplMJlQqFS6/+CypEJMKEb/x3/w8L7z6ImPPJ0kSFFkkdMecWOzweOMhq6urTKOU+dMnud3zuLbV58+/9TZ/8s13OIhUBLuOZldpnXqG925t0JvGJLlMs95g58E6733nG/Q2HzDfcNjdvM/d29eoVDTarSpjd8D+4R7DOCUzHALVYHMwYX1vn73xmPdv3eTG+joDd0KlXsOpOVi2cQzjFWfbniyNEYqMiu2wfu8OGxsbmKZeqllVlQKBWq2BrBu02vPIioFTa1NtdNg7HHD/wQZLK6sURcETT5wlTSLSLOaFF57jcH+XqmOjiAJLix2Wlha4d+8OSVbg+iGN1hySpMxYG+XfR6fTKVveacKNG9fpdDqohkZWFKydPEEhiPSHI3q9HoPREFGW6I+GyGrplO4FPrKqIkkS+czhHDLCaIoq52hGzmi4x2ufeonRsIdlaty7e4de7xCxyAm8aQkU0jVEqeykCIKA707L4nQUEIcRWZKytraG7Zg83trAtC2caoWp7+H63idZ6uV6+MR3AkVRjIBvAa8ANUEQjjKNj3s7HPs+zK5XgX+PL10UxW8XRfFCURQvCIJAxbIwNYmqKdJwDIQsJovKPwxNAjErMFQTVVQQhQwhz8jTbFZXKGcN0iwrlX0CpHlBkhcIooiiqsRJUhrViqXSDEEqhStCSa+RFaU0n1UUFFUv1WiFQLVa4/kXnsWyNJ69fB5Vzbn4xClW5jv0dveQRRgMeuR5SuS5JF5AOA3I04yKUcF1PQRDJlUVNLOKIOlkmcziyirzyyeZeiHvvH0FCoV3vnOF7a1dwjBE0zSEGPJMYHevx8bOPpmYc/7yecz5KvZSiw/vX+X+43U2N3Z59GCTidslE13+6CvfLLFzWSm8GY0GdAcHkBf4rospqfzKz/wsK60aQpHQDwI82eB//71/w/r9O6hCytXrd+jML7MzHvOo1+c7V27w7uYD9KbDG5eeZP2DH2DIKo8ebrG/s0vvYB9d1pHUKlERQZHRsBqsLp1Dstr4WhW5tYZYWWbfFbmx1+fD7QPujzwiu4GztIpkGeRSgm7JiGJBFHgoAtiyiJom5N4Qt7uDXsSE3ghdk0mzjCDwaNQdTLlAzRMWWg3ytEA3a9y+t0m91UZVdN5/912yoiArwA1CRFXDsB1USScJYsQkwx+W2HzSFE2WqVcdHj5cR1FhMOwx12jiWAah50Oesr+7gyoJ6IpMkWdYho5t29ScCkUqoGs2smSwu9PF8zPGUYafFxSqhK4ZpHFBnsgMex69nUPazTbv/vBDzl56EsUwkVWTxE9RCxkpy5hr1Ikjn4KULE8xNA1Tt0DICBOfSqWC6wW0O/O43oTJuI9tq1iW9XcXFARBmBMEoTb73gC+CNwG3gJ+ZXbbPwH+ZPb9V2aPmV3/ZvG3IKOLoiDLE5qNKpqukGcRFDm2ZZTz4FGMrmkUWVlXKPIcQcyOR5ILUTjWQ5TtrxwEgVwoARdJkmBZ1nGR8aiYyCwjOJJKq6p6nDWUdCeV06dP02q1qFQdkEQWFha4cO4JZEEkTzL6/SGabhNn+WzIZIZRL3Js00FWdXJRQrNNBElGVUyKAlRVp9ftk6TwC7/0D3nrrW8fKzWzLDv2d/TciLl2h+XlZTa3HrP+6CF31u/wvXevcPrcRURVZTxxOX32DJouUp8z+E//858GCgRJQjN0JEWm1qgjKTKTscugP2I6GPHUhSc4ubLC5tYOe90+p8+eY2Vlhf3tPZo1h2+/9SaFkPPSyy+jGDLTLOfcU8/w8OEGi4uLxHHMy6++wo07d1lfX6empCzKPvXcQ0k8Qm+EoUmIRYKhSKiigIRIpphkWoXcqhEaVXamCevdMVsTn61RSD9VEKttjMY8gmajWRU0Q6Uc6Y+omiqDgy0yb4ySBjRNhXwyQApdSBMODw9JswzbqaBoKoPRhDhNyvFmRWGuNY9TqXFw2MPzI+I0w9DLzEuQRKIkZmFxkVqziR8nLK2cZOKHLK6u4Xk+3W4XQ9dpNZrIsoyqyuh62dmqOA6aMvN3CEOyNEVTVFqtNllRIEgikiLjuQFxnCIrOkEKsayy2x9RmWvzy//xP+bGjTukecHhYW8m7DKREI69Uw2j3LKMx6XqNPR8DFklDgNMTSWPU3RZRpElItc9Lsj/nQQFYAF4SxCEj4D3gDeLovgz4H8EflMoDWSblIYxzL42Z+d/E/if/rYnEASoVCrHsmdRFNEUudQXkCOIKkEYEycRSRSjSrOW4scGMkqDlx+NNx8t9uO9l/IjheTRov+rI89HAeRHugqxXNSFQGt+EX02LltvzmNVKtjVCoZugyAjKQYFMtVmiyQrCOKILKcsNlk2iqxh2hVAxDDKqN2Ya3Hy5EmazbmPKTfLwFYKuEp/AF3XuX/nPk8/+QzzrTmWFzp43pSr126wtLKKrKn0RwN0S2Xz8TqtOYfhsE+WZbOxbQ+KcuJNVcug5YUBk8mEhYUFdN3E90MOuoe4XkCcgTcZ8vxzz7Ay38ZWdQzTxvVC/vKtd/ju1Vtcv3OfqT9lY3uPvWHA7sEhT52YYzl/zCm94PDhLdodB6MqkSdTksE+cjzFGx8gaTKJIJCKMrGoMkzAkxw8vUE+t8JhYXN3ELExTRjkMrFuIDgOhWWCrpDmCY5lkIY+wWQAsYueB1jESCLoukoU+hwe7JKnKVKRYWkqsT+liGNGwz5R6NOZn8O2TBRVJorDssMzGzHudnulNFnWyEQZVXfY3u2iqvqxN+lkMkEWQVZERKnUNsy3WtQqVRRZplGvljzMyQhFEkBIEEhRJZG6U0GWdIJUYJIWeKLKQRBz8uIznH3iIuv3HvDtr7+FIoj0hj2SIsF1/VldrIQBeZ5XBp48x9B0hEJAFaXSmCdNMFUN0gTbMqjZxidY6uXxSVynP6I0lf2r5x9S1hf+6vkQ+NVP/AoAChiNRhi5ytxqHVEswSfMnI5FRSV0I/K8QJEEJE0i9bPZnHiEIH0c8iqAWLINjuoNRVEcg1ilGcPgaA9bFNmMrS8dXy/t7RXiOGF3fw/XC9jY3MF58ixIOoeDEcsLixzs7bO6ulo6WOsWpmUhqhJ6pUIUeBRpTrXSJMsjvOkEJRcII5dKtU6UZCyIGnt7fb7znW8SRaVOvhzQkstUP4xAVLh69YdU6wqjkUscJcy359jceESUhTzceMDUn7K42CJIXGRF4Rvf+AZ+kLHYbjIc9bEsg/v3H6DrJmmSo2oyP/zh+zzz7HN8dP0mF849waONB3jjCSdWFnAclek44Oq19/nVX/tP2J75Gg77LsMsQjYFTizO8eH1a7SWTqPUOgxTn3/3J/+O/+4fvsrOUGJ4uMd3fvAdvLyg/3CTL33qNearFbIsIYhdTEvH9zIEUSbNRFAUojTHTyPSXMY2bVIJvDTEdX3ELEIRcwxJZ6ntILgeURggFTlREqIIQJ4jiAL+1CvrD7lAlpR7aSMvO1aaVUORNcbTCYR+SfsWSxCPpsvoqoJh2QRJShYFTIOAfr+LIAjllg4FRdXKraXjMJ5OGfd7SJJEtWKTZRmaqdFq1Dk4OEAURYLAQ1MlLFsnzTMMWUKcdVrCNKe+uMLeeMQ//vVf52Bji739HufPnee5C5coioxCLAiiiGarWY7YayWBuygKLMdBFOXSdCfyjjNdQRIYjoeYpl7WNIS/40Lj/99HAbh+wsQP8IOENCtQNJU8z7F0g7yQSOKMIgdZlmaMPhDEcvb7aGLx43bzH29NhmF4bEd/ROw5klkftTiPth76rOp8lG2MBkN+91//PvXGHLZT54nzT7J+/yG+73Pv/h0cx8G0HURVQ1BUclHCqdcpJJkkz1FNC8uuIEgypu0giCqKZpDlAgIS0+mU69evoxsGCELZqqIE2QqSjGqonD13hm63y1yjhT8N2dp4hGVITKYHICcEiU+cJGiqTpGJ3Lg2RFNFut0+p0+dJU1zGo0WRV7qLmzbZjQZ44cB58+fZ2lpqSye6Sqd5WUKSaJaNegOXXYfPaK3tYOqawRBWmZD7Xn2+11yRO493uHxwCU1Gtzd9/nLK9e5cfchEy9h/fE2YQGTMEEzdP7PP/gDHu/vE3oDwtEeVbWgoua06yZVW6HZqtBs1SiKjKk/pT8dM0kzhhn4usNErjGSq9zqjjjMBQLdJLUqBJpG5tQIdZNqtUpF13AUhaalU1NVlhpVtDTGIiV3RwTTLqacoQoRppLjqFAxBPLER5VyithFTgPycIIuJGhkyEVGFvpMJyP8qctkMOBgb5fQndKs1DAUpeRSDnoc7u7S7x6gqzKH+7tUHBtZgCjwOL22DHk6y4YVOp0OL7z0Ir/yj36Vfr+PJIh8+O77VDUTXVZRZaW0lxNL6pUsq0xGY0I/wjJtECX6gxFnL1zAbtRQDJ2MHLtaQTM1vDTAatWZRJO/bun9tcdPBGTlt37rt/5nSQRZgpqtoQml1h1BJUeiO/JJckrBiVTQXpijVnVwXY8oLhAlYdY9UMhnxUVBEFE1rWQb5D8KHEfKx6P+c1HkJHF2/LiEqsizGoOC504xdJ3VE6tMJxM8b4o7HpFEPpefeorJeEi92UTWNEyngqobTCZjFEWhUW/hex5xkuK5UxRFJUek0ZojFyQ+unmbu/cf8N3vv0uWQ4GEIIqIAiiqhiiLPPXsMorhU63Y+NMYUZBxbIMs82k26gSRT2e+w2g4QFUkGpUOrVqHxw930QydwXCIIEpYtsPefo9avYqiqViWTrfb48KFi0RRxP/w3/8mrucyGA2ZTF3Gk5LVSBhw7uxZClOj4jjULIe9w33yJMKPMlZPn+fR4z2sao3V5UWQZZy5E9za6SLVmsRJgSQUSJLIXLvFfq/L7vYWoTvEHw/YebzB2tIy33zrmzj1EotetWwqjoGiSOi6QZSmTIME2XCYximGY+PGCZmsECQZsungZznVzhKR56JrGrKq4gYBkiQSBgGKKpGlKaphIKsyklRmiaIkkiYxFBmyWNaYsjTCsXSEPEVXFHSl3JvrilKm7oZKkRcIFMiihAhkSUyS5ggIiJKMpqnIsoQkiagyuJMRcRThui6GrpMlCUkc88EPP2A0mVLkKb//L/8FapqgCZBFAbIgkOQx3X4Py3ZIwwhVUVBVDV3X6ff6pFmGbprsd7v4QUAShaRJQpYlDEYld6LeapKT8fV3r38iyMpPRKYAAikiYVTgBglRVpBmOWGS0B+NyRFLAGmeoykyaRzx/AvPsrjUQVQ4/tT/q+i2o1mFo8d5npPN2pVHtc+jjOLj98hyGRTiOKbVrPPUpYvs7ezi+z7NWpNbt25x7vRpuoe7VKs608mQJElmfWENRTagkBlNXApKWlOSFciqjl2pkmQ5iqojqyoFImkKaZof10HK509IspisKBHxpU2aRhLCqDdAkTT293sc7Bwi5KWENopdPLfH/JxFnBy9T0o60tRFVSW63S67u7tsbD1GlmX+6I/+iCRJ+NrXvo4XRAzHU/rDKc3OMqKhMhqMuXvzFt3DfbY3HnH+zGmCKMSoNPnsl36eQX/EXFVHLyIebu/w7qMhf/beNRLFJAsEutuHyLLK2+9f5+H2JmHgkkga4yhHrzQJY/jaN97i8fYOEz9gfWOD6XiErilUbRPLVEnDgLptUkQRC3NtJNUhiAUGA59xkNCdeIhWDS9X6BUKhyj0BZnYqRM5FRKniidrRKbNJMsI8gIvzShUjVxSEBWdXJDLGgcShaSSZWU2KZKTxCGaJFLkGWIRkSUhpi5TMQ00SSQNAzRBQhFAICcJA/zphJ3Hm+iKjCRAZ77NhbMXMDWTKIpQVZnAn3Du5DLe4Q4H927zhctPUhczTFIMRSSKynpYs9YscfdFfrxtyPOcS5cuHdfKRFFGKqBZrWGIIkUY0rBtWvUak8GQPP/k00s/IUEBREkhSGHiegRRQjQrshVAms1MTWb3Vh2bF198ntde+xRPP/0kcRz/GEPxKDgcm9V+DMgCHBvJHsE+j9iQSZL8WM9cEATyNOHhw3Xu3LlDNIv0SRTRbNVZWmzjexOioJQX53lRmqI2GoCI41Qx7QqiJKPqBpph0qg3ESSZHIF2e56DgwMkSUD8seJnGRh0vWQRpGlMGIbousl04uN7IVmcMe5HKLKFKMpMxkM8d8h0eoCppei6QKPRIAxjLMui2WxSrVZL3Fgcs7a2xmA04plnnmE6ddna2mJvbw/X9XEqVcZ+QpSVAfdzb7zOidUVHMNgMujT6bR5uL3HcOKzu7NFPJpybqGGLBR03RRzcYlEgDxKSN2IyWjMpcun6Cy3+S//yX9GmCusPHGZe1uHHEwCbj3YpVBtRl7EtVv3+dbb73Dn7n0qlQq3rl+lYWqc6rSoSDm4U/zhhKXWAoZmMuqPkASV4WCKqtvk1SbG6mlGuklflNl0Yw5zgbGi00MiNSt4hYhoV/FzmVw1yWSdIJcIUkAxUK0qMRLICkkuIskqcQ5JmiJLkMcBSRgShwFkaTnpmGYzebOMoZUg2fZ8izgK0DWVLEvwpy7D4ZA4TemP+iRpSNUyONXpYKYJDXIqEpgKhP50Rh8rD8epMp1OaTQaZHFCFidsbGxg2zaqoZOFMQ2rxuiwR6tSo2oa1G0LJQchyQjdv1vtw3+QoyhKqzhTN3AME1VSGY4DolwhLSCXZHzAT3NU3eAP/vXv02rW+fwbr6FqEkkSkyTlp7silfUIcYZzk2UVUZQRRZmjEeYoSkqYZSGXWgrKT2nXdWcRukAQSyfqNM1JswJ3GqLqJo5dZWF+EUGQyAsRRdcYdveI/QHepE8Y+siqguWYaKaKbtl4QUwhyEgzkEmSBNy+fZfRaESp/CxTPlkWCePSEDcOEypGlSLOsQ2d3a2HnDtzEl036fWnnDp1hqpTIfQmnFw+hRTZ2GqDgglPXzrPaNDDMSRkUvr7hzScelkwM0X62zusdOY47G4zGPc56Pdozy/yD37uZ0v9iKzjVDT+2T/7b7nYqrKsakgW5OmQL52/gKGaXHvvXV586RUWTp3i/bubZLlAy1JYsgySTGAiyrRXF6hXDH7hSz+Hqta4duMuve4+t27cZHnlBJXmHG4OA99Dkix8L+PAi3jv7jr/4t/8Ie2T5/jdL3+Ne9u7zJ9ao3NqmfZclXjcY77qMJr4rO/tU2u3ef973+b+3XXef+9DDg8G+EGCWW2SKDZTwaKoLTFJZW5uuNzc8+hrKmPD4CA3GchN7nsCDycF25FMD4vtSERZOol96jzK/BJae5VErqPZcyW1WZWQsgAh8VClFCVPkPOQ2O9TRGOk1MOWYoppHy12Sbw+rYqOIxdYM66EH4VMXLcU9sURRRwSjEaYiogpSxgIWIKMXshUK002NjaQxBzbkLBMmTiNSLKUSs3BjTyarRZ5nmMaNlKhIBYKsqjQNBqfeC3+REinoZi5GZd1g4pls3+wi6RqhG5MngvEWYooycR5TrvT4ed/9kvolkmBzMWL53n3vRtIkoAsq8fkpnKa0TpmJaiqeny+JBKLMx/Kckw6SaJjNaVpmiRpRBxGJKMRhmmy1z0gzXJe+tSn+PCjm1RtjZNnT7K9vc3a2goHvSELixau62JXyr17NA3QDZ1Wq4WulzZrE3eKH7j82Z/8Ma9/7vOlRiGISfMyU7DMsnWpyhIbDx5z7oknCf0xnbkqGxsbFOTYho2IgCKIyKJIHGRUK212t3cwDI1nXjqPosIP371P6OVIksh+d4MoypAynWqrQupP6O3sUKvVEJwW0yznL258hKrq6JLEo80paeLjKBKGJBKELo8eDXip0+b8Yo29QOCdd77LL/7Mp9nZynnwYIN6XWf39nucXrrIt67eoxu6nJgz+O3f+X3sSp1Hm9s06hZynnPj6jWeePIirXYVP4xxp1PW1k5gODa3rt9gaXGBq9fvImoif/n2e1y5egtvOubccpu1VptJGLPV7+PuZ2SChJ4JTAKP3b0D4sijUaswNzfHG298lp39faIgYr4icvmZi/xff/hlqu0aTm2OjXvrfOHTl9DEMdbcRbqjPqpRA8kkDBS8rketUmc66qJlIWoi0G7USWURrdZAFGX6wwEaOZqu4egqqiqTJhF5XNZTRFFEIsJSVASxIJcLEiEjTUoIS0ZEZmskFCRCOYBXCBBGIWQpgReyWLepdhr4nkuUSQiSglikGLJKHo8hiwnTHAkBMpEsSzBNnbxIEeW/Q+n0f7Cj+BGQ8mgYKUkiZEUCcvJZDaDZbPK5z30eSVLo9kb89r/6HWzbRlF+pG841izkOWkaH28hyv7/TIo9Q71/HNN2dF+apqUiLknK7CNJCMOYyWRCWuScfeIi12/c4cTZC7heQK3eZOx6SJLEaDRB1/XjOodhGLOtgD5DZ5XvI0kS2vNN7ty5iW7ISLJwPDxVFAJpmiEhIqAxHoYkMViWQ8V2WJhfpFZroUkyezu7pHGGP/V4vLlNoznHwtIy1WZGo6MSJSmN5hy1egWEDF1XUCWzBMMUAs+eO0FDAXd3k4oq4/s+m9s7jEeHPHG2zdUbt+h6ATvdHvPtRSZugRd6CHnE0EsxVIHJ7kPc3h5zFYn/6h/9DC+fW6b/+D5ykdBo1FAth6EX8Xi/xyuvvQ5pSrtZo+7YDHp95pot8jTl9o0bVG2H8XDA8vIyruvxeHsPp95k6Pk82tlH0AzCLEO2LXb6A9wk53AUIBg2qxeeYhpnCIZNXEi0l05w4859fuf3fp9vf/vb9A67aJrMo/WbGGLKnFmhu3OASMZaU+Ks7dPMd9i4+m0sYcJkdEAU+jgVi+Goj2ma7I8GaM0Gb155l8cDl+sbO3ywvsnGwGNn5LLZ7TNNMgZ+TKaamM02arWFh4xsmuQzJaOhaqiqQsWxkMQcTZYIw5gkSmlUa6iyilhQwlREmVOrywR+6eGpmTYJMppZwTTsktFomui2Q6FqBJKCJ6p0o5Q91yMoBNzsky/1n5ygQNmaLCihInmeo0oiiihwRF9Os5RWq0W/P8T1Q7769Tf57Oc+jyiKx6YsmqYhz4w5fhQM0hnZqUCSyt+nqDKK8iO2wtFxpJMXxPJnj4JMEHikaWnIIika5y89zcT16Q1HqIZJmuZ0FhY5ODggmUnSNM1AkctK8VFNoxyOEtA0lbUTSwhiwaVLl6jVqsfB5GiWIstS3InHuO9SsauM+gOiwKPf71OkBVmcoIgyo96INIHTp88xHrtQiIzGXVQ94tf/619mEuwwmvShUMjiDFks2N87ZHVxgd72JvOWxnKzwq1rH2IqKqZhYtertNpLfPmPv86fvXOFfpiSCyrnnnmK1Gqw1ffJgE6rhu1UUapNXDdjzYxoiR7JeMoTp1YZjUZMg5jT5y4gqRpfe/NNHEOnYmpUKxa72495/Pgxvp/w3OVn6R0e0mpWcd0BaydXSPOUMI2ptZqYtQoj1yNJ4aN797Hb84y8mIW1FfwE/u2f/wVmo8XA9cgVg2u37+LUmqQFJHGGNx3zg+9/yImzpxEFaFYEXnz+CXRdYG/zMXVBQDl4wFwMWx/+gKS7g+D3iIY7rDRUdh9dRzUN3nzrW5y+8CQf3r6H2WyTyQayXWOQCIwyhbu7fTLNYWfkc2PrkO/dfMDN3QEPui5TwWCYaey5KbHiEEoGqVIhl03atQ5KLjPtjhG8HLNQsCQdU5QZdQeo9TajXGCKjq/YvHPtDnd2emz1pmx0x2yOfDbHITtexsY0ZIjK1jTm8TRivfv3sCUJIopYoJJR0SSKLEHWDPy4IE5z4jwnLwSee+FZNFXFnU5YXl3DtCu8e+UHXHzyKdbvr6OqGkEYlVOL5EBJYjry8zvKII6p0ZJ8POEoSeLx9iKMgvJTXlIwdJU0iVEkkfX1+7z++mdoz88ThAGmacw8KBV83yeKEwzDptlooaoKWZoynbhkWYooCkRxuUXxAx/TtNB0k2ZrjmazXWo0Zm5ViqIiCgV54XJibY7FTpPJdESv32W+3eLUyZMYmkEUBdRrDWRRwzRsdM04bn0tLswx9Ue88tKLbG5uE3oZ8+0O7rRLEmfIqU/DVqnoOnkhM/ZCBn7ENArpLCxy69ZdTp29iB8X3Hr4CFEzBROkiQAAIABJREFUWFxcoVpv8dTrP8P1j67RdhSq7Q77gcjksMvLCxkGOXKlyb29MUGaUyCwub3L6dMn6TQsPvXC07z15jdZXF6iNxwzDUJUTcGbupi6Spj6eJ7Ly6+8RC6ULI3BaMj5ixeZTsdErsckDEkFkYdb+9TrLQb9AaZt0esP6Y/GMx9Qh5/+mZ+mVqsiUTAeDTnRXmPzcJ8H9w851Sm4c3udVqfF43tdznbm8MY+QZIgaFXCQmZz55DuYMBXv/41RpMRdqXBZ17/HEUh015cJkkLlpaXyfMC2aghaCZhmhEj4EcphaKTyTpoNiM/YxQm9NwQH4m9gcfjwxGTWGAcJGSSQCEpoKhUGk0ySWYaxez1BvgIPB6MGYUZ4zBlMPERNItYUhA0Bw8Zp7VId+wTihK5qiJpJma9SSKqCIrGlQ/e+/vUkoTSn0Egz8vUWjMMfN9FEAry/MjURaBer7OwsMDi0grXb9xha2uH3/iN3+D1118/pjsLcOyAHMelZ+HHOxMfB7keTTEedSaOAS1IpfIsDRHIcQyVyPdwJ2Me3F+n2+0iKiqKqhOEMYZlMhpPWVlZw3GcY7bDUY2j2+0ev44kjSiKDMuyOH36NOfOnePFF5/nF3/x5/mFX/g5nrz0BLajI4kphqpimjZpmlKrGiwvtRClnPX1ewA0Zrr/8XDCXKPD/FwHf+JSteo8XH9AkU5JiwFPPXUCVY1xJ/vIQk7VUrBtE1nV2Nza42C/y8E4RFNlDF3h8c52iUITFR4ddEEux87TOEQwK1y7eYtf+5VfZGVtlW9ducrhJEbQJeprF1lcmOcffOEzM1v7MkCvrS6SRx7tisGNa+8y13Q4PDxEMw0qtSq6aSLIAvuHe1QqVeI44YMPPmBrY5PNzU1kWWYyGbGz0yPKoFBU3vvoBtV6FV3RqdgO3W6fldVlHMc6nmj9zjvf5e6dewzHEyzL4sGtj0CSac3D6U6Dp5ZUPvPikwgq9GILef48/dTCFyvcfLDHKBXBnqOydo49P+Nb336HN7/+TX547SOSNOfrb36Vf/nb/wfv/uBt6nNNoiyns7SKKCtIioZmmKiGjahZ2J0FAlkl0228QiWzaojVOca5jK/ZPPR9HqcZN3p9fri9zbX9PQayyFCRmKoKlc4iiVAw166jyAJrJ5apNxrIpolZbfKD93/I0vICeTLFUXJMrWDQ75IJUDWVT7wSf4KCAmRFgVVxSPKcIAioVCpoWvlmRFEEIafZbDI3v0BnaZmzT5zj4oUn+eCDD9jb2/sxCfVRi/FoC3GkAzi6flRHOKpDlMKWsg5wBKpI05gkjJDJybOUZqOOIol85St/zJUrV8rXpciohkmclq95ZWXlOMiEQXQs1xbFUsRyVDfIsgzHrrK0uEKr1cK2bWRF4plnnuKzn/0Mr3/2VS5cPIPt6JCnBP6U8WRAmkVEocdgeEhv0EeUJIaDCaZp446njHsjyAWEIkFXDRyzjkDO0orOF37qIs26xMr8PJqqEMYRu4ddVs+cpTo3T7tRul6/9MJlWs0K3nTM3t4enZUF8iymokrUbR3fHRCP99lcv8UkTGnNLzI63EXWbP7p//rnnDh7gZ3Nh5iazrlzZzBNk93tbV545kmUzCOLfM6dP0u16vDM5ctYFQfLMfE8j1Z7nitXbjDfXmHr8QF7e0PWVk8zHk7IkpyabWIaDn4QISsKw+EYdzTmxPIKly89SRT4yKKAIMLLL79c/j/mBY5dZW/vgF/4wgskqcdzz79AMfJYUAXS8R4HI/jz795gYzzh+Tc+Q3fSR5ALJpMR2wf7hJmEoDq0OgtU2212e4d85f/5U1ZOLfPyq88zHO/zz/+3/4XE8zBlkVbFIQmn5SyDIqPJMqKQY1kGpmMiKgU5WUl71g1E3USy66SCglFpYlabzC+sMhgHVBpzGJUao+mQC2dWmXckLqzWWKhKZMEQVUiJfZ+nL5ylqsRoYY+nV6v81EvnSUfbfOdrX0EN/0acyb93/ERtH2RyTi+3IXFxLBNBKifW4jQnzjIKsbSSb7QayJLMfGcBURKwTB3bcXjnnXeIo9LKvpw4E8hnC/zjBrNHo9Dl+bLwVxYCOTasTZIEw9CwFJlmo8aJtWUOD3Zo1KsMBwMePHrAa6+9hqHrFDkzZWTGztYOZ86cJYlLNFwcxQhiCfowTIMgDEiSlCzPsEyHLC+fW9UMFpeWESWRxaVFWo06O4/XmU4PabcdesMdCiGjyEtzXNtyiLKcNI6pVmostpd4cH+dhYU2/cN90iLhucsvcPv2I2zHJIgGVOoaX/zsF3nvB9dot1rEoY9lOYymEdce7DHfaRFEAVEUMJmMCNwY151yYnWZYXeXz73yAk+sLbK60Obh3VuMRlNu3dug2x/SrNqsra4yTjKacY/1xwdc25mAZiAVOa1WHUtT+dJnXyHLMr78p+/x5DMX6Q0GaLrOeOpDEqGRUzUtRp7L2qlTTN0JZCDLOuF0iilLiLLCbreLbhjEYUoY+Jw6sYLnTzjs9Tgc9LBNC3c0xdA1slwgSVKqlsjT8/Dh/X3eufKQX/vUGQp3wijLOHGugyjLGA0Lw7F4/sUXOOz3mWt3eLy1TX84YjQcoesKhSDSG/Y5ODig2z3g0cYDJtMJaVywsfGA99//PrapcOV738cPfGrVCoeH+0ThlJX5FpE/Zv3eHTrtOZr1KrahlhL2/oDN++ucP3kaA5EijtBmysvvf/cdBCFi59FdXnnuIlnkcuXK93j77e9y8uRJWo0K3//2myy2HFbnq7jDA/7tl/+QNI4QhIyou8P1neEn2j78xAQFXRaQ84KWLaEQo2oKcZGTFDmyKEEBYZwRxAlPPv08KydWCXyPmzc+QlFkBoM+k/GY7uEhAEVezDoa0qyCKTADKszGmPOZU1TZrkuSGN1QiaIQxzFJs5hWo4GtS7z++qucOLmIYUgURcyZM6dQJYUP3/+AV199lX6vi2no2KaJIIglTVlVEZUSMitLEvLMrj4rSvNWRLmcgJRUNM2k2WpRrdaoVWuIgsD21gbvfu+b1GsyOS7oIma1QhDnLM51kCWRaTgljXIUUSXwXJyqwcQf01ldwLbq3LpxB8uxyUjY7e2TCOB5LlEw4vTcCrJm8uHtDdAsZF1hMhlQtTSi6YQ8KUqAR5ozHvVQ8oKVZpU7736PBUentXQCQa+xuFbKrU+dOoGhqXzw4Q3ONQ1u7ozZ8FTSLEOIPXIEPvzoDh9dv83e9h6DQiYpBE4vtRmNRgzHPmrk8auvP8v+/bvEusz2aB/yiCLKkVGZMwQunZnncd/FC0LStGB1bQ1BgnqziWqYPNjcRdAgjQsaisPO3gYrT77AvbsbtOjyyimD3qiGpvV59bxIb5BjLp1Czl28sUxaW+S9a/e4t7FHjEpn5QSDsU8UpwRhxOLSPGmeMp5OuHDhAnGUMZ2EhGFZvA6jgAsXztHpdOj2ezx+vEGSlh8Yw94BD259xP1bV7l5/TYLC3NMJwPu3nofSYz5xve+RRZMcdSCnQc32du8T71u4AcDev1tPvXaS6iGwVvf+x6SbbLbH1Ag8eH7N9nbvMbFCycoFJ0//fo3ePud97Fti4WFNuN+j4WVU7x/b/PvV1DI8oK5uo1aJKikCHmCaTkEYYAi6bhhSJzlJFnBhx9dY3F+HkmEOAqpViukacqlS0/x9nfeIcuOAoIwU1DmsyxARJYl8jybLVyFXABBEkmTCFkW8TyXWtWm4tg89+xlDE1ivjPHa595lc5Ch7xIOXX6NBcuPkk+qwusrCzhOFbJ9nc9NK20Ilc1HfISAJOlGWmakGUzh+lCIEliJFGhQEJWNFRNJ0lSdnd3eec73yQJB0TxmHrLJAg9pr6PJCpUrSpxkuEFCbZhEccJ4/GY7Z1tDNOg3x8iZAIgM+iWWob6XIM0LciinAvnLnHn7l02tzeJ4oIsixHygiROkBWFyTSi2aiTFuCHMZIosdiZ4+oHd6hYCqfOnKW2uMJ33/uQVBTQDI3RoMcPf/gBv/wf/RKj4ZDDVGNjGOG6Y2xTxrZssjwn9jzqzTqT0YRf+dk3uH/nI27d28R26jAd4cRDmlaT+3t9DEvnwtIci1WLqm0hqTlu5BNkCqqugyDOpjNP4Po+lWqFyI1wpy5FWlC3bZyaxr0Hd3jpwin+6X/x08jTAx7sZui2yMm6xs5ujLywSk7KdjfivfuP8MOI0WjKU5efJSsKVN3io1u3MTSVNC2nYXf3+rjTEZ1OmxNrJ5FEEVGSGY2n7OwcYFkaL738MqPxmN5gyOFhl3qtWs5ZPHGGMIp4sLnJxuPHnDp1gt3dHVZPrtHb26HTaKIIBU8+eYHVtVVu3L7J2fPn2dk75P69B8y157h27SqNRoPhyKWzsETdsalUHKq2SVUTePmpVT733EX6j+7AdMDm1g6PJtnft0IjJUzCKqGUjm0R+ROqlkEeBziGjpgXyAK4ozG/97v/ije/9nXev/Iunhdw79562Y782DjzkdrxR246xY91HgCSLCVOI3IhJwx9alWTPIv49KvP88ylc1x+9ikuX34a3/doNuu88cYbNBp1OgstPv/5N9jb28KpGERxcNx6VBQFgVkAKkrGQ05BIYhomoFp2miqQRKWcvBCFIhn7c7NR4+YDgcszc+hkVGrlD4OlUqFztwSFbPK9u4BORKOXStT98YcolzyC0tUWZ0kybC1/7e99w6y5DgPPH9ZVc97295Mm7E9BjMDDAhDAiAhgQSNDCWR4krihVbc29Vd6G4vtCfGRexppeVFKPaC1GmDsSutuKK44sosKQkURZEECZDEwLvxMz3tfT/vbZm8P+p1T/dgBhiIpGYQ8X4RL96rzHxVX2ZVfpVZ9eX3efF57KjcjXoTRdPoGeynabaYuvcgB05OMrQniM8n+MBPPoyqKISCUYQiMHUDU28Rj4WwLIvl1XU8QRebpToXZpZ44oknmJ+f5d6TJ2hWyywvzjMwMMD5i5d4ZnqdvHQTigXwehxMTU2RKxQoFKsIzcF9Dz/KR953N6Xlizgt2+luo1LlxIFRkj4Xht5m7/gkEW+IPq/KsUE/srxMoZAnVaoyMTFBoVDA5w/i8fpZWFwmk80zO7eAailo0n5OtFlII1XBiakJegKSUnoNU7cwG1UsU6XQcFKyPPz90y/Rt3eKgmlRqrfxRxI4fD6uLsyRyWXpH+hlsDeJ5lAY37OHRqNBKOAiEomwurpKq91gbGyUlc00fUP9BKN+llfXuTR9BVQFt9dD22iRLZaYW1rmmeeeZ8/kXhSnk97BIc5cuMjl6ausLi2TThdxez2M79tLQ2/z/MuvMDo6RiaTY3ZuEdNSyOVLeH0BWm0DRVN49rmXmBgbJ5/K8M2vfYWekEqPz8Td3mQ0IHn3/mFCXv8t98MfJu7DF4UQC0KIM53PsU66EEL8QSfuwzkhxPFbEUTVFDK5LLplEYnEcLlcREJ+9EYVl1MDQycaDqC37ai6DlVjY22FUqnE5z77//HyS6/yxS9+cZdS6MizvTBqy3Bo6+Fio90C9doDx1g8yqGD+xno6+HI1BTDIwOcOnUKt9tNMplkeHiYwcFBjh07QiIRx+N1MXX4AKZpEAoFkVISCoVQFQ1dtz1DNfUmpjS2Y06gCHTTsle6OT2204wt1/VSEvS78Xs09HoZU6/jcmuYmOi6ycbyGtFAhEZDZ3Z+ib7kIMlkL0IFS0qSvX3Uag3cbq89cvE4ODy1l4DXw/jEKD6/k0azTK6U5qVLLyHcBvEeP9GIi5nZC5w6dcJWkq1OWPaGTk8iTrtlEEskifX00TM8zrmrC+j1Ng+cPInWbpL0e/jQT7yXvWNjZNNZYoMjZNKrRKjyyY9+gHajxsmTJ5FAuGeQF147x8lDE2itInqjjq6bRIJB0msr7N2/j8VCmZVsiWAoyvrCCvXMBlZVR1OcBINJnn76+3i8XtZWV3H7/CQSPRw6dIj9+w/StBroZhtLWNQxcQWjXDp7kaFEHAwnr5ybIRT04nT4md9o8p0z6wxMHubJ515jYP8UxXob3VLQ3F47/FujwaUL5wmF/bzngQc4cfxuBgeHefzxx1FVlVqtzvr6OgsLC8TiEXz+AIcOH6ZQKjK/sIDmcPDggw8SiUWp1KocPXaMPeOTXJyeRvN42MhkCUbiBOMJqvU2/nCAv/vWk3zn9PNcXlplcSPFf/wvf87iyjrSUimVKmxuZNl34CB+v59Dhw7hcMGlM6/zM4+/n0TYT9CjUsimWZqfozfZRy5XxOny3rJSuBUz5624D1UhhAM4LYT4h07eb0opv3Jd+fcDk53PKeA/db5virtjB2AYBoZuB7MwTROHpuBxu6gV6miqxvEjR3jt4lWyhTJOp+1cM5PJMDm5l/n5ue1I0ZbVREqB6ESV2lIGdsh62+Pzlo1CNBohkYjhcmqcOHqYRr3KQF8Pe8ZG6IkncDqdFIt5Bgb77AbTNCqVCoFA2N5WnbTaDTweLwIVw2CXlaRDc+FyOFCw4wYoqoaJpNm275B6xyG2Kk0Mo4FRL5JZnmZz+artm1IB3TJRFIVYKMrm2ib9Pf3Mryxw+fJlXG6VTGaDiYkJMO2FZariIl1axq062dxc5/iJY6wV1snn0qgoJEK9DI0O4VI0NCQPPnAv//nzf80nP/luVjfX8QecBAIBNIeLB991Lxcuz6EKSGfz1Ot1nFJSy5YYHhrDoetkF+cxqyUeeORRypUmL519FUo1HrlnDxeffZJMA1bOXcECcuUaV+cXuCuqMzm+lzNLL2NYkvc99CCZi8/z0uU52rEEpaLO5tmLfGAqQaVaxu33oDtDeHxRTBYA8Po9jI+OsLiwQE88Rr1aJdYbJZXdoGWYvO/Dj7NwdZ5jh47yp3/xFA8fijPeP061LOntH6eYWmJg7yjL+SpOtY2XMr5gkHQhR6NWZbC/n6XVaWLROHefuocLly6ztrbGysoKgYCPcrFIKBCgWa/RrtfYf+QuZuYXuHRpmr3jA6Q21rc9JWVSacbG96G5VMqVIqfuvZcXXz9Poq8ft6bi9Xq5dOkqI0ODFESG+c0MWjDEWq6MPxqk1pYM9cV46aVF7r77ON976vs88si7+Zu/eYJHHr6f1toyT/zNVyjmyqyn8+zpHeLVZ07zyqspEskEZrVwC13d5oeJ+3AzPgJ8qfO/F7AdvPa92TG21pw3anrndaLVCWhRo9VqEA0HURRwuRzEYhHcPg8ulwtfMECt1ubChUsYhonH4+kogmuu1q6PVr217XQ6Cfr9+H0efvpDH+Zf/PNf495772NgYIAHH3yQ8bFJkr399A0M0T84SjCUJBLtw0LDF4gQCEXwB6NEIglcTh/BQBSXy0Or1bI9MTmdHcMoDWkBQsHpcm+/BWk0Gri9LizLpNmsUyxkWF+a4+r5F1mZOYOHGhLbi0+lXiMYDFPK5jGqLSKhMA8++CB9PQnC4SBCk+RLWV5+7WXi8SRtHaKxJMneHlq6yVPf/R7ZzSyJaJz9+w6yuryC0bKo1Wr4on4uL10CLzzx9b9kZXWVnmSYfL6IwOIbX3+CieEE+Wwar9eN2+vB6fXh9nhIb2wyM32RT3zs5zm4f5JSqcSFK9P0JxP8x9/9X0ioDd5z8jDpVAW324MQ4HI7uPvuu2mZgh+8dBZT8xMJx/iHv/879h45wfMzmywVipSqFR554BQn7z5FumaiBpMMDE9Qr1Xx+t00m03q1RrSspcZXzj7Kocmx5ifn8EwLE6eOMra2hoOxcXxw/v5z//h19lzYD9/+4M5qqZgbj3Fel3najqNwx8i2TtCMJrk1D0n7aArHie1WoWeeJxmq069XscwDOZn5wF4/vQLJBIJKpUKyWSSSCTCK6+8xvr6Jh63g3g0QW+yj4Dfz/SVS/zixz7O0tIS6+vrXLk8z8zMHIFQmLX1FLppkc0X+NDjH0QVAo/fx8T+fUwdu4tSrbrtbj4ei3DwwF6efup7JOMJHnn4YTJpg6DPj8vjYnp2loNH7+IfnrzIX33tGaqmF2csQboh2T8cf6uuvs0tPVMQQqhCiDNAGttH44udrM90pgifE0K4OmnbcR867IwJceP9IxkZ7kMCjVYbC9ANE0VzEgxH7Ll+JEgqvQEqoEjK1RK1RhW3z4Gi2D4LWq12RxHwBqWw8/c1ByuSe0+eIJmIMTw0xJ6RUQ4cOMS+A4eIJ3oJR+K4XF683gCGIQEVaSlIS0FT3fi8to/GSDiOw+HC6XQDdJST7eLL7faiOOz1+aZp0jZ1avUybrdtAelyOxCKRaNWZn7mAqnlGTS9jKLbaylMCzSHi4DPz7Gpw4T8ATZWljl/9owduUmVuD32FGNi7yRnzp1n5uoCFy9d5dL0AqrmYaB/lFy6wpWLc8xenuf4sZMUshXm5pZIZVNofpX7HxnnyN37OHS4F6G2MU2TfD6Pz+0iGvTRE4sQCQVoNpvUmg3WKw1qZpuZ+RlaZoOzl87xh1/8AuVmnWyhjiJhfKCfWDhOMBxEKBpep0C2qywvLnHu0hyZhqDQVmzHJyr88Zf/B7GJKYYGRpjoTVBZW+byxUuYviBGMMorl89Sq+dts2qHbWl65cJZRgf7Cbg0Xnr2e1gWOHDiNKEnFCLm97MyfRYhs4xO9GJ43aSrVTbLFaQ3iO7QWFhaIZspkdrMUCnnOXRwH7FwmEymgNPpIB6P8dxzp8nn851l8eD3+1heXmZwsJ9EMoaUJq1mCwXwe7y8/tpZyuUyioRGtcH3n36a3mQPqyvr7NkzTE9PH5VKjVgsQX/fAIVcnldOf5+Qz0XI5yKbXuXcmZcoF8oM9MQ4uG+cxYVZFCQ/99MfZnVpmcW5eR44tY9nvv8D0Jz0jY6xmi4yPDaM5gyA6qdYrSOFSq1euZWuDvwj4z4IIaaATwP7gbuBKLYjV7uP32AX1yfsjPvQ1g2cmoLLacesMCW4vB6EUFGEisOhYoeG13E4NN776Pu474F34fN5mBzbgyJBGia1ctV2RqKIjpt3/Q3xIh0OB35vgIDPj0NVqJfLVMsVjLZOOBzh8NRRfL4AgUgUly+IQ/Pg9fhpNptkU5s0a/WOt+U6DocLRTgJh+NIS8HldONyugkGg+h6C9OQKKoDRWjbhlOtdoN8PkupmKfaqJNOp1lbmie9toQw6ihmk0Yli2U2cfn8lCplVFXF5XTTbBiUK1VWV9dxO9xgCSzdopSv4kBjz8gY73nPwzz8vvfy0MM/CUIjEkvg8vro7R1gZGCMiT37aNR1eqJJIsEI9WaLqzMz+EI+AlEvd506hKm0MFXJ8PAgk3vGcHZeq+bzOTTNHrHtn+zD7ZRcmkvxO7/3WdY2UkTDfiyrSSqb4jOf/Txnphf487/+GqZmW4laLcmRgwcYGewh1tOPNxRjz+g4mhD4AyEC8SSq20/Q4SLhdbK5vEGt0WSz0uTS4hL5SolQJEg0EsLpdOLxeHBoKs1GhQ++/yfYO7EHLBgdGkY1JRF/kFJmg4DT4twrz/KDH3yLULIXy+3DUATL6TQb2TJOl8aRw8fw+/24XC5y6QxDg/1MjPbzvvc+TKvV2jZmCwT8aJqDYrlGs2niDwao1+sMDg7idDlxaCqaEGimZKy/j3I2h9fr5tXz0yiKwoc/8kEuX12mXC7jcTqo1ypoLidTU1PEYxEsU+fx9/8ERqtOPrPJQI8flyIYSMQZHxnGqSmUSgXGx8d54ftPcfLQBF6nk1y5RrVlUay1cLi8nDxxLx/64AdIRsPUyllapnV9F/zhlMJ2z74W9+ExKeVGZ4rQAv6Ea05ct+M+dNgZE2LnvrbjPiBhPbOBDrRMiappbKTTpNNZ8pkqCInXqREJ+XG6Xfzg+WdYXFtBmhbVYoH7Th1ndKifWNiP0nGBbUoD4dBQFZcd30GagIXZ0gn7PcR9TgbDTqzqJrnNRQzDwOX2Mjw8TMAfwuX2kStVKNWqrG4sUa2kyGbmWVu9zGsvP0M+vUmlWABVQXG4MXGgSw1fKIrD4cI0TSrVEkiTZquOJSCdTlOvVKmXS5QLaQqFHOtLM6QXL7Nw9jS19VlkvYDb6UBxuJhPpYmEYqzPLHPxzBV8kQQDYwcJePsopJuk1kpsLlTxyR5yyzVeefZ1nnn6Wf7bl/47SzNLuJ0u2lqT5cwi45N7CHsiNMoNvG43LavJwakphnpGcAkf2c0Cdb3JTHqWez5wFz/3rz5IurBIaXMJpd2i1WoQikboSyQ5OXWIhN/BxGCUgBcahgtVuvmXH/0Iz/zp7/PpX/sAtZbkB+dWuf/RnyBTLeD1OHEAL52dplJM8dBD7+K+4wfYuPIi40MJGkJlYSPNwsxVFmeuYjarfPLXfomNJpiOMO1am75kH9NX54gEXTSrFcxmG4cquPfUSV5++UW++pW/wSUt9g15OTIWZ+nCGeIhN+cuzfHzv/ibpDMmuVyKtUKDTK6CqvoYGxwgu77Gt7/7bY4enCSVzbGZyZBO5djczPD0d77Hvom9hEIh9u2bJBD08OhPvh8TcPo9zC0u4HQ6yWQyHDiwj4DXgYcW/+Jjj2MWNuiPBnE7PaAqvPjaGS5fmSUQdHHuzOvsHe2nsDKHH4P+ZA/Pv36FasPgT/7rn6GpLjxOH4enjnP5ylUioQg90TjVSpkzZ15H13V+4Sfup19mCbok6XyZtVSGSCTC+voa9UaZ//4XX2ZoZBjV5eTjH/+FH51SuEnchytbzwk6cSJ/CrjQ+cvXgF/uvIW4FyhJKTfe7BhSSsLhML6Ak3qzYdvDB1w4NZBmG8swERJyqQyaohKLRDuRfyV79+7FNBqcOH6Ywf4eIiEfpm7iUDXMlrHr9aNQIBLygV4jEXGydzROT0Swf3wAj1fD7fXg9vgRQqNWrlHJFSjm0zTqFYr5PBKTRq2CYumsrMywsbpMtVrGkiYto22HMHM6EZqKJaBSKVFfXMeVAAAgAElEQVQs5tH1Fpbexh/wkc1m7ZBe5RqlfIZKZp3i5gJWLU+7VqDdbtG2BKVmE7fLQbPe4J6Tp7j/nndx/sx5sqksPl+Axx79SS5dnGHf3immr8zTbkkS8QGq5Toep49spoCiukhtZjlx/BRXp+eo1GsITeX5l19geHSYeqvG6sY6fX19KIodG3F8ZJhqKYvZynH3qQncIR2Hv0WzXSXk86IZKsX1AqWqzulXLhP0+/BIAyz4g8/+EX/wf/8bJn1tPvWh+xj1u3n+20/S5/MR9vpxKRCPeAkFgnzpS3+Bx+WkJxGhrydmP1CV4AkHKRs66UqdVy9eweMJ06jViUXDCCF5zyMPg9Tw++0Yk2Oje/jG154gu77OJ37hZ3nsvqMUZ87SWj7LoKdNq1pkswnv/fhvsFDSmZw6gtcfpK3bth2FYo5oNMyBQwd57rnnOHH0BO995FHG9u+n2NYJ9vbwzPMvIE2FoDfI8soGf/f1bxKOxKlUG/j8QVLZAuV6i/vuuYdD+/bRbOk8+cxzLGeqzCyvUyqVOHxwEo/Xx4uvncc0FD7xC7/I4fFJ7j92hPrmGkq1wK98/COsryzSqNcpF2tIqXLk6F34IiE+8//+Pn/513/NudeniQV9DPcl+YPPfp5EJIqr460rFosQjYbp6eslW64S6R/B3zNEfHgPf/nNF9+sC749pcDN4z58WQhxHjgPxIF/3yn/DWAemAX+C/Cv3lIIReDyOhkYHqDekjSbBvFYDL/PRSjkIRIKYBltysUiQa+PaChMIBDgnnvuQdM0NFVy8cIZ/H4nE+Oj9CQimB0HrfYTC8VeLylAERb9PWFcNBB6jt5IgEg4aEeFcripNltsbKyRXl+lVs5QKWZQLB1Db9jLuKVBJOxHmE1WV2YoV4rQiThdKhdomwZ6Z91FvVohn82Q3tyg0ayTzdqRpNY21tFNA4c0iYe8uGSbeMAF7RbtdptMsUpbOojFYvh8PpKxJCtLqzRqTQq5In09vZw/f57x8XE20ik8vgAOl4fz58/Tk0iiKYLZ2XlyuSKRcIwzZ86iKBoet4+N1CbD4yOU6mXbGYzfNoxKxuP09yQpF/O0Gk0UdBSPwV0PHWVoqof+sQCVegaPS0EREs3rB1eAZr2B0TJpVevoLWhsVlCzCyipORKKwWQ0ymjASz2bw5KAXmNxcYmJfZN86ztPUarVefqZ06TzOXr6e1hYXsLld1Ntt1nazLG4lqLRaBGNRujrTfLMs6cplqt24NxyhUqpyNTB/UTDQR44dYrq5irvuXuKd9+1H7+sMtQbZezQMXSPh0j/CJrbiyktHE6VRDLG+J5Re5GXEAwNDRH0+fmHb34H6XAxfugQDRMefvQxAoGQHcKv1WJodIR6o4XH46VYLDO/uIpuSL74J18gm05TrhtsFGuMTx1mYHSMX/7kL5FLbxDwuwn6/VTqDb7y1a9SqdaIRuIcnpqiL5lkff4yDxw/gkda/MKHf5rpC7P87d98FadLMH5gCOF0c889B7jvnhMM9PXyMz/zYV4/c46hkTE0RVAuFQn6fZQqZQpNnYsL67xw/gpXVzZxJYZvWSn8MHEfHrlJeQn8+i1LgP3AoVwtkYj7MIHNVJrBeB+JeARpKeRLRRyah6DHw+LsNN5kL4lYnGKxSDWfxedW8fu99lP8Yp5oOMhGqgBbXqEBECjA6PAg1WKKodEII71+/O4IesPE6/bRbjY488rzyFYZp2piGi1cLhd6s4GqSRr1NlKaWEYLvVXHsBoszk8Ti4VpNSrkc0XC4TDS5bKDdJgt2q0apWKFWqVs2yjoOsVikXK5RG51nuzKPEHVIOpzgKLSlgqbuQJNRcVhGihqmEIuT1+yjwtnpmm1CuRyGaaO7qet11hfr1IsZfnAB9/L7JxGIVtgdKiXSjnIfQ/cT6GaY6C/n2qpimKBWbEo1cusrqXoSSTJZDJMjI0yPz9PMOQnGA7gUFRW11OoDgd5vUhTqzN5ZJCgu4e//6vvMZjoYW4+RTTZQ48/yUhPP6+emSYeUvjg46fYO+hl6cJp+qMRMo0WVibHWP846/kCA8kYKy2LSr1NXVdIlZrEBkfwuQKsrW8ScDsJOiws1Y3idJEtlhkcHERToFAoMDw0imGpmKa90G1ldYnNlauMDw3zvaefJp9J8+5P/jx//Pnfxx0IoyA5cPAg569eJdEbx+t1Yxht4tEIDz3wLl599RUy0qBYyDK25yS6Lrjn3lN849vf5p777uc733ySB3/jAYx6k7m5Gf7lL/8Kn/vs5wmHAvT0xpi+fIFQKIDb7SYUCJMvlvEGA0xMTFCq1DBMky99+c/w+3040MnXqzg0Qa5S4Q//9L8R9PqQLhftWgknbTya5GM/9SH+9q++zEDcx+H9Y3jCHgxUNDVM0m1x+jvfYurYSVSHiS/WS2GlTrK3j42VJVyaIJ1OcWUxxdDoCFdWNjh+6CCvXbx8y/3xjjBz/sxnfve3XT4Tw7SwmiaiqRMLOYgGHQhhommOjqlzi2qzzeG7jpMvFmjU67gdDlZXlgmHQ/zap/45G5ubLC+v0jYM2m3D9hQvACGRlqScz+HVJKMDEdxai0bdQSiapFypMjd9kXp2lWZxlVxqnoWZi5jtJppiobd1Crk8TpebZr1Os1Wn1WyjOdyUigV0Q2d2ZgaPx41l6rQadVrNKunUBvVGjXw+j2VY5PJZfH4v1WqVqxcu4HI6WVtZpVxtUKq1KbZMctUWoXiSlc1V9k6O4/N4CAXCjI9PEoqG0VwKq5uL7BkbIRyOEomEaDQqLC5c5eCBfVQqBY4cPMLqxgr5QobZqzOoUiGdThMI+am2q6jY6yWSiQShYIBWu0UgGGBlbR0pFFTNhz/oZWZ+hmAo0PFY3SSeDBJOhigUCpQKFWhX7eW5lsDlAI9Tw5Q6Vy6vk+wdolhY5/jRUfr3HGB6KQ1mhY/9/M+zsrqCPxSmLTSapoJA4JQGzUyRAz1eSuUy1YZJpVanr7+XaqVIu9WgWqvj94WJxeKYehNNhbGRQfRmC6fLw6GxPnQcvHhhjpG9B/nuD14lW60QjEZRrBbhcJy1tVUG+3pZWZwlHPSzb+843/7Wc6jCYHp+kc1clgff8zCzs/MYps7C7Cz33XsvA/19PPHE1/B5fOh6k4MH9rKxukRfMkGt2iCeSJAvFClVa3zwwx/CsAxS2RRur49arc7RIweZX1xHdSqoThcmgoauc+7iNPv27eXeu6Yo5Qusrizx/sceJR4LEo7YznY3N3MsLC6TXbjI3VP76ekf4vlnvo/P5+H12RQBv58j+yco5TLcfeo+ekb2sLSZpVQq4ndrmJbJQuodtCDqd37n3/224rEIBIKUsjVcAsaGYvjcEqROq9lCotLWLRqmREdQqpZptZsUsnmOHz/J5enLfPNb30TXDTz+AOVak1bbQEiJxI4cJC0wDUl/PMT4UBK3ZhLx+9FUgUsxaBU2ySxcZOXqWTYXrqJYOqZhoCDI5wsoqoaiqmRzWdq6gWUYSAmZbBrT0Cnk8zTqNTxuF5VSiXq9SC6XpV6v02y2saTt2u3SpcvMz89htHRmZhcxLZVSXcd0eKm3JQ63n96BAXCBgsWzp18mGg3icbvIFrN4gk5KlRyH9x+m1bZ46unTtJp1xveM0NMTx606KZeLtNo1LGmSjMd56smX2Ts5wtLqElKzaJWbbKxnOXzwAPV6neXlJVBVNKdGpVrFoTpQpIWGROoGvdE4iXgMh9eJcDsZH+3l8fcdZ2AgSbnWopgvYknJpfk8r15OkUjEWF7d5NjhUZIBk9m1PFc2atTyVTxKg3Q6hTcYJl9tUKk18EgTq7jJgBNODEc4dOQuvv/KFZJDfUQiIR5978OEAgEunr9MtW7bDQwM9vPoow9x9eplWm3bQe89+/r4wz/7KtMFi7PTq8STAY6cuBtvMIxpmtRrdRyaitGqo7fqPHDfKQJ+H/e/6y5eee1V6m2TfXsPsLGxSSQcxet0E/B7yWQ3yWbTHJ06zNLiPO1mg2o5y8H9k6gIZueXcftD1JsGTk1lbvYqfX09nDh5kldeO4MpFJbmFxndM0Kt0QZVo9XWsQyD/p4o05cvMTu3SKXWwOfzcfbsa/ziL32CL3zxS2xs5hCKg3Ypz/GRGBuzF1hcWWegN0alVOD0pSyDvVGGehIc3L+X6bkFnnr2FUqNFu9/7FGGesJYUuHC/Oo7Ryn8+8/87m8n+lzUGy1kW8VpSiZGYnidOgoGzbaBrpu0DGhJwWo6w+j4ONlslma9yfLCCslknKNHD5NI9pArltANk0KhgqqomJZpL5AUDjQBtBr4nBZuh8lIbxC3C1ZmL1NJr7B8+SylzTWifj/lUgmnz0c+lyMQDDG7sEi7bdjLpE0LUzdRFUmlWqFWq1OvNzp+GE070IhiUSoVqVbrODUHpXKZ1dVVLl26xNWr01w4O49QBZl8mVrLolBuojo9NHWdZF8P4/v3EI9HiceDHJk6hD8QoGcgidursbq+wuZqDqfTz0MPPUIkEmJ+bobVxWWWl5YZHhxkcWmBqcMHbcV5+BATExNk8hmC8SAOy8H42AjtZpNyuUj/QB9CUTGBWDSKE5NwMIDRaBLxBAi7g+SzRdbSmyT6+6mXNmgV1/D4ArgDSbxON7NzWbRoiJrZwtQh6AswEBdEPU2eO7dGzgrgc+oMx9wIIchVqrRMQbvRwCjluX/fCO87NoaZW2UlXWKjVscXj+N0qGysruJSnZRKVQZGhlldXcHtcpFKr9FsNnC73BiG5IF9cc4trlPzD7Pv8BF8Lo29+/eTLdWYnl9keKCPbGqDxx97lPHhAaRpx5/M53IIVUPzBvnOU8/Ql4xjmeB1OgmHArT1FooqqRSK9CZ76IlHWV2YRVgGrXoDqRukS00aug7SYOrQPrBMUpkUI2PjaC4vPq+f9fUMXl+AfC6PS0giPid+B5SLbdLVFqlcFSlb7DswyfdPn+bQ1F20LI3z5y4Tc7Y4MRrjA488QCqT5eD+vdTrZQ7cfYKrV2Y5dewwVy6cZ3ltHekOsriRojce45Vnvkup3majWHvnKIX/8Ln/57f3nhgnFupn7uIKfk1ybF8fqplDk00aDQftNkjhoVzTcXtCxJJ9rKxvgKpyeOoga2trWBIuTU8jTYlhtPG4NMrVTgwHBBITS0oCATd6rUjI7URpVGgUy/hUjfzmBh6nk2a7hY6k0WrSbuu0miapTJknnzpNraajqKr9HKHdJJPO0mq1kYZEb7dxupxomgO3242htzoLZgwUVWXm6iJXr85TrRksLqZoGCbFmk7LENR1qDXa1JtNhKZy/PghMHMUcmlGR4a5dPkyl6avkM7kkJZCs6mzvLJCIOgjndpAmm0mx8cplSsEA0FWVjfwBSIkEwNEIj1s5lKcvXQGf8iJtFrIlobeMqjXaui6TmpjnaDfR8jvIRoKI02BbBtoSDBs+VfWN/D6/CRifbRKTQrZEpZlEQ54CEfdxAd9nLzvGHvGe2nLCqOTg5ybucpyvokzGKeQz5II+dm7fy/ZusVqpky5ViPhVflf/9ljhM0N4q4GmsvPCxdTZFsKnqCLci6DigvF6aatWmyupxCWjsPSaddrhPx+/P4wfQOD/MUT36J39AA+r4egRyMRi9Co1UhvrqOYBtXMGoo06e0dIJLopVpvIoWKkBZ6q4FD1bCMFhevzNPTG2d1fRXLMHA6FDKpFEf276eYT3HvqeP4Ax5iPX3gcOGKxqg26ximDkJhbT1FMBRn3/ik7WrfpXHk0BSbKwvkUxlOTQ3zyz/9OC6rweRwHz2JIC3hpt2s23EhckVmZ7M4FJ2gx8HP/NQH2FxeY7AnwfriLMcPH2J5eY2a5Waz0OTy0ioL6RzOcJxCo02hXMKpqoSDXqqNFvW2Tr7WviWlcEe4eBfCthJ0O22vzHacBxcSL0bbIhD20SrWaJRKSGnQahlcPP8iXp+HZkvnhZdeZHJyEn84QntlDYdTMjQ0RLVapVhu0Wy2UVQVAfj8PtKFCtF+F6rTx/CoG68rwMrcBmaryfpGiWjPEKlMmbph4jRqlOsVsuU2Ld3BeqrI4OgYqVSJeDJANbWKQEUquh2hWnjQTQeoLqrlGhubWTweL4VijdfPnKXZtlBUJw3dxBIACm1TYOl22DLZNJGlGpYFY0O9rGKytrpMKrVBf/8g6WwOaVmsLq9x14ljZLNZYtEoLoeTpfVlvH4Pfr8ftz/K1elFTt4TZ3Z2llS6gmE4UFQfzVaFcqlENBomnU4zPjGCy6USiUTweBxks0WSiXFWFmYZ6h/gyqWLHO0dp9pYZnhyD6n1HO1GG1cggj8YoFLNoThdRHvCpHLLHDp0CM1lcP71Mzz8/vdRzpdZXFjjxLsO0WyZXNlc4emXlxgaDBORCo5yBXN5hXithVMXVAhRsxyoLgf79k/y4rOnwSyxZ/8BZjdWiMUSVAtw94mjPPvsM6iqg0uXF/H6/QjVhysQQa9WSW9usO/BB3n1tZd5/fXzPPjgu7hr/708c/o0uWyJy9NzaJqGS1Pp64kydegY2XKFbKFCG8HlK1cY3zvJ2soKLoegPx7nhe88xcEDk0y/+hq5Qh5fOI5PdTB111FUh5NUOks+X6ZebfDqmTMcnTpEvVSj2Sjx2muvcXDvJBMjfTgVOH36B2xurJGIR1lYzVHVvGguJ0JTcPnDJFQHL19cIewGE8nlpU3a9SoPHttPoaGgBvuYPjvNs+cWOHL3XcwvLuIq1siU60RiCQwrw+XpGXp6emhWirfcH++IkcJnPvO7v53OZVhbTFGv6Bgm7Jscpa1LXL4glaaOLlXaUqXSNNAllGt1O5ZBqsTAwAjhSIxqrYGiOsjmCqyubdA/MIREpVlvAiYW0DYsYtEAe4YGiYSDxHtqNE2DfK3GaraAIxDj7JVNXIEoK9kSVcvBzGIBTzjB6maeYqVJpd4gmy/QbLYRmknbtPB3QtO73V6kqiBUhfn5TZ781vfxBWO8+OLrLK1ukC0UKZWrtNoGlgSh2gu37IjT4HQ4MCxJNBpioN8OFzc6NoY0Ja++9jr7JvdhmAbjE2O4/B6Wl5fpHxywPTb195HJZ22X8j4Fhwc20otoLpNyI0eyL0hTL6HTIB7pwZQGLo8L3dQpVor09vfZoeh1nUargi/oYDO1TCwZpGHU8If9rG4ukytk8AVCqJpCpV5hPZNmZHKC5fV1nD4PF2avUG02ePej7+HKwlUaVovEcD/jR/fjS0a456F3sWciyeBQj22UJWBPMojXqWE5ffzxd66SrpsIn5+hoV68Lid7RieYWVph/9QUtWqVer3GyuoKjWaTQChESzdxuNwgVHyBIM22zpGjd7G6scaesQk0p4NETy8rc4tcvDDNgakjXLo6x8LcEuOj47z4/EuUazUqjTaRRA9rm1mEw0mrrSNNE58vAJbF/cePMTV1iCuXLrK6ar9a/shP/SzPPfcCi6urJHt7kVLg8XqolEqsLa8yNDxAvV5F0dwomsJP/+xHOXvuPPc+8CCpXAnV7aPRNtksVFFVDbfbh8cXxOl24/FqNI0mwu1nabNAz8AIydEJPvW/f5pv/OBFvvLt51G8HjYzWUKRKLl8kfGJvdSbLTY20+imRVs3iSeTbGTytzRSENebAd8OTpw8Ll985XkM08KtOrCXGppgtuzXihKQKigO7DDtgKbQ1ls4XS4sKVHENZMLS1o0m028Hi+g0HGxhESlZUpcmkDIBjRL4ALb04oGlgOEw95WHKBYICyQip0O6LrE4ZSACRhg6KCqtmWUZYFybfBlNA00pxOEwLIkimpHorJlARMdla3oVGB7s5egdPZvNaDdtvepOTDrTVS3xz4egDCo12t4vT5MvY2qOdCbTRweT0cCBdk2Ec4tp50mhtFG05SOExqJZdorMFHU686KnY+pgypAN205VM22Q5fSLqIIsIxOOiAELcPE5XTZ6fa68I7MKvWGfV5Mw0JVHXabmSYIE0zDbm9LAWcYaRkIWQdNAR10xQUOB3ZtLNBbYFrgdGK0mmhuH2a7jercGfjEwtL1jhcsbDt6Kezlp1LZLgMmSLD0JorbC52oYRYSBQlYmM0mqoPdhvwWoDk659V2bNNq2a+y6Xj2ks0GWBaWqiAsC0UVIC1wOMC0kJaJcHrsfSkKUjdsgztNsdtGsV+h2fVw2m0vJVgWuqHj8Pi229jqBD5SVBVpWQhN2xZUKI5XpZQneQvuCKVw8uRJ+fIrL3UsCQAsOufBRtzAxqrjXc0+QW9m160gsOyTILTt6HwqFlg6UnHtKm27Q7E6e5Q4UbeNn67t0Q6Ja//hBjMwcZPfXL8IZGuv1+q3y7Ri6xhb+VK5bn9vYc8ub9xu1/Z9E9u1reNsC3udnFv7kFt5VifvOvkkdiffbk27He04zR2PVNi6RKJgAgoK7o7jLCG35LTPmhQOTBTUbRGsazKKHfK9gevb6ZpivladzjUCnevtWpmdVTI7+9qqga2+7bJO3nC6d7eRUHZsbx1cuUF734TtG9R1dZPWLplvjIUQ6i0phTvimQKwQyHA9sXVSTLfpGPZXhhv3hhya3+dE6Nsd3D77i+uu15UFBDKtsIxd+TZR9m6wN/iOtwqdN1Vtbsqb9Zpwbz+9FzXDspNDi62OqPYqVR2lrVAvtWpt25whV9TDlvtI+SODtS5sAVcO0lS2VbqHY+Zu2RSxbWzs9Uv2sJW2nbcHs0exQl9ex9buxfXKaGb96kdo8iblBOd836j8dJO1B2Kdqus2ikkdmiZ7Z+CjnK+TqGylW5f31vjjJvdRLYV19a1ubOokLvK3phbX+Z0xyiFG7LduLvDaKs7qi86Q7absXUPsy9UC7E16pDYOaLGtU7TKSkVu5xljzJhx0nZbtyt7zcJ8S1uIteNr8o3SK6g79jefVKvyfPG3UkBAgdvUAS7drAlt7xBvgJv6B47MRDIbX+4u2TaGrndUGO+cWQEIKRARaJKexpnCDp170ytdvxflbarf7kr/dbZUkA3y7t+ZLBL5p2j153y0/njdU22fe11dnitM3ekEHaJG3dXa0fZnRLuON6ONpY/Qs+Kd4hS2NHaW5q4M+wUKKg7xXybV4K8vrNtzd07v6Xi287aPv1bmn97CLvFjobfOik36vjbZ/8GV9CNhvTb+9tdXuC6cX230nYorLdsljcU2CHHdhvdyjD7Wp64UV6nHtdGaNcdZoccUnSO2PmzItih4lvYD3w0TGEr/903gzdWSexS2jdHfZNp0Y2nd53fQkFe1/F3T2OuV8LK7pvSDbmRzNemXMD2lEF22nxXG+6Q/+bHeHvcIUphx1xhu2bX35HZnX/9HOImbM8/dzyX2L6jvWE4fhPR3k76rrw3nx68kbdb/m0Uu6X93GQ68ibl3pDXuXvd9HDXjSxu3oU7D4nF1g145/Vxs05wi3fLbY3yxiH9W03vblyv6+f5dG5mb/bfG7ThDa+ba/t+Y7kfnSLYyR2iFG7Gm5zkt91ZbvWCfwfwjhT6xty8Ktp2AbvMj254/BYHvkP4Edf3HXHkLl263JF0lUKXLl12cctKoeO89XUhxNc723uEEC8KIWaEEH8phHB20l2d7dlO/uiPR/QuXbr8OHg7I4XfAHZ6avg94HNSykmgAPxqJ/1XgYKUcgL4XKdcly5d3iHcklIQQgwCjwN/3NkWwCPAViCYP8X20wh23Ic/7fz+CvBesTNkU5cuXe5obnWk8PvAv+Hay9MYUJRSblnA7IztsB33oZNf6pTv0qXLO4C3VApCiA8CaSnlqzuTb1D0xjYuu/N27nc77kMmk7klYbt06fLj51ZGCvcDHxZCLAJ/gT1t+H3scHBbdg47Yztsx33o5IeA/PU73Rn3IZFI/FCV6NKly4+Ot1QKUspPSykHpZSjwMeAp6SUnwCeBj7aKfYrwBOd31/rbNPJf0reCUsxu3Tpckv8MHYK/yfwr4UQs9jPDL7QSf8CEOuk/2vgt344Ebt06fJPydsyc5ZSfg87bBxSynmuhYrbWaYJ/NyPQLYuXbrcBroWjV26dNlFVyl06dJlF12l0KVLl110lUKXLl120VUKXbp02UVXKXTp0mUXXaXQpUuXXXSVQpcuXXbRVQpdunTZRVcpdOnSZRddpdClS5dddJVCly5ddtFVCl26dNlFVyl06dJlF12l0KVLl110lUKXLl128cMEg/miEGJBCHGm8znWSRdCiD/oBIM5J4Q4/uMSvkuXLj963o7npa1gMMEdab8ppfzKdeXeD0x2PqeA/9T57tKlyzuAf1QwmLfgI8CXpM0L2F6f+34IGbt06fJPyK2OFLaCwQSuS/+MEOLfAt8FfktK2WJHMJgOW4FiNnb+UQjxKeBTnc2WEOLC25T9TiMOZG+3ED8EXflvPz/uOozcSqG3VAo7g8EIIR7akfVpYBNwAn+E7d35d7jFYDBSyj/q/A8hxCtSypO3IvCdyju9Dl35bz93Sh3+UcFghBB/JqXc6EwRWsCfcM2z83YwmA47A8V06dLlDucfGwzmn209J+gEj/0pYGv4/zXglztvIe4FSlLKjRvtu0uXLncebyvuw3V8WQiRwJ4unAH+5076N4APALNAHfifbmFff/RDyHGn8E6vQ1f+288dUQfRjejWpUuXnXQtGrt06bKL264UhBCPCSGmOxaQd2TcSSHEfxVCpHe+NhVCRIUQTwohZjrfkU76HWfRKYQYEkI8LYS4LIS4KIT4jU76O6kObiHES0KIs506/LtO+h4hxIudOvylEMLZSXd1tmc7+aO3U/4tbmAZfMfJf1uVghBCBT6PbQV5EPi4EOLg7ZTpJnwReOy6tN8CviulnKRjp9FJ32nR+Slsi87bjQH8H1LKA8C9wK932vmdVIcW8IiU8ihwDHis8yD794DPdepQAH61U/5XgYKUcgL4XKfcnVshq8oAAAI0SURBVMCWZfAWd578Usrb9gHeBXxrx/angU/fTpneRNZR4MKO7Wmgr/O7D5ju/P5D4OM3KnenfIAngEffqXUAvMBr2ObzWUC7/noCvgW8q/Nb65QTt1nuQWzl+wjwdeyH9Hec/Ld7+nAz68d3Aj2y86q1853spN/RdeoMQ+8CXuQdVofO0PsMkAaeBOaAopTS6BTZKed2HTr5JSD2TyvxG9iyDLY62zHuQPlvt1K4JevHdxh3bJ2EEH7gq8D/JqUsv1nRG6Td9jpIKU0p5THsO+49wIEbFet831F12GkZvDP5BkVvu/y3Wym8k60fUzsMuPqw715wh9ZJCOHAVghfllL+dSf5HVWHLaSUReB72M9HwkKILXubnXJu16GTHwLy/7SS7uINlsHYI4c7Tv7brRReBiY7T2Cd2BaTX7vNMt0qXwN+pfP7V7Dn6Vvpd5RFZ8fq9AvAZSnlZ3dkvZPqkBBChDu/PcD7sB/YPQ18tFPs+jps1e2j2Ja4t22kIG9sGfwJ7kT574CHRh8ArmLPD/+v2y3PTWT8c+xVnjq2Bv9V7Pndd4GZzne0U1Zgv1GZA84DJ+8A+R/AHnqew7Y+PdNp93dSHY4Ar3fqcAH4t530MeAlbAva/wG4OunuzvZsJ3/sdtdhR10eAr5+p8rftWjs0qXLLm739KFLly53GF2l0KVLl110lUKXLl120VUKXbp02UVXKXTp0mUXXaXQpUuXXXSVQpcuXXbRVQpdunTZxf8PRB/kuysPAJYAAAAASUVORK5CYII=\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "def get_image(path):\n", " with open(os.path.abspath(path), 'rb') as f:\n", " with Image.open(f) as img:\n", " return img.convert('RGB') \n", " \n", "img = get_image('./data/dogs.png')\n", "plt.imshow(img)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We need to convert this image to Pytorch tensor and also apply whitening as used by our pretrained model." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# resize and take the center part of image to what our model expects\n", "def get_input_transform():\n", " normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406],\n", " std=[0.229, 0.224, 0.225]) \n", " transf = transforms.Compose([\n", " transforms.Resize((256, 256)),\n", " transforms.CenterCrop(224),\n", " transforms.ToTensor(),\n", " normalize\n", " ]) \n", "\n", " return transf\n", "\n", "def get_input_tensors(img):\n", " transf = get_input_transform()\n", " # unsqeeze converts single image to batch of 1\n", " return transf(img).unsqueeze(0)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Load the pretrained model for Resnet50 available in Pytorch." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "model = models.inception_v3(pretrained=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Load label texts for ImageNet predictions so we know what model is predicting" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "scrolled": true }, "outputs": [], "source": [ "idx2label, cls2label, cls2idx = [], {}, {}\n", "with open(os.path.abspath('./data/imagenet_class_index.json'), 'r') as read_file:\n", " class_idx = json.load(read_file)\n", " idx2label = [class_idx[str(k)][1] for k in range(len(class_idx))]\n", " cls2label = {class_idx[str(k)][0]: class_idx[str(k)][1] for k in range(len(class_idx))}\n", " cls2idx = {class_idx[str(k)][0]: k for k in range(len(class_idx))} " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Get the predicition for our image." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "img_t = get_input_tensors(img)\n", "model.eval()\n", "logits = model(img_t)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Predicitions we got are logits. Let's pass that through softmax to get probabilities and class labels for top 5 predictions." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "((0.93593013, 239, 'Bernese_mountain_dog'),\n", " (0.038447894, 241, 'EntleBucher'),\n", " (0.023756264, 240, 'Appenzeller'),\n", " (0.0018181818, 238, 'Greater_Swiss_Mountain_dog'),\n", " (9.1132988e-06, 214, 'Gordon_setter'))" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "probs = F.softmax(logits, dim=1)\n", "probs5 = probs.topk(5)\n", "tuple((p,c, idx2label[c]) for p, c in zip(probs5[0][0].detach().numpy(), probs5[1][0].detach().numpy()))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We are getting ready to use Lime. Lime produces the array of images from original input image by pertubation algorithm. So we need to provide two things: (1) original image as numpy array (2) classification function that would take array of purturbed images as input and produce the probabilities for each class for each image as output. \n", "\n", "For Pytorch, first we need to define two separate transforms: (1) to take PIL image, resize and crop it (2) take resized, cropped image and apply whitening." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "def get_pil_transform(): \n", " transf = transforms.Compose([\n", " transforms.Resize((256, 256)),\n", " transforms.CenterCrop(224)\n", " ]) \n", "\n", " return transf\n", "\n", "def get_preprocess_transform():\n", " normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406],\n", " std=[0.229, 0.224, 0.225]) \n", " transf = transforms.Compose([\n", " transforms.ToTensor(),\n", " normalize\n", " ]) \n", "\n", " return transf \n", "\n", "pill_transf = get_pil_transform()\n", "preprocess_transform = get_preprocess_transform()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we are ready to define classification function that Lime needs. The input to this function is numpy array of images where each image is ndarray of shape (channel, height, width). The output is numpy aaray of shape (image index, classes) where each value in array should be probability for that image, class combination." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "def batch_predict(images):\n", " model.eval()\n", " batch = torch.stack(tuple(preprocess_transform(i) for i in images), dim=0)\n", "\n", " device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n", " model.to(device)\n", " batch = batch.to(device)\n", " \n", " logits = model(batch)\n", " probs = F.softmax(logits, dim=1)\n", " return probs.detach().cpu().numpy()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's test our function for the sample image." ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "scrolled": false }, "outputs": [ { "data": { "text/plain": [ "239" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "test_pred = batch_predict([pill_transf(img)])\n", "test_pred.squeeze().argmax()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Import lime and create explanation for this prediciton." ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "scrolled": true }, "outputs": [], "source": [ "from lime import lime_image" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "explainer = lime_image.LimeImageExplainer()\n", "explanation = explainer.explain_instance(np.array(pill_transf(img)), \n", " batch_predict, # classification function\n", " top_labels=5, \n", " hide_color=0, \n", " num_samples=1000) # number of images that will be sent to classification function" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's use mask on image and see the areas that are encouraging the top prediction." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "from skimage.segmentation import mark_boundaries" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "scrolled": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "temp, mask = explanation.get_image_and_mask(explanation.top_labels[0], positive_only=True, num_features=5, hide_rest=False)\n", "img_boundry1 = mark_boundaries(temp/255.0, mask)\n", "plt.imshow(img_boundry1)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's turn on areas that contributes against the top prediction." ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "temp, mask = explanation.get_image_and_mask(explanation.top_labels[0], positive_only=False, num_features=10, hide_rest=False)\n", "img_boundry2 = mark_boundaries(temp/255.0, mask)\n", "plt.imshow(img_boundry2)" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.5" } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: doc/notebooks/Tutorial - images.ipynb ================================================ { "cells": [ { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "Prerequisites: install [tensorflow 1.0](https://www.tensorflow.org/install/) and [scikit-image](http://scikit-image.org/docs/dev/api/skimage.html).\n", "\n", "clone this fork of [tf-slim](https://github.com/marcotcr/tf-models) somewhere\n", "download [the pretrained model](http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz) and put it in tf-models/slim/pretrained/" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "import tensorflow as tf\n", "slim = tf.contrib.slim\n", "import sys\n", "sys.path.append('/Users/marcotcr/phd/tf-models/slim')\n", "%load_ext autoreload\n", "%autoreload 2\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline\n", "import numpy as np" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "## Create a predict fn for inception v3, takes in a list of images and returns a matrix of prediction probabilities" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "from nets import inception\n", "from preprocessing import inception_preprocessing" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": true, "deletable": true, "editable": true }, "outputs": [], "source": [ "session = tf.Session()" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": true, "deletable": true, "editable": true }, "outputs": [], "source": [ "image_size = inception.inception_v3.default_image_size\n", "def transform_img_fn(path_list):\n", " out = []\n", " for f in path_list:\n", " image_raw = tf.image.decode_jpeg(open(f).read(), channels=3)\n", " image = inception_preprocessing.preprocess_image(image_raw, image_size, image_size, is_training=False)\n", " out.append(image)\n", " return session.run([out])[0]" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": true, "deletable": true, "editable": true }, "outputs": [], "source": [ "from datasets import imagenet\n", "names = imagenet.create_readable_names_for_imagenet_labels()" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": true, "deletable": true, "editable": true }, "outputs": [], "source": [ "processed_images = tf.placeholder(tf.float32, shape=(None, 299, 299, 3))" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "import os\n", "with slim.arg_scope(inception.inception_v3_arg_scope()):\n", " logits, _ = inception.inception_v3(processed_images, num_classes=1001, is_training=False)\n", "probabilities = tf.nn.softmax(logits)\n", "\n", "checkpoints_dir = '/Users/marcotcr/phd/tf-models/slim/pretrained'\n", "init_fn = slim.assign_from_checkpoint_fn(\n", " os.path.join(checkpoints_dir, 'inception_v3.ckpt'),\n", " slim.get_model_variables('InceptionV3'))\n", "init_fn(session)\n" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": true, "deletable": true, "editable": true }, "outputs": [], "source": [ "def predict_fn(images):\n", " return session.run(probabilities, feed_dict={processed_images: images})" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "## Let's see the top 5 prediction for some image" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": false, "deletable": true, "editable": true, "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "286 Egyptian cat 0.000892741\n", "242 EntleBucher 0.0163564\n", "239 Greater Swiss Mountain dog 0.0171362\n", "241 Appenzeller 0.0393639\n", "240 Bernese mountain dog 0.829222\n" ] }, { "data": { "image/png": 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Xt6iymlfvvIXrM/72v/t3+Vt/4++g0HhryXQxMfLW4YYBN4wMfX/DrkeyLMP7AAFynZOS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\nr8F87tNstwnjCCct0VWLSvjYls1itiBDYBW1+jPNP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oT192UpYRgSxRlvfuUX+Z2/91+w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bbv77C3d0AUxWAEwkgs5eE6HgJDLXDZ2ztiMgoptSZoKB69uEajUcMWJUFgM59NybUh0xBm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\naidXMUzBjft3OGwf8cMfvcjW/Xscd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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "images = transform_img_fn(['dogs.jpg'])\n", "# I'm dividing by 2 and adding 0.5 because of how this Inception represents images\n", "plt.imshow(images[0] / 2 + 0.5)\n", "preds = predict_fn(images)\n", "for x in preds.argsort()[0][-5:]:\n", " print x, names[x], preds[0,x]" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": true, "deletable": true, "editable": true }, "outputs": [], "source": [ "image = images[0]" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": true, "deletable": true, "editable": true }, "outputs": [], "source": [ "## Now let's get an explanation" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "from lime import lime_image\n", "import time" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "collapsed": true, "deletable": true, "editable": true }, "outputs": [], "source": [ "explainer = lime_image.LimeImageExplainer()" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "hide_color is the color for a superpixel turned OFF. Alternatively, if it is NONE, the superpixel will be replaced by the average of its pixels. Here, we set it to 0 (in the representation used by inception model, 0 means gray)" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "440.970395088\n" ] } ], "source": [ "tmp = time.time()\n", "# Hide color is the color for a superpixel turned OFF. Alternatively, if it is NONE, the superpixel will be replaced by the average of its pixels\n", "explanation = explainer.explain_instance(image, predict_fn, top_labels=5, hide_color=0, num_samples=1000)\n", "print time.time() - tmp" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "Image classifiers are a bit slow. Notice that an explanation in my macbookpro took 7.33 minutes" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Now let's see the explanation for the top class (Bernese mountain dog)" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "We can see the top 5 superpixels that are most positive towards the class with the rest of the image hidden" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "collapsed": true, "deletable": true, "editable": true }, "outputs": [], "source": [ "from skimage.segmentation import mark_boundaries" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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ZW7QuEQuB71XrIFpNrovJOoca3/c5cvT6HStLHIfV+glZynA8RhToMqfQEIQJ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\nA5h+TCFOW/ZjAAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "temp, mask = explanation.get_image_and_mask(240, positive_only=True, num_features=5, hide_rest=True)\n", "plt.imshow(mark_boundaries(temp / 2 + 0.5, mask))" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "Or with the rest of the image present:" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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Xt6iymlfvvIXrM/72v/t3+Vt/4++g0HhryXQxMfLW4YYBN4wMfX/DrkeyLMP7AAFynZOS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\n0aNGCh/HDjBa0DTt1KgbOmLfJYki7rdrfvjjH/H+6h377Za+bUjTmP1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1SZYyqpFlNqc8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WrG8a1bSCl59/57OJ6NYelstxE7u42bNEkaP8nDh4+Jowzbdrl/7x2Gow5CV2m1h0ThFlSBa1oU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RcB1QXFB5KouYHrfABJSYV2VF1IU4o8z5FKM4siigrW1tbx/QbNdo80z3E9n8oY4iRlMpnM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\nudEgRSFKJQxFxsyX+OwLX+D05gqqZ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24RiYQZ6Q8h7Cr5bJqemI9CpUytYqApfm7emMM0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\ngg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "temp, mask = explanation.get_image_and_mask(240, positive_only=True, num_features=5, hide_rest=False)\n", "plt.imshow(mark_boundaries(temp / 2 + 0.5, mask))\n" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "We can also see the 'pros and cons' (pros in green, cons in red)" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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6nBh55/HDgB9Ghr6/YdcT1lpCiBCh0AU5C5TQWFNipGVoR4yyGGWJEWIA7xOjT8yXa7JI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RnaVM4wU9w2O738GlRmtJXSV4vsciydB1TavdRng+ltB0uiHjRUy60NS+IghNHNekLBVCKRzH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tDy/x/q3ivG0vw88/t9OZ18Tp2qUzl1DhM5nOFwhjMURYpBokSFDV6uwkKCvTB8YQO+cIIB\nY+/WWMPwLoxd72qllSyvBNGULGkkDjkcznDyTHdP51RduU6dOjl8Ofniq25yF7qYy9kDNBqNPtVd\n+FDve/7/932e36Pg+x6yorF/cMhwMMQqm4x6A9JY5K9ffZMbl26gh3Dm/DlmFuYJIp+jgzZCrPPc\n40+jSDIbex3mpiQqYp/Ts2rWtBIBy9CZOB66biLJEhfOX2B1aZGjgyaKrDGcOAxGY2RZoDcco5s6\npKBIErXaDO9/cJnTp04yMzNDkqZUa1UEEZ55+jPkcxZnz5xgMBoiKTLuJGJ2doHBcEB9rkEsy7hR\nRBAETMY2n3/ySRqFIjNWiaHj4Y6HEETI+TxDL6Cel7h58zLPnaswZeqMIg07ERl4EflaHnsSgh9R\nrdXYc0XGqsWDZo/7Bx2cCK5dv0kapwz6Q8x8HdUoIEoKOVNHkgUkXUWQLYxcjZxewlBylApVJgHI\nqoksaES+RBhpiFqNsVSkGRnc7Irc6sK1o4C7bZuNrs313SN8PyUVFCahQMcJuLW7T9OLaKUKR6KM\naOY+cT1+KpqCLMn0egMkUWZ5aYW11ZNZEfr+I2x7lCSPvBFJEpEcY8mSOAIxY949jJdLEhDF7Fie\nORXFY9hKgiQJGZ77GKeWxFnReZ5Np32E5wXHwimBMMwGhln4LbiOj66bKHKW4iurMqIoZN9Pkhx/\nTTbwDIKfaCZM06RarVGr1alN1cjncywtL5HLm8iyiGUaqKqEKAgooowsaMhKQm0qTxL63LlxjfEo\nA6qmckJlaopWa4Dn+ExV68iiTBxHjEYjHtzfQJE0Uh+uXbuHRISlyzgjmzQKECUwZI2psgkIdDoT\nho5PIkuookA+n2PsuIRRhJTE2N6EOAZJk7h04x7lqTrzczP81XdfxRQkXnrmM+w12+zu7fIv/u2/\nxosiEtOkUDRpVAXKOY84TAj9GE1TSZKI6Zlp6lN1HmxsEIY+RUtnZ2cLQVGwLB1FlnDcgO5giO2G\n5EyD/f02O/ttfN/LovcKBQI/U7Pu7+0dT/h1dg72iZOE3d09ivk8aZxgOw4XH3sMSZEJg4BSuUTn\n8Ij2QYv9/Q4V0+T23Ts4wy5RKtHp9WjUTU7O5ThbMvniqSLDfoBqyewPXca+SChA86hHkKj0xj1c\n16NYqGCHCc3OgGvXb3FncxM5lycVVA4PW7zz5o9o722hi5DTdCxRRU4EZEVA0ySKlkJREigmIhXZ\nwNAtUDS8VEBSTRQlh6LmkPUiUq7GSC3SEXIElXk+uN/i3bu77NkiR6FCH4W2KxPGMoKiIQT2J67H\nT0VTqFSrbG7t0On0+cVf+hVa7SPWVlezTEE/OP60y15BlCn30jQiCQMgPi7KY56jkAFPRFEkTOJH\nBqkkyRiPSZIwHruEYcR4OCJvGqiKiJAEyErMe+99wGg0JE0jJhObarVG66iJqMiMxzb1eoNyufII\nnhInIVESEcUBhULheF2ZPdYMAy9RyBdZmF/k9OkzWFaO8+fP8uUvf5lvfetbnD9/Dt2QKRVz5HQF\nVdJoHrRpD/bwxQkTe0i1WKC132Ts+PipT65Uot/z8SYC42GH8bBLo97AMsrIikjoDdH8kF//zZ9H\nE0aksYOVy1GSQoqChBxrxEmAE2jkzCIRMR0/pO8M0TQFzTBZml/GFEQqisXlqxucOnGS4WCCY5m8\ne+0Gi/PTbO3dZW/jBs+8/BK74xBfkKhWiry7OcHXzqIYU0hWGU3WOXv6NFYul81XDIP19RX2D/aY\nm51HT31MQ2HiOkyVC/i2j5Wr4CPS69ts73a4u3VEolS4cfs2k/GEg+YB+80D8sUCB+0eXpBwb+sA\nJ4zwwpAz60toQoIhydjtMRvXrzNVKOHYHrNLS3znr/4aVxCZpCpEIz53oc5jS2UEJExi5ubybN5o\nUiLFUAO2Q4nvXBrw9V9+gRNr53nQFumkEZdu3+LCuXP8o1//R+QKBQJFwSdGFiRuX/2Yf/f//AE/\nvvI39J0HJEkH3CMe3HgfQ0wxy2UK1RLVUg5V8FBTl1pRRlAiEgVEA2Q9RZJ8olETLR5g6RIIMRPX\nYRCJ9GKFoWCirK5grZ4kUovEIiwtTTOTn0dJDFQtz0yh9Inr8VPRFNI0ZXVtjVOnz2YbhThmbm4G\nSRaO06czNkIax6QPhUsPsVfHaVGioDwSNAHHG4AMBS9KAoKUxdxnTkYR4VhZJggpcZKgaQaCIHDr\nznXGowBSmZQkGwhKMkmcEsYhhXzuWE0Z43susqAQhTGSmA05JVlGksSMNk0GgdF1I3NTJimWmWOq\nNo2uqGiqxtzcHBcunqdUzKEqMr1hF8syaNQaJEAuZzAZD3H9zJClySapF7E6P0vJsBgNxoz7Du7I\nRVMz+EySCOSKBrt7N1k9VadS0VGkiFQUyMkih/s7OG7KYbvD1EwdLZcnrwoEqcjKygqDYZ/RcEB/\n7DDxfFRdB1Fh5cRZctUpCpU6BVNn7eQpZuan6R31qBSn6AxGeFHIJFFYf/KLeLbAYPeQVBIY2x5D\nJ2IytplvNMjbO5ipw8z0In6QoFs6jz12liRNMRQFRYqolnIUSxaaptJYmOWjj68wHLjMzlbRNJVc\nvoisW9ieTxKnDByXOE4wDIWtnQ0ULTtBFYo5VDUbzuZyFtPVGnqhyO2NbUzTJJUVjnZ3mSlpKFoB\nBAVV1RiMY6Q45N5hysR2aQ5jSGD99BJGUUdQdIxynub+AT947YeMnDFBFJKIMqkss7C8nClfDYMw\njJlbmOOdS9f48OptNjbvocgptjPBdYYomkGSiLheTBBFmXw+ETAEiZolUy2ryELEeGKjIKIJKZYs\nYqoC9bIKYYwsKJC4xP6EJHCRCPGCAUpoUyr8J7Z98H2fxaWlbNDUbLG6uoTvO2SngGMJMhlKjeME\nrIehMXGcZk1BlP6DoWIKpIKArEkIx7NJQcwkyJlMOntIgpQd/0VJ4qjTZmf3AUetHkmcPZp2r0el\nWsfzAhAy5aSqqsTHGRBJnCAkmbDo4b+fHG9JSBN03UQUZVRVgxR0XUeWZGRZolQqUSwWWVpcYGlp\nnjiJ0XIqtXoFdxwQhQJB4KEoKpqhYlk5Yj/BHU9YW54ljQMMxcTQcrSabRbmpymWilRKVdzYo1rL\ncfrxJVbXZkhSh5EfM1MrkcQesmqQCAId2+ag1WNtukwSgyyLpMT4octBp0+QpJg5jQf37uC5DmIc\n0z3cQZdV3nn7PRTTYHNjh1FvQCILJIKEn4j83h//KaHr8dSp0ywuz+F7AaVajXanR/eoxctnaizW\nLN588120QoWllWUUKcV2XOIkpdcbUzFVZEJKxTwJAStrK0xNl3E9ByEVmZ9fpFAqYxkmaRQSJFkx\nKbLMxPORdZ1ytcZec4cgSegPxiiqiCoIOEGIpGr4zggjV8BxwNRCtndbXHhsHc0qECQppXyOoe3R\nKJisLVWwrDIb2/d5/rNniMOAbndCr9vlzsZddnb3URWNVJTwELh66z6apnP5o9vcu7tLnBhEqkYo\nybz2+mvYwxaalPD6j37Aj378Np3+GFUxURAIRjZqHFOQZSwxZna6CiTohoUmiRQNGVmMCd0hg9YD\nipqGEoMoxAS2jUxKtWoiqx4VLWJz8/InrsdPRVNQVY3xaMzBwR5xEnF01MIw9GN79ENV40+OAVla\n1E+2Cw/j6x++I+MnhI/CX5IkypKgVPWY7iRmNKWZKZ5+6jFmGzWiwCZn6YwnPb77Z3/M9s4mnuth\n2w66oWLbNo3GLNev38D3PaIozlKZ4ghJllF1PWM/HPsgUgQ03UTXdTQtayLFUpGFxUU0XWd2bo65\n2Tkev3ge09SJQpfp6SKqKXJr4waeHzI7v4yq5UllmVKtQrO9R7vbpFYvoFsq1RPzGHk4d+4Emqmj\nSCaPrZ2nc7hP6AtIYZ5ueMD6sw2+8fe/RD6vUa+U8R2f0kyVTuCyNR4RpxKJbbNgWUyah6S+j+P4\nJIpEzjRQApfH5sukW5f4pcdn+S9+Zo292+/zd3/lF/j4+k1cEXwpRYojcqaB6wTM6j6CZvK//9lH\nVPIaM1MGttOmsTjDfnsHY3YJs1pHLBrcORrSnThIssqXvvgzKDkTzcpTSn1eWqjjeWPCwRC/1cYO\nFexARBFU/G4Tf+MGgjNCEgQCJ8B2QiTZoFCo8O67tylUVkhFk0KxmCWZhzGXPvyI2bk54jQhTgMM\nzyFXLFLNGySCz2tv3eDt9+7wwlN5Bl7If/aVBX7nhQILQp/DgcRg6GIYEk+cW+TbP/8SQqpwNOgS\nJyCLAqos44UusZgSIRJFIeOxzdvvvc/QDRj7AW4i8Npf/CmvvfInRInM5t4ub7z7BrfufsDNW29x\n6/qPSCe3kfwWwaDPH/3JXyApAtNlKApdNLfJrXsfc/f2JUqJh8CQsh5RNizmylMsTBV468evMl3S\n2du7QST4n7gePxVNQZZlNFWh3W6h6yrNwwNqtUom8iF5NNXPmsBPZgSZ70HIqL3HMJbsfWm2rkyz\nyHpZliFNkY/DYDRVzgCqEpSLOc6dOUmxYHDixDrLS/Mc7G9x6+YNAj+iXpui3+8+clsKgnBsdgox\nDCNzFYoZLo40RRSyTYd6TIF6ZNeW5eNMCJVSqUKxWMQwDcRj0u5oOECSU4LQBynFzBcAgemZWWrT\n0yRklCHT0rHtCVEU4/kOyDH9SZep+jSHhx0+unQF1dDRNZPRwAZFwotdBk6fqWIOQxSZrRUZjSd4\ncYIfpuTNAokgUC8UGHV7iHGCrmooskK7P0Qh5rDdI7Rhf2ePmzfu8/d+7gtMWtssLy6wsjTPhccu\ncPGJpzPPSRJxcNBkECYc+tDc3+WgdYQhaIx7Nt3mgH/+B2/w3tU9uj2XJErY2+/x9HMv47oOxXwJ\nTZNYm6swIye4cUp5apbBeELi2shJxMR18e0uP/fZNZIoIFZkOA76sR0HWdGYqs/gegG+HxAEAfX6\nFLbtISky+wctcrkiY1tEU2UsXUGMHXRTAQmWGwWKkkI0GtPvurijENmw0AWNrb0Wez2HUWrS7IxI\nfB9FFI4/yBKGgx7FQvZMe8MhU7VKBgxKEjw/IhUEHM9nbmaaJ568iKEZpGKKG7h8cOk9coaMPRlx\n+fpVPrh+jXcvfcyD7S02bn7E4d2PcHvb4HQ42L3DpQ8vEYUB/njM9vYmG1fe4rC1Q3fYw7As7t7d\n5tnPPc9Oz/vE9fipaAppkvJH//cfMl2voigSpqlz8tQ6hUI+w7gfE5PgoSkyfSRg4ljB+PDPmqY9\nWkEqokjgumiyTJqE6IaKpsmcv3CaWrVAY6bGs889zdraPF/60gsU8yanTq1x8fGTfPDhW/zhH/4B\nvu/T63XRdQ1NNdA0Hce1URSF4BiOGqdZpLooyoRhpkU3zTymmUfTtGNvRoqmqeiaTqVSwTRNZEni\nxvWrXP7gHcTIQ9NEiuUSw8kI1coxGI9oHbUJwgDXtbFHEw53muxuHXL18i06m7t0nTY3HtwgEhJO\nnr3I3KkzxFKenZ09BAkG7YjmwZid5i5H3S7t/hZDd8SDnS6JrDP2AjRdohl7OPYYWZLISQIrlRqp\n7ZFXTX7uuSeQFQ3PKLJ5NGb1c1/hr965yj/4jX/M/btt1taXsco5XnzqWcTI57d/57fomtNc6YQ0\nTp4gSUV6YxclAl2vsLPf4ea+S9eWuXxnG8KQuHPAP/uf/kd+8NoP6feHxPaEhmUysZvEQcjm3h4T\nb8KM4ZNPJ2hCRH/i0+zZPPP8CzhRgGaaxFFImgT86q99k5u3r3L67BLzizMcNJscHLZozM3geQEn\nT57AjyJe/MrXmGkYnJ+NuHvzKkIESgqLVQ0fmfd3RvjqEtvpLDtxjf/j9/+U9x90uHowoWSY9NtN\navPLGEYV2/GQ0wghjen1uki6gR9FCLGHrorompz9vCQxqqaxcbDPn//5K5xYX8TtTYhcn5e/9DKT\nUCBS82weuQyDmNWzp/iZl56mVq8T56Y5lCq8cmUDx4s4+dTT/LM/fR1l3KXz4DrPnl6gUpVo93tc\nunmJ13/8Dv/6//p97m4dfuJ6/FQ0BUGA5cUlAEzDpNfrcfHiBS5cOI96bPwQRZE4TpGkrMAeWqll\nWSHwfdI4RtMyYm2SRJltOYmOVYbi8VwiJWcZzDWmKRXyzM5OY5km1Wol+yHxPdZPrLK8vMDi0jyd\nzhGiJB4DYaXj9Wb2/2ef/pmFW9M0wiAkCMPsBJOmj2TPD+PqJEmCNCaKInzPIwojXNvG9xyiwEVI\nYjzPo3V4hB8EtA4P0TQVKfN/EUcxhXyJucYikZ9QMCvc3dhkMB5TLJfZ2Nhg494Ge7t7bNzdIolF\nNMNgrr6AFMlUyhWe++oJ+qlA49QykpiF5UYpDP0JoaAim0UGozGVosWg3UQiwQ0Crt66h+uFqGrC\ntatXsIcjfuWbv8yf/sm/p1C28JvbCKMur77yl8SiyH7ziJ0xDFOV4WjMxPYIgojYcxj2e8iiiB2k\neEFErVbDVAW++eJZnlnRUWQNN/YggTvbTUBidcpCClwUXWK1qvPsYoH1uQbzBZnf/tbXuXX9FnGQ\nUlAVVFkiCVMebNzH0BXaR01EMUVTdXRdZTAYomk63W6fNIX/7y++w/mVGt/+xZ9DVHSmqkXEGIp6\ngVgtcDgWWF2b48R8iWJepe8HGFoR23UxpJBf/ebXOP/EOWzHRVNkRAQ82ydKYDgcEYYJaRRhairz\njVlypoEqq4SBx05riJOKFHQFIYn43DPP8N47l7h86wErp07jORE/+9ILbN+9RnN3m+99/wMuXb7G\n0HNpzM9TEAXOLU+zvlBFkWLmSyYTG2an5lBSgZdeep6ltQYrK6ucvfjYJ67HT0VT8H0fU9fxXI+j\nozZPP/UMH314iWKxSMrD68Lf7vIKH7IXxSx4JbNKZwvMKIqOrxnxsX06ZXZ2hnKxwPzcDPWpKnEc\nMTc/j6rpnD17msD3mJ+fZ262QbVaRASK+QJRFKJp+k8h4GLSRCAIw4wVSfporiGKEla+gHIsj34o\noBKOg8GCY2t34E0wkdoAACAASURBVPuIaUwhZ0ASHecEZolYYRATxwmmZT2CurQPO8QRCIlMuTqN\nZJh0O30c26Fcq5CS0mt1WJqZQ0BiOLAZdvtwLOU++8w5Tn92mc3DJmVDRo4T4iBEkMEeBfjI6KaG\nqatUKhaRCKKmstsZMnR88qZJsTzNq6/+gMs376BpKqNen85hm1RQcNwQ24vpdHp4ap7WJEDWdSZO\ngKrJqHKIZ/chiRn5NoKcUsirnJgvkktdZkomsqKwuDCLqSjkJQVFUzm5sEApn6NeyrFUMjk5W6ff\nOcIOU17/6Dabe4c0Gg0cx6dWrSMIElc/vo4sy7z7zrsUCkVEKWvqrufR6XYZTyaUSkUWZhv80s8+\nTae5Rb5UY9hpggRmIU8gQ9eJ2ev1GQ1GlKca6KUCiqLS7w046I145dW3cCYDpmpFquUStWqFYjEH\ngoIsKciSgCxJ5K0c4/EI33dxbBtDV0GXCFMRM2+xtrzC/u4enu1j6hqylGAaJt975RVefvHz/Obf\n/3vouslRu0PrYJf6dJ3x0OHSe+/hOkPsMGZqdh5Zk/GdgI/e/RBDlDi9tsBTp08y6rQ/cT1+KlyS\nnXab3/vdf8uXf+6raJrG1Y/HXHzsAsvLK0BGP46irClkwAoeQVYy30GWUh2GwSOpc5wmiGRGKlkW\nma5X0RSJF59/hoX5aaZrRUajEbKiUa1VcX2PNUnNTiCSwOLzC5w62SYKfcqlIhPHRZJkCoUiipKt\nMyRJIT2OJFNV5diLoZKKWZhpGGXht2EYIpGlXCWeRyhkRqfA9zFkgVJOwy3o+PGERnWN0WaPQcul\nUI64f7CN47usnzyFKuTx3YgTZ09za2MTTxCYMabQNINCySLyXE4sLxK5Ebdu32L1xCqFmspDjuWd\nOzeZXmzgjx1mcw7jXsRIEzGm89gtl51mE91IicKYgeeiFy1qpkWrneIMbXKVClfevEw9JzHbD7FK\nBmZe4+svv8hfvvU+YW+T0I2ZrlV59dXr6LrMM89+jt/4O7/E//q//XPWT65xbbuNF4OppDSmSmiF\nGs9aEbubu4z1GoPhLpVyjrnFKrO6jRtIjGMDJ4Hl+iyyv8F0aZlA3EHJGXy810atFgnThL47wfFD\nwiimVKyRz5cY9Dv88IdvkgpCphsRsy1UEAbs7e1iSTG3rr3DqUKVyx/uoMZ5VmfL/PUbl5hSDYpV\nk4nUID+d58qVDWzFoNk8YHVhhp4nUKuUkGWdKPI5sbTI5uYWiiZz5vxFTFXmrTd+RH8wZjgcUy3X\n+OpXv8b3Xn2VIPBpzNTZ3G7xf/7uv+fihbPs7mxx7tR5Pr7+LpPONm7gce1+m417Wzz7mVOcWl5C\nKWlEzhjb98jPzjAZj+hPIpphnnLtBKPRbXa3etzaOOLZz+Y5aLd4d6/NaPKf2KARUubn53jttdf5\n3ve+z9bWDhv3N/jBD36Q/e1PkZyPxwikxzvJjFEgEkfZVSE8PsKLYvZGTZNRVYVKpUKlUqJWK1Ms\nFKjVaiwcZyDk8gU0zaBULWEYBqViBUFImZ7OfjdNE13PAKq6rj/KrRRFEUmUsswHIYOncHxdiMKs\nYf0kmCYmPqY7p2lKzrLQdI3p6Rpx4AMRiibiuz6FXIFKqU61Og2IlGo19vcPKdemaLWPGIwHjJ0B\nBcMiX5oiihJM06JQzlOslijNTLGwOIdpyIgqhASEaUTqhdy/fx+pqJHoIWZJIZfT2Lzb4unHGqhy\ngh2FxDEMJzEFq4CpaciajK7LdHt9zpxeRVUV7ty4w9ryDOvrK1y8cJFGY5b/5r/+L1meyfP+22+z\nsrIEAvzoh9/nr/78z1hZXScME06fPo0gyiwv1LHtCXEiMFXJIesaRwMbUjh5cg3NKrC2tkDOtHj7\n6jWGzpg0CpBK04x9kSgJsaw89x5sMuj06R4docgKQeQjqxKqoXPhwgUcx2F+fu6R9BwEoigL9k1S\nMHSdjpOnVJwn9gXmpiyS0McySmz2Ig67Npev38aOUqZnqowHHRozNdI4ot88oNfZ5803fswLzzxL\nu9PiqScf4zPPPMvqyjoXLpxncXaaIAbbjSlWqvzN935IGMakqUCtWKCQ0xEUlf1Oh2986xd59tnH\n0WQjg9cWTM5fPMfnvvAFekFKe9Lj+r27uEHCYWdIu3NI92iA74bsHRyxf7DP+c+8gB345CoSm7ub\nmcfCsuiNRp+4Gj8lTQE812N1ZQXLytFqHfHjH79Nu9V+BFD5SVPITEjHhPfs0/fYQh0EAenxUV2R\nM3l0pVKmVCowNVVleWmRQjFPIZ+nXC7RaDQoFktIkoym61hWjnq9jmXl0DQd07IyeEuYYBjmI66D\nqqkIZKTeNE0Rj9HtmqYTpwmynLEf0ySjRmfrU9BUDfGnoDCaotBqHjAcDvA9lyAO6Q+6GIaJaVrY\nYxdF1YmihNFkQr5YoFqvo5oa0zNllurTxJGAaRVoHhwwGg3Z2N+m2W9RyGssLzWwPRs39ImiAF1U\nCfwAdBF12qAwl8OOXCzdZHV1Dk1NCKKEKMm0H+Yxtjyf04klmdB1SB0bDTDllGG3hT0Z8b3X3ySR\nNWr1GX7hq18iDQPs8RDfdSiYGpaUUKrWaHc7RKENaYSgiJy5cIbDvW1Us0gqZgFAkiiyu73B7Vub\njKIYT5AxShZzc3UG3R53mj3eu3qPimmhihqikkMUYNgbIEkyggiSIrG9u4GeM/jqz/88Tz39FIos\no6kakqhQrZWp1SqIIkycgO/89X0Oj0Jmpw1k0UGTwA9iNsYeWrlIe9jHDkNCEeQkJm9IyKrEycUF\nAm+Irqng++RMk8Ggj6qpOK7HjWvXWV5ewgsiZFVhc3uX+bkGM7OzeH6M7zjkLZUwTeiOx9y4dYud\nnU3q9Tl29rpIJPhuyOb2NoGmo5aKJKrKOEi4t7XPwtwMp0/OowgpraMjrl+5zF++cYW7O4fUGjUm\nyYS9wz3a/UNm5ht/S9X97a9PRVNQNYV2p8/dO/cBAccNOWj2GI19omOzzk8YjcIxrejhiSEmCFwg\nebSBqNdqSIg89/zTfOPrX+aXv/VNTq4v8Oxzz9BoLDC3sMTFx59icXmV+cVlcrkChVyR6eocqp5H\n1S2KpQb5/CyqbpGKAvlCLVMqKjJBkBKlCVGa+RxEWUFWsu0EMaiyiiwrTCZjdDPTKkRJjOPaCCSE\nQYBAwqh/QGf/HlISYhgqWrGGILs4wYA0cVARMBSDw2aXYOzx4Xsf4fgu3VGXcimhMB0fB5gmzM/M\ncbjdYrB7gGgPeeLMGr1RmzgRUAKZSXdCKqqcXF0kJ0NaSLFOKHzp259FVRLOnT4FUcqUKdOYKnJy\nyuIXXj7NxVNTlDQDs5iHKGHc79MZ+ZxbyfPB1S1SwaLvd7jz9pu8+/YHVOsLFGemmYzHuLaH5Nh8\n/azKrfff5NqDJvu7TRQBtrabfO8H7xB4Ie/fHXDiyZfpHPWx8gbrhsyvnVP57q0uH/QF7P4QLdS4\ns9POIuUUqPoTFuSE1ZVpUiSiVECXRIx8iedfepGTqwsoqs5Bd8T+XhNLtQj9CEXReflLXyBJfU6c\nXKe+sszJpWn+6b97hWjxIsNxyOzsNMX5OUbOhMfPrTLpH/LKpXtcO+gjJgnt9pCjicP9VofNnsfI\ns6mtL6IbMjcf3OWgfcgPX3+VjQf3OegcgSqj5g2QIya9Q6TQ41d+6Rvc2N1lqzVEDLKgl85+i06/\nQypNKOQUDKPAN7/xVaQkYMoykFOVoqZRnSkTOW0OtjuoZoWF1UW6do8D3+G1d9/AkxNu7/UJZIPT\nT19gdvkE+/e2P3E9fiqagiAI2b5fkjhstY53yrXjNKcUxP9Yq/BT1wlAEEFVJGQR6lNVVFVmbW2V\nubk55hcXacw2yBdLLCwuoZtGVsC6iaxoKKqOomhYZh5JzcCuqmagGxaqrmMYVhbo8tBPcWx4yhKt\npZ8SUWVg1TRNs8QeUSCOExAlNMNE14xMUpvEiGLK/tZ9Bq0DLFUg8Mb4fraBiJKYWq1MmiaIQL06\nzWJjlSef+ix5s4Qhm/i2S9fu8qB5B12B7kGLJJIoFOrMzSxzuD9kNPE42D9CEiROnTxJHHqIIlTK\nVQQESMVMfZdEWDrcvHKbNIGVao10EjMWNb7/2oe4fYfReEiz1SFfyTF2QmI/pnXkcn52huVijp//\n8ldYqVi8/d5lKtNLBImIVVD46ssXWNBE6iUDU5QyqXqaZknIqopVyJMqIoYa4bgyenmegeNxeaPP\n/FwZ1/ZpjXwqtTp7/THFok41r+CnAZXpGRBlXN+nUqlkVzoB/NGYo519JGT67TZiGPH+Bx8REKAo\nMVNTeYJul8k4Iq/pzORFnrgwy1bL4y/euYlamcNJEi5v7bI/SbEjOHP2PI2pKarFIqVagUhQ8Z0Q\nzTIhSZn0evz5d/6Emdk5qmaexAs4d/YMm1u75DUT4oRBe4CqKBiazqDT5Xt/8yquk6LreYrFPFPV\nEkkYsH/vPqEbsN1ssjBd5fd+7w84sj0O9loctVvsNzt02n1qlWnWV2f56KPLjIYDCtU8kSTw3/7j\n/5zm9i6mYeFNBJxApLF6kp77yQNmPxVNIU1TFE0mSUNkJTta9/t9CoXcsSoxPXYqCo+m+Q+bRJzE\nj+LZcrkcYRhSqVT49d/4DR5/4klW1k6ysnKCWm2GtfWTzM7OU67WSZDQjByGkUNRDXK5IkGYYuWK\nTM/MoWompWKV6ekGSZKlVllWDs8LMzz8MUb+oUZCkmUEQcCyrEfgFM3Q8DyPKIEYgfF4jD0eMmof\nEPR3OXrwMeOjXTQZTF1DlxRcz4cwRjM1Pr50i8D2MWWZ0aDLyvIsJxZWKBsFvHSCWbGI4ihbkQ1D\ndDWPKMlU6hX+8tU3UNUCea3Ig3sbPHbhLAUrz9bWLoIgI6QyaRSTpgG1+RofXb/Mi88+ha5ERGQ5\niZ5c42ivw8geUyyYxCL4AqiazqYjsnHY5NY7b/Hdv/4bfvvv/iKt3iH/8l/9C+q5POPBhPqUznd+\n/7+nrkZ8cdHk5S+8hKZpREmMqhs8/dlnOHP+LIJa4v3bH7Dntpg2FKyiwl/dTUCzGKUyndGIwPco\nKBEztSKd7oR7zTE9N+HW/Saqkl0V/TAEQWT/oEnfF+gPB+zv3Of0iVMIaYwXw2PL02xsHuL5Pp97\n4gl+9VSBZnubz//sBXaORtze7HJq8Txn1p/EqJa4srnP9c19SlMzLC4sMphEjD2H2fo0B/aA0+dO\noqg6ThDyYLdJtVSkvb/DtQ8/oloucfv2XURSrLyCEMf4vk8gSoSAaRYQ3ABZDNnbbdF2ZfzEwPNl\nojDm1p076JZJLKlIZgE3hep0g/UT5xBFifXVFX725WcgSJgtGHz98xf4N//mX3L27DmUWKAzsCnE\nJqvSGDNyPnE9fiqagiAKIGao9zhOUJSMXRjHKamQYVT+ttfDxpCmP5k7iKJILmdmltxCmXyuSK5Q\nolqrYxgWpWIZM1dA1Q1yuUKWch2lWdxbGBIEIaKkHJ8kVDTVwDTziMdg2cxMlTUo+diSndGfstNO\nmqaMRiOC8Bi04voYxjH1RkiZjIfs7W4z7B4yVTTQ1cy0I4gSAjK6YVHMlyiXiyzOl9k72OXO3eu0\n23tEkU0ce8frNQkx1OlOHA5HQ5AFbHvA1vFdulAq0e0OeHB3E1GQOWq1icMQe+Jw8+ZtIi9i0B8i\nibB0psH5506TL+n4sszBaIQ37tM8OiQVBQQxYyE4E5cgSZB0DTcMUGKfYs0giQV8WSA3PY1kCgzd\nDrXpGWxfR8mvMz+/SiWv0+11EASBMIpRZY0H9zfY3XzAvf0uB7sDnL6NQMxo7PLW7QPqi/OYOQVD\nVpmbnyWvG7T7PpWZWU6cO83drV38wMf3XUQxJVfIo1saSRIy3aihqwLPP32B5dk6494YASjlC2j5\nEnNLDd774D3utWxWF+ewCgaCIjMMHA7dPkNvwng8QEwjpmozeEHI7lGXWj7HU2dOgj1h0p8gumMa\n1SqaYtLca7G1v4esytRKRXrdAXqhSOQnqIhM1ar4nk/geNTrdco5kyT2cbo2C/UypmZwcNSnMVtB\nEiT6bohhGfjDAb/1O79Nf+gwmDjcuXcbq5Dn2rW7FAtlGo08X3npee5evkl35PDuu1f4B9/+NeYa\nVfa27nDr46ucOLv8ievx09EUBJF6vY4gppimDkAQJFkWItkVIcuWTP+jrxMym7IgIEnycVOJKZfL\nBJ5HsVjEsnIkicDU1AyyrKBqGqqSiWQEIVtrBoFPHP9ke5GRmFQEst22oqqkiCiKTs7KI8vycaJ1\n+ggB9zAoNo5jxuMs4ddzXUhTBv1BRoiKY0QhRUwjWvvbbN2/S5rGRHHMyHYI/ZjQT4iDBHcyoVgs\nkCvmWD+5wpnTa4xGQ0ISrt68joyB3c+QYM1Bn+v3bjEc9UlJGQz7zC0vMJrYiKlC3iwyGjq0D9tI\ngsS5c+cQBAkhEdnd2UE2UgLZ5m/efo+hGzMJExRZoWzILMxNo5k6siiiajp6zqQ/HFIqyBiWztBx\niGKZrb5DhEBnMObOvR0OW4f0RiG/+90fcufAxphe5v79e2iaimWa2KMJOxtb6JLM0PZIUwUBk9n5\nJXTLwqgWeLC7RxK4qIqEP+kRexE3Nw4YRTKFyhT5cpXF1XmeePxxpo9zNTxnQhoHFHSRRkkDp8/+\n5ga6kvEq/vx776BpGkHgY+kyojWNqui0BzaKplJbmOXy3Vt8ePkDFASciU2Ypnx45TKXrlxBlyXq\n1QKmqaDIIv7gCF0Cy8wxcR1UU+eo06ZQtIhT8OKQE2tzLMzN0Wg0ECQR0pTNjW16gzblaom1hSnm\nqjlKVkqiCRy0jviFb3yZXN7gwYNN5mameeudt5mbW2B6eoaVtVVM02L/sEOSZFu29z78kLvbHfw4\n5sSJGq+/9jpnFqocbN9na3eLpfUTn7gePxU6BVmWyZk6q8vz7O42SRMBVRYZDe3jIZ2XCX+OG8ND\njYIgCAhSxju0LBNFFomiAN8ZYY977O1uMTVVRdN1GnPzGGYBVcnSlyUUnNAm8Cb0ukf4jgFijKpq\nhH6AZeSI4gRZUchZBZJUQFU1ZFkhl8sxHA6RJZlUy4hRWXMJ0TQVQYLDg11kVUUgwXNdPNem3WwS\nuiPccYda0cAdjumOAmJJQdMsXDelkKugCCqlvEan2+Tu5i75YgFZUFhcXOfBfov5lVNYUcrMygor\nSzD0xzTm60iuyOUfv8XC7CKD0KZWq1K2SvT7DnNzazhjj2anSRrFRG6ME4QIQsj0nIQUaXzxHz7G\nh680GYZjHl+doeBMULwBipDgphEBETISpZzGieVZotAmFkXe+tG7vPHW25iSwGqjgFCts3PQ4cbV\nTa5cvsIpw+PGQGbkxSwvzeB5PssLixiSwGRwhCUmSKbF0+dP8+Ybl1ldbjAZDumOHJ4+dY6bu3d4\neXmeH775EdsyTASXjbfepTcckI+K6PI+uqZiBx6WrmOICpODXR5/6ixKxeL1Nz4kliUWG1MkvkLO\n0DjYvsfj64ucMgQOdjoIQp4olXAdAVGwMI2QJJyQyAmiJPJb3/473Lp5lb3dLh/fuMmLL3yW5OO7\nfPnZBV559T2m62tsH+yjiRZKLs8k8EEV6XQG1Esltg9aaJrM6VOneOfyVUgiYkkmTickPZmRm3Lk\nh6iazP2tFlOVTZ47fxo1V+KPvvOXPPeFz1HQkgyFJ+XY3buBUcxx+/59klgjX5/DmpsQhhJH/T6V\nosv6VI7KN79Mapm88eP3PnE9fipOClEU4dgOlWqJpaVZUmLCMEEgIx2Lx4O8h6+fXBtSkihGUyQq\n5SKKLOCMBrj2gG5rnzjwUcSMuFwsFNE0HVVVj5Ok0mM4S4TtjPG8CaNhnyjwEMmGhRnZRUQzM9aC\nQGZ0+mnEWxRFSHIGh82YjDK9fp9KpUy320FIQSBBlSV0WSD0xsTuGGcyJAr8DN5i2+RLJa5evc2g\n0yfwIy5/cInaVINhP6TfGbO702Lj/iaDwYgkFHlw84DXf/Rjhu0jXvl/X6XVbNEdjEBUSBPY3tlG\nEFPyZp7AjxgOx8zOzjMejzAMA8uy0BUDUzfZ2j4AVPYPN9k93MX2PKIwJAldFmfq5HQNSInTiMiP\nqJUKCFHEVKGAJqZYqkacgJaK/NP/7r8imbRZW5xmPOgjpAIvPXuWxYUKpaJJsZgnSWMebG4SJTGF\nQp6lmRxCYtPvtKiVdAaTMd7EQZEM7ty+i+v4VCsVCpZA33EZuw6O4yLJCoIAo2Gffr8LgoAg6Zw4\nfZ6tB9vcurtJe+hRqtYpV0rUalVyisTdB3d58twZnrp4kfPrJWqlCteuvEcYOkxGPjIqh4cdzLyF\nLCkIcUIwGTE3PcXH168xGrh0uj16rS6KZhI5AQ/u3uKJpx8n9gN+6zd+k+deeJ5cLk/eMJmemeMz\nzzyJKCtZNmQ5T5KAKcjUJZA8n5yiMxl7OJ0hOUPl5t37rC0ucLh/QCLKJH6INx4ghCFplPLcs5+j\nPFUGQaBSLNFtDegf9VhZOUm7PyGNR/zgzQ8YjnvEgs7W/c1PXI+fiqYAKcVcnk7rkOlaBVNTKBd1\nQMAPvOMgl/9w+/Dwl0AWdCGLCWngUq8UKGgyQugRug6SJJE3LeRjhkKaQuD5j0hNSRwgiylR5BP4\nDvfv3SYMA3zfQ5FkkMTjbEiBVBQy4AhZvkMmS04Rj1Ohi8Uiu7u7zMw06HTaaIqM7zlIgDMa4jsj\nLFWgaMpYWnY6yijMEofNQ6ZmS9n3Fqc899yLKGqONBAQIol+zyUVRIQoZNjqsLpwklPrJxm0h/zD\nX/0VHty4x+7uPvXGDMVKmdnZuWN4bUp/OEA1THzXZXV1lVbrEEkQs8xDUUWUVe7duk/e0Hjpi6d5\n/uWTOPaYWmORW3du0KhUKFg5dFmlXtR57PwZxt0WBSXFJEASBYREZeBEDI4GvPz8Ci88u8LpUw0M\nRWLanKKQJCRRQOB7uJ6PqpscddvEUkqjLrA2LSLZY06dOEF7NCDxAkaDAaou8tknHuePv/9j5hsV\nVE1HUBSSNHveruuyMD/HzMwMlmURJWC7IY89dpGjwYT3rt3jqDdkeX4OPJdk0mFvN8PZ/9n3X+P1\nW5e5eekSp8+cIBJkuqMRThyiF4qcOXOSSIhRcxZbm9usLSwRCSkIMjduX0fKWXz39fd48Ss/w/nH\nz5DTNT7/+c8zmdgUciWiOCJNYX19nacuPk6n0+bMmTOcWV1Hk0ANXL72zAnq9TKJM+Hk+iJqnBD4\nEaOJzfsffESr3cYyTZrNJjlDI/Em3LvxMYEzwbYdmgcH3Lt9h1F3xAtPXaCYN/jyyy/i2j7DyGa/\n0+LVN15HN4ufuBo/FTTnf/JP/pf/WZbAUFUm4wFf+8bXuHnzBtVqAVXVsR0X+ImACXiUK6mqErIY\nMVevYEgxMyULXYooF0zOXniS6bkFdN3AymVXhxSBbqeN69lMJkPsUY8kDhiPuwx7beIoQJINVFVD\n1QwUTSWKYrJk2JQoCJElEVWRMyusF2S26jDCtieYpkES+bjOGNe1cRyXbrvFzuYGR7sb7N6/Tr+1\ngxR7xFGAmwrkq3X2jlo0luvIacLRYRsSnXxlmqlchfmZBktrJxgMurzw7GNs3byGY8P2TgtJFrj8\n3sekE5+19SUO+ntcuX6FXL7I4twCm3fvsX76BMPxgPWlZTRD5qjTQkwkNF1l4mQcg+XZeTxvQqXi\no+YiAhdGfZcTK3O09gfsN7vMlovIUTbY2+6MKeYN5uplHrR7uLbHxXNnYHuXx86tko4OOep1OeiO\nWH/6M7xx5T6z01OMJmMmrkdjcZHuoMNw1ONf/A/fxhKGXL3foVwsoxgW+wdd6hWdgIjEcVBKdb54\nZpF7LZtSsYSs6IiyiKqIlEolHMejddiiaMooacDXfvY53vnwMutnznL/9k1KcoI0GvDU+SWi8Zhb\nrR5bh23OnDnNK2/vcG8QoucNxkGCkwYoqshUrYzjOOw+2GcymRBGCU7goAT/fztnExNXFYbh5w20\nlVosUoQQShW0/jSmUSQGk8rGqC0bdNeVXZi40UQXLjDddKuJLkyMC2OTaozdqLEbE39iNKbyUxtK\nQQIdKtoSCkWoxRoqyufiHuIMYYC0M3Pu4nuSm3vm3JvcJ++d+XLOmZu7RH3NNqbnF6nedT99p4d4\n7PE2+k72ULH9Nnp6eynXJsYy4ywsLpIZG+NkXw9aWmJubhYrh9raWi5OzvCPrtP92xwVFbfwF/PU\n7mxkdn4eKGP22gLTM1dhYYHKqgqqtm7nz9lLtO59gHvva+aH77r5ffoKuxrquHz1CpnRX3nwnh0s\nzl1geGSO/U8+Qfsje2koL6d2axk/np/a0NuctXLxLgaSLgPXgJnYLlnU4D7rkTYn91mbO83sjvVO\nSkVRAJB0ysxaY3ss4z7rkzYn9ykMKVlTcBwnLXhRcBwnhzQVhXUXQEqM+6xP2pzcpwCkZk3BcZx0\nkKaRguM4KSB6UZC0X9KIpIykrkgO45LOSuqXdCr0VUv6StK5sL+9yA5HJU1LGszqW9VBCW+HzAYk\ntZTI54ikiZBTv6SOrGOvBZ8RSU8XwadR0reSfpY0JOnl0B8zo3xO0XIqCNlPB5Z6A8qAMaAZ2Ayc\nAfZE8BgHalb0vQF0hXYX8HqRHdqBFmBwPQegA/iC5EHsNqCnRD5HgFdXOXdPuHdbgKZwT8sK7FMP\ntIR2JTAarhszo3xO0XIqxBZ7pPAokDGz82b2N3Ac6IzstEwncCy0jwHPFPNiZvY9MLtBh07gA0vo\nBqokbfx9Wzfuk49O4LiZXTezX4AMyb0tpM+kmZ0O7XlgGGggbkb5nPJR9JwKQeyi0ABcyPp8kbVD\nLRYGfCnpJ0kvhL46M5sM7UtAXQSvfA4xc3spDMePZk2pSuoj6S7gYaCHlGS0wglSkNONErsopIV9\nZtYCHABeGcA8HwAAAWdJREFUlNSefdCSsV/Uv2nS4AC8C9wNPARMAm+WWkDSNuAT4BUzy3lFcayM\nVnGKntPNELsoTACNWZ93hr6SYmYTYT8NfEYypJtaHm6G/XSpvdZwiJKbmU2Z2b+WvF//Pf4f+pbE\nR9Imkh/fR2b2aeiOmtFqTrFzulliF4U+YLekJkmbgYPAiVIKSLpVUuVyG3gKGAweh8Jph4DPS+kV\nyOdwAngurLC3AX9kDaGLxoo5+bMkOS37HJS0RVITsBvoLfC1BbwPDJvZW1mHomWUzylmTgUh9kon\nySrxKMlK7OEI128mWRE+AwwtOwA7gG+Ac8DXQHWRPT4mGWouksw1n8/nQLKi/k7I7CzQWiKfD8P1\nBki+4PVZ5x8OPiPAgSL47COZGgwA/WHriJxRPqdoORVi8ycaHcfJIfb0wXGclOFFwXGcHLwoOI6T\ngxcFx3Fy8KLgOE4OXhQcx8nBi4LjODl4UXAcJ4f/AEtSV1i74rlAAAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "temp, mask = explanation.get_image_and_mask(240, positive_only=False, num_features=10, hide_rest=False)\n", "plt.imshow(mark_boundaries(temp / 2 + 0.5, mask))\n" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "Or the pros and cons that have weight at least 0.1" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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Xt6iymlfvvIXrM/72v/t3+Vt/4++g0HhryXQxMfLW4YYBN4wMfX/DrkeyLMP7AAFynZOS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UaNwPeI44CjVoso8rL8ijhhMnHQNA1F1VhfP8H9nT1UM4eXwL2dfRRDR1Ykuv0eiiqYry9h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\nLqQfqpqz+OTkXTsQQmwCFSDTbpdtdOH5PIi95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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "temp, mask = explanation.get_image_and_mask(240, positive_only=False, num_features=1000, hide_rest=False, min_weight=0.1)\n", "plt.imshow(mark_boundaries(temp / 2 + 0.5, mask))" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Let's see the explanation for Egyptian cat " ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "Most positive towards egyptian cat:" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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f9z/j+/59vu/fFwqF3mIzAoHv7PZy4YMrq/i+QygUptPpkUgkeOyxL7G1tYVt2fR6Pba3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\nfAev+u/Ponugj8Rv0p3LYbQE1UqD7t5emmEAmkY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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "temp, mask = explanation.get_image_and_mask(286, positive_only=True, num_features=5, hide_rest=True)\n", "plt.imshow(mark_boundaries(temp / 2 + 0.5, mask))" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "Pros and cons:" ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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bPsB4OKCiIrnE5dMtT588ReTIal5TG0MOjrOjI8au48bRKSJJjJ5z4/bzFPWC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4QRM86QwAlXSah4iuc4YYJAsmHLEzzNV3mThzzCZPvuve56LnXX8PwHnmUwHVHOLzAsga7pHARj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\nDH0u/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knX2Kx36AxdMpZFbqzCc899nQtXb6DrGt1mi/pejVioDG2fgRNSrzdxtAzVvodi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\nrA4lVvZ2ufbKS/zJX/4Vv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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "temp, mask = explanation.get_image_and_mask(286, positive_only=False, num_features=10, hide_rest=False)\n", "plt.imshow(mark_boundaries(temp / 2 + 0.5, mask))\n" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.5.2" }, "widgets": { "state": {}, "version": "1.1.2" } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: doc/notebooks/Tutorial_H2O_continuous_and_cat.ipynb ================================================ { "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "import sklearn\n", "import sklearn.datasets\n", "import sklearn.ensemble\n", "import pandas as pd\n", "import numpy as np\n", "import lime\n", "import lime.lime_tabular\n", "import h2o\n", "from h2o.estimators.random_forest import H2ORandomForestEstimator\n", "from h2o.estimators.gbm import H2OGradientBoostingEstimator\n", "\n", "np.random.seed(1)" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Checking whether there is an H2O instance running at http://localhost:54321. connected.\n" ] }, { "data": { "text/html": [ "
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H2O cluster uptime:2 mins 30 secs
H2O cluster version:3.10.4.8
H2O cluster version age:16 days
H2O cluster name:H2O_from_python_marcotcr_ph8pt1
H2O cluster total nodes:1
H2O cluster free memory:5.314 Gb
H2O cluster total cores:4
H2O cluster allowed cores:4
H2O cluster status:locked, healthy
H2O connection url:http://localhost:54321
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H2O internal security:False
Python version:2.7.13 final
" ], "text/plain": [ "-------------------------- -------------------------------\n", "H2O cluster uptime: 2 mins 30 secs\n", "H2O cluster version: 3.10.4.8\n", "H2O cluster version age: 16 days\n", "H2O cluster name: H2O_from_python_marcotcr_ph8pt1\n", "H2O cluster total nodes: 1\n", "H2O cluster free memory: 5.314 Gb\n", "H2O cluster total cores: 4\n", "H2O cluster allowed cores: 4\n", "H2O cluster status: locked, healthy\n", "H2O connection url: http://localhost:54321\n", "H2O connection proxy:\n", "H2O internal security: False\n", "Python version: 2.7.13 final\n", "-------------------------- -------------------------------" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Start an H2O virtual cluster that uses 6 gigs of RAM and 6 cores\n", "h2o.init(max_mem_size = \"500M\", nthreads = 6) \n", "\n", "# Clean up the cluster just in case\n", "h2o.remove_all()" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "## Wrapper class\n", "\n", "We need a wrapper class that makes an H2O distributed random forest behave like a scikit learn random forest. We instantiate the class with an h2o distributed random forest object and column names. The predict_proba method takes a numpy array as input and returns an array of predicted probabilities for each class." ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": true, "deletable": true, "editable": true }, "outputs": [], "source": [ "class h2o_predict_proba_wrapper:\n", " # drf is the h2o distributed random forest object, the column_names is the\n", " # labels of the X values\n", " def __init__(self,model,column_names):\n", " \n", " self.model = model\n", " self.column_names = column_names\n", " \n", " def predict_proba(self,this_array): \n", " # If we have just 1 row of data we need to reshape it\n", " shape_tuple = np.shape(this_array) \n", " if len(shape_tuple) == 1:\n", " this_array = this_array.reshape(1, -1)\n", " \n", " # We convert the numpy array that Lime sends to a pandas dataframe and\n", " # convert the pandas dataframe to an h2o frame\n", " self.pandas_df = pd.DataFrame(data = this_array,columns = self.column_names)\n", " self.h2o_df = h2o.H2OFrame(self.pandas_df)\n", " \n", " # Predict with the h2o drf\n", " self.predictions = self.model.predict(self.h2o_df).as_data_frame()\n", " # the first column is the class labels, the rest are probabilities for\n", " # each class\n", " self.predictions = self.predictions.iloc[:,1:].as_matrix()\n", " return self.predictions" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "## Continuous features" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Loading data, training a model" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "For this part, we'll use the Iris dataset, and we'll replace the scikit learn random forest with an h2o distributed random forest. " ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "iris = sklearn.datasets.load_iris()\n", "\n", "# Get the text names for the features and the class labels\n", "feature_names = iris.feature_names\n", "class_labels = 'species'\n" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Parse progress: |█████████████████████████████████████████████████████████| 100%\n", "Parse progress: |█████████████████████████████████████████████████████████| 100%\n", "Parse progress: |█████████████████████████████████████████████████████████| 100%\n", "Parse progress: |█████████████████████████████████████████████████████████| 100%\n" ] } ], "source": [ "# Generate a train test split and convert to pandas and h2o frames\n", "\n", "train, test, labels_train, labels_test = sklearn.model_selection.train_test_split(iris.data, iris.target, train_size=0.80)\n", "\n", "train_h2o_df = h2o.H2OFrame(train)\n", "train_h2o_df.set_names(iris.feature_names)\n", "train_h2o_df['species'] = h2o.H2OFrame(iris.target_names[labels_train])\n", "train_h2o_df['species'] = train_h2o_df['species'].asfactor()\n", "\n", "test_h2o_df = h2o.H2OFrame(test)\n", "test_h2o_df.set_names(iris.feature_names)\n", "test_h2o_df['species'] = h2o.H2OFrame(iris.target_names[labels_test])\n", "test_h2o_df['species'] = test_h2o_df['species'].asfactor()" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "drf Model Build progress: |███████████████████████████████████████████████| 100%\n" ] } ], "source": [ "# rf = sklearn.ensemble.RandomForestClassifier(n_estimators=500)\n", "# rf.fit(train, labels_train)\n", "\n", "iris_drf = H2ORandomForestEstimator(\n", " model_id=\"iris_drf\",\n", " ntrees=500,\n", " stopping_rounds=2,\n", " score_each_iteration=True,\n", " seed=1000000,\n", " balance_classes=False,\n", " histogram_type=\"AUTO\")\n", "\n", "iris_drf.train(x=feature_names,\n", " y='species',\n", " training_frame=train_h2o_df)\n" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "ModelMetricsMultinomial: drf\n", "** Reported on test data. **\n", "\n", "MSE: 0.0270187026781\n", "RMSE: 0.164373667837\n", "LogLoss: 0.0874284925626\n", "Mean Per-Class Error: 0.025641025641\n", "Confusion Matrix: vertical: actual; across: predicted\n", "\n" ] }, { "data": { "text/html": [ "
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setosaversicolorvirginicaErrorRate
11.00.00.00.00 / 11
0.012.01.00.07692311 / 13
0.00.06.00.00 / 6
11.012.07.00.03333331 / 30
" ], "text/plain": [ "setosa versicolor virginica Error Rate\n", "-------- ------------ ----------- --------- ------\n", "11 0 0 0 0 / 11\n", "0 12 1 0.0769231 1 / 13\n", "0 0 6 0 0 / 6\n", "11 12 7 0.0333333 1 / 30" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Top-3 Hit Ratios: \n" ] }, { "data": { "text/html": [ "
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khit_ratio
10.9666666
21.0
31.0
" ], "text/plain": [ "k hit_ratio\n", "--- -----------\n", "1 0.966667\n", "2 1\n", "3 1" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# sklearn.metrics.accuracy_score(labels_test, rf.predict(test))\n", "\n", "iris_drf.model_performance(test_h2o_df)" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Convert h2o to numpy array" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "The explainer requires numpy arrays as input and h2o requires the train and test data to be in h2o frames. In this case we could just use the train and test numpy arrays but for illustrative purposes here is how to convert an h2o frame to a pandas dataframe and a pandas dataframe to a numpy array. " ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": true, "deletable": true, "editable": true }, "outputs": [], "source": [ "train_pandas_df = train_h2o_df[feature_names].as_data_frame() \n", "train_numpy_array = train_pandas_df.as_matrix() \n", "\n", "test_pandas_df = test_h2o_df[feature_names].as_data_frame() \n", "test_numpy_array = test_pandas_df.as_matrix() " ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Create the explainer" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "As opposed to lime_text.TextExplainer, tabular explainers need a training set. The reason for this is because we compute statistics on each feature (column). If the feature is numerical, we compute the mean and std, and discretize it into quartiles. If the feature is categorical, we compute the frequency of each value. For this tutorial, we'll only look at numerical features." ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "We use these computed statistics for two things:\n", "1. To scale the data, so that we can meaningfully compute distances when the attributes are not on the same scale\n", "2. To sample perturbed instances - which we do by sampling from a Normal(0,1), multiplying by the std and adding back the mean." ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "#explainer = lime.lime_tabular.LimeTabularExplainer(train, feature_names=iris.feature_names, class_names=iris.target_names, discretize_continuous=True)\n", "\n", "explainer = lime.lime_tabular.LimeTabularExplainer(train_numpy_array,\n", " feature_names=feature_names,\n", " class_names=iris.target_names,\n", " discretize_continuous=True)\n" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Create the predictor wrapper instance for the h2o drf" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "We have a trained h2o distributed random forest that we would like to explain. We need to create a wrapper instance that will make it behave as a scikit learn random forest for our Lime explainer." ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": true, "deletable": true, "editable": true }, "outputs": [], "source": [ "h2o_drf_wrapper = h2o_predict_proba_wrapper(iris_drf,feature_names) " ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Explaining an instance" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "Since this is a multi-class classification problem, we set the top_labels parameter, so that we only explain the top class." ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Parse progress: |█████████████████████████████████████████████████████████| 100%\n", "drf prediction progress: |████████████████████████████████████████████████| 100%\n" ] } ], "source": [ "# i = np.random.randint(0, test_numpy_array.shape[0])\n", "\n", "i = 27\n", "# exp = explainer.explain_instance(test[i], rf.predict_proba, num_features=2, top_labels=1)\n", "\n", "exp = explainer.explain_instance(test_numpy_array[i], h2o_drf_wrapper.predict_proba, num_features=2, top_labels=1)" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "We now explain a single instance:" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [ { "data": { "text/html": [ "\n", " \n", " \n", "
\n", " \n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "exp.show_in_notebook(show_table=True, show_all=False)" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "Now, there is a lot going on here. First, note that the row we are explained is displayed on the right side, in table format. Since we had the show_all parameter set to false, only the features used in the explanation are displayed.\n", "\n", "The *value* column displays the original value for each feature.\n", "\n", "Note that LIME has discretized the features in the explanation. This is because we let discretize_continuous=True in the constructor (this is the default). Discretized features make for more intuitive explanations.\n" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Checking the local linear approximation" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[ 5.1 3.8 1.5 0.3]\n", "[ 5.1 3.8 1.5 0.3]\n" ] } ], "source": [ "feature_index = lambda x: iris.feature_names.index(x)\n", "\n", "print(test[i])\n", "print(test_numpy_array[i])\n", "\n", "# hide the parse and predict progress bars\n", "h2o.no_progress()" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Increasing petal width\n", "P(setosa) before: 0.993871818745\n", "P(setosa) after: 0.523090430918\n", "\n", "Increasing petal length\n", "P(setosa) before: 0.993871818745\n", "P(setosa) after: 0.523090430918\n", "\n", "Increasing both\n", "P(setosa) before: 0.993871818745\n", "P(setosa) after: 0.0523090430918\n" ] } ], "source": [ "print('Increasing petal width')\n", "temp = test_numpy_array[i].copy()\n", "print('P(setosa) before:', h2o_drf_wrapper.predict_proba(temp)[0,0])\n", "temp[feature_index('petal width (cm)')] = 1.5\n", "print('P(setosa) after:', h2o_drf_wrapper.predict_proba(temp)[0,0])\n", "print ()\n", "print('Increasing petal length')\n", "temp = test_numpy_array[i].copy()\n", "print('P(setosa) before:', h2o_drf_wrapper.predict_proba(temp)[0,0])\n", "temp[feature_index('petal length (cm)')] = 3.5\n", "print('P(setosa) after:', h2o_drf_wrapper.predict_proba(temp)[0,0])\n", "print()\n", "print('Increasing both')\n", "temp = test_numpy_array[i].copy()\n", "print('P(setosa) before:', h2o_drf_wrapper.predict_proba(temp)[0,0])\n", "temp[feature_index('petal width (cm)')] = 1.5\n", "temp[feature_index('petal length (cm)')] = 3.5\n", "print('P(setosa) after:', h2o_drf_wrapper.predict_proba(temp)[0,0])\n" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "Note that both features had the impact we thought they would. The scale at which they need to be perturbed of course depends on the scale of the feature in the training set." ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "We now show all features, just for completeness:" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [ { "data": { "text/html": [ "\n", " \n", " \n", "
\n", " \n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "exp.show_in_notebook(show_table=True, show_all=True)" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "## Categorical features" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "For this part, we will use the Mushroom dataset, which will be downloaded [here](http://archive.ics.uci.edu/ml/machine-learning-databases/mushroom/agaricus-lepiota.data). The task is to predict if a mushroom is edible or poisonous, based on categorical features." ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Loading data" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "# data = np.genfromtxt('http://archive.ics.uci.edu/ml/machine-learning-databases/mushroom/agaricus-lepiota.data', delimiter=',', dtype='\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
01ErrorRate
0849.00.00.0 (0.0/849.0)
10.0776.00.0 (0.0/776.0)
Total849.0776.00.0 (0.0/1625.0)
" ], "text/plain": [ " 0 1 Error Rate\n", "----- --- --- ------- ------------\n", "0 849 0 0 (0.0/849.0)\n", "1 0 776 0 (0.0/776.0)\n", "Total 849 776 0 (0.0/1625.0)" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Maximum Metrics: Maximum metrics at their respective thresholds\n", "\n" ] }, { "data": { "text/html": [ "
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metricthresholdvalueidx
max f10.85802471.03.0
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max accuracy0.85802471.03.0
max precision1.01.00.0
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max specificity1.01.00.0
max absolute_mcc0.85802471.03.0
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" ], "text/plain": [ "metric threshold value idx\n", "--------------------------- ----------- ------- -----\n", "max f1 0.858025 1 3\n", "max f2 0.858025 1 3\n", "max f0point5 0.858025 1 3\n", "max accuracy 0.858025 1 3\n", "max precision 1 1 0\n", "max recall 0.858025 1 3\n", "max specificity 1 1 0\n", "max absolute_mcc 0.858025 1 3\n", "max min_per_class_accuracy 0.858025 1 3\n", "max mean_per_class_accuracy 0.858025 1 3" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Gains/Lift Table: Avg response rate: 47.75 %\n", "\n" ] }, { "data": { "text/html": [ "
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" ], "text/plain": [ " group cumulative_data_fraction lower_threshold lift cumulative_lift response_rate cumulative_response_rate capture_rate cumulative_capture_rate gain cumulative_gain\n", "-- ------- -------------------------- ----------------- --------- ----------------- --------------- -------------------------- -------------- ------------------------- -------- -----------------\n", " 1 0.469538 1 2.09407 2.09407 1 1 0.983247 0.983247 109.407 109.407\n", " 2 1 0 0.0315811 1 0.0150812 0.477538 0.0167526 1 -96.8419 0" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n" ] }, { "data": { "text/plain": [] }, "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# sklearn.metrics.accuracy_score(labels_test, rf.predict(encoder.transform(test)))\n", "\n", "mushroom_drf.model_performance(test_h2o_df)" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Explaining predictions" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "We now create our explainer. The categorical_features parameter lets it know which features are categorical (in this case, all of them). The categorical names parameter gives a string representation of each categorical feature's numerical value, as we saw before." ] }, { "cell_type": "code", "execution_count": 31, "metadata": { "collapsed": true, "deletable": true, "editable": true }, "outputs": [], "source": [ "np.random.seed(1)" ] }, { "cell_type": "code", "execution_count": 32, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "explainer = lime.lime_tabular.LimeTabularExplainer(train ,class_names=class_names, feature_names = feature_names,\n", " categorical_features=categorical_features, \n", " categorical_names=categorical_names, kernel_width=3, verbose=True)" ] }, { "cell_type": "code", "execution_count": 33, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Intercept 0.488622041715\n", "Prediction_local [ 0.38943212]\n", "Right: 0.0\n" ] }, { "data": { "text/html": [ "\n", " \n", " \n", "
\n", " \n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "i = 137\n", "exp = explainer.explain_instance(test[i], h2o_drf_wrapper.predict_proba, num_features=5)\n", "exp.show_in_notebook()" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "Now note that the explanations are based not only on features, but on feature-value pairs. For example, we are saying that odor=foul is indicative of a poisonous mushroom. In the context of a categorical feature, odor could take many other values (see below). Since we perturb each categorical feature drawing samples according to the original training distribution, the way to interpret this is: if odor was not foul, on average, this prediction would be 0.24 less 'poisonous'. Let's check if this is the case" ] }, { "cell_type": "code", "execution_count": 34, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [ { "data": { "text/plain": [ "array([u'almond', u'anise', u'creosote', u'fishy', u'foul', u'musty',\n", " u'none', u'pungent', u'spicy'], \n", " dtype='\n" ] } ], "source": [ "# Generate a train test split and convert to pandas and h2o frames\n", "\n", "np.random.seed(1)\n", "train, test, labels_train, labels_test = sklearn.model_selection.train_test_split(data, labels, train_size=0.80)\n", "\n", "\n", "train_h2o_df = h2o.H2OFrame(train)\n", "train_h2o_df.set_names(feature_names)\n", "train_h2o_df['class'] = h2o.H2OFrame(labels_train)\n", "train_h2o_df['class'] = train_h2o_df['class'].asfactor()\n", "\n", "test_h2o_df = h2o.H2OFrame(test)\n", "test_h2o_df.set_names(feature_names)\n", "test_h2o_df['class'] = h2o.H2OFrame(labels_test)\n", "test_h2o_df['class'] = test_h2o_df['class'].asfactor()\n", "\n", "print(type(train_h2o_df))" ] }, { "cell_type": "code", "execution_count": 46, "metadata": { "collapsed": true, "deletable": true, "editable": true }, "outputs": [], "source": [ "# We don't need to one-hot encode from h2o\n", "# encoder.fit(data)\n", "# encoded_train = encoder.transform(train)" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "We need to tell h2o which features are categorical." ] }, { "cell_type": "code", "execution_count": 47, "metadata": { "collapsed": true, "deletable": true, "editable": true }, "outputs": [], "source": [ "for feature in categorical_features:\n", " train_h2o_df[feature] = train_h2o_df[feature].asfactor()\n", " test_h2o_df[feature] = test_h2o_df[feature].asfactor()\n", " " ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "~~This time, we use gradient boosted trees as the model, using the [xgboost](https://github.com/dmlc/xgboost) package.~~\n", "\n", "We will use the H2OGradientBoostingEstimator which is h2o's version of gradient boosted trees." ] }, { "cell_type": "code", "execution_count": 48, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "adult_gbm = H2OGradientBoostingEstimator(\n", " ntrees=300,\n", " learn_rate=0.1,\n", " max_depth=5,\n", " stopping_tolerance=0.01,\n", " stopping_rounds=2,\n", " score_each_iteration=True,\n", " model_id=\"gbm_v1\",\n", " seed=2000000\n", ")\n", "adult_gbm.train(feature_names, 'class', training_frame = train_h2o_df)\n" ] }, { "cell_type": "code", "execution_count": 49, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "ModelMetricsBinomial: gbm\n", "** Reported on test data. **\n", "\n", "MSE: 0.0926845991628\n", "RMSE: 0.304441454409\n", "LogLoss: 0.29897266577\n", "Mean Per-Class Error: 0.167136137545\n", "AUC: 0.917242377298\n", "Gini: 0.834484754596\n", "Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.402214919768: \n" ] }, { "data": { "text/html": [ "
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01ErrorRate
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50.05005370.87052614.31152284.32621780.9843750.98773010.04236720.2165434331.1522781332.6217814
60.10026100.71760373.50932553.91714610.80122320.89433380.17619370.3927371250.9325469291.7146150
70.15000770.58138142.82534433.55507470.64506170.81166840.14055140.5332885182.5344342255.5074721
80.20052200.46173182.40964353.26652430.55015200.74578870.12172160.6550101140.9643455226.6524272
90.30001540.30278151.44646822.66294370.33024690.60798360.14391390.798924044.6468156166.2943738
100.39996930.19126731.04284752.25807520.23809520.51554700.10423670.90316074.2847536125.8075167
110.50023030.10572530.55001021.91572820.12557430.43738490.05514460.9583053-44.998975391.5728208
120.60033780.05992570.24855601.63772400.05674850.37391300.02488230.9831876-75.144400863.7724043
130.69998460.03820680.12822691.42283840.02927580.32485190.01277740.9959650-87.177313842.2838395
140.79993860.03104270.02018411.24757390.00460830.28483690.00201750.9979825-97.981585424.7573920
150.90127440.02417610.01327261.10879390.00303030.25315160.00134500.9993275-98.672739510.8793874
161.00.01502210.00681181.00.00155520.22831260.00067251.0-99.31882430.0
" ], "text/plain": [ " group cumulative_data_fraction lower_threshold lift cumulative_lift response_rate cumulative_response_rate capture_rate cumulative_capture_rate gain cumulative_gain\n", "-- ------- -------------------------- ----------------- ---------- ----------------- --------------- -------------------------- -------------- ------------------------- -------- -----------------\n", " 1 0.0101336 0.942431 4.24723 4.24723 0.969697 0.969697 0.0430397 0.0430397 324.723 324.723\n", " 2 0.0201136 0.9349 4.37996 4.31309 1 0.984733 0.0437122 0.0867518 337.996 331.309\n", " 3 0.0300937 0.928762 4.37996 4.33527 1 0.989796 0.0437122 0.130464 337.996 333.527\n", " 4 0.0402272 0.91637 4.3136 4.32981 0.984848 0.98855 0.0437122 0.174176 331.36 332.981\n", " 5 0.0500537 0.870526 4.31152 4.32622 0.984375 0.98773 0.0423672 0.216543 331.152 332.622\n", " 6 0.100261 0.717604 3.50933 3.91715 0.801223 0.894334 0.176194 0.392737 250.933 291.715\n", " 7 0.150008 0.581381 2.82534 3.55507 0.645062 0.811668 0.140551 0.533289 182.534 255.507\n", " 8 0.200522 0.461732 2.40964 3.26652 0.550152 0.745789 0.121722 0.65501 140.964 226.652\n", " 9 0.300015 0.302782 1.44647 2.66294 0.330247 0.607984 0.143914 0.798924 44.6468 166.294\n", " 10 0.399969 0.191267 1.04285 2.25808 0.238095 0.515547 0.104237 0.903161 4.28475 125.808\n", " 11 0.50023 0.105725 0.55001 1.91573 0.125574 0.437385 0.0551446 0.958305 -44.999 91.5728\n", " 12 0.600338 0.0599257 0.248556 1.63772 0.0567485 0.373913 0.0248823 0.983188 -75.1444 63.7724\n", " 13 0.699985 0.0382068 0.128227 1.42284 0.0292758 0.324852 0.0127774 0.995965 -87.1773 42.2838\n", " 14 0.799939 0.0310427 0.0201841 1.24757 0.00460829 0.284837 0.00201748 0.997983 -97.9816 24.7574\n", " 15 0.901274 0.0241761 0.0132726 1.10879 0.0030303 0.253152 0.00134499 0.999328 -98.6727 10.8794\n", " 16 1 0.0150221 0.00681176 1 0.00155521 0.228313 0.000672495 1 -99.3188 0" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n" ] }, { "data": { "text/plain": [] }, "execution_count": 49, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# sklearn.metrics.accuracy_score(labels_test, rf.predict(encoder.transform(test)))\n", "\n", "adult_gbm.model_performance(test_h2o_df)" ] }, { "cell_type": "code", "execution_count": 50, "metadata": { "collapsed": true, "deletable": true, "editable": true }, "outputs": [], "source": [ "# predict_fn = lambda x: rf.predict_proba(encoder.transform(x)).astype(float)\n", "\n", "h2o_drf_wrapper = h2o_predict_proba_wrapper(adult_gbm,feature_names) " ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Explaining predictions" ] }, { "cell_type": "code", "execution_count": 51, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "explainer = lime.lime_tabular.LimeTabularExplainer(train ,feature_names = feature_names,class_names=class_names,\n", " categorical_features=categorical_features, \n", " categorical_names=categorical_names, kernel_width=3)" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "We now show a few explanations. These are just a mix of the continuous and categorical examples we showed before. For categorical features, the feature contribution is always the same as the linear model weight." ] }, { "cell_type": "code", "execution_count": 52, "metadata": { "collapsed": false, "deletable": true, "editable": true, "scrolled": false }, "outputs": [ { "data": { "text/html": [ "\n", " \n", " \n", "
\n", " \n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "np.random.seed(1)\n", "i = 1653\n", "exp = explainer.explain_instance(test[i], h2o_drf_wrapper.predict_proba, num_features=5)\n", "exp.show_in_notebook(show_all=False)" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "Note that capital gain has very high weight. This makes sense. Now let's see an example where the person has a capital gain below the mean:" ] }, { "cell_type": "code", "execution_count": 53, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [ { "data": { "text/html": [ "\n", " \n", " \n", "
\n", " \n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "i = 10\n", "exp = explainer.explain_instance(test[i], h2o_drf_wrapper.predict_proba, num_features=5)\n", "exp.show_in_notebook(show_all=False)" ] }, { "cell_type": "code", "execution_count": 54, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[WARNING] in line 1:\n", " >>> h2o.shutdown(prompt=False)\n", " ^^^^ Deprecated, use ``h2o.cluster().shutdown()``.\n", "H2O session _sid_a932 closed.\n" ] } ], "source": [ "h2o.shutdown(prompt=False)" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.5.2" }, "widgets": { "state": {}, "version": "1.1.2" } }, "nbformat": 4, "nbformat_minor": 0 } ================================================ FILE: doc/notebooks/Using lime for regression.ipynb ================================================ { "cells": [ { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "from sklearn.datasets import load_boston\n", "import sklearn.ensemble\n", "import sklearn.model_selection\n", "import numpy as np" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "boston = load_boston()" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "rf = sklearn.ensemble.RandomForestRegressor(n_estimators=1000)" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "train, test, labels_train, labels_test = sklearn.model_selection.train_test_split(boston.data, boston.target, train_size=0.80, test_size=0.20)\n" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "RandomForestRegressor(bootstrap=True, criterion='mse', max_depth=None,\n", " max_features='auto', max_leaf_nodes=None,\n", " min_impurity_decrease=0.0, min_impurity_split=None,\n", " min_samples_leaf=1, min_samples_split=2,\n", " min_weight_fraction_leaf=0.0, n_estimators=1000, n_jobs=1,\n", " oob_score=False, random_state=None, verbose=0, warm_start=False)" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "rf.fit(train, labels_train)" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "('Random Forest MSError', 12.492700792156878)\n" ] } ], "source": [ "print('Random Forest MSError', np.mean((rf.predict(test) - labels_test) ** 2))" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "('MSError when predicting the mean', 101.94960262930775)\n" ] } ], "source": [ "print('MSError when predicting the mean', np.mean((labels_train.mean() - labels_test) ** 2))" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": [ "categorical_features = np.argwhere(np.array([len(set(boston.data[:,x])) for x in range(boston.data.shape[1])]) <= 10).flatten()" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [], "source": [ "import lime\n", "import lime.lime_tabular" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [], "source": [ "explainer = lime.lime_tabular.LimeTabularExplainer(train, feature_names=boston.feature_names, class_names=['price'], categorical_features=categorical_features, verbose=True, mode='regression')" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Intercept 23.3472933614\n", "Prediction_local [ 22.26816652]\n", "Right: 22.0623\n" ] } ], "source": [ "i = 25\n", "exp = explainer.explain_instance(test[i], rf.predict, num_features=5)\n" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " \n", " \n", "
\n", " \n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "exp.show_in_notebook(show_table=True)" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[('7.43 < LSTAT <= 11.73', 1.6485568658614111),\n", " ('6.18 < RM <= 6.57', -1.5185815542882575),\n", " ('284.00 < TAX <= 341.00', -0.46847722088708765),\n", " ('0.27 < CRIM <= 4.28', -0.39482132673497322),\n", " ('5.81 < INDUS <= 9.90', -0.34580360269472482)]" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "exp.as_list()" ] } ], "metadata": { "kernelspec": { "display_name": "Python 2", "language": "python", "name": "python2" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.12" } }, "nbformat": 4, "nbformat_minor": 1 } ================================================ FILE: doc/notebooks/data/adult.csv ================================================ 39, State-gov, 77516, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 2174, 0, 40, United-States, <=50K 50, Self-emp-not-inc, 83311, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 13, United-States, <=50K 38, Private, 215646, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 234721, 11th, 7, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, United-States, <=50K 28, Private, 338409, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, Black, Female, 0, 0, 40, Cuba, <=50K 37, Private, 284582, Masters, 14, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 160187, 9th, 5, Married-spouse-absent, Other-service, Not-in-family, Black, Female, 0, 0, 16, Jamaica, <=50K 52, Self-emp-not-inc, 209642, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 31, Private, 45781, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 14084, 0, 50, United-States, >50K 42, Private, 159449, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 5178, 0, 40, United-States, >50K 37, Private, 280464, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 80, United-States, >50K 30, State-gov, 141297, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, India, >50K 23, Private, 122272, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 30, United-States, <=50K 32, Private, 205019, Assoc-acdm, 12, Never-married, Sales, Not-in-family, Black, Male, 0, 0, 50, United-States, <=50K 40, Private, 121772, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, ?, >50K 34, Private, 245487, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, Amer-Indian-Eskimo, Male, 0, 0, 45, Mexico, <=50K 25, Self-emp-not-inc, 176756, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 35, United-States, <=50K 32, Private, 186824, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 28887, 11th, 7, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 43, Self-emp-not-inc, 292175, Masters, 14, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 45, United-States, >50K 40, Private, 193524, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 54, Private, 302146, HS-grad, 9, Separated, Other-service, Unmarried, Black, Female, 0, 0, 20, United-States, <=50K 35, Federal-gov, 76845, 9th, 5, Married-civ-spouse, Farming-fishing, Husband, Black, Male, 0, 0, 40, United-States, <=50K 43, Private, 117037, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 2042, 40, United-States, <=50K 59, Private, 109015, HS-grad, 9, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 56, Local-gov, 216851, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 19, Private, 168294, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 54, ?, 180211, Some-college, 10, Married-civ-spouse, ?, Husband, Asian-Pac-Islander, Male, 0, 0, 60, South, >50K 39, Private, 367260, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 80, United-States, <=50K 49, Private, 193366, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Local-gov, 190709, Assoc-acdm, 12, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 52, United-States, <=50K 20, Private, 266015, Some-college, 10, Never-married, Sales, Own-child, Black, Male, 0, 0, 44, United-States, <=50K 45, Private, 386940, Bachelors, 13, Divorced, Exec-managerial, Own-child, White, Male, 0, 1408, 40, United-States, <=50K 30, Federal-gov, 59951, Some-college, 10, Married-civ-spouse, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 22, State-gov, 311512, Some-college, 10, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 15, United-States, <=50K 48, Private, 242406, 11th, 7, Never-married, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, Puerto-Rico, <=50K 21, Private, 197200, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 544091, HS-grad, 9, Married-AF-spouse, Adm-clerical, Wife, White, Female, 0, 0, 25, United-States, <=50K 31, Private, 84154, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 38, ?, >50K 48, Self-emp-not-inc, 265477, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 507875, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 43, United-States, <=50K 53, Self-emp-not-inc, 88506, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 172987, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 50, United-States, <=50K 49, Private, 94638, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 289980, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 57, Federal-gov, 337895, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 40, United-States, >50K 53, Private, 144361, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 38, United-States, <=50K 44, Private, 128354, Masters, 14, 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United-States, >50K 29, Private, 105598, Some-college, 10, Divorced, Tech-support, Not-in-family, White, Male, 0, 0, 58, United-States, <=50K 36, Private, 155537, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 183175, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 53, Private, 169846, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 49, Self-emp-inc, 191681, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 25, ?, 200681, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 101509, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 32, United-States, <=50K 31, Private, 309974, Bachelors, 13, Separated, Sales, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 29, Self-emp-not-inc, 162298, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 70, United-States, >50K 23, Private, 211678, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 79, Private, 124744, Some-college, 10, Married-civ-spouse, Prof-specialty, Other-relative, White, Male, 0, 0, 20, United-States, <=50K 27, Private, 213921, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, Mexico, <=50K 40, Private, 32214, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 67, ?, 212759, 10th, 6, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 2, United-States, <=50K 18, Private, 309634, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 22, United-States, <=50K 31, Local-gov, 125927, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 446839, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 52, Private, 276515, Bachelors, 13, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Cuba, <=50K 46, Private, 51618, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, <=50K 59, Private, 159937, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 48, United-States, <=50K 44, Private, 343591, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Female, 14344, 0, 40, United-States, >50K 53, Private, 346253, HS-grad, 9, Divorced, Sales, Own-child, White, Female, 0, 0, 35, United-States, <=50K 49, Local-gov, 268234, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Private, 202051, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 30, Private, 54334, 9th, 5, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 43, Federal-gov, 410867, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 57, Private, 249977, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 286730, Some-college, 10, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 212563, Some-college, 10, Divorced, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 25, United-States, <=50K 30, Private, 117747, HS-grad, 9, Married-civ-spouse, Sales, Wife, Asian-Pac-Islander, Female, 0, 1573, 35, ?, <=50K 34, Local-gov, 226296, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Local-gov, 115585, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 48, Self-emp-not-inc, 191277, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 60, United-States, >50K 37, Private, 202683, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 48, United-States, >50K 48, Private, 171095, Assoc-acdm, 12, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, England, <=50K 32, Federal-gov, 249409, HS-grad, 9, Never-married, Other-service, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 76, Private, 124191, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 44, Private, 198282, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 60, United-States, >50K 47, Self-emp-not-inc, 149116, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 20, Private, 188300, Some-college, 10, Never-married, Tech-support, Own-child, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 103432, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Self-emp-inc, 317660, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 7688, 0, 40, United-States, >50K 17, ?, 304873, 10th, 6, Never-married, ?, Own-child, White, Female, 34095, 0, 32, United-States, <=50K 30, Private, 194901, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 31, Local-gov, 189265, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 124692, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 432376, Bachelors, 13, Never-married, Sales, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 65324, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 56, Self-emp-not-inc, 335605, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 1887, 50, Canada, >50K 28, Private, 377869, Some-college, 10, Married-civ-spouse, Sales, Wife, White, Female, 4064, 0, 25, United-States, <=50K 36, Private, 102864, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 53, Private, 95647, 9th, 5, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 50, United-States, <=50K 56, Self-emp-inc, 303090, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 49, Local-gov, 197371, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, >50K 55, Private, 247552, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 56, United-States, <=50K 22, Private, 102632, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 41, United-States, <=50K 21, Private, 199915, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 118853, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 30, Private, 77143, Bachelors, 13, Never-married, Exec-managerial, Own-child, Black, Male, 0, 0, 40, Germany, <=50K 29, State-gov, 267989, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 19, Private, 301606, Some-college, 10, Never-married, Other-service, Own-child, Black, Male, 0, 0, 35, United-States, <=50K 47, Private, 287828, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 20, Private, 111697, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 1719, 28, United-States, <=50K 31, Private, 114937, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 35, ?, 129305, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 365739, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 69621, Assoc-acdm, 12, Never-married, Sales, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 24, Private, 43323, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 1762, 40, United-States, <=50K 38, Self-emp-not-inc, 120985, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 4386, 0, 35, United-States, <=50K 37, Private, 254202, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 46, Private, 146195, Assoc-acdm, 12, Divorced, Tech-support, Not-in-family, Black, Female, 0, 0, 36, United-States, <=50K 38, Federal-gov, 125933, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, Iran, >50K 43, Self-emp-not-inc, 56920, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 27, Private, 163127, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 35, United-States, <=50K 20, Private, 34310, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 20, United-States, <=50K 49, Private, 81973, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, >50K 61, Self-emp-inc, 66614, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 232782, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 316868, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, Mexico, <=50K 45, Private, 196584, Assoc-voc, 11, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 1564, 40, United-States, >50K 70, Private, 105376, Some-college, 10, Never-married, Tech-support, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 185814, HS-grad, 9, Never-married, Transport-moving, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 22, Private, 175374, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 24, United-States, <=50K 36, Private, 108293, HS-grad, 9, Widowed, Other-service, Unmarried, White, Female, 0, 0, 24, United-States, <=50K 64, Private, 181232, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 2179, 40, United-States, <=50K 43, ?, 174662, Some-college, 10, Divorced, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Local-gov, 186009, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 38, Mexico, <=50K 34, Private, 198183, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 163003, Bachelors, 13, Never-married, Exec-managerial, Other-relative, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 21, Private, 296158, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 35, United-States, <=50K 52, ?, 252903, HS-grad, 9, Divorced, ?, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 48, Private, 187715, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 46, United-States, <=50K 23, Private, 214542, Bachelors, 13, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 71, Self-emp-not-inc, 494223, Some-college, 10, Separated, Sales, Unmarried, Black, Male, 0, 1816, 2, United-States, <=50K 29, Private, 191535, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 42, Private, 228456, Bachelors, 13, Separated, Other-service, Other-relative, Black, Male, 0, 0, 50, United-States, <=50K 68, ?, 38317, 1st-4th, 2, Divorced, ?, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 25, Private, 252752, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 44, Self-emp-inc, 78374, Masters, 14, Divorced, Exec-managerial, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 28, Private, 88419, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, England, <=50K 45, Self-emp-not-inc, 201080, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 207157, Some-college, 10, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 39, Federal-gov, 235485, Assoc-acdm, 12, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 42, United-States, <=50K 46, State-gov, 102628, Masters, 14, Widowed, Protective-serv, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 25828, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 16, United-States, <=50K 66, Local-gov, 54826, Assoc-voc, 11, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 27, Private, 124953, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 1980, 40, United-States, <=50K 28, State-gov, 175325, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 96062, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 1977, 40, United-States, >50K 27, Private, 428030, Bachelors, 13, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 28, State-gov, 149624, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 253814, HS-grad, 9, Married-spouse-absent, Sales, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 21, Private, 312956, HS-grad, 9, Never-married, Craft-repair, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 34, Private, 483777, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 18, Private, 183930, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 12, United-States, <=50K 33, Private, 37274, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 65, United-States, <=50K 44, Local-gov, 181344, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 38, United-States, >50K 43, Private, 114580, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 633742, Some-college, 10, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 45, United-States, <=50K 40, Private, 286370, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, >50K 37, Federal-gov, 29054, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 42, United-States, >50K 34, Private, 304030, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, <=50K 41, Self-emp-not-inc, 143129, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 53, ?, 135105, Bachelors, 13, Divorced, ?, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 31, Private, 99928, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 50, United-States, <=50K 58, State-gov, 109567, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 1, United-States, >50K 38, Private, 155222, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 28, United-States, <=50K 24, Private, 159567, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Local-gov, 523910, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 47, Private, 120939, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 45, United-States, <=50K 41, Federal-gov, 130760, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 24, United-States, <=50K 23, Private, 197387, 5th-6th, 3, Married-civ-spouse, Transport-moving, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 36, Private, 99374, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 40, Federal-gov, 56795, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 14084, 0, 55, United-States, >50K 35, Private, 138992, Masters, 14, Married-civ-spouse, Prof-specialty, Other-relative, White, Male, 7298, 0, 40, United-States, >50K 24, Self-emp-not-inc, 32921, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 397317, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 1876, 40, United-States, <=50K 19, ?, 170653, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 0, 40, Italy, <=50K 51, Private, 259323, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 42, Local-gov, 254817, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 1340, 40, United-States, <=50K 37, State-gov, 48211, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 18, Private, 140164, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 128757, Bachelors, 13, Married-civ-spouse, Other-service, Husband, Black, Male, 7298, 0, 36, United-States, >50K 35, Private, 36270, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 58, Self-emp-inc, 210563, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 15024, 0, 35, United-States, >50K 17, Private, 65368, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 12, United-States, <=50K 44, Local-gov, 160943, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 37, Private, 208358, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 153790, Some-college, 10, Never-married, Sales, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 60, Private, 85815, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 54, Self-emp-inc, 125417, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Private, 635913, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, Black, Male, 0, 0, 60, United-States, >50K 50, Private, 313321, Assoc-acdm, 12, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 182609, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, Poland, <=50K 45, Private, 109434, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, <=50K 25, Private, 255004, 10th, 6, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 197860, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 64, ?, 187656, 1st-4th, 2, Divorced, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 90, Private, 51744, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Male, 0, 2206, 40, United-States, <=50K 54, Private, 176681, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 20, United-States, <=50K 53, Local-gov, 140359, Preschool, 1, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 18, Private, 243313, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 60, ?, 24215, 10th, 6, Divorced, ?, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 10, United-States, <=50K 66, Self-emp-not-inc, 167687, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 1409, 0, 50, United-States, <=50K 75, Private, 314209, Assoc-voc, 11, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 20, Columbia, <=50K 65, Private, 176796, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 538583, 11th, 7, Separated, Transport-moving, Not-in-family, Black, Male, 3674, 0, 40, United-States, <=50K 41, Private, 130408, HS-grad, 9, Divorced, Sales, Unmarried, Black, Female, 0, 0, 38, United-States, <=50K 25, Private, 159732, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 42, United-States, <=50K 33, Private, 110978, Some-college, 10, Divorced, Craft-repair, Other-relative, Other, Female, 0, 0, 40, United-States, <=50K 28, Private, 76714, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 55, United-States, >50K 59, State-gov, 268700, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, State-gov, 170525, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 41, Private, 180138, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, Iran, >50K 38, Local-gov, 115076, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 70, United-States, >50K 23, Private, 115458, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 347890, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Self-emp-not-inc, 196001, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 20, United-States, <=50K 24, State-gov, 273905, Assoc-acdm, 12, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 50, United-States, <=50K 20, ?, 119156, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 20, United-States, <=50K 38, Private, 179488, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 1741, 40, United-States, <=50K 56, Private, 203580, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 35, ?, <=50K 58, Private, 236596, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, >50K 32, Private, 183916, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 34, United-States, <=50K 40, Private, 207578, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 1977, 60, United-States, >50K 45, Private, 153141, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, ?, <=50K 41, Private, 112763, Prof-school, 15, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 42, Private, 390781, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 0, 40, United-States, <=50K 59, Local-gov, 171328, 10th, 6, Widowed, Other-service, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 19, Local-gov, 27382, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 58, Private, 259014, Some-college, 10, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 42, Self-emp-not-inc, 303044, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Cambodia, >50K 20, Private, 117789, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 172579, HS-grad, 9, Separated, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 45, Private, 187666, Assoc-voc, 11, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 50, Private, 204518, 7th-8th, 4, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 150042, Bachelors, 13, Divorced, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 98092, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 17, Private, 245918, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 12, United-States, <=50K 59, Private, 146013, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 4064, 0, 40, United-States, <=50K 26, Private, 378322, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Self-emp-inc, 257295, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 75, Thailand, >50K 19, ?, 218956, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 24, Canada, <=50K 64, Private, 21174, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Private, 185480, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 33, Private, 222205, HS-grad, 9, Married-civ-spouse, Craft-repair, Wife, White, Female, 0, 0, 40, United-States, >50K 61, Private, 69867, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 17, Private, 191260, 9th, 5, Never-married, Other-service, Own-child, White, Male, 1055, 0, 24, United-States, <=50K 50, Self-emp-not-inc, 30653, Masters, 14, Married-civ-spouse, Farming-fishing, Husband, White, Male, 2407, 0, 98, United-States, <=50K 27, Local-gov, 209109, Masters, 14, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 35, United-States, <=50K 30, Private, 70377, HS-grad, 9, Divorced, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 477983, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, United-States, <=50K 44, Private, 170924, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 40, United-States, >50K 35, Private, 190174, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 193787, Some-college, 10, Never-married, Tech-support, Own-child, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 279472, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 7298, 0, 48, United-States, >50K 22, Private, 34918, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 15, Germany, <=50K 42, Local-gov, 97688, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 5178, 0, 40, United-States, >50K 34, Private, 175413, Assoc-acdm, 12, Divorced, Sales, Unmarried, Black, Female, 0, 0, 45, United-States, <=50K 60, Private, 173960, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 42, United-States, <=50K 21, Private, 205759, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 57, Federal-gov, 425161, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 40, United-States, >50K 41, Private, 220531, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 50, Private, 176609, Some-college, 10, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 25, Private, 371987, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 50, Private, 193884, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Ecuador, <=50K 36, Private, 200352, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, <=50K 31, Private, 127595, HS-grad, 9, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, Local-gov, 220419, Bachelors, 13, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 56, United-States, <=50K 21, Private, 231931, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 45, United-States, <=50K 27, Private, 248402, Bachelors, 13, Never-married, Tech-support, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 65, Private, 111095, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 16, United-States, <=50K 37, Self-emp-inc, 57424, Bachelors, 13, Divorced, Sales, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 39, ?, 157443, Masters, 14, Married-civ-spouse, ?, Wife, Asian-Pac-Islander, Female, 3464, 0, 40, ?, <=50K 24, Private, 278130, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 169469, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 80, United-States, <=50K 48, Private, 146268, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 7688, 0, 40, United-States, >50K 21, Private, 153718, Some-college, 10, Never-married, Other-service, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 25, United-States, <=50K 31, Private, 217460, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, >50K 55, Private, 238638, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 4386, 0, 40, United-States, >50K 24, Private, 303296, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, Asian-Pac-Islander, Female, 0, 0, 40, Laos, <=50K 43, Private, 173321, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 193945, Assoc-acdm, 12, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 46, Private, 83082, Assoc-acdm, 12, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 33, United-States, <=50K 35, Private, 193815, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Self-emp-inc, 34987, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 54, United-States, >50K 26, Private, 59306, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 142897, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 7298, 0, 35, Taiwan, >50K 19, ?, 860348, Some-college, 10, Never-married, ?, Own-child, Black, Female, 0, 0, 25, United-States, <=50K 36, Self-emp-not-inc, 205607, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, Black, Female, 0, 0, 40, United-States, >50K 22, Private, 199698, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 15, United-States, <=50K 24, Private, 191954, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 77, Self-emp-not-inc, 138714, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 399087, 5th-6th, 3, Married-civ-spouse, Machine-op-inspct, Other-relative, White, Female, 0, 0, 40, Mexico, <=50K 29, Private, 423158, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 62, Private, 159841, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 24, United-States, <=50K 39, Self-emp-not-inc, 174308, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 50356, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1485, 50, United-States, <=50K 35, Private, 186110, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 29, Private, 200381, 11th, 7, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 76, Self-emp-not-inc, 174309, Masters, 14, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 10, United-States, <=50K 63, Self-emp-not-inc, 78383, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 45, United-States, <=50K 23, ?, 211601, Assoc-voc, 11, Never-married, ?, Own-child, Black, Female, 0, 0, 15, United-States, <=50K 43, Private, 187728, Some-college, 10, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 1887, 50, United-States, >50K 58, Self-emp-not-inc, 321171, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 66, Private, 127921, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 2050, 0, 55, United-States, <=50K 41, Private, 206565, Some-college, 10, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 45, United-States, <=50K 26, Private, 224563, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 178686, Assoc-voc, 11, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 55, Local-gov, 98545, 10th, 6, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 242606, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 270942, 5th-6th, 3, Never-married, Other-service, Other-relative, White, Male, 0, 0, 48, Mexico, <=50K 30, Private, 94235, HS-grad, 9, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 71195, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 19, Private, 104112, HS-grad, 9, Never-married, Sales, Unmarried, Black, Male, 0, 0, 30, Haiti, <=50K 45, Private, 261192, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 40, United-States, <=50K 26, Private, 94936, Assoc-acdm, 12, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 296478, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 40, United-States, >50K 36, State-gov, 119272, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 7298, 0, 40, United-States, >50K 33, Private, 85043, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 22, State-gov, 293364, Some-college, 10, Never-married, Protective-serv, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 43, Self-emp-not-inc, 241895, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 42, United-States, <=50K 67, ?, 36135, 11th, 7, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 8, United-States, <=50K 30, ?, 151989, Assoc-voc, 11, Divorced, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 56, Private, 101128, Assoc-acdm, 12, Married-spouse-absent, Other-service, Not-in-family, White, Male, 0, 0, 25, Iran, <=50K 31, Private, 156464, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 25, United-States, <=50K 33, Private, 117963, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 192262, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 111363, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Local-gov, 329752, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 30, United-States, <=50K 59, ?, 372020, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Federal-gov, 95432, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 65, Private, 161400, 11th, 7, Widowed, Other-service, Unmarried, Other, Male, 0, 0, 40, United-States, <=50K 40, Private, 96129, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Private, 111949, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 35, United-States, <=50K 26, Self-emp-not-inc, 117125, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Portugal, <=50K 36, Private, 348022, 10th, 6, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 24, United-States, <=50K 62, Private, 270092, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 43, Private, 180609, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 43, Private, 174575, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 1564, 45, United-States, >50K 22, Private, 410439, HS-grad, 9, Married-spouse-absent, Sales, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 28, Private, 92262, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, Self-emp-not-inc, 183081, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 22, Private, 362589, Assoc-acdm, 12, Never-married, Sales, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 57, Private, 212448, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, >50K 39, Private, 481060, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 26, Federal-gov, 185885, Some-college, 10, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 15, United-States, <=50K 17, Private, 89821, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 10, United-States, <=50K 40, State-gov, 184018, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 38, United-States, >50K 45, Private, 256649, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 44, Private, 160323, HS-grad, 9, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 20, Local-gov, 350845, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 10, United-States, <=50K 33, Private, 267404, HS-grad, 9, Married-civ-spouse, Craft-repair, Wife, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 35633, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 46, Self-emp-not-inc, 80914, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 38, Private, 172927, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 54, Private, 174319, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 214955, 5th-6th, 3, Divorced, Craft-repair, Not-in-family, White, Female, 0, 2339, 45, United-States, <=50K 25, Private, 344991, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 108699, Some-college, 10, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, Local-gov, 117312, Some-college, 10, Married-civ-spouse, Transport-moving, Wife, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 396099, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 29, Private, 134152, HS-grad, 9, Separated, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 162028, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 2415, 6, United-States, >50K 19, Private, 25429, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 16, United-States, <=50K 19, Private, 232392, HS-grad, 9, Never-married, Other-service, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 220098, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, >50K 27, Private, 301302, Bachelors, 13, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 46, Self-emp-not-inc, 277946, Assoc-acdm, 12, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, State-gov, 98101, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 45, ?, >50K 34, Private, 196164, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 44, Private, 115562, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 96975, Some-college, 10, Divorced, Handlers-cleaners, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 20, ?, 137300, HS-grad, 9, Never-married, ?, Other-relative, White, Female, 0, 0, 35, United-States, <=50K 25, Private, 86872, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 52, Self-emp-inc, 132178, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 20, Private, 416103, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 108574, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 50, State-gov, 288353, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 34, Private, 227689, Assoc-voc, 11, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 64, United-States, <=50K 28, Private, 166481, 7th-8th, 4, Married-civ-spouse, Handlers-cleaners, Husband, Other, Male, 0, 2179, 40, Puerto-Rico, <=50K 41, Private, 445382, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 65, United-States, >50K 28, Private, 110145, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Self-emp-not-inc, 317253, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 25, United-States, <=50K 28, ?, 123147, Some-college, 10, Married-civ-spouse, ?, Wife, White, Female, 0, 1887, 40, United-States, >50K 32, Private, 364657, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 41, Local-gov, 42346, Some-college, 10, Divorced, Other-service, Not-in-family, Black, Female, 0, 0, 24, United-States, <=50K 24, Private, 241951, HS-grad, 9, Never-married, Handlers-cleaners, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 33, Private, 118500, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 188386, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 60, United-States, >50K 31, State-gov, 1033222, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 92440, 12th, 8, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 52, Private, 190762, 1st-4th, 2, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 30, Private, 426017, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 19, United-States, <=50K 34, Local-gov, 243867, 11th, 7, Separated, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 34, State-gov, 240283, HS-grad, 9, Divorced, Transport-moving, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 61777, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 30, United-States, <=50K 17, Private, 175024, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 2176, 0, 18, United-States, <=50K 32, State-gov, 92003, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 29, Private, 188401, HS-grad, 9, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 228528, 10th, 6, Never-married, Craft-repair, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 25, Private, 133373, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 36, Federal-gov, 255191, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 1408, 40, United-States, <=50K 23, Private, 204653, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 72, Dominican-Republic, <=50K 63, Self-emp-inc, 222289, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 47, Local-gov, 287480, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 80, ?, 107762, HS-grad, 9, Widowed, ?, Not-in-family, White, Male, 0, 0, 24, United-States, <=50K 17, ?, 202521, 11th, 7, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 40, Self-emp-not-inc, 204116, Bachelors, 13, Married-spouse-absent, Prof-specialty, Not-in-family, White, Female, 2174, 0, 40, United-States, <=50K 30, Private, 29662, Assoc-acdm, 12, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 25, United-States, >50K 27, Private, 116358, Some-college, 10, Never-married, Craft-repair, Own-child, Asian-Pac-Islander, Male, 0, 1980, 40, Philippines, <=50K 33, Private, 208405, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 34, Local-gov, 284843, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, Black, Male, 594, 0, 60, United-States, <=50K 34, Local-gov, 117018, Some-college, 10, Never-married, Protective-serv, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 81281, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Local-gov, 340148, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 363425, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 45857, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 28, United-States, <=50K 24, Federal-gov, 191073, HS-grad, 9, Never-married, Armed-Forces, Own-child, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 116632, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 405855, 9th, 5, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 20, Private, 298227, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 44, Private, 290521, HS-grad, 9, Widowed, Exec-managerial, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 51, Private, 56915, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 20, Private, 146538, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 17, ?, 258872, 11th, 7, Never-married, ?, Own-child, White, Female, 0, 0, 5, United-States, <=50K 19, Private, 206399, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 45, Self-emp-inc, 197332, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, >50K 60, Private, 245062, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Private, 197583, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, ?, >50K 44, Self-emp-not-inc, 234885, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, >50K 40, Private, 72887, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, >50K 30, Private, 180374, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 351299, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 50, United-States, <=50K 23, Private, 54012, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 32, ?, 115745, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 116632, Assoc-acdm, 12, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 54, Local-gov, 288825, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 32, Private, 132601, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 50, Private, 193374, 1st-4th, 2, Married-spouse-absent, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 170070, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 37, Private, 126708, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 60, United-States, <=50K 52, Private, 35598, HS-grad, 9, Divorced, Transport-moving, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 33983, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 192776, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 45, United-States, >50K 30, Private, 118551, Bachelors, 13, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 16, United-States, >50K 60, Private, 201965, Some-college, 10, Never-married, Prof-specialty, Unmarried, White, Male, 0, 0, 40, United-States, >50K 22, ?, 139883, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 285020, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 303990, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 67, Private, 49401, Assoc-voc, 11, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 24, United-States, <=50K 46, Private, 279196, Bachelors, 13, Never-married, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 17, Private, 211870, 9th, 5, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 6, United-States, <=50K 22, Private, 281432, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 30, United-States, <=50K 27, Private, 161155, 10th, 6, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 197904, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 33, Private, 111746, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, Portugal, <=50K 43, Self-emp-not-inc, 170721, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 20, United-States, <=50K 28, State-gov, 70100, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 41, Private, 193626, HS-grad, 9, Married-spouse-absent, Craft-repair, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 52, ?, 271749, 12th, 8, Never-married, ?, Other-relative, Black, Male, 594, 0, 40, United-States, <=50K 25, Private, 189775, Some-college, 10, Married-spouse-absent, Adm-clerical, Own-child, Black, Female, 0, 0, 20, United-States, <=50K 63, ?, 401531, 1st-4th, 2, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 35, United-States, <=50K 59, Local-gov, 286967, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 45, Local-gov, 164427, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 91039, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 60, United-States, >50K 40, Private, 347934, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 46, Federal-gov, 371373, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 32220, Assoc-acdm, 12, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 34, Private, 187251, HS-grad, 9, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 33, Private, 178107, Bachelors, 13, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 20, United-States, <=50K 41, Private, 343121, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 36, United-States, <=50K 20, Private, 262749, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 403107, 5th-6th, 3, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, El-Salvador, <=50K 26, Private, 64293, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 72, ?, 303588, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 20, United-States, <=50K 23, Local-gov, 324960, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, Poland, <=50K 62, Local-gov, 114060, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 48925, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, Private, 180980, Some-college, 10, Divorced, Other-service, Unmarried, White, Female, 0, 0, 42, France, <=50K 25, Private, 181054, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 388093, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 19, Private, 249609, Some-college, 10, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 8, United-States, <=50K 43, Private, 112131, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Local-gov, 543162, HS-grad, 9, Separated, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 39, Private, 91996, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 141944, Assoc-voc, 11, Married-spouse-absent, Handlers-cleaners, Unmarried, White, Male, 0, 1380, 42, United-States, <=50K 53, ?, 251804, 5th-6th, 3, Widowed, ?, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 32, Private, 37070, Assoc-voc, 11, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 34, Private, 337587, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 28, Private, 189346, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 57, ?, 222216, Assoc-voc, 11, Widowed, ?, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 25, Private, 267044, Some-college, 10, Never-married, Adm-clerical, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 20, United-States, <=50K 20, ?, 214635, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 24, United-States, <=50K 21, ?, 204226, Some-college, 10, Never-married, ?, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 34, Private, 108116, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 38, Self-emp-inc, 99146, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 80, United-States, >50K 50, Private, 196232, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 50, United-States, >50K 24, Local-gov, 248344, Some-college, 10, Divorced, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 50, United-States, <=50K 37, Local-gov, 186035, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 45, United-States, >50K 44, Private, 177905, Some-college, 10, Divorced, Machine-op-inspct, Unmarried, White, Male, 0, 0, 58, United-States, >50K 28, Private, 85812, Some-college, 10, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 221172, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 74, Private, 99183, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 9, United-States, <=50K 38, Self-emp-not-inc, 190387, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 44, Self-emp-not-inc, 202692, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 109339, 11th, 7, Divorced, Machine-op-inspct, Unmarried, Other, Female, 0, 0, 46, Puerto-Rico, <=50K 26, Private, 108658, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 197202, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 40, United-States, <=50K 41, Private, 101739, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 50, United-States, >50K 67, Private, 231559, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 20051, 0, 48, United-States, >50K 39, Local-gov, 207853, 12th, 8, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 50, United-States, <=50K 57, Private, 190942, 1st-4th, 2, Widowed, Priv-house-serv, Not-in-family, Black, Female, 0, 0, 30, United-States, <=50K 29, Private, 102345, Assoc-voc, 11, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Self-emp-inc, 41493, Bachelors, 13, Never-married, Farming-fishing, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 34, ?, 190027, HS-grad, 9, Never-married, ?, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 44, Private, 210525, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 133937, Doctorate, 16, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 237903, Some-college, 10, Never-married, Handlers-cleaners, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 163862, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 201872, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 32, Private, 84179, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 58, Private, 51662, 10th, 6, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 8, United-States, <=50K 35, Local-gov, 233327, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 259510, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 36, United-States, <=50K 28, Private, 184831, Some-college, 10, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 46, Self-emp-not-inc, 245724, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 36, Self-emp-not-inc, 27053, HS-grad, 9, Separated, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 72, Private, 205343, 11th, 7, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 229328, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, Black, Female, 0, 0, 40, United-States, <=50K 33, Federal-gov, 319560, Assoc-voc, 11, Divorced, Craft-repair, Unmarried, Black, Female, 0, 0, 40, United-States, >50K 69, Private, 136218, 11th, 7, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 54576, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 323069, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 20, ?, <=50K 34, Private, 148291, HS-grad, 9, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 32, United-States, <=50K 30, Private, 152453, 11th, 7, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Mexico, <=50K 28, Private, 114053, Bachelors, 13, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 54, Private, 212960, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 35, United-States, >50K 47, Private, 264052, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 24, Private, 82804, HS-grad, 9, Never-married, Handlers-cleaners, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 52, Self-emp-not-inc, 334273, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 20, Private, 27337, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, Amer-Indian-Eskimo, Male, 0, 0, 48, United-States, <=50K 43, Self-emp-inc, 188436, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 5013, 0, 45, United-States, <=50K 45, Private, 433665, 7th-8th, 4, Separated, Other-service, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 29, Self-emp-not-inc, 110663, HS-grad, 9, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 47, Private, 87490, Masters, 14, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 42, United-States, <=50K 24, Private, 354351, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 95469, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 242718, 11th, 7, Never-married, Sales, Own-child, White, Male, 0, 0, 12, United-States, <=50K 37, Private, 22463, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1977, 40, United-States, >50K 27, Private, 158156, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 70, United-States, <=50K 29, Private, 350162, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Male, 0, 0, 40, United-States, >50K 18, ?, 165532, 12th, 8, Never-married, ?, Own-child, White, Male, 0, 0, 25, United-States, <=50K 36, Self-emp-not-inc, 28738, Assoc-acdm, 12, Divorced, Sales, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 58, Local-gov, 283635, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, Self-emp-not-inc, 86646, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 65, ?, 195733, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 30, United-States, >50K 57, Private, 69884, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 59, Private, 199713, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 181659, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Self-emp-not-inc, 340939, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 197747, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 24, United-States, <=50K 29, Private, 34292, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 18, Private, 156764, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 25826, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1887, 47, United-States, >50K 57, Self-emp-inc, 103948, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 80, United-States, <=50K 42, ?, 137390, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, ?, 105138, HS-grad, 9, Married-civ-spouse, ?, Wife, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 60, Private, 39352, 7th-8th, 4, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 48, United-States, >50K 31, Private, 168387, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 40, Canada, >50K 23, Private, 117789, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 267147, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 23, ?, 99399, Some-college, 10, Never-married, ?, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 25, United-States, <=50K 42, Self-emp-not-inc, 214242, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 50, United-States, >50K 25, Private, 200408, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Male, 2174, 0, 40, United-States, <=50K 49, Private, 136455, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 32, Private, 239824, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 217039, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 28, United-States, <=50K 60, Private, 51290, 7th-8th, 4, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Local-gov, 175674, 9th, 5, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Self-emp-not-inc, 194404, Assoc-acdm, 12, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 45612, HS-grad, 9, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 37, United-States, <=50K 51, Private, 410114, Masters, 14, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Private, 182521, HS-grad, 9, Never-married, Craft-repair, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 36, Local-gov, 339772, HS-grad, 9, Separated, Exec-managerial, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 17, Private, 169658, 10th, 6, Never-married, Other-service, Own-child, White, Female, 0, 0, 21, United-States, <=50K 52, Private, 200853, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 6849, 0, 60, United-States, <=50K 24, Private, 247564, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 249909, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 50, United-States, <=50K 26, Local-gov, 208122, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 1055, 0, 40, United-States, <=50K 27, Private, 109881, Bachelors, 13, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 39, Private, 207824, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 60, United-States, <=50K 30, Private, 369027, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 45, United-States, <=50K 50, Self-emp-not-inc, 114117, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 32, United-States, <=50K 52, Self-emp-inc, 51048, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, <=50K 46, Private, 102388, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 45, United-States, >50K 23, Private, 190483, Bachelors, 13, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 45, Private, 462440, 11th, 7, Widowed, Other-service, Not-in-family, Black, Female, 0, 0, 20, United-States, <=50K 65, Private, 109351, 9th, 5, Widowed, Priv-house-serv, Unmarried, Black, Female, 0, 0, 24, United-States, <=50K 29, Private, 34383, Assoc-voc, 11, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 55, United-States, <=50K 47, Private, 241832, 9th, 5, Married-spouse-absent, Handlers-cleaners, Unmarried, White, Male, 0, 0, 40, El-Salvador, <=50K 30, Private, 124187, HS-grad, 9, Never-married, Farming-fishing, Own-child, Black, Male, 0, 0, 60, United-States, <=50K 34, Private, 153614, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 38, Self-emp-not-inc, 267556, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 64, United-States, <=50K 33, Private, 205469, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 49, Private, 268090, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 26, United-States, >50K 47, Self-emp-not-inc, 165039, Some-college, 10, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 49, Local-gov, 120451, 10th, 6, Separated, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 43, Private, 154374, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 15024, 0, 60, United-States, >50K 30, Private, 103649, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 0, 40, United-States, >50K 58, Self-emp-not-inc, 35723, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 19, Private, 262601, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 14, United-States, <=50K 21, Private, 226181, Bachelors, 13, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 175697, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 60, United-States, >50K 47, Self-emp-inc, 248145, 5th-6th, 3, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, Cuba, <=50K 52, Self-emp-not-inc, 289436, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 26, Private, 75654, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 60, Private, 199378, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 160968, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 188563, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 5178, 0, 50, United-States, >50K 31, Private, 55849, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 50, Self-emp-inc, 195322, Doctorate, 16, Separated, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 31, Local-gov, 402089, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 71, Private, 78277, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 15, United-States, <=50K 58, ?, 158611, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 50, United-States, <=50K 30, State-gov, 169496, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Private, 130959, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 24, Private, 556660, HS-grad, 9, Never-married, Exec-managerial, Other-relative, White, Male, 4101, 0, 50, United-States, <=50K 35, Private, 292472, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Taiwan, >50K 38, State-gov, 143774, Some-college, 10, Separated, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 27, Private, 288341, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 32, United-States, <=50K 29, State-gov, 71592, Some-college, 10, Never-married, Adm-clerical, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 70, ?, 167358, 9th, 5, Widowed, ?, Unmarried, White, Female, 1111, 0, 15, United-States, <=50K 34, Private, 106742, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 44, Private, 219288, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 43, Private, 174524, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 44, Self-emp-not-inc, 335183, 12th, 8, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, United-States, >50K 35, Private, 261293, Masters, 14, Never-married, Sales, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 27, Private, 111900, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 43, Local-gov, 194360, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 20, Private, 81145, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 42, Private, 341204, Assoc-acdm, 12, Divorced, Prof-specialty, Unmarried, White, Female, 8614, 0, 40, United-States, >50K 27, State-gov, 249362, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 3411, 0, 40, United-States, <=50K 42, Private, 247019, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, >50K 20, ?, 114746, 11th, 7, Married-spouse-absent, ?, Own-child, Asian-Pac-Islander, Female, 0, 1762, 40, South, <=50K 24, Private, 172146, 9th, 5, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 1721, 40, United-States, <=50K 48, Federal-gov, 110457, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 17, ?, 80077, 11th, 7, Never-married, ?, Own-child, White, Female, 0, 0, 20, United-States, <=50K 17, Self-emp-not-inc, 368700, 11th, 7, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 10, United-States, <=50K 33, Private, 182556, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 50, Self-emp-inc, 219420, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 22, Private, 240817, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 2597, 0, 40, United-States, <=50K 17, Private, 102726, 12th, 8, Never-married, Other-service, Own-child, White, Male, 0, 0, 16, United-States, <=50K 32, Private, 226267, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, Mexico, <=50K 31, Private, 125457, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 58, Self-emp-not-inc, 204021, HS-grad, 9, Widowed, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 29, Local-gov, 92262, HS-grad, 9, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 48, United-States, <=50K 37, Private, 161141, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Portugal, >50K 34, Self-emp-not-inc, 190290, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Local-gov, 430828, Some-college, 10, Separated, Exec-managerial, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 18, State-gov, 59342, 11th, 7, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 5, United-States, <=50K 34, Private, 136721, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 66, ?, 149422, 7th-8th, 4, Never-married, ?, Not-in-family, White, Male, 0, 0, 4, United-States, <=50K 45, Local-gov, 86644, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 55, United-States, <=50K 41, Private, 195124, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 35, Dominican-Republic, <=50K 26, Private, 167350, HS-grad, 9, Never-married, Other-service, Other-relative, White, Male, 0, 0, 30, United-States, <=50K 54, Local-gov, 113000, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 140027, Some-college, 10, Never-married, Machine-op-inspct, Own-child, Black, Female, 0, 0, 45, United-States, <=50K 42, Private, 262425, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 20, Private, 316702, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 20, United-States, <=50K 23, State-gov, 335453, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 25, ?, 202480, Assoc-acdm, 12, Never-married, ?, Other-relative, White, Male, 0, 0, 45, United-States, <=50K 35, Private, 203628, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 31, Private, 118710, Masters, 14, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 1902, 40, United-States, >50K 30, Private, 189620, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, Poland, <=50K 19, Private, 475028, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 36, Local-gov, 110866, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 31, Private, 243605, Bachelors, 13, Widowed, Sales, Unmarried, White, Female, 0, 1380, 40, Cuba, <=50K 21, Private, 163870, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 30, United-States, <=50K 31, Self-emp-not-inc, 80145, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 295566, Doctorate, 16, Divorced, Prof-specialty, Unmarried, White, Female, 25236, 0, 65, United-States, >50K 44, Private, 63042, Bachelors, 13, Divorced, Exec-managerial, Own-child, White, Female, 0, 0, 50, United-States, >50K 40, Private, 229148, 12th, 8, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 40, Jamaica, <=50K 45, Private, 242552, Some-college, 10, Never-married, Sales, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 60, Private, 177665, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 18, Private, 208103, 11th, 7, Never-married, Other-service, Other-relative, White, Male, 0, 0, 25, United-States, <=50K 28, Private, 296450, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 70282, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 36, Private, 271767, Bachelors, 13, Separated, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, ?, <=50K 40, Private, 144995, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 4386, 0, 40, United-States, <=50K 36, Local-gov, 382635, Bachelors, 13, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 35, Honduras, <=50K 31, Private, 295697, HS-grad, 9, Separated, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 33, Private, 194141, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, State-gov, 378418, HS-grad, 9, Never-married, Tech-support, Own-child, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 214399, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 15, United-States, <=50K 34, Private, 217460, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 33, Private, 182556, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 125831, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 2051, 60, United-States, <=50K 29, Private, 271328, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 4650, 0, 40, United-States, <=50K 50, Local-gov, 50459, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 42, United-States, >50K 42, Private, 162140, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 45, United-States, >50K 43, Private, 177937, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, ?, >50K 44, Private, 111502, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 299047, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 31, Private, 223212, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Mexico, <=50K 65, Self-emp-not-inc, 118474, 11th, 7, Married-civ-spouse, Exec-managerial, Husband, White, Male, 9386, 0, 59, ?, >50K 23, Private, 352139, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 24, United-States, <=50K 55, Private, 173093, Some-college, 10, Divorced, Adm-clerical, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 26, Private, 181655, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 2377, 45, United-States, <=50K 25, Private, 332702, Assoc-voc, 11, Never-married, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 45, ?, 51164, Some-college, 10, Married-civ-spouse, ?, Wife, Black, Female, 0, 0, 40, United-States, <=50K 35, Private, 234901, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 2407, 0, 40, United-States, <=50K 36, Private, 131414, Some-college, 10, Never-married, Sales, Not-in-family, Black, Female, 0, 0, 36, United-States, <=50K 43, State-gov, 260960, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 56, Private, 156052, HS-grad, 9, Widowed, Other-service, Unmarried, Black, Female, 594, 0, 20, United-States, <=50K 42, Private, 279914, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 19, Private, 192453, Some-college, 10, Never-married, Other-service, Other-relative, White, Female, 0, 0, 25, United-States, <=50K 55, Self-emp-not-inc, 200939, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 72, United-States, <=50K 42, Private, 151408, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 14084, 0, 50, United-States, >50K 26, Private, 112847, Assoc-voc, 11, Never-married, Tech-support, Own-child, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 316929, 12th, 8, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, United-States, <=50K 42, Local-gov, 126319, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 55, Private, 197422, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 7688, 0, 40, United-States, >50K 32, Private, 267736, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 29, Private, 267034, 11th, 7, Never-married, Craft-repair, Own-child, Black, Male, 0, 0, 40, Haiti, <=50K 46, State-gov, 193047, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 37, United-States, <=50K 29, State-gov, 356089, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 40, United-States, >50K 22, Private, 223515, Bachelors, 13, Never-married, Prof-specialty, Unmarried, White, Male, 0, 0, 20, United-States, <=50K 58, Self-emp-not-inc, 87510, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 145111, HS-grad, 9, Never-married, Transport-moving, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 39, Private, 48093, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 31757, Assoc-voc, 11, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 38, United-States, <=50K 54, Private, 285854, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Local-gov, 120064, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 46, Federal-gov, 167381, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 37, Private, 103408, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 36, Private, 101460, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 18, United-States, <=50K 59, Local-gov, 420537, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 38, United-States, >50K 34, Local-gov, 119411, HS-grad, 9, Divorced, Protective-serv, Unmarried, White, Male, 0, 0, 40, Portugal, <=50K 53, Self-emp-inc, 128272, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 70, United-States, >50K 51, Private, 386773, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 55, United-States, >50K 32, Private, 283268, 10th, 6, Separated, Other-service, Unmarried, White, Female, 0, 0, 42, United-States, <=50K 31, State-gov, 301526, Some-college, 10, Married-spouse-absent, Other-service, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 151790, Some-college, 10, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 30, Germany, <=50K 47, Self-emp-not-inc, 106252, Bachelors, 13, Divorced, Sales, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 32, Private, 188557, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 171114, Some-college, 10, Never-married, Farming-fishing, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 37, Private, 327323, 5th-6th, 3, Separated, Farming-fishing, Not-in-family, White, Male, 0, 0, 32, Guatemala, <=50K 31, Private, 244147, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 55, United-States, <=50K 37, Private, 280282, Assoc-voc, 11, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 24, United-States, >50K 55, Private, 116442, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 23, Local-gov, 282579, Assoc-voc, 11, Divorced, Tech-support, Not-in-family, White, Male, 0, 0, 56, United-States, <=50K 36, Private, 51838, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 73585, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, ?, <=50K 43, Private, 226902, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 54, Private, 279129, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 43, State-gov, 146908, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, ?, <=50K 28, Private, 196690, Assoc-voc, 11, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 1669, 42, United-States, <=50K 40, Private, 130760, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 41, Self-emp-not-inc, 49572, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 40, Private, 237601, Bachelors, 13, Never-married, Sales, Not-in-family, Other, Female, 0, 0, 55, United-States, >50K 42, Private, 169628, Some-college, 10, Divorced, Adm-clerical, Not-in-family, Black, Female, 0, 0, 38, United-States, <=50K 61, Self-emp-not-inc, 36671, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 2352, 50, United-States, <=50K 18, Private, 231193, 12th, 8, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 30, United-States, <=50K 59, ?, 192130, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 16, United-States, <=50K 21, ?, 149704, HS-grad, 9, Never-married, ?, Not-in-family, White, Female, 1055, 0, 40, United-States, <=50K 48, Private, 102102, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 50, United-States, >50K 41, Self-emp-inc, 32185, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, ?, 196061, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 33, United-States, <=50K 23, Private, 211046, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 2463, 0, 40, United-States, <=50K 60, Private, 31577, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, >50K 22, Private, 162343, Some-college, 10, Never-married, Other-service, Other-relative, Black, Male, 0, 0, 20, United-States, <=50K 61, Private, 128831, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 316688, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 46, Private, 90758, Masters, 14, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 35, United-States, >50K 43, Private, 274363, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 40, England, >50K 43, Private, 154538, Assoc-acdm, 12, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 106085, HS-grad, 9, Never-married, Other-service, Own-child, Black, Male, 0, 1721, 30, United-States, <=50K 68, Self-emp-not-inc, 315859, 11th, 7, Never-married, Farming-fishing, Unmarried, White, Male, 0, 0, 20, United-States, <=50K 31, Private, 51471, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 17, Private, 193830, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 32, Private, 231043, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 5178, 0, 48, United-States, >50K 50, ?, 23780, Masters, 14, Married-spouse-absent, ?, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 169879, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 3103, 0, 47, United-States, >50K 64, Private, 270333, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Private, 138768, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 30, United-States, <=50K 30, Private, 191571, HS-grad, 9, Separated, Other-service, Own-child, White, Female, 0, 0, 36, United-States, <=50K 22, ?, 219941, Some-college, 10, Never-married, ?, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 43, Private, 94113, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 22, Private, 137510, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 32607, 10th, 6, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 20, United-States, <=50K 47, Self-emp-not-inc, 93208, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 75, Italy, <=50K 41, Private, 254440, Assoc-voc, 11, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 56, Private, 186556, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 64, Private, 169871, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 47, Private, 191277, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 48, Private, 167159, Assoc-voc, 11, Never-married, Adm-clerical, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 171871, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 46, United-States, <=50K 29, Private, 154411, Assoc-voc, 11, Never-married, Tech-support, Own-child, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 129227, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 110331, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1672, 60, United-States, <=50K 57, Private, 34269, HS-grad, 9, Widowed, Transport-moving, Unmarried, White, Male, 0, 653, 42, United-States, >50K 62, Private, 174355, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 680390, HS-grad, 9, Separated, Machine-op-inspct, Unmarried, White, Female, 0, 0, 24, United-States, <=50K 43, Private, 233130, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 24, Self-emp-inc, 165474, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 42, ?, 257780, 11th, 7, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 15, United-States, <=50K 53, Private, 194259, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 4386, 0, 40, United-States, >50K 26, Private, 280093, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 73, Self-emp-not-inc, 177387, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 72, ?, 28929, 11th, 7, Widowed, ?, Not-in-family, White, Female, 0, 0, 24, United-States, <=50K 55, Private, 105304, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 499233, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 180572, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 24, Private, 321435, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 63, Private, 86108, HS-grad, 9, Widowed, Farming-fishing, Not-in-family, White, Male, 0, 0, 6, United-States, <=50K 17, Private, 198124, 11th, 7, Never-married, Sales, Own-child, White, Male, 0, 0, 20, United-States, <=50K 35, Private, 135162, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 51, Private, 146813, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 62, Local-gov, 291175, Bachelors, 13, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 55, Private, 387569, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 4386, 0, 40, United-States, >50K 43, Private, 102895, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 40, Local-gov, 33274, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 37, Private, 86551, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 39, Private, 138192, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 118966, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 18, United-States, <=50K 61, Private, 99784, Masters, 14, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 26, Private, 90980, Assoc-voc, 11, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 46, Self-emp-not-inc, 177407, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 26, Private, 96467, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 48, State-gov, 327886, Doctorate, 16, Divorced, Prof-specialty, Own-child, White, Male, 0, 0, 50, United-States, >50K 34, Private, 111567, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 34, Local-gov, 166545, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 59, Private, 142182, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, >50K 34, Private, 188798, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 38563, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 56, United-States, >50K 18, Private, 216284, 11th, 7, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 43, Private, 191547, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, Mexico, <=50K 48, Private, 285335, 11th, 7, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 28, Self-emp-inc, 142712, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 70, United-States, <=50K 33, Private, 80945, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 309055, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 21, Private, 62339, 10th, 6, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 368700, 11th, 7, Never-married, Sales, Own-child, White, Male, 0, 0, 28, United-States, <=50K 39, Private, 176186, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, >50K 29, Self-emp-not-inc, 266855, Bachelors, 13, Separated, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 48087, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 24, Private, 121313, Some-college, 10, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 50, United-States, <=50K 71, Self-emp-not-inc, 143437, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 10605, 0, 40, United-States, >50K 51, Self-emp-not-inc, 160724, Bachelors, 13, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 2415, 40, China, >50K 55, Private, 282753, 5th-6th, 3, Divorced, Other-service, Unmarried, Black, Male, 0, 0, 25, United-States, <=50K 41, Private, 194636, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 23, Private, 153044, HS-grad, 9, Never-married, Handlers-cleaners, Unmarried, Black, Female, 0, 0, 7, United-States, <=50K 38, Private, 411797, Assoc-voc, 11, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 117683, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 19, Private, 376540, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 49, Private, 72393, 9th, 5, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 270335, Bachelors, 13, Married-civ-spouse, Adm-clerical, Other-relative, White, Male, 0, 0, 40, Philippines, >50K 27, Private, 96226, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 70, United-States, <=50K 38, Private, 95336, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 33, Private, 258498, Some-college, 10, Married-civ-spouse, Craft-repair, Wife, White, Female, 0, 0, 60, United-States, <=50K 63, ?, 149698, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 15, United-States, <=50K 23, Private, 205865, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 28, United-States, <=50K 33, Self-emp-inc, 155781, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, ?, <=50K 54, Self-emp-not-inc, 406468, HS-grad, 9, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 40, United-States, <=50K 29, Private, 177119, Assoc-voc, 11, Divorced, Tech-support, Not-in-family, White, Female, 2174, 0, 45, United-States, <=50K 48, ?, 144397, Some-college, 10, Divorced, ?, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 35, Self-emp-not-inc, 372525, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 164170, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Wife, Asian-Pac-Islander, Female, 0, 0, 40, India, <=50K 37, Private, 183800, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 50, United-States, >50K 42, Self-emp-not-inc, 177307, Prof-school, 15, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 65, United-States, >50K 40, Private, 170108, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 341995, Some-college, 10, Divorced, Sales, Own-child, White, Male, 0, 0, 55, United-States, <=50K 22, Private, 226508, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 50, United-States, <=50K 30, Private, 87418, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 28, Private, 109165, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 63, Local-gov, 28856, 7th-8th, 4, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 55, United-States, <=50K 51, Self-emp-not-inc, 175897, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 20, United-States, <=50K 22, Private, 99697, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 40, United-States, <=50K 27, ?, 90270, Assoc-acdm, 12, Married-civ-spouse, ?, Own-child, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 35, Private, 152375, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 46, Private, 171550, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 37, Private, 211154, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 52, United-States, <=50K 24, Private, 202570, Bachelors, 13, Never-married, Prof-specialty, Own-child, Black, Male, 0, 0, 15, United-States, <=50K 37, Self-emp-not-inc, 168496, HS-grad, 9, Divorced, Handlers-cleaners, Own-child, White, Male, 0, 0, 10, United-States, <=50K 53, Private, 68898, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 93235, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 38, Private, 278924, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 44, United-States, <=50K 53, Self-emp-not-inc, 311020, 10th, 6, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 34, Private, 175878, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 543028, HS-grad, 9, Never-married, Sales, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 39, Private, 202027, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 45, United-States, >50K 43, Private, 158926, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, Asian-Pac-Islander, Female, 0, 0, 50, South, <=50K 67, Self-emp-inc, 76860, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, >50K 81, Self-emp-not-inc, 136063, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 30, United-States, <=50K 21, Private, 186648, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 23, Private, 257509, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 25, Private, 98155, Some-college, 10, Never-married, Transport-moving, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 274198, 5th-6th, 3, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 38, Mexico, <=50K 38, Private, 97083, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 0, 40, United-States, <=50K 64, ?, 29825, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 5, United-States, <=50K 32, Private, 262153, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 214738, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 138022, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 22, Private, 91842, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 42, United-States, <=50K 33, Private, 373662, 1st-4th, 2, Married-spouse-absent, Priv-house-serv, Not-in-family, White, Female, 0, 0, 40, Guatemala, <=50K 42, Private, 162003, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 19, ?, 52114, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 10, United-States, <=50K 51, Local-gov, 241843, Preschool, 1, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 375871, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, Mexico, <=50K 37, Private, 186934, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 3103, 0, 44, United-States, >50K 37, Private, 176900, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 99, United-States, >50K 47, Private, 21906, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 41, Private, 132222, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 2415, 40, United-States, >50K 33, Private, 143653, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 30, United-States, <=50K 31, Private, 111567, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 31, Private, 78602, Assoc-acdm, 12, Divorced, Other-service, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 35, Private, 465507, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 38, Self-emp-inc, 196373, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 18, Private, 293227, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 20, Private, 241752, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Local-gov, 166398, Some-college, 10, Divorced, Exec-managerial, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 40, Private, 184682, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 36, Self-emp-inc, 108293, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 1977, 45, United-States, >50K 43, Private, 250802, Some-college, 10, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 35, United-States, <=50K 44, Self-emp-not-inc, 325159, Some-college, 10, Divorced, Farming-fishing, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 44, State-gov, 174675, HS-grad, 9, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 43, Private, 227065, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 43, United-States, >50K 51, Private, 269080, 7th-8th, 4, Widowed, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 18, Private, 177722, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 51, Private, 133461, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 239683, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 30, ?, <=50K 44, Self-emp-inc, 398473, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 70, United-States, >50K 33, Local-gov, 298785, 10th, 6, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, Self-emp-not-inc, 123424, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Private, 176286, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Private, 150062, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, <=50K 32, Private, 169240, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 32, Private, 288273, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 70, Mexico, <=50K 36, Private, 526968, 10th, 6, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 57066, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 323573, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 35, Self-emp-inc, 368825, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 55, Self-emp-not-inc, 189721, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 20, United-States, <=50K 48, Private, 164966, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 40, India, >50K 36, ?, 94954, Assoc-voc, 11, Widowed, ?, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 34, Private, 202046, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, >50K 28, Private, 161538, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 67, Private, 105252, Bachelors, 13, Widowed, Exec-managerial, Not-in-family, White, Male, 0, 2392, 40, United-States, >50K 37, Private, 200153, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 32185, HS-grad, 9, Never-married, Transport-moving, Unmarried, White, Male, 0, 0, 70, United-States, <=50K 25, Private, 178326, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 255957, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 4101, 0, 40, United-States, <=50K 40, State-gov, 188693, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, >50K 78, Private, 182977, HS-grad, 9, Widowed, Other-service, Not-in-family, Black, Female, 2964, 0, 40, United-States, <=50K 34, Private, 159929, HS-grad, 9, Divorced, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 123207, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 44, United-States, <=50K 22, Private, 284317, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, ?, 184699, HS-grad, 9, Never-married, ?, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 60, Self-emp-not-inc, 154474, HS-grad, 9, Never-married, Farming-fishing, Unmarried, White, Male, 0, 0, 42, United-States, <=50K 45, Local-gov, 318280, HS-grad, 9, Widowed, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 63, Private, 254907, Assoc-voc, 11, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 41, Private, 349221, HS-grad, 9, Never-married, Craft-repair, Own-child, Black, Female, 0, 0, 35, United-States, <=50K 47, Private, 335973, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 126701, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 122159, Some-college, 10, Widowed, Prof-specialty, Not-in-family, White, Female, 3325, 0, 40, United-States, <=50K 46, Private, 187370, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 1504, 40, United-States, <=50K 41, Private, 194636, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Self-emp-not-inc, 124793, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 30, United-States, <=50K 47, Private, 192835, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, >50K 35, Private, 290226, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 56, Private, 112840, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 45, Private, 89325, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 48, Federal-gov, 33109, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 58, United-States, >50K 40, Private, 82465, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 2580, 0, 40, United-States, <=50K 39, Self-emp-inc, 329980, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 20, Private, 148294, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 168212, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 65, United-States, >50K 38, State-gov, 343642, HS-grad, 9, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 23, Local-gov, 115244, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 60, United-States, <=50K 31, Private, 162572, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 16, United-States, <=50K 58, Private, 356067, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 66, Private, 271567, HS-grad, 9, Separated, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 39, Self-emp-inc, 180804, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 54, Self-emp-not-inc, 123011, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 15024, 0, 52, United-States, >50K 26, Private, 109186, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, Germany, <=50K 51, Private, 220537, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 124827, Assoc-voc, 11, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 767403, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 3103, 0, 40, United-States, >50K 42, Private, 118494, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 44, United-States, >50K 38, Private, 173208, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 25, United-States, <=50K 48, Private, 107373, 7th-8th, 4, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 26973, Assoc-voc, 11, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 40, United-States, >50K 51, Private, 191965, HS-grad, 9, Widowed, Other-service, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 22, Private, 122346, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 19, ?, 117201, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 0, 30, United-States, <=50K 41, Private, 198316, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, Japan, <=50K 48, Local-gov, 123075, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, >50K 42, Private, 209370, HS-grad, 9, Separated, Sales, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 34, Private, 33117, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 129042, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 56, Private, 169133, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 50, Yugoslavia, <=50K 30, Private, 201624, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Black, Male, 0, 0, 45, ?, <=50K 45, Private, 368561, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 48, Private, 207848, 10th, 6, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 48, Self-emp-inc, 138370, Masters, 14, Married-spouse-absent, Sales, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 50, India, <=50K 31, Private, 93106, Assoc-voc, 11, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 20, State-gov, 223515, Assoc-acdm, 12, Never-married, Other-service, Own-child, White, Male, 0, 1719, 20, United-States, <=50K 27, Private, 389713, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 206365, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 76, ?, 431192, 7th-8th, 4, Widowed, ?, Not-in-family, White, Male, 0, 0, 2, United-States, <=50K 19, ?, 241616, HS-grad, 9, Never-married, ?, Unmarried, White, Male, 0, 2001, 40, United-States, <=50K 66, Self-emp-inc, 150726, 9th, 5, Married-civ-spouse, Exec-managerial, Husband, White, Male, 1409, 0, 1, ?, <=50K 37, Private, 123785, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 75, United-States, <=50K 34, Private, 289984, HS-grad, 9, Divorced, Priv-house-serv, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 34, ?, 164309, 11th, 7, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 8, United-States, <=50K 90, Private, 137018, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 137994, Some-college, 10, Never-married, Machine-op-inspct, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 43, Private, 341204, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 167005, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 60, United-States, >50K 24, Private, 34446, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 37, United-States, <=50K 28, Private, 187160, Prof-school, 15, Divorced, Prof-specialty, Unmarried, White, Male, 0, 0, 55, United-States, <=50K 64, ?, 196288, Assoc-acdm, 12, Never-married, ?, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 23, Private, 217961, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 74631, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 36, Private, 156667, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 50, United-States, >50K 61, Private, 125155, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 53, Self-emp-not-inc, 263925, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, Canada, >50K 30, Private, 296453, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 7298, 0, 40, United-States, >50K 52, Self-emp-not-inc, 44728, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, >50K 38, Private, 193026, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Iran, <=50K 32, Private, 87643, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Self-emp-not-inc, 106742, 12th, 8, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 75, United-States, <=50K 41, Private, 302122, Assoc-voc, 11, Divorced, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 49, Local-gov, 193960, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 40, United-States, >50K 45, Private, 185385, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 47, United-States, >50K 43, Self-emp-not-inc, 277647, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 35, United-States, <=50K 61, Private, 128848, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 3471, 0, 40, United-States, <=50K 54, Private, 377701, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 32, Mexico, <=50K 34, Private, 157886, Assoc-acdm, 12, Separated, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 175958, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 80, United-States, >50K 38, Private, 223004, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 199352, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 80, United-States, >50K 36, Private, 29984, 12th, 8, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 181651, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 36, Private, 117312, Assoc-acdm, 12, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 22, Local-gov, 34029, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 20, United-States, <=50K 38, Private, 132879, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1902, 40, United-States, >50K 37, Private, 215310, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 48, State-gov, 55863, Doctorate, 16, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 1902, 46, United-States, >50K 17, Private, 220384, 11th, 7, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 15, United-States, <=50K 19, Self-emp-not-inc, 36012, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 20, United-States, <=50K 27, Private, 137645, Bachelors, 13, Never-married, Sales, Not-in-family, Black, Female, 0, 1590, 40, United-States, <=50K 22, Private, 191342, Bachelors, 13, Never-married, Sales, Own-child, Asian-Pac-Islander, Male, 0, 0, 50, Taiwan, <=50K 49, Private, 31339, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, State-gov, 227910, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 43, Private, 173728, Bachelors, 13, Separated, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 19, Local-gov, 167816, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 58, Self-emp-not-inc, 81642, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 41, Local-gov, 195258, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 232475, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 241259, Assoc-voc, 11, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 118161, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 201954, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 42, Private, 150533, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 52, United-States, >50K 38, Private, 412296, HS-grad, 9, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 28, United-States, <=50K 41, Federal-gov, 133060, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 44, Self-emp-not-inc, 120539, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 31, Private, 196025, Doctorate, 16, Married-spouse-absent, Prof-specialty, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 60, China, <=50K 34, Private, 107793, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 163870, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 22, Self-emp-not-inc, 361280, Bachelors, 13, Never-married, Prof-specialty, Own-child, Asian-Pac-Islander, Male, 0, 0, 20, India, <=50K 62, Private, 92178, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, ?, 80710, HS-grad, 9, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 29, Self-emp-inc, 260729, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 1977, 25, United-States, >50K 43, Private, 182254, Some-college, 10, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 68, ?, 140282, 7th-8th, 4, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 8, United-States, <=50K 45, Self-emp-inc, 149865, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 60, United-States, >50K 39, Self-emp-inc, 218184, 9th, 5, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1651, 40, Mexico, <=50K 41, Private, 118619, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 50, United-States, <=50K 34, Self-emp-not-inc, 196791, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 25, United-States, >50K 34, Local-gov, 167999, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 33, United-States, <=50K 31, Private, 51259, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 47, United-States, <=50K 29, Private, 131088, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 25, United-States, <=50K 41, Private, 118212, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 3103, 0, 40, United-States, >50K 41, Private, 293791, Assoc-voc, 11, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 55, United-States, <=50K 35, Self-emp-inc, 289430, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, Mexico, >50K 33, Private, 35378, Bachelors, 13, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 45, United-States, >50K 37, State-gov, 60227, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 69, Private, 168139, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 290763, HS-grad, 9, Divorced, Handlers-cleaners, Own-child, White, Female, 0, 0, 40, United-States, <=50K 60, Self-emp-inc, 226355, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 2415, 70, ?, >50K 36, Private, 51100, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 227644, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 58, Local-gov, 205267, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 53, Private, 288020, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Japan, <=50K 29, Private, 140863, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Federal-gov, 170915, HS-grad, 9, Divorced, Tech-support, Not-in-family, White, Female, 4865, 0, 40, United-States, <=50K 34, State-gov, 50178, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 38, United-States, <=50K 36, Private, 112497, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 95244, Some-college, 10, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 20, Private, 117606, Assoc-voc, 11, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 89508, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 63, Federal-gov, 124244, HS-grad, 9, Widowed, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 41, Self-emp-not-inc, 154374, Some-college, 10, Divorced, Other-service, Unmarried, White, Male, 0, 0, 45, United-States, <=50K 28, Private, 294936, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, <=50K 30, Private, 347132, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 34, ?, 181934, HS-grad, 9, Divorced, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 316672, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 37, Private, 189382, Assoc-voc, 11, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 38, United-States, <=50K 42, ?, 184018, Some-college, 10, Divorced, ?, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 184307, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, Jamaica, >50K 46, Self-emp-not-inc, 246212, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 35, Federal-gov, 250504, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 60, United-States, >50K 27, Private, 138705, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 53, United-States, <=50K 41, Private, 328447, 1st-4th, 2, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, Mexico, <=50K 19, Private, 194608, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 20, Private, 230891, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 59, Federal-gov, 212448, HS-grad, 9, Widowed, Sales, Unmarried, White, Female, 0, 0, 40, Germany, <=50K 40, Private, 214010, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 37, United-States, <=50K 56, Self-emp-not-inc, 200235, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 33, Private, 354573, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 44, United-States, >50K 30, Self-emp-inc, 205733, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 46, Private, 185041, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, <=50K 61, Self-emp-inc, 84409, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 35, United-States, >50K 50, Self-emp-inc, 293196, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 40, United-States, >50K 25, Private, 241626, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, United-States, <=50K 40, Private, 520586, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 39, United-States, <=50K 24, ?, 35633, Some-college, 10, Never-married, ?, Not-in-family, White, Male, 0, 0, 40, ?, <=50K 51, Private, 302847, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 54, United-States, <=50K 43, State-gov, 165309, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 117529, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 54, Mexico, <=50K 46, Private, 106092, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 28, State-gov, 445824, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 50, United-States, >50K 26, Private, 227332, Bachelors, 13, Never-married, Transport-moving, Unmarried, Asian-Pac-Islander, Male, 0, 0, 40, ?, <=50K 20, Private, 275691, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 28, United-States, <=50K 44, Private, 193459, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 3411, 0, 40, United-States, <=50K 51, Private, 284329, HS-grad, 9, Widowed, Transport-moving, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 114691, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 54, Private, 96062, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 50, Private, 133963, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 1977, 40, United-States, >50K 33, Private, 178506, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 65, Private, 350498, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 10605, 0, 20, United-States, >50K 22, ?, 131573, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 8, United-States, <=50K 88, Self-emp-not-inc, 206291, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 182302, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 241346, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 43, United-States, <=50K 50, Private, 157043, 11th, 7, Divorced, Other-service, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 25, Private, 404616, Masters, 14, Married-civ-spouse, Farming-fishing, Not-in-family, White, Male, 0, 0, 99, United-States, >50K 20, Private, 411862, Assoc-voc, 11, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 47, Private, 183013, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, ?, 169982, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, >50K 22, Private, 188544, Assoc-voc, 11, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 30, United-States, <=50K 50, State-gov, 356619, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 48, United-States, >50K 47, Private, 45857, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 24, Local-gov, 289886, 11th, 7, Never-married, Other-service, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 45, United-States, <=50K 50, ?, 146015, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Private, 216237, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, >50K 36, Private, 416745, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 202952, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 167725, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, ?, 165637, Masters, 14, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 59, Federal-gov, 43280, Some-college, 10, Never-married, Exec-managerial, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 65, Private, 118779, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 30, United-States, <=50K 24, State-gov, 191269, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 65, United-States, <=50K 27, Local-gov, 247507, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 35, United-States, <=50K 51, Private, 239155, Assoc-voc, 11, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 182862, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 33886, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 28, Private, 444304, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 187161, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 49, Local-gov, 116892, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 51, Local-gov, 176813, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 59, Private, 151616, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, <=50K 18, Private, 240747, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, Dominican-Republic, <=50K 50, Private, 75472, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 4386, 0, 40, ?, <=50K 45, Federal-gov, 320818, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 80, United-States, >50K 30, Local-gov, 235271, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 37, Private, 166497, Bachelors, 13, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 44, Private, 344060, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 33, Private, 221196, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 61, Self-emp-inc, 113544, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 61, Local-gov, 321117, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 79619, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 42, United-States, >50K 22, ?, 42004, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 30, United-States, <=50K 36, Private, 135289, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, <=50K 44, Self-emp-inc, 320984, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 5178, 0, 60, United-States, >50K 37, Private, 203070, Some-college, 10, Separated, Adm-clerical, Own-child, White, Male, 0, 0, 62, United-States, <=50K 31, Private, 32406, Some-college, 10, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 54, Private, 99185, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 45, United-States, >50K 20, Private, 205839, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 16, United-States, <=50K 63, ?, 150389, Bachelors, 13, Widowed, ?, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 48, Self-emp-not-inc, 243631, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Amer-Indian-Eskimo, Male, 7688, 0, 40, United-States, >50K 33, ?, 163003, HS-grad, 9, Divorced, ?, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 41, China, <=50K 31, Private, 231263, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 4650, 0, 45, United-States, <=50K 38, Private, 200818, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 45, Self-emp-not-inc, 247379, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 48, Private, 349151, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 22154, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 176317, HS-grad, 9, Widowed, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 22245, Masters, 14, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 72, ?, >50K 29, Private, 236436, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 354078, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 42, Self-emp-not-inc, 166813, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 50, Private, 358740, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, England, <=50K 75, Self-emp-not-inc, 208426, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, <=50K 46, Private, 265266, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 40, United-States, >50K 52, Federal-gov, 31838, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 175034, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 413297, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 31, Private, 106347, 11th, 7, Separated, Other-service, Not-in-family, Black, Female, 0, 0, 42, United-States, <=50K 23, Private, 174754, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 34, Private, 441454, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 24, United-States, <=50K 41, Self-emp-not-inc, 209344, HS-grad, 9, Married-civ-spouse, Sales, Other-relative, White, Female, 0, 0, 40, Cuba, <=50K 31, Private, 185732, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 42, Private, 65372, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 33975, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 55, Private, 326297, HS-grad, 9, Separated, Adm-clerical, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 36, State-gov, 194630, HS-grad, 9, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 65, Self-emp-not-inc, 167414, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 59, United-States, >50K 38, Local-gov, 165799, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 12, United-States, <=50K 62, Private, 192866, Some-college, 10, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 54, Self-emp-inc, 166459, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 60, United-States, >50K 49, Private, 148995, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 190040, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 209432, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 40, United-States, <=50K 51, Self-emp-inc, 229465, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 48, Self-emp-not-inc, 397466, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 30, Private, 283767, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, ?, <=50K 52, Federal-gov, 202452, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 43, United-States, <=50K 28, Self-emp-not-inc, 218555, Some-college, 10, Never-married, Transport-moving, Not-in-family, White, Male, 0, 1762, 40, United-States, <=50K 29, Private, 128604, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 38, Private, 65466, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 57, Private, 141326, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 43, Federal-gov, 369468, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 37, State-gov, 136137, Some-college, 10, Separated, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 236770, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 89534, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 48, United-States, >50K 69, ?, 195779, Assoc-voc, 11, Widowed, ?, Not-in-family, White, Female, 0, 0, 1, United-States, <=50K 73, Private, 29778, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 37, United-States, <=50K 22, Self-emp-inc, 153516, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 35, United-States, <=50K 31, Private, 163594, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 38, Private, 189623, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1887, 40, United-States, >50K 50, Self-emp-not-inc, 343748, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 37, Private, 387430, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 37, United-States, <=50K 44, Local-gov, 409505, Bachelors, 13, Divorced, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 200734, Bachelors, 13, Never-married, Exec-managerial, Unmarried, Black, Female, 0, 0, 45, United-States, <=50K 27, Private, 115831, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 150296, Assoc-acdm, 12, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 80, United-States, <=50K 25, Private, 323545, HS-grad, 9, Never-married, Tech-support, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 20, Private, 232577, Some-college, 10, Never-married, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 51, Local-gov, 152754, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Private, 129007, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 1977, 40, United-States, >50K 67, Private, 171584, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 6514, 0, 7, United-States, >50K 47, Private, 386136, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 35, United-States, <=50K 42, Private, 342865, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 186785, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 1876, 50, United-States, <=50K 42, Federal-gov, 158926, Assoc-acdm, 12, Divorced, Prof-specialty, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, >50K 65, ?, 36039, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, >50K 21, Private, 164019, Some-college, 10, Never-married, Farming-fishing, Own-child, Black, Male, 0, 0, 10, United-States, <=50K 50, Private, 88926, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 5178, 0, 40, United-States, >50K 46, Private, 188861, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Self-emp-not-inc, 370119, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 50, United-States, >50K 57, Private, 182062, 10th, 6, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 37238, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 50, Private, 421132, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, ?, 178660, 12th, 8, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 63, Self-emp-not-inc, 795830, 1st-4th, 2, Widowed, Other-service, Unmarried, White, Female, 0, 0, 30, El-Salvador, <=50K 39, Private, 278403, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 65, United-States, <=50K 46, Private, 279661, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 35, United-States, <=50K 36, Private, 113397, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 280093, 5th-6th, 3, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1628, 50, United-States, <=50K 21, Private, 236696, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 57, United-States, <=50K 41, Private, 265266, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Local-gov, 34935, Some-college, 10, Never-married, Other-service, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 22, Private, 58222, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Federal-gov, 301010, Some-college, 10, Never-married, Armed-Forces, Not-in-family, Black, Male, 0, 0, 60, United-States, <=50K 29, Private, 419721, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, Japan, <=50K 58, Self-emp-inc, 186791, Some-college, 10, Married-civ-spouse, Transport-moving, Wife, White, Female, 0, 0, 40, United-States, >50K 36, Self-emp-not-inc, 180686, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 30, Private, 209103, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 48, United-States, <=50K 37, Private, 32668, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 43, United-States, >50K 29, Private, 256956, Assoc-voc, 11, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 202203, 5th-6th, 3, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, Mexico, <=50K 43, Private, 85995, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 49, Private, 125421, HS-grad, 9, Married-civ-spouse, Craft-repair, Wife, White, Female, 0, 0, 40, United-States, >50K 45, Federal-gov, 283037, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 192932, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 20, ?, 244689, Some-college, 10, Never-married, ?, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 51, Private, 179646, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 509350, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 50, Canada, >50K 24, Private, 96279, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 119098, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7298, 0, 40, United-States, >50K 35, ?, 327120, Assoc-acdm, 12, Never-married, ?, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 41, State-gov, 144928, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 48, Private, 55237, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 61, Local-gov, 101265, HS-grad, 9, Widowed, Adm-clerical, Unmarried, White, Female, 1471, 0, 35, United-States, <=50K 20, Private, 114874, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 30, United-States, <=50K 27, Private, 190525, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 55, Private, 121912, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 24, United-States, >50K 39, Private, 83893, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 17, ?, 138507, 10th, 6, Never-married, ?, Own-child, White, Male, 0, 0, 20, United-States, <=50K 47, Private, 256522, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, ?, <=50K 52, Private, 168381, HS-grad, 9, Widowed, Other-service, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, India, >50K 24, Private, 293579, HS-grad, 9, Never-married, Sales, Own-child, Black, Female, 0, 0, 20, United-States, <=50K 29, Private, 285290, 11th, 7, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 25, Private, 188488, HS-grad, 9, Never-married, Machine-op-inspct, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 324469, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 275244, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 35, United-States, <=50K 57, Private, 265099, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 51, Private, 146767, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Private, 40681, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Female, 3674, 0, 16, United-States, <=50K 39, Private, 174938, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 240124, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 71, Private, 269708, Bachelors, 13, Divorced, Tech-support, Own-child, White, Female, 2329, 0, 16, United-States, <=50K 38, State-gov, 34180, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, State-gov, 225904, Prof-school, 15, Never-married, Prof-specialty, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 89392, Masters, 14, Married-spouse-absent, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 46857, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 59, State-gov, 105363, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 195105, HS-grad, 9, Never-married, Sales, Not-in-family, Other, Male, 0, 0, 40, United-States, <=50K 35, Private, 184117, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 61, Self-emp-inc, 134768, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, Germany, >50K 17, ?, 145886, 11th, 7, Never-married, ?, Own-child, White, Female, 0, 0, 30, United-States, <=50K 36, Private, 153078, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 60, ?, >50K 62, ?, 225652, 7th-8th, 4, Married-civ-spouse, ?, Husband, White, Male, 3411, 0, 50, United-States, <=50K 34, Private, 467108, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 32, Self-emp-inc, 199765, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 7688, 0, 50, United-States, >50K 42, Private, 173938, HS-grad, 9, Separated, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 191161, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, Private, 132606, 5th-6th, 3, Divorced, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 61, Self-emp-not-inc, 30073, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 1848, 60, United-States, >50K 40, Private, 155190, 10th, 6, Never-married, Craft-repair, Other-relative, Black, Male, 0, 0, 55, United-States, <=50K 31, Private, 42900, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 37, United-States, <=50K 36, Private, 191161, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 23, Private, 181820, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 105974, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 41, United-States, <=50K 52, Private, 146378, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 22, Private, 103440, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 24, United-States, <=50K 51, Private, 203435, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, Italy, <=50K 31, Federal-gov, 168312, Assoc-voc, 11, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 49, Self-emp-inc, 257764, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 171301, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, Black, Female, 0, 0, 40, United-States, <=50K 53, Federal-gov, 225339, Some-college, 10, Widowed, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 52, Private, 152234, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 99999, 0, 40, Japan, >50K 20, Private, 444554, 10th, 6, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 403788, Assoc-acdm, 12, Never-married, Other-service, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 61, ?, 190997, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 6, United-States, <=50K 43, Private, 221550, Masters, 14, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 30, Poland, <=50K 46, Self-emp-inc, 98929, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 52, United-States, <=50K 43, Local-gov, 169203, Assoc-voc, 11, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 41, Private, 102332, HS-grad, 9, Divorced, Sales, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 44, Self-emp-not-inc, 230684, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 55, United-States, <=50K 54, Private, 449257, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 65, Private, 198766, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 20051, 0, 40, United-States, >50K 32, Private, 97429, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, Canada, <=50K 25, Private, 208999, Some-college, 10, Separated, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 37072, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 25, Local-gov, 163101, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 19, Private, 119075, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 50, United-States, <=50K 37, Self-emp-not-inc, 137314, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 45, Private, 127303, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 45, United-States, <=50K 37, Private, 349116, HS-grad, 9, Never-married, Sales, Not-in-family, Black, Male, 0, 0, 44, United-States, <=50K 40, Self-emp-not-inc, 266324, Some-college, 10, Divorced, Exec-managerial, Other-relative, White, Male, 0, 1564, 70, Iran, >50K 19, ?, 194095, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 46496, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 5, United-States, <=50K 27, Private, 29904, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 40, Local-gov, 289403, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 1887, 40, ?, >50K 59, Private, 226922, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 1762, 30, United-States, <=50K 19, Federal-gov, 234151, HS-grad, 9, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 43, Private, 238287, 10th, 6, Never-married, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 42, Private, 230624, 10th, 6, Never-married, Transport-moving, Unmarried, White, Male, 0, 0, 40, United-States, >50K 54, Private, 398212, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 5013, 0, 40, United-States, <=50K 54, Self-emp-not-inc, 114758, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 51, Private, 246519, 10th, 6, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 2105, 0, 45, United-States, <=50K 50, Private, 137815, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, >50K 40, Private, 260696, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 55, Private, 325007, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 25, United-States, <=50K 50, Private, 113176, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 66815, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 42, ?, 51795, HS-grad, 9, Divorced, ?, Unmarried, Black, Female, 0, 0, 32, United-States, <=50K 24, Private, 241523, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 45, United-States, >50K 30, Private, 30226, 11th, 7, Divorced, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 39, Local-gov, 352628, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Wife, White, Female, 0, 0, 50, United-States, >50K 37, Private, 143912, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 33, Private, 130021, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 329778, HS-grad, 9, Widowed, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 43, Self-emp-inc, 196945, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 78, Thailand, <=50K 39, Private, 24342, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 53, Private, 34368, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 52, Self-emp-not-inc, 173839, 10th, 6, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 28, State-gov, 73211, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 0, 20, United-States, <=50K 32, Private, 86723, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 52, United-States, <=50K 31, Private, 179186, Bachelors, 13, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 90, United-States, >50K 31, Private, 127610, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 47, Private, 115070, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 19, ?, 172582, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 50, United-States, <=50K 40, Private, 256202, Assoc-voc, 11, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, United-States, <=50K 40, Private, 202872, Assoc-acdm, 12, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 45, United-States, <=50K 41, Private, 184102, 11th, 7, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 53, Federal-gov, 130703, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, <=50K 46, Private, 134727, 11th, 7, Divorced, Machine-op-inspct, Unmarried, Amer-Indian-Eskimo, Male, 0, 0, 43, Germany, <=50K 45, Self-emp-inc, 36228, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 4386, 0, 35, United-States, >50K 39, Private, 297847, 9th, 5, Married-civ-spouse, Other-service, Wife, Black, Female, 3411, 0, 34, United-States, <=50K 19, Private, 213644, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 173796, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1887, 40, United-States, >50K 49, Private, 147322, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, Peru, <=50K 59, Private, 296253, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 180871, Assoc-voc, 11, Divorced, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 18, ?, 169882, Some-college, 10, Never-married, ?, Own-child, White, Female, 594, 0, 15, United-States, <=50K 35, State-gov, 211115, Some-college, 10, Never-married, Protective-serv, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 58, Self-emp-inc, 183870, 10th, 6, Married-civ-spouse, Transport-moving, Wife, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 441620, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 43, Mexico, <=50K 36, Federal-gov, 218542, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 41, Self-emp-not-inc, 141327, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 47, Private, 67716, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 50, Self-emp-inc, 175339, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1672, 60, United-States, <=50K 61, ?, 347089, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 16, United-States, <=50K 36, Private, 336595, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 38, Private, 27997, Assoc-voc, 11, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 56, Self-emp-not-inc, 145574, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 1902, 60, United-States, >50K 50, Private, 30447, Assoc-voc, 11, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 45, Self-emp-not-inc, 256866, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 5013, 0, 40, United-States, <=50K 44, Self-emp-not-inc, 120837, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 66, United-States, <=50K 51, Private, 185283, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 44, Self-emp-inc, 229466, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 25, Private, 298225, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 60, Private, 185749, 11th, 7, Widowed, Transport-moving, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 17, ?, 333100, 10th, 6, Never-married, ?, Own-child, White, Male, 1055, 0, 30, United-States, <=50K 49, Self-emp-inc, 125892, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 46, Private, 563883, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 60, United-States, >50K 56, Private, 311249, HS-grad, 9, Widowed, Adm-clerical, Unmarried, Black, Female, 0, 0, 38, United-States, <=50K 25, Private, 221757, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 3325, 0, 45, United-States, <=50K 22, Private, 310152, Some-college, 10, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 76, ?, 211453, HS-grad, 9, Widowed, ?, Not-in-family, Black, Female, 0, 0, 2, United-States, <=50K 41, Self-emp-inc, 94113, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 48, Self-emp-inc, 192945, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 40, United-States, >50K 46, Private, 161508, 10th, 6, Never-married, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 30, Private, 177675, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 39, Private, 51100, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Private, 100584, 10th, 6, Divorced, Craft-repair, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 70, Federal-gov, 163003, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, <=50K 35, Private, 67728, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 2051, 45, United-States, <=50K 49, Private, 101320, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 75, United-States, <=50K 24, Private, 42706, Assoc-voc, 11, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 40, Private, 228535, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7298, 0, 36, United-States, >50K 61, Private, 120939, Prof-school, 15, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 5, United-States, >50K 25, Private, 98283, Bachelors, 13, Never-married, Prof-specialty, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 28, Local-gov, 216481, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 69, State-gov, 208869, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 11, United-States, <=50K 22, Private, 207940, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 36, United-States, <=50K 47, Private, 34248, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 38, United-States, <=50K 38, Private, 83727, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 48, United-States, <=50K 26, Private, 183077, Assoc-voc, 11, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 17, Private, 197850, 11th, 7, Never-married, Adm-clerical, Own-child, Asian-Pac-Islander, Female, 0, 0, 24, United-States, <=50K 33, Self-emp-not-inc, 235271, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 43, Self-emp-not-inc, 35236, HS-grad, 9, Married-spouse-absent, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 58, Private, 255822, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 53, Self-emp-inc, 263925, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 99999, 0, 40, United-States, >50K 26, Private, 256263, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 43, Local-gov, 293535, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 40, United-States, >50K 31, Private, 209448, 10th, 6, Married-civ-spouse, Farming-fishing, Husband, White, Male, 2105, 0, 40, Mexico, <=50K 30, Private, 57651, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Male, 0, 2001, 42, United-States, <=50K 25, Private, 174592, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 57, Federal-gov, 278763, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 175232, Masters, 14, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 60, United-States, >50K 32, Private, 402812, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 48, United-States, <=50K 26, Private, 101150, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 41, United-States, <=50K 45, Private, 103538, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 53, State-gov, 156877, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 15024, 0, 35, United-States, >50K 27, Private, 23940, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 28, Self-emp-inc, 210295, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 32, Private, 80058, 11th, 7, Divorced, Sales, Not-in-family, White, Male, 0, 0, 43, United-States, >50K 35, Private, 187119, Bachelors, 13, Divorced, Sales, Not-in-family, White, Female, 0, 1980, 65, United-States, <=50K 36, Self-emp-not-inc, 105021, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 19, Private, 225775, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Self-emp-inc, 395831, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 80, United-States, >50K 49, Private, 50282, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, White, Male, 3325, 0, 45, United-States, <=50K 20, Private, 32732, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 64, Self-emp-inc, 179436, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 55, United-States, >50K 60, ?, 290593, Masters, 14, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 123253, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 42, United-States, <=50K 58, State-gov, 48433, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 245317, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 20, Private, 431745, Some-college, 10, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 14, United-States, <=50K 42, State-gov, 436006, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, <=50K 25, Private, 224943, Some-college, 10, Married-spouse-absent, Prof-specialty, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 30, Self-emp-not-inc, 167990, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 65, United-States, >50K 37, Self-emp-inc, 217054, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, >50K 66, Self-emp-not-inc, 298834, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 59, Self-emp-inc, 125000, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, England, >50K 44, Private, 123983, Bachelors, 13, Divorced, Other-service, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, China, <=50K 46, Private, 155489, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 58, United-States, >50K 59, Private, 284834, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 2885, 0, 30, United-States, <=50K 25, Private, 212495, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 1340, 40, United-States, <=50K 17, Local-gov, 32124, 9th, 5, Never-married, Other-service, Own-child, Black, Male, 0, 0, 9, United-States, <=50K 47, Local-gov, 246891, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, State-gov, 141483, 9th, 5, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 31985, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 170800, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Female, 0, 0, 40, United-States, <=50K 26, Local-gov, 166295, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 2339, 55, United-States, <=50K 20, Private, 231286, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 15, United-States, <=50K 33, Private, 159322, HS-grad, 9, Divorced, Other-service, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 176026, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 118025, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 50, United-States, >50K 37, Private, 26898, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 12, United-States, <=50K 47, Private, 232628, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 40, Private, 85995, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 48, Private, 125421, Masters, 14, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, >50K 49, Private, 245305, 10th, 6, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 42, United-States, >50K 50, Private, 73493, Some-college, 10, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 197058, Assoc-acdm, 12, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 122116, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 75742, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 214731, 10th, 6, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 265954, HS-grad, 9, Separated, Other-service, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 26, State-gov, 197156, HS-grad, 9, Divorced, Adm-clerical, Own-child, White, Female, 0, 0, 30, United-States, <=50K 62, Private, 162245, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1628, 70, United-States, <=50K 39, Local-gov, 203070, HS-grad, 9, Separated, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 59, Local-gov, 165695, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 69, ?, 473040, 5th-6th, 3, Divorced, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 168107, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 163494, 10th, 6, Never-married, Sales, Own-child, White, Male, 0, 0, 30, United-States, <=50K 38, Private, 180342, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 122381, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1887, 50, United-States, >50K 27, Private, 148069, 10th, 6, Never-married, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 200973, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 17, Private, 130806, 10th, 6, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 24, United-States, <=50K 56, Private, 117148, 7th-8th, 4, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 213977, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 62, Private, 134768, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 40, ?, >50K 44, Private, 139338, 12th, 8, Divorced, Transport-moving, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 23, Private, 315877, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 41, Self-emp-not-inc, 195124, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, ?, <=50K 25, Private, 352057, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 21, Private, 236684, Some-college, 10, Never-married, Other-service, Other-relative, Black, Female, 0, 0, 8, United-States, <=50K 18, Private, 208447, 12th, 8, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 6, United-States, <=50K 45, Private, 149640, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 75, ?, 111177, Bachelors, 13, Widowed, ?, Not-in-family, White, Female, 25124, 0, 16, United-States, >50K 51, Private, 154342, 7th-8th, 4, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Federal-gov, 141459, HS-grad, 9, Separated, Other-service, Other-relative, Black, Female, 0, 0, 40, United-States, <=50K 47, Private, 111797, Some-college, 10, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 35, Outlying-US(Guam-USVI-etc), <=50K 29, Private, 111900, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 78707, 11th, 7, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 43, Local-gov, 160574, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, ?, 174714, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 16, United-States, <=50K 19, ?, 62534, Bachelors, 13, Never-married, ?, Own-child, Black, Female, 0, 0, 40, Jamaica, <=50K 44, Private, 216907, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1848, 40, United-States, >50K 24, Private, 198148, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, United-States, <=50K 19, Private, 124265, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 49, ?, 261059, 10th, 6, Separated, ?, Own-child, White, Male, 2176, 0, 40, United-States, <=50K 52, Private, 208137, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Self-emp-not-inc, 257250, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 52, United-States, <=50K 24, State-gov, 147253, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 32, Local-gov, 244268, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 72, ?, 213255, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 8, United-States, <=50K 26, Private, 266912, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 31, Private, 169104, Bachelors, 13, Never-married, Sales, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, ?, <=50K 29, Private, 200511, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 39, Private, 128715, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Male, 10520, 0, 40, United-States, >50K 48, Self-emp-not-inc, 65535, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 40, Private, 103395, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 51, Private, 71046, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 45, Scotland, <=50K 28, Self-emp-not-inc, 125442, HS-grad, 9, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 169188, HS-grad, 9, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 20, United-States, <=50K 23, Private, 121471, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 65, Private, 207281, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 16, United-States, <=50K 26, Local-gov, 46097, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, ?, 206671, Some-college, 10, Never-married, ?, Own-child, White, Male, 1055, 0, 50, United-States, <=50K 55, Private, 98361, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 50, ?, >50K 38, Self-emp-not-inc, 322143, Bachelors, 13, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 10, United-States, <=50K 33, Private, 149184, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 33, Local-gov, 119829, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 60, United-States, <=50K 37, Private, 910398, Bachelors, 13, Never-married, Sales, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 19, Private, 176570, 11th, 7, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 60, United-States, <=50K 24, Private, 216129, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 30, Private, 27207, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 57, State-gov, 68830, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 22, State-gov, 178818, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 20, United-States, <=50K 57, Private, 236944, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, >50K 46, State-gov, 273771, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 67, Private, 318533, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 35, United-States, <=50K 35, ?, 451940, HS-grad, 9, Never-married, ?, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 47, Private, 102318, HS-grad, 9, Separated, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 379350, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 21095, Some-college, 10, Divorced, Other-service, Unmarried, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 58, Self-emp-not-inc, 211547, 12th, 8, Divorced, Sales, Not-in-family, White, Female, 0, 0, 52, United-States, <=50K 36, Private, 85272, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 30, United-States, >50K 45, Private, 46406, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 36, England, >50K 54, Private, 53833, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 161007, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 30, United-States, <=50K 60, Private, 53707, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Private, 370119, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 60, United-States, >50K 26, Private, 310907, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 35, United-States, <=50K 32, Private, 375833, 11th, 7, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 38, Local-gov, 107513, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Self-emp-not-inc, 58683, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 70, United-States, >50K 44, Self-emp-not-inc, 179557, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 45, United-States, >50K 37, Private, 70240, HS-grad, 9, Never-married, Other-service, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 44, Private, 147206, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 175548, HS-grad, 9, Never-married, Other-service, Not-in-family, Other, Female, 0, 0, 35, United-States, <=50K 61, Self-emp-not-inc, 163174, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, >50K 51, Private, 126010, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 147876, Bachelors, 13, Married-civ-spouse, Sales, Wife, White, Female, 15024, 0, 60, United-States, >50K 45, Private, 428350, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 1740, 40, United-States, <=50K 36, ?, 200904, Assoc-acdm, 12, Married-civ-spouse, ?, Wife, Black, Female, 0, 0, 21, Haiti, <=50K 39, Private, 328466, 11th, 7, Married-civ-spouse, Other-service, Husband, White, Male, 2407, 0, 70, Mexico, <=50K 67, Local-gov, 258973, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 24, United-States, <=50K 40, State-gov, 345969, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 127796, 5th-6th, 3, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 35, Mexico, <=50K 37, Private, 405723, 1st-4th, 2, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 57, Private, 175942, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 27, Private, 284196, 10th, 6, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 89718, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 2202, 0, 48, United-States, <=50K 34, Self-emp-inc, 175761, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 54, Private, 206369, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 5178, 0, 50, United-States, >50K 52, Private, 158993, HS-grad, 9, Divorced, Other-service, Other-relative, Black, Female, 0, 0, 38, United-States, <=50K 42, Private, 285066, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 48, Private, 126754, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 40, United-States, >50K 65, State-gov, 209280, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 6514, 0, 35, United-States, >50K 55, Self-emp-not-inc, 52888, Prof-school, 15, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 10, United-States, <=50K 71, Self-emp-inc, 133821, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 20, United-States, >50K 33, Private, 240763, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 30, Private, 39054, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 119272, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 59, Private, 143372, 10th, 6, Divorced, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 19, Private, 323421, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, United-States, <=50K 36, Self-emp-not-inc, 136028, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 30, United-States, <=50K 26, Self-emp-not-inc, 163189, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 34, Local-gov, 202729, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 421871, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, >50K 44, Private, 120277, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 50, Italy, >50K 26, ?, 211798, HS-grad, 9, Separated, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 198901, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, <=50K 18, Private, 214617, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 16, United-States, <=50K 55, Self-emp-not-inc, 179715, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 18, United-States, <=50K 49, Local-gov, 107231, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 2002, 40, United-States, <=50K 44, Private, 110355, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 43, Private, 184378, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 62, Private, 273454, 7th-8th, 4, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, Cuba, <=50K 44, Private, 443040, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, United-States, <=50K 39, ?, 71701, HS-grad, 9, Divorced, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 50, Self-emp-inc, 160151, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 35, Private, 107991, 11th, 7, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 52, Private, 94391, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 99835, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 44, Private, 43711, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 40, United-States, >50K 43, Private, 83756, Some-college, 10, Never-married, Exec-managerial, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 51, Private, 120914, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 2961, 0, 40, United-States, <=50K 20, Private, 180052, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 20, United-States, <=50K 47, Private, 170846, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, Italy, >50K 43, Private, 37937, Masters, 14, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 64, ?, 168340, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, ?, >50K 24, Private, 38455, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Federal-gov, 128059, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 32, Private, 420895, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 166744, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 12, United-States, <=50K 26, Private, 238768, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 60, United-States, <=50K 43, Private, 176270, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 60, United-States, >50K 50, Private, 140592, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, United-States, <=50K 20, Self-emp-not-inc, 211466, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 80, United-States, <=50K 37, Private, 188540, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 45, United-States, >50K 43, Private, 39581, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 45, United-States, <=50K 37, Private, 171150, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1887, 50, United-States, >50K 53, Private, 117496, 9th, 5, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 36, Canada, <=50K 44, Private, 145160, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Private, 28520, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 17, Private, 103851, 11th, 7, Never-married, Adm-clerical, Own-child, White, Female, 1055, 0, 20, United-States, <=50K 19, Private, 375077, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 50, United-States, <=50K 53, State-gov, 281590, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 15024, 0, 40, United-States, >50K 44, Private, 151504, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 51, Private, 415287, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 1902, 40, United-States, >50K 49, Private, 32212, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 43, United-States, <=50K 35, Private, 123606, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 202565, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 54, Private, 177927, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 37, Private, 256723, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 18, Private, 46247, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 24, Private, 266926, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 112031, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 22, ?, 376277, Some-college, 10, Divorced, ?, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 35, Private, 168817, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 56, Private, 187487, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, >50K 32, ?, 158784, 7th-8th, 4, Widowed, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 67222, Bachelors, 13, Never-married, Machine-op-inspct, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 45, China, <=50K 43, Private, 201723, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 40, United-States, >50K 73, Private, 267408, HS-grad, 9, Widowed, Sales, Other-relative, White, Female, 0, 0, 15, United-States, <=50K 47, Federal-gov, 168191, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, ?, <=50K 49, Private, 105444, 12th, 8, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 39, United-States, <=50K 38, Private, 156728, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 148600, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 39, Private, 19914, Some-college, 10, Divorced, Adm-clerical, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 42, Private, 190767, Bachelors, 13, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 233955, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 45, China, >50K 35, Private, 30381, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 38, Private, 187069, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 31, Private, 367314, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 51, Local-gov, 101119, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 70, United-States, <=50K 38, Private, 86551, Bachelors, 13, Divorced, Sales, Not-in-family, White, Male, 0, 0, 48, United-States, >50K 40, Local-gov, 218995, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 42, United-States, >50K 21, Private, 57711, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 44, Private, 303521, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 199067, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Private, 247445, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 49, Private, 186078, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 50, United-States, >50K 31, Private, 77634, Assoc-voc, 11, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 42, United-States, <=50K 24, Private, 180060, Masters, 14, Never-married, Exec-managerial, Own-child, White, Male, 6849, 0, 90, United-States, <=50K 46, Private, 56482, Some-college, 10, Never-married, Exec-managerial, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 26, Private, 314177, HS-grad, 9, Never-married, Sales, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 35, Private, 239755, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 27, Private, 377680, Assoc-voc, 11, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 64, Self-emp-not-inc, 134960, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 35, United-States, >50K 26, Private, 294493, Bachelors, 13, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 32616, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 1719, 16, United-States, <=50K 45, Private, 182655, Bachelors, 13, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 45, ?, >50K 57, Local-gov, 52267, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 72, United-States, <=50K 30, Private, 117963, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 45, Private, 98881, 11th, 7, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 32, United-States, <=50K 50, Private, 196963, 7th-8th, 4, Divorced, Craft-repair, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 38, Private, 166988, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 43, Self-emp-not-inc, 193459, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 42, Private, 182342, Some-college, 10, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 32, Private, 496743, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 154781, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 219371, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 45, Private, 99179, 11th, 7, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 224910, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 304651, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 37, Private, 349689, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 60, Private, 106850, 10th, 6, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 53, Self-emp-not-inc, 196328, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 45, United-States, >50K 25, Private, 169323, Bachelors, 13, Married-civ-spouse, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 47, Self-emp-not-inc, 162924, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 60, Japan, <=50K 40, Self-emp-not-inc, 34037, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 51, ?, 167651, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 197384, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 10, United-States, <=50K 42, Private, 251795, Some-college, 10, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 50, United-States, >50K 65, ?, 266081, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 165309, Bachelors, 13, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 215873, 10th, 6, Never-married, Machine-op-inspct, Own-child, Black, Male, 0, 0, 45, United-States, <=50K 46, Private, 133938, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Female, 27828, 0, 50, United-States, >50K 49, Private, 159816, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 99999, 0, 20, United-States, >50K 24, Private, 228424, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, Black, Male, 0, 0, 40, United-States, <=50K 32, Private, 195576, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 71, Private, 105200, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 6767, 0, 20, United-States, <=50K 26, Private, 167350, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 3103, 0, 40, United-States, >50K 29, Private, 52199, HS-grad, 9, Married-spouse-absent, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 171338, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 50, United-States, >50K 51, Private, 120173, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 3103, 0, 50, United-States, >50K 17, ?, 158762, 10th, 6, Never-married, ?, Own-child, White, Female, 0, 0, 20, United-States, <=50K 49, Private, 169818, HS-grad, 9, Married-civ-spouse, Other-service, Wife, Black, Female, 0, 0, 40, United-States, >50K 31, Private, 288419, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 207546, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 59, Local-gov, 147707, HS-grad, 9, Widowed, Farming-fishing, Unmarried, White, Male, 0, 2339, 40, United-States, <=50K 17, ?, 228373, 10th, 6, Never-married, ?, Own-child, White, Male, 0, 0, 30, United-States, <=50K 43, Private, 193882, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 40, United-States, >50K 38, Private, 31033, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 7298, 0, 40, United-States, >50K 37, Private, 272950, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 183523, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 238415, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 31, Private, 19302, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Male, 2202, 0, 38, United-States, <=50K 42, Local-gov, 339671, Bachelors, 13, Married-spouse-absent, Prof-specialty, Not-in-family, White, Female, 8614, 0, 45, United-States, >50K 35, Local-gov, 103260, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 35, United-States, >50K 39, Private, 79331, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 15024, 0, 40, United-States, >50K 40, Private, 135056, Assoc-acdm, 12, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 66, Private, 142723, 5th-6th, 3, Married-spouse-absent, Handlers-cleaners, Unmarried, White, Female, 0, 0, 40, Puerto-Rico, <=50K 30, Federal-gov, 188569, 9th, 5, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 57322, Assoc-acdm, 12, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 178309, 9th, 5, Never-married, Other-service, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 45, Private, 166107, Masters, 14, Never-married, Adm-clerical, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 31, Private, 53042, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, Trinadad&Tobago, <=50K 33, Private, 155343, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 3103, 0, 40, United-States, >50K 32, Private, 35595, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 429507, Assoc-acdm, 12, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, United-States, <=50K 50, Federal-gov, 159670, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 63, Private, 151210, 7th-8th, 4, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 186792, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 204640, Some-college, 10, Widowed, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 52, Private, 87205, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 38, Self-emp-inc, 112847, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, >50K 41, Private, 107306, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 2174, 0, 40, United-States, <=50K 50, State-gov, 211319, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 59, Private, 183606, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 205390, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 49, United-States, <=50K 73, Local-gov, 232871, 7th-8th, 4, Married-civ-spouse, Protective-serv, Husband, White, Male, 2228, 0, 10, United-States, <=50K 52, Self-emp-inc, 101017, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 38, United-States, <=50K 57, Private, 114495, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 35, Private, 183898, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 50, United-States, >50K 51, Private, 163921, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 56, United-States, >50K 22, Private, 311764, 11th, 7, Widowed, Sales, Own-child, Black, Female, 0, 0, 35, United-States, <=50K 49, Private, 188330, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 22, Private, 267174, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 46, Local-gov, 36228, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1902, 40, United-States, <=50K 48, Private, 199739, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 52, Private, 185407, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, ?, <=50K 43, State-gov, 206139, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, >50K 25, Private, 282063, 7th-8th, 4, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Mexico, <=50K 31, Private, 332379, 7th-8th, 4, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 418324, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 36, United-States, <=50K 19, ?, 263338, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 45, United-States, <=50K 51, Private, 158948, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 84, United-States, >50K 51, Private, 221532, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 40, United-States, >50K 22, Self-emp-not-inc, 202920, HS-grad, 9, Never-married, Prof-specialty, Unmarried, White, Female, 99999, 0, 40, Dominican-Republic, >50K 37, Local-gov, 118909, HS-grad, 9, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 19, Private, 286469, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 30, United-States, <=50K 45, Private, 191914, HS-grad, 9, Divorced, Transport-moving, Unmarried, White, Female, 0, 0, 55, United-States, <=50K 21, State-gov, 142766, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 10, United-States, <=50K 52, Private, 198744, HS-grad, 9, Widowed, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 46, Local-gov, 272780, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 24, United-States, <=50K 42, State-gov, 219553, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 56, Private, 261232, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 64292, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 58, Private, 312131, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 70, Private, 30713, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 30, United-States, <=50K 30, Private, 246439, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 338105, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 23, Private, 228243, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 44, United-States, <=50K 34, Local-gov, 62463, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1579, 40, United-States, <=50K 38, Private, 31603, Bachelors, 13, Married-civ-spouse, Craft-repair, Wife, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 165054, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 121618, 7th-8th, 4, Never-married, Transport-moving, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 45, Federal-gov, 273194, HS-grad, 9, Never-married, Transport-moving, Not-in-family, Black, Male, 3325, 0, 40, United-States, <=50K 21, ?, 163665, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 538319, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, Puerto-Rico, <=50K 34, Private, 238246, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 32, Self-emp-inc, 244665, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 5178, 0, 45, United-States, >50K 21, Private, 131811, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 63, ?, 231777, Masters, 14, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 30, United-States, <=50K 23, Private, 156807, 9th, 5, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 36, United-States, <=50K 28, Private, 236861, Bachelors, 13, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 29, Self-emp-not-inc, 229842, HS-grad, 9, Never-married, Transport-moving, Unmarried, Black, Male, 0, 0, 45, United-States, <=50K 25, Local-gov, 190057, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 44, State-gov, 55076, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 18, Private, 152545, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 8, United-States, <=50K 26, Private, 153434, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 24, United-States, <=50K 47, Local-gov, 171095, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 35, United-States, >50K 23, Private, 239322, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 138999, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, Local-gov, 95450, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 5178, 0, 50, United-States, >50K 25, Private, 176520, HS-grad, 9, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 38, Local-gov, 72338, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, Asian-Pac-Islander, Male, 0, 0, 54, United-States, >50K 60, ?, 386261, Bachelors, 13, Married-spouse-absent, ?, Unmarried, Black, Female, 0, 0, 15, United-States, <=50K 23, Private, 235722, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 36, Federal-gov, 128884, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 46, Private, 187226, 9th, 5, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 32, Self-emp-not-inc, 298332, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 40, Private, 173607, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 226756, HS-grad, 9, Never-married, Adm-clerical, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 31, Private, 157887, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 65, United-States, >50K 32, State-gov, 171111, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 37, United-States, <=50K 21, Private, 126314, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 10, United-States, <=50K 63, Private, 174018, Some-college, 10, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 40, United-States, >50K 44, Private, 144778, Some-college, 10, Separated, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 42, Self-emp-not-inc, 201522, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 23, ?, 22966, Bachelors, 13, Never-married, ?, Own-child, White, Male, 0, 0, 35, United-States, <=50K 30, Private, 399088, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 24, Private, 282202, HS-grad, 9, Never-married, Other-service, Unmarried, White, Male, 0, 0, 40, El-Salvador, <=50K 42, Private, 102606, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 44, Self-emp-not-inc, 246862, HS-grad, 9, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, Italy, >50K 27, Federal-gov, 508336, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, Black, Male, 0, 0, 48, United-States, <=50K 27, Local-gov, 263431, Some-college, 10, Never-married, Exec-managerial, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 235733, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 68, Private, 107910, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 55, Self-emp-not-inc, 184425, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 99, United-States, >50K 22, Self-emp-not-inc, 143062, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, Greece, <=50K 25, Private, 199545, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 15, United-States, <=50K 68, Self-emp-not-inc, 197015, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 45, United-States, <=50K 62, Private, 149617, Some-college, 10, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 16, United-States, <=50K 26, Private, 33610, HS-grad, 9, Divorced, Other-service, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 192002, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 68, Private, 67791, Some-college, 10, Widowed, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Local-gov, 445382, Bachelors, 13, Separated, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 45, Private, 112283, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, <=50K 26, Private, 157249, 11th, 7, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 109872, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, <=50K 23, Private, 119838, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 50, United-States, <=50K 29, Private, 149943, Some-college, 10, Never-married, Other-service, Not-in-family, Other, Male, 0, 1590, 40, ?, <=50K 65, Without-pay, 27012, 7th-8th, 4, Widowed, Farming-fishing, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 31, Private, 91666, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 26, Private, 270276, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 179271, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 44, Private, 161819, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 45, Local-gov, 339681, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 1506, 0, 45, United-States, <=50K 26, Self-emp-not-inc, 219897, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 26, Private, 91683, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 35, United-States, <=50K 36, Private, 188834, 9th, 5, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 38, Private, 187046, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 39, Private, 191807, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, White, Male, 0, 0, 48, United-States, <=50K 52, Self-emp-inc, 179951, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 324420, 1st-4th, 2, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, Mexico, <=50K 41, Self-emp-not-inc, 66632, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Local-gov, 121718, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 60, United-States, >50K 47, Private, 162034, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 70, United-States, <=50K 28, Local-gov, 218990, Assoc-voc, 11, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 46, United-States, <=50K 25, Local-gov, 125863, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 35, United-States, <=50K 35, Private, 225330, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 120426, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 119741, Masters, 14, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, >50K 44, Private, 32000, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 18, United-States, >50K 21, ?, 124242, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 278581, Bachelors, 13, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 230224, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 55, United-States, >50K 30, Private, 204374, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 1741, 48, United-States, <=50K 45, Private, 188386, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 1628, 45, United-States, <=50K 20, Private, 164922, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 195176, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 80, United-States, <=50K 43, Private, 166740, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 50, ?, 156008, 11th, 7, Married-civ-spouse, ?, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 28, Private, 162551, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Other-relative, Asian-Pac-Islander, Female, 0, 0, 48, China, <=50K 25, Private, 211231, HS-grad, 9, Married-civ-spouse, Tech-support, Other-relative, White, Female, 0, 0, 48, United-States, >50K 25, Private, 169990, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 90, Private, 221832, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 38, Local-gov, 255454, Bachelors, 13, Separated, Prof-specialty, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 35, Private, 28160, Bachelors, 13, Married-spouse-absent, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 50, State-gov, 159219, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, Canada, >50K 26, Local-gov, 103148, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 165186, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 45, United-States, <=50K 56, Private, 31782, 10th, 6, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Local-gov, 249101, HS-grad, 9, Divorced, Protective-serv, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 46, Private, 243190, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 7688, 0, 40, United-States, >50K 18, Local-gov, 153405, 11th, 7, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 25, United-States, <=50K 37, Private, 329980, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 2415, 60, United-States, >50K 57, Private, 176079, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, State-gov, 218542, HS-grad, 9, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 29, State-gov, 303446, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 25, Nicaragua, <=50K 40, Private, 102606, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 44, Self-emp-not-inc, 483201, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 77, Local-gov, 144608, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 6, United-States, <=50K 30, Private, 226013, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 21, Private, 165475, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 66, Private, 263637, 10th, 6, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 201495, 11th, 7, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 35, United-States, <=50K 68, Private, 213720, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 64, Private, 170483, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 26, Private, 214303, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 32, Private, 190511, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Private, 242150, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 38, United-States, <=50K 51, Local-gov, 159755, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 50, Private, 147629, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 45, United-States, >50K 49, Private, 268022, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 28, Private, 188711, Bachelors, 13, Never-married, Transport-moving, Unmarried, White, Male, 0, 0, 20, United-States, <=50K 29, Private, 452205, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 36, United-States, <=50K 21, Private, 260847, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 30, United-States, <=50K 28, Private, 291374, HS-grad, 9, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 55, Private, 189933, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Self-emp-not-inc, 133969, HS-grad, 9, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 0, 50, South, >50K 35, Private, 330664, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, ?, 672412, 11th, 7, Separated, ?, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 26, Private, 122999, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 8614, 0, 40, United-States, >50K 30, Private, 111415, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 55, Germany, <=50K 33, Private, 217235, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 20, United-States, <=50K 40, Private, 121956, Bachelors, 13, Married-spouse-absent, Prof-specialty, Not-in-family, Asian-Pac-Islander, Male, 13550, 0, 40, Cambodia, >50K 23, Private, 120172, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 343403, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 48, Self-emp-not-inc, 104790, 11th, 7, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, >50K 39, Local-gov, 473547, 10th, 6, Divorced, Handlers-cleaners, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 53, Local-gov, 260106, Prof-school, 15, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 49, Federal-gov, 168232, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 348491, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 36, Private, 24106, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 3103, 0, 40, United-States, >50K 60, Self-emp-inc, 197553, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 50, United-States, >50K 29, Private, 421065, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 54, Self-emp-inc, 138852, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 28, ?, 169631, Assoc-acdm, 12, Married-AF-spouse, ?, Wife, White, Female, 0, 0, 3, United-States, <=50K 34, Private, 379412, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 30, Private, 181992, Some-college, 10, Never-married, Sales, Not-in-family, Black, Female, 0, 0, 35, United-States, <=50K 19, Private, 365640, HS-grad, 9, Never-married, Priv-house-serv, Not-in-family, White, Female, 0, 0, 45, ?, <=50K 26, Private, 236564, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 363418, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 70, United-States, >50K 50, Private, 112351, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 38, United-States, <=50K 30, Private, 204704, Bachelors, 13, Never-married, Exec-managerial, Unmarried, White, Female, 0, 0, 45, United-States, >50K 44, Private, 54611, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 49, Private, 128132, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 75, Self-emp-not-inc, 30599, Masters, 14, Married-spouse-absent, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 37, Private, 379522, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, >50K 51, State-gov, 196504, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 38, United-States, <=50K 35, Private, 82552, HS-grad, 9, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 35, United-States, <=50K 28, Private, 104024, Some-college, 10, Never-married, Sales, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 66, Self-emp-not-inc, 293114, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 1409, 0, 40, United-States, <=50K 72, Private, 74141, 9th, 5, Married-civ-spouse, Exec-managerial, Wife, Asian-Pac-Islander, Female, 0, 0, 48, United-States, >50K 39, Private, 192337, Bachelors, 13, Separated, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 27, Private, 262478, HS-grad, 9, Never-married, Farming-fishing, Own-child, Black, Male, 0, 0, 30, United-States, <=50K 57, Private, 185072, Some-college, 10, Never-married, Adm-clerical, Other-relative, Black, Female, 0, 0, 40, Jamaica, <=50K 24, Private, 296045, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 2635, 0, 38, United-States, <=50K 28, Private, 246595, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 70, United-States, <=50K 23, Private, 54472, Some-college, 10, Married-spouse-absent, Other-service, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 31, Private, 331065, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 1408, 40, United-States, <=50K 23, Private, 161708, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 31, Private, 264936, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, Local-gov, 113545, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 212237, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1740, 45, United-States, <=50K 31, Private, 170430, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 80, ?, <=50K 34, Private, 173806, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 4865, 0, 60, United-States, <=50K 57, Federal-gov, 370890, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 2258, 40, United-States, <=50K 39, Private, 505119, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, Cuba, >50K 23, Private, 193089, 11th, 7, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 24, Local-gov, 33432, Assoc-acdm, 12, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 103110, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, England, <=50K 32, Private, 160362, Some-college, 10, Divorced, Other-service, Other-relative, White, Male, 0, 0, 40, Nicaragua, <=50K 35, Private, 204621, Assoc-acdm, 12, Divorced, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 35309, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, ?, 154373, Bachelors, 13, Never-married, ?, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 47, Private, 194772, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 154410, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Federal-gov, 220563, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, State-gov, 253354, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 32, Private, 211699, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 1485, 40, United-States, >50K 63, Self-emp-not-inc, 167501, Some-college, 10, Married-civ-spouse, Prof-specialty, Wife, White, Female, 20051, 0, 10, United-States, >50K 34, Private, 229732, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 185465, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 27, Private, 335764, 11th, 7, Married-civ-spouse, Sales, Own-child, Black, Male, 0, 0, 35, United-States, <=50K 23, Private, 460046, HS-grad, 9, Separated, Exec-managerial, Unmarried, White, Female, 0, 0, 42, United-States, <=50K 19, ?, 33487, Some-college, 10, Never-married, ?, Other-relative, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 50, Private, 176924, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 38, United-States, <=50K 49, State-gov, 213307, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 83893, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Private, 194102, Bachelors, 13, Never-married, Exec-managerial, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 238611, 7th-8th, 4, Widowed, Other-service, Unmarried, Black, Female, 0, 0, 38, United-States, <=50K 41, Private, 113597, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 16, United-States, <=50K 27, Self-emp-not-inc, 208406, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 53, Private, 274528, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 17, Self-emp-not-inc, 60116, 10th, 6, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 10, United-States, <=50K 23, ?, 196816, HS-grad, 9, Never-married, ?, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 53, Private, 166368, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 303954, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1848, 42, United-States, >50K 24, Private, 99386, Bachelors, 13, Married-spouse-absent, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 188569, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 53, Private, 302868, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 18, Private, 283342, 11th, 7, Never-married, Other-service, Other-relative, Black, Male, 0, 0, 20, United-States, <=50K 24, Private, 233777, Some-college, 10, Never-married, Sales, Unmarried, White, Male, 0, 0, 50, Mexico, <=50K 20, Private, 170038, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Local-gov, 261319, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, State-gov, 367237, Assoc-voc, 11, Never-married, Prof-specialty, Not-in-family, White, Male, 8614, 0, 40, United-States, >50K 34, Private, 126838, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 354104, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 30, United-States, <=50K 20, Private, 176321, 12th, 8, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, Mexico, <=50K 47, Private, 85129, HS-grad, 9, Divorced, Other-service, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 20, ?, 376474, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 32, United-States, <=50K 22, Private, 62507, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 42, Local-gov, 111252, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 40, United-States, >50K 60, Private, 156889, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 549430, HS-grad, 9, Never-married, Priv-house-serv, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 46, Private, 29696, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 66, Private, 98837, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 86150, Bachelors, 13, Married-civ-spouse, Other-service, Wife, Asian-Pac-Islander, Female, 0, 0, 30, United-States, >50K 34, Private, 204991, Some-college, 10, Divorced, Exec-managerial, Own-child, White, Male, 0, 0, 44, United-States, <=50K 45, Private, 371886, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 46, United-States, <=50K 35, Private, 103605, 11th, 7, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 63, ?, 54851, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Local-gov, 133050, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, United-States, >50K 36, Local-gov, 126569, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Federal-gov, 144259, HS-grad, 9, Never-married, Adm-clerical, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 51, Private, 161482, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 25, Self-emp-not-inc, 305449, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 125010, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 45, United-States, <=50K 47, Private, 304133, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 59, Local-gov, 120617, HS-grad, 9, Separated, Protective-serv, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 34, Private, 157747, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Private, 297396, Some-college, 10, Separated, Exec-managerial, Unmarried, White, Female, 0, 0, 60, United-States, <=50K 42, Private, 121287, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 28, ?, 308493, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 17, Honduras, <=50K 37, Private, 49115, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 51, Self-emp-inc, 208302, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 38, United-States, >50K 25, Private, 304032, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 36, United-States, <=50K 31, Federal-gov, 207301, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 37, Private, 123211, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 44, United-States, >50K 42, Private, 33521, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 29, ?, 410351, Bachelors, 13, Never-married, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 410034, Some-college, 10, Divorced, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 51, Private, 175339, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 47, United-States, >50K 22, ?, 27937, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 36, United-States, <=50K 49, Private, 168211, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1485, 40, United-States, >50K 26, Private, 125680, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 16, Japan, <=50K 56, Local-gov, 160829, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 46, United-States, <=50K 52, Private, 266529, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 61, Self-emp-not-inc, 115023, Masters, 14, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 4, ?, <=50K 47, State-gov, 224149, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 52, Private, 150930, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 343699, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 43, Self-emp-inc, 172826, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 99999, 0, 55, United-States, >50K 35, Private, 163392, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, Asian-Pac-Islander, Male, 0, 0, 40, ?, <=50K 17, ?, 103810, 12th, 8, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 213821, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1887, 40, United-States, >50K 26, Private, 211265, Some-college, 10, Married-spouse-absent, Craft-repair, Other-relative, Black, Female, 0, 0, 35, Dominican-Republic, <=50K 58, Local-gov, 160586, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 66, Private, 146454, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 5556, 0, 40, United-States, >50K 30, Private, 203277, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 60, United-States, >50K 46, Private, 309895, Some-college, 10, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 26522, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 1902, 35, United-States, >50K 57, Private, 103809, HS-grad, 9, Never-married, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 90291, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 21, State-gov, 181761, Some-college, 10, Never-married, Tech-support, Own-child, White, Female, 0, 0, 10, United-States, <=50K 37, Private, 35330, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 1669, 55, United-States, <=50K 45, Local-gov, 135776, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 61, ?, 188172, Doctorate, 16, Widowed, ?, Not-in-family, White, Female, 0, 0, 5, United-States, <=50K 39, Private, 179579, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 193626, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 53, United-States, <=50K 20, Private, 108887, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 199070, HS-grad, 9, Never-married, Protective-serv, Own-child, Black, Male, 0, 0, 16, United-States, <=50K 25, Private, 441591, Bachelors, 13, Never-married, Tech-support, Own-child, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 185254, 5th-6th, 3, Never-married, Priv-house-serv, Own-child, White, Female, 0, 0, 40, El-Salvador, <=50K 24, Private, 109307, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 45, United-States, <=50K 20, ?, 81853, Some-college, 10, Never-married, ?, Own-child, Asian-Pac-Islander, Female, 0, 0, 15, United-States, <=50K 35, Private, 23621, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 44, Local-gov, 145178, HS-grad, 9, Married-civ-spouse, Other-service, Wife, Black, Female, 0, 0, 38, Jamaica, >50K 47, State-gov, 30575, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 28, State-gov, 130620, 11th, 7, Separated, Adm-clerical, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, India, <=50K 41, Local-gov, 22155, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 60, United-States, <=50K 31, Private, 106437, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 79787, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 47, Private, 326857, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 5013, 0, 40, United-States, <=50K 44, Private, 81853, HS-grad, 9, Never-married, Sales, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 61, Private, 120933, Some-college, 10, Never-married, Priv-house-serv, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Federal-gov, 153143, Some-college, 10, Divorced, Adm-clerical, Other-relative, White, Female, 0, 0, 40, Puerto-Rico, <=50K 46, Private, 27669, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 28, United-States, <=50K 46, Private, 105444, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 54, Local-gov, 169785, Masters, 14, Widowed, Prof-specialty, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 49, Private, 122493, HS-grad, 9, Widowed, Tech-support, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 56, Local-gov, 242670, Some-college, 10, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 52, Private, 54933, Masters, 14, Divorced, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 209317, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, Puerto-Rico, <=50K 25, Self-emp-not-inc, 282631, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 98044, 11th, 7, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 58, Private, 187487, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, State-gov, 60186, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 75648, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, <=50K 28, Private, 201175, 11th, 7, Never-married, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 30, Private, 19302, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 21, ?, 300812, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 30, United-States, <=50K 44, Private, 146659, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1887, 35, United-States, >50K 75, Private, 101887, 10th, 6, Widowed, Priv-house-serv, Not-in-family, White, Female, 0, 0, 70, United-States, <=50K 66, ?, 117778, 11th, 7, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 60726, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 33, Self-emp-inc, 201763, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 57, Self-emp-inc, 119253, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 65, United-States, >50K 47, Self-emp-not-inc, 121124, 5th-6th, 3, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, Italy, >50K 41, Private, 220132, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 40, United-States, >50K 21, Private, 60639, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 37, United-States, <=50K 17, Private, 195262, 11th, 7, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 17, United-States, <=50K 61, ?, 113544, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 55, United-States, <=50K 47, ?, 331650, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 8, United-States, >50K 22, Private, 100587, Some-college, 10, Never-married, Other-service, Own-child, Black, Female, 0, 0, 15, United-States, <=50K 47, Private, 298130, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 242391, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Self-emp-not-inc, 197867, Assoc-voc, 11, Divorced, Sales, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 59, Private, 151977, 10th, 6, Separated, Priv-house-serv, Not-in-family, Black, Female, 0, 0, 30, United-States, <=50K 38, Private, 277347, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 33, Private, 125249, HS-grad, 9, Separated, Protective-serv, Own-child, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 222142, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 270194, 9th, 5, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 169995, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 48, United-States, <=50K 27, Private, 359155, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 60, Private, 123992, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 64, Local-gov, 266080, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 37, Private, 201531, Assoc-acdm, 12, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 54, Self-emp-not-inc, 179704, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 36, Private, 393673, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 50, United-States, >50K 34, Private, 244147, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, ?, >50K 41, Self-emp-not-inc, 438696, Masters, 14, Divorced, Sales, Unmarried, White, Male, 0, 0, 5, United-States, >50K 35, Self-emp-not-inc, 207568, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 75, United-States, <=50K 63, Self-emp-inc, 54052, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 68, United-States, >50K 46, Private, 187581, HS-grad, 9, Divorced, Craft-repair, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 47, Self-emp-not-inc, 77102, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 353010, Bachelors, 13, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 29, Private, 54131, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 74, Federal-gov, 39890, Some-college, 10, Widowed, Transport-moving, Not-in-family, White, Female, 0, 0, 18, United-States, <=50K 50, Private, 156877, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 70, United-States, >50K 22, Private, 355686, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 48, Private, 300168, 12th, 8, Separated, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 30, Private, 488720, 9th, 5, Married-civ-spouse, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 32, Private, 157287, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 184659, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 214169, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Private, 192149, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 50, Private, 137253, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 44, Private, 373050, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 65, Private, 90377, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 6767, 0, 60, United-States, <=50K 28, Federal-gov, 183151, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 60, United-States, <=50K 55, Private, 227158, Bachelors, 13, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 49, Local-gov, 34021, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 50, United-States, <=50K 31, Private, 165148, HS-grad, 9, Separated, Exec-managerial, Unmarried, White, Female, 0, 0, 12, United-States, <=50K 47, Private, 211668, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, Black, Female, 0, 0, 40, United-States, >50K 45, Private, 358886, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 47707, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 34, Self-emp-not-inc, 306982, Bachelors, 13, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 0, 60, South, <=50K 49, Local-gov, 52590, HS-grad, 9, Widowed, Protective-serv, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 39, ?, 179352, Some-college, 10, Divorced, ?, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 27, Private, 158156, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 42, United-States, <=50K 42, Private, 70055, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 60, ?, 131852, 5th-6th, 3, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 30, United-States, >50K 64, Self-emp-not-inc, 177825, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 1055, 0, 40, United-States, <=50K 33, Private, 127215, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 48, United-States, >50K 23, Private, 175183, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 142287, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 34, Private, 221324, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 53, Private, 227602, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 37, Mexico, <=50K 22, Private, 228452, 10th, 6, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 57, State-gov, 39380, HS-grad, 9, Separated, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 20, ?, 96862, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 8, United-States, <=50K 23, Private, 336360, 7th-8th, 4, Never-married, Craft-repair, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 31, Private, 257644, 11th, 7, Never-married, Transport-moving, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 23, State-gov, 235853, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 22, United-States, <=50K 30, Private, 270577, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 32, Local-gov, 222900, Bachelors, 13, Separated, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 42, Private, 99254, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 0, 40, United-States, >50K 51, Private, 224763, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, Cuba, <=50K 59, Self-emp-not-inc, 174056, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 40, United-States, >50K 36, Private, 127306, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 339506, HS-grad, 9, Never-married, Sales, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 35, Private, 178322, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, Germany, >50K 33, Private, 189843, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 160815, Assoc-voc, 11, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 60, Private, 207665, HS-grad, 9, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 40, United-States, >50K 37, State-gov, 160402, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 35, Private, 170263, Some-college, 10, Never-married, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 184659, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 52, United-States, <=50K 38, Federal-gov, 338320, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 50, United-States, >50K 54, Private, 101017, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 204322, Assoc-voc, 11, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, >50K 45, Private, 241350, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 63, Federal-gov, 217994, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 128143, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 58, Self-emp-not-inc, 164065, Masters, 14, Divorced, Sales, Not-in-family, White, Male, 0, 0, 18, United-States, <=50K 64, Local-gov, 78866, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 236769, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 44, Federal-gov, 239539, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, >50K 39, Private, 34028, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 48, United-States, <=50K 45, State-gov, 207847, Some-college, 10, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 175935, Doctorate, 16, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 55, United-States, >50K 22, Federal-gov, 218445, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 63, Self-emp-inc, 215833, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 156976, Assoc-voc, 11, Separated, Other-service, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 42, Self-emp-not-inc, 220647, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 45, United-States, <=50K 20, Private, 218343, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 29, Private, 241431, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 7298, 0, 40, United-States, >50K 38, Local-gov, 123983, Bachelors, 13, Never-married, Exec-managerial, Unmarried, Asian-Pac-Islander, Male, 0, 1741, 40, Vietnam, <=50K 25, Private, 73289, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 408623, Bachelors, 13, Married-civ-spouse, Craft-repair, Other-relative, White, Male, 0, 0, 50, United-States, <=50K 46, Private, 169180, Assoc-voc, 11, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 54929, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 24, Private, 306779, Assoc-voc, 11, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 35, United-States, <=50K 43, Private, 159549, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 23, Private, 482082, 12th, 8, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 21, Mexico, <=50K 32, Local-gov, 286101, HS-grad, 9, Never-married, Transport-moving, Unmarried, Black, Female, 0, 0, 37, United-States, <=50K 44, Private, 167955, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Poland, <=50K 40, Self-emp-not-inc, 209040, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 105017, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 27776, Assoc-voc, 11, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 242941, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 1602, 10, United-States, <=50K 41, Private, 118853, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 119565, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 196827, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 1902, 40, United-States, <=50K 47, Private, 275361, Assoc-acdm, 12, Widowed, Other-service, Own-child, White, Female, 0, 0, 35, United-States, <=50K 42, Private, 225193, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 329783, 10th, 6, Never-married, Sales, Other-relative, White, Female, 0, 0, 10, United-States, <=50K 29, Local-gov, 107411, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 70, United-States, <=50K 21, State-gov, 258490, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 18, ?, 120243, 11th, 7, Never-married, ?, Own-child, White, Male, 0, 0, 27, United-States, <=50K 31, Private, 219509, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Mexico, >50K 27, Local-gov, 29174, Bachelors, 13, Never-married, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 40083, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, Canada, <=50K 23, Private, 87528, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 41, Private, 116379, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 55, Taiwan, >50K 46, Local-gov, 216214, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, >50K 34, Private, 268051, Some-college, 10, Married-civ-spouse, Protective-serv, Other-relative, Black, Female, 0, 0, 25, Haiti, <=50K 42, Self-emp-not-inc, 121718, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 24, United-States, <=50K 18, Private, 201901, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 1719, 15, United-States, <=50K 46, Private, 109089, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 37, United-States, <=50K 18, ?, 346382, 11th, 7, Never-married, ?, Own-child, White, Male, 0, 0, 15, United-States, <=50K 52, Private, 284129, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 56, Private, 143030, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 212619, Assoc-voc, 11, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 22, Self-emp-not-inc, 199011, HS-grad, 9, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 20, United-States, <=50K 31, Private, 118901, Bachelors, 13, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 41, Self-emp-not-inc, 129865, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 60, United-States, <=50K 25, Private, 157900, Some-college, 10, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 43, Self-emp-not-inc, 349341, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 45, Private, 158685, HS-grad, 9, Separated, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 386585, Some-college, 10, Divorced, Tech-support, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 90, Private, 52386, Some-college, 10, Never-married, Other-service, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 35, United-States, <=50K 45, Private, 246891, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 1902, 40, United-States, >50K 30, Private, 190385, Bachelors, 13, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, >50K 42, Private, 37869, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 217807, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 35, United-States, <=50K 53, Private, 149784, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 40, United-States, >50K 64, State-gov, 201293, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 56, Private, 128764, 7th-8th, 4, Widowed, Transport-moving, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 42, Private, 27444, Some-college, 10, Married-spouse-absent, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 26, Private, 62438, Bachelors, 13, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, >50K 31, Local-gov, 151726, Assoc-acdm, 12, Never-married, Adm-clerical, Own-child, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 40, Private, 29841, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 58, Private, 131608, Some-college, 10, Widowed, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 110562, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, Self-emp-inc, 190541, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 47, United-States, <=50K 62, State-gov, 33142, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 65, Self-emp-inc, 139272, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 99999, 0, 60, United-States, >50K 40, Private, 234633, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 45, Local-gov, 238386, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 22, Private, 460835, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 55, United-States, <=50K 23, ?, 243190, Some-college, 10, Never-married, ?, Own-child, Asian-Pac-Islander, Male, 0, 0, 20, China, <=50K 63, Federal-gov, 97855, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 39, Private, 77146, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1887, 50, United-States, >50K 37, Private, 200863, Some-college, 10, Widowed, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 25, ?, 41107, Bachelors, 13, Married-spouse-absent, ?, Not-in-family, White, Male, 0, 0, 40, Canada, <=50K 56, Private, 77415, 11th, 7, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 32, Private, 236770, Some-college, 10, Divorced, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 53, Federal-gov, 173093, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, Asian-Pac-Islander, Female, 0, 1887, 40, Philippines, >50K 32, Private, 235124, Assoc-voc, 11, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Self-emp-not-inc, 282604, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 7688, 0, 60, United-States, >50K 35, Private, 199288, 11th, 7, Separated, Transport-moving, Not-in-family, White, Male, 0, 0, 90, United-States, <=50K 51, Private, 191659, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1887, 65, United-States, >50K 19, Private, 43285, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 41, Private, 160837, 11th, 7, Married-spouse-absent, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, Guatemala, <=50K 22, Private, 230574, 10th, 6, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 25, United-States, <=50K 23, Private, 176178, HS-grad, 9, Never-married, Tech-support, Own-child, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 116358, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Taiwan, >50K 27, ?, 253873, Some-college, 10, Divorced, ?, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 45, Private, 107787, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Canada, <=50K 23, Self-emp-not-inc, 519627, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 25, Mexico, <=50K 21, Private, 191460, 11th, 7, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 44, Private, 198282, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 40, United-States, >50K 29, Private, 214858, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Self-emp-not-inc, 64875, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 60, United-States, <=50K 18, Private, 675421, 9th, 5, Never-married, Handlers-cleaners, Own-child, White, Male, 594, 0, 40, United-States, <=50K 62, Self-emp-not-inc, 134768, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Federal-gov, 207342, Some-college, 10, Never-married, Exec-managerial, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 34, Private, 64830, Assoc-acdm, 12, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 31, Private, 220066, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 14344, 0, 50, United-States, >50K 37, Private, 82521, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 40, United-States, >50K 33, Private, 176711, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, England, <=50K 22, ?, 217421, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 30, United-States, <=50K 28, Private, 111900, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 30, United-States, <=50K 22, ?, 196943, Some-college, 10, Separated, ?, Own-child, White, Male, 0, 0, 25, United-States, <=50K 47, Private, 481987, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, >50K 67, ?, 184506, 11th, 7, Married-civ-spouse, ?, Husband, White, Male, 0, 419, 3, United-States, <=50K 20, ?, 121313, 10th, 6, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 158420, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 70, United-States, <=50K 26, Private, 256000, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 60, United-States, >50K 36, Private, 183892, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 44, United-States, >50K 28, Private, 42734, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 181773, HS-grad, 9, Never-married, Transport-moving, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 47, Private, 184945, Some-college, 10, Separated, Other-service, Not-in-family, Black, Female, 0, 0, 35, United-States, <=50K 33, Private, 107248, Assoc-voc, 11, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 34, Self-emp-inc, 215382, Masters, 14, Separated, Prof-specialty, Not-in-family, White, Female, 4787, 0, 40, United-States, >50K 25, Private, 122999, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 758700, 9th, 5, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 3781, 0, 50, Mexico, <=50K 36, State-gov, 166606, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, Local-gov, 192060, Bachelors, 13, Separated, Prof-specialty, Not-in-family, White, Male, 0, 0, 30, ?, <=50K 74, ?, 340939, 9th, 5, Married-civ-spouse, ?, Husband, White, Male, 3471, 0, 40, United-States, <=50K 57, Private, 205708, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Poland, <=50K 55, Private, 67450, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, England, <=50K 20, Private, 242077, HS-grad, 9, Divorced, Sales, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 43, Private, 129573, HS-grad, 9, Never-married, Sales, Not-in-family, Black, Female, 0, 0, 44, United-States, <=50K 54, Private, 181132, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, England, >50K 25, Private, 212302, Some-college, 10, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 83411, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 1408, 40, United-States, <=50K 23, ?, 148751, Some-college, 10, Never-married, ?, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 17, Private, 317681, 11th, 7, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 10, United-States, <=50K 39, ?, 103986, HS-grad, 9, Never-married, ?, Not-in-family, White, Male, 0, 1590, 40, United-States, <=50K 63, Private, 30602, 7th-8th, 4, Married-spouse-absent, Other-service, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 19, Private, 172893, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 30, United-States, <=50K 56, Self-emp-inc, 211804, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 50, United-States, >50K 33, Self-emp-not-inc, 312055, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 37, Private, 65390, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 27, Private, 200500, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 36, Local-gov, 241962, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Self-emp-inc, 78530, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 65, Canada, >50K 22, Private, 189950, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 35, Private, 111387, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 1579, 40, United-States, <=50K 20, Private, 241951, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 18, Private, 343059, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 302465, 12th, 8, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 1741, 40, United-States, <=50K 53, Private, 156843, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 1564, 54, United-States, >50K 21, ?, 79728, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 55284, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 35, United-States, <=50K 34, Private, 509364, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 32, State-gov, 117927, Some-college, 10, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 20, Private, 137651, Some-college, 10, Never-married, Machine-op-inspct, Own-child, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 70, Private, 131060, 7th-8th, 4, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 25, United-States, <=50K 57, Private, 346963, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 54, Private, 183611, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 3137, 0, 50, United-States, <=50K 34, Private, 134737, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 36503, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Private, 250121, 11th, 7, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 330535, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 3325, 0, 40, United-States, <=50K 27, Private, 387776, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 41474, 10th, 6, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Mexico, <=50K 36, Local-gov, 318972, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 65, United-States, <=50K 33, Private, 86143, Some-college, 10, Never-married, Exec-managerial, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 50, Private, 181139, Some-college, 10, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 326232, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Male, 0, 2547, 50, United-States, >50K 39, Local-gov, 153976, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 55, Self-emp-not-inc, 59469, 9th, 5, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 25, United-States, <=50K 24, Private, 127139, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 136343, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Self-emp-not-inc, 350624, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 66, ?, 177351, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 2174, 40, United-States, >50K 68, Private, 166149, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 2206, 30, United-States, <=50K 29, Private, 121523, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 24, Self-emp-not-inc, 267396, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 83045, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 160449, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 44, United-States, >50K 55, Self-emp-inc, 124137, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 2415, 35, Greece, >50K 20, ?, 287681, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 36, United-States, <=50K 41, Private, 154194, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 36, Self-emp-not-inc, 295127, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 84, United-States, <=50K 60, Private, 240521, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 40, United-States, >50K 61, Self-emp-not-inc, 244087, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 52, United-States, >50K 35, Private, 356250, Prof-school, 15, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 0, 35, China, <=50K 42, State-gov, 293791, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 26, Private, 44308, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Local-gov, 210527, Some-college, 10, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 31, State-gov, 151763, Masters, 14, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 39, State-gov, 267581, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 20, Private, 100188, Some-college, 10, Never-married, Tech-support, Own-child, White, Female, 0, 0, 24, United-States, <=50K 32, Self-emp-inc, 111746, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Self-emp-not-inc, 171091, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 355645, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 20, Trinadad&Tobago, <=50K 54, Local-gov, 137678, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 70894, Assoc-acdm, 12, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 171306, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 3, United-States, <=50K 31, Private, 100997, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 35, Private, 63921, 5th-6th, 3, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Mexico, <=50K 29, Private, 32897, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 29, Local-gov, 251854, HS-grad, 9, Never-married, Protective-serv, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 25, Private, 345121, 10th, 6, Separated, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 46, Private, 86220, Bachelors, 13, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 172845, Assoc-voc, 11, Never-married, Other-service, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 20, Private, 171398, 10th, 6, Never-married, Sales, Not-in-family, Other, Male, 0, 0, 40, United-States, <=50K 24, Self-emp-not-inc, 174391, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 48, Private, 207058, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 37, United-States, <=50K 37, Private, 291251, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 60, Self-emp-not-inc, 224377, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 105813, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Local-gov, 180916, Some-college, 10, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 31, Self-emp-not-inc, 122749, Assoc-voc, 11, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 20, United-States, <=50K 38, Private, 31069, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 4386, 0, 40, United-States, >50K 26, Self-emp-not-inc, 284343, Assoc-acdm, 12, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 64, Private, 319371, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 40, United-States, >50K 46, Private, 174224, Assoc-voc, 11, Divorced, Protective-serv, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 69, ?, 183958, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 8, United-States, <=50K 39, Private, 127772, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 3103, 0, 44, United-States, >50K 48, Private, 80651, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 46, Private, 62793, HS-grad, 9, Divorced, Sales, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 191712, Bachelors, 13, Divorced, Sales, Not-in-family, White, Male, 0, 1590, 40, United-States, <=50K 39, Self-emp-not-inc, 237532, HS-grad, 9, Married-civ-spouse, Sales, Wife, Black, Female, 0, 0, 54, Dominican-Republic, >50K 50, Federal-gov, 20179, Masters, 14, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 24, Private, 311376, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 432565, Assoc-voc, 11, Married-civ-spouse, Tech-support, Other-relative, White, Female, 0, 0, 40, Canada, >50K 39, Self-emp-inc, 329980, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 2415, 60, United-States, >50K 29, Self-emp-not-inc, 125190, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 342946, 11th, 7, Never-married, Transport-moving, Own-child, White, Female, 0, 0, 38, United-States, <=50K 21, ?, 219835, Assoc-voc, 11, Never-married, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 123429, 10th, 6, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 69, Self-emp-inc, 69209, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 3818, 0, 30, United-States, <=50K 55, Private, 66356, HS-grad, 9, Separated, Handlers-cleaners, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 195897, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 44, Self-emp-inc, 153132, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 52, United-States, >50K 18, Private, 230875, 11th, 7, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 74, Self-emp-not-inc, 92298, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 10, United-States, <=50K 40, Private, 185145, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 297296, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 75, ?, 164849, 9th, 5, Married-civ-spouse, ?, Husband, Black, Male, 1409, 0, 5, United-States, <=50K 55, Private, 145214, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 52, Self-emp-not-inc, 242341, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 54, Private, 240542, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 0, 48, United-States, <=50K 36, Private, 104772, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 48, United-States, <=50K 76, ?, 152802, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 8, United-States, <=50K 26, Private, 181666, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 415520, 11th, 7, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 20, United-States, <=50K 38, Private, 258761, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 50, Private, 88842, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 7298, 0, 40, United-States, >50K 19, ?, 356717, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 25, United-States, <=50K 32, Private, 158438, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 57, Private, 206206, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Private, 51816, HS-grad, 9, Never-married, Protective-serv, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 27, Private, 253814, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Self-emp-not-inc, 161745, Bachelors, 13, Married-spouse-absent, Exec-managerial, Not-in-family, White, Male, 0, 1980, 60, United-States, <=50K 60, Private, 162947, 5th-6th, 3, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, Puerto-Rico, <=50K 52, Private, 163027, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 61, Private, 146788, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 57, Self-emp-not-inc, 73309, HS-grad, 9, Widowed, Craft-repair, Not-in-family, White, Male, 0, 0, 55, United-States, >50K 19, ?, 143867, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 59, Self-emp-not-inc, 104216, Prof-school, 15, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 25, United-States, <=50K 34, Self-emp-not-inc, 345705, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 31, Private, 133770, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 50, United-States, >50K 42, Private, 209392, HS-grad, 9, Divorced, Protective-serv, Not-in-family, Black, Male, 0, 0, 35, United-States, <=50K 70, Private, 262345, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 6, United-States, <=50K 47, Private, 277545, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 0, 40, ?, >50K 47, ?, 174525, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 3942, 0, 40, ?, <=50K 29, Private, 490332, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, >50K 27, Private, 211570, 11th, 7, Never-married, Handlers-cleaners, Other-relative, Black, Male, 0, 0, 40, United-States, <=50K 25, Private, 374918, 12th, 8, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 106728, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 5178, 0, 60, United-States, >50K 28, Private, 173649, HS-grad, 9, Never-married, Other-service, Own-child, Black, Female, 0, 0, 40, ?, <=50K 35, Private, 174597, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Self-emp-not-inc, 233533, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, >50K 54, ?, 169785, Masters, 14, Never-married, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 133169, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 198824, Assoc-voc, 11, Separated, Other-service, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 65, Private, 174056, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 188696, Assoc-voc, 11, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Local-gov, 90692, HS-grad, 9, Divorced, Prof-specialty, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 34, Private, 271933, Bachelors, 13, Never-married, Exec-managerial, Other-relative, White, Female, 0, 1741, 45, United-States, <=50K 47, Self-emp-not-inc, 102359, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 30, United-States, <=50K 49, Federal-gov, 213668, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 56, United-States, >50K 21, Private, 294789, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 20, Private, 157599, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 18, Local-gov, 134935, 12th, 8, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 466224, Some-college, 10, Never-married, Sales, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 34, Self-emp-not-inc, 111985, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 38, Private, 264627, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 213427, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 279015, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 47, Private, 165937, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, >50K 27, Federal-gov, 188343, HS-grad, 9, Separated, Exec-managerial, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 63, Private, 158609, Assoc-voc, 11, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 8, United-States, <=50K 34, Private, 193036, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, >50K 25, Private, 198632, Some-college, 10, Married-spouse-absent, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 54, Private, 175912, HS-grad, 9, Widowed, Machine-op-inspct, Unmarried, White, Male, 914, 0, 40, United-States, <=50K 19, ?, 192773, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 35, United-States, <=50K 35, Private, 101387, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 24, Private, 60783, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 70, United-States, >50K 26, Private, 183224, Some-college, 10, Never-married, Adm-clerical, Own-child, Asian-Pac-Islander, Female, 0, 0, 35, United-States, <=50K 59, Local-gov, 100776, Assoc-voc, 11, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 57600, Doctorate, 16, Married-spouse-absent, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, ?, <=50K 20, Private, 174063, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 306495, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 249741, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 93021, HS-grad, 9, Never-married, Adm-clerical, Unmarried, Other, Female, 0, 0, 40, United-States, <=50K 36, Private, 49626, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 63062, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 60, United-States, <=50K 55, Private, 320835, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 22, Local-gov, 123727, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 21, United-States, <=50K 58, State-gov, 110517, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 4064, 0, 40, India, <=50K 43, Private, 149670, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 4064, 0, 15, United-States, <=50K 39, Private, 172425, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 20, United-States, >50K 40, Private, 216116, 9th, 5, Never-married, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, Haiti, <=50K 46, Private, 174209, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 54, Federal-gov, 175083, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 19, Private, 129059, Some-college, 10, Never-married, Sales, Own-child, Black, Male, 0, 0, 30, United-States, <=50K 24, Private, 121313, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 53, ?, 181317, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, State-gov, 166851, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 13, United-States, <=50K 29, Self-emp-not-inc, 29616, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 65, United-States, <=50K 56, Self-emp-inc, 105582, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 50, United-States, >50K 54, ?, 124993, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, >50K 21, ?, 148509, Some-college, 10, Never-married, ?, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 34, Private, 230246, 9th, 5, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 40, ?, <=50K 56, Private, 117881, 11th, 7, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 203408, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 50, United-States, >50K 19, Private, 446219, 10th, 6, Never-married, Sales, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 32, Self-emp-inc, 110331, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 65, United-States, >50K 48, Private, 207946, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 52, United-States, <=50K 67, ?, 45537, Masters, 14, Married-civ-spouse, ?, Husband, Black, Male, 0, 0, 40, United-States, >50K 47, Private, 188330, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 25, United-States, <=50K 52, Private, 147629, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, >50K 40, Private, 153799, 1st-4th, 2, Married-spouse-absent, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, Dominican-Republic, <=50K 28, Private, 203776, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 41, Private, 168071, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 50, United-States, >50K 57, Private, 348430, 1st-4th, 2, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, Portugal, <=50K 51, Private, 103407, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, ?, 152046, 11th, 7, Never-married, ?, Not-in-family, White, Female, 0, 0, 35, Germany, <=50K 36, Private, 153205, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 45, ?, <=50K 33, Private, 326104, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 46, Private, 238162, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 50, Private, 221336, HS-grad, 9, Divorced, Adm-clerical, Other-relative, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 33, Private, 180656, Some-college, 10, Married-spouse-absent, Craft-repair, Not-in-family, White, Male, 0, 0, 40, ?, <=50K 77, Self-emp-not-inc, 145329, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 401, 0, 20, United-States, <=50K 39, Private, 315776, Masters, 14, Never-married, Exec-managerial, Not-in-family, Black, Male, 8614, 0, 52, United-States, >50K 67, ?, 150516, HS-grad, 9, Widowed, ?, Unmarried, White, Male, 0, 0, 3, United-States, <=50K 35, Private, 325802, Assoc-acdm, 12, Divorced, Handlers-cleaners, Unmarried, White, Female, 0, 0, 24, United-States, <=50K 23, Private, 133985, 10th, 6, Never-married, Craft-repair, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 37, Private, 269329, Assoc-voc, 11, Divorced, Prof-specialty, Not-in-family, White, Female, 8614, 0, 45, United-States, >50K 41, Private, 183203, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 60, Private, 76127, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 35, United-States, >50K 32, Private, 195891, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 56, Federal-gov, 162137, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 45, State-gov, 37672, Assoc-voc, 11, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 161708, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, >50K 18, Private, 80616, 10th, 6, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 27, United-States, <=50K 31, Private, 209276, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Other, Male, 0, 0, 40, United-States, <=50K 21, ?, 34443, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 50, United-States, <=50K 45, Private, 192835, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 55, United-States, >50K 23, Private, 203240, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, State-gov, 102308, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 40829, 11th, 7, Never-married, Sales, Other-relative, Amer-Indian-Eskimo, Female, 0, 0, 25, United-States, <=50K 25, Private, 60726, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 30, United-States, <=50K 31, State-gov, 116677, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 57067, HS-grad, 9, Never-married, Machine-op-inspct, Other-relative, White, Male, 0, 0, 45, United-States, <=50K 41, Private, 304906, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 74, Private, 101590, Prof-school, 15, Widowed, Adm-clerical, Not-in-family, Black, Female, 0, 0, 20, United-States, <=50K 27, Private, 258102, 5th-6th, 3, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 23, Private, 241185, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 124827, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Self-emp-inc, 76625, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Federal-gov, 263339, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Private, 135645, Masters, 14, Never-married, Sales, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 42, Private, 245626, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Amer-Indian-Eskimo, Male, 0, 0, 60, United-States, <=50K 24, Private, 210781, Bachelors, 13, Never-married, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 235786, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 45, Self-emp-not-inc, 160167, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 70, United-States, <=50K 52, Federal-gov, 30731, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 40, United-States, >50K 34, Private, 314375, Assoc-voc, 11, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 81528, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 60, United-States, <=50K 54, Private, 182854, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 42, Federal-gov, 296798, 11th, 7, Never-married, Tech-support, Not-in-family, White, Male, 0, 1340, 40, United-States, <=50K 32, Private, 194426, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 15024, 0, 40, United-States, >50K 40, ?, 70645, Some-college, 10, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 20, United-States, <=50K 55, Self-emp-inc, 141807, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 66, ?, 112871, 11th, 7, Never-married, ?, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 52, State-gov, 71344, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, State-gov, 341410, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 33, Private, 118941, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 52, ?, 159755, Assoc-voc, 11, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 50, United-States, >50K 28, Private, 128509, 5th-6th, 3, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, ?, <=50K 27, Self-emp-not-inc, 229125, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Local-gov, 142756, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 27, Self-emp-inc, 243871, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 45, United-States, <=50K 47, Private, 213140, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 7688, 0, 40, United-States, >50K 19, Private, 196857, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 138626, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Self-emp-not-inc, 161334, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 25, Nicaragua, <=50K 50, Private, 273536, 7th-8th, 4, Married-civ-spouse, Sales, Husband, Other, Male, 0, 0, 49, Dominican-Republic, <=50K 32, Private, 115631, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 4101, 0, 50, United-States, <=50K 28, Private, 185957, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 334357, HS-grad, 9, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 43, Private, 96102, Masters, 14, Married-spouse-absent, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 34, Private, 213226, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, Iran, >50K 19, Private, 115248, Some-college, 10, Never-married, Adm-clerical, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, Vietnam, <=50K 37, Private, 185061, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 55, United-States, <=50K 27, Private, 147638, Bachelors, 13, Never-married, Adm-clerical, Other-relative, Asian-Pac-Islander, Female, 0, 0, 40, Hong, <=50K 18, Private, 280298, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 24, United-States, <=50K 31, Private, 163516, Some-college, 10, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 277434, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 26, Federal-gov, 206983, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, Columbia, <=50K 48, Private, 108993, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 39, Private, 288551, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 41, Private, 176069, HS-grad, 9, Separated, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 48, State-gov, 183486, Assoc-voc, 11, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 56, United-States, >50K 40, Private, 163215, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Female, 10520, 0, 40, United-States, >50K 70, Private, 94692, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 70, United-States, >50K 20, Private, 118462, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 43, United-States, <=50K 38, Private, 407068, 5th-6th, 3, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 75, Mexico, <=50K 37, Self-emp-not-inc, 243587, Some-college, 10, Separated, Other-service, Own-child, White, Female, 0, 0, 40, Cuba, <=50K 49, Private, 23074, Some-college, 10, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 51, Private, 237735, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 3103, 0, 40, United-States, >50K 43, Private, 188291, 1st-4th, 2, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 284166, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 18, ?, 423460, 11th, 7, Never-married, ?, Own-child, White, Male, 0, 0, 36, United-States, <=50K 23, Private, 287681, 7th-8th, 4, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 25, Mexico, <=50K 34, Private, 509364, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 62, ?, 139391, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 24, United-States, <=50K 33, Private, 91964, Some-college, 10, Never-married, Adm-clerical, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 117526, Some-college, 10, Never-married, Farming-fishing, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 64, Private, 91343, Some-college, 10, Widowed, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 26, Local-gov, 336969, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 28, El-Salvador, <=50K 55, Private, 255364, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, Local-gov, 167670, Bachelors, 13, Married-spouse-absent, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 211494, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 78, Local-gov, 136198, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 15, United-States, <=50K 27, Federal-gov, 409815, Some-college, 10, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 49, Private, 188823, HS-grad, 9, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 42, United-States, <=50K 55, State-gov, 146326, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 45, United-States, >50K 42, Private, 154374, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 58, United-States, <=50K 22, ?, 216563, HS-grad, 9, Never-married, ?, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 61, Private, 197286, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 64, Self-emp-not-inc, 100722, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 5, United-States, <=50K 46, Local-gov, 377622, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 145964, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 358636, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 2829, 0, 70, United-States, <=50K 47, Private, 155489, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 7688, 0, 55, United-States, >50K 18, Private, 57413, Some-college, 10, Divorced, Other-service, Own-child, White, Male, 0, 0, 15, United-States, <=50K 48, Private, 320421, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 50, Self-emp-not-inc, 174752, HS-grad, 9, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 40, State-gov, 229364, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 56, Self-emp-not-inc, 157486, 10th, 6, Divorced, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 92682, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 4865, 0, 40, United-States, <=50K 56, Federal-gov, 101338, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 132652, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 21, Private, 34616, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 40, Private, 218903, HS-grad, 9, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 27, Local-gov, 204098, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Other-relative, White, Male, 0, 0, 50, United-States, <=50K 52, Self-emp-not-inc, 64045, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 45, United-States, >50K 46, Private, 189763, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 23, Private, 26248, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 50, Private, 92079, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 45, United-States, >50K 19, Private, 280071, Some-college, 10, Never-married, Machine-op-inspct, Other-relative, White, Male, 0, 0, 50, United-States, <=50K 20, Private, 224059, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 185520, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 8614, 0, 40, United-States, >50K 24, Private, 265567, 11th, 7, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 35, United-States, <=50K 72, Private, 106890, Assoc-voc, 11, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, State-gov, 39586, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 20, United-States, >50K 42, Private, 153132, Bachelors, 13, Divorced, Sales, Unmarried, White, Male, 0, 0, 45, ?, <=50K 51, Private, 209912, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 50, United-States, <=50K 39, Private, 144169, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 40, Local-gov, 50442, Some-college, 10, Never-married, Adm-clerical, Unmarried, Amer-Indian-Eskimo, Female, 2977, 0, 35, United-States, <=50K 34, Private, 89644, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, >50K 19, Private, 275889, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, Mexico, <=50K 26, Private, 231638, HS-grad, 9, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 45, Local-gov, 224474, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 4934, 0, 50, United-States, >50K 28, Private, 355259, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 30, Federal-gov, 68330, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 32, Private, 185410, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 87653, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 21, Private, 286853, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 35, United-States, <=50K 54, Private, 96710, HS-grad, 9, Married-civ-spouse, Priv-house-serv, Other-relative, Black, Female, 0, 0, 20, United-States, <=50K 62, Private, 160143, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 30, United-States, >50K 25, Private, 186925, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 2597, 0, 48, United-States, <=50K 49, Self-emp-inc, 109705, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 32, Private, 94235, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 225279, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 1602, 40, ?, <=50K 37, Local-gov, 297449, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 58, Private, 205896, HS-grad, 9, Divorced, Sales, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 93717, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 7298, 0, 45, United-States, >50K 41, Private, 194710, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 236391, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 40, United-States, >50K 47, State-gov, 189123, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 358677, HS-grad, 9, Divorced, Other-service, Unmarried, Black, Male, 0, 0, 35, United-States, <=50K 30, State-gov, 199539, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 1902, 40, United-States, <=50K 43, Private, 128170, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 40, United-States, >50K 34, Private, 231238, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 57, Private, 296152, Some-college, 10, Divorced, Exec-managerial, Other-relative, White, Female, 594, 0, 10, United-States, <=50K 46, Private, 166003, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 281437, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 55, United-States, <=50K 20, Private, 190231, 9th, 5, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 11, Nicaragua, <=50K 47, Private, 122026, Assoc-voc, 11, Divorced, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 55, ?, 205527, HS-grad, 9, Divorced, ?, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 53, Self-emp-not-inc, 174102, 7th-8th, 4, Married-civ-spouse, Exec-managerial, Husband, White, Male, 4386, 0, 50, Greece, >50K 43, Private, 125461, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 65, United-States, >50K 80, Self-emp-not-inc, 184335, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 30, United-States, <=50K 24, Private, 211345, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, Mexico, <=50K 43, Local-gov, 147328, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 60, United-States, >50K 22, Private, 222993, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 225978, Some-college, 10, Separated, Exec-managerial, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 48, Private, 121124, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 56, ?, 656036, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 25, United-States, <=50K 34, ?, 346762, 11th, 7, Divorced, ?, Own-child, White, Male, 0, 0, 84, United-States, <=50K 51, Private, 234057, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 24, Federal-gov, 306515, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 116562, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 171159, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 24, Private, 199011, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 443508, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 48, Canada, >50K 24, Private, 29810, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 22, Local-gov, 238831, Some-college, 10, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 40, United-States, <=50K 32, Federal-gov, 566117, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 255044, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 20, Private, 436253, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 35, United-States, <=50K 31, Private, 300687, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 55, Private, 144071, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 18, United-States, >50K 49, State-gov, 133917, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 1902, 60, ?, >50K 26, Private, 188767, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 27, Self-emp-not-inc, 300777, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 35, Private, 26987, HS-grad, 9, Separated, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 174395, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 60, Greece, <=50K 59, Private, 90290, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 34, United-States, <=50K 61, Private, 183735, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 31, Private, 123273, HS-grad, 9, Never-married, Sales, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 43, Federal-gov, 186916, Masters, 14, Divorced, Protective-serv, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 61, Private, 43554, 5th-6th, 3, Never-married, Handlers-cleaners, Not-in-family, Black, Male, 0, 2339, 40, United-States, <=50K 54, Private, 178251, Assoc-acdm, 12, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 30, Private, 255885, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 20, Private, 64292, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 27, State-gov, 194773, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, Germany, <=50K 44, Self-emp-inc, 133060, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 64, Private, 258006, Some-college, 10, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, Cuba, <=50K 55, Private, 92215, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 33945, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 6849, 0, 55, United-States, <=50K 61, Private, 153048, HS-grad, 9, Widowed, Sales, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 28, Private, 192200, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, ?, <=50K 34, Private, 355571, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 47, Self-emp-inc, 139268, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 60, United-States, >50K 26, Private, 34402, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 35, Private, 25955, 11th, 7, Never-married, Other-service, Unmarried, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 36, Private, 209609, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 38, United-States, <=50K 47, Private, 168283, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 17, Private, 295488, 11th, 7, Never-married, Other-service, Own-child, Black, Female, 0, 0, 25, United-States, <=50K 35, Private, 190895, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 33, Private, 164190, Masters, 14, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 20, United-States, <=50K 25, Private, 216010, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 387568, 10th, 6, Never-married, Sales, Own-child, White, Male, 0, 0, 10, United-States, <=50K 47, State-gov, 188386, Masters, 14, Separated, Prof-specialty, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 44, Private, 174491, HS-grad, 9, Widowed, Other-service, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 41, Private, 31221, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 30, Private, 272451, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 53, Self-emp-not-inc, 152652, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 53, Private, 104413, HS-grad, 9, Widowed, Other-service, Unmarried, Black, Female, 0, 0, 20, United-States, <=50K 40, Private, 105936, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 5013, 0, 20, United-States, <=50K 24, Private, 379066, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 2205, 24, United-States, <=50K 27, Private, 214858, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 237735, 5th-6th, 3, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 37, Mexico, <=50K 36, Private, 158592, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 41, Private, 237321, 1st-4th, 2, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, >50K 41, Private, 23646, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 169240, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 32, Federal-gov, 454508, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 130356, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 48, United-States, <=50K 22, Private, 427686, 10th, 6, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 18, Local-gov, 36411, 12th, 8, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 30, United-States, <=50K 39, Private, 548510, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 30, United-States, <=50K 38, Private, 187264, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 55, United-States, <=50K 35, State-gov, 140752, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 325596, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 54, Self-emp-not-inc, 175804, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 107302, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 63, Local-gov, 41161, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, <=50K 39, Private, 401832, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 48, United-States, <=50K 57, Self-emp-not-inc, 353808, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 58, Self-emp-inc, 349910, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 50, United-States, >50K 29, Private, 161478, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, Japan, <=50K 17, Private, 400225, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 40, Private, 367533, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 69, Self-emp-not-inc, 69306, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 15, United-States, <=50K 28, Private, 270366, 10th, 6, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 103751, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 75227, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Male, 14084, 0, 40, United-States, >50K 45, Local-gov, 132563, Prof-school, 15, Divorced, Prof-specialty, Unmarried, Black, Female, 0, 1726, 40, United-States, <=50K 33, State-gov, 79580, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, <=50K 41, Local-gov, 344624, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 1485, 40, United-States, >50K 37, Self-emp-inc, 186359, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 60, United-States, >50K 50, Private, 121685, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 48, Private, 75104, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 26, ?, 188343, HS-grad, 9, Never-married, ?, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 36, Private, 246449, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 21, Private, 85088, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 37, United-States, <=50K 37, Private, 545483, Assoc-acdm, 12, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, State-gov, 243986, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 20, United-States, <=50K 54, Self-emp-not-inc, 32778, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 30, United-States, <=50K 28, Private, 369114, HS-grad, 9, Separated, Sales, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 217200, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 149220, Assoc-voc, 11, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 46, ?, 162034, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, ?, 157813, 11th, 7, Divorced, ?, Unmarried, White, Female, 0, 0, 58, Canada, <=50K 17, ?, 179715, 10th, 6, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 40, Self-emp-not-inc, 335549, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 2444, 45, United-States, >50K 47, Private, 102308, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 44, Private, 367749, 1st-4th, 2, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, El-Salvador, <=50K 25, Private, 98281, 12th, 8, Never-married, Handlers-cleaners, Unmarried, White, Male, 0, 0, 43, United-States, <=50K 35, Private, 115792, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, <=50K 29, Private, 277788, Some-college, 10, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 25, United-States, <=50K 30, Private, 103435, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 37646, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, Self-emp-not-inc, 385632, 7th-8th, 4, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 25, Self-emp-not-inc, 210278, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 30, United-States, <=50K 28, Private, 335357, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 43, Self-emp-not-inc, 272165, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Local-gov, 148995, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 60, United-States, >50K 46, Self-emp-not-inc, 113434, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, State-gov, 132551, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 38, Federal-gov, 115433, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Wife, White, Female, 7688, 0, 33, United-States, >50K 29, Private, 227890, HS-grad, 9, Never-married, Protective-serv, Other-relative, Black, Male, 0, 0, 40, United-States, <=50K 25, Private, 503012, 5th-6th, 3, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 56, Private, 250873, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 31, Private, 407930, 7th-8th, 4, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 148187, 11th, 7, Never-married, Other-service, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 159322, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 334368, Some-college, 10, Separated, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 53, Private, 196328, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, United-States, <=50K 45, Private, 270842, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 71, Private, 235079, Preschool, 1, Widowed, Craft-repair, Unmarried, Black, Male, 0, 0, 10, United-States, <=50K 65, ?, 327154, HS-grad, 9, Widowed, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 188391, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 50, United-States, >50K 19, Federal-gov, 30559, HS-grad, 9, Married-AF-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, <=50K 34, Local-gov, 255098, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 248010, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, <=50K 40, Private, 174515, HS-grad, 9, Married-spouse-absent, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 90, Private, 171956, Some-college, 10, Separated, Adm-clerical, Own-child, White, Female, 0, 0, 40, Puerto-Rico, <=50K 56, Private, 193130, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 16, United-States, <=50K 21, Private, 108670, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 48, Private, 186172, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 45, Private, 348854, Some-college, 10, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 27, United-States, <=50K 46, Private, 271828, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 64, Private, 148606, 10th, 6, Separated, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 29, Local-gov, 123983, Masters, 14, Never-married, Prof-specialty, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, Taiwan, <=50K 22, Private, 24896, HS-grad, 9, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 30, Germany, <=50K 47, Private, 573583, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 48, Italy, >50K 67, Self-emp-inc, 106175, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 2392, 75, United-States, >50K 43, Private, 307767, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 200574, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 59083, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 1672, 50, United-States, <=50K 53, Private, 358056, 11th, 7, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 81, Private, 114670, 9th, 5, Widowed, Priv-house-serv, Not-in-family, Black, Female, 2062, 0, 5, United-States, <=50K 33, Local-gov, 262042, HS-grad, 9, Divorced, Adm-clerical, Own-child, White, Female, 0, 1138, 40, United-States, <=50K 17, Private, 206010, 12th, 8, Never-married, Other-service, Own-child, White, Female, 0, 0, 8, United-States, <=50K 55, Self-emp-inc, 183869, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, ?, >50K 28, Private, 159001, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 30, United-States, <=50K 24, Private, 155818, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 96055, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 30, Local-gov, 131776, Masters, 14, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 228613, 11th, 7, Never-married, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 198163, Masters, 14, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 37028, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 30, Private, 177304, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Private, 144064, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 40, Private, 146659, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 63, Self-emp-not-inc, 26904, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 98, United-States, <=50K 23, Private, 238917, 7th-8th, 4, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 36, United-States, <=50K 56, Private, 170148, HS-grad, 9, Divorced, Craft-repair, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 42, Self-emp-not-inc, 27821, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 40, Private, 220460, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Canada, <=50K 49, Private, 101320, Assoc-acdm, 12, Married-civ-spouse, Sales, Wife, White, Female, 0, 1902, 40, United-States, >50K 35, Private, 173858, HS-grad, 9, Married-spouse-absent, Craft-repair, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, ?, <=50K 52, Private, 91048, HS-grad, 9, Divorced, Machine-op-inspct, Own-child, Black, Female, 0, 0, 35, United-States, <=50K 28, Private, 298696, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 207202, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 70, United-States, <=50K 21, ?, 230397, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 5, United-States, <=50K 43, Self-emp-not-inc, 180599, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 32, ?, 199046, Assoc-voc, 11, Never-married, ?, Unmarried, White, Female, 0, 0, 2, United-States, <=50K 29, Self-emp-not-inc, 132686, Prof-school, 15, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 50, Italy, >50K 23, Private, 240063, Bachelors, 13, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 25, United-States, <=50K 50, Local-gov, 177705, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 1740, 48, United-States, <=50K 34, Private, 511361, Some-college, 10, Never-married, Other-service, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 19, Private, 89397, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 239439, 11th, 7, Married-civ-spouse, Machine-op-inspct, Wife, Black, Female, 0, 0, 40, United-States, <=50K 37, Self-emp-not-inc, 36989, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 76978, HS-grad, 9, Never-married, Sales, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 75, Private, 200068, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 35, United-States, >50K 24, Private, 454941, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, State-gov, 107218, Bachelors, 13, Never-married, Tech-support, Own-child, Asian-Pac-Islander, Male, 0, 0, 20, United-States, <=50K 17, Local-gov, 182070, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 16, United-States, <=50K 31, Private, 176360, HS-grad, 9, Never-married, Craft-repair, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 31, Private, 452405, Preschool, 1, Never-married, Other-service, Other-relative, White, Female, 0, 0, 35, Mexico, <=50K 18, ?, 297396, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 0, 10, United-States, <=50K 45, Private, 84790, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 31, Private, 186787, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 42, United-States, <=50K 27, Private, 169662, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 42, United-States, >50K 48, Private, 125933, Some-college, 10, Widowed, Exec-managerial, Unmarried, Black, Female, 0, 1669, 38, United-States, <=50K 22, ?, 35448, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 22, United-States, <=50K 34, Private, 225548, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 30, United-States, <=50K 26, Private, 240842, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 53, Private, 103931, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 60, Private, 232618, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 35, United-States, >50K 49, Local-gov, 288548, Masters, 14, Separated, Prof-specialty, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 40, Private, 220609, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 48, Self-emp-inc, 26145, 10th, 6, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 80, United-States, <=50K 23, Private, 268525, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 68, ?, 133758, 7th-8th, 4, Widowed, ?, Not-in-family, Black, Male, 0, 0, 10, United-States, <=50K 42, Private, 121264, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Self-emp-not-inc, 29814, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 85, United-States, <=50K 27, Private, 193701, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Female, 0, 0, 45, United-States, <=50K 38, Private, 183279, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 44, United-States, >50K 27, Private, 163942, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 35, Ireland, <=50K 75, Private, 188612, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 49, Self-emp-inc, 102771, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 52, United-States, >50K 27, Private, 85625, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 36, Self-emp-not-inc, 245090, Bachelors, 13, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 50, Mexico, <=50K 36, Private, 131239, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 3103, 0, 45, United-States, >50K 35, Private, 182074, HS-grad, 9, Divorced, Handlers-cleaners, Own-child, White, Male, 0, 0, 35, United-States, <=50K 36, Private, 187046, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 53, Private, 90624, 11th, 7, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 27, Private, 37933, Some-college, 10, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 34, Private, 182177, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 3325, 0, 35, United-States, <=50K 61, Private, 716416, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 44, United-States, >50K 29, Private, 190562, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Male, 0, 0, 56, United-States, <=50K 40, State-gov, 141583, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 37, Private, 98941, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 22, Private, 201729, 9th, 5, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 30, United-States, <=50K 43, Self-emp-inc, 175485, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Self-emp-not-inc, 149168, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 30, United-States, <=50K 28, Private, 115971, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 161708, Bachelors, 13, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 64, Local-gov, 244903, 11th, 7, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, >50K 46, Private, 155664, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 112754, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 178385, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 48, India, <=50K 20, Private, 44064, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 25, United-States, <=50K 62, Self-emp-not-inc, 120939, Some-college, 10, Divorced, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 165134, Assoc-voc, 11, Never-married, Exec-managerial, Unmarried, White, Female, 0, 0, 35, Columbia, <=50K 29, Private, 100405, 10th, 6, Married-civ-spouse, Farming-fishing, Wife, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 35, Self-emp-not-inc, 361888, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, Japan, <=50K 39, Local-gov, 167864, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 30, United-States, <=50K 39, Private, 202950, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 37, Private, 218188, HS-grad, 9, Divorced, Machine-op-inspct, Other-relative, White, Female, 0, 0, 32, United-States, <=50K 38, Private, 234962, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 2829, 0, 30, Mexico, <=50K 72, ?, 177226, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 8, United-States, <=50K 31, Private, 259931, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 189528, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 38, Private, 34996, Some-college, 10, Separated, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 112584, Some-college, 10, Divorced, Sales, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 25, Private, 117589, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 19, ?, 145234, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 30, United-States, <=50K 37, Private, 267086, Assoc-voc, 11, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 52, United-States, <=50K 49, Private, 44434, Some-college, 10, Divorced, Tech-support, Other-relative, White, Male, 0, 0, 35, United-States, <=50K 26, Private, 96130, HS-grad, 9, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 181382, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 43, United-States, <=50K 44, Self-emp-inc, 168845, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 60, United-States, <=50K 37, Private, 271767, Masters, 14, Separated, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 42, Private, 194636, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 64, State-gov, 194894, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Female, 4787, 0, 40, United-States, >50K 28, Private, 132686, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Self-emp-not-inc, 185848, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 4650, 0, 50, United-States, <=50K 40, State-gov, 184378, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Federal-gov, 270859, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 21, Private, 231866, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 65, United-States, <=50K 49, Private, 36032, Some-college, 10, Never-married, Exec-managerial, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 51, State-gov, 172962, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 57, Private, 98350, Prof-school, 15, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 1902, 40, Philippines, >50K 51, Private, 24185, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 53930, 10th, 6, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, ?, <=50K 24, Private, 85088, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 1762, 32, United-States, <=50K 45, Self-emp-not-inc, 94962, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, England, <=50K 28, Private, 480861, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, <=50K 42, Self-emp-inc, 187702, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 2415, 60, United-States, >50K 22, Private, 52262, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, State-gov, 52636, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 60, Private, 175273, HS-grad, 9, Widowed, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 327825, HS-grad, 9, Separated, Machine-op-inspct, Unmarried, White, Female, 0, 2238, 40, United-States, <=50K 47, Private, 125892, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 75, United-States, >50K 40, ?, 78255, HS-grad, 9, Divorced, ?, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 30, Private, 398827, HS-grad, 9, Married-AF-spouse, Adm-clerical, Husband, White, Male, 0, 0, 60, United-States, <=50K 61, Private, 208919, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 71, Local-gov, 365996, Bachelors, 13, Widowed, Prof-specialty, Unmarried, White, Female, 0, 0, 6, United-States, <=50K 42, Private, 307638, HS-grad, 9, Divorced, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 44, Local-gov, 33068, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, <=50K 46, Self-emp-not-inc, 254291, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 50, Local-gov, 125417, Prof-school, 15, Never-married, Exec-managerial, Not-in-family, Black, Female, 0, 0, 52, United-States, >50K 27, State-gov, 28848, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 9, United-States, <=50K 40, ?, 273425, Assoc-voc, 11, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 15, United-States, <=50K 21, Private, 194723, Some-college, 10, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 40, Mexico, <=50K 25, Private, 195118, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 35, United-States, <=50K 61, Private, 123273, 5th-6th, 3, Divorced, Transport-moving, Not-in-family, White, Male, 0, 1876, 56, United-States, <=50K 54, Private, 220115, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 31, Private, 265706, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 53, Self-emp-not-inc, 279129, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 30, United-States, <=50K 39, Self-emp-inc, 122742, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 55, United-States, >50K 57, Self-emp-inc, 172654, Prof-school, 15, Married-civ-spouse, Transport-moving, Husband, White, Male, 15024, 0, 50, United-States, >50K 48, Private, 119199, Bachelors, 13, Divorced, Sales, Unmarried, White, Female, 0, 0, 44, United-States, <=50K 30, Private, 107793, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 56, United-States, >50K 35, Private, 237943, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 60, United-States, <=50K 42, Self-emp-not-inc, 64632, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 34, Self-emp-not-inc, 96245, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 59, Private, 361494, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 69, Local-gov, 122850, 10th, 6, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 20, United-States, <=50K 29, Private, 173652, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 164663, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 98678, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 15, United-States, <=50K 40, Private, 245529, Assoc-acdm, 12, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 55294, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 140583, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 79797, HS-grad, 9, Married-spouse-absent, Prof-specialty, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, Japan, >50K 72, ?, 113044, HS-grad, 9, Widowed, ?, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 20, Private, 283499, Some-college, 10, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 30, United-States, <=50K 41, Local-gov, 51111, Bachelors, 13, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 232475, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 48, Private, 176140, 11th, 7, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 27, Private, 301654, HS-grad, 9, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 376455, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 60, United-States, >50K 28, ?, 192569, HS-grad, 9, Never-married, ?, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 27, Private, 229803, HS-grad, 9, Never-married, Craft-repair, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 20, Private, 337639, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 130849, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 15, United-States, <=50K 32, Private, 296282, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 266645, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 23, State-gov, 110128, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 90196, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 40, State-gov, 40024, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 38, United-States, >50K 35, Private, 144322, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 74, Self-emp-inc, 162340, Some-college, 10, Widowed, Exec-managerial, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 169069, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 113601, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 30, United-States, <=50K 20, Self-emp-not-inc, 157145, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Male, 0, 2258, 10, United-States, <=50K 44, Private, 111275, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 56, United-States, <=50K 46, Local-gov, 102076, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 20, ?, 182117, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 51, Self-emp-not-inc, 145409, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 50, United-States, >50K 40, Private, 190122, Some-college, 10, Separated, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 48, Private, 331482, Prof-school, 15, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 1977, 40, United-States, >50K 60, Self-emp-not-inc, 170114, 9th, 5, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 1672, 84, United-States, <=50K 48, Self-emp-inc, 193188, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Local-gov, 267588, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 70, United-States, <=50K 48, Self-emp-inc, 200471, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 22, ?, 175586, HS-grad, 9, Never-married, ?, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 24, Local-gov, 322658, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, State-gov, 263982, Some-college, 10, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 266287, 12th, 8, Never-married, Sales, Own-child, White, Female, 0, 0, 35, United-States, <=50K 39, Private, 278187, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 65, Self-emp-inc, 81413, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 2352, 65, United-States, <=50K 22, Private, 221745, Some-college, 10, Divorced, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 140764, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 28, Private, 206351, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 176814, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 50, United-States, >50K 42, Local-gov, 245307, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 48, United-States, >50K 61, State-gov, 124971, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, ?, >50K 28, Private, 119545, Some-college, 10, Married-civ-spouse, Exec-managerial, Own-child, White, Male, 7688, 0, 50, United-States, >50K 18, Private, 179203, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 24, Federal-gov, 44075, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 45, Private, 178319, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 56, United-States, >50K 24, Private, 219754, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 198316, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 20, Private, 168165, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, United-States, <=50K 35, Private, 356838, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 2829, 0, 55, Poland, <=50K 52, Self-emp-inc, 210736, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 25, Private, 173212, Assoc-acdm, 12, Never-married, Farming-fishing, Not-in-family, White, Male, 2354, 0, 45, United-States, <=50K 19, Private, 130431, 5th-6th, 3, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 36, Mexico, <=50K 35, ?, 169809, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 20, United-States, <=50K 54, Private, 197481, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 155066, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 31290, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 42, Private, 54102, Assoc-voc, 11, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 181546, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 55, Private, 153484, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 50, United-States, >50K 44, State-gov, 351228, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 131976, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 55, United-States, <=50K 26, Private, 200639, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 64, Federal-gov, 267546, Assoc-acdm, 12, Separated, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 41, Private, 179875, 11th, 7, Divorced, Other-service, Unmarried, Other, Female, 0, 0, 40, United-States, <=50K 25, ?, 237865, Some-college, 10, Never-married, ?, Own-child, Black, Male, 0, 0, 40, ?, <=50K 43, Private, 300528, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 67716, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 10520, 0, 48, United-States, >50K 48, Federal-gov, 326048, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 44, United-States, >50K 60, Private, 191188, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Self-emp-not-inc, 32172, Some-college, 10, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 51, Private, 252903, 10th, 6, Married-civ-spouse, Sales, Husband, White, Male, 0, 1977, 40, United-States, >50K 37, Federal-gov, 334314, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 83704, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 30, United-States, <=50K 44, Private, 160574, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 65, United-States, >50K 27, Private, 203776, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 47, Local-gov, 328610, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 295589, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 1977, 40, United-States, >50K 40, Private, 174373, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 41, Private, 247752, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, ?, 199244, 10th, 6, Divorced, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 139992, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 95680, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 55, Self-emp-inc, 189933, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 38, Private, 498785, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, State-gov, 177526, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 15, United-States, <=50K 64, Self-emp-not-inc, 150121, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 25, United-States, >50K 56, Federal-gov, 130454, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Private, 119079, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 49, United-States, >50K 33, Private, 220939, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 7298, 0, 45, United-States, >50K 33, Private, 94235, Prof-school, 15, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 42, United-States, >50K 21, Private, 305874, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 59, Local-gov, 62020, HS-grad, 9, Widowed, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 58, Private, 235624, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, Germany, >50K 43, Local-gov, 247514, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 275726, HS-grad, 9, Never-married, Craft-repair, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 45, Private, 72896, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 53, Local-gov, 110510, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 50, United-States, >50K 41, Private, 173938, Prof-school, 15, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, ?, >50K 27, Private, 200641, 10th, 6, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, Mexico, <=50K 53, Private, 211654, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, ?, >50K 38, Private, 242720, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, >50K 31, Private, 111567, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 70, United-States, >50K 41, Private, 179533, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 35, United-States, <=50K 22, State-gov, 334693, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 43, Self-emp-not-inc, 198096, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 41, State-gov, 355756, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 19395, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Wife, White, Female, 0, 0, 35, United-States, <=50K 41, Local-gov, 242586, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 208358, Prof-school, 15, Divorced, Prof-specialty, Not-in-family, White, Male, 99999, 0, 45, United-States, >50K 49, Private, 160647, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 20, Private, 227943, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 45, United-States, <=50K 58, Self-emp-not-inc, 197665, HS-grad, 9, Married-spouse-absent, Other-service, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 35, Self-emp-not-inc, 216129, 12th, 8, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 40, Trinadad&Tobago, <=50K 30, Local-gov, 326104, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 21, Private, 57211, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 100219, Assoc-acdm, 12, Never-married, Machine-op-inspct, Unmarried, White, Male, 0, 0, 45, United-States, <=50K 40, Private, 291192, HS-grad, 9, Widowed, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 54, State-gov, 93415, Bachelors, 13, Never-married, Prof-specialty, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, United-States, >50K 35, Private, 191502, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 35, Private, 261382, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 40, Private, 170230, Bachelors, 13, Married-spouse-absent, Other-service, Not-in-family, White, Female, 0, 0, 40, ?, <=50K 59, Private, 374924, HS-grad, 9, Separated, Sales, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 43, Self-emp-inc, 320984, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, <=50K 39, Private, 338320, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, >50K 51, Private, 135190, 7th-8th, 4, Separated, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 30, United-States, <=50K 71, Private, 157909, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 2964, 0, 60, United-States, <=50K 33, Private, 637222, 12th, 8, Divorced, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 28, Private, 430084, HS-grad, 9, Divorced, Other-service, Own-child, Black, Male, 0, 0, 35, United-States, <=50K 30, Private, 125279, HS-grad, 9, Married-spouse-absent, Sales, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 221955, 5th-6th, 3, Married-spouse-absent, Farming-fishing, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 51, Self-emp-inc, 180195, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 39, Private, 208778, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, United-States, >50K 62, Private, 81534, Some-college, 10, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, >50K 37, Private, 325538, HS-grad, 9, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 60, ?, <=50K 28, Private, 142264, 9th, 5, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 50, Dominican-Republic, <=50K 23, Private, 128604, HS-grad, 9, Never-married, Sales, Own-child, Asian-Pac-Islander, Male, 0, 0, 48, South, <=50K 39, Private, 277886, Bachelors, 13, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 30, United-States, <=50K 50, Self-emp-inc, 100029, Bachelors, 13, Widowed, Sales, Unmarried, White, Male, 0, 0, 65, United-States, >50K 31, Private, 169269, 7th-8th, 4, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 45, Local-gov, 160472, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 50, United-States, >50K 23, ?, 123983, Bachelors, 13, Never-married, ?, Own-child, Other, Male, 0, 0, 40, United-States, <=50K 47, Private, 297884, 10th, 6, Widowed, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 59, Private, 99131, HS-grad, 9, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 18, United-States, <=50K 32, Private, 44392, Assoc-acdm, 12, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 82, ?, 29441, 7th-8th, 4, Widowed, ?, Not-in-family, White, Male, 0, 0, 5, United-States, <=50K 49, Private, 199029, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 2415, 55, United-States, >50K 74, Federal-gov, 181508, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Male, 0, 0, 17, United-States, <=50K 22, Private, 190625, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 35, United-States, <=50K 32, Private, 194740, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, Greece, <=50K 34, Private, 27380, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, >50K 59, Private, 160631, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, >50K 36, Private, 224531, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 59, Private, 283005, 11th, 7, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 47, Self-emp-inc, 101926, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 70, United-States, >50K 53, Local-gov, 135102, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 2002, 45, United-States, <=50K 25, Self-emp-not-inc, 113436, Some-college, 10, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 35, United-States, <=50K 44, Private, 248973, Bachelors, 13, Divorced, Adm-clerical, Not-in-family, Black, Male, 0, 0, 65, United-States, <=50K 57, Self-emp-not-inc, 225334, Prof-school, 15, Married-civ-spouse, Sales, Wife, White, Female, 15024, 0, 35, United-States, >50K 42, Self-emp-not-inc, 157562, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 1902, 80, United-States, >50K 58, Local-gov, 310085, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 129597, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 3464, 0, 40, United-States, <=50K 32, ?, 53042, HS-grad, 9, Never-married, ?, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 45, Private, 204205, 7th-8th, 4, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 47, Private, 169324, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, Black, Female, 0, 0, 35, United-States, >50K 52, ?, 134447, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 50, United-States, <=50K 56, Self-emp-not-inc, 236731, 1st-4th, 2, Separated, Exec-managerial, Not-in-family, White, Male, 0, 0, 25, ?, <=50K 52, Private, 141301, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 235124, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 36, Self-emp-not-inc, 367020, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 41, Private, 149102, HS-grad, 9, Married-spouse-absent, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Poland, <=50K 30, Private, 423770, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, Mexico, <=50K 44, Private, 211759, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Other, Male, 0, 0, 40, Puerto-Rico, <=50K 17, ?, 110998, Some-college, 10, Never-married, ?, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 34, Private, 56883, Some-college, 10, Never-married, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 223062, Some-college, 10, Separated, Other-service, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 29, Private, 406662, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 206600, 9th, 5, Never-married, Machine-op-inspct, Other-relative, White, Male, 0, 0, 48, Mexico, <=50K 42, Local-gov, 147510, Bachelors, 13, Separated, Prof-specialty, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 235646, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 3103, 0, 40, United-States, >50K 26, Private, 187577, Assoc-voc, 11, Never-married, Sales, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 64, Self-emp-inc, 132832, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 20051, 0, 40, ?, >50K 46, Self-emp-inc, 278322, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 38, Private, 278924, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1887, 50, United-States, >50K 49, State-gov, 203039, 11th, 7, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 145651, Some-college, 10, Never-married, Sales, Own-child, Black, Female, 0, 0, 20, United-States, <=50K 46, Local-gov, 144531, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 30, Private, 91145, HS-grad, 9, Never-married, Handlers-cleaners, Unmarried, White, Male, 0, 0, 55, United-States, <=50K 49, Self-emp-not-inc, 211762, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 47, ?, 111563, Assoc-voc, 11, Divorced, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 180985, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, ?, >50K 31, Private, 207537, HS-grad, 9, Divorced, Craft-repair, Own-child, White, Male, 0, 1669, 50, United-States, <=50K 19, Private, 417657, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 50, United-States, <=50K 45, Private, 189890, Assoc-acdm, 12, Divorced, Prof-specialty, Unmarried, White, Female, 5455, 0, 38, United-States, <=50K 34, Private, 223212, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1848, 40, Peru, >50K 26, Private, 108658, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, Self-emp-not-inc, 190023, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 222130, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 43, United-States, <=50K 36, Self-emp-inc, 164866, Assoc-acdm, 12, Separated, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 31, Private, 170983, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 30, Private, 186269, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 286026, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Private, 403433, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Black, Male, 0, 0, 50, United-States, >50K 21, ?, 224209, HS-grad, 9, Married-civ-spouse, ?, Wife, Black, Female, 0, 0, 30, United-States, <=50K 73, Private, 123160, 10th, 6, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 10, United-States, <=50K 38, Federal-gov, 99527, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Private, 123178, 10th, 6, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 33, Private, 231043, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 52, Local-gov, 317733, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 40, United-States, >50K 58, Private, 241056, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 46, United-States, <=50K 34, Local-gov, 220066, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 35, Private, 180342, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 59, Federal-gov, 31840, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 45, Private, 183168, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 386036, Some-college, 10, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 31, Local-gov, 446358, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, Mexico, >50K 45, Private, 28035, Some-college, 10, Never-married, Farming-fishing, Other-relative, White, Male, 0, 0, 50, United-States, <=50K 40, Private, 282155, HS-grad, 9, Separated, Other-service, Other-relative, White, Female, 0, 0, 25, United-States, <=50K 27, Private, 192384, Prof-school, 15, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 383637, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 29, Private, 457402, 5th-6th, 3, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 25, Mexico, <=50K 34, Self-emp-inc, 80249, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 72, United-States, <=50K 32, State-gov, 159537, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 240859, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Cuba, <=50K 33, Private, 83446, 11th, 7, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, >50K 74, ?, 29866, 7th-8th, 4, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 2, United-States, <=50K 62, Private, 185503, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 39, Self-emp-not-inc, 68781, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 220589, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 51136, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 24, Private, 54560, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 76, ?, 28221, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, Canada, >50K 25, Private, 201413, Some-college, 10, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 19, Private, 40425, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 28, United-States, <=50K 31, Private, 189461, Assoc-acdm, 12, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 41, United-States, <=50K 53, Private, 200576, 11th, 7, Divorced, Craft-repair, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 61, Private, 92691, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 3, United-States, <=50K 47, Private, 664821, Bachelors, 13, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, El-Salvador, <=50K 37, Private, 175130, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 50, Self-emp-not-inc, 391016, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 27, Private, 249315, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 44, United-States, <=50K 58, Private, 111169, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 334946, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, United-States, <=50K 39, Private, 352248, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 173804, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 56, Private, 155449, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 26, Private, 73689, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 55, United-States, <=50K 23, Private, 227594, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 38, United-States, <=50K 47, Private, 161676, 11th, 7, Never-married, Transport-moving, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 68, Private, 75913, 12th, 8, Widowed, Sales, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 47, Local-gov, 242552, Some-college, 10, Never-married, Protective-serv, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 45, Federal-gov, 352094, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 7688, 0, 40, Guatemala, >50K 26, Private, 159732, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 20, Private, 131230, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 1590, 40, United-States, <=50K 46, Private, 180695, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 189922, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 50, United-States, >50K 37, Private, 409189, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 43, Private, 111252, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 42, United-States, <=50K 59, Private, 294395, Masters, 14, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 172718, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 43403, Some-college, 10, Divorced, Farming-fishing, Not-in-family, White, Female, 0, 1590, 54, United-States, <=50K 63, Private, 111963, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 16, United-States, <=50K 45, Private, 247869, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 59, Private, 114032, Bachelors, 13, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 36, ?, 356838, 12th, 8, Never-married, ?, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 26, Private, 179633, HS-grad, 9, Never-married, Tech-support, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 19847, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 231689, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 209942, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 53, Private, 197492, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 262439, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 35, United-States, >50K 46, Private, 283037, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 79, ?, 144533, HS-grad, 9, Widowed, ?, Not-in-family, Black, Female, 0, 0, 30, United-States, <=50K 31, Private, 83446, HS-grad, 9, Widowed, Craft-repair, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 215443, HS-grad, 9, Separated, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 57, Local-gov, 268252, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 62, United-States, <=50K 40, Private, 181015, HS-grad, 9, Separated, Other-service, Unmarried, White, Female, 0, 0, 47, United-States, <=50K 41, Self-emp-inc, 139916, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, Other, Male, 0, 2179, 84, Mexico, <=50K 20, Private, 195770, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 26, United-States, <=50K 45, Private, 125194, 11th, 7, Never-married, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 27, Private, 58654, Assoc-voc, 11, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 252327, 5th-6th, 3, Married-spouse-absent, Craft-repair, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 30, Private, 116508, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Germany, <=50K 36, Private, 166988, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 25, Private, 374163, HS-grad, 9, Married-spouse-absent, Farming-fishing, Not-in-family, Other, Male, 0, 0, 40, Mexico, <=50K 30, ?, 96851, Some-college, 10, Never-married, ?, Not-in-family, White, Female, 0, 1719, 25, United-States, <=50K 31, Private, 196788, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 186172, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 7688, 0, 45, United-States, >50K 26, Private, 245628, 11th, 7, Never-married, Handlers-cleaners, Unmarried, White, Male, 0, 0, 20, United-States, <=50K 25, Private, 159732, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 129856, Assoc-voc, 11, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 182812, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 3325, 0, 52, Dominican-Republic, <=50K 41, Private, 314322, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 102976, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 57, Self-emp-inc, 42959, Bachelors, 13, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, >50K 21, Private, 256356, 11th, 7, Never-married, Priv-house-serv, Other-relative, White, Female, 0, 0, 40, Mexico, <=50K 29, Private, 136277, 10th, 6, Never-married, Other-service, Own-child, Black, Female, 0, 0, 32, United-States, <=50K 36, Private, 284616, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 185554, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 25, United-States, <=50K 51, Private, 138847, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 33487, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 84306, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 5013, 0, 50, United-States, <=50K 40, Self-emp-not-inc, 223881, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 70, United-States, >50K 61, Private, 149653, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 38, Private, 348739, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 20, ?, 235442, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 35, United-States, <=50K 21, Private, 34506, HS-grad, 9, Separated, Other-service, Own-child, White, Female, 0, 0, 35, United-States, <=50K 40, Private, 346964, HS-grad, 9, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 192208, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 21, Private, 305874, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 54, United-States, <=50K 35, Self-emp-not-inc, 462890, 10th, 6, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 50, United-States, <=50K 39, Private, 89508, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Self-emp-not-inc, 200153, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 30, Private, 179446, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 208965, 9th, 5, Never-married, Machine-op-inspct, Unmarried, Other, Male, 0, 0, 40, Mexico, <=50K 32, Private, 40142, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Self-emp-not-inc, 57452, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Private, 327573, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 151267, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, Black, Female, 15024, 0, 40, United-States, >50K 44, Private, 265266, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 203836, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 3464, 0, 40, Columbia, <=50K 51, ?, 163998, HS-grad, 9, Married-spouse-absent, ?, Not-in-family, White, Male, 0, 0, 20, United-States, >50K 46, Self-emp-not-inc, 28281, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, >50K 51, Private, 293196, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 60, Iran, >50K 45, Private, 214627, Doctorate, 16, Widowed, Prof-specialty, Unmarried, White, Male, 15020, 0, 40, Iran, >50K 20, Private, 368852, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 44, Private, 353396, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, <=50K 33, Private, 161745, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 45, United-States, <=50K 18, Private, 97963, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 61, Self-emp-inc, 156542, Prof-school, 15, Separated, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 50, State-gov, 198103, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Federal-gov, 55377, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 34, Private, 173730, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 53, Private, 374588, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 60, United-States, <=50K 39, Self-emp-not-inc, 174330, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, Private, 78141, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 66, ?, 190324, HS-grad, 9, Married-civ-spouse, ?, Husband, Black, Male, 0, 0, 18, United-States, <=50K 26, Private, 31350, 11th, 7, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 41, Private, 243607, 5th-6th, 3, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, Mexico, <=50K 47, Local-gov, 134671, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 197023, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 52, Private, 117674, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Private, 169815, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 43, Private, 598606, 9th, 5, Separated, Handlers-cleaners, Unmarried, Black, Female, 0, 0, 50, United-States, <=50K 42, Federal-gov, 122861, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 166235, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 30, United-States, <=50K 41, Private, 187821, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 2885, 0, 40, United-States, <=50K 34, Private, 340940, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 7298, 0, 60, United-States, >50K 52, Self-emp-not-inc, 194791, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 231323, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Local-gov, 305597, HS-grad, 9, Separated, Exec-managerial, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 25429, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 46, State-gov, 192779, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 40, United-States, >50K 39, Private, 346478, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 22, Private, 341368, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 30, State-gov, 295612, HS-grad, 9, Separated, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 168936, Assoc-voc, 11, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 43, Private, 218558, Bachelors, 13, Married-spouse-absent, Prof-specialty, Not-in-family, White, Male, 3325, 0, 40, United-States, <=50K 37, Private, 336598, 5th-6th, 3, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 36, Mexico, <=50K 23, Private, 308205, Assoc-acdm, 12, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 39, Local-gov, 357173, Assoc-acdm, 12, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 59, United-States, <=50K 54, Private, 457237, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Self-emp-inc, 284799, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 20, Private, 179423, Some-college, 10, Never-married, Transport-moving, Own-child, White, Female, 0, 0, 40, United-States, <=50K 50, Self-emp-not-inc, 363405, Bachelors, 13, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 50, United-States, >50K 17, Private, 139183, 10th, 6, Never-married, Sales, Own-child, White, Female, 0, 0, 15, United-States, <=50K 36, Private, 203482, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 112554, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 53, Private, 99476, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 50, Private, 93690, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 220585, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 63, Self-emp-not-inc, 194638, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 32, United-States, <=50K 53, Private, 154785, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 40, ?, 162108, Bachelors, 13, Divorced, ?, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 23, Self-emp-inc, 214542, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 20, Private, 161922, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 43, United-States, <=50K 46, Private, 207940, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, >50K 28, Private, 259351, 10th, 6, Never-married, Other-service, Other-relative, Amer-Indian-Eskimo, Male, 0, 0, 40, Mexico, <=50K 59, Private, 208395, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 41, Private, 116391, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Private, 239781, Preschool, 1, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, Mexico, <=50K 56, Private, 174351, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Italy, <=50K 50, Self-emp-not-inc, 44368, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 55, El-Salvador, >50K 31, Local-gov, 188798, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 41, Private, 50122, Assoc-voc, 11, Divorced, Sales, Own-child, White, Male, 0, 0, 50, United-States, <=50K 38, Private, 111398, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 7688, 0, 40, United-States, >50K 25, State-gov, 152035, Assoc-acdm, 12, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 18, ?, 139003, HS-grad, 9, Never-married, ?, Other-relative, Other, Female, 0, 0, 12, United-States, <=50K 49, Local-gov, 249289, Bachelors, 13, Divorced, Prof-specialty, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 39, Private, 257726, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 22, ?, 113175, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 20, United-States, <=50K 21, Private, 151158, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 25, United-States, <=50K 35, Private, 465326, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, ?, 356772, HS-grad, 9, Never-married, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 364782, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 55, Private, 198385, 7th-8th, 4, Widowed, Other-service, Unmarried, White, Female, 0, 0, 20, ?, <=50K 31, Private, 329301, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 17, Self-emp-inc, 254859, 11th, 7, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 20, United-States, <=50K 31, Private, 203488, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 7298, 0, 50, United-States, >50K 25, Local-gov, 222800, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 96452, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 50, Private, 170050, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Local-gov, 116580, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 20, United-States, >50K 50, Private, 400004, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 63, Private, 183608, 10th, 6, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 194055, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 23, Private, 210443, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 43272, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 43, Local-gov, 108945, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 48, United-States, <=50K 34, Private, 114691, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 18, Private, 304169, 11th, 7, Never-married, Sales, Own-child, White, Male, 0, 0, 35, United-States, <=50K 46, Private, 503923, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 4386, 0, 40, United-States, >50K 35, Private, 340428, Bachelors, 13, Never-married, Sales, Unmarried, White, Female, 0, 0, 40, United-States, >50K 46, State-gov, 106705, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 59, Private, 146391, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 7298, 0, 40, United-States, >50K 31, Private, 235389, 7th-8th, 4, Never-married, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 30, Portugal, <=50K 27, Private, 39665, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 37, United-States, <=50K 41, Private, 113823, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, England, <=50K 42, Private, 217826, HS-grad, 9, Never-married, Craft-repair, Own-child, Black, Male, 0, 0, 40, ?, <=50K 55, Private, 349304, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 34, ?, 197688, HS-grad, 9, Never-married, ?, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 44, Private, 54507, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 117833, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 1669, 50, United-States, <=50K 36, Private, 163396, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 69, Private, 88566, 9th, 5, Married-civ-spouse, Other-service, Husband, White, Male, 1424, 0, 35, United-States, <=50K 33, Private, 323619, Some-college, 10, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 75755, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 148903, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 16, United-States, >50K 25, Private, 40915, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 21, Private, 182606, Some-college, 10, Never-married, Other-service, Own-child, Black, Male, 0, 0, 40, ?, <=50K 18, Private, 131033, 11th, 7, Never-married, Other-service, Other-relative, Black, Male, 0, 0, 15, United-States, <=50K 35, Self-emp-not-inc, 168475, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, >50K 20, Private, 121568, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 50, United-States, <=50K 26, Private, 139098, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 5013, 0, 40, United-States, <=50K 46, Private, 357338, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 283268, Bachelors, 13, Never-married, Prof-specialty, Unmarried, White, Female, 0, 0, 36, United-States, <=50K 40, Private, 572751, Prof-school, 15, Married-civ-spouse, Craft-repair, Husband, White, Male, 5178, 0, 40, Mexico, >50K 40, Private, 315321, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 625, 52, United-States, <=50K 31, Private, 120461, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 32, Self-emp-not-inc, 65278, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Self-emp-not-inc, 208503, Some-college, 10, Divorced, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Local-gov, 112835, Masters, 14, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 265038, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 18, Private, 89478, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 55, Private, 276229, HS-grad, 9, Widowed, Sales, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 52, Private, 366232, 9th, 5, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 40, Cuba, <=50K 26, Private, 152035, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 205339, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 39, Private, 75995, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 62, Self-emp-not-inc, 192236, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 19, ?, 188618, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 25, United-States, <=50K 47, Private, 229737, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 51, Local-gov, 199688, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 55, Private, 52953, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 221043, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 59, Federal-gov, 115389, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 36, United-States, <=50K 45, Self-emp-not-inc, 204205, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 65, United-States, <=50K 52, Private, 338816, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 45, United-States, >50K 21, Private, 197387, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, United-States, <=50K 31, Private, 42485, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 55, United-States, <=50K 29, Private, 367706, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 24, Private, 102493, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 263746, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 24, United-States, <=50K 47, Private, 115358, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 46, Private, 189680, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 32, ?, 282622, HS-grad, 9, Divorced, ?, Unmarried, White, Female, 0, 0, 28, United-States, <=50K 34, Private, 127651, 10th, 6, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 44, ?, <=50K 63, Private, 230823, 12th, 8, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, Cuba, <=50K 21, Private, 300812, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 25, United-States, <=50K 18, Private, 174732, HS-grad, 9, Never-married, Other-service, Other-relative, Black, Male, 0, 0, 36, United-States, <=50K 49, State-gov, 183710, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 81, Self-emp-not-inc, 137018, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 36, Self-emp-inc, 213008, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 47, Private, 357848, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 165799, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 39, Self-emp-not-inc, 188571, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 46, Private, 97883, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 43, Local-gov, 105862, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 1902, 40, United-States, >50K 39, Local-gov, 57424, Bachelors, 13, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 29, Private, 151476, Some-college, 10, Separated, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 129583, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, Black, Female, 0, 0, 16, United-States, <=50K 57, Private, 180920, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 43, United-States, <=50K 38, Self-emp-not-inc, 182416, HS-grad, 9, Never-married, Sales, Unmarried, Black, Female, 0, 0, 42, United-States, <=50K 25, Private, 251915, Bachelors, 13, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 39, Local-gov, 187127, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 69045, Some-college, 10, Never-married, Sales, Not-in-family, Black, Male, 0, 0, 40, Jamaica, <=50K 56, Private, 192869, Masters, 14, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1977, 44, United-States, >50K 39, Private, 74163, 12th, 8, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 60847, Assoc-voc, 11, Never-married, Sales, Unmarried, White, Female, 0, 0, 60, United-States, <=50K 17, ?, 213055, 11th, 7, Never-married, ?, Not-in-family, Other, Female, 0, 0, 20, United-States, <=50K 67, Self-emp-not-inc, 116057, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 3273, 0, 16, United-States, <=50K 41, Private, 82393, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 50, United-States, <=50K 24, Local-gov, 134181, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 50, United-States, <=50K 51, Private, 159910, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, Black, Male, 10520, 0, 40, United-States, >50K 30, Self-emp-inc, 117570, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 47, Self-emp-inc, 214169, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 15024, 0, 40, United-States, >50K 56, Private, 56331, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 32, United-States, <=50K 51, Private, 35576, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 57, Self-emp-not-inc, 149168, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, <=50K 34, Private, 157165, Some-college, 10, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 278130, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 257200, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 283122, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Private, 580248, HS-grad, 9, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 230054, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 58, Private, 519006, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 52, United-States, <=50K 19, ?, 37332, HS-grad, 9, Never-married, ?, Own-child, White, Female, 1055, 0, 12, United-States, <=50K 19, ?, 365871, 7th-8th, 4, Never-married, ?, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 68, State-gov, 235882, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 2377, 60, United-States, >50K 43, Private, 336513, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 40, United-States, >50K 17, Private, 115551, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 53, State-gov, 50048, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 50, United-States, >50K 37, Self-emp-inc, 382802, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 99, United-States, >50K 21, ?, 180303, Bachelors, 13, Never-married, ?, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 25, ?, <=50K 63, Private, 106023, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 332379, Some-college, 10, Married-spouse-absent, Transport-moving, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 29, Private, 95465, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Local-gov, 96102, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 1887, 40, United-States, >50K 27, Private, 36440, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 65, United-States, >50K 25, Self-emp-not-inc, 209384, HS-grad, 9, Never-married, Other-service, Other-relative, White, Male, 0, 0, 32, United-States, <=50K 28, Private, 50814, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 54, Private, 143865, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 74, ?, 104661, Some-college, 10, Widowed, ?, Not-in-family, White, Female, 0, 0, 12, United-States, <=50K 31, Local-gov, 50442, Some-college, 10, Never-married, Exec-managerial, Own-child, Amer-Indian-Eskimo, Female, 0, 0, 32, United-States, <=50K 23, Private, 236601, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 19, Private, 100999, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 30, United-States, <=50K 39, ?, 362685, Preschool, 1, Widowed, ?, Not-in-family, White, Female, 0, 0, 20, El-Salvador, <=50K 61, Self-emp-not-inc, 32423, HS-grad, 9, Married-civ-spouse, Farming-fishing, Wife, White, Female, 22040, 0, 40, United-States, <=50K 59, ?, 154236, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 7688, 0, 40, United-States, >50K 27, Self-emp-inc, 153546, Assoc-voc, 11, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 36, United-States, >50K 19, Private, 182355, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 20, United-States, <=50K 23, ?, 191444, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Local-gov, 44216, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 35, United-States, <=50K 40, Private, 97688, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 48, United-States, >50K 53, Private, 209022, 11th, 7, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 37, United-States, <=50K 32, Private, 96016, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 72, Self-emp-not-inc, 52138, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 2392, 25, United-States, >50K 61, Private, 159046, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 138634, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 130125, 10th, 6, Never-married, Other-service, Own-child, Amer-Indian-Eskimo, Female, 1055, 0, 20, United-States, <=50K 73, Private, 247355, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 16, Canada, <=50K 41, Self-emp-not-inc, 227065, Some-college, 10, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 244771, Some-college, 10, Never-married, Machine-op-inspct, Own-child, Black, Female, 0, 0, 20, Jamaica, <=50K 23, Private, 215616, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, Canada, <=50K 65, Private, 386672, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 15, United-States, <=50K 45, Self-emp-inc, 177543, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 50, United-States, <=50K 52, Federal-gov, 617021, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, Black, Male, 7688, 0, 40, United-States, >50K 24, Local-gov, 117109, Bachelors, 13, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 27, United-States, <=50K 23, Private, 373550, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 19847, Some-college, 10, Divorced, Tech-support, Own-child, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 189590, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Self-emp-not-inc, 58343, HS-grad, 9, Divorced, Farming-fishing, Unmarried, White, Male, 0, 0, 56, United-States, <=50K 17, Private, 354201, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 119422, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 363405, HS-grad, 9, Separated, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 63, Private, 181863, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 27, United-States, <=50K 27, Private, 194472, HS-grad, 9, Never-married, Priv-house-serv, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 31, Private, 247328, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 3137, 0, 40, Mexico, <=50K 71, Self-emp-not-inc, 130731, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 35, Private, 236910, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 44, Private, 378251, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 38, United-States, <=50K 36, Private, 120760, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, China, <=50K 22, Private, 203182, Bachelors, 13, Never-married, Exec-managerial, Other-relative, White, Female, 0, 0, 20, United-States, <=50K 32, Private, 130304, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1485, 48, United-States, <=50K 30, Local-gov, 352542, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 60, ?, 191024, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 197728, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 76, Private, 316185, 7th-8th, 4, Widowed, Protective-serv, Not-in-family, White, Female, 0, 0, 12, United-States, <=50K 41, Private, 89226, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 292353, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, Other, Male, 0, 0, 40, United-States, <=50K 45, Private, 304570, 12th, 8, Married-civ-spouse, Machine-op-inspct, Husband, Asian-Pac-Islander, Male, 0, 0, 40, ?, <=50K 32, Private, 180296, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 361487, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 218490, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 1848, 40, United-States, >50K 63, Self-emp-not-inc, 231777, Bachelors, 13, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 189832, Assoc-acdm, 12, Never-married, Transport-moving, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 61, Private, 232308, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, State-gov, 33308, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 333677, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, <=50K 33, Private, 170651, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 1055, 0, 40, United-States, <=50K 39, Private, 343403, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 36, United-States, <=50K 53, Private, 166386, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Wife, Asian-Pac-Islander, Female, 0, 0, 40, China, <=50K 26, Federal-gov, 48099, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 143062, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 32, United-States, <=50K 18, Private, 104704, HS-grad, 9, Never-married, Adm-clerical, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 34, Private, 30497, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 60, United-States, >50K 44, State-gov, 174325, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 7688, 0, 40, United-States, >50K 31, Private, 286675, HS-grad, 9, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 50, United-States, <=50K 44, Private, 59474, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Private, 378384, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 60, United-States, >50K 43, Private, 245842, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 44, Mexico, <=50K 33, Private, 274222, Bachelors, 13, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 7688, 0, 38, United-States, >50K 21, Private, 342575, Some-college, 10, Never-married, Sales, Own-child, Black, Female, 0, 0, 30, United-States, <=50K 30, Private, 206051, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, >50K 55, Private, 234213, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 57, Private, 145189, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 233490, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 32, Private, 344129, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 62, Self-emp-not-inc, 171315, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 31, Self-emp-not-inc, 181485, Bachelors, 13, Never-married, Sales, Not-in-family, Black, Male, 0, 0, 40, United-States, >50K 51, Private, 255412, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, France, >50K 37, Private, 262409, Masters, 14, Divorced, Exec-managerial, Unmarried, White, Female, 0, 213, 45, United-States, <=50K 45, Private, 199590, 5th-6th, 3, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 38, Mexico, <=50K 47, Private, 84726, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, ?, 226883, HS-grad, 9, Divorced, ?, Own-child, White, Male, 0, 0, 75, United-States, <=50K 75, Self-emp-not-inc, 184335, 11th, 7, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 30, United-States, <=50K 43, Private, 102025, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Other, Male, 0, 0, 50, United-States, <=50K 39, Private, 183898, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 7688, 0, 60, Germany, >50K 30, Private, 55291, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 150025, 5th-6th, 3, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, Guatemala, <=50K 44, Private, 100584, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 53, Local-gov, 181755, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 35, United-States, >50K 40, Private, 150528, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 107277, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 33, Private, 247205, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 40, England, <=50K 20, Private, 291979, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 270985, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 50, United-States, <=50K 48, Private, 62605, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 46, Self-emp-not-inc, 176863, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 53197, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Self-emp-not-inc, 267776, HS-grad, 9, Never-married, Other-service, Other-relative, White, Female, 0, 0, 30, United-States, <=50K 24, Private, 308205, 7th-8th, 4, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 30, Private, 306383, Some-college, 10, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 70, Private, 35494, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 30, United-States, <=50K 26, Private, 291968, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 44, United-States, <=50K 34, Private, 80933, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1672, 40, United-States, <=50K 46, Private, 271828, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 70, Private, 121993, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 5, United-States, <=50K 37, Local-gov, 31023, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Self-emp-not-inc, 36425, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 23, Private, 407684, 9th, 5, Never-married, Machine-op-inspct, Other-relative, White, Female, 0, 0, 40, Mexico, <=50K 28, Private, 241895, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 1628, 40, United-States, <=50K 44, Self-emp-not-inc, 158555, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 58, Private, 140363, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 3325, 0, 30, United-States, <=50K 53, Private, 123429, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 23, Private, 40060, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 290286, HS-grad, 9, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 21, ?, 249271, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Local-gov, 106169, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 43, Private, 76487, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 437994, Some-college, 10, Never-married, Other-service, Other-relative, Black, Male, 0, 0, 20, United-States, <=50K 41, Private, 113555, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Amer-Indian-Eskimo, Male, 7298, 0, 50, United-States, >50K 36, Private, 160120, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Vietnam, <=50K 41, Local-gov, 343079, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 1740, 20, United-States, <=50K 27, Private, 406662, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 4416, 0, 40, United-States, <=50K 42, Self-emp-not-inc, 37618, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 27, Private, 114158, Assoc-voc, 11, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 35, United-States, <=50K 41, Private, 115562, HS-grad, 9, Divorced, Protective-serv, Own-child, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 353994, Bachelors, 13, Married-civ-spouse, Exec-managerial, Other-relative, Asian-Pac-Islander, Female, 0, 0, 40, China, >50K 21, Private, 344891, Some-college, 10, Never-married, Adm-clerical, Own-child, Asian-Pac-Islander, Male, 0, 0, 20, United-States, <=50K 44, Private, 286750, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 50, United-States, >50K 29, Private, 194197, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 19, Self-emp-not-inc, 206599, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 22, United-States, <=50K 21, Local-gov, 596776, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, Guatemala, <=50K 46, Private, 56841, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 112561, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 43, Private, 147110, Some-college, 10, Never-married, Adm-clerical, Unmarried, White, Male, 0, 0, 48, United-States, >50K 54, Self-emp-inc, 175339, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 38, Private, 234901, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 60, United-States, >50K 18, ?, 298133, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 217083, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 30, Private, 97757, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 36, United-States, >50K 30, Private, 151868, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Local-gov, 25864, HS-grad, 9, Never-married, Exec-managerial, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 35, United-States, <=50K 26, Private, 109419, Assoc-voc, 11, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 37, Federal-gov, 203070, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 43, United-States, <=50K 32, Private, 107843, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 5178, 0, 50, United-States, >50K 64, State-gov, 264544, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 5, United-States, >50K 18, Private, 148644, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 28, United-States, <=50K 30, Private, 125762, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 30, United-States, <=50K 36, ?, 53606, Assoc-voc, 11, Married-civ-spouse, ?, Wife, White, Female, 3908, 0, 8, United-States, <=50K 18, Private, 193741, 11th, 7, Never-married, Other-service, Other-relative, Black, Male, 0, 0, 30, United-States, <=50K 27, Private, 588905, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 115613, 9th, 5, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, State-gov, 222374, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 43, United-States, >50K 37, Private, 185359, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 173647, Some-college, 10, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 31166, HS-grad, 9, Divorced, Prof-specialty, Not-in-family, Other, Female, 0, 0, 30, Germany, <=50K 22, ?, 517995, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 0, 40, Mexico, <=50K 25, Self-emp-not-inc, 189027, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 30, United-States, <=50K 38, Private, 296125, HS-grad, 9, Separated, Priv-house-serv, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 32, ?, 640383, Bachelors, 13, Divorced, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 334291, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 56, Private, 318450, Masters, 14, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 80, United-States, >50K 29, Private, 174163, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 119721, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 142719, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 162593, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 46, Self-emp-not-inc, 236852, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 28, Local-gov, 154863, HS-grad, 9, Never-married, Protective-serv, Other-relative, Black, Male, 0, 1876, 40, United-States, <=50K 39, Private, 168894, Bachelors, 13, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 42, Self-emp-not-inc, 344920, Some-college, 10, Married-civ-spouse, Farming-fishing, Wife, White, Female, 0, 0, 50, United-States, <=50K 39, Private, 33355, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 7298, 0, 48, United-States, >50K 68, ?, 196782, 7th-8th, 4, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 30, United-States, <=50K 37, Self-emp-inc, 291518, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 15024, 0, 55, United-States, >50K 57, Private, 170244, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 369549, Some-college, 10, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 30, United-States, <=50K 24, Private, 23438, Assoc-voc, 11, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 30, United-States, >50K 19, Private, 202673, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 50, United-States, <=50K 55, Private, 171780, Assoc-acdm, 12, Divorced, Sales, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 37, Local-gov, 264503, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Local-gov, 244341, Some-college, 10, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 28, Private, 209109, Bachelors, 13, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 50, United-States, <=50K 27, Private, 187392, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 40, State-gov, 119578, Bachelors, 13, Never-married, Prof-specialty, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 51, Private, 195105, HS-grad, 9, Divorced, Priv-house-serv, Own-child, White, Female, 0, 0, 40, United-States, <=50K 52, Private, 101752, Assoc-voc, 11, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 56, United-States, <=50K 74, ?, 95825, Some-college, 10, Widowed, ?, Not-in-family, White, Female, 0, 0, 3, United-States, <=50K 49, Self-emp-inc, 362654, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 20, ?, 29810, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 40, Federal-gov, 77332, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 80, Private, 87518, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 1816, 60, United-States, <=50K 63, Private, 113324, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 63, Private, 96299, HS-grad, 9, Divorced, Transport-moving, Unmarried, White, Male, 0, 0, 45, United-States, >50K 51, Private, 237729, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 200973, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 66, Self-emp-not-inc, 212456, HS-grad, 9, Widowed, Craft-repair, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 33, Self-emp-not-inc, 131568, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 66, United-States, <=50K 49, Private, 185859, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 43, United-States, <=50K 20, Private, 231981, Some-college, 10, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 32, United-States, <=50K 33, Self-emp-inc, 117963, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1887, 60, United-States, >50K 26, Private, 78172, Some-college, 10, Married-AF-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 164135, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 33, Private, 171216, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 47, Private, 140664, Bachelors, 13, Divorced, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 23, Private, 249277, HS-grad, 9, Never-married, Exec-managerial, Own-child, Black, Male, 0, 0, 75, United-States, <=50K 53, Federal-gov, 117847, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 52372, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 26, Federal-gov, 95806, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 3325, 0, 40, United-States, <=50K 53, Private, 137428, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, >50K 65, Private, 169047, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 10, United-States, <=50K 68, Private, 339168, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 30, United-States, <=50K 30, Private, 504725, 10th, 6, Never-married, Sales, Other-relative, White, Male, 0, 0, 18, Guatemala, <=50K 28, Private, 132870, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 54, Local-gov, 135840, 10th, 6, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 45, United-States, <=50K 30, Private, 35644, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 10, United-States, <=50K 22, Private, 198148, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 50, United-States, <=50K 25, Private, 220098, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, United-States, <=50K 19, Private, 262515, 11th, 7, Never-married, Other-service, Other-relative, White, Male, 0, 0, 20, United-States, <=50K 19, ?, 423863, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 35, United-States, <=50K 32, Federal-gov, 111567, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Private, 194096, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 51, Local-gov, 420917, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, <=50K 25, Private, 197871, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 44, United-States, >50K 46, Local-gov, 253116, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 38, Private, 206535, Some-college, 10, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 26, State-gov, 70447, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, >50K 46, Private, 201217, HS-grad, 9, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 209970, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 196745, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 594, 0, 16, United-States, <=50K 29, Local-gov, 175262, Masters, 14, Married-civ-spouse, Prof-specialty, Other-relative, White, Male, 0, 0, 35, United-States, <=50K 51, Self-emp-inc, 304955, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 40, Private, 181265, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 52, United-States, <=50K 24, Private, 200973, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 24, Self-emp-not-inc, 37440, Bachelors, 13, Never-married, Farming-fishing, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 31, Private, 395170, Assoc-voc, 11, Married-civ-spouse, Other-service, Wife, Amer-Indian-Eskimo, Female, 0, 0, 24, Mexico, <=50K 54, ?, 32385, HS-grad, 9, Divorced, ?, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 34, Private, 353213, Assoc-acdm, 12, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 19, Private, 38619, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 66, United-States, <=50K 21, Private, 177711, HS-grad, 9, Never-married, Transport-moving, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 21, Private, 190761, 10th, 6, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 70, United-States, <=50K 23, Private, 27776, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 24, United-States, <=50K 37, Federal-gov, 470663, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 71738, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 46, United-States, >50K 57, Private, 74156, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 30, United-States, <=50K 48, Private, 202467, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1485, 40, United-States, >50K 24, Private, 123983, 11th, 7, Married-civ-spouse, Transport-moving, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Vietnam, <=50K 43, Private, 193494, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, ?, 169886, Bachelors, 13, Never-married, ?, Not-in-family, White, Female, 0, 0, 20, ?, <=50K 40, Private, 130571, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 52, Self-emp-inc, 90363, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 35, United-States, >50K 49, Private, 83444, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 45, Self-emp-not-inc, 239093, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Amer-Indian-Eskimo, Male, 3137, 0, 40, United-States, <=50K 62, Local-gov, 151369, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 56630, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 117095, HS-grad, 9, Separated, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 55, Federal-gov, 189985, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 20, ?, 34862, Some-college, 10, Never-married, ?, Own-child, Amer-Indian-Eskimo, Male, 0, 0, 72, United-States, <=50K 37, Self-emp-inc, 126675, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 43, State-gov, 199806, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Private, 57596, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 103459, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, >50K 28, Private, 282398, Some-college, 10, Separated, Tech-support, Unmarried, White, Male, 0, 0, 40, United-States, >50K 38, Private, 298841, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 45, Private, 33300, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 1977, 50, United-States, >50K 22, ?, 306031, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 306467, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 20, Private, 189888, 12th, 8, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 60, Private, 83861, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 117393, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 129934, Some-college, 10, Never-married, Adm-clerical, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, ?, <=50K 51, Private, 179010, Some-college, 10, Divorced, Sales, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 31, Private, 375680, Bachelors, 13, Never-married, Prof-specialty, Unmarried, Black, Female, 0, 0, 40, ?, <=50K 48, Private, 316101, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 293305, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 1887, 40, United-States, >50K 51, Local-gov, 175750, HS-grad, 9, Divorced, Transport-moving, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 41, Private, 121718, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 1848, 48, United-States, >50K 62, ?, 94931, Assoc-voc, 11, Married-civ-spouse, ?, Husband, White, Male, 3411, 0, 40, United-States, <=50K 50, State-gov, 229272, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, >50K 46, Private, 142828, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, >50K 54, Private, 22743, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 15024, 0, 60, United-States, >50K 68, Private, 76371, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 45, United-States, >50K 23, Self-emp-not-inc, 216129, Assoc-acdm, 12, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 49, Private, 107425, Masters, 14, Never-married, Sales, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 24, Private, 611029, 10th, 6, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Local-gov, 363032, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 40, United-States, <=50K 38, Private, 170020, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 3137, 0, 45, United-States, <=50K 34, Private, 137900, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 22, Private, 322674, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 23778, 7th-8th, 4, Separated, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 147845, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 31, United-States, <=50K 36, Private, 175759, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 51, Self-emp-inc, 166459, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 128212, 5th-6th, 3, Married-civ-spouse, Machine-op-inspct, Wife, Asian-Pac-Islander, Female, 0, 0, 40, Vietnam, >50K 54, Federal-gov, 127455, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 48, United-States, >50K 63, Private, 134699, HS-grad, 9, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 51, Private, 254230, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 63, Self-emp-not-inc, 159715, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Local-gov, 116286, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 27, Private, 146719, HS-grad, 9, Divorced, Sales, Own-child, White, Female, 0, 0, 35, United-States, <=50K 35, Private, 361888, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 31, ?, 26553, Bachelors, 13, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 25, United-States, >50K 46, Self-emp-not-inc, 32825, HS-grad, 9, Separated, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 225768, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, >50K 26, Federal-gov, 393728, Some-college, 10, Divorced, Adm-clerical, Own-child, White, Male, 0, 0, 24, United-States, <=50K 43, Private, 160369, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 191807, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 50, United-States, >50K 50, Federal-gov, 176969, HS-grad, 9, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 1590, 40, United-States, <=50K 54, Federal-gov, 33863, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 62, ?, 182687, Some-college, 10, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 45, United-States, >50K 57, State-gov, 141459, Some-college, 10, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 19, ?, 174233, Some-college, 10, Never-married, ?, Own-child, Black, Male, 0, 0, 24, United-States, <=50K 29, Local-gov, 95393, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 20, Private, 221095, HS-grad, 9, Never-married, Craft-repair, Other-relative, Black, Male, 0, 0, 40, United-States, <=50K 53, Private, 104501, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 55, United-States, >50K 18, ?, 437851, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 22, ?, 131230, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 495888, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, El-Salvador, <=50K 69, Private, 185691, 11th, 7, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 20, United-States, <=50K 56, Private, 201822, 7th-8th, 4, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 2002, 40, United-States, <=50K 53, Local-gov, 549341, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 35, United-States, <=50K 28, Private, 247445, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 199566, Bachelors, 13, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 40, United-States, <=50K 33, Self-emp-inc, 139057, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 84, Taiwan, >50K 48, Private, 185039, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 61, Private, 166124, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 49, Private, 82649, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 5013, 0, 45, United-States, <=50K 48, Private, 109275, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 408328, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 186338, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 27, ?, 130856, Bachelors, 13, Never-married, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 251579, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 14, United-States, <=50K 47, Private, 76612, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 25, Private, 22546, Bachelors, 13, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 60, United-States, <=50K 72, Private, 53684, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 40, United-States, <=50K 29, Private, 183627, 11th, 7, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 73203, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 57, Private, 108426, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 48, England, <=50K 50, Private, 116287, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 60, Columbia, <=50K 45, Self-emp-inc, 145697, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 30, United-States, <=50K 52, Private, 326156, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 53, Private, 201127, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 48, United-States, >50K 36, Private, 250791, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 48, United-States, <=50K 46, Private, 328216, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Private, 400443, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 75, Private, 95985, 5th-6th, 3, Widowed, Other-service, Unmarried, Black, Male, 0, 0, 10, United-States, <=50K 32, Local-gov, 127651, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 250679, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 103950, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 17, Private, 200199, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 35, United-States, <=50K 46, State-gov, 295791, Assoc-voc, 11, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 39, Private, 191841, Assoc-acdm, 12, Separated, Prof-specialty, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 38, Private, 82622, Some-college, 10, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 160728, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 60, United-States, <=50K 63, Local-gov, 109849, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Black, Female, 0, 0, 21, United-States, <=50K 28, Private, 339897, 1st-4th, 2, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 43, Mexico, <=50K 28, ?, 37215, Bachelors, 13, Never-married, ?, Own-child, White, Male, 0, 0, 45, United-States, <=50K 49, Private, 371299, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 43, Private, 421837, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 38, Private, 29702, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 39, Private, 117381, HS-grad, 9, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 62, England, <=50K 42, ?, 240027, HS-grad, 9, Divorced, ?, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 40, Private, 338740, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, ?, 28359, HS-grad, 9, Separated, ?, Unmarried, White, Female, 0, 0, 10, United-States, <=50K 29, ?, 315026, HS-grad, 9, Divorced, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 24, Federal-gov, 314525, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 1741, 45, United-States, <=50K 30, Private, 173005, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 50, United-States, >50K 44, Private, 286750, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 40, Private, 163985, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 24, United-States, <=50K 30, Private, 219318, HS-grad, 9, Never-married, Machine-op-inspct, Other-relative, White, Female, 0, 0, 35, Puerto-Rico, <=50K 42, Private, 44121, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 1876, 40, United-States, <=50K 52, Self-emp-not-inc, 103794, Assoc-voc, 11, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 42, Private, 310632, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, >50K 39, Private, 153976, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 52, United-States, >50K 43, Private, 174575, Some-college, 10, Divorced, Prof-specialty, Unmarried, White, Male, 0, 0, 45, United-States, <=50K 62, Self-emp-not-inc, 82388, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 10566, 0, 40, United-States, <=50K 30, Private, 207253, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, England, <=50K 83, ?, 251951, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 39, Private, 746786, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 41, Private, 308296, HS-grad, 9, Married-civ-spouse, Transport-moving, Wife, White, Female, 0, 0, 20, United-States, <=50K 49, Private, 101825, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 1977, 40, United-States, >50K 25, Private, 109009, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 413363, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 2002, 40, United-States, <=50K 59, ?, 117751, Assoc-acdm, 12, Divorced, ?, Not-in-family, White, Male, 0, 0, 8, United-States, <=50K 44, State-gov, 296326, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 208358, 9th, 5, Divorced, Handlers-cleaners, Not-in-family, White, Male, 4650, 0, 56, United-States, <=50K 40, Private, 120277, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, Ireland, <=50K 21, Private, 193219, HS-grad, 9, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 35, Jamaica, <=50K 41, Private, 86399, Some-college, 10, Separated, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 24, Private, 215251, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 67, Self-emp-not-inc, 124470, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 24, Private, 228649, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 38, United-States, <=50K 50, Self-emp-not-inc, 386397, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 48, Private, 96798, Masters, 14, Divorced, Sales, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 55, ?, 106707, Assoc-acdm, 12, Married-civ-spouse, ?, Husband, Black, Male, 0, 0, 20, United-States, >50K 29, Private, 159768, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 3325, 0, 40, Ecuador, <=50K 50, Private, 139464, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 36, Ireland, <=50K 64, State-gov, 550848, 10th, 6, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 49, Private, 68505, 9th, 5, Divorced, Other-service, Not-in-family, Black, Male, 0, 0, 37, United-States, <=50K 20, Private, 122215, HS-grad, 9, Never-married, Other-service, Own-child, Black, Male, 0, 0, 52, United-States, <=50K 30, Private, 159442, HS-grad, 9, Separated, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 80638, Bachelors, 13, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 30, China, <=50K 52, Private, 192390, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 22, Private, 191324, Some-college, 10, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 25, United-States, <=50K 77, ?, 147284, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 14, United-States, <=50K 19, State-gov, 73009, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 15, United-States, <=50K 52, Private, 177858, HS-grad, 9, Divorced, Craft-repair, Other-relative, White, Male, 0, 0, 55, United-States, >50K 42, Private, 163003, Bachelors, 13, Married-spouse-absent, Tech-support, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 35, Private, 95551, HS-grad, 9, Separated, Exec-managerial, Not-in-family, White, Female, 0, 0, 36, United-States, <=50K 27, Private, 125298, Some-college, 10, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 54, State-gov, 198186, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 38, United-States, <=50K 37, Private, 295949, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1628, 40, United-States, <=50K 37, Private, 182668, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 35, United-States, <=50K 28, Private, 124905, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 30, United-States, <=50K 63, Private, 171635, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 376240, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 42, United-States, <=50K 28, Private, 157391, Bachelors, 13, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 23, ?, 114357, Some-college, 10, Never-married, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 178134, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 31, Private, 207201, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 124483, Bachelors, 13, Never-married, Sales, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 50, ?, >50K 64, Private, 102103, HS-grad, 9, Divorced, Priv-house-serv, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 40, Private, 92036, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, >50K 59, Local-gov, 236426, Assoc-acdm, 12, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 22, Private, 400966, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 404573, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 44, United-States, <=50K 35, Private, 227571, 7th-8th, 4, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Mexico, <=50K 20, Private, 145917, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 15, United-States, <=50K 35, Local-gov, 190226, HS-grad, 9, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 356555, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 48, United-States, <=50K 28, Private, 66473, HS-grad, 9, Divorced, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 37, ?, 172256, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 20, United-States, <=50K 72, ?, 118902, Doctorate, 16, Married-civ-spouse, ?, Husband, White, Male, 0, 2392, 6, United-States, >50K 25, Self-emp-inc, 163039, Assoc-acdm, 12, Never-married, Sales, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 37, Private, 89559, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 19, ?, 35507, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 45, United-States, <=50K 31, Private, 163303, Assoc-voc, 11, Divorced, Sales, Own-child, White, Female, 0, 0, 38, United-States, <=50K 41, Private, 192712, HS-grad, 9, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 381153, 10th, 6, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 44, Private, 222434, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 34706, Some-college, 10, Never-married, Exec-managerial, Not-in-family, Black, Male, 0, 0, 47, United-States, <=50K 57, Self-emp-not-inc, 47857, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 26, Private, 195216, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 12, United-States, <=50K 44, Self-emp-inc, 103643, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 5013, 0, 60, Greece, <=50K 29, Local-gov, 329426, HS-grad, 9, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 183612, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 40, United-States, >50K 40, Private, 184105, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 21, Private, 211385, Assoc-acdm, 12, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 35, Jamaica, <=50K 21, Private, 61777, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 34, Self-emp-not-inc, 320194, Prof-school, 15, Separated, Prof-specialty, Unmarried, White, Male, 0, 0, 48, United-States, >50K 24, Private, 199444, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 15, United-States, <=50K 28, Private, 312588, 10th, 6, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 168675, HS-grad, 9, Separated, Transport-moving, Own-child, White, Male, 0, 0, 50, United-States, <=50K 35, Private, 87556, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, State-gov, 220421, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 44, Federal-gov, 404599, HS-grad, 9, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 39, Private, 99065, Bachelors, 13, Married-civ-spouse, Handlers-cleaners, Wife, White, Female, 0, 0, 40, Poland, >50K 57, Local-gov, 109973, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 246652, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 57423, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, <=50K 23, Private, 291248, HS-grad, 9, Never-married, Machine-op-inspct, Other-relative, Black, Male, 0, 0, 40, United-States, <=50K 50, Private, 163708, HS-grad, 9, Widowed, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 51, Self-emp-not-inc, 240358, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 20, United-States, <=50K 28, Private, 25955, Assoc-voc, 11, Divorced, Craft-repair, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 44, Private, 101593, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 29, Self-emp-not-inc, 227890, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 31, Private, 225053, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 27, Private, 228472, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 34, Private, 245378, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 50, Self-emp-inc, 156623, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 7688, 0, 50, Philippines, >50K 27, Private, 35032, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 258849, Assoc-voc, 11, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 46, Private, 190115, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 63910, Some-college, 10, Never-married, Adm-clerical, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 40, Private, 510072, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, >50K 28, Private, 210867, 11th, 7, Divorced, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 263024, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 306785, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 58, Self-emp-inc, 104333, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 66, Private, 340734, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Self-emp-not-inc, 288585, HS-grad, 9, Married-civ-spouse, Other-service, Wife, Asian-Pac-Islander, Female, 0, 0, 20, South, <=50K 38, Private, 241765, 11th, 7, Divorced, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 25, Private, 111058, Assoc-acdm, 12, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 104662, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 22, United-States, <=50K 90, Private, 313986, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 41, Local-gov, 52037, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 34, ?, 146589, HS-grad, 9, Never-married, ?, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 33, Private, 131776, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 914, 0, 40, Germany, <=50K 33, Private, 254221, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 152909, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1887, 45, United-States, >50K 39, Self-emp-not-inc, 211785, HS-grad, 9, Never-married, Craft-repair, Own-child, Black, Female, 0, 0, 20, United-States, <=50K 59, Private, 160362, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 19, Private, 387215, Some-college, 10, Never-married, Tech-support, Own-child, White, Male, 0, 1719, 16, United-States, <=50K 39, Private, 187046, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 4064, 0, 38, United-States, <=50K 19, ?, 208874, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 169631, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 40, United-States, <=50K 52, Private, 202956, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 59, Self-emp-not-inc, 80467, HS-grad, 9, Divorced, Other-service, Own-child, White, Female, 0, 0, 24, United-States, <=50K 28, Private, 407672, Some-college, 10, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 243425, HS-grad, 9, Divorced, Other-service, Other-relative, White, Female, 0, 0, 50, Peru, <=50K 50, ?, 174964, 10th, 6, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 99, United-States, <=50K 36, Private, 347491, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 34, Private, 146161, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 23, Private, 449432, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 19, ?, 175499, 11th, 7, Never-married, ?, Own-child, White, Female, 0, 0, 30, United-States, <=50K 33, Private, 288825, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 2258, 84, United-States, <=50K 27, Local-gov, 134813, Masters, 14, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 52, United-States, <=50K 31, Local-gov, 190401, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 260617, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 36, United-States, <=50K 31, Private, 45604, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 54, United-States, <=50K 59, Private, 67841, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Local-gov, 244522, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 48, United-States, >50K 19, Private, 430471, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 194698, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 34, Private, 94235, Bachelors, 13, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 188330, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 78, United-States, <=50K 51, Local-gov, 146181, 9th, 5, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 21, Private, 177125, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 30, Self-emp-inc, 68330, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 46, Private, 95636, Some-college, 10, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 40, Private, 238329, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 52, Private, 416129, Preschool, 1, Married-civ-spouse, Other-service, Not-in-family, White, Male, 0, 0, 40, El-Salvador, <=50K 23, Private, 285004, Bachelors, 13, Never-married, Sales, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 50, Taiwan, <=50K 90, ?, 256514, Bachelors, 13, Widowed, ?, Other-relative, White, Female, 991, 0, 10, United-States, <=50K 25, Private, 186294, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 43, Private, 188786, Some-college, 10, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 38, State-gov, 31352, Some-college, 10, Divorced, Protective-serv, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, >50K 22, Private, 197613, Assoc-voc, 11, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 33, Local-gov, 161942, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 1055, 0, 40, United-States, <=50K 34, Private, 275438, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 5178, 0, 40, United-States, >50K 65, Private, 361721, Assoc-voc, 11, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 20, United-States, <=50K 50, Private, 144968, HS-grad, 9, Never-married, Tech-support, Own-child, White, Male, 0, 0, 15, United-States, <=50K 29, Private, 190539, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 6849, 0, 48, United-States, <=50K 25, Private, 178037, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 306985, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 87928, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 44, Private, 242619, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 154165, 9th, 5, Divorced, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 511331, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 65, Local-gov, 221026, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 20, United-States, <=50K 56, Self-emp-not-inc, 222182, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 45, United-States, <=50K 39, Self-emp-not-inc, 126569, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 60, United-States, >50K 23, Private, 202344, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 190423, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 24, Private, 238917, 5th-6th, 3, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, El-Salvador, <=50K 41, Private, 221947, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1887, 50, United-States, >50K 40, Self-emp-inc, 37997, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 55, Private, 147098, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 38, Private, 278253, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 48, United-States, <=50K 23, Private, 195411, HS-grad, 9, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 44, Private, 76196, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 45, Private, 120131, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1887, 40, United-States, >50K 20, Self-emp-not-inc, 186014, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 12, Germany, <=50K 29, Private, 205903, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 43, State-gov, 125405, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 219838, 12th, 8, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, State-gov, 19395, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 31, Private, 223327, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 52, Private, 114062, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 95654, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 50, Iran, >50K 38, Private, 177305, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 66, ?, 299616, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 63, Self-emp-not-inc, 117681, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 237651, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 35, United-States, <=50K 33, State-gov, 150570, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 46, State-gov, 106705, Some-college, 10, Divorced, Prof-specialty, Unmarried, White, Female, 1506, 0, 50, United-States, <=50K 20, ?, 174714, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 20, United-States, <=50K 47, Self-emp-inc, 175958, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 3325, 0, 60, United-States, <=50K 33, Private, 144064, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 66, ?, 107112, 7th-8th, 4, Never-married, ?, Other-relative, Black, Male, 0, 0, 30, United-States, <=50K 20, Private, 54152, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 30, ?, <=50K 28, Private, 152951, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 190487, HS-grad, 9, Divorced, Priv-house-serv, Unmarried, White, Female, 0, 0, 28, Ecuador, <=50K 25, Private, 306666, Some-college, 10, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 45, United-States, <=50K 37, Private, 195148, HS-grad, 9, Married-civ-spouse, Craft-repair, Own-child, White, Male, 3137, 0, 40, United-States, <=50K 31, Self-emp-not-inc, 226624, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 49, Private, 157569, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, State-gov, 22966, Some-college, 10, Married-spouse-absent, Tech-support, Unmarried, White, Male, 0, 0, 20, United-States, <=50K 52, Private, 379682, Assoc-voc, 11, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 20, United-States, >50K 29, Private, 446559, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 50, United-States, <=50K 18, Private, 41794, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 31, Local-gov, 90409, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 35, United-States, <=50K 23, Private, 125491, Some-college, 10, Never-married, Other-service, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 35, Vietnam, <=50K 27, ?, 129661, Assoc-voc, 11, Married-civ-spouse, ?, Wife, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, >50K 54, Self-emp-not-inc, 104748, 10th, 6, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 65, United-States, <=50K 50, Local-gov, 169182, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 49, Dominican-Republic, <=50K 46, Private, 324655, Masters, 14, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 1902, 40, ?, >50K 24, Private, 122272, Bachelors, 13, Never-married, Farming-fishing, Own-child, White, Female, 0, 0, 40, United-States, <=50K 17, ?, 114798, 11th, 7, Never-married, ?, Own-child, White, Female, 0, 0, 18, United-States, <=50K 49, Self-emp-inc, 289707, HS-grad, 9, Separated, Other-service, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 54, Local-gov, 137691, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Private, 84610, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 60, United-States, >50K 49, Private, 166789, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Local-gov, 348728, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 23, Private, 348092, HS-grad, 9, Never-married, Transport-moving, Own-child, Black, Male, 0, 0, 40, Haiti, <=50K 63, Private, 154526, Some-college, 10, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 67, Private, 288371, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, Canada, >50K 23, Private, 182342, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 244366, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 66, Private, 102423, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 30, United-States, <=50K 25, Private, 259688, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 30, Private, 98733, Some-college, 10, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 35, Private, 174856, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 2885, 0, 40, United-States, <=50K 67, Self-emp-not-inc, 141797, 7th-8th, 4, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 327202, 12th, 8, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 26, Private, 76996, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 38, United-States, <=50K 34, Private, 260560, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 370990, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 129010, 12th, 8, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 10, United-States, <=50K 21, Private, 452640, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 76, Self-emp-inc, 120796, 9th, 5, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Federal-gov, 45334, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, Asian-Pac-Islander, Male, 0, 0, 70, ?, <=50K 26, Private, 229523, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 56, United-States, <=50K 18, Private, 127388, 12th, 8, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 18, ?, 395567, 11th, 7, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 119422, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 1672, 50, United-States, <=50K 59, Private, 193895, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 55, Private, 163083, Bachelors, 13, Separated, Exec-managerial, Not-in-family, White, Male, 14084, 0, 45, United-States, >50K 33, Self-emp-not-inc, 155343, Some-college, 10, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 72, United-States, <=50K 25, Private, 73895, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 10, United-States, <=50K 48, Private, 107682, HS-grad, 9, Widowed, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 10, United-States, <=50K 64, Private, 321166, Bachelors, 13, Divorced, Sales, Not-in-family, White, Female, 0, 0, 5, United-States, <=50K 47, Local-gov, 154940, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, >50K 26, Private, 103700, Some-college, 10, Never-married, Tech-support, Own-child, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 63509, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 48, United-States, >50K 21, Private, 243842, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, ?, 187221, 7th-8th, 4, Never-married, ?, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 30, Private, 58597, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 44, United-States, <=50K 41, Self-emp-not-inc, 190290, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 53, ?, 158352, Masters, 14, Never-married, ?, Not-in-family, White, Female, 8614, 0, 35, United-States, >50K 34, Private, 62165, Some-college, 10, Never-married, Sales, Other-relative, Black, Male, 0, 0, 30, United-States, <=50K 20, ?, 307149, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 35, United-States, <=50K 24, Private, 280134, 10th, 6, Never-married, Sales, Not-in-family, White, Male, 0, 0, 49, El-Salvador, <=50K 26, Private, 118736, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 25, Private, 171114, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 35, Private, 169638, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 0, 36, United-States, <=50K 41, Private, 125461, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 33, Private, 145434, 11th, 7, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 152182, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 27, Self-emp-inc, 233724, HS-grad, 9, Separated, Adm-clerical, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 32, Private, 153963, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 51, Local-gov, 88120, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 38, Private, 96330, Assoc-voc, 11, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 41, Local-gov, 66118, Some-college, 10, Married-civ-spouse, Transport-moving, Wife, White, Female, 0, 0, 25, United-States, <=50K 26, Private, 182178, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 2829, 0, 40, United-States, <=50K 38, Self-emp-not-inc, 53628, Assoc-voc, 11, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 35, United-States, <=50K 54, Private, 174865, 9th, 5, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 30, Private, 66194, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 60, Outlying-US(Guam-USVI-etc), <=50K 31, Private, 73796, Some-college, 10, Widowed, Exec-managerial, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 26, State-gov, 28366, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 75, Self-emp-not-inc, 231741, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 4931, 0, 3, United-States, <=50K 29, Private, 237865, Masters, 14, Never-married, Transport-moving, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 61, Private, 195453, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 24, Private, 116934, Some-college, 10, Separated, Sales, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 22, ?, 87867, 12th, 8, Never-married, ?, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 34, Private, 456399, Assoc-acdm, 12, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 263608, Some-college, 10, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 263498, 11th, 7, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Self-emp-not-inc, 183765, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, ?, <=50K 27, Federal-gov, 469705, HS-grad, 9, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 1980, 40, United-States, <=50K 39, Local-gov, 113253, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 50, United-States, >50K 20, Private, 138768, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 302146, 11th, 7, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 68, Private, 253866, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 30, United-States, <=50K 28, Federal-gov, 214858, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 48, United-States, <=50K 43, Private, 243476, HS-grad, 9, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 169104, Some-college, 10, Married-spouse-absent, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 103218, HS-grad, 9, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 41, Private, 57233, Bachelors, 13, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 228320, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 45, United-States, >50K 20, Private, 217421, HS-grad, 9, Married-civ-spouse, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 185041, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 75, United-States, >50K 27, Self-emp-not-inc, 37302, Assoc-acdm, 12, Married-civ-spouse, Transport-moving, Husband, White, Male, 7688, 0, 70, United-States, >50K 32, Private, 261059, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 46, Private, 59767, Some-college, 10, Divorced, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 26, Private, 333541, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 24, United-States, <=50K 20, Private, 133352, Some-college, 10, Never-married, Adm-clerical, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, Vietnam, <=50K 36, Private, 99270, HS-grad, 9, Married-civ-spouse, Farming-fishing, Wife, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 204629, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Private, 34104, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 3103, 0, 55, United-States, >50K 32, Private, 312667, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 50, United-States, >50K 49, Private, 329603, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1902, 40, United-States, >50K 36, Private, 281021, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 22, Private, 275385, Some-college, 10, Never-married, Other-service, Other-relative, White, Male, 0, 0, 25, United-States, <=50K 52, Federal-gov, 129177, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 385591, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 22, ?, 201179, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 72, Private, 38360, HS-grad, 9, Widowed, Other-service, Unmarried, White, Female, 0, 0, 16, United-States, <=50K 30, Local-gov, 73796, Bachelors, 13, Separated, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 67671, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 257621, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 22, Private, 180052, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 20, United-States, <=50K 59, Private, 656036, Bachelors, 13, Separated, Adm-clerical, Unmarried, White, Male, 0, 0, 60, United-States, <=50K 46, Private, 215943, HS-grad, 9, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 488720, Assoc-voc, 11, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Mexico, <=50K 64, Federal-gov, 199298, 7th-8th, 4, Widowed, Other-service, Unmarried, White, Female, 0, 0, 30, Puerto-Rico, <=50K 31, Private, 305692, Some-college, 10, Married-civ-spouse, Sales, Wife, Black, Female, 0, 0, 40, United-States, <=50K 64, Private, 114994, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 20, United-States, <=50K 45, Private, 88265, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 59, Private, 168569, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 1887, 40, United-States, >50K 32, Private, 175413, HS-grad, 9, Never-married, Adm-clerical, Other-relative, Black, Female, 0, 0, 40, Jamaica, <=50K 43, Private, 161226, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 66, ?, 160995, 10th, 6, Divorced, ?, Not-in-family, White, Female, 1086, 0, 20, United-States, <=50K 23, Private, 208598, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 49, Self-emp-not-inc, 200471, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 256609, 12th, 8, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 49, Private, 176684, Assoc-voc, 11, Never-married, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 206512, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 212640, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 85, United-States, <=50K 47, Private, 148724, HS-grad, 9, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 40, United-States, <=50K 41, Private, 266510, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 34, Local-gov, 240252, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Private, 358975, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 20, ?, 124242, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 434710, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 25, Private, 204338, HS-grad, 9, Never-married, Farming-fishing, Unmarried, White, Male, 0, 0, 30, ?, <=50K 46, Private, 241844, 9th, 5, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 191342, 1st-4th, 2, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Cambodia, <=50K 41, Private, 221947, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 56, United-States, >50K 44, Private, 111483, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 1504, 50, United-States, <=50K 30, Private, 65278, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 54, Private, 133403, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Self-emp-not-inc, 166416, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 99, United-States, <=50K 58, ?, 142158, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 12, United-States, <=50K 21, Private, 221480, Some-college, 10, Never-married, Tech-support, Own-child, White, Female, 0, 0, 25, Ecuador, <=50K 35, Self-emp-not-inc, 189878, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 278403, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 80, United-States, >50K 19, Private, 184710, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 20, United-States, <=50K 48, Private, 177775, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 56, ?, 275943, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, Nicaragua, <=50K 65, Self-emp-not-inc, 225473, Some-college, 10, Widowed, Craft-repair, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 40, Private, 289403, Bachelors, 13, Separated, Adm-clerical, Unmarried, Black, Male, 0, 0, 35, United-States, <=50K 26, Private, 269060, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 449354, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 214413, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 80058, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 202027, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 27828, 0, 50, United-States, >50K 22, Self-emp-not-inc, 123440, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 37, Private, 191524, Assoc-voc, 11, Separated, Prof-specialty, Own-child, White, Female, 0, 0, 38, United-States, <=50K 25, Private, 308144, Bachelors, 13, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 64, Private, 164204, 1st-4th, 2, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 53, ?, <=50K 46, Private, 205100, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 48, United-States, >50K 30, Private, 195750, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 27, United-States, <=50K 63, Private, 149756, Assoc-acdm, 12, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 51, Local-gov, 240358, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 68, Self-emp-not-inc, 241174, 7th-8th, 4, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 16, United-States, <=50K 36, Private, 356838, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, Canada, <=50K 28, Self-emp-inc, 115705, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 41, Local-gov, 137142, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 296066, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 401335, Some-college, 10, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 33, ?, 182771, Bachelors, 13, Never-married, ?, Own-child, Asian-Pac-Islander, Male, 0, 0, 80, Philippines, <=50K 34, Self-emp-inc, 186824, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 40, United-States, >50K 46, Federal-gov, 162187, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 98010, Some-college, 10, Married-spouse-absent, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 172538, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 52, United-States, >50K 18, Private, 80163, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 33, Local-gov, 43959, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 50, United-States, >50K 51, Private, 162632, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 7298, 0, 60, United-States, >50K 56, Self-emp-not-inc, 115422, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 35, United-States, <=50K 54, Private, 100933, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 270379, HS-grad, 9, Never-married, Exec-managerial, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 40, Private, 20109, Some-college, 10, Divorced, Handlers-cleaners, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 84, United-States, <=50K 53, Private, 114758, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 65, United-States, >50K 22, Private, 100345, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 35, United-States, <=50K 33, Private, 184901, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 87239, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 63, Private, 127363, Some-college, 10, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 12, United-States, <=50K 53, Federal-gov, 199720, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 60, Germany, >50K 37, Private, 143058, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 50, Federal-gov, 36489, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 141698, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 40, Federal-gov, 26358, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 195532, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 8614, 0, 40, United-States, >50K 21, Private, 30039, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 125159, Assoc-acdm, 12, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, Jamaica, <=50K 20, Private, 246250, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Federal-gov, 77370, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 355569, Assoc-voc, 11, Never-married, Exec-managerial, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 32, Private, 180603, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Private, 201785, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 33, Private, 256211, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Asian-Pac-Islander, Male, 0, 0, 40, South, <=50K 27, Private, 146764, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 22, ?, 211968, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, Iran, <=50K 29, Private, 200515, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 38, United-States, <=50K 29, Private, 52636, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 27049, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 20, United-States, <=50K 35, Private, 111128, 10th, 6, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 31, Self-emp-not-inc, 348038, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 50, Puerto-Rico, >50K 33, Private, 93930, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 67, Private, 397831, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1539, 40, United-States, <=50K 46, Private, 33794, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 10, United-States, <=50K 45, Private, 178215, 9th, 5, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, United-States, >50K 17, Local-gov, 191910, 11th, 7, Never-married, Sales, Own-child, White, Male, 0, 0, 20, United-States, <=50K 35, Private, 340110, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1848, 70, United-States, >50K 48, Self-emp-not-inc, 133694, Bachelors, 13, Married-spouse-absent, Exec-managerial, Not-in-family, Black, Male, 0, 0, 40, Jamaica, >50K 49, Private, 148398, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 20, Private, 133515, Some-college, 10, Never-married, Sales, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 181667, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 5013, 0, 46, Canada, <=50K 64, Private, 159715, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 20, United-States, <=50K 53, Federal-gov, 174040, Some-college, 10, Separated, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 52, Private, 117700, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 37215, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, <=50K 32, Self-emp-inc, 46807, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 99999, 0, 40, United-States, >50K 48, Self-emp-not-inc, 317360, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 20, United-States, >50K 30, Private, 425627, Some-college, 10, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 34, Private, 82623, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 20, United-States, <=50K 19, ?, 63574, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 50, United-States, <=50K 39, Private, 140854, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 28, Private, 185061, 11th, 7, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 160118, 12th, 8, Never-married, Sales, Not-in-family, White, Female, 0, 0, 10, ?, <=50K 54, Private, 282680, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 24, Private, 137591, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 1762, 40, United-States, <=50K 25, Private, 198163, HS-grad, 9, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 132749, 11th, 7, Divorced, Other-service, Unmarried, White, Female, 0, 0, 12, United-States, <=50K 48, Local-gov, 31264, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 5178, 0, 40, United-States, >50K 24, Private, 399449, Bachelors, 13, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 27494, Some-college, 10, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 0, 50, Taiwan, <=50K 47, Private, 368561, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 45, Private, 102096, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, ?, >50K 19, Private, 406078, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 25, United-States, <=50K 52, Self-emp-inc, 100506, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 50, United-States, >50K 52, Private, 29658, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, ?, 20469, HS-grad, 9, Never-married, ?, Other-relative, Asian-Pac-Islander, Female, 0, 0, 12, South, <=50K 60, Private, 181953, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 28, United-States, <=50K 43, Private, 304175, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 24, Private, 170070, Assoc-acdm, 12, Divorced, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 20, ?, 193416, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 194908, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Self-emp-not-inc, 357962, 9th, 5, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 214716, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 10, United-States, <=50K 40, Self-emp-inc, 207578, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, >50K 54, Private, 146409, Some-college, 10, Widowed, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 341643, Bachelors, 13, Never-married, Other-service, Other-relative, White, Male, 0, 0, 50, United-States, <=50K 52, Private, 131631, 11th, 7, Separated, Machine-op-inspct, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 53, Private, 88842, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 40, United-States, >50K 56, ?, 128900, Some-college, 10, Widowed, ?, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 35, Private, 417136, HS-grad, 9, Divorced, Craft-repair, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 43, Self-emp-not-inc, 336763, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 880, 42, United-States, <=50K 29, Private, 209301, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Canada, <=50K 29, Private, 120986, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Amer-Indian-Eskimo, Male, 0, 0, 65, United-States, <=50K 27, Private, 51025, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 58, Private, 218281, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, Mexico, <=50K 64, Private, 114994, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 18, United-States, <=50K 53, Private, 335481, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 0, 32, United-States, <=50K 21, Private, 174503, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 40, Self-emp-not-inc, 230478, Assoc-acdm, 12, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 52, State-gov, 149650, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, Iran, >50K 38, Private, 149419, Assoc-voc, 11, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 40, ?, 341539, Some-college, 10, Divorced, ?, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 39, Private, 185099, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, ?, 132930, Masters, 14, Never-married, ?, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 68, Private, 128472, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 24, Private, 124971, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 40, Self-emp-inc, 344060, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 43, Self-emp-inc, 286750, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 99, United-States, >50K 38, Private, 296999, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 70, United-States, <=50K 45, Private, 123681, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 18, Private, 232024, 11th, 7, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 55, United-States, <=50K 57, Local-gov, 52267, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 49, Private, 119182, HS-grad, 9, Separated, Other-service, Not-in-family, Black, Female, 0, 0, 35, United-States, <=50K 25, Private, 191230, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, Yugoslavia, <=50K 52, Federal-gov, 23780, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 56, Private, 184553, 10th, 6, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 56, United-States, <=50K 26, Self-emp-inc, 242651, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 19, Private, 246226, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, Self-emp-inc, 86745, Bachelors, 13, Never-married, Adm-clerical, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 25, Private, 106889, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 30, United-States, <=50K 21, Private, 460835, HS-grad, 9, Never-married, Sales, Other-relative, White, Male, 0, 0, 45, United-States, <=50K 48, Self-emp-not-inc, 213140, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Italy, <=50K 33, State-gov, 37070, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, Canada, <=50K 31, State-gov, 93589, HS-grad, 9, Divorced, Protective-serv, Own-child, Other, Male, 0, 0, 40, United-States, <=50K 26, Self-emp-not-inc, 213258, HS-grad, 9, Divorced, Farming-fishing, Unmarried, White, Male, 0, 0, 65, United-States, <=50K 37, State-gov, 46814, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 29, ?, 168873, Some-college, 10, Divorced, ?, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 20, Private, 284737, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 28, Private, 309620, Some-college, 10, Married-civ-spouse, Sales, Husband, Other, Male, 0, 0, 60, ?, <=50K 49, Private, 197418, HS-grad, 9, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 73, ?, 132737, 10th, 6, Never-married, ?, Not-in-family, White, Male, 0, 0, 4, United-States, <=50K 49, Private, 185041, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 40, United-States, >50K 51, Private, 159604, Some-college, 10, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 40, Private, 123557, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 275421, Assoc-voc, 11, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 167147, 12th, 8, Never-married, Sales, Own-child, White, Male, 0, 0, 24, United-States, <=50K 41, Private, 197583, 10th, 6, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, >50K 46, Private, 175109, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 1485, 40, United-States, >50K 46, Private, 117502, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 64, Private, 180401, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 50, Self-emp-not-inc, 146603, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 53, State-gov, 143822, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 36, United-States, >50K 21, Private, 51985, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 22, State-gov, 48121, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 25, United-States, <=50K 37, Private, 234807, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Female, 7430, 0, 45, United-States, >50K 39, Federal-gov, 65324, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 55, United-States, >50K 30, Private, 302149, Bachelors, 13, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 0, 40, India, <=50K 25, Private, 168403, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 1741, 40, United-States, <=50K 26, Private, 159897, Some-college, 10, Never-married, Exec-managerial, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 43, Private, 416338, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 59, Private, 370615, HS-grad, 9, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 60, United-States, <=50K 27, Private, 219371, HS-grad, 9, Married-spouse-absent, Adm-clerical, Unmarried, White, Female, 0, 0, 40, Jamaica, <=50K 55, Private, 120970, 10th, 6, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, >50K 20, Private, 22966, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 12, Canada, <=50K 25, Private, 34541, Assoc-voc, 11, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 36, Canada, <=50K 28, Private, 191027, Assoc-acdm, 12, Separated, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 107458, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 60, Private, 121832, 11th, 7, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Local-gov, 233825, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 15024, 0, 50, United-States, >50K 25, Private, 73839, 11th, 7, Divorced, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 109165, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 50, State-gov, 103063, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Self-emp-not-inc, 29762, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 5013, 0, 70, United-States, <=50K 46, Private, 111979, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 47, United-States, <=50K 35, Private, 150125, Assoc-voc, 11, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 21, ?, 301853, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 35, ?, 296738, 11th, 7, Separated, ?, Not-in-family, White, Female, 6849, 0, 60, United-States, <=50K 40, Private, 118001, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 49, Private, 149337, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Private, 36601, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 43, Local-gov, 118600, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 625, 40, United-States, <=50K 39, Private, 279272, Assoc-acdm, 12, Never-married, Transport-moving, Not-in-family, Black, Male, 0, 0, 60, United-States, <=50K 35, Private, 181020, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 60, United-States, <=50K 52, Private, 165998, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 218136, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 40, Outlying-US(Guam-USVI-etc), <=50K 20, Self-emp-inc, 182200, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 30, United-States, <=50K 46, Private, 39363, Some-college, 10, Divorced, Other-service, Unmarried, White, Female, 0, 0, 10, ?, <=50K 24, Private, 140001, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 193260, Bachelors, 13, Married-civ-spouse, Craft-repair, Other-relative, Asian-Pac-Islander, Male, 0, 0, 30, India, <=50K 21, Private, 191243, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 37, Federal-gov, 207887, Bachelors, 13, Divorced, Exec-managerial, Other-relative, White, Female, 0, 0, 50, United-States, <=50K 43, Federal-gov, 211450, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 184759, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 26, United-States, <=50K 47, Private, 197836, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 61, Private, 232308, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, >50K 21, ?, 189888, Assoc-acdm, 12, Never-married, ?, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 35, Private, 301614, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 60, United-States, <=50K 60, Private, 146674, 10th, 6, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, United-States, <=50K 27, Private, 225291, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 57, Local-gov, 148509, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 35, India, <=50K 56, Private, 136413, 1st-4th, 2, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 126060, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 73064, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Wife, Black, Female, 0, 0, 35, United-States, <=50K 19, Private, 39026, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 28, Self-emp-not-inc, 33035, 12th, 8, Divorced, Other-service, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 43, Private, 193494, 10th, 6, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 63, Local-gov, 147440, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 22, ?, 153131, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 64671, HS-grad, 9, Divorced, Handlers-cleaners, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 35, Self-emp-not-inc, 225399, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 8614, 0, 40, United-States, >50K 20, Private, 174391, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 40, United-States, <=50K 48, Private, 377757, 10th, 6, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 70, United-States, <=50K 30, Local-gov, 364310, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Black, Female, 0, 0, 40, Germany, <=50K 31, Private, 110643, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Private, 70240, HS-grad, 9, Never-married, Sales, Own-child, Asian-Pac-Islander, Female, 0, 0, 24, Philippines, <=50K 57, State-gov, 32694, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 41, Private, 95047, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Wife, White, Female, 7688, 0, 44, United-States, >50K 33, Private, 264936, HS-grad, 9, Divorced, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 367329, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 56026, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, >50K 22, Private, 186452, 10th, 6, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 50, Private, 125417, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Wife, Black, Female, 0, 0, 40, United-States, >50K 40, Self-emp-not-inc, 242082, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 37, Private, 31023, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 51, United-States, <=50K 40, ?, 397346, Assoc-acdm, 12, Divorced, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 424079, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 55, United-States, >50K 38, Self-emp-not-inc, 108947, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 7688, 0, 40, United-States, >50K 25, State-gov, 261979, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 55507, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 22, ?, 291407, 12th, 8, Never-married, ?, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 18, Private, 353358, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 16, United-States, <=50K 41, Private, 67339, 11th, 7, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 7688, 0, 40, United-States, >50K 33, Private, 235109, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 208180, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 67, State-gov, 423561, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Self-emp-not-inc, 145290, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 2415, 50, United-States, >50K 24, Private, 403671, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Local-gov, 49325, 7th-8th, 4, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 370494, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 25, Private, 267012, Assoc-voc, 11, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 33, Private, 191856, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 55, Private, 80445, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 379798, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Local-gov, 168387, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 18, Private, 301948, HS-grad, 9, Never-married, Protective-serv, Own-child, White, Male, 34095, 0, 3, United-States, <=50K 36, Private, 274809, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 58, Private, 233193, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 27, United-States, <=50K 34, Private, 299635, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 50, United-States, >50K 19, Private, 236396, 11th, 7, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 688355, HS-grad, 9, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 36, Self-emp-inc, 37019, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 37, Private, 148015, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, Black, Female, 15024, 0, 40, United-States, >50K 43, Private, 122975, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, Black, Female, 0, 0, 21, Trinadad&Tobago, <=50K 52, State-gov, 349795, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 229846, Assoc-voc, 11, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, ?, <=50K 43, Private, 108945, Some-college, 10, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 22, Private, 237498, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 188872, 5th-6th, 3, Divorced, Transport-moving, Unmarried, White, Male, 6497, 0, 40, United-States, <=50K 37, Private, 324019, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 82488, Some-college, 10, Divorced, Sales, Unmarried, Asian-Pac-Islander, Female, 0, 0, 38, United-States, <=50K 54, Private, 206964, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 37088, Assoc-acdm, 12, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 152540, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 65, Private, 143554, Some-college, 10, Separated, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 30, Private, 126242, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 127185, 9th, 5, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 164018, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 4064, 0, 50, United-States, <=50K 25, Private, 210184, 11th, 7, Separated, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 35, ?, 117528, Assoc-voc, 11, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 40, United-States, >50K 47, Private, 124973, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 23, Private, 182117, Assoc-acdm, 12, Never-married, Other-service, Own-child, White, Male, 0, 0, 60, United-States, <=50K 42, Private, 220049, HS-grad, 9, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 40, United-States, >50K 39, Self-emp-not-inc, 247975, Some-college, 10, Never-married, Craft-repair, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 30, United-States, <=50K 55, Private, 50164, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 24, State-gov, 123160, Masters, 14, Married-spouse-absent, Prof-specialty, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 10, China, <=50K 46, Self-emp-inc, 219962, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 7298, 0, 40, ?, >50K 53, Private, 79324, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 44, Private, 129100, 11th, 7, Separated, Other-service, Unmarried, Black, Female, 0, 0, 60, United-States, <=50K 40, Private, 210275, HS-grad, 9, Separated, Transport-moving, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 48, Private, 189462, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 7688, 0, 40, United-States, >50K 26, Private, 171114, Assoc-voc, 11, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 22, Private, 201799, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 35, ?, 200426, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 12, United-States, <=50K 20, ?, 24395, Some-college, 10, Never-married, ?, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 43, Private, 191149, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 37, Local-gov, 34173, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 25, United-States, <=50K 30, Private, 350979, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Laos, <=50K 41, Private, 147314, HS-grad, 9, Married-civ-spouse, Sales, Husband, Amer-Indian-Eskimo, Male, 0, 0, 50, United-States, <=50K 38, Private, 136081, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 77, ?, 232894, 9th, 5, Married-civ-spouse, ?, Husband, Black, Male, 0, 0, 40, United-States, <=50K 42, Self-emp-not-inc, 373403, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 20, Private, 120601, HS-grad, 9, Never-married, Transport-moving, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 36, Private, 130926, Bachelors, 13, Divorced, Adm-clerical, Not-in-family, White, Female, 3674, 0, 40, United-States, <=50K 32, Federal-gov, 72338, Assoc-voc, 11, Never-married, Prof-specialty, Other-relative, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 27, Private, 129624, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 25, State-gov, 328697, Some-college, 10, Divorced, Protective-serv, Other-relative, White, Male, 0, 0, 45, United-States, <=50K 40, Private, 191196, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 18, ?, 191117, 11th, 7, Never-married, ?, Own-child, White, Male, 0, 0, 25, United-States, <=50K 49, Private, 110243, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 17, Private, 181580, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 16, United-States, <=50K 29, Private, 89030, HS-grad, 9, Never-married, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 345493, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 99999, 0, 55, Taiwan, >50K 24, Self-emp-not-inc, 277700, Some-college, 10, Separated, Handlers-cleaners, Own-child, White, Male, 0, 0, 45, United-States, <=50K 58, ?, 198478, 7th-8th, 4, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 24, United-States, <=50K 29, Private, 250679, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 168837, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 24, Canada, >50K 30, Private, 142675, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 19, Private, 299050, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 20, United-States, <=50K 59, Private, 107833, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1485, 40, United-States, >50K 47, Private, 121958, 7th-8th, 4, Married-spouse-absent, Other-service, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 41, Private, 282948, Some-college, 10, Married-civ-spouse, Tech-support, Husband, Black, Male, 3137, 0, 40, United-States, <=50K 28, Private, 176683, Assoc-acdm, 12, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, France, <=50K 46, Private, 34377, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Self-emp-not-inc, 209833, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 66, State-gov, 41506, 10th, 6, Divorced, Other-service, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 30, Local-gov, 125159, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Black, Male, 14084, 0, 45, ?, >50K 44, Self-emp-not-inc, 147206, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 12, United-States, <=50K 58, Self-emp-not-inc, 93664, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 60, United-States, >50K 21, Private, 315065, 7th-8th, 4, Never-married, Other-service, Other-relative, White, Male, 0, 0, 48, Mexico, <=50K 59, Private, 381851, 9th, 5, Widowed, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 35, Local-gov, 185769, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 186272, 9th, 5, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 5178, 0, 40, United-States, >50K 30, Private, 312667, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 343925, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 40, Jamaica, <=50K 26, Private, 195994, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 48, Private, 398843, Some-college, 10, Separated, Sales, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 31, Private, 73514, HS-grad, 9, Never-married, Sales, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 36, Private, 288049, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 48, Private, 54759, HS-grad, 9, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 30, Private, 155343, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 5013, 0, 40, United-States, <=50K 33, Private, 401104, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 50, United-States, >50K 19, ?, 124884, 9th, 5, Never-married, ?, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 37, Local-gov, 287306, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Wife, Black, Female, 99999, 0, 40, ?, >50K 53, Private, 113995, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 18, Private, 146378, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, ?, <=50K 38, Private, 111499, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 7298, 0, 50, United-States, >50K 34, Private, 34374, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 45, Private, 162187, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 52, United-States, >50K 33, Local-gov, 147654, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 35, Private, 182467, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Wife, White, Female, 0, 0, 44, United-States, <=50K 22, Private, 183970, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 35, Private, 332588, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 45, Private, 26781, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, Amer-Indian-Eskimo, Male, 0, 0, 8, United-States, <=50K 17, Private, 48610, 11th, 7, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 45, United-States, <=50K 50, Private, 162632, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 38, Local-gov, 91711, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 33, Private, 198003, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 50, United-States, >50K 46, Private, 179048, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 35, ?, <=50K 25, Private, 262778, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 6849, 0, 50, United-States, <=50K 64, Private, 102470, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 62, Self-emp-not-inc, 123170, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 10, United-States, <=50K 32, Private, 164243, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 60, United-States, >50K 17, Private, 262511, 11th, 7, Never-married, Sales, Own-child, White, Male, 0, 0, 20, United-States, <=50K 61, Private, 51170, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, <=50K 40, State-gov, 91949, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 21, Private, 123727, HS-grad, 9, Never-married, Exec-managerial, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 173175, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 35, Self-emp-not-inc, 120301, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 29, Private, 250967, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Federal-gov, 285432, Assoc-acdm, 12, Never-married, Transport-moving, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 20, Private, 36235, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, ?, 317219, Some-college, 10, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 20, United-States, >50K 51, Local-gov, 110965, Masters, 14, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 123283, HS-grad, 9, Separated, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 15, United-States, <=50K 20, ?, 249087, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 152940, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 376680, HS-grad, 9, Never-married, Tech-support, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 56, Private, 231232, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 30, Canada, <=50K 55, Self-emp-not-inc, 168625, Some-college, 10, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 12, United-States, >50K 26, Private, 33939, Some-college, 10, Never-married, Tech-support, Own-child, White, Male, 0, 0, 20, United-States, <=50K 46, Private, 155659, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 15024, 0, 45, United-States, >50K 32, Local-gov, 190228, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 216178, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 587310, 7th-8th, 4, Never-married, Other-service, Other-relative, White, Male, 0, 0, 35, Guatemala, <=50K 23, Private, 155919, 9th, 5, Married-spouse-absent, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 59, Private, 227386, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 138152, 12th, 8, Never-married, Craft-repair, Other-relative, Other, Male, 0, 0, 48, Guatemala, <=50K 36, Private, 167482, 10th, 6, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 57957, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 15, United-States, <=50K 33, Private, 157747, 9th, 5, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 60, Self-emp-not-inc, 88570, Assoc-voc, 11, Married-civ-spouse, Transport-moving, Wife, White, Female, 0, 0, 15, Germany, >50K 40, Private, 273308, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 48, Mexico, <=50K 48, Private, 216292, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 43, United-States, <=50K 27, Self-emp-not-inc, 131298, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, <=50K 19, Private, 386378, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 38, Private, 179668, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 26, Private, 210812, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 43, United-States, <=50K 45, Federal-gov, 311671, Assoc-voc, 11, Married-civ-spouse, Protective-serv, Husband, White, Male, 3908, 0, 40, United-States, <=50K 20, Private, 215247, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 32, Federal-gov, 125856, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 74631, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 13, United-States, <=50K 22, Private, 24008, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, State-gov, 354591, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 114, 0, 38, United-States, <=50K 34, Private, 155343, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1848, 50, United-States, >50K 46, Private, 308334, 1st-4th, 2, Widowed, Other-service, Unmarried, Other, Female, 0, 0, 30, Mexico, <=50K 39, Private, 245361, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 79, Self-emp-not-inc, 158319, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 24, United-States, <=50K 60, ?, 204486, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 8, United-States, >50K 24, Private, 314823, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 40, Dominican-Republic, <=50K 31, Private, 211334, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 2407, 0, 65, United-States, <=50K 37, Self-emp-not-inc, 73199, Bachelors, 13, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 3137, 0, 77, Vietnam, <=50K 23, Private, 126550, HS-grad, 9, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 260782, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1579, 45, El-Salvador, <=50K 29, Private, 114224, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 22, State-gov, 64292, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 43, United-States, <=50K 69, ?, 628797, Some-college, 10, Widowed, ?, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 55, Local-gov, 219775, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 43, Private, 212894, HS-grad, 9, Divorced, Craft-repair, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 260019, 7th-8th, 4, Never-married, Farming-fishing, Unmarried, Other, Male, 0, 0, 36, Mexico, <=50K 29, Private, 228075, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Male, 0, 0, 35, Mexico, <=50K 22, Private, 239806, Assoc-voc, 11, Never-married, Other-service, Other-relative, White, Female, 0, 0, 40, Mexico, <=50K 22, Private, 324637, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 42, United-States, <=50K 25, Private, 163620, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 84, United-States, >50K 29, Private, 194200, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 45, United-States, <=50K 25, State-gov, 129200, Some-college, 10, Never-married, Transport-moving, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 33, Federal-gov, 207172, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 135312, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 31, Private, 100734, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 28, United-States, <=50K 30, Local-gov, 226443, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1887, 45, United-States, >50K 55, Private, 110871, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 192704, 12th, 8, Never-married, Exec-managerial, Not-in-family, White, Male, 4650, 0, 50, United-States, <=50K 47, ?, 224108, HS-grad, 9, Widowed, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 78870, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 8614, 0, 40, United-States, >50K 42, Private, 107762, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 51, Private, 183611, Assoc-acdm, 12, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 55, Germany, <=50K 62, Local-gov, 249078, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 65, Self-emp-inc, 208452, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 35, United-States, >50K 23, Private, 302195, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 60, ?, 199947, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 32, United-States, <=50K 47, Private, 379118, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 60, United-States, >50K 50, Self-emp-inc, 174855, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 70, ?, 173736, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 6, United-States, <=50K 32, Self-emp-not-inc, 39369, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Federal-gov, 196348, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 340917, HS-grad, 9, Never-married, Craft-repair, Unmarried, White, Male, 14344, 0, 40, United-States, >50K 76, Private, 97077, 10th, 6, Widowed, Sales, Unmarried, Black, Female, 0, 0, 12, United-States, <=50K 54, Private, 200098, Bachelors, 13, Divorced, Sales, Not-in-family, Black, Female, 0, 0, 60, United-States, <=50K 32, Federal-gov, 127651, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 315128, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 52, United-States, <=50K 31, Federal-gov, 206823, Bachelors, 13, Divorced, Protective-serv, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 65, Self-emp-not-inc, 316093, Prof-school, 15, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 1668, 40, United-States, <=50K 30, Private, 112115, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 60, Ireland, >50K 63, ?, 203821, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 250051, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 10, United-States, <=50K 40, Federal-gov, 298635, Masters, 14, Married-civ-spouse, Tech-support, Husband, Asian-Pac-Islander, Male, 0, 1902, 40, Philippines, >50K 26, State-gov, 109193, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 130849, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 8, United-States, <=50K 34, Local-gov, 43959, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 50, United-States, <=50K 66, Local-gov, 222810, Some-college, 10, Divorced, Other-service, Other-relative, White, Female, 7896, 0, 40, ?, >50K 44, Self-emp-not-inc, 27242, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 60, United-States, <=50K 30, Private, 53158, Assoc-acdm, 12, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, Self-emp-not-inc, 206520, Bachelors, 13, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 164190, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 22, Private, 287988, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 28, ?, 200819, 7th-8th, 4, Divorced, ?, Own-child, White, Male, 0, 0, 84, United-States, <=50K 23, Private, 83891, HS-grad, 9, Never-married, Sales, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 49, Private, 65087, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 39, Self-emp-not-inc, 363418, Bachelors, 13, Separated, Craft-repair, Own-child, White, Male, 0, 0, 35, United-States, <=50K 67, ?, 182378, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 9386, 0, 60, United-States, >50K 19, Private, 278870, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 16, United-States, <=50K 30, Private, 174789, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1848, 50, United-States, >50K 25, Private, 228608, Some-college, 10, Never-married, Craft-repair, Other-relative, Asian-Pac-Islander, Female, 0, 0, 40, Cambodia, <=50K 24, Private, 184400, HS-grad, 9, Never-married, Transport-moving, Own-child, Asian-Pac-Islander, Male, 0, 0, 30, ?, <=50K 46, Private, 263568, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 117381, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, <=50K 41, Federal-gov, 83411, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Self-emp-not-inc, 49156, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 20, United-States, <=50K 44, Private, 421449, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 238944, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, Private, 188982, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 20, United-States, >50K 48, Private, 175925, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, <=50K 34, Private, 164190, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 232914, Assoc-voc, 11, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 46, Self-emp-inc, 120121, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 36, Local-gov, 180805, HS-grad, 9, Never-married, Transport-moving, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 59, Local-gov, 161944, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 29, Private, 319149, 12th, 8, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, Mexico, <=50K 50, ?, 22428, Masters, 14, Never-married, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 290528, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 123984, Assoc-acdm, 12, Never-married, Other-service, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 35, Philippines, <=50K 48, Private, 34186, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 70, United-States, <=50K 51, Federal-gov, 282680, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 1564, 70, United-States, >50K 36, Private, 183892, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 8614, 0, 45, United-States, >50K 42, Local-gov, 195124, 11th, 7, Divorced, Sales, Unmarried, White, Male, 7430, 0, 50, Puerto-Rico, >50K 49, State-gov, 55938, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Private, 209900, Some-college, 10, Never-married, Tech-support, Own-child, White, Male, 0, 0, 20, United-States, <=50K 40, Private, 179717, Bachelors, 13, Divorced, Sales, Not-in-family, White, Male, 0, 1564, 60, United-States, >50K 26, Private, 150361, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 69, ?, 164102, HS-grad, 9, Divorced, ?, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 59, Private, 252714, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 30, Italy, <=50K 30, Private, 205204, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 31, Local-gov, 168906, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 35, United-States, <=50K 30, Private, 112115, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 27, Private, 116531, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 20, ?, 202994, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 16, United-States, <=50K 56, Private, 191917, Assoc-acdm, 12, Divorced, Adm-clerical, Unmarried, White, Female, 4101, 0, 40, United-States, <=50K 24, Private, 341294, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 216734, Bachelors, 13, Divorced, Sales, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 51, Private, 182187, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Black, Male, 0, 0, 35, United-States, <=50K 34, Private, 424988, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 47, Private, 379118, HS-grad, 9, Divorced, Other-service, Unmarried, Black, Male, 0, 0, 9, United-States, <=50K 47, Private, 168232, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 44, United-States, >50K 20, Private, 147171, Some-college, 10, Never-married, Adm-clerical, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, Vietnam, <=50K 34, Self-emp-inc, 207668, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 54, ?, >50K 31, Private, 193650, 11th, 7, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 200187, Assoc-voc, 11, Divorced, Other-service, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 52, Private, 188644, 5th-6th, 3, Married-spouse-absent, Craft-repair, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 56, Private, 398067, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 53, Private, 29658, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 154966, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 81, Private, 364099, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 28, ?, 291374, 10th, 6, Never-married, ?, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 57, Federal-gov, 97837, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 48, United-States, >50K 34, Private, 117983, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, ?, 345497, 10th, 6, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 64167, Assoc-voc, 11, Never-married, Tech-support, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 20, Private, 315877, HS-grad, 9, Never-married, Other-service, Unmarried, White, Male, 0, 2001, 40, United-States, <=50K 68, Federal-gov, 232151, Some-college, 10, Divorced, Adm-clerical, Other-relative, Black, Female, 2346, 0, 40, United-States, <=50K 60, Private, 225526, HS-grad, 9, Separated, Sales, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 37, Federal-gov, 289653, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 179462, 7th-8th, 4, Never-married, Handlers-cleaners, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 36, Federal-gov, 67317, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 77764, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 253438, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 31, Private, 150309, Bachelors, 13, Separated, Exec-managerial, Not-in-family, White, Female, 0, 0, 70, United-States, <=50K 47, Self-emp-not-inc, 83064, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 60, Self-emp-not-inc, 376973, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 42, United-States, >50K 75, Private, 311184, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 24, United-States, <=50K 43, Local-gov, 159449, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 168288, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 74883, Bachelors, 13, Never-married, Tech-support, Not-in-family, Asian-Pac-Islander, Female, 0, 1092, 40, Philippines, <=50K 20, Private, 275190, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 189838, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 57, Self-emp-inc, 101338, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 20, United-States, <=50K 43, Private, 331894, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, >50K 18, Self-emp-not-inc, 40293, HS-grad, 9, Never-married, Farming-fishing, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 41, Local-gov, 88904, Bachelors, 13, Separated, Prof-specialty, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 48, Private, 145041, HS-grad, 9, Never-married, Machine-op-inspct, Other-relative, White, Male, 0, 0, 40, Dominican-Republic, <=50K 35, Private, 46385, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 5178, 0, 90, United-States, >50K 41, State-gov, 363591, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 183327, HS-grad, 9, Never-married, Craft-repair, Own-child, Black, Female, 0, 1594, 20, United-States, <=50K 32, State-gov, 182556, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 1887, 45, United-States, >50K 33, Private, 267859, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, El-Salvador, <=50K 58, Private, 190747, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 162869, Some-college, 10, Never-married, Sales, Other-relative, White, Male, 0, 0, 65, United-States, <=50K 33, Private, 141229, Some-college, 10, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 42, Self-emp-not-inc, 174216, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 38, United-States, >50K 25, Private, 366416, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 172538, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 35, Private, 193026, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 50, Private, 184424, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 1902, 38, United-States, >50K 49, Local-gov, 337768, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 25, Local-gov, 179059, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 47, Federal-gov, 99549, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 46, Private, 72619, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 42, State-gov, 55764, Assoc-acdm, 12, Divorced, Prof-specialty, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 37, Private, 30267, 11th, 7, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 25, Private, 308144, Bachelors, 13, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 29, Private, 206351, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 5013, 0, 40, United-States, <=50K 26, Private, 282304, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 26, ?, 176077, Some-college, 10, Never-married, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 45, Self-emp-inc, 142719, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 34, Private, 114973, HS-grad, 9, Separated, Exec-managerial, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 33, Federal-gov, 159548, Assoc-acdm, 12, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 43, Private, 91209, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 196564, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 51, Self-emp-not-inc, 149220, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 75, United-States, <=50K 21, Private, 169699, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 23, Private, 218215, Assoc-acdm, 12, Never-married, Other-service, Own-child, White, Female, 0, 0, 35, United-States, <=50K 30, Private, 156718, HS-grad, 9, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 55720, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 38, Self-emp-inc, 257250, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 20, Private, 194630, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 398931, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1485, 50, United-States, >50K 37, Self-emp-not-inc, 362062, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 50, United-States, >50K 44, Local-gov, 101593, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 1876, 42, United-States, <=50K 33, Private, 196266, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 45, Local-gov, 197332, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 97842, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 86837, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 1902, 40, United-States, >50K 17, Private, 57324, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, United-States, <=50K 43, Private, 116852, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 36, Portugal, >50K 45, Private, 154430, Bachelors, 13, Widowed, Prof-specialty, Not-in-family, White, Female, 10520, 0, 50, United-States, >50K 37, Private, 38468, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 44, Local-gov, 188808, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 55, Local-gov, 177163, Masters, 14, Widowed, Prof-specialty, Unmarried, White, Female, 914, 0, 50, United-States, <=50K 41, Private, 187322, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, <=50K 23, Private, 107578, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 2174, 0, 40, United-States, <=50K 38, Private, 168680, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 23, Private, 256755, Bachelors, 13, Never-married, Handlers-cleaners, Other-relative, White, Female, 0, 0, 40, Cuba, <=50K 35, Private, 360799, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 40, United-States, >50K 18, Private, 188476, 11th, 7, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 20, United-States, <=50K 47, Private, 30457, Assoc-voc, 11, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 252752, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 8, United-States, <=50K 41, Self-emp-not-inc, 443508, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 23, Private, 244408, Some-college, 10, Never-married, Adm-clerical, Other-relative, Asian-Pac-Islander, Female, 0, 0, 24, Vietnam, <=50K 41, Private, 178983, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 143068, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 2407, 0, 50, United-States, <=50K 30, Local-gov, 247328, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 201732, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 246829, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 28, ?, 290267, Bachelors, 13, Never-married, ?, Not-in-family, White, Male, 0, 0, 18, United-States, <=50K 29, Private, 119170, Some-college, 10, Separated, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 207923, Some-college, 10, Married-spouse-absent, Adm-clerical, Own-child, White, Female, 0, 0, 15, United-States, <=50K 48, State-gov, 170142, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 44, Self-emp-not-inc, 187164, HS-grad, 9, Divorced, Transport-moving, Unmarried, White, Male, 0, 0, 60, United-States, <=50K 34, Local-gov, 303867, 9th, 5, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 291429, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 32, Private, 213179, Some-college, 10, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, >50K 31, State-gov, 111843, Assoc-acdm, 12, Separated, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 25, Private, 297154, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 2407, 0, 40, United-States, <=50K 47, Federal-gov, 68493, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, >50K 46, Federal-gov, 340718, 11th, 7, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 194059, 12th, 8, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 47296, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 1740, 20, United-States, <=50K 28, State-gov, 286310, HS-grad, 9, Married-civ-spouse, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 207202, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, >50K 33, Self-emp-inc, 132601, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 17, ?, 139183, 10th, 6, Never-married, ?, Own-child, White, Female, 0, 0, 15, United-States, <=50K 41, Private, 160785, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Private, 117849, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 40, United-States, >50K 38, Local-gov, 225605, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 44, United-States, <=50K 24, Private, 190290, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 49, Private, 164799, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 60, Federal-gov, 21876, Some-college, 10, Divorced, Prof-specialty, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 44, Private, 160785, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 63, Self-emp-inc, 272425, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Private, 168538, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 45, Self-emp-inc, 204205, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 49, Private, 142287, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 1902, 50, United-States, >50K 36, Private, 169926, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 65, Local-gov, 205024, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 8, United-States, <=50K 41, Private, 374764, Bachelors, 13, Widowed, Exec-managerial, Unmarried, White, Male, 0, 0, 20, United-States, <=50K 25, Private, 108779, Masters, 14, Separated, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 20, ?, 293136, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 35, United-States, <=50K 60, Private, 227332, Assoc-voc, 11, Widowed, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 17, Local-gov, 246308, 11th, 7, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 20, Puerto-Rico, <=50K 28, Private, 51331, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 16, United-States, >50K 31, Private, 153078, Assoc-acdm, 12, Never-married, Craft-repair, Own-child, Other, Male, 0, 0, 50, United-States, <=50K 47, Private, 169180, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 45, Self-emp-not-inc, 193451, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 51, Private, 305147, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 138892, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 44, Self-emp-not-inc, 402397, Masters, 14, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 1902, 60, United-States, >50K 34, Private, 223267, HS-grad, 9, Never-married, Exec-managerial, Other-relative, White, Male, 0, 0, 50, United-States, <=50K 19, Private, 29250, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 10, United-States, <=50K 51, ?, 203953, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, >50K 46, State-gov, 29696, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 315640, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 1977, 40, China, >50K 37, Private, 632613, 10th, 6, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 35, Mexico, <=50K 56, Private, 282023, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 29, Private, 77760, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, <=50K 46, Self-emp-not-inc, 148599, Masters, 14, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 55, Private, 414994, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 339863, Bachelors, 13, Divorced, Sales, Not-in-family, White, Male, 8614, 0, 48, United-States, >50K 34, Private, 499249, HS-grad, 9, Married-spouse-absent, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, Guatemala, <=50K 45, ?, 144354, 9th, 5, Separated, ?, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 41, Private, 252058, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 22, ?, 99543, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 20, United-States, <=50K 34, Private, 117963, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 27, Private, 194652, HS-grad, 9, Never-married, Craft-repair, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 29, Private, 299705, Some-college, 10, Never-married, Handlers-cleaners, Unmarried, Black, Male, 0, 0, 37, United-States, <=50K 19, Federal-gov, 27433, 12th, 8, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 47, Local-gov, 39986, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Self-emp-inc, 135342, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 52, Private, 270142, Assoc-voc, 11, Separated, Exec-managerial, Unmarried, Black, Female, 0, 0, 60, United-States, <=50K 33, Self-emp-not-inc, 118267, Assoc-acdm, 12, Divorced, Sales, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 29, Private, 266043, 9th, 5, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 35633, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 74568, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 214816, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 43, Private, 222971, 5th-6th, 3, Never-married, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 31, Private, 259425, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 47, Self-emp-inc, 212120, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 245880, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 58, Local-gov, 54947, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 47, Self-emp-inc, 79627, Prof-school, 15, Divorced, Prof-specialty, Not-in-family, White, Male, 27828, 0, 50, United-States, >50K 55, Private, 151474, Bachelors, 13, Never-married, Tech-support, Other-relative, White, Female, 0, 1590, 38, United-States, <=50K 26, Private, 132661, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 5013, 0, 40, United-States, <=50K 28, Private, 161674, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 62346, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 40, Private, 227236, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 19, Private, 283033, 11th, 7, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 63, Self-emp-not-inc, 298249, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 10605, 0, 40, United-States, >50K 42, Private, 251229, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 76, Private, 199949, 9th, 5, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 13, United-States, <=50K 23, State-gov, 305498, Assoc-voc, 11, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Self-emp-not-inc, 203836, 5th-6th, 3, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, State-gov, 79440, Masters, 14, Never-married, Prof-specialty, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 30, Japan, <=50K 48, Local-gov, 142719, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 56, Private, 119859, Some-college, 10, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 32, Private, 141410, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 44, Local-gov, 202872, Some-college, 10, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 27, Private, 198813, HS-grad, 9, Divorced, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 33, Federal-gov, 129707, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 22, Private, 445758, 5th-6th, 3, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 18, ?, 30246, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 20, United-States, <=50K 44, Private, 173981, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 108506, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Amer-Indian-Eskimo, Male, 0, 0, 60, United-States, <=50K 34, Private, 134886, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, Federal-gov, 181970, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 1672, 40, United-States, <=50K 57, Self-emp-inc, 282913, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, Cuba, <=50K 59, Local-gov, 196013, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Federal-gov, 348491, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, Black, Female, 0, 0, 40, United-States, >50K 52, Private, 416164, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, Other, Male, 0, 0, 49, Mexico, <=50K 17, Private, 121037, 12th, 8, Never-married, Sales, Own-child, White, Female, 0, 0, 15, United-States, <=50K 29, Private, 103111, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, Canada, <=50K 63, Self-emp-not-inc, 147589, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 30, United-States, >50K 20, Private, 24008, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 24, United-States, <=50K 42, Self-emp-inc, 123838, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 50, United-States, >50K 50, Self-emp-not-inc, 175456, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 55, Private, 84774, HS-grad, 9, Married-civ-spouse, Priv-house-serv, Wife, White, Female, 0, 0, 30, United-States, <=50K 27, Private, 194590, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 0, 25, United-States, <=50K 28, Private, 134566, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 55, Private, 211678, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, <=50K 44, Federal-gov, 44822, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 53, State-gov, 144586, Some-college, 10, Never-married, Protective-serv, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 119156, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 371987, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 44, State-gov, 144125, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 55, Private, 31905, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 40, United-States, >50K 48, Self-emp-not-inc, 121124, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, >50K 46, Private, 58126, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 318518, Some-college, 10, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 296509, 7th-8th, 4, Separated, Farming-fishing, Not-in-family, White, Male, 0, 0, 45, Mexico, <=50K 32, Private, 473133, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 52, Private, 155434, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 48, United-States, <=50K 52, Private, 99185, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 7298, 0, 50, United-States, >50K 39, Private, 56648, HS-grad, 9, Separated, Sales, Not-in-family, White, Female, 0, 0, 47, United-States, <=50K 57, Local-gov, 118481, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 40, United-States, >50K 21, Private, 321666, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 594, 0, 40, United-States, <=50K 22, State-gov, 119838, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 10, United-States, <=50K 26, Private, 330695, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, State-gov, 58039, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 313022, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, United-States, >50K 42, Private, 178134, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 40, Private, 165309, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 43, United-States, <=50K 22, Private, 216181, 11th, 7, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 45, United-States, <=50K 62, Private, 178745, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 44, Private, 111067, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, ?, 163788, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 33, Self-emp-not-inc, 295591, 1st-4th, 2, Married-spouse-absent, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 45, Private, 123075, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 18, Private, 78045, 11th, 7, Married-civ-spouse, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 32, Local-gov, 255004, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 254221, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 60, United-States, >50K 20, Private, 174714, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 15, United-States, <=50K 68, Self-emp-not-inc, 450580, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 20, United-States, <=50K 61, Private, 128230, 7th-8th, 4, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 48, Private, 192894, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 45, Private, 325390, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Self-emp-not-inc, 20333, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 7688, 0, 40, United-States, >50K 32, Federal-gov, 128714, HS-grad, 9, Never-married, Other-service, Own-child, Black, Female, 0, 0, 32, United-States, <=50K 35, Private, 170797, Bachelors, 13, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 269186, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 127671, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 211840, Some-college, 10, Separated, Sales, Unmarried, Black, Female, 0, 0, 16, United-States, <=50K 37, Private, 163392, HS-grad, 9, Never-married, Transport-moving, Other-relative, Asian-Pac-Islander, Male, 0, 0, 40, ?, <=50K 40, Private, 201495, Bachelors, 13, Divorced, Protective-serv, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 25, Private, 251854, Some-college, 10, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, Jamaica, <=50K 41, Private, 279297, HS-grad, 9, Never-married, Sales, Not-in-family, Black, Female, 0, 0, 60, United-States, <=50K 52, Self-emp-not-inc, 195462, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 98, United-States, >50K 33, Private, 170769, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 142443, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Self-emp-not-inc, 182809, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 40, United-States, >50K 53, Private, 121441, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, <=50K 44, Private, 275094, 1st-4th, 2, Never-married, Other-service, Own-child, White, Male, 0, 0, 10, United-States, <=50K 35, Private, 170263, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 172571, Some-college, 10, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 58, Poland, <=50K 34, Private, 178615, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 279524, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 24, State-gov, 165201, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 45, United-States, <=50K 65, Local-gov, 323006, HS-grad, 9, Widowed, Other-service, Unmarried, Black, Female, 0, 0, 25, United-States, <=50K 29, Private, 235168, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 39, Self-emp-inc, 114844, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 65, United-States, >50K 46, Local-gov, 216414, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Private, 34378, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 2580, 0, 60, United-States, <=50K 47, State-gov, 80914, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 47, United-States, >50K 62, Private, 73292, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Self-emp-not-inc, 212165, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 90, Private, 52386, Some-college, 10, Never-married, Other-service, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 35, United-States, <=50K 33, Private, 205649, Assoc-acdm, 12, Married-spouse-absent, Craft-repair, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 57, Private, 109638, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1672, 45, United-States, <=50K 25, Private, 200408, Assoc-acdm, 12, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 44, Self-emp-inc, 187720, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 52, Private, 236180, Bachelors, 13, Married-spouse-absent, Other-service, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 21, Private, 118693, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 363130, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Male, 0, 0, 18, United-States, <=50K 39, Private, 225544, Masters, 14, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, Poland, <=50K 59, Federal-gov, 243612, HS-grad, 9, Widowed, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 29, Self-emp-not-inc, 160786, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, <=50K 49, Private, 234320, 7th-8th, 4, Never-married, Prof-specialty, Other-relative, Black, Male, 0, 0, 45, United-States, <=50K 34, Private, 314646, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 124971, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 209184, Bachelors, 13, Married-civ-spouse, Sales, Husband, Other, Male, 0, 0, 40, Puerto-Rico, <=50K 39, State-gov, 121838, HS-grad, 9, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 46, Private, 265275, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 50, Private, 71417, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 3103, 0, 40, United-States, >50K 34, Private, 45522, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, Local-gov, 250135, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 1902, 55, United-States, <=50K 18, Private, 120283, 12th, 8, Never-married, Sales, Own-child, White, Female, 0, 0, 24, United-States, <=50K 20, Private, 216972, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 20, Private, 116791, HS-grad, 9, Never-married, Machine-op-inspct, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 55, State-gov, 26290, Assoc-voc, 11, Widowed, Exec-managerial, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 38, United-States, <=50K 22, Private, 216134, Some-college, 10, Never-married, Sales, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 60, Self-emp-not-inc, 143932, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 217120, 10th, 6, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 47, State-gov, 223944, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 30, United-States, <=50K 23, Private, 185452, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 35, Canada, <=50K 57, Local-gov, 44273, HS-grad, 9, Widowed, Transport-moving, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 52, Private, 178983, 11th, 7, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 219288, 7th-8th, 4, Widowed, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 349190, Assoc-acdm, 12, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, United-States, <=50K 49, Self-emp-inc, 158685, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 2377, 40, United-States, >50K 41, Federal-gov, 57924, Some-college, 10, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 40, United-States, <=50K 40, State-gov, 270324, Assoc-voc, 11, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 30, United-States, <=50K 38, Private, 33001, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 58, Private, 204021, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, Canada, <=50K 26, Private, 192506, Bachelors, 13, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 35, United-States, <=50K 57, Private, 372967, 10th, 6, Divorced, Adm-clerical, Other-relative, White, Female, 0, 0, 70, Germany, <=50K 28, Private, 273929, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 1628, 60, United-States, <=50K 42, Private, 195821, HS-grad, 9, Separated, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 56179, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 2174, 0, 55, United-States, <=50K 17, ?, 127003, 9th, 5, Never-married, ?, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 39, Self-emp-not-inc, 124090, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 199600, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 42, Private, 255847, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 4386, 0, 48, United-States, >50K 51, Self-emp-not-inc, 218311, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 27, Private, 167336, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 39, United-States, <=50K 41, Private, 59938, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 43, United-States, <=50K 28, Private, 263728, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Self-emp-not-inc, 278230, Some-college, 10, Divorced, Farming-fishing, Unmarried, White, Female, 10520, 0, 30, United-States, >50K 73, ?, 180603, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 8, United-States, <=50K 49, Private, 43910, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 30, United-States, <=50K 47, Private, 190139, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 109001, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 49, United-States, <=50K 42, Local-gov, 159931, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 45, United-States, >50K 32, Private, 194987, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 0, 40, United-States, <=50K 32, Local-gov, 87310, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 41, United-States, <=50K 27, Private, 133937, Masters, 14, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 207064, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 22, Private, 36011, Assoc-voc, 11, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 41, Federal-gov, 168294, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 5178, 0, 40, United-States, >50K 49, Local-gov, 194895, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 7298, 0, 40, United-States, >50K 58, Self-emp-not-inc, 49884, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 41, Self-emp-not-inc, 27305, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 7688, 0, 40, United-States, >50K 26, Private, 229977, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 21, Private, 64520, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 32, ?, 134886, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 2, United-States, >50K 37, Private, 305379, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 23, Private, 202284, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 0, 20, United-States, <=50K 42, Self-emp-not-inc, 99185, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Private, 159662, HS-grad, 9, Married-civ-spouse, Sales, Own-child, White, Male, 0, 0, 26, United-States, >50K 67, Private, 197865, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 41, Local-gov, 175149, HS-grad, 9, Divorced, Transport-moving, Not-in-family, Black, Female, 0, 0, 38, United-States, <=50K 49, Local-gov, 349633, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 50, United-States, >50K 36, Private, 135293, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 1506, 0, 45, ?, <=50K 18, Private, 242893, 11th, 7, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 35, United-States, <=50K 25, Private, 218667, 5th-6th, 3, Married-civ-spouse, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 43, State-gov, 144811, Prof-school, 15, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 38, Private, 146091, Doctorate, 16, Married-civ-spouse, Exec-managerial, Wife, White, Female, 99999, 0, 36, United-States, >50K 21, Private, 206861, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 20, ?, <=50K 65, Self-emp-not-inc, 226215, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 15, United-States, <=50K 66, Private, 114447, Assoc-voc, 11, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 33, Private, 124187, 11th, 7, Never-married, Transport-moving, Not-in-family, Black, Male, 0, 0, 60, United-States, <=50K 51, Private, 147954, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 3411, 0, 38, United-States, <=50K 27, Self-emp-inc, 64379, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1740, 40, United-States, <=50K 17, Private, 156501, 12th, 8, Never-married, Other-service, Own-child, White, Female, 0, 0, 16, United-States, <=50K 32, Private, 207668, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 45, United-States, >50K 61, ?, 161279, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 36, United-States, <=50K 38, Private, 225707, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Cuba, >50K 43, Local-gov, 115603, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 40, State-gov, 506329, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Taiwan, >50K 63, Private, 275034, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 1740, 35, United-States, <=50K 76, ?, 172637, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 20, United-States, >50K 42, Private, 56483, Assoc-acdm, 12, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 43, Federal-gov, 144778, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 76, Self-emp-not-inc, 33213, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 30, ?, >50K 41, Local-gov, 297248, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 2415, 45, United-States, >50K 17, Private, 137042, 10th, 6, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 20, United-States, <=50K 30, Self-emp-not-inc, 33308, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 158420, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, Iran, <=50K 22, Private, 41763, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 53, ?, 220640, Bachelors, 13, Divorced, ?, Other-relative, Other, Female, 0, 0, 20, United-States, <=50K 28, Private, 149734, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 52, United-States, <=50K 25, ?, 262245, Assoc-voc, 11, Never-married, ?, Own-child, White, Female, 3418, 0, 40, United-States, <=50K 24, Private, 349691, Some-college, 10, Never-married, Sales, Other-relative, Black, Female, 0, 0, 40, United-States, <=50K 47, Private, 185385, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 34, Self-emp-not-inc, 174463, Assoc-voc, 11, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 26, Private, 236068, Some-college, 10, Never-married, Sales, Other-relative, White, Female, 0, 0, 20, United-States, <=50K 63, ?, 445168, Bachelors, 13, Widowed, ?, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 56, United-States, <=50K 25, Private, 91334, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 75, United-States, <=50K 28, Private, 33895, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 36, Private, 214816, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 229773, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 51, Self-emp-inc, 166386, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, Asian-Pac-Islander, Female, 0, 0, 35, Taiwan, <=50K 44, Private, 266135, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 18, Private, 300379, 12th, 8, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 12, United-States, <=50K 54, Federal-gov, 392502, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 61, Private, 73809, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 193720, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 43, Private, 316183, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 162944, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Local-gov, 186888, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, Black, Female, 0, 0, 40, United-States, >50K 27, ?, 330132, HS-grad, 9, Never-married, ?, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 24, Private, 192017, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 30, United-States, <=50K 20, State-gov, 161978, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 20, United-States, <=50K 52, Private, 202930, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 57, Local-gov, 323309, 7th-8th, 4, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 49, Self-emp-inc, 197332, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 42, Self-emp-inc, 204033, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 35, ?, <=50K 22, Private, 271274, 11th, 7, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 174242, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 21, Private, 209483, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 39, Federal-gov, 99146, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 1887, 60, United-States, >50K 52, Self-emp-not-inc, 102346, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 35, United-States, <=50K 25, Private, 181666, Assoc-acdm, 12, Never-married, Tech-support, Own-child, White, Female, 0, 0, 40, United-States, <=50K 50, Private, 207367, Some-college, 10, Married-spouse-absent, Other-service, Not-in-family, White, Female, 0, 0, 40, Cuba, <=50K 35, State-gov, 82622, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 80, United-States, <=50K 50, Private, 202296, Assoc-voc, 11, Separated, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 58, Private, 142182, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 25, United-States, <=50K 48, Federal-gov, 94342, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 30, Private, 41493, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, Canada, <=50K 18, Private, 181712, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 12, United-States, <=50K 29, Self-emp-not-inc, 164607, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Self-emp-not-inc, 41496, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 63, Private, 143098, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 4064, 0, 40, United-States, <=50K 36, Local-gov, 196529, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 24, Private, 157332, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 42, United-States, <=50K 30, Local-gov, 154935, Assoc-acdm, 12, Never-married, Protective-serv, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 23, Private, 223231, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Other, Male, 0, 0, 40, Mexico, <=50K 35, ?, 253860, HS-grad, 9, Divorced, ?, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 21, Private, 362589, Bachelors, 13, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 28, Private, 94880, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 43, Mexico, <=50K 20, Private, 309580, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 130389, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, Scotland, <=50K 21, Private, 349365, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 15, United-States, <=50K 27, Private, 376936, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 179557, Some-college, 10, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 105577, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 51, Private, 224207, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Federal-gov, 47907, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Self-emp-not-inc, 191283, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 20953, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 1902, 40, United-States, >50K 22, State-gov, 186569, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 12, United-States, <=50K 59, Private, 43221, 9th, 5, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, >50K 38, Private, 161141, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 203003, HS-grad, 9, Never-married, Transport-moving, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 90, Private, 141758, 9th, 5, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 113322, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 343847, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 38, United-States, >50K 45, Private, 214068, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 44, Private, 116632, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 23, Private, 240160, Assoc-acdm, 12, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 516337, 11th, 7, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Mexico, <=50K 23, Self-emp-inc, 284651, Bachelors, 13, Divorced, Sales, Not-in-family, White, Female, 0, 0, 43, United-States, <=50K 39, State-gov, 141420, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 42750, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 54, Private, 165278, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Private, 167265, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 43, United-States, <=50K 44, Private, 139907, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 50, United-States, <=50K 31, Self-emp-inc, 236415, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 20, United-States, >50K 25, Private, 312966, 9th, 5, Separated, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, El-Salvador, <=50K 33, Private, 118941, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 32, United-States, >50K 32, Private, 198068, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 36, Private, 373952, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Self-emp-not-inc, 236111, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, Other, Male, 0, 0, 55, United-States, >50K 80, Private, 157778, Masters, 14, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 10, United-States, <=50K 21, Private, 143604, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 8, United-States, <=50K 35, Self-emp-not-inc, 319831, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 77, ?, 132728, Masters, 14, Divorced, ?, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 30, Private, 137606, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 5013, 0, 40, United-States, <=50K 35, ?, 61343, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 268234, 7th-8th, 4, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 100135, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 1740, 25, United-States, <=50K 53, Self-emp-not-inc, 34973, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 45, United-States, <=50K 41, Private, 323790, HS-grad, 9, Divorced, Handlers-cleaners, Unmarried, White, Male, 0, 0, 55, United-States, <=50K 57, Private, 319733, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Poland, >50K 21, ?, 180339, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 25, United-States, <=50K 19, Private, 125591, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 60772, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 45, United-States, <=50K 42, Federal-gov, 74680, Masters, 14, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 2001, 60, United-States, <=50K 29, Self-emp-not-inc, 141185, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 55, United-States, <=50K 38, ?, 204668, Assoc-voc, 11, Separated, ?, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 26, Private, 273792, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 41, Private, 70037, Some-college, 10, Never-married, Craft-repair, Unmarried, White, Male, 0, 3004, 60, ?, >50K 40, Private, 343068, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, Self-emp-not-inc, 177907, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 28, Private, 144063, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Self-emp-not-inc, 257574, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 20, United-States, <=50K 42, Self-emp-not-inc, 67065, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 32, Private, 183356, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 152940, Assoc-acdm, 12, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 30, United-States, <=50K 37, Private, 227128, 5th-6th, 3, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Local-gov, 45607, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 56, United-States, <=50K 49, Private, 155489, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, ?, 230704, HS-grad, 9, Never-married, ?, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 24, ?, 267955, 9th, 5, Never-married, ?, Own-child, White, Female, 0, 0, 20, United-States, <=50K 19, Private, 165115, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 49923, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 272240, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 255476, 7th-8th, 4, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 30, Mexico, <=50K 59, Private, 194290, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 48, United-States, <=50K 52, Private, 145548, Assoc-acdm, 12, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 175262, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 45, Local-gov, 37306, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 58, Private, 137547, Bachelors, 13, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 40, South, <=50K 53, Private, 276515, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, Cuba, <=50K 23, Private, 174626, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 25, United-States, <=50K 35, Private, 215310, 11th, 7, Divorced, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 332355, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 204057, Assoc-acdm, 12, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 391591, 12th, 8, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 169092, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 50, United-States, >50K 28, Private, 230743, Assoc-acdm, 12, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 190963, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 74, ?, 204840, 5th-6th, 3, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 56, Mexico, <=50K 19, Private, 169853, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 24, United-States, <=50K 28, Private, 212091, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 2580, 0, 40, United-States, <=50K 31, Private, 202822, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 61, ?, 226989, Some-college, 10, Married-spouse-absent, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 140011, Assoc-voc, 11, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 53, United-States, <=50K 20, ?, 432376, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, Germany, <=50K 35, Private, 90273, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, ?, >50K 23, Private, 224424, Bachelors, 13, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 168943, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 30, United-States, >50K 19, Private, 571853, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, United-States, <=50K 30, Private, 156464, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 26, Private, 108542, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 35, United-States, <=50K 34, Local-gov, 194325, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 49, Private, 114797, Bachelors, 13, Divorced, Exec-managerial, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 35, Private, 40135, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 2042, 40, United-States, <=50K 38, Private, 204756, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 228190, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 20, United-States, <=50K 33, Private, 163392, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, Amer-Indian-Eskimo, Male, 0, 0, 48, United-States, >50K 54, Private, 138845, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 19, Local-gov, 169853, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 18, Never-worked, 206359, 10th, 6, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 60, Private, 224097, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Self-emp-not-inc, 160786, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 43, Self-emp-not-inc, 190044, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Local-gov, 145290, 5th-6th, 3, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 120268, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 70, United-States, <=50K 17, Private, 327434, 10th, 6, Never-married, Sales, Own-child, White, Male, 0, 0, 20, United-States, <=50K 41, Self-emp-inc, 218302, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 30, Private, 1184622, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 35, United-States, <=50K 90, Local-gov, 227796, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 20051, 0, 60, United-States, >50K 25, Private, 206343, HS-grad, 9, Never-married, Protective-serv, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 36851, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 35, United-States, <=50K 29, Private, 148550, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 157079, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 40, ?, >50K 31, Federal-gov, 142470, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 43, Private, 86750, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 99, United-States, <=50K 63, Private, 361631, Masters, 14, Separated, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 46, Private, 163229, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 59, Private, 179594, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 254773, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, Black, Female, 0, 0, 50, United-States, >50K 26, Private, 58065, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 26, Private, 205428, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 20, ?, 41183, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 30, United-States, <=50K 19, ?, 308064, HS-grad, 9, Never-married, ?, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 61, Private, 173924, 9th, 5, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, Puerto-Rico, >50K 23, State-gov, 142547, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 119704, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 275364, Bachelors, 13, Divorced, Tech-support, Unmarried, White, Male, 7430, 0, 40, Germany, >50K 42, Self-emp-not-inc, 207392, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 12, United-States, <=50K 31, Private, 147215, 12th, 8, Divorced, Other-service, Unmarried, White, Female, 0, 0, 21, United-States, <=50K 31, Private, 101562, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 55, United-States, <=50K 63, Private, 216413, Bachelors, 13, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 29, State-gov, 188986, Assoc-voc, 11, Never-married, Tech-support, Not-in-family, White, Female, 0, 1590, 64, United-States, <=50K 43, State-gov, 52849, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 304710, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 10, Vietnam, <=50K 17, Private, 265657, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 25, United-States, <=50K 23, Self-emp-not-inc, 258298, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Male, 0, 2231, 40, United-States, >50K 35, Private, 360814, 9th, 5, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 32, Private, 53260, HS-grad, 9, Divorced, Other-service, Unmarried, Other, Female, 0, 0, 28, United-States, <=50K 50, Self-emp-inc, 127315, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 60, United-States, >50K 25, Private, 233777, HS-grad, 9, Never-married, Transport-moving, Other-relative, White, Male, 0, 0, 40, ?, <=50K 26, Local-gov, 197530, Masters, 14, Married-spouse-absent, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 340940, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 88432, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 57, Private, 183810, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 90, Private, 51744, Masters, 14, Never-married, Exec-managerial, Not-in-family, Black, Male, 0, 0, 50, United-States, >50K 35, Private, 175614, Assoc-voc, 11, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, >50K 31, Self-emp-not-inc, 235237, Some-college, 10, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 60, United-States, >50K 60, Private, 227266, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 33, United-States, <=50K 21, Private, 146499, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Other-relative, White, Female, 0, 1579, 40, United-States, <=50K 71, Local-gov, 337064, Masters, 14, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 141003, Assoc-voc, 11, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, United-States, <=50K 50, Local-gov, 117791, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 172846, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 23, Private, 73514, HS-grad, 9, Never-married, Adm-clerical, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, Vietnam, <=50K 74, Private, 211075, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 30, United-States, <=50K 67, Private, 197816, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 1844, 70, United-States, <=50K 59, Private, 43221, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 43, United-States, >50K 28, Private, 183780, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1740, 40, United-States, <=50K 45, Private, 26781, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 63, Self-emp-not-inc, 271550, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 20, United-States, <=50K 39, Private, 250157, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 63, United-States, <=50K 33, State-gov, 913447, Some-college, 10, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 32, Private, 153078, Bachelors, 13, Never-married, Other-service, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, South, <=50K 34, Private, 181091, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 45, United-States, >50K 39, Private, 231491, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 29, State-gov, 95423, Masters, 14, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 36, United-States, <=50K 22, Private, 234663, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 283602, Bachelors, 13, Divorced, Sales, Not-in-family, White, Female, 13550, 0, 43, United-States, >50K 46, Private, 328669, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 42, United-States, <=50K 51, Private, 143741, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, >50K 44, Private, 83508, Prof-school, 15, Divorced, Prof-specialty, Not-in-family, White, Female, 2354, 0, 99, United-States, <=50K 56, State-gov, 81954, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 261375, Bachelors, 13, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 52, Private, 310045, 9th, 5, Married-spouse-absent, Machine-op-inspct, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 30, China, <=50K 39, Private, 316211, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 45, Federal-gov, 88564, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 40, United-States, >50K 37, Private, 61299, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 33, Private, 113364, HS-grad, 9, Divorced, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 35, ?, 476573, HS-grad, 9, Never-married, ?, Not-in-family, White, Female, 0, 0, 4, United-States, <=50K 46, Private, 267107, 5th-6th, 3, Married-civ-spouse, Craft-repair, Wife, White, Female, 0, 0, 45, Italy, <=50K 35, Private, 48123, 12th, 8, Married-civ-spouse, Craft-repair, Wife, White, Female, 0, 0, 50, United-States, <=50K 33, Private, 214635, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 50, United-States, <=50K 48, Private, 115585, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 194141, HS-grad, 9, Divorced, Machine-op-inspct, Own-child, White, Male, 0, 0, 50, United-States, <=50K 18, ?, 23233, 10th, 6, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 89991, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 32, United-States, <=50K 35, Private, 101709, HS-grad, 9, Never-married, Transport-moving, Own-child, Asian-Pac-Islander, Male, 0, 0, 60, United-States, <=50K 19, Private, 237455, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 25, United-States, <=50K 21, Private, 206492, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 40, ?, <=50K 56, Private, 28729, 11th, 7, Separated, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 153475, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 16, El-Salvador, <=50K 45, Private, 275517, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 128002, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 45, United-States, <=50K 44, Private, 175485, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 12, United-States, <=50K 55, Private, 189664, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 34, Private, 209808, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Private, 176992, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 154669, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 55, United-States, <=50K 25, Private, 191271, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 375482, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 102953, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 7298, 0, 55, United-States, >50K 53, Private, 169182, 10th, 6, Married-spouse-absent, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, Columbia, <=50K 47, Private, 184005, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, Amer-Indian-Eskimo, Female, 3325, 0, 45, United-States, <=50K 49, Self-emp-inc, 30751, Assoc-voc, 11, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 22, Private, 145477, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 31, Private, 91964, Some-college, 10, Never-married, Adm-clerical, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 44, Self-emp-inc, 49249, Some-college, 10, Divorced, Other-service, Unmarried, White, Male, 0, 0, 80, United-States, <=50K 19, Private, 218956, HS-grad, 9, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 37, Self-emp-not-inc, 241306, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 60, ?, 251572, HS-grad, 9, Widowed, ?, Not-in-family, White, Male, 0, 0, 35, Poland, <=50K 23, Private, 319842, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 25, United-States, <=50K 44, Private, 332401, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 65, United-States, >50K 54, Local-gov, 182388, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 35, United-States, <=50K 23, Private, 205939, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 38, United-States, <=50K 21, Private, 203914, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 10, United-States, <=50K 19, State-gov, 156294, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 25, United-States, <=50K 51, Private, 254211, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 20, United-States, >50K 41, Private, 151504, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 50, United-States, >50K 61, Private, 85548, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 15024, 0, 18, United-States, >50K 19, Self-emp-not-inc, 30800, 10th, 6, Married-spouse-absent, Adm-clerical, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 22, Private, 131230, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 61850, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 227800, 7th-8th, 4, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 32, United-States, <=50K 35, Private, 133454, 10th, 6, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 38, Private, 104094, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 105422, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 56, Private, 142182, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 41, Private, 336643, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 80, United-States, <=50K 62, Self-emp-inc, 200577, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 27, Private, 208703, HS-grad, 9, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 40, Japan, <=50K 55, ?, 193895, HS-grad, 9, Divorced, ?, Not-in-family, White, Female, 0, 0, 40, England, <=50K 25, Private, 272428, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 4416, 0, 42, United-States, <=50K 33, Private, 56701, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 75, United-States, >50K 26, Private, 288592, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 266439, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 53, Federal-gov, 276868, Masters, 14, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 43, Private, 131435, Bachelors, 13, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 56, Private, 175127, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 35, United-States, <=50K 25, Private, 277444, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 60, Private, 63296, Masters, 14, Divorced, Prof-specialty, Other-relative, Black, Male, 0, 0, 40, United-States, <=50K 28, Private, 96337, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 221955, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, Mexico, <=50K 40, Private, 197923, Bachelors, 13, Never-married, Adm-clerical, Unmarried, Black, Female, 2977, 0, 40, United-States, <=50K 29, Private, 632593, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 20, Private, 205970, Some-college, 10, Never-married, Craft-repair, Own-child, White, Female, 0, 0, 25, United-States, <=50K 25, Private, 139730, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 80, United-States, >50K 18, Private, 201901, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 10, United-States, <=50K 32, State-gov, 230224, Assoc-acdm, 12, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 35, United-States, <=50K 27, Private, 113464, 1st-4th, 2, Never-married, Other-service, Own-child, Other, Male, 0, 0, 35, Dominican-Republic, <=50K 48, Private, 94461, HS-grad, 9, Widowed, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 16, United-States, <=50K 20, Private, 271379, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 25, United-States, <=50K 55, Private, 231738, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, England, <=50K 33, Local-gov, 198183, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 21, State-gov, 140764, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 12, United-States, <=50K 43, Self-emp-not-inc, 183479, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 30, United-States, <=50K 35, Private, 165767, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Local-gov, 139364, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, >50K 19, Private, 227491, HS-grad, 9, Never-married, Sales, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 25, Private, 222254, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 44, Private, 193494, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 72, United-States, >50K 27, Private, 29261, Assoc-acdm, 12, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 174368, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 69, Private, 108196, 10th, 6, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 110622, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 20, ?, 201680, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 35, United-States, <=50K 37, Private, 130277, 5th-6th, 3, Separated, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 43, Local-gov, 98130, Bachelors, 13, Divorced, Prof-specialty, Own-child, White, Female, 0, 0, 39, United-States, <=50K 62, ?, 235521, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 48, United-States, <=50K 34, State-gov, 595000, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, Black, Female, 0, 0, 40, United-States, >50K 31, Self-emp-not-inc, 349148, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, <=50K 42, State-gov, 117583, Doctorate, 16, Divorced, Prof-specialty, Not-in-family, White, Female, 8614, 0, 60, United-States, >50K 26, Private, 164583, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 39, Private, 340091, Some-college, 10, Separated, Other-service, Unmarried, White, Female, 0, 0, 75, United-States, <=50K 25, Private, 49092, Bachelors, 13, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 54, Local-gov, 186884, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 30, United-States, <=50K 44, State-gov, 167265, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 34, State-gov, 34104, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 38, United-States, >50K 21, Self-emp-inc, 265116, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 128378, 5th-6th, 3, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 55, ?, <=50K 33, Private, 158416, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 40, Self-emp-inc, 169878, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 44, Private, 296728, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Local-gov, 342458, Assoc-acdm, 12, Divorced, Protective-serv, Not-in-family, White, Male, 0, 0, 56, United-States, <=50K 21, Local-gov, 38771, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 35, Self-emp-not-inc, 269300, Bachelors, 13, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 60, United-States, <=50K 43, Private, 111483, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 7298, 0, 40, United-States, >50K 57, ?, 199114, 10th, 6, Separated, ?, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 51, Local-gov, 33863, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, <=50K 29, Private, 132874, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Local-gov, 277024, HS-grad, 9, Separated, Protective-serv, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 35, Private, 112160, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 703067, 11th, 7, Never-married, Sales, Own-child, White, Male, 0, 0, 20, United-States, <=50K 58, Private, 127264, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 57, Self-emp-inc, 257200, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 19, Private, 57206, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 37, Private, 201319, Some-college, 10, Separated, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 114079, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 44, United-States, <=50K 45, Private, 230979, Some-college, 10, Married-spouse-absent, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 292472, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Cambodia, >50K 64, ?, 286732, 7th-8th, 4, Widowed, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Local-gov, 134444, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 72, United-States, <=50K 30, Private, 172403, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 46, Private, 191357, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, ?, 279288, 10th, 6, Never-married, ?, Other-relative, White, Female, 0, 0, 30, United-States, <=50K 60, Private, 389254, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Private, 303867, HS-grad, 9, Separated, Transport-moving, Not-in-family, White, Male, 0, 0, 44, United-States, <=50K 47, Private, 164113, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Black, Male, 7688, 0, 40, United-States, >50K 39, Private, 111499, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 266084, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 45, United-States, >50K 27, Private, 61580, Some-college, 10, Divorced, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 231348, Some-college, 10, Divorced, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 164748, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 205337, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 58, Self-emp-not-inc, 54566, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 35, United-States, <=50K 45, Private, 34419, Bachelors, 13, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 59, Private, 116442, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, <=50K 29, Private, 290740, Assoc-acdm, 12, Never-married, Priv-house-serv, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 27, Private, 255582, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 112517, Masters, 14, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 20, United-States, >50K 44, Private, 169397, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Private, 172664, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 70, United-States, >50K 27, Private, 329005, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 123253, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 55, Private, 81865, Assoc-voc, 11, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 32, Self-emp-not-inc, 173314, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, Other, Male, 0, 0, 60, United-States, <=50K 31, Private, 34572, Assoc-voc, 11, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 45, United-States, <=50K 57, Self-emp-inc, 159028, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 60, United-States, >50K 30, Private, 149184, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 78, ?, 363134, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 1, United-States, <=50K 28, Private, 308709, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 30, Self-emp-not-inc, 257295, Some-college, 10, Never-married, Sales, Other-relative, Asian-Pac-Islander, Male, 0, 2258, 40, South, <=50K 29, Private, 168479, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 66, Private, 142501, HS-grad, 9, Never-married, Other-service, Other-relative, Black, Female, 0, 0, 3, United-States, <=50K 60, Private, 338345, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 31, Private, 177675, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 262617, HS-grad, 9, Never-married, Craft-repair, Other-relative, White, Male, 2597, 0, 40, United-States, <=50K 24, Private, 200997, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 45, United-States, <=50K 29, Private, 176683, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 44, Private, 376072, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 45, United-States, >50K 34, Local-gov, 177675, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 59, Private, 348430, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 43, United-States, >50K 23, Private, 320451, Bachelors, 13, Never-married, Exec-managerial, Own-child, Asian-Pac-Islander, Male, 0, 0, 24, United-States, <=50K 23, Private, 38151, 11th, 7, Never-married, Other-service, Other-relative, White, Male, 0, 0, 40, Philippines, <=50K 55, Local-gov, 123382, Assoc-voc, 11, Separated, Prof-specialty, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 39, Self-emp-inc, 151029, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 484475, 11th, 7, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 57, Private, 329792, 7th-8th, 4, Divorced, Transport-moving, Unmarried, White, Male, 0, 0, 75, United-States, <=50K 35, Private, 148903, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 39, Local-gov, 301614, Assoc-voc, 11, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 48, United-States, >50K 47, Private, 176319, HS-grad, 9, Married-civ-spouse, Sales, Own-child, White, Female, 0, 0, 38, United-States, >50K 53, State-gov, 53197, Doctorate, 16, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, >50K 23, Private, 291407, Some-college, 10, Never-married, Sales, Own-child, Black, Male, 0, 0, 25, United-States, <=50K 35, Private, 204527, Masters, 14, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 44, Private, 476391, Some-college, 10, Divorced, Farming-fishing, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 224964, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 26, Private, 306225, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, Poland, <=50K 23, Private, 292023, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 32, Private, 94041, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 25, Ireland, <=50K 49, Self-emp-inc, 187563, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 36, Private, 176101, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 2174, 0, 60, United-States, <=50K 36, Private, 749105, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 36, United-States, <=50K 41, ?, 230020, 5th-6th, 3, Married-civ-spouse, ?, Husband, Other, Male, 0, 0, 40, United-States, <=50K 21, Private, 216070, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Wife, Amer-Indian-Eskimo, Female, 0, 0, 46, United-States, >50K 54, Self-emp-not-inc, 105010, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 43, Private, 198203, Some-college, 10, Married-spouse-absent, Other-service, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 35, Local-gov, 215419, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 120460, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, >50K 46, Private, 199316, Some-college, 10, Married-civ-spouse, Craft-repair, Other-relative, Asian-Pac-Islander, Male, 0, 0, 40, India, <=50K 46, Private, 146919, HS-grad, 9, Separated, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 56, Private, 174744, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, ?, 189564, Masters, 14, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 1, United-States, <=50K 21, Private, 249957, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 146574, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 47, State-gov, 156417, Some-college, 10, Divorced, Prof-specialty, Unmarried, White, Male, 0, 0, 20, United-States, <=50K 42, Private, 236110, 5th-6th, 3, Married-spouse-absent, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Puerto-Rico, <=50K 19, Private, 63363, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 30, United-States, <=50K 25, Private, 190107, Bachelors, 13, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 126569, Masters, 14, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 60, United-States, >50K 35, Private, 176756, 12th, 8, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 40, United-States, <=50K 40, Private, 115161, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 30, United-States, <=50K 57, Self-emp-not-inc, 138892, 11th, 7, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 15, United-States, <=50K 38, Private, 256864, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 50, United-States, >50K 48, Private, 265083, 10th, 6, Divorced, Sales, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 34, Private, 249948, Some-college, 10, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 34, United-States, <=50K 46, Federal-gov, 31141, Some-college, 10, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 164190, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 38, ?, <=50K 45, State-gov, 67544, Masters, 14, Divorced, Protective-serv, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 32, Self-emp-not-inc, 174789, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 35, Private, 199753, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 48, United-States, <=50K 62, Private, 122246, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Female, 8614, 0, 39, United-States, >50K 56, ?, 188166, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 96586, Assoc-voc, 11, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 189590, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 140590, Some-college, 10, Never-married, Sales, Not-in-family, Black, Male, 0, 0, 33, United-States, <=50K 35, Private, 255702, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 27, United-States, <=50K 33, Private, 260782, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 41, United-States, >50K 38, Private, 169926, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 1902, 40, United-States, >50K 37, State-gov, 151322, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 56, Private, 192869, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 19, Private, 93604, 7th-8th, 4, Never-married, Craft-repair, Own-child, White, Male, 0, 1602, 32, United-States, <=50K 31, Private, 86958, 9th, 5, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 53, Local-gov, 228723, HS-grad, 9, Divorced, Craft-repair, Not-in-family, Other, Male, 0, 0, 40, ?, >50K 33, Private, 192644, HS-grad, 9, Separated, Handlers-cleaners, Unmarried, White, Male, 0, 0, 35, Puerto-Rico, <=50K 72, Private, 284080, 1st-4th, 2, Divorced, Other-service, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 54, Private, 43269, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 30, Private, 190040, Bachelors, 13, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 306108, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 30, Private, 220148, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1848, 50, United-States, >50K 30, Private, 381645, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 32, Private, 216361, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 16, United-States, <=50K 30, Private, 213722, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 35, Private, 112271, Masters, 14, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 208277, Some-college, 10, Divorced, Adm-clerical, Own-child, White, Female, 0, 0, 44, United-States, >50K 38, State-gov, 352628, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 129620, 10th, 6, Never-married, Other-service, Other-relative, White, Female, 0, 0, 30, United-States, <=50K 32, Private, 249550, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 44, United-States, <=50K 49, Private, 178749, Masters, 14, Married-spouse-absent, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 76, ?, 173542, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 10, United-States, <=50K 60, Private, 167670, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, <=50K 60, Private, 81578, 9th, 5, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 160662, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 80, United-States, >50K 41, Private, 163322, Bachelors, 13, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 30, ?, <=50K 24, Private, 152189, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 106176, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 7298, 0, 60, United-States, >50K 69, State-gov, 159191, Some-college, 10, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 810, 38, United-States, <=50K 71, ?, 250263, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 3432, 0, 30, United-States, <=50K 41, Private, 78410, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 32, Private, 131379, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 166929, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 59, Private, 380357, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 79190, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 35, United-States, <=50K 40, Private, 342164, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 37, United-States, <=50K 44, Private, 182616, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 63, Private, 339473, Some-college, 10, Divorced, Sales, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 31, Local-gov, 381153, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 15024, 0, 56, United-States, >50K 51, Private, 300816, Bachelors, 13, Never-married, Adm-clerical, Unmarried, White, Male, 0, 0, 20, United-States, <=50K 51, Private, 240988, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 23, Private, 149224, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 168216, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, <=50K 56, Private, 286487, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 2885, 0, 45, United-States, <=50K 39, Private, 305597, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Self-emp-not-inc, 109766, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 50, United-States, >50K 30, Self-emp-not-inc, 188798, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 43, Self-emp-not-inc, 240170, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, Germany, <=50K 31, Private, 459465, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 44, Local-gov, 162506, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, <=50K 43, Self-emp-not-inc, 145441, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 30, United-States, >50K 37, Federal-gov, 129573, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 72, ?, >50K 41, Private, 27444, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 46, United-States, >50K 43, Private, 195258, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 47, State-gov, 55272, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Self-emp-not-inc, 164526, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 2824, 45, United-States, >50K 46, Private, 27802, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, State-gov, 165289, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 274657, 5th-6th, 3, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 50, Guatemala, <=50K 24, Private, 317175, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 39, Self-emp-inc, 163237, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 65, United-States, <=50K 37, Private, 170408, Assoc-voc, 11, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 28, ?, 55950, Bachelors, 13, Never-married, ?, Own-child, Black, Female, 0, 0, 40, Germany, <=50K 40, Private, 76625, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 366066, Assoc-acdm, 12, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 349368, HS-grad, 9, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 286824, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 12, United-States, <=50K 32, Private, 373263, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 161978, HS-grad, 9, Separated, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 543922, Masters, 14, Divorced, Transport-moving, Not-in-family, White, Male, 14344, 0, 48, United-States, >50K 46, Local-gov, 109089, Prof-school, 15, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Private, 110151, Assoc-voc, 11, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 26, Private, 34110, Some-college, 10, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 44, United-States, <=50K 47, Self-emp-not-inc, 118506, Bachelors, 13, Married-civ-spouse, Exec-managerial, Own-child, White, Male, 0, 0, 60, United-States, <=50K 22, Private, 117789, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 10, United-States, <=50K 34, Self-emp-not-inc, 353881, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 49, Private, 200471, 1st-4th, 2, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Portugal, <=50K 20, Private, 258517, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 25, United-States, <=50K 28, Private, 190367, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, <=50K 30, Private, 174704, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 23, Private, 179413, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 329530, 9th, 5, Never-married, Priv-house-serv, Own-child, White, Male, 0, 0, 40, Mexico, <=50K 31, Private, 273818, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 55, Mexico, <=50K 46, Private, 256522, 1st-4th, 2, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, Puerto-Rico, <=50K 42, Private, 196001, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 60, Self-emp-not-inc, 282660, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 72630, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 27, Private, 50295, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 48, United-States, <=50K 20, Private, 203240, 9th, 5, Never-married, Sales, Own-child, White, Female, 0, 0, 32, United-States, <=50K 56, Self-emp-not-inc, 172618, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 40, United-States, >50K 41, Private, 202168, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 61, Private, 176839, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 176140, HS-grad, 9, Divorced, Exec-managerial, Unmarried, Black, Female, 0, 0, 40, United-States, >50K 60, Private, 39952, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 2228, 0, 37, United-States, <=50K 33, Private, 292465, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, <=50K 40, ?, 161285, Some-college, 10, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 25, United-States, <=50K 48, Private, 355320, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, Canada, >50K 56, Private, 182460, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, >50K 50, Private, 69345, Assoc-voc, 11, Married-civ-spouse, Transport-moving, Husband, White, Male, 3103, 0, 55, United-States, >50K 57, Self-emp-not-inc, 102058, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Private, 165804, Some-college, 10, Never-married, Adm-clerical, Own-child, Other, Female, 0, 0, 40, United-States, <=50K 46, Private, 318259, Assoc-voc, 11, Divorced, Tech-support, Other-relative, White, Female, 0, 0, 36, United-States, <=50K 21, Private, 117606, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 170718, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 413297, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 190457, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 54, Private, 88278, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 50, United-States, >50K 32, Local-gov, 217296, HS-grad, 9, Married-civ-spouse, Transport-moving, Wife, White, Female, 4064, 0, 22, United-States, <=50K 62, ?, 97231, Some-college, 10, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 1, United-States, <=50K 50, Private, 123429, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 49, Federal-gov, 420282, Some-college, 10, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 48, Private, 498325, Assoc-acdm, 12, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 24, Private, 248533, Some-college, 10, Never-married, Sales, Other-relative, Black, Female, 0, 0, 40, United-States, <=50K 46, Private, 137354, Masters, 14, Married-civ-spouse, Tech-support, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, >50K 42, Private, 272910, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 52, Self-emp-inc, 206054, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, Local-gov, 92141, Assoc-acdm, 12, Widowed, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 37, Private, 163199, Some-college, 10, Divorced, Tech-support, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 34, Private, 195860, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 115717, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 2051, 40, United-States, <=50K 18, Private, 120029, Some-college, 10, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 20, United-States, <=50K 33, Private, 221762, Some-college, 10, Never-married, Prof-specialty, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 41, Private, 342164, Some-college, 10, Divorced, Sales, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 21, Private, 176356, Assoc-acdm, 12, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 23, Private, 133239, Assoc-voc, 11, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, Federal-gov, 169101, Some-college, 10, Never-married, Tech-support, Own-child, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 159442, Bachelors, 13, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 174461, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 45, United-States, <=50K 43, Private, 361280, 10th, 6, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 42, China, <=50K 52, State-gov, 447579, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, England, <=50K 27, ?, 308995, Some-college, 10, Divorced, ?, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 61, Private, 248448, 7th-8th, 4, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 161141, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 212465, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 45, Self-emp-inc, 170871, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 55, United-States, >50K 43, Local-gov, 233865, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 51, Private, 163052, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 348690, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Federal-gov, 34845, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, Germany, >50K 22, Private, 206861, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 49, Self-emp-inc, 349230, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 20, Private, 130840, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 20, United-States, <=50K 19, Private, 415354, 10th, 6, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 132191, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 202466, Assoc-acdm, 12, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 27, ?, 224421, Some-college, 10, Divorced, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 23, Self-emp-not-inc, 236804, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 35, United-States, <=50K 20, Private, 107658, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 10, United-States, <=50K 47, Private, 102771, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 17, Private, 221403, 12th, 8, Never-married, Other-service, Own-child, Black, Male, 0, 0, 18, United-States, <=50K 76, ?, 211574, 10th, 6, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 1, United-States, <=50K 39, Private, 52645, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 276310, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 31, Private, 134613, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Wife, Black, Female, 0, 0, 43, United-States, <=50K 44, Private, 215479, HS-grad, 9, Divorced, Transport-moving, Not-in-family, Black, Male, 0, 0, 20, Haiti, <=50K 53, Private, 266529, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 34, Private, 265807, Some-college, 10, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 45, Self-emp-not-inc, 67716, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 34, Private, 178951, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 35, Private, 241126, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 176544, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 45, Private, 169180, Some-college, 10, Widowed, Other-service, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 37, Self-emp-not-inc, 282461, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 53, Private, 157069, Assoc-acdm, 12, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 99357, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 15024, 0, 50, United-States, >50K 38, Self-emp-not-inc, 414991, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 70, ?, <=50K 65, Self-emp-inc, 338316, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Self-emp-not-inc, 59612, 10th, 6, Divorced, Farming-fishing, Unmarried, White, Male, 0, 0, 70, United-States, <=50K 24, Private, 220426, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 115912, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 27032, 10th, 6, Never-married, Sales, Own-child, White, Female, 0, 0, 12, United-States, <=50K 19, Private, 170720, 12th, 8, Never-married, Other-service, Own-child, White, Male, 0, 0, 16, United-States, <=50K 60, Private, 183162, HS-grad, 9, Widowed, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 192360, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 35, United-States, >50K 78, ?, 165694, Masters, 14, Widowed, ?, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 26, Private, 128553, Some-college, 10, Never-married, Exec-managerial, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 58, Private, 209423, 1st-4th, 2, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 38, Cuba, <=50K 37, Self-emp-not-inc, 121510, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 55, United-States, <=50K 41, Private, 93793, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 38, United-States, >50K 30, Private, 133602, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 391329, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 48, Private, 96359, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, Greece, >50K 22, Private, 203894, Some-college, 10, Never-married, Transport-moving, Not-in-family, White, Female, 0, 0, 24, United-States, <=50K 50, Private, 196193, Masters, 14, Married-spouse-absent, Prof-specialty, Other-relative, White, Male, 0, 0, 60, ?, <=50K 25, Private, 195994, 1st-4th, 2, Never-married, Priv-house-serv, Not-in-family, White, Female, 0, 0, 40, Guatemala, <=50K 18, Private, 50879, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 6, United-States, <=50K 21, Private, 186849, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 201127, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 33, Private, 110998, HS-grad, 9, Never-married, Other-service, Other-relative, Amer-Indian-Eskimo, Female, 0, 0, 36, United-States, <=50K 39, Private, 190466, HS-grad, 9, Divorced, Craft-repair, Own-child, White, Male, 2174, 0, 40, United-States, <=50K 67, Self-emp-not-inc, 173935, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 8, United-States, >50K 19, Private, 167140, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 1602, 24, United-States, <=50K 18, Private, 110230, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 11, United-States, <=50K 36, Private, 287658, HS-grad, 9, Never-married, Adm-clerical, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 23, Private, 224954, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 25, United-States, <=50K 25, ?, 394820, Some-college, 10, Separated, ?, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 40, Private, 37618, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, ?, <=50K 73, Self-emp-not-inc, 29306, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 37314, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 5013, 0, 40, United-States, <=50K 31, Private, 420749, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Private, 482732, 10th, 6, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 206215, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 101364, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Mexico, <=50K 66, Self-emp-inc, 185369, 10th, 6, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 30, United-States, <=50K 66, Private, 216856, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 64, Private, 256019, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 48, Private, 348144, Some-college, 10, Divorced, Transport-moving, Not-in-family, White, Male, 3325, 0, 53, United-States, <=50K 24, Private, 190293, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 51, Self-emp-not-inc, 25932, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 25, Private, 176729, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, >50K 33, Private, 166961, 11th, 7, Separated, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 50, Private, 86373, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, <=50K 51, Private, 320513, 7th-8th, 4, Married-spouse-absent, Craft-repair, Not-in-family, Black, Male, 0, 0, 50, Dominican-Republic, <=50K 34, State-gov, 190290, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 38, United-States, >50K 41, Local-gov, 111891, 7th-8th, 4, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 30, Self-emp-not-inc, 45796, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 59, Private, 108496, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 2907, 0, 40, United-States, <=50K 41, Self-emp-not-inc, 120539, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 3103, 0, 40, United-States, >50K 36, Self-emp-not-inc, 164526, Masters, 14, Never-married, Sales, Not-in-family, White, Male, 10520, 0, 45, United-States, >50K 37, Private, 323155, 1st-4th, 2, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 85, Mexico, <=50K 28, Private, 65389, HS-grad, 9, Never-married, Other-service, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 30, United-States, <=50K 19, Private, 414871, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 161607, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 62, Private, 224953, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 36, Private, 261382, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 45, United-States, >50K 58, Self-emp-not-inc, 231818, 10th, 6, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Greece, <=50K 42, Self-emp-inc, 184018, HS-grad, 9, Divorced, Sales, Unmarried, White, Male, 1151, 0, 50, United-States, <=50K 43, Self-emp-inc, 133060, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 35032, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, State-gov, 304212, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 64, Local-gov, 50442, 9th, 5, Never-married, Adm-clerical, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 146091, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 20, United-States, >50K 26, Private, 267431, Bachelors, 13, Never-married, Sales, Own-child, Black, Female, 0, 0, 20, United-States, <=50K 19, Private, 121240, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 21, Private, 192572, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 45, United-States, <=50K 32, Private, 211028, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Local-gov, 346122, Assoc-acdm, 12, Married-civ-spouse, Protective-serv, Husband, White, Male, 5013, 0, 45, United-States, <=50K 26, Private, 202203, Bachelors, 13, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 50, United-States, <=50K 20, Private, 159297, Some-college, 10, Never-married, Adm-clerical, Own-child, Asian-Pac-Islander, Female, 0, 0, 15, United-States, <=50K 19, Private, 310158, Some-college, 10, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 30, United-States, <=50K 33, Federal-gov, 193246, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 42, United-States, >50K 23, Private, 200089, Some-college, 10, Married-civ-spouse, Craft-repair, Other-relative, White, Male, 0, 0, 40, El-Salvador, <=50K 29, Private, 38353, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 42, Private, 76280, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 30, Self-emp-not-inc, 243665, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 63, Private, 68872, HS-grad, 9, Married-civ-spouse, Transport-moving, Wife, Asian-Pac-Islander, Female, 0, 0, 20, United-States, <=50K 34, Private, 103596, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 60, Self-emp-not-inc, 88055, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 24, United-States, <=50K 48, Private, 186203, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 50, United-States, <=50K 25, Private, 257910, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 27, Private, 200227, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 0, 40, United-States, <=50K 55, Self-emp-not-inc, 124975, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 27828, 0, 55, United-States, >50K 32, Private, 227669, Some-college, 10, Never-married, Machine-op-inspct, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 22, Private, 117210, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 25, Greece, <=50K 25, Private, 76144, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 18, Private, 98667, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 16, United-States, <=50K 24, Local-gov, 155818, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 44, United-States, <=50K 29, Private, 283760, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 73, ?, 281907, 11th, 7, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 3, United-States, <=50K 39, Private, 186183, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Self-emp-inc, 202153, Masters, 14, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 365683, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 22, Private, 187538, 10th, 6, Separated, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 33, ?, 209432, HS-grad, 9, Separated, ?, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 33, Private, 126950, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 42, Private, 110028, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 104660, Bachelors, 13, Separated, Prof-specialty, Unmarried, White, Male, 0, 0, 45, United-States, <=50K 57, Self-emp-not-inc, 437281, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 38, United-States, >50K 42, Private, 259643, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Male, 4650, 0, 40, United-States, <=50K 22, Private, 217961, Some-college, 10, Never-married, Transport-moving, Own-child, White, Male, 0, 1719, 30, United-States, <=50K 21, ?, 134746, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 35, United-States, <=50K 42, Self-emp-not-inc, 120539, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 39, Private, 25803, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, <=50K 41, Private, 63596, Some-college, 10, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 32, United-States, >50K 20, Local-gov, 325493, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 47, Private, 211239, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 206686, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 427965, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 52, Private, 218550, Some-college, 10, Married-spouse-absent, Adm-clerical, Not-in-family, White, Female, 14084, 0, 16, United-States, >50K 71, Private, 163385, Some-college, 10, Widowed, Sales, Not-in-family, White, Male, 0, 0, 35, United-States, >50K 52, Private, 124993, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 55, United-States, <=50K 36, Private, 107410, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 152373, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 48, United-States, >50K 37, Private, 161226, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 30, United-States, >50K 26, Private, 213799, 10th, 6, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 204461, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 35, Private, 377798, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 20, Private, 116375, 9th, 5, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 34, Local-gov, 210164, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1740, 40, United-States, <=50K 56, Self-emp-not-inc, 258752, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 39, Private, 327435, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 36, United-States, >50K 24, Private, 301199, Some-college, 10, Never-married, Tech-support, Own-child, White, Female, 0, 0, 20, United-States, <=50K 24, Private, 186221, 11th, 7, Divorced, Sales, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 23, Private, 203924, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 27, Private, 192236, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 25, Private, 152035, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 201454, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 156580, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 37, United-States, >50K 51, Private, 115851, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 106753, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1740, 40, United-States, <=50K 59, Private, 359292, 1st-4th, 2, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 29, Private, 83003, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 78817, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 24, Private, 200967, HS-grad, 9, Married-civ-spouse, Craft-repair, Wife, White, Female, 0, 0, 36, United-States, <=50K 38, State-gov, 107164, Some-college, 10, Separated, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 189674, HS-grad, 9, Never-married, Priv-house-serv, Unmarried, Black, Female, 0, 0, 28, ?, <=50K 34, Self-emp-not-inc, 90614, HS-grad, 9, Separated, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 42, Self-emp-not-inc, 323790, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 70, United-States, >50K 45, Self-emp-not-inc, 242552, 12th, 8, Divorced, Craft-repair, Other-relative, Black, Male, 0, 0, 35, United-States, <=50K 21, Private, 90935, Assoc-voc, 11, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 64, Self-emp-inc, 165667, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 60, Canada, >50K 32, Private, 162604, HS-grad, 9, Never-married, Machine-op-inspct, Other-relative, Black, Male, 0, 0, 40, United-States, <=50K 45, Private, 205424, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 53, Private, 97411, 5th-6th, 3, Married-civ-spouse, Machine-op-inspct, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Laos, <=50K 42, Private, 184857, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 16, United-States, <=50K 32, Private, 165226, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 115784, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 62, Private, 368476, 5th-6th, 3, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 24, Mexico, <=50K 28, Private, 53063, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 29, ?, 134566, Doctorate, 16, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 50, United-States, >50K 32, Private, 153471, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 37, Self-emp-inc, 107164, 10th, 6, Never-married, Transport-moving, Not-in-family, White, Male, 0, 2559, 50, United-States, >50K 38, Private, 180303, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 50, Japan, >50K 44, Local-gov, 236321, HS-grad, 9, Divorced, Transport-moving, Own-child, White, Male, 0, 0, 25, United-States, <=50K 19, Private, 141868, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 22, ?, 367655, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 203518, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 58, Private, 119558, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 56, Private, 108276, Bachelors, 13, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 385452, 10th, 6, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 162003, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 349028, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 45114, Bachelors, 13, Never-married, Sales, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 44, Private, 112797, 9th, 5, Divorced, Other-service, Own-child, White, Female, 0, 0, 50, United-States, <=50K 28, Private, 183639, HS-grad, 9, Never-married, Handlers-cleaners, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 177121, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 38, Private, 239755, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 150361, Some-college, 10, Never-married, Tech-support, Own-child, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 293091, 11th, 7, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 60, United-States, <=50K 24, Private, 200089, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, Mexico, >50K 40, Private, 91836, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 23, Private, 324960, HS-grad, 9, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 79, Local-gov, 84616, 11th, 7, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 7, United-States, <=50K 44, Private, 252930, 10th, 6, Divorced, Adm-clerical, Unmarried, Other, Female, 0, 0, 42, United-States, <=50K 51, Private, 44000, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 99999, 0, 50, United-States, >50K 30, Private, 154843, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 99307, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 3103, 0, 48, United-States, >50K 41, Private, 182567, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, ?, >50K 33, Private, 93206, 5th-6th, 3, Married-civ-spouse, Farming-fishing, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 50, Private, 100109, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 45, United-States, >50K 51, Private, 114927, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 7298, 0, 40, United-States, >50K 41, Private, 121287, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 189916, Bachelors, 13, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 30, United-States, >50K 34, Private, 157747, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 40, United-States, >50K 28, Private, 39232, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 31, Self-emp-inc, 133861, Assoc-voc, 11, Divorced, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 505980, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 67, ?, 183374, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 2329, 0, 15, United-States, <=50K 65, Private, 193216, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 9386, 0, 40, United-States, >50K 39, Self-emp-not-inc, 140752, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 23, Private, 549349, Some-college, 10, Never-married, Tech-support, Own-child, White, Male, 0, 0, 40, United-States, <=50K 29, Self-emp-not-inc, 179008, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 57, Self-emp-not-inc, 190554, 10th, 6, Divorced, Exec-managerial, Own-child, White, Male, 0, 0, 60, United-States, >50K 47, Private, 80924, Some-college, 10, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 51, Local-gov, 319054, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 60, United-States, <=50K 34, Private, 297094, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, United-States, <=50K 52, Private, 170562, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 29, Private, 240738, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Private, 297544, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Local-gov, 169905, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 149637, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 182526, Bachelors, 13, Married-spouse-absent, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 55, Self-emp-not-inc, 158315, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 61, Self-emp-inc, 227232, Bachelors, 13, Separated, Sales, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 34, Private, 96483, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, Asian-Pac-Islander, Female, 8614, 0, 60, United-States, >50K 41, Private, 286970, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Local-gov, 223529, Assoc-voc, 11, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 43, United-States, <=50K 78, Self-emp-not-inc, 316261, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 99999, 0, 20, United-States, >50K 40, Private, 170214, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Self-emp-not-inc, 224361, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 75, United-States, <=50K 43, Private, 124919, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 60, Japan, <=50K 55, ?, 103654, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 25, Private, 306352, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, Mexico, <=50K 26, Self-emp-not-inc, 227858, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 43, Self-emp-inc, 150533, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 68, United-States, >50K 25, Private, 144478, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, Poland, <=50K 22, Private, 254547, Some-college, 10, Never-married, Adm-clerical, Other-relative, Black, Female, 0, 0, 30, Jamaica, <=50K 52, Self-emp-not-inc, 313243, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, >50K 61, Private, 149981, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 2414, 0, 5, United-States, <=50K 42, Private, 125461, Bachelors, 13, Never-married, Sales, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 306967, Assoc-voc, 11, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 192976, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 65, Private, 192133, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 2290, 0, 40, Greece, <=50K 56, ?, 131608, HS-grad, 9, Divorced, ?, Not-in-family, White, Male, 0, 0, 10, United-States, <=50K 33, Federal-gov, 339388, Assoc-acdm, 12, Divorced, Other-service, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 203240, 10th, 6, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 83827, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 24, United-States, <=50K 45, Self-emp-inc, 160440, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 42, United-States, <=50K 42, Private, 108502, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 42, United-States, <=50K 37, Private, 410913, HS-grad, 9, Married-spouse-absent, Farming-fishing, Unmarried, Other, Male, 0, 0, 40, Mexico, <=50K 56, Private, 193818, 9th, 5, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, ?, 163582, 10th, 6, Divorced, ?, Unmarried, White, Female, 0, 0, 16, ?, <=50K 40, Private, 103789, Assoc-acdm, 12, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 32, United-States, <=50K 31, Private, 34572, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, <=50K 26, Private, 43408, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, State-gov, 105787, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 42, Self-emp-inc, 90693, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 70, United-States, <=50K 45, Self-emp-not-inc, 285575, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 40, China, <=50K 47, Local-gov, 56482, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 7688, 0, 50, United-States, >50K 22, Private, 496025, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 33, Private, 382764, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 259284, HS-grad, 9, Never-married, Transport-moving, Not-in-family, Black, Male, 0, 0, 50, United-States, <=50K 48, Self-emp-not-inc, 185385, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 98, United-States, <=50K 57, Self-emp-not-inc, 286836, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 8, United-States, <=50K 47, Private, 139145, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 58, Local-gov, 44246, 9th, 5, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 169611, 11th, 7, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 52, Private, 133403, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, <=50K 29, Private, 187327, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 180032, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 46561, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 23, Private, 86065, 12th, 8, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 46, Self-emp-not-inc, 256014, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 30, Private, 188403, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 43, Self-emp-not-inc, 396758, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 1887, 70, United-States, >50K 25, Private, 60485, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 30, United-States, <=50K 32, Private, 271276, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 80, United-States, >50K 56, Private, 229525, 9th, 5, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 33, Private, 34574, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 43, United-States, <=50K 19, State-gov, 112432, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 10, United-States, <=50K 20, Private, 105312, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 18, United-States, <=50K 34, Private, 221396, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 304872, 9th, 5, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 55, Self-emp-not-inc, 319733, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 176012, 9th, 5, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 23, United-States, <=50K 31, Private, 213750, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 30, Private, 248384, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 351187, HS-grad, 9, Divorced, Other-service, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 138179, HS-grad, 9, Separated, Machine-op-inspct, Not-in-family, White, Male, 0, 1876, 40, United-States, <=50K 59, Private, 50223, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, Private, 117477, HS-grad, 9, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 36, United-States, <=50K 40, Private, 194360, 9th, 5, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 118108, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 25, Local-gov, 90730, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 40, United-States, >50K 18, Self-emp-inc, 38307, 11th, 7, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 30, United-States, <=50K 41, Private, 116391, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 210496, 10th, 6, Widowed, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 168475, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Private, 174386, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 24, United-States, <=50K 39, Private, 166744, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 38, United-States, <=50K 19, Private, 375114, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 373469, Assoc-acdm, 12, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 339667, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 41, United-States, <=50K 39, Private, 91711, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Private, 82049, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 236242, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 57, Self-emp-inc, 140319, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, <=50K 33, Local-gov, 34080, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 56, Private, 204816, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 60, Private, 187124, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 72310, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 58, Private, 175127, 12th, 8, Married-civ-spouse, Transport-moving, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 48, Federal-gov, 205707, Masters, 14, Married-spouse-absent, Exec-managerial, Not-in-family, White, Female, 10520, 0, 50, United-States, >50K 45, Local-gov, 236586, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 55, United-States, >50K 18, Private, 71792, HS-grad, 9, Never-married, Sales, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 56, Private, 87584, HS-grad, 9, Widowed, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 48, Self-emp-inc, 136878, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, >50K 40, Private, 287983, Bachelors, 13, Never-married, Tech-support, Not-in-family, Asian-Pac-Islander, Female, 0, 2258, 48, Philippines, <=50K 38, Private, 110607, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 32, United-States, <=50K 58, Private, 109015, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 235071, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 50, United-States, <=50K 63, Private, 88653, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, ?, <=50K 51, Private, 332243, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 22, ?, 291547, 5th-6th, 3, Married-civ-spouse, ?, Wife, Other, Female, 0, 0, 40, Mexico, <=50K 44, Private, 45093, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 70, United-States, <=50K 46, Federal-gov, 161337, Some-college, 10, Divorced, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 64, State-gov, 211222, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 295117, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, England, >50K 31, Private, 206541, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 238415, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 21, Private, 29810, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 30, Private, 108023, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 114324, Assoc-voc, 11, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 54, Private, 172281, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 2051, 50, United-States, <=50K 59, Local-gov, 197290, 9th, 5, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Local-gov, 191177, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 20, United-States, >50K 57, Private, 562558, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 79531, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 53, Self-emp-inc, 157881, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 58, Self-emp-not-inc, 204816, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 19, Private, 185695, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 39, Self-emp-inc, 167482, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 31, Self-emp-inc, 83748, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, Asian-Pac-Islander, Female, 0, 0, 70, South, <=50K 27, Private, 39232, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Local-gov, 236827, 9th, 5, Separated, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 37, Self-emp-not-inc, 154410, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 135308, Bachelors, 13, Never-married, Sales, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 33, Private, 204042, Some-college, 10, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 20, Private, 308239, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 16, United-States, <=50K 55, Private, 183884, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 39, Private, 98948, Assoc-acdm, 12, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 141642, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 162623, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 39, Self-emp-inc, 186934, Bachelors, 13, Married-spouse-absent, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 179512, HS-grad, 9, Separated, Exec-managerial, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 25, Private, 391192, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 24, United-States, <=50K 31, Private, 87054, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 51, Private, 30008, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 24, Private, 113466, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 70, Private, 642830, HS-grad, 9, Divorced, Protective-serv, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 23, Private, 182117, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 162432, HS-grad, 9, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, Self-emp-not-inc, 242184, 7th-8th, 4, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 47, Private, 170850, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 4064, 0, 60, United-States, <=50K 56, Private, 435022, Some-college, 10, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 79, Private, 120707, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 20051, 0, 35, El-Salvador, >50K 20, Private, 170800, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 15, United-States, <=50K 30, Private, 268575, HS-grad, 9, Never-married, Craft-repair, Unmarried, Asian-Pac-Islander, Male, 0, 0, 40, Vietnam, <=50K 27, Private, 269354, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 25, ?, <=50K 40, Private, 224232, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 60, ?, 153072, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 5, United-States, <=50K 58, Private, 177368, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 71, Self-emp-not-inc, 163293, Prof-school, 15, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 2, United-States, <=50K 50, Private, 178530, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 29, Local-gov, 183523, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, Iran, <=50K 33, Private, 207267, 10th, 6, Separated, Other-service, Unmarried, White, Female, 3418, 0, 35, United-States, <=50K 60, State-gov, 27037, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, >50K 33, Private, 176711, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 43, Private, 163215, Bachelors, 13, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 35, ?, >50K 33, Private, 394727, 10th, 6, Never-married, Handlers-cleaners, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 33, Private, 195488, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 52, United-States, <=50K 32, State-gov, 443546, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 45, United-States, <=50K 21, Private, 121023, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 9, United-States, <=50K 38, Private, 51838, HS-grad, 9, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 258888, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 35, United-States, >50K 39, State-gov, 189385, Some-college, 10, Separated, Exec-managerial, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 17, Private, 198146, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 15, United-States, <=50K 21, Private, 337766, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 210525, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 20, United-States, >50K 42, Private, 185602, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 36, Private, 173804, 11th, 7, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 251243, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 37, Self-emp-not-inc, 415847, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 119793, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 181705, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 182360, HS-grad, 9, Separated, Prof-specialty, Unmarried, Other, Female, 0, 0, 60, Puerto-Rico, <=50K 49, Private, 61885, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 146520, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Private, 323790, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 146268, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Federal-gov, 287031, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Male, 8614, 0, 40, United-States, >50K 33, Local-gov, 292217, HS-grad, 9, Divorced, Protective-serv, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 88126, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 143046, Masters, 14, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 401623, Some-college, 10, Married-civ-spouse, Tech-support, Husband, Black, Male, 0, 0, 40, Jamaica, >50K 36, Self-emp-not-inc, 283122, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 1902, 60, United-States, >50K 84, Self-emp-not-inc, 155057, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 20, United-States, <=50K 23, Private, 260254, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 152292, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 55, Self-emp-inc, 138594, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 45, United-States, >50K 30, Self-emp-not-inc, 523095, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 46, Private, 175262, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 0, 40, India, <=50K 55, Private, 323706, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 40, United-States, >50K 34, Private, 316470, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 54, Self-emp-not-inc, 163815, Masters, 14, Divorced, Sales, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 27, Private, 72208, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 52, Local-gov, 74784, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 36, Private, 383518, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 99999, 0, 40, United-States, >50K 25, Self-emp-not-inc, 266668, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 347519, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 24, Private, 336088, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 50, United-States, <=50K 36, Private, 190350, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 31, Private, 204052, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 66, ?, 31362, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 20, United-States, <=50K 90, Self-emp-not-inc, 155981, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 10566, 0, 50, United-States, <=50K 67, Private, 195161, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 20051, 0, 60, United-States, >50K 22, Self-emp-inc, 269583, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 2580, 0, 40, United-States, <=50K 47, Private, 26994, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 32, Private, 116539, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1887, 55, United-States, >50K 55, Self-emp-not-inc, 189933, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 32, Private, 101283, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 48, Private, 113598, Some-college, 10, Separated, Adm-clerical, Other-relative, Black, Female, 0, 0, 40, United-States, <=50K 21, Private, 188793, HS-grad, 9, Married-civ-spouse, Sales, Husband, Other, Male, 0, 0, 35, United-States, <=50K 33, Private, 109996, Assoc-acdm, 12, Married-spouse-absent, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 195681, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 48, ?, <=50K 47, Private, 436770, Assoc-voc, 11, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 84253, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 24, United-States, <=50K 44, Self-emp-inc, 383493, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, >50K 23, Private, 216867, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 37, Mexico, <=50K 18, Private, 401051, 10th, 6, Never-married, Sales, Own-child, White, Female, 0, 0, 35, United-States, <=50K 56, Private, 83196, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 24, Private, 325596, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 35, United-States, <=50K 43, Private, 187322, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Private, 193949, Bachelors, 13, Never-married, Sales, Own-child, White, Female, 0, 0, 60, United-States, <=50K 26, Private, 133373, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 42, United-States, <=50K 42, Private, 113324, HS-grad, 9, Widowed, Sales, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 178818, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 53, Self-emp-not-inc, 152810, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 335997, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 4386, 0, 55, United-States, >50K 40, Private, 436493, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 25, United-States, <=50K 27, Private, 704108, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 24, Local-gov, 150084, Some-college, 10, Separated, Protective-serv, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 42, Private, 341204, HS-grad, 9, Divorced, Craft-repair, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 187336, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 204209, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 10, United-States, <=50K 42, Self-emp-not-inc, 206066, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 65, United-States, <=50K 38, Private, 63509, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 63, Self-emp-not-inc, 391121, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 30, United-States, <=50K 31, Private, 56026, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Self-emp-not-inc, 60981, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 4, United-States, <=50K 21, Private, 228255, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, United-States, <=50K 24, Private, 86745, Bachelors, 13, Married-civ-spouse, Prof-specialty, Other-relative, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 55, Private, 234327, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 59948, 9th, 5, Never-married, Adm-clerical, Unmarried, Black, Female, 114, 0, 20, United-States, <=50K 31, Private, 137814, Some-college, 10, Divorced, Sales, Own-child, White, Female, 0, 0, 30, United-States, <=50K 23, Private, 167692, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 35, Private, 245090, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Mexico, <=50K 51, Self-emp-not-inc, 256963, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 19, Private, 160033, Some-college, 10, Never-married, Protective-serv, Own-child, White, Female, 0, 0, 30, United-States, <=50K 38, Local-gov, 289430, HS-grad, 9, Divorced, Protective-serv, Not-in-family, White, Male, 0, 0, 56, United-States, <=50K 52, Local-gov, 305053, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 2051, 40, United-States, <=50K 70, Self-emp-not-inc, 172370, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 25, United-States, <=50K 53, Private, 320510, 10th, 6, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 59, Private, 171355, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 65027, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 43, United-States, <=50K 18, Private, 215190, 12th, 8, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 41, ?, 149385, HS-grad, 9, Never-married, ?, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 19, ?, 169324, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 10, United-States, <=50K 24, Private, 138938, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 557082, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 32, Private, 273287, Some-college, 10, Never-married, Exec-managerial, Not-in-family, Black, Male, 0, 0, 40, Jamaica, <=50K 34, Self-emp-not-inc, 77209, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 1902, 60, United-States, >50K 35, Private, 317153, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 50, Private, 95469, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 7298, 0, 45, United-States, >50K 18, Private, 302859, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 20, United-States, <=50K 37, Private, 333651, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 42, United-States, <=50K 30, Private, 177596, Some-college, 10, Never-married, Other-service, Unmarried, White, Female, 0, 0, 36, United-States, <=50K 40, Self-emp-inc, 157240, Masters, 14, Married-civ-spouse, Exec-managerial, Wife, White, Female, 15024, 0, 30, Iran, >50K 22, Private, 184779, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 50, Local-gov, 138358, Some-college, 10, Separated, Other-service, Unmarried, Black, Female, 0, 0, 28, United-States, <=50K 70, Private, 176285, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 23, United-States, <=50K 43, Private, 102180, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 77, Self-emp-not-inc, 209507, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Self-emp-not-inc, 229741, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 324546, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 39, United-States, <=50K 51, Private, 337195, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 1902, 50, United-States, >50K 58, State-gov, 194068, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 50, United-States, >50K 22, Private, 250647, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 12, United-States, <=50K 33, Private, 477106, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 27, Private, 104329, 11th, 7, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 224566, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 32, Private, 169841, Some-college, 10, Divorced, Sales, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 41, Private, 42563, Bachelors, 13, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 25, United-States, >50K 37, Private, 31368, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 132755, 11th, 7, Never-married, Sales, Own-child, White, Male, 0, 0, 15, United-States, <=50K 50, Private, 279129, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 55, United-States, >50K 31, ?, 86143, HS-grad, 9, Married-civ-spouse, ?, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 54, State-gov, 44172, HS-grad, 9, Separated, Exec-managerial, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 23, State-gov, 93076, HS-grad, 9, Never-married, Other-service, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 40, Private, 146653, Bachelors, 13, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 29, Private, 221366, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 5013, 0, 40, Germany, <=50K 38, Private, 189404, HS-grad, 9, Married-spouse-absent, Other-service, Not-in-family, White, Male, 0, 0, 35, ?, <=50K 30, Private, 172304, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, <=50K 20, Private, 116666, Some-college, 10, Never-married, Sales, Own-child, Asian-Pac-Islander, Male, 0, 0, 8, India, <=50K 43, Self-emp-not-inc, 64112, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 25, Private, 55718, Some-college, 10, Never-married, Tech-support, Own-child, White, Male, 0, 0, 25, United-States, <=50K 39, Private, 126675, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 48, Private, 102112, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 41, Self-emp-not-inc, 226505, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 211527, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 20, Private, 175069, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, Yugoslavia, <=50K 25, Private, 25249, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 57, Private, 73411, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 207185, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 35, Puerto-Rico, >50K 66, Private, 127139, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 34, Private, 41809, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 297449, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 14084, 0, 40, United-States, >50K 46, Private, 141483, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, <=50K 42, Local-gov, 117227, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 46, Private, 377401, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1902, 70, Canada, >50K 34, Local-gov, 167063, HS-grad, 9, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 253759, Some-college, 10, Married-civ-spouse, Tech-support, Wife, Black, Female, 0, 0, 40, United-States, <=50K 42, Private, 183096, Some-college, 10, Divorced, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 269654, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 70, ?, 293076, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 30, United-States, <=50K 32, Private, 34104, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Federal-gov, 80057, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, Germany, >50K 42, Self-emp-inc, 369781, 7th-8th, 4, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 25, United-States, <=50K 21, Private, 223811, Assoc-voc, 11, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 163053, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 189461, HS-grad, 9, Never-married, Sales, Other-relative, White, Male, 0, 0, 55, United-States, <=50K 50, Local-gov, 145166, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7298, 0, 40, United-States, >50K 37, Private, 86310, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 19, ?, 263224, 11th, 7, Never-married, ?, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 44, Federal-gov, 280362, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Private, 301031, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 30, Private, 74966, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 24, United-States, <=50K 36, Private, 254493, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 44, United-States, <=50K 49, Self-emp-not-inc, 204241, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 29, Private, 225024, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 45, Local-gov, 148222, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 75, State-gov, 113868, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 20, United-States, >50K 42, Private, 132633, HS-grad, 9, Never-married, Priv-house-serv, Not-in-family, White, Female, 0, 0, 40, ?, <=50K 37, Private, 44780, Assoc-acdm, 12, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 86373, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 25, United-States, <=50K 61, Local-gov, 176753, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 48, United-States, <=50K 33, Private, 164707, Assoc-acdm, 12, Never-married, Exec-managerial, Unmarried, White, Female, 2174, 0, 55, ?, <=50K 50, Local-gov, 370733, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, <=50K 59, Private, 216851, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 137951, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 22, Private, 185279, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 16, United-States, <=50K 56, Private, 159724, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 44, Private, 103233, Bachelors, 13, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 35, Private, 63509, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 57, Private, 174353, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 47, Self-emp-not-inc, 168109, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 15024, 0, 50, United-States, >50K 27, Private, 159724, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 50, Self-emp-not-inc, 105010, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 2051, 20, United-States, <=50K 30, Private, 179112, Bachelors, 13, Never-married, Prof-specialty, Own-child, Black, Male, 0, 0, 40, ?, <=50K 46, Private, 364913, 11th, 7, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 48, Self-emp-inc, 155664, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 61, Private, 230568, Bachelors, 13, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 33, Private, 86492, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 87, United-States, <=50K 40, Private, 71305, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 40, United-States, <=50K 58, Self-emp-inc, 189933, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 65, United-States, >50K 46, Self-emp-inc, 191978, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 2392, 50, United-States, >50K 35, Private, 38948, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 51, Self-emp-inc, 139127, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 37, Private, 301568, 12th, 8, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 64, Private, 149044, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 2057, 60, China, <=50K 41, Private, 197344, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 54, United-States, <=50K 18, Private, 32244, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 594, 0, 30, United-States, <=50K 44, Self-emp-not-inc, 315406, 11th, 7, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 88, United-States, <=50K 41, State-gov, 47170, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, Amer-Indian-Eskimo, Female, 0, 0, 48, United-States, >50K 33, State-gov, 208785, Some-college, 10, Separated, Prof-specialty, Not-in-family, White, Male, 10520, 0, 40, United-States, >50K 37, Private, 196338, 9th, 5, Separated, Priv-house-serv, Unmarried, White, Female, 0, 0, 16, Mexico, <=50K 34, Private, 269243, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 24, Federal-gov, 215115, Bachelors, 13, Never-married, Tech-support, Own-child, White, Female, 0, 0, 40, ?, <=50K 20, Private, 117767, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 176101, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 138283, Assoc-voc, 11, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 20, Self-emp-not-inc, 132320, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 45, United-States, <=50K 22, Federal-gov, 471452, Bachelors, 13, Never-married, Tech-support, Own-child, White, Male, 0, 0, 8, United-States, <=50K 55, Private, 147653, Bachelors, 13, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 73, United-States, <=50K 20, Private, 49179, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 26, Private, 174921, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 20, Self-emp-inc, 95997, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 70, United-States, <=50K 40, Private, 247245, 9th, 5, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 67072, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 54, ?, 95329, Some-college, 10, Divorced, ?, Own-child, White, Male, 0, 0, 50, United-States, <=50K 24, Private, 107882, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 241825, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 46, United-States, <=50K 18, Private, 79443, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 8, United-States, <=50K 49, Self-emp-not-inc, 233059, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 17, Private, 226980, 12th, 8, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 17, United-States, <=50K 34, Self-emp-not-inc, 181087, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 37, Private, 305597, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 49, Federal-gov, 311671, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 74, Private, 129879, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 15831, 0, 40, United-States, >50K 37, Private, 83375, HS-grad, 9, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 115824, 11th, 7, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 1573, 40, United-States, <=50K 40, Private, 141657, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 35, United-States, >50K 34, Private, 50276, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 27828, 0, 40, United-States, >50K 30, Private, 177216, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 1740, 40, Haiti, <=50K 44, Private, 228057, HS-grad, 9, Separated, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, Puerto-Rico, <=50K 40, Private, 222848, 10th, 6, Married-civ-spouse, Other-service, Wife, Black, Female, 0, 0, 32, United-States, <=50K 58, Private, 121111, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, Greece, <=50K 44, Private, 298885, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 149909, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 25, United-States, >50K 39, Private, 387430, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 18, United-States, <=50K 19, Private, 121972, HS-grad, 9, Never-married, Other-service, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 41, Private, 280167, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 70, United-States, >50K 29, State-gov, 191355, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, Federal-gov, 112115, Some-college, 10, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 38, ?, 104094, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 15, United-States, <=50K 27, Private, 211032, Preschool, 1, Married-civ-spouse, Farming-fishing, Other-relative, White, Male, 41310, 0, 24, Mexico, <=50K 54, Private, 199307, Some-college, 10, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 48, United-States, <=50K 40, Private, 205175, HS-grad, 9, Widowed, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 37, United-States, <=50K 19, Private, 257750, Some-college, 10, Never-married, Sales, Other-relative, White, Female, 0, 0, 25, United-States, <=50K 17, Private, 191260, 11th, 7, Never-married, Other-service, Own-child, White, Male, 594, 0, 10, United-States, <=50K 33, Private, 342730, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 52, United-States, <=50K 80, Private, 249983, 7th-8th, 4, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 24, United-States, <=50K 24, Self-emp-not-inc, 161508, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 50, United-States, <=50K 28, Private, 338376, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 334308, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 30, United-States, >50K 21, Private, 133471, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 129177, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 19, Private, 178811, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 42, Private, 178537, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 24, United-States, <=50K 60, Self-emp-not-inc, 235535, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 48, United-States, <=50K 20, ?, 298155, Some-college, 10, Never-married, ?, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 51, Private, 145114, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 194096, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 37, State-gov, 191779, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 159732, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 52, United-States, <=50K 42, Federal-gov, 170230, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 14084, 0, 60, United-States, >50K 40, Private, 104719, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 163083, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Private, 403552, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 32, United-States, <=50K 62, Private, 218009, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1977, 60, United-States, >50K 47, Private, 179313, 10th, 6, Divorced, Sales, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 26, Private, 51961, 12th, 8, Never-married, Sales, Other-relative, Black, Male, 0, 0, 51, United-States, <=50K 59, Private, 426001, HS-grad, 9, Married-spouse-absent, Adm-clerical, Unmarried, White, Female, 0, 0, 20, Puerto-Rico, <=50K 70, Local-gov, 176493, Some-college, 10, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 17, United-States, <=50K 26, Private, 124068, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 47, Private, 108510, 10th, 6, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 65, United-States, <=50K 25, Private, 181528, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 43, United-States, <=50K 52, Self-emp-inc, 173754, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 60, United-States, >50K 46, Private, 169699, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 67, Private, 126849, 10th, 6, Married-civ-spouse, Transport-moving, Husband, Amer-Indian-Eskimo, Male, 0, 0, 20, United-States, <=50K 34, Private, 204470, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 53, State-gov, 116367, Some-college, 10, Divorced, Adm-clerical, Other-relative, White, Female, 4650, 0, 40, United-States, <=50K 22, Private, 117363, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 39, Local-gov, 106297, HS-grad, 9, Divorced, Adm-clerical, Own-child, White, Male, 0, 0, 42, United-States, <=50K 54, Self-emp-not-inc, 108933, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 24, Private, 190143, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 246677, HS-grad, 9, Separated, Prof-specialty, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 38, Private, 175360, 10th, 6, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 2559, 90, United-States, >50K 41, Local-gov, 210259, Masters, 14, Never-married, Prof-specialty, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 36, Private, 166304, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 33, United-States, <=50K 43, Private, 303051, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 40, United-States, >50K 39, Private, 49308, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 192262, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 0, 45, United-States, <=50K 49, Local-gov, 192349, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 4650, 0, 40, United-States, <=50K 37, Self-emp-not-inc, 48063, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 43, Private, 170214, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 54, Federal-gov, 51048, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 53, Self-emp-inc, 246562, 5th-6th, 3, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, Mexico, >50K 57, Local-gov, 215175, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 28, Private, 114967, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Private, 464536, Bachelors, 13, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 451996, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 138852, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, State-gov, 353012, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Self-emp-inc, 321822, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 75, United-States, >50K 50, Self-emp-not-inc, 324506, HS-grad, 9, Widowed, Exec-managerial, Unmarried, Asian-Pac-Islander, Female, 0, 0, 48, South, <=50K 36, Private, 162256, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 31, Local-gov, 356689, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 260199, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 10, United-States, <=50K 36, Private, 103605, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 316211, HS-grad, 9, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 308691, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 39, Private, 194404, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 40, United-States, >50K 18, Private, 334427, 10th, 6, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 36, United-States, <=50K 33, Private, 213226, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 35, Private, 342824, HS-grad, 9, Never-married, Tech-support, Not-in-family, White, Female, 1151, 0, 40, United-States, <=50K 23, Private, 33105, Some-college, 10, Never-married, Handlers-cleaners, Own-child, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 37, Private, 147638, Bachelors, 13, Separated, Other-service, Unmarried, Asian-Pac-Islander, Female, 0, 0, 36, Philippines, <=50K 25, Private, 315643, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 30, United-States, <=50K 51, Federal-gov, 106257, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, Black, Male, 0, 0, 40, United-States, <=50K 35, Private, 342768, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 108960, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 66, ?, 168071, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 30, United-States, <=50K 32, Private, 136935, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 13, United-States, <=50K 37, Self-emp-not-inc, 188774, Bachelors, 13, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 55, United-States, >50K 29, Private, 280344, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 45, Private, 202496, Bachelors, 13, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 37, United-States, <=50K 61, Self-emp-inc, 134768, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 175686, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 194748, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Female, 0, 0, 49, United-States, <=50K 49, Private, 61307, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, Other, Male, 0, 0, 38, United-States, <=50K 51, Self-emp-not-inc, 165001, Masters, 14, Divorced, Exec-managerial, Unmarried, White, Male, 25236, 0, 50, United-States, >50K 34, Private, 325658, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, ?, 201844, HS-grad, 9, Separated, ?, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 20, Private, 505980, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 185336, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 37, United-States, <=50K 49, Self-emp-inc, 362795, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Male, 99999, 0, 80, Mexico, >50K 26, Private, 126829, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 63, Private, 264600, 10th, 6, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, <=50K 36, Private, 82743, Assoc-acdm, 12, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 55, Iran, <=50K 63, Self-emp-not-inc, 125178, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 22, Private, 128487, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 10, United-States, <=50K 40, Private, 321758, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 128220, 7th-8th, 4, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 49, Private, 176814, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, Canada, <=50K 35, Private, 188069, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 13550, 0, 55, ?, >50K 23, State-gov, 156423, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 20, United-States, <=50K 25, Private, 169905, Assoc-voc, 11, Never-married, Sales, Not-in-family, White, Male, 27828, 0, 40, United-States, >50K 34, ?, 157289, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 176972, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 44, Self-emp-not-inc, 171424, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 2205, 35, United-States, <=50K 33, Private, 91811, HS-grad, 9, Separated, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 203924, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 2597, 0, 45, United-States, <=50K 55, Private, 177484, 11th, 7, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 1672, 40, United-States, <=50K 17, ?, 454614, 11th, 7, Never-married, ?, Own-child, White, Female, 0, 0, 8, United-States, <=50K 75, Self-emp-not-inc, 242108, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 2346, 0, 15, United-States, <=50K 61, Private, 132972, 9th, 5, Never-married, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 53, Private, 157947, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, Local-gov, 177482, Assoc-acdm, 12, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 45, United-States, >50K 48, Private, 246891, Some-college, 10, Widowed, Sales, Unmarried, White, Male, 0, 0, 50, United-States, >50K 28, State-gov, 158834, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 30, ?, 203834, Bachelors, 13, Never-married, ?, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 50, Taiwan, <=50K 29, Private, 110442, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 45, United-States, <=50K 25, Private, 240676, Some-college, 10, Divorced, Tech-support, Own-child, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 192939, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Local-gov, 260696, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 55, United-States, <=50K 40, Local-gov, 55363, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 144949, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 55, Private, 116878, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 30, United-States, >50K 31, Local-gov, 357954, Assoc-acdm, 12, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 21, ?, 170038, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 32, Self-emp-not-inc, 190290, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, Italy, <=50K 26, State-gov, 203279, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, Asian-Pac-Islander, Male, 2463, 0, 50, India, <=50K 26, Private, 167761, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 44, Private, 138845, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 144844, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 52, United-States, >50K 21, ?, 161930, HS-grad, 9, Never-married, ?, Own-child, Black, Female, 0, 1504, 30, United-States, <=50K 26, Private, 55743, HS-grad, 9, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 40, Self-emp-not-inc, 117721, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 19, Self-emp-not-inc, 116385, 11th, 7, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 58, Private, 301867, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 238913, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Self-emp-not-inc, 123983, Some-college, 10, Married-civ-spouse, Sales, Own-child, Asian-Pac-Islander, Male, 0, 0, 63, South, <=50K 26, Private, 165510, Bachelors, 13, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 64, Private, 183513, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 42, Self-emp-inc, 119281, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 41, Private, 152629, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 45, Private, 110171, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 211440, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 41, Local-gov, 359259, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 125796, 11th, 7, Separated, Other-service, Not-in-family, Black, Female, 0, 0, 40, Jamaica, <=50K 34, Private, 39609, Assoc-voc, 11, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 111567, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 45, Germany, >50K 23, Private, 44064, Some-college, 10, Separated, Other-service, Not-in-family, White, Male, 0, 2559, 40, United-States, >50K 35, Self-emp-not-inc, 120066, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Amer-Indian-Eskimo, Male, 0, 0, 60, United-States, <=50K 41, Private, 132633, 11th, 7, Divorced, Priv-house-serv, Unmarried, White, Female, 0, 0, 25, Guatemala, <=50K 39, Private, 192702, Masters, 14, Never-married, Craft-repair, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 41, Private, 166813, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, <=50K 33, Self-emp-inc, 40444, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 290504, HS-grad, 9, Never-married, Other-service, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 178505, Some-college, 10, Never-married, Exec-managerial, Other-relative, White, Female, 0, 1504, 45, United-States, <=50K 25, Private, 175370, Some-college, 10, Divorced, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 77, Self-emp-not-inc, 72931, 7th-8th, 4, Married-spouse-absent, Adm-clerical, Not-in-family, White, Male, 0, 0, 20, Italy, >50K 33, ?, 234542, Assoc-voc, 11, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 66, Private, 284021, HS-grad, 9, Widowed, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 277974, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 35, United-States, <=50K 44, Private, 111275, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 38, United-States, <=50K 45, Self-emp-inc, 191776, Masters, 14, Divorced, Sales, Unmarried, White, Female, 25236, 0, 42, United-States, >50K 28, Private, 125527, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 19, Private, 38294, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, White, Male, 2597, 0, 40, United-States, <=50K 43, Private, 313022, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 4386, 0, 40, United-States, >50K 39, Private, 179668, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 15024, 0, 40, United-States, >50K 33, Private, 198660, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 44, Private, 216116, HS-grad, 9, Married-spouse-absent, Other-service, Not-in-family, Black, Female, 0, 0, 40, Jamaica, <=50K 62, Private, 200922, 7th-8th, 4, Widowed, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 153372, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 41, Private, 406603, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 6, Iran, <=50K 23, Local-gov, 248344, Some-college, 10, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 30, United-States, <=50K 48, Private, 240629, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Italy, >50K 38, Private, 314310, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, <=50K 37, Private, 259785, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 45, Private, 127111, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 29, Private, 178272, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 66, Local-gov, 75134, HS-grad, 9, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 19, Private, 195985, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 23, Private, 221955, 9th, 5, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 39, Mexico, <=50K 34, Private, 177675, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 182828, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 33, Self-emp-not-inc, 270889, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 43, Private, 183096, Some-college, 10, Separated, Sales, Unmarried, White, Female, 0, 0, 10, United-States, <=50K 27, Private, 336951, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 99, United-States, <=50K 33, State-gov, 295589, Some-college, 10, Separated, Adm-clerical, Own-child, Black, Male, 0, 0, 35, United-States, <=50K 26, Private, 289980, 5th-6th, 3, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 30, Mexico, <=50K 56, Self-emp-inc, 70720, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Male, 27828, 0, 60, United-States, >50K 46, Private, 163352, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 36, United-States, <=50K 38, Private, 190776, Assoc-acdm, 12, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 90, Private, 313986, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 72, Self-emp-inc, 473748, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 25, United-States, >50K 20, Private, 163003, HS-grad, 9, Never-married, Adm-clerical, Unmarried, Asian-Pac-Islander, Female, 0, 0, 15, United-States, <=50K 29, Private, 183061, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Amer-Indian-Eskimo, Male, 0, 0, 48, United-States, <=50K 49, Private, 123584, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 75, United-States, <=50K 23, Private, 120910, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 20, Private, 227554, Some-college, 10, Married-spouse-absent, Sales, Own-child, Black, Female, 0, 0, 18, United-States, <=50K 57, Private, 182677, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 4508, 0, 40, South, <=50K 46, Private, 214955, Assoc-acdm, 12, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 209768, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 24, Private, 258120, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 55, Jamaica, <=50K 49, Private, 110015, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, Greece, <=50K 54, Private, 152652, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 65, United-States, <=50K 46, Federal-gov, 43206, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 1564, 50, United-States, >50K 31, Self-emp-not-inc, 114639, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 43, Self-emp-inc, 221172, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 40, United-States, >50K 18, ?, 128538, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 6, United-States, <=50K 19, Private, 131615, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 353824, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 178417, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 58, Private, 178644, HS-grad, 9, Widowed, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 43, Self-emp-not-inc, 271665, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 37, ?, 223732, Some-college, 10, Separated, ?, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 21, Federal-gov, 169003, 12th, 8, Never-married, Adm-clerical, Own-child, Black, Male, 0, 0, 25, United-States, <=50K 52, State-gov, 338816, Masters, 14, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 70, United-States, >50K 34, Private, 506858, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 32, United-States, >50K 28, Private, 265628, Assoc-voc, 11, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 173495, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 177413, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 31670, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 65, United-States, <=50K 49, Private, 154451, 11th, 7, Divorced, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 35, Private, 265535, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 50, Jamaica, >50K 31, Private, 118941, Some-college, 10, Divorced, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 18, Private, 214617, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 30, United-States, <=50K 47, Local-gov, 265097, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 4386, 0, 40, United-States, >50K 46, Private, 276087, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 5013, 0, 50, United-States, <=50K 43, Private, 124692, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 51, Federal-gov, 306784, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 4386, 0, 40, United-States, >50K 21, Private, 434102, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 18, ?, 387641, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 31, State-gov, 181824, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 1902, 35, United-States, >50K 39, Local-gov, 177907, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 1887, 40, United-States, >50K 58, Private, 87329, 11th, 7, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 48, United-States, <=50K 36, Private, 263130, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 262882, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 37546, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 1902, 35, United-States, >50K 19, Private, 27433, 11th, 7, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 393945, Assoc-voc, 11, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 36, United-States, <=50K 26, Private, 173927, Assoc-voc, 11, Never-married, Prof-specialty, Own-child, Other, Female, 0, 0, 60, Jamaica, <=50K 38, Private, 343403, Assoc-acdm, 12, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 16, United-States, <=50K 36, Private, 111128, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 40, Private, 193882, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 25, Private, 310864, Bachelors, 13, Never-married, Tech-support, Not-in-family, Black, Male, 0, 0, 40, ?, <=50K 41, Private, 128354, Bachelors, 13, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 25, United-States, >50K 33, Private, 113364, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 63, ?, 198559, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 16, United-States, <=50K 51, Private, 136913, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 115488, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 154227, Assoc-voc, 11, Divorced, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 279667, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 30, Self-emp-not-inc, 281030, HS-grad, 9, Never-married, Sales, Unmarried, White, Male, 0, 0, 66, United-States, <=50K 19, Private, 283945, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 25, United-States, <=50K 47, Private, 454989, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 26, Private, 391349, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, State-gov, 166704, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 14, United-States, <=50K 36, Private, 151835, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 60, United-States, >50K 60, Private, 199085, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 61487, HS-grad, 9, Never-married, Prof-specialty, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 19, Private, 120251, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 14, United-States, <=50K 42, Private, 273230, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 90, United-States, <=50K 36, Private, 358373, HS-grad, 9, Separated, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 36, United-States, <=50K 35, Private, 267891, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 38, United-States, <=50K 22, Private, 234880, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 25, United-States, <=50K 54, Private, 48358, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 96452, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, <=50K 55, Private, 204751, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 65, United-States, <=50K 57, Private, 375868, Masters, 14, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, Private, 413373, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 36, United-States, <=50K 24, Private, 537222, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 35, Local-gov, 33975, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 51, Self-emp-inc, 162327, 11th, 7, Divorced, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 182691, HS-grad, 9, Divorced, Exec-managerial, Own-child, White, Male, 0, 0, 44, United-States, <=50K 36, Private, 300829, Assoc-acdm, 12, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 42, United-States, <=50K 51, Local-gov, 114508, 9th, 5, Separated, Other-service, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 46, Self-emp-inc, 214627, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 42, Private, 129684, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, Black, Female, 5455, 0, 50, United-States, <=50K 25, State-gov, 120041, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 361138, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 50, United-States, <=50K 37, Private, 76893, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 205424, Bachelors, 13, Divorced, Sales, Unmarried, White, Male, 0, 0, 40, United-States, >50K 61, Private, 176839, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 50, United-States, >50K 40, Private, 229148, 12th, 8, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, Jamaica, <=50K 58, Self-emp-inc, 154537, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 20, United-States, >50K 52, Private, 181901, HS-grad, 9, Married-spouse-absent, Farming-fishing, Other-relative, White, Male, 0, 0, 20, Mexico, <=50K 18, Private, 152004, 11th, 7, Never-married, Other-service, Own-child, Black, Male, 0, 0, 20, United-States, <=50K 27, Private, 205188, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Self-emp-not-inc, 30840, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 5013, 0, 45, United-States, <=50K 63, Private, 66634, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 16, United-States, <=50K 38, Self-emp-not-inc, 180220, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 31, Private, 291052, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 2051, 40, United-States, <=50K 40, Self-emp-not-inc, 99651, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 41, Private, 327723, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 32291, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 2174, 0, 40, United-States, <=50K 31, Private, 345122, Prof-school, 15, Divorced, Prof-specialty, Not-in-family, White, Male, 14084, 0, 50, United-States, >50K 32, Private, 127384, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, >50K 30, Private, 363296, HS-grad, 9, Never-married, Handlers-cleaners, Unmarried, Black, Male, 0, 0, 72, United-States, <=50K 39, Local-gov, 86551, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 1876, 40, United-States, <=50K 28, Private, 30070, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 31, Private, 595000, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, Black, Female, 0, 0, 35, United-States, <=50K 21, ?, 152328, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 20, United-States, <=50K 33, ?, 177824, HS-grad, 9, Separated, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 44, State-gov, 111483, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 22, Private, 199555, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 25, United-States, <=50K 42, Private, 50018, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, ?, <=50K 36, Private, 218490, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 39, Private, 49020, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 1974, 40, United-States, <=50K 61, Private, 213321, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1672, 40, United-States, <=50K 31, Private, 159187, HS-grad, 9, Divorced, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 83033, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 25, Germany, <=50K 39, Self-emp-not-inc, 31848, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 2829, 0, 90, United-States, <=50K 34, Self-emp-not-inc, 24961, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 80, United-States, <=50K 21, Private, 182117, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 15, United-States, <=50K 75, Self-emp-not-inc, 146576, Bachelors, 13, Widowed, Prof-specialty, Unmarried, White, Male, 0, 0, 48, United-States, >50K 21, Private, 176690, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 24, United-States, <=50K 81, Private, 122651, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 15, United-States, <=50K 54, Self-emp-inc, 149650, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 40, Canada, <=50K 34, Private, 454508, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 65, Iran, <=50K 54, Self-emp-not-inc, 269068, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 99999, 0, 50, Philippines, >50K 41, Private, 266530, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Amer-Indian-Eskimo, Male, 0, 0, 45, United-States, <=50K 61, ?, 198542, Bachelors, 13, Divorced, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 63, Private, 133144, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 2580, 0, 20, United-States, <=50K 24, Private, 217961, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 221661, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, Mexico, <=50K 44, Local-gov, 60735, Bachelors, 13, Divorced, Prof-specialty, Own-child, White, Female, 0, 0, 60, United-States, <=50K 47, Self-emp-not-inc, 121124, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 48588, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 48087, 7th-8th, 4, Divorced, Craft-repair, Not-in-family, White, Male, 0, 1590, 40, United-States, <=50K 53, Self-emp-not-inc, 240138, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 63, Private, 273010, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 3471, 0, 40, United-States, <=50K 44, Private, 104196, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 37, Private, 230035, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 46, United-States, >50K 28, Private, 38918, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, Germany, >50K 71, ?, 205011, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 10, United-States, <=50K 57, Private, 176079, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 180052, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 10, United-States, <=50K 33, Local-gov, 173005, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 1848, 45, United-States, >50K 30, Private, 378723, Some-college, 10, Divorced, Adm-clerical, Own-child, White, Female, 0, 0, 55, United-States, <=50K 20, Private, 233624, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 192591, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 54, Private, 249860, 11th, 7, Divorced, Priv-house-serv, Unmarried, Black, Female, 0, 0, 10, United-States, <=50K 20, Private, 247564, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 35, United-States, <=50K 34, Private, 238912, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 190227, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 29, State-gov, 293287, Some-college, 10, Never-married, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 180807, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 250217, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 70, United-States, <=50K 19, Private, 217418, Some-college, 10, Never-married, Adm-clerical, Other-relative, Black, Female, 0, 0, 38, United-States, <=50K 22, Local-gov, 137510, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 59, State-gov, 163047, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 18, Private, 577521, 11th, 7, Never-married, Sales, Own-child, White, Male, 0, 0, 13, United-States, <=50K 22, Private, 221533, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 42, Local-gov, 255675, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 114079, Assoc-acdm, 12, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 155781, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 243762, 11th, 7, Separated, Craft-repair, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 113062, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 7, United-States, <=50K 67, Private, 217028, Masters, 14, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 17, Private, 110723, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 25, United-States, <=50K 47, Federal-gov, 191858, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Private, 179423, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 5, United-States, <=50K 20, Private, 339588, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, Peru, <=50K 22, Private, 206815, HS-grad, 9, Never-married, Sales, Unmarried, White, Female, 0, 0, 40, Peru, <=50K 47, State-gov, 103743, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 235683, Some-college, 10, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, >50K 64, ?, 207321, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 20, United-States, <=50K 35, State-gov, 197495, Some-college, 10, Divorced, Exec-managerial, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 52, Federal-gov, 424012, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 178469, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 73, Self-emp-inc, 92886, 10th, 6, Widowed, Sales, Unmarried, White, Female, 0, 0, 40, Canada, <=50K 38, Self-emp-not-inc, 214008, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 59, Self-emp-not-inc, 325732, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 52, United-States, >50K 35, Private, 28572, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 4064, 0, 35, United-States, <=50K 18, Private, 118376, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 15, United-States, <=50K 24, Private, 51799, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 0, 40, United-States, <=50K 33, Local-gov, 115488, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 40, Private, 190621, Some-college, 10, Divorced, Exec-managerial, Other-relative, Black, Female, 0, 0, 55, United-States, <=50K 55, Private, 193568, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 192878, HS-grad, 9, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 264663, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 60, United-States, <=50K 22, Private, 234731, HS-grad, 9, Divorced, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 308373, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 45, Private, 205644, HS-grad, 9, Separated, Tech-support, Not-in-family, White, Female, 0, 0, 26, United-States, <=50K 47, Local-gov, 321851, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 56, Private, 206399, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 124563, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 32, State-gov, 198211, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 17, Private, 130795, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 44, Private, 71269, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 32, Self-emp-not-inc, 319280, Assoc-acdm, 12, Never-married, Sales, Not-in-family, White, Male, 0, 0, 80, United-States, <=50K 35, Private, 125933, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 27, Private, 107236, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 32732, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 68, Private, 284763, 11th, 7, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 20, Private, 112668, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 33, Private, 376483, Some-college, 10, Divorced, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 24, Private, 402778, 9th, 5, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 12, United-States, <=50K 48, Private, 36177, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 45, Private, 125489, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 48, Private, 304791, Some-college, 10, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 209205, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 60, ?, 112821, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 35, United-States, >50K 39, Local-gov, 178100, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 70261, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, United-States, <=50K 23, State-gov, 186634, 12th, 8, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 32958, Some-college, 10, Separated, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 254746, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, <=50K 52, Private, 158746, HS-grad, 9, Never-married, Other-service, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 35, Self-emp-not-inc, 140854, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 51506, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 189564, Bachelors, 13, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 42, United-States, >50K 37, Federal-gov, 325538, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, ?, >50K 58, Private, 213975, Assoc-voc, 11, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 67, Self-emp-not-inc, 431426, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 2, United-States, <=50K 48, Private, 199763, HS-grad, 9, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 8, United-States, <=50K 63, Private, 161563, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, <=50K 24, Local-gov, 252024, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 72, United-States, >50K 43, Private, 43945, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 178487, HS-grad, 9, Divorced, Transport-moving, Own-child, White, Male, 0, 0, 60, United-States, <=50K 32, Private, 604506, HS-grad, 9, Married-civ-spouse, Transport-moving, Own-child, White, Male, 0, 0, 72, Mexico, <=50K 36, Private, 228157, Some-college, 10, Never-married, Craft-repair, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, Laos, <=50K 43, Private, 199191, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 27, Private, 189775, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 17, Private, 171080, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 12, United-States, <=50K 45, Private, 117310, Bachelors, 13, Divorced, Sales, Not-in-family, White, Female, 0, 0, 46, United-States, <=50K 41, Self-emp-inc, 82049, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Self-emp-not-inc, 126094, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 38, United-States, <=50K 18, ?, 202516, HS-grad, 9, Never-married, ?, Own-child, White, Female, 0, 0, 35, United-States, <=50K 48, Local-gov, 246392, Assoc-acdm, 12, Separated, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 51, ?, 69328, Assoc-voc, 11, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 50, United-States, >50K 26, Private, 292803, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 24, United-States, <=50K 54, Private, 286989, Preschool, 1, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 22, Private, 190483, Some-college, 10, Divorced, Sales, Own-child, White, Female, 0, 0, 48, Iran, <=50K 19, Private, 235849, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 35, United-States, <=50K 47, Private, 359766, 7th-8th, 4, Divorced, Handlers-cleaners, Other-relative, Black, Male, 0, 0, 40, United-States, <=50K 32, Private, 128016, HS-grad, 9, Married-spouse-absent, Other-service, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 46, Private, 360096, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 60, United-States, >50K 30, Private, 170154, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 35, Private, 337286, Masters, 14, Never-married, Exec-managerial, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 52, Private, 204322, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 5013, 0, 40, United-States, <=50K 73, Self-emp-not-inc, 143833, 12th, 8, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 18, United-States, <=50K 17, Private, 365613, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 10, Canada, <=50K 32, Private, 100135, Bachelors, 13, Separated, Prof-specialty, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 43, Local-gov, 180096, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 19, ?, 371827, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 0, 40, Portugal, <=50K 26, Private, 61270, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, Other, Female, 0, 0, 40, Columbia, <=50K 41, Federal-gov, 564135, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 49, Private, 198759, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 60, United-States, >50K 52, State-gov, 303462, Some-college, 10, Separated, Protective-serv, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 193106, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 57, Private, 250201, 11th, 7, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 52, United-States, <=50K 35, Private, 200426, Assoc-voc, 11, Married-spouse-absent, Prof-specialty, Unmarried, White, Female, 0, 0, 44, United-States, <=50K 33, Private, 222654, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 56, Private, 53366, 7th-8th, 4, Divorced, Transport-moving, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 132222, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 0, 60, United-States, <=50K 17, Private, 100828, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 20, United-States, <=50K 49, Private, 31264, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 39, Private, 202027, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 34, Self-emp-not-inc, 168906, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 37, Self-emp-not-inc, 255454, Some-college, 10, Never-married, Prof-specialty, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 22, Private, 245524, 12th, 8, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 27, Private, 386040, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Mexico, <=50K 21, Private, 35424, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 25, United-States, <=50K 59, ?, 93655, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 152629, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 3103, 0, 40, United-States, >50K 53, Self-emp-not-inc, 151159, 10th, 6, Married-spouse-absent, Transport-moving, Not-in-family, White, Male, 0, 0, 99, United-States, <=50K 26, Private, 410240, 11th, 7, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 138970, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 39, Private, 269722, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 70, United-States, <=50K 34, Private, 223678, HS-grad, 9, Never-married, Other-service, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 32, United-States, <=50K 54, State-gov, 197184, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 38, United-States, <=50K 36, Private, 143486, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 7298, 0, 50, United-States, >50K 60, Private, 160625, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 5013, 0, 40, United-States, <=50K 50, Private, 140516, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 48, Local-gov, 85341, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, <=50K 35, Private, 108293, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 2205, 40, United-States, <=50K 40, Self-emp-not-inc, 192507, Assoc-acdm, 12, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 30, Private, 186932, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 70, United-States, <=50K 65, Self-emp-not-inc, 223580, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 6514, 0, 40, United-States, >50K 31, Private, 236861, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 46, Local-gov, 327886, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 67, ?, 407618, 9th, 5, Divorced, ?, Not-in-family, White, Female, 2050, 0, 40, United-States, <=50K 62, Self-emp-inc, 197060, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 38, Private, 229180, Bachelors, 13, Never-married, Exec-managerial, Unmarried, White, Female, 0, 0, 40, Cuba, <=50K 24, Private, 284317, Bachelors, 13, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 24, Private, 73514, Some-college, 10, Never-married, Sales, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 50, Philippines, <=50K 27, Private, 47907, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 43, State-gov, 134782, Assoc-acdm, 12, Married-spouse-absent, Other-service, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 48, Private, 118831, HS-grad, 9, Divorced, Handlers-cleaners, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, South, <=50K 41, Private, 299505, HS-grad, 9, Separated, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 30, Private, 267161, Some-college, 10, Married-civ-spouse, Tech-support, Wife, Black, Female, 0, 0, 45, United-States, <=50K 38, Private, 119177, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 45, Private, 327886, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 45, Private, 187730, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 109015, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 46, Self-emp-not-inc, 110015, 7th-8th, 4, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 75, Greece, <=50K 24, Private, 104146, Bachelors, 13, Never-married, Prof-specialty, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 31, Local-gov, 50442, Some-college, 10, Never-married, Adm-clerical, Own-child, Amer-Indian-Eskimo, Female, 0, 0, 25, United-States, <=50K 35, Private, 57640, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 37, Local-gov, 333664, Some-college, 10, Separated, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 224858, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, <=50K 56, Private, 290641, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 60, ?, 191118, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 1848, 40, United-States, >50K 25, Private, 34402, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 1590, 60, United-States, <=50K 33, Private, 245378, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 179136, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 116788, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 129699, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 46, Federal-gov, 39606, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, England, >50K 44, Self-emp-inc, 95150, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 63, Private, 102479, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 199191, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 30, United-States, <=50K 31, Private, 229636, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, Mexico, <=50K 26, Private, 53833, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 42, United-States, <=50K 37, Self-emp-inc, 27997, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 60, ?, 124487, Some-college, 10, Divorced, ?, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 33, Private, 111363, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 38, Private, 107630, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 134287, Assoc-voc, 11, Never-married, Sales, Own-child, White, Female, 0, 0, 35, United-States, <=50K 46, Self-emp-inc, 283004, Assoc-voc, 11, Divorced, Exec-managerial, Unmarried, Asian-Pac-Islander, Female, 0, 0, 63, Thailand, <=50K 24, Private, 33616, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 47, Local-gov, 121124, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, >50K 27, Private, 188189, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 46, Private, 106255, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Federal-gov, 282830, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, >50K 47, Private, 243904, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Male, 0, 0, 40, Honduras, <=50K 69, Private, 165017, HS-grad, 9, Widowed, Machine-op-inspct, Unmarried, White, Male, 2538, 0, 40, United-States, <=50K 32, Private, 131584, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 7298, 0, 40, United-States, >50K 51, Private, 427781, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 36, Private, 334291, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 50, Local-gov, 173224, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 87507, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 60, India, <=50K 32, Private, 187560, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 3908, 0, 40, United-States, <=50K 27, Private, 204497, 10th, 6, Divorced, Transport-moving, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 75, United-States, <=50K 60, Private, 230545, 7th-8th, 4, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, Cuba, <=50K 31, Private, 118161, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 150499, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Local-gov, 96554, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 288551, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 52, United-States, >50K 69, Self-emp-not-inc, 104003, 7th-8th, 4, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, <=50K 54, Self-emp-inc, 124963, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 56, Private, 198388, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Federal-gov, 126204, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 91709, Assoc-acdm, 12, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 34, Self-emp-not-inc, 152109, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 24, Self-emp-not-inc, 191954, 7th-8th, 4, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 50, United-States, <=50K 63, Private, 108097, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 10566, 0, 45, United-States, <=50K 29, Local-gov, 289991, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 64, Private, 92115, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 320277, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 33610, HS-grad, 9, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 60, United-States, <=50K 36, Private, 168276, 10th, 6, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 55, State-gov, 175127, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 7688, 0, 38, United-States, >50K 37, Private, 254973, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Wife, White, Female, 0, 0, 40, United-States, >50K 37, Private, 95336, 10th, 6, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 63, Private, 346975, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 7688, 0, 36, United-States, >50K 33, Private, 227282, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 19, Private, 138153, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 10, United-States, <=50K 57, Local-gov, 174132, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, Black, Female, 0, 1977, 40, United-States, >50K 31, Private, 182237, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 4386, 0, 45, United-States, >50K 20, ?, 111252, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 30, United-States, <=50K 58, Local-gov, 217775, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 40, United-States, >50K 20, ?, 168863, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 20, United-States, <=50K 25, Private, 394503, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 141657, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 125441, 11th, 7, Never-married, Other-service, Own-child, White, Male, 1055, 0, 20, United-States, <=50K 26, Private, 172230, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 282944, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 45, Local-gov, 55377, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 40, United-States, <=50K 35, State-gov, 49352, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 38, United-States, <=50K 32, Private, 213887, Some-college, 10, Divorced, Machine-op-inspct, Unmarried, White, Male, 0, 0, 45, United-States, <=50K 61, Self-emp-not-inc, 24046, HS-grad, 9, Widowed, Other-service, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 26, State-gov, 208122, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 15, United-States, <=50K 56, Private, 176118, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 3103, 0, 40, United-States, >50K 22, Private, 227994, Some-college, 10, Married-spouse-absent, Adm-clerical, Own-child, Asian-Pac-Islander, Female, 0, 0, 39, United-States, <=50K 49, Private, 215389, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 48, United-States, <=50K 40, Private, 99434, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 12, United-States, <=50K 37, Private, 190964, HS-grad, 9, Separated, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 23, ?, 113700, Bachelors, 13, Never-married, ?, Own-child, White, Male, 0, 0, 50, United-States, <=50K 28, Private, 259840, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 27, Private, 168827, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Self-emp-inc, 28984, Assoc-voc, 11, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 182211, 9th, 5, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 45, United-States, <=50K 41, Private, 82393, Some-college, 10, Never-married, Craft-repair, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 28, Private, 183639, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 21, United-States, <=50K 38, Private, 342448, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 47, State-gov, 469907, Assoc-acdm, 12, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 1740, 40, United-States, <=50K 28, Local-gov, 211920, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, State-gov, 33658, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 50, United-States, >50K 41, Federal-gov, 34178, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 400630, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 36, United-States, >50K 73, Self-emp-not-inc, 161251, HS-grad, 9, Widowed, Craft-repair, Not-in-family, White, Male, 0, 0, 24, United-States, <=50K 21, Private, 255685, Some-college, 10, Never-married, Other-service, Own-child, Black, Male, 0, 0, 40, Outlying-US(Guam-USVI-etc), <=50K 38, Private, 199256, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 64, ?, 143716, Masters, 14, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 2, United-States, <=50K 47, Private, 221666, Some-college, 10, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 52, Private, 145409, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 15024, 0, 60, Canada, >50K 24, Private, 39615, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 44, Private, 104440, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 151382, 7th-8th, 4, Divorced, Machine-op-inspct, Unmarried, White, Male, 0, 974, 40, United-States, <=50K 61, Self-emp-not-inc, 503675, Some-college, 10, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 60, United-States, >50K 58, Private, 306233, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 40, United-States, >50K 51, Private, 216475, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 1564, 43, United-States, >50K 49, Private, 50748, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 0, 55, England, <=50K 23, Private, 107190, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Male, 0, 0, 20, United-States, <=50K 19, Private, 206874, Assoc-voc, 11, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 21, Private, 83141, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 53, United-States, <=50K 56, Private, 444089, 11th, 7, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 141896, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Federal-gov, 33487, Some-college, 10, Divorced, Tech-support, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 20, United-States, <=50K 41, Private, 65372, Doctorate, 16, Divorced, Sales, Unmarried, White, Female, 0, 0, 50, United-States, >50K 30, Private, 341346, 11th, 7, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 343403, Doctorate, 16, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 20, ?, <=50K 47, Private, 287480, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 59, Self-emp-inc, 107287, 10th, 6, Widowed, Exec-managerial, Unmarried, White, Female, 0, 2559, 50, United-States, >50K 55, Private, 199067, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 32, United-States, <=50K 22, ?, 182771, Assoc-voc, 11, Never-married, ?, Own-child, Asian-Pac-Islander, Male, 0, 0, 20, United-States, <=50K 31, Private, 159737, 10th, 6, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 30, Private, 110643, Masters, 14, Married-civ-spouse, Adm-clerical, Husband, White, Male, 4386, 0, 40, United-States, >50K 24, Private, 117583, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 48, United-States, <=50K 49, Self-emp-not-inc, 43479, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 203003, 7th-8th, 4, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 25, Germany, <=50K 50, Private, 133963, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 38, Private, 227794, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 20, Self-emp-not-inc, 112137, Some-college, 10, Never-married, Prof-specialty, Other-relative, Asian-Pac-Islander, Female, 0, 0, 20, South, <=50K 49, Self-emp-not-inc, 110457, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 45, Private, 281565, HS-grad, 9, Widowed, Other-service, Other-relative, Asian-Pac-Islander, Female, 0, 0, 50, South, <=50K 46, Federal-gov, 297906, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 50, United-States, >50K 19, Private, 151506, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 31, Federal-gov, 139455, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, Cuba, <=50K 38, Private, 26987, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 56, Self-emp-not-inc, 233312, Masters, 14, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 24, Private, 161092, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 58, Local-gov, 98361, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 28, Private, 188928, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 164922, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 185673, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 193598, Preschool, 1, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 56, Private, 274111, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, >50K 32, Private, 245482, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Asian-Pac-Islander, Male, 0, 0, 40, ?, <=50K 56, Private, 160932, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 44, United-States, >50K 50, Private, 44368, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, ?, 291374, HS-grad, 9, Separated, ?, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 30, Private, 280927, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 222993, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 42, Federal-gov, 25240, Assoc-voc, 11, Divorced, Prof-specialty, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 31, Self-emp-not-inc, 204052, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 18, Private, 74054, 11th, 7, Never-married, Sales, Own-child, Other, Female, 0, 0, 20, ?, <=50K 46, Private, 169042, 10th, 6, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 25, Ecuador, <=50K 31, Private, 104509, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 65, United-States, >50K 38, Local-gov, 185394, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 7688, 0, 40, United-States, >50K 44, Local-gov, 254146, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 55, Self-emp-inc, 227856, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 2415, 50, United-States, >50K 19, Private, 183041, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 45, Private, 107682, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 50, Self-emp-inc, 287598, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 70, United-States, <=50K 53, Private, 182186, 9th, 5, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Dominican-Republic, <=50K 41, Self-emp-inc, 194636, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 99999, 0, 65, United-States, >50K 45, Private, 112305, Some-college, 10, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 21, Private, 212661, 10th, 6, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 39, United-States, <=50K 37, Private, 32709, Bachelors, 13, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 40, United-States, >50K 42, Federal-gov, 46366, HS-grad, 9, Separated, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 37, Self-emp-not-inc, 24106, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 30, United-States, <=50K 46, Private, 170850, Bachelors, 13, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 1590, 40, ?, <=50K 45, Self-emp-not-inc, 40666, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 32, Private, 182975, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 30, Private, 345122, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 57, ?, 208311, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 80, United-States, >50K 37, Private, 120045, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 56, United-States, <=50K 18, ?, 201299, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 152940, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 43, Private, 243580, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Private, 182128, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 6497, 0, 50, United-States, <=50K 36, ?, 176458, HS-grad, 9, Divorced, ?, Unmarried, White, Female, 0, 0, 28, United-States, <=50K 33, Private, 101562, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 48, Private, 108699, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 175878, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Female, 0, 0, 40, United-States, <=50K 34, Local-gov, 177675, Some-college, 10, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 33, Private, 213887, HS-grad, 9, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 357619, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 60, Germany, <=50K 23, Private, 435835, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 1669, 55, United-States, <=50K 39, Private, 165799, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 71469, Assoc-acdm, 12, Never-married, Sales, Own-child, White, Female, 0, 0, 25, United-States, <=50K 19, Private, 229745, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 20, United-States, <=50K 47, Private, 284916, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 7298, 0, 45, United-States, >50K 46, Private, 28419, Assoc-voc, 11, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 47, Private, 26950, Masters, 14, Divorced, Sales, Not-in-family, White, Female, 0, 0, 6, United-States, <=50K 47, Self-emp-not-inc, 107231, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, >50K 52, Local-gov, 512103, Some-college, 10, Divorced, Transport-moving, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Self-emp-not-inc, 245090, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Mexico, <=50K 58, Private, 314153, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Private, 243988, 5th-6th, 3, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Mexico, <=50K 54, Self-emp-not-inc, 82551, Assoc-voc, 11, Married-civ-spouse, Tech-support, Other-relative, White, Female, 0, 0, 10, United-States, <=50K 20, Private, 42706, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 25, Private, 235795, Assoc-acdm, 12, Never-married, Sales, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 25, Self-emp-not-inc, 108001, 9th, 5, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 15, United-States, <=50K 36, State-gov, 112497, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 1876, 44, United-States, <=50K 69, Self-emp-not-inc, 128206, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 30, United-States, <=50K 28, Private, 224634, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 45, United-States, >50K 20, Private, 362999, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 21, Private, 346693, 7th-8th, 4, Never-married, Farming-fishing, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 175759, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 21, Private, 99199, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 32, United-States, <=50K 25, ?, 219987, Assoc-acdm, 12, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 13, United-States, <=50K 39, Private, 143445, HS-grad, 9, Married-civ-spouse, Other-service, Other-relative, Black, Female, 0, 0, 40, United-States, <=50K 34, Private, 118710, Assoc-voc, 11, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Local-gov, 224185, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 118972, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 29, Private, 165360, Assoc-voc, 11, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 48, Private, 38950, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 89, United-States, <=50K 42, Self-emp-inc, 277256, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 60, United-States, >50K 29, Private, 247151, 11th, 7, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 213722, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 209955, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 25, United-States, <=50K 41, Private, 174395, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 45, Private, 138626, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 1876, 50, United-States, <=50K 22, ?, 179973, Assoc-voc, 11, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 200207, HS-grad, 9, Divorced, Handlers-cleaners, Own-child, White, Male, 0, 0, 44, United-States, <=50K 19, Private, 156587, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 38, United-States, <=50K 24, Private, 33016, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 197496, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 30, ?, <=50K 32, Private, 153588, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 99736, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Male, 15020, 0, 50, United-States, >50K 36, Private, 284166, HS-grad, 9, Never-married, Sales, Unmarried, White, Male, 0, 0, 60, United-States, >50K 18, Private, 716066, 10th, 6, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 30, United-States, <=50K 27, Private, 188519, HS-grad, 9, Divorced, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 109080, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 52, Private, 174421, Assoc-acdm, 12, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 24, Private, 259351, Some-college, 10, Never-married, Craft-repair, Unmarried, Amer-Indian-Eskimo, Male, 0, 0, 40, Mexico, <=50K 42, Federal-gov, 284403, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 39, Private, 85319, Prof-school, 15, Married-civ-spouse, Prof-specialty, Wife, White, Female, 7688, 0, 60, United-States, >50K 20, ?, 201766, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 35, United-States, <=50K 20, State-gov, 340475, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 10, United-States, <=50K 39, Private, 487486, HS-grad, 9, Widowed, Handlers-cleaners, Unmarried, White, Male, 0, 0, 40, ?, <=50K 68, ?, 484298, 11th, 7, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 30, United-States, <=50K 35, Private, 170617, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 48, United-States, <=50K 54, Private, 94055, Bachelors, 13, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 117779, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 209770, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 8, United-States, <=50K 20, Private, 317443, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 15, United-States, <=50K 64, ?, 140237, Preschool, 1, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 107411, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 36, Self-emp-not-inc, 122493, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 47, United-States, <=50K 44, Self-emp-inc, 195124, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, ?, <=50K 38, Private, 101978, Some-college, 10, Separated, Machine-op-inspct, Not-in-family, White, Male, 0, 2258, 55, United-States, >50K 22, Private, 335453, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 56, Private, 318329, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 100321, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, <=50K 24, Self-emp-not-inc, 81145, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 75, United-States, <=50K 22, Private, 62865, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 176262, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 30, United-States, <=50K 42, Private, 168103, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Local-gov, 208174, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 55, United-States, <=50K 19, Private, 188815, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 34095, 0, 20, United-States, <=50K 67, Self-emp-not-inc, 226092, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 44, United-States, <=50K 20, Private, 212668, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 30, United-States, <=50K 32, Private, 381583, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Other, Male, 0, 0, 40, United-States, <=50K 46, Private, 239439, HS-grad, 9, Separated, Machine-op-inspct, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 52, Private, 172493, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 36, United-States, <=50K 44, Private, 239876, Bachelors, 13, Divorced, Prof-specialty, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 65, ?, 221881, 11th, 7, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, Mexico, <=50K 37, Local-gov, 218184, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1887, 40, United-States, >50K 27, Self-emp-not-inc, 206889, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 35, Private, 110668, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, Black, Female, 0, 0, 35, United-States, <=50K 30, Private, 211028, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 64, Local-gov, 202984, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 3137, 0, 40, United-States, <=50K 48, Private, 20296, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 37, United-States, >50K 35, Private, 194690, 7th-8th, 4, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 28, Self-emp-not-inc, 204984, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 63, Self-emp-not-inc, 35021, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 1977, 32, China, >50K 40, Self-emp-not-inc, 238574, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 33, Private, 345360, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 192381, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 25, Private, 479765, 7th-8th, 4, Never-married, Sales, Other-relative, White, Male, 0, 0, 45, Guatemala, <=50K 45, Self-emp-inc, 34091, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 38, United-States, >50K 30, Private, 151773, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 53, Private, 299080, Some-college, 10, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 63, Private, 135339, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 2105, 0, 40, Vietnam, <=50K 27, Local-gov, 52156, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 60, United-States, <=50K 31, Private, 318647, 11th, 7, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 80145, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 39, State-gov, 343646, Bachelors, 13, Divorced, Protective-serv, Not-in-family, White, Male, 0, 0, 40, Mexico, >50K 42, Self-emp-not-inc, 198692, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 19, Private, 266635, HS-grad, 9, Never-married, Other-service, Own-child, Black, Male, 0, 0, 30, United-States, <=50K 31, Private, 197672, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 185846, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Self-emp-not-inc, 315110, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 20, United-States, <=50K 27, Private, 220754, Doctorate, 16, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 64292, HS-grad, 9, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 126060, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, >50K 52, Private, 78012, HS-grad, 9, Widowed, Sales, Unmarried, White, Female, 0, 1762, 40, United-States, <=50K 32, Private, 210562, Assoc-voc, 11, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 46, United-States, <=50K 23, Private, 350181, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 233421, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 20, United-States, <=50K 53, Private, 167170, HS-grad, 9, Widowed, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 18, Private, 260801, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, United-States, <=50K 41, Private, 173370, Bachelors, 13, Separated, Sales, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 27, Private, 135520, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, Dominican-Republic, <=50K 30, Private, 121308, Some-college, 10, Divorced, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 444743, HS-grad, 9, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 65225, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 58, State-gov, 136982, HS-grad, 9, Married-spouse-absent, Other-service, Unmarried, Black, Female, 0, 0, 40, Honduras, <=50K 45, State-gov, 271962, Bachelors, 13, Divorced, Protective-serv, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 204046, 10th, 6, Divorced, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 225823, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 183009, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Other, Female, 0, 1590, 40, United-States, <=50K 50, Private, 121038, Assoc-voc, 11, Married-civ-spouse, Other-service, Wife, Black, Female, 0, 0, 40, United-States, <=50K 26, Private, 49092, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 148709, HS-grad, 9, Separated, Handlers-cleaners, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 209205, Bachelors, 13, Never-married, Tech-support, Own-child, White, Male, 0, 0, 40, United-States, <=50K 36, Local-gov, 285865, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 22, Federal-gov, 216129, HS-grad, 9, Never-married, Adm-clerical, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 37, Federal-gov, 40955, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, Japan, <=50K 54, Private, 197189, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 33001, HS-grad, 9, Divorced, Farming-fishing, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 44, Private, 227399, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, United-States, <=50K 38, Private, 164050, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 40, United-States, >50K 49, Private, 259087, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 236262, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 12, United-States, <=50K 26, Private, 177929, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 48, Private, 166929, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, ?, >50K 32, Private, 199963, 11th, 7, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, United-States, <=50K 35, State-gov, 98776, HS-grad, 9, Never-married, Tech-support, Own-child, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 135056, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 40, Self-emp-not-inc, 55363, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 3411, 0, 40, United-States, <=50K 42, State-gov, 102343, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 72, India, >50K 30, Private, 231263, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 226913, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 36, Private, 129573, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 31, Private, 191001, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 50, Federal-gov, 69345, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 38, Private, 204556, HS-grad, 9, Divorced, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 35, Private, 192626, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 45, Private, 202812, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Private, 405177, 10th, 6, Separated, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 227890, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 46, United-States, >50K 33, Private, 101352, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 49, Private, 82572, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 28, Private, 132686, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 49, Local-gov, 149210, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, Black, Male, 15024, 0, 40, United-States, >50K 27, Private, 245661, HS-grad, 9, Separated, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 47, Self-emp-inc, 483596, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 2885, 0, 32, United-States, <=50K 42, State-gov, 104663, Doctorate, 16, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, Italy, >50K 30, Private, 347166, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 37, Local-gov, 108540, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 333305, Doctorate, 16, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 35, United-States, <=50K 51, Private, 155408, HS-grad, 9, Married-spouse-absent, Sales, Not-in-family, Black, Female, 0, 0, 38, United-States, <=50K 27, Federal-gov, 246372, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 30290, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 347321, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Self-emp-inc, 205852, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, <=50K 40, Federal-gov, 163215, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, ?, <=50K 54, State-gov, 93449, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, India, >50K 47, Self-emp-inc, 116927, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 42, United-States, >50K 35, Private, 164526, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Yugoslavia, >50K 33, Private, 31573, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Local-gov, 125159, Some-college, 10, Never-married, Adm-clerical, Other-relative, Black, Male, 0, 0, 40, Haiti, <=50K 39, State-gov, 201105, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 55, United-States, >50K 25, ?, 122745, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 1602, 40, United-States, <=50K 33, Private, 150570, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 118941, 11th, 7, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, Ireland, <=50K 53, Private, 141388, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 21, Private, 174714, Assoc-acdm, 12, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 35, United-States, <=50K 31, State-gov, 75755, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 55, United-States, >50K 63, Private, 133144, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, <=50K 21, Self-emp-not-inc, 318865, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, United-States, <=50K 59, Private, 109638, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 50, Private, 92969, 1st-4th, 2, Separated, Prof-specialty, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 66, ?, 376028, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 20, United-States, <=50K 19, Private, 144161, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 30, United-States, <=50K 31, Private, 183778, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 23, Private, 398904, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 170846, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 35, Local-gov, 204277, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 205152, Bachelors, 13, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 225395, 7th-8th, 4, Never-married, Machine-op-inspct, Other-relative, White, Female, 0, 0, 60, Mexico, <=50K 38, Private, 33975, HS-grad, 9, Married-civ-spouse, Exec-managerial, Other-relative, White, Male, 0, 0, 40, United-States, >50K 49, Private, 147032, HS-grad, 9, Married-civ-spouse, Other-service, Wife, Asian-Pac-Islander, Female, 0, 0, 8, Philippines, <=50K 64, Private, 174826, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 60, Local-gov, 232769, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 20, United-States, <=50K 25, Private, 36984, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 21, Private, 292264, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 26, Private, 303973, HS-grad, 9, Never-married, Priv-house-serv, Other-relative, White, Female, 0, 1602, 15, Mexico, <=50K 23, Private, 287988, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 67, Self-emp-inc, 330144, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 48, United-States, >50K 24, Private, 191948, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 46, Private, 324601, 1st-4th, 2, Separated, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, Guatemala, <=50K 38, State-gov, 200289, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Taiwan, <=50K 20, Private, 113307, 7th-8th, 4, Never-married, Machine-op-inspct, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 28, ?, 194087, Some-college, 10, Never-married, ?, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 155213, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 58, Private, 175127, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, State-gov, 358461, Some-college, 10, Never-married, Other-service, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 37, State-gov, 354929, Assoc-acdm, 12, Divorced, Protective-serv, Not-in-family, Black, Male, 0, 0, 38, United-States, <=50K 53, State-gov, 104501, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, ?, >50K 45, Private, 112929, 7th-8th, 4, Divorced, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 35, United-States, <=50K 33, Private, 132832, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 33, State-gov, 357691, Masters, 14, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 40, United-States, <=50K 35, Private, 114605, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 60, Self-emp-not-inc, 525878, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, United-States, <=50K 21, Private, 68358, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 38, Private, 174571, 10th, 6, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 45, United-States, <=50K 40, Private, 42703, Assoc-voc, 11, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 220589, Some-college, 10, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, >50K 44, Self-emp-not-inc, 197558, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 70, United-States, >50K 27, Private, 423250, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 34, Self-emp-not-inc, 29254, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, >50K 20, ?, 308924, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 25, United-States, <=50K 49, Local-gov, 276247, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 213841, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 52, Private, 181677, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 30, United-States, >50K 46, Private, 160061, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 20, Private, 285295, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, ?, <=50K 43, Private, 265266, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Local-gov, 222115, Bachelors, 13, Divorced, Adm-clerical, Not-in-family, White, Female, 99999, 0, 40, United-States, >50K 25, State-gov, 194954, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 15, United-States, <=50K 48, Private, 156926, Bachelors, 13, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Local-gov, 217414, Some-college, 10, Divorced, Protective-serv, Unmarried, White, Male, 0, 0, 55, United-States, <=50K 37, Private, 538443, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 14344, 0, 40, United-States, >50K 18, ?, 192399, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 60, United-States, <=50K 42, Private, 383493, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 60, Private, 193235, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 24, United-States, <=50K 37, Self-emp-inc, 99452, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 55, United-States, >50K 44, Local-gov, 254134, Assoc-acdm, 12, Divorced, Tech-support, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 32, Private, 90446, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 116613, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, Portugal, <=50K 42, Local-gov, 238188, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, >50K 17, Private, 95909, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 12, United-States, <=50K 41, Private, 82319, 12th, 8, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 10, United-States, <=50K 34, Private, 182274, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 1887, 40, United-States, >50K 56, Private, 179625, 10th, 6, Separated, Other-service, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 28, Private, 119793, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 28, Self-emp-not-inc, 254989, 11th, 7, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 104830, 7th-8th, 4, Never-married, Transport-moving, Unmarried, White, Male, 0, 0, 25, Guatemala, <=50K 49, Federal-gov, 110373, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Self-emp-not-inc, 135416, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 50, United-States, <=50K 25, Private, 298225, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 35, United-States, <=50K 42, Private, 166740, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 47, Self-emp-not-inc, 213668, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 50, United-States, >50K 26, Private, 276624, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 226789, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 58, United-States, <=50K 37, Private, 31023, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 39, Local-gov, 116666, HS-grad, 9, Never-married, Protective-serv, Own-child, Amer-Indian-Eskimo, Male, 4650, 0, 48, United-States, <=50K 42, Private, 136986, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 35, United-States, >50K 41, Private, 179580, Some-college, 10, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 36, United-States, >50K 23, Private, 103277, Some-college, 10, Divorced, Other-service, Own-child, White, Female, 0, 0, 24, United-States, <=50K 31, Federal-gov, 351141, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Local-gov, 191161, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 57, United-States, >50K 20, Private, 148709, Some-college, 10, Never-married, Prof-specialty, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 36, Private, 128382, Some-college, 10, Never-married, Machine-op-inspct, Unmarried, White, Male, 0, 0, 45, United-States, <=50K 50, Private, 144361, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, >50K 37, Private, 172538, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 102476, Bachelors, 13, Never-married, Farming-fishing, Own-child, White, Male, 27828, 0, 50, United-States, >50K 39, Private, 46028, Some-college, 10, Divorced, Other-service, Unmarried, White, Female, 0, 0, 60, United-States, <=50K 32, Private, 198452, HS-grad, 9, Married-civ-spouse, Farming-fishing, Wife, White, Female, 0, 0, 40, United-States, <=50K 59, Private, 193895, Some-college, 10, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 29, Private, 233421, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 3411, 0, 45, United-States, <=50K 50, Private, 378747, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 42, Private, 31251, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 37, United-States, <=50K 32, Private, 71540, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 194772, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 1902, 40, United-States, >50K 20, Private, 34568, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 3781, 0, 35, United-States, <=50K 50, Self-emp-not-inc, 36480, 10th, 6, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 18, Private, 116528, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 60, Private, 52152, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 60, Private, 216690, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, ?, <=50K 42, Local-gov, 227065, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 22, United-States, <=50K 49, Private, 84013, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 35, Self-emp-inc, 82051, Some-college, 10, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, <=50K 30, Self-emp-not-inc, 176185, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, Iran, <=50K 59, Private, 115414, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 24, Self-emp-inc, 493034, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Male, 13550, 0, 50, United-States, >50K 55, Private, 354923, Assoc-acdm, 12, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 393712, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 39, Private, 98941, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 141483, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 172479, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 40, United-States, >50K 21, Private, 226145, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 30, United-States, <=50K 23, Private, 394612, Bachelors, 13, Never-married, Tech-support, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 22, Private, 231085, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, United-States, <=50K 55, Self-emp-not-inc, 183810, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 19, Private, 186159, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 162282, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 46, Private, 219021, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 15024, 0, 44, United-States, >50K 23, Private, 273206, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 23, United-States, <=50K 47, Self-emp-inc, 332355, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 23, Private, 102729, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 15, United-States, <=50K 42, Private, 198096, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, >50K 22, State-gov, 292933, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 10, United-States, <=50K 18, Private, 135924, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 20, United-States, <=50K 37, Private, 99146, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 50, United-States, >50K 34, Private, 27409, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 30, Private, 299507, Assoc-acdm, 12, Separated, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 62, Self-emp-not-inc, 102631, Some-college, 10, Widowed, Farming-fishing, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 51, Private, 153486, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 434292, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 30, United-States, <=50K 28, Self-emp-not-inc, 240172, Masters, 14, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 56, Private, 219426, 10th, 6, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 295791, HS-grad, 9, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 46, Private, 114032, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 1887, 45, United-States, >50K 23, Local-gov, 496382, Some-college, 10, Married-spouse-absent, Adm-clerical, Own-child, White, Female, 0, 0, 40, Guatemala, <=50K 33, Private, 376483, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 0, 30, United-States, <=50K 27, Private, 107218, HS-grad, 9, Never-married, Other-service, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 21, Private, 246207, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 20, United-States, <=50K 18, ?, 80564, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 0, 60, United-States, <=50K 36, Private, 83089, 5th-6th, 3, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 7298, 0, 40, Mexico, >50K 37, Local-gov, 328301, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 36, United-States, <=50K 39, Local-gov, 301614, 11th, 7, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 199739, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 7298, 0, 60, United-States, >50K 24, Private, 180060, Assoc-acdm, 12, Never-married, Craft-repair, Not-in-family, White, Male, 2354, 0, 40, United-States, <=50K 26, Private, 121040, Assoc-acdm, 12, Never-married, Exec-managerial, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 37, Private, 125550, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 34, Private, 170772, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 33, Private, 180551, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 33, Self-emp-not-inc, 48189, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 30, United-States, <=50K 20, Private, 432154, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 8, Mexico, <=50K 26, Private, 263200, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 47, Private, 123207, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 20, United-States, >50K 17, Private, 110798, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 53, Private, 238481, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1485, 40, United-States, <=50K 31, Private, 185528, Some-college, 10, Divorced, Sales, Own-child, White, Female, 0, 0, 35, United-States, <=50K 34, Private, 181311, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 528616, 5th-6th, 3, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Mexico, <=50K 39, Private, 272950, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 22, ?, 195532, HS-grad, 9, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 197583, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 40, Private, 48612, HS-grad, 9, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 54, Local-gov, 31533, Masters, 14, Married-civ-spouse, Adm-clerical, Husband, White, Male, 7298, 0, 40, United-States, >50K 32, Federal-gov, 148138, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 2002, 40, Iran, <=50K 29, Local-gov, 30069, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 2635, 0, 40, United-States, <=50K 68, ?, 170182, Some-college, 10, Never-married, ?, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 27, Local-gov, 230885, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 45, United-States, >50K 54, Private, 174102, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 23, Private, 352606, HS-grad, 9, Divorced, Priv-house-serv, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 241153, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 48, United-States, >50K 54, Private, 155433, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 35, United-States, <=50K 21, Private, 109414, Some-college, 10, Never-married, Prof-specialty, Own-child, Asian-Pac-Islander, Male, 0, 1974, 40, United-States, <=50K 40, Private, 125461, Assoc-voc, 11, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 42, United-States, <=50K 19, Private, 331556, 10th, 6, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, ?, 138575, HS-grad, 9, Never-married, ?, Other-relative, White, Male, 0, 0, 60, United-States, <=50K 35, Private, 223514, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 0, 40, United-States, <=50K 39, Private, 115418, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 2174, 0, 45, United-States, <=50K 38, Private, 193026, HS-grad, 9, Never-married, Other-service, Unmarried, White, Male, 0, 1408, 40, ?, <=50K 41, Private, 147206, 12th, 8, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 174592, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 268620, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 70, Self-emp-not-inc, 150886, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 25, United-States, <=50K 45, Private, 112362, 10th, 6, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 83, Private, 195507, HS-grad, 9, Widowed, Protective-serv, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 59, Private, 192983, HS-grad, 9, Separated, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 120544, 9th, 5, Never-married, Other-service, Own-child, Black, Male, 0, 0, 15, United-States, <=50K 31, Private, 59083, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 208277, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 45, United-States, >50K 24, Local-gov, 184678, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 278736, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, <=50K 48, Local-gov, 39464, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 52, United-States, <=50K 27, Private, 162343, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, Dominican-Republic, <=50K 41, Private, 204046, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 255647, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 25, Mexico, <=50K 53, Private, 123011, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 66, Self-emp-not-inc, 291362, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 31, Private, 159187, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 30, State-gov, 126414, Bachelors, 13, Married-spouse-absent, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 227626, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 47, Self-emp-inc, 173783, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 60, United-States, >50K 74, Private, 211075, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Private, 176756, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 1485, 70, United-States, >50K 35, Self-emp-not-inc, 31095, Some-college, 10, Separated, Farming-fishing, Not-in-family, White, Male, 4101, 0, 60, United-States, <=50K 51, Self-emp-not-inc, 32372, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1672, 70, United-States, <=50K 40, Private, 331651, Some-college, 10, Separated, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 51, Local-gov, 146325, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1887, 40, United-States, >50K 26, Private, 515025, 10th, 6, Married-civ-spouse, Handlers-cleaners, Wife, White, Female, 0, 0, 40, United-States, <=50K 53, Private, 394474, Assoc-acdm, 12, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 32, Private, 400535, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 3781, 0, 40, United-States, <=50K 29, Self-emp-not-inc, 337505, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, South, <=50K 42, Private, 211860, HS-grad, 9, Separated, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 102684, Some-college, 10, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 32, United-States, <=50K 62, ?, 225657, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 24, United-States, <=50K 33, Private, 121966, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 396790, HS-grad, 9, Never-married, Transport-moving, Own-child, Black, Male, 0, 0, 20, United-States, <=50K 46, Local-gov, 149949, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 25, Private, 252187, 11th, 7, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 209934, 5th-6th, 3, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Mexico, <=50K 29, Federal-gov, 229300, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 33, Private, 170769, Doctorate, 16, Divorced, Sales, Not-in-family, White, Male, 99999, 0, 60, United-States, >50K 50, Private, 200618, Assoc-acdm, 12, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 216984, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 40, Private, 212760, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 150309, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Amer-Indian-Eskimo, Male, 0, 0, 45, United-States, <=50K 54, Private, 174655, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 109621, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 225124, HS-grad, 9, Widowed, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 46, Private, 172695, 11th, 7, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 27, El-Salvador, <=50K 71, Self-emp-not-inc, 238479, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 8, United-States, <=50K 27, Private, 37754, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 80, United-States, <=50K 56, Private, 85018, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 64, Private, 256466, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, Asian-Pac-Islander, Male, 0, 0, 60, Philippines, >50K 23, Private, 169188, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 25, United-States, <=50K 36, Private, 210945, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Local-gov, 287031, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 26, Private, 224361, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Federal-gov, 108464, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 75826, Bachelors, 13, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 120277, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Private, 104439, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 27, Private, 56870, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 200819, 12th, 8, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 50, Self-emp-not-inc, 170562, Assoc-acdm, 12, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 20, United-States, <=50K 30, Private, 80933, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 33088, 11th, 7, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Local-gov, 112763, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 7430, 0, 36, United-States, >50K 29, Private, 177651, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 31, Private, 261943, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 169785, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, Italy, <=50K 20, Private, 141481, 11th, 7, Married-civ-spouse, Sales, Other-relative, White, Female, 0, 0, 50, United-States, <=50K 37, Private, 433491, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 28, Local-gov, 86615, HS-grad, 9, Never-married, Other-service, Own-child, Black, Male, 0, 0, 30, United-States, <=50K 39, Private, 125550, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 46, State-gov, 421223, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 26999, Bachelors, 13, Separated, Exec-managerial, Unmarried, White, Female, 0, 0, 42, United-States, <=50K 36, Self-emp-not-inc, 241998, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 99999, 0, 20, United-States, >50K 34, ?, 133861, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 25, United-States, <=50K 44, Private, 115323, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 34, Self-emp-inc, 23778, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 28, Self-emp-not-inc, 190836, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 38, Self-emp-inc, 159179, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 64, ?, 205479, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 50, United-States, >50K 19, ?, 47713, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 163237, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 52, United-States, >50K 61, Private, 202202, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 168837, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 112271, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 52537, HS-grad, 9, Never-married, Transport-moving, Unmarried, Black, Male, 0, 0, 30, United-States, <=50K 27, Private, 38353, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 22, Private, 141698, 10th, 6, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 28856, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 175652, 11th, 7, Never-married, Other-service, Other-relative, White, Female, 0, 0, 15, United-States, <=50K 36, Private, 213008, HS-grad, 9, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 196501, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 14084, 0, 50, United-States, >50K 63, Private, 118798, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 99999, 0, 40, United-States, >50K 51, Private, 92463, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, State-gov, 125165, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 25, United-States, <=50K 42, Self-emp-not-inc, 103980, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 40, ?, 180362, Bachelors, 13, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 53903, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 179735, Assoc-voc, 11, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 41, ?, 277390, Bachelors, 13, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 30, United-States, >50K 49, Private, 122177, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 80, United-States, <=50K 46, Private, 188161, HS-grad, 9, Separated, Machine-op-inspct, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 32, Self-emp-not-inc, 170108, HS-grad, 9, Separated, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 28, Private, 175262, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, Mexico, <=50K 19, ?, 204441, HS-grad, 9, Never-married, ?, Other-relative, Black, Male, 0, 0, 20, United-States, <=50K 19, Private, 164395, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 25, United-States, <=50K 18, Private, 115630, 11th, 7, Never-married, Adm-clerical, Own-child, Black, Male, 0, 0, 20, United-States, <=50K 39, Private, 178815, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 60, Self-emp-not-inc, 168223, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 46, Local-gov, 202560, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 1408, 40, United-States, <=50K 38, Private, 100295, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 50, Canada, >50K 36, Private, 172256, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 44, United-States, >50K 45, Private, 51664, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 60, State-gov, 358893, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 2339, 40, United-States, <=50K 30, Private, 115963, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 333910, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 43, United-States, <=50K 23, Private, 148948, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 48, State-gov, 130561, Some-college, 10, Never-married, Prof-specialty, Not-in-family, Black, Female, 0, 0, 24, United-States, <=50K 46, Private, 428350, HS-grad, 9, Married-civ-spouse, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 43, Private, 188808, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 25, Private, 112847, HS-grad, 9, Married-civ-spouse, Transport-moving, Own-child, Other, Male, 0, 0, 40, United-States, <=50K 50, Private, 110748, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 61, Self-emp-inc, 156653, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 35, Private, 196491, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 65, Local-gov, 254413, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 56, Private, 91262, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Asian-Pac-Islander, Male, 0, 0, 45, United-States, <=50K 43, Self-emp-not-inc, 154785, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Wife, Asian-Pac-Islander, Female, 0, 0, 80, Thailand, <=50K 55, Private, 84231, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 22, Private, 226327, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 248406, Some-college, 10, Divorced, Machine-op-inspct, Own-child, White, Male, 0, 0, 32, United-States, <=50K 35, Private, 54317, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 1672, 50, United-States, <=50K 22, ?, 32732, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 50, United-States, <=50K 20, Private, 95918, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Local-gov, 375675, 12th, 8, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 35, United-States, >50K 43, Private, 244172, HS-grad, 9, Separated, Transport-moving, Unmarried, White, Male, 0, 0, 40, Mexico, <=50K 46, Federal-gov, 233555, HS-grad, 9, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, ?, <=50K 39, Private, 326342, 11th, 7, Married-civ-spouse, Other-service, Husband, Black, Male, 2635, 0, 37, United-States, <=50K 34, Private, 77271, HS-grad, 9, Never-married, Exec-managerial, Unmarried, White, Female, 0, 0, 20, England, <=50K 35, Private, 33397, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 30, Private, 446358, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Male, 0, 0, 41, United-States, <=50K 25, Private, 151810, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 28, United-States, <=50K 44, Private, 125461, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 35, United-States, >50K 35, Private, 133906, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 155106, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Federal-gov, 203637, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 7298, 0, 40, United-States, >50K 32, Private, 232766, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 50, Private, 305319, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 121023, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 15, United-States, <=50K 29, Private, 198997, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 20, United-States, <=50K 38, Private, 167140, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 70, United-States, >50K 20, Private, 38772, 10th, 6, Never-married, Handlers-cleaners, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 41, Private, 253759, HS-grad, 9, Never-married, Sales, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 27, Private, 130067, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 65, United-States, <=50K 37, Private, 203828, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 62, State-gov, 221558, Masters, 14, Separated, Prof-specialty, Unmarried, White, Female, 0, 0, 24, ?, <=50K 31, Private, 156464, 10th, 6, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 72333, Some-college, 10, Divorced, Adm-clerical, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 33, Local-gov, 83671, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Black, Female, 0, 0, 50, United-States, <=50K 31, Private, 339482, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1848, 40, United-States, >50K 19, Private, 91928, Some-college, 10, Never-married, Other-service, Other-relative, White, Female, 0, 0, 35, United-States, <=50K 44, Private, 99203, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Self-emp-inc, 455995, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 65, United-States, >50K 62, Private, 192515, HS-grad, 9, Widowed, Farming-fishing, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 65, Self-emp-not-inc, 111483, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 2174, 10, United-States, >50K 17, Private, 221129, 9th, 5, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 60, Private, 85413, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 44, United-States, >50K 31, Private, 196125, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 265638, Some-college, 10, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 53, Private, 177727, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 44, Private, 205822, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 43, Private, 112607, 11th, 7, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 40, Federal-gov, 177595, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1579, 40, United-States, <=50K 18, Private, 183315, 11th, 7, Never-married, Sales, Own-child, Black, Female, 0, 0, 10, United-States, <=50K 47, Private, 116279, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 43, United-States, <=50K 38, Federal-gov, 122493, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 4064, 0, 40, United-States, <=50K 37, Private, 215419, Assoc-acdm, 12, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 25, United-States, <=50K 40, Private, 310101, Some-college, 10, Separated, Sales, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 57, Self-emp-inc, 61885, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 60, United-States, >50K 43, Private, 59107, HS-grad, 9, Separated, Other-service, Not-in-family, White, Female, 4101, 0, 40, United-States, <=50K 32, Private, 227214, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Other, Male, 0, 0, 40, Ecuador, <=50K 64, Private, 239450, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 118847, 12th, 8, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 40, Self-emp-not-inc, 95226, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 17, ?, 659273, 11th, 7, Never-married, ?, Own-child, Black, Female, 0, 0, 40, Trinadad&Tobago, <=50K 23, Private, 215395, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 170600, Assoc-voc, 11, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 45, Self-emp-not-inc, 91044, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 27, Private, 318639, 10th, 6, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 60, Mexico, <=50K 23, Private, 160398, Some-college, 10, Married-spouse-absent, Handlers-cleaners, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 58, Self-emp-not-inc, 216824, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, Asian-Pac-Islander, Male, 0, 0, 30, United-States, <=50K 35, Private, 308945, HS-grad, 9, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 75, United-States, <=50K 47, Private, 30840, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 33, Private, 99309, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 27, Private, 188576, Bachelors, 13, Separated, Prof-specialty, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, >50K 46, Private, 83064, Assoc-acdm, 12, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 24, Private, 403865, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 56, United-States, <=50K 40, Private, 235786, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 44, United-States, >50K 44, Private, 191893, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 24, United-States, <=50K 31, Local-gov, 149184, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 97, United-States, >50K 37, Private, 152909, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Husband, White, Male, 7688, 0, 40, United-States, >50K 23, Private, 435604, Assoc-voc, 11, Separated, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 30, Self-emp-inc, 109282, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 52, United-States, >50K 31, Private, 248178, Some-college, 10, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 35, United-States, <=50K 24, ?, 112683, HS-grad, 9, Never-married, ?, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 32, Private, 209103, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 3464, 0, 40, United-States, <=50K 27, Private, 183639, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 35, Local-gov, 107233, HS-grad, 9, Never-married, Adm-clerical, Unmarried, Amer-Indian-Eskimo, Male, 0, 0, 55, United-States, <=50K 27, Private, 175387, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 1876, 40, United-States, <=50K 30, Self-emp-not-inc, 178255, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 70, ?, <=50K 33, Self-emp-not-inc, 38223, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 70, United-States, <=50K 34, Private, 228873, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 29, Private, 202182, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 26, Local-gov, 425092, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 2174, 0, 40, United-States, <=50K 39, Self-emp-not-inc, 152587, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 37, Self-emp-inc, 39089, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 3103, 0, 50, United-States, >50K 51, Private, 204304, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 40, Private, 116103, Some-college, 10, Separated, Craft-repair, Unmarried, White, Male, 4934, 0, 47, United-States, >50K 53, Private, 290640, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Vietnam, <=50K 58, Federal-gov, 81973, Some-college, 10, Married-civ-spouse, Tech-support, Husband, Asian-Pac-Islander, Male, 0, 1485, 40, United-States, >50K 29, Private, 134890, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Private, 452924, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Other, Male, 0, 0, 40, Mexico, <=50K 57, Private, 245193, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 69, State-gov, 34339, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 184756, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 12, United-States, <=50K 56, Private, 392160, HS-grad, 9, Widowed, Sales, Unmarried, White, Female, 0, 0, 25, Mexico, <=50K 49, Private, 168337, 5th-6th, 3, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 309513, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 70, Private, 77219, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 37, United-States, <=50K 44, Private, 212888, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 37, Private, 361888, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 10520, 0, 40, United-States, >50K 58, Local-gov, 237879, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 58, United-States, <=50K 42, Self-emp-not-inc, 93099, Some-college, 10, Married-civ-spouse, Prof-specialty, Own-child, White, Female, 0, 0, 25, United-States, <=50K 41, Private, 225193, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 50814, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Local-gov, 123681, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 60, United-States, >50K 24, Private, 249351, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, United-States, <=50K 58, Self-emp-not-inc, 222311, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 7688, 0, 55, United-States, >50K 18, Private, 301762, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 25, United-States, <=50K 50, Private, 195298, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 69, Private, 541737, Some-college, 10, Widowed, Adm-clerical, Not-in-family, White, Female, 2050, 0, 24, United-States, <=50K 84, Private, 241065, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 66, United-States, <=50K 47, Private, 129513, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 19, Private, 374262, 12th, 8, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, United-States, <=50K 24, Private, 382146, Some-college, 10, Never-married, Prof-specialty, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 48, ?, 185291, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 6, United-States, <=50K 53, Private, 30447, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 58, Private, 49893, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 22, Private, 197387, Some-college, 10, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 24, Mexico, <=50K 36, Self-emp-not-inc, 111957, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 52, United-States, <=50K 34, Private, 340458, 12th, 8, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 185670, 1st-4th, 2, Widowed, Prof-specialty, Unmarried, White, Female, 0, 0, 21, Mexico, <=50K 37, Private, 210945, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 24, United-States, <=50K 43, Private, 350661, Prof-school, 15, Separated, Tech-support, Not-in-family, White, Male, 0, 0, 50, Columbia, >50K 42, Private, 190543, Some-college, 10, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 40, United-States, >50K 21, Private, 70261, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, United-States, <=50K 49, Self-emp-not-inc, 179048, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, Greece, <=50K 35, Private, 242094, HS-grad, 9, Married-civ-spouse, Other-service, Other-relative, Black, Male, 0, 0, 40, United-States, <=50K 49, Self-emp-not-inc, 117634, Some-college, 10, Widowed, Craft-repair, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 28, Private, 82531, Some-college, 10, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 51, Private, 193374, 1st-4th, 2, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Mexico, <=50K 30, ?, 186420, Bachelors, 13, Never-married, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 323605, 7th-8th, 4, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 56, Private, 371064, 9th, 5, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 39927, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 8, United-States, <=50K 22, Private, 64292, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 37, United-States, <=50K 33, Private, 198660, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 99999, 0, 56, United-States, >50K 54, ?, 196975, HS-grad, 9, Divorced, ?, Other-relative, White, Male, 0, 0, 45, United-States, <=50K 22, Private, 210165, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 68, Private, 144137, Some-college, 10, Divorced, Priv-house-serv, Other-relative, White, Female, 0, 0, 30, United-States, <=50K 56, Local-gov, 155657, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 23, ?, 72953, HS-grad, 9, Never-married, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 69, Self-emp-not-inc, 107548, 9th, 5, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 163258, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 221324, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 18, Private, 444822, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 8, Mexico, <=50K 17, Private, 154398, 11th, 7, Never-married, Other-service, Own-child, Black, Male, 0, 0, 16, Haiti, <=50K 31, Private, 120672, 11th, 7, Divorced, Handlers-cleaners, Other-relative, Black, Male, 0, 1721, 40, United-States, <=50K 50, Private, 159650, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 60, United-States, >50K 62, Private, 290754, 10th, 6, Widowed, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 49654, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 52, United-States, <=50K 20, Federal-gov, 147352, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 227943, Assoc-acdm, 12, Never-married, Sales, Own-child, White, Male, 0, 0, 30, United-States, <=50K 18, Private, 423024, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 53, ?, 64322, 7th-8th, 4, Separated, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 445940, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Mexico, <=50K 23, Private, 230824, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 48882, HS-grad, 9, Divorced, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 168195, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, <=50K 53, Local-gov, 188644, 5th-6th, 3, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Mexico, <=50K 28, Private, 136077, 10th, 6, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, State-gov, 119793, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 336513, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, <=50K 58, Private, 186991, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, ?, 218948, 7th-8th, 4, Never-married, ?, Not-in-family, White, Female, 0, 0, 32, Mexico, <=50K 26, Private, 211435, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 36, Self-emp-not-inc, 280169, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 3456, 0, 8, United-States, <=50K 27, Private, 109997, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 286789, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 25, Private, 102460, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 287160, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 39, Private, 198097, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 52, Private, 119111, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 174461, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 26, Self-emp-not-inc, 281678, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 55, United-States, <=50K 24, ?, 377725, Bachelors, 13, Never-married, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 151053, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, >50K 49, Local-gov, 186539, Masters, 14, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 20, ?, 149478, Some-college, 10, Never-married, ?, Other-relative, White, Female, 0, 0, 25, United-States, <=50K 40, Private, 198452, 11th, 7, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 198863, Prof-school, 15, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 2559, 60, United-States, >50K 33, Private, 176711, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 165310, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Other-relative, White, Male, 0, 0, 20, United-States, <=50K 37, Private, 213008, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, Japan, <=50K 21, State-gov, 38251, Some-college, 10, Never-married, Tech-support, Own-child, White, Female, 0, 0, 20, United-States, <=50K 33, Private, 125761, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 36, United-States, <=50K 28, Private, 148645, Assoc-acdm, 12, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 48, Private, 273435, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1579, 40, United-States, <=50K 43, Private, 208613, Bachelors, 13, Separated, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 192565, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 183885, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, United-States, <=50K 47, Self-emp-not-inc, 243631, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, South, <=50K 37, Private, 191754, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, >50K 26, Private, 261278, Some-college, 10, Separated, Sales, Other-relative, Black, Male, 0, 0, 30, United-States, <=50K 55, Private, 127014, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 60, United-States, <=50K 40, Private, 197919, Assoc-acdm, 12, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 217460, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 86551, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, >50K 54, Self-emp-inc, 98051, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 54, United-States, >50K 38, Private, 215917, Some-college, 10, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 53, Self-emp-not-inc, 192982, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 85, United-States, <=50K 27, Self-emp-not-inc, 334132, Assoc-acdm, 12, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 78, United-States, <=50K 42, Private, 136986, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 62, Private, 116812, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 189123, 11th, 7, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 1485, 58, United-States, <=50K 26, Private, 89648, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 33, ?, 190027, HS-grad, 9, Never-married, ?, Unmarried, Black, Female, 0, 0, 20, United-States, <=50K 59, Private, 99248, Some-college, 10, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 57600, HS-grad, 9, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 25, Private, 199224, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 58, Private, 140363, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 36, United-States, <=50K 30, Private, 308812, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 21, Private, 275421, Some-college, 10, Never-married, Craft-repair, Own-child, White, Female, 0, 0, 40, United-States, <=50K 61, Private, 213321, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 157747, Assoc-acdm, 12, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 182314, Masters, 14, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 70, Private, 220589, Some-college, 10, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 12, United-States, <=50K 55, ?, 208640, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 30, United-States, >50K 29, Self-emp-not-inc, 189346, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 2202, 0, 50, United-States, <=50K 46, Private, 124071, Masters, 14, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 44, United-States, <=50K 35, Federal-gov, 20469, Some-college, 10, Divorced, Exec-managerial, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 31, Private, 154227, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 43, United-States, >50K 37, Private, 105044, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 42, United-States, >50K 43, Private, 35910, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 43, United-States, >50K 23, Private, 189203, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 116493, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 13550, 0, 44, United-States, >50K 42, Local-gov, 19700, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 50, United-States, >50K 26, Private, 48718, 10th, 6, Never-married, Adm-clerical, Not-in-family, White, Female, 2907, 0, 40, United-States, <=50K 45, Private, 106113, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Private, 256263, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, ?, 202498, 7th-8th, 4, Separated, ?, Not-in-family, White, Male, 0, 0, 40, Guatemala, <=50K 38, Private, 120074, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, >50K 28, Private, 122922, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 68, Self-emp-not-inc, 116903, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 2149, 40, United-States, <=50K 42, Local-gov, 222596, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 107302, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, India, <=50K 36, Private, 156400, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 53373, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 22, Private, 58916, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 45, Local-gov, 167159, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 50, United-States, >50K 24, Private, 283806, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 57, Private, 140426, 1st-4th, 2, Married-spouse-absent, Other-service, Not-in-family, White, Male, 0, 0, 35, ?, <=50K 36, Local-gov, 61778, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 40, United-States, >50K 41, Private, 33310, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, Self-emp-not-inc, 202560, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 35, United-States, <=50K 25, Self-emp-not-inc, 60828, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Female, 0, 0, 50, United-States, <=50K 53, State-gov, 153486, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 28, Local-gov, 167536, Assoc-acdm, 12, Widowed, Prof-specialty, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 30, Local-gov, 370990, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Self-emp-not-inc, 198867, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Local-gov, 174924, Some-college, 10, Divorced, Protective-serv, Unmarried, White, Male, 0, 0, 48, Germany, <=50K 30, Private, 175856, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 38, United-States, <=50K 41, Private, 169628, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, Black, Female, 0, 0, 40, ?, <=50K 29, ?, 125159, Some-college, 10, Never-married, ?, Not-in-family, Black, Male, 0, 0, 36, ?, <=50K 31, Private, 220690, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 80, United-States, <=50K 36, Private, 160035, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 3908, 0, 55, United-States, <=50K 59, Self-emp-not-inc, 116878, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, Greece, <=50K 33, Self-emp-not-inc, 134737, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 29, Private, 81648, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 1887, 55, United-States, >50K 49, State-gov, 122177, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 50, Federal-gov, 69614, 10th, 6, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 56, United-States, <=50K 33, Private, 112115, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 45, United-States, >50K 28, Private, 299422, 7th-8th, 4, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Mexico, <=50K 81, ?, 162882, HS-grad, 9, Divorced, ?, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 24, Private, 112854, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 16, United-States, <=50K 32, Self-emp-not-inc, 33417, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 47, Federal-gov, 224559, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, >50K 44, ?, 468706, HS-grad, 9, Married-civ-spouse, ?, Husband, Black, Male, 0, 0, 40, United-States, <=50K 24, Private, 357028, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 37, Local-gov, 51158, Some-college, 10, Married-civ-spouse, Tech-support, Wife, White, Female, 7298, 0, 36, United-States, >50K 51, Private, 186303, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 52, Private, 127749, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 22, Private, 291386, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 138054, Assoc-acdm, 12, Never-married, Other-service, Not-in-family, Other, Male, 0, 0, 40, United-States, <=50K 47, Self-emp-not-inc, 174533, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 200835, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 108658, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 43, Private, 180985, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, >50K 25, Private, 34803, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 20, United-States, <=50K 59, Private, 75867, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 29, Private, 156819, Assoc-acdm, 12, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 30, Private, 61272, 9th, 5, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, Portugal, <=50K 24, Private, 39827, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Wife, Other, Female, 0, 0, 40, Puerto-Rico, <=50K 38, Private, 130007, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Self-emp-not-inc, 80324, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 26, Private, 322614, Preschool, 1, Married-spouse-absent, Machine-op-inspct, Not-in-family, White, Male, 0, 1719, 40, Mexico, <=50K 30, Private, 140869, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 73, Local-gov, 181902, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 10, Poland, >50K 30, Private, 287908, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 33, Private, 309630, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 28225, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 58, United-States, <=50K 40, ?, 428584, HS-grad, 9, Married-civ-spouse, ?, Wife, Black, Female, 3464, 0, 20, United-States, <=50K 18, Private, 39222, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 359131, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 7298, 0, 8, ?, >50K 22, Private, 122272, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 50, Self-emp-inc, 198400, HS-grad, 9, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 60, United-States, <=50K 62, ?, 73091, 7th-8th, 4, Widowed, ?, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 39, Self-emp-inc, 283338, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 40, United-States, >50K 22, Private, 208946, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 348416, HS-grad, 9, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 31, Private, 379046, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, Vietnam, <=50K 29, Private, 183887, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 38, Self-emp-not-inc, 127961, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, >50K 24, Private, 211129, Bachelors, 13, Never-married, Sales, Own-child, White, Female, 0, 0, 35, United-States, <=50K 29, Local-gov, 187649, HS-grad, 9, Separated, Protective-serv, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 49, Federal-gov, 94754, Masters, 14, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Private, 231826, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 28, Private, 142764, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 22, Private, 126822, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 60, United-States, <=50K 37, Private, 188069, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 284395, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 49, Private, 31267, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 161444, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, Columbia, <=50K 25, Private, 144483, HS-grad, 9, Separated, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 133655, HS-grad, 9, Married-spouse-absent, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 36, State-gov, 112074, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 21, Private, 249727, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 22, United-States, <=50K 18, Private, 165754, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 30, Local-gov, 172822, Assoc-voc, 11, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 288433, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 40, Private, 33331, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 43, Private, 168071, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 44, United-States, <=50K 45, Private, 207277, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 29, Private, 130620, Some-college, 10, Married-spouse-absent, Sales, Own-child, Asian-Pac-Islander, Female, 0, 0, 26, India, <=50K 40, Private, 136244, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 972354, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 48, United-States, <=50K 20, Private, 245297, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 32, State-gov, 71151, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 20, United-States, <=50K 19, Private, 118352, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 16, United-States, <=50K 21, Private, 117210, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 120068, Assoc-voc, 11, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 48343, 11th, 7, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 52, Private, 84451, Assoc-voc, 11, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 32, United-States, <=50K 51, ?, 76437, Some-college, 10, Divorced, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 281704, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 54, Private, 123011, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 50, Private, 104729, HS-grad, 9, Divorced, Machine-op-inspct, Other-relative, White, Female, 0, 0, 48, United-States, <=50K 29, Private, 110134, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 186067, 10th, 6, Never-married, Tech-support, Own-child, White, Male, 0, 0, 10, United-States, <=50K 47, Private, 214702, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 37, Puerto-Rico, <=50K 46, Private, 384795, Bachelors, 13, Divorced, Prof-specialty, Unmarried, Black, Female, 0, 0, 32, United-States, <=50K 30, Private, 175931, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 44, United-States, <=50K 58, Private, 366324, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 30, United-States, <=50K 48, Private, 118717, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 23, Private, 219835, Some-college, 10, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 40, Mexico, <=50K 23, Private, 176486, Assoc-voc, 11, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 36, United-States, <=50K 45, Private, 273435, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 182661, Some-college, 10, Never-married, Sales, Own-child, Black, Male, 0, 0, 20, United-States, <=50K 26, Private, 212304, 7th-8th, 4, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 48, United-States, <=50K 50, Local-gov, 133963, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, >50K 49, Private, 165152, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 48, United-States, >50K 26, Private, 274724, Some-college, 10, Never-married, Other-service, Other-relative, White, Male, 0, 0, 40, Nicaragua, <=50K 47, Private, 196707, Prof-school, 15, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 213002, 12th, 8, Never-married, Sales, Not-in-family, White, Male, 4650, 0, 50, United-States, <=50K 19, ?, 26620, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 361481, 10th, 6, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, ?, <=50K 35, Private, 148581, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1740, 40, United-States, <=50K 46, Private, 459189, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1902, 50, United-States, >50K 28, Self-emp-not-inc, 214689, 11th, 7, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 58, Private, 289364, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 45, United-States, >50K 21, Private, 174907, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 50, Self-emp-not-inc, 348099, 10th, 6, Divorced, Sales, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 30, ?, 104965, 9th, 5, Never-married, ?, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 31, Private, 31600, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Self-emp-not-inc, 286282, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 20, United-States, <=50K 35, Self-emp-not-inc, 181705, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 3103, 0, 40, United-States, >50K 33, Private, 238912, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 34, Private, 134737, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 55, United-States, >50K 67, ?, 157403, Prof-school, 15, Married-civ-spouse, ?, Husband, White, Male, 6418, 0, 10, United-States, >50K 37, Private, 197429, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 45, United-States, >50K 48, Private, 47343, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 34, Federal-gov, 67083, Bachelors, 13, Never-married, Exec-managerial, Unmarried, Asian-Pac-Islander, Male, 1471, 0, 40, Cambodia, <=50K 24, Private, 249957, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 175942, HS-grad, 9, Divorced, Priv-house-serv, Not-in-family, White, Female, 0, 0, 40, France, <=50K 50, Private, 192982, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 1848, 40, United-States, >50K 40, Private, 209547, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 1977, 60, United-States, >50K 33, Private, 142675, Bachelors, 13, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 51, Federal-gov, 190333, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 196396, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 166740, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Local-gov, 174533, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 210867, 7th-8th, 4, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 50, ?, <=50K 37, Private, 118486, Bachelors, 13, Separated, Prof-specialty, Unmarried, White, Female, 4934, 0, 32, United-States, >50K 40, Private, 144067, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 106964, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 178136, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 38, Private, 196554, Prof-school, 15, Separated, Prof-specialty, Not-in-family, White, Male, 0, 0, 35, United-States, >50K 40, Self-emp-not-inc, 403550, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 35, Private, 498216, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 47, Self-emp-not-inc, 192755, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 20, United-States, >50K 20, ?, 53738, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 60, United-States, <=50K 33, Private, 156192, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 45, Private, 189802, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 66, ?, 213149, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 1825, 40, United-States, >50K 35, Self-emp-not-inc, 179171, HS-grad, 9, Never-married, Sales, Unmarried, Black, Female, 0, 0, 38, Germany, <=50K 32, Private, 77634, 11th, 7, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, <=50K 23, Private, 189830, Some-college, 10, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 50, United-States, <=50K 19, Private, 127190, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 44, ?, 174147, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 138107, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 35, United-States, <=50K 44, Self-emp-inc, 269733, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 30, United-States, <=50K 41, State-gov, 227734, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 3464, 0, 40, United-States, <=50K 19, Private, 318822, Some-college, 10, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 48, Private, 48885, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 45, Private, 205424, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 65, United-States, >50K 40, Private, 173858, 7th-8th, 4, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 42, Cambodia, <=50K 34, Private, 202450, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, >50K 20, Private, 154779, Some-college, 10, Never-married, Sales, Other-relative, Other, Female, 0, 0, 40, United-States, <=50K 33, Private, 180551, Some-college, 10, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 177522, HS-grad, 9, Married-civ-spouse, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 23, Private, 277328, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 32, Cuba, <=50K 34, Private, 112584, 10th, 6, Divorced, Other-service, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 48, State-gov, 85384, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 32, ?, 123971, 11th, 7, Divorced, ?, Not-in-family, White, Female, 0, 0, 49, United-States, <=50K 42, Private, 69019, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, >50K 22, Private, 112847, HS-grad, 9, Never-married, Adm-clerical, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 60, Self-emp-not-inc, 52900, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 42, United-States, >50K 42, Private, 37937, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 45, Private, 59380, Bachelors, 13, Separated, Exec-managerial, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 47, Private, 114770, HS-grad, 9, Divorced, Other-service, Own-child, White, Female, 0, 0, 32, United-States, <=50K 29, Private, 216481, Masters, 14, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 34, Private, 176469, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 34, Private, 176831, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, >50K 39, Federal-gov, 410034, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 93662, Some-college, 10, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 24, United-States, <=50K 42, Self-emp-inc, 144236, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 48, Private, 240917, 11th, 7, Separated, Other-service, Not-in-family, Black, Female, 0, 0, 35, United-States, <=50K 53, Private, 608184, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 1902, 40, United-States, >50K 51, Private, 243361, Some-college, 10, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 44, Self-emp-not-inc, 35166, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 90, United-States, <=50K 46, Self-emp-inc, 182655, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 51, Private, 142717, Doctorate, 16, Divorced, Craft-repair, Not-in-family, White, Female, 4787, 0, 60, United-States, >50K 32, Private, 272944, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, ?, 219233, HS-grad, 9, Never-married, ?, Own-child, Black, Male, 0, 1602, 30, United-States, <=50K 24, Private, 228686, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 33, Private, 236818, Assoc-voc, 11, Never-married, Prof-specialty, Unmarried, Black, Female, 0, 0, 26, United-States, <=50K 47, Self-emp-not-inc, 117865, HS-grad, 9, Married-AF-spouse, Craft-repair, Husband, White, Male, 0, 0, 90, United-States, <=50K 64, Self-emp-not-inc, 106538, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 62, Private, 153891, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 52, Private, 190909, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 191002, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, Poland, <=50K 42, Private, 89073, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 48, United-States, <=50K 38, Federal-gov, 238342, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 42, United-States, >50K 55, Private, 259532, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 29, ?, 189282, HS-grad, 9, Married-civ-spouse, ?, Not-in-family, White, Female, 0, 0, 27, United-States, <=50K 42, Private, 132481, Assoc-acdm, 12, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 24, United-States, <=50K 30, Private, 205659, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 50, Thailand, >50K 32, Private, 182323, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, ?, 216256, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 3464, 0, 30, United-States, <=50K 50, Federal-gov, 166419, 11th, 7, Never-married, Sales, Not-in-family, Black, Female, 3674, 0, 40, United-States, <=50K 27, Private, 152246, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 47, Private, 155659, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 33, Private, 155198, 9th, 5, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 48, Self-emp-not-inc, 100931, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 162945, 7th-8th, 4, Never-married, Other-service, Own-child, White, Male, 0, 0, 35, United-States, <=50K 31, Federal-gov, 334346, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 181597, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 61, Self-emp-not-inc, 133969, HS-grad, 9, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 0, 63, South, <=50K 50, Private, 210217, Bachelors, 13, Divorced, Sales, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 49, Private, 169711, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, Germany, >50K 57, ?, 300104, 5th-6th, 3, Married-civ-spouse, ?, Husband, White, Male, 7298, 0, 84, United-States, >50K 19, Private, 271521, HS-grad, 9, Never-married, Other-service, Other-relative, Asian-Pac-Islander, Male, 0, 0, 24, United-States, <=50K 18, Private, 51255, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 15, United-States, <=50K 44, Self-emp-not-inc, 26669, Assoc-acdm, 12, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 99, United-States, <=50K 54, Private, 194580, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 35, State-gov, 177974, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 27, State-gov, 315640, Masters, 14, Never-married, Prof-specialty, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 20, China, <=50K 50, Self-emp-inc, 136913, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 43, State-gov, 230961, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 167062, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 120131, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 243368, Preschool, 1, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 50, Mexico, <=50K 30, Private, 171876, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 19, Private, 136866, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 45, United-States, <=50K 40, Private, 316820, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 1485, 40, United-States, <=50K 55, Private, 185459, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 67, ?, 81761, HS-grad, 9, Divorced, ?, Own-child, White, Male, 0, 0, 20, United-States, <=50K 31, Private, 43716, Assoc-voc, 11, Divorced, Machine-op-inspct, Unmarried, White, Male, 0, 0, 43, United-States, <=50K 30, Private, 220939, Assoc-voc, 11, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 54, ?, 148657, Preschool, 1, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 40, Mexico, <=50K 51, Federal-gov, 40808, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 43, United-States, <=50K 34, Private, 183473, HS-grad, 9, Divorced, Transport-moving, Own-child, White, Female, 0, 0, 40, United-States, <=50K 59, Private, 108496, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 50, Private, 204838, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 29, Private, 132686, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 17, State-gov, 117906, 10th, 6, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 304386, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 52, ?, 248113, Preschool, 1, Married-spouse-absent, ?, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 39, Private, 165215, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 1902, 18, United-States, >50K 18, ?, 215463, 12th, 8, Never-married, ?, Own-child, White, Female, 0, 0, 25, United-States, <=50K 32, Private, 259719, Some-college, 10, Divorced, Handlers-cleaners, Unmarried, Black, Male, 0, 0, 40, Nicaragua, <=50K 25, ?, 35829, Some-college, 10, Divorced, ?, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 34, Private, 248795, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 44, Self-emp-not-inc, 124692, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 40, United-States, >50K 37, Local-gov, 128054, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 179731, Masters, 14, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 2415, 65, United-States, >50K 32, Self-emp-inc, 113543, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Private, 252153, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 28, United-States, <=50K 45, Federal-gov, 45891, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Male, 0, 0, 42, United-States, <=50K 30, Private, 112263, 11th, 7, Divorced, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 47791, 12th, 8, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 10, United-States, <=50K 41, Private, 202980, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 4, Peru, <=50K 21, Private, 34918, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 30, United-States, <=50K 48, Private, 91251, 7th-8th, 4, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 30, China, <=50K 31, Private, 132996, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 5178, 0, 45, United-States, >50K 34, Private, 306215, Assoc-voc, 11, Never-married, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 25, Private, 203570, HS-grad, 9, Separated, Other-service, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 41, Self-emp-not-inc, 355918, Bachelors, 13, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 35, Self-emp-not-inc, 198841, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 42, Private, 282964, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 34, Self-emp-not-inc, 312197, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 75, Mexico, >50K 44, Private, 98779, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 4386, 0, 60, United-States, <=50K 32, Private, 200246, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Private, 182771, Some-college, 10, Never-married, Sales, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 23, Private, 199908, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 36, Private, 172104, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, Other, Male, 0, 0, 40, India, >50K 53, Self-emp-not-inc, 35295, Bachelors, 13, Never-married, Sales, Unmarried, White, Male, 0, 0, 60, United-States, >50K 27, Private, 216858, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 52, United-States, <=50K 27, Private, 332187, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 65, United-States, <=50K 57, Private, 255109, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 17, Private, 111332, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 59, Local-gov, 238431, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 34, Private, 131552, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 110239, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 55, United-States, <=50K 31, State-gov, 255830, Assoc-acdm, 12, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 45, United-States, <=50K 18, ?, 175648, 11th, 7, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 82998, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 19, Private, 164320, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 20, Self-emp-not-inc, 263498, Assoc-voc, 11, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 52, Self-emp-not-inc, 162381, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Local-gov, 229651, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 27, Private, 357348, HS-grad, 9, Separated, Other-service, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 19, Private, 269657, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 38, Local-gov, 82880, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 15, United-States, <=50K 19, Private, 389755, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 16, United-States, <=50K 34, Private, 195136, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 1887, 40, United-States, >50K 41, Private, 207685, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, ?, <=50K 23, Private, 222925, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Own-child, White, Female, 2105, 0, 40, United-States, <=50K 24, ?, 196388, Assoc-acdm, 12, Never-married, ?, Not-in-family, White, Male, 0, 0, 12, United-States, <=50K 24, Private, 50341, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 214134, 10th, 6, Never-married, Transport-moving, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 84, United-States, <=50K 45, Private, 114032, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 45, Private, 192053, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 48, Private, 240231, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Japan, >50K 42, Private, 44402, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 35, Self-emp-not-inc, 191503, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 32, Private, 163530, HS-grad, 9, Divorced, Other-service, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 51, Local-gov, 136823, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 32, United-States, <=50K 59, Private, 121912, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Local-gov, 58624, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 27, Local-gov, 74056, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 29, Private, 144259, Bachelors, 13, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 4386, 0, 80, ?, >50K 57, Private, 182028, Assoc-acdm, 12, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 40, Private, 209040, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 206046, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 182494, 7th-8th, 4, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 185057, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 35, Scotland, <=50K 60, Private, 147473, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 53, Local-gov, 221722, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 14344, 0, 50, United-States, >50K 20, ?, 388811, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 221912, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 48189, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 29, State-gov, 382272, Bachelors, 13, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 48347, Bachelors, 13, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 143046, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 1564, 38, United-States, >50K 63, Self-emp-inc, 137940, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 50, United-States, >50K 28, Private, 249571, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 79, Private, 121318, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 20, United-States, <=50K 39, Private, 224531, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 40, United-States, >50K 29, Private, 185019, 12th, 8, Never-married, Other-service, Not-in-family, Other, Male, 0, 0, 40, United-States, <=50K 60, Private, 27886, 7th-8th, 4, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 58, Private, 94741, 12th, 8, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 24, United-States, <=50K 20, Private, 107801, Assoc-acdm, 12, Never-married, Other-service, Own-child, White, Female, 0, 2205, 18, United-States, <=50K 44, Private, 191256, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 65, United-States, >50K 47, Private, 256866, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 48, United-States, <=50K 59, Private, 197148, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 24, United-States, >50K 37, Private, 312271, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 21, Private, 118657, HS-grad, 9, Separated, Machine-op-inspct, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 68, Private, 224338, Assoc-voc, 11, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 242488, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 5013, 0, 40, United-States, <=50K 23, ?, 234970, Some-college, 10, Never-married, ?, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 23, Private, 227915, HS-grad, 9, Never-married, Craft-repair, Unmarried, White, Female, 0, 0, 33, United-States, <=50K 40, Local-gov, 105717, Masters, 14, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 1876, 35, United-States, <=50K 45, Self-emp-not-inc, 160962, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 35, United-States, <=50K 34, ?, 353881, Assoc-voc, 11, Married-civ-spouse, ?, Husband, White, Male, 3103, 0, 60, United-States, >50K 22, Private, 188950, Some-college, 10, Never-married, Tech-support, Own-child, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 201328, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 24, Private, 218678, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 49, United-States, <=50K 23, Private, 184255, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, <=50K 39, Federal-gov, 200968, Some-college, 10, Married-civ-spouse, Adm-clerical, Other-relative, White, Male, 0, 0, 45, United-States, >50K 26, Private, 102264, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 300584, HS-grad, 9, Never-married, Handlers-cleaners, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 208946, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 25, United-States, <=50K 36, Private, 105021, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, <=50K 20, Private, 124751, Some-college, 10, Never-married, Priv-house-serv, Own-child, White, Female, 0, 0, 20, United-States, <=50K 18, Private, 274057, 11th, 7, Never-married, Other-service, Own-child, Black, Male, 0, 0, 8, United-States, <=50K 38, Private, 132879, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 43, Self-emp-inc, 260960, Bachelors, 13, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 56, Private, 208415, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, Black, Male, 0, 0, 40, ?, <=50K 42, Private, 356934, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 154410, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 31, Private, 35378, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 73, Private, 301210, 1st-4th, 2, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1735, 20, United-States, <=50K 32, Private, 73621, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 42, United-States, <=50K 37, Private, 108140, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 45, United-States, >50K 66, Private, 217198, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 10, United-States, <=50K 22, Private, 157332, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 35, United-States, <=50K 51, Private, 202956, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 173495, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 35, United-States, <=50K 65, Private, 149811, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 2206, 59, Canada, <=50K 39, Private, 444219, HS-grad, 9, Married-civ-spouse, Craft-repair, Wife, Black, Female, 0, 0, 45, United-States, <=50K 48, Private, 125120, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 37, United-States, <=50K 20, Private, 190429, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, ?, 190303, Assoc-acdm, 12, Never-married, ?, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 248164, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 4386, 0, 50, United-States, >50K 29, Federal-gov, 208534, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 80, United-States, <=50K 36, Self-emp-not-inc, 343721, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 30, ?, >50K 35, Self-emp-inc, 196373, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 31, Private, 433788, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 48, State-gov, 122086, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 137314, Assoc-voc, 11, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 40, Self-emp-not-inc, 33068, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 57, Private, 210688, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 15, United-States, <=50K 26, Local-gov, 117833, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 4865, 0, 35, United-States, <=50K 37, State-gov, 103474, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 65, Private, 115880, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Self-emp-not-inc, 233933, 10th, 6, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 42, Private, 52781, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 586657, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, Japan, >50K 62, Private, 113080, 7th-8th, 4, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 251905, Assoc-voc, 11, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 50, United-States, <=50K 76, Self-emp-not-inc, 225964, Some-college, 10, Widowed, Sales, Not-in-family, White, Male, 0, 0, 8, United-States, <=50K 20, ?, 194096, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 263831, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 133136, 12th, 8, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Private, 121634, 10th, 6, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, Mexico, <=50K 22, Self-emp-inc, 40767, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Federal-gov, 355789, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 50, United-States, <=50K 43, Local-gov, 311914, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 91189, Bachelors, 13, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 20, United-States, <=50K 44, Federal-gov, 344060, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Private, 113823, Bachelors, 13, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 49, State-gov, 185800, Masters, 14, Divorced, Prof-specialty, Unmarried, Black, Female, 7430, 0, 40, United-States, >50K 30, Private, 76107, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 23, Private, 117618, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 35, United-States, <=50K 39, Private, 238008, HS-grad, 9, Widowed, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 136480, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 50, Private, 285200, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1887, 35, United-States, >50K 19, Private, 351040, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, Puerto-Rico, <=50K 35, Private, 1226583, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 52, United-States, >50K 23, Private, 195767, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 187540, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 79372, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 226665, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 42, United-States, >50K 52, Private, 213209, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 49, Private, 211005, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 60, United-States, <=50K 24, Private, 96178, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 328216, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 40, United-States, >50K 39, Private, 110713, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 45, Self-emp-not-inc, 225456, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 62, Local-gov, 159908, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 1258, 38, United-States, <=50K 43, Private, 118308, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 50, United-States, >50K 45, Private, 180309, Some-college, 10, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 62, Self-emp-not-inc, 39630, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 273828, 5th-6th, 3, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 56, Private, 172071, HS-grad, 9, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 40, Jamaica, <=50K 28, Private, 218887, HS-grad, 9, Never-married, Farming-fishing, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 23, Private, 664670, HS-grad, 9, Never-married, Craft-repair, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 43, Private, 209149, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 26, Private, 84619, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 447346, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 55, Local-gov, 37869, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 48, State-gov, 99086, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 43, Private, 143582, 5th-6th, 3, Married-civ-spouse, Machine-op-inspct, Wife, Asian-Pac-Islander, Female, 0, 2129, 72, ?, <=50K 38, Private, 326886, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 18, Private, 181755, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 56, Self-emp-not-inc, 249368, HS-grad, 9, Married-spouse-absent, Exec-managerial, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 39, Self-emp-not-inc, 326400, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 504725, 5th-6th, 3, Separated, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 50, Mexico, <=50K 36, Private, 88967, 11th, 7, Never-married, Transport-moving, Unmarried, Amer-Indian-Eskimo, Male, 0, 0, 65, United-States, <=50K 42, Self-emp-not-inc, 170721, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 2002, 40, United-States, <=50K 50, Private, 148953, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 17, Private, 342752, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, United-States, <=50K 57, Private, 220871, 7th-8th, 4, Widowed, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 73, Private, 29675, HS-grad, 9, Widowed, Other-service, Other-relative, White, Female, 0, 0, 12, United-States, <=50K 50, Federal-gov, 183611, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 115215, Some-college, 10, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 45, United-States, <=50K 27, Private, 152231, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, <=50K 24, ?, 41356, Some-college, 10, Never-married, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 225142, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 23, Self-emp-not-inc, 121313, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 134821, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 311350, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 102106, 10th, 6, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 427055, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, Mexico, <=50K 40, Private, 117860, HS-grad, 9, Divorced, Other-service, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 58, Private, 285885, 9th, 5, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 212800, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 194864, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 18, United-States, <=50K 36, Private, 31438, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 43, United-States, <=50K 46, Private, 148254, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 69, Private, 113035, 1st-4th, 2, Widowed, Priv-house-serv, Not-in-family, Black, Female, 0, 0, 4, United-States, <=50K 69, Private, 106595, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 1848, 0, 40, United-States, <=50K 28, Private, 144521, HS-grad, 9, Never-married, Other-service, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 20, Private, 172232, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 48, United-States, <=50K 54, State-gov, 123592, HS-grad, 9, Separated, Adm-clerical, Unmarried, Black, Female, 3887, 0, 35, United-States, <=50K 25, Private, 191921, Some-college, 10, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 64, Local-gov, 237379, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 3471, 0, 40, United-States, <=50K 17, Private, 208463, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 53, Federal-gov, 68985, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 22418, 9th, 5, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 57, Private, 163047, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 38, United-States, <=50K 51, Private, 153870, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 2603, 40, United-States, <=50K 20, ?, 124954, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 30, United-States, <=50K 47, Private, 197702, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 166415, HS-grad, 9, Never-married, Transport-moving, Unmarried, White, Male, 0, 0, 52, United-States, <=50K 50, State-gov, 116211, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 52, United-States, >50K 20, Private, 33644, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 30, United-States, <=50K 43, State-gov, 33331, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 70, United-States, >50K 46, Private, 73019, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 54, Private, 169182, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 38, Puerto-Rico, <=50K 53, Private, 20438, Some-college, 10, Separated, Exec-managerial, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 15, United-States, <=50K 21, Private, 109869, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 30, United-States, <=50K 58, Private, 316849, Some-college, 10, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 208043, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, >50K 61, Private, 153790, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 0, 40, United-States, <=50K 56, State-gov, 153451, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 59, Private, 96840, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 72, Private, 192732, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 20, United-States, <=50K 33, Private, 209101, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 146919, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 46, Local-gov, 192323, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 38, United-States, >50K 48, Private, 217019, HS-grad, 9, Never-married, Prof-specialty, Unmarried, Black, Female, 0, 0, 28, United-States, <=50K 33, Private, 198211, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 222490, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 106758, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 31, Private, 561334, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 203710, Bachelors, 13, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 45, Local-gov, 203322, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 51, Private, 123703, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 4386, 0, 40, United-States, >50K 46, State-gov, 312015, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 25, Private, 209428, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 25, El-Salvador, <=50K 61, Private, 230292, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 7688, 0, 40, United-States, >50K 17, Private, 114420, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 30, United-States, <=50K 26, Private, 120238, Bachelors, 13, Never-married, Craft-repair, Not-in-family, White, Male, 3325, 0, 40, United-States, <=50K 35, Private, 100375, 10th, 6, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 33, Self-emp-not-inc, 42485, 11th, 7, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 70, United-States, <=50K 37, Private, 130620, 12th, 8, Married-civ-spouse, Sales, Wife, Asian-Pac-Islander, Female, 0, 0, 33, ?, <=50K 39, Local-gov, 134367, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 35, United-States, <=50K 42, Private, 147099, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 35, Private, 36214, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 4386, 0, 47, United-States, >50K 45, Private, 119904, HS-grad, 9, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 47, Self-emp-inc, 105779, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, >50K 64, Private, 165020, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, <=50K 39, Private, 187098, Prof-school, 15, Married-civ-spouse, Exec-managerial, Wife, White, Female, 15024, 0, 47, United-States, >50K 43, ?, 142030, HS-grad, 9, Divorced, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 241360, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, ?, <=50K 62, Private, 121319, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 3103, 0, 40, United-States, >50K 53, Private, 151580, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 40, United-States, >50K 31, Private, 162572, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 35917, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, Self-emp-inc, 35723, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 43, Private, 194773, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 62155, Some-college, 10, Never-married, Sales, Not-in-family, Black, Male, 0, 0, 35, United-States, <=50K 45, Self-emp-not-inc, 192203, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1485, 40, United-States, >50K 46, Private, 174370, Some-college, 10, Separated, Sales, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 26, Private, 161007, Assoc-voc, 11, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 80, United-States, <=50K 24, Private, 270517, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, Mexico, <=50K 43, Private, 163847, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, >50K 40, Private, 193882, Assoc-voc, 11, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 160037, 7th-8th, 4, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 34, Federal-gov, 189944, Some-college, 10, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 72, United-States, <=50K 85, Private, 115364, HS-grad, 9, Widowed, Sales, Unmarried, White, Male, 0, 0, 35, United-States, <=50K 41, Private, 163174, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, State-gov, 188900, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 3325, 0, 35, United-States, <=50K 22, Private, 214399, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 30, United-States, <=50K 60, Private, 156616, HS-grad, 9, Widowed, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 29, Private, 204862, Assoc-acdm, 12, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 36, United-States, <=50K 34, ?, 55921, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, State-gov, 172475, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, Asian-Pac-Islander, Female, 2977, 0, 45, United-States, <=50K 24, Private, 153082, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 45, Local-gov, 195418, Masters, 14, Divorced, Prof-specialty, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 21, Local-gov, 276840, 12th, 8, Never-married, Other-service, Own-child, Black, Male, 0, 0, 20, United-States, <=50K 30, Private, 97933, Assoc-acdm, 12, Married-civ-spouse, Transport-moving, Wife, White, Female, 0, 1485, 37, United-States, >50K 50, Self-emp-inc, 119099, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 99, United-States, >50K 41, Self-emp-not-inc, 83411, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 21, Private, 198992, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 33, United-States, <=50K 45, Private, 337825, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 34, Private, 192002, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 189346, HS-grad, 9, Divorced, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 231962, HS-grad, 9, Never-married, Other-service, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 164488, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 13550, 0, 50, United-States, >50K 48, Private, 200471, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, >50K 69, Private, 228921, Bachelors, 13, Widowed, Prof-specialty, Not-in-family, White, Male, 0, 2282, 40, United-States, >50K 41, Private, 184846, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 233851, Bachelors, 13, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 499001, HS-grad, 9, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, Mexico, <=50K 65, Local-gov, 125768, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 28, United-States, <=50K 31, Private, 255004, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 1741, 38, United-States, <=50K 28, Private, 157624, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 146767, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 45, Private, 118291, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Female, 0, 0, 80, United-States, <=50K 43, Private, 313181, HS-grad, 9, Divorced, Adm-clerical, Other-relative, Black, Male, 0, 0, 38, United-States, <=50K 31, Private, 87891, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 31, Private, 226443, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, >50K 45, Private, 81132, Some-college, 10, Married-civ-spouse, Craft-repair, Other-relative, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 20, Private, 216436, Bachelors, 13, Never-married, Sales, Other-relative, Black, Female, 0, 0, 30, United-States, <=50K 25, Private, 213412, Bachelors, 13, Never-married, Tech-support, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 179358, HS-grad, 9, Widowed, Handlers-cleaners, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 31, Private, 369825, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 4101, 0, 50, United-States, <=50K 56, Private, 199763, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 26, Private, 239390, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 0, 18, United-States, <=50K 47, Self-emp-not-inc, 173613, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 65, United-States, <=50K 40, Self-emp-inc, 37869, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 32, Private, 302845, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 48, United-States, <=50K 34, State-gov, 85218, Masters, 14, Never-married, Prof-specialty, Unmarried, Black, Female, 0, 0, 24, United-States, <=50K 37, Private, 48268, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, <=50K 38, Private, 173968, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 19, Private, 70982, Assoc-voc, 11, Never-married, Other-service, Own-child, Asian-Pac-Islander, Male, 0, 0, 16, United-States, <=50K 49, Private, 166857, 9th, 5, Divorced, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 18, ?, 256191, HS-grad, 9, Never-married, ?, Own-child, Black, Female, 0, 0, 25, United-States, <=50K 26, Private, 162872, Assoc-acdm, 12, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 82, Private, 152148, 7th-8th, 4, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 2, United-States, <=50K 40, Private, 139193, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 791084, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 50, United-States, <=50K 23, Private, 137214, HS-grad, 9, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 37, United-States, <=50K 19, Private, 183258, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 67, Private, 154035, HS-grad, 9, Widowed, Handlers-cleaners, Other-relative, Black, Male, 0, 0, 32, United-States, <=50K 43, Private, 115323, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 3103, 0, 40, United-States, >50K 41, Private, 213055, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, Other, Female, 0, 0, 50, United-States, <=50K 37, Private, 155064, Assoc-voc, 11, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 33551, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 169995, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 168262, Masters, 14, Separated, Exec-managerial, Not-in-family, White, Male, 99999, 0, 50, United-States, >50K 40, Private, 104196, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, State-gov, 114055, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 274398, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 20, United-States, <=50K 78, ?, 27979, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 2228, 0, 32, United-States, <=50K 67, ?, 244122, Assoc-voc, 11, Widowed, ?, Not-in-family, White, Female, 0, 0, 1, United-States, <=50K 49, Private, 196571, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 66, Private, 101607, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 10, United-States, <=50K 52, Private, 122109, HS-grad, 9, Never-married, Prof-specialty, Unmarried, White, Female, 0, 323, 40, United-States, <=50K 59, Self-emp-inc, 255822, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 72, Private, 195184, HS-grad, 9, Widowed, Priv-house-serv, Unmarried, White, Female, 0, 0, 12, Cuba, <=50K 35, Federal-gov, 245372, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 169583, Bachelors, 13, Married-AF-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 36, Private, 224531, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 186151, HS-grad, 9, Separated, Tech-support, Own-child, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 118693, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 39, Private, 297449, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Self-emp-not-inc, 125206, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 393264, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 108140, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 63, Private, 264968, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 58, Self-emp-not-inc, 318106, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Private, 156025, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 38, State-gov, 149455, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 25, Private, 359985, 5th-6th, 3, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 33, Mexico, <=50K 44, State-gov, 165108, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 43, Private, 115178, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 21, Private, 149224, Some-college, 10, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 30, United-States, <=50K 41, Local-gov, 352056, Assoc-acdm, 12, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 174717, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 75, ?, 173064, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 6, United-States, <=50K 29, Private, 147755, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1672, 40, United-States, <=50K 52, Self-emp-not-inc, 135716, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 70, United-States, <=50K 47, Private, 44216, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 28, Private, 37359, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 50, United-States, >50K 24, Private, 178255, Some-college, 10, Married-civ-spouse, Priv-house-serv, Wife, White, Female, 0, 0, 40, ?, <=50K 30, State-gov, 70617, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 10, China, <=50K 30, Private, 154950, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 60, United-States, >50K 40, Private, 356934, Assoc-acdm, 12, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 27, Private, 271714, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 26, Private, 247025, HS-grad, 9, Never-married, Protective-serv, Unmarried, White, Male, 0, 0, 44, United-States, <=50K 32, Private, 107417, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 37, United-States, <=50K 36, State-gov, 116554, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 917220, 12th, 8, Never-married, Transport-moving, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 25, Private, 430084, Some-college, 10, Never-married, Transport-moving, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 39, Private, 202937, Some-college, 10, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 40, Poland, <=50K 27, Private, 62737, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 508548, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 38, Self-emp-inc, 275223, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 40, United-States, >50K 35, Self-emp-not-inc, 381931, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 55, United-States, <=50K 29, Private, 246974, Assoc-voc, 11, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 105431, HS-grad, 9, Divorced, Other-service, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 36, Private, 146311, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Self-emp-not-inc, 159869, Doctorate, 16, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 21, Private, 204641, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 66297, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, >50K 38, Private, 227615, 1st-4th, 2, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Mexico, <=50K 66, ?, 107744, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 360393, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 50, United-States, >50K 19, Private, 263340, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 18, Private, 141918, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 22, United-States, <=50K 37, Private, 294292, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 128736, Bachelors, 13, Never-married, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 33, Local-gov, 511289, Assoc-voc, 11, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 48, United-States, >50K 27, Private, 302406, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 34, Local-gov, 101517, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 54, State-gov, 161334, Masters, 14, Married-spouse-absent, Prof-specialty, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, China, <=50K 24, Self-emp-inc, 189148, Some-college, 10, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 44, Self-emp-not-inc, 103111, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 48, Self-emp-not-inc, 51620, Bachelors, 13, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 23, Private, 31606, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 34292, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 38, United-States, <=50K 21, Private, 107882, Assoc-acdm, 12, Never-married, Other-service, Own-child, White, Female, 0, 0, 9, United-States, <=50K 18, Private, 39529, 12th, 8, Never-married, Other-service, Own-child, White, Female, 0, 0, 32, United-States, <=50K 18, Private, 135315, 9th, 5, Never-married, Sales, Own-child, Other, Female, 0, 0, 32, United-States, <=50K 29, Private, 107812, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 229729, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 111891, HS-grad, 9, Separated, Machine-op-inspct, Other-relative, Black, Female, 0, 0, 40, United-States, <=50K 32, Private, 340917, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 202952, 10th, 6, Divorced, Other-service, Not-in-family, Black, Female, 0, 0, 24, United-States, <=50K 79, Private, 333230, HS-grad, 9, Married-spouse-absent, Prof-specialty, Not-in-family, White, Male, 0, 0, 6, United-States, <=50K 34, Private, 114955, Assoc-acdm, 12, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 159869, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 50, Self-emp-not-inc, 57758, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 29, Private, 207064, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 193090, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 3674, 0, 40, United-States, <=50K 64, Private, 151364, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 70, Local-gov, 88638, Masters, 14, Never-married, Prof-specialty, Unmarried, White, Female, 7896, 0, 50, United-States, >50K 28, Local-gov, 304960, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 1980, 40, United-States, <=50K 51, Private, 102828, Assoc-voc, 11, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Greece, <=50K 20, ?, 210029, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 34, State-gov, 154246, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 4865, 0, 55, United-States, <=50K 29, Private, 142519, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 104455, Bachelors, 13, Married-spouse-absent, Other-service, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 77, Self-emp-inc, 192230, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 292592, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 35, United-States, <=50K 27, Private, 330132, Bachelors, 13, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 40, United-States, >50K 22, Private, 51111, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Local-gov, 258037, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Cuba, >50K 42, Local-gov, 188291, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 1902, 40, United-States, >50K 35, State-gov, 349066, HS-grad, 9, Divorced, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 62, ?, 191188, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 133503, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 2635, 0, 16, United-States, <=50K 45, Private, 146497, Some-college, 10, Widowed, Exec-managerial, Unmarried, White, Female, 0, 0, 55, United-States, <=50K 19, Private, 240468, Some-college, 10, Married-spouse-absent, Sales, Own-child, White, Female, 0, 1602, 40, United-States, <=50K 38, Private, 175120, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 416577, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 45, United-States, <=50K 29, Private, 253814, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 33, Private, 159247, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Self-emp-not-inc, 102471, HS-grad, 9, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 0, 80, Puerto-Rico, <=50K 42, Private, 213464, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 211968, Assoc-voc, 11, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 43, Federal-gov, 32016, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 69, Private, 512992, 11th, 7, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 45, United-States, <=50K 39, Private, 135020, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 109133, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Portugal, <=50K 28, Private, 142712, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Federal-gov, 76900, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 112176, Some-college, 10, Divorced, Sales, Own-child, White, Male, 0, 0, 30, United-States, <=50K 43, Federal-gov, 262233, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 49, Private, 122066, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 30, Hungary, <=50K 28, Private, 194690, 7th-8th, 4, Separated, Other-service, Own-child, White, Male, 0, 0, 60, Mexico, <=50K 35, Private, 306678, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 2885, 0, 40, United-States, <=50K 19, ?, 217769, Some-college, 10, Never-married, ?, Own-child, White, Female, 594, 0, 10, United-States, <=50K 35, Local-gov, 308945, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 57, Private, 46699, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 377757, 9th, 5, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 220993, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 1590, 48, United-States, <=50K 45, Private, 102147, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 113770, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 139012, Bachelors, 13, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Vietnam, <=50K 45, Private, 148900, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 28, Federal-gov, 329426, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 64, Self-emp-inc, 181408, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 10, United-States, <=50K 44, Local-gov, 101950, Prof-school, 15, Separated, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 59, Self-emp-not-inc, 32537, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Private, 209547, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 202373, Some-college, 10, Never-married, Sales, Own-child, Black, Male, 0, 0, 25, United-States, <=50K 29, Self-emp-not-inc, 151476, Assoc-voc, 11, Never-married, Adm-clerical, Not-in-family, White, Female, 2174, 0, 40, United-States, <=50K 51, Self-emp-not-inc, 174824, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 8614, 0, 40, United-States, >50K 22, Private, 138768, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 143482, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 53, Private, 200190, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 80, United-States, >50K 38, Private, 168407, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 5721, 0, 44, United-States, <=50K 23, Private, 148315, Some-college, 10, Separated, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 270517, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, Mexico, <=50K 40, Private, 53506, Bachelors, 13, Divorced, Craft-repair, Own-child, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 105693, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 189589, Some-college, 10, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 164574, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, United-States, <=50K 37, Private, 185744, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 20, United-States, <=50K 40, Local-gov, 33155, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 215955, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 3103, 0, 40, United-States, >50K 38, Self-emp-not-inc, 233571, HS-grad, 9, Separated, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 211253, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 32, Federal-gov, 191385, Assoc-acdm, 12, Divorced, Protective-serv, Not-in-family, White, Male, 2174, 0, 40, United-States, <=50K 20, Private, 137895, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 62, State-gov, 159699, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 38, United-States, <=50K 31, Private, 295922, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Self-emp-not-inc, 175856, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 24, Private, 216129, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 62, Local-gov, 407669, 7th-8th, 4, Widowed, Other-service, Not-in-family, Black, Female, 0, 0, 35, United-States, <=50K 43, Local-gov, 214242, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 21, Private, 285457, Some-college, 10, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 50, United-States, <=50K 30, Self-emp-inc, 124420, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 4650, 0, 40, United-States, <=50K 22, ?, 246386, HS-grad, 9, Never-married, ?, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 18, Private, 142751, 10th, 6, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 59, Local-gov, 283635, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 24, Self-emp-not-inc, 322931, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1902, 40, United-States, >50K 49, Private, 76482, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, State-gov, 431745, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, United-States, <=50K 48, Private, 141944, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 4386, 0, 40, United-States, >50K 32, Private, 193042, Prof-school, 15, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 60, United-States, >50K 33, Private, 67006, 10th, 6, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 23, Private, 240398, Bachelors, 13, Never-married, Sales, Not-in-family, Black, Male, 0, 0, 15, United-States, <=50K 33, Federal-gov, 182714, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 65, United-States, >50K 50, Federal-gov, 172046, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Private, 185177, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 43, United-States, <=50K 32, Private, 102858, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 2002, 42, United-States, <=50K 39, Private, 84954, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 2829, 0, 65, United-States, <=50K 21, Private, 115895, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 23, Private, 184589, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 21, United-States, <=50K 32, Private, 282611, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 57, Private, 218649, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, State-gov, 157541, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 10, United-States, <=50K 70, Private, 145419, HS-grad, 9, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 5, United-States, <=50K 34, Private, 122616, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 84, United-States, >50K 53, Private, 204584, Masters, 14, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 117210, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 45, United-States, <=50K 37, Private, 69481, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 60, Self-emp-not-inc, 148492, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1485, 50, United-States, >50K 23, Private, 106957, 11th, 7, Never-married, Craft-repair, Own-child, Asian-Pac-Islander, Male, 14344, 0, 40, Vietnam, >50K 32, Private, 29312, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 80, United-States, >50K 57, Private, 120302, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 65, ?, 111916, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 182227, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 30, Private, 219110, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 46, United-States, <=50K 31, Private, 200192, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, Germany, <=50K 19, Private, 427862, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 35, United-States, <=50K 23, State-gov, 33551, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 38, United-States, <=50K 44, Private, 164043, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, ?, 116632, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 45, United-States, >50K 42, Private, 175133, Some-college, 10, Never-married, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 34, Self-emp-not-inc, 289731, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 256362, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Private, 282612, Assoc-voc, 11, Never-married, Tech-support, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 21, Private, 73679, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 237824, HS-grad, 9, Married-spouse-absent, Priv-house-serv, Other-relative, Black, Female, 0, 0, 60, Jamaica, <=50K 36, Local-gov, 357720, Assoc-voc, 11, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 49, Self-emp-not-inc, 155489, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 65, Poland, <=50K 44, Private, 138077, Bachelors, 13, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 42, Private, 183479, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Private, 103596, HS-grad, 9, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 99, United-States, <=50K 33, Private, 172304, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Self-emp-not-inc, 313853, Bachelors, 13, Divorced, Other-service, Unmarried, Black, Male, 0, 0, 45, United-States, >50K 17, Private, 294485, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, United-States, <=50K 20, Private, 637080, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 32, Private, 385959, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 50, United-States, <=50K 33, Self-emp-not-inc, 116539, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 129263, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 60, United-States, <=50K 60, Private, 141253, 10th, 6, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 35, State-gov, 35626, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 15, United-States, <=50K 43, Federal-gov, 94937, Bachelors, 13, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 220269, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Self-emp-not-inc, 169544, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 5178, 0, 40, United-States, >50K 36, Private, 214604, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 42, United-States, >50K 27, Private, 81540, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 50, Private, 24013, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 84, United-States, >50K 22, Private, 124940, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, Amer-Indian-Eskimo, Female, 0, 0, 44, United-States, <=50K 33, State-gov, 313729, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 61, Private, 192237, 10th, 6, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 28, ?, 168524, Assoc-voc, 11, Married-civ-spouse, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 41, Self-emp-not-inc, 113324, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 70, United-States, >50K 22, Private, 215477, Some-college, 10, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 199903, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 431861, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 105938, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, Black, Female, 0, 1602, 20, United-States, <=50K 28, Private, 274679, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 25, Private, 177499, Bachelors, 13, Never-married, Craft-repair, Own-child, White, Male, 0, 1590, 35, United-States, <=50K 28, Private, 206125, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Local-gov, 221740, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 30, United-States, >50K 58, Private, 202652, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 37, United-States, <=50K 39, Private, 348960, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 171876, Some-college, 10, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 59, Private, 157932, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 58, Private, 201344, Bachelors, 13, Divorced, Craft-repair, Own-child, White, Female, 0, 0, 20, United-States, <=50K 38, Private, 354739, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 36, Philippines, >50K 34, Private, 40067, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 326862, Some-college, 10, Divorced, Craft-repair, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 48, Local-gov, 189762, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 65, ?, 149049, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 226246, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 80, ?, 29020, Prof-school, 15, Married-civ-spouse, ?, Husband, White, Male, 10605, 0, 10, United-States, >50K 23, Private, 38251, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 196385, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 37, United-States, >50K 38, Self-emp-not-inc, 217054, Some-college, 10, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Self-emp-not-inc, 104973, Masters, 14, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, >50K 48, Local-gov, 238959, Masters, 14, Divorced, Exec-managerial, Unmarried, Black, Female, 9562, 0, 40, United-States, >50K 40, State-gov, 34218, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Local-gov, 292962, HS-grad, 9, Never-married, Craft-repair, Other-relative, Black, Female, 0, 0, 40, United-States, <=50K 45, Private, 235924, Bachelors, 13, Divorced, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 98656, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 70, Private, 102610, Some-college, 10, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 80, United-States, <=50K 32, Local-gov, 296466, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 33, Private, 323069, Assoc-voc, 11, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 184756, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Local-gov, 233993, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 15, United-States, <=50K 22, Private, 130724, Some-college, 10, Never-married, Sales, Own-child, Black, Male, 0, 0, 25, United-States, <=50K 52, Self-emp-inc, 181855, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, Other, Male, 99999, 0, 65, United-States, >50K 67, Self-emp-not-inc, 127543, 10th, 6, Married-civ-spouse, Farming-fishing, Husband, White, Male, 2414, 0, 80, United-States, <=50K 40, Private, 187164, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1672, 45, United-States, <=50K 55, Private, 113912, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 20, United-States, <=50K 29, Private, 216479, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 62, Private, 135480, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 16, United-States, <=50K 22, Private, 204160, HS-grad, 9, Divorced, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 64, State-gov, 114650, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Self-emp-not-inc, 240172, Bachelors, 13, Never-married, Exec-managerial, Other-relative, White, Male, 0, 0, 50, United-States, <=50K 28, Private, 184831, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 124590, HS-grad, 9, Never-married, Exec-managerial, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 47, State-gov, 120429, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 50, United-States, >50K 26, Private, 202033, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 18, Private, 156874, 12th, 8, Never-married, Other-service, Own-child, White, Male, 0, 0, 27, United-States, <=50K 52, Self-emp-inc, 177727, 10th, 6, Married-civ-spouse, Sales, Husband, White, Male, 4064, 0, 45, United-States, <=50K 48, Local-gov, 334409, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 50, United-States, >50K 36, Private, 311255, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, Haiti, <=50K 23, Private, 214227, Assoc-voc, 11, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 41, Private, 115849, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, State-gov, 671292, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 38, United-States, >50K 53, Private, 31460, HS-grad, 9, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 141824, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 310152, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 3325, 0, 40, United-States, <=50K 25, Private, 179953, Masters, 14, Never-married, Prof-specialty, Own-child, White, Female, 2597, 0, 31, United-States, <=50K 31, Private, 137952, Some-college, 10, Married-civ-spouse, Other-service, Husband, Other, Male, 0, 0, 40, Puerto-Rico, <=50K 36, Private, 103323, Assoc-acdm, 12, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 2829, 0, 40, United-States, <=50K 46, Private, 174426, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, State-gov, 192779, Assoc-acdm, 12, Divorced, Adm-clerical, Unmarried, White, Male, 0, 2258, 38, United-States, >50K 32, Private, 169955, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 36, Puerto-Rico, <=50K 43, Self-emp-not-inc, 48087, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 30, Private, 132601, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 50, United-States, >50K 41, Self-emp-inc, 253060, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 45, United-States, >50K 50, Private, 108435, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 60, United-States, >50K 37, State-gov, 210452, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 38, United-States, <=50K 22, Local-gov, 134181, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 50, United-States, <=50K 51, Federal-gov, 45487, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 80, United-States, <=50K 47, Private, 183522, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, Black, Female, 0, 0, 40, United-States, >50K 40, Private, 199303, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 83064, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, ?, 134997, Some-college, 10, Separated, ?, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 30, Private, 44419, Some-college, 10, Never-married, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 27, Self-emp-not-inc, 442612, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 65, United-States, >50K 31, Local-gov, 158092, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 35, United-States, <=50K 31, Private, 374833, 1st-4th, 2, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Mexico, <=50K 30, Private, 112650, HS-grad, 9, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 50, Local-gov, 183390, Bachelors, 13, Separated, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 27, Private, 207418, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 22, ?, 335453, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 16, United-States, <=50K 29, Private, 243660, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, >50K 28, Private, 54243, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 54, Private, 50385, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, Black, Female, 0, 0, 45, United-States, >50K 47, State-gov, 187581, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 48, United-States, >50K 34, Private, 37380, HS-grad, 9, Married-spouse-absent, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 247025, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 53, ?, 29231, 7th-8th, 4, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 35, United-States, <=50K 23, State-gov, 101094, Some-college, 10, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 60, United-States, <=50K 42, Local-gov, 176716, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Self-emp-not-inc, 118429, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 52, Federal-gov, 221532, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 45, United-States, >50K 22, ?, 120572, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 27, Local-gov, 124680, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 153160, HS-grad, 9, Widowed, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 114678, HS-grad, 9, Divorced, Other-service, Unmarried, Black, Female, 5455, 0, 40, United-States, <=50K 49, State-gov, 142856, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 29702, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 40, United-States, >50K 20, Private, 277700, Preschool, 1, Never-married, Other-service, Own-child, White, Male, 0, 0, 32, United-States, <=50K 55, Self-emp-inc, 67433, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 47, Private, 121124, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 394447, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 33, United-States, >50K 36, Private, 79649, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 203763, Doctorate, 16, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 80, United-States, <=50K 55, Private, 229029, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 48, United-States, >50K 21, ?, 494638, Assoc-acdm, 12, Never-married, ?, Own-child, White, Male, 0, 0, 15, United-States, <=50K 48, Private, 162816, Assoc-acdm, 12, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 30, Private, 109117, Assoc-voc, 11, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 45, United-States, <=50K 24, Private, 32732, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 57, Self-emp-not-inc, 217692, HS-grad, 9, Widowed, Craft-repair, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 20, Private, 34590, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 60, United-States, <=50K 18, ?, 276864, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 1602, 20, United-States, <=50K 56, Private, 168625, HS-grad, 9, Divorced, Prof-specialty, Not-in-family, White, Female, 4101, 0, 40, United-States, <=50K 36, Private, 91037, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 44, Private, 171484, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 57, Private, 200453, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 15024, 0, 40, United-States, >50K 57, Private, 36990, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 52, United-States, <=50K 33, Private, 198211, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, ?, 30475, 7th-8th, 4, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 70995, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 15024, 0, 99, United-States, >50K 28, Private, 245790, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 273324, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 1721, 16, United-States, <=50K 60, Private, 182687, Assoc-acdm, 12, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, Local-gov, 247807, Assoc-voc, 11, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 58, Private, 163113, HS-grad, 9, Widowed, Sales, Not-in-family, White, Female, 0, 0, 35, United-States, >50K 50, Private, 180522, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 23, Local-gov, 203353, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 12, United-States, <=50K 30, Private, 87469, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, ?, 216563, 11th, 7, Never-married, ?, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 90, Private, 87372, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 20051, 0, 72, United-States, >50K 49, Local-gov, 173584, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 47, Local-gov, 80282, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 3137, 0, 40, United-States, <=50K 34, Private, 319854, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, Taiwan, >50K 37, Federal-gov, 408229, HS-grad, 9, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 431307, 10th, 6, Married-civ-spouse, Protective-serv, Wife, Black, Female, 0, 0, 50, United-States, <=50K 37, Private, 134088, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 246396, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, Mexico, <=50K 34, Private, 159255, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 34, Private, 106014, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 186934, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 50, United-States, >50K 39, Private, 120130, Some-college, 10, Separated, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 32, State-gov, 203849, 7th-8th, 4, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 19, United-States, <=50K 24, Private, 207940, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 30, United-States, <=50K 28, Private, 302406, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 41, Self-emp-not-inc, 144594, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 2179, 40, United-States, <=50K 69, ?, 171050, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 9, United-States, <=50K 32, Private, 459007, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 90, United-States, <=50K 58, Private, 372181, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, >50K 47, Self-emp-not-inc, 172034, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 75, United-States, >50K 41, Private, 156566, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 4386, 0, 50, United-States, >50K 35, Self-emp-inc, 338320, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 24, Private, 353696, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, Canada, <=50K 46, Self-emp-not-inc, 342907, HS-grad, 9, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 60, United-States, >50K 69, Self-emp-inc, 169717, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 6418, 0, 45, United-States, >50K 22, Private, 103762, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 36, State-gov, 47570, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 119432, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Local-gov, 144165, Bachelors, 13, Never-married, Prof-specialty, Own-child, Amer-Indian-Eskimo, Male, 0, 0, 30, United-States, <=50K 35, Private, 180647, Some-college, 10, Never-married, Prof-specialty, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 37, Local-gov, 312232, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 5178, 0, 40, United-States, >50K 35, State-gov, 150488, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 200876, 11th, 7, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 16, United-States, <=50K 43, Private, 188199, 9th, 5, Divorced, Handlers-cleaners, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 53, State-gov, 118793, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Local-gov, 204325, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 52, United-States, <=50K 29, Private, 256671, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 231515, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 47, Cuba, <=50K 24, Private, 100669, Some-college, 10, Never-married, Handlers-cleaners, Own-child, Asian-Pac-Islander, Male, 0, 0, 30, United-States, <=50K 30, Private, 88913, Some-college, 10, Separated, Other-service, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 23, Private, 363219, Some-college, 10, Never-married, Priv-house-serv, Not-in-family, White, Female, 0, 0, 6, United-States, <=50K 27, ?, 291547, Bachelors, 13, Married-civ-spouse, ?, Not-in-family, Other, Female, 0, 0, 6, Mexico, <=50K 36, Private, 308945, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Self-emp-not-inc, 100316, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 33, Private, 296453, Masters, 14, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 15, United-States, <=50K 66, Private, 298834, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, Canada, <=50K 45, Self-emp-not-inc, 188694, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 68, ?, 29240, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 12, United-States, <=50K 37, Private, 186934, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 60, United-States, >50K 17, Private, 154908, 10th, 6, Never-married, Other-service, Own-child, White, Female, 0, 0, 10, United-States, <=50K 31, Private, 22201, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, >50K 46, Private, 216999, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 55, United-States, >50K 40, Private, 186916, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 116677, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, Private, 95763, 10th, 6, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 42, Private, 266710, Some-college, 10, Separated, Adm-clerical, Unmarried, Black, Female, 0, 0, 41, United-States, <=50K 46, Private, 117849, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 30, Private, 242460, HS-grad, 9, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 33, Self-emp-not-inc, 202729, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 47, Private, 181652, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, United-States, <=50K 57, Self-emp-not-inc, 174760, Assoc-acdm, 12, Married-spouse-absent, Farming-fishing, Unmarried, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 34, Private, 56121, 11th, 7, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 390369, HS-grad, 9, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 149726, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 22, Private, 51262, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 190350, 12th, 8, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 35, ?, <=50K 53, Federal-gov, 205288, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 7688, 0, 35, United-States, >50K 36, Private, 154835, HS-grad, 9, Separated, Adm-clerical, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 45, Private, 89028, HS-grad, 9, Divorced, Craft-repair, Not-in-family, Asian-Pac-Islander, Male, 10520, 0, 40, United-States, >50K 36, Private, 194630, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 18, Self-emp-not-inc, 212207, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 11, United-States, <=50K 27, Private, 204788, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 158688, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 97723, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 193026, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Self-emp-not-inc, 257250, 7th-8th, 4, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 75, United-States, <=50K 48, Private, 355978, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Self-emp-not-inc, 200574, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 60, United-States, >50K 21, Private, 376929, 5th-6th, 3, Never-married, Priv-house-serv, Not-in-family, White, Female, 0, 0, 40, Mexico, <=50K 47, State-gov, 123219, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 38, United-States, >50K 41, Private, 82778, 1st-4th, 2, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, Mexico, <=50K 61, Self-emp-not-inc, 115882, 1st-4th, 2, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 20, United-States, <=50K 64, Private, 103021, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 297767, Some-college, 10, Separated, Adm-clerical, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 44, Private, 259479, HS-grad, 9, Divorced, Transport-moving, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 20, Private, 167787, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 23, Local-gov, 40021, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 70, United-States, <=50K 52, Private, 245275, 10th, 6, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 35, United-States, <=50K 43, Private, 37402, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 32, Private, 103608, Bachelors, 13, Married-civ-spouse, Handlers-cleaners, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 63, Private, 137192, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, South, <=50K 29, Private, 137618, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 41, United-States, >50K 42, Self-emp-inc, 96509, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 60, Taiwan, <=50K 65, Private, 196174, 10th, 6, Divorced, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 28, United-States, <=50K 24, Private, 172612, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 141186, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 228190, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 40, Self-emp-inc, 190290, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, ?, >50K 38, Federal-gov, 307404, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 152436, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 46, Self-emp-not-inc, 182541, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 1672, 50, United-States, <=50K 39, Private, 282153, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 29, ?, 41281, Bachelors, 13, Married-spouse-absent, ?, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 42, Private, 162003, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 36, United-States, >50K 36, Private, 190759, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 26, Private, 208122, Some-college, 10, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 57, Private, 173832, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 1902, 40, United-States, >50K 55, Private, 129173, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 35, Private, 287548, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, >50K 41, Private, 216116, HS-grad, 9, Separated, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, ?, <=50K 24, Private, 146706, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 47, Private, 285200, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Self-emp-inc, 314375, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 44, Private, 203943, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 35, United-States, >50K 18, ?, 274746, HS-grad, 9, Never-married, ?, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 27, Private, 517000, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 36, Private, 66173, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 21, Private, 182823, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 0, 30, United-States, <=50K 29, Private, 159479, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Other, Male, 0, 0, 55, United-States, <=50K 25, Private, 135568, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 73, Private, 333676, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 45, Private, 201699, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 96020, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 50, United-States, >50K 43, Private, 176138, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 47, Private, 47496, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 42, United-States, <=50K 20, Private, 187158, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 15, United-States, <=50K 22, Private, 249727, Some-college, 10, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 20, United-States, <=50K 76, Self-emp-not-inc, 237624, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 10, United-States, <=50K 24, Private, 175254, Some-college, 10, Never-married, Transport-moving, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 54, Self-emp-not-inc, 42924, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 30, Private, 205950, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Private, 111985, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 58, United-States, <=50K 30, Private, 167476, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 40, Private, 221172, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 27, ?, 188711, Some-college, 10, Divorced, ?, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 49, Private, 199448, Assoc-voc, 11, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 313038, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 148431, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, Other, Female, 0, 0, 40, United-States, <=50K 19, Private, 112432, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 58, United-States, <=50K 46, Private, 57914, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 145166, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, <=50K 56, Private, 247119, 7th-8th, 4, Widowed, Machine-op-inspct, Unmarried, Other, Female, 0, 0, 40, Dominican-Republic, <=50K 53, Private, 196278, Some-college, 10, Widowed, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 60, ?, 366531, Assoc-voc, 11, Widowed, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 216481, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 188027, Some-college, 10, Never-married, Exec-managerial, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 37, Private, 66686, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Private, 74775, Bachelors, 13, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 30, Vietnam, <=50K 65, ?, 325537, Assoc-voc, 11, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 50, United-States, >50K 30, Self-emp-not-inc, 250499, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 55, United-States, >50K 57, Self-emp-not-inc, 192869, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 72, United-States, <=50K 44, Self-emp-inc, 121352, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 32, Self-emp-not-inc, 70985, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 4064, 0, 40, United-States, <=50K 27, Self-emp-not-inc, 123116, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 57, Local-gov, 339163, Some-college, 10, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 59, Self-emp-not-inc, 124771, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 30, United-States, <=50K 32, Private, 167531, Prof-school, 15, Married-civ-spouse, Prof-specialty, Wife, Asian-Pac-Islander, Female, 15024, 0, 50, United-States, >50K 90, ?, 77053, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 4356, 40, United-States, <=50K 22, Private, 199266, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 39, Private, 190728, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 99212, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 3103, 0, 48, United-States, >50K 38, Local-gov, 421446, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 50, United-States, >50K 61, Private, 215944, 9th, 5, Divorced, Sales, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 24, Private, 72310, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 43, United-States, <=50K 25, Private, 57512, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 44, Private, 89413, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Local-gov, 28151, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 90, Private, 46786, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 9386, 0, 15, United-States, >50K 30, Private, 226943, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 44, Private, 182402, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 305352, 10th, 6, Divorced, Craft-repair, Other-relative, Black, Male, 0, 0, 40, United-States, <=50K 63, Self-emp-inc, 189253, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 60, Private, 296485, 5th-6th, 3, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Self-emp-not-inc, 204375, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 60, United-States, >50K 49, Self-emp-not-inc, 249585, 11th, 7, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 65, United-States, <=50K 47, Private, 148995, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 65, United-States, >50K 42, Self-emp-inc, 168071, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 43, United-States, >50K 53, Private, 194995, 5th-6th, 3, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, Italy, <=50K 23, Private, 211049, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Female, 4101, 0, 40, United-States, <=50K 28, ?, 196630, Assoc-voc, 11, Separated, ?, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 20, Private, 50397, Some-college, 10, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 35, United-States, <=50K 43, Private, 177905, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 3908, 0, 40, United-States, <=50K 32, Private, 204374, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 60, United-States, >50K 43, Private, 60001, Bachelors, 13, Divorced, Sales, Unmarried, White, Male, 0, 0, 44, United-States, >50K 31, Private, 223046, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 29, ?, 44921, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 154571, Some-college, 10, Never-married, Adm-clerical, Own-child, Asian-Pac-Islander, Male, 0, 0, 20, United-States, <=50K 39, Private, 67136, Assoc-voc, 11, Separated, Adm-clerical, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 29, Private, 188675, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, Jamaica, >50K 20, Private, 390817, 5th-6th, 3, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 25, Mexico, <=50K 23, ?, 145964, Some-college, 10, Never-married, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 30424, 11th, 7, Separated, Other-service, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 53, Private, 548361, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 189148, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 48, United-States, <=50K 58, Self-emp-not-inc, 266707, 1st-4th, 2, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 2179, 18, United-States, <=50K 51, Self-emp-not-inc, 311569, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 187653, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 38, Private, 235379, Assoc-acdm, 12, Never-married, Prof-specialty, Unmarried, White, Female, 0, 0, 36, United-States, <=50K 41, Private, 188615, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 58, Private, 322691, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Private, 184698, 10th, 6, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, Dominican-Republic, <=50K 50, Private, 144361, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 130057, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 31, Self-emp-inc, 117963, Doctorate, 16, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 123876, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 37, Private, 248445, HS-grad, 9, Divorced, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, El-Salvador, <=50K 32, Private, 207172, Some-college, 10, Never-married, Sales, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 46, State-gov, 119904, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 1564, 55, United-States, >50K 62, Private, 134768, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Local-gov, 269168, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Other, Male, 0, 0, 40, ?, <=50K 56, Private, 132026, Bachelors, 13, Married-civ-spouse, Sales, Husband, Black, Male, 7688, 0, 45, United-States, >50K 37, Private, 60722, Some-college, 10, Divorced, Exec-managerial, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, Japan, >50K 41, Private, 648223, 1st-4th, 2, Married-spouse-absent, Farming-fishing, Unmarried, White, Male, 0, 0, 40, Mexico, <=50K 56, Private, 298695, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, <=50K 20, Private, 219835, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 34, Self-emp-not-inc, 313729, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 45, Private, 140644, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 30, Private, 203488, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 51, Self-emp-not-inc, 132341, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 27, Private, 161683, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 42, United-States, <=50K 38, Private, 312771, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 258102, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 50, United-States, <=50K 57, ?, 24127, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 8, United-States, <=50K 47, Private, 254367, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 77, ?, 185426, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 15, United-States, <=50K 43, Private, 152629, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Local-gov, 141058, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 65, United-States, <=50K 41, Private, 233130, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Private, 406641, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 30, State-gov, 119422, 10th, 6, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 255486, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 25, United-States, <=50K 22, Private, 161532, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 35, United-States, <=50K 25, Private, 75759, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 44, United-States, >50K 18, Private, 163332, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 22, United-States, <=50K 28, Private, 103802, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 1408, 40, ?, <=50K 50, Private, 34832, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 15024, 0, 40, United-States, >50K 28, Private, 37933, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 48, United-States, <=50K 21, Private, 165107, Some-college, 10, Never-married, Priv-house-serv, Own-child, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 126011, Assoc-voc, 11, Divorced, Tech-support, Own-child, White, Male, 0, 0, 40, United-States, <=50K 28, Federal-gov, 56651, Bachelors, 13, Never-married, Prof-specialty, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 23, Private, 522881, 5th-6th, 3, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 35, Mexico, <=50K 32, Private, 191777, Assoc-voc, 11, Never-married, Exec-managerial, Not-in-family, Black, Female, 0, 0, 35, England, <=50K 27, Private, 132686, 12th, 8, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 50, United-States, <=50K 55, Private, 201112, HS-grad, 9, Divorced, Prof-specialty, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 44, Private, 174283, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Private, 208591, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 126399, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 50, Private, 142073, HS-grad, 9, Married-spouse-absent, Exec-managerial, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 18, Private, 395567, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 74, Private, 180455, Bachelors, 13, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 8, United-States, <=50K 22, Private, 235853, 9th, 5, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 160731, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, State-gov, 31935, Some-college, 10, Never-married, Tech-support, Own-child, White, Female, 0, 0, 80, United-States, <=50K 41, Private, 35166, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 50, United-States, >50K 24, Private, 161092, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 7298, 0, 40, United-States, >50K 23, Private, 223019, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 34, Self-emp-not-inc, 179673, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 60, United-States, >50K 46, State-gov, 248895, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Private, 200323, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 41, Private, 230020, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Other, Male, 0, 0, 40, United-States, <=50K 29, Private, 134890, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, >50K 48, Private, 162096, 9th, 5, Married-civ-spouse, Machine-op-inspct, Other-relative, Asian-Pac-Islander, Female, 0, 0, 45, China, <=50K 51, Private, 103824, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 40, Haiti, <=50K 34, State-gov, 61431, 12th, 8, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 58, Private, 197319, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 52, Private, 183618, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Self-emp-not-inc, 268598, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Other, Male, 7298, 0, 50, Puerto-Rico, >50K 53, Private, 263729, Some-college, 10, Separated, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 54, Private, 39493, Assoc-voc, 11, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 20, United-States, <=50K 36, Private, 185360, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 25, Private, 132661, Assoc-voc, 11, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 60, United-States, <=50K 20, Private, 266400, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 48, United-States, <=50K 23, Private, 433669, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Self-emp-inc, 216473, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 20, Self-emp-not-inc, 217404, 10th, 6, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 227778, Assoc-voc, 11, Never-married, Other-service, Other-relative, Black, Male, 0, 0, 40, United-States, <=50K 73, State-gov, 96262, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 67, Private, 247566, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 24, United-States, <=50K 56, Private, 139616, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 32, Private, 73585, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 37869, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 1590, 40, United-States, <=50K 33, Private, 165814, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 40, United-States, <=50K 37, Private, 108913, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 34975, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 31, Private, 157078, 10th, 6, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 59, Private, 232672, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 21, Private, 294295, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 58, Self-emp-inc, 130454, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 24, Local-gov, 461678, 10th, 6, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 26, State-gov, 252284, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 256737, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Local-gov, 96480, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, Germany, <=50K 25, Private, 234263, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 109952, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, <=50K 24, Private, 262570, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Self-emp-not-inc, 65716, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 68, Private, 201732, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 66, Self-emp-not-inc, 174788, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 38, Private, 278924, Bachelors, 13, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 101593, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 71, ?, 193863, 7th-8th, 4, Widowed, ?, Other-relative, White, Female, 0, 0, 16, Poland, <=50K 37, Private, 342768, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Self-emp-not-inc, 242606, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 4386, 0, 45, United-States, >50K 27, State-gov, 176727, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 99179, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 19, State-gov, 354104, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 10, United-States, <=50K 25, Private, 61956, Some-college, 10, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 47, Federal-gov, 137917, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, >50K 40, Private, 224658, Some-college, 10, Married-civ-spouse, Sales, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 51100, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 3325, 0, 40, United-States, <=50K 25, Private, 224361, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 362912, Some-college, 10, Never-married, Craft-repair, Own-child, White, Female, 0, 0, 50, United-States, <=50K 23, Private, 218782, 10th, 6, Never-married, Handlers-cleaners, Other-relative, Other, Male, 0, 0, 40, United-States, <=50K 28, Private, 103389, Masters, 14, Divorced, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 308944, HS-grad, 9, Married-spouse-absent, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 140092, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 202210, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 52, Private, 416059, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 40, United-States, >50K 33, Self-emp-not-inc, 281030, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 94, United-States, <=50K 19, Private, 169758, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 35, United-States, <=50K 68, Private, 193666, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 20051, 0, 55, United-States, >50K 41, Private, 139907, 10th, 6, Never-married, Handlers-cleaners, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 18, Self-emp-inc, 119422, HS-grad, 9, Never-married, Other-service, Unmarried, Asian-Pac-Islander, Female, 0, 0, 30, India, <=50K 29, Private, 149324, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1485, 40, United-States, >50K 40, Private, 259307, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 51, Self-emp-not-inc, 74160, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Male, 0, 0, 60, United-States, >50K 49, Private, 134797, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, State-gov, 41103, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 38, Local-gov, 193026, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 57, Private, 303986, 5th-6th, 3, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, Cuba, <=50K 35, Private, 126569, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 4064, 0, 40, United-States, <=50K 66, Private, 166461, 11th, 7, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 26, United-States, <=50K 27, ?, 61387, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 15, United-States, <=50K 25, Private, 254746, Assoc-voc, 11, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 77, ?, 28678, Masters, 14, Married-civ-spouse, ?, Husband, White, Male, 9386, 0, 6, United-States, >50K 19, ?, 180976, 10th, 6, Never-married, ?, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 70, Private, 282642, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 2174, 40, United-States, >50K 59, Self-emp-not-inc, 136413, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 48, United-States, <=50K 25, Private, 131463, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Local-gov, 177240, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Male, 10520, 0, 40, United-States, >50K 37, Private, 218490, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, El-Salvador, >50K 75, ?, 260543, 10th, 6, Widowed, ?, Other-relative, Asian-Pac-Islander, Female, 0, 0, 1, China, <=50K 21, ?, 80680, HS-grad, 9, Never-married, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 20728, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 4101, 0, 40, United-States, <=50K 47, Federal-gov, 117628, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Private, 91939, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 1721, 30, United-States, <=50K 32, State-gov, 175931, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 309566, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 53, Private, 123703, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 19, ?, 369678, HS-grad, 9, Never-married, ?, Not-in-family, Other, Male, 0, 0, 30, United-States, <=50K 58, Private, 29928, Some-college, 10, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 36, United-States, <=50K 22, Private, 167868, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 23, Private, 235894, 11th, 7, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, <=50K 21, Private, 189888, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 3325, 0, 60, United-States, <=50K 36, Private, 111545, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 70, United-States, <=50K 39, Private, 175972, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 15, United-States, <=50K 34, Local-gov, 254270, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 41, Local-gov, 185057, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 72, Private, 157593, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 1455, 0, 6, United-States, <=50K 34, Private, 101345, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, >50K 51, Local-gov, 176751, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 40, United-States, >50K 32, Self-emp-not-inc, 97723, Assoc-voc, 11, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 127601, Some-college, 10, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 37, Private, 227597, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, ?, 143995, Some-college, 10, Never-married, ?, Own-child, Black, Male, 0, 0, 20, United-States, <=50K 21, Private, 250051, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 10, United-States, <=50K 26, Private, 284078, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 207668, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 1887, 40, United-States, >50K 18, Private, 163787, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 15, United-States, <=50K 27, Private, 119170, 11th, 7, Never-married, Exec-managerial, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 20, Private, 188612, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 38, Nicaragua, <=50K 36, Private, 114605, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 31, ?, 317761, Bachelors, 13, Never-married, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 164197, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 54, Private, 329266, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 44, United-States, >50K 34, Local-gov, 207383, Masters, 14, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 123598, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 48, United-States, >50K 33, Private, 259931, 11th, 7, Separated, Machine-op-inspct, Other-relative, White, Male, 0, 0, 30, United-States, <=50K 32, Private, 134737, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 50, United-States, >50K 42, Private, 106900, Assoc-voc, 11, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 87054, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 37, Private, 82622, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 181659, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 321205, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 4101, 0, 35, United-States, <=50K 44, Self-emp-not-inc, 231348, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Private, 276096, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 290560, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 21, Private, 307315, Some-college, 10, Never-married, Adm-clerical, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 39, State-gov, 99156, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 24, Private, 237928, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 39, United-States, <=50K 46, Private, 153501, HS-grad, 9, Never-married, Transport-moving, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 47, ?, 149700, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 36, United-States, >50K 47, Private, 189680, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 1977, 40, United-States, >50K 35, Private, 374524, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 75, United-States, >50K 60, Self-emp-not-inc, 127805, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 150217, Bachelors, 13, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 24, Poland, <=50K 33, Private, 295649, HS-grad, 9, Separated, Other-service, Unmarried, White, Female, 0, 0, 40, China, <=50K 21, Private, 197182, Assoc-acdm, 12, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 241998, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 50, United-States, >50K 48, Federal-gov, 156410, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 50, United-States, >50K 58, Private, 473836, 7th-8th, 4, Widowed, Farming-fishing, Other-relative, White, Female, 0, 0, 45, Guatemala, <=50K 21, Private, 198431, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 113936, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 318915, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 28, Self-emp-not-inc, 175406, Masters, 14, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 30, United-States, >50K 33, ?, 193172, Assoc-voc, 11, Married-civ-spouse, ?, Own-child, White, Female, 7688, 0, 50, United-States, >50K 23, Federal-gov, 320294, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 58, State-gov, 400285, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, >50K 24, ?, 283731, Bachelors, 13, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 38, Local-gov, 227154, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 49, Private, 298659, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 15, Mexico, <=50K 47, Private, 212120, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 50, Private, 320510, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 40, United-States, >50K 21, Private, 175800, HS-grad, 9, Never-married, Prof-specialty, Unmarried, White, Female, 0, 0, 55, United-States, <=50K 55, Private, 170169, HS-grad, 9, Separated, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 344157, 11th, 7, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 199441, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 225456, HS-grad, 9, Never-married, Tech-support, Other-relative, White, Male, 0, 0, 50, United-States, <=50K 36, Private, 61178, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Local-gov, 175262, Assoc-acdm, 12, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 2002, 40, England, <=50K 42, Private, 152568, HS-grad, 9, Widowed, Sales, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 41, Private, 182108, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 27828, 0, 35, United-States, >50K 46, Private, 273771, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 99999, 0, 40, United-States, >50K 32, Private, 208291, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 34, Private, 224358, 10th, 6, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 33, Private, 55176, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 60, State-gov, 152711, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 53, Private, 68684, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 185452, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 39, Federal-gov, 175232, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 1977, 60, United-States, >50K 23, Private, 173851, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 162327, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 1902, 50, ?, >50K 36, Local-gov, 51424, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 123416, 12th, 8, Separated, Prof-specialty, Own-child, White, Female, 1055, 0, 40, United-States, <=50K 26, Private, 262656, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 233194, HS-grad, 9, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 40, United-States, >50K 41, Private, 290660, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 7688, 0, 55, United-States, >50K 22, Private, 151105, Some-college, 10, Never-married, Sales, Other-relative, White, Female, 0, 0, 18, United-States, <=50K 38, Private, 179117, Assoc-acdm, 12, Never-married, Machine-op-inspct, Not-in-family, Black, Female, 10520, 0, 50, United-States, >50K 72, ?, 33608, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 9386, 0, 30, United-States, >50K 39, Private, 317434, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, State-gov, 126569, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 40, United-States, >50K 38, Local-gov, 745768, Some-college, 10, Divorced, Exec-managerial, Unmarried, Black, Female, 0, 0, 45, United-States, <=50K 19, Private, 69927, HS-grad, 9, Married-civ-spouse, Other-service, Wife, Black, Female, 0, 0, 16, United-States, <=50K 26, Private, 302603, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 45, United-States, <=50K 52, Private, 46788, Bachelors, 13, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 25, United-States, <=50K 41, Private, 289886, 5th-6th, 3, Married-civ-spouse, Other-service, Husband, Other, Male, 0, 1579, 40, Nicaragua, <=50K 45, Private, 179135, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 58, Federal-gov, 175873, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 34, Private, 57426, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 36, Private, 312206, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Without-pay, 344858, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 20, United-States, <=50K 26, State-gov, 177035, 11th, 7, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 60, Private, 88055, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Self-emp-not-inc, 111095, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 39, Private, 192251, 10th, 6, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 27, Private, 29807, HS-grad, 9, Separated, Handlers-cleaners, Unmarried, White, Female, 0, 0, 40, Japan, <=50K 26, Federal-gov, 211596, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 268276, 12th, 8, Never-married, Other-service, Own-child, White, Male, 0, 0, 12, United-States, <=50K 59, Self-emp-not-inc, 181070, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, England, >50K 53, Local-gov, 20676, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, Amer-Indian-Eskimo, Male, 0, 0, 48, United-States, <=50K 35, Private, 115803, 11th, 7, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, Local-gov, 124827, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 95336, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 45, United-States, >50K 36, Private, 257942, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 72593, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 147340, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 185325, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 59, Self-emp-not-inc, 357943, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 22, Private, 215395, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 1602, 10, United-States, <=50K 50, Local-gov, 30682, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 24, Federal-gov, 29591, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Other, Female, 0, 0, 40, United-States, <=50K 36, Private, 215392, Bachelors, 13, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 110554, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 4386, 0, 40, United-States, >50K 42, Self-emp-not-inc, 133584, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, El-Salvador, <=50K 38, Private, 210438, 7th-8th, 4, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 52, Private, 256916, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 73541, 10th, 6, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 109952, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 54, Private, 197975, 5th-6th, 3, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 51, United-States, <=50K 27, Private, 401723, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 42, Private, 179524, Bachelors, 13, Separated, Other-service, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 33, State-gov, 296282, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 145844, Assoc-acdm, 12, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 59, Private, 191965, 11th, 7, Married-civ-spouse, Other-service, Wife, White, Female, 3908, 0, 28, United-States, <=50K 54, Private, 96792, HS-grad, 9, Widowed, Other-service, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 48, Private, 185041, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1672, 55, United-States, <=50K 19, ?, 233779, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 60, United-States, <=50K 45, Private, 347834, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 215373, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 35, Self-emp-not-inc, 169426, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 202856, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 36, United-States, <=50K 33, Private, 50276, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 48, Self-emp-not-inc, 187454, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 126098, HS-grad, 9, Separated, Craft-repair, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 19, Private, 250639, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 24, United-States, <=50K 64, Self-emp-inc, 195366, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Self-emp-not-inc, 186845, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 8, United-States, <=50K 20, Federal-gov, 119156, HS-grad, 9, Never-married, Adm-clerical, Other-relative, White, Male, 0, 0, 20, United-States, <=50K 28, Private, 162343, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, Puerto-Rico, <=50K 52, Private, 108435, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 50, Greece, >50K 29, Self-emp-not-inc, 394927, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 51, Private, 172281, Bachelors, 13, Separated, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 370767, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 2377, 60, United-States, <=50K 43, Private, 352005, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 45, United-States, >50K 52, Private, 165681, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 258819, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 25, Private, 130793, Some-college, 10, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 36, Private, 118909, Assoc-acdm, 12, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, Jamaica, <=50K 44, Private, 202466, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 60, United-States, <=50K 47, Private, 161558, 10th, 6, Married-spouse-absent, Transport-moving, Not-in-family, Black, Male, 0, 0, 45, United-States, <=50K 32, Private, 188246, HS-grad, 9, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 160120, Masters, 14, Never-married, Prof-specialty, Unmarried, Asian-Pac-Islander, Male, 0, 0, 40, South, <=50K 40, Private, 144594, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 2829, 0, 40, United-States, <=50K 34, Self-emp-not-inc, 123429, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 35, Self-emp-inc, 340110, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 26, Private, 523067, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 3, El-Salvador, <=50K 49, Self-emp-not-inc, 113513, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 63, ?, 186809, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 30, United-States, >50K 46, Self-emp-not-inc, 320421, Bachelors, 13, Married-spouse-absent, Prof-specialty, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 31, Local-gov, 295589, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 22, Private, 370548, Assoc-voc, 11, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 20, Private, 120572, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 12, United-States, <=50K 52, Private, 110977, Doctorate, 16, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 26, Private, 55860, Some-college, 10, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 34, Private, 158800, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 31, Private, 131568, 9th, 5, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 173613, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 22, Private, 216867, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 38, Private, 104089, Assoc-voc, 11, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 208106, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, Ecuador, <=50K 27, State-gov, 340269, Some-college, 10, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 236246, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 213408, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, Cuba, <=50K 40, ?, 84232, HS-grad, 9, Never-married, ?, Not-in-family, White, Female, 0, 0, 4, United-States, <=50K 19, Private, 302945, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 10, Thailand, <=50K 69, ?, 28197, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 60, United-States, >50K 20, Private, 262749, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 35, United-States, <=50K 34, Federal-gov, 198265, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 60, United-States, <=50K 49, Private, 170871, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 27, Private, 177761, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, Other, Male, 0, 0, 50, United-States, <=50K 59, Private, 175689, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 14, Cuba, >50K 45, Private, 205100, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 60, United-States, >50K 21, Private, 77759, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 15, United-States, <=50K 51, State-gov, 77905, Assoc-voc, 11, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 64, ?, 193575, 11th, 7, Never-married, ?, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 41, State-gov, 116520, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 18, ?, 85154, 12th, 8, Never-married, ?, Own-child, Asian-Pac-Islander, Female, 0, 0, 24, Germany, <=50K 49, Private, 180532, Masters, 14, Married-spouse-absent, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 508891, HS-grad, 9, Divorced, Machine-op-inspct, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 20, Private, 211345, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 20, United-States, <=50K 69, Self-emp-not-inc, 170877, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 48, United-States, <=50K 18, ?, 97318, HS-grad, 9, Never-married, ?, Own-child, White, Female, 0, 0, 35, United-States, <=50K 43, Private, 184105, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 50, United-States, <=50K 50, Private, 150941, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 44, United-States, <=50K 32, Private, 303942, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Local-gov, 273929, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 197077, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 62, Private, 162825, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Private, 159869, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 44, United-States, <=50K 19, Private, 158343, Some-college, 10, Never-married, Tech-support, Own-child, White, Female, 0, 0, 40, ?, <=50K 17, ?, 406920, 10th, 6, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 227986, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 137527, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 36, Private, 180150, 12th, 8, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 239539, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 58, Private, 281792, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Private, 224799, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, <=50K 64, Private, 292639, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 10566, 0, 35, United-States, <=50K 66, Private, 22313, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 20, United-States, <=50K 42, Private, 194636, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 156089, Some-college, 10, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 53, Private, 193720, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 40, United-States, >50K 25, Private, 218667, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 358837, Some-college, 10, Never-married, Tech-support, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 20, Private, 174685, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 168854, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 54, United-States, <=50K 28, Private, 133696, Bachelors, 13, Never-married, Sales, Unmarried, White, Male, 0, 0, 65, United-States, <=50K 23, Federal-gov, 350680, Assoc-acdm, 12, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, Poland, <=50K 18, Private, 115215, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 25, United-States, <=50K 43, Self-emp-not-inc, 152958, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 35, United-States, >50K 29, Private, 217200, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 235124, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 46, Dominican-Republic, <=50K 31, Local-gov, 144949, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 60, Private, 135470, 5th-6th, 3, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Mexico, <=50K 42, Private, 281209, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 46, Private, 155489, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 38, Private, 290306, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 18, Private, 182042, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 19, United-States, <=50K 31, Private, 210008, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 54, Private, 234938, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 4064, 0, 55, United-States, <=50K 46, Private, 315423, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 2042, 50, United-States, <=50K 27, Self-emp-not-inc, 30244, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 80, United-States, <=50K 50, Local-gov, 30008, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 38, Self-emp-not-inc, 201328, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 56, United-States, <=50K 36, State-gov, 96468, Masters, 14, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 486332, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 19, Private, 46162, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 25, United-States, <=50K 60, Local-gov, 98350, Some-college, 10, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 60, Philippines, <=50K 45, Local-gov, 175958, 9th, 5, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 119309, Some-college, 10, Never-married, Tech-support, Own-child, White, Male, 0, 1602, 16, United-States, <=50K 42, Private, 175935, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 1980, 46, United-States, <=50K 38, Private, 204527, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 22, ?, 57827, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 418176, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, Black, Male, 0, 0, 32, United-States, <=50K 23, Private, 262744, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 177287, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 30, United-States, <=50K 30, Private, 255004, Assoc-acdm, 12, Divorced, Sales, Not-in-family, White, Male, 0, 0, 52, United-States, <=50K 62, Private, 183735, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Self-emp-not-inc, 318644, Prof-school, 15, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 20, United-States, <=50K 42, Federal-gov, 132125, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 52, United-States, >50K 33, Private, 206051, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Self-emp-inc, 99185, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, ?, >50K 35, Private, 225750, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 33, Private, 245777, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 169092, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 62, Private, 211035, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 30, United-States, >50K 24, Private, 285432, HS-grad, 9, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 50, Local-gov, 154779, Some-college, 10, Divorced, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 54, Private, 37237, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 58, Private, 417419, 7th-8th, 4, Divorced, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 39, Self-emp-inc, 33975, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 32, Private, 42485, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 170017, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 152683, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 3908, 0, 35, United-States, <=50K 20, Private, 41721, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 60, United-States, <=50K 64, Private, 66634, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Self-emp-inc, 257216, Masters, 14, Widowed, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 167882, HS-grad, 9, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 43, United-States, <=50K 45, Private, 179428, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 55, United-States, <=50K 26, Private, 57512, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 301614, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 193820, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 1876, 40, United-States, <=50K 58, Private, 222247, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1887, 40, United-States, >50K 39, Self-emp-inc, 189092, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 47, Private, 217509, HS-grad, 9, Widowed, Priv-house-serv, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 45, Thailand, <=50K 35, Private, 308691, Masters, 14, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, <=50K 38, Private, 169672, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 120914, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 370156, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 28, Private, 398220, 5th-6th, 3, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 44, Self-emp-not-inc, 208277, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 45, United-States, <=50K 40, Private, 337456, HS-grad, 9, Divorced, Protective-serv, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 55, Private, 172666, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Self-emp-not-inc, 32280, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 33, Private, 194901, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 19, ?, 57329, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 30, Japan, <=50K 32, Private, 173730, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 40, United-States, >50K 45, Local-gov, 153312, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 10, United-States, >50K 23, Private, 274797, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 25, United-States, <=50K 31, Private, 359249, Assoc-voc, 11, Never-married, Protective-serv, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 22, Private, 152744, Some-college, 10, Never-married, Other-service, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 59, Private, 188041, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 32, Private, 97723, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 49, State-gov, 354529, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 249727, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 30, United-States, <=50K 26, Private, 189590, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 23, State-gov, 298871, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Vietnam, <=50K 55, Self-emp-not-inc, 205296, Some-college, 10, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 50, United-States, <=50K 47, Private, 303637, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 49, United-States, >50K 44, Private, 242861, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 37599, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 24, United-States, <=50K 40, State-gov, 199381, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 15024, 0, 37, United-States, >50K 32, Self-emp-not-inc, 56328, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 8, United-States, >50K 20, Private, 256211, Some-college, 10, Never-married, Machine-op-inspct, Other-relative, Asian-Pac-Islander, Male, 0, 0, 40, Vietnam, <=50K 84, Local-gov, 163685, HS-grad, 9, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 33, United-States, <=50K 40, Private, 266084, Some-college, 10, Divorced, Craft-repair, Other-relative, White, Male, 0, 0, 50, United-States, <=50K 37, Private, 161111, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 199031, Some-college, 10, Divorced, Transport-moving, Own-child, White, Male, 0, 1380, 40, United-States, <=50K 47, Private, 166634, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, Germany, <=50K 62, Self-emp-not-inc, 204085, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 25, United-States, <=50K 19, ?, 369527, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 464945, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 44, Local-gov, 174684, HS-grad, 9, Divorced, Craft-repair, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 26, Local-gov, 166295, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 41, United-States, <=50K 36, Private, 220511, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 246936, 11th, 7, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 104509, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 48, ?, 266337, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 252168, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 25, Private, 92093, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 20, United-States, <=50K 62, Private, 88055, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 129591, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 142719, HS-grad, 9, Married-spouse-absent, Farming-fishing, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 18, ?, 264924, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 128796, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 44, United-States, >50K 38, Private, 115336, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 70, United-States, <=50K 52, Private, 190333, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 63, Self-emp-not-inc, 179444, 7th-8th, 4, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 15, United-States, <=50K 49, Private, 218676, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 43, United-States, <=50K 17, Local-gov, 148194, 11th, 7, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 12, United-States, <=50K 33, Private, 184833, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 70, Self-emp-not-inc, 280639, HS-grad, 9, Widowed, Other-service, Other-relative, White, Female, 2329, 0, 20, United-States, <=50K 19, Private, 217769, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 27, ?, 180553, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 40, United-States, >50K 61, Private, 56009, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 255334, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 25, United-States, >50K 46, Self-emp-inc, 328216, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 1902, 42, ?, >50K 29, Private, 349154, 10th, 6, Separated, Farming-fishing, Unmarried, White, Female, 0, 0, 40, Guatemala, <=50K 40, Local-gov, 24763, Some-college, 10, Divorced, Transport-moving, Unmarried, White, Male, 6849, 0, 40, United-States, <=50K 43, State-gov, 41834, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 38, United-States, >50K 24, Private, 113466, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 130856, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 61, Self-emp-not-inc, 268797, HS-grad, 9, Married-civ-spouse, Other-service, Wife, Black, Female, 0, 0, 17, United-States, <=50K 48, Private, 202117, 11th, 7, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 34, United-States, <=50K 19, Private, 280146, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, United-States, <=50K 30, Private, 70377, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 236696, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 39, Local-gov, 222572, Masters, 14, Never-married, Prof-specialty, Unmarried, White, Female, 0, 0, 43, United-States, <=50K 46, Self-emp-inc, 110702, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 2036, 0, 60, United-States, <=50K 40, Private, 96129, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 72, United-States, >50K 27, Local-gov, 200492, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 193820, Masters, 14, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 454508, 11th, 7, Never-married, Craft-repair, Not-in-family, White, Male, 0, 2001, 40, United-States, <=50K 58, Private, 220789, Bachelors, 13, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 33, Private, 101345, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 42, Canada, >50K 40, Private, 140559, HS-grad, 9, Widowed, Other-service, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 40, Self-emp-inc, 64885, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 70, United-States, >50K 31, Private, 402361, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 143582, HS-grad, 9, Separated, Other-service, Unmarried, Asian-Pac-Islander, Female, 0, 0, 48, China, <=50K 49, Private, 185385, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 24, Private, 112706, Assoc-voc, 11, Never-married, Tech-support, Own-child, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 130364, HS-grad, 9, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 58, Local-gov, 147428, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Private, 205895, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 65, ?, 273569, HS-grad, 9, Widowed, ?, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 153160, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 48, Self-emp-not-inc, 167918, Masters, 14, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 0, 50, India, <=50K 41, Private, 195661, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 54, United-States, <=50K 27, State-gov, 146243, Some-college, 10, Separated, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 52, ?, 105428, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 12, United-States, <=50K 26, Private, 149943, HS-grad, 9, Never-married, Other-service, Other-relative, Asian-Pac-Islander, Male, 0, 0, 60, ?, <=50K 52, Local-gov, 246197, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Local-gov, 192563, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 19, Private, 244115, HS-grad, 9, Never-married, Other-service, Own-child, Black, Male, 0, 0, 30, United-States, <=50K 39, Local-gov, 98587, Some-college, 10, Divorced, Prof-specialty, Own-child, White, Female, 0, 0, 45, United-States, <=50K 47, Private, 145886, Some-college, 10, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 244315, HS-grad, 9, Divorced, Craft-repair, Other-relative, Other, Male, 0, 0, 40, United-States, <=50K 48, Private, 192779, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 209464, HS-grad, 9, Separated, Other-service, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 60, Private, 25141, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 28, Private, 405793, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 45, United-States, >50K 47, Federal-gov, 53498, HS-grad, 9, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 69, ?, 476653, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 20, United-States, <=50K 40, Self-emp-not-inc, 162312, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 66, South, <=50K 37, Private, 277022, HS-grad, 9, Never-married, Handlers-cleaners, Unmarried, White, Female, 3887, 0, 40, Nicaragua, <=50K 41, State-gov, 109762, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 123031, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 0, 48, Trinadad&Tobago, <=50K 46, Federal-gov, 119890, Assoc-voc, 11, Separated, Tech-support, Not-in-family, Other, Female, 0, 0, 30, United-States, <=50K 21, Self-emp-not-inc, 409230, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 30, United-States, <=50K 44, Private, 223308, Masters, 14, Separated, Sales, Unmarried, White, Female, 0, 0, 48, United-States, <=50K 38, ?, 129150, 10th, 6, Separated, ?, Own-child, White, Male, 0, 0, 35, United-States, <=50K 47, Self-emp-not-inc, 119199, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 35, United-States, >50K 42, Private, 46221, Doctorate, 16, Married-spouse-absent, Other-service, Not-in-family, White, Male, 27828, 0, 60, ?, >50K 42, Local-gov, 351161, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 56, Private, 174533, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, >50K 32, Private, 324386, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 126568, Bachelors, 13, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 33, United-States, <=50K 26, Private, 275703, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Self-emp-not-inc, 219611, Bachelors, 13, Never-married, Sales, Not-in-family, Black, Female, 2174, 0, 50, United-States, <=50K 49, Private, 200471, 11th, 7, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 65, Private, 155261, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 73, State-gov, 74040, 7th-8th, 4, Divorced, Other-service, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 34, Private, 226296, 11th, 7, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 211968, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 49, Local-gov, 126446, Some-college, 10, Never-married, Other-service, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 25, Private, 262885, 11th, 7, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 32, United-States, <=50K 39, Private, 188069, 9th, 5, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 25, United-States, <=50K 19, Private, 113546, 11th, 7, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 56, United-States, <=50K 24, Private, 227070, 10th, 6, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 136997, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 35, ?, 119006, HS-grad, 9, Widowed, ?, Own-child, White, Female, 0, 0, 38, United-States, <=50K 21, Private, 212407, HS-grad, 9, Never-married, Machine-op-inspct, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 197810, Masters, 14, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 35, Federal-gov, 35309, Bachelors, 13, Never-married, Tech-support, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 28, ?, <=50K 39, Private, 141802, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 48, ?, 184513, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 80, United-States, >50K 33, Self-emp-not-inc, 124187, Assoc-acdm, 12, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 32, United-States, <=50K 19, Private, 201743, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 26, United-States, <=50K 17, Private, 156736, 10th, 6, Never-married, Sales, Unmarried, White, Female, 0, 0, 12, United-States, <=50K 43, Self-emp-not-inc, 47261, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 62, Private, 150693, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 42, United-States, <=50K 53, Local-gov, 233734, Masters, 14, Divorced, Prof-specialty, Not-in-family, Black, Female, 0, 0, 40, United-States, >50K 45, State-gov, 35969, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 47, Private, 159550, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 30, Private, 190823, Some-college, 10, Never-married, Other-service, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 53, Private, 213378, HS-grad, 9, Separated, Sales, Not-in-family, White, Female, 0, 0, 33, United-States, <=50K 24, Private, 257500, HS-grad, 9, Separated, Machine-op-inspct, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 41, Local-gov, 488706, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, Local-gov, 239405, 5th-6th, 3, Divorced, Other-service, Other-relative, Black, Female, 0, 0, 40, Haiti, <=50K 27, Federal-gov, 105189, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Male, 4865, 0, 50, United-States, <=50K 63, State-gov, 109735, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 50, Private, 172942, Some-college, 10, Divorced, Other-service, Own-child, White, Male, 0, 0, 28, United-States, <=50K 43, Local-gov, 209899, Masters, 14, Never-married, Tech-support, Not-in-family, Black, Female, 8614, 0, 47, United-States, >50K 29, Self-emp-inc, 87745, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 41, Private, 187881, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 3942, 0, 40, United-States, <=50K 55, Private, 234125, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 272944, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 23, Local-gov, 129232, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 100345, Bachelors, 13, Never-married, Craft-repair, Not-in-family, White, Male, 13550, 0, 55, United-States, >50K 58, Self-emp-not-inc, 195835, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 25, Private, 251854, 11th, 7, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 40, Private, 103474, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 30, United-States, <=50K 38, Private, 22042, Assoc-voc, 11, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 39, United-States, <=50K 37, Private, 343721, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 19, Private, 232368, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 35, United-States, <=50K 55, Private, 174478, 10th, 6, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 29, United-States, <=50K 55, Private, 282023, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 50, United-States, >50K 28, Private, 274690, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 53, Private, 251675, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, El-Salvador, <=50K 32, ?, 647882, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, ?, <=50K 60, Private, 128367, Some-college, 10, Divorced, Prof-specialty, Unmarried, White, Male, 3325, 0, 42, United-States, <=50K 32, Private, 37380, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 34, Private, 173730, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 49, Private, 353824, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 21, Private, 225890, Some-college, 10, Never-married, Other-service, Other-relative, White, Female, 0, 0, 30, United-States, <=50K 24, State-gov, 147147, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 20, United-States, <=50K 53, Private, 233780, Assoc-voc, 11, Divorced, Adm-clerical, Not-in-family, Black, Female, 2202, 0, 40, United-States, <=50K 29, Private, 394927, Assoc-voc, 11, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, ?, <=50K 34, Local-gov, 188682, Bachelors, 13, Married-spouse-absent, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 52, ?, 115209, Prof-school, 15, Married-spouse-absent, ?, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, Vietnam, <=50K 41, Private, 277192, 5th-6th, 3, Married-civ-spouse, Farming-fishing, Wife, White, Female, 0, 0, 40, Mexico, <=50K 21, Private, 314182, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 220776, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 35, United-States, >50K 31, Local-gov, 189269, HS-grad, 9, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 35429, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 2042, 40, United-States, <=50K 42, Private, 154374, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 2415, 60, United-States, >50K 62, Private, 161460, Bachelors, 13, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 51, Private, 251487, 7th-8th, 4, Widowed, Machine-op-inspct, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 30, Private, 177531, HS-grad, 9, Never-married, Sales, Unmarried, Black, Female, 0, 0, 25, United-States, <=50K 24, Private, 53942, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 113481, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 361324, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 330087, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 33, Private, 276221, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 121055, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 62, Private, 118696, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 64, Self-emp-not-inc, 289741, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 20, United-States, <=50K 18, Private, 238401, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 25, United-States, <=50K 43, Private, 262038, 5th-6th, 3, Married-spouse-absent, Farming-fishing, Unmarried, White, Male, 0, 0, 35, Mexico, <=50K 62, Self-emp-not-inc, 26911, 7th-8th, 4, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 66, United-States, <=50K 29, Private, 161155, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 43, Private, 252519, Bachelors, 13, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, Haiti, >50K 39, Private, 43712, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 40, United-States, >50K 69, ?, 167826, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 188900, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 120057, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 4386, 0, 45, United-States, >50K 25, Private, 134113, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 47, Local-gov, 165822, Some-college, 10, Divorced, Transport-moving, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 99161, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 8, United-States, <=50K 41, Local-gov, 74581, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Male, 0, 0, 65, United-States, <=50K 19, Private, 304643, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 20, United-States, <=50K 57, Private, 121821, 1st-4th, 2, Married-civ-spouse, Other-service, Husband, Other, Male, 0, 0, 40, Dominican-Republic, <=50K 25, Private, 154863, HS-grad, 9, Never-married, Adm-clerical, Unmarried, Black, Male, 0, 0, 35, United-States, <=50K 37, Local-gov, 365430, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, Canada, >50K 29, Private, 183111, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 50178, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 35, United-States, <=50K 35, Private, 186845, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 52, Private, 159908, 12th, 8, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 162189, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Female, 1831, 0, 40, Peru, <=50K 29, Private, 128509, HS-grad, 9, Married-spouse-absent, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 38, El-Salvador, <=50K 23, Private, 143032, Masters, 14, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 36, United-States, <=50K 31, Private, 382368, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 210013, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 19, Private, 293928, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 21, Private, 208503, Some-college, 10, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 10, United-States, <=50K 37, State-gov, 191841, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 8614, 0, 40, United-States, >50K 49, Self-emp-not-inc, 355978, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 35, United-States, >50K 64, Local-gov, 202738, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 35, United-States, <=50K 37, Local-gov, 144322, Assoc-voc, 11, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 43, United-States, <=50K 70, Self-emp-not-inc, 155141, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 2377, 12, United-States, >50K 22, Private, 160120, 10th, 6, Never-married, Transport-moving, Own-child, Asian-Pac-Islander, Male, 0, 0, 30, United-States, <=50K 29, Self-emp-inc, 190450, HS-grad, 9, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Germany, <=50K 37, Private, 212900, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 115677, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 252250, 11th, 7, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 27, Private, 212041, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 58, State-gov, 198145, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 35, United-States, >50K 60, Local-gov, 113658, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 35, United-States, <=50K 20, Private, 32426, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 51, Private, 98791, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Private, 203828, 9th, 5, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 65, United-States, <=50K 22, State-gov, 186634, 12th, 8, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 56, Self-emp-not-inc, 125147, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 26, Private, 247455, Bachelors, 13, Married-civ-spouse, Sales, Wife, White, Female, 5178, 0, 42, United-States, >50K 19, Private, 97215, Some-college, 10, Separated, Sales, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 37, Private, 330826, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 30, United-States, <=50K 27, Private, 200802, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 156266, HS-grad, 9, Never-married, Sales, Own-child, Amer-Indian-Eskimo, Male, 0, 0, 20, United-States, <=50K 52, Self-emp-not-inc, 72257, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 45, Private, 363087, HS-grad, 9, Separated, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 28, Private, 25955, Some-college, 10, Never-married, Craft-repair, Own-child, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 20, Private, 334633, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 109162, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 44, Private, 569761, Assoc-voc, 11, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, United-States, <=50K 30, Private, 209900, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, State-gov, 272986, Assoc-acdm, 12, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 8, United-States, <=50K 55, ?, 52267, Masters, 14, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 18, United-States, <=50K 46, Private, 82946, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 104651, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 25, Local-gov, 58441, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Local-gov, 269733, HS-grad, 9, Separated, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 19, ?, 128453, HS-grad, 9, Never-married, ?, Own-child, White, Female, 0, 0, 28, United-States, <=50K 36, Private, 179468, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 183081, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 102938, Bachelors, 13, Never-married, Other-service, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, Vietnam, <=50K 30, ?, 157289, 11th, 7, Never-married, ?, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 359828, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 44, United-States, >50K 30, Private, 155659, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 36, United-States, <=50K 24, Private, 585203, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 7688, 0, 45, United-States, >50K 62, Private, 173601, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Self-emp-not-inc, 214541, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 1590, 40, United-States, <=50K 49, Self-emp-not-inc, 163352, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 85, United-States, >50K 36, Self-emp-not-inc, 153976, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 47, Local-gov, 247676, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 5455, 0, 45, United-States, <=50K 49, State-gov, 155372, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 52, Private, 329733, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 162576, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 176520, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 53, United-States, <=50K 51, State-gov, 226885, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 120781, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 30, Private, 375827, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 205504, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 28, Private, 198813, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 48, Self-emp-inc, 254291, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 50, United-States, >50K 62, Private, 159908, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 38, United-States, >50K 49, Private, 40000, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 4064, 0, 44, United-States, <=50K 69, Private, 102874, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 24, United-States, <=50K 35, Private, 117381, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 8614, 0, 45, United-States, >50K 78, Private, 180239, Masters, 14, Widowed, Craft-repair, Unmarried, Asian-Pac-Islander, Male, 0, 0, 40, South, <=50K 61, Private, 539563, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 24, Private, 261561, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 81057, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 36, Self-emp-not-inc, 160120, Bachelors, 13, Married-civ-spouse, Sales, Husband, Other, Male, 0, 0, 45, ?, <=50K 17, Private, 41979, 10th, 6, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 275110, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 80, United-States, >50K 64, Private, 265661, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Self-emp-not-inc, 193246, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 55, France, <=50K 32, Private, 236543, 12th, 8, Married-civ-spouse, Craft-repair, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 19, Private, 29510, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 42, State-gov, 105804, 11th, 7, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 194604, Bachelors, 13, Never-married, Sales, Own-child, White, Female, 0, 0, 15, United-States, <=50K 23, Private, 1038553, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, Black, Male, 0, 0, 45, United-States, <=50K 51, Local-gov, 209320, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Male, 3325, 0, 40, United-States, <=50K 31, Private, 193231, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 3325, 0, 60, United-States, <=50K 44, Private, 307468, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 29, United-States, >50K 38, Private, 255941, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 10520, 0, 50, United-States, >50K 44, Local-gov, 107845, Assoc-acdm, 12, Divorced, Protective-serv, Not-in-family, White, Female, 0, 0, 56, United-States, >50K 44, Self-emp-not-inc, 567788, 5th-6th, 3, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, Mexico, <=50K 38, Private, 91857, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 44, United-States, <=50K 36, Private, 732569, 9th, 5, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 86613, 1st-4th, 2, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 20, El-Salvador, <=50K 46, Private, 35961, Assoc-acdm, 12, Divorced, Sales, Not-in-family, White, Female, 0, 0, 25, Germany, <=50K 47, Private, 114754, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 235124, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 99999, 0, 40, United-States, >50K 37, Local-gov, 218490, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 7688, 0, 35, United-States, >50K 27, Private, 329426, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 43, Private, 181015, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 44, Self-emp-not-inc, 264740, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 381153, Some-college, 10, Never-married, Exec-managerial, Unmarried, White, Male, 0, 0, 60, United-States, <=50K 34, Private, 189759, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 45, United-States, >50K 39, Private, 230467, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 1092, 40, Germany, <=50K 36, Private, 218542, Some-college, 10, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 57, Private, 298507, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 3103, 0, 40, United-States, >50K 78, Private, 111189, 7th-8th, 4, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 35, Dominican-Republic, <=50K 24, Private, 168997, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 168894, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 149809, Assoc-acdm, 12, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 344073, HS-grad, 9, Separated, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 22, Private, 416165, Some-college, 10, Never-married, Sales, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 36, Private, 41490, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 61, Private, 40269, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 67, ?, 243256, 9th, 5, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 15, United-States, <=50K 42, Private, 250536, Some-college, 10, Separated, Other-service, Unmarried, Black, Female, 0, 0, 21, Haiti, <=50K 49, Federal-gov, 105586, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, >50K 58, Private, 51499, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Local-gov, 189878, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 60, United-States, <=50K 39, Private, 179481, HS-grad, 9, Never-married, Tech-support, Not-in-family, White, Male, 4650, 0, 44, United-States, <=50K 25, Private, 299765, Some-college, 10, Separated, Adm-clerical, Other-relative, Black, Female, 0, 0, 40, Jamaica, <=50K 45, Self-emp-inc, 155664, 5th-6th, 3, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, ?, >50K 30, Private, 54608, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, ?, 174702, Some-college, 10, Never-married, ?, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 36, Self-emp-not-inc, 285020, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 2885, 0, 40, United-States, <=50K 23, Private, 201145, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 51, Private, 125796, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 0, 35, Jamaica, <=50K 55, Private, 249072, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 35, Private, 99156, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 45, State-gov, 94754, Masters, 14, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, India, <=50K 36, Private, 111128, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 48, United-States, >50K 32, Local-gov, 157887, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 74194, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, <=50K 47, Self-emp-inc, 168191, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 28334, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 52, Private, 84278, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 55, ?, >50K 44, Private, 721161, Some-college, 10, Separated, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 36, Private, 188069, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 40, Private, 145178, Some-college, 10, Divorced, Craft-repair, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 17, Private, 52967, 10th, 6, Never-married, Other-service, Own-child, White, Female, 0, 0, 6, United-States, <=50K 18, Private, 177578, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 38, United-States, <=50K 30, Self-emp-inc, 185384, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 25, United-States, <=50K 66, Private, 66008, HS-grad, 9, Widowed, Priv-house-serv, Not-in-family, White, Female, 0, 0, 50, England, <=50K 59, Private, 329059, Bachelors, 13, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 30, Local-gov, 348802, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, <=50K 50, Private, 34233, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 24, Private, 509629, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 28, Private, 27956, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 99, Philippines, <=50K 44, Local-gov, 83286, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 25, Private, 309098, Assoc-voc, 11, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 188950, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 20, Private, 224217, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 67, Private, 222899, Assoc-voc, 11, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 40, Self-emp-not-inc, 123306, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 52, Federal-gov, 279337, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 347166, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 37, Local-gov, 251396, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, Canada, >50K 17, Self-emp-inc, 143034, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 4, United-States, <=50K 25, Private, 57635, Assoc-voc, 11, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 42, United-States, >50K 35, Local-gov, 162651, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, Puerto-Rico, <=50K 63, Private, 28334, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 38, Local-gov, 84570, Some-college, 10, Never-married, Adm-clerical, Own-child, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 33, Private, 181091, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 60, Iran, >50K 51, Local-gov, 117496, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 64, State-gov, 216160, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, Columbia, >50K 50, Self-emp-inc, 204447, Some-college, 10, Divorced, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 374969, 10th, 6, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 56, United-States, <=50K 67, Private, 35015, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 99, United-States, <=50K 46, Private, 179869, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 60, Self-emp-not-inc, 137733, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 29, Private, 193125, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 103649, Some-college, 10, Never-married, Other-service, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 56, State-gov, 54260, Doctorate, 16, Married-civ-spouse, Prof-specialty, Not-in-family, Asian-Pac-Islander, Male, 2885, 0, 40, China, <=50K 29, Private, 197932, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Wife, White, Female, 0, 0, 40, Mexico, >50K 37, Private, 249720, Bachelors, 13, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 27, United-States, <=50K 55, Private, 223613, 1st-4th, 2, Divorced, Priv-house-serv, Unmarried, White, Female, 0, 0, 30, Cuba, <=50K 24, Private, 259865, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 21, Private, 301694, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 35, Mexico, <=50K 46, Self-emp-inc, 276934, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 70, United-States, >50K 25, Private, 395512, 12th, 8, Married-civ-spouse, Machine-op-inspct, Other-relative, Other, Male, 0, 0, 40, Mexico, <=50K 40, Private, 168071, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 28, United-States, <=50K 23, Private, 45317, Some-college, 10, Separated, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 43, Self-emp-not-inc, 311177, Some-college, 10, Never-married, Transport-moving, Not-in-family, Black, Male, 0, 0, 30, United-States, <=50K 29, Self-emp-not-inc, 190636, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Amer-Indian-Eskimo, Male, 0, 1485, 60, United-States, >50K 59, Private, 221336, 10th, 6, Widowed, Other-service, Other-relative, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 18, Private, 120691, Some-college, 10, Never-married, Other-service, Own-child, Black, Male, 0, 0, 35, ?, <=50K 28, Private, 107389, HS-grad, 9, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 32, United-States, <=50K 17, Private, 293440, 11th, 7, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 15, United-States, <=50K 53, Private, 145409, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 22, Private, 213902, 5th-6th, 3, Never-married, Priv-house-serv, Other-relative, White, Female, 0, 0, 40, El-Salvador, <=50K 63, Private, 100099, HS-grad, 9, Married-spouse-absent, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 191856, Masters, 14, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 45, United-States, >50K 40, Local-gov, 233891, HS-grad, 9, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 61, Self-emp-not-inc, 96073, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, England, >50K 35, Private, 474136, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 1408, 40, United-States, <=50K 43, Self-emp-not-inc, 355856, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 50, Philippines, <=50K 20, ?, 144685, Some-college, 10, Never-married, ?, Own-child, Asian-Pac-Islander, Female, 0, 1602, 40, Taiwan, <=50K 48, Self-emp-not-inc, 139212, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 56, State-gov, 143931, Bachelors, 13, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 51, Federal-gov, 160703, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 191291, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 68729, Some-college, 10, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 1902, 40, United-States, >50K 61, Private, 119986, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, ?, >50K 37, Private, 227545, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 44, United-States, >50K 36, Private, 32776, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 40, United-States, >50K 34, Private, 228881, Some-college, 10, Separated, Machine-op-inspct, Not-in-family, Other, Male, 0, 0, 40, United-States, <=50K 23, Private, 84648, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 25, United-States, <=50K 63, Federal-gov, 101996, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 63, ?, 68954, HS-grad, 9, Widowed, ?, Not-in-family, Black, Female, 0, 0, 11, United-States, <=50K 47, Local-gov, 285060, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 41, United-States, >50K 55, Self-emp-inc, 209569, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 50, United-States, >50K 31, Local-gov, 331126, Bachelors, 13, Never-married, Protective-serv, Own-child, Black, Male, 0, 0, 48, United-States, <=50K 27, Private, 279872, Some-college, 10, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 58, Private, 150560, Bachelors, 13, Divorced, Adm-clerical, Not-in-family, White, Female, 14084, 0, 40, United-States, >50K 28, Local-gov, 185647, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 48, United-States, <=50K 52, Private, 128871, 7th-8th, 4, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 64, United-States, <=50K 31, Federal-gov, 386331, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 50, United-States, <=50K 53, Private, 117814, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 43, Private, 220609, Some-college, 10, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 43, Local-gov, 117022, HS-grad, 9, Married-spouse-absent, Farming-fishing, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 50, Self-emp-inc, 176751, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 80, United-States, >50K 68, ?, 76371, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 35, United-States, <=50K 37, Private, 80410, 11th, 7, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 127202, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 121471, 11th, 7, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 219086, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, <=50K 59, Private, 271571, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 15024, 0, 50, United-States, >50K 30, Private, 241583, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 374253, HS-grad, 9, Separated, Other-service, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 30, Private, 214993, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Local-gov, 199995, Bachelors, 13, Divorced, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 38, Private, 450924, 12th, 8, Married-civ-spouse, Other-service, Husband, White, Male, 3942, 0, 40, United-States, <=50K 29, Private, 120359, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 76, Private, 93125, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 1424, 0, 24, United-States, <=50K 21, Private, 187513, Assoc-voc, 11, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 65, Private, 243569, Some-college, 10, Widowed, Other-service, Unmarried, White, Female, 0, 0, 24, United-States, <=50K 43, Private, 295510, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 29, Private, 29732, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 24, United-States, <=50K 32, Private, 211743, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 37, Private, 251396, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 65, United-States, >50K 64, Private, 477697, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 16, United-States, <=50K 49, Private, 151584, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 44, Private, 193882, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 68, ?, 117542, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 1409, 0, 15, United-States, <=50K 34, Private, 242460, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 40, United-States, >50K 35, Private, 411395, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 36, United-States, <=50K 53, Private, 191025, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 43, United-States, <=50K 24, Private, 154571, Assoc-voc, 11, Never-married, Sales, Unmarried, Asian-Pac-Islander, Male, 0, 0, 50, South, <=50K 31, Private, 208657, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 29599, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 38, United-States, <=50K 36, Private, 423711, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, <=50K 29, Private, 122000, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 37, Private, 148581, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 42, Self-emp-not-inc, 222978, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 30, Private, 149118, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 32, Self-emp-inc, 218407, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 70, Cuba, <=50K 47, Self-emp-not-inc, 112200, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, Black, Male, 10520, 0, 45, United-States, >50K 44, Private, 85604, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 19, Private, 111232, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 99199, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 48, United-States, <=50K 51, Private, 199995, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 69, Private, 122850, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 16, United-States, <=50K 73, ?, 90557, 11th, 7, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 8, United-States, <=50K 18, ?, 271935, 11th, 7, Never-married, ?, Other-relative, White, Female, 0, 0, 20, United-States, <=50K 33, Self-emp-not-inc, 361497, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 22, Local-gov, 399020, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 33, Private, 345277, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 45, United-States, >50K 20, Federal-gov, 55233, Some-college, 10, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 28, Self-emp-not-inc, 200515, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 188119, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 176683, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 22, Private, 309178, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 67, Self-emp-not-inc, 40021, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 35, United-States, <=50K 31, Self-emp-inc, 49923, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, ?, 36635, Some-college, 10, Never-married, ?, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 43, Federal-gov, 325706, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 50, India, >50K 33, Private, 124407, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 37, Self-emp-not-inc, 301568, HS-grad, 9, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 35, United-States, >50K 27, Private, 339956, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 60, United-States, <=50K 36, Private, 176335, Some-college, 10, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 198452, Assoc-acdm, 12, Divorced, Sales, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 63, Private, 213945, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 40, Iran, >50K 48, Private, 171807, Bachelors, 13, Divorced, Other-service, Unmarried, White, Female, 0, 0, 56, United-States, >50K 25, Private, 362826, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 45, United-States, <=50K 41, Self-emp-not-inc, 344329, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 10, United-States, <=50K 26, Private, 137678, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 175424, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 33, State-gov, 73296, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 1831, 0, 40, United-States, <=50K 30, State-gov, 137613, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 17, Taiwan, <=50K 67, Self-emp-not-inc, 354405, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 32, Private, 130057, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, >50K 48, Self-emp-not-inc, 362883, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 51, Private, 49017, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 24, United-States, <=50K 39, Private, 149943, Masters, 14, Never-married, Sales, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, China, <=50K 40, Self-emp-inc, 99185, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 40, Private, 294708, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, >50K 19, Private, 228238, HS-grad, 9, Never-married, Machine-op-inspct, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 28, Private, 156819, HS-grad, 9, Divorced, Handlers-cleaners, Unmarried, White, Female, 0, 0, 36, United-States, <=50K 47, Private, 332727, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 20, Private, 289944, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 41, Private, 116103, HS-grad, 9, Widowed, Exec-managerial, Other-relative, White, Male, 914, 0, 40, United-States, <=50K 29, Private, 24153, Some-college, 10, Married-civ-spouse, Other-service, Wife, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 40, Private, 273425, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 61, Private, 231183, HS-grad, 9, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 313930, 11th, 7, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 26, Private, 114483, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 162108, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 17, Private, 168807, 7th-8th, 4, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 43, Local-gov, 143828, Masters, 14, Divorced, Prof-specialty, Unmarried, Black, Female, 9562, 0, 40, United-States, >50K 73, Private, 242769, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 3471, 0, 40, England, <=50K 46, Local-gov, 111558, Some-college, 10, Divorced, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 69770, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 37, Private, 291981, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 102460, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 151584, HS-grad, 9, Divorced, Sales, Own-child, White, Male, 0, 1876, 40, United-States, <=50K 47, Local-gov, 287320, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 115677, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 239632, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 409172, Bachelors, 13, Married-civ-spouse, Exec-managerial, Own-child, White, Male, 0, 0, 55, United-States, <=50K 20, Private, 186849, HS-grad, 9, Never-married, Transport-moving, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 118861, 10th, 6, Married-civ-spouse, Craft-repair, Wife, Other, Female, 0, 0, 48, Guatemala, <=50K 26, Private, 142689, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, ?, <=50K 41, State-gov, 170924, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 67, ?, 274451, 7th-8th, 4, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 153489, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 35, Private, 186489, 9th, 5, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 46, United-States, <=50K 18, Private, 192409, 12th, 8, Never-married, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 55, State-gov, 337599, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 195545, HS-grad, 9, Divorced, Machine-op-inspct, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 64, Private, 61892, HS-grad, 9, Widowed, Priv-house-serv, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 34, Self-emp-not-inc, 175697, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 75, United-States, <=50K 38, Private, 80303, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 25, Private, 419658, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 8, United-States, <=50K 21, Private, 319163, Some-college, 10, Never-married, Transport-moving, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 37, Private, 126743, 1st-4th, 2, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 53, Mexico, <=50K 39, Private, 301568, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 120461, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 23, Private, 268145, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 54, Private, 257337, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 49, Self-emp-inc, 213354, Masters, 14, Separated, Exec-managerial, Not-in-family, White, Male, 0, 0, 70, United-States, >50K 25, Private, 303431, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 124963, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 29, Private, 158218, HS-grad, 9, Never-married, Farming-fishing, Unmarried, White, Male, 0, 0, 35, United-States, <=50K 27, State-gov, 553473, Bachelors, 13, Married-civ-spouse, Protective-serv, Wife, Black, Female, 0, 0, 48, United-States, <=50K 53, Private, 46155, HS-grad, 9, Married-civ-spouse, Priv-house-serv, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 68, Private, 138714, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 56, Private, 231781, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Private, 496414, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, ?, <=50K 24, Private, 19410, HS-grad, 9, Divorced, Sales, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 48, United-States, <=50K 70, ?, 28471, 9th, 5, Widowed, ?, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 24, Private, 185821, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 74, ?, 272667, Assoc-acdm, 12, Widowed, ?, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 23, ?, 194031, Some-college, 10, Never-married, ?, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 41, Local-gov, 144995, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, <=50K 45, Private, 162494, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 19, United-States, <=50K 35, Private, 171968, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 232569, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 161819, 11th, 7, Separated, Adm-clerical, Unmarried, Black, Female, 0, 0, 25, United-States, <=50K 18, Private, 123343, 11th, 7, Never-married, Sales, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 49, Private, 105449, Bachelors, 13, Never-married, Priv-house-serv, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 49, Private, 181717, Assoc-voc, 11, Separated, Prof-specialty, Own-child, White, Female, 0, 0, 36, United-States, <=50K 45, Local-gov, 102359, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 37, United-States, <=50K 27, Private, 72887, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 28, Private, 154571, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 35, Private, 255191, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 33, Private, 174789, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 110402, 11th, 7, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 35, United-States, <=50K 19, Private, 208513, HS-grad, 9, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 121904, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 28, United-States, <=50K 28, Private, 34335, HS-grad, 9, Divorced, Sales, Not-in-family, Amer-Indian-Eskimo, Male, 14084, 0, 40, United-States, >50K 49, Private, 59380, Some-college, 10, Married-spouse-absent, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 61, ?, 135285, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 2603, 32, United-States, <=50K 39, Self-emp-inc, 126675, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 25, United-States, <=50K 22, Private, 217363, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 91836, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 184813, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 178142, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 49, Local-gov, 102359, 9th, 5, Widowed, Handlers-cleaners, Unmarried, White, Male, 0, 2231, 40, United-States, >50K 33, Self-emp-inc, 281832, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, Cuba, >50K 28, Private, 96226, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 42, Private, 195124, 7th-8th, 4, Married-spouse-absent, Prof-specialty, Other-relative, White, Male, 0, 0, 35, Puerto-Rico, <=50K 20, Private, 56322, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 2176, 0, 25, United-States, <=50K 50, Local-gov, 97449, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 48, United-States, <=50K 32, Private, 339773, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Federal-gov, 210926, HS-grad, 9, Separated, Handlers-cleaners, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 199499, Assoc-voc, 11, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 46, Federal-gov, 190729, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Self-emp-inc, 191385, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 77, United-States, <=50K 61, Private, 193479, HS-grad, 9, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 24, United-States, <=50K 43, Self-emp-not-inc, 225165, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, <=50K 35, Private, 346766, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 39, State-gov, 152307, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, ?, 79990, 11th, 7, Never-married, ?, Own-child, White, Male, 0, 0, 35, United-States, <=50K 42, Self-emp-not-inc, 170649, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 23, Private, 197207, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 229732, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 52, Private, 204402, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 85, United-States, >50K 36, Private, 181065, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 179579, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, ?, >50K 50, Private, 237729, HS-grad, 9, Widowed, Sales, Not-in-family, White, Female, 0, 2444, 72, United-States, >50K 23, ?, 164574, Assoc-acdm, 12, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 71, Private, 179574, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 12, United-States, >50K 27, Private, 191782, HS-grad, 9, Never-married, Other-service, Other-relative, Black, Female, 0, 0, 30, United-States, <=50K 56, Private, 146660, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 28, Self-emp-not-inc, 115945, Some-college, 10, Never-married, Prof-specialty, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 210875, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 137898, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, United-States, <=50K 28, Local-gov, 216965, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 201554, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 62, Private, 57970, 7th-8th, 4, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 208378, 12th, 8, Separated, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 61343, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 60, United-States, <=50K 24, Private, 283872, Some-college, 10, Never-married, Adm-clerical, Not-in-family, Black, Male, 0, 0, 20, United-States, <=50K 58, Private, 225603, 9th, 5, Divorced, Farming-fishing, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 48, Private, 401333, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 278228, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 31, Private, 145377, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 25, Private, 120238, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 187215, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 15024, 0, 36, United-States, >50K 29, Self-emp-not-inc, 144063, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 72, United-States, <=50K 38, Private, 238721, Assoc-acdm, 12, Divorced, Exec-managerial, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 21, Private, 164920, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 34, Self-emp-not-inc, 152493, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 70, United-States, <=50K 50, Private, 92968, Bachelors, 13, Never-married, Sales, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 50, Private, 136836, HS-grad, 9, Divorced, Prof-specialty, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 49, Federal-gov, 216453, Assoc-voc, 11, Divorced, Exec-managerial, Unmarried, Black, Female, 0, 0, 45, United-States, <=50K 30, Private, 349148, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 29, State-gov, 309620, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 20, Taiwan, <=50K 22, State-gov, 347803, Some-college, 10, Never-married, Adm-clerical, Not-in-family, Other, Male, 0, 0, 20, United-States, <=50K 42, Private, 85995, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 19, ?, 167428, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 164569, Some-college, 10, Divorced, Other-service, Unmarried, White, Female, 0, 0, 48, United-States, <=50K 42, Self-emp-not-inc, 308279, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 21, United-States, <=50K 20, Private, 56322, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 51, ?, 203015, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 211654, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Self-emp-inc, 120126, 9th, 5, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 239043, 11th, 7, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 61, ?, 179761, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Private, 312017, Some-college, 10, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 40, Germany, <=50K 51, Private, 257485, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 52, Private, 49243, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 229716, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 31, Private, 341672, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 0, 60, India, <=50K 24, Private, 32311, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, <=50K 56, Private, 275236, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, ?, 400356, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 184596, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 3942, 0, 50, United-States, <=50K 18, Private, 186909, HS-grad, 9, Never-married, Sales, Other-relative, White, Female, 1055, 0, 30, United-States, <=50K 43, Private, 152420, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 50, United-States, <=50K 43, State-gov, 261929, Doctorate, 16, Married-spouse-absent, Prof-specialty, Unmarried, White, Male, 25236, 0, 64, United-States, >50K 21, Private, 235442, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 161691, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 20, ?, 173945, 11th, 7, Married-civ-spouse, ?, Other-relative, White, Female, 0, 0, 39, United-States, <=50K 41, Private, 355918, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 65, United-States, >50K 45, State-gov, 198660, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Private, 122649, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 28, Private, 421967, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 60, United-States, >50K 50, Local-gov, 259377, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 15024, 0, 40, United-States, >50K 47, Private, 74305, Bachelors, 13, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 80, Self-emp-not-inc, 34340, 7th-8th, 4, Widowed, Farming-fishing, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 47, Self-emp-not-inc, 182752, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 35, Iran, <=50K 19, ?, 48393, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 84, United-States, <=50K 45, Private, 34248, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 17, Private, 186677, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 12, United-States, <=50K 37, Private, 167851, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 27, Private, 146460, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 17, Private, 209650, 12th, 8, Never-married, Other-service, Own-child, White, Male, 0, 0, 16, United-States, <=50K 18, Self-emp-not-inc, 132986, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 94429, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 252406, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 174592, Masters, 14, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 36, Self-emp-not-inc, 151322, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 51, Private, 37237, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 80, United-States, >50K 38, Private, 101192, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 77, ?, 152900, 5th-6th, 3, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 20, United-States, <=50K 51, Private, 94081, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 24, Private, 329408, 11th, 7, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 106028, HS-grad, 9, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 35, ?, 164866, 10th, 6, Divorced, ?, Not-in-family, White, Male, 0, 0, 99, United-States, <=50K 51, Self-emp-inc, 167793, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 40, United-States, >50K 28, Private, 138692, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Private, 173968, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 228320, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 96585, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 42, Private, 156580, Bachelors, 13, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, Puerto-Rico, <=50K 58, Private, 210673, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 52, Local-gov, 137753, HS-grad, 9, Married-civ-spouse, Other-service, Wife, Black, Female, 0, 0, 20, United-States, <=50K 29, Private, 29865, HS-grad, 9, Divorced, Sales, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 50, United-States, <=50K 27, Private, 196044, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 28, Private, 308995, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, Jamaica, <=50K 59, Private, 159008, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 20, United-States, >50K 28, Private, 362491, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 94395, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 320047, 10th, 6, Married-spouse-absent, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 98535, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 65, Private, 183170, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 18, ?, 331511, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 30, United-States, <=50K 38, Private, 195686, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Private, 178244, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 127833, HS-grad, 9, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 36, Private, 269722, Masters, 14, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, State-gov, 136819, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 205604, 5th-6th, 3, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 30, Mexico, <=50K 28, Private, 132078, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 234880, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 30, United-States, <=50K 24, Private, 196816, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 3908, 0, 40, United-States, <=50K 36, Private, 237943, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 68, Self-emp-inc, 140852, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Self-emp-not-inc, 105614, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 18, Private, 83492, 7th-8th, 4, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 50, Self-emp-not-inc, 225772, Doctorate, 16, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 60, United-States, >50K 37, Private, 242713, 12th, 8, Separated, Priv-house-serv, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 60, Private, 355865, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 43, Private, 173316, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Self-emp-inc, 35662, Doctorate, 16, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 70, United-States, >50K 17, Private, 297246, 11th, 7, Never-married, Priv-house-serv, Own-child, White, Female, 0, 0, 9, United-States, <=50K 43, Private, 108945, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 39, Private, 112158, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 26, ?, <=50K 21, Self-emp-not-inc, 57298, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 15, United-States, <=50K 42, Self-emp-not-inc, 115323, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 7, ?, <=50K 48, Self-emp-not-inc, 164582, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 7298, 0, 60, United-States, >50K 56, Private, 295067, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 14084, 0, 45, United-States, >50K 21, Private, 177265, Assoc-acdm, 12, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 28, Local-gov, 336543, Assoc-acdm, 12, Married-civ-spouse, Protective-serv, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Hong, >50K 39, Self-emp-not-inc, 52870, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Private, 316820, 7th-8th, 4, Married-civ-spouse, Sales, Husband, White, Male, 4064, 0, 40, United-States, <=50K 38, Local-gov, 200153, Assoc-acdm, 12, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 59, Private, 453067, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 36, United-States, >50K 51, Federal-gov, 27166, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 299598, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 16, United-States, <=50K 23, Private, 122048, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 345277, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 113147, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 40, United-States, <=50K 43, Private, 34007, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 45, Private, 255014, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, >50K 34, Private, 152667, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 35, United-States, <=50K 21, Private, 231053, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 30, United-States, <=50K 34, Private, 103651, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 55, Self-emp-inc, 124137, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Private, 198183, Assoc-voc, 11, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 183627, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 3137, 0, 48, Ireland, <=50K 19, Private, 466458, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 45, Self-emp-not-inc, 114396, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 42, Private, 186376, Bachelors, 13, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 72, Philippines, >50K 32, Private, 290964, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 1590, 40, United-States, <=50K 90, Self-emp-not-inc, 282095, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, State-gov, 244974, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 44, United-States, >50K 34, Self-emp-not-inc, 114691, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 107160, 12th, 8, Separated, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 39, Self-emp-not-inc, 142573, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 29, Private, 203833, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 24, Private, 47791, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 49, Private, 133729, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 17, United-States, <=50K 52, Self-emp-not-inc, 135339, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, ?, >50K 54, Private, 135803, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 15024, 0, 60, South, >50K 31, Private, 128591, 9th, 5, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 133853, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 18, ?, 137363, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 30, United-States, <=50K 27, Self-emp-not-inc, 243569, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 119156, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 391114, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 60, United-States, <=50K 27, Private, 252506, Some-college, 10, Divorced, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 34, State-gov, 117503, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 20, Italy, <=50K 25, State-gov, 117833, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 19, United-States, <=50K 39, Private, 294183, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 394927, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 51, Self-emp-not-inc, 259323, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 70, United-States, <=50K 21, ?, 207988, HS-grad, 9, Married-civ-spouse, ?, Other-relative, White, Female, 0, 0, 35, United-States, <=50K 33, Private, 96635, Some-college, 10, Never-married, Sales, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 26, South, <=50K 27, Private, 192283, Assoc-voc, 11, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 38, United-States, <=50K 29, Private, 214881, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, State-gov, 167474, 10th, 6, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 110713, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 20, Private, 201204, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 197666, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 162002, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 35, United-States, <=50K 31, Private, 263561, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 2246, 45, United-States, >50K 41, Private, 224799, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Self-emp-not-inc, 89942, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 238685, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 54, Private, 38795, 9th, 5, Separated, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 90414, Bachelors, 13, Married-spouse-absent, Craft-repair, Unmarried, White, Female, 0, 0, 55, Ireland, <=50K 21, Private, 190805, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 32, United-States, <=50K 52, Private, 23780, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 45, United-States, >50K 19, Private, 285263, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 177331, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 22, Private, 347530, HS-grad, 9, Separated, Other-service, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 59, Private, 230039, HS-grad, 9, Never-married, Exec-managerial, Unmarried, White, Female, 0, 625, 38, United-States, <=50K 17, ?, 210547, 10th, 6, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 204752, 12th, 8, Never-married, Sales, Own-child, White, Male, 0, 0, 32, United-States, <=50K 74, Self-emp-not-inc, 104001, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 45, Private, 253116, 10th, 6, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 36, Private, 169037, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Self-emp-inc, 202027, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 45, Private, 170099, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Self-emp-not-inc, 212847, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 85, United-States, <=50K 50, State-gov, 307392, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 233428, HS-grad, 9, Divorced, Exec-managerial, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 355728, Some-college, 10, Separated, Exec-managerial, Not-in-family, White, Male, 0, 1980, 45, England, <=50K 52, Private, 177995, 1st-4th, 2, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 56, Mexico, >50K 24, Private, 283613, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 43, United-States, <=50K 56, Self-emp-inc, 184598, 9th, 5, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 99, United-States, <=50K 27, Private, 185647, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, >50K 47, Self-emp-inc, 192894, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 45, United-States, >50K 40, Self-emp-not-inc, 284706, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, Amer-Indian-Eskimo, Male, 0, 1977, 60, United-States, >50K 38, Private, 179579, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 131679, Assoc-voc, 11, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 52, Private, 132973, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 22, Private, 154713, HS-grad, 9, Divorced, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 121718, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Italy, <=50K 30, Private, 255279, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 55, Private, 202559, Bachelors, 13, Married-civ-spouse, Other-service, Other-relative, Asian-Pac-Islander, Male, 0, 0, 35, Philippines, <=50K 25, Private, 123095, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 1590, 40, United-States, <=50K 32, Private, 153326, Bachelors, 13, Married-civ-spouse, Prof-specialty, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 75695, Some-college, 10, Separated, Other-service, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 33, Self-emp-inc, 206609, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 17, Private, 234780, HS-grad, 9, Never-married, Farming-fishing, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 27, Private, 178778, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 171355, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 20, United-States, <=50K 63, Federal-gov, 95680, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 18, United-States, >50K 39, Private, 196673, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 5013, 0, 40, United-States, <=50K 51, Federal-gov, 73670, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 4386, 0, 52, United-States, >50K 67, Self-emp-not-inc, 139960, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Self-emp-inc, 397280, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 72, ?, <=50K 27, Private, 60374, HS-grad, 9, Widowed, Craft-repair, Unmarried, White, Female, 0, 1594, 26, United-States, <=50K 54, Private, 421561, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 59, Private, 245196, 10th, 6, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, >50K 18, Private, 27620, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 19, Private, 187570, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 20, United-States, <=50K 31, Private, 102884, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, <=50K 17, Private, 228399, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 7, United-States, <=50K 42, Private, 340234, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, Asian-Pac-Islander, Male, 15024, 0, 40, United-States, >50K 37, Private, 176293, Some-college, 10, Married-spouse-absent, Prof-specialty, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 51, Local-gov, 108435, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 161187, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 2463, 0, 40, United-States, <=50K 23, Private, 278391, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 157941, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 25, Private, 182866, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 69, Private, 370888, Assoc-acdm, 12, Divorced, Adm-clerical, Not-in-family, White, Female, 2964, 0, 6, Germany, <=50K 30, Private, 206512, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 44, United-States, <=50K 33, Private, 357954, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 35, India, <=50K 28, Private, 189346, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 48, United-States, <=50K 45, Private, 234652, 5th-6th, 3, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 25, Private, 113436, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 15, United-States, <=50K 37, Private, 204145, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 59, Private, 157305, Preschool, 1, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, Dominican-Republic, <=50K 26, Private, 104045, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 48, Private, 280422, Some-college, 10, Separated, Other-service, Not-in-family, White, Female, 0, 0, 25, Peru, <=50K 64, Federal-gov, 173754, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 211154, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 50, United-States, <=50K 24, Private, 321435, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 40, State-gov, 177083, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 46, Private, 178829, Masters, 14, Married-spouse-absent, Exec-managerial, Not-in-family, White, Male, 0, 0, 70, United-States, >50K 35, Federal-gov, 287658, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 40, United-States, >50K 43, Private, 209894, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 31, Private, 334744, HS-grad, 9, Separated, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 306967, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 35, Private, 52187, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 35, Private, 101978, HS-grad, 9, Separated, Transport-moving, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 35, State-gov, 483530, Some-college, 10, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 77357, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 50, Private, 149770, Masters, 14, Never-married, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 48, Self-emp-not-inc, 328606, Prof-school, 15, Divorced, Prof-specialty, Unmarried, White, Male, 14084, 0, 63, United-States, >50K 70, ?, 172652, Masters, 14, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 8, United-States, <=50K 46, Private, 188293, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 116608, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 37, State-gov, 348960, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 36, United-States, >50K 24, Private, 329530, 9th, 5, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, Mexico, <=50K 47, Local-gov, 93476, Bachelors, 13, Separated, Prof-specialty, Not-in-family, White, Female, 0, 0, 70, United-States, <=50K 35, Self-emp-not-inc, 195744, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 43, Private, 125833, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Vietnam, <=50K 18, State-gov, 191117, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 54, Private, 311020, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 50, United-States, <=50K 62, Private, 210464, HS-grad, 9, Never-married, Other-service, Other-relative, Black, Female, 0, 0, 38, United-States, <=50K 36, Private, 135289, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, >50K 27, Private, 156266, 9th, 5, Married-civ-spouse, Farming-fishing, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 23, Private, 154210, Some-college, 10, Never-married, Adm-clerical, Other-relative, Asian-Pac-Islander, Male, 0, 0, 14, Puerto-Rico, <=50K 61, ?, 160625, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 4386, 0, 15, United-States, >50K 39, Self-emp-not-inc, 331481, Bachelors, 13, Divorced, Craft-repair, Not-in-family, Black, Male, 0, 1669, 60, ?, <=50K 33, Self-emp-not-inc, 249249, 5th-6th, 3, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 28, Private, 261725, 1st-4th, 2, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, Mexico, <=50K 22, Private, 239612, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 20, United-States, <=50K 31, Self-emp-not-inc, 226696, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, >50K 26, Private, 190330, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 44, Private, 193755, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 73, Private, 192740, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 30, United-States, <=50K 44, Private, 201924, Bachelors, 13, Divorced, Sales, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 35, Private, 77146, Assoc-voc, 11, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 33, Private, 126414, Bachelors, 13, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, ?, <=50K 27, Private, 43652, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Federal-gov, 227244, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 50, United-States, >50K 29, Private, 160731, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 33, Private, 287878, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 26, United-States, <=50K 50, Private, 166758, Some-college, 10, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 32, Private, 183811, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 2829, 0, 40, United-States, <=50K 41, Self-emp-not-inc, 254818, Masters, 14, Divorced, Handlers-cleaners, Unmarried, White, Male, 0, 0, 40, Peru, <=50K 19, ?, 220517, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 35, United-States, <=50K 45, Private, 295046, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 65, Private, 190568, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 810, 36, United-States, <=50K 42, State-gov, 211915, Some-college, 10, Separated, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 33, Self-emp-not-inc, 295621, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 25, United-States, >50K 32, Private, 204567, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 99999, 0, 60, United-States, >50K 42, Private, 204235, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 49, Private, 186982, Some-college, 10, Separated, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, >50K 38, Private, 133586, HS-grad, 9, Married-civ-spouse, Protective-serv, Own-child, White, Male, 0, 0, 45, United-States, <=50K 38, Private, 165930, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 37, Private, 164898, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 52, United-States, <=50K 24, Private, 278155, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 27, Self-emp-not-inc, 115705, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 25, Private, 150553, 9th, 5, Married-spouse-absent, Adm-clerical, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, Vietnam, <=50K 29, Private, 185127, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 46, Private, 201595, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 70, United-States, <=50K 44, Self-emp-inc, 165815, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 96, United-States, <=50K 26, Private, 102420, Bachelors, 13, Never-married, Sales, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, South, <=50K 46, Local-gov, 344172, Assoc-acdm, 12, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 49, United-States, >50K 38, Private, 222450, Some-college, 10, Separated, Exec-managerial, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 212245, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, State-gov, 190625, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 20, United-States, <=50K 33, Private, 203488, Some-college, 10, Divorced, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 304260, Assoc-acdm, 12, Divorced, Adm-clerical, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 31, Local-gov, 243665, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 41, United-States, >50K 26, Self-emp-not-inc, 189238, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 4, Mexico, <=50K 42, Private, 77373, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 38, United-States, <=50K 27, Private, 410351, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 36385, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 64, Private, 110150, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 198316, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 127772, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Self-emp-not-inc, 199058, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 56, Private, 285730, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 66, United-States, <=50K 25, Local-gov, 334133, Masters, 14, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 20, United-States, <=50K 60, State-gov, 97030, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 52, Private, 67090, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 44, United-States, <=50K 43, Private, 397963, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, White, Male, 594, 0, 16, United-States, <=50K 46, Private, 182533, Bachelors, 13, Never-married, Adm-clerical, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 19, Private, 560804, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 30, United-States, <=50K 56, Private, 365050, 7th-8th, 4, Never-married, Farming-fishing, Unmarried, Black, Female, 0, 0, 20, United-States, <=50K 22, Private, 110200, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 150025, 11th, 7, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, ?, <=50K 39, Private, 299828, 5th-6th, 3, Separated, Sales, Unmarried, Black, Female, 0, 0, 30, Puerto-Rico, <=50K 28, Private, 109282, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 103435, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 22, Private, 34747, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 35, United-States, <=50K 39, Private, 137522, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Asian-Pac-Islander, Male, 0, 0, 40, ?, >50K 39, Private, 286789, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Self-emp-not-inc, 211032, 11th, 7, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 67, ?, 192916, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 3818, 0, 11, United-States, <=50K 31, Private, 219318, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 35, Puerto-Rico, <=50K 50, Private, 112873, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 36069, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 3908, 0, 46, United-States, <=50K 48, Private, 73434, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, Germany, >50K 51, Private, 200576, Bachelors, 13, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 54, Private, 172962, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 44006, Assoc-voc, 11, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 234474, Some-college, 10, Never-married, Sales, Own-child, Black, Female, 0, 0, 20, United-States, <=50K 37, Private, 212826, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 40, United-States, <=50K 38, Private, 234901, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 59, Federal-gov, 200700, Assoc-acdm, 12, Married-civ-spouse, Farming-fishing, Husband, Black, Male, 0, 0, 40, United-States, <=50K 59, Self-emp-not-inc, 41258, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 51, Private, 249644, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 48, United-States, >50K 60, ?, 230165, Bachelors, 13, Married-civ-spouse, ?, Husband, Black, Male, 0, 0, 40, United-States, <=50K 29, Private, 351731, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 114765, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 349884, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 28, Self-emp-inc, 204247, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 34, Private, 143392, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 50, Self-emp-not-inc, 37913, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, Italy, >50K 22, Self-emp-inc, 150683, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 24, United-States, <=50K 27, Private, 207611, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 52, United-States, <=50K 45, State-gov, 319666, Prof-school, 15, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 43, United-States, <=50K 39, Private, 155961, HS-grad, 9, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 38, United-States, <=50K 25, Local-gov, 117833, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 63, ?, 447079, HS-grad, 9, Never-married, ?, Not-in-family, White, Male, 0, 0, 15, United-States, <=50K 24, Self-emp-inc, 142404, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 18, Private, 155752, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 19, ?, 252292, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 111450, 12th, 8, Never-married, Other-service, Unmarried, Black, Male, 0, 0, 38, United-States, <=50K 20, Private, 528616, 5th-6th, 3, Never-married, Other-service, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 17, Self-emp-not-inc, 228786, 10th, 6, Never-married, Other-service, Own-child, White, Female, 0, 0, 24, United-States, <=50K 63, Self-emp-inc, 80572, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Local-gov, 180271, Bachelors, 13, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 65, United-States, >50K 51, Federal-gov, 237819, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 29, Private, 157612, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 3325, 0, 45, United-States, <=50K 64, Private, 379062, Some-college, 10, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 12, United-States, <=50K 17, Private, 191910, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 25, United-States, <=50K 45, Local-gov, 326064, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 6497, 0, 35, United-States, <=50K 18, Private, 312353, 12th, 8, Never-married, Other-service, Own-child, Black, Male, 0, 0, 20, United-States, <=50K 31, Local-gov, 213307, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 48, Self-emp-not-inc, 209057, Bachelors, 13, Married-spouse-absent, Sales, Own-child, White, Male, 0, 0, 50, United-States, >50K 41, Private, 340148, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 65, Private, 154171, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 20051, 0, 60, United-States, >50K 27, Private, 94064, Assoc-voc, 11, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 119098, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Self-emp-not-inc, 388496, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 8, Puerto-Rico, >50K 49, Private, 181363, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 58, ?, 210031, HS-grad, 9, Divorced, ?, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 206951, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 1902, 45, United-States, >50K 25, Private, 485496, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 41, Private, 210259, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 37, United-States, <=50K 31, Private, 118551, 9th, 5, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 63, Private, 180911, 11th, 7, Married-civ-spouse, Protective-serv, Husband, White, Male, 4386, 0, 37, United-States, >50K 50, State-gov, 242517, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 63, Private, 298113, Some-college, 10, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Self-emp-not-inc, 277783, Masters, 14, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 99, United-States, <=50K 48, Private, 155862, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 51, Self-emp-not-inc, 171924, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 18, Private, 243900, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 15, United-States, <=50K 23, Private, 231160, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 25, United-States, <=50K 31, Private, 356882, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 5013, 0, 40, United-States, <=50K 38, Private, 49020, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, ?, 105460, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 20, England, <=50K 56, Private, 157749, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, >50K 31, Private, 131568, 7th-8th, 4, Divorced, Transport-moving, Unmarried, White, Male, 0, 0, 20, United-States, <=50K 46, Private, 332355, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 204501, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 56, Local-gov, 305767, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 40, China, <=50K 31, Private, 129761, HS-grad, 9, Never-married, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 42, Self-emp-inc, 130126, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 40, United-States, >50K 53, Private, 102828, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 35, United-States, >50K 18, Private, 160984, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 18, ?, 255282, 11th, 7, Never-married, ?, Own-child, Black, Male, 0, 1602, 48, United-States, <=50K 20, ?, 346341, Some-college, 10, Never-married, ?, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 27, Private, 285897, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1848, 45, United-States, >50K 31, Private, 356689, Bachelors, 13, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 52, Federal-gov, 192386, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 5013, 0, 40, United-States, <=50K 46, Private, 394860, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 113129, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 24, United-States, <=50K 26, Private, 55929, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 48, Local-gov, 177018, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 37, Private, 161141, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Private, 309463, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 165468, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 55, United-States, >50K 24, Private, 49218, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 74, Self-emp-not-inc, 119129, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 2149, 20, United-States, <=50K 56, Self-emp-not-inc, 162130, 5th-6th, 3, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1887, 67, United-States, >50K 39, Federal-gov, 129573, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 1741, 40, United-States, <=50K 21, Private, 306850, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 135296, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 2258, 45, United-States, >50K 43, Self-emp-not-inc, 187322, HS-grad, 9, Divorced, Other-service, Unmarried, White, Male, 0, 0, 45, United-States, <=50K 23, Private, 55674, Bachelors, 13, Never-married, Protective-serv, Not-in-family, White, Female, 2907, 0, 40, United-States, <=50K 26, Private, 148298, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 47, Private, 34845, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 27, Private, 200733, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 55, United-States, <=50K 45, Private, 191858, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, >50K 30, Private, 425528, HS-grad, 9, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 70, United-States, <=50K 35, Private, 44780, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 7688, 0, 20, United-States, >50K 33, Private, 125856, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 100508, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 21, Private, 148294, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 20, United-States, <=50K 42, Private, 39324, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Federal-gov, 147397, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 36, United-States, <=50K 46, Private, 24728, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 36, Private, 177616, 5th-6th, 3, Separated, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 54, Private, 163826, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 199947, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 26, Local-gov, 386949, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 36, Self-emp-inc, 116133, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 57, United-States, <=50K 56, Self-emp-not-inc, 196307, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 37, Private, 177181, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 324854, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 23, Private, 188505, Bachelors, 13, Never-married, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 23, State-gov, 502316, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 41, State-gov, 26892, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 102058, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 39, Private, 167728, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 67, Local-gov, 233681, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 35, United-States, <=50K 60, Private, 26756, HS-grad, 9, Widowed, Sales, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 54, Private, 101890, HS-grad, 9, Widowed, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 192337, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, England, >50K 47, Private, 340982, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, Asian-Pac-Islander, Male, 3103, 0, 40, Philippines, >50K 49, State-gov, 102308, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 42, United-States, >50K 19, Private, 84747, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 24, United-States, <=50K 20, Private, 197752, Some-college, 10, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 66, Private, 185336, HS-grad, 9, Widowed, Sales, Other-relative, White, Female, 0, 0, 35, United-States, <=50K 22, ?, 289984, Some-college, 10, Never-married, ?, Not-in-family, Black, Female, 0, 0, 25, United-States, <=50K 51, Self-emp-not-inc, 125417, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 42, United-States, >50K 19, Private, 278480, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 146412, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 193042, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, >50K 41, Private, 53956, Bachelors, 13, Divorced, Sales, Not-in-family, White, Male, 0, 1980, 56, United-States, <=50K 90, Private, 175491, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 9386, 0, 50, Ecuador, >50K 78, ?, 33186, 7th-8th, 4, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 60, United-States, <=50K 36, Private, 144154, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 194901, Prof-school, 15, Divorced, Sales, Own-child, White, Male, 0, 0, 55, United-States, <=50K 35, Private, 335777, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 46, Private, 139268, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 38, Private, 33887, HS-grad, 9, Never-married, Machine-op-inspct, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 283613, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 141245, Bachelors, 13, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, Puerto-Rico, <=50K 49, Private, 298130, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 186096, HS-grad, 9, Never-married, Other-service, Own-child, Black, Male, 0, 0, 30, United-States, <=50K 77, Private, 187656, Some-college, 10, Widowed, Priv-house-serv, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 46, Private, 102308, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 56, United-States, >50K 41, Private, 124639, Some-college, 10, Separated, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 28, Private, 388112, 1st-4th, 2, Never-married, Farming-fishing, Unmarried, White, Male, 0, 0, 77, Mexico, <=50K 21, Private, 109952, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 164529, 12th, 8, Never-married, Farming-fishing, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 36, Private, 247750, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 45, United-States, <=50K 23, State-gov, 103588, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 25, United-States, <=50K 38, Federal-gov, 248919, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 2051, 40, United-States, <=50K 29, Self-emp-not-inc, 178551, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 136137, Some-college, 10, Married-civ-spouse, Exec-managerial, Other-relative, White, Male, 0, 0, 50, United-States, >50K 47, Federal-gov, 55377, Bachelors, 13, Never-married, Adm-clerical, Unmarried, Black, Male, 0, 0, 40, United-States, >50K 39, Local-gov, 177728, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 40, Local-gov, 243580, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 48, United-States, <=50K 21, ?, 188535, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 63910, HS-grad, 9, Divorced, Adm-clerical, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 23, Private, 219535, HS-grad, 9, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 44, State-gov, 180609, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 59313, Some-college, 10, Separated, Other-service, Not-in-family, Black, Male, 0, 0, 40, ?, <=50K 70, Private, 170428, Bachelors, 13, Widowed, Prof-specialty, Unmarried, White, Female, 0, 0, 20, Puerto-Rico, <=50K 51, Private, 102615, Masters, 14, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 1977, 40, United-States, >50K 66, Private, 193132, 9th, 5, Separated, Other-service, Not-in-family, Black, Female, 0, 0, 30, United-States, <=50K 57, Self-emp-inc, 124137, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 136629, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 48, Self-emp-inc, 148995, Bachelors, 13, Divorced, Sales, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 24, ?, 203076, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 63424, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 43, Private, 241895, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 27, Private, 266973, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 32, Private, 188048, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 366929, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 35, United-States, <=50K 33, Private, 214129, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 250818, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Local-gov, 240979, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, >50K 35, Private, 98283, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, India, >50K 26, Private, 104746, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 5013, 0, 60, United-States, <=50K 39, Private, 103710, HS-grad, 9, Never-married, Sales, Unmarried, White, Female, 0, 0, 60, United-States, <=50K 24, Private, 159580, Bachelors, 13, Never-married, Other-service, Own-child, Black, Female, 0, 0, 75, United-States, <=50K 45, Private, 117409, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Private, 140001, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 49, State-gov, 31650, Bachelors, 13, Married-civ-spouse, Prof-specialty, Other-relative, White, Female, 0, 0, 45, United-States, <=50K 35, State-gov, 80771, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 66278, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 107801, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 1617, 25, United-States, <=50K 33, Private, 206609, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 35, Private, 282461, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 31, Private, 188246, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 20, Private, 279763, 11th, 7, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 25, United-States, <=50K 44, Private, 467799, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Self-emp-not-inc, 137674, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 40, United-States, <=50K 50, Private, 158284, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 204219, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 28, State-gov, 210498, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 60, Federal-gov, 63526, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, >50K 38, Federal-gov, 216924, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 372559, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 57, Federal-gov, 199114, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 2258, 40, United-States, <=50K 50, Private, 168539, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Local-gov, 189911, 11th, 7, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 69, Local-gov, 61958, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 1424, 0, 6, United-States, <=50K 51, State-gov, 68898, Assoc-voc, 11, Divorced, Tech-support, Not-in-family, White, Male, 0, 2444, 39, United-States, >50K 42, Private, 204450, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, United-States, <=50K 53, Private, 311350, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 37, Private, 113750, Bachelors, 13, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 359591, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 132879, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 50, United-States, >50K 20, Private, 301199, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 24, United-States, <=50K 38, State-gov, 267540, Some-college, 10, Separated, Adm-clerical, Unmarried, Black, Female, 0, 0, 38, United-States, <=50K 52, Private, 185407, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, Poland, >50K 48, Self-emp-inc, 191277, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 30, Private, 78980, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Self-emp-not-inc, 241463, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1848, 65, United-States, >50K 47, Private, 216999, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 33, Local-gov, 120508, Bachelors, 13, Divorced, Protective-serv, Unmarried, White, Female, 0, 0, 60, Germany, <=50K 33, Private, 122612, HS-grad, 9, Married-spouse-absent, Other-service, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 35, Thailand, <=50K 20, Private, 94057, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 15, United-States, <=50K 41, State-gov, 197558, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 351869, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1485, 45, United-States, >50K 54, Self-emp-not-inc, 121761, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 50, ?, <=50K 36, Federal-gov, 184556, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 268281, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 235646, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 18, Private, 186909, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 16, United-States, <=50K 62, Private, 35783, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 33, Private, 188861, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 363591, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 469921, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 51150, Assoc-voc, 11, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 174325, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 20, Private, 347530, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 25, United-States, <=50K 50, Private, 72351, Bachelors, 13, Divorced, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 42, Local-gov, 185129, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 43, ?, >50K 36, Private, 188571, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 255252, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 291951, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 33, Self-emp-not-inc, 223046, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 43, Local-gov, 37937, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 43, United-States, <=50K 38, Private, 295127, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Local-gov, 183801, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 14, United-States, <=50K 40, Private, 116218, Some-college, 10, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 40, Private, 143069, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Local-gov, 235951, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 57, Private, 112840, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 65, Local-gov, 146454, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1648, 4, Greece, <=50K 52, Federal-gov, 43705, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 50, United-States, <=50K 59, Private, 122283, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 99999, 0, 40, India, >50K 18, Private, 376647, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 2176, 0, 25, United-States, <=50K 48, Private, 101299, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, <=50K 45, Private, 96798, 5th-6th, 3, Divorced, Transport-moving, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 194654, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, State-gov, 206889, Assoc-acdm, 12, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 226902, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 44, State-gov, 150755, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 5013, 0, 40, United-States, <=50K 24, Private, 200679, HS-grad, 9, Never-married, Farming-fishing, Own-child, Black, Male, 0, 0, 50, United-States, <=50K 71, Private, 183678, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 16, United-States, <=50K 17, Private, 33138, 12th, 8, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 57, Self-emp-not-inc, 57071, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 3137, 0, 40, United-States, <=50K 71, ?, 35303, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 9386, 0, 30, United-States, >50K 37, Private, 188576, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, ?, <=50K 33, Private, 169496, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 58124, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 356344, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 42, Self-emp-not-inc, 444134, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 15, United-States, <=50K 18, ?, 340117, 11th, 7, Never-married, ?, Unmarried, Black, Female, 0, 0, 50, United-States, <=50K 34, Private, 219619, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 57, ?, 334585, 10th, 6, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 40, United-States, <=50K 27, Local-gov, 331046, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 46, ?, 443179, Bachelors, 13, Divorced, ?, Not-in-family, White, Female, 0, 0, 8, United-States, <=50K 64, ?, 239529, 11th, 7, Widowed, ?, Not-in-family, White, Female, 3674, 0, 35, United-States, <=50K 24, Private, 100345, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 20, United-States, <=50K 23, Private, 205653, Bachelors, 13, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 30, United-States, <=50K 33, Private, 112383, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, Self-emp-inc, 21626, Assoc-voc, 11, Divorced, Sales, Not-in-family, White, Male, 2202, 0, 56, United-States, <=50K 25, Private, 135568, 9th, 5, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 190532, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 53, Federal-gov, 266598, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Local-gov, 116608, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 35, United-States, >50K 36, Private, 353263, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, >50K 25, State-gov, 157617, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 54, Federal-gov, 21698, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 77143, 12th, 8, Separated, Transport-moving, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 18, State-gov, 342852, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 176602, HS-grad, 9, Divorced, Other-service, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 26, Private, 146343, Some-college, 10, Married-civ-spouse, Sales, Wife, Black, Female, 0, 0, 40, United-States, <=50K 68, ?, 146645, Doctorate, 16, Married-civ-spouse, ?, Husband, White, Male, 20051, 0, 50, United-States, >50K 33, Private, 221966, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 2202, 0, 50, United-States, <=50K 22, Private, 215546, Assoc-acdm, 12, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 50, State-gov, 173020, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, ?, 247734, Bachelors, 13, Never-married, ?, Own-child, White, Male, 0, 0, 30, United-States, <=50K 44, Private, 252202, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 497300, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 34, Self-emp-not-inc, 426431, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Federal-gov, 162410, Some-college, 10, Widowed, Tech-support, Not-in-family, White, Female, 0, 0, 45, United-States, >50K 77, ?, 143516, Masters, 14, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 8, United-States, >50K 25, Private, 190350, 10th, 6, Married-civ-spouse, Other-service, Own-child, White, Female, 0, 0, 35, United-States, <=50K 20, Private, 194504, Some-college, 10, Separated, Sales, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 46, Federal-gov, 110884, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 26, Private, 187652, Assoc-acdm, 12, Never-married, Tech-support, Own-child, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 81400, 1st-4th, 2, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 25, El-Salvador, <=50K 70, ?, 97831, HS-grad, 9, Widowed, ?, Unmarried, White, Female, 0, 0, 4, United-States, <=50K 57, Private, 180920, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 189186, Assoc-voc, 11, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, ?, 144172, Assoc-acdm, 12, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 16, United-States, <=50K 36, Private, 607848, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 45, United-States, >50K 32, Private, 207301, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 293073, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 36, Private, 210452, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Male, 0, 0, 45, United-States, <=50K 19, Private, 41400, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 30, United-States, <=50K 27, Private, 164170, Bachelors, 13, Never-married, Tech-support, Unmarried, Asian-Pac-Islander, Female, 0, 0, 20, Philippines, <=50K 48, Private, 112906, Masters, 14, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 55, United-States, >50K 49, Self-emp-not-inc, 126268, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 55, Private, 208311, Masters, 14, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 1977, 20, United-States, >50K 61, Private, 28291, HS-grad, 9, Divorced, Farming-fishing, Not-in-family, White, Female, 0, 0, 82, United-States, <=50K 42, Local-gov, 121998, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 40, United-States, >50K 42, Federal-gov, 31621, Assoc-acdm, 12, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Local-gov, 108386, Assoc-voc, 11, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Self-emp-not-inc, 134727, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 208391, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 112271, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 30, Private, 173350, Assoc-voc, 11, Married-spouse-absent, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 243190, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 20, India, >50K 55, Private, 185436, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 70, United-States, >50K 36, Private, 290409, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 80058, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 48, United-States, <=50K 56, Local-gov, 370045, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 36936, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 2002, 40, United-States, <=50K 37, Private, 231180, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 119793, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 60, United-States, <=50K 38, Private, 102178, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 76, ?, 135039, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 20, United-States, <=50K 35, ?, 317780, Some-college, 10, Never-married, ?, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 48, Private, 232840, Some-college, 10, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 43, United-States, <=50K 35, Private, 33975, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Local-gov, 256997, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 64, Private, 298301, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 310380, HS-grad, 9, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 45, Local-gov, 182100, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 501172, 5th-6th, 3, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, Mexico, <=50K 43, State-gov, 143939, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 50, United-States, >50K 23, Private, 85088, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 37, United-States, <=50K 25, Private, 282313, 10th, 6, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 1602, 40, United-States, <=50K 39, Private, 230054, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 63, Private, 236338, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 35, United-States, <=50K 37, Private, 321943, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Federal-gov, 218782, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Other, Male, 0, 0, 40, United-States, <=50K 33, Private, 191385, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, Canada, <=50K 45, Self-emp-inc, 185497, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, Asian-Pac-Islander, Female, 0, 0, 70, ?, <=50K 28, Private, 126129, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 199268, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 34, Private, 255693, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 20, United-States, <=50K 34, Private, 203488, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 203233, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 203836, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 36, Private, 187847, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 40, United-States, >50K 38, Private, 116358, Some-college, 10, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 46, Self-emp-inc, 198660, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 99999, 0, 72, United-States, >50K 43, Self-emp-not-inc, 89636, Bachelors, 13, Married-civ-spouse, Sales, Wife, Asian-Pac-Islander, Female, 0, 0, 60, South, <=50K 49, Private, 120629, Some-college, 10, Widowed, Sales, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 26, Local-gov, 150226, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 35, United-States, <=50K 28, Private, 137898, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 54, Self-emp-inc, 146574, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 53, Private, 88725, HS-grad, 9, Never-married, Craft-repair, Not-in-family, Other, Female, 0, 0, 40, ?, <=50K 24, Private, 142022, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 50, United-States, <=50K 23, Private, 284898, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 30, United-States, <=50K 55, Local-gov, 212448, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 58, Self-emp-not-inc, 203039, 9th, 5, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 227489, HS-grad, 9, Never-married, Tech-support, Other-relative, Black, Male, 0, 0, 40, ?, <=50K 19, Private, 105289, 10th, 6, Never-married, Other-service, Other-relative, Black, Female, 0, 0, 20, United-States, <=50K 28, ?, 223745, Some-college, 10, Never-married, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 242994, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 52, United-States, <=50K 30, Private, 196385, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 76, Private, 116202, HS-grad, 9, Widowed, Other-service, Unmarried, White, Female, 0, 0, 33, United-States, <=50K 47, Private, 140045, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 133503, Some-college, 10, Divorced, Transport-moving, Not-in-family, White, Male, 2174, 0, 40, United-States, <=50K 40, Private, 226585, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 35, United-States, >50K 24, Private, 85041, HS-grad, 9, Separated, Other-service, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 30, Private, 162442, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 7688, 0, 50, United-States, >50K 67, Private, 279980, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 10605, 0, 10, United-States, >50K 24, Private, 216563, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, United-States, <=50K 43, Local-gov, 231964, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 263855, 12th, 8, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 124915, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, Federal-gov, 178312, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Local-gov, 215862, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 45, United-States, >50K 21, State-gov, 39236, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 58, Private, 349910, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 40, United-States, >50K 52, Private, 75839, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 176711, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 266525, Some-college, 10, Never-married, Prof-specialty, Other-relative, Black, Female, 594, 0, 20, United-States, <=50K 25, ?, 34307, Some-college, 10, Never-married, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 331776, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 111469, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, State-gov, 198965, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Private, 288185, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 21, Private, 198050, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 65, Private, 242580, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Male, 11678, 0, 50, United-States, >50K 37, Private, 173128, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 87905, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Male, 10520, 0, 40, United-States, >50K 44, Private, 173704, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Federal-gov, 93225, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 7688, 0, 40, United-States, >50K 38, Private, 323269, Some-college, 10, Married-civ-spouse, Other-service, Wife, Black, Female, 0, 0, 40, United-States, <=50K 35, Private, 158046, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 5013, 0, 70, United-States, <=50K 32, Private, 133503, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Self-emp-not-inc, 172296, Some-college, 10, Separated, Sales, Unmarried, White, Male, 0, 0, 60, United-States, <=50K 39, ?, 201105, Bachelors, 13, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 30, United-States, <=50K 23, Private, 176486, Some-college, 10, Never-married, Other-service, Other-relative, White, Female, 0, 0, 25, United-States, <=50K 25, Self-emp-inc, 182750, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 23, Private, 82497, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 28, United-States, <=50K 47, Private, 208872, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 145269, 11th, 7, Divorced, Craft-repair, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 25, Private, 19214, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 149347, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 68, ?, 53850, 7th-8th, 4, Married-civ-spouse, ?, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 50, Private, 158294, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 3103, 0, 40, United-States, >50K 47, Private, 152073, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 189623, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 24, Private, 341368, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 201603, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 2176, 0, 40, United-States, <=50K 35, Private, 270572, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 30, Private, 285295, Bachelors, 13, Married-civ-spouse, Other-service, Wife, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 17, Private, 126779, 11th, 7, Never-married, Other-service, Own-child, Black, Male, 0, 0, 20, United-States, <=50K 49, ?, 202874, HS-grad, 9, Separated, ?, Unmarried, White, Female, 0, 0, 40, Columbia, <=50K 27, Private, 373499, 5th-6th, 3, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 60, El-Salvador, <=50K 22, Private, 244773, HS-grad, 9, Never-married, Sales, Own-child, Black, Female, 0, 0, 15, United-States, <=50K 22, State-gov, 96862, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 50, Private, 162632, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 2, United-States, <=50K 51, Self-emp-not-inc, 159755, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 38, United-States, >50K 27, Private, 37088, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 30, United-States, <=50K 27, Private, 335421, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 23, Never-worked, 188535, 7th-8th, 4, Divorced, ?, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 20, State-gov, 349365, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 33002, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 48, United-States, <=50K 32, Private, 330715, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 99999, 0, 40, United-States, >50K 45, Private, 146857, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 38, United-States, >50K 35, Private, 275522, 7th-8th, 4, Widowed, Other-service, Unmarried, White, Female, 0, 0, 80, United-States, <=50K 22, Private, 43646, HS-grad, 9, Married-civ-spouse, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 154548, Some-college, 10, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 28, Private, 47907, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 238397, Bachelors, 13, Divorced, Priv-house-serv, Unmarried, White, Female, 0, 0, 24, United-States, <=50K 48, Local-gov, 195949, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 42, United-States, >50K 22, ?, 354351, Some-college, 10, Never-married, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 349169, Masters, 14, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Mexico, <=50K 25, Private, 158662, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 50, United-States, >50K 23, Local-gov, 23438, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 107302, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 43, Private, 174196, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 49, Local-gov, 226871, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, >50K 23, Private, 124971, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 214061, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 441700, Bachelors, 13, Never-married, Tech-support, Own-child, White, Male, 0, 0, 40, United-States, <=50K 44, Self-emp-inc, 104892, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 58, United-States, >50K 34, Private, 234386, Assoc-acdm, 12, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 29, Local-gov, 188278, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 244395, 11th, 7, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 35, Private, 30916, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 48, Private, 219565, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 377486, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 36, United-States, <=50K 42, Local-gov, 137232, HS-grad, 9, Divorced, Protective-serv, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 53, Private, 233369, Some-college, 10, Widowed, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 71067, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 59, Private, 195176, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 72, United-States, <=50K 31, Private, 98639, HS-grad, 9, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 183778, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 123011, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 2559, 50, United-States, >50K 25, Private, 164938, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 4416, 0, 40, United-States, <=50K 28, ?, 147471, HS-grad, 9, Divorced, ?, Own-child, White, Female, 0, 0, 10, United-States, <=50K 30, Private, 206046, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1848, 40, United-States, >50K 46, Private, 81497, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 45, Private, 189225, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 23, Private, 141264, Some-college, 10, Never-married, Exec-managerial, Other-relative, Black, Female, 0, 0, 40, United-States, <=50K 33, Private, 97939, Assoc-acdm, 12, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 42, United-States, <=50K 44, Private, 160829, Bachelors, 13, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 20, United-States, >50K 25, Private, 483822, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, El-Salvador, <=50K 48, State-gov, 148738, Some-college, 10, Divorced, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 289982, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 33, Self-emp-not-inc, 58702, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Wife, White, Female, 3103, 0, 50, United-States, >50K 20, Private, 146706, Some-college, 10, Married-civ-spouse, Sales, Other-relative, White, Female, 0, 0, 30, United-States, <=50K 23, Private, 420973, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 71, Private, 124959, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, State-gov, 121471, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 198237, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 50, United-States, >50K 27, Private, 280758, 11th, 7, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 60, United-States, <=50K 40, Private, 191544, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 30, Private, 261023, Some-college, 10, Divorced, Machine-op-inspct, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 30, State-gov, 231043, Assoc-voc, 11, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 340917, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 167140, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 5013, 0, 40, United-States, <=50K 39, Private, 370795, HS-grad, 9, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 39, Federal-gov, 209609, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, <=50K 74, Private, 209454, 5th-6th, 3, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 32, Self-emp-inc, 78530, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 25, Private, 88922, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 64, Private, 86972, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 47, Self-emp-not-inc, 165468, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 7298, 0, 40, United-States, >50K 37, Private, 134367, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 37, United-States, >50K 47, Private, 199058, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Private, 183612, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Private, 191982, Assoc-voc, 11, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, >50K 22, Private, 514033, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 80, United-States, <=50K 56, Private, 172364, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 190105, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 55, United-States, <=50K 30, Self-emp-inc, 119422, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 70, United-States, <=50K 20, Private, 236592, 12th, 8, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 35, Italy, <=50K 53, State-gov, 43952, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 38, United-States, >50K 43, Private, 194636, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, >50K 23, Private, 235853, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Self-emp-not-inc, 150528, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 30, United-States, <=50K 30, Private, 213722, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 41432, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 46, United-States, <=50K 22, Private, 285775, Assoc-voc, 11, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 470663, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 54, Self-emp-not-inc, 114520, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 113466, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 224559, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 59, Private, 186385, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, ?, 167094, 10th, 6, Divorced, ?, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 18, ?, 216508, 12th, 8, Never-married, ?, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 41, Local-gov, 384236, Assoc-voc, 11, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 181265, Assoc-voc, 11, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 48, United-States, <=50K 58, Private, 190997, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 24, Private, 98287, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 39, Private, 103456, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, >50K 28, Private, 184723, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Female, 0, 1980, 35, United-States, <=50K 25, Private, 165622, Masters, 14, Never-married, Sales, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 29, Private, 101597, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 0, 54, United-States, <=50K 53, Private, 146378, 5th-6th, 3, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 63, Local-gov, 152163, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, State-gov, 106812, Assoc-voc, 11, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 21, Private, 148211, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 3674, 0, 50, United-States, <=50K 45, Private, 187581, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Private, 135296, Assoc-voc, 11, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 72, Local-gov, 144515, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1258, 40, United-States, <=50K 51, Private, 210736, 10th, 6, Married-spouse-absent, Craft-repair, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 210165, 9th, 5, Married-spouse-absent, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 224584, Some-college, 10, Divorced, Sales, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 38, Private, 80771, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 46, Private, 164733, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 41, United-States, <=50K 31, Self-emp-not-inc, 119411, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 60, United-States, >50K 68, Local-gov, 177596, 10th, 6, Separated, Other-service, Not-in-family, Black, Female, 0, 0, 90, United-States, <=50K 43, ?, 396116, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 185251, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 173590, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 3, United-States, <=50K 56, Federal-gov, 196307, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 20, ?, 293091, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 0, 12, United-States, <=50K 36, Private, 175232, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 5178, 0, 40, United-States, >50K 21, Private, 51047, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 21, Private, 334618, Some-college, 10, Never-married, Protective-serv, Not-in-family, Black, Female, 99999, 0, 40, United-States, >50K 52, Local-gov, 152795, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, Self-emp-inc, 205601, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 70, United-States, >50K 52, Private, 129177, Bachelors, 13, Widowed, Other-service, Not-in-family, White, Female, 0, 2824, 20, United-States, >50K 51, Self-emp-not-inc, 121548, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 25, United-States, <=50K 29, Private, 244566, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 75073, Some-college, 10, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 55, United-States, <=50K 29, Private, 179008, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 55, United-States, <=50K 21, Private, 170800, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 30, United-States, <=50K 58, Private, 373344, 1st-4th, 2, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 127961, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 99392, Some-college, 10, Divorced, Craft-repair, Not-in-family, Black, Female, 0, 0, 45, United-States, <=50K 30, Private, 392812, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 50, Germany, <=50K 29, Private, 262478, HS-grad, 9, Never-married, Farming-fishing, Own-child, Black, Male, 0, 0, 30, United-States, <=50K 48, Self-emp-not-inc, 32825, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Self-emp-not-inc, 167380, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 203204, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 25, United-States, >50K 35, Federal-gov, 105138, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, <=50K 54, Private, 145714, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 7688, 0, 25, United-States, >50K 24, Private, 182276, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 25, United-States, <=50K 20, Private, 275385, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 45, United-States, <=50K 30, Self-emp-not-inc, 292472, Some-college, 10, Married-civ-spouse, Sales, Husband, Amer-Indian-Eskimo, Male, 0, 0, 55, United-States, >50K 19, Self-emp-not-inc, 73514, HS-grad, 9, Never-married, Adm-clerical, Own-child, Asian-Pac-Islander, Female, 0, 0, 30, United-States, <=50K 26, Private, 199600, HS-grad, 9, Never-married, Sales, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 38, Private, 111499, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 1977, 99, United-States, >50K 25, Private, 202560, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 99309, Some-college, 10, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 60, Local-gov, 124987, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7298, 0, 40, United-States, >50K 30, Private, 287986, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 119411, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 198668, 7th-8th, 4, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 117583, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 234664, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 20, ?, 114357, Some-college, 10, Never-married, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, State-gov, 176949, Assoc-acdm, 12, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 52, United-States, <=50K 33, Private, 189710, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 45, Mexico, <=50K 65, Private, 205309, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 24, United-States, <=50K 34, Private, 195576, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 20, Private, 216825, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 25, Mexico, <=50K 23, ?, 329174, Some-college, 10, Never-married, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 197036, 10th, 6, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 181291, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 1564, 50, United-States, >50K 31, Private, 206512, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 25, United-States, <=50K 28, State-gov, 38309, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 6849, 0, 40, United-States, <=50K 37, Private, 312766, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 52, Private, 139671, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 50, United-States, >50K 66, Federal-gov, 38621, Assoc-voc, 11, Widowed, Other-service, Unmarried, Black, Female, 3273, 0, 40, United-States, <=50K 31, Private, 124827, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 77820, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 45, Federal-gov, 56904, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 5013, 0, 45, United-States, <=50K 45, Private, 190115, Assoc-acdm, 12, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 106682, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 32, Local-gov, 42596, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 143058, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 60, United-States, >50K 53, Private, 102615, 11th, 7, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, Canada, <=50K 54, Private, 139703, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 3103, 0, 40, Germany, >50K 43, Private, 240124, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 132565, Some-college, 10, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 323798, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 3325, 0, 50, United-States, <=50K 52, Private, 96359, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 57, United-States, >50K 20, Private, 165201, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 4, United-States, <=50K 60, Federal-gov, 165630, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 1977, 40, United-States, >50K 45, Private, 264526, Assoc-acdm, 12, Divorced, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 102359, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 60, United-States, >50K 28, Private, 37359, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 61, ?, 232618, Prof-school, 15, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, >50K 48, Local-gov, 115497, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 157747, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 45, United-States, <=50K 27, Self-emp-not-inc, 41099, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 38, Private, 472604, Bachelors, 13, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 35, Mexico, <=50K 33, Private, 348618, 5th-6th, 3, Married-spouse-absent, Transport-moving, Unmarried, Other, Male, 0, 0, 20, El-Salvador, <=50K 43, Private, 135606, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 36, Private, 248445, HS-grad, 9, Separated, Transport-moving, Other-relative, White, Male, 0, 0, 60, Mexico, <=50K 38, Private, 112093, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Local-gov, 197552, HS-grad, 9, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 303822, 10th, 6, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 288566, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 55, ?, 487411, Masters, 14, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Self-emp-not-inc, 43348, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 55, United-States, >50K 39, State-gov, 239409, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 50, United-States, <=50K 50, Private, 337606, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 1485, 40, United-States, <=50K 34, Private, 32528, Assoc-voc, 11, Married-spouse-absent, Adm-clerical, Unmarried, White, Female, 0, 974, 40, United-States, <=50K 47, State-gov, 118447, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 46, Private, 234690, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, ?, 141003, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 0, 60, United-States, <=50K 43, Private, 216042, Some-college, 10, Divorced, Tech-support, Own-child, White, Female, 0, 1617, 72, United-States, <=50K 45, Private, 190482, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 381965, Bachelors, 13, Married-civ-spouse, Craft-repair, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 68, Private, 186943, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 8, United-States, <=50K 39, Private, 142707, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 53447, HS-grad, 9, Divorced, Farming-fishing, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 127772, Bachelors, 13, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 344414, Some-college, 10, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 194138, 11th, 7, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 20, United-States, <=50K 49, ?, 558183, Assoc-voc, 11, Married-spouse-absent, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 150154, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 306114, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 72, ?, 177121, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 3, United-States, <=50K 58, Local-gov, 368797, Masters, 14, Widowed, Prof-specialty, Unmarried, White, Male, 0, 0, 35, United-States, >50K 43, Self-emp-inc, 175715, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, Black, Male, 0, 0, 55, United-States, <=50K 62, Private, 416829, 11th, 7, Separated, Other-service, Not-in-family, Black, Female, 0, 0, 21, United-States, <=50K 21, Private, 350001, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 20, United-States, <=50K 26, Private, 339952, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 27, Private, 114967, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 164190, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 38, United-States, >50K 49, Local-gov, 166039, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 250135, HS-grad, 9, Never-married, Prof-specialty, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 34, Self-emp-not-inc, 234960, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 1887, 48, United-States, >50K 29, Private, 103628, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 58, Private, 430005, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 45, Self-emp-inc, 106517, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Self-emp-not-inc, 162236, Bachelors, 13, Never-married, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 53, Private, 92430, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 52, Local-gov, 40641, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 5013, 0, 40, United-States, <=50K 47, Private, 169388, 11th, 7, Divorced, Other-service, Unmarried, White, Female, 0, 0, 15, United-States, <=50K 36, Local-gov, 410034, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1887, 40, United-States, >50K 48, Private, 237525, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 65, United-States, >50K 35, Private, 150057, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 49, Private, 148549, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 50, United-States, >50K 43, Private, 75742, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 33, Private, 177675, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, Germany, >50K 49, Local-gov, 193249, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 266072, 10th, 6, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 20, El-Salvador, <=50K 28, ?, 80165, Some-college, 10, Divorced, ?, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 25, Private, 339324, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 69, ?, 111238, 9th, 5, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 20, United-States, <=50K 41, Self-emp-not-inc, 284086, Assoc-voc, 11, Divorced, Sales, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 31, Private, 206051, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 57, Private, 426263, Masters, 14, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 40, United-States, >50K 49, Private, 102583, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1848, 44, United-States, >50K 40, Private, 277647, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 55, Private, 124808, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 50, Germany, >50K 47, Private, 193061, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 50, Private, 121411, 12th, 8, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 89202, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 50, United-States, <=50K 17, Private, 232900, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 25, United-States, <=50K 30, Local-gov, 319280, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 79, ?, 165209, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 193494, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 67, Self-emp-not-inc, 195066, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 36, Private, 99146, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, >50K 35, Private, 92028, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 27, Private, 174419, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 57916, 7th-8th, 4, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 383384, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 198223, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 1902, 45, United-States, >50K 20, Private, 109813, 11th, 7, Never-married, Tech-support, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 174298, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 40, Private, 45687, Some-college, 10, Divorced, Other-service, Not-in-family, Black, Male, 4787, 0, 50, United-States, >50K 28, Private, 263614, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Private, 96128, 11th, 7, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 220262, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 55, Self-emp-not-inc, 35340, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 47, Private, 280483, HS-grad, 9, Separated, Craft-repair, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 52, Self-emp-inc, 254211, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 60, United-States, >50K 29, Private, 351324, Some-college, 10, Never-married, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 58602, 5th-6th, 3, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 37, Private, 64922, Bachelors, 13, Separated, Other-service, Not-in-family, White, Male, 0, 0, 70, England, <=50K 41, Federal-gov, 185616, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 1980, 40, United-States, <=50K 43, Private, 185832, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, >50K 24, Private, 254767, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 2105, 0, 50, United-States, <=50K 39, Federal-gov, 32312, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 47, Self-emp-not-inc, 109421, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 42, Private, 183205, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 39, Private, 156897, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 2258, 42, United-States, >50K 48, Local-gov, 145886, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 60, United-States, <=50K 47, Local-gov, 29819, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 1977, 50, United-States, >50K 27, Private, 244566, 10th, 6, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 253801, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Ecuador, <=50K 22, Private, 181313, Assoc-voc, 11, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 37, State-gov, 150566, HS-grad, 9, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 44, United-States, <=50K 38, Private, 237713, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 32, Private, 112137, Preschool, 1, Married-civ-spouse, Machine-op-inspct, Wife, Asian-Pac-Islander, Female, 4508, 0, 40, Cambodia, <=50K 48, Local-gov, 187969, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 80, United-States, <=50K 46, Self-emp-not-inc, 224108, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 50, United-States, <=50K 51, Private, 174754, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 38, United-States, <=50K 28, Self-emp-inc, 219705, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 5013, 0, 55, United-States, <=50K 35, Private, 167062, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 190325, 11th, 7, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 30, United-States, <=50K 45, Private, 108859, HS-grad, 9, Separated, Craft-repair, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 36, Self-emp-not-inc, 344351, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 73, Private, 153127, Some-college, 10, Widowed, Priv-house-serv, Unmarried, White, Female, 0, 0, 10, United-States, <=50K 52, Private, 180881, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 183066, 10th, 6, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 29, Federal-gov, 339002, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 185480, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, ?, >50K 20, Private, 172047, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 10, United-States, <=50K 42, Private, 94600, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 5178, 0, 40, United-States, >50K 37, Private, 302604, Some-college, 10, Separated, Other-service, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 248094, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 36467, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, >50K 29, Private, 53181, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 20, Private, 181032, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 248990, 11th, 7, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Private, 40512, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 3674, 0, 30, United-States, <=50K 37, Private, 117381, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 80, United-States, >50K 18, ?, 173125, 12th, 8, Never-married, ?, Own-child, White, Female, 0, 0, 24, United-States, <=50K 33, ?, 316663, Some-college, 10, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 50, United-States, <=50K 26, Private, 154966, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Puerto-Rico, <=50K 24, Private, 198259, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 30, United-States, <=50K 33, Private, 167939, HS-grad, 9, Married-civ-spouse, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 23, Private, 131275, HS-grad, 9, Never-married, Craft-repair, Own-child, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 20, ?, 236523, 10th, 6, Never-married, ?, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 36, Private, 272950, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 37, Private, 174503, Bachelors, 13, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 24, Private, 116800, Assoc-voc, 11, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 35, United-States, <=50K 38, Private, 110713, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 50, Private, 202044, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 44, Private, 300528, 11th, 7, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Private, 54985, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 1887, 40, United-States, >50K 57, Private, 133126, Some-college, 10, Never-married, Craft-repair, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 37, Private, 74593, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 70, United-States, <=50K 44, Private, 302424, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 21, Private, 344492, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 31, Private, 349148, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Private, 222221, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7298, 0, 42, United-States, >50K 45, Private, 234699, HS-grad, 9, Married-spouse-absent, Other-service, Unmarried, Black, Female, 0, 0, 60, United-States, >50K 20, Local-gov, 243178, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 189728, HS-grad, 9, Separated, Priv-house-serv, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 47, Self-emp-not-inc, 318593, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 25, United-States, <=50K 41, Private, 108681, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 187376, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 41, State-gov, 75409, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 46, Private, 172581, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 50, United-States, >50K 49, Private, 266150, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, United-States, <=50K 65, Private, 271092, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, ?, <=50K 50, Private, 135643, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Other-relative, Asian-Pac-Islander, Female, 0, 0, 40, China, <=50K 59, Private, 46466, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 18, Private, 130652, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 25, United-States, <=50K 47, Local-gov, 114459, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 45, United-States, >50K 47, ?, 109832, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 5178, 0, 30, Canada, >50K 45, Private, 195554, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, >50K 17, Private, 244589, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 45, Self-emp-inc, 271901, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 32, United-States, >50K 73, Private, 139978, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 180446, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 64, ?, 178724, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 20, United-States, <=50K 38, State-gov, 341643, Assoc-acdm, 12, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 37, Federal-gov, 289653, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, >50K 62, Self-emp-inc, 118725, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 20051, 0, 72, United-States, >50K 26, Private, 187891, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 46, Self-emp-inc, 116338, Masters, 14, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 50, United-States, >50K 46, Private, 102771, Masters, 14, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 1977, 40, United-States, >50K 51, Private, 89652, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 4787, 0, 24, United-States, >50K 54, Federal-gov, 439608, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 65, Private, 330144, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 251905, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 37, Private, 218955, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Self-emp-not-inc, 188972, Doctorate, 16, Separated, Prof-specialty, Unmarried, White, Female, 0, 0, 10, Canada, <=50K 60, Self-emp-not-inc, 25825, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 33, Private, 202046, Bachelors, 13, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 2001, 40, United-States, <=50K 62, Private, 116104, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 20, Germany, <=50K 20, Private, 194891, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 125550, HS-grad, 9, Never-married, Tech-support, Not-in-family, White, Female, 14084, 0, 35, United-States, >50K 66, Private, 116468, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 2936, 0, 20, United-States, <=50K 32, ?, 285131, Assoc-acdm, 12, Never-married, ?, Unmarried, White, Male, 0, 0, 20, United-States, <=50K 29, State-gov, 409201, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 70, Self-emp-inc, 379819, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 10566, 0, 40, United-States, <=50K 74, Private, 97167, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 15, United-States, <=50K 37, Local-gov, 244803, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, ?, <=50K 51, Self-emp-not-inc, 115851, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 118058, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 42, Private, 258589, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 26, Private, 158810, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 27, Local-gov, 92431, Some-college, 10, Never-married, Protective-serv, Not-in-family, White, Male, 0, 2231, 40, United-States, >50K 58, Self-emp-not-inc, 165695, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 30, ?, 97281, Some-college, 10, Separated, ?, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 32, Private, 244147, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 1876, 50, United-States, <=50K 66, Self-emp-inc, 253741, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 1825, 10, United-States, >50K 23, Private, 170482, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 45, United-States, <=50K 35, Private, 241001, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 44, United-States, <=50K 50, Private, 165001, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 17, ?, 297117, 11th, 7, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 340260, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 48, United-States, <=50K 31, Private, 96480, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 30, Private, 185177, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 49, United-States, <=50K 84, Self-emp-inc, 172907, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 35, United-States, >50K 35, Self-emp-not-inc, 308874, HS-grad, 9, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 45, Self-emp-not-inc, 54098, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, >50K 46, Private, 288608, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 50, Local-gov, 254148, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, Mexico, <=50K 37, Private, 111128, 11th, 7, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 171116, HS-grad, 9, Divorced, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 53, Self-emp-inc, 96062, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 48, United-States, >50K 27, Federal-gov, 276776, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 22, Private, 152878, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 149211, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 58343, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 44, United-States, <=50K 38, Private, 127601, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Wife, White, Female, 0, 0, 35, United-States, <=50K 29, Private, 357781, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 137367, Some-college, 10, Never-married, Handlers-cleaners, Other-relative, Asian-Pac-Islander, Male, 0, 0, 44, Philippines, <=50K 34, Private, 110978, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 31, Private, 34503, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Private, 84119, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 2051, 40, United-States, <=50K 20, Private, 223515, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 372525, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Male, 0, 0, 48, United-States, <=50K 32, Private, 116365, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 20, United-States, <=50K 36, Private, 111268, Assoc-acdm, 12, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 54, Private, 225599, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 7298, 0, 40, India, >50K 78, ?, 83511, 7th-8th, 4, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, Portugal, <=50K 46, Self-emp-not-inc, 199596, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 18, Private, 301867, HS-grad, 9, Never-married, Sales, Own-child, Amer-Indian-Eskimo, Female, 0, 0, 20, United-States, <=50K 57, Private, 191983, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 50, United-States, <=50K 37, Private, 105803, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 456236, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 45, Private, 116255, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 32, Private, 235109, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 38, Federal-gov, 91716, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 121102, Assoc-acdm, 12, Never-married, Tech-support, Not-in-family, White, Female, 0, 2001, 30, United-States, <=50K 70, Private, 235781, Some-college, 10, Divorced, Farming-fishing, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, Vietnam, <=50K 40, Private, 136986, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, >50K 40, Self-emp-not-inc, 33658, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 53878, HS-grad, 9, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 200928, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 24, Private, 173736, Assoc-voc, 11, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 28, Private, 214385, Assoc-voc, 11, Never-married, Exec-managerial, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 58, Private, 102509, 10th, 6, Divorced, Transport-moving, Not-in-family, Black, Male, 0, 0, 50, United-States, <=50K 38, Private, 173047, Bachelors, 13, Divorced, Adm-clerical, Unmarried, Asian-Pac-Islander, Female, 0, 213, 40, Philippines, <=50K 59, Self-emp-not-inc, 241297, Some-college, 10, Widowed, Farming-fishing, Not-in-family, White, Female, 6849, 0, 40, United-States, <=50K 18, Private, 329054, 11th, 7, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 15, United-States, <=50K 40, Private, 274158, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Self-emp-inc, 241153, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 35, Private, 200117, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 1887, 50, ?, >50K 45, Private, 229516, HS-grad, 9, Married-spouse-absent, Craft-repair, Not-in-family, White, Male, 0, 0, 72, Mexico, <=50K 62, ?, 250091, Bachelors, 13, Divorced, ?, Not-in-family, White, Male, 0, 0, 5, United-States, <=50K 24, State-gov, 247075, HS-grad, 9, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 20, United-States, <=50K 22, Private, 315524, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Male, 0, 0, 30, Dominican-Republic, <=50K 23, Private, 126945, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Self-emp-not-inc, 29874, Some-college, 10, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 28, Private, 115579, Assoc-voc, 11, Never-married, Tech-support, Own-child, White, Female, 0, 0, 38, United-States, <=50K 51, Private, 29580, 11th, 7, Married-civ-spouse, Sales, Husband, White, Male, 4386, 0, 30, United-States, >50K 44, Private, 56483, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 37, United-States, <=50K 73, ?, 89852, 1st-4th, 2, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, Portugal, <=50K 24, Private, 420779, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, Black, Male, 0, 0, 35, United-States, <=50K 24, Private, 255474, 11th, 7, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 241444, 1st-4th, 2, Married-civ-spouse, Craft-repair, Husband, Other, Male, 0, 0, 50, Puerto-Rico, <=50K 43, Private, 85995, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 67, Self-emp-inc, 116986, 12th, 8, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 20, United-States, <=50K 31, Private, 217962, 12th, 8, Never-married, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 40, ?, <=50K 36, Private, 20507, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 7688, 0, 50, United-States, >50K 43, Private, 184099, Assoc-acdm, 12, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 117816, 7th-8th, 4, Divorced, Handlers-cleaners, Other-relative, White, Male, 0, 0, 70, United-States, <=50K 23, Private, 263899, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Male, 0, 0, 20, Haiti, <=50K 26, Private, 45869, Bachelors, 13, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 186539, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 326310, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 44, United-States, <=50K 55, Local-gov, 84564, Prof-school, 15, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 39, United-States, <=50K 49, Private, 247294, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 34, Private, 72793, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 29, Private, 261375, HS-grad, 9, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 60, United-States, <=50K 50, Private, 77905, Bachelors, 13, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 8, United-States, <=50K 19, Private, 66838, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 9, United-States, <=50K 63, State-gov, 194682, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 50, United-States, >50K 66, Private, 180211, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 30, Philippines, <=50K 65, ?, 79272, Some-college, 10, Widowed, ?, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 6, United-States, <=50K 60, Private, 101198, Assoc-voc, 11, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 60, Private, 80574, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 19, Private, 198663, HS-grad, 9, Never-married, Tech-support, Own-child, White, Male, 0, 0, 40, United-States, <=50K 26, Self-emp-inc, 160340, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 75, Self-emp-not-inc, 205860, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 1735, 40, United-States, <=50K 58, State-gov, 69579, Some-college, 10, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 18, Self-emp-not-inc, 379242, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 65, Private, 113323, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 3818, 0, 40, United-States, <=50K 50, Self-emp-not-inc, 312477, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1887, 40, United-States, >50K 26, Private, 259505, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 45, Federal-gov, 171335, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 19, ?, 541282, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 29, Federal-gov, 155970, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 52, Private, 99682, Some-college, 10, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 52, Canada, >50K 23, Private, 117789, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 296158, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 48, Local-gov, 78859, HS-grad, 9, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 59, ?, 188070, Masters, 14, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 35, United-States, >50K 50, Private, 189811, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 41, State-gov, 518030, Bachelors, 13, Never-married, Protective-serv, Not-in-family, Black, Male, 0, 1590, 40, Puerto-Rico, <=50K 32, Private, 360593, HS-grad, 9, Divorced, Sales, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 40, Private, 145504, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, Black, Male, 0, 0, 40, United-States, <=50K 19, Private, 459248, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 30, ?, 288419, 5th-6th, 3, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, Mexico, <=50K 42, State-gov, 126094, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Male, 0, 0, 39, United-States, <=50K 23, Private, 209483, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 50, United-States, <=50K 37, Self-emp-not-inc, 32239, HS-grad, 9, Divorced, Farming-fishing, Not-in-family, White, Male, 27828, 0, 40, United-States, >50K 21, Private, 210355, 11th, 7, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 24, United-States, <=50K 28, Private, 84547, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 50, ?, 260579, HS-grad, 9, Married-civ-spouse, ?, Husband, Black, Male, 0, 0, 40, United-States, <=50K 20, Private, 105585, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 25, United-States, <=50K 21, Private, 132320, 11th, 7, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 21, Private, 129172, Some-college, 10, Never-married, Other-service, Other-relative, White, Male, 0, 0, 16, United-States, <=50K 45, Self-emp-not-inc, 222374, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 49, Self-emp-inc, 201498, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 53, Self-emp-inc, 251675, Some-college, 10, Divorced, Sales, Not-in-family, White, Male, 8614, 0, 50, Cuba, >50K 41, Private, 114157, HS-grad, 9, Divorced, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 48, Local-gov, 148121, Bachelors, 13, Married-spouse-absent, Adm-clerical, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 73, ?, 84053, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 34, Private, 96480, Some-college, 10, Separated, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 179423, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 58, State-gov, 123329, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 16, United-States, <=50K 41, Private, 134130, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 53, Private, 188644, Preschool, 1, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Mexico, <=50K 40, Private, 226388, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 28, Self-emp-not-inc, 209205, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 40, United-States, >50K 32, Private, 209808, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 1740, 47, United-States, <=50K 44, Self-emp-inc, 56236, Some-college, 10, Never-married, Exec-managerial, Not-in-family, Black, Male, 2202, 0, 45, United-States, <=50K 18, Private, 28648, 11th, 7, Never-married, Other-service, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 37, State-gov, 34996, HS-grad, 9, Separated, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 281422, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 45, United-States, <=50K 22, Private, 214716, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 314177, 10th, 6, Never-married, Handlers-cleaners, Other-relative, Black, Male, 0, 0, 40, United-States, <=50K 51, Private, 112310, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 63, Private, 203783, HS-grad, 9, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 72, United-States, <=50K 29, Private, 205499, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 45, United-States, <=50K 44, Private, 145441, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 48, United-States, >50K 44, Private, 155701, 7th-8th, 4, Separated, Other-service, Unmarried, White, Female, 0, 0, 38, Peru, <=50K 37, State-gov, 186934, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 62, Federal-gov, 209433, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, <=50K 31, Private, 80933, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 52, United-States, <=50K 20, Private, 102607, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 30, United-States, <=50K 48, Private, 254809, 10th, 6, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 1594, 32, United-States, <=50K 24, Self-emp-not-inc, 102942, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 56, State-gov, 175057, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Federal-gov, 68781, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 35, United-States, <=50K 29, Private, 108594, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 98283, Prof-school, 15, Never-married, Tech-support, Not-in-family, Asian-Pac-Islander, Male, 0, 1564, 40, India, >50K 39, Private, 56269, Some-college, 10, Never-married, Craft-repair, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 29, Private, 152503, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 45, United-States, <=50K 38, Self-emp-inc, 206951, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 65, United-States, <=50K 23, Private, 82393, 9th, 5, Never-married, Other-service, Own-child, Asian-Pac-Islander, Male, 0, 0, 20, Philippines, <=50K 37, Private, 167396, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Guatemala, <=50K 30, Self-emp-not-inc, 123397, Some-college, 10, Divorced, Other-service, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 58, ?, 147653, Some-college, 10, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 36, United-States, <=50K 42, Private, 118652, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 59, Local-gov, 114401, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Female, 0, 1504, 19, United-States, <=50K 45, Private, 186272, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 7298, 0, 40, United-States, >50K 46, Private, 182689, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 231016, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 4650, 0, 37, United-States, <=50K 41, Self-emp-inc, 60949, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 49, Private, 129513, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 37, Private, 84306, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 117507, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 22, Private, 88050, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 6, United-States, <=50K 22, Private, 305498, HS-grad, 9, Divorced, Sales, Own-child, White, Female, 0, 0, 33, United-States, <=50K 17, Private, 295308, 11th, 7, Never-married, Priv-house-serv, Own-child, White, Female, 0, 0, 20, United-States, <=50K 47, Private, 114459, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 17, Private, 176017, 10th, 6, Never-married, Other-service, Other-relative, White, Male, 0, 0, 15, United-States, <=50K 39, Private, 248445, 5th-6th, 3, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Mexico, <=50K 23, Private, 214542, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 20, United-States, <=50K 41, Private, 384508, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Federal-gov, 403489, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 52, Private, 143953, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 40, United-States, >50K 21, Private, 254904, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 33, Private, 98995, 10th, 6, Divorced, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 36, United-States, <=50K 17, ?, 237078, 11th, 7, Never-married, ?, Own-child, White, Female, 0, 0, 35, United-States, <=50K 41, Private, 193995, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 44, United-States, <=50K 19, Private, 205829, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 35, United-States, <=50K 38, Federal-gov, 205852, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 24, Private, 37072, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 275338, Bachelors, 13, Divorced, Sales, Unmarried, White, Female, 1151, 0, 40, United-States, <=50K 39, State-gov, 122353, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 19, Private, 100009, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 15, United-States, <=50K 31, ?, 37030, Assoc-acdm, 12, Never-married, ?, Own-child, White, Female, 0, 0, 25, United-States, <=50K 42, Private, 135056, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 135162, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 45, ?, <=50K 29, Private, 280618, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 226717, 12th, 8, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, United-States, <=50K 47, Local-gov, 173938, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 24, Private, 291355, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 61, Federal-gov, 160155, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Self-emp-not-inc, 29762, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 31, ?, 82473, 9th, 5, Divorced, ?, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 59, Private, 172071, HS-grad, 9, Married-civ-spouse, Prof-specialty, Wife, Black, Female, 0, 0, 38, Jamaica, <=50K 29, Private, 166210, Some-college, 10, Divorced, Tech-support, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 26, Private, 330263, HS-grad, 9, Separated, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 247043, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 56, Federal-gov, 155238, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Private, 130557, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 17, Private, 56986, 12th, 8, Never-married, Sales, Own-child, White, Female, 0, 0, 18, United-States, <=50K 29, Private, 220692, Assoc-voc, 11, Never-married, Exec-managerial, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 23, Private, 121650, 5th-6th, 3, Never-married, Handlers-cleaners, Unmarried, White, Male, 0, 0, 30, United-States, <=50K 67, Private, 174603, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 29, Private, 341846, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 33, Private, 99339, Assoc-acdm, 12, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 880, 40, United-States, <=50K 32, Private, 34437, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 141058, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 62, Mexico, <=50K 49, Private, 192323, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Self-emp-not-inc, 117674, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, ?, <=50K 39, Private, 28572, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 120277, Bachelors, 13, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 164309, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 47, Federal-gov, 102771, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 147951, HS-grad, 9, Never-married, Machine-op-inspct, Other-relative, White, Male, 0, 0, 1, United-States, <=50K 23, Private, 188409, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 4508, 0, 25, United-States, <=50K 44, Private, 173888, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 80, United-States, >50K 25, Private, 247006, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 23, Private, 82889, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 16, United-States, <=50K 52, Private, 259363, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 62, Federal-gov, 159165, HS-grad, 9, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 36, United-States, <=50K 31, Private, 112062, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 299050, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 22, ?, 186452, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 36, United-States, <=50K 53, Private, 548580, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Guatemala, <=50K 25, Private, 234057, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 241350, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 69, Private, 108196, 9th, 5, Never-married, Craft-repair, Other-relative, White, Male, 2993, 0, 40, United-States, <=50K 49, Private, 278322, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Private, 157443, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, Asian-Pac-Islander, Female, 0, 0, 27, Taiwan, >50K 44, Self-emp-not-inc, 37618, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, >50K 56, Local-gov, 238582, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 41, United-States, >50K 37, State-gov, 28887, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Private, 77820, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 22, Private, 110946, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Local-gov, 230420, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 206521, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 54, ?, 156877, HS-grad, 9, Divorced, ?, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 28, Local-gov, 283227, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 65, United-States, <=50K 28, Private, 141957, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 36, Private, 58337, 10th, 6, Never-married, Sales, Unmarried, White, Female, 0, 0, 35, ?, <=50K 73, Local-gov, 161027, 5th-6th, 3, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 20, United-States, <=50K 37, Self-emp-not-inc, 31670, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 24, Private, 205844, Bachelors, 13, Never-married, Exec-managerial, Own-child, Black, Female, 0, 0, 65, United-States, <=50K 30, State-gov, 46144, HS-grad, 9, Married-AF-spouse, Adm-clerical, Own-child, White, Female, 0, 0, 38, United-States, <=50K 38, Private, 168055, Assoc-voc, 11, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 98350, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, >50K 69, ?, 182668, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 45, United-States, >50K 43, Private, 208613, Prof-school, 15, Married-spouse-absent, Prof-specialty, Not-in-family, White, Male, 99999, 0, 40, United-States, >50K 42, Private, 334522, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, United-States, <=50K 54, State-gov, 187686, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 27, State-gov, 365916, Assoc-acdm, 12, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 58, United-States, <=50K 39, Private, 190719, Some-college, 10, Divorced, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 27, Private, 218184, Some-college, 10, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, Jamaica, <=50K 30, Private, 222162, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 66, United-States, <=50K 30, Private, 148524, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 2057, 40, United-States, <=50K 37, Private, 267085, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Federal-gov, 307555, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 36, Private, 229180, Some-college, 10, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 40, Cuba, <=50K 22, Private, 279041, Some-college, 10, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 10, United-States, <=50K 21, Private, 312017, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 54782, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 1579, 42, United-States, <=50K 76, Private, 70697, 7th-8th, 4, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 22, ?, 263970, Some-college, 10, Never-married, ?, Not-in-family, White, Female, 0, 0, 28, United-States, <=50K 37, Private, 188774, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 302770, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 29, Private, 183639, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 97, United-States, <=50K 29, Private, 178551, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 175343, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 73, Self-emp-not-inc, 190078, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 35, United-States, <=50K 43, Private, 117627, Some-college, 10, Divorced, Exec-managerial, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 39, Private, 108419, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 74, Private, 183701, 10th, 6, Widowed, Other-service, Not-in-family, Black, Female, 0, 0, 6, United-States, <=50K 27, State-gov, 208406, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 47, Private, 148884, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 90, Private, 87285, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 24, United-States, <=50K 47, Private, 199058, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 42, Private, 173628, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 69, Private, 370837, Bachelors, 13, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 18, ?, 179484, 12th, 8, Never-married, ?, Own-child, Other, Male, 0, 0, 40, United-States, <=50K 23, Private, 342769, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 44, Local-gov, 65145, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 30, United-States, <=50K 41, Private, 150533, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 2829, 0, 40, United-States, <=50K 47, Local-gov, 272182, Some-college, 10, Never-married, Adm-clerical, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 43, Private, 403467, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 7688, 0, 40, United-States, >50K 33, Private, 252168, Some-college, 10, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 48, Private, 80430, 11th, 7, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 39, Private, 189623, Bachelors, 13, Divorced, Sales, Unmarried, White, Male, 0, 0, 60, United-States, <=50K 43, Private, 115806, Masters, 14, Divorced, Exec-managerial, Unmarried, White, Female, 0, 2547, 40, United-States, >50K 18, ?, 28357, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 20, United-States, <=50K 52, Private, 226084, HS-grad, 9, Widowed, Priv-house-serv, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 150817, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 27, Self-emp-inc, 190911, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 45, United-States, <=50K 27, Self-emp-inc, 120126, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1887, 45, United-States, >50K 45, Local-gov, 255559, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 79, ?, 142370, Prof-school, 15, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 10, United-States, <=50K 24, Private, 173679, Assoc-voc, 11, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 20, United-States, <=50K 25, Private, 35854, Some-college, 10, Married-spouse-absent, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 42, Self-emp-not-inc, 82161, 10th, 6, Widowed, Transport-moving, Unmarried, White, Male, 0, 0, 35, United-States, <=50K 63, Self-emp-not-inc, 129845, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 226505, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 46, United-States, >50K 47, Private, 151584, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 60, United-States, >50K 42, Private, 136419, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 42, Private, 66460, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 63, Local-gov, 379940, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Local-gov, 102936, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 55, United-States, <=50K 65, Private, 205309, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 20, United-States, <=50K 30, ?, 156890, 10th, 6, Divorced, ?, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 62, Private, 208711, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 7688, 0, 50, United-States, >50K 46, Private, 137547, HS-grad, 9, Divorced, Craft-repair, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 23, Private, 220168, HS-grad, 9, Never-married, Sales, Other-relative, Black, Female, 0, 0, 25, Jamaica, <=50K 47, Local-gov, 37672, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 45, United-States, <=50K 20, Private, 196643, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 21, ?, 355686, HS-grad, 9, Never-married, ?, Own-child, White, Female, 0, 0, 10, United-States, <=50K 28, Private, 197484, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 61, Local-gov, 115023, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, State-gov, 234824, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 72, United-States, <=50K 30, State-gov, 361497, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 72, United-States, >50K 29, Private, 351871, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 39, Private, 324231, HS-grad, 9, Widowed, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 23, Private, 123490, 11th, 7, Divorced, Other-service, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 32, Private, 188245, 11th, 7, Never-married, Priv-house-serv, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 63, Private, 50349, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 34, United-States, <=50K 19, Self-emp-not-inc, 47176, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 57, State-gov, 290661, Doctorate, 16, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 41, Private, 221172, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Private, 188950, Assoc-voc, 11, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 356882, Doctorate, 16, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 20, United-States, <=50K 43, Self-emp-inc, 150533, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 64, Self-emp-not-inc, 167149, 7th-8th, 4, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 25, United-States, <=50K 56, Private, 301835, 5th-6th, 3, Separated, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 313729, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 130957, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 17, Private, 197732, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 12, United-States, <=50K 17, Private, 250541, 10th, 6, Never-married, Other-service, Own-child, Black, Male, 0, 0, 20, United-States, <=50K 29, Private, 218785, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 65, United-States, <=50K 23, ?, 232512, HS-grad, 9, Separated, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 194630, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 39, Private, 38721, HS-grad, 9, Divorced, Priv-house-serv, Unmarried, White, Female, 0, 0, 22, United-States, <=50K 36, Private, 201519, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 50, Private, 279337, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 55, United-States, >50K 41, ?, 27187, Assoc-voc, 11, Married-civ-spouse, ?, Husband, White, Male, 0, 2415, 12, United-States, >50K 31, Private, 87560, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 71, ?, 100820, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 2489, 15, United-States, <=50K 56, Private, 208431, Some-college, 10, Widowed, Exec-managerial, Not-in-family, Black, Female, 0, 0, 32, United-States, <=50K 51, Private, 143822, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 40, United-States, >50K 20, Private, 163205, Some-college, 10, Separated, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 53, Private, 171924, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 14344, 0, 55, United-States, >50K 33, State-gov, 137616, Masters, 14, Never-married, Prof-specialty, Not-in-family, Black, Female, 0, 0, 35, United-States, <=50K 27, Private, 156516, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 2377, 20, United-States, <=50K 40, Private, 119101, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 5178, 0, 40, United-States, >50K 45, Private, 117556, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 32, United-States, <=50K 54, Private, 147863, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 5013, 0, 40, Vietnam, <=50K 33, Self-emp-not-inc, 24504, HS-grad, 9, Separated, Craft-repair, Other-relative, White, Male, 0, 0, 50, United-States, <=50K 27, ?, 157624, HS-grad, 9, Separated, ?, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 181721, 10th, 6, Never-married, Farming-fishing, Own-child, Black, Male, 0, 0, 60, United-States, <=50K 42, Local-gov, 55363, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 33, Private, 92865, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 258633, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 25, ?, <=50K 52, Federal-gov, 221532, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 41, Local-gov, 183224, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, Asian-Pac-Islander, Female, 0, 0, 40, Taiwan, >50K 30, Private, 381153, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 300871, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 33710, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 3103, 0, 60, United-States, >50K 26, Private, 158333, 5th-6th, 3, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, Columbia, <=50K 36, Private, 288103, 11th, 7, Separated, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 35, Private, 108907, HS-grad, 9, Separated, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 358533, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 40, United-States, >50K 24, Private, 126613, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 8, United-States, <=50K 30, Private, 164190, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 5178, 0, 52, United-States, >50K 38, Private, 199816, HS-grad, 9, Divorced, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 98228, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 41, Local-gov, 129060, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 38, Private, 22245, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 36, Private, 226918, Bachelors, 13, Never-married, Sales, Not-in-family, Black, Male, 0, 0, 48, United-States, <=50K 47, Private, 398652, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 59, Private, 268840, Some-college, 10, Married-civ-spouse, Adm-clerical, Other-relative, White, Female, 0, 0, 16, United-States, >50K 35, ?, 103710, Bachelors, 13, Divorced, ?, Unmarried, White, Female, 0, 0, 16, ?, <=50K 59, Private, 91384, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 52, Private, 174767, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 37, Self-emp-inc, 126675, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 52, Private, 82285, Bachelors, 13, Married-spouse-absent, Other-service, Other-relative, Black, Female, 0, 0, 40, Haiti, <=50K 51, Private, 177727, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 67, Self-emp-not-inc, 345236, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, <=50K 58, ?, 347692, 11th, 7, Divorced, ?, Not-in-family, Black, Male, 0, 0, 15, United-States, <=50K 68, Private, 156000, 10th, 6, Widowed, Other-service, Unmarried, Black, Female, 0, 0, 20, United-States, <=50K 71, Private, 228806, 9th, 5, Divorced, Priv-house-serv, Not-in-family, Black, Female, 0, 0, 6, United-States, <=50K 49, Local-gov, 184428, Masters, 14, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Local-gov, 102938, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 161063, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 253752, 10th, 6, Married-civ-spouse, Farming-fishing, Wife, White, Female, 0, 0, 40, United-States, <=50K 47, Self-emp-not-inc, 274800, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 31, Private, 129804, 9th, 5, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, Puerto-Rico, <=50K 22, Federal-gov, 65547, Some-college, 10, Never-married, Exec-managerial, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 20, Private, 107658, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 10, United-States, <=50K 57, Private, 161097, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 26, United-States, <=50K 18, Private, 118376, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 32, Private, 131224, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 120985, HS-grad, 9, Divorced, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 215392, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 63685, HS-grad, 9, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 0, 50, Cambodia, <=50K 48, Private, 131826, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 211440, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 55, United-States, >50K 35, Private, 31023, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 40, Private, 145439, 5th-6th, 3, Married-civ-spouse, Other-service, Husband, Other, Male, 4064, 0, 40, Mexico, <=50K 19, Private, 255161, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 25, United-States, <=50K 28, Private, 411950, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 275818, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 1974, 40, United-States, <=50K 18, Private, 318082, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 35, United-States, <=50K 23, Local-gov, 287988, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 47, Local-gov, 138342, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 3411, 0, 40, El-Salvador, <=50K 42, Federal-gov, 115932, Bachelors, 13, Divorced, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 60358, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 140117, 10th, 6, Never-married, Sales, Own-child, White, Female, 0, 0, 12, United-States, <=50K 34, Private, 158040, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 30, Self-emp-inc, 321990, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 60, ?, >50K 29, Private, 232784, Assoc-acdm, 12, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 349368, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 46, Federal-gov, 325573, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 69, Private, 140176, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 24, United-States, <=50K 50, Private, 128478, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, >50K 19, ?, 318264, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 30, United-States, <=50K 59, Private, 147989, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, ?, <=50K 45, Federal-gov, 155659, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 41, State-gov, 288433, Masters, 14, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 47, Federal-gov, 329205, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 64, Private, 171373, 11th, 7, Widowed, Farming-fishing, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 228860, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 35, United-States, <=50K 29, Private, 196116, Prof-school, 15, Divorced, Prof-specialty, Own-child, White, Female, 2174, 0, 72, United-States, <=50K 17, Private, 47771, 11th, 7, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 20, United-States, <=50K 24, Private, 201680, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Male, 0, 0, 60, United-States, <=50K 28, Private, 337378, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 246449, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 3325, 0, 50, United-States, <=50K 48, Private, 227714, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 36, Private, 177285, Assoc-voc, 11, Never-married, Prof-specialty, Unmarried, Black, Female, 0, 0, 38, United-States, <=50K 38, Private, 71701, Assoc-voc, 11, Never-married, Craft-repair, Not-in-family, White, Female, 0, 0, 40, Portugal, <=50K 49, Private, 30219, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 1669, 40, United-States, <=50K 42, Private, 280167, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Self-emp-inc, 27408, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 25, Private, 167031, 10th, 6, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, Columbia, <=50K 41, Private, 173682, Masters, 14, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Self-emp-not-inc, 278557, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 30, United-States, <=50K 32, Private, 113688, Assoc-voc, 11, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 41, Self-emp-not-inc, 252986, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 48, Private, 33669, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 56, Private, 100776, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 50, United-States, <=50K 47, Self-emp-not-inc, 177457, Some-college, 10, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 40, United-States, <=50K 30, State-gov, 312767, HS-grad, 9, Never-married, Sales, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 51, Private, 43354, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 22, Self-emp-inc, 375422, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, South, <=50K 49, Self-emp-not-inc, 263568, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 67, ?, 74335, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 10, Germany, <=50K 26, Private, 302097, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 3464, 0, 48, United-States, <=50K 35, Private, 248010, Bachelors, 13, Married-spouse-absent, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 37, ?, 87369, 9th, 5, Divorced, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 405577, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 51, State-gov, 167065, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 102476, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Federal-gov, 526528, Some-college, 10, Never-married, Adm-clerical, Unmarried, Black, Female, 3887, 0, 40, United-States, <=50K 32, Private, 175878, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 55, Private, 213894, 11th, 7, Separated, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 17, Private, 150262, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 40, Private, 75363, Some-college, 10, Separated, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 272671, Bachelors, 13, Divorced, Sales, Own-child, White, Male, 0, 0, 50, United-States, <=50K 67, Self-emp-inc, 411007, HS-grad, 9, Widowed, Exec-managerial, Not-in-family, White, Female, 15831, 0, 40, United-States, >50K 44, Private, 222434, HS-grad, 9, Divorced, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 180246, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 40, United-States, >50K 25, Private, 171236, HS-grad, 9, Divorced, Handlers-cleaners, Own-child, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 367037, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 304651, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, >50K 62, Private, 97017, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 20, Private, 146879, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 2001, 40, United-States, <=50K 45, State-gov, 320818, Some-college, 10, Married-spouse-absent, Other-service, Other-relative, Black, Male, 0, 0, 40, Haiti, <=50K 47, Self-emp-not-inc, 84735, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 20, United-States, >50K 49, Private, 184428, Bachelors, 13, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 326886, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 24, ?, 169624, HS-grad, 9, Divorced, ?, Unmarried, Black, Female, 0, 0, 37, United-States, <=50K 29, Private, 212102, HS-grad, 9, Separated, Other-service, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 23, Private, 175837, 11th, 7, Never-married, Farming-fishing, Other-relative, White, Female, 0, 0, 40, Puerto-Rico, <=50K 50, Private, 177487, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 286750, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 1902, 40, United-States, >50K 44, Private, 171424, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Private, 194981, HS-grad, 9, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 36, United-States, <=50K 73, Private, 199362, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 30, United-States, <=50K 24, Private, 204226, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 46, State-gov, 72506, HS-grad, 9, Married-civ-spouse, Other-service, Wife, Black, Female, 0, 0, 40, United-States, <=50K 61, Self-emp-inc, 61040, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 36, United-States, >50K 37, Federal-gov, 194630, Masters, 14, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 391867, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Private, 94080, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 17, Private, 289405, 11th, 7, Never-married, Machine-op-inspct, Own-child, Other, Male, 0, 0, 12, United-States, <=50K 30, Private, 170130, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 158118, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 1719, 40, United-States, <=50K 30, Private, 447739, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 90, ?, 39824, HS-grad, 9, Widowed, ?, Not-in-family, White, Male, 401, 0, 4, United-States, <=50K 76, ?, 312500, 5th-6th, 3, Widowed, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 223342, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 1504, 35, United-States, <=50K 65, ?, 293385, Preschool, 1, Married-civ-spouse, ?, Husband, Black, Male, 0, 0, 30, United-States, <=50K 25, Private, 106377, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 66118, Bachelors, 13, Divorced, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 274883, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Local-gov, 123773, Assoc-acdm, 12, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 42, Local-gov, 70655, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 44, United-States, <=50K 49, Private, 177426, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 37, Private, 200374, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 1902, 40, United-States, >50K 19, State-gov, 159269, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 15, United-States, <=50K 24, Private, 235894, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 38, United-States, <=50K 34, Local-gov, 97723, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Private, 167309, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Self-emp-not-inc, 98106, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 37, Federal-gov, 22201, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 7298, 0, 40, Philippines, >50K 45, Private, 108993, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 265954, Bachelors, 13, Never-married, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 58, Self-emp-inc, 100960, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 45, Private, 170092, Some-college, 10, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 54, Private, 326156, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 45, Private, 216932, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 69, Private, 36956, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 20051, 0, 50, United-States, >50K 24, Private, 214014, HS-grad, 9, Never-married, Craft-repair, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 36, Private, 99872, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, India, <=50K 61, State-gov, 151459, 10th, 6, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 38, United-States, <=50K 57, Self-emp-inc, 161662, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 60, United-States, >50K 56, Private, 367200, HS-grad, 9, Divorced, Craft-repair, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 86648, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 45, United-States, >50K 51, Local-gov, 168539, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 50, Private, 140741, 11th, 7, Never-married, Machine-op-inspct, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 197651, Some-college, 10, Never-married, Tech-support, Own-child, White, Female, 0, 0, 43, United-States, <=50K 46, Private, 123053, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 50, Japan, >50K 23, Private, 330571, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 25, United-States, <=50K 44, Private, 204235, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, State-gov, 346766, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 35, ?, 257250, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 163396, Some-college, 10, Never-married, Tech-support, Not-in-family, Other, Female, 0, 0, 40, United-States, <=50K 78, ?, 135839, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 1086, 0, 20, United-States, <=50K 18, Private, 36251, 10th, 6, Never-married, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 40, Private, 149102, HS-grad, 9, Married-spouse-absent, Handlers-cleaners, Not-in-family, White, Male, 2174, 0, 60, Poland, <=50K 61, ?, 222395, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, State-gov, 29152, 12th, 8, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 79303, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 45, United-States, <=50K 35, Private, 272338, Assoc-voc, 11, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 55, State-gov, 200497, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 19, Private, 148392, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 30, United-States, <=50K 31, Private, 164243, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1579, 40, United-States, <=50K 43, State-gov, 129298, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 49, Local-gov, 174981, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 47, United-States, >50K 48, Local-gov, 328610, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 27, Private, 77774, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 34, United-States, <=50K 38, State-gov, 134069, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 60, United-States, >50K 35, Private, 209214, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 4386, 0, 35, United-States, >50K 29, Private, 153805, HS-grad, 9, Never-married, Machine-op-inspct, Other-relative, Other, Male, 0, 0, 40, Ecuador, <=50K 27, Private, 168827, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 0, 2, United-States, <=50K 31, Private, 373432, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 43, United-States, <=50K 26, Private, 57600, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 53, Self-emp-not-inc, 302847, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 35, United-States, <=50K 23, Private, 227594, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 32, Federal-gov, 44777, HS-grad, 9, Separated, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 46, United-States, <=50K 54, ?, 133963, HS-grad, 9, Widowed, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 279615, Bachelors, 13, Divorced, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 276133, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 62, Private, 136314, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 204410, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1485, 44, United-States, >50K 59, Self-emp-inc, 223215, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 50, United-States, >50K 43, Private, 184625, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 34, Self-emp-inc, 265917, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 158647, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 22055, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, Amer-Indian-Eskimo, Male, 0, 0, 60, United-States, <=50K 41, Local-gov, 176716, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 42, Private, 270721, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 32, United-States, <=50K 24, Private, 100321, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 35, Private, 79050, HS-grad, 9, Never-married, Transport-moving, Unmarried, Black, Male, 0, 0, 72, United-States, <=50K 40, Local-gov, 42703, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 46, Private, 116952, 7th-8th, 4, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 45, United-States, <=50K 45, Private, 331643, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Private, 207937, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 1092, 40, United-States, <=50K 68, Private, 223486, HS-grad, 9, Widowed, Other-service, Unmarried, White, Female, 0, 0, 7, England, <=50K 33, Private, 340332, Bachelors, 13, Separated, Exec-managerial, Not-in-family, Black, Female, 0, 0, 45, United-States, <=50K 23, Private, 184813, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 20, United-States, <=50K 42, Self-emp-not-inc, 32185, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, >50K 30, Private, 197886, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 35, State-gov, 248374, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 40, Private, 382499, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 36, State-gov, 108320, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Male, 5455, 0, 30, United-States, <=50K 46, Self-emp-inc, 161386, 9th, 5, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 50, United-States, <=50K 49, Local-gov, 110172, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 144032, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 26, Private, 224426, Masters, 14, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 38, United-States, <=50K 37, Private, 230408, HS-grad, 9, Divorced, Other-service, Not-in-family, Black, Female, 0, 0, 20, United-States, <=50K 50, Local-gov, 20795, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Private, 174714, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 59, State-gov, 398626, Doctorate, 16, Divorced, Prof-specialty, Unmarried, White, Male, 25236, 0, 45, United-States, >50K 30, Private, 149531, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 34113, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 44, Local-gov, 323790, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 331381, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 160647, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, Ireland, >50K 34, Private, 339142, HS-grad, 9, Separated, Handlers-cleaners, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 58, Private, 164857, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 99, United-States, <=50K 33, Local-gov, 267859, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 167725, Bachelors, 13, Married-spouse-absent, Transport-moving, Not-in-family, Other, Male, 0, 0, 84, India, <=50K 49, Federal-gov, 586657, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 40, United-States, >50K 67, Self-emp-not-inc, 105907, 1st-4th, 2, Widowed, Other-service, Not-in-family, Black, Female, 0, 0, 20, United-States, <=50K 23, Private, 200677, 10th, 6, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 193882, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 54, Private, 138026, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 122385, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 49020, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 26, Private, 283715, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 286406, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 3325, 0, 40, United-States, <=50K 36, Private, 166416, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 156334, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Local-gov, 45607, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 40, Local-gov, 112362, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 200419, Assoc-acdm, 12, Separated, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 42, State-gov, 341638, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 25, ?, 34161, 12th, 8, Separated, ?, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 50, Self-emp-not-inc, 127151, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, Canada, >50K 52, Private, 321959, Some-college, 10, Married-civ-spouse, Tech-support, Husband, Black, Male, 0, 0, 40, United-States, >50K 51, Local-gov, 35211, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 19, Private, 214935, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 132130, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, >50K 57, Private, 222247, 12th, 8, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 165799, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 30, Private, 257874, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 38, Private, 357173, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, State-gov, 305739, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 172047, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 110677, Some-college, 10, Separated, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 21, ?, 405684, HS-grad, 9, Never-married, ?, Other-relative, White, Male, 0, 0, 35, Mexico, <=50K 60, Private, 82388, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 38, United-States, <=50K 45, Private, 289230, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 48, United-States, >50K 26, Private, 101812, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, White, Male, 5721, 0, 40, United-States, <=50K 49, State-gov, 336509, 10th, 6, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 383402, Some-college, 10, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 47, Private, 328216, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 7298, 0, 40, United-States, >50K 40, Private, 280362, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 35, United-States, <=50K 34, Private, 212064, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 7443, 0, 35, United-States, <=50K 42, Private, 173704, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 433375, 1st-4th, 2, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, Mexico, <=50K 63, Self-emp-not-inc, 106551, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 22418, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 54816, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 44, Private, 358199, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 43, Private, 190044, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 97698, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 32, United-States, <=50K 56, Private, 53366, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 236136, Assoc-voc, 11, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 44, Private, 326232, 7th-8th, 4, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 34, Private, 581071, HS-grad, 9, Separated, Adm-clerical, Not-in-family, White, Male, 0, 0, 48, United-States, >50K 40, Private, 220589, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Federal-gov, 161463, Some-college, 10, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 40, United-States, <=50K 44, Private, 95255, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 34, Federal-gov, 223267, Some-college, 10, Divorced, Protective-serv, Own-child, White, Male, 0, 0, 72, United-States, <=50K 22, Private, 236769, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 20, England, <=50K 58, Self-emp-inc, 229498, Some-college, 10, Widowed, Sales, Not-in-family, White, Female, 0, 0, 20, United-States, >50K 43, Private, 177083, Some-college, 10, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 23, Private, 287681, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, Columbia, <=50K 41, Private, 49797, Some-college, 10, Separated, Exec-managerial, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 44, Private, 174051, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 32, Private, 194901, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Local-gov, 252250, Assoc-acdm, 12, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 56, United-States, >50K 47, Private, 191277, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 24, Private, 174907, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 39, Private, 167140, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 236543, 12th, 8, Divorced, Protective-serv, Own-child, White, Male, 0, 0, 54, Mexico, <=50K 40, Private, 214242, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, <=50K 34, Private, 216864, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 3770, 45, United-States, <=50K 34, Private, 245211, HS-grad, 9, Never-married, Craft-repair, Unmarried, White, Male, 2036, 0, 30, United-States, <=50K 57, Private, 437727, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 45, United-States, >50K 71, Private, 200418, 5th-6th, 3, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Local-gov, 167334, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 54, Private, 146834, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 26, Private, 78424, Assoc-voc, 11, Never-married, Sales, Unmarried, White, Female, 0, 0, 54, United-States, <=50K 37, Private, 182675, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 45, United-States, >50K 28, Self-emp-not-inc, 38079, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 55, United-States, <=50K 42, Private, 115178, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 15, United-States, <=50K 45, Private, 195949, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 167415, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 57, Private, 223214, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 39, Private, 22245, Bachelors, 13, Married-civ-spouse, Prof-specialty, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 45, State-gov, 81853, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, Asian-Pac-Islander, Female, 0, 0, 40, United-States, >50K 30, Private, 147921, Assoc-voc, 11, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 46, United-States, <=50K 27, Private, 29261, HS-grad, 9, Married-AF-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 44, Private, 257758, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 44, State-gov, 136546, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 40, United-States, >50K 38, Private, 205493, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 60, United-States, >50K 19, Private, 71650, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 150217, Some-college, 10, Divorced, Sales, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 55, Self-emp-inc, 258648, 10th, 6, Widowed, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 114798, 10th, 6, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 43, Private, 186188, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 36, Local-gov, 175255, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 35, United-States, <=50K 45, Private, 249935, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 44, Private, 120277, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 38, United-States, >50K 26, Private, 193165, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 52, United-States, >50K 32, Private, 185027, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1887, 40, Ireland, >50K 21, Private, 221418, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 43, Federal-gov, 56063, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 34, Private, 153927, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, State-gov, 163110, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 40, Self-emp-inc, 175696, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 51, United-States, <=50K 46, Private, 143189, 5th-6th, 3, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, Dominican-Republic, <=50K 20, ?, 114969, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 54, State-gov, 32778, HS-grad, 9, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 150683, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 58, Self-emp-inc, 78104, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 25, Private, 335005, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 3137, 0, 40, United-States, <=50K 50, Local-gov, 311551, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 50, United-States, >50K 42, Self-emp-not-inc, 201520, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 25, Private, 124111, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 60, Private, 166386, 11th, 7, Married-civ-spouse, Machine-op-inspct, Wife, Asian-Pac-Islander, Female, 0, 0, 30, Hong, <=50K 43, State-gov, 117471, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 361307, Bachelors, 13, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 142038, HS-grad, 9, Married-civ-spouse, Craft-repair, Wife, White, Female, 0, 0, 45, United-States, <=50K 35, Private, 276552, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 50402, Some-college, 10, Divorced, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 43, Self-emp-not-inc, 174090, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 20, United-States, >50K 27, Private, 277760, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 24243, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 1590, 40, United-States, <=50K 44, Self-emp-inc, 151089, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1887, 70, United-States, >50K 52, Self-emp-not-inc, 165278, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 22, United-States, <=50K 49, Private, 182752, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 31, Private, 173002, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 59, Private, 261232, 11th, 7, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 164607, Bachelors, 13, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Self-emp-not-inc, 129573, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 51, Federal-gov, 36186, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 24, Private, 325744, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 58, Self-emp-inc, 329793, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 46, Private, 133616, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 55, Private, 83401, 5th-6th, 3, Widowed, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 76, Private, 239880, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 8, United-States, <=50K 25, Private, 201737, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 192182, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 7298, 0, 40, United-States, >50K 33, Private, 143540, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 28334, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 245873, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 42, Local-gov, 199095, Assoc-voc, 11, Widowed, Prof-specialty, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 53, Private, 104461, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Male, 8614, 0, 50, Italy, >50K 33, Local-gov, 183923, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 7688, 0, 35, United-States, >50K 30, Private, 129707, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 35, United-States, >50K 41, Local-gov, 575442, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, State-gov, 184682, Assoc-acdm, 12, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 69251, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, >50K 31, Private, 225507, Assoc-voc, 11, Never-married, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 167515, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 50, United-States, >50K 35, Private, 407068, 1st-4th, 2, Married-spouse-absent, Other-service, Not-in-family, White, Male, 0, 0, 40, Guatemala, <=50K 40, Private, 170019, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, ?, <=50K 46, Local-gov, 125892, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 43, Local-gov, 35824, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 35, Private, 67083, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 40, China, <=50K 23, Private, 107801, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 50, Self-emp-not-inc, 95577, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 12, ?, <=50K 43, Private, 118536, HS-grad, 9, Divorced, Machine-op-inspct, Other-relative, Black, Male, 0, 0, 40, United-States, <=50K 61, Private, 198078, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Private, 78261, Prof-school, 15, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 50, United-States, <=50K 21, Private, 234108, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Local-gov, 241998, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1672, 50, United-States, <=50K 40, Private, 92717, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 23, Private, 257683, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 90, Private, 40388, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 24, Private, 55424, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 169600, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 2176, 0, 12, United-States, <=50K 40, Local-gov, 319271, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 37, Self-emp-not-inc, 75050, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, <=50K 31, Private, 182896, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 188274, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 211497, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 113806, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 40, ?, >50K 47, Local-gov, 172246, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 48, Local-gov, 219962, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, ?, 186815, Masters, 14, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 50, United-States, <=50K 26, ?, 132749, Bachelors, 13, Never-married, ?, Not-in-family, White, Female, 0, 0, 80, United-States, <=50K 28, Private, 209801, 9th, 5, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, United-States, <=50K 20, State-gov, 178517, Some-college, 10, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 169364, Some-college, 10, Divorced, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 40, Ireland, <=50K 32, Federal-gov, 164707, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 55, Private, 144084, 10th, 6, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Local-gov, 133692, Bachelors, 13, Divorced, Protective-serv, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 184169, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 7688, 0, 35, United-States, >50K 45, Self-emp-inc, 145290, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, >50K 65, Local-gov, 24824, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 178319, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 50, United-States, >50K 22, Private, 235829, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 22, ?, 196280, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 20, United-States, <=50K 42, Self-emp-not-inc, 54202, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 37, Private, 220237, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 5178, 0, 40, United-States, >50K 24, Private, 59146, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 67, Private, 64148, Some-college, 10, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 41, United-States, <=50K 28, Private, 196621, HS-grad, 9, Married-spouse-absent, Tech-support, Not-in-family, White, Female, 0, 0, 37, United-States, <=50K 56, Private, 195668, 10th, 6, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 35, Cuba, >50K 31, State-gov, 263000, Assoc-voc, 11, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 38, United-States, <=50K 33, Private, 554986, Some-college, 10, Separated, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 52, ?, 108211, 7th-8th, 4, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 217654, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Germany, >50K 53, Private, 139671, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 40, United-States, >50K 47, Private, 102771, 7th-8th, 4, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Portugal, <=50K 40, Private, 213019, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 35, Private, 228493, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 48, United-States, <=50K 65, Self-emp-not-inc, 22907, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 24364, Some-college, 10, Married-civ-spouse, Other-service, Wife, Black, Female, 0, 0, 30, United-States, <=50K 23, Federal-gov, 41432, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 39, Private, 235259, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 343476, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 30, United-States, <=50K 37, Private, 326886, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 248313, Assoc-voc, 11, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Self-emp-not-inc, 30290, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 188540, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 39, Private, 237943, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 30, United-States, >50K 25, Private, 198870, Bachelors, 13, Never-married, Adm-clerical, Own-child, Black, Male, 0, 0, 35, United-States, <=50K 30, Private, 233980, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 171090, 9th, 5, Married-civ-spouse, Machine-op-inspct, Wife, Black, Female, 0, 0, 48, United-States, <=50K 22, Private, 353039, HS-grad, 9, Never-married, Craft-repair, Unmarried, White, Female, 0, 0, 36, Mexico, <=50K 46, Federal-gov, 213140, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 40, United-States, >50K 54, Private, 188136, Bachelors, 13, Divorced, Sales, Not-in-family, White, Female, 0, 1408, 38, United-States, <=50K 33, Private, 130057, Assoc-acdm, 12, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 70, State-gov, 345339, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 182074, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 53, Local-gov, 176557, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 55, State-gov, 71630, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 1617, 40, United-States, <=50K 17, Private, 159849, 11th, 7, Never-married, Protective-serv, Own-child, White, Female, 0, 0, 30, United-States, <=50K 36, Private, 183425, Some-college, 10, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Self-emp-not-inc, 125933, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 55, United-States, >50K 40, Local-gov, 180123, HS-grad, 9, Married-spouse-absent, Farming-fishing, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 36, Private, 592930, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 50, United-States, >50K 28, Private, 183802, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 55, United-States, <=50K 39, Private, 77005, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 40, United-States, >50K 49, Private, 80914, 5th-6th, 3, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 63, Self-emp-inc, 165667, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 123991, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 20, United-States, <=50K 48, Self-emp-inc, 181307, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, >50K 55, Private, 124137, HS-grad, 9, Married-spouse-absent, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, Poland, <=50K 18, ?, 137363, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 4, United-States, <=50K 20, Private, 291979, HS-grad, 9, Married-civ-spouse, Sales, Other-relative, White, Male, 0, 0, 20, United-States, <=50K 49, Private, 91251, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 40, China, <=50K 27, Federal-gov, 148153, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 37, Private, 131463, 10th, 6, Divorced, Other-service, Unmarried, White, Female, 0, 0, 33, United-States, <=50K 32, State-gov, 127651, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Self-emp-inc, 239018, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 47, Private, 276087, Assoc-voc, 11, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 26, United-States, <=50K 34, Private, 386877, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 61, Private, 210464, HS-grad, 9, Divorced, Adm-clerical, Other-relative, Black, Female, 0, 0, 35, United-States, <=50K 25, Private, 632834, HS-grad, 9, Never-married, Craft-repair, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 26, Private, 245465, Assoc-acdm, 12, Never-married, Sales, Own-child, White, Male, 0, 0, 30, United-States, <=50K 18, Private, 198087, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 30, United-States, <=50K 35, Private, 27408, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 36, Private, 242713, HS-grad, 9, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, ?, <=50K 56, Private, 314727, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, >50K 40, State-gov, 269733, Assoc-voc, 11, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 177287, 12th, 8, Never-married, Other-service, Own-child, White, Female, 0, 0, 38, United-States, <=50K 66, Private, 167711, HS-grad, 9, Widowed, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 42, Private, 112181, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 339002, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 20, United-States, <=50K 39, State-gov, 24721, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 65, Self-emp-not-inc, 37092, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 25, United-States, <=50K 20, Private, 216563, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 52, Private, 204447, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 4386, 0, 40, United-States, >50K 24, ?, 151153, Some-college, 10, Never-married, ?, Not-in-family, Asian-Pac-Islander, Male, 99999, 0, 50, South, >50K 39, Private, 187089, Some-college, 10, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 423052, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 49, Private, 169180, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, Hong, <=50K 21, Private, 104981, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 48, United-States, <=50K 35, ?, 120074, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 30, United-States, <=50K 38, Private, 269323, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 55, Private, 141549, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 214858, 10th, 6, Married-civ-spouse, Craft-repair, Other-relative, White, Male, 0, 0, 55, United-States, <=50K 34, Private, 173524, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 54, Local-gov, 365049, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, Mexico, <=50K 38, Private, 60355, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 86808, HS-grad, 9, Divorced, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 33, State-gov, 174171, Some-college, 10, Separated, Tech-support, Not-in-family, White, Male, 0, 0, 12, United-States, <=50K 32, Federal-gov, 504951, Assoc-acdm, 12, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 50, United-States, <=50K 34, Private, 294064, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, France, <=50K 46, Private, 120131, Bachelors, 13, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 30, United-States, >50K 48, Private, 199058, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Private, 152328, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 48, Federal-gov, 88564, 7th-8th, 4, Married-spouse-absent, Handlers-cleaners, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 67, Private, 95113, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 37, United-States, >50K 36, Private, 247558, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 5178, 0, 60, ?, >50K 25, Private, 178421, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 43, Private, 484861, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 4064, 0, 38, United-States, <=50K 27, Local-gov, 225291, Assoc-acdm, 12, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 56, Private, 205735, 1st-4th, 2, Separated, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 54, Self-emp-not-inc, 58898, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1579, 48, United-States, <=50K 39, Private, 355468, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 1887, 46, United-States, >50K 60, Self-emp-not-inc, 184362, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 25, United-States, <=50K 27, Private, 347513, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 138768, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 29810, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 126501, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 60783, 10th, 6, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 15, United-States, <=50K 26, Private, 179772, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 45, Self-emp-inc, 281911, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, <=50K 33, Private, 70447, HS-grad, 9, Never-married, Transport-moving, Other-relative, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 55, ?, 449576, 5th-6th, 3, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 48, Mexico, <=50K 29, Private, 327964, 9th, 5, Divorced, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 72, Private, 496538, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 6360, 0, 40, United-States, <=50K 35, Self-emp-not-inc, 153066, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, >50K 53, State-gov, 77651, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 119493, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 256240, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, United-States, <=50K 69, Private, 177374, HS-grad, 9, Widowed, Adm-clerical, Unmarried, White, Female, 1848, 0, 12, United-States, <=50K 41, Local-gov, 37848, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 45, Private, 129336, Masters, 14, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, >50K 27, Private, 183511, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Self-emp-inc, 120131, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 60, United-States, >50K 55, Private, 190508, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 35, United-States, <=50K 31, Private, 363130, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, United-States, >50K 45, Private, 240356, Some-college, 10, Divorced, Sales, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 64, Private, 133166, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 5, United-States, <=50K 38, Private, 32916, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 17, Private, 117477, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 34748, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 1887, 20, United-States, >50K 22, Private, 459463, 12th, 8, Married-spouse-absent, Other-service, Unmarried, Black, Female, 0, 0, 50, United-States, <=50K 23, Private, 95989, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 25, Private, 118088, HS-grad, 9, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 150570, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 3103, 0, 43, United-States, >50K 31, ?, 505438, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 30, Mexico, <=50K 37, Private, 179731, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 53, Private, 122109, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 0, 1876, 38, United-States, <=50K 28, Local-gov, 163942, Some-college, 10, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 106670, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 41, Private, 123403, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, Self-emp-inc, 119986, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 25, Private, 66622, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 20, ?, 40060, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 56, United-States, <=50K 35, Private, 260578, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, >50K 64, Local-gov, 96076, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 70604, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 38, United-States, <=50K 39, Self-emp-not-inc, 230329, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 1564, 12, United-States, >50K 53, Private, 49715, HS-grad, 9, Divorced, Transport-moving, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 116531, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Federal-gov, 214542, Some-college, 10, Divorced, Handlers-cleaners, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 25, Local-gov, 335005, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 35, Italy, <=50K 19, Private, 258633, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 20, Private, 203240, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 27, Private, 104457, Bachelors, 13, Never-married, Machine-op-inspct, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, ?, <=50K 55, Local-gov, 99131, HS-grad, 9, Married-civ-spouse, Prof-specialty, Other-relative, White, Female, 0, 2246, 40, United-States, >50K 52, State-gov, 125796, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, Black, Female, 0, 1848, 40, United-States, >50K 21, ?, 479482, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 167790, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 133758, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 1974, 40, United-States, <=50K 22, Private, 106843, 10th, 6, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 30, United-States, <=50K 24, Private, 117959, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 4386, 0, 40, United-States, >50K 26, Private, 174921, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 134152, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, <=50K 57, Private, 99364, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Puerto-Rico, <=50K 18, Local-gov, 155905, Masters, 14, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 60, United-States, <=50K 30, Private, 467108, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 34, Self-emp-not-inc, 304622, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 40, Private, 198692, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 5178, 0, 60, United-States, >50K 60, Private, 178050, HS-grad, 9, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 38, United-States, <=50K 25, Private, 162687, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 113151, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, <=50K 48, Private, 158924, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 27, Self-emp-not-inc, 141795, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 30, United-States, <=50K 33, Self-emp-not-inc, 33404, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 65, United-States, >50K 65, Self-emp-inc, 178771, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 168553, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1977, 40, United-States, >50K 27, Private, 110648, Bachelors, 13, Never-married, Tech-support, Own-child, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 151053, Some-college, 10, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 45, Self-emp-not-inc, 142871, Some-college, 10, Separated, Sales, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 18, ?, 343161, 11th, 7, Never-married, ?, Own-child, White, Male, 0, 0, 16, United-States, <=50K 27, Private, 183523, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 57, Self-emp-not-inc, 222216, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 60, United-States, <=50K 44, Private, 121874, Some-college, 10, Divorced, Sales, Unmarried, White, Male, 0, 0, 55, United-States, >50K 30, Private, 467108, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 44, United-States, >50K 26, Private, 34393, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Federal-gov, 42003, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 61, Private, 180418, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 49, Self-emp-not-inc, 199590, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, Mexico, <=50K 33, Private, 144949, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 40, United-States, >50K 50, Private, 155594, Assoc-acdm, 12, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, >50K 53, Self-emp-not-inc, 162576, 7th-8th, 4, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 99, United-States, <=50K 33, Private, 232475, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 22, Private, 269474, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 10, United-States, <=50K 45, Local-gov, 140644, Bachelors, 13, Divorced, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 26, ?, 39640, Some-college, 10, Never-married, ?, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 50, ?, 346014, 7th-8th, 4, Separated, ?, Own-child, White, Female, 0, 0, 20, United-States, <=50K 47, Self-emp-not-inc, 159726, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 52, Federal-gov, 290856, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 57, Private, 217886, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 36, United-States, <=50K 21, ?, 199915, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 35, United-States, <=50K 58, Private, 106546, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 2174, 0, 40, United-States, <=50K 50, Local-gov, 220640, Masters, 14, Divorced, Prof-specialty, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 50, United-States, >50K 33, Federal-gov, 88913, Some-college, 10, Never-married, Adm-clerical, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 34, Self-emp-not-inc, 288486, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 227411, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 37, Local-gov, 99935, Masters, 14, Married-civ-spouse, Protective-serv, Husband, White, Male, 7688, 0, 50, United-States, >50K 57, Private, 201112, Assoc-acdm, 12, Divorced, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 57, Self-emp-not-inc, 123778, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 48, United-States, <=50K 21, Private, 204596, Assoc-acdm, 12, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 8, United-States, <=50K 40, Private, 190290, Some-college, 10, Divorced, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 196674, Some-college, 10, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 108435, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 20, United-States, <=50K 38, Private, 186359, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Private, 137076, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 60, United-States, >50K 22, State-gov, 262819, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 171655, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 42, United-States, <=50K 42, Private, 183319, 5th-6th, 3, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, El-Salvador, <=50K 36, Private, 127306, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 47, United-States, <=50K 22, Private, 68678, HS-grad, 9, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 40, United-States, <=50K 40, State-gov, 140108, 9th, 5, Separated, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 26, Private, 263444, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, <=50K 46, State-gov, 265554, HS-grad, 9, Never-married, Transport-moving, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 28, Private, 410216, 11th, 7, Married-civ-spouse, Craft-repair, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 46, State-gov, 20534, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 55, Private, 188917, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 76, Private, 98695, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 27, Private, 411950, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 50, Private, 237819, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 75, Private, 187424, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 20, United-States, <=50K 42, Federal-gov, 198316, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Local-gov, 139703, Masters, 14, Never-married, Prof-specialty, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 51, Private, 152596, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 194726, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 55, United-States, >50K 44, Private, 82601, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, ?, 229843, Some-college, 10, Never-married, ?, Not-in-family, Black, Female, 0, 0, 20, United-States, <=50K 60, Private, 122276, 5th-6th, 3, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, Italy, <=50K 47, State-gov, 188386, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 73, Private, 92298, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 15, United-States, <=50K 27, Private, 390657, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, United-States, <=50K 50, Private, 89041, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 15024, 0, 50, United-States, >50K 35, Private, 314897, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Puerto-Rico, <=50K 31, Private, 166343, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, Black, Male, 0, 0, 50, ?, <=50K 45, Private, 88781, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Germany, >50K 57, Private, 41762, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, South, >50K 34, Private, 849857, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Nicaragua, <=50K 19, Private, 307496, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 16, United-States, <=50K 25, Private, 324372, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 39, Private, 99270, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 50, Germany, >50K 28, Private, 160731, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Poland, >50K 48, State-gov, 148306, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 259019, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 44, United-States, <=50K 53, Private, 224894, 5th-6th, 3, Married-civ-spouse, Priv-house-serv, Wife, Black, Female, 0, 0, 10, Haiti, <=50K 19, Private, 258470, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 197919, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 60, United-States, <=50K 23, Private, 213719, Assoc-acdm, 12, Never-married, Sales, Own-child, Black, Female, 0, 0, 36, United-States, <=50K 32, Private, 226535, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 146042, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 21, Private, 180339, Assoc-voc, 11, Never-married, Farming-fishing, Not-in-family, White, Female, 0, 1602, 30, United-States, <=50K 24, Private, 99970, Bachelors, 13, Never-married, Tech-support, Own-child, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 300687, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 29, Local-gov, 219906, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 25, United-States, >50K 24, Private, 122234, Some-college, 10, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 20, ?, <=50K 55, Private, 158641, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 239539, HS-grad, 9, Married-spouse-absent, Machine-op-inspct, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 46, Local-gov, 102308, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 186934, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 234447, Some-college, 10, Divorced, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 35, Private, 125933, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 29, Private, 142760, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 41, State-gov, 309056, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 40, Self-emp-not-inc, 48859, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 32, United-States, <=50K 30, Private, 110594, HS-grad, 9, Divorced, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 72, Private, 426562, 11th, 7, Divorced, Other-service, Not-in-family, Black, Female, 0, 0, 35, United-States, <=50K 17, Private, 169037, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 46, Self-emp-inc, 123075, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 70, United-States, <=50K 38, Private, 195744, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 36, Private, 81896, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 24, Self-emp-not-inc, 172047, Assoc-acdm, 12, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 253814, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 28, Private, 66473, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 60, ?, 56248, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 1485, 70, United-States, >50K 42, Local-gov, 271521, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, Other, Male, 0, 0, 40, United-States, >50K 48, Private, 265295, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Self-emp-not-inc, 174308, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 196342, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 55, Private, 223594, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Black, Male, 7688, 0, 40, Puerto-Rico, >50K 30, Private, 149787, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 68, Private, 124686, 7th-8th, 4, Widowed, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 10, United-States, <=50K 45, Private, 50163, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 26, Private, 175789, HS-grad, 9, Divorced, Handlers-cleaners, Own-child, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 218215, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 166371, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 169469, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 40, United-States, >50K 52, Private, 145081, 7th-8th, 4, Never-married, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 68, Private, 214521, Prof-school, 15, Widowed, Prof-specialty, Unmarried, White, Female, 0, 0, 16, United-States, <=50K 26, Local-gov, 287233, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, Black, Female, 0, 0, 40, United-States, >50K 52, Private, 201310, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, ?, <=50K 46, Self-emp-not-inc, 197836, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 1672, 50, United-States, <=50K 53, Private, 158294, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7298, 0, 40, United-States, >50K 17, Private, 127366, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 8, United-States, <=50K 29, Private, 203697, Bachelors, 13, Married-civ-spouse, Prof-specialty, Own-child, White, Male, 0, 0, 75, United-States, <=50K 41, Private, 168730, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 45, Private, 165232, Some-college, 10, Divorced, Tech-support, Not-in-family, Black, Female, 0, 0, 40, Trinadad&Tobago, <=50K 57, Private, 175942, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 30, Federal-gov, 356689, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 30, Japan, <=50K 46, Private, 132912, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 45, Private, 187226, Assoc-acdm, 12, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 59, ?, 254765, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Private, 202565, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 52, United-States, <=50K 38, State-gov, 103925, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 2036, 0, 20, United-States, <=50K 22, Private, 112164, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, ?, <=50K 59, Self-emp-not-inc, 70623, 7th-8th, 4, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 85, United-States, <=50K 36, Private, 102729, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 558944, 7th-8th, 4, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 256967, 10th, 6, Never-married, Sales, Other-relative, Black, Female, 0, 0, 40, United-States, <=50K 62, ?, 144583, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 63, Private, 102412, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 159788, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 80, United-States, <=50K 27, Private, 55743, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, Black, Female, 0, 0, 45, United-States, >50K 47, State-gov, 148171, Doctorate, 16, Divorced, Prof-specialty, Unmarried, White, Male, 0, 0, 50, France, >50K 20, Local-gov, 271354, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 98524, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 29, Private, 272913, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 30, Mexico, <=50K 22, Private, 324445, HS-grad, 9, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 155469, Assoc-acdm, 12, Widowed, Tech-support, Unmarried, White, Female, 0, 0, 24, United-States, <=50K 36, Private, 102945, Assoc-voc, 11, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 60, Private, 291904, 10th, 6, Divorced, Other-service, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 41, Federal-gov, 186601, HS-grad, 9, Separated, Exec-managerial, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 43, Private, 172401, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Private, 193285, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 38, United-States, >50K 34, Private, 176244, 7th-8th, 4, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 117779, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Female, 0, 0, 35, United-States, <=50K 22, ?, 34616, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 20, United-States, <=50K 52, Private, 169182, 9th, 5, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 25, Puerto-Rico, <=50K 27, Private, 180758, Assoc-acdm, 12, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 60, Local-gov, 141637, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Self-emp-not-inc, 169023, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 7688, 0, 40, United-States, >50K 34, Self-emp-not-inc, 101266, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 62, United-States, <=50K 30, Private, 164190, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 142282, Some-college, 10, Separated, Other-service, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 39, Federal-gov, 103984, Bachelors, 13, Divorced, Exec-managerial, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 64, Private, 187601, Some-college, 10, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 17, Self-emp-not-inc, 36218, 11th, 7, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 20, United-States, <=50K 29, State-gov, 106334, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, ?, <=50K 37, Local-gov, 249392, Assoc-voc, 11, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 43, Self-emp-not-inc, 110355, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 30, Self-emp-not-inc, 117944, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 25, United-States, <=50K 17, Private, 163836, 10th, 6, Never-married, Sales, Own-child, White, Female, 0, 0, 12, United-States, <=50K 29, Private, 145592, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Guatemala, <=50K 24, Private, 108495, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, India, <=50K 27, Self-emp-not-inc, 212041, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 69, Self-emp-inc, 182451, Bachelors, 13, Separated, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 124020, HS-grad, 9, Married-spouse-absent, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 199116, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Puerto-Rico, <=50K 17, ?, 144114, 10th, 6, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 107438, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 1651, 40, United-States, <=50K 70, Private, 405362, 7th-8th, 4, Widowed, Other-service, Unmarried, Black, Female, 0, 0, 38, United-States, <=50K 32, Private, 175856, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 1902, 40, United-States, >50K 21, ?, 262241, HS-grad, 9, Never-married, ?, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 27, Self-emp-not-inc, 420054, HS-grad, 9, Never-married, Craft-repair, Unmarried, White, Male, 9562, 0, 50, United-States, >50K 27, Private, 86681, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 187161, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 25, United-States, <=50K 44, State-gov, 691903, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 60, United-States, >50K 36, Private, 219483, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 199058, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 50, United-States, >50K 29, Private, 192010, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 60, Poland, <=50K 34, Federal-gov, 419691, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 7298, 0, 54, United-States, >50K 28, Local-gov, 356089, Bachelors, 13, Never-married, Prof-specialty, Other-relative, White, Male, 0, 0, 50, United-States, <=50K 34, Private, 684015, 5th-6th, 3, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, El-Salvador, <=50K 18, Private, 36882, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 39, Private, 203180, Some-college, 10, Divorced, Farming-fishing, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 34, Private, 183811, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Local-gov, 103966, Masters, 14, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 41, United-States, <=50K 24, Private, 304602, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 57233, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 70, United-States, <=50K 50, State-gov, 289207, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 45, United-States, >50K 68, Private, 224019, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 35, Private, 267966, 11th, 7, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 47, Private, 214800, Assoc-voc, 11, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Local-gov, 241528, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 197365, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 296724, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 17, United-States, <=50K 26, Private, 136226, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 40623, Some-college, 10, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 264874, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 112847, HS-grad, 9, Never-married, Farming-fishing, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 18, ?, 236090, HS-grad, 9, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 52, Self-emp-not-inc, 89028, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 71, State-gov, 210673, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 28, United-States, <=50K 55, Private, 60193, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 17, Private, 216137, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 8, United-States, <=50K 36, Private, 139743, Some-college, 10, Widowed, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 25, ?, 32276, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Local-gov, 423605, 12th, 8, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1848, 40, Nicaragua, >50K 27, Private, 298871, Bachelors, 13, Never-married, Other-service, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 42, Private, 318255, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 347867, HS-grad, 9, Married-spouse-absent, Sales, Not-in-family, White, Male, 0, 1719, 40, United-States, <=50K 57, Private, 279636, Assoc-voc, 11, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 34, Private, 405386, Some-college, 10, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 28, United-States, <=50K 31, Private, 297188, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 24, Private, 182342, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 41, Self-emp-not-inc, 229148, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 60, Jamaica, <=50K 30, Private, 189620, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Female, 6849, 0, 40, England, <=50K 17, Private, 413557, 11th, 7, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 32, United-States, <=50K 26, Self-emp-inc, 246025, HS-grad, 9, Separated, Sales, Unmarried, White, Female, 0, 0, 20, Honduras, <=50K 32, Private, 390997, 1st-4th, 2, Never-married, Farming-fishing, Not-in-family, Other, Male, 0, 0, 50, Mexico, <=50K 55, Private, 102058, 10th, 6, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 19, Private, 247298, 12th, 8, Married-spouse-absent, Other-service, Own-child, Other, Female, 0, 0, 20, United-States, <=50K 28, Private, 140108, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 55, ?, 216941, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 2885, 0, 40, United-States, <=50K 49, Private, 81654, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 23, Private, 177526, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 64631, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 110028, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 203761, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Private, 163870, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 59, Federal-gov, 117299, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1887, 40, United-States, >50K 20, Private, 50648, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 35, United-States, <=50K 21, Private, 166517, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 28, ?, 173800, Bachelors, 13, Married-spouse-absent, ?, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 10, Taiwan, <=50K 44, Self-emp-inc, 181762, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 31, Self-emp-not-inc, 340880, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 48, United-States, <=50K 50, Self-emp-not-inc, 114758, Bachelors, 13, Never-married, Craft-repair, Not-in-family, White, Male, 4416, 0, 45, United-States, <=50K 54, Private, 138847, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, >50K 28, Private, 215014, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 34, Private, 183778, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 273629, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Self-emp-inc, 113870, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 23, Private, 213955, HS-grad, 9, Never-married, Adm-clerical, Own-child, Black, Male, 0, 2001, 40, United-States, <=50K 29, Private, 114982, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 205338, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Self-emp-not-inc, 57924, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 7688, 0, 50, United-States, >50K 90, ?, 225063, Some-college, 10, Never-married, ?, Own-child, Asian-Pac-Islander, Male, 0, 0, 10, South, <=50K 35, Self-emp-not-inc, 202027, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 55, United-States, >50K 20, Private, 281356, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, Other, Male, 0, 0, 40, United-States, <=50K 42, Private, 30824, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 2354, 0, 16, United-States, <=50K 56, Private, 98809, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 5013, 0, 45, United-States, <=50K 31, Private, 38223, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 0, 45, United-States, <=50K 23, Private, 172232, HS-grad, 9, Never-married, Tech-support, Own-child, White, Male, 0, 0, 50, United-States, <=50K 60, Private, 140544, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 221366, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 180799, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, >50K 36, Private, 111499, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 14084, 0, 40, United-States, >50K 44, Self-emp-not-inc, 155930, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 34, Private, 201122, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, >50K 27, Private, 101709, HS-grad, 9, Never-married, Sales, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 49, Private, 140121, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 48, Private, 172709, HS-grad, 9, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 47, Private, 120131, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 34, Private, 117444, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 65, United-States, >50K 27, Private, 256764, Assoc-acdm, 12, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Local-gov, 176185, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 4064, 0, 40, ?, <=50K 24, Private, 223811, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 201603, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 25, Private, 138765, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 133974, Assoc-voc, 11, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 38, Federal-gov, 137953, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, <=50K 57, Private, 103403, 5th-6th, 3, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 461678, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, >50K 41, State-gov, 70884, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, State-gov, 466498, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 60, United-States, >50K 19, Private, 148644, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 190739, HS-grad, 9, Never-married, Other-service, Other-relative, Black, Male, 0, 0, 32, United-States, <=50K 34, Private, 299507, Assoc-voc, 11, Never-married, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 211424, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 27, State-gov, 106721, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 192017, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 59, Private, 530099, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1887, 55, United-States, >50K 34, Private, 119153, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 30, Private, 202450, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 65, United-States, >50K 21, Private, 50341, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 24, Private, 140001, Some-college, 10, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, Italy, <=50K 19, ?, 220517, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 15, United-States, <=50K 82, ?, 52921, Some-college, 10, Widowed, ?, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 3, United-States, <=50K 35, Private, 31964, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 32, Private, 148207, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 151627, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 30, Private, 402539, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 28, Self-emp-not-inc, 188278, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, <=50K 28, Self-emp-not-inc, 96219, Bachelors, 13, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 5, United-States, <=50K 29, Private, 340534, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 44, United-States, <=50K 60, Private, 160339, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Columbia, <=50K 28, Private, 120135, Assoc-voc, 11, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Federal-gov, 303817, Some-college, 10, Divorced, Exec-managerial, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 31, Private, 181091, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 28, Private, 200515, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 35, United-States, >50K 42, Private, 160893, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 23, United-States, <=50K 40, Local-gov, 183096, 9th, 5, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, Yugoslavia, >50K 24, Private, 241367, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Self-emp-inc, 342084, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 36, Private, 193855, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 80410, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 554317, 9th, 5, Married-spouse-absent, Other-service, Other-relative, White, Male, 0, 0, 35, Mexico, <=50K 46, Private, 85109, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 1628, 40, United-States, <=50K 28, Private, 108569, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 43, United-States, <=50K 34, Private, 120959, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 222011, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 0, 43, United-States, <=50K 43, Private, 238530, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 48404, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 60, Private, 88055, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 3781, 0, 16, United-States, <=50K 33, Private, 238381, Some-college, 10, Never-married, Craft-repair, Not-in-family, Black, Male, 8614, 0, 40, United-States, >50K 22, Private, 243923, HS-grad, 9, Married-civ-spouse, Transport-moving, Other-relative, White, Male, 0, 0, 80, United-States, <=50K 39, Private, 305597, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 141841, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 5178, 0, 40, United-States, >50K 39, Private, 129764, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Self-emp-not-inc, 150993, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 63, Self-emp-not-inc, 147140, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, >50K 46, State-gov, 30219, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 38, United-States, >50K 48, Private, 167967, HS-grad, 9, Separated, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 33, Private, 133278, HS-grad, 9, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 65, Private, 172510, Some-college, 10, Widowed, Prof-specialty, Not-in-family, White, Female, 1848, 0, 20, Hungary, <=50K 39, Private, 192251, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, >50K 43, Private, 210844, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, Black, Female, 0, 0, 40, United-States, >50K 28, Private, 263015, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Self-emp-not-inc, 155118, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 99999, 0, 35, United-States, >50K 24, State-gov, 232918, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 48, Private, 143542, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 45607, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 62, Private, 29828, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Self-emp-not-inc, 104118, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 60, Private, 191446, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 40, United-States, >50K 50, Private, 27484, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 40, Private, 205987, Prof-school, 15, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, Cuba, <=50K 39, Local-gov, 143385, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, ?, 200508, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Local-gov, 186995, HS-grad, 9, Divorced, Protective-serv, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 54159, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 38, United-States, <=50K 39, Private, 113481, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 30, Local-gov, 235271, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Private, 349365, Some-college, 10, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 65, United-States, <=50K 18, Private, 283637, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 70282, Assoc-acdm, 12, Never-married, Sales, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 26, Private, 166051, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 193720, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 42, United-States, <=50K 35, ?, 124836, Some-college, 10, Divorced, ?, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 36, United-States, <=50K 33, Private, 236379, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 46, Private, 122026, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 44, United-States, >50K 40, Private, 114537, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 34, Private, 191834, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, <=50K 29, Private, 420054, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Self-emp-not-inc, 160045, Some-college, 10, Widowed, Other-service, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 34, Private, 303187, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, ?, >50K 45, Private, 190088, HS-grad, 9, Married-spouse-absent, Adm-clerical, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 53, Private, 126977, HS-grad, 9, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 52, Self-emp-not-inc, 63004, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 64, Private, 391121, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Private, 211450, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 44, Private, 156413, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 44, United-States, >50K 41, Private, 116797, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 7298, 0, 50, United-States, >50K 53, Local-gov, 204447, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 43, United-States, >50K 25, Private, 66935, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 20, Private, 344278, 11th, 7, Separated, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 108574, Assoc-voc, 11, Never-married, Priv-house-serv, Own-child, White, Female, 0, 0, 40, United-States, <=50K 56, Private, 244605, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 363677, Doctorate, 16, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 1977, 30, United-States, >50K 56, Private, 219762, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 35, United-States, <=50K 38, Self-emp-inc, 269318, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 40, United-States, >50K 62, Private, 77884, HS-grad, 9, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 28, Self-emp-not-inc, 70100, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 31, Private, 213643, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 3908, 0, 40, United-States, <=50K 24, Private, 69640, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 65, Private, 170012, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 34, United-States, <=50K 40, Private, 329924, HS-grad, 9, Separated, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 30, United-States, <=50K 31, Private, 193285, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 261241, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 1741, 60, United-States, <=50K 42, Federal-gov, 108183, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 1902, 40, South, >50K 20, Private, 296618, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 30, Local-gov, 257796, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 155320, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 45, United-States, <=50K 22, Private, 151888, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 65, ?, 143118, HS-grad, 9, Widowed, ?, Unmarried, White, Female, 0, 2206, 10, United-States, <=50K 31, Private, 66278, Some-college, 10, Married-civ-spouse, Prof-specialty, Wife, White, Female, 3908, 0, 40, United-States, <=50K 56, Private, 92444, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 50, United-States, >50K 51, Private, 229272, HS-grad, 9, Divorced, Other-service, Other-relative, Black, Male, 0, 0, 32, Haiti, <=50K 36, Self-emp-not-inc, 207202, 10th, 6, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 44, State-gov, 154176, Some-college, 10, Divorced, Adm-clerical, Not-in-family, Black, Female, 0, 1590, 40, United-States, <=50K 49, Private, 180899, Masters, 14, Divorced, Exec-managerial, Unmarried, White, Male, 0, 1755, 45, United-States, >50K 28, Private, 205337, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 180779, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7298, 0, 40, United-States, >50K 33, Self-emp-not-inc, 343021, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 49, Private, 176814, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 5178, 0, 40, United-States, >50K 74, State-gov, 88638, Doctorate, 16, Never-married, Prof-specialty, Other-relative, White, Female, 0, 3683, 20, United-States, >50K 48, Private, 248059, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 5013, 0, 45, United-States, <=50K 38, Private, 409604, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 40, United-States, >50K 39, Private, 185053, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 332884, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 65, United-States, >50K 56, Private, 212864, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 66473, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 17, Private, 285169, 11th, 7, Never-married, Priv-house-serv, Own-child, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 175431, 9th, 5, Divorced, Prof-specialty, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 18, ?, 152641, 10th, 6, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 339346, Masters, 14, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 39, Private, 287306, Some-college, 10, Separated, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 29, Self-emp-not-inc, 70604, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 3464, 0, 40, United-States, <=50K 21, Private, 88926, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 10, United-States, <=50K 36, Private, 91275, Some-college, 10, Never-married, Adm-clerical, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 56, Private, 244554, 10th, 6, Widowed, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 49, Private, 232586, 5th-6th, 3, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Self-emp-inc, 127678, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 80, United-States, <=50K 44, Private, 162184, Some-college, 10, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 408229, 1st-4th, 2, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 45, El-Salvador, <=50K 43, State-gov, 139734, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 40, United-States, >50K 62, Private, 197286, 12th, 8, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 48, Germany, <=50K 52, Private, 229983, Prof-school, 15, Married-civ-spouse, Prof-specialty, Wife, White, Female, 3103, 0, 30, United-States, >50K 25, Private, 252803, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 63, Self-emp-inc, 110890, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 70, United-States, >50K 51, Private, 160724, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 99, South, <=50K 25, Private, 89625, HS-grad, 9, Never-married, Adm-clerical, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 62, ?, 266037, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 126730, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 48, Federal-gov, 96854, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 32, Private, 186788, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 28996, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 30, Self-emp-not-inc, 347166, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 45, State-gov, 110311, Masters, 14, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 310850, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 41, Private, 220694, Bachelors, 13, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 37, United-States, <=50K 61, Private, 149405, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 40, United-States, <=50K 70, Self-emp-inc, 131699, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 55, United-States, <=50K 55, Private, 49996, 11th, 7, Never-married, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 35, Private, 187112, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 36, Private, 180859, Assoc-voc, 11, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 38, United-States, <=50K 29, Private, 185647, Some-college, 10, Never-married, Tech-support, Own-child, White, Male, 0, 0, 60, United-States, <=50K 30, Private, 316606, Bachelors, 13, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 274657, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, ?, <=50K 39, Federal-gov, 193583, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 5455, 0, 60, United-States, <=50K 18, Private, 338836, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 28, Private, 216814, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 27, Private, 106935, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 38, Private, 223433, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 174789, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 135603, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 25, ?, 344719, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 4, United-States, <=50K 38, Private, 372484, 11th, 7, Never-married, Other-service, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 23, Private, 181820, Some-college, 10, Never-married, Farming-fishing, Unmarried, White, Male, 0, 0, 45, United-States, <=50K 40, Private, 235371, Assoc-voc, 11, Divorced, Prof-specialty, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 36, Self-emp-inc, 216711, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 50, ?, >50K 20, Private, 299399, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 41, Private, 202508, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, <=50K 44, Private, 172025, Some-college, 10, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 49, Self-emp-inc, 246891, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 22, Private, 450920, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 26, Private, 53598, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 103757, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 76017, HS-grad, 9, Widowed, Other-service, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 28, Self-emp-inc, 80158, HS-grad, 9, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 37, Federal-gov, 90881, Some-college, 10, Separated, Exec-managerial, Not-in-family, White, Male, 8614, 0, 55, United-States, >50K 44, Private, 427952, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, ?, 230955, 12th, 8, Never-married, ?, Not-in-family, Black, Female, 0, 0, 35, United-States, <=50K 53, Private, 177916, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 7298, 0, 40, United-States, >50K 36, Private, 342642, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 15, United-States, <=50K 77, Private, 253642, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, Other, Male, 0, 0, 30, United-States, <=50K 21, Private, 219086, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 35, United-States, <=50K 24, Private, 162593, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 30, Private, 87561, Assoc-acdm, 12, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 51, Local-gov, 142411, Assoc-voc, 11, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 22, Private, 154422, Some-college, 10, Divorced, Sales, Own-child, Asian-Pac-Islander, Female, 0, 0, 30, Philippines, <=50K 23, Private, 169104, Some-college, 10, Never-married, Sales, Own-child, Asian-Pac-Islander, Male, 0, 0, 25, United-States, <=50K 47, Private, 193047, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 50, United-States, >50K 17, Private, 151141, 12th, 8, Never-married, Sales, Own-child, White, Male, 0, 0, 20, United-States, <=50K 48, Private, 267912, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 50, Mexico, >50K 43, Private, 137126, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 34, Private, 152453, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Guatemala, <=50K 19, Private, 357059, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 35, United-States, <=50K 42, State-gov, 202011, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 98283, Bachelors, 13, Never-married, Exec-managerial, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 61, Self-emp-not-inc, 176965, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 63, Private, 187919, 11th, 7, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 30, United-States, <=50K 65, Private, 274916, HS-grad, 9, Widowed, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 105813, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Husband, White, Male, 7298, 0, 40, United-States, >50K 41, Local-gov, 193524, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 152734, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 40, ?, <=50K 21, Private, 263641, HS-grad, 9, Divorced, Sales, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 48, Local-gov, 102076, Bachelors, 13, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 51, State-gov, 155594, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 1887, 40, United-States, >50K 43, Private, 33331, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, <=50K 22, State-gov, 156773, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 15, ?, <=50K 56, Self-emp-not-inc, 115439, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 47, Private, 181652, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 120268, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 24, United-States, <=50K 39, Private, 196308, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 24, United-States, <=50K 45, Self-emp-not-inc, 40690, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 75, United-States, <=50K 49, Private, 228583, HS-grad, 9, Divorced, Other-service, Unmarried, White, Male, 0, 0, 40, Columbia, <=50K 23, Private, 695136, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 69, Private, 209236, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 36, United-States, <=50K 41, Federal-gov, 214838, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 40, Self-emp-not-inc, 188436, HS-grad, 9, Separated, Exec-managerial, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 177625, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 124591, HS-grad, 9, Never-married, Handlers-cleaners, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 230856, Some-college, 10, Never-married, Prof-specialty, Not-in-family, Black, Female, 3325, 0, 50, United-States, <=50K 50, Federal-gov, 221532, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 21, Private, 232577, Assoc-voc, 11, Never-married, Tech-support, Own-child, White, Female, 0, 0, 30, United-States, <=50K 48, Private, 168216, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 214702, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 42, United-States, >50K 63, Private, 237620, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 30, United-States, <=50K 47, State-gov, 54887, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Self-emp-not-inc, 164526, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 14084, 0, 45, United-States, >50K 28, Private, 224506, Some-college, 10, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 40, ?, <=50K 58, Private, 183870, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 208330, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 51, United-States, <=50K 67, Self-emp-inc, 168370, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 62, Self-emp-not-inc, 320376, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 48, United-States, <=50K 28, Private, 192384, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 167350, 12th, 8, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 46, Self-emp-not-inc, 103538, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 65, United-States, >50K 29, Private, 58522, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 191342, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, >50K 25, Private, 193820, Masters, 14, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 35, United-States, <=50K 20, Private, 258490, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 21, Private, 56520, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 102476, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 44, Self-emp-inc, 311357, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 37, Private, 166497, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 38, United-States, <=50K 50, Private, 160724, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 7298, 0, 40, Philippines, >50K 29, Private, 338270, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 282394, Some-college, 10, Never-married, Sales, Own-child, Black, Female, 0, 0, 21, United-States, <=50K 32, Private, 383269, Bachelors, 13, Never-married, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 58, Private, 119386, Assoc-voc, 11, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 50, Private, 196975, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Private, 334221, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 18, United-States, <=50K 58, Private, 27385, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 29, State-gov, 133846, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 361888, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, >50K 21, Private, 230429, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 49, Private, 328776, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 60, Private, 243829, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 39, Private, 306646, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 3103, 0, 50, United-States, >50K 50, Private, 138179, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1902, 40, United-States, >50K 30, Private, 280069, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 55, Private, 305759, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 40, ?, <=50K 64, Local-gov, 164876, HS-grad, 9, Divorced, Transport-moving, Unmarried, White, Male, 0, 0, 20, United-States, <=50K 29, Self-emp-inc, 138597, Assoc-acdm, 12, Never-married, Prof-specialty, Other-relative, Black, Female, 0, 0, 40, United-States, <=50K 40, Private, 111483, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 40, United-States, >50K 42, Private, 144778, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 55, Private, 171015, HS-grad, 9, Widowed, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 112494, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 28, Private, 408473, 12th, 8, Never-married, Sales, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 46, State-gov, 27802, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 38, United-States, >50K 34, Private, 236318, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 121836, Masters, 14, Married-civ-spouse, Adm-clerical, Wife, White, Female, 7688, 0, 38, United-States, >50K 43, Self-emp-not-inc, 315971, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 698418, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 25, United-States, <=50K 21, Private, 329530, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Mexico, <=50K 65, Private, 194456, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, England, >50K 20, Private, 282579, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, State-gov, 26401, Masters, 14, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 38, State-gov, 364958, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 3464, 0, 40, United-States, <=50K 22, Private, 83998, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 94364, Some-college, 10, Never-married, Prof-specialty, Not-in-family, Other, Female, 0, 0, 20, United-States, <=50K 44, Private, 174189, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 44, Local-gov, 101967, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 146908, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 38, Private, 126675, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 2205, 40, United-States, <=50K 21, Private, 31606, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 25, Germany, <=50K 24, Private, 132327, Some-college, 10, Married-spouse-absent, Sales, Unmarried, Other, Female, 0, 0, 30, Ecuador, <=50K 24, Private, 112459, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 28, Private, 48894, HS-grad, 9, Married-civ-spouse, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 181943, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 48, Private, 247685, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 3325, 0, 40, United-States, <=50K 24, Local-gov, 195808, HS-grad, 9, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 172052, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 35, South, >50K 50, Local-gov, 50178, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 4064, 0, 55, United-States, <=50K 68, Private, 351711, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, State-gov, 190305, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 22, Private, 464103, 1st-4th, 2, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Guatemala, <=50K 18, ?, 36348, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 48, United-States, <=50K 25, Private, 120238, HS-grad, 9, Married-spouse-absent, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, Poland, <=50K 28, Private, 354095, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 17, Local-gov, 308901, 11th, 7, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 15, United-States, <=50K 24, State-gov, 208826, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 99, England, <=50K 20, Private, 369677, 10th, 6, Separated, Sales, Not-in-family, White, Female, 0, 0, 36, United-States, <=50K 45, Federal-gov, 98524, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 44, Private, 239723, Some-college, 10, Married-spouse-absent, Craft-repair, Unmarried, White, Female, 1506, 0, 45, United-States, <=50K 57, Private, 231232, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 236396, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 1902, 55, United-States, >50K 24, ?, 119156, Bachelors, 13, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 320451, Some-college, 10, Never-married, Protective-serv, Own-child, Asian-Pac-Islander, Male, 0, 0, 24, India, <=50K 41, Private, 38397, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 51, Self-emp-inc, 189183, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Local-gov, 199281, Bachelors, 13, Separated, Prof-specialty, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 286342, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 50, Private, 152810, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Self-emp-inc, 176981, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 50, United-States, <=50K 17, Private, 117549, 10th, 6, Never-married, Sales, Other-relative, Black, Female, 0, 0, 12, United-States, <=50K 64, Private, 254797, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 133336, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Self-emp-not-inc, 182826, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, <=50K 51, Private, 136224, Bachelors, 13, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 39, Self-emp-not-inc, 134475, Bachelors, 13, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 1762, 40, United-States, <=50K 48, Private, 272778, Some-college, 10, Divorced, Other-service, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 44, Private, 279183, Some-college, 10, Married-civ-spouse, Other-service, Own-child, White, Female, 0, 0, 40, United-States, >50K 47, Private, 110243, 11th, 7, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 202071, HS-grad, 9, Widowed, Craft-repair, Own-child, White, Female, 0, 0, 40, United-States, <=50K 58, Private, 197642, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 39, United-States, <=50K 19, Private, 125591, 11th, 7, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 197462, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Private, 238831, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 182177, Bachelors, 13, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Yugoslavia, <=50K 40, Local-gov, 240504, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 48, Self-emp-inc, 125892, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 38, United-States, >50K 46, Private, 154430, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 32, Private, 207685, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Wife, Black, Female, 3908, 0, 40, United-States, <=50K 50, Private, 222020, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 243240, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 37, United-States, <=50K 26, Private, 158734, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 36, Private, 257691, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 26, Private, 144483, Assoc-voc, 11, Divorced, Sales, Own-child, White, Female, 594, 0, 35, United-States, <=50K 19, Private, 209826, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 15, United-States, <=50K 53, Private, 30244, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 40, United-States, >50K 54, Private, 133050, Some-college, 10, Never-married, Sales, Not-in-family, Black, Male, 0, 0, 41, United-States, <=50K 29, Private, 138332, Some-college, 10, Married-civ-spouse, Adm-clerical, Own-child, White, Female, 0, 0, 6, United-States, <=50K 81, Private, 201398, Masters, 14, Widowed, Prof-specialty, Unmarried, White, Male, 0, 0, 60, ?, <=50K 37, Private, 526968, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 38, United-States, >50K 40, Private, 79036, Assoc-voc, 11, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 36, Private, 240323, Some-college, 10, Widowed, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 18, Private, 270544, 12th, 8, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 30, United-States, <=50K 44, State-gov, 199551, 11th, 7, Separated, Tech-support, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 36, Private, 231052, HS-grad, 9, Separated, Other-service, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 69, State-gov, 203072, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 17, Private, 126771, 12th, 8, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 7, United-States, <=50K 38, Private, 31848, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 328981, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 52, Private, 159670, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 450695, Assoc-acdm, 12, Never-married, Sales, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 57, Private, 182028, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 349620, 10th, 6, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 161066, HS-grad, 9, Divorced, Craft-repair, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 50, United-States, <=50K 46, Private, 213611, 7th-8th, 4, Married-spouse-absent, Priv-house-serv, Unmarried, White, Female, 0, 1594, 24, Guatemala, <=50K 21, Private, 548303, HS-grad, 9, Married-civ-spouse, Prof-specialty, Own-child, White, Male, 0, 0, 40, Mexico, >50K 29, Private, 150861, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, Japan, <=50K 33, ?, 335625, Some-college, 10, Divorced, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 133766, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 70, United-States, <=50K 28, Private, 200511, HS-grad, 9, Separated, Farming-fishing, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 26, Private, 50103, Some-college, 10, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, <=50K 37, ?, 148266, Prof-school, 15, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 6, Mexico, <=50K 49, Private, 177211, Bachelors, 13, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 132686, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, <=50K 57, Federal-gov, 21626, Some-college, 10, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 60, Private, 52900, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, ?, 150084, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 0, 25, United-States, <=50K 38, Private, 248886, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 42, United-States, <=50K 51, Self-emp-not-inc, 118259, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 3137, 0, 60, United-States, <=50K 60, Private, 145493, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 219546, Bachelors, 13, Married-civ-spouse, Exec-managerial, Other-relative, White, Male, 3411, 0, 47, United-States, <=50K 44, Federal-gov, 399155, HS-grad, 9, Never-married, Craft-repair, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 19, Self-emp-not-inc, 227310, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 59, Private, 333270, Masters, 14, Married-civ-spouse, Craft-repair, Wife, Asian-Pac-Islander, Female, 0, 0, 35, Philippines, <=50K 50, Private, 231495, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Federal-gov, 133935, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Federal-gov, 55237, Some-college, 10, Divorced, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 183034, Some-college, 10, Never-married, Sales, Own-child, Black, Male, 0, 0, 35, United-States, <=50K 32, Private, 245487, 5th-6th, 3, Married-civ-spouse, Machine-op-inspct, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, Mexico, <=50K 32, Private, 185480, Assoc-voc, 11, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 114251, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Private, 181814, HS-grad, 9, Never-married, Craft-repair, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 340917, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 60, United-States, >50K 37, Private, 241998, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 1977, 40, United-States, >50K 38, Self-emp-inc, 125324, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 80, United-States, >50K 36, Private, 34744, Assoc-acdm, 12, Divorced, Other-service, Unmarried, White, Female, 0, 0, 37, United-States, <=50K 56, Private, 131608, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Federal-gov, 226916, Bachelors, 13, Widowed, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 56, Private, 124137, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 41, United-States, <=50K 17, Private, 96282, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 14, United-States, <=50K 46, Private, 337050, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 45, United-States, >50K 56, Private, 229335, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 61, State-gov, 199495, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 111675, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 43, United-States, <=50K 27, Private, 139209, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 50, Self-emp-not-inc, 32372, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 30, United-States, <=50K 33, Self-emp-not-inc, 203784, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 62, United-States, <=50K 33, Private, 164190, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 40, United-States, >50K 38, Private, 64875, Some-college, 10, Never-married, Farming-fishing, Unmarried, White, Male, 0, 0, 60, United-States, <=50K 51, Private, 41806, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 208725, Assoc-acdm, 12, Never-married, Sales, Not-in-family, White, Male, 0, 0, 42, United-States, <=50K 49, Local-gov, 79019, Masters, 14, Widowed, Prof-specialty, Unmarried, White, Female, 0, 0, 16, United-States, <=50K 26, Private, 136951, HS-grad, 9, Separated, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 42, Private, 203554, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 37, Private, 252947, Bachelors, 13, Never-married, Machine-op-inspct, Not-in-family, Black, Male, 0, 1719, 32, United-States, <=50K 38, Private, 170861, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 48, Private, 199590, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Mexico, >50K 41, Private, 529216, Bachelors, 13, Divorced, Tech-support, Unmarried, Black, Male, 7430, 0, 45, ?, >50K 33, Private, 195576, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 4386, 0, 60, United-States, <=50K 30, Private, 182177, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, Ireland, <=50K 25, State-gov, 183678, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 50, Private, 209320, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 54, Self-emp-inc, 206862, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 36, United-States, >50K 37, Private, 168941, 11th, 7, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 59, Self-emp-not-inc, 201263, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 55, United-States, >50K 17, Private, 75333, 10th, 6, Never-married, Sales, Own-child, Black, Female, 0, 0, 24, United-States, <=50K 65, ?, 299494, 11th, 7, Married-civ-spouse, ?, Husband, White, Male, 1797, 0, 40, United-States, <=50K 56, Self-emp-not-inc, 163212, HS-grad, 9, Widowed, Adm-clerical, Unmarried, White, Female, 99999, 0, 40, United-States, >50K 57, Private, 139290, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 33, Private, 400416, 10th, 6, Never-married, Other-service, Own-child, Black, Male, 0, 0, 20, United-States, <=50K 41, Self-emp-not-inc, 223763, Masters, 14, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 65, United-States, <=50K 45, Private, 77927, Bachelors, 13, Widowed, Other-service, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 50, Private, 175804, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 48, United-States, <=50K 18, Private, 91525, HS-grad, 9, Never-married, Sales, Other-relative, White, Male, 0, 0, 25, United-States, <=50K 19, Private, 279968, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 26, Private, 77698, Some-college, 10, Married-civ-spouse, Prof-specialty, Wife, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 61, ?, 198686, Assoc-acdm, 12, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 2, United-States, >50K 67, ?, 190340, 11th, 7, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 113491, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Private, 202878, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 27, Private, 108431, Some-college, 10, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 35, Private, 194490, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 37, Private, 48093, Bachelors, 13, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 90, United-States, >50K 22, Private, 136824, 11th, 7, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 143280, 10th, 6, Never-married, Priv-house-serv, Own-child, White, Female, 0, 0, 24, United-States, <=50K 26, Private, 150062, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 27, Local-gov, 298510, HS-grad, 9, Divorced, Protective-serv, Own-child, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 177147, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 6849, 0, 65, United-States, <=50K 51, Private, 115025, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 350440, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, >50K 60, Private, 83850, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 62669, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 24, Private, 229773, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 40, Local-gov, 196234, HS-grad, 9, Divorced, Craft-repair, Own-child, White, Female, 0, 0, 40, Puerto-Rico, <=50K 69, ?, 163595, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 44, Private, 157249, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 1977, 50, United-States, >50K 65, Private, 80174, HS-grad, 9, Divorced, Exec-managerial, Other-relative, White, Female, 1848, 0, 50, United-States, <=50K 52, Self-emp-inc, 49069, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 38, Private, 122952, HS-grad, 9, Separated, Craft-repair, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 18, Private, 123856, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 49, United-States, <=50K 24, Private, 216181, Assoc-voc, 11, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 180062, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 21, Private, 188535, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 44, United-States, <=50K 67, Self-emp-not-inc, 106143, Doctorate, 16, Married-civ-spouse, Sales, Husband, White, Male, 20051, 0, 40, United-States, >50K 64, Self-emp-not-inc, 170421, Some-college, 10, Widowed, Craft-repair, Not-in-family, White, Female, 0, 0, 8, United-States, <=50K 25, Private, 283087, Some-college, 10, Never-married, Exec-managerial, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 34, Federal-gov, 341051, Masters, 14, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, >50K 39, Self-emp-not-inc, 34378, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 26, Private, 380674, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 52, United-States, <=50K 19, Private, 304469, 10th, 6, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 25, United-States, <=50K 35, Private, 99146, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 26, Private, 205109, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 99156, HS-grad, 9, Separated, Other-service, Own-child, White, Male, 0, 0, 35, United-States, <=50K 45, Private, 97842, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 65, United-States, <=50K 18, Private, 100875, 11th, 7, Never-married, Other-service, Unmarried, White, Female, 0, 0, 28, United-States, <=50K 51, Private, 200576, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 63, United-States, <=50K 36, Private, 355053, HS-grad, 9, Separated, Other-service, Unmarried, Black, Female, 0, 0, 28, United-States, <=50K 18, Private, 118376, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 16, ?, <=50K 37, Local-gov, 117760, Assoc-voc, 11, Never-married, Protective-serv, Not-in-family, White, Male, 4650, 0, 40, United-States, <=50K 37, Private, 117567, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 39, Federal-gov, 189632, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 21, Private, 170108, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 46, State-gov, 27243, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 45, United-States, >50K 33, Private, 192663, HS-grad, 9, Separated, Sales, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 23, Private, 526164, Bachelors, 13, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 52, Self-emp-not-inc, 146579, HS-grad, 9, Divorced, Sales, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 28, Private, 60288, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 23, State-gov, 241951, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 48, Self-emp-inc, 213140, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 17, Private, 218124, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 22, Self-emp-not-inc, 279802, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 3, United-States, <=50K 26, Private, 153078, HS-grad, 9, Never-married, Adm-clerical, Own-child, Asian-Pac-Islander, Male, 0, 0, 80, ?, >50K 40, Private, 167919, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 90, Private, 250832, 10th, 6, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 193158, HS-grad, 9, Divorced, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 172032, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 39484, Bachelors, 13, Married-civ-spouse, Other-service, Husband, White, Male, 7298, 0, 42, United-States, >50K 45, Private, 84298, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 50, United-States, >50K 43, Private, 269015, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, Germany, >50K 17, ?, 262196, 10th, 6, Never-married, ?, Own-child, White, Male, 0, 0, 8, United-States, <=50K 49, Federal-gov, 125892, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 134890, Bachelors, 13, Never-married, Tech-support, Own-child, White, Male, 0, 0, 50, United-States, <=50K 60, Self-emp-not-inc, 261119, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 119409, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, Other, Female, 0, 0, 40, Columbia, <=50K 53, Self-emp-not-inc, 118793, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 19, Private, 184207, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, Self-emp-not-inc, 191027, HS-grad, 9, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 207782, Assoc-acdm, 12, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, United-States, <=50K 48, Self-emp-not-inc, 209146, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 76, ?, 79445, 10th, 6, Married-civ-spouse, ?, Husband, White, Male, 1173, 0, 40, United-States, <=50K 19, Private, 187724, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 28, Private, 66777, Assoc-voc, 11, Married-civ-spouse, Other-service, Other-relative, White, Female, 3137, 0, 40, United-States, <=50K 58, Private, 158002, Some-college, 10, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 40, United-States, <=50K 19, Self-emp-not-inc, 305834, Some-college, 10, Never-married, Craft-repair, Own-child, White, Female, 0, 0, 25, United-States, <=50K 37, ?, 122265, HS-grad, 9, Divorced, ?, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 42, ?, <=50K 22, Private, 211798, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 52, Self-emp-not-inc, 123011, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 31, Private, 36302, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, <=50K 50, Self-emp-not-inc, 176867, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 3781, 0, 40, United-States, <=50K 62, Private, 169204, HS-grad, 9, Widowed, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 38232, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 64, State-gov, 277657, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 24, United-States, <=50K 38, Private, 32271, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 116825, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 80, United-States, >50K 28, Self-emp-not-inc, 226198, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 28145, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 52, United-States, <=50K 39, Private, 140477, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 10, United-States, <=50K 50, Private, 165050, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Self-emp-inc, 202937, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 36, Private, 316298, Bachelors, 13, Never-married, Tech-support, Own-child, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 203070, Assoc-voc, 11, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 49, United-States, <=50K 51, Self-emp-inc, 103995, Assoc-acdm, 12, Never-married, Sales, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 28, Private, 176137, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 32, United-States, <=50K 57, Self-emp-not-inc, 103948, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 30, United-States, >50K 40, Local-gov, 39581, Prof-school, 15, Separated, Prof-specialty, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 27, Private, 506436, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, Peru, <=50K 32, Private, 226975, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 1876, 60, United-States, <=50K 49, State-gov, 154493, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 44, United-States, <=50K 34, Self-emp-not-inc, 137223, 10th, 6, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 102323, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 257765, 7th-8th, 4, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, Guatemala, <=50K 52, Private, 42924, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 43, Private, 167599, 11th, 7, Married-civ-spouse, Handlers-cleaners, Wife, White, Female, 0, 0, 25, United-States, <=50K 84, ?, 368925, 5th-6th, 3, Widowed, ?, Not-in-family, White, Male, 0, 0, 15, United-States, <=50K 79, ?, 100881, Assoc-acdm, 12, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 2, United-States, >50K 35, Private, 52738, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 46, United-States, <=50K 56, Private, 98418, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 30, Private, 381153, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 103700, HS-grad, 9, Widowed, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 298635, Bachelors, 13, Never-married, Sales, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 50, United-States, <=50K 32, Private, 127895, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 44, Self-emp-inc, 212760, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 32, Private, 281384, HS-grad, 9, Married-AF-spouse, Other-service, Other-relative, White, Female, 0, 0, 10, United-States, <=50K 60, Private, 181200, 12th, 8, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 257364, Some-college, 10, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 50, Private, 283281, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 58, Private, 214502, 9th, 5, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 50, United-States, >50K 41, Private, 69333, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 28, Private, 190060, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 53, Private, 95864, HS-grad, 9, Never-married, Adm-clerical, Other-relative, White, Male, 0, 0, 35, United-States, <=50K 71, ?, 144872, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 6514, 0, 40, United-States, >50K 17, ?, 275778, 9th, 5, Never-married, ?, Own-child, White, Female, 0, 0, 25, Mexico, <=50K 45, Private, 27332, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 24395, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 30, United-States, <=50K 25, Private, 330695, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 40, Self-emp-not-inc, 171615, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 35, United-States, >50K 28, Private, 116372, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 27, Private, 38599, 12th, 8, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 19, Local-gov, 202184, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 15, United-States, <=50K 24, Private, 315303, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 25, United-States, <=50K 38, Private, 103456, Bachelors, 13, Separated, Prof-specialty, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 24, State-gov, 163480, Masters, 14, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 18, Private, 317425, 11th, 7, Never-married, Other-service, Own-child, Black, Male, 0, 0, 7, United-States, <=50K 58, Private, 216941, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 116541, Masters, 14, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 44, United-States, >50K 43, Private, 186396, 9th, 5, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 45, Private, 273194, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 3137, 0, 35, United-States, <=50K 24, Private, 385540, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, Mexico, <=50K 63, Private, 201631, 9th, 5, Married-civ-spouse, Farming-fishing, Husband, Black, Male, 0, 0, 40, United-States, <=50K 40, Private, 439919, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 21, Private, 182117, Bachelors, 13, Never-married, Other-service, Other-relative, White, Male, 0, 0, 20, United-States, <=50K 20, State-gov, 334113, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 184837, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 7298, 0, 40, United-States, >50K 49, ?, 228372, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 20, United-States, >50K 47, Federal-gov, 211123, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Self-emp-inc, 38819, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 36, United-States, <=50K 61, Private, 162391, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1651, 40, United-States, <=50K 23, ?, 302836, Assoc-acdm, 12, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, El-Salvador, <=50K 35, State-gov, 89040, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Private, 264210, Some-college, 10, Married-civ-spouse, Farming-fishing, Wife, White, Female, 0, 0, 20, United-States, <=50K 18, Private, 87157, 12th, 8, Never-married, Other-service, Own-child, White, Male, 0, 0, 25, United-States, <=50K 28, Self-emp-not-inc, 398918, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 62, ?, 123612, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 4, United-States, <=50K 20, Private, 155818, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 28, Private, 243660, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 134195, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, Private, 238638, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 159929, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 198668, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 215504, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 158002, Some-college, 10, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 55, Ecuador, <=50K 53, Local-gov, 35305, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 57, United-States, <=50K 25, Private, 195994, 1st-4th, 2, Never-married, Priv-house-serv, Not-in-family, White, Female, 0, 0, 40, Guatemala, <=50K 44, State-gov, 321824, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 38, United-States, <=50K 22, Private, 180449, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 28, United-States, <=50K 40, Private, 201764, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 250038, Assoc-voc, 11, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, ?, <=50K 30, Self-emp-not-inc, 226535, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, Mexico, <=50K 51, Private, 136121, Assoc-voc, 11, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 17, Private, 47199, 11th, 7, Never-married, Priv-house-serv, Own-child, White, Female, 0, 0, 24, United-States, <=50K 46, Local-gov, 215895, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 50, State-gov, 24647, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 34, Private, 734193, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 42, ?, 321086, Masters, 14, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 50, United-States, <=50K 41, Federal-gov, 192589, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 326283, Bachelors, 13, Never-married, Other-service, Unmarried, Other, Male, 0, 0, 40, United-States, <=50K 32, Private, 207284, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 109089, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 70, United-States, <=50K 50, Private, 274528, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 77, Private, 142646, 7th-8th, 4, Widowed, Priv-house-serv, Unmarried, White, Female, 0, 0, 23, United-States, <=50K 33, Private, 180859, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 47, Self-emp-inc, 188610, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, <=50K 64, Private, 169604, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 260560, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 34, Local-gov, 188245, HS-grad, 9, Never-married, Prof-specialty, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 67, Local-gov, 103315, Masters, 14, Never-married, Exec-managerial, Other-relative, White, Female, 15831, 0, 72, United-States, >50K 37, Local-gov, 52465, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 737315, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 22, ?, 195143, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 29, United-States, <=50K 50, Self-emp-not-inc, 219420, Doctorate, 16, Divorced, Sales, Not-in-family, White, Male, 0, 0, 64, United-States, <=50K 60, Private, 198170, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 46, Local-gov, 183168, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 43, United-States, <=50K 44, Private, 196545, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 40, United-States, >50K 43, Private, 168412, HS-grad, 9, Married-civ-spouse, Sales, Other-relative, White, Female, 0, 0, 44, Poland, <=50K 48, Private, 174386, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, El-Salvador, >50K 36, Private, 544686, HS-grad, 9, Never-married, Adm-clerical, Other-relative, White, Female, 2907, 0, 40, Nicaragua, <=50K 48, Private, 95661, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 43, United-States, <=50K 37, Private, 468713, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 169112, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 52, Private, 74024, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 27, Private, 110622, 5th-6th, 3, Never-married, Sales, Own-child, Asian-Pac-Islander, Female, 0, 0, 20, Vietnam, <=50K 43, Local-gov, 33331, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Private, 181557, HS-grad, 9, Never-married, Other-service, Own-child, Black, Male, 0, 0, 25, United-States, <=50K 66, Private, 142624, Assoc-acdm, 12, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 5556, 0, 40, Yugoslavia, >50K 37, Self-emp-not-inc, 192251, 10th, 6, Married-civ-spouse, Other-service, Wife, White, Female, 2635, 0, 40, United-States, <=50K 35, Private, 146091, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Local-gov, 174575, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 5178, 0, 40, United-States, >50K 49, Private, 200949, 10th, 6, Never-married, Other-service, Unmarried, White, Female, 0, 0, 38, Peru, <=50K 51, Local-gov, 201560, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 71, Federal-gov, 149386, HS-grad, 9, Widowed, Exec-managerial, Not-in-family, White, Male, 0, 0, 9, United-States, <=50K 50, Local-gov, 168672, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 1902, 40, United-States, >50K 63, Private, 38352, HS-grad, 9, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 41, State-gov, 180272, Masters, 14, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 35, United-States, <=50K 24, State-gov, 275421, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 41, Local-gov, 173051, Some-college, 10, Divorced, Other-service, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 33, Local-gov, 167474, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Local-gov, 267138, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 23, Private, 135138, Bachelors, 13, Never-married, Sales, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 49, Private, 218357, Assoc-voc, 11, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 28, Self-emp-not-inc, 107236, 12th, 8, Married-civ-spouse, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 138416, 5th-6th, 3, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 56, Mexico, <=50K 28, Private, 154863, Bachelors, 13, Never-married, Adm-clerical, Own-child, Black, Male, 0, 0, 35, United-States, <=50K 37, Private, 194004, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 25, United-States, <=50K 19, Private, 339123, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 51, Local-gov, 548361, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 26, United-States, <=50K 25, Private, 101812, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 41, United-States, <=50K 49, Self-emp-inc, 127111, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 47, Private, 171807, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 48, Local-gov, 40666, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Local-gov, 340682, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 175052, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 26, ?, 321629, HS-grad, 9, Never-married, ?, Unmarried, White, Female, 0, 0, 16, United-States, <=50K 46, Private, 154405, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, United-States, <=50K 17, Private, 108402, 10th, 6, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 34, Private, 346275, 11th, 7, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 43, United-States, <=50K 44, Private, 42476, HS-grad, 9, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 30, United-States, <=50K 23, Private, 161708, Assoc-acdm, 12, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 35, Private, 70447, Some-college, 10, Never-married, Prof-specialty, Unmarried, Asian-Pac-Islander, Male, 4650, 0, 20, United-States, <=50K 30, Private, 189759, Bachelors, 13, Never-married, Transport-moving, Not-in-family, White, Male, 4865, 0, 40, United-States, <=50K 65, ?, 137354, Some-college, 10, Married-civ-spouse, ?, Husband, Asian-Pac-Islander, Male, 0, 0, 20, United-States, <=50K 34, Private, 250724, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, Jamaica, <=50K 34, Federal-gov, 149368, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 154641, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 38309, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Husband, White, Male, 2407, 0, 40, United-States, <=50K 53, Local-gov, 202733, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 70, United-States, >50K 34, Private, 56150, 11th, 7, Never-married, Transport-moving, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 260254, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 108083, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 45, United-States, <=50K 54, Self-emp-not-inc, 71344, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 32, Private, 174215, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 39, State-gov, 114366, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 39, Private, 158962, Some-college, 10, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 179498, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, Germany, <=50K 29, Private, 31935, HS-grad, 9, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 149909, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 42, United-States, >50K 20, ?, 58740, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 15, United-States, <=50K 39, Private, 216552, Masters, 14, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 255348, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 176050, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 71, ?, 125101, Assoc-voc, 11, Widowed, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 62, ?, 197286, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Local-gov, 337469, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 594, 0, 20, Mexico, <=50K 31, Private, 159737, HS-grad, 9, Never-married, Sales, Unmarried, Black, Female, 0, 0, 58, United-States, <=50K 39, Private, 316211, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 32, Private, 127610, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 1902, 32, United-States, >50K 45, Local-gov, 556652, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, >50K 19, Private, 265576, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 50, United-States, <=50K 43, Private, 347653, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 48, United-States, >50K 32, Private, 62374, Assoc-voc, 11, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Self-emp-not-inc, 170230, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 34, Private, 203051, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 27, United-States, <=50K 66, Self-emp-inc, 115880, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 167735, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1887, 40, United-States, >50K 46, Self-emp-inc, 181413, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 185554, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 350387, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 63, Private, 225102, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, ?, <=50K 55, Private, 105582, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 3103, 0, 40, United-States, >50K 35, Self-emp-not-inc, 350247, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 28, Private, 150025, 9th, 5, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, ?, >50K 37, Private, 107737, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 63, ?, 334741, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 20, United-States, <=50K 43, Private, 115562, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 42, United-States, >50K 30, Self-emp-not-inc, 131584, Assoc-voc, 11, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 60, United-States, <=50K 36, Local-gov, 95855, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 60, United-States, >50K 54, Private, 391016, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Federal-gov, 51089, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, >50K 78, Self-emp-inc, 188044, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 2392, 40, United-States, >50K 77, Private, 117898, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 28, Private, 70240, HS-grad, 9, Married-spouse-absent, Other-service, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 39, Self-emp-not-inc, 187693, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 72, United-States, >50K 37, Private, 341672, Bachelors, 13, Separated, Tech-support, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 34, Private, 208043, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7298, 0, 45, United-States, >50K 22, Local-gov, 289982, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 35, United-States, <=50K 54, Private, 76344, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 21, Private, 200973, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 36, Private, 111377, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 62, Self-emp-not-inc, 136684, HS-grad, 9, Widowed, Adm-clerical, Other-relative, White, Female, 0, 0, 30, United-States, <=50K 40, Private, 176716, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 47, Self-emp-not-inc, 166894, Some-college, 10, Divorced, Prof-specialty, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 38, Private, 243872, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 70, United-States, >50K 28, Private, 155621, 5th-6th, 3, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Columbia, <=50K 46, Private, 102597, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 60331, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 35, United-States, <=50K 37, Private, 75024, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 25, Canada, <=50K 69, Private, 174474, 10th, 6, Separated, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 28, Peru, <=50K 43, Private, 145441, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 53, Private, 83434, Bachelors, 13, Never-married, Other-service, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 21, Japan, >50K 20, Private, 691830, HS-grad, 9, Never-married, Sales, Own-child, Black, Female, 0, 0, 35, United-States, <=50K 22, Private, 189203, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 48, Private, 115784, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 44, United-States, <=50K 40, Federal-gov, 280167, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 68, ?, 407338, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 20, United-States, <=50K 39, Private, 52978, Some-college, 10, Divorced, Other-service, Not-in-family, White, Female, 0, 1721, 55, United-States, <=50K 57, Private, 169329, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, Black, Male, 0, 1887, 40, Trinadad&Tobago, >50K 23, Private, 315065, 10th, 6, Never-married, Other-service, Unmarried, White, Male, 0, 0, 60, Mexico, <=50K 25, Local-gov, 167835, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 38, United-States, >50K 22, Private, 63105, HS-grad, 9, Never-married, Prof-specialty, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 23, Private, 520775, 12th, 8, Never-married, Priv-house-serv, Own-child, White, Male, 0, 0, 30, United-States, <=50K 41, Local-gov, 47902, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 25, Private, 145434, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 58, Private, 56392, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 162312, HS-grad, 9, Divorced, Sales, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 45, Japan, <=50K 28, Private, 204074, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 48, United-States, <=50K 19, Private, 99246, 11th, 7, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 44, Private, 102085, Some-college, 10, Divorced, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 68, Private, 168794, Preschool, 1, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 10, United-States, <=50K 33, State-gov, 332379, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 24, Private, 233419, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 44, Self-emp-not-inc, 57233, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 38, Private, 192337, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 40, United-States, >50K 31, Private, 442429, HS-grad, 9, Separated, Craft-repair, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 29, Private, 369114, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 65, Private, 261334, 9th, 5, Widowed, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 55, Private, 160303, HS-grad, 9, Widowed, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 50474, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 321577, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 41, Private, 29591, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 33, Self-emp-not-inc, 334744, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 22, Self-emp-not-inc, 269474, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 287306, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 40, United-States, >50K 66, Private, 33619, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 4, United-States, <=50K 38, Private, 149347, Some-college, 10, Divorced, Sales, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 43, Private, 96249, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 42, United-States, >50K 40, Local-gov, 370502, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Mexico, <=50K 32, Private, 188246, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Private, 167558, HS-grad, 9, Never-married, Sales, Unmarried, White, Female, 0, 0, 35, Mexico, <=50K 35, Private, 292185, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 101593, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 50, United-States, >50K 33, Local-gov, 70164, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 60, United-States, <=50K 36, Private, 269722, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 33, Self-emp-not-inc, 175502, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 53, Private, 233165, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 27, Private, 177351, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 22, Private, 212114, Bachelors, 13, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 15, United-States, <=50K 26, Private, 288959, HS-grad, 9, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 36, United-States, <=50K 64, Private, 231619, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 21, United-States, <=50K 48, Private, 146919, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 23, Private, 388811, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 243560, Some-college, 10, Never-married, Sales, Unmarried, White, Female, 0, 0, 40, ?, <=50K 35, Self-emp-not-inc, 98360, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 369538, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 65, Self-emp-not-inc, 31740, Some-college, 10, Widowed, Exec-managerial, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 53, Private, 223660, HS-grad, 9, Widowed, Machine-op-inspct, Not-in-family, White, Male, 6849, 0, 40, United-States, <=50K 18, Private, 333611, 5th-6th, 3, Never-married, Other-service, Other-relative, White, Male, 0, 0, 54, Mexico, <=50K 34, Self-emp-not-inc, 108247, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 28, Private, 76129, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, Guatemala, <=50K 37, Private, 91711, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 61, ?, 166855, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 10, United-States, <=50K 59, Private, 182062, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 5013, 0, 40, United-States, <=50K 32, Private, 252752, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 13550, 0, 60, United-States, >50K 31, Private, 43953, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 35, United-States, <=50K 25, Local-gov, 84224, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 81, Private, 100675, 1st-4th, 2, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 15, Poland, <=50K 47, Private, 155509, HS-grad, 9, Separated, Other-service, Other-relative, Black, Female, 0, 0, 35, United-States, <=50K 39, Private, 29814, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 241805, Some-college, 10, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 30, United-States, <=50K 44, Private, 214838, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, >50K 37, Private, 240810, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 41, Private, 154076, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, >50K 27, ?, 175552, 5th-6th, 3, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 40, Mexico, <=50K 55, Private, 170287, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, Poland, >50K 60, Private, 145995, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 22, Private, 433669, Assoc-acdm, 12, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 36, ?, <=50K 23, Private, 233626, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 19, Private, 607799, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 45, Private, 88500, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 44, United-States, >50K 36, Private, 127809, HS-grad, 9, Separated, Other-service, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 46, Private, 243743, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 48, Private, 177211, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Self-emp-not-inc, 231180, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 50, United-States, <=50K 29, Private, 253856, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 20, United-States, <=50K 39, Private, 177075, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 152855, HS-grad, 9, Never-married, Exec-managerial, Own-child, Other, Female, 0, 0, 40, Mexico, <=50K 37, Private, 191137, Assoc-acdm, 12, Divorced, Prof-specialty, Unmarried, White, Male, 0, 0, 25, United-States, <=50K 49, Private, 255559, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 27, Private, 169815, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 221215, 10th, 6, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 35, Private, 270059, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 54, ?, 31588, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 2635, 0, 40, United-States, <=50K 17, Private, 345403, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 194897, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 33, Private, 388741, Some-college, 10, Never-married, Adm-clerical, Unmarried, Other, Female, 0, 0, 38, United-States, <=50K 33, Private, 355856, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 0, 60, United-States, <=50K 51, Private, 122109, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 35, United-States, <=50K 49, Private, 75673, HS-grad, 9, Never-married, Adm-clerical, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 49, Self-emp-inc, 141058, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 2339, 50, United-States, <=50K 41, Private, 47902, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 35, United-States, >50K 64, Private, 221343, 1st-4th, 2, Divorced, Priv-house-serv, Not-in-family, White, Female, 0, 0, 12, United-States, <=50K 40, Private, 255675, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 49, Federal-gov, 203505, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 125106, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 139890, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 76878, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 5178, 0, 40, United-States, >50K 47, Self-emp-not-inc, 28035, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 86, United-States, <=50K 30, Private, 43953, HS-grad, 9, Never-married, Adm-clerical, Other-relative, White, Female, 0, 1974, 40, United-States, <=50K 36, Private, 163237, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Local-gov, 55890, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Self-emp-not-inc, 255934, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 80, United-States, <=50K 61, Private, 168654, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, Canada, <=50K 47, Self-emp-not-inc, 39986, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, Private, 208451, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Private, 206681, 12th, 8, Never-married, Sales, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 33, Private, 117779, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 46, United-States, >50K 36, Self-emp-not-inc, 129150, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, >50K 38, ?, 177273, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 35, United-States, <=50K 34, Local-gov, 226443, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 56, Private, 146326, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 32, Private, 187901, Assoc-voc, 11, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 23, United-States, <=50K 26, Private, 97153, Assoc-acdm, 12, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 5178, 0, 40, United-States, >50K 49, Private, 188694, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 71, Private, 187493, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 19, Private, 212468, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 20, Private, 84726, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 137907, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 51, Private, 34361, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 20, United-States, >50K 38, Private, 254114, Some-college, 10, Married-spouse-absent, Prof-specialty, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 38, Private, 170174, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Self-emp-not-inc, 190895, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 24, Local-gov, 317443, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, Black, Female, 0, 0, 40, United-States, <=50K 40, Private, 375603, HS-grad, 9, Divorced, Adm-clerical, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 21, Private, 203076, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 35, United-States, <=50K 49, Private, 53893, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 18, ?, 171748, Some-college, 10, Never-married, ?, Own-child, Black, Female, 0, 0, 24, United-States, <=50K 54, Private, 167770, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 55, United-States, >50K 52, Private, 204584, Bachelors, 13, Married-spouse-absent, Exec-managerial, Not-in-family, White, Female, 0, 0, 42, United-States, <=50K 27, Private, 660870, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 20, Private, 105686, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, ?, 70282, Masters, 14, Married-civ-spouse, ?, Wife, Black, Female, 15024, 0, 2, United-States, >50K 31, Private, 148607, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 255849, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 19, Federal-gov, 255921, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, England, <=50K 33, Private, 113326, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 23, Private, 440456, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 105493, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 259757, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Male, 0, 653, 50, United-States, >50K 37, Local-gov, 89491, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 171818, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 51151, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Self-emp-not-inc, 188957, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 97933, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 32, Self-emp-inc, 195447, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 63, ?, 46907, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 8, United-States, >50K 54, Self-emp-inc, 383365, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 70, United-States, >50K 32, Self-emp-not-inc, 203408, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 44, United-States, <=50K 29, Local-gov, 148182, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 26, Local-gov, 211497, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Self-emp-not-inc, 48063, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 57, Private, 211804, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 3103, 0, 50, United-States, >50K 54, Private, 185407, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 225927, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Federal-gov, 314525, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Self-emp-not-inc, 208577, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 42, Private, 222884, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 55, United-States, >50K 31, Private, 209538, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Local-gov, 177114, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 50, Private, 173754, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Local-gov, 121370, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 37, Private, 67125, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 26, Private, 67240, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 198346, Bachelors, 13, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 24, Private, 141003, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 25, United-States, <=50K 24, Self-emp-inc, 60668, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 104256, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 34, United-States, <=50K 47, Private, 131002, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 33, Self-emp-not-inc, 155151, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 1740, 50, United-States, <=50K 26, Private, 177720, Assoc-acdm, 12, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 20, Private, 39615, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 203871, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 1887, 40, United-States, >50K 57, State-gov, 25045, Bachelors, 13, Divorced, Adm-clerical, Unmarried, White, Male, 2174, 0, 37, United-States, <=50K 36, Private, 112264, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 25, Private, 169100, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 155659, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Germany, >50K 39, Private, 291665, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 4508, 0, 24, United-States, <=50K 29, Private, 224215, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 18, Private, 270502, 11th, 7, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 20, United-States, <=50K 46, Private, 125487, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 51385, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 41, Private, 112763, HS-grad, 9, Widowed, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 50, Private, 108926, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 53, Private, 366957, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 99999, 0, 50, India, >50K 36, Local-gov, 109766, Bachelors, 13, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 38, Private, 226106, Some-college, 10, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 75, Self-emp-not-inc, 92792, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 35, United-States, <=50K 26, Private, 186950, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 44, Private, 230478, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Private, 231638, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 120461, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 33673, 12th, 8, Never-married, Transport-moving, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 35, United-States, <=50K 34, Private, 191385, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, <=50K 31, Self-emp-not-inc, 229946, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, Columbia, <=50K 47, Self-emp-not-inc, 160131, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 190895, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 50, United-States, >50K 18, Private, 126021, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Female, 0, 0, 20, United-States, <=50K 47, Private, 27815, 9th, 5, Divorced, Other-service, Not-in-family, White, Female, 0, 1719, 30, United-States, <=50K 42, Private, 203542, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 144592, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 38, Local-gov, 223004, Some-college, 10, Divorced, Protective-serv, Not-in-family, White, Male, 0, 0, 75, United-States, <=50K 22, Private, 183257, Some-college, 10, Never-married, Sales, Own-child, Black, Female, 0, 0, 20, United-States, <=50K 32, Private, 172714, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 131611, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 48, United-States, <=50K 41, Private, 253060, Prof-school, 15, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 46, Private, 471990, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 46, United-States, >50K 44, Private, 138966, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 38, United-States, <=50K 35, Private, 385412, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 18, ?, 184101, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 25, United-States, <=50K 60, Private, 103344, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 15024, 0, 40, United-States, >50K 36, Local-gov, 135786, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 25, United-States, <=50K 30, Private, 227359, Some-college, 10, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 40, State-gov, 86912, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 21, Private, 83033, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 2176, 0, 20, United-States, <=50K 25, Private, 172581, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 56, State-gov, 274111, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 1669, 40, United-States, <=50K 42, Private, 187795, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 55, United-States, >50K 26, Private, 483822, 7th-8th, 4, Never-married, Handlers-cleaners, Unmarried, White, Male, 0, 0, 40, Guatemala, <=50K 66, Self-emp-inc, 220543, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 48, Private, 152953, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 32, Dominican-Republic, <=50K 35, Private, 239755, Some-college, 10, Never-married, Sales, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 41, Private, 177905, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 19, Private, 200136, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 55, Self-emp-not-inc, 111625, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Self-emp-not-inc, 336513, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 15024, 0, 60, United-States, >50K 45, Private, 162915, Some-college, 10, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 29, Private, 116662, Bachelors, 13, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Self-emp-not-inc, 24763, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 40, United-States, >50K 65, Private, 225580, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 30, Private, 169104, Assoc-acdm, 12, Never-married, Other-service, Other-relative, Asian-Pac-Islander, Male, 0, 0, 40, Vietnam, <=50K 43, Private, 212894, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 93997, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Italy, <=50K 22, Private, 189924, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 23, Private, 274424, 11th, 7, Separated, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 188246, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 284211, HS-grad, 9, Widowed, Prof-specialty, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 21, Private, 198259, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 15, United-States, <=50K 31, Private, 368517, Assoc-acdm, 12, Never-married, Prof-specialty, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 34, Private, 168768, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 33, Federal-gov, 122220, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, Black, Female, 0, 0, 40, United-States, >50K 32, Private, 136204, Masters, 14, Separated, Exec-managerial, Not-in-family, White, Male, 0, 2824, 55, United-States, >50K 44, Private, 175641, 11th, 7, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 21, State-gov, 173324, Some-college, 10, Never-married, Other-service, Own-child, Black, Male, 0, 0, 20, United-States, <=50K 75, Local-gov, 31195, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 55, Federal-gov, 88876, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 60, United-States, >50K 43, Self-emp-not-inc, 176069, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 16, United-States, <=50K 31, Private, 215297, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 41, Private, 198425, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 26, Local-gov, 180957, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 23, Private, 206129, Assoc-voc, 11, Never-married, Craft-repair, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 42, Federal-gov, 65950, HS-grad, 9, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 29, Private, 197618, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 185357, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 28, Private, 134890, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 64, ?, 193043, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Federal-gov, 153633, Some-college, 10, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 65, Private, 115890, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 20, United-States, <=50K 34, Private, 394447, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 2463, 0, 50, France, <=50K 58, Private, 343957, Bachelors, 13, Divorced, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 63, ?, 247986, Prof-school, 15, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 30, United-States, >50K 50, Private, 238959, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 99999, 0, 60, ?, >50K 59, Private, 159048, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 423222, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 40, United-States, >50K 30, Private, 89735, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 31778, Bachelors, 13, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 51, ?, 157327, 5th-6th, 3, Married-civ-spouse, ?, Husband, Black, Male, 0, 0, 8, United-States, <=50K 47, Private, 233511, Masters, 14, Divorced, Sales, Not-in-family, White, Male, 27828, 0, 60, United-States, >50K 30, Private, 327112, Bachelors, 13, Divorced, Sales, Not-in-family, White, Male, 0, 1564, 40, United-States, >50K 34, Private, 236543, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 51, State-gov, 194475, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 303510, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 171242, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Self-emp-not-inc, 39388, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 62, Local-gov, 197218, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 18, United-States, <=50K 22, State-gov, 151991, Some-college, 10, Never-married, Tech-support, Own-child, White, Male, 0, 0, 20, United-States, <=50K 38, Private, 374524, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 34, ?, 267352, 11th, 7, Never-married, ?, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 45, Local-gov, 364563, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Private, 186035, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, <=50K 21, Private, 47541, HS-grad, 9, Divorced, Machine-op-inspct, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 151107, HS-grad, 9, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 24, Private, 500509, HS-grad, 9, Never-married, Other-service, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 47, Private, 138107, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 2258, 40, United-States, >50K 20, Federal-gov, 225515, Some-college, 10, Never-married, Tech-support, Own-child, White, Female, 0, 0, 24, United-States, <=50K 27, Private, 153291, Prof-school, 15, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 50, United-States, >50K 40, Private, 169885, HS-grad, 9, Separated, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 19, ?, 112780, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 30, United-States, <=50K 31, Local-gov, 175778, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 55213, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 1977, 52, United-States, >50K 48, Private, 38950, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 64, Self-emp-not-inc, 65991, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 7298, 0, 45, United-States, >50K 39, Private, 174330, HS-grad, 9, Separated, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 35224, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 175622, Assoc-voc, 11, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 164678, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 45, United-States, <=50K 50, ?, 87263, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 55, United-States, >50K 54, Private, 163671, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1887, 65, United-States, >50K 17, Self-emp-not-inc, 181317, 10th, 6, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 35, United-States, <=50K 33, Federal-gov, 177945, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, <=50K 28, Private, 47168, 10th, 6, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 39, Self-emp-not-inc, 190023, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 33, Private, 168782, Assoc-voc, 11, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 59, Private, 175290, 7th-8th, 4, Never-married, Other-service, Other-relative, White, Male, 0, 0, 32, United-States, <=50K 74, Private, 145463, 1st-4th, 2, Widowed, Priv-house-serv, Not-in-family, Black, Female, 0, 0, 15, United-States, <=50K 54, Private, 159755, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 113364, Assoc-acdm, 12, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 55, United-States, <=50K 31, Private, 487742, Some-college, 10, Separated, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 304710, Some-college, 10, Never-married, Sales, Own-child, Asian-Pac-Islander, Female, 0, 0, 20, United-States, <=50K 54, Local-gov, 185846, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 40, United-States, >50K 42, Private, 212894, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Husband, White, Male, 2407, 0, 40, United-States, <=50K 57, Self-emp-not-inc, 315460, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 36, United-States, <=50K 49, Private, 135643, HS-grad, 9, Widowed, Craft-repair, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, South, <=50K 40, Private, 220977, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 3103, 0, 40, India, >50K 19, ?, 117444, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 0, 30, United-States, <=50K 38, Private, 202683, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 164866, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 42, United-States, >50K 43, Private, 191814, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 50, United-States, >50K 32, ?, 227160, Some-college, 10, Divorced, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 158077, Bachelors, 13, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 191103, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 99, United-States, >50K 25, Private, 193701, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 40, Private, 143046, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 34, Private, 206297, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 48, United-States, >50K 35, Self-emp-not-inc, 188563, HS-grad, 9, Divorced, Farming-fishing, Own-child, White, Male, 0, 0, 50, United-States, <=50K 53, Private, 35102, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 34, United-States, <=50K 21, Private, 203055, Some-college, 10, Never-married, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 309932, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Self-emp-not-inc, 243432, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 22, Private, 177107, Assoc-voc, 11, Never-married, Prof-specialty, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 64, Self-emp-not-inc, 113929, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 35, United-States, <=50K 19, ?, 291509, 12th, 8, Never-married, ?, Own-child, White, Male, 0, 0, 28, United-States, <=50K 40, Private, 222011, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 3325, 0, 40, United-States, <=50K 34, Private, 186824, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 70, United-States, <=50K 46, Private, 192768, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 234962, HS-grad, 9, Never-married, Machine-op-inspct, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 32, Private, 83253, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 26, Private, 248990, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 346159, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 272656, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 55, United-States, >50K 22, Private, 60552, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 29, State-gov, 33798, Some-college, 10, Divorced, Adm-clerical, Own-child, White, Male, 0, 0, 20, United-States, <=50K 38, Self-emp-not-inc, 112158, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 99, United-States, <=50K 55, Private, 200992, Some-college, 10, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 26, Private, 98155, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Self-emp-inc, 79586, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Other, Male, 0, 0, 60, United-States, <=50K 25, State-gov, 143062, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 101146, HS-grad, 9, Divorced, Prof-specialty, Not-in-family, White, Female, 4650, 0, 40, United-States, <=50K 18, ?, 284450, 11th, 7, Never-married, ?, Own-child, White, Male, 0, 0, 25, United-States, <=50K 58, State-gov, 159021, 9th, 5, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Local-gov, 353270, Assoc-voc, 11, Never-married, Craft-repair, Own-child, White, Female, 0, 0, 40, United-States, <=50K 29, Self-emp-not-inc, 162312, Some-college, 10, Never-married, Exec-managerial, Own-child, Asian-Pac-Islander, Male, 0, 0, 45, South, <=50K 49, State-gov, 231961, Doctorate, 16, Divorced, Prof-specialty, Unmarried, White, Male, 0, 0, 50, United-States, >50K 38, Private, 181943, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 21, Private, 163595, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 35, United-States, <=50K 28, Private, 130856, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Private, 208875, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, El-Salvador, >50K 29, Self-emp-not-inc, 58744, Assoc-acdm, 12, Never-married, Other-service, Own-child, White, Male, 0, 0, 60, United-States, <=50K 48, Private, 116641, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 40, Private, 69333, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 320811, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 34, Private, 197886, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 57, Self-emp-not-inc, 253914, 1st-4th, 2, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 35, Mexico, <=50K 24, Private, 89154, 9th, 5, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, El-Salvador, <=50K 32, Private, 372317, 9th, 5, Separated, Other-service, Unmarried, White, Female, 0, 0, 23, Mexico, <=50K 18, Self-emp-not-inc, 296090, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 48, ?, <=50K 39, Private, 192614, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 56, United-States, <=50K 39, Private, 403489, 11th, 7, Divorced, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 169652, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 12, United-States, <=50K 20, Private, 217467, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 27, ?, 162104, 9th, 5, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 54, Private, 175912, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Self-emp-not-inc, 179533, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 75, United-States, >50K 27, Private, 149624, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 30, United-States, <=50K 27, Private, 289147, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 43, Federal-gov, 347720, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 22, Private, 406978, Bachelors, 13, Never-married, Exec-managerial, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 17, Private, 193199, 11th, 7, Never-married, Sales, Unmarried, White, Female, 0, 0, 12, Poland, <=50K 37, Self-emp-inc, 163998, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 49, Private, 173115, 10th, 6, Separated, Exec-managerial, Not-in-family, Black, Male, 4416, 0, 99, United-States, <=50K 33, Private, 333701, Assoc-voc, 11, Never-married, Other-service, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 21, State-gov, 48121, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Male, 0, 1602, 10, United-States, <=50K 45, Private, 186256, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 104525, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 104097, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 2829, 0, 60, United-States, <=50K 71, Private, 212806, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 36, United-States, <=50K 23, Local-gov, 203353, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 45, United-States, <=50K 41, Private, 130126, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 80, United-States, >50K 21, ?, 270043, 10th, 6, Never-married, ?, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 47, Private, 218435, HS-grad, 9, Married-spouse-absent, Sales, Unmarried, White, Female, 0, 0, 20, Cuba, <=50K 30, Private, 154120, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 40, Private, 193537, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, Dominican-Republic, <=50K 44, Private, 84535, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 0, 48, United-States, <=50K 50, Private, 150999, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 40, United-States, >50K 31, State-gov, 157673, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 68, Private, 217424, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 24, United-States, <=50K 45, Private, 358886, 12th, 8, Married-civ-spouse, Adm-clerical, Husband, White, Male, 2407, 0, 50, United-States, <=50K 38, Private, 186191, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 78, Self-emp-inc, 212660, 11th, 7, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 10, United-States, <=50K 31, Self-emp-inc, 31740, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 55, United-States, <=50K 39, Private, 498785, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Self-emp-not-inc, 35945, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 7298, 0, 45, United-States, >50K 46, Local-gov, 162566, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 50, Canada, <=50K 30, Private, 118861, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 0, 50, United-States, >50K 34, Private, 206609, Some-college, 10, Never-married, Sales, Unmarried, White, Male, 0, 0, 35, United-States, <=50K 30, Federal-gov, 423064, HS-grad, 9, Separated, Adm-clerical, Other-relative, Black, Male, 0, 0, 35, United-States, <=50K 47, Private, 191957, Bachelors, 13, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 40, United-States, >50K 40, Private, 223934, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 17, United-States, >50K 62, ?, 129246, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Self-emp-not-inc, 195486, HS-grad, 9, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 70, Jamaica, <=50K 40, Private, 114580, HS-grad, 9, Divorced, Craft-repair, Other-relative, White, Female, 0, 0, 40, Vietnam, <=50K 20, Private, 119215, Some-college, 10, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 240554, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 55, Private, 199067, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 42, United-States, >50K 51, Private, 144084, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 358682, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Local-gov, 59612, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 49, State-gov, 391585, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 40, United-States, >50K 30, Local-gov, 101345, HS-grad, 9, Separated, Other-service, Unmarried, White, Female, 0, 0, 26, United-States, <=50K 20, Private, 117618, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 231238, 9th, 5, Separated, Farming-fishing, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 42, Local-gov, 143046, HS-grad, 9, Widowed, Transport-moving, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 326857, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 2415, 65, United-States, >50K 43, Private, 203642, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 62, Private, 88579, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 21, Private, 240517, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 70, United-States, <=50K 58, Local-gov, 156649, 1st-4th, 2, Widowed, Handlers-cleaners, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 30, Private, 143392, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 365465, HS-grad, 9, Separated, Craft-repair, Unmarried, White, Male, 0, 0, 70, Philippines, <=50K 22, State-gov, 264710, Bachelors, 13, Never-married, Tech-support, Own-child, White, Female, 0, 0, 40, United-States, <=50K 64, State-gov, 223830, 9th, 5, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 42, Private, 154374, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 43, State-gov, 242521, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 124569, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 209230, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 6, United-States, <=50K 21, Private, 162228, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 45, Federal-gov, 60267, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 55, Self-emp-not-inc, 76901, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 24, Private, 137876, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 50, United-States, <=50K 70, Self-emp-not-inc, 347910, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 35, United-States, <=50K 27, Local-gov, 138917, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 34, Private, 532379, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 31532, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Self-emp-not-inc, 30973, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 117295, 1st-4th, 2, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 32, Private, 295282, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, <=50K 42, Private, 190786, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 246207, Bachelors, 13, Never-married, Machine-op-inspct, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 50, Private, 130780, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, United-States, <=50K 36, Private, 186212, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 42, Private, 175526, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 207025, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 6849, 0, 38, United-States, <=50K 39, Federal-gov, 82622, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 51, Private, 199688, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 60, ?, >50K 38, State-gov, 318886, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 52, United-States, <=50K 18, Private, 256005, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 63, Self-emp-not-inc, 217715, 5th-6th, 3, Never-married, Sales, Not-in-family, White, Female, 0, 0, 3, United-States, <=50K 50, Private, 205803, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 40, United-States, >50K 82, Self-emp-not-inc, 240491, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Cuba, <=50K 33, Private, 154120, HS-grad, 9, Divorced, Handlers-cleaners, Own-child, White, Male, 0, 0, 45, United-States, <=50K 37, Private, 69251, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 24, Private, 333505, HS-grad, 9, Married-spouse-absent, Transport-moving, Own-child, White, Male, 0, 0, 40, Peru, <=50K 31, Private, 168521, Bachelors, 13, Never-married, Exec-managerial, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 59, Private, 193568, HS-grad, 9, Divorced, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 426895, 12th, 8, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 55, United-States, <=50K 47, Self-emp-not-inc, 131826, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 79646, 11th, 7, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 27, Private, 167031, Bachelors, 13, Never-married, Prof-specialty, Unmarried, Other, Female, 0, 0, 33, United-States, <=50K 34, Private, 73199, 11th, 7, Never-married, Other-service, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 50, Private, 114056, Assoc-voc, 11, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 84, United-States, <=50K 57, Self-emp-not-inc, 110417, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 75, United-States, <=50K 60, Private, 33266, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 154410, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 56, ?, 154537, Some-college, 10, Divorced, ?, Unmarried, White, Female, 0, 0, 50, United-States, >50K 18, Private, 27780, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 25, United-States, <=50K 26, Private, 142914, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 75, United-States, <=50K 37, Private, 190987, Some-college, 10, Married-civ-spouse, Sales, Wife, White, Female, 7298, 0, 40, United-States, >50K 20, Private, 314422, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 30, United-States, <=50K 29, Local-gov, 273771, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 30, Private, 175083, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 52, United-States, <=50K 21, Private, 63665, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 15, United-States, <=50K 24, Local-gov, 193416, Some-college, 10, Never-married, Protective-serv, Own-child, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 74275, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 122609, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 225456, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 40, United-States, >50K 36, Local-gov, 116892, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 196971, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 72, United-States, <=50K 20, Private, 105312, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 46, Private, 108699, Some-college, 10, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 44, Private, 171615, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 39, Private, 388023, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 39, Private, 181553, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 45, Private, 170850, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 44, United-States, >50K 28, Private, 187479, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, <=50K 44, Private, 277720, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 35, United-States, <=50K 48, Local-gov, 493862, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 7298, 0, 38, United-States, >50K 27, Private, 220754, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 70, United-States, <=50K 34, Self-emp-not-inc, 209768, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 93225, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Federal-gov, 341709, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 236242, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 21, Private, 121889, Some-college, 10, Never-married, Sales, Own-child, Black, Female, 0, 0, 20, United-States, <=50K 18, Private, 318190, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 15, United-States, <=50K 63, Self-emp-not-inc, 111306, 7th-8th, 4, Widowed, Farming-fishing, Unmarried, White, Female, 0, 0, 10, United-States, <=50K 18, Private, 198614, 11th, 7, Never-married, Sales, Own-child, Black, Female, 0, 0, 8, United-States, <=50K 32, Private, 193231, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, ?, 104614, 11th, 7, Never-married, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 172368, 11th, 7, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 20, United-States, <=50K 23, Private, 60331, Some-college, 10, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 38, Private, 154568, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 40, ?, <=50K 36, Private, 192939, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 60, United-States, >50K 43, Private, 138184, HS-grad, 9, Divorced, Other-service, Not-in-family, Black, Female, 0, 1762, 35, United-States, <=50K 45, Private, 238567, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, England, >50K 30, Private, 208068, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Other, Male, 0, 0, 40, Mexico, <=50K 46, Private, 181810, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 4064, 0, 40, United-States, <=50K 24, Federal-gov, 283918, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 25, United-States, <=50K 42, Private, 107276, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 2444, 40, United-States, >50K 23, Private, 37783, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 263552, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 48, Private, 255439, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Self-emp-inc, 344275, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 44, United-States, <=50K 31, Private, 70568, 1st-4th, 2, Never-married, Other-service, Other-relative, White, Female, 0, 0, 25, El-Salvador, <=50K 18, Private, 127827, 12th, 8, Never-married, Sales, Own-child, White, Female, 0, 0, 25, United-States, <=50K 36, Private, 185203, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 58, Private, 123436, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 50, United-States, >50K 51, Self-emp-not-inc, 136322, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 1579, 40, United-States, <=50K 22, Private, 187052, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 72, Private, 177769, 10th, 6, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 15, United-States, <=50K 61, Private, 68268, 10th, 6, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 55, United-States, <=50K 42, Private, 424855, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 3908, 0, 40, United-States, <=50K 37, Federal-gov, 81853, HS-grad, 9, Divorced, Prof-specialty, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, ?, <=50K 30, Self-emp-inc, 153549, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 40, Private, 271393, Assoc-acdm, 12, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 198148, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 65, Private, 469602, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 15, United-States, <=50K 36, Private, 163290, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 295949, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, Self-emp-not-inc, 125279, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 64, Local-gov, 182866, HS-grad, 9, Widowed, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 61, Self-emp-not-inc, 111563, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 20, United-States, >50K 38, Private, 34173, Bachelors, 13, Never-married, Sales, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 27, Private, 183627, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 50, United-States, >50K 24, Private, 197757, Bachelors, 13, Never-married, Prof-specialty, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 39, Private, 98941, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 44, Private, 205474, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 47, Private, 206659, Some-college, 10, Divorced, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 73, ?, 191394, Prof-school, 15, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 66, Private, 244661, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 53, Private, 47396, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, >50K 43, State-gov, 270721, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 57, State-gov, 32694, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 44, Private, 171256, Assoc-acdm, 12, Divorced, Machine-op-inspct, Own-child, White, Female, 0, 0, 45, United-States, <=50K 59, Private, 169982, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 2002, 50, United-States, <=50K 52, Self-emp-not-inc, 217210, HS-grad, 9, Widowed, Other-service, Other-relative, Black, Female, 0, 0, 40, United-States, <=50K 46, Private, 218329, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 386643, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 37, Federal-gov, 125933, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Self-emp-not-inc, 155767, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 39, Federal-gov, 432555, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 1628, 40, United-States, <=50K 30, Private, 54929, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, <=50K 59, Private, 162136, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 56, United-States, <=50K 22, Private, 256504, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 162098, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 39, Self-emp-not-inc, 103110, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 24, Private, 227610, 10th, 6, Divorced, Handlers-cleaners, Unmarried, White, Female, 0, 0, 58, United-States, <=50K 63, Private, 176696, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 51, Private, 220019, Assoc-acdm, 12, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Self-emp-inc, 242984, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 38, Private, 187847, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 17, Private, 132636, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 15, United-States, <=50K 20, Private, 108887, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 25, United-States, <=50K 42, Self-emp-not-inc, 195897, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 112181, Bachelors, 13, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 12, United-States, >50K 56, Local-gov, 391926, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 195505, 10th, 6, Never-married, Sales, Own-child, White, Male, 0, 0, 5, United-States, <=50K 31, Private, 43819, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 7688, 0, 43, United-States, >50K 23, Private, 145389, Some-college, 10, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, <=50K 33, ?, 186824, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 36, Local-gov, 101833, Bachelors, 13, Separated, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 82283, 5th-6th, 3, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 40, ?, <=50K 52, Private, 99602, HS-grad, 9, Separated, Craft-repair, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 28, Private, 213276, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 59, Private, 424468, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, ?, <=50K 30, Private, 176123, 10th, 6, Never-married, Machine-op-inspct, Other-relative, Asian-Pac-Islander, Male, 0, 0, 40, Vietnam, <=50K 32, Private, 38797, Assoc-voc, 11, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 101859, 7th-8th, 4, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 53, Private, 87158, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 54, Self-emp-not-inc, 205066, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 36, United-States, <=50K 26, Private, 56929, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, Black, Male, 0, 0, 50, ?, <=50K 34, Private, 25322, Bachelors, 13, Married-spouse-absent, Machine-op-inspct, Not-in-family, Asian-Pac-Islander, Male, 0, 2339, 40, ?, <=50K 31, Private, 87950, Assoc-voc, 11, Divorced, Sales, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 34, Private, 150154, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 58, Private, 142076, HS-grad, 9, Divorced, Tech-support, Not-in-family, White, Male, 4787, 0, 39, United-States, >50K 30, State-gov, 112139, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 149217, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Puerto-Rico, <=50K 27, Private, 189974, Some-college, 10, Divorced, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 23, Private, 109199, 5th-6th, 3, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Mexico, <=50K 24, Private, 190290, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 36, Private, 189404, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 1977, 35, United-States, >50K 33, Federal-gov, 428271, HS-grad, 9, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 22, State-gov, 134192, Some-college, 10, Never-married, Tech-support, Own-child, White, Female, 0, 0, 10, United-States, <=50K 47, Private, 168211, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 44, United-States, <=50K 34, Private, 277314, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, Black, Male, 0, 1902, 50, United-States, >50K 44, Federal-gov, 316120, Prof-school, 15, Divorced, Prof-specialty, Unmarried, White, Male, 0, 0, 40, United-States, >50K 41, Private, 107276, Assoc-voc, 11, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 45, ?, 112453, HS-grad, 9, Separated, ?, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 4, United-States, <=50K 24, Private, 346909, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 44, Mexico, <=50K 65, ?, 105017, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 317360, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 23, Private, 189017, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 54, Private, 138179, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 299813, 11th, 7, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 37, Dominican-Republic, <=50K 45, Private, 265083, 5th-6th, 3, Divorced, Priv-house-serv, Unmarried, White, Female, 0, 0, 35, Mexico, <=50K 50, Private, 185846, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 184655, Assoc-acdm, 12, Never-married, Other-service, Other-relative, White, Male, 0, 0, 25, United-States, <=50K 24, Private, 200295, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 117319, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1672, 40, United-States, <=50K 50, Private, 63000, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 58, Self-emp-not-inc, 106942, Some-college, 10, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 52795, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 46, United-States, <=50K 37, Private, 51264, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 99, France, >50K 37, Self-emp-not-inc, 410919, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 35, United-States, <=50K 22, Private, 105592, Assoc-acdm, 12, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 29, Self-emp-not-inc, 183151, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 48, United-States, <=50K 45, Private, 209912, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 40, India, >50K 49, Self-emp-not-inc, 275845, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 44, Local-gov, 241851, Assoc-voc, 11, Married-civ-spouse, Transport-moving, Husband, White, Male, 4386, 0, 40, United-States, >50K 72, Private, 89299, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 16, United-States, <=50K 63, Self-emp-not-inc, 106648, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 12, United-States, <=50K 26, Private, 58426, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 58, Self-emp-not-inc, 121912, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 42, United-States, <=50K 40, Private, 170730, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 56, Private, 257555, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Self-emp-not-inc, 51499, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 72, United-States, <=50K 28, Private, 195000, Bachelors, 13, Never-married, Sales, Other-relative, White, Female, 0, 0, 45, United-States, <=50K 57, Private, 108741, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 184964, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 44, Private, 156815, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 49325, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 121718, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, Germany, <=50K 18, Private, 172076, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 57, Self-emp-not-inc, 327901, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 53, Local-gov, 215990, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 35, United-States, <=50K 38, Private, 210866, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 44, United-States, >50K 33, Private, 322873, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 42, Private, 265698, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 70, ?, 26990, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 60, United-States, <=50K 50, Private, 177896, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 50, Private, 189107, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 306830, Assoc-acdm, 12, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Nicaragua, <=50K 72, Federal-gov, 39110, 11th, 7, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 8, Canada, <=50K 33, Private, 155475, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 135803, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 25, Philippines, <=50K 48, Private, 117849, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 64, Self-emp-not-inc, 339321, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 24, United-States, >50K 19, Private, 318822, 11th, 7, Never-married, Priv-house-serv, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 48, Private, 174794, Assoc-voc, 11, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 204277, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 1848, 48, United-States, >50K 55, Private, 182460, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 15024, 0, 35, United-States, >50K 24, Private, 193920, Masters, 14, Never-married, Priv-house-serv, Not-in-family, White, Female, 0, 0, 45, ?, <=50K 42, Federal-gov, 91468, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 106760, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 50, Canada, >50K 34, Private, 375680, Assoc-acdm, 12, Never-married, Craft-repair, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 55, Self-emp-inc, 222615, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 22, Private, 190968, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 76767, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 50, Self-emp-not-inc, 203098, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 35, United-States, <=50K 47, Local-gov, 162187, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1887, 40, United-States, >50K 25, Private, 242729, Bachelors, 13, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 52, Private, 253784, 11th, 7, Divorced, Other-service, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 30, Private, 206051, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Self-emp-not-inc, 181553, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 73, Self-emp-inc, 80986, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 20, United-States, <=50K 50, Private, 200783, 7th-8th, 4, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 34, Private, 42596, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 24, Private, 464502, Assoc-acdm, 12, Never-married, Sales, Not-in-family, Black, Male, 0, 0, 40, ?, <=50K 66, Private, 205724, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 24, United-States, >50K 22, Private, 446140, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 55, United-States, <=50K 69, Local-gov, 32287, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 25, United-States, <=50K 23, Private, 56774, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 308118, Bachelors, 13, Widowed, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, ?, <=50K 35, Private, 176279, Some-college, 10, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 20, Private, 103277, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 35, United-States, <=50K 70, Self-emp-inc, 225780, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 20, United-States, >50K 54, Private, 154728, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 7688, 0, 40, United-States, >50K 34, Private, 149943, HS-grad, 9, Never-married, Other-service, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, Japan, <=50K 38, State-gov, 22245, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 33, Private, 93056, 7th-8th, 4, Divorced, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 270522, HS-grad, 9, Separated, Other-service, Not-in-family, White, Female, 0, 0, 26, United-States, <=50K 60, Self-emp-inc, 123218, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 81, Self-emp-not-inc, 123959, Bachelors, 13, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 1668, 3, Hungary, <=50K 32, Self-emp-not-inc, 103642, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, <=50K 34, Private, 157747, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 46, Self-emp-not-inc, 154083, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 30, State-gov, 23037, Some-college, 10, Never-married, Other-service, Own-child, Amer-Indian-Eskimo, Male, 0, 0, 84, United-States, <=50K 23, ?, 226891, HS-grad, 9, Never-married, ?, Other-relative, Asian-Pac-Islander, Female, 0, 0, 20, South, <=50K 29, Private, 50028, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 138251, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 31, Private, 369825, 7th-8th, 4, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 25, United-States, <=50K 36, Federal-gov, 44364, HS-grad, 9, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 36, United-States, <=50K 23, Private, 230704, Some-college, 10, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 22, United-States, <=50K 35, Private, 42044, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 30, United-States, <=50K 28, Local-gov, 56340, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 33, State-gov, 156015, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Private, 163434, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 85251, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 38, Self-emp-inc, 187411, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 47, Private, 155124, Assoc-voc, 11, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 1669, 40, United-States, <=50K 25, Private, 396633, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 0, 56, United-States, >50K 45, Private, 182313, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 50, United-States, >50K 38, Private, 52596, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 66, ?, 260111, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, >50K 65, Local-gov, 143570, Some-college, 10, Never-married, Prof-specialty, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 30, Private, 160634, Assoc-voc, 11, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, >50K 54, Private, 29909, 11th, 7, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 43, United-States, <=50K 49, Private, 94215, 12th, 8, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 41, Self-emp-not-inc, 151990, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 15, United-States, >50K 48, Federal-gov, 188081, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Private, 218445, 5th-6th, 3, Never-married, Priv-house-serv, Unmarried, White, Female, 0, 0, 12, Mexico, <=50K 77, Private, 235775, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 25, Cuba, <=50K 19, Private, 98605, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 30, Private, 188398, HS-grad, 9, Married-spouse-absent, Adm-clerical, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 41, Self-emp-inc, 140365, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 55, United-States, >50K 35, Private, 202950, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, Iran, >50K 20, Private, 218215, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 66, Self-emp-inc, 197816, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 10605, 0, 40, United-States, >50K 49, Private, 147002, HS-grad, 9, Never-married, Craft-repair, Unmarried, White, Female, 0, 0, 40, Puerto-Rico, <=50K 52, Private, 138497, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 24, Private, 57711, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 35, United-States, >50K 50, Private, 169925, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 15, United-States, <=50K 22, Private, 72310, 11th, 7, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 19, Private, 170800, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 39, Private, 215095, 11th, 7, Never-married, Prof-specialty, Unmarried, White, Female, 0, 0, 30, Puerto-Rico, <=50K 45, Private, 480717, Bachelors, 13, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 38, ?, <=50K 61, Local-gov, 34632, Bachelors, 13, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 45, Private, 140664, Assoc-acdm, 12, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 36, Local-gov, 177858, Bachelors, 13, Married-civ-spouse, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 160369, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 2415, 45, United-States, >50K 38, Private, 129102, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 52, Local-gov, 278522, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 29, Federal-gov, 124953, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 42, United-States, >50K 33, Private, 63184, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 40, Self-emp-not-inc, 165815, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 248584, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 46, Local-gov, 226871, Bachelors, 13, Divorced, Protective-serv, Not-in-family, Black, Male, 0, 0, 50, United-States, >50K 44, Private, 267717, Masters, 14, Married-civ-spouse, Craft-repair, Husband, White, Male, 15024, 0, 45, United-States, >50K 19, Private, 60367, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 13, United-States, <=50K 44, Private, 134120, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 40, Private, 95639, HS-grad, 9, Never-married, Craft-repair, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 20, Private, 132053, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 2, United-States, <=50K 24, Private, 138768, Assoc-acdm, 12, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 30, United-States, <=50K 76, Private, 203910, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Male, 0, 0, 17, United-States, <=50K 20, Private, 109952, HS-grad, 9, Married-civ-spouse, Tech-support, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 155781, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 31, Private, 49398, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 159303, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 248339, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 35, United-States, <=50K 29, Private, 190539, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 1590, 50, United-States, <=50K 30, Private, 183620, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 48, Private, 25468, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Male, 99999, 0, 50, United-States, >50K 42, Private, 201495, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 52221, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Self-emp-inc, 96460, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 60, United-States, >50K 42, Private, 325353, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, White, Male, 7688, 0, 42, United-States, >50K 28, Self-emp-not-inc, 176027, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 28, United-States, <=50K 42, Local-gov, 266135, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 52, United-States, >50K 60, State-gov, 194252, Masters, 14, Married-civ-spouse, Exec-managerial, Wife, White, Female, 3103, 0, 40, United-States, >50K 76, ?, 164835, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 21, Private, 363192, Assoc-voc, 11, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 31360, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 63503, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 44, Private, 157614, HS-grad, 9, Divorced, Sales, Own-child, White, Male, 0, 0, 38, United-States, <=50K 45, Private, 160647, Bachelors, 13, Divorced, Adm-clerical, Unmarried, White, Female, 4687, 0, 35, United-States, >50K 38, Private, 363395, Some-college, 10, Never-married, Sales, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 28, Private, 338376, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, >50K 29, Private, 87523, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 280714, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 49, Self-emp-inc, 119565, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Local-gov, 171482, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 56, United-States, >50K 40, Self-emp-inc, 49249, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 17, Private, 331552, 12th, 8, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 30, United-States, <=50K 45, Private, 174426, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 184105, Some-college, 10, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 28, United-States, <=50K 29, Private, 37933, Bachelors, 13, Never-married, Exec-managerial, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 57, Self-emp-not-inc, 291529, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 4386, 0, 13, United-States, >50K 23, Private, 376416, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 263612, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, Haiti, <=50K 23, Private, 227471, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 24, United-States, <=50K 39, Private, 191103, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 35644, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 43, Self-emp-not-inc, 227298, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 25, State-gov, 187508, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 184378, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, Puerto-Rico, <=50K 52, Self-emp-not-inc, 190333, HS-grad, 9, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 48, Private, 155372, HS-grad, 9, Widowed, Machine-op-inspct, Unmarried, White, Female, 0, 0, 36, United-States, <=50K 37, Private, 259882, Assoc-voc, 11, Never-married, Sales, Unmarried, Black, Female, 0, 0, 6, United-States, <=50K 36, Private, 217077, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 33, Private, 103596, Assoc-voc, 11, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Local-gov, 188236, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 24, Private, 353010, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 10, United-States, <=50K 42, Local-gov, 70655, HS-grad, 9, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Self-emp-inc, 64874, Assoc-acdm, 12, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 40, Federal-gov, 219240, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 22, United-States, <=50K 50, Self-emp-inc, 104849, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, India, <=50K 40, Private, 173590, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 22, Private, 412316, HS-grad, 9, Never-married, Sales, Other-relative, Black, Male, 0, 0, 40, ?, <=50K 57, Self-emp-inc, 195835, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Local-gov, 170579, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 61, Federal-gov, 230545, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 35, Puerto-Rico, <=50K 71, Private, 162297, HS-grad, 9, Widowed, Sales, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 47, Private, 169549, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 117528, Bachelors, 13, Never-married, Other-service, Other-relative, White, Female, 0, 0, 45, United-States, <=50K 25, Private, 273876, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 33, Private, 529104, 11th, 7, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 50, United-States, <=50K 40, State-gov, 456110, 11th, 7, Divorced, Transport-moving, Unmarried, White, Female, 0, 0, 52, United-States, <=50K 39, ?, 180868, 11th, 7, Never-married, ?, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 29, Private, 170301, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 2829, 0, 40, United-States, <=50K 33, Private, 55717, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 166181, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 36, United-States, <=50K 24, Private, 52242, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, >50K 28, Private, 224629, Masters, 14, Never-married, Exec-managerial, Not-in-family, Other, Male, 0, 0, 30, Cuba, <=50K 20, Private, 197997, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 46144, Some-college, 10, Divorced, Handlers-cleaners, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 34, State-gov, 180871, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 55, United-States, <=50K 25, Private, 212311, Some-college, 10, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 36, Private, 232874, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 175999, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 177121, Some-college, 10, Separated, Other-service, Not-in-family, White, Female, 0, 0, 58, United-States, <=50K 57, Private, 299358, HS-grad, 9, Widowed, Other-service, Other-relative, White, Female, 0, 1719, 25, United-States, <=50K 20, ?, 326624, HS-grad, 9, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 56, Private, 129836, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 10, United-States, <=50K 24, Private, 225515, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 60, Private, 145664, Some-college, 10, Divorced, Sales, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 37, Private, 151764, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 27, Private, 183523, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 54, Private, 257869, Some-college, 10, Separated, Other-service, Not-in-family, White, Male, 0, 0, 28, Columbia, <=50K 40, Private, 73025, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 30, China, <=50K 18, Private, 165532, 12th, 8, Never-married, Other-service, Own-child, White, Male, 0, 0, 15, United-States, <=50K 51, Federal-gov, 140035, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Self-emp-not-inc, 325159, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 50, United-States, >50K 64, Federal-gov, 161926, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 8, United-States, <=50K 24, Private, 163665, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 2174, 0, 40, United-States, <=50K 33, Private, 106938, HS-grad, 9, Married-civ-spouse, Tech-support, Wife, Black, Female, 0, 0, 38, United-States, <=50K 31, Private, 97453, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 26, Local-gov, 242464, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 3103, 0, 40, United-States, >50K 54, Private, 155233, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 14084, 0, 40, United-States, >50K 31, Private, 248653, 1st-4th, 2, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 37, Mexico, <=50K 39, Private, 59313, 12th, 8, Married-spouse-absent, Transport-moving, Not-in-family, Black, Male, 0, 0, 45, ?, <=50K 22, Private, 141297, Some-college, 10, Never-married, Tech-support, Own-child, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 227325, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 68, Private, 123653, 5th-6th, 3, Separated, Other-service, Not-in-family, White, Male, 0, 0, 12, Italy, <=50K 59, Federal-gov, 176317, 10th, 6, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 37, United-States, <=50K 35, Self-emp-not-inc, 77146, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 2829, 0, 45, United-States, <=50K 25, Private, 169124, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 179413, HS-grad, 9, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 180137, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 60, United-States, <=50K 17, State-gov, 179319, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, United-States, <=50K 19, Private, 45766, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 53, Private, 152810, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 55, United-States, >50K 59, Private, 214052, 5th-6th, 3, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 201141, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 37, United-States, <=50K 74, Self-emp-not-inc, 43599, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 28, Private, 292536, Some-college, 10, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 40, Private, 82161, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 180656, Some-college, 10, Married-spouse-absent, Craft-repair, Not-in-family, White, Male, 0, 0, 40, ?, <=50K 20, Private, 181370, Some-college, 10, Never-married, Other-service, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 80, Private, 148623, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, >50K 51, Private, 84399, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 17, Private, 143331, 10th, 6, Never-married, Sales, Own-child, White, Male, 0, 0, 15, United-States, <=50K 37, Federal-gov, 48779, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, ?, 175495, HS-grad, 9, Never-married, ?, Own-child, Black, Female, 0, 0, 24, United-States, <=50K 58, Private, 83542, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 214619, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 160035, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Federal-gov, 39603, Some-college, 10, Never-married, Craft-repair, Unmarried, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 36, Private, 181589, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 32, Columbia, <=50K 33, Private, 261511, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 29522, Some-college, 10, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 36340, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 24, United-States, <=50K 41, Private, 320984, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 65, United-States, >50K 57, ?, 403625, Some-college, 10, Married-civ-spouse, ?, Husband, Asian-Pac-Islander, Male, 0, 0, 60, United-States, >50K 23, Private, 122346, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 105794, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Female, 14084, 0, 50, United-States, >50K 53, Private, 152883, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 31, State-gov, 123037, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 13, United-States, <=50K 41, ?, 339682, 5th-6th, 3, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, Mexico, <=50K 36, Private, 182074, HS-grad, 9, Never-married, Adm-clerical, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 248588, 12th, 8, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 187584, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, Canada, <=50K 36, Private, 46706, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 190290, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 48, Self-emp-not-inc, 247294, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 30, Peru, <=50K 22, Private, 117779, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 121602, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 451744, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 32, Private, 107793, HS-grad, 9, Divorced, Other-service, Own-child, White, Male, 2174, 0, 40, United-States, <=50K 35, Private, 339772, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, United-States, <=50K 21, Private, 185582, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 43, United-States, <=50K 26, Private, 260614, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Local-gov, 53220, HS-grad, 9, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 43, Private, 213844, HS-grad, 9, Married-AF-spouse, Craft-repair, Wife, Black, Female, 0, 0, 42, United-States, >50K 33, Private, 213226, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 30, Private, 58582, Bachelors, 13, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 10, United-States, <=50K 52, Private, 193116, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 38, Local-gov, 201410, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 190525, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 46, United-States, >50K 57, Self-emp-not-inc, 138285, Assoc-acdm, 12, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Iran, <=50K 51, Private, 111939, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 50, Private, 109277, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, <=50K 32, Private, 331539, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 50, China, >50K 32, Private, 396745, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 2415, 48, United-States, >50K 37, Private, 126675, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 69, Self-emp-not-inc, 349022, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 33, United-States, <=50K 33, ?, 98145, Some-college, 10, Divorced, ?, Unmarried, Amer-Indian-Eskimo, Male, 0, 0, 30, United-States, <=50K 37, Private, 234901, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, Germany, >50K 36, Private, 100681, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 2463, 0, 40, United-States, <=50K 47, Self-emp-not-inc, 265097, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, >50K 63, Private, 237379, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 44793, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 17, Private, 270942, HS-grad, 9, Never-married, Other-service, Other-relative, White, Male, 0, 0, 35, Mexico, <=50K 56, Private, 193622, HS-grad, 9, Separated, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 90, Local-gov, 187749, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 0, 20, Philippines, <=50K 27, Private, 160178, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 38, Private, 680390, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 33, Private, 96245, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 26, Private, 34803, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 170091, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 35, United-States, <=50K 42, Private, 231813, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 23789, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 32, State-gov, 438711, Some-college, 10, Married-civ-spouse, Prof-specialty, Wife, Black, Female, 0, 0, 40, United-States, <=50K 66, Private, 169804, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 20051, 0, 40, United-States, >50K 66, Local-gov, 376506, Doctorate, 16, Divorced, Prof-specialty, Not-in-family, White, Female, 3273, 0, 40, United-States, <=50K 49, Private, 28791, Some-college, 10, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 162814, HS-grad, 9, Divorced, Protective-serv, Not-in-family, Black, Male, 0, 0, 45, United-States, <=50K 38, Private, 58108, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 40, Self-emp-inc, 102226, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Federal-gov, 209131, Assoc-acdm, 12, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 46, Self-emp-not-inc, 157117, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 172865, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, <=50K 19, Private, 29798, 12th, 8, Never-married, Handlers-cleaners, Own-child, Amer-Indian-Eskimo, Male, 0, 0, 20, United-States, <=50K 71, ?, 229424, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 37, Local-gov, 80680, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 1151, 0, 35, United-States, <=50K 52, Local-gov, 238959, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 32, United-States, >50K 27, Private, 189462, Masters, 14, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 46, United-States, <=50K 52, Private, 139347, HS-grad, 9, Married-civ-spouse, Transport-moving, Wife, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 188108, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 4101, 0, 40, United-States, <=50K 37, Self-emp-inc, 111128, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 28, Private, 81540, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 257562, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Mexico, <=50K 31, Private, 59496, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, <=50K 29, Private, 29974, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 102597, HS-grad, 9, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 69, Private, 41419, 7th-8th, 4, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 20, United-States, <=50K 50, Private, 118565, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 54, State-gov, 312897, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 46, England, >50K 17, Private, 166290, 9th, 5, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 34, Private, 160261, HS-grad, 9, Never-married, Tech-support, Own-child, Asian-Pac-Islander, Male, 14084, 0, 35, China, >50K 32, Self-emp-not-inc, 116834, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 5, ?, <=50K 23, Private, 203076, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 66, Private, 201197, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 61, Private, 273803, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 156797, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 283896, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 149368, HS-grad, 9, Divorced, Sales, Unmarried, White, Male, 1151, 0, 30, United-States, <=50K 49, Private, 156926, Assoc-voc, 11, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 21, ?, 163911, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 3, United-States, <=50K 56, Self-emp-inc, 165881, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 25, Private, 86872, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 167523, Bachelors, 13, Divorced, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 58, Private, 154950, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Federal-gov, 171231, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, Puerto-Rico, <=50K 62, Private, 244933, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 54, Private, 256908, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 25, United-States, >50K 34, Self-emp-not-inc, 33442, Assoc-voc, 11, Never-married, Other-service, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 126142, 10th, 6, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 30, United-States, <=50K 28, ?, 268222, 11th, 7, Never-married, ?, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 32, Private, 167106, HS-grad, 9, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Hong, <=50K 22, Local-gov, 50065, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 34, State-gov, 252529, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 53, ?, 199665, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 30, United-States, >50K 47, Private, 343579, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Mexico, <=50K 19, Private, 190817, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 41, Self-emp-inc, 151089, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 2415, 55, United-States, >50K 46, Private, 186820, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 5013, 0, 40, United-States, <=50K 56, Self-emp-not-inc, 210731, 7th-8th, 4, Divorced, Sales, Other-relative, White, Male, 0, 0, 20, Mexico, <=50K 42, Private, 123816, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 25, Private, 77071, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 2339, 35, United-States, <=50K 42, Private, 115085, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, <=50K 43, Private, 170525, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 14344, 0, 40, United-States, >50K 17, Private, 209949, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 1602, 12, United-States, <=50K 57, Self-emp-not-inc, 34297, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Private, 180985, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 62, Local-gov, 33365, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 40, Canada, <=50K 20, Private, 197752, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 16, United-States, <=50K 47, Private, 180551, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 40, Private, 77975, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 159297, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, Asian-Pac-Islander, Female, 0, 0, 40, ?, >50K 48, Private, 94342, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, <=50K 39, Self-emp-inc, 34180, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, >50K 46, Local-gov, 367251, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, >50K 72, Self-emp-inc, 172407, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 50, United-States, >50K 53, Private, 303462, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 30, United-States, <=50K 47, Federal-gov, 220269, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Self-emp-not-inc, 45093, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 45, Canada, <=50K 34, Private, 101709, HS-grad, 9, Separated, Transport-moving, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 41, Private, 219591, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 76625, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 342599, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 35, United-States, <=50K 42, Self-emp-inc, 125846, 1st-4th, 2, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, ?, <=50K 54, Local-gov, 238257, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 39, Self-emp-inc, 206253, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 172571, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 59, Private, 95165, Doctorate, 16, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 69, Private, 141181, 5th-6th, 3, Married-civ-spouse, Adm-clerical, Husband, White, Male, 1797, 0, 40, United-States, <=50K 24, Private, 267843, Bachelors, 13, Never-married, Prof-specialty, Own-child, Black, Female, 0, 0, 35, United-States, <=50K 36, Private, 181382, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 3103, 0, 40, United-States, >50K 21, ?, 207782, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 30, United-States, <=50K 68, ?, 103161, HS-grad, 9, Widowed, ?, Not-in-family, White, Male, 0, 0, 32, United-States, <=50K 20, Private, 132320, Some-college, 10, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 26, Self-emp-not-inc, 201138, Assoc-voc, 11, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 48, Private, 239058, 12th, 8, Widowed, Handlers-cleaners, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 39, Self-emp-inc, 239755, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 50, United-States, >50K 21, Private, 176262, Assoc-acdm, 12, Never-married, Other-service, Own-child, White, Female, 0, 0, 18, United-States, <=50K 22, Private, 264738, HS-grad, 9, Never-married, Exec-managerial, Other-relative, White, Female, 0, 0, 42, Germany, <=50K 34, Private, 182218, Assoc-voc, 11, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 318982, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 46, Private, 216666, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Guatemala, <=50K 47, Private, 274200, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 40, United-States, >50K 65, Private, 150095, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Private, 192978, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 68021, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 34, Self-emp-not-inc, 28568, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 20, Private, 115057, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 139568, 11th, 7, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 52, Self-emp-inc, 138497, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 40, State-gov, 182460, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, Asian-Pac-Islander, Female, 0, 0, 38, China, >50K 22, Private, 253310, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 7, United-States, <=50K 29, Self-emp-inc, 130856, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 31, Self-emp-not-inc, 389765, 7th-8th, 4, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 42, Federal-gov, 52781, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 40, United-States, >50K 38, Private, 146178, HS-grad, 9, Never-married, Craft-repair, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 22, Private, 231053, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 70, United-States, >50K 21, ?, 145964, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 483450, 9th, 5, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, Mexico, <=50K 43, Self-emp-inc, 198316, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 33, Private, 160614, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 17, Self-emp-inc, 325171, 10th, 6, Never-married, Other-service, Own-child, Black, Male, 0, 0, 35, United-States, <=50K 54, Self-emp-not-inc, 172898, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 5178, 0, 50, United-States, >50K 45, Private, 186473, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 55, Local-gov, 286967, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 51, Self-emp-not-inc, 111939, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 35, United-States, >50K 65, Federal-gov, 325089, 10th, 6, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 143582, Bachelors, 13, Never-married, Prof-specialty, Own-child, Asian-Pac-Islander, Female, 0, 0, 45, United-States, <=50K 40, Private, 308027, HS-grad, 9, Widowed, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 58, Private, 105060, Some-college, 10, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 37, United-States, <=50K 53, Federal-gov, 39643, HS-grad, 9, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 58, United-States, <=50K 39, Private, 186191, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1848, 50, United-States, >50K 56, Local-gov, 267763, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 124293, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, <=50K 44, Private, 36271, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 143459, 9th, 5, Separated, Handlers-cleaners, Own-child, White, Male, 0, 0, 38, United-States, <=50K 36, Private, 186376, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, Asian-Pac-Islander, Male, 0, 0, 50, United-States, >50K 59, Self-emp-inc, 52822, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 33, Private, 104509, HS-grad, 9, Divorced, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 184456, Prof-school, 15, Never-married, Exec-managerial, Not-in-family, White, Male, 27828, 0, 50, United-States, >50K 26, Private, 192302, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 25, United-States, <=50K 22, Private, 156822, 10th, 6, Never-married, Sales, Not-in-family, White, Female, 0, 1762, 25, United-States, <=50K 25, Private, 214413, Masters, 14, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 108574, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 15, United-States, <=50K 41, Private, 223934, Assoc-acdm, 12, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 45, Private, 200559, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 70, United-States, <=50K 43, Private, 137722, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 261677, 9th, 5, Never-married, Handlers-cleaners, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 33, Private, 136331, HS-grad, 9, Married-spouse-absent, Craft-repair, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 34, Private, 329993, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 91819, Assoc-voc, 11, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 31, Private, 201122, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 1902, 45, United-States, >50K 48, Private, 315423, 5th-6th, 3, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 103277, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 47, Private, 236805, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 0, 60, United-States, <=50K 27, Private, 74883, Bachelors, 13, Never-married, Tech-support, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 18, Private, 115443, 11th, 7, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 43, Private, 150528, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 43701, Some-college, 10, Widowed, Sales, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 37, Federal-gov, 419053, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 183594, Assoc-voc, 11, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 20, United-States, <=50K 24, Private, 390348, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 36989, Bachelors, 13, Married-civ-spouse, Other-service, Husband, White, Male, 3908, 0, 70, United-States, <=50K 48, Private, 247895, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, United-States, >50K 75, Private, 191446, 1st-4th, 2, Married-civ-spouse, Other-service, Other-relative, Black, Female, 0, 0, 16, United-States, <=50K 43, Self-emp-not-inc, 33521, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 70, United-States, >50K 64, Private, 46087, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 67, ?, 129188, Doctorate, 16, Married-civ-spouse, ?, Husband, White, Male, 20051, 0, 5, United-States, >50K 36, Private, 356824, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 53, Private, 158746, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 153323, Some-college, 10, Never-married, Prof-specialty, Not-in-family, Black, Male, 0, 0, 20, United-States, <=50K 73, Self-emp-not-inc, 130391, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 36, United-States, <=50K 46, Private, 173613, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 362883, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 5013, 0, 40, United-States, <=50K 43, Private, 182757, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Private, 50397, HS-grad, 9, Never-married, Adm-clerical, Own-child, Black, Male, 0, 0, 20, United-States, <=50K 43, Federal-gov, 101709, Some-college, 10, Divorced, Handlers-cleaners, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 21, Private, 202570, 12th, 8, Never-married, Adm-clerical, Other-relative, Black, Male, 0, 0, 48, ?, <=50K 40, Private, 145649, HS-grad, 9, Separated, Sales, Unmarried, Black, Female, 0, 0, 25, United-States, <=50K 36, Private, 136343, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 64, Self-emp-inc, 142166, Bachelors, 13, Divorced, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 19, ?, 242001, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 127089, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 5178, 0, 38, United-States, >50K 46, Local-gov, 124071, Masters, 14, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 65, United-States, >50K 41, Local-gov, 190368, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 70, United-States, <=50K 29, ?, 19793, Some-college, 10, Divorced, ?, Unmarried, White, Female, 0, 0, 8, United-States, <=50K 28, Private, 67661, Some-college, 10, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 62278, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 30, Federal-gov, 295010, Bachelors, 13, Never-married, Protective-serv, Not-in-family, White, Female, 0, 0, 60, United-States, >50K 44, Private, 203897, Bachelors, 13, Married-spouse-absent, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, Cuba, <=50K 27, Private, 265314, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, >50K 25, Private, 159603, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 34, United-States, <=50K 29, Private, 134331, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 123011, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Poland, >50K 27, Private, 274964, Bachelors, 13, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 34, Private, 66309, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 38, Private, 73471, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 24, ?, 26671, HS-grad, 9, Never-married, ?, Other-relative, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 56, Private, 357118, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 35, Self-emp-inc, 184655, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 62, United-States, <=50K 23, ?, 55492, Assoc-voc, 11, Never-married, ?, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 30, United-States, <=50K 23, Private, 175266, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 188008, Some-college, 10, Never-married, Sales, Own-child, Black, Female, 0, 0, 20, United-States, <=50K 42, Private, 87284, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7298, 0, 35, United-States, >50K 46, Private, 330087, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 45, United-States, >50K 48, Self-emp-inc, 56975, HS-grad, 9, Divorced, Sales, Unmarried, Asian-Pac-Islander, Female, 0, 0, 84, ?, <=50K 27, Private, 150025, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, Puerto-Rico, <=50K 22, ?, 189203, Assoc-acdm, 12, Never-married, ?, Other-relative, White, Male, 0, 0, 15, United-States, <=50K 49, Self-emp-inc, 330874, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 70, United-States, >50K 23, Private, 136824, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 24, Private, 201179, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 324654, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, China, <=50K 25, Federal-gov, 366207, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 33, Self-emp-not-inc, 103860, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 22, Private, 106700, Assoc-acdm, 12, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 27, United-States, <=50K 54, Local-gov, 163557, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 39, Self-emp-inc, 286261, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 123083, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 75, Self-emp-inc, 125197, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 26, United-States, <=50K 28, Self-emp-not-inc, 278073, HS-grad, 9, Never-married, Machine-op-inspct, Other-relative, Black, Male, 0, 0, 30, United-States, <=50K 50, Private, 133963, Bachelors, 13, Divorced, Sales, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 62, Self-emp-not-inc, 71467, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, >50K 40, Private, 76487, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, Local-gov, 215245, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 37, United-States, <=50K 24, Federal-gov, 127185, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 179720, HS-grad, 9, Never-married, Other-service, Other-relative, White, Female, 0, 0, 30, United-States, <=50K 40, Private, 88909, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 45, Private, 341995, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 42, United-States, >50K 48, Private, 173938, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 34, Private, 344275, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 23, Private, 150463, HS-grad, 9, Never-married, Priv-house-serv, Unmarried, Other, Female, 0, 0, 40, Guatemala, <=50K 43, Local-gov, 209544, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 10520, 0, 50, United-States, >50K 42, Local-gov, 201723, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Self-emp-not-inc, 343476, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 50, Japan, >50K 52, Self-emp-inc, 77392, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 21, ?, 171156, Some-college, 10, Never-married, ?, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 56, Self-emp-not-inc, 357118, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 48, Federal-gov, 167749, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 37, Self-emp-not-inc, 352882, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 70, South, >50K 25, Private, 51201, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 40, Private, 365986, Bachelors, 13, Married-civ-spouse, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, >50K 34, Private, 400416, 11th, 7, Never-married, Machine-op-inspct, Own-child, Black, Male, 0, 0, 45, United-States, <=50K 52, Private, 31533, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 106900, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 1902, 42, United-States, >50K 36, Local-gov, 192337, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 118712, Assoc-voc, 11, Never-married, Craft-repair, Own-child, White, Male, 0, 1504, 40, United-States, <=50K 28, Private, 301654, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Self-emp-not-inc, 145162, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, ?, >50K 20, Private, 88126, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 9, England, <=50K 68, Private, 165017, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, Italy, >50K 35, Private, 238342, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 857532, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 64, Private, 134378, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 17, Private, 260797, 10th, 6, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 23, United-States, <=50K 25, Private, 138765, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 74, ?, 256674, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 31, Private, 247444, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Columbia, <=50K 51, State-gov, 454063, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 40, United-States, >50K 67, Private, 180539, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 10, United-States, <=50K 42, Private, 397346, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 3325, 0, 40, United-States, <=50K 29, Private, 107160, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 262024, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 21, Private, 131230, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 37, United-States, <=50K 67, Private, 274451, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 16, United-States, <=50K 41, State-gov, 365986, HS-grad, 9, Divorced, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 27, Private, 204515, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 36, United-States, <=50K 51, Private, 99316, 12th, 8, Divorced, Transport-moving, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 21, ?, 206681, 11th, 7, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 268726, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 46, United-States, <=50K 21, Private, 275395, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 383322, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Private, 126822, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 35, United-States, <=50K 39, Self-emp-inc, 168355, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 70, United-States, <=50K 21, Private, 162667, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, Columbia, <=50K 43, Private, 373403, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Self-emp-not-inc, 274562, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 14344, 0, 40, United-States, >50K 28, Private, 249362, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 31, Private, 111567, 9th, 5, Never-married, Sales, Not-in-family, White, Male, 0, 0, 43, United-States, >50K 18, ?, 216508, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 0, 30, United-States, <=50K 27, Private, 145784, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, Amer-Indian-Eskimo, Female, 0, 0, 45, United-States, <=50K 34, State-gov, 209317, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 259505, HS-grad, 9, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 345360, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, England, <=50K 43, Local-gov, 198096, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 7688, 0, 40, United-States, >50K 40, Self-emp-inc, 33126, Masters, 14, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 21, Private, 206354, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 25, Private, 1484705, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 21, Private, 26410, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 19, Self-emp-not-inc, 220901, Some-college, 10, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 30, United-States, <=50K 49, Self-emp-inc, 44671, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Private, 38620, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 36, Private, 89040, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 47, United-States, <=50K 32, Private, 370160, Some-college, 10, Separated, Exec-managerial, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 23, Private, 208946, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 32, United-States, <=50K 21, Private, 131230, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 10, United-States, <=50K 25, Private, 60358, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 350853, 5th-6th, 3, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, ?, <=50K 24, Private, 209782, Bachelors, 13, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 351952, Some-college, 10, Never-married, Prof-specialty, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 26, Private, 142081, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, Mexico, <=50K 22, Private, 164775, 9th, 5, Never-married, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, Guatemala, <=50K 41, Local-gov, 47858, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 18, Private, 404085, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 218678, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 184655, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1740, 48, United-States, <=50K 36, Private, 321760, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 17, United-States, <=50K 45, Local-gov, 185399, Masters, 14, Divorced, Prof-specialty, Own-child, White, Female, 0, 0, 55, United-States, <=50K 38, Local-gov, 409200, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 40077, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 34, Self-emp-not-inc, 31740, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 53, Local-gov, 233722, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 32, Private, 192039, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 17, Private, 222618, 11th, 7, Never-married, Sales, Own-child, Black, Female, 0, 0, 30, United-States, <=50K 45, State-gov, 213646, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 40, United-States, >50K 31, Local-gov, 194141, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 48, United-States, <=50K 47, State-gov, 80282, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, <=50K 27, Private, 166350, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 61, Federal-gov, 60641, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 30, United-States, <=50K 33, Private, 124827, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 67, Private, 105438, HS-grad, 9, Separated, Machine-op-inspct, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 85244, Bachelors, 13, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 120535, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 33, Local-gov, 269604, 5th-6th, 3, Never-married, Other-service, Unmarried, Other, Female, 0, 0, 40, El-Salvador, <=50K 27, Private, 247711, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 380922, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, >50K 24, Private, 281221, Bachelors, 13, Never-married, Adm-clerical, Other-relative, Asian-Pac-Islander, Female, 0, 0, 40, Taiwan, <=50K 23, Private, 269687, Assoc-voc, 11, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 181758, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 61, Federal-gov, 136787, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 22, Private, 107882, HS-grad, 9, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 20, United-States, <=50K 34, Private, 172579, Assoc-voc, 11, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 29933, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 5178, 0, 40, United-States, >50K 35, Federal-gov, 38905, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 36, Private, 168826, 10th, 6, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 424034, HS-grad, 9, Never-married, Exec-managerial, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 60, Private, 117509, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, ?, 196971, Bachelors, 13, Never-married, ?, Not-in-family, White, Female, 0, 0, 43, United-States, <=50K 64, Private, 69525, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 20, United-States, <=50K 22, Private, 374116, HS-grad, 9, Never-married, Sales, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 27, Private, 283913, 5th-6th, 3, Never-married, Priv-house-serv, Not-in-family, White, Female, 0, 0, 65, England, <=50K 36, State-gov, 147258, Some-college, 10, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 27, Private, 139903, HS-grad, 9, Never-married, Sales, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 52, Private, 112959, Some-college, 10, Widowed, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 57, Self-emp-not-inc, 264148, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 45, United-States, <=50K 23, Private, 256211, Some-college, 10, Never-married, Adm-clerical, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 24, Vietnam, <=50K 29, Self-emp-not-inc, 142519, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 281852, HS-grad, 9, Never-married, Transport-moving, Not-in-family, Black, Male, 0, 0, 80, United-States, <=50K 38, Private, 380543, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 50, Self-emp-not-inc, 204402, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 84, United-States, >50K 50, Private, 192203, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Self-emp-not-inc, 199005, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 17, Self-emp-inc, 61838, 10th, 6, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 210095, 11th, 7, Married-spouse-absent, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 40, Mexico, <=50K 19, Private, 187352, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Self-emp-not-inc, 32451, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 59, Private, 140569, Some-college, 10, Separated, Sales, Not-in-family, White, Male, 14084, 0, 60, United-States, >50K 39, Private, 87556, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 6849, 0, 40, United-States, <=50K 18, Private, 79443, 9th, 5, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, Mexico, <=50K 27, Private, 212622, Masters, 14, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 32650, Assoc-voc, 11, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 44, Private, 125461, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 19, Private, 219867, HS-grad, 9, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 35, United-States, <=50K 32, Local-gov, 206609, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 101299, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Private, 29437, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 65, Private, 87164, 11th, 7, Widowed, Sales, Other-relative, White, Female, 0, 0, 20, United-States, <=50K 57, Self-emp-inc, 146103, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 48, Private, 169324, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 32, Haiti, <=50K 46, Private, 138370, 7th-8th, 4, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 1651, 40, China, <=50K 27, Private, 29523, 10th, 6, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Local-gov, 383745, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 1485, 40, United-States, >50K 21, ?, 247075, HS-grad, 9, Never-married, ?, Unmarried, Black, Female, 0, 0, 25, United-States, <=50K 20, ?, 200967, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 12, United-States, <=50K 51, ?, 175985, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Self-emp-inc, 189404, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 1740, 40, United-States, <=50K 29, Self-emp-not-inc, 267661, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 70, United-States, <=50K 30, Local-gov, 182926, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 15024, 0, 40, United-States, >50K 65, Private, 243858, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 20, ?, 43587, HS-grad, 9, Married-spouse-absent, ?, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 47, Federal-gov, 31339, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 204682, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 2174, 0, 40, Japan, <=50K 17, Private, 73145, 9th, 5, Never-married, Craft-repair, Own-child, White, Female, 0, 0, 16, United-States, <=50K 38, Local-gov, 218184, 5th-6th, 3, Married-civ-spouse, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 38, Local-gov, 223237, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Self-emp-not-inc, 93319, HS-grad, 9, Never-married, Sales, Other-relative, White, Female, 0, 0, 4, United-States, <=50K 24, ?, 212300, HS-grad, 9, Separated, ?, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 52, Private, 187356, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 41, United-States, <=50K 46, Self-emp-not-inc, 220832, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 58, United-States, >50K 22, Private, 211361, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 56, Private, 134195, Masters, 14, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 37, Self-emp-not-inc, 218249, 11th, 7, Divorced, Prof-specialty, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 59, Private, 70720, Bachelors, 13, Divorced, Sales, Not-in-family, White, Male, 0, 0, 55, United-States, >50K 19, Self-emp-not-inc, 342384, 11th, 7, Married-civ-spouse, Craft-repair, Own-child, White, Male, 0, 2129, 55, United-States, <=50K 31, Private, 237317, 9th, 5, Never-married, Craft-repair, Not-in-family, Other, Male, 0, 0, 45, United-States, <=50K 22, Private, 359759, Some-college, 10, Never-married, Sales, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 20, Philippines, <=50K 48, Self-emp-not-inc, 181758, Doctorate, 16, Never-married, Prof-specialty, Unmarried, White, Female, 0, 0, 60, United-States, >50K 63, Self-emp-inc, 267101, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 33, Private, 222221, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 45, United-States, >50K 53, Private, 55139, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 10, United-States, <=50K 38, Private, 220237, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, ?, >50K 39, Private, 101073, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 24, United-States, <=50K 59, Private, 69884, Prof-school, 15, Married-spouse-absent, Prof-specialty, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 45, Private, 201127, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 164733, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 60, State-gov, 129447, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 38, Private, 32837, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 56, United-States, <=50K 31, Private, 200117, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 61, Self-emp-not-inc, 219183, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 66, ?, 188842, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 24, United-States, <=50K 26, Private, 272669, Bachelors, 13, Never-married, Sales, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 20, South, <=50K 60, Self-emp-inc, 336188, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 2415, 80, United-States, >50K 68, ?, 191288, 7th-8th, 4, Widowed, ?, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 32, Private, 176185, Some-college, 10, Divorced, Exec-managerial, Other-relative, White, Male, 0, 0, 60, United-States, <=50K 25, Local-gov, 197728, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 43, Local-gov, 144778, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, ?, <=50K 26, ?, 133373, Bachelors, 13, Never-married, ?, Own-child, White, Male, 0, 0, 44, United-States, <=50K 55, Private, 197399, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 55, United-States, >50K 66, Private, 86010, 10th, 6, Widowed, Transport-moving, Not-in-family, White, Female, 0, 0, 11, United-States, <=50K 31, Private, 228873, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 187415, 5th-6th, 3, Married-civ-spouse, Machine-op-inspct, Husband, Asian-Pac-Islander, Male, 0, 0, 50, ?, <=50K 58, Self-emp-inc, 112945, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Male, 27828, 0, 40, United-States, >50K 56, Private, 98361, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, ?, >50K 22, Private, 129172, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 16, United-States, <=50K 46, Local-gov, 316205, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, United-States, >50K 33, Private, 226629, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 35, United-States, <=50K 26, State-gov, 180886, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 30, United-States, <=50K 42, Self-emp-not-inc, 69333, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 45, Private, 213620, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 197397, Some-college, 10, Married-civ-spouse, Prof-specialty, Wife, Other, Female, 0, 0, 6, Puerto-Rico, <=50K 19, Private, 223648, 11th, 7, Never-married, Sales, Own-child, White, Male, 0, 0, 20, ?, <=50K 27, Private, 179915, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 99, United-States, <=50K 51, Private, 339905, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 40, United-States, >50K 42, Private, 112956, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 43, Self-emp-not-inc, 421837, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 7298, 0, 50, Mexico, >50K 38, Private, 187999, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 45, United-States, >50K 44, Private, 77313, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 231948, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 64, United-States, >50K 37, Private, 37109, HS-grad, 9, Married-civ-spouse, Other-service, Wife, Asian-Pac-Islander, Female, 0, 0, 60, Philippines, <=50K 29, Private, 79387, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 53, ?, 133963, HS-grad, 9, Divorced, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Self-emp-not-inc, 177937, Bachelors, 13, Married-spouse-absent, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, Poland, <=50K 80, Private, 173488, Some-college, 10, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 61, Private, 183355, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 147989, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 5013, 0, 52, United-States, <=50K 20, Private, 289944, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 23, Private, 62278, HS-grad, 9, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 48, Federal-gov, 110457, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 24, Private, 295763, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 50, United-States, <=50K 71, State-gov, 100063, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 49, Private, 194962, 11th, 7, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 6, United-States, <=50K 39, Federal-gov, 227597, HS-grad, 9, Never-married, Armed-Forces, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 22, Private, 117606, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 25, United-States, <=50K 67, Federal-gov, 44774, Bachelors, 13, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 177648, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 25, United-States, <=50K 38, Private, 172571, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1848, 54, United-States, >50K 38, ?, 203482, 7th-8th, 4, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 45, United-States, <=50K 50, Private, 153931, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 56, Self-emp-not-inc, 84774, Assoc-acdm, 12, Married-civ-spouse, Farming-fishing, Wife, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 157127, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 26, Private, 170786, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 281030, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 203761, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 10520, 0, 40, United-States, >50K 27, Private, 167405, HS-grad, 9, Married-spouse-absent, Farming-fishing, Own-child, White, Female, 0, 0, 40, Mexico, <=50K 40, Local-gov, 188436, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 7298, 0, 40, United-States, >50K 43, Private, 388849, Assoc-acdm, 12, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 60, United-States, <=50K 31, State-gov, 176998, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, >50K 57, Private, 200316, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Private, 160300, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 22, Private, 236684, Assoc-voc, 11, Never-married, Other-service, Own-child, Black, Female, 0, 0, 36, United-States, <=50K 20, Local-gov, 247794, Assoc-voc, 11, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 35, United-States, <=50K 27, Private, 267325, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 3464, 0, 40, United-States, <=50K 39, Private, 279490, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 27, State-gov, 280618, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Local-gov, 248406, HS-grad, 9, Separated, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 31, Local-gov, 226494, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 41, Private, 220460, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 20, United-States, <=50K 25, Private, 108317, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, State-gov, 147256, Assoc-acdm, 12, Never-married, Prof-specialty, Not-in-family, Black, Male, 0, 0, 40, United-States, >50K 22, Private, 110371, HS-grad, 9, Married-civ-spouse, Other-service, Own-child, White, Male, 0, 0, 50, United-States, <=50K 62, Private, 114060, 7th-8th, 4, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 91, United-States, <=50K 29, Federal-gov, 31161, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, Other, Female, 0, 0, 40, United-States, <=50K 44, Private, 105862, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 70, United-States, >50K 32, Private, 402089, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 2, United-States, <=50K 19, ?, 425447, HS-grad, 9, Never-married, ?, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 20, Private, 137300, Assoc-voc, 11, Never-married, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 65, State-gov, 326691, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, >50K 24, Private, 275093, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 36, United-States, <=50K 37, Self-emp-not-inc, 112497, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 43, Local-gov, 174491, HS-grad, 9, Divorced, Tech-support, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 38, Self-emp-not-inc, 114835, Bachelors, 13, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 60, United-States, >50K 28, Private, 137898, Assoc-acdm, 12, Never-married, Sales, Own-child, White, Female, 0, 0, 35, United-States, <=50K 33, Private, 153151, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 4416, 0, 40, United-States, <=50K 32, Private, 134886, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 38, Private, 193815, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 33, Private, 237833, Some-college, 10, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Self-emp-not-inc, 101593, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 27, Private, 164924, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 174201, HS-grad, 9, Divorced, Handlers-cleaners, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 47, Local-gov, 36169, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 55, Private, 144071, 11th, 7, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 30, Self-emp-not-inc, 180859, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 8, United-States, <=50K 54, Private, 221915, Some-college, 10, Widowed, Craft-repair, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 40, Private, 26892, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 21, Private, 351084, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 97306, Bachelors, 13, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 30, Private, 185027, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 182539, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 22, Private, 215395, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 37, United-States, <=50K 37, Private, 186434, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 40, United-States, >50K 41, ?, 217921, 9th, 5, Married-civ-spouse, ?, Wife, Asian-Pac-Islander, Female, 0, 0, 40, Hong, <=50K 52, Local-gov, 346668, Masters, 14, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 57, Self-emp-inc, 412952, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 167009, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 58, Private, 316000, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Self-emp-not-inc, 216256, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 40, Private, 341835, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 30, Private, 169841, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 26, Self-emp-not-inc, 200681, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, Outlying-US(Guam-USVI-etc), <=50K 46, Self-emp-not-inc, 456956, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 26, Federal-gov, 276075, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, <=50K 50, Federal-gov, 96657, Bachelors, 13, Divorced, Prof-specialty, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 22, Private, 374313, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 36, Private, 110998, Masters, 14, Widowed, Tech-support, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, India, <=50K 30, Private, 53285, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 52, United-States, >50K 58, Private, 104613, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 17, ?, 303317, 11th, 7, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 72, Private, 298070, Assoc-voc, 11, Separated, Other-service, Unmarried, White, Female, 6723, 0, 25, United-States, <=50K 19, Private, 318822, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 375078, 7th-8th, 4, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, Mexico, <=50K 20, ?, 232799, HS-grad, 9, Never-married, ?, Own-child, Black, Female, 0, 0, 25, United-States, <=50K 30, Private, 210851, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Self-emp-not-inc, 213745, Some-college, 10, Divorced, Other-service, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 51, Private, 204447, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 26, Private, 318934, 10th, 6, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 237386, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 42, United-States, <=50K 44, Private, 182629, Masters, 14, Divorced, Sales, Not-in-family, White, Male, 0, 0, 24, Iran, <=50K 43, Private, 144778, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 35, Private, 117166, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 51, Private, 237630, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 7298, 0, 50, United-States, >50K 41, Private, 171550, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 165302, Some-college, 10, Divorced, Adm-clerical, Unmarried, Other, Female, 0, 0, 40, United-States, <=50K 39, State-gov, 42186, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, Asian-Pac-Islander, Female, 3464, 0, 20, United-States, <=50K 54, Private, 284952, 10th, 6, Separated, Sales, Unmarried, White, Female, 0, 0, 43, Italy, <=50K 62, Private, 96099, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 198759, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 30, Private, 227886, HS-grad, 9, Never-married, Exec-managerial, Own-child, Black, Female, 0, 0, 35, Jamaica, <=50K 32, Private, 391874, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Self-emp-not-inc, 184370, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 84, Local-gov, 135839, Assoc-voc, 11, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 14, United-States, <=50K 46, Private, 194698, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 60, United-States, <=50K 67, Local-gov, 342175, Masters, 14, Divorced, Adm-clerical, Not-in-family, White, Female, 2009, 0, 40, United-States, <=50K 29, Private, 67218, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Private, 205152, Assoc-voc, 11, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 55, United-States, >50K 23, Private, 434467, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 42, United-States, <=50K 63, ?, 110150, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 55, United-States, >50K 55, ?, 123382, HS-grad, 9, Separated, ?, Not-in-family, Black, Female, 0, 2001, 40, United-States, <=50K 42, State-gov, 404573, Prof-school, 15, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 17, Private, 99462, 11th, 7, Never-married, Other-service, Own-child, Amer-Indian-Eskimo, Female, 0, 0, 20, United-States, <=50K 60, Private, 170310, 5th-6th, 3, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 199883, 12th, 8, Divorced, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 70034, 7th-8th, 4, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, Portugal, <=50K 31, Private, 393357, 9th, 5, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 48, United-States, <=50K 65, ?, 249043, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 10605, 0, 40, United-States, >50K 31, Private, 72630, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 14084, 0, 50, United-States, >50K 61, Private, 223133, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 43, State-gov, 345969, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 40, State-gov, 195520, Some-college, 10, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 49, United-States, <=50K 39, Private, 257942, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Local-gov, 269300, Some-college, 10, Married-spouse-absent, Adm-clerical, Unmarried, Black, Female, 0, 0, 27, United-States, <=50K 47, Private, 137354, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 45, Federal-gov, 232997, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 65, United-States, >50K 30, Private, 77266, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 30, Self-emp-not-inc, 164190, Prof-school, 15, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 153536, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Male, 14084, 0, 44, United-States, >50K 51, Local-gov, 26832, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 188096, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 72, United-States, >50K 48, Self-emp-inc, 369522, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 25, United-States, >50K 20, Private, 110998, Some-college, 10, Never-married, Adm-clerical, Own-child, Asian-Pac-Islander, Female, 0, 0, 30, United-States, <=50K 32, Private, 205152, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 3103, 0, 40, United-States, >50K 31, ?, 163890, Some-college, 10, Never-married, ?, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 19, Private, 358631, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 50, Private, 185354, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 33, Private, 336061, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 25, ?, 47011, Bachelors, 13, Never-married, ?, Own-child, White, Male, 0, 0, 20, United-States, <=50K 49, Private, 149949, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 1876, 40, United-States, <=50K 30, Private, 59496, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 32950, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 109912, Doctorate, 16, Married-civ-spouse, Exec-managerial, Wife, White, Female, 15024, 0, 32, United-States, >50K 24, Private, 199555, Assoc-voc, 11, Never-married, Sales, Unmarried, White, Male, 0, 0, 5, United-States, <=50K 28, Private, 91299, Assoc-voc, 11, Never-married, Adm-clerical, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 45, United-States, <=50K 56, Private, 99359, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 1617, 40, United-States, <=50K 38, Private, 242559, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 20, Private, 286391, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 2176, 0, 20, United-States, <=50K 82, Private, 132870, HS-grad, 9, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 4356, 18, United-States, <=50K 52, Federal-gov, 22428, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 60, United-States, >50K 32, Private, 239150, Some-college, 10, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 37, Private, 170563, Assoc-voc, 11, Separated, Prof-specialty, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 36, Private, 173542, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 286026, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Private, 72887, HS-grad, 9, Married-civ-spouse, Craft-repair, Own-child, Asian-Pac-Islander, Male, 3411, 0, 40, United-States, <=50K 49, Local-gov, 163229, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 56, United-States, <=50K 40, Local-gov, 165726, Assoc-voc, 11, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 70055, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 35, Private, 184655, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 139906, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 81, United-States, <=50K 32, Local-gov, 198211, Assoc-voc, 11, Married-spouse-absent, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 146540, 11th, 7, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 53, Local-gov, 132304, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 190916, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 17, Never-worked, 237272, 10th, 6, Never-married, ?, Own-child, White, Male, 0, 0, 30, United-States, <=50K 44, Private, 755858, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 70, United-States, >50K 52, Private, 127315, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 42, State-gov, 304302, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 34, Private, 184942, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 27, Private, 267989, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 188377, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 39, State-gov, 221059, Masters, 14, Married-civ-spouse, Prof-specialty, Other-relative, Other, Female, 7688, 0, 38, United-States, >50K 26, Private, 340787, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 140782, Masters, 14, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 1902, 38, United-States, >50K 57, Private, 169071, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 28, United-States, <=50K 36, Self-emp-not-inc, 151094, Assoc-voc, 11, Separated, Exec-managerial, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 27, Private, 122922, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 17, Private, 151141, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 15, United-States, <=50K 30, Private, 136651, 5th-6th, 3, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Mexico, <=50K 37, Private, 177285, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 0, 48, United-States, >50K 31, Local-gov, 128016, Bachelors, 13, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 200318, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 32, Private, 250354, 10th, 6, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 45, United-States, <=50K 58, Private, 191069, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 27856, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 8, United-States, <=50K 44, Private, 523484, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, United-States, >50K 39, Federal-gov, 257175, Bachelors, 13, Divorced, Tech-support, Unmarried, Black, Female, 0, 625, 40, United-States, <=50K 59, Private, 174864, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1485, 45, United-States, >50K 42, Private, 196029, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 48, United-States, >50K 45, Private, 200471, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 35, United-States, <=50K 20, Private, 353195, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 35, Private, 222868, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 221791, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, Black, Male, 0, 0, 40, United-States, <=50K 56, Private, 197114, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 28, United-States, <=50K 48, Private, 160220, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 58, Self-emp-not-inc, 274917, Masters, 14, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 32, Private, 348460, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 23, Private, 112683, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 12, United-States, <=50K 48, Private, 345831, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 105370, HS-grad, 9, Divorced, Protective-serv, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 48, Private, 345006, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, Mexico, <=50K 55, Private, 195329, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Female, 2202, 0, 35, Italy, <=50K 40, Local-gov, 108765, Assoc-voc, 11, Never-married, Exec-managerial, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 50, Private, 138022, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Self-emp-not-inc, 175029, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 19, Private, 189574, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 55, Self-emp-not-inc, 141409, 10th, 6, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 50, United-States, >50K 36, Self-emp-not-inc, 186035, Prof-school, 15, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 30, United-States, >50K 39, Private, 165235, Bachelors, 13, Separated, Prof-specialty, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, >50K 22, Private, 105043, Some-college, 10, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 230684, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 50, United-States, >50K 34, Private, 345705, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 1408, 38, United-States, <=50K 33, Private, 248584, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 50, United-States, <=50K 55, Private, 436861, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 14084, 0, 40, United-States, >50K 35, Private, 200153, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 50, Private, 398625, 11th, 7, Widowed, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 114043, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 29, Private, 169544, Assoc-voc, 11, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 56, Private, 343849, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 33, Private, 162572, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 40, United-States, >50K 24, Private, 291578, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 46, Private, 136162, Assoc-voc, 11, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 60, Self-emp-inc, 376133, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 15024, 0, 15, United-States, >50K 48, Self-emp-inc, 302612, Masters, 14, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 65, Local-gov, 240166, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 35, United-States, <=50K 29, Private, 193152, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 1408, 40, United-States, <=50K 42, Private, 248094, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1740, 43, United-States, <=50K 44, Private, 119281, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 73, Self-emp-not-inc, 300404, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 6, United-States, >50K 21, Private, 82847, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 32, Self-emp-inc, 161153, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 1902, 55, United-States, >50K 43, Federal-gov, 287008, Masters, 14, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 35, United-States, >50K 21, Private, 654141, HS-grad, 9, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 32, United-States, <=50K 30, Private, 252646, Some-college, 10, Separated, Transport-moving, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 54, Private, 171924, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 48, United-States, <=50K 19, Private, 219742, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 55, State-gov, 153788, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 37, United-States, <=50K 20, Private, 60639, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 28, United-States, <=50K 53, Private, 96062, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, Greece, <=50K 51, Private, 165614, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 55, United-States, >50K 33, Private, 159888, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 62, Private, 110586, Some-college, 10, Widowed, Priv-house-serv, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 24, Self-emp-not-inc, 143062, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, United-States, <=50K 17, Self-emp-inc, 413557, 9th, 5, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 137658, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 36, Private, 398931, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 311764, 10th, 6, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 35, United-States, <=50K 58, Private, 98725, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 38, Private, 140854, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 72, Private, 97304, HS-grad, 9, Married-spouse-absent, Machine-op-inspct, Unmarried, White, Male, 2346, 0, 40, ?, <=50K 26, Federal-gov, 352768, HS-grad, 9, Divorced, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 45, ?, 27184, HS-grad, 9, Widowed, ?, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 72, ?, 237229, Assoc-voc, 11, Widowed, ?, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 60, Private, 142494, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 40, United-States, >50K 27, Private, 210313, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, Guatemala, <=50K 38, Private, 194538, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, >50K 37, Self-emp-inc, 26698, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 1485, 44, United-States, >50K 28, Private, 211032, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 38, Self-emp-inc, 107909, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Private, 136077, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 19, Private, 184737, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 1721, 40, United-States, <=50K 28, Private, 214689, Bachelors, 13, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 25, United-States, <=50K 70, ?, 147558, Bachelors, 13, Divorced, ?, Not-in-family, White, Female, 0, 0, 7, United-States, <=50K 40, Self-emp-not-inc, 93793, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 26, Private, 247025, Assoc-voc, 11, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 284403, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 60, United-States, <=50K 29, Private, 221977, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 25, Federal-gov, 339956, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 40, United-States, <=50K 29, Private, 161097, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, >50K 60, Private, 223696, 1st-4th, 2, Divorced, Craft-repair, Not-in-family, Other, Male, 0, 0, 38, Dominican-Republic, <=50K 31, Private, 234500, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 51, Local-gov, 97005, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 242615, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 15, United-States, <=50K 36, Private, 174938, Bachelors, 13, Divorced, Tech-support, Unmarried, White, Male, 0, 0, 20, United-States, <=50K 35, Private, 160120, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, >50K 48, Private, 193775, Bachelors, 13, Divorced, Adm-clerical, Own-child, White, Male, 0, 0, 38, United-States, >50K 78, Self-emp-not-inc, 59583, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 25, United-States, <=50K 72, Private, 157913, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 17, United-States, <=50K 24, Private, 308205, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 58, ?, 158506, 11th, 7, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 16, United-States, <=50K 36, Private, 201769, 11th, 7, Never-married, Protective-serv, Not-in-family, Black, Male, 13550, 0, 40, United-States, >50K 48, Private, 330470, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 30, United-States, <=50K 28, Private, 184078, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 123384, Masters, 14, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 330132, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 47, Private, 274720, 5th-6th, 3, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 40, Jamaica, <=50K 50, Private, 129673, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 35, Federal-gov, 205584, 5th-6th, 3, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 17, Private, 327127, 11th, 7, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 20, United-States, <=50K 41, Private, 225892, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, >50K 37, Private, 224886, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 42, United-States, <=50K 35, Local-gov, 27763, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 56, Private, 73684, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Portugal, <=50K 23, Private, 107452, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 23871, Assoc-acdm, 12, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 79, Self-emp-inc, 309272, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 469864, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 55, Private, 286230, 11th, 7, Divorced, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 59, State-gov, 186308, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 22, Private, 113062, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 86150, 11th, 7, Never-married, Sales, Own-child, Asian-Pac-Islander, Female, 0, 0, 19, Philippines, <=50K 41, Private, 262038, 5th-6th, 3, Married-spouse-absent, Farming-fishing, Not-in-family, White, Male, 0, 0, 35, Mexico, <=50K 32, Private, 279231, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, Italy, <=50K 67, ?, 188903, 7th-8th, 4, Married-civ-spouse, ?, Husband, White, Male, 2414, 0, 40, United-States, <=50K 45, Private, 183786, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 61, Private, 339358, 5th-6th, 3, Married-civ-spouse, Farming-fishing, Other-relative, White, Female, 0, 0, 45, Mexico, <=50K 34, Private, 287737, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Self-emp-not-inc, 99203, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 297449, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 7298, 0, 50, United-States, >50K 35, Private, 113481, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 65, Private, 204042, HS-grad, 9, Divorced, Protective-serv, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 24, Private, 43387, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, England, >50K 37, Private, 99233, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Self-emp-not-inc, 313729, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 42, Private, 99679, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, >50K 18, Private, 169745, 7th-8th, 4, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 43, Federal-gov, 19914, Some-college, 10, Widowed, Exec-managerial, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 15, United-States, <=50K 31, Private, 113543, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, >50K 19, Private, 224241, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 40, Self-emp-inc, 137367, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 50, China, <=50K 32, Private, 263908, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 280798, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Local-gov, 203849, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Self-emp-inc, 62546, Doctorate, 16, Separated, Prof-specialty, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 40, Private, 197344, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 65, United-States, >50K 36, Private, 93225, Bachelors, 13, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 33, Private, 187560, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 36, United-States, <=50K 23, State-gov, 61743, 5th-6th, 3, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 21, Private, 186648, 10th, 6, Separated, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 173321, HS-grad, 9, Married-civ-spouse, Other-service, Wife, Black, Female, 0, 0, 32, United-States, <=50K 53, State-gov, 246820, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 20, ?, 424034, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 15, United-States, <=50K 53, Self-emp-not-inc, 291755, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 72, United-States, <=50K 58, Private, 104945, 9th, 5, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 60, United-States, <=50K 51, Private, 85423, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, >50K 31, Private, 214235, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 65, United-States, <=50K 35, Self-emp-not-inc, 278632, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, ?, 27415, 11th, 7, Never-married, ?, Own-child, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 31, Local-gov, 143392, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 21, Private, 277408, Some-college, 10, Never-married, Other-service, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 39, Self-emp-not-inc, 336793, Masters, 14, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, >50K 36, Private, 184112, Prof-school, 15, Married-civ-spouse, Prof-specialty, Wife, White, Female, 15024, 0, 45, United-States, >50K 51, Private, 74660, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 18, Private, 395026, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 12, United-States, <=50K 32, Private, 171215, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 56, Private, 121362, Bachelors, 13, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 35, Private, 409200, Assoc-acdm, 12, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 63, Private, 268965, 12th, 8, Widowed, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 61, Private, 136262, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 23, Private, 141323, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 52, Local-gov, 108083, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 19, Private, 82210, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 33, State-gov, 400943, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 35, Private, 308489, Bachelors, 13, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 50, United-States, <=50K 35, Private, 187053, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Female, 0, 0, 60, United-States, >50K 38, Private, 75826, Prof-school, 15, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 413345, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 22, Private, 356567, Assoc-voc, 11, Divorced, Tech-support, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 20, Private, 223811, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 159313, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 250170, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, >50K 59, Private, 135617, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 187346, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 108103, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 50, United-States, <=50K 27, Private, 255476, 5th-6th, 3, Never-married, Other-service, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 24, Private, 68577, Assoc-voc, 11, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 155961, HS-grad, 9, Never-married, Other-service, Own-child, Black, Female, 0, 0, 35, Jamaica, <=50K 22, State-gov, 264102, Some-college, 10, Never-married, Other-service, Other-relative, Black, Male, 0, 0, 39, Haiti, <=50K 37, Private, 167777, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 52, United-States, <=50K 36, Private, 225399, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 40, United-States, >50K 28, Private, 199998, HS-grad, 9, Separated, Other-service, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 55, Private, 199856, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 50, United-States, <=50K 29, ?, 189765, 5th-6th, 3, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 193042, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 44, United-States, <=50K 66, ?, 222810, Some-college, 10, Divorced, ?, Other-relative, White, Female, 0, 0, 35, United-States, <=50K 47, Local-gov, 162595, Some-college, 10, Married-spouse-absent, Craft-repair, Other-relative, White, Male, 0, 0, 45, United-States, <=50K 23, Private, 208826, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 50, Local-gov, 120190, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 40, Self-emp-not-inc, 27242, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 84, United-States, <=50K 51, Private, 348099, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 1590, 40, United-States, <=50K 34, Private, 185041, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 1669, 45, United-States, <=50K 28, Private, 309196, Bachelors, 13, Never-married, Protective-serv, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 52, State-gov, 254285, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1887, 70, Germany, >50K 39, Self-emp-inc, 336226, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 3103, 0, 60, United-States, >50K 43, Private, 240698, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 411797, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 35, United-States, >50K 25, Private, 178843, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 15, United-States, <=50K 42, Private, 136177, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 35, Private, 243409, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, Germany, <=50K 43, Private, 258049, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 53, United-States, >50K 34, Private, 164748, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, State-gov, 24185, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 38, United-States, >50K 30, Private, 167476, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 44, Private, 106900, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 44, United-States, >50K 52, Private, 53497, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 335704, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 36, Private, 211022, Assoc-voc, 11, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 30, Private, 163003, Bachelors, 13, Never-married, Exec-managerial, Own-child, Asian-Pac-Islander, Female, 0, 0, 52, Taiwan, <=50K 36, Self-emp-inc, 77146, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 45, United-States, >50K 39, Private, 67433, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 458549, 1st-4th, 2, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 96, Mexico, <=50K 26, Private, 190469, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 195411, HS-grad, 9, Never-married, Sales, Own-child, Black, Female, 0, 0, 20, United-States, <=50K 20, Private, 216889, Some-college, 10, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 40, United-States, <=50K 70, ?, 336007, 5th-6th, 3, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 20, United-States, <=50K 26, Private, 167350, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 50, United-States, <=50K 24, Private, 241857, Some-college, 10, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 35, United-States, <=50K 48, Private, 125892, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 62, Private, 272209, HS-grad, 9, Divorced, Priv-house-serv, Unmarried, Black, Female, 0, 0, 99, United-States, <=50K 48, Private, 175221, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 180195, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Private, 38090, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 44, United-States, <=50K 58, Private, 310085, 5th-6th, 3, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Federal-gov, 118686, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 29, ?, 112963, Some-college, 10, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 40, United-States, <=50K 45, Self-emp-inc, 120131, 7th-8th, 4, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 52, ?, <=50K 19, Private, 43937, Some-college, 10, Never-married, Other-service, Other-relative, White, Female, 0, 0, 20, United-States, <=50K 37, Private, 210438, 11th, 7, Never-married, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 23, Private, 176724, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Puerto-Rico, <=50K 31, Self-emp-not-inc, 113364, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 64, Self-emp-not-inc, 73986, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 20, United-States, <=50K 28, Local-gov, 197932, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 16, United-States, <=50K 32, Private, 193285, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 49, Local-gov, 223342, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 44, United-States, <=50K 35, Private, 49749, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 19, ?, 211553, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 35, United-States, <=50K 45, Private, 201865, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 39, Private, 322143, 12th, 8, Married-civ-spouse, Transport-moving, Husband, White, Male, 15024, 0, 70, United-States, >50K 55, Private, 158702, Some-college, 10, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 2339, 45, ?, <=50K 46, Self-emp-not-inc, 275625, Bachelors, 13, Divorced, Other-service, Unmarried, Asian-Pac-Islander, Female, 0, 0, 60, South, >50K 19, Private, 206599, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 16, United-States, <=50K 29, Private, 89813, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, Scotland, <=50K 25, State-gov, 156848, HS-grad, 9, Married-civ-spouse, Protective-serv, Own-child, White, Male, 0, 0, 35, United-States, <=50K 37, Private, 162494, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 205407, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 375313, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 36, Federal-gov, 930948, Some-college, 10, Separated, Adm-clerical, Unmarried, Black, Female, 6497, 0, 56, United-States, <=50K 32, Private, 127895, Some-college, 10, Never-married, Exec-managerial, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 34, Private, 248754, 11th, 7, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 188096, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 36, United-States, <=50K 20, Private, 216811, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 27, Self-emp-inc, 113870, Masters, 14, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 36, Federal-gov, 343052, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 280966, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 42044, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 32, Private, 309513, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 32, Private, 163604, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 52, Private, 224198, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 50, Private, 338283, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Private, 242375, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 25, Private, 81286, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 21, Private, 243368, Preschool, 1, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 50, Mexico, <=50K 31, Private, 217803, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 31, Self-emp-not-inc, 323020, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 30, United-States, <=50K 41, Private, 34278, Assoc-voc, 11, Separated, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 184579, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 60, United-States, <=50K 20, ?, 210781, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 10, United-States, <=50K 20, Private, 142673, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 29, Private, 131714, 10th, 6, Divorced, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 25, United-States, <=50K 51, Local-gov, 74784, Some-college, 10, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Local-gov, 181372, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 33, United-States, >50K 23, ?, 62507, Some-college, 10, Never-married, ?, Not-in-family, White, Female, 0, 0, 12, United-States, <=50K 48, Private, 155664, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 35, United-States, >50K 39, Private, 174924, HS-grad, 9, Separated, Exec-managerial, Not-in-family, White, Male, 14344, 0, 40, United-States, >50K 62, Private, 113440, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 35, United-States, <=50K 22, Private, 147227, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 46, Federal-gov, 207022, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 40, United-States, >50K 51, Local-gov, 123011, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 35, United-States, >50K 20, Private, 184678, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 40, Self-emp-inc, 182437, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 50, United-States, >50K 31, Private, 98639, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 174201, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 123780, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 38, United-States, <=50K 20, Private, 374116, HS-grad, 9, Never-married, Prof-specialty, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 37, Local-gov, 212005, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 65, Private, 123965, Bachelors, 13, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 242619, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 4650, 0, 40, United-States, <=50K 60, Local-gov, 138502, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 7298, 0, 48, United-States, >50K 27, Private, 113635, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 35, Ireland, <=50K 62, Private, 664366, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 53, Private, 218311, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 38, Private, 278557, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 49, Private, 314773, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 194861, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 400616, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 208117, Bachelors, 13, Never-married, Prof-specialty, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 184498, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 117674, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 19, Private, 162621, Some-college, 10, Never-married, Tech-support, Own-child, White, Male, 0, 0, 14, United-States, <=50K 23, Private, 368739, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 63, Self-emp-not-inc, 196994, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 15, United-States, <=50K 63, Self-emp-not-inc, 420629, Assoc-voc, 11, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 45, United-States, <=50K 62, Self-emp-inc, 245491, Bachelors, 13, Divorced, Sales, Not-in-family, White, Male, 99999, 0, 40, United-States, >50K 51, Self-emp-not-inc, 276456, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 3103, 0, 30, United-States, >50K 76, Local-gov, 169133, Some-college, 10, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 50, Private, 99307, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 5013, 0, 45, United-States, <=50K 45, Self-emp-inc, 120131, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 44, Self-emp-inc, 456236, Some-college, 10, Divorced, Sales, Own-child, White, Male, 0, 0, 45, United-States, >50K 51, Private, 107123, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 42, Local-gov, 125461, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 4650, 0, 35, United-States, <=50K 43, Local-gov, 36924, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 53, Private, 167065, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 53642, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 154668, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Federal-gov, 102238, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 54595, 10th, 6, Widowed, Other-service, Not-in-family, Black, Female, 0, 1980, 40, United-States, <=50K 27, Private, 152951, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 257042, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 60, Private, 74243, Assoc-voc, 11, Widowed, Craft-repair, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 49, Private, 149049, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 14344, 0, 45, United-States, >50K 33, Private, 117186, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 35, Private, 178322, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 31, State-gov, 286911, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 38, United-States, <=50K 54, Private, 203635, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 7298, 0, 60, United-States, >50K 57, Self-emp-not-inc, 177271, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, <=50K 30, Private, 149427, 9th, 5, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 45, United-States, <=50K 45, Private, 101656, 10th, 6, Never-married, Machine-op-inspct, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, Vietnam, <=50K 41, Private, 274363, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 7298, 0, 42, United-States, >50K 25, Private, 241025, Bachelors, 13, Never-married, Other-service, Own-child, White, Male, 0, 0, 18, United-States, <=50K 51, Self-emp-inc, 338836, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Private, 210534, 5th-6th, 3, Separated, Adm-clerical, Other-relative, White, Male, 0, 0, 40, El-Salvador, <=50K 28, Private, 95725, Assoc-voc, 11, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 47, ?, 178013, 10th, 6, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 20, Cuba, <=50K 53, Federal-gov, 167410, Bachelors, 13, Divorced, Tech-support, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 31, Private, 158162, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 13550, 0, 50, United-States, >50K 46, Private, 241935, 11th, 7, Married-civ-spouse, Other-service, Husband, Black, Male, 7688, 0, 40, United-States, >50K 25, Federal-gov, 406955, HS-grad, 9, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 341762, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 239303, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, ?, <=50K 30, Private, 38848, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 54744, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 332194, Some-college, 10, Never-married, Other-service, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 32, Self-emp-not-inc, 154950, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 30, United-States, <=50K 33, Self-emp-not-inc, 196342, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 31, Private, 201292, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 339767, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 20, England, >50K 26, Private, 250066, Assoc-voc, 11, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 318886, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, Black, Male, 0, 0, 40, United-States, <=50K 50, Local-gov, 124076, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 30, State-gov, 242122, HS-grad, 9, Separated, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 17, Private, 34019, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 35, Local-gov, 230754, Masters, 14, Never-married, Prof-specialty, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 29, Private, 213842, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Federal-gov, 196386, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, White, Male, 4064, 0, 40, El-Salvador, <=50K 32, Self-emp-not-inc, 62165, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, ?, <=50K 34, Private, 134737, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, >50K 32, Private, 515629, HS-grad, 9, Separated, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Federal-gov, 119199, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 90222, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 28443, Assoc-voc, 11, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 159442, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, Ireland, <=50K 54, Private, 315804, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 135840, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 38, Private, 81232, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, ?, >50K 43, Private, 118001, 7th-8th, 4, Separated, Farming-fishing, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 25, Private, 207875, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 20, United-States, <=50K 39, Private, 164898, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 57, Local-gov, 170066, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 25, United-States, >50K 47, Private, 111994, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 34, United-States, <=50K 45, Private, 166636, HS-grad, 9, Divorced, Other-service, Other-relative, Black, Female, 0, 0, 35, United-States, <=50K 24, State-gov, 61737, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Self-emp-not-inc, 241885, 10th, 6, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 234190, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 57, Private, 230899, 5th-6th, 3, Separated, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 114158, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 1977, 24, United-States, >50K 28, Private, 222442, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 51, Cuba, <=50K 27, Private, 157612, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 28, Private, 199903, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 74, ?, 292627, 1st-4th, 2, Married-civ-spouse, ?, Husband, Black, Male, 0, 0, 40, United-States, <=50K 44, Self-emp-not-inc, 156687, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, Asian-Pac-Islander, Male, 0, 0, 42, Japan, <=50K 27, Private, 369522, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 45, United-States, <=50K 61, Private, 226297, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 356017, 11th, 7, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 99, United-States, <=50K 28, Private, 189257, 9th, 5, Never-married, Handlers-cleaners, Own-child, Black, Female, 0, 0, 24, United-States, <=50K 20, Private, 157541, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 69251, Assoc-voc, 11, Never-married, Sales, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 38, State-gov, 272944, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 113667, HS-grad, 9, Never-married, Sales, Unmarried, Black, Female, 0, 0, 25, United-States, <=50K 40, Private, 222011, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, >50K 43, Private, 191196, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 38, Private, 169104, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 19, Private, 146679, Some-college, 10, Never-married, Exec-managerial, Own-child, Black, Male, 0, 0, 30, United-States, <=50K 56, Private, 226985, Assoc-acdm, 12, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 50, United-States, <=50K 38, Private, 153066, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 30, ?, 159303, Bachelors, 13, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 4, United-States, <=50K 22, Private, 200109, HS-grad, 9, Married-civ-spouse, Priv-house-serv, Wife, White, Female, 4508, 0, 40, United-States, <=50K 18, State-gov, 109445, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 25, United-States, <=50K 68, Private, 99491, Some-college, 10, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 35, Private, 172571, Assoc-voc, 11, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 42, Private, 143582, 7th-8th, 4, Married-civ-spouse, Other-service, Other-relative, Asian-Pac-Islander, Female, 0, 0, 48, ?, <=50K 32, Private, 207113, 10th, 6, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 43, Federal-gov, 192712, Some-college, 10, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 30, Private, 154297, 10th, 6, Never-married, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 62, Private, 238913, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 2829, 0, 24, United-States, <=50K 38, Private, 110402, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 207213, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 606111, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 60, Germany, >50K 26, Private, 34112, Assoc-voc, 11, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 119156, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 20, United-States, <=50K 19, Private, 249787, HS-grad, 9, Never-married, Other-service, Other-relative, Black, Male, 0, 0, 40, United-States, <=50K 20, Private, 153516, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 30, United-States, <=50K 25, State-gov, 260754, Bachelors, 13, Never-married, Protective-serv, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 28, Self-emp-not-inc, 155621, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 50, Columbia, <=50K 36, Private, 33983, Assoc-voc, 11, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 42, United-States, >50K 23, Private, 306601, Bachelors, 13, Never-married, Craft-repair, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 40, Mexico, <=50K 24, Private, 270075, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 50, United-States, <=50K 23, Private, 109430, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 187115, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 20, United-States, <=50K 25, Self-emp-not-inc, 463667, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 8, United-States, <=50K 24, Private, 52262, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 144064, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 62, United-States, <=50K 26, Private, 147821, Bachelors, 13, Never-married, Sales, Own-child, White, Female, 0, 0, 45, ?, <=50K 62, ?, 232719, Masters, 14, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 50, United-States, <=50K 36, Private, 268620, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 33, United-States, <=50K 45, Private, 81132, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 31, Private, 323069, Assoc-acdm, 12, Divorced, Sales, Unmarried, White, Female, 0, 880, 45, United-States, <=50K 34, Private, 242984, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 65, Self-emp-inc, 172684, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 44, Mexico, >50K 42, Private, 103932, Assoc-voc, 11, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 27, State-gov, 431637, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 40, Private, 188942, Some-college, 10, Married-civ-spouse, Sales, Wife, Black, Female, 0, 0, 40, Puerto-Rico, <=50K 53, Federal-gov, 170354, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 54, Private, 28518, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 30, State-gov, 193380, Bachelors, 13, Never-married, Prof-specialty, Other-relative, White, Male, 0, 0, 35, United-States, <=50K 59, Private, 175942, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, >50K 42, Self-emp-not-inc, 53956, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 55, United-States, <=50K 23, Private, 120773, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 96219, Bachelors, 13, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 15, United-States, <=50K 20, Private, 104164, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 190429, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 73, ?, 243030, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 30, United-States, <=50K 47, Self-emp-not-inc, 228660, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1977, 40, United-States, >50K 44, Private, 368757, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 220563, 12th, 8, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 233571, Assoc-voc, 11, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 37, United-States, >50K 39, Private, 187847, HS-grad, 9, Divorced, Machine-op-inspct, Own-child, White, Male, 0, 0, 50, United-States, <=50K 49, Private, 84298, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 40, United-States, >50K 44, Self-emp-not-inc, 254303, Some-college, 10, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 27, Private, 109611, 9th, 5, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 37, Portugal, <=50K 50, Private, 189183, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 206951, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Private, 282882, HS-grad, 9, Never-married, Sales, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 55, Private, 377061, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 53, Private, 209906, 1st-4th, 2, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 35, Puerto-Rico, <=50K 53, Local-gov, 176059, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 31, Private, 279015, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 2415, 70, Taiwan, >50K 21, Private, 347292, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 277314, HS-grad, 9, Separated, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 74, ?, 29887, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 10, United-States, <=50K 53, Private, 341439, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 60, United-States, >50K 47, Private, 209460, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1485, 47, United-States, <=50K 60, Private, 114263, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, Hungary, >50K 59, Private, 230899, 9th, 5, Separated, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 37, Private, 271767, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 48, United-States, >50K 47, Federal-gov, 20956, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1740, 40, United-States, <=50K 49, Private, 39986, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 73, Local-gov, 45784, Some-college, 10, Never-married, Prof-specialty, Other-relative, White, Female, 0, 0, 11, United-States, <=50K 58, Private, 126991, HS-grad, 9, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 20, United-States, <=50K 18, ?, 234648, 11th, 7, Never-married, ?, Own-child, Black, Male, 0, 0, 15, United-States, <=50K 35, Private, 207676, Some-college, 10, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 24, State-gov, 413345, Some-college, 10, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 50, United-States, <=50K 62, Private, 122033, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 58, Private, 169611, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 90363, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 15024, 0, 40, United-States, >50K 21, Private, 372636, HS-grad, 9, Never-married, Sales, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 30, Private, 340917, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 34273, Assoc-voc, 11, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 1876, 36, Canada, <=50K 25, Private, 161027, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 5178, 0, 40, United-States, >50K 31, Private, 99844, HS-grad, 9, Never-married, Craft-repair, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 45, United-States, <=50K 31, Private, 207685, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 34, United-States, <=50K 44, Private, 74680, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 5178, 0, 50, United-States, >50K 52, Self-emp-inc, 334273, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 65, United-States, >50K 30, Private, 36069, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 100563, HS-grad, 9, Never-married, Transport-moving, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 36, Private, 174308, 11th, 7, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 54, Self-emp-not-inc, 109413, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 59, Local-gov, 212600, Some-college, 10, Separated, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 55, Private, 271710, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 70, ?, 230816, Assoc-voc, 11, Never-married, ?, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 22, Private, 103277, Assoc-acdm, 12, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 42, Private, 318947, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 187167, Assoc-acdm, 12, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 204742, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 44, Private, 282062, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, ?, 283510, HS-grad, 9, Never-married, ?, Unmarried, Black, Male, 0, 0, 45, United-States, <=50K 25, Private, 280093, 11th, 7, Married-spouse-absent, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 31, Private, 202729, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 33, Private, 205950, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 54, Self-emp-not-inc, 392286, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 42, Self-emp-not-inc, 119207, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 49, Private, 195554, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 44, United-States, <=50K 30, Private, 173005, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 44, United-States, <=50K 54, Private, 192862, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 39, Private, 164712, Some-college, 10, Never-married, Transport-moving, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 195808, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 199444, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 44, United-States, <=50K 23, Private, 126346, 9th, 5, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 54, Private, 177675, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 42, United-States, <=50K 23, Private, 50341, Masters, 14, Never-married, Sales, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 39, Private, 237943, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Male, 0, 1726, 40, United-States, <=50K 23, Private, 126945, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 67, ?, 92061, HS-grad, 9, Widowed, ?, Other-relative, White, Female, 0, 0, 8, United-States, <=50K 19, ?, 109938, 11th, 7, Married-civ-spouse, ?, Wife, Asian-Pac-Islander, Female, 0, 0, 40, Laos, <=50K 41, Private, 267252, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 1902, 40, United-States, >50K 32, Private, 174704, 11th, 7, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 57, Private, 124771, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 200603, HS-grad, 9, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 30, United-States, <=50K 60, State-gov, 165827, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 60, United-States, >50K 21, Private, 301199, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 53, Private, 215790, Some-college, 10, Widowed, Adm-clerical, Other-relative, White, Female, 0, 0, 22, United-States, <=50K 38, Private, 87556, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 55, United-States, >50K 21, Private, 111467, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 82646, Doctorate, 16, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 55, United-States, >50K 24, Private, 162282, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Federal-gov, 239074, Assoc-acdm, 12, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 214925, Masters, 14, Never-married, Exec-managerial, Not-in-family, Black, Male, 0, 0, 60, United-States, <=50K 23, Private, 194247, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 211531, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 32, Local-gov, 223267, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 48, United-States, <=50K 25, Private, 201635, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 41, Self-emp-not-inc, 188738, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 27, United-States, <=50K 18, Private, 133055, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 57, Private, 61761, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1672, 45, United-States, <=50K 62, Private, 103344, Bachelors, 13, Widowed, Exec-managerial, Not-in-family, White, Male, 10520, 0, 50, United-States, >50K 29, Private, 109814, Bachelors, 13, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 225294, HS-grad, 9, Never-married, Other-service, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 35, Self-emp-not-inc, 97277, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 65, United-States, >50K 52, Private, 146711, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 28, Private, 286452, 10th, 6, Never-married, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 20308, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 224203, Some-college, 10, Widowed, Sales, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 41, Private, 225978, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 23, Private, 237720, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 31, Private, 156743, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 76, United-States, >50K 31, Private, 509364, 5th-6th, 3, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 45, Mexico, <=50K 46, Private, 144351, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 18, Private, 375515, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 57, Self-emp-not-inc, 103529, Masters, 14, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 38, United-States, >50K 25, Private, 199472, Assoc-voc, 11, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 32, Private, 348152, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 221166, 9th, 5, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 46, Federal-gov, 341762, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 45, United-States, >50K 17, ?, 634226, 10th, 6, Never-married, ?, Own-child, White, Female, 0, 0, 17, United-States, <=50K 43, State-gov, 159449, HS-grad, 9, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 56, Self-emp-not-inc, 110238, Bachelors, 13, Married-spouse-absent, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 19, Private, 458558, HS-grad, 9, Married-civ-spouse, Craft-repair, Wife, White, Female, 0, 0, 40, United-States, <=50K 20, Federal-gov, 340217, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 155106, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 90, Private, 90523, HS-grad, 9, Widowed, Transport-moving, Unmarried, White, Male, 0, 0, 99, United-States, <=50K 25, Private, 122756, 11th, 7, Separated, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 35, United-States, <=50K 27, Private, 293828, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 40, Jamaica, <=50K 48, Private, 299291, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 44, United-States, <=50K 48, Federal-gov, 483261, Some-college, 10, Never-married, Adm-clerical, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 27, Private, 122038, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, <=50K 46, Private, 160647, Bachelors, 13, Widowed, Tech-support, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 32, Private, 106541, 5th-6th, 3, Married-civ-spouse, Other-service, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 126945, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 188505, Bachelors, 13, Married-AF-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 31, Private, 377850, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 65, United-States, <=50K 20, Private, 193586, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 18, United-States, <=50K 28, Self-emp-not-inc, 315417, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Male, 2176, 0, 40, United-States, <=50K 40, Self-emp-inc, 57233, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 39, Private, 195253, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 54, Local-gov, 172991, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 59, Local-gov, 223215, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 42, United-States, <=50K 17, Private, 95799, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 18, United-States, <=50K 25, Self-emp-not-inc, 213385, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 80, United-States, <=50K 49, Local-gov, 202467, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 55, Self-emp-not-inc, 145574, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 34095, 0, 60, United-States, <=50K 39, Private, 147548, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 67, Private, 105216, Some-college, 10, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 16, United-States, <=50K 28, Private, 77760, HS-grad, 9, Never-married, Other-service, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 167990, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Canada, <=50K 44, Private, 167005, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 48, United-States, >50K 51, Private, 108435, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 47, United-States, >50K 55, Private, 56645, Bachelors, 13, Widowed, Farming-fishing, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 45, Local-gov, 304973, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 78, United-States, >50K 32, Private, 42596, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, <=50K 45, Private, 220641, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 101452, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 60, England, >50K 35, Private, 188888, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 55, Local-gov, 168790, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 44, United-States, <=50K 59, Private, 98361, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 22, Private, 401762, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 46, Local-gov, 160187, Masters, 14, Widowed, Exec-managerial, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 23, Private, 203715, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 144351, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 34, Private, 420749, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 30, Germany, <=50K 51, Private, 106151, 11th, 7, Divorced, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 362482, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 24, State-gov, 38151, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 12, United-States, <=50K 20, Private, 42706, Some-college, 10, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 72, United-States, <=50K 44, Private, 126199, Some-college, 10, Divorced, Transport-moving, Unmarried, White, Male, 1831, 0, 50, United-States, <=50K 26, Private, 165510, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 35, Local-gov, 216068, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 23, Private, 215624, Some-college, 10, Never-married, Machine-op-inspct, Unmarried, Asian-Pac-Islander, Male, 0, 0, 40, Vietnam, <=50K 40, Private, 239708, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 49, Local-gov, 199378, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 230420, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 28, Private, 395022, Assoc-voc, 11, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 338620, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 60, United-States, >50K 62, Private, 210142, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 31, Private, 446358, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 47, Local-gov, 352614, Assoc-acdm, 12, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 293528, Assoc-voc, 11, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 3, United-States, <=50K 44, State-gov, 55395, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 18, ?, 128538, HS-grad, 9, Never-married, ?, Own-child, White, Female, 0, 0, 20, United-States, <=50K 46, Private, 428405, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Private, 126838, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 51, Self-emp-not-inc, 136836, Assoc-acdm, 12, Divorced, Transport-moving, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 48, Private, 105838, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 28, Private, 139903, Bachelors, 13, Never-married, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 57, Self-emp-inc, 106103, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 60, United-States, >50K 33, Private, 186824, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 350387, HS-grad, 9, Separated, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 15, United-States, <=50K 17, Private, 142912, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 63, ?, 321403, 9th, 5, Separated, ?, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 31, Self-emp-inc, 114937, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 34, ?, 286689, Masters, 14, Never-married, ?, Not-in-family, White, Male, 4650, 0, 30, United-States, <=50K 35, Private, 147258, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 1974, 40, United-States, <=50K 20, Private, 451996, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 149833, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 211968, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 24, United-States, <=50K 33, Private, 287908, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 50, United-States, >50K 36, Private, 166549, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 25216, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 286452, Assoc-acdm, 12, Divorced, Sales, Unmarried, White, Female, 3418, 0, 40, United-States, <=50K 47, Private, 162034, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 30, Private, 186932, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 5178, 0, 75, United-States, >50K 34, Private, 82938, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 23, Private, 122048, HS-grad, 9, Never-married, Machine-op-inspct, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 118710, Assoc-voc, 11, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 59, Private, 243226, 10th, 6, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 67, Self-emp-not-inc, 268514, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 365289, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 165365, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Asian-Pac-Islander, Male, 2885, 0, 40, Laos, <=50K 20, Private, 219266, HS-grad, 9, Married-civ-spouse, Prof-specialty, Own-child, White, Female, 0, 0, 36, ?, <=50K 24, Private, 283757, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 39, United-States, <=50K 44, Federal-gov, 206553, Assoc-voc, 11, Divorced, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 113364, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 328949, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 19, Private, 83930, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 31, Self-emp-not-inc, 325355, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 1902, 40, United-States, >50K 20, Private, 131852, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 64, Private, 119506, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 47, State-gov, 100818, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 36, Private, 162302, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 48, Private, 182211, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 44, United-States, >50K 19, Self-emp-not-inc, 194205, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, Mexico, <=50K 22, Private, 141040, HS-grad, 9, Never-married, Sales, Own-child, Black, Female, 0, 0, 35, United-States, <=50K 56, Private, 346033, 9th, 5, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 177125, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 37, Private, 241174, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 99, United-States, >50K 57, Local-gov, 130532, Bachelors, 13, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 38, Private, 168496, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 34, Private, 362787, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 22, ?, 244771, 11th, 7, Separated, ?, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 38, Federal-gov, 48123, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Self-emp-inc, 173858, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 1902, 40, South, >50K 32, Private, 207201, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 29, Private, 37933, 12th, 8, Married-spouse-absent, Other-service, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 56, Private, 33323, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 175943, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Wife, White, Female, 7298, 0, 35, United-States, >50K 66, ?, 306178, 10th, 6, Divorced, ?, Not-in-family, White, Male, 2050, 0, 40, United-States, <=50K 71, Local-gov, 229110, HS-grad, 9, Widowed, Exec-managerial, Other-relative, White, Female, 0, 0, 33, United-States, <=50K 20, Private, 113511, 11th, 7, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 333677, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 36, United-States, <=50K 42, Private, 236021, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, ?, >50K 20, ?, 371089, HS-grad, 9, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 61, Private, 115023, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 24, State-gov, 133586, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 91137, 9th, 5, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 27, Private, 105598, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 352812, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 1902, 40, United-States, >50K 31, Private, 204829, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 247733, HS-grad, 9, Divorced, Priv-house-serv, Unmarried, Black, Female, 0, 0, 16, United-States, <=50K 36, ?, 370585, HS-grad, 9, Married-civ-spouse, ?, Husband, Black, Male, 0, 0, 40, United-States, <=50K 51, Self-emp-not-inc, 103257, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 178915, HS-grad, 9, Never-married, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 54260, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 43, Private, 55395, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 233511, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 60, United-States, >50K 49, Private, 318331, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 195985, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 44, Self-emp-not-inc, 38876, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 67, Self-emp-inc, 81413, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, Private, 172618, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 36, Private, 174717, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 40, United-States, >50K 67, Private, 224984, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 15831, 0, 16, Germany, >50K 61, Private, 423297, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 55, Local-gov, 88856, 7th-8th, 4, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 23, ?, 169104, Assoc-acdm, 12, Never-married, ?, Own-child, Asian-Pac-Islander, Male, 0, 0, 16, Philippines, <=50K 35, Federal-gov, 39207, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 340018, 10th, 6, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 38, United-States, <=50K 20, State-gov, 30796, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 10, United-States, <=50K 51, Private, 155403, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 0, 40, United-States, <=50K 23, Private, 238092, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 225605, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 24, United-States, <=50K 36, Private, 289148, Some-college, 10, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 339863, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 27, Private, 178778, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 80, United-States, >50K 29, Private, 568490, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, State-gov, 129345, Some-college, 10, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 447882, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 24, Private, 314165, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 20, United-States, <=50K 39, Federal-gov, 382859, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 51, State-gov, 82504, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 149700, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 15024, 0, 40, United-States, >50K 62, Private, 209844, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 49, Private, 62546, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Private, 228686, 11th, 7, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 326587, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 202091, HS-grad, 9, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 54, Self-emp-not-inc, 310774, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 450246, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 20, ?, 84375, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 45, United-States, <=50K 43, Private, 142444, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 0, 55, United-States, >50K 26, Private, 82246, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 1876, 38, United-States, <=50K 24, Private, 192766, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 53109, 11th, 7, Never-married, Other-service, Own-child, Amer-Indian-Eskimo, Male, 0, 0, 20, United-States, <=50K 45, Self-emp-inc, 121836, Some-college, 10, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, ?, >50K 45, Self-emp-not-inc, 298130, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 25, United-States, <=50K 26, Private, 135645, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 265275, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 54, ?, 410114, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Without-pay, 232719, HS-grad, 9, Never-married, Craft-repair, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 29, Private, 167716, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 99, United-States, <=50K 68, Private, 107627, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 15, United-States, <=50K 21, Private, 129674, Some-college, 10, Never-married, Exec-managerial, Not-in-family, Black, Male, 0, 0, 48, Mexico, <=50K 28, Self-emp-inc, 114053, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 46, Private, 202560, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 35, Private, 219902, HS-grad, 9, Separated, Transport-moving, Unmarried, Black, Female, 0, 0, 48, United-States, <=50K 50, Self-emp-not-inc, 192654, 10th, 6, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 48, Self-emp-inc, 238966, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 17, ?, 112942, 10th, 6, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 59, Private, 153484, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 15024, 0, 50, United-States, >50K 23, Private, 161874, Some-college, 10, Never-married, Exec-managerial, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 53, Private, 260106, HS-grad, 9, Widowed, Sales, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 50, Self-emp-inc, 240374, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 32, ?, 251612, 5th-6th, 3, Never-married, ?, Unmarried, White, Female, 0, 0, 45, Mexico, <=50K 53, Private, 223696, 12th, 8, Married-spouse-absent, Handlers-cleaners, Not-in-family, Other, Male, 0, 0, 56, Dominican-Republic, <=50K 52, Private, 176134, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 48, United-States, <=50K 38, Private, 186959, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 43, Private, 456236, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 35, Private, 98948, Bachelors, 13, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 32, United-States, <=50K 41, Private, 166662, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 22, Private, 448626, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 167482, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 60, United-States, >50K 45, Private, 189792, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 399052, 9th, 5, Married-civ-spouse, Farming-fishing, Wife, White, Female, 0, 0, 42, United-States, <=50K 40, Private, 104196, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1887, 40, United-States, >50K 47, Self-emp-not-inc, 152752, 5th-6th, 3, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 20, United-States, <=50K 53, Private, 268545, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, Jamaica, <=50K 53, Self-emp-inc, 148532, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 33, Local-gov, 281784, Bachelors, 13, Never-married, Tech-support, Not-in-family, Black, Male, 0, 1564, 52, United-States, >50K 24, Private, 225724, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 34, Private, 200192, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 46, Self-emp-inc, 170850, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 29, Federal-gov, 224858, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 60, United-States, <=50K 61, State-gov, 159908, 11th, 7, Widowed, Other-service, Unmarried, White, Female, 0, 0, 32, United-States, >50K 31, Private, 115488, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 1268339, HS-grad, 9, Married-spouse-absent, Tech-support, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 42, Private, 195755, HS-grad, 9, Separated, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 50, Federal-gov, 186272, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 181388, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 177181, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 74, Private, 91488, 1st-4th, 2, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 20, United-States, <=50K 40, Private, 230961, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 75, Self-emp-not-inc, 309955, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 2174, 50, United-States, >50K 40, Local-gov, 63042, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 36, Private, 29814, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, ?, 116230, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, >50K 42, ?, 167678, 11th, 7, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 22, Ecuador, <=50K 28, Private, 191088, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 19, Private, 63814, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 18, United-States, <=50K 36, Private, 285865, Assoc-acdm, 12, Separated, Other-service, Unmarried, Black, Female, 0, 0, 32, United-States, <=50K 33, ?, 160776, Assoc-voc, 11, Divorced, ?, Not-in-family, White, Female, 0, 0, 40, France, <=50K 50, Federal-gov, 299831, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 880, 40, United-States, <=50K 47, Private, 162741, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Wife, Black, Female, 15024, 0, 40, United-States, >50K 48, Private, 204990, HS-grad, 9, Never-married, Tech-support, Unmarried, Black, Female, 0, 0, 33, Jamaica, <=50K 60, Self-emp-inc, 171315, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 296462, Masters, 14, Never-married, Prof-specialty, Not-in-family, Black, Male, 0, 0, 30, United-States, <=50K 32, Private, 103860, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 45, Local-gov, 159816, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 1977, 35, United-States, >50K 51, Private, 96586, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 53, Private, 202720, 9th, 5, Married-spouse-absent, Machine-op-inspct, Unmarried, Black, Male, 0, 0, 75, Haiti, <=50K 34, Private, 202822, Masters, 14, Never-married, Tech-support, Unmarried, Black, Female, 0, 0, 40, ?, <=50K 48, Self-emp-not-inc, 379883, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, Mexico, >50K 68, ?, 123464, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 45, United-States, <=50K 32, Private, 294121, Assoc-acdm, 12, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 63, ?, 179981, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 4, United-States, <=50K 31, Private, 234387, HS-grad, 9, Divorced, Exec-managerial, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 58, Self-emp-not-inc, 154537, Bachelors, 13, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 32, Private, 125856, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 32, Private, 156015, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 116632, Bachelors, 13, Divorced, Sales, Own-child, White, Male, 0, 0, 80, United-States, <=50K 50, Private, 124963, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 55, United-States, >50K 38, Self-emp-not-inc, 115215, 10th, 6, Separated, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 254905, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 195532, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 190067, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 1564, 40, United-States, >50K 63, Private, 181828, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 48, ?, <=50K 32, Private, 203674, Assoc-acdm, 12, Divorced, Prof-specialty, Unmarried, White, Female, 0, 880, 36, United-States, <=50K 25, Private, 322585, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 59, Private, 246262, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 22, Local-gov, 211129, Assoc-voc, 11, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 10, ?, <=50K 49, Private, 139268, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 188540, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, ?, 251167, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 30, Mexico, <=50K 46, Private, 94809, Some-college, 10, Divorced, Priv-house-serv, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 37, Local-gov, 265038, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 48, Private, 182566, Bachelors, 13, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 40, United-States, >50K 43, Private, 220109, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 1672, 44, United-States, <=50K 41, Private, 208470, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 54, Private, 28683, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 3464, 0, 40, United-States, <=50K 36, Private, 233571, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 4, United-States, <=50K 29, Private, 24562, Bachelors, 13, Divorced, Other-service, Unmarried, Other, Female, 0, 0, 40, United-States, <=50K 66, Local-gov, 36364, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 2267, 40, United-States, <=50K 59, Private, 168569, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 62, Private, 167098, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Private, 271579, 10th, 6, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 28, Private, 191355, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 27, Private, 31659, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 1887, 60, United-States, >50K 42, State-gov, 83411, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 60, Private, 40856, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 46, United-States, >50K 58, Private, 115605, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 27, Private, 132326, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 220213, HS-grad, 9, Widowed, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 50, Private, 172511, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 43, Private, 156745, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 39, Private, 218916, Prof-school, 15, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 21, Private, 306114, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 20, United-States, <=50K 24, Private, 196675, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 70, United-States, <=50K 59, Self-emp-not-inc, 73411, Prof-school, 15, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 30, United-States, <=50K 36, Private, 184659, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 72, ?, 75890, Some-college, 10, Widowed, ?, Unmarried, Asian-Pac-Islander, Female, 0, 0, 4, United-States, <=50K 35, Private, 320451, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 65, Hong, >50K 33, Private, 172498, Some-college, 10, Divorced, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 131588, HS-grad, 9, Never-married, Craft-repair, Not-in-family, Black, Female, 0, 0, 45, United-States, <=50K 40, Private, 124520, Assoc-voc, 11, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 50, United-States, >50K 26, Self-emp-not-inc, 93806, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, <=50K 37, Federal-gov, 173192, Assoc-voc, 11, Separated, Adm-clerical, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 68, Self-emp-not-inc, 198554, Some-college, 10, Divorced, Transport-moving, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 45, Private, 26502, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 72, United-States, >50K 56, Private, 225267, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 150042, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 50, Private, 211319, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 50, United-States, >50K 38, Private, 208358, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 58115, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 41, United-States, <=50K 28, Private, 219267, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 28, United-States, <=50K 39, Federal-gov, 129573, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, <=50K 26, Local-gov, 27834, Bachelors, 13, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 52, Self-emp-inc, 415037, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 65, United-States, >50K 52, Private, 191529, Bachelors, 13, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 84, Private, 132806, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 13, United-States, <=50K 33, Federal-gov, 137059, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 10, United-States, <=50K 46, Federal-gov, 102308, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 50, United-States, >50K 30, Private, 164309, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 38, Private, 40955, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, England, >50K 66, Private, 141085, HS-grad, 9, Widowed, Priv-house-serv, Not-in-family, White, Female, 0, 0, 8, United-States, <=50K 62, Federal-gov, 258124, Masters, 14, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, Italy, >50K 31, Private, 467579, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 1887, 40, United-States, >50K 31, Private, 145139, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 231141, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 2829, 0, 40, United-States, <=50K 60, Self-emp-not-inc, 146674, HS-grad, 9, Divorced, Craft-repair, Not-in-family, Black, Male, 0, 0, 50, ?, <=50K 27, Private, 242207, Bachelors, 13, Never-married, Tech-support, Own-child, White, Female, 0, 0, 40, United-States, <=50K 37, ?, 102541, Assoc-voc, 11, Married-civ-spouse, ?, Wife, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 38, Private, 135416, Some-college, 10, Divorced, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 267284, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 130812, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 42, Self-emp-not-inc, 183765, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, ?, <=50K 45, Local-gov, 188823, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 22, Private, 200593, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 124094, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Poland, <=50K 21, Private, 50411, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Local-gov, 101689, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 60, Self-emp-not-inc, 73091, HS-grad, 9, Separated, Other-service, Not-in-family, Black, Male, 0, 1876, 50, United-States, <=50K 21, ?, 107801, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 6, United-States, <=50K 51, Private, 176969, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, <=50K 30, Private, 342709, HS-grad, 9, Married-spouse-absent, Craft-repair, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 46, Self-emp-not-inc, 368561, Assoc-acdm, 12, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 26915, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 57, Private, 157974, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 48, United-States, <=50K 48, Private, 109832, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 40, United-States, >50K 39, Self-emp-inc, 116358, Bachelors, 13, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 7688, 0, 40, ?, >50K 68, Self-emp-not-inc, 195881, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 2414, 0, 40, United-States, <=50K 33, Private, 183000, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 24, United-States, <=50K 22, Without-pay, 302347, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 4416, 0, 40, United-States, <=50K 18, ?, 151463, 11th, 7, Never-married, ?, Other-relative, White, Male, 0, 0, 7, United-States, <=50K 28, Private, 217200, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 32, Private, 31740, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, India, <=50K 56, Private, 35520, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 42, United-States, <=50K 36, Private, 369843, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 50, United-States, <=50K 34, Private, 199227, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, <=50K 18, Private, 144711, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 1721, 40, United-States, <=50K 39, Private, 382802, 10th, 6, Widowed, Machine-op-inspct, Not-in-family, Black, Male, 0, 1590, 40, United-States, <=50K 25, Private, 254781, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, Self-emp-not-inc, 70657, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 56, Self-emp-not-inc, 50791, Masters, 14, Divorced, Sales, Not-in-family, White, Male, 0, 1876, 60, United-States, <=50K 33, Self-emp-not-inc, 222162, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Self-emp-inc, 94606, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 60, United-States, >50K 44, Self-emp-not-inc, 104196, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 84, United-States, <=50K 30, Self-emp-not-inc, 455995, 11th, 7, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 27, Private, 166210, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 25, Private, 198986, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 30, Self-emp-inc, 292465, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 99388, Assoc-acdm, 12, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, El-Salvador, <=50K 38, Private, 698363, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 154940, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 401998, HS-grad, 9, Widowed, Machine-op-inspct, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 62, Private, 162825, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 55, Self-emp-not-inc, 271795, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Self-emp-not-inc, 134671, HS-grad, 9, Married-spouse-absent, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 87583, HS-grad, 9, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 14, United-States, <=50K 50, Private, 248619, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 130200, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 178922, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 23, Private, 51985, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 37, Private, 125933, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 50, United-States, >50K 38, State-gov, 104280, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 27, Private, 617860, Some-college, 10, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 29, Private, 122112, Bachelors, 13, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 50, United-States, <=50K 45, Local-gov, 181758, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 41, Self-emp-inc, 223671, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 1887, 55, United-States, >50K 38, Self-emp-not-inc, 140117, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 27, Private, 107458, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 51, Federal-gov, 215948, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, Other, Male, 0, 0, 40, ?, <=50K 44, Federal-gov, 306440, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, Federal-gov, 615893, Masters, 14, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, Nicaragua, <=50K 28, Self-emp-inc, 201186, HS-grad, 9, Married-civ-spouse, Sales, Husband, Black, Male, 99999, 0, 40, United-States, >50K 32, Private, 37210, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 43, Private, 196084, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, <=50K 45, Local-gov, 166181, HS-grad, 9, Divorced, Other-service, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 52, Federal-gov, 291096, Assoc-acdm, 12, Married-civ-spouse, Other-service, Husband, White, Male, 7298, 0, 40, United-States, >50K 24, Private, 232841, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 19, ?, 131982, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 408788, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 53, Self-emp-inc, 42924, Doctorate, 16, Divorced, Exec-managerial, Not-in-family, White, Male, 14084, 0, 50, United-States, >50K 31, Private, 181091, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Private, 200246, Assoc-voc, 11, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 56, Private, 282023, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Federal-gov, 128990, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 106838, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 144750, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 18, United-States, <=50K 39, Private, 108140, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 103323, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 268022, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 55, United-States, >50K 58, Private, 197114, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 191628, HS-grad, 9, Never-married, Transport-moving, Not-in-family, Black, Male, 2174, 0, 40, United-States, <=50K 59, Local-gov, 176118, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 24, Private, 42401, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 47, United-States, <=50K 42, Private, 322385, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 2407, 0, 40, United-States, <=50K 53, State-gov, 123011, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 35, Private, 210945, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 50, United-States, <=50K 36, Local-gov, 130620, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, Asian-Pac-Islander, Female, 0, 0, 40, China, >50K 26, Private, 248990, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Mexico, <=50K 33, Private, 132705, 9th, 5, Separated, Adm-clerical, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 29, Private, 94892, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 141858, 11th, 7, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 81232, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 50, United-States, >50K 48, Private, 114561, Bachelors, 13, Married-spouse-absent, Prof-specialty, Other-relative, Asian-Pac-Islander, Female, 0, 0, 36, Philippines, >50K 45, Local-gov, 191776, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 128354, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 37088, 9th, 5, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, United-States, <=50K 21, Private, 414812, 7th-8th, 4, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 63, ?, 156799, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 4, United-States, <=50K 39, Private, 33983, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 15024, 0, 40, United-States, >50K 52, Self-emp-not-inc, 194995, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 55, United-States, >50K 41, Self-emp-inc, 73431, Bachelors, 13, Widowed, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 48, Private, 155664, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 7688, 0, 70, United-States, >50K 27, ?, 182386, 11th, 7, Divorced, ?, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 53, State-gov, 281074, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 1092, 40, United-States, <=50K 33, Local-gov, 248346, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 37, Private, 167482, 10th, 6, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 35, United-States, <=50K 18, ?, 171088, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 43, Federal-gov, 211763, Doctorate, 16, Separated, Prof-specialty, Unmarried, Black, Female, 0, 0, 24, United-States, >50K 20, Private, 122166, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 370119, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 36, Self-emp-not-inc, 138940, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 70, United-States, <=50K 41, Private, 174575, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1887, 45, United-States, >50K 67, Private, 101132, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 1797, 0, 40, United-States, <=50K 38, Private, 292307, Bachelors, 13, Married-spouse-absent, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, Dominican-Republic, <=50K 47, Self-emp-not-inc, 248776, Masters, 14, Never-married, Exec-managerial, Not-in-family, Black, Male, 0, 0, 25, United-States, <=50K 39, Private, 314007, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Self-emp-not-inc, 213226, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1485, 35, ?, <=50K 36, Private, 76845, HS-grad, 9, Never-married, Other-service, Own-child, Black, Male, 0, 0, 35, United-States, <=50K 24, Private, 148320, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, <=50K 50, Self-emp-not-inc, 54261, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 84, United-States, <=50K 21, Private, 223352, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 1055, 0, 30, United-States, <=50K 21, Private, 211013, 9th, 5, Never-married, Other-service, Own-child, White, Female, 0, 0, 50, Mexico, <=50K 40, Private, 209833, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 356272, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 38, Private, 143538, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 242960, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 44, Local-gov, 263871, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 20, Private, 151105, Assoc-acdm, 12, Never-married, Sales, Own-child, White, Female, 0, 0, 25, United-States, <=50K 44, Private, 207685, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 1564, 55, England, >50K 49, Local-gov, 46537, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 594, 0, 10, United-States, <=50K 45, Self-emp-inc, 84324, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 24, Private, 224716, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 186269, HS-grad, 9, Divorced, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 58, Self-emp-not-inc, 143731, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 72, United-States, >50K 39, Private, 236391, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 22, Private, 54560, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 266325, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 32, United-States, >50K 32, Federal-gov, 42900, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 50, United-States, >50K 45, State-gov, 183710, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 23, Private, 278254, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 45, United-States, <=50K 35, Private, 119992, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 52, Private, 284329, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 55, Private, 368727, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 353696, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 31387, Bachelors, 13, Married-civ-spouse, Adm-clerical, Own-child, Amer-Indian-Eskimo, Female, 2885, 0, 25, United-States, <=50K 27, Private, 110931, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 169532, Assoc-acdm, 12, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 15, United-States, <=50K 21, Private, 285522, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 198774, Bachelors, 13, Divorced, Sales, Other-relative, White, Female, 0, 0, 35, United-States, <=50K 32, Private, 123291, 12th, 8, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 64, Private, 146110, Some-college, 10, Widowed, Other-service, Unmarried, White, Female, 0, 0, 24, United-States, <=50K 37, Self-emp-not-inc, 29814, HS-grad, 9, Never-married, Farming-fishing, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 61, Private, 195595, 7th-8th, 4, Married-spouse-absent, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, Guatemala, <=50K 44, Private, 92649, HS-grad, 9, Married-civ-spouse, Craft-repair, Wife, White, Female, 0, 0, 40, United-States, >50K 53, Private, 290688, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 52, United-States, >50K 43, Private, 427382, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 60, State-gov, 234854, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 40, United-States, >50K 23, Private, 276568, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 250038, Masters, 14, Married-civ-spouse, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 29, Private, 150861, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 87205, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 55, England, <=50K 47, Private, 343579, 1st-4th, 2, Married-spouse-absent, Farming-fishing, Not-in-family, White, Male, 0, 0, 12, Mexico, <=50K 20, Private, 94401, HS-grad, 9, Never-married, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 120238, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 5178, 0, 40, Poland, >50K 27, Private, 205440, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 198996, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 294253, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 27, United-States, <=50K 23, Private, 256628, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 32, United-States, <=50K 59, Self-emp-not-inc, 223131, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 46, Private, 207301, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 37, United-States, <=50K 66, ?, 270460, 7th-8th, 4, Divorced, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 46, Local-gov, 125457, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 38, United-States, >50K 36, Local-gov, 212856, 11th, 7, Never-married, Other-service, Unmarried, White, Female, 0, 0, 23, United-States, <=50K 44, Private, 197389, HS-grad, 9, Married-spouse-absent, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 17, Private, 73338, 11th, 7, Never-married, Sales, Own-child, White, Male, 0, 0, 20, United-States, <=50K 27, Private, 68037, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 32, Private, 185027, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 53, Private, 107123, HS-grad, 9, Divorced, Other-service, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 22, Private, 109482, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 98, United-States, <=50K 30, Private, 174543, Assoc-acdm, 12, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 47, Self-emp-not-inc, 208407, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 2002, 30, United-States, <=50K 68, Self-emp-not-inc, 211584, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 108540, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 202416, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 62, ?, 160155, 7th-8th, 4, Married-civ-spouse, ?, Husband, White, Male, 6418, 0, 40, United-States, >50K 20, Private, 176178, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 35, United-States, <=50K 21, Private, 265148, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 38, Jamaica, <=50K 34, Private, 220631, Assoc-voc, 11, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 50, ?, <=50K 30, Self-emp-not-inc, 303692, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 75, United-States, <=50K 25, Private, 135845, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 23, State-gov, 199915, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 21, United-States, <=50K 40, State-gov, 150533, Bachelors, 13, Married-civ-spouse, Prof-specialty, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 26, Federal-gov, 85482, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 57, Self-emp-not-inc, 24473, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 272944, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 43, ?, 82077, Some-college, 10, Divorced, ?, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 49, State-gov, 194895, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 58, Private, 314153, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Private, 176253, Some-college, 10, Divorced, Exec-managerial, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 59, Private, 113959, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, >50K 42, State-gov, 167581, Bachelors, 13, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 79586, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Iran, <=50K 40, Private, 166662, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 45, United-States, >50K 47, Private, 72896, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, Private, 345730, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 30, Private, 302473, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 42346, HS-grad, 9, Widowed, Exec-managerial, Not-in-family, Black, Female, 0, 0, 35, United-States, <=50K 21, Private, 243921, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 131620, HS-grad, 9, Married-spouse-absent, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, Dominican-Republic, <=50K 47, Private, 158924, HS-grad, 9, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 40, United-States, <=50K 22, Self-emp-not-inc, 32921, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 20, United-States, <=50K 35, Private, 252897, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 14344, 0, 40, United-States, >50K 41, Private, 155657, 11th, 7, Never-married, Handlers-cleaners, Other-relative, Black, Female, 0, 0, 40, United-States, <=50K 43, Federal-gov, 155106, Bachelors, 13, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 53, United-States, <=50K 60, Private, 82775, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, <=50K 73, Private, 26248, 7th-8th, 4, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 30, United-States, >50K 90, Private, 88991, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, England, >50K 62, Federal-gov, 125155, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 38, United-States, <=50K 28, Private, 218039, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 53524, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 259352, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 30, Private, 296453, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 19, Private, 278915, 12th, 8, Never-married, Handlers-cleaners, Own-child, Black, Female, 0, 0, 52, United-States, <=50K 23, Private, 565313, Some-college, 10, Never-married, Other-service, Own-child, Black, Male, 2202, 0, 80, United-States, <=50K 22, Federal-gov, 274103, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 10, United-States, <=50K 19, Private, 271118, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 28, United-States, <=50K 45, Federal-gov, 207107, Assoc-acdm, 12, Divorced, Adm-clerical, Unmarried, Asian-Pac-Islander, Male, 0, 2080, 40, Philippines, <=50K 26, Local-gov, 138597, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 25, United-States, <=50K 42, Local-gov, 180985, 10th, 6, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 99999, 0, 40, United-States, >50K 62, Self-emp-not-inc, 159939, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 35, United-States, <=50K 61, Private, 110920, 10th, 6, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 34862, Bachelors, 13, Divorced, Sales, Not-in-family, Amer-Indian-Eskimo, Male, 0, 1564, 60, United-States, >50K 22, Local-gov, 163205, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 53, United-States, <=50K 56, Private, 110003, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Private, 229051, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, ?, 144898, Some-college, 10, Never-married, ?, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 211596, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 48458, HS-grad, 9, Never-married, Sales, Own-child, Black, Female, 0, 1669, 45, United-States, <=50K 58, Private, 201393, Assoc-acdm, 12, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 1876, 40, United-States, <=50K 25, Self-emp-not-inc, 136450, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 35, United-States, >50K 23, Private, 193586, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 25, United-States, <=50K 23, Private, 91189, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 227832, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 271936, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 35, Private, 61343, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Private, 157778, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 25, United-States, >50K 23, Private, 201680, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 228320, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 50, United-States, >50K 72, Private, 33404, 10th, 6, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 21, Private, 103205, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 279029, Bachelors, 13, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 213092, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 58, Private, 126104, Masters, 14, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 1980, 45, United-States, <=50K 32, Private, 119124, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 65, Private, 31924, Some-college, 10, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 22, Private, 253799, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, ?, <=50K 52, Private, 266138, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, ?, >50K 65, Private, 185001, 10th, 6, Widowed, Sales, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 33, Self-emp-not-inc, 34102, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 35, Private, 115214, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, White, Male, 6497, 0, 65, United-States, <=50K 27, Private, 289484, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 34, State-gov, 287908, HS-grad, 9, Never-married, Other-service, Own-child, Black, Male, 0, 0, 42, United-States, <=50K 53, Self-emp-not-inc, 158284, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 70, United-States, <=50K 23, Private, 60668, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Portugal, <=50K 43, State-gov, 222978, Doctorate, 16, Separated, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, >50K 58, Private, 244605, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 3908, 0, 40, United-States, <=50K 38, Private, 150601, 10th, 6, Separated, Adm-clerical, Unmarried, White, Male, 0, 3770, 40, United-States, <=50K 26, Private, 199143, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 50, United-States, <=50K 60, Private, 131681, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 28, Private, 346406, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 1672, 50, United-States, <=50K 33, Federal-gov, 391122, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 30, United-States, <=50K 29, Local-gov, 280344, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, State-gov, 188809, Doctorate, 16, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 41, Private, 277488, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 36, United-States, <=50K 63, Self-emp-not-inc, 181561, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 31, Private, 158545, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 27, United-States, <=50K 23, Private, 313573, Bachelors, 13, Never-married, Sales, Own-child, Black, Female, 0, 0, 25, United-States, <=50K 31, Private, 591711, Some-college, 10, Married-spouse-absent, Transport-moving, Not-in-family, Black, Male, 0, 0, 40, ?, <=50K 41, Private, 268183, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 51, Private, 392286, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 59, Private, 233312, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Private, 520231, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 24, Self-emp-not-inc, 186831, Some-college, 10, Never-married, Exec-managerial, Not-in-family, Black, Male, 0, 0, 45, United-States, <=50K 67, Self-emp-not-inc, 141085, HS-grad, 9, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 65, ?, 198019, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 47, Local-gov, 198660, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 21, Private, 409230, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Guatemala, <=50K 38, Private, 376025, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 80167, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 99357, Masters, 14, Divorced, Prof-specialty, Own-child, White, Female, 1506, 0, 40, United-States, <=50K 24, Private, 82847, HS-grad, 9, Separated, Other-service, Unmarried, White, Female, 0, 0, 50, Portugal, >50K 24, Private, 22201, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Thailand, <=50K 38, Private, 275223, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 7298, 0, 40, United-States, >50K 19, Private, 117595, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 24, United-States, <=50K 32, Private, 207668, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 63, Self-emp-not-inc, 179981, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 18, Private, 192583, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 36, Private, 66304, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 41, Private, 200671, Bachelors, 13, Divorced, Transport-moving, Own-child, Black, Male, 6497, 0, 40, United-States, <=50K 57, Private, 32365, Some-college, 10, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 28497, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 222978, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 1504, 40, United-States, <=50K 25, Private, 160261, Some-college, 10, Never-married, Exec-managerial, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, China, <=50K 48, Private, 120724, 12th, 8, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 20, Private, 91733, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 8, United-States, <=50K 74, Self-emp-not-inc, 146929, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, <=50K 44, Private, 205706, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 181666, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, United-States, <=50K 54, Local-gov, 279452, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 207568, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 48, United-States, >50K 38, Private, 22494, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 7443, 0, 40, United-States, <=50K 18, Private, 210026, 10th, 6, Never-married, Other-service, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 32, Local-gov, 190889, Masters, 14, Never-married, Prof-specialty, Not-in-family, Other, Female, 0, 0, 40, ?, <=50K 24, Private, 109869, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 19, Self-emp-not-inc, 285263, 9th, 5, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 35, Mexico, <=50K 28, Private, 192588, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 232945, HS-grad, 9, Separated, Handlers-cleaners, Not-in-family, Other, Male, 0, 0, 30, United-States, <=50K 49, Local-gov, 31339, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 305147, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 63, Private, 188914, HS-grad, 9, Widowed, Machine-op-inspct, Other-relative, Black, Female, 0, 0, 40, Haiti, <=50K 58, Self-emp-not-inc, 141165, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 68, Self-emp-inc, 136218, HS-grad, 9, Widowed, Other-service, Unmarried, White, Female, 0, 0, 15, United-States, <=50K 41, Federal-gov, 371382, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, United-States, >50K 21, ?, 199177, HS-grad, 9, Never-married, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 221366, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 3103, 0, 50, United-States, >50K 24, Private, 403671, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 193871, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 306183, Some-college, 10, Divorced, Other-service, Own-child, White, Female, 0, 0, 44, United-States, <=50K 64, ?, 159938, HS-grad, 9, Divorced, ?, Not-in-family, White, Male, 8614, 0, 40, United-States, >50K 54, Private, 124194, HS-grad, 9, Widowed, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 69847, Bachelors, 13, Never-married, Adm-clerical, Own-child, Asian-Pac-Islander, Female, 0, 0, 30, United-States, <=50K 26, State-gov, 169323, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, State-gov, 172327, Bachelors, 13, Separated, Exec-managerial, Not-in-family, White, Male, 0, 0, 42, United-States, <=50K 48, Private, 118889, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 2885, 0, 15, United-States, <=50K 50, Private, 166220, Assoc-acdm, 12, Married-civ-spouse, Sales, Wife, White, Female, 3942, 0, 40, United-States, <=50K 39, Private, 186420, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 192779, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 41, Private, 105616, Some-college, 10, Widowed, Adm-clerical, Unmarried, Black, Female, 0, 0, 48, United-States, <=50K 24, Private, 141113, 7th-8th, 4, Married-civ-spouse, Sales, Husband, White, Male, 2580, 0, 40, United-States, <=50K 57, Private, 160275, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 164507, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, Columbia, <=50K 41, Private, 207578, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 50, India, >50K 55, Private, 314592, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 41, ?, 254630, Assoc-voc, 11, Divorced, ?, Not-in-family, White, Male, 0, 0, 80, United-States, <=50K 69, Private, 159522, 7th-8th, 4, Divorced, Machine-op-inspct, Unmarried, Black, Female, 2964, 0, 40, United-States, <=50K 22, Private, 112130, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 45, Private, 192835, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 3942, 0, 40, United-States, <=50K 33, Private, 206280, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 57, Private, 308861, Some-college, 10, Separated, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Self-emp-not-inc, 93206, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 1902, 65, United-States, >50K 40, Private, 206066, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 48, Self-emp-not-inc, 309895, Some-college, 10, Divorced, Handlers-cleaners, Own-child, White, Female, 0, 0, 40, United-States, <=50K 38, Local-gov, 216129, Some-college, 10, Married-spouse-absent, Exec-managerial, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 26, State-gov, 287420, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 24, Private, 163595, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 170092, HS-grad, 9, Married-spouse-absent, Other-service, Unmarried, Black, Female, 0, 0, 20, United-States, <=50K 37, Private, 287031, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 5178, 0, 75, United-States, >50K 42, Private, 59474, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 99151, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 37, Private, 206888, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 28, Private, 177119, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 80, ?, <=50K 22, Private, 173736, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 182163, 11th, 7, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, Germany, <=50K 45, Local-gov, 311080, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Self-emp-not-inc, 389857, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 23, Private, 297152, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 25, United-States, <=50K 24, Federal-gov, 130534, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 137301, Assoc-acdm, 12, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 58, Private, 316235, HS-grad, 9, Divorced, Sales, Other-relative, White, Female, 0, 0, 32, United-States, <=50K 28, Self-emp-inc, 32922, Assoc-voc, 11, Never-married, Sales, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 58, Private, 118303, HS-grad, 9, Widowed, Sales, Not-in-family, White, Female, 0, 0, 35, United-States, >50K 18, Private, 188241, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 16, United-States, <=50K 59, Private, 236731, 7th-8th, 4, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, Puerto-Rico, <=50K 39, Private, 209397, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 53, Self-emp-inc, 290640, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 54, Private, 221915, Prof-school, 15, Never-married, Prof-specialty, Other-relative, White, Female, 0, 0, 65, United-States, <=50K 51, Private, 175246, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 59, Private, 159724, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 7298, 0, 55, United-States, >50K 42, State-gov, 160369, HS-grad, 9, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 36, Private, 461337, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 187311, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 32, Private, 29312, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 38, Self-emp-not-inc, 197365, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 50, United-States, <=50K 19, Private, 301747, HS-grad, 9, Separated, Adm-clerical, Own-child, White, Female, 0, 0, 30, United-States, <=50K 55, Local-gov, 135439, Bachelors, 13, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 30, Private, 340917, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 155057, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 65, ?, 200749, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 25, United-States, <=50K 44, Private, 323627, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 5, United-States, <=50K 23, ?, 154921, 5th-6th, 3, Never-married, ?, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 32, Private, 131425, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, <=50K 60, Private, 184242, HS-grad, 9, Married-spouse-absent, Other-service, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 28, Private, 149769, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, Cambodia, <=50K 44, Private, 124924, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, Mexico, <=50K 29, Private, 253003, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 16, United-States, <=50K 57, State-gov, 250976, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 104196, Some-college, 10, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 34, Self-emp-not-inc, 250182, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 44, Private, 188331, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 42, United-States, <=50K 44, Private, 187322, Bachelors, 13, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 130714, 1st-4th, 2, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 22, United-States, <=50K 37, Private, 40955, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 35, Private, 107125, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 16, United-States, >50K 51, Private, 145714, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 50, ?, >50K 27, Private, 133937, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 41, State-gov, 293485, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 3103, 0, 40, United-States, >50K 28, ?, 203260, Bachelors, 13, Never-married, ?, Not-in-family, White, Male, 0, 0, 8, United-States, <=50K 37, Self-emp-not-inc, 143368, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 18, Private, 51789, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 8, United-States, <=50K 24, State-gov, 211049, 7th-8th, 4, Never-married, Tech-support, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 53, Private, 81794, 12th, 8, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 139193, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 1980, 48, United-States, <=50K 54, Private, 150999, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 22, Private, 332657, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 240043, 10th, 6, Married-spouse-absent, Adm-clerical, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 43, Private, 186188, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 45, Iran, <=50K 58, State-gov, 223400, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 20, United-States, >50K 59, Local-gov, 102442, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 45, United-States, >50K 31, Private, 236599, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 35, Private, 283237, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 150106, 10th, 6, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 45, Private, 102076, Some-college, 10, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 40, Private, 374764, Some-college, 10, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 32528, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 45, United-States, <=50K 25, Federal-gov, 50053, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 58, Private, 212864, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 30673, Some-college, 10, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 69, ?, 248248, 1st-4th, 2, Married-civ-spouse, ?, Husband, Asian-Pac-Islander, Male, 0, 0, 34, Philippines, <=50K 23, Private, 419554, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 54, United-States, <=50K 32, State-gov, 177216, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 48, Private, 118158, Assoc-acdm, 12, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 44, United-States, <=50K 41, Private, 116391, Bachelors, 13, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Germany, <=50K 74, Private, 194312, 9th, 5, Widowed, Craft-repair, Not-in-family, White, Male, 0, 0, 10, ?, <=50K 43, Private, 111895, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 18, Private, 193290, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 1721, 20, United-States, <=50K 24, Federal-gov, 287988, Bachelors, 13, Never-married, Armed-Forces, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 58, Private, 147653, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 32, United-States, <=50K 54, Private, 117674, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 60, Private, 187458, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 410351, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 207578, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 62, ?, 55621, Some-college, 10, Married-civ-spouse, ?, Husband, Black, Male, 0, 0, 35, United-States, >50K 27, State-gov, 271243, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Male, 0, 0, 40, Jamaica, <=50K 30, Private, 188798, Some-college, 10, Divorced, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 63, Local-gov, 168656, Bachelors, 13, Divorced, Craft-repair, Not-in-family, Black, Male, 0, 0, 35, Outlying-US(Guam-USVI-etc), <=50K 33, Private, 460408, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 3325, 0, 50, United-States, <=50K 34, Private, 241885, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 20, ?, 133061, 9th, 5, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 194097, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 219137, 10th, 6, Never-married, Other-service, Own-child, Black, Male, 0, 0, 25, United-States, <=50K 50, Private, 31621, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 43, Private, 207685, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 57052, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 2885, 0, 40, United-States, <=50K 19, Private, 109854, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 20, ?, 369678, HS-grad, 9, Never-married, ?, Not-in-family, Other, Male, 0, 0, 43, United-States, <=50K 17, Private, 53611, 12th, 8, Never-married, Other-service, Own-child, White, Female, 0, 0, 6, United-States, <=50K 47, Private, 344916, Assoc-acdm, 12, Divorced, Transport-moving, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 25, Local-gov, 198813, Bachelors, 13, Never-married, Adm-clerical, Other-relative, Black, Female, 0, 0, 40, United-States, <=50K 71, Private, 180733, Masters, 14, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 21, Private, 188073, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 69, ?, 159077, 11th, 7, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 48, United-States, <=50K 48, Private, 174829, Assoc-acdm, 12, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 142791, 7th-8th, 4, Widowed, Sales, Other-relative, White, Female, 0, 1602, 3, United-States, <=50K 58, Self-emp-not-inc, 43221, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 2415, 40, United-States, >50K 34, Private, 188736, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Other-relative, Other, Female, 0, 0, 20, Columbia, <=50K 33, Local-gov, 222654, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 66, ?, <=50K 56, Private, 251836, 5th-6th, 3, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, ?, <=50K 40, Federal-gov, 112388, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 209641, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 32, United-States, <=50K 42, Private, 313945, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, Ecuador, <=50K 19, ?, 134974, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 20, United-States, <=50K 41, Private, 152742, Assoc-voc, 11, Divorced, Tech-support, Not-in-family, White, Female, 3325, 0, 40, United-States, <=50K 28, Self-emp-inc, 153291, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 35, United-States, <=50K 40, Private, 353432, 10th, 6, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 23, Private, 96635, Some-college, 10, Never-married, Machine-op-inspct, Own-child, Asian-Pac-Islander, Male, 0, 0, 30, United-States, <=50K 46, ?, 202560, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 40, United-States, >50K 39, Private, 150057, Masters, 14, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 39, Private, 114844, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 1876, 50, United-States, <=50K 45, Private, 132847, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, ?, 41356, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 35, United-States, <=50K 50, Self-emp-not-inc, 93705, Some-college, 10, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 309350, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 123084, 11th, 7, Married-civ-spouse, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 55, Private, 174662, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 32, United-States, <=50K 62, Federal-gov, 177295, HS-grad, 9, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 211880, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Self-emp-not-inc, 454915, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 232475, HS-grad, 9, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 57, Self-emp-inc, 244605, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 50, Private, 150876, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 1887, 55, United-States, >50K 51, Private, 257337, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 47, Private, 329144, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 4386, 0, 45, United-States, >50K 37, Private, 116960, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 58, Private, 267663, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, Mexico, <=50K 39, Private, 47871, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 50, United-States, >50K 34, Private, 295922, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, England, >50K 45, Private, 175625, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 19, ?, 129586, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 190179, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 40, United-States, >50K 40, Private, 168071, Assoc-voc, 11, Divorced, Tech-support, Not-in-family, White, Male, 3325, 0, 40, United-States, <=50K 39, Self-emp-not-inc, 202027, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 50, United-States, >50K 36, Private, 202662, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 56, Private, 101436, HS-grad, 9, Divorced, Adm-clerical, Other-relative, Amer-Indian-Eskimo, Female, 0, 0, 35, United-States, <=50K 19, ?, 119234, Some-college, 10, Never-married, ?, Other-relative, White, Female, 0, 0, 15, United-States, <=50K 37, Private, 360743, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, United-States, >50K 60, Local-gov, 93272, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, Private, 145574, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 51, Private, 101722, 7th-8th, 4, Married-civ-spouse, Exec-managerial, Husband, Amer-Indian-Eskimo, Male, 3908, 0, 47, United-States, <=50K 34, Private, 135785, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 36, United-States, <=50K 23, ?, 218415, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 10, United-States, <=50K 19, Private, 127709, HS-grad, 9, Never-married, Farming-fishing, Own-child, Black, Male, 0, 0, 30, United-States, <=50K 37, Federal-gov, 448337, HS-grad, 9, Never-married, Exec-managerial, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 58, Private, 310320, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Private, 251521, 11th, 7, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 39, Private, 255503, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 36, Private, 116608, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 4865, 0, 40, United-States, <=50K 26, Private, 71009, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 22, Private, 174975, Assoc-voc, 11, Never-married, Tech-support, Own-child, White, Female, 0, 0, 36, United-States, <=50K 32, Private, 108023, Masters, 14, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 204018, 11th, 7, Never-married, Sales, Unmarried, White, Male, 0, 0, 15, United-States, <=50K 57, ?, 366563, Some-college, 10, Divorced, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 68, Private, 121846, 7th-8th, 4, Widowed, Other-service, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 20, United-States, <=50K 70, Private, 278139, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 3432, 0, 40, United-States, <=50K 30, Private, 114691, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 19, State-gov, 536725, Some-college, 10, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 15, Japan, <=50K 51, Private, 94432, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 286002, Some-college, 10, Never-married, Adm-clerical, Other-relative, White, Male, 0, 0, 30, Nicaragua, <=50K 47, Private, 101684, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 352834, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 55, United-States, >50K 36, Private, 99146, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 1887, 40, United-States, >50K 30, Private, 231413, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 158846, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, <=50K 41, Local-gov, 190786, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 25, Private, 306513, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, <=50K 62, Private, 152148, 9th, 5, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 309580, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 26, ?, 130832, Bachelors, 13, Never-married, ?, Unmarried, White, Female, 0, 0, 10, United-States, <=50K 25, Private, 194897, HS-grad, 9, Never-married, Sales, Own-child, Amer-Indian-Eskimo, Male, 6849, 0, 40, United-States, <=50K 30, Private, 130078, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 48, Private, 39986, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 379198, HS-grad, 9, Never-married, Other-service, Other-relative, Other, Male, 0, 0, 40, Mexico, <=50K 51, Private, 189762, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 15, United-States, >50K 19, Private, 178147, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 10, United-States, <=50K 31, Private, 332379, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 175759, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 50, United-States, >50K 21, ?, 262062, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 275446, HS-grad, 9, Never-married, Sales, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 30, Self-emp-not-inc, 278522, 11th, 7, Never-married, Farming-fishing, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 28, Self-emp-not-inc, 54683, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 1590, 40, United-States, <=50K 57, Private, 136107, 9th, 5, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, >50K 18, Private, 205894, 11th, 7, Never-married, Sales, Own-child, White, Male, 0, 0, 15, United-States, <=50K 54, Private, 210736, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Private, 166634, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 52, Private, 185283, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 180553, HS-grad, 9, Separated, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 199058, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 48, ?, <=50K 18, Private, 145005, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 37, Self-emp-not-inc, 184655, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 52, Private, 358554, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, >50K 59, Private, 307423, 9th, 5, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 50, United-States, <=50K 27, Private, 472070, Assoc-voc, 11, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 43, Federal-gov, 115562, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, Private, 32446, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 44, Self-emp-not-inc, 33121, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 72, United-States, <=50K 37, Private, 183345, Assoc-voc, 11, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 28, Private, 119793, Assoc-voc, 11, Divorced, Exec-managerial, Not-in-family, White, Male, 10520, 0, 50, United-States, >50K 48, Self-emp-not-inc, 97883, HS-grad, 9, Separated, Other-service, Other-relative, White, Female, 0, 0, 25, United-States, <=50K 58, Self-emp-not-inc, 31732, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 29, Private, 206250, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 37, Private, 103323, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Self-emp-inc, 135436, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 36, Private, 376455, Assoc-voc, 11, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 52, Private, 160703, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 48, United-States, <=50K 30, Private, 131699, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 243842, 9th, 5, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 55, Self-emp-not-inc, 349910, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 61, Private, 170262, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 15024, 0, 38, United-States, >50K 33, Private, 184306, HS-grad, 9, Divorced, Handlers-cleaners, Unmarried, White, Male, 0, 0, 30, United-States, <=50K 46, Private, 224202, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 64, Private, 151540, 11th, 7, Widowed, Tech-support, Unmarried, White, Female, 0, 0, 16, United-States, <=50K 28, Private, 231197, 10th, 6, Married-spouse-absent, Craft-repair, Unmarried, White, Male, 0, 0, 40, Mexico, <=50K 19, Private, 279968, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 42, United-States, <=50K 36, Private, 162651, HS-grad, 9, Separated, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, Columbia, <=50K 43, Self-emp-not-inc, 130126, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Self-emp-not-inc, 160120, Doctorate, 16, Divorced, Adm-clerical, Other-relative, Other, Male, 0, 0, 40, ?, <=50K 56, Private, 161662, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 42, United-States, >50K 24, Local-gov, 201664, Some-college, 10, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 137142, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 45, Self-emp-inc, 122206, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 56, Local-gov, 183169, Masters, 14, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 126513, HS-grad, 9, Separated, Craft-repair, Unmarried, Black, Female, 0, 0, 40, ?, <=50K 35, Federal-gov, 185053, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 36, Self-emp-not-inc, 408427, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 50, Self-emp-not-inc, 198581, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 61, Private, 199198, 7th-8th, 4, Widowed, Other-service, Not-in-family, Black, Female, 0, 0, 21, United-States, <=50K 31, Private, 184306, Assoc-voc, 11, Never-married, Transport-moving, Own-child, White, Male, 0, 1980, 60, United-States, <=50K 63, Private, 172740, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 205153, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 164964, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 162606, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 24, Private, 179627, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 103408, Some-college, 10, Divorced, Prof-specialty, Not-in-family, Black, Male, 0, 0, 40, Germany, >50K 27, Private, 36440, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 57512, Assoc-voc, 11, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 48, United-States, <=50K 27, Private, 187981, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 393768, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 108726, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 180551, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 51, Self-emp-not-inc, 176240, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 56, Private, 70720, 12th, 8, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 35890, Assoc-acdm, 12, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 283676, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 34, Local-gov, 105540, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 2051, 40, United-States, <=50K 44, Private, 408717, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 3674, 0, 50, United-States, <=50K 21, Private, 57916, HS-grad, 9, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 177974, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 70, United-States, <=50K 34, ?, 177304, 10th, 6, Divorced, ?, Not-in-family, White, Male, 0, 0, 40, Columbia, <=50K 18, Private, 115839, 12th, 8, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 34, ?, 205256, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 2885, 0, 80, United-States, <=50K 38, Private, 117802, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 65, United-States, >50K 19, Private, 211355, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 12, United-States, <=50K 46, Private, 173243, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 343200, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 25, United-States, <=50K 22, Private, 401690, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 20, Mexico, <=50K 38, Private, 196123, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 33, Private, 168981, Masters, 14, Divorced, Exec-managerial, Own-child, White, Female, 14084, 0, 50, United-States, >50K 83, Self-emp-not-inc, 213866, HS-grad, 9, Widowed, Exec-managerial, Not-in-family, White, Male, 0, 0, 8, United-States, <=50K 34, Private, 55176, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 153976, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 119176, Some-college, 10, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 169117, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 1887, 40, United-States, >50K 38, Private, 156550, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 25, Private, 109609, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 38, Private, 26698, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 236497, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 48, United-States, >50K 33, State-gov, 306309, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 17, Private, 242773, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 28, Private, 124680, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 6849, 0, 60, United-States, <=50K 52, Local-gov, 43909, HS-grad, 9, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 34, Private, 112820, HS-grad, 9, Separated, Handlers-cleaners, Not-in-family, White, Male, 2463, 0, 40, United-States, <=50K 25, Private, 148300, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 15, United-States, <=50K 17, Private, 133449, 9th, 5, Never-married, Other-service, Own-child, Black, Male, 0, 0, 26, United-States, <=50K 22, Private, 263670, HS-grad, 9, Never-married, Other-service, Own-child, Black, Male, 0, 0, 80, United-States, <=50K 22, Private, 276494, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 46, Private, 190115, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 1887, 40, United-States, >50K 58, Private, 317479, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 39, Private, 151248, Some-college, 10, Divorced, Sales, Other-relative, White, Female, 0, 0, 35, United-States, <=50K 59, Local-gov, 130532, Some-college, 10, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 40, Poland, <=50K 61, Private, 160062, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 299635, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 50, Private, 171225, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, >50K 51, Private, 33304, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 95634, Bachelors, 13, Married-civ-spouse, Other-service, Wife, Asian-Pac-Islander, Female, 0, 0, 45, ?, <=50K 20, Private, 243878, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 38, Local-gov, 181721, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, United-States, <=50K 44, Federal-gov, 201435, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, >50K 28, Private, 334032, Assoc-voc, 11, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 50, Private, 220019, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, <=50K 53, Private, 71772, Doctorate, 16, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 42, Self-emp-not-inc, 27661, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 47, Private, 191411, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 45, India, <=50K 39, Private, 123945, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 38, Self-emp-not-inc, 37778, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 34, State-gov, 171216, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 50, United-States, <=50K 40, Private, 93955, Some-college, 10, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, <=50K 63, Private, 163809, Some-college, 10, Widowed, Sales, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 53, Private, 346754, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 43, Private, 188436, Assoc-voc, 11, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 28, Private, 72443, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 1669, 60, United-States, <=50K 68, Private, 186350, HS-grad, 9, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 10, United-States, >50K 22, ?, 214238, 7th-8th, 4, Never-married, ?, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 46, State-gov, 394860, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 38, United-States, <=50K 57, Private, 262642, HS-grad, 9, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 125550, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 66, Private, 192504, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 131310, Assoc-acdm, 12, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 54, Private, 249322, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 50, United-States, >50K 38, Private, 172755, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 209993, 11th, 7, Separated, Priv-house-serv, Unmarried, White, Female, 0, 0, 8, Mexico, <=50K 30, Private, 166961, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 37, United-States, <=50K 39, Private, 315291, HS-grad, 9, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 31, Private, 284703, Masters, 14, Never-married, Prof-specialty, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 50, Private, 166565, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, <=50K 30, Self-emp-not-inc, 173854, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 25, Private, 189219, Bachelors, 13, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 210781, Bachelors, 13, Never-married, Priv-house-serv, Not-in-family, White, Female, 0, 0, 40, France, <=50K 59, Local-gov, 171328, HS-grad, 9, Separated, Protective-serv, Other-relative, Black, Female, 0, 2339, 40, United-States, <=50K 45, Private, 199832, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 15, United-States, <=50K 64, Private, 251292, 5th-6th, 3, Separated, Other-service, Other-relative, White, Female, 0, 0, 20, Cuba, <=50K 61, Private, 122246, 12th, 8, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 190767, Assoc-voc, 11, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 278736, 5th-6th, 3, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 53, Private, 124963, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, Self-emp-not-inc, 167476, 11th, 7, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 7, United-States, <=50K 34, Local-gov, 246104, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 40, United-States, <=50K 41, Private, 171615, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 48, United-States, <=50K 67, Private, 264095, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 9386, 0, 24, Cuba, >50K 46, Private, 177114, Assoc-acdm, 12, Widowed, Prof-specialty, Unmarried, White, Female, 0, 0, 27, United-States, <=50K 32, Private, 146154, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 198196, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 79712, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Other, Male, 0, 0, 40, United-States, <=50K 54, Self-emp-not-inc, 154785, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 33, Private, 182423, HS-grad, 9, Divorced, Other-service, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 20, ?, 347292, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 0, 32, United-States, <=50K 34, Private, 118584, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 219835, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 30, ?, <=50K 17, ?, 148769, HS-grad, 9, Never-married, ?, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 45, Private, 197418, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 21, Private, 253190, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 192273, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 129573, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 41, United-States, <=50K 17, Private, 173807, 11th, 7, Never-married, Craft-repair, Own-child, White, Female, 0, 0, 15, United-States, <=50K 35, Private, 217893, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 38, Private, 102938, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Local-gov, 407495, Assoc-acdm, 12, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 56, United-States, >50K 25, Private, 50053, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 40, Japan, <=50K 57, Private, 233382, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, Cuba, <=50K 32, Private, 270968, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 39, Local-gov, 272166, Bachelors, 13, Separated, Prof-specialty, Not-in-family, Black, Male, 0, 0, 30, United-States, <=50K 23, Private, 199915, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 35, United-States, <=50K 21, Private, 305781, HS-grad, 9, Never-married, Handlers-cleaners, Unmarried, White, Male, 0, 0, 45, United-States, <=50K 47, Private, 107682, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 48, United-States, <=50K 25, Private, 188507, 7th-8th, 4, Never-married, Machine-op-inspct, Other-relative, White, Female, 0, 0, 40, Dominican-Republic, <=50K 18, ?, 28311, 11th, 7, Never-married, ?, Own-child, White, Female, 0, 0, 35, United-States, <=50K 41, Federal-gov, 197069, Some-college, 10, Married-spouse-absent, Adm-clerical, Not-in-family, Black, Male, 4650, 0, 40, United-States, <=50K 19, Private, 177839, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 24, Private, 77665, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 42, United-States, <=50K 57, Private, 127728, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 51, ?, 172175, Doctorate, 16, Never-married, ?, Not-in-family, White, Male, 0, 2824, 40, United-States, >50K 32, Private, 106742, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Self-emp-not-inc, 192838, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 40, Private, 79531, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 75, United-States, >50K 21, State-gov, 337766, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 20, United-States, <=50K 45, Self-emp-not-inc, 33234, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 17, ?, 34088, 12th, 8, Never-married, ?, Own-child, White, Female, 0, 0, 25, United-States, <=50K 55, Private, 176904, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 42, Private, 172148, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, <=50K 49, Private, 199058, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 38, United-States, <=50K 38, Private, 48093, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 143664, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 168337, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, >50K 43, Private, 195212, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, Black, Female, 0, 0, 40, ?, <=50K 39, Private, 230329, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, Canada, >50K 42, Private, 376072, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 30, United-States, <=50K 32, Private, 430175, HS-grad, 9, Divorced, Craft-repair, Other-relative, Black, Female, 0, 0, 50, United-States, <=50K 44, Federal-gov, 240628, Assoc-acdm, 12, Divorced, Exec-managerial, Not-in-family, White, Female, 2354, 0, 40, United-States, <=50K 50, Self-emp-inc, 158294, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 80, United-States, >50K 55, Private, 28735, HS-grad, 9, Divorced, Adm-clerical, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 45, United-States, <=50K 37, Private, 167482, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 59, Private, 113203, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 56, Private, 103948, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Self-emp-not-inc, 310525, 12th, 8, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 32, United-States, <=50K 35, Private, 105138, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 44, Private, 153489, HS-grad, 9, Never-married, Other-service, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 57, State-gov, 254949, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 118149, Some-college, 10, Never-married, Exec-managerial, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 18, Private, 267965, 11th, 7, Never-married, Sales, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 43, Private, 50646, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 70, United-States, <=50K 33, Private, 147700, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Other, Male, 0, 0, 40, United-States, <=50K 18, Private, 446771, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 25, United-States, <=50K 47, Private, 168262, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 117058, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 59, Self-emp-not-inc, 140957, Assoc-voc, 11, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 35, United-States, >50K 35, Private, 186126, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 38, ?, <=50K 49, Private, 268234, 10th, 6, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 485117, Assoc-acdm, 12, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 31350, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 60, England, <=50K 36, State-gov, 210830, Masters, 14, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 30, United-States, <=50K 29, Private, 196420, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 52, Private, 172165, 10th, 6, Divorced, Other-service, Other-relative, White, Female, 0, 0, 25, United-States, <=50K 50, Self-emp-not-inc, 186565, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 22, Private, 119359, Bachelors, 13, Never-married, Exec-managerial, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 44, Self-emp-not-inc, 109684, Masters, 14, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 169589, Assoc-voc, 11, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, >50K 49, Private, 125421, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 31, Private, 500002, 1st-4th, 2, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 45, Mexico, <=50K 33, Private, 224141, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 113290, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 15, United-States, <=50K 62, ?, 123992, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 58098, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 1974, 40, United-States, <=50K 46, ?, 37672, HS-grad, 9, Divorced, ?, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 55, Private, 198145, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7298, 0, 40, United-States, >50K 49, Federal-gov, 35406, HS-grad, 9, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 22, Private, 199419, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 145441, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 38, United-States, >50K 58, Private, 238438, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 42, United-States, <=50K 48, State-gov, 212954, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 40, United-States, >50K 21, Private, 56582, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 50, United-States, <=50K 67, Local-gov, 176931, 7th-8th, 4, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 39, Self-emp-not-inc, 188571, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Federal-gov, 312500, Assoc-voc, 11, Divorced, Farming-fishing, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 278404, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Self-emp-not-inc, 114225, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 18, Private, 184016, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 41, Local-gov, 183009, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, >50K 59, Private, 205759, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 23, Private, 462294, Assoc-acdm, 12, Never-married, Other-service, Own-child, Black, Male, 0, 0, 44, United-States, <=50K 42, Private, 102085, HS-grad, 9, Divorced, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 54, Self-emp-not-inc, 83311, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 30, United-States, >50K 39, Private, 248694, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 57, Local-gov, 190747, 9th, 5, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 162988, 10th, 6, Divorced, Other-service, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 31, Self-emp-not-inc, 156890, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 310380, Some-college, 10, Married-spouse-absent, Adm-clerical, Own-child, Black, Female, 0, 0, 45, United-States, <=50K 35, Private, 172186, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 311497, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Self-emp-inc, 443508, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 31, Private, 152156, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 46, Private, 155890, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 38, State-gov, 312528, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 37, United-States, <=50K 51, Private, 282744, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, Canada, <=50K 27, Private, 205145, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, ?, 119918, Bachelors, 13, Never-married, ?, Not-in-family, Black, Male, 0, 0, 45, ?, <=50K 22, Private, 401451, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 48, United-States, >50K 72, ?, 173427, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, Cuba, <=50K 25, Private, 189027, Bachelors, 13, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 58, Self-emp-not-inc, 35551, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 70, United-States, >50K 23, Private, 42706, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 63, Private, 106910, 5th-6th, 3, Widowed, Other-service, Other-relative, Asian-Pac-Islander, Female, 0, 0, 19, Philippines, <=50K 23, Private, 53245, 9th, 5, Separated, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 221672, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 50, United-States, >50K 75, Private, 71898, Preschool, 1, Never-married, Priv-house-serv, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 48, Philippines, <=50K 52, Private, 222107, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 69, Private, 277588, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 10, United-States, <=50K 52, Private, 178983, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, ?, >50K 40, Federal-gov, 391744, HS-grad, 9, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 34, Private, 418020, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 21, State-gov, 39236, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 8, United-States, <=50K 30, Private, 86808, Bachelors, 13, Never-married, Prof-specialty, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 147640, 5th-6th, 3, Married-civ-spouse, Transport-moving, Husband, Amer-Indian-Eskimo, Male, 0, 1902, 40, United-States, <=50K 21, Private, 184756, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 16, United-States, <=50K 44, Private, 191256, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, State-gov, 105943, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 3908, 0, 40, United-States, <=50K 40, Private, 101272, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 33, State-gov, 175023, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 37, United-States, <=50K 22, Self-emp-not-inc, 357612, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 23, Private, 82777, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 30, United-States, <=50K 75, Self-emp-not-inc, 218521, Some-college, 10, Married-spouse-absent, Craft-repair, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 55, Private, 179534, 11th, 7, Widowed, Handlers-cleaners, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 24, ?, 33339, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 20, United-States, <=50K 45, Private, 148549, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 27828, 0, 56, United-States, >50K 31, Private, 198069, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 24, United-States, <=50K 49, Private, 236586, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Local-gov, 167261, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 61, Private, 160942, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 3103, 0, 50, United-States, <=50K 44, Private, 107584, Masters, 14, Married-civ-spouse, Adm-clerical, Husband, White, Male, 3908, 0, 50, United-States, <=50K 28, Local-gov, 251854, Some-college, 10, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 79, ?, 163140, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, >50K 51, Private, 302579, HS-grad, 9, Divorced, Other-service, Other-relative, Black, Female, 0, 0, 30, United-States, <=50K 44, Self-emp-inc, 64632, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 24, Private, 83141, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 46, Self-emp-inc, 326048, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 83471, HS-grad, 9, Widowed, Other-service, Unmarried, Asian-Pac-Islander, Female, 0, 0, 20, United-States, <=50K 23, Private, 170070, 12th, 8, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 25, Private, 207875, 7th-8th, 4, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Mexico, <=50K 48, Private, 119722, Some-college, 10, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 8, United-States, <=50K 18, Private, 335665, 11th, 7, Never-married, Other-service, Other-relative, Black, Female, 0, 0, 24, United-States, <=50K 25, Private, 212522, HS-grad, 9, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 42069, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 2176, 0, 45, United-States, <=50K 26, ?, 131777, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 2002, 40, United-States, <=50K 33, Private, 236396, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 35, United-States, <=50K 42, Private, 159911, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 133833, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 226947, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Private, 174201, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 34, Self-emp-not-inc, 49707, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 70, United-States, <=50K 33, Private, 201988, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, <=50K 62, Self-emp-not-inc, 162347, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 15, United-States, >50K 30, Private, 182833, Some-college, 10, Never-married, Exec-managerial, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 22, Private, 383603, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 70466, Assoc-voc, 11, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 184846, HS-grad, 9, Widowed, Machine-op-inspct, Unmarried, White, Female, 0, 0, 60, United-States, <=50K 25, Private, 176756, Bachelors, 13, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 112512, HS-grad, 9, Widowed, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 137296, Assoc-acdm, 12, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 28, Private, 37821, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 25, Private, 295108, HS-grad, 9, Never-married, Handlers-cleaners, Unmarried, Black, Female, 0, 0, 25, United-States, <=50K 40, Private, 408717, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 255635, 9th, 5, Married-civ-spouse, Craft-repair, Husband, Other, Male, 0, 0, 40, Mexico, <=50K 48, Self-emp-not-inc, 177783, 7th-8th, 4, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 63, Self-emp-not-inc, 179400, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 2290, 0, 20, United-States, <=50K 31, Private, 240283, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 36, Private, 410034, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 39, Private, 180667, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 196332, HS-grad, 9, Never-married, Other-service, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 32, Local-gov, 159187, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 46, Private, 225065, Preschool, 1, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, Mexico, <=50K 19, Private, 178147, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 35, United-States, <=50K 30, Private, 272669, Some-college, 10, Never-married, Tech-support, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 35, Private, 347491, Assoc-voc, 11, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, ?, 146399, Bachelors, 13, Never-married, ?, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 33, Private, 75167, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 55, United-States, <=50K 25, Private, 133373, HS-grad, 9, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 64, Local-gov, 84737, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 35, United-States, >50K 18, Private, 96483, HS-grad, 9, Never-married, Other-service, Own-child, Asian-Pac-Islander, Female, 0, 0, 20, United-States, <=50K 59, Private, 368005, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, State-gov, 36032, HS-grad, 9, Divorced, Protective-serv, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 30, Private, 174215, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 24, Private, 228772, 5th-6th, 3, Never-married, Machine-op-inspct, Other-relative, White, Female, 0, 0, 40, Mexico, <=50K 22, Private, 242912, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 49, Self-emp-inc, 86701, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 56, United-States, >50K 35, Private, 166549, 12th, 8, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Local-gov, 121622, Masters, 14, Never-married, Prof-specialty, Unmarried, White, Female, 0, 1380, 40, United-States, <=50K 18, Private, 201613, 12th, 8, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 35, Private, 29874, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 168138, HS-grad, 9, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 162404, Bachelors, 13, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 60, United-States, <=50K 21, ?, 162160, Some-college, 10, Never-married, ?, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, Taiwan, <=50K 26, Private, 139116, Some-college, 10, Never-married, Other-service, Own-child, Black, Female, 0, 0, 50, United-States, <=50K 44, Private, 192381, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1848, 40, United-States, >50K 39, Private, 370585, HS-grad, 9, Separated, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 40, State-gov, 151038, Bachelors, 13, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 70, Self-emp-not-inc, 36311, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 20051, 0, 35, United-States, >50K 34, Private, 271933, Masters, 14, Never-married, Exec-managerial, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 34, Private, 182401, Assoc-acdm, 12, Divorced, Adm-clerical, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 66, Private, 234743, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 40, Private, 182140, HS-grad, 9, Separated, Transport-moving, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 61, Self-emp-not-inc, 215591, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1887, 40, United-States, >50K 59, Self-emp-not-inc, 96459, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, ?, 205562, Masters, 14, Never-married, ?, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 47, Private, 188081, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 33, State-gov, 121245, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 18, Private, 127273, 11th, 7, Never-married, Other-service, Other-relative, White, Male, 0, 0, 20, United-States, <=50K 25, Private, 114345, 9th, 5, Never-married, Craft-repair, Unmarried, White, Male, 914, 0, 40, United-States, <=50K 22, Private, 341227, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 40, Local-gov, 166893, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 40, United-States, >50K 68, ?, 65730, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 25, United-States, <=50K 30, Private, 145231, Assoc-acdm, 12, Divorced, Adm-clerical, Own-child, White, Female, 0, 1762, 40, United-States, <=50K 73, Self-emp-not-inc, 102510, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 6418, 0, 99, United-States, >50K 45, Self-emp-not-inc, 285335, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 10, United-States, <=50K 23, Private, 177087, 11th, 7, Never-married, Adm-clerical, Unmarried, Black, Male, 0, 0, 35, United-States, <=50K 40, Private, 240504, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 39, Private, 218490, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 40, United-States, >50K 23, Private, 384651, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 189551, HS-grad, 9, Divorced, Craft-repair, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 53, Private, 194791, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 45, United-States, <=50K 24, Private, 194630, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 53, Private, 177647, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 49, Self-emp-not-inc, 51620, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 34, Private, 251421, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Self-emp-not-inc, 180477, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 47, United-States, <=50K 40, State-gov, 391736, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, State-gov, 170091, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 6, United-States, <=50K 36, Private, 175360, Masters, 14, Never-married, Adm-clerical, Not-in-family, White, Male, 13550, 0, 50, United-States, >50K 35, Private, 276153, Bachelors, 13, Never-married, Tech-support, Not-in-family, Asian-Pac-Islander, Female, 4650, 0, 40, United-States, <=50K 53, Federal-gov, 105788, Bachelors, 13, Divorced, Exec-managerial, Unmarried, Black, Female, 0, 0, 50, United-States, >50K 42, Local-gov, 248476, Some-college, 10, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 65, United-States, >50K 32, Private, 168443, Masters, 14, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 120201, HS-grad, 9, Divorced, Adm-clerical, Own-child, Other, Female, 0, 0, 65, United-States, <=50K 59, Private, 114678, HS-grad, 9, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 60, United-States, <=50K 36, Private, 167440, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 44, United-States, <=50K 37, Self-emp-not-inc, 265266, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, Cuba, >50K 31, Private, 212235, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 46, Private, 44671, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, State-gov, 87282, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 38, United-States, <=50K 27, Private, 112754, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1485, 60, United-States, >50K 29, Self-emp-not-inc, 322238, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 65382, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 62, Self-emp-not-inc, 115176, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 65, United-States, <=50K 48, Self-emp-not-inc, 162236, Masters, 14, Widowed, Exec-managerial, Unmarried, White, Female, 0, 0, 40, ?, >50K 42, Private, 409902, HS-grad, 9, Never-married, Exec-managerial, Unmarried, Black, Female, 0, 0, 25, United-States, <=50K 60, Local-gov, 204062, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 48, United-States, >50K 35, Private, 283305, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 435638, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, Self-emp-inc, 114733, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 36, United-States, <=50K 22, Private, 162343, Some-college, 10, Never-married, Adm-clerical, Other-relative, Black, Male, 0, 0, 22, United-States, <=50K 18, ?, 195981, HS-grad, 9, Widowed, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 79531, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 44, State-gov, 395078, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 49, Local-gov, 159641, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Female, 0, 625, 40, United-States, <=50K 21, Private, 159567, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 49, Private, 133917, Assoc-voc, 11, Never-married, Sales, Other-relative, Black, Male, 0, 0, 40, ?, <=50K 52, Private, 196894, 11th, 7, Separated, Handlers-cleaners, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 39, Local-gov, 132879, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1887, 40, United-States, >50K 23, Private, 190290, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 102828, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 49, United-States, <=50K 31, Private, 128493, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 30, State-gov, 290677, Masters, 14, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 20, United-States, <=50K 21, Private, 283757, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 38, Local-gov, 169104, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, >50K 51, Private, 171409, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 34, Self-emp-not-inc, 319165, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 22, Private, 203182, Bachelors, 13, Never-married, Exec-managerial, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 20, ?, 211968, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 45, United-States, <=50K 26, Private, 215384, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 1974, 55, United-States, <=50K 26, Private, 166666, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 41, Private, 156566, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 140564, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Local-gov, 322208, Some-college, 10, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 65, Private, 420277, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 123430, 11th, 7, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 65, Mexico, <=50K 45, Self-emp-inc, 151584, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, >50K 37, Self-emp-not-inc, 348960, Assoc-acdm, 12, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 47, Private, 168232, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1887, 45, United-States, >50K 47, Self-emp-inc, 201699, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 33, Private, 511517, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 118001, 10th, 6, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 38, Private, 193961, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, >50K 21, Private, 32732, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 223548, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, Mexico, <=50K 33, Private, 389932, HS-grad, 9, Divorced, Transport-moving, Not-in-family, Black, Male, 0, 0, 55, United-States, <=50K 29, Private, 102345, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 52, United-States, <=50K 41, Private, 107584, Some-college, 10, Separated, Transport-moving, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 20, ?, 34321, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 30, United-States, <=50K 20, State-gov, 39478, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 54, United-States, <=50K 34, Self-emp-not-inc, 276221, 10th, 6, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 78, Self-emp-inc, 385242, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 9386, 0, 45, United-States, >50K 46, Private, 235646, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Private, 123306, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 59, Private, 38573, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Private, 216889, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 386705, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 24, United-States, <=50K 47, Self-emp-not-inc, 249585, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 30, United-States, <=50K 31, Local-gov, 47276, Bachelors, 13, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 38, United-States, >50K 42, Self-emp-not-inc, 162758, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 56, United-States, >50K 46, Local-gov, 146497, HS-grad, 9, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 190765, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 44, United-States, <=50K 21, Private, 186314, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 213615, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 162322, Assoc-voc, 11, Never-married, Tech-support, Own-child, White, Female, 0, 0, 40, United-States, <=50K 44, State-gov, 115932, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, Self-emp-not-inc, 392694, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 38, State-gov, 143517, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 50, Self-emp-inc, 123429, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, Italy, >50K 53, Private, 254285, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Private, 238311, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 36, United-States, >50K 49, Private, 281647, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 30, Private, 75167, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 19, Private, 252862, Assoc-voc, 11, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 59, Self-emp-not-inc, 199240, HS-grad, 9, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 20, England, <=50K 43, Private, 145762, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Local-gov, 142443, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 49, Private, 99361, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, <=50K 36, Private, 105138, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 26, Private, 183171, 11th, 7, Never-married, Other-service, Own-child, Black, Male, 1055, 0, 32, United-States, <=50K 18, Private, 151866, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 60, Private, 297261, Some-college, 10, Widowed, Sales, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 43, Private, 148998, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 143046, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 183850, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 55, Self-emp-not-inc, 248841, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 40, United-States, >50K 31, Private, 198452, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 161092, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 112497, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 51, Self-emp-not-inc, 155963, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, <=50K 28, Private, 147560, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 1902, 55, United-States, >50K 24, Private, 376393, Assoc-voc, 11, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, State-gov, 151790, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 30, United-States, <=50K 21, Private, 438139, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 20, ?, 163911, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 214896, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 30, Private, 102821, Some-college, 10, Married-civ-spouse, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 44, Self-emp-not-inc, 90021, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 30, United-States, <=50K 45, Private, 77085, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Japan, >50K 42, Private, 158555, 10th, 6, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, ?, 28160, HS-grad, 9, Divorced, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 462255, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 144949, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 116207, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 32, United-States, <=50K 17, Private, 187308, 10th, 6, Never-married, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 45, Local-gov, 189890, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 185267, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 63434, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 45, Private, 1366120, Assoc-voc, 11, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 8, United-States, <=50K 41, Self-emp-inc, 495061, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 70, United-States, >50K 34, Local-gov, 134886, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 1740, 35, United-States, <=50K 33, Private, 129707, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 17, ?, 181337, 10th, 6, Never-married, ?, Own-child, Other, Female, 0, 0, 20, United-States, <=50K 51, Private, 74784, Bachelors, 13, Divorced, Sales, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 33, Private, 44392, HS-grad, 9, Divorced, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, United-States, <=50K 23, Private, 406641, Some-college, 10, Never-married, Handlers-cleaners, Other-relative, White, Female, 0, 0, 18, United-States, <=50K 52, Private, 89041, Bachelors, 13, Married-spouse-absent, Prof-specialty, Not-in-family, White, Male, 0, 0, 30, United-States, >50K 36, ?, 139770, Some-college, 10, Divorced, ?, Own-child, White, Female, 0, 0, 32, United-States, <=50K 25, Private, 180212, HS-grad, 9, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 38, ?, 338212, Some-college, 10, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 20, United-States, <=50K 64, Self-emp-not-inc, 178472, 9th, 5, Separated, Transport-moving, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 42, Private, 384236, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 40, United-States, >50K 29, Private, 168470, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 26, Local-gov, 80485, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 38, ?, 181705, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 24, United-States, <=50K 24, Private, 216867, 10th, 6, Never-married, Other-service, Other-relative, White, Male, 0, 0, 30, Mexico, <=50K 43, Federal-gov, 214541, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 383239, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 3103, 0, 40, United-States, >50K 28, Private, 70034, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 18, ?, 266287, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 25, United-States, <=50K 44, Private, 128485, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 81, ?, 89015, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 18, United-States, <=50K 55, Private, 106740, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 52, Private, 167527, 11th, 7, Widowed, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 31, Private, 19302, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 210150, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 179824, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 36, United-States, <=50K 27, Private, 420351, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 23, State-gov, 215443, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 15, United-States, <=50K 26, Private, 116044, 11th, 7, Separated, Craft-repair, Other-relative, White, Male, 2907, 0, 50, United-States, <=50K 33, Private, 215306, Assoc-voc, 11, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, Cuba, <=50K 39, Private, 108069, Some-college, 10, Never-married, Craft-repair, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 260046, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 31053, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 362302, 12th, 8, Never-married, Other-service, Own-child, White, Male, 0, 0, 15, United-States, <=50K 54, Private, 87205, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 45, Private, 191703, HS-grad, 9, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 43, Private, 242968, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 40, India, >50K 23, Local-gov, 185575, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 177858, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 2174, 0, 40, United-States, <=50K 33, Self-emp-not-inc, 73585, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 45, Private, 301802, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 32, Self-emp-inc, 108467, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 47, Private, 431245, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 157217, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 22, Private, 204935, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 277112, 11th, 7, Never-married, Sales, Own-child, White, Male, 0, 0, 30, United-States, <=50K 64, Self-emp-inc, 59145, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 60, United-States, >50K 30, Local-gov, 159773, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 45, United-States, >50K 51, Private, 118793, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 70, United-States, >50K 26, State-gov, 152457, HS-grad, 9, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 187901, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 1504, 40, United-States, <=50K 50, Private, 266529, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, ?, 256179, Some-college, 10, Never-married, ?, Own-child, White, Male, 594, 0, 10, United-States, <=50K 63, Private, 113756, HS-grad, 9, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 48, Private, 83444, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 43, United-States, >50K 37, Self-emp-inc, 30529, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 2415, 50, United-States, >50K 51, ?, 146325, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 28, United-States, <=50K 29, Private, 198825, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 69, Private, 71489, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 25, United-States, <=50K 56, Private, 111218, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 26, ?, 221626, Bachelors, 13, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 40, United-States, <=50K 39, Local-gov, 203482, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7298, 0, 40, United-States, >50K 42, Self-emp-not-inc, 352196, HS-grad, 9, Separated, Other-service, Not-in-family, White, Female, 0, 0, 22, United-States, <=50K 41, Federal-gov, 355918, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 45, Private, 168262, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 1887, 40, United-States, >50K 23, Private, 182615, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 211482, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 34, Private, 386370, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 31, ?, 85077, Bachelors, 13, Married-civ-spouse, ?, Wife, White, Female, 0, 1902, 20, United-States, >50K 46, Local-gov, 180010, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 46, Without-pay, 142210, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 25, United-States, <=50K 33, Private, 415706, 5th-6th, 3, Separated, Other-service, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 46, Private, 237731, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 343506, HS-grad, 9, Never-married, Other-service, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 49, Local-gov, 116163, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 50, France, <=50K 66, ?, 206560, HS-grad, 9, Widowed, ?, Not-in-family, Other, Female, 0, 0, 35, Puerto-Rico, <=50K 55, State-gov, 153451, HS-grad, 9, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 1887, 40, United-States, >50K 35, Private, 301862, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 33429, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 169583, HS-grad, 9, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 146497, Some-college, 10, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 16, Germany, <=50K 48, Self-emp-not-inc, 383384, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 240809, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 56, United-States, <=50K 38, Private, 203763, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 218785, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 23, ?, 381741, Assoc-acdm, 12, Never-married, ?, Own-child, White, Male, 0, 1721, 20, United-States, <=50K 17, Private, 244602, 12th, 8, Never-married, Other-service, Own-child, White, Male, 0, 0, 15, United-States, <=50K 44, State-gov, 175696, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 101027, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 48, United-States, <=50K 37, Private, 99270, HS-grad, 9, Never-married, Transport-moving, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 224393, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 42, Private, 192381, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 131686, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 73, ?, 84390, Assoc-voc, 11, Married-spouse-absent, ?, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 44, Private, 277533, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 72880, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, ?, 149646, Some-college, 10, Divorced, ?, Own-child, White, Female, 0, 0, 20, ?, <=50K 49, Private, 209057, Some-college, 10, Divorced, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 108909, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 42, Private, 74949, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 235639, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, State-gov, 137421, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, Asian-Pac-Islander, Male, 0, 0, 37, Hong, <=50K 53, Private, 122412, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 434894, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, United-States, <=50K 35, Private, 379959, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 95885, 11th, 7, Never-married, Craft-repair, Not-in-family, Amer-Indian-Eskimo, Male, 13550, 0, 60, United-States, >50K 39, Private, 225330, Bachelors, 13, Widowed, Prof-specialty, Unmarried, White, Female, 0, 0, 50, Poland, >50K 40, Private, 32627, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 28, Private, 65171, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 193380, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 184823, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 81259, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 43, United-States, <=50K 35, Private, 301369, 12th, 8, Never-married, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 21, Private, 190968, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 71, Private, 196610, 7th-8th, 4, Widowed, Exec-managerial, Not-in-family, White, Male, 6097, 0, 40, United-States, >50K 31, Private, 330715, HS-grad, 9, Separated, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Local-gov, 77698, Some-college, 10, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 35, Private, 139770, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 6849, 0, 40, United-States, <=50K 24, Private, 109053, HS-grad, 9, Never-married, Other-service, Other-relative, White, Male, 0, 0, 25, United-States, <=50K 69, Private, 312653, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 25, United-States, <=50K 35, Self-emp-not-inc, 193260, Masters, 14, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 0, 40, ?, >50K 35, Private, 331831, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 54202, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 10520, 0, 50, United-States, >50K 51, Private, 163948, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 48, Private, 36228, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 44, United-States, <=50K 49, Private, 160167, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 178356, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 2407, 0, 99, United-States, <=50K 43, Private, 104196, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 288353, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 187693, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 114988, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Local-gov, 117392, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 48, Private, 121124, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, >50K 53, Private, 195638, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 245053, Some-college, 10, Divorced, Handlers-cleaners, Own-child, White, Male, 0, 1504, 40, United-States, <=50K 49, State-gov, 216734, Prof-school, 15, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, ?, 197827, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 49156, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 126133, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 304463, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 65, United-States, <=50K 34, Private, 214288, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 274969, HS-grad, 9, Never-married, Craft-repair, Unmarried, White, Female, 0, 0, 42, United-States, <=50K 23, Private, 189072, Bachelors, 13, Never-married, Tech-support, Not-in-family, Black, Female, 0, 0, 45, United-States, <=50K 46, Private, 128047, Some-college, 10, Separated, Sales, Not-in-family, White, Male, 0, 0, 42, United-States, <=50K 20, Private, 210338, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 63, Private, 122442, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Self-emp-not-inc, 167081, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 3103, 0, 50, United-States, <=50K 33, Private, 251421, Assoc-acdm, 12, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 24, Federal-gov, 219519, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 36, Private, 33355, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 45, United-States, <=50K 25, Private, 441210, HS-grad, 9, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 54, Local-gov, 178356, 9th, 5, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Self-emp-not-inc, 231196, Bachelors, 13, Divorced, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 58, State-gov, 40925, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 270587, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, England, <=50K 40, Private, 219266, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 50, United-States, >50K 27, Private, 114967, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 344492, HS-grad, 9, Separated, Sales, Own-child, White, Female, 0, 0, 26, United-States, <=50K 22, Private, 369387, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 80, Self-emp-not-inc, 101771, 11th, 7, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 25, United-States, <=50K 52, Private, 137428, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 40, Federal-gov, 121012, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 7298, 0, 48, United-States, >50K 48, Private, 139290, 10th, 6, Separated, Machine-op-inspct, Own-child, White, Female, 0, 0, 48, United-States, <=50K 62, Private, 199193, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 25, United-States, <=50K 32, Private, 286689, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 42, United-States, >50K 21, ?, 123727, Some-college, 10, Never-married, ?, Not-in-family, White, Female, 0, 0, 28, United-States, <=50K 58, Federal-gov, 208640, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Self-emp-not-inc, 120130, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 29, Self-emp-inc, 241431, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, >50K 25, Private, 120450, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 152240, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 200960, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 30, Federal-gov, 314310, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Local-gov, 44566, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 80, United-States, <=50K 59, Private, 21792, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 10, United-States, <=50K 36, Private, 182074, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 221850, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, Ecuador, >50K 42, Private, 240628, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 34, Private, 318641, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 45, United-States, >50K 27, Self-emp-not-inc, 140863, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 129150, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 50, United-States, >50K 41, Private, 143003, Assoc-voc, 11, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 7298, 0, 60, India, >50K 34, Self-emp-not-inc, 198664, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 15024, 0, 70, South, >50K 41, Private, 244945, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 138514, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 18, Private, 92008, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, White, Female, 0, 0, 28, United-States, <=50K 23, Private, 207415, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 15, United-States, <=50K 26, Private, 188626, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, <=50K 38, Private, 257250, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 7298, 0, 60, United-States, >50K 27, Private, 133696, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 88, United-States, <=50K 21, Private, 195919, 10th, 6, Never-married, Handlers-cleaners, Not-in-family, Other, Male, 0, 0, 40, Dominican-Republic, <=50K 41, Private, 119266, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Self-emp-not-inc, 140474, Assoc-acdm, 12, Divorced, Craft-repair, Own-child, Amer-Indian-Eskimo, Male, 0, 0, 35, United-States, <=50K 25, Private, 69739, 10th, 6, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 293176, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Private, 217961, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 15, United-States, <=50K 40, Local-gov, 163725, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 40, United-States, >50K 23, Private, 419394, Some-college, 10, Never-married, Sales, Own-child, Black, Male, 0, 0, 9, United-States, <=50K 18, Private, 220836, 11th, 7, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 37, Private, 334291, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 58, Private, 298601, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 3781, 0, 40, United-States, <=50K 36, Private, 200360, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 203482, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Private, 99126, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Wife, White, Female, 7688, 0, 40, United-States, >50K 62, Private, 109190, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 40, United-States, >50K 34, Private, 34848, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 4064, 0, 40, United-States, <=50K 27, Private, 29732, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 4865, 0, 36, United-States, <=50K 23, Private, 87867, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 35, United-States, <=50K 55, Private, 123515, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 175935, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 229456, HS-grad, 9, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 38, United-States, <=50K 44, Private, 184105, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 4386, 0, 40, United-States, >50K 42, Local-gov, 99554, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 190227, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 29020, Assoc-acdm, 12, Divorced, Adm-clerical, Not-in-family, Black, Female, 0, 0, 45, United-States, <=50K 31, Private, 306459, 1st-4th, 2, Separated, Handlers-cleaners, Unmarried, White, Male, 0, 0, 35, Honduras, <=50K 42, Private, 193995, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 26, Private, 105059, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 20, United-States, <=50K 62, Private, 71751, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 98, United-States, >50K 28, Private, 176683, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 5178, 0, 50, United-States, >50K 34, Private, 342709, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 53838, Bachelors, 13, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Local-gov, 209482, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 45, United-States, >50K 44, Private, 214242, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 47, ?, 34458, 7th-8th, 4, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 10, United-States, <=50K 35, Private, 100375, Some-college, 10, Married-spouse-absent, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 149949, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 189762, Assoc-acdm, 12, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 56, United-States, <=50K 46, Private, 79874, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 53, United-States, >50K 66, Self-emp-not-inc, 104576, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 8, United-States, >50K 34, State-gov, 355700, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 26, Private, 213625, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 204984, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Private, 144593, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 40, ?, <=50K 23, Private, 217169, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 184883, 9th, 5, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, United-States, <=50K 44, ?, 136419, 10th, 6, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 57758, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 68, United-States, >50K 54, Self-emp-not-inc, 30908, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 71, Private, 217971, 9th, 5, Widowed, Sales, Unmarried, White, Female, 0, 0, 13, United-States, <=50K 51, Private, 160703, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 32, Private, 142675, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 75, ?, 248833, HS-grad, 9, Married-AF-spouse, ?, Wife, White, Female, 2653, 0, 14, United-States, <=50K 57, Private, 171242, 11th, 7, Married-spouse-absent, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Canada, <=50K 34, Private, 376979, 9th, 5, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 175935, Bachelors, 13, Divorced, Sales, Not-in-family, White, Male, 14084, 0, 40, United-States, >50K 21, Private, 277530, HS-grad, 9, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 50, Private, 104501, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Private, 94041, Assoc-voc, 11, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 44, Ireland, <=50K 37, Local-gov, 593246, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 50, United-States, >50K 19, Private, 121074, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 99, United-States, <=50K 64, Private, 192596, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 17, Private, 142457, 11th, 7, Never-married, Other-service, Own-child, Black, Male, 0, 0, 20, United-States, <=50K 37, Private, 136028, Assoc-voc, 11, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 216145, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 4650, 0, 45, United-States, <=50K 20, Private, 157894, Some-college, 10, Never-married, Other-service, Own-child, Black, Male, 0, 0, 20, United-States, <=50K 39, Self-emp-not-inc, 164593, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 4787, 0, 40, United-States, >50K 18, Private, 252993, 12th, 8, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, Columbia, <=50K 42, Private, 145711, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 50, United-States, >50K 43, Private, 358199, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 3103, 0, 40, United-States, >50K 42, Private, 219591, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 55, United-States, >50K 53, Local-gov, 205005, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 60, United-States, >50K 52, Private, 221936, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 120914, 10th, 6, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 77, Self-emp-inc, 155761, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 8, United-States, <=50K 25, Private, 195914, Some-college, 10, Never-married, Sales, Own-child, Black, Female, 3418, 0, 30, United-States, <=50K 38, Local-gov, 236687, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 318036, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 53306, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 27, Private, 174645, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 321817, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 206948, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 47, Federal-gov, 402975, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, United-States, <=50K 72, ?, 289930, Bachelors, 13, Separated, ?, Not-in-family, White, Female, 991, 0, 7, United-States, <=50K 42, Private, 367049, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 4650, 0, 40, United-States, <=50K 36, Private, 143486, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Self-emp-inc, 27187, Masters, 14, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, >50K 24, Private, 187717, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 378104, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 113870, 1st-4th, 2, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, ?, <=50K 42, Private, 252518, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 40, United-States, >50K 24, Private, 326334, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 20, United-States, <=50K 41, Private, 279914, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, >50K 29, Private, 320451, HS-grad, 9, Never-married, Protective-serv, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 36, Private, 207853, HS-grad, 9, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 78, Self-emp-inc, 237294, HS-grad, 9, Widowed, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 43, Private, 112181, Assoc-voc, 11, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 1902, 32, United-States, >50K 34, State-gov, 259705, Some-college, 10, Separated, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 20, ?, 117789, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 449432, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Federal-gov, 89083, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 59612, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 44, United-States, <=50K 21, Private, 129980, 9th, 5, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 108233, Assoc-acdm, 12, Separated, Other-service, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 30, Private, 342709, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 126675, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 141118, Assoc-voc, 11, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 20, ?, 273701, Some-college, 10, Never-married, ?, Other-relative, Black, Male, 34095, 0, 10, United-States, <=50K 46, Private, 173243, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Local-gov, 161092, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 209691, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 42, United-States, >50K 36, Private, 89508, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 30, Private, 399522, 11th, 7, Married-spouse-absent, Handlers-cleaners, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 60, State-gov, 136939, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, Local-gov, 264436, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 57, Private, 199572, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, Federal-gov, 28291, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 50, Private, 215990, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 56, Self-emp-not-inc, 179594, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 48, United-States, <=50K 61, Self-emp-inc, 139391, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 1902, 35, United-States, >50K 45, Private, 187370, Masters, 14, Divorced, Exec-managerial, Unmarried, White, Male, 7430, 0, 70, United-States, >50K 31, Private, 473133, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 5178, 0, 40, United-States, >50K 60, Self-emp-not-inc, 205246, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, Black, Male, 0, 2559, 50, United-States, >50K 26, Private, 182308, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, Self-emp-not-inc, 51662, 11th, 7, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 289468, 11th, 7, Widowed, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 201954, Assoc-acdm, 12, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 65, United-States, >50K 45, Self-emp-not-inc, 26781, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 58, Private, 100960, 9th, 5, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 203761, Assoc-voc, 11, Never-married, Tech-support, Not-in-family, White, Female, 2354, 0, 40, United-States, <=50K 23, Private, 213811, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 124672, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 19, Private, 219300, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 25, United-States, <=50K 22, Private, 270436, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 212619, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, <=50K 23, Private, 193586, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 3908, 0, 40, United-States, <=50K 40, Private, 84136, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 25, United-States, <=50K 55, Federal-gov, 264834, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, State-gov, 98995, Assoc-voc, 11, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 278254, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 28, Private, 167987, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 43, Federal-gov, 72887, Bachelors, 13, Married-spouse-absent, Tech-support, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 17, Private, 176467, 9th, 5, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 51, Self-emp-not-inc, 85902, 10th, 6, Widowed, Transport-moving, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 223433, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 54, Self-emp-inc, 108435, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 24, Private, 172496, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 35, Private, 241998, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 48, Private, 245948, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, Black, Female, 2174, 0, 40, United-States, <=50K 23, Private, 187513, Assoc-voc, 11, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 440138, HS-grad, 9, Never-married, Priv-house-serv, Not-in-family, White, Female, 0, 0, 45, England, <=50K 24, Private, 218215, Assoc-voc, 11, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 50, Private, 158948, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 3411, 0, 40, United-States, <=50K 34, Private, 94413, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 45, Private, 183598, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 192664, 11th, 7, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 392812, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 21, Private, 155818, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 32, Private, 195000, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 308205, 5th-6th, 3, Never-married, Farming-fishing, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 53, Private, 104879, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 152307, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 145964, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 97419, HS-grad, 9, Married-civ-spouse, Protective-serv, Wife, Black, Female, 0, 0, 40, United-States, <=50K 25, ?, 12285, Some-college, 10, Never-married, ?, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 20, United-States, <=50K 30, Private, 263150, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 49, ?, 189885, HS-grad, 9, Widowed, ?, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 23, Private, 151888, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 254167, 10th, 6, Separated, Transport-moving, Own-child, White, Male, 0, 0, 35, United-States, <=50K 45, Local-gov, 331482, Assoc-acdm, 12, Divorced, Tech-support, Own-child, White, Male, 0, 0, 40, United-States, <=50K 61, Local-gov, 177189, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 42, United-States, <=50K 35, Private, 186886, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 55, United-States, <=50K 20, Private, 33221, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 27, Private, 188171, 10th, 6, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 60, United-States, <=50K 23, Private, 209770, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 164488, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, ?, <=50K 65, Local-gov, 180869, Some-college, 10, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 25, Private, 190350, HS-grad, 9, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 49, Private, 137192, Bachelors, 13, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 1977, 50, South, >50K 45, Private, 204057, Bachelors, 13, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, Germany, <=50K 46, Private, 198774, Masters, 14, Divorced, Exec-managerial, Unmarried, White, Female, 0, 323, 45, United-States, <=50K 67, Private, 134906, HS-grad, 9, Widowed, Sales, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 40, Private, 174515, HS-grad, 9, Widowed, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 259363, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 44, Self-emp-not-inc, 201742, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 2415, 50, United-States, >50K 35, Private, 209609, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 28, Private, 185127, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 462838, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 37, Private, 176967, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 54, Private, 284129, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, >50K 33, Federal-gov, 37546, Prof-school, 15, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 46, Private, 116666, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 120724, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 4386, 0, 40, United-States, <=50K 27, Private, 314240, Assoc-acdm, 12, Never-married, Exec-managerial, Not-in-family, White, Male, 3325, 0, 40, United-States, <=50K 49, Private, 423222, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 51, Private, 201127, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 27, Private, 202239, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 209629, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 59, Private, 165922, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 40, United-States, >50K 24, Private, 133520, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 15, United-States, <=50K 66, ?, 99888, Assoc-voc, 11, Widowed, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 176410, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 38, United-States, <=50K 35, Federal-gov, 103214, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 60, United-States, >50K 34, Private, 122612, Bachelors, 13, Married-civ-spouse, Other-service, Wife, Asian-Pac-Islander, Female, 7688, 0, 50, Philippines, >50K 50, Private, 226735, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 70, United-States, >50K 43, Self-emp-inc, 151089, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 21, Private, 244312, 9th, 5, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 30, El-Salvador, <=50K 33, Private, 209317, 9th, 5, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 45, El-Salvador, <=50K 48, Private, 99096, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 1590, 38, United-States, <=50K 22, Private, 374116, HS-grad, 9, Never-married, Priv-house-serv, Own-child, White, Female, 0, 0, 36, United-States, <=50K 29, Private, 205249, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Japan, <=50K 42, Self-emp-not-inc, 326083, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Self-emp-not-inc, 183523, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, Hungary, <=50K 36, Private, 350783, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 66, Local-gov, 140849, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 44, Private, 175943, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 20, United-States, <=50K 45, Local-gov, 125933, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 49, Private, 225124, HS-grad, 9, Divorced, Other-service, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 36, Private, 272090, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 45, El-Salvador, <=50K 48, Private, 40666, 11th, 7, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 60, United-States, <=50K 19, Private, 35245, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 167482, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Private, 204662, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 32, Private, 291147, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 49, Private, 179869, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 51, Self-emp-not-inc, 205100, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 352139, Some-college, 10, Divorced, Other-service, Own-child, White, Female, 0, 0, 29, United-States, <=50K 39, Private, 111268, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 247111, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 19, Private, 271446, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 29, Local-gov, 132412, Bachelors, 13, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 52, Self-emp-inc, 74712, HS-grad, 9, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, >50K 22, Private, 94662, Assoc-voc, 11, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 44, United-States, <=50K 44, Self-emp-inc, 33126, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 80, United-States, <=50K 43, Private, 133584, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Local-gov, 103759, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 3942, 0, 40, United-States, <=50K 63, ?, 64448, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 374367, Assoc-voc, 11, Separated, Sales, Not-in-family, Black, Male, 0, 0, 44, United-States, <=50K 40, Private, 179666, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 30, Canada, <=50K 18, Private, 99219, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 15, United-States, <=50K 57, Self-emp-inc, 180211, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 50, Taiwan, >50K 54, Local-gov, 219276, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, >50K 44, Private, 150011, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 231231, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 40, Private, 182217, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, Scotland, <=50K 29, Private, 277342, Some-college, 10, Never-married, Transport-moving, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 140001, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 99651, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 5178, 0, 40, United-States, >50K 45, Private, 223319, Some-college, 10, Divorced, Sales, Own-child, White, Male, 0, 0, 45, United-States, <=50K 52, Private, 235307, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 57, Private, 206343, HS-grad, 9, Separated, Machine-op-inspct, Not-in-family, White, Male, 2174, 0, 40, Cuba, <=50K 51, Local-gov, 156003, HS-grad, 9, Divorced, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 529223, Bachelors, 13, Never-married, Sales, Own-child, Black, Male, 0, 0, 10, United-States, <=50K 22, Private, 202871, Assoc-voc, 11, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 44, United-States, <=50K 37, Private, 58337, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 58, Federal-gov, 298643, HS-grad, 9, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 61, Private, 191188, 10th, 6, Widowed, Farming-fishing, Unmarried, White, Male, 0, 0, 20, United-States, <=50K 30, Private, 96287, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 23, Private, 104443, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 323054, 10th, 6, Divorced, Other-service, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 18, Private, 95917, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 25, Canada, <=50K 34, Private, 238305, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 0, 1628, 12, ?, <=50K 23, Private, 49296, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, Black, Male, 0, 0, 40, United-States, <=50K 23, Private, 50953, Some-college, 10, Never-married, Priv-house-serv, Own-child, White, Female, 0, 0, 10, United-States, <=50K 57, Private, 124507, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, >50K 58, Private, 239523, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 59, Self-emp-not-inc, 309124, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 240172, Bachelors, 13, Married-spouse-absent, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 105010, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 45, United-States, >50K 44, Local-gov, 135056, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 16, ?, <=50K 25, Private, 178478, Bachelors, 13, Never-married, Tech-support, Own-child, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 23871, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 22, Private, 362309, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 35, United-States, <=50K 21, Private, 257781, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 1719, 30, United-States, <=50K 44, Private, 175669, 11th, 7, Married-civ-spouse, Prof-specialty, Wife, White, Female, 5178, 0, 36, United-States, >50K 50, Private, 297906, Some-college, 10, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 0, 50, United-States, >50K 44, Private, 230684, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 53, ?, 123011, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Private, 170866, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 54, Local-gov, 182543, Some-college, 10, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 60, Self-emp-not-inc, 236470, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, Private, 33725, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 27, Private, 188941, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 3908, 0, 40, United-States, <=50K 43, Private, 206878, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 60, United-States, <=50K 33, Local-gov, 173806, Assoc-acdm, 12, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 190709, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 65, United-States, <=50K 41, Private, 149102, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, Poland, <=50K 21, Private, 25265, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 100669, Some-college, 10, Married-civ-spouse, Craft-repair, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 27, Self-emp-inc, 114158, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 50, Private, 228057, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 54012, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 46, Federal-gov, 219967, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 49, Private, 239865, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, State-gov, 119421, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 35, United-States, >50K 56, Self-emp-not-inc, 220187, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 45, United-States, >50K 41, Local-gov, 33068, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 1974, 40, United-States, <=50K 41, Self-emp-not-inc, 277783, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 2001, 50, United-States, <=50K 42, Private, 175515, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, Local-gov, 271795, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 70055, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 352806, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, Mexico, <=50K 57, Private, 266189, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 42, United-States, <=50K 49, Private, 102945, 7th-8th, 4, Widowed, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 173851, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 59, Private, 144092, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 198681, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 70, United-States, >50K 33, Private, 351810, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, Mexico, <=50K 52, Private, 180142, Masters, 14, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 45, United-States, <=50K 37, Self-emp-inc, 175360, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Self-emp-inc, 224498, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 39, Self-emp-inc, 154641, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 60, United-States, <=50K 54, Local-gov, 152540, Some-college, 10, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 42, United-States, <=50K 52, Private, 217663, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 22, Local-gov, 138575, HS-grad, 9, Never-married, Protective-serv, Unmarried, White, Male, 0, 0, 56, United-States, <=50K 19, ?, 32477, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 25, United-States, <=50K 65, Private, 101104, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 9386, 0, 10, United-States, >50K 32, Private, 44677, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 456618, 7th-8th, 4, Never-married, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, El-Salvador, <=50K 34, Private, 227282, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 27624, Assoc-voc, 11, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 24, Private, 281403, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 98, United-States, <=50K 63, Federal-gov, 39181, Doctorate, 16, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 2559, 60, United-States, >50K 48, Private, 377140, 5th-6th, 3, Never-married, Priv-house-serv, Unmarried, White, Female, 0, 0, 35, Nicaragua, <=50K 26, Private, 299810, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 28, Private, 181916, Some-college, 10, Separated, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 237044, HS-grad, 9, Never-married, Other-service, Own-child, Black, Male, 0, 0, 12, United-States, <=50K 57, Self-emp-inc, 123053, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 15024, 0, 50, India, >50K 64, State-gov, 269512, Bachelors, 13, Divorced, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 44767, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 50, United-States, >50K 28, Private, 67218, 7th-8th, 4, Married-civ-spouse, Sales, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 176992, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Self-emp-not-inc, 43712, 11th, 7, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1887, 45, United-States, >50K 44, Private, 379919, Assoc-acdm, 12, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, >50K 34, Private, 104509, Assoc-voc, 11, Never-married, Prof-specialty, Not-in-family, White, Female, 1639, 0, 20, United-States, <=50K 18, Private, 212370, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 25, United-States, <=50K 36, Private, 179666, 12th, 8, Married-civ-spouse, Craft-repair, Husband, Other, Male, 0, 0, 40, United-States, <=50K 73, Self-emp-not-inc, 233882, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, Asian-Pac-Islander, Male, 0, 2457, 40, Vietnam, <=50K 24, Private, 197387, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, Mexico, <=50K 29, Local-gov, 220656, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, United-States, >50K 33, Private, 181091, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 57, Federal-gov, 135028, HS-grad, 9, Separated, Adm-clerical, Other-relative, Black, Female, 0, 0, 35, United-States, <=50K 41, Private, 185057, Assoc-voc, 11, Never-married, Craft-repair, Not-in-family, White, Female, 0, 0, 40, ?, <=50K 55, Private, 106498, 10th, 6, Widowed, Transport-moving, Not-in-family, Black, Female, 0, 0, 35, United-States, <=50K 21, Private, 203003, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Self-emp-not-inc, 223789, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 26, Private, 184026, Some-college, 10, Never-married, Prof-specialty, Not-in-family, Other, Male, 0, 0, 50, United-States, <=50K 32, ?, 335427, Bachelors, 13, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 20, United-States, >50K 40, Private, 65866, Some-college, 10, Divorced, Tech-support, Unmarried, White, Female, 0, 213, 40, United-States, <=50K 32, Private, 372692, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 45607, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 59, State-gov, 303176, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 2179, 40, United-States, <=50K 29, Private, 138190, HS-grad, 9, Never-married, Sales, Unmarried, Black, Female, 0, 1138, 40, United-States, <=50K 29, Self-emp-not-inc, 212895, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 59, Self-emp-inc, 31359, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 80, United-States, >50K 58, Private, 147989, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 47, Private, 145290, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, <=50K 44, Private, 262684, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 1504, 45, United-States, <=50K 31, Private, 132601, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 42, Self-emp-not-inc, 30759, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 19, Private, 319889, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 25, United-States, <=50K 66, Private, 29431, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 41, Private, 111483, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, <=50K 22, Private, 184756, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 30, United-States, <=50K 31, Private, 651396, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 1594, 30, United-States, <=50K 30, Private, 187560, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Self-emp-not-inc, 84848, HS-grad, 9, Separated, Other-service, Not-in-family, White, Female, 0, 0, 16, United-States, <=50K 75, ?, 36243, Doctorate, 16, Never-married, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, State-gov, 88913, Assoc-acdm, 12, Divorced, Prof-specialty, Unmarried, Asian-Pac-Islander, Female, 0, 0, 36, United-States, <=50K 19, Private, 73190, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, United-States, <=50K 60, Private, 132529, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 214542, 11th, 7, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 217006, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 169785, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 30, Private, 75573, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, Germany, <=50K 37, Private, 239171, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 55, Self-emp-not-inc, 53566, Doctorate, 16, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 20, Private, 117109, Some-college, 10, Never-married, Adm-clerical, Other-relative, Black, Female, 0, 0, 24, United-States, <=50K 32, Private, 398019, 7th-8th, 4, Never-married, Priv-house-serv, Not-in-family, White, Female, 0, 0, 15, Mexico, <=50K 18, Private, 114008, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 35, United-States, <=50K 24, Private, 204653, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 33, Local-gov, 254935, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 45, United-States, <=50K 76, ?, 84755, Some-college, 10, Widowed, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 57, Local-gov, 198145, Masters, 14, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 14, United-States, >50K 53, Private, 174020, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 1876, 38, United-States, <=50K 19, Private, 451951, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 50, Local-gov, 172175, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 209472, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 40, Private, 336707, Assoc-voc, 11, Separated, Craft-repair, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 26, ?, 431861, 10th, 6, Separated, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 47, Self-emp-inc, 156728, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, <=50K 39, Federal-gov, 290321, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 49, State-gov, 206577, Some-college, 10, Divorced, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 28, Self-emp-not-inc, 149324, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 7, United-States, <=50K 33, ?, 49593, Some-college, 10, Married-civ-spouse, ?, Wife, Black, Female, 0, 0, 30, United-States, <=50K 50, Private, 98975, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 40, United-States, >50K 28, Private, 181659, 11th, 7, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 50, United-States, <=50K 30, Private, 174789, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 102308, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 50, United-States, >50K 39, Private, 184801, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Private, 176014, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 50, Private, 256861, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 80, United-States, <=50K 37, Private, 239397, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 26, Private, 233777, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 55, Private, 236520, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Private, 70754, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Private, 245378, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 26, Private, 176729, Bachelors, 13, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 32, Private, 154120, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 7298, 0, 40, United-States, >50K 43, Private, 88913, Some-college, 10, Never-married, Handlers-cleaners, Own-child, Asian-Pac-Islander, Female, 1055, 0, 40, United-States, <=50K 19, Private, 517036, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Female, 0, 0, 40, El-Salvador, <=50K 38, Private, 436361, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 75, United-States, <=50K 38, Private, 231037, 5th-6th, 3, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, Mexico, <=50K 65, Private, 209831, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 70, Self-emp-not-inc, 143833, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 2246, 40, United-States, >50K 48, ?, 167381, HS-grad, 9, Widowed, ?, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 44, Private, 215468, Bachelors, 13, Separated, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 7, United-States, <=50K 32, Private, 200700, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 30, Local-gov, 191777, HS-grad, 9, Never-married, Protective-serv, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 49, Federal-gov, 195437, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 60, United-States, >50K 23, Private, 149396, HS-grad, 9, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 25, Private, 104746, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 16, United-States, <=50K 19, Private, 108147, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 15, United-States, <=50K 27, Private, 238859, Assoc-voc, 11, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 43, State-gov, 23157, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 38, Private, 497788, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 42, Private, 141558, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 33, Federal-gov, 117963, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 38, United-States, <=50K 30, Private, 232356, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Private, 157941, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 103642, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 169727, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 274731, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Private, 161572, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 45, United-States, <=50K 38, Private, 48779, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 48, Private, 141511, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 57, Private, 314153, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 1887, 55, United-States, >50K 30, Private, 168334, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 30, United-States, <=50K 42, Local-gov, 267252, Masters, 14, Separated, Exec-managerial, Unmarried, Black, Male, 0, 0, 45, United-States, >50K 31, Self-emp-not-inc, 312055, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 70, United-States, <=50K 32, Private, 207937, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 232653, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 63, Private, 246841, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 154087, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 199011, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 12, United-States, <=50K 51, Self-emp-not-inc, 205100, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 30, United-States, >50K 36, Private, 177907, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Male, 2176, 0, 20, ?, <=50K 24, Private, 50400, Some-college, 10, Married-civ-spouse, Sales, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 41, Local-gov, 97064, Assoc-voc, 11, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 44, United-States, <=50K 21, Private, 65038, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 292472, Some-college, 10, Never-married, Craft-repair, Not-in-family, Asian-Pac-Islander, Male, 0, 1876, 45, Cambodia, <=50K 17, Private, 225211, 9th, 5, Never-married, Other-service, Own-child, Black, Male, 0, 0, 35, United-States, <=50K 45, Private, 320192, 1st-4th, 2, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, <=50K 39, State-gov, 119421, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 0, 625, 35, United-States, <=50K 21, Private, 83580, Some-college, 10, Never-married, Prof-specialty, Own-child, Amer-Indian-Eskimo, Female, 0, 0, 4, United-States, <=50K 29, Private, 133696, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 8614, 0, 45, United-States, >50K 39, Private, 141584, Masters, 14, Never-married, Sales, Not-in-family, White, Male, 0, 2444, 45, United-States, >50K 42, Private, 529216, HS-grad, 9, Separated, Transport-moving, Other-relative, Black, Male, 0, 0, 40, United-States, <=50K 22, Private, 390817, 5th-6th, 3, Married-civ-spouse, Craft-repair, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 21, ?, 85733, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 59, Private, 155976, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 221172, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 65, United-States, >50K 45, Private, 270842, Some-college, 10, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 82622, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 58, Private, 371064, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 20, United-States, <=50K 45, Private, 54744, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1848, 40, United-States, >50K 29, Private, 22641, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Amer-Indian-Eskimo, Male, 0, 0, 45, United-States, <=50K 21, Private, 218957, 11th, 7, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 45, United-States, <=50K 51, Private, 441637, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Local-gov, 143699, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 183096, Bachelors, 13, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 45, Private, 97176, 11th, 7, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 16, United-States, <=50K 38, Self-emp-not-inc, 122493, 10th, 6, Married-civ-spouse, Sales, Husband, White, Male, 0, 1887, 40, United-States, >50K 22, Private, 311376, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 78928, 9th, 5, Married-civ-spouse, Other-service, Husband, White, Male, 3137, 0, 40, United-States, <=50K 62, Private, 123582, 10th, 6, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 32, Federal-gov, 174215, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 36, Private, 183902, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 4, United-States, >50K 43, Private, 247880, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 256636, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, ?, 152875, Bachelors, 13, Married-civ-spouse, ?, Wife, Asian-Pac-Islander, Female, 0, 0, 40, China, <=50K 28, Private, 22422, HS-grad, 9, Never-married, Transport-moving, Unmarried, White, Male, 0, 0, 55, United-States, <=50K 49, ?, 178215, Some-college, 10, Widowed, ?, Unmarried, White, Female, 0, 0, 28, United-States, <=50K 47, Local-gov, 194360, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 7, United-States, >50K 59, Private, 247187, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 63921, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 224889, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Self-emp-not-inc, 178564, Bachelors, 13, Never-married, Prof-specialty, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 47619, Assoc-acdm, 12, Divorced, Prof-specialty, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 41, Private, 92775, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 37, Private, 50837, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 20, Local-gov, 235894, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 244974, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 20, Local-gov, 526734, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 38, Self-emp-not-inc, 243484, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 28, United-States, >50K 23, Private, 201664, HS-grad, 9, Married-civ-spouse, Adm-clerical, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 234640, HS-grad, 9, Married-spouse-absent, Sales, Own-child, White, Female, 0, 0, 36, United-States, <=50K 46, Private, 268022, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Local-gov, 223267, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Self-emp-not-inc, 99199, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 137076, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 115411, Some-college, 10, Divorced, Sales, Own-child, White, Male, 2174, 0, 45, United-States, <=50K 51, Private, 313146, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 69, Self-emp-not-inc, 29980, 7th-8th, 4, Never-married, Farming-fishing, Other-relative, White, Male, 1848, 0, 10, United-States, <=50K 39, Self-emp-inc, 543042, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 5178, 0, 50, United-States, >50K 43, Private, 271807, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 51, Federal-gov, 97934, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 5178, 0, 40, United-States, >50K 43, Private, 191196, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Self-emp-not-inc, 264627, 11th, 7, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 84, United-States, <=50K 32, Private, 183801, HS-grad, 9, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 209227, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 21, United-States, <=50K 64, Private, 216208, Some-college, 10, Widowed, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 377095, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 317535, 1st-4th, 2, Married-civ-spouse, Protective-serv, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 40, Private, 247880, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 21, Private, 152246, Some-college, 10, Never-married, Handlers-cleaners, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 23, Private, 428299, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 161708, Some-college, 10, Never-married, Other-service, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 19, Private, 167859, HS-grad, 9, Never-married, Other-service, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 61, Private, 85194, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 25, United-States, <=50K 47, Self-emp-inc, 119471, 7th-8th, 4, Never-married, Craft-repair, Not-in-family, Other, Male, 0, 0, 40, ?, <=50K 39, Private, 117683, 10th, 6, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 45, United-States, <=50K 51, Private, 139347, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 7688, 0, 40, United-States, >50K 25, Private, 427744, 10th, 6, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 122116, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 34, State-gov, 227931, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 54, Self-emp-not-inc, 226497, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 24, Private, 83783, Bachelors, 13, Never-married, Tech-support, Own-child, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 197113, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, Other, Male, 0, 0, 50, Puerto-Rico, <=50K 33, Private, 204742, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 44, United-States, <=50K 63, ?, 331527, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 14, United-States, <=50K 31, Private, 213179, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, >50K 70, Self-emp-inc, 188260, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 16, United-States, <=50K 43, Private, 298161, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, Nicaragua, <=50K 36, Private, 143774, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 12, United-States, >50K 50, Local-gov, 139296, 11th, 7, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 152389, Some-college, 10, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 30, United-States, <=50K 31, Private, 309974, Some-college, 10, Separated, Tech-support, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 19, ?, 37085, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 30, United-States, <=50K 39, Private, 270059, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 29, Private, 130045, 7th-8th, 4, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 188038, Some-college, 10, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 168203, 7th-8th, 4, Never-married, Farming-fishing, Other-relative, Other, Male, 0, 0, 40, Mexico, <=50K 46, Private, 171807, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 62, Private, 186696, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 177531, 10th, 6, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 23, United-States, <=50K 28, Private, 115464, HS-grad, 9, Never-married, Other-service, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 19, Private, 501144, Some-college, 10, Never-married, Sales, Other-relative, Black, Female, 0, 0, 40, United-States, <=50K 61, Local-gov, 180079, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 4064, 0, 40, United-States, <=50K 18, Private, 205894, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 25, ?, <=50K 39, Self-emp-not-inc, 218490, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 2415, 50, ?, >50K 24, Local-gov, 203924, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 45, United-States, <=50K 38, Private, 91857, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 41, United-States, <=50K 38, Private, 229700, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 40, United-States, >50K 17, Private, 158704, 10th, 6, Never-married, Sales, Own-child, White, Male, 0, 0, 20, United-States, <=50K 28, Private, 190911, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 139176, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 8, United-States, <=50K 61, Private, 119684, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 20, United-States, >50K 69, Private, 124930, 5th-6th, 3, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 2267, 40, United-States, <=50K 19, Private, 168693, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 25, United-States, <=50K 26, Private, 250038, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 34, Self-emp-inc, 353927, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 70, Private, 216390, 9th, 5, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 2653, 0, 40, United-States, <=50K 21, Private, 230248, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 43, Private, 117728, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 44, United-States, <=50K 52, Private, 115851, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 59, Private, 193335, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 21, Private, 203894, Assoc-voc, 11, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 53, Self-emp-not-inc, 100109, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 40, United-States, >50K 55, State-gov, 157639, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Self-emp-inc, 235320, Masters, 14, Divorced, Sales, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 36, Private, 127686, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 37, United-States, <=50K 39, Private, 28572, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 48, United-States, <=50K 78, ?, 91534, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 3, United-States, <=50K 30, Private, 184687, HS-grad, 9, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 30, United-States, <=50K 22, Private, 267945, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 16, United-States, <=50K 43, Private, 131899, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 192614, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 56, United-States, <=50K 36, Private, 186808, Bachelors, 13, Married-civ-spouse, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, >50K 50, Private, 44116, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 27, Federal-gov, 46442, Bachelors, 13, Never-married, Protective-serv, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 46, Federal-gov, 78022, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 24, Private, 417668, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 20, United-States, <=50K 41, Private, 223763, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 68, Private, 223851, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 24, United-States, <=50K 38, Local-gov, 115634, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 114459, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Private, 197093, Some-college, 10, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 20, United-States, <=50K 31, Self-emp-not-inc, 357145, Doctorate, 16, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 48, United-States, <=50K 29, Private, 59231, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 42, United-States, <=50K 26, Private, 292303, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 122288, Some-college, 10, Widowed, Machine-op-inspct, Unmarried, White, Female, 0, 0, 36, United-States, <=50K 26, Federal-gov, 52322, Bachelors, 13, Never-married, Tech-support, Not-in-family, Other, Male, 0, 0, 60, United-States, <=50K 27, Local-gov, 105830, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 36, Private, 107125, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 50, United-States, <=50K 28, Federal-gov, 281860, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 53, Private, 283320, Bachelors, 13, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 40, State-gov, 26598, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 220783, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 21, ?, 121694, 7th-8th, 4, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 208302, 10th, 6, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 34, United-States, <=50K 34, Local-gov, 172664, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 54611, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 64, Private, 631947, 10th, 6, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 394484, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 25, ?, 239120, Bachelors, 13, Never-married, ?, Not-in-family, White, Male, 0, 0, 13, United-States, <=50K 38, Federal-gov, 37683, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, Asian-Pac-Islander, Female, 99999, 0, 57, Canada, >50K 47, Local-gov, 193012, Masters, 14, Divorced, Protective-serv, Not-in-family, Black, Male, 0, 0, 50, United-States, >50K 48, Private, 143098, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 1902, 40, China, >50K 57, Private, 84888, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 37, Private, 188503, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 37, Private, 337778, 11th, 7, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 51, Self-emp-not-inc, 94432, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 55, United-States, >50K 32, Private, 168906, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 116143, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 128272, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 14, United-States, <=50K 64, Federal-gov, 301383, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 9386, 0, 45, United-States, >50K 46, Private, 174995, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 24, State-gov, 289909, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 154641, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 23, Private, 209034, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 3942, 0, 40, United-States, <=50K 30, Private, 203488, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 44, United-States, <=50K 34, Private, 141118, Masters, 14, Divorced, Prof-specialty, Own-child, White, Female, 0, 0, 60, United-States, >50K 30, Private, 169589, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 137645, Bachelors, 13, Never-married, Sales, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 58, Local-gov, 489085, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 40, United-States, <=50K 32, Private, 36302, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, <=50K 37, Private, 253420, HS-grad, 9, Separated, Other-service, Unmarried, Black, Female, 0, 0, 25, United-States, <=50K 35, Private, 269300, HS-grad, 9, Separated, Other-service, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 18, Private, 282609, 5th-6th, 3, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 30, Honduras, <=50K 46, Private, 346978, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 71, Private, 182395, Bachelors, 13, Never-married, Craft-repair, Not-in-family, White, Male, 11678, 0, 45, United-States, >50K 44, Private, 205051, 10th, 6, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 128736, 10th, 6, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 236110, 12th, 8, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, Cuba, >50K 38, Private, 312271, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 52, Private, 126978, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, Asian-Pac-Islander, Female, 0, 0, 40, China, <=50K 47, Private, 204692, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 195956, Bachelors, 13, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 59, State-gov, 202682, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 231912, Assoc-voc, 11, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 37, United-States, <=50K 44, Local-gov, 24982, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 76, Private, 278938, Bachelors, 13, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 50, Local-gov, 36489, 10th, 6, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, Local-gov, 154874, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 74581, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, >50K 27, Private, 311446, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 5178, 0, 40, United-States, >50K 37, Self-emp-inc, 162164, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 239708, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 55, United-States, <=50K 49, Self-emp-not-inc, 162856, Some-college, 10, Divorced, Exec-managerial, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 48, Self-emp-inc, 85109, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 49, Private, 169042, HS-grad, 9, Separated, Prof-specialty, Unmarried, White, Female, 0, 625, 40, Puerto-Rico, <=50K 22, Private, 436798, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 345363, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, England, <=50K 36, Private, 49837, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 57, ?, 296516, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 50, United-States, <=50K 30, State-gov, 180283, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 40, Local-gov, 95639, HS-grad, 9, Never-married, Craft-repair, Other-relative, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 42, Private, 33155, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, <=50K 56, Private, 329059, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Italy, >50K 55, Private, 24694, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 443855, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Mexico, <=50K 52, ?, 294691, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 301867, Some-college, 10, Never-married, Adm-clerical, Unmarried, Asian-Pac-Islander, Female, 0, 0, 35, United-States, <=50K 55, Private, 226875, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 4064, 0, 40, United-States, <=50K 47, Private, 362835, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 23, Private, 180339, Assoc-acdm, 12, Never-married, Sales, Own-child, White, Female, 0, 0, 65, United-States, <=50K 55, Self-emp-inc, 207489, Bachelors, 13, Divorced, Sales, Not-in-family, White, Female, 0, 0, 50, Germany, <=50K 43, Private, 336643, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 31, Private, 143653, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 62, State-gov, 101475, Assoc-acdm, 12, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Local-gov, 263871, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 8, United-States, <=50K 38, Self-emp-not-inc, 77820, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Private, 95465, HS-grad, 9, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 42, United-States, <=50K 26, Private, 257910, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 26, Private, 244372, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 52, United-States, >50K 37, Self-emp-not-inc, 126738, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 72, United-States, <=50K 79, Self-emp-inc, 97082, 12th, 8, Widowed, Sales, Not-in-family, White, Male, 18481, 0, 45, United-States, >50K 61, Private, 133164, 7th-8th, 4, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 28, Self-emp-not-inc, 104617, 7th-8th, 4, Never-married, Other-service, Other-relative, White, Female, 0, 0, 99, Mexico, <=50K 60, Self-emp-inc, 105339, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 60, United-States, >50K 51, Self-emp-inc, 258735, HS-grad, 9, Divorced, Protective-serv, Not-in-family, White, Male, 0, 0, 81, United-States, <=50K 34, Private, 182926, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 43, United-States, >50K 35, Private, 166193, HS-grad, 9, Divorced, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 27, Local-gov, 206125, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 44, Private, 346594, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 108301, HS-grad, 9, Separated, Other-service, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 32, Private, 73498, 7th-8th, 4, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 129150, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 20, United-States, >50K 27, Private, 181280, Masters, 14, Never-married, Handlers-cleaners, Unmarried, White, Male, 0, 0, 30, United-States, <=50K 40, Private, 146908, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 43, Private, 183765, Some-college, 10, Divorced, Tech-support, Not-in-family, White, Male, 0, 0, 40, ?, >50K 25, Private, 164488, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 307468, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 30, Private, 93884, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 26, Private, 279833, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 2258, 45, United-States, >50K 52, Private, 137658, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, Other, Male, 0, 0, 40, Dominican-Republic, <=50K 32, Private, 101562, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 33, Private, 136331, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 259846, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, <=50K 48, Private, 98719, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 44, United-States, <=50K 62, Self-emp-not-inc, 168682, 7th-8th, 4, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 5, United-States, <=50K 40, Self-emp-not-inc, 198953, Assoc-acdm, 12, Never-married, Prof-specialty, Own-child, Black, Female, 0, 0, 2, United-States, <=50K 41, ?, 29115, Some-college, 10, Widowed, ?, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 28, Private, 173673, 5th-6th, 3, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, Mexico, <=50K 23, Private, 67958, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 50, Federal-gov, 98980, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 40, United-States, >50K 51, State-gov, 94174, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 63, Self-emp-not-inc, 122442, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 48, United-States, <=50K 63, Federal-gov, 154675, HS-grad, 9, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 116632, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 20, ?, 238685, 11th, 7, Divorced, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 61, ?, 139391, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 99999, 0, 30, United-States, >50K 40, Private, 169031, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 237452, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 15, Cuba, >50K 41, Private, 216968, Bachelors, 13, Never-married, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 40, ?, <=50K 27, ?, 216479, Bachelors, 13, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 24, United-States, >50K 20, State-gov, 126822, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 15, United-States, <=50K 28, Private, 51461, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 1887, 40, United-States, >50K 35, Private, 54953, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 222654, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 37676, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 57, Private, 159319, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 28, Private, 125321, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 209609, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Private, 224947, Assoc-voc, 11, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 43, State-gov, 438427, Some-college, 10, Divorced, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 26, Self-emp-not-inc, 384276, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 196805, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 65, United-States, <=50K 27, Private, 242097, Assoc-voc, 11, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 33, Private, 184306, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, <=50K 45, Private, 161954, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, Germany, <=50K 65, Private, 258561, Bachelors, 13, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 20, United-States, <=50K 57, Self-emp-not-inc, 95280, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 99999, 0, 45, United-States, >50K 59, Private, 212783, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 18, Private, 205004, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 26, United-States, <=50K 44, Local-gov, 387844, 12th, 8, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 83880, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 161155, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Local-gov, 265698, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 45, United-States, >50K 59, Self-emp-inc, 146477, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 19, Private, 97261, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, State-gov, 437890, HS-grad, 9, Never-married, Exec-managerial, Unmarried, Black, Male, 0, 0, 90, United-States, <=50K 68, Self-emp-not-inc, 133736, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 20051, 0, 40, United-States, >50K 63, Private, 169983, 11th, 7, Widowed, Sales, Not-in-family, White, Female, 2176, 0, 30, United-States, <=50K 37, Private, 126675, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 57, United-States, <=50K 46, Local-gov, 175754, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 1876, 60, United-States, <=50K 31, Private, 121768, Assoc-acdm, 12, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 35, Poland, <=50K 23, Private, 180052, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 124454, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 49, Private, 190115, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 1672, 44, United-States, <=50K 36, Private, 222584, HS-grad, 9, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 38, Private, 22245, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 46, Local-gov, 114160, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 45, United-States, >50K 24, Private, 228960, Assoc-acdm, 12, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 132572, Bachelors, 13, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 47, Private, 103020, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Wife, Other, Female, 0, 0, 40, Puerto-Rico, <=50K 40, Private, 187802, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 1887, 40, United-States, >50K 31, Local-gov, 50649, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 42, Private, 137698, 5th-6th, 3, Married-spouse-absent, Farming-fishing, Not-in-family, White, Male, 0, 0, 35, Mexico, <=50K 48, Self-emp-inc, 30575, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 70, United-States, >50K 56, Private, 202220, Some-college, 10, Separated, Tech-support, Unmarried, Black, Female, 0, 0, 38, United-States, <=50K 50, Private, 50178, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 17, Private, 207791, 10th, 6, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, United-States, <=50K 21, Private, 540712, HS-grad, 9, Never-married, Other-service, Other-relative, Black, Male, 0, 1719, 25, United-States, <=50K 50, Private, 321770, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 202053, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 34, Private, 143699, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 15, United-States, <=50K 32, Self-emp-not-inc, 115066, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 28, Private, 223751, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 62, Self-emp-inc, 354075, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 23, Private, 32732, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 15, United-States, <=50K 24, State-gov, 390867, Masters, 14, Never-married, Prof-specialty, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 31, Private, 101697, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 279721, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, Private, 223400, Assoc-acdm, 12, Married-civ-spouse, Priv-house-serv, Other-relative, White, Female, 0, 0, 35, Poland, <=50K 46, ?, 206357, 5th-6th, 3, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 40, Mexico, <=50K 39, Private, 76417, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 48, ?, 184682, HS-grad, 9, Never-married, ?, Own-child, White, Female, 0, 0, 18, United-States, <=50K 21, Private, 78170, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 42, United-States, <=50K 39, Private, 201410, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 189013, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 35, United-States, <=50K 33, Private, 119913, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Private, 549174, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 29, Local-gov, 214706, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 30, ?, 33811, Bachelors, 13, Married-civ-spouse, ?, Wife, Other, Female, 0, 0, 40, Taiwan, >50K 43, Private, 234220, HS-grad, 9, Divorced, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, Cuba, <=50K 22, Private, 237720, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 185942, Masters, 14, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, >50K 69, Local-gov, 286983, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 140027, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 18, ?, 115258, 11th, 7, Never-married, ?, Own-child, White, Male, 0, 0, 12, United-States, <=50K 54, Private, 155408, HS-grad, 9, Widowed, Handlers-cleaners, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 65, ?, 117963, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 45, United-States, <=50K 28, Private, 158737, 12th, 8, Married-civ-spouse, Machine-op-inspct, Other-relative, Other, Male, 0, 0, 40, Ecuador, <=50K 27, Local-gov, 199471, Assoc-voc, 11, Never-married, Tech-support, Own-child, White, Female, 0, 0, 38, United-States, <=50K 35, Private, 287701, Assoc-acdm, 12, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 45, United-States, >50K 38, Private, 137707, Assoc-voc, 11, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 40, United-States, >50K 33, State-gov, 108116, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 366900, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 56, Self-emp-inc, 187355, Some-college, 10, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 60, Canada, >50K 38, Private, 33105, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Amer-Indian-Eskimo, Male, 0, 0, 70, United-States, >50K 51, Self-emp-not-inc, 268639, Some-college, 10, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 2057, 60, Canada, <=50K 26, Private, 358975, Some-college, 10, Never-married, Priv-house-serv, Not-in-family, White, Female, 0, 0, 50, Hungary, <=50K 33, Private, 199227, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 44, Private, 248249, 7th-8th, 4, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 50, United-States, <=50K 36, Private, 460437, 9th, 5, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 187294, Some-college, 10, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 115932, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 181762, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 15024, 0, 55, United-States, >50K 21, Private, 27049, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 41, Private, 806552, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 41, Private, 150755, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, Canada, >50K 62, Private, 69867, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7298, 0, 50, United-States, >50K 27, Private, 160786, 11th, 7, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 45, Germany, <=50K 38, Private, 219546, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 60, Private, 24872, Some-college, 10, Separated, Transport-moving, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 30, United-States, <=50K 24, Private, 110371, 12th, 8, Never-married, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, Mexico, <=50K 24, ?, 376474, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 304602, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 32, ?, 143699, Some-college, 10, Never-married, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 238917, 1st-4th, 2, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 24, Mexico, <=50K 51, Private, 200618, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 183043, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 48, United-States, >50K 42, Local-gov, 209752, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 48, ?, 175653, Assoc-acdm, 12, Divorced, ?, Not-in-family, White, Female, 14084, 0, 40, United-States, >50K 49, Private, 196707, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 7298, 0, 43, United-States, >50K 37, Local-gov, 98725, Bachelors, 13, Never-married, Tech-support, Own-child, White, Female, 0, 0, 42, United-States, <=50K 37, Self-emp-not-inc, 180150, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 66, Private, 151227, Bachelors, 13, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, >50K 18, ?, 118847, HS-grad, 9, Never-married, ?, Own-child, White, Female, 0, 0, 24, United-States, <=50K 46, Private, 282538, Assoc-voc, 11, Separated, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 52, Private, 89534, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Private, 291011, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 67, Private, 166187, HS-grad, 9, Widowed, Exec-managerial, Unmarried, White, Male, 0, 0, 38, United-States, >50K 19, Private, 188669, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 25, United-States, <=50K 37, Private, 178948, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 42, Self-emp-inc, 188738, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 60, Italy, >50K 39, Self-emp-not-inc, 160808, Some-college, 10, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 40, United-States, <=50K 54, Private, 93605, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 1848, 40, United-States, >50K 46, Private, 318331, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, ?, 109921, HS-grad, 9, Separated, ?, Unmarried, Black, Female, 0, 0, 32, United-States, <=50K 33, Private, 87605, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 69, Self-emp-not-inc, 89477, Some-college, 10, Widowed, Farming-fishing, Not-in-family, White, Female, 0, 0, 14, United-States, <=50K 21, Private, 48301, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 220748, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, Black, Male, 0, 0, 48, United-States, <=50K 39, Private, 387068, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Private, 250743, Some-college, 10, Divorced, Adm-clerical, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 26, Private, 78258, Assoc-voc, 11, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 36, United-States, <=50K 42, Private, 31387, Doctorate, 16, Married-spouse-absent, Prof-specialty, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 36, Private, 289190, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 604537, HS-grad, 9, Never-married, Transport-moving, Unmarried, White, Male, 0, 0, 40, Mexico, <=50K 35, Private, 328466, 9th, 5, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Mexico, <=50K 42, Private, 403187, HS-grad, 9, Divorced, Handlers-cleaners, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 37, Private, 219546, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 4386, 0, 44, United-States, >50K 41, Private, 220531, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 27, Private, 204648, Assoc-voc, 11, Never-married, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 42, Self-emp-not-inc, 201908, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 50, United-States, >50K 44, ?, 109912, Bachelors, 13, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 16, United-States, >50K 18, Private, 365683, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 16, United-States, <=50K 41, Private, 175674, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 203488, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 106406, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 67, Private, 172756, 1st-4th, 2, Widowed, Machine-op-inspct, Not-in-family, White, Female, 2062, 0, 34, Ecuador, <=50K 37, Private, 125167, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 51, Private, 249339, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 94652, Some-college, 10, Never-married, Craft-repair, Own-child, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 40, Private, 195394, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 40, United-States, >50K 25, Private, 130302, HS-grad, 9, Never-married, Handlers-cleaners, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 66686, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 43, Private, 336042, HS-grad, 9, Separated, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 193586, Some-college, 10, Separated, Farming-fishing, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 325461, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 50, United-States, >50K 60, Local-gov, 313852, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 38, Local-gov, 30509, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 1669, 55, United-States, <=50K 21, Local-gov, 32639, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 18, Private, 234953, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 25, United-States, <=50K 49, Private, 120629, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, Black, Female, 27828, 0, 60, United-States, >50K 43, Private, 350379, 5th-6th, 3, Divorced, Priv-house-serv, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 26, ?, 176967, 11th, 7, Never-married, ?, Not-in-family, White, Female, 0, 0, 65, United-States, <=50K 36, Private, 36423, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 25, United-States, >50K 31, Private, 123397, HS-grad, 9, Married-civ-spouse, Transport-moving, Wife, White, Female, 5178, 0, 35, United-States, >50K 38, Private, 130813, HS-grad, 9, Divorced, Machine-op-inspct, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 43, Self-emp-not-inc, 35236, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 84, United-States, <=50K 58, Private, 33350, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 55, Private, 177380, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 29, United-States, <=50K 39, Private, 216129, Assoc-acdm, 12, Divorced, Exec-managerial, Unmarried, Black, Female, 0, 0, 35, Jamaica, <=50K 38, Private, 335104, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 54, Self-emp-not-inc, 199741, HS-grad, 9, Widowed, Craft-repair, Not-in-family, White, Male, 0, 2001, 35, United-States, <=50K 57, Self-emp-inc, 165881, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Local-gov, 387777, Assoc-acdm, 12, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 52, United-States, <=50K 44, Self-emp-not-inc, 149943, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 60, Taiwan, >50K 36, Private, 188834, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, Private, 290661, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 155603, Some-college, 10, Never-married, Other-service, Own-child, Black, Female, 0, 2205, 40, United-States, <=50K 25, Private, 114838, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 8, Italy, <=50K 54, Local-gov, 168553, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 103064, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 123833, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 60, Federal-gov, 55621, Assoc-acdm, 12, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 40, United-States, <=50K 66, Local-gov, 189834, 7th-8th, 4, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 36, Private, 217926, Assoc-acdm, 12, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 50, United-States, <=50K 29, Self-emp-not-inc, 341672, HS-grad, 9, Married-spouse-absent, Transport-moving, Other-relative, Asian-Pac-Islander, Male, 0, 1564, 50, India, >50K 29, Private, 163003, Bachelors, 13, Never-married, Adm-clerical, Own-child, Asian-Pac-Islander, Female, 2202, 0, 40, Taiwan, <=50K 25, Private, 194352, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 44, United-States, <=50K 62, ?, 54878, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 23, Private, 393248, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 279315, HS-grad, 9, Never-married, Other-service, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 33, Private, 392812, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 50, United-States, >50K 49, Self-emp-inc, 34998, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 57, Self-emp-inc, 51016, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 57, Local-gov, 132717, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 46, Private, 186078, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 37, Self-emp-inc, 196123, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 70, United-States, >50K 43, Self-emp-inc, 304906, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 26, Private, 41521, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 40, Private, 346847, Assoc-voc, 11, Separated, Prof-specialty, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 39, Self-emp-not-inc, 107233, HS-grad, 9, Never-married, Craft-repair, Other-relative, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 39, Private, 150125, Assoc-acdm, 12, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 31, Private, 400535, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 409622, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, Other, Male, 0, 0, 36, Mexico, <=50K 27, Private, 136448, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 36, Self-emp-not-inc, 202950, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, Iran, <=50K 40, Local-gov, 197012, Bachelors, 13, Divorced, Tech-support, Not-in-family, White, Female, 8614, 0, 40, England, >50K 57, Private, 237691, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Mexico, <=50K 24, Private, 170277, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 30, Private, 160784, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 28, Private, 33798, 12th, 8, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 22, Private, 197838, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 223212, 7th-8th, 4, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 50, United-States, <=50K 33, Private, 125762, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 44, United-States, >50K 20, Private, 283969, Some-college, 10, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 15, United-States, <=50K 25, Private, 374163, 12th, 8, Married-civ-spouse, Farming-fishing, Husband, Other, Male, 0, 0, 60, Mexico, <=50K 49, State-gov, 118567, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 147655, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 35, United-States, <=50K 45, Private, 82797, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 36, Local-gov, 142573, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 41, Private, 235167, 5th-6th, 3, Married-spouse-absent, Priv-house-serv, Not-in-family, White, Female, 0, 0, 32, Mexico, <=50K 23, Private, 53245, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 1602, 12, United-States, <=50K 47, Private, 28035, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 41, Private, 247082, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 30, Private, 123397, HS-grad, 9, Never-married, Handlers-cleaners, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 29, Local-gov, 133327, Some-college, 10, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 102270, 7th-8th, 4, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 64, ?, 45817, 9th, 5, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 50, United-States, <=50K 55, Private, 240988, 9th, 5, Married-civ-spouse, Machine-op-inspct, Other-relative, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 19, Private, 386378, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 31, State-gov, 350651, 12th, 8, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 40, United-States, >50K 18, State-gov, 76142, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 8, United-States, <=50K 68, Private, 73773, HS-grad, 9, Widowed, Sales, Not-in-family, White, Female, 0, 0, 24, United-States, <=50K 50, ?, 281504, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Local-gov, 293358, Some-college, 10, Never-married, Exec-managerial, Unmarried, Black, Female, 0, 0, 48, United-States, <=50K 44, Private, 146906, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 58, Self-emp-not-inc, 331474, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 20, United-States, >50K 20, Private, 213719, HS-grad, 9, Never-married, Sales, Own-child, Black, Female, 0, 0, 20, United-States, <=50K 18, Private, 101795, 10th, 6, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 228265, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 30, United-States, <=50K 49, Self-emp-not-inc, 130206, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 324254, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 223019, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 189666, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 45, United-States, <=50K 35, Private, 139086, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 359327, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, ?, <=50K 44, Self-emp-not-inc, 75065, 12th, 8, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 60, Vietnam, <=50K 55, Private, 139843, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 21, Private, 34310, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 2603, 40, United-States, <=50K 54, Private, 346014, Some-college, 10, Married-civ-spouse, Craft-repair, Wife, White, Female, 0, 0, 40, United-States, <=50K 39, Local-gov, 163278, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 2202, 0, 44, United-States, <=50K 52, Private, 31460, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 57, Self-emp-inc, 33725, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 67, ?, 63552, 7th-8th, 4, Widowed, ?, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 58, State-gov, 300623, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 27, Local-gov, 177072, Some-college, 10, Never-married, Prof-specialty, Other-relative, White, Male, 0, 0, 16, United-States, <=50K 66, ?, 37331, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 15, United-States, <=50K 41, Private, 167725, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 131180, 11th, 7, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 16, United-States, <=50K 58, Private, 275859, HS-grad, 9, Widowed, Craft-repair, Unmarried, White, Male, 8614, 0, 52, Mexico, >50K 50, Private, 275181, 5th-6th, 3, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 37, Cuba, <=50K 31, Private, 398988, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 222654, 10th, 6, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Self-emp-not-inc, 111129, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 26, Self-emp-not-inc, 137795, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 20, United-States, <=50K 33, Local-gov, 242150, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 50, United-States, <=50K 35, State-gov, 237873, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 44, Private, 367749, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, Mexico, <=50K 26, Private, 206600, Bachelors, 13, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, Mexico, <=50K 48, Federal-gov, 247043, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 187702, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 62, Private, 41718, 10th, 6, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 35, United-States, <=50K 37, Private, 151835, Prof-school, 15, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 18, Private, 118938, 11th, 7, Never-married, Sales, Own-child, White, Male, 0, 0, 18, United-States, <=50K 48, Private, 224870, HS-grad, 9, Divorced, Machine-op-inspct, Other-relative, Other, Female, 0, 0, 38, Ecuador, <=50K 45, Private, 178341, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 35, Private, 61343, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 35, Private, 36989, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 34, Self-emp-not-inc, 226296, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 51, United-States, <=50K 29, Private, 186624, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, Cuba, <=50K 19, Private, 172582, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 30, United-States, <=50K 53, State-gov, 227392, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 60, United-States, <=50K 49, Private, 187563, Some-college, 10, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 71, Private, 137499, HS-grad, 9, Widowed, Sales, Other-relative, White, Female, 0, 0, 16, United-States, <=50K 38, Private, 239397, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 36, Mexico, <=50K 39, Local-gov, 327164, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 23, Private, 140798, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, Self-emp-inc, 187450, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 52, Private, 194580, 5th-6th, 3, Divorced, Farming-fishing, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 372682, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 20, Private, 235442, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 30, Private, 128065, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 45, United-States, <=50K 56, Private, 91545, 10th, 6, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 36, United-States, <=50K 26, Private, 154604, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 36, Federal-gov, 192150, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 26, Local-gov, 216522, Bachelors, 13, Never-married, Prof-specialty, Own-child, Black, Female, 0, 0, 42, United-States, <=50K 58, Private, 156040, Assoc-acdm, 12, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 1848, 40, United-States, >50K 24, Private, 206861, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 97632, Some-college, 10, Divorced, Sales, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 32, United-States, <=50K 27, Private, 189530, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 35, United-States, <=50K 28, State-gov, 381789, Some-college, 10, Separated, Exec-managerial, Own-child, White, Male, 0, 2339, 40, United-States, <=50K 57, Self-emp-inc, 368797, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, State-gov, 41183, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 20, United-States, <=50K 50, Private, 191062, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 132963, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, United-States, <=50K 58, Private, 153551, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 27, Self-emp-not-inc, 66473, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 36, Private, 240323, HS-grad, 9, Separated, Sales, Unmarried, Black, Female, 0, 0, 17, United-States, <=50K 68, Local-gov, 242095, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 20051, 0, 40, United-States, >50K 33, Self-emp-inc, 128016, HS-grad, 9, Widowed, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 29526, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 18, United-States, <=50K 26, Private, 342953, HS-grad, 9, Separated, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 37, Private, 215476, HS-grad, 9, Never-married, Handlers-cleaners, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 53, Private, 231919, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, <=50K 32, Private, 52537, Some-college, 10, Never-married, Tech-support, Not-in-family, Black, Male, 0, 0, 38, United-States, <=50K 18, Private, 27920, 11th, 7, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 25, United-States, <=50K 53, Private, 153052, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Self-emp-not-inc, 199303, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 233369, Some-college, 10, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 345789, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 15024, 0, 50, United-States, >50K 60, Private, 238913, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 46, United-States, >50K 28, Self-emp-not-inc, 195607, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 245173, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 1669, 45, United-States, <=50K 37, Private, 138441, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 67467, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 102569, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 65, United-States, >50K 21, Private, 213341, 11th, 7, Married-spouse-absent, Handlers-cleaners, Own-child, White, Male, 0, 1762, 40, Dominican-Republic, <=50K 26, Private, 37202, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 47, Private, 140219, HS-grad, 9, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 298860, 12th, 8, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, United-States, <=50K 22, Private, 51362, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 16, United-States, <=50K 36, Private, 199947, Some-college, 10, Divorced, Machine-op-inspct, Own-child, White, Female, 0, 0, 30, United-States, <=50K 59, Self-emp-not-inc, 32552, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 48, United-States, <=50K 33, Private, 183845, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 38, El-Salvador, <=50K 33, Private, 181091, 10th, 6, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 35, England, <=50K 53, Self-emp-inc, 135643, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, Asian-Pac-Islander, Female, 0, 0, 50, South, <=50K 44, State-gov, 96249, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 3411, 0, 40, United-States, <=50K 55, Private, 181220, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 56, Private, 133025, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 54, Self-emp-not-inc, 124865, Some-college, 10, Divorced, Sales, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 51, Private, 45599, HS-grad, 9, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 194293, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 2463, 0, 38, United-States, <=50K 43, Private, 102180, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 44, Private, 121130, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 138768, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 50, United-States, <=50K 43, State-gov, 98989, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 26, State-gov, 126327, Assoc-acdm, 12, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 30, Private, 113364, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 0, 18, United-States, <=50K 30, Private, 326199, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 2580, 0, 40, United-States, <=50K 46, Private, 376789, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 15, United-States, <=50K 27, Private, 137063, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 26, Private, 279145, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 36, Private, 178815, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 8614, 0, 40, United-States, >50K 25, Self-emp-not-inc, 245369, HS-grad, 9, Separated, Craft-repair, Own-child, White, Male, 0, 0, 35, United-States, <=50K 30, Federal-gov, 49593, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 46, State-gov, 238648, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 7298, 0, 40, United-States, >50K 47, Private, 166181, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 0, 48, United-States, >50K 66, Self-emp-inc, 249043, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 5556, 0, 26, United-States, >50K 43, Private, 156403, 10th, 6, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 71, ?, 128529, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 36, Federal-gov, 186934, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 1848, 55, United-States, >50K 46, ?, 148489, HS-grad, 9, Married-spouse-absent, ?, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 44, Local-gov, 387770, Some-college, 10, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 15, United-States, <=50K 42, Private, 115511, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 39, Private, 201410, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1977, 45, Philippines, >50K 36, Private, 220585, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 60, Self-emp-not-inc, 282066, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 45, United-States, >50K 37, Private, 280966, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, >50K 26, Private, 291586, Bachelors, 13, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 20, United-States, <=50K 24, Private, 142227, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 17, ?, 104025, 11th, 7, Never-married, ?, Own-child, White, Male, 0, 0, 18, United-States, <=50K 45, Local-gov, 148254, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 54, Private, 170562, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 48, United-States, >50K 22, Private, 222490, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 30, United-States, <=50K 63, Local-gov, 57674, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 48, United-States, <=50K 22, Private, 233624, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 43, United-States, <=50K 27, Private, 42734, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 33, Private, 233107, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 33, Mexico, <=50K 64, Private, 143110, Bachelors, 13, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 50, Private, 195844, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 44, Self-emp-not-inc, 115896, Assoc-voc, 11, Widowed, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 303851, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 44, Private, 172475, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, Vietnam, <=50K 53, Self-emp-not-inc, 30008, 10th, 6, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 35, United-States, <=50K 33, Local-gov, 147921, HS-grad, 9, Widowed, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 34, Federal-gov, 172716, 12th, 8, Married-civ-spouse, Armed-Forces, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 155057, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 43, ?, 152569, Assoc-voc, 11, Widowed, ?, Not-in-family, White, Female, 0, 2339, 36, United-States, <=50K 80, Self-emp-not-inc, 132728, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 31, Private, 195136, Assoc-acdm, 12, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 40, Private, 377322, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, >50K 53, Local-gov, 293941, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, Private, 182123, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 44, United-States, <=50K 38, Private, 32528, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Private, 140206, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 48, Local-gov, 378221, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, Mexico, >50K 23, Private, 211601, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, Black, Female, 0, 0, 40, United-States, <=50K 31, Self-emp-not-inc, 119411, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 50, United-States, <=50K 52, Self-emp-not-inc, 240013, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 70, United-States, <=50K 24, Private, 95552, HS-grad, 9, Never-married, Tech-support, Own-child, White, Male, 0, 0, 40, United-States, <=50K 45, Self-emp-not-inc, 183710, 9th, 5, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 189382, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 52, Private, 380633, 5th-6th, 3, Widowed, Other-service, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 54, Private, 53407, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 150480, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 40, Private, 175674, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 28, Private, 375313, HS-grad, 9, Never-married, Tech-support, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 50, United-States, <=50K 21, ?, 278391, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 16, United-States, <=50K 23, Private, 212888, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, Self-emp-inc, 487085, 7th-8th, 4, Never-married, Craft-repair, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 22, Private, 174461, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 15, United-States, <=50K 55, Local-gov, 133201, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 71, Private, 77253, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 17, United-States, <=50K 47, Private, 141511, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 17, Self-emp-inc, 181608, 10th, 6, Never-married, Sales, Own-child, White, Male, 0, 0, 12, United-States, <=50K 31, Private, 127610, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 50, United-States, >50K 32, Private, 154571, Some-college, 10, Never-married, Other-service, Other-relative, Asian-Pac-Islander, Male, 0, 0, 40, ?, <=50K 46, Private, 33842, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 3103, 0, 40, United-States, >50K 27, Private, 150080, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 39, Federal-gov, 30916, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 50, United-States, >50K 40, Private, 151294, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 30, Private, 48829, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 1602, 30, United-States, <=50K 17, Private, 193769, 9th, 5, Never-married, Other-service, Unmarried, White, Male, 0, 0, 20, United-States, <=50K 33, Private, 277455, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 72, Private, 225780, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 34, Federal-gov, 436341, Some-college, 10, Married-AF-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 65, Private, 255386, HS-grad, 9, Never-married, Craft-repair, Other-relative, Asian-Pac-Islander, Male, 0, 0, 40, Cambodia, <=50K 36, Private, 174938, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1887, 50, United-States, >50K 32, Private, 174789, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 245628, Some-college, 10, Never-married, Adm-clerical, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 22, Private, 228752, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 354148, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 48, United-States, >50K 31, Private, 192900, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, Self-emp-not-inc, 190391, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 38, Private, 353263, Masters, 14, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 50, Italy, >50K 34, Private, 113198, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 28, United-States, <=50K 44, Private, 207578, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, >50K 27, Private, 93206, Some-college, 10, Never-married, Handlers-cleaners, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 50, Local-gov, 163998, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 44, United-States, >50K 47, Private, 111961, HS-grad, 9, Married-civ-spouse, Other-service, Wife, Black, Female, 0, 0, 30, United-States, <=50K 20, Private, 219122, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 111445, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 29, Federal-gov, 309778, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Local-gov, 223020, Assoc-voc, 11, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 32, United-States, <=50K 42, Private, 303155, Assoc-acdm, 12, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, ?, 41035, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 20, United-States, <=50K 68, Private, 159191, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, Local-gov, 244408, Some-college, 10, Never-married, Adm-clerical, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, Vietnam, <=50K 72, Self-emp-not-inc, 473748, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 30, United-States, <=50K 45, Federal-gov, 71823, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 20, United-States, <=50K 30, Local-gov, 83066, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 40, United-States, <=50K 33, Private, 150154, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 190786, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, >50K 56, Private, 178033, Some-college, 10, Widowed, Exec-managerial, Not-in-family, White, Male, 4416, 0, 60, United-States, <=50K 25, Self-emp-not-inc, 159909, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 190885, HS-grad, 9, Divorced, Priv-house-serv, Not-in-family, White, Female, 0, 0, 40, Guatemala, <=50K 25, Private, 243786, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 37, United-States, <=50K 31, State-gov, 124020, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 159016, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 38, United-States, <=50K 37, Private, 183800, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 58, Self-emp-not-inc, 193434, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 20, United-States, <=50K 26, Private, 245029, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 55, Private, 98746, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 50, Canada, >50K 46, Federal-gov, 140664, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 48, United-States, >50K 44, Private, 344920, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 1617, 20, United-States, <=50K 44, Private, 169980, 11th, 7, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 60, United-States, <=50K 28, State-gov, 155397, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 42, Private, 245317, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 41, Private, 74182, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 280570, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 64, Self-emp-not-inc, 30664, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 30, United-States, <=50K 20, Private, 109952, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 25, United-States, <=50K 45, Local-gov, 192793, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 243442, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, <=50K 36, Federal-gov, 106297, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Private, 328060, 9th, 5, Separated, Other-service, Unmarried, Other, Female, 0, 0, 40, Mexico, <=50K 33, Self-emp-not-inc, 48702, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 65, United-States, <=50K 51, Self-emp-not-inc, 111283, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 99999, 0, 35, United-States, >50K 36, Private, 484024, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 208470, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 172032, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Husband, White, Male, 7298, 0, 51, United-States, >50K 40, Private, 29927, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 45, England, <=50K 46, Private, 98012, Assoc-voc, 11, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Self-emp-not-inc, 108468, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 30, Private, 207301, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 1980, 40, United-States, <=50K 26, Private, 168403, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 66935, Bachelors, 13, Never-married, Other-service, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 35, Self-emp-not-inc, 42044, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 184806, Prof-school, 15, Never-married, Prof-specialty, Other-relative, White, Male, 0, 0, 50, United-States, <=50K 39, Private, 1455435, Assoc-acdm, 12, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Self-emp-not-inc, 445382, Some-college, 10, Divorced, Other-service, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 278576, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 60, United-States, >50K 79, Self-emp-not-inc, 84979, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 20, United-States, >50K 36, Private, 659504, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 45, United-States, >50K 44, Private, 136986, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, >50K 23, Private, 278107, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 1573, 30, United-States, <=50K 27, Private, 96219, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 46, Self-emp-not-inc, 131091, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 1902, 40, United-States, >50K 58, Private, 205410, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 416745, Assoc-acdm, 12, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 36, Private, 180667, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1887, 60, United-States, >50K 21, Private, 72119, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 41, State-gov, 108945, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Female, 14344, 0, 40, United-States, >50K 49, Federal-gov, 195949, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 101345, Bachelors, 13, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, >50K 29, Private, 439263, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 35, Peru, <=50K 63, Private, 213095, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 29, Federal-gov, 59932, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 65, Private, 172815, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 40915, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 42, Private, 139012, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Taiwan, >50K 44, Private, 121781, Some-college, 10, Divorced, Adm-clerical, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 37, United-States, <=50K 51, ?, 130667, HS-grad, 9, Separated, ?, Not-in-family, Black, Male, 0, 0, 6, United-States, <=50K 41, Self-emp-not-inc, 147110, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 25, United-States, <=50K 22, Local-gov, 237811, Assoc-acdm, 12, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 35, Haiti, <=50K 36, ?, 128640, Some-college, 10, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 25, United-States, <=50K 18, Private, 111476, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 33, Local-gov, 289716, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Local-gov, 141944, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 38, United-States, >50K 49, Private, 323773, 11th, 7, Married-civ-spouse, Priv-house-serv, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 41, State-gov, 176663, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 52, Private, 155233, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 143327, Some-college, 10, Separated, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 53, Federal-gov, 177212, Some-college, 10, Never-married, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 45, Self-emp-not-inc, 123088, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 30, Local-gov, 47085, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, Private, 102106, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 235894, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 71, Self-emp-not-inc, 172046, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 20, Self-emp-not-inc, 197207, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 26, Private, 152452, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 50, United-States, <=50K 34, Private, 172928, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 65, United-States, <=50K 36, ?, 214896, 9th, 5, Divorced, ?, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 49, Private, 116338, HS-grad, 9, Separated, Prof-specialty, Unmarried, White, Female, 0, 653, 60, United-States, <=50K 48, Private, 276664, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 50, United-States, >50K 22, Private, 59924, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 194141, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 1617, 40, United-States, <=50K 51, Private, 95128, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 292504, Some-college, 10, Married-spouse-absent, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 32, Self-emp-inc, 45796, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 42, Private, 119359, Prof-school, 15, Married-civ-spouse, Sales, Wife, Amer-Indian-Eskimo, Female, 15024, 0, 40, South, >50K 52, State-gov, 104280, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 50, United-States, <=50K 57, Private, 172291, HS-grad, 9, Divorced, Adm-clerical, Other-relative, Black, Female, 0, 0, 40, United-States, <=50K 35, Private, 180988, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 39, United-States, <=50K 52, Private, 110748, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 59, ?, 556688, 9th, 5, Divorced, ?, Not-in-family, White, Female, 0, 0, 12, United-States, <=50K 36, Private, 22494, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 267859, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, Cuba, >50K 67, Local-gov, 256821, HS-grad, 9, Divorced, Protective-serv, Not-in-family, Black, Male, 0, 0, 20, United-States, <=50K 31, Self-emp-not-inc, 117346, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 48, United-States, <=50K 31, Private, 62374, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 28, Private, 314659, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 42, United-States, <=50K 72, ?, 114761, 7th-8th, 4, Widowed, ?, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 36, Private, 93225, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 58, Self-emp-not-inc, 165315, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 35, United-States, >50K 56, Private, 124771, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 27408, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 198841, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 44, Private, 271792, Bachelors, 13, Married-spouse-absent, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 64289, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 183390, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 240771, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 4386, 0, 50, United-States, >50K 30, Private, 234919, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 40, El-Salvador, <=50K 20, Private, 88231, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 154422, Some-college, 10, Never-married, Adm-clerical, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 37, Private, 119098, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 53, State-gov, 151580, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 4386, 0, 40, United-States, >50K 54, Private, 118793, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, <=50K 32, ?, 30499, Bachelors, 13, Divorced, ?, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 34, ?, 166545, Some-college, 10, Married-civ-spouse, ?, Wife, White, Female, 7688, 0, 6, United-States, >50K 30, Private, 271710, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 7298, 0, 50, United-States, >50K 43, State-gov, 308498, HS-grad, 9, Married-spouse-absent, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 48, Private, 172695, Assoc-voc, 11, Divorced, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 42, Self-emp-not-inc, 29962, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 48, United-States, <=50K 62, Private, 200332, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 291702, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 67234, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 45, Private, 168038, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 32, United-States, <=50K 34, Private, 137814, Some-college, 10, Separated, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 64, Private, 126233, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 20, United-States, <=50K 42, Self-emp-not-inc, 79036, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 65, United-States, <=50K 60, Self-emp-not-inc, 327474, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 70, United-States, <=50K 44, Private, 145160, HS-grad, 9, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 58, United-States, <=50K 67, ?, 37092, 7th-8th, 4, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 4, United-States, <=50K 45, Private, 129387, Assoc-acdm, 12, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 40, ?, <=50K 53, Self-emp-not-inc, 33304, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 38, United-States, >50K 37, Private, 359001, Assoc-voc, 11, Married-civ-spouse, Transport-moving, Husband, White, Male, 15024, 0, 50, United-States, >50K 32, ?, 143162, 10th, 6, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 133515, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 28, Private, 168901, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Taiwan, <=50K 55, Private, 750972, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 41, United-States, <=50K 58, Private, 142924, Masters, 14, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 24, United-States, >50K 74, Self-emp-inc, 228075, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 20051, 0, 25, United-States, >50K 27, Private, 91189, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 290609, HS-grad, 9, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 22, ?, 31102, Some-college, 10, Never-married, ?, Own-child, Asian-Pac-Islander, Female, 0, 0, 4, South, <=50K 44, Self-emp-not-inc, 216921, 10th, 6, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 70, United-States, <=50K 23, Private, 120046, Assoc-acdm, 12, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 324629, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, Yugoslavia, <=50K 45, Private, 81132, Some-college, 10, Married-civ-spouse, Tech-support, Husband, Asian-Pac-Islander, Male, 0, 0, 55, United-States, >50K 29, Private, 160279, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 229732, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 61, Local-gov, 144723, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 60, United-States, >50K 29, Private, 148431, Assoc-acdm, 12, Married-civ-spouse, Sales, Wife, Other, Female, 7688, 0, 45, United-States, >50K 22, Private, 160398, Some-college, 10, Never-married, Sales, Other-relative, White, Male, 0, 0, 38, United-States, <=50K 28, Private, 129460, 9th, 5, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, El-Salvador, <=50K 30, Private, 252752, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 58222, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, United-States, <=50K 28, ?, 424884, 10th, 6, Separated, ?, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 45, Private, 114459, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 19, ?, 46400, Some-college, 10, Never-married, ?, Not-in-family, White, Female, 0, 0, 24, United-States, <=50K 42, Private, 223934, Assoc-acdm, 12, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 84119, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 159123, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 23, Private, 195532, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 50, Private, 191299, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 40, Private, 198316, 10th, 6, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 57, Private, 162301, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 35, Private, 143152, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 3908, 0, 27, United-States, <=50K 24, Private, 92609, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 45, United-States, <=50K 27, Private, 247819, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 27, Local-gov, 229223, Some-college, 10, Never-married, Protective-serv, Own-child, White, Female, 0, 0, 40, United-States, >50K 45, Self-emp-inc, 142719, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 80, Private, 86111, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 30, United-States, <=50K 23, State-gov, 35633, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 46, Private, 164749, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 607848, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 50, Private, 173630, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 90, Private, 311184, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 20, ?, <=50K 55, Private, 49737, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 72, Private, 183616, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 50, England, <=50K 65, Private, 129426, Some-college, 10, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 454915, 10th, 6, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, State-gov, 55568, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 29874, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 393715, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 50, Private, 143953, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 65, United-States, >50K 54, Private, 90363, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Private, 53727, Masters, 14, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 30, Private, 130021, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 2829, 0, 40, United-States, <=50K 50, Private, 173630, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 35, United-States, <=50K 28, Private, 410351, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 34, Private, 399386, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 53, United-States, <=50K 55, Private, 157932, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 133061, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 19, ?, 46400, Some-college, 10, Never-married, ?, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 21, Private, 107895, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 39, Private, 63021, Some-college, 10, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 43, Private, 186144, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Local-gov, 27959, HS-grad, 9, Never-married, Other-service, Unmarried, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 26, Private, 179569, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, State-gov, 101299, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 31, State-gov, 113129, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 65, United-States, <=50K 32, Private, 316470, 5th-6th, 3, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, Mexico, <=50K 60, Self-emp-not-inc, 89884, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 41, Private, 32121, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 21, Private, 315303, Some-college, 10, Never-married, Other-service, Own-child, Black, Male, 0, 0, 20, United-States, <=50K 27, Private, 254500, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 36, United-States, <=50K 33, Private, 419895, 5th-6th, 3, Divorced, Handlers-cleaners, Unmarried, White, Male, 0, 0, 40, Mexico, <=50K 43, Private, 159549, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 160786, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1902, 40, United-States, >50K 18, Self-emp-not-inc, 258474, 10th, 6, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 48, Self-emp-not-inc, 370119, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Private, 50837, 7th-8th, 4, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 58, Private, 137506, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 548256, 12th, 8, Married-civ-spouse, Transport-moving, Husband, Black, Male, 7688, 0, 40, United-States, >50K 42, Local-gov, 175642, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 99999, 0, 40, United-States, >50K 24, Private, 183594, HS-grad, 9, Never-married, Adm-clerical, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 341353, Bachelors, 13, Never-married, Other-service, Other-relative, White, Male, 0, 0, 15, United-States, <=50K 43, Self-emp-inc, 247981, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 5455, 0, 50, United-States, <=50K 34, Private, 193565, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 39606, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 51, Self-emp-not-inc, 127149, 11th, 7, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 45, United-States, >50K 31, ?, 233371, HS-grad, 9, Married-civ-spouse, ?, Wife, Black, Female, 0, 0, 45, United-States, <=50K 49, Self-emp-not-inc, 182752, Doctorate, 16, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 35, United-States, >50K 26, Private, 269060, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 179949, HS-grad, 9, Divorced, Transport-moving, Unmarried, Black, Female, 0, 0, 20, United-States, <=50K 22, Federal-gov, 32950, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 1902, 37, United-States, <=50K 26, Private, 160445, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 223999, 9th, 5, Married-civ-spouse, Other-service, Husband, White, Male, 0, 1848, 40, United-States, >50K 39, Private, 81487, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 625, 40, United-States, <=50K 23, Private, 314539, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 62, ?, 337721, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 8, United-States, <=50K 42, Local-gov, 100793, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 39, Federal-gov, 255407, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Federal-gov, 92775, Assoc-voc, 11, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, Self-emp-not-inc, 33308, Some-college, 10, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 68, State-gov, 493363, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 20, United-States, <=50K 30, ?, 159589, Masters, 14, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 46, United-States, >50K 32, Private, 107218, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 25, Private, 123586, Some-college, 10, Never-married, Adm-clerical, Unmarried, Other, Male, 0, 0, 40, United-States, <=50K 53, Private, 158352, 5th-6th, 3, Married-civ-spouse, Other-service, Other-relative, White, Female, 0, 0, 24, Italy, <=50K 38, Private, 76317, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 62, ?, 176753, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 122346, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 463194, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 162228, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 43, State-gov, 115005, HS-grad, 9, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, State-gov, 183285, Some-college, 10, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 36, United-States, <=50K 34, Private, 169605, 10th, 6, Separated, Other-service, Unmarried, White, Female, 0, 0, 36, United-States, <=50K 24, Private, 450695, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 35, United-States, <=50K 44, Local-gov, 124692, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, >50K 19, Private, 63918, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 102569, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Private, 289309, Some-college, 10, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 45, Private, 101825, HS-grad, 9, Widowed, Sales, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 43, Private, 206833, HS-grad, 9, Separated, Handlers-cleaners, Unmarried, Black, Female, 0, 0, 45, United-States, <=50K 22, ?, 77873, 9th, 5, Never-married, ?, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 50, Private, 145333, Doctorate, 16, Divorced, Prof-specialty, Other-relative, White, Male, 10520, 0, 50, United-States, >50K 72, ?, 194548, Some-college, 10, Married-spouse-absent, ?, Not-in-family, White, Male, 0, 0, 3, United-States, <=50K 29, Private, 206351, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 198200, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 24, Private, 140001, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 35, El-Salvador, <=50K 22, ?, 287988, Some-college, 10, Never-married, ?, Not-in-family, White, Male, 0, 0, 15, United-States, <=50K 21, Private, 143604, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 30, Self-emp-not-inc, 146161, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1887, 50, United-States, >50K 37, Private, 196529, Some-college, 10, Widowed, Other-service, Not-in-family, White, Female, 2354, 0, 40, ?, <=50K 74, Self-emp-not-inc, 192413, Prof-school, 15, Divorced, Prof-specialty, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 70, Self-emp-not-inc, 139889, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 2653, 0, 70, United-States, <=50K 27, Private, 104917, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Local-gov, 161478, Bachelors, 13, Divorced, Adm-clerical, Unmarried, Asian-Pac-Islander, Female, 0, 0, 46, United-States, <=50K 30, Private, 35644, 11th, 7, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 50, United-States, <=50K 29, Local-gov, 116751, Assoc-voc, 11, Divorced, Protective-serv, Unmarried, White, Male, 0, 0, 56, United-States, <=50K 18, Private, 238867, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 1602, 40, United-States, <=50K 31, Private, 265706, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 40, United-States, >50K 39, State-gov, 179668, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 70, United-States, <=50K 21, Private, 57951, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 31, Private, 176711, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 38, United-States, <=50K 33, Local-gov, 368675, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 216149, Prof-school, 15, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 70, United-States, >50K 29, Private, 173851, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 90705, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 1485, 40, United-States, <=50K 52, State-gov, 216342, Bachelors, 13, Widowed, Exec-managerial, Unmarried, White, Female, 0, 0, 55, United-States, <=50K 35, Private, 140752, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 33, Private, 116508, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, ?, 224361, 9th, 5, Divorced, ?, Unmarried, White, Female, 0, 0, 5, Cuba, <=50K 43, Private, 180303, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 50, United-States, >50K 66, ?, 196736, 1st-4th, 2, Never-married, ?, Not-in-family, Black, Male, 0, 0, 30, United-States, <=50K 51, Local-gov, 110327, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 185607, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 17, Local-gov, 244856, 11th, 7, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 198068, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 97136, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 19, Self-emp-inc, 164658, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 60, United-States, <=50K 54, Private, 235693, 11th, 7, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 45, Private, 197038, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 47, Local-gov, 97419, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 49, Self-emp-not-inc, 208872, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 1672, 98, United-States, <=50K 32, Private, 205528, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 28, Self-emp-inc, 146042, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 39, Self-emp-inc, 222641, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Self-emp-inc, 376936, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 42, Local-gov, 138077, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 38, United-States, >50K 24, Private, 155913, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 44, United-States, <=50K 45, Private, 36006, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 19, Private, 214678, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, United-States, <=50K 46, Private, 369538, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 50, Private, 166565, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 257043, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 42, United-States, <=50K 47, Self-emp-inc, 181130, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 50, United-States, >50K 69, ?, 254834, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 10605, 0, 10, United-States, >50K 43, Self-emp-not-inc, 38876, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 29, Private, 187073, Bachelors, 13, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 43, Federal-gov, 156996, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 2415, 55, ?, >50K 90, Private, 313749, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 10, United-States, <=50K 41, Private, 331651, Prof-school, 15, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 50, Japan, >50K 24, Private, 243368, Preschool, 1, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 36, Mexico, <=50K 24, Private, 32921, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 50, United-States, <=50K 24, Private, 117167, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 53, United-States, <=50K 35, Private, 401930, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 1887, 42, United-States, >50K 30, Private, 114691, Bachelors, 13, Never-married, Adm-clerical, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 99385, Bachelors, 13, Separated, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 19, Local-gov, 210308, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 1721, 30, United-States, <=50K 39, Private, 252327, 9th, 5, Separated, Craft-repair, Own-child, White, Male, 0, 0, 35, Mexico, <=50K 43, Private, 90582, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 190194, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 65, Private, 264188, HS-grad, 9, Widowed, Sales, Not-in-family, White, Female, 0, 0, 24, United-States, <=50K 34, Private, 243776, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 67065, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Self-emp-not-inc, 204209, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 60, United-States, <=50K 24, Private, 226668, HS-grad, 9, Never-married, Other-service, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 35, United-States, <=50K 34, Self-emp-inc, 174215, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 4787, 0, 45, France, >50K 33, Private, 315143, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, Cuba, >50K 37, Private, 118681, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 38, Puerto-Rico, <=50K 39, Self-emp-not-inc, 208109, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, >50K 58, Private, 116901, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 36, Self-emp-not-inc, 405644, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, Mexico, <=50K 33, Federal-gov, 293550, Some-college, 10, Married-civ-spouse, Tech-support, Wife, White, Female, 4064, 0, 40, United-States, <=50K 42, Local-gov, 328581, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, <=50K 31, Private, 217962, Some-college, 10, Never-married, Protective-serv, Other-relative, Black, Male, 0, 0, 40, ?, <=50K 57, Private, 158827, HS-grad, 9, Separated, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 67, Federal-gov, 65475, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Private, 159709, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 140474, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 43, Private, 144778, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, Italy, >50K 39, Self-emp-not-inc, 83242, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 36, Private, 143385, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Local-gov, 167544, Assoc-acdm, 12, Divorced, Other-service, Unmarried, White, Female, 0, 0, 13, United-States, <=50K 25, Private, 122175, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 378747, 10th, 6, Separated, Transport-moving, Unmarried, Black, Male, 0, 0, 45, United-States, >50K 24, Private, 230475, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 44, United-States, <=50K 50, Self-emp-inc, 120781, Bachelors, 13, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 0, 60, South, >50K 70, Private, 206232, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, <=50K 61, Private, 298400, Bachelors, 13, Divorced, Sales, Not-in-family, Black, Male, 4787, 0, 48, United-States, >50K 51, Federal-gov, 163671, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 40, United-States, <=50K 38, Self-emp-not-inc, 140583, Masters, 14, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 70, United-States, <=50K 51, Private, 137253, HS-grad, 9, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, >50K 28, Private, 246974, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 66, Self-emp-not-inc, 182470, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 25, United-States, >50K 57, Self-emp-inc, 107617, HS-grad, 9, Separated, Farming-fishing, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 44, Self-emp-inc, 116358, Bachelors, 13, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 0, 50, ?, >50K 29, Private, 250819, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 196508, Some-college, 10, Never-married, Sales, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 42, Private, 367533, 10th, 6, Married-civ-spouse, Craft-repair, Own-child, Other, Male, 0, 0, 43, United-States, >50K 74, Private, 188709, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 50, United-States, >50K 50, Private, 271160, Some-college, 10, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 65, Private, 173674, HS-grad, 9, Divorced, Other-service, Other-relative, White, Female, 0, 0, 14, United-States, <=50K 64, ?, 257790, HS-grad, 9, Divorced, ?, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 44, Private, 322391, 11th, 7, Separated, Other-service, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 34, Private, 209691, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 4386, 0, 50, United-States, >50K 17, Private, 104232, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 10, United-States, <=50K 17, ?, 86786, 10th, 6, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 88233, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 32, Private, 240888, Assoc-acdm, 12, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 54, Private, 169719, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 3103, 0, 40, United-States, >50K 20, Private, 129240, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 23, Private, 160968, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 10, United-States, <=50K 34, Private, 236861, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 45, United-States, <=50K 30, Private, 109282, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 20, United-States, <=50K 32, Private, 215047, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 115932, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, Ireland, >50K 28, Private, 55360, Some-college, 10, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 44, Private, 224658, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 29, Local-gov, 376302, Assoc-voc, 11, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 35, Nicaragua, >50K 28, Private, 183597, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 594, 0, 50, Germany, <=50K 37, Private, 115289, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, Self-emp-inc, 258883, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 69132, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 207301, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 37, Private, 179671, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 66, Self-emp-not-inc, 140456, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 19, Private, 327397, HS-grad, 9, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 30, United-States, <=50K 60, Private, 200235, Assoc-voc, 11, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 54, Self-emp-not-inc, 108435, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 2829, 0, 30, United-States, <=50K 47, Private, 195978, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 47, Private, 329144, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 48, United-States, >50K 48, Self-emp-inc, 250674, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 57, ?, 176897, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 60, United-States, <=50K 50, Self-emp-inc, 132716, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, Germany, >50K 62, Private, 174201, 9th, 5, Widowed, Other-service, Unmarried, Black, Female, 0, 0, 25, United-States, <=50K 45, Private, 167617, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Local-gov, 254949, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 62, Private, 319582, HS-grad, 9, Widowed, Sales, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 25, Private, 248990, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Guatemala, <=50K 49, Private, 144396, 11th, 7, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 32, State-gov, 200469, Some-college, 10, Never-married, Protective-serv, Unmarried, Black, Female, 3887, 0, 40, United-States, <=50K 25, Federal-gov, 55636, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 39, Private, 185624, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, <=50K 27, Local-gov, 125442, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 43, Private, 160943, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 40, United-States, >50K 30, Private, 243841, HS-grad, 9, Divorced, Other-service, Other-relative, Asian-Pac-Islander, Female, 0, 0, 40, South, <=50K 21, Private, 34616, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 33, Private, 235847, Prof-school, 15, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 33, Private, 174789, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 33, Private, 280111, 11th, 7, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 38, United-States, <=50K 70, Private, 236055, 7th-8th, 4, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 25, Private, 237865, Some-college, 10, Never-married, Other-service, Own-child, Black, Male, 0, 0, 42, United-States, <=50K 17, Private, 194612, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 25, United-States, <=50K 20, Private, 173851, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 372483, Some-college, 10, Never-married, Other-service, Other-relative, Black, Male, 0, 0, 35, United-States, <=50K 71, Federal-gov, 422149, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 20051, 0, 40, United-States, >50K 31, Private, 174201, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 272618, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, <=50K 52, Private, 74660, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 201481, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 175232, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 25, Private, 336440, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 46645, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 9, United-States, <=50K 48, State-gov, 31141, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 1902, 40, United-States, >50K 53, Private, 281425, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Self-emp-not-inc, 31510, Assoc-acdm, 12, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 44, Private, 310255, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, >50K 32, Federal-gov, 82393, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 56, United-States, >50K 59, Self-emp-not-inc, 190514, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 20, United-States, <=50K 49, Private, 165513, Some-college, 10, Divorced, Handlers-cleaners, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 65, ?, 178931, HS-grad, 9, Married-civ-spouse, ?, Husband, Amer-Indian-Eskimo, Male, 3818, 0, 40, United-States, <=50K 31, Private, 226696, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 53, Private, 195813, 5th-6th, 3, Married-civ-spouse, Craft-repair, Husband, Other, Male, 5178, 0, 40, Puerto-Rico, >50K 44, Private, 165815, 9th, 5, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 123983, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 55, Japan, >50K 36, Private, 235371, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 147258, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, >50K 63, ?, 222289, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 7688, 0, 54, United-States, >50K 67, Self-emp-inc, 171564, HS-grad, 9, Married-civ-spouse, Prof-specialty, Wife, White, Female, 20051, 0, 30, England, >50K 29, Private, 255949, Bachelors, 13, Never-married, Sales, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 52, Private, 186272, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 282872, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1628, 40, United-States, <=50K 21, Private, 111676, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 199501, Some-college, 10, Divorced, Exec-managerial, Unmarried, Black, Female, 0, 0, 38, United-States, <=50K 24, Private, 151443, HS-grad, 9, Never-married, Machine-op-inspct, Other-relative, Black, Female, 0, 0, 30, United-States, <=50K 31, Private, 145935, HS-grad, 9, Never-married, Exec-managerial, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 54, Federal-gov, 230387, HS-grad, 9, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 44, Private, 127592, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 210828, Some-college, 10, Never-married, Handlers-cleaners, Own-child, Other, Male, 0, 0, 30, United-States, <=50K 41, Private, 297186, HS-grad, 9, Married-civ-spouse, Transport-moving, Wife, White, Female, 0, 0, 40, United-States, <=50K 37, Self-emp-inc, 116554, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 70, United-States, <=50K 30, Private, 144593, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 40, ?, <=50K 26, State-gov, 147719, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 20, India, <=50K 68, Self-emp-not-inc, 89011, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, Canada, <=50K 31, Private, 38158, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 178686, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 80, ?, 172826, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 8, United-States, <=50K 26, Private, 155752, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 63, Private, 100099, 9th, 5, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 231688, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 20, United-States, <=50K 30, ?, 147215, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 30, United-States, <=50K 42, Self-emp-inc, 50122, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 64, Federal-gov, 86837, Assoc-acdm, 12, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, >50K 32, Private, 113364, Bachelors, 13, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 289390, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 47, United-States, <=50K 73, Private, 77884, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 32, Private, 390157, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 53, Private, 89587, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 7298, 0, 45, United-States, >50K 58, Private, 234328, Bachelors, 13, Divorced, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Local-gov, 365430, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 5178, 0, 40, United-States, >50K 24, Private, 410439, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 15, United-States, <=50K 53, Private, 129525, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 23, Private, 166527, Some-college, 10, Never-married, Exec-managerial, Own-child, Other, Female, 0, 0, 40, United-States, <=50K 42, ?, 109912, Assoc-acdm, 12, Never-married, ?, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 210906, HS-grad, 9, Married-civ-spouse, Exec-managerial, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 405284, Bachelors, 13, Never-married, Other-service, Own-child, White, Female, 0, 0, 35, United-States, <=50K 28, Private, 138269, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 25429, 12th, 8, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 45, Private, 231672, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 26, Private, 258550, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 268147, 9th, 5, Never-married, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 54411, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 50, ?, <=50K 54, Private, 37289, Masters, 14, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 55, United-States, >50K 23, Private, 157951, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 43, Self-emp-inc, 225165, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, >50K 37, Private, 238049, 9th, 5, Never-married, Priv-house-serv, Not-in-family, White, Female, 0, 0, 30, El-Salvador, <=50K 31, Private, 197252, 7th-8th, 4, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Mexico, <=50K 56, Self-emp-inc, 216636, 12th, 8, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1651, 40, United-States, <=50K 25, Private, 183575, 11th, 7, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 19752, 11th, 7, Never-married, Other-service, Own-child, Black, Female, 0, 0, 25, United-States, <=50K 37, Private, 103925, HS-grad, 9, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 68, United-States, <=50K 60, Private, 31577, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 59, Federal-gov, 61298, Bachelors, 13, Married-spouse-absent, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 59, Federal-gov, 190541, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Self-emp-not-inc, 366089, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 40, United-States, >50K 28, ?, 389857, HS-grad, 9, Married-civ-spouse, ?, Other-relative, White, Male, 0, 0, 16, United-States, <=50K 33, ?, 192644, HS-grad, 9, Never-married, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 216129, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 1408, 50, United-States, <=50K 29, Private, 51944, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 4386, 0, 40, United-States, >50K 33, Self-emp-not-inc, 67482, Assoc-voc, 11, Divorced, Other-service, Unmarried, White, Female, 0, 0, 99, United-States, <=50K 29, ?, 108775, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, Dominican-Republic, <=50K 23, State-gov, 279243, Some-college, 10, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 278391, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 25, Nicaragua, <=50K 60, Private, 349898, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 44, United-States, <=50K 44, Private, 219441, 10th, 6, Never-married, Sales, Unmarried, Other, Female, 0, 0, 35, Dominican-Republic, <=50K 18, Private, 173255, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 1055, 0, 25, United-States, <=50K 52, Federal-gov, 29623, 12th, 8, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 31, Private, 217460, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 30, Private, 163604, Bachelors, 13, Widowed, Prof-specialty, Unmarried, White, Female, 0, 0, 55, United-States, >50K 33, Private, 163110, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 3781, 0, 40, United-States, <=50K 20, Private, 238685, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 27, ?, 251854, Bachelors, 13, Married-civ-spouse, ?, Wife, Black, Female, 0, 0, 35, ?, >50K 33, Private, 213308, Assoc-voc, 11, Separated, Adm-clerical, Own-child, Black, Female, 0, 0, 50, United-States, <=50K 25, Private, 193773, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 35, United-States, <=50K 63, Private, 114011, HS-grad, 9, Separated, Craft-repair, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 63, Self-emp-not-inc, 52144, Some-college, 10, Widowed, Exec-managerial, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 43, Private, 347934, HS-grad, 9, Separated, Sales, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 58, Private, 293399, 11th, 7, Widowed, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 70, ?, 118630, Assoc-voc, 11, Widowed, ?, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 35, Private, 127306, Assoc-voc, 11, Never-married, Adm-clerical, Own-child, White, Female, 14344, 0, 40, United-States, >50K 42, Private, 366180, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 20, Local-gov, 188950, Some-college, 10, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 25, United-States, <=50K 35, Private, 189382, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 62, Private, 24515, 9th, 5, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 283116, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Female, 1506, 0, 50, United-States, <=50K 43, Self-emp-not-inc, 182217, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 35, United-States, <=50K 19, Private, 552354, 12th, 8, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 163021, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 61885, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 50, United-States, >50K 36, Self-emp-not-inc, 182898, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 40, United-States, >50K 45, Private, 183092, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 48, Private, 30289, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 30, United-States, <=50K 29, Private, 77572, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 48, State-gov, 118330, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 5178, 0, 40, United-States, >50K 36, Private, 469056, HS-grad, 9, Divorced, Sales, Unmarried, Black, Female, 0, 0, 25, United-States, <=50K 58, Private, 145574, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 302041, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 59, Private, 32552, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 4, United-States, <=50K 42, Private, 185413, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Federal-gov, 26543, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Federal-gov, 163870, Some-college, 10, Never-married, Armed-Forces, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 240063, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 25, United-States, <=50K 48, Private, 208748, 5th-6th, 3, Divorced, Machine-op-inspct, Unmarried, Other, Female, 0, 0, 40, Dominican-Republic, <=50K 32, Local-gov, 84119, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 84130, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, >50K 66, Local-gov, 261062, Masters, 14, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Local-gov, 336010, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 32, United-States, <=50K 52, Private, 389270, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 35, United-States, >50K 17, Private, 138293, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 15, United-States, <=50K 35, Private, 240389, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 43, United-States, >50K 39, Private, 190297, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 55, United-States, >50K 21, ?, 170070, Some-college, 10, Never-married, ?, Not-in-family, White, Female, 0, 0, 10, United-States, <=50K 24, Private, 149457, Some-college, 10, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 81534, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 84, Japan, >50K 25, Private, 378322, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 2001, 50, United-States, <=50K 29, Federal-gov, 196912, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 56, Private, 116143, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 5178, 0, 44, United-States, >50K 34, Self-emp-not-inc, 80933, HS-grad, 9, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 64, Local-gov, 190660, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 27, Private, 120155, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 39, United-States, <=50K 47, Private, 167159, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 4650, 0, 40, United-States, <=50K 36, Private, 58343, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 3103, 0, 42, United-States, >50K 44, Federal-gov, 161240, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 126402, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, Black, Female, 0, 0, 60, United-States, <=50K 23, Private, 148709, HS-grad, 9, Married-civ-spouse, Adm-clerical, Other-relative, White, Female, 0, 0, 35, United-States, <=50K 45, Local-gov, 318280, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 50, United-States, >50K 31, Local-gov, 80058, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 64, United-States, <=50K 45, Private, 274689, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 42, Private, 157367, HS-grad, 9, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 35, ?, <=50K 33, Private, 217460, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Local-gov, 33727, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, <=50K 30, Self-emp-not-inc, 166961, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 20, United-States, >50K 25, Private, 146117, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 42, United-States, <=50K 33, Private, 160216, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 32, ?, <=50K 70, Self-emp-not-inc, 124449, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 2246, 8, United-States, >50K 22, Private, 50163, 9th, 5, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 235271, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Private, 121124, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 43, Self-emp-not-inc, 144218, 12th, 8, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 37, Private, 94334, 7th-8th, 4, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 25, United-States, <=50K 59, Self-emp-inc, 169982, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 60, United-States, >50K 51, Self-emp-not-inc, 35295, HS-grad, 9, Never-married, Farming-fishing, Unmarried, White, Male, 0, 0, 45, United-States, <=50K 47, Private, 133969, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 2885, 0, 65, Japan, <=50K 36, Private, 35429, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 73, Local-gov, 205580, 5th-6th, 3, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 6, United-States, <=50K 32, Local-gov, 177794, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 167474, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 51, Local-gov, 35211, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 20, Private, 117244, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 57, Private, 194850, Some-college, 10, Married-civ-spouse, Other-service, Husband, Other, Male, 0, 0, 40, Mexico, <=50K 19, Private, 144911, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 45, Private, 197240, 12th, 8, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 40, United-States, >50K 55, Private, 101338, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 60, Private, 148522, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 19, Private, 97261, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 166606, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 229414, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 30, United-States, <=50K 34, Local-gov, 209213, Bachelors, 13, Never-married, Prof-specialty, Other-relative, Black, Male, 0, 0, 15, United-States, <=50K 26, Private, 291968, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 40, United-States, >50K 73, Federal-gov, 127858, Some-college, 10, Widowed, Tech-support, Not-in-family, White, Female, 3273, 0, 40, United-States, <=50K 27, Private, 302406, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, <=50K 37, Self-emp-not-inc, 29054, Assoc-voc, 11, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 84, United-States, <=50K 73, Self-emp-not-inc, 336007, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Federal-gov, 349230, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 1848, 40, United-States, >50K 36, Local-gov, 101481, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 54, Self-emp-not-inc, 46704, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, >50K 49, Private, 233639, 11th, 7, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 50, United-States, <=50K 68, Local-gov, 31725, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 54850, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 1590, 50, United-States, <=50K 30, Private, 293512, Assoc-voc, 11, Never-married, Prof-specialty, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 28, Private, 375655, Bachelors, 13, Never-married, Sales, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 28, Private, 105817, 11th, 7, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 25, Local-gov, 203408, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 162302, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 40, Private, 163455, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 55, United-States, >50K 32, Local-gov, 100135, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 60, ?, 41517, 11th, 7, Married-spouse-absent, ?, Unmarried, Black, Female, 0, 0, 20, United-States, <=50K 18, Private, 102182, 12th, 8, Never-married, Priv-house-serv, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 36, Private, 414683, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 40, United-States, <=50K 26, Private, 194352, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 194096, HS-grad, 9, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 45, United-States, <=50K 90, Local-gov, 153602, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 6767, 0, 40, United-States, <=50K 20, Private, 215495, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, Mexico, <=50K 27, Private, 164607, Bachelors, 13, Separated, Tech-support, Own-child, White, Male, 0, 0, 50, United-States, <=50K 58, Local-gov, 34878, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 37, Private, 126569, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 40, United-States, >50K 65, ?, 315728, HS-grad, 9, Widowed, ?, Unmarried, White, Female, 2329, 0, 75, United-States, <=50K 28, Private, 22422, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Local-gov, 178222, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 45, Local-gov, 56841, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Private, 300275, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 69, Local-gov, 197288, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 35, United-States, <=50K 58, Self-emp-not-inc, 157786, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 110684, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 20, United-States, <=50K 58, Self-emp-not-inc, 140729, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 35, United-States, <=50K 53, Federal-gov, 90127, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 60, United-States, >50K 44, Self-emp-inc, 37997, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 31, Private, 61308, 10th, 6, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 171199, Bachelors, 13, Divorced, Machine-op-inspct, Unmarried, Other, Female, 0, 0, 40, Puerto-Rico, <=50K 48, Private, 128432, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Federal-gov, 195023, Some-college, 10, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 122473, 9th, 5, Never-married, Machine-op-inspct, Unmarried, Black, Female, 0, 625, 40, United-States, <=50K 43, Private, 171888, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 17, Self-emp-inc, 183784, 10th, 6, Never-married, Sales, Own-child, White, Male, 0, 0, 15, United-States, <=50K 20, Private, 219262, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 71379, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 19, ?, 234519, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 35, United-States, <=50K 35, Private, 96824, Some-college, 10, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 242597, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 18, ?, 127388, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 204536, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 54, Private, 143804, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 80680, Some-college, 10, Married-civ-spouse, Sales, Own-child, White, Female, 0, 0, 16, United-States, <=50K 36, Private, 301227, 5th-6th, 3, Separated, Priv-house-serv, Unmarried, Other, Female, 0, 0, 35, Mexico, <=50K 26, Self-emp-not-inc, 201930, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 25, Local-gov, 176616, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 353219, 9th, 5, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 126076, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 31, Private, 156493, HS-grad, 9, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 48, Federal-gov, 435503, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 52, Self-emp-inc, 561489, Masters, 14, Divorced, Exec-managerial, Not-in-family, Black, Female, 0, 0, 50, United-States, <=50K 22, Federal-gov, 100345, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 43, United-States, <=50K 18, Private, 36275, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 25, United-States, <=50K 46, Private, 110794, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Local-gov, 143766, Some-college, 10, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 40, United-States, <=50K 30, Federal-gov, 76313, HS-grad, 9, Married-civ-spouse, Armed-Forces, Other-relative, Amer-Indian-Eskimo, Male, 0, 0, 48, United-States, <=50K 31, Private, 121308, 11th, 7, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 216672, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Self-emp-not-inc, 89942, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 3674, 0, 45, United-States, <=50K 45, State-gov, 103406, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 60, United-States, >50K 30, State-gov, 158291, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 455361, 9th, 5, Never-married, Other-service, Unmarried, White, Male, 0, 0, 35, Mexico, <=50K 44, Private, 225263, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 1408, 46, United-States, <=50K 54, Private, 225307, 11th, 7, Divorced, Craft-repair, Own-child, White, Female, 0, 0, 50, United-States, >50K 36, Private, 286115, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 50, Private, 187830, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 26, Private, 142506, Bachelors, 13, Never-married, Prof-specialty, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 47, Local-gov, 148576, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, <=50K 36, Private, 185325, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 37, United-States, <=50K 32, Self-emp-not-inc, 27939, Some-college, 10, Married-civ-spouse, Sales, Husband, Amer-Indian-Eskimo, Male, 0, 0, 60, United-States, <=50K 21, Private, 383603, 10th, 6, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 30, Private, 140790, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 34, Private, 226629, HS-grad, 9, Never-married, Priv-house-serv, Not-in-family, White, Female, 0, 0, 40, Mexico, <=50K 51, Private, 228516, HS-grad, 9, Married-spouse-absent, Craft-repair, Not-in-family, White, Male, 0, 0, 45, Columbia, <=50K 55, Self-emp-not-inc, 119762, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 43, Private, 299197, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 149297, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 30, United-States, <=50K 28, Local-gov, 202558, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 175232, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 35, Self-emp-not-inc, 157473, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 59, ?, 409842, Masters, 14, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 20, United-States, <=50K 26, Private, 105787, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 36, United-States, <=50K 68, Private, 144056, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 3818, 0, 40, United-States, <=50K 46, Private, 45363, Prof-school, 15, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 2824, 40, United-States, >50K 21, Private, 205838, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 37, United-States, <=50K 23, Private, 115326, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 17, Private, 186890, 10th, 6, Married-civ-spouse, Sales, Own-child, White, Female, 0, 0, 30, United-States, <=50K 23, Local-gov, 304386, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 24529, HS-grad, 9, Widowed, Adm-clerical, Unmarried, White, Male, 0, 0, 15, United-States, <=50K 33, Private, 183557, Assoc-acdm, 12, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 342730, Assoc-acdm, 12, Separated, Transport-moving, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 31, ?, 182191, Bachelors, 13, Married-civ-spouse, ?, Wife, White, Female, 4064, 0, 30, Canada, <=50K 56, Self-emp-not-inc, 67841, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 351381, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 293691, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, Asian-Pac-Islander, Female, 0, 1590, 40, Japan, <=50K 41, Self-emp-inc, 220821, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 40, United-States, >50K 26, Private, 190027, 10th, 6, Divorced, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 41, Private, 343944, 11th, 7, Widowed, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 46, Self-emp-inc, 110457, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 47, State-gov, 72333, HS-grad, 9, Divorced, Adm-clerical, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 43, Self-emp-not-inc, 193494, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 35, Private, 334999, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 44, Self-emp-not-inc, 274363, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 58, Self-emp-inc, 113806, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 30, United-States, >50K 25, Private, 52536, Assoc-acdm, 12, Divorced, Tech-support, Own-child, White, Female, 0, 1594, 25, United-States, <=50K 44, Private, 187720, Assoc-voc, 11, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 104996, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 42, United-States, <=50K 24, Private, 214555, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 52963, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 33, Private, 190511, 7th-8th, 4, Divorced, Handlers-cleaners, Not-in-family, White, Male, 2176, 0, 35, United-States, <=50K 25, Private, 75821, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 123291, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 84, United-States, >50K 50, Local-gov, 226497, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 52, United-States, >50K 35, Private, 282979, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 5178, 0, 50, United-States, >50K 36, Private, 166549, Bachelors, 13, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 55, United-States, >50K 27, Private, 187746, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 157145, Assoc-voc, 11, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 50, United-States, <=50K 30, Private, 227551, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 90, Private, 115306, Masters, 14, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 169249, HS-grad, 9, Separated, Other-service, Other-relative, Black, Male, 0, 0, 40, United-States, <=50K 34, State-gov, 221966, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 39, Private, 224566, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 19, Private, 28119, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 4, United-States, <=50K 19, Private, 323810, 10th, 6, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 210498, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 66, Self-emp-not-inc, 174995, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 2290, 0, 30, Hungary, <=50K 38, Private, 161141, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 45, United-States, <=50K 44, Private, 210534, 5th-6th, 3, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Mexico, <=50K 34, Self-emp-not-inc, 112650, 7th-8th, 4, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 35, State-gov, 318891, Assoc-acdm, 12, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, Local-gov, 375655, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 228465, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 33, ?, 102130, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 73, Private, 183213, Assoc-voc, 11, Widowed, Prof-specialty, Not-in-family, White, Male, 25124, 0, 60, United-States, >50K 35, Local-gov, 177305, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 2377, 40, United-States, <=50K 41, Private, 34037, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Self-emp-not-inc, 116613, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 50, United-States, <=50K 25, Private, 175540, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 47, Private, 150768, Bachelors, 13, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 1564, 51, United-States, >50K 36, Private, 176634, Bachelors, 13, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 35, United-States, >50K 36, Private, 209993, 1st-4th, 2, Widowed, Other-service, Other-relative, White, Female, 0, 0, 20, Mexico, <=50K 25, Local-gov, 206002, HS-grad, 9, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 201259, 11th, 7, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 26, Local-gov, 202286, Bachelors, 13, Never-married, Tech-support, Own-child, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 96062, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1740, 40, United-States, <=50K 36, Local-gov, 578377, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 509500, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Female, 4787, 0, 45, United-States, >50K 53, Local-gov, 324021, Some-college, 10, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 37, Self-emp-not-inc, 107737, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 41, State-gov, 129865, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 103586, Bachelors, 13, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 55, United-States, <=50K 23, Private, 187513, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 32, United-States, <=50K 28, Private, 172891, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 53, Local-gov, 207449, 10th, 6, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 209103, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 20, United-States, >50K 33, Private, 408813, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 27, Private, 209292, HS-grad, 9, Never-married, Sales, Other-relative, Black, Female, 0, 0, 32, Dominican-Republic, <=50K 52, Private, 144361, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1902, 40, United-States, >50K 31, Private, 209538, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 55, United-States, <=50K 27, Private, 244402, Assoc-acdm, 12, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 44, Private, 889965, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Wife, White, Female, 3137, 0, 30, United-States, <=50K 37, Self-emp-not-inc, 298444, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 163237, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 18, Private, 311795, 12th, 8, Never-married, Sales, Own-child, Black, Female, 0, 0, 20, United-States, <=50K 42, Private, 155972, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, >50K 49, Private, 291783, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 153535, HS-grad, 9, Divorced, Handlers-cleaners, Unmarried, Black, Female, 0, 0, 36, United-States, <=50K 43, Private, 249771, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Asian-Pac-Islander, Male, 0, 0, 99, United-States, <=50K 43, Private, 462180, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 60, United-States, >50K 31, Private, 308540, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 34701, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 46, Federal-gov, 106252, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 54, Private, 138944, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 44, United-States, <=50K 37, Private, 140713, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, Jamaica, >50K 53, Local-gov, 216931, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 4386, 0, 40, United-States, >50K 26, Private, 162312, Some-college, 10, Never-married, Adm-clerical, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 20, Philippines, <=50K 59, Self-emp-inc, 253062, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 36, Federal-gov, 359249, Some-college, 10, Separated, Adm-clerical, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 32, Private, 231413, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 53, Local-gov, 197054, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 130931, HS-grad, 9, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 35, Private, 30565, HS-grad, 9, Married-AF-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, >50K 48, Private, 105138, HS-grad, 9, Divorced, Exec-managerial, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 30, Local-gov, 178383, Some-college, 10, Separated, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 38, Private, 241998, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 7688, 0, 40, United-States, >50K 58, Self-emp-not-inc, 196403, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 10, United-States, >50K 44, Private, 232421, HS-grad, 9, Married-spouse-absent, Transport-moving, Not-in-family, Other, Male, 0, 0, 32, Canada, <=50K 30, Private, 130369, Assoc-voc, 11, Separated, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 68, Self-emp-not-inc, 336329, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 10, United-States, <=50K 26, Local-gov, 337867, Bachelors, 13, Never-married, Prof-specialty, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 26, Local-gov, 104614, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 223548, 1st-4th, 2, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 43, State-gov, 506329, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 15024, 0, 40, ?, >50K 48, Private, 64479, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 47, United-States, <=50K 55, Private, 284095, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 37, United-States, <=50K 50, Self-emp-not-inc, 221336, Some-college, 10, Divorced, Exec-managerial, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, ?, <=50K 41, Private, 428499, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1485, 50, United-States, >50K 52, Private, 208302, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 36, United-States, <=50K 24, ?, 412156, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 40, Mexico, <=50K 31, Self-emp-not-inc, 182177, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1902, 40, United-States, >50K 54, Local-gov, 129972, Assoc-voc, 11, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 38, United-States, >50K 31, Self-emp-not-inc, 186420, Masters, 14, Separated, Tech-support, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 31, Self-emp-inc, 203488, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 47, Private, 128796, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Private, 55395, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 46, State-gov, 314770, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 48, United-States, <=50K 45, Private, 135044, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 319248, 10th, 6, Never-married, Other-service, Unmarried, White, Female, 0, 0, 25, Mexico, <=50K 34, Local-gov, 236415, Some-college, 10, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 18, United-States, <=50K 48, ?, 151584, Some-college, 10, Never-married, ?, Not-in-family, White, Male, 8614, 0, 60, United-States, >50K 19, ?, 133983, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 20, United-States, <=50K 56, Private, 81220, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, Canada, <=50K 47, Private, 151087, HS-grad, 9, Separated, Prof-specialty, Other-relative, Other, Female, 0, 0, 40, Puerto-Rico, <=50K 35, Private, 322171, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, >50K 25, Private, 190628, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Columbia, <=50K 43, Local-gov, 106982, Bachelors, 13, Separated, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 59, Private, 227856, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 37, United-States, >50K 66, ?, 213477, 7th-8th, 4, Divorced, ?, Not-in-family, White, Male, 0, 0, 10, United-States, <=50K 63, Private, 266083, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, >50K 32, Private, 257068, Some-college, 10, Married-spouse-absent, Transport-moving, Not-in-family, White, Female, 0, 0, 37, United-States, <=50K 58, ?, 37591, Bachelors, 13, Widowed, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Self-emp-inc, 150533, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Other-relative, White, Male, 0, 0, 50, United-States, >50K 27, Private, 211184, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 52, United-States, <=50K 21, Private, 136610, 12th, 8, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 32, United-States, <=50K 44, Federal-gov, 244054, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 60, United-States, >50K 40, Self-emp-not-inc, 240698, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 65, Private, 172906, HS-grad, 9, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 50, Private, 238959, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, >50K 18, ?, 163085, HS-grad, 9, Separated, ?, Own-child, White, Male, 0, 0, 20, United-States, <=50K 51, State-gov, 172022, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 44, Federal-gov, 218062, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 20, Private, 201799, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 13, United-States, <=50K 29, Private, 150717, Assoc-voc, 11, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 94391, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 50, Local-gov, 153064, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 5178, 0, 40, United-States, >50K 43, Private, 156771, 10th, 6, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 216639, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 82161, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, ?, 159159, Some-college, 10, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 30, United-States, <=50K 58, Self-emp-not-inc, 310014, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 25, United-States, <=50K 50, State-gov, 133014, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Self-emp-not-inc, 36214, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 65, United-States, >50K 21, Private, 399022, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 24, United-States, <=50K 33, Private, 179758, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 20, United-States, <=50K 52, Private, 48947, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 47, Private, 201865, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Self-emp-not-inc, 319122, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 14084, 0, 45, United-States, >50K 34, Private, 155151, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 24106, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, Philippines, >50K 31, Private, 257863, Some-college, 10, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 19, ?, 28967, Some-college, 10, Never-married, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 379393, Some-college, 10, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 45, Self-emp-not-inc, 152752, Assoc-voc, 11, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 3, United-States, <=50K 34, Private, 154874, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 4416, 0, 30, United-States, <=50K 27, Private, 154210, 11th, 7, Married-spouse-absent, Sales, Own-child, Asian-Pac-Islander, Male, 0, 0, 35, India, <=50K 37, Private, 335716, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 94744, HS-grad, 9, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 20, United-States, <=50K 32, Private, 133861, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 13550, 0, 48, United-States, >50K 24, Private, 240137, 1st-4th, 2, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 55, Mexico, <=50K 39, Private, 80004, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 109702, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 30, United-States, <=50K 62, Self-emp-not-inc, 39610, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 80, United-States, <=50K 24, Private, 90046, Bachelors, 13, Separated, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 193855, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 46, Private, 206889, Bachelors, 13, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 44, Private, 86298, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 149650, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 2559, 48, United-States, >50K 25, Private, 323139, Bachelors, 13, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 35, United-States, <=50K 44, Private, 237993, Prof-school, 15, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, ?, <=50K 24, Private, 36058, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 61, Private, 163393, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 20, United-States, <=50K 45, Local-gov, 93535, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 33, Self-emp-not-inc, 112952, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 48, United-States, <=50K 48, Private, 182541, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 45, United-States, >50K 26, Local-gov, 73392, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, Amer-Indian-Eskimo, Male, 0, 0, 30, United-States, <=50K 40, ?, 507086, HS-grad, 9, Divorced, ?, Not-in-family, Black, Female, 0, 0, 32, United-States, <=50K 68, Private, 195868, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 20051, 0, 40, United-States, >50K 24, Private, 276851, HS-grad, 9, Divorced, Protective-serv, Own-child, White, Female, 0, 1762, 40, United-States, <=50K 25, ?, 39901, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 60, United-States, <=50K 31, Local-gov, 33124, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 55, Private, 419732, Some-college, 10, Divorced, Other-service, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 46, Private, 171095, Assoc-acdm, 12, Divorced, Sales, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 58, Private, 199278, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 56, Private, 235205, HS-grad, 9, Widowed, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 45, Federal-gov, 168232, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 55, United-States, >50K 24, Private, 145964, Bachelors, 13, Never-married, Exec-managerial, Unmarried, White, Male, 0, 0, 40, United-States, >50K 35, Local-gov, 72338, HS-grad, 9, Divorced, Farming-fishing, Own-child, Asian-Pac-Islander, Male, 0, 0, 56, United-States, <=50K 51, Private, 153870, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 47, Private, 323798, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 55, United-States, >50K 17, Private, 198830, 11th, 7, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 10, United-States, <=50K 21, Private, 267040, 10th, 6, Never-married, Prof-specialty, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 45, Private, 167187, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 42, Private, 230684, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 5178, 0, 50, United-States, >50K 56, Private, 659558, 12th, 8, Widowed, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 39, Private, 181661, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 186144, 7th-8th, 4, Never-married, Machine-op-inspct, Not-in-family, Other, Female, 0, 0, 40, Mexico, <=50K 20, Federal-gov, 178517, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 65, Self-emp-not-inc, 131417, 5th-6th, 3, Married-civ-spouse, Farming-fishing, Husband, White, Male, 1797, 0, 21, United-States, <=50K 44, Private, 57233, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, <=50K 33, Private, 379798, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 122175, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 38, Private, 107302, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 31, Local-gov, 127651, 10th, 6, Never-married, Transport-moving, Other-relative, White, Male, 0, 1741, 40, United-States, <=50K 33, Self-emp-not-inc, 102884, Bachelors, 13, Married-civ-spouse, Sales, Own-child, White, Male, 0, 0, 20, United-States, <=50K 49, Self-emp-not-inc, 241753, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 173611, HS-grad, 9, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 232666, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 352207, Assoc-voc, 11, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 37, Self-emp-not-inc, 241998, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 5, United-States, >50K 52, Private, 279129, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 37, United-States, >50K 27, Private, 177057, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 155659, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 7688, 0, 55, United-States, >50K 21, Private, 251603, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 41, Federal-gov, 19914, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, >50K 61, Private, 115023, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Private, 101709, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, >50K 21, Private, 313702, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 63, Private, 250068, 12th, 8, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 34, Private, 227359, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 42, United-States, <=50K 21, State-gov, 196827, Assoc-acdm, 12, Never-married, Tech-support, Own-child, White, Male, 0, 0, 10, United-States, <=50K 44, Private, 118550, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 33, United-States, <=50K 26, Private, 285004, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 35, South, <=50K 36, Private, 280169, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 39, Private, 144608, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, ?, >50K 52, Private, 76860, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, Asian-Pac-Islander, Male, 0, 0, 8, Philippines, <=50K 44, Self-emp-not-inc, 167280, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 334783, HS-grad, 9, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, <=50K 60, ?, 141580, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 50, United-States, >50K 31, Private, 226443, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 366065, Some-college, 10, Never-married, Craft-repair, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 23, Private, 225724, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 25, United-States, <=50K 81, State-gov, 132204, 1st-4th, 2, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 39, Private, 258276, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, Asian-Pac-Islander, Male, 3137, 0, 40, ?, <=50K 38, Private, 197711, 10th, 6, Divorced, Machine-op-inspct, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, Portugal, <=50K 21, Private, 30619, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 28, Local-gov, 335015, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 61272, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 106544, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 144169, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 27, Private, 40295, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 99, United-States, <=50K 56, Private, 266091, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 2907, 0, 52, Cuba, <=50K 57, Private, 143030, HS-grad, 9, Widowed, Other-service, Unmarried, White, Female, 0, 0, 30, ?, <=50K 42, State-gov, 192397, Some-college, 10, Divorced, Adm-clerical, Own-child, White, Female, 0, 0, 38, United-States, <=50K 43, Private, 114351, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 48, ?, 63466, HS-grad, 9, Married-spouse-absent, ?, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 53, Private, 132304, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, Scotland, <=50K 58, Private, 128162, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 24, United-States, <=50K 19, Private, 125938, 12th, 8, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, El-Salvador, <=50K 37, Private, 170174, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 46, United-States, >50K 41, Self-emp-not-inc, 203451, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 31, Private, 109917, 7th-8th, 4, Separated, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 114937, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, <=50K 53, Local-gov, 231196, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 238474, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 25, United-States, <=50K 56, Private, 314149, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 55, Federal-gov, 31728, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 51, Private, 360131, 5th-6th, 3, Married-civ-spouse, Craft-repair, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 62, Private, 141308, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 83411, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 45, ?, 119835, 7th-8th, 4, Divorced, ?, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 48, United-States, <=50K 28, Local-gov, 296537, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 46, Private, 193047, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 62, State-gov, 39630, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 57, Local-gov, 213975, HS-grad, 9, Widowed, Other-service, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 60, Local-gov, 259803, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 45, United-States, >50K 23, Federal-gov, 55465, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 181307, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 99999, 0, 60, United-States, >50K 21, Private, 211301, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 8, United-States, <=50K 51, Private, 200450, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 48, United-States, <=50K 61, Local-gov, 176731, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Self-emp-not-inc, 140985, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 99999, 0, 30, United-States, >50K 76, Private, 125784, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 152176, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 39, United-States, <=50K 31, Self-emp-not-inc, 111423, Bachelors, 13, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 43, Private, 130126, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 58, Federal-gov, 30111, Some-college, 10, Widowed, Prof-specialty, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 18, ?, 214989, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 1602, 24, United-States, <=50K 19, Private, 272800, 12th, 8, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 25, United-States, <=50K 44, Private, 195881, Some-college, 10, Divorced, Exec-managerial, Other-relative, White, Female, 0, 0, 45, United-States, <=50K 41, Local-gov, 170924, Some-college, 10, Never-married, Prof-specialty, Other-relative, White, Male, 0, 0, 7, United-States, <=50K 21, Private, 131473, Some-college, 10, Never-married, Sales, Own-child, Asian-Pac-Islander, Male, 0, 0, 20, Vietnam, <=50K 40, Private, 149466, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 35, United-States, <=50K 25, Private, 190418, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, Canada, <=50K 62, Local-gov, 167889, Doctorate, 16, Widowed, Prof-specialty, Unmarried, White, Female, 0, 0, 40, Iran, <=50K 42, Private, 177989, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 186035, Assoc-voc, 11, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 195805, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 12, United-States, <=50K 60, Private, 54800, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 100605, HS-grad, 9, Never-married, Sales, Own-child, Other, Male, 0, 0, 40, Puerto-Rico, <=50K 23, Private, 253190, Assoc-acdm, 12, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 25, United-States, <=50K 18, Private, 203301, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 175696, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 19, Private, 278304, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 51, Private, 93193, HS-grad, 9, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 41, Local-gov, 158688, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 50, United-States, <=50K 18, Private, 327612, 10th, 6, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 41, Private, 210844, Some-college, 10, Married-spouse-absent, Sales, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 27, Private, 147340, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 71, Self-emp-not-inc, 130436, 1st-4th, 2, Divorced, Craft-repair, Not-in-family, White, Female, 0, 0, 28, United-States, <=50K 25, Private, 206600, 12th, 8, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, El-Salvador, <=50K 73, Private, 284680, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 45, Private, 127738, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 213412, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 50, Private, 287927, HS-grad, 9, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 16, United-States, <=50K 44, Private, 249332, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, Ecuador, <=50K 44, Local-gov, 290403, Assoc-voc, 11, Divorced, Protective-serv, Own-child, White, Female, 0, 0, 40, Cuba, <=50K 49, Private, 54772, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 3103, 0, 45, United-States, >50K 44, Self-emp-inc, 56651, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 45, United-States, >50K 42, Federal-gov, 178470, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 62865, HS-grad, 9, Never-married, Priv-house-serv, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 66, Private, 107196, HS-grad, 9, Widowed, Tech-support, Not-in-family, White, Female, 0, 0, 18, United-States, <=50K 19, Private, 86860, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 15, United-States, <=50K 60, Private, 130684, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, <=50K 46, Private, 164682, Assoc-voc, 11, Separated, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 198316, Assoc-voc, 11, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 59, Private, 261816, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 52, Outlying-US(Guam-USVI-etc), <=50K 58, Private, 280309, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 5178, 0, 60, United-States, >50K 47, Private, 97176, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 58, Private, 95835, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 36, United-States, <=50K 69, ?, 323016, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 99999, 0, 40, United-States, >50K 17, ?, 280670, 10th, 6, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 136306, 11th, 7, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 24, United-States, <=50K 28, Private, 65171, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 70, United-States, <=50K 37, Private, 25864, HS-grad, 9, Separated, Prof-specialty, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 30, Private, 149531, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 36, Private, 33887, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 172822, 11th, 7, Divorced, Transport-moving, Not-in-family, White, Male, 0, 2824, 76, United-States, >50K 59, Private, 106748, 7th-8th, 4, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 99, United-States, <=50K 45, Private, 131826, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 53, Local-gov, 216691, Doctorate, 16, Divorced, Prof-specialty, Not-in-family, White, Female, 10520, 0, 40, United-States, >50K 37, Private, 133328, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 164737, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 53, Local-gov, 99064, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, State-gov, 59460, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 15, United-States, <=50K 27, Private, 208725, Bachelors, 13, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 138513, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 121055, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 149784, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, Private, 114495, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, ?, 133278, 12th, 8, Separated, ?, Unmarried, Black, Female, 0, 0, 53, United-States, <=50K 32, Private, 212276, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 32, Private, 440129, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 38, Mexico, <=50K 47, Private, 98012, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 7688, 0, 40, United-States, >50K 27, Private, 145284, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 177147, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 141537, 10th, 6, Divorced, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 36, Self-emp-not-inc, 48093, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 92, United-States, <=50K 23, Local-gov, 314819, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 123572, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 19, Private, 170800, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 60, United-States, <=50K 42, Private, 332401, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 60, Self-emp-not-inc, 193038, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 15, United-States, <=50K 41, Private, 351161, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 1848, 45, United-States, >50K 45, Federal-gov, 106910, HS-grad, 9, Never-married, Transport-moving, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 67, ?, 163726, 5th-6th, 3, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 49, United-States, <=50K 36, Self-emp-not-inc, 609935, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 48, ?, <=50K 52, State-gov, 314627, Masters, 14, Divorced, Prof-specialty, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 28, Private, 115945, Doctorate, 16, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 18, United-States, <=50K 83, Self-emp-inc, 272248, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 17, Private, 167878, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 27, Private, 176972, Assoc-voc, 11, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Self-emp-not-inc, 31095, Assoc-voc, 11, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 40, Private, 130834, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 207415, Assoc-acdm, 12, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 25, United-States, <=50K 51, Local-gov, 264457, 11th, 7, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, United-States, <=50K 51, Private, 340588, 1st-4th, 2, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 54, Mexico, <=50K 82, ?, 42435, 10th, 6, Widowed, ?, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 28, Private, 107411, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 53, Private, 290640, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 50, Germany, >50K 29, Private, 106179, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, Canada, <=50K 19, Private, 247679, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 30, Private, 171598, Bachelors, 13, Married-spouse-absent, Sales, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 23, Private, 234460, 7th-8th, 4, Never-married, Machine-op-inspct, Own-child, Black, Female, 0, 0, 40, Dominican-Republic, <=50K 66, Private, 196674, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 15, United-States, >50K 27, Private, 182540, 11th, 7, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 172694, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 17, Private, 29571, 12th, 8, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 15, United-States, <=50K 27, Private, 130438, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 213421, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 44, Local-gov, 189956, Bachelors, 13, Married-civ-spouse, Protective-serv, Wife, Black, Female, 15024, 0, 40, United-States, >50K 64, Private, 133144, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 16, United-States, <=50K 62, Self-emp-inc, 24050, HS-grad, 9, Widowed, Sales, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 26, Private, 276967, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 184857, HS-grad, 9, Separated, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 145160, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 192251, HS-grad, 9, Divorced, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 190650, Bachelors, 13, Never-married, Prof-specialty, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, Taiwan, <=50K 52, Local-gov, 255927, Some-college, 10, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 24, United-States, <=50K 46, Private, 99086, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 30, Private, 216811, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 52, Private, 110563, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 120471, HS-grad, 9, Never-married, Transport-moving, Not-in-family, Other, Male, 0, 0, 40, United-States, <=50K 17, Private, 183066, 10th, 6, Never-married, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 46, State-gov, 298786, Some-college, 10, Never-married, Other-service, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 45, Private, 297884, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 21, Private, 253612, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 1055, 0, 32, United-States, <=50K 18, Self-emp-not-inc, 207438, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, <=50K 17, Private, 148522, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 1721, 15, United-States, <=50K 90, Private, 139660, Some-college, 10, Divorced, Sales, Unmarried, Black, Female, 0, 0, 37, United-States, <=50K 23, Private, 165474, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 120277, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 19, Self-emp-not-inc, 67929, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 50, United-States, <=50K 69, Private, 229418, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Federal-gov, 41356, Assoc-acdm, 12, Never-married, Exec-managerial, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 28, Private, 185127, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 54, United-States, <=50K 37, Private, 109133, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 1977, 45, United-States, >50K 57, Private, 148315, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 30, United-States, <=50K 30, Local-gov, 145692, Some-college, 10, Never-married, Protective-serv, Not-in-family, Black, Male, 0, 1974, 40, United-States, <=50K 48, Private, 210424, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 914, 0, 40, United-States, <=50K 73, Private, 198526, HS-grad, 9, Widowed, Other-service, Other-relative, White, Female, 0, 0, 32, United-States, <=50K 25, Private, 521400, 5th-6th, 3, Never-married, Machine-op-inspct, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 33, Private, 100882, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 36, Private, 124818, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 190836, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 3411, 0, 40, United-States, <=50K 57, Private, 71367, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 303032, Some-college, 10, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 35, ?, 98989, 9th, 5, Divorced, ?, Own-child, Amer-Indian-Eskimo, Male, 0, 0, 38, United-States, <=50K 40, State-gov, 390781, HS-grad, 9, Divorced, Other-service, Not-in-family, Black, Female, 0, 0, 48, United-States, <=50K 32, Private, 54782, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 35, ?, 202683, Bachelors, 13, Never-married, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 213081, HS-grad, 9, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, Jamaica, <=50K 27, Self-emp-inc, 89718, Some-college, 10, Separated, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 17, Private, 225106, 10th, 6, Never-married, Other-service, Own-child, White, Female, 0, 1602, 18, United-States, <=50K 29, Private, 253262, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 78181, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 20, Private, 158206, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 69, ?, 337720, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 24, United-States, <=50K 18, State-gov, 391257, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 56, Private, 134756, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 40, Private, 183404, Some-college, 10, Separated, Other-service, Unmarried, White, Female, 0, 0, 8, United-States, <=50K 46, Private, 192793, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 203943, 12th, 8, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 40, ?, <=50K 53, Private, 89400, Some-college, 10, Widowed, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 50, Private, 237868, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 23, Private, 139187, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 50, United-States, <=50K 40, Private, 126701, Bachelors, 13, Married-spouse-absent, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 54, Self-emp-inc, 172175, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 45, Private, 164210, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 53, Local-gov, 608184, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, >50K 17, ?, 198797, 11th, 7, Never-married, ?, Own-child, White, Male, 0, 0, 20, Peru, <=50K 50, Local-gov, 425804, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 22, ?, 117618, Bachelors, 13, Never-married, ?, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 30, Private, 119164, Bachelors, 13, Never-married, Other-service, Unmarried, White, Male, 0, 0, 40, ?, <=50K 40, Self-emp-inc, 92036, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, State-gov, 77146, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Self-emp-not-inc, 191803, Assoc-acdm, 12, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 29, Private, 54932, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 251694, Bachelors, 13, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 50, United-States, <=50K 22, Private, 268145, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 56, Private, 104842, Bachelors, 13, Divorced, Prof-specialty, Unmarried, Black, Female, 0, 0, 50, Haiti, <=50K 60, Local-gov, 227332, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Private, 212512, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 3464, 0, 50, United-States, <=50K 53, Private, 133436, 7th-8th, 4, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, State-gov, 309055, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 18, Private, 59202, HS-grad, 9, Never-married, Priv-house-serv, Other-relative, White, Female, 0, 0, 10, United-States, <=50K 36, Private, 32709, Some-college, 10, Divorced, Sales, Not-in-family, White, Female, 3325, 0, 45, United-States, <=50K 67, Self-emp-inc, 73559, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 9386, 0, 50, United-States, >50K 31, Private, 117963, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 26, Private, 169121, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 48, United-States, >50K 18, Private, 308889, 11th, 7, Never-married, Adm-clerical, Other-relative, Asian-Pac-Islander, Female, 0, 0, 20, United-States, <=50K 45, Local-gov, 144940, Masters, 14, Divorced, Prof-specialty, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 64, Private, 102041, 11th, 7, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 335998, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 53, Private, 29557, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 210313, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 28, Guatemala, <=50K 32, Private, 190784, Some-college, 10, Divorced, Machine-op-inspct, Unmarried, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 49, Self-emp-not-inc, 107597, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 14084, 0, 30, United-States, >50K 59, Private, 97168, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 44, Private, 155930, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 55, United-States, >50K 61, Self-emp-not-inc, 181033, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 41, ?, 344572, HS-grad, 9, Divorced, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 46, State-gov, 170165, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 37, United-States, <=50K 32, Private, 178835, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 118230, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 48, Private, 149640, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 30271, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 21, Private, 154165, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 35, United-States, <=50K 50, Self-emp-not-inc, 341797, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 44, Local-gov, 145246, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 44, United-States, >50K 51, Private, 280093, HS-grad, 9, Separated, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 373469, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 199172, Bachelors, 13, Never-married, Protective-serv, Own-child, White, Female, 0, 0, 40, United-States, <=50K 70, Self-emp-not-inc, 177199, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 3, United-States, <=50K 33, Private, 258932, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 65, Self-emp-not-inc, 139960, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 10605, 0, 60, United-States, >50K 39, Private, 258037, Masters, 14, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, ?, <=50K 32, Private, 116677, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 59496, Some-college, 10, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 43, Self-emp-inc, 34218, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 200246, 9th, 5, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 64, Federal-gov, 316246, Bachelors, 13, Divorced, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 37, Local-gov, 239161, Some-college, 10, Separated, Protective-serv, Own-child, Other, Male, 0, 0, 52, United-States, <=50K 49, Self-emp-not-inc, 173411, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 259226, 11th, 7, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 48, United-States, <=50K 35, Local-gov, 195516, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 200598, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1740, 45, United-States, <=50K 42, State-gov, 160369, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 21, ?, 415913, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 147253, Assoc-acdm, 12, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Local-gov, 199674, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 29, State-gov, 198493, Assoc-voc, 11, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Private, 377121, Some-college, 10, Never-married, Other-service, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 21, Private, 400635, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 20, ?, <=50K 45, Private, 513660, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 24, ?, 175069, Bachelors, 13, Never-married, ?, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 38, Private, 82552, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 594, 0, 50, United-States, <=50K 28, ?, 78388, 10th, 6, Never-married, ?, Own-child, White, Female, 0, 0, 38, United-States, <=50K 23, Private, 171705, HS-grad, 9, Never-married, Sales, Unmarried, White, Female, 0, 0, 48, United-States, <=50K 39, Self-emp-not-inc, 315640, Bachelors, 13, Never-married, Sales, Own-child, Asian-Pac-Islander, Male, 0, 0, 60, Iran, <=50K 45, Private, 266860, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 68, Private, 192829, Assoc-acdm, 12, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 43, United-States, <=50K 60, Federal-gov, 237317, Assoc-voc, 11, Divorced, Prof-specialty, Unmarried, White, Male, 4934, 0, 40, United-States, >50K 38, State-gov, 110426, Doctorate, 16, Married-civ-spouse, Prof-specialty, Wife, White, Female, 7688, 0, 40, ?, >50K 41, Private, 327606, 12th, 8, Separated, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 48, Private, 34845, HS-grad, 9, Divorced, Craft-repair, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 58582, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 155659, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Local-gov, 210029, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 26, Private, 381618, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 55, Self-emp-inc, 298449, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 2415, 50, United-States, >50K 35, State-gov, 226789, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 75, United-States, <=50K 52, Private, 210736, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 3103, 0, 55, United-States, >50K 46, State-gov, 111163, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 72, ?, 76860, HS-grad, 9, Married-civ-spouse, ?, Husband, Asian-Pac-Islander, Male, 0, 0, 1, United-States, <=50K 18, Private, 92112, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 62, Local-gov, 136787, HS-grad, 9, Divorced, Transport-moving, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 29810, Some-college, 10, Never-married, Transport-moving, Own-child, White, Female, 0, 0, 30, United-States, <=50K 40, Private, 360884, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 7298, 0, 40, United-States, >50K 26, Private, 266022, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 35, Private, 142874, Assoc-acdm, 12, Married-spouse-absent, Sales, Own-child, Black, Female, 0, 0, 36, United-States, <=50K 25, Self-emp-not-inc, 72338, HS-grad, 9, Never-married, Sales, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 46, ?, 177305, Assoc-voc, 11, Married-civ-spouse, ?, Wife, Black, Female, 0, 0, 35, United-States, >50K 39, Private, 165106, Bachelors, 13, Married-spouse-absent, Craft-repair, Not-in-family, White, Male, 0, 1564, 50, ?, >50K 41, Private, 424478, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 45, United-States, >50K 59, Private, 189721, Bachelors, 13, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Italy, >50K 37, Private, 34180, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 183279, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 43, United-States, <=50K 33, Private, 35309, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, ?, <=50K 23, Private, 259109, Assoc-acdm, 12, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, Puerto-Rico, <=50K 67, Self-emp-not-inc, 148690, Masters, 14, Widowed, Prof-specialty, Not-in-family, White, Male, 18481, 0, 2, United-States, >50K 60, Private, 125019, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 8614, 0, 48, United-States, >50K 39, Self-emp-inc, 172538, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 32, Self-emp-not-inc, 410615, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1887, 60, United-States, >50K 26, Private, 322547, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 39, Private, 300760, HS-grad, 9, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 28, Private, 232782, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 174645, 11th, 7, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 52, United-States, <=50K 43, Private, 164693, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 23, Private, 206861, Some-college, 10, Never-married, Tech-support, Own-child, White, Male, 0, 0, 25, United-States, <=50K 32, Private, 195602, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 1977, 45, United-States, >50K 33, Self-emp-not-inc, 422960, Some-college, 10, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 60, United-States, >50K 45, Private, 116360, HS-grad, 9, Divorced, Other-service, Not-in-family, Black, Female, 0, 0, 35, United-States, <=50K 48, Private, 278530, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 43, Local-gov, 188291, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 45, United-States, >50K 50, Self-emp-not-inc, 163948, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 63, Private, 64544, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 55, Private, 101468, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 3103, 0, 40, United-States, >50K 22, Private, 107882, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 35, United-States, <=50K 32, Self-emp-not-inc, 182691, HS-grad, 9, Never-married, Other-service, Unmarried, White, Male, 0, 0, 60, United-States, <=50K 27, Private, 203776, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, <=50K 22, Private, 201268, Bachelors, 13, Never-married, Sales, Own-child, White, Female, 0, 0, 15, United-States, <=50K 44, Private, 29762, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 68, United-States, <=50K 34, Private, 186346, HS-grad, 9, Separated, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 196690, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 99604, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 15024, 0, 24, United-States, >50K 45, Private, 194772, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 55, United-States, <=50K 17, Private, 95446, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 15, United-States, <=50K 53, Self-emp-not-inc, 257126, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 58, Private, 194733, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 55, Self-emp-not-inc, 98361, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 35, United-States, <=50K 44, Local-gov, 124924, Assoc-voc, 11, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 44, United-States, <=50K 40, Self-emp-not-inc, 111971, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 30, United-States, <=50K 58, Self-emp-not-inc, 130714, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 38, Private, 208358, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 62, Private, 147627, 9th, 5, Never-married, Priv-house-serv, Not-in-family, Black, Female, 1055, 0, 22, United-States, <=50K 31, Private, 149507, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 3464, 0, 38, United-States, <=50K 31, Private, 164870, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Mexico, <=50K 30, Private, 236861, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 1876, 45, United-States, <=50K 37, Private, 220314, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 38, Local-gov, 329980, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 1876, 40, Canada, <=50K 58, Local-gov, 318537, 12th, 8, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 183284, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 28, Private, 334368, Assoc-voc, 11, Never-married, Prof-specialty, Not-in-family, White, Female, 4650, 0, 40, United-States, <=50K 46, Private, 109227, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 70, United-States, <=50K 34, Private, 118551, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 39, Self-emp-inc, 163057, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 99, United-States, <=50K 61, Self-emp-inc, 253101, Some-college, 10, Widowed, Sales, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 30, Self-emp-not-inc, 20098, Assoc-voc, 11, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 196227, HS-grad, 9, Separated, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 175374, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 234037, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 58, United-States, <=50K 47, Private, 341762, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 33, United-States, <=50K 20, Private, 174714, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 222835, Bachelors, 13, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 46, Private, 251786, 1st-4th, 2, Separated, Other-service, Not-in-family, White, Female, 0, 0, 40, Mexico, <=50K 20, Private, 164219, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 45, United-States, <=50K 33, Private, 251120, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 50, United-States, >50K 30, Private, 236993, Some-college, 10, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 43, Local-gov, 105896, Some-college, 10, Divorced, Protective-serv, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 211527, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 60, United-States, <=50K 34, Private, 317809, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, ?, >50K 25, Private, 185287, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 31014, HS-grad, 9, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 44, Private, 151985, Masters, 14, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 24, United-States, >50K 26, Private, 89389, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 406051, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 80, United-States, >50K 48, Self-emp-not-inc, 171986, HS-grad, 9, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 15, United-States, <=50K 26, Private, 167848, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 41, Local-gov, 213019, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 211424, Bachelors, 13, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 168981, Assoc-voc, 11, Never-married, Prof-specialty, Unmarried, White, Female, 0, 0, 55, United-States, <=50K 24, Private, 122348, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 139753, Bachelors, 13, Married-spouse-absent, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 24, Local-gov, 176178, Assoc-acdm, 12, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 2, United-States, <=50K 41, Private, 145220, 9th, 5, Never-married, Priv-house-serv, Unmarried, White, Female, 0, 0, 40, Columbia, <=50K 38, Local-gov, 188612, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 19, Private, 445728, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 318002, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 235722, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 59, ?, 367984, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 67, Private, 212705, Masters, 14, Married-spouse-absent, Exec-managerial, Not-in-family, White, Male, 0, 0, 55, United-States, >50K 49, Private, 411273, 10th, 6, Divorced, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 35, Private, 103986, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 44, Private, 203761, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 58, ?, 266792, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 99999, 0, 40, United-States, >50K 22, Private, 116800, Assoc-acdm, 12, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 60, United-States, <=50K 21, State-gov, 99199, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 10, United-States, <=50K 50, Private, 162327, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 50, United-States, <=50K 44, Local-gov, 100479, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 48, United-States, <=50K 36, Local-gov, 32587, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 30, Federal-gov, 321990, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 7298, 0, 48, Cuba, >50K 52, Private, 108914, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Self-emp-not-inc, 61343, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 90, United-States, <=50K 48, Local-gov, 81154, Assoc-voc, 11, Never-married, Protective-serv, Unmarried, White, Male, 0, 0, 48, United-States, <=50K 23, Private, 162945, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 2377, 40, United-States, <=50K 37, Private, 225504, Masters, 14, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 44, Self-emp-inc, 191712, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 2415, 55, United-States, >50K 44, Private, 176063, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 36, Private, 198587, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 26, State-gov, 34965, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 12, United-States, <=50K 31, Self-emp-inc, 467108, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 23, ?, 263899, HS-grad, 9, Never-married, ?, Own-child, Black, Male, 0, 0, 12, England, <=50K 29, Private, 204984, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 53, Private, 217568, HS-grad, 9, Widowed, Craft-repair, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 52, Private, 48343, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 193130, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 1887, 40, United-States, >50K 31, Private, 253354, 10th, 6, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, ?, 258026, HS-grad, 9, Never-married, ?, Not-in-family, White, Female, 0, 0, 16, United-States, <=50K 64, ?, 211360, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 55, Private, 191367, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 148995, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 20, Private, 123901, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Female, 0, 0, 40, United-States, <=50K 50, Local-gov, 117496, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 7298, 0, 30, United-States, >50K 45, Self-emp-inc, 32356, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 51, United-States, <=50K 17, Private, 206506, 10th, 6, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 10, El-Salvador, <=50K 38, Private, 218729, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 43, Private, 52498, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, >50K 22, Private, 136767, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 30, United-States, <=50K 63, Private, 219540, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 114059, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 56, Private, 247337, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 43, State-gov, 310969, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 40, United-States, <=50K 41, Private, 171546, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 45, United-States, >50K 41, Private, 217455, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 410489, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 59, Private, 146391, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 46, Local-gov, 165484, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 44, United-States, >50K 23, Private, 184271, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 36, United-States, <=50K 46, Self-emp-not-inc, 231347, Some-college, 10, Separated, Prof-specialty, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 53, Private, 95469, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 1902, 40, United-States, >50K 47, Private, 244025, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, Amer-Indian-Eskimo, Male, 0, 0, 56, Puerto-Rico, <=50K 46, Federal-gov, 46537, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 205730, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 56, United-States, >50K 29, Private, 383745, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 1887, 30, United-States, >50K 32, Private, 328199, Assoc-voc, 11, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 90, Private, 84553, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 63, Private, 221072, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 49, ?, <=50K 23, Private, 123983, Assoc-voc, 11, Never-married, Prof-specialty, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 76, ?, 191024, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 30, United-States, <=50K 23, Private, 167868, Assoc-voc, 11, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 225879, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, Other, Female, 0, 0, 30, Mexico, >50K 81, Self-emp-inc, 247232, 10th, 6, Married-civ-spouse, Exec-managerial, Wife, White, Female, 2936, 0, 28, United-States, <=50K 17, Private, 143791, 10th, 6, Never-married, Other-service, Own-child, Black, Female, 0, 0, 12, United-States, <=50K 56, Private, 177271, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 58, Federal-gov, 129786, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 31339, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, >50K 25, Private, 236267, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 130620, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, Asian-Pac-Islander, Female, 0, 0, 35, Philippines, >50K 32, Private, 208180, Assoc-voc, 11, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 24, United-States, >50K 25, Private, 292058, HS-grad, 9, Never-married, Other-service, Other-relative, White, Male, 0, 0, 30, United-States, <=50K 29, Federal-gov, 142712, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Private, 119665, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 41, Private, 116825, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 48, State-gov, 201177, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, United-States, >50K 29, Private, 118337, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 27, ?, 173800, Masters, 14, Never-married, ?, Unmarried, Asian-Pac-Islander, Male, 0, 0, 20, Taiwan, <=50K 55, Private, 289257, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 190912, 11th, 7, Married-civ-spouse, Handlers-cleaners, Husband, Asian-Pac-Islander, Male, 0, 1651, 40, Vietnam, <=50K 45, Private, 140581, Some-college, 10, Widowed, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 50, Private, 174102, HS-grad, 9, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 40, Puerto-Rico, <=50K 22, Private, 316509, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 80, Local-gov, 20101, HS-grad, 9, Widowed, Other-service, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 32, United-States, <=50K 30, Private, 187279, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 44, United-States, <=50K 20, Private, 259496, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 29, Self-emp-not-inc, 181466, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 35, United-States, <=50K 56, Private, 178202, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 63, Private, 188976, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 203027, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 38, State-gov, 142022, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 0, 40, United-States, <=50K 31, Private, 119033, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 216181, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 35, United-States, <=50K 47, Private, 178341, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 46, United-States, >50K 25, Local-gov, 244408, Bachelors, 13, Never-married, Tech-support, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, Vietnam, <=50K 31, Private, 198953, Some-college, 10, Separated, Adm-clerical, Unmarried, Black, Female, 0, 0, 38, United-States, <=50K 28, Private, 173110, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 66326, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 99, United-States, <=50K 30, Local-gov, 181091, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Self-emp-inc, 135500, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 40, United-States, >50K 27, Private, 133929, Bachelors, 13, Never-married, Prof-specialty, Unmarried, White, Female, 0, 0, 36, ?, <=50K 26, Private, 86483, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 167787, HS-grad, 9, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 27, Self-emp-not-inc, 208577, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 2258, 50, United-States, <=50K 43, Private, 216697, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, Other, Male, 0, 0, 32, United-States, <=50K 32, Local-gov, 118457, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 20, Private, 298635, Some-college, 10, Never-married, Sales, Own-child, Asian-Pac-Islander, Male, 0, 0, 30, Philippines, <=50K 21, Local-gov, 212780, 12th, 8, Never-married, Handlers-cleaners, Unmarried, Black, Female, 0, 0, 20, United-States, <=50K 32, Private, 159187, Assoc-voc, 11, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 237995, Assoc-voc, 11, Divorced, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 48, United-States, <=50K 45, Private, 160724, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Vietnam, <=50K 37, Self-emp-inc, 183800, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 1887, 40, United-States, >50K 54, ?, 185936, 9th, 5, Divorced, ?, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 24, Private, 161198, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 28, ?, 113635, 11th, 7, Never-married, ?, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 23, Private, 214542, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 54, ?, 172991, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 203761, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 161141, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, >50K 71, Private, 180117, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 317396, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 52, Self-emp-not-inc, 237868, Some-college, 10, Never-married, Adm-clerical, Unmarried, White, Male, 0, 0, 5, United-States, <=50K 30, Private, 323069, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 181091, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 7688, 0, 40, United-States, >50K 38, Private, 309122, 10th, 6, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Federal-gov, 105936, Assoc-voc, 11, Never-married, Prof-specialty, Not-in-family, White, Female, 13550, 0, 40, United-States, >50K 43, Private, 40024, 11th, 7, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 42, United-States, <=50K 36, Federal-gov, 192443, Some-college, 10, Never-married, Exec-managerial, Not-in-family, Black, Male, 13550, 0, 40, United-States, >50K 24, State-gov, 184216, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 29, ?, 256211, 1st-4th, 2, Never-married, ?, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 55, Private, 205422, 10th, 6, Married-civ-spouse, Other-service, Wife, Black, Female, 0, 0, 40, United-States, <=50K 51, Private, 22211, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 60, United-States, >50K 43, Local-gov, 196308, HS-grad, 9, Divorced, Exec-managerial, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 28, Private, 389713, HS-grad, 9, Divorced, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 82566, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 47, Private, 199058, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 47, Private, 160440, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, >50K 47, Private, 76034, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 57, United-States, >50K 38, Private, 188503, Some-college, 10, Never-married, Adm-clerical, Unmarried, White, Female, 6497, 0, 35, United-States, <=50K 60, Self-emp-not-inc, 92845, 5th-6th, 3, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 29083, HS-grad, 9, Never-married, Sales, Own-child, Amer-Indian-Eskimo, Female, 0, 0, 25, United-States, <=50K 22, Private, 234474, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 25, United-States, <=50K 55, Local-gov, 107308, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 44, Private, 111891, Some-college, 10, Separated, Sales, Other-relative, Black, Female, 0, 0, 35, United-States, <=50K 53, Self-emp-not-inc, 145419, 1st-4th, 2, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 67, Italy, >50K 44, Local-gov, 193425, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 4386, 0, 40, United-States, >50K 28, Federal-gov, 188278, Bachelors, 13, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 30, Local-gov, 303485, Some-college, 10, Never-married, Transport-moving, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 39, Local-gov, 67187, HS-grad, 9, Never-married, Exec-managerial, Own-child, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 43, State-gov, 114508, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 204172, Bachelors, 13, Never-married, Sales, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 27, Local-gov, 162973, Assoc-voc, 11, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 56, United-States, <=50K 64, Self-emp-not-inc, 192695, 5th-6th, 3, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 70, Canada, <=50K 41, Local-gov, 89172, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 163320, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 128230, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 30, United-States, <=50K 27, Private, 246440, 11th, 7, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 50567, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 20, Private, 117476, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 315834, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 1876, 40, United-States, <=50K 28, Local-gov, 214881, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 195516, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Self-emp-not-inc, 218653, Bachelors, 13, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 87205, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 7688, 0, 20, United-States, >50K 40, Private, 164647, Some-college, 10, Divorced, Prof-specialty, Unmarried, Black, Female, 0, 0, 38, United-States, <=50K 19, Private, 129151, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 54, Private, 319697, Some-college, 10, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, <=50K 55, Self-emp-not-inc, 193374, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 167864, Assoc-voc, 11, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 197932, Some-college, 10, Separated, Priv-house-serv, Not-in-family, White, Female, 0, 0, 30, Guatemala, <=50K 51, Private, 102904, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 43, United-States, <=50K 44, Private, 216907, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 37, United-States, <=50K 35, Local-gov, 331395, Assoc-voc, 11, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 42, United-States, <=50K 40, Private, 171424, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 35406, 7th-8th, 4, Separated, Other-service, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 25, Private, 238964, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, >50K 33, Private, 213002, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 1408, 36, United-States, <=50K 32, Private, 27882, Some-college, 10, Never-married, Machine-op-inspct, Other-relative, White, Female, 0, 2205, 40, Holand-Netherlands, <=50K 22, Private, 340543, HS-grad, 9, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 70240, Some-college, 10, Married-civ-spouse, Sales, Wife, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 18, Self-emp-not-inc, 87169, HS-grad, 9, Never-married, Farming-fishing, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 43, Private, 253759, HS-grad, 9, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 45, United-States, <=50K 46, Private, 194431, HS-grad, 9, Never-married, Tech-support, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 63, Private, 137843, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 7298, 0, 48, United-States, >50K 40, ?, 170649, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 8, United-States, <=50K 59, Private, 182460, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 40, Local-gov, 26929, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 399022, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 35, United-States, <=50K 64, ?, 50171, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 10, United-States, <=50K 36, Private, 218490, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 48, Private, 164423, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 124436, Some-college, 10, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 18, Private, 60981, 10th, 6, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 17, Private, 70868, 11th, 7, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 16, United-States, <=50K 36, Private, 150601, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, ?, <=50K 53, Private, 228500, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 36, State-gov, 76767, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 39, United-States, <=50K 20, Private, 218178, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 615367, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 34, Private, 150324, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 51264, 11th, 7, Divorced, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 197642, Some-college, 10, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 229895, 10th, 6, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 167415, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 51, Private, 166934, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 305597, HS-grad, 9, Never-married, Transport-moving, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 301591, HS-grad, 9, Never-married, Exec-managerial, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 47, Federal-gov, 229646, HS-grad, 9, Married-spouse-absent, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, Puerto-Rico, <=50K 28, Self-emp-not-inc, 51461, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 206600, 10th, 6, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 24, Nicaragua, <=50K 25, Private, 176836, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 50, Private, 204447, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 65, United-States, >50K 50, Private, 33304, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 43, Private, 174051, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, <=50K 27, Private, 38918, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 1876, 75, United-States, <=50K 32, Private, 170017, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 44, Private, 98466, 10th, 6, Never-married, Farming-fishing, Unmarried, White, Male, 0, 0, 35, United-States, <=50K 19, Private, 188864, HS-grad, 9, Never-married, Sales, Unmarried, Black, Female, 0, 0, 20, United-States, <=50K 53, Self-emp-inc, 137815, Some-college, 10, Widowed, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 21, Private, 43475, HS-grad, 9, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 557236, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 68, Private, 32779, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 419, 12, United-States, <=50K 31, Private, 161765, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 2051, 57, United-States, <=50K 32, Private, 207668, Bachelors, 13, Never-married, Exec-managerial, Other-relative, White, Male, 0, 2444, 50, United-States, >50K 33, Private, 171215, Masters, 14, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 49, ?, 52590, HS-grad, 9, Never-married, ?, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 24, Private, 183751, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 65, United-States, <=50K 30, Private, 149507, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 42, United-States, <=50K 49, Private, 98092, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 18, Private, 123714, 11th, 7, Never-married, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 30, State-gov, 190385, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 37, United-States, <=50K 51, Private, 334273, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 343440, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 208302, HS-grad, 9, Divorced, Other-service, Other-relative, White, Male, 0, 0, 30, United-States, <=50K 23, Local-gov, 280164, HS-grad, 9, Never-married, Other-service, Own-child, Black, Male, 0, 0, 32, United-States, <=50K 23, Self-emp-not-inc, 174714, 10th, 6, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 36, Private, 184655, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, <=50K 19, Private, 140459, 11th, 7, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 25, United-States, <=50K 53, Self-emp-not-inc, 108815, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 17, Private, 152652, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 25, United-States, <=50K 69, Private, 269499, HS-grad, 9, Widowed, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 8, United-States, <=50K 46, Local-gov, 33373, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 243674, HS-grad, 9, Separated, Tech-support, Not-in-family, White, Male, 0, 0, 46, United-States, <=50K 40, Private, 225432, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, <=50K 56, Private, 215839, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, ?, <=50K 29, Local-gov, 195520, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 70092, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 22, Private, 189888, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 28, Private, 64307, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 94235, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 46, United-States, <=50K 35, Private, 62333, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 260997, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 17, Private, 146268, 10th, 6, Never-married, Other-service, Own-child, White, Female, 0, 0, 10, United-States, <=50K 39, Private, 147258, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Self-emp-not-inc, 207948, Some-college, 10, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 50, Private, 180607, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 56, Local-gov, 104996, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 80, Self-emp-not-inc, 562336, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 20, United-States, <=50K 38, Self-emp-not-inc, 334366, Some-college, 10, Married-civ-spouse, Farming-fishing, Wife, White, Female, 0, 0, 15, United-States, <=50K 52, State-gov, 142757, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 40, United-States, >50K 26, Local-gov, 220656, Bachelors, 13, Never-married, Prof-specialty, Own-child, Black, Male, 0, 0, 38, England, <=50K 43, Private, 96483, HS-grad, 9, Divorced, Other-service, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, South, <=50K 45, Private, 51744, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 42, United-States, <=50K 41, Self-emp-inc, 114967, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, United-States, >50K 30, Private, 393965, Assoc-acdm, 12, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 24, Private, 41838, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 2407, 0, 40, United-States, <=50K 43, Local-gov, 143046, Some-college, 10, Divorced, Other-service, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 44, Private, 209174, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 70, United-States, >50K 54, Private, 183248, HS-grad, 9, Divorced, Transport-moving, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 23, Private, 102942, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 2258, 40, United-States, >50K 33, Self-emp-not-inc, 427474, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 18, Private, 338632, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 16, United-States, <=50K 38, Private, 89559, Some-college, 10, Separated, Prof-specialty, Unmarried, White, Female, 0, 0, 40, Germany, <=50K 41, Self-emp-not-inc, 32533, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 45, United-States, <=50K 22, ?, 255969, 12th, 8, Never-married, ?, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 66, Self-emp-inc, 112376, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 70, ?, 346053, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, Self-emp-not-inc, 147653, 10th, 6, Married-civ-spouse, Craft-repair, Wife, White, Female, 0, 1977, 35, ?, >50K 60, Self-emp-not-inc, 44915, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 10, United-States, <=50K 24, Local-gov, 111450, 10th, 6, Never-married, Craft-repair, Unmarried, Black, Male, 0, 0, 65, Haiti, <=50K 61, Private, 171429, 11th, 7, Divorced, Other-service, Unmarried, White, Female, 0, 0, 36, United-States, <=50K 35, Local-gov, 190964, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 109005, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 52, Private, 404453, HS-grad, 9, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 38, Self-emp-not-inc, 280169, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 7298, 0, 50, United-States, >50K 39, Self-emp-not-inc, 163204, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Self-emp-not-inc, 192256, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 52, Private, 181755, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 183105, HS-grad, 9, Separated, Machine-op-inspct, Unmarried, White, Female, 0, 0, 44, Cuba, <=50K 37, Private, 335168, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, <=50K 38, Local-gov, 86643, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 27, Private, 180262, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 127865, Masters, 14, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 38, Self-emp-not-inc, 146042, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 3103, 0, 60, United-States, >50K 49, Self-emp-not-inc, 102110, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 30, United-States, >50K 38, Private, 152237, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, ?, >50K 22, Private, 202745, HS-grad, 9, Never-married, Machine-op-inspct, Other-relative, White, Male, 0, 0, 55, United-States, <=50K 40, Federal-gov, 199303, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Private, 266467, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Federal-gov, 345259, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 99, United-States, <=50K 24, Private, 204935, Masters, 14, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 56, United-States, <=50K 58, Federal-gov, 244830, Bachelors, 13, Separated, Prof-specialty, Not-in-family, White, Male, 4787, 0, 40, United-States, >50K 24, Private, 190457, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 180138, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 38, Private, 166585, HS-grad, 9, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 29962, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 191129, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 378707, 10th, 6, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 37, Private, 116358, HS-grad, 9, Never-married, Craft-repair, Other-relative, Amer-Indian-Eskimo, Male, 27828, 0, 48, United-States, >50K 48, Private, 240629, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 40, Private, 233320, 7th-8th, 4, Separated, Other-service, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 50, Self-emp-inc, 302708, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 7688, 0, 50, Japan, >50K 57, Private, 29375, HS-grad, 9, Separated, Sales, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 35, United-States, <=50K 36, Local-gov, 137314, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 60, United-States, >50K 41, Private, 140886, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 90, Private, 226968, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 66, Private, 151793, 7th-8th, 4, Widowed, Other-service, Not-in-family, Black, Female, 0, 0, 10, United-States, <=50K 34, Self-emp-not-inc, 56460, HS-grad, 9, Married-civ-spouse, Farming-fishing, Wife, White, Female, 0, 2179, 12, United-States, <=50K 23, Private, 72887, HS-grad, 9, Never-married, Craft-repair, Own-child, Asian-Pac-Islander, Male, 0, 0, 1, Vietnam, <=50K 35, Private, 261646, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 55, United-States, <=50K 32, Private, 178615, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 2407, 0, 40, United-States, <=50K 33, Private, 295589, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Black, Male, 0, 0, 50, United-States, >50K 32, Self-emp-inc, 377836, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 56510, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 32, Self-emp-not-inc, 337696, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 40, Private, 183765, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Self-emp-not-inc, 107846, HS-grad, 9, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 34, Local-gov, 22641, HS-grad, 9, Never-married, Protective-serv, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 35, Private, 204590, Assoc-voc, 11, Married-civ-spouse, Other-service, Wife, Black, Female, 0, 0, 40, United-States, >50K 29, Private, 114801, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 190591, HS-grad, 9, Separated, Other-service, Unmarried, Black, Female, 0, 0, 20, United-States, <=50K 33, State-gov, 220066, Doctorate, 16, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 48, United-States, >50K 22, ?, 228480, HS-grad, 9, Married-civ-spouse, ?, Own-child, White, Female, 0, 0, 20, United-States, <=50K 52, Private, 128378, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Private, 157595, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Local-gov, 152171, 11th, 7, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 10, United-States, <=50K 63, Private, 339755, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, ?, >50K 49, Private, 240841, 7th-8th, 4, Divorced, Other-service, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 58, Private, 94345, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Self-emp-not-inc, 289116, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 59, Private, 176647, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 49, Self-emp-not-inc, 79627, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Local-gov, 210781, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 15, United-States, <=50K 17, ?, 161981, 10th, 6, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 493443, 11th, 7, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 86459, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1887, 50, United-States, >50K 64, Private, 312242, Some-college, 10, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 3, United-States, <=50K 34, Private, 185408, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 63, Private, 101077, Assoc-acdm, 12, Married-spouse-absent, Adm-clerical, Other-relative, White, Female, 0, 0, 35, United-States, <=50K 51, Private, 147200, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 40, State-gov, 166327, Some-college, 10, Divorced, Adm-clerical, Not-in-family, Black, Female, 0, 0, 35, United-States, <=50K 55, Private, 178644, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, <=50K 35, Private, 126675, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 46, ?, <=50K 30, Private, 158420, Bachelors, 13, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 47, ?, 83046, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 18, United-States, <=50K 29, Private, 46609, 10th, 6, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, ?, <=50K 17, ?, 170320, 11th, 7, Never-married, ?, Own-child, White, Female, 0, 0, 8, United-States, <=50K 32, Self-emp-not-inc, 37232, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 45, United-States, >50K 55, Private, 141877, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Local-gov, 81654, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 56, United-States, >50K 50, Private, 177705, Bachelors, 13, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 124792, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 7688, 0, 45, United-States, >50K 32, Self-emp-not-inc, 129497, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, >50K 60, Private, 114413, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 30, United-States, <=50K 53, Private, 189511, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, Private, 111625, Bachelors, 13, Widowed, Exec-managerial, Unmarried, White, Male, 8614, 0, 40, United-States, >50K 45, Private, 246431, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 31, Private, 147654, HS-grad, 9, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 32, Self-emp-not-inc, 443546, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 281751, Some-college, 10, Divorced, Other-service, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 28, Private, 263128, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 26, Private, 292692, 12th, 8, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 47, Self-emp-inc, 96798, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 80, United-States, >50K 34, Private, 430554, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 42, Private, 317078, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 48, Private, 108557, Bachelors, 13, Married-civ-spouse, Tech-support, Wife, White, Female, 99999, 0, 40, United-States, >50K 32, Private, 207400, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 35, Private, 187089, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 42, United-States, >50K 46, Local-gov, 398986, Doctorate, 16, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 1902, 52, United-States, >50K 38, Private, 238980, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, ?, 407495, HS-grad, 9, Married-spouse-absent, ?, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 35, Private, 183800, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 61, ?, 226989, HS-grad, 9, Divorced, ?, Not-in-family, White, Male, 4865, 0, 40, United-States, <=50K 45, Private, 287190, Assoc-acdm, 12, Divorced, Adm-clerical, Unmarried, Black, Male, 0, 0, 35, United-States, <=50K 31, Private, 111363, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 52, Self-emp-inc, 260938, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 20, Private, 183594, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 50, United-States, <=50K 64, ?, 49194, 11th, 7, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 30, United-States, <=50K 20, ?, 117618, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 172496, Masters, 14, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 29, Private, 389713, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Private, 174413, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, State-gov, 189843, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 198546, Masters, 14, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 21, Private, 82497, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 23, Private, 193090, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 30, United-States, <=50K 79, Private, 172220, 7th-8th, 4, Widowed, Priv-house-serv, Not-in-family, White, Female, 2964, 0, 30, United-States, <=50K 55, Private, 208451, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 42, ?, 234277, HS-grad, 9, Married-spouse-absent, ?, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 60, Private, 163729, HS-grad, 9, Divorced, Tech-support, Unmarried, White, Female, 2597, 0, 40, United-States, <=50K 37, Private, 434097, Assoc-acdm, 12, Divorced, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 47, Private, 192053, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 1590, 40, United-States, <=50K 20, State-gov, 178628, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 96827, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, Canada, <=50K 34, Private, 154667, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 160246, Some-college, 10, Divorced, Prof-specialty, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 24, Self-emp-not-inc, 166036, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 23, Private, 186813, HS-grad, 9, Never-married, Protective-serv, Own-child, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 29, Private, 162312, Assoc-voc, 11, Never-married, Machine-op-inspct, Not-in-family, Other, Male, 0, 0, 40, United-States, <=50K 58, Private, 183893, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 55, ?, 270228, Assoc-acdm, 12, Married-civ-spouse, ?, Husband, Black, Male, 7688, 0, 40, United-States, >50K 40, Private, 111829, Masters, 14, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 43, Federal-gov, 175669, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 25, State-gov, 104097, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Local-gov, 117618, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 24, United-States, <=50K 34, Self-emp-inc, 202450, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 26, Private, 109570, Some-college, 10, Separated, Sales, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 60, Private, 101096, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 65, United-States, >50K 39, Private, 236391, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 21, Private, 136975, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 167523, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 2179, 45, United-States, <=50K 33, Private, 240979, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 248612, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 70, United-States, >50K 39, Private, 151023, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 114, 0, 45, United-States, <=50K 29, Private, 236436, Assoc-acdm, 12, Never-married, Prof-specialty, Not-in-family, White, Female, 8614, 0, 40, United-States, >50K 29, ?, 153167, Some-college, 10, Never-married, ?, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 52, Private, 61735, 11th, 7, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 243165, Bachelors, 13, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 30, United-States, >50K 24, Private, 388885, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 77, Self-emp-inc, 84979, Doctorate, 16, Married-civ-spouse, Farming-fishing, Husband, White, Male, 20051, 0, 40, United-States, >50K 34, Self-emp-not-inc, 87209, Masters, 14, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 53, Self-emp-not-inc, 168539, 9th, 5, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 70, United-States, <=50K 31, Private, 179013, HS-grad, 9, Separated, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 58, Private, 196643, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 50, Self-emp-not-inc, 68898, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 55, United-States, >50K 32, Private, 156464, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 35884, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 182714, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 77, Private, 344425, 9th, 5, Married-civ-spouse, Priv-house-serv, Wife, Black, Female, 0, 0, 10, United-States, <=50K 37, Self-emp-not-inc, 177277, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 70767, HS-grad, 9, Married-civ-spouse, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 33, Self-emp-not-inc, 520078, Assoc-acdm, 12, Divorced, Sales, Unmarried, Black, Male, 0, 0, 60, United-States, <=50K 53, Local-gov, 321770, HS-grad, 9, Married-spouse-absent, Transport-moving, Other-relative, White, Female, 0, 0, 35, United-States, <=50K 32, Private, 158416, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 30, Private, 312667, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 208656, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 594, 0, 20, United-States, <=50K 33, Private, 31481, Bachelors, 13, Married-spouse-absent, Other-service, Unmarried, White, Female, 0, 0, 24, United-States, <=50K 31, Private, 259531, Assoc-voc, 11, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 186239, Some-college, 10, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 19, Private, 162954, 12th, 8, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 27, Private, 249315, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 21, Private, 308237, 5th-6th, 3, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Mexico, <=50K 24, Private, 103064, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 185847, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 54, United-States, <=50K 31, Private, 168521, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 60, Private, 198170, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 21, Private, 353628, 10th, 6, Separated, Sales, Unmarried, Black, Female, 0, 0, 38, United-States, <=50K 38, ?, 273285, 11th, 7, Never-married, ?, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 31, Private, 272069, Assoc-voc, 11, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 22328, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Private, 309212, HS-grad, 9, Divorced, Priv-house-serv, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 25, Self-emp-inc, 148888, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 23, Local-gov, 324637, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 53, Self-emp-inc, 55139, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 42, ?, 212206, Masters, 14, Married-civ-spouse, ?, Wife, White, Female, 0, 1887, 48, United-States, >50K 29, Private, 119004, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 2179, 40, United-States, <=50K 45, Private, 252079, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 70, Private, 315868, Bachelors, 13, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 55, Self-emp-inc, 392325, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 99999, 0, 60, United-States, >50K 40, State-gov, 174283, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1887, 50, United-States, >50K 17, Private, 126832, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, United-States, <=50K 18, Private, 126071, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 265706, Masters, 14, Never-married, Sales, Unmarried, White, Male, 0, 0, 60, United-States, >50K 41, Private, 282964, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 328518, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, State-gov, 283499, HS-grad, 9, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 286675, Some-college, 10, Never-married, Exec-managerial, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 56, Private, 136472, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 48, United-States, <=50K 36, Private, 132879, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 45, United-States, <=50K 26, Private, 314798, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 62, Private, 143943, Bachelors, 13, Widowed, Tech-support, Unmarried, White, Female, 0, 0, 7, United-States, <=50K 35, Private, 134367, Assoc-acdm, 12, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 25, Local-gov, 366796, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 195573, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 21, Private, 33616, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 25, United-States, <=50K 31, Private, 164190, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 380281, Assoc-acdm, 12, Never-married, Other-service, Own-child, White, Male, 0, 0, 25, Columbia, <=50K 58, Self-emp-inc, 190763, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 55, Local-gov, 209535, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 54, Private, 156003, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 55699, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 3908, 0, 40, United-States, <=50K 28, Private, 183151, 11th, 7, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 7688, 0, 40, United-States, >50K 40, Private, 198790, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 30, United-States, <=50K 33, Self-emp-not-inc, 272359, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 7298, 0, 80, United-States, >50K 27, Private, 236481, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 10, India, <=50K 55, Private, 143266, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Male, 0, 0, 25, United-States, <=50K 53, Private, 192386, HS-grad, 9, Separated, Transport-moving, Unmarried, White, Male, 0, 0, 45, United-States, <=50K 23, Private, 99543, 12th, 8, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 46, United-States, <=50K 66, Private, 169435, HS-grad, 9, Widowed, Craft-repair, Not-in-family, White, Male, 0, 0, 16, United-States, <=50K 34, Self-emp-not-inc, 34572, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 39, Private, 119272, 10th, 6, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 211601, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 26, Private, 154785, Some-college, 10, Married-spouse-absent, Adm-clerical, Own-child, Other, Female, 0, 0, 35, United-States, <=50K 21, Private, 213041, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, Cuba, <=50K 59, Private, 229939, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 175331, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 226443, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 22, Private, 46561, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 161311, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 50, Private, 98215, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 67, Private, 118363, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 2206, 5, United-States, <=50K 59, Local-gov, 181242, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 356238, Assoc-acdm, 12, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 80, United-States, >50K 56, Self-emp-not-inc, 39380, Some-college, 10, Married-spouse-absent, Farming-fishing, Not-in-family, White, Female, 27828, 0, 20, United-States, >50K 28, Private, 315287, HS-grad, 9, Never-married, Adm-clerical, Other-relative, Black, Male, 0, 0, 40, ?, <=50K 34, Private, 269723, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 2977, 0, 50, United-States, <=50K 63, Private, 34098, 10th, 6, Widowed, Farming-fishing, Unmarried, White, Female, 0, 0, 56, United-States, <=50K 48, Private, 50880, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Germany, <=50K 41, Federal-gov, 356934, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 44, United-States, >50K 26, Private, 276309, Some-college, 10, Never-married, Handlers-cleaners, Own-child, Black, Female, 0, 0, 20, United-States, <=50K 47, Private, 175925, 10th, 6, Married-civ-spouse, Sales, Husband, White, Male, 0, 2179, 52, United-States, <=50K 29, Self-emp-not-inc, 164607, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 30, Private, 224462, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 92863, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 20, United-States, <=50K 27, Private, 179565, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 37, United-States, <=50K 59, Self-emp-not-inc, 31137, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 70, United-States, <=50K 19, Private, 199495, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 175262, 9th, 5, Married-civ-spouse, Handlers-cleaners, Husband, Asian-Pac-Islander, Male, 0, 0, 40, India, <=50K 37, Private, 220585, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Local-gov, 231793, Doctorate, 16, Married-spouse-absent, Prof-specialty, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 34, Federal-gov, 191342, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 0, 38, United-States, <=50K 30, Private, 186420, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 30, Private, 328242, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Hong, >50K 56, Private, 279340, 11th, 7, Separated, Other-service, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 19, Private, 174478, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 151771, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 145636, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 43, United-States, >50K 21, Private, 120326, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 34, Self-emp-not-inc, 246439, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 45, United-States, <=50K 27, Private, 144133, Bachelors, 13, Married-civ-spouse, Exec-managerial, Other-relative, White, Male, 0, 0, 50, United-States, <=50K 44, Local-gov, 145522, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 312055, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 235847, Some-college, 10, Never-married, Exec-managerial, Other-relative, White, Female, 0, 0, 50, United-States, <=50K 37, Private, 187748, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 396482, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 49, Private, 261688, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 5013, 0, 60, United-States, <=50K 20, Private, 39477, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 37, Private, 143058, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 216867, 5th-6th, 3, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, Mexico, <=50K 44, Private, 230592, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 30, Local-gov, 40338, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Local-gov, 115457, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 374983, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 285419, 12th, 8, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 19, ?, 385901, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 22, United-States, <=50K 45, State-gov, 187581, Assoc-voc, 11, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Self-emp-inc, 299036, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, >50K 42, Private, 68729, Some-college, 10, Never-married, Craft-repair, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 27, Private, 333990, Assoc-voc, 11, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 117767, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 25, United-States, <=50K 43, Private, 184378, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, <=50K 21, Private, 232591, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 143851, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, Self-emp-not-inc, 89622, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 80, United-States, >50K 34, Private, 202498, 12th, 8, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Dominican-Republic, <=50K 72, Private, 268861, 7th-8th, 4, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 99, ?, <=50K 54, Private, 343242, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 44, United-States, >50K 30, Private, 460408, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 63, Private, 205246, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 36, Private, 230329, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 25, Private, 197871, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 72, ?, 201375, Assoc-acdm, 12, Widowed, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 55, Private, 194290, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 191814, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 41, Private, 95168, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 20, ?, 137876, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 386136, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 71, ?, 108390, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 3432, 0, 20, United-States, <=50K 41, Private, 152529, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 35, Private, 214891, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Other, Male, 0, 0, 40, Dominican-Republic, <=50K 18, Private, 133654, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 147548, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 57, Private, 73051, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, Self-emp-not-inc, 60166, 1st-4th, 2, Never-married, Exec-managerial, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 65, United-States, <=50K 25, Self-emp-inc, 454934, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 35, United-States, <=50K 64, ?, 338355, Assoc-voc, 11, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 15, United-States, <=50K 35, Self-emp-not-inc, 185621, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 61, Private, 101500, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, State-gov, 36397, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 18, Private, 276540, 12th, 8, Never-married, Sales, Own-child, Black, Female, 0, 0, 15, United-States, <=50K 21, Private, 293968, Some-college, 10, Married-spouse-absent, Sales, Own-child, Black, Female, 0, 0, 20, United-States, <=50K 43, ?, 35523, Assoc-acdm, 12, Divorced, ?, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 32, Local-gov, 186993, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 232132, 12th, 8, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, >50K 48, Private, 176917, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, <=50K 40, Private, 105936, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 105821, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 5178, 0, 40, United-States, >50K 22, ?, 34506, Some-college, 10, Separated, ?, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 42, Private, 178074, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 60, ?, 116961, 7th-8th, 4, Widowed, ?, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 34, Private, 191930, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 27, Private, 130807, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Self-emp-not-inc, 94100, Bachelors, 13, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 65, Self-emp-not-inc, 144822, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 61, Self-emp-inc, 102191, Masters, 14, Widowed, Exec-managerial, Unmarried, White, Female, 0, 0, 99, United-States, <=50K 18, Private, 90934, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 28, United-States, <=50K 49, ?, 296892, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, Puerto-Rico, <=50K 48, Private, 173243, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 26, Private, 258768, Some-college, 10, Never-married, Transport-moving, Not-in-family, Black, Male, 2174, 0, 75, United-States, <=50K 30, Private, 189759, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 68, Self-emp-not-inc, 69249, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, >50K 23, Private, 133061, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 80, United-States, <=50K 65, Self-emp-not-inc, 175202, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 24, United-States, <=50K 32, Private, 27051, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 44, United-States, <=50K 44, Private, 60414, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 48, Local-gov, 317360, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 24, Private, 258298, Assoc-voc, 11, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 58, Private, 174040, Some-college, 10, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Local-gov, 177566, Some-college, 10, Married-spouse-absent, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, Germany, <=50K 54, Private, 162238, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 35, Private, 87556, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 35, Private, 144322, Assoc-acdm, 12, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 24, Private, 190015, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 183173, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 40, United-States, >50K 38, Self-emp-not-inc, 151322, HS-grad, 9, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 57, Local-gov, 47392, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 107125, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 49, Private, 265295, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 189219, Bachelors, 13, Never-married, Tech-support, Own-child, White, Female, 0, 0, 16, United-States, <=50K 56, Private, 147989, Some-college, 10, Married-spouse-absent, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 185732, 11th, 7, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 153516, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, ?, 191910, Some-college, 10, Never-married, ?, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 216145, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 202872, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 12, United-States, <=50K 62, Self-emp-not-inc, 39630, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 48, United-States, <=50K 24, ?, 114292, 9th, 5, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 26, Local-gov, 206721, Bachelors, 13, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 358585, Some-college, 10, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, >50K 33, Private, 377283, Bachelors, 13, Separated, Sales, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 65, ?, 76043, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 1, United-States, >50K 65, Without-pay, 172949, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 2414, 0, 20, United-States, <=50K 46, Private, 110171, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 7688, 0, 40, United-States, >50K 43, Local-gov, 223861, Assoc-voc, 11, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 163455, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 183892, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 47022, HS-grad, 9, Widowed, Handlers-cleaners, Other-relative, White, Female, 0, 0, 48, United-States, <=50K 55, Federal-gov, 145401, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 45, Private, 387074, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, Private, 105363, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 4508, 0, 40, United-States, <=50K 59, Federal-gov, 195467, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 56, Local-gov, 170217, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 156807, HS-grad, 9, Never-married, Other-service, Own-child, Black, Male, 0, 0, 10, United-States, <=50K 26, Private, 255193, 11th, 7, Married-civ-spouse, Exec-managerial, Husband, White, Male, 3411, 0, 40, United-States, <=50K 38, Private, 273640, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 191177, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 48, Self-emp-inc, 184787, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 37, State-gov, 239409, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 63, Self-emp-not-inc, 404547, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 30, United-States, <=50K 27, State-gov, 23740, HS-grad, 9, Never-married, Transport-moving, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 38, United-States, >50K 20, Private, 382153, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 25, United-States, <=50K 26, Private, 164488, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1887, 40, United-States, >50K 21, ?, 228424, 10th, 6, Never-married, ?, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 51, Self-emp-not-inc, 168539, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 189530, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 89419, Assoc-voc, 11, Divorced, Other-service, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 40, Columbia, <=50K 35, Private, 224512, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, >50K 21, ?, 314645, Some-college, 10, Never-married, ?, Not-in-family, White, Female, 0, 0, 43, United-States, <=50K 65, Private, 85787, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Local-gov, 279881, Assoc-voc, 11, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 39, Private, 194287, 7th-8th, 4, Never-married, Other-service, Own-child, White, Male, 0, 1602, 35, United-States, <=50K 24, Private, 141040, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 36, Private, 222294, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 70, ?, 410980, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 10, United-States, >50K 52, Private, 38795, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 64, Private, 182979, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 223277, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 67065, Assoc-voc, 11, Never-married, Priv-house-serv, Not-in-family, White, Male, 594, 0, 25, United-States, <=50K 47, Federal-gov, 160647, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 45796, 12th, 8, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 110597, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 30, United-States, <=50K 33, Private, 166961, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 52, Private, 318975, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, Cuba, <=50K 49, Private, 305657, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 120857, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 18, United-States, <=50K 62, Self-emp-not-inc, 158712, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 6, United-States, <=50K 44, Private, 304530, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 28, Local-gov, 327533, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 3908, 0, 40, United-States, <=50K 68, Local-gov, 233954, Masters, 14, Widowed, Prof-specialty, Unmarried, Black, Female, 0, 0, 40, United-States, >50K 40, Federal-gov, 26880, Some-college, 10, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 70754, 7th-8th, 4, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 22, Private, 184665, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 37, Self-emp-not-inc, 245372, Bachelors, 13, Divorced, Tech-support, Not-in-family, White, Male, 0, 0, 15, United-States, <=50K 62, Private, 252668, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 37, Private, 86551, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 35, Private, 241998, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 4787, 0, 40, United-States, >50K 44, Private, 106900, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 68, United-States, <=50K 41, Private, 204235, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Local-gov, 127772, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 117217, Bachelors, 13, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 48, Federal-gov, 215389, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, >50K 21, Private, 198050, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 28, United-States, <=50K 39, Private, 173476, Prof-school, 15, Married-civ-spouse, Craft-repair, Husband, White, Male, 7688, 0, 40, United-States, >50K 38, Private, 217349, Assoc-voc, 11, Divorced, Prof-specialty, Not-in-family, White, Female, 14344, 0, 40, United-States, >50K 44, Private, 377018, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 56, Private, 99894, 10th, 6, Married-civ-spouse, Sales, Wife, Asian-Pac-Islander, Female, 0, 0, 30, Japan, >50K 25, Private, 170786, 9th, 5, Never-married, Transport-moving, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 32, Local-gov, 250585, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 47, Private, 198769, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 26, Private, 306513, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 178623, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Black, Female, 14084, 0, 60, United-States, >50K 23, Private, 109307, Assoc-voc, 11, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 41, Federal-gov, 106982, Some-college, 10, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, >50K 55, Self-emp-not-inc, 396878, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 25, United-States, <=50K 23, Private, 344278, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 45, Private, 203653, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 7298, 0, 40, United-States, >50K 42, Local-gov, 227890, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1485, 40, United-States, <=50K 29, Private, 107812, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 15, United-States, <=50K 48, Private, 185143, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 143068, Some-college, 10, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 52, Self-emp-inc, 114758, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 50, United-States, >50K 46, Private, 266337, Assoc-voc, 11, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 321787, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 27, State-gov, 21306, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, Germany, <=50K 18, Private, 271935, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 148952, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 24, United-States, <=50K 42, Private, 196626, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 64, ?, 108082, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 199439, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 20, ?, 304076, 11th, 7, Never-married, ?, Own-child, Black, Female, 0, 0, 20, United-States, <=50K 52, Self-emp-inc, 81436, Prof-school, 15, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 44, Self-emp-inc, 352971, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 53, Private, 375134, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 36, Private, 206521, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 27, Private, 330466, Bachelors, 13, Never-married, Tech-support, Other-relative, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 52, Private, 208302, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 60, United-States, <=50K 60, Self-emp-not-inc, 135285, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 171615, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 45, United-States, >50K 64, Self-emp-not-inc, 149698, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Private, 71351, 1st-4th, 2, Never-married, Other-service, Other-relative, White, Male, 0, 0, 25, El-Salvador, <=50K 63, Private, 84737, 7th-8th, 4, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 40, South, <=50K 54, Local-gov, 375134, Assoc-voc, 11, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 207103, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 199314, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, Poland, <=50K 63, Self-emp-not-inc, 289741, Masters, 14, Married-civ-spouse, Farming-fishing, Husband, White, Male, 41310, 0, 50, United-States, <=50K 37, Private, 240837, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 22, Private, 283499, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 54, Private, 97778, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 21698, 10th, 6, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 60, Local-gov, 232618, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 175820, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 25, United-States, <=50K 25, Local-gov, 63996, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 51, Local-gov, 182985, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 47, Federal-gov, 380127, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 44, Self-emp-not-inc, 111483, 10th, 6, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 50, United-States, <=50K 18, ?, 31008, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 30, United-States, <=50K 57, Private, 96346, HS-grad, 9, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 57, United-States, <=50K 22, Private, 317528, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 34, United-States, <=50K 36, State-gov, 223020, Some-college, 10, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 20, United-States, <=50K 33, ?, 173998, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 0, 1485, 38, United-States, <=50K 39, Private, 115076, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 133969, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, Other, Male, 0, 0, 50, United-States, >50K 41, Private, 173858, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 40, China, <=50K 35, Private, 193241, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 38, United-States, <=50K 40, Self-emp-inc, 50644, Assoc-acdm, 12, Divorced, Sales, Unmarried, White, Female, 1506, 0, 40, United-States, <=50K 30, Private, 178841, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 177017, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 1504, 37, United-States, <=50K 25, Private, 253267, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 1902, 36, United-States, >50K 37, Private, 202027, Masters, 14, Married-civ-spouse, Adm-clerical, Husband, White, Male, 7688, 0, 50, United-States, >50K 53, Self-emp-not-inc, 321865, Prof-school, 15, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 34, Self-emp-not-inc, 321709, Assoc-acdm, 12, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 22, Private, 166371, HS-grad, 9, Never-married, Other-service, Other-relative, White, Male, 0, 0, 40, ?, <=50K 18, Private, 210574, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 52, ?, 92968, Masters, 14, Married-civ-spouse, ?, Wife, White, Female, 15024, 0, 40, United-States, >50K 45, Private, 474617, HS-grad, 9, Divorced, Sales, Unmarried, Black, Male, 5455, 0, 40, United-States, <=50K 19, Private, 264390, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 2001, 40, United-States, <=50K 33, Self-emp-inc, 144949, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 65, United-States, <=50K 45, State-gov, 90803, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, State-gov, 126701, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 35, United-States, >50K 40, Private, 178417, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 41, Self-emp-not-inc, 197176, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 75, United-States, >50K 25, Private, 182227, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1579, 40, United-States, <=50K 22, Private, 117606, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 32, United-States, <=50K 52, Private, 349502, Some-college, 10, Never-married, Adm-clerical, Unmarried, White, Male, 0, 0, 45, United-States, <=50K 45, Federal-gov, 81487, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, Puerto-Rico, >50K 32, State-gov, 169583, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 70, United-States, <=50K 26, Private, 485117, Bachelors, 13, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 20, United-States, <=50K 24, Private, 35603, Some-college, 10, Divorced, Other-service, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 37, Private, 175390, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 49, Private, 184986, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Local-gov, 174395, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 35, Private, 187711, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 189878, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 17, Private, 224073, 11th, 7, Never-married, Sales, Own-child, White, Male, 0, 0, 20, United-States, <=50K 48, Private, 159726, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 55, United-States, >50K 40, ?, 65545, Masters, 14, Divorced, ?, Own-child, White, Female, 0, 0, 55, United-States, <=50K 26, Private, 456618, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 2597, 0, 40, United-States, <=50K 35, Private, 202397, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, >50K 21, Private, 206681, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 15, United-States, <=50K 54, Private, 222020, 10th, 6, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 40, Private, 137304, Bachelors, 13, Divorced, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 51, Private, 141645, Some-college, 10, Separated, Exec-managerial, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 60, Self-emp-not-inc, 218085, HS-grad, 9, Married-civ-spouse, Other-service, Wife, Black, Female, 0, 0, 50, United-States, <=50K 22, Private, 52596, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 8, United-States, <=50K 20, Private, 197997, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 191444, 11th, 7, Never-married, Farming-fishing, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 40767, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 172577, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 44, United-States, <=50K 36, Private, 241998, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 65, State-gov, 215908, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 2174, 40, United-States, >50K 48, Private, 212120, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Private, 109133, Masters, 14, Separated, Exec-managerial, Not-in-family, White, Male, 27828, 0, 60, Iran, >50K 20, Private, 224424, 12th, 8, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 41, State-gov, 214985, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 55, Self-emp-not-inc, 147098, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 39, Local-gov, 149833, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 41, Federal-gov, 253770, Some-college, 10, Married-civ-spouse, Transport-moving, Wife, White, Female, 7298, 0, 40, United-States, >50K 80, Private, 252466, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 24, United-States, <=50K 59, State-gov, 132717, 10th, 6, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 138944, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 280570, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 3103, 0, 50, United-States, >50K 56, Self-emp-not-inc, 144380, Some-college, 10, Married-spouse-absent, Prof-specialty, Not-in-family, Black, Male, 0, 0, 50, United-States, <=50K 69, Local-gov, 660461, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, Black, Female, 0, 0, 20, United-States, <=50K 49, Private, 177211, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 33, Private, 197424, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 5013, 0, 40, United-States, <=50K 28, Self-emp-inc, 31717, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 49, Private, 296849, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 51, Local-gov, 193720, HS-grad, 9, Married-spouse-absent, Handlers-cleaners, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 106698, Some-college, 10, Divorced, Other-service, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 66, Private, 214469, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 13, United-States, <=50K 44, Private, 185798, Assoc-voc, 11, Separated, Craft-repair, Other-relative, White, Male, 0, 0, 48, United-States, >50K 26, Private, 333108, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 35210, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 140845, 10th, 6, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 155, 40, United-States, <=50K 25, ?, 335376, Bachelors, 13, Never-married, ?, Own-child, White, Female, 0, 0, 30, United-States, <=50K 17, Private, 170455, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 8, United-States, <=50K 52, Private, 298215, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 34, ?, 93834, HS-grad, 9, Separated, ?, Own-child, White, Female, 0, 0, 8, United-States, <=50K 24, Private, 404416, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, ?, 206916, Bachelors, 13, Married-spouse-absent, ?, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 65, Private, 143175, Some-college, 10, Widowed, Sales, Other-relative, White, Female, 0, 0, 45, United-States, <=50K 36, Self-emp-not-inc, 409189, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 19, Private, 285750, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 30, United-States, <=50K 43, Private, 235556, Some-college, 10, Married-spouse-absent, Sales, Not-in-family, White, Male, 0, 0, 45, Mexico, <=50K 39, Local-gov, 170382, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 50, England, >50K 48, Private, 195437, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 50, Local-gov, 191130, Assoc-voc, 11, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 21, Private, 231160, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 25, United-States, <=50K 36, Private, 47310, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 33, Private, 214635, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 36, Haiti, <=50K 50, Federal-gov, 65160, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, State-gov, 423222, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 99999, 0, 80, United-States, >50K 34, Private, 263307, Bachelors, 13, Never-married, Sales, Unmarried, Black, Male, 0, 0, 45, ?, <=50K 70, Self-emp-inc, 272896, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 232854, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 442035, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 127875, Bachelors, 13, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 40, United-States, >50K 40, Private, 283724, 9th, 5, Never-married, Craft-repair, Other-relative, Black, Male, 0, 0, 49, United-States, <=50K 46, Private, 403911, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 1902, 40, United-States, >50K 21, ?, 228649, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 20, United-States, <=50K 40, Private, 177027, Bachelors, 13, Married-civ-spouse, Other-service, Wife, Asian-Pac-Islander, Female, 7688, 0, 52, Japan, >50K 47, Private, 249935, 11th, 7, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 8, United-States, <=50K 19, Private, 533147, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 22, Private, 137862, Some-college, 10, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 16, United-States, <=50K 20, Private, 249543, Some-college, 10, Never-married, Protective-serv, Own-child, White, Female, 0, 0, 16, United-States, <=50K 46, Local-gov, 230979, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 4787, 0, 25, United-States, >50K 41, Private, 137126, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 45, United-States, >50K 17, Private, 147339, 10th, 6, Never-married, Prof-specialty, Own-child, Other, Female, 0, 0, 15, United-States, <=50K 41, Private, 256647, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 28, Private, 111696, HS-grad, 9, Separated, Craft-repair, Not-in-family, White, Male, 0, 1974, 40, United-States, <=50K 20, ?, 150084, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 25, United-States, <=50K 24, Private, 285457, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 303867, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 44, Federal-gov, 113597, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 26, Self-emp-not-inc, 151626, HS-grad, 9, Never-married, Prof-specialty, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 47, Self-emp-not-inc, 26145, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 24, Private, 176189, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, Federal-gov, 497253, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, United-States, >50K 41, Private, 41090, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 2002, 60, United-States, <=50K 38, Self-emp-not-inc, 282461, 7th-8th, 4, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 35, United-States, >50K 21, Private, 225541, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 203488, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 45, United-States, <=50K 23, ?, 296613, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 32, United-States, <=50K 40, Private, 99373, 10th, 6, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 47, Local-gov, 109705, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 144947, Bachelors, 13, Divorced, Exec-managerial, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 38, Private, 617898, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 50, Private, 38310, 7th-8th, 4, Divorced, Other-service, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 248993, HS-grad, 9, Married-spouse-absent, Farming-fishing, Other-relative, Black, Male, 0, 0, 40, United-States, <=50K 65, ?, 149131, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, Italy, >50K 33, Private, 69311, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, Federal-gov, 143766, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 65, Private, 213477, Masters, 14, Divorced, Sales, Not-in-family, White, Male, 0, 0, 28, United-States, <=50K 24, Private, 275691, 11th, 7, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 39, United-States, <=50K 26, Private, 59367, Bachelors, 13, Never-married, Machine-op-inspct, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 35551, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 66, Private, 236784, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 8, Cuba, <=50K 43, Local-gov, 193755, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 315291, Bachelors, 13, Never-married, Adm-clerical, Other-relative, Black, Female, 0, 0, 40, United-States, <=50K 22, Private, 290504, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 256240, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 69, ?, 199591, Prof-school, 15, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 25, ?, <=50K 27, Private, 178709, Masters, 14, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 48, Private, 449354, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 4386, 0, 45, United-States, >50K 24, Private, 187937, Bachelors, 13, Never-married, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 18, Never-worked, 157131, 11th, 7, Never-married, ?, Own-child, White, Female, 0, 0, 10, United-States, <=50K 53, Local-gov, 188772, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 26, Private, 157617, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Poland, <=50K 60, Private, 96099, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 21, Private, 122322, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 60, United-States, <=50K 39, Private, 409189, 5th-6th, 3, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Mexico, <=50K 45, Private, 175925, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 76, Self-emp-not-inc, 236878, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 30, United-States, <=50K 19, Private, 216647, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 34, Private, 300681, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 40, Jamaica, >50K 54, Private, 327769, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 194723, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 44, Local-gov, 31251, 7th-8th, 4, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 212506, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 23, Private, 23037, 12th, 8, Never-married, Handlers-cleaners, Own-child, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 37, Self-emp-not-inc, 29054, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 41, Private, 92733, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 21, State-gov, 184678, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 35, United-States, <=50K 37, Federal-gov, 32528, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, England, >50K 63, Private, 125954, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 2174, 0, 40, United-States, <=50K 35, Private, 73715, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 209212, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 56, ?, <=50K 41, Private, 287037, Some-college, 10, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 50, Self-emp-not-inc, 64667, HS-grad, 9, Divorced, Prof-specialty, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 60, Vietnam, <=50K 26, Self-emp-inc, 366662, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 50, United-States, <=50K 36, Local-gov, 113337, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 42, United-States, >50K 47, Private, 387468, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, Scotland, >50K 51, Private, 384248, Some-college, 10, Divorced, Exec-managerial, Unmarried, Black, Female, 0, 0, 50, United-States, <=50K 41, Private, 332703, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, Other, Female, 0, 625, 40, United-States, <=50K 40, Private, 198873, Prof-school, 15, Married-civ-spouse, Prof-specialty, Wife, White, Female, 15024, 0, 30, United-States, >50K 32, Private, 317809, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 4064, 0, 50, United-States, <=50K 37, Local-gov, 160910, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 7298, 0, 40, United-States, >50K 40, Self-emp-inc, 182629, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 56, Private, 267652, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 410186, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 365411, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 42, United-States, <=50K 28, Private, 205337, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Self-emp-not-inc, 100999, 11th, 7, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 30, United-States, <=50K 44, Private, 197462, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Self-emp-not-inc, 199143, Prof-school, 15, Divorced, Prof-specialty, Unmarried, White, Female, 7430, 0, 44, United-States, >50K 47, Private, 191978, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 50178, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 72442, 11th, 7, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, >50K 21, Private, 248512, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 178140, Bachelors, 13, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 45, United-States, >50K 58, Private, 354024, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 35, Private, 143589, Bachelors, 13, Married-spouse-absent, Prof-specialty, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 35, Private, 219902, Assoc-voc, 11, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 29, Local-gov, 419722, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Male, 3674, 0, 40, United-States, <=50K 40, Private, 154374, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 40, United-States, >50K 33, Private, 132601, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, >50K 38, Self-emp-not-inc, 29430, Some-college, 10, Divorced, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 50, Self-emp-not-inc, 30731, Assoc-voc, 11, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 66, Private, 210825, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Local-gov, 251091, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Private, 219034, 11th, 7, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 55, Federal-gov, 35723, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 46, Private, 358886, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 248708, Assoc-acdm, 12, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, ?, 77937, 12th, 8, Divorced, ?, Not-in-family, White, Female, 0, 0, 40, Canada, <=50K 30, Private, 30063, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 29, Private, 253799, 12th, 8, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 42, England, <=50K 60, ?, 41553, Some-college, 10, Widowed, ?, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 24, Private, 59146, HS-grad, 9, Separated, Sales, Unmarried, White, Female, 0, 0, 48, United-States, <=50K 42, Self-emp-not-inc, 343609, Some-college, 10, Separated, Other-service, Unmarried, Black, Female, 0, 0, 50, United-States, <=50K 26, Private, 216010, HS-grad, 9, Separated, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 164526, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 150958, 5th-6th, 3, Never-married, Farming-fishing, Unmarried, White, Male, 0, 0, 48, Guatemala, <=50K 26, Private, 244495, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, <=50K 23, Private, 199336, Assoc-voc, 11, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 60, Private, 151369, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 49, Federal-gov, 118701, HS-grad, 9, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 46, Private, 219611, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 184568, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 48, Self-emp-not-inc, 246891, Prof-school, 15, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 70, Self-emp-inc, 243436, 9th, 5, Divorced, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 44, Local-gov, 68318, Masters, 14, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 55, United-States, <=50K 58, Private, 56331, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 190591, Assoc-acdm, 12, Divorced, Exec-managerial, Not-in-family, Black, Female, 0, 0, 40, Jamaica, <=50K 54, Private, 140359, 7th-8th, 4, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 3900, 40, United-States, <=50K 42, Self-emp-inc, 23510, Masters, 14, Divorced, Exec-managerial, Unmarried, Asian-Pac-Islander, Male, 0, 2201, 60, India, >50K 28, Private, 122540, 10th, 6, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 65, Private, 212562, 11th, 7, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 20, United-States, <=50K 35, Self-emp-not-inc, 112497, HS-grad, 9, Married-civ-spouse, Craft-repair, Other-relative, White, Male, 0, 0, 35, Ireland, <=50K 82, Private, 147729, 5th-6th, 3, Widowed, Other-service, Unmarried, White, Male, 0, 0, 20, United-States, <=50K 48, Self-emp-not-inc, 296066, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 44, Private, 148138, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 15024, 0, 40, Japan, >50K 68, Private, 50351, Masters, 14, Never-married, Adm-clerical, Not-in-family, White, Female, 6360, 0, 20, United-States, <=50K 42, Private, 306496, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 210029, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 2001, 37, United-States, <=50K 54, Private, 163894, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, United-States, <=50K 22, Private, 113936, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 43, Self-emp-not-inc, 316820, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 84, United-States, <=50K 17, Private, 53367, 9th, 5, Never-married, Other-service, Own-child, White, Female, 0, 0, 35, United-States, <=50K 46, Self-emp-not-inc, 95256, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 59, Private, 127728, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Private, 66686, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 70, ?, 207627, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 2228, 0, 24, United-States, <=50K 57, Self-emp-inc, 199768, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 1902, 30, United-States, >50K 47, ?, 186805, HS-grad, 9, Married-civ-spouse, ?, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 31, Private, 154297, HS-grad, 9, Never-married, Sales, Unmarried, Black, Female, 0, 0, 24, United-States, <=50K 23, Private, 103064, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 17, Private, 93235, 12th, 8, Never-married, Other-service, Own-child, White, Female, 0, 1721, 25, United-States, <=50K 63, Private, 440607, Preschool, 1, Married-civ-spouse, Prof-specialty, Husband, Other, Male, 0, 0, 30, Mexico, <=50K 44, Private, 212894, Prof-school, 15, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 55, United-States, >50K 30, Private, 167990, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 23, Private, 378460, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 20, United-States, <=50K 44, Private, 151089, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1887, 60, United-States, >50K 24, Private, 153583, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 114639, Some-college, 10, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 20, United-States, <=50K 37, Private, 344480, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 65, United-States, <=50K 24, Private, 188300, 11th, 7, Never-married, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 105938, HS-grad, 9, Divorced, Machine-op-inspct, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 42, Self-emp-not-inc, 217826, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 25, Jamaica, <=50K 20, Private, 379525, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 10, United-States, <=50K 34, State-gov, 177331, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 4386, 0, 40, United-States, >50K 37, Private, 127918, Some-college, 10, Never-married, Transport-moving, Unmarried, White, Female, 0, 0, 20, Puerto-Rico, <=50K 47, Federal-gov, 27067, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 250038, 9th, 5, Never-married, Farming-fishing, Other-relative, White, Male, 0, 0, 45, Mexico, <=50K 36, Self-emp-not-inc, 36270, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 1977, 65, United-States, >50K 60, Private, 308608, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 64, Self-emp-inc, 213574, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 2635, 0, 10, United-States, <=50K 32, Local-gov, 235109, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 33, State-gov, 374905, 10th, 6, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 71, Private, 118876, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 14, United-States, <=50K 55, Local-gov, 223716, Some-college, 10, Divorced, Exec-managerial, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 85, Self-emp-not-inc, 166027, HS-grad, 9, Widowed, Sales, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 57, Self-emp-not-inc, 275943, 7th-8th, 4, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, ?, <=50K 39, Private, 198654, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 2415, 67, India, >50K 25, Private, 109080, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 55, United-States, <=50K 58, Private, 104333, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 57, Private, 195876, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 390879, Assoc-voc, 11, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 36, United-States, <=50K 19, Private, 197748, 11th, 7, Divorced, Sales, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 40, Private, 442045, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 44216, HS-grad, 9, Never-married, Protective-serv, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 43, Federal-gov, 114537, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, ?, 253370, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 35, United-States, >50K 19, Private, 274830, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 24, Private, 321763, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 34, Private, 213226, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 65, United-States, >50K 22, Private, 167787, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 64, Self-emp-not-inc, 352712, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 55, United-States, <=50K 55, ?, 316027, 7th-8th, 4, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, ?, <=50K 26, Private, 213412, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 80, Private, 202483, HS-grad, 9, Married-spouse-absent, Adm-clerical, Not-in-family, White, Female, 0, 0, 16, United-States, <=50K 79, Local-gov, 146244, Doctorate, 16, Widowed, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 58, Self-emp-not-inc, 450544, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 43, Private, 81243, Bachelors, 13, Divorced, Tech-support, Not-in-family, White, Male, 0, 1876, 40, United-States, <=50K 43, Private, 195258, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Private, 57929, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 35, Private, 953588, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 51, Private, 99064, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 5013, 0, 40, United-States, <=50K 52, Local-gov, 194788, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Female, 4787, 0, 60, United-States, >50K 43, Self-emp-inc, 155293, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 68, Private, 204082, Some-college, 10, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 34, State-gov, 216283, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 45, United-States, >50K 37, Private, 355856, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Cambodia, >50K 22, Private, 297380, HS-grad, 9, Never-married, Sales, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 32, Private, 425622, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 55, United-States, <=50K 65, Self-emp-not-inc, 145628, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 115549, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 60, United-States, <=50K 37, Private, 245482, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Asian-Pac-Islander, Male, 0, 0, 40, ?, <=50K 40, Self-emp-inc, 142444, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 40, Private, 134026, 11th, 7, Never-married, Other-service, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 177366, HS-grad, 9, Separated, Other-service, Other-relative, White, Female, 0, 0, 20, United-States, <=50K 35, Private, 38245, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 62, Self-emp-not-inc, 215944, 5th-6th, 3, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 30, United-States, <=50K 49, Private, 115784, Assoc-voc, 11, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 45, United-States, <=50K 49, Private, 170165, HS-grad, 9, Divorced, Machine-op-inspct, Other-relative, White, Female, 0, 0, 55, United-States, <=50K 47, Private, 355320, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 40, United-States, >50K 45, Private, 116163, HS-grad, 9, Separated, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 405644, 1st-4th, 2, Married-spouse-absent, Farming-fishing, Other-relative, White, Male, 0, 0, 77, Mexico, <=50K 36, Local-gov, 223433, Assoc-voc, 11, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 53, United-States, >50K 36, Private, 41624, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 70, Mexico, <=50K 44, Private, 151089, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 50, United-States, >50K 51, State-gov, 285747, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 60, United-States, >50K 25, State-gov, 108542, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Self-emp-not-inc, 212318, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 57, Private, 173090, HS-grad, 9, Widowed, Sales, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 46, Private, 26781, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 59, Private, 31782, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, >50K 28, Private, 189241, 11th, 7, Married-civ-spouse, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 164229, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Male, 2597, 0, 40, United-States, <=50K 35, Private, 240467, HS-grad, 9, Married-spouse-absent, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 27, Private, 263614, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 29, Private, 74500, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 43, Federal-gov, 263502, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, Federal-gov, 47707, HS-grad, 9, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 26, Private, 231638, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 55, ?, 389479, Masters, 14, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 50, United-States, >50K 36, Private, 111128, HS-grad, 9, Separated, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 152307, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 23, ?, 280134, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 609789, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 30, ?, <=50K 41, Private, 184466, 11th, 7, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 55, United-States, <=50K 44, Private, 216411, Assoc-voc, 11, Separated, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, Dominican-Republic, <=50K 48, Self-emp-not-inc, 324173, Assoc-voc, 11, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 35, Local-gov, 300681, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, Black, Male, 7298, 0, 35, United-States, >50K 43, Local-gov, 598995, Bachelors, 13, Divorced, Prof-specialty, Unmarried, Black, Female, 0, 0, 42, United-States, <=50K 57, Federal-gov, 140711, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 44, Local-gov, 262241, HS-grad, 9, Married-civ-spouse, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 308136, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 148590, 10th, 6, Widowed, Craft-repair, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 52, Private, 195635, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 2051, 38, United-States, <=50K 30, Private, 228406, HS-grad, 9, Separated, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 31, Private, 136398, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 50, Thailand, >50K 21, ?, 305466, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 70, United-States, <=50K 50, Self-emp-inc, 175070, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 43, Self-emp-not-inc, 34007, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 70, United-States, >50K 33, Private, 121195, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, Other, Male, 0, 0, 50, United-States, <=50K 23, Federal-gov, 216853, Assoc-voc, 11, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 25, United-States, <=50K 35, Private, 81280, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 65, Yugoslavia, >50K 18, Private, 212936, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 15, United-States, <=50K 21, ?, 213055, Some-college, 10, Never-married, ?, Unmarried, Other, Female, 0, 0, 40, United-States, <=50K 33, Local-gov, 220430, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 70, United-States, >50K 30, Federal-gov, 73514, Bachelors, 13, Never-married, Exec-managerial, Other-relative, Asian-Pac-Islander, Female, 0, 0, 45, United-States, <=50K 21, Private, 307371, Some-college, 10, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 15, United-States, <=50K 36, Local-gov, 380614, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 35, Germany, >50K 38, Private, 119992, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 192002, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 60, Canada, >50K 24, Private, 327518, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 24, Private, 220323, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 40, United-States, <=50K 39, Private, 421633, Some-college, 10, Divorced, Protective-serv, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 43, Private, 154210, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 2829, 0, 60, China, <=50K 43, Self-emp-not-inc, 35034, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 21, United-States, <=50K 62, ?, 378239, Masters, 14, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 2, United-States, >50K 30, State-gov, 270218, Bachelors, 13, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 25, Private, 254933, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 61751, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 35, United-States, <=50K 22, Private, 137876, Some-college, 10, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 73, Private, 336007, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 2246, 40, United-States, >50K 26, Private, 222539, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 24, Private, 233856, HS-grad, 9, Never-married, Machine-op-inspct, Other-relative, Black, Male, 0, 0, 45, United-States, <=50K 18, Private, 198616, 12th, 8, Never-married, Craft-repair, Own-child, White, Male, 594, 0, 20, United-States, <=50K 35, Private, 202027, Bachelors, 13, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 7298, 0, 35, United-States, >50K 22, Private, 203182, Some-college, 10, Separated, Sales, Unmarried, White, Female, 0, 0, 43, United-States, <=50K 28, Private, 221317, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Mexico, <=50K 38, Private, 186934, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 68, ?, 351402, Doctorate, 16, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 70, United-States, <=50K 40, Local-gov, 179580, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 26803, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 84, United-States, >50K 42, Private, 344624, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1902, 50, United-States, >50K 31, State-gov, 59969, HS-grad, 9, Married-civ-spouse, Adm-clerical, Other-relative, White, Female, 0, 0, 35, United-States, <=50K 33, Private, 162930, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, Italy, <=50K 54, Self-emp-not-inc, 192654, Bachelors, 13, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 63, Private, 117681, HS-grad, 9, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 67, Self-emp-not-inc, 179285, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 30, United-States, <=50K 47, Private, 217161, HS-grad, 9, Divorced, Other-service, Not-in-family, Black, Female, 0, 0, 14, United-States, <=50K 67, Self-emp-inc, 116517, Bachelors, 13, Widowed, Other-service, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 33, Private, 170336, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, Other, Female, 0, 0, 19, United-States, <=50K 33, Local-gov, 256529, HS-grad, 9, Separated, Other-service, Own-child, White, Female, 0, 0, 80, United-States, <=50K 25, Local-gov, 227886, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 141706, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 361888, Some-college, 10, Divorced, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 185407, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 7688, 0, 40, United-States, >50K 35, Self-emp-not-inc, 176101, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 80, United-States, >50K 18, Private, 216730, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 12, United-States, <=50K 54, ?, 155755, HS-grad, 9, Divorced, ?, Not-in-family, White, Female, 4416, 0, 25, United-States, <=50K 30, Private, 609789, 11th, 7, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, Mexico, <=50K 29, Private, 136017, 10th, 6, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 41, Private, 58880, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 7688, 0, 10, United-States, >50K 40, Private, 285787, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Private, 173243, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 5178, 0, 40, United-States, >50K 39, Private, 160916, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 45, United-States, <=50K 42, Private, 227397, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 49, Self-emp-not-inc, 111066, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 23, Private, 189924, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 31740, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Self-emp-not-inc, 120837, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 2042, 48, United-States, <=50K 31, Private, 172304, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 72, ?, 166253, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 2, United-States, <=50K 31, Private, 86492, Assoc-voc, 11, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 30, United-States, >50K 90, Private, 206667, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 27, Self-emp-not-inc, 153546, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 18, ?, 189041, HS-grad, 9, Never-married, ?, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 30, Self-emp-not-inc, 115932, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 99999, 0, 50, United-States, >50K 27, Local-gov, 151626, HS-grad, 9, Never-married, Prof-specialty, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 27, Self-emp-not-inc, 37302, 11th, 7, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 28, Private, 109001, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 195488, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 45, United-States, <=50K 43, Local-gov, 216116, Masters, 14, Separated, Prof-specialty, Unmarried, Black, Female, 0, 0, 37, United-States, <=50K 26, Private, 118497, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 48, Self-emp-not-inc, 101233, Assoc-voc, 11, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 15, United-States, <=50K 41, Private, 349703, Assoc-acdm, 12, Married-civ-spouse, Farming-fishing, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 32, Private, 226883, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Germany, <=50K 23, Private, 214635, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 169672, 11th, 7, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 65, United-States, <=50K 42, Private, 71458, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 27, State-gov, 142621, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 4101, 0, 40, United-States, <=50K 34, Private, 125279, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 197303, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 46, Local-gov, 148995, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 4787, 0, 45, United-States, >50K 34, Private, 69251, Some-college, 10, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 39, Private, 160123, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 137310, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, ?, <=50K 25, Private, 323229, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 138626, Assoc-voc, 11, Divorced, Exec-managerial, Not-in-family, White, Male, 2174, 0, 50, United-States, <=50K 46, Private, 102359, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 151888, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 4650, 0, 50, Ireland, <=50K 37, Private, 404661, Some-college, 10, Never-married, Exec-managerial, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 39, Private, 99146, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, ?, >50K 38, Self-emp-not-inc, 185325, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Self-emp-not-inc, 230268, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Self-emp-inc, 38819, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 37, Private, 380614, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 13, United-States, >50K 45, Private, 319637, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 71, Private, 149040, 12th, 8, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 320984, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 19, ?, 117201, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 22, United-States, <=50K 38, Private, 81965, Assoc-voc, 11, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Local-gov, 182302, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 53434, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 48, Private, 216214, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, Self-emp-inc, 24127, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 54, United-States, >50K 32, Federal-gov, 115066, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 120277, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 57, Self-emp-not-inc, 134286, Some-college, 10, Separated, Sales, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 55, Private, 26716, 10th, 6, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 48, ?, 174533, 11th, 7, Separated, ?, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 46, Self-emp-inc, 175958, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, ?, <=50K 36, Private, 218948, 9th, 5, Separated, Other-service, Unmarried, Black, Female, 0, 0, 40, ?, <=50K 66, Private, 117746, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 26, Private, 206199, HS-grad, 9, Never-married, Adm-clerical, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 58, Self-emp-inc, 89922, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 40, United-States, >50K 62, Private, 69867, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 31, Private, 109020, Bachelors, 13, Never-married, Prof-specialty, Unmarried, Other, Male, 0, 0, 40, United-States, <=50K 77, ?, 158847, Assoc-voc, 11, Married-spouse-absent, ?, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 25, Private, 130302, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 156728, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 56, United-States, <=50K 33, Private, 424719, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 51, Federal-gov, 217647, Some-college, 10, Divorced, Prof-specialty, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 20, Private, 33087, Assoc-voc, 11, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 40, Federal-gov, 241895, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 38455, 10th, 6, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Local-gov, 81054, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 44, Private, 163215, 12th, 8, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 156728, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Self-emp-not-inc, 127930, HS-grad, 9, Married-spouse-absent, Farming-fishing, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 46, Federal-gov, 227310, Some-college, 10, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 24, Private, 96844, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 17, United-States, <=50K 18, Private, 245199, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 46385, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, Private, 186385, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 8, United-States, <=50K 55, Private, 252714, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 68, Private, 154897, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 41, Private, 320744, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 50, Private, 138852, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 48, Private, 102092, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, ?, 32533, Some-college, 10, Never-married, ?, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 45, Private, 278151, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 338290, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 34378, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 43, Private, 91959, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 36, Private, 265881, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 60, Private, 276009, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 30, Philippines, <=50K 27, Private, 193898, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 36, Private, 139364, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 47, State-gov, 306473, Assoc-acdm, 12, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 37232, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 80, United-States, <=50K 19, State-gov, 56424, 12th, 8, Never-married, Transport-moving, Own-child, Black, Male, 0, 0, 20, United-States, <=50K 33, Private, 165235, Bachelors, 13, Never-married, Other-service, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 35, Thailand, <=50K 34, Private, 153326, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Private, 106976, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 57, Private, 109015, Some-college, 10, Divorced, Sales, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 59, Private, 154100, Masters, 14, Never-married, Sales, Not-in-family, White, Female, 27828, 0, 45, United-States, >50K 36, Private, 183739, HS-grad, 9, Married-civ-spouse, Craft-repair, Own-child, White, Female, 0, 2002, 40, United-States, <=50K 60, Private, 367695, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Local-gov, 156015, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 185132, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 20, Self-emp-not-inc, 188274, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 10, United-States, <=50K 28, Local-gov, 50512, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 2202, 0, 50, United-States, <=50K 24, State-gov, 147719, Masters, 14, Never-married, Prof-specialty, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 20, India, <=50K 31, Private, 414525, 12th, 8, Never-married, Farming-fishing, Not-in-family, Black, Male, 0, 0, 60, United-States, <=50K 38, Private, 289148, HS-grad, 9, Married-spouse-absent, Craft-repair, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 176069, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 55, State-gov, 199713, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 15, United-States, <=50K 49, Private, 297884, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 4064, 0, 50, United-States, <=50K 33, Private, 204829, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 52, Private, 155433, 5th-6th, 3, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, ?, <=50K 24, Local-gov, 32950, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 46, Private, 233511, Bachelors, 13, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 20, Private, 210781, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 50, Private, 190762, 5th-6th, 3, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Mexico, <=50K 22, Private, 83315, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 32, Self-emp-inc, 343872, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 35, Haiti, <=50K 46, Private, 185385, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 65, United-States, >50K 62, ?, 302142, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 2961, 0, 30, United-States, <=50K 39, Private, 80324, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 62, United-States, >50K 26, Private, 357933, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 15, United-States, <=50K 20, Private, 211293, Some-college, 10, Never-married, Sales, Own-child, Black, Female, 0, 0, 14, United-States, <=50K 37, Self-emp-inc, 199265, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 40, Private, 202872, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 24, United-States, <=50K 22, Private, 195075, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 38, United-States, <=50K 32, Private, 317378, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 10520, 0, 40, United-States, >50K 41, Private, 187802, Some-college, 10, Divorced, Tech-support, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 24, Private, 97212, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 47902, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, State-gov, 76767, Prof-school, 15, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 39, United-States, >50K 42, Private, 172297, Masters, 14, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 1902, 40, United-States, >50K 56, Private, 274475, 9th, 5, Widowed, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 105244, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 55, Local-gov, 165695, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 253801, HS-grad, 9, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 305597, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 61, Self-emp-not-inc, 352448, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 26, Private, 242768, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 49, Self-emp-inc, 201080, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 18, Local-gov, 159032, 7th-8th, 4, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 149568, 9th, 5, Never-married, Farming-fishing, Other-relative, Black, Male, 0, 0, 40, United-States, <=50K 24, Private, 229553, HS-grad, 9, Never-married, Other-service, Own-child, Black, Female, 0, 0, 20, ?, <=50K 24, State-gov, 155775, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 120074, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Local-gov, 257588, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 177907, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 65, United-States, <=50K 40, Private, 309311, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Self-emp-not-inc, 138975, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, <=50K 43, Self-emp-not-inc, 187778, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 20, United-States, <=50K 19, Private, 35865, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 50, Private, 234373, Masters, 14, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 1485, 40, United-States, <=50K 17, ?, 151141, 10th, 6, Never-married, ?, Own-child, White, Male, 0, 0, 30, United-States, <=50K 39, Private, 144688, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 0, 50, United-States, <=50K 43, Private, 248094, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 248094, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 213821, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 31, State-gov, 55849, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 121712, Bachelors, 13, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Federal-gov, 164552, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 1876, 40, United-States, <=50K 55, Private, 223127, 9th, 5, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 190514, 7th-8th, 4, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 75, United-States, <=50K 29, Private, 203797, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, United-States, <=50K 28, Private, 378460, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 10520, 0, 60, United-States, >50K 30, Private, 105908, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 232356, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 1672, 55, United-States, <=50K 23, Private, 210526, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 71, Private, 193530, 11th, 7, Never-married, Priv-house-serv, Not-in-family, White, Female, 0, 0, 75, United-States, <=50K 22, ?, 22966, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 6, United-States, <=50K 21, Private, 43535, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 62, ?, 72486, HS-grad, 9, Married-civ-spouse, ?, Husband, Asian-Pac-Islander, Male, 0, 0, 24, China, <=50K 22, ?, 229997, Some-college, 10, Married-spouse-absent, ?, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 49, Private, 183013, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 113364, Assoc-acdm, 12, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 20, United-States, <=50K 27, Private, 197380, Assoc-acdm, 12, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 298635, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Hong, >50K 26, Private, 213385, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 30, ?, 108464, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 31007, 10th, 6, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 26, Private, 35917, Some-college, 10, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 45, Private, 99385, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, Canada, <=50K 50, Private, 48358, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 7688, 0, 40, United-States, >50K 31, Private, 241885, HS-grad, 9, Never-married, Farming-fishing, Unmarried, White, Male, 0, 0, 45, United-States, <=50K 51, Private, 24344, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 56, Private, 149686, 9th, 5, Widowed, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 24, State-gov, 154432, Bachelors, 13, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 29, Private, 331875, 12th, 8, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, Dominican-Republic, <=50K 26, Private, 259585, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 24, United-States, <=50K 51, Private, 104748, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 32, Local-gov, 144949, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, State-gov, 199512, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Private, 302438, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, ?, 129155, 11th, 7, Widowed, ?, Other-relative, Black, Female, 0, 0, 40, United-States, <=50K 49, Federal-gov, 115784, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 96509, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, >50K 62, Private, 226733, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 43, Self-emp-inc, 244945, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 76, Private, 243768, 5th-6th, 3, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 40, ?, 351161, Masters, 14, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 60, United-States, >50K 35, Private, 186934, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 27, Private, 89813, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 40, United-States, <=50K 54, Self-emp-inc, 129432, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 40, United-States, >50K 55, Self-emp-not-inc, 184702, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 275291, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 12, United-States, <=50K 20, Private, 258298, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, United-States, <=50K 39, Private, 139743, HS-grad, 9, Separated, Adm-clerical, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 26, Private, 102476, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 10520, 0, 64, United-States, >50K 20, Private, 103840, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 42, United-States, <=50K 28, Private, 274579, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 56, Federal-gov, 156842, Some-college, 10, Separated, Other-service, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 39, Private, 101020, 12th, 8, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Federal-gov, 68729, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, >50K 55, Private, 141326, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 54, Self-emp-not-inc, 168723, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 347166, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 13550, 0, 45, United-States, >50K 34, Local-gov, 213722, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 57, United-States, >50K 42, Private, 196797, HS-grad, 9, Never-married, Transport-moving, Unmarried, Black, Female, 0, 0, 38, United-States, <=50K 50, Self-emp-inc, 207246, Some-college, 10, Separated, Exec-managerial, Unmarried, White, Female, 0, 0, 75, United-States, <=50K 34, Federal-gov, 199934, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, >50K 23, Private, 272185, Assoc-voc, 11, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 33, United-States, <=50K 27, ?, 190650, Bachelors, 13, Never-married, ?, Unmarried, Asian-Pac-Islander, Male, 0, 0, 25, Philippines, <=50K 81, ?, 147097, Bachelors, 13, Widowed, ?, Not-in-family, White, Male, 0, 0, 5, United-States, <=50K 47, Private, 266281, 11th, 7, Never-married, Machine-op-inspct, Unmarried, Black, Female, 6849, 0, 40, United-States, <=50K 57, Private, 96779, 5th-6th, 3, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 65, ?, 117162, Assoc-voc, 11, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 56, United-States, >50K 33, Private, 188352, Masters, 14, Never-married, Prof-specialty, Not-in-family, Black, Male, 0, 0, 50, United-States, <=50K 37, Private, 359131, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 48, United-States, <=50K 53, Private, 198824, Bachelors, 13, Never-married, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 27, State-gov, 68393, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 115613, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 42, Private, 45363, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 39, Private, 121590, Some-college, 10, Never-married, Prof-specialty, Not-in-family, Black, Male, 4787, 0, 40, United-States, >50K 58, Local-gov, 292379, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 482732, HS-grad, 9, Never-married, Adm-clerical, Other-relative, White, Male, 0, 0, 24, United-States, <=50K 19, Private, 198663, HS-grad, 9, Never-married, Machine-op-inspct, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 230329, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 51, Private, 29887, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 44, United-States, <=50K 52, Private, 194259, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, Germany, <=50K 53, Private, 126368, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 50, Private, 108446, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 220696, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 32008, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 72, United-States, <=50K 30, Private, 191777, Some-college, 10, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, ?, <=50K 50, Private, 185846, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, >50K 76, Private, 127016, 7th-8th, 4, Widowed, Priv-house-serv, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 46, Self-emp-not-inc, 102308, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 2415, 40, United-States, >50K 24, Private, 157894, Some-college, 10, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 26, Private, 345405, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 2885, 0, 40, United-States, <=50K 56, Self-emp-not-inc, 94156, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 50, United-States, >50K 50, Private, 145409, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 40, United-States, >50K 22, Private, 190968, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 2407, 0, 40, United-States, <=50K 23, Local-gov, 212803, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 51, Private, 168660, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 58, Private, 234481, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 131461, 9th, 5, Married-civ-spouse, Other-service, Wife, Black, Female, 0, 0, 24, Haiti, <=50K 45, Private, 408773, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 55, Self-emp-not-inc, 126117, HS-grad, 9, Widowed, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 155489, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 42, Private, 296749, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 44, State-gov, 185832, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 46, United-States, >50K 60, Private, 43235, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 27, Private, 213152, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Local-gov, 334267, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 61, ?, 253101, Bachelors, 13, Divorced, ?, Not-in-family, White, Female, 0, 0, 24, United-States, <=50K 43, Private, 64631, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 44, Local-gov, 193882, Assoc-voc, 11, Never-married, Tech-support, Not-in-family, White, Male, 0, 1340, 40, United-States, <=50K 63, Private, 71800, 7th-8th, 4, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 41, United-States, <=50K 46, Local-gov, 170092, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 43, United-States, <=50K 47, Private, 198223, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 359796, Some-college, 10, Divorced, Sales, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 43, Private, 110556, HS-grad, 9, Separated, Exec-managerial, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 46, Private, 196858, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, >50K 48, ?, 112860, 10th, 6, Married-civ-spouse, ?, Wife, Black, Female, 0, 0, 35, United-States, <=50K 61, Self-emp-not-inc, 224784, Assoc-acdm, 12, Married-spouse-absent, Exec-managerial, Not-in-family, White, Female, 0, 0, 90, United-States, <=50K 53, Federal-gov, 271544, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 1977, 40, United-States, >50K 79, ?, 142171, 7th-8th, 4, Married-civ-spouse, ?, Husband, White, Male, 1409, 0, 35, United-States, <=50K 44, Private, 221172, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 54, Private, 256916, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 22, Private, 157332, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 47, Federal-gov, 192894, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 50, United-States, >50K 18, Private, 240183, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 25, Private, 204338, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Mexico, <=50K 24, Private, 122166, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, Iran, <=50K 37, Local-gov, 397877, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 51, Private, 115066, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 2547, 40, United-States, >50K 35, Self-emp-not-inc, 170174, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 60, United-States, >50K 59, Private, 171015, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 34, United-States, <=50K 46, Private, 91262, Some-college, 10, Married-spouse-absent, Craft-repair, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 45, Local-gov, 127678, Assoc-voc, 11, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 60, United-States, >50K 19, Private, 263338, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 15, United-States, <=50K 22, Private, 129508, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 28, United-States, <=50K 41, Private, 192107, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Self-emp-not-inc, 93930, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Federal-gov, 207537, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 22, Private, 138542, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 35, United-States, <=50K 29, Self-emp-not-inc, 116207, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 65, United-States, >50K 22, Private, 198244, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 39, United-States, <=50K 34, Private, 90614, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 2042, 10, United-States, <=50K 23, Private, 211160, 12th, 8, Married-civ-spouse, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 194630, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 3781, 0, 50, United-States, <=50K 25, Private, 161478, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 59, Private, 144071, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 44, Private, 167005, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 4386, 0, 55, United-States, <=50K 55, Private, 342121, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 77, Self-emp-not-inc, 71676, Some-college, 10, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 1944, 1, United-States, <=50K 42, Private, 124692, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 47, Private, 147236, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Private, 145175, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 259323, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 154978, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Guatemala, <=50K 60, ?, 163946, 9th, 5, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 127768, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 98588, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 192894, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Private, 194848, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 34446, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 23, Local-gov, 177265, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 45, United-States, <=50K 30, Private, 142977, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 45, Private, 241350, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 48, United-States, >50K 30, Private, 154882, Prof-school, 15, Widowed, Other-service, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 17, Private, 60562, 9th, 5, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 22, Private, 142566, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 176162, Bachelors, 13, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 186303, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 55, Canada, >50K 40, Private, 237671, Some-college, 10, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 40, United-States, >50K 18, ?, 184416, 10th, 6, Never-married, ?, Own-child, Black, Male, 0, 0, 30, United-States, <=50K 58, Private, 68624, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 30, Private, 229504, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 59, Private, 340591, 10th, 6, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 3942, 0, 40, United-States, <=50K 29, Private, 262208, Some-college, 10, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 30, Jamaica, <=50K 26, Private, 236008, Assoc-voc, 11, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 39, Local-gov, 214284, Bachelors, 13, Widowed, Prof-specialty, Unmarried, Asian-Pac-Islander, Female, 0, 0, 10, Japan, <=50K 33, Private, 169496, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 21, ?, 205940, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 195179, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 24, United-States, <=50K 25, Private, 469697, Some-college, 10, Married-civ-spouse, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 19, ?, 140242, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 20, United-States, <=50K 44, Private, 214415, Some-college, 10, Separated, Prof-specialty, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 35, Private, 452283, HS-grad, 9, Divorced, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 244172, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 231972, 11th, 7, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 37, Private, 412296, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, Mexico, >50K 32, Private, 30497, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Self-emp-not-inc, 189216, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 36, Private, 268292, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 41, United-States, <=50K 38, Private, 69306, Some-college, 10, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 57, State-gov, 111224, Bachelors, 13, Divorced, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 39, United-States, <=50K 22, State-gov, 309348, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 80, ?, 174995, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 8, Canada, <=50K 20, Private, 210781, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 35, United-States, <=50K 40, Private, 286750, 11th, 7, Separated, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 36, United-States, <=50K 36, Self-emp-not-inc, 321274, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 27, Private, 192936, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 52, Private, 72743, HS-grad, 9, Married-spouse-absent, Adm-clerical, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 43, Private, 187861, HS-grad, 9, Separated, Transport-moving, Unmarried, White, Female, 0, 0, 44, United-States, <=50K 35, Private, 179579, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 663394, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, Black, Male, 0, 0, 40, United-States, <=50K 27, Private, 302422, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 24, ?, 154373, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 25, United-States, <=50K 49, Local-gov, 37353, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Self-emp-not-inc, 109609, Some-college, 10, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 47, Private, 184402, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 32, United-States, <=50K 20, Private, 224640, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 405526, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 36385, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 2258, 50, United-States, <=50K 20, Private, 147884, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 164231, 11th, 7, Separated, Prof-specialty, Own-child, White, Male, 0, 0, 35, United-States, <=50K 25, Private, 383306, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 417668, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 36, United-States, <=50K 25, Private, 161007, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 63, State-gov, 99823, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 32, United-States, <=50K 25, Private, 37379, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 28, Private, 148645, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 180477, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 28, Private, 123147, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Female, 4865, 0, 40, United-States, <=50K 30, Private, 111415, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 41, Local-gov, 107327, Assoc-voc, 11, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 52, Local-gov, 146565, Assoc-acdm, 12, Divorced, Other-service, Not-in-family, White, Female, 4865, 0, 30, United-States, <=50K 36, Private, 267556, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 4064, 0, 40, United-States, <=50K 47, Private, 284871, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1887, 40, United-States, >50K 27, Private, 194690, 9th, 5, Never-married, Other-service, Own-child, White, Male, 0, 0, 50, Mexico, <=50K 32, Federal-gov, 145983, Some-college, 10, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 40, United-States, <=50K 52, Private, 163998, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 99999, 0, 45, United-States, >50K 50, Private, 128478, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 70, United-States, <=50K 21, Private, 250647, Some-college, 10, Never-married, Adm-clerical, Other-relative, White, Male, 0, 0, 30, Nicaragua, <=50K 60, Private, 226949, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 37, United-States, <=50K 47, Private, 157901, 11th, 7, Married-civ-spouse, Other-service, Husband, Amer-Indian-Eskimo, Male, 0, 0, 36, United-States, <=50K 54, Self-emp-not-inc, 33863, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, >50K 32, Local-gov, 40444, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 61, Private, 54373, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 52753, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 1504, 40, United-States, <=50K 29, Self-emp-not-inc, 104423, Some-college, 10, Married-civ-spouse, Exec-managerial, Other-relative, White, Male, 4386, 0, 45, United-States, >50K 36, Local-gov, 305714, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 70, United-States, <=50K 38, Local-gov, 167440, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 20, United-States, <=50K 59, Private, 291529, 10th, 6, Widowed, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 52, United-States, <=50K 43, Private, 243380, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 38619, 11th, 7, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 10, United-States, <=50K 42, Private, 230684, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 5013, 0, 40, United-States, <=50K 33, Private, 132601, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 47, Private, 193285, HS-grad, 9, Married-civ-spouse, Other-service, Wife, Black, Female, 5013, 0, 40, United-States, <=50K 51, Private, 279156, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 40, United-States, >50K 28, Private, 339372, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 101265, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 43, United-States, <=50K 23, Private, 117789, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 31, Private, 312667, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Self-emp-not-inc, 255503, 11th, 7, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 21, Private, 221955, 9th, 5, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 22, Private, 139190, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 50, United-States, <=50K 35, Private, 185556, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1887, 40, United-States, >50K 53, Federal-gov, 84278, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 48, United-States, >50K 40, Private, 114580, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 24, United-States, >50K 36, Private, 185405, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, >50K 33, Self-emp-not-inc, 199539, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 65, United-States, <=50K 23, Private, 346480, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 51, Local-gov, 349431, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 4386, 0, 40, United-States, >50K 31, Private, 219619, HS-grad, 9, Never-married, Sales, Other-relative, White, Male, 0, 0, 48, United-States, <=50K 28, Local-gov, 127491, HS-grad, 9, Separated, Adm-clerical, Not-in-family, White, Female, 5721, 0, 40, United-States, <=50K 26, Self-emp-not-inc, 253899, Bachelors, 13, Divorced, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 155232, Bachelors, 13, Divorced, Protective-serv, Not-in-family, Black, Male, 0, 0, 60, United-States, >50K 43, Private, 182437, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 19, Private, 530454, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 46, Private, 101430, 11th, 7, Divorced, Handlers-cleaners, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 49, Local-gov, 358668, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 31, Private, 90668, 10th, 6, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 126141, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Private, 238355, 5th-6th, 3, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, Mexico, <=50K 22, Private, 194031, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 25, Private, 117833, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 1876, 40, United-States, <=50K 46, Private, 249686, Prof-school, 15, Separated, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 44, Self-emp-not-inc, 219591, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 221757, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 80625, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 185407, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 34, Private, 163110, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 34, ?, 24504, HS-grad, 9, Never-married, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 159187, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 55, United-States, >50K 21, Private, 100462, Assoc-voc, 11, Never-married, Exec-managerial, Own-child, White, Female, 2174, 0, 60, United-States, <=50K 27, Private, 192936, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 145011, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 60, Self-emp-inc, 181196, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Self-emp-not-inc, 37778, Masters, 14, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 70, United-States, <=50K 27, Private, 60288, Masters, 14, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 57, Self-emp-not-inc, 84231, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 48, United-States, <=50K 24, Private, 52028, 1st-4th, 2, Married-civ-spouse, Other-service, Own-child, Asian-Pac-Islander, Female, 0, 0, 5, Vietnam, <=50K 63, Private, 318763, Some-college, 10, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 22, United-States, <=50K 29, Private, 168138, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 34, Private, 113530, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 321896, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 145791, Assoc-voc, 11, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 131425, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 145214, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 4650, 0, 20, United-States, <=50K 64, Local-gov, 142166, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 99, United-States, <=50K 20, Private, 494784, HS-grad, 9, Never-married, Sales, Other-relative, Black, Female, 0, 0, 35, United-States, <=50K 44, Self-emp-not-inc, 172479, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 15024, 0, 60, United-States, >50K 35, Private, 184655, 11th, 7, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 41, Local-gov, 26669, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 191479, Some-college, 10, Divorced, Exec-managerial, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 21, Private, 86625, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, ?, <=50K 64, State-gov, 111795, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 42, Private, 242564, 7th-8th, 4, Never-married, Handlers-cleaners, Not-in-family, Black, Male, 0, 2205, 40, United-States, <=50K 31, Private, 364657, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, Germany, >50K 42, Self-emp-not-inc, 436107, Assoc-acdm, 12, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 35, Private, 272476, Assoc-acdm, 12, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 35, United-States, >50K 36, Federal-gov, 47310, Some-college, 10, Divorced, Exec-managerial, Unmarried, Black, Female, 0, 0, 40, United-States, >50K 23, Private, 283796, 12th, 8, Never-married, Machine-op-inspct, Other-relative, White, Male, 0, 0, 30, Mexico, <=50K 20, Private, 161092, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 14, United-States, <=50K 26, Local-gov, 265230, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 56, Federal-gov, 61885, Bachelors, 13, Never-married, Transport-moving, Not-in-family, Black, Male, 0, 2001, 65, United-States, <=50K 40, Private, 150471, Assoc-acdm, 12, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 183041, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 24, United-States, <=50K 33, Private, 176673, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 45, Federal-gov, 235891, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, Columbia, <=50K 41, Private, 163287, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 43, United-States, >50K 29, Private, 164040, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Local-gov, 324561, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 45, United-States, >50K 48, Private, 99127, Assoc-acdm, 12, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 38, Private, 334999, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 29, Private, 543477, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 35, Private, 65876, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 59, Local-gov, 105866, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 30, United-States, <=50K 27, Private, 214858, HS-grad, 9, Married-civ-spouse, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 154076, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, >50K 70, Private, 280307, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 20, Cuba, <=50K 30, Private, 97723, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 45, United-States, <=50K 24, Private, 233499, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 76, Local-gov, 259612, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 15, United-States, <=50K 25, Private, 236977, HS-grad, 9, Separated, Craft-repair, Own-child, White, Male, 0, 0, 40, Mexico, <=50K 39, Private, 347814, Assoc-acdm, 12, Never-married, Other-service, Own-child, White, Female, 0, 0, 56, United-States, <=50K 36, Local-gov, 197495, Bachelors, 13, Divorced, Prof-specialty, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 23, Private, 227594, 12th, 8, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 60, Private, 165441, 7th-8th, 4, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 20, ?, 337488, Some-college, 10, Never-married, ?, Own-child, Black, Male, 0, 0, 30, United-States, <=50K 54, Private, 167552, 1st-4th, 2, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, Haiti, >50K 20, Private, 396722, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, Federal-gov, 146538, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 51973, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 20, United-States, <=50K 41, Private, 144778, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 169672, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 240137, 5th-6th, 3, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 55, Mexico, <=50K 54, State-gov, 103179, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 50, United-States, >50K 17, Private, 172050, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 16, United-States, <=50K 43, Private, 178976, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 176185, 12th, 8, Divorced, Craft-repair, Not-in-family, White, Male, 0, 2258, 42, United-States, <=50K 30, Private, 158200, Prof-school, 15, Never-married, Prof-specialty, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, ?, <=50K 38, Federal-gov, 172571, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 54, Self-emp-not-inc, 226735, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 45, United-States, <=50K 39, Private, 148015, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 52, United-States, <=50K 32, Private, 199529, Some-college, 10, Separated, Tech-support, Not-in-family, Amer-Indian-Eskimo, Male, 0, 1980, 40, United-States, <=50K 61, Local-gov, 35001, 7th-8th, 4, Married-civ-spouse, Adm-clerical, Husband, White, Male, 2885, 0, 40, United-States, <=50K 24, ?, 67586, Assoc-voc, 11, Married-civ-spouse, ?, Wife, Black, Female, 0, 0, 35, United-States, <=50K 22, Private, 88126, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 226296, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, >50K 18, Private, 452452, 10th, 6, Never-married, Priv-house-serv, Own-child, Black, Female, 0, 0, 20, United-States, <=50K 20, Private, 378546, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 25, United-States, <=50K 53, Federal-gov, 186087, HS-grad, 9, Divorced, Tech-support, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 27856, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 68, Self-emp-not-inc, 234859, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 30, United-States, <=50K 28, Private, 71733, Some-college, 10, Separated, Other-service, Unmarried, White, Female, 0, 0, 15, United-States, <=50K 28, Private, 207473, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, El-Salvador, <=50K 54, Private, 179291, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 56, Haiti, >50K 21, ?, 253190, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 48, United-States, <=50K 52, Private, 92968, Bachelors, 13, Separated, Exec-managerial, Unmarried, White, Female, 0, 0, 40, ?, <=50K 25, Private, 209286, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 122889, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 50, India, >50K 33, Private, 112358, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 32, United-States, <=50K 49, Private, 176341, Bachelors, 13, Never-married, Tech-support, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, India, <=50K 58, Private, 247276, 7th-8th, 4, Widowed, Other-service, Not-in-family, Other, Female, 0, 0, 30, United-States, <=50K 45, Private, 276087, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 24, United-States, >50K 67, Private, 257557, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, Black, Male, 10566, 0, 40, United-States, <=50K 42, Local-gov, 177937, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, ?, <=50K 69, Self-emp-inc, 106395, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, >50K 61, Private, 167138, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 213887, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 185647, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 19, Private, 143360, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 34, United-States, <=50K 31, Self-emp-not-inc, 176862, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Federal-gov, 97614, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 76, ?, 224680, Prof-school, 15, Married-civ-spouse, ?, Husband, White, Male, 0, 1258, 20, United-States, <=50K 53, Private, 196763, Assoc-acdm, 12, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 46, Private, 306183, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 37, United-States, <=50K 43, Self-emp-not-inc, 343061, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 4508, 0, 40, Cuba, <=50K 48, ?, 193047, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 348521, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 2415, 99, United-States, >50K 59, Private, 195835, 7th-8th, 4, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 106273, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 38, United-States, <=50K 40, Private, 222756, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 63, Self-emp-inc, 110610, 10th, 6, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 44, ?, 191982, Some-college, 10, Divorced, ?, Unmarried, White, Female, 0, 0, 10, Poland, <=50K 46, Private, 247286, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 219042, 10th, 6, Never-married, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 224566, Assoc-acdm, 12, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 1669, 45, United-States, <=50K 57, Private, 204751, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 58, Private, 113398, HS-grad, 9, Never-married, Other-service, Other-relative, White, Male, 0, 0, 25, United-States, <=50K 25, ?, 170428, Bachelors, 13, Never-married, ?, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 28, Taiwan, <=50K 59, Private, 258579, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 3103, 0, 35, United-States, >50K 36, Private, 162424, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 29, Private, 263005, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, Germany, <=50K 49, Self-emp-inc, 26502, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Male, 6497, 0, 45, United-States, <=50K 42, Private, 369131, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, >50K 43, Local-gov, 114859, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 17, United-States, <=50K 46, Private, 405309, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Local-gov, 323627, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 12, United-States, <=50K 40, Private, 106698, Assoc-acdm, 12, Divorced, Transport-moving, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 51506, 12th, 8, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 117251, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 26, Private, 106705, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 28, United-States, <=50K 30, Private, 217296, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 35, United-States, <=50K 58, Private, 34788, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 1887, 40, United-States, >50K 43, Private, 143368, HS-grad, 9, Divorced, Farming-fishing, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 53, Local-gov, 86600, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 40, United-States, <=50K 74, State-gov, 117017, Some-college, 10, Separated, Sales, Not-in-family, White, Male, 0, 0, 16, United-States, <=50K 64, ?, 104756, Some-college, 10, Widowed, ?, Unmarried, White, Female, 0, 0, 8, United-States, <=50K 45, Private, 55720, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 32, State-gov, 481096, 5th-6th, 3, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 10, United-States, <=50K 23, ?, 281668, 10th, 6, Never-married, ?, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 38, Private, 186145, Some-college, 10, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, >50K 42, Self-emp-not-inc, 96524, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 24, Local-gov, 187397, Some-college, 10, Never-married, Protective-serv, Unmarried, Other, Male, 1151, 0, 40, United-States, <=50K 63, Private, 181153, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 35, United-States, <=50K 25, Local-gov, 375170, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 35, United-States, <=50K 37, Private, 360743, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 28, Self-emp-not-inc, 420054, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Italy, <=50K 31, Private, 137681, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 28419, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 50, United-States, >50K 44, Private, 101214, Bachelors, 13, Divorced, Sales, Unmarried, White, Male, 0, 0, 44, United-States, >50K 42, Local-gov, 213019, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 45, Private, 207540, Doctorate, 16, Separated, Exec-managerial, Unmarried, White, Male, 0, 0, 40, United-States, >50K 52, Private, 145333, Bachelors, 13, Divorced, Sales, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 40, Private, 107306, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 195327, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 196126, Bachelors, 13, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 40, ?, <=50K 17, Private, 175465, 10th, 6, Never-married, Other-service, Own-child, White, Female, 0, 0, 14, United-States, <=50K 27, Private, 197905, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 71, Self-emp-inc, 118119, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 20051, 0, 50, United-States, >50K 35, Private, 172571, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 17, Private, 25051, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 16, United-States, <=50K 26, Private, 210714, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 52, United-States, >50K 22, Private, 183083, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 51, Private, 99185, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 33, Private, 283921, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Local-gov, 396467, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 50, United-States, >50K 50, Private, 158680, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 26, Private, 202091, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 285127, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 53, Private, 218630, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Self-emp-inc, 99309, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 19, Private, 165505, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 22, Private, 122272, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 35, United-States, <=50K 58, Private, 147707, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 60, United-States, >50K 47, Federal-gov, 44257, Bachelors, 13, Married-spouse-absent, Exec-managerial, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 51, Self-emp-inc, 194995, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 42, State-gov, 345969, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 48, United-States, >50K 28, Private, 31842, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 143582, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, Asian-Pac-Islander, Female, 0, 0, 35, Vietnam, <=50K 50, Private, 161438, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 22, Private, 317019, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 47, Self-emp-not-inc, 158451, Some-college, 10, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 60, Private, 225883, Some-college, 10, Widowed, Sales, Unmarried, White, Female, 0, 0, 27, United-States, <=50K 46, Self-emp-not-inc, 176319, HS-grad, 9, Married-civ-spouse, Sales, Own-child, White, Female, 7298, 0, 40, United-States, >50K 58, Self-emp-inc, 258883, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 62, Private, 26966, Some-college, 10, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 202812, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, ?, >50K 59, Private, 35411, HS-grad, 9, Widowed, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 190885, HS-grad, 9, Separated, Other-service, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 31, Private, 182162, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 37, United-States, <=50K 18, Private, 352640, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 64, Self-emp-not-inc, 213945, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 51, Self-emp-not-inc, 135102, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 65, United-States, <=50K 47, Self-emp-not-inc, 102583, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 68, Private, 225612, Bachelors, 13, Widowed, Sales, Not-in-family, White, Male, 0, 0, 35, United-States, >50K 32, Private, 241802, HS-grad, 9, Married-civ-spouse, Other-service, Wife, Other, Female, 0, 0, 40, United-States, <=50K 39, Private, 347434, 9th, 5, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 43, Mexico, <=50K 37, Private, 305259, Assoc-acdm, 12, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 29, Private, 140830, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 291568, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, Other, Male, 0, 0, 40, United-States, <=50K 46, Private, 203067, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Self-emp-not-inc, 155106, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 19, ?, 252752, HS-grad, 9, Never-married, ?, Own-child, Black, Male, 0, 0, 35, United-States, <=50K 65, ?, 404601, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 2414, 0, 30, United-States, <=50K 52, Local-gov, 100226, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 40, Private, 63503, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 61, Private, 95929, 9th, 5, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 187618, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 61, Self-emp-not-inc, 92178, 11th, 7, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 220362, Assoc-voc, 11, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 84, United-States, >50K 32, Local-gov, 209900, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 65, United-States, >50K 32, Private, 272376, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 32, Self-emp-not-inc, 173854, Bachelors, 13, Divorced, Prof-specialty, Other-relative, White, Male, 0, 0, 35, United-States, >50K 37, Private, 278924, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 324568, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 51, Self-emp-inc, 124963, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Private, 211299, Assoc-voc, 11, Never-married, Sales, Not-in-family, Black, Male, 0, 0, 45, United-States, <=50K 48, Private, 192791, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 69, Private, 182862, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 15831, 0, 40, United-States, >50K 28, Private, 46868, Masters, 14, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 55, Local-gov, 31365, Bachelors, 13, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 45, Private, 148171, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 15024, 0, 40, United-States, >50K 18, Private, 142647, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 60, Private, 116230, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 108907, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, ?, <=50K 19, Private, 495982, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 10, United-States, <=50K 18, Private, 334026, 11th, 7, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 25, United-States, <=50K 33, Private, 268571, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 213813, Some-college, 10, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 241667, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 37, Private, 160920, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 50, Private, 107265, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 19, ?, 41609, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 10, United-States, <=50K 28, Private, 129460, 10th, 6, Widowed, Adm-clerical, Unmarried, White, Female, 0, 2238, 35, United-States, <=50K 43, ?, 109912, Bachelors, 13, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 7, United-States, >50K 23, Private, 167424, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 35, United-States, <=50K 47, Private, 270079, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 325923, Some-college, 10, Never-married, Tech-support, Own-child, White, Male, 0, 0, 35, United-States, <=50K 19, Private, 194905, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 12, United-States, <=50K 47, Local-gov, 183486, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 50, United-States, >50K 36, Federal-gov, 153066, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 62, Self-emp-inc, 56248, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 2415, 60, United-States, >50K 65, Private, 105252, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Self-emp-not-inc, 168195, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 45, United-States, >50K 35, Private, 167735, 11th, 7, Never-married, Craft-repair, Own-child, White, Male, 6849, 0, 40, United-States, <=50K 50, Private, 146310, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 256504, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 6, United-States, <=50K 17, Private, 121425, 11th, 7, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 16, United-States, <=50K 33, Private, 146440, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1740, 40, United-States, <=50K 57, ?, 155259, Some-college, 10, Divorced, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 53, Self-emp-not-inc, 98829, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 47, Self-emp-inc, 239321, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 62, Self-emp-inc, 134768, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 35, United-States, <=50K 35, Private, 556902, HS-grad, 9, Divorced, Other-service, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 27, Private, 47907, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 43, United-States, <=50K 23, Private, 114357, HS-grad, 9, Never-married, Tech-support, Own-child, White, Male, 0, 0, 50, United-States, <=50K 27, Private, 189462, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 1504, 45, United-States, <=50K 39, Private, 90646, Assoc-voc, 11, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 232914, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 0, 38, United-States, <=50K 24, Private, 192201, Some-college, 10, Never-married, Exec-managerial, Not-in-family, Black, Female, 0, 0, 20, United-States, <=50K 23, Private, 27776, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 137476, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 35, United-States, >50K 30, Private, 100734, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 38, United-States, <=50K 34, Private, 111746, HS-grad, 9, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 45, Portugal, <=50K 32, Private, 184833, 10th, 6, Separated, Craft-repair, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 414721, 11th, 7, Never-married, Other-service, Own-child, Black, Male, 0, 1602, 23, United-States, <=50K 20, Private, 151780, Assoc-voc, 11, Never-married, Sales, Not-in-family, Black, Female, 0, 0, 35, United-States, <=50K 38, State-gov, 203628, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 18, Private, 137363, 12th, 8, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 41, Private, 172307, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 273403, Assoc-voc, 11, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 36, State-gov, 37931, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 48, United-States, >50K 61, Private, 97030, Some-college, 10, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 30, Private, 54608, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, <=50K 26, Private, 108542, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 253814, Bachelors, 13, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 40, United-States, >50K 45, Private, 421412, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, >50K 47, Private, 207140, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 19, Private, 138153, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 10, United-States, <=50K 29, Private, 46987, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 51, Self-emp-inc, 183173, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 70, United-States, >50K 34, Local-gov, 229531, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 42, Self-emp-not-inc, 320744, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 3908, 0, 45, United-States, <=50K 26, Private, 257405, 5th-6th, 3, Never-married, Farming-fishing, Other-relative, Black, Male, 0, 0, 40, Mexico, <=50K 20, State-gov, 432052, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 15, United-States, <=50K 43, Private, 397280, Assoc-acdm, 12, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 20, Private, 38001, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 27, Private, 101618, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 46, Federal-gov, 332727, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 115215, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 178449, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 49, United-States, <=50K 42, Private, 185267, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 32, United-States, <=50K 23, Private, 410439, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 25, United-States, <=50K 29, Private, 85572, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 42, United-States, >50K 27, Private, 83517, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 60, United-States, <=50K 43, Self-emp-not-inc, 194726, HS-grad, 9, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 35, United-States, <=50K 23, Private, 322674, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 40, Local-gov, 34540, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 44, United-States, <=50K 35, Local-gov, 211073, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 61, United-States, >50K 30, Private, 194901, HS-grad, 9, Never-married, Sales, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 59, Private, 117059, 11th, 7, Married-civ-spouse, Transport-moving, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 65, Self-emp-not-inc, 78875, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 2290, 0, 40, United-States, <=50K 28, Private, 51461, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 79, Private, 266119, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Local-gov, 92374, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, Black, Female, 0, 0, 35, United-States, >50K 54, Private, 175262, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 208249, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 62, United-States, <=50K 30, Private, 196385, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 35, United-States, >50K 22, ?, 110622, Bachelors, 13, Never-married, ?, Own-child, Asian-Pac-Islander, Female, 0, 0, 15, Taiwan, <=50K 34, Private, 146980, HS-grad, 9, Married-spouse-absent, Other-service, Unmarried, White, Female, 0, 0, 65, United-States, <=50K 18, Private, 112974, 11th, 7, Never-married, Prof-specialty, Other-relative, White, Male, 0, 0, 3, United-States, <=50K 40, Self-emp-not-inc, 175943, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 1977, 15, United-States, >50K 28, Private, 163265, 9th, 5, Married-civ-spouse, Sales, Husband, White, Male, 4508, 0, 40, United-States, <=50K 18, Private, 210932, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 145290, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 198992, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 35, United-States, <=50K 77, ?, 174887, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 6, United-States, <=50K 41, Federal-gov, 36651, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1848, 40, United-States, >50K 48, Private, 190072, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 29, Private, 49087, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 41, Private, 126622, 11th, 7, Divorced, Handlers-cleaners, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 174189, 9th, 5, Separated, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 118605, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, <=50K 49, Self-emp-not-inc, 377622, Assoc-acdm, 12, Divorced, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 49, Private, 157272, HS-grad, 9, Separated, Sales, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 30, Private, 78530, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 190391, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 62, State-gov, 162678, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 103980, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 52, United-States, <=50K 20, Private, 293726, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 98350, Preschool, 1, Married-spouse-absent, Other-service, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, China, <=50K 30, Private, 207668, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 60, Hungary, <=50K 29, Federal-gov, 41013, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 50, Private, 188186, Masters, 14, Divorced, Sales, Not-in-family, White, Female, 0, 1590, 45, United-States, <=50K 44, Federal-gov, 320071, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Private, 306908, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 62, Private, 167652, Assoc-voc, 11, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 57, Private, 173580, Some-college, 10, Widowed, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 273612, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 26, Private, 195555, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 60, Private, 186446, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 418405, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 62, Local-gov, 41793, Masters, 14, Separated, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, ?, <=50K 26, Private, 183965, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 354784, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 20, United-States, <=50K 44, Private, 198096, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 40, United-States, >50K 32, Private, 732102, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 66, Self-emp-not-inc, 97847, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 24, Private, 196678, Preschool, 1, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 30, United-States, <=50K 19, Private, 320014, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 25, United-States, <=50K 54, Self-emp-inc, 298215, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 37, Private, 295127, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 368140, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 37, Self-emp-not-inc, 187411, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, ?, <=50K 22, ?, 121070, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 35, United-States, <=50K 34, Private, 212163, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 25, United-States, <=50K 35, Self-emp-not-inc, 108198, HS-grad, 9, Divorced, Craft-repair, Own-child, Amer-Indian-Eskimo, Male, 0, 0, 15, United-States, <=50K 42, Federal-gov, 294431, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Federal-gov, 202560, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 29, Self-emp-inc, 266070, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 80, United-States, <=50K 34, Private, 346122, HS-grad, 9, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, Self-emp-inc, 308686, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 70, United-States, >50K 62, Self-emp-inc, 236096, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 35, Private, 187711, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 238959, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 93557, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 329980, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 125010, Assoc-voc, 11, Never-married, Priv-house-serv, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 60, Self-emp-inc, 90915, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 289731, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 74, ?, 33114, 10th, 6, Married-civ-spouse, ?, Husband, Amer-Indian-Eskimo, Male, 1797, 0, 30, United-States, <=50K 63, Private, 206052, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 191385, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, ?, 268804, HS-grad, 9, Married-civ-spouse, ?, Husband, Black, Male, 0, 0, 30, United-States, <=50K 40, Self-emp-inc, 191429, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 40, United-States, >50K 35, Self-emp-not-inc, 199753, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 60, United-States, <=50K 50, Local-gov, 92486, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 171088, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 10, United-States, <=50K 33, Private, 112820, Assoc-voc, 11, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 59, Self-emp-not-inc, 32855, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 70, United-States, <=50K 17, Private, 142964, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 47, Private, 89146, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, >50K 51, ?, 147015, Some-college, 10, Divorced, ?, Not-in-family, Black, Male, 0, 0, 50, United-States, <=50K 26, Private, 291968, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Local-gov, 29235, Some-college, 10, Married-civ-spouse, Protective-serv, Wife, White, Female, 0, 0, 40, France, >50K 55, Private, 238216, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, State-gov, 323726, Some-college, 10, Never-married, Tech-support, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 54, Private, 141663, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 19, ?, 218471, HS-grad, 9, Never-married, ?, Own-child, White, Female, 0, 1602, 30, United-States, <=50K 32, Private, 118551, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, >50K 52, Local-gov, 35092, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 139703, HS-grad, 9, Married-spouse-absent, Sales, Unmarried, Black, Female, 0, 0, 28, Jamaica, <=50K 39, Federal-gov, 206190, HS-grad, 9, Never-married, Exec-managerial, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 59, Self-emp-not-inc, 178353, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 55, Federal-gov, 169133, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 54, Self-emp-not-inc, 103179, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, >50K 31, Private, 354464, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, ?, 124651, 11th, 7, Never-married, ?, Own-child, Black, Male, 0, 0, 25, United-States, <=50K 30, Private, 60426, HS-grad, 9, Married-civ-spouse, Adm-clerical, Own-child, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 47, Federal-gov, 98726, Bachelors, 13, Married-spouse-absent, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 133861, Assoc-acdm, 12, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Self-emp-not-inc, 180303, Bachelors, 13, Divorced, Craft-repair, Unmarried, Asian-Pac-Islander, Male, 0, 0, 47, Iran, <=50K 33, Private, 221324, Assoc-voc, 11, Never-married, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 31, Private, 325658, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 210562, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 152249, HS-grad, 9, Married-spouse-absent, Other-service, Not-in-family, White, Male, 0, 0, 35, Mexico, <=50K 29, Private, 178649, HS-grad, 9, Married-spouse-absent, Other-service, Not-in-family, White, Female, 0, 0, 20, France, <=50K 41, State-gov, 48997, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 39, Private, 243409, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 34, Private, 162442, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 20, United-States, >50K 23, Private, 203078, Bachelors, 13, Never-married, Adm-clerical, Own-child, Black, Male, 0, 0, 24, United-States, <=50K 53, Self-emp-inc, 155983, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 65, United-States, >50K 45, Self-emp-not-inc, 182677, HS-grad, 9, Married-spouse-absent, Craft-repair, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, Thailand, <=50K 34, ?, 170276, Bachelors, 13, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 10, United-States, >50K 47, Private, 105381, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 24, ?, 256240, 7th-8th, 4, Married-civ-spouse, ?, Own-child, White, Male, 0, 0, 60, United-States, <=50K 42, Private, 210275, Masters, 14, Divorced, Tech-support, Unmarried, Black, Female, 4687, 0, 35, United-States, >50K 53, Private, 150980, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 3137, 0, 40, United-States, <=50K 38, Self-emp-inc, 141584, HS-grad, 9, Divorced, Sales, Unmarried, White, Male, 0, 0, 55, United-States, <=50K 26, Private, 113571, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 18, Private, 154089, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, United-States, <=50K 43, Private, 50197, 10th, 6, Separated, Other-service, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 26, Private, 132572, Bachelors, 13, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 32, United-States, <=50K 47, Private, 238185, Bachelors, 13, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 112754, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 65, United-States, >50K 21, ?, 357029, Some-college, 10, Married-civ-spouse, ?, Wife, Black, Female, 2105, 0, 20, United-States, <=50K 32, State-gov, 213389, Some-college, 10, Divorced, Protective-serv, Unmarried, White, Female, 0, 1726, 38, United-States, <=50K 48, Self-emp-inc, 287647, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 55, United-States, >50K 39, Private, 150061, Masters, 14, Divorced, Exec-managerial, Unmarried, Black, Female, 15020, 0, 60, United-States, >50K 58, Self-emp-inc, 143266, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Self-emp-not-inc, 68006, 7th-8th, 4, Never-married, Other-service, Other-relative, White, Female, 0, 0, 60, United-States, <=50K 40, Private, 287079, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 33, Private, 223212, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 74, Self-emp-not-inc, 173929, Doctorate, 16, Married-spouse-absent, Prof-specialty, Not-in-family, White, Male, 0, 0, 25, United-States, >50K 49, Self-emp-not-inc, 182211, HS-grad, 9, Widowed, Farming-fishing, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 56, Self-emp-not-inc, 62539, 11th, 7, Widowed, Other-service, Unmarried, White, Female, 0, 0, 65, Greece, >50K 29, Private, 157612, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 14344, 0, 40, United-States, >50K 25, Private, 305472, Assoc-acdm, 12, Never-married, Machine-op-inspct, Own-child, Black, Male, 0, 0, 48, United-States, <=50K 57, Private, 548256, 12th, 8, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, <=50K 29, Private, 40295, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 112403, HS-grad, 9, Never-married, Craft-repair, Unmarried, White, Male, 2354, 0, 40, United-States, <=50K 59, Private, 31137, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Private, 116138, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 27828, 0, 60, United-States, >50K 28, ?, 127833, HS-grad, 9, Never-married, ?, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 19, Private, 201743, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 40, Private, 240027, Some-college, 10, Never-married, Sales, Unmarried, Black, Female, 0, 0, 45, United-States, <=50K 28, Private, 129882, Some-college, 10, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 48, ?, 355890, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 55, United-States, >50K 20, Private, 107658, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 10, Canada, <=50K 58, Private, 136841, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 99999, 0, 35, United-States, >50K 19, Private, 146679, Some-college, 10, Never-married, Exec-managerial, Own-child, Black, Male, 0, 0, 30, United-States, <=50K 75, ?, 35724, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 8, United-States, <=50K 24, Federal-gov, 42251, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 31, Private, 113838, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, <=50K 28, Self-emp-not-inc, 282398, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 41, Private, 33331, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 23, Federal-gov, 41031, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 46, Private, 155489, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 43, United-States, >50K 33, Private, 53042, 12th, 8, Never-married, Craft-repair, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 34, Private, 174789, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 50, United-States, <=50K 47, Local-gov, 203067, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 81, Private, 177408, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 2377, 26, United-States, >50K 45, Private, 216626, HS-grad, 9, Widowed, Machine-op-inspct, Unmarried, Other, Male, 0, 0, 40, Columbia, <=50K 35, Private, 93034, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, Cambodia, <=50K 59, Self-emp-not-inc, 188003, Bachelors, 13, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 46, Local-gov, 65535, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 48, United-States, >50K 39, Private, 366757, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 23, Private, 414545, Some-college, 10, Never-married, Machine-op-inspct, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 25, Private, 295919, Assoc-acdm, 12, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 34378, 1st-4th, 2, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 49, Self-emp-inc, 58359, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 25, Private, 476334, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 48, United-States, <=50K 32, Private, 255424, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 34, Local-gov, 175856, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 124692, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Private, 118551, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 78, ?, 292019, 7th-8th, 4, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 20, United-States, <=50K 31, Private, 288566, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 43, United-States, >50K 61, Private, 137733, Some-college, 10, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 22, Private, 39432, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 138537, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Laos, <=50K 37, Private, 709445, HS-grad, 9, Separated, Craft-repair, Other-relative, Black, Male, 0, 0, 40, United-States, <=50K 35, Private, 194809, 11th, 7, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 52, Self-emp-inc, 89041, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 60, United-States, >50K 37, ?, 299090, HS-grad, 9, Divorced, ?, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 18, Private, 159561, 11th, 7, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 20, United-States, <=50K 37, Private, 236328, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, <=50K 46, Private, 269045, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 40, United-States, >50K 25, ?, 196627, 11th, 7, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 47, Federal-gov, 323798, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 55, Private, 463072, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 32, Private, 199655, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, Other, Female, 0, 1740, 40, ?, <=50K 25, Self-emp-inc, 98756, Some-college, 10, Divorced, Adm-clerical, Own-child, White, Female, 0, 0, 50, United-States, <=50K 50, State-gov, 161075, HS-grad, 9, Widowed, Tech-support, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 18, Private, 192485, 12th, 8, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 20, United-States, <=50K 25, Private, 201579, 9th, 5, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 23, Private, 117606, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 51, ?, 177487, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Self-emp-not-inc, 237731, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 2829, 0, 65, United-States, <=50K 37, Private, 60313, HS-grad, 9, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 270059, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 25236, 0, 25, United-States, >50K 27, Private, 169958, 5th-6th, 3, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, ?, <=50K 19, Private, 240686, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 25, United-States, <=50K 52, Local-gov, 124793, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Self-emp-not-inc, 113948, Assoc-voc, 11, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 45, United-States, <=50K 17, ?, 241021, 12th, 8, Never-married, ?, Own-child, Other, Female, 0, 0, 40, United-States, <=50K 21, Private, 147655, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 41, Self-emp-not-inc, 38876, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 55, Private, 117299, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 7688, 0, 40, United-States, >50K 20, ?, 114813, 10th, 6, Separated, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 136310, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Federal-gov, 153132, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 38, United-States, >50K 23, Private, 197552, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 35, United-States, <=50K 33, Private, 69748, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 175738, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, >50K 50, State-gov, 78649, Some-college, 10, Married-spouse-absent, Adm-clerical, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 37, Self-emp-inc, 188774, 11th, 7, Married-spouse-absent, Sales, Not-in-family, White, Male, 0, 0, 60, ?, <=50K 48, Private, 155659, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 7688, 0, 40, United-States, >50K 19, Federal-gov, 215891, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 10, United-States, <=50K 40, Private, 144928, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 33688, HS-grad, 9, Never-married, Transport-moving, Unmarried, White, Female, 0, 1669, 70, United-States, <=50K 65, Private, 262446, 11th, 7, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 20, United-States, <=50K 44, Federal-gov, 191295, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 48, United-States, <=50K 32, Private, 279173, Bachelors, 13, Divorced, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 41, Private, 153031, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 65, United-States, >50K 28, Private, 202239, 7th-8th, 4, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, <=50K 44, Federal-gov, 469454, Assoc-voc, 11, Married-civ-spouse, Protective-serv, Husband, White, Male, 7298, 0, 48, United-States, >50K 39, Local-gov, 164156, Assoc-acdm, 12, Divorced, Other-service, Unmarried, White, Female, 0, 0, 55, United-States, <=50K 59, Private, 196482, HS-grad, 9, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 176185, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, France, >50K 34, Private, 287315, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 117210, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 41610, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 160703, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 65, United-States, >50K 31, Private, 80511, Assoc-acdm, 12, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 44, United-States, <=50K 39, Private, 219155, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 43, United-States, <=50K 35, Private, 106347, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 37, Self-emp-not-inc, 68899, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 2129, 40, United-States, <=50K 44, Self-emp-not-inc, 163985, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 32, United-States, >50K 28, Private, 270887, Assoc-acdm, 12, Never-married, Sales, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 17, Private, 205726, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 15, United-States, <=50K 23, Private, 218899, Bachelors, 13, Never-married, Sales, Own-child, White, Female, 0, 0, 60, United-States, <=50K 35, Private, 186183, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 15024, 0, 80, United-States, >50K 19, Private, 248749, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 20, United-States, <=50K 30, Private, 197558, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 176514, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, ?, 116820, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 0, 50, United-States, <=50K 27, Private, 128730, Assoc-voc, 11, Never-married, Exec-managerial, Not-in-family, White, Male, 10520, 0, 65, Greece, >50K 37, Private, 215503, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 4386, 0, 45, United-States, >50K 44, Private, 226129, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 34, Private, 175856, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 3103, 0, 55, United-States, >50K 43, Private, 281138, HS-grad, 9, Separated, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 98061, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, Self-emp-not-inc, 260560, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 23, Private, 289909, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 51, Private, 59590, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 20, United-States, <=50K 24, Private, 236769, Assoc-acdm, 12, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 38, Self-emp-not-inc, 423616, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 24, United-States, >50K 24, Private, 291407, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 53, Self-emp-inc, 100029, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Private, 204494, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 56, United-States, >50K 24, Private, 201680, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 154308, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, United-States, >50K 31, Private, 150324, 11th, 7, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 38, Local-gov, 331609, Some-college, 10, Widowed, Transport-moving, Not-in-family, Black, Female, 0, 0, 47, United-States, <=50K 28, Private, 100829, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 50, United-States, >50K 38, Private, 203169, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 25, Private, 122075, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 29, Private, 178778, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 276345, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 48, Private, 233511, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 24, Private, 289448, Assoc-voc, 11, Never-married, Adm-clerical, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 31, Private, 173350, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 36, Private, 130589, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 62, Private, 94318, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 25, Private, 297531, Bachelors, 13, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 55, Private, 129762, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 182614, Some-college, 10, Never-married, Sales, Other-relative, White, Female, 0, 0, 40, Poland, <=50K 60, Private, 120067, 9th, 5, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 45, United-States, <=50K 41, Private, 182370, Assoc-acdm, 12, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 43, State-gov, 60949, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 190511, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 47, Private, 188195, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 89534, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Self-emp-inc, 125831, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 1887, 55, United-States, >50K 23, Private, 183358, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Puerto-Rico, <=50K 38, ?, 75024, 7th-8th, 4, Divorced, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 251120, Assoc-acdm, 12, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, England, <=50K 35, Private, 108946, HS-grad, 9, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 93223, Some-college, 10, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 61, Private, 147393, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 20, United-States, <=50K 71, ?, 45801, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 70, United-States, <=50K 35, State-gov, 225385, HS-grad, 9, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 35, Federal-gov, 23892, HS-grad, 9, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 179668, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, Scotland, <=50K 27, Self-emp-not-inc, 404998, Assoc-voc, 11, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 68882, 1st-4th, 2, Widowed, Other-service, Unmarried, White, Female, 0, 0, 35, Portugal, <=50K 55, Self-emp-not-inc, 194065, Assoc-acdm, 12, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 357540, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 2002, 55, United-States, <=50K 33, Private, 185336, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 0, 40, United-States, <=50K 25, State-gov, 152503, Some-college, 10, Never-married, Tech-support, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 52, Private, 167794, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 38, United-States, >50K 46, Private, 96552, Some-college, 10, Divorced, Machine-op-inspct, Own-child, White, Female, 0, 0, 17, United-States, <=50K 34, Private, 169527, Some-college, 10, Married-civ-spouse, Sales, Wife, White, Female, 4386, 0, 20, United-States, <=50K 52, State-gov, 254285, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 32509, Some-college, 10, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 125492, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 36, Self-emp-inc, 186035, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 69, ?, 168794, 7th-8th, 4, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 48, United-States, <=50K 34, Private, 191856, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 7298, 0, 40, United-States, >50K 36, Private, 215503, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 31, Private, 187560, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 2174, 0, 40, United-States, <=50K 31, Self-emp-not-inc, 252752, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 2415, 40, United-States, >50K 38, Local-gov, 210991, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1740, 40, United-States, <=50K 57, Local-gov, 190748, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 24, Private, 117767, Assoc-acdm, 12, Never-married, Sales, Own-child, White, Male, 0, 0, 20, United-States, <=50K 37, Private, 301070, HS-grad, 9, Divorced, Farming-fishing, Unmarried, White, Male, 0, 0, 45, United-States, <=50K 69, Self-emp-not-inc, 204645, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 9386, 0, 72, United-States, >50K 39, Private, 186183, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 131808, Assoc-voc, 11, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 34, State-gov, 156292, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 21, Private, 124589, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 262819, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 61, Private, 95500, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 241306, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, <=50K 29, Private, 238680, Some-college, 10, Never-married, Sales, Not-in-family, Black, Male, 0, 0, 55, Outlying-US(Guam-USVI-etc), <=50K 18, ?, 42293, 10th, 6, Never-married, ?, Own-child, White, Female, 0, 0, 30, United-States, <=50K 41, Local-gov, 168071, HS-grad, 9, Divorced, Exec-managerial, Own-child, White, Male, 0, 0, 45, United-States, <=50K 42, Private, 337629, 12th, 8, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 60, ?, >50K 52, Private, 168001, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 38, Private, 97759, 12th, 8, Never-married, Other-service, Unmarried, White, Female, 0, 0, 17, United-States, <=50K 51, Self-emp-not-inc, 107096, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 55, Private, 76860, HS-grad, 9, Married-civ-spouse, Other-service, Other-relative, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 20, Private, 70076, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 312017, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 174138, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 125892, Bachelors, 13, Divorced, Exec-managerial, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 210474, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, State-gov, 157332, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 28, Private, 30771, Some-college, 10, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 28, Private, 319768, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, France, >50K 34, Private, 209101, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 5178, 0, 55, United-States, >50K 25, Private, 324609, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 48, Private, 268234, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 32, Local-gov, 178109, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 43, United-States, <=50K 31, Private, 25955, 9th, 5, Never-married, Craft-repair, Own-child, Amer-Indian-Eskimo, Male, 0, 0, 35, United-States, <=50K 65, ?, 123484, HS-grad, 9, Widowed, ?, Other-relative, White, Female, 0, 0, 25, United-States, <=50K 56, Local-gov, 129762, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 22, Self-emp-not-inc, 108506, Assoc-voc, 11, Never-married, Farming-fishing, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 75, United-States, <=50K 27, Private, 241607, Bachelors, 13, Never-married, Tech-support, Other-relative, White, Male, 0, 0, 50, United-States, <=50K 27, Federal-gov, 214385, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 30, Local-gov, 183000, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, <=50K 33, Private, 290763, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 50, Private, 171924, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 43, United-States, >50K 19, Private, 97189, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 22, United-States, <=50K 42, Private, 195096, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 4064, 0, 40, United-States, <=50K 37, Federal-gov, 329088, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, <=50K 26, Private, 58371, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 32, ?, 256371, 12th, 8, Never-married, ?, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 43, Private, 35824, Some-college, 10, Separated, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 173271, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 391349, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 24, Private, 86153, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 295855, 11th, 7, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 70, United-States, <=50K 33, Self-emp-not-inc, 327902, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 35, Private, 285102, Masters, 14, Never-married, Prof-specialty, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, Taiwan, >50K 57, Private, 178353, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 45, Private, 28119, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 7, United-States, <=50K 42, Private, 197522, Some-college, 10, Separated, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 25, Private, 108542, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 35, United-States, <=50K 56, Private, 179781, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Private, 126974, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 180060, Bachelors, 13, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 50, United-States, <=50K 35, Local-gov, 38948, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 50, United-States, <=50K 28, Private, 271572, 9th, 5, Never-married, Other-service, Other-relative, White, Male, 0, 0, 52, United-States, <=50K 41, Private, 177305, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, >50K 26, Private, 238367, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 172232, HS-grad, 9, Divorced, Other-service, Not-in-family, Black, Female, 0, 0, 30, United-States, <=50K 22, Private, 153805, HS-grad, 9, Never-married, Other-service, Unmarried, Other, Male, 0, 0, 20, Puerto-Rico, <=50K 30, Private, 26543, Bachelors, 13, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 109067, Bachelors, 13, Separated, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 213716, Assoc-voc, 11, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 49, Private, 149809, Preschool, 1, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, ?, <=50K 27, Private, 185670, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 43, Federal-gov, 233851, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 68, ?, 192052, Some-college, 10, Married-civ-spouse, ?, Wife, White, Female, 0, 2457, 40, United-States, <=50K 41, Private, 193524, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1485, 40, United-States, <=50K 25, Private, 213385, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 38238, Bachelors, 13, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 68, Private, 104438, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, Ireland, >50K 17, Private, 202344, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 25, United-States, <=50K 45, Self-emp-not-inc, 43434, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 102147, Assoc-voc, 11, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 30, Private, 231826, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 49, State-gov, 247378, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 42, Private, 78765, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 3103, 0, 45, United-States, >50K 29, Private, 184078, HS-grad, 9, Never-married, Other-service, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 21, Local-gov, 102942, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 2001, 40, United-States, <=50K 20, Private, 258430, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 19, United-States, <=50K 59, Private, 244554, 11th, 7, Divorced, Other-service, Not-in-family, Black, Female, 0, 0, 35, United-States, <=50K 26, Private, 252565, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, <=50K 25, Private, 262778, Masters, 14, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 37, United-States, <=50K 33, Private, 162572, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 55, United-States, >50K 35, Private, 65706, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 45, Federal-gov, 102569, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 66, Private, 350498, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 28, United-States, <=50K 67, ?, 159542, 5th-6th, 3, Widowed, ?, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 33, Private, 142383, Assoc-acdm, 12, Never-married, Sales, Not-in-family, Other, Male, 0, 0, 36, United-States, <=50K 38, Private, 229236, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Other, Male, 0, 0, 40, Puerto-Rico, <=50K 72, Private, 56559, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 12, United-States, <=50K 21, Private, 27049, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 12, United-States, <=50K 39, Private, 36376, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 41, Private, 194360, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1887, 40, United-States, >50K 22, Private, 246965, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 12, United-States, <=50K 49, Self-emp-inc, 191277, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 24, Private, 268525, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 32, United-States, <=50K 25, Private, 456604, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 223464, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 341797, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 174461, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 392167, 10th, 6, Divorced, Sales, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 60, Private, 210064, HS-grad, 9, Divorced, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 67, ?, 233182, HS-grad, 9, Divorced, ?, Not-in-family, White, Female, 0, 0, 7, United-States, <=50K 77, Local-gov, 177550, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 3818, 0, 14, United-States, <=50K 62, Private, 143312, Some-college, 10, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 22, Private, 326334, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 35, United-States, <=50K 37, Private, 179088, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 17, Private, 207637, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 10, United-States, <=50K 52, Federal-gov, 37289, Masters, 14, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 31, Private, 36069, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 23, Federal-gov, 53245, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Self-emp-inc, 399904, HS-grad, 9, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 50, Mexico, <=50K 38, Self-emp-inc, 199346, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 45, United-States, <=50K 23, Private, 343019, 10th, 6, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, State-gov, 232742, Some-college, 10, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 61, Self-emp-not-inc, 390472, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 290124, 5th-6th, 3, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 23, Private, 242912, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 4650, 0, 40, United-States, <=50K 39, Private, 70240, 5th-6th, 3, Married-spouse-absent, Other-service, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 38, Local-gov, 286405, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1887, 50, United-States, >50K 25, Private, 153841, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 137367, Bachelors, 13, Never-married, Sales, Unmarried, Asian-Pac-Islander, Male, 0, 0, 44, Philippines, <=50K 66, Private, 313255, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 24, United-States, <=50K 30, Private, 100734, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 248584, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 60001, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 18, Private, 335065, 7th-8th, 4, Never-married, Sales, Own-child, White, Male, 0, 0, 30, Mexico, <=50K 20, Private, 219262, 11th, 7, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 20, Private, 186830, HS-grad, 9, Never-married, Transport-moving, Other-relative, Black, Male, 0, 0, 45, United-States, <=50K 34, Private, 226385, Masters, 14, Divorced, Exec-managerial, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 33, Private, 609789, Assoc-acdm, 12, Married-spouse-absent, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 307767, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 33, Private, 217460, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 30, Private, 104052, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 1741, 42, United-States, <=50K 41, Local-gov, 160893, Preschool, 1, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 30, United-States, <=50K 20, Private, 68358, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 12, United-States, <=50K 40, Self-emp-not-inc, 243636, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 44, Self-emp-not-inc, 71269, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 71898, 5th-6th, 3, Married-civ-spouse, Machine-op-inspct, Wife, Asian-Pac-Islander, Female, 0, 0, 35, Philippines, <=50K 38, ?, 212048, Prof-school, 15, Divorced, ?, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 30, Local-gov, 115040, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Other-relative, White, Male, 0, 0, 25, United-States, <=50K 45, Private, 111994, Some-college, 10, Divorced, Sales, Not-in-family, White, Male, 4650, 0, 40, United-States, <=50K 25, Private, 210794, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 22, ?, 88126, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 570821, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 63, ?, 146196, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, State-gov, 169482, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 63577, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 22, Private, 208946, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Self-emp-not-inc, 26598, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 189203, Assoc-voc, 11, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 183892, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 82, ?, 194590, Assoc-voc, 11, Widowed, ?, Not-in-family, White, Female, 0, 0, 8, United-States, <=50K 18, Private, 188616, 11th, 7, Never-married, Sales, Own-child, White, Male, 0, 0, 15, United-States, <=50K 60, Private, 116707, 11th, 7, Divorced, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 99199, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, United-States, <=50K 39, Local-gov, 183620, Some-college, 10, Never-married, Protective-serv, Not-in-family, Black, Female, 0, 0, 40, United-States, >50K 34, Private, 110476, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Local-gov, 157043, Masters, 14, Divorced, Prof-specialty, Not-in-family, Black, Female, 2202, 0, 30, ?, <=50K 53, Private, 150726, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 214695, HS-grad, 9, Never-married, Sales, Own-child, Black, Male, 0, 0, 60, United-States, <=50K 37, Private, 172694, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 50, United-States, <=50K 25, Private, 344804, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 50, Mexico, <=50K 33, Private, 319422, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, Peru, <=50K 34, State-gov, 327902, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, <=50K 35, Private, 438176, Assoc-voc, 11, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 65, United-States, <=50K 51, Private, 197656, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 33, Private, 219838, 10th, 6, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 57, Self-emp-not-inc, 35561, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, >50K 25, ?, 156848, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 56, Private, 190257, 7th-8th, 4, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 156464, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 85, England, >50K 36, Private, 65624, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 201699, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 55, Private, 349910, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 45, United-States, >50K 88, Self-emp-not-inc, 187097, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 60, Self-emp-not-inc, 264314, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 35, Columbia, <=50K 40, Self-emp-not-inc, 282678, Masters, 14, Separated, Exec-managerial, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 21, Private, 188923, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 55, United-States, <=50K 46, Private, 114797, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, Black, Female, 0, 0, 36, United-States, <=50K 56, Private, 245215, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 36, Self-emp-not-inc, 36270, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 67, Self-emp-not-inc, 107138, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 77820, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 20, Private, 39477, Some-college, 10, Never-married, Farming-fishing, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 58305, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1573, 40, United-States, <=50K 23, Private, 359759, HS-grad, 9, Never-married, Craft-repair, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 19, ?, 249147, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 0, 30, United-States, <=50K 19, Private, 44797, Some-college, 10, Never-married, Farming-fishing, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 25, Private, 164488, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 48413, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, ?, 261276, Some-college, 10, Never-married, ?, Own-child, Black, Female, 0, 1602, 40, Cambodia, <=50K 31, Self-emp-not-inc, 36592, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 91, United-States, <=50K 33, Private, 280923, 7th-8th, 4, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Mexico, <=50K 33, Federal-gov, 29617, Some-college, 10, Divorced, Other-service, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 45, Self-emp-inc, 208802, Prof-school, 15, Divorced, Prof-specialty, Unmarried, White, Male, 25236, 0, 36, United-States, >50K 35, Private, 189240, Some-college, 10, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 20, ?, 37932, HS-grad, 9, Never-married, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 181705, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 147548, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 85, United-States, <=50K 51, Self-emp-not-inc, 306784, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 30, United-States, <=50K 45, ?, 260953, Masters, 14, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, State-gov, 190406, Prof-school, 15, Divorced, Prof-specialty, Unmarried, Black, Male, 25236, 0, 36, United-States, >50K 24, Private, 230229, 5th-6th, 3, Never-married, Machine-op-inspct, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 28, Private, 46987, Assoc-voc, 11, Never-married, Tech-support, Own-child, White, Female, 2174, 0, 36, United-States, <=50K 63, Private, 301108, 11th, 7, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 22, United-States, <=50K 35, Private, 263081, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 60, United-States, >50K 25, Self-emp-not-inc, 37741, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 115834, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Wife, White, Female, 7298, 0, 55, United-States, >50K 44, Private, 150076, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 49, Self-emp-not-inc, 148254, HS-grad, 9, Divorced, Farming-fishing, Not-in-family, White, Female, 0, 0, 28, United-States, <=50K 52, Private, 183611, 1st-4th, 2, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 258768, Bachelors, 13, Never-married, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 35, Private, 287658, Some-college, 10, Never-married, Adm-clerical, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 51, Private, 95946, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 49, Private, 31267, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Local-gov, 302149, Bachelors, 13, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 7298, 0, 40, Philippines, >50K 28, Private, 250135, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 176073, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 65, Private, 23580, Bachelors, 13, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 163665, Bachelors, 13, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 30, Federal-gov, 43953, Assoc-acdm, 12, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 144860, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 65, United-States, <=50K 58, Self-emp-not-inc, 61474, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, >50K 57, Private, 141570, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 1977, 40, United-States, >50K 40, Private, 225660, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 45, United-States, >50K 42, Private, 336891, Some-college, 10, Divorced, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 31, Self-emp-not-inc, 210164, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 17, Private, 171080, 12th, 8, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, United-States, <=50K 42, Private, 143342, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 281627, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 409922, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7298, 0, 40, United-States, >50K 65, ?, 224472, Prof-school, 15, Never-married, ?, Not-in-family, White, Male, 25124, 0, 80, United-States, >50K 29, Private, 157262, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 31, Private, 144949, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 71, Local-gov, 303860, Masters, 14, Widowed, Exec-managerial, Not-in-family, White, Male, 2050, 0, 20, United-States, <=50K 34, Private, 104293, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 195481, HS-grad, 9, Married-civ-spouse, Adm-clerical, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 193995, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 30, United-States, <=50K 67, Private, 105216, Some-college, 10, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 40, Private, 147206, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 18, Private, 173585, HS-grad, 9, Never-married, Sales, Own-child, Black, Female, 0, 0, 18, United-States, <=50K 38, Private, 187870, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7298, 0, 50, United-States, >50K 38, Private, 248919, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Guatemala, <=50K 42, Private, 280410, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 40, Haiti, <=50K 36, State-gov, 170861, HS-grad, 9, Separated, Other-service, Own-child, White, Female, 0, 0, 32, United-States, <=50K 23, Self-emp-not-inc, 409230, 1st-4th, 2, Married-civ-spouse, Sales, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 56, Private, 340171, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 36, Private, 41017, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 52, United-States, >50K 22, Private, 416356, Some-college, 10, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 261504, 12th, 8, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 36, State-gov, 205555, Prof-school, 15, Divorced, Prof-specialty, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 44, Private, 245317, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 56, United-States, >50K 38, Private, 153685, 11th, 7, Divorced, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 52, United-States, <=50K 19, ?, 169758, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 99374, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 55, United-States, <=50K 57, Local-gov, 139452, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 16, United-States, <=50K 54, Private, 227832, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Self-emp-not-inc, 213024, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 30, United-States, <=50K 22, ?, 24008, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 72, United-States, <=50K 63, Self-emp-not-inc, 33487, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Self-emp-inc, 187934, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 20, Poland, <=50K 26, Private, 421561, 11th, 7, Married-civ-spouse, Other-service, Other-relative, White, Male, 0, 0, 25, United-States, <=50K 40, Private, 109969, 11th, 7, Divorced, Other-service, Other-relative, White, Female, 0, 0, 20, United-States, <=50K 20, Private, 116830, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 117166, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 2635, 0, 40, United-States, <=50K 28, Private, 106951, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 42, United-States, <=50K 30, Private, 89625, Some-college, 10, Married-civ-spouse, Prof-specialty, Wife, Asian-Pac-Islander, Female, 0, 0, 5, United-States, >50K 42, Private, 194537, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 144002, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 21, Private, 202214, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 109762, Some-college, 10, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 292570, 11th, 7, Never-married, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 67, Private, 105252, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Male, 7978, 0, 35, United-States, <=50K 65, Private, 94552, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 50, Local-gov, 46401, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 18, Private, 151150, 10th, 6, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 27, United-States, <=50K 31, Private, 197689, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 38, United-States, <=50K 36, Self-emp-inc, 180477, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 20, Private, 181761, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 381153, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 165474, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 39, United-States, <=50K 38, Federal-gov, 190174, HS-grad, 9, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 17, Private, 295991, 10th, 6, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 52, Without-pay, 198262, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 30, United-States, <=50K 34, Private, 190385, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 30, ?, 411560, HS-grad, 9, Married-civ-spouse, ?, Husband, Black, Male, 0, 0, 40, United-States, <=50K 49, Private, 262116, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 48, United-States, <=50K 45, Private, 178922, 9th, 5, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 46, Private, 192963, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 2415, 35, Philippines, >50K 34, Self-emp-inc, 209538, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 21, Self-emp-not-inc, 103277, 12th, 8, Married-civ-spouse, Adm-clerical, Wife, White, Female, 4508, 0, 30, Portugal, <=50K 17, Private, 216086, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 23, Private, 636017, Some-college, 10, Never-married, Other-service, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 32, Private, 155781, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 136873, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 48, State-gov, 122066, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 35, United-States, >50K 27, State-gov, 346406, Bachelors, 13, Never-married, Prof-specialty, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 43, Private, 117915, Masters, 14, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 19914, HS-grad, 9, Married-civ-spouse, Other-service, Wife, Asian-Pac-Islander, Female, 0, 0, 50, Philippines, <=50K 55, Private, 255364, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 31, Private, 703107, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 34, Private, 62374, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 34, Private, 96245, HS-grad, 9, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 348796, Bachelors, 13, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 136873, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 10, United-States, <=50K 35, Private, 388252, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, <=50K 28, Private, 47783, Some-college, 10, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 62, Private, 194167, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Female, 2174, 0, 40, United-States, <=50K 40, Federal-gov, 544792, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 434463, Bachelors, 13, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 39, United-States, <=50K 32, Private, 317219, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 1590, 40, United-States, <=50K 70, Private, 221603, Some-college, 10, Widowed, Sales, Not-in-family, White, Female, 0, 0, 34, United-States, <=50K 23, Private, 233711, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 50, United-States, <=50K 30, Private, 111567, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 48, United-States, <=50K 57, Private, 79830, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 34, Self-emp-not-inc, 192259, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, >50K 24, Private, 239663, 10th, 6, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Mexico, <=50K 41, Local-gov, 34987, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, >50K 38, Self-emp-not-inc, 409189, 7th-8th, 4, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, Mexico, <=50K 48, Private, 135525, Assoc-acdm, 12, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 152159, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 18, Private, 141363, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 214816, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Private, 42907, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Male, 0, 0, 48, United-States, <=50K 30, Private, 161815, Some-college, 10, Divorced, Other-service, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 42, Private, 127314, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 45, United-States, >50K 48, Private, 395368, Some-college, 10, Divorced, Handlers-cleaners, Other-relative, Black, Male, 0, 0, 40, United-States, <=50K 70, Private, 184176, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 28, United-States, <=50K 37, Private, 112660, 9th, 5, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 35, United-States, <=50K 51, Private, 183709, Assoc-voc, 11, Separated, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 434114, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Mexico, <=50K 59, Self-emp-not-inc, 165315, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 43, United-States, >50K 57, Private, 190997, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 26, Private, 335533, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 20, United-States, <=50K 26, Private, 176146, 5th-6th, 3, Separated, Craft-repair, Not-in-family, Other, Male, 0, 0, 35, Mexico, <=50K 19, Private, 272063, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 35, United-States, <=50K 34, Private, 169564, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 56, Private, 188856, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 8614, 0, 55, United-States, >50K 25, Private, 69847, Bachelors, 13, Never-married, Adm-clerical, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 46, Self-emp-not-inc, 198759, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 2415, 80, United-States, >50K 22, Private, 175431, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 20, United-States, <=50K 32, Private, 228357, Assoc-voc, 11, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, ?, <=50K 72, Self-emp-not-inc, 284120, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 109133, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 167336, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 45, United-States, >50K 76, ?, 42209, 9th, 5, Widowed, ?, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 37, Private, 282951, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 303155, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 44, Private, 261899, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 44, United-States, <=50K 33, Private, 168030, Some-college, 10, Married-civ-spouse, Prof-specialty, Wife, White, Female, 7298, 0, 21, United-States, >50K 53, State-gov, 71417, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 239130, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 69, Private, 200560, Bachelors, 13, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 20, United-States, <=50K 20, Private, 157541, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 27, United-States, <=50K 33, Private, 255004, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 47, Private, 230136, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 60, United-States, >50K 50, Local-gov, 124963, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1977, 35, United-States, >50K 22, Private, 39615, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 20, Private, 47678, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 42, Local-gov, 281315, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 23, Private, 176123, HS-grad, 9, Never-married, Tech-support, Other-relative, Asian-Pac-Islander, Male, 0, 0, 40, Vietnam, <=50K 24, ?, 165350, HS-grad, 9, Separated, ?, Not-in-family, Black, Male, 0, 0, 50, Germany, <=50K 32, Private, 235862, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 41, Private, 142579, Bachelors, 13, Widowed, Sales, Unmarried, Black, Male, 0, 0, 50, United-States, <=50K 35, Private, 38294, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 111483, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 25, Private, 189850, Some-college, 10, Never-married, Machine-op-inspct, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 34, State-gov, 145874, Doctorate, 16, Married-civ-spouse, Tech-support, Husband, Asian-Pac-Islander, Male, 0, 0, 20, China, <=50K 23, Private, 139012, Assoc-voc, 11, Never-married, Transport-moving, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, South, <=50K 30, Local-gov, 211654, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 55, Local-gov, 173090, Masters, 14, Widowed, Prof-specialty, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 26, Private, 104834, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 1669, 40, United-States, <=50K 42, ?, 195124, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 60, Dominican-Republic, <=50K 39, Private, 32146, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 52, Private, 282674, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, >50K 42, Private, 190403, Some-college, 10, Separated, Exec-managerial, Not-in-family, White, Male, 0, 0, 60, Canada, <=50K 25, Private, 247025, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 3325, 0, 48, United-States, <=50K 27, Private, 198258, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 0, 35, United-States, <=50K 30, Self-emp-not-inc, 172748, 7th-8th, 4, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 23, State-gov, 287988, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 10520, 0, 40, United-States, >50K 47, Self-emp-not-inc, 122307, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 1887, 40, United-States, >50K 58, ?, 175017, Bachelors, 13, Divorced, ?, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 18, Private, 170183, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 52, Private, 150812, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 24, Private, 241185, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 58, Self-emp-inc, 174864, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, >50K 35, Private, 30529, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 301637, Assoc-voc, 11, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 423222, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 3103, 0, 60, United-States, >50K 43, Private, 214781, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 5178, 0, 40, United-States, >50K 21, Private, 242912, HS-grad, 9, Never-married, Other-service, Other-relative, White, Female, 0, 0, 35, United-States, <=50K 52, Private, 191529, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1740, 60, United-States, <=50K 24, Private, 117363, Bachelors, 13, Never-married, Sales, Own-child, White, Female, 0, 0, 35, United-States, <=50K 22, Private, 333158, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 39, Private, 193260, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 0, 25, Mexico, <=50K 34, State-gov, 278378, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 58, Private, 111394, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 102476, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 25, United-States, <=50K 29, Private, 26451, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 67, ?, 209137, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 210945, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 0, 35, Haiti, <=50K 62, Local-gov, 115023, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 53833, 5th-6th, 3, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 150057, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 65, United-States, <=50K 18, Private, 128086, 12th, 8, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 18, United-States, <=50K 25, Private, 28473, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 155509, Some-college, 10, Never-married, Craft-repair, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 56, Private, 165315, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 70, ?, <=50K 30, Private, 171889, Prof-school, 15, Never-married, Tech-support, Own-child, White, Female, 0, 0, 24, United-States, <=50K 41, Local-gov, 185057, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 59, Private, 277034, HS-grad, 9, Divorced, Tech-support, Unmarried, White, Male, 0, 0, 60, United-States, >50K 36, Private, 166606, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 97453, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 54, United-States, <=50K 27, Private, 136094, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 19, ?, 61855, HS-grad, 9, Never-married, ?, Other-relative, White, Female, 0, 0, 30, United-States, <=50K 30, Private, 182771, Bachelors, 13, Never-married, Other-service, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 15, China, <=50K 47, Private, 418961, Assoc-voc, 11, Divorced, Sales, Unmarried, Black, Female, 0, 0, 25, United-States, <=50K 39, Private, 106961, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 81846, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 44, Private, 105936, Assoc-acdm, 12, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 36425, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 595088, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 63, United-States, <=50K 38, Private, 149018, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 229613, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 33521, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Private, 70539, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 4386, 0, 50, United-States, <=50K 53, State-gov, 105728, HS-grad, 9, Married-civ-spouse, Other-service, Wife, Amer-Indian-Eskimo, Female, 0, 0, 28, United-States, >50K 31, Private, 193215, Some-college, 10, Married-civ-spouse, Exec-managerial, Own-child, White, Male, 0, 0, 50, United-States, <=50K 18, Private, 137363, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 43, Self-emp-inc, 104892, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 45, United-States, <=50K 30, Private, 149427, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 35, United-States, <=50K 19, State-gov, 176634, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 183279, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, ?, 225775, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 202091, Masters, 14, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 60, United-States, <=50K 36, Private, 123151, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 22, Private, 168187, Some-college, 10, Never-married, Other-service, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 42, Federal-gov, 33521, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, State-gov, 243678, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 164898, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, ?, 262280, Some-college, 10, Married-civ-spouse, ?, Wife, White, Female, 3781, 0, 40, United-States, <=50K 33, State-gov, 290614, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Self-emp-not-inc, 199265, HS-grad, 9, Divorced, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 30, Private, 207668, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 30, United-States, <=50K 18, State-gov, 30687, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 10, United-States, <=50K 24, State-gov, 27939, Some-college, 10, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 24, ?, <=50K 17, Private, 438996, 10th, 6, Never-married, Other-service, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 48, Private, 152915, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 66, ?, 186030, 7th-8th, 4, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 32, United-States, <=50K 46, Local-gov, 297759, Some-college, 10, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 55, Private, 171242, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 28, Private, 206088, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 182792, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 167725, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 24, United-States, <=50K 43, Private, 160674, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 194710, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 255027, Assoc-voc, 11, Divorced, Exec-managerial, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 23, Private, 204641, 10th, 6, Never-married, Handlers-cleaners, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 20, State-gov, 177787, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 29, Private, 54932, Some-college, 10, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 35, United-States, >50K 54, Self-emp-not-inc, 91506, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 65, United-States, <=50K 34, Private, 198634, Assoc-voc, 11, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 227146, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 59, Private, 135647, 11th, 7, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 40, Private, 55508, 7th-8th, 4, Divorced, Farming-fishing, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 174912, HS-grad, 9, Separated, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 175925, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Self-emp-not-inc, 157486, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7298, 0, 40, United-States, >50K 49, Local-gov, 329144, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 44, United-States, >50K 67, ?, 81761, Masters, 14, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 2, United-States, <=50K 49, Self-emp-not-inc, 102318, Assoc-acdm, 12, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 30, Federal-gov, 266463, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 56, Federal-gov, 107314, Some-college, 10, Divorced, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 29, Private, 114158, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 124052, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 144301, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 42, United-States, <=50K 28, Private, 176683, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 70, United-States, >50K 23, Private, 234663, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Self-emp-not-inc, 178948, HS-grad, 9, Married-civ-spouse, Farming-fishing, Wife, White, Female, 0, 0, 50, United-States, <=50K 37, Self-emp-not-inc, 607848, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 202937, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 32, Federal-gov, 83413, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 35, United-States, >50K 26, Private, 212798, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 57, Federal-gov, 192258, Some-college, 10, Divorced, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 112497, 9th, 5, Married-civ-spouse, Sales, Own-child, White, Male, 0, 0, 50, United-States, >50K 30, Private, 97521, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 27, Private, 160972, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 21, Private, 322931, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 22, Private, 403519, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Local-gov, 330174, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 278155, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 39054, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 65, United-States, >50K 57, Private, 170287, Masters, 14, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Private, 336643, Assoc-voc, 11, Separated, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 264166, Assoc-voc, 11, Divorced, Other-service, Unmarried, White, Female, 0, 0, 45, Columbia, <=50K 44, Local-gov, 433705, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 52, United-States, >50K 28, Private, 27044, Assoc-acdm, 12, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 43, United-States, <=50K 42, Private, 165599, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 159759, Bachelors, 13, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 385092, Some-college, 10, Divorced, Prof-specialty, Own-child, White, Female, 0, 0, 36, United-States, <=50K 42, Private, 188808, Bachelors, 13, Divorced, Adm-clerical, Unmarried, White, Male, 0, 0, 30, United-States, <=50K 30, Private, 167476, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 21, State-gov, 194096, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 10, United-States, <=50K 59, Private, 182460, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 30, United-States, >50K 21, ?, 102323, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 30, United-States, <=50K 56, Private, 232139, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 341741, Preschool, 1, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 12, United-States, <=50K 21, Private, 206008, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Male, 0, 0, 50, United-States, <=50K 48, Private, 344415, Bachelors, 13, Married-spouse-absent, Prof-specialty, Not-in-family, White, Male, 0, 0, 37, United-States, >50K 35, State-gov, 372130, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 40, United-States, <=50K 43, Private, 27766, Bachelors, 13, Separated, Exec-managerial, Unmarried, White, Male, 0, 0, 60, United-States, >50K 23, Private, 140764, Assoc-voc, 11, Never-married, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 17, ?, 161259, 10th, 6, Never-married, ?, Other-relative, White, Male, 0, 0, 12, United-States, <=50K 41, Private, 22201, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Japan, >50K 35, Self-emp-inc, 187046, Masters, 14, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, <=50K 22, Private, 137591, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 35, United-States, <=50K 53, Private, 274276, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 341757, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 218542, HS-grad, 9, Separated, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 44, Local-gov, 190020, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 27, Private, 221436, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, Cuba, >50K 39, Self-emp-not-inc, 52187, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 59, Private, 158776, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Local-gov, 51543, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 17, Private, 146329, 12th, 8, Never-married, Sales, Own-child, White, Female, 0, 0, 23, United-States, <=50K 31, Private, 397467, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 59, Private, 105592, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 12, United-States, <=50K 39, Private, 78171, Some-college, 10, Married-spouse-absent, Adm-clerical, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 46, State-gov, 55377, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 40, United-States, >50K 31, Private, 258932, HS-grad, 9, Married-spouse-absent, Other-service, Not-in-family, White, Female, 0, 0, 80, Italy, <=50K 27, Private, 38606, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 1504, 45, United-States, <=50K 18, Private, 219841, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 12, United-States, <=50K 46, Private, 156926, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 55, Private, 160362, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 48, Private, 192161, Bachelors, 13, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 43, United-States, <=50K 53, Private, 208570, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 26, United-States, <=50K 44, Self-emp-not-inc, 182771, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 48, South, >50K 43, Private, 151089, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 50, Private, 163002, HS-grad, 9, Separated, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 56, Private, 155657, 7th-8th, 4, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 20, Yugoslavia, <=50K 27, Private, 217530, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 20, Private, 244406, HS-grad, 9, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 18, Local-gov, 152182, 10th, 6, Never-married, Protective-serv, Own-child, White, Female, 0, 0, 6, United-States, <=50K 34, Private, 55717, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1848, 50, United-States, >50K 38, Private, 201454, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 40, Self-emp-inc, 144371, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 15, United-States, <=50K 55, Private, 277034, Some-college, 10, Divorced, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Self-emp-not-inc, 462832, HS-grad, 9, Married-civ-spouse, Craft-repair, Wife, Black, Female, 0, 0, 40, United-States, >50K 26, Private, 200681, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 54, State-gov, 119565, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, Puerto-Rico, >50K 22, Private, 192017, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 52, Local-gov, 84808, HS-grad, 9, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 33, Private, 100154, 10th, 6, Separated, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 169383, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 19, Without-pay, 43887, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 10, United-States, <=50K 45, Private, 54260, Some-college, 10, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 99, United-States, <=50K 53, Self-emp-not-inc, 159876, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 3103, 0, 72, United-States, <=50K 46, Private, 160474, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 1590, 43, United-States, <=50K 25, Private, 476334, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 90, Private, 52386, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 33, Private, 83671, HS-grad, 9, Never-married, Sales, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 45, Private, 172960, Some-college, 10, Divorced, Protective-serv, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 47, Private, 191957, HS-grad, 9, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 40, United-States, >50K 38, Local-gov, 40955, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 43, United-States, <=50K 35, ?, 98080, Prof-school, 15, Never-married, ?, Not-in-family, Asian-Pac-Islander, Male, 4787, 0, 45, Japan, >50K 37, Private, 175643, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 30, United-States, <=50K 53, State-gov, 197184, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 70, United-States, >50K 56, Private, 187295, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 18, Private, 40822, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 15, United-States, <=50K 44, Private, 228729, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, ?, <=50K 50, Private, 240496, Some-college, 10, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 36, United-States, <=50K 26, Private, 51961, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, Black, Male, 0, 0, 20, United-States, <=50K 36, Private, 174887, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 95855, 11th, 7, Divorced, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 362259, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Self-emp-not-inc, 30916, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 62, Private, 153148, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 84, United-States, <=50K 46, Private, 167915, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 45156, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 2174, 0, 41, United-States, <=50K 37, Private, 98776, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 15, United-States, <=50K 27, Private, 209801, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 45, ?, <=50K 38, Private, 183800, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 54595, 12th, 8, Never-married, Sales, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 34, Private, 79637, Bachelors, 13, Never-married, Exec-managerial, Own-child, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 50, Private, 126566, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, United-States, <=50K 28, Private, 233796, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 7298, 0, 32, United-States, >50K 67, Local-gov, 191800, Bachelors, 13, Divorced, Adm-clerical, Unmarried, Black, Female, 6360, 0, 35, United-States, <=50K 34, Self-emp-not-inc, 527162, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 30, United-States, <=50K 19, Private, 139466, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 25, United-States, <=50K 23, Private, 64520, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 30, United-States, <=50K 50, Private, 97741, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, >50K 45, Local-gov, 160173, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 50, United-States, >50K 17, Private, 350995, 12th, 8, Never-married, Other-service, Own-child, White, Male, 0, 0, 16, United-States, <=50K 59, ?, 182836, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 40, United-States, >50K 25, Private, 143267, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 21, Private, 346341, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 50, Private, 172175, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 17, Private, 153035, 10th, 6, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 63, Private, 200127, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Local-gov, 204470, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 43, United-States, <=50K 45, Private, 353012, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 194342, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 57898, 12th, 8, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 164707, Some-college, 10, Never-married, Sales, Other-relative, White, Female, 0, 0, 40, ?, <=50K 42, Private, 269028, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, France, <=50K 56, Private, 83922, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 47, Private, 160647, HS-grad, 9, Never-married, Farming-fishing, Unmarried, White, Female, 0, 0, 46, United-States, <=50K 69, Private, 125437, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 42, Private, 246011, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 55, United-States, <=50K 19, Private, 216937, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, Other, Female, 0, 0, 60, Guatemala, <=50K 56, Self-emp-not-inc, 66356, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 33, Private, 154981, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 1902, 50, United-States, >50K 61, Federal-gov, 197311, Masters, 14, Widowed, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 301743, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 50, Self-emp-not-inc, 401118, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 99999, 0, 50, United-States, >50K 39, Private, 98776, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 35, Self-emp-not-inc, 32528, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 27, Private, 177119, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 44, United-States, <=50K 40, Self-emp-inc, 193524, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, >50K 59, State-gov, 192258, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 20, ?, 145917, Some-college, 10, Never-married, ?, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 42, Federal-gov, 214838, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 30, United-States, >50K 59, Private, 176011, Some-college, 10, Separated, Adm-clerical, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 54, Self-emp-inc, 147239, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 38, Private, 159179, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 50, United-States, >50K 53, Private, 155963, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 30, United-States, <=50K 20, Private, 360457, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 30, United-States, <=50K 54, Federal-gov, 114674, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Self-emp-not-inc, 95708, Masters, 14, Never-married, Exec-managerial, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 45, United-States, >50K 33, Local-gov, 100734, HS-grad, 9, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 35, Private, 188972, HS-grad, 9, Widowed, Exec-managerial, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 22, Private, 162667, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 50, Portugal, <=50K 45, Self-emp-not-inc, 28497, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 1485, 70, United-States, >50K 29, Private, 180758, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 56, Self-emp-not-inc, 346635, Masters, 14, Divorced, Sales, Unmarried, White, Female, 0, 2339, 60, United-States, <=50K 23, Private, 46645, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 30, Private, 203258, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 17, Private, 134480, 11th, 7, Never-married, Priv-house-serv, Own-child, White, Female, 0, 0, 25, United-States, <=50K 35, Local-gov, 85548, Some-college, 10, Separated, Adm-clerical, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 25, Private, 195994, 1st-4th, 2, Never-married, Priv-house-serv, Not-in-family, White, Female, 0, 0, 40, Guatemala, <=50K 42, State-gov, 148316, Assoc-voc, 11, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Private, 227466, HS-grad, 9, Never-married, Other-service, Other-relative, Black, Male, 0, 0, 40, United-States, <=50K 19, Private, 68552, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 30, United-States, <=50K 32, Private, 252257, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 44, Private, 30126, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 53, Private, 304353, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 36, United-States, >50K 47, Self-emp-not-inc, 171968, Bachelors, 13, Widowed, Exec-managerial, Unmarried, Asian-Pac-Islander, Female, 0, 0, 60, Thailand, <=50K 24, Private, 205839, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 30, State-gov, 218640, Some-college, 10, Married-civ-spouse, Prof-specialty, Wife, Black, Female, 0, 0, 40, United-States, >50K 42, Private, 150568, HS-grad, 9, Separated, Sales, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 19, Private, 382738, HS-grad, 9, Never-married, Other-service, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 37, Self-emp-not-inc, 138940, 11th, 7, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 37, United-States, <=50K 26, Self-emp-not-inc, 258306, 10th, 6, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 99, United-States, <=50K 25, Local-gov, 190107, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 1719, 16, United-States, <=50K 52, Private, 152373, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Local-gov, 141875, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 79586, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 99999, 0, 40, ?, >50K 32, Private, 157289, HS-grad, 9, Married-spouse-absent, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 184498, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Local-gov, 109684, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 1741, 35, United-States, <=50K 47, Private, 199832, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 23545, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 175710, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 27, Private, 52028, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, Asian-Pac-Islander, Female, 0, 0, 40, South, <=50K 61, Self-emp-not-inc, 315977, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 47, Private, 202322, 5th-6th, 3, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Mexico, <=50K 30, Private, 251825, Assoc-acdm, 12, Never-married, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 54, Private, 202115, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, United-States, >50K 56, Local-gov, 216824, Prof-school, 15, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, >50K 69, Private, 145656, Some-college, 10, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 24, United-States, <=50K 30, Private, 137076, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 152621, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Canada, >50K 42, Self-emp-not-inc, 27242, 11th, 7, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 45, Federal-gov, 358242, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 39, Private, 184117, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 7688, 0, 20, United-States, >50K 26, Private, 300290, 11th, 7, Divorced, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 28, Local-gov, 149991, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 42, United-States, >50K 31, Private, 189759, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Private, 339482, 5th-6th, 3, Separated, Farming-fishing, Other-relative, White, Male, 0, 0, 60, Mexico, <=50K 51, Private, 100933, HS-grad, 9, Never-married, Exec-managerial, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 354558, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 38, Local-gov, 162613, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 2258, 60, United-States, <=50K 64, Private, 285052, Some-college, 10, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 10, United-States, <=50K 26, State-gov, 175044, Some-college, 10, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 40, United-States, <=50K 68, Private, 45508, 5th-6th, 3, Married-spouse-absent, Sales, Not-in-family, White, Male, 0, 0, 22, United-States, <=50K 32, Private, 173351, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, <=50K 29, Private, 173611, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 51, ?, 182543, 1st-4th, 2, Separated, ?, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 21, Private, 143062, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 26, ?, 137951, 10th, 6, Separated, ?, Other-relative, White, Female, 0, 0, 40, Puerto-Rico, <=50K 33, Local-gov, 293063, Bachelors, 13, Married-spouse-absent, Prof-specialty, Other-relative, Black, Male, 0, 0, 40, ?, <=50K 26, Private, 377754, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 152373, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 2105, 0, 40, United-States, <=50K 31, Private, 193477, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, <=50K 29, Local-gov, 277323, HS-grad, 9, Never-married, Protective-serv, Unmarried, White, Male, 0, 0, 45, United-States, <=50K 19, Private, 69182, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 27, United-States, <=50K 51, Private, 219599, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 129371, 9th, 5, Separated, Other-service, Unmarried, Other, Female, 0, 0, 40, Trinadad&Tobago, <=50K 20, Private, 470875, HS-grad, 9, Married-civ-spouse, Sales, Own-child, Black, Male, 0, 0, 32, United-States, <=50K 40, Private, 201734, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 43, Private, 58447, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 55, United-States, >50K 52, Local-gov, 91689, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 166546, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 24, United-States, <=50K 24, Private, 293324, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 219262, 9th, 5, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 38, Self-emp-not-inc, 403391, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 44, Private, 367749, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, Mexico, <=50K 24, Private, 128487, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 32, State-gov, 111363, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 75, United-States, >50K 49, Private, 240869, 7th-8th, 4, Never-married, Other-service, Other-relative, White, Male, 0, 0, 35, United-States, <=50K 36, Private, 163278, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 416415, HS-grad, 9, Separated, Adm-clerical, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 46, ?, 280030, 5th-6th, 3, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, Mexico, <=50K 46, Private, 251243, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 46, Local-gov, 167159, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 70, United-States, >50K 29, Private, 161857, HS-grad, 9, Married-spouse-absent, Other-service, Not-in-family, Other, Female, 0, 0, 40, Columbia, <=50K 37, Private, 160035, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, ?, 190205, 7th-8th, 4, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 25, United-States, <=50K 28, ?, 161290, Some-college, 10, Never-married, ?, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 28, Self-emp-not-inc, 112403, Bachelors, 13, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 238726, HS-grad, 9, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 52, Private, 164530, 11th, 7, Divorced, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 20, United-States, <=50K 19, Private, 456572, HS-grad, 9, Never-married, Farming-fishing, Other-relative, White, Male, 0, 0, 35, United-States, <=50K 31, Self-emp-not-inc, 177675, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 47, Private, 246739, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 55, United-States, >50K 37, Private, 102953, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, ?, 224238, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 2, United-States, <=50K 46, Private, 155489, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 44, United-States, >50K 51, Self-emp-not-inc, 156802, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 3103, 0, 60, United-States, >50K 50, Private, 168212, Masters, 14, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1902, 45, United-States, >50K 38, Private, 331395, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 3942, 0, 84, Portugal, <=50K 40, Local-gov, 261497, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 35, United-States, <=50K 58, Private, 365511, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, Other, Male, 0, 0, 40, Mexico, <=50K 36, Private, 187999, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Local-gov, 190350, Bachelors, 13, Never-married, Prof-specialty, Own-child, Black, Female, 0, 0, 35, United-States, <=50K 17, ?, 166759, 12th, 8, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 168262, 10th, 6, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 39, State-gov, 122011, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 5178, 0, 38, United-States, >50K 46, Private, 165953, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, >50K 26, Private, 375980, HS-grad, 9, Separated, Sales, Unmarried, Black, Female, 0, 0, 37, United-States, <=50K 40, Federal-gov, 406463, Masters, 14, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 53, State-gov, 231472, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 60, Self-emp-not-inc, 78913, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 28, Private, 69107, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, United-States, <=50K 22, ?, 182387, Some-college, 10, Never-married, ?, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 12, Thailand, <=50K 31, Private, 169002, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 55, United-States, <=50K 45, Private, 229967, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 13550, 0, 50, United-States, >50K 34, Private, 422836, HS-grad, 9, Divorced, Prof-specialty, Unmarried, White, Male, 0, 0, 40, Mexico, <=50K 27, State-gov, 230922, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, Scotland, <=50K 40, Private, 195892, Some-college, 10, Divorced, Transport-moving, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 68, Private, 163346, HS-grad, 9, Widowed, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 51, Private, 82566, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 55, Private, 86505, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 20, United-States, <=50K 43, Private, 178780, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 23, State-gov, 173945, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 27, United-States, <=50K 48, Private, 176810, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Self-emp-inc, 23813, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, Amer-Indian-Eskimo, Male, 2885, 0, 30, United-States, <=50K 51, Self-emp-inc, 210736, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 10520, 0, 40, United-States, >50K 32, Private, 343789, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 5013, 0, 55, United-States, <=50K 34, Private, 113838, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 31, Local-gov, 121055, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 70, United-States, >50K 71, ?, 52171, 7th-8th, 4, Divorced, ?, Unmarried, White, Male, 0, 0, 45, United-States, <=50K 17, Private, 566049, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 8, United-States, <=50K 37, Private, 67433, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 26, Private, 39014, 12th, 8, Married-civ-spouse, Priv-house-serv, Wife, Other, Female, 0, 0, 40, Dominican-Republic, <=50K 17, Private, 51939, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 15, United-States, <=50K 34, Private, 100669, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, >50K 46, Private, 155659, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1902, 40, United-States, >50K 33, Private, 112847, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Asian-Pac-Islander, Male, 0, 0, 40, ?, <=50K 41, Local-gov, 32185, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 59, Private, 138370, 10th, 6, Married-spouse-absent, Protective-serv, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, India, <=50K 50, Self-emp-not-inc, 172281, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 50, United-States, >50K 46, Private, 180505, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 45, Private, 168262, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 85126, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 113838, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 32, Private, 197457, HS-grad, 9, Divorced, Tech-support, Unmarried, White, Female, 1471, 0, 38, United-States, <=50K 28, Private, 197905, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 32, Private, 316589, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 336367, Assoc-acdm, 12, Never-married, Exec-managerial, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 39, Self-emp-inc, 143123, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 2415, 40, United-States, >50K 23, Private, 209955, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 210013, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Private, 224541, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 275653, 7th-8th, 4, Married-spouse-absent, Machine-op-inspct, Unmarried, White, Female, 2977, 0, 40, Puerto-Rico, <=50K 45, Private, 88061, 11th, 7, Married-spouse-absent, Machine-op-inspct, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, South, <=50K 43, Federal-gov, 195897, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 7298, 0, 40, United-States, >50K 49, Private, 43206, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 55, United-States, >50K 37, Private, 202950, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 154093, HS-grad, 9, Never-married, Transport-moving, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 34, Private, 112115, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 55, United-States, >50K 51, Private, 355954, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, >50K 24, Private, 379418, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 67, Self-emp-not-inc, 286372, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 48087, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 7298, 0, 45, United-States, >50K 32, Private, 387270, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, >50K 21, Private, 270043, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 16, United-States, <=50K 39, Self-emp-not-inc, 65738, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 15, United-States, >50K 33, Private, 159888, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 278039, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 21, Private, 265434, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 30, United-States, <=50K 68, Self-emp-inc, 52052, Assoc-voc, 11, Widowed, Sales, Not-in-family, White, Female, 25124, 0, 50, United-States, >50K 24, Private, 208882, HS-grad, 9, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 24, Private, 229393, 11th, 7, Never-married, Farming-fishing, Unmarried, White, Male, 2463, 0, 40, United-States, <=50K 23, Private, 53513, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 45, United-States, <=50K 40, Private, 225193, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 63, United-States, <=50K 48, Private, 166809, Bachelors, 13, Married-spouse-absent, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 42, Self-emp-not-inc, 175674, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 45, Federal-gov, 368947, Bachelors, 13, Never-married, Protective-serv, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 31, Private, 194901, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 53, Private, 203173, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 25, Private, 267431, Bachelors, 13, Never-married, Prof-specialty, Own-child, Black, Female, 0, 0, 55, United-States, <=50K 32, Private, 111836, Some-college, 10, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 50, United-States, <=50K 34, Private, 198613, 11th, 7, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 25, ?, <=50K 41, Self-emp-inc, 149102, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 35, United-States, >50K 57, Local-gov, 121111, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 130397, 10th, 6, Never-married, Farming-fishing, Unmarried, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 40, Private, 212847, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 2179, 40, United-States, <=50K 17, Private, 184198, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 13, United-States, <=50K 17, Private, 121287, 9th, 5, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 82, Self-emp-inc, 120408, Some-college, 10, Widowed, Sales, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 40, Private, 164678, Assoc-acdm, 12, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 26, Private, 388812, Some-college, 10, Never-married, Sales, Not-in-family, Black, Male, 0, 0, 35, United-States, <=50K 37, Private, 294919, Some-college, 10, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 101684, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 65, Private, 36209, 10th, 6, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 22, United-States, >50K 39, Private, 123983, Bachelors, 13, Divorced, Sales, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, China, <=50K 36, Self-emp-not-inc, 340001, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Self-emp-not-inc, 203828, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 23, Private, 183789, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 305619, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 63, Self-emp-not-inc, 174181, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 20, United-States, <=50K 59, Private, 131869, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 49, Self-emp-not-inc, 43479, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 62, ?, 203126, 9th, 5, Never-married, ?, Unmarried, White, Female, 0, 0, 40, Dominican-Republic, <=50K 17, Private, 118792, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 9, United-States, <=50K 28, Private, 272913, 10th, 6, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 30, Mexico, <=50K 45, Federal-gov, 222011, Bachelors, 13, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Self-emp-inc, 301007, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 45, Private, 197731, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 173736, 9th, 5, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 19, ?, 182590, 10th, 6, Never-married, ?, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 59, Local-gov, 93211, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 22, United-States, >50K 41, Private, 24763, HS-grad, 9, Divorced, Transport-moving, Unmarried, White, Male, 7443, 0, 40, United-States, <=50K 49, Local-gov, 219021, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 48, United-States, >50K 37, Private, 137229, Assoc-voc, 11, Divorced, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 31, Self-emp-not-inc, 281030, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 21, Private, 234108, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 46868, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 20, ?, 162667, HS-grad, 9, Never-married, ?, Other-relative, White, Male, 0, 0, 40, El-Salvador, <=50K 51, Private, 173291, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 305160, 1st-4th, 2, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Mexico, <=50K 48, Private, 212954, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, >50K 39, Local-gov, 112284, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 50, Private, 164198, Assoc-acdm, 12, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 15024, 0, 45, United-States, >50K 41, Private, 152958, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 21, Private, 145389, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 54, Self-emp-inc, 119570, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 40, Private, 272343, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 44, Private, 187720, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 41, United-States, <=50K 50, Private, 145409, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 42, Private, 208726, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 34, Private, 203488, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 330416, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 25803, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 171150, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Private, 82576, Prof-school, 15, Divorced, Prof-specialty, Not-in-family, White, Male, 14084, 0, 36, United-States, >50K 30, Private, 329425, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 185452, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 201179, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 182268, Preschool, 1, Married-spouse-absent, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 56, Self-emp-not-inc, 95763, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, <=50K 48, Private, 125892, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Poland, <=50K 21, Private, 121407, Assoc-voc, 11, Never-married, Other-service, Own-child, White, Female, 0, 0, 36, United-States, <=50K 52, Private, 373367, 11th, 7, Widowed, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 60, Local-gov, 165982, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 45, Private, 165484, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 30, Private, 156890, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, <=50K 31, Private, 156763, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 2829, 0, 40, United-States, <=50K 43, Private, 244172, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 35, ?, <=50K 36, Private, 219814, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, Guatemala, <=50K 42, Private, 171841, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 28, Local-gov, 168524, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 7688, 0, 35, United-States, >50K 62, Private, 205643, Prof-school, 15, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 65, ?, 174904, HS-grad, 9, Separated, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 102559, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Canada, >50K 47, Private, 60267, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 38, United-States, >50K 43, Private, 388725, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 215712, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 44, Private, 171722, HS-grad, 9, Separated, Other-service, Unmarried, White, Female, 0, 0, 39, United-States, <=50K 25, Private, 193051, HS-grad, 9, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 25, United-States, <=50K 21, Private, 305446, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 146949, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 43, United-States, <=50K 21, Private, 322144, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Self-emp-inc, 75742, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, El-Salvador, >50K 64, ?, 380687, Bachelors, 13, Married-civ-spouse, ?, Wife, Black, Female, 0, 0, 8, United-States, <=50K 55, Self-emp-not-inc, 95149, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 99, United-States, <=50K 42, Private, 68469, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 63, Self-emp-not-inc, 27653, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 35, United-States, <=50K 21, Private, 410439, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 24, United-States, <=50K 28, Private, 37821, Assoc-voc, 11, Never-married, Sales, Unmarried, White, Female, 0, 0, 55, ?, <=50K 45, Private, 228570, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 35, United-States, <=50K 21, Private, 141453, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 88215, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, Asian-Pac-Islander, Female, 0, 0, 40, China, >50K 53, Private, 48641, 12th, 8, Never-married, Other-service, Not-in-family, Other, Female, 0, 0, 35, United-States, <=50K 45, Private, 185385, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 341471, HS-grad, 9, Divorced, Priv-house-serv, Not-in-family, White, Female, 0, 0, 4, United-States, <=50K 41, Private, 163322, 11th, 7, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 36, United-States, <=50K 35, Private, 99357, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 1977, 30, United-States, >50K 43, Self-emp-inc, 602513, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 53, Local-gov, 287192, 1st-4th, 2, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 32, Mexico, <=50K 34, Private, 215047, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 46, Federal-gov, 97863, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Husband, White, Male, 5178, 0, 40, United-States, >50K 59, Private, 308118, Assoc-acdm, 12, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 53, Private, 137192, Bachelors, 13, Divorced, Exec-managerial, Unmarried, Asian-Pac-Islander, Male, 0, 0, 50, United-States, <=50K 33, Private, 275369, 7th-8th, 4, Separated, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 35, Haiti, <=50K 45, Private, 99971, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 48, Self-emp-inc, 103713, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Private, 253770, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 55, Private, 162205, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 5178, 0, 72, United-States, >50K 46, Self-emp-not-inc, 31267, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 17, Private, 198146, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 16, United-States, <=50K 23, Private, 178207, Some-college, 10, Never-married, Handlers-cleaners, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 35, United-States, <=50K 21, Private, 317175, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 53, Federal-gov, 221791, HS-grad, 9, Divorced, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 61, Self-emp-inc, 187124, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 20, United-States, >50K 58, State-gov, 280519, HS-grad, 9, Divorced, Other-service, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 36, Private, 207568, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 45, Local-gov, 192684, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 38, United-States, <=50K 39, Private, 103260, Bachelors, 13, Married-civ-spouse, Craft-repair, Wife, White, Female, 0, 0, 30, United-States, >50K 39, Private, 191227, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Female, 13550, 0, 50, United-States, >50K 48, Self-emp-inc, 382242, Doctorate, 16, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 41, Private, 106900, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 38, United-States, <=50K 30, Private, 48520, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 2002, 40, United-States, <=50K 50, Private, 55527, Assoc-acdm, 12, Divorced, Craft-repair, Not-in-family, Black, Male, 0, 0, 45, United-States, <=50K 51, Self-emp-not-inc, 246820, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 48, United-States, >50K 23, Private, 33884, Some-college, 10, Separated, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 29762, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 47, Federal-gov, 168109, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 70, United-States, <=50K 51, Private, 207449, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, <=50K 60, Self-emp-inc, 189098, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 194259, Bachelors, 13, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 20, Local-gov, 194630, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Local-gov, 179681, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Female, 0, 0, 37, United-States, <=50K 42, State-gov, 136996, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 48, United-States, <=50K 32, Private, 143604, HS-grad, 9, Divorced, Other-service, Not-in-family, Black, Female, 0, 0, 16, United-States, <=50K 19, Private, 243373, 12th, 8, Never-married, Sales, Other-relative, White, Male, 1055, 0, 40, United-States, <=50K 34, Private, 261799, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 45, United-States, >50K 48, Private, 143281, HS-grad, 9, Widowed, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 38, Private, 185556, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Italy, <=50K 38, Private, 111499, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 40, Self-emp-not-inc, 280433, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 39, Private, 37314, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 38, Private, 103408, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, ?, <=50K 26, Private, 270151, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, State-gov, 96748, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 10, United-States, <=50K 20, Private, 164775, 5th-6th, 3, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, Guatemala, <=50K 49, Private, 190319, Bachelors, 13, Married-spouse-absent, Adm-clerical, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 40, Philippines, <=50K 23, Private, 213115, HS-grad, 9, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 47, Private, 156926, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, Canada, >50K 43, Private, 112967, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, Private, 35373, Some-college, 10, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 60, Self-emp-not-inc, 220342, 11th, 7, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 35, United-States, <=50K 29, Private, 163167, HS-grad, 9, Divorced, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 404951, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, Black, Female, 0, 0, 38, United-States, <=50K 39, Private, 122032, Assoc-voc, 11, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 143582, Assoc-voc, 11, Never-married, Adm-clerical, Not-in-family, Other, Female, 4101, 0, 35, United-States, <=50K 38, Private, 108140, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 2202, 0, 45, United-States, <=50K 47, Private, 251508, HS-grad, 9, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 36, United-States, <=50K 50, Self-emp-not-inc, 197054, Prof-school, 15, Divorced, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 64, Self-emp-not-inc, 36960, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 165930, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, ?, 178960, 11th, 7, Never-married, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 214503, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 44, United-States, >50K 51, Private, 110458, Bachelors, 13, Separated, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 202125, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 53, Self-emp-not-inc, 284329, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 29, Private, 192924, Assoc-voc, 11, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 340917, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 2829, 0, 50, ?, <=50K 37, Private, 340614, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 20, Private, 196678, 12th, 8, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 266489, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 57, Private, 61474, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 45, United-States, >50K 47, ?, 99127, Assoc-voc, 11, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 215955, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 2829, 0, 40, United-States, <=50K 23, Self-emp-inc, 215395, Assoc-voc, 11, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 36, Self-emp-inc, 183898, Bachelors, 13, Divorced, Sales, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 48, Private, 97176, HS-grad, 9, Divorced, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 145160, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 43, United-States, <=50K 51, Private, 357949, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 16, United-States, <=50K 59, Private, 177120, 9th, 5, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 288229, Some-college, 10, Married-civ-spouse, Sales, Other-relative, Asian-Pac-Islander, Female, 0, 0, 40, Greece, <=50K 39, Private, 509060, Some-college, 10, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 47932, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 103925, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 44, State-gov, 183829, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 51, Private, 138852, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 188186, HS-grad, 9, Never-married, Other-service, Other-relative, White, Female, 0, 0, 20, Hungary, <=50K 22, Private, 34616, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 19, Private, 220819, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Female, 0, 0, 40, United-States, <=50K 31, Federal-gov, 281540, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 45, United-States, <=50K 53, Private, 47396, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 141350, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 19, Private, 331433, HS-grad, 9, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 32, United-States, <=50K 40, Federal-gov, 346532, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, >50K 21, Private, 241367, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 10, United-States, <=50K 39, Private, 216256, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, Italy, >50K 40, Local-gov, 153031, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7298, 0, 35, United-States, >50K 36, Private, 116138, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Cambodia, <=50K 18, Private, 193166, 9th, 5, Never-married, Sales, Own-child, White, Female, 0, 0, 42, United-States, <=50K 32, Self-emp-inc, 275094, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 55, Mexico, >50K 50, Private, 81548, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 167979, 11th, 7, Never-married, Sales, Own-child, White, Male, 0, 0, 15, United-States, <=50K 19, Private, 67759, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 43, United-States, <=50K 53, Private, 200190, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 49, Private, 403112, HS-grad, 9, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 32, United-States, <=50K 40, Private, 214891, Bachelors, 13, Married-spouse-absent, Transport-moving, Own-child, Other, Male, 0, 0, 45, ?, <=50K 31, Private, 142675, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 47, Self-emp-not-inc, 88500, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 35, United-States, <=50K 35, Local-gov, 145308, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Local-gov, 204377, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 43, Self-emp-not-inc, 260696, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 51, Private, 231181, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 21, United-States, <=50K 54, Private, 260052, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 76, Local-gov, 178665, 9th, 5, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 30, United-States, <=50K 33, Private, 226267, 7th-8th, 4, Never-married, Sales, Not-in-family, White, Male, 0, 0, 43, Mexico, <=50K 19, Private, 111232, 12th, 8, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 15, United-States, <=50K 49, Private, 87928, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 5013, 0, 40, United-States, <=50K 26, Private, 212748, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 110677, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 49, Private, 139268, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 40, United-States, >50K 24, Private, 306779, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 48, Private, 318331, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 36, State-gov, 143385, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 288273, 12th, 8, Separated, Adm-clerical, Unmarried, White, Female, 1471, 0, 40, United-States, <=50K 31, Private, 167725, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 15024, 0, 48, Philippines, >50K 53, Private, 94081, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 44, United-States, >50K 22, Private, 194723, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 10, United-States, <=50K 43, Private, 163985, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 189759, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, Italy, <=50K 53, State-gov, 195922, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, Federal-gov, 54159, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 47, Local-gov, 166863, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 52, Private, 104501, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, Germany, >50K 39, Private, 210626, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 448026, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 17, Local-gov, 170916, 10th, 6, Never-married, Protective-serv, Own-child, White, Female, 0, 1602, 40, United-States, <=50K 53, Local-gov, 283602, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 15024, 0, 40, United-States, >50K 21, Private, 189749, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 90934, Bachelors, 13, Never-married, Prof-specialty, Own-child, Asian-Pac-Islander, Male, 0, 0, 64, Philippines, >50K 34, State-gov, 253121, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 181776, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 61, Private, 162397, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Private, 70708, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 60, United-States, <=50K 47, State-gov, 103406, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 224658, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 26, Local-gov, 213451, Some-college, 10, Never-married, Other-service, Own-child, Black, Female, 0, 0, 10, Jamaica, <=50K 53, Private, 139671, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 36201, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 39, Private, 237713, Prof-school, 15, Married-civ-spouse, Sales, Husband, White, Male, 0, 2415, 99, United-States, >50K 17, Local-gov, 173497, 11th, 7, Never-married, Prof-specialty, Own-child, Black, Male, 0, 0, 15, United-States, <=50K 46, Private, 375606, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 34, Private, 203488, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 40, United-States, >50K 45, Self-emp-not-inc, 107231, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, France, <=50K 23, Private, 216811, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 16, United-States, <=50K 41, Private, 288679, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 105516, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Self-emp-not-inc, 282972, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 4, United-States, <=50K 18, Self-emp-inc, 117372, 11th, 7, Never-married, Sales, Own-child, White, Male, 0, 0, 15, United-States, <=50K 38, Private, 112497, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 66, ?, 186032, Assoc-voc, 11, Widowed, ?, Not-in-family, White, Female, 2964, 0, 30, United-States, <=50K 28, Private, 192384, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 49, Private, 43348, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 29, Private, 181822, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 43, Local-gov, 216070, Masters, 14, Married-civ-spouse, Exec-managerial, Wife, Amer-Indian-Eskimo, Female, 0, 0, 50, United-States, >50K 34, State-gov, 112062, Masters, 14, Never-married, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 218551, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 25, Private, 404616, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 169460, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 240081, HS-grad, 9, Never-married, Sales, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 22, Private, 147655, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 90277, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, ?, <=50K 49, Private, 60751, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Self-emp-not-inc, 194636, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 3137, 0, 50, United-States, <=50K 37, Self-emp-not-inc, 154641, Assoc-acdm, 12, Married-civ-spouse, Farming-fishing, Husband, White, Male, 2105, 0, 50, United-States, <=50K 39, Private, 491000, Bachelors, 13, Never-married, Exec-managerial, Other-relative, Black, Male, 0, 0, 45, United-States, <=50K 33, Private, 399088, HS-grad, 9, Divorced, Transport-moving, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 41, Self-emp-not-inc, 186909, Masters, 14, Married-civ-spouse, Sales, Wife, White, Female, 0, 1902, 35, United-States, >50K 65, Private, 105491, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 40, United-States, >50K 40, Private, 34987, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 53, United-States, <=50K 26, ?, 167835, Bachelors, 13, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 20, United-States, <=50K 31, Private, 288983, Some-college, 10, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 266070, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 71, Private, 110380, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 2467, 52, United-States, <=50K 25, Local-gov, 31873, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 294400, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 19, ?, 184308, Some-college, 10, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 30, United-States, <=50K 36, Self-emp-not-inc, 175769, Prof-school, 15, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 56, Private, 182273, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 106541, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 138192, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 196791, Prof-school, 15, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, >50K 22, Private, 223019, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 44, Private, 109273, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 60, Self-emp-not-inc, 95490, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 65, Private, 149131, 11th, 7, Divorced, Machine-op-inspct, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 219155, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, England, >50K 53, Local-gov, 82783, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 214858, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 170230, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 40, Self-emp-inc, 209344, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 15, ?, <=50K 35, Private, 90406, 11th, 7, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, <=50K 41, Self-emp-inc, 299813, 9th, 5, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 70, Dominican-Republic, <=50K 28, Private, 188064, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, Canada, <=50K 53, Private, 246117, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Mexico, <=50K 26, Private, 132749, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 45, United-States, <=50K 28, Local-gov, 201099, HS-grad, 9, Never-married, Transport-moving, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 27, Private, 97490, Some-college, 10, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 221252, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 8, United-States, <=50K 26, Private, 116991, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 53, Private, 161691, HS-grad, 9, Widowed, Sales, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 34, Private, 107793, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Germany, >50K 50, Self-emp-inc, 194514, Masters, 14, Never-married, Prof-specialty, Not-in-family, Black, Male, 0, 0, 50, Trinadad&Tobago, <=50K 30, Private, 278502, HS-grad, 9, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 62, United-States, <=50K 47, Private, 343742, HS-grad, 9, Separated, Craft-repair, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 27, ?, 204074, HS-grad, 9, Never-married, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 55, Federal-gov, 31965, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 143604, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 29, ?, <=50K 35, Private, 174308, Some-college, 10, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 31, Self-emp-not-inc, 162551, 12th, 8, Married-civ-spouse, Sales, Wife, Asian-Pac-Islander, Female, 0, 0, 50, ?, <=50K 39, Self-emp-inc, 372525, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 30, Private, 75167, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, <=50K 39, Private, 176296, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 1887, 40, United-States, >50K 19, Private, 93518, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 25, ?, 126797, HS-grad, 9, Married-spouse-absent, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 57, Self-emp-not-inc, 25124, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 60, United-States, <=50K 21, Private, 112137, Some-college, 10, Never-married, Prof-specialty, Other-relative, Asian-Pac-Islander, Female, 0, 0, 20, South, <=50K 30, ?, 58798, 7th-8th, 4, Widowed, ?, Not-in-family, White, Female, 0, 0, 44, United-States, <=50K 25, Self-emp-not-inc, 21472, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 22, United-States, <=50K 32, Private, 90969, Assoc-voc, 11, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, >50K 26, Private, 149734, HS-grad, 9, Separated, Craft-repair, Unmarried, Black, Female, 0, 1594, 40, United-States, <=50K 42, Private, 52849, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Self-emp-not-inc, 106347, Some-college, 10, Divorced, Sales, Unmarried, White, Male, 0, 0, 47, United-States, <=50K 48, Private, 199735, Bachelors, 13, Divorced, Priv-house-serv, Not-in-family, White, Female, 0, 0, 44, Germany, <=50K 24, Private, 488541, Some-college, 10, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 46, Private, 403911, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, >50K 53, Private, 172991, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 25, United-States, <=50K 36, Federal-gov, 210945, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 70, United-States, <=50K 34, Private, 157446, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 45, United-States, <=50K 25, Private, 109390, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 70, United-States, <=50K 33, Private, 134886, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 99999, 0, 30, United-States, >50K 45, Private, 144579, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Federal-gov, 203488, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 202871, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 20, United-States, <=50K 33, Private, 175412, 9th, 5, Divorced, Craft-repair, Unmarried, White, Male, 114, 0, 55, United-States, <=50K 44, Private, 336906, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 177596, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, Puerto-Rico, >50K 30, Private, 79448, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 10, United-States, <=50K 32, Local-gov, 191731, Some-college, 10, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 46, ?, 233014, HS-grad, 9, Divorced, ?, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 29, Private, 133937, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Private, 219211, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 35, State-gov, 94529, HS-grad, 9, Divorced, Protective-serv, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 247547, HS-grad, 9, Separated, Prof-specialty, Other-relative, Black, Female, 0, 0, 40, United-States, <=50K 29, Private, 29361, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 21, Private, 166851, HS-grad, 9, Never-married, Machine-op-inspct, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 43, Federal-gov, 197069, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, Philippines, >50K 33, Private, 153588, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, Federal-gov, 151369, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 42, Private, 174112, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 520033, 12th, 8, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 35, State-gov, 194828, Some-college, 10, Never-married, Prof-specialty, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 32, ?, 216908, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 24, United-States, <=50K 22, Private, 126613, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 61, Private, 26254, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 54042, Assoc-voc, 11, Never-married, Other-service, Not-in-family, White, Female, 2463, 0, 35, United-States, <=50K 24, Private, 67804, HS-grad, 9, Never-married, Other-service, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 58, Local-gov, 53481, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 42, Private, 412379, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, Private, 220187, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 26, ?, 256141, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 268222, HS-grad, 9, Separated, Handlers-cleaners, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 59, Private, 99131, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 65, Self-emp-not-inc, 115498, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 3818, 0, 10, United-States, <=50K 57, Private, 317847, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 2824, 50, United-States, >50K 36, Private, 98389, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 44, United-States, >50K 42, Private, 173704, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 1887, 50, United-States, >50K 18, ?, 211177, 12th, 8, Never-married, ?, Other-relative, Black, Male, 0, 0, 20, United-States, <=50K 18, Private, 115443, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 65078, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Private, 24896, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 20, United-States, <=50K 19, Private, 184710, Some-college, 10, Never-married, Tech-support, Own-child, White, Male, 0, 0, 30, United-States, <=50K 28, Private, 410450, Bachelors, 13, Divorced, Other-service, Unmarried, White, Female, 0, 0, 48, England, >50K 37, Private, 83893, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 113309, Some-college, 10, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 60, Private, 160625, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 47, United-States, <=50K 17, Local-gov, 340043, 12th, 8, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 12, United-States, <=50K 37, Local-gov, 48976, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 4865, 0, 45, United-States, <=50K 29, State-gov, 243875, Assoc-voc, 11, Divorced, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 554206, HS-grad, 9, Separated, Transport-moving, Not-in-family, Black, Male, 0, 0, 20, United-States, <=50K 36, Private, 361888, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, ?, >50K 37, Self-emp-not-inc, 205359, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 15, United-States, <=50K 47, State-gov, 167281, Bachelors, 13, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 35663, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 61, Private, 357437, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 390856, 5th-6th, 3, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 45, Mexico, <=50K 33, Federal-gov, 331615, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1848, 40, United-States, >50K 54, Private, 202415, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Private, 180032, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 1669, 40, United-States, <=50K 40, Private, 77247, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 40, Local-gov, 101795, HS-grad, 9, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 42, United-States, <=50K 35, Private, 272019, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 2057, 40, United-States, <=50K 32, Private, 198068, 11th, 7, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 49, Self-emp-not-inc, 199326, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 31, Private, 178841, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 58, Private, 136951, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 26, Self-emp-inc, 109240, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 35, Self-emp-not-inc, 128876, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 103358, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, India, <=50K 43, Private, 354408, 12th, 8, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, <=50K 32, Private, 206051, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 45, Private, 155659, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 48, Private, 143299, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 31, Private, 252210, 5th-6th, 3, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, Mexico, <=50K 20, ?, 129240, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 25, United-States, <=50K 28, Private, 398918, HS-grad, 9, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 50, Self-emp-not-inc, 240612, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 22, Private, 429346, HS-grad, 9, Never-married, Adm-clerical, Other-relative, Black, Male, 0, 0, 40, United-States, <=50K 19, Private, 123718, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 38, Private, 455379, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 63, United-States, >50K 23, Private, 376416, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 24, Self-emp-inc, 234663, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 282142, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 45, State-gov, 208049, HS-grad, 9, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 88, Private, 68539, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 126501, 11th, 7, Never-married, Adm-clerical, Own-child, Amer-Indian-Eskimo, Female, 0, 0, 15, South, <=50K 24, Private, 186452, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 84, ?, 127184, 5th-6th, 3, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 20, United-States, <=50K 48, Private, 165267, 10th, 6, Married-civ-spouse, Farming-fishing, Husband, Black, Male, 0, 0, 40, United-States, <=50K 46, Private, 124733, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Vietnam, <=50K 31, Self-emp-inc, 149726, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 58, Private, 41374, HS-grad, 9, Widowed, Adm-clerical, Unmarried, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 35, Local-gov, 329759, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 212433, HS-grad, 9, Never-married, Craft-repair, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 36, Private, 185099, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 47, Local-gov, 126754, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 57, Private, 122497, 9th, 5, Widowed, Other-service, Unmarried, Black, Male, 0, 0, 52, ?, <=50K 30, Private, 118056, Some-college, 10, Married-spouse-absent, Exec-managerial, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 30, Local-gov, 200892, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, ?, 200790, 12th, 8, Married-civ-spouse, ?, Other-relative, White, Female, 15024, 0, 40, United-States, >50K 30, Self-emp-inc, 84119, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 43, United-States, <=50K 23, Local-gov, 197918, Some-college, 10, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 40, United-States, >50K 41, Self-emp-not-inc, 150533, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 52, Private, 443742, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 27, Private, 104423, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 59, Private, 169133, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 21, Private, 185551, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 36, United-States, <=50K 60, Private, 174486, HS-grad, 9, Widowed, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 69, State-gov, 50468, Prof-school, 15, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 34, United-States, >50K 24, Private, 196943, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 120691, HS-grad, 9, Never-married, Sales, Own-child, Black, Male, 0, 0, 25, United-States, <=50K 60, State-gov, 198815, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 20, Mexico, <=50K 64, Private, 22186, Some-college, 10, Widowed, Tech-support, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 39, Self-emp-inc, 188069, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 51, Private, 233149, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 51, Private, 138358, 10th, 6, Divorced, Craft-repair, Not-in-family, Black, Female, 0, 0, 35, United-States, <=50K 25, Private, 338013, Some-college, 10, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 17, ?, 332666, 10th, 6, Never-married, ?, Own-child, White, Female, 0, 0, 4, United-States, <=50K 37, Private, 166339, Some-college, 10, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 74, Self-emp-not-inc, 392886, HS-grad, 9, Widowed, Farming-fishing, Not-in-family, White, Female, 0, 0, 14, United-States, <=50K 26, State-gov, 141838, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, United-States, >50K 23, Private, 520759, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 30, United-States, <=50K 57, Self-emp-inc, 37345, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 36, United-States, >50K 20, Private, 387779, 11th, 7, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 15, United-States, <=50K 37, Private, 201531, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 123598, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 380614, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, >50K 40, Private, 83859, HS-grad, 9, Widowed, Machine-op-inspct, Own-child, White, Female, 0, 0, 30, United-States, <=50K 50, State-gov, 24790, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 266820, Preschool, 1, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 35, Mexico, <=50K 44, Private, 85440, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, <=50K 41, Private, 421837, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Self-emp-not-inc, 404062, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 15, United-States, >50K 38, Private, 224566, Assoc-voc, 11, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 50, United-States, <=50K 54, Private, 294991, 10th, 6, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Federal-gov, 189610, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, Black, Female, 0, 0, 52, United-States, <=50K 37, Private, 219141, 11th, 7, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 7688, 0, 40, United-States, >50K 46, Federal-gov, 20956, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 40, United-States, >50K 38, Private, 70995, HS-grad, 9, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 20, Private, 215232, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 10, United-States, <=50K 71, ?, 178295, Assoc-acdm, 12, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 3, United-States, <=50K 35, Private, 56201, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, Mexico, <=50K 62, Private, 98076, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 34, Private, 351810, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, Cuba, <=50K 56, Self-emp-not-inc, 144351, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 90, United-States, <=50K 30, State-gov, 137613, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 20, Taiwan, <=50K 17, Private, 54257, 11th, 7, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 18, Self-emp-not-inc, 230373, 11th, 7, Never-married, Other-service, Own-child, White, Female, 594, 0, 4, United-States, <=50K 35, Private, 98389, 11th, 7, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 184135, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, Black, Male, 0, 0, 1, United-States, <=50K 46, Self-emp-not-inc, 140121, HS-grad, 9, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 50, United-States, <=50K 33, Self-emp-not-inc, 24504, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 27, Private, 129528, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 415578, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Private, 97142, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 201328, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 25, Private, 256620, Bachelors, 13, Separated, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 47, Federal-gov, 96854, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 44, State-gov, 141858, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 75, United-States, >50K 51, Federal-gov, 20795, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 7688, 0, 40, United-States, >50K 53, Private, 95519, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 42, United-States, >50K 47, Private, 112791, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 291407, 11th, 7, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 32, Private, 239659, Some-college, 10, Separated, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 70, United-States, <=50K 28, Private, 183151, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 58, ?, 97634, 5th-6th, 3, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 143807, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 186934, Masters, 14, Separated, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 30, Private, 170065, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 108328, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 6849, 0, 50, United-States, <=50K 56, State-gov, 83696, Bachelors, 13, Separated, Prof-specialty, Not-in-family, White, Female, 0, 0, 38, ?, <=50K 21, Private, 204596, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 56, ?, 32604, Some-college, 10, Never-married, ?, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 56, Private, 193453, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 65, United-States, >50K 45, Private, 148995, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 15024, 0, 40, United-States, >50K 20, Private, 85041, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 20, United-States, <=50K 62, Local-gov, 140851, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, >50K 24, Private, 196280, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 52, Federal-gov, 38973, Bachelors, 13, Separated, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 23, Private, 39182, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 198841, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Private, 694812, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 247444, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Nicaragua, <=50K 41, Private, 294270, 9th, 5, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 35, United-States, <=50K 59, Private, 195820, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 329426, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 37, United-States, <=50K 19, ?, 174871, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 23, United-States, <=50K 41, Private, 116103, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 27, Private, 206903, Bachelors, 13, Never-married, Handlers-cleaners, Unmarried, White, Male, 0, 0, 35, United-States, <=50K 50, Private, 217577, HS-grad, 9, Widowed, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 337693, 5th-6th, 3, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, El-Salvador, <=50K 38, Private, 204501, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 30, Private, 169186, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 60, United-States, <=50K 48, Private, 109421, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, <=50K 39, Local-gov, 267893, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, Black, Male, 7298, 0, 40, United-States, >50K 40, Private, 200479, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Local-gov, 221317, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Mexico, <=50K 59, Self-emp-not-inc, 132925, Masters, 14, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 31, ?, 283531, HS-grad, 9, Divorced, ?, Unmarried, Black, Female, 0, 0, 20, United-States, <=50K 34, Private, 170769, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, >50K 47, Self-emp-inc, 186410, Prof-school, 15, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 64, Self-emp-inc, 307786, 1st-4th, 2, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 20, United-States, <=50K 29, Private, 380560, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 38, Local-gov, 147258, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 212894, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 1887, 40, United-States, >50K 49, Private, 124356, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 53, Private, 98791, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 216473, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, >50K 70, ?, 135339, Bachelors, 13, Married-civ-spouse, ?, Husband, Asian-Pac-Islander, Male, 0, 0, 40, China, <=50K 38, Private, 107303, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 152744, Bachelors, 13, Divorced, Sales, Other-relative, Asian-Pac-Islander, Female, 0, 0, 40, South, <=50K 34, Self-emp-not-inc, 100079, Bachelors, 13, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 0, 55, India, <=50K 24, Private, 117779, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 10, Hungary, <=50K 23, Private, 197613, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 411068, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 35, United-States, <=50K 47, Private, 192984, Some-college, 10, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 59, Private, 66356, 7th-8th, 4, Never-married, Farming-fishing, Unmarried, White, Male, 4865, 0, 40, United-States, <=50K 33, Federal-gov, 137184, Assoc-acdm, 12, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 50, United-States, >50K 63, Self-emp-not-inc, 231105, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 35, United-States, >50K 18, Local-gov, 146586, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 60, United-States, <=50K 32, Private, 32406, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 33, Private, 578701, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, ?, <=50K 19, Private, 206777, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 27, Local-gov, 133495, HS-grad, 9, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 34722, Some-college, 10, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 48, United-States, >50K 38, Self-emp-not-inc, 133299, Assoc-acdm, 12, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 24967, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 47, United-States, <=50K 35, Self-emp-not-inc, 171968, HS-grad, 9, Separated, Transport-moving, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 22, Private, 412156, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 51290, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 34, Private, 198265, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 3103, 0, 40, United-States, >50K 23, Private, 293565, 10th, 6, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 226288, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 53, Self-emp-inc, 110445, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 34, Private, 160634, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 174242, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 390316, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Mexico, <=50K 18, Private, 298860, 11th, 7, Never-married, Sales, Own-child, White, Male, 0, 0, 20, United-States, <=50K 65, Private, 171584, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 49, Self-emp-not-inc, 232664, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 64, Private, 63676, 10th, 6, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 40, United-States, <=50K 68, Private, 170376, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 56, Self-emp-not-inc, 175964, Some-college, 10, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 68, Federal-gov, 422013, HS-grad, 9, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 3683, 40, United-States, <=50K 35, Private, 105813, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 48, United-States, >50K 50, Federal-gov, 306707, HS-grad, 9, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 12, United-States, <=50K 45, Private, 177543, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 28, United-States, <=50K 43, Private, 320277, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 129495, Some-college, 10, Separated, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 37, Private, 257042, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 1506, 0, 40, United-States, <=50K 45, Private, 275995, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 50, United-States, >50K 20, ?, 86318, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 10, United-States, <=50K 36, Private, 280440, Assoc-acdm, 12, Never-married, Tech-support, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 26, Private, 371556, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 408229, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 47, Private, 149337, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 34, Private, 209297, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, Black, Male, 0, 2001, 40, United-States, <=50K 53, Private, 355802, Some-college, 10, Widowed, Sales, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 32, Private, 165949, Bachelors, 13, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 1590, 42, United-States, <=50K 44, Self-emp-not-inc, 112507, 5th-6th, 3, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 462869, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 35, Private, 413648, 5th-6th, 3, Never-married, Farming-fishing, Unmarried, White, Male, 0, 0, 36, United-States, <=50K 34, Private, 29235, Assoc-acdm, 12, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 149823, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 39530, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 4, United-States, <=50K 23, Private, 197387, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 37, Mexico, <=50K 56, Local-gov, 255406, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 50, Private, 43764, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 50, United-States, >50K 38, Private, 168322, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 46, Private, 278322, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 47, Private, 115813, Assoc-acdm, 12, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 57, United-States, <=50K 38, Self-emp-not-inc, 184456, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 3464, 0, 80, Italy, <=50K 42, Private, 289636, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 46, United-States, <=50K 48, Private, 101684, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 133425, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 40, Private, 349405, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 36, United-States, <=50K 53, Private, 124076, Doctorate, 16, Married-civ-spouse, Prof-specialty, Wife, White, Female, 99999, 0, 37, United-States, >50K 75, Self-emp-not-inc, 165968, Assoc-voc, 11, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 39, Private, 185099, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 48, United-States, >50K 46, Federal-gov, 268281, Assoc-acdm, 12, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 154949, HS-grad, 9, Widowed, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 34, Private, 176711, HS-grad, 9, Divorced, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 165064, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 213750, Assoc-voc, 11, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 45, Self-emp-not-inc, 77132, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 21, Private, 109667, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 162164, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 44, United-States, <=50K 40, Private, 219591, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 20, ?, 327462, 10th, 6, Divorced, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 68, Private, 236943, 9th, 5, Divorced, Farming-fishing, Not-in-family, Black, Male, 0, 0, 20, United-States, <=50K 40, Private, 89226, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Private, 124751, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 24, United-States, <=50K 48, Local-gov, 144122, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 27, Private, 98769, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 57, Federal-gov, 170066, Assoc-voc, 11, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 54, Self-emp-inc, 162439, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 98, United-States, >50K 47, Private, 22900, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Local-gov, 102130, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 17, ?, 215743, 11th, 7, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 381583, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Other, Male, 0, 0, 45, United-States, >50K 56, Local-gov, 198277, 12th, 8, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 243178, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 28, United-States, <=50K 38, Local-gov, 177305, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 38, United-States, <=50K 19, Private, 167149, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 25, United-States, <=50K 24, Private, 270872, HS-grad, 9, Never-married, Craft-repair, Other-relative, White, Male, 594, 0, 40, ?, <=50K 31, Private, 382368, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, Germany, <=50K 44, Local-gov, 277144, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 60, United-States, <=50K 21, State-gov, 145651, Some-college, 10, Never-married, Sales, Own-child, Black, Female, 0, 1602, 12, United-States, <=50K 41, Private, 171351, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 265099, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 16, United-States, <=50K 23, Private, 105617, 9th, 5, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 37, Local-gov, 217689, Some-college, 10, Married-civ-spouse, Other-service, Husband, Amer-Indian-Eskimo, Male, 0, 0, 32, United-States, <=50K 46, ?, 81136, Assoc-voc, 11, Divorced, ?, Unmarried, White, Male, 0, 0, 30, United-States, <=50K 43, Self-emp-not-inc, 73883, Bachelors, 13, Divorced, Sales, Unmarried, White, Male, 0, 0, 45, United-States, <=50K 31, Private, 339482, 1st-4th, 2, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 40, Private, 326232, Some-college, 10, Divorced, Transport-moving, Unmarried, White, Male, 0, 0, 40, United-States, >50K 27, Private, 106316, Prof-school, 15, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 12, United-States, <=50K 64, Local-gov, 198728, Some-college, 10, Never-married, Transport-moving, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 31, Federal-gov, 126501, Assoc-voc, 11, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 233802, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 45, United-States, <=50K 37, Self-emp-not-inc, 204501, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 20, Canada, >50K 28, Private, 208249, Some-college, 10, Divorced, Tech-support, Not-in-family, White, Male, 0, 0, 24, United-States, <=50K 42, Private, 188693, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 60, Self-emp-inc, 93272, 7th-8th, 4, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 17, Private, 159299, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 21, ?, 303588, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 30, United-States, <=50K 46, Private, 35136, 10th, 6, Divorced, Adm-clerical, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 18, Private, 139576, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 252355, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 27, United-States, <=50K 44, Self-emp-not-inc, 83812, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 36, Private, 89718, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 65, Private, 222810, Assoc-voc, 11, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 456618, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 21, Private, 296158, 10th, 6, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 25, United-States, <=50K 41, Private, 162140, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 2339, 40, United-States, <=50K 28, Private, 36601, Some-college, 10, Never-married, Other-service, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 27, Private, 195337, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 19, State-gov, 282721, Some-college, 10, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 12, United-States, <=50K 40, Private, 206049, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 223392, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 15, United-States, <=50K 40, Private, 27821, Assoc-voc, 11, Married-civ-spouse, Transport-moving, Husband, White, Male, 2829, 0, 40, United-States, <=50K 37, Private, 131827, HS-grad, 9, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 549413, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, >50K 34, Private, 69491, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Local-gov, 193755, Assoc-acdm, 12, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 598802, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 72, Local-gov, 259762, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 2290, 0, 10, United-States, <=50K 19, Private, 266255, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 59, Private, 32954, Assoc-voc, 11, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 36, United-States, <=50K 40, Private, 291808, HS-grad, 9, Divorced, Protective-serv, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 35, Private, 190728, HS-grad, 9, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 59184, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 41, Private, 196456, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 59, Private, 147989, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 50, United-States, >50K 50, Private, 195784, 12th, 8, Divorced, Handlers-cleaners, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 202214, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 10, United-States, <=50K 40, Self-emp-inc, 225165, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 54825, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 188905, 5th-6th, 3, Separated, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, Mexico, <=50K 17, Private, 132636, 11th, 7, Never-married, Transport-moving, Own-child, White, Female, 0, 0, 16, United-States, <=50K 42, Local-gov, 228320, 7th-8th, 4, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 415500, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, >50K 19, Private, 254247, 12th, 8, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 38, ?, <=50K 43, Private, 255635, 5th-6th, 3, Married-civ-spouse, Machine-op-inspct, Husband, Other, Male, 0, 0, 40, Mexico, <=50K 46, Private, 96080, 9th, 5, Separated, Craft-repair, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 18, ?, 78181, HS-grad, 9, Never-married, ?, Own-child, White, Female, 0, 0, 20, United-States, <=50K 50, Local-gov, 339547, Prof-school, 15, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Laos, >50K 47, Self-emp-not-inc, 126500, 7th-8th, 4, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, Puerto-Rico, <=50K 31, Private, 511289, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 2907, 0, 99, United-States, <=50K 33, Private, 159574, 7th-8th, 4, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, <=50K 27, Private, 224105, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 7298, 0, 40, United-States, >50K 59, Self-emp-not-inc, 128105, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 35, United-States, <=50K 39, Local-gov, 89508, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Private, 370242, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 67257, Bachelors, 13, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 24, Private, 62952, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 111058, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 1980, 40, United-States, <=50K 30, Private, 29235, Some-college, 10, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 20, United-States, <=50K 52, State-gov, 101119, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Federal-gov, 140516, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Private, 159888, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 19, ?, 45643, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 25, United-States, <=50K 23, Private, 166371, Some-college, 10, Never-married, Tech-support, Own-child, White, Male, 0, 0, 60, United-States, <=50K 37, State-gov, 160910, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, <=50K 25, State-gov, 257064, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 38, United-States, <=50K 49, Self-emp-not-inc, 181307, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 65, United-States, >50K 30, Private, 83253, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, <=50K 40, Private, 128700, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 243010, HS-grad, 9, Never-married, Machine-op-inspct, Other-relative, Other, Male, 0, 0, 32, United-States, <=50K 35, Self-emp-not-inc, 37778, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 3103, 0, 55, United-States, <=50K 24, Private, 132320, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 45, United-States, <=50K 32, Private, 234755, HS-grad, 9, Separated, Craft-repair, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 35, Private, 142616, HS-grad, 9, Separated, Other-service, Own-child, Black, Female, 0, 0, 30, United-States, <=50K 20, Private, 148509, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, State-gov, 240738, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Private, 32276, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 28, United-States, <=50K 50, Local-gov, 163921, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 464103, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 49, ?, 271346, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 15024, 0, 60, United-States, >50K 30, Local-gov, 327825, HS-grad, 9, Divorced, Protective-serv, Own-child, White, Female, 0, 0, 32, United-States, <=50K 37, Private, 267085, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 266945, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 3137, 0, 40, El-Salvador, <=50K 20, Private, 234663, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 30, United-States, <=50K 49, Self-emp-not-inc, 189123, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 5013, 0, 50, United-States, <=50K 55, Private, 104996, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 61, Private, 101265, 12th, 8, Widowed, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, Italy, <=50K 22, Private, 184975, HS-grad, 9, Married-spouse-absent, Other-service, Own-child, White, Female, 0, 0, 3, United-States, <=50K 23, Private, 246965, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 12, United-States, <=50K 43, Private, 227065, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Male, 4650, 0, 40, United-States, <=50K 39, Private, 301867, Bachelors, 13, Divorced, Adm-clerical, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 24, Philippines, <=50K 21, Private, 185948, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 35, United-States, <=50K 52, Self-emp-inc, 134854, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Private, 281030, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 4064, 0, 40, United-States, <=50K 42, Private, 126701, Bachelors, 13, Divorced, Adm-clerical, Unmarried, White, Male, 9562, 0, 45, United-States, >50K 50, Self-emp-not-inc, 95949, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 51, Self-emp-not-inc, 88528, Assoc-acdm, 12, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 99, United-States, <=50K 47, Private, 24723, 10th, 6, Divorced, Exec-managerial, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 45, United-States, <=50K 49, ?, 171411, 9th, 5, Divorced, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 184581, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Federal-gov, 100067, Some-college, 10, Widowed, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 36, Private, 182863, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 20, Never-worked, 462294, Some-college, 10, Never-married, ?, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 61, Private, 85434, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 72, Private, 158092, Bachelors, 13, Divorced, Sales, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 19, Private, 104844, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 15, United-States, <=50K 54, Self-emp-inc, 304570, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, Asian-Pac-Islander, Male, 7688, 0, 40, ?, >50K 47, ?, 89806, Some-college, 10, Divorced, ?, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 35, United-States, <=50K 39, Private, 106183, HS-grad, 9, Divorced, Other-service, Unmarried, Amer-Indian-Eskimo, Female, 6849, 0, 40, United-States, <=50K 24, Private, 89347, 11th, 7, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 157236, Some-college, 10, Married-spouse-absent, Handlers-cleaners, Unmarried, White, Male, 0, 0, 40, Poland, <=50K 19, Private, 261259, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, United-States, <=50K 20, Private, 286166, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 23, Private, 122272, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Female, 0, 0, 40, United-States, <=50K 58, Private, 248739, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 53, United-States, >50K 20, Private, 224238, 12th, 8, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 62, Private, 138157, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 12, United-States, <=50K 25, Private, 148460, HS-grad, 9, Never-married, Adm-clerical, Own-child, Black, Female, 4416, 0, 40, Puerto-Rico, <=50K 67, Private, 236627, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 2, United-States, <=50K 37, Local-gov, 191364, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, France, >50K 36, Private, 353524, HS-grad, 9, Divorced, Exec-managerial, Own-child, White, Female, 1831, 0, 40, United-States, <=50K 38, Private, 391040, Assoc-voc, 11, Separated, Tech-support, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 23, Private, 134997, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 80, United-States, <=50K 28, Private, 392487, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 216724, HS-grad, 9, Divorced, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 41, Self-emp-not-inc, 174395, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 55, United-States, >50K 63, Private, 383058, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 1848, 40, United-States, >50K 60, Self-emp-not-inc, 96073, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 30, United-States, <=50K 31, Self-emp-inc, 103435, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 29, Self-emp-not-inc, 96718, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 37, United-States, <=50K 37, Private, 178948, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 7688, 0, 45, United-States, >50K 51, Private, 173987, 9th, 5, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 34419, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 40, United-States, >50K 27, Private, 224849, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 249857, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 34, Private, 340458, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 66, Self-emp-not-inc, 427422, Doctorate, 16, Married-civ-spouse, Sales, Husband, White, Male, 0, 2377, 25, United-States, >50K 19, ?, 440417, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 15, United-States, <=50K 36, Private, 175643, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 35, Private, 297485, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 232954, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 29, Private, 326330, Some-college, 10, Divorced, Exec-managerial, Own-child, White, Female, 1831, 0, 40, United-States, <=50K 25, Private, 109419, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 127768, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 32, United-States, >50K 41, Private, 252986, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, >50K 20, Private, 380544, Assoc-acdm, 12, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 20, United-States, <=50K 52, Private, 306108, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 232855, Some-college, 10, Separated, Other-service, Unmarried, Black, Female, 0, 0, 37, United-States, <=50K 44, Private, 130126, Prof-school, 15, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 50, Private, 194231, Masters, 14, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 49, Self-emp-inc, 197038, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 36, ?, 168223, Bachelors, 13, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 71, State-gov, 26109, Prof-school, 15, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 28, United-States, <=50K 20, Private, 285671, HS-grad, 9, Never-married, Other-service, Other-relative, Black, Male, 0, 0, 25, United-States, <=50K 20, Private, 153583, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, ?, <=50K 59, Self-emp-inc, 103948, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 41, Private, 439919, 5th-6th, 3, Married-civ-spouse, Farming-fishing, Husband, White, Male, 3411, 0, 40, Mexico, <=50K 38, Private, 40319, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 42, United-States, <=50K 55, Local-gov, 159028, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 98675, 9th, 5, Never-married, Other-service, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 45, Private, 90758, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 43, Self-emp-not-inc, 75435, HS-grad, 9, Divorced, Craft-repair, Unmarried, Amer-Indian-Eskimo, Male, 0, 0, 30, United-States, <=50K 19, Private, 219189, 12th, 8, Never-married, Other-service, Own-child, White, Male, 0, 0, 25, United-States, <=50K 33, Private, 203463, HS-grad, 9, Divorced, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 63, Private, 187635, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Self-emp-not-inc, 154641, HS-grad, 9, Divorced, Farming-fishing, Not-in-family, White, Male, 8614, 0, 50, United-States, >50K 34, Private, 27153, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 150324, Assoc-acdm, 12, Never-married, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 83704, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 176262, Assoc-voc, 11, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 36, United-States, <=50K 20, Private, 179423, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 8, United-States, <=50K 45, Private, 168038, Bachelors, 13, Divorced, Sales, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 59, Private, 108765, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 58, Private, 146477, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 40, Greece, >50K 66, Local-gov, 188220, HS-grad, 9, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 35, United-States, >50K 37, Private, 292855, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 1887, 35, United-States, >50K 29, Private, 114870, Some-college, 10, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 32, State-gov, 77723, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 39, Private, 284166, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 50, United-States, >50K 57, Private, 133902, HS-grad, 9, Widowed, Exec-managerial, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 57, Private, 191318, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 50, Self-emp-inc, 67794, HS-grad, 9, Married-spouse-absent, Sales, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 44, Self-emp-inc, 357679, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 15024, 0, 65, United-States, >50K 56, Private, 117872, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, >50K 26, Private, 55929, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 22, ?, 165065, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, Italy, <=50K 26, Self-emp-not-inc, 34307, Assoc-voc, 11, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 65, United-States, <=50K 33, Private, 246038, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Self-emp-not-inc, 147258, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, >50K 45, Private, 329144, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 56, Local-gov, 52953, Doctorate, 16, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 1669, 38, United-States, <=50K 23, Private, 216181, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 36, Iran, <=50K 23, Private, 391171, Some-college, 10, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 25, United-States, <=50K 35, Local-gov, 223242, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 103925, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 7688, 0, 32, United-States, >50K 45, Private, 38240, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 148444, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 25, United-States, <=50K 56, State-gov, 110257, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Federal-gov, 101345, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 268098, 12th, 8, Never-married, Transport-moving, Not-in-family, Black, Male, 0, 0, 36, United-States, <=50K 21, ?, 369084, Some-college, 10, Never-married, ?, Other-relative, White, Male, 0, 0, 10, United-States, <=50K 31, Private, 288825, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 5013, 0, 40, United-States, <=50K 20, Private, 162688, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 38, United-States, <=50K 17, ?, 48751, 11th, 7, Never-married, ?, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 44, Federal-gov, 184099, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 19, Private, 307496, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 23, United-States, <=50K 71, ?, 176986, HS-grad, 9, Widowed, ?, Unmarried, White, Male, 0, 0, 24, United-States, <=50K 23, Private, 267955, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 283969, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, Mexico, <=50K 29, State-gov, 204516, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 15, United-States, <=50K 33, Private, 167771, Some-college, 10, Separated, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 46, Private, 345073, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 48, United-States, >50K 21, ?, 380219, Some-college, 10, Never-married, ?, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 36, Self-emp-inc, 306156, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 60, United-States, >50K 70, Self-emp-not-inc, 37203, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 9386, 0, 30, United-States, >50K 19, Private, 185097, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 37, United-States, <=50K 29, Private, 144808, Some-college, 10, Married-civ-spouse, Exec-managerial, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 34, Private, 187203, Assoc-acdm, 12, Never-married, Sales, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 26, Private, 125089, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 289458, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 144798, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 24, ?, 172152, Bachelors, 13, Never-married, ?, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 25, Taiwan, <=50K 28, Private, 207513, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 48, United-States, <=50K 24, ?, 164574, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 76, Private, 199949, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 20051, 0, 50, United-States, >50K 19, Private, 213024, 12th, 8, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 213140, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 2829, 0, 40, United-States, <=50K 24, Self-emp-not-inc, 83374, Some-college, 10, Never-married, Prof-specialty, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 30, United-States, >50K 37, Private, 192939, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 24, Private, 424494, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 30, United-States, <=50K 24, Private, 215243, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 42, United-States, <=50K 40, Private, 30682, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, >50K 20, Private, 306639, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, United-States, <=50K 23, Local-gov, 218678, 11th, 7, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 219130, Some-college, 10, Never-married, Other-service, Not-in-family, Other, Female, 0, 0, 40, United-States, <=50K 64, Private, 180624, Assoc-acdm, 12, Never-married, Prof-specialty, Other-relative, White, Female, 0, 0, 30, United-States, <=50K 53, Local-gov, 200190, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 55, United-States, >50K 28, Private, 194472, Some-college, 10, Married-civ-spouse, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 52, Local-gov, 205767, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 40, United-States, >50K 28, Private, 249870, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, Black, Male, 0, 0, 50, United-States, <=50K 31, Private, 211242, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 77, Private, 149912, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 10, United-States, <=50K 22, Private, 85389, HS-grad, 9, Never-married, Tech-support, Own-child, White, Male, 0, 0, 40, United-States, <=50K 17, ?, 806316, 11th, 7, Never-married, ?, Own-child, White, Female, 0, 0, 20, United-States, <=50K 38, Private, 329980, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 45, ?, 236612, 11th, 7, Divorced, ?, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 25, Local-gov, 249214, Some-college, 10, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 50, Private, 257126, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 53, Local-gov, 204397, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 24, Private, 291979, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 138667, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, >50K 57, Federal-gov, 42298, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 15024, 0, 40, United-States, >50K 39, Private, 375452, Prof-school, 15, Married-civ-spouse, Exec-managerial, Wife, White, Female, 15024, 0, 48, United-States, >50K 30, Private, 94413, Some-college, 10, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 31, Federal-gov, 166626, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 39, State-gov, 326566, Some-college, 10, Never-married, Transport-moving, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 30, Private, 165503, Bachelors, 13, Never-married, Sales, Own-child, White, Female, 0, 0, 65, United-States, <=50K 48, Private, 102597, Some-college, 10, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 44, United-States, <=50K 62, ?, 113234, Masters, 14, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 177277, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, >50K 34, Private, 198103, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 1980, 40, United-States, <=50K 45, Private, 260490, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 32, Private, 237478, 11th, 7, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 40, Federal-gov, 36885, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 17, Private, 166242, 10th, 6, Never-married, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 19, ?, 158603, 10th, 6, Never-married, ?, Own-child, Black, Male, 0, 0, 25, United-States, <=50K 25, Private, 274228, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 84, United-States, <=50K 42, Private, 185145, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 57, United-States, <=50K 66, Private, 28367, Bachelors, 13, Married-civ-spouse, Priv-house-serv, Other-relative, White, Male, 0, 0, 99, United-States, <=50K 63, Self-emp-not-inc, 28612, HS-grad, 9, Widowed, Sales, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 43, Private, 191429, 7th-8th, 4, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 25, United-States, <=50K 26, Private, 459548, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 20, Mexico, <=50K 23, Private, 65481, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, United-States, >50K 39, Private, 186130, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 47, Self-emp-inc, 350759, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 359678, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 48, United-States, <=50K 35, Private, 220595, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 29599, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, State-gov, 299153, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 15, United-States, <=50K 46, Private, 75256, HS-grad, 9, Married-civ-spouse, Priv-house-serv, Wife, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 143583, 10th, 6, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, United-States, <=50K 31, State-gov, 207505, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 70, United-States, >50K 41, Private, 308550, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 60, United-States, <=50K 50, Private, 145717, HS-grad, 9, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 36, Private, 334366, 11th, 7, Separated, Exec-managerial, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 31, ?, 76198, HS-grad, 9, Separated, ?, Own-child, White, Female, 0, 0, 20, United-States, <=50K 45, Self-emp-not-inc, 155489, 7th-8th, 4, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 65, United-States, >50K 50, Private, 197322, 11th, 7, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 52, Private, 194259, 7th-8th, 4, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 50, United-States, <=50K 40, Private, 346189, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 55, Private, 98361, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 55, United-States, >50K 64, ?, 178556, 10th, 6, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 56, United-States, >50K 51, Self-emp-inc, 162943, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Private, 19302, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 40, United-States, >50K 56, State-gov, 67662, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 39, United-States, <=50K 35, Private, 126675, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 48, United-States, <=50K 55, Self-emp-not-inc, 278228, 10th, 6, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 35, United-States, <=50K 30, Private, 169152, HS-grad, 9, Never-married, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 204052, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 215392, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 43, Self-emp-inc, 83348, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 24, Local-gov, 196816, Some-college, 10, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 30, Private, 541343, 10th, 6, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 40, United-States, <=50K 33, Local-gov, 55921, Assoc-voc, 11, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 32, Private, 251701, Assoc-acdm, 12, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, ?, <=50K 29, Federal-gov, 119848, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 50, Private, 160572, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 3137, 0, 47, United-States, <=50K 18, Private, 25837, 11th, 7, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 15, United-States, <=50K 20, Private, 236592, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 25, United-States, <=50K 45, State-gov, 199326, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 22, Private, 341610, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 35, ?, <=50K 45, Private, 175958, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Private, 198965, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Local-gov, 193537, 7th-8th, 4, Married-spouse-absent, Other-service, Not-in-family, White, Female, 0, 0, 35, Puerto-Rico, <=50K 24, Private, 438839, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 298227, HS-grad, 9, Never-married, Handlers-cleaners, Unmarried, White, Male, 0, 0, 35, United-States, <=50K 28, Private, 271466, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 23, Private, 335570, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 35, United-States, <=50K 21, Private, 206891, 7th-8th, 4, Never-married, Farming-fishing, Own-child, White, Female, 0, 0, 38, United-States, <=50K 23, Private, 162551, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 20, United-States, <=50K 45, Private, 145637, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 48, United-States, <=50K 41, Private, 101290, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 49, Federal-gov, 229376, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 439592, Some-college, 10, Never-married, Other-service, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 37, Private, 161141, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 70, Private, 304570, Bachelors, 13, Widowed, Machine-op-inspct, Other-relative, Asian-Pac-Islander, Male, 0, 0, 32, Philippines, <=50K 24, Private, 103277, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 2597, 0, 40, United-States, <=50K 28, Local-gov, 407672, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 73928, Assoc-voc, 11, Never-married, Adm-clerical, Own-child, Asian-Pac-Islander, Female, 0, 0, 20, United-States, <=50K 83, Self-emp-inc, 240150, 10th, 6, Married-civ-spouse, Farming-fishing, Husband, White, Male, 20051, 0, 50, United-States, >50K 69, Private, 230417, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, China, >50K 37, Private, 260093, HS-grad, 9, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 28, Private, 96020, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 54, Private, 104421, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 71, Private, 152307, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 2377, 45, United-States, >50K 56, State-gov, 93415, HS-grad, 9, Widowed, Adm-clerical, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 27, Local-gov, 282664, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Other, Female, 0, 0, 45, ?, <=50K 42, Self-emp-not-inc, 269733, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 99999, 0, 80, United-States, >50K 21, Private, 202871, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 44, United-States, <=50K 29, Private, 169683, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 271603, 7th-8th, 4, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 24, ?, <=50K 32, Private, 340917, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 31, Private, 329874, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 43770, Some-college, 10, Separated, Other-service, Not-in-family, White, Female, 4650, 0, 72, United-States, <=50K 55, State-gov, 120781, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, India, >50K 48, Private, 138069, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 58, Self-emp-not-inc, 33309, HS-grad, 9, Widowed, Farming-fishing, Not-in-family, White, Male, 0, 0, 80, United-States, <=50K 23, Private, 76432, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, State-gov, 277635, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 49, Local-gov, 123088, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 46, United-States, <=50K 51, Private, 57698, HS-grad, 9, Married-spouse-absent, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 181820, HS-grad, 9, Separated, Craft-repair, Own-child, White, Male, 0, 0, 53, United-States, <=50K 40, Self-emp-not-inc, 98985, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, Black, Male, 0, 0, 50, United-States, <=50K 59, Private, 98350, HS-grad, 9, Divorced, Other-service, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, China, <=50K 47, Private, 125120, Bachelors, 13, Divorced, Craft-repair, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 37, Private, 243409, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 39, Private, 58972, Assoc-acdm, 12, Divorced, Exec-managerial, Unmarried, White, Male, 1506, 0, 40, United-States, <=50K 43, Private, 62857, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 40, Private, 283174, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 48, Private, 107373, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Private, 201155, 9th, 5, Never-married, Sales, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 48, Private, 187505, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 37, Private, 61778, Bachelors, 13, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 19, Private, 223648, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 4101, 0, 48, United-States, <=50K 28, Private, 149652, 10th, 6, Never-married, Other-service, Own-child, Black, Female, 0, 0, 30, United-States, <=50K 56, Private, 170324, 5th-6th, 3, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, Trinadad&Tobago, <=50K 45, Private, 165937, HS-grad, 9, Divorced, Transport-moving, Own-child, White, Male, 0, 0, 60, United-States, <=50K 60, State-gov, 114060, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 53, State-gov, 58913, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 42, United-States, >50K 37, State-gov, 378916, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 241885, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 224421, Assoc-voc, 11, Married-AF-spouse, Farming-fishing, Husband, White, Male, 0, 0, 44, United-States, >50K 31, ?, 213771, HS-grad, 9, Widowed, ?, Unmarried, White, Female, 0, 0, 36, United-States, <=50K 39, Private, 315565, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, Cuba, <=50K 31, Local-gov, 153005, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Private, 98211, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 45, United-States, >50K 17, Private, 198606, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 16, United-States, <=50K 19, Private, 260333, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 24, Private, 219510, Bachelors, 13, Never-married, Other-service, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 32, United-States, <=50K 62, Private, 266624, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 6418, 0, 40, United-States, >50K 34, Private, 136862, 1st-4th, 2, Never-married, Other-service, Other-relative, White, Female, 0, 0, 40, Guatemala, <=50K 47, Self-emp-inc, 215620, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 55, United-States, >50K 58, Private, 187067, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 62, Canada, <=50K 23, Private, 325921, Assoc-voc, 11, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 36, United-States, <=50K 33, Private, 268127, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 76, Private, 142535, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Male, 0, 0, 6, United-States, <=50K 40, Private, 177083, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 28, Private, 77009, 7th-8th, 4, Divorced, Other-service, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 41, Private, 306405, Some-college, 10, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 40, United-States, <=50K 46, Local-gov, 303918, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 7688, 0, 96, United-States, >50K 22, Federal-gov, 262819, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 49087, Assoc-voc, 11, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 53833, HS-grad, 9, Never-married, Other-service, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 1033222, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 8614, 0, 40, United-States, >50K 22, Private, 81145, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 41, Private, 215479, Some-college, 10, Never-married, Transport-moving, Not-in-family, Black, Male, 0, 0, 43, United-States, <=50K 29, Private, 113464, HS-grad, 9, Never-married, Transport-moving, Other-relative, Other, Male, 0, 0, 40, Dominican-Republic, <=50K 60, Private, 109530, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 7298, 0, 40, United-States, >50K 72, Federal-gov, 217864, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Self-emp-inc, 117721, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 65, United-States, <=50K 19, Private, 199484, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 25, Private, 248851, Bachelors, 13, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 116968, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 59, Private, 366618, 9th, 5, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 30, United-States, <=50K 17, Private, 240143, 11th, 7, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 30, United-States, <=50K 59, ?, 424468, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, >50K 69, ?, 320280, Some-college, 10, Never-married, ?, Not-in-family, White, Male, 1848, 0, 1, United-States, <=50K 25, Private, 120238, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 2885, 0, 43, United-States, <=50K 50, ?, 194186, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 60, United-States, <=50K 29, Private, 247053, HS-grad, 9, Separated, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 180599, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, <=50K 29, Local-gov, 190330, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 10, United-States, <=50K 29, State-gov, 199450, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 32, Local-gov, 199539, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 17, ?, 94366, 10th, 6, Never-married, ?, Other-relative, White, Male, 0, 0, 6, United-States, <=50K 50, Self-emp-not-inc, 29231, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 43, Private, 33126, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 41, Private, 102085, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 212064, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 54, State-gov, 166774, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, >50K 65, Private, 95303, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 18, ?, 379768, HS-grad, 9, Never-married, ?, Own-child, Other, Female, 0, 0, 40, United-States, <=50K 70, Self-emp-inc, 247383, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 53, Private, 229465, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 37, Private, 135436, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 60, United-States, >50K 21, Private, 180052, Some-college, 10, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 30, United-States, <=50K 20, Private, 214387, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 47, State-gov, 149337, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Male, 0, 0, 38, United-States, <=50K 26, Private, 208326, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 3942, 0, 45, United-States, <=50K 31, Private, 34374, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 45, Self-emp-not-inc, 58683, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 403037, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 55, Private, 32365, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 49, Private, 155489, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 33, Self-emp-inc, 289886, HS-grad, 9, Never-married, Other-service, Unmarried, Asian-Pac-Islander, Male, 0, 0, 40, Vietnam, <=50K 30, Federal-gov, 54684, Prof-school, 15, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 55, ?, <=50K 19, Private, 101549, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 15, United-States, <=50K 48, Self-emp-inc, 51579, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 41, Private, 40151, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 29, Private, 244721, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 35, United-States, >50K 47, Local-gov, 228372, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 48, United-States, >50K 53, Local-gov, 236873, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, United-States, >50K 19, Private, 250249, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 10, United-States, <=50K 71, Private, 93202, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 16, United-States, <=50K 29, Private, 176723, Some-college, 10, Never-married, Sales, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 43, Local-gov, 175526, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 91842, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 52, Private, 71768, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 56, Private, 181220, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 204516, 10th, 6, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Self-emp-not-inc, 89172, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 80, United-States, <=50K 37, Federal-gov, 143547, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 310889, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 31, Local-gov, 150324, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 216472, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 25, United-States, <=50K 64, Private, 212838, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 65, United-States, >50K 45, Private, 168283, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 187702, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 19, Private, 60661, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 52, United-States, <=50K 54, Private, 115284, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 45, United-States, >50K 61, Self-emp-inc, 98350, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Taiwan, >50K 18, Private, 195372, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 62, ?, 81578, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Private, 111567, Assoc-voc, 11, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 244572, HS-grad, 9, Separated, Other-service, Not-in-family, Black, Female, 0, 0, 37, United-States, <=50K 54, Private, 230919, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 282604, Some-college, 10, Married-civ-spouse, Protective-serv, Other-relative, White, Male, 0, 0, 24, United-States, <=50K 54, Private, 320196, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, Germany, <=50K 42, Private, 201466, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 51, Federal-gov, 254211, Masters, 14, Widowed, Sales, Unmarried, White, Male, 0, 0, 50, El-Salvador, >50K 41, Private, 599629, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 0, 40, United-States, >50K 47, Local-gov, 219632, Assoc-acdm, 12, Separated, Exec-managerial, Not-in-family, White, Male, 0, 1408, 40, United-States, <=50K 31, State-gov, 161631, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 202373, Assoc-voc, 11, Never-married, Craft-repair, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 52, Private, 169549, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 127185, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 15, United-States, <=50K 18, Private, 184277, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 25, United-States, <=50K 58, Private, 119751, HS-grad, 9, Married-civ-spouse, Priv-house-serv, Other-relative, Asian-Pac-Islander, Female, 0, 0, 60, Philippines, <=50K 23, Private, 294701, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 26842, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 43, State-gov, 114537, Assoc-voc, 11, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 126386, HS-grad, 9, Divorced, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 163787, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 98211, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 175509, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 48, Private, 159854, 1st-4th, 2, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Self-emp-inc, 120920, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 24, Private, 187551, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 20, United-States, <=50K 41, State-gov, 27305, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 216711, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 47, Local-gov, 218596, Assoc-voc, 11, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 54, Private, 280292, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 32, United-States, <=50K 40, Private, 200496, Bachelors, 13, Separated, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 56, Self-emp-not-inc, 78090, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 0, 48, United-States, <=50K 23, Private, 118693, Assoc-voc, 11, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, Self-emp-not-inc, 203488, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 27, Local-gov, 172091, HS-grad, 9, Never-married, Craft-repair, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 32, Private, 113364, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 72, Self-emp-not-inc, 139889, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 74, United-States, <=50K 43, Local-gov, 301638, 12th, 8, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1579, 40, United-States, <=50K 32, Private, 110279, Assoc-acdm, 12, Divorced, Prof-specialty, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 53, Private, 242859, Some-college, 10, Separated, Adm-clerical, Own-child, White, Male, 0, 0, 40, Cuba, <=50K 18, Private, 132986, 12th, 8, Never-married, Other-service, Own-child, White, Male, 0, 0, 10, United-States, <=50K 38, Private, 254439, 10th, 6, Widowed, Transport-moving, Unmarried, Black, Male, 114, 0, 40, United-States, <=50K 41, Federal-gov, 187462, Assoc-voc, 11, Divorced, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 29, Private, 264961, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 45, United-States, <=50K 70, ?, 148065, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 4, United-States, >50K 46, Self-emp-inc, 200949, Bachelors, 13, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, ?, <=50K 47, Private, 47247, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 56, Local-gov, 571017, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 15, United-States, <=50K 28, Private, 416577, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 2829, 0, 40, United-States, <=50K 55, State-gov, 296991, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 40, United-States, >50K 50, State-gov, 45961, Bachelors, 13, Married-spouse-absent, Prof-specialty, Not-in-family, White, Male, 6849, 0, 40, United-States, <=50K 47, Private, 302711, 11th, 7, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 42, Self-emp-inc, 50356, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 199336, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 25, United-States, <=50K 42, Private, 341178, 5th-6th, 3, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 44, Mexico, <=50K 42, Federal-gov, 70240, Some-college, 10, Divorced, Exec-managerial, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 46, Private, 229394, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 390368, Some-college, 10, Married-civ-spouse, Sales, Husband, Black, Male, 15024, 0, 99, United-States, >50K 55, Private, 82098, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 55, United-States, <=50K 57, Private, 170411, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Private, 109532, 12th, 8, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 142682, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 30, Dominican-Republic, <=50K 34, Self-emp-inc, 127651, Bachelors, 13, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 27, Local-gov, 236472, Bachelors, 13, Divorced, Prof-specialty, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 176047, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Female, 2176, 0, 40, United-States, <=50K 37, Private, 111499, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 48, Private, 425199, Some-college, 10, Divorced, Sales, Unmarried, White, Male, 0, 0, 45, United-States, <=50K 38, Private, 229009, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 45, United-States, <=50K 17, Private, 232713, 10th, 6, Never-married, Craft-repair, Not-in-family, White, Male, 594, 0, 30, United-States, <=50K 70, Private, 141742, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 9386, 0, 50, United-States, >50K 37, Private, 234807, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 37, United-States, <=50K 45, Private, 738812, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 46, United-States, <=50K 56, Private, 204816, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, >50K 64, Private, 342494, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Local-gov, 226311, Some-college, 10, Divorced, Adm-clerical, Own-child, White, Female, 0, 0, 38, United-States, <=50K 23, Private, 143062, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 42, Local-gov, 125155, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 90, United-States, <=50K 23, Private, 329925, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 30, United-States, <=50K 26, ?, 208994, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 12, United-States, <=50K 56, Local-gov, 212864, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Private, 214242, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1887, 40, United-States, >50K 47, Self-emp-not-inc, 191175, 5th-6th, 3, Married-civ-spouse, Sales, Husband, White, Male, 0, 2179, 50, Mexico, <=50K 21, Private, 118693, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 253593, HS-grad, 9, Never-married, Craft-repair, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 32, State-gov, 206051, Some-college, 10, Married-spouse-absent, Farming-fishing, Own-child, White, Male, 0, 0, 50, United-States, <=50K 72, Private, 497280, 9th, 5, Widowed, Other-service, Unmarried, Black, Female, 0, 0, 20, United-States, <=50K 69, Self-emp-not-inc, 240562, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 40, United-States, >50K 19, Private, 140985, Some-college, 10, Never-married, Adm-clerical, Other-relative, White, Male, 0, 0, 25, United-States, <=50K 25, Local-gov, 191921, Bachelors, 13, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 25, United-States, <=50K 56, Private, 204049, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 1848, 50, United-States, >50K 42, Private, 331651, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 8614, 0, 50, United-States, >50K 58, Private, 142158, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 24, Private, 249046, Bachelors, 13, Never-married, Tech-support, Own-child, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 213019, Assoc-voc, 11, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 38, United-States, >50K 40, Private, 199599, 10th, 6, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Private, 186191, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 45, ?, <=50K 25, Private, 28008, Assoc-acdm, 12, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 43, Self-emp-inc, 82488, Bachelors, 13, Married-civ-spouse, Sales, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, >50K 36, Private, 117073, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 325786, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 37546, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 204226, HS-grad, 9, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 133299, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 29702, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 307812, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 25, Private, 174545, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 46, United-States, <=50K 23, Private, 233472, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 184147, HS-grad, 9, Separated, Sales, Unmarried, Black, Female, 0, 0, 20, United-States, <=50K 27, Private, 198188, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 2580, 0, 45, United-States, <=50K 32, Private, 447066, Bachelors, 13, Married-civ-spouse, Sales, Husband, Black, Male, 15024, 0, 50, United-States, >50K 33, Private, 200246, Some-college, 10, Married-spouse-absent, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 166585, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 21, Private, 335570, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 30, ?, <=50K 39, Private, 53569, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 167065, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Private, 113364, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 40, Federal-gov, 219266, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 58, Federal-gov, 200042, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 40, United-States, >50K 20, Private, 205975, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 63, ?, 234083, HS-grad, 9, Divorced, ?, Not-in-family, White, Female, 0, 2205, 40, United-States, <=50K 56, Private, 65325, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, <=50K 30, Local-gov, 194740, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 99065, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 39, United-States, <=50K 25, Private, 212793, Assoc-acdm, 12, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 33, Private, 112941, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 41, State-gov, 187322, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 283676, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 173682, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 168470, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 186454, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Asian-Pac-Islander, Male, 13550, 0, 40, United-States, >50K 58, Private, 141807, 5th-6th, 3, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Italy, <=50K 25, Private, 245628, Some-college, 10, Never-married, Tech-support, Own-child, White, Male, 0, 0, 15, Mexico, <=50K 31, Private, 264864, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 39, Private, 262841, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 55, Private, 37438, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 22, Private, 170800, Assoc-voc, 11, Never-married, Other-service, Own-child, White, Female, 0, 0, 12, United-States, <=50K 44, Private, 152150, Assoc-acdm, 12, Separated, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, ?, 211873, Assoc-voc, 11, Married-civ-spouse, ?, Wife, White, Female, 0, 1628, 5, ?, <=50K 44, Private, 159580, 12th, 8, Divorced, Transport-moving, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 61, Private, 477209, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 54, United-States, <=50K 32, Private, 70985, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 241998, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 28, Private, 249541, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 135339, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, >50K 32, Private, 44675, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 65, United-States, >50K 46, State-gov, 247992, 7th-8th, 4, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 26, Self-emp-not-inc, 221626, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 1579, 20, United-States, <=50K 43, Self-emp-inc, 48087, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 62, Local-gov, 114045, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 60, State-gov, 69251, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 38, China, >50K 67, Private, 192670, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 19, Private, 268392, HS-grad, 9, Never-married, Sales, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 55, ?, 170994, HS-grad, 9, Never-married, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 48, Private, 431513, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 65, United-States, >50K 19, State-gov, 37332, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 19, Private, 35865, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 43, Private, 183891, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 150309, Doctorate, 16, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 90, United-States, <=50K 65, Private, 93318, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 45, United-States, <=50K 32, Private, 171814, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, State-gov, 183735, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Private, 353541, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 33, Local-gov, 152351, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 3908, 0, 40, United-States, <=50K 72, ?, 271352, 10th, 6, Divorced, ?, Not-in-family, White, Male, 0, 0, 12, United-States, <=50K 34, Private, 345705, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 1977, 50, United-States, >50K 27, Private, 223751, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 75, Self-emp-inc, 164570, 11th, 7, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 39, ?, 281363, 10th, 6, Widowed, ?, Unmarried, White, Female, 0, 0, 15, United-States, <=50K 51, Private, 110747, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1887, 40, United-States, >50K 47, Private, 34458, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 254293, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 270147, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 48, Private, 195491, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 36, Local-gov, 255454, Bachelors, 13, Never-married, Protective-serv, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 18, Private, 126125, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 33, Private, 618191, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 163110, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 145409, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 3103, 0, 48, United-States, >50K 39, State-gov, 235379, Assoc-acdm, 12, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 55465, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 35, United-States, <=50K 67, Local-gov, 181220, Some-college, 10, Divorced, Adm-clerical, Not-in-family, Black, Female, 0, 0, 20, United-States, <=50K 42, Private, 26672, Assoc-voc, 11, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 59, Private, 98361, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Local-gov, 219883, HS-grad, 9, Never-married, Protective-serv, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 19, Private, 376683, Some-college, 10, Never-married, Other-service, Unmarried, Black, Female, 2036, 0, 30, United-States, <=50K 47, Private, 33865, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 68, Private, 168794, 7th-8th, 4, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 30, United-States, <=50K 30, Private, 94245, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 34572, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 49, Private, 348751, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 65382, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 60, Private, 116707, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 7298, 0, 40, United-States, >50K 51, Private, 178054, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, ?, >50K 24, Private, 140001, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 166889, Some-college, 10, Never-married, Handlers-cleaners, Own-child, Black, Female, 0, 1602, 35, United-States, <=50K 24, Private, 117789, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 238917, 5th-6th, 3, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Mexico, <=50K 48, Local-gov, 242923, HS-grad, 9, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 1848, 40, United-States, >50K 52, Local-gov, 330799, 9th, 5, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, <=50K 48, Private, 209460, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 40, Federal-gov, 75313, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 66, United-States, >50K 29, ?, 339100, 11th, 7, Divorced, ?, Not-in-family, White, Female, 3418, 0, 48, United-States, <=50K 20, Private, 184779, Some-college, 10, Never-married, Tech-support, Own-child, White, Female, 0, 0, 20, United-States, <=50K 31, Private, 139000, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 30, Private, 361742, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 30, Private, 260782, HS-grad, 9, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, ?, <=50K 51, Private, 203435, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 100579, Assoc-voc, 11, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 56, Self-emp-not-inc, 356067, Masters, 14, Never-married, Sales, Not-in-family, White, Male, 0, 0, 16, United-States, <=50K 46, Private, 87250, Bachelors, 13, Separated, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 264663, Some-college, 10, Separated, Prof-specialty, Own-child, White, Female, 0, 3900, 40, United-States, <=50K 29, Private, 255817, 5th-6th, 3, Never-married, Other-service, Other-relative, White, Female, 0, 0, 40, El-Salvador, <=50K 48, Self-emp-not-inc, 243631, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 30, South, <=50K 34, Self-emp-inc, 544268, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 42, Self-emp-not-inc, 98061, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 25, Private, 95691, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 30, Columbia, <=50K 47, Private, 145868, 11th, 7, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 23, Private, 65038, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 43, Local-gov, 227734, Assoc-voc, 11, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 22, United-States, <=50K 19, Local-gov, 176831, Some-college, 10, Never-married, Other-service, Own-child, Black, Female, 0, 0, 35, United-States, <=50K 22, Private, 211678, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 40, Local-gov, 157240, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 70, United-States, <=50K 41, Self-emp-not-inc, 145441, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Yugoslavia, <=50K 71, Self-emp-inc, 66624, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 2392, 60, United-States, >50K 42, Private, 76487, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, <=50K 31, State-gov, 557853, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 47, United-States, <=50K 69, ?, 262352, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 32, United-States, <=50K 58, Self-emp-not-inc, 118253, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 70, United-States, <=50K 36, Private, 146625, 11th, 7, Widowed, Other-service, Unmarried, Black, Female, 0, 0, 12, United-States, <=50K 31, Private, 174201, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 65, United-States, <=50K 20, ?, 66695, Some-college, 10, Never-married, ?, Own-child, Other, Female, 594, 0, 35, United-States, <=50K 41, Private, 121130, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 385847, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 62, ?, 83439, 7th-8th, 4, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 114158, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 15, United-States, <=50K 27, Private, 381789, 12th, 8, Married-civ-spouse, Farming-fishing, Own-child, White, Male, 0, 0, 55, United-States, <=50K 17, Private, 82041, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, Canada, <=50K 35, Self-emp-not-inc, 115618, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 45, Self-emp-not-inc, 106110, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 99, United-States, <=50K 44, Private, 267521, Bachelors, 13, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 90692, Assoc-voc, 11, Never-married, Other-service, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 51, Private, 57101, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 236913, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 64, Self-emp-not-inc, 388625, 10th, 6, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 10, United-States, >50K 54, Self-emp-not-inc, 261207, 7th-8th, 4, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 45, Cuba, <=50K 43, Private, 245487, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Other, Male, 0, 0, 40, Mexico, <=50K 32, Private, 262153, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 35, United-States, <=50K 36, Private, 225516, Assoc-acdm, 12, Never-married, Sales, Not-in-family, Black, Male, 10520, 0, 43, United-States, >50K 26, Self-emp-not-inc, 68729, HS-grad, 9, Never-married, Sales, Other-relative, Asian-Pac-Islander, Male, 0, 0, 50, United-States, >50K 37, Private, 126954, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 38, Private, 85074, Assoc-acdm, 12, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 383306, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 128143, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1887, 50, United-States, >50K 47, Private, 185041, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 40, United-States, >50K 42, Private, 99373, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 66, Local-gov, 157942, HS-grad, 9, Widowed, Transport-moving, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 43, Private, 241928, HS-grad, 9, Separated, Adm-clerical, Not-in-family, Black, Female, 0, 0, 32, United-States, <=50K 37, Private, 348739, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 37, Private, 95654, 10th, 6, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 25, Private, 367306, Some-college, 10, Never-married, Tech-support, Own-child, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 270421, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 63, ?, 221592, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, >50K 50, Self-emp-not-inc, 156951, Assoc-acdm, 12, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 3103, 0, 40, United-States, >50K 42, State-gov, 39239, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 32, Private, 72744, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 42, State-gov, 367292, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Self-emp-not-inc, 408498, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 25, Private, 361493, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 3325, 0, 40, United-States, <=50K 65, Self-emp-inc, 157403, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 32, Private, 231263, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, <=50K 32, Private, 244147, HS-grad, 9, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 10, United-States, <=50K 24, Private, 220944, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 51, Federal-gov, 314007, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 67, ?, 200862, 10th, 6, Never-married, ?, Not-in-family, Black, Female, 0, 0, 35, United-States, <=50K 28, Private, 33374, 11th, 7, Married-spouse-absent, Other-service, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 32, Self-emp-inc, 345489, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 77, Private, 83601, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 162302, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 26, Private, 112847, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 147344, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, United-States, <=50K 57, State-gov, 183657, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 35, United-States, >50K 40, Private, 130760, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, <=50K 50, Private, 163948, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 19, Private, 316797, 7th-8th, 4, Married-civ-spouse, Handlers-cleaners, Own-child, White, Male, 0, 0, 45, Mexico, <=50K 54, Federal-gov, 332243, 12th, 8, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Local-gov, 195844, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 51, Local-gov, 387250, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, >50K 38, State-gov, 188303, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 7688, 0, 40, United-States, >50K 68, ?, 40956, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 25, United-States, <=50K 17, Private, 178953, 12th, 8, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 32, Private, 398988, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 535978, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 42, Private, 296982, Some-college, 10, Divorced, Sales, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 231991, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 295799, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, State-gov, 201569, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 20, United-States, <=50K 58, Private, 193568, 11th, 7, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 61, Private, 97128, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 42, Private, 203393, Bachelors, 13, Married-civ-spouse, Craft-repair, Wife, Black, Female, 0, 0, 35, United-States, >50K 49, Private, 138370, Masters, 14, Married-spouse-absent, Protective-serv, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, India, <=50K 41, Self-emp-inc, 120277, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, ?, <=50K 43, Private, 91949, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 46, Private, 228372, Bachelors, 13, Divorced, Sales, Unmarried, White, Male, 0, 0, 40, United-States, >50K 28, Private, 132191, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, >50K 39, Self-emp-not-inc, 274683, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 50, United-States, >50K 50, Local-gov, 196307, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 7688, 0, 40, United-States, >50K 57, Private, 195835, Some-college, 10, Married-spouse-absent, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 185399, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 38, United-States, <=50K 79, Self-emp-not-inc, 103684, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 140559, HS-grad, 9, Married-civ-spouse, Priv-house-serv, Wife, White, Female, 0, 0, 45, United-States, <=50K 35, Federal-gov, 110188, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Vietnam, <=50K 35, Local-gov, 668319, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1740, 80, United-States, <=50K 30, Private, 112358, Bachelors, 13, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 60, United-States, >50K 26, Private, 151810, 10th, 6, Never-married, Farming-fishing, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 49, Private, 48120, HS-grad, 9, Never-married, Transport-moving, Unmarried, Black, Female, 1506, 0, 40, United-States, <=50K 48, Private, 144844, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 205839, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 22, Private, 113760, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 50, Private, 138358, 10th, 6, Separated, Adm-clerical, Not-in-family, Black, Female, 0, 0, 47, Jamaica, <=50K 47, Self-emp-not-inc, 216657, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 36, Private, 278576, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 44, Private, 174373, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 73, Private, 220019, 9th, 5, Widowed, Other-service, Unmarried, White, Female, 0, 0, 9, United-States, <=50K 24, ?, 311949, HS-grad, 9, Never-married, ?, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 45, ?, <=50K 34, Private, 303867, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Private, 154210, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Hong, <=50K 28, ?, 131310, 12th, 8, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 20, Germany, <=50K 46, Private, 202560, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 20, ?, 358783, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 35, United-States, <=50K 29, Private, 423024, 5th-6th, 3, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, Mexico, <=50K 24, Private, 206671, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, State-gov, 245310, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 18, Private, 31983, 12th, 8, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 41, Private, 124956, Bachelors, 13, Divorced, Exec-managerial, Unmarried, Black, Female, 0, 0, 90, United-States, >50K 59, Private, 118358, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 491421, 5th-6th, 3, Never-married, Farming-fishing, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 50, Private, 151580, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 25, Private, 248990, 1st-4th, 2, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 24, Mexico, <=50K 42, Private, 157425, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 36, Private, 221650, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Japan, <=50K 62, Private, 88055, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 60, United-States, >50K 71, Private, 216608, Assoc-voc, 11, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 682947, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 55, United-States, >50K 44, Private, 228124, HS-grad, 9, Married-spouse-absent, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 19, ?, 217194, 10th, 6, Never-married, ?, Own-child, White, Male, 0, 0, 30, United-States, <=50K 49, Self-emp-not-inc, 171540, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 60, Self-emp-inc, 210827, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 40, United-States, >50K 28, Self-emp-not-inc, 410351, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, Poland, <=50K 26, Private, 163747, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 18, Private, 108892, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 12, United-States, <=50K 43, Private, 180096, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 65, Local-gov, 153890, 12th, 8, Widowed, Exec-managerial, Not-in-family, White, Male, 2009, 0, 44, United-States, <=50K 23, Private, 117480, 10th, 6, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 44, United-States, <=50K 21, Private, 163333, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 35, United-States, <=50K 20, Self-emp-not-inc, 306710, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 150553, Some-college, 10, Never-married, Sales, Own-child, Asian-Pac-Islander, Female, 0, 0, 18, Philippines, <=50K 77, Private, 123959, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 32, Private, 24961, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Local-gov, 327120, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 30, United-States, <=50K 29, Self-emp-not-inc, 33798, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 59, Private, 81929, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 2415, 45, United-States, >50K 22, Private, 298489, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 30, ?, 101697, Bachelors, 13, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 20, United-States, <=50K 31, Private, 144064, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, >50K 59, Self-emp-not-inc, 195835, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 29, Federal-gov, 184723, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 56, Private, 265086, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 19, Private, 235909, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 37, Private, 42645, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, State-gov, 279878, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Private, 104892, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Private, 137063, HS-grad, 9, Never-married, Sales, Unmarried, White, Male, 0, 0, 38, United-States, <=50K 38, Self-emp-not-inc, 58972, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 36, Private, 126675, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 50, United-States, >50K 19, Private, 286435, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 594, 0, 40, United-States, <=50K 46, Private, 191389, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 28, United-States, >50K 42, Private, 183241, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 45, United-States, >50K 29, Private, 91547, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 52781, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 40, United-States, >50K 29, Private, 210959, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 365516, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 112271, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 269455, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 45, United-States, <=50K 46, Private, 164379, Bachelors, 13, Divorced, Sales, Unmarried, Black, Female, 0, 0, 35, United-States, >50K 28, Private, 109621, Assoc-acdm, 12, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 104858, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 56, United-States, >50K 39, Private, 99270, HS-grad, 9, Divorced, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 193524, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 70, ?, 149040, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 2964, 0, 12, United-States, <=50K 60, State-gov, 313946, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 162358, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 59, Private, 200700, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 48, United-States, >50K 21, Private, 116489, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 60, United-States, <=50K 22, Private, 118310, Assoc-acdm, 12, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 16, United-States, <=50K 31, Private, 352465, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 40, Private, 107433, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 50, United-States, >50K 33, Private, 296538, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 41, Local-gov, 195897, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 31, Self-emp-not-inc, 216283, Assoc-acdm, 12, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 35, United-States, >50K 62, Private, 345780, Assoc-voc, 11, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 216685, HS-grad, 9, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 35, United-States, <=50K 28, Local-gov, 210945, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Black, Female, 0, 0, 60, United-States, <=50K 43, Private, 184321, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 1887, 40, United-States, >50K 55, Self-emp-not-inc, 322691, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 3103, 0, 55, United-States, >50K 42, Private, 192712, HS-grad, 9, Separated, Other-service, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 23, Private, 178272, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 55, Federal-gov, 321333, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 44, Self-emp-inc, 120277, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 45, United-States, >50K 19, Private, 294029, 11th, 7, Never-married, Sales, Own-child, Other, Female, 0, 0, 32, Nicaragua, <=50K 23, Private, 112819, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 152636, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 63, ?, 301611, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 20, United-States, <=50K 51, Private, 134808, HS-grad, 9, Separated, Handlers-cleaners, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 64216, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 90, United-States, <=50K 29, State-gov, 214284, Masters, 14, Never-married, Prof-specialty, Unmarried, Asian-Pac-Islander, Female, 0, 0, 20, Taiwan, <=50K 25, Private, 469572, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 8614, 0, 40, United-States, >50K 44, Self-emp-not-inc, 282722, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 50, United-States, >50K 17, Private, 231439, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 30, United-States, <=50K 42, Self-emp-inc, 120277, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 21, Private, 364685, 11th, 7, Never-married, Tech-support, Own-child, White, Female, 0, 0, 35, United-States, <=50K 26, Private, 18827, Some-college, 10, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 169129, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 202051, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 42, United-States, >50K 58, ?, 353244, Bachelors, 13, Widowed, ?, Unmarried, White, Female, 27828, 0, 50, United-States, >50K 19, Private, 574271, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 28, United-States, <=50K 65, State-gov, 29276, 7th-8th, 4, Widowed, Other-service, Other-relative, White, Female, 0, 0, 24, United-States, <=50K 52, Self-emp-not-inc, 104501, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 60, United-States, >50K 17, Private, 394176, 10th, 6, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, United-States, <=50K 27, Private, 85625, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 22, United-States, <=50K 53, Private, 340723, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 149342, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 73715, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 34, Private, 143083, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 18, United-States, <=50K 40, Local-gov, 290660, Assoc-acdm, 12, Divorced, Exec-managerial, Not-in-family, White, Male, 8614, 0, 50, United-States, >50K 49, Local-gov, 98738, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 86, Private, 149912, Masters, 14, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 309033, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Wife, White, Female, 15024, 0, 60, United-States, >50K 43, Self-emp-not-inc, 96129, 11th, 7, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 60, United-States, <=50K 47, Private, 216096, Some-college, 10, Married-spouse-absent, Exec-managerial, Unmarried, White, Female, 0, 0, 35, Puerto-Rico, <=50K 32, Private, 171091, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 30, Self-emp-not-inc, 79303, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 25, Local-gov, 182380, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 36271, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 60, Private, 118197, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 65, United-States, <=50K 46, Private, 269652, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 4386, 0, 38, United-States, >50K 39, Local-gov, 193815, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 141957, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 1887, 70, United-States, >50K 26, Private, 222637, 10th, 6, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 55, Puerto-Rico, <=50K 27, Private, 118230, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 59, Private, 174040, Some-college, 10, Divorced, Prof-specialty, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 64, State-gov, 105748, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 90, Self-emp-not-inc, 82628, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 2964, 0, 12, United-States, <=50K 51, Private, 205100, Some-college, 10, Divorced, Sales, Not-in-family, White, Female, 0, 0, 45, United-States, >50K 36, Private, 107916, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 2002, 40, United-States, <=50K 39, Private, 130620, 7th-8th, 4, Married-spouse-absent, Machine-op-inspct, Unmarried, Other, Female, 0, 0, 40, Dominican-Republic, <=50K 30, ?, 361817, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 0, 25, United-States, <=50K 47, Self-emp-not-inc, 235646, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Private, 53277, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 24, Private, 456460, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 293091, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 30, United-States, <=50K 62, Private, 210935, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 20, United-States, <=50K 48, ?, 199763, Some-college, 10, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 20, United-States, <=50K 62, ?, 223447, 12th, 8, Divorced, ?, Not-in-family, White, Male, 0, 0, 40, Canada, <=50K 35, Self-emp-not-inc, 233533, Bachelors, 13, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 27, Private, 95647, Bachelors, 13, Never-married, Prof-specialty, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 49, Private, 199763, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 18, Private, 74539, 10th, 6, Never-married, Sales, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 19, Private, 84610, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 63, Self-emp-inc, 96930, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 54, Private, 115602, HS-grad, 9, Married-civ-spouse, Other-service, Wife, Black, Female, 0, 0, 40, United-States, <=50K 24, Private, 237341, Some-college, 10, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 61, Private, 143800, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 50, Self-emp-inc, 163921, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 48, United-States, >50K 36, Private, 68273, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 21, Private, 113163, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 50, United-States, <=50K 38, Self-emp-inc, 478829, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 50, United-States, >50K 30, Private, 345705, Some-college, 10, Married-civ-spouse, Exec-managerial, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 385077, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 2907, 0, 40, United-States, <=50K 33, Private, 192286, Some-college, 10, Divorced, Adm-clerical, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 52, United-States, <=50K 39, Local-gov, 236391, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 38, United-States, >50K 42, Private, 106679, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 47, ?, 308242, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Local-gov, 46094, Bachelors, 13, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 33, United-States, <=50K 29, Private, 194940, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 341643, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 23, Private, 210474, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 28, Private, 76313, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Amer-Indian-Eskimo, Male, 0, 0, 60, United-States, <=50K 34, Private, 115858, HS-grad, 9, Divorced, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 55191, Some-college, 10, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 67, Self-emp-not-inc, 364862, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 49, Private, 334787, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 205733, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 60, ?, 120163, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 333677, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 2463, 0, 35, United-States, <=50K 25, Private, 208591, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 341204, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 1831, 0, 30, United-States, <=50K 56, Self-emp-not-inc, 115422, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Self-emp-inc, 111319, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 1887, 45, United-States, >50K 54, Private, 816750, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 2051, 40, United-States, <=50K 25, Private, 167835, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 3325, 0, 40, United-States, <=50K 28, Private, 92262, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 91964, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 107682, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 52, State-gov, 135388, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 5013, 0, 40, United-States, <=50K 39, Self-emp-not-inc, 597843, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, Columbia, <=50K 19, Private, 389942, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 442274, 12th, 8, Never-married, Adm-clerical, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 595461, 7th-8th, 4, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 52, Private, 284329, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 40, United-States, >50K 33, Self-emp-not-inc, 127894, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 35, Private, 196899, Bachelors, 13, Never-married, Handlers-cleaners, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 50, Haiti, <=50K 58, Private, 212534, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 71209, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 39, Private, 237943, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 70, United-States, >50K 38, Private, 190759, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 59, Private, 100313, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1887, 40, United-States, >50K 41, Private, 344624, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 27, ?, 194024, 9th, 5, Separated, ?, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 19, Private, 87497, 11th, 7, Never-married, Transport-moving, Other-relative, White, Male, 0, 0, 10, United-States, <=50K 22, Private, 236907, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, United-States, <=50K 59, Private, 169639, Assoc-acdm, 12, Widowed, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 105803, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 3103, 0, 45, United-States, >50K 31, Private, 149507, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 43, United-States, <=50K 18, Private, 294387, 11th, 7, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 161708, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 35, United-States, <=50K 28, Private, 282389, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 28, Private, 64940, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 49, Private, 195727, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Local-gov, 37931, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 19, Private, 170720, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 20, United-States, <=50K 43, Private, 152958, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 40, United-States, >50K 28, Private, 312372, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 15024, 0, 40, United-States, >50K 41, Private, 39581, Some-college, 10, Divorced, Adm-clerical, Not-in-family, Black, Female, 0, 0, 24, El-Salvador, <=50K 50, Private, 206862, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 65, United-States, >50K 46, Private, 216934, Bachelors, 13, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, Portugal, <=50K 20, Private, 143062, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 242391, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 28, Private, 165030, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 37, Private, 199251, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, <=50K 46, Self-emp-not-inc, 353012, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 50, United-States, >50K 66, Private, 174491, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, ?, 333305, Some-college, 10, Married-civ-spouse, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 203138, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 50, United-States, >50K 25, Private, 220220, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 45, United-States, <=50K 55, Federal-gov, 305850, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 40, United-States, >50K 48, Local-gov, 273402, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1902, 40, United-States, <=50K 56, Private, 201344, Some-college, 10, Widowed, Craft-repair, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 47, Self-emp-not-inc, 218676, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 55, Self-emp-not-inc, 141807, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 41, State-gov, 222434, Assoc-acdm, 12, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 266860, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 65, United-States, >50K 40, Private, 34113, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, Amer-Indian-Eskimo, Male, 6849, 0, 43, United-States, <=50K 41, Private, 159549, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 195248, Some-college, 10, Never-married, Sales, Own-child, Other, Female, 0, 0, 20, United-States, <=50K 52, Private, 109413, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 62, Private, 195343, Doctorate, 16, Divorced, Prof-specialty, Unmarried, White, Male, 15020, 0, 50, United-States, >50K 46, Private, 185291, 11th, 7, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 45, United-States, >50K 21, ?, 140012, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 20, United-States, <=50K 35, Self-emp-not-inc, 114366, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 169631, HS-grad, 9, Married-spouse-absent, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 163870, 10th, 6, Married-civ-spouse, Other-service, Husband, White, Male, 3908, 0, 40, United-States, <=50K 35, Private, 312232, HS-grad, 9, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 46, Private, 229737, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, India, >50K 70, ?, 306563, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 161637, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 1902, 40, Taiwan, >50K 34, Private, 106014, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 21, Private, 25265, Assoc-voc, 11, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 29, Private, 71860, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 41, Self-emp-inc, 94113, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 51, Self-emp-not-inc, 208003, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 113550, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 83046, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Self-emp-inc, 277488, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 65, United-States, >50K 19, Private, 205830, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, El-Salvador, <=50K 46, Private, 273575, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 15024, 0, 40, United-States, >50K 23, Private, 245147, Some-college, 10, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 49, Private, 274720, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 58, Self-emp-not-inc, 163047, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 41, State-gov, 47902, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, >50K 50, Private, 128798, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 77, Private, 154205, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 10, United-States, <=50K 27, Private, 176683, Assoc-voc, 11, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 60, United-States, <=50K 29, Self-emp-inc, 104737, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 54, Private, 349340, Preschool, 1, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, India, <=50K 39, State-gov, 218249, Some-college, 10, Separated, Prof-specialty, Unmarried, Black, Female, 0, 0, 37, United-States, <=50K 32, Private, 281540, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 50, United-States, <=50K 36, Federal-gov, 112847, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 24, Local-gov, 126613, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 20, United-States, <=50K 50, Self-emp-not-inc, 145419, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 45, United-States, >50K 32, Self-emp-not-inc, 34572, HS-grad, 9, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 26, Private, 104045, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 49, ?, 57665, Bachelors, 13, Divorced, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 359001, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 42, United-States, <=50K 47, Private, 105273, Bachelors, 13, Widowed, Craft-repair, Unmarried, Black, Female, 6497, 0, 40, United-States, <=50K 31, Private, 201122, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 160035, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, <=50K 50, Private, 167886, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 18, Private, 32059, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 59, Self-emp-inc, 200453, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, Self-emp-not-inc, 403072, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 34, Private, 37210, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 50, United-States, <=50K 32, Private, 199416, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 413227, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 29, ?, 188675, Some-college, 10, Divorced, ?, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 42, Private, 226902, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 45, United-States, >50K 37, Private, 195189, Some-college, 10, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 36, Private, 116608, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 59, Private, 99131, Masters, 14, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 32, Private, 553405, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 99999, 0, 50, United-States, >50K 52, Local-gov, 186117, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 56, United-States, >50K 29, State-gov, 67053, HS-grad, 9, Never-married, Other-service, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, Thailand, <=50K 39, Private, 347960, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Female, 14084, 0, 35, United-States, >50K 39, Private, 325374, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 69, Private, 130413, Bachelors, 13, Widowed, Exec-managerial, Not-in-family, White, Female, 2346, 0, 15, United-States, <=50K 43, Private, 111949, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 35, United-States, <=50K 39, Private, 278557, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1628, 48, United-States, <=50K 19, Private, 194905, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 60, Local-gov, 195453, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 51, Private, 282549, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 3137, 0, 40, United-States, <=50K 75, Private, 316119, Some-college, 10, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 8, United-States, <=50K 37, State-gov, 252939, Assoc-voc, 11, Never-married, Prof-specialty, Unmarried, Black, Female, 5455, 0, 40, United-States, <=50K 24, State-gov, 506329, Some-college, 10, Never-married, Adm-clerical, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, ?, <=50K 20, Private, 316043, 11th, 7, Never-married, Other-service, Own-child, Black, Male, 594, 0, 20, United-States, <=50K 58, Federal-gov, 319733, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 70, United-States, <=50K 21, State-gov, 99199, Masters, 14, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 15, United-States, <=50K 28, Private, 204600, HS-grad, 9, Separated, Protective-serv, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 173307, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Self-emp-not-inc, 34446, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 40, Self-emp-not-inc, 237293, Prof-school, 15, Married-civ-spouse, Prof-specialty, Wife, White, Female, 15024, 0, 40, United-States, >50K 41, Private, 175642, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 58, Private, 203735, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 44, Local-gov, 171589, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 7688, 0, 40, United-States, >50K 26, Private, 197967, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 65, United-States, <=50K 29, Private, 413297, Assoc-acdm, 12, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, Mexico, <=50K 45, Private, 240841, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 152189, Assoc-acdm, 12, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, State-gov, 85874, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 45, Self-emp-not-inc, 176814, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 40, United-States, >50K 51, Local-gov, 133336, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 40, United-States, >50K 22, Private, 362623, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 67, ?, 37170, 7th-8th, 4, Divorced, ?, Not-in-family, White, Male, 0, 0, 3, United-States, <=50K 28, Private, 30912, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 35448, Some-college, 10, Never-married, Other-service, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 33, Private, 173248, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 35, United-States, <=50K 37, Private, 49626, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 43, United-States, <=50K 19, Private, 102723, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 90, ?, 166343, 1st-4th, 2, Widowed, ?, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 35, Private, 168322, 11th, 7, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 62, Private, 131117, 7th-8th, 4, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 38, Columbia, <=50K 20, ?, 210474, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 15, United-States, <=50K 25, Private, 110138, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 107452, HS-grad, 9, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 160594, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 35, United-States, <=50K 32, Local-gov, 186784, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 5013, 0, 45, United-States, <=50K 70, Local-gov, 334666, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 12, United-States, <=50K 65, ?, 191380, 10th, 6, Married-civ-spouse, ?, Husband, White, Male, 9386, 0, 50, United-States, >50K 57, Private, 104272, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 19491, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 128715, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 34, Private, 128063, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 36, United-States, <=50K 26, Self-emp-not-inc, 37023, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 78, United-States, <=50K 44, Private, 68748, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 48, United-States, <=50K 66, Private, 140576, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Local-gov, 327435, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 202729, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 53, Private, 277471, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 189670, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 50, United-States, <=50K 61, Private, 204908, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 171841, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 78247, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 68895, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 50, Mexico, <=50K 27, Private, 56658, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, Amer-Indian-Eskimo, Male, 0, 0, 8, United-States, <=50K 58, Local-gov, 259216, 9th, 5, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 37, State-gov, 270278, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 12, Puerto-Rico, <=50K 56, Private, 238806, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 26, United-States, <=50K 36, Private, 111128, Some-college, 10, Separated, Exec-managerial, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 29, Private, 119429, HS-grad, 9, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 28, Private, 73037, 10th, 6, Never-married, Transport-moving, Unmarried, White, Male, 0, 0, 30, United-States, <=50K 61, Self-emp-not-inc, 84409, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 66, Self-emp-not-inc, 274451, 9th, 5, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 25, United-States, >50K 31, Private, 246439, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 7298, 0, 50, United-States, >50K 21, Private, 124242, Assoc-acdm, 12, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 67, Self-emp-not-inc, 123393, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 6418, 0, 58, United-States, >50K 26, Private, 159732, HS-grad, 9, Widowed, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 161415, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 33, Private, 157568, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 168030, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 59, State-gov, 349910, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 10605, 0, 50, United-States, >50K 82, Self-emp-inc, 130329, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 34, State-gov, 56964, Doctorate, 16, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 50, United-States, >50K 29, Private, 370509, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, France, >50K 19, Private, 106306, Some-college, 10, Divorced, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 57, Self-emp-not-inc, 56480, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 1, United-States, <=50K 41, Private, 115932, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 50, United-States, >50K 55, Private, 154580, 10th, 6, Married-civ-spouse, Other-service, Husband, Black, Male, 2580, 0, 40, United-States, <=50K 27, Private, 404421, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 33, Private, 194901, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 43, State-gov, 164790, Some-college, 10, Divorced, Adm-clerical, Not-in-family, Black, Male, 0, 0, 50, United-States, >50K 72, Federal-gov, 94242, Some-college, 10, Widowed, Tech-support, Not-in-family, White, Female, 0, 0, 16, United-States, <=50K 68, Self-emp-not-inc, 365020, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 160512, HS-grad, 9, Separated, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 170331, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 30, Private, 101266, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 100252, Bachelors, 13, Divorced, Other-service, Not-in-family, Asian-Pac-Islander, Male, 99999, 0, 70, United-States, >50K 54, Private, 217718, 5th-6th, 3, Married-spouse-absent, Other-service, Unmarried, Black, Female, 0, 0, 30, Haiti, <=50K 32, Private, 170154, Assoc-acdm, 12, Separated, Exec-managerial, Unmarried, White, Female, 25236, 0, 50, United-States, >50K 56, Private, 105281, HS-grad, 9, Widowed, Sales, Not-in-family, White, Female, 0, 1974, 40, United-States, <=50K 39, ?, 361838, Bachelors, 13, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 6, United-States, >50K 41, State-gov, 283917, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, >50K 48, Private, 39530, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 66, Self-emp-not-inc, 212185, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 48, United-States, <=50K 25, Self-emp-inc, 90752, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 31, Private, 202450, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 1573, 40, United-States, <=50K 32, Private, 168138, Assoc-acdm, 12, Divorced, Sales, Not-in-family, White, Male, 2597, 0, 48, United-States, <=50K 51, Private, 159755, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 40, United-States, >50K 42, Private, 191765, HS-grad, 9, Never-married, Adm-clerical, Other-relative, Black, Female, 0, 2339, 40, Trinadad&Tobago, <=50K 22, ?, 210802, Some-college, 10, Never-married, ?, Not-in-family, Black, Female, 0, 0, 35, United-States, <=50K 31, Private, 340880, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 43, Self-emp-not-inc, 113211, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 134509, Some-college, 10, Never-married, Transport-moving, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 20, State-gov, 147280, HS-grad, 9, Never-married, Other-service, Other-relative, Other, Male, 0, 0, 40, United-States, <=50K 40, Private, 145441, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 65, Private, 398001, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 53, Private, 31588, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 52, United-States, >50K 56, Private, 189975, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1902, 60, United-States, >50K 51, State-gov, 231495, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 55, United-States, >50K 38, ?, 121135, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 186916, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 49, Self-emp-inc, 213140, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 60, United-States, >50K 47, Private, 176893, HS-grad, 9, Divorced, Craft-repair, Not-in-family, Black, Male, 8614, 0, 44, United-States, >50K 22, Private, 115244, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, <=50K 53, Private, 313243, Some-college, 10, Separated, Craft-repair, Not-in-family, White, Male, 0, 2444, 45, United-States, >50K 41, Local-gov, 169995, Some-college, 10, Divorced, Protective-serv, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 19, Private, 198459, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 2001, 40, United-States, <=50K 27, Local-gov, 66824, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Amer-Indian-Eskimo, Female, 3325, 0, 43, United-States, <=50K 48, Self-emp-not-inc, 52240, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 25, United-States, >50K 52, Private, 35305, 7th-8th, 4, Never-married, Other-service, Own-child, White, Female, 0, 0, 7, United-States, <=50K 61, State-gov, 186451, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 40, United-States, >50K 45, Self-emp-not-inc, 160724, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 45, China, >50K 29, Private, 210464, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 207685, Some-college, 10, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 21, United-States, <=50K 38, Private, 233717, Some-college, 10, Divorced, Exec-managerial, Unmarried, Black, Male, 0, 0, 60, United-States, <=50K 32, Private, 222205, Some-college, 10, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 37, Private, 167613, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 148773, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 62, Local-gov, 68268, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 174533, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 273230, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 25, Private, 187502, HS-grad, 9, Never-married, Sales, Own-child, Black, Male, 0, 0, 24, United-States, <=50K 47, Private, 209320, HS-grad, 9, Separated, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 49, Self-emp-not-inc, 56841, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 70, United-States, <=50K 55, Private, 254627, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 42703, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 374137, HS-grad, 9, Divorced, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 196385, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 192930, HS-grad, 9, Separated, Sales, Unmarried, White, Female, 0, 0, 10, United-States, <=50K 39, Private, 99527, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 45, Private, 185437, Assoc-acdm, 12, Divorced, Craft-repair, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 43, Private, 247162, Assoc-acdm, 12, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 32, Federal-gov, 131534, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 18, Private, 184693, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, Mexico, <=50K 27, Private, 704108, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 220262, Assoc-acdm, 12, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 95654, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 60, United-States, <=50K 67, Private, 89346, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 94392, 11th, 7, Separated, Other-service, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 21, Private, 334113, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 32763, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 15, United-States, <=50K 31, Private, 136651, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Mexico, <=50K 51, Self-emp-not-inc, 240236, Assoc-acdm, 12, Separated, Sales, Not-in-family, Black, Male, 0, 0, 30, United-States, <=50K 29, Private, 53271, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 31493, Bachelors, 13, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, >50K 32, Private, 195891, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 31, Local-gov, 209103, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 3464, 0, 45, United-States, <=50K 26, Private, 211424, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Local-gov, 84657, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 151408, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 106819, 7th-8th, 4, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 19, United-States, <=50K 62, Private, 132917, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 20, United-States, <=50K 54, Private, 146834, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 60, United-States, <=50K 55, Private, 164332, HS-grad, 9, Separated, Other-service, Not-in-family, White, Female, 0, 0, 16, United-States, <=50K 24, Private, 30656, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 27, Private, 113501, Masters, 14, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 45, United-States, <=50K 18, Private, 165316, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 30, United-States, <=50K 22, Private, 233955, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Amer-Indian-Eskimo, Female, 14344, 0, 40, United-States, >50K 21, Private, 126613, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 44, Self-emp-not-inc, 361280, Some-college, 10, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 0, 80, Philippines, >50K 50, ?, 123044, Masters, 14, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 60, United-States, >50K 38, Private, 165472, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 99452, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 27, Private, 84977, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 240458, 11th, 7, Divorced, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 51, Private, 230858, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1977, 60, United-States, >50K 60, Private, 123218, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 62, ?, 191118, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 7298, 0, 40, United-States, >50K 38, Private, 115289, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 373895, Some-college, 10, Separated, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 35, United-States, <=50K 43, Private, 152617, Some-college, 10, Divorced, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 49, State-gov, 72619, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 17, Private, 41865, 10th, 6, Never-married, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 32, Private, 190228, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 23, Private, 193090, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 28, Private, 138692, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1887, 40, United-States, >50K 83, Self-emp-inc, 153183, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 2392, 55, United-States, >50K 25, Private, 181896, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 268183, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1485, 60, United-States, <=50K 46, Local-gov, 213668, 11th, 7, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 99369, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Other, Female, 0, 0, 50, United-States, <=50K 44, Private, 104196, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 60, Self-emp-not-inc, 176839, Prof-school, 15, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 30, Local-gov, 99502, Assoc-voc, 11, Divorced, Protective-serv, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 24, Private, 183410, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 17, United-States, <=50K 17, Private, 25690, 10th, 6, Never-married, Other-service, Own-child, White, Female, 0, 0, 10, United-States, <=50K 76, ?, 201986, 11th, 7, Widowed, ?, Other-relative, White, Female, 0, 0, 16, United-States, <=50K 31, Private, 188961, Assoc-acdm, 12, Never-married, Tech-support, Own-child, White, Female, 0, 0, 40, United-States, <=50K 52, Private, 114971, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 121468, Bachelors, 13, Never-married, Exec-managerial, Own-child, Asian-Pac-Islander, Female, 0, 0, 35, United-States, <=50K 73, Self-emp-inc, 191540, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 38, Private, 146398, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 24, United-States, <=50K 48, Private, 193553, HS-grad, 9, Divorced, Other-service, Not-in-family, Black, Female, 0, 0, 20, United-States, <=50K 60, Private, 121127, 10th, 6, Widowed, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 389856, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 290504, HS-grad, 9, Never-married, Other-service, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 54, State-gov, 137065, Doctorate, 16, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 50, Local-gov, 212685, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 40, United-States, <=50K 20, Private, 71475, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 111450, Some-college, 10, Never-married, Adm-clerical, Other-relative, Black, Male, 0, 0, 22, United-States, <=50K 35, Private, 225860, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 43, Private, 129853, 10th, 6, Never-married, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 50, Private, 99925, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 32, United-States, <=50K 58, Private, 227800, 1st-4th, 2, Separated, Farming-fishing, Not-in-family, Black, Male, 0, 0, 50, United-States, <=50K 55, State-gov, 111130, Assoc-acdm, 12, Divorced, Adm-clerical, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 29, Private, 100764, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 47, Private, 275095, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 147500, HS-grad, 9, Married-civ-spouse, Prof-specialty, Wife, Black, Female, 0, 0, 40, United-States, <=50K 63, Local-gov, 150079, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 35, United-States, >50K 27, Private, 140863, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 62, ?, 199198, 11th, 7, Divorced, ?, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 38, Private, 193372, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 196771, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 31, Private, 231826, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 52, Mexico, <=50K 40, Federal-gov, 196456, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 34037, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 52, Private, 174964, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Private, 91608, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 403468, Some-college, 10, Separated, Other-service, Unmarried, White, Female, 0, 0, 50, Mexico, <=50K 33, Private, 112900, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 58, Private, 242670, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 52, Local-gov, 187830, HS-grad, 9, Divorced, Tech-support, Unmarried, White, Male, 4934, 0, 36, United-States, >50K 25, Self-emp-not-inc, 368115, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 13550, 0, 35, United-States, >50K 54, Private, 343242, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Private, 113390, Masters, 14, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 1740, 60, United-States, <=50K 28, Private, 200733, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Self-emp-not-inc, 236769, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 22494, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 60, Federal-gov, 129379, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 239098, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 167501, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 77146, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 47, Private, 82797, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 33, Self-emp-not-inc, 134886, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 50, United-States, >50K 40, Self-emp-inc, 218558, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 38, Private, 207568, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 5178, 0, 40, United-States, >50K 26, Private, 196899, Assoc-acdm, 12, Separated, Craft-repair, Not-in-family, Other, Female, 0, 0, 40, United-States, <=50K 54, Self-emp-not-inc, 200960, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 39, Private, 188069, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, ?, <=50K 60, Private, 232337, 7th-8th, 4, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 98656, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 19, State-gov, 194260, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 15, United-States, <=50K 49, ?, 481987, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 60, United-States, <=50K 31, Private, 234976, 11th, 7, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 48, United-States, <=50K 29, Private, 349116, HS-grad, 9, Separated, Sales, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 39, Private, 175390, HS-grad, 9, Never-married, Sales, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 42, Private, 187720, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 50, ?, >50K 26, Private, 214637, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 27, Private, 185127, Assoc-voc, 11, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 98752, 9th, 5, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 50, Local-gov, 218382, Some-college, 10, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 51, Private, 153486, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, >50K 51, Federal-gov, 174102, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Private, 137142, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 61, Private, 241013, 7th-8th, 4, Widowed, Farming-fishing, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 35, Private, 267798, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 41, ?, 152880, HS-grad, 9, Divorced, ?, Not-in-family, Black, Female, 0, 0, 28, United-States, <=50K 31, Private, 263561, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 43, Private, 113324, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1902, 40, United-States, >50K 20, Private, 39764, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 172186, Some-college, 10, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 460408, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 1672, 45, United-States, <=50K 42, Self-emp-not-inc, 185129, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1887, 40, United-States, >50K 51, Private, 61270, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Self-emp-inc, 124685, Masters, 14, Divorced, Exec-managerial, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 99, Japan, >50K 69, Self-emp-not-inc, 76968, 9th, 5, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 25, United-States, <=50K 63, ?, 310396, 9th, 5, Married-civ-spouse, ?, Husband, White, Male, 5178, 0, 40, United-States, >50K 29, Federal-gov, 37933, Some-college, 10, Never-married, Adm-clerical, Unmarried, Black, Female, 2174, 0, 40, United-States, <=50K 21, Private, 38772, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 20, United-States, <=50K 24, Private, 172496, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 55, Private, 306164, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 40, United-States, <=50K 42, Self-emp-not-inc, 33795, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 48, Private, 47686, 11th, 7, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 193132, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 42, United-States, <=50K 52, Private, 400004, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Private, 101283, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 192384, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 113838, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 278322, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 40, United-States, >50K 56, Private, 199713, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 236021, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 138938, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 10, United-States, <=50K 36, Private, 126946, Some-college, 10, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 44791, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 31964, 9th, 5, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 60, State-gov, 352156, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 70, Self-emp-not-inc, 205860, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, United-States, <=50K 21, Private, 113106, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 57, Private, 89182, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 250782, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, <=50K 37, Private, 193855, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1902, 50, United-States, <=50K 50, Self-emp-not-inc, 132716, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 50, United-States, >50K 68, Private, 218637, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 2377, 55, United-States, >50K 28, Private, 177955, 11th, 7, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, Mexico, <=50K 32, Private, 198660, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 207937, Prof-school, 15, Divorced, Prof-specialty, Not-in-family, White, Male, 10520, 0, 50, United-States, >50K 18, Private, 168740, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 30, United-States, <=50K 45, Private, 199625, Some-college, 10, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 22, Private, 213902, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 38, Private, 208379, Bachelors, 13, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 8, United-States, <=50K 37, Private, 113120, Assoc-voc, 11, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 57827, Bachelors, 13, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 59, Private, 515712, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Self-emp-inc, 54190, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 40, United-States, >50K 53, Self-emp-inc, 134793, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 18, Private, 396270, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 25, United-States, <=50K 30, Private, 231620, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, Mexico, <=50K 50, Private, 174655, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 63, ?, 97823, 11th, 7, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Self-emp-not-inc, 344480, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 4064, 0, 40, United-States, <=50K 48, Private, 176732, 9th, 5, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 60, Private, 143932, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 551962, HS-grad, 9, Separated, Handlers-cleaners, Unmarried, White, Female, 0, 0, 50, Peru, <=50K 30, ?, 298577, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 0, 30, United-States, <=50K 39, Private, 257942, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 55, Local-gov, 253062, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 17, Private, 193748, 11th, 7, Never-married, Sales, Own-child, White, Male, 0, 0, 15, United-States, <=50K 46, Private, 368561, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, >50K 50, Private, 192964, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 65, United-States, <=50K 32, Private, 217304, Bachelors, 13, Never-married, Protective-serv, Not-in-family, Black, Male, 0, 0, 30, United-States, <=50K 18, Private, 120029, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 62124, HS-grad, 9, Separated, Other-service, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 50, Private, 94885, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 32, Private, 192565, 11th, 7, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, <=50K 23, Local-gov, 220912, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 26, Private, 184120, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 46, Private, 140782, Assoc-acdm, 12, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 43, Self-emp-inc, 170785, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, <=50K 32, Private, 90705, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, >50K 37, State-gov, 108293, Assoc-acdm, 12, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 48, Private, 168283, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, >50K 28, Private, 339372, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 1408, 40, United-States, <=50K 43, Private, 193672, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Local-gov, 143865, 10th, 6, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 24, United-States, <=50K 30, Private, 209317, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 50, Dominican-Republic, <=50K 34, State-gov, 204461, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 34, Private, 137088, HS-grad, 9, Married-civ-spouse, Craft-repair, Other-relative, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 41, Private, 149102, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 53, Private, 182855, 10th, 6, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 48, United-States, <=50K 42, Private, 572751, Preschool, 1, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Nicaragua, <=50K 18, Private, 83451, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 81, Private, 98116, Bachelors, 13, Widowed, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 40, Private, 119225, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 134888, Bachelors, 13, Never-married, Tech-support, Own-child, White, Female, 0, 0, 35, United-States, <=50K 20, Private, 745817, Some-college, 10, Never-married, Tech-support, Own-child, White, Female, 0, 0, 15, United-States, <=50K 41, Private, 88368, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 49, State-gov, 122066, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 22, Private, 363219, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 46, Private, 84402, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 56, Private, 34626, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 1980, 40, United-States, <=50K 35, Private, 150042, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 34, Private, 48014, Bachelors, 13, Separated, Exec-managerial, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 29, Local-gov, 177398, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 28, Private, 373698, 12th, 8, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, ?, <=50K 35, Private, 422933, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 37, United-States, <=50K 29, Private, 131088, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 178255, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 30, Columbia, <=50K 52, Self-emp-not-inc, 129311, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 95, United-States, >50K 45, Private, 473171, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 236985, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 35, ?, 226379, HS-grad, 9, Married-civ-spouse, ?, Other-relative, White, Female, 0, 0, 25, United-States, <=50K 21, ?, 277700, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 20, United-States, <=50K 35, Private, 207568, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 85708, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 98765, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, Canada, <=50K 29, Private, 192283, Some-college, 10, Never-married, Other-service, Other-relative, White, Female, 0, 0, 20, United-States, <=50K 29, State-gov, 271012, 10th, 6, Never-married, Other-service, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 33, Private, 189265, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 17, Private, 321880, 10th, 6, Never-married, Other-service, Own-child, Black, Male, 0, 0, 15, United-States, <=50K 52, Private, 177465, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 24, Private, 127647, Some-college, 10, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 32, State-gov, 119033, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Private, 289748, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 4650, 0, 48, United-States, <=50K 32, Private, 209317, HS-grad, 9, Separated, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, ?, <=50K 33, Private, 284531, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 251120, 7th-8th, 4, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 28, Private, 113870, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 62, Without-pay, 170114, Assoc-acdm, 12, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 46, Local-gov, 121124, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 15024, 0, 40, United-States, >50K 32, Private, 328199, Assoc-voc, 11, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 64, United-States, <=50K 26, Private, 206307, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Self-emp-inc, 236021, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 40, United-States, >50K 57, Federal-gov, 170603, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 52, Private, 74275, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 7298, 0, 45, United-States, >50K 35, Self-emp-not-inc, 112271, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 19, Private, 118306, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 16, United-States, <=50K 49, Private, 126754, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 47, Private, 267205, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, ?, >50K 38, Private, 205359, 11th, 7, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 32, United-States, <=50K 30, Private, 398662, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 202498, 11th, 7, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Columbia, <=50K 32, Private, 105650, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 50, United-States, >50K 46, Private, 191204, Assoc-voc, 11, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 56582, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 47, Local-gov, 51579, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 50, United-States, <=50K 57, Self-emp-not-inc, 152030, Some-college, 10, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 25, United-States, >50K 47, Private, 227310, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 41, Private, 55854, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 56, United-States, >50K 36, Local-gov, 28996, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 160634, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 37, Private, 222450, 11th, 7, Married-spouse-absent, Other-service, Other-relative, White, Male, 0, 0, 40, El-Salvador, <=50K 36, Self-emp-inc, 180419, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 45, United-States, <=50K 64, Private, 116084, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 2635, 0, 40, United-States, <=50K 17, Private, 202521, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 15, United-States, <=50K 23, Private, 186014, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 15, United-States, <=50K 40, Private, 88368, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 914, 0, 40, United-States, <=50K 42, State-gov, 190044, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 37, Self-emp-not-inc, 35330, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 42, United-States, <=50K 35, Federal-gov, 84848, Some-college, 10, Never-married, Handlers-cleaners, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 56, Self-emp-not-inc, 176280, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 52, Private, 145271, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 37, Local-gov, 108320, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 45, United-States, >50K 48, State-gov, 106377, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 65, United-States, >50K 24, Private, 258730, HS-grad, 9, Divorced, Other-service, Own-child, White, Female, 0, 0, 40, Japan, <=50K 33, Private, 58305, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 341672, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 34, Private, 176648, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, Black, Male, 0, 0, 42, United-States, <=50K 24, ?, 32616, Bachelors, 13, Divorced, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 481175, Some-college, 10, Never-married, Exec-managerial, Own-child, Other, Male, 0, 0, 24, Peru, <=50K 49, Private, 187454, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 99999, 0, 65, United-States, >50K 18, Private, 25837, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 20, Private, 385077, 12th, 8, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 68985, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, >50K 19, Private, 181572, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 23698, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 46, United-States, >50K 34, ?, 268127, 12th, 8, Separated, ?, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 28, Private, 162298, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 144608, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 250630, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 31, Private, 150441, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 37, Private, 189251, Doctorate, 16, Separated, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 64, Private, 260082, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Columbia, <=50K 42, Private, 139126, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 50132, Some-college, 10, Divorced, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 36, Self-emp-not-inc, 167691, Some-college, 10, Never-married, Other-service, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 36, Private, 77820, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Private, 156513, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 46, Private, 248059, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 3464, 0, 40, United-States, <=50K 24, Private, 283092, 11th, 7, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 35, Jamaica, <=50K 22, Private, 175883, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 62, Private, 232308, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 19, Private, 269991, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, Puerto-Rico, <=50K 20, Private, 305446, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, United-States, <=50K 47, Private, 120781, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 15024, 0, 40, ?, >50K 57, Private, 78707, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 351802, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 35, United-States, <=50K 37, Local-gov, 196529, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 45, United-States, >50K 35, Self-emp-inc, 175769, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 65, United-States, >50K 17, Private, 153021, 12th, 8, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 36, Local-gov, 331902, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 50, Private, 279461, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 145704, HS-grad, 9, Married-civ-spouse, Prof-specialty, Wife, White, Female, 3942, 0, 35, United-States, <=50K 27, State-gov, 205499, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 77, United-States, <=50K 28, Private, 293926, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1740, 30, United-States, <=50K 29, Self-emp-not-inc, 69132, Prof-school, 15, Divorced, Prof-specialty, Not-in-family, White, Male, 99999, 0, 60, United-States, >50K 25, Private, 113099, HS-grad, 9, Separated, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 47, Self-emp-inc, 206947, Assoc-acdm, 12, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 67, United-States, <=50K 29, State-gov, 159782, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 45, United-States, >50K 19, Private, 410543, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 34446, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 209101, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 25, United-States, >50K 43, Federal-gov, 95902, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Wife, Black, Female, 0, 0, 40, United-States, <=50K 56, Self-emp-not-inc, 214323, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 236323, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 45, Federal-gov, 201127, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 56, United-States, >50K 40, Private, 142886, Bachelors, 13, Widowed, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 77313, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 17, ?, 212125, 10th, 6, Never-married, ?, Own-child, White, Female, 0, 0, 20, United-States, <=50K 36, Private, 187098, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 196857, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 53, Local-gov, 155314, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 72, Self-emp-not-inc, 203289, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 46, Private, 117059, Assoc-voc, 11, Married-civ-spouse, Transport-moving, Husband, Amer-Indian-Eskimo, Male, 0, 0, 60, United-States, <=50K 33, Private, 178587, Some-college, 10, Separated, Prof-specialty, Unmarried, White, Female, 0, 0, 37, United-States, <=50K 22, Private, 82393, 9th, 5, Never-married, Handlers-cleaners, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 17, ?, 145258, 11th, 7, Never-married, ?, Other-relative, White, Female, 0, 0, 25, United-States, <=50K 41, Private, 185145, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 45, ?, >50K 46, Private, 72896, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 43, United-States, <=50K 33, Private, 134886, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 32, Private, 223212, Preschool, 1, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 52, Self-emp-not-inc, 174752, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 230563, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 48, State-gov, 353824, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 72, United-States, >50K 22, Private, 117363, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 25, Private, 285367, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 60, ?, 139391, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 42, United-States, <=50K 38, Private, 198170, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 38948, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 49, Private, 188515, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 40, Self-emp-not-inc, 177810, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 30, United-States, <=50K 48, Private, 188432, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 3103, 0, 46, United-States, >50K 31, Private, 178506, Some-college, 10, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 40, Self-emp-not-inc, 129298, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 45, United-States, <=50K 25, Private, 165315, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 37, United-States, <=50K 68, Private, 117236, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 20051, 0, 45, United-States, >50K 18, ?, 172214, HS-grad, 9, Never-married, ?, Own-child, Black, Female, 0, 0, 20, United-States, <=50K 19, Private, 63434, 12th, 8, Never-married, Farming-fishing, Own-child, White, Female, 0, 0, 30, United-States, <=50K 35, Self-emp-inc, 140854, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 28, Private, 133043, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 53, Private, 113176, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 2597, 0, 40, United-States, <=50K 33, Private, 259301, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 41, United-States, <=50K 20, Private, 196643, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 45, Self-emp-not-inc, 364365, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 36, Private, 269318, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 34, Private, 108454, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 32, Private, 171637, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 183589, Some-college, 10, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 25, United-States, <=50K 24, Private, 107801, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 179877, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Private, 168981, HS-grad, 9, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 35, United-States, <=50K 37, Private, 120590, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 31, Private, 310773, Some-college, 10, Separated, Sales, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 21, Private, 197050, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 35, United-States, <=50K 47, Private, 159726, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 85, United-States, >50K 23, Private, 210797, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 55291, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 60, ?, 141221, Bachelors, 13, Married-civ-spouse, ?, Husband, Asian-Pac-Islander, Male, 0, 2163, 25, South, <=50K 17, Private, 276718, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 20, United-States, <=50K 67, Private, 336163, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 24, United-States, <=50K 57, Private, 112840, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 17, Private, 165918, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, Peru, <=50K 53, Private, 165745, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Self-emp-not-inc, 259299, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 3103, 0, 50, United-States, >50K 24, State-gov, 197731, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 49, United-States, >50K 48, Self-emp-not-inc, 197702, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 162238, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1887, 47, United-States, >50K 38, Private, 213260, HS-grad, 9, Separated, Protective-serv, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 51, Private, 53833, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 46, United-States, >50K 18, Private, 89419, HS-grad, 9, Never-married, Tech-support, Own-child, White, Female, 0, 0, 10, United-States, <=50K 23, Private, 119704, Some-college, 10, Separated, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 433170, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, >50K 34, Private, 182714, HS-grad, 9, Separated, Other-service, Not-in-family, White, Female, 0, 0, 35, ?, <=50K 39, Private, 172538, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 20, ?, 220115, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 0, 12, United-States, <=50K 39, Private, 158956, Some-college, 10, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 21, Self-emp-not-inc, 25631, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 476558, 7th-8th, 4, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 54, Federal-gov, 35576, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 203463, Some-college, 10, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 32, State-gov, 317647, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 59, Self-emp-not-inc, 170411, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, ?, 174182, 11th, 7, Married-civ-spouse, ?, Wife, Other, Female, 0, 0, 24, United-States, <=50K 54, Private, 220055, Bachelors, 13, Widowed, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 54, Private, 231482, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 67, Private, 335979, HS-grad, 9, Widowed, Sales, Not-in-family, White, Female, 991, 0, 18, United-States, <=50K 33, Private, 279173, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 37, Private, 89559, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 161950, Bachelors, 13, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 25, Germany, <=50K 51, Private, 131068, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 219632, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 175507, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 58, Self-emp-inc, 182062, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 24, United-States, >50K 27, Private, 287476, HS-grad, 9, Never-married, Craft-repair, Not-in-family, Black, Male, 3325, 0, 40, United-States, <=50K 36, Private, 206253, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 1617, 40, United-States, <=50K 20, ?, 189203, Assoc-acdm, 12, Never-married, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 21698, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, Self-emp-not-inc, 328051, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 32, Private, 356689, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Male, 3887, 0, 40, United-States, <=50K 59, Private, 121865, HS-grad, 9, Divorced, Other-service, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 45, Self-emp-not-inc, 420986, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 43, ?, 218558, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 288992, 10th, 6, Divorced, Prof-specialty, Unmarried, White, Male, 14344, 0, 68, United-States, >50K 20, ?, 189740, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 32, United-States, <=50K 29, Local-gov, 188909, Bachelors, 13, Never-married, Prof-specialty, Own-child, Black, Female, 0, 0, 42, United-States, <=50K 28, Private, 213081, 11th, 7, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 40, Jamaica, <=50K 18, Self-emp-not-inc, 157131, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 98010, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 46, Private, 207677, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 58, ?, 361870, HS-grad, 9, Married-civ-spouse, ?, Husband, Black, Male, 0, 0, 30, United-States, <=50K 56, Private, 266091, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, Mexico, <=50K 41, Private, 106627, Assoc-acdm, 12, Divorced, Exec-managerial, Unmarried, Black, Female, 0, 0, 50, United-States, <=50K 50, Self-emp-inc, 167793, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 2415, 60, United-States, >50K 74, Self-emp-not-inc, 206682, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1648, 35, United-States, <=50K 30, Private, 243165, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 62, Private, 201928, HS-grad, 9, Widowed, Craft-repair, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 19, Private, 128346, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 197288, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 0, 40, United-States, <=50K 20, ?, 169184, Some-college, 10, Never-married, ?, Other-relative, Black, Female, 0, 0, 40, United-States, <=50K 36, Private, 245521, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 35, Mexico, <=50K 36, Private, 129591, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 51, Local-gov, 47415, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 1628, 30, United-States, <=50K 37, Self-emp-not-inc, 188563, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 4386, 0, 50, United-States, >50K 29, Self-emp-not-inc, 184710, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 63734, 10th, 6, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, United-States, <=50K 18, Private, 111256, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 40, Self-emp-inc, 111483, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 26, Self-emp-inc, 266639, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Self-emp-not-inc, 93853, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 32, Private, 184207, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 238002, 9th, 5, Married-civ-spouse, Transport-moving, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 28, ?, 30237, Some-college, 10, Never-married, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 196545, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 1902, 40, United-States, >50K 47, Private, 144844, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 280500, Some-college, 10, Never-married, Tech-support, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 73, ?, 135601, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 10, United-States, <=50K 37, Private, 409189, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 30, Mexico, <=50K 50, Private, 23686, Some-college, 10, Married-civ-spouse, Adm-clerical, Other-relative, White, Female, 0, 0, 35, United-States, >50K 19, Private, 229756, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 50, United-States, <=50K 32, Local-gov, 95530, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Local-gov, 73199, Assoc-voc, 11, Divorced, Tech-support, Unmarried, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 20, Private, 196745, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 16, United-States, <=50K 29, Private, 79481, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, ?, 116934, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 100950, Assoc-voc, 11, Never-married, Prof-specialty, Unmarried, White, Female, 0, 0, 40, Germany, <=50K 44, Local-gov, 56651, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 52, United-States, <=50K 18, Private, 186954, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 22, Private, 264874, Some-college, 10, Never-married, Tech-support, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 39, State-gov, 183092, Doctorate, 16, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 26, Local-gov, 273399, Some-college, 10, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 40, Peru, <=50K 29, ?, 142443, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 25, United-States, <=50K 21, Private, 177526, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 49, Local-gov, 31267, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 24, Private, 321666, Assoc-acdm, 12, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 20, United-States, <=50K 26, Private, 331861, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 60, ?, <=50K 25, Private, 283515, Some-college, 10, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 30, Private, 54608, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 162238, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 38, United-States, >50K 30, Private, 175931, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 236804, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 168782, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 227065, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Self-emp-inc, 285335, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 31, Private, 259705, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Female, 0, 0, 40, United-States, <=50K 57, Private, 24384, 7th-8th, 4, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 10, United-States, <=50K 58, Private, 322013, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 49797, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 52566, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 266275, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 72, Self-emp-not-inc, 285408, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 2246, 28, United-States, >50K 26, Self-emp-not-inc, 177858, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 1876, 38, United-States, <=50K 45, Federal-gov, 183804, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 107231, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 50, United-States, >50K 23, Private, 173679, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, Local-gov, 163965, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 18, Private, 173585, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 15, Peru, <=50K 27, Private, 172009, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 44363, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 45, Private, 246392, HS-grad, 9, Never-married, Priv-house-serv, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 53, Private, 167033, Some-college, 10, Never-married, Exec-managerial, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 54, Private, 143822, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 41, Private, 37869, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 1902, 40, United-States, >50K 23, Private, 447488, 9th, 5, Never-married, Machine-op-inspct, Other-relative, White, Male, 0, 0, 35, Mexico, <=50K 17, Private, 239346, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 18, United-States, <=50K 42, Private, 245975, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 34632, 12th, 8, Married-spouse-absent, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 121362, Some-college, 10, Widowed, Adm-clerical, Unmarried, White, Female, 0, 2258, 38, United-States, >50K 21, State-gov, 24008, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 35, United-States, <=50K 44, Private, 165492, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 48, Private, 326048, Assoc-acdm, 12, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 44, United-States, <=50K 46, Private, 250821, Prof-school, 15, Divorced, Farming-fishing, Unmarried, White, Male, 0, 0, 48, United-States, <=50K 37, Self-emp-not-inc, 154641, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 86, United-States, <=50K 35, Private, 198202, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 54, United-States, <=50K 27, Local-gov, 170504, Bachelors, 13, Never-married, Transport-moving, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 191342, Some-college, 10, Never-married, Sales, Not-in-family, Other, Male, 0, 0, 40, India, <=50K 19, Private, 238969, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 10, United-States, <=50K 63, Self-emp-not-inc, 344128, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 69, ?, 148694, HS-grad, 9, Divorced, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 69, ?, 180187, Assoc-acdm, 12, Widowed, ?, Not-in-family, White, Female, 0, 0, 6, Italy, <=50K 36, State-gov, 168894, Assoc-voc, 11, Married-spouse-absent, Protective-serv, Own-child, White, Female, 0, 0, 40, Germany, <=50K 20, Private, 203263, 12th, 8, Never-married, Other-service, Own-child, White, Male, 0, 0, 35, United-States, <=50K 28, State-gov, 89564, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 50, United-States, <=50K 58, Private, 97562, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 38, United-States, <=50K 48, Private, 336540, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 139647, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 56, United-States, <=50K 38, Private, 160192, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 2051, 44, United-States, <=50K 50, Local-gov, 320386, Assoc-acdm, 12, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 32126, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, Self-emp-not-inc, 275445, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 38, Self-emp-inc, 54953, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 38, United-States, <=50K 54, Private, 103580, Assoc-acdm, 12, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 55, United-States, >50K 42, Private, 245565, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 12, England, <=50K 32, Private, 39223, 10th, 6, Separated, Craft-repair, Unmarried, Black, Female, 0, 0, 40, ?, <=50K 55, State-gov, 117357, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 70, ?, >50K 63, Private, 207385, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 30, United-States, <=50K 21, Private, 355287, 9th, 5, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 48, Mexico, <=50K 62, ?, 141218, Masters, 14, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 30, United-States, >50K 46, Local-gov, 207677, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 43, Private, 102114, Some-college, 10, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 35, Self-emp-not-inc, 60269, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 37, Private, 278632, 9th, 5, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 355551, HS-grad, 9, Never-married, Craft-repair, Unmarried, White, Female, 0, 0, 45, Mexico, <=50K 45, Private, 246891, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 72, Canada, >50K 19, Private, 124486, 12th, 8, Never-married, Other-service, Own-child, White, Male, 0, 1602, 20, United-States, <=50K 61, ?, 202106, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 1902, 40, United-States, >50K 61, Private, 191417, 9th, 5, Widowed, Exec-managerial, Not-in-family, Black, Male, 0, 0, 65, United-States, <=50K 21, Private, 184543, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 122206, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 229015, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 28, Private, 130067, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 40, Local-gov, 306495, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, <=50K 32, Private, 232855, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 55, Local-gov, 171328, Some-college, 10, Married-spouse-absent, Adm-clerical, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 64, Private, 144182, HS-grad, 9, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 23, United-States, <=50K 34, Private, 102858, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 19, ?, 199495, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 60, United-States, <=50K 58, Private, 209438, Some-college, 10, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 46, Private, 74895, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1485, 55, United-States, <=50K 44, Private, 184378, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 446512, Some-college, 10, Separated, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 31, Federal-gov, 113688, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 333305, Some-college, 10, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 45, United-States, >50K 19, Private, 118535, 12th, 8, Never-married, Sales, Own-child, White, Female, 0, 0, 18, United-States, <=50K 56, Private, 76142, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 53, Local-gov, 38795, 9th, 5, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 68, Private, 208478, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 18, ?, <=50K 69, Private, 203313, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Female, 991, 0, 18, United-States, <=50K 62, Private, 247483, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 62, State-gov, 198686, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 56118, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 45, Federal-gov, 359808, Assoc-acdm, 12, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 231554, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 50, United-States, <=50K 33, Private, 34848, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 199934, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 7298, 0, 40, United-States, >50K 29, Private, 196243, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 65, Self-emp-inc, 66360, 11th, 7, Married-civ-spouse, Exec-managerial, Husband, White, Male, 6418, 0, 35, United-States, >50K 18, Private, 189487, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 35, United-States, <=50K 22, Private, 194848, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 167309, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 1902, 40, United-States, >50K 44, Private, 192878, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 48, Private, 70209, Some-college, 10, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 52, Federal-gov, 123011, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 53, Self-emp-not-inc, 135339, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 7688, 0, 20, China, >50K 48, Federal-gov, 497486, HS-grad, 9, Married-spouse-absent, Adm-clerical, Unmarried, White, Female, 1471, 0, 40, United-States, <=50K 25, Private, 178478, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 149909, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 50, United-States, >50K 37, Private, 103323, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 239404, 10th, 6, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 45, United-States, <=50K 67, Private, 165082, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 36, Private, 389725, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 47, Private, 374580, HS-grad, 9, Separated, Sales, Not-in-family, White, Female, 0, 0, 52, United-States, <=50K 36, ?, 187983, HS-grad, 9, Never-married, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 259300, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 16, United-States, <=50K 19, Private, 277695, 9th, 5, Never-married, Farming-fishing, Other-relative, White, Male, 0, 0, 16, Mexico, <=50K 24, Private, 230248, 7th-8th, 4, Separated, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 30, Self-emp-not-inc, 196342, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 25, United-States, <=50K 17, Private, 160968, 11th, 7, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 16, United-States, <=50K 28, Private, 115438, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 231043, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Husband, White, Male, 3908, 0, 45, United-States, <=50K 35, Private, 129597, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 46, United-States, <=50K 24, Local-gov, 387108, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 40, United-States, <=50K 43, Private, 105936, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 35, United-States, >50K 20, Private, 107242, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 40, ?, <=50K 55, Private, 125000, Masters, 14, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 40, United-States, >50K 22, Private, 229456, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 35, United-States, <=50K 20, Private, 230113, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 50, United-States, <=50K 44, Private, 106698, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 133454, Assoc-acdm, 12, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 295520, 9th, 5, Widowed, Sales, Unmarried, Black, Female, 0, 0, 25, United-States, <=50K 26, Private, 151551, Some-college, 10, Separated, Sales, Own-child, Amer-Indian-Eskimo, Male, 2597, 0, 48, United-States, <=50K 58, Private, 100313, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 1902, 40, United-States, >50K 23, Private, 320294, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 162381, 1st-4th, 2, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 35, Private, 183898, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 2354, 0, 40, United-States, <=50K 41, Self-emp-inc, 32016, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 62, United-States, <=50K 31, Private, 117028, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 280278, HS-grad, 9, Widowed, Prof-specialty, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 57, Private, 342906, 9th, 5, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 55, United-States, >50K 25, Private, 181598, 11th, 7, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 224059, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 148549, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 34, Private, 97355, Some-college, 10, Divorced, Sales, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 37, Private, 154571, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, ?, <=50K 43, Self-emp-inc, 140988, Bachelors, 13, Married-civ-spouse, Sales, Other-relative, Asian-Pac-Islander, Male, 0, 0, 45, India, <=50K 20, Private, 148409, Some-college, 10, Never-married, Sales, Other-relative, White, Male, 1055, 0, 20, United-States, <=50K 40, Local-gov, 150755, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 75, United-States, >50K 27, Private, 87006, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 1579, 40, United-States, <=50K 35, Private, 112158, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 121488, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 57, State-gov, 283635, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 69758, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 40, Private, 199900, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1848, 55, United-States, >50K 54, Private, 88019, Some-college, 10, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 28, Private, 31935, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 323055, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 189498, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 52, Private, 89041, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 112507, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 19, Private, 236940, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 278514, HS-grad, 9, Divorced, Craft-repair, Own-child, White, Female, 0, 0, 42, United-States, <=50K 21, ?, 433330, Some-college, 10, Never-married, ?, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 258379, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 32, United-States, <=50K 44, Private, 162028, 11th, 7, Divorced, Sales, Unmarried, White, Female, 0, 0, 44, United-States, <=50K 20, Private, 197997, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 98350, 10th, 6, Married-spouse-absent, Other-service, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 37, China, <=50K 39, Private, 165848, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 34, Private, 178615, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 228939, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 35, United-States, <=50K 27, Private, 210498, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 5178, 0, 40, United-States, >50K 53, Private, 154891, 9th, 5, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 165937, Assoc-voc, 11, Divorced, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 23, ?, 138768, Bachelors, 13, Never-married, ?, Own-child, White, Male, 2907, 0, 40, United-States, <=50K 39, Private, 160120, Some-college, 10, Never-married, Machine-op-inspct, Other-relative, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 30, Private, 382368, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 123011, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 33, Private, 119033, 9th, 5, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 496856, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 194049, Some-college, 10, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 30, Private, 299223, Some-college, 10, Divorced, Sales, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 66, Private, 174788, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 39, Private, 176101, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 38948, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 34, Private, 271933, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Wife, White, Female, 0, 0, 40, United-States, <=50K 17, Private, 122041, 11th, 7, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 20, United-States, <=50K 43, Private, 115932, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 46, Private, 265105, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 17, Private, 100828, 11th, 7, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 60, Private, 121319, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 3137, 0, 40, Poland, <=50K 63, Private, 308028, Masters, 14, Married-civ-spouse, Tech-support, Husband, White, Male, 5013, 0, 40, United-States, <=50K 42, Private, 213214, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 348618, 9th, 5, Married-civ-spouse, Craft-repair, Husband, Other, Male, 0, 0, 40, Mexico, <=50K 33, Private, 275632, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 239161, Some-college, 10, Married-civ-spouse, Sales, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 20, Private, 215495, 9th, 5, Never-married, Exec-managerial, Other-relative, White, Female, 0, 0, 40, Mexico, <=50K 30, Private, 214063, Some-college, 10, Never-married, Farming-fishing, Other-relative, Black, Male, 0, 0, 72, United-States, <=50K 37, Private, 122493, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 33, ?, 211699, Some-college, 10, Divorced, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 49, Self-emp-not-inc, 175622, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 65, Private, 153522, HS-grad, 9, Widowed, Other-service, Unmarried, White, Female, 0, 0, 17, United-States, <=50K 35, Private, 258339, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 27, Private, 119793, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 133503, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 1977, 45, United-States, >50K 18, Private, 162840, 12th, 8, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 41, Local-gov, 67671, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 38, Private, 188888, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 1340, 40, United-States, <=50K 45, Private, 140644, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, ?, 126154, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 245659, Some-college, 10, Separated, Other-service, Unmarried, White, Female, 0, 0, 38, El-Salvador, <=50K 28, Private, 129624, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, ?, <=50K 47, Private, 104068, HS-grad, 9, Divorced, Prof-specialty, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 30, Private, 337908, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 0, 20, United-States, <=50K 36, Private, 161141, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 162228, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 30, United-States, <=50K 44, Private, 116391, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 314310, HS-grad, 9, Married-spouse-absent, Sales, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 61, ?, 394534, HS-grad, 9, Married-civ-spouse, ?, Husband, Black, Male, 0, 0, 6, United-States, <=50K 29, Private, 308136, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 194698, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 18, ?, 67793, HS-grad, 9, Never-married, ?, Own-child, White, Female, 0, 0, 60, United-States, <=50K 29, Local-gov, 302422, Assoc-voc, 11, Never-married, Protective-serv, Not-in-family, White, Male, 0, 1564, 56, United-States, >50K 27, Private, 289147, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 229826, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 20, United-States, <=50K 22, ?, 154235, Some-college, 10, Married-civ-spouse, ?, Wife, White, Female, 3781, 0, 35, United-States, <=50K 49, Self-emp-inc, 246739, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 35, Private, 188041, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 47, Private, 187440, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 5178, 0, 40, United-States, >50K 37, Local-gov, 105266, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 249208, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 48, United-States, >50K 26, Private, 203492, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 18, ?, 71076, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 55, Federal-gov, 146477, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 47, Private, 201699, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 5178, 0, 50, United-States, >50K 59, Private, 205949, HS-grad, 9, Separated, Craft-repair, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 70, Private, 90245, HS-grad, 9, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 5, United-States, <=50K 53, Federal-gov, 177647, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, France, >50K 39, Private, 126494, HS-grad, 9, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 257735, 9th, 5, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 1161363, Some-college, 10, Separated, Tech-support, Unmarried, White, Female, 0, 0, 50, Columbia, <=50K 19, ?, 257343, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 221452, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 74, Private, 260669, 10th, 6, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 1, United-States, <=50K 40, Private, 192344, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 80479, Assoc-voc, 11, Divorced, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Self-emp-not-inc, 108808, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 41, Private, 175674, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 272950, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 29, Self-emp-not-inc, 160786, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, >50K 46, Self-emp-not-inc, 122206, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 46, Private, 121168, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 209547, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 29, Federal-gov, 244473, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 40, United-States, >50K 39, Private, 176296, Assoc-acdm, 12, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 60, United-States, <=50K 31, Private, 91666, HS-grad, 9, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 60, United-States, <=50K 50, Local-gov, 191025, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Female, 4650, 0, 70, United-States, <=50K 31, State-gov, 63704, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 31659, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 27, Private, 191230, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 25, United-States, <=50K 28, Private, 56340, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 21, Private, 221157, HS-grad, 9, Never-married, Other-service, Own-child, Black, Female, 0, 0, 30, United-States, <=50K 57, Local-gov, 143910, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 56, Local-gov, 435836, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, ?, 61499, HS-grad, 9, Never-married, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 48, Private, 209182, Preschool, 1, Separated, Other-service, Unmarried, White, Female, 0, 0, 40, El-Salvador, <=50K 36, Self-emp-inc, 107218, Some-college, 10, Divorced, Sales, Unmarried, Asian-Pac-Islander, Male, 0, 0, 55, United-States, <=50K 51, Private, 55500, 12th, 8, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Local-gov, 357962, Assoc-acdm, 12, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 43, Private, 200355, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 70, United-States, >50K 38, Private, 320451, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, ?, <=50K 51, Local-gov, 184542, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, State-gov, 206927, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 54310, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7298, 0, 40, United-States, >50K 35, Private, 208165, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 40, Private, 146908, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 40, United-States, >50K 39, Private, 318416, 10th, 6, Separated, Other-service, Own-child, Black, Female, 0, 0, 12, United-States, <=50K 47, Self-emp-inc, 207540, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, ?, <=50K 23, Private, 69911, Preschool, 1, Never-married, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 26, Private, 305304, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Local-gov, 295289, HS-grad, 9, Never-married, Prof-specialty, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 29, Private, 275110, Some-college, 10, Separated, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 42, United-States, <=50K 30, Private, 339773, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 57, State-gov, 399246, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 1485, 40, China, <=50K 37, Self-emp-inc, 51264, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 49020, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 3103, 0, 48, United-States, >50K 37, Private, 178100, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 45, ?, 215943, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 176178, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 16, United-States, <=50K 25, State-gov, 180884, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 0, 40, United-States, <=50K 61, State-gov, 130466, HS-grad, 9, Widowed, Adm-clerical, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 59, Private, 328525, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 2414, 0, 15, United-States, <=50K 28, Private, 142712, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 176321, Some-college, 10, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 145041, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Cuba, >50K 29, Private, 95423, HS-grad, 9, Married-AF-spouse, Transport-moving, Husband, White, Male, 0, 0, 80, United-States, <=50K 49, Self-emp-not-inc, 215096, 9th, 5, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 41, Local-gov, 177599, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 33, Private, 123920, Some-college, 10, Never-married, Exec-managerial, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 20, ?, 201490, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 46990, Doctorate, 16, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 1977, 20, United-States, >50K 32, Private, 388672, Some-college, 10, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 16, United-States, <=50K 48, Private, 149210, Bachelors, 13, Divorced, Sales, Not-in-family, Black, Male, 0, 0, 40, United-States, >50K 24, Private, 134787, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 50, Private, 185407, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 38, United-States, >50K 31, State-gov, 86143, HS-grad, 9, Never-married, Protective-serv, Other-relative, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 23, Private, 41721, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, >50K 35, Private, 195744, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Local-gov, 96062, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 215150, 9th, 5, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 52, Private, 270728, 7th-8th, 4, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 48, Cuba, <=50K 44, Private, 75012, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 80, United-States, <=50K 43, Private, 206139, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 39, Private, 50700, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 224258, 7th-8th, 4, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, Mexico, >50K 31, Private, 240441, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 1564, 40, United-States, >50K 40, Self-emp-not-inc, 406811, Some-college, 10, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 28, Local-gov, 34452, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 361341, 12th, 8, Never-married, Prof-specialty, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 25, Thailand, <=50K 35, Private, 78247, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 44, Private, 106900, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 40, Self-emp-not-inc, 165108, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, England, <=50K 20, Private, 406641, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 35, United-States, <=50K 55, Private, 171467, HS-grad, 9, Divorced, Craft-repair, Unmarried, Black, Male, 0, 0, 48, United-States, >50K 30, Private, 341187, 7th-8th, 4, Separated, Transport-moving, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 38, Private, 119177, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, >50K 75, Private, 104896, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 2653, 0, 20, United-States, <=50K 17, Private, 342752, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 15, United-States, <=50K 79, ?, 76641, Masters, 14, Married-civ-spouse, ?, Husband, White, Male, 20051, 0, 40, Poland, >50K 20, Private, 47541, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 30, United-States, <=50K 25, Private, 233461, Assoc-acdm, 12, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 27, Private, 303954, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 19, Private, 163015, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 21, Private, 75763, Some-college, 10, Married-civ-spouse, Sales, Wife, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 19, Private, 43003, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 42, Private, 328239, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 130856, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 36, United-States, <=50K 47, Self-emp-not-inc, 190072, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Iran, >50K 59, Private, 170148, Some-college, 10, Divorced, Other-service, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 50, Private, 104501, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 48, Self-emp-inc, 213140, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 80, United-States, <=50K 33, Local-gov, 175509, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 173611, Assoc-acdm, 12, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 148995, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 99999, 0, 30, United-States, >50K 24, Private, 64520, 7th-8th, 4, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 139822, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 24, Private, 258700, 5th-6th, 3, Never-married, Farming-fishing, Other-relative, Black, Male, 0, 0, 40, Mexico, <=50K 29, Private, 34796, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 124963, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 30, United-States, <=50K 24, Private, 65743, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 28, Private, 161087, Some-college, 10, Never-married, Exec-managerial, Not-in-family, Black, Female, 0, 0, 45, Jamaica, <=50K 63, ?, 424591, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Federal-gov, 203836, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 50, United-States, <=50K 58, State-gov, 110199, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 316059, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 36, United-States, <=50K 42, Private, 255667, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 39, Private, 193689, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 60722, Bachelors, 13, Never-married, Prof-specialty, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 39, Private, 187847, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 233275, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 51, Private, 215404, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Amer-Indian-Eskimo, Male, 15024, 0, 40, United-States, >50K 45, Private, 201865, Bachelors, 13, Married-spouse-absent, Exec-managerial, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 118889, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, State-gov, 368739, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 123833, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 1408, 40, United-States, <=50K 38, Private, 171344, 11th, 7, Married-spouse-absent, Transport-moving, Own-child, White, Male, 0, 0, 36, Mexico, <=50K 39, Private, 153976, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 374883, Assoc-voc, 11, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 17, Private, 167658, 12th, 8, Never-married, Sales, Own-child, White, Female, 0, 0, 6, United-States, <=50K 31, Private, 348504, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 22, Private, 258509, HS-grad, 9, Never-married, Transport-moving, Own-child, Black, Male, 0, 0, 24, United-States, <=50K 47, State-gov, 108890, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 1831, 0, 38, United-States, <=50K 28, Private, 188236, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, ?, 355571, HS-grad, 9, Never-married, ?, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 41, Private, 425049, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 29, Private, 142555, Masters, 14, Never-married, Prof-specialty, Not-in-family, Black, Male, 0, 0, 42, United-States, <=50K 42, Self-emp-not-inc, 29320, Prof-school, 15, Divorced, Prof-specialty, Unmarried, White, Male, 0, 0, 60, United-States, >50K 52, Federal-gov, 207841, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 187329, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 270973, Assoc-acdm, 12, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 197332, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 46, United-States, >50K 21, ?, 175166, Some-college, 10, Never-married, ?, Own-child, White, Female, 2176, 0, 40, United-States, <=50K 45, Local-gov, 160187, HS-grad, 9, Married-spouse-absent, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 21, Private, 197918, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 74, Private, 192290, 10th, 6, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 20, United-States, <=50K 29, Private, 241895, HS-grad, 9, Married-civ-spouse, Transport-moving, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 39, Local-gov, 164515, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 147206, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 7688, 0, 45, United-States, >50K 23, Self-emp-inc, 306868, Bachelors, 13, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Local-gov, 169837, Assoc-acdm, 12, Divorced, Exec-managerial, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 61, ?, 124648, 10th, 6, Divorced, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 185057, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 30, United-States, >50K 23, Private, 240049, Preschool, 1, Never-married, Other-service, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, Laos, <=50K 18, Private, 164441, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 38, United-States, <=50K 38, Private, 179314, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 319854, Bachelors, 13, Separated, Prof-specialty, Not-in-family, White, Male, 4650, 0, 35, United-States, <=50K 19, Self-emp-inc, 148955, Some-college, 10, Never-married, Other-service, Own-child, Asian-Pac-Islander, Female, 0, 0, 35, South, <=50K 23, Private, 32950, Some-college, 10, Never-married, Transport-moving, Not-in-family, White, Male, 4101, 0, 40, United-States, <=50K 37, Private, 206699, HS-grad, 9, Divorced, Tech-support, Own-child, White, Male, 0, 0, 45, United-States, <=50K 25, Private, 385646, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 31438, HS-grad, 9, Divorced, Transport-moving, Unmarried, White, Male, 0, 0, 43, ?, <=50K 45, Private, 168598, 12th, 8, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 3103, 0, 40, United-States, >50K 32, Private, 97306, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 65, ?, 106910, 11th, 7, Divorced, ?, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 15, United-States, <=50K 18, Self-emp-not-inc, 29582, 11th, 7, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 220284, HS-grad, 9, Never-married, Transport-moving, Unmarried, White, Male, 0, 0, 40, Mexico, <=50K 29, Private, 110226, Masters, 14, Never-married, Sales, Not-in-family, White, Male, 0, 0, 65, ?, <=50K 53, Private, 240914, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 115496, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 27, Private, 105817, Bachelors, 13, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 24, State-gov, 330836, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Self-emp-not-inc, 36327, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, <=50K 23, Private, 33423, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 45, Private, 75673, Assoc-voc, 11, Widowed, Adm-clerical, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 36, Private, 185744, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 35, United-States, >50K 36, Private, 186035, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 5178, 0, 40, United-States, >50K 44, Local-gov, 196456, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 1669, 40, United-States, <=50K 24, Private, 111450, HS-grad, 9, Never-married, Transport-moving, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 39, Private, 115289, Some-college, 10, Divorced, Sales, Own-child, White, Male, 0, 1380, 70, United-States, <=50K 50, Private, 74879, HS-grad, 9, Married-spouse-absent, Handlers-cleaners, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 117312, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 15024, 0, 40, United-States, >50K 58, Private, 272902, Bachelors, 13, Widowed, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 44, Self-emp-inc, 220230, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 48, United-States, <=50K 24, Private, 90934, Bachelors, 13, Never-married, Sales, Own-child, Asian-Pac-Islander, Male, 0, 0, 55, United-States, <=50K 52, Self-emp-inc, 234286, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 40, United-States, >50K 46, Private, 364548, Bachelors, 13, Divorced, Sales, Not-in-family, White, Male, 8614, 0, 40, United-States, >50K 50, Self-emp-inc, 283676, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 60, United-States, >50K 34, Private, 195602, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 44, United-States, <=50K 40, Private, 70761, Assoc-acdm, 12, Never-married, Tech-support, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 53, Private, 142717, Bachelors, 13, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 124242, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 58, ?, 53481, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 70, United-States, <=50K 26, Private, 287797, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 22, Private, 188274, Assoc-acdm, 12, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 171968, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 78, ?, 74795, Assoc-acdm, 12, Widowed, ?, Not-in-family, White, Female, 0, 0, 4, United-States, <=50K 36, Private, 218490, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, Germany, >50K 43, Local-gov, 94937, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 28, United-States, <=50K 60, Private, 109511, 7th-8th, 4, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Local-gov, 269527, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7298, 0, 40, United-States, >50K 50, Self-emp-inc, 201689, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1977, 63, ?, >50K 34, Self-emp-not-inc, 120672, 7th-8th, 4, Never-married, Handlers-cleaners, Unmarried, Black, Male, 0, 0, 10, United-States, <=50K 46, Private, 130779, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Local-gov, 441542, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 69, Private, 114801, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 20, United-States, <=50K 32, Private, 180284, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Local-gov, 27444, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 61, Private, 180382, 5th-6th, 3, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 3411, 0, 45, United-States, <=50K 56, Private, 143266, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 47, Private, 139268, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 126208, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 37, Private, 186191, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 46, United-States, <=50K 51, Private, 197163, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 2559, 50, United-States, >50K 44, State-gov, 193524, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 40, United-States, >50K 33, Private, 181388, HS-grad, 9, Separated, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 51, Self-emp-not-inc, 124963, Prof-school, 15, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 80, United-States, >50K 24, Private, 188925, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Self-emp-not-inc, 149230, Assoc-voc, 11, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 388725, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 113543, Masters, 14, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 61, ?, 187636, Bachelors, 13, Divorced, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 56, Self-emp-inc, 267763, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, ?, <=50K 69, Federal-gov, 143849, 11th, 7, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 41, Self-emp-not-inc, 97277, Assoc-voc, 11, Divorced, Other-service, Unmarried, White, Female, 0, 0, 10, United-States, <=50K 40, Private, 199303, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 124852, Some-college, 10, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 26, Private, 50053, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, <=50K 53, Private, 97005, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 46, United-States, >50K 90, ?, 175444, 7th-8th, 4, Separated, ?, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 39, Private, 337898, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 51, Federal-gov, 124076, Bachelors, 13, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 56, Federal-gov, 277420, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, Puerto-Rico, >50K 51, Private, 280278, 10th, 6, Separated, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 17, Private, 241185, 12th, 8, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 20, United-States, <=50K 42, Private, 202188, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 1741, 50, United-States, <=50K 42, Private, 198422, Some-college, 10, Divorced, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 82242, Prof-school, 15, Never-married, Prof-specialty, Unmarried, White, Male, 27828, 0, 45, Germany, >50K 33, Private, 178429, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 47, Private, 185866, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, ?, >50K 43, Private, 212847, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 64, Self-emp-not-inc, 219661, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 9, United-States, >50K 40, Private, 321856, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 21, Private, 313873, 5th-6th, 3, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 31, Private, 144064, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 60, Private, 139586, Assoc-voc, 11, Widowed, Exec-managerial, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, United-States, >50K 32, Private, 419691, 12th, 8, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 66, ?, 212759, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 6767, 0, 20, United-States, <=50K 27, Private, 195562, HS-grad, 9, Never-married, Craft-repair, Own-child, Black, Male, 0, 0, 20, United-States, <=50K 40, Private, 205706, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 131310, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, >50K 18, Private, 54440, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, United-States, <=50K 43, Private, 200734, HS-grad, 9, Separated, Other-service, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 52, Private, 81859, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, >50K 31, Private, 159589, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 85, United-States, <=50K 28, Private, 300915, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 44, Private, 185057, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 37, Self-emp-not-inc, 42044, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 84, United-States, <=50K 35, Private, 166416, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 42, Private, 212737, 9th, 5, Separated, Craft-repair, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 18, Private, 236069, 10th, 6, Never-married, Other-service, Own-child, Black, Male, 0, 0, 10, United-States, <=50K 46, Self-emp-inc, 216414, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 1977, 60, United-States, >50K 54, Federal-gov, 27432, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 54, Private, 145419, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 1672, 50, United-States, <=50K 56, Private, 147202, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 45, Germany, <=50K 27, Private, 29261, Some-college, 10, Never-married, Sales, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 26, Private, 359543, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, Mexico, <=50K 41, Local-gov, 227644, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 90021, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, ?, <=50K 32, Private, 188154, Some-college, 10, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 110142, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 30, United-States, <=50K 36, Private, 186415, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 65, United-States, <=50K 37, Private, 175720, 10th, 6, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 172865, 5th-6th, 3, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 25, Mexico, <=50K 46, Private, 35969, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 51, United-States, <=50K 24, Private, 433330, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Self-emp-inc, 160261, Bachelors, 13, Never-married, Exec-managerial, Own-child, Asian-Pac-Islander, Male, 0, 0, 35, Taiwan, <=50K 55, Private, 189528, 5th-6th, 3, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 64, Local-gov, 113324, HS-grad, 9, Widowed, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Local-gov, 118500, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 65, Private, 89681, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 99, United-States, <=50K 46, Federal-gov, 199925, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 102308, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 60, United-States, >50K 18, Private, 444607, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 25, United-States, <=50K 32, Private, 176998, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, ?, 94559, Bachelors, 13, Married-civ-spouse, ?, Wife, Other, Female, 7688, 0, 50, ?, >50K 34, State-gov, 366198, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, Germany, >50K 35, Private, 180686, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 3137, 0, 40, United-States, <=50K 26, Private, 108019, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 3325, 0, 40, United-States, <=50K 24, Private, 153542, Some-college, 10, Never-married, Sales, Other-relative, White, Male, 0, 0, 35, United-States, <=50K 45, Self-emp-not-inc, 210364, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 80, United-States, >50K 36, Private, 185394, 10th, 6, Never-married, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 34, United-States, <=50K 44, Private, 222703, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, Other, Male, 0, 0, 40, Nicaragua, <=50K 23, Private, 183945, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 57, Private, 161964, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, <=50K 41, Self-emp-not-inc, 375574, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, Mexico, >50K 20, Local-gov, 312427, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 30, Puerto-Rico, <=50K 32, Private, 53373, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 36, United-States, <=50K 60, Private, 166330, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 99999, 0, 40, United-States, >50K 38, Self-emp-inc, 124665, Bachelors, 13, Never-married, Craft-repair, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 29, Private, 146719, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 22, Private, 306593, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 156687, Some-college, 10, Never-married, Sales, Own-child, Asian-Pac-Islander, Male, 0, 0, 30, India, <=50K 40, Local-gov, 153489, HS-grad, 9, Married-civ-spouse, Other-service, Other-relative, White, Male, 3137, 0, 40, United-States, <=50K 59, Private, 231377, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1848, 45, United-States, >50K 45, State-gov, 127089, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 76, Local-gov, 329355, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 13, United-States, <=50K 45, Private, 178319, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 49, Local-gov, 304246, Masters, 14, Separated, Prof-specialty, Unmarried, White, Female, 0, 0, 70, United-States, <=50K 36, Local-gov, 174640, Assoc-voc, 11, Never-married, Protective-serv, Not-in-family, Black, Female, 0, 0, 60, United-States, >50K 22, Private, 148294, 11th, 7, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 35, United-States, <=50K 47, Private, 298037, Assoc-voc, 11, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 44, United-States, <=50K 26, Private, 98155, HS-grad, 9, Married-AF-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, <=50K 21, Private, 102766, Some-college, 10, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 78529, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Female, 0, 0, 15, United-States, <=50K 26, Private, 136309, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 275357, Assoc-voc, 11, Never-married, Tech-support, Own-child, White, Female, 0, 0, 25, United-States, <=50K 31, Self-emp-not-inc, 33117, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, England, <=50K 57, Local-gov, 199546, Masters, 14, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 39, Private, 184128, 11th, 7, Divorced, Sales, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 337039, Assoc-acdm, 12, Never-married, Tech-support, Not-in-family, Black, Male, 14344, 0, 40, England, >50K 66, Private, 126511, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 34, Local-gov, 325792, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 80, ?, 91901, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 25, United-States, <=50K 21, Private, 119474, HS-grad, 9, Never-married, Other-service, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 153238, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 32, United-States, >50K 49, Local-gov, 321851, Assoc-acdm, 12, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 48, Self-emp-not-inc, 108557, Some-college, 10, Divorced, Sales, Not-in-family, White, Female, 3325, 0, 60, United-States, <=50K 19, State-gov, 67217, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 594, 0, 24, United-States, <=50K 42, Private, 195508, 11th, 7, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 59, Private, 102193, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 63, Private, 20323, Some-college, 10, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 122206, HS-grad, 9, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 200652, 9th, 5, Divorced, Other-service, Other-relative, White, Female, 0, 0, 35, United-States, <=50K 42, Private, 173590, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 1628, 40, United-States, <=50K 19, Private, 184121, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 45, Local-gov, 53123, 11th, 7, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 25, United-States, <=50K 47, Private, 175990, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 30, United-States, >50K 47, Private, 316101, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 34080, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, England, <=50K 49, Self-emp-not-inc, 219718, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 40, United-States, >50K 36, Private, 126954, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 99185, HS-grad, 9, Widowed, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, >50K 21, ?, 40052, Some-college, 10, Never-married, ?, Not-in-family, White, Male, 0, 2001, 45, United-States, <=50K 39, Private, 120074, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 52, Self-emp-not-inc, 77336, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 60981, Some-college, 10, Never-married, Sales, Own-child, White, Female, 2176, 0, 35, United-States, <=50K 59, Private, 77884, Assoc-voc, 11, Never-married, Craft-repair, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 50, Private, 65408, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 31, Private, 173279, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, >50K 52, ?, 318351, Some-college, 10, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 40, United-States, >50K 41, Self-emp-not-inc, 157686, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 45, Private, 277434, Assoc-acdm, 12, Widowed, Tech-support, Unmarried, White, Male, 0, 0, 40, United-States, >50K 54, Local-gov, 184620, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 34443, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 50, Private, 268553, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 7298, 0, 40, United-States, >50K 20, ?, 41356, Assoc-acdm, 12, Never-married, ?, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 43, Private, 459342, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 48, Local-gov, 148549, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 254293, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 2174, 0, 45, United-States, <=50K 54, Private, 104501, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 40, United-States, >50K 26, Private, 238367, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 180439, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 51, Self-emp-inc, 100029, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 40, United-States, >50K 54, Private, 215990, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1887, 44, United-States, >50K 32, State-gov, 111567, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 49, United-States, >50K 46, Private, 319163, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 60, ?, 160155, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 12, United-States, <=50K 52, Local-gov, 378045, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 44, Private, 177083, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 56, Self-emp-inc, 119891, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1672, 40, United-States, <=50K 57, Private, 127779, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 299353, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 30, Private, 63861, Assoc-acdm, 12, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 112403, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 49, Private, 83610, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 66, United-States, >50K 28, Private, 452808, 10th, 6, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 176871, Some-college, 10, Separated, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 45, Private, 100651, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Male, 0, 1980, 40, United-States, <=50K 17, Private, 266134, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 12, United-States, <=50K 54, Local-gov, 196307, 10th, 6, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 87891, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 182314, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 50, United-States, >50K 55, ?, 136819, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 181666, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Own-child, White, Female, 0, 0, 40, ?, <=50K 37, Private, 179671, 9th, 5, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 50, United-States, <=50K 34, Private, 27494, HS-grad, 9, Divorced, Craft-repair, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 48, United-States, >50K 38, Private, 338320, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, Canada, <=50K 51, Private, 199688, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 41, Private, 96635, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 60, United-States, <=50K 24, Private, 165064, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 56, Self-emp-inc, 109856, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 33, Private, 82393, HS-grad, 9, Never-married, Craft-repair, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 31, Private, 209538, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 209891, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 50, United-States, <=50K 32, Self-emp-not-inc, 56026, Bachelors, 13, Married-civ-spouse, Sales, Other-relative, White, Male, 0, 0, 45, United-States, <=50K 35, Private, 210844, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, Puerto-Rico, <=50K 43, Private, 117158, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 40, Private, 193144, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 36, United-States, <=50K 19, Self-emp-not-inc, 137578, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 53, United-States, <=50K 23, Private, 234108, Assoc-acdm, 12, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 32, United-States, <=50K 40, Private, 155767, HS-grad, 9, Separated, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 59, Private, 110820, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 38, United-States, >50K 43, Private, 403276, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Self-emp-not-inc, 147269, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, ?, <=50K 53, Private, 123092, HS-grad, 9, Widowed, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 165673, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 68, Self-emp-inc, 182131, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 10605, 0, 20, United-States, >50K 41, Private, 204415, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 48, United-States, >50K 32, Self-emp-not-inc, 92531, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 25, State-gov, 157028, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 228649, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 147253, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 15, United-States, <=50K 33, Private, 160784, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Local-gov, 163189, Some-college, 10, Married-civ-spouse, Other-service, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 146343, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 25, United-States, <=50K 20, Private, 225811, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 23, United-States, <=50K 68, State-gov, 202699, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 2377, 42, ?, >50K 58, Private, 374108, Some-college, 10, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 93930, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 412248, Assoc-acdm, 12, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 30, Private, 427474, 9th, 5, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Mexico, <=50K 67, State-gov, 160158, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 8, United-States, <=50K 26, Private, 159603, Assoc-acdm, 12, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 53, Self-emp-not-inc, 101017, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 35, United-States, <=50K 27, Local-gov, 163862, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 29, Without-pay, 212588, Some-college, 10, Married-civ-spouse, Farming-fishing, Own-child, White, Male, 0, 0, 65, United-States, <=50K 38, State-gov, 321943, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 17, Private, 317702, 9th, 5, Never-married, Other-service, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 48, Private, 287480, Masters, 14, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 52, Private, 135607, Some-college, 10, Widowed, Other-service, Unmarried, Black, Female, 0, 0, 40, ?, <=50K 28, Private, 168514, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 88642, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 15, United-States, <=50K 28, Private, 227104, Some-college, 10, Divorced, Sales, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 34, Private, 157289, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 62, Private, 213321, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Private, 294907, 5th-6th, 3, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 30, Private, 251411, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 183594, Some-college, 10, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 189565, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 2174, 0, 50, United-States, <=50K 55, Private, 217802, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 25, United-States, <=50K 20, Private, 388156, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 24, United-States, <=50K 54, Private, 447555, 10th, 6, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 27, Private, 204098, 10th, 6, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 43, Private, 193882, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 17, ?, 89870, 10th, 6, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 48, State-gov, 49595, Masters, 14, Divorced, Protective-serv, Not-in-family, White, Male, 0, 0, 72, United-States, <=50K 34, Private, 228873, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 66, ?, 108185, 9th, 5, Married-civ-spouse, ?, Husband, Black, Male, 0, 0, 40, United-States, <=50K 29, Private, 176027, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, ?, 405374, Some-college, 10, Separated, ?, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 37, Private, 39606, Assoc-voc, 11, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 56, Private, 178353, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 58, Private, 160662, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 54, Self-emp-inc, 196328, Bachelors, 13, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 40, Jamaica, <=50K 45, Private, 20534, Some-college, 10, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 41, United-States, <=50K 29, Self-emp-inc, 156815, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 360252, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 245056, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, >50K 33, Local-gov, 422718, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Self-emp-not-inc, 118081, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 3103, 0, 42, United-States, <=50K 25, Private, 262978, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 25, Private, 187577, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 69, ?, 259323, Prof-school, 15, Divorced, ?, Not-in-family, White, Male, 0, 0, 5, United-States, <=50K 37, Private, 160920, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 194247, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 39, Private, 134367, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 1977, 24, United-States, >50K 17, Private, 123335, 10th, 6, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 27, Local-gov, 332249, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 358124, HS-grad, 9, Never-married, Other-service, Other-relative, Black, Female, 0, 0, 40, United-States, <=50K 55, Private, 208019, 5th-6th, 3, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 39, Private, 318452, 11th, 7, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 41, Private, 207779, HS-grad, 9, Separated, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 238376, 1st-4th, 2, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Mexico, <=50K 51, Private, 673764, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 67, State-gov, 239705, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 12, ?, <=50K 40, Private, 133974, Some-college, 10, Divorced, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 58, Private, 138285, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1740, 40, United-States, <=50K 23, Private, 152140, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, Local-gov, 287920, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 51, Private, 289572, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 50, United-States, >50K 43, State-gov, 78765, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 25, State-gov, 99076, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Female, 2597, 0, 50, United-States, <=50K 36, Self-emp-not-inc, 224886, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 2407, 0, 40, United-States, <=50K 58, Private, 206532, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 33, Private, 129529, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 60, Local-gov, 202473, Assoc-voc, 11, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 162312, HS-grad, 9, Never-married, Sales, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, South, <=50K 45, Private, 72844, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 46, United-States, <=50K 49, Private, 206947, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 64112, 12th, 8, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, State-gov, 20057, Some-college, 10, Married-spouse-absent, Adm-clerical, Unmarried, Asian-Pac-Islander, Female, 0, 0, 38, Philippines, <=50K 42, State-gov, 222884, Bachelors, 13, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 132683, HS-grad, 9, Never-married, Priv-house-serv, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 73, ?, 177773, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 15, United-States, <=50K 59, Self-emp-not-inc, 144071, 5th-6th, 3, Married-civ-spouse, Other-service, Husband, White, Male, 2580, 0, 15, El-Salvador, <=50K 28, Private, 148429, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 2885, 0, 40, United-States, <=50K 19, Private, 168601, 11th, 7, Never-married, Other-service, Other-relative, White, Male, 0, 0, 30, United-States, <=50K 31, State-gov, 78291, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 58, Federal-gov, 243929, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 21, Private, 215039, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 13, ?, <=50K 47, Self-emp-not-inc, 185673, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 30, Private, 121142, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 41, Private, 173858, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, China, <=50K 59, ?, 87247, 10th, 6, Divorced, ?, Not-in-family, White, Female, 0, 0, 40, England, <=50K 43, Private, 334991, Some-college, 10, Separated, Transport-moving, Unmarried, White, Male, 4934, 0, 51, United-States, >50K 48, Private, 93476, HS-grad, 9, Separated, Adm-clerical, Not-in-family, White, Female, 0, 2001, 40, United-States, <=50K 44, Private, 174283, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 44, Private, 128676, Some-college, 10, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 24, Private, 205844, Bachelors, 13, Never-married, Exec-managerial, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 28, Private, 62535, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 43, United-States, <=50K 50, Private, 240612, HS-grad, 9, Married-spouse-absent, Exec-managerial, Unmarried, White, Female, 0, 0, 10, United-States, <=50K 33, Private, 176992, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Local-gov, 254127, Bachelors, 13, Never-married, Prof-specialty, Other-relative, White, Female, 0, 0, 50, United-States, <=50K 30, ?, 138744, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 128460, 10th, 6, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, State-gov, 56582, Some-college, 10, Never-married, Tech-support, Own-child, White, Male, 0, 0, 10, United-States, <=50K 52, Private, 153751, 9th, 5, Separated, Other-service, Not-in-family, Black, Female, 0, 0, 30, United-States, <=50K 26, Private, 284343, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 27, State-gov, 312692, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 12, United-States, <=50K 28, Private, 111520, 11th, 7, Never-married, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, Nicaragua, <=50K 50, Self-emp-inc, 304955, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 28, Private, 288598, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 61, Self-emp-not-inc, 117387, 11th, 7, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 20, United-States, <=50K 32, Private, 230484, 7th-8th, 4, Separated, Sales, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 30, Federal-gov, 319280, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 51, Local-gov, 186416, Bachelors, 13, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 40, Local-gov, 147372, Some-college, 10, Never-married, Protective-serv, Not-in-family, White, Male, 0, 2444, 40, United-States, >50K 36, Private, 145933, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 2258, 70, United-States, <=50K 28, Private, 110164, Some-college, 10, Divorced, Other-service, Other-relative, Black, Male, 0, 0, 24, United-States, <=50K 49, Private, 225454, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 61, Self-emp-not-inc, 220342, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 30, United-States, <=50K 41, Self-emp-not-inc, 144002, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 55, Private, 225365, HS-grad, 9, Widowed, Other-service, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 36, Private, 187983, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 89991, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 57, Self-emp-not-inc, 225913, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, >50K 49, Self-emp-inc, 229737, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 37, United-States, >50K 59, Private, 145574, 11th, 7, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 274363, Some-college, 10, Separated, Sales, Not-in-family, White, Male, 0, 0, 80, United-States, >50K 59, Private, 365390, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 266467, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 25, United-States, <=50K 42, Private, 183384, Some-college, 10, Divorced, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 41, Local-gov, 112797, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 60, United-States, <=50K 45, Federal-gov, 76008, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 36, Private, 156780, HS-grad, 9, Never-married, Sales, Other-relative, Asian-Pac-Islander, Female, 0, 0, 40, ?, <=50K 42, Local-gov, 186909, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 45, United-States, >50K 25, Private, 25497, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 102771, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1887, 40, United-States, >50K 58, Self-emp-not-inc, 248841, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 40, United-States, >50K 39, Private, 30916, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 123270, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 22, Self-emp-not-inc, 210165, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 222596, HS-grad, 9, Divorced, Tech-support, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 53, Self-emp-inc, 188067, Some-college, 10, Widowed, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 119592, Assoc-acdm, 12, Never-married, Handlers-cleaners, Not-in-family, Black, Male, 0, 2824, 40, ?, >50K 27, Private, 250314, 9th, 5, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, Guatemala, <=50K 60, Private, 205934, HS-grad, 9, Separated, Other-service, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 46, Private, 186172, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 3103, 0, 40, United-States, >50K 56, Self-emp-inc, 98418, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 40, United-States, >50K 36, Private, 329980, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 27828, 0, 40, United-States, >50K 56, Private, 147653, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 35, ?, 195946, Some-college, 10, Married-civ-spouse, ?, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, >50K 29, Self-emp-inc, 168221, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1740, 70, United-States, <=50K 19, Private, 151801, 10th, 6, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 39, United-States, <=50K 38, Private, 177154, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Federal-gov, 73883, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 52, Private, 175714, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 22, Private, 43535, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 32, State-gov, 104509, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 27, Private, 118230, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 152046, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, Guatemala, <=50K 36, Private, 52327, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Other, Male, 0, 0, 40, Iran, >50K 22, Private, 218886, 12th, 8, Never-married, Handlers-cleaners, Own-child, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 32, Self-emp-not-inc, 84119, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 37, Private, 189674, Bachelors, 13, Separated, Exec-managerial, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 22, Private, 222993, HS-grad, 9, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 54, United-States, <=50K 29, Private, 47429, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 42, Private, 144995, Preschool, 1, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 45, Private, 187969, Assoc-voc, 11, Never-married, Sales, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 33, Private, 288398, Bachelors, 13, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 39, Private, 114591, Some-college, 10, Separated, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 167737, 12th, 8, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 53, Local-gov, 248834, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 50, United-States, >50K 30, Private, 165686, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 52, Self-emp-not-inc, 40200, Some-college, 10, Widowed, Craft-repair, Not-in-family, Black, Male, 0, 0, 35, United-States, <=50K 43, Self-emp-inc, 117158, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 60, United-States, >50K 47, Local-gov, 216657, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 35, United-States, >50K 61, Private, 124242, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 40, India, <=50K 39, Local-gov, 239119, Masters, 14, Divorced, Prof-specialty, Not-in-family, Black, Male, 0, 0, 40, Dominican-Republic, <=50K 47, Private, 190072, Some-college, 10, Divorced, Sales, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 19, Private, 378114, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 25, United-States, <=50K 37, Private, 236990, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 3464, 0, 40, United-States, <=50K 31, Private, 101761, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 51, United-States, <=50K 69, Self-emp-not-inc, 37745, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 8, United-States, <=50K 22, ?, 424494, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 25, United-States, <=50K 29, Private, 130438, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 100605, Some-college, 10, Never-married, Machine-op-inspct, Own-child, Other, Male, 0, 0, 14, United-States, <=50K 42, Private, 220776, HS-grad, 9, Separated, Handlers-cleaners, Unmarried, White, Male, 0, 0, 40, Poland, <=50K 30, Local-gov, 154950, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 72, United-States, >50K 28, Private, 192283, Masters, 14, Married-spouse-absent, Sales, Not-in-family, White, Female, 0, 0, 80, United-States, >50K 27, Private, 210765, Assoc-voc, 11, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 147476, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 35, State-gov, 193241, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1651, 40, United-States, <=50K 22, Private, 109053, 12th, 8, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 265618, HS-grad, 9, Separated, Protective-serv, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 38, Local-gov, 172855, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, Black, Female, 0, 1887, 40, United-States, >50K 27, Private, 68848, Bachelors, 13, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 30, Private, 229051, 9th, 5, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 37, United-States, <=50K 27, Private, 106039, Bachelors, 13, Divorced, Prof-specialty, Own-child, White, Female, 0, 0, 50, United-States, <=50K 25, Private, 112835, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, ?, 205396, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 4, United-States, <=50K 32, Private, 283400, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 70, Private, 195739, 10th, 6, Widowed, Craft-repair, Unmarried, White, Male, 0, 0, 45, United-States, <=50K 50, Private, 36480, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 303291, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 35, United-States, <=50K 34, Private, 293900, 11th, 7, Married-spouse-absent, Craft-repair, Not-in-family, Black, Male, 0, 0, 55, United-States, <=50K 57, Self-emp-not-inc, 165922, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 39, Private, 65738, Masters, 14, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 49, Private, 175070, Some-college, 10, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 339814, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 5178, 0, 40, United-States, >50K 26, Private, 150132, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 31, Private, 377374, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, Japan, <=50K 60, Self-emp-not-inc, 166153, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 46, Private, 110171, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 50, United-States, >50K 26, Private, 94477, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 7298, 0, 55, United-States, >50K 27, Private, 194243, Prof-school, 15, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 106347, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 0, 40, United-States, <=50K 59, Private, 214865, HS-grad, 9, Widowed, Exec-managerial, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 19, ?, 185619, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 20, United-States, <=50K 18, Private, 96445, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 24, United-States, <=50K 22, Private, 102632, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 24, Private, 209034, Assoc-acdm, 12, Married-civ-spouse, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 53, State-gov, 153486, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 43, Private, 144371, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 42, United-States, >50K 24, Private, 186213, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 50, United-States, >50K 60, Private, 188236, 10th, 6, Widowed, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 418405, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Federal-gov, 125796, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 32, Private, 183304, Assoc-voc, 11, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 99, United-States, >50K 34, Private, 329587, 10th, 6, Separated, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 35, Local-gov, 182570, Assoc-acdm, 12, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 446654, 9th, 5, Married-spouse-absent, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 34, Self-emp-not-inc, 254304, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 4508, 0, 90, United-States, <=50K 53, Local-gov, 131258, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 23, Private, 103632, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 241895, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 244945, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 20795, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, >50K 17, Private, 347322, 10th, 6, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 53, Local-gov, 103995, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 1876, 54, United-States, <=50K 32, Private, 53206, Bachelors, 13, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 43, ?, 387839, HS-grad, 9, Never-married, ?, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 57108, 11th, 7, Never-married, Sales, Own-child, White, Male, 0, 0, 16, United-States, <=50K 62, Private, 177791, 10th, 6, Divorced, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 33794, Masters, 14, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 249935, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 70, United-States, <=50K 73, Self-emp-not-inc, 241121, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 64, Private, 98586, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 26, Private, 181920, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 45, United-States, >50K 23, Private, 434467, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 30, Private, 113364, HS-grad, 9, Never-married, Machine-op-inspct, Other-relative, White, Male, 0, 0, 40, Vietnam, <=50K 51, Private, 249706, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 35, Self-emp-not-inc, 95455, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 55, United-States, <=50K 39, Private, 209867, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 13550, 0, 45, United-States, >50K 35, Self-emp-inc, 79586, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, India, >50K 41, Private, 289669, HS-grad, 9, Widowed, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 347166, Some-college, 10, Divorced, Craft-repair, Own-child, White, Male, 4650, 0, 40, United-States, <=50K 40, Private, 53835, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 46, Local-gov, 14878, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, >50K 31, Private, 266126, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 41, Self-emp-inc, 146659, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, Honduras, <=50K 42, Private, 125280, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 3137, 0, 40, United-States, <=50K 23, Private, 173535, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 21, ?, 77665, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 35, United-States, <=50K 49, Private, 280525, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, >50K 53, Private, 479621, Assoc-voc, 11, Divorced, Tech-support, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 38, Local-gov, 194630, Bachelors, 13, Never-married, Protective-serv, Not-in-family, White, Female, 4787, 0, 43, United-States, >50K 36, Private, 247600, Assoc-acdm, 12, Divorced, Exec-managerial, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, Taiwan, <=50K 32, Private, 258406, Some-college, 10, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 72, Mexico, <=50K 20, Private, 107746, 11th, 7, Never-married, Transport-moving, Other-relative, White, Male, 0, 0, 40, Guatemala, <=50K 17, ?, 47407, 11th, 7, Never-married, ?, Own-child, White, Male, 0, 0, 10, United-States, <=50K 22, Private, 229987, Some-college, 10, Never-married, Tech-support, Other-relative, Asian-Pac-Islander, Female, 0, 0, 32, United-States, <=50K 25, Private, 312338, Assoc-voc, 11, Never-married, Craft-repair, Unmarried, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 58, Private, 225394, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1902, 40, United-States, <=50K 24, Private, 373718, Some-college, 10, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 48, State-gov, 120131, HS-grad, 9, Divorced, Craft-repair, Own-child, White, Male, 8614, 0, 40, United-States, >50K 20, Private, 472789, 1st-4th, 2, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 30, El-Salvador, <=50K 60, Self-emp-not-inc, 27886, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Private, 138352, HS-grad, 9, Never-married, Other-service, Other-relative, White, Male, 0, 0, 30, United-States, <=50K 52, Private, 123011, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 36, Private, 306567, HS-grad, 9, Married-civ-spouse, Transport-moving, Wife, White, Female, 0, 0, 40, United-States, >50K 46, Local-gov, 187749, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, >50K 22, Private, 260594, 11th, 7, Never-married, Sales, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 19, Private, 236879, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 35, United-States, <=50K 37, Private, 186808, HS-grad, 9, Never-married, Sales, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 373213, Assoc-voc, 11, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 44, Private, 187629, Assoc-acdm, 12, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 63, ?, 106648, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 25, United-States, <=50K 22, Private, 305781, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, Canada, <=50K 31, Self-emp-inc, 256362, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 3908, 0, 50, United-States, <=50K 17, Private, 239947, 11th, 7, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 349041, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 67, Private, 105252, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Private, 182715, 7th-8th, 4, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 166210, HS-grad, 9, Divorced, Handlers-cleaners, Own-child, White, Male, 0, 0, 50, United-States, <=50K 20, Private, 113200, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 6, United-States, <=50K 27, Private, 142075, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 24, United-States, <=50K 35, Private, 454843, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 19, Private, 142219, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 30, United-States, <=50K 36, Private, 112512, 12th, 8, Separated, Other-service, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 43, Private, 212894, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 62, State-gov, 265201, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 251905, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 2339, 40, Canada, <=50K 18, Private, 170627, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 59, Private, 354037, Prof-school, 15, Married-civ-spouse, Transport-moving, Husband, Black, Male, 15024, 0, 50, United-States, >50K 37, Private, 259089, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 21856, Some-college, 10, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 46, Local-gov, 207946, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 43, United-States, <=50K 29, Private, 77009, 11th, 7, Separated, Sales, Not-in-family, White, Female, 0, 2754, 42, United-States, <=50K 33, Private, 36539, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 62, Private, 176811, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 456062, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 2415, 55, United-States, >50K 28, Private, 277746, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 288132, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 35, United-States, <=50K 46, Federal-gov, 344415, Masters, 14, Married-civ-spouse, Armed-Forces, Husband, White, Male, 0, 1887, 40, United-States, >50K 54, Self-emp-inc, 206964, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 1977, 40, United-States, >50K 34, Private, 198091, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 72, United-States, <=50K 67, ?, 150264, Doctorate, 16, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 20, Canada, >50K 62, Private, 588484, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 20, United-States, >50K 30, Private, 113364, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Poland, <=50K 19, Private, 270551, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 49, ?, 31478, 7th-8th, 4, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 99, United-States, <=50K 27, Private, 190525, Assoc-voc, 11, Never-married, Machine-op-inspct, Unmarried, White, Male, 0, 0, 45, United-States, <=50K 36, Private, 153066, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 52, Private, 150393, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 47, Private, 99911, 12th, 8, Married-spouse-absent, Exec-managerial, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 57, Local-gov, 343447, HS-grad, 9, Divorced, Protective-serv, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 64, Private, 169482, Some-college, 10, Married-spouse-absent, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 56, ?, 32855, HS-grad, 9, Divorced, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 194501, 11th, 7, Widowed, Other-service, Own-child, White, Female, 0, 0, 47, United-States, <=50K 53, Private, 177705, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 44, United-States, >50K 31, Private, 123983, Some-college, 10, Separated, Sales, Unmarried, Asian-Pac-Islander, Male, 0, 0, 40, South, <=50K 41, Private, 138975, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 45, United-States, >50K 45, Local-gov, 235431, HS-grad, 9, Separated, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 63, ?, 83043, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 2179, 45, United-States, <=50K 45, State-gov, 130206, HS-grad, 9, Divorced, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 210053, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 28, United-States, <=50K 39, Local-gov, 249392, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 72, United-States, <=50K 31, Private, 87418, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Self-emp-not-inc, 190387, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 45, United-States, <=50K 54, Private, 176240, Masters, 14, Married-civ-spouse, Transport-moving, Husband, White, Male, 7688, 0, 60, United-States, >50K 22, ?, 211013, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, Mexico, <=50K 40, Local-gov, 105862, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 5455, 0, 40, United-States, <=50K 55, Self-emp-not-inc, 185195, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 173495, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, Self-emp-inc, 78634, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 31, Private, 147284, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 99, United-States, >50K 46, Self-emp-not-inc, 82572, HS-grad, 9, Widowed, Other-service, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 154641, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Local-gov, 39236, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 594, 0, 25, United-States, <=50K 17, ?, 64785, 10th, 6, Never-married, ?, Own-child, White, Male, 0, 0, 30, United-States, <=50K 48, Self-emp-not-inc, 179337, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, England, <=50K 73, Private, 173047, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 15, United-States, <=50K 25, Private, 264012, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, >50K 53, Federal-gov, 227836, Some-college, 10, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 321327, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 7298, 0, 45, United-States, >50K 45, Self-emp-inc, 108100, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, Asian-Pac-Islander, Female, 99999, 0, 25, ?, >50K 37, Private, 146398, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 30, Private, 324120, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 50, United-States, <=50K 29, Private, 367329, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, State-gov, 301582, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 75, ?, 222789, Bachelors, 13, Widowed, ?, Not-in-family, White, Female, 0, 0, 6, United-States, <=50K 58, Private, 170108, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Self-emp-not-inc, 82297, 7th-8th, 4, Married-civ-spouse, Other-service, Wife, Black, Female, 0, 0, 50, United-States, <=50K 62, Local-gov, 180162, 9th, 5, Divorced, Protective-serv, Not-in-family, Black, Male, 0, 0, 24, United-States, <=50K 45, Local-gov, 348172, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, Asian-Pac-Islander, Male, 7298, 0, 40, United-States, >50K 38, Private, 809585, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Self-emp-not-inc, 67728, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 70, ?, 163057, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 2009, 0, 40, United-States, <=50K 42, Self-emp-not-inc, 102069, 7th-8th, 4, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 30, United-States, <=50K 47, Local-gov, 149700, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 35, United-States, >50K 42, Self-emp-not-inc, 109273, Some-college, 10, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 393354, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 0, 38, United-States, >50K 37, Private, 226947, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 36, State-gov, 86805, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 7298, 0, 39, United-States, >50K 27, Private, 493689, Bachelors, 13, Never-married, Tech-support, Not-in-family, Black, Female, 0, 0, 40, France, <=50K 54, Private, 299324, 5th-6th, 3, Married-spouse-absent, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, Mexico, <=50K 48, Self-emp-not-inc, 353012, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1902, 40, United-States, >50K 29, Private, 174419, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 29, Private, 209472, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 38, United-States, <=50K 37, Private, 295127, Some-college, 10, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 47, United-States, <=50K 55, Self-emp-inc, 182273, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 67, Private, 228200, HS-grad, 9, Married-civ-spouse, Priv-house-serv, Wife, Black, Female, 0, 0, 20, United-States, <=50K 51, Private, 263836, HS-grad, 9, Widowed, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 35, Private, 178948, Masters, 14, Never-married, Prof-specialty, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 41, Private, 43945, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, ?, <=50K 64, Self-emp-not-inc, 253296, HS-grad, 9, Widowed, Other-service, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 240137, 5th-6th, 3, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 55, Mexico, <=50K 49, Private, 24712, Bachelors, 13, Never-married, Other-service, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 35, Philippines, <=50K 38, Self-emp-not-inc, 342635, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 70, United-States, <=50K 62, Private, 115387, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, Black, Female, 0, 0, 40, United-States, <=50K 62, Self-emp-not-inc, 182998, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 10, United-States, <=50K 70, ?, 133248, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 14, United-States, <=50K 45, Self-emp-not-inc, 246891, Masters, 14, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 30035, Assoc-acdm, 12, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 175232, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, <=50K 50, Self-emp-inc, 140516, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 64980, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 55, United-States, >50K 30, Private, 155781, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 70, United-States, <=50K 52, Federal-gov, 192065, Some-college, 10, Separated, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Self-emp-not-inc, 227890, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Black, Male, 0, 0, 50, United-States, >50K 62, Self-emp-not-inc, 162249, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 30, United-States, <=50K 31, Private, 165949, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 445382, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 34, Private, 211948, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 1590, 40, United-States, <=50K 53, Private, 163678, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Private, 89413, 12th, 8, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 289700, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 25, United-States, <=50K 51, Private, 163826, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 49, Private, 185385, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 43, Private, 169031, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 54611, Some-college, 10, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 130620, 11th, 7, Married-spouse-absent, Sales, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, India, <=50K 26, Private, 328663, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Other, Male, 0, 0, 40, United-States, <=50K 50, Private, 169646, Bachelors, 13, Separated, Prof-specialty, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 35, Private, 186815, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 103925, Some-college, 10, Never-married, Tech-support, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 53, ?, 150393, HS-grad, 9, Never-married, ?, Not-in-family, White, Male, 0, 1504, 35, United-States, <=50K 20, Private, 82777, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 16, United-States, <=50K 31, Local-gov, 178449, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 51672, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 46, Private, 380162, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, Black, Male, 0, 0, 40, United-States, >50K 21, Private, 212114, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 8, United-States, <=50K 41, Self-emp-not-inc, 100800, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 70, United-States, >50K 30, Private, 162572, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 70, United-States, >50K 66, Self-emp-inc, 179951, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 70, United-States, <=50K 37, Self-emp-inc, 190759, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 74, State-gov, 236012, 7th-8th, 4, Widowed, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 46, State-gov, 164023, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 70, United-States, >50K 51, Private, 172046, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 50, United-States, >50K 33, Private, 182926, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 30, Private, 151001, 5th-6th, 3, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 3464, 0, 40, Mexico, <=50K 47, Self-emp-inc, 362835, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 49, Private, 97883, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 53, Private, 91911, HS-grad, 9, Divorced, Craft-repair, Unmarried, Black, Female, 0, 0, 48, United-States, <=50K 24, Private, 278130, Assoc-voc, 11, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 146310, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 32, Private, 379412, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 37987, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 46, Self-emp-inc, 256909, HS-grad, 9, Married-spouse-absent, Farming-fishing, Not-in-family, White, Male, 3325, 0, 45, United-States, <=50K 37, State-gov, 482927, Some-college, 10, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 48, State-gov, 44434, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 61, United-States, >50K 25, Private, 255474, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, ?, 303674, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 3103, 0, 20, United-States, <=50K 44, ?, 195488, 12th, 8, Separated, ?, Not-in-family, White, Female, 0, 0, 36, Puerto-Rico, <=50K 58, ?, 114362, Some-college, 10, Married-civ-spouse, ?, Husband, Black, Male, 0, 0, 30, United-States, <=50K 27, Private, 341504, Some-college, 10, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 69, Private, 197080, HS-grad, 9, Widowed, Adm-clerical, Unmarried, White, Male, 0, 0, 8, United-States, <=50K 38, Private, 102945, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 52, United-States, >50K 47, Private, 503454, 12th, 8, Never-married, Adm-clerical, Other-relative, Black, Female, 0, 0, 40, United-States, <=50K 30, Self-emp-not-inc, 87561, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 46, Private, 270693, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 3674, 0, 30, United-States, <=50K 27, Private, 252813, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 19, Private, 574271, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 35, United-States, <=50K 18, Private, 184016, HS-grad, 9, Married-civ-spouse, Priv-house-serv, Not-in-family, White, Female, 3103, 0, 40, United-States, <=50K 24, Private, 235071, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 32, Private, 158242, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 299810, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, United-States, <=50K 19, Private, 277695, Preschool, 1, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 36, Hong, <=50K 28, Private, 23324, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Local-gov, 316582, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 38, Self-emp-not-inc, 176657, Some-college, 10, Separated, Sales, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 60, Japan, <=50K 42, Private, 93770, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, United-States, >50K 31, Private, 124569, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 46, Private, 117313, 9th, 5, Separated, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, Ireland, <=50K 53, Private, 53812, Some-college, 10, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 54, United-States, <=50K 21, Private, 170456, Assoc-acdm, 12, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 15, United-States, <=50K 48, Self-emp-not-inc, 115971, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 46, Private, 31432, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 3103, 0, 52, United-States, >50K 30, Private, 112383, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 24, Private, 283092, HS-grad, 9, Never-married, Adm-clerical, Other-relative, Black, Male, 0, 0, 40, Jamaica, <=50K 32, Private, 27207, 10th, 6, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 30, Private, 46712, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 57, State-gov, 19520, Doctorate, 16, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 56, Private, 98630, 7th-8th, 4, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 159897, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, Black, Female, 0, 0, 37, United-States, <=50K 38, Private, 136629, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Iran, <=50K 19, Private, 407759, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 61, Self-emp-not-inc, 221884, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, >50K 49, Private, 148475, Assoc-voc, 11, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 274964, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 38, United-States, <=50K 50, Self-emp-inc, 160107, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 43, Private, 167265, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 84, United-States, >50K 34, Private, 148226, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 48, United-States, <=50K 28, Private, 153869, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 208881, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 256953, HS-grad, 9, Widowed, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 44, United-States, <=50K 26, Private, 100147, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 45, United-States, >50K 51, Local-gov, 166461, Doctorate, 16, Married-civ-spouse, Prof-specialty, Wife, Black, Female, 0, 0, 40, United-States, >50K 35, Private, 171327, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 297335, Assoc-acdm, 12, Married-spouse-absent, Exec-managerial, Unmarried, Asian-Pac-Islander, Female, 0, 0, 31, Laos, <=50K 63, ?, 133166, Doctorate, 16, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 12, United-States, <=50K 31, Private, 169589, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 22, Local-gov, 273734, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 20, United-States, <=50K 67, Private, 158301, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 50, ?, 257117, 9th, 5, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 50, United-States, <=50K 63, Private, 196725, HS-grad, 9, Widowed, Other-service, Unmarried, White, Female, 0, 0, 24, United-States, <=50K 31, Private, 137444, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 17, Private, 286960, 11th, 7, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 41, Local-gov, 201435, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 53, Local-gov, 216931, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 38, United-States, <=50K 44, Local-gov, 212665, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 99, United-States, <=50K 24, Private, 462820, Bachelors, 13, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 198841, Assoc-voc, 11, Divorced, Tech-support, Own-child, White, Male, 0, 0, 35, United-States, <=50K 61, Private, 219886, Some-college, 10, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 40, United-States, >50K 31, Private, 163003, Assoc-acdm, 12, Never-married, Prof-specialty, Other-relative, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 44, Private, 112262, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 5178, 0, 40, United-States, >50K 56, Private, 213105, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 36, United-States, >50K 66, Private, 302072, Assoc-acdm, 12, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 338105, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Vietnam, <=50K 69, Self-emp-not-inc, 58213, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 20051, 0, 45, United-States, >50K 64, Private, 125684, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 215419, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 36, United-States, >50K 43, Local-gov, 413760, Some-college, 10, Separated, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 37, Private, 205339, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 49, United-States, <=50K 19, Private, 236570, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 16, United-States, <=50K 59, Self-emp-not-inc, 247552, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Federal-gov, 184007, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 341187, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 56, Private, 220187, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 45, United-States, >50K 28, Private, 198258, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 175821, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 34, United-States, <=50K 42, Private, 92288, Masters, 14, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 0, 40, ?, <=50K 34, Private, 261418, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 203319, 11th, 7, Never-married, Sales, Own-child, White, Male, 0, 0, 30, United-States, <=50K 68, Self-emp-not-inc, 166083, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 109001, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 38, United-States, >50K 81, ?, 106765, Some-college, 10, Widowed, ?, Unmarried, White, Female, 0, 0, 4, United-States, <=50K 22, Self-emp-not-inc, 197387, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 58, Private, 284834, Assoc-acdm, 12, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 87535, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 17, Local-gov, 175587, 11th, 7, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 30, United-States, <=50K 25, Private, 242700, Some-college, 10, Never-married, Transport-moving, Not-in-family, White, Male, 10520, 0, 50, United-States, >50K 23, Private, 161478, Some-college, 10, Never-married, Other-service, Own-child, Asian-Pac-Islander, Female, 0, 0, 23, United-States, <=50K 25, Private, 51498, 12th, 8, Never-married, Other-service, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 220124, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 188503, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 60, United-States, >50K 44, Private, 113324, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 208872, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Self-emp-not-inc, 34180, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 35, United-States, <=50K 23, Private, 292023, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 30, United-States, <=50K 34, Private, 141118, Bachelors, 13, Married-spouse-absent, Prof-specialty, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 33, Private, 348592, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 38, Private, 185203, HS-grad, 9, Widowed, Other-service, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 52, Self-emp-not-inc, 165278, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 116933, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 33, United-States, <=50K 38, Private, 237608, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 2444, 45, United-States, >50K 35, Private, 84787, Bachelors, 13, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 67, Self-emp-not-inc, 217892, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 10605, 0, 35, United-States, >50K 60, Private, 325971, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 7688, 0, 40, United-States, >50K 44, Private, 206878, HS-grad, 9, Never-married, Sales, Other-relative, White, Female, 0, 0, 15, United-States, <=50K 38, Self-emp-not-inc, 127772, HS-grad, 9, Divorced, Farming-fishing, Own-child, White, Male, 0, 0, 50, United-States, <=50K 29, Private, 208577, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 65, Private, 344152, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 5556, 0, 50, United-States, >50K 33, Private, 40681, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, ?, 95108, HS-grad, 9, Never-married, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 280603, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 30, United-States, <=50K 43, Private, 188436, Prof-school, 15, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 134220, Assoc-voc, 11, Divorced, Exec-managerial, Own-child, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 42, Private, 177989, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 164190, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 30, United-States, <=50K 36, Private, 90897, Assoc-acdm, 12, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 41, State-gov, 33126, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Private, 270886, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 216129, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 35, United-States, <=50K 33, Private, 189368, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, >50K 19, ?, 141418, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 15, United-States, <=50K 19, Private, 306225, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 25, United-States, <=50K 35, Private, 330664, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 191765, HS-grad, 9, Divorced, Tech-support, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 45, Private, 289353, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 24, United-States, <=50K 25, Private, 53147, Bachelors, 13, Never-married, Exec-managerial, Own-child, Black, Male, 0, 0, 50, United-States, <=50K 39, Self-emp-not-inc, 122353, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 188767, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 60, Private, 239576, Masters, 14, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 10, United-States, <=50K 52, Local-gov, 155141, Doctorate, 16, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 22, Private, 64520, 12th, 8, Never-married, Transport-moving, Unmarried, White, Male, 0, 0, 30, United-States, <=50K 23, Private, 478994, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 155654, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, <=50K 34, Self-emp-not-inc, 124052, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 30, United-States, <=50K 39, Private, 245053, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 38, Private, 183585, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 56, Self-emp-not-inc, 323639, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 25, United-States, <=50K 55, Federal-gov, 186791, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 284303, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 7688, 0, 40, United-States, >50K 23, Private, 186666, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 200153, Bachelors, 13, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 180931, Bachelors, 13, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 30, United-States, <=50K 51, Self-emp-not-inc, 183173, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 47, Self-emp-inc, 120131, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, Cuba, >50K 25, Self-emp-not-inc, 263300, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 34, Private, 226443, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 18, Private, 404868, 11th, 7, Never-married, Sales, Own-child, Black, Female, 0, 1602, 20, United-States, <=50K 19, Private, 208506, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 28, United-States, <=50K 32, Private, 46746, Some-college, 10, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 246183, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 40, ?, 165309, 7th-8th, 4, Separated, ?, Not-in-family, White, Female, 0, 0, 8, United-States, <=50K 43, Private, 122749, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, <=50K 71, Self-emp-inc, 38822, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 40, United-States, >50K 59, Private, 167963, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 273241, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 25, Private, 120238, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 167990, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, Ireland, <=50K 17, Private, 225507, 11th, 7, Never-married, Handlers-cleaners, Not-in-family, Black, Female, 0, 0, 15, United-States, <=50K 57, Self-emp-inc, 125000, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, >50K 17, Self-emp-not-inc, 174120, 12th, 8, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 15, United-States, <=50K 27, Private, 230959, Bachelors, 13, Never-married, Tech-support, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 41, Local-gov, 132125, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 62, ?, 68461, Doctorate, 16, Married-civ-spouse, ?, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, >50K 19, Private, 227178, 11th, 7, Never-married, Sales, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 41, Private, 165798, 5th-6th, 3, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, Puerto-Rico, <=50K 39, Private, 129573, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 30, Private, 224377, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 179481, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 18, Private, 434268, 11th, 7, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 15, United-States, <=50K 40, Self-emp-not-inc, 173716, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 38, Self-emp-inc, 244803, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 1485, 60, Cuba, >50K 24, Private, 114230, HS-grad, 9, Never-married, Sales, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 188661, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 48, Private, 216093, Bachelors, 13, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 124963, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 48, Private, 85341, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 193490, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 34, Private, 80058, Prof-school, 15, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 50, United-States, <=50K 41, Private, 139907, Assoc-voc, 11, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 51, Self-emp-inc, 54342, Prof-school, 15, Divorced, Prof-specialty, Not-in-family, White, Male, 27828, 0, 60, United-States, >50K 25, Private, 188767, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 117222, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 50, United-States, <=50K 61, Self-emp-inc, 171831, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 2829, 0, 45, United-States, <=50K 35, Private, 187119, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 70, United-States, <=50K 42, Local-gov, 97277, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 26, Local-gov, 219760, HS-grad, 9, Never-married, Other-service, Other-relative, White, Male, 0, 0, 16, United-States, <=50K 46, Private, 63299, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 50, United-States, <=50K 39, State-gov, 171482, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 18, ?, 344742, 10th, 6, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 210869, Some-college, 10, Never-married, Sales, Own-child, Black, Male, 0, 0, 80, United-States, <=50K 39, Private, 38312, Some-college, 10, Married-spouse-absent, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, >50K 47, Private, 119939, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Private, 83953, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 43, State-gov, 101383, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Private, 204374, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 176831, 10th, 6, Divorced, Sales, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 19, ?, 60688, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 35, United-States, <=50K 44, Federal-gov, 251305, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Local-gov, 200947, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 53, Self-emp-not-inc, 46704, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 43, Private, 119721, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, State-gov, 58930, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 247750, HS-grad, 9, Widowed, Other-service, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 48, Private, 67725, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 28, State-gov, 200775, Masters, 14, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 183542, Bachelors, 13, Widowed, Prof-specialty, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 20, ?, 25139, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 51, Local-gov, 123325, Prof-school, 15, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 269786, HS-grad, 9, Never-married, Transport-moving, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 36, Private, 51089, Bachelors, 13, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 28, Private, 136985, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 35, United-States, <=50K 21, Private, 129350, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 34, ?, 35595, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 30, United-States, <=50K 36, Local-gov, 61299, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, ?, 192321, Assoc-acdm, 12, Never-married, ?, Own-child, White, Female, 0, 0, 80, United-States, <=50K 31, Private, 257644, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 43, United-States, <=50K 44, Self-emp-not-inc, 70884, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 49, Local-gov, 159726, 11th, 7, Divorced, Handlers-cleaners, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 174395, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 64, Federal-gov, 175534, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, China, >50K 54, Local-gov, 173050, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 40, United-States, >50K 27, Private, 32519, Some-college, 10, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 0, 55, South, <=50K 18, Private, 322999, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 68, Private, 148874, 9th, 5, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 44, United-States, <=50K 64, Private, 43738, Doctorate, 16, Widowed, Prof-specialty, Not-in-family, White, Male, 0, 0, 80, United-States, >50K 36, Private, 195385, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 21, Private, 149809, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 24, United-States, <=50K 22, Private, 51985, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 30, United-States, <=50K 61, Private, 105384, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 137591, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 10, Greece, <=50K 49, State-gov, 324791, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 25, Private, 184303, Some-college, 10, Separated, Priv-house-serv, Other-relative, White, Female, 0, 0, 30, El-Salvador, <=50K 66, ?, 314347, HS-grad, 9, Married-civ-spouse, ?, Husband, Black, Male, 0, 0, 40, United-States, <=50K 29, Private, 274010, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 22, Private, 321031, HS-grad, 9, Never-married, Sales, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 57, Federal-gov, 313929, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 41, Private, 394669, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 1741, 40, United-States, <=50K 29, Private, 152951, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Private, 247115, Some-college, 10, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 47, Private, 175958, Prof-school, 15, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 22, Private, 109039, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 59, Self-emp-inc, 141326, Assoc-voc, 11, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 42, State-gov, 74334, Masters, 14, Married-civ-spouse, Adm-clerical, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, >50K 64, Self-emp-not-inc, 47462, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 29, Federal-gov, 182344, HS-grad, 9, Married-spouse-absent, Other-service, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 25, State-gov, 295912, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 62, Private, 311495, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 236746, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Male, 10520, 0, 45, United-States, >50K 21, Private, 187643, HS-grad, 9, Separated, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 60, Private, 282923, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7298, 0, 40, United-States, >50K 46, Private, 501671, 10th, 6, Divorced, Machine-op-inspct, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 44, Federal-gov, 29591, Bachelors, 13, Divorced, Tech-support, Not-in-family, White, Male, 0, 2258, 40, United-States, >50K 21, Private, 301556, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 19, United-States, <=50K 18, Private, 187240, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 18, United-States, <=50K 39, Private, 219483, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 5013, 0, 32, United-States, <=50K 33, Private, 594187, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 63, Private, 200474, 1st-4th, 2, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 52, Local-gov, 152795, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 52, United-States, >50K 17, Private, 230789, 9th, 5, Never-married, Sales, Own-child, Black, Male, 0, 0, 22, United-States, <=50K 45, Self-emp-inc, 311231, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1485, 50, United-States, >50K 31, Private, 114691, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 194591, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 114691, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 51, State-gov, 42017, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 48, Local-gov, 383384, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 28, Private, 29444, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 42, Federal-gov, 53727, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, ?, <=50K 38, Private, 277022, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, Columbia, <=50K 43, Local-gov, 113324, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Private, 342709, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 179203, 12th, 8, Never-married, Sales, Other-relative, White, Male, 0, 0, 55, United-States, <=50K 46, Private, 251474, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 50, Private, 93730, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 22, Private, 37894, HS-grad, 9, Separated, Other-service, Other-relative, White, Male, 0, 0, 35, United-States, <=50K 18, State-gov, 272918, HS-grad, 9, Never-married, Adm-clerical, Own-child, Black, Male, 0, 0, 15, United-States, <=50K 53, Private, 151411, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 40, Private, 210648, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 44, United-States, >50K 36, Self-emp-not-inc, 347491, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, <=50K 32, Private, 255885, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 43, United-States, >50K 39, Private, 356838, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 12, United-States, <=50K 46, Private, 216164, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Local-gov, 288781, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 42, United-States, <=50K 19, Private, 439779, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 15, United-States, <=50K 24, Private, 161638, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, Ecuador, <=50K 28, Private, 190525, Masters, 14, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Local-gov, 276249, Masters, 14, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 147265, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 245090, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Nicaragua, <=50K 42, State-gov, 219682, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 28, Private, 392100, HS-grad, 9, Married-civ-spouse, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 358682, Bachelors, 13, Never-married, Exec-managerial, Other-relative, White, Male, 0, 0, 50, ?, <=50K 47, Private, 262244, Bachelors, 13, Never-married, Sales, Not-in-family, Black, Male, 0, 0, 60, United-States, >50K 46, Private, 171228, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 3411, 0, 35, Guatemala, <=50K 21, Local-gov, 218445, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, Mexico, <=50K 19, ?, 182609, HS-grad, 9, Never-married, ?, Own-child, Black, Female, 0, 0, 25, United-States, <=50K 35, Private, 509462, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 26, Private, 213258, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 118401, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 67, Self-emp-not-inc, 45814, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 329733, HS-grad, 9, Never-married, Exec-managerial, Unmarried, White, Male, 0, 0, 40, United-States, >50K 26, Private, 29957, Masters, 14, Never-married, Tech-support, Other-relative, White, Male, 0, 0, 25, United-States, <=50K 51, Private, 215854, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 27, Private, 327766, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 27, Private, 405765, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, ?, >50K 39, Private, 80680, Some-college, 10, Divorced, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 177792, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 48, United-States, >50K 52, Private, 273514, HS-grad, 9, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 202373, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, United-States, <=50K 27, Local-gov, 332785, HS-grad, 9, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 38, United-States, <=50K 46, Private, 149640, 7th-8th, 4, Married-spouse-absent, Transport-moving, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 42, Private, 40151, Assoc-voc, 11, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 30, United-States, <=50K 79, Self-emp-inc, 183686, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 20, United-States, >50K 50, Federal-gov, 32801, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, >50K 19, ?, 195282, HS-grad, 9, Never-married, ?, Own-child, Black, Female, 0, 0, 20, United-States, <=50K 43, Federal-gov, 134026, Some-college, 10, Never-married, Adm-clerical, Other-relative, White, Male, 2174, 0, 40, United-States, <=50K 51, Local-gov, 96678, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 45, Private, 174533, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 7298, 0, 50, United-States, >50K 65, Private, 180807, HS-grad, 9, Separated, Protective-serv, Not-in-family, White, Male, 991, 0, 20, United-States, <=50K 66, Private, 186324, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 5, United-States, >50K 36, Self-emp-not-inc, 257250, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 99, United-States, <=50K 26, Private, 212800, Assoc-acdm, 12, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 36, United-States, <=50K 28, Private, 55360, Some-college, 10, Never-married, Sales, Not-in-family, Black, Male, 0, 0, 50, United-States, <=50K 39, Self-emp-not-inc, 195253, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 43, Private, 45156, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 20, Private, 435469, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, Mexico, <=50K 29, Private, 231287, Some-college, 10, Divorced, Tech-support, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 168854, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 1848, 50, United-States, >50K 44, Self-emp-not-inc, 185057, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Female, 3325, 0, 40, United-States, <=50K 18, ?, 91670, Some-college, 10, Never-married, ?, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 60, Private, 165517, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 73161, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 60, Private, 178792, HS-grad, 9, Widowed, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 32897, 11th, 7, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 250967, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 41901, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 1408, 40, United-States, <=50K 49, Private, 379779, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 37, Private, 217838, 5th-6th, 3, Separated, Other-service, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 37, Self-emp-not-inc, 137527, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 2559, 60, United-States, >50K 43, Private, 198965, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 38, United-States, >50K 41, Private, 70645, Masters, 14, Widowed, Prof-specialty, Not-in-family, White, Female, 4650, 0, 55, United-States, <=50K 37, Private, 220644, HS-grad, 9, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 40, ?, <=50K 19, Private, 175081, 9th, 5, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 60, United-States, <=50K 29, Private, 180299, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 35, United-States, <=50K 40, Self-emp-not-inc, 548664, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 15, United-States, <=50K 53, Private, 278114, 7th-8th, 4, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 394927, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, <=50K 44, Self-emp-not-inc, 127482, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 50, England, >50K 29, Private, 236938, Assoc-acdm, 12, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 25, Private, 232991, 5th-6th, 3, Married-civ-spouse, Machine-op-inspct, Husband, Other, Male, 0, 0, 40, Mexico, <=50K 38, Private, 34378, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, <=50K 48, Self-emp-inc, 81513, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 18, Private, 106780, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 12, United-States, <=50K 50, Private, 178596, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 1408, 50, United-States, <=50K 37, Private, 329026, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 48, Private, 26490, Bachelors, 13, Widowed, Other-service, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 50, Private, 338033, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 32, United-States, <=50K 74, ?, 169303, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 6767, 0, 6, United-States, <=50K 24, Private, 21154, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 30, United-States, <=50K 34, Private, 209449, Some-college, 10, Married-civ-spouse, Tech-support, Husband, Black, Male, 0, 0, 40, United-States, >50K 19, Private, 389143, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 101260, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 198270, Some-college, 10, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 45781, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 134566, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, ?, 283806, 9th, 5, Divorced, ?, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 68, ?, 286869, 7th-8th, 4, Widowed, ?, Not-in-family, White, Female, 0, 1668, 40, ?, <=50K 46, Private, 422813, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 24, Local-gov, 103277, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 50, United-States, <=50K 18, Private, 201871, 12th, 8, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 50, Self-emp-not-inc, 167728, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 42, Private, 211517, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 118212, 9th, 5, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 259846, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Husband, White, Male, 3471, 0, 40, United-States, <=50K 57, Private, 98926, Some-college, 10, Widowed, Tech-support, Not-in-family, White, Female, 0, 0, 16, United-States, <=50K 27, Private, 207352, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, Asian-Pac-Islander, Male, 0, 0, 40, India, >50K 31, Private, 206609, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Local-gov, 104509, Masters, 14, Separated, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 55, Self-emp-not-inc, 170350, HS-grad, 9, Divorced, Other-service, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 56, Private, 183884, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, State-gov, 110964, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 1672, 38, United-States, <=50K 35, State-gov, 154410, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 63, ?, 257659, Masters, 14, Never-married, ?, Not-in-family, White, Female, 0, 0, 3, United-States, <=50K 28, Private, 274679, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 38, Private, 252662, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Self-emp-inc, 356689, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 60, United-States, <=50K 18, Private, 205218, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 35, Private, 241306, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 53, Private, 139127, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 175625, Prof-school, 15, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 206459, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 176123, 10th, 6, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 60, India, <=50K 41, Private, 111483, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 60, Self-emp-not-inc, 106118, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 70, United-States, >50K 18, Private, 77845, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 1602, 15, United-States, <=50K 19, Private, 162094, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 216469, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 1579, 50, United-States, <=50K 56, Local-gov, 381965, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 40, United-States, >50K 28, Private, 145284, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 29, Private, 242482, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 32, United-States, <=50K 35, Self-emp-not-inc, 160192, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 27, ?, 280699, Some-college, 10, Never-married, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 55, Private, 175942, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 55, ?, >50K 18, Private, 156950, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 35, United-States, <=50K 53, Private, 215572, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 173593, Masters, 14, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 20, Canada, <=50K 55, Private, 193374, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 45, Local-gov, 334039, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 337664, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 113504, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 177072, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 174503, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 214807, HS-grad, 9, Divorced, Handlers-cleaners, Unmarried, White, Female, 0, 0, 37, United-States, <=50K 41, Private, 222596, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 45, United-States, >50K 23, Private, 100345, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 0, 20, United-States, <=50K 22, Private, 409230, 12th, 8, Never-married, Transport-moving, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 36, Self-emp-not-inc, 112497, Prof-school, 15, Divorced, Prof-specialty, Unmarried, White, Male, 25236, 0, 40, United-States, >50K 65, Self-emp-inc, 115922, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 59, ?, 375049, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 41, United-States, >50K 25, Private, 243560, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 40, Columbia, <=50K 33, Local-gov, 182971, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 1887, 40, United-States, >50K 31, Private, 127215, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, State-gov, 276241, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 49, State-gov, 175109, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 43, Private, 498079, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 23, Federal-gov, 344394, Some-college, 10, Married-civ-spouse, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 99872, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 3103, 0, 40, India, >50K 23, Private, 245302, Some-college, 10, Divorced, Sales, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 63, Private, 43313, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 188467, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 51, Self-emp-inc, 351278, Bachelors, 13, Divorced, Farming-fishing, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 31, Private, 182246, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 32, Private, 79870, Some-college, 10, Married-civ-spouse, Exec-managerial, Own-child, White, Female, 2597, 0, 40, Japan, <=50K 48, ?, 353824, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, ?, >50K 31, Private, 387116, Some-college, 10, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 36, Jamaica, <=50K 47, Private, 34248, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 54, State-gov, 198741, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Private, 32950, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 381153, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Private, 100067, 11th, 7, Married-civ-spouse, Other-service, Wife, Black, Female, 0, 0, 35, United-States, >50K 34, Private, 208785, Assoc-acdm, 12, Divorced, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 31, Private, 61559, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 41, Private, 176452, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, Peru, <=50K 41, ?, 128700, HS-grad, 9, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 27, Self-emp-not-inc, 328518, Assoc-voc, 11, Never-married, Prof-specialty, Other-relative, White, Male, 0, 0, 30, United-States, <=50K 30, ?, 201196, 11th, 7, Never-married, ?, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 23, Private, 378546, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 24, Local-gov, 212210, Assoc-acdm, 12, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, ?, <=50K 59, Federal-gov, 178660, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, Private, 235826, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 5013, 0, 40, United-States, <=50K 35, Self-emp-not-inc, 22641, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 59, Private, 316027, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 45, Cuba, <=50K 47, Private, 431515, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 51, Self-emp-not-inc, 149770, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 44, United-States, <=50K 42, Private, 165916, Bachelors, 13, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 29, Federal-gov, 107411, Some-college, 10, Married-spouse-absent, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 217961, HS-grad, 9, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 45, Outlying-US(Guam-USVI-etc), <=50K 43, Self-emp-not-inc, 350387, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 46, Private, 325372, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 156718, Some-college, 10, Separated, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 216472, Some-college, 10, Never-married, Tech-support, Own-child, White, Female, 0, 0, 20, United-States, <=50K 29, State-gov, 106972, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 33, Private, 131934, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 33, Local-gov, 365908, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 2105, 0, 40, United-States, <=50K 46, Local-gov, 359193, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 35, Private, 261012, Some-college, 10, Married-spouse-absent, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 36, Private, 272944, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1887, 40, United-States, >50K 25, Private, 113654, HS-grad, 9, Separated, Exec-managerial, Unmarried, White, Female, 0, 0, 37, United-States, <=50K 35, Private, 218955, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 115963, 7th-8th, 4, Never-married, Machine-op-inspct, Unmarried, White, Male, 0, 0, 42, United-States, <=50K 39, Private, 80638, Some-college, 10, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 84, United-States, >50K 37, Private, 147258, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, <=50K 22, Private, 214635, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 42, United-States, <=50K 25, Private, 200318, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 50, Private, 138270, HS-grad, 9, Married-civ-spouse, Sales, Wife, Black, Female, 0, 0, 40, United-States, <=50K 64, Federal-gov, 388594, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 45, ?, >50K 33, Private, 103435, Assoc-voc, 11, Separated, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 59, Self-emp-inc, 133201, 5th-6th, 3, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, Italy, <=50K 24, Private, 175183, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 99870, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, <=50K 38, ?, 107479, 9th, 5, Never-married, ?, Own-child, White, Female, 0, 0, 12, United-States, <=50K 60, Private, 113440, Bachelors, 13, Divorced, Exec-managerial, Own-child, White, Male, 0, 0, 60, United-States, <=50K 19, Private, 85690, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, White, Male, 0, 0, 30, United-States, <=50K 23, Private, 45713, Some-college, 10, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 57, Self-emp-inc, 376230, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 99999, 0, 40, United-States, >50K 36, Private, 145576, Masters, 14, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 1977, 40, Japan, >50K 17, ?, 67808, 10th, 6, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 113936, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 158291, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 27, Private, 193898, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 43, Private, 191982, Assoc-voc, 11, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 55, United-States, <=50K 21, ?, 72953, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 271160, Assoc-voc, 11, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 33087, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 45, United-States, <=50K 29, Private, 106153, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 22, Private, 29444, 12th, 8, Never-married, Farming-fishing, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 50, United-States, <=50K 37, Private, 105021, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 38, Self-emp-not-inc, 239045, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 34, Private, 94413, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 20534, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 84, United-States, >50K 28, Private, 350254, 1st-4th, 2, Never-married, Priv-house-serv, Not-in-family, White, Female, 0, 0, 40, Mexico, <=50K 68, Private, 194746, Doctorate, 16, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, Cuba, <=50K 36, Private, 269042, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Laos, <=50K 20, Private, 447488, 9th, 5, Never-married, Other-service, Unmarried, White, Male, 0, 0, 30, Mexico, <=50K 24, Private, 267706, Some-college, 10, Never-married, Craft-repair, Own-child, White, Female, 0, 0, 45, United-States, <=50K 38, Private, 198216, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 227931, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 252646, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7298, 0, 50, United-States, >50K 47, Private, 223342, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 2174, 0, 40, England, <=50K 28, Private, 181776, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 32, Private, 132601, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 58, Private, 205410, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 64, Self-emp-inc, 185912, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 35, United-States, >50K 38, Private, 292570, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 50, United-States, <=50K 43, Private, 76460, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 295163, 12th, 8, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 27255, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, ?, <=50K 23, Private, 69847, Bachelors, 13, Never-married, Prof-specialty, Own-child, Asian-Pac-Islander, Female, 0, 0, 20, United-States, <=50K 25, Private, 104993, 9th, 5, Never-married, Handlers-cleaners, Own-child, Black, Male, 2907, 0, 40, United-States, <=50K 41, Private, 322980, HS-grad, 9, Separated, Adm-clerical, Not-in-family, Black, Male, 2354, 0, 40, United-States, <=50K 24, ?, 390608, HS-grad, 9, Never-married, ?, Not-in-family, White, Female, 0, 0, 36, United-States, <=50K 41, Private, 317539, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 27, Private, 195678, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 466502, 7th-8th, 4, Widowed, Other-service, Unmarried, White, Male, 0, 0, 30, United-States, <=50K 28, Local-gov, 220754, HS-grad, 9, Separated, Transport-moving, Own-child, White, Female, 0, 0, 25, United-States, <=50K 29, Private, 202878, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 2042, 40, United-States, <=50K 36, Private, 343476, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 41, Self-emp-inc, 93227, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 1977, 60, Taiwan, >50K 60, Self-emp-not-inc, 38622, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, State-gov, 173730, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 38, United-States, <=50K 32, Private, 178623, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 40, ?, <=50K 27, Private, 300783, Some-college, 10, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 42, United-States, >50K 60, Private, 224644, 10th, 6, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 191502, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 59, Private, 61885, 12th, 8, Divorced, Transport-moving, Other-relative, Black, Male, 0, 0, 35, United-States, <=50K 34, Self-emp-not-inc, 213887, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 32, Canada, >50K 36, Private, 331395, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 145098, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 48, Private, 123075, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 19, Private, 216804, 7th-8th, 4, Never-married, Other-service, Own-child, White, Male, 0, 0, 33, United-States, <=50K 40, Private, 188291, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Private, 33610, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 39, Private, 234901, Assoc-acdm, 12, Separated, Adm-clerical, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 34, Self-emp-not-inc, 349148, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 168443, HS-grad, 9, Separated, Other-service, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 43, Private, 211860, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 24, United-States, <=50K 35, Private, 193961, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, >50K 36, Local-gov, 52532, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1887, 50, United-States, >50K 59, Self-emp-not-inc, 75804, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 65, United-States, >50K 33, Self-emp-not-inc, 176185, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 306779, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 50, United-States, <=50K 48, Private, 265192, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 54, Private, 139347, HS-grad, 9, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 107682, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 37, Private, 34173, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 128378, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 51, Self-emp-inc, 195638, Some-college, 10, Separated, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 59287, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Self-emp-not-inc, 162442, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 29, ?, 350603, 10th, 6, Never-married, ?, Own-child, White, Female, 0, 0, 38, United-States, <=50K 39, Private, 344743, Some-college, 10, Married-civ-spouse, Adm-clerical, Own-child, Black, Female, 0, 0, 50, United-States, >50K 35, Private, 112077, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 5013, 0, 40, United-States, <=50K 26, Private, 176795, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, >50K 51, Private, 137815, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 7298, 0, 40, United-States, >50K 31, Private, 309620, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 6, South, <=50K 39, Private, 336880, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 206600, 11th, 7, Never-married, Other-service, Other-relative, White, Male, 0, 0, 30, Mexico, <=50K 25, Private, 193051, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 35, United-States, <=50K 61, Federal-gov, 229062, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 1887, 40, United-States, >50K 49, Private, 62793, HS-grad, 9, Divorced, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 53, Private, 264939, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, Mexico, <=50K 52, Private, 370552, Preschool, 1, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, El-Salvador, <=50K 52, Private, 163678, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 55, United-States, <=50K 74, ?, 89667, Bachelors, 13, Widowed, ?, Not-in-family, Other, Female, 0, 0, 35, United-States, <=50K 50, Private, 558490, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 29, Private, 124680, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 13550, 0, 35, United-States, >50K 76, Private, 208843, 7th-8th, 4, Widowed, Protective-serv, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 19, Private, 95078, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 15, United-States, <=50K 25, Private, 169679, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 101320, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 168906, Assoc-acdm, 12, Divorced, Adm-clerical, Own-child, White, Female, 0, 0, 35, United-States, <=50K 20, Private, 212582, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 16, United-States, <=50K 66, ?, 170617, Masters, 14, Widowed, ?, Not-in-family, White, Male, 0, 0, 6, United-States, <=50K 63, ?, 170529, Bachelors, 13, Married-civ-spouse, ?, Wife, Black, Female, 0, 0, 45, United-States, <=50K 27, Private, 99897, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 104892, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 2829, 0, 40, United-States, <=50K 43, Private, 175224, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 60, Nicaragua, <=50K 23, Private, 149704, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 37, Federal-gov, 214542, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 31, Private, 167319, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, State-gov, 43716, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 4, United-States, <=50K 28, Private, 191935, Assoc-acdm, 12, Never-married, Sales, Own-child, White, Male, 0, 0, 20, United-States, <=50K 70, ?, 158642, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 2993, 0, 20, United-States, <=50K 35, Private, 338611, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 136419, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 75, United-States, >50K 17, Private, 72321, 11th, 7, Never-married, Other-service, Other-relative, White, Female, 0, 0, 12, United-States, <=50K 41, Local-gov, 189956, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, Black, Female, 0, 0, 40, United-States, >50K 44, Private, 403782, Assoc-voc, 11, Divorced, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 47, Private, 456661, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Mexico, <=50K 24, Private, 279041, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 38, Self-emp-not-inc, 65716, Assoc-voc, 11, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 189809, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 52, Jamaica, <=50K 62, Local-gov, 223637, HS-grad, 9, Divorced, Other-service, Not-in-family, Black, Female, 0, 0, 35, United-States, <=50K 27, Local-gov, 199343, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 38, United-States, <=50K 59, Private, 139344, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 35, Private, 119098, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 195025, HS-grad, 9, Separated, Other-service, Unmarried, Black, Female, 0, 0, 32, United-States, <=50K 28, Private, 186720, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 50, United-States, <=50K 28, Private, 328923, HS-grad, 9, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 38, United-States, <=50K 59, State-gov, 159472, 9th, 5, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 138662, Some-college, 10, Separated, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 54, Local-gov, 286342, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 32, United-States, >50K 39, Private, 181705, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, <=50K 41, Private, 193882, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 216497, Bachelors, 13, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, Germany, <=50K 32, Self-emp-inc, 124919, Bachelors, 13, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 50, Iran, >50K 62, Private, 109463, Some-college, 10, Separated, Sales, Unmarried, White, Female, 0, 1617, 33, United-States, <=50K 58, Private, 256274, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 326379, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 67, ?, 174995, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 2457, 40, United-States, <=50K 31, Private, 243142, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 51, Local-gov, 155118, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 70, United-States, >50K 54, Private, 189607, Bachelors, 13, Never-married, Other-service, Own-child, Black, Female, 0, 0, 36, United-States, <=50K 20, Private, 39478, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 35, Private, 206951, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 22, Private, 127647, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 36, United-States, <=50K 38, Private, 234298, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 6849, 0, 60, United-States, <=50K 42, Private, 182302, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, State-gov, 166597, Masters, 14, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Self-emp-not-inc, 33363, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 70, United-States, >50K 74, Self-emp-inc, 167537, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 35, United-States, >50K 34, Private, 179378, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, Black, Female, 0, 0, 40, United-States, <=50K 50, State-gov, 297551, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 52, United-States, <=50K 50, Private, 198362, Assoc-voc, 11, Widowed, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 240504, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Self-emp-not-inc, 169662, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, ?, 164940, HS-grad, 9, Separated, ?, Unmarried, Black, Female, 0, 0, 25, United-States, <=50K 61, Private, 210488, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 21, Private, 154835, Some-college, 10, Never-married, Adm-clerical, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, Vietnam, <=50K 27, Private, 333296, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 30, ?, <=50K 47, Private, 192793, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, Iran, >50K 39, Private, 49436, Assoc-acdm, 12, Divorced, Prof-specialty, Unmarried, White, Female, 0, 1380, 40, United-States, <=50K 33, Private, 136331, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 509048, HS-grad, 9, Never-married, Sales, Other-relative, Black, Female, 0, 0, 37, United-States, <=50K 38, Private, 318610, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 45, Private, 104521, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 247695, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, >50K 35, Private, 219546, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 45, Germany, <=50K 21, Private, 169699, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 49, State-gov, 131302, Assoc-voc, 11, Divorced, Adm-clerical, Not-in-family, Black, Female, 0, 0, 44, United-States, <=50K 50, Private, 171852, Bachelors, 13, Separated, Prof-specialty, Own-child, Other, Female, 0, 0, 40, United-States, <=50K 36, State-gov, 340091, Doctorate, 16, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 36, United-States, >50K 20, Private, 204641, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 20, United-States, <=50K 49, Private, 213431, HS-grad, 9, Separated, Prof-specialty, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 40, State-gov, 377018, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 22, Private, 184543, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 60, ?, 188236, HS-grad, 9, Divorced, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 67, Private, 233022, 11th, 7, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 21, Private, 177420, Some-college, 10, Never-married, Adm-clerical, Not-in-family, Other, Female, 0, 0, 40, United-States, <=50K 60, Self-emp-not-inc, 21101, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, Amer-Indian-Eskimo, Male, 0, 0, 50, United-States, <=50K 17, Private, 52486, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 12, United-States, <=50K 43, Private, 183273, Masters, 14, Married-civ-spouse, Exec-managerial, Wife, White, Female, 15024, 0, 32, United-States, >50K 49, State-gov, 36177, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 41, Private, 124956, Bachelors, 13, Separated, Prof-specialty, Not-in-family, Black, Female, 99999, 0, 60, United-States, >50K 38, Private, 102350, Some-college, 10, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 165930, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 297574, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 99, United-States, >50K 40, Private, 120277, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, ?, 87569, Some-college, 10, Separated, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 19, ?, 278220, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 1602, 40, United-States, <=50K 40, Private, 155972, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, >50K 46, State-gov, 162852, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 64860, Some-college, 10, Married-spouse-absent, Adm-clerical, Unmarried, White, Female, 0, 0, 22, United-States, <=50K 36, Private, 226013, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 5178, 0, 40, United-States, >50K 24, Private, 322674, Assoc-acdm, 12, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 62, Private, 202242, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, <=50K 54, Private, 175262, Preschool, 1, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, China, <=50K 23, Private, 201682, Bachelors, 13, Married-civ-spouse, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 60, Private, 166330, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 18, Self-emp-inc, 147612, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Female, 0, 0, 8, United-States, <=50K 41, Local-gov, 213154, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 0, 40, United-States, <=50K 45, Local-gov, 33798, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 62, State-gov, 199198, Assoc-voc, 11, Widowed, Exec-managerial, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 28, Private, 90915, Bachelors, 13, Married-spouse-absent, Tech-support, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 36, Self-emp-inc, 337778, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, Yugoslavia, >50K 31, Private, 187203, HS-grad, 9, Never-married, Sales, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 261497, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, ?, <=50K 33, Self-emp-not-inc, 361817, HS-grad, 9, Separated, Craft-repair, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 62, Self-emp-not-inc, 226546, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 16, United-States, <=50K 27, Private, 100168, 7th-8th, 4, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, <=50K 42, Federal-gov, 272625, Assoc-voc, 11, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, >50K 55, Private, 254516, 9th, 5, Never-married, Handlers-cleaners, Other-relative, Black, Male, 0, 0, 37, United-States, <=50K 41, Private, 207375, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 26, Private, 39092, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 4064, 0, 50, United-States, <=50K 45, Private, 48271, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 67, Self-emp-not-inc, 152102, HS-grad, 9, Widowed, Farming-fishing, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 25, Private, 234665, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 30, Self-emp-inc, 127651, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1887, 48, United-States, >50K 22, Private, 180060, Bachelors, 13, Never-married, Exec-managerial, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 32477, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 26, Private, 137658, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 61, Private, 228287, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 32, Private, 159442, Prof-school, 15, Never-married, Sales, Not-in-family, White, Female, 13550, 0, 50, United-States, >50K 43, Private, 33310, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 53, Private, 270546, HS-grad, 9, Divorced, Priv-house-serv, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 53, Federal-gov, 290290, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 42, Self-emp-inc, 287037, 12th, 8, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 10, United-States, <=50K 36, Private, 128516, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 55, Self-emp-not-inc, 185195, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 99, United-States, <=50K 35, Federal-gov, 49657, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7298, 0, 40, United-States, >50K 17, Private, 98005, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 16, United-States, <=50K 55, Self-emp-not-inc, 283635, Prof-school, 15, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 36, Private, 98360, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Local-gov, 202872, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 54, Self-emp-not-inc, 118365, 10th, 6, Divorced, Other-service, Not-in-family, Black, Female, 0, 0, 10, United-States, <=50K 45, Self-emp-not-inc, 184285, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 48, Private, 345831, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Local-gov, 99679, Prof-school, 15, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 31, Private, 253354, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 26, Private, 190650, Bachelors, 13, Never-married, Adm-clerical, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, Taiwan, <=50K 34, Private, 287737, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 1485, 40, United-States, >50K 19, Private, 204389, HS-grad, 9, Never-married, Adm-clerical, Own-child, Other, Female, 0, 0, 25, Puerto-Rico, <=50K 31, Federal-gov, 294870, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 159442, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 55, Local-gov, 161662, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 38, Private, 52738, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 252024, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 20, Mexico, <=50K 27, Private, 189702, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 407913, HS-grad, 9, Separated, Other-service, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 20, Private, 166527, Some-college, 10, Never-married, Adm-clerical, Own-child, Other, Female, 0, 0, 20, United-States, <=50K 24, Self-emp-not-inc, 34918, Assoc-voc, 11, Never-married, Other-service, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 27, Private, 142712, Masters, 14, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, ?, <=50K 18, Federal-gov, 201686, 11th, 7, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 4, United-States, <=50K 28, Local-gov, 179759, Some-college, 10, Married-spouse-absent, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 94954, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 66, Private, 350498, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1258, 20, United-States, <=50K 19, Private, 201743, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 59, Self-emp-not-inc, 119344, 10th, 6, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 36, United-States, <=50K 33, Private, 149726, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 46, United-States, <=50K 28, Private, 419146, 7th-8th, 4, Separated, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 34, Private, 174789, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Male, 0, 2001, 40, United-States, <=50K 41, Private, 171234, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 30, Private, 206325, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 59, Private, 202682, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 121055, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 47, Private, 160187, HS-grad, 9, Separated, Prof-specialty, Other-relative, Black, Female, 14084, 0, 38, United-States, >50K 29, Private, 84366, 10th, 6, Married-spouse-absent, Adm-clerical, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 60, Private, 139391, Some-college, 10, Married-spouse-absent, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 53, Local-gov, 124094, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 5013, 0, 35, United-States, <=50K 41, Private, 30759, 7th-8th, 4, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 32, Private, 137875, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 73, ?, 139049, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 22, United-States, >50K 20, Private, 238384, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 49, Private, 340755, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Local-gov, 224947, Bachelors, 13, Never-married, Prof-specialty, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 33, State-gov, 111994, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 25, Private, 125491, Some-college, 10, Never-married, Other-service, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 34, United-States, <=50K 34, ?, 310525, HS-grad, 9, Married-civ-spouse, ?, Husband, Black, Male, 0, 0, 10, United-States, <=50K 19, ?, 71592, Some-college, 10, Never-married, ?, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 40, Local-gov, 99185, Assoc-acdm, 12, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 249935, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 44, United-States, <=50K 51, Private, 206775, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 50, United-States, <=50K 22, Private, 230704, Assoc-acdm, 12, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 20, Jamaica, <=50K 34, Private, 242361, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 50, United-States, <=50K 22, Private, 134746, 10th, 6, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, <=50K 34, Self-emp-inc, 198613, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 2002, 40, United-States, <=50K 56, Private, 174040, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 165953, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 1902, 40, United-States, <=50K 36, Private, 273604, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 192409, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 26, Self-emp-not-inc, 102476, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 50, United-States, <=50K 48, Private, 234504, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 35, Self-emp-not-inc, 468713, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 84560, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 148995, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 21, Private, 34816, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 12, United-States, <=50K 28, Private, 211184, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 53, Private, 33304, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 65, Federal-gov, 179985, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 219815, Some-college, 10, Married-spouse-absent, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 50, Private, 134766, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 50, United-States, >50K 26, Private, 106548, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 70, Private, 89787, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 20, United-States, <=50K 55, Private, 164857, Some-college, 10, Divorced, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 27, Federal-gov, 257124, Bachelors, 13, Never-married, Transport-moving, Other-relative, White, Male, 0, 0, 35, United-States, <=50K 31, Private, 227446, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, Cuba, >50K 43, Private, 125461, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 1902, 55, United-States, >50K 24, Private, 189749, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 176321, 7th-8th, 4, Never-married, Other-service, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 26, Private, 284250, HS-grad, 9, Never-married, Craft-repair, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 23, Private, 101885, 10th, 6, Never-married, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 41, Self-emp-not-inc, 134130, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 52, Private, 260938, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Self-emp-not-inc, 238184, HS-grad, 9, Married-civ-spouse, Farming-fishing, Wife, White, Female, 0, 0, 40, United-States, <=50K 59, Self-emp-not-inc, 148626, 10th, 6, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, Self-emp-not-inc, 48102, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 1977, 50, United-States, >50K 58, Private, 234213, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 14344, 0, 48, United-States, >50K 65, Private, 113323, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 24, Local-gov, 34246, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 51, Private, 175070, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 5178, 0, 45, United-States, >50K 31, Private, 279680, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 45, United-States, <=50K 84, Private, 188328, HS-grad, 9, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 16, United-States, <=50K 51, Private, 96609, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Local-gov, 84257, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 30, Private, 275632, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, <=50K 22, Private, 385540, 10th, 6, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 30, Private, 196342, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, Ireland, <=50K 47, Private, 97176, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 197714, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 35, United-States, <=50K 43, Self-emp-not-inc, 147099, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 36, United-States, <=50K 30, Private, 186346, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 46, Private, 73434, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 49, Local-gov, 275074, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 37, Private, 209214, 5th-6th, 3, Never-married, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 42, Private, 210525, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 372020, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 5013, 0, 50, United-States, <=50K 46, Private, 176684, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 210474, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 26, Private, 293690, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 58, United-States, >50K 64, Private, 149775, Masters, 14, Never-married, Prof-specialty, Other-relative, White, Female, 0, 0, 8, United-States, <=50K 20, Private, 323009, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, Germany, <=50K 31, Private, 126950, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 172538, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 1977, 40, United-States, >50K 44, Private, 115411, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Self-emp-not-inc, 101709, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 2885, 0, 40, United-States, <=50K 23, Private, 265356, Bachelors, 13, Never-married, Exec-managerial, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 31, Local-gov, 192565, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 90, United-States, >50K 35, Self-emp-not-inc, 348771, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 36, United-States, <=50K 30, Self-emp-not-inc, 148959, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 35, Private, 126569, HS-grad, 9, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 20, United-States, <=50K 40, Private, 105936, HS-grad, 9, Married-spouse-absent, Adm-clerical, Own-child, White, Female, 0, 0, 38, United-States, <=50K 18, Private, 188076, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 23, Private, 184400, 10th, 6, Never-married, Transport-moving, Own-child, Asian-Pac-Islander, Male, 0, 0, 30, ?, <=50K 63, Private, 124242, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, <=50K 20, State-gov, 200819, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 50, Local-gov, 100480, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 49, Private, 129513, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 53, Self-emp-not-inc, 297796, 10th, 6, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 195488, HS-grad, 9, Separated, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 54, Private, 153486, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 56, United-States, >50K 40, Private, 126845, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 22, Private, 206974, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 412149, 10th, 6, Never-married, Farming-fishing, Other-relative, White, Male, 0, 0, 35, Mexico, <=50K 24, Private, 653574, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, El-Salvador, <=50K 37, Private, 70562, 1st-4th, 2, Never-married, Other-service, Unmarried, White, Female, 0, 0, 48, El-Salvador, <=50K 62, Private, 197514, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 16, United-States, <=50K 19, ?, 309284, Some-college, 10, Never-married, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 334679, Assoc-voc, 11, Widowed, Prof-specialty, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 65, Private, 105116, Some-college, 10, Widowed, Adm-clerical, Not-in-family, White, Female, 2346, 0, 40, United-States, <=50K 31, Private, 151484, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 8, United-States, <=50K 42, Self-emp-inc, 78765, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 90, United-States, >50K 42, Private, 98427, HS-grad, 9, Married-civ-spouse, Other-service, Wife, Black, Female, 0, 0, 35, United-States, <=50K 54, Private, 230767, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Cuba, <=50K 23, Private, 117606, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 60, United-States, <=50K 28, Private, 68642, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 46, United-States, <=50K 42, Private, 341638, 11th, 7, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 65920, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 33, Federal-gov, 188246, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 198727, HS-grad, 9, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 160728, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Male, 2977, 0, 40, United-States, <=50K 27, Private, 706026, 11th, 7, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, ?, 348148, 11th, 7, Never-married, ?, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 62, Private, 77884, 5th-6th, 3, Married-civ-spouse, Farming-fishing, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 17, Private, 160758, 10th, 6, Never-married, Sales, Other-relative, White, Male, 0, 0, 30, United-States, <=50K 58, Private, 201112, Some-college, 10, Divorced, Adm-clerical, Not-in-family, Black, Female, 0, 0, 55, United-States, >50K 69, Self-emp-inc, 107850, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 6514, 0, 40, United-States, >50K 34, Private, 230246, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 42, United-States, >50K 34, Private, 203034, Bachelors, 13, Separated, Sales, Not-in-family, White, Male, 0, 2824, 50, United-States, >50K 20, Private, 373935, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 35, United-States, <=50K 64, Federal-gov, 341695, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 27, Private, 119793, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, ?, <=50K 41, Private, 178002, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 40, Private, 233130, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, El-Salvador, <=50K 53, Local-gov, 192982, Masters, 14, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 38, United-States, >50K 44, Private, 33155, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 37, Private, 187346, 5th-6th, 3, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 40, Mexico, <=50K 46, Private, 78529, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 60, United-States, >50K 17, Private, 101626, 9th, 5, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 20, United-States, <=50K 35, Private, 117567, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Local-gov, 110791, Assoc-acdm, 12, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 49, State-gov, 207120, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, >50K 48, Private, 43206, Prof-school, 15, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 26, Private, 120238, Bachelors, 13, Never-married, Sales, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 189219, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 8, United-States, <=50K 35, State-gov, 190895, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 83517, 9th, 5, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 35557, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 7298, 0, 50, United-States, >50K 36, Local-gov, 59313, Some-college, 10, Separated, Adm-clerical, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 25, Private, 202033, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Local-gov, 55658, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 25, United-States, <=50K 21, Private, 118186, Some-college, 10, Never-married, Sales, Own-child, Black, Female, 0, 0, 20, United-States, <=50K 22, Private, 279901, HS-grad, 9, Married-civ-spouse, Other-service, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 52, Private, 110954, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, El-Salvador, >50K 36, Self-emp-not-inc, 90159, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 122489, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 1726, 60, United-States, <=50K 49, Self-emp-not-inc, 43348, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 99999, 0, 70, United-States, >50K 42, Private, 34278, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 37, Private, 37778, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 54, United-States, <=50K 39, Private, 160623, Assoc-acdm, 12, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 342458, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 64322, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 373914, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 205884, Some-college, 10, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 40, United-States, >50K 62, Local-gov, 208266, Assoc-voc, 11, Divorced, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 38, Private, 222450, 5th-6th, 3, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 23, Private, 348420, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 136081, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 2051, 40, United-States, <=50K 37, Federal-gov, 197284, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 27, ?, 204773, Assoc-acdm, 12, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 206066, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Self-emp-not-inc, 61885, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Private, 299908, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, Black, Female, 0, 0, 40, United-States, >50K 35, Private, 46028, Assoc-acdm, 12, Divorced, Other-service, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 47, Private, 239865, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1977, 45, United-States, >50K 30, Private, 154587, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, Puerto-Rico, <=50K 29, Private, 244473, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 2051, 40, United-States, <=50K 36, Private, 32334, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 50, United-States, >50K 42, Private, 319588, Bachelors, 13, Married-spouse-absent, Transport-moving, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 51, Private, 226735, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 34, Private, 226443, HS-grad, 9, Divorced, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 44, Self-emp-inc, 359259, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 60, Portugal, <=50K 27, Private, 36851, Bachelors, 13, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 41, United-States, <=50K 39, Private, 393480, HS-grad, 9, Separated, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 46, Private, 33109, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 1741, 40, United-States, <=50K 32, Self-emp-not-inc, 188246, HS-grad, 9, Divorced, Sales, Own-child, White, Male, 0, 1590, 62, United-States, <=50K 31, Private, 231569, Bachelors, 13, Never-married, Sales, Not-in-family, Black, Female, 0, 0, 50, United-States, <=50K 23, Private, 353010, 11th, 7, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 35, United-States, <=50K 47, Private, 102628, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 55, United-States, >50K 66, Private, 262285, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 99, United-States, <=50K 26, Private, 160300, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 156953, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, >50K 53, Self-emp-inc, 136823, 11th, 7, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 48, Self-emp-not-inc, 160724, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Japan, <=50K 37, Self-emp-inc, 86459, Assoc-acdm, 12, Separated, Exec-managerial, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 17, Private, 238628, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 5, United-States, <=50K 50, Private, 339954, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 28, ?, 222005, HS-grad, 9, Never-married, ?, Other-relative, White, Female, 0, 0, 40, Mexico, <=50K 17, Federal-gov, 99893, 11th, 7, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 1602, 40, United-States, <=50K 39, Private, 214117, Some-college, 10, Divorced, Craft-repair, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 28, Federal-gov, 298661, Bachelors, 13, Never-married, Tech-support, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 38, Private, 179488, Assoc-acdm, 12, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 48343, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1902, 40, United-States, >50K 28, Local-gov, 100270, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 227065, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 32, United-States, >50K 40, Private, 126701, 9th, 5, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 20, Private, 209131, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 32, State-gov, 400132, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 23, State-gov, 278155, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 139012, Bachelors, 13, Never-married, Sales, Own-child, Asian-Pac-Islander, Male, 2174, 0, 40, Vietnam, <=50K 41, Private, 178431, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Taiwan, <=50K 42, Private, 511068, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 40, United-States, >50K 18, Private, 199039, 12th, 8, Never-married, Sales, Own-child, White, Male, 594, 0, 14, United-States, <=50K 29, Local-gov, 190525, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1848, 60, Germany, >50K 36, Private, 115700, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 34, Private, 167832, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 218164, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 44, United-States, <=50K 48, State-gov, 171926, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 50, United-States, >50K 36, Self-emp-inc, 242080, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 80, United-States, >50K 67, Federal-gov, 223257, HS-grad, 9, Widowed, Other-service, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 386773, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 40, United-States, >50K 53, Self-emp-not-inc, 105478, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 2415, 40, United-States, >50K 45, Private, 140644, Doctorate, 16, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 22, Private, 205970, 10th, 6, Separated, Other-service, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 25, Private, 216583, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 43, United-States, <=50K 61, Private, 162432, Some-college, 10, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Local-gov, 83671, Some-college, 10, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 47, Self-emp-inc, 205100, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 38, Germany, <=50K 31, Private, 195750, 1st-4th, 2, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, <=50K 17, Private, 220562, 9th, 5, Never-married, Sales, Other-relative, Other, Female, 0, 0, 32, Mexico, <=50K 38, Self-emp-inc, 312232, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 23, Private, 386337, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, ?, <=50K 42, Private, 86185, Some-college, 10, Widowed, Exec-managerial, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 78, Private, 105586, 5th-6th, 3, Married-civ-spouse, Transport-moving, Husband, Asian-Pac-Islander, Male, 0, 0, 36, United-States, <=50K 54, Private, 103345, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Local-gov, 150553, Bachelors, 13, Never-married, Adm-clerical, Own-child, Asian-Pac-Islander, Female, 0, 0, 50, United-States, <=50K 30, Private, 26009, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, >50K 46, Private, 149388, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 151626, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Black, Female, 0, 0, 45, United-States, <=50K 30, Private, 169583, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 35, United-States, <=50K 66, Local-gov, 174486, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 20051, 0, 35, Jamaica, >50K 23, Private, 160951, HS-grad, 9, Never-married, Craft-repair, Own-child, Black, Male, 2597, 0, 40, United-States, <=50K 25, Private, 213383, Some-college, 10, Never-married, Tech-support, Own-child, White, Male, 0, 0, 40, United-States, <=50K 32, Self-emp-inc, 103078, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Local-gov, 109526, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 38, United-States, <=50K 51, Private, 142835, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, State-gov, 43475, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 190916, Some-college, 10, Never-married, Tech-support, Own-child, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 175987, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, Local-gov, 214385, 11th, 7, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 20, United-States, <=50K 26, Private, 192652, Bachelors, 13, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 41, Federal-gov, 207685, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 19, Private, 143857, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 35, United-States, <=50K 39, Private, 163392, HS-grad, 9, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 0, 26, ?, <=50K 51, Private, 310774, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 29, ?, 427965, HS-grad, 9, Separated, ?, Unmarried, Black, Female, 0, 0, 20, United-States, <=50K 27, Private, 279608, 5th-6th, 3, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, Mexico, <=50K 33, Private, 312881, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 40, United-States, >50K 19, Private, 175083, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 8, United-States, <=50K 67, ?, 132057, HS-grad, 9, Married-civ-spouse, ?, Husband, Black, Male, 0, 0, 20, United-States, <=50K 41, Private, 32878, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 29, Federal-gov, 360527, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 99478, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, <=50K 25, Private, 113035, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 21, Federal-gov, 99199, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 36, United-States, <=50K 24, Local-gov, 452640, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Male, 14344, 0, 50, United-States, >50K 48, Private, 236858, 11th, 7, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 31, United-States, <=50K 46, Self-emp-inc, 201865, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 35, Private, 268661, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 35, Federal-gov, 475324, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 50, Private, 117295, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 65704, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 40, ?, <=50K 45, Private, 192835, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 62, Local-gov, 76720, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, <=50K 39, Local-gov, 180686, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 45, United-States, >50K 33, Local-gov, 133876, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 123727, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 50, Private, 129956, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, >50K 25, Private, 96268, 11th, 7, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 317320, Some-college, 10, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 86872, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 31, State-gov, 100863, Masters, 14, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 50, United-States, >50K 56, Private, 164332, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 15, United-States, <=50K 49, Self-emp-not-inc, 122584, 7th-8th, 4, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 34377, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Private, 162030, HS-grad, 9, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 43, United-States, <=50K 33, Private, 199170, Some-college, 10, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 25, Private, 470203, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 40, Private, 266803, Assoc-acdm, 12, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 72, ?, 188009, 7th-8th, 4, Divorced, ?, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 32, State-gov, 513416, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 10, United-States, <=50K 44, Private, 98211, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 55, United-States, <=50K 48, Private, 196107, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 17, Private, 108273, 10th, 6, Never-married, Sales, Own-child, White, Female, 0, 0, 12, United-States, <=50K 50, Private, 213290, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 1887, 36, United-States, >50K 61, Private, 96660, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 15024, 0, 34, United-States, >50K 22, Local-gov, 412316, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 17, Private, 120068, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 17, United-States, <=50K 49, Self-emp-inc, 101722, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 26, Private, 120268, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 50, United-States, <=50K 19, State-gov, 144429, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 10, United-States, <=50K 17, Private, 271122, 12th, 8, Never-married, Other-service, Own-child, White, Female, 0, 0, 16, United-States, <=50K 38, Private, 255621, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Local-gov, 90934, Assoc-voc, 11, Divorced, Protective-serv, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 51, Private, 162745, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 50, United-States, >50K 48, Private, 128460, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 42, United-States, >50K 63, Private, 30813, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 19, Private, 164585, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 73, Private, 148003, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 20051, 0, 36, United-States, >50K 51, Private, 215647, HS-grad, 9, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 43, United-States, <=50K 38, Private, 300975, Masters, 14, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 1485, 40, ?, <=50K 54, Private, 421561, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Private, 149909, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1848, 40, United-States, >50K 65, ?, 240857, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 2377, 40, United-States, >50K 36, Self-emp-not-inc, 138940, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 4386, 0, 50, United-States, >50K 42, Private, 66755, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, Other, Male, 0, 0, 40, United-States, <=50K 38, Private, 103323, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 7688, 0, 40, United-States, >50K 20, ?, 117222, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 37, State-gov, 29145, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 35, State-gov, 184659, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1485, 40, United-States, >50K 51, Self-emp-not-inc, 20795, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 311376, Assoc-voc, 11, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, State-gov, 122660, Bachelors, 13, Never-married, Prof-specialty, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 19, ?, 137578, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 16, United-States, <=50K 37, Private, 193689, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 42, United-States, >50K 29, Private, 144556, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, <=50K 33, Private, 228696, 1st-4th, 2, Married-civ-spouse, Craft-repair, Not-in-family, White, Male, 0, 2603, 32, Mexico, <=50K 60, Private, 184183, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 4650, 0, 40, United-States, <=50K 22, Private, 243178, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 20, United-States, <=50K 22, ?, 236330, Some-college, 10, Never-married, ?, Own-child, Black, Male, 0, 1721, 20, United-States, <=50K 60, State-gov, 190682, Assoc-voc, 11, Widowed, Other-service, Not-in-family, Black, Female, 0, 0, 37, United-States, <=50K 35, Private, 233786, 11th, 7, Separated, Other-service, Unmarried, White, Male, 0, 0, 20, United-States, <=50K 45, Private, 102202, Assoc-voc, 11, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 95299, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Vietnam, >50K 43, Self-emp-inc, 240504, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 70, United-States, >50K 32, State-gov, 169973, Masters, 14, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 35, Private, 144937, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 42, United-States, <=50K 32, Private, 211751, Assoc-voc, 11, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 61, Private, 84587, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, >50K 40, State-gov, 150874, Masters, 14, Divorced, Exec-managerial, Unmarried, White, Female, 1506, 0, 40, United-States, <=50K 20, ?, 187332, 10th, 6, Never-married, ?, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 42, Self-emp-inc, 188615, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 21, Private, 119704, Some-college, 10, Never-married, Sales, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 21, Private, 275190, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 26, Private, 417941, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, State-gov, 196348, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 24, Private, 221955, Bachelors, 13, Married-civ-spouse, Sales, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 173938, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 57, United-States, >50K 51, Private, 123429, Assoc-acdm, 12, Divorced, Tech-support, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 65, ?, 143732, HS-grad, 9, Widowed, ?, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 61, Private, 203126, Bachelors, 13, Divorced, Priv-house-serv, Not-in-family, White, Female, 0, 0, 12, ?, <=50K 67, Private, 174693, Some-college, 10, Widowed, Sales, Not-in-family, White, Female, 0, 0, 25, Nicaragua, <=50K 49, Private, 357540, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 25, United-States, <=50K 63, ?, 29859, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 1485, 40, United-States, >50K 58, Private, 314092, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1887, 48, United-States, >50K 61, Private, 280088, 7th-8th, 4, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 257380, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 35, United-States, <=50K 19, Private, 165306, Some-college, 10, Never-married, Tech-support, Other-relative, Asian-Pac-Islander, Male, 0, 0, 40, Vietnam, <=50K 29, Self-emp-not-inc, 109001, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 43, Private, 266439, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 1887, 40, United-States, >50K 60, Self-emp-not-inc, 153356, HS-grad, 9, Divorced, Sales, Not-in-family, Black, Male, 2597, 0, 55, United-States, <=50K 21, Private, 32950, Some-college, 10, Never-married, Sales, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 182163, HS-grad, 9, Separated, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 188246, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 65, United-States, >50K 36, Private, 297335, Bachelors, 13, Never-married, Sales, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 50, China, <=50K 37, Private, 108366, Bachelors, 13, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 46, United-States, <=50K 35, Private, 328301, Assoc-acdm, 12, Married-AF-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 17, Private, 182158, 10th, 6, Never-married, Priv-house-serv, Own-child, White, Male, 0, 0, 30, United-States, <=50K 37, Private, 169426, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, >50K 22, ?, 330571, HS-grad, 9, Never-married, ?, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 28, Private, 535978, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Private, 29393, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 57, Self-emp-inc, 258883, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 5178, 0, 60, Hungary, >50K 26, Private, 369166, Some-college, 10, Never-married, Farming-fishing, Other-relative, White, Female, 0, 0, 65, United-States, <=50K 45, Local-gov, 257855, 11th, 7, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 50, United-States, <=50K 32, Private, 164197, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 44, United-States, >50K 63, Private, 109517, Some-college, 10, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 43, United-States, <=50K 22, Private, 112137, Some-college, 10, Never-married, Prof-specialty, Other-relative, Asian-Pac-Islander, Female, 0, 0, 20, South, <=50K 36, Private, 160035, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 45, State-gov, 50567, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 34, Self-emp-not-inc, 140011, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 27, State-gov, 271328, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 20, ?, 183083, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 20, United-States, <=50K 47, Self-emp-not-inc, 159869, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 56, United-States, >50K 46, Private, 102542, 7th-8th, 4, Never-married, Other-service, Own-child, White, Male, 0, 0, 52, United-States, <=50K 28, Private, 297742, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 176917, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 165235, Bachelors, 13, Never-married, Adm-clerical, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, Thailand, <=50K 32, Self-emp-not-inc, 52647, 10th, 6, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 30, Local-gov, 48542, 12th, 8, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 59, Private, 279232, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, Puerto-Rico, <=50K 58, State-gov, 259929, Doctorate, 16, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 43, United-States, >50K 45, Private, 221780, Some-college, 10, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 76, Self-emp-not-inc, 253408, Some-college, 10, Widowed, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 298841, HS-grad, 9, Divorced, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 321313, Masters, 14, Never-married, Sales, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 38, Self-emp-not-inc, 64875, HS-grad, 9, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 30, Private, 275232, Assoc-acdm, 12, Never-married, Prof-specialty, Unmarried, Black, Female, 0, 0, 36, United-States, <=50K 53, Self-emp-inc, 134854, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, Greece, >50K 41, Private, 67339, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, ?, <=50K 27, State-gov, 192355, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 44, Local-gov, 208528, Assoc-acdm, 12, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 30, United-States, <=50K 35, Private, 160120, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 50, United-States, >50K 36, Private, 250238, 1st-4th, 2, Never-married, Other-service, Other-relative, Other, Female, 0, 0, 40, El-Salvador, <=50K 51, Private, 25031, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 10, United-States, >50K 42, Local-gov, 255847, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Self-emp-not-inc, 26892, Bachelors, 13, Married-AF-spouse, Prof-specialty, Husband, White, Male, 7298, 0, 50, United-States, >50K 45, Private, 111979, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 408537, 9th, 5, Divorced, Craft-repair, Unmarried, White, Female, 99999, 0, 37, United-States, >50K 36, Private, 231037, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 57, Federal-gov, 30030, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, >50K 27, Private, 292120, HS-grad, 9, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 62, Private, 138253, Masters, 14, Never-married, Handlers-cleaners, Not-in-family, White, Male, 4650, 0, 40, United-States, <=50K 29, Private, 190777, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, <=50K 38, Self-emp-not-inc, 41591, Bachelors, 13, Never-married, Craft-repair, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 30, United-States, <=50K 29, Private, 186733, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 18, ?, 78567, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 30, United-States, <=50K 19, ?, 140590, 12th, 8, Never-married, ?, Own-child, Black, Male, 0, 0, 30, United-States, <=50K 32, Local-gov, 230912, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 4865, 0, 40, United-States, <=50K 34, Private, 176185, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 1741, 40, United-States, <=50K 25, Private, 182227, Assoc-acdm, 12, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 34, Local-gov, 205704, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 37, State-gov, 24342, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 38, United-States, <=50K 37, Private, 138192, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 18, Private, 334676, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 25, United-States, <=50K 24, Private, 177526, Assoc-voc, 11, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 152696, 12th, 8, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 35, Private, 114765, Bachelors, 13, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 265509, Assoc-voc, 11, Separated, Tech-support, Unmarried, Black, Female, 0, 0, 32, United-States, <=50K 29, Private, 180758, Assoc-acdm, 12, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 49, Self-emp-not-inc, 127921, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 71, ?, 177906, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 10, United-States, >50K 35, Federal-gov, 182898, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Self-emp-not-inc, 422249, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 37, Private, 222450, 5th-6th, 3, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 33, Local-gov, 190027, Some-college, 10, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 18, United-States, <=50K 49, Private, 281647, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 32, Private, 117963, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 45, United-States, <=50K 63, ?, 319121, 11th, 7, Separated, ?, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 39, Private, 225504, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Local-gov, 104334, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, El-Salvador, <=50K 30, State-gov, 48214, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 50, United-States, >50K 30, Private, 145714, Assoc-voc, 11, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 48, Self-emp-inc, 38240, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, >50K 57, Self-emp-not-inc, 27385, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 10, United-States, <=50K 56, Private, 204254, 10th, 6, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 45, United-States, <=50K 28, Private, 411587, Some-college, 10, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 40, Honduras, <=50K 43, Private, 221172, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 24, United-States, >50K 46, Private, 54190, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 60, Private, 93997, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 45, United-States, >50K 50, Local-gov, 24139, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 65, United-States, <=50K 37, Private, 112497, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 41, Private, 138907, HS-grad, 9, Divorced, Priv-house-serv, Other-relative, Black, Female, 0, 0, 40, United-States, <=50K 38, Private, 186325, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 38, United-States, >50K 23, Private, 199452, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 59, Private, 126677, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 72, Private, 107814, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 2329, 0, 60, United-States, <=50K 47, Local-gov, 93618, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 33, United-States, <=50K 29, Private, 353352, Assoc-voc, 11, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 143058, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 24, Private, 239663, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 15, United-States, <=50K 22, Private, 167615, HS-grad, 9, Never-married, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 442274, HS-grad, 9, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 149210, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7298, 0, 45, United-States, >50K 55, Federal-gov, 174533, Bachelors, 13, Separated, Other-service, Unmarried, White, Female, 0, 0, 72, ?, <=50K 40, State-gov, 50093, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 61, Private, 270056, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, Japan, <=50K 58, Self-emp-not-inc, 131991, Bachelors, 13, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 72, United-States, <=50K 39, State-gov, 126336, HS-grad, 9, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 45, Self-emp-not-inc, 341117, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 25, Private, 108505, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 69, ?, 106566, Doctorate, 16, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 50, United-States, >50K 36, Private, 74791, Bachelors, 13, Married-civ-spouse, Sales, Wife, White, Male, 0, 0, 60, ?, <=50K 34, Private, 24266, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 7688, 0, 40, United-States, >50K 45, Private, 267967, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 27, ?, 181284, 12th, 8, Married-civ-spouse, ?, Husband, Black, Male, 0, 0, 45, United-States, <=50K 28, Private, 102533, Some-college, 10, Separated, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 27, Private, 69757, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 41, State-gov, 210094, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 18, State-gov, 389147, HS-grad, 9, Never-married, Sales, Not-in-family, Black, Female, 0, 0, 30, United-States, <=50K 44, Private, 210648, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 47, Private, 94809, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 45, United-States, >50K 36, Local-gov, 298717, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 66, Private, 236879, Preschool, 1, Widowed, Priv-house-serv, Other-relative, White, Female, 0, 0, 40, Guatemala, <=50K 33, Private, 170148, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 39, Local-gov, 166497, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 30, Private, 247156, HS-grad, 9, Never-married, Transport-moving, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 34, Self-emp-not-inc, 204052, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 62, Self-emp-not-inc, 122246, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 21, Private, 180339, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 50, Self-emp-inc, 155574, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7298, 0, 50, United-States, >50K 30, Private, 114912, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 3103, 0, 60, United-States, >50K 43, Private, 193882, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 19, Private, 112269, Some-college, 10, Never-married, Other-service, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 26, Federal-gov, 171928, Assoc-voc, 11, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 50, Japan, <=50K 50, Private, 95435, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1579, 65, Canada, <=50K 45, Federal-gov, 179638, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 46, Self-emp-inc, 125892, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 17, Private, 721712, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 15, United-States, <=50K 56, Private, 197369, 7th-8th, 4, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Private, 353795, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 3103, 0, 40, United-States, >50K 47, Private, 334679, Masters, 14, Separated, Machine-op-inspct, Unmarried, Asian-Pac-Islander, Female, 0, 0, 42, India, <=50K 23, Private, 235853, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 51, Self-emp-not-inc, 353281, HS-grad, 9, Separated, Other-service, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 19, Private, 203061, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 33, Self-emp-not-inc, 62932, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 118551, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 80, United-States, <=50K 52, Private, 99184, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 189674, Some-college, 10, Separated, Other-service, Other-relative, Black, Female, 0, 0, 40, United-States, <=50K 34, Private, 226883, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 26, ?, 109564, HS-grad, 9, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 26, Self-emp-inc, 66872, 12th, 8, Married-civ-spouse, Sales, Husband, Other, Male, 0, 0, 98, Dominican-Republic, <=50K 35, Local-gov, 268292, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, Federal-gov, 139290, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Private, 206541, 11th, 7, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 50, United-States, <=50K 23, Private, 203139, Some-college, 10, Never-married, Other-service, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 28, Self-emp-not-inc, 294398, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 20, Private, 386864, 10th, 6, Never-married, Other-service, Other-relative, White, Male, 0, 0, 35, Mexico, <=50K 17, Private, 369909, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 56, Private, 89922, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 3103, 0, 45, United-States, >50K 26, Private, 176008, HS-grad, 9, Divorced, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 43, State-gov, 241506, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 1506, 0, 36, United-States, <=50K 45, Self-emp-not-inc, 174426, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 34, Private, 167497, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 7688, 0, 50, United-States, >50K 54, Private, 292673, 1st-4th, 2, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 35, Mexico, <=50K 51, Local-gov, 134808, HS-grad, 9, Widowed, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 58, Self-emp-not-inc, 95763, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 49, Private, 83622, Assoc-acdm, 12, Separated, Adm-clerical, Not-in-family, White, Female, 2597, 0, 40, United-States, <=50K 21, Private, 222490, Assoc-voc, 11, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 29115, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 66638, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 39, Private, 53926, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, ?, 43739, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 104359, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 124604, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 32, United-States, <=50K 45, Private, 114797, HS-grad, 9, Separated, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 60, Federal-gov, 67320, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 28, Federal-gov, 53147, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 23, Private, 13769, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, Amer-Indian-Eskimo, Male, 0, 0, 30, United-States, <=50K 44, Private, 202872, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 19, State-gov, 149528, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 12, United-States, <=50K 37, Private, 132879, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Self-emp-not-inc, 112362, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 38, United-States, <=50K 56, Federal-gov, 156229, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 40, United-States, >50K 44, Private, 131650, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 54, United-States, >50K 30, Private, 154568, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 36, Vietnam, >50K 23, Private, 132300, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 124747, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 3103, 0, 40, United-States, >50K 38, Private, 276559, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 70, United-States, >50K 32, Private, 106014, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 5178, 0, 50, United-States, >50K 57, Self-emp-not-inc, 135134, Masters, 14, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 35, Private, 86648, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 50, United-States, >50K 48, Self-emp-not-inc, 107231, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 50, United-States, >50K 32, Local-gov, 113838, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 99, United-States, <=50K 76, Federal-gov, 25319, Masters, 14, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 57, Local-gov, 190561, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, Black, Female, 0, 0, 30, United-States, <=50K 58, ?, 150031, Some-college, 10, Never-married, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 48343, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 50, United-States, >50K 50, Private, 211116, 10th, 6, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 40, United-States, <=50K 38, Private, 226311, HS-grad, 9, Married-AF-spouse, Other-service, Wife, White, Female, 0, 0, 25, United-States, <=50K 53, Private, 283743, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 2002, 40, United-States, <=50K 59, Self-emp-not-inc, 64102, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 20, United-States, <=50K 23, Private, 234663, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 247880, Assoc-voc, 11, Divorced, Exec-managerial, Not-in-family, White, Male, 8614, 0, 40, United-States, >50K 23, Private, 615367, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 163090, Assoc-acdm, 12, Never-married, Sales, Own-child, White, Male, 0, 0, 20, United-States, <=50K 44, Private, 192225, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Private, 370183, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 242482, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 169953, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Local-gov, 144182, Preschool, 1, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 25, United-States, <=50K 38, Private, 125933, Bachelors, 13, Separated, Exec-managerial, Not-in-family, White, Male, 27828, 0, 45, United-States, >50K 26, Private, 203777, Some-college, 10, Never-married, Sales, Not-in-family, Black, Female, 0, 0, 37, United-States, <=50K 39, Private, 210991, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 472580, Some-college, 10, Never-married, Sales, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 33, State-gov, 200289, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 19, India, <=50K 43, Private, 289669, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 2547, 40, United-States, >50K 30, Private, 110622, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, China, <=50K 59, State-gov, 139616, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 26, Private, 39212, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, <=50K 28, Private, 51961, Some-college, 10, Never-married, Tech-support, Own-child, Black, Male, 0, 0, 24, United-States, <=50K 48, Self-emp-not-inc, 117849, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 50748, Bachelors, 13, Widowed, Prof-specialty, Unmarried, White, Female, 1506, 0, 35, United-States, <=50K 41, Self-emp-not-inc, 170214, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 2179, 40, United-States, <=50K 20, Private, 151790, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 30, United-States, <=50K 49, Private, 168211, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 37, State-gov, 117651, Bachelors, 13, Never-married, Prof-specialty, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 157131, 12th, 8, Never-married, Sales, Own-child, White, Female, 0, 0, 8, United-States, <=50K 61, Private, 225970, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 177951, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 48, United-States, <=50K 66, Private, 134130, Bachelors, 13, Widowed, Other-service, Not-in-family, White, Male, 0, 0, 12, United-States, <=50K 68, Private, 191581, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 3273, 0, 40, United-States, <=50K 27, Local-gov, 199172, HS-grad, 9, Married-civ-spouse, Protective-serv, Wife, White, Female, 0, 0, 40, United-States, <=50K 66, Self-emp-not-inc, 262552, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 7, United-States, <=50K 28, Private, 66434, 10th, 6, Never-married, Other-service, Unmarried, White, Female, 0, 0, 15, United-States, <=50K 26, Private, 77661, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, ?, 230856, HS-grad, 9, Never-married, ?, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 46, Private, 192835, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 48, United-States, <=50K 62, ?, 181014, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 200445, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 1974, 40, United-States, <=50K 26, Self-emp-not-inc, 37918, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 60, United-States, <=50K 40, Private, 111020, HS-grad, 9, Separated, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 244665, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, Honduras, <=50K 52, Private, 312477, HS-grad, 9, Widowed, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 61, Self-emp-not-inc, 243493, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 12, United-States, <=50K 39, State-gov, 152023, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 104193, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 114, 0, 40, United-States, <=50K 47, Private, 170850, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 48, United-States, <=50K 33, Private, 137088, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, Other, Male, 0, 0, 40, Ecuador, <=50K 17, Private, 340557, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 25, United-States, <=50K 26, Private, 298225, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, <=50K 25, Private, 114150, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 39, Self-emp-not-inc, 194668, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 16, United-States, <=50K 33, Private, 188246, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 45, United-States, >50K 46, Federal-gov, 330901, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, United-States, <=50K 27, Private, 80165, Some-college, 10, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 48, Private, 83444, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7298, 0, 40, United-States, >50K 29, Self-emp-not-inc, 85572, 11th, 7, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 5, United-States, <=50K 40, Private, 116632, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 139989, Bachelors, 13, Never-married, Sales, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 55, Private, 135803, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Other, Male, 0, 1579, 35, India, <=50K 56, Private, 75785, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Private, 248612, Assoc-acdm, 12, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 36, Private, 28572, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 26, Self-emp-not-inc, 31143, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 37, Private, 216924, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 44, United-States, >50K 36, Private, 549174, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Self-emp-not-inc, 111296, 11th, 7, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 50, Mexico, <=50K 25, Private, 208881, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 36, State-gov, 243666, HS-grad, 9, Divorced, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 37, Self-emp-not-inc, 327164, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 70, ?, <=50K 39, Self-emp-inc, 131288, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 5178, 0, 48, United-States, >50K 35, Private, 257416, Assoc-voc, 11, Never-married, Craft-repair, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 33, Private, 215288, 11th, 7, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 31, Private, 58582, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 46, United-States, <=50K 49, Private, 199378, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 22, United-States, <=50K 34, Self-emp-not-inc, 114185, Bachelors, 13, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 50, ?, <=50K 40, Private, 137421, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Asian-Pac-Islander, Male, 0, 0, 60, Trinadad&Tobago, <=50K 27, Private, 216481, Some-college, 10, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 50, Self-emp-not-inc, 196504, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 23, United-States, <=50K 38, Private, 357870, 12th, 8, Never-married, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 50, United-States, <=50K 55, State-gov, 256335, Bachelors, 13, Divorced, Exec-managerial, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 49, Self-emp-not-inc, 168191, 7th-8th, 4, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 70, Italy, <=50K 40, Private, 215596, Bachelors, 13, Married-spouse-absent, Other-service, Not-in-family, Other, Male, 0, 0, 40, Mexico, <=50K 42, Private, 184682, Assoc-voc, 11, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 51, Private, 171914, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 27, Private, 288229, Bachelors, 13, Never-married, Adm-clerical, Own-child, Asian-Pac-Islander, Female, 0, 0, 50, Laos, <=50K 30, State-gov, 144064, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 70, ?, 54849, Doctorate, 16, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 20, United-States, >50K 40, Private, 141583, 10th, 6, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 43, Self-emp-not-inc, 180985, Bachelors, 13, Separated, Craft-repair, Unmarried, White, Male, 0, 0, 35, United-States, <=50K 24, Private, 148709, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, ?, 174626, 7th-8th, 4, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 184801, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 52, Private, 89054, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 147284, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 33, Private, 169973, Assoc-voc, 11, Separated, Protective-serv, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 222993, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 41099, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 31, Private, 33117, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 29, Private, 162551, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, Asian-Pac-Islander, Female, 0, 0, 40, Hong, >50K 49, Private, 122066, 5th-6th, 3, Married-civ-spouse, Other-service, Husband, White, Male, 0, 2603, 40, Greece, <=50K 61, ?, 42938, Bachelors, 13, Never-married, ?, Not-in-family, White, Male, 0, 0, 7, United-States, >50K 46, Private, 389843, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, Germany, >50K 37, Private, 138940, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, Federal-gov, 141877, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Private, 172722, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Self-emp-not-inc, 118523, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 227886, Some-college, 10, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 36, Private, 80743, HS-grad, 9, Married-civ-spouse, Other-service, Wife, Asian-Pac-Islander, Female, 0, 0, 40, South, <=50K 52, Private, 199688, 10th, 6, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 45, United-States, <=50K 40, Private, 225823, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 21, Private, 176486, HS-grad, 9, Married-spouse-absent, Exec-managerial, Other-relative, White, Female, 0, 0, 60, United-States, <=50K 63, Private, 175777, 10th, 6, Separated, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 30, Private, 295010, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 437825, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 20, Peru, <=50K 50, Private, 270194, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 41, Private, 242089, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 39, Self-emp-inc, 117555, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 23, Private, 146499, HS-grad, 9, Separated, Machine-op-inspct, Unmarried, White, Female, 0, 0, 48, United-States, <=50K 52, Private, 222405, HS-grad, 9, Married-civ-spouse, Sales, Husband, Black, Male, 0, 2377, 40, United-States, <=50K 17, ?, 216595, 11th, 7, Never-married, ?, Own-child, Black, Female, 0, 0, 20, United-States, <=50K 46, Private, 157991, Assoc-voc, 11, Divorced, Tech-support, Unmarried, Black, Female, 0, 625, 40, United-States, <=50K 26, Private, 373553, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 42, United-States, <=50K 30, Private, 194827, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1740, 40, United-States, <=50K 23, Private, 60331, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 21, State-gov, 96483, Some-college, 10, Never-married, Adm-clerical, Own-child, Asian-Pac-Islander, Female, 0, 0, 12, United-States, <=50K 39, Private, 211154, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 55, United-States, <=50K 37, Local-gov, 247750, Assoc-voc, 11, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 40, United-States, <=50K 40, Self-emp-not-inc, 204235, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 50, United-States, >50K 38, Private, 197113, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 20, United-States, <=50K 47, Private, 178341, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 4064, 0, 60, United-States, <=50K 20, Private, 293297, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 35, United-States, <=50K 35, Private, 35330, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 62, State-gov, 202056, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 14084, 0, 40, United-States, >50K 32, Private, 61898, 11th, 7, Divorced, Other-service, Unmarried, White, Female, 0, 0, 15, United-States, <=50K 42, Self-emp-inc, 1097453, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 32, Private, 176992, 10th, 6, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 295289, Some-college, 10, Never-married, Other-service, Own-child, Black, Female, 0, 0, 30, United-States, <=50K 53, Self-emp-inc, 298215, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 28, Self-emp-not-inc, 209934, 5th-6th, 3, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 25, Mexico, <=50K 26, Private, 164938, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 423222, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 23, Private, 124259, Some-college, 10, Never-married, Protective-serv, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 70, Self-emp-inc, 232871, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 30, United-States, <=50K 41, State-gov, 73199, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 43, State-gov, 27661, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 65, Private, 461715, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 25, ?, <=50K 40, Self-emp-not-inc, 89413, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1672, 40, United-States, <=50K 64, Self-emp-not-inc, 31826, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 40, Private, 279679, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 43, Private, 221172, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 50, Federal-gov, 222020, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 48, United-States, <=50K 19, ?, 181265, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 30, United-States, <=50K 32, Self-emp-not-inc, 261056, Bachelors, 13, Never-married, Prof-specialty, Own-child, Black, Female, 2174, 0, 60, ?, <=50K 32, Private, 204792, 11th, 7, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 384508, 11th, 7, Divorced, Sales, Unmarried, White, Male, 1506, 0, 50, Mexico, <=50K 41, Private, 288568, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Private, 182714, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, England, <=50K 20, Private, 471452, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, United-States, <=50K 45, State-gov, 264052, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 146659, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 50, United-States, >50K 24, Private, 203027, Assoc-acdm, 12, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 218309, Bachelors, 13, Divorced, Sales, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 28, Private, 133625, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 35, Private, 45937, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, ?, 389850, HS-grad, 9, Married-spouse-absent, ?, Unmarried, Black, Male, 0, 0, 50, United-States, <=50K 38, Federal-gov, 201617, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 32, Local-gov, 114733, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 50, State-gov, 97778, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 149507, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, >50K 35, Private, 82622, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 48014, Masters, 14, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, France, <=50K 61, State-gov, 162678, 5th-6th, 3, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 213842, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 38, United-States, <=50K 61, Private, 221447, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 18, Private, 426836, 5th-6th, 3, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 31, Local-gov, 206609, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 50276, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 20, Private, 180497, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 35, Private, 220585, 12th, 8, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 202752, HS-grad, 9, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 43, Private, 75993, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 40, United-States, >50K 18, Private, 170544, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, United-States, <=50K 55, Private, 115439, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 40, United-States, >50K 59, Private, 24384, HS-grad, 9, Widowed, Priv-house-serv, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 209067, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 65225, 10th, 6, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 60, Federal-gov, 27466, Some-college, 10, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, England, <=50K 49, Federal-gov, 179869, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 21, Private, 442131, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 40, United-States, <=50K 61, Private, 243283, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 64, Private, 316627, 5th-6th, 3, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 63, Private, 208862, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Federal-gov, 38645, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 141272, Bachelors, 13, Never-married, Other-service, Own-child, Black, Female, 0, 0, 30, United-States, <=50K 41, State-gov, 29324, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 18, ?, 348588, 12th, 8, Never-married, ?, Own-child, Black, Male, 0, 0, 25, United-States, <=50K 40, Private, 124747, HS-grad, 9, Married-civ-spouse, Craft-repair, Wife, White, Female, 7298, 0, 40, United-States, >50K 55, Self-emp-not-inc, 477867, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 17, Private, 218361, 10th, 6, Never-married, Other-service, Own-child, White, Female, 0, 1602, 12, United-States, <=50K 34, Self-emp-not-inc, 156809, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 1504, 60, United-States, <=50K 24, Private, 267945, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 35724, Prof-school, 15, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 45, United-States, >50K 29, Private, 187188, Masters, 14, Never-married, Exec-managerial, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 60, United-States, <=50K 52, Private, 155983, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 57, Federal-gov, 414994, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 103474, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 43, Private, 211128, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 61, Private, 203445, Some-college, 10, Widowed, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 38312, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 65, United-States, >50K 51, Private, 178241, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, >50K 40, Private, 260761, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, Mexico, <=50K 41, Local-gov, 36924, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 19, Private, 292590, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 28, Private, 461929, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, Mexico, <=50K 59, Private, 189664, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, State-gov, 190577, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 344200, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Private, 337494, Assoc-acdm, 12, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 54, Self-emp-not-inc, 52634, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 194901, Assoc-voc, 11, Separated, Craft-repair, Not-in-family, White, Male, 0, 2444, 42, United-States, >50K 20, Private, 170091, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 10, United-States, <=50K 27, ?, 189399, Some-college, 10, Divorced, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 32, Self-emp-not-inc, 205072, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 48, United-States, <=50K 35, Private, 310290, HS-grad, 9, Married-civ-spouse, Transport-moving, Wife, Black, Female, 0, 0, 40, United-States, <=50K 27, Private, 134048, 11th, 7, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 40, Private, 91959, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 46, United-States, >50K 34, Private, 153942, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Local-gov, 234096, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 185330, Some-college, 10, Never-married, Craft-repair, Own-child, White, Female, 0, 0, 25, United-States, <=50K 28, Private, 163772, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Other, Male, 0, 0, 40, United-States, <=50K 65, Private, 83800, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 27, United-States, <=50K 61, Private, 139391, Some-college, 10, Never-married, Tech-support, Own-child, White, Male, 0, 0, 16, United-States, <=50K 18, Private, 478380, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 25, United-States, <=50K 35, Self-emp-inc, 186845, Bachelors, 13, Married-civ-spouse, Sales, Own-child, White, Male, 5178, 0, 50, United-States, >50K 45, Private, 262802, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 68, ?, 152157, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 25, Private, 114483, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 48, Private, 118023, Prof-school, 15, Divorced, Sales, Not-in-family, White, Male, 0, 0, 13, United-States, <=50K 19, Private, 220101, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 219424, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, Black, Female, 0, 0, 50, United-States, >50K 54, Private, 186117, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 47, Self-emp-not-inc, 479611, Bachelors, 13, Divorced, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 25, Private, 80312, Assoc-voc, 11, Never-married, Adm-clerical, Not-in-family, White, Female, 4865, 0, 40, United-States, <=50K 30, Private, 108386, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 67, ?, 125926, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 8, United-States, <=50K 35, Private, 177102, HS-grad, 9, Divorced, Handlers-cleaners, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 190762, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 18, United-States, <=50K 61, Private, 180632, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 88019, HS-grad, 9, Divorced, Other-service, Unmarried, White, Male, 0, 0, 32, United-States, <=50K 50, Private, 135339, 12th, 8, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Cambodia, >50K 32, Private, 100662, 9th, 5, Separated, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, Columbia, <=50K 34, Private, 183557, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 36, Private, 160035, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 306790, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 269246, 11th, 7, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 308334, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 19, United-States, <=50K 58, Private, 215190, 11th, 7, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 20, United-States, <=50K 27, Private, 419146, 5th-6th, 3, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 75, Mexico, <=50K 62, Private, 176839, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 38, United-States, <=50K 36, Self-emp-inc, 184456, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 27828, 0, 55, United-States, >50K 21, Local-gov, 309348, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 594, 0, 4, United-States, <=50K 41, Private, 56795, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 45, England, <=50K 28, Private, 201861, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, <=50K 33, Private, 179509, Bachelors, 13, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 291755, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 19, Private, 243941, Some-college, 10, Never-married, Sales, Own-child, Amer-Indian-Eskimo, Female, 0, 1721, 25, United-States, <=50K 76, Self-emp-not-inc, 117169, 7th-8th, 4, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 25, ?, 100903, Bachelors, 13, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 25, United-States, <=50K 34, Private, 159322, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 40, Private, 262872, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 187052, 11th, 7, Never-married, Sales, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 17, Private, 277583, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 15, United-States, <=50K 55, Private, 169071, Some-college, 10, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 51, Local-gov, 96190, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 61603, 5th-6th, 3, Married-civ-spouse, Handlers-cleaners, Husband, Other, Male, 0, 0, 40, Mexico, <=50K 44, Private, 43711, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 65, ?, 197883, 10th, 6, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 70, United-States, <=50K 54, Private, 99434, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 34, Self-emp-not-inc, 177639, Assoc-acdm, 12, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 201723, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 222248, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 39, Private, 86143, 5th-6th, 3, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 46, ?, 228620, 11th, 7, Widowed, ?, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 34, Private, 346034, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, El-Salvador, <=50K 59, Private, 87510, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 37932, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 50, United-States, <=50K 34, Private, 185063, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, >50K 62, ?, 125493, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 5178, 0, 40, Scotland, >50K 51, Private, 159755, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 20, United-States, <=50K 34, Private, 108837, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, >50K 47, Private, 110669, Bachelors, 13, Separated, Prof-specialty, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 21, ?, 220115, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 20, United-States, <=50K 30, Self-emp-not-inc, 45427, Assoc-voc, 11, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 49, United-States, <=50K 38, Private, 154669, HS-grad, 9, Separated, Sales, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 45, Private, 261278, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, Asian-Pac-Islander, Female, 5178, 0, 40, Philippines, >50K 23, Private, 71864, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 34, Private, 173495, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, >50K 22, Private, 254293, 12th, 8, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 111883, HS-grad, 9, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 146429, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 472807, 1st-4th, 2, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 52, Mexico, <=50K 28, Private, 285294, Bachelors, 13, Married-civ-spouse, Sales, Wife, Black, Female, 15024, 0, 45, United-States, >50K 23, Private, 184665, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 35, Private, 205852, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 83879, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 27, Private, 178564, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 30, United-States, <=50K 46, Self-emp-inc, 168796, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, <=50K 27, Private, 269444, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 47353, 10th, 6, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, <=50K 34, Self-emp-inc, 29254, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 70, United-States, <=50K 33, Private, 155343, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 234271, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 257849, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, <=50K 23, Private, 228230, Some-college, 10, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 47, United-States, <=50K 36, Private, 227615, 5th-6th, 3, Married-spouse-absent, Craft-repair, Other-relative, White, Male, 0, 0, 32, Mexico, <=50K 29, Private, 406826, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 50, Self-emp-not-inc, 27539, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 7688, 0, 40, United-States, >50K 19, Private, 97261, 12th, 8, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, ?, 232022, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 52, Federal-gov, 168539, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Private, 515797, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 351381, Assoc-voc, 11, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 161018, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, >50K 60, Private, 26721, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 164123, 11th, 7, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 59, Self-emp-not-inc, 98418, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 20, United-States, <=50K 36, Private, 29814, HS-grad, 9, Never-married, Transport-moving, Other-relative, White, Male, 0, 0, 50, United-States, <=50K 25, Private, 254613, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, Cuba, <=50K 49, Private, 207677, 7th-8th, 4, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 25, Self-emp-not-inc, 217030, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 50, Private, 171199, 11th, 7, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 198270, Assoc-acdm, 12, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 43, United-States, <=50K 28, ?, 131310, HS-grad, 9, Separated, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 79923, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 20, United-States, <=50K 40, Self-emp-inc, 475322, Bachelors, 13, Separated, Craft-repair, Own-child, White, Male, 0, 0, 50, United-States, <=50K 56, Private, 134286, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 56, Self-emp-not-inc, 73746, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 23, Private, 125525, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 42, United-States, <=50K 38, ?, 155676, HS-grad, 9, Divorced, ?, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 21, Private, 304949, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 10, United-States, <=50K 67, Private, 150516, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 24, United-States, <=50K 54, State-gov, 249096, Assoc-voc, 11, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Local-gov, 164127, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 59, Private, 304779, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 157043, 11th, 7, Widowed, Handlers-cleaners, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 30, Private, 396538, HS-grad, 9, Separated, Exec-managerial, Unmarried, White, Female, 0, 0, 29, United-States, <=50K 42, Private, 510072, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 64, ?, 200017, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 61, ?, 60641, Bachelors, 13, Never-married, ?, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 26, Private, 89326, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 200471, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Husband, White, Male, 4064, 0, 40, United-States, <=50K 78, Self-emp-not-inc, 82815, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 3, United-States, >50K 24, Self-emp-not-inc, 117210, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 27, Private, 202206, 11th, 7, Separated, Farming-fishing, Other-relative, White, Male, 0, 0, 40, Puerto-Rico, <=50K 51, Private, 123429, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 46, Private, 353512, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 55, Self-emp-not-inc, 26683, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 20, Private, 204641, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 225053, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 36, ?, 98776, Some-college, 10, Never-married, ?, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 19, Private, 263932, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 30, Private, 108247, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Self-emp-not-inc, 369648, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 26, Private, 339324, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 96, United-States, <=50K 59, ?, 145574, Assoc-acdm, 12, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 35, United-States, >50K 53, Private, 317313, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, >50K 24, Local-gov, 162919, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 186314, Some-college, 10, Separated, Prof-specialty, Own-child, White, Male, 0, 0, 54, United-States, <=50K 36, Private, 254202, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 39, Private, 108140, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 53, Private, 287317, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, Black, Male, 0, 0, 32, United-States, <=50K 75, Self-emp-inc, 81534, HS-grad, 9, Widowed, Sales, Other-relative, Asian-Pac-Islander, Male, 0, 0, 35, United-States, >50K 36, Private, 35945, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 46, Self-emp-inc, 204928, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, Self-emp-inc, 208809, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 1902, 40, United-States, >50K 29, Private, 133625, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, United-States, <=50K 60, Private, 71683, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 49, United-States, <=50K 58, Private, 570562, HS-grad, 9, Widowed, Sales, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 67, Self-emp-not-inc, 36876, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 55, United-States, <=50K 35, Private, 253006, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 38, United-States, >50K 39, Self-emp-not-inc, 50096, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 80, United-States, <=50K 37, Private, 336880, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 54, ?, 135840, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 50, United-States, <=50K 63, Self-emp-not-inc, 168048, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 30, United-States, <=50K 47, Private, 187969, 11th, 7, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 23, Private, 117363, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 55, Private, 256526, HS-grad, 9, Separated, Machine-op-inspct, Not-in-family, White, Male, 4865, 0, 45, United-States, <=50K 49, Private, 304416, 11th, 7, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 248011, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 5178, 0, 40, United-States, >50K 23, Private, 229826, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 159796, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 12, United-States, <=50K 44, Private, 165346, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Private, 25386, Assoc-voc, 11, Never-married, Other-service, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 35, Private, 491000, Assoc-voc, 11, Divorced, Prof-specialty, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 23, Local-gov, 247731, HS-grad, 9, Divorced, Adm-clerical, Own-child, White, Female, 0, 0, 40, Cuba, <=50K 48, Private, 180532, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 189462, Some-college, 10, Divorced, Handlers-cleaners, Own-child, White, Male, 2176, 0, 40, United-States, <=50K 44, Private, 419134, HS-grad, 9, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 55, Self-emp-not-inc, 170166, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 25, United-States, <=50K 33, Self-emp-not-inc, 173495, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 18, Private, 423024, 12th, 8, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, United-States, <=50K 24, Private, 72119, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Male, 2202, 0, 30, United-States, <=50K 32, Local-gov, 19302, Assoc-acdm, 12, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 56, England, >50K 24, State-gov, 257621, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 44, Self-emp-inc, 118212, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 70, United-States, >50K 27, Private, 259840, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, <=50K 39, Private, 115289, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, France, >50K 26, Local-gov, 159662, 10th, 6, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 379798, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 227945, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 65, United-States, >50K 41, State-gov, 36999, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 75, United-States, >50K 73, ?, 131982, Bachelors, 13, Married-civ-spouse, ?, Husband, Asian-Pac-Islander, Male, 0, 0, 5, Vietnam, <=50K 32, Self-emp-inc, 124052, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 56, Local-gov, 273084, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, United-States, >50K 59, Private, 170104, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 50, United-States, >50K 44, Private, 96249, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 35, Private, 140915, Bachelors, 13, Never-married, Sales, Own-child, Asian-Pac-Islander, Male, 0, 1590, 40, South, <=50K 52, Private, 230657, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Other, Male, 3781, 0, 40, Columbia, <=50K 30, Private, 195576, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Male, 3325, 0, 50, United-States, <=50K 23, Private, 117767, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 112763, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 8614, 0, 43, United-States, >50K 61, Private, 79827, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 38, Private, 103925, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 68, Private, 161744, 10th, 6, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 16, United-States, <=50K 41, Private, 106679, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Male, 27828, 0, 50, United-States, >50K 42, Self-emp-not-inc, 196514, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 48, ?, 61985, 9th, 5, Separated, ?, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 20, United-States, <=50K 19, Private, 157605, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 137367, 11th, 7, Married-spouse-absent, Handlers-cleaners, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, India, <=50K 40, Self-emp-inc, 110862, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 2377, 50, United-States, <=50K 32, Private, 74883, Bachelors, 13, Never-married, Tech-support, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 51, Self-emp-inc, 98642, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 14084, 0, 40, United-States, >50K 44, Local-gov, 144778, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Private, 177787, Bachelors, 13, Never-married, Sales, Own-child, White, Female, 0, 0, 30, England, <=50K 30, ?, 103651, 11th, 7, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 35, United-States, <=50K 44, Private, 162108, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 24, Private, 217602, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 34, Private, 473133, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 17, Private, 113301, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 12, ?, <=50K 61, Private, 80896, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 45, India, >50K 30, Local-gov, 168387, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 38950, Bachelors, 13, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 107801, Assoc-voc, 11, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 191277, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 205359, Assoc-acdm, 12, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 39, ?, 240226, HS-grad, 9, Married-civ-spouse, ?, Husband, Black, Male, 0, 0, 40, United-States, <=50K 34, Private, 203357, Some-college, 10, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 52, Local-gov, 153064, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 24, Private, 202959, Assoc-voc, 11, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 105150, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 19, Private, 238474, 11th, 7, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 1085515, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 25, Private, 82560, Assoc-acdm, 12, Never-married, Other-service, Own-child, White, Male, 0, 0, 43, United-States, <=50K 71, Private, 55965, 7th-8th, 4, Widowed, Transport-moving, Not-in-family, White, Male, 0, 0, 10, United-States, <=50K 27, Private, 161087, HS-grad, 9, Married-civ-spouse, Prof-specialty, Wife, Black, Female, 0, 0, 40, United-States, <=50K 28, Private, 261278, Assoc-voc, 11, Never-married, Tech-support, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 54, Private, 182187, Assoc-voc, 11, Married-civ-spouse, Protective-serv, Husband, Black, Male, 15024, 0, 38, Jamaica, >50K 18, Private, 138917, 11th, 7, Never-married, Sales, Own-child, Black, Female, 0, 0, 10, United-States, <=50K 49, Private, 200198, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 40, United-States, <=50K 36, Private, 205359, HS-grad, 9, Married-spouse-absent, Other-service, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 57, Private, 250201, HS-grad, 9, Widowed, Transport-moving, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 56, Federal-gov, 67153, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, Portugal, >50K 17, Private, 244523, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 30, Private, 236599, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 41, Private, 108713, 10th, 6, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 177147, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 129246, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, <=50K 50, ?, 222381, Some-college, 10, Divorced, ?, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 145111, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 44, Private, 62258, 11th, 7, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, State-gov, 108293, Masters, 14, Never-married, Prof-specialty, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 61, ?, 167284, 7th-8th, 4, Widowed, ?, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 25, Private, 97789, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 0, 50, United-States, <=50K 34, Private, 111415, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 70, United-States, <=50K 38, Private, 374524, Some-college, 10, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 287244, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, <=50K 17, ?, 341395, 10th, 6, Never-married, ?, Own-child, Black, Male, 0, 0, 20, United-States, <=50K 48, Private, 278039, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 98360, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 52, Private, 317032, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 55, State-gov, 294395, Assoc-voc, 11, Widowed, Prof-specialty, Unmarried, White, Female, 6849, 0, 40, United-States, <=50K 41, Self-emp-not-inc, 240900, HS-grad, 9, Divorced, Farming-fishing, Other-relative, White, Male, 0, 0, 20, United-States, <=50K 45, Private, 32896, 5th-6th, 3, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 35, United-States, <=50K 49, Private, 97411, 7th-8th, 4, Never-married, Machine-op-inspct, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 45, Laos, <=50K 19, Private, 72355, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 39, Private, 342448, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, <=50K 43, Private, 187702, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 2174, 0, 45, United-States, <=50K 42, Private, 303388, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 65, United-States, <=50K 17, Private, 112291, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 12, United-States, <=50K 30, Private, 208668, Assoc-acdm, 12, Never-married, Prof-specialty, Not-in-family, Black, Female, 0, 0, 25, United-States, <=50K 61, Local-gov, 28375, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 70, United-States, <=50K 48, Private, 207277, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 40, United-States, >50K 60, ?, 88675, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 47857, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Private, 372500, 5th-6th, 3, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 45, Mexico, <=50K 24, Private, 190968, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 48, United-States, <=50K 41, Private, 37997, 12th, 8, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 84, United-States, >50K 42, Private, 257328, HS-grad, 9, Widowed, Transport-moving, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 127610, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 15, United-States, <=50K 22, ?, 139324, 9th, 5, Never-married, ?, Unmarried, Black, Female, 0, 0, 36, United-States, <=50K 47, Private, 164423, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 43, United-States, <=50K 50, Private, 104501, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 1980, 40, United-States, <=50K 30, Private, 56121, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 296212, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 31, Private, 157640, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 44, Private, 222504, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 45, United-States, >50K 34, Private, 261023, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1651, 38, United-States, <=50K 52, Private, 146567, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, Black, Male, 14344, 0, 40, United-States, >50K 34, Private, 116910, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 31, Private, 132601, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 68, Private, 185537, Some-college, 10, Divorced, Sales, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 22, Private, 500720, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, Mexico, <=50K 42, Private, 182108, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 37, Private, 231491, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 36, Self-emp-not-inc, 239415, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 35, United-States, <=50K 38, Private, 179262, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 72, Without-pay, 121004, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 55, United-States, <=50K 40, Private, 252392, 5th-6th, 3, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Mexico, <=50K 19, Private, 163578, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 30, United-States, <=50K 55, Private, 143266, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, Hungary, >50K 30, Private, 285902, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 113094, Bachelors, 13, Separated, Adm-clerical, Unmarried, White, Female, 0, 1092, 40, United-States, <=50K 29, Private, 278637, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 3103, 0, 45, United-States, >50K 41, Private, 174540, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 4, United-States, <=50K 29, Private, 188729, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 24, Private, 72143, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 46, Self-emp-not-inc, 328216, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 44, Private, 165815, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 17, Private, 317702, 10th, 6, Never-married, Sales, Own-child, Black, Female, 0, 0, 15, United-States, <=50K 35, Private, 215323, Assoc-voc, 11, Divorced, Other-service, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 38, Private, 192939, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 156352, 9th, 5, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 155066, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 60, United-States, <=50K 38, Self-emp-not-inc, 152621, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 99, United-States, <=50K 19, Private, 298891, 11th, 7, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, Honduras, <=50K 30, Private, 193298, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 36, Local-gov, 150309, Assoc-voc, 11, Married-civ-spouse, Transport-moving, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 27, Private, 384308, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 27, Private, 305647, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 66, ?, 182378, 7th-8th, 4, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 30, United-States, <=50K 65, Federal-gov, 23494, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 2174, 40, United-States, >50K 37, Private, 421633, Masters, 14, Never-married, Exec-managerial, Not-in-family, Black, Female, 0, 0, 40, United-States, >50K 17, Private, 57723, 11th, 7, Never-married, Sales, Own-child, White, Male, 0, 0, 30, United-States, <=50K 19, ?, 307837, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 103540, 5th-6th, 3, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 50, United-States, <=50K 54, Self-emp-not-inc, 136224, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 21, Private, 231573, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 242804, HS-grad, 9, Separated, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 163671, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 287701, 11th, 7, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 48, United-States, >50K 31, Private, 187560, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 40, United-States, >50K 41, Private, 222504, Prof-school, 15, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 20, Private, 41356, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 59335, Bachelors, 13, Married-civ-spouse, Adm-clerical, Other-relative, White, Female, 0, 0, 15, United-States, <=50K 62, Private, 84756, 9th, 5, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 35, United-States, <=50K 41, Private, 407425, 12th, 8, Divorced, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 37, Private, 162424, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 53, Self-emp-not-inc, 175456, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 30, United-States, <=50K 28, Private, 52603, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 23, Private, 250630, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 46, Self-emp-not-inc, 233974, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 35, United-States, <=50K 28, Private, 376302, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 50, Private, 195638, 10th, 6, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 225775, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 45, Mexico, <=50K 84, Private, 388384, 7th-8th, 4, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 10, United-States, <=50K 48, Self-emp-not-inc, 219021, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, >50K 61, Self-emp-not-inc, 168654, HS-grad, 9, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 44, Private, 180609, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 42, United-States, <=50K 32, Private, 114746, HS-grad, 9, Separated, Handlers-cleaners, Unmarried, Asian-Pac-Islander, Female, 0, 0, 60, South, <=50K 25, Private, 178037, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 35, United-States, <=50K 47, State-gov, 160045, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 268524, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 15, United-States, <=50K 37, Private, 174844, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 17, United-States, <=50K 28, Private, 82488, HS-grad, 9, Divorced, Tech-support, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 34, Private, 221167, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 32, Self-emp-not-inc, 48014, Some-college, 10, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 24, Private, 217226, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 22, ?, 177902, Some-college, 10, Never-married, ?, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 25, United-States, <=50K 30, Private, 39386, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 99, United-States, <=50K 56, Private, 37394, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 115426, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 114158, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 26, United-States, <=50K 40, Private, 119101, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1887, 68, United-States, >50K 28, Private, 360527, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 39, Private, 225544, 12th, 8, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, Self-emp-not-inc, 108438, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Private, 230315, Some-college, 10, Never-married, Other-service, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, Dominican-Republic, <=50K 32, Private, 158002, Some-college, 10, Never-married, Machine-op-inspct, Other-relative, White, Male, 0, 0, 55, Ecuador, <=50K 37, Private, 179468, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 71, Private, 99894, 5th-6th, 3, Widowed, Priv-house-serv, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 75, United-States, <=50K 30, Private, 270889, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Private, 42279, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 53, Federal-gov, 167380, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1740, 50, United-States, <=50K 42, Private, 274913, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 45, United-States, <=50K 44, Private, 35910, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 56, United-States, >50K 26, Private, 68001, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 27162, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 16, United-States, <=50K 37, Self-emp-not-inc, 286146, HS-grad, 9, Married-spouse-absent, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 36, Local-gov, 95462, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 50103, HS-grad, 9, Never-married, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 54, Private, 511668, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 43, United-States, >50K 38, Self-emp-inc, 189679, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 29, Private, 115064, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, State-gov, 215443, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 38, United-States, <=50K 32, Private, 174789, HS-grad, 9, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 50, United-States, <=50K 24, Private, 91999, Assoc-acdm, 12, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 59, Federal-gov, 100931, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 56, Self-emp-not-inc, 119069, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Self-emp-not-inc, 277488, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 84, United-States, <=50K 35, Private, 265662, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 114591, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 15024, 0, 40, United-States, >50K 24, Private, 227594, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 30, Private, 129707, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 1848, 40, United-States, >50K 61, ?, 175032, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 133569, 1st-4th, 2, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 20, Local-gov, 308654, Some-college, 10, Never-married, Protective-serv, Own-child, Asian-Pac-Islander, Female, 0, 0, 20, United-States, <=50K 36, Private, 156084, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 45, Federal-gov, 380127, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 210781, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 189759, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 2001, 40, United-States, <=50K 34, Private, 258675, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 223367, 11th, 7, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 42, ?, 204817, 9th, 5, Never-married, ?, Own-child, Black, Male, 0, 0, 35, United-States, <=50K 23, Private, 409230, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 46, Federal-gov, 308077, Prof-school, 15, Separated, Prof-specialty, Unmarried, White, Female, 0, 0, 40, Germany, >50K 60, Private, 159049, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 70, Germany, >50K 40, Private, 353142, Some-college, 10, Divorced, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 55, Private, 143030, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 304857, Masters, 14, Separated, Tech-support, Not-in-family, White, Male, 27828, 0, 40, United-States, >50K 28, Private, 30912, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 43, United-States, <=50K 55, Private, 125000, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 47, Private, 181363, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 54, Private, 338620, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 52, United-States, >50K 32, Private, 115989, 11th, 7, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 60, United-States, <=50K 38, Private, 111128, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 61, Self-emp-not-inc, 201273, Some-college, 10, Widowed, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 62, Self-emp-inc, 137354, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, South, <=50K 29, Private, 133420, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 5013, 0, 40, United-States, <=50K 26, Private, 192208, HS-grad, 9, Never-married, Protective-serv, Not-in-family, Black, Female, 0, 0, 32, United-States, <=50K 19, Private, 220001, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 50, United-States, <=50K 40, Private, 352612, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 169426, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 7298, 0, 40, United-States, >50K 42, Private, 319016, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 2885, 0, 45, United-States, <=50K 55, Private, 119751, Masters, 14, Never-married, Prof-specialty, Other-relative, Asian-Pac-Islander, Female, 0, 0, 40, Thailand, <=50K 55, Private, 202220, HS-grad, 9, Married-civ-spouse, Other-service, Wife, Black, Female, 2407, 0, 35, United-States, <=50K 43, Self-emp-not-inc, 99220, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 111275, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Federal-gov, 261241, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, >50K 28, Private, 261725, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 36, Private, 182013, Some-college, 10, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 40666, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 41, Private, 216461, Some-college, 10, Divorced, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 60, Private, 320376, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 282951, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 70, United-States, <=50K 36, State-gov, 166697, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 290856, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Private, 455361, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, Guatemala, <=50K 51, Private, 82783, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 56536, 11th, 7, Never-married, Sales, Own-child, White, Female, 1055, 0, 18, India, <=50K 33, Self-emp-not-inc, 109959, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 25, United-States, <=50K 50, Private, 177927, HS-grad, 9, Divorced, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 192337, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 18, Private, 236272, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 35, United-States, <=50K 26, Private, 33610, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 209483, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 47, United-States, <=50K 26, Private, 247006, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 52, United-States, <=50K 30, Local-gov, 311913, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 39, ?, 204756, Some-college, 10, Divorced, ?, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 33, Local-gov, 300681, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 42, State-gov, 24264, Some-college, 10, Divorced, Transport-moving, Unmarried, White, Male, 0, 0, 38, United-States, <=50K 28, Private, 266070, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 20, Private, 226978, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 35, United-States, <=50K 66, Local-gov, 362165, Bachelors, 13, Widowed, Prof-specialty, Not-in-family, Black, Female, 0, 2206, 25, United-States, <=50K 31, Private, 341672, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 0, 50, India, <=50K 36, Private, 179488, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Male, 0, 0, 40, Canada, <=50K 39, Federal-gov, 243872, Assoc-acdm, 12, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 52, Private, 259583, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 159822, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 7688, 0, 40, Poland, >50K 27, Private, 219863, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 206947, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 21, Private, 245572, 9th, 5, Never-married, Other-service, Own-child, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 25, Private, 38488, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 182504, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 38, Private, 193815, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, Italy, <=50K 51, ?, 521665, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 24, United-States, <=50K 29, Private, 46442, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 1902, 50, United-States, >50K 45, Private, 60267, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 59, Private, 264357, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 41, Private, 191814, HS-grad, 9, Married-civ-spouse, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 107882, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 174575, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 17, Private, 143331, 11th, 7, Never-married, Sales, Own-child, White, Male, 0, 0, 20, United-States, <=50K 32, Private, 126132, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 42, Private, 198619, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 68, Private, 211287, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 2392, 40, United-States, >50K 55, Federal-gov, 238192, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 1887, 40, United-States, >50K 43, Private, 257780, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 183355, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 148429, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 71221, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 60, United-States, <=50K 21, Self-emp-not-inc, 236769, 7th-8th, 4, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 32146, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 347491, 11th, 7, Divorced, Craft-repair, Not-in-family, White, Male, 0, 1876, 46, United-States, <=50K 34, Private, 180714, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 2179, 40, United-States, <=50K 57, ?, 188877, 9th, 5, Divorced, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 306747, Bachelors, 13, Divorced, Handlers-cleaners, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 21, State-gov, 478457, Some-college, 10, Never-married, Other-service, Own-child, Black, Female, 0, 0, 12, United-States, <=50K 25, Private, 248990, 5th-6th, 3, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 51, Self-emp-inc, 46281, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 35, Private, 148015, Bachelors, 13, Never-married, Sales, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 19, Private, 278115, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 12, United-States, <=50K 27, Private, 190525, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 55, United-States, >50K 34, Private, 176673, Some-college, 10, Never-married, Sales, Other-relative, Black, Female, 0, 0, 35, United-States, <=50K 33, ?, 202366, HS-grad, 9, Divorced, ?, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 36, Private, 238415, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 33, Self-emp-not-inc, 37939, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 60, Self-emp-not-inc, 35649, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 383493, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 47, Federal-gov, 204900, HS-grad, 9, Married-civ-spouse, Prof-specialty, Wife, Black, Female, 0, 0, 40, United-States, <=50K 42, Private, 20809, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 75, United-States, >50K 34, Private, 148207, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 65, United-States, >50K 21, Private, 200153, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 32, United-States, <=50K 30, Private, 169496, Masters, 14, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 15, United-States, >50K 53, Private, 22978, Masters, 14, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 50, United-States, >50K 34, Private, 366898, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Germany, <=50K 37, Private, 324947, Bachelors, 13, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 321577, HS-grad, 9, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 31, Private, 241360, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 207564, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 220860, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 41, Local-gov, 336571, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, State-gov, 56402, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 30, United-States, <=50K 65, Private, 180280, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 81282, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 86332, Assoc-voc, 11, Married-civ-spouse, Other-service, Husband, White, Male, 4064, 0, 55, United-States, <=50K 30, Local-gov, 27051, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 287647, Masters, 14, Divorced, Sales, Not-in-family, White, Male, 4787, 0, 45, United-States, >50K 37, Self-emp-not-inc, 183735, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 3137, 0, 30, United-States, <=50K 42, Private, 100800, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 62, Private, 155094, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 45, United-States, >50K 67, ?, 102693, HS-grad, 9, Widowed, ?, Not-in-family, White, Male, 1086, 0, 35, United-States, <=50K 31, Private, 151053, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 5178, 0, 40, United-States, >50K 50, Private, 548361, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 20, United-States, >50K 33, Private, 173858, Bachelors, 13, Married-civ-spouse, Adm-clerical, Other-relative, Asian-Pac-Islander, Male, 0, 0, 40, India, <=50K 27, Private, 347153, Some-college, 10, Never-married, Transport-moving, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 319146, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 4386, 0, 40, Mexico, >50K 35, Private, 197719, Some-college, 10, Never-married, Machine-op-inspct, Other-relative, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 55, Private, 197114, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 6, United-States, >50K 54, Self-emp-not-inc, 109418, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 1977, 35, United-States, >50K 56, Private, 182062, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 48, United-States, >50K 21, Private, 184543, Assoc-voc, 11, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 66, Private, 175558, 7th-8th, 4, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 20, Germany, <=50K 46, Private, 122026, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 23, Private, 340543, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 43, Private, 101950, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 40, Private, 179508, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 55, United-States, <=50K 52, Private, 225317, 5th-6th, 3, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Mexico, <=50K 59, Local-gov, 53304, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 36, Local-gov, 282602, Assoc-voc, 11, Separated, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 33, Private, 184016, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 250165, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 196467, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 59, ?, 220783, 10th, 6, Widowed, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 42, Self-emp-not-inc, 178780, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 62, Private, 65868, HS-grad, 9, Widowed, Sales, Not-in-family, White, Female, 0, 0, 43, United-States, <=50K 54, Private, 35459, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 98986, 7th-8th, 4, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 30, United-States, <=50K 36, Private, 282092, Assoc-acdm, 12, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 140764, HS-grad, 9, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 45, United-States, <=50K 30, Private, 33124, HS-grad, 9, Separated, Farming-fishing, Unmarried, White, Female, 0, 0, 14, United-States, <=50K 46, Private, 90042, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Private, 102986, 5th-6th, 3, Married-civ-spouse, Machine-op-inspct, Wife, Asian-Pac-Islander, Female, 0, 0, 40, Laos, >50K 21, Private, 214387, Some-college, 10, Never-married, Sales, Other-relative, White, Male, 0, 0, 64, United-States, <=50K 39, Private, 180667, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 278329, HS-grad, 9, Married-spouse-absent, Exec-managerial, Not-in-family, White, Female, 0, 0, 43, United-States, <=50K 32, Private, 184440, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 3464, 0, 40, United-States, <=50K 23, Private, 140462, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 202565, 1st-4th, 2, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Italy, <=50K 62, ?, 181063, 10th, 6, Widowed, ?, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 28, Private, 287268, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 28, Private, 215955, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 82552, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 41745, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 73587, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 35, United-States, <=50K 54, Private, 263925, 1st-4th, 2, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 19, Private, 196119, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 35, United-States, <=50K 27, Private, 284741, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 30, Private, 293936, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 50, ?, <=50K 35, Private, 340428, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 66, ?, 175891, 9th, 5, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Local-gov, 276973, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 20, United-States, <=50K 30, Private, 161599, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Private, 144064, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 236391, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 224943, Assoc-voc, 11, Never-married, Sales, Other-relative, Black, Male, 0, 0, 65, United-States, <=50K 44, Private, 151294, Some-college, 10, Widowed, Sales, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 52, Private, 68982, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 30, Private, 241885, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Self-emp-not-inc, 189461, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 19, Self-emp-not-inc, 36012, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 85355, HS-grad, 9, Separated, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 20, Private, 157595, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 197286, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 362747, Some-college, 10, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 35, United-States, <=50K 24, Private, 395297, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 35, United-States, <=50K 31, Self-emp-not-inc, 144949, Bachelors, 13, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 20, ?, 163665, HS-grad, 9, Never-married, ?, Own-child, White, Female, 0, 0, 20, United-States, <=50K 32, Private, 141490, Assoc-voc, 11, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 29, Private, 147889, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 40, United-States, <=50K 61, Private, 232808, 10th, 6, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 24, United-States, <=50K 48, Private, 70668, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 50, United-States, <=50K 29, Federal-gov, 33315, Assoc-acdm, 12, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 61, ?, 63526, 12th, 8, Never-married, ?, Not-in-family, Black, Male, 0, 0, 52, United-States, <=50K 34, Private, 591711, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 48, ?, <=50K 22, Private, 200318, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 32, Private, 97723, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1672, 40, United-States, <=50K 38, Private, 109231, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 102889, Some-college, 10, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 167106, HS-grad, 9, Never-married, Craft-repair, Other-relative, Asian-Pac-Islander, Male, 0, 0, 40, Hong, <=50K 35, Private, 182898, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 8614, 0, 40, United-States, >50K 62, Private, 197918, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 67386, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 50, Private, 126592, HS-grad, 9, Separated, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 34, Private, 49469, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 99999, 0, 50, United-States, >50K 37, Self-emp-not-inc, 119929, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 63, Private, 158199, 1st-4th, 2, Widowed, Machine-op-inspct, Unmarried, White, Female, 0, 0, 44, Portugal, <=50K 35, Private, 341102, 9th, 5, Never-married, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 55, Private, 101524, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Private, 202872, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, >50K 25, Private, 195201, HS-grad, 9, Married-civ-spouse, Sales, Husband, Other, Male, 0, 0, 50, United-States, <=50K 51, Private, 128272, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 263094, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 40, United-States, >50K 54, Self-emp-inc, 357596, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 55, United-States, >50K 47, Local-gov, 102628, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 171114, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 216414, Assoc-voc, 11, Married-spouse-absent, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 127753, 12th, 8, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 282698, 7th-8th, 4, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 80, United-States, <=50K 35, Private, 139364, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 1902, 40, United-States, >50K 36, Local-gov, 312785, Bachelors, 13, Never-married, Prof-specialty, Own-child, Black, Male, 0, 0, 35, United-States, <=50K 18, Private, 92864, 12th, 8, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 46, Local-gov, 175428, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Private, 104223, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 32, United-States, <=50K 29, Private, 144784, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 65, Private, 178934, HS-grad, 9, Widowed, Other-service, Unmarried, Black, Female, 0, 0, 20, Jamaica, <=50K 41, Private, 211253, Masters, 14, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 34, Private, 133122, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, Private, 103540, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 39, State-gov, 172700, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 21, Private, 282484, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 323055, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 33, State-gov, 291494, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 28, Private, 214702, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 32, Private, 116055, HS-grad, 9, Never-married, Adm-clerical, Unmarried, Black, Female, 2977, 0, 35, United-States, <=50K 32, Private, 226696, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 55, United-States, >50K 31, Private, 216827, HS-grad, 9, Separated, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 41, Self-emp-not-inc, 153132, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 40, United-States, >50K 48, Private, 307440, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, Asian-Pac-Islander, Male, 0, 0, 45, Philippines, >50K 27, Private, 278122, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 122195, HS-grad, 9, Widowed, Craft-repair, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 34, Self-emp-not-inc, 156890, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 17, Private, 36877, 10th, 6, Never-married, Sales, Own-child, White, Female, 0, 0, 10, United-States, <=50K 25, Private, 131178, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 23, United-States, <=50K 34, Self-emp-inc, 62396, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 62, United-States, >50K 33, Private, 73054, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 96844, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 22, Private, 324922, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 61, Private, 130684, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 42, United-States, <=50K 40, Private, 178983, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 30, United-States, >50K 58, Private, 81038, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 12, United-States, <=50K 30, Private, 151967, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 58, United-States, <=50K 24, Private, 278107, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 60, United-States, <=50K 52, Self-emp-not-inc, 183146, 12th, 8, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 50, Private, 183638, HS-grad, 9, Widowed, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 247892, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 30, United-States, <=50K 22, Private, 221480, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 118551, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 35, ?, >50K 21, Private, 518530, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 193787, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 50, United-States, <=50K 34, Self-emp-inc, 157466, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, <=50K 48, Private, 141511, 10th, 6, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 61, ?, 158712, HS-grad, 9, Divorced, ?, Not-in-family, White, Female, 0, 0, 99, United-States, <=50K 21, Private, 252253, Some-college, 10, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 20, Private, 200450, 7th-8th, 4, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 52, United-States, <=50K 30, State-gov, 343789, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 44, Private, 277647, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 1902, 40, United-States, >50K 44, Private, 291566, HS-grad, 9, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 60, United-States, <=50K 29, Private, 151382, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 31, Private, 221167, Prof-school, 15, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 35, Private, 196178, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 302422, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 37379, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 37, Self-emp-not-inc, 82540, 9th, 5, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 70, United-States, >50K 33, Self-emp-not-inc, 182926, Bachelors, 13, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, ?, <=50K 44, Private, 159911, 7th-8th, 4, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 55, United-States, <=50K 34, Private, 212781, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Local-gov, 207213, Assoc-acdm, 12, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 5, United-States, <=50K 30, Private, 200192, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 45, United-States, <=50K 41, Local-gov, 180096, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, <=50K 23, Private, 192812, Bachelors, 13, Never-married, Tech-support, Own-child, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 105908, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 70, United-States, <=50K 48, Private, 373366, 1st-4th, 2, Married-civ-spouse, Farming-fishing, Husband, White, Male, 3781, 0, 50, Mexico, <=50K 26, State-gov, 234190, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 32, Private, 260868, Bachelors, 13, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 40, United-States, >50K 26, Private, 109097, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 48, United-States, <=50K 36, Private, 171393, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7298, 0, 55, United-States, >50K 49, Private, 209146, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, ?, 289046, HS-grad, 9, Divorced, ?, Not-in-family, Black, Male, 0, 1741, 40, United-States, <=50K 54, Private, 172281, Masters, 14, Divorced, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 36, Private, 73023, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 41, Private, 122626, HS-grad, 9, Divorced, Handlers-cleaners, Unmarried, White, Male, 0, 0, 48, United-States, <=50K 27, Private, 113635, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 68, ?, 257269, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 2377, 35, United-States, >50K 21, ?, 191806, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 75, United-States, <=50K 56, ?, 35723, HS-grad, 9, Divorced, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 40, Self-emp-not-inc, 30759, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 46, Private, 105327, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 55, ?, 376058, 9th, 5, Never-married, ?, Own-child, White, Female, 0, 0, 45, United-States, <=50K 43, Private, 219307, 9th, 5, Divorced, Transport-moving, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 46, Private, 208067, HS-grad, 9, Divorced, Craft-repair, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 51, Self-emp-not-inc, 78631, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Amer-Indian-Eskimo, Male, 0, 0, 60, United-States, <=50K 19, Private, 210308, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 15, United-States, <=50K 67, Local-gov, 190661, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Female, 7896, 0, 50, United-States, >50K 31, Private, 594187, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 228476, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 21, Private, 126613, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 30267, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 23, Private, 216811, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 16, United-States, <=50K 62, Local-gov, 115763, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 31, Local-gov, 199368, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 50, United-States, >50K 52, Private, 159755, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1887, 40, United-States, >50K 39, Self-emp-not-inc, 188335, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 417668, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 30, United-States, <=50K 55, ?, 141807, HS-grad, 9, Never-married, ?, Not-in-family, White, Male, 13550, 0, 40, United-States, >50K 38, Private, 296317, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 36, Private, 164898, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 452406, 11th, 7, Never-married, Sales, Own-child, Black, Female, 0, 0, 15, United-States, <=50K 27, Private, 42696, HS-grad, 9, Married-spouse-absent, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 262994, Some-college, 10, Divorced, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 43, State-gov, 167298, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 103529, 11th, 7, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 47, Private, 97883, Bachelors, 13, Widowed, Priv-house-serv, Unmarried, White, Female, 25236, 0, 35, United-States, >50K 49, State-gov, 269417, Doctorate, 16, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 2258, 50, United-States, >50K 34, Private, 199539, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, >50K 19, ?, 39460, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 0, 60, United-States, <=50K 79, Federal-gov, 62176, Doctorate, 16, Widowed, Exec-managerial, Not-in-family, White, Male, 0, 0, 6, United-States, >50K 28, State-gov, 239130, Some-college, 10, Divorced, Other-service, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 41, Self-emp-inc, 151089, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 21, Private, 331611, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 50, United-States, <=50K 31, Self-emp-not-inc, 203463, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 151518, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 23, Self-emp-inc, 39844, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 32, Private, 299635, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, Germany, <=50K 67, Private, 123393, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 209538, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 35, Self-emp-not-inc, 238802, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 29, Private, 499197, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 200220, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 114059, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 18, Private, 434430, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 47, Private, 185385, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 5013, 0, 24, United-States, <=50K 22, Private, 225156, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 377931, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 2377, 48, United-States, <=50K 27, ?, 133359, Bachelors, 13, Married-spouse-absent, ?, Not-in-family, White, Male, 0, 0, 50, ?, <=50K 28, Private, 226891, Some-college, 10, Never-married, Adm-clerical, Unmarried, Asian-Pac-Islander, Female, 0, 0, 30, ?, <=50K 32, Private, 201988, Prof-school, 15, Married-civ-spouse, Sales, Husband, White, Male, 4508, 0, 40, ?, <=50K 40, Private, 287008, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 55, Germany, >50K 23, Private, 151910, Bachelors, 13, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 1719, 40, United-States, <=50K 25, Private, 231714, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Self-emp-inc, 178510, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 2258, 60, United-States, <=50K 43, Private, 178866, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 25, United-States, >50K 31, Private, 110643, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 55, United-States, >50K 33, Private, 148261, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 217902, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Self-emp-not-inc, 77207, Masters, 14, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 30, United-States, <=50K 32, ?, 377017, Assoc-acdm, 12, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 78, Private, 184759, 7th-8th, 4, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 1797, 0, 15, United-States, <=50K 64, Self-emp-inc, 80333, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 58, Private, 265086, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 55, ?, 102058, 12th, 8, Widowed, ?, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 20, Private, 333843, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 296478, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Local-gov, 116662, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Self-emp-not-inc, 353298, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 99999, 0, 50, United-States, >50K 42, Private, 142424, Assoc-voc, 11, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Local-gov, 200808, 12th, 8, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 35, Puerto-Rico, <=50K 29, Private, 119052, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 33, Private, 168981, 1st-4th, 2, Never-married, Sales, Own-child, White, Female, 0, 0, 24, United-States, <=50K 44, Private, 151780, Some-college, 10, Widowed, Exec-managerial, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 70, Private, 237065, 5th-6th, 3, Widowed, Other-service, Other-relative, White, Female, 2346, 0, 40, ?, <=50K 25, Private, 509866, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 78, United-States, <=50K 24, State-gov, 249385, Bachelors, 13, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 10, United-States, <=50K 42, State-gov, 109462, Bachelors, 13, Divorced, Adm-clerical, Unmarried, Black, Female, 2977, 0, 40, United-States, <=50K 53, Private, 250034, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 50, United-States, >50K 39, Private, 249720, Bachelors, 13, Divorced, Exec-managerial, Unmarried, Black, Female, 0, 0, 60, United-States, <=50K 72, Self-emp-not-inc, 258761, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Self-emp-inc, 64048, 9th, 5, Never-married, Sales, Own-child, White, Female, 0, 0, 44, Portugal, <=50K 25, State-gov, 153534, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 193815, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 27, Private, 255582, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 204527, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 64, Self-emp-not-inc, 159938, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 2635, 0, 24, Italy, <=50K 29, Self-emp-not-inc, 229341, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 50, Private, 128143, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 33, Private, 175479, 5th-6th, 3, Never-married, Other-service, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 18, Private, 301814, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 20, Private, 238917, 11th, 7, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 32, Mexico, <=50K 32, Private, 205581, Some-college, 10, Separated, Tech-support, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 45, Private, 340341, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 48, Private, 147860, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Wife, Black, Female, 0, 0, 40, United-States, <=50K 20, ?, 121023, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 259496, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 34, Federal-gov, 190228, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 1902, 48, United-States, >50K 43, Private, 180599, Bachelors, 13, Separated, Exec-managerial, Unmarried, White, Male, 8614, 0, 40, United-States, >50K 44, Private, 116358, Bachelors, 13, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, >50K 47, Self-emp-not-inc, 180446, Some-college, 10, Married-civ-spouse, Tech-support, Husband, Black, Male, 0, 0, 40, United-States, >50K 47, Private, 264244, HS-grad, 9, Married-spouse-absent, Craft-repair, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 46, Local-gov, 197988, 1st-4th, 2, Never-married, Other-service, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 20, United-States, <=50K 19, Private, 206599, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 313146, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Self-emp-inc, 99212, HS-grad, 9, Separated, Exec-managerial, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 340599, 11th, 7, Separated, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 31, Private, 62932, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 44861, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 53893, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 53, Self-emp-inc, 152810, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 5178, 0, 45, United-States, >50K 47, Local-gov, 128401, Doctorate, 16, Never-married, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 336951, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 60, Self-emp-not-inc, 95445, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 3137, 0, 46, United-States, <=50K 43, Private, 54611, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Self-emp-not-inc, 315984, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 7688, 0, 50, United-States, >50K 28, Private, 210313, 10th, 6, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 19, Private, 181020, 11th, 7, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 30, United-States, <=50K 51, Self-emp-not-inc, 120781, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, Other, Male, 99999, 0, 70, India, >50K 19, Private, 256979, HS-grad, 9, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 35, United-States, <=50K 64, Private, 47298, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 44, Private, 125461, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 21, Private, 209955, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 33, Private, 182246, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 63, Private, 76860, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, >50K 44, ?, 91949, HS-grad, 9, Never-married, ?, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 44, Local-gov, 136986, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 35, United-States, >50K 28, Federal-gov, 183445, HS-grad, 9, Never-married, Exec-managerial, Unmarried, White, Female, 0, 0, 70, Puerto-Rico, <=50K 24, Private, 130741, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 20, Federal-gov, 191878, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 20, United-States, <=50K 21, ?, 233923, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 24, United-States, <=50K 20, Private, 48121, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 304302, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 34, Federal-gov, 284703, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 52, United-States, <=50K 17, Private, 401198, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 15, United-States, <=50K 35, Private, 243357, 11th, 7, Separated, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 26, Private, 32276, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 110538, HS-grad, 9, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 25, Private, 257310, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Self-emp-not-inc, 411950, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Local-gov, 392668, Assoc-voc, 11, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 43, Self-emp-not-inc, 52498, Bachelors, 13, Never-married, Prof-specialty, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 36, Private, 223433, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 50, United-States, >50K 37, Private, 87076, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 58, Private, 224854, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 193379, Assoc-acdm, 12, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 54, Private, 98436, Masters, 14, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, ?, 116632, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 60, United-States, <=50K 65, Self-emp-inc, 210381, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 65, United-States, >50K 44, Private, 90688, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 45, Laos, <=50K 61, Private, 229744, 5th-6th, 3, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, El-Salvador, <=50K 29, Private, 59732, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 34, Private, 192900, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 24, State-gov, 90046, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, Canada, <=50K 40, Private, 272960, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 42, United-States, >50K 42, Self-emp-inc, 152071, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, Cuba, >50K 50, Private, 301583, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 18, ?, 171964, HS-grad, 9, Never-married, ?, Own-child, White, Female, 0, 1602, 20, United-States, <=50K 49, Private, 315984, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 241962, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 131591, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 45, United-States, <=50K 70, Self-emp-inc, 207938, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 5, United-States, <=50K 51, Private, 53197, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 24, Private, 121023, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 57, Self-emp-not-inc, 287229, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, >50K 22, Private, 163911, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 31, Private, 191834, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 204734, Some-college, 10, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 40, United-States, <=50K 45, Self-emp-not-inc, 220978, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 39, Private, 365739, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 50103, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 283293, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 38, Self-emp-not-inc, 194534, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 99999, 0, 60, United-States, >50K 19, Private, 263338, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, United-States, <=50K 36, ?, 504871, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Private, 348592, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 44, United-States, <=50K 28, Private, 173944, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 53, Private, 226135, 9th, 5, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, Jamaica, <=50K 32, Private, 172375, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 57, Self-emp-inc, 127728, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 60, United-States, >50K 47, Private, 347025, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 191335, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 56, United-States, <=50K 21, Private, 247779, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 38, United-States, <=50K 25, State-gov, 262664, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Private, 95855, HS-grad, 9, Divorced, Protective-serv, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 74501, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 43, Private, 245317, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 61, Private, 29059, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 2754, 25, United-States, <=50K 56, Private, 200316, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 35, United-States, <=50K 35, Private, 198341, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 40, ?, <=50K 59, Private, 100453, 7th-8th, 4, Separated, Other-service, Own-child, Black, Female, 0, 0, 38, United-States, <=50K 44, Self-emp-not-inc, 343190, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1887, 55, United-States, >50K 47, Private, 235683, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 83237, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 64, Private, 88470, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 198801, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 53, Private, 168107, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 50, Private, 196193, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, ?, <=50K 30, ?, 205418, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 20, United-States, <=50K 46, Private, 695411, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 44, United-States, <=50K 45, Self-emp-inc, 139268, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 44, Federal-gov, 192771, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 59, Self-emp-inc, 122390, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 48, United-States, >50K 65, Self-emp-inc, 184965, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 40, United-States, >50K 23, Private, 180837, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 33, Private, 159548, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 38, United-States, <=50K 34, Private, 110554, HS-grad, 9, Divorced, Sales, Own-child, White, Female, 0, 0, 35, United-States, <=50K 38, Private, 103474, Assoc-voc, 11, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 62, Private, 178249, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 35, United-States, >50K 21, Private, 138768, Some-college, 10, Never-married, Sales, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 321824, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 8, United-States, <=50K 35, Private, 244803, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, Peru, <=50K 62, Local-gov, 206063, Some-college, 10, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 53, Private, 167651, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 69, State-gov, 163689, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 16, United-States, <=50K 19, Self-emp-not-inc, 45546, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 16, United-States, <=50K 47, Private, 420986, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 52, Self-emp-inc, 68015, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 90, United-States, >50K 54, Private, 175594, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, ?, 148673, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 10, United-States, <=50K 30, Private, 206322, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 73, United-States, >50K 39, Private, 272338, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 25, United-States, <=50K 73, Private, 105886, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 1173, 0, 75, United-States, <=50K 64, Private, 312498, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 177675, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 152810, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 57, Private, 319122, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 212304, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 208321, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 1740, 40, United-States, <=50K 39, Private, 240841, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 49, Private, 208978, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 16, United-States, <=50K 23, Local-gov, 442359, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 1092, 40, United-States, <=50K 28, Private, 198197, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 55, United-States, >50K 46, Private, 261059, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 50, United-States, >50K 40, Private, 72791, Some-college, 10, Never-married, Craft-repair, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 24, Private, 275395, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, <=50K 20, ?, 195767, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 462966, 10th, 6, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 8, El-Salvador, <=50K 24, ?, 265434, Bachelors, 13, Never-married, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 31269, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Local-gov, 246291, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 46, United-States, <=50K 54, Federal-gov, 128378, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Local-gov, 231180, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 31, Local-gov, 206297, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 47, Self-emp-inc, 337050, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 193075, HS-grad, 9, Divorced, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 33, Local-gov, 169652, Assoc-voc, 11, Never-married, Adm-clerical, Own-child, White, Male, 0, 1669, 55, United-States, <=50K 35, Private, 35945, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 20, ?, 141453, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 10, United-States, <=50K 36, Private, 252231, Preschool, 1, Never-married, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 40, Puerto-Rico, <=50K 30, Private, 128016, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 39, Private, 150057, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, >50K 25, Private, 258276, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 40, Private, 188465, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 25, Self-emp-inc, 161007, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 403468, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, Mexico, <=50K 53, Federal-gov, 181677, Some-college, 10, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 120243, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 10, United-States, <=50K 41, Private, 157025, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 25, Private, 306908, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 66, Self-emp-not-inc, 28061, 7th-8th, 4, Widowed, Farming-fishing, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 53, Private, 95540, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 1471, 0, 40, United-States, <=50K 27, Private, 135001, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 293398, HS-grad, 9, Separated, Sales, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 23, Private, 185106, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 29, Self-emp-not-inc, 245790, 10th, 6, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 80, United-States, <=50K 26, Private, 134004, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 205036, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 42, United-States, <=50K 26, Private, 244495, 9th, 5, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 38, Private, 159179, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 405155, 5th-6th, 3, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Mexico, <=50K 34, Private, 177437, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 15024, 0, 45, United-States, >50K 32, Federal-gov, 402361, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 57, Self-emp-not-inc, 184553, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 31, Private, 302626, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 99138, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 39, Private, 112731, HS-grad, 9, Divorced, Other-service, Not-in-family, Other, Female, 0, 0, 40, Dominican-Republic, <=50K 35, Private, 192923, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 2377, 40, United-States, <=50K 18, Private, 761006, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 75, ?, 125784, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 8, United-States, <=50K 28, Private, 182344, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 41, Self-emp-not-inc, 117012, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 39, Federal-gov, 30673, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Federal-gov, 484669, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, State-gov, 314052, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 43, State-gov, 38537, Some-college, 10, Divorced, Exec-managerial, Unmarried, Black, Female, 0, 0, 38, ?, <=50K 27, Private, 165412, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 198341, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 1902, 55, India, >50K 46, Private, 116635, Bachelors, 13, Separated, Prof-specialty, Unmarried, Black, Female, 0, 0, 36, United-States, <=50K 20, Private, 185452, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 118686, Some-college, 10, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 69, Private, 76939, HS-grad, 9, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Federal-gov, 160646, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 35, United-States, <=50K 49, State-gov, 126754, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Portugal, <=50K 20, Private, 211049, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 30, United-States, <=50K 52, Private, 311931, 5th-6th, 3, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 15, El-Salvador, <=50K 33, Private, 283602, 5th-6th, 3, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 59, Mexico, <=50K 18, Private, 155021, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 6, United-States, <=50K 55, Self-emp-not-inc, 100569, HS-grad, 9, Separated, Farming-fishing, Unmarried, White, Female, 0, 0, 55, United-States, <=50K 61, Private, 380462, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, Black, Male, 0, 0, 40, United-States, <=50K 61, Federal-gov, 221943, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 9386, 0, 40, United-States, >50K 39, Private, 114544, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, >50K 30, Private, 248584, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 227468, HS-grad, 9, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 36, Private, 66173, Assoc-acdm, 12, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 15, United-States, <=50K 34, Private, 107624, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 53, Private, 70387, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 4386, 0, 40, India, >50K 38, Private, 423616, Assoc-voc, 11, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 36, United-States, >50K 46, Private, 98637, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 50, United-States, >50K 27, Local-gov, 216013, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Self-emp-not-inc, 210926, 11th, 7, Separated, Handlers-cleaners, Unmarried, White, Female, 0, 0, 40, Nicaragua, <=50K 60, Local-gov, 255711, Bachelors, 13, Widowed, Prof-specialty, Unmarried, White, Female, 0, 0, 60, United-States, >50K 23, Private, 77581, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 152461, Bachelors, 13, Never-married, Prof-specialty, Unmarried, White, Female, 14344, 0, 50, United-States, >50K 22, Private, 203263, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 50, United-States, <=50K 25, Private, 261519, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 35, United-States, <=50K 29, Private, 91189, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, <=50K 90, Federal-gov, 195433, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 30, United-States, <=50K 37, Local-gov, 272471, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 311524, HS-grad, 9, Never-married, Craft-repair, Own-child, Black, Male, 0, 0, 38, United-States, <=50K 18, Private, 151386, HS-grad, 9, Married-spouse-absent, Other-service, Own-child, Black, Male, 0, 0, 40, Jamaica, <=50K 35, Private, 187625, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 65, United-States, <=50K 50, Private, 108933, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 2885, 0, 40, United-States, <=50K 54, Private, 135388, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 5178, 0, 40, United-States, >50K 43, Private, 169383, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 28, Self-emp-inc, 191129, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 65, United-States, >50K 51, Private, 467611, 9th, 5, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, Mexico, <=50K 31, Private, 373185, Some-college, 10, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 42, Mexico, <=50K 69, Private, 130060, HS-grad, 9, Separated, Transport-moving, Unmarried, Black, Female, 2387, 0, 40, United-States, <=50K 57, Private, 199934, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 71, ?, 116165, Some-college, 10, Widowed, ?, Not-in-family, White, Female, 0, 0, 14, Canada, <=50K 28, Private, 42881, 10th, 6, Divorced, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 28, ?, 174666, 10th, 6, Separated, ?, Not-in-family, White, Male, 0, 0, 80, United-States, <=50K 25, Private, 169759, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 95, United-States, <=50K 49, Self-emp-not-inc, 181547, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 30, Columbia, <=50K 52, Private, 95704, 9th, 5, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 237432, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, ?, <=50K 32, Private, 226267, 5th-6th, 3, Married-spouse-absent, Craft-repair, Other-relative, White, Male, 0, 0, 40, El-Salvador, <=50K 31, Private, 159979, Some-college, 10, Never-married, Sales, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 50, United-States, <=50K 30, Private, 203488, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 50, United-States, <=50K 24, Private, 403671, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 45, Private, 192323, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 66, Yugoslavia, <=50K 30, Private, 167832, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 145166, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 55, United-States, >50K 42, State-gov, 155657, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, Black, Female, 0, 0, 25, United-States, <=50K 49, Private, 116789, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 39234, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, United-States, <=50K 25, Private, 124111, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 172828, 9th, 5, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 55, Outlying-US(Guam-USVI-etc), <=50K 55, Private, 143372, HS-grad, 9, Divorced, Sales, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 31, Self-emp-not-inc, 265807, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 3137, 0, 50, United-States, <=50K 25, State-gov, 218184, Bachelors, 13, Never-married, Protective-serv, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 32, Private, 154087, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Federal-gov, 440647, Some-college, 10, Never-married, Adm-clerical, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 193952, HS-grad, 9, Divorced, Other-service, Not-in-family, Black, Female, 0, 0, 40, ?, <=50K 52, Private, 125932, 7th-8th, 4, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 284652, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 15, United-States, <=50K 21, ?, 214635, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 24, United-States, <=50K 43, Private, 173316, Assoc-acdm, 12, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, State-gov, 65390, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, ?, <=50K 40, Self-emp-inc, 45054, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 54, Private, 185042, 1st-4th, 2, Separated, Priv-house-serv, Other-relative, White, Female, 0, 0, 40, Mexico, <=50K 35, Private, 117381, Bachelors, 13, Divorced, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 258666, Assoc-voc, 11, Never-married, Tech-support, Not-in-family, White, Female, 0, 1974, 40, United-States, <=50K 35, Private, 179668, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 57, Private, 127277, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Taiwan, >50K 26, Private, 192022, Bachelors, 13, Never-married, Other-service, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 55, Self-emp-not-inc, 99551, Bachelors, 13, Widowed, Sales, Unmarried, White, Female, 0, 0, 15, United-States, <=50K 51, Private, 208899, Bachelors, 13, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 287658, Assoc-acdm, 12, Never-married, Transport-moving, Not-in-family, Black, Male, 0, 0, 30, Jamaica, <=50K 31, Private, 196125, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 275051, 11th, 7, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 8, United-States, <=50K 38, Private, 23892, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, United-States, <=50K 39, Federal-gov, 376455, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1887, 50, United-States, >50K 29, Private, 267989, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 39, Private, 30269, Assoc-voc, 11, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 204235, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 46, Local-gov, 209057, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 73, Private, 349347, 7th-8th, 4, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 25, United-States, <=50K 47, Local-gov, 154033, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 1876, 40, United-States, <=50K 28, Private, 124680, HS-grad, 9, Never-married, Sales, Unmarried, White, Female, 0, 0, 70, United-States, <=50K 27, Private, 132805, 10th, 6, Never-married, Sales, Other-relative, White, Male, 0, 1980, 40, United-States, <=50K 38, Private, 99233, Prof-school, 15, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 19, Private, 224849, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 60, Local-gov, 101110, Assoc-voc, 11, Divorced, Prof-specialty, Unmarried, White, Male, 0, 0, 40, United-States, >50K 24, Private, 184839, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 302847, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 181322, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 26, Local-gov, 192213, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, Canada, <=50K 28, State-gov, 37250, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 16, United-States, <=50K 38, Self-emp-inc, 140854, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 47, Private, 158286, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 50, Private, 269095, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, >50K 27, Private, 279960, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 176239, Some-college, 10, Widowed, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 115360, 10th, 6, Married-civ-spouse, Machine-op-inspct, Own-child, White, Female, 3464, 0, 40, United-States, <=50K 49, Private, 337666, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 68, ?, 255276, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 48, United-States, >50K 63, Private, 145212, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 185099, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 70, United-States, >50K 42, Private, 142756, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 28, Private, 156300, Masters, 14, Never-married, Exec-managerial, Not-in-family, Black, Female, 0, 0, 45, United-States, <=50K 68, ?, 186266, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 8, United-States, <=50K 38, Private, 219137, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 22, United-States, <=50K 43, Private, 110970, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 40, United-States, >50K 49, Private, 203067, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 59, Private, 148844, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 154941, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 124111, Assoc-acdm, 12, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 36, United-States, <=50K 59, Private, 157303, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 34, Private, 113838, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 34, Private, 165737, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 43, India, >50K 67, Private, 140849, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 24, United-States, <=50K 45, Private, 200363, Assoc-voc, 11, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 44, United-States, <=50K 64, Private, 180247, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 51, Private, 82578, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 38, Canada, >50K 31, Private, 227146, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, >50K 42, Self-emp-inc, 348886, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 65, Private, 90907, 5th-6th, 3, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 23, Private, 142766, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 31, Private, 246439, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 33, Private, 184784, 10th, 6, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 17, Local-gov, 195262, 11th, 7, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 35, United-States, <=50K 63, Private, 167967, Masters, 14, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 46, United-States, <=50K 48, Private, 145636, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 60, United-States, >50K 45, Local-gov, 170099, Assoc-acdm, 12, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 17, Private, 228253, 10th, 6, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 10, United-States, <=50K 26, Local-gov, 205570, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Federal-gov, 506830, Some-college, 10, Divorced, Tech-support, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 29, Private, 412435, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, Outlying-US(Guam-USVI-etc), <=50K 44, Private, 163331, Some-college, 10, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 43, Federal-gov, 222756, Masters, 14, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, State-gov, 318918, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 105188, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 40, Haiti, <=50K 23, Private, 199884, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 19, Private, 96483, HS-grad, 9, Never-married, Other-service, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 49, Self-emp-not-inc, 192203, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Canada, <=50K 52, Private, 203392, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 5013, 0, 40, United-States, <=50K 32, Private, 99646, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 38, Private, 167440, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 4508, 0, 40, United-States, <=50K 25, ?, 210095, 5th-6th, 3, Never-married, ?, Unmarried, White, Female, 0, 0, 25, El-Salvador, <=50K 44, Private, 219591, Some-college, 10, Divorced, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 63, Private, 30270, 7th-8th, 4, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Local-gov, 226020, HS-grad, 9, Separated, Other-service, Not-in-family, Black, Female, 0, 0, 60, ?, <=50K 21, Private, 314165, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 40, Columbia, <=50K 32, Private, 330715, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Self-emp-not-inc, 35448, HS-grad, 9, Separated, Other-service, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 50, State-gov, 172970, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, Puerto-Rico, <=50K 26, Self-emp-inc, 189502, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 80, United-States, >50K 35, Private, 61518, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 35, United-States, <=50K 31, Private, 574005, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 44, United-States, >50K 24, Private, 281356, 1st-4th, 2, Never-married, Farming-fishing, Not-in-family, Other, Male, 0, 0, 66, Mexico, <=50K 40, Private, 138975, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 56, United-States, <=50K 31, Private, 176969, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 43, Private, 132393, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, Poland, <=50K 44, Private, 194924, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 35, United-States, >50K 40, Private, 478205, Bachelors, 13, Never-married, Prof-specialty, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 75, ?, 128224, 5th-6th, 3, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 25, United-States, <=50K 52, Local-gov, 30118, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 3137, 0, 42, United-States, <=50K 51, Self-emp-not-inc, 290688, 5th-6th, 3, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, State-gov, 85566, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 121874, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 50, United-States, >50K 40, Self-emp-not-inc, 29036, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 33, Private, 348152, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Local-gov, 73715, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 60, United-States, >50K 29, Private, 151382, Assoc-voc, 11, Divorced, Handlers-cleaners, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 37, Private, 236359, Some-college, 10, Divorced, Adm-clerical, Not-in-family, Black, Female, 0, 0, 37, United-States, <=50K 37, Private, 19899, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 15024, 0, 45, United-States, >50K 19, Private, 138760, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 46, Local-gov, 354962, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 46, Private, 181363, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Private, 393360, Some-college, 10, Never-married, Protective-serv, Own-child, Black, Male, 0, 0, 30, United-States, <=50K 34, Private, 210736, Some-college, 10, Separated, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, ?, <=50K 38, Private, 110013, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 43, United-States, <=50K 26, Private, 193304, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 118551, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 57, Private, 201991, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 157446, 11th, 7, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 26, Local-gov, 283217, Some-college, 10, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 247794, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 84, United-States, <=50K 38, Private, 43712, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7298, 0, 60, United-States, >50K 61, Private, 35649, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 6, United-States, <=50K 36, Self-emp-not-inc, 342719, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, ?, >50K 61, ?, 71467, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 3103, 0, 40, United-States, >50K 17, Private, 271837, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 16, United-States, <=50K 40, Private, 400061, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, Other, Male, 0, 0, 40, United-States, >50K 18, Private, 62972, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 16, United-States, <=50K 21, Private, 174907, Assoc-acdm, 12, Never-married, Sales, Own-child, White, Female, 0, 0, 32, United-States, <=50K 41, Private, 176452, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, Peru, <=50K 46, Private, 268358, 11th, 7, Separated, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 55, Federal-gov, 176904, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 176683, Assoc-acdm, 12, Never-married, Sales, Not-in-family, White, Male, 0, 0, 52, United-States, <=50K 39, Private, 98077, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 42, United-States, <=50K 36, Private, 266461, HS-grad, 9, Never-married, Transport-moving, Own-child, Black, Male, 0, 0, 48, United-States, <=50K 51, Private, 312477, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 3908, 0, 40, United-States, <=50K 27, Private, 604045, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Local-gov, 131568, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Private, 97688, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 47, United-States, <=50K 23, Private, 373628, Bachelors, 13, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 56, Private, 367984, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 40, United-States, >50K 41, Self-emp-not-inc, 193459, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 49, Private, 250733, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 46, United-States, <=50K 46, Federal-gov, 199725, Assoc-voc, 11, Divorced, Craft-repair, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 60, United-States, <=50K 54, Private, 156877, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Greece, <=50K 38, Private, 122076, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 7298, 0, 43, United-States, >50K 45, Self-emp-not-inc, 216402, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 50, India, >50K 50, Self-emp-not-inc, 42402, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 2415, 30, United-States, >50K 22, Private, 315974, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 63437, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, Ireland, <=50K 27, Private, 160786, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 34, Private, 85374, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 465974, 11th, 7, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 30, United-States, <=50K 47, Private, 78529, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 36, State-gov, 98037, Assoc-voc, 11, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 22, Private, 178390, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 210940, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 2002, 45, United-States, <=50K 43, Private, 64506, Some-college, 10, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 54, Private, 128378, Some-college, 10, Widowed, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 24, Private, 234460, 9th, 5, Never-married, Machine-op-inspct, Own-child, Black, Female, 0, 0, 40, Dominican-Republic, <=50K 29, Private, 176760, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 55, United-States, <=50K 40, State-gov, 59460, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 18, Private, 234428, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 31, Private, 215047, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 57, Private, 140426, Doctorate, 16, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 1977, 40, Germany, >50K 32, Private, 191777, Masters, 14, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 48, Private, 148995, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 24, Private, 229773, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 24, Private, 174461, Assoc-acdm, 12, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 22, United-States, <=50K 24, Private, 250647, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Guatemala, <=50K 49, Local-gov, 119904, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 7688, 0, 30, United-States, >50K 27, Self-emp-not-inc, 151402, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 1573, 70, United-States, <=50K 37, Private, 184556, Some-college, 10, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 263561, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, >50K 19, Private, 177945, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 25, United-States, <=50K 45, Private, 306889, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 54, Local-gov, 54377, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 144351, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 625, 40, United-States, <=50K 22, Private, 95566, Some-college, 10, Married-spouse-absent, Sales, Own-child, Other, Female, 0, 0, 22, Dominican-Republic, <=50K 20, Private, 181675, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 172129, 9th, 5, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, ?, 350759, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, Self-emp-not-inc, 105592, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 20, ?, 200061, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, ?, <=50K 34, Self-emp-inc, 200689, Bachelors, 13, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 386726, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 1977, 44, United-States, >50K 28, Local-gov, 135567, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, Black, Female, 4101, 0, 60, United-States, <=50K 38, Local-gov, 282753, Assoc-voc, 11, Divorced, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 137367, 11th, 7, Never-married, Craft-repair, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, India, <=50K 35, Self-emp-inc, 153976, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 51, Self-emp-inc, 96062, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 33, Private, 152933, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 71, Private, 97870, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 15, Germany, <=50K 48, Private, 254291, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 53, Self-emp-not-inc, 101432, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 40, Private, 125776, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 64, Self-emp-not-inc, 165479, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 5, United-States, <=50K 42, Federal-gov, 172307, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 48, United-States, >50K 25, Private, 176729, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 66, Private, 174276, Some-college, 10, Widowed, Sales, Unmarried, White, Female, 0, 0, 50, United-States, >50K 59, Federal-gov, 48102, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, ?, >50K 42, Self-emp-not-inc, 79531, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 24, Private, 306460, HS-grad, 9, Never-married, Farming-fishing, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 55284, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 25, United-States, <=50K 26, Private, 172063, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 24, United-States, <=50K 22, Private, 141028, HS-grad, 9, Never-married, Other-service, Own-child, Black, Male, 0, 0, 30, United-States, <=50K 33, Private, 37274, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 63, Private, 31389, 11th, 7, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 12, United-States, <=50K 20, Private, 415913, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 33, Private, 295591, 5th-6th, 3, Married-spouse-absent, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 57, ?, 202903, 7th-8th, 4, Married-civ-spouse, ?, Wife, White, Female, 1173, 0, 45, Puerto-Rico, <=50K 56, Private, 159770, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 70, Self-emp-not-inc, 268832, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 24, United-States, >50K 42, Private, 126003, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 25, Local-gov, 225193, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 28, Private, 297735, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 80, Self-emp-not-inc, 225892, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 1409, 0, 40, United-States, <=50K 36, Private, 605502, 10th, 6, Never-married, Transport-moving, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 37, Private, 174150, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 165466, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 60, United-States, >50K 52, State-gov, 189728, HS-grad, 9, Separated, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 49, Private, 360491, HS-grad, 9, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 115040, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 262688, Some-college, 10, Married-civ-spouse, Sales, Husband, Black, Male, 7688, 0, 50, United-States, >50K 70, Self-emp-inc, 158437, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, >50K 55, Private, 41108, Some-college, 10, Widowed, Farming-fishing, Not-in-family, White, Male, 0, 2258, 62, United-States, >50K 25, Private, 149875, Bachelors, 13, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 59, Private, 131916, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, Italy, >50K 22, Private, 60668, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Local-gov, 153132, Assoc-acdm, 12, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 62, Private, 155256, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 54, Private, 244770, HS-grad, 9, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 312108, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 52, Private, 102828, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 40, United-States, >50K 36, Private, 93225, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 74, Self-emp-inc, 231002, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 30, United-States, >50K 35, Self-emp-not-inc, 256992, 5th-6th, 3, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 15, Mexico, <=50K 41, Private, 118721, 12th, 8, Divorced, Adm-clerical, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 30, Private, 151989, Assoc-voc, 11, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 109112, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, <=50K 35, Private, 589809, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 13550, 0, 60, United-States, >50K 38, Private, 172538, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 34, State-gov, 318982, Masters, 14, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 1848, 40, United-States, >50K 48, Private, 204629, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 50, Self-emp-not-inc, 99894, 5th-6th, 3, Never-married, Tech-support, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 15, United-States, <=50K 19, Private, 369463, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 79324, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 61178, Bachelors, 13, Divorced, Adm-clerical, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 204226, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 17, Private, 183110, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 16, United-States, <=50K 42, Private, 96321, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 25, Private, 167031, Some-college, 10, Never-married, Other-service, Other-relative, Other, Female, 0, 0, 25, Ecuador, <=50K 36, Private, 108997, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 65, Private, 176796, Doctorate, 16, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 32, Self-emp-not-inc, 134737, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 70, United-States, >50K 33, Self-emp-inc, 49795, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 32, State-gov, 131588, Some-college, 10, Never-married, Tech-support, Unmarried, Black, Female, 0, 0, 20, United-States, <=50K 25, Private, 307643, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Local-gov, 351350, Some-college, 10, Divorced, Protective-serv, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 260761, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 72, Private, 156310, 10th, 6, Married-civ-spouse, Other-service, Husband, White, Male, 2414, 0, 12, United-States, <=50K 36, Private, 207789, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 52, United-States, <=50K 67, Self-emp-not-inc, 252842, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 1797, 0, 20, United-States, <=50K 28, Private, 294936, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 4064, 0, 45, United-States, <=50K 24, Private, 196269, 11th, 7, Married-civ-spouse, Handlers-cleaners, Husband, Other, Male, 0, 0, 40, United-States, <=50K 17, Private, 46402, 7th-8th, 4, Never-married, Sales, Own-child, White, Male, 0, 0, 8, United-States, <=50K 32, Self-emp-not-inc, 267161, Bachelors, 13, Divorced, Exec-managerial, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 67, Private, 160456, 11th, 7, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, ?, 123983, Some-college, 10, Never-married, ?, Other-relative, Asian-Pac-Islander, Male, 0, 0, 10, Vietnam, <=50K 51, Private, 123053, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 5013, 0, 40, India, <=50K 32, Private, 426467, 1st-4th, 2, Never-married, Craft-repair, Not-in-family, White, Male, 3674, 0, 40, Guatemala, <=50K 39, Private, 269323, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 18, Self-emp-not-inc, 42857, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 50, Self-emp-not-inc, 183915, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 24, Private, 211391, 10th, 6, Never-married, Sales, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 21, Local-gov, 193130, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 86745, Bachelors, 13, Never-married, Adm-clerical, Other-relative, Asian-Pac-Islander, Female, 0, 0, 16, United-States, <=50K 34, Private, 226525, Assoc-voc, 11, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 68, ?, 270339, 10th, 6, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 35, United-States, <=50K 49, Self-emp-not-inc, 343742, 10th, 6, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 32, United-States, <=50K 50, Private, 150975, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 33, Private, 207301, Assoc-acdm, 12, Divorced, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 135924, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 184277, Assoc-voc, 11, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 55, United-States, >50K 20, Private, 142233, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 46, Self-emp-inc, 120902, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 3103, 0, 37, United-States, >50K 64, Local-gov, 158412, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 126161, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 35, Private, 149347, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 21, Private, 322674, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 32, United-States, <=50K 29, Private, 55390, Assoc-acdm, 12, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 38, State-gov, 200904, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, Black, Female, 0, 0, 30, United-States, >50K 45, Private, 166056, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 30, Self-emp-not-inc, 116666, Masters, 14, Divorced, Prof-specialty, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 50, India, >50K 41, Private, 168324, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 37, Private, 121772, HS-grad, 9, Never-married, Craft-repair, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, Hong, <=50K 45, Private, 126889, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 1887, 60, United-States, >50K 20, ?, 401690, HS-grad, 9, Never-married, ?, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 45, Self-emp-inc, 117605, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 48, United-States, >50K 20, Federal-gov, 410446, HS-grad, 9, Never-married, Adm-clerical, Other-relative, White, Male, 0, 0, 20, United-States, <=50K 63, Self-emp-inc, 38472, Some-college, 10, Widowed, Sales, Not-in-family, White, Female, 14084, 0, 60, United-States, >50K 35, Self-emp-not-inc, 335704, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 70261, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 19, Private, 47577, Some-college, 10, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 23, Private, 117767, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 35, United-States, <=50K 34, Private, 179641, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 23, ?, 343553, 11th, 7, Never-married, ?, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 36, Self-emp-not-inc, 328466, 5th-6th, 3, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, Mexico, >50K 46, Private, 265097, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 5, United-States, <=50K 38, Local-gov, 414791, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 42, United-States, >50K 55, Local-gov, 48055, 12th, 8, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 341672, Some-college, 10, Never-married, Adm-clerical, Other-relative, Asian-Pac-Islander, Male, 0, 0, 40, India, <=50K 48, Private, 266764, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 35, Private, 233571, HS-grad, 9, Divorced, Other-service, Own-child, White, Female, 0, 0, 50, United-States, <=50K 53, Private, 126592, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Black, Male, 7688, 0, 40, United-States, >50K 47, Private, 70754, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 138852, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 4650, 0, 22, United-States, <=50K 32, Private, 175856, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 193494, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 46, United-States, <=50K 41, Private, 104334, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 47, Federal-gov, 197332, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 205844, Some-college, 10, Never-married, Sales, Own-child, Black, Female, 0, 0, 25, United-States, <=50K 45, Local-gov, 206459, Masters, 14, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 35, United-States, <=50K 33, Private, 202822, 7th-8th, 4, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 14, Trinadad&Tobago, <=50K 68, Without-pay, 174695, Some-college, 10, Married-spouse-absent, Farming-fishing, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 44, Private, 183342, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 49, Private, 105614, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, <=50K 45, Private, 329603, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, Poland, >50K 41, Private, 77373, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1848, 65, United-States, >50K 29, Private, 207473, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, Mexico, <=50K 46, Private, 149161, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 60, ?, <=50K 19, Private, 311974, HS-grad, 9, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 25, Mexico, <=50K 56, Private, 175127, 10th, 6, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Self-emp-not-inc, 111625, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 29, Private, 48895, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 21, Private, 27049, HS-grad, 9, Never-married, Priv-house-serv, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 38, Private, 108907, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, ?, <=50K 52, Private, 94988, 5th-6th, 3, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 22, Private, 218343, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 227626, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 60, United-States, <=50K 31, Private, 272856, HS-grad, 9, Never-married, Craft-repair, Own-child, Black, Male, 0, 0, 50, England, <=50K 39, Private, 30916, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 276229, Some-college, 10, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 289106, Assoc-acdm, 12, Separated, Sales, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 67, ?, 39100, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 5, United-States, <=50K 45, Private, 192776, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 55, United-States, >50K 61, Private, 147280, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 18, Private, 187770, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 30, United-States, <=50K 51, State-gov, 213296, Bachelors, 13, Widowed, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Self-emp-not-inc, 107410, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, ?, 170272, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 25, United-States, <=50K 32, Private, 86808, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 38, United-States, <=50K 48, Private, 149210, HS-grad, 9, Separated, Craft-repair, Unmarried, Black, Male, 0, 0, 45, United-States, <=50K 62, Private, 123411, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 53, United-States, <=50K 21, ?, 306779, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 487347, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 19, Private, 283945, 10th, 6, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 1602, 45, United-States, <=50K 20, Private, 375698, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 15, United-States, <=50K 41, Private, 271753, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 251854, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 47, Private, 264052, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 43, State-gov, 28451, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 37, United-States, >50K 20, Private, 282604, Some-college, 10, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 20, United-States, <=50K 29, Private, 185908, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 55, United-States, >50K 51, Federal-gov, 198186, Bachelors, 13, Widowed, Prof-specialty, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 40, Private, 242521, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 337940, 5th-6th, 3, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 30, Private, 212064, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 129263, HS-grad, 9, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 68, Local-gov, 144761, HS-grad, 9, Widowed, Protective-serv, Not-in-family, White, Male, 0, 1668, 20, United-States, <=50K 42, Private, 109912, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 41, Private, 113324, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 187795, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 20, Private, 173724, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, United-States, <=50K 43, Private, 185129, Bachelors, 13, Divorced, Tech-support, Own-child, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 73134, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 60, United-States, >50K 45, Private, 236040, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 74194, HS-grad, 9, Never-married, Farming-fishing, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 31, Local-gov, 102130, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, <=50K 23, Private, 140915, Some-college, 10, Never-married, Sales, Other-relative, Asian-Pac-Islander, Male, 0, 0, 25, Philippines, <=50K 69, ?, 107575, HS-grad, 9, Divorced, ?, Not-in-family, White, Female, 2964, 0, 35, United-States, <=50K 38, State-gov, 34364, Masters, 14, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 37, Self-emp-not-inc, 258037, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, Cuba, >50K 18, Private, 391585, HS-grad, 9, Never-married, Machine-op-inspct, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 41, Self-emp-not-inc, 233130, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, Mexico, <=50K 30, Private, 101345, Bachelors, 13, Married-civ-spouse, Sales, Wife, White, Female, 3103, 0, 55, United-States, >50K 23, ?, 32897, Assoc-acdm, 12, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 20, United-States, <=50K 26, Private, 248612, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 30, United-States, <=50K 37, Private, 212465, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 198587, Some-college, 10, Never-married, Tech-support, Not-in-family, Black, Female, 2174, 0, 50, United-States, <=50K 33, Private, 405913, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, Peru, >50K 37, Private, 588003, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 40, United-States, >50K 31, Private, 46807, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 210498, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 80, United-States, <=50K 35, Private, 206951, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Self-emp-not-inc, 237466, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 30, United-States, >50K 59, Private, 279636, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 50, Guatemala, <=50K 42, Private, 29320, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 271262, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 27, ?, 29361, Assoc-acdm, 12, Never-married, ?, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 32, Private, 76773, Some-college, 10, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 109004, HS-grad, 9, Separated, Craft-repair, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 43, Private, 226902, Bachelors, 13, Divorced, Machine-op-inspct, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 176552, 11th, 7, Divorced, Prof-specialty, Unmarried, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, >50K 41, Private, 182303, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 59, Local-gov, 296253, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 8614, 0, 60, United-States, >50K 20, Private, 218215, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 30, United-States, <=50K 57, Private, 165695, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, ?, >50K 46, Self-emp-not-inc, 51271, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 4386, 0, 70, United-States, <=50K 45, Private, 96100, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 29, Local-gov, 82393, HS-grad, 9, Never-married, Handlers-cleaners, Unmarried, Asian-Pac-Islander, Male, 0, 1590, 45, United-States, <=50K 23, Private, 248978, 11th, 7, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Mexico, <=50K 46, Private, 254367, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 1590, 48, United-States, <=50K 55, ?, 200235, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 50, United-States, >50K 58, Private, 94429, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 87282, Assoc-voc, 11, Never-married, Exec-managerial, Other-relative, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 29, Private, 119793, Some-college, 10, Never-married, Sales, Other-relative, White, Male, 0, 0, 50, United-States, <=50K 57, ?, 85815, HS-grad, 9, Divorced, ?, Own-child, Asian-Pac-Islander, Male, 0, 0, 20, United-States, <=50K 26, Local-gov, 197764, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 306982, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, >50K 61, Private, 80896, HS-grad, 9, Separated, Transport-moving, Unmarried, Asian-Pac-Islander, Male, 0, 0, 45, United-States, >50K 31, Private, 197886, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 45, United-States, >50K 43, Private, 355728, HS-grad, 9, Divorced, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 121124, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 15024, 0, 50, United-States, >50K 51, State-gov, 193720, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 56, United-States, >50K 23, Private, 347292, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 34506, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 326370, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 38, ?, <=50K 22, ?, 269221, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 63509, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 48, Private, 148254, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Wife, White, Female, 0, 0, 16, United-States, >50K 33, Private, 190511, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 46, Private, 268022, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, ?, >50K 18, Private, 20057, 7th-8th, 4, Never-married, Other-service, Other-relative, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 52, Private, 206862, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 189498, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1848, 45, United-States, >50K 28, Private, 166320, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 289886, Some-college, 10, Never-married, Other-service, Other-relative, Asian-Pac-Islander, Male, 0, 0, 30, Vietnam, <=50K 23, ?, 86337, Some-college, 10, Never-married, ?, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 45, Local-gov, 54190, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 17, Private, 147069, 10th, 6, Never-married, Sales, Own-child, White, Female, 0, 0, 16, United-States, <=50K 56, Private, 282023, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Self-emp-inc, 379485, Assoc-acdm, 12, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 45, United-States, <=50K 81, Private, 129338, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 10, United-States, <=50K 22, Private, 99829, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 30, United-States, <=50K 43, State-gov, 182254, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 109428, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 1740, 40, United-States, <=50K 42, Self-emp-not-inc, 351161, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1887, 40, United-States, >50K 66, ?, 210750, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 50, United-States, <=50K 50, Private, 132716, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 242984, Some-college, 10, Separated, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 101509, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, ?, 509629, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 35, United-States, <=50K 36, Private, 119957, Bachelors, 13, Separated, Other-service, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 33, Private, 69727, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, Mexico, <=50K 36, Private, 204590, Bachelors, 13, Divorced, Prof-specialty, Unmarried, Black, Female, 0, 213, 40, United-States, <=50K 37, ?, 50862, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 55, United-States, <=50K 50, Private, 182907, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 25, United-States, <=50K 55, Private, 206487, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Private, 168015, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 149396, Some-college, 10, Never-married, Other-service, Other-relative, Black, Female, 0, 0, 30, Haiti, <=50K 39, Federal-gov, 184964, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 34, Private, 398988, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 128777, 7th-8th, 4, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 55, United-States, <=50K 60, Private, 252413, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Other, Male, 0, 0, 32, United-States, >50K 33, Private, 181372, Masters, 14, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 50, United-States, >50K 58, Private, 216851, 9th, 5, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, El-Salvador, <=50K 27, Private, 106935, Some-college, 10, Separated, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 46, State-gov, 363875, Some-college, 10, Divorced, Protective-serv, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 63, Private, 287277, HS-grad, 9, Divorced, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, Self-emp-not-inc, 172342, Some-college, 10, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 308498, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 15, United-States, <=50K 29, Private, 122127, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 8614, 0, 40, United-States, >50K 31, Private, 106437, Prof-school, 15, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 60, United-States, >50K 49, Self-emp-inc, 306289, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 45, Self-emp-inc, 201699, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 42, Private, 282062, 9th, 5, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 235108, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 339482, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 181820, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 49, Self-emp-not-inc, 99335, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 40, Private, 367533, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 2580, 0, 40, United-States, <=50K 57, Private, 64960, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 45, United-States, <=50K 50, Private, 269095, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 58683, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 55, United-States, >50K 35, Self-emp-not-inc, 89508, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 3908, 0, 60, United-States, <=50K 19, Private, 100999, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 18, Private, 34125, 10th, 6, Never-married, Other-service, Own-child, White, Female, 0, 0, 28, United-States, <=50K 20, Private, 115057, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 139126, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 104632, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Cambodia, >50K 40, Federal-gov, 178866, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 20, United-States, >50K 54, Private, 139850, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 45, United-States, >50K 28, Private, 61435, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 38, Private, 309230, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 45613, Some-college, 10, Never-married, Priv-house-serv, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 272615, 11th, 7, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 54318, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 27, Private, 165519, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 48495, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 42, United-States, >50K 38, Private, 143123, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 67, Self-emp-not-inc, 431426, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Wife, White, Female, 20051, 0, 4, United-States, >50K 75, Private, 256474, Masters, 14, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 16, United-States, <=50K 41, Private, 191451, Masters, 14, Divorced, Exec-managerial, Unmarried, Black, Female, 0, 0, 60, United-States, >50K 37, Private, 99146, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 47, Private, 235986, HS-grad, 9, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 50, Cuba, <=50K 34, Local-gov, 429897, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, Mexico, >50K 25, Private, 189897, HS-grad, 9, Married-civ-spouse, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 145155, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, State-gov, 192257, HS-grad, 9, Never-married, Protective-serv, Own-child, White, Male, 2174, 0, 40, United-States, <=50K 35, Private, 194960, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, Other, Male, 0, 0, 40, Puerto-Rico, <=50K 44, Local-gov, 357814, 12th, 8, Married-civ-spouse, Other-service, Other-relative, White, Female, 0, 0, 35, Mexico, <=50K 27, Local-gov, 137629, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 80, United-States, >50K 42, Private, 156526, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 33, United-States, <=50K 26, Private, 189238, 9th, 5, Never-married, Other-service, Own-child, White, Female, 0, 0, 38, El-Salvador, <=50K 23, Private, 202989, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, Canada, <=50K 28, Private, 25684, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 38, Self-emp-not-inc, 192939, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 28, Private, 138692, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 50, United-States, <=50K 29, Private, 222249, HS-grad, 9, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 56, Self-emp-not-inc, 201318, 9th, 5, Married-civ-spouse, Exec-managerial, Other-relative, White, Male, 3411, 0, 50, Columbia, <=50K 23, ?, 190650, Bachelors, 13, Never-married, ?, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 35, United-States, <=50K 30, Private, 56004, Some-college, 10, Never-married, Exec-managerial, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 48, Private, 182313, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Self-emp-not-inc, 138962, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 72, ?, <=50K 38, Private, 277248, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, Cuba, >50K 24, Private, 125031, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 47, State-gov, 216414, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 22, Private, 171176, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 48, ?, <=50K 29, Private, 356133, Some-college, 10, Never-married, Prof-specialty, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 185397, Assoc-acdm, 12, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 308285, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 56651, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Local-gov, 154863, 9th, 5, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, Trinadad&Tobago, >50K 46, Federal-gov, 44706, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 50, United-States, >50K 34, ?, 222548, Some-college, 10, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 4, United-States, <=50K 32, Private, 248754, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 104981, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 315065, Some-college, 10, Never-married, Other-service, Unmarried, White, Male, 0, 0, 35, Mexico, <=50K 46, Private, 188325, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 221661, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 35, United-States, <=50K 59, Private, 81973, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, >50K 31, Private, 169122, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 48, Private, 216734, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 98101, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 292511, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 25, United-States, <=50K 20, Private, 122971, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 35, United-States, <=50K 29, Private, 124953, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 50, United-States, <=50K 54, Private, 123011, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 76417, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 52, United-States, <=50K 43, Private, 351576, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 46, Federal-gov, 33794, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 3103, 0, 40, United-States, >50K 33, Private, 79923, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 33, Private, 117983, 10th, 6, Divorced, Other-service, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 36, Private, 186110, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 187589, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 5178, 0, 40, United-States, >50K 37, ?, 319685, Assoc-voc, 11, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 54, United-States, >50K 64, ?, 64101, 12th, 8, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 24, United-States, <=50K 45, Self-emp-not-inc, 162923, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 25, Private, 288519, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 33798, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 195734, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 2354, 0, 40, United-States, <=50K 23, Private, 214120, HS-grad, 9, Never-married, Priv-house-serv, Own-child, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 113515, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 58, Self-emp-not-inc, 261230, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 98515, Assoc-voc, 11, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 187715, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 23, ?, 214238, 7th-8th, 4, Never-married, ?, Not-in-family, White, Female, 0, 0, 40, Mexico, <=50K 32, Private, 123964, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 4386, 0, 50, United-States, <=50K 26, Private, 68991, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 52, Private, 292110, 5th-6th, 3, Never-married, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 198320, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 33, Private, 709798, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 60, Private, 372838, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 160402, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 45, Private, 98475, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 37, Local-gov, 97136, Some-college, 10, Married-spouse-absent, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 29, Private, 136985, Assoc-acdm, 12, Never-married, Tech-support, Own-child, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 187356, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 66, United-States, <=50K 46, State-gov, 107231, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1740, 40, United-States, <=50K 20, Private, 305874, Some-college, 10, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 290922, Masters, 14, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 48, Private, 248254, Some-college, 10, Married-civ-spouse, Prof-specialty, Wife, White, Female, 7298, 0, 40, United-States, >50K 38, Private, 160808, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 4386, 0, 48, United-States, <=50K 36, Private, 247321, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 53, Private, 247651, 7th-8th, 4, Divorced, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 56, United-States, <=50K 29, Private, 214702, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 1974, 35, United-States, <=50K 64, Private, 75577, 7th-8th, 4, Married-civ-spouse, Adm-clerical, Husband, White, Male, 2580, 0, 50, United-States, <=50K 34, Private, 561334, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 36, ?, 224886, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Local-gov, 401134, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 258170, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 68, ?, 141181, 9th, 5, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 2, United-States, <=50K 37, Private, 292370, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Other, Male, 0, 0, 50, ?, >50K 22, Private, 300871, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 136721, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, ?, 140399, Some-college, 10, Never-married, ?, Other-relative, White, Female, 0, 0, 30, United-States, <=50K 36, Private, 109133, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 186534, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, >50K 25, Private, 226891, Assoc-voc, 11, Never-married, Other-service, Other-relative, Asian-Pac-Islander, Female, 0, 0, 40, ?, <=50K 33, Private, 241885, Some-college, 10, Separated, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 97165, Some-college, 10, Never-married, Machine-op-inspct, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 212918, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 24, Private, 211585, HS-grad, 9, Married-civ-spouse, Transport-moving, Own-child, White, Female, 0, 0, 40, United-States, <=50K 47, Local-gov, 178309, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 48, Self-emp-inc, 481987, 10th, 6, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 215211, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 33, Local-gov, 194901, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 44, Private, 340885, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 1977, 40, United-States, >50K 33, Local-gov, 190290, Assoc-voc, 11, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 56, United-States, <=50K 26, Private, 188569, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 22, Private, 162282, Assoc-voc, 11, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 287315, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 31, Self-emp-inc, 304212, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 45, United-States, <=50K 73, ?, 200878, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 38, Local-gov, 256864, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Self-emp-not-inc, 46401, Some-college, 10, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 36, Private, 37778, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 191722, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 7688, 0, 54, United-States, >50K 64, Self-emp-not-inc, 103643, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 15, United-States, >50K 24, Private, 143766, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 55, United-States, <=50K 21, State-gov, 204425, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 20, United-States, <=50K 28, Private, 156257, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, >50K 18, ?, 113185, 11th, 7, Never-married, ?, Own-child, White, Male, 0, 0, 25, United-States, <=50K 41, Self-emp-inc, 112262, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 17, Private, 28031, 9th, 5, Never-married, Other-service, Own-child, White, Male, 0, 0, 16, United-States, <=50K 58, Private, 320102, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 50, Self-emp-not-inc, 334273, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 8, United-States, <=50K 30, Private, 356015, 11th, 7, Married-spouse-absent, Handlers-cleaners, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 40, Mexico, <=50K 47, Private, 278900, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 142528, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 20, United-States, <=50K 50, Federal-gov, 343014, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, United-States, <=50K 29, Private, 201017, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 55, Scotland, <=50K 31, Self-emp-not-inc, 81030, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Self-emp-not-inc, 34007, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 70, United-States, >50K 31, Private, 29662, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 53, Private, 347446, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 33, Private, 90668, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 190403, Bachelors, 13, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, Private, 109015, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 7688, 0, 50, United-States, >50K 38, Private, 234807, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 50, United-States, >50K 18, Private, 157131, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 30, United-States, <=50K 50, Private, 94081, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 78, Private, 135566, HS-grad, 9, Widowed, Sales, Unmarried, White, Female, 2329, 0, 12, United-States, <=50K 27, Private, 103164, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 570002, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 25, United-States, <=50K 24, State-gov, 215797, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 289405, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 1602, 15, United-States, <=50K 25, Private, 239461, Masters, 14, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 35, United-States, <=50K 34, Private, 101510, Bachelors, 13, Divorced, Sales, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 30, Self-emp-inc, 443546, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 35, United-States, <=50K 37, Federal-gov, 141029, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 207202, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, >50K 67, Without-pay, 137192, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 0, 12, Philippines, <=50K 35, Private, 222989, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 30, United-States, <=50K 75, Self-emp-not-inc, 36325, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 30, United-States, <=50K 47, Private, 73394, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 50, United-States, <=50K 23, Private, 249046, 10th, 6, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Federal-gov, 100653, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 8, United-States, <=50K 42, Local-gov, 1125613, HS-grad, 9, Divorced, Other-service, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 32, Private, 101352, Some-college, 10, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 32, United-States, >50K 54, Private, 340476, HS-grad, 9, Separated, Sales, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 20, Private, 192711, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 273362, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Private, 100451, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 7688, 0, 38, United-States, >50K 35, Private, 85399, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, Local-gov, 168191, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, >50K 27, Private, 153475, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 61, Self-emp-not-inc, 196773, 7th-8th, 4, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 30, United-States, >50K 41, Private, 180138, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 22, Private, 48347, Some-college, 10, Never-married, Tech-support, Own-child, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 175071, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Black, Male, 15024, 0, 40, United-States, >50K 66, ?, 129476, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 6, United-States, <=50K 25, Private, 181772, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 284317, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 35, United-States, <=50K 20, Private, 237305, Some-college, 10, Never-married, Machine-op-inspct, Other-relative, Black, Female, 0, 0, 35, United-States, <=50K 67, Self-emp-inc, 111321, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 16, United-States, <=50K 44, Private, 278476, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 42, Private, 39060, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 29, Local-gov, 205262, Some-college, 10, Never-married, Adm-clerical, Not-in-family, Other, Male, 0, 0, 40, Ecuador, <=50K 48, Private, 198000, Some-college, 10, Never-married, Craft-repair, Unmarried, White, Female, 0, 0, 38, United-States, >50K 25, Private, 397962, HS-grad, 9, Never-married, Adm-clerical, Other-relative, Black, Female, 0, 0, 40, United-States, <=50K 31, Private, 178370, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 99, United-States, >50K 48, Private, 121253, Bachelors, 13, Married-spouse-absent, Sales, Unmarried, White, Female, 0, 2472, 70, United-States, >50K 40, Private, 56072, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 26, Private, 176756, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 60374, HS-grad, 9, Married-civ-spouse, Other-service, Own-child, White, Female, 0, 0, 35, United-States, <=50K 52, Private, 165681, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Self-emp-not-inc, 287037, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Self-emp-not-inc, 55568, Bachelors, 13, Married-civ-spouse, Farming-fishing, Wife, White, Female, 0, 0, 50, United-States, <=50K 48, Private, 155509, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 16, Trinadad&Tobago, <=50K 19, Private, 201178, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 27, Private, 37250, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 1651, 40, United-States, <=50K 59, Private, 314149, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 1740, 50, United-States, <=50K 19, Private, 264593, Some-college, 10, Never-married, Sales, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 159589, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 50, United-States, <=50K 39, Private, 454915, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 285131, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 150057, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 55390, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 45, United-States, <=50K 23, Private, 314894, HS-grad, 9, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 45, United-States, <=50K 59, ?, 184948, Assoc-voc, 11, Divorced, ?, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 25, Local-gov, 124483, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 20, India, <=50K 37, Self-emp-inc, 97986, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 68, United-States, <=50K 31, Private, 210562, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 65, United-States, <=50K 24, Private, 233280, Assoc-acdm, 12, Never-married, Sales, Own-child, White, Female, 0, 0, 37, United-States, <=50K 53, Local-gov, 164300, Bachelors, 13, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 38, Dominican-Republic, <=50K 26, Private, 227489, Some-college, 10, Never-married, Handlers-cleaners, Other-relative, Black, Male, 0, 0, 40, ?, <=50K 25, Private, 263773, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 59, Private, 96459, 11th, 7, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Federal-gov, 116608, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 180007, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 305466, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 238917, HS-grad, 9, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 40, El-Salvador, <=50K 25, Private, 129784, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 367390, Some-college, 10, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 20, Private, 235691, HS-grad, 9, Never-married, Sales, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 63, ?, 166425, Some-college, 10, Widowed, ?, Not-in-family, Black, Female, 0, 0, 24, United-States, <=50K 43, Self-emp-not-inc, 160369, 10th, 6, Divorced, Farming-fishing, Unmarried, White, Male, 0, 0, 25, United-States, <=50K 39, Private, 206298, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 183523, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 17, Private, 217342, 10th, 6, Never-married, Sales, Own-child, White, Female, 0, 0, 5, United-States, <=50K 40, State-gov, 141858, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 72, United-States, <=50K 50, Private, 213296, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, >50K 23, Self-emp-inc, 201682, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 35, United-States, <=50K 60, Private, 178312, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 7298, 0, 65, United-States, >50K 30, Private, 269723, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 200593, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 50, United-States, <=50K 23, Private, 32616, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 24, Private, 259510, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 5013, 0, 30, United-States, <=50K 45, Self-emp-not-inc, 271828, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 20, United-States, <=50K 58, Self-emp-inc, 78104, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 60, United-States, >50K 22, Private, 113703, Some-college, 10, Never-married, Sales, Other-relative, White, Male, 0, 0, 20, United-States, <=50K 41, Private, 187802, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 440706, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 191834, HS-grad, 9, Divorced, Machine-op-inspct, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 149184, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 50, United-States, >50K 49, Self-emp-inc, 315998, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 30, Private, 159589, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 50, United-States, >50K 38, Private, 60313, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 58, Local-gov, 32855, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 48, United-States, <=50K 58, Private, 142326, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 61, Self-emp-not-inc, 201965, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, Private, 172333, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 40, United-States, >50K 32, Private, 206541, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 45, United-States, >50K 33, Self-emp-not-inc, 177828, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 28, Private, 303440, Bachelors, 13, Separated, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 22, Private, 89991, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 11, United-States, <=50K 35, Private, 186009, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 59, Private, 170988, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, <=50K 45, Self-emp-inc, 180239, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 7688, 0, 40, ?, >50K 50, Self-emp-not-inc, 213654, HS-grad, 9, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 40, United-States, <=50K 56, Self-emp-inc, 32316, 12th, 8, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, Self-emp-not-inc, 150371, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 18, ?, 387871, 10th, 6, Never-married, ?, Own-child, White, Male, 0, 0, 30, United-States, <=50K 28, Private, 314649, Some-college, 10, Married-civ-spouse, Sales, Husband, Amer-Indian-Eskimo, Male, 0, 0, 60, United-States, <=50K 42, Private, 240255, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 40, United-States, >50K 60, Private, 206339, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Self-emp-inc, 230168, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 91, United-States, <=50K 42, Private, 171424, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 7298, 0, 45, United-States, >50K 36, Private, 148581, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, >50K 52, Local-gov, 89705, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Self-emp-not-inc, 248406, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Local-gov, 72594, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 55, United-States, >50K 31, Local-gov, 137537, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 225065, 5th-6th, 3, Separated, Sales, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 35, Private, 217274, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, <=50K 19, Private, 69151, 9th, 5, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 25, United-States, <=50K 59, Self-emp-not-inc, 81107, Some-college, 10, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 80, United-States, >50K 38, Private, 205852, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 201117, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 35, Private, 397307, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 39, Private, 115422, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 30, United-States, <=50K 64, Private, 114994, Some-college, 10, Separated, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 17, Local-gov, 39815, 10th, 6, Never-married, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 49, Private, 151584, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 32, United-States, <=50K 19, Private, 164938, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 36, Self-emp-not-inc, 179896, HS-grad, 9, Married-civ-spouse, Prof-specialty, Wife, White, Female, 3137, 0, 40, United-States, <=50K 26, Private, 253841, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 27, Private, 177955, 5th-6th, 3, Never-married, Priv-house-serv, Other-relative, White, Female, 2176, 0, 40, El-Salvador, <=50K 66, Private, 113323, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 20051, 0, 40, United-States, >50K 38, Private, 320305, 7th-8th, 4, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 229287, Bachelors, 13, Never-married, Exec-managerial, Other-relative, White, Female, 0, 0, 25, United-States, <=50K 19, Private, 100790, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 331419, Assoc-acdm, 12, Never-married, Craft-repair, Not-in-family, White, Male, 4787, 0, 50, United-States, >50K 22, Private, 171419, Assoc-voc, 11, Never-married, Exec-managerial, Unmarried, Asian-Pac-Islander, Male, 0, 0, 40, South, <=50K 60, Private, 202226, Some-college, 10, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 44, United-States, >50K 54, Private, 308087, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 1977, 18, United-States, >50K 46, Private, 220124, HS-grad, 9, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 37, United-States, <=50K 33, State-gov, 31703, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 51, Local-gov, 153908, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 180599, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 60, United-States, >50K 18, ?, 252046, HS-grad, 9, Never-married, ?, Own-child, White, Female, 0, 0, 30, United-States, <=50K 60, Self-emp-inc, 160062, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 25, United-States, <=50K 39, Self-emp-not-inc, 148443, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 23, Private, 91733, Bachelors, 13, Never-married, Tech-support, Own-child, White, Female, 3325, 0, 40, United-States, <=50K 39, Private, 176634, Assoc-acdm, 12, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 40, Local-gov, 74949, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 165484, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 65, United-States, >50K 24, Private, 44738, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 130040, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Self-emp-not-inc, 234537, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 39, Private, 179016, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 27, Private, 335421, Masters, 14, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 45, State-gov, 312678, Masters, 14, Never-married, Adm-clerical, Not-in-family, Black, Male, 0, 0, 38, United-States, <=50K 22, ?, 313786, HS-grad, 9, Divorced, ?, Other-relative, Black, Female, 0, 0, 40, United-States, <=50K 31, Private, 198751, Bachelors, 13, Never-married, Craft-repair, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, Vietnam, <=50K 63, Private, 131519, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 285060, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 28, State-gov, 189765, Some-college, 10, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 23, Private, 130905, Bachelors, 13, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 50, Private, 146325, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 44, United-States, >50K 33, Private, 102821, 12th, 8, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, ?, 137876, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 388998, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 13550, 0, 46, United-States, >50K 29, Private, 82910, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 309122, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 60, Private, 532845, 1st-4th, 2, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Mexico, >50K 46, Private, 195833, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, ?, <=50K 67, ?, 98882, Masters, 14, Widowed, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 20, ?, 133515, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 15, France, <=50K 23, Private, 55215, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 0, 55, United-States, <=50K 38, Self-emp-inc, 176357, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 60, Private, 185836, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Self-emp-not-inc, 54152, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 37, Private, 212437, Some-college, 10, Widowed, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 48, United-States, <=50K 37, Private, 224566, HS-grad, 9, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 58, Private, 200040, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 41526, Bachelors, 13, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 30, Canada, <=50K 27, Private, 89598, Some-college, 10, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 60, United-States, <=50K 33, Private, 323811, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 55, United-States, <=50K 43, State-gov, 30824, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, Federal-gov, 181096, Some-college, 10, Never-married, Tech-support, Own-child, Black, Male, 0, 0, 20, United-States, <=50K 45, Private, 217953, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Other, Male, 0, 0, 40, Mexico, <=50K 44, Private, 222635, 5th-6th, 3, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 52, ?, 121942, 7th-8th, 4, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 346871, HS-grad, 9, Divorced, Prof-specialty, Not-in-family, White, Male, 4787, 0, 46, United-States, >50K 31, Private, 184889, HS-grad, 9, Never-married, Other-service, Own-child, Black, Female, 0, 0, 20, United-States, <=50K 18, Federal-gov, 101709, 11th, 7, Never-married, Other-service, Own-child, Asian-Pac-Islander, Male, 0, 0, 15, Philippines, <=50K 20, Private, 125010, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 32, Private, 53135, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 498328, 10th, 6, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 46, Private, 604380, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 40, United-States, <=50K 28, Private, 174327, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, <=50K 27, Self-emp-not-inc, 357283, HS-grad, 9, Never-married, Sales, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 18, Federal-gov, 280728, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 32, United-States, <=50K 69, Self-emp-not-inc, 185039, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 9386, 0, 12, United-States, >50K 50, Self-emp-inc, 251240, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 43, Private, 143046, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, Greece, <=50K 32, Private, 210541, Bachelors, 13, Divorced, Sales, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 43, Private, 172364, HS-grad, 9, Separated, Exec-managerial, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 52, Self-emp-not-inc, 138611, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 55, United-States, >50K 50, Private, 176227, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, ?, >50K 35, Private, 139647, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 20, ?, 174461, HS-grad, 9, Never-married, ?, Own-child, White, Female, 0, 0, 5, United-States, <=50K 73, ?, 123345, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 65, United-States, <=50K 46, Private, 164427, HS-grad, 9, Divorced, Adm-clerical, Own-child, White, Female, 0, 0, 45, United-States, <=50K 58, Private, 205235, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, >50K 46, Self-emp-inc, 192779, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 60, United-States, >50K 40, Private, 163434, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 25, Private, 264055, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 336215, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 33, Federal-gov, 78307, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Federal-gov, 233059, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 62, Private, 91433, 10th, 6, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 56, Local-gov, 157525, Some-college, 10, Divorced, Protective-serv, Not-in-family, Black, Male, 0, 0, 48, United-States, <=50K 24, Private, 86065, HS-grad, 9, Never-married, Transport-moving, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 42, Private, 22831, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 180181, Masters, 14, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 212617, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 66, Ecuador, <=50K 22, ?, 125905, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 336793, Bachelors, 13, Never-married, Adm-clerical, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 314649, HS-grad, 9, Married-spouse-absent, Handlers-cleaners, Other-relative, Asian-Pac-Islander, Male, 0, 0, 40, ?, <=50K 22, Private, 283969, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, Mexico, <=50K 32, Self-emp-not-inc, 35595, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 25, Private, 410240, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 66, Private, 178120, 5th-6th, 3, Divorced, Priv-house-serv, Not-in-family, Black, Female, 0, 0, 15, United-States, <=50K 26, State-gov, 294400, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 38, United-States, <=50K 46, Private, 65353, Some-college, 10, Divorced, Transport-moving, Own-child, White, Male, 3325, 0, 55, United-States, <=50K 55, Private, 189719, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 24, Private, 23438, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 178037, HS-grad, 9, Never-married, Sales, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 109815, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 197860, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 271933, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 54, Private, 141663, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 15, United-States, <=50K 19, ?, 199609, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 56, Private, 92215, 9th, 5, Divorced, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 47, Private, 93449, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 60, Japan, <=50K 29, Private, 235393, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 53, Private, 151864, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 189277, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 50, ?, 204577, Bachelors, 13, Married-civ-spouse, ?, Husband, Black, Male, 0, 1902, 60, United-States, >50K 42, Private, 344572, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 21, Private, 265356, Some-college, 10, Never-married, Sales, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 36, Self-emp-inc, 166880, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 70, United-States, <=50K 60, Private, 188650, 5th-6th, 3, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, ?, >50K 69, Private, 213249, Assoc-voc, 11, Widowed, Sales, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 31, Private, 112627, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 48, Private, 125120, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 55, United-States, <=50K 23, Private, 60409, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 243190, Assoc-acdm, 12, Separated, Craft-repair, Unmarried, Asian-Pac-Islander, Male, 8614, 0, 40, United-States, >50K 47, Private, 583755, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, >50K 36, Private, 68089, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 39, Private, 306646, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 22, Private, 186573, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Female, 0, 0, 46, United-States, <=50K 27, Private, 279580, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 10520, 0, 45, United-States, >50K 36, Private, 437909, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 420691, 1st-4th, 2, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Mexico, <=50K 33, Federal-gov, 94193, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 154076, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 50, United-States, >50K 52, Private, 145879, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 65, United-States, <=50K 23, Private, 208946, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 0, 32, United-States, <=50K 33, Private, 231826, 1st-4th, 2, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Mexico, <=50K 30, Private, 178587, Assoc-voc, 11, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 35, Private, 213208, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, Black, Male, 0, 0, 38, Jamaica, <=50K 35, ?, 139770, Assoc-voc, 11, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 20, United-States, >50K 27, Private, 153869, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 37, United-States, <=50K 24, Private, 88676, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 35, United-States, <=50K 44, Local-gov, 151089, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 62, Private, 138621, Assoc-voc, 11, Separated, Priv-house-serv, Not-in-family, Black, Female, 0, 0, 20, United-States, <=50K 45, Private, 30457, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 40, United-States, >50K 75, Self-emp-not-inc, 213349, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 20, United-States, <=50K 47, Private, 192776, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 64, Private, 192884, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 54, Private, 103024, HS-grad, 9, Divorced, Tech-support, Not-in-family, White, Male, 0, 0, 42, United-States, >50K 41, Federal-gov, 510072, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Private, 178615, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 249956, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 10, United-States, <=50K 51, Private, 177705, Bachelors, 13, Divorced, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 45, Self-emp-inc, 121124, Prof-school, 15, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 18, ?, 25837, 11th, 7, Never-married, ?, Own-child, White, Male, 0, 0, 72, United-States, <=50K 43, Private, 557349, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, Yugoslavia, <=50K 30, Private, 89735, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 1504, 40, United-States, <=50K 32, Private, 222548, HS-grad, 9, Divorced, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 47314, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1902, 40, ?, >50K 61, Private, 316359, Some-college, 10, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 200089, 1st-4th, 2, Married-civ-spouse, Other-service, Other-relative, White, Male, 0, 0, 40, England, <=50K 56, Private, 271795, 11th, 7, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 49, United-States, <=50K 28, Private, 31801, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 60, United-States, <=50K 23, Private, 196508, Some-college, 10, Never-married, Handlers-cleaners, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 55, Private, 189933, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 84, United-States, <=50K 27, ?, 501172, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 419, 20, Mexico, <=50K 33, Private, 361497, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 70, United-States, <=50K 22, Private, 150175, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 43, Local-gov, 155106, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Self-emp-not-inc, 62272, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 189916, Some-college, 10, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 324011, 9th, 5, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 20, United-States, <=50K 35, Private, 105803, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 67, ?, 53588, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 107998, HS-grad, 9, Divorced, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 340567, 1st-4th, 2, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 55, Mexico, <=50K 39, Private, 167777, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 29, Private, 228860, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1887, 50, United-States, >50K 45, Self-emp-inc, 40666, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 44, Private, 277488, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 3103, 0, 40, United-States, >50K 42, Local-gov, 195897, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 242984, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 52, Local-gov, 236497, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, ?, 312634, 11th, 7, Never-married, ?, Own-child, White, Male, 0, 0, 25, United-States, <=50K 64, Private, 59829, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 25, France, <=50K 30, Private, 24292, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 43, Local-gov, 180407, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 42, Germany, <=50K 49, Self-emp-not-inc, 121238, Some-college, 10, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 281982, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Self-emp-not-inc, 348739, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 49, Private, 194189, 7th-8th, 4, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 329130, 11th, 7, Separated, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 205939, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 2202, 0, 4, United-States, <=50K 31, Private, 62165, HS-grad, 9, Never-married, Other-service, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 26, Private, 224361, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 34722, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, <=50K 38, Private, 175972, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, <=50K 33, Self-emp-not-inc, 359428, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 24, ?, 138504, HS-grad, 9, Separated, ?, Unmarried, Black, Female, 0, 0, 37, United-States, <=50K 18, Private, 268952, 12th, 8, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 32, Private, 257978, Assoc-voc, 11, Widowed, Tech-support, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 27, Private, 118799, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, State-gov, 78356, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, Jamaica, <=50K 30, Self-emp-not-inc, 609789, Assoc-voc, 11, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 123157, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 38, United-States, <=50K 74, Private, 84197, Masters, 14, Divorced, Sales, Not-in-family, White, Female, 0, 0, 10, United-States, <=50K 36, Private, 162312, HS-grad, 9, Never-married, Craft-repair, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 70, South, <=50K 36, Private, 138441, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 55, United-States, <=50K 29, Private, 239753, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 2057, 20, United-States, <=50K 39, Private, 262158, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 25, Self-emp-inc, 133373, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 80, United-States, <=50K 21, Private, 57916, HS-grad, 9, Separated, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 39, State-gov, 142897, Assoc-voc, 11, Never-married, Exec-managerial, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 38, Private, 161016, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 20, Private, 227491, HS-grad, 9, Never-married, Sales, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 25, United-States, <=50K 51, Private, 306790, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 33831, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 188972, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 50, Private, 313546, HS-grad, 9, Separated, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 38, Private, 220585, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 25, Local-gov, 476599, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 163665, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 15, United-States, <=50K 36, Private, 306646, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 41, Private, 206470, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, Germany, <=50K 34, Private, 169583, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 19, State-gov, 127085, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 10, United-States, <=50K 18, Private, 152044, 10th, 6, Never-married, Other-service, Own-child, White, Female, 0, 0, 3, United-States, <=50K 36, Private, 111387, 10th, 6, Divorced, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 102318, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1887, 40, United-States, >50K 29, Private, 213692, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 45, United-States, <=50K 23, Private, 163665, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 35, Private, 30529, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 290226, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 182136, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 73266, Some-college, 10, Never-married, Transport-moving, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 19, State-gov, 60412, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 15, United-States, <=50K 70, Private, 187891, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 194304, Some-college, 10, Divorced, Transport-moving, Not-in-family, Black, Male, 0, 0, 55, United-States, <=50K 35, Private, 160910, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 25, Private, 148300, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 35, United-States, <=50K 39, Private, 165743, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 50, Private, 123174, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 37, ?, >50K 43, Private, 184018, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 37, Federal-gov, 188069, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, Philippines, >50K 51, Private, 138852, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 7298, 0, 40, El-Salvador, >50K 29, ?, 78529, 10th, 6, Separated, ?, Unmarried, White, Female, 0, 0, 12, United-States, <=50K 20, Private, 164441, HS-grad, 9, Never-married, Other-service, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 21, Private, 199419, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 181342, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Wife, Black, Female, 0, 0, 40, United-States, <=50K 44, Private, 173382, Assoc-acdm, 12, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 17, Private, 184924, 9th, 5, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 1719, 15, United-States, <=50K 25, Private, 215384, 11th, 7, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 43, State-gov, 424094, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 46, Federal-gov, 212120, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Private, 185764, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 60, United-States, <=50K 46, Local-gov, 133969, Masters, 14, Divorced, Prof-specialty, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 22, Private, 32616, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 49, Private, 149210, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 21, Private, 161210, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, <=50K 53, Private, 285621, Masters, 14, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 43, Private, 282069, Some-college, 10, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 42, United-States, <=50K 22, Private, 97508, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 50, United-States, <=50K 33, Private, 356823, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 10520, 0, 45, United-States, >50K 28, Private, 171133, Assoc-voc, 11, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 231638, Some-college, 10, Never-married, Tech-support, Unmarried, White, Female, 0, 0, 24, United-States, <=50K 40, Private, 191342, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 40, China, >50K 50, Private, 226497, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 45, United-States, >50K 48, Self-emp-not-inc, 373606, Some-college, 10, Divorced, Sales, Unmarried, White, Male, 0, 0, 65, United-States, >50K 30, Private, 39150, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 288840, HS-grad, 9, Married-spouse-absent, Other-service, Unmarried, Black, Female, 0, 0, 38, United-States, <=50K 34, Private, 293703, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 42, Private, 79586, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, >50K 48, Self-emp-not-inc, 82098, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 65, United-States, <=50K 38, Private, 245372, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 45, United-States, >50K 29, Private, 78261, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 355996, 10th, 6, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 64, Private, 218490, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 27828, 0, 55, United-States, >50K 44, Private, 110908, Assoc-voc, 11, Married-civ-spouse, Transport-moving, Wife, White, Female, 0, 0, 25, United-States, <=50K 42, Federal-gov, 34218, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 50, United-States, >50K 49, Private, 248895, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, <=50K 25, Private, 363707, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 272411, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 128033, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 20, Private, 177287, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 44, Private, 197344, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 45, Private, 285858, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Self-emp-inc, 193868, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 18, Private, 232082, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 27408, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 45, Private, 247043, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 42, United-States, <=50K 27, Local-gov, 162404, HS-grad, 9, Never-married, Protective-serv, Not-in-family, Black, Male, 2174, 0, 40, United-States, <=50K 64, Private, 236341, 5th-6th, 3, Widowed, Other-service, Not-in-family, Black, Female, 0, 0, 16, United-States, <=50K 66, Local-gov, 179285, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 3432, 0, 20, United-States, <=50K 34, Private, 30433, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 45, Self-emp-not-inc, 102771, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Self-emp-not-inc, 221172, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 108116, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 60, United-States, >50K 26, Private, 375499, 10th, 6, Never-married, Adm-clerical, Not-in-family, Black, Male, 0, 0, 20, United-States, <=50K 27, Private, 178688, Assoc-voc, 11, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 276709, Some-college, 10, Never-married, Sales, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 23, ?, 238087, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 30, United-States, <=50K 47, Private, 84790, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, State-gov, 37482, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 46, State-gov, 178686, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 38, United-States, >50K 35, ?, 153926, HS-grad, 9, Married-civ-spouse, ?, Wife, Black, Female, 0, 0, 40, United-States, <=50K 55, Private, 110748, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1887, 40, United-States, >50K 28, Private, 116613, Some-college, 10, Never-married, Tech-support, Own-child, White, Female, 0, 0, 24, United-States, <=50K 21, Private, 108687, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 365739, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 195284, Doctorate, 16, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 60, United-States, >50K 38, Private, 125933, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, ?, >50K 37, Private, 140854, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 81, Self-emp-not-inc, 193237, 1st-4th, 2, Widowed, Sales, Other-relative, White, Male, 0, 0, 45, Mexico, <=50K 41, Private, 46870, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 351324, Bachelors, 13, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 30, Self-emp-not-inc, 189265, Assoc-acdm, 12, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 236564, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Federal-gov, 557644, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 374454, HS-grad, 9, Divorced, Transport-moving, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 65, ?, 160654, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 20, United-States, <=50K 18, Private, 122775, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 35, United-States, <=50K 26, Private, 214413, 11th, 7, Never-married, Machine-op-inspct, Unmarried, White, Male, 6497, 0, 48, United-States, <=50K 30, Private, 329425, Some-college, 10, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 48, United-States, <=50K 61, Private, 178312, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 42, United-States, <=50K 21, Private, 241951, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 53, Private, 130143, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, <=50K 41, Self-emp-inc, 114580, Prof-school, 15, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 2415, 55, United-States, >50K 43, Self-emp-inc, 130126, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 45, United-States, >50K 60, Private, 399387, 7th-8th, 4, Separated, Priv-house-serv, Unmarried, Black, Female, 0, 0, 15, United-States, <=50K 47, Private, 163814, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 69586, Some-college, 10, Divorced, Adm-clerical, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 32, Private, 237903, Bachelors, 13, Never-married, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 25, ?, 219897, Masters, 14, Never-married, ?, Not-in-family, White, Female, 0, 0, 35, Canada, <=50K 31, Private, 243165, Bachelors, 13, Never-married, Prof-specialty, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 33, State-gov, 173806, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 27, Self-emp-not-inc, 65308, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 44, Private, 408531, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, >50K 44, Private, 235786, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7298, 0, 45, United-States, >50K 37, Private, 314963, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 81206, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 51, Federal-gov, 293196, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 51, Private, 95329, Masters, 14, Divorced, Protective-serv, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 25, Local-gov, 45474, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 25, Private, 372728, Bachelors, 13, Never-married, Other-service, Not-in-family, Black, Female, 0, 0, 24, Jamaica, <=50K 29, Federal-gov, 116394, Bachelors, 13, Married-AF-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 36, Self-emp-not-inc, 34180, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 70, United-States, >50K 55, Private, 327589, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 706180, Bachelors, 13, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 32550, 10th, 6, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 173858, Prof-school, 15, Married-civ-spouse, Tech-support, Husband, Asian-Pac-Islander, Male, 0, 0, 40, India, <=50K 51, Self-emp-inc, 230095, Assoc-voc, 11, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 139012, Assoc-voc, 11, Never-married, Adm-clerical, Other-relative, Asian-Pac-Islander, Male, 2463, 0, 40, Vietnam, <=50K 62, Private, 174711, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 37, Private, 171150, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 99999, 0, 60, United-States, >50K 30, Self-emp-inc, 77689, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 50, United-States, >50K 27, Private, 193898, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 52, United-States, <=50K 32, Private, 195000, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 45, United-States, >50K 23, Private, 303121, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 30, United-States, <=50K 35, Self-emp-not-inc, 188540, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 46, Private, 158656, Assoc-acdm, 12, Never-married, Prof-specialty, Unmarried, White, Female, 0, 0, 36, United-States, <=50K 45, Self-emp-inc, 204196, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Male, 0, 0, 50, United-States, >50K 27, Private, 183802, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 148995, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 22, Private, 190903, 11th, 7, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 20, United-States, <=50K 37, State-gov, 173780, Some-college, 10, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 42, Private, 251239, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, Puerto-Rico, <=50K 45, Private, 112761, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 33, State-gov, 425785, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 197731, Assoc-voc, 11, Married-spouse-absent, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 119156, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 50, United-States, <=50K 56, Private, 133819, HS-grad, 9, Separated, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 185556, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 12, United-States, >50K 50, Private, 109277, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 48, Self-emp-inc, 36020, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 45, Private, 45857, 11th, 7, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 36, United-States, <=50K 55, Private, 184882, Assoc-voc, 11, Married-civ-spouse, Transport-moving, Husband, White, Male, 5178, 0, 50, United-States, >50K 41, State-gov, 342834, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 66, Private, 234743, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 24, United-States, <=50K 29, Federal-gov, 106179, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 1408, 40, United-States, <=50K 37, Private, 177895, Some-college, 10, Married-civ-spouse, Tech-support, Wife, White, Female, 5013, 0, 40, United-States, <=50K 63, ?, 257876, Prof-school, 15, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 86067, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 40, United-States, >50K 64, Private, 66634, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Male, 27828, 0, 50, United-States, >50K 35, Private, 138441, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 35, United-States, <=50K 22, Private, 279802, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 58, Private, 407138, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 2936, 0, 50, Mexico, <=50K 58, Private, 31732, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 24, Private, 204172, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 48, United-States, <=50K 34, Private, 100593, Some-college, 10, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 6, United-States, <=50K 33, Local-gov, 162623, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 33, Self-emp-not-inc, 80933, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, <=50K 17, Private, 47425, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 27, Private, 107812, Bachelors, 13, Married-civ-spouse, Sales, Other-relative, White, Male, 0, 0, 40, United-States, >50K 20, Self-emp-inc, 104443, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 52, Private, 117496, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 1755, 40, United-States, >50K 30, Private, 209691, 7th-8th, 4, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 314525, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 190772, Assoc-acdm, 12, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 64, Local-gov, 199298, 5th-6th, 3, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 45, ?, <=50K 49, Private, 187370, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 50, United-States, >50K 38, Private, 216129, Bachelors, 13, Divorced, Other-service, Not-in-family, Black, Female, 0, 0, 60, ?, <=50K 46, Federal-gov, 219293, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 80, United-States, >50K 17, Private, 136363, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 45, Private, 233799, 1st-4th, 2, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 27, Private, 207611, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 45, Self-emp-inc, 178344, Assoc-voc, 11, Divorced, Sales, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 26, Self-emp-inc, 187652, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 78, United-States, >50K 23, Private, 188545, Assoc-acdm, 12, Never-married, Adm-clerical, Own-child, White, Female, 0, 1974, 20, United-States, <=50K 44, Local-gov, 58124, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Male, 0, 0, 45, United-States, <=50K 36, Private, 321733, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 1741, 40, United-States, <=50K 35, Private, 206253, 9th, 5, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 24, ?, 152140, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 40, United-States, <=50K 56, Private, 76281, Bachelors, 13, Married-spouse-absent, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 606752, Masters, 14, Divorced, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 29933, Bachelors, 13, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 50, United-States, >50K 29, Private, 114158, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 3325, 0, 10, United-States, <=50K 55, ?, 227203, Assoc-acdm, 12, Married-spouse-absent, ?, Not-in-family, White, Female, 0, 0, 5, United-States, <=50K 35, Self-emp-inc, 65624, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 37, Private, 34146, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 68, United-States, <=50K 36, Self-emp-not-inc, 34378, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 3908, 0, 75, United-States, <=50K 33, Private, 141490, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 45, United-States, <=50K 34, Private, 199227, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 24, Private, 224954, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 231357, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Self-emp-inc, 113530, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 38, Private, 22245, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 36383, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, Mexico, >50K 35, Private, 320305, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 32, United-States, <=50K 67, ?, 201657, Bachelors, 13, Divorced, ?, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 34, Private, 48935, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 101455, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 19, Local-gov, 243960, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 16, United-States, <=50K 26, Private, 90915, Assoc-acdm, 12, Never-married, Other-service, Own-child, Black, Female, 0, 0, 15, United-States, <=50K 28, Private, 315287, Some-college, 10, Never-married, Prof-specialty, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 47, Private, 106255, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Local-gov, 215895, Masters, 14, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, Italy, >50K 33, Self-emp-not-inc, 170979, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1887, 40, United-States, >50K 44, Private, 210525, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Private, 195488, HS-grad, 9, Never-married, Priv-house-serv, Own-child, White, Female, 0, 0, 40, Guatemala, <=50K 18, Private, 152246, Some-college, 10, Never-married, Other-service, Own-child, Asian-Pac-Islander, Male, 0, 0, 16, United-States, <=50K 60, Self-emp-not-inc, 187794, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 3103, 0, 60, United-States, >50K 44, Private, 110396, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Male, 14084, 0, 56, United-States, >50K 81, ?, 89391, Prof-school, 15, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 24, United-States, >50K 43, State-gov, 254817, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 41777, 12th, 8, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 58, Self-emp-not-inc, 234841, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 72, United-States, <=50K 32, Private, 79586, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, India, <=50K 40, Private, 115331, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 35, United-States, <=50K 32, Private, 63564, HS-grad, 9, Never-married, Other-service, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 21, Private, 132053, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 1721, 35, United-States, <=50K 44, Private, 370502, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 25, Mexico, <=50K 33, Private, 59083, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 1902, 45, United-States, >50K 25, Private, 69413, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 32981, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 176683, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 62, ?, 144116, 10th, 6, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Self-emp-not-inc, 209213, HS-grad, 9, Never-married, Sales, Not-in-family, Black, Male, 0, 0, 40, ?, <=50K 33, State-gov, 150657, Bachelors, 13, Never-married, Prof-specialty, Other-relative, Black, Female, 0, 0, 40, United-States, <=50K 50, Self-emp-not-inc, 124793, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, <=50K 50, Private, 22211, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 50, United-States, >50K 46, Private, 270565, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 22, Private, 38251, Assoc-acdm, 12, Never-married, Other-service, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 66, State-gov, 162945, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 20051, 0, 55, United-States, >50K 52, Private, 195638, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 57, Self-emp-not-inc, 118806, 1st-4th, 2, Widowed, Craft-repair, Other-relative, White, Female, 0, 1602, 45, Columbia, <=50K 41, Self-emp-not-inc, 44006, Assoc-voc, 11, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 119679, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 1579, 42, United-States, <=50K 19, Private, 333953, 12th, 8, Never-married, Other-service, Other-relative, White, Female, 0, 0, 30, United-States, <=50K 45, Local-gov, 172111, Bachelors, 13, Divorced, Exec-managerial, Unmarried, Black, Female, 0, 0, 60, United-States, <=50K 51, Self-emp-not-inc, 32372, 12th, 8, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 99, United-States, <=50K 69, ?, 117525, Assoc-acdm, 12, Divorced, ?, Unmarried, White, Female, 0, 0, 1, United-States, <=50K 45, Self-emp-not-inc, 123681, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 30, United-States, <=50K 48, Private, 317360, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 60, Federal-gov, 119832, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 7298, 0, 40, United-States, >50K 42, Private, 135056, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 19, State-gov, 135162, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 10, United-States, <=50K 39, Self-emp-not-inc, 194004, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 70, United-States, <=50K 46, Private, 177633, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, >50K 58, Local-gov, 212864, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 3908, 0, 40, United-States, <=50K 36, Private, 30509, Some-college, 10, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 21, Private, 118712, HS-grad, 9, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 35, United-States, <=50K 41, Private, 199018, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 17, Private, 151799, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 29, Private, 181280, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 232024, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 33, Private, 226267, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, Mexico, <=50K 38, Private, 240467, Masters, 14, Never-married, Exec-managerial, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 42, Private, 154374, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 24, State-gov, 231473, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 30, United-States, <=50K 59, Private, 158813, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 36, Private, 346478, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 2415, 45, United-States, >50K 54, Private, 215990, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 7688, 0, 40, United-States, >50K 39, Private, 177154, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 50, United-States, >50K 42, Self-emp-not-inc, 238188, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 96, United-States, <=50K 54, Self-emp-not-inc, 156800, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 26, Private, 130620, Assoc-acdm, 12, Married-spouse-absent, Craft-repair, Other-relative, Asian-Pac-Islander, Female, 0, 0, 40, ?, <=50K 50, Private, 175339, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Private, 37937, Assoc-voc, 11, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 45, United-States, <=50K 48, Federal-gov, 166634, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 7688, 0, 40, United-States, >50K 31, Private, 221167, Bachelors, 13, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 56, Private, 179641, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 28, Local-gov, 213195, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 34, Private, 157747, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, >50K 28, Private, 227840, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 169104, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, ?, >50K 44, Private, 186916, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1887, 60, United-States, >50K 34, Private, 37646, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 65, United-States, <=50K 26, Private, 157028, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 55, United-States, >50K 37, Private, 188774, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 2824, 40, United-States, >50K 64, ?, 146272, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 3411, 0, 15, United-States, <=50K 25, Private, 182656, Assoc-voc, 11, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 48, Self-emp-not-inc, 200471, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 358465, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 17, Private, 78602, 11th, 7, Never-married, Other-service, Other-relative, White, Female, 0, 0, 20, United-States, <=50K 44, Private, 213416, 5th-6th, 3, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 46, Local-gov, 345911, Some-college, 10, Divorced, Transport-moving, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 32, ?, 119522, Bachelors, 13, Divorced, ?, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 42, Federal-gov, 126320, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 33, Self-emp-not-inc, 235271, Bachelors, 13, Divorced, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 61, Private, 141745, HS-grad, 9, Divorced, Other-service, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 47, Private, 359461, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 109351, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 8614, 0, 45, United-States, >50K 62, Private, 148113, 10th, 6, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 62, Self-emp-not-inc, 75478, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 100375, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 60, United-States, >50K 19, ?, 28455, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 231413, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Local-gov, 119421, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 42, United-States, <=50K 17, Private, 206998, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 10, United-States, <=50K 58, Private, 183810, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Self-emp-inc, 187053, Bachelors, 13, Separated, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 34, Local-gov, 155781, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 4064, 0, 50, United-States, <=50K 55, ?, 193895, 7th-8th, 4, Divorced, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 48520, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, Self-emp-inc, 170125, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 107584, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 196742, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 52, ?, 244214, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 35, United-States, <=50K 48, Local-gov, 127921, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 42617, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 47, Local-gov, 191389, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 38, Private, 187983, Prof-school, 15, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 215110, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 25, Private, 230292, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 90159, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 32, United-States, >50K 40, Private, 175398, Assoc-voc, 11, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 56, Self-emp-not-inc, 53366, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 20, United-States, <=50K 50, Private, 46155, Assoc-voc, 11, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, >50K 55, Private, 61708, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 6418, 0, 50, United-States, >50K 32, Local-gov, 112650, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 173682, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 43, United-States, >50K 28, Private, 160981, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 52, United-States, <=50K 53, Private, 72257, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, <=50K 26, ?, 182332, Assoc-voc, 11, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 40, United-States, <=50K 60, Local-gov, 48788, Bachelors, 13, Separated, Prof-specialty, Unmarried, White, Female, 5455, 0, 55, United-States, <=50K 21, Private, 417668, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 29, Private, 107458, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 73, Private, 147551, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 2174, 50, United-States, >50K 43, Self-emp-inc, 33729, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 45, Private, 101977, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 35, ?, 374716, 9th, 5, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 35, United-States, <=50K 36, Private, 214378, HS-grad, 9, Divorced, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, >50K 25, Private, 111243, HS-grad, 9, Never-married, Sales, Other-relative, White, Female, 0, 0, 50, United-States, <=50K 38, Private, 252947, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 40, United-States, <=50K 30, Local-gov, 118500, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 195612, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 40, United-States, >50K 41, Local-gov, 174575, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 190391, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 64, Private, 166715, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 20, United-States, <=50K 41, Self-emp-not-inc, 142725, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 37, Private, 73471, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1887, 47, United-States, >50K 51, Private, 241745, 5th-6th, 3, Separated, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, Mexico, <=50K 35, Private, 316141, Some-college, 10, Divorced, Prof-specialty, Unmarried, White, Female, 7443, 0, 40, United-States, <=50K 61, Local-gov, 248595, 1st-4th, 2, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Mexico, <=50K 52, Private, 90189, 7th-8th, 4, Divorced, Priv-house-serv, Own-child, Black, Female, 0, 0, 16, United-States, <=50K 40, Private, 205195, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 20, Private, 148940, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 52, Local-gov, 298035, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 154728, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 49, Private, 166809, Bachelors, 13, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, >50K 36, State-gov, 97136, Bachelors, 13, Never-married, Prof-specialty, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 33, Private, 347623, Masters, 14, Never-married, Exec-managerial, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 117917, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, Amer-Indian-Eskimo, Male, 0, 0, 50, United-States, <=50K 45, Private, 266860, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 22, Private, 71864, Some-college, 10, Never-married, Craft-repair, Own-child, White, Female, 0, 0, 35, United-States, <=50K 47, Private, 158451, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 2, United-States, >50K 24, Private, 229826, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 19, Private, 121788, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 40, Private, 151365, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 360884, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 54, Private, 36480, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 50, United-States, >50K 43, Self-emp-not-inc, 116666, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, Other, Male, 0, 0, 35, United-States, >50K 63, Local-gov, 214143, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, Cuba, <=50K 18, Private, 45316, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 19, Private, 311974, 1st-4th, 2, Never-married, Machine-op-inspct, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 49, Self-emp-not-inc, 48495, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 27, Private, 115945, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 49, Local-gov, 170846, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 60, Private, 142922, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 71, ?, 181301, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 286675, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 233168, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 46, United-States, >50K 30, Private, 177304, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 44, United-States, <=50K 46, Private, 336984, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 17, United-States, <=50K 32, Self-emp-not-inc, 379412, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 180778, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 75, United-States, <=50K 25, Private, 141876, Masters, 14, Never-married, Prof-specialty, Unmarried, White, Male, 0, 0, 45, ?, <=50K 22, Private, 228306, Some-college, 10, Married-AF-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, >50K 32, Private, 329993, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 40, Private, 247469, Doctorate, 16, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 30, United-States, >50K 51, Private, 673764, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 27828, 0, 40, United-States, >50K 20, Private, 155775, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 30, United-States, <=50K 34, Private, 81223, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 40, Private, 236021, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 34, State-gov, 103371, Assoc-voc, 11, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 199480, 10th, 6, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 25, United-States, <=50K 53, Private, 152657, 10th, 6, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 42, Federal-gov, 460214, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 91039, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 65, United-States, >50K 41, Private, 197372, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, >50K 64, ?, 267198, Prof-school, 15, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 16, United-States, <=50K 30, State-gov, 111883, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 66917, 11th, 7, Married-civ-spouse, Farming-fishing, Own-child, White, Male, 0, 0, 40, Mexico, <=50K 19, Private, 292583, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 20, Private, 391679, HS-grad, 9, Never-married, Sales, Other-relative, White, Male, 0, 0, 60, United-States, <=50K 35, Private, 475324, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 33, Self-emp-not-inc, 218164, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Self-emp-not-inc, 101534, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 15, United-States, >50K 38, Federal-gov, 65706, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 50, Self-emp-not-inc, 156606, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 30, United-States, <=50K 23, Private, 200967, HS-grad, 9, Divorced, Other-service, Own-child, White, Female, 0, 0, 10, United-States, <=50K 30, Local-gov, 164493, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 10, United-States, <=50K 33, Private, 547886, Bachelors, 13, Separated, Exec-managerial, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 48, Private, 232145, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 96421, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 24, Outlying-US(Guam-USVI-etc), <=50K 33, Private, 554206, Some-college, 10, Never-married, Tech-support, Not-in-family, Black, Male, 0, 0, 40, Philippines, <=50K 50, Local-gov, 234143, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 45, United-States, >50K 23, Private, 380544, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Local-gov, 103886, Some-college, 10, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 50, State-gov, 54709, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 46, United-States, <=50K 26, Private, 276548, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 20, United-States, <=50K 55, Local-gov, 176046, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 2267, 40, United-States, <=50K 37, Private, 114605, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 323713, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Self-emp-not-inc, 261382, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 223548, 7th-8th, 4, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 30, Mexico, <=50K 47, Self-emp-not-inc, 355978, Doctorate, 16, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 2002, 45, United-States, <=50K 44, Private, 107218, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 28, Self-emp-not-inc, 31717, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 328947, Some-college, 10, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 51, Private, 148431, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 121602, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 62, Private, 244087, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 50, United-States, >50K 31, Private, 83425, Some-college, 10, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 157308, 11th, 7, Married-civ-spouse, Handlers-cleaners, Wife, Asian-Pac-Islander, Female, 2829, 0, 14, Philippines, <=50K 23, Private, 57898, Some-college, 10, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 40, State-gov, 175304, Some-college, 10, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 66, Self-emp-inc, 102663, 7th-8th, 4, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 17, Private, 99175, 11th, 7, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 37, Private, 208358, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 69, Private, 361561, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 3, United-States, <=50K 23, Private, 215115, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Federal-gov, 207066, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 42, United-States, >50K 37, Federal-gov, 160910, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 64879, Some-college, 10, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 430035, 9th, 5, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 54, Mexico, <=50K 37, State-gov, 74163, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 37, Self-emp-inc, 98389, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 23, Private, 386019, 9th, 5, Never-married, Farming-fishing, Unmarried, White, Male, 0, 0, 70, United-States, <=50K 17, Private, 112795, 10th, 6, Never-married, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 48, Private, 332465, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, United-States, <=50K 17, Private, 38611, 11th, 7, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 23, United-States, <=50K 55, Private, 368797, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 60, United-States, >50K 35, Private, 24106, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 68, ?, 108683, Some-college, 10, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 12, United-States, >50K 35, Self-emp-not-inc, 241998, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 53, Private, 312446, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 43, Private, 69333, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, <=50K 36, Private, 172538, Masters, 14, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 275884, HS-grad, 9, Separated, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 45, Private, 43479, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 48, United-States, <=50K 34, Private, 199864, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 2057, 40, United-States, <=50K 56, Private, 235197, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 36, Private, 170376, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 22, Private, 325179, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 50, United-States, <=50K 19, ?, 351195, 9th, 5, Never-married, ?, Other-relative, White, Male, 0, 1719, 35, El-Salvador, <=50K 33, Private, 141841, HS-grad, 9, Never-married, Other-service, Own-child, Black, Male, 0, 0, 36, United-States, <=50K 48, Private, 207817, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 32, Columbia, <=50K 20, Private, 137974, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 64, Self-emp-inc, 161325, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 1887, 50, United-States, >50K 47, Private, 293623, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Dominican-Republic, <=50K 20, Private, 37783, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 44, Federal-gov, 308027, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 45, Self-emp-not-inc, 149218, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 77, United-States, <=50K 45, Local-gov, 374450, HS-grad, 9, Married-civ-spouse, Transport-moving, Wife, White, Female, 5178, 0, 40, United-States, >50K 45, Local-gov, 61885, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 37, United-States, >50K 27, State-gov, 291196, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 41, Private, 45366, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 72, United-States, >50K 20, Private, 203027, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 54, Self-emp-inc, 223752, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 40, ?, >50K 17, Private, 132680, 10th, 6, Never-married, Other-service, Own-child, White, Female, 0, 1602, 10, United-States, <=50K 50, Private, 155574, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 31, State-gov, 193565, Masters, 14, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 49, Self-emp-not-inc, 123598, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 44, Private, 456236, Masters, 14, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 163229, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 28, Local-gov, 419740, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 52, United-States, <=50K 43, Local-gov, 118853, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 4386, 0, 99, United-States, >50K 33, Private, 31449, Assoc-acdm, 12, Divorced, Machine-op-inspct, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 35, Private, 204163, Some-college, 10, Divorced, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 55, United-States, <=50K 17, Private, 177629, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 25, Private, 186370, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 188307, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 55481, Masters, 14, Never-married, Tech-support, Unmarried, White, Male, 0, 0, 45, Nicaragua, <=50K 48, Private, 119471, Assoc-voc, 11, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 56, Philippines, >50K 61, Local-gov, 167347, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 35, United-States, <=50K 41, Private, 184378, HS-grad, 9, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 348960, HS-grad, 9, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 24, Local-gov, 69640, Some-college, 10, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 297457, HS-grad, 9, Never-married, Adm-clerical, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 18, Private, 279593, 11th, 7, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 2, United-States, <=50K 20, Private, 211968, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 15, United-States, <=50K 18, Private, 194561, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 12, United-States, <=50K 23, Private, 140414, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, State-gov, 24763, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1887, 45, United-States, >50K 38, State-gov, 462832, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, Black, Female, 0, 0, 40, Trinadad&Tobago, <=50K 36, Private, 48972, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 28, Self-emp-not-inc, 35032, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 47, Private, 228583, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, ?, <=50K 51, Private, 392668, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 84, United-States, >50K 35, Private, 108140, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 38, State-gov, 112497, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 60, United-States, <=50K 47, Federal-gov, 142581, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, >50K 26, Private, 147982, 11th, 7, Divorced, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, State-gov, 440129, Some-college, 10, Divorced, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 46, Private, 200734, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 35, Trinadad&Tobago, <=50K 49, Private, 31807, Some-college, 10, Never-married, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 166153, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 30, United-States, <=50K 45, Self-emp-inc, 212954, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 46, Private, 52291, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 45, United-States, >50K 70, Self-emp-not-inc, 303588, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 20, United-States, <=50K 19, Private, 96176, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 46, Private, 184632, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 20, Private, 137618, Some-college, 10, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 35, United-States, <=50K 17, Private, 160029, 11th, 7, Never-married, Other-service, Other-relative, White, Female, 0, 0, 22, United-States, <=50K 43, Private, 178780, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 49, United-States, >50K 19, Private, 39756, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 37, Private, 35309, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 117253, HS-grad, 9, Widowed, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 40, Local-gov, 303212, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 24, Private, 214542, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 60, Canada, <=50K 31, Private, 342019, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 59, Private, 126668, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 5178, 0, 50, United-States, >50K 27, Private, 401508, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 40, Private, 25005, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 99, United-States, >50K 30, Self-emp-not-inc, 85708, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 115677, Assoc-acdm, 12, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 32, United-States, <=50K 25, Private, 144259, HS-grad, 9, Never-married, Craft-repair, Own-child, Black, Male, 0, 0, 50, United-States, <=50K 22, Private, 197583, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 21, State-gov, 142766, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 67, ?, 132626, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 6, United-States, <=50K 35, Self-emp-inc, 185621, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 60, United-States, >50K 54, Local-gov, 29887, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 56, United-States, <=50K 36, Private, 117381, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 211482, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Federal-gov, 90653, HS-grad, 9, Never-married, Exec-managerial, Unmarried, White, Female, 0, 1380, 40, United-States, <=50K 55, Private, 209535, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 56, Federal-gov, 187873, Masters, 14, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 174732, Some-college, 10, Never-married, Other-service, Own-child, Black, Male, 0, 0, 25, United-States, <=50K 36, Private, 297847, HS-grad, 9, Never-married, Other-service, Not-in-family, Black, Female, 0, 2001, 40, United-States, <=50K 58, Private, 110213, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 35, Private, 162601, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 108438, 10th, 6, Separated, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 40, Self-emp-inc, 132222, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 174394, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 71, Self-emp-not-inc, 322789, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, Amer-Indian-Eskimo, Male, 0, 0, 35, United-States, <=50K 51, Federal-gov, 72436, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 57, United-States, >50K 27, ?, 60726, HS-grad, 9, Never-married, ?, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 20, Private, 190273, 12th, 8, Never-married, Other-service, Own-child, White, Male, 0, 0, 35, United-States, <=50K 33, ?, 393376, 11th, 7, Never-married, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 140571, Assoc-voc, 11, Divorced, Tech-support, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 28, Private, 584790, Assoc-voc, 11, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Private, 197666, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 24, Greece, <=50K 36, Private, 245090, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 3137, 0, 50, El-Salvador, <=50K 42, Private, 192569, Prof-school, 15, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 39, United-States, >50K 31, Local-gov, 158291, Bachelors, 13, Never-married, Craft-repair, Not-in-family, White, Male, 8614, 0, 40, United-States, >50K 19, ?, 113915, HS-grad, 9, Never-married, ?, Own-child, Black, Male, 0, 0, 10, United-States, <=50K 38, Local-gov, 287658, Masters, 14, Divorced, Prof-specialty, Not-in-family, Black, Male, 0, 0, 40, Jamaica, <=50K 22, Private, 192455, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 317040, Assoc-voc, 11, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 54, United-States, <=50K 36, Private, 218689, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 1977, 50, United-States, >50K 17, Private, 116626, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 1719, 18, United-States, <=50K 30, Federal-gov, 48458, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 35, Self-emp-not-inc, 241469, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 2635, 0, 30, United-States, <=50K 32, Private, 167990, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Male, 14084, 0, 40, United-States, >50K 42, Private, 261929, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 40, United-States, >50K 54, Private, 425804, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, >50K 36, Private, 33394, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 1887, 35, United-States, >50K 58, Private, 72812, 10th, 6, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 89040, Assoc-voc, 11, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 62, Local-gov, 164518, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 51, Private, 182740, HS-grad, 9, Divorced, Prof-specialty, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 361875, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 25, Private, 197130, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 30, United-States, <=50K 26, Private, 340335, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 293984, 10th, 6, Married-civ-spouse, Craft-repair, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 59, State-gov, 261584, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, Black, Female, 0, 0, 40, Outlying-US(Guam-USVI-etc), <=50K 21, Private, 170302, HS-grad, 9, Never-married, Farming-fishing, Other-relative, White, Male, 0, 0, 50, United-States, <=50K 45, Private, 481987, Masters, 14, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 18, United-States, >50K 26, Private, 88449, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 36, United-States, <=50K 68, Self-emp-not-inc, 261897, 10th, 6, Widowed, Farming-fishing, Unmarried, White, Male, 0, 0, 20, United-States, <=50K 60, Private, 250552, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, >50K 65, Private, 88513, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 18, United-States, <=50K 41, Private, 168293, Masters, 14, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 34, Private, 283921, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 28, Private, 407043, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, <=50K 40, Private, 63745, Assoc-voc, 11, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 57, Private, 49893, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 37, Private, 241962, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 34, Private, 338416, 10th, 6, Divorced, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 60, United-States, <=50K 21, ?, 212888, 11th, 7, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 56, United-States, <=50K 57, Federal-gov, 310320, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 48, United-States, >50K 55, Private, 359972, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1887, 40, United-States, >50K 51, Private, 64643, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 60, ?, <=50K 56, Private, 125000, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Private, 286675, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 18, Private, 165532, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 15, United-States, <=50K 48, Private, 349986, Assoc-voc, 11, Married-spouse-absent, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 213140, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, ?, >50K 41, Federal-gov, 219155, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, India, >50K 33, Private, 183612, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 20, United-States, <=50K 33, Private, 391114, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 219632, 5th-6th, 3, Married-spouse-absent, Machine-op-inspct, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 46, Self-emp-inc, 320124, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, Amer-Indian-Eskimo, Female, 15024, 0, 40, United-States, >50K 40, Private, 799281, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 38, United-States, <=50K 42, Private, 657397, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 31, State-gov, 373432, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7298, 0, 55, United-States, >50K 51, Private, 168660, 11th, 7, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 191149, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 57, United-States, <=50K 37, Private, 356824, HS-grad, 9, Separated, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 191782, 11th, 7, Never-married, Machine-op-inspct, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 63, Self-emp-not-inc, 29859, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 7688, 0, 60, United-States, >50K 52, Private, 204226, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 42, Local-gov, 246862, Some-college, 10, Divorced, Tech-support, Not-in-family, White, Female, 3325, 0, 40, United-States, <=50K 28, Private, 496526, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 426431, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 10520, 0, 40, United-States, >50K 34, Private, 84154, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 37, Federal-gov, 45937, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 31, Private, 130021, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, <=50K 35, Private, 63021, Some-college, 10, Divorced, Sales, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 25, Private, 367306, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 65624, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 43, Self-emp-not-inc, 144928, HS-grad, 9, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 22, Private, 117747, Some-college, 10, Never-married, Craft-repair, Other-relative, Asian-Pac-Islander, Female, 0, 0, 40, Vietnam, <=50K 18, Private, 266681, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 26, Private, 152035, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 190023, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, >50K 43, Private, 233130, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 21, Private, 149637, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 62, Federal-gov, 224277, Some-college, 10, Widowed, Protective-serv, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 121559, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Self-emp-not-inc, 230951, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 18, Private, 345285, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 65, Self-emp-not-inc, 28367, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, <=50K 41, Private, 320744, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 3325, 0, 50, United-States, <=50K 31, Private, 243773, 9th, 5, Never-married, Other-service, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 56, Private, 151474, 9th, 5, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 50, Private, 135465, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 22, Private, 210781, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 35, United-States, <=50K 36, Local-gov, 359001, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 48, United-States, <=50K 48, Private, 119471, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, India, >50K 30, Private, 226396, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 30, United-States, <=50K 35, Private, 283122, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 45, United-States, <=50K 37, Self-emp-not-inc, 326400, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 30, United-States, <=50K 32, ?, 169186, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 5, United-States, <=50K 56, Private, 158752, Masters, 14, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 50, United-States, <=50K 29, ?, 208406, HS-grad, 9, Never-married, ?, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 41, Private, 96741, Assoc-acdm, 12, Divorced, Sales, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 38, State-gov, 255191, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 177733, 9th, 5, Separated, Machine-op-inspct, Unmarried, White, Female, 0, 0, 35, Dominican-Republic, <=50K 54, State-gov, 137815, 12th, 8, Never-married, Other-service, Own-child, White, Male, 4101, 0, 40, United-States, <=50K 36, ?, 187203, Assoc-voc, 11, Divorced, ?, Own-child, White, Male, 0, 0, 50, United-States, <=50K 42, Private, 168515, Assoc-voc, 11, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 122672, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 21, Private, 195199, HS-grad, 9, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 30, United-States, <=50K 69, Local-gov, 179813, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 10, United-States, <=50K 32, Private, 178623, Assoc-acdm, 12, Never-married, Sales, Not-in-family, Black, Female, 0, 0, 46, Trinadad&Tobago, <=50K 50, Private, 41890, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 373050, 12th, 8, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, ?, <=50K 45, Private, 80430, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 31, Private, 198613, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 35, United-States, <=50K 24, Private, 330571, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 209205, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 21, Private, 132243, Assoc-acdm, 12, Never-married, Other-service, Own-child, White, Female, 0, 0, 5, United-States, <=50K 43, Self-emp-not-inc, 237670, Assoc-voc, 11, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 22, Private, 193586, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 62, Self-emp-not-inc, 197353, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1740, 40, United-States, <=50K 21, Self-emp-not-inc, 74538, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 37, Private, 89718, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 34, Private, 93169, Some-college, 10, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 74, Self-emp-not-inc, 292915, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1825, 12, United-States, >50K 43, Private, 328570, Some-college, 10, Divorced, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 38, United-States, <=50K 25, Private, 312157, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 193459, 11th, 7, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 236804, 11th, 7, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 126223, HS-grad, 9, Separated, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 51, State-gov, 172281, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 35, United-States, >50K 64, Private, 153894, Bachelors, 13, Never-married, Sales, Unmarried, White, Female, 0, 0, 40, Peru, <=50K 35, Private, 331395, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 69, Self-emp-not-inc, 92472, 10th, 6, Married-spouse-absent, Farming-fishing, Not-in-family, White, Male, 3273, 0, 45, United-States, <=50K 32, Private, 318647, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 48, United-States, >50K 20, Private, 332931, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, United-States, <=50K 66, Self-emp-inc, 76212, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 31, Private, 301168, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Italy, <=50K 22, Private, 440969, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 24, United-States, <=50K 32, Private, 154950, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 218343, Assoc-acdm, 12, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 239577, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 247936, HS-grad, 9, Married-civ-spouse, Other-service, Wife, Asian-Pac-Islander, Female, 0, 0, 2, Taiwan, <=50K 62, Local-gov, 203525, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 2829, 0, 40, United-States, <=50K 24, Private, 182342, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 25649, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 7298, 0, 50, United-States, >50K 27, Private, 243569, 11th, 7, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 3942, 0, 40, United-States, <=50K 38, Private, 187870, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 2415, 90, United-States, >50K 20, ?, 289116, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 5, United-States, <=50K 30, Private, 487330, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 30, United-States, <=50K 17, ?, 34019, 10th, 6, Never-married, ?, Own-child, White, Male, 0, 0, 20, United-States, <=50K 17, ?, 250541, 11th, 7, Never-married, ?, Own-child, Black, Male, 0, 0, 8, United-States, <=50K 21, Self-emp-not-inc, 318987, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, Self-emp-not-inc, 140558, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 59, Local-gov, 303455, Masters, 14, Widowed, Prof-specialty, Unmarried, White, Female, 4787, 0, 60, United-States, >50K 37, Self-emp-not-inc, 76855, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 52, Private, 308764, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 50, Federal-gov, 339905, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 55, Private, 227856, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 60, United-States, >50K 55, Private, 156430, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 45, ?, 98265, HS-grad, 9, Divorced, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 72, Private, 116640, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 3471, 0, 20, United-States, <=50K 39, Private, 187167, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 184078, 12th, 8, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 108140, Bachelors, 13, Divorced, Tech-support, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 150533, Some-college, 10, Separated, Craft-repair, Not-in-family, White, Male, 0, 1876, 55, United-States, <=50K 51, Self-emp-not-inc, 313702, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 39803, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 1719, 36, United-States, <=50K 25, Private, 252752, Some-college, 10, Never-married, Transport-moving, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 52, Private, 111700, Some-college, 10, Divorced, Sales, Other-relative, White, Female, 0, 0, 20, United-States, >50K 45, Private, 361842, HS-grad, 9, Widowed, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 17, Private, 231438, 11th, 7, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 12, United-States, <=50K 20, Private, 178469, HS-grad, 9, Never-married, Other-service, Own-child, Asian-Pac-Islander, Female, 0, 0, 15, ?, <=50K 64, Local-gov, 116620, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 25, United-States, <=50K 34, Private, 112212, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 1485, 40, United-States, <=50K 74, Self-emp-not-inc, 109101, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 4, United-States, <=50K 58, Federal-gov, 72998, 11th, 7, Divorced, Craft-repair, Not-in-family, Black, Female, 14084, 0, 40, United-States, >50K 44, Private, 147265, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 23, State-gov, 314645, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 23, Private, 444554, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 50, United-States, <=50K 27, Private, 129629, Assoc-voc, 11, Never-married, Tech-support, Other-relative, White, Female, 0, 0, 36, United-States, <=50K 34, Private, 106761, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 18, Private, 189924, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 24, United-States, <=50K 33, Private, 311194, 11th, 7, Never-married, Sales, Unmarried, Black, Female, 0, 0, 17, United-States, <=50K 50, Self-emp-not-inc, 89737, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, <=50K 47, Private, 49298, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 50, Self-emp-inc, 190333, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 99999, 0, 55, United-States, >50K 18, Private, 251923, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 15, United-States, <=50K 49, Local-gov, 298445, Prof-school, 15, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 1977, 60, United-States, >50K 34, Private, 180284, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 50, United-States, <=50K 51, Private, 154342, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 45, United-States, >50K 56, State-gov, 68658, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 64, Private, 203783, HS-grad, 9, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 8, United-States, <=50K 23, Private, 250037, Some-college, 10, Never-married, Farming-fishing, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 33, Private, 158688, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 214781, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 60, Federal-gov, 404023, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 10520, 0, 40, United-States, >50K 57, State-gov, 109015, 12th, 8, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 194630, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 23, Private, 239375, Bachelors, 13, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 35576, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 2415, 50, United-States, >50K 39, Federal-gov, 363630, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 7688, 0, 52, United-States, >50K 32, Self-emp-not-inc, 182926, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 117222, Some-college, 10, Never-married, Tech-support, Own-child, White, Male, 0, 0, 15, United-States, <=50K 30, Private, 110643, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 52, United-States, <=50K 56, Self-emp-not-inc, 170217, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 45, United-States, <=50K 34, Private, 193285, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 161075, HS-grad, 9, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 59, Private, 322691, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 19, Private, 229431, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 11, United-States, <=50K 60, ?, 106282, 9th, 5, Widowed, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 105694, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 42, United-States, <=50K 24, Private, 199883, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 41, State-gov, 100800, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 23, Private, 256278, 7th-8th, 4, Married-civ-spouse, Handlers-cleaners, Other-relative, Other, Female, 0, 0, 30, El-Salvador, <=50K 32, Private, 156464, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 1902, 50, United-States, >50K 51, Self-emp-inc, 129525, HS-grad, 9, Never-married, Sales, Other-relative, White, Male, 0, 0, 40, ?, <=50K 18, Private, 285013, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 10, United-States, <=50K 28, Private, 248911, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, ?, <=50K 33, ?, 369386, Some-college, 10, Married-civ-spouse, ?, Wife, White, Female, 5178, 0, 40, United-States, >50K 38, Private, 219902, HS-grad, 9, Separated, Transport-moving, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 29, Private, 375482, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, England, <=50K 25, Private, 169124, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 31, Private, 183000, Prof-school, 15, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 34, Private, 28053, Bachelors, 13, Married-spouse-absent, Adm-clerical, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 34, Private, 242984, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1887, 45, United-States, >50K 66, State-gov, 132055, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1825, 40, United-States, >50K 41, Private, 212894, 5th-6th, 3, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Guatemala, <=50K 62, Private, 223975, 7th-8th, 4, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 20, United-States, <=50K 58, Private, 357788, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 40, Private, 406811, HS-grad, 9, Separated, Exec-managerial, Unmarried, White, Female, 0, 0, 40, Canada, <=50K 24, Private, 154422, Bachelors, 13, Never-married, Exec-managerial, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 47, Private, 140644, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 19, Private, 355477, HS-grad, 9, Never-married, Other-service, Own-child, Black, Male, 0, 0, 25, United-States, <=50K 32, Private, 151773, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 51, State-gov, 341548, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 512771, 9th, 5, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 60, ?, 141580, Masters, 14, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 48988, Some-college, 10, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 201022, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 50, United-States, >50K 20, Private, 82777, HS-grad, 9, Married-civ-spouse, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 152676, 7th-8th, 4, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, Puerto-Rico, <=50K 18, Private, 115815, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 20, United-States, <=50K 23, Private, 168009, 10th, 6, Married-civ-spouse, Machine-op-inspct, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, Vietnam, <=50K 28, Private, 213152, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, ?, >50K 55, Private, 89690, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 40, Private, 126868, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 52, Private, 95128, Some-college, 10, Divorced, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 37, Private, 185567, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Male, 0, 0, 40, United-States, >50K 21, Private, 301408, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 1602, 22, United-States, <=50K 35, Private, 216256, Assoc-voc, 11, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 45, Private, 182541, Some-college, 10, Divorced, Machine-op-inspct, Unmarried, White, Male, 0, 0, 48, United-States, <=50K 39, Private, 172855, HS-grad, 9, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 54, Private, 68684, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 44, United-States, <=50K 42, Private, 364832, 7th-8th, 4, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, ?, 264300, Some-college, 10, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 20, United-States, <=50K 59, Self-emp-inc, 349910, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 276218, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, >50K 22, Private, 251196, Some-college, 10, Never-married, Protective-serv, Own-child, Black, Female, 0, 0, 20, United-States, <=50K 33, Private, 196898, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 58343, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 18, Self-emp-inc, 101061, 11th, 7, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 70, United-States, <=50K 46, Private, 415051, Some-college, 10, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 60, United-States, >50K 24, Private, 174043, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 129460, Assoc-voc, 11, Married-civ-spouse, Handlers-cleaners, Wife, White, Female, 0, 0, 30, Ecuador, <=50K 21, State-gov, 110946, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 43, United-States, <=50K 22, Private, 313873, 11th, 7, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 30, United-States, <=50K 61, Private, 81132, 5th-6th, 3, Married-civ-spouse, Handlers-cleaners, Husband, Asian-Pac-Islander, Male, 7298, 0, 40, Philippines, >50K 56, Federal-gov, 255386, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Laos, <=50K 21, Private, 191497, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 17, Private, 128617, 10th, 6, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 26, United-States, <=50K 29, Private, 368949, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, ?, >50K 28, Local-gov, 263600, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 62, Private, 257277, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 39, Private, 339442, HS-grad, 9, Separated, Machine-op-inspct, Not-in-family, Black, Male, 2176, 0, 40, United-States, <=50K 30, Local-gov, 289442, HS-grad, 9, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, ?, 162667, 11th, 7, Never-married, ?, Unmarried, White, Male, 0, 0, 40, El-Salvador, <=50K 18, Local-gov, 466325, 11th, 7, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 12, United-States, <=50K 54, Private, 142169, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 252079, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 33, State-gov, 119628, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 50, Hong, <=50K 50, Private, 175804, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 57, Private, 70720, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 78, United-States, <=50K 50, State-gov, 201513, HS-grad, 9, Divorced, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 257609, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Private, 124692, Some-college, 10, Married-civ-spouse, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, >50K 23, Private, 268525, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, <=50K 23, Private, 250630, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 180277, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, Hungary, <=50K 39, Self-emp-not-inc, 191342, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 50, South, <=50K 29, Private, 250967, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 1887, 48, United-States, >50K 46, Private, 153254, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 18, Private, 362600, 5th-6th, 3, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 68, Private, 171933, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 62, Private, 211408, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 43, Private, 48193, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 22463, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 440969, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 21, State-gov, 164922, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 41, Local-gov, 134524, Assoc-voc, 11, Divorced, Craft-repair, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 61, Private, 176689, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 220993, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 21, Private, 512828, HS-grad, 9, Never-married, Protective-serv, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 36, State-gov, 422275, 5th-6th, 3, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Mexico, <=50K 37, Local-gov, 65291, Assoc-voc, 11, Never-married, Protective-serv, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 69, Private, 197080, 12th, 8, Married-civ-spouse, Transport-moving, Husband, White, Male, 9386, 0, 60, United-States, >50K 49, Federal-gov, 181657, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 55, Private, 190257, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 53, United-States, >50K 21, Private, 238068, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 337046, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 187248, HS-grad, 9, Married-civ-spouse, Prof-specialty, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 20, ?, 250037, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 18, ?, <=50K 46, Private, 285750, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 4064, 0, 55, United-States, <=50K 23, Private, 260617, 10th, 6, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 216999, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 531055, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1902, 48, United-States, >50K 42, State-gov, 121265, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Local-gov, 184466, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 38, United-States, >50K 45, Private, 297676, Assoc-acdm, 12, Widowed, Sales, Unmarried, White, Female, 0, 0, 40, Cuba, <=50K 52, Private, 114228, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 3325, 0, 40, United-States, <=50K 22, Local-gov, 121144, Bachelors, 13, Never-married, Prof-specialty, Own-child, Black, Female, 0, 0, 18, United-States, <=50K 20, Private, 26842, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Female, 2176, 0, 40, United-States, <=50K 27, Private, 113054, HS-grad, 9, Separated, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 43, United-States, <=50K 36, Private, 256636, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 152246, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Amer-Indian-Eskimo, Male, 0, 0, 52, United-States, <=50K 38, Private, 108140, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 20, ?, 203353, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 207207, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 21, Private, 115420, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 33, Private, 80058, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Local-gov, 48520, Assoc-acdm, 12, Never-married, Protective-serv, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 411652, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Mexico, <=50K 46, Private, 154405, 10th, 6, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 45, United-States, <=50K 55, Local-gov, 104917, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 40, United-States, >50K 19, State-gov, 261422, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 48915, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 61, Private, 172037, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 144833, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 275116, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, ?, 72886, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 38, United-States, >50K 61, Private, 103575, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 37, United-States, <=50K 54, Private, 200783, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Self-emp-inc, 152810, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 70, Germany, <=50K 37, Local-gov, 44694, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 45, United-States, >50K 17, ?, 48703, 11th, 7, Never-married, ?, Own-child, White, Female, 0, 0, 30, United-States, <=50K 56, Private, 91905, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 4, United-States, <=50K 31, Private, 168906, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 32, State-gov, 147215, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 55, United-States, >50K 28, Private, 153546, 11th, 7, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 35595, Assoc-voc, 11, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 225507, 10th, 6, Never-married, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 42, Private, 345504, Assoc-voc, 11, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 64, Private, 137205, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, <=50K 29, Private, 327779, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 20, United-States, <=50K 41, ?, 213416, 5th-6th, 3, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 32, Mexico, <=50K 45, Private, 362883, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 131309, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 44, Private, 188331, Some-college, 10, Separated, Tech-support, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 34, Federal-gov, 194740, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 43711, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 45, Private, 187033, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 2051, 40, United-States, <=50K 23, Private, 233923, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 51, Private, 84278, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 24, Private, 437666, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 2885, 0, 50, United-States, <=50K 57, Private, 186386, Bachelors, 13, Widowed, Prof-specialty, Unmarried, White, Male, 10520, 0, 40, United-States, >50K 23, Private, 129767, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 1721, 40, United-States, <=50K 34, Private, 180284, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 108320, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 4101, 0, 40, United-States, <=50K 56, Self-emp-inc, 75214, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 32, United-States, >50K 42, Private, 284758, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 45, Self-emp-inc, 188330, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 38, Private, 333651, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 70, United-States, >50K 29, Local-gov, 115305, Assoc-voc, 11, Married-civ-spouse, Protective-serv, Husband, White, Male, 7688, 0, 40, United-States, >50K 54, Private, 172962, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 1340, 40, United-States, <=50K 40, Private, 198096, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Private, 163265, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Federal-gov, 128608, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 107460, HS-grad, 9, Separated, Exec-managerial, Unmarried, White, Female, 0, 0, 37, United-States, <=50K 51, Private, 251841, Assoc-voc, 11, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 43, United-States, <=50K 28, Private, 403671, HS-grad, 9, Never-married, Other-service, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 58, Private, 159378, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, >50K 24, Private, 170070, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 25, United-States, <=50K 46, State-gov, 192323, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 135796, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 48, United-States, <=50K 22, Private, 232985, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 20, United-States, <=50K 28, Private, 34532, Bachelors, 13, Never-married, Tech-support, Not-in-family, Black, Male, 0, 0, 30, Jamaica, <=50K 17, ?, 371316, 10th, 6, Never-married, ?, Own-child, White, Male, 0, 0, 25, United-States, <=50K 23, Private, 236994, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 60, United-States, <=50K 19, Private, 208366, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 66, State-gov, 102640, HS-grad, 9, Widowed, Prof-specialty, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 38, Private, 111377, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, <=50K 39, Federal-gov, 472166, Some-college, 10, Divorced, Exec-managerial, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 39, ?, 86551, 12th, 8, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 70943, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 5178, 0, 40, United-States, >50K 39, Private, 294919, HS-grad, 9, Divorced, Transport-moving, Own-child, White, Male, 0, 0, 60, United-States, <=50K 22, Private, 408383, Some-college, 10, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 255454, HS-grad, 9, Never-married, Craft-repair, Own-child, Black, Male, 0, 0, 30, United-States, <=50K 32, Private, 193260, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 29, ?, 191935, HS-grad, 9, Never-married, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 43, Local-gov, 125461, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 97005, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 183319, 5th-6th, 3, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 32, State-gov, 167049, 12th, 8, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 185216, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 161838, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 57, United-States, <=50K 38, Private, 165848, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 44, United-States, <=50K 21, Private, 138816, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 20, United-States, <=50K 33, Self-emp-not-inc, 99761, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 34, Private, 112139, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 129020, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, ?, 365465, Assoc-voc, 11, Never-married, ?, Own-child, White, Male, 0, 0, 15, United-States, <=50K 27, Self-emp-not-inc, 259873, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 60, United-States, >50K 35, Self-emp-inc, 89622, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 29, State-gov, 201556, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 40, Private, 176286, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 192894, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, Black, Male, 0, 0, 30, United-States, <=50K 37, Private, 172232, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 38, Self-emp-not-inc, 163204, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 3411, 0, 25, United-States, <=50K 37, Private, 265737, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 1887, 60, Cuba, >50K 44, Private, 215304, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 25, Private, 185952, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 38, Private, 216845, HS-grad, 9, Never-married, Sales, Unmarried, White, Male, 0, 0, 42, United-States, <=50K 34, Local-gov, 35683, Assoc-acdm, 12, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 10, United-States, <=50K 50, Self-emp-not-inc, 371305, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 1902, 60, United-States, >50K 46, Private, 102359, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 20, Private, 200089, 5th-6th, 3, Never-married, Handlers-cleaners, Unmarried, White, Male, 0, 0, 30, Guatemala, <=50K 47, State-gov, 207120, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 38, United-States, >50K 46, Private, 295334, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 34, Private, 234537, Assoc-acdm, 12, Divorced, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 142922, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, State-gov, 181641, Some-college, 10, Divorced, Prof-specialty, Not-in-family, Black, Female, 0, 0, 37, United-States, <=50K 36, Private, 185325, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 28, Private, 167336, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 10520, 0, 40, United-States, >50K 22, Private, 379778, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 176117, Some-college, 10, Never-married, Sales, Own-child, Black, Female, 0, 0, 35, United-States, <=50K 33, Private, 100228, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 27, Private, 150296, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 32, United-States, <=50K 43, Federal-gov, 25005, Masters, 14, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 5013, 0, 12, United-States, <=50K 55, Private, 134120, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 99999, 0, 40, United-States, >50K 39, Self-emp-not-inc, 251710, 10th, 6, Married-spouse-absent, Other-service, Not-in-family, White, Female, 0, 1721, 15, United-States, <=50K 20, Private, 653574, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 33, El-Salvador, <=50K 38, Private, 175441, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 30, Private, 333119, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 89154, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 42, El-Salvador, <=50K 60, Private, 198727, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 30, United-States, <=50K 43, Private, 87284, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 180686, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 23, Private, 227070, Some-college, 10, Never-married, Other-service, Unmarried, White, Female, 0, 0, 48, El-Salvador, <=50K 57, Local-gov, 189824, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 7298, 0, 40, United-States, >50K 25, Local-gov, 348986, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, Black, Male, 0, 0, 40, United-States, <=50K 38, Private, 96185, HS-grad, 9, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 32, United-States, <=50K 22, Private, 112693, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 23, Private, 417605, 5th-6th, 3, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 61, Self-emp-not-inc, 140300, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 44, United-States, <=50K 28, Private, 340408, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 46, United-States, <=50K 17, ?, 187539, 11th, 7, Never-married, ?, Own-child, White, Female, 0, 0, 10, United-States, <=50K 21, Private, 237051, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 49, Private, 175622, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 389725, 12th, 8, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 35, United-States, <=50K 23, Private, 182812, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, Dominican-Republic, <=50K 38, Self-emp-not-inc, 245372, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 3137, 0, 50, United-States, <=50K 34, Local-gov, 93886, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 46, United-States, >50K 21, Private, 502837, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Female, 0, 0, 40, Peru, <=50K 27, State-gov, 212232, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 40, United-States, >50K 57, Private, 300104, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 84, United-States, >50K 22, Private, 156933, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 25, United-States, <=50K 20, Private, 286734, Some-college, 10, Never-married, Adm-clerical, Not-in-family, Other, Female, 0, 0, 35, United-States, <=50K 49, Self-emp-inc, 143482, Some-college, 10, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 65, United-States, >50K 38, Private, 226357, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 104892, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 223194, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 1485, 40, Haiti, <=50K 37, Self-emp-not-inc, 272090, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 20, United-States, <=50K 57, Private, 204816, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 56, Private, 230039, 7th-8th, 4, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 41, Private, 242619, Assoc-acdm, 12, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 80, United-States, <=50K 50, Self-emp-not-inc, 131982, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 0, 60, South, <=50K 33, Private, 87310, 9th, 5, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 29, Private, 134566, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 20, United-States, <=50K 28, Federal-gov, 163862, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 5178, 0, 40, United-States, >50K 35, Private, 239409, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, <=50K 36, Private, 203717, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 172274, Doctorate, 16, Divorced, Prof-specialty, Unmarried, Black, Female, 0, 3004, 35, United-States, >50K 30, Self-emp-not-inc, 65278, Assoc-acdm, 12, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 35, Self-emp-inc, 135289, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 60, United-States, <=50K 27, Private, 246974, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 180060, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, Yugoslavia, <=50K 24, Private, 118023, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 30, United-States, <=50K 47, Private, 102308, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 47, Private, 45564, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 18, Private, 137646, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 18, Private, 237646, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 30, United-States, <=50K 31, Local-gov, 189843, HS-grad, 9, Divorced, Protective-serv, Not-in-family, White, Male, 0, 0, 47, United-States, >50K 43, Self-emp-not-inc, 118261, Masters, 14, Divorced, Other-service, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 45, Private, 288437, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Other, Male, 4064, 0, 40, United-States, <=50K 39, Private, 106347, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 316471, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 22, Private, 50058, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 30, Self-emp-not-inc, 182089, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 85, United-States, <=50K 36, Private, 186865, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 20, State-gov, 158206, Assoc-acdm, 12, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 61, ?, 229744, 1st-4th, 2, Married-civ-spouse, ?, Husband, White, Male, 3942, 0, 20, Mexico, <=50K 27, Private, 141545, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1902, 45, United-States, <=50K 59, Local-gov, 50929, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 60, Private, 132529, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 260696, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 231180, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 40, Private, 223277, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 50, United-States, >50K 20, Private, 279538, 11th, 7, Married-civ-spouse, Handlers-cleaners, Other-relative, White, Male, 2961, 0, 35, United-States, <=50K 47, Private, 46044, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 168071, Assoc-acdm, 12, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 20, Private, 79691, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 75, ?, 114204, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 13, United-States, <=50K 25, Private, 124111, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 104521, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Self-emp-not-inc, 128516, Assoc-acdm, 12, Widowed, Sales, Unmarried, White, Female, 0, 0, 40, United-States, >50K 34, Private, 112564, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 45, State-gov, 32186, Bachelors, 13, Separated, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 239663, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 2597, 0, 50, United-States, <=50K 46, Private, 269284, Assoc-acdm, 12, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 41, State-gov, 175537, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, Black, Female, 0, 0, 38, United-States, <=50K 29, Private, 444304, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 17, Private, 27415, 11th, 7, Never-married, Handlers-cleaners, Own-child, Amer-Indian-Eskimo, Male, 0, 0, 20, United-States, <=50K 39, Private, 174343, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 148143, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 34, Private, 209213, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, ?, <=50K 20, Private, 165097, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 18, ?, 51574, HS-grad, 9, Never-married, ?, Own-child, Asian-Pac-Islander, Female, 0, 1602, 38, United-States, <=50K 52, Private, 167651, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Local-gov, 29075, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Wife, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 22, Private, 396895, 5th-6th, 3, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, Mexico, <=50K 66, State-gov, 71075, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 35, Private, 129573, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 65, United-States, <=50K 40, Local-gov, 183765, Assoc-acdm, 12, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 21, Private, 164991, HS-grad, 9, Divorced, Sales, Unmarried, Amer-Indian-Eskimo, Female, 0, 0, 38, United-States, <=50K 51, Local-gov, 154891, HS-grad, 9, Divorced, Protective-serv, Unmarried, White, Male, 0, 0, 52, United-States, <=50K 34, Private, 200117, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 176389, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 342567, Bachelors, 13, Married-spouse-absent, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 178841, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 42, Local-gov, 191149, Masters, 14, Never-married, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 29702, Assoc-voc, 11, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 21, Private, 157893, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Female, 0, 0, 40, United-States, <=50K 64, Local-gov, 31993, 7th-8th, 4, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 10, United-States, <=50K 24, Federal-gov, 210736, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 1974, 40, United-States, <=50K 23, Private, 39615, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 10, United-States, <=50K 29, Private, 200511, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 44, Self-emp-not-inc, 47818, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 60, United-States, <=50K 28, Private, 183155, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, <=50K 33, Self-emp-inc, 374905, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 35, Private, 128876, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 202872, 10th, 6, Married-spouse-absent, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 153414, Bachelors, 13, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 40, United-States, >50K 51, Self-emp-not-inc, 24790, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 99, United-States, >50K 32, Private, 316769, 11th, 7, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, Jamaica, <=50K 37, Private, 126569, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 128538, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 25, United-States, <=50K 24, Private, 234640, Assoc-voc, 11, Never-married, Other-service, Own-child, White, Female, 0, 0, 35, United-States, <=50K 29, ?, 65372, Some-college, 10, Divorced, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 343377, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 52, Federal-gov, 30731, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 35, Private, 412379, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 46, Self-emp-inc, 112320, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 63, Private, 181929, HS-grad, 9, Widowed, Exec-managerial, Unmarried, White, Male, 0, 0, 50, United-States, >50K 32, Local-gov, 100135, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 35, United-States, >50K 24, Private, 128061, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 594, 0, 15, United-States, <=50K 72, ?, 402306, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 32, Canada, <=50K 35, ?, 98389, Some-college, 10, Never-married, ?, Unmarried, White, Male, 0, 0, 10, United-States, <=50K 29, Private, 179565, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 64922, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 50, United-States, >50K 70, Private, 102610, 10th, 6, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 32, United-States, <=50K 65, ?, 115513, Bachelors, 13, Married-civ-spouse, ?, Husband, White, Male, 5556, 0, 48, United-States, >50K 36, Private, 150548, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 53, Private, 133219, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 4386, 0, 30, United-States, >50K 49, Local-gov, 67001, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 60, Private, 162347, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 40, United-States, >50K 18, Private, 138557, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 170456, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 35, Italy, <=50K 42, Private, 66006, 10th, 6, Never-married, Transport-moving, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 25, State-gov, 176077, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 37, United-States, <=50K 32, Private, 218322, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Self-emp-inc, 181691, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, ?, <=50K 47, Private, 168232, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 7298, 0, 40, United-States, >50K 30, Private, 161690, Assoc-voc, 11, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, ?, 242736, Assoc-acdm, 12, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 38, Self-emp-not-inc, 67317, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 34, Private, 265807, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 2051, 55, United-States, <=50K 37, Private, 99357, Assoc-acdm, 12, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 56, Private, 170070, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 52, State-gov, 231166, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 62339, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 29, State-gov, 118520, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 42, United-States, <=50K 45, Private, 155659, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 23, Local-gov, 157331, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 341762, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 65, United-States, >50K 30, Private, 164190, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 42, United-States, <=50K 45, Private, 83064, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 26, Private, 304283, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 436798, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 29302, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 40, ?, <=50K 43, Private, 104660, Masters, 14, Widowed, Exec-managerial, Unmarried, White, Male, 4934, 0, 40, United-States, >50K 42, Private, 79036, HS-grad, 9, Divorced, Handlers-cleaners, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 72, Private, 165622, Some-college, 10, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 21, ?, 177287, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 57, Private, 199847, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 60, United-States, >50K 24, Private, 22966, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 27, Private, 59068, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 77336, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Local-gov, 96524, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 17, Private, 143868, 9th, 5, Never-married, Other-service, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 48, Private, 121424, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 39, Private, 176279, Bachelors, 13, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 41, Self-emp-inc, 177905, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 70, United-States, >50K 50, Private, 205100, 7th-8th, 4, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 35, ?, <=50K 57, Private, 353881, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 44, Local-gov, 177937, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 36, United-States, >50K 20, ?, 122244, HS-grad, 9, Never-married, ?, Not-in-family, White, Female, 0, 0, 28, United-States, <=50K 49, Private, 125892, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 155472, Assoc-acdm, 12, Never-married, Prof-specialty, Unmarried, Black, Female, 1151, 0, 50, United-States, <=50K 42, Private, 355728, Assoc-voc, 11, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 44, United-States, <=50K 18, ?, 245274, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 16, United-States, <=50K 18, Private, 240330, 12th, 8, Never-married, Other-service, Own-child, White, Male, 0, 0, 18, United-States, <=50K 51, Private, 182944, HS-grad, 9, Widowed, Tech-support, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 28, Private, 264498, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 110426, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Wife, White, Female, 15024, 0, 45, United-States, >50K 25, Private, 166971, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 52, United-States, <=50K 41, Private, 347653, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 50, United-States, >50K 39, Private, 33975, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Self-emp-not-inc, 215219, 11th, 7, Separated, Other-service, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 33, Private, 190772, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 1617, 40, United-States, <=50K 63, ?, 331527, 10th, 6, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 162494, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 0, 45, United-States, >50K 27, Local-gov, 85918, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 68, United-States, <=50K 39, Private, 91367, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1848, 45, United-States, >50K 20, Private, 182342, Some-college, 10, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 129640, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 70, ?, 133536, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 28, United-States, <=50K 46, Private, 148738, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 1740, 35, United-States, <=50K 47, Private, 102583, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 30, United-States, >50K 35, Private, 111387, 9th, 5, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 241752, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 22, ?, 334593, Some-college, 10, Never-married, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 101950, Bachelors, 13, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 60, Local-gov, 212856, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, ?, >50K 53, Private, 183973, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, >50K 47, Private, 142061, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 158615, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 29145, Assoc-voc, 11, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 40135, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, United-States, <=50K 23, Private, 224640, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, ?, 146651, HS-grad, 9, Married-civ-spouse, ?, Own-child, White, Female, 0, 0, 15, United-States, <=50K 29, Private, 167737, HS-grad, 9, Never-married, Transport-moving, Other-relative, White, Male, 0, 0, 50, United-States, <=50K 23, Private, 60331, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 187167, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 18, ?, 157131, HS-grad, 9, Never-married, ?, Own-child, White, Female, 0, 0, 12, United-States, <=50K 27, Local-gov, 255237, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 56, ?, 192325, Some-college, 10, Divorced, ?, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 40, Private, 163342, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 70, United-States, <=50K 31, Private, 129775, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 65, United-States, <=50K 18, Private, 206008, Some-college, 10, Never-married, Sales, Unmarried, White, Male, 2176, 0, 40, United-States, <=50K 25, Private, 397317, Assoc-acdm, 12, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 745768, Some-college, 10, Never-married, Protective-serv, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 38, Private, 141550, 10th, 6, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 35576, HS-grad, 9, Widowed, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 376383, HS-grad, 9, Never-married, Other-service, Unmarried, White, Male, 0, 0, 35, Mexico, <=50K 48, Self-emp-not-inc, 200825, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 30, United-States, >50K 34, ?, 362787, HS-grad, 9, Never-married, ?, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 46, Private, 116789, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 160300, HS-grad, 9, Married-spouse-absent, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 362654, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, ?, 107801, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 3, United-States, <=50K 65, Private, 170939, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 6723, 0, 40, United-States, <=50K 31, Local-gov, 224234, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 38, Private, 478346, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 7688, 0, 40, United-States, >50K 68, Private, 211162, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 147638, Bachelors, 13, Never-married, Adm-clerical, Other-relative, Asian-Pac-Islander, Female, 0, 0, 40, Hong, <=50K 42, Private, 104647, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 67365, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Private, 230959, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, Asian-Pac-Islander, Female, 0, 1887, 40, Philippines, >50K 39, Private, 176335, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 65, United-States, >50K 31, Self-emp-not-inc, 268482, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, State-gov, 288731, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 20, United-States, <=50K 36, Private, 231082, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 42, State-gov, 333530, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, >50K 62, Private, 214288, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 118023, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 24, United-States, <=50K 21, Private, 187088, Some-college, 10, Never-married, Adm-clerical, Own-child, Other, Female, 0, 0, 20, Cuba, <=50K 60, ?, 174073, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 133833, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 30, Private, 229772, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 64, Private, 210082, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 119287, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 15024, 0, 28, United-States, >50K 41, Self-emp-not-inc, 111772, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1887, 40, United-States, >50K 25, Private, 122999, HS-grad, 9, Never-married, Craft-repair, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 44767, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 200574, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 44, United-States, <=50K 58, Private, 236596, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 33124, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 99, United-States, <=50K 50, Local-gov, 308764, HS-grad, 9, Widowed, Transport-moving, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 103524, HS-grad, 9, Separated, Handlers-cleaners, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 31, ?, 99483, HS-grad, 9, Never-married, ?, Own-child, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 50, Private, 230951, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 99355, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 40, United-States, >50K 33, Private, 857532, 12th, 8, Never-married, Protective-serv, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 62, Private, 81116, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 1974, 40, United-States, <=50K 38, Private, 154410, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 2051, 40, Poland, <=50K 19, Private, 198943, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 35, United-States, <=50K 30, Private, 311696, 11th, 7, Married-civ-spouse, Other-service, Wife, Black, Female, 0, 0, 30, United-States, <=50K 38, Private, 252897, Some-college, 10, Divorced, Sales, Own-child, White, Female, 0, 0, 25, United-States, <=50K 42, Self-emp-not-inc, 39539, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 99, United-States, >50K 49, Self-emp-inc, 122066, Some-college, 10, Divorced, Sales, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 53, Private, 110977, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 50, United-States, >50K 45, Local-gov, 199590, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1887, 40, Mexico, >50K 24, Private, 202721, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 29, Private, 197565, Assoc-voc, 11, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 35, United-States, <=50K 24, Private, 206827, Some-college, 10, Never-married, Sales, Own-child, White, Female, 5060, 0, 30, United-States, <=50K 38, Federal-gov, 190895, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, ?, >50K 25, Self-emp-inc, 158751, Assoc-voc, 11, Never-married, Transport-moving, Unmarried, White, Male, 0, 0, 55, United-States, <=50K 51, State-gov, 243631, 10th, 6, Married-civ-spouse, Craft-repair, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 17, ?, 219277, 11th, 7, Never-married, ?, Own-child, White, Female, 0, 0, 20, United-States, <=50K 19, Private, 45381, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 8, United-States, <=50K 38, Private, 167482, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 52, United-States, >50K 60, Private, 225014, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, Self-emp-not-inc, 405083, HS-grad, 9, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 66, ?, 186061, Some-college, 10, Widowed, ?, Unmarried, Black, Female, 0, 4356, 40, United-States, <=50K 28, Federal-gov, 24153, 10th, 6, Married-civ-spouse, Other-service, Wife, Amer-Indian-Eskimo, Female, 0, 0, 40, United-States, <=50K 36, Private, 126569, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, Ecuador, >50K 57, ?, 137658, HS-grad, 9, Married-civ-spouse, ?, Husband, Other, Male, 0, 0, 5, Columbia, <=50K 24, Private, 315476, Assoc-acdm, 12, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 248186, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 29, Self-emp-inc, 206903, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, >50K 67, Self-emp-not-inc, 191380, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 20051, 0, 25, United-States, >50K 20, Private, 191910, HS-grad, 9, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 145119, Some-college, 10, Never-married, Other-service, Own-child, Asian-Pac-Islander, Male, 0, 0, 20, United-States, <=50K 20, Private, 130840, 10th, 6, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 33126, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 20, Private, 334105, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 10, United-States, <=50K 19, Local-gov, 354104, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 35, United-States, <=50K 34, Private, 111985, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 40, Local-gov, 321187, Bachelors, 13, Never-married, Prof-specialty, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 33, Private, 138142, Some-college, 10, Separated, Other-service, Unmarried, Black, Female, 0, 0, 25, United-States, <=50K 36, Private, 296999, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Female, 0, 0, 37, United-States, <=50K 43, Private, 155106, Assoc-acdm, 12, Divorced, Craft-repair, Not-in-family, White, Male, 0, 2444, 70, United-States, >50K 41, Local-gov, 174491, HS-grad, 9, Separated, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 34, State-gov, 173266, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 33, Private, 25610, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, Other, Male, 0, 0, 40, Japan, >50K 47, Private, 187563, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 196344, 1st-4th, 2, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, Mexico, <=50K 40, Private, 205047, HS-grad, 9, Married-spouse-absent, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 28, Private, 715938, Bachelors, 13, Never-married, Craft-repair, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 62, Self-emp-not-inc, 224520, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 90, United-States, >50K 29, Private, 229656, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 46, Private, 97883, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 131298, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 57, Federal-gov, 197875, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 172766, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 28, Local-gov, 175796, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 51973, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 54, Self-emp-not-inc, 28186, Bachelors, 13, Divorced, Farming-fishing, Not-in-family, White, Male, 27828, 0, 50, United-States, >50K 22, Private, 291979, 11th, 7, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, State-gov, 180752, Bachelors, 13, Never-married, Protective-serv, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 50, Private, 234657, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 18, Private, 39411, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 24, United-States, <=50K 52, State-gov, 334273, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 41, Private, 192779, 7th-8th, 4, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, ?, <=50K 21, ?, 105312, HS-grad, 9, Never-married, ?, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 36, Private, 171676, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 1741, 40, United-States, <=50K 34, Self-emp-not-inc, 182714, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 55, United-States, >50K 21, Private, 231866, Assoc-voc, 11, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 102102, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 57, ?, 50248, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, Local-gov, 195519, Masters, 14, Never-married, Prof-specialty, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 22, State-gov, 34310, Some-college, 10, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 25, United-States, <=50K 33, ?, 314913, 11th, 7, Divorced, ?, Own-child, White, Male, 0, 0, 53, United-States, <=50K 36, State-gov, 747719, Prof-school, 15, Married-civ-spouse, Prof-specialty, Wife, White, Female, 15024, 0, 50, United-States, >50K 43, Local-gov, 188280, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 914, 0, 40, United-States, <=50K 25, Private, 110978, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Wife, Asian-Pac-Islander, Female, 0, 0, 37, India, >50K 17, Private, 79682, 10th, 6, Never-married, Priv-house-serv, Other-relative, White, Male, 0, 0, 30, United-States, <=50K 45, Private, 294671, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 4386, 0, 38, United-States, >50K 30, Private, 340899, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 1590, 80, United-States, <=50K 40, Private, 192259, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 31, Local-gov, 190228, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 42, Private, 118947, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 53, Private, 55861, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Private, 238433, 1st-4th, 2, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, Cuba, <=50K 37, State-gov, 166744, HS-grad, 9, Married-spouse-absent, Other-service, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 54, Private, 144586, Some-college, 10, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, >50K 36, Private, 134367, HS-grad, 9, Divorced, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 46, Private, 133616, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 203039, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 48, United-States, <=50K 32, Private, 217460, 9th, 5, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 17, Private, 106733, 11th, 7, Never-married, Craft-repair, Own-child, White, Male, 594, 0, 40, United-States, <=50K 42, State-gov, 212027, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 37, Local-gov, 126569, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 289960, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, <=50K 54, Private, 174102, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 181716, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, <=50K 46, Local-gov, 172822, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 293091, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 107443, 1st-4th, 2, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Portugal, <=50K 59, Private, 95283, 1st-4th, 2, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 65278, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 35, Private, 220943, HS-grad, 9, Divorced, Other-service, Unmarried, Black, Female, 0, 1594, 40, United-States, <=50K 53, Private, 257940, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 2829, 0, 40, United-States, <=50K 26, Private, 134945, HS-grad, 9, Never-married, Machine-op-inspct, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 55, Self-emp-not-inc, 105582, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 2228, 0, 50, United-States, <=50K 46, Private, 169324, HS-grad, 9, Separated, Other-service, Not-in-family, Black, Female, 0, 0, 45, Jamaica, <=50K 44, State-gov, 98989, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Amer-Indian-Eskimo, Male, 0, 0, 38, United-States, >50K 30, Self-emp-not-inc, 113838, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 3137, 0, 60, Germany, <=50K 24, Private, 143436, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 24, United-States, <=50K 32, Private, 143604, 10th, 6, Married-spouse-absent, Other-service, Not-in-family, Black, Female, 0, 0, 37, United-States, <=50K 35, Private, 226311, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 67, Private, 94610, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 30, United-States, >50K 56, Self-emp-not-inc, 26716, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 20, United-States, >50K 26, Private, 160261, Masters, 14, Never-married, Prof-specialty, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 20, India, <=50K 46, Private, 117310, Assoc-acdm, 12, Widowed, Tech-support, Unmarried, White, Female, 6497, 0, 40, United-States, <=50K 52, Private, 154342, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, >50K 38, Self-emp-not-inc, 89202, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 174704, HS-grad, 9, Divorced, Sales, Unmarried, Black, Male, 0, 0, 50, United-States, <=50K 53, Private, 153486, HS-grad, 9, Separated, Transport-moving, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 27, Private, 360097, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 39, Private, 230356, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 163870, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 199753, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, >50K 20, Private, 333505, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 30, Nicaragua, <=50K 60, Local-gov, 149281, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Private, 138514, Assoc-voc, 11, Divorced, Tech-support, Unmarried, Black, Female, 0, 0, 48, United-States, <=50K 57, Federal-gov, 66504, Prof-school, 15, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 59, Private, 206487, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Private, 170020, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 217605, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Wife, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 145711, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 72, United-States, >50K 17, Private, 169155, 12th, 8, Never-married, Other-service, Own-child, White, Male, 0, 0, 35, United-States, <=50K 45, Private, 34127, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 18, Private, 110142, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 52, Private, 222646, 12th, 8, Separated, Machine-op-inspct, Other-relative, White, Female, 0, 0, 40, Cuba, <=50K 18, Private, 182643, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 9, United-States, <=50K 20, Private, 303565, Some-college, 10, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 40, Germany, <=50K 34, Private, 140092, HS-grad, 9, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 178811, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, Black, Female, 0, 0, 20, United-States, <=50K 18, ?, 267399, 12th, 8, Never-married, ?, Own-child, White, Female, 0, 0, 12, United-States, <=50K 17, Local-gov, 192387, 9th, 5, Never-married, Other-service, Own-child, White, Male, 0, 0, 45, United-States, <=50K 30, Federal-gov, 127610, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 29, Private, 258862, Bachelors, 13, Never-married, Craft-repair, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 30, Private, 225231, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 8614, 0, 50, United-States, >50K 18, Private, 174926, 9th, 5, Never-married, Other-service, Own-child, White, Male, 0, 0, 15, ?, <=50K 50, State-gov, 238187, Bachelors, 13, Divorced, Adm-clerical, Not-in-family, Black, Female, 0, 0, 37, United-States, <=50K 22, Private, 191444, HS-grad, 9, Never-married, Sales, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 198822, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 35, United-States, <=50K 39, Self-emp-not-inc, 251323, 9th, 5, Married-civ-spouse, Farming-fishing, Other-relative, White, Male, 0, 0, 40, Cuba, <=50K 20, Private, 168187, Some-college, 10, Never-married, Other-service, Other-relative, White, Female, 4416, 0, 25, United-States, <=50K 62, Private, 370881, Assoc-acdm, 12, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 7, United-States, <=50K 32, Private, 198183, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 38, Private, 210610, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Private, 269182, Some-college, 10, Separated, Tech-support, Unmarried, Black, Female, 3887, 0, 40, United-States, <=50K 55, Private, 141727, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 3464, 0, 40, United-States, <=50K 38, Private, 185848, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 70, United-States, >50K 34, Private, 46746, 11th, 7, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 28, Private, 120475, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 26, Private, 135845, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 37, United-States, <=50K 41, Private, 310255, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, State-gov, 379885, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 40, United-States, >50K 75, Self-emp-not-inc, 31428, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 3456, 0, 40, United-States, <=50K 21, Private, 211013, Assoc-voc, 11, Married-civ-spouse, Other-service, Other-relative, White, Female, 0, 0, 50, Mexico, <=50K 50, Private, 175029, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, >50K 49, Self-emp-inc, 119539, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, ?, >50K 26, Private, 247025, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 65, United-States, <=50K 39, Private, 252327, 7th-8th, 4, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, Mexico, <=50K 24, Self-emp-not-inc, 375313, Some-college, 10, Never-married, Prof-specialty, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 56, Private, 107165, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 18, United-States, <=50K 17, Private, 108470, 11th, 7, Never-married, Other-service, Own-child, Black, Male, 0, 0, 17, United-States, <=50K 37, Private, 150057, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 52, United-States, >50K 23, Private, 189468, Assoc-voc, 11, Married-civ-spouse, Machine-op-inspct, Own-child, White, Female, 0, 0, 30, United-States, <=50K 28, ?, 198393, HS-grad, 9, Never-married, ?, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 57, Self-emp-not-inc, 181031, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 42, Local-gov, 569930, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, >50K 25, Private, 27411, Bachelors, 13, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 147397, Bachelors, 13, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 39, Private, 242922, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 54, Private, 154949, 11th, 7, Married-civ-spouse, Other-service, Wife, Black, Female, 0, 0, 40, United-States, >50K 41, Self-emp-inc, 423217, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 43, Federal-gov, 195385, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 19, Private, 100009, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 191628, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 340880, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, Philippines, >50K 19, Private, 207173, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 30, United-States, <=50K 33, Private, 48010, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 229051, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 52, United-States, <=50K 49, Private, 193366, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 65, United-States, >50K 31, Private, 57781, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 69, ?, 121136, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 13, United-States, <=50K 41, Private, 433989, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 4386, 0, 60, United-States, >50K 24, Private, 136687, HS-grad, 9, Separated, Machine-op-inspct, Unmarried, Other, Female, 0, 0, 40, United-States, <=50K 45, State-gov, 154117, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 38, United-States, >50K 63, Private, 294009, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 45, United-States, >50K 75, Private, 239038, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 16, United-States, <=50K 34, Private, 244064, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 69, Private, 128348, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 9386, 0, 50, United-States, >50K 33, Private, 66278, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 162643, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 43, United-States, <=50K 45, Private, 179659, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 3103, 0, 40, United-States, >50K 18, Private, 205218, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 48, Private, 154033, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 0, 0, 52, United-States, <=50K 43, Private, 158528, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 366219, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 1848, 60, United-States, >50K 35, Private, 301862, HS-grad, 9, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 34, Private, 228406, Some-college, 10, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 48, Private, 120131, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 70, United-States, >50K 54, Local-gov, 127943, HS-grad, 9, Widowed, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 57, Private, 301514, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 156980, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 60, United-States, <=50K 28, Private, 124685, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, Amer-Indian-Eskimo, Male, 0, 0, 55, United-States, <=50K 51, Private, 305673, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Canada, >50K 34, Local-gov, 31391, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 53, United-States, >50K 41, Local-gov, 33658, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 45, United-States, >50K 21, Private, 211391, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 27, United-States, <=50K 26, Private, 402998, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 58, United-States, >50K 66, Private, 78855, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 40, Private, 320451, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 1977, 45, Hong, >50K 48, Private, 49278, Assoc-acdm, 12, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 44, ?, 248876, Bachelors, 13, Divorced, ?, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 41, Private, 242586, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 359696, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 15024, 0, 60, United-States, >50K 55, Local-gov, 296085, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, >50K 43, Private, 233130, Bachelors, 13, Divorced, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 51, Private, 189511, Assoc-voc, 11, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 50, Germany, >50K 31, Private, 124420, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Self-emp-not-inc, 67072, Bachelors, 13, Married-spouse-absent, Craft-repair, Not-in-family, White, Male, 6849, 0, 60, United-States, <=50K 51, Private, 194908, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 31, Local-gov, 94991, HS-grad, 9, Divorced, Other-service, Unmarried, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 18, Private, 194561, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 37, United-States, <=50K 60, Private, 75726, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 1092, 40, United-States, <=50K 29, Private, 60722, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 33, Private, 59944, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 220840, 5th-6th, 3, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, Mexico, <=50K 40, Self-emp-inc, 104235, Masters, 14, Never-married, Other-service, Own-child, White, Male, 0, 0, 99, United-States, <=50K 57, Private, 142714, Some-college, 10, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 55, Local-gov, 110490, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 60, United-States, <=50K 40, Self-emp-not-inc, 154076, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 26, State-gov, 130557, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 29, Private, 107108, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 30, Private, 207172, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, Mexico, <=50K 29, Private, 304595, Masters, 14, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 43, Private, 475322, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 65, Private, 107620, 11th, 7, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 8, United-States, <=50K 19, Private, 301911, Some-college, 10, Never-married, Sales, Own-child, Asian-Pac-Islander, Male, 0, 0, 35, Laos, <=50K 35, Private, 267866, HS-grad, 9, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 1887, 50, Iran, >50K 28, Private, 269786, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 167474, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 115023, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1887, 60, United-States, >50K 63, Local-gov, 86590, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 32, United-States, <=50K 47, State-gov, 187087, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 184307, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 225859, Some-college, 10, Never-married, Transport-moving, Own-child, White, Male, 2907, 0, 30, United-States, <=50K 29, Private, 57889, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 59, Private, 157932, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 187830, Masters, 14, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 62, United-States, >50K 49, Private, 251180, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 2407, 0, 50, United-States, <=50K 60, Private, 317083, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 35, Self-emp-not-inc, 190895, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 48, Federal-gov, 328606, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, ?, 403860, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 215479, HS-grad, 9, Separated, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 56, Private, 157639, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 26, Private, 152129, 12th, 8, Never-married, Other-service, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 53, Private, 239284, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 234302, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 58, Private, 218724, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 61, Private, 106330, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 35032, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 60, United-States, <=50K 22, Private, 234641, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 170730, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 50, United-States, >50K 31, Private, 218322, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 90, Private, 47929, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 142411, Assoc-voc, 11, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 22, ?, 219122, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 132887, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, Black, Male, 3411, 0, 40, Jamaica, <=50K 34, State-gov, 44464, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 28, Private, 180928, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 5013, 0, 55, United-States, <=50K 22, ?, 199426, Some-college, 10, Never-married, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 139703, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 33, Private, 202642, Bachelors, 13, Separated, Prof-specialty, Other-relative, Black, Female, 0, 0, 40, Jamaica, <=50K 17, Private, 160049, 10th, 6, Never-married, Other-service, Own-child, White, Female, 0, 0, 12, United-States, <=50K 38, Private, 239755, 11th, 7, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 60, Private, 152369, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 34, Private, 42900, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 72, ?, 117017, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 8, United-States, <=50K 57, Private, 175017, 5th-6th, 3, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Italy, <=50K 39, Private, 342642, HS-grad, 9, Divorced, Sales, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 50, Self-emp-not-inc, 143730, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 80, United-States, <=50K 45, Private, 191098, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, China, <=50K 37, Private, 208106, Bachelors, 13, Separated, Exec-managerial, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 27, Private, 167737, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 43, Private, 315971, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, >50K 41, Private, 142717, Some-college, 10, Divorced, Tech-support, Unmarried, Black, Female, 0, 0, 36, United-States, <=50K 20, Private, 190227, Masters, 14, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 25, United-States, <=50K 44, Private, 79864, Masters, 14, Separated, Exec-managerial, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 50, Private, 34067, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 54, Private, 222882, HS-grad, 9, Widowed, Exec-managerial, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 31, Private, 44464, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 1564, 60, United-States, >50K 33, Private, 256062, Some-college, 10, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 35, Puerto-Rico, <=50K 22, Private, 251073, 9th, 5, Never-married, Other-service, Own-child, White, Male, 0, 0, 50, United-States, <=50K 46, Private, 149949, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 165235, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, >50K 22, ?, 243190, Some-college, 10, Never-married, ?, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, China, <=50K 59, ?, 160662, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 2407, 0, 60, United-States, <=50K 57, Self-emp-not-inc, 175942, Some-college, 10, Widowed, Exec-managerial, Other-relative, White, Male, 0, 0, 25, United-States, <=50K 26, Private, 212793, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 52, Local-gov, 153312, Assoc-acdm, 12, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 55, Local-gov, 173296, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 47, Private, 120131, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 19, Private, 117444, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 226196, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 202872, Assoc-acdm, 12, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 42, Private, 176716, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 39, Private, 82540, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, <=50K 17, ?, 41643, 11th, 7, Never-married, ?, Own-child, White, Female, 0, 0, 15, United-States, <=50K 26, Private, 197292, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 26, Private, 76491, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 20, United-States, <=50K 50, Self-emp-inc, 101094, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, <=50K 46, Self-emp-not-inc, 119944, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 18, Private, 141626, Some-college, 10, Never-married, Tech-support, Own-child, White, Male, 2176, 0, 20, United-States, <=50K 26, Private, 122575, Bachelors, 13, Never-married, Exec-managerial, Unmarried, Asian-Pac-Islander, Male, 0, 0, 60, Vietnam, <=50K 32, Private, 194740, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 1902, 40, United-States, >50K 50, Private, 263200, 5th-6th, 3, Married-spouse-absent, Other-service, Unmarried, White, Female, 0, 0, 34, Mexico, <=50K 47, Local-gov, 140644, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 52, Private, 202115, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 25, United-States, <=50K 25, Federal-gov, 27142, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Local-gov, 318046, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 276369, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 30, Private, 67187, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, Amer-Indian-Eskimo, Female, 0, 0, 8, United-States, <=50K 23, Private, 133582, 1st-4th, 2, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 36, Mexico, <=50K 23, Private, 216672, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 30, ?, <=50K 32, Private, 45796, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, <=50K 29, Self-emp-inc, 31778, HS-grad, 9, Separated, Prof-specialty, Other-relative, White, Male, 0, 0, 25, United-States, <=50K 40, Private, 190044, Assoc-acdm, 12, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, State-gov, 144351, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 17, ?, 172145, 10th, 6, Never-married, ?, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 55, Private, 193130, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 59, Local-gov, 140478, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 56, Private, 122390, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 15024, 0, 40, United-States, >50K 23, Private, 116830, 12th, 8, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 37, Local-gov, 117683, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 106491, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, <=50K 22, ?, 39803, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 363053, 9th, 5, Never-married, Priv-house-serv, Unmarried, White, Female, 0, 0, 24, Mexico, <=50K 21, Private, 54472, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 47, Local-gov, 200471, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 5178, 0, 40, United-States, >50K 38, Private, 54317, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 60, United-States, <=50K 62, Local-gov, 113443, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 10520, 0, 33, United-States, >50K 27, Private, 159623, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, ?, 161235, Assoc-voc, 11, Never-married, ?, Own-child, White, Male, 0, 0, 90, United-States, <=50K 27, Private, 247978, HS-grad, 9, Never-married, Other-service, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 40, Private, 305846, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 22, Self-emp-not-inc, 214014, Some-college, 10, Never-married, Sales, Own-child, Black, Male, 99999, 0, 55, United-States, >50K 33, Private, 226525, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 28, Private, 247819, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 5, United-States, <=50K 28, Private, 194940, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 289991, HS-grad, 9, Never-married, Transport-moving, Unmarried, White, Male, 0, 0, 55, United-States, <=50K 46, Private, 585361, 9th, 5, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 91145, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 65, ?, 231604, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 45, Germany, <=50K 28, Private, 273269, Some-college, 10, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 39, Private, 202683, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 159179, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 28952, Some-college, 10, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 39, United-States, <=50K 25, ?, 214925, 10th, 6, Never-married, ?, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 63, Private, 163708, 9th, 5, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 56, Private, 200235, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, >50K 46, Private, 109209, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 19, Private, 166153, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 30, United-States, <=50K 56, Local-gov, 268213, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 35, ?, >50K 31, Private, 69056, HS-grad, 9, Divorced, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 51, State-gov, 237141, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 17, Private, 277541, 11th, 7, Never-married, Sales, Own-child, White, Male, 0, 0, 5, United-States, <=50K 27, Local-gov, 289039, Some-college, 10, Never-married, Protective-serv, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 30, Private, 134737, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 45, United-States, <=50K 18, Private, 56613, Some-college, 10, Never-married, Protective-serv, Own-child, White, Female, 0, 0, 20, United-States, <=50K 41, Private, 36699, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 4650, 0, 40, United-States, <=50K 40, Local-gov, 333530, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 40, United-States, >50K 35, Private, 185366, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 29, Private, 154017, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 10, United-States, <=50K 27, Private, 215504, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 1848, 55, United-States, >50K 25, Private, 222539, 10th, 6, Never-married, Transport-moving, Not-in-family, White, Male, 2597, 0, 50, United-States, <=50K 53, Private, 191565, 1st-4th, 2, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 40, Dominican-Republic, <=50K 53, Private, 111939, Bachelors, 13, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 35, United-States, <=50K 26, State-gov, 53903, HS-grad, 9, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 41, Private, 146659, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 70, United-States, <=50K 28, Private, 194200, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 70, United-States, <=50K 48, State-gov, 78529, Masters, 14, Separated, Prof-specialty, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 22, Private, 194829, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 40, Federal-gov, 330174, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 40, United-States, >50K 52, Self-emp-inc, 230767, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 60, Cuba, >50K 53, Local-gov, 137250, Masters, 14, Widowed, Prof-specialty, Unmarried, Black, Female, 0, 1669, 35, United-States, <=50K 40, Private, 254478, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 50, United-States, >50K 57, Private, 300908, Assoc-acdm, 12, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 75, United-States, <=50K 53, Self-emp-not-inc, 187830, Assoc-voc, 11, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Poland, <=50K 23, Private, 201138, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 8, United-States, <=50K 31, Self-emp-not-inc, 44503, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 381357, 9th, 5, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 28, United-States, <=50K 25, Private, 311124, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 37, Private, 96330, Some-college, 10, Never-married, Exec-managerial, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 50, Private, 228238, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 34, Self-emp-not-inc, 56964, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 35, United-States, <=50K 37, Private, 127772, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 52, Private, 386397, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 29, Self-emp-not-inc, 404998, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 90, United-States, <=50K 49, Private, 34545, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1887, 40, United-States, >50K 31, Private, 157886, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 101299, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Self-emp-not-inc, 134447, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 70, United-States, <=50K 27, Private, 191822, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 50, United-States, <=50K 23, Private, 70919, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 266343, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 46, United-States, <=50K 28, Private, 87239, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 31, Local-gov, 236487, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, Germany, <=50K 30, Private, 224147, HS-grad, 9, Never-married, Transport-moving, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 23, Private, 197200, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 60, United-States, <=50K 19, Private, 124265, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 50, United-States, <=50K 22, Private, 79980, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 25, United-States, <=50K 50, Private, 128814, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 64, ?, 208862, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 50, United-States, >50K 21, Private, 51262, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 35, United-States, <=50K 75, Self-emp-inc, 98116, Some-college, 10, Widowed, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 29, Private, 82393, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, Germany, <=50K 47, Private, 57534, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 20, Private, 218962, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 204752, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 243631, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 45, China, >50K 41, Private, 170299, Assoc-voc, 11, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 43, United-States, <=50K 23, Private, 60331, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 269318, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 5178, 0, 50, United-States, >50K 67, State-gov, 132819, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 41, United-States, >50K 21, Private, 119665, Some-college, 10, Never-married, Tech-support, Own-child, White, Male, 0, 0, 35, United-States, <=50K 38, Private, 150057, Some-college, 10, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 31, Private, 128567, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 19, ?, 230874, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 59, Self-emp-not-inc, 148526, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 160192, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 50, Local-gov, 74660, Some-college, 10, Widowed, Prof-specialty, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 60, Self-emp-inc, 142494, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 122042, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 28, Self-emp-inc, 37088, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 36, Private, 61778, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, >50K 21, ?, 176356, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 10, Germany, <=50K 27, Private, 123302, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, Poland, <=50K 18, Private, 89760, 12th, 8, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 44, Local-gov, 165304, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1485, 40, United-States, >50K 56, Private, 104945, 7th-8th, 4, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 40, United-States, <=50K 51, Self-emp-inc, 192973, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 40, United-States, >50K 48, Private, 97863, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, Italy, >50K 31, Private, 73585, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, <=50K 35, Private, 29145, Assoc-voc, 11, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 175232, HS-grad, 9, Divorced, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 325374, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Self-emp-not-inc, 107231, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1672, 65, United-States, <=50K 23, Private, 129345, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 25, United-States, <=50K 21, Private, 228395, Some-college, 10, Never-married, Sales, Other-relative, Black, Female, 0, 0, 20, United-States, <=50K 49, Private, 452402, Some-college, 10, Separated, Exec-managerial, Unmarried, Black, Female, 0, 0, 60, United-States, <=50K 51, Self-emp-inc, 338260, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 60, United-States, >50K 46, Private, 165138, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 109055, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 3137, 0, 45, United-States, <=50K 27, Private, 193122, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, ?, 425497, Assoc-acdm, 12, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 20, United-States, <=50K 48, Private, 191858, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 297155, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 29, Local-gov, 181282, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 50, Federal-gov, 111700, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 18, Private, 35065, HS-grad, 9, Never-married, Transport-moving, Not-in-family, Black, Male, 0, 0, 35, United-States, <=50K 37, Private, 298539, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 55, United-States, >50K 51, Self-emp-not-inc, 95435, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 31, Private, 162160, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 47, United-States, <=50K 29, Private, 176037, Assoc-voc, 11, Divorced, Tech-support, Not-in-family, Black, Male, 14344, 0, 40, United-States, >50K 39, Private, 314007, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 2051, 40, United-States, <=50K 48, Private, 197683, Some-college, 10, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 40, United-States, >50K 44, Private, 242521, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 7688, 0, 50, United-States, >50K 39, Private, 290321, 10th, 6, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Local-gov, 44064, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 35, United-States, <=50K 27, ?, 174163, Some-college, 10, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 40, United-States, >50K 42, Private, 374790, 9th, 5, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 231562, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 33, United-States, <=50K 27, Private, 376150, Some-college, 10, Married-spouse-absent, Sales, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 51, Private, 99987, 10th, 6, Separated, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 27, Self-emp-not-inc, 120126, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 60, Self-emp-not-inc, 33717, 11th, 7, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 36, Private, 132879, 1st-4th, 2, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Italy, <=50K 45, Private, 304570, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 60, China, >50K 40, Private, 100292, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 52, United-States, >50K 63, Private, 117473, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 4386, 0, 40, United-States, >50K 41, Private, 239833, HS-grad, 9, Married-spouse-absent, Transport-moving, Unmarried, Black, Male, 0, 0, 50, United-States, <=50K 53, ?, 155233, 12th, 8, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 40, Italy, <=50K 34, Private, 130369, HS-grad, 9, Divorced, Transport-moving, Unmarried, White, Female, 1151, 0, 48, Germany, <=50K 34, Private, 347166, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 502752, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, >50K 22, State-gov, 255575, Assoc-acdm, 12, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 15, United-States, <=50K 49, Private, 277946, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 43, ?, 214541, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 35, United-States, <=50K 36, Private, 143123, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 27, Private, 69132, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 37, United-States, <=50K 52, Self-emp-not-inc, 34973, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 1887, 60, United-States, >50K 29, Private, 236992, HS-grad, 9, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 50, United-States, <=50K 27, Private, 492263, 10th, 6, Separated, Machine-op-inspct, Own-child, White, Male, 0, 0, 35, Mexico, <=50K 42, Private, 180019, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 65, United-States, <=50K 49, Self-emp-not-inc, 47086, Bachelors, 13, Widowed, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 222853, Some-college, 10, Never-married, Craft-repair, Unmarried, White, Male, 0, 0, 50, United-States, <=50K 22, Private, 344176, HS-grad, 9, Never-married, Sales, Unmarried, White, Male, 0, 0, 20, United-States, <=50K 30, Self-emp-not-inc, 223212, Bachelors, 13, Never-married, Sales, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 110981, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 162688, Assoc-voc, 11, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 45, Self-emp-inc, 181307, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 43, United-States, >50K 39, Private, 148903, HS-grad, 9, Divorced, Sales, Not-in-family, White, Female, 4687, 0, 50, United-States, >50K 43, Private, 306440, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 66, France, <=50K 18, Private, 210311, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 53, Private, 127117, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 74, Private, 54732, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 20, United-States, >50K 39, Private, 271521, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 48, Philippines, >50K 33, ?, 216908, 10th, 6, Never-married, ?, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 543922, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 42, United-States, >50K 21, Private, 766115, 10th, 6, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 35, United-States, <=50K 65, ?, 52728, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 284166, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 1564, 50, United-States, >50K 49, Private, 122206, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 25, United-States, <=50K 20, ?, 95989, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 334039, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 44, United-States, >50K 46, Self-emp-not-inc, 225456, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 112847, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 7298, 0, 32, United-States, >50K 61, Self-emp-not-inc, 171840, HS-grad, 9, Widowed, Prof-specialty, Unmarried, White, Female, 0, 0, 16, United-States, <=50K 48, Private, 180695, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 44, Private, 121012, 9th, 5, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 37, Self-emp-inc, 126569, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 45, Private, 227791, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 1740, 50, United-States, <=50K 51, Self-emp-not-inc, 290290, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 33, Local-gov, 251521, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 55, Self-emp-not-inc, 41938, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 8, United-States, <=50K 25, Private, 27678, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 60, United-States, <=50K 26, Private, 133756, HS-grad, 9, Divorced, Farming-fishing, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 54, Private, 215990, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 461337, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 33, United-States, <=50K 39, Local-gov, 344855, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 1977, 20, United-States, >50K 20, State-gov, 214542, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 258170, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, Federal-gov, 242147, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, Other, Male, 0, 0, 45, United-States, <=50K 42, Private, 235700, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 278130, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, Private, 261241, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, >50K 60, Private, 85995, Masters, 14, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 0, 50, South, >50K 42, Private, 340885, HS-grad, 9, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 0, 44, United-States, <=50K 42, Private, 152889, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 46, Private, 195023, HS-grad, 9, Married-spouse-absent, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, Columbia, <=50K 52, State-gov, 109600, Masters, 14, Married-spouse-absent, Exec-managerial, Unmarried, White, Female, 4787, 0, 44, United-States, >50K 27, ?, 249463, Assoc-voc, 11, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 20, United-States, <=50K 43, Private, 158177, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 43, State-gov, 47818, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 391468, 11th, 7, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 52, Local-gov, 199995, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7298, 0, 60, United-States, >50K 31, Private, 231043, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 38, ?, 281768, 7th-8th, 4, Divorced, ?, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 44, Private, 267790, 9th, 5, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 27, Private, 217379, Some-college, 10, Divorced, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 50, Private, 421561, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 50953, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 138504, Some-college, 10, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 36, State-gov, 177064, Some-college, 10, Never-married, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 103064, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Female, 3674, 0, 40, United-States, <=50K 59, Private, 184493, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 104089, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 23, Private, 149204, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 405284, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 1340, 42, United-States, <=50K 25, Local-gov, 137296, Assoc-acdm, 12, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 38, United-States, <=50K 40, Private, 87771, HS-grad, 9, Married-civ-spouse, Craft-repair, Wife, White, Female, 0, 1628, 45, United-States, <=50K 38, State-gov, 125499, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 7688, 0, 60, India, >50K 31, Private, 59083, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 35, United-States, <=50K 28, Local-gov, 138332, Doctorate, 16, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 198914, HS-grad, 9, Never-married, Sales, Unmarried, Black, Male, 0, 0, 25, United-States, <=50K 46, Local-gov, 238162, Assoc-acdm, 12, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 1887, 50, United-States, >50K 29, Private, 123677, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, Asian-Pac-Islander, Female, 0, 0, 40, Laos, <=50K 38, Federal-gov, 325538, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 53, Private, 251063, Some-college, 10, Separated, Exec-managerial, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 33, Private, 51471, HS-grad, 9, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 1902, 40, United-States, >50K 39, Private, 175681, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 60, ?, <=50K 44, Private, 165599, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, <=50K 46, Private, 149640, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Male, 0, 0, 45, England, >50K 30, Private, 143526, Bachelors, 13, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 211160, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 342989, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 62, Self-emp-not-inc, 173631, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 70, United-States, <=50K 25, Private, 141876, HS-grad, 9, Married-spouse-absent, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 45, Private, 137604, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 129232, Some-college, 10, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 64, Federal-gov, 271550, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 456922, Bachelors, 13, Divorced, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 60, Private, 232242, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 352188, HS-grad, 9, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 114967, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 201981, HS-grad, 9, Divorced, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 32, State-gov, 159247, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 24, Private, 125905, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 186824, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Local-gov, 121012, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 58, Private, 110844, Masters, 14, Widowed, Sales, Not-in-family, White, Female, 0, 0, 27, United-States, <=50K 23, Private, 143003, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 1887, 50, India, >50K 31, Federal-gov, 59732, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 28, Private, 178489, Bachelors, 13, Never-married, Exec-managerial, Unmarried, Black, Female, 0, 0, 45, ?, <=50K 41, ?, 252127, Some-college, 10, Widowed, ?, Unmarried, Black, Female, 0, 0, 20, United-States, <=50K 37, Private, 109633, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 16, United-States, >50K 19, Private, 160811, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 38, United-States, <=50K 27, Self-emp-not-inc, 365110, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 61, Self-emp-not-inc, 113080, 9th, 5, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 58, United-States, >50K 39, Private, 206074, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 25, Private, 173062, Bachelors, 13, Never-married, Handlers-cleaners, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 58, Private, 117273, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 27, Self-emp-not-inc, 153805, Some-college, 10, Married-civ-spouse, Transport-moving, Other-relative, Other, Male, 0, 0, 50, Ecuador, >50K 51, Private, 293802, 5th-6th, 3, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male, 0, 0, 52, United-States, <=50K 43, Local-gov, 153132, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 40, United-States, >50K 46, Private, 166809, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 67, ?, 34122, 5th-6th, 3, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Local-gov, 231725, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 63210, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 15, United-States, <=50K 35, Private, 108293, Bachelors, 13, Widowed, Prof-specialty, Unmarried, White, Female, 0, 0, 32, United-States, >50K 57, Private, 116878, 1st-4th, 2, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Italy, <=50K 40, Private, 110622, Prof-school, 15, Married-civ-spouse, Adm-clerical, Other-relative, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 42, Local-gov, 180318, 10th, 6, Never-married, Farming-fishing, Unmarried, White, Male, 0, 0, 35, United-States, <=50K 67, Self-emp-inc, 112318, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 252079, Bachelors, 13, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 7688, 0, 44, United-States, >50K 30, Private, 27153, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 26, Private, 73312, 11th, 7, Never-married, Machine-op-inspct, Unmarried, White, Female, 0, 0, 15, United-States, <=50K 51, Private, 145409, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 167882, Some-college, 10, Widowed, Other-service, Other-relative, Black, Female, 0, 0, 45, Haiti, <=50K 24, Private, 236696, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Own-child, White, Male, 0, 0, 35, United-States, <=50K 48, Self-emp-not-inc, 28791, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 50, United-States, <=50K 34, State-gov, 118551, Bachelors, 13, Married-civ-spouse, Tech-support, Own-child, White, Female, 5178, 0, 25, ?, >50K 70, Private, 187292, Bachelors, 13, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 6418, 0, 40, United-States, >50K 35, Private, 189922, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, ?, 584259, Masters, 14, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 2, United-States, >50K 26, Private, 173992, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 64, Private, 253759, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 3, United-States, <=50K 26, Private, 111243, HS-grad, 9, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 39, Self-emp-not-inc, 147850, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 30, United-States, <=50K 55, Private, 171015, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 36, United-States, <=50K 23, Private, 118023, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 45, ?, <=50K 33, Self-emp-not-inc, 361497, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 137290, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 28, Local-gov, 401886, HS-grad, 9, Never-married, Adm-clerical, Other-relative, White, Male, 0, 0, 20, United-States, <=50K 50, Private, 201882, Masters, 14, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 30, United-States, <=50K 26, Local-gov, 30793, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 55, United-States, >50K 44, Federal-gov, 139161, Assoc-acdm, 12, Divorced, Adm-clerical, Not-in-family, Black, Female, 0, 1741, 40, United-States, <=50K 51, Private, 210736, HS-grad, 9, Married-spouse-absent, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 167781, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 50, United-States, <=50K 37, Private, 103986, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 39, United-States, >50K 29, Private, 144592, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 24, Private, 493034, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 27, Private, 184078, Assoc-voc, 11, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 191814, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 24, Private, 329852, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 223660, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 47, Private, 177087, Some-college, 10, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 50, United-States, >50K 30, Private, 143766, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 35, Private, 234271, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 39, Federal-gov, 314822, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, <=50K 42, Private, 195584, Assoc-acdm, 12, Separated, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 70, Self-emp-inc, 207938, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 2377, 50, United-States, >50K 41, Private, 126850, Prof-school, 15, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 36, Private, 279485, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 44, Private, 267717, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 42, United-States, >50K 42, ?, 175935, HS-grad, 9, Separated, ?, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 163665, Some-college, 10, Never-married, Transport-moving, Own-child, White, Female, 0, 0, 17, United-States, <=50K 29, Private, 200468, 10th, 6, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 91501, HS-grad, 9, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 182771, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, >50K 59, Self-emp-not-inc, 56392, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 1579, 60, United-States, <=50K 31, Private, 20511, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 21, Private, 538822, HS-grad, 9, Never-married, Other-service, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 26, Private, 332008, Some-college, 10, Never-married, Craft-repair, Unmarried, Asian-Pac-Islander, Male, 0, 0, 37, Taiwan, <=50K 57, Self-emp-inc, 220789, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 59, Self-emp-not-inc, 114760, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 20, United-States, >50K 87, ?, 90338, HS-grad, 9, Widowed, ?, Not-in-family, White, Male, 0, 0, 2, United-States, <=50K 25, Private, 181576, Some-college, 10, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 39, Private, 198841, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 45, United-States, >50K 53, Private, 53197, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 3103, 0, 40, United-States, >50K 32, State-gov, 542265, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 193026, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 25505, Assoc-voc, 11, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 35, United-States, <=50K 17, Private, 375657, 11th, 7, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 30, United-States, <=50K 44, Private, 201599, 11th, 7, Never-married, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 23, Private, 181820, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 20, United-States, <=50K 57, Private, 334224, Some-college, 10, Married-civ-spouse, Craft-repair, Wife, White, Female, 9386, 0, 40, United-States, >50K 30, State-gov, 54318, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Self-emp-not-inc, 141388, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 55, United-States, <=50K 54, Self-emp-not-inc, 57101, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 35, United-States, <=50K 44, Private, 168515, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, Germany, <=50K 60, Private, 163665, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 16, United-States, >50K 28, Private, 207513, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 7298, 0, 42, United-States, >50K 39, Private, 293291, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 50, United-States, >50K 55, Private, 70088, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 199346, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 50, United-States, >50K 55, Local-gov, 143949, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 3103, 0, 45, United-States, >50K 33, Private, 207201, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 55, United-States, >50K 30, Private, 430283, HS-grad, 9, Married-civ-spouse, Adm-clerical, Wife, White, Female, 7298, 0, 40, United-States, >50K 40, Local-gov, 293809, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 20, United-States, <=50K 30, Private, 378009, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 40, Private, 226608, Some-college, 10, Divorced, Tech-support, Not-in-family, White, Male, 0, 0, 30, Guatemala, >50K 24, Private, 314182, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 18, Private, 170544, 11th, 7, Never-married, Sales, Own-child, White, Male, 0, 0, 20, United-States, <=50K 18, Private, 94196, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 25, United-States, <=50K 49, Private, 193047, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 42, Private, 112607, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 28, Local-gov, 146949, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 309513, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 48, Self-emp-not-inc, 191389, Some-college, 10, Separated, Sales, Unmarried, White, Female, 0, 0, 50, United-States, <=50K 24, Private, 213902, 7th-8th, 4, Never-married, Priv-house-serv, Own-child, White, Female, 0, 0, 32, El-Salvador, <=50K 73, Self-emp-not-inc, 46514, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 25, United-States, <=50K 35, Private, 75855, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 7298, 0, 40, ?, >50K 23, Private, 38707, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 60, United-States, >50K 19, Private, 188568, Some-college, 10, Never-married, Priv-house-serv, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 215014, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 35, Mexico, <=50K 27, Private, 184477, 12th, 8, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Self-emp-not-inc, 204235, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 31, Private, 39054, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 20, United-States, <=50K 64, Self-emp-inc, 272531, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 45, Private, 358701, 12th, 8, Never-married, Other-service, Own-child, White, Male, 0, 0, 10, Mexico, <=50K 47, Private, 217750, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 35, United-States, <=50K 22, Private, 200374, HS-grad, 9, Never-married, Machine-op-inspct, Other-relative, White, Male, 0, 0, 35, United-States, <=50K 24, Private, 498349, Bachelors, 13, Never-married, Transport-moving, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 69, State-gov, 170458, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 20, United-States, <=50K 40, Self-emp-not-inc, 57233, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 45, Private, 188432, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Self-emp-not-inc, 33300, Assoc-acdm, 12, Never-married, Farming-fishing, Other-relative, White, Male, 10520, 0, 45, United-States, >50K 31, Private, 225779, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 48, Private, 46677, Assoc-acdm, 12, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 42, United-States, <=50K 41, Private, 227968, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, Black, Female, 0, 0, 35, Haiti, >50K 34, Private, 85355, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 207120, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Local-gov, 229223, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Wife, White, Female, 7688, 0, 36, United-States, >50K 20, Private, 224640, Assoc-acdm, 12, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 139012, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, >50K 40, Federal-gov, 130749, Some-college, 10, Divorced, Exec-managerial, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 28, Private, 204516, 10th, 6, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 20, Private, 105479, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 41, Private, 197093, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 49, Self-emp-inc, 431245, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 24, Private, 155150, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, State-gov, 216035, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 388247, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 23, Private, 208908, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 23, Private, 259301, HS-grad, 9, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 42, Self-emp-not-inc, 69333, Assoc-voc, 11, Married-civ-spouse, Transport-moving, Husband, White, Male, 4386, 0, 80, United-States, >50K 34, Private, 167893, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 64, United-States, >50K 32, Federal-gov, 386877, Assoc-voc, 11, Never-married, Tech-support, Own-child, Black, Male, 4650, 0, 40, United-States, <=50K 54, Private, 146551, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 54, United-States, >50K 48, Private, 238360, Bachelors, 13, Separated, Adm-clerical, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 38, Private, 187748, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 48, State-gov, 50748, Bachelors, 13, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 50136, 5th-6th, 3, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, El-Salvador, <=50K 42, Private, 111483, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 50, United-States, >50K 31, Private, 298871, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, China, <=50K 27, Private, 147340, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 57, Private, 132704, Masters, 14, Separated, Prof-specialty, Not-in-family, White, Male, 10520, 0, 32, United-States, >50K 46, State-gov, 327786, Assoc-voc, 11, Divorced, Tech-support, Not-in-family, White, Female, 3325, 0, 42, United-States, <=50K 44, Federal-gov, 243636, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Local-gov, 194417, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 24, Private, 236696, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, Private, 337130, 1st-4th, 2, Married-spouse-absent, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 29, Private, 273051, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 52, Yugoslavia, >50K 38, Private, 186191, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, <=50K 33, Private, 268451, Some-college, 10, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 61, Private, 154600, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 4, United-States, <=50K 49, Local-gov, 405309, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 51, Self-emp-not-inc, 99185, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 42, Private, 191765, HS-grad, 9, Divorced, Other-service, Other-relative, Black, Female, 0, 0, 35, United-States, <=50K 21, Private, 253583, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 29, ?, 297054, HS-grad, 9, Divorced, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 204397, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 23, Private, 288771, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 52, Private, 173987, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Local-gov, 33662, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 7298, 0, 40, United-States, >50K 23, Private, 91658, Some-college, 10, Divorced, Handlers-cleaners, Own-child, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 226902, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 80, United-States, >50K 45, Private, 232586, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 51, Self-emp-not-inc, 291755, 7th-8th, 4, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 42, United-States, <=50K 29, ?, 207032, HS-grad, 9, Married-spouse-absent, ?, Unmarried, Black, Female, 0, 0, 42, Haiti, <=50K 23, Private, 161478, Some-college, 10, Never-married, Sales, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 73, Self-emp-not-inc, 109833, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 30, United-States, <=50K 47, Self-emp-not-inc, 229394, 11th, 7, Divorced, Exec-managerial, Unmarried, White, Female, 0, 0, 55, United-States, <=50K 61, ?, 69285, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 37, United-States, <=50K 26, Private, 491862, Assoc-voc, 11, Never-married, Exec-managerial, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 40, Private, 311534, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Self-emp-not-inc, 420895, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 47, United-States, <=50K 39, Private, 226374, 10th, 6, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 33, Federal-gov, 101345, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 48779, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 35, United-States, <=50K 42, Private, 152676, HS-grad, 9, Divorced, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 164877, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 44, United-States, <=50K 33, Private, 97521, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 88564, 5th-6th, 3, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 20, United-States, <=50K 33, Private, 188246, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 189185, HS-grad, 9, Divorced, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 42, State-gov, 163069, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 28, Private, 251905, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 29, Private, 112403, 5th-6th, 3, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, ?, <=50K 18, Private, 36882, 12th, 8, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 33, Self-emp-not-inc, 195891, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 36, Private, 194905, Bachelors, 13, Widowed, Prof-specialty, Unmarried, White, Female, 0, 0, 44, United-States, <=50K 33, Private, 133503, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 7688, 0, 48, United-States, >50K 40, Private, 31621, HS-grad, 9, Married-spouse-absent, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 57, Self-emp-not-inc, 413373, Doctorate, 16, Married-civ-spouse, Sales, Husband, White, Male, 0, 1902, 40, United-States, >50K 40, Private, 196029, HS-grad, 9, Divorced, Transport-moving, Unmarried, White, Male, 0, 0, 45, United-States, <=50K 36, Private, 107302, HS-grad, 9, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 50, United-States, <=50K 45, Private, 151267, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, Black, Female, 0, 0, 40, United-States, >50K 52, Private, 256861, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 24, Private, 82777, HS-grad, 9, Separated, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 147430, HS-grad, 9, Married-spouse-absent, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, ?, 60726, HS-grad, 9, Never-married, ?, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 46, Self-emp-not-inc, 165754, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 36, Private, 448337, HS-grad, 9, Separated, Sales, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 48, Private, 185079, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 36, Private, 418702, Assoc-voc, 11, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 48, Private, 41504, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, >50K 21, Private, 387335, Some-college, 10, Never-married, Tech-support, Own-child, White, Female, 0, 1719, 9, United-States, <=50K 18, Private, 261720, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 38, Private, 133963, Bachelors, 13, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 66, ?, 357750, 11th, 7, Widowed, ?, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 36, State-gov, 179488, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 7298, 0, 55, United-States, >50K 38, Private, 60135, HS-grad, 9, Never-married, Transport-moving, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 55, Self-emp-not-inc, 308746, Prof-school, 15, Widowed, Prof-specialty, Not-in-family, White, Male, 0, 0, 55, United-States, >50K 27, Private, 278720, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, >50K 22, State-gov, 477505, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 164711, Some-college, 10, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 208277, Some-college, 10, Never-married, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 39943, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 49, Private, 104542, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 286634, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 50, United-States, >50K 28, Private, 142712, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 26, Private, 336404, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 117983, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 41, United-States, <=50K 72, ?, 108796, Prof-school, 15, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, >50K 59, Private, 59469, Masters, 14, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, Iran, <=50K 37, Private, 171968, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 56, ?, 119254, 10th, 6, Divorced, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 278617, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 72338, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, >50K 49, Local-gov, 343231, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 80, United-States, <=50K 30, Private, 63910, HS-grad, 9, Married-civ-spouse, Sales, Own-child, Asian-Pac-Islander, Female, 0, 0, 40, United-States, <=50K 28, Private, 190350, 9th, 5, Married-civ-spouse, Protective-serv, Wife, Black, Female, 0, 0, 40, United-States, <=50K 25, State-gov, 176162, Bachelors, 13, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 37720, 10th, 6, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 421467, Assoc-acdm, 12, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 26, United-States, <=50K 36, Private, 138441, Some-college, 10, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 52, Private, 146767, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 20, ?, 369678, 12th, 8, Never-married, ?, Not-in-family, Other, Male, 0, 1602, 40, United-States, <=50K 25, Private, 160445, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 211695, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 102346, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 2415, 20, United-States, >50K 48, Private, 128796, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 39, Private, 111129, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Local-gov, 44566, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 118497, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 36, Private, 334291, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1887, 40, United-States, >50K 49, Private, 237920, Doctorate, 16, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 34, Local-gov, 136331, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, <=50K 28, Private, 187397, HS-grad, 9, Never-married, Other-service, Other-relative, Other, Male, 0, 0, 48, Mexico, <=50K 28, Self-emp-not-inc, 119793, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 24982, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 7688, 0, 40, United-States, >50K 26, Self-emp-not-inc, 231714, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 229272, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, >50K 66, ?, 68219, 9th, 5, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, Self-emp-not-inc, 268831, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 53, United-States, <=50K 45, Self-emp-not-inc, 149640, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 30, United-States, >50K 29, Private, 261725, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 74, Private, 161387, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 16, United-States, <=50K 61, Local-gov, 260167, HS-grad, 9, Widowed, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 200928, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 22, United-States, <=50K 53, Federal-gov, 155594, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 57, Self-emp-not-inc, 79539, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 41, Private, 469454, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 331482, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 43, Private, 225193, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 26, ?, 370727, Bachelors, 13, Married-civ-spouse, ?, Wife, White, Female, 0, 1977, 40, United-States, >50K 29, Private, 82393, HS-grad, 9, Married-civ-spouse, Other-service, Own-child, Asian-Pac-Islander, Male, 0, 0, 25, Philippines, <=50K 65, ?, 37170, 7th-8th, 4, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 20, United-States, <=50K 41, Private, 58484, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 40, United-States, <=50K 31, Local-gov, 156464, Bachelors, 13, Never-married, Prof-specialty, Other-relative, White, Male, 0, 0, 40, ?, <=50K 50, Private, 344621, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 52, Private, 174752, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 18, Self-emp-inc, 174202, HS-grad, 9, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 60, United-States, <=50K 26, Private, 261203, 7th-8th, 4, Never-married, Other-service, Unmarried, Other, Female, 0, 0, 30, ?, <=50K 57, Private, 316000, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 63, State-gov, 216871, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 1740, 40, United-States, <=50K 29, Private, 246933, HS-grad, 9, Never-married, Adm-clerical, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 32, Self-emp-not-inc, 112115, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7688, 0, 40, United-States, >50K 34, Private, 264651, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 43, Private, 99185, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 58, United-States, <=50K 39, Private, 176186, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 100219, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 45, United-States, <=50K 32, Private, 46691, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, State-gov, 297735, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 90, United-States, <=50K 40, Private, 132222, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 4386, 0, 50, United-States, >50K 25, Private, 189656, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 60, United-States, >50K 54, Local-gov, 224934, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 48, Self-emp-inc, 149218, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 70, United-States, >50K 51, Private, 158508, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 36, United-States, <=50K 67, State-gov, 261203, 7th-8th, 4, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 35, United-States, <=50K 17, Private, 309504, 10th, 6, Never-married, Sales, Unmarried, White, Female, 0, 0, 24, United-States, <=50K 24, State-gov, 324637, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 267426, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 68, ?, 229016, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 25, United-States, <=50K 54, Private, 46401, Some-college, 10, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 47, United-States, <=50K 32, Private, 114288, HS-grad, 9, Divorced, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 61, ?, 203849, Some-college, 10, Divorced, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 41, Federal-gov, 193882, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 311269, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, Private, 156117, Assoc-voc, 11, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 64, ?, 169917, 7th-8th, 4, Widowed, ?, Not-in-family, White, Female, 0, 0, 4, United-States, <=50K 51, Private, 222615, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 41, State-gov, 106900, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 7298, 0, 60, United-States, >50K 40, Federal-gov, 78036, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 65, United-States, >50K 27, Private, 380560, HS-grad, 9, Never-married, Farming-fishing, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 41, Private, 167106, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, Asian-Pac-Islander, Male, 3103, 0, 35, Philippines, >50K 51, Private, 289436, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 36, Private, 749636, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 34, Self-emp-inc, 154120, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 55, United-States, <=50K 43, Private, 105119, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, Federal-gov, 181081, HS-grad, 9, Divorced, Adm-clerical, Own-child, Black, Female, 0, 0, 20, United-States, <=50K 31, Private, 182237, 10th, 6, Separated, Transport-moving, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 102130, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 65, United-States, >50K 43, Private, 266324, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1902, 99, United-States, >50K 52, Private, 170562, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 240543, 11th, 7, Never-married, Other-service, Own-child, White, Female, 0, 0, 20, United-States, <=50K 37, Federal-gov, 187046, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 60, Private, 389254, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 47, Private, 179955, Some-college, 10, Widowed, Transport-moving, Unmarried, White, Female, 0, 0, 25, Outlying-US(Guam-USVI-etc), <=50K 21, Private, 197997, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 30, United-States, <=50K 34, Self-emp-inc, 343789, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 55, United-States, >50K 28, Private, 191088, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 1741, 52, United-States, <=50K 40, Local-gov, 141649, Assoc-voc, 11, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 433906, Assoc-acdm, 12, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 48, Private, 207982, Some-college, 10, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 46, Private, 175925, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 40, United-States, <=50K 58, Private, 85767, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 48, United-States, <=50K 32, Self-emp-inc, 281030, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 90, ?, 313986, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, >50K 38, Private, 396595, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, >50K 20, ?, 189203, Assoc-acdm, 12, Never-married, ?, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 43, Self-emp-not-inc, 163108, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 99, United-States, <=50K 17, Private, 141590, 11th, 7, Never-married, Priv-house-serv, Own-child, White, Female, 0, 0, 12, United-States, <=50K 36, Private, 137421, 12th, 8, Never-married, Transport-moving, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 45, ?, <=50K 36, Private, 67728, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 5013, 0, 40, Italy, <=50K 30, Private, 345522, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 3103, 0, 70, United-States, >50K 45, Private, 330087, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, Self-emp-not-inc, 204322, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 29, Private, 50295, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 48, United-States, <=50K 35, Self-emp-not-inc, 147258, Assoc-voc, 11, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 65, United-States, <=50K 19, Private, 194260, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 56, Private, 437727, 9th, 5, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 64, ?, 34100, Some-college, 10, Widowed, ?, Not-in-family, White, Male, 0, 0, 4, United-States, <=50K 62, ?, 186611, HS-grad, 9, Never-married, ?, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 280960, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 24, United-States, <=50K 33, Private, 33117, Assoc-acdm, 12, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 169628, Bachelors, 13, Never-married, Sales, Unmarried, Black, Female, 0, 0, 35, United-States, >50K 22, State-gov, 124942, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 45, United-States, <=50K 44, Private, 143368, Some-college, 10, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 55, United-States, <=50K 37, Private, 255621, HS-grad, 9, Separated, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 34, Self-emp-inc, 154227, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 75, United-States, <=50K 43, Private, 171438, Assoc-voc, 11, Separated, Sales, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 39, Private, 191524, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 30, Private, 377017, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 32, United-States, <=50K 58, Private, 192806, 7th-8th, 4, Never-married, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 33, United-States, <=50K 31, ?, 259120, Some-college, 10, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 10, United-States, <=50K 45, Local-gov, 234195, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 30, Private, 147596, Some-college, 10, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 42, Private, 147251, Some-college, 10, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 36, United-States, <=50K 50, Private, 176157, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 25, Local-gov, 176162, Assoc-voc, 11, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 30, United-States, <=50K 34, Private, 384150, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 50, Private, 107665, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 72, ?, 82635, 11th, 7, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 60, State-gov, 165827, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, <=50K 41, Private, 287306, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 60, United-States, >50K 71, Self-emp-not-inc, 78786, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 10, United-States, <=50K 40, Self-emp-not-inc, 33310, Prof-school, 15, Divorced, Other-service, Not-in-family, White, Female, 0, 2339, 35, United-States, <=50K 22, Private, 349368, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 30, United-States, <=50K 52, Private, 117674, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 30, Private, 310889, Some-college, 10, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 36, ?, 187167, HS-grad, 9, Separated, ?, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 40, Private, 379919, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Federal-gov, 34862, Assoc-acdm, 12, Married-civ-spouse, Sales, Husband, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 44, Private, 201723, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 45, United-States, >50K 38, Local-gov, 161463, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 0, 0, 40, United-States, >50K 46, Private, 186410, Prof-school, 15, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 57, Federal-gov, 62020, Prof-school, 15, Divorced, Exec-managerial, Not-in-family, Black, Male, 0, 0, 55, United-States, >50K 39, Private, 42044, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, Private, 170230, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 55, United-States, >50K 43, Private, 341358, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 22, Private, 199426, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 17, United-States, <=50K 44, Private, 89172, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 22, ?, 148955, Some-college, 10, Never-married, ?, Own-child, Asian-Pac-Islander, Female, 0, 0, 15, South, <=50K 37, Private, 140673, Some-college, 10, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, >50K 20, ?, 71788, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 18, United-States, <=50K 26, State-gov, 326033, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 80, United-States, <=50K 35, Private, 129305, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 28, Private, 171067, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 143582, Some-college, 10, Never-married, Adm-clerical, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 35, Japan, <=50K 17, ?, 171461, 10th, 6, Never-married, ?, Own-child, White, Female, 0, 0, 20, United-States, <=50K 18, Private, 257980, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 182866, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 44, Self-emp-inc, 69333, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 61, Private, 668362, 1st-4th, 2, Widowed, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 132879, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 61, Private, 181219, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1848, 40, United-States, >50K 19, ?, 166018, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 120518, HS-grad, 9, Widowed, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 19, Private, 183532, Some-college, 10, Never-married, Handlers-cleaners, Own-child, White, Male, 0, 0, 25, United-States, <=50K 45, Private, 49298, Bachelors, 13, Never-married, Tech-support, Own-child, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 157332, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 25, United-States, <=50K 37, Private, 213726, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 26, Private, 31143, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 17, ?, 256173, 10th, 6, Never-married, ?, Own-child, White, Female, 0, 0, 15, United-States, <=50K 26, Private, 184872, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 55, United-States, >50K 58, Private, 202652, HS-grad, 9, Separated, Other-service, Unmarried, White, Female, 0, 0, 40, Dominican-Republic, <=50K 61, ?, 101602, Doctorate, 16, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 25, United-States, >50K 64, Private, 60940, HS-grad, 9, Widowed, Sales, Not-in-family, White, Female, 8614, 0, 50, France, >50K 19, Private, 292590, HS-grad, 9, Married-civ-spouse, Sales, Other-relative, White, Female, 0, 0, 25, United-States, <=50K 36, Private, 141420, Bachelors, 13, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 47, Private, 159389, Assoc-acdm, 12, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 62, Private, 254534, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, State-gov, 89508, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 38, Self-emp-not-inc, 238980, Some-college, 10, Never-married, Sales, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 54, Private, 178946, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, >50K 31, Private, 204752, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 26, Private, 290213, Some-college, 10, Separated, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 102615, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1902, 40, United-States, >50K 41, Private, 291965, Some-college, 10, Never-married, Tech-support, Unmarried, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 52, Local-gov, 175339, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 28, Private, 90547, HS-grad, 9, Married-civ-spouse, Other-service, Wife, Black, Female, 0, 0, 23, United-States, <=50K 23, ?, 449101, HS-grad, 9, Married-civ-spouse, ?, Own-child, White, Female, 0, 0, 30, United-States, <=50K 46, Self-emp-not-inc, 101722, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 3137, 0, 40, United-States, <=50K 32, ?, 981628, HS-grad, 9, Divorced, ?, Unmarried, Black, Male, 0, 0, 40, United-States, <=50K 59, ?, 147989, HS-grad, 9, Widowed, ?, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 30, Self-emp-inc, 204470, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 36, United-States, >50K 58, Local-gov, 311409, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, Black, Male, 7688, 0, 30, United-States, >50K 31, Private, 190027, HS-grad, 9, Never-married, Other-service, Other-relative, Black, Female, 0, 0, 40, ?, <=50K 36, Private, 218015, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 48, United-States, <=50K 31, State-gov, 77634, Preschool, 1, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 24, United-States, <=50K 52, Self-emp-not-inc, 42984, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 70, United-States, >50K 29, Private, 413297, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 3411, 0, 70, Mexico, <=50K 48, Self-emp-not-inc, 218835, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, England, <=50K 30, Private, 341051, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 60, United-States, >50K 58, Private, 252419, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, <=50K 20, Federal-gov, 347935, Some-college, 10, Never-married, Protective-serv, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 19, Private, 237848, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 3, United-States, <=50K 63, Private, 174826, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 51, Self-emp-not-inc, 170086, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 45, United-States, >50K 53, Private, 470368, Assoc-acdm, 12, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 48, United-States, <=50K 54, Federal-gov, 75235, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 5178, 0, 40, United-States, >50K 35, ?, 35854, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 746432, HS-grad, 9, Never-married, Handlers-cleaners, Own-child, Black, Male, 0, 0, 48, United-States, <=50K 47, Self-emp-not-inc, 258498, Some-college, 10, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 52, United-States, <=50K 44, Private, 176063, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 80, Self-emp-not-inc, 26865, 7th-8th, 4, Never-married, Farming-fishing, Unmarried, White, Male, 0, 0, 20, United-States, <=50K 55, Private, 104724, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 43, Private, 346321, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 49, Private, 402462, Bachelors, 13, Married-spouse-absent, Transport-moving, Unmarried, White, Male, 0, 0, 30, Columbia, <=50K 27, Private, 153078, Prof-school, 15, Never-married, Prof-specialty, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, United-States, <=50K 42, Private, 176063, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 55, United-States, >50K 39, Private, 451059, 9th, 5, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, ?, 229533, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 106437, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 58, Local-gov, 294313, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, Black, Female, 0, 0, 55, United-States, <=50K 63, Private, 67903, 9th, 5, Separated, Farming-fishing, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 49, Private, 133669, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Self-emp-inc, 251730, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 60, United-States, >50K 46, Private, 72896, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 47, Private, 155664, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 55, United-States, >50K 39, Private, 206520, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 33, Private, 72338, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 65, Japan, >50K 43, Local-gov, 34640, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, Other, Male, 0, 1887, 40, United-States, >50K 30, Private, 236543, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 68, United-States, <=50K 39, Local-gov, 43702, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 37, United-States, <=50K 44, Private, 335248, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 198197, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 80, ?, 281768, Assoc-acdm, 12, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 4, United-States, <=50K 31, Private, 160594, Assoc-acdm, 12, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 3, United-States, <=50K 34, Local-gov, 231826, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, El-Salvador, <=50K 28, Private, 188171, Assoc-acdm, 12, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 60, United-States, <=50K 55, Private, 125000, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Private, 166509, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Private, 402367, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, Black, Male, 7688, 0, 45, United-States, >50K 67, Local-gov, 204123, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 10, United-States, <=50K 53, Self-emp-inc, 220786, Some-college, 10, Widowed, Sales, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 43, Private, 254146, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1902, 40, United-States, >50K 29, Local-gov, 152461, Bachelors, 13, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 42, United-States, <=50K 19, Private, 223669, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, United-States, <=50K 51, Private, 120270, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 21, Self-emp-not-inc, 304602, Assoc-voc, 11, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 98, United-States, <=50K 54, Private, 24108, Some-college, 10, Separated, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 42, Self-emp-not-inc, 32546, Prof-school, 15, Divorced, Prof-specialty, Unmarried, White, Male, 7430, 0, 40, United-States, >50K 41, Private, 93885, Some-college, 10, Divorced, Sales, Unmarried, White, Female, 0, 0, 48, United-States, <=50K 28, Private, 210765, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 191276, Assoc-voc, 11, Divorced, Handlers-cleaners, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 82, Self-emp-not-inc, 71438, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 20, United-States, <=50K 23, Private, 330571, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 16, United-States, <=50K 40, Local-gov, 138634, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 112264, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 24, Private, 205865, HS-grad, 9, Never-married, Sales, Unmarried, White, Male, 0, 0, 45, United-States, <=50K 21, Private, 224640, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 180758, Some-college, 10, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 30, United-States, <=50K 29, ?, 499935, Assoc-voc, 11, Never-married, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 40, Self-emp-not-inc, 107762, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 17, Private, 214787, 12th, 8, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 25, United-States, <=50K 27, Private, 211032, 1st-4th, 2, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 34, Private, 208353, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 157273, 10th, 6, Never-married, Other-service, Other-relative, Black, Male, 0, 0, 15, United-States, <=50K 39, Private, 75891, Bachelors, 13, Divorced, Tech-support, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 34, Self-emp-inc, 177675, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 65, United-States, >50K 44, Private, 182370, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, ?, 200525, 11th, 7, Never-married, ?, Own-child, White, Female, 0, 0, 25, United-States, <=50K 39, Private, 174242, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 60, United-States, >50K 28, Private, 95566, 1st-4th, 2, Married-spouse-absent, Other-service, Own-child, Other, Female, 0, 0, 35, Dominican-Republic, <=50K 30, Private, 30290, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 60, Private, 240951, HS-grad, 9, Divorced, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 58, Private, 183810, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 24, United-States, <=50K 49, Private, 94342, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, <=50K 61, Self-emp-inc, 148577, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, >50K 27, Private, 103634, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 59, Self-emp-not-inc, 83542, Assoc-acdm, 12, Divorced, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 52, Federal-gov, 76131, Some-college, 10, Married-civ-spouse, Exec-managerial, Wife, Asian-Pac-Islander, Female, 0, 0, 40, United-States, >50K 42, Federal-gov, 262402, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 27, Private, 198286, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 34, United-States, <=50K 41, Self-emp-inc, 145441, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 35, ?, 273558, Some-college, 10, Never-married, ?, Not-in-family, Black, Male, 0, 0, 30, United-States, <=50K 50, Local-gov, 117496, Bachelors, 13, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 24, United-States, <=50K 36, Private, 128876, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, Private, 199698, HS-grad, 9, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 45, United-States, <=50K 38, Private, 65390, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 46, Private, 128645, Some-college, 10, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 59, Private, 53481, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 55, Private, 92215, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 49, Local-gov, 78859, Masters, 14, Widowed, Prof-specialty, Unmarried, White, Female, 0, 323, 20, United-States, <=50K 59, Self-emp-inc, 187502, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 38, Private, 242080, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 55, United-States, >50K 22, Private, 41837, Some-college, 10, Never-married, Transport-moving, Own-child, White, Male, 0, 0, 25, United-States, <=50K 28, Private, 291374, 12th, 8, Never-married, Sales, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 47, Private, 148995, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 2415, 60, United-States, >50K 59, Private, 159008, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 56, United-States, <=50K 37, Private, 271013, HS-grad, 9, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 199046, Bachelors, 13, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 164280, 10th, 6, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, Portugal, <=50K 35, Local-gov, 116960, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1887, 40, United-States, >50K 55, Private, 100054, 10th, 6, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 183824, 12th, 8, Never-married, Other-service, Own-child, White, Male, 0, 0, 30, United-States, <=50K 48, Private, 313925, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 30, United-States, >50K 48, Private, 379883, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, Cuba, >50K 70, ?, 92593, Some-college, 10, Widowed, ?, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 27, Private, 189777, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 198330, Masters, 14, Widowed, Prof-specialty, Unmarried, Black, Female, 0, 0, 37, United-States, <=50K 32, Private, 127451, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 38, United-States, >50K 62, ?, 31577, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 18, United-States, <=50K 18, ?, 90230, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 0, 20, United-States, <=50K 50, Private, 301024, Bachelors, 13, Separated, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, >50K 38, Self-emp-not-inc, 175732, HS-grad, 9, Never-married, Craft-repair, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 15, United-States, <=50K 18, Private, 218889, 9th, 5, Never-married, Other-service, Own-child, Black, Male, 0, 0, 35, United-States, <=50K 46, Private, 117605, 9th, 5, Divorced, Sales, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 26, Private, 154571, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 45, United-States, >50K 44, Private, 228057, 7th-8th, 4, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, Dominican-Republic, <=50K 32, Private, 173998, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 25, Private, 90752, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 55, Private, 51008, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 55, Federal-gov, 113398, Some-college, 10, Never-married, Adm-clerical, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 74977, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 40, United-States, <=50K 40, Private, 101593, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 29, Private, 228346, Assoc-voc, 11, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 60, Private, 180418, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 44489, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, <=50K 43, Self-emp-not-inc, 277488, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 30, United-States, <=50K 24, Private, 103064, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 0, 55, United-States, <=50K 34, Private, 226872, Bachelors, 13, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Self-emp-not-inc, 330416, Some-college, 10, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 24, Private, 186495, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 47, State-gov, 205712, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 38, United-States, <=50K 18, Private, 217743, 11th, 7, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 50, Self-emp-inc, 52565, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 1485, 40, United-States, <=50K 22, Private, 239954, Some-college, 10, Never-married, Adm-clerical, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 49, Self-emp-not-inc, 349986, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 41, Private, 117585, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1485, 40, United-States, >50K 68, Self-emp-not-inc, 122094, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 15, United-States, <=50K 62, Self-emp-not-inc, 26857, 7th-8th, 4, Widowed, Farming-fishing, Other-relative, White, Female, 0, 0, 35, United-States, <=50K 25, Local-gov, 192321, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 88095, Some-college, 10, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 24, Mexico, <=50K 44, Private, 144067, Bachelors, 13, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 12, ?, <=50K 32, Private, 124187, 9th, 5, Married-civ-spouse, Farming-fishing, Husband, Black, Male, 0, 0, 40, United-States, <=50K 49, Private, 123681, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 43, United-States, >50K 68, Private, 145638, Some-college, 10, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 130513, Assoc-acdm, 12, Never-married, Sales, Own-child, White, Female, 0, 0, 40, Peru, <=50K 47, Federal-gov, 197038, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 35, Private, 189092, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 37, Self-emp-not-inc, 198841, 11th, 7, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 317969, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, <=50K 37, Private, 103121, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 1848, 40, United-States, >50K 34, Private, 111589, 10th, 6, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, Jamaica, <=50K 46, Local-gov, 267952, Assoc-voc, 11, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 36, United-States, <=50K 21, Private, 63899, 11th, 7, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 473625, HS-grad, 9, Married-civ-spouse, Other-service, Wife, White, Female, 0, 0, 30, United-States, <=50K 45, Private, 187901, HS-grad, 9, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 2258, 44, United-States, >50K 17, Private, 24090, HS-grad, 9, Never-married, Exec-managerial, Own-child, White, Female, 0, 0, 35, United-States, <=50K 36, Self-emp-inc, 102729, Assoc-acdm, 12, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 70, United-States, <=50K 33, Private, 91666, 12th, 8, Divorced, Exec-managerial, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 215873, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, Black, Male, 0, 0, 40, United-States, <=50K 32, Private, 152109, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, <=50K 24, Private, 175586, HS-grad, 9, Never-married, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 37, Private, 232614, HS-grad, 9, Divorced, Other-service, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 53, State-gov, 229465, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 44, Private, 147110, Some-college, 10, Divorced, Adm-clerical, Own-child, White, Male, 14344, 0, 40, United-States, >50K 43, Local-gov, 161240, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 45, United-States, >50K 29, Private, 358124, HS-grad, 9, Never-married, Other-service, Other-relative, Black, Female, 0, 0, 52, United-States, <=50K 47, Private, 222529, Bachelors, 13, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 65, United-States, <=50K 37, Self-emp-not-inc, 338320, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 43, Self-emp-inc, 62026, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 40, United-States, >50K 23, Private, 263886, Some-college, 10, Never-married, Sales, Not-in-family, Black, Female, 0, 0, 20, United-States, <=50K 50, Private, 310774, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 35, United-States, <=50K 25, Private, 98155, Some-college, 10, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 259307, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 39, Private, 358753, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 7688, 0, 40, United-States, >50K 41, Private, 29762, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 52, United-States, >50K 32, Private, 202729, HS-grad, 9, Married-civ-spouse, Transport-moving, Own-child, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 28790, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, Private, 53209, HS-grad, 9, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 30, Local-gov, 169020, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 34, Private, 127195, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 211731, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, Mexico, <=50K 42, Self-emp-not-inc, 126614, Bachelors, 13, Divorced, Exec-managerial, Not-in-family, Other, Male, 0, 0, 30, Iran, <=50K 45, Private, 259463, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 22, Private, 228411, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 25, Private, 117827, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Federal-gov, 57216, Some-college, 10, Never-married, Adm-clerical, Own-child, Black, Male, 0, 0, 20, United-States, <=50K 46, State-gov, 250821, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 15024, 0, 40, United-States, >50K 48, Self-emp-inc, 88564, Some-college, 10, Divorced, Farming-fishing, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 45, Private, 172822, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 52, United-States, >50K 19, Private, 251579, Some-college, 10, Never-married, Other-service, Own-child, White, Male, 0, 0, 14, United-States, <=50K 31, Private, 118399, 11th, 7, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Self-emp-inc, 178383, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 70, United-States, <=50K 40, Self-emp-not-inc, 170866, Assoc-acdm, 12, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, >50K 60, ?, 268954, Some-college, 10, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 12, United-States, >50K 52, ?, 89951, 12th, 8, Married-civ-spouse, ?, Wife, Black, Female, 0, 0, 40, United-States, >50K 22, Private, 203894, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 15, United-States, <=50K 25, Private, 237065, Some-college, 10, Divorced, Other-service, Own-child, Black, Male, 0, 0, 38, United-States, <=50K 51, Local-gov, 108435, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 80, United-States, >50K 32, Private, 93213, Assoc-acdm, 12, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 62, United-States, <=50K 51, Self-emp-inc, 231230, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 25, United-States, <=50K 42, Private, 386175, Some-college, 10, Divorced, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 39, Private, 128392, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 1887, 40, United-States, >50K 24, Private, 223515, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 52, Private, 208630, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 1741, 38, United-States, <=50K 58, ?, 97969, 1st-4th, 2, Married-spouse-absent, ?, Unmarried, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 43, Private, 174295, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, <=50K 31, Private, 60229, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 66095, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 31, Federal-gov, 130057, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 60, United-States, >50K 61, Private, 179743, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 2051, 20, United-States, <=50K 26, Private, 192022, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 45288, Bachelors, 13, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 62, ?, 178764, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, United-States, >50K 50, Private, 99476, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 18, Private, 41973, 11th, 7, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 5, United-States, <=50K 23, Private, 162228, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 48, United-States, <=50K 21, Private, 211968, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 1762, 28, United-States, <=50K 46, Private, 211226, Assoc-acdm, 12, Married-civ-spouse, Transport-moving, Husband, Other, Male, 0, 0, 36, United-States, <=50K 38, Private, 33397, HS-grad, 9, Divorced, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 53, Private, 120839, 12th, 8, Divorced, Farming-fishing, Own-child, White, Male, 0, 0, 40, United-States, <=50K 53, Private, 36327, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 50, Private, 139703, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 26, Private, 107827, HS-grad, 9, Never-married, Other-service, Unmarried, White, Male, 0, 0, 25, United-States, <=50K 46, Local-gov, 140219, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 8614, 0, 55, United-States, >50K 44, Local-gov, 203761, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 36, Local-gov, 114719, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 20, Private, 344394, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 35, Private, 195516, 7th-8th, 4, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, Mexico, <=50K 40, State-gov, 31627, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 20, United-States, <=50K 70, Private, 174032, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 57, Private, 226875, 7th-8th, 4, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, <=50K 40, Private, 566537, Preschool, 1, Married-civ-spouse, Other-service, Husband, White, Male, 0, 1672, 40, Mexico, <=50K 18, Private, 36162, 11th, 7, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 5, United-States, <=50K 45, Self-emp-not-inc, 31478, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 2829, 0, 60, United-States, <=50K 52, Private, 294991, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 24, ?, 108495, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 42, Self-emp-inc, 161532, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 60, United-States, <=50K 28, Local-gov, 332249, HS-grad, 9, Separated, Transport-moving, Own-child, White, Male, 0, 0, 45, United-States, <=50K 32, Private, 268147, Assoc-voc, 11, Never-married, Tech-support, Unmarried, White, Female, 0, 0, 60, United-States, <=50K 56, Federal-gov, 317847, Bachelors, 13, Divorced, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 44, Private, 52028, 1st-4th, 2, Married-civ-spouse, Other-service, Wife, Asian-Pac-Islander, Female, 0, 0, 40, Vietnam, <=50K 20, Private, 184045, Some-college, 10, Never-married, Sales, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 32, Private, 206609, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 59, Private, 152968, Some-college, 10, Separated, Adm-clerical, Other-relative, White, Male, 3325, 0, 40, United-States, <=50K 21, Private, 213015, HS-grad, 9, Never-married, Handlers-cleaners, Other-relative, Black, Male, 2176, 0, 40, United-States, <=50K 32, Private, 313835, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 49, Private, 66385, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 5013, 0, 40, United-States, <=50K 22, Private, 205940, Bachelors, 13, Never-married, Adm-clerical, Own-child, White, Female, 1055, 0, 30, United-States, <=50K 51, Self-emp-inc, 260938, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 33, Private, 60567, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 3411, 0, 40, United-States, <=50K 23, Private, 335067, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 34, Private, 331126, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Male, 0, 0, 30, United-States, <=50K 53, Private, 156612, 12th, 8, Divorced, Transport-moving, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 188436, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 45, United-States, <=50K 60, Private, 227468, Some-college, 10, Widowed, Protective-serv, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 55, Private, 183580, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 38, United-States, <=50K 57, Self-emp-not-inc, 50990, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 30, United-States, <=50K 59, Private, 384246, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 26, ?, 375313, Some-college, 10, Never-married, ?, Own-child, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, <=50K 30, Private, 176410, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Own-child, White, Female, 7298, 0, 16, United-States, >50K 49, Private, 93639, Bachelors, 13, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 43, United-States, <=50K 45, Private, 30289, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Self-emp-inc, 124950, Bachelors, 13, Never-married, Sales, Own-child, White, Female, 0, 0, 40, United-States, <=50K 37, Self-emp-not-inc, 126675, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 60, United-States, >50K 21, Private, 145964, 12th, 8, Never-married, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 36, State-gov, 345712, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, ?, 97474, HS-grad, 9, Never-married, ?, Own-child, White, Female, 0, 0, 20, United-States, <=50K 37, Private, 180342, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 19, Private, 167087, HS-grad, 9, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 65, ?, 192825, 7th-8th, 4, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 25, United-States, <=50K 30, Private, 318749, Assoc-voc, 11, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 35, Germany, <=50K 27, ?, 147638, Masters, 14, Never-married, ?, Not-in-family, Other, Female, 0, 0, 40, Japan, <=50K 59, Federal-gov, 293971, Some-college, 10, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, >50K 32, Private, 229566, Assoc-voc, 11, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 60, United-States, >50K 25, Private, 242464, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 111067, Bachelors, 13, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 80, United-States, >50K 21, ?, 155697, 9th, 5, Never-married, ?, Own-child, White, Male, 0, 0, 42, United-States, <=50K 49, Local-gov, 106554, Bachelors, 13, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 40, United-States, >50K 49, Private, 23776, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 51, ?, 43909, HS-grad, 9, Divorced, ?, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 48, Private, 105808, 9th, 5, Widowed, Transport-moving, Unmarried, White, Male, 0, 0, 40, United-States, >50K 42, Private, 169995, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, <=50K 53, Private, 141388, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Self-emp-not-inc, 241431, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 21, ?, 78374, HS-grad, 9, Never-married, ?, Other-relative, Asian-Pac-Islander, Female, 0, 0, 24, United-States, <=50K 54, Self-emp-not-inc, 158948, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 15, United-States, <=50K 66, Private, 115498, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 55, ?, >50K 34, Private, 272411, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 39, Private, 30529, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1887, 40, United-States, >50K 62, ?, 263374, Assoc-voc, 11, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 40, Canada, <=50K 30, Private, 190228, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 126060, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 25, Private, 391192, Assoc-voc, 11, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 26, Private, 214069, HS-grad, 9, Separated, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 170871, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 60, United-States, >50K 55, Private, 118993, Some-college, 10, Separated, Exec-managerial, Unmarried, White, Female, 0, 0, 10, United-States, <=50K 26, Private, 245880, HS-grad, 9, Never-married, Other-service, Other-relative, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 174794, Bachelors, 13, Separated, Prof-specialty, Unmarried, White, Female, 0, 0, 56, Germany, <=50K 61, Local-gov, 153408, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 34, ?, 330301, 7th-8th, 4, Separated, ?, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 26, Private, 385278, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, Black, Male, 0, 0, 60, United-States, <=50K 44, Federal-gov, 38434, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 45, Self-emp-not-inc, 111679, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 30, United-States, <=50K 55, Private, 168956, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 86143, Some-college, 10, Never-married, Other-service, Other-relative, Asian-Pac-Islander, Male, 0, 0, 30, United-States, <=50K 48, Private, 99835, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 33, Private, 263561, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 60, United-States, <=50K 44, Private, 118536, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 32, Self-emp-inc, 209691, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, Canada, <=50K 54, Private, 123374, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 137225, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 29, Private, 119359, HS-grad, 9, Married-civ-spouse, Prof-specialty, Wife, Asian-Pac-Islander, Female, 0, 0, 10, China, >50K 56, Private, 134153, 10th, 6, Married-civ-spouse, Adm-clerical, Husband, Black, Male, 0, 0, 40, United-States, <=50K 47, Private, 121124, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 22, Private, 147655, Some-college, 10, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 46, Private, 165138, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 45, United-States, >50K 24, Federal-gov, 312017, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 272950, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 259323, HS-grad, 9, Divorced, Craft-repair, Unmarried, White, Male, 0, 0, 40, United-States, <=50K 44, Federal-gov, 281739, Some-college, 10, Never-married, Adm-clerical, Not-in-family, White, Male, 13550, 0, 50, United-States, >50K 21, Private, 119156, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 165881, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 23, State-gov, 136075, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 50, Private, 187465, 11th, 7, Divorced, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 44, Private, 328561, Assoc-voc, 11, Married-civ-spouse, Adm-clerical, Other-relative, White, Female, 0, 0, 20, United-States, <=50K 48, Private, 350440, Some-college, 10, Married-civ-spouse, Craft-repair, Other-relative, Asian-Pac-Islander, Male, 0, 0, 40, Cambodia, >50K 38, Self-emp-not-inc, 109133, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 70, United-States, >50K 48, Private, 109814, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 45, United-States, >50K 39, Private, 86643, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 52, Federal-gov, 154521, HS-grad, 9, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 44, United-States, >50K 63, Private, 45912, HS-grad, 9, Widowed, Other-service, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 48, Private, 175070, HS-grad, 9, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 2258, 40, United-States, >50K 37, Private, 338033, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 26, State-gov, 158963, Masters, 14, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 50, Self-emp-inc, 121441, 11th, 7, Never-married, Exec-managerial, Other-relative, White, Male, 0, 2444, 40, United-States, >50K 47, Self-emp-not-inc, 242391, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 40, United-States, >50K 19, Private, 119964, HS-grad, 9, Never-married, Craft-repair, Other-relative, White, Female, 0, 0, 15, United-States, <=50K 34, Private, 193344, Some-college, 10, Never-married, Adm-clerical, Unmarried, White, Female, 0, 0, 40, Germany, <=50K 29, Local-gov, 45554, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 249716, HS-grad, 9, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 53, Private, 58985, Some-college, 10, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 24, United-States, <=50K 24, Private, 456367, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 39, Private, 117381, Some-college, 10, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 50, Self-emp-not-inc, 240922, Assoc-acdm, 12, Never-married, Sales, Not-in-family, White, Female, 0, 1408, 5, United-States, <=50K 31, Private, 226443, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 364342, Assoc-voc, 11, Never-married, Sales, Not-in-family, Black, Female, 0, 0, 25, United-States, <=50K 42, Local-gov, 101593, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 42, United-States, <=50K 23, Private, 267471, 12th, 8, Never-married, Sales, Own-child, White, Female, 0, 0, 25, United-States, <=50K 22, Private, 186849, 11th, 7, Divorced, Sales, Own-child, White, Male, 0, 0, 50, United-States, <=50K 65, Private, 174603, 5th-6th, 3, Widowed, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 10, Italy, <=50K 34, Private, 115040, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 44, United-States, <=50K 23, Private, 142766, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 1055, 0, 20, United-States, <=50K 38, Private, 59660, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 7298, 0, 40, United-States, >50K 45, Self-emp-not-inc, 49595, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 80, United-States, <=50K 19, Private, 127491, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 155933, Bachelors, 13, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 1602, 8, United-States, <=50K 23, Private, 122272, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 20, United-States, <=50K 37, Private, 143771, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 59, Private, 91384, Bachelors, 13, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, State-gov, 135874, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Private, 207066, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 10520, 0, 45, United-States, >50K 51, Private, 172493, Some-college, 10, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 12, United-States, <=50K 42, Local-gov, 189956, Bachelors, 13, Divorced, Prof-specialty, Unmarried, Black, Female, 0, 0, 30, United-States, <=50K 35, Private, 106967, Masters, 14, Never-married, Sales, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 20, Private, 200153, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 38, United-States, <=50K 25, Private, 149943, HS-grad, 9, Never-married, Other-service, Other-relative, Asian-Pac-Islander, Male, 4101, 0, 60, ?, <=50K 41, Private, 151736, 10th, 6, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 40, Private, 67852, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 36, Private, 54229, Assoc-acdm, 12, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 37, United-States, <=50K 34, Self-emp-inc, 154120, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, >50K 44, Self-emp-not-inc, 157217, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 42, United-States, <=50K 31, Federal-gov, 381645, Bachelors, 13, Separated, Prof-specialty, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 41, Local-gov, 160785, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 133584, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 43, Private, 170230, Masters, 14, Never-married, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 58, Private, 250206, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 5178, 0, 40, United-States, >50K 19, Private, 128363, Some-college, 10, Never-married, Sales, Own-child, White, Female, 0, 0, 30, United-States, <=50K 43, Local-gov, 163434, Bachelors, 13, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 55, United-States, >50K 50, Private, 195690, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 45, United-States, <=50K 44, Self-emp-inc, 138991, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 46, Private, 118419, HS-grad, 9, Divorced, Machine-op-inspct, Unmarried, White, Male, 0, 0, 38, United-States, <=50K 52, Self-emp-not-inc, 185407, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 52, Self-emp-not-inc, 283079, HS-grad, 9, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 18, Private, 119655, 12th, 8, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 12, United-States, <=50K 29, Private, 153416, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 55, United-States, <=50K 19, ?, 204868, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 36, United-States, <=50K 34, Private, 220362, Bachelors, 13, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 23, Local-gov, 203078, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, Black, Male, 0, 0, 40, United-States, <=50K 64, State-gov, 104361, Some-college, 10, Separated, Adm-clerical, Not-in-family, White, Female, 0, 0, 65, United-States, <=50K 68, Private, 274096, 10th, 6, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 42, State-gov, 455553, HS-grad, 9, Never-married, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 41, Private, 112283, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 60, United-States, >50K 41, Self-emp-inc, 64506, HS-grad, 9, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, <=50K 22, State-gov, 24395, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 20, United-States, <=50K 67, Self-emp-inc, 182581, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 20051, 0, 20, United-States, >50K 27, Private, 100669, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, Asian-Pac-Islander, Male, 0, 0, 40, Philippines, >50K 25, Private, 178025, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 49, ?, 113913, HS-grad, 9, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 60, United-States, <=50K 28, Private, 55191, Assoc-acdm, 12, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 51, Federal-gov, 223206, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, Asian-Pac-Islander, Male, 15024, 0, 40, Vietnam, >50K 23, Local-gov, 162551, Bachelors, 13, Never-married, Prof-specialty, Own-child, Asian-Pac-Islander, Female, 0, 0, 35, China, <=50K 19, Private, 693066, 12th, 8, Never-married, Other-service, Own-child, White, Female, 0, 0, 15, United-States, <=50K 72, ?, 96867, 5th-6th, 3, Widowed, ?, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 256362, Some-college, 10, Never-married, Other-service, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 53, Private, 539864, Some-college, 10, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 20, United-States, <=50K 35, Private, 241153, Assoc-voc, 11, Never-married, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 284395, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 18, Private, 180039, 12th, 8, Never-married, Sales, Own-child, White, Female, 0, 0, 20, United-States, <=50K 45, Private, 178416, Assoc-voc, 11, Divorced, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 175710, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Female, 0, 0, 30, ?, <=50K 22, Local-gov, 164775, 5th-6th, 3, Never-married, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, Guatemala, >50K 55, Private, 176897, Some-college, 10, Divorced, Tech-support, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 265097, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 1902, 40, United-States, >50K 22, Private, 193090, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 37, United-States, <=50K 37, Private, 186009, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1672, 60, United-States, <=50K 28, Private, 175262, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 19, Private, 109928, 11th, 7, Never-married, Sales, Own-child, Black, Female, 0, 0, 35, United-States, <=50K 37, Self-emp-not-inc, 162834, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 1902, 45, United-States, >50K 50, Private, 177896, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, >50K 31, Private, 181372, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 40, Private, 70645, Preschool, 1, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 20, United-States, <=50K 51, Private, 128272, 9th, 5, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, <=50K 56, Private, 106723, HS-grad, 9, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 21, Private, 122348, Some-college, 10, Never-married, Tech-support, Own-child, White, Female, 0, 0, 35, United-States, <=50K 40, Private, 177905, Assoc-voc, 11, Married-civ-spouse, Exec-managerial, Husband, White, Male, 7688, 0, 44, United-States, >50K 22, Private, 254547, Some-college, 10, Never-married, Exec-managerial, Unmarried, Black, Female, 0, 0, 40, Jamaica, <=50K 47, Self-emp-inc, 102308, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 2415, 45, United-States, >50K 44, Private, 33105, HS-grad, 9, Married-civ-spouse, Exec-managerial, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 30, Private, 215441, Some-college, 10, Never-married, Adm-clerical, Not-in-family, Other, Male, 0, 0, 40, ?, <=50K 44, Local-gov, 197919, Some-college, 10, Divorced, Other-service, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 41, Private, 206139, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, >50K 47, Private, 117849, Assoc-acdm, 12, Divorced, Sales, Own-child, White, Male, 0, 0, 44, United-States, <=50K 26, Private, 323044, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, Germany, >50K 34, Private, 90415, Assoc-voc, 11, Never-married, Tech-support, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 47, Private, 294913, Prof-school, 15, Married-civ-spouse, Exec-managerial, Husband, White, Male, 99999, 0, 40, United-States, >50K 36, Private, 127573, HS-grad, 9, Separated, Adm-clerical, Not-in-family, White, Female, 0, 0, 38, United-States, <=50K 21, Private, 180190, Assoc-voc, 11, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 46, United-States, <=50K 45, State-gov, 231013, Bachelors, 13, Divorced, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 33, Private, 356015, HS-grad, 9, Separated, Craft-repair, Not-in-family, Amer-Indian-Eskimo, Male, 0, 0, 35, Hong, <=50K 33, Private, 198069, HS-grad, 9, Never-married, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 58, Self-emp-not-inc, 99141, HS-grad, 9, Divorced, Farming-fishing, Unmarried, White, Female, 0, 0, 10, United-States, <=50K 31, Private, 188246, Assoc-acdm, 12, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, >50K 32, Self-emp-not-inc, 116508, Some-college, 10, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 50, United-States, >50K 44, Federal-gov, 38434, Bachelors, 13, Widowed, Exec-managerial, Unmarried, White, Female, 0, 0, 40, United-States, >50K 24, Private, 128477, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 35, Private, 91839, Bachelors, 13, Married-civ-spouse, Other-service, Husband, Amer-Indian-Eskimo, Male, 7688, 0, 20, United-States, >50K 43, Private, 409922, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 50, United-States, >50K 49, Private, 185041, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Self-emp-not-inc, 103925, Bachelors, 13, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 50, United-States, <=50K 42, Self-emp-not-inc, 34037, Bachelors, 13, Never-married, Farming-fishing, Own-child, White, Male, 0, 0, 35, United-States, <=50K 31, Private, 251659, Some-college, 10, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male, 0, 1485, 55, ?, >50K 19, Private, 57145, HS-grad, 9, Never-married, Other-service, Own-child, White, Female, 0, 0, 25, United-States, <=50K 41, Private, 182108, Doctorate, 16, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, >50K 51, Self-emp-inc, 213296, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 30, United-States, <=50K 51, Self-emp-inc, 28765, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 63, Private, 37792, 10th, 6, Widowed, Other-service, Not-in-family, White, Female, 0, 0, 31, United-States, <=50K 39, Federal-gov, 232036, Some-college, 10, Married-civ-spouse, Adm-clerical, Husband, White, Male, 0, 0, 40, United-States, >50K 30, Private, 33678, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 62, Without-pay, 159908, Some-college, 10, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 16, United-States, <=50K 27, Private, 176761, HS-grad, 9, Never-married, Craft-repair, Other-relative, Other, Male, 0, 0, 40, Nicaragua, <=50K 32, Private, 260954, 11th, 7, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 2042, 30, United-States, <=50K 37, Local-gov, 180342, Bachelors, 13, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, >50K 47, Local-gov, 324791, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1887, 50, United-States, >50K 31, Private, 183801, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1902, 43, United-States, >50K 42, Private, 204235, HS-grad, 9, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 249720, Assoc-voc, 11, Married-spouse-absent, Sales, Unmarried, Black, Female, 0, 0, 32, United-States, <=50K 60, Private, 127084, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 2042, 34, United-States, <=50K 42, Local-gov, 201495, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 72, United-States, >50K 38, Private, 447346, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 36, United-States, >50K 24, Private, 206008, Assoc-acdm, 12, Never-married, Prof-specialty, Own-child, Black, Male, 0, 0, 20, United-States, <=50K 34, Private, 286020, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 45, United-States, <=50K 20, ?, 99891, Some-college, 10, Never-married, ?, Own-child, White, Female, 0, 0, 30, United-States, <=50K 29, Local-gov, 169544, Some-college, 10, Never-married, Protective-serv, Own-child, White, Male, 0, 0, 48, United-States, <=50K 90, Private, 313749, HS-grad, 9, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 25, United-States, <=50K 55, Private, 89182, 12th, 8, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, Italy, <=50K 36, Private, 258102, HS-grad, 9, Never-married, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 49, Private, 255466, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 60, United-States, <=50K 50, Private, 38795, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 17, Private, 311907, 11th, 7, Never-married, Other-service, Own-child, White, Male, 0, 0, 25, United-States, <=50K 54, Private, 171924, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 70, United-States, <=50K 26, Private, 164488, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 10, United-States, <=50K 44, Private, 297991, Assoc-acdm, 12, Never-married, Exec-managerial, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 50, United-States, <=50K 28, Private, 478315, Bachelors, 13, Never-married, Prof-specialty, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 54, Local-gov, 34832, Doctorate, 16, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 21, Private, 67804, 9th, 5, Never-married, Machine-op-inspct, Own-child, Black, Male, 0, 0, 20, United-States, <=50K 24, Private, 34568, Assoc-voc, 11, Never-married, Transport-moving, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 47151, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 56, United-States, <=50K 59, ?, 120617, Some-college, 10, Never-married, ?, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 41, Private, 318046, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 48, United-States, >50K 29, Private, 363963, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 50, Private, 92811, Bachelors, 13, Married-civ-spouse, Tech-support, Husband, White, Male, 0, 0, 40, United-States, <=50K 32, Private, 33678, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 50, United-States, >50K 42, Private, 66118, Some-college, 10, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 47, Private, 160474, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 0, 0, 30, United-States, >50K 44, Private, 159960, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 49, Private, 242987, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, Columbia, <=50K 61, Private, 232719, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 65, Local-gov, 103153, 7th-8th, 4, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1411, 40, United-States, <=50K 45, Local-gov, 162187, HS-grad, 9, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 0, 40, United-States, >50K 59, Private, 207391, HS-grad, 9, Divorced, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 30, Never-worked, 176673, HS-grad, 9, Married-civ-spouse, ?, Wife, Black, Female, 0, 0, 40, United-States, <=50K 34, Private, 356882, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 24, Private, 427686, 1st-4th, 2, Married-civ-spouse, Handlers-cleaners, Other-relative, White, Male, 0, 0, 40, Mexico, <=50K 42, Self-emp-inc, 191196, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 1977, 60, ?, >50K 37, Private, 377798, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 3103, 0, 40, United-States, >50K 36, Private, 43712, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 21, ?, 205939, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 54, Private, 161691, Masters, 14, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 2559, 40, United-States, >50K 34, Private, 346034, 12th, 8, Married-spouse-absent, Handlers-cleaners, Unmarried, White, Male, 0, 0, 35, Mexico, <=50K 41, Private, 144460, Some-college, 10, Divorced, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, Italy, <=50K 18, Never-worked, 153663, Some-college, 10, Never-married, ?, Own-child, White, Male, 0, 0, 4, United-States, <=50K 26, Private, 262617, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, <=50K 23, Federal-gov, 173851, HS-grad, 9, Never-married, Armed-Forces, Not-in-family, White, Male, 0, 0, 8, United-States, <=50K 63, ?, 126540, Some-college, 10, Divorced, ?, Not-in-family, White, Female, 0, 0, 5, United-States, <=50K 34, Private, 117963, Bachelors, 13, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, >50K 54, Private, 219737, HS-grad, 9, Widowed, Sales, Not-in-family, White, Female, 0, 0, 37, United-States, <=50K 37, Private, 328466, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 72, Mexico, <=50K 54, State-gov, 138852, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Local-gov, 195532, Some-college, 10, Never-married, Protective-serv, Other-relative, White, Female, 0, 0, 43, United-States, <=50K 32, Private, 188246, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 42, State-gov, 138162, Some-college, 10, Divorced, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 31, State-gov, 110714, Some-college, 10, Never-married, Other-service, Own-child, White, Female, 0, 0, 37, United-States, <=50K 48, Private, 123075, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, United-States, >50K 28, Private, 330466, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 40, Hong, <=50K 31, Private, 254304, 10th, 6, Divorced, Craft-repair, Not-in-family, White, Male, 0, 0, 38, United-States, <=50K 28, Private, 435842, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, <=50K 24, Private, 118657, 12th, 8, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 278188, HS-grad, 9, Divorced, Craft-repair, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 26, Private, 233777, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 72, Mexico, <=50K 37, Self-emp-inc, 328466, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 50, United-States, >50K 24, Private, 176580, 5th-6th, 3, Married-spouse-absent, Farming-fishing, Not-in-family, White, Male, 0, 0, 40, Mexico, <=50K 18, ?, 156608, 11th, 7, Never-married, ?, Own-child, White, Female, 0, 0, 25, United-States, <=50K 32, Private, 172415, HS-grad, 9, Never-married, Other-service, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 23, Private, 194951, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 55, Ireland, <=50K 33, Local-gov, 318921, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Female, 0, 0, 35, United-States, <=50K 49, Private, 189462, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 75, Self-emp-not-inc, 192813, Masters, 14, Widowed, Sales, Not-in-family, White, Male, 0, 0, 45, United-States, <=50K 74, Self-emp-not-inc, 199136, Bachelors, 13, Widowed, Craft-repair, Not-in-family, White, Male, 15831, 0, 8, Germany, >50K 26, Private, 156805, Some-college, 10, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male, 0, 0, 40, United-States, <=50K 66, ?, 93318, HS-grad, 9, Widowed, ?, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 34, Private, 121966, Bachelors, 13, Married-spouse-absent, Adm-clerical, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 18, Private, 347336, 12th, 8, Never-married, Other-service, Own-child, White, Male, 0, 0, 12, United-States, <=50K 33, Private, 205950, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 36, State-gov, 212143, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 20, United-States, >50K 44, Private, 187821, Bachelors, 13, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 55, United-States, <=50K 36, Private, 250807, 11th, 7, Never-married, Craft-repair, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 53, Private, 291755, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 60, Private, 36077, 7th-8th, 4, Married-spouse-absent, Machine-op-inspct, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 28, Private, 119793, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, Portugal, <=50K 36, Private, 184655, 10th, 6, Divorced, Transport-moving, Unmarried, White, Male, 0, 0, 48, United-States, <=50K 35, Private, 162256, Assoc-voc, 11, Divorced, Adm-clerical, Not-in-family, White, Female, 6849, 0, 40, United-States, <=50K 45, Self-emp-not-inc, 204405, Assoc-voc, 11, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 20, United-States, <=50K 23, Private, 133355, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 15, United-States, <=50K 35, Private, 89559, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 55, United-States, <=50K 34, Private, 115066, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 42, United-States, >50K 46, Private, 139514, Preschool, 1, Married-civ-spouse, Machine-op-inspct, Other-relative, Black, Male, 0, 0, 75, Dominican-Republic, <=50K 58, State-gov, 200316, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Local-gov, 166502, Masters, 14, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 63, Private, 226422, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 41, Self-emp-not-inc, 251305, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 190482, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 76, United-States, <=50K 41, Private, 122215, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 40, United-States, >50K 42, Private, 248356, HS-grad, 9, Never-married, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 90, Local-gov, 214594, 7th-8th, 4, Married-civ-spouse, Protective-serv, Husband, White, Male, 2653, 0, 40, United-States, <=50K 41, Private, 220460, HS-grad, 9, Never-married, Sales, Own-child, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 174043, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 53, Self-emp-not-inc, 137547, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, Asian-Pac-Islander, Male, 27828, 0, 40, Philippines, >50K 49, Self-emp-not-inc, 111959, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, Scotland, >50K 51, Private, 40641, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 60, United-States, >50K 22, Private, 205940, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 23, Private, 265077, Assoc-voc, 11, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 59, Private, 395736, HS-grad, 9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male, 0, 0, 40, United-States, >50K 40, Private, 306225, HS-grad, 9, Divorced, Craft-repair, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 40, Japan, <=50K 28, Private, 180299, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 70, United-States, <=50K 39, Private, 214896, HS-grad, 9, Separated, Other-service, Not-in-family, White, Female, 0, 0, 40, El-Salvador, <=50K 25, Private, 273792, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 37, United-States, <=50K 48, State-gov, 224474, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 62, Private, 271431, 9th, 5, Married-civ-spouse, Other-service, Husband, Black, Male, 0, 0, 42, United-States, <=50K 44, Local-gov, 150171, HS-grad, 9, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 28, Federal-gov, 381789, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 62, Private, 170984, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 45, United-States, <=50K 32, Private, 108256, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 59, Federal-gov, 23789, HS-grad, 9, Married-civ-spouse, Sales, Wife, White, Female, 0, 0, 40, United-States, >50K 20, Private, 176321, Some-college, 10, Never-married, Adm-clerical, Other-relative, White, Female, 0, 0, 20, United-States, <=50K 40, Private, 260425, Assoc-acdm, 12, Separated, Tech-support, Unmarried, White, Female, 1471, 0, 32, United-States, <=50K 47, Private, 248059, Some-college, 10, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 47, United-States, >50K 60, Private, 56248, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 55, Private, 199763, HS-grad, 9, Separated, Protective-serv, Not-in-family, White, Male, 0, 0, 81, United-States, <=50K 18, Private, 200047, 12th, 8, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 35, United-States, <=50K 43, Private, 191712, Bachelors, 13, Never-married, Adm-clerical, Not-in-family, White, Male, 0, 1741, 40, United-States, <=50K 31, Self-emp-not-inc, 156033, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Male, 0, 0, 35, United-States, <=50K 22, Private, 173736, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 56, Private, 135458, HS-grad, 9, Divorced, Tech-support, Not-in-family, Black, Female, 0, 0, 40, United-States, <=50K 41, Private, 185660, HS-grad, 9, Separated, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 222005, HS-grad, 9, Never-married, Other-service, Other-relative, White, Male, 0, 0, 30, United-States, <=50K 42, Private, 161510, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 7298, 0, 40, United-States, >50K 53, Local-gov, 186303, Some-college, 10, Married-civ-spouse, Protective-serv, Husband, White, Male, 0, 1887, 40, United-States, >50K 52, Local-gov, 143533, 7th-8th, 4, Never-married, Other-service, Other-relative, Black, Female, 0, 0, 40, United-States, <=50K 42, Private, 288154, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 89, United-States, >50K 48, Private, 325372, 1st-4th, 2, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Portugal, <=50K 35, Private, 379959, HS-grad, 9, Divorced, Other-service, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 168387, 11th, 7, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 20, Private, 234640, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 33, Private, 232475, Some-college, 10, Never-married, Sales, Own-child, White, Male, 0, 0, 45, United-States, <=50K 30, Private, 205152, Bachelors, 13, Never-married, Sales, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 112115, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 29, Private, 183854, HS-grad, 9, Never-married, Sales, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 26, Private, 164386, HS-grad, 9, Never-married, Craft-repair, Own-child, White, Male, 0, 0, 48, United-States, <=50K 61, Private, 149620, Some-college, 10, Divorced, Other-service, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 45, Private, 199590, 5th-6th, 3, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, ?, <=50K 29, Private, 83742, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 45, United-States, <=50K 57, Self-emp-not-inc, 65080, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, >50K 33, Private, 191335, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 1902, 50, United-States, >50K 20, Private, 227778, Some-college, 10, Never-married, Sales, Not-in-family, White, Female, 0, 0, 56, United-States, <=50K 26, Private, 48280, Bachelors, 13, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, Private, 66304, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 55, United-States, >50K 23, Private, 45834, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 31, Private, 298995, HS-grad, 9, Married-civ-spouse, Other-service, Wife, Black, Female, 0, 0, 35, United-States, <=50K 47, Private, 161950, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 61, Private, 98776, 11th, 7, Widowed, Handlers-cleaners, Not-in-family, White, Female, 0, 0, 30, United-States, <=50K 35, Private, 102268, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, <=50K 23, Private, 180771, 1st-4th, 2, Married-civ-spouse, Machine-op-inspct, Wife, Amer-Indian-Eskimo, Female, 0, 0, 35, Mexico, <=50K 20, ?, 203992, HS-grad, 9, Never-married, ?, Own-child, White, Male, 0, 0, 40, United-States, <=50K 41, Private, 206878, HS-grad, 9, Divorced, Other-service, Unmarried, White, Female, 0, 0, 32, United-States, <=50K 39, Federal-gov, 110622, Bachelors, 13, Married-civ-spouse, Adm-clerical, Wife, Asian-Pac-Islander, Female, 0, 0, 40, Philippines, <=50K 51, Local-gov, 203334, Doctorate, 16, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 45, United-States, >50K 61, Self-emp-not-inc, 50483, 7th-8th, 4, Married-civ-spouse, Farming-fishing, Husband, White, Male, 0, 0, 56, United-States, <=50K 51, Private, 274502, 7th-8th, 4, Divorced, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 48, United-States, <=50K 36, Private, 208068, Preschool, 1, Divorced, Other-service, Not-in-family, Other, Male, 0, 0, 72, Mexico, <=50K 41, Self-emp-not-inc, 168098, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 34, Private, 213307, HS-grad, 9, Never-married, Handlers-cleaners, Unmarried, White, Female, 7443, 0, 35, United-States, <=50K 25, Private, 175128, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 37, Private, 40955, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, >50K 19, Private, 60890, HS-grad, 9, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 49, United-States, <=50K 66, Self-emp-not-inc, 102686, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 20, United-States, >50K 23, Private, 190273, Bachelors, 13, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 40, United-States, <=50K 30, Self-emp-not-inc, 176185, Some-college, 10, Married-spouse-absent, Craft-repair, Own-child, White, Male, 0, 0, 60, United-States, >50K 53, Private, 304504, Some-college, 10, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 1887, 45, United-States, >50K 25, Private, 390657, Some-college, 10, Never-married, Other-service, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 18, Private, 41381, HS-grad, 9, Never-married, Sales, Own-child, White, Female, 0, 1602, 20, United-States, <=50K 51, Private, 101432, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 190682, HS-grad, 9, Widowed, Craft-repair, Not-in-family, Black, Female, 0, 1669, 50, United-States, <=50K 53, Private, 158993, HS-grad, 9, Widowed, Machine-op-inspct, Unmarried, Black, Female, 0, 0, 38, United-States, <=50K 17, Private, 117798, 10th, 6, Never-married, Other-service, Own-child, White, Male, 0, 0, 20, United-States, <=50K 61, Private, 137554, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 44, Self-emp-inc, 71556, Masters, 14, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, ?, >50K 38, Private, 257416, 9th, 5, Married-civ-spouse, Transport-moving, Husband, Black, Male, 0, 0, 40, United-States, <=50K 40, Private, 195617, Some-college, 10, Separated, Exec-managerial, Unmarried, White, Female, 0, 0, 20, United-States, <=50K 32, Private, 236318, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 32, United-States, <=50K 46, Private, 42251, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, >50K 50, Private, 257933, Some-college, 10, Divorced, Adm-clerical, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 36, Self-emp-not-inc, 109133, Bachelors, 13, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 50, United-States, >50K 30, Self-emp-not-inc, 261943, 11th, 7, Married-spouse-absent, Craft-repair, Not-in-family, White, Male, 0, 0, 30, Honduras, <=50K 33, Private, 139057, Masters, 14, Married-civ-spouse, Tech-support, Husband, Asian-Pac-Islander, Male, 0, 0, 50, United-States, >50K 36, Private, 237943, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 1977, 45, United-States, >50K 85, Private, 98611, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 3, Poland, <=50K 62, Private, 128092, HS-grad, 9, Widowed, Adm-clerical, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 24, Private, 284317, Bachelors, 13, Never-married, Machine-op-inspct, Not-in-family, White, Female, 0, 0, 32, United-States, <=50K 48, Self-emp-inc, 185041, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 7298, 0, 50, United-States, >50K 58, Local-gov, 223214, HS-grad, 9, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Self-emp-inc, 173664, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 45, United-States, >50K 66, Private, 269665, HS-grad, 9, Widowed, Exec-managerial, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 37, Private, 121521, Prof-school, 15, Married-civ-spouse, Prof-specialty, Husband, White, Male, 15024, 0, 45, United-States, >50K 55, Private, 199713, 9th, 5, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 48, United-States, <=50K 39, Self-emp-not-inc, 193689, HS-grad, 9, Never-married, Exec-managerial, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 58, Self-emp-inc, 181974, Doctorate, 16, Never-married, Prof-specialty, Not-in-family, White, Female, 0, 0, 99, ?, <=50K 50, Private, 485710, Doctorate, 16, Divorced, Prof-specialty, Not-in-family, White, Female, 0, 0, 50, United-States, <=50K 28, Private, 185647, Some-college, 10, Divorced, Handlers-cleaners, Not-in-family, White, Male, 0, 0, 50, United-States, <=50K 34, Private, 30673, Masters, 14, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 55, United-States, <=50K 41, Federal-gov, 160467, Masters, 14, Divorced, Prof-specialty, Unmarried, White, Female, 1506, 0, 40, United-States, <=50K 36, Private, 186819, Assoc-acdm, 12, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 52, United-States, >50K 22, Private, 67234, HS-grad, 9, Never-married, Handlers-cleaners, Unmarried, White, Male, 0, 0, 45, United-States, <=50K 35, Private, 30673, 12th, 8, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 84, United-States, <=50K 49, ?, 114648, 12th, 8, Divorced, ?, Other-relative, Black, Male, 0, 0, 40, United-States, <=50K 21, Private, 182117, Assoc-acdm, 12, Never-married, Other-service, Own-child, White, Male, 0, 0, 40, United-States, <=50K 64, State-gov, 222966, 7th-8th, 4, Married-civ-spouse, Other-service, Wife, Black, Female, 0, 0, 40, United-States, <=50K 41, Private, 201495, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 52, Private, 301229, Assoc-voc, 11, Separated, Sales, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 32, Private, 157747, Some-college, 10, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 155382, Some-college, 10, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 25, United-States, <=50K 48, Private, 268083, Some-college, 10, Divorced, Exec-managerial, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 28, Private, 113987, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, United-States, <=50K 24, Private, 216984, Some-college, 10, Married-civ-spouse, Other-service, Own-child, Asian-Pac-Islander, Female, 0, 0, 35, United-States, <=50K 51, Private, 177669, Some-college, 10, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 60, United-States, <=50K 32, Private, 164190, Some-college, 10, Never-married, Exec-managerial, Own-child, White, Male, 0, 0, 40, United-States, <=50K 61, Private, 355645, HS-grad, 9, Married-civ-spouse, Sales, Husband, Black, Male, 0, 0, 40, United-States, <=50K 60, ?, 134152, 9th, 5, Divorced, ?, Not-in-family, Black, Male, 0, 0, 35, United-States, <=50K 33, Private, 63079, HS-grad, 9, Divorced, Adm-clerical, Unmarried, Black, Female, 0, 0, 40, United-States, <=50K 42, Self-emp-not-inc, 217597, HS-grad, 9, Divorced, Sales, Own-child, White, Male, 0, 0, 50, ?, <=50K 24, Private, 381895, 11th, 7, Divorced, Machine-op-inspct, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 82, ?, 403910, HS-grad, 9, Never-married, ?, Not-in-family, White, Male, 0, 0, 3, United-States, <=50K 26, Private, 179010, Some-college, 10, Never-married, Craft-repair, Not-in-family, White, Male, 0, 0, 65, United-States, <=50K 18, Private, 436163, 11th, 7, Never-married, Prof-specialty, Own-child, White, Male, 0, 0, 20, United-States, <=50K 34, Private, 321709, HS-grad, 9, Never-married, Other-service, Not-in-family, White, Female, 0, 0, 28, United-States, <=50K 57, Private, 153918, HS-grad, 9, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 25, Private, 403788, HS-grad, 9, Never-married, Craft-repair, Other-relative, Black, Male, 0, 0, 40, United-States, <=50K 34, Private, 60567, 11th, 7, Divorced, Transport-moving, Unmarried, White, Male, 0, 880, 60, United-States, <=50K 71, Private, 138145, 9th, 5, Married-civ-spouse, Other-service, Husband, White, Male, 0, 0, 40, United-States, <=50K 35, Local-gov, 79649, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 50, United-States, <=50K 47, Private, 312088, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 50, Private, 208630, Masters, 14, Divorced, Sales, Not-in-family, White, Female, 0, 0, 50, United-States, >50K 33, Private, 182401, 10th, 6, Never-married, Adm-clerical, Not-in-family, Black, Male, 0, 0, 40, United-States, <=50K 38, Private, 32916, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 55, United-States, >50K 50, Private, 302372, Bachelors, 13, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 40, United-States, <=50K 45, Private, 155093, 10th, 6, Divorced, Other-service, Not-in-family, Black, Female, 0, 0, 38, Dominican-Republic, <=50K 32, Private, 192965, HS-grad, 9, Separated, Sales, Not-in-family, White, Female, 0, 0, 45, United-States, <=50K 39, Private, 107302, HS-grad, 9, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 45, ?, >50K 25, Local-gov, 514716, Bachelors, 13, Never-married, Adm-clerical, Own-child, Black, Female, 0, 0, 40, United-States, <=50K 20, Private, 270436, HS-grad, 9, Never-married, Machine-op-inspct, Own-child, White, Male, 0, 0, 40, United-States, <=50K 46, Private, 42972, Masters, 14, Married-civ-spouse, Prof-specialty, Wife, White, Female, 0, 0, 22, United-States, >50K 40, Private, 142657, Assoc-voc, 11, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 45, United-States, <=50K 66, Federal-gov, 47358, 10th, 6, Married-civ-spouse, Craft-repair, Husband, White, Male, 3471, 0, 40, United-States, <=50K 30, Private, 176175, Assoc-voc, 11, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 24, United-States, <=50K 36, Private, 131459, 7th-8th, 4, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 40, United-States, <=50K 57, Local-gov, 110417, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, White, Male, 99999, 0, 40, United-States, >50K 46, Private, 364548, Some-college, 10, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 48, United-States, >50K 27, Private, 177398, HS-grad, 9, Never-married, Other-service, Unmarried, White, Female, 0, 0, 64, United-States, <=50K 33, Private, 273243, HS-grad, 9, Married-civ-spouse, Craft-repair, Husband, Black, Male, 0, 0, 40, United-States, <=50K 58, Private, 147707, 11th, 7, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 40, United-States, <=50K 30, Private, 77266, HS-grad, 9, Divorced, Transport-moving, Not-in-family, White, Male, 0, 0, 55, United-States, <=50K 26, Private, 191648, Assoc-acdm, 12, Never-married, Machine-op-inspct, Other-relative, White, Female, 0, 0, 15, United-States, <=50K 81, ?, 120478, Assoc-voc, 11, Divorced, ?, Unmarried, White, Female, 0, 0, 1, ?, <=50K 32, Private, 211349, 10th, 6, Married-civ-spouse, Transport-moving, Husband, White, Male, 0, 0, 40, United-States, <=50K 22, Private, 203715, Some-college, 10, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 40, United-States, <=50K 31, Private, 292592, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female, 0, 0, 40, United-States, <=50K 29, Private, 125976, HS-grad, 9, Separated, Sales, Unmarried, White, Female, 0, 0, 35, United-States, <=50K 35, ?, 320084, Bachelors, 13, Married-civ-spouse, ?, Wife, White, Female, 0, 0, 55, United-States, >50K 30, ?, 33811, Bachelors, 13, Never-married, ?, Not-in-family, Asian-Pac-Islander, Female, 0, 0, 99, United-States, <=50K 34, Private, 204461, Doctorate, 16, Married-civ-spouse, Prof-specialty, Husband, White, Male, 0, 0, 60, United-States, >50K 54, Private, 337992, Bachelors, 13, Married-civ-spouse, Exec-managerial, Husband, Asian-Pac-Islander, Male, 0, 0, 50, Japan, >50K 37, Private, 179137, Some-college, 10, Divorced, Adm-clerical, Unmarried, White, Female, 0, 0, 39, United-States, <=50K 22, Private, 325033, 12th, 8, Never-married, Protective-serv, Own-child, Black, Male, 0, 0, 35, United-States, <=50K 34, Private, 160216, Bachelors, 13, Never-married, Exec-managerial, Not-in-family, White, Female, 0, 0, 55, United-States, >50K 30, Private, 345898, HS-grad, 9, Never-married, Craft-repair, Not-in-family, Black, Male, 0, 0, 46, United-States, <=50K 38, Private, 139180, Bachelors, 13, Divorced, Prof-specialty, Unmarried, Black, Female, 15020, 0, 45, United-States, >50K 71, ?, 287372, Doctorate, 16, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 10, United-States, >50K 45, State-gov, 252208, HS-grad, 9, Separated, Adm-clerical, Own-child, White, Female, 0, 0, 40, United-States, <=50K 41, ?, 202822, HS-grad, 9, Separated, ?, Not-in-family, Black, Female, 0, 0, 32, United-States, <=50K 72, ?, 129912, HS-grad, 9, Married-civ-spouse, ?, Husband, White, Male, 0, 0, 25, United-States, <=50K 45, Local-gov, 119199, Assoc-acdm, 12, Divorced, Prof-specialty, Unmarried, White, Female, 0, 0, 48, United-States, <=50K 31, Private, 199655, Masters, 14, Divorced, Other-service, Not-in-family, Other, Female, 0, 0, 30, United-States, <=50K 39, Local-gov, 111499, Assoc-acdm, 12, Married-civ-spouse, Adm-clerical, Wife, White, Female, 0, 0, 20, United-States, >50K 37, Private, 198216, Assoc-acdm, 12, Divorced, Tech-support, Not-in-family, White, Female, 0, 0, 40, United-States, <=50K 43, Private, 260761, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, Mexico, <=50K 65, Self-emp-not-inc, 99359, Prof-school, 15, Never-married, Prof-specialty, Not-in-family, White, Male, 1086, 0, 60, United-States, <=50K 43, State-gov, 255835, Some-college, 10, Divorced, Adm-clerical, Other-relative, White, Female, 0, 0, 40, United-States, <=50K 43, Self-emp-not-inc, 27242, Some-college, 10, Married-civ-spouse, Craft-repair, Husband, White, Male, 0, 0, 50, United-States, <=50K 32, Private, 34066, 10th, 6, Married-civ-spouse, Handlers-cleaners, Husband, Amer-Indian-Eskimo, Male, 0, 0, 40, United-States, <=50K 43, Private, 84661, Assoc-voc, 11, Married-civ-spouse, Sales, Husband, White, Male, 0, 0, 45, United-States, <=50K 32, Private, 116138, Masters, 14, Never-married, Tech-support, Not-in-family, Asian-Pac-Islander, Male, 0, 0, 11, Taiwan, <=50K 53, Private, 321865, Masters, 14, Married-civ-spouse, Exec-managerial, Husband, White, Male, 0, 0, 40, United-States, >50K 22, Private, 310152, Some-college, 10, Never-married, Protective-serv, Not-in-family, White, Male, 0, 0, 40, United-States, <=50K 27, Private, 257302, Assoc-acdm, 12, Married-civ-spouse, Tech-support, Wife, White, Female, 0, 0, 38, United-States, <=50K 40, Private, 154374, HS-grad, 9, Married-civ-spouse, Machine-op-inspct, Husband, White, Male, 0, 0, 40, United-States, >50K 58, Private, 151910, HS-grad, 9, Widowed, Adm-clerical, Unmarried, White, Female, 0, 0, 40, United-States, <=50K 22, Private, 201490, HS-grad, 9, Never-married, Adm-clerical, Own-child, White, Male, 0, 0, 20, United-States, <=50K 52, Self-emp-inc, 287927, HS-grad, 9, Married-civ-spouse, Exec-managerial, Wife, White, Female, 15024, 0, 40, United-States, >50K ================================================ FILE: doc/notebooks/data/co2_data.csv ================================================ ,co2,co2_detrended,rising 1958-03-29,316.1,0.33173315343884724,True 1958-04-05,317.3,1.524894697365255,True 1958-04-12,317.6,1.8180254614364912,True 1958-04-19,317.5,1.7111254720549027,True 1958-04-26,316.4,0.604194755612184,False 1958-05-03,316.9,1.0972333384893318,False 1958-05-10,317.2,1.3902412470565082,True 1958-05-17,317.5,1.683218507673189,True 1958-05-24,317.9,2.0761651466880267,True 1958-05-31,317.54999999999995,1.7190811904390557,False 1958-06-07,317.2,1.3619666652535898,False 1958-06-14,316.85,1.0048215974480286,False 1958-06-21,316.5,0.6476460133280852,False 1958-06-28,316.15,0.29043993918884325,False 1958-07-05,315.8,-0.06679659868535737,False 1958-07-12,315.8,-0.07406357402106778,False 1958-07-19,315.4,-0.4813609605554916,False 1958-07-26,315.5,-0.38868873203654175,False 1958-08-02,315.6,-0.29604686222290866,False 1958-08-09,315.1,-0.803435324883992,False 1958-08-16,315.0,-0.9108540938000829,False 1958-08-23,314.55,-1.3683031427619312,False 1958-08-30,314.1,-1.8257824455712353,False 1958-09-06,313.5,-2.4332919760404366,False 1958-09-13,313.44444444444446,-2.4963872635481152,False 1958-09-20,313.3888888888889,-2.559512726372702,False 1958-09-27,313.3333333333333,-2.6226683383587783,False 1958-10-04,313.27777777777777,-2.685854073361611,False 1958-10-11,313.22222222222223,-2.7490699052473246,False 1958-10-18,313.1666666666667,-2.8123158078927872,False 1958-10-25,313.1111111111111,-2.87559175518561,False 1958-11-01,313.05555555555554,-2.938897721024034,True 1958-11-08,313.0,-3.0022336793171007,True 1958-11-15,313.2,-2.810044048429063,True 1958-11-22,313.5,-2.5178843578460715,True 1958-11-29,314.0,-2.025754581509318,True 1958-12-06,314.5,-1.5336546933708064,True 1958-12-13,314.4,-1.6415846673934311,True 1958-12-20,314.7,-1.3495444775505234,True 1958-12-27,315.2,-0.8575340978263739,True 1959-01-03,315.2,-0.8655535022160166,True 1959-01-10,315.5,-0.5736026647250583,True 1959-01-17,315.6,-0.48168155937008805,True 1959-01-24,315.8,-0.2897901601781996,True 1959-01-31,315.4,-0.6979284411874005,True 1959-02-07,316.15,0.04390362355366051,True 1959-02-14,316.9,0.7857060599855572,True 1959-02-21,316.6,0.47747889403819954,True 1959-02-28,316.6,0.46922215163061765,True 1959-03-07,316.8,0.6609358586711096,False 1959-03-14,316.75,0.6026200410573779,False 1959-03-21,316.7,0.5442747246763133,True 1959-03-28,316.7,0.5358999354040179,True 1959-04-04,317.7,1.5274956991058843,True 1959-04-11,317.1,0.9190620416366073,True 1959-04-18,317.6,1.4105989888400359,True 1959-04-25,318.3,2.1021065665493666,True 1959-05-02,318.2,1.9935848005870866,True 1959-05-09,318.7,2.4850337167648604,True 1959-05-16,318.0,1.77645334088362,False 1959-05-23,318.4,2.167843698733577,False 1959-05-30,318.45,2.209204816094257,False 1959-06-06,318.5,2.250536718734395,False 1959-06-13,318.1,1.8418394324119163,False 1959-06-20,317.8,1.5331129828740586,False 1959-06-27,317.7,1.4243573958573847,False 1959-07-04,316.8,0.5155726970876913,False 1959-07-11,316.8,0.5067589122799632,False 1959-07-18,316.4,0.09791606713844203,False 1959-07-25,316.1,-0.21095581264313523,False 1959-08-01,315.6,-0.7198567013821844,False 1959-08-08,314.9,-1.4287865734066258,False 1959-08-15,314.95,-1.3877454030549075,False 1959-08-22,315.0,-1.3467331646766638,False 1959-08-29,314.1,-2.2557498326319205,False 1959-09-05,314.4,-1.9647953812916512,False 1959-09-12,313.9,-2.4738697850374933,False 1959-09-19,313.5,-2.882973018261737,False 1959-09-26,313.5,-2.8921050553675514,False 1959-10-03,313.0,-3.401265870768839,False 1959-10-10,313.1,-3.3104554388901306,True 1959-10-17,313.4,-3.0196737341668154,True 1959-10-24,313.4,-3.0289207310448774,True 1959-10-31,314.1,-2.3381964039812146,True 1959-11-07,314.4,-2.0475007274434347,True 1959-11-14,314.8,-1.656833675909695,True 1959-11-21,315.2,-1.266195223869147,True 1959-11-28,315.1,-1.3755853458214915,True 1959-12-05,315.0,-1.485004016277344,True 1959-12-12,315.6,-0.8944512097579036,True 1959-12-19,315.8,-0.7039269007951816,True 1959-12-26,315.7,-0.8134310639319438,True 1960-01-02,315.7,-0.822963673721631,True 1960-01-09,316.4,-0.1325247047284961,True 1960-01-16,316.7,0.15788586847253328,True 1960-01-23,316.5,-0.051731928704327856,True 1960-01-30,316.6,0.038621929144596834,True 1960-02-06,316.6,0.028947467412024253,True 1960-02-13,316.9,0.31924471147993927,True 1960-02-20,317.4,0.8095136867199244,True 1960-02-27,317.0,0.3997544184924209,True 1960-03-05,316.9,0.28996693214725155,True 1960-03-12,317.7,1.0801512530236437,True 1960-03-19,318.0,1.3703074064498537,True 1960-03-26,317.7,1.0604354177435766,True 1960-04-02,318.6,1.9505353122117413,True 1960-04-09,319.3,2.640607115150374,True 1960-04-16,319.0,2.3306508518449505,True 1960-04-23,319.0,2.3206665475701698,True 1960-04-30,319.7,3.010654227589896,True 1960-05-07,319.9,3.2006139171573977,True 1960-05-14,319.8,3.0905456415151207,True 1960-05-21,320.0,3.2804494258946306,True 1960-05-28,320.0,3.2703252955170683,False 1960-06-04,319.4,2.6601732755925127,False 1960-06-11,320.0,3.2499933913205723,False 1960-06-18,319.4,2.639785667889896,False 1960-06-25,319.0,2.2295501304786285,False 1960-07-02,318.1,1.3192868042538635,False 1960-07-09,318.6,1.8089957143722017,False 1960-07-16,318.4,1.598676885979387,False 1960-07-23,317.9,1.088330344210533,False 1960-07-30,317.3,0.47795611418996486,False 1960-08-06,316.6,-0.2324457789688381,False 1960-08-13,316.7,-0.14287531016310595,False 1960-08-20,315.1,-1.7533324543006188,False 1960-08-27,314.7,-2.1638171863001503,False 1960-09-03,314.7,-2.1743294810910356,False 1960-09-10,314.5,-2.3848693136134216,False 1960-09-17,314.2,-2.6954366588182097,False 1960-09-24,313.3,-3.606031491667011,False 1960-10-01,313.6,-3.316653787132168,False 1960-10-08,313.3,-3.627303520196847,True 1960-10-15,313.9,-3.0379806658548887,True 1960-10-22,314.2,-2.7486851991108097,True 1960-10-29,314.2,-2.7594170949799377,True 1960-11-05,314.5,-2.470176328488378,True 1960-11-12,315.1,-1.880962874672889,True 1960-11-19,315.1,-1.8917767085811192,True 1960-11-26,315.4,-1.6026178052713362,True 1960-12-03,315.8,-1.213486139812403,True 1960-12-10,316.0,-1.02438168728429,True 1960-12-17,316.2,-0.8353044227774262,True 1960-12-24,316.4,-0.6462543213930303,True 1960-12-31,316.6,-0.4572313582430638,True 1961-01-07,316.7,-0.36823550845036834,True 1961-01-14,317.0,-0.079266747148381,True 1961-01-21,317.0,-0.09032504948123687,True 1961-01-28,317.0,-0.10141039060397361,True 1961-02-04,317.0,-0.1125227456822131,True 1961-02-11,317.7,0.5763379101074975,True 1961-02-18,317.9,0.7651716015781176,True 1961-02-25,318.0,0.8539783535317156,True 1961-03-04,318.0,0.8427581907595254,True 1961-03-11,318.5,1.3315111380422877,True 1961-03-18,318.9,1.7202372201497838,True 1961-03-25,318.7,1.5089364618411878,True 1961-04-01,319.4,2.197608887864817,True 1961-04-08,319.5,2.286254522958359,True 1961-04-15,318.9,1.6748733918487346,True 1961-04-22,319.7,2.463465519252111,True 1961-04-29,319.6,2.3520309298738766,True 1961-05-06,320.6,3.340569648408689,True 1961-05-13,320.4,3.1290816995405066,True 1961-05-20,320.6,3.3175671079425797,False 1961-05-27,320.3,3.0060258982773576,False 1961-06-03,320.0,2.6944580951964667,False 1961-06-10,320.0,2.6828637233409722,False 1961-06-17,319.6,2.271242807341139,False 1961-06-24,319.4,2.0595953718163287,False 1961-07-01,319.2,1.8479214413754903,False 1961-07-08,319.0,1.6362210406164763,False 1961-07-15,318.4,1.024494194126646,False 1961-07-22,317.1,-0.28725907351741853,False 1961-07-29,317.9,0.5009612622499162,False 1961-08-05,317.9,0.4891552259837795,False 1961-08-12,317.3,-0.12267715777136345,False 1961-08-19,316.7,-0.7345358644821545,False 1961-08-26,315.2,-2.2464208696256946,False 1961-09-02,315.2,-2.258332148689817,False 1961-09-09,314.9,-2.5702696771732576,False 1961-09-16,314.5,-2.9822334305853246,True 1961-09-23,315.0,-2.4942233844462294,True 1961-09-30,315.6,-1.9062395142867672,True 1961-10-07,314.9,-2.61828179564867,True 1961-10-14,315.4,-2.130350204084152,True 1961-10-21,315.4,-2.142444715156387,True 1961-10-28,315.7,-1.8545653044391202,True 1961-11-04,315.8,-1.766711947516967,True 1961-11-11,315.7,-1.8788846199852856,True 1961-11-18,316.2,-1.391083297450109,True 1961-11-25,316.5,-1.1033079555281802,True 1961-12-02,316.5,-1.11555856984711,True 1961-12-09,317.0,-0.6278351160451052,True 1961-12-16,316.9,-0.7401375697712069,True 1961-12-23,317.1,-0.5524659066851427,True 1961-12-30,317.4,-0.2648201024575201,True 1962-01-06,317.9,0.2227998672305489,True 1962-01-13,318.1,0.4103940266871291,True 1962-01-20,318.0,0.29796240020931464,True 1962-01-27,317.7,-0.01449498791617998,True 1962-02-03,318.0,0.27302188658632076,True 1962-02-10,318.3,0.5605130479819991,True 1962-02-17,318.9,1.1479785205250437,True 1962-02-24,319.3,1.5354183284591727,True 1962-03-03,319.2,1.4228324960171221,True 1962-03-10,319.4,1.610221047421021,True 1962-03-17,319.9,2.0975840068822436,True 1962-03-24,319.7,1.8849213986014206,True 1962-03-31,320.2,2.37223324676836,True 1962-04-07,320.2,2.359519575562274,True 1962-04-14,321.0,3.1467804091515745,True 1962-04-21,320.7,2.834015771693771,True 1962-04-28,320.3,2.4212256873360047,True 1962-05-05,320.8,2.9084101802142186,True 1962-05-12,320.7,2.79556927445401,True 1962-05-19,321.0,3.082702994170006,True 1962-05-26,321.1,3.169811363466181,False 1962-06-02,320.9,2.9568944064356515,False 1962-06-09,320.8,2.843952147161076,False 1962-06-16,320.5,2.5309846097140962,False 1962-06-23,320.1,2.1179918181556445,False 1962-06-30,320.2,2.2049737965360237,False 1962-07-07,320.1,2.0919305688947816,False 1962-07-14,319.9,1.8788621592605637,False 1962-07-21,319.0,0.9657685916515675,False 1962-07-28,318.7,0.6526498900749971,False 1962-08-04,318.6,0.5395060785273813,False 1962-08-11,317.2,-0.8736628190054603,False 1962-08-18,317.4,-0.6868567785484743,False 1962-08-25,317.2,-0.9000757761372711,False 1962-09-01,317.0,-1.1133197878182841,False 1962-09-08,316.8,-1.3265887896486674,False 1962-09-15,316.6,-1.5398827576963754,False 1962-09-22,315.7,-2.4532016680400943,False 1962-09-29,315.9,-2.2665454967690266,False 1962-10-06,315.1,-3.0799142199833227,False 1962-10-13,315.4,-2.7933078137940015,True 1962-10-20,315.7,-2.506726254322473,True 1962-10-27,315.7,-2.520169517701163,True 1962-11-03,315.9,-2.333637580073116,True 1962-11-10,316.4,-1.8471304175922114,True 1962-11-17,316.9,-1.3606480064229345,True 1962-11-24,317.0,-1.2741903227405942,True 1962-12-01,317.1,-1.1877573427312882,True 1962-12-08,317.3,-1.0013490425917553,True 1962-12-15,317.6,-0.7149653985295572,True 1962-12-22,318.1,-0.22860638676291956,True 1962-12-29,318.3,-0.042271983520834056,True 1963-01-05,318.5,0.1440378349569187,True 1963-01-12,318.7,0.33032309241986013,True 1963-01-19,318.9,0.5165838126068252,True 1963-01-26,318.8,0.4028200192458371,True 1963-02-02,318.7,0.28903173605408483,True 1963-02-09,318.9,0.47521898673824126,True 1963-02-16,319.1,0.6613817949940994,True 1963-02-23,319.3,0.8475201845067204,True 1963-03-02,319.3,0.8336341789503763,True 1963-03-09,319.7,1.2197238019887209,True 1963-03-16,319.8,1.3057890772745964,True 1963-03-23,320.3,1.7918300284501356,True 1963-03-30,320.2,1.6778466791466258,True 1963-04-06,320.3,1.7638390529848493,True 1963-04-13,320.9,2.349807173574561,True 1963-04-20,322.0,3.4357510645149887,True 1963-04-27,321.9,3.321670749394457,True 1963-05-04,321.9,3.3075662517907176,True 1963-05-11,321.9,3.293437595270632,True 1963-05-18,322.2,3.5792848033904647,False 1963-05-25,322.2,3.565107899695647,False 1963-06-01,322.3,3.6509069077208096,False 1963-06-08,322.0,3.336681850989976,False 1963-06-15,321.8,3.122432753016369,False 1963-06-22,320.8,2.1081596373024922,False 1963-06-29,320.4,1.693862527340002,False 1963-07-06,320.1,1.3795414466100624,False 1963-07-13,319.8,1.0651964185827865,False 1963-07-20,319.5,0.7508274667177375,False 1963-07-27,319.0,0.23643461446368974,False 1963-08-03,318.6,-0.17798211474121217,False 1963-08-10,318.2,-0.5924226974698854,False 1963-08-17,317.7,-1.1068871103055358,False 1963-08-24,317.1,-1.7213753298424308,False 1963-08-31,316.4,-2.4358873326855246,False 1963-09-07,316.8,-2.0504230954504123,False 1963-09-14,315.9,-2.964982594763626,False 1963-09-21,316.0,-2.879565807262111,False 1963-09-28,315.9,-2.994172709593954,True 1963-10-05,316.2,-2.7088032784176335,True 1963-10-12,315.6,-3.323457490402518,True 1963-10-19,316.1,-2.8381353222287657,True 1963-10-26,316.3,-2.652836750587255,True 1963-11-02,316.6,-2.3675617521794834,True 1963-11-09,316.8,-2.182310303717884,True 1963-11-16,317.1,-1.8970823819253724,True 1963-11-23,317.3,-1.7118779635358692,True 1963-11-30,317.5,-1.5266970252939132,True 1963-12-07,318.0,-1.041539543954741,True 1963-12-14,318.2,-0.8564054962844239,True 1963-12-21,318.5,-0.5712948590597193,True 1963-12-28,318.7,-0.38620760906809437,True 1964-01-04,319.0,-0.10114372310783892,True 1964-01-11,319.4,0.28389682201202504,True 1964-01-18,319.8,0.6689140494718231,True 1964-01-25,319.91578947368424,0.7696974561253,True 1964-02-01,320.0315789473684,0.8704575914469501,True 1964-02-08,320.14736842105265,0.9711944785849482,True 1964-02-15,320.2631578947369,1.0719081406765554,True 1964-02-22,320.37894736842105,1.1725986008482323,True 1964-02-29,320.4947368421053,1.2732658822159237,True 1964-03-07,320.61052631578946,1.3739100078846604,True 1964-03-14,320.7263157894737,1.4745310009488435,True 1964-03-21,320.8421052631579,1.5751288844920737,True 1964-03-28,320.9578947368421,1.6757036815870947,True 1964-04-04,321.0736842105263,1.7762554152961911,True 1964-04-11,321.18947368421055,1.8767841086706767,True 1964-04-18,321.30526315789473,1.9772897847511217,True 1964-04-25,321.42105263157896,2.0777724665675805,True 1964-05-02,321.53684210526313,2.17823217713908,True 1964-05-09,321.65263157894736,2.278668939474187,True 1964-05-16,321.7684210526316,2.379082776570442,True 1964-05-23,321.88421052631577,2.479473711414812,True 1964-05-30,322.0,2.5798417669835203,True 1964-06-06,322.0,2.564397492557873,False 1964-06-13,321.8333333333333,2.382263718109982,False 1964-06-20,321.6666666666667,2.2001071332506967,False 1964-06-27,321.5,2.0179277609130963,False 1964-07-04,321.1,1.6023922906863959,False 1964-07-11,319.9,0.3868340788156388,False 1964-07-18,320.2,0.6712531482019699,False 1964-07-25,320.0,0.45564952173555184,False 1964-08-01,319.1,-0.4599767777040711,False 1964-08-08,318.85,-0.7256257272480298,False 1964-08-15,318.6,-0.991297304038369,False 1964-08-22,318.2,-1.4069914852277634,False 1964-08-29,318.1,-1.5227082479795513,False 1964-09-05,317.4,-2.2384475694680077,False 1964-09-12,316.5,-3.1542094268779124,False 1964-09-19,315.5,-4.169993797405027,False 1964-09-26,317.0,-2.6858006582557437,True 1964-10-03,316.9,-2.8016299866471286,True 1964-10-10,316.5,-3.217481759807015,True 1964-10-17,316.8,-2.933355954974104,True 1964-10-24,317.0,-2.7492525493976814,True 1964-10-31,317.6,-2.1651715203378785,True 1964-11-07,317.7,-2.0811128450656042,True 1964-11-14,317.6,-2.197076500862238,True 1964-11-21,317.5,-2.3130624650202662,True 1964-11-28,318.1,-1.729070714842635,True 1964-12-05,318.4,-1.4451012276432493,True 1964-12-12,318.5,-1.3611539807465078,True 1964-12-19,318.9,-0.9772289514878025,True 1964-12-26,318.9,-0.993326117213087,True 1965-01-02,319.0,-0.9094454552790694,True 1965-01-09,319.1,-0.8255869430532812,True 1965-01-16,319.1,-0.8417505579140538,True 1965-01-23,319.7,-0.2579362772503373,True 1965-01-30,320.1,0.12585592153828884,True 1965-02-06,320.2,0.20962606104120596,True 1965-02-13,320.1,0.09337416383738173,True 1965-02-20,320.7,0.6771002524946539,True 1965-02-27,320.8,0.7608043495705488,True 1965-03-06,321.0,0.9444864776115196,True 1965-03-13,320.9,0.8281466591533899,True 1965-03-20,320.4,0.3117849167214217,True 1965-03-27,321.4,1.2954012728297926,True 1965-04-03,321.9,1.7789957499822435,True 1965-04-10,322.2,2.062568370671613,True 1965-04-17,322.1,1.9461191573800534,True 1965-04-24,321.8,1.6296481325788363,False 1965-05-01,322.4,2.2131553187287523,False 1965-05-08,322.2,1.9966407382797229,False 1965-05-15,321.9,1.680104413670847,False 1965-05-22,321.6,1.3635463673306276,False 1965-05-29,322.2,1.9469666216766086,False 1965-06-05,321.8,1.5303651991159768,True 1965-06-12,321.7,1.4137421220447663,True 1965-06-19,321.7,1.3970974128484954,True 1965-06-26,321.9,1.5804310939019501,False 1965-07-03,321.9,1.5637431875690595,False 1965-07-10,321.8,1.4470337162031228,False 1965-07-17,321.7,1.3303027021465255,False 1965-07-24,320.4,0.013550167731182228,False 1965-07-31,319.4,-1.0032238647219174,False 1965-08-07,319.4,-1.0200193729024818,False 1965-08-14,318.0,-2.4368363345109856,False 1965-08-21,318.8,-1.6536747272586467,False 1965-08-28,318.7,-1.7705345288673584,False 1965-09-04,318.3,-2.1874157170697686,False 1965-09-11,318.0,-2.504318269609371,False 1965-09-18,318.2,-2.3212421642402887,False 1965-09-25,316.8,-3.738187378727332,False 1965-10-02,316.6,-3.9551538908462476,False 1965-10-09,317.2,-3.3721416783834,True 1965-10-16,317.8,-2.7891507191358187,True 1965-10-23,317.5,-3.1061809909114686,True 1965-10-30,317.6,-3.0232324715288996,True 1965-11-06,318.3,-2.3403051388174276,True 1965-11-13,319.2,-1.4573989706171915,True 1965-11-20,318.9,-1.7745139447789597,True 1965-11-27,319.1,-1.5916500391642217,True 1965-12-04,319.0,-1.7088072316454372,True 1965-12-11,319.3,-1.4259855001055257,True 1965-12-18,319.3,-1.4431848224383543,True 1965-12-25,319.7,-1.0604051765484428,True 1966-01-01,319.6,-1.1776465403509064,True 1966-01-08,320.4,-0.3949088917719905,True 1966-01-15,320.6,-0.21219220874814937,True 1966-01-22,321.0,0.17050353077286218,True 1966-01-29,321.1,0.2531783488329893,True 1966-02-05,321.2,0.33583226746316086,True 1966-02-12,321.7,0.8184653086837557,True 1966-02-19,321.6,0.7010774945043181,True 1966-02-26,321.8,0.8836688469236265,True 1966-03-05,322.1,1.1662393879297497,True 1966-03-12,322.1,1.1487891395000247,True 1966-03-19,322.5,1.5313181236010678,True 1966-03-26,322.8,1.8138263621887631,True 1966-04-02,323.5,2.496313877208138,True 1966-04-09,323.6,2.5787806905936463,True 1966-04-16,323.8,2.7612268242688174,True 1966-04-23,323.9,2.843652300146573,True 1966-04-30,323.5,2.42605714012916,True 1966-05-07,324.0,2.9084413661078656,True 1966-05-14,324.1,2.9908049999634727,True 1966-05-21,323.7,2.573148063565725,True 1966-05-28,324.3,3.155470578774043,False 1966-06-04,324.0,2.837772567436673,False 1966-06-11,323.8,2.6200540513914916,False 1966-06-18,323.7,2.502315052465292,False 1966-06-25,323.3,2.0845555924744303,False 1966-07-02,322.8,1.566775693224315,False 1966-07-09,322.9,1.6489753765097248,False 1966-07-16,322.5,1.2311546641146833,False 1966-07-23,322.1,0.813313577812437,False 1966-07-30,321.7,0.3954521393654886,False 1966-08-06,321.3,-0.02242962947440219,False 1966-08-13,320.8,-0.5403317069661284,False 1966-08-20,319.1,-2.2582540713793833,False 1966-08-27,319.6,-1.776196700994717,False 1966-09-03,319.9,-1.4941595741032643,False 1966-09-10,318.2,-3.2121426690068233,False 1966-09-17,318.4,-3.0301459640182316,False 1966-09-24,318.3,-3.1481694374607514,False 1966-10-01,317.9,-3.5662130676686274,False 1966-10-08,317.9,-3.5842768329866885,True 1966-10-15,318.2,-3.3023607117705183,True 1966-10-22,318.6,-2.92046468238658,True 1966-10-29,318.3,-3.238588723211933,True 1966-11-05,318.9,-2.6567328126344023,True 1966-11-12,319.5,-2.0748969290526134,True 1966-11-19,320.0,-1.59308105087581,True 1966-11-26,320.2,-1.4112851565241726,True 1966-12-03,320.8,-0.8295092244284206,True 1966-12-10,320.8,-0.8477532330301187,True 1966-12-17,321.1,-0.5660171607815982,True 1966-12-24,321.3,-0.3843009861458313,True 1966-12-31,321.3,-0.4026046875966358,True 1967-01-07,321.9,0.179071756381461,True 1967-01-14,322.9,1.1607283672933022,True 1967-01-21,322.6333333333333,0.8756984999661768,True 1967-01-28,322.3666666666667,0.5906488425500243,True 1967-02-04,322.1,0.3055794165173893,False 1967-02-11,322.2,0.38715690999663366,False 1967-02-18,322.8,0.9687146777723115,True 1967-02-25,322.6,0.7502527412846121,True 1967-03-04,322.9,1.031771121963061,True 1967-03-11,322.6,0.7132698412266336,True 1967-03-18,323.3,1.3947489204832664,True 1967-03-25,323.2,1.2762083811303455,True 1967-04-01,323.1,1.1576482445545366,True 1967-04-08,324.2,2.2390685321316255,True 1967-04-15,324.4,2.4204692652267568,True 1967-04-22,324.6,2.6018504651944454,True 1967-04-29,325.1,3.083212153378156,True 1967-05-06,325.2,3.1645543511107803,True 1967-05-13,324.7,2.645877079714637,False 1967-05-20,325.0,2.9271803605010405,False 1967-05-27,324.9,2.808464214770652,False 1967-06-03,324.9,2.7897286638134915,False 1967-06-10,324.6,2.4709737289087457,False 1967-06-17,323.3,1.1521994313247887,False 1967-06-24,323.5,1.333405792319411,False 1967-07-01,322.8,0.6145928331396249,False 1967-07-08,322.8,0.5957605750215862,False 1967-07-15,322.4,0.17690903919077527,False 1967-07-22,322.4,0.15803824686202006,False 1967-07-29,322.0,-0.26085178076061766,False 1967-08-05,321.6,-0.6797610224839445,False 1967-08-12,321.4,-0.8986894571254993,False 1967-08-19,320.4,-1.9176370635133253,False 1967-08-26,320.0,-2.3366038204864594,False 1967-09-02,320.0,-2.355589706894534,False 1967-09-09,319.4,-2.9745947015981073,False 1967-09-16,319.3,-3.0936187834681164,False 1967-09-23,319.0,-3.412661931386708,False 1967-09-30,318.8,-3.631724124246432,True 1967-10-07,318.8,-3.650805340950626,True 1967-10-14,319.8,-2.669905560413497,True 1967-10-21,319.4,-3.0890247615599264,True 1967-10-28,319.8,-2.7081629233254034,True 1967-11-04,320.0,-2.527320024656433,True 1967-11-11,320.3,-2.2464960445099678,True 1967-11-18,320.9,-1.6656909618540112,True 1967-11-25,321.5,-1.084904755666912,True 1967-12-02,321.4,-1.2041374049381943,True 1967-12-09,321.8,-0.8233888886677505,True 1967-12-16,322.2,-0.44265918586654607,True 1967-12-23,321.9,-0.7619482755559375,True 1967-12-30,322.3,-0.38125613676828607,True 1968-01-06,322.4,-0.30058274854661704,True 1968-01-13,322.5,-0.21992808994463076,True 1968-01-20,322.5,-0.2392921400269188,True 1968-01-27,322.8,0.04132512213141126,True 1968-02-03,322.6,-0.17807628255576446,True 1968-02-10,323.1,0.302503666814971,True 1968-02-17,323.4,0.5830649911359842,True 1968-02-24,323.1,0.2636077112892963,True 1968-03-02,323.1,0.24413184814579836,True 1968-03-09,323.8,0.9246374225659224,True 1968-03-16,323.8,0.9051244553991751,True 1968-03-23,324.2,1.2855929674843765,True 1968-03-30,324.7,1.7660429796496828,True 1968-04-06,324.7,1.7464745127124388,True 1968-04-13,325.0,2.026887587479223,True 1968-04-20,324.8,1.807282224746018,True 1968-04-27,325.4,2.3876584452978022,True 1968-05-04,325.6,2.568016269909151,True 1968-05-11,325.0,1.9483557193435104,True 1968-05-18,325.5,2.4286768143539916,True 1968-05-25,325.8,2.7089795756826334,False 1968-06-01,325.6,2.489264024060958,False 1968-06-08,325.7,2.569530180209597,False 1968-06-15,325.5,2.3497780648385174,False 1968-06-22,324.9,1.7300076986469435,False 1968-06-29,324.6,1.4102191023233672,False 1968-07-06,324.7,1.4904122965454576,False 1968-07-13,324.1,0.8705873019803221,False 1968-07-20,323.9,0.6507441392840292,False 1968-07-27,323.4,0.1308828291022337,False 1968-08-03,322.4,-0.8889966079303235,False 1968-08-10,322.2,-1.108894151189645,False 1968-08-17,322.0,-1.3288097800624428,False 1968-08-24,321.7,-1.6487434739461264,False 1968-08-31,321.4,-1.9686952122489174,False 1968-09-07,320.4,-2.988664974389792,False 1968-09-14,321.1,-2.3086527397982763,False 1968-09-21,319.7,-3.728658487915027,False 1968-09-28,319.8,-3.6486821981909543,False 1968-10-05,320.5,-2.968723850088111,True 1968-10-12,320.5,-2.9887834230790986,True 1968-10-19,320.2,-3.308860896647218,True 1968-10-26,319.9,-3.6289562502867057,True 1968-11-02,320.7,-2.84906946350236,True 1968-11-09,320.8,-2.7692005158097004,True 1968-11-16,321.4,-2.189349386735273,True 1968-11-23,321.7,-1.9095160558159137,True 1968-11-30,322.0,-1.6297005025996327,True 1968-12-07,322.4,-1.249902706644889,True 1968-12-14,322.9,-0.7701226475210206,True 1968-12-21,323.3,-0.39036030480798445,True 1968-12-28,323.1,-0.6106156580967195,True 1969-01-04,323.3,-0.43088868698868055,True 1969-01-11,324.0,0.24882062890395673,True 1969-01-18,324.3,0.528512309958046,True 1969-01-25,324.1,0.30818637653999303,True 1969-02-01,324.1,0.2878428490051874,True 1969-02-08,323.9,0.06748174769842308,True 1969-02-15,324.3,0.447103092953796,True 1969-02-22,324.8,0.9267069050945906,True 1969-03-01,325.1,1.2062932044333365,True 1969-03-08,325.5,1.5858620112717858,True 1969-03-15,325.7,1.7654133459011518,True 1969-03-22,325.9,1.9449472286016203,True 1969-03-29,325.8,1.8244636796429177,True 1969-04-05,326.2,2.2039627192837656,True 1969-04-12,327.1,3.0834443677724153,True 1969-04-19,326.5,2.46290864534609,True 1969-04-26,326.5,2.44235557223152,True 1969-05-03,327.5,3.421785168644533,True 1969-05-10,327.8,3.7011974547903606,False 1969-05-17,326.8,2.680592450863344,True 1969-05-24,326.9,2.75997017704708,False 1969-05-31,327.4,3.239330653514685,False 1969-06-07,326.5,2.318673900428223,False 1969-06-14,326.7,2.4979999379390847,False 1969-06-21,326.7,2.477308786188132,False 1969-06-28,326.3,2.0566004653052232,False 1969-07-05,326.1,1.835874995409597,False 1969-07-12,326.0,1.7151323966097038,False 1969-07-19,325.7,1.3943726890033759,False 1969-07-26,325.4,1.073595892677531,False 1969-08-02,324.5,0.15280202770856022,False 1969-08-09,324.5,0.13199111416184905,False 1969-08-16,323.1,-1.2888368279078009,False 1969-08-23,322.5,-1.9096817784563314,False 1969-08-30,323.1,-1.3305437174503822,False 1969-09-06,322.2,-2.25142262486753,False 1969-09-13,322.7,-1.7723184806957875,False 1969-09-20,322.8,-1.6932312649341839,False 1969-09-27,321.9,-2.6141609575923894,False 1969-10-04,321.5,-3.0351075386906814,False 1969-10-11,321.8,-2.756070988260376,False 1969-10-18,322.0,-2.5770512863432486,True 1969-10-25,321.9,-2.698048412991966,True 1969-11-01,322.2,-2.419062348269847,True 1969-11-08,322.6,-2.040093072251011,True 1969-11-15,322.7,-1.9611405650203437,True 1969-11-22,323.1,-1.58220480667336,True 1969-11-29,323.5,-1.2032857773165233,True 1969-12-06,323.9,-0.8243834570667445,True 1969-12-13,323.9,-0.8454978260519397,True 1969-12-20,324.2,-0.566628864410518,True 1969-12-27,324.5,-0.28777655229191623,True 1970-01-03,324.7,-0.10894086985609874,True 1970-01-10,325.4,0.5698782027261018,True 1970-01-17,325.0,0.148680685273348,True 1970-01-24,324.8,-0.07253340240680473,True 1970-01-31,325.5,0.6062359594827171,True 1970-02-07,325.7,0.7849887907282209,True 1970-02-14,326.0,1.0637251111052137,True 1970-02-21,326.3,1.3424449403785275,True 1970-02-28,326.1,1.1211482983021028,True 1970-03-07,326.8,1.799835204619285,True 1970-03-14,326.8,1.7785056790627323,True 1970-03-21,327.5,2.4571597413541326,True 1970-03-28,326.9,1.8357974112046236,True 1970-04-04,328.2,3.114418708314588,True 1970-04-11,327.8,2.693023652373654,True 1970-04-18,327.8,2.671612263060581,True 1970-04-25,328.5,3.3501845600435445,True 1970-05-02,327.9,2.728740562979908,False 1970-05-09,327.5,2.307280291516406,True 1970-05-16,328.0,2.785803765288847,False 1970-05-23,328.3,3.0643110039223984,False 1970-05-30,327.9,2.6428020270314505,True 1970-06-06,327.5,2.221276854219809,False 1970-06-13,327.8,2.4997355050803094,False 1970-06-20,327.7,2.3781779991951453,False 1970-06-27,327.2,1.8566043561357901,False 1970-07-04,327.2,1.835014595463008,False 1970-07-11,326.2,0.8134087367267284,False 1970-07-18,326.2,0.7917867994662515,False 1970-07-25,325.6,0.17014880320999737,False 1970-08-01,325.2,-0.2515052325242664,False 1970-08-08,325.2,-0.27317528822948134,False 1970-08-15,324.8,-0.6948613444093894,False 1970-08-22,324.8,-0.71656338157851,False 1970-08-29,323.3,-2.2382813802619808,False 1970-09-05,322.9,-2.6600153209957966,False 1970-09-12,323.5,-2.0817651843265708,False 1970-09-19,323.1,-2.5035309508118075,False 1970-09-26,323.1,-2.525312601019607,True 1970-10-03,323.2,-2.4471101155289716,False 1970-10-10,323.5,-2.1689234749294997,False 1970-10-17,322.9,-2.790752659821578,True 1970-10-24,323.0,-2.712597650816292,True 1970-10-31,323.1,-2.634458428535538,True 1970-11-07,323.6,-2.1563349736119903,True 1970-11-14,323.7,-2.078227266688998,True 1970-11-21,324.2,-1.6001352884205744,True 1970-11-28,324.7,-1.1220590194715783,True 1970-12-05,324.7,-1.1439984405176347,True 1970-12-12,325.0,-0.865953532244987,True 1970-12-19,325.2,-0.6879242753507242,True 1970-12-26,325.5,-0.40991065054259934,True 1971-01-02,325.7,-0.23191263853919963,True 1971-01-09,325.8,-0.15393022006981028,True 1971-01-16,325.9,-0.07596337587443713,True 1971-01-23,326.7,0.7019879132961933,True 1971-01-30,326.6,0.5799236666805996,True 1971-02-06,326.5,0.4578439035065003,True 1971-02-13,326.4,0.33574864299089313,True 1971-02-20,326.7,0.6136379043401234,True 1971-02-27,327.0,0.8915117067496681,True 1971-03-06,327.1,0.9693700694044196,True 1971-03-13,327.3,1.1472130114783567,True 1971-03-20,327.0,0.8250405521347943,True 1971-03-27,327.4,1.2028527105263151,True 1971-04-03,327.4,1.180649505794861,True 1971-04-10,327.1,0.8584309570714481,True 1971-04-17,327.7,1.4361970834763724,True 1971-04-24,328.5,2.2139479041193226,True 1971-05-01,328.2,1.8916834380991645,True 1971-05-08,329.0,2.6694037045040773,True 1971-05-15,329.2,2.847108722411349,False 1971-05-22,328.9,2.524798510887763,False 1971-05-29,328.8,2.4024730889891543,False 1971-06-05,328.5,2.0801324757607063,False 1971-06-12,328.8,2.3577766902368467,False 1971-06-19,328.1,1.635405751441283,False 1971-06-26,328.5,2.013019678386968,False 1971-07-03,327.9,1.390618490076065,False 1971-07-10,327.8,1.2682022055001312,False 1971-07-17,327.5,0.9457708436398207,False 1971-07-24,326.2,-0.376675576534808,False 1971-07-31,326.7,0.10086296393541261,False 1971-08-07,326.1,-0.5216135160009117,False 1971-08-14,325.6,-1.044104997406066,False 1971-08-21,325.3,-1.3666114613530453,False 1971-08-28,324.0,-2.689132888925542,False 1971-09-04,323.6,-3.111669261217969,False 1971-09-11,323.5,-3.234220559335597,False 1971-09-18,323.2,-3.556786764394303,False 1971-09-25,323.3,-3.4793678575207423,True 1971-10-02,323.3,-3.501963819852392,True 1971-10-09,322.9,-3.9245746325374284,True 1971-10-16,323.5,-3.347200276734668,True 1971-10-23,323.6,-3.269840733613705,True 1971-10-30,324.4,-2.4924959843551164,True 1971-11-06,324.3,-2.6151660101497782,True 1971-11-13,324.5,-2.437850792199754,True 1971-11-20,325.0,-1.9605503117174976,True 1971-11-27,325.5,-1.4832645499264459,True 1971-12-04,325.3,-1.7059934880605852,True 1971-12-11,325.9,-1.1287371073648274,True 1971-12-18,326.2,-0.8514953890946799,True 1971-12-25,326.3,-0.7742683145164051,True 1972-01-01,326.6,-0.4970558649071677,True 1972-01-08,326.6,-0.5198580215546258,True 1972-01-15,326.6,-0.5426747657573969,True 1972-01-22,326.6,-0.5655060788246828,True 1972-01-29,327.2,0.011648057923423494,True 1972-02-05,327.4,0.1887876631563472,True 1972-02-12,327.9,0.6659127555324744,True 1972-02-19,327.8,0.5430233536995956,True 1972-02-26,327.4,0.12011947629474662,True 1972-03-04,327.5,0.19720114194427651,True 1972-03-11,327.1,-0.2257316307362771,True 1972-03-18,327.7,0.3513211768577662,True 1972-03-25,328.6,1.228359583320696,True 1972-04-01,328.9,1.5053836072356148,True 1972-04-08,329.4,1.9823932671752686,True 1972-04-15,329.8,2.3593885817015234,True 1972-04-22,330.1,2.6363695693653995,True 1972-04-29,330.0,2.513336248707276,True 1972-05-06,330.0,2.4902886382568568,False 1972-05-13,329.7,2.167226756532955,False 1972-05-20,330.1,2.5441506220437873,False 1972-05-27,330.2,2.6210602532866574,False 1972-06-03,329.7,2.097955668748284,False 1972-06-10,329.1,1.4748368869047113,False 1972-06-17,329.0,1.351703926220921,False 1972-06-24,328.5,0.8285568051514929,False 1972-07-01,328.6,0.9053955421400701,False 1972-07-08,328.3,0.582220155619666,False 1972-07-15,327.7,-0.04096933598754049,False 1972-07-22,328.1,0.33582708572998854,False 1972-07-29,327.5,-0.2873905608270775,False 1972-08-05,326.9,-0.9106222572686988,False 1972-08-12,326.6,-1.233867985215511,False 1972-08-19,326.5,-1.3571277262992112,False 1972-08-26,325.0,-2.880401462161842,False 1972-09-02,325.4,-2.503689174456497,False 1972-09-09,325.7,-2.226990844846682,False 1972-09-16,324.8,-3.150306455007012,False 1972-09-23,324.2,-3.7736359866226508,True 1972-09-30,324.2,-3.7969794213894374,True 1972-10-07,324.8,-3.220336741014023,True 1972-10-14,325.5,-2.5437079272139727,True 1972-10-21,325.1,-2.967092961717242,True 1972-10-28,325.8,-2.290491826262837,True 1972-11-04,326.3,-1.8139045026002805,True 1972-11-11,326.1,-2.0373309724900537,True 1972-11-18,326.4,-1.7607712177032226,True 1972-11-25,326.9,-1.2842252200215967,True 1972-12-02,326.9,-1.3076929612377626,True 1972-12-09,327.1,-1.1311744231550165,True 1972-12-16,327.6,-0.6546695875874775,True 1972-12-23,327.9,-0.3781784363600309,True 1972-12-30,328.2,-0.10170095130808932,True 1973-01-06,328.4,0.07476288572195244,True 1973-01-13,328.4,0.05121309287318354,True 1973-01-20,328.6,0.2276496882777792,True 1973-01-27,328.8,0.40407269005720536,True 1973-02-03,329.1,0.6804821163221959,True 1973-02-10,329.5,1.0568779851727754,True 1973-02-17,329.6,1.1332603146983047,True 1973-02-24,329.7,1.2096291229771055,True 1973-03-03,329.9,1.3859844280771654,True 1973-03-10,330.1,1.5623262480555127,True 1973-03-17,330.5,1.938654600958273,True 1973-03-24,330.8,2.2149695048212266,True 1973-03-31,330.6,1.991270977669103,True 1973-04-07,331.2,2.5675590375159345,True 1973-04-14,331.1,2.4438337023652252,True 1973-04-21,331.9,3.220094990209361,True 1973-04-28,332.1,3.396342919030417,True 1973-05-05,332.2,3.4725775067993254,True 1973-05-12,332.3,3.5487987714766405,True 1973-05-19,332.6,3.8250067310119107,False 1973-05-26,332.5,3.7012014033440437,False 1973-06-02,332.2,3.377382806401215,False 1973-06-09,332.5,3.6535509581008228,False 1973-06-16,332.0,3.1297058763495897,False 1973-06-23,331.6,2.705847579043393,False 1973-06-30,331.4,2.481976084067469,False 1973-07-07,331.5,2.55809140929631,False 1973-07-14,331.0,2.0341935725935514,False 1973-07-21,330.0,1.0102825918122562,False 1973-07-28,330.1,1.08635848479463,False 1973-08-04,330.0,0.9624212693721006,False 1973-08-11,329.5,0.4384709633654893,False 1973-08-18,329.3,0.21450758458485097,False 1973-08-25,328.5,-0.6094688491706393,False 1973-09-01,328.4,-0.7334583201123905,False 1973-09-08,327.6,-1.557460810462544,False 1973-09-15,327.8,-1.381476302454189,False 1973-09-22,327.1,-2.1055047783308964,False 1973-09-29,326.6,-2.6295462203471516,False 1973-10-06,327.0,-2.25360061076816,True 1973-10-13,327.4,-1.8776679318697802,True 1973-10-20,327.4,-1.9017481659386135,True 1973-10-27,327.1,-2.2258412952721187,True 1973-11-03,327.5,-1.849947302178407,True 1973-11-10,328.0,-1.3740661689763556,True 1973-11-17,328.2,-1.1981978779955966,True 1973-11-24,328.5,-0.9223424115763805,True 1973-12-01,329.0,-0.44649975206993986,True 1973-12-08,328.7,-0.770669881838046,True 1973-12-15,328.6,-0.8948527832532136,True 1973-12-22,328.2,-1.3190484386988715,True 1973-12-29,328.7,-0.8432568305689756,True 1974-01-05,328.9,-0.6674779412683733,True 1974-01-12,329.2,-0.39171175321263263,True 1974-01-19,329.4,-0.21595824882791703,True 1974-01-26,329.8,0.15978258944869594,True 1974-02-02,330.5,0.8355107791693399,True 1974-02-09,330.8,1.1112263378757348,True 1974-02-16,330.6,0.8869292830984818,True 1974-02-23,330.6,0.862619632357621,True 1974-03-02,330.7,0.9382974031624371,True 1974-03-09,331.2,1.4139626130115062,True 1974-03-16,332.1,2.289615279392649,True 1974-03-23,332.0,2.165255419782852,True 1974-03-30,331.5,1.6408830516485295,True 1974-04-06,332.4,2.5164981924451126,True 1974-04-13,332.1,2.1921008596175966,True 1974-04-20,332.9,2.967691070599983,True 1974-04-27,333.1,3.1432688428157007,True 1974-05-04,332.9,2.918834193677185,False 1974-05-11,333.0,2.994387140586582,False 1974-05-18,333.2,3.1699277009348066,False 1974-05-25,332.8,2.7454558921024272,False 1974-06-01,332.9,2.8209717314589398,False 1974-06-08,332.0,1.896475236363358,False 1974-06-15,332.0,1.8719664241638156,False 1974-06-22,332.2,2.0474453121977376,False 1974-06-29,331.7,1.5229119177918164,False 1974-07-06,331.7,1.498366258262081,False 1974-07-13,331.2,0.9738083509136004,False 1974-07-20,330.4,0.14923821304097373,False 1974-07-27,331.0,0.7246558619278858,False 1974-08-03,330.0,-0.29993868515265376,False 1974-08-10,329.9,-0.4245454109384923,False 1974-08-17,329.2,-1.1491642981779933,False 1974-08-24,328.9,-1.4737953296304909,False 1974-08-31,328.1,-2.2984384880658126,False 1974-09-07,328.0,-2.423093756264848,False 1974-09-14,327.3,-3.147761117018945,False 1974-09-21,326.9,-3.5724405531303773,False 1974-09-28,327.3,-3.1971320474119693,True 1974-10-05,327.3,-3.221835582687504,True 1974-10-12,327.0,-3.5465511417913262,True 1974-10-19,327.5,-3.071278707568581,True 1974-10-26,327.7,-2.896018262875259,True 1974-11-02,327.9,-2.72076979057789,True 1974-11-09,328.0,-2.6455332735538946,True 1974-11-16,328.8,-1.8703086946913459,True 1974-11-23,328.6,-2.095096036889231,True 1974-11-30,328.7,-2.0198952830570533,True 1974-12-07,329.5,-1.2447064161151502,True 1974-12-14,329.7,-1.069529418994648,True 1974-12-21,329.8,-0.9943642746372916,True 1974-12-28,329.7,-1.1192109659957055,True 1975-01-04,329.9,-0.9440694760332349,True 1975-01-11,329.8,-1.0689397877237639,True 1975-01-18,330.2,-0.6938218840522268,True 1975-01-25,331.1,0.18128425198597142,True 1975-02-01,331.1,0.15637863738442093,True 1975-02-08,331.4,0.4314612891262186,True 1975-02-15,331.0,0.006532224183615654,True 1975-02-22,331.7,0.6815914595181312,True 1975-03-01,331.8,0.756639012080484,True 1975-03-08,331.6,0.5316748988107634,True 1975-03-15,331.9,0.8066991366382013,True 1975-03-22,332.2,1.0817117424814455,True 1975-03-29,332.5,1.35671273324823,True 1975-04-05,333.0,1.8317021258356476,True 1975-04-12,333.5,2.3066799371300704,True 1975-04-19,333.5,2.281646184007002,True 1975-04-26,333.1,1.8566008833313958,True 1975-05-03,333.9,2.631544051957235,True 1975-05-10,333.9,2.6064757067280198,True 1975-05-17,333.7,2.3813958644763034,True 1975-05-24,333.7,2.35630454202402,False 1975-05-31,334.1,2.7312017561822586,False 1975-06-07,333.8,2.4060875237514665,False 1975-06-14,333.3,1.880961861521314,False 1975-06-21,333.4,1.9558247862706253,False 1975-06-28,333.1,1.6306763147678112,False 1975-07-05,332.7,1.2055164637700955,False 1975-07-12,332.0,0.48034525002429973,False 1975-07-19,331.0,-0.5448373097336798,False 1975-07-26,331.5,-0.07003119877856534,False 1975-08-02,330.8,-0.7952364003958792,False 1975-08-09,330.7,-0.920452897881944,False 1975-08-16,330.3,-1.3456806745436438,False 1975-08-23,329.3,-2.370919713698811,False 1975-08-30,328.8,-2.896169998675873,False 1975-09-06,329.4,-2.321431512814115,False 1975-09-13,328.5,-3.2467042394633836,False 1975-09-20,328.0,-3.7719881619844955,False 1975-09-27,328.2,-3.5972832637488636,True 1975-10-04,328.0,-3.8225895281386215,True 1975-10-11,328.0,-3.847906938546714,True 1975-10-18,328.5,-3.3732354783767846,True 1975-10-25,328.8,-3.098575131043276,True 1975-11-01,329.3,-2.6239258799713525,True 1975-11-08,329.2,-2.749287708596853,True 1975-11-15,329.1,-2.874660600366383,True 1975-11-22,329.5,-2.50004453873737,True 1975-11-29,330.1,-1.9254395071778276,True 1975-12-06,330.3,-1.750845489166693,True 1975-12-13,330.5,-1.5762624681935336,True 1975-12-20,331.1,-1.0016904277586605,True 1975-12-27,331.2,-0.9271293513731393,True 1976-01-03,331.5,-0.6525792225587566,True 1976-01-10,331.5,-0.6780400248481442,True 1976-01-17,331.7,-0.5035117417845072,True 1976-01-24,331.8,-0.42899435692186216,True 1976-01-31,332.2,-0.054487853825094135,True 1976-02-07,332.1,-0.17999221606953597,True 1976-02-14,332.5,0.19449257275834952,True 1976-02-21,333.2,0.8689665290617654,True 1976-02-28,332.4,0.043429669232807555,True 1976-03-06,332.8,0.41788200965316946,True 1976-03-13,333.6,1.1923235666935739,True 1976-03-20,333.1,0.666754356713966,True 1976-03-27,334.3,1.8411743960637637,True 1976-04-03,334.7,2.2155837010815276,True 1976-04-10,334.2,1.6899822880950524,True 1976-04-17,334.4,1.8643701734213778,True 1976-04-24,334.5,1.9387473733669935,True 1976-05-01,334.7,2.1131139042273617,True 1976-05-08,334.3,1.687469782287394,True 1976-05-15,334.6,1.9618150238212024,True 1976-05-22,335.4,2.736149645092155,False 1976-05-29,334.8,2.1104736623529448,False 1976-06-05,334.3,1.5847870918454419,False 1976-06-12,334.6,1.8590899498008184,False 1976-06-19,334.3,1.5333822524394805,False 1976-06-26,333.95000000000005,1.157664015971136,False 1976-07-03,333.6,0.7819352565945792,False 1976-07-10,333.4,0.5561959904981677,False 1976-07-17,332.8,-0.0695537661405865,False 1976-07-24,332.4,-0.495313997155165,False 1976-07-31,332.1,-0.8210846863894403,False 1976-08-07,331.7,-1.2468658176982785,False 1976-08-14,330.6,-2.372657374947039,False 1976-08-21,330.6,-2.3984593420121314,False 1976-08-28,330.0,-3.0242717027804247,False 1976-09-04,329.7,-3.3500944411497358,False 1976-09-11,330.0,-3.075927541028477,False 1976-09-18,329.3,-3.801770986335839,False 1976-09-25,328.4,-4.7276247610018345,False 1976-10-02,328.8,-4.353488848967004,False 1976-10-09,329.0,-4.179363234182972,True 1976-10-16,329.6,-3.6052479006118006,True 1976-10-23,329.1,-4.131142832226374,True 1976-10-30,329.0,-4.25704801301049,True 1976-11-06,329.8,-3.4829634269583494,True 1976-11-13,330.4,-2.9088890580752036,True 1976-11-20,330.5,-2.834824890376865,True 1976-11-27,330.7,-2.660770907889969,True 1976-12-04,331.1,-2.2867270946518374,True 1976-12-11,331.3,-2.11269343471065,True 1976-12-18,331.9,-1.5386699121251581,True 1976-12-25,332.2,-1.2646565109649828,True 1977-01-01,332.5,-0.990653215310374,True 1977-01-08,332.4,-1.1166600092524845,True 1977-01-15,333.1,-0.4426768768930174,True 1977-01-22,333.2,-0.36870380234455524,True 1977-01-29,333.2,-0.3947407697303902,True 1977-02-05,333.4,-0.22078776318448945,True 1977-02-12,333.3,-0.3468447668516319,True 1977-02-19,333.4,-0.27291176488739666,True 1977-02-26,333.6,-0.09898874145778791,True 1977-03-05,334.1,0.3749243192599465,True 1977-03-12,334.6,0.8488274330782133,True 1977-03-19,335.1,1.3227206157985165,True 1977-03-26,335.0,1.196603883211651,True 1977-04-02,335.5,1.6704772510977364,True 1977-04-09,335.9,2.044340735226001,True 1977-04-16,336.0,2.1181943513551573,True 1977-04-23,336.1,2.192038115232947,True 1977-04-30,336.7,2.7658720425964134,True 1977-05-07,336.8,2.8396961491720276,True 1977-05-14,336.4,2.4135104506753464,True 1977-05-21,336.8,2.7873149628113083,False 1977-05-28,336.7,2.661109701273915,False 1977-06-04,336.4,2.3348946817466754,False 1977-06-11,336.3,2.2086699199022064,False 1977-06-18,336.1,1.9824354314024504,False 1977-06-25,336.0,1.8561912318984923,False 1977-07-02,335.5,1.3299373370308558,False 1977-07-09,335.1,0.9036737624292073,False 1977-07-16,335.1,0.8774005237124811,False 1977-07-23,334.6,0.35111763648893657,False 1977-07-30,333.7,-0.5751748836440811,False 1977-08-06,333.0,-1.3014770210996858,False 1977-08-13,332.9,-1.4277887603020076,False 1977-08-20,332.8,-1.5541100856856929,False 1977-08-27,332.8,-1.580440981696313,False 1977-09-03,332.1,-2.3067814327901033,False 1977-09-10,331.2,-3.2331314234339743,False 1977-09-17,332.1,-2.3594909381056937,False 1977-09-24,330.9,-3.5858599612936928,False 1977-10-01,330.4,-4.112238477497215,True 1977-10-08,330.9,-3.6386264712260754,True 1977-10-15,331.5,-3.06502392700105,True 1977-10-22,331.5,-3.0914308293534987,True 1977-10-29,331.7,-2.9178471628256943,True 1977-11-05,332.1,-2.5442729119703245,True 1977-11-12,332.0,-2.670708061351263,True 1977-11-19,332.5,-2.197152595542775,True 1977-11-26,332.8,-1.9236064991299031,True 1977-12-03,333.2,-1.5500697567086377,True 1977-12-10,333.5,-1.2765423528854853,True 1977-12-17,333.8,-1.0030242722778553,True 1977-12-24,334.2,-0.6295154995138432,True 1977-12-31,334.6,-0.2560160192321064,True 1978-01-07,334.2,-0.6825258160824319,True 1978-01-14,334.6,-0.3090448747249752,True 1978-01-21,335.4,0.4644268201691375,True 1978-01-28,335.9,0.9378892839182527,True 1978-02-04,335.0,0.011342531829711788,True 1978-02-11,335.1,0.08478657920034038,True 1978-02-18,335.6,0.55822144131605,True 1978-02-25,335.7,0.6316471334521339,True 1978-03-04,336.2,1.1050636708731076,True 1978-03-11,336.1,0.978471068832846,True 1978-03-18,336.8,1.651869342574173,True 1978-03-25,337.3,2.1252585073295336,True 1978-04-01,337.0,1.7986385783204355,True 1978-04-08,337.9,2.672009570757666,True 1978-04-15,337.9,2.6453714998413034,True 1978-04-22,337.4,2.1187243807607956,True 1978-04-29,338.0,2.692068228694609,True 1978-05-06,338.0,2.6654030588105684,True 1978-05-13,338.1,2.7387288862659034,True 1978-05-20,337.8,2.412045726206884,True 1978-05-27,337.9,2.485353593769105,False 1978-06-03,338.4,2.958652504077577,False 1978-06-10,338.2,2.7319424722464305,False 1978-06-17,337.8,2.305223513379019,False 1978-06-24,337.3,1.7784956425679752,False 1978-07-01,337.6,2.051758874895313,False 1978-07-08,336.7,1.1250132254321557,False 1978-07-15,336.7,1.0982587092389053,False 1978-07-22,335.9,0.2714953413653802,False 1978-07-29,335.6,-0.05527686314945868,False 1978-08-05,335.1,-0.5820578892774506,False 1978-08-12,334.8,-0.9088477220011555,False 1978-08-19,334.4,-1.3356463463138084,False 1978-08-26,334.3,-1.4624537472192856,False 1978-09-02,333.8,-1.9892699097324567,False 1978-09-09,332.8,-3.0160948188787415,False 1978-09-16,332.1,-3.742928459694383,False 1978-09-23,332.3,-3.569770817226356,False 1978-09-30,332.7,-3.1966218765323333,True 1978-10-07,332.1,-3.823481622680788,True 1978-10-14,332.4,-3.5503500407509136,True 1978-10-21,333.0,-2.977227115832477,True 1978-10-28,333.1,-2.9041128330263177,True 1978-11-04,333.5,-2.5310071774438256,True 1978-11-11,333.8,-2.2579101342070658,True 1978-11-18,333.8,-2.2848216884490284,True 1978-11-25,334.2,-1.9117418253132428,True 1978-12-02,334.5,-1.6386705299540267,True 1978-12-09,334.8,-1.3656077875366464,True 1978-12-16,335.1,-1.0925535832367927,True 1978-12-23,335.1,-1.119507902241196,True 1978-12-30,335.3,-0.9464707297470909,True 1979-01-06,335.3,-0.9734420509625465,True 1979-01-13,335.9,-0.4004218511064437,True 1979-01-20,336.8,0.4725898845917982,True 1979-01-27,336.9,0.5455931708917205,True 1979-02-03,336.9,0.5185880225424171,True 1979-02-10,336.5,0.0915744542821244,False 1979-02-17,336.7,0.26455248083823335,True 1979-02-24,336.7,0.23752211692760739,True 1979-03-03,337.1,0.6104833772561733,True 1979-03-10,337.7,1.1834362765192168,True 1979-03-17,337.4,0.856380829401246,True 1979-03-24,339.0,2.429317050576117,True 1979-03-31,338.8,2.2022449547068277,True 1979-04-07,338.1,1.475164556445634,True 1979-04-14,338.6,1.9480758704341952,True 1979-04-21,339.2,2.5209789113032457,True 1979-04-28,339.6,2.893873693673015,True 1979-05-05,339.3,2.56676023215266,True 1979-05-12,338.8,2.039638541340878,True 1979-05-19,339.8,3.0125086358255544,False 1979-05-26,339.6,2.785370530183741,False 1979-06-02,339.9,3.058224238981836,False 1979-06-09,339.5,2.6310697767755755,False 1979-06-16,338.9,2.0039071581097687,False 1979-06-23,338.9,1.9767363975185503,False 1979-06-30,339.0,2.049557509525414,False 1979-07-07,338.2,1.222370508642996,False 1979-07-14,337.8,0.7951754093733143,False 1979-07-21,337.3,0.26797222620740513,False 1979-07-28,336.8,-0.2592390263741322,False 1979-08-04,337.0,-0.08645833390164626,False 1979-08-11,336.5,-0.6136856819161949,False 1979-08-18,336.1,-1.0409210559694202,False 1979-08-25,334.5,-2.668164441623901,False 1979-09-01,334.4,-2.7954158244529594,False 1979-09-08,334.0,-3.222675190040434,False 1979-09-15,334.2,-3.0499425239811444,False 1979-09-22,333.2,-4.07721781188053,True 1979-09-29,334.1,-3.2045010393547955,True 1979-10-06,334.1,-3.2317921920308663,True 1979-10-13,333.9,-3.459091255546582,True 1979-10-20,333.7,-3.6863982155501276,True 1979-10-27,334.1,-3.313713057700795,True 1979-11-03,334.7,-2.7410357676685635,True 1979-11-10,334.8,-2.6683663311339956,True 1979-11-17,335.5,-1.9957047337885,True 1979-11-24,335.6,-1.9230509613341837,True 1979-12-01,335.9,-1.6504049994840102,True 1979-12-08,336.5,-1.077766833961448,True 1979-12-15,336.7,-0.9051364505009474,True 1979-12-22,336.8,-0.8325138348475889,True 1979-12-29,337.4,-0.2598989727572416,True 1980-01-05,337.6,-0.08729184999634754,True 1980-01-12,337.4,-0.31469245234239906,True 1980-01-19,338.3,0.5578992344166522,True 1980-01-26,338.4,0.6304832244820204,True 1980-02-02,338.0,0.20305953204410798,True 1980-02-09,338.1,0.2756281712827331,True 1980-02-16,338.6,0.7481891563667773,True 1980-02-23,338.2,0.32074250145444694,True 1980-03-01,339.3,1.393288220693421,True 1980-03-08,339.5,1.5658263282202824,True 1980-03-15,340.0,2.038356838161178,True 1980-03-22,340.5,2.5108797646312837,True 1980-03-29,341.0,2.9833951217352137,True 1980-04-05,340.4,2.3559029235667595,True 1980-04-12,340.9,2.8284031842089234,True 1980-04-19,340.7,2.6008959177341353,True 1980-04-26,341.0,2.873381138203854,True 1980-05-03,341.5,3.345858859668965,True 1980-05-10,341.3,3.118329096169532,True 1980-05-17,341.3,3.090791861734999,True 1980-05-24,340.9,2.6632471703838405,False 1980-05-31,341.7,3.4356950361240592,False 1980-06-07,341.3,3.0081354729528016,False 1980-06-14,341.3,2.9805684948563567,False 1980-06-21,340.8,2.452994115810384,False 1980-06-28,340.4,2.025412349779856,False 1980-07-05,340.4,1.9978232107189342,False 1980-07-12,339.7,1.2702267125710591,False 1980-07-19,338.5,0.04262286926888237,False 1980-07-26,338.9,0.4150116947343463,False 1980-08-02,337.9,-0.6126067971212592,False 1980-08-09,337.7,-0.8402325923975127,False 1980-08-16,337.7,-0.8678656772046907,False 1980-08-23,337.7,-0.8955060376638357,False 1980-08-30,337.0,-1.6231536599066203,False 1980-09-06,336.6,-2.050808530075585,False 1980-09-13,335.7,-2.978470634324026,False 1980-09-20,335.2,-3.5061399588157656,False 1980-09-27,336.0,-2.7338164897256547,True 1980-10-04,335.8,-2.9615002132390487,True 1980-10-11,335.8,-2.9891911155522166,True 1980-10-18,336.1,-2.7168891828720803,True 1980-10-25,336.4,-2.4445944014163388,True 1980-11-01,336.6,-2.2723067574132756,True 1980-11-08,336.9,-2.0000262371021904,True 1980-11-15,337.1,-1.8277528267328762,True 1980-11-22,337.3,-1.6554865125661422,True 1980-11-29,337.4,-1.5832272808731886,True 1980-12-06,337.7,-1.3109751179362092,True 1980-12-13,338.1,-0.9387300100480047,True 1980-12-20,338.3,-0.7664919435122783,True 1980-12-27,338.7,-0.39426090464331764,True 1981-01-03,338.9,-0.22203687976622177,True 1981-01-10,339.1,-0.04981985521669685,True 1981-01-17,339.3,0.1223901826584779,True 1981-01-24,339.3,0.09459324750218912,True 1981-01-31,339.5,0.26678935294631856,True 1981-02-07,340.5,1.238978512612107,True 1981-02-14,340.0,0.7111607401099604,True 1981-02-21,340.2,0.8833360490397126,True 1981-02-28,341.1,1.7555044529902943,True 1981-03-07,340.7,1.3276659655400067,True 1981-03-14,341.0,1.5998206002562938,True 1981-03-21,341.8,2.3719683706959813,True 1981-03-28,342.1,2.64410929040514,True 1981-04-04,342.4,2.9162433729189274,True 1981-04-11,342.4,2.8883706317620295,True 1981-04-18,342.7,3.160491080448196,True 1981-04-25,342.3,2.7326047324805245,True 1981-05-02,342.9,3.3047116013513005,True 1981-05-09,343.0,3.3768117005421914,True 1981-05-16,342.8,3.148905043523996,False 1981-05-23,342.7,3.0209916437568154,False 1981-05-30,342.7,2.9930715146900297,False 1981-06-06,342.6,2.8651446697622873,False 1981-06-13,342.5,2.7372111224013906,False 1981-06-20,341.8,2.0092708860246375,False 1981-06-27,341.6,1.781323974038287,False 1981-07-04,341.0,1.1533703998380815,False 1981-07-11,340.8,0.9254101768088958,False 1981-07-18,339.7,-0.20255668167504837,False 1981-07-25,340.2,0.26946983774973887,False 1981-08-01,339.5,-0.45851025156412106,False 1981-08-08,338.9,-1.0864969362746137,False 1981-08-15,338.4,-1.6144902030505364,False 1981-08-22,337.5,-2.5424900385713727,False 1981-08-29,337.7,-2.3704964295275204,False 1981-09-05,337.2,-2.898509362619791,False 1981-09-12,337.0,-3.126528824559955,False 1981-09-19,336.7,-3.454554802070618,False 1981-09-26,335.9,-4.2825872818849575,False 1981-10-03,336.3,-3.910626250746816,True 1981-10-10,336.6,-3.6386716954110057,True 1981-10-17,337.1,-3.1667236026429464,True 1981-10-24,337.2,-3.0947819592188353,True 1981-10-31,337.5,-2.8228467519255673,True 1981-11-07,337.8,-2.5509179675607925,True 1981-11-14,338.1,-2.278995592932972,True 1981-11-21,338.5,-1.9070796148612317,True 1981-11-28,339.3,-1.1351700201753943,True 1981-12-05,339.2,-1.263266795716163,True 1981-12-12,339.4,-1.0913699283348706,True 1981-12-19,339.6,-0.9194794048935364,True 1981-12-26,340.2,-0.34759521226521883,True 1982-01-02,340.2,-0.37571733733335577,True 1982-01-09,340.3,-0.30384576699225363,True 1982-01-16,340.7,0.0680195118529241,True 1982-01-23,341.1,0.43987851228644104,True 1982-01-30,341.2,0.5117312473817037,True 1982-02-06,341.9,1.1835777302014208,True 1982-02-13,341.1,0.3554179737976142,True 1982-02-20,341.1,0.3272519912114831,True 1982-02-27,342.1,1.2990797954735172,True 1982-03-06,342.6,1.7709013996034173,True 1982-03-13,342.6,1.7427168166102547,True 1982-03-20,342.7,1.8145260594922092,True 1982-03-27,342.8,1.8863291412369563,True 1982-04-03,342.9,1.9581260748211662,True 1982-04-10,343.3,2.329916873210948,True 1982-04-17,343.5,2.501701549361485,True 1982-04-24,344.2,3.1734801162174904,True 1982-05-01,343.8,2.745252586712752,True 1982-05-08,343.6,2.5170189737702913,False 1982-05-15,344.2,3.0887792903025115,False 1982-05-22,344.1,2.960533549210993,False 1982-05-29,344.1,2.932281763386584,False 1982-06-05,343.4,2.204023945709366,False 1982-06-12,343.5,2.2757601090488606,False 1982-06-19,343.4,2.147490266263503,False 1982-06-26,342.9,1.6192144302013958,False 1982-07-03,342.5,1.1909326136996583,False 1982-07-10,342.0,0.6626448295845648,False 1982-07-17,342.0,0.6343510906719416,False 1982-07-24,341.8,0.40605140976668963,False 1982-07-31,341.3,-0.12225420033706769,False 1982-08-07,340.5,-0.950565726855757,False 1982-08-14,340.0,-1.478883157016753,False 1982-08-21,339.7,-1.807206478058049,False 1982-08-28,338.3,-3.23553567722837,False 1982-09-04,338.8,-2.7638707417872297,False 1982-09-11,338.6,-2.9922116590049654,False 1982-09-18,337.8,-3.8205584161624984,False 1982-09-25,336.9,-4.748911000551573,True 1982-10-02,337.3,-4.377269399474585,False 1982-10-09,338.0,-3.7056336002448234,True 1982-10-16,337.6,-4.134003590186239,True 1982-10-23,337.9,-3.8623793566334825,True 1982-10-30,338.7,-3.090760886932003,True 1982-11-06,338.4,-3.419148168437914,True 1982-11-13,339.2,-2.6475411885182325,True 1982-11-20,339.7,-2.175939934550513,True 1982-11-27,339.8,-2.1043443939231565,True 1982-12-04,339.8,-2.13275455403533,True 1982-12-11,340.4,-1.5611704022969661,True 1982-12-18,340.7,-1.289591926128594,True 1982-12-25,340.8,-1.2180191129615423,True 1983-01-01,340.9,-1.1464519502379744,True 1983-01-08,341.4,-0.6748904254106947,True 1983-01-15,341.5,-0.6033345259432394,True 1983-01-22,341.2,-0.9317842393100477,True 1983-01-29,341.7,-0.46023955299602903,True 1983-02-05,342.0,-0.1887004544970523,True 1983-02-12,342.7,0.4828330686803497,True 1983-02-19,342.5,0.25436102901892355,True 1983-02-26,342.8,0.5258834389906042,True 1983-03-05,342.3,-0.0025996889433486103,True 1983-03-12,342.5,0.16891165766759286,True 1983-03-19,344.0,1.640417491263122,True 1983-03-26,343.8,1.4119178242723933,True 1983-04-02,344.0,1.5834126691134998,True 1983-04-09,344.8,2.3549020381941546,True 1983-04-16,345.0,2.526385943911066,True 1983-04-23,345.3,2.7978643986502902,True 1983-04-30,345.4,2.8693374147871396,True 1983-05-07,345.4,2.840805004686274,True 1983-05-14,345.7,3.1122671807014513,True 1983-05-21,345.8,3.183723955175765,False 1983-05-28,345.7,3.055175340441565,False 1983-06-04,345.6,2.926621348820561,False 1983-06-11,345.6,2.898061992623525,False 1983-06-18,345.0,2.2694972841506456,False 1983-06-25,344.9,2.1409272356912084,False 1983-07-02,344.7,1.9123518595240512,False 1983-07-09,344.5,1.683771167916973,False 1983-07-16,343.7,0.8551851731270972,False 1983-07-23,343.6,0.7265938874010089,False 1983-07-30,342.6,-0.30200267702576866,False 1983-08-06,343.0,0.06939549207180562,False 1983-08-13,341.7,-1.2592115930921182,False 1983-08-20,342.1,-0.887823920313906,False 1983-08-27,341.8,-1.2164414774010197,False 1983-09-03,339.9,-3.145064252171437,False 1983-09-10,339.9,-3.1736922324538455,False 1983-09-17,339.8,-3.302325406087732,False 1983-09-24,339.9,-3.23096376092343,False 1983-10-01,339.8,-3.3596072848217773,True 1983-10-08,339.7,-3.4882559656546164,True 1983-10-15,340.1,-3.1169097913042947,True 1983-10-22,340.2,-3.0455687496641417,True 1983-10-29,340.3,-2.9742328286379234,True 1983-11-05,340.8,-2.5029020161404105,True 1983-11-12,341.0,-2.3315763000970264,True 1983-11-19,341.1,-2.2602556684439037,True 1983-11-26,341.7,-1.6889401091280547,True 1983-12-03,341.8,-1.6176296101068601,True 1983-12-10,342.8,-0.6463241593489215,True 1983-12-17,343.3,-0.17502374483331096,True 1983-12-24,343.6,0.0962716454502015,True 1983-12-31,343.4,-0.13243797649914768,True 1984-01-07,343.7,0.13884740130743012,True 1984-01-14,343.4,-0.1898722091521563,True 1984-01-21,343.5,-0.11859679591077565,True 1984-01-28,344.1,0.45267365298809636,True 1984-02-04,344.3,0.6239391494900133,True 1984-02-11,344.5,0.795199705530024,True 1984-02-18,344.3,0.5664553330323656,True 1984-02-25,344.6,0.8377060439104298,True 1984-03-03,344.8,1.0089518500670351,True 1984-03-10,344.9,1.0801927633940522,True 1984-03-17,345.4,1.5514287957728925,True 1984-03-24,345.6,1.7226599590740648,True 1984-03-31,345.96000000000004,2.053886265157246,True 1984-04-07,346.32,2.3851077258714213,True 1984-04-14,346.68,2.716324353055029,True 1984-04-21,347.03999999999996,3.047536158535479,True 1984-04-28,347.4,3.3787431541297224,True 1984-05-05,347.4,3.3499453516437825,True 1984-05-12,347.7,3.621142762872921,False 1984-05-19,347.3,3.1923353996018022,False 1984-05-26,347.0,2.863523273604244,False 1984-06-02,347.0,2.834706396643355,False 1984-06-09,347.0,2.8058847804715015,False 1984-06-16,346.8,2.5770584368303275,False 1984-06-23,346.3,2.0482273774507007,False 1984-06-30,346.2,1.9193916140527563,False 1984-07-07,345.8,1.4905511583459656,False 1984-07-14,345.4,1.0617060220288863,False 1984-07-21,345.2,0.832856216789537,False 1984-07-28,344.4,0.004001754305022587,False 1984-08-04,344.0,-0.4248573537580569,False 1984-08-11,344.1,-0.353721095744163,False 1984-08-18,343.1,-1.3825894600083188,False 1984-08-25,342.0,-2.5114624349162114,False 1984-09-01,341.6,-2.94034000884443,False 1984-09-08,340.6,-3.969222170180217,False 1984-09-15,341.3,-3.2981089073215912,True 1984-09-22,341.3,-3.327000208677248,True 1984-09-29,340.8,-3.855896062666659,True 1984-10-06,341.1,-3.584796457720074,True 1984-10-13,341.3,-3.413701382278475,True 1984-10-20,341.9,-2.84261082479361,True 1984-10-27,341.6,-3.1715247737277537,True 1984-11-03,342.0,-2.800443217554232,True 1984-11-10,342.6,-2.2293661447569093,True 1984-11-17,343.1,-1.7582935438304617,True 1984-11-24,343.7,-1.1872254032803653,True 1984-12-01,343.6,-1.3161617116226125,True 1984-12-08,343.9,-1.045102457384246,True 1984-12-15,344.2,-0.7740476291028244,True 1984-12-22,344.5,-0.5029972153266158,True 1984-12-29,344.5,-0.5319512046149271,True 1985-01-05,344.7,-0.3609095855374562,True 1985-01-12,345.0,-0.0898723466748379,True 1985-01-19,345.0,-0.11883947661834782,True 1985-01-26,345.0,-0.147810963970187,True 1985-02-02,345.9,0.7232132026569502,True 1985-02-09,345.5,0.2942330346394897,True 1985-02-16,345.8,0.5652485433431593,True 1985-02-23,346.3,1.03625974012283,True 1985-03-02,346.7,1.407266636322845,True 1985-03-09,347.1,1.778269243276668,True 1985-03-16,347.5,2.1492675723069397,True 1985-03-23,347.7,2.320261634725796,True 1985-03-30,348.2,2.791251441834504,True 1985-04-06,348.0,2.5622370049234746,True 1985-04-13,348.0,2.533218335272636,True 1985-04-20,348.5,3.0041954441509233,True 1985-04-27,348.8,3.2751683428166984,True 1985-05-04,348.8,3.246137042517489,True 1985-05-11,349.3,3.7171015544901707,True 1985-05-18,349.1,3.488061889960761,False 1985-05-25,348.1,2.459018060144615,False 1985-06-01,349.0,3.3299700762463544,False 1985-06-08,348.4,2.7009179494598357,False 1985-06-15,348.2,2.4718616909681828,False 1985-06-22,347.9,2.142801311943799,False 1985-06-29,347.4,1.6137368235482654,False 1985-07-06,346.9,1.0846682369325436,False 1985-07-13,346.8,0.9555955632368409,False 1985-07-20,346.4,0.5265188135903713,False 1985-07-27,345.7,-0.20256200088800824,False 1985-08-03,345.2,-0.7316468690904117,False 1985-08-10,344.7,-1.260735779919628,False 1985-08-17,344.5,-1.4898287222892463,False 1985-08-24,344.3,-1.7189256851234518,False 1985-08-31,343.7,-2.3480266573574227,False 1985-09-07,344.2,-1.8771316279368193,False 1985-09-14,343.3,-2.8062405858181023,False 1985-09-21,342.4,-3.735353519968669,False 1985-09-28,342.1,-4.06447041936633,False 1985-10-05,342.4,-3.793591273000004,False 1985-10-12,342.5,-3.7227160698690227,True 1985-10-19,343.1,-3.151844798983575,True 1985-10-26,343.2,-3.0809774493647524,True 1985-11-02,343.3,-3.010114010044049,True 1985-11-09,343.7,-2.6392544700640883,True 1985-11-16,344.2,-2.1683988184779537,True 1985-11-23,344.6,-1.7975470443494714,True 1985-11-30,345.3,-1.126699136753416,True 1985-12-07,345.3,-1.155855084775169,True 1985-12-14,345.6,-0.8850148775108551,True 1985-12-21,345.1,-1.4141785040672517,True 1985-12-28,346.3,-0.24334595356214095,True 1986-01-04,346.4,-0.1725172151237757,True 1986-01-11,346.0,-0.6016922778911749,True 1986-01-18,346.2,-0.4308711310142712,True 1986-01-25,346.4,-0.26005376365367283,True 1986-02-01,346.2,-0.48924016498062883,True 1986-02-08,346.8,0.0815696758227773,True 1986-02-15,347.1,0.35237576956376415,True 1986-02-22,347.2,0.42317812703879554,True 1986-03-01,347.0,0.1939767590335464,True 1986-03-08,346.6,-0.23522832367689261,True 1986-03-15,347.2,0.33556288967156434,True 1986-03-22,349.1,2.2063504098325666,True 1986-03-29,348.8,1.8771342475487813,True 1986-04-05,349.2,2.2479144135522233,True 1986-04-12,349.4,2.4186909185642094,True 1986-04-19,349.3,2.2894637732953242,True 1986-04-26,350.2,3.160232988445273,True 1986-05-03,349.9,2.8309985747031305,True 1986-05-10,350.1,3.00176054274732,True 1986-05-17,350.2,3.0725189032452818,False 1986-05-24,350.1,2.9432736668539405,False 1986-05-31,350.1,2.914024844219284,False 1986-06-07,349.7,2.4847724459767733,False 1986-06-14,349.5,2.255516482750977,False 1986-06-21,349.4,2.1262569651557897,False 1986-06-28,348.9,1.5969939037943277,False 1986-07-05,348.6,1.267727309259044,False 1986-07-12,347.7,0.3384571921314432,False 1986-07-19,347.6,0.20918356298261642,False 1986-07-26,347.4,-0.02009356762744119,False 1986-08-02,346.6,-0.8493741891491027,False 1986-08-09,346.2,-1.2786582910438256,False 1986-08-16,345.5,-2.007945862783629,False 1986-08-23,345.6,-1.9372368938512636,False 1986-08-30,345.2,-2.366531373740372,False 1986-09-06,345.0,-2.595829291955056,False 1986-09-13,345.3,-2.325130638010421,False 1986-09-20,344.4,-3.2544354014322607,False 1986-09-27,344.5,-3.18374357175702,False 1986-10-04,343.9,-3.8130551385319222,False 1986-10-11,344.1,-3.6423700913148878,True 1986-10-18,343.9,-3.871688419674797,True 1986-10-25,344.5,-3.301010113190955,True 1986-11-01,345.1,-2.7303351614535813,True 1986-11-08,345.3,-2.559663554063718,True 1986-11-15,345.6,-2.2889952806328893,True 1986-11-22,345.7,-2.218330330783658,True 1986-11-29,346.4,-1.5476686941490811,True 1986-12-06,346.9,-1.0770103603730945,True 1986-12-13,346.7,-1.3063553191102528,True 1986-12-20,346.9,-1.1357035600261156,True 1986-12-27,347.0,-1.0650550727966106,True 1987-01-03,347.6,-0.49440984710872726,True 1987-01-10,348.3,0.17623212733997207,True 1987-01-17,348.2,0.046870860841124795,True 1987-01-24,347.9,-0.28249363632431823,True 1987-01-31,348.0,-0.21186135388614957,True 1987-02-07,347.9,-0.3412322815850075,True 1987-02-14,348.2,-0.07060640917217142,True 1987-02-21,348.5,0.2000162735903359,True 1987-02-28,349.4,1.0706357769297483,True 1987-03-07,348.8,0.4412521110625107,True 1987-03-14,349.2,0.8118652861942905,True 1987-03-21,349.7,1.282475312520205,True 1987-03-28,350.2,1.753082200224469,True 1987-04-04,350.8,2.323685959480599,True 1987-04-11,350.2,1.694286600451278,True 1987-04-18,351.1,2.564884133288672,True 1987-04-25,351.3,2.735478568133942,True 1987-05-02,351.4,2.806069915117746,True 1987-05-09,352.0,3.376658184359826,True 1987-05-16,351.7,3.0472433859693524,False 1987-05-23,351.9,3.217825530044479,False 1987-05-30,351.7,2.9884046266729456,False 1987-06-06,351.6,2.8589806859316127,False 1987-06-13,351.1,2.3295537178864834,False 1987-06-20,351.0,2.2001237325929424,False 1987-06-27,350.9,2.0706907400956425,False 1987-07-04,349.7,0.8412547504285044,False 1987-07-11,349.8,0.9118157736145918,False 1987-07-18,348.8,-0.11762618033361605,False 1987-07-25,349.5,0.5529288985855487,False 1987-08-01,349.0,0.023481020362964955,False 1987-08-08,348.1,-0.9059698050211864,False 1987-08-15,348.6,-0.43542356759741097,False 1987-08-22,348.0,-1.0648802574070828,False 1987-08-29,346.7,-2.3943398645021716,False 1987-09-05,347.0,-2.12380237894547,False 1987-09-12,346.6,-2.5532677908104233,False 1987-09-19,346.2,-2.982736090181504,False 1987-09-26,345.8,-3.4122072671535193,True 1987-10-03,345.7,-3.541681311832292,True 1987-10-10,346.3,-2.9711582143342525,True 1987-10-17,346.5,-2.800637964786688,True 1987-10-24,346.8,-2.5301205533274924,True 1987-10-31,346.9,-2.4596059701054287,True 1987-11-07,347.3,-2.0890942052798778,True 1987-11-14,347.6,-1.818585249021055,True 1987-11-21,348.1,-1.3480790915099305,True 1987-11-28,348.7,-0.7775757229380815,True 1987-12-05,348.6,-0.9070751335079308,True 1987-12-12,348.8,-0.7365773134326901,True 1987-12-19,349.1,-0.46608225293618943,True 1987-12-26,349.2,-0.39558994225308197,True 1988-01-02,349.7,0.07489962837126996,True 1988-01-09,350.2,0.5453864686807606,True 1988-01-16,350.2,0.5158705884086316,True 1988-01-23,350.7,0.9863519972771542,True 1988-01-30,351.2,1.4568307049980262,True 1988-02-06,351.8,2.027306721272282,True 1988-02-13,351.3,1.497780055790031,True 1988-02-20,351.5,1.668250718230695,True 1988-02-27,352.5,2.6387187182630214,True 1988-03-05,352.8,2.9091840655449914,True 1988-03-12,351.8,1.87964676972382,True 1988-03-19,351.7,1.7501068404359899,True 1988-03-26,352.2,2.2205642873072406,True 1988-04-02,353.1,3.091019119952591,True 1988-04-09,353.5,3.4614713479762713,True 1988-04-16,353.1,3.031920980971904,True 1988-04-23,354.0,3.902368028522176,True 1988-04-30,354.2,4.072812500199177,True 1988-05-07,353.7,3.5432544055641984,True 1988-05-14,354.3,4.113693754167855,True 1988-05-21,354.5,4.284130555549837,False 1988-05-28,354.2,3.9545648192393514,False 1988-06-04,354.1,3.824996554754705,False 1988-06-11,354.2,3.8954257716034704,False 1988-06-18,353.6,3.2658524792825574,False 1988-06-25,353.1,2.736276687278064,False 1988-07-02,353.0,2.6066984050652877,False 1988-07-09,352.5,2.0771176421089876,False 1988-07-16,352.6,2.147534407863077,False 1988-07-23,351.9,1.4179487117705776,False 1988-07-30,351.1,0.5883605632640752,False 1988-08-06,350.9,0.35876997176507075,False 1988-08-13,350.3,-0.2708230533153255,False 1988-08-20,350.4,-0.20041850257712213,False 1988-08-27,349.6,-1.0300163666306048,False 1988-09-03,349.3,-1.3596166360972575,False 1988-09-10,348.7,-1.9892193016090687,False 1988-09-17,348.9,-1.8188243538087931,False 1988-09-24,348.1,-2.6484317833498494,True 1988-10-01,348.8,-1.9780415808965586,True 1988-10-08,348.8,-2.0076537371239738,True 1988-10-15,348.6,-2.2372682427177324,True 1988-10-22,349.4,-1.4668850883743403,True 1988-10-29,349.2,-1.6965042648009785,True 1988-11-05,349.7,-1.2261257627156397,True 1988-11-12,349.8,-1.1557495728469007,True 1988-11-19,350.1,-0.8853756859343207,True 1988-11-26,350.4,-0.6150040927280997,True 1988-12-03,350.5,-0.5446347839890109,True 1988-12-10,351.0,-0.07426775048872969,True 1988-12-17,351.6,0.4960970169902339,True 1988-12-24,351.3,0.16645952765486527,True 1988-12-31,352.4,1.2368197907011904,True 1989-01-07,352.7,1.5071778153147193,True 1989-01-14,352.9,1.6775336106700252,True 1989-01-21,352.5,1.2478871859310061,True 1989-01-28,353.0,1.7182385502508737,False 1989-02-04,352.8,1.4885877127719596,True 1989-02-11,352.6,1.2589346826260908,True 1989-02-18,353.2,1.8292794689340326,True 1989-02-25,353.4,1.9996220808060912,True 1989-03-04,353.1,1.669962527341795,True 1989-03-11,353.4,1.9403008176296908,True 1989-03-18,353.5,2.010636960747945,True 1989-03-25,354.4,2.8809709657636517,True 1989-04-01,354.5,2.9513028417334226,True 1989-04-08,355.0,3.42163259770291,True 1989-04-15,355.4,3.791960242707205,True 1989-04-22,356.0,4.362285785770609,True 1989-04-29,355.9,4.232609235906523,True 1989-05-06,355.3,3.602930602117965,False 1989-05-13,355.8,4.073249893396792,False 1989-05-20,355.6,3.8435671187244225,False 1989-05-27,355.7,3.913882287071374,False 1989-06-03,355.8,3.9841954073975216,False 1989-06-10,355.0,3.1545064886519754,False 1989-06-17,354.8,2.9248155397730784,False 1989-06-24,354.9,2.9951225696883625,False 1989-07-01,354.5,2.5654275873148435,False 1989-07-08,354.7,2.7357306015586005,False 1989-07-15,353.8,1.8060316213149576,False 1989-07-22,353.1,1.0763306554686665,False 1989-07-29,353.2,1.146627712893462,False 1989-08-05,352.6,0.5169228024527683,False 1989-08-12,352.2,0.08721593299884489,False 1989-08-19,351.1,-1.042492886626519,False 1989-08-26,350.4,-1.7722036475925051,False 1989-09-02,350.7,-1.501916341078811,False 1989-09-09,350.2,-2.0316309582759686,False 1989-09-16,349.4,-2.861347490385299,False 1989-09-23,349.3,-2.9910659286187524,False 1989-09-30,349.7,-2.6207862641991255,True 1989-10-07,349.9,-2.450508488359901,True 1989-10-14,349.7,-2.6802325923453054,True 1989-10-21,350.2,-2.209958567410297,True 1989-10-28,350.4,-2.0396864048206567,True 1989-11-04,350.6,-1.8694160958527277,True 1989-11-11,351.2,-1.2991476317938577,True 1989-11-18,351.6,-0.9288810039418536,True 1989-11-25,351.4,-1.1586162036055043,True 1989-12-02,352.0,-0.5883532221041037,True 1989-12-09,352.1,-0.5180920507678479,True 1989-12-16,352.4,-0.24783268093779043,True 1989-12-23,352.5,-0.17757510396529597,True 1989-12-30,353.4,0.6926806887870498,True 1990-01-06,353.4,0.6629347059461566,True 1990-01-13,353.5,0.7331869561282929,True 1990-01-20,353.8,1.0034374479387225,True 1990-01-27,353.9,1.0736861899720793,True 1990-02-03,354.1,1.2439331908124132,True 1990-02-10,355.0,2.1141784590328143,True 1990-02-17,354.8,1.8844220031957093,True 1990-02-24,354.7,1.754663831852838,True 1990-03-03,355.7,2.7249039535451516,True 1990-03-10,354.9,1.8951423768028235,True 1990-03-17,355.8,2.765379110145375,True 1990-03-24,355.1,2.035614162081515,True 1990-03-31,355.9,2.8058475411092445,True 1990-04-07,356.1,2.976079255715831,True 1990-04-14,355.9,2.746309314377754,True 1990-04-21,356.6,3.416537725560829,True 1990-04-28,356.1,2.886764497720037,True 1990-05-05,357.3,4.056989639299729,True 1990-05-12,357.0,3.7272131587333774,True 1990-05-19,356.9,3.5974350644438005,False 1990-05-26,357.1,3.767655364843222,False 1990-06-02,357.0,3.637874068332735,False 1990-06-09,356.6,3.208091183303111,False 1990-06-16,355.6,2.178306718134081,False 1990-06-23,355.5,2.048520681194816,False 1990-06-30,355.7,2.2187330808437196,False 1990-07-07,355.5,1.988943925428316,False 1990-07-14,354.0,0.4591532232855684,False 1990-07-21,354.5,0.9293609827415708,False 1990-07-28,354.7,1.099567212111765,False 1990-08-04,353.5,-0.13022808029916177,False 1990-08-11,353.2,-0.4600248861973455,False 1990-08-18,352.9,-0.7898231972995973,False 1990-08-25,352.0,-1.7196230053334602,False 1990-09-01,350.9,-2.849424302037221,False 1990-09-08,350.7,-3.079227079159864,False 1990-09-15,351.3,-2.509031328461276,False 1990-09-22,350.9,-2.938837041711963,True 1990-09-29,350.9,-2.9686442106930713,True 1990-10-06,351.1,-2.7984528271966838,True 1990-10-13,351.0,-2.9282628830255817,True 1990-10-20,351.4,-2.5580743699932214,True 1990-10-27,351.4,-2.5878872799237342,True 1990-11-03,352.1,-1.9177016046521658,True 1990-11-10,352.6,-1.447517336024191,True 1990-11-17,353.0,-1.0773344658963424,True 1990-11-24,353.1,-1.0071529861356794,True 1990-12-01,353.6,-0.5369728886201415,True 1990-12-08,354.0,-0.16679416523851387,True 1990-12-15,353.8,-0.39661680789004095,True 1990-12-22,354.5,0.2735591915150053,True 1990-12-29,354.8,0.5437338410558255,True 1991-01-05,354.2,-0.08609285119928245,True 1991-01-12,354.7,0.38407912280740675,True 1991-01-19,354.8,0.45424977112270426,True 1991-01-26,355.0,0.6244191017827916,True 1991-02-02,355.2,0.7945871228130841,True 1991-02-09,355.2,0.764753842228231,True 1991-02-16,356.4,1.9349192680321607,True 1991-02-23,355.8,1.3050834082181382,True 1991-03-02,356.4,1.8752462707684572,True 1991-03-09,357.2,2.6454078636550094,True 1991-03-16,357.6,3.0155681948386928,True 1991-03-23,356.9,2.2857272722696393,True 1991-03-30,357.9,3.255885103887465,True 1991-04-06,358.3,3.626041697620906,True 1991-04-13,357.8,3.0961970613878407,True 1991-04-20,359.1,4.3663512030956895,True 1991-04-27,359.2,4.436504130640856,True 1991-05-04,359.1,4.306655851909227,True 1991-05-11,358.9,4.076806374775742,False 1991-05-18,360.0,5.146955707104837,False 1991-05-25,359.0,4.117103856749964,False 1991-06-01,358.5,3.587250831553945,False 1991-06-08,358.4,3.4573966393489286,False 1991-06-15,358.2,3.227541287956228,False 1991-06-22,358.1,3.097684785186459,False 1991-06-29,357.7,2.6678271388394137,False 1991-07-06,357.2,2.1379683567043344,False 1991-07-13,356.5,1.4081084465594813,False 1991-07-20,355.2,0.07824741617253039,False 1991-07-27,355.3,0.14838527330044826,False 1991-08-03,354.8,-0.3814779743107124,False 1991-08-10,354.6,-0.6113423189254945,False 1991-08-17,353.7,-1.5412077528192185,False 1991-08-24,353.0,-2.271074268277914,False 1991-08-31,353.2,-2.100941857598457,False 1991-09-07,353.0,-2.330810513088295,False 1991-09-14,352.1,-3.260680227065791,False 1991-09-21,351.8,-3.5905509918599705,False 1991-09-28,351.6,-3.820422799810501,False 1991-10-05,351.7,-3.750295643268089,True 1991-10-12,352.1,-3.3801695145937174,True 1991-10-19,352.5,-3.0100444061596363,True 1991-10-26,352.7,-2.8399203103484183,True 1991-11-02,353.4,-2.169797219553516,True 1991-11-09,353.7,-1.8996751261792042,True 1991-11-16,353.5,-2.129554022640434,True 1991-11-23,353.8,-1.859433901362877,True 1991-11-30,354.3,-1.3893147547829585,True 1991-12-07,354.5,-1.219196575347894,True 1991-12-14,354.9,-0.8490793555155278,True 1991-12-21,355.2,-0.5789630877545164,True 1991-12-28,355.5,-0.30884776454433904,True 1992-01-04,355.6,-0.2387333783750023,True 1992-01-11,356.0,0.13138007825250497,True 1992-01-18,356.1,0.2014926128266552,True 1992-01-25,355.9,-0.02839576717502723,True 1992-02-01,356.0,0.04171494571454559,True 1992-02-08,356.7,0.7118247589513658,True 1992-02-15,357.3,1.281933679981023,True 1992-02-22,356.9,0.8520417162379772,True 1992-02-29,356.5,0.42214887514637667,True 1992-03-07,357.3,1.1922551641193309,True 1992-03-14,357.8,1.6623605905593308,True 1992-03-21,358.1,1.9324651618580901,True 1992-03-28,358.4,2.202568885396488,True 1992-04-04,358.5,2.272671768544967,True 1992-04-11,358.9,2.6427738186628744,True 1992-04-18,359.7,3.4128750430990067,True 1992-04-25,359.2,2.882975449191406,True 1992-05-02,359.6,3.253075044267348,True 1992-05-09,359.7,3.323173835643331,True 1992-05-16,358.6,2.1932718306252355,True 1992-05-23,359.6,3.1633690365080156,False 1992-05-30,360.2,3.733465460575985,False 1992-06-06,360.0,3.503561110102794,False 1992-06-13,359.4,2.873655992351246,False 1992-06-20,358.7,2.143750114573436,False 1992-06-27,358.4,1.8138434840107038,False 1992-07-04,358.4,1.7839361078937372,False 1992-07-11,357.2,0.5540279934423324,False 1992-07-18,356.3,-0.37588085213434397,False 1992-07-25,356.1,-0.6057904216379484,False 1992-08-01,354.9,-1.8357007078808465,False 1992-08-08,355.3,-1.4656117036859655,False 1992-08-15,355.3,-1.4955234018873398,False 1992-08-22,354.5,-2.3254357953294402,False 1992-08-29,354.3,-2.5553488768675265,False 1992-09-05,353.5,-3.3852626393677383,False 1992-09-12,353.6,-3.315177075706856,False 1992-09-19,352.3,-4.645092178772359,False 1992-09-26,352.7,-4.275007941462604,False 1992-10-03,353.6,-3.404924356686479,True 1992-10-10,353.3,-3.7348414173638957,True 1992-10-17,353.2,-3.864759116425205,True 1992-10-24,353.5,-3.5946774468117155,True 1992-10-31,353.5,-3.624596401475401,True 1992-11-07,353.9,-3.254515973379,True 1992-11-14,353.8,-3.384436155495848,True 1992-11-21,354.5,-2.714356940810262,True 1992-11-28,354.6,-2.6442783223171773,True 1992-12-05,354.8,-2.474200293022193,True 1992-12-12,355.3,-2.004122845941822,True 1992-12-19,355.4,-1.934045974103185,True 1992-12-26,355.9,-1.4639696705441452,True 1993-01-02,356.2,-1.1938939283133436,True 1993-01-09,356.9,-0.5238187404701762,True 1993-01-16,356.7,-0.7537441000848162,True 1993-01-23,356.6,-0.8836700002379985,True 1993-01-30,357.0,-0.5135964340215082,True 1993-02-06,356.6,-0.9435233945375217,True 1993-02-13,357.2,-0.37345087489927664,True 1993-02-20,357.3,-0.3033788682304248,True 1993-02-27,357.6,-0.033307367665656784,True 1993-03-06,358.3,0.6367636336498208,True 1993-03-13,358.5,0.8068341425598646,True 1993-03-20,358.1,0.37690416589776987,True 1993-03-27,358.8,1.0469737104859291,True 1993-04-03,359.1,1.3170427831361167,True 1993-04-10,358.8,0.9871113906493747,True 1993-04-17,359.4,1.5571795398158201,True 1993-04-24,360.0,2.1272472374151903,True 1993-05-01,359.6,1.6973144902160584,True 1993-05-08,359.7,1.7673813049764817,True 1993-05-15,360.7,2.737447688443865,False 1993-05-22,360.6,2.607513647354665,False 1993-05-29,360.3,2.277579188434686,False 1993-06-05,359.7,1.6476443183989886,False 1993-06-12,359.9,1.817709043951936,False 1993-06-19,359.3,1.1877733717871592,False 1993-06-26,359.1,0.9578373085875,False 1993-07-03,357.9,-0.27209913897513616,False 1993-07-10,358.0,-0.2020359642390872,False 1993-07-17,358.1,-0.131973160553855,False 1993-07-24,356.6,-1.6619107212795825,False 1993-07-31,356.5,-1.7918486397871902,False 1993-08-07,355.8,-2.5217869094581147,False 1993-08-14,355.9,-2.451725523684786,False 1993-08-21,354.9,-3.481664475870275,False 1993-08-28,354.7,-3.7116037594283284,False 1993-09-04,354.3,-4.141543367783584,False 1993-09-11,353.2,-5.2714832943713645,False 1993-09-18,353.8,-4.701423532637591,True 1993-09-25,353.8,-4.731364076039142,True 1993-10-02,353.8,-4.761304918043493,True 1993-10-09,353.8,-4.7912460521288835,True 1993-10-16,354.0,-4.621187471784424,True 1993-10-23,354.4,-4.251129170509785,True 1993-10-30,354.3,-4.381071141815369,True 1993-11-06,354.7,-4.011013379222504,True 1993-11-13,355.1,-3.6409558762630923,True 1993-11-20,355.6,-3.170898626479925,True 1993-11-27,356.0,-2.800841623426379,True 1993-12-04,356.2,-2.6307848606666084,True 1993-12-11,356.5,-2.36072833177559,True 1993-12-18,356.9,-1.9906720303389989,True 1993-12-25,357.5,-1.4206159499531736,True 1994-01-01,358.1,-0.8505600842253216,True 1994-01-08,358.1,-0.8805044267733138,True 1994-01-15,358.4,-0.6104489712258214,True 1994-01-22,358.3,-0.7403937112221115,True 1994-01-29,358.7,-0.37033864041239895,True 1994-02-05,358.4,-0.7002837524574375,True 1994-02-12,358.6,-0.5302290410288037,True 1994-02-19,359.0,-0.16017449980898846,True 1994-02-26,359.6,0.4098798775091268,True 1994-03-05,358.7,-0.5200659027784127,True 1994-03-12,359.8,0.549988165613911,True 1994-03-19,360.4,1.1200420889607585,True 1994-03-26,360.8,1.4900958735262293,True 1994-04-02,360.6,1.2601495255634632,True 1994-04-09,361.0,1.6302030513148225,True 1994-04-16,361.0,1.6002564570122217,True 1994-04-23,361.3,1.8703097488766502,True 1994-04-30,362.2,2.7403629331183197,True 1994-05-07,361.6,2.110416015936778,False 1994-05-14,361.4,1.8804690035207727,False 1994-05-21,361.7,2.1505219020484105,False 1994-05-28,361.9,2.3205747176869522,False 1994-06-04,361.0,1.3906274565929948,False 1994-06-11,361.0,1.360680124912335,False 1994-06-18,360.9,1.2307327287799694,False 1994-06-25,360.7,1.0007852743204353,False 1994-07-02,360.2,0.47083776764714,False 1994-07-09,359.9,0.1408902148630773,False 1994-07-16,359.4,-0.3890573779397073,False 1994-07-23,359.0,-0.8190050046797523,False 1994-07-30,358.8,-1.048952659286499,False 1994-08-06,358.1,-1.7789003357000865,False 1994-08-13,357.5,-2.4088480278712723,False 1994-08-20,357.6,-2.338795729761614,False 1994-08-27,356.3,-3.668743435343572,False 1994-09-03,356.4,-3.5986911386001452,False 1994-09-10,356.4,-3.6286388335250876,False 1994-09-17,355.4,-4.658586514122931,False 1994-09-24,355.5,-4.588534174409006,True 1994-10-01,355.4,-4.718481808409365,True 1994-10-08,355.8,-4.3484294101607475,True 1994-10-15,356.0,-4.1783769737106695,True 1994-10-22,356.3,-3.908324493117334,True 1994-10-29,356.6,-3.638271962449778,True 1994-11-05,356.9,-3.3682193757878167,True 1994-11-12,357.4,-2.898166727221735,True 1994-11-19,357.9,-2.4281140108528234,True 1994-11-26,358.1,-2.2580612207930244,True 1994-12-03,358.4,-1.9880083511650923,True 1994-12-10,359.1,-1.317955396102377,True 1994-12-17,359.2,-1.247902349749097,True 1994-12-24,359.1,-1.377849206260123,True 1994-12-31,359.5,-1.0077959598011716,True 1995-01-07,359.6,-0.937742604548589,True 1995-01-14,360.2,-0.36768913468949904,True 1995-01-21,360.1,-0.4976355444217688,True 1995-01-28,360.0,-0.6275818279541454,True 1995-02-04,360.6,-0.05752797950577815,True 1995-02-11,361.0,0.31252600669313324,True 1995-02-18,360.8,0.08258013640170248,True 1995-02-25,361.3,0.552634415368459,True 1995-03-04,362.2,1.4226888493309389,True 1995-03-11,361.2,0.3927434440162756,True 1995-03-18,360.9,0.06279820514049561,True 1995-03-25,362.0,1.1328531384092457,True 1995-04-01,363.8,2.902908249517054,True 1995-04-08,363.4,2.4729635441480013,True 1995-04-15,363.3,2.3430190279753447,True 1995-04-22,362.8,1.8130747066614958,False 1995-04-29,363.5,2.483130585858305,False 1995-05-06,363.2,2.153186671206754,True 1995-05-13,364.1,3.023242968337115,True 1995-05-20,364.1,2.993299482868906,True 1995-05-27,363.4,2.2633562204109126,False 1995-06-03,363.9,2.733413186561279,False 1995-06-10,363.4,2.20347038690727,False 1995-06-17,362.9,1.6735278270254526,False 1995-06-24,362.8,1.543585512481684,False 1995-07-01,362.5,1.2136434488310215,False 1995-07-08,362.2,0.8837016416177903,False 1995-07-15,361.9,0.5537600963756972,False 1995-07-22,361.5,0.12381881862756927,False 1995-07-29,360.9,-0.50612218611451,False 1995-08-05,360.4,-1.0360629123490526,False 1995-08-12,359.2,-2.2660033545854503,False 1995-08-19,358.7,-2.79594350734385,False 1995-08-26,359.2,-2.3258833651549935,False 1995-09-02,357.3,-4.255822922560469,False 1995-09-09,358.5,-3.0857621741126877,False 1995-09-16,358.5,-3.115701114374531,False 1995-09-23,358.2,-3.4456397379199757,False 1995-09-30,357.5,-4.175578039333345,True 1995-10-07,357.6,-4.105516013210092,False 1995-10-14,357.6,-4.135453654156208,True 1995-10-21,358.0,-3.7653909567883375,True 1995-10-28,358.2,-3.595327915734117,True 1995-11-04,359.1,-2.7252645256315873,True 1995-11-11,359.4,-2.4552007811299745,True 1995-11-18,359.6,-2.285136676888783,True 1995-11-25,359.8,-2.115072207578578,True 1995-12-02,360.1,-1.8450073678804984,True 1995-12-09,360.4,-1.574942152486642,True 1995-12-16,360.5,-1.5048765560994184,True 1995-12-23,360.8,-1.2348105734324122,True 1995-12-30,361.7,-0.3647441992098379,True 1996-01-06,361.8,-0.29467742816638065,True 1996-01-13,362.0,-0.12461025504791223,True 1996-01-20,362.1,-0.05454267461067275,True 1996-01-27,362.2,0.015525318378138309,True 1996-02-03,362.6,0.3855937291407372,True 1996-02-10,363.1,0.8556625628884831,True 1996-02-17,363.0,0.7257318248219349,True 1996-02-24,364.0,1.6958015201311696,True 1996-03-02,363.8,1.4658716539952934,True 1996-03-09,363.6,1.2359422315827828,True 1996-03-16,364.1,1.7060132580512573,True 1996-03-23,364.5,2.0760847385477064,True 1996-03-30,364.3,1.8461566782083878,True 1996-04-06,364.5,2.0162290821586453,True 1996-04-13,364.8,2.2863019555134088,True 1996-04-20,364.4,1.856375303376467,True 1996-04-27,365.1,2.526449130841229,True 1996-05-04,364.9,2.2965234429901216,True 1996-05-11,365.3,2.666598244894942,True 1996-05-18,365.7,3.0366735416167216,True 1996-05-25,365.4,2.706749338205782,False 1996-06-01,364.8,2.0768256397016103,False 1996-06-08,365.1,2.346902451133076,False 1996-06-15,365.2,2.4169797775181223,False 1996-06-22,365.0,2.187057623864291,False 1996-06-29,364.3,1.4571359951679597,False 1996-07-06,364.1,1.2272148964151484,False 1996-07-13,363.7,0.7972943325807478,False 1996-07-20,363.3,0.3673743086293939,False 1996-07-27,362.8,-0.16254517048548678,False 1996-08-03,361.7,-1.292464099820961,False 1996-08-10,362.1,-0.9223824744448166,False 1996-08-17,361.2,-1.8523002894357887,False 1996-08-24,360.8,-2.2822175398830495,False 1996-08-31,360.8,-2.312134220886776,False 1996-09-07,359.8,-3.3420503275577857,False 1996-09-14,359.8,-3.371965855017663,False 1996-09-21,359.0,-4.201880798398577,False 1996-09-28,359.0,-4.231795152843688,False 1996-10-05,359.4,-3.8617089135067317,True 1996-10-12,359.5,-3.7916220755522545,True 1996-10-19,359.8,-3.5215346341554437,True 1996-10-26,359.8,-3.5514465845024006,True 1996-11-02,359.9,-3.4813579217898223,True 1996-11-09,360.5,-2.911268641225149,True 1996-11-16,360.7,-2.74117873802669,True 1996-11-23,361.2,-2.271088207423361,True 1996-11-30,361.4,-2.1009970446548323,True 1996-12-07,361.9,-1.6309052449715864,True 1996-12-14,362.6,-0.9608128036347807,True 1996-12-21,362.4,-1.1907197159164298,True 1996-12-28,362.6,-1.02062597709903,True 1997-01-04,362.9,-0.750531582476242,True 1997-01-11,363.0,-0.6804365273519579,True 1997-01-18,363.1,-0.6103408070411547,True 1997-01-25,363.5,-0.2402444168695297,True 1997-02-01,363.2,-0.5701473521733647,True 1997-02-08,364.1,0.29995039170023574,True 1997-02-15,364.0,0.17004881939328698,True 1997-02-22,364.2,0.34014793553734535,True 1997-03-01,364.5,0.6102477447530532,True 1997-03-08,364.1,0.18034825165034363,True 1997-03-15,364.1,0.1504494608283835,True 1997-03-22,364.7,0.7205513768755623,True 1997-03-29,365.4,1.390654004369651,True 1997-04-05,365.8,1.760757347877643,True 1997-04-12,366.2,2.1308614119557205,True 1997-04-19,366.6,2.5009662011494243,True 1997-04-26,366.7,2.5710717199933697,True 1997-05-03,366.7,2.541177973011713,False 1997-05-10,366.8,2.611284964717697,False 1997-05-17,367.0,2.7813926996137184,False 1997-05-24,366.6,2.3515011821917255,False 1997-05-31,366.3,2.0216104169326172,False 1997-06-07,365.7,1.3917204083067531,False 1997-06-14,365.6,1.261831160773795,False 1997-06-21,365.5,1.1319426787823659,False 1997-06-28,365.1,0.7020549667707314,False 1997-07-05,365.0,0.5721680291661073,False 1997-07-12,364.6,0.14228187038520446,False 1997-07-19,364.1,-0.38760350516622566,False 1997-07-26,363.8,-0.7174880930929817,False 1997-08-02,363.3,-1.2473718890107648,False 1997-08-09,363.3,-1.2772548885458832,False 1997-08-16,362.6,-2.0071370873354795,False 1997-08-23,361.5,-3.137018481027326,False 1997-08-30,361.6,-3.0668990652800403,False 1997-09-06,360.6,-4.096778835763018,False 1997-09-13,360.2,-4.526657788156228,False 1997-09-20,360.0,-4.756535918150462,False 1997-09-27,359.8,-4.986413221447378,True 1997-10-04,360.5,-4.316289693759131,True 1997-10-11,360.4,-4.446165330808867,True 1997-10-18,361.0,-3.87604012833026,True 1997-10-25,361.1,-3.8059140820678863,True 1997-11-01,361.7,-3.235787187776964,True 1997-11-08,362.1,-2.8656594412234426,True 1997-11-15,362.0,-2.995530838184152,True 1997-11-22,362.6,-2.4254013744464373,True 1997-11-29,363.5,-1.5552710458085812,True 1997-12-06,363.9,-1.1851398480795865,True 1997-12-13,363.9,-1.2150077770789949,True 1997-12-20,364.2,-0.944874828637353,True 1997-12-27,365.0,-0.17474099859583703,True 1998-01-03,365.2,-0.00460628280632136,True 1998-01-10,365.3,0.06552932286859914,True 1998-01-17,365.3,0.035665822555415616,True 1998-01-24,365.3,0.005803220370012241,True 1998-01-31,365.6,0.27594152041757525,True 1998-02-07,366.0,0.6460807267924906,True 1998-02-14,365.5,0.11622084357833273,True 1998-02-21,366.0,0.5863618748480235,True 1998-02-28,367.3,1.8565038246638323,True 1998-03-07,367.0,1.5266466970770125,True 1998-03-14,366.6,1.096790496128392,True 1998-03-21,367.4,1.866935225847783,True 1998-03-28,368.5,2.9370808902544923,True 1998-04-04,368.6,3.007227493356936,True 1998-04-11,368.6,2.9773750391528893,True 1998-04-18,368.0,2.3475235316292355,True 1998-04-25,368.9,3.217672974762195,True 1998-05-02,369.1,3.3878233725174596,True 1998-05-09,368.8,3.057974728849615,True 1998-05-16,368.5,2.728127047702685,True 1998-05-23,369.6,3.798280333010041,False 1998-05-30,369.7,3.8684345886941287,False 1998-06-06,369.4,3.5385898186667646,False 1998-06-13,368.8,2.908746026829135,False 1998-06-20,368.5,2.5789032170713426,False 1998-06-27,368.3,2.3490613932730753,False 1998-07-04,368.0,2.0192205593031076,False 1998-07-11,367.5,1.4893807190196071,False 1998-07-18,367.6,1.559541876269975,False 1998-07-25,367.3,1.2297040348906307,False 1998-08-01,366.8,0.6998671987076364,False 1998-08-08,366.4,0.27003137153599255,False 1998-08-15,365.6,-0.5598034428197707,False 1998-08-22,365.6,-0.5896372405661623,False 1998-08-29,364.2,-2.0194700179201845,False 1998-09-05,364.7,-1.5493017711096968,False 1998-09-12,363.9,-2.379132496373245,False 1998-09-19,363.5,-2.8089621899600843,False 1998-09-26,363.6,-2.73879084813035,True 1998-10-03,364.0,-2.3686184671548745,True 1998-10-10,364.1,-2.2984450433150982,True 1998-10-17,364.4,-2.0282705729033523,True 1998-10-24,364.4,-2.0580950522225976,True 1998-10-31,364.7,-1.7879184775866293,True 1998-11-07,365.0,-1.5177408453199632,True 1998-11-14,365.4,-1.1475621517577679,True 1998-11-21,365.8,-0.7773823932460004,True 1998-11-28,366.0,-0.607201566141498,True 1998-12-05,366.4,-0.2370196668117046,True 1998-12-12,366.7,0.033163308365317334,True 1998-12-19,367.3,0.6033473630005233,True 1998-12-26,367.3,0.5735325006942844,True 1999-01-02,367.5,0.7437187250361035,True 1999-01-09,367.8,1.013906039604933,True 1999-01-16,367.8,0.9840944479687437,True 1999-01-23,368.3,1.4542839536850352,True 1999-01-30,369.2,2.3244745603002457,True 1999-02-06,369.1,2.1946662713505134,False 1999-02-13,368.8,1.86485909036071,True 1999-02-20,369.0,2.0350530208453392,True 1999-02-27,368.5,1.505248066308127,True 1999-03-06,368.1,1.075444230241942,True 1999-03-13,369.5,2.4456415161288874,True 1999-03-20,370.2,3.115839927440504,True 1999-03-27,370.6,3.486039467637454,True 1999-04-03,371.1,3.956240140169598,True 1999-04-10,371.5,4.326441948476258,False 1999-04-17,371.0,3.796644895985935,True 1999-04-24,370.3,3.0668489861162698,False 1999-05-01,370.8,3.5370542222742642,False 1999-05-08,371.3,4.007260607856267,False 1999-05-15,371.0,3.6774681462476337,False 1999-05-22,370.8,3.4476768408232488,False 1999-05-29,370.3,2.9178866949471285,False 1999-06-05,370.9,3.4880977119725003,False 1999-06-12,370.3,2.85830989524203,False 1999-06-19,369.9,2.4285232480874015,False 1999-06-26,369.9,2.398737773829737,False 1999-07-03,369.4,1.8689534757793922,False 1999-07-10,370.1,2.539170357235946,False 1999-07-17,369.5,1.9093884214881882,False 1999-07-24,368.6,0.9796076718142785,False 1999-07-31,367.4,-0.25017188851848005,False 1999-08-07,367.6,-0.07995025625331209,False 1999-08-14,366.7,-1.009727428144572,False 1999-08-21,366.4,-1.3395034009569144,False 1999-08-28,366.1,-1.669278171465919,False 1999-09-04,364.1,-3.6990517364581024,False 1999-09-11,364.7,-3.128824092730497,False 1999-09-18,365.2,-2.658595237090765,False 1999-09-25,364.7,-3.1883651663576416,True 1999-10-02,364.5,-3.418133877360333,True 1999-10-09,365.0,-2.947901366938879,True 1999-10-16,364.9,-3.0776676319441094,True 1999-10-23,365.6,-2.407432669237437,True 1999-10-30,365.7,-2.3371964756913144,True 1999-11-06,366.2,-1.866959048188562,True 1999-11-13,366.7,-1.3967203836230624,True 1999-11-20,366.6,-1.5264804788990887,True 1999-11-27,367.1,-1.056239330932101,True 1999-12-04,367.4,-0.7859969366480186,True 1999-12-11,368.0,-0.2157532929833792,True 1999-12-18,368.0,-0.24550839688583892,True 1999-12-25,368.2,-0.07526224531341086,True 2000-01-01,368.6,0.29498516476490977,True 2000-01-08,368.5,0.1652338363693957,True 2000-01-15,369.0,0.6354837725097582,True 2000-01-22,369.8,1.4057349761847604,True 2000-01-29,369.2,0.7759874503825017,True 2000-02-05,369.1,0.6462411980805314,True 2000-02-12,369.6,1.116496222245246,True 2000-02-19,369.3,0.7867525258326395,True 2000-02-26,369.5,0.957010111787838,True 2000-03-04,370.0,1.4272689830452805,True 2000-03-11,370.0,1.3975291425286969,True 2000-03-18,370.9,2.267790593150835,True 2000-03-25,370.7,2.0380533378140626,True 2000-04-01,370.9,2.2083173794097775,True 2000-04-08,371.7,2.978582720818622,True 2000-04-15,371.8,3.048849364910666,True 2000-04-22,372.0,3.2191173145450307,True 2000-04-29,371.3,2.489386572570311,True 2000-05-06,371.2,2.359657141824073,False 2000-05-13,371.7,2.829929025133538,True 2000-05-20,371.9,3.0002022253148084,True 2000-05-27,371.8,2.870476745173562,True 2000-06-03,371.9,2.9407525875043916,False 2000-06-10,371.6,2.611029755091522,False 2000-06-17,371.7,2.6813082507081276,False 2000-06-24,371.3,2.251588077116878,False 2000-07-01,370.8,1.721869237069427,False 2000-07-08,370.0,0.8921517333070028,False 2000-07-15,370.2,1.0624355685599198,False 2000-07-22,369.7,0.5327207455477492,False 2000-07-29,369.0,-0.19699273302063602,False 2000-08-05,368.7,-0.5267048644471402,False 2000-08-12,368.3,-0.9564156460443201,False 2000-08-19,367.7,-1.5861250751356124,False 2000-08-26,367.1,-2.2158331490550722,False 2000-09-02,367.2,-2.1455398651476116,False 2000-09-09,366.7,-2.6752452207687156,False 2000-09-16,366.2,-3.204949213284806,False 2000-09-23,366.2,-3.234651840072843,False 2000-09-30,366.4,-3.064353098520769,True 2000-10-07,366.3,-3.194052986026918,True 2000-10-14,366.6,-2.923751500000776,True 2000-10-21,366.7,-2.853448637862357,True 2000-10-28,367.3,-2.2831443970423493,True 2000-11-04,367.6,-2.0128387749822423,True 2000-11-11,368.0,-1.6425317691343366,True 2000-11-18,368.6,-1.072223376961631,True 2000-11-25,368.3,-1.401913595937856,True 2000-12-02,369.0,-0.7316024235474856,True 2000-12-09,369.6,-0.16128985728562384,True 2000-12-16,369.3,-0.4909758946583338,True 2000-12-23,369.5,-0.3206605331823198,True 2000-12-30,369.8,-0.05034377038492721,True 2001-01-06,369.8,-0.08002560380441537,True 2001-01-13,370.2,0.29029396901034943,True 2001-01-20,369.9,-0.03938504950031074,True 2001-01-27,370.8,0.8309373430932965,True 2001-02-03,371.3,1.3012611492098927,True 2001-02-10,371.1,1.0715863712577516,True 2001-02-17,371.7,1.6419130116341307,True 2001-02-24,371.2,1.1122410727257375,True 2001-03-03,372.2,2.082570556908479,True 2001-03-10,372.2,2.052901466547439,True 2001-03-17,372.1,1.9232338039972205,True 2001-03-24,371.8,1.5935675716013407,True 2001-03-31,372.0,1.7639027716927558,True 2001-04-07,372.7,2.43423940659369,True 2001-04-14,372.7,2.4045774786156358,True 2001-04-21,373.0,2.6749169900592733,True 2001-04-28,372.7,2.3452579432146194,True 2001-05-05,373.7,3.315600340360902,True 2001-05-12,373.9,3.4859441837666054,True 2001-05-19,373.7,3.2562894756894707,False 2001-05-26,373.9,3.4266362183765295,False 2001-06-02,373.8,3.296984414064127,False 2001-06-09,373.1,2.5673340649777288,False 2001-06-16,372.8,2.2376851733320677,False 2001-06-23,372.9,2.3080377413313045,False 2001-06-30,372.7,2.0783917711686968,False 2001-07-07,372.1,1.4487472650268955,False 2001-07-14,371.3,0.6191042250776491,False 2001-07-21,371.2,0.4894626534820645,False 2001-07-28,370.6,-0.14017744760946016,False 2001-08-04,369.9,-0.8698160760574183,False 2001-08-11,369.5,-1.2994532297327623,False 2001-08-18,369.3,-1.5290889065174724,False 2001-08-25,369.0,-1.8587231043042038,False 2001-09-01,368.4,-2.488355820996219,False 2001-09-08,368.2,-2.7179870545076596,False 2001-09-15,368.0,-2.947616802763264,False 2001-09-22,367.4,-3.577245063698797,False 2001-09-29,367.4,-3.6068718352603355,True 2001-10-06,367.8,-3.2364971154050295,True 2001-10-13,367.6,-3.4661209021007835,True 2001-10-20,368.1,-2.995743193326007,True 2001-10-27,368.7,-2.42536398707,True 2001-11-03,368.7,-2.4549832813327725,True 2001-11-10,368.8,-2.384601074125044,True 2001-11-17,369.7,-1.5142173634684468,True 2001-11-24,370.3,-0.9438321473950282,True 2001-12-01,370.3,-0.9734454239479078,True 2001-12-08,370.8,-0.5030571911807442,True 2001-12-15,371.2,-0.1326674471580418,True 2001-12-22,371.3,-0.062276189954900474,True ================================================ FILE: doc/notebooks/data/imagenet_class_index.json ================================================ {"0": ["n01440764", "tench"], "1": ["n01443537", "goldfish"], "2": ["n01484850", "great_white_shark"], "3": ["n01491361", "tiger_shark"], "4": ["n01494475", "hammerhead"], "5": ["n01496331", "electric_ray"], "6": ["n01498041", "stingray"], "7": ["n01514668", "cock"], "8": ["n01514859", "hen"], "9": ["n01518878", "ostrich"], "10": ["n01530575", "brambling"], "11": ["n01531178", "goldfinch"], "12": ["n01532829", "house_finch"], "13": ["n01534433", "junco"], "14": ["n01537544", "indigo_bunting"], "15": ["n01558993", "robin"], "16": ["n01560419", 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["n01770393", "scorpion"], "72": ["n01773157", "black_and_gold_garden_spider"], "73": ["n01773549", "barn_spider"], "74": ["n01773797", "garden_spider"], "75": ["n01774384", "black_widow"], "76": ["n01774750", "tarantula"], "77": ["n01775062", "wolf_spider"], "78": ["n01776313", "tick"], "79": ["n01784675", "centipede"], "80": ["n01795545", "black_grouse"], "81": ["n01796340", "ptarmigan"], "82": ["n01797886", "ruffed_grouse"], "83": ["n01798484", "prairie_chicken"], "84": ["n01806143", "peacock"], "85": ["n01806567", "quail"], "86": ["n01807496", "partridge"], "87": ["n01817953", "African_grey"], "88": ["n01818515", "macaw"], "89": ["n01819313", "sulphur-crested_cockatoo"], "90": ["n01820546", "lorikeet"], "91": ["n01824575", "coucal"], "92": ["n01828970", "bee_eater"], "93": ["n01829413", "hornbill"], "94": ["n01833805", "hummingbird"], "95": ["n01843065", "jacamar"], "96": ["n01843383", "toucan"], "97": ["n01847000", "drake"], "98": ["n01855032", "red-breasted_merganser"], "99": ["n01855672", "goose"], "100": ["n01860187", "black_swan"], "101": ["n01871265", "tusker"], "102": ["n01872401", "echidna"], "103": ["n01873310", "platypus"], "104": ["n01877812", "wallaby"], "105": ["n01882714", "koala"], "106": ["n01883070", "wombat"], "107": ["n01910747", "jellyfish"], "108": ["n01914609", "sea_anemone"], "109": ["n01917289", "brain_coral"], "110": ["n01924916", "flatworm"], "111": ["n01930112", "nematode"], "112": ["n01943899", "conch"], "113": ["n01944390", "snail"], "114": ["n01945685", "slug"], "115": ["n01950731", "sea_slug"], "116": ["n01955084", "chiton"], "117": ["n01968897", "chambered_nautilus"], "118": ["n01978287", "Dungeness_crab"], "119": ["n01978455", "rock_crab"], "120": ["n01980166", "fiddler_crab"], "121": ["n01981276", "king_crab"], "122": ["n01983481", "American_lobster"], "123": ["n01984695", "spiny_lobster"], "124": ["n01985128", "crayfish"], "125": ["n01986214", "hermit_crab"], "126": ["n01990800", "isopod"], "127": ["n02002556", 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"West_Highland_white_terrier"], "204": ["n02098413", "Lhasa"], "205": ["n02099267", "flat-coated_retriever"], "206": ["n02099429", "curly-coated_retriever"], "207": ["n02099601", "golden_retriever"], "208": ["n02099712", "Labrador_retriever"], "209": ["n02099849", "Chesapeake_Bay_retriever"], "210": ["n02100236", "German_short-haired_pointer"], "211": ["n02100583", "vizsla"], "212": ["n02100735", "English_setter"], "213": ["n02100877", "Irish_setter"], "214": ["n02101006", "Gordon_setter"], "215": ["n02101388", "Brittany_spaniel"], "216": ["n02101556", "clumber"], "217": ["n02102040", "English_springer"], "218": ["n02102177", "Welsh_springer_spaniel"], "219": ["n02102318", "cocker_spaniel"], "220": ["n02102480", "Sussex_spaniel"], "221": ["n02102973", "Irish_water_spaniel"], "222": ["n02104029", "kuvasz"], "223": ["n02104365", "schipperke"], "224": ["n02105056", "groenendael"], "225": ["n02105162", "malinois"], "226": ["n02105251", "briard"], "227": ["n02105412", "kelpie"], "228": ["n02105505", "komondor"], "229": ["n02105641", "Old_English_sheepdog"], "230": ["n02105855", "Shetland_sheepdog"], "231": ["n02106030", "collie"], "232": ["n02106166", "Border_collie"], "233": ["n02106382", "Bouvier_des_Flandres"], "234": ["n02106550", "Rottweiler"], "235": ["n02106662", "German_shepherd"], "236": ["n02107142", "Doberman"], "237": ["n02107312", "miniature_pinscher"], "238": ["n02107574", "Greater_Swiss_Mountain_dog"], "239": ["n02107683", "Bernese_mountain_dog"], "240": ["n02107908", "Appenzeller"], "241": ["n02108000", "EntleBucher"], "242": ["n02108089", "boxer"], "243": ["n02108422", "bull_mastiff"], "244": ["n02108551", "Tibetan_mastiff"], "245": ["n02108915", "French_bulldog"], "246": ["n02109047", "Great_Dane"], "247": ["n02109525", "Saint_Bernard"], "248": ["n02109961", "Eskimo_dog"], "249": ["n02110063", "malamute"], "250": ["n02110185", "Siberian_husky"], "251": ["n02110341", "dalmatian"], "252": ["n02110627", "affenpinscher"], "253": ["n02110806", "basenji"], "254": ["n02110958", "pug"], "255": ["n02111129", "Leonberg"], "256": ["n02111277", "Newfoundland"], "257": ["n02111500", "Great_Pyrenees"], "258": ["n02111889", "Samoyed"], "259": ["n02112018", "Pomeranian"], "260": ["n02112137", "chow"], "261": ["n02112350", "keeshond"], "262": ["n02112706", "Brabancon_griffon"], "263": ["n02113023", "Pembroke"], "264": ["n02113186", "Cardigan"], "265": ["n02113624", "toy_poodle"], "266": ["n02113712", "miniature_poodle"], "267": ["n02113799", "standard_poodle"], "268": ["n02113978", "Mexican_hairless"], "269": ["n02114367", "timber_wolf"], "270": ["n02114548", "white_wolf"], "271": ["n02114712", "red_wolf"], "272": ["n02114855", "coyote"], "273": ["n02115641", "dingo"], "274": ["n02115913", "dhole"], "275": ["n02116738", "African_hunting_dog"], "276": ["n02117135", "hyena"], "277": ["n02119022", "red_fox"], "278": ["n02119789", "kit_fox"], "279": ["n02120079", "Arctic_fox"], "280": ["n02120505", "grey_fox"], "281": ["n02123045", "tabby"], "282": ["n02123159", "tiger_cat"], "283": ["n02123394", "Persian_cat"], "284": ["n02123597", "Siamese_cat"], "285": ["n02124075", "Egyptian_cat"], "286": ["n02125311", "cougar"], "287": ["n02127052", "lynx"], "288": ["n02128385", "leopard"], "289": ["n02128757", "snow_leopard"], "290": ["n02128925", "jaguar"], "291": ["n02129165", "lion"], "292": ["n02129604", "tiger"], "293": ["n02130308", "cheetah"], "294": ["n02132136", "brown_bear"], "295": ["n02133161", "American_black_bear"], "296": ["n02134084", "ice_bear"], "297": ["n02134418", "sloth_bear"], "298": ["n02137549", "mongoose"], "299": ["n02138441", "meerkat"], "300": ["n02165105", "tiger_beetle"], "301": ["n02165456", "ladybug"], "302": ["n02167151", "ground_beetle"], "303": ["n02168699", "long-horned_beetle"], "304": ["n02169497", "leaf_beetle"], "305": ["n02172182", "dung_beetle"], "306": ["n02174001", "rhinoceros_beetle"], "307": ["n02177972", "weevil"], "308": ["n02190166", "fly"], "309": ["n02206856", "bee"], "310": ["n02219486", "ant"], "311": ["n02226429", "grasshopper"], "312": ["n02229544", "cricket"], "313": ["n02231487", "walking_stick"], "314": ["n02233338", "cockroach"], "315": ["n02236044", "mantis"], "316": ["n02256656", "cicada"], "317": ["n02259212", "leafhopper"], "318": ["n02264363", "lacewing"], "319": ["n02268443", "dragonfly"], "320": ["n02268853", "damselfly"], "321": ["n02276258", "admiral"], "322": ["n02277742", "ringlet"], "323": ["n02279972", "monarch"], "324": ["n02280649", "cabbage_butterfly"], "325": ["n02281406", "sulphur_butterfly"], "326": ["n02281787", "lycaenid"], "327": ["n02317335", "starfish"], "328": ["n02319095", "sea_urchin"], "329": ["n02321529", "sea_cucumber"], "330": ["n02325366", "wood_rabbit"], "331": ["n02326432", "hare"], "332": ["n02328150", "Angora"], "333": ["n02342885", "hamster"], "334": ["n02346627", "porcupine"], "335": ["n02356798", "fox_squirrel"], "336": ["n02361337", "marmot"], "337": ["n02363005", "beaver"], "338": ["n02364673", "guinea_pig"], "339": ["n02389026", "sorrel"], "340": ["n02391049", "zebra"], "341": ["n02395406", "hog"], "342": ["n02396427", "wild_boar"], "343": ["n02397096", "warthog"], "344": ["n02398521", "hippopotamus"], "345": ["n02403003", "ox"], "346": ["n02408429", "water_buffalo"], "347": ["n02410509", "bison"], "348": ["n02412080", "ram"], "349": ["n02415577", "bighorn"], "350": ["n02417914", "ibex"], "351": ["n02422106", "hartebeest"], "352": ["n02422699", "impala"], "353": ["n02423022", "gazelle"], "354": ["n02437312", "Arabian_camel"], "355": ["n02437616", "llama"], "356": ["n02441942", "weasel"], "357": ["n02442845", "mink"], "358": ["n02443114", "polecat"], "359": ["n02443484", "black-footed_ferret"], "360": ["n02444819", "otter"], "361": ["n02445715", "skunk"], "362": ["n02447366", "badger"], "363": ["n02454379", "armadillo"], "364": ["n02457408", "three-toed_sloth"], "365": ["n02480495", "orangutan"], "366": ["n02480855", "gorilla"], "367": ["n02481823", "chimpanzee"], "368": ["n02483362", "gibbon"], "369": ["n02483708", "siamang"], "370": ["n02484975", "guenon"], "371": ["n02486261", "patas"], "372": ["n02486410", "baboon"], "373": ["n02487347", "macaque"], "374": ["n02488291", "langur"], "375": ["n02488702", "colobus"], "376": ["n02489166", "proboscis_monkey"], "377": ["n02490219", "marmoset"], "378": ["n02492035", "capuchin"], "379": ["n02492660", "howler_monkey"], "380": ["n02493509", "titi"], "381": ["n02493793", "spider_monkey"], "382": ["n02494079", "squirrel_monkey"], "383": ["n02497673", "Madagascar_cat"], "384": ["n02500267", "indri"], "385": ["n02504013", "Indian_elephant"], "386": ["n02504458", "African_elephant"], "387": ["n02509815", "lesser_panda"], "388": ["n02510455", "giant_panda"], "389": ["n02514041", "barracouta"], "390": ["n02526121", "eel"], "391": ["n02536864", "coho"], "392": ["n02606052", "rock_beauty"], "393": ["n02607072", "anemone_fish"], "394": ["n02640242", "sturgeon"], "395": ["n02641379", "gar"], "396": ["n02643566", "lionfish"], "397": ["n02655020", "puffer"], "398": ["n02666196", "abacus"], "399": ["n02667093", "abaya"], "400": ["n02669723", "academic_gown"], "401": ["n02672831", "accordion"], "402": ["n02676566", "acoustic_guitar"], "403": ["n02687172", "aircraft_carrier"], "404": ["n02690373", "airliner"], "405": ["n02692877", "airship"], "406": ["n02699494", "altar"], "407": ["n02701002", "ambulance"], "408": ["n02704792", "amphibian"], "409": ["n02708093", "analog_clock"], "410": ["n02727426", "apiary"], "411": ["n02730930", "apron"], "412": ["n02747177", "ashcan"], "413": ["n02749479", "assault_rifle"], "414": ["n02769748", "backpack"], "415": ["n02776631", "bakery"], "416": ["n02777292", "balance_beam"], "417": ["n02782093", "balloon"], "418": ["n02783161", "ballpoint"], "419": ["n02786058", "Band_Aid"], "420": ["n02787622", "banjo"], "421": ["n02788148", "bannister"], "422": ["n02790996", "barbell"], "423": ["n02791124", "barber_chair"], "424": ["n02791270", "barbershop"], "425": ["n02793495", "barn"], "426": ["n02794156", "barometer"], "427": ["n02795169", "barrel"], "428": ["n02797295", "barrow"], "429": ["n02799071", "baseball"], "430": ["n02802426", "basketball"], "431": ["n02804414", "bassinet"], "432": ["n02804610", "bassoon"], "433": ["n02807133", "bathing_cap"], "434": ["n02808304", "bath_towel"], "435": ["n02808440", "bathtub"], "436": ["n02814533", "beach_wagon"], "437": ["n02814860", "beacon"], "438": ["n02815834", "beaker"], "439": ["n02817516", "bearskin"], "440": ["n02823428", "beer_bottle"], "441": ["n02823750", "beer_glass"], "442": ["n02825657", "bell_cote"], "443": ["n02834397", "bib"], "444": ["n02835271", "bicycle-built-for-two"], "445": ["n02837789", "bikini"], "446": ["n02840245", "binder"], "447": ["n02841315", "binoculars"], "448": ["n02843684", "birdhouse"], "449": ["n02859443", "boathouse"], "450": ["n02860847", "bobsled"], "451": ["n02865351", "bolo_tie"], "452": ["n02869837", "bonnet"], "453": ["n02870880", "bookcase"], "454": ["n02871525", "bookshop"], "455": ["n02877765", "bottlecap"], "456": ["n02879718", "bow"], "457": ["n02883205", "bow_tie"], "458": ["n02892201", "brass"], "459": ["n02892767", "brassiere"], "460": ["n02894605", "breakwater"], "461": ["n02895154", "breastplate"], "462": ["n02906734", "broom"], "463": ["n02909870", "bucket"], "464": ["n02910353", "buckle"], "465": ["n02916936", "bulletproof_vest"], "466": ["n02917067", "bullet_train"], "467": ["n02927161", "butcher_shop"], "468": ["n02930766", "cab"], "469": ["n02939185", "caldron"], "470": ["n02948072", "candle"], "471": ["n02950826", "cannon"], "472": ["n02951358", "canoe"], "473": ["n02951585", "can_opener"], "474": ["n02963159", "cardigan"], "475": ["n02965783", "car_mirror"], "476": ["n02966193", "carousel"], "477": ["n02966687", "carpenter's_kit"], "478": ["n02971356", "carton"], "479": ["n02974003", "car_wheel"], "480": ["n02977058", "cash_machine"], "481": ["n02978881", "cassette"], "482": ["n02979186", "cassette_player"], "483": ["n02980441", "castle"], "484": ["n02981792", "catamaran"], "485": ["n02988304", "CD_player"], "486": ["n02992211", "cello"], "487": ["n02992529", "cellular_telephone"], "488": ["n02999410", "chain"], "489": ["n03000134", "chainlink_fence"], "490": ["n03000247", "chain_mail"], "491": ["n03000684", "chain_saw"], "492": ["n03014705", "chest"], "493": ["n03016953", "chiffonier"], "494": ["n03017168", "chime"], "495": ["n03018349", "china_cabinet"], "496": ["n03026506", "Christmas_stocking"], "497": ["n03028079", "church"], "498": ["n03032252", "cinema"], "499": ["n03041632", "cleaver"], "500": ["n03042490", "cliff_dwelling"], "501": ["n03045698", "cloak"], "502": ["n03047690", "clog"], "503": ["n03062245", "cocktail_shaker"], "504": ["n03063599", "coffee_mug"], "505": ["n03063689", "coffeepot"], "506": ["n03065424", "coil"], "507": ["n03075370", "combination_lock"], "508": ["n03085013", "computer_keyboard"], "509": ["n03089624", "confectionery"], "510": ["n03095699", "container_ship"], "511": ["n03100240", "convertible"], "512": ["n03109150", "corkscrew"], "513": ["n03110669", "cornet"], "514": ["n03124043", "cowboy_boot"], "515": ["n03124170", "cowboy_hat"], "516": ["n03125729", "cradle"], "517": ["n03126707", "crane"], "518": ["n03127747", "crash_helmet"], "519": ["n03127925", "crate"], "520": ["n03131574", "crib"], "521": ["n03133878", "Crock_Pot"], "522": ["n03134739", "croquet_ball"], "523": ["n03141823", "crutch"], "524": ["n03146219", "cuirass"], "525": ["n03160309", "dam"], "526": ["n03179701", "desk"], "527": ["n03180011", "desktop_computer"], "528": ["n03187595", "dial_telephone"], "529": ["n03188531", "diaper"], "530": ["n03196217", "digital_clock"], "531": ["n03197337", "digital_watch"], "532": ["n03201208", "dining_table"], "533": ["n03207743", "dishrag"], "534": ["n03207941", "dishwasher"], "535": ["n03208938", "disk_brake"], "536": ["n03216828", "dock"], "537": ["n03218198", "dogsled"], "538": ["n03220513", "dome"], "539": ["n03223299", "doormat"], "540": ["n03240683", "drilling_platform"], "541": ["n03249569", "drum"], "542": ["n03250847", "drumstick"], "543": ["n03255030", "dumbbell"], "544": ["n03259280", "Dutch_oven"], "545": ["n03271574", "electric_fan"], "546": ["n03272010", "electric_guitar"], "547": ["n03272562", "electric_locomotive"], "548": ["n03290653", "entertainment_center"], "549": ["n03291819", "envelope"], "550": ["n03297495", "espresso_maker"], "551": ["n03314780", "face_powder"], "552": ["n03325584", "feather_boa"], "553": ["n03337140", "file"], "554": ["n03344393", "fireboat"], "555": ["n03345487", "fire_engine"], "556": ["n03347037", "fire_screen"], "557": ["n03355925", "flagpole"], "558": ["n03372029", "flute"], "559": ["n03376595", "folding_chair"], "560": ["n03379051", "football_helmet"], "561": ["n03384352", "forklift"], "562": ["n03388043", "fountain"], "563": ["n03388183", "fountain_pen"], "564": ["n03388549", "four-poster"], "565": ["n03393912", "freight_car"], "566": ["n03394916", "French_horn"], "567": ["n03400231", "frying_pan"], "568": ["n03404251", "fur_coat"], "569": ["n03417042", "garbage_truck"], "570": ["n03424325", "gasmask"], "571": ["n03425413", "gas_pump"], "572": ["n03443371", "goblet"], "573": ["n03444034", "go-kart"], "574": ["n03445777", "golf_ball"], "575": ["n03445924", "golfcart"], "576": ["n03447447", "gondola"], "577": ["n03447721", "gong"], "578": ["n03450230", "gown"], "579": ["n03452741", "grand_piano"], "580": ["n03457902", "greenhouse"], "581": ["n03459775", "grille"], "582": ["n03461385", "grocery_store"], "583": ["n03467068", "guillotine"], "584": ["n03476684", "hair_slide"], "585": ["n03476991", "hair_spray"], "586": ["n03478589", "half_track"], "587": ["n03481172", "hammer"], "588": ["n03482405", "hamper"], "589": ["n03483316", "hand_blower"], "590": ["n03485407", "hand-held_computer"], "591": ["n03485794", "handkerchief"], "592": ["n03492542", "hard_disc"], "593": ["n03494278", "harmonica"], "594": ["n03495258", "harp"], "595": ["n03496892", "harvester"], "596": ["n03498962", "hatchet"], "597": ["n03527444", "holster"], "598": ["n03529860", "home_theater"], "599": ["n03530642", "honeycomb"], "600": ["n03532672", "hook"], "601": ["n03534580", "hoopskirt"], "602": ["n03535780", "horizontal_bar"], "603": ["n03538406", "horse_cart"], "604": ["n03544143", "hourglass"], "605": ["n03584254", "iPod"], "606": ["n03584829", "iron"], "607": ["n03590841", "jack-o'-lantern"], "608": ["n03594734", "jean"], "609": ["n03594945", "jeep"], "610": ["n03595614", "jersey"], "611": ["n03598930", "jigsaw_puzzle"], "612": ["n03599486", "jinrikisha"], "613": ["n03602883", "joystick"], "614": ["n03617480", "kimono"], "615": ["n03623198", "knee_pad"], "616": ["n03627232", "knot"], "617": ["n03630383", "lab_coat"], "618": ["n03633091", "ladle"], "619": ["n03637318", "lampshade"], "620": ["n03642806", "laptop"], "621": ["n03649909", "lawn_mower"], "622": ["n03657121", "lens_cap"], "623": ["n03658185", "letter_opener"], "624": ["n03661043", "library"], "625": ["n03662601", "lifeboat"], "626": ["n03666591", "lighter"], "627": ["n03670208", "limousine"], "628": ["n03673027", "liner"], "629": ["n03676483", "lipstick"], "630": ["n03680355", "Loafer"], "631": ["n03690938", "lotion"], "632": ["n03691459", "loudspeaker"], "633": ["n03692522", "loupe"], "634": ["n03697007", "lumbermill"], "635": ["n03706229", "magnetic_compass"], "636": ["n03709823", "mailbag"], "637": ["n03710193", "mailbox"], "638": ["n03710637", "maillot"], "639": ["n03710721", "maillot"], "640": ["n03717622", "manhole_cover"], "641": ["n03720891", "maraca"], "642": ["n03721384", "marimba"], "643": ["n03724870", "mask"], "644": ["n03729826", "matchstick"], "645": ["n03733131", "maypole"], "646": ["n03733281", "maze"], "647": ["n03733805", "measuring_cup"], "648": ["n03742115", "medicine_chest"], "649": ["n03743016", "megalith"], "650": ["n03759954", "microphone"], "651": ["n03761084", "microwave"], "652": ["n03763968", "military_uniform"], "653": ["n03764736", "milk_can"], "654": ["n03769881", "minibus"], "655": ["n03770439", "miniskirt"], "656": ["n03770679", "minivan"], "657": ["n03773504", "missile"], "658": ["n03775071", "mitten"], "659": ["n03775546", "mixing_bowl"], "660": ["n03776460", "mobile_home"], "661": ["n03777568", "Model_T"], "662": ["n03777754", "modem"], "663": ["n03781244", "monastery"], "664": ["n03782006", "monitor"], "665": ["n03785016", "moped"], "666": ["n03786901", "mortar"], "667": ["n03787032", "mortarboard"], "668": ["n03788195", "mosque"], "669": ["n03788365", "mosquito_net"], "670": ["n03791053", "motor_scooter"], "671": ["n03792782", "mountain_bike"], "672": ["n03792972", "mountain_tent"], "673": ["n03793489", "mouse"], "674": ["n03794056", "mousetrap"], "675": ["n03796401", "moving_van"], "676": ["n03803284", "muzzle"], "677": ["n03804744", "nail"], "678": ["n03814639", "neck_brace"], "679": ["n03814906", "necklace"], "680": ["n03825788", "nipple"], "681": ["n03832673", "notebook"], "682": ["n03837869", 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["n03916031", "perfume"], "712": ["n03920288", "Petri_dish"], "713": ["n03924679", "photocopier"], "714": ["n03929660", "pick"], "715": ["n03929855", "pickelhaube"], "716": ["n03930313", "picket_fence"], "717": ["n03930630", "pickup"], "718": ["n03933933", "pier"], "719": ["n03935335", "piggy_bank"], "720": ["n03937543", "pill_bottle"], "721": ["n03938244", "pillow"], "722": ["n03942813", "ping-pong_ball"], "723": ["n03944341", "pinwheel"], "724": ["n03947888", "pirate"], "725": ["n03950228", "pitcher"], "726": ["n03954731", "plane"], "727": ["n03956157", "planetarium"], "728": ["n03958227", "plastic_bag"], "729": ["n03961711", "plate_rack"], "730": ["n03967562", "plow"], "731": ["n03970156", "plunger"], "732": ["n03976467", "Polaroid_camera"], "733": ["n03976657", "pole"], "734": ["n03977966", "police_van"], "735": ["n03980874", "poncho"], "736": ["n03982430", "pool_table"], "737": ["n03983396", "pop_bottle"], "738": ["n03991062", "pot"], "739": ["n03992509", "potter's_wheel"], "740": 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e,x,f,y,t,a,f,w,n,p,t,b,s,s,w,w,p,w,o,p,n,v,d e,b,s,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,m e,b,y,y,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,s,g e,x,y,y,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,y,p e,x,f,n,f,n,f,c,n,g,e,e,s,s,w,w,p,w,o,p,k,y,u p,x,y,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,v,g e,x,s,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,y,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,y,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,m e,x,s,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,n,m e,x,y,y,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,s,p e,f,y,y,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,s,p e,x,y,n,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,s,g e,x,s,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,g e,b,s,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,m p,x,y,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,v,u p,x,s,w,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,v,u e,b,y,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,m e,f,f,g,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,n,a,g e,b,s,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,s,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,y,n,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,y,p e,s,f,g,f,n,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,v,u e,b,y,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,s,m e,b,s,y,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,m e,b,y,y,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,n,m e,b,y,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,s,g e,f,s,n,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,k,a,g e,x,s,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,g e,f,y,y,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,s,g e,x,y,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,f,g,f,n,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,v,u e,f,f,y,t,l,f,w,n,p,t,b,s,s,w,w,p,w,o,p,n,v,d e,b,y,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,m e,f,f,y,t,l,f,w,n,w,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,y,n,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,s,p e,b,s,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,g e,f,s,y,t,l,f,w,n,p,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,s,w,t,l,f,w,n,n,t,b,s,s,w,w,p,w,o,p,u,v,d e,f,y,n,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,y,p p,x,y,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,v,u e,f,y,n,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,y,g e,x,s,n,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,n,s,g p,x,y,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,s,g e,f,f,g,f,n,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,y,u e,x,f,g,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,n,s,g e,x,y,y,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,s,g e,x,s,n,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,k,s,g e,b,s,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,g e,x,s,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,s,g e,f,y,n,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,y,g e,s,f,n,f,n,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,v,u e,x,f,n,f,n,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,y,u e,b,s,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,g e,x,y,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,s,g e,x,y,y,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,s,n,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,s,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,g e,f,y,n,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,s,g e,x,s,y,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,g e,b,s,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,g e,x,y,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,s,g e,x,f,n,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,k,s,g e,b,s,y,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,g e,f,y,y,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,s,g e,x,y,y,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,y,p e,b,y,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,y,y,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,y,y,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,y,g e,b,y,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,m e,b,y,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,m e,x,s,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,s,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,g e,s,f,g,f,n,f,c,n,g,e,e,s,s,w,w,p,w,o,p,k,y,u e,x,f,w,t,a,f,w,n,w,t,b,s,s,w,w,p,w,o,p,u,v,d e,x,s,y,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,m p,x,y,w,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,v,u e,x,y,y,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,s,g e,s,f,g,f,n,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,y,u e,x,y,y,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,y,g e,x,s,y,t,l,f,w,n,p,t,b,s,s,w,w,p,w,o,p,u,v,d e,s,f,n,f,n,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,y,u p,x,s,w,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,v,g e,x,y,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,n,m p,f,y,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,v,g e,f,s,g,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,s,y,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,m e,x,s,w,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,k,s,g e,b,s,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,n,g e,f,f,g,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,s,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,g e,b,s,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,s,m e,b,s,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,g e,b,y,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,m e,f,s,w,t,l,f,w,n,w,t,b,s,s,w,w,p,w,o,p,u,v,d e,x,y,y,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,s,m e,f,s,w,t,a,f,w,n,p,t,b,s,s,w,w,p,w,o,p,n,v,d p,x,y,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,v,u e,f,f,w,t,l,f,w,n,w,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,y,y,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,s,g p,x,s,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,v,g e,b,s,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,y,n,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,y,p e,b,y,y,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,m e,s,f,n,f,n,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,v,u e,f,y,n,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,y,p e,x,y,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,f,g,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,k,s,g e,f,f,w,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,n,a,g e,x,y,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,n,m e,b,s,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,g e,b,y,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,y,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,g e,x,s,n,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,n,a,g e,x,y,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,g e,s,f,n,f,n,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,v,u e,x,s,w,t,a,f,w,n,w,t,b,s,s,w,w,p,w,o,p,u,v,d e,x,y,n,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,s,g e,b,y,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,y,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,g e,b,y,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,m e,b,s,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,s,g e,b,s,y,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,s,m e,b,y,y,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,f,n,f,n,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,y,u e,f,y,n,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,y,g e,x,y,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,s,g e,f,y,y,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,y,p e,b,s,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,g e,b,s,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,m e,x,y,n,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,y,g e,b,s,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,g e,x,f,g,f,n,f,c,n,g,e,e,s,s,w,w,p,w,o,p,n,y,u e,b,s,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,s,g e,x,f,y,t,l,f,w,n,n,t,b,s,s,w,w,p,w,o,p,u,v,d e,b,y,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,g e,f,y,y,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,s,g e,b,y,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,m e,b,y,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,m e,b,y,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,g e,x,y,y,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,n,m e,b,s,y,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,n,g p,x,y,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,v,u e,s,f,n,f,n,f,c,n,g,e,e,s,s,w,w,p,w,o,p,n,y,u e,f,f,n,f,n,f,c,n,g,e,e,s,s,w,w,p,w,o,p,k,v,u e,x,s,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,m e,f,y,n,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,s,p p,x,y,w,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,s,g e,b,s,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,m e,f,f,g,f,n,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,v,u e,b,y,y,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,y,n,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,y,p e,x,f,w,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,k,s,g e,x,s,w,t,l,f,w,n,w,t,b,s,s,w,w,p,w,o,p,n,v,d e,b,s,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,m e,f,s,y,t,a,f,w,n,w,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,s,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,m e,f,f,g,f,n,f,c,n,g,e,e,s,s,w,w,p,w,o,p,n,y,u e,b,s,y,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,g e,x,s,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,n,m e,x,y,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,s,m e,f,s,w,t,a,f,w,n,n,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,y,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,g e,b,s,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,g e,x,s,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,f,w,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,k,s,g e,f,y,n,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,y,p p,x,s,w,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,v,u e,b,s,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,n,g e,b,s,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,m e,b,y,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,n,g e,b,y,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,s,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,g e,b,s,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,f,y,t,a,f,w,n,n,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,f,g,f,n,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,y,u e,f,y,y,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,s,g e,b,s,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,s,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,s,g e,x,y,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,g e,x,y,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,g e,s,f,g,f,n,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,v,u e,x,s,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,n,m p,x,s,w,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,s,g e,x,y,y,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,s,g e,f,f,w,t,a,f,w,n,p,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,y,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,m e,b,y,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,g e,x,s,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,s,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,g p,x,y,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,v,u e,b,s,y,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,f,g,f,n,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,y,u p,x,y,w,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,s,u e,x,y,y,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,y,p e,f,f,n,f,n,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,v,u e,b,s,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,f,w,t,l,f,w,n,w,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,y,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,g e,b,y,y,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,s,g e,x,y,y,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,s,g e,f,y,y,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,s,p e,f,y,y,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,y,p e,x,s,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,g e,x,s,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,n,m p,x,s,w,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,v,u e,f,f,w,t,a,f,w,n,p,t,b,s,s,w,w,p,w,o,p,u,v,d e,x,s,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,g e,x,s,w,t,l,f,w,n,p,t,b,s,s,w,w,p,w,o,p,u,v,d e,x,y,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,m e,f,y,y,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,y,p e,x,s,n,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,k,s,g e,f,y,y,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,y,g p,x,s,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,s,g e,s,f,n,f,n,f,c,n,g,e,e,s,s,w,w,p,w,o,p,n,v,u e,b,y,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,m e,b,s,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,s,g e,b,y,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,m e,f,f,n,f,n,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,v,u e,x,s,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,m e,b,y,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,g e,b,y,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,n,m e,f,y,n,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,s,g p,x,y,w,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,v,g e,x,s,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,y,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,s,m e,f,f,w,t,l,f,w,n,w,t,b,s,s,w,w,p,w,o,p,u,v,d e,f,f,g,f,n,f,c,n,g,e,e,s,s,w,w,p,w,o,p,k,v,u e,f,s,g,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,k,a,g e,x,y,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,m e,b,s,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,s,m p,f,y,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,s,u e,x,s,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,m p,f,s,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,v,u e,x,y,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,s,g e,x,y,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,m e,f,y,y,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,s,p e,x,y,n,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,s,p e,f,y,n,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,y,g e,x,y,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,n,m e,f,f,n,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,k,s,g e,x,s,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,m p,x,y,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,s,g e,b,y,y,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,n,m e,s,f,n,f,n,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,v,u e,x,s,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,m e,b,y,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,m e,f,y,n,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,s,g e,b,y,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,s,m e,b,y,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,s,g e,x,y,n,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,y,p e,f,f,g,f,n,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,y,u e,x,f,g,f,n,f,c,n,g,e,e,s,s,w,w,p,w,o,p,k,y,u e,b,y,y,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,g e,x,s,y,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,m e,b,y,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,s,g e,x,s,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,s,m e,b,s,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,n,m e,x,s,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,m e,x,f,g,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,k,s,g e,f,s,y,t,a,f,w,n,p,t,b,s,s,w,w,p,w,o,p,n,v,d p,x,y,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,s,g e,x,f,w,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,k,a,g e,b,y,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,g e,x,s,y,t,l,f,w,n,w,t,b,s,s,w,w,p,w,o,p,n,v,d e,b,y,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,g e,x,y,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,s,g e,x,f,n,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,n,y,d e,b,y,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,s,m e,x,s,y,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,n,m e,f,y,n,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,y,g e,x,f,w,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,n,s,g e,x,s,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,g p,x,y,w,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,v,g e,x,y,y,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,g e,x,f,w,t,a,f,w,n,p,t,b,s,s,w,w,p,w,o,p,n,v,d e,b,s,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,n,g p,x,y,w,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,v,u e,x,s,y,t,a,f,w,n,w,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,y,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,f,w,t,l,f,w,n,n,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,s,w,t,l,f,w,n,w,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,y,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,s,m e,f,f,y,t,a,f,w,n,w,t,b,s,s,w,w,p,w,o,p,u,v,d e,x,s,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,g e,b,y,y,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,m e,x,y,n,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,s,p e,b,y,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,s,y,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,s,m p,x,y,n,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,v,u e,b,s,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,g e,b,y,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,g p,x,y,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,v,u e,b,s,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,m e,b,y,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,n,m e,b,y,y,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,g e,x,y,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,f,n,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,k,y,d e,x,y,n,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,y,g e,b,s,y,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,s,g e,x,f,g,f,n,f,c,n,g,e,e,s,s,w,w,p,w,o,p,n,v,u e,x,y,n,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,y,g e,x,s,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,s,g e,b,y,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,s,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,s,m e,f,f,y,t,a,f,w,n,p,t,b,s,s,w,w,p,w,o,p,n,v,d e,b,y,y,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,g e,x,f,n,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,n,a,g e,x,f,y,t,l,f,w,n,n,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,s,y,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,n,m e,f,s,g,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,k,s,g e,x,f,n,f,n,f,c,n,g,e,e,s,s,w,w,p,w,o,p,n,y,u e,f,s,g,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,n,a,g e,f,y,n,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,s,p e,b,y,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,s,g e,b,s,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,m e,x,y,y,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,s,p e,s,f,g,f,n,f,c,n,g,e,e,s,s,w,w,p,w,o,p,n,v,u e,f,y,n,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,y,p p,x,y,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,s,u e,x,y,y,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,y,p e,x,y,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,g e,x,f,n,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,n,s,g e,x,f,n,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,k,a,g e,f,s,n,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,k,a,g e,f,y,n,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,s,p e,x,s,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,g e,f,f,n,f,n,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,v,u e,x,y,y,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,s,p e,x,f,y,t,a,f,w,n,p,t,b,s,s,w,w,p,w,o,p,u,v,d e,b,y,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,f,g,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,k,s,g e,x,y,y,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,s,g e,f,y,n,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,y,g e,x,s,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,m e,s,f,n,f,n,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,y,u e,x,s,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,m e,b,s,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,g e,s,f,n,f,n,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,y,u e,b,y,y,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,n,m e,x,y,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,g e,b,y,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,s,g p,x,y,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,s,u e,x,s,w,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,n,s,g e,x,y,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,m e,b,s,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,f,n,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,n,y,d p,x,s,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,s,u e,x,y,n,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,y,p e,x,s,n,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,k,a,g e,b,y,y,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,s,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,n,m e,b,s,y,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,s,m e,x,s,y,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,m e,b,y,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,f,g,f,n,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,v,u e,f,y,n,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,s,g e,x,f,g,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,n,a,g e,x,s,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,m e,x,y,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,m e,x,f,g,f,n,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,v,u p,x,s,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,s,u e,b,y,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,n,g e,b,y,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,m p,x,y,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,v,u e,b,s,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,m e,x,s,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,s,m e,x,y,y,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,m e,b,y,y,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,s,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,m e,x,s,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,s,g e,x,y,n,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,y,p e,x,s,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,m e,x,s,n,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,k,s,g e,x,y,n,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,s,p e,x,y,y,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,y,g p,x,y,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,v,g e,b,y,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,f,w,t,l,f,w,n,p,t,b,s,s,w,w,p,w,o,p,u,v,d p,x,s,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,s,u e,x,y,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,g e,f,f,g,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,n,a,g e,x,y,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,g e,b,y,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,m p,x,y,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,s,u e,f,y,n,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,s,g e,x,s,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,n,m e,x,s,w,t,a,f,w,n,n,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,y,n,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,y,p e,b,s,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,m e,x,s,w,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,k,a,g e,f,f,g,f,n,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,v,u e,x,y,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,g e,x,y,y,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,y,g e,b,s,y,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,g e,b,s,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,g e,f,s,w,t,l,f,w,n,n,t,b,s,s,w,w,p,w,o,p,n,v,d e,b,s,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,f,y,t,a,f,w,n,n,t,b,s,s,w,w,p,w,o,p,u,v,d e,x,y,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,n,m e,b,y,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,m e,x,y,n,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,y,p e,x,y,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,m e,x,y,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,s,m e,x,y,y,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,y,p e,x,y,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,s,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,y,n,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,s,g e,x,s,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,n,g e,f,y,n,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,s,g e,b,s,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,m e,x,f,n,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,n,y,d e,x,y,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,s,m e,b,s,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,g e,b,s,y,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,f,y,t,l,f,w,n,p,t,b,s,s,w,w,p,w,o,p,n,v,d e,b,s,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,n,m e,x,s,g,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,k,a,g e,b,s,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,g e,b,s,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,m e,f,y,y,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,y,p e,f,y,n,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,y,p e,x,s,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,s,m e,f,y,y,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,s,g e,b,s,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,s,g e,x,y,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,n,m e,x,f,n,f,n,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,v,u e,f,y,n,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,y,g e,x,s,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,s,y,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,g e,b,y,y,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,g e,f,y,y,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,s,p e,x,y,y,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,y,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,m e,f,f,w,t,a,f,w,n,n,t,b,s,s,w,w,p,w,o,p,u,v,d e,s,f,g,f,n,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,y,u e,f,s,y,t,l,f,w,n,n,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,f,g,f,n,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,y,u e,x,f,n,f,n,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,y,u e,b,y,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,s,w,t,a,f,w,n,p,t,b,s,s,w,w,p,w,o,p,n,v,d e,b,y,y,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,m e,b,y,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,m e,b,y,y,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,s,g e,f,s,w,t,l,f,w,n,p,t,b,s,s,w,w,p,w,o,p,u,v,d e,f,f,g,f,n,f,c,n,g,e,e,s,s,w,w,p,w,o,p,k,y,u e,f,s,w,t,a,f,w,n,w,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,y,y,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,y,g e,x,y,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,m e,s,f,n,f,n,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,y,u e,x,y,n,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,s,p e,x,y,n,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,s,p e,f,f,y,t,a,f,w,n,n,t,b,s,s,w,w,p,w,o,p,u,v,d p,f,s,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,s,g p,x,s,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,v,u e,f,y,n,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,s,p e,x,y,y,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,s,g e,b,s,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,m e,f,f,w,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,n,a,g e,f,y,n,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,s,g e,x,y,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,s,g e,b,s,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,s,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,n,g e,b,y,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,s,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,m e,b,s,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,m e,b,y,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,g p,x,s,n,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,v,g e,x,s,g,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,n,s,g e,f,s,n,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,n,a,g e,x,f,w,t,a,f,w,n,n,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,f,g,f,n,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,v,u e,f,f,n,f,n,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,y,u e,b,y,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,g e,x,f,w,t,a,f,w,n,n,t,b,s,s,w,w,p,w,o,p,u,v,d e,s,f,g,f,n,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,v,u e,x,f,n,f,n,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,v,u e,x,f,w,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,n,a,g e,x,y,n,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,y,p e,b,s,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,y,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,g e,x,y,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,s,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,m e,b,s,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,g e,f,y,y,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,y,p p,x,s,n,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,s,u e,f,f,g,f,n,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,y,u e,b,s,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,g e,f,y,n,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,s,p e,x,s,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,s,m e,x,f,n,f,n,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,y,u e,f,y,y,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,y,p e,x,y,n,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,y,p e,x,s,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,g p,x,y,w,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,s,g e,f,y,n,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,y,p p,f,s,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,s,g e,x,f,w,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,k,s,g e,b,y,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,m e,s,f,n,f,n,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,v,u e,x,y,y,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,m e,f,s,w,t,a,f,w,n,p,t,b,s,s,w,w,p,w,o,p,u,v,d e,x,s,y,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,m e,f,f,g,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,k,s,g p,x,y,w,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,s,g e,x,y,y,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,s,g e,f,f,n,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,k,a,g e,x,s,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,m e,b,y,y,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,m e,f,f,g,f,n,f,c,n,g,e,e,s,s,w,w,p,w,o,p,n,v,u e,x,f,y,t,l,f,w,n,p,t,b,s,s,w,w,p,w,o,p,u,v,d e,x,s,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,n,m e,f,f,n,f,n,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,y,u e,x,f,g,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,n,s,g e,x,y,y,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,s,p e,f,s,w,t,l,f,w,n,p,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,s,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,g e,f,y,y,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,y,p p,x,y,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,v,u e,x,f,w,t,l,f,w,n,w,t,b,s,s,w,w,p,w,o,p,u,v,d e,x,s,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,y,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,n,m e,b,s,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,g e,x,s,y,t,a,f,w,n,w,t,b,s,s,w,w,p,w,o,p,u,v,d e,x,s,y,t,a,f,w,n,n,t,b,s,s,w,w,p,w,o,p,u,v,d e,x,f,w,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,k,s,g e,b,s,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,m p,x,y,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,v,g e,x,y,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,n,g e,f,s,g,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,k,s,g p,x,s,n,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,s,g e,b,y,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,s,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,m e,f,f,y,t,l,f,w,n,n,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,s,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,g e,b,y,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,y,n,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,y,g e,x,s,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,g e,x,f,n,f,n,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,v,u e,x,s,y,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,s,g e,x,y,y,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,y,g p,x,s,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,s,g e,x,s,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,n,m e,x,s,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,m e,x,y,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,y,y,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,y,g e,f,y,y,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,s,g e,x,y,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,s,m e,s,f,g,f,n,f,c,n,g,e,e,s,s,w,w,p,w,o,p,k,v,u e,f,f,n,f,n,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,y,u e,s,f,g,f,n,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,v,u e,x,y,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,m p,x,s,w,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,s,u e,x,s,g,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,k,s,g e,x,y,y,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,s,g p,x,y,w,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,s,g e,x,s,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,m p,x,s,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,v,u e,b,s,y,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,m e,b,y,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,s,m p,x,y,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,s,g p,x,s,n,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,s,u e,x,s,g,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,n,a,g e,x,y,n,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,y,g e,f,f,w,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,n,a,g e,f,y,n,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,s,p e,b,y,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,m e,b,s,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,s,g,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,n,s,g e,f,y,n,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,y,g e,x,s,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,m e,f,f,g,f,n,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,v,u e,f,s,n,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,n,a,g e,x,f,g,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,n,s,g e,f,s,w,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,k,a,g p,x,s,w,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,s,u e,x,y,y,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,s,g e,b,s,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,s,g e,f,f,g,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,k,a,g e,b,y,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,s,g e,b,s,y,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,n,m e,s,f,g,f,n,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,y,u e,f,y,y,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,s,g e,b,s,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,f,w,t,l,f,w,n,n,t,b,s,s,w,w,p,w,o,p,u,v,d e,f,y,y,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,s,p e,f,f,g,f,n,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,y,u e,x,s,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,s,m e,f,f,y,t,l,f,w,n,w,t,b,s,s,w,w,p,w,o,p,u,v,d e,s,f,g,f,n,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,y,u e,b,y,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,g e,b,s,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,g e,f,f,n,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,n,s,g e,b,y,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,f,n,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,k,v,d e,x,y,n,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,s,g e,x,y,n,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,s,g e,b,y,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,m e,f,y,y,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,s,g e,x,y,y,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,s,n,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,k,s,g e,x,y,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,s,m e,b,y,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,y,n,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,y,g e,f,y,n,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,s,p e,f,y,n,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,y,g e,f,y,y,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,s,p e,x,s,y,t,l,f,w,n,n,t,b,s,s,w,w,p,w,o,p,u,v,d e,b,y,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,s,m e,b,s,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,y,y,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,g e,f,f,w,t,l,f,w,n,p,t,b,s,s,w,w,p,w,o,p,u,v,d e,x,s,y,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,g e,b,s,y,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,n,m e,f,y,y,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,y,g p,x,y,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,s,g p,x,y,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,v,u e,x,s,y,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,g e,f,f,w,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,n,s,g e,b,s,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,y,y,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,y,p e,f,f,g,f,n,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,y,u e,b,s,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,g e,x,s,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,m p,x,y,n,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,s,g p,x,s,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,s,g e,b,s,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,g e,b,s,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,n,m e,f,y,n,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,s,g e,x,y,y,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,y,g e,f,y,y,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,y,p e,x,y,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,s,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,g e,f,f,n,f,n,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,v,u e,f,f,n,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,k,a,g e,x,f,y,t,l,f,w,n,w,t,b,s,s,w,w,p,w,o,p,u,v,d e,f,y,y,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,s,p e,f,f,n,f,n,f,c,n,g,e,e,s,s,w,w,p,w,o,p,k,y,u e,f,f,g,f,n,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,v,u e,x,y,n,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,y,g e,x,y,y,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,y,p e,b,s,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,s,m e,x,s,w,t,l,f,w,n,n,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,y,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,n,m e,x,f,y,t,a,f,w,n,w,t,b,s,s,w,w,p,w,o,p,u,v,d e,b,s,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,f,n,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,n,v,d e,x,y,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,m e,f,f,g,f,n,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,v,u e,b,y,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,s,m e,x,y,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,s,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,g e,b,s,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,g e,b,y,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,g e,x,y,n,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,s,p e,f,s,g,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,n,a,g p,x,y,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,s,g e,b,y,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,s,g e,b,s,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,m p,x,y,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,v,g p,x,s,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,v,u e,f,s,n,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,n,a,g p,x,s,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,s,g e,f,f,g,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,n,a,g e,x,y,y,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,s,p e,b,y,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,m e,f,y,y,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,s,p e,f,y,y,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,y,p e,b,y,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,m e,s,f,n,f,n,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,y,u e,x,s,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,m e,b,y,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,m e,f,y,y,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,s,p e,f,s,n,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,n,a,g e,x,s,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,m e,b,y,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,n,g e,b,y,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,g e,b,y,y,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,s,m e,b,s,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,s,m e,x,y,y,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,s,p e,x,y,n,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,s,g e,s,f,n,f,n,f,c,n,g,e,e,s,s,w,w,p,w,o,p,k,v,u e,f,y,n,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,s,g e,x,s,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,g e,f,s,y,t,l,f,w,n,w,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,s,n,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,n,a,g e,f,y,y,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,s,g p,x,y,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,v,g e,x,s,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,f,w,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,n,s,g e,b,s,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,s,m e,x,y,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,m e,f,y,y,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,y,g e,x,f,n,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,n,s,g p,x,s,w,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,s,g p,x,y,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,s,u e,x,y,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,g e,b,y,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,g e,x,f,w,t,a,f,w,n,w,t,b,s,s,w,w,p,w,o,p,n,v,d p,x,y,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,s,u e,x,s,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,s,g e,x,f,g,f,n,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,v,u e,x,f,n,f,n,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,v,u e,b,s,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,m e,x,y,n,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,s,g e,b,y,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,m e,f,y,y,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,s,p e,x,y,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,n,g e,b,y,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,g e,b,y,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,m p,x,s,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,v,u e,f,s,y,t,a,f,w,n,n,t,b,s,s,w,w,p,w,o,p,u,v,d e,x,y,n,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,s,p e,b,s,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,g e,f,s,w,t,a,f,w,n,n,t,b,s,s,w,w,p,w,o,p,u,v,d e,b,y,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,g e,b,y,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,m e,b,s,y,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,g e,f,y,y,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,y,g e,x,s,w,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,n,a,g e,b,y,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,n,m e,x,y,n,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,y,p e,b,s,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,n,g e,f,y,n,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,y,g e,x,s,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,f,n,f,n,f,c,n,g,e,e,s,s,w,w,p,w,o,p,n,v,u e,x,y,n,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,s,p e,f,f,g,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,k,a,g e,x,s,w,t,l,f,w,n,p,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,f,n,f,n,f,c,n,g,e,e,s,s,w,w,p,w,o,p,n,y,u e,b,y,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,m e,b,s,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,s,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,n,g e,b,s,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,s,m e,x,y,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,s,y,t,a,f,w,n,p,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,f,g,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,k,a,g e,x,y,y,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,s,g p,x,y,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,s,u e,x,y,n,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,y,g e,x,s,y,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,n,g e,b,y,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,n,m e,x,y,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,m e,s,f,n,f,n,f,c,n,g,e,e,s,s,w,w,p,w,o,p,k,y,u e,b,y,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,m e,x,s,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,m e,x,s,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,g p,x,s,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,v,g e,x,f,n,f,n,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,v,u e,x,y,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,n,g p,x,y,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,s,g e,x,y,y,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,y,p e,b,y,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,s,g e,f,y,n,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,y,p e,x,y,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,s,y,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,n,g p,x,y,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,v,g p,x,y,n,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,s,u e,b,y,y,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,s,w,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,k,s,g p,x,s,w,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,v,g e,x,y,n,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,s,p e,b,s,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,y,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,n,g p,x,s,n,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,v,u e,b,y,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,g e,b,y,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,g e,f,y,y,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,s,g e,b,y,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,g e,x,y,y,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,y,g e,b,s,y,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,s,m e,x,s,y,t,l,f,w,n,p,t,b,s,s,w,w,p,w,o,p,n,v,d e,b,s,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,m e,b,s,y,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,m p,x,y,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,v,u p,x,y,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,v,g p,x,s,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,v,u e,x,s,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,m e,x,y,n,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,y,g e,x,y,y,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,y,g e,x,s,w,t,a,f,w,n,w,t,b,s,s,w,w,p,w,o,p,n,v,d e,b,y,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,g e,b,s,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,n,m e,x,f,g,f,n,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,v,u e,b,s,y,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,m e,x,s,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,g e,x,y,n,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,s,p e,x,y,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,m e,f,f,w,t,l,f,w,n,n,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,f,w,t,a,f,w,n,w,t,b,s,s,w,w,p,w,o,p,u,v,d e,x,s,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,m e,f,s,y,t,l,f,w,n,p,t,b,s,s,w,w,p,w,o,p,u,v,d e,s,f,g,f,n,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,v,u e,f,f,y,t,a,f,w,n,w,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,y,n,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,y,g e,x,y,y,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,s,g e,x,y,y,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,y,p p,x,s,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,v,g e,x,s,y,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,s,m p,x,y,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,s,u e,x,y,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,g e,x,y,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,g e,f,s,y,t,a,f,w,n,w,t,b,s,s,w,w,p,w,o,p,u,v,d p,x,y,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,v,g e,b,s,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,s,g e,s,f,g,f,n,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,y,u e,x,s,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,f,g,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,n,s,g e,x,y,y,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,s,m e,b,y,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,g e,b,s,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,m e,x,s,w,t,l,f,w,n,w,t,b,s,s,w,w,p,w,o,p,u,v,d e,b,s,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,s,g e,f,y,n,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,s,g e,s,f,g,f,n,f,c,n,g,e,e,s,s,w,w,p,w,o,p,n,y,u e,x,f,w,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,n,a,g e,s,f,n,f,n,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,v,u e,f,y,n,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,s,p e,f,s,y,t,l,f,w,n,n,t,b,s,s,w,w,p,w,o,p,u,v,d e,b,s,y,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,s,g e,b,s,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,m p,x,s,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,v,g e,f,y,n,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,y,p e,x,s,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,g e,f,y,y,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,s,g e,x,y,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,y,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,m e,x,y,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,g e,f,f,n,f,n,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,v,u e,f,y,y,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,y,p e,x,f,g,f,n,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,y,u e,x,s,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,g e,f,y,n,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,y,p e,x,s,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,y,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,s,m e,x,f,n,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,k,v,d e,x,s,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,s,m e,x,y,y,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,s,p e,x,y,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,m e,x,s,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,g e,f,y,y,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,y,g e,b,s,y,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,n,g e,f,f,w,t,a,f,w,n,w,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,s,g,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,n,s,g e,x,y,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,y,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,g e,f,y,y,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,s,g e,x,s,w,t,a,f,w,n,p,t,b,s,s,w,w,p,w,o,p,u,v,d e,x,s,y,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,s,g e,f,y,y,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,y,g e,x,y,y,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,y,p e,x,s,y,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,f,n,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,n,y,d e,f,y,y,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,y,g e,x,s,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,g e,b,s,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,m e,x,s,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,s,m e,x,y,n,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,s,g e,b,y,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,s,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,y,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,m e,x,s,y,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,g e,f,y,y,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,y,p e,x,f,w,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,n,a,g e,x,s,n,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,k,s,g e,x,s,w,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,n,s,g e,x,s,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,n,m e,f,f,w,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,k,s,g p,f,s,n,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,s,g e,x,f,g,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,n,s,g p,f,y,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,v,u p,x,s,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,v,g e,b,s,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,f,g,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,k,a,g e,x,s,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,g e,f,f,g,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,k,a,g e,x,s,g,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,k,s,g e,x,s,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,s,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,s,m e,x,y,g,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,n,y,d e,f,f,n,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,n,a,g e,x,s,w,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,k,s,g e,f,f,n,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,k,a,g e,x,s,n,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,n,a,g e,x,y,y,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,s,y,t,l,f,w,n,w,t,b,s,s,w,w,p,w,o,p,u,v,d e,f,f,w,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,n,s,g e,x,s,n,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,n,a,g e,x,s,g,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,k,a,g p,x,y,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,s,u e,x,f,g,f,n,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,y,u e,b,s,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,n,m e,x,s,g,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,k,a,g e,f,f,g,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,n,s,g p,f,s,n,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,v,g e,x,s,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,s,g e,x,f,n,f,n,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,y,u e,f,s,w,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,k,s,g e,x,y,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,f,n,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,k,s,g e,f,s,g,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,k,a,g e,x,y,e,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,n,y,d e,b,y,y,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,f,w,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,k,s,g p,x,s,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,s,g e,x,f,g,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,n,s,g e,f,f,g,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,n,v,d e,f,f,n,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,n,a,g e,f,f,w,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,k,s,g e,b,y,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,g e,f,f,n,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,k,a,g p,f,y,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,v,u p,x,y,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,s,u e,b,s,y,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,g e,f,s,g,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,n,a,g e,x,f,g,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,n,a,g e,f,f,n,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,n,s,g e,b,s,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,m p,x,s,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,v,u e,x,y,n,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,k,v,d e,f,f,w,t,l,f,w,n,n,t,b,s,s,w,w,p,w,o,p,u,v,d e,x,y,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,m e,x,f,n,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,k,a,g e,f,f,w,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,k,a,g e,x,f,n,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,k,v,d e,x,f,n,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,n,y,d e,f,s,g,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,k,s,g e,f,s,g,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,k,s,g p,f,s,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,s,g e,x,f,n,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,k,y,d e,x,s,n,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,k,s,g e,x,f,w,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,k,s,g e,f,f,n,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,n,s,g e,x,f,n,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,k,v,d e,x,f,g,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,k,s,g e,f,f,n,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,k,y,d e,x,s,g,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,k,s,g e,b,y,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,f,n,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,k,y,d e,x,y,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,s,g e,f,f,g,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,k,a,g e,f,f,n,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,n,y,d e,x,s,y,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,s,m e,f,f,g,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,k,s,g e,x,f,n,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,n,s,g p,x,s,w,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,s,u e,x,f,w,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,n,s,g e,f,f,w,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,k,a,g e,x,s,w,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,n,a,g e,x,s,g,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,k,a,g e,x,y,y,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,s,y,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,s,g,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,k,a,g e,x,s,n,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,n,s,g e,f,f,n,f,n,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,v,u e,f,s,w,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,k,s,g e,f,s,w,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,k,a,g e,x,y,y,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,s,m e,f,s,w,t,a,f,w,n,w,t,b,s,s,w,w,p,w,o,p,u,v,d e,b,s,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,n,m p,f,y,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,v,u e,x,f,g,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,k,y,d e,f,y,n,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,y,g e,f,s,n,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,n,s,g p,x,s,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,v,g e,x,y,n,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,y,g e,x,s,g,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,n,a,g e,x,s,w,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,n,a,g e,f,f,w,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,n,s,g e,x,f,n,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,s,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,s,g e,x,y,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,m e,x,s,w,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,k,s,g e,f,y,y,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,s,p e,f,s,n,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,k,s,g e,f,f,g,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,k,s,g e,f,f,y,t,a,f,w,n,p,t,b,s,s,w,w,p,w,o,p,u,v,d e,f,y,n,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,s,g e,x,f,n,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,n,y,d p,f,s,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,s,g e,x,f,n,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,k,v,d e,f,f,n,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,n,a,g e,b,s,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,m e,b,y,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,y,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,m p,f,y,w,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,v,u p,f,y,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,s,g e,x,f,n,f,n,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,v,u e,f,s,y,t,l,f,w,n,w,t,b,s,s,w,w,p,w,o,p,u,v,d e,x,y,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,s,w,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,k,a,g e,x,f,g,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,n,y,d p,x,y,n,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,v,g e,x,f,g,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,n,s,g e,f,f,n,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,n,s,g e,x,s,w,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,n,s,g e,f,f,w,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,k,a,g e,x,y,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,m e,f,f,y,t,a,f,w,n,n,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,f,g,f,n,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,y,u p,x,s,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,s,u e,x,y,y,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,y,p e,f,y,n,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,s,p e,x,f,w,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,k,a,g e,x,y,n,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,n,v,d e,x,s,g,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,n,a,g e,x,s,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,g e,x,f,g,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,n,s,g p,f,y,n,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,s,u e,x,f,n,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,k,v,d e,x,f,g,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,k,a,g e,x,f,e,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,k,v,d e,x,f,n,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,k,y,d e,x,f,g,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,n,a,g e,x,y,y,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,s,p e,x,f,n,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,k,s,g e,b,s,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,g e,x,f,w,t,l,f,w,n,p,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,s,g,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,n,s,g e,x,y,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,f,n,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,n,s,g e,f,s,w,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,n,a,g e,x,s,y,t,l,f,w,n,n,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,s,g,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,n,s,g e,x,f,g,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,n,s,g p,f,y,w,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,s,u e,f,f,y,t,l,f,w,n,p,t,b,s,s,w,w,p,w,o,p,u,v,d e,x,y,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,g e,f,f,w,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,n,a,g e,x,f,n,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,k,v,d e,x,y,n,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,s,g e,x,s,w,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,n,a,g p,f,y,w,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,v,g e,x,s,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,s,g e,x,f,g,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,k,y,d e,f,y,y,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,s,p e,f,s,g,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,k,a,g e,f,f,n,f,n,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,y,u p,f,y,w,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,v,g e,f,f,g,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,n,s,g e,x,y,n,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,s,p e,f,f,w,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,k,a,g p,f,y,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,v,u e,b,s,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,m e,f,f,g,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,k,s,g e,b,s,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,g e,f,f,g,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,n,s,g e,b,y,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,n,m e,x,y,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,m p,f,y,n,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,v,g e,x,y,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,g e,s,f,n,f,n,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,y,u e,x,y,n,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,y,g e,f,f,g,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,n,a,g e,f,f,y,t,l,f,w,n,n,t,b,s,s,w,w,p,w,o,p,u,v,d e,x,s,g,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,n,a,g p,f,y,n,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,v,u e,x,f,g,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,k,a,g e,x,s,g,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,k,a,g e,x,f,g,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,k,s,g p,x,y,n,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,s,g e,x,f,n,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,n,a,g e,f,s,w,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,n,s,g e,x,f,g,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,n,s,g p,x,y,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,s,g e,f,f,n,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,n,a,g e,f,s,w,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,k,a,g p,x,y,w,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,v,u e,f,f,g,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,n,a,g e,b,y,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,s,n,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,n,a,g e,f,f,n,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,k,a,g p,f,s,w,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,s,g e,x,y,n,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,s,g e,f,f,w,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,k,a,g e,f,y,n,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,s,g e,f,f,g,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,k,s,g e,f,f,g,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,n,s,g e,f,s,g,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,n,s,g e,f,f,n,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,k,s,g e,x,s,g,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,n,s,g e,x,f,w,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,k,s,g e,f,f,w,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,k,a,g e,x,s,n,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,n,s,g e,x,f,n,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,k,v,d e,f,s,y,t,a,f,w,n,p,t,b,s,s,w,w,p,w,o,p,u,v,d e,x,f,w,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,k,s,g e,f,s,w,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,k,a,g e,b,s,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,f,w,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,n,a,g e,x,f,g,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,k,a,g p,f,s,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,v,u e,x,f,g,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,k,a,g p,x,s,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,s,g e,f,s,w,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,n,s,g e,x,y,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,f,n,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,k,s,g e,x,f,n,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,n,y,d e,b,y,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,g e,f,f,w,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,s,n,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,n,a,g e,f,f,w,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,f,n,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,n,v,d e,f,f,w,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,n,s,g e,x,s,w,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,k,a,g e,x,s,n,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,n,a,g e,x,f,w,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,n,s,g e,f,s,g,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,k,s,g e,x,f,g,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,f,g,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,k,a,g e,f,s,n,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,k,a,g e,f,s,w,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,k,a,g e,f,y,n,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,y,p p,x,y,w,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,v,g e,f,s,g,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,k,a,g p,x,y,w,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,v,g e,b,y,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,s,m e,x,s,g,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,k,s,g e,f,f,g,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,k,a,g e,f,f,w,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,n,s,g e,f,s,g,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,k,s,g e,b,y,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,f,g,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,k,s,g e,x,f,e,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,y,y,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,s,p e,x,s,w,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,k,s,g e,b,s,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,n,m p,x,s,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,v,g e,x,f,n,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,k,y,d e,f,s,n,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,k,s,g e,b,s,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,n,m e,x,s,g,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,k,s,g e,x,f,n,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,k,v,d e,f,f,w,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,n,a,g e,x,f,n,f,n,f,c,n,g,e,e,s,s,w,w,p,w,o,p,k,v,u e,x,f,g,f,n,f,c,n,g,e,e,s,s,w,w,p,w,o,p,k,v,u e,x,f,g,f,n,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,y,u e,b,y,y,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,s,m e,f,f,n,f,n,f,c,n,g,e,e,s,s,w,w,p,w,o,p,n,v,u e,x,f,w,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,n,a,g e,f,y,n,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,s,p e,x,y,n,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,y,p e,x,y,y,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,k,y,g e,f,f,g,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,n,a,g e,x,y,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,y,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,g e,f,s,w,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,n,a,g e,f,s,g,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,k,a,g p,f,s,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,v,u e,x,y,y,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,s,g e,x,f,n,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,n,s,g e,x,f,w,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,k,s,g e,x,s,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,s,m e,x,f,e,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,n,v,d e,f,y,n,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,s,p e,b,s,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,g p,x,s,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,s,g e,x,f,g,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,k,s,g e,b,y,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,n,m e,x,s,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,g e,b,y,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,m e,x,y,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,s,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,n,g e,b,s,w,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,g e,f,s,n,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,k,s,g p,f,s,w,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,s,g e,f,s,n,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,n,a,g e,f,f,n,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,k,a,g p,f,y,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,s,u e,f,s,w,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,k,a,g e,x,f,w,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,n,s,g e,x,s,n,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,k,a,g e,f,s,n,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,k,a,g e,f,y,y,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,y,g e,x,f,g,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,k,a,g e,x,f,n,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,k,a,g p,f,s,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,v,g e,x,s,w,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,n,a,g e,f,f,n,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,k,s,g e,f,f,w,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,n,a,g e,f,f,w,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,n,s,g e,x,y,y,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,s,g e,x,s,g,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,n,s,g e,x,f,g,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,n,a,g e,f,f,n,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,k,s,g e,f,s,n,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,k,a,g e,x,f,w,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,k,s,g e,x,y,e,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,n,v,d e,x,f,n,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,k,a,g p,x,s,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,v,g e,x,y,n,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,k,y,d e,x,f,n,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,n,s,g p,f,y,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,s,g e,f,f,g,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,k,a,g e,x,f,w,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,n,a,g e,f,s,n,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,k,a,g e,f,f,g,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,k,a,g e,f,s,g,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,k,a,g e,f,f,g,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,n,s,g e,x,s,g,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,n,s,g e,x,s,n,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,k,s,g p,f,s,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,v,u e,x,s,g,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,n,a,g p,x,s,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,s,g p,f,s,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,s,u e,f,s,n,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,n,s,g e,x,f,g,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,k,a,g e,f,s,g,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,s,g,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,k,a,g e,f,f,g,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,k,a,g e,f,f,g,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,n,a,g e,x,y,g,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,n,y,d e,x,f,n,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,s,w,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,n,a,g p,f,y,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,v,g p,f,y,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,s,g e,x,s,w,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,n,a,g p,f,s,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,s,g e,f,f,n,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,k,s,g e,f,s,w,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,n,a,g p,f,s,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,v,g p,f,y,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,v,g p,f,y,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,v,g p,f,s,w,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,s,g e,x,s,w,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,k,a,g e,x,f,n,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,n,v,d e,f,s,w,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,n,a,g e,f,f,g,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,k,a,g p,f,y,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,v,u e,x,s,w,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,n,s,g e,x,y,e,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,n,y,d e,f,s,g,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,k,s,g e,x,s,w,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,n,s,g p,f,s,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,s,g e,f,f,n,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,n,a,g e,x,f,w,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,k,s,g p,f,s,w,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,s,u e,x,f,n,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,n,a,g e,f,f,w,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,n,s,g e,x,s,w,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,k,s,g e,f,s,w,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,n,s,g e,b,y,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,s,g,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,f,w,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,k,s,g e,x,s,n,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,n,s,g e,x,f,n,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,k,a,g e,f,f,g,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,k,a,g p,x,y,n,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,s,u e,f,s,g,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,k,s,g e,x,f,n,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,k,y,d e,f,s,w,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,k,a,g e,x,f,n,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,k,v,d e,x,f,g,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,n,a,g e,x,f,w,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,k,a,g p,f,s,w,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,v,g p,f,s,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,v,g e,x,s,g,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,n,a,g e,x,f,n,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,n,v,d e,x,s,g,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,k,s,g e,x,y,y,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,s,p e,f,s,w,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,s,w,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,f,g,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,k,a,g e,f,s,w,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,n,s,g e,x,f,n,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,n,y,d e,f,s,g,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,n,a,g e,f,s,g,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,n,s,g e,f,f,n,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,n,s,g e,f,s,w,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,n,s,g e,f,s,w,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,n,a,g e,f,s,g,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,n,s,g e,f,f,w,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,n,s,g e,f,s,n,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,n,a,g p,f,s,w,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,s,g e,x,f,g,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,n,a,g e,b,y,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,g e,f,f,n,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,n,s,g e,f,s,g,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,n,s,g e,x,f,n,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,k,y,d e,b,s,y,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,s,m e,x,s,w,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,k,s,g e,f,f,n,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,n,y,d p,x,s,w,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,s,g e,f,f,w,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,k,s,g p,f,y,w,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,s,u e,x,s,n,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,n,a,g e,f,s,n,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,k,a,g e,b,s,y,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,g e,f,s,g,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,n,a,g e,x,s,g,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,n,a,g e,f,f,g,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,k,s,g e,x,f,g,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,k,s,g e,f,s,w,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,k,a,g p,f,s,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,v,g e,f,f,g,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,n,a,g e,f,s,w,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,k,a,g e,x,f,n,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,k,y,d e,x,s,n,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,n,a,g e,x,f,e,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,n,y,d e,x,y,y,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,n,g e,f,f,w,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,k,s,g e,x,s,w,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,k,a,g e,f,f,n,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,n,a,g p,f,s,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,s,u e,f,f,g,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,n,y,d e,f,s,w,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,n,s,g e,f,f,w,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,k,a,g p,f,y,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,v,g e,x,s,w,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,k,s,g e,x,f,n,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,n,y,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,n,v,d e,x,y,g,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,n,v,d e,f,s,n,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,n,s,g e,f,s,w,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,n,s,g e,f,s,n,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,n,a,g e,x,s,n,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,k,a,g e,f,f,w,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,k,a,g e,x,f,n,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,k,s,g e,f,f,w,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,k,a,g e,f,f,n,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,n,a,g e,f,s,w,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,k,s,g e,f,f,n,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,n,a,g p,f,y,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,v,u e,f,f,w,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,k,a,g e,f,s,w,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,n,s,g e,x,f,n,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,n,a,g e,f,f,w,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,n,s,g e,x,f,g,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,k,a,g e,f,s,n,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,f,g,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,k,v,d e,f,f,w,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,n,a,g e,f,f,n,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,k,s,g e,x,s,n,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,k,s,g e,x,f,w,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,k,s,g e,b,s,y,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,s,g p,x,y,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,s,g p,f,s,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,v,g e,f,f,w,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,k,s,g e,f,f,n,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,k,s,g p,f,y,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,s,g e,f,f,n,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,k,s,g p,x,s,w,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,v,u e,f,s,n,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,n,a,g p,f,y,w,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,v,u e,f,s,n,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,k,a,g e,f,s,g,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,k,a,g e,x,f,g,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,k,a,g e,f,f,n,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,n,s,g e,x,f,g,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,n,v,d e,x,f,n,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,k,v,d e,x,f,n,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,n,s,g e,x,f,g,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,k,y,d e,x,s,w,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,n,s,g e,f,s,w,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,k,a,g e,x,s,w,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,k,s,g e,f,f,g,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,k,s,g e,x,f,n,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,n,y,d e,x,s,w,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,n,s,g e,x,s,n,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,k,s,g e,f,s,g,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,n,s,g p,f,y,w,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,s,g e,f,s,n,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,k,s,g e,f,y,y,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,y,g e,x,f,g,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,k,y,d e,f,s,g,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,s,g,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,n,a,g p,f,y,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,s,u e,x,s,w,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,k,a,g e,x,s,w,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,k,a,g e,f,s,g,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,k,a,g e,f,s,n,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,n,s,g e,x,f,n,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,k,s,g e,f,s,n,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,k,s,g e,f,s,n,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,n,a,g e,x,f,w,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,n,a,g e,f,f,w,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,n,a,g e,f,f,n,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,k,a,g e,x,y,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,m e,x,s,n,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,k,a,g e,x,s,g,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,n,s,g e,f,s,w,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,k,a,g p,x,s,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,s,u e,x,s,w,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,k,s,g e,x,f,n,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,n,v,d e,f,f,g,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,n,s,g e,x,s,g,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,k,a,g e,f,f,n,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,n,a,g e,f,s,n,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,n,s,g e,x,s,g,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,k,s,g e,f,y,n,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,s,p p,f,y,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,v,u e,x,s,n,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,n,s,g e,x,f,n,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,k,v,d p,f,y,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,s,g p,x,s,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,s,u p,f,s,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,s,u e,x,f,n,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,k,y,d e,b,y,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,m p,f,y,w,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,s,g e,f,f,w,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,k,a,g e,x,s,w,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,n,s,g e,x,f,n,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,k,y,d e,x,s,n,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,k,a,g e,f,f,n,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,k,s,g e,f,f,n,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,n,s,g p,f,y,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,s,u p,f,y,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,v,g e,x,s,n,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,k,s,g e,f,f,g,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,n,s,g e,x,f,n,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,k,v,d e,f,s,g,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,n,s,g e,f,f,n,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,k,a,g p,f,s,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,v,u e,x,f,n,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,n,a,g p,f,y,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,v,g e,x,s,g,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,k,a,g e,f,f,w,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,k,s,g e,x,s,w,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,f,n,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,n,y,d e,x,s,n,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,n,s,g p,f,s,w,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,s,u e,x,f,n,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,n,v,d e,x,s,w,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,k,s,g e,f,s,w,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,k,s,g e,x,s,w,t,a,f,w,n,n,t,b,s,s,w,w,p,w,o,p,u,v,d e,x,f,n,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,n,s,g e,x,y,g,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,k,v,d e,x,f,n,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,n,y,d e,x,s,y,t,a,f,w,n,p,t,b,s,s,w,w,p,w,o,p,u,v,d e,f,f,g,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,k,a,g e,x,s,n,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,k,s,g e,x,y,e,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,n,y,d e,f,s,g,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,k,a,g p,f,s,w,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,v,u e,f,f,w,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,n,s,g e,x,f,g,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,n,a,g e,f,f,n,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,n,s,g e,f,s,n,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,k,a,g e,x,f,w,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,n,a,g p,f,y,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,s,g e,x,f,w,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,n,s,g e,f,s,n,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,n,a,g e,x,s,n,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,k,s,g e,x,f,g,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,k,s,g e,x,s,n,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,k,a,g e,f,y,y,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,y,g p,x,y,n,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,v,u e,x,f,w,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,k,a,g e,f,s,w,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,k,s,g e,x,s,n,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,n,s,g p,f,y,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,s,g e,f,f,g,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,k,s,g p,f,s,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,s,u e,f,s,n,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,k,s,g e,x,s,g,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,k,s,g e,x,f,g,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,k,a,g e,f,f,n,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,k,s,g e,f,s,g,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,n,s,g e,x,s,w,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,n,s,g e,x,f,n,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,k,a,g e,x,f,g,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,k,s,g e,f,f,n,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,n,a,g e,b,y,y,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,m e,f,f,g,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,n,s,g e,x,f,g,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,k,a,g e,f,f,w,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,n,a,g e,x,f,n,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,n,y,d p,f,s,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,s,u e,x,f,n,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,n,y,d e,x,f,n,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,n,a,g e,x,f,n,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,k,y,d e,x,f,w,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,n,a,g e,f,s,g,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,k,s,g e,f,s,n,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,k,a,g e,x,y,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,s,m e,x,f,w,t,a,f,w,n,p,t,b,s,s,w,w,p,w,o,p,u,v,d e,f,f,g,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,n,a,g e,f,f,n,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,n,a,g e,f,f,n,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,n,s,g e,b,y,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,s,g e,x,f,n,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,k,s,g e,x,y,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,s,g e,f,s,w,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,k,s,g e,x,s,w,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,f,n,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,n,s,g e,x,s,n,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,n,a,g e,x,s,n,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,n,s,g e,x,y,n,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,n,y,d e,f,s,g,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,k,s,g e,x,y,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,s,w,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,k,a,g p,f,y,w,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,s,u e,f,s,w,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,n,s,g p,f,s,w,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,s,u e,f,s,g,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,k,s,g e,f,f,g,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,n,s,g p,x,s,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,s,g e,x,s,g,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,k,a,g p,x,s,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,s,u e,x,s,g,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,n,s,g e,f,s,w,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,k,s,g p,f,y,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,v,g e,x,f,w,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,k,a,g e,x,s,n,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,k,a,g e,x,f,w,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,n,s,g e,x,f,w,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,k,a,g e,x,y,e,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,k,y,d p,f,s,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,s,u e,f,f,g,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,k,s,g e,x,y,y,t,a,f,c,b,w,e,r,s,y,w,w,p,w,o,p,k,y,g e,x,f,n,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,n,a,g e,f,f,n,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,k,a,g e,b,s,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,m e,f,s,g,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,k,a,g e,f,f,w,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,k,a,g e,f,f,n,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,n,a,g p,f,s,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,s,u e,x,s,n,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,n,a,g e,b,y,y,t,a,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,g e,f,s,g,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,n,a,g e,f,s,n,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,k,s,g e,x,f,g,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,n,a,g e,f,s,g,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,k,s,g e,x,f,n,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,k,a,g e,x,f,n,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,n,v,d e,b,y,w,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,n,m e,x,f,g,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,n,v,d p,f,y,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,s,g e,x,s,w,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,n,a,g p,f,s,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,v,u e,f,s,n,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,n,a,g e,f,f,n,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,k,a,g e,x,f,w,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,k,a,g e,x,f,n,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,n,a,g e,f,s,n,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,n,s,g e,x,s,y,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,s,g e,f,s,w,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,k,a,g e,x,s,w,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,k,s,g p,x,y,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,v,g e,f,f,g,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,k,a,g p,f,y,n,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,s,g e,f,f,w,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,k,a,g e,x,f,n,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,k,v,d e,x,f,g,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,k,s,g p,f,s,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,v,u e,f,s,g,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,k,s,g p,x,s,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,v,u e,x,f,n,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,n,v,d e,x,f,n,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,n,s,g e,x,y,y,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,s,p e,f,f,w,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,k,s,g e,f,s,w,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,n,a,g e,x,f,g,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,n,s,g e,f,f,g,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,k,s,g e,f,f,w,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,n,a,g e,x,f,g,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,k,s,g e,f,f,g,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,n,a,g e,x,f,g,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,s,g,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,k,a,g e,f,s,g,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,k,s,g e,x,y,n,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,s,g e,x,y,g,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,k,y,d e,f,s,g,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,k,a,g e,f,f,w,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,n,s,g e,f,s,n,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,n,a,g e,f,f,w,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,k,s,g e,f,f,n,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,k,a,g e,f,s,g,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,k,a,g e,x,s,n,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,n,s,g e,x,f,n,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,n,y,d e,x,s,n,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,n,s,g e,x,f,n,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,k,a,g e,f,s,w,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,n,a,g e,x,f,n,f,n,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,y,u p,f,s,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,s,u p,f,s,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,v,g e,x,f,n,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,k,v,d e,x,s,w,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,n,a,g e,f,f,g,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,s,n,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,n,s,g e,x,f,n,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,n,s,g e,x,s,g,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,k,s,g e,f,f,g,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,k,a,g e,f,s,n,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,n,s,g e,f,s,g,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,k,a,g e,x,f,e,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,k,v,d p,f,y,w,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,v,u e,x,f,n,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,n,s,g e,x,f,n,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,n,v,d p,f,s,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,s,u p,f,s,w,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,v,g p,f,s,w,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,s,u e,f,f,w,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,n,a,g e,f,s,n,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,n,s,g e,f,f,n,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,k,a,g e,x,s,n,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,k,a,g e,f,s,n,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,k,a,g p,f,s,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,v,g p,f,s,w,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,v,g e,f,s,g,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,n,a,g e,x,s,n,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,k,a,g e,x,s,n,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,n,s,g e,x,f,n,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,k,v,d e,x,f,n,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,n,v,d e,f,f,w,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,k,a,g e,f,f,w,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,n,s,g e,x,f,w,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,k,a,g e,x,s,y,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,n,m e,f,s,g,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,n,a,g e,x,s,w,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,n,s,g e,x,f,n,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,n,s,g e,x,f,n,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,n,a,g e,x,s,w,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,n,s,g e,x,s,n,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,k,s,g e,x,s,g,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,n,s,g e,x,s,g,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,k,s,g e,f,s,w,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,n,s,g e,x,s,n,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,k,a,g e,f,f,g,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,n,s,g e,f,f,w,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,k,s,g e,x,f,w,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,n,a,g e,f,f,g,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,k,s,g e,x,f,g,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,k,a,g e,x,y,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,s,y,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,s,w,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,k,a,g p,x,y,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,s,g e,x,f,w,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,n,s,g p,x,s,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,s,u e,x,y,g,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,n,v,d p,f,s,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,v,u e,x,y,y,t,l,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,g e,x,y,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,n,m e,f,y,n,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,y,p e,x,s,w,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,n,s,g e,f,s,n,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,k,s,g e,x,s,g,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,k,a,g e,x,s,w,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,k,a,g e,f,s,n,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,n,s,g e,f,s,n,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,k,a,g e,x,s,g,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,k,s,g e,b,s,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,n,g e,x,s,g,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,k,s,g e,x,s,y,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,s,m p,f,y,w,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,v,g e,f,s,w,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,k,s,g e,f,s,n,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,k,s,g e,f,s,g,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,n,s,g e,f,f,g,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,n,s,g e,x,y,n,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,n,y,d e,x,f,n,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,k,y,d e,x,y,y,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,y,p e,x,f,g,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,k,y,d e,f,f,g,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,n,a,g e,f,s,n,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,k,s,g e,f,s,w,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,n,a,g e,x,f,g,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,n,a,g e,f,s,w,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,k,s,g e,f,f,g,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,n,a,g e,x,f,g,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,s,n,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,n,a,g e,x,f,n,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,k,y,d e,f,s,w,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,n,s,g e,f,f,n,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,k,s,g p,f,y,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,s,g e,x,f,n,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,k,y,d e,x,f,n,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,k,s,g e,f,f,w,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,k,s,g p,f,y,n,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,v,u e,f,f,g,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,k,s,g e,x,f,g,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,k,v,d e,x,f,w,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,k,a,g e,x,f,g,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,k,s,g e,x,f,n,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,n,v,d e,x,s,g,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,n,a,g e,f,f,w,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,n,a,g e,x,f,g,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,k,y,d e,x,y,w,t,l,f,c,b,w,e,c,s,s,w,w,p,w,o,p,k,n,g e,x,y,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,m e,f,s,g,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,n,s,g e,f,s,w,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,k,a,g e,f,s,n,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,k,s,g e,f,s,w,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,k,a,g e,x,f,n,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,n,a,g e,x,s,n,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,n,s,g e,b,y,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,n,m p,f,y,w,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,v,g e,x,s,n,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,k,a,g e,f,s,n,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,k,s,g e,x,y,n,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,k,s,g e,x,s,g,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,n,a,g e,f,s,w,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,n,a,g p,x,s,n,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,v,u e,f,s,g,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,k,a,g e,x,f,w,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,n,s,g p,f,s,n,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,v,g e,x,f,n,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,s,n,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,k,a,g e,x,f,n,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,k,v,d e,f,s,w,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,k,s,g p,f,s,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,v,u e,x,f,w,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,k,a,g e,f,f,n,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,n,s,g e,f,s,g,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,n,s,g e,x,f,w,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,k,a,g e,f,y,n,t,l,f,c,b,w,e,r,s,y,w,w,p,w,o,p,n,y,g p,f,s,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,s,g e,x,f,w,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,n,a,g e,f,f,n,f,n,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,y,u p,f,y,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,s,u e,f,s,w,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,n,s,g e,x,f,g,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,n,s,g e,f,y,y,t,a,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,y,p e,x,f,w,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,n,s,g e,x,f,w,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,k,a,g p,f,y,n,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,s,g e,f,f,n,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,k,s,g e,f,f,g,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,n,s,g e,x,f,n,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,k,s,g e,x,f,n,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,n,v,d e,x,s,g,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,k,s,g e,x,s,g,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,k,a,g e,x,f,w,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,k,s,g e,f,f,g,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,n,s,g e,x,f,n,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,k,y,d e,x,s,w,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,n,s,g p,x,s,w,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,s,u e,f,s,g,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,n,a,g e,x,s,n,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,n,s,g e,x,f,n,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,k,v,d e,x,y,y,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,y,g e,x,s,g,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,k,a,g e,x,f,n,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,k,a,g e,x,f,w,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,k,a,g e,x,y,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,s,g e,x,f,n,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,k,y,d e,x,f,w,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,k,a,g e,x,f,w,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,k,a,g p,f,s,n,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,s,u p,f,s,w,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,v,u e,x,s,n,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,k,a,g e,x,f,g,f,n,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,v,u e,f,s,n,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,k,s,g e,x,s,w,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,k,a,g p,f,s,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,s,g e,b,s,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,s,g e,x,f,n,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,k,a,g p,f,y,n,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,s,u e,x,s,g,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,k,a,g e,x,s,g,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,n,s,g e,x,s,w,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,k,s,g p,f,s,w,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,v,u e,f,s,w,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,k,a,g e,x,f,n,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,n,a,g e,f,f,n,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,n,s,g e,x,f,n,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,n,a,g p,f,y,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,v,g e,x,f,w,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,n,s,g e,f,s,w,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,n,a,g p,f,y,w,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,v,u e,f,s,g,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,k,a,g e,f,y,n,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,n,v,d e,x,f,g,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,n,a,g e,x,f,g,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,n,y,d e,f,y,e,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,k,v,d e,f,s,g,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,n,s,g e,x,f,g,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,n,y,d e,x,y,g,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,k,y,d e,x,f,g,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,n,s,g p,f,s,n,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,s,g e,f,f,n,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,k,v,d p,x,s,n,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,v,g e,x,s,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,s,g e,x,s,w,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,k,a,g e,x,y,y,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,g p,x,f,g,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,y,g e,f,s,n,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,n,a,g e,f,s,w,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,n,s,g e,x,f,n,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,k,v,d e,f,s,n,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,k,s,g e,x,f,n,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,k,s,g p,x,s,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,v,u e,f,f,n,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,n,y,d e,x,y,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,g e,f,f,g,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,k,s,g e,x,y,e,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,n,v,d e,f,f,w,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,k,s,g e,x,s,g,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,n,a,g e,x,y,n,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,k,v,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,n,y,d e,x,f,g,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,k,v,d e,f,s,w,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,n,a,g e,x,f,g,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,k,v,d e,x,f,n,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,n,v,d e,x,f,e,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,n,y,d e,f,f,w,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,n,s,g e,x,y,n,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,k,y,d e,x,s,g,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,k,s,g e,x,f,g,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,k,a,g e,f,f,w,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,y,g,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,k,v,d p,f,y,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,s,u e,x,y,e,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,k,v,d e,f,f,w,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,k,s,g e,f,s,g,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,n,a,g e,x,y,g,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,n,v,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,k,v,d e,x,f,n,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,k,v,d e,f,f,e,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,k,v,d e,x,s,w,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,n,a,g e,x,f,e,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,n,v,d e,x,f,n,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,k,v,d e,x,f,g,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,k,y,d e,x,f,n,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,n,y,d e,x,f,y,t,a,f,w,n,w,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,f,e,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,n,v,d p,f,s,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,v,g e,x,s,w,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,k,s,g e,x,f,e,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,n,y,d e,x,y,n,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,k,v,d e,x,f,w,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,k,a,g e,x,f,g,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,n,y,d e,x,s,g,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,n,s,g e,x,y,e,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,n,y,d e,x,y,n,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,n,v,d e,x,s,w,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,k,a,g e,x,s,n,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,k,a,g e,x,s,w,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,k,s,g e,x,s,n,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,k,s,g e,f,f,e,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,n,y,d e,f,f,w,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,k,a,g e,f,f,g,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,k,a,g e,x,y,e,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,n,v,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,n,y,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,k,y,d e,f,s,n,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,n,s,g e,x,s,w,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,k,a,g e,x,s,w,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,k,a,g e,x,f,w,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,f,e,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,n,v,d e,x,f,n,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,k,v,d e,f,f,w,t,l,f,w,n,p,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,f,w,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,k,a,g p,f,y,w,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,s,g e,f,f,g,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,k,v,d e,x,f,n,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,n,v,d e,x,s,w,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,n,a,g e,x,f,w,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,n,a,g e,x,s,n,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,f,n,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,s,g,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,y,n,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,n,v,d e,x,f,n,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,n,y,d e,f,s,g,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,n,s,g e,f,s,n,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,k,a,g e,x,s,g,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,n,s,g e,f,f,g,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,k,y,d e,x,s,w,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,n,a,g e,f,f,n,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,n,a,g e,f,s,w,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,k,s,g e,x,f,g,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,n,s,g e,f,f,n,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,n,a,g e,f,f,n,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,k,a,g e,x,f,n,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,n,v,d e,f,s,g,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,k,a,g e,f,s,w,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,n,s,g e,x,y,e,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,k,v,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,k,v,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,k,v,d e,x,f,g,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,k,s,g e,f,f,g,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,n,a,g e,f,y,y,t,l,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,y,g p,f,y,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,v,u e,f,s,n,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,k,a,g e,f,f,n,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,k,s,g e,f,f,n,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,k,v,d e,x,f,e,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,k,y,d e,f,f,g,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,f,n,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,k,s,g e,x,f,g,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,n,s,g e,x,y,e,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,k,v,d e,x,f,n,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,k,s,g e,x,f,n,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,k,a,g e,f,s,w,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,k,s,g e,f,s,g,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,k,s,g p,f,y,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,s,u e,b,s,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,s,g e,x,f,n,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,n,v,d e,f,f,g,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,k,a,g e,x,f,n,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,n,s,g e,x,s,n,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,n,s,g e,f,s,w,t,l,f,w,n,n,t,b,s,s,w,w,p,w,o,p,u,v,d e,x,f,w,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,s,w,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,k,a,g e,x,s,g,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,k,s,g e,x,y,e,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,k,v,d e,x,f,n,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,k,v,d e,f,f,w,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,k,s,g e,f,s,n,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,n,s,g p,f,s,w,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,n,v,u e,f,f,n,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,n,s,g e,x,y,g,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,n,y,d e,x,y,g,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,n,v,d e,x,f,g,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,f,g,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,n,v,d e,x,f,g,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,k,y,d e,x,f,g,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,n,v,d e,x,f,n,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,k,v,d p,x,s,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,v,g e,x,f,n,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,k,s,g e,x,y,n,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,n,v,d e,x,f,g,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,n,y,d p,f,y,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,s,g e,x,f,g,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,k,y,d e,x,f,g,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,k,s,g e,x,f,e,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,k,v,d e,f,f,n,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,n,s,g e,f,s,w,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,n,a,g e,f,s,n,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,k,s,g e,x,y,e,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,n,v,d e,f,s,n,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,k,s,g e,f,f,n,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,n,v,d e,f,s,w,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,k,s,g e,x,f,n,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,k,a,g e,f,f,n,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,n,s,g p,x,s,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,v,u e,x,f,n,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,k,y,d e,f,s,n,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,n,s,g p,f,y,w,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,s,g e,x,f,n,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,n,v,d e,x,f,g,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,n,y,d e,f,f,n,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,n,a,g e,x,f,e,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,k,v,d e,f,f,w,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,n,s,g e,x,f,w,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,k,s,g e,x,y,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,s,w,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,n,s,g e,x,y,g,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,n,v,d e,x,f,g,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,k,y,d e,x,s,g,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,n,a,g p,f,y,w,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,s,u e,x,f,e,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,n,v,d p,f,s,n,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,s,u p,f,y,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,v,g e,x,f,g,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,n,v,d e,f,s,n,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,n,a,g e,x,f,g,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,n,y,d e,x,f,n,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,k,a,g e,x,f,n,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,n,y,d e,f,s,n,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,n,s,g e,f,f,n,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,k,a,g e,x,s,n,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,k,a,g e,x,s,n,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,k,s,g e,x,f,n,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,n,v,d e,f,s,n,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,k,a,g e,x,f,n,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,k,y,d p,f,y,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,v,u e,x,y,y,t,l,f,c,b,n,e,r,s,y,w,w,p,w,o,p,n,s,g p,f,s,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,s,g e,f,f,w,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,n,s,g e,f,f,n,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,k,a,g p,f,s,n,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,v,g e,x,s,n,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,n,a,g e,x,f,n,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,k,s,g e,x,f,e,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,k,v,d e,f,f,n,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,k,a,g e,x,f,w,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,n,s,g e,f,s,g,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,n,a,g e,f,f,w,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,k,s,g e,f,s,y,t,a,f,w,n,n,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,f,w,t,a,f,w,n,n,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,f,n,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,n,a,g e,x,f,n,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,n,y,d e,x,y,g,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,k,y,d e,x,f,n,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,n,y,d e,x,f,n,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,k,s,g e,x,f,g,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,n,y,d e,x,f,n,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,k,v,d e,x,f,g,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,k,a,g e,x,f,n,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,n,v,d e,x,s,n,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,k,a,g e,b,y,w,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,m e,x,y,e,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,k,v,d e,f,s,n,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,n,s,g e,x,f,e,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,k,y,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,k,v,d e,x,s,g,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,s,n,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,k,s,g e,x,f,g,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,n,a,g e,x,s,g,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,k,a,g e,x,y,e,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,k,y,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,k,y,d e,x,f,n,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,n,s,g e,f,s,n,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,n,s,g e,x,f,w,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,k,s,g e,x,y,y,t,a,f,c,b,p,e,r,s,y,w,w,p,w,o,p,n,s,p e,x,f,e,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,n,v,d e,x,f,n,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,k,s,g e,x,y,n,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,n,y,d e,x,f,w,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,n,a,g e,x,y,w,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,s,m e,x,s,n,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,n,s,g e,f,s,w,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,n,a,g e,f,f,n,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,n,v,d e,f,f,w,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,k,s,g e,x,f,g,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,n,v,d e,x,f,n,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,n,y,d e,x,f,w,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,n,a,g e,x,s,w,t,a,f,c,b,n,e,c,s,s,w,w,p,w,o,p,k,n,m e,f,s,g,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,n,s,g p,f,y,n,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,v,g e,f,f,g,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,n,s,g e,x,f,n,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,n,v,d e,x,f,w,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,n,s,g e,x,y,n,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,k,v,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,n,v,d p,f,s,n,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,v,u e,f,s,g,f,n,f,w,b,p,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,f,g,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,k,y,d e,f,f,g,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,k,y,d e,x,f,g,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,k,v,d e,x,f,g,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,n,y,d e,x,f,n,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,k,y,d p,x,s,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,v,u e,x,s,y,t,l,f,c,b,k,e,c,s,s,w,w,p,w,o,p,k,n,m e,x,f,n,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,n,v,d e,f,y,n,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,n,y,d e,x,s,g,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,n,s,g e,x,y,e,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,n,y,d e,x,f,g,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,n,s,g e,f,s,w,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,n,s,g e,x,f,n,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,n,v,d e,f,f,g,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,k,s,g e,f,f,g,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,k,s,g e,f,f,n,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,n,s,g e,x,f,g,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,n,y,d p,f,y,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,s,u e,x,y,g,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,k,v,d e,x,s,w,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,n,a,g e,b,s,w,t,a,f,c,b,g,e,c,s,s,w,w,p,w,o,p,n,s,m e,x,s,w,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,n,s,g e,f,f,n,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,k,s,g e,x,y,g,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,k,y,d e,f,f,g,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,f,g,f,n,f,w,b,p,t,e,f,s,w,w,p,w,o,e,k,s,g p,x,s,w,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,s,g e,x,s,n,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,y,g,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,k,y,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,n,v,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,n,y,d e,x,f,e,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,k,y,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,k,y,d e,x,f,g,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,k,v,d e,x,f,e,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,k,v,d e,x,y,e,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,n,v,d p,x,s,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,v,g e,x,f,e,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,n,v,d e,x,y,g,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,k,v,d e,x,f,n,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,n,y,d e,x,y,e,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,k,v,d e,x,f,g,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,k,v,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,k,v,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,n,y,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,k,v,d e,x,f,n,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,k,v,d e,f,y,g,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,k,v,d e,x,y,e,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,n,v,d e,x,f,g,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,n,y,d e,x,y,g,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,k,v,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,y,g p,f,s,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,s,g e,x,f,e,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,k,v,d e,x,f,w,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,n,s,g e,x,y,n,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,n,y,d e,x,f,n,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,n,v,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,n,y,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,n,v,d e,x,f,e,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,n,y,d e,x,f,g,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,k,v,d e,x,y,e,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,n,y,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,k,y,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,n,v,d e,f,y,n,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,n,v,d p,f,s,n,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,v,u e,f,f,e,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,n,y,d p,x,s,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,s,g e,x,f,e,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,k,y,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,k,y,d e,x,y,n,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,n,v,d e,f,f,e,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,n,v,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,n,y,d e,x,f,g,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,n,y,d e,x,f,e,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,k,v,d e,x,f,n,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,n,y,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,k,y,d e,f,f,n,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,n,y,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,n,y,d e,x,y,e,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,n,y,d e,x,f,g,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,k,y,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,n,v,d e,x,y,g,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,k,v,d e,x,f,g,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,n,v,d e,f,f,g,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,n,v,d e,x,y,g,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,k,v,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,k,y,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,y,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,n,y,d e,x,y,n,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,n,y,d e,x,y,e,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,k,v,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,k,y,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,k,y,d e,x,f,g,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,k,v,d e,x,f,g,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,n,v,d e,x,f,n,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,k,v,d e,x,f,g,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,k,y,d e,x,s,g,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,n,s,g e,x,y,e,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,k,y,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,k,y,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,n,v,d e,f,f,g,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,k,v,d e,x,f,g,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,k,y,d e,x,f,g,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,n,v,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,n,y,d e,x,s,w,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,n,a,g e,x,f,n,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,k,v,d e,x,f,n,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,k,y,d e,f,y,g,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,n,v,d p,x,s,p,f,c,f,w,n,g,e,b,s,s,w,w,p,w,o,p,n,s,d e,x,y,n,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,n,y,d e,f,f,g,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,k,v,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,k,y,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,n,v,d e,x,f,g,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,k,v,d e,x,f,e,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,n,v,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,k,v,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,n,y,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,k,v,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,n,y,d e,x,f,w,f,n,f,w,b,k,t,e,f,f,w,w,p,w,o,e,n,s,g e,x,y,g,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,k,v,d e,x,y,g,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,n,v,d e,x,f,e,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,k,v,d e,x,f,g,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,n,y,d e,f,y,e,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,n,v,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,k,v,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,n,y,d e,f,f,g,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,k,s,g p,x,f,g,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,y,p e,x,f,e,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,k,y,d e,x,y,e,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,n,y,d p,f,s,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,k,v,g e,f,y,n,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,n,y,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,k,v,d e,x,f,g,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,k,v,d e,x,y,g,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,n,v,d e,x,f,g,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,n,a,g e,x,f,n,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,n,y,d e,f,f,e,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,k,y,d e,f,f,g,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,n,s,g e,f,f,g,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,k,y,d e,f,y,n,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,n,y,d e,x,f,g,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,n,v,d e,f,s,g,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,n,a,g e,x,f,n,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,k,y,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,k,y,d e,x,y,e,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,n,y,d e,x,y,e,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,k,y,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,k,y,d e,f,s,w,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,k,a,g e,x,y,n,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,k,y,d e,x,f,g,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,n,v,d e,f,f,g,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,n,v,d e,f,f,n,f,n,f,w,b,n,t,e,s,f,w,w,p,w,o,e,k,s,g e,f,f,g,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,k,v,d e,x,y,e,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,k,y,d e,f,f,g,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,n,y,d e,x,f,e,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,k,y,d e,x,f,n,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,n,y,d e,x,f,g,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,n,v,d e,x,f,n,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,k,y,d e,x,y,n,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,n,y,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,n,v,d e,f,f,g,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,k,y,d e,x,y,n,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,k,y,d p,x,s,p,f,c,f,w,n,n,e,b,s,s,w,w,p,w,o,p,k,v,d e,f,y,g,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,k,y,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,n,y,d p,f,s,n,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,k,s,u e,x,y,n,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,k,y,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,k,v,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,k,v,d e,x,f,g,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,n,y,d e,f,s,w,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,k,s,g e,x,y,g,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,n,v,d e,x,f,n,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,n,s,g e,x,f,n,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,n,y,d e,x,y,g,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,k,v,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,k,v,d e,x,f,g,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,n,v,d e,x,f,g,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,k,v,d e,x,y,g,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,n,y,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,n,v,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,k,v,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,k,y,d e,x,f,n,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,n,v,d e,x,f,n,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,n,y,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,n,v,d e,x,f,e,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,k,y,d e,f,y,n,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,k,v,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,k,v,d e,f,y,n,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,k,y,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,n,v,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,k,y,d e,x,y,e,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,k,y,d e,x,f,g,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,n,y,d e,x,f,n,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,n,y,d e,f,y,g,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,n,v,d e,x,f,n,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,k,v,d e,x,y,e,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,k,y,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,k,y,d e,x,y,e,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,n,y,d e,x,y,e,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,n,y,d e,x,f,g,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,n,v,d e,x,f,g,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,n,v,d e,f,f,e,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,n,v,d e,x,f,n,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,n,y,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,n,y,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,n,v,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,n,y,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,k,v,d e,x,f,w,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,n,s,g e,f,y,g,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,n,y,d e,f,s,g,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,n,s,g e,f,f,n,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,n,y,d e,x,y,e,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,k,y,d p,f,y,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,s,u e,x,y,g,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,k,y,d e,x,f,g,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,n,y,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,n,y,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,k,y,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,k,y,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,k,v,d e,f,s,w,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,y,n,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,k,v,d e,x,f,g,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,k,y,d e,x,f,n,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,k,y,d e,x,f,n,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,n,y,d p,f,s,w,t,p,f,c,n,w,e,e,s,s,w,w,p,w,o,p,n,v,u e,x,f,g,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,k,v,d e,f,s,w,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,k,s,g e,x,s,g,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,n,s,g e,x,f,g,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,k,v,d e,x,y,g,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,k,y,d e,x,f,n,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,y,d e,x,y,e,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,k,y,d e,x,f,n,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,k,a,g p,x,s,w,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,n,v,g e,x,y,g,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,f,n,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,k,v,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,k,y,d e,x,f,g,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,n,y,d e,x,y,e,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,n,y,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,k,y,d p,x,s,w,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,v,g e,f,f,g,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,k,v,d e,x,f,g,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,k,v,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,k,v,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,n,y,d e,x,f,e,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,n,y,d e,x,y,e,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,k,y,d e,f,f,g,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,n,y,d e,x,f,g,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,n,v,d e,x,y,g,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,k,v,d e,x,f,g,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,k,y,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,k,y,d e,x,y,n,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,k,y,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,k,v,d e,x,f,n,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,n,y,d e,x,f,n,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,k,y,d e,f,f,g,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,n,y,d e,x,f,e,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,n,v,d p,x,s,p,f,c,f,c,n,g,e,b,s,s,w,w,p,w,o,p,k,v,d e,x,f,e,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,k,y,d e,x,f,n,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,k,y,d e,f,f,e,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,k,y,d e,x,f,g,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,n,y,d e,x,f,g,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,n,y,d e,x,f,g,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,k,v,d e,x,f,g,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,n,y,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,n,y,d e,x,f,e,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,n,v,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,k,y,d e,f,y,e,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,k,v,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,n,y,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,k,y,d e,x,f,g,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,k,y,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,y,g e,x,y,n,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,k,v,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,n,y,d e,x,f,n,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,k,y,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,n,y,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,n,y,d e,x,f,g,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,n,a,g e,x,y,g,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,k,y,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,k,v,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,n,y,d e,x,f,g,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,f,n,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,k,y,d e,x,y,e,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,n,v,d e,x,f,n,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,n,y,d e,x,f,g,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,k,v,d e,x,f,n,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,k,v,d e,x,f,g,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,n,v,d e,x,f,n,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,k,v,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,n,v,d e,x,y,g,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,n,y,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,k,v,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,k,y,d p,f,y,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,s,u e,x,s,g,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,n,s,g e,x,f,g,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,k,v,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,k,y,d p,x,s,p,f,c,f,w,n,u,e,b,s,s,w,w,p,w,o,p,n,s,d e,x,y,n,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,n,y,d e,x,y,e,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,k,v,d e,x,s,w,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,n,s,g e,f,f,g,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,n,v,d e,x,y,g,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,n,v,d e,x,y,g,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,n,v,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,n,y,d e,x,y,g,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,k,v,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,n,v,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,k,y,d p,f,y,w,t,p,f,c,n,p,e,e,s,s,w,w,p,w,o,p,n,v,u e,f,f,n,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,n,y,d e,x,f,e,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,n,v,d e,x,y,g,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,k,v,d e,f,s,w,f,n,f,w,b,h,t,e,f,f,w,w,p,w,o,e,k,s,g e,x,f,n,f,n,f,w,b,k,t,e,f,s,w,w,p,w,o,e,n,a,g e,x,f,n,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,n,y,d e,x,y,e,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,n,y,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,k,y,d e,x,f,g,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,k,v,d e,f,f,e,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,n,y,d e,x,y,e,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,n,v,d p,x,s,w,f,c,f,w,n,p,e,b,s,s,w,w,p,w,o,p,n,s,d e,f,f,n,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,k,y,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,k,v,d e,x,f,e,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,k,y,d e,f,s,w,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,n,s,g e,x,y,g,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,n,y,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,n,y,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,k,v,d e,x,f,g,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,n,y,d e,x,y,n,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,k,y,d e,x,y,n,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,n,y,d e,x,y,g,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,k,y,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,k,y,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,y,p e,f,f,g,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,k,v,d e,x,y,e,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,k,v,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,v,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,k,v,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,k,v,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,y,d p,x,f,p,f,c,f,w,n,n,e,b,s,s,w,w,p,w,o,p,n,s,d e,x,f,g,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,n,y,d e,x,f,g,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,n,v,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,n,v,d e,f,f,g,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,n,y,d e,x,f,g,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,n,y,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,k,v,d e,x,f,n,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,k,y,d e,x,y,n,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,k,y,d e,f,f,n,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,n,v,d e,f,f,g,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,k,y,d e,x,f,g,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,k,y,d e,x,y,n,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,n,v,d e,x,y,g,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,k,y,d p,x,f,w,f,c,f,c,n,g,e,b,s,s,w,w,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,k,y,d e,x,y,e,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,n,y,d e,f,f,g,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,k,v,d e,x,f,e,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,k,y,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,y,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,k,y,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,n,v,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,k,v,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,v,g e,x,y,n,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,n,y,d e,x,y,n,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,n,y,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,k,y,d e,x,f,g,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,k,y,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,k,y,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,k,v,d e,x,y,g,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,n,v,d e,f,f,e,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,n,v,d e,x,y,g,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,n,v,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,n,y,d e,x,f,e,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,k,y,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,k,y,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,v,p e,x,f,g,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,k,y,d e,x,y,n,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,n,y,d e,x,f,g,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,n,y,d e,x,f,g,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,n,y,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,k,y,d e,f,f,g,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,k,y,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,k,v,d e,x,f,e,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,k,y,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,v,p e,x,f,e,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,n,v,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,k,y,d e,f,y,g,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,n,y,d e,x,f,g,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,n,y,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,n,y,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,n,y,d e,x,f,n,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,n,y,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,k,y,d e,f,f,n,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,n,v,d e,x,f,n,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,k,y,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,n,v,d e,x,f,g,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,n,v,d p,x,f,g,f,c,f,c,n,g,e,b,s,s,w,w,p,w,o,p,n,v,d e,f,f,g,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,n,v,d e,x,f,n,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,n,y,d e,f,s,n,f,n,f,w,b,p,t,e,s,f,w,w,p,w,o,e,k,a,g e,f,f,n,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,n,v,d e,x,y,g,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,n,y,d e,f,y,g,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,n,v,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,y,e,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,n,v,d e,x,y,g,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,n,y,d e,x,f,g,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,n,v,d e,f,f,g,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,k,y,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,k,v,d e,f,y,n,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,n,y,d e,x,f,g,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,n,y,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,k,y,d e,f,f,w,f,n,f,w,b,h,t,e,s,f,w,w,p,w,o,e,k,s,g e,x,y,n,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,n,v,d e,x,f,g,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,k,y,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,n,y,d e,x,f,e,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,n,y,d e,f,y,n,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,k,v,d e,x,y,e,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,k,y,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,k,v,d e,x,y,e,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,k,v,d e,x,f,e,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,n,y,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,n,v,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,n,y,d e,x,f,g,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,k,v,d e,x,f,g,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,k,v,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,k,y,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,n,v,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,n,y,d e,x,f,g,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,n,y,d e,x,f,e,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,n,y,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,k,v,d e,x,f,g,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,k,v,d e,x,f,e,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,n,y,d e,f,f,g,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,k,y,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,k,v,d p,x,f,p,f,c,f,c,n,p,e,b,s,s,w,w,p,w,o,p,n,v,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,k,y,d e,x,f,n,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,k,v,d e,f,s,n,f,n,f,w,b,n,t,e,s,s,w,w,p,w,o,e,n,a,g e,x,y,g,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,k,y,d e,x,y,n,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,n,v,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,k,y,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,y,g e,x,y,e,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,f,g,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,k,v,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,n,v,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,k,y,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,k,v,d e,x,f,e,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,n,y,d e,x,y,e,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,k,v,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,n,y,d e,x,f,e,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,n,y,d e,x,f,e,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,k,y,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,n,y,d e,f,f,e,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,k,y,d e,x,y,e,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,k,v,d e,x,f,n,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,n,y,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,n,y,d e,x,y,n,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,n,v,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,k,y,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,n,y,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,n,y,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,n,y,d e,x,s,g,f,n,f,w,b,h,t,e,f,s,w,w,p,w,o,e,k,s,g e,f,f,n,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,n,y,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,n,y,d e,x,y,g,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,k,y,d e,x,f,n,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,k,y,d e,x,y,n,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,k,y,d e,x,y,e,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,k,y,d e,x,y,n,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,n,y,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,n,y,d e,x,f,e,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,k,y,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,n,v,d e,x,f,e,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,n,y,d e,x,f,g,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,n,y,d p,x,f,g,f,c,f,c,n,p,e,b,s,s,w,w,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,n,y,d e,x,f,g,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,n,y,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,k,y,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,k,y,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,n,y,d e,f,y,g,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,k,y,d e,x,f,g,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,n,v,d e,x,f,g,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,v,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,n,v,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,k,y,d e,x,f,g,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,n,y,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,y,d e,f,f,n,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,k,v,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,k,v,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,n,y,d e,x,y,n,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,k,v,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,n,v,d e,x,f,g,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,k,y,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,n,v,d e,x,f,g,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,k,y,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,k,y,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,k,y,d e,x,f,n,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,n,y,d e,x,y,e,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,n,y,d e,f,s,g,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,k,s,g e,x,y,e,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,k,y,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,n,y,d e,x,y,e,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,k,y,d e,x,f,g,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,n,v,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,n,v,d e,x,f,g,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,k,v,d p,x,f,w,f,c,f,w,n,g,e,b,s,s,w,w,p,w,o,p,n,s,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,n,y,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,n,y,d e,f,f,w,f,n,f,w,b,h,t,e,s,s,w,w,p,w,o,e,n,s,g e,x,f,g,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,n,y,d e,f,f,g,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,n,v,d e,x,f,g,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,n,y,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,k,y,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,k,v,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,n,v,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,n,v,d e,x,y,g,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,y,g,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,n,y,d e,x,f,g,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,n,v,d e,x,f,e,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,n,v,d e,x,f,n,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,k,y,d e,f,f,n,f,n,f,w,b,n,t,e,f,f,w,w,p,w,o,e,k,s,g e,x,f,e,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,n,y,d e,x,y,g,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,n,y,d e,x,y,n,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,k,v,d e,x,f,g,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,n,y,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,k,v,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,k,y,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,n,v,d e,x,f,e,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,k,v,d e,x,y,g,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,n,y,d e,x,y,n,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,n,y,d e,x,y,e,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,k,v,d e,x,f,e,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,k,y,d e,x,f,n,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,k,v,d e,x,f,e,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,n,y,d e,x,y,e,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,k,y,d e,x,f,g,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,k,y,d e,x,f,g,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,k,v,d p,x,f,p,f,c,f,w,n,u,e,b,s,s,w,w,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,n,y,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,n,v,d e,f,s,n,f,n,f,w,b,p,t,e,f,f,w,w,p,w,o,e,n,s,g e,x,y,g,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,k,y,d e,x,f,n,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,k,y,d e,f,f,g,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,n,y,d e,x,f,g,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,n,y,d e,x,f,n,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,n,v,d e,f,f,g,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,n,y,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,n,y,d e,x,y,g,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,n,y,d p,x,s,p,f,c,f,w,n,u,e,b,s,s,w,w,p,w,o,p,k,s,d e,f,y,n,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,k,v,d e,x,y,e,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,k,v,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,k,v,d e,x,f,g,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,n,y,d e,x,y,n,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,n,y,d e,x,y,g,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,n,y,d e,x,y,e,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,k,v,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,n,y,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,n,y,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,n,y,d e,f,f,g,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,k,y,d e,f,f,e,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,n,y,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,n,y,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,n,y,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,n,v,d e,x,s,w,f,n,f,w,b,k,t,e,s,f,w,w,p,w,o,e,k,s,g e,x,y,n,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,k,v,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,n,y,d e,f,f,e,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,k,v,d e,x,f,g,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,k,y,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,k,v,d p,x,s,g,f,c,f,c,n,n,e,b,s,s,w,w,p,w,o,p,k,v,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,k,v,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,k,v,d e,x,f,n,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,k,a,g e,x,y,e,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,k,y,d p,x,f,w,f,c,f,w,n,u,e,b,s,s,w,w,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,k,v,d e,x,f,g,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,n,y,d e,f,y,n,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,k,v,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,n,y,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,n,y,d e,x,f,g,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,y,p e,x,y,g,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,n,y,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,k,v,d e,x,f,g,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,k,y,d e,x,f,g,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,k,y,d e,x,f,g,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,n,y,d e,f,f,g,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,n,y,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,n,y,d e,x,f,g,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,k,v,d e,x,f,n,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,k,y,d e,f,y,n,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,n,v,d e,f,f,e,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,k,y,d e,x,f,g,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,n,y,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,y,p e,x,f,g,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,k,v,d e,x,f,g,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,n,y,d e,x,f,n,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,f,g,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,k,y,d e,x,y,n,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,k,v,d e,f,y,g,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,v,p e,x,f,n,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,n,y,d e,x,y,n,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,n,v,d e,x,f,n,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,n,y,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,k,v,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,n,y,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,k,y,d e,x,f,g,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,k,v,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,f,g,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,k,y,d e,x,y,n,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,n,v,d e,x,f,e,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,k,y,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,n,y,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,k,y,d e,x,f,n,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,n,y,d e,x,f,e,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,k,v,d e,x,f,n,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,n,y,d e,x,y,e,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,n,y,d e,x,y,n,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,k,y,d e,x,y,e,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,n,v,d e,f,f,g,f,n,f,w,b,n,t,e,f,s,w,w,p,w,o,e,n,s,g e,x,y,e,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,k,v,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,k,y,d e,x,f,g,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,k,v,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,k,v,d e,x,f,n,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,n,y,d e,x,y,n,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,k,v,d e,x,f,g,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,n,y,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,k,y,d e,x,f,g,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,n,v,d e,x,f,g,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,n,v,d e,x,f,e,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,n,v,d e,x,f,e,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,f,e,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,k,y,d e,f,y,g,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,k,y,d e,x,f,g,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,k,v,d e,x,f,g,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,k,v,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,v,d e,x,f,n,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,k,v,d e,x,y,g,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,n,y,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,n,y,d e,x,f,e,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,k,y,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,k,y,d e,x,y,e,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,k,v,d p,x,y,y,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,v,p e,f,y,n,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,n,y,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,y,d p,x,f,g,f,c,f,w,n,g,e,b,s,s,w,w,p,w,o,p,k,s,d e,f,f,g,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,n,y,d e,f,f,e,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,n,v,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,k,y,d e,f,f,e,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,k,y,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,y,p e,f,f,g,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,y,e,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,k,y,d e,f,y,e,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,n,y,d p,x,f,w,f,c,f,c,n,p,e,b,s,s,w,w,p,w,o,p,n,s,d e,x,f,e,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,n,y,d e,f,y,n,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,k,v,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,v,g p,x,f,g,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,y,p e,f,y,e,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,n,v,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,k,v,d e,f,f,e,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,n,y,d e,f,y,e,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,n,v,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,n,y,d e,f,y,e,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,k,v,d p,x,f,p,f,c,f,w,n,u,e,b,s,s,w,w,p,w,o,p,k,s,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,y,d e,f,f,e,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,n,y,d e,f,y,g,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,k,v,d e,f,y,g,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,n,y,d e,f,f,e,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,k,y,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,n,v,d p,f,f,g,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,v,p e,f,y,n,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,n,y,d e,f,y,e,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,n,v,d p,x,f,g,f,c,f,c,n,p,e,b,s,s,w,w,p,w,o,p,n,s,d e,f,f,e,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,k,y,d e,f,y,e,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,k,v,d p,x,y,y,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,v,g p,f,f,y,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,v,d e,f,y,n,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,k,v,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,k,v,d e,f,y,g,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,k,v,d p,x,s,p,f,c,f,w,n,n,e,b,s,s,w,w,p,w,o,p,n,v,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,k,y,d e,x,y,e,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,k,v,d e,f,f,e,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,k,y,d e,f,y,n,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,k,v,d p,x,s,w,f,c,f,c,n,p,e,b,s,s,w,w,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,n,v,d e,f,y,g,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,n,y,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,n,v,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,k,v,d p,x,s,g,f,c,f,c,n,u,e,b,s,s,w,w,p,w,o,p,n,s,d p,x,f,p,f,c,f,c,n,n,e,b,s,s,w,w,p,w,o,p,k,s,d e,f,y,e,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,k,y,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,y,d p,x,s,w,f,c,f,w,n,g,e,b,s,s,w,w,p,w,o,p,k,v,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,v,p e,f,y,n,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,n,v,d p,x,y,y,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,y,p e,f,y,g,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,n,v,d e,f,y,n,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,k,y,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,k,y,d p,x,s,w,f,c,f,c,n,p,e,b,s,s,w,w,p,w,o,p,n,s,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,v,p e,f,y,g,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,k,y,d e,f,y,g,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,k,y,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,v,p e,f,y,n,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,n,y,d p,f,f,g,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,y,p e,f,f,e,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,n,y,d e,x,f,n,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,k,v,d p,f,f,g,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,v,p e,f,y,g,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,k,v,d e,f,y,g,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,n,y,d e,f,y,e,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,n,y,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,v,p e,f,f,e,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,y,n,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,k,v,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,v,g e,f,y,e,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,k,y,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,y,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,n,y,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,y,g p,x,f,g,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,y,p p,x,f,g,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,y,g e,f,y,e,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,n,y,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,v,g e,f,f,e,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,n,v,d p,x,s,g,f,c,f,w,n,g,e,b,s,s,w,w,p,w,o,p,n,v,d e,f,y,g,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,k,v,d p,x,s,p,f,c,f,c,n,p,e,b,s,s,w,w,p,w,o,p,n,s,d e,f,f,e,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,n,y,d e,f,f,e,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,n,y,d e,f,y,e,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,k,y,d e,f,y,n,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,k,y,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,y,g p,f,f,y,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,y,p p,x,s,g,f,c,f,w,n,g,e,b,s,s,w,w,p,w,o,p,k,s,d e,f,f,e,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,k,v,d e,f,f,e,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,k,y,d e,f,y,e,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,k,v,d e,f,y,n,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,k,y,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,v,g p,x,f,g,f,c,f,c,n,u,e,b,s,s,w,w,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,k,y,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,n,v,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,n,v,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,k,y,d e,f,y,n,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,k,y,d e,f,f,e,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,k,v,d p,x,s,g,f,c,f,c,n,u,e,b,s,s,w,w,p,w,o,p,k,v,d p,x,f,w,f,c,f,c,n,n,e,b,s,s,w,w,p,w,o,p,n,v,d e,f,f,g,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,k,y,d e,f,y,g,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,n,y,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,y,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,k,v,d p,x,s,w,f,c,f,w,n,p,e,b,s,s,w,w,p,w,o,p,k,s,d e,f,y,g,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,n,y,d e,f,y,g,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,k,y,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,n,v,d e,f,f,e,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,n,v,d e,f,y,n,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,n,y,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,k,v,d e,f,y,n,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,n,y,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,k,y,d e,f,y,g,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,n,v,d e,x,f,n,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,k,y,d e,f,y,e,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,k,y,d e,f,f,e,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,k,v,d e,f,y,e,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,n,v,d p,x,f,y,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,v,p e,f,y,g,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,n,y,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,k,v,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,y,d e,f,y,g,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,k,y,d e,f,y,g,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,k,y,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,n,y,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,n,y,d e,f,y,g,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,k,v,d p,x,s,w,f,c,f,c,n,g,e,b,s,s,w,w,p,w,o,p,n,s,d p,x,f,w,f,c,f,w,n,n,e,b,s,s,w,w,p,w,o,p,n,s,d e,f,f,n,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,k,v,d e,f,f,e,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,k,y,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,n,y,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,y,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,n,v,d e,f,f,g,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,k,y,d e,f,f,g,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,k,y,d p,x,s,w,f,c,f,w,n,g,e,b,s,s,w,w,p,w,o,p,n,s,d e,x,y,e,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,k,v,d e,f,y,e,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,k,v,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,y,d e,f,f,e,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,k,y,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,v,p p,x,f,p,f,c,f,w,n,g,e,b,s,s,w,w,p,w,o,p,k,s,d e,f,y,g,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,k,v,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,v,p p,x,f,w,f,c,f,c,n,g,e,b,s,s,w,w,p,w,o,p,n,s,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,v,p e,f,y,e,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,n,v,d p,x,y,g,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,v,p p,x,s,g,f,c,f,w,n,u,e,b,s,s,w,w,p,w,o,p,n,s,d e,f,y,g,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,n,y,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,k,v,d e,f,f,e,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,n,y,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,v,p p,x,f,p,f,c,f,w,n,g,e,b,s,s,w,w,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,n,v,d e,f,f,e,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,k,y,d e,f,y,n,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,k,y,d e,f,y,g,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,k,v,d p,x,y,g,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,v,g e,f,y,n,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,n,v,d p,x,f,p,f,c,f,c,n,u,e,b,s,s,w,w,p,w,o,p,k,v,d p,x,f,w,f,c,f,c,n,n,e,b,s,s,w,w,p,w,o,p,k,s,d e,f,f,e,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,n,y,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,n,y,d e,f,y,e,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,k,v,d e,f,y,g,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,k,v,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,v,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,y,p e,f,f,e,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,k,y,d p,x,y,y,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,v,g p,x,s,p,f,c,f,c,n,u,e,b,s,s,w,w,p,w,o,p,k,s,d e,f,f,e,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,n,y,d p,f,f,y,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,v,d e,f,y,e,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,k,y,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,n,v,d e,x,f,n,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,k,y,d e,f,f,e,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,v,g e,f,y,e,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,n,y,d p,f,f,g,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,y,p e,f,y,e,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,n,y,d e,f,f,e,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,n,y,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,y,g e,f,y,g,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,k,v,d e,f,y,g,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,k,y,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,v,g p,x,f,w,f,c,f,c,n,u,e,b,s,s,w,w,p,w,o,p,n,s,d e,f,f,e,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,k,v,d p,x,f,y,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,v,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,n,y,d e,f,y,g,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,n,v,d e,f,f,e,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,n,v,d e,f,y,g,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,k,v,d e,f,f,e,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,n,v,d p,x,s,g,f,c,f,w,n,g,e,b,s,s,w,w,p,w,o,p,k,v,d e,f,y,g,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,n,y,d e,f,y,n,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,n,y,d e,f,y,g,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,n,y,d e,f,y,g,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,n,y,d e,f,y,n,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,k,y,d e,x,f,g,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,n,v,d e,f,f,g,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,n,y,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,y,p p,x,s,w,f,c,f,w,n,p,e,b,s,s,w,w,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,k,v,d e,f,y,g,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,y,p p,x,s,w,f,c,f,w,n,u,e,b,s,s,w,w,p,w,o,p,n,s,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,y,p e,x,y,g,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,k,y,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,v,g e,f,y,e,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,n,y,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,n,y,d e,x,f,g,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,k,v,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,v,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,k,y,d e,f,y,g,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,k,v,d p,x,s,w,f,c,f,c,n,p,e,b,s,s,w,w,p,w,o,p,k,s,d p,x,y,y,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,y,g e,f,f,e,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,k,y,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,y,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,y,d e,x,y,n,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,y,g e,f,y,n,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,n,y,d e,f,f,g,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,k,y,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,n,v,d e,f,y,g,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,k,y,d p,x,s,g,f,c,f,w,n,n,e,b,s,s,w,w,p,w,o,p,n,s,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,k,v,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,n,v,d e,f,y,n,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,n,v,d e,f,y,g,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,k,v,d p,x,f,p,f,c,f,c,n,g,e,b,s,s,w,w,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,y,g e,f,y,g,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,k,y,d e,f,f,g,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,k,y,d p,x,s,p,f,c,f,w,n,p,e,b,s,s,w,w,p,w,o,p,n,v,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,n,y,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,y,p p,x,f,g,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,y,p e,f,y,n,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,n,y,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,n,v,d p,x,s,g,f,c,f,c,n,u,e,b,s,s,w,w,p,w,o,p,n,v,d p,f,f,g,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,v,d p,x,f,p,f,c,f,w,n,p,e,b,s,s,w,w,p,w,o,p,n,s,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,k,v,d e,f,y,g,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,k,v,d e,f,f,e,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,n,y,d p,x,f,y,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,y,g e,f,f,g,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,k,y,d p,x,f,w,f,c,f,w,n,p,e,b,s,s,w,w,p,w,o,p,k,v,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,v,d e,f,f,e,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,n,y,d e,f,y,g,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,n,y,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,v,p p,x,f,g,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,v,p p,x,s,p,f,c,f,w,n,p,e,b,s,s,w,w,p,w,o,p,k,v,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,k,v,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,v,d e,f,y,n,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,n,y,d e,x,y,n,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,y,e,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,n,y,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,n,y,d e,f,f,e,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,k,y,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,k,y,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,n,y,d p,x,f,p,f,c,f,w,n,n,e,b,s,s,w,w,p,w,o,p,k,s,d e,f,f,e,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,n,v,d e,f,f,e,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,k,v,d p,x,s,w,f,c,f,w,n,n,e,b,s,s,w,w,p,w,o,p,n,s,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,k,y,d e,f,y,n,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,k,v,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,v,g e,f,f,e,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,y,g e,f,f,e,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,n,y,d e,f,y,g,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,n,y,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,v,g e,f,y,e,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,n,v,d p,x,f,w,f,c,f,c,n,p,e,b,s,s,w,w,p,w,o,p,k,s,d e,f,y,n,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,n,y,d e,x,y,g,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,k,y,d e,f,y,n,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,n,y,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,n,v,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,n,y,d e,f,y,e,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,y,d e,f,y,g,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,k,y,d e,f,y,g,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,n,v,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,n,y,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,n,v,d e,f,f,e,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,k,y,d e,f,f,e,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,k,y,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,k,v,d p,x,f,p,f,c,f,c,n,u,e,b,s,s,w,w,p,w,o,p,n,s,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,v,d e,f,y,g,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,n,v,d e,f,y,e,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,n,v,d p,x,s,w,f,c,f,c,n,g,e,b,s,s,w,w,p,w,o,p,k,s,d p,x,f,p,f,c,f,w,n,g,e,b,s,s,w,w,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,y,p e,x,f,g,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,k,v,d e,f,y,e,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,k,v,d p,x,s,p,f,c,f,w,n,p,e,b,s,s,w,w,p,w,o,p,k,s,d e,f,y,g,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,n,y,d e,f,y,n,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,k,y,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,v,g e,f,y,n,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,k,v,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,k,y,d p,x,f,w,f,c,f,w,n,g,e,b,s,s,w,w,p,w,o,p,k,v,d e,f,y,n,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,n,y,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,v,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,k,y,d p,x,f,y,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,y,p e,f,f,g,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,k,v,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,k,y,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,n,v,d e,f,y,g,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,k,v,d p,x,f,g,f,c,f,w,n,u,e,b,s,s,w,w,p,w,o,p,k,v,d e,f,y,g,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,n,y,d e,f,f,e,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,k,v,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,y,p e,f,y,n,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,n,v,d p,x,s,g,f,c,f,w,n,g,e,b,s,s,w,w,p,w,o,p,n,s,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,v,g e,f,f,e,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,k,v,d e,f,y,n,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,n,v,d e,f,y,g,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,n,y,d p,x,f,w,f,c,f,c,n,p,e,b,s,s,w,w,p,w,o,p,k,v,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,v,g p,x,f,g,f,c,f,w,n,u,e,b,s,s,w,w,p,w,o,p,n,v,d e,f,f,e,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,n,v,d p,f,y,g,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,y,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,y,g e,f,y,e,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,n,y,d p,x,f,p,f,c,f,w,n,g,e,b,s,s,w,w,p,w,o,p,n,s,d p,x,s,g,f,c,f,c,n,u,e,b,s,s,w,w,p,w,o,p,k,s,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,k,v,d e,f,f,e,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,n,y,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,k,y,d e,f,y,n,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,k,v,d p,x,s,p,f,c,f,w,n,g,e,b,s,s,w,w,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,y,d e,f,f,e,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,k,v,d e,f,y,e,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,n,v,d e,f,f,g,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,k,v,d e,f,f,e,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,n,y,d e,f,y,n,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,n,y,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,k,v,d p,f,f,y,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,v,p e,x,f,g,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,k,y,d p,x,s,p,f,c,f,w,n,p,e,b,s,s,w,w,p,w,o,p,n,s,d e,x,y,e,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,n,y,d e,f,f,g,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,k,y,d e,f,f,e,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,n,v,d e,x,f,e,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,k,v,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,k,v,d e,f,f,e,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,n,v,d p,x,s,w,f,c,f,w,n,n,e,b,s,s,w,w,p,w,o,p,n,v,d p,x,y,g,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,y,d p,x,f,p,f,c,f,c,n,n,e,b,s,s,w,w,p,w,o,p,k,v,d e,f,y,g,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,n,y,d e,x,y,n,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,n,v,d p,x,f,g,f,c,f,c,n,n,e,b,s,s,w,w,p,w,o,p,n,s,d e,f,y,n,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,k,y,d p,x,f,p,f,c,f,c,n,g,e,b,s,s,w,w,p,w,o,p,k,v,d e,f,f,e,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,n,y,d p,x,s,w,f,c,f,w,n,n,e,b,s,s,w,w,p,w,o,p,k,s,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,y,g p,x,s,g,f,c,f,c,n,n,e,b,s,s,w,w,p,w,o,p,k,s,d e,f,y,n,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,n,y,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,y,g p,x,s,p,f,c,f,c,n,p,e,b,s,s,w,w,p,w,o,p,k,v,d e,f,y,e,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,k,y,d p,x,s,g,f,c,f,w,n,p,e,b,s,s,w,w,p,w,o,p,n,s,d e,x,y,g,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,n,v,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,k,y,d e,f,y,n,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,n,y,d e,f,y,n,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,k,v,d e,f,f,n,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,n,y,d p,x,s,g,f,c,f,c,n,n,e,b,s,s,w,w,p,w,o,p,n,s,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,k,v,d e,x,f,e,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,n,v,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,n,y,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,n,y,d e,f,y,n,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,k,v,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,y,g p,x,s,g,f,c,f,c,n,p,e,b,s,s,w,w,p,w,o,p,n,s,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,n,y,d p,x,f,g,f,c,f,w,n,g,e,b,s,s,w,w,p,w,o,p,k,v,d e,f,y,n,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,k,y,d e,f,y,g,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,k,y,d e,f,f,e,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,k,v,d p,x,f,y,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,v,p p,x,s,g,f,c,f,w,n,p,e,b,s,s,w,w,p,w,o,p,k,v,d e,f,y,g,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,n,y,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,n,y,d e,f,y,n,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,k,y,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,n,v,d e,f,y,g,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,k,v,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,v,p e,f,y,g,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,k,y,d e,f,f,e,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,n,v,d p,x,f,g,f,c,f,w,n,g,e,b,s,s,w,w,p,w,o,p,n,v,d e,f,y,g,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,n,v,d p,f,y,g,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,y,p e,f,f,e,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,k,y,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,v,p e,f,y,g,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,k,v,d p,x,f,p,f,c,f,c,n,n,e,b,s,s,w,w,p,w,o,p,n,s,d e,f,f,e,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,n,v,d p,x,f,p,f,c,f,w,n,p,e,b,s,s,w,w,p,w,o,p,n,v,d p,x,s,w,f,c,f,c,n,u,e,b,s,s,w,w,p,w,o,p,n,s,d e,f,y,g,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,n,v,d p,x,s,p,f,c,f,w,n,u,e,b,s,s,w,w,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,y,d e,x,f,n,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,n,v,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,k,y,d e,f,y,e,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,k,y,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,y,g p,x,f,g,f,c,f,w,n,n,e,b,s,s,w,w,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,v,p p,x,f,w,f,c,f,w,n,u,e,b,s,s,w,w,p,w,o,p,n,s,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,k,y,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,k,y,d p,x,f,w,f,c,f,w,n,g,e,b,s,s,w,w,p,w,o,p,k,s,d e,x,y,g,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,k,y,d e,f,y,n,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,k,y,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,k,y,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,k,y,d p,x,f,w,f,c,f,w,n,n,e,b,s,s,w,w,p,w,o,p,k,s,d e,f,f,e,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,n,y,d p,x,y,y,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,y,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,n,v,d e,f,y,n,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,n,v,d p,x,f,g,f,c,f,w,n,p,e,b,s,s,w,w,p,w,o,p,n,v,d p,x,s,p,f,c,f,c,n,n,e,b,s,s,w,w,p,w,o,p,n,v,d e,f,f,e,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,n,y,d e,x,f,g,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,k,v,d e,f,y,g,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,k,y,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,v,p e,x,y,n,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,k,v,d e,f,y,g,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,k,y,d e,f,f,g,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,n,y,d p,x,f,g,f,c,f,c,n,p,e,b,s,s,w,w,p,w,o,p,k,s,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,v,p e,f,y,g,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,k,v,d e,f,f,e,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,k,v,d e,f,f,e,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,k,y,d p,x,s,w,f,c,f,c,n,u,e,b,s,s,w,w,p,w,o,p,n,v,d p,x,f,w,f,c,f,w,n,p,e,b,s,s,w,w,p,w,o,p,n,s,d e,f,f,e,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,k,v,d e,f,f,e,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,k,v,d e,f,y,n,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,k,y,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,v,g e,f,y,g,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,k,y,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,y,p e,f,f,e,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,n,y,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,v,g e,f,y,g,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,n,v,d e,f,f,e,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,k,y,d e,f,y,n,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,y,d e,f,f,e,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,k,y,d e,x,f,g,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,n,v,d e,f,y,g,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,n,v,d p,x,f,w,f,c,f,w,n,u,e,b,s,s,w,w,p,w,o,p,k,s,d e,f,f,e,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,k,y,d e,f,f,e,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,k,y,d e,f,y,e,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,n,y,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,k,v,d e,f,y,n,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,k,v,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,v,g e,x,f,g,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,k,v,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,y,d e,f,y,g,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,k,v,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,n,y,d p,x,y,g,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,v,d e,f,y,g,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,n,y,d p,f,f,g,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,v,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,k,y,d p,x,s,g,f,c,f,c,n,g,e,b,s,s,w,w,p,w,o,p,n,v,d e,f,y,e,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,k,v,d e,f,y,n,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,k,v,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,k,v,d e,f,y,g,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,n,v,d p,x,s,p,f,c,f,w,n,n,e,b,s,s,w,w,p,w,o,p,k,s,d p,f,f,g,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,v,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,n,v,d e,f,f,e,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,n,y,d p,x,f,p,f,c,f,c,n,u,e,b,s,s,w,w,p,w,o,p,n,v,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,n,y,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,k,v,d e,f,y,e,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,k,y,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,k,y,d e,x,f,g,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,n,y,d p,x,s,w,f,c,f,w,n,p,e,b,s,s,w,w,p,w,o,p,n,v,d e,f,y,g,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,k,y,d p,x,y,g,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,v,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,k,v,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,k,v,d p,x,s,g,f,c,f,w,n,n,e,b,s,s,w,w,p,w,o,p,k,s,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,n,y,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,y,d e,x,y,n,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,n,y,d e,f,y,e,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,n,v,d e,f,f,e,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,k,v,d p,x,s,p,f,c,f,c,n,n,e,b,s,s,w,w,p,w,o,p,n,s,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,v,d e,f,y,e,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,k,v,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,k,v,d p,x,s,p,f,c,f,c,n,p,e,b,s,s,w,w,p,w,o,p,n,v,d e,f,f,g,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,n,y,d e,f,f,e,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,k,y,d e,f,f,n,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,k,v,d e,x,y,g,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,n,y,d e,f,y,n,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,n,y,d p,x,f,p,f,c,f,c,n,p,e,b,s,s,w,w,p,w,o,p,k,v,d e,f,f,e,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,k,v,d p,x,y,y,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,y,d p,x,s,g,f,c,f,w,n,p,e,b,s,s,w,w,p,w,o,p,n,v,d e,f,y,n,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,k,v,d p,f,f,g,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,v,d p,x,f,g,f,c,f,w,n,n,e,b,s,s,w,w,p,w,o,p,k,s,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,k,y,d e,f,y,g,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,k,v,d e,f,y,g,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,n,y,d p,x,f,y,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,v,g e,f,f,g,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,n,y,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,v,p e,f,y,e,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,n,v,d e,f,f,e,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,n,y,d p,f,f,g,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,y,d e,f,f,e,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,k,v,d p,x,f,y,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,y,p e,f,f,e,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,n,v,d e,f,f,g,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,f,e,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,k,v,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,k,y,d e,f,y,n,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,n,v,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,n,v,d e,f,f,e,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,v,g e,f,y,n,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,k,y,d p,x,f,g,f,c,f,c,n,n,e,b,s,s,w,w,p,w,o,p,k,v,d e,f,y,n,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,n,v,d e,f,y,g,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,k,v,d e,x,f,e,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,k,y,d e,f,y,e,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,k,y,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,n,v,d e,x,y,g,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,n,v,d p,x,f,p,f,c,f,c,n,g,e,b,s,s,w,w,p,w,o,p,k,s,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,n,y,d e,f,y,n,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,k,v,d e,f,y,g,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,k,y,d p,f,f,g,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,y,g e,f,y,g,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,n,v,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,k,y,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,y,g e,f,y,n,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,k,y,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,v,g e,f,f,e,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,k,y,d e,x,y,n,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,k,y,d e,x,y,g,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,k,y,d e,f,y,e,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,k,v,d p,x,y,g,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,v,d p,x,s,g,f,c,f,c,n,g,e,b,s,s,w,w,p,w,o,p,k,v,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,v,g p,x,f,g,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,v,p p,f,f,g,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,y,p e,f,f,g,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,k,v,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,v,d e,f,y,e,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,k,v,d e,f,y,n,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,n,v,d e,f,y,n,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,k,y,d p,x,y,y,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,y,d e,f,y,g,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,k,y,d p,x,f,p,f,c,f,w,n,u,e,b,s,s,w,w,p,w,o,p,n,s,d e,f,f,e,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,n,y,d e,f,y,n,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,k,y,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,k,v,d e,f,f,e,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,n,y,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,y,g p,x,f,g,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,v,p e,f,f,g,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,k,v,d e,x,f,n,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,v,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,n,y,d p,x,f,p,f,c,f,c,n,g,e,b,s,s,w,w,p,w,o,p,n,s,d e,f,y,n,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,y,g,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,k,y,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,y,p e,x,f,e,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,k,y,d p,x,s,g,f,c,f,w,n,u,e,b,s,s,w,w,p,w,o,p,k,s,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,v,g e,f,y,n,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,v,d e,f,y,e,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,n,y,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,n,y,d e,f,y,n,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,n,y,d e,f,y,e,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,n,y,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,k,y,d e,f,y,e,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,k,y,d e,f,y,n,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,k,y,d p,x,y,y,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,y,g e,f,f,g,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,k,y,d e,f,y,n,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,y,g p,x,f,g,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,v,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,y,p e,f,y,e,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,n,y,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,k,v,d p,x,y,g,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,y,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,v,p p,f,y,g,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,v,p e,f,y,n,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,n,v,d p,x,f,g,f,c,f,w,n,n,e,b,s,s,w,w,p,w,o,p,n,s,d e,f,f,e,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,n,v,d p,f,f,y,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,y,d e,f,y,n,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,n,v,d e,x,y,e,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,k,y,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,y,p e,x,y,n,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,k,y,d p,x,s,w,f,c,f,c,n,g,e,b,s,s,w,w,p,w,o,p,n,v,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,k,v,d e,f,f,e,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,n,v,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,n,y,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,v,d e,f,y,e,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,y,e,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,n,y,d p,x,s,p,f,c,f,c,n,g,e,b,s,s,w,w,p,w,o,p,k,s,d e,f,f,e,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,k,y,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,n,y,d e,f,f,g,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,v,p e,f,y,n,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,n,y,d e,f,y,g,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,k,v,d e,f,y,n,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,k,y,d p,x,s,p,f,c,f,c,n,n,e,b,s,s,w,w,p,w,o,p,k,s,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,k,y,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,k,v,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,k,y,d p,x,s,w,f,c,f,c,n,u,e,b,s,s,w,w,p,w,o,p,k,s,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,v,p e,f,y,n,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,v,g p,x,f,w,f,c,f,c,n,n,e,b,s,s,w,w,p,w,o,p,n,s,d e,f,y,n,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,k,y,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,y,g,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,y,g,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,n,v,d p,x,f,w,f,c,f,w,n,p,e,b,s,s,w,w,p,w,o,p,n,v,d e,f,f,e,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,v,g e,f,y,n,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,n,y,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,n,v,d p,x,s,p,f,c,f,c,n,u,e,b,s,s,w,w,p,w,o,p,k,v,d e,f,y,g,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,n,y,d p,x,s,p,f,c,f,c,n,g,e,b,s,s,w,w,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,n,y,d p,x,y,g,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,y,g e,f,y,e,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,k,y,d p,x,f,p,f,c,f,c,n,p,e,b,s,s,w,w,p,w,o,p,n,s,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,v,p e,f,f,e,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,n,y,d e,f,f,e,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,k,y,d p,x,f,g,f,c,f,c,n,u,e,b,s,s,w,w,p,w,o,p,n,s,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,v,g e,f,y,g,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,n,y,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,v,d e,f,f,e,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,k,v,d e,f,y,n,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,k,v,d p,f,y,y,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,y,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,k,y,d e,f,y,e,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,k,v,d e,f,y,n,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,n,y,d e,x,f,n,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,k,v,d p,f,y,g,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,v,d e,f,y,g,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,n,v,d e,f,f,e,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,k,y,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,n,v,d e,x,y,g,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,n,y,d e,x,y,n,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,k,v,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,v,d p,x,s,w,f,c,f,w,n,g,e,b,s,s,w,w,p,w,o,p,n,v,d p,f,f,y,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,v,p e,f,y,n,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,n,v,d e,f,y,e,t,n,f,c,b,p,t,b,s,s,p,g,p,w,o,p,k,y,d e,f,f,e,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,n,y,d e,f,f,e,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,n,y,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,n,v,d e,f,y,n,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,k,y,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,k,v,d p,x,y,g,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,y,g e,f,y,e,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,n,y,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,n,y,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,v,d p,x,f,w,f,c,f,w,n,p,e,b,s,s,w,w,p,w,o,p,k,s,d p,x,f,g,f,c,f,w,n,p,e,b,s,s,w,w,p,w,o,p,k,v,d e,x,y,n,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,n,y,d p,f,f,y,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,v,p p,x,s,g,f,c,f,w,n,n,e,b,s,s,w,w,p,w,o,p,n,v,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,n,v,d e,f,y,e,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,n,y,d e,f,f,e,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,k,v,d p,x,f,y,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,v,d e,f,y,n,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,n,v,d e,f,f,e,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,y,e,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,n,v,d p,x,f,y,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,v,p p,x,f,g,f,c,f,c,n,n,e,b,s,s,w,w,p,w,o,p,n,v,d e,f,f,e,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,k,v,d p,x,s,g,f,c,f,c,n,g,e,b,s,s,w,w,p,w,o,p,n,s,d p,x,f,w,f,c,f,c,n,u,e,b,s,s,w,w,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,y,g e,f,y,g,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,n,v,d e,f,f,e,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,k,v,d p,f,f,y,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,y,p e,f,f,e,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,k,y,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,n,v,d e,f,f,g,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,n,v,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,n,y,d e,f,f,g,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,k,v,d e,f,y,n,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,k,y,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,k,v,d e,f,y,n,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,n,v,d e,f,f,e,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,n,y,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,n,y,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,k,y,d e,x,f,g,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,n,y,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,n,y,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,n,v,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,k,y,d e,f,f,n,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,k,y,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,y,p e,f,y,e,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,n,y,d e,x,y,g,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,k,y,d e,f,y,n,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,n,v,d e,f,y,n,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,k,y,d e,f,y,g,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,n,y,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,v,d e,f,f,e,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,n,v,d p,f,f,g,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,v,d e,f,y,g,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,n,y,d e,f,y,g,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,n,v,d e,f,f,g,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,k,y,d p,f,f,y,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,v,p e,x,y,n,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,n,v,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,n,y,d p,f,f,g,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,v,d e,f,y,n,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,k,v,d p,x,f,g,f,c,f,w,n,u,e,b,s,s,w,w,p,w,o,p,k,s,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,n,y,d p,x,s,w,f,c,f,w,n,g,e,b,s,s,w,w,p,w,o,p,k,s,d e,f,y,n,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,k,v,d p,x,s,w,f,c,f,c,n,n,e,b,s,s,w,w,p,w,o,p,n,v,d e,f,y,e,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,n,y,d e,f,f,g,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,n,v,d e,f,f,e,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,k,y,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,n,y,d p,x,s,g,f,c,f,c,n,p,e,b,s,s,w,w,p,w,o,p,k,s,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,k,y,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,k,v,d p,x,f,p,f,c,f,w,n,n,e,b,s,s,w,w,p,w,o,p,k,v,d e,f,f,e,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,k,y,d p,x,s,p,f,c,f,c,n,u,e,b,s,s,w,w,p,w,o,p,n,v,d e,f,f,e,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,k,y,d p,f,f,g,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,y,g e,f,y,g,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,n,y,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,y,g e,f,y,n,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,k,v,d e,f,y,e,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,n,v,d e,f,y,n,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,k,v,d p,x,s,p,f,c,f,w,n,g,e,b,s,s,w,w,p,w,o,p,k,s,d p,x,y,g,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,y,p e,f,f,e,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,n,v,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,k,v,d e,f,y,g,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,k,v,d e,f,y,e,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,n,y,d e,f,y,e,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,k,v,d e,x,f,g,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,n,y,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,y,d e,x,y,n,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,n,y,d e,f,y,e,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,k,y,d e,f,f,e,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,k,y,d p,x,f,w,f,c,f,c,n,n,e,b,s,s,w,w,p,w,o,p,k,v,d e,f,y,e,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,k,y,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,n,y,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,y,g e,f,y,g,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,n,y,d p,x,s,w,f,c,f,w,n,n,e,b,s,s,w,w,p,w,o,p,k,v,d e,f,f,e,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,k,v,d p,x,s,w,f,c,f,c,n,n,e,b,s,s,w,w,p,w,o,p,k,s,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,v,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,y,d e,f,y,g,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,n,v,d e,f,y,g,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,n,v,d e,f,y,e,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,n,y,d e,f,y,e,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,k,y,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,v,p e,f,f,e,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,n,y,d e,f,f,e,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,k,y,d p,x,y,g,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,v,g e,f,f,e,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,k,y,d p,x,f,g,f,c,f,w,n,p,e,b,s,s,w,w,p,w,o,p,n,s,d e,f,y,g,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,k,y,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,n,y,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,n,y,d e,f,y,g,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,k,y,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,n,y,d e,f,y,g,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,k,y,d p,x,s,p,f,c,f,c,n,p,e,b,s,s,w,w,p,w,o,p,k,s,d e,f,y,n,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,y,g e,f,y,e,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,k,v,d e,f,y,g,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,n,v,d e,f,f,e,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,n,v,d p,x,s,w,f,c,f,w,n,u,e,b,s,s,w,w,p,w,o,p,n,v,d p,x,f,w,f,c,f,w,n,n,e,b,s,s,w,w,p,w,o,p,n,v,d e,x,y,n,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,n,v,d e,f,f,e,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,k,v,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,k,v,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,n,y,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,v,d p,x,f,w,f,c,f,w,n,n,e,b,s,s,w,w,p,w,o,p,k,v,d e,f,y,n,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,k,y,d e,f,f,e,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,k,v,d p,x,f,w,f,c,f,w,n,u,e,b,s,s,w,w,p,w,o,p,k,v,d p,x,s,g,f,c,f,w,n,p,e,b,s,s,w,w,p,w,o,p,k,s,d e,x,y,e,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,k,v,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,v,d p,x,f,g,f,c,f,c,n,p,e,b,s,s,w,w,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,v,d p,x,s,g,f,c,f,c,n,n,e,b,s,s,w,w,p,w,o,p,n,v,d e,x,f,g,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,k,v,d p,x,f,p,f,c,f,c,n,u,e,b,s,s,w,w,p,w,o,p,k,s,d e,f,f,e,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,n,v,d p,x,s,p,f,c,f,c,n,n,e,b,s,s,w,w,p,w,o,p,k,v,d p,x,f,g,f,c,f,w,n,p,e,b,s,s,w,w,p,w,o,p,k,s,d e,f,y,e,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,k,y,d p,x,f,g,f,c,f,c,n,n,e,b,s,s,w,w,p,w,o,p,k,s,d p,x,s,g,f,c,f,w,n,n,e,b,s,s,w,w,p,w,o,p,k,v,d e,f,y,g,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,n,y,d e,f,y,n,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,n,y,d p,x,f,g,f,c,f,w,n,g,e,b,s,s,w,w,p,w,o,p,n,s,d e,f,f,e,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,k,v,d p,x,s,w,f,c,f,c,n,n,e,b,s,s,w,w,p,w,o,p,n,s,d e,f,y,n,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,k,v,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,v,d p,f,y,g,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,y,g e,f,y,g,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,k,v,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,v,g e,f,y,g,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,y,g p,f,f,g,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,y,p e,f,f,e,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,k,v,d p,x,f,w,f,c,f,c,n,p,e,b,s,s,w,w,p,w,o,p,n,v,d e,f,f,g,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,n,y,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,y,p p,x,y,y,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,v,d p,f,y,g,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,y,p p,x,f,y,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,v,g p,x,f,w,f,c,f,w,n,g,e,b,s,s,w,w,p,w,o,p,n,v,d p,x,y,y,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,y,d p,x,y,y,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,v,d p,x,f,y,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,v,p p,f,f,y,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,v,d p,f,f,y,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,y,d e,f,y,g,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,k,y,d p,x,y,g,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,y,g p,f,f,y,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,y,p p,f,f,y,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,y,g e,x,f,g,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,k,y,d e,f,y,n,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,n,v,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,n,v,d p,x,y,y,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,v,g p,f,y,g,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,v,g p,f,y,g,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,v,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,k,y,d p,f,y,g,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,v,g e,f,f,e,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,k,v,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,y,d p,x,y,y,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,y,g p,f,f,y,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,y,g e,f,y,e,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,n,v,d p,x,f,y,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,y,d p,f,y,g,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,y,p p,f,f,y,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,v,g p,f,y,y,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,v,d p,x,y,g,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,y,p p,f,f,y,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,v,p p,x,s,p,f,c,f,c,n,g,e,b,s,s,w,w,p,w,o,p,n,s,d p,x,y,y,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,v,g e,f,f,e,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,k,v,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,k,y,d p,x,f,p,f,c,f,c,n,n,e,b,s,s,w,w,p,w,o,p,n,v,d p,x,f,y,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,v,g p,f,y,g,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,v,g e,x,y,g,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,k,y,d e,f,f,e,t,n,f,c,b,p,t,b,s,s,w,g,p,w,o,p,n,y,d p,f,y,g,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,v,d e,f,y,g,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,n,v,d p,x,f,y,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,v,d p,f,y,g,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,y,g e,f,f,e,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,n,v,d p,x,y,y,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,v,g p,f,f,y,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,y,g p,x,y,y,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,v,g p,f,f,g,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,y,g p,x,s,p,f,c,f,w,n,n,e,b,s,s,w,w,p,w,o,p,n,s,d p,x,f,g,f,c,f,c,n,g,e,b,s,s,w,w,p,w,o,p,k,s,d p,x,y,g,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,v,p p,x,y,y,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,y,p p,f,f,g,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,v,d e,f,y,g,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,n,v,d p,x,s,g,t,f,f,c,b,w,t,b,f,s,w,w,p,w,o,p,h,v,u p,x,y,y,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,y,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,k,v,d p,f,f,y,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,y,d p,x,y,g,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,y,p p,f,f,y,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,v,p p,x,y,g,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,y,g p,f,y,g,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,y,g p,f,y,y,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,y,p p,x,f,y,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,y,p p,x,s,w,f,c,f,c,n,g,e,b,s,s,w,w,p,w,o,p,k,v,d p,x,y,g,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,v,p p,x,f,g,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,y,p e,f,y,n,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,n,v,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,k,v,d p,x,f,y,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,y,p p,x,s,p,f,c,f,c,n,u,e,b,s,s,w,w,p,w,o,p,n,s,d p,f,f,g,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,v,g p,x,f,g,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,v,g p,x,s,w,f,c,f,c,n,u,e,b,s,s,w,w,p,w,o,p,k,v,d e,f,f,e,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,n,v,d p,f,y,g,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,v,g p,x,f,p,f,c,f,w,n,p,e,b,s,s,w,w,p,w,o,p,k,v,d p,f,s,w,t,f,f,c,b,p,t,b,f,s,w,w,p,w,o,p,h,v,g p,x,y,y,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,v,p e,x,y,b,t,n,f,c,b,e,e,?,s,s,e,w,p,w,t,e,w,c,w p,f,f,g,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,y,g p,x,f,g,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,y,g p,x,f,y,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,y,g p,f,f,y,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,y,g e,f,f,g,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,n,y,d p,x,f,y,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,v,d p,x,y,g,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,v,d p,f,f,g,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,y,g p,x,f,g,f,c,f,w,n,u,e,b,s,s,w,w,p,w,o,p,n,s,d p,x,f,g,f,c,f,c,n,u,e,b,s,s,w,w,p,w,o,p,n,v,d p,x,y,g,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,v,g p,x,s,g,t,f,f,c,b,h,t,b,s,s,w,w,p,w,o,p,h,s,g p,x,y,g,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,v,g e,f,y,g,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,k,y,d p,f,f,y,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,v,d e,f,f,e,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,k,v,d p,f,y,g,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,y,p e,f,y,n,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,k,v,d e,f,f,e,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,k,y,d p,x,y,g,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,y,p p,x,y,g,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,y,d e,f,f,e,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,n,v,d p,f,f,g,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,v,p e,f,f,g,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,k,y,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,k,y,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,n,v,d p,f,f,g,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,y,p e,x,f,e,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,k,v,d p,f,y,g,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,v,d p,x,y,y,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,v,p p,f,y,y,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,v,d p,x,f,y,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,v,p p,x,y,y,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,v,d e,x,f,g,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,n,v,d e,x,y,g,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,n,v,d p,f,y,g,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,v,g p,f,f,y,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,y,d p,x,y,g,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,y,p p,x,y,e,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p p,x,y,g,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,y,p p,x,y,g,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,v,g p,x,s,g,f,c,f,w,n,u,e,b,s,s,w,w,p,w,o,p,n,v,d p,f,f,g,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,v,g p,f,s,b,t,f,f,c,b,p,t,b,s,f,w,w,p,w,o,p,h,s,g p,x,y,g,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,v,d p,x,y,y,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,y,d p,x,s,w,f,c,f,w,n,u,e,b,s,s,w,w,p,w,o,p,k,s,d p,x,y,y,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,v,d e,f,f,e,t,n,f,c,b,w,t,b,s,s,w,p,p,w,o,p,k,v,d p,x,y,g,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,y,g p,x,f,y,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,v,d p,x,f,y,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,v,p p,f,f,g,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,v,g p,x,f,y,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,y,d e,f,f,g,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,k,v,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,y,d e,f,y,n,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,n,y,d p,f,y,g,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,v,d p,f,f,g,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,y,p p,f,f,g,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,v,d p,x,s,w,f,c,f,w,n,u,e,b,s,s,w,w,p,w,o,p,k,v,d p,x,y,g,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,y,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,g,w,p,w,o,p,k,v,d p,x,f,w,f,c,f,c,n,u,e,b,s,s,w,w,p,w,o,p,k,s,d p,x,f,y,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,v,d p,x,f,y,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,y,d p,x,f,p,f,c,f,w,n,u,e,b,s,s,w,w,p,w,o,p,n,v,d p,f,f,y,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,y,d p,f,f,g,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,v,p e,f,y,e,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,k,v,d p,x,y,y,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,v,p p,f,f,y,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,v,p p,x,f,g,f,c,f,c,n,g,e,b,s,s,w,w,p,w,o,p,n,s,d p,x,s,p,f,c,f,w,n,u,e,b,s,s,w,w,p,w,o,p,k,v,d e,x,f,e,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,n,v,d p,x,y,y,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,v,g e,f,f,n,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,n,y,d e,f,y,e,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,k,y,d p,f,y,y,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,y,d p,x,f,y,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,y,g p,x,y,g,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,v,d p,f,f,g,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,y,d p,f,f,y,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,y,p e,f,y,g,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,n,y,d p,x,y,g,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,v,p p,x,y,y,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,v,p p,f,f,g,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,v,p p,f,f,y,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,y,p e,f,f,e,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,n,v,d e,f,y,n,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,n,v,d p,x,f,y,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,y,g e,f,y,u,f,n,f,c,n,h,e,?,s,f,w,w,p,w,o,f,h,y,d e,f,y,n,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,n,y,d p,f,y,y,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,v,g p,f,f,y,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,v,g p,x,y,g,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,y,d p,x,y,g,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,y,p p,f,f,y,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,v,p p,x,y,y,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,y,d p,x,f,y,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,v,p p,x,y,g,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,v,p p,x,f,y,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,y,p e,x,f,g,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,n,v,d p,f,y,g,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,y,d e,f,y,e,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,v,d p,f,f,y,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,v,d e,f,y,n,t,n,f,c,b,n,t,b,s,s,w,w,p,w,o,p,n,y,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,k,y,d p,f,y,g,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,v,g e,x,f,e,t,n,f,c,b,w,t,b,s,s,p,p,p,w,o,p,k,v,d e,f,f,e,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,n,y,d p,f,y,y,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,v,p p,x,f,w,f,c,f,c,n,u,e,b,s,s,w,w,p,w,o,p,k,v,d p,x,y,g,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,y,d p,x,y,e,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d p,x,f,y,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,v,p p,f,y,g,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,y,d e,f,y,g,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,n,y,d p,x,y,n,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l e,f,y,e,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,n,v,d p,b,s,b,t,n,f,c,b,g,e,b,s,s,w,w,p,w,t,p,r,v,m e,f,f,g,t,n,f,c,b,w,t,b,s,s,g,g,p,w,o,p,k,y,d p,f,f,g,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,v,g e,f,y,g,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,k,y,d p,f,f,y,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,y,p p,f,f,y,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,y,g p,f,f,g,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,v,g e,f,f,e,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,n,v,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,y,p p,f,f,y,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,v,g p,x,f,y,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,v,d p,x,f,y,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,y,p p,f,f,y,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,v,g p,f,f,y,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,v,g p,x,y,g,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,v,p e,f,y,e,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,k,v,d p,f,f,g,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,v,d p,f,f,y,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,v,g e,f,f,n,t,n,f,c,b,u,t,b,s,s,w,p,p,w,o,p,k,v,d p,x,y,y,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,v,p p,x,y,y,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,v,p e,f,y,n,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,k,y,d p,f,y,g,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,y,p e,f,f,e,t,n,f,c,b,p,t,b,s,s,g,g,p,w,o,p,k,y,d p,x,y,y,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,v,g p,f,y,g,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,v,d p,x,y,y,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,v,d p,x,s,g,f,c,f,c,n,g,e,b,s,s,w,w,p,w,o,p,k,s,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,k,v,d p,f,y,g,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,y,g p,x,f,g,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,y,d p,f,y,g,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,v,p e,f,y,n,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,k,v,d p,x,y,y,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,y,d p,f,f,g,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,y,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,n,v,d e,f,y,e,t,n,f,c,b,w,t,b,s,s,p,g,p,w,o,p,k,v,d p,f,s,g,t,f,f,c,b,p,t,b,f,f,w,w,p,w,o,p,h,v,u p,x,f,g,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,y,p p,f,y,g,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,v,p p,x,y,g,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,v,p p,x,f,y,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,v,d p,f,y,g,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,v,d p,f,y,g,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,v,p e,f,y,e,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,n,y,d p,x,y,g,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,v,g p,f,y,g,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,v,g p,x,y,g,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,y,p e,f,f,e,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,n,v,d e,f,y,e,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,n,v,d e,f,y,e,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,n,y,d p,f,f,y,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,v,g p,f,f,g,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,y,p e,f,y,n,t,n,f,c,b,u,t,b,s,s,g,p,p,w,o,p,k,y,d p,x,y,g,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,y,g e,f,f,g,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,n,v,d p,x,f,y,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,v,p p,x,y,y,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,v,d p,x,y,y,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,v,d e,f,f,c,f,n,f,w,n,w,e,b,f,f,w,n,p,w,o,e,w,v,l p,x,f,g,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,v,d p,f,f,g,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,y,g p,x,y,g,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,v,g p,f,y,g,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,y,g p,x,s,b,t,f,f,c,b,w,t,b,f,s,w,w,p,w,o,p,h,s,u p,f,f,g,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,v,d p,x,y,g,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,v,g p,f,f,y,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,y,p p,f,f,g,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,v,p p,f,f,g,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,y,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,k,y,d p,x,f,y,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,y,p p,x,f,y,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,y,p e,f,y,e,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,k,y,d p,f,y,g,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,v,p p,f,f,g,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,y,d p,x,y,y,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,y,d e,f,f,g,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,k,y,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,v,g p,x,f,g,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,y,p e,f,y,n,t,n,f,c,b,p,t,b,s,s,p,w,p,w,o,p,n,y,d e,f,f,g,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,n,v,d p,x,y,g,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,v,d p,f,y,y,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,v,p p,f,f,y,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,v,d p,f,f,g,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,v,p p,f,f,g,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,y,p p,f,y,g,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,y,g p,f,s,b,t,f,f,c,b,w,t,b,f,f,w,w,p,w,o,p,h,s,u e,f,f,e,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,n,y,d p,x,y,n,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d e,x,y,g,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,n,v,d p,x,f,g,f,c,f,w,n,n,e,b,s,s,w,w,p,w,o,p,k,v,d p,x,f,p,f,c,f,w,n,n,e,b,s,s,w,w,p,w,o,p,n,v,d p,x,y,n,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l p,f,f,g,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,y,p p,x,f,y,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,v,g p,x,s,g,t,f,f,c,b,w,t,b,s,f,w,w,p,w,o,p,h,s,u p,f,y,g,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,y,p p,x,f,y,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,y,d p,f,y,g,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,y,p p,f,f,g,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,y,d p,f,y,g,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,y,d p,x,y,g,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,y,g p,f,f,g,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,y,g p,x,f,y,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,y,g p,f,f,y,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,v,g p,x,f,y,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,v,g p,x,f,y,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,y,g p,x,y,y,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,v,g p,f,s,g,t,f,f,c,b,h,t,b,s,s,w,w,p,w,o,p,h,v,u p,x,f,y,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,y,g p,f,f,y,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,y,g p,f,y,g,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,y,d p,f,f,y,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,y,d p,f,f,y,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,v,d p,x,y,g,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,v,p p,x,y,g,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,y,p e,f,y,e,t,n,f,c,b,p,t,b,s,s,w,w,p,w,o,p,n,v,d p,f,f,y,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,v,d p,f,f,g,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,y,d p,f,y,g,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,v,p p,x,f,y,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,v,g p,x,f,y,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,v,p p,x,f,g,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,y,d p,x,y,y,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,y,p p,f,s,w,t,f,f,c,b,p,t,b,f,f,w,w,p,w,o,p,h,s,u p,f,f,y,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,v,g p,f,f,y,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,v,d p,f,y,g,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,y,p p,f,f,y,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,y,d p,f,f,y,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,v,d p,f,f,g,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,v,p p,x,y,g,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,y,g p,x,f,y,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,y,p p,f,f,g,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,v,g p,x,f,y,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,y,d p,f,y,g,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,v,d p,x,y,y,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,v,d p,x,s,w,t,f,f,c,b,h,t,b,f,s,w,w,p,w,o,p,h,s,g p,f,f,g,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,y,g p,x,s,b,t,f,f,c,b,p,t,b,f,s,w,w,p,w,o,p,h,s,g p,f,y,g,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,v,d p,x,y,g,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,v,d p,x,f,y,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,y,g p,x,f,y,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,y,g p,x,y,y,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,v,g e,f,y,g,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,n,y,d p,f,y,y,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,y,p p,x,y,g,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,y,p p,f,f,y,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,v,g p,f,y,y,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,v,p p,f,f,y,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,y,d p,x,y,g,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,v,p p,f,f,g,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,y,g p,x,y,g,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,y,p p,x,f,p,f,c,f,c,n,p,e,b,s,s,w,w,p,w,o,p,k,s,d p,x,y,y,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,y,d p,x,f,y,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,y,g p,f,f,y,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,y,g p,x,y,g,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,v,g p,f,f,g,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,v,g p,x,y,g,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,v,d p,x,f,y,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,y,g p,x,f,y,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,v,p p,x,y,g,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,y,d p,x,y,y,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,v,d p,f,y,g,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,y,p p,f,y,g,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,v,d p,x,f,y,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,y,p e,k,y,n,f,n,f,w,n,w,e,b,f,f,w,n,p,w,o,e,w,v,l p,f,f,g,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,y,p p,x,y,y,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,y,g p,f,f,y,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,y,g p,x,y,g,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,v,d p,x,f,g,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,y,p p,f,f,y,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,v,g e,f,s,p,t,n,f,c,b,e,e,?,s,s,w,w,p,w,t,e,w,c,w p,f,f,y,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,v,p p,x,f,y,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,y,d p,x,y,g,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,y,d p,f,y,g,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,y,p p,x,f,y,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,v,d p,f,y,g,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,y,g p,f,y,g,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,v,g e,k,s,p,t,n,f,c,b,e,e,?,s,s,w,e,p,w,t,e,w,c,w p,x,f,y,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,v,d p,f,f,y,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,v,p p,f,f,g,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,y,p p,f,f,g,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,v,g p,x,f,y,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,y,p p,f,f,g,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,y,p p,x,y,g,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,y,g p,f,y,y,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,y,g p,f,f,g,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,y,d p,x,f,y,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,v,d p,f,f,g,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,v,g p,f,f,g,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,y,d p,f,f,y,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,y,g e,f,y,g,t,n,f,c,b,w,t,b,s,s,p,w,p,w,o,p,n,y,d p,f,y,g,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,y,d p,f,y,g,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,v,d p,f,y,g,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,v,g p,x,y,y,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,v,g p,x,y,g,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,y,g p,x,y,y,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,y,p p,f,f,y,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,y,d p,x,f,y,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,v,g p,x,y,y,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,y,p p,f,f,g,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,v,g p,x,f,y,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,v,d p,f,f,g,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,v,g p,f,y,g,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,y,d p,f,f,g,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,y,g p,f,y,y,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,v,g p,f,f,g,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,y,g p,x,f,y,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,y,p p,f,y,g,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,y,g p,f,y,g,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,y,g p,f,y,g,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,v,p e,x,y,r,f,n,f,c,n,p,e,?,s,f,w,w,p,w,o,f,h,v,d p,f,y,y,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,y,g p,x,f,y,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,y,d p,x,y,n,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p p,f,y,y,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,v,d p,k,y,n,f,n,f,c,n,w,e,?,k,y,w,n,p,w,o,e,w,v,d p,f,f,y,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,y,d p,x,y,g,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,v,d p,x,y,g,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,y,g p,f,y,g,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,y,g p,x,f,y,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,v,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,v,d p,x,y,g,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,v,d p,x,y,g,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,y,g p,x,y,g,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,y,g e,f,y,e,t,n,f,c,b,w,t,b,s,s,g,p,p,w,o,p,k,y,d p,f,f,y,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,y,p p,x,y,y,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,v,g p,f,f,y,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,v,g p,x,f,y,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,v,p p,f,f,g,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,y,g p,f,f,g,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,v,g p,x,y,y,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,y,g p,f,s,b,t,f,f,c,b,w,t,b,s,s,w,w,p,w,o,p,h,s,u p,x,y,g,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,v,g p,x,y,y,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,v,p p,f,f,g,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,v,p p,f,y,g,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,y,d p,f,f,y,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,v,d p,f,y,g,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,y,g p,x,y,g,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,v,g e,x,s,e,t,n,f,c,b,e,e,?,s,s,w,e,p,w,t,e,w,c,w p,f,f,g,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,v,d p,f,f,y,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,y,d p,f,y,g,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,y,d p,x,y,y,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,y,p p,f,y,g,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,v,d p,x,f,y,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,y,g p,b,y,w,t,n,f,w,n,w,e,b,s,s,w,w,p,w,o,p,w,c,l p,f,s,b,t,f,f,c,b,h,t,b,s,s,w,w,p,w,o,p,h,v,u p,x,y,y,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,y,p p,f,y,g,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,y,d p,f,y,g,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,v,p p,f,y,y,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,v,p p,f,f,g,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,y,d p,x,y,y,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,v,d p,x,f,y,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,v,g p,f,f,g,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,y,g p,x,s,w,t,f,f,c,b,w,t,b,f,f,w,w,p,w,o,p,h,s,u e,f,y,g,t,n,f,c,b,n,t,b,s,s,g,p,p,w,o,p,n,v,d p,x,y,n,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d p,f,y,g,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,y,d p,f,f,g,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,y,g e,f,y,e,t,n,f,c,b,n,t,b,s,s,p,g,p,w,o,p,k,v,d e,x,y,b,t,n,f,c,b,e,e,?,s,s,w,e,p,w,t,e,w,c,w p,x,y,y,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,y,g p,x,y,y,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,y,d p,x,y,y,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,v,p p,x,y,y,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,y,g p,f,f,y,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,y,g p,f,y,g,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,y,g p,x,f,g,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,y,g p,f,y,y,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,v,g p,x,y,g,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,v,g p,x,y,y,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,y,g p,f,y,g,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,y,p p,f,y,y,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,y,g p,x,y,g,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,y,d p,f,y,g,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,v,d p,f,y,g,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,y,p e,x,y,u,f,n,f,c,n,h,e,?,s,f,w,w,p,w,o,f,h,y,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,v,g p,f,f,y,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,v,g p,f,f,y,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,y,g p,x,f,y,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,v,g p,f,f,y,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,v,g p,f,f,g,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,v,g p,f,y,g,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,y,d p,f,f,g,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,v,g p,f,f,y,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,y,d p,f,y,y,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,v,p p,f,f,g,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,v,p p,f,y,g,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,y,g p,f,f,y,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,y,d e,f,f,e,t,n,f,c,b,u,t,b,s,s,g,w,p,w,o,p,n,y,d p,f,s,b,t,f,f,c,b,h,t,b,s,f,w,w,p,w,o,p,h,v,u p,f,y,g,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,v,d p,f,f,g,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,v,p p,x,y,y,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,y,g p,f,f,y,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,y,p p,f,y,y,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,v,d e,f,y,n,t,n,f,c,b,u,t,b,s,s,w,g,p,w,o,p,k,v,d p,f,y,y,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,y,g e,x,s,b,t,n,f,c,b,e,e,?,s,s,w,w,p,w,t,e,w,c,w p,x,y,y,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,y,g p,x,f,y,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,y,d p,x,y,y,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,y,g p,f,y,g,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,v,p e,f,f,e,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,k,y,d p,f,f,y,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,v,d p,f,f,y,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,v,g p,x,y,y,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,v,d p,x,f,y,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,v,g p,x,y,n,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,f,f,y,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,v,p p,x,y,y,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,v,g p,f,f,y,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,v,p p,f,f,y,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,v,d p,f,y,g,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,v,p p,f,y,g,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,v,g p,f,y,g,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,v,d p,f,f,g,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,v,g p,x,s,g,f,c,f,c,n,p,e,b,s,s,w,w,p,w,o,p,k,v,d p,x,y,y,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,y,g p,f,s,g,t,f,f,c,b,h,t,b,f,f,w,w,p,w,o,p,h,s,u p,x,y,g,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,v,g p,x,y,y,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,y,p p,x,y,y,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,y,d e,f,y,g,t,n,f,c,b,u,t,b,s,s,p,g,p,w,o,p,k,y,d p,f,f,g,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,y,d p,f,y,y,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,v,g p,f,y,g,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,y,p p,x,y,y,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,y,g p,x,y,g,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,y,d p,x,f,y,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,y,p e,f,y,n,t,n,f,c,b,n,t,b,s,s,g,g,p,w,o,p,n,v,d p,x,y,g,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,y,g p,f,f,y,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,v,g p,x,y,g,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,v,p p,x,y,y,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,y,g p,f,f,g,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,y,p p,f,f,g,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,y,g p,x,y,y,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,y,g e,k,y,b,t,n,f,c,b,e,e,?,s,s,e,e,p,w,t,e,w,c,w p,x,y,y,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,y,p p,x,y,n,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d p,f,y,g,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,y,p p,x,y,g,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,y,p p,f,y,y,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,v,g p,f,y,g,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,v,d p,f,f,g,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,y,g p,f,y,y,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,y,g p,x,f,y,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,y,d p,x,s,w,t,f,f,c,b,p,t,b,f,f,w,w,p,w,o,p,h,v,u p,x,y,y,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,v,g p,f,f,y,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,y,p p,x,f,y,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,y,g p,x,y,y,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,v,p p,f,y,y,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,v,g p,x,y,y,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,y,g p,x,y,y,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,v,p p,f,y,g,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,y,p p,f,f,y,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,y,p p,f,f,g,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,v,p e,f,y,n,t,n,f,c,b,p,t,b,s,s,w,p,p,w,o,p,k,y,d p,x,y,y,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,v,d p,x,y,g,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,v,p p,f,y,g,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,v,g p,f,y,g,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,v,g p,x,y,y,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,y,d p,f,f,g,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,v,p p,x,y,g,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,v,d p,x,y,y,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,v,d p,x,f,y,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,y,d p,f,f,y,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,y,d e,f,f,c,f,n,f,w,n,w,e,b,s,f,w,n,p,w,o,e,w,v,l p,f,y,g,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,v,g p,x,y,g,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,y,p p,f,f,y,f,n,f,c,n,w,e,?,k,y,w,y,p,w,o,e,w,v,d p,f,f,y,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,y,p p,x,s,g,t,f,f,c,b,p,t,b,f,s,w,w,p,w,o,p,h,v,g e,f,s,n,t,n,f,c,b,e,e,?,s,s,w,w,p,w,t,e,w,c,w p,x,y,n,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p p,x,s,g,f,c,f,w,n,u,e,b,s,s,w,w,p,w,o,p,k,v,d p,x,f,y,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,y,d p,f,y,g,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,v,g p,f,y,g,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,y,d p,x,y,y,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,v,g p,x,y,y,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,v,g p,x,y,g,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,y,d p,f,y,g,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,y,d p,f,y,g,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,y,g p,f,f,y,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,y,g p,x,f,y,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,v,d p,f,f,y,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,v,p p,f,f,g,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,y,p p,f,f,y,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,y,p p,f,y,y,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,y,d p,f,f,y,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,v,p p,f,f,y,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,v,d p,x,y,g,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,v,g p,x,y,g,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,v,g p,x,y,g,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,v,d e,x,s,b,t,n,f,c,b,w,e,?,s,s,e,w,p,w,t,e,w,c,w p,f,f,g,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,v,d p,x,f,y,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,v,d p,x,y,n,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l p,x,y,g,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,y,d p,f,y,g,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,v,p p,f,y,g,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,y,d p,f,f,y,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,y,g p,x,y,y,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,v,d p,x,f,y,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,v,g p,f,f,g,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,y,p p,x,y,g,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,v,p p,f,f,y,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,y,g p,x,f,y,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,y,g e,x,y,u,f,n,f,c,n,h,e,?,s,f,w,w,p,w,o,f,h,v,d e,f,y,b,t,n,f,c,b,e,e,?,s,s,e,e,p,w,t,e,w,c,w p,f,y,y,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,y,d p,x,y,y,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,y,p p,x,y,g,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,v,g p,f,f,g,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,y,d p,f,y,g,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,v,g p,f,f,g,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,y,g p,f,y,g,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,v,g p,x,f,y,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,y,g p,f,f,y,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,v,d p,f,f,g,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,v,d p,f,y,y,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,v,g p,f,y,y,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,y,g p,f,f,g,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,v,g p,f,s,b,t,f,f,c,b,w,t,b,s,f,w,w,p,w,o,p,h,v,g p,f,s,w,t,n,f,c,b,g,e,b,s,s,w,w,p,w,t,p,r,v,m p,x,y,y,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,y,p p,f,f,y,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,v,p p,f,y,g,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,v,g p,x,y,y,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,v,d p,x,f,y,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,v,p p,x,f,y,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,y,d e,f,f,g,t,n,f,c,b,u,t,b,s,s,g,g,p,w,o,p,n,v,d e,x,y,u,f,n,f,c,n,u,e,?,s,f,w,w,p,w,o,f,h,v,d p,x,y,g,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,y,d p,f,f,y,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,v,g p,x,y,y,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,v,d p,f,y,g,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,v,d p,x,y,y,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,y,p p,x,f,y,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,v,d p,x,y,y,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,y,p p,f,f,y,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,v,g p,x,y,g,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,y,p p,f,y,g,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,y,g p,f,y,g,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,v,p p,x,f,y,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,y,p e,f,f,e,t,n,f,c,b,w,t,b,s,s,w,g,p,w,o,p,n,v,d p,x,y,y,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,y,d p,f,f,g,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,v,d p,x,y,g,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,y,p p,f,y,g,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,v,p p,f,f,g,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,y,p p,f,f,g,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,y,d p,f,f,g,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,v,g p,f,y,g,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,y,d p,f,f,y,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,v,d p,x,f,y,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,y,d p,x,y,g,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,v,p p,x,y,g,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,y,p p,x,f,w,f,c,f,c,n,g,e,b,s,s,w,w,p,w,o,p,n,v,d p,f,f,g,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,y,d p,x,f,y,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,v,p p,f,y,g,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,v,d p,x,f,y,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,v,g p,f,y,g,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,v,d p,f,y,g,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,v,d p,f,f,y,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,y,p p,x,y,g,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,v,g p,f,y,y,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,v,g p,f,f,y,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,y,p p,x,f,y,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,v,d p,f,f,y,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,v,g p,x,y,y,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,y,p p,f,f,y,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,y,d p,x,f,y,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,v,g p,f,y,g,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,y,d p,f,f,g,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,y,d p,f,f,y,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,v,g p,f,f,g,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,v,d p,f,f,g,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,y,g p,f,f,y,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,v,d p,x,y,y,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,y,d p,x,y,y,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,v,d p,f,f,y,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,y,d p,x,y,y,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,v,d p,x,y,y,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,v,g p,x,y,n,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d e,f,y,b,t,n,f,c,b,w,e,?,s,s,w,w,p,w,t,e,w,c,w p,x,f,y,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,v,g p,x,y,y,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,y,d p,f,y,g,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,y,d p,x,y,y,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,y,d p,f,y,g,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,v,p p,f,y,g,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,y,d p,f,f,g,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,v,p p,x,f,y,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,v,p p,f,f,y,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,y,g p,f,f,y,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,y,d p,f,y,g,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,v,p p,f,y,g,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,y,g p,f,f,g,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,y,g p,f,y,g,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,v,d p,f,f,g,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,v,d p,f,y,g,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,v,p p,x,f,g,f,c,f,c,n,u,e,b,s,s,w,w,p,w,o,p,k,s,d p,f,s,b,t,f,f,c,b,w,t,b,f,f,w,w,p,w,o,p,h,v,g e,f,f,e,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,k,v,d p,x,y,y,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,v,p p,x,y,g,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,y,d p,f,y,g,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,v,g e,f,f,g,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,k,v,d p,x,y,y,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,y,d p,x,y,y,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,v,p p,f,f,y,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,y,p p,x,f,y,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,v,p p,x,f,y,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,y,d p,x,y,g,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,v,g p,f,s,w,t,f,f,c,b,w,t,b,s,f,w,w,p,w,o,p,h,s,u p,x,y,g,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,v,d p,x,f,y,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,v,g p,f,y,g,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,y,p p,x,y,g,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,v,p p,x,f,y,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,v,d e,f,y,u,f,n,f,c,n,h,e,?,s,f,w,w,p,w,o,f,h,v,d p,f,f,y,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,y,d p,f,y,g,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,v,g p,x,y,y,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,y,g p,f,f,g,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,y,g e,f,y,n,t,n,f,c,b,n,t,b,s,s,p,p,p,w,o,p,n,y,d p,x,f,y,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,v,p p,f,f,g,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,y,d p,x,y,g,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,y,p p,f,f,y,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,y,g p,x,f,y,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,v,d p,x,y,y,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,v,p p,x,f,y,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,v,p p,f,y,g,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,v,g p,x,s,w,t,f,f,c,b,h,t,b,f,f,w,w,p,w,o,p,h,s,u e,f,y,e,t,n,f,c,b,w,e,?,s,s,w,w,p,w,t,e,w,c,w e,x,y,u,f,n,f,c,n,w,e,?,s,f,w,w,p,w,o,f,h,y,d p,x,y,y,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,v,g p,x,y,g,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,y,d p,x,f,y,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,y,p p,f,f,g,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,y,d p,x,y,g,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,y,p p,f,f,g,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,y,g p,f,f,y,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,y,g p,x,y,g,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,y,p p,f,y,g,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,y,p e,f,s,p,t,n,f,c,b,w,e,?,s,s,w,e,p,w,t,e,w,c,w p,f,f,g,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,y,p p,x,y,y,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,y,p p,x,y,g,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,y,p p,f,f,y,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,v,g p,x,f,y,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,y,d p,f,y,g,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,y,d p,f,y,y,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,y,p p,x,y,g,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,y,g p,x,y,g,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,y,d p,f,f,y,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,y,p p,f,f,g,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,y,d p,x,y,g,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,y,p p,f,f,y,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,v,p p,f,y,g,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,v,d p,x,y,g,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,y,g p,f,f,g,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,v,d p,x,y,g,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,y,g p,f,f,g,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,v,d p,x,y,y,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,y,p p,x,f,y,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,y,g p,x,y,g,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,v,p p,f,f,y,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,v,p e,f,y,n,t,n,f,c,b,n,t,b,s,s,w,g,p,w,o,p,n,y,d p,f,f,g,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,y,d p,x,y,y,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,y,p p,x,s,g,t,f,f,c,b,h,t,b,f,f,w,w,p,w,o,p,h,s,g p,f,y,y,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,v,p p,x,y,y,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,v,p p,x,f,w,f,c,f,c,n,g,e,b,s,s,w,w,p,w,o,p,k,s,d p,x,f,y,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,y,d p,f,s,b,t,f,f,c,b,h,t,b,f,s,w,w,p,w,o,p,h,s,u p,x,y,y,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,y,g p,x,y,g,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,y,d p,f,f,y,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,y,g p,f,s,p,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,r,v,g p,f,s,b,t,f,f,c,b,p,t,b,f,f,w,w,p,w,o,p,h,v,u p,x,y,g,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,v,g p,x,y,g,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,y,g p,x,y,g,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,v,g p,f,f,g,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,y,p p,f,f,g,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,v,p p,x,f,y,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,y,p p,f,f,y,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,v,p e,f,y,u,f,n,f,c,n,u,e,?,s,f,w,w,p,w,o,f,h,v,d p,x,f,y,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,y,g e,f,f,e,t,n,f,c,b,w,t,b,s,s,g,w,p,w,o,p,n,v,d p,f,f,y,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,y,g p,x,f,y,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,v,g p,x,y,n,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l p,x,y,g,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,y,g p,x,f,y,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,y,d p,f,f,g,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,y,g p,x,y,g,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,v,p p,x,y,g,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,y,g p,x,f,y,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,y,d p,f,f,y,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,y,g p,f,y,g,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,v,p p,f,y,g,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,y,g e,f,y,n,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,n,y,d p,x,y,y,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,v,g e,f,f,e,t,n,f,c,b,w,t,b,s,s,w,w,p,w,o,p,k,y,d p,x,f,y,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,y,d p,x,y,g,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,y,p p,f,y,g,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,y,p p,x,f,y,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,y,p p,f,f,g,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,v,d p,f,f,g,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,v,d p,f,y,g,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,y,p p,f,y,g,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,y,g p,x,f,y,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,v,d p,x,y,y,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,y,p p,f,f,y,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,v,d p,x,y,g,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,y,d p,f,f,y,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,y,p p,f,y,g,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,v,d p,x,f,p,f,c,f,w,n,p,e,b,s,s,w,w,p,w,o,p,k,s,d p,f,f,y,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,v,d p,x,y,g,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,v,d p,x,y,y,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,y,g p,x,y,g,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,v,d p,f,y,y,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,v,p p,x,y,g,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,y,p p,x,f,y,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,v,d p,f,y,g,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,v,d p,f,y,g,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,v,g p,x,y,y,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,y,d p,f,f,y,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,y,d p,x,y,g,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,v,d p,x,y,y,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,y,d p,x,y,g,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,v,d p,x,y,g,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,y,g p,x,f,y,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,v,g p,x,y,g,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,y,d p,f,f,g,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,y,p p,f,f,g,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,v,g p,x,y,g,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,v,p p,x,f,y,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,v,d p,x,y,g,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,y,d p,f,f,g,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,v,p p,x,y,y,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,v,p p,x,f,y,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,v,d p,f,y,g,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,y,d p,f,f,g,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,v,p e,x,s,p,t,n,f,c,b,e,e,?,s,s,w,w,p,w,t,e,w,c,w p,f,f,y,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,v,d p,x,s,p,f,c,f,w,n,g,e,b,s,s,w,w,p,w,o,p,k,v,d p,x,f,y,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,y,g p,f,f,g,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,y,p p,x,f,y,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,y,g e,f,f,e,t,n,f,c,b,p,t,b,s,s,p,p,p,w,o,p,n,y,d p,x,y,y,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,v,d p,x,f,y,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,y,g p,f,y,g,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,v,g p,f,f,y,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,y,g e,f,y,n,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,n,v,d p,x,y,y,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,y,p p,f,f,g,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,v,p p,x,y,y,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,v,p p,f,f,y,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,y,d p,f,y,y,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,y,d p,f,y,g,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,v,g p,f,f,g,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,v,g p,x,y,y,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,y,g p,f,y,g,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,y,p p,x,y,y,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,y,g e,f,f,g,t,n,f,c,b,u,t,b,s,s,w,w,p,w,o,p,n,y,d p,x,s,g,t,f,f,c,b,h,t,b,f,s,w,w,p,w,o,p,h,s,g p,x,y,n,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p p,f,s,g,t,f,f,c,b,p,t,b,s,f,w,w,p,w,o,p,h,v,g p,f,y,g,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,y,g p,f,y,y,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,v,g p,f,y,g,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,v,d e,f,y,e,t,n,f,c,b,e,e,?,s,s,w,e,p,w,t,e,w,c,w p,f,y,g,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,v,p p,x,f,y,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,v,g p,f,f,g,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,y,d p,x,y,y,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,y,d p,f,f,y,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,y,g e,f,y,n,t,n,f,c,b,e,e,?,s,s,e,e,p,w,t,e,w,c,w p,f,y,g,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,v,g p,k,f,n,f,n,f,c,n,w,e,?,k,y,w,n,p,w,o,e,w,v,d p,f,f,g,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,v,d p,f,f,y,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,v,p p,x,y,n,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p p,f,f,g,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,v,d p,f,f,g,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,y,p p,f,s,w,t,f,f,c,b,w,t,b,f,f,w,w,p,w,o,p,h,v,g p,f,f,y,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,v,d p,x,y,g,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,y,g p,x,f,y,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,y,g e,x,y,e,t,n,f,c,b,w,e,?,s,s,e,e,p,w,t,e,w,c,w p,f,y,y,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,v,d p,b,f,y,f,n,f,c,n,w,e,?,k,y,w,n,p,w,o,e,w,v,d p,f,y,y,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,v,d p,x,s,g,t,f,f,c,b,p,t,b,f,f,w,w,p,w,o,p,h,s,u p,f,y,y,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,v,d p,f,f,y,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,v,g e,k,y,e,t,n,f,c,b,e,e,?,s,s,w,w,p,w,t,e,w,c,w p,f,f,y,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,v,p p,f,f,y,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,v,p e,k,y,n,f,n,f,w,n,w,e,b,f,s,w,n,p,w,o,e,w,v,l p,x,s,w,f,c,f,c,n,p,e,b,s,s,w,w,p,w,o,p,n,v,d p,x,f,y,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,y,g p,x,f,y,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,v,p p,x,f,y,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,y,d p,f,y,y,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,v,p p,b,s,b,t,n,f,c,b,g,e,b,s,s,w,w,p,w,t,p,r,v,g p,x,s,w,t,f,f,c,b,h,t,b,f,f,w,w,p,w,o,p,h,v,g e,f,y,e,t,n,f,c,b,n,t,b,s,s,w,p,p,w,o,p,n,y,d p,b,s,w,t,n,f,c,b,g,e,b,s,s,w,w,p,w,t,p,r,v,m e,f,y,p,t,n,f,c,b,w,e,?,s,s,e,e,p,w,t,e,w,c,w p,x,s,w,t,f,f,c,b,p,t,b,f,f,w,w,p,w,o,p,h,v,g e,k,y,n,t,n,f,c,b,w,e,?,s,s,w,w,p,w,t,e,w,c,w p,x,y,y,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,y,p p,f,s,b,t,f,f,c,b,h,t,b,f,s,w,w,p,w,o,p,h,v,u p,f,y,g,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,v,d p,x,y,y,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,v,d p,x,y,g,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,v,d p,x,f,y,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,y,p p,x,y,y,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,v,d p,x,y,y,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,y,d p,x,f,y,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,y,p p,x,y,g,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,y,p p,f,f,g,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,v,p e,k,s,e,t,n,f,c,b,w,e,?,s,s,e,w,p,w,t,e,w,c,w e,f,y,n,t,n,f,c,b,e,e,?,s,s,e,w,p,w,t,e,w,c,w e,f,s,b,t,n,f,c,b,w,e,?,s,s,e,w,p,w,t,e,w,c,w p,x,y,y,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,v,d e,f,f,g,t,n,f,c,b,u,t,b,s,s,p,p,p,w,o,p,n,v,d p,f,f,y,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,y,p p,f,y,g,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,y,g p,x,s,g,t,f,f,c,b,p,t,b,f,f,w,w,p,w,o,p,h,v,g p,f,f,g,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,v,p p,x,f,y,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,y,d p,f,f,y,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,v,g p,x,y,n,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l p,f,f,g,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,v,p e,f,y,n,t,n,f,c,b,e,e,?,s,s,w,w,p,w,t,e,w,c,w e,f,y,e,t,n,f,c,b,p,t,b,s,s,g,p,p,w,o,p,k,v,d p,f,y,g,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,y,g p,x,y,y,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,v,p p,f,f,g,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,y,d e,f,f,e,t,n,f,c,b,n,t,b,s,s,p,w,p,w,o,p,n,v,d p,x,y,y,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,v,p p,f,f,y,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,y,p p,f,f,g,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,v,p p,f,y,y,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,y,d p,x,y,g,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,v,d p,b,y,w,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,r,v,m p,f,f,y,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,y,p p,x,y,n,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d p,f,f,g,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,y,g p,x,y,y,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,v,g p,f,y,y,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,y,p e,f,y,p,t,n,f,c,b,e,e,?,s,s,e,e,p,w,t,e,w,c,w p,x,s,w,t,f,f,c,b,h,t,b,s,s,w,w,p,w,o,p,h,s,g p,f,y,g,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,y,g p,x,y,g,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,v,p p,x,f,y,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,v,g p,f,s,b,t,f,f,c,b,w,t,b,f,s,w,w,p,w,o,p,h,s,u p,x,f,g,f,c,f,c,n,g,e,b,s,s,w,w,p,w,o,p,k,v,d p,x,f,y,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,y,p p,f,y,g,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,y,g p,f,y,y,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,y,p e,x,y,r,f,n,f,c,n,p,e,?,s,f,w,w,p,w,o,f,h,y,d e,f,y,w,f,n,f,c,n,h,e,?,s,f,w,w,p,w,o,f,h,v,d p,x,f,y,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,v,d p,f,y,y,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,y,p p,f,y,y,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,y,g p,x,y,e,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p p,x,y,e,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l p,x,y,g,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,y,d p,x,y,y,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,v,g p,f,f,g,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,y,d p,x,y,g,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,y,g p,x,y,y,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,v,d p,f,f,y,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,y,p e,f,s,e,t,n,f,c,b,w,e,?,s,s,w,e,p,w,t,e,w,c,w p,f,f,y,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,y,p p,x,y,y,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,y,p p,f,s,g,t,f,f,c,b,p,t,b,f,s,w,w,p,w,o,p,h,s,g p,f,f,y,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,v,g p,x,y,y,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,y,d p,x,f,y,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,y,p p,x,s,g,t,f,f,c,b,h,t,b,f,f,w,w,p,w,o,p,h,v,u p,f,y,g,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,y,g p,f,f,g,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,v,g p,x,s,w,f,c,f,c,n,n,e,b,s,s,w,w,p,w,o,p,k,v,d p,f,y,g,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,y,p e,f,y,e,t,n,f,c,b,u,t,b,s,s,p,w,p,w,o,p,n,y,d p,x,f,y,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,y,g p,x,y,y,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,y,p e,k,s,b,t,n,f,c,b,e,e,?,s,s,w,w,p,w,t,e,w,c,w p,f,f,y,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,v,g p,f,f,y,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,v,d p,x,y,y,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,y,g e,x,f,n,f,n,f,w,n,w,e,b,s,f,w,n,p,w,o,e,w,v,l e,x,y,e,t,n,f,c,b,e,e,?,s,s,e,e,p,w,t,e,w,c,w p,x,y,g,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,v,p p,x,f,y,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,v,g p,f,s,g,t,f,f,c,b,h,t,b,f,f,w,w,p,w,o,p,h,v,g p,x,y,y,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,y,g p,f,y,g,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,v,p p,x,y,g,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,v,g p,x,y,n,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p e,k,s,b,t,n,f,c,b,w,e,?,s,s,e,w,p,w,t,e,w,c,w p,f,f,y,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,y,d p,x,f,g,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,v,p p,f,y,g,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,y,p p,x,f,y,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,v,d p,f,y,y,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,v,g e,k,s,p,t,n,f,c,b,w,e,?,s,s,e,e,p,w,t,e,w,c,w p,f,y,n,f,n,f,c,n,w,e,?,k,y,w,n,p,w,o,e,w,v,d p,x,y,g,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,y,d p,x,f,y,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,y,d p,x,y,g,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,v,p p,f,s,b,t,f,f,c,b,w,t,b,f,f,w,w,p,w,o,p,h,v,u e,f,s,b,t,n,f,c,b,w,e,?,s,s,w,w,p,w,t,e,w,c,w p,f,s,w,t,f,f,c,b,w,t,b,f,f,w,w,p,w,o,p,h,s,u p,f,y,g,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,y,p p,x,f,y,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,v,p p,f,y,g,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,v,p p,f,y,y,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,y,g p,f,f,y,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,v,d p,x,s,b,t,f,f,c,b,h,t,b,s,s,w,w,p,w,o,p,h,v,u p,f,f,g,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,y,p p,x,y,g,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,y,d p,f,f,y,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,y,g p,f,y,y,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,y,d p,f,s,g,t,f,f,c,b,p,t,b,s,f,w,w,p,w,o,p,h,s,u e,f,s,b,t,n,f,c,b,w,e,?,s,s,w,e,p,w,t,e,w,c,w e,x,s,p,t,n,f,c,b,w,e,?,s,s,e,e,p,w,t,e,w,c,w e,k,s,n,t,n,f,c,b,e,e,?,s,s,w,w,p,w,t,e,w,c,w p,f,y,p,t,n,f,c,b,g,e,b,s,s,w,w,p,w,t,p,r,v,g p,f,y,g,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,v,p p,x,y,y,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,v,p p,f,f,g,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,v,g p,f,f,g,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,y,d p,x,f,y,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,y,p p,f,f,g,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,v,d p,f,y,g,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,y,d p,f,y,y,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,v,d p,f,f,y,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,v,g p,f,y,y,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,y,g p,x,y,y,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,v,d p,x,y,y,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,y,p p,f,y,g,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,v,g p,f,f,g,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,y,d p,x,y,y,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,v,p p,x,y,y,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,y,p e,f,y,u,f,n,f,c,n,w,e,?,s,f,w,w,p,w,o,f,h,y,d p,f,f,g,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,v,g p,x,y,n,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l p,x,y,y,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,v,g p,x,y,y,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,y,p p,x,y,g,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,v,g p,f,f,y,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,v,d p,x,f,y,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,y,d p,x,y,g,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,v,p e,f,s,b,t,n,f,c,b,e,e,?,s,s,w,w,p,w,t,e,w,c,w p,f,f,g,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,y,p p,f,y,y,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,v,d e,x,s,n,t,n,f,c,b,w,e,?,s,s,w,e,p,w,t,e,w,c,w p,f,f,g,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,y,p p,x,y,g,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,v,d p,x,y,n,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,f,f,y,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,v,d p,x,y,n,f,n,f,c,n,w,e,?,k,y,w,n,p,w,o,e,w,v,d p,b,s,b,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,r,v,g p,f,f,y,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,v,d p,f,y,g,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,y,d e,f,y,u,f,n,f,c,n,u,e,?,s,f,w,w,p,w,o,f,h,y,d p,x,f,y,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,v,g p,f,y,y,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,y,g p,f,f,y,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,y,g p,x,y,y,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,y,d e,x,y,e,t,n,f,c,b,w,e,?,s,s,e,w,p,w,t,e,w,c,w p,f,f,g,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,v,g p,x,y,y,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,v,g p,x,y,y,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,v,p p,f,y,g,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,v,p e,k,s,b,t,n,f,c,b,w,e,?,s,s,w,e,p,w,t,e,w,c,w p,f,y,y,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,y,d p,x,y,g,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,v,p p,x,f,y,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,v,d p,f,f,y,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,v,p p,f,s,w,t,f,f,c,b,h,t,b,s,f,w,w,p,w,o,p,h,v,u p,x,s,g,f,c,f,c,n,p,e,b,s,s,w,w,p,w,o,p,n,v,d p,f,y,y,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,y,d e,f,y,u,f,n,f,c,n,p,e,?,s,f,w,w,p,w,o,f,h,v,d p,x,f,y,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,y,d p,f,y,g,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,y,d p,x,f,y,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,v,g p,x,f,y,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,v,p p,x,s,g,t,f,f,c,b,p,t,b,f,s,w,w,p,w,o,p,h,s,u p,f,y,g,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,y,d p,f,f,y,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,y,p p,f,f,y,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,y,d p,x,y,g,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,v,d p,x,y,g,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,v,g p,x,y,g,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,y,d p,x,f,g,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,y,g p,x,y,y,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,y,p p,f,f,g,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,v,g p,f,f,y,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,y,d p,x,y,g,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,y,p p,f,f,y,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,v,p p,x,y,n,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l p,x,f,y,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,y,p p,x,y,y,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,v,p p,f,s,b,t,f,f,c,b,w,t,b,f,s,w,w,p,w,o,p,h,v,g p,f,f,g,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,v,d p,f,y,y,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,y,p p,x,f,y,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,y,p p,f,f,g,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,v,d p,x,y,y,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,y,d p,x,y,g,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,v,d p,x,y,e,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l e,k,y,b,t,n,f,c,b,e,e,?,s,s,e,w,p,w,t,e,w,c,w e,f,y,b,t,n,f,c,b,w,e,?,s,s,e,w,p,w,t,e,w,c,w p,x,y,g,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,y,d p,f,f,y,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,y,p p,x,y,g,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,y,g p,f,y,g,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,y,g p,x,s,b,t,f,f,c,b,w,t,b,s,f,w,w,p,w,o,p,h,s,u p,f,y,y,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,v,p p,x,s,w,t,f,f,c,b,p,t,b,f,f,w,w,p,w,o,p,h,s,u p,x,f,y,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,v,p p,x,y,g,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,y,p p,x,s,w,t,f,f,c,b,p,t,b,s,f,w,w,p,w,o,p,h,s,u p,f,s,b,t,f,f,c,b,p,t,b,f,f,w,w,p,w,o,p,h,s,g p,x,s,w,t,f,f,c,b,h,t,b,f,s,w,w,p,w,o,p,h,s,u p,f,f,y,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,y,d p,f,y,g,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,y,p p,x,f,y,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,v,g p,f,f,g,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,v,p e,x,y,w,f,n,f,c,n,u,e,?,s,f,w,w,p,w,o,f,h,y,d e,x,s,e,t,n,f,c,b,e,e,?,s,s,w,w,p,w,t,e,w,c,w p,x,y,g,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,v,g p,f,f,g,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,v,g p,x,y,n,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l p,x,y,g,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,v,p p,f,f,g,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,y,p p,f,f,y,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,v,p p,f,f,y,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,y,d e,f,f,e,t,n,f,c,b,n,t,b,s,s,g,w,p,w,o,p,n,y,d p,x,y,y,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,y,g p,f,y,y,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,v,d p,f,f,g,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,v,p p,x,y,y,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,y,g p,x,f,y,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,y,p p,k,f,y,f,n,f,c,n,w,e,?,k,y,w,n,p,w,o,e,w,v,d p,f,f,y,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,y,g e,k,f,c,f,n,f,w,n,w,e,b,f,s,w,n,p,w,o,e,w,v,l p,f,f,g,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,v,p p,f,y,y,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,y,p p,x,y,g,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,v,d p,x,y,g,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,v,p p,f,f,y,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,v,g p,f,y,y,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,v,d p,x,f,y,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,y,d p,f,f,y,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,v,p p,x,y,y,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,y,d p,b,y,p,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,r,v,g e,k,y,p,t,n,f,c,b,e,e,?,s,s,w,w,p,w,t,e,w,c,w p,x,y,y,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,v,p p,x,f,y,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,v,g e,k,y,b,t,n,f,c,b,e,e,?,s,s,w,e,p,w,t,e,w,c,w p,f,y,y,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,y,d p,x,s,w,t,f,f,c,b,p,t,b,s,s,w,w,p,w,o,p,h,s,u p,x,y,n,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p p,x,y,n,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d p,x,y,e,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p p,f,g,w,t,n,f,w,n,w,e,b,s,s,w,w,p,w,o,p,w,c,l p,x,s,g,t,f,f,c,b,p,t,b,f,s,w,w,p,w,o,p,h,v,u e,f,y,c,f,n,f,w,n,w,e,b,f,s,w,n,p,w,o,e,w,v,l p,x,y,g,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,y,g p,f,y,y,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,v,d p,f,y,y,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,y,p e,f,y,p,t,n,f,c,b,w,e,?,s,s,w,e,p,w,t,e,w,c,w p,x,s,b,t,f,f,c,b,w,t,b,f,s,w,w,p,w,o,p,h,v,g p,x,s,g,t,f,f,c,b,h,t,b,s,f,w,w,p,w,o,p,h,s,g p,x,y,e,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p e,k,y,c,f,n,f,w,n,w,e,b,s,f,w,n,p,w,o,e,w,v,l p,x,s,w,t,f,f,c,b,w,t,b,s,f,w,w,p,w,o,p,h,s,u p,x,s,w,t,f,f,c,b,h,t,b,s,f,w,w,p,w,o,p,h,v,g p,f,s,b,t,f,f,c,b,w,t,b,s,f,w,w,p,w,o,p,h,v,u p,f,s,b,t,f,f,c,b,p,t,b,s,s,w,w,p,w,o,p,h,v,g e,k,y,c,f,n,f,w,n,w,e,b,f,s,w,n,p,w,o,e,w,v,l p,x,y,g,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,v,d p,f,s,w,t,f,f,c,b,h,t,b,f,f,w,w,p,w,o,p,h,v,g p,f,s,g,t,f,f,c,b,w,t,b,s,s,w,w,p,w,o,p,h,s,u p,c,g,w,t,n,f,w,n,w,e,b,s,s,w,w,p,w,o,p,w,c,l p,x,s,g,t,f,f,c,b,p,t,b,s,f,w,w,p,w,o,p,h,s,u p,b,g,w,t,n,f,w,n,w,e,b,s,s,w,w,p,w,o,p,w,c,l p,x,s,b,t,f,f,c,b,p,t,b,s,s,w,w,p,w,o,p,h,v,g p,f,s,w,t,f,f,c,b,h,t,b,f,f,w,w,p,w,o,p,h,s,u p,b,f,y,f,n,f,c,n,w,e,?,k,y,w,y,p,w,o,e,w,v,d p,x,y,n,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d p,x,y,n,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d e,k,s,n,t,n,f,c,b,w,e,?,s,s,e,w,p,w,t,e,w,c,w e,k,y,b,t,n,f,c,b,w,e,?,s,s,e,e,p,w,t,e,w,c,w p,f,s,w,t,f,f,c,b,w,t,b,s,s,w,w,p,w,o,p,h,v,g p,f,s,b,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,r,v,m p,f,y,y,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,y,p p,x,y,g,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,y,g p,f,s,b,t,n,f,c,b,r,e,b,s,s,w,w,p,w,t,p,r,v,g p,x,y,n,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p p,x,y,e,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,f,f,g,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,y,d e,x,s,e,t,n,f,c,b,e,e,?,s,s,e,w,p,w,t,e,w,c,w p,x,y,n,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l p,x,f,y,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,y,g p,x,y,n,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d e,f,f,n,f,n,f,w,n,w,e,b,s,f,w,n,p,w,o,e,w,v,l p,x,y,n,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p e,x,s,b,t,n,f,c,b,e,e,?,s,s,e,e,p,w,t,e,w,c,w e,f,y,n,t,n,f,c,b,w,e,?,s,s,w,e,p,w,t,e,w,c,w p,f,y,y,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,y,p p,f,y,b,t,n,f,c,b,r,e,b,s,s,w,w,p,w,t,p,r,v,m p,x,y,n,f,n,f,c,n,w,e,?,k,y,w,y,p,w,o,e,w,v,d p,x,y,n,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l p,x,s,b,t,f,f,c,b,w,t,b,s,s,w,w,p,w,o,p,h,s,g p,x,s,b,t,f,f,c,b,h,t,b,f,s,w,w,p,w,o,p,h,v,g p,f,y,y,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,y,p p,f,s,g,t,f,f,c,b,w,t,b,s,f,w,w,p,w,o,p,h,v,g p,x,y,n,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l p,x,s,b,t,f,f,c,b,p,t,b,f,s,w,w,p,w,o,p,h,v,g p,f,f,n,f,n,f,c,n,w,e,?,k,y,w,y,p,w,o,e,w,v,d e,x,y,e,t,n,f,c,b,w,e,?,s,s,w,w,p,w,t,e,w,c,w p,f,s,b,t,f,f,c,b,w,t,b,f,f,w,w,p,w,o,p,h,s,g p,f,s,w,t,f,f,c,b,p,t,b,f,s,w,w,p,w,o,p,h,s,g e,k,y,e,t,n,f,c,b,w,e,?,s,s,e,e,p,w,t,e,w,c,w p,x,f,y,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,y,p p,x,f,n,f,n,f,c,n,w,e,?,k,y,w,n,p,w,o,e,w,v,d e,x,y,n,t,n,f,c,b,e,e,?,s,s,e,w,p,w,t,e,w,c,w p,x,y,g,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,y,g p,f,s,b,t,f,f,c,b,h,t,b,f,s,w,w,p,w,o,p,h,v,g p,f,s,b,t,f,f,c,b,h,t,b,f,s,w,w,p,w,o,p,h,s,g p,f,y,y,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,v,g p,f,y,y,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,v,d e,x,s,p,t,n,f,c,b,w,e,?,s,s,w,w,p,w,t,e,w,c,w e,f,s,p,t,n,f,c,b,e,e,?,s,s,e,e,p,w,t,e,w,c,w p,b,y,w,t,n,f,c,b,r,e,b,s,s,w,w,p,w,t,p,r,v,g e,x,y,c,f,n,f,w,n,w,e,b,f,f,w,n,p,w,o,e,w,v,l e,f,s,n,t,n,f,c,b,w,e,?,s,s,e,w,p,w,t,e,w,c,w p,x,s,b,t,f,f,c,b,h,t,b,f,s,w,w,p,w,o,p,h,v,u p,x,s,g,t,f,f,c,b,w,t,b,f,s,w,w,p,w,o,p,h,v,g p,f,y,y,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,y,d p,x,s,b,t,f,f,c,b,w,t,b,f,s,w,w,p,w,o,p,h,v,u p,x,s,w,t,f,f,c,b,p,t,b,s,s,w,w,p,w,o,p,h,s,g e,f,y,c,f,n,f,w,n,w,e,b,s,f,w,n,p,w,o,e,w,v,l p,x,y,e,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d p,f,f,y,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,y,d e,x,y,w,f,n,f,c,n,h,e,?,s,f,w,w,p,w,o,f,h,v,d p,x,y,y,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,v,p p,f,y,p,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,r,v,g p,f,s,g,t,f,f,c,b,h,t,b,f,s,w,w,p,w,o,p,h,v,u p,x,y,n,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d e,k,s,p,t,n,f,c,b,w,e,?,s,s,e,w,p,w,t,e,w,c,w p,x,y,n,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,x,y,g,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,v,p p,f,s,b,t,f,f,c,b,h,t,b,f,f,w,w,p,w,o,p,h,s,u e,k,y,p,t,n,f,c,b,e,e,?,s,s,w,e,p,w,t,e,w,c,w p,x,f,y,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,v,p p,f,y,g,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,v,g p,f,f,g,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,y,d p,x,s,b,t,f,f,c,b,p,t,b,s,f,w,w,p,w,o,p,h,s,g p,x,y,n,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p p,x,y,y,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,v,d p,f,f,y,f,f,f,c,b,h,e,b,k,k,n,n,p,w,o,l,h,v,d p,f,f,n,f,n,f,c,n,w,e,?,k,y,w,n,p,w,o,e,w,v,d e,k,s,b,t,n,f,c,b,w,e,?,s,s,w,w,p,w,t,e,w,c,w p,f,y,y,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,v,g p,x,y,e,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l p,x,s,g,t,f,f,c,b,h,t,b,f,f,w,w,p,w,o,p,h,s,u e,f,s,n,t,n,f,c,b,e,e,?,s,s,w,e,p,w,t,e,w,c,w p,x,y,g,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,v,p p,x,y,n,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d p,x,s,g,t,f,f,c,b,p,t,b,s,s,w,w,p,w,o,p,h,v,u p,x,s,g,t,f,f,c,b,h,t,b,f,s,w,w,p,w,o,p,h,v,g p,f,y,p,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,r,v,m e,k,y,b,t,n,f,c,b,w,e,?,s,s,e,w,p,w,t,e,w,c,w p,x,s,w,t,f,f,c,b,w,t,b,s,s,w,w,p,w,o,p,h,v,u p,x,y,n,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d e,k,y,n,t,n,f,c,b,w,e,?,s,s,e,w,p,w,t,e,w,c,w p,f,y,y,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,y,d e,x,y,p,t,n,f,c,b,w,e,?,s,s,e,e,p,w,t,e,w,c,w p,f,s,g,t,f,f,c,b,p,t,b,f,f,w,w,p,w,o,p,h,s,u e,x,s,p,t,n,f,c,b,e,e,?,s,s,w,e,p,w,t,e,w,c,w p,b,y,n,f,n,f,c,n,w,e,?,k,y,w,n,p,w,o,e,w,v,d 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p,x,y,n,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l p,x,s,w,t,f,f,c,b,h,t,b,f,s,w,w,p,w,o,p,h,v,u e,k,s,n,t,n,f,c,b,e,e,?,s,s,e,e,p,w,t,e,w,c,w p,f,y,g,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,y,g e,x,s,b,t,n,f,c,b,e,e,?,s,s,w,e,p,w,t,e,w,c,w p,f,s,w,t,f,f,c,b,w,t,b,f,s,w,w,p,w,o,p,h,s,u e,k,f,n,f,n,f,w,n,w,e,b,s,s,w,n,p,w,o,e,w,v,l p,x,y,n,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,f,s,w,t,f,f,c,b,h,t,b,f,s,w,w,p,w,o,p,h,v,g p,x,s,g,t,f,f,c,b,h,t,b,s,s,w,w,p,w,o,p,h,v,u p,k,y,y,f,n,f,c,n,w,e,?,k,y,w,y,p,w,o,e,w,v,d p,f,s,w,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,r,v,m p,f,f,y,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,y,p e,k,y,p,t,n,f,c,b,w,e,?,s,s,e,w,p,w,t,e,w,c,w p,f,y,w,t,n,f,w,n,w,e,b,s,s,w,w,p,w,o,p,w,c,l p,f,s,b,t,f,f,c,b,p,t,b,f,s,w,w,p,w,o,p,h,v,u e,f,y,w,f,n,f,c,n,u,e,?,s,f,w,w,p,w,o,f,h,y,d e,x,y,r,f,n,f,c,n,w,e,?,s,f,w,w,p,w,o,f,h,v,d e,x,s,b,t,n,f,c,b,w,e,?,s,s,w,e,p,w,t,e,w,c,w p,f,s,g,t,f,f,c,b,h,t,b,s,s,w,w,p,w,o,p,h,v,g p,x,y,e,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d p,f,y,y,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,y,p p,f,s,g,t,f,f,c,b,w,t,b,s,s,w,w,p,w,o,p,h,s,g p,f,s,b,t,f,f,c,b,h,t,b,s,s,w,w,p,w,o,p,h,s,g e,f,s,e,t,n,f,c,b,e,e,?,s,s,e,w,p,w,t,e,w,c,w p,x,y,e,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d p,f,f,g,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,y,g p,f,y,y,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,y,d e,x,s,n,t,n,f,c,b,e,e,?,s,s,e,w,p,w,t,e,w,c,w p,f,s,g,t,f,f,c,b,p,t,b,f,f,w,w,p,w,o,p,h,s,g p,x,y,n,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l p,f,s,w,t,f,f,c,b,p,t,b,s,s,w,w,p,w,o,p,h,s,g e,x,f,c,f,n,f,w,n,w,e,b,s,s,w,n,p,w,o,e,w,v,l p,f,s,g,t,f,f,c,b,w,t,b,f,s,w,w,p,w,o,p,h,v,g p,f,f,g,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,v,p e,x,y,r,f,n,f,c,n,w,e,?,s,f,w,w,p,w,o,f,h,y,d p,x,f,y,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,v,p p,x,y,n,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l p,x,y,n,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l e,f,y,e,t,n,f,c,b,w,e,?,s,s,e,w,p,w,t,e,w,c,w p,x,s,g,t,f,f,c,b,w,t,b,s,f,w,w,p,w,o,p,h,v,u e,k,y,n,t,n,f,c,b,w,e,?,s,s,w,e,p,w,t,e,w,c,w e,f,y,e,t,n,f,c,b,e,e,?,s,s,w,w,p,w,t,e,w,c,w p,x,y,n,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p p,b,y,n,f,n,f,c,n,w,e,?,k,y,w,y,p,w,o,e,w,v,d p,x,y,n,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p e,f,y,b,t,n,f,c,b,e,e,?,s,s,w,e,p,w,t,e,w,c,w p,x,s,w,t,f,f,c,b,h,t,b,f,s,w,w,p,w,o,p,h,v,g p,f,y,y,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,v,g e,f,y,n,t,n,f,c,b,w,e,?,s,s,w,w,p,w,t,e,w,c,w p,b,y,w,t,n,f,c,b,g,e,b,s,s,w,w,p,w,t,p,r,v,m e,x,y,n,f,n,f,w,n,w,e,b,s,f,w,n,p,w,o,e,w,v,l p,f,y,y,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,v,p p,x,s,b,t,f,f,c,b,h,t,b,f,s,w,w,p,w,o,p,h,s,g p,x,y,n,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l p,x,s,g,t,f,f,c,b,h,t,b,s,s,w,w,p,w,o,p,h,s,u p,f,s,g,t,f,f,c,b,w,t,b,s,f,w,w,p,w,o,p,h,s,u p,x,y,n,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p e,f,y,w,f,n,f,c,n,p,e,?,s,f,w,w,p,w,o,f,h,v,d p,x,y,n,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l p,f,f,g,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,v,g p,x,y,e,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l p,x,s,w,t,f,f,c,b,w,t,b,s,s,w,w,p,w,o,p,h,v,g p,f,y,g,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,v,d p,x,s,w,t,f,f,c,b,h,t,b,s,f,w,w,p,w,o,p,h,s,u p,k,y,y,f,n,f,c,n,w,e,?,k,y,w,n,p,w,o,e,w,v,d p,f,s,w,t,f,f,c,b,w,t,b,s,f,w,w,p,w,o,p,h,v,u p,f,s,g,t,f,f,c,b,h,t,b,f,f,w,w,p,w,o,p,h,v,u e,x,y,c,f,n,f,w,n,w,e,b,f,s,w,n,p,w,o,e,w,v,l p,x,s,w,t,f,f,c,b,h,t,b,s,s,w,w,p,w,o,p,h,v,u p,x,y,n,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,f,y,p,t,n,f,c,b,r,e,b,s,s,w,w,p,w,t,p,r,v,g p,f,y,y,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,y,p e,x,s,p,t,n,f,c,b,e,e,?,s,s,e,e,p,w,t,e,w,c,w p,f,y,b,t,n,f,c,b,r,e,b,s,s,w,w,p,w,t,p,r,v,g p,x,f,y,f,n,f,c,n,w,e,?,k,y,w,n,p,w,o,e,w,v,d p,f,y,y,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,y,p e,f,f,n,f,n,f,w,n,w,e,b,f,f,w,n,p,w,o,e,w,v,l e,x,f,n,f,n,f,w,n,w,e,b,f,s,w,n,p,w,o,e,w,v,l p,x,y,n,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l p,f,s,g,t,f,f,c,b,p,t,b,f,s,w,w,p,w,o,p,h,v,u p,x,s,b,t,f,f,c,b,h,t,b,f,f,w,w,p,w,o,p,h,s,u p,f,s,g,t,f,f,c,b,w,t,b,s,s,w,w,p,w,o,p,h,v,g p,x,s,b,t,f,f,c,b,h,t,b,f,f,w,w,p,w,o,p,h,s,g e,x,y,r,f,n,f,c,n,h,e,?,s,f,w,w,p,w,o,f,h,v,d p,f,y,y,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,y,d p,f,s,g,t,f,f,c,b,h,t,b,f,s,w,w,p,w,o,p,h,s,u p,x,y,n,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p p,f,y,y,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,y,g p,f,s,w,t,f,f,c,b,w,t,b,f,f,w,w,p,w,o,p,h,v,u p,x,s,w,t,f,f,c,b,w,t,b,f,s,w,w,p,w,o,p,h,s,u p,f,y,g,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,y,p p,f,y,y,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,y,p p,x,y,n,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d p,x,y,y,f,n,f,c,n,w,e,?,k,y,w,n,p,w,o,e,w,v,d e,f,s,n,t,n,f,c,b,e,e,?,s,s,e,e,p,w,t,e,w,c,w p,f,y,y,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,y,d p,f,s,g,t,f,f,c,b,h,t,b,s,f,w,w,p,w,o,p,h,s,u p,x,y,n,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l p,f,y,y,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,v,d p,f,y,y,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,y,d p,f,s,w,t,f,f,c,b,h,t,b,s,s,w,w,p,w,o,p,h,s,u p,f,s,p,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,r,v,m p,f,y,y,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,y,g e,k,s,p,t,n,f,c,b,w,e,?,s,s,w,e,p,w,t,e,w,c,w p,x,s,b,t,f,f,c,b,h,t,b,s,s,w,w,p,w,o,p,h,s,g p,x,s,w,t,f,f,c,b,p,t,b,f,s,w,w,p,w,o,p,h,s,g p,x,s,w,t,f,f,c,b,h,t,b,f,f,w,w,p,w,o,p,h,s,g p,x,y,n,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d p,b,y,p,t,n,f,c,b,r,e,b,s,s,w,w,p,w,t,p,r,v,m p,x,s,b,t,f,f,c,b,h,t,b,f,s,w,w,p,w,o,p,h,s,u e,x,y,p,t,n,f,c,b,w,e,?,s,s,w,w,p,w,t,e,w,c,w p,x,y,n,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p p,x,y,y,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,v,p p,x,s,w,t,f,f,c,b,p,t,b,s,f,w,w,p,w,o,p,h,v,u e,f,y,b,t,n,f,c,b,e,e,?,s,s,e,w,p,w,t,e,w,c,w p,f,s,b,t,f,f,c,b,w,t,b,f,s,w,w,p,w,o,p,h,v,u e,x,f,c,f,n,f,w,n,w,e,b,f,f,w,n,p,w,o,e,w,v,l e,f,s,p,t,n,f,c,b,e,e,?,s,s,w,e,p,w,t,e,w,c,w e,x,y,n,f,n,f,w,n,w,e,b,f,f,w,n,p,w,o,e,w,v,l e,f,s,p,t,n,f,c,b,w,e,?,s,s,e,e,p,w,t,e,w,c,w p,f,s,g,t,f,f,c,b,w,t,b,s,s,w,w,p,w,o,p,h,v,u e,k,s,e,t,n,f,c,b,w,e,?,s,s,w,e,p,w,t,e,w,c,w e,k,y,e,t,n,f,c,b,w,e,?,s,s,w,e,p,w,t,e,w,c,w p,f,s,w,t,f,f,c,b,p,t,b,s,f,w,w,p,w,o,p,h,v,g e,k,s,b,t,n,f,c,b,e,e,?,s,s,e,w,p,w,t,e,w,c,w p,x,s,b,t,f,f,c,b,p,t,b,f,f,w,w,p,w,o,p,h,v,g p,b,y,y,f,n,f,c,n,w,e,?,k,y,w,y,p,w,o,e,w,v,d p,x,s,w,t,f,f,c,b,h,t,b,s,s,w,w,p,w,o,p,h,s,u p,x,f,y,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,v,g p,f,y,y,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,y,p p,b,f,n,f,n,f,c,n,w,e,?,k,y,w,y,p,w,o,e,w,v,d p,f,y,y,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,y,p p,f,y,y,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,v,p e,f,y,c,f,n,f,w,n,w,e,b,s,s,w,n,p,w,o,e,w,v,l p,x,y,e,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d p,f,s,w,t,f,f,c,b,h,t,b,s,s,w,w,p,w,o,p,h,s,g p,x,y,n,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p p,b,y,p,t,n,f,c,b,r,e,b,s,s,w,w,p,w,t,p,r,v,g p,f,y,y,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,y,d p,x,s,b,t,f,f,c,b,w,t,b,s,f,w,w,p,w,o,p,h,s,g p,f,y,y,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,v,p p,f,s,b,t,f,f,c,b,p,t,b,f,s,w,w,p,w,o,p,h,s,g p,f,s,b,t,f,f,c,b,h,t,b,s,s,w,w,p,w,o,p,h,s,u p,x,y,n,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,f,y,y,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,v,p e,x,s,n,t,n,f,c,b,e,e,?,s,s,w,w,p,w,t,e,w,c,w p,f,y,y,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,v,g e,f,s,b,t,n,f,c,b,e,e,?,s,s,w,e,p,w,t,e,w,c,w e,f,s,e,t,n,f,c,b,w,e,?,s,s,e,w,p,w,t,e,w,c,w e,x,s,n,t,n,f,c,b,e,e,?,s,s,e,e,p,w,t,e,w,c,w p,f,s,w,t,f,f,c,b,p,t,b,f,s,w,w,p,w,o,p,h,v,u p,f,y,y,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,v,d e,f,s,p,t,n,f,c,b,e,e,?,s,s,e,w,p,w,t,e,w,c,w e,x,s,e,t,n,f,c,b,w,e,?,s,s,w,e,p,w,t,e,w,c,w p,f,y,y,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,v,d p,b,y,b,t,n,f,c,b,g,e,b,s,s,w,w,p,w,t,p,r,v,m p,f,s,b,t,f,f,c,b,h,t,b,s,f,w,w,p,w,o,p,h,s,u p,f,s,g,t,f,f,c,b,w,t,b,f,s,w,w,p,w,o,p,h,s,g p,x,s,b,t,f,f,c,b,p,t,b,s,s,w,w,p,w,o,p,h,s,g p,x,f,y,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,y,p p,f,s,w,t,f,f,c,b,w,t,b,s,s,w,w,p,w,o,p,h,s,g p,x,s,g,t,f,f,c,b,w,t,b,f,s,w,w,p,w,o,p,h,s,u e,f,y,r,f,n,f,c,n,h,e,?,s,f,w,w,p,w,o,f,h,y,d p,f,y,y,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,v,g p,x,y,n,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d p,x,s,b,t,f,f,c,b,w,t,b,f,s,w,w,p,w,o,p,h,s,g e,x,f,c,f,n,f,w,n,w,e,b,f,s,w,n,p,w,o,e,w,v,l p,x,s,g,t,f,f,c,b,h,t,b,f,s,w,w,p,w,o,p,h,v,u e,x,y,u,f,n,f,c,n,p,e,?,s,f,w,w,p,w,o,f,h,y,d p,x,f,y,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,v,p p,f,f,g,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,v,g p,f,y,w,t,n,f,c,b,g,e,b,s,s,w,w,p,w,t,p,r,v,m p,x,y,n,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d p,x,y,n,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,x,y,g,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,v,p e,x,y,p,t,n,f,c,b,e,e,?,s,s,e,e,p,w,t,e,w,c,w p,f,s,g,t,f,f,c,b,w,t,b,f,f,w,w,p,w,o,p,h,s,g p,x,s,b,t,f,f,c,b,w,t,b,s,f,w,w,p,w,o,p,h,v,g p,x,y,n,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p p,x,s,g,t,f,f,c,b,h,t,b,f,s,w,w,p,w,o,p,h,s,u p,x,y,n,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p p,f,s,w,t,f,f,c,b,p,t,b,f,f,w,w,p,w,o,p,h,s,g p,x,s,g,t,f,f,c,b,w,t,b,s,s,w,w,p,w,o,p,h,v,u p,x,s,g,t,f,f,c,b,w,t,b,s,f,w,w,p,w,o,p,h,s,g p,f,y,y,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,v,p p,f,y,y,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,v,p p,f,y,g,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,y,g p,x,y,y,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,y,g p,x,s,g,t,f,f,c,b,w,t,b,f,f,w,w,p,w,o,p,h,s,u p,f,s,b,t,f,f,c,b,p,t,b,f,f,w,w,p,w,o,p,h,s,u p,f,s,w,t,f,f,c,b,h,t,b,f,s,w,w,p,w,o,p,h,s,u p,f,f,g,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,y,g p,f,s,b,t,f,f,c,b,h,t,b,f,f,w,w,p,w,o,p,h,s,g p,x,y,n,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d p,x,s,w,t,f,f,c,b,w,t,b,s,s,w,w,p,w,o,p,h,s,g e,k,s,e,t,n,f,c,b,e,e,?,s,s,e,w,p,w,t,e,w,c,w p,f,y,b,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,r,v,m p,x,y,n,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p e,k,y,n,t,n,f,c,b,e,e,?,s,s,w,e,p,w,t,e,w,c,w p,f,s,w,t,f,f,c,b,w,t,b,s,s,w,w,p,w,o,p,h,v,u p,f,s,w,t,f,f,c,b,p,t,b,s,s,w,w,p,w,o,p,h,v,u p,x,y,n,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d p,x,s,w,t,f,f,c,b,w,t,b,f,s,w,w,p,w,o,p,h,s,g p,x,y,n,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l p,b,s,p,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,r,v,g p,x,y,e,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d p,f,y,g,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,v,p p,x,y,y,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,v,d p,x,y,g,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,v,g p,f,y,w,t,n,f,c,b,r,e,b,s,s,w,w,p,w,t,p,r,v,m p,f,s,g,t,f,f,c,b,h,t,b,f,f,w,w,p,w,o,p,h,s,g e,k,y,p,t,n,f,c,b,w,e,?,s,s,e,e,p,w,t,e,w,c,w p,x,s,w,t,f,f,c,b,w,t,b,f,s,w,w,p,w,o,p,h,v,g e,k,s,p,t,n,f,c,b,e,e,?,s,s,w,w,p,w,t,e,w,c,w p,f,s,w,t,f,f,c,b,p,t,b,s,f,w,w,p,w,o,p,h,s,u p,x,y,n,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p p,x,f,y,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,v,d p,f,y,g,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,v,p p,x,y,g,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,y,p e,x,y,e,t,n,f,c,b,w,e,?,s,s,w,e,p,w,t,e,w,c,w p,f,y,y,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,v,p p,x,y,n,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d p,x,s,b,t,f,f,c,b,w,t,b,f,f,w,w,p,w,o,p,h,v,g p,f,y,y,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,y,d e,k,y,e,t,n,f,c,b,e,e,?,s,s,e,w,p,w,t,e,w,c,w p,f,y,p,t,n,f,c,b,g,e,b,s,s,w,w,p,w,t,p,r,v,m p,f,y,w,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,r,v,m p,f,y,y,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,y,p p,f,y,y,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,v,g e,f,y,r,f,n,f,c,n,w,e,?,s,f,w,w,p,w,o,f,h,v,d p,x,s,w,t,f,f,c,b,p,t,b,s,f,w,w,p,w,o,p,h,s,g p,x,s,w,t,f,f,c,b,p,t,b,f,f,w,w,p,w,o,p,h,s,g p,x,s,b,t,f,f,c,b,p,t,b,f,s,w,w,p,w,o,p,h,s,u p,x,y,n,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p e,k,y,e,t,n,f,c,b,e,e,?,s,s,e,e,p,w,t,e,w,c,w e,k,s,p,t,n,f,c,b,w,e,?,s,s,w,w,p,w,t,e,w,c,w e,x,y,b,t,n,f,c,b,w,e,?,s,s,w,e,p,w,t,e,w,c,w p,x,s,g,t,f,f,c,b,h,t,b,s,s,w,w,p,w,o,p,h,v,g p,f,y,y,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,y,g p,x,y,n,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l p,c,y,w,t,n,f,w,n,w,e,b,s,s,w,w,p,w,o,p,w,c,l p,f,s,w,t,f,f,c,b,p,t,b,f,f,w,w,p,w,o,p,h,v,g p,f,s,g,t,f,f,c,b,w,t,b,s,f,w,w,p,w,o,p,h,s,g p,x,y,e,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,x,s,g,t,f,f,c,b,w,t,b,s,s,w,w,p,w,o,p,h,s,g p,x,y,n,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d e,x,y,p,t,n,f,c,b,e,e,?,s,s,e,w,p,w,t,e,w,c,w e,f,y,w,f,n,f,c,n,h,e,?,s,f,w,w,p,w,o,f,h,y,d p,f,y,y,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,y,g p,x,y,n,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d p,x,f,y,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,y,d p,x,y,n,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l p,x,s,g,t,f,f,c,b,h,t,b,s,f,w,w,p,w,o,p,h,v,u p,x,y,n,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d e,k,f,n,f,n,f,w,n,w,e,b,s,f,w,n,p,w,o,e,w,v,l p,x,s,w,t,f,f,c,b,p,t,b,f,s,w,w,p,w,o,p,h,v,u p,f,y,y,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,y,p e,x,y,p,t,n,f,c,b,e,e,?,s,s,w,e,p,w,t,e,w,c,w p,b,y,b,t,n,f,c,b,r,e,b,s,s,w,w,p,w,t,p,r,v,m p,f,y,g,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,v,p e,f,y,r,f,n,f,c,n,h,e,?,s,f,w,w,p,w,o,f,h,v,d p,x,y,n,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l p,x,y,n,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,f,s,b,t,f,f,c,b,p,t,b,f,f,w,w,p,w,o,p,h,v,g p,f,y,y,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,v,d p,x,y,n,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d e,f,y,n,t,n,f,c,b,e,e,?,s,s,w,e,p,w,t,e,w,c,w p,x,y,n,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l e,f,y,e,t,n,f,c,b,w,e,?,s,s,w,e,p,w,t,e,w,c,w e,x,y,b,t,n,f,c,b,w,e,?,s,s,w,w,p,w,t,e,w,c,w e,x,s,n,t,n,f,c,b,e,e,?,s,s,w,e,p,w,t,e,w,c,w p,f,s,w,t,f,f,c,b,w,t,b,s,f,w,w,p,w,o,p,h,v,g e,x,y,b,t,n,f,c,b,e,e,?,s,s,w,w,p,w,t,e,w,c,w p,x,f,y,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,y,g p,f,y,y,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,y,d p,f,y,y,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,y,g e,k,y,e,t,n,f,c,b,w,e,?,s,s,w,w,p,w,t,e,w,c,w p,f,s,w,t,f,f,c,b,p,t,b,s,f,w,w,p,w,o,p,h,v,u e,k,y,c,f,n,f,w,n,w,e,b,s,s,w,n,p,w,o,e,w,v,l e,k,y,n,f,n,f,w,n,w,e,b,s,s,w,n,p,w,o,e,w,v,l p,b,s,p,t,n,f,c,b,r,e,b,s,s,w,w,p,w,t,p,r,v,m p,x,y,n,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p p,x,s,b,t,f,f,c,b,h,t,b,s,f,w,w,p,w,o,p,h,s,u e,f,y,r,f,n,f,c,n,p,e,?,s,f,w,w,p,w,o,f,h,v,d p,x,s,b,t,f,f,c,b,w,t,b,f,f,w,w,p,w,o,p,h,s,g e,f,y,u,f,n,f,c,n,p,e,?,s,f,w,w,p,w,o,f,h,y,d p,x,y,n,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p p,x,s,w,t,f,f,c,b,p,t,b,s,s,w,w,p,w,o,p,h,v,u e,x,s,e,t,n,f,c,b,w,e,?,s,s,e,w,p,w,t,e,w,c,w e,f,y,p,t,n,f,c,b,e,e,?,s,s,w,e,p,w,t,e,w,c,w p,x,y,n,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p p,x,y,n,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p p,x,s,w,t,f,f,c,b,p,t,b,s,s,w,w,p,w,o,p,h,v,g p,f,y,y,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,v,p e,x,y,n,t,n,f,c,b,e,e,?,s,s,w,w,p,w,t,e,w,c,w e,x,y,e,t,n,f,c,b,e,e,?,s,s,e,w,p,w,t,e,w,c,w p,x,s,w,t,f,f,c,b,w,t,b,s,f,w,w,p,w,o,p,h,v,u p,x,y,y,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,v,g p,f,s,b,t,n,f,c,b,g,e,b,s,s,w,w,p,w,t,p,r,v,m p,f,f,y,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,v,p p,x,s,g,t,f,f,c,b,p,t,b,s,f,w,w,p,w,o,p,h,v,g e,f,s,p,t,n,f,c,b,w,e,?,s,s,e,w,p,w,t,e,w,c,w e,x,y,n,t,n,f,c,b,e,e,?,s,s,w,e,p,w,t,e,w,c,w p,b,y,w,t,n,f,c,b,r,e,b,s,s,w,w,p,w,t,p,r,v,m p,f,y,y,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,v,d p,x,y,e,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d p,x,s,b,t,f,f,c,b,h,t,b,s,f,w,w,p,w,o,p,h,s,g p,x,s,b,t,f,f,c,b,h,t,b,s,s,w,w,p,w,o,p,h,v,g p,x,y,n,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p p,b,y,p,t,n,f,c,b,g,e,b,s,s,w,w,p,w,t,p,r,v,g e,x,y,c,f,n,f,w,n,w,e,b,s,s,w,n,p,w,o,e,w,v,l p,x,y,n,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d p,x,s,w,t,f,f,c,b,w,t,b,s,s,w,w,p,w,o,p,h,s,u p,x,y,n,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d e,f,y,n,f,n,f,w,n,w,e,b,f,s,w,n,p,w,o,e,w,v,l p,x,y,n,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p p,f,s,g,t,f,f,c,b,p,t,b,s,s,w,w,p,w,o,p,h,s,u p,x,y,e,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d e,x,y,r,f,n,f,c,n,h,e,?,s,f,w,w,p,w,o,f,h,y,d p,b,y,p,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,r,v,m e,x,s,p,t,n,f,c,b,w,e,?,s,s,e,w,p,w,t,e,w,c,w p,x,y,n,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l p,x,y,n,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,f,s,g,t,f,f,c,b,w,t,b,f,f,w,w,p,w,o,p,h,v,g p,f,y,y,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,v,p p,f,y,p,t,n,f,c,b,r,e,b,s,s,w,w,p,w,t,p,r,v,m p,x,y,n,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,x,y,n,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d e,f,s,b,t,n,f,c,b,e,e,?,s,s,e,w,p,w,t,e,w,c,w p,f,s,b,t,f,f,c,b,p,t,b,s,s,w,w,p,w,o,p,h,v,u e,x,y,c,f,n,f,w,n,w,e,b,s,f,w,n,p,w,o,e,w,v,l e,x,y,w,f,n,f,c,n,w,e,?,s,f,w,w,p,w,o,f,h,y,d p,x,y,n,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l e,f,y,n,f,n,f,w,n,w,e,b,s,s,w,n,p,w,o,e,w,v,l p,x,y,n,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,x,y,n,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d e,k,y,p,t,n,f,c,b,e,e,?,s,s,e,w,p,w,t,e,w,c,w p,f,s,w,t,n,f,c,b,r,e,b,s,s,w,w,p,w,t,p,r,v,m p,x,y,n,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,f,y,y,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,v,g e,k,y,n,f,n,f,w,n,w,e,b,s,f,w,n,p,w,o,e,w,v,l p,f,s,g,t,f,f,c,b,p,t,b,f,s,w,w,p,w,o,p,h,v,g p,f,s,w,t,n,f,c,b,r,e,b,s,s,w,w,p,w,t,p,r,v,g p,f,f,g,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,y,g e,f,s,n,t,n,f,c,b,w,e,?,s,s,w,e,p,w,t,e,w,c,w p,x,f,y,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,y,d p,x,y,n,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,x,y,e,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p p,f,y,y,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,v,g p,b,s,w,t,n,f,c,b,g,e,b,s,s,w,w,p,w,t,p,r,v,g p,x,s,b,t,f,f,c,b,p,t,b,s,f,w,w,p,w,o,p,h,v,u e,f,y,b,t,n,f,c,b,w,e,?,s,s,w,e,p,w,t,e,w,c,w e,x,f,c,f,n,f,w,n,w,e,b,s,f,w,n,p,w,o,e,w,v,l p,f,s,w,t,f,f,c,b,h,t,b,f,s,w,w,p,w,o,p,h,v,u e,k,s,p,t,n,f,c,b,e,e,?,s,s,e,w,p,w,t,e,w,c,w e,k,y,n,t,n,f,c,b,e,e,?,s,s,e,w,p,w,t,e,w,c,w e,x,y,b,t,n,f,c,b,e,e,?,s,s,e,e,p,w,t,e,w,c,w p,x,f,y,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,y,g p,f,s,g,t,f,f,c,b,h,t,b,f,s,w,w,p,w,o,p,h,v,g p,f,y,y,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,v,p e,x,y,e,t,n,f,c,b,e,e,?,s,s,w,e,p,w,t,e,w,c,w p,f,s,b,t,f,f,c,b,p,t,b,f,s,w,w,p,w,o,p,h,v,g e,x,y,n,f,n,f,w,n,w,e,b,s,s,w,n,p,w,o,e,w,v,l p,f,y,y,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,v,d p,f,f,g,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,v,d p,b,y,b,t,n,f,c,b,r,e,b,s,s,w,w,p,w,t,p,r,v,g p,x,y,e,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p p,f,y,y,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,y,p p,f,f,y,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,v,p p,f,y,w,t,n,f,c,b,g,e,b,s,s,w,w,p,w,t,p,r,v,g e,k,s,e,t,n,f,c,b,e,e,?,s,s,w,e,p,w,t,e,w,c,w p,f,y,y,f,f,f,c,b,g,e,b,k,k,n,n,p,w,o,l,h,v,p e,k,s,n,t,n,f,c,b,e,e,?,s,s,w,e,p,w,t,e,w,c,w p,f,y,y,f,n,f,c,n,w,e,?,k,y,w,n,p,w,o,e,w,v,d p,f,y,g,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,y,p p,f,y,y,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,v,g p,x,y,e,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p e,f,s,b,t,n,f,c,b,w,e,?,s,s,e,e,p,w,t,e,w,c,w p,f,s,w,t,f,f,c,b,w,t,b,f,s,w,w,p,w,o,p,h,v,u p,x,s,w,t,f,f,c,b,w,t,b,f,f,w,w,p,w,o,p,h,s,g p,f,y,g,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,y,d e,f,y,p,t,n,f,c,b,w,e,?,s,s,e,w,p,w,t,e,w,c,w p,f,y,y,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,y,g p,f,y,y,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,y,p e,k,s,e,t,n,f,c,b,w,e,?,s,s,e,e,p,w,t,e,w,c,w e,x,y,n,t,n,f,c,b,e,e,?,s,s,e,e,p,w,t,e,w,c,w p,x,y,y,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,v,g p,f,s,b,t,f,f,c,b,p,t,b,s,f,w,w,p,w,o,p,h,v,g p,x,y,g,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,v,d p,f,s,g,t,f,f,c,b,w,t,b,f,f,w,w,p,w,o,p,h,s,u p,x,s,w,t,f,f,c,b,p,t,b,f,s,w,w,p,w,o,p,h,v,g p,x,f,n,f,n,f,c,n,w,e,?,k,y,w,y,p,w,o,e,w,v,d p,f,s,b,t,f,f,c,b,h,t,b,s,f,w,w,p,w,o,p,h,s,g e,f,y,e,t,n,f,c,b,e,e,?,s,s,e,e,p,w,t,e,w,c,w p,f,y,y,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,y,g p,x,s,b,t,f,f,c,b,p,t,b,s,f,w,w,p,w,o,p,h,s,u e,k,f,n,f,n,f,w,n,w,e,b,f,s,w,n,p,w,o,e,w,v,l p,f,y,y,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,y,g e,k,y,c,f,n,f,w,n,w,e,b,f,f,w,n,p,w,o,e,w,v,l p,x,f,g,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,y,p p,x,y,n,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p e,f,y,p,t,n,f,c,b,w,e,?,s,s,w,w,p,w,t,e,w,c,w p,x,s,b,t,f,f,c,b,h,t,b,f,f,w,w,p,w,o,p,h,v,g p,x,y,g,f,f,f,c,b,h,e,b,k,k,b,n,p,w,o,l,h,y,d p,f,y,y,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,y,g p,x,y,e,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d e,f,y,r,f,n,f,c,n,w,e,?,s,f,w,w,p,w,o,f,h,y,d p,f,y,y,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,y,p p,x,s,g,t,f,f,c,b,h,t,b,f,f,w,w,p,w,o,p,h,v,g p,x,s,w,t,f,f,c,b,w,t,b,f,f,w,w,p,w,o,p,h,v,g p,f,s,b,t,f,f,c,b,w,t,b,f,s,w,w,p,w,o,p,h,s,g e,x,y,n,t,n,f,c,b,w,e,?,s,s,e,e,p,w,t,e,w,c,w p,f,f,y,f,n,f,c,n,w,e,?,k,y,w,n,p,w,o,e,w,v,d e,f,y,u,f,n,f,c,n,w,e,?,s,f,w,w,p,w,o,f,h,v,d p,x,y,n,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l e,x,s,n,t,n,f,c,b,w,e,?,s,s,w,w,p,w,t,e,w,c,w p,x,s,w,t,f,f,c,b,w,t,b,f,s,w,w,p,w,o,p,h,v,u p,f,y,y,f,f,f,c,b,p,e,b,k,k,p,b,p,w,o,l,h,v,d e,f,s,b,t,n,f,c,b,e,e,?,s,s,e,e,p,w,t,e,w,c,w e,k,f,c,f,n,f,w,n,w,e,b,s,s,w,n,p,w,o,e,w,v,l p,x,s,g,t,f,f,c,b,p,t,b,s,f,w,w,p,w,o,p,h,v,u p,f,y,g,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,v,p p,x,y,e,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l e,f,y,p,t,n,f,c,b,e,e,?,s,s,e,w,p,w,t,e,w,c,w e,k,y,p,t,n,f,c,b,w,e,?,s,s,w,w,p,w,t,e,w,c,w p,x,y,y,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,v,g p,x,y,n,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d e,f,s,n,t,n,f,c,b,e,e,?,s,s,e,w,p,w,t,e,w,c,w p,f,y,y,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,y,g p,x,y,n,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d e,f,s,n,t,n,f,c,b,w,e,?,s,s,e,e,p,w,t,e,w,c,w p,f,y,y,f,f,f,c,b,p,e,b,k,k,p,p,p,w,o,l,h,v,d p,f,y,y,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,v,p p,f,y,y,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,y,p e,f,f,c,f,n,f,w,n,w,e,b,f,s,w,n,p,w,o,e,w,v,l p,b,y,b,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,r,v,g e,k,y,e,t,n,f,c,b,w,e,?,s,s,e,w,p,w,t,e,w,c,w p,x,s,b,t,f,f,c,b,w,t,b,f,f,w,w,p,w,o,p,h,v,u p,x,s,g,t,f,f,c,b,w,t,b,s,s,w,w,p,w,o,p,h,v,g p,f,y,y,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,v,g p,x,s,g,t,f,f,c,b,p,t,b,s,s,w,w,p,w,o,p,h,s,u p,x,y,e,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p p,f,s,w,t,f,f,c,b,p,t,b,f,f,w,w,p,w,o,p,h,v,u e,f,s,p,t,n,f,c,b,w,e,?,s,s,w,w,p,w,t,e,w,c,w p,f,s,b,t,f,f,c,b,h,t,b,s,s,w,w,p,w,o,p,h,v,g p,x,y,e,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p e,f,y,w,f,n,f,c,n,u,e,?,s,f,w,w,p,w,o,f,h,v,d e,x,y,p,t,n,f,c,b,w,e,?,s,s,w,e,p,w,t,e,w,c,w p,x,s,b,t,f,f,c,b,p,t,b,s,s,w,w,p,w,o,p,h,v,u p,k,g,w,t,n,f,w,n,w,e,b,s,s,w,w,p,w,o,p,w,c,l p,f,s,g,t,f,f,c,b,p,t,b,s,s,w,w,p,w,o,p,h,s,g p,x,y,n,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p e,k,s,e,t,n,f,c,b,w,e,?,s,s,w,w,p,w,t,e,w,c,w p,x,y,n,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d p,x,y,n,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p p,f,s,w,t,f,f,c,b,h,t,b,f,f,w,w,p,w,o,p,h,s,g e,f,s,e,t,n,f,c,b,e,e,?,s,s,w,e,p,w,t,e,w,c,w p,f,s,b,t,f,f,c,b,p,t,b,s,s,w,w,p,w,o,p,h,s,g p,b,s,w,t,n,f,c,b,r,e,b,s,s,w,w,p,w,t,p,r,v,m e,f,f,n,f,n,f,w,n,w,e,b,f,s,w,n,p,w,o,e,w,v,l p,f,s,g,t,f,f,c,b,p,t,b,s,s,w,w,p,w,o,p,h,v,u p,x,s,w,t,f,f,c,b,h,t,b,s,s,w,w,p,w,o,p,h,v,g p,f,y,y,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,v,g e,x,s,b,t,n,f,c,b,e,e,?,s,s,e,w,p,w,t,e,w,c,w e,f,y,n,t,n,f,c,b,w,e,?,s,s,e,w,p,w,t,e,w,c,w e,x,y,r,f,n,f,c,n,u,e,?,s,f,w,w,p,w,o,f,h,v,d e,k,s,b,t,n,f,c,b,e,e,?,s,s,e,e,p,w,t,e,w,c,w p,x,s,w,t,f,f,c,b,h,t,b,s,f,w,w,p,w,o,p,h,v,u p,x,y,n,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d e,x,y,b,t,n,f,c,b,w,e,?,s,s,e,e,p,w,t,e,w,c,w p,f,y,w,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,r,v,g p,f,s,b,t,f,f,c,b,w,t,b,s,f,w,w,p,w,o,p,h,s,u p,x,s,g,t,f,f,c,b,p,t,b,s,s,w,w,p,w,o,p,h,v,g e,k,s,n,t,n,f,c,b,w,e,?,s,s,w,w,p,w,t,e,w,c,w p,f,s,g,t,f,f,c,b,p,t,b,s,f,w,w,p,w,o,p,h,s,g e,k,y,p,t,n,f,c,b,e,e,?,s,s,e,e,p,w,t,e,w,c,w p,f,y,b,t,n,f,c,b,g,e,b,s,s,w,w,p,w,t,p,r,v,m p,x,y,n,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d p,f,y,y,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,v,p p,x,s,b,t,f,f,c,b,w,t,b,f,f,w,w,p,w,o,p,h,s,u e,k,f,c,f,n,f,w,n,w,e,b,s,f,w,n,p,w,o,e,w,v,l p,f,s,g,t,f,f,c,b,p,t,b,s,f,w,w,p,w,o,p,h,v,u p,f,s,w,t,f,f,c,b,w,t,b,f,s,w,w,p,w,o,p,h,v,g p,b,s,b,t,n,f,c,b,r,e,b,s,s,w,w,p,w,t,p,r,v,m p,b,s,p,t,n,f,c,b,r,e,b,s,s,w,w,p,w,t,p,r,v,g p,f,s,w,t,f,f,c,b,w,t,b,s,f,w,w,p,w,o,p,h,s,g e,x,y,n,t,n,f,c,b,w,e,?,s,s,w,e,p,w,t,e,w,c,w p,x,y,n,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l p,x,y,g,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,v,g e,x,s,b,t,n,f,c,b,w,e,?,s,s,w,w,p,w,t,e,w,c,w p,x,y,n,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,x,s,b,t,f,f,c,b,p,t,b,s,s,w,w,p,w,o,p,h,s,u p,f,s,p,t,n,f,c,b,g,e,b,s,s,w,w,p,w,t,p,r,v,g p,x,y,n,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,x,s,w,t,f,f,c,b,h,t,b,f,f,w,w,p,w,o,p,h,v,u p,f,s,w,t,f,f,c,b,h,t,b,s,s,w,w,p,w,o,p,h,v,u e,f,y,r,f,n,f,c,n,u,e,?,s,f,w,w,p,w,o,f,h,y,d p,f,s,w,t,f,f,c,b,h,t,b,f,s,w,w,p,w,o,p,h,s,g p,f,s,w,t,f,f,c,b,p,t,b,f,s,w,w,p,w,o,p,h,s,u e,x,y,w,f,n,f,c,n,u,e,?,s,f,w,w,p,w,o,f,h,v,d p,x,y,n,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d e,k,y,b,t,n,f,c,b,w,e,?,s,s,w,w,p,w,t,e,w,c,w p,x,y,n,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d p,x,y,n,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l p,x,s,b,t,f,f,c,b,p,t,b,f,f,w,w,p,w,o,p,h,s,u e,f,y,r,f,n,f,c,n,p,e,?,s,f,w,w,p,w,o,f,h,y,d p,b,s,p,t,n,f,c,b,g,e,b,s,s,w,w,p,w,t,p,r,v,g p,x,s,b,t,f,f,c,b,p,t,b,f,f,w,w,p,w,o,p,h,v,u e,f,y,c,f,n,f,w,n,w,e,b,f,f,w,n,p,w,o,e,w,v,l e,x,y,u,f,n,f,c,n,p,e,?,s,f,w,w,p,w,o,f,h,v,d p,x,s,b,t,f,f,c,b,w,t,b,s,f,w,w,p,w,o,p,h,v,u e,x,y,w,f,n,f,c,n,w,e,?,s,f,w,w,p,w,o,f,h,v,d p,x,y,n,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l e,x,s,p,t,n,f,c,b,e,e,?,s,s,e,w,p,w,t,e,w,c,w p,f,s,p,t,n,f,c,b,r,e,b,s,s,w,w,p,w,t,p,r,v,m p,f,y,n,f,n,f,c,n,w,e,?,k,y,w,y,p,w,o,e,w,v,d p,f,y,y,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,y,p p,f,s,w,t,f,f,c,b,h,t,b,s,f,w,w,p,w,o,p,h,v,g p,x,y,g,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,v,g e,f,y,e,t,n,f,c,b,w,e,?,s,s,e,e,p,w,t,e,w,c,w p,f,s,b,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,r,v,g p,b,s,p,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,r,v,m p,x,y,n,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l p,x,s,b,t,f,f,c,b,p,t,b,f,s,w,w,p,w,o,p,h,v,u p,x,y,y,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,y,p p,b,y,w,t,n,f,c,b,g,e,b,s,s,w,w,p,w,t,p,r,v,g e,f,y,n,f,n,f,w,n,w,e,b,s,f,w,n,p,w,o,e,w,v,l p,f,f,y,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,y,g p,f,y,y,f,f,f,c,b,h,e,b,k,k,p,b,p,w,o,l,h,v,p p,f,y,y,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,v,g p,x,s,g,t,f,f,c,b,h,t,b,s,f,w,w,p,w,o,p,h,s,u p,x,y,e,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l p,x,y,y,f,n,f,c,n,w,e,?,k,y,w,y,p,w,o,e,w,v,d p,x,y,n,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p p,f,s,w,t,f,f,c,b,h,t,b,s,f,w,w,p,w,o,p,h,s,g p,f,f,g,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,y,g e,f,f,n,f,n,f,w,n,w,e,b,s,s,w,n,p,w,o,e,w,v,l p,x,s,g,t,f,f,c,b,w,t,b,f,s,w,w,p,w,o,p,h,s,g p,f,s,b,t,f,f,c,b,h,t,b,f,f,w,w,p,w,o,p,h,v,u e,f,s,e,t,n,f,c,b,e,e,?,s,s,e,e,p,w,t,e,w,c,w p,x,s,b,t,f,f,c,b,h,t,b,s,s,w,w,p,w,o,p,h,s,u p,f,y,y,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,v,d p,x,y,n,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d p,f,s,w,t,f,f,c,b,p,t,b,s,s,w,w,p,w,o,p,h,v,g p,f,s,g,t,f,f,c,b,h,t,b,s,s,w,w,p,w,o,p,h,s,g p,f,y,y,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,v,g e,f,f,c,f,n,f,w,n,w,e,b,s,s,w,n,p,w,o,e,w,v,l p,x,y,n,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l e,k,y,e,t,n,f,c,b,e,e,?,s,s,w,e,p,w,t,e,w,c,w p,x,y,n,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,f,s,w,t,f,f,c,b,p,t,b,s,f,w,w,p,w,o,p,h,s,g p,x,y,e,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l e,x,s,n,t,n,f,c,b,w,e,?,s,s,e,e,p,w,t,e,w,c,w p,f,y,g,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,v,p p,x,s,w,t,f,f,c,b,w,t,b,f,f,w,w,p,w,o,p,h,v,u e,f,s,e,t,n,f,c,b,w,e,?,s,s,e,e,p,w,t,e,w,c,w p,f,y,y,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,v,d p,f,y,y,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,v,d e,f,y,e,t,n,f,c,b,e,e,?,s,s,e,w,p,w,t,e,w,c,w p,f,s,g,t,f,f,c,b,p,t,b,f,f,w,w,p,w,o,p,h,v,g e,k,s,n,t,n,f,c,b,e,e,?,s,s,e,w,p,w,t,e,w,c,w p,f,y,y,f,f,f,c,b,p,e,b,k,k,n,b,p,w,o,l,h,y,d p,x,s,w,t,f,f,c,b,w,t,b,s,f,w,w,p,w,o,p,h,s,g p,x,y,n,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p p,f,y,y,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,y,g p,f,y,w,t,n,f,c,b,r,e,b,s,s,w,w,p,w,t,p,r,v,g p,x,y,n,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d e,f,y,w,f,n,f,c,n,w,e,?,s,f,w,w,p,w,o,f,h,v,d e,x,y,w,f,n,f,c,n,h,e,?,s,f,w,w,p,w,o,f,h,y,d p,x,y,n,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p p,f,s,g,t,f,f,c,b,p,t,b,f,s,w,w,p,w,o,p,h,s,u e,x,y,u,f,n,f,c,n,w,e,?,s,f,w,w,p,w,o,f,h,v,d p,f,s,w,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,r,v,g p,x,y,y,f,f,f,c,b,g,e,b,k,k,p,b,p,w,o,l,h,v,d p,f,s,g,t,f,f,c,b,h,t,b,s,f,w,w,p,w,o,p,h,v,g p,f,y,y,f,f,f,c,b,g,e,b,k,k,p,n,p,w,o,l,h,y,p p,x,f,y,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,v,g p,f,y,y,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,y,d p,x,s,g,t,f,f,c,b,p,t,b,f,f,w,w,p,w,o,p,h,s,g e,f,y,r,f,n,f,c,n,u,e,?,s,f,w,w,p,w,o,f,h,v,d p,f,s,w,t,f,f,c,b,w,t,b,f,s,w,w,p,w,o,p,h,s,g e,k,s,n,t,n,f,c,b,w,e,?,s,s,e,e,p,w,t,e,w,c,w p,x,y,n,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d p,x,s,g,t,f,f,c,b,w,t,b,f,f,w,w,p,w,o,p,h,s,g p,f,y,y,f,f,f,c,b,g,e,b,k,k,p,p,p,w,o,l,h,y,g p,b,s,w,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,r,v,m p,x,y,n,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d p,b,s,b,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,r,v,m p,f,f,y,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,y,g p,x,y,g,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,y,d e,x,y,e,t,n,f,c,b,e,e,?,s,s,w,w,p,w,t,e,w,c,w e,k,s,b,t,n,f,c,b,w,e,?,s,s,e,e,p,w,t,e,w,c,w p,x,y,n,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l e,x,s,e,t,n,f,c,b,e,e,?,s,s,e,e,p,w,t,e,w,c,w p,f,s,b,t,n,f,c,b,r,e,b,s,s,w,w,p,w,t,p,r,v,m e,f,s,n,t,n,f,c,b,w,e,?,s,s,w,w,p,w,t,e,w,c,w p,x,y,e,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p e,f,y,b,t,n,f,c,b,w,e,?,s,s,e,e,p,w,t,e,w,c,w p,x,s,g,t,f,f,c,b,w,t,b,s,s,w,w,p,w,o,p,h,s,u p,f,s,b,t,n,f,c,b,g,e,b,s,s,w,w,p,w,t,p,r,v,g p,x,y,n,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l p,x,y,e,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,f,y,y,f,f,f,c,b,h,e,b,k,k,b,b,p,w,o,l,h,y,g p,x,y,n,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l p,x,y,n,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d p,f,s,g,t,f,f,c,b,w,t,b,f,s,w,w,p,w,o,p,h,v,u e,x,y,p,t,n,f,c,b,w,e,?,s,s,e,w,p,w,t,e,w,c,w e,x,y,u,f,n,f,c,n,u,e,?,s,f,w,w,p,w,o,f,h,y,d p,f,y,y,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,y,p p,x,s,g,t,f,f,c,b,h,t,b,s,f,w,w,p,w,o,p,h,v,g p,x,y,n,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l p,f,s,g,t,f,f,c,b,h,t,b,s,f,w,w,p,w,o,p,h,v,u p,x,s,b,t,f,f,c,b,h,t,b,s,f,w,w,p,w,o,p,h,v,g p,x,f,y,f,f,f,c,b,h,e,b,k,k,b,p,p,w,o,l,h,y,g p,b,s,w,t,n,f,c,b,r,e,b,s,s,w,w,p,w,t,p,r,v,g e,k,y,n,t,n,f,c,b,e,e,?,s,s,e,e,p,w,t,e,w,c,w p,x,y,e,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d p,f,y,y,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,v,p e,x,y,b,t,n,f,c,b,w,e,?,s,s,e,w,p,w,t,e,w,c,w p,x,s,b,t,f,f,c,b,p,t,b,s,f,w,w,p,w,o,p,h,v,g p,f,s,g,t,f,f,c,b,w,t,b,f,f,w,w,p,w,o,p,h,v,u p,f,s,b,t,f,f,c,b,p,t,b,s,s,w,w,p,w,o,p,h,s,u p,f,y,y,f,f,f,c,b,p,e,b,k,k,b,b,p,w,o,l,h,y,d p,x,y,n,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p p,f,s,w,t,f,f,c,b,h,t,b,f,f,w,w,p,w,o,p,h,v,u e,k,y,n,t,n,f,c,b,e,e,?,s,s,w,w,p,w,t,e,w,c,w e,x,s,e,t,n,f,c,b,w,e,?,s,s,e,e,p,w,t,e,w,c,w e,x,y,w,f,n,f,c,n,p,e,?,s,f,w,w,p,w,o,f,h,v,d p,f,s,b,t,f,f,c,b,p,t,b,f,s,w,w,p,w,o,p,h,s,u p,f,s,g,t,f,f,c,b,h,t,b,s,s,w,w,p,w,o,p,h,s,u e,f,s,e,t,n,f,c,b,e,e,?,s,s,w,w,p,w,t,e,w,c,w p,f,y,y,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,y,g p,x,y,n,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l p,f,s,w,t,n,f,c,b,g,e,b,s,s,w,w,p,w,t,p,r,v,g p,f,y,g,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,y,d e,x,f,n,f,n,f,w,n,w,e,b,s,s,w,n,p,w,o,e,w,v,l p,f,y,y,f,f,f,c,b,p,e,b,k,k,b,n,p,w,o,l,h,y,d p,x,s,w,t,f,f,c,b,p,t,b,f,s,w,w,p,w,o,p,h,s,u e,x,s,b,t,n,f,c,b,w,e,?,s,s,e,e,p,w,t,e,w,c,w e,x,s,p,t,n,f,c,b,w,e,?,s,s,w,e,p,w,t,e,w,c,w p,x,s,g,t,f,f,c,b,w,t,b,f,f,w,w,p,w,o,p,h,v,g p,f,f,g,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,y,p p,x,s,w,t,f,f,c,b,h,t,b,s,f,w,w,p,w,o,p,h,s,g p,x,f,y,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,v,p p,f,s,w,t,f,f,c,b,p,t,b,s,s,w,w,p,w,o,p,h,s,u e,k,y,n,t,n,f,c,b,w,e,?,s,s,e,e,p,w,t,e,w,c,w e,x,y,p,t,n,f,c,b,e,e,?,s,s,w,w,p,w,t,e,w,c,w p,f,y,y,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,y,g e,f,y,b,t,n,f,c,b,e,e,?,s,s,w,w,p,w,t,e,w,c,w e,x,s,e,t,n,f,c,b,w,e,?,s,s,w,w,p,w,t,e,w,c,w p,x,s,g,t,f,f,c,b,p,t,b,f,f,w,w,p,w,o,p,h,v,u p,f,s,b,t,f,f,c,b,w,t,b,s,s,w,w,p,w,o,p,h,v,u p,f,y,y,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,v,p p,x,s,b,t,f,f,c,b,h,t,b,s,f,w,w,p,w,o,p,h,v,u p,f,s,w,t,f,f,c,b,h,t,b,s,s,w,w,p,w,o,p,h,v,g p,f,y,y,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,v,g p,f,y,y,f,f,f,c,b,p,e,b,k,k,n,p,p,w,o,l,h,y,d p,f,y,g,f,f,f,c,b,h,e,b,k,k,n,p,p,w,o,l,h,y,p p,f,f,g,f,f,f,c,b,g,e,b,k,k,b,n,p,w,o,l,h,v,p p,b,s,p,t,n,f,c,b,g,e,b,s,s,w,w,p,w,t,p,r,v,m p,x,y,n,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l p,b,s,w,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,r,v,g e,x,y,n,t,n,f,c,b,w,e,?,s,s,w,w,p,w,t,e,w,c,w p,x,y,n,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p p,x,y,n,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p p,x,y,n,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p p,f,s,b,t,f,f,c,b,w,t,b,s,s,w,w,p,w,o,p,h,s,g p,b,y,y,f,n,f,c,n,w,e,?,k,y,w,n,p,w,o,e,w,v,d p,x,s,g,t,f,f,c,b,w,t,b,f,f,w,w,p,w,o,p,h,v,u e,f,y,p,t,n,f,c,b,e,e,?,s,s,w,w,p,w,t,e,w,c,w e,k,s,p,t,n,f,c,b,e,e,?,s,s,e,e,p,w,t,e,w,c,w e,f,y,n,t,n,f,c,b,w,e,?,s,s,e,e,p,w,t,e,w,c,w p,b,y,p,t,n,f,c,b,g,e,b,s,s,w,w,p,w,t,p,r,v,m p,x,s,g,t,f,f,c,b,w,t,b,s,f,w,w,p,w,o,p,h,v,g p,x,s,g,t,f,f,c,b,p,t,b,s,s,w,w,p,w,o,p,h,s,g p,x,f,y,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,v,g p,x,y,n,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p p,f,y,b,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,r,v,g p,x,s,b,t,f,f,c,b,h,t,b,f,f,w,w,p,w,o,p,h,v,u p,b,s,b,t,n,f,c,b,r,e,b,s,s,w,w,p,w,t,p,r,v,g e,f,y,w,f,n,f,c,n,p,e,?,s,f,w,w,p,w,o,f,h,y,d e,x,y,n,f,n,f,w,n,w,e,b,f,s,w,n,p,w,o,e,w,v,l p,x,f,y,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,v,p p,f,s,b,t,f,f,c,b,h,t,b,s,f,w,w,p,w,o,p,h,v,g p,f,y,y,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,v,g e,k,s,e,t,n,f,c,b,e,e,?,s,s,e,e,p,w,t,e,w,c,w p,f,f,y,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,y,p p,b,f,n,f,n,f,c,n,w,e,?,k,y,w,n,p,w,o,e,w,v,d p,x,y,n,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p p,f,y,y,f,f,f,c,b,h,e,b,k,k,n,b,p,w,o,l,h,y,d p,x,y,y,f,f,f,c,b,g,e,b,k,k,n,b,p,w,o,l,h,y,g p,x,s,g,t,f,f,c,b,p,t,b,f,s,w,w,p,w,o,p,h,s,g p,x,y,n,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d e,x,y,n,t,n,f,c,b,w,e,?,s,s,e,w,p,w,t,e,w,c,w e,f,y,n,f,n,f,w,n,w,e,b,f,f,w,n,p,w,o,e,w,v,l p,f,y,b,t,n,f,c,b,g,e,b,s,s,w,w,p,w,t,p,r,v,g p,k,f,n,f,n,f,c,n,w,e,?,k,y,w,y,p,w,o,e,w,v,d p,f,y,g,f,f,f,c,b,h,e,b,k,k,p,n,p,w,o,l,h,v,g p,x,y,n,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p p,f,f,g,f,f,f,c,b,h,e,b,k,k,p,p,p,w,o,l,h,y,d p,f,f,g,f,f,f,c,b,p,e,b,k,k,b,p,p,w,o,l,h,v,d p,x,s,g,t,f,f,c,b,p,t,b,s,f,w,w,p,w,o,p,h,s,g e,x,y,r,f,n,f,c,n,u,e,?,s,f,w,w,p,w,o,f,h,y,d p,x,y,n,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p p,f,s,p,t,n,f,c,b,g,e,b,s,s,w,w,p,w,t,p,r,v,m p,x,y,e,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l p,f,s,b,t,f,f,c,b,w,t,b,s,s,w,w,p,w,o,p,h,v,g p,x,s,b,t,f,f,c,b,w,t,b,s,s,w,w,p,w,o,p,h,v,u e,k,s,e,t,n,f,c,b,e,e,?,s,s,w,w,p,w,t,e,w,c,w p,f,s,b,t,f,f,c,b,w,t,b,s,f,w,w,p,w,o,p,h,s,g e,x,f,n,f,n,f,w,n,w,e,b,f,f,w,n,p,w,o,e,w,v,l p,f,y,y,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,v,d e,f,y,w,f,n,f,c,n,w,e,?,s,f,w,w,p,w,o,f,h,y,d p,f,s,w,t,f,f,c,b,w,t,b,s,s,w,w,p,w,o,p,h,s,u p,f,s,p,t,n,f,c,b,r,e,b,s,s,w,w,p,w,t,p,r,v,g p,f,y,y,f,f,f,c,b,p,e,b,k,k,p,n,p,w,o,l,h,y,d p,f,s,g,t,f,f,c,b,h,t,b,s,f,w,w,p,w,o,p,h,s,g p,x,y,n,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l p,f,y,y,f,f,f,c,b,g,e,b,k,k,b,b,p,w,o,l,h,v,g p,f,s,g,t,f,f,c,b,h,t,b,f,s,w,w,p,w,o,p,h,s,g p,f,s,w,t,f,f,c,b,h,t,b,s,f,w,w,p,w,o,p,h,s,u p,x,y,n,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d p,f,f,y,f,f,f,c,b,p,e,b,k,k,n,n,p,w,o,l,h,y,d p,x,y,n,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d p,b,y,b,t,n,f,c,b,g,e,b,s,s,w,w,p,w,t,p,r,v,g p,f,y,y,f,f,f,c,b,g,e,b,k,k,b,p,p,w,o,l,h,v,g p,x,y,e,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,x,y,n,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d e,k,y,b,t,n,f,c,b,e,e,?,s,s,w,w,p,w,t,e,w,c,w e,x,y,w,f,n,f,c,n,p,e,?,s,f,w,w,p,w,o,f,h,y,d p,f,s,b,t,f,f,c,b,p,t,b,s,f,w,w,p,w,o,p,h,v,u p,f,y,y,f,f,f,c,b,g,e,b,k,k,n,p,p,w,o,l,h,y,g p,x,y,e,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p p,f,s,e,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d p,x,y,e,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d p,x,s,n,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p p,f,y,n,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p p,f,y,e,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d p,k,y,n,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l p,f,y,e,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p p,x,s,e,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l p,f,y,n,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p p,f,y,e,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d p,x,s,e,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l p,x,s,n,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l p,f,s,e,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d p,f,s,e,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,f,y,e,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p p,f,y,n,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p p,f,y,n,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p p,x,y,e,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,k,s,n,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p p,x,s,n,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l p,f,s,e,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d p,f,y,e,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l p,k,s,e,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p p,f,y,e,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d p,x,s,n,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p p,f,s,e,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d p,f,s,n,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l p,f,y,e,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d p,f,s,e,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l p,f,s,n,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p p,f,y,e,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p p,x,s,e,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l p,f,s,e,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p p,x,s,n,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d p,f,y,n,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p p,x,y,e,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,f,y,n,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l e,b,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,n,o,p,n,c,l p,f,s,n,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d e,x,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,n,v,l p,f,y,e,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d p,f,y,n,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l p,f,y,e,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p p,f,s,n,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,x,y,e,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l p,x,s,n,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d p,f,s,n,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d p,f,y,e,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d p,f,s,n,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d p,f,s,n,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p p,f,s,n,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l p,f,y,e,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,f,s,e,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l p,x,y,e,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l p,x,s,e,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,f,s,e,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d p,f,y,n,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p p,x,y,e,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,k,s,e,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l p,k,s,n,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,f,y,n,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d p,x,s,e,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l p,x,y,e,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,f,y,e,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p p,f,y,n,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l p,f,s,e,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p p,x,s,n,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p e,x,f,w,f,n,f,w,b,w,e,?,k,k,w,w,p,w,t,p,w,n,g p,f,y,n,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p p,x,s,n,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d p,x,s,e,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d p,f,s,n,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l p,f,s,n,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l p,x,y,e,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,x,s,e,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d p,f,s,n,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l p,k,s,n,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,f,y,n,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p p,x,s,n,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l p,f,y,e,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l p,x,s,e,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d p,f,s,n,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l p,f,y,n,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p p,k,y,n,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,f,y,n,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d p,f,s,n,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,x,s,e,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l p,f,s,n,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l p,f,s,n,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d p,f,s,e,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l p,f,y,n,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l p,f,s,n,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d p,f,y,n,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l p,f,s,e,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l p,f,s,e,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l p,x,y,e,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p p,f,s,n,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p p,x,y,e,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d p,f,y,e,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,x,s,n,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p p,f,y,n,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p p,f,y,e,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d p,x,y,e,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l p,f,y,n,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d p,f,y,n,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l p,x,y,e,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l p,f,y,n,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l p,f,s,n,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l p,x,s,n,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p p,f,y,e,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,x,y,e,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l p,x,s,e,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,f,s,e,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l p,f,y,e,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d p,x,y,e,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l p,x,y,e,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l p,x,s,n,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l p,x,s,e,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l p,k,s,e,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p e,x,s,c,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,v,p p,x,s,e,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p p,f,s,n,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d p,x,s,n,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l p,f,y,n,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p p,f,y,e,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l p,f,s,e,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l p,x,y,e,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l p,x,s,e,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l p,x,s,n,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d p,x,y,e,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d p,f,s,e,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p p,f,s,n,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l p,f,y,e,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p p,x,y,e,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l p,k,s,e,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p p,f,y,n,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d p,f,s,n,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d p,x,s,e,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,f,s,n,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l p,f,s,e,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,f,y,e,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l e,b,f,w,f,n,f,w,b,g,e,?,s,s,w,w,p,w,t,p,w,n,g p,x,y,e,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l p,x,y,e,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,f,y,e,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,f,y,e,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l e,k,f,w,f,n,f,w,b,g,e,?,k,s,w,w,p,w,t,p,w,s,g p,x,s,n,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p p,f,s,n,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p p,x,s,n,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d p,f,s,e,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d p,x,s,n,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p p,x,s,n,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,x,s,e,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,k,s,n,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d p,x,y,e,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d p,x,s,e,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d p,x,y,e,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d p,x,s,e,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d p,x,s,e,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d p,x,s,e,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,x,s,e,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d p,f,y,e,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d p,x,s,n,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d p,f,s,n,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d p,x,s,e,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d p,f,s,e,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p p,x,s,n,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l p,f,y,e,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d p,x,s,n,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,k,s,n,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p p,f,s,e,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l p,f,s,e,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l p,f,y,e,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p p,k,s,n,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p p,f,y,n,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,f,s,e,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p p,x,y,e,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d p,f,s,e,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l p,f,y,e,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l p,f,s,n,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d p,f,s,n,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d p,x,y,e,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p p,x,y,e,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l p,f,s,e,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,k,y,e,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d p,f,y,e,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p p,k,y,n,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d p,x,s,e,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,x,y,e,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p p,x,s,n,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l p,f,y,n,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l p,x,s,e,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p e,b,s,g,f,n,f,w,b,w,e,?,s,k,w,w,p,w,t,p,w,n,g p,x,y,e,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,x,s,e,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d p,f,y,e,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l p,x,s,e,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p p,f,y,e,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d p,f,y,e,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,x,s,n,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d p,f,y,n,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p e,k,s,w,f,n,f,w,b,g,e,?,k,s,w,w,p,w,t,p,w,s,g p,f,y,e,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p p,x,s,e,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p p,f,y,n,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,f,y,n,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l p,x,s,e,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,f,y,e,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d p,f,y,e,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p p,f,s,n,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p p,x,y,e,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p p,f,y,e,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d e,b,f,g,f,n,f,w,b,p,e,?,k,s,w,w,p,w,t,p,w,n,g p,k,y,e,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l p,x,y,e,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l p,k,s,e,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l p,x,s,n,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p e,k,s,w,f,n,f,w,b,g,e,?,s,k,w,w,p,w,t,p,w,s,g p,f,s,e,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d p,x,s,n,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p p,k,s,e,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p p,k,y,n,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l p,k,y,e,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p p,x,s,e,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d p,f,s,e,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p p,f,y,e,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,x,y,e,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d p,f,y,n,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d p,x,y,e,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d p,f,y,n,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l p,x,y,e,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l p,k,y,n,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,f,s,e,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l p,x,s,n,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p p,f,y,n,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d p,f,s,e,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d p,x,s,e,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d p,f,s,n,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d p,f,y,n,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l p,x,y,e,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d p,x,s,e,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d p,f,y,e,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l p,f,s,e,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l p,f,y,e,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,x,s,n,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l p,f,s,n,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d p,x,s,n,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l p,f,y,n,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,k,y,n,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d p,x,s,e,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p p,f,y,n,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d p,x,y,e,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p p,f,y,e,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d p,x,y,e,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d p,f,y,e,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,f,y,e,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d p,f,s,e,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l p,k,y,e,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l p,x,s,e,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p e,k,s,g,f,n,f,w,b,g,e,?,k,s,w,w,p,w,t,p,w,s,g p,x,s,n,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l p,f,s,e,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d p,f,s,n,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d p,f,s,e,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l p,f,y,n,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p p,x,s,e,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p p,x,s,e,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p p,x,s,e,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d p,x,s,e,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p p,f,s,e,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d p,x,s,e,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p p,x,s,n,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l p,f,s,n,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l p,k,y,n,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d p,x,y,e,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p p,x,s,n,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l p,x,s,e,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p e,b,s,w,f,n,f,w,b,p,e,?,k,k,w,w,p,w,t,p,w,s,g p,f,s,e,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p p,x,s,e,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l p,x,y,e,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d p,f,y,n,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p p,f,s,e,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l p,f,y,n,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d p,f,y,e,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d p,f,s,n,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d p,x,y,e,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l p,f,s,n,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d p,x,s,n,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,f,s,e,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p p,x,s,n,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d p,f,s,e,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l p,x,y,e,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p p,f,y,n,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p p,x,y,e,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l p,f,s,n,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p p,f,s,n,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p p,x,s,n,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p p,f,s,e,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d p,k,y,n,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p p,x,y,e,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l p,x,y,e,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d p,k,s,n,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d p,x,s,e,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p p,x,s,e,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p p,f,y,n,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l p,f,s,e,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d p,f,s,e,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p p,f,s,n,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,f,y,e,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p p,f,y,e,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l p,k,s,e,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d p,x,s,n,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,f,y,n,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d p,f,s,e,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p p,k,s,n,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d p,f,y,n,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p p,x,y,e,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l p,x,y,e,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,x,s,e,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p p,f,y,n,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l p,f,y,n,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p p,f,y,e,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p p,k,y,n,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,x,s,n,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d p,x,s,e,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l p,x,s,n,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l p,f,y,e,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p p,k,y,e,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d e,x,f,g,f,n,f,w,b,w,e,?,s,k,w,w,p,w,t,p,w,s,g p,f,y,e,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l p,x,s,e,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,x,s,e,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l p,x,y,e,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d p,f,y,n,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,f,y,n,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l p,x,s,n,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p p,x,s,e,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,f,y,e,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d p,f,s,n,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l p,f,y,n,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,f,y,n,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d p,x,y,e,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,x,s,e,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p p,f,s,n,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l p,f,s,n,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,x,s,e,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d p,f,s,n,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,f,s,n,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,f,y,n,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p p,x,s,n,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l p,f,s,n,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,f,s,n,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p p,x,s,n,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p p,f,y,n,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,x,s,n,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p p,x,s,n,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p p,f,s,n,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,f,y,n,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d p,x,y,e,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d p,f,s,e,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l p,f,y,n,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d p,f,s,e,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l p,x,s,n,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p e,k,f,w,f,n,f,w,b,p,e,?,k,k,w,w,p,w,t,p,w,n,g p,x,s,n,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p p,f,s,n,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,f,y,n,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p p,f,s,n,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d p,f,y,n,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d p,f,y,n,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l p,f,s,n,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d p,f,y,e,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p e,b,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,o,v,l p,f,s,e,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,f,s,e,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,x,s,e,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l p,f,y,n,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l p,f,y,e,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p p,f,s,n,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l p,f,y,e,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,f,s,n,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p p,k,y,n,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p p,f,y,e,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l p,f,s,e,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d p,x,y,e,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p p,f,s,n,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l p,x,s,e,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p p,k,y,n,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p p,x,s,n,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,x,y,e,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d p,f,y,n,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d p,f,s,e,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d p,f,s,n,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p e,x,s,w,f,n,f,w,b,g,e,?,k,s,w,w,p,w,t,p,w,s,g p,f,y,n,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d p,f,s,n,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l p,x,y,e,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l p,f,s,e,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l p,x,s,n,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p p,x,y,e,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l e,k,f,g,f,n,f,w,b,g,e,?,k,k,w,w,p,w,t,p,w,s,g p,f,s,e,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,f,y,e,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p e,b,f,w,f,n,f,w,b,w,e,?,s,k,w,w,p,w,t,p,w,s,g p,f,s,n,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l p,x,y,e,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,x,y,e,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d p,f,s,n,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p p,x,s,n,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d p,f,s,e,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p p,f,s,e,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l p,f,s,e,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l p,x,y,e,f,m,f,c,b,w,e,c,k,y,c,c,p,w,n,n,w,c,d p,f,y,n,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d p,f,y,e,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d p,x,s,e,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p p,f,s,e,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p p,f,y,e,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p p,f,y,e,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l p,x,s,e,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l p,f,s,e,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p e,x,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,n,o,p,y,c,l p,f,y,n,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d p,f,y,e,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l p,f,y,e,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l p,x,s,n,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p p,x,s,e,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d p,x,y,e,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d p,x,s,e,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p p,x,y,e,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p p,f,y,e,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p e,x,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,n,o,p,o,v,l p,f,s,n,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,x,y,e,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p p,f,s,n,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d p,f,y,e,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p p,x,y,e,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d p,x,s,n,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d p,x,s,n,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l p,x,s,n,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l p,x,y,e,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d p,f,s,n,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l p,f,s,n,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l p,k,y,e,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l p,x,s,n,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,f,y,n,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p e,k,s,w,f,n,f,w,b,g,e,?,s,k,w,w,p,w,t,p,w,n,g p,f,s,e,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l p,x,s,e,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l p,f,y,n,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d p,f,y,n,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,f,y,e,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d p,x,s,n,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,f,y,n,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,x,s,n,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l p,k,y,n,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l p,f,s,e,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,f,y,e,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l p,f,y,e,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l p,f,y,e,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,f,y,n,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p p,f,y,n,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l p,k,y,n,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l p,k,y,n,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p p,f,s,e,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p p,x,s,e,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d p,k,s,n,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l p,x,s,e,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p p,f,s,n,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d p,x,s,e,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l p,f,s,n,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p p,x,s,n,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,f,y,e,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d p,x,s,n,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,x,s,e,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p p,x,s,e,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d p,x,s,n,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,x,y,e,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d p,f,y,e,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p p,f,s,e,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d p,x,s,e,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d p,f,y,e,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l p,f,s,e,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p p,f,s,e,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l p,f,y,n,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d p,f,s,n,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p p,x,s,e,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p p,f,y,n,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l p,f,s,n,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d p,f,y,n,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l p,f,s,e,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l p,f,y,e,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p p,f,y,n,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,f,s,e,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d p,f,s,e,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d p,f,y,n,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d p,f,s,e,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d p,f,s,n,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d p,k,y,e,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d p,f,y,e,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d p,f,s,e,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d p,f,y,e,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d p,f,y,n,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,f,y,e,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p p,f,s,n,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p p,x,y,e,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d e,x,f,w,f,n,f,w,b,p,e,?,k,s,w,w,p,w,t,p,w,n,g p,x,s,e,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d p,x,s,e,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l p,f,y,n,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l p,x,s,e,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d p,x,s,n,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d p,x,s,n,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p p,x,s,n,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l e,x,f,g,f,n,f,w,b,p,e,?,s,k,w,w,p,w,t,p,w,n,g p,f,y,e,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,f,y,e,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l p,x,y,e,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p p,x,s,n,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p p,k,s,e,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p p,k,y,e,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d p,f,y,e,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d p,x,s,n,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l p,f,s,n,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,x,s,e,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p p,f,y,n,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d p,x,s,n,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p e,k,f,w,f,n,f,w,b,p,e,?,s,k,w,w,p,w,t,p,w,n,g p,k,y,n,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d p,f,s,e,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d p,x,y,e,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d p,x,s,n,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l p,x,s,n,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d p,f,y,e,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,f,y,n,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l p,x,y,e,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l p,f,s,e,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p p,x,s,e,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d p,x,s,n,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p p,f,y,n,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,f,y,e,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l p,f,y,n,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,f,y,n,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d p,f,s,n,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p p,f,y,e,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p p,f,y,e,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,x,y,e,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p p,k,s,e,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p p,f,y,e,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p p,f,y,n,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p p,f,s,n,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d p,f,s,e,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p p,k,s,e,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p p,f,y,e,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p p,f,s,n,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p e,x,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,o,o,p,b,v,l p,x,s,n,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l p,k,s,n,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l p,f,s,n,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d p,f,s,n,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d p,x,s,n,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p p,f,s,n,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d p,f,y,e,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p p,f,y,e,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d p,f,s,n,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l p,x,s,e,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l p,x,s,n,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p p,x,s,e,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p p,x,s,e,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d p,f,y,e,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l p,x,s,e,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p p,k,s,e,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l p,x,y,e,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p p,f,s,n,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p p,f,s,n,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l p,x,s,n,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d p,k,y,e,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p p,x,s,e,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l p,f,y,n,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d p,f,y,e,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d p,f,y,n,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p p,f,s,n,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l p,f,s,e,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p p,k,y,n,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,f,y,e,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l p,f,s,e,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p p,f,s,n,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d p,x,s,n,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l p,f,y,n,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d p,f,y,e,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d p,x,y,e,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d p,f,s,e,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p p,x,s,n,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,f,s,n,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,f,s,n,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l p,f,s,e,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p e,x,s,g,f,n,f,w,b,p,e,?,s,k,w,w,p,w,t,p,w,n,g p,k,y,n,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p p,x,y,e,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p p,x,s,n,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p p,x,s,n,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d p,f,y,e,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l p,k,y,n,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l p,x,s,e,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d p,x,s,n,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d p,k,y,n,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d p,x,y,e,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l p,k,s,n,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p 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p,f,y,e,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d p,x,s,n,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d p,x,s,e,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l p,f,s,n,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,x,s,n,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d p,f,s,e,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d p,k,y,n,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p p,x,s,n,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l p,f,y,n,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p p,k,y,n,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p p,f,s,e,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d p,f,s,n,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p p,x,s,e,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d p,x,s,n,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l p,f,y,n,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p p,f,y,n,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p p,x,s,e,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l p,f,y,n,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,x,y,e,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p p,f,y,n,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l p,f,y,e,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p p,x,y,e,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l p,f,s,e,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l p,k,s,n,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d p,x,y,e,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p p,x,s,n,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l p,f,s,e,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p p,f,s,e,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p e,b,f,g,f,n,f,w,b,p,e,?,s,k,w,w,p,w,t,p,w,s,g p,x,s,n,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p p,k,s,n,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p e,b,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,y,v,l p,f,s,n,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d p,f,y,n,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d p,x,y,e,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d p,x,s,e,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d p,k,y,c,f,m,a,c,b,w,e,c,k,y,c,c,p,w,n,n,w,c,d p,x,s,e,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l p,f,s,n,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,x,s,n,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l p,x,y,e,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d p,x,s,e,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d p,f,s,e,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l p,f,s,n,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d p,f,s,n,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d p,f,y,e,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p p,x,s,e,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l p,f,y,e,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d p,f,y,n,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l p,x,y,e,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l p,f,y,e,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p p,f,s,e,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l p,f,s,e,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p p,x,s,e,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p p,x,s,e,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d p,k,y,e,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p p,x,y,e,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l p,x,s,e,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d p,x,s,n,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d p,x,s,n,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l p,f,s,n,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d p,f,y,n,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,x,s,e,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d p,k,s,n,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p p,f,s,n,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d p,f,y,n,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d p,f,y,e,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p p,f,y,e,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l p,f,y,n,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d p,x,s,e,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,f,y,n,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d p,f,s,n,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d p,f,s,e,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p p,x,s,n,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d p,f,y,e,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d p,k,y,n,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l p,f,s,n,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p p,f,y,n,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p p,f,s,e,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l p,x,s,n,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l p,f,s,e,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p p,x,s,e,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d p,f,y,e,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d p,x,s,e,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,f,s,e,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p p,f,s,n,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p p,x,s,n,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p p,x,s,e,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d p,f,s,e,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d p,x,s,e,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l p,x,s,n,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,f,s,e,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d p,x,y,e,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l p,x,s,n,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p p,x,y,e,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p p,f,s,e,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l p,x,s,e,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,f,y,n,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l p,x,s,e,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,x,s,n,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,f,s,e,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d p,x,s,e,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d p,f,s,n,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,x,y,e,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,f,y,e,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d p,x,y,e,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p p,k,y,n,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l p,f,y,n,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l p,x,y,e,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l p,f,s,n,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p p,x,s,e,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d p,f,s,e,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d e,x,f,g,f,n,f,w,b,g,e,?,k,k,w,w,p,w,t,p,w,s,g p,x,s,e,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p p,f,s,n,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l p,f,s,n,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p p,x,s,e,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l p,x,s,e,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,x,s,e,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,f,y,e,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d e,b,f,g,f,n,f,w,b,w,e,?,s,s,w,w,p,w,t,p,w,s,g p,f,y,n,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,f,y,e,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d p,f,y,n,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d p,f,s,n,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l p,f,y,n,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d p,x,y,e,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d p,f,y,n,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l p,x,s,n,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d p,f,y,e,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d e,k,f,g,f,n,f,w,b,p,e,?,k,s,w,w,p,w,t,p,w,s,g e,b,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,n,o,p,o,c,l p,f,s,n,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l p,x,s,n,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p p,f,y,n,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l p,f,s,e,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,f,y,n,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l p,f,s,n,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d p,f,y,e,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p p,f,y,e,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l p,f,s,n,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,x,s,e,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d e,x,f,w,f,n,f,w,b,g,e,?,s,k,w,w,p,w,t,p,w,n,g p,f,s,n,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p p,x,s,e,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l p,x,s,n,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d p,x,s,n,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l p,x,s,n,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d p,k,y,n,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d p,f,s,n,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,x,y,e,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p p,f,s,n,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p p,f,s,n,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d p,x,s,n,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l p,x,s,n,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d p,x,y,e,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l p,f,s,e,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d p,f,s,e,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,f,y,n,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p p,x,s,e,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l p,f,s,e,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l p,f,y,e,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d p,f,y,e,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l p,x,y,e,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l p,f,y,n,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l p,f,s,n,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l p,f,s,n,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p p,k,y,e,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l p,f,s,e,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l p,x,s,e,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p p,x,y,e,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p p,f,y,e,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l p,x,y,e,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d p,f,y,e,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l p,f,y,n,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d p,f,y,e,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l p,x,y,e,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p p,x,s,e,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d p,f,s,e,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l p,f,s,e,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p p,x,s,e,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p p,f,s,e,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p p,f,s,e,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p p,f,s,n,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l p,f,y,e,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d p,f,y,n,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p p,k,s,e,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,f,s,n,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d p,f,y,n,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p p,f,s,e,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l p,f,y,e,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l p,x,s,n,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p p,k,y,n,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,x,y,e,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d p,x,s,e,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l e,x,s,g,f,n,f,w,b,w,e,?,k,s,w,w,p,w,t,p,w,n,g p,k,y,n,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d p,x,s,n,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p p,f,s,n,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p p,f,s,n,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p p,x,s,e,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p p,f,s,e,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l p,f,y,e,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l p,f,y,e,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,f,s,n,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,f,s,e,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p p,x,s,n,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p p,f,s,e,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l p,x,s,e,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p p,f,s,e,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d p,f,y,e,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p p,k,y,e,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p p,f,s,n,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p p,k,y,e,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d p,f,s,e,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l p,f,y,e,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l p,f,s,e,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l e,b,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,o,o,p,o,c,l p,x,s,n,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d p,f,y,e,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l p,f,y,n,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d p,f,s,e,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d p,f,y,n,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p p,k,y,n,f,m,f,c,b,w,e,c,k,y,c,c,p,w,n,n,w,c,d p,x,s,e,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p p,f,s,e,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l p,k,y,n,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,f,s,e,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p e,k,s,w,f,n,f,w,b,g,e,?,k,k,w,w,p,w,t,p,w,s,g p,f,y,n,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l p,f,y,n,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d p,f,y,n,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p p,f,s,n,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d p,f,s,n,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l p,f,y,e,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p p,x,s,e,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,f,y,n,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p p,x,s,n,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p p,x,s,e,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l p,x,s,e,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l p,f,y,e,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d p,x,s,n,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d p,x,s,e,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p p,f,s,n,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l p,x,s,n,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l p,f,y,e,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,x,s,n,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d p,f,y,e,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l p,f,s,e,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p p,f,y,n,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l p,f,y,n,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d p,x,y,e,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d e,k,f,g,f,n,f,w,b,w,e,?,k,k,w,w,p,w,t,p,w,n,g p,x,s,e,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d p,k,y,n,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d p,k,y,n,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d p,x,y,e,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p p,f,s,e,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,f,s,n,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l p,f,s,e,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p p,x,s,e,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p p,f,s,n,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d p,f,y,e,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p p,x,s,n,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l p,x,y,e,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p p,f,s,e,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p p,x,s,n,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d p,f,s,n,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p e,x,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,o,o,p,y,v,l p,k,s,n,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,f,s,n,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l p,k,y,e,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p e,x,y,c,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,y,p e,b,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,n,o,p,y,c,l e,k,s,g,f,n,f,w,b,w,e,?,s,k,w,w,p,w,t,p,w,n,g e,x,f,g,f,n,f,w,b,g,e,?,s,k,w,w,p,w,t,p,w,s,g p,x,s,n,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d p,k,y,e,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p e,x,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,o,c,l p,k,s,e,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d p,b,y,y,f,n,f,w,n,y,e,c,y,y,y,y,p,y,o,e,w,c,l p,x,s,e,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d e,b,s,g,f,n,f,w,b,g,e,?,k,k,w,w,p,w,t,p,w,n,g p,k,y,e,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p p,k,s,e,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p p,f,s,e,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d p,f,y,n,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p p,f,s,e,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d e,k,f,g,f,n,f,w,b,w,e,?,s,k,w,w,p,w,t,p,w,s,g p,k,s,n,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p p,k,s,e,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d p,f,s,e,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l e,b,f,g,f,n,f,w,b,p,e,?,k,k,w,w,p,w,t,p,w,n,g p,f,y,n,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d p,f,s,n,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p e,f,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,n,c,l e,x,y,p,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,y,p p,f,s,n,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d p,k,y,e,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,f,s,n,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l e,b,s,w,f,n,f,w,b,w,e,?,s,k,w,w,p,w,t,p,w,n,g p,x,y,e,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p p,f,y,e,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l p,f,s,e,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,k,y,n,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d e,x,f,w,f,n,f,w,b,p,e,?,s,s,w,w,p,w,t,p,w,s,g e,b,s,w,f,n,f,w,b,p,e,?,s,s,w,w,p,w,t,p,w,n,g p,k,s,e,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l p,f,y,n,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l e,f,y,n,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,v,p p,k,s,n,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d p,k,s,n,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l p,f,y,n,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l p,f,y,e,f,m,a,c,b,w,e,c,k,y,c,c,p,w,n,n,w,c,d p,x,s,e,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d p,k,y,e,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p p,x,s,n,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l p,k,s,e,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l p,k,y,n,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l p,f,y,e,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p e,x,f,w,f,n,f,w,b,w,e,?,s,s,w,w,p,w,t,p,w,s,g p,k,s,n,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d p,f,s,n,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p p,k,s,e,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d p,k,s,e,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l p,k,y,n,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l e,k,f,w,f,n,f,w,b,g,e,?,s,s,w,w,p,w,t,p,w,s,g p,k,s,n,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p p,k,y,n,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l p,k,s,n,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l p,k,s,e,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d p,x,s,n,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,x,y,e,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l p,f,s,e,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p p,k,y,n,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d e,b,s,n,f,n,f,c,b,w,e,b,y,y,n,n,p,w,t,p,w,y,d p,f,s,n,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p p,k,y,e,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d e,x,s,n,f,n,f,c,b,w,e,b,y,y,n,n,p,w,t,p,w,y,d p,f,s,n,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d p,k,s,n,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l p,f,y,n,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p p,x,s,n,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p e,k,f,w,f,n,f,w,b,w,e,?,s,s,w,w,p,w,t,p,w,s,g p,f,y,e,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d p,x,s,e,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p p,x,s,n,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,f,s,n,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p p,k,s,n,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l p,k,s,e,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p p,k,s,e,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l p,x,s,e,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d e,b,s,n,f,n,f,c,b,w,e,b,y,y,n,n,p,w,t,p,w,y,p p,k,s,e,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p p,x,s,n,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p p,x,y,e,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p p,f,s,e,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l e,b,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,n,o,p,n,c,l e,k,s,g,f,n,f,w,b,p,e,?,k,k,w,w,p,w,t,p,w,n,g p,k,y,e,f,m,f,c,b,y,e,c,k,y,c,c,p,w,n,n,w,c,d p,k,y,e,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,f,s,e,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d e,k,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,o,c,l p,f,y,e,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d p,k,y,e,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d e,k,f,w,f,n,f,w,b,p,e,?,k,s,w,w,p,w,t,p,w,s,g e,x,s,g,f,n,f,w,b,w,e,?,s,k,w,w,p,w,t,p,w,s,g e,k,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,o,v,l p,k,y,e,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d p,k,y,n,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,k,s,e,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p e,x,s,w,f,n,f,w,b,w,e,?,k,k,w,w,p,w,t,p,w,s,g e,k,s,w,f,n,f,w,b,g,e,?,k,k,w,w,p,w,t,p,w,n,g e,k,s,w,f,n,f,w,b,p,e,?,k,s,w,w,p,w,t,p,w,s,g p,k,s,e,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l p,x,s,e,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p e,k,s,g,f,n,f,w,b,w,e,?,s,k,w,w,p,w,t,p,w,s,g e,x,f,w,f,n,f,w,b,g,e,?,s,k,w,w,p,w,t,p,w,s,g p,k,y,e,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d e,b,s,w,f,n,f,w,b,g,e,?,s,s,w,w,p,w,t,p,w,s,g p,k,s,e,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p p,f,s,n,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p p,f,y,n,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d e,k,s,g,f,n,f,w,b,p,e,?,s,k,w,w,p,w,t,p,w,s,g e,x,s,w,f,n,f,w,b,w,e,?,s,s,w,w,p,w,t,p,w,n,g p,f,y,e,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p p,x,s,e,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d e,x,f,w,f,n,f,w,b,g,e,?,k,k,w,w,p,w,t,p,w,s,g e,k,f,w,f,n,f,w,b,g,e,?,k,k,w,w,p,w,t,p,w,n,g p,f,s,e,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d e,f,s,g,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,v,p p,k,s,e,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,x,s,n,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p e,k,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,n,o,p,b,c,l e,x,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,o,o,p,n,c,l p,k,y,e,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,x,s,e,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d p,x,s,n,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,k,s,e,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d p,x,s,n,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l e,k,f,w,f,n,f,w,b,g,e,?,k,s,w,w,p,w,t,p,w,n,g e,k,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,n,c,l p,k,y,c,f,m,f,c,b,w,e,c,k,y,c,c,p,w,n,n,w,c,d e,x,f,g,f,n,f,w,b,g,e,?,s,s,w,w,p,w,t,p,w,s,g e,x,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,o,o,p,o,v,l e,x,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,b,v,l p,k,y,e,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p e,k,f,w,f,n,f,w,b,p,e,?,s,s,w,w,p,w,t,p,w,n,g e,x,f,g,f,n,f,w,b,g,e,?,k,s,w,w,p,w,t,p,w,s,g e,f,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,n,v,l p,k,y,n,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d p,k,y,n,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l p,f,y,n,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d p,f,y,e,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p e,k,f,g,f,n,f,w,b,p,e,?,s,k,w,w,p,w,t,p,w,n,g p,f,y,e,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d p,f,y,n,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p p,k,s,e,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l e,k,s,g,f,n,f,w,b,w,e,?,k,k,w,w,p,w,t,p,w,s,g e,b,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,n,o,p,y,c,l p,k,y,n,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l p,x,s,n,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p e,b,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,o,v,l p,k,s,n,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d p,k,s,n,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p p,k,s,e,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l p,f,s,e,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p p,x,s,e,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p p,x,s,e,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d p,x,s,n,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d p,k,y,n,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d e,x,s,p,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,y,p p,f,s,e,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d p,x,y,n,f,m,a,c,b,w,e,c,k,y,c,c,p,w,n,n,w,c,d p,k,s,n,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l e,k,s,g,f,n,f,w,b,g,e,?,k,k,w,w,p,w,t,p,w,s,g p,k,s,n,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d p,f,y,n,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p p,k,s,n,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p p,k,y,e,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d p,f,y,e,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d e,f,s,c,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,y,p p,f,y,n,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l p,k,s,e,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d p,x,s,e,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l p,f,y,e,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l p,x,s,n,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p e,f,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,n,o,p,n,c,l p,f,s,e,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d p,x,y,e,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p p,x,y,e,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d p,x,s,e,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,k,s,e,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l p,x,s,e,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l e,b,f,g,f,n,f,w,b,w,e,?,k,s,w,w,p,w,t,p,w,s,g p,k,y,e,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p p,k,s,e,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l e,k,f,g,f,n,f,w,b,g,e,?,s,s,w,w,p,w,t,p,w,n,g e,f,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,n,o,p,n,v,l p,f,y,n,f,m,f,c,b,w,e,c,k,y,c,c,p,w,n,n,w,c,d p,k,s,e,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d p,f,s,n,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l p,k,y,n,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,k,s,e,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l p,k,y,n,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p p,k,y,n,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l e,x,f,g,f,n,f,w,b,g,e,?,k,k,w,w,p,w,t,p,w,n,g p,k,y,e,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,x,y,c,f,m,a,c,b,y,e,c,k,y,c,c,p,w,n,n,w,c,d p,k,y,e,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,k,y,e,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l e,b,s,w,f,n,f,w,b,p,e,?,s,k,w,w,p,w,t,p,w,s,g p,k,s,n,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d p,x,s,e,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p p,f,y,n,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l p,f,s,e,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,k,y,e,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d p,k,y,e,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d e,b,f,w,f,n,f,w,b,w,e,?,s,s,w,w,p,w,t,p,w,n,g p,k,y,n,f,m,a,c,b,w,e,c,k,y,c,c,p,w,n,n,w,c,d p,f,y,e,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d p,k,s,n,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p p,k,y,n,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p p,x,s,e,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l e,x,y,g,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,v,p p,f,s,n,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d p,k,y,e,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p e,k,f,w,f,n,f,w,b,w,e,?,k,k,w,w,p,w,t,p,w,n,g p,x,s,n,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d p,k,y,n,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d p,x,s,e,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d e,k,s,w,f,n,f,w,b,w,e,?,s,k,w,w,p,w,t,p,w,n,g p,f,y,n,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p p,k,s,e,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,k,s,e,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p p,f,y,e,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l e,f,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,n,o,p,y,v,l p,f,y,n,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d p,k,y,e,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d p,k,s,e,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d p,k,s,e,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l e,b,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,b,v,l e,k,s,g,f,n,f,w,b,p,e,?,k,k,w,w,p,w,t,p,w,s,g e,x,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,o,o,p,n,v,l e,x,f,g,f,n,f,w,b,p,e,?,k,k,w,w,p,w,t,p,w,n,g p,k,s,e,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d p,f,y,e,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d p,k,s,n,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d p,k,s,n,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p e,b,s,w,f,n,f,w,b,p,e,?,k,s,w,w,p,w,t,p,w,n,g p,f,s,n,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d e,b,f,g,f,n,f,w,b,p,e,?,s,k,w,w,p,w,t,p,w,n,g p,x,s,n,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d p,x,y,e,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l p,f,y,c,f,m,f,c,b,w,e,c,k,y,c,c,p,w,n,n,w,c,d p,f,s,n,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d p,x,y,e,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l p,f,s,n,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l p,f,y,e,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p p,f,s,e,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,x,s,e,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d e,k,s,g,f,n,f,w,b,w,e,?,k,s,w,w,p,w,t,p,w,s,g p,x,s,e,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p p,k,s,n,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,k,y,e,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,x,s,n,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p e,b,s,g,f,n,f,w,b,g,e,?,s,k,w,w,p,w,t,p,w,n,g p,x,s,n,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l p,f,s,e,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d p,k,s,n,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d e,b,s,g,f,n,f,w,b,w,e,?,s,s,w,w,p,w,t,p,w,s,g p,x,s,n,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,f,y,e,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p p,f,s,e,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d p,f,y,n,f,m,f,c,b,y,e,c,k,y,c,c,p,w,n,n,w,c,d e,b,f,g,f,n,f,w,b,g,e,?,k,s,w,w,p,w,t,p,w,s,g p,f,s,e,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,k,s,n,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l e,k,s,g,f,n,f,w,b,p,e,?,s,k,w,w,p,w,t,p,w,n,g p,k,y,n,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l p,x,s,e,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l e,b,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,y,c,l p,k,y,n,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l p,f,y,n,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l e,x,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,n,o,p,b,c,l p,k,s,n,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l p,k,s,n,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d p,k,s,n,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p p,k,s,n,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p e,f,y,c,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,y,p e,f,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,n,o,p,n,c,l e,b,s,w,f,n,f,w,b,g,e,?,k,k,w,w,p,w,t,p,w,n,g p,k,s,e,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p e,b,s,g,f,n,f,w,b,w,e,?,s,s,w,w,p,w,t,p,w,n,g p,k,y,e,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p p,k,y,n,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d e,x,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,y,c,l p,x,s,e,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p p,x,s,n,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d p,f,s,e,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,f,y,e,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p p,x,y,e,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p p,k,s,e,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d e,k,y,n,f,n,f,c,b,w,e,b,y,y,n,n,p,w,t,p,w,y,d p,f,s,e,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d p,k,s,n,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p p,f,y,n,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p p,f,s,e,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d e,k,f,g,f,n,f,w,b,w,e,?,s,s,w,w,p,w,t,p,w,n,g p,k,s,n,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d e,b,f,w,f,n,f,w,b,p,e,?,k,s,w,w,p,w,t,p,w,s,g p,k,s,e,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l e,x,s,g,f,n,f,w,b,p,e,?,k,k,w,w,p,w,t,p,w,n,g e,k,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,y,c,l p,k,s,e,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p p,k,y,n,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l e,k,f,g,f,n,f,w,b,g,e,?,k,k,w,w,p,w,t,p,w,n,g p,x,s,n,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l p,k,y,n,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l e,x,f,w,f,n,f,w,b,g,e,?,k,s,w,w,p,w,t,p,w,n,g p,k,y,e,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p p,k,s,e,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l p,k,s,e,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l p,k,y,e,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p p,k,y,n,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p e,k,s,g,f,n,f,w,b,g,e,?,k,k,w,w,p,w,t,p,w,n,g p,k,y,n,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,k,s,e,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l e,x,s,g,f,n,f,w,b,w,e,?,s,k,w,w,p,w,t,p,w,n,g e,f,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,y,v,l e,k,s,g,f,n,f,w,b,g,e,?,k,s,w,w,p,w,t,p,w,n,g p,x,s,e,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p p,k,s,n,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d p,k,s,n,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p e,x,s,g,f,n,f,w,b,p,e,?,k,s,w,w,p,w,t,p,w,s,g p,k,y,e,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p e,f,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,o,o,p,y,v,l e,k,s,w,f,n,f,w,b,w,e,?,k,k,w,w,p,w,t,p,w,n,g p,f,y,e,f,m,f,c,b,y,e,c,k,y,c,c,p,w,n,n,w,c,d e,b,s,g,f,n,f,w,b,g,e,?,k,k,w,w,p,w,t,p,w,s,g p,f,y,n,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p e,b,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,b,c,l e,b,s,g,f,n,f,w,b,w,e,?,k,s,w,w,p,w,t,p,w,n,g e,k,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,o,o,p,y,c,l e,b,s,g,f,n,f,w,b,p,e,?,k,k,w,w,p,w,t,p,w,n,g p,k,s,n,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,k,y,n,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p e,f,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,n,o,p,o,c,l p,k,s,e,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,f,s,e,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p p,k,s,n,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l p,k,s,n,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l e,b,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,y,v,l e,k,f,g,f,n,f,w,b,w,e,?,k,k,w,w,p,w,t,p,w,s,g e,b,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,o,c,l p,k,s,n,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l p,k,y,e,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l p,k,y,e,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p p,k,s,n,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l e,f,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,o,o,p,n,c,l p,k,s,e,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d e,x,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,o,v,l p,k,s,n,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d e,k,s,w,f,n,f,w,b,p,e,?,s,s,w,w,p,w,t,p,w,s,g p,k,y,e,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d p,k,y,n,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d e,k,f,g,f,n,f,w,b,g,e,?,s,s,w,w,p,w,t,p,w,s,g p,f,s,n,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p e,x,s,g,f,n,f,w,b,w,e,?,s,s,w,w,p,w,t,p,w,n,g p,k,y,n,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p p,f,s,e,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d e,x,f,w,f,n,f,w,b,p,e,?,k,k,w,w,p,w,t,p,w,n,g p,k,y,n,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,f,y,n,f,m,a,c,b,w,e,c,k,y,c,c,p,w,n,n,w,c,d e,b,f,g,f,n,f,w,b,w,e,?,s,s,w,w,p,w,t,p,w,n,g p,k,y,e,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,x,y,e,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d p,k,s,e,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l e,k,f,g,f,n,f,w,b,g,e,?,s,k,w,w,p,w,t,p,w,n,g e,k,f,w,f,n,f,w,b,p,e,?,s,s,w,w,p,w,t,p,w,s,g p,k,y,e,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d e,k,s,g,f,n,f,w,b,g,e,?,s,s,w,w,p,w,t,p,w,n,g p,k,s,n,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d p,k,y,n,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l e,k,s,w,f,n,f,w,b,w,e,?,k,s,w,w,p,w,t,p,w,s,g p,k,y,e,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l e,b,s,w,f,n,f,w,b,w,e,?,k,s,w,w,p,w,t,p,w,s,g p,k,s,n,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d e,x,s,w,f,n,f,w,b,w,e,?,s,k,w,w,p,w,t,p,w,n,g e,b,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,o,o,p,n,v,l p,k,s,n,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,k,y,e,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p e,x,f,w,f,n,f,w,b,w,e,?,s,s,w,w,p,w,t,p,w,n,g p,x,y,e,f,m,a,c,b,y,e,c,k,y,c,c,p,w,n,n,w,c,d p,k,s,e,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p p,k,s,n,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,l p,k,y,n,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p p,k,s,e,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d e,k,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,b,c,l p,k,y,n,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l e,f,y,n,f,n,f,c,b,w,e,b,y,y,n,n,p,w,t,p,w,y,d e,k,s,g,f,n,f,w,b,w,e,?,s,s,w,w,p,w,t,p,w,n,g p,f,y,e,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,k,y,y,f,n,f,w,n,y,e,c,y,y,y,y,p,y,o,e,w,c,l p,k,y,e,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p p,k,s,e,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l p,k,y,e,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l e,b,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,n,c,l e,x,s,g,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,y,p e,k,s,g,f,n,f,w,b,p,e,?,k,s,w,w,p,w,t,p,w,n,g p,f,y,e,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p p,k,s,e,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p p,k,y,e,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l e,b,f,w,f,n,f,w,b,w,e,?,k,k,w,w,p,w,t,p,w,n,g e,f,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,o,o,p,o,c,l p,k,s,n,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p p,k,s,e,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d e,x,f,w,f,n,f,w,b,g,e,?,k,s,w,w,p,w,t,p,w,s,g p,k,y,e,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l e,x,f,w,f,n,f,w,b,g,e,?,s,s,w,w,p,w,t,p,w,s,g p,k,y,e,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l p,k,y,n,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p e,x,s,g,f,n,f,w,b,p,e,?,k,s,w,w,p,w,t,p,w,n,g e,x,s,w,f,n,f,w,b,g,e,?,s,k,w,w,p,w,t,p,w,n,g p,k,y,n,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d p,k,s,n,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,k,s,e,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d e,b,f,w,f,n,f,w,b,p,e,?,k,k,w,w,p,w,t,p,w,n,g p,f,s,n,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p p,k,s,e,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d p,k,s,n,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l p,x,y,n,f,m,f,c,b,y,e,c,k,y,c,c,p,w,n,n,w,c,d p,k,y,n,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l e,f,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,y,c,l p,x,y,e,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d e,f,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,n,o,p,y,v,l e,b,s,w,f,n,f,w,b,g,e,?,s,s,w,w,p,w,t,p,w,n,g e,b,s,g,f,n,f,w,b,p,e,?,s,s,w,w,p,w,t,p,w,n,g p,k,y,e,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,k,s,n,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d p,k,s,e,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p p,k,s,e,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d e,b,f,w,f,n,f,w,b,g,e,?,s,s,w,w,p,w,t,p,w,s,g e,k,s,g,f,n,f,w,b,p,e,?,s,s,w,w,p,w,t,p,w,n,g p,f,y,e,f,m,f,c,b,w,e,c,k,y,c,c,p,w,n,n,w,c,d p,k,y,n,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d p,k,y,n,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p p,f,s,e,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d p,x,s,n,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d p,k,y,n,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,k,y,c,f,m,f,c,b,y,e,c,k,y,c,c,p,w,n,n,w,c,d p,k,y,n,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d e,k,s,w,f,n,f,w,b,g,e,?,s,s,w,w,p,w,t,p,w,n,g p,f,y,n,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l e,b,f,g,f,n,f,w,b,p,e,?,s,s,w,w,p,w,t,p,w,s,g p,f,s,e,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d p,k,s,e,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l e,k,s,g,f,n,f,w,b,p,e,?,k,s,w,w,p,w,t,p,w,s,g e,x,s,g,f,n,f,w,b,p,e,?,s,s,w,w,p,w,t,p,w,s,g p,k,s,e,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l e,k,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,n,o,p,y,c,l e,f,y,p,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,y,p e,b,s,w,f,n,f,w,b,g,e,?,s,k,w,w,p,w,t,p,w,n,g p,f,y,n,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l p,f,s,e,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,k,s,e,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l e,k,f,g,f,n,f,w,b,p,e,?,s,s,w,w,p,w,t,p,w,n,g e,x,f,w,f,n,f,w,b,p,e,?,k,k,w,w,p,w,t,p,w,s,g e,x,s,c,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,y,p e,k,f,g,f,n,f,w,b,w,e,?,s,s,w,w,p,w,t,p,w,s,g p,k,s,e,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l p,k,y,e,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p p,k,s,n,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p p,x,y,e,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p e,k,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,o,c,l p,f,y,y,f,n,f,w,n,w,e,c,y,y,y,y,p,y,o,e,w,c,l p,x,y,c,f,m,a,c,b,w,e,c,k,y,c,c,p,w,n,n,w,c,d p,x,s,n,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d e,x,y,p,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,v,p p,k,y,n,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p e,k,s,g,f,n,f,w,b,g,e,?,s,k,w,w,p,w,t,p,w,n,g e,b,s,g,f,n,f,w,b,p,e,?,s,k,w,w,p,w,t,p,w,s,g p,k,s,e,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p e,x,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,b,v,l e,b,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,b,v,l e,f,s,n,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,y,p e,k,s,g,f,n,f,w,b,g,e,?,s,s,w,w,p,w,t,p,w,s,g p,f,s,n,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d p,k,s,n,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d p,f,y,n,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l p,k,y,e,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,k,s,n,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l p,k,s,e,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p e,b,s,w,f,n,f,w,b,w,e,?,k,s,w,w,p,w,t,p,w,n,g p,k,y,n,f,m,f,c,b,y,e,c,k,y,c,c,p,w,n,n,w,c,d p,k,y,e,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d e,k,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,y,v,l p,k,s,e,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p e,b,s,w,f,n,f,w,b,w,e,?,k,k,w,w,p,w,t,p,w,s,g e,x,s,g,f,n,f,w,b,p,e,?,k,k,w,w,p,w,t,p,w,s,g p,k,s,n,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l p,k,y,n,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p p,k,s,n,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d p,k,y,e,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p p,k,s,e,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,k,y,n,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p e,b,s,g,f,n,f,w,b,p,e,?,k,k,w,w,p,w,t,p,w,s,g p,k,y,e,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p e,b,f,w,f,n,f,w,b,g,e,?,s,k,w,w,p,w,t,p,w,s,g p,c,y,y,f,n,f,w,n,y,e,c,y,y,y,y,p,y,o,e,w,c,l p,x,s,n,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p p,k,y,e,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l e,x,s,g,f,n,f,w,b,g,e,?,s,s,w,w,p,w,t,p,w,s,g e,b,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,n,o,p,y,v,l p,k,y,e,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l e,b,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,n,c,l p,k,y,e,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l p,k,y,e,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l p,k,s,e,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p e,b,s,g,f,n,f,w,b,p,e,?,s,s,w,w,p,w,t,p,w,s,g e,k,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,o,o,p,n,c,l e,b,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,n,o,p,n,v,l p,x,s,n,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d e,x,s,g,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,v,p e,x,f,g,f,n,f,w,b,w,e,?,k,s,w,w,p,w,t,p,w,s,g p,k,s,n,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l e,k,f,g,f,n,f,w,b,p,e,?,k,s,w,w,p,w,t,p,w,n,g p,k,s,n,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p p,k,y,e,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d p,k,y,n,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d e,f,s,p,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,y,p p,k,y,n,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,k,y,e,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p e,f,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,n,o,p,b,c,l p,k,y,e,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l p,k,y,n,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d p,k,y,n,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d p,f,y,n,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p p,k,s,e,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,k,y,e,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l e,x,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,o,o,p,o,c,l p,f,s,e,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p e,k,s,g,f,n,f,w,b,p,e,?,s,s,w,w,p,w,t,p,w,s,g p,k,s,e,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l p,k,s,e,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l e,f,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,o,o,p,o,v,l p,k,s,n,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l e,x,f,g,f,n,f,w,b,p,e,?,s,k,w,w,p,w,t,p,w,s,g e,k,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,o,o,p,o,v,l p,f,s,e,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p p,k,s,n,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d e,f,y,n,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,y,p e,x,f,g,f,n,f,w,b,g,e,?,s,k,w,w,p,w,t,p,w,n,g e,k,s,w,f,n,f,w,b,w,e,?,k,s,w,w,p,w,t,p,w,n,g e,b,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,n,o,p,b,c,l p,k,y,e,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p p,k,y,e,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l e,k,y,n,f,n,f,c,b,w,e,b,y,y,n,n,p,w,t,p,w,y,p e,x,f,g,f,n,f,w,b,p,e,?,k,k,w,w,p,w,t,p,w,s,g p,k,s,n,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p p,k,y,e,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l p,k,y,n,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d p,f,y,n,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l e,f,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,n,o,p,b,v,l p,f,y,e,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d p,k,s,n,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p p,k,s,n,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l e,b,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,o,o,p,y,c,l e,x,f,g,f,n,f,w,b,g,e,?,k,s,w,w,p,w,t,p,w,n,g p,k,s,n,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p p,k,y,n,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p e,x,s,g,f,n,f,w,b,w,e,?,s,s,w,w,p,w,t,p,w,s,g p,k,y,n,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d p,k,s,e,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,k,y,e,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l e,b,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,o,c,l e,b,s,g,f,n,f,w,b,g,e,?,s,k,w,w,p,w,t,p,w,s,g p,x,y,e,f,m,a,c,b,w,e,c,k,y,c,c,p,w,n,n,w,c,d p,k,s,n,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p p,k,y,e,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d p,k,y,e,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d p,k,s,n,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d p,k,y,e,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l p,k,s,e,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d p,x,s,e,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p p,k,s,e,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d p,k,s,n,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d e,b,f,g,f,n,f,w,b,w,e,?,k,k,w,w,p,w,t,p,w,s,g p,k,y,n,f,m,a,c,b,y,e,c,k,y,c,c,p,w,n,n,w,c,d e,f,s,n,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,v,p p,k,s,n,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,f,y,y,f,n,f,w,n,y,e,c,y,y,y,y,p,y,o,e,w,c,l p,k,s,n,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,f,y,e,f,m,a,c,b,y,e,c,k,y,c,c,p,w,n,n,w,c,d e,x,f,g,f,n,f,w,b,p,e,?,s,s,w,w,p,w,t,p,w,n,g p,k,y,n,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d p,k,s,n,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,f,y,n,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d e,f,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,o,o,p,y,c,l p,k,y,n,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d p,f,y,n,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d p,k,s,n,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p p,f,y,e,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l p,k,s,n,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,x,y,e,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d p,k,y,n,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p e,x,s,w,f,n,f,w,b,p,e,?,k,s,w,w,p,w,t,p,w,s,g e,x,s,g,f,n,f,w,b,g,e,?,s,k,w,w,p,w,t,p,w,s,g e,x,f,w,f,n,f,w,b,w,e,?,k,k,w,w,p,w,t,p,w,s,g p,k,s,n,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d p,k,s,e,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d p,k,y,e,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p p,k,s,e,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d p,k,s,n,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p p,k,y,n,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,k,y,e,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p p,k,s,n,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d p,k,s,e,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d e,f,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,o,c,l p,f,s,n,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d p,k,s,n,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l e,x,s,g,f,n,f,w,b,g,e,?,k,s,w,w,p,w,t,p,w,n,g e,x,f,w,f,n,f,w,b,p,e,?,s,s,w,w,p,w,t,p,w,n,g p,k,y,n,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d e,x,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,n,o,p,o,c,l p,k,y,n,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,k,y,n,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l p,k,y,n,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p p,k,y,e,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l p,k,s,n,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l e,b,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,n,o,p,b,c,l e,f,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,n,c,l e,b,s,w,f,n,f,w,b,g,e,?,k,k,w,w,p,w,t,p,w,s,g p,k,s,n,f,y,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l e,x,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,n,o,p,n,c,l p,k,y,n,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d e,b,f,g,f,n,f,w,b,g,e,?,k,k,w,w,p,w,t,p,w,s,g e,b,s,g,f,n,f,w,b,p,e,?,k,s,w,w,p,w,t,p,w,n,g p,x,s,n,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d e,x,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,o,o,p,b,c,l e,x,s,w,f,n,f,w,b,p,e,?,s,k,w,w,p,w,t,p,w,n,g e,x,s,n,f,n,f,c,b,w,e,b,y,y,n,n,p,w,t,p,w,y,p e,k,s,g,f,n,f,w,b,g,e,?,s,k,w,w,p,w,t,p,w,s,g e,x,s,w,f,n,f,w,b,g,e,?,k,k,w,w,p,w,t,p,w,n,g p,f,y,c,f,m,f,c,b,y,e,c,k,y,c,c,p,w,n,n,w,c,d e,x,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,y,c,l p,k,s,e,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l p,k,y,e,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l e,x,s,w,f,n,f,w,b,p,e,?,k,s,w,w,p,w,t,p,w,n,g e,k,f,w,f,n,f,w,b,g,e,?,k,k,w,w,p,w,t,p,w,s,g e,b,f,g,f,n,f,w,b,p,e,?,k,s,w,w,p,w,t,p,w,s,g e,k,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,o,o,p,b,v,l p,k,y,n,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p p,f,y,e,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,k,s,e,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l e,k,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,n,o,p,n,v,l e,f,s,p,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,v,p p,k,y,n,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p e,b,s,w,f,n,f,w,b,g,e,?,k,s,w,w,p,w,t,p,w,s,g p,k,s,e,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p e,k,s,w,f,n,f,w,b,p,e,?,k,k,w,w,p,w,t,p,w,s,g p,k,y,n,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l p,k,s,n,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l e,f,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,b,c,l p,k,s,n,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l p,k,y,e,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d e,x,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,n,o,p,y,v,l e,x,f,w,f,n,f,w,b,g,e,?,k,k,w,w,p,w,t,p,w,n,g e,x,f,g,f,n,f,w,b,w,e,?,k,s,w,w,p,w,t,p,w,n,g e,x,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,n,o,p,b,v,l p,k,s,n,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p p,k,y,e,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p e,x,s,w,f,n,f,w,b,g,e,?,s,s,w,w,p,w,t,p,w,s,g p,k,y,e,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d e,x,f,g,f,n,f,w,b,w,e,?,s,s,w,w,p,w,t,p,w,s,g p,k,s,n,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l p,f,y,n,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d p,k,s,e,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d e,k,s,n,f,n,f,c,b,w,e,b,y,y,n,n,p,w,t,p,w,y,p p,k,s,e,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,k,s,n,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p e,b,s,g,f,n,f,w,b,g,e,?,s,s,w,w,p,w,t,p,w,s,g p,k,y,n,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l p,k,s,n,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p e,k,f,g,f,n,f,w,b,w,e,?,k,s,w,w,p,w,t,p,w,n,g p,k,y,n,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l p,k,s,e,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l p,k,y,n,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p p,k,s,e,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d e,k,f,w,f,n,f,w,b,g,e,?,s,k,w,w,p,w,t,p,w,n,g p,k,y,e,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d p,k,y,e,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d e,b,f,w,f,n,f,w,b,g,e,?,k,s,w,w,p,w,t,p,w,s,g e,x,s,g,f,n,f,w,b,g,e,?,s,s,w,w,p,w,t,p,w,n,g e,b,s,g,f,n,f,w,b,w,e,?,k,s,w,w,p,w,t,p,w,s,g p,k,y,e,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p p,k,s,n,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p p,k,y,e,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d e,b,s,w,f,n,f,w,b,w,e,?,s,k,w,w,p,w,t,p,w,s,g p,f,s,e,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d p,k,s,n,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d e,k,s,w,f,n,f,w,b,p,e,?,s,k,w,w,p,w,t,p,w,s,g p,k,y,e,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d p,k,s,e,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,k,s,n,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d e,x,s,n,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,v,p p,k,s,n,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,k,y,e,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,b,y,y,f,n,f,w,n,w,e,c,y,y,y,y,p,y,o,e,w,c,l p,k,y,e,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l e,x,s,n,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,y,p p,k,s,e,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p e,k,f,g,f,n,f,w,b,p,e,?,k,k,w,w,p,w,t,p,w,s,g p,k,s,e,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d p,k,s,e,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d p,k,s,n,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l p,k,y,n,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l e,x,f,g,f,n,f,w,b,p,e,?,k,s,w,w,p,w,t,p,w,n,g e,b,s,w,f,n,f,w,b,g,e,?,k,s,w,w,p,w,t,p,w,n,g p,k,y,e,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d e,b,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,n,c,l p,k,y,e,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,k,s,e,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,p e,b,s,g,f,n,f,w,b,g,e,?,k,s,w,w,p,w,t,p,w,s,g p,k,s,e,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p e,b,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,n,o,p,o,v,l p,f,s,n,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p p,k,s,e,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d p,k,s,n,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l p,k,y,n,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l e,b,f,g,f,n,f,w,b,g,e,?,s,s,w,w,p,w,t,p,w,n,g e,k,s,w,f,n,f,w,b,g,e,?,s,s,w,w,p,w,t,p,w,s,g p,k,s,n,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l p,f,y,n,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d e,x,s,w,f,n,f,w,b,p,e,?,k,k,w,w,p,w,t,p,w,s,g e,x,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,b,c,l p,k,s,n,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p p,k,y,n,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l e,k,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,b,v,l e,b,f,w,f,n,f,w,b,w,e,?,k,k,w,w,p,w,t,p,w,s,g e,x,s,w,f,n,f,w,b,w,e,?,k,k,w,w,p,w,t,p,w,n,g p,f,y,e,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p p,k,y,e,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l p,x,y,e,f,m,f,c,b,y,e,c,k,y,c,c,p,w,n,n,w,c,d e,f,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,n,o,p,y,c,l p,k,s,n,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d p,x,s,n,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d p,k,y,e,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d e,b,s,w,f,n,f,w,b,p,e,?,s,s,w,w,p,w,t,p,w,s,g e,b,s,g,f,n,f,w,b,p,e,?,k,s,w,w,p,w,t,p,w,s,g e,k,f,g,f,n,f,w,b,g,e,?,k,s,w,w,p,w,t,p,w,n,g e,k,f,g,f,n,f,w,b,p,e,?,k,k,w,w,p,w,t,p,w,n,g e,x,f,w,f,n,f,w,b,w,e,?,k,s,w,w,p,w,t,p,w,n,g p,k,y,e,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p p,f,y,e,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l p,k,y,e,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l p,f,s,n,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l e,b,s,w,f,n,f,w,b,p,e,?,k,s,w,w,p,w,t,p,w,s,g e,k,s,w,f,n,f,w,b,w,e,?,k,k,w,w,p,w,t,p,w,s,g e,b,f,w,f,n,f,w,b,p,e,?,s,s,w,w,p,w,t,p,w,n,g e,f,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,n,o,p,b,c,l p,k,y,e,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d p,k,s,n,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p p,k,s,n,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p p,f,y,n,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d p,x,s,e,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l e,f,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,o,v,l e,k,f,w,f,n,f,w,b,w,e,?,s,k,w,w,p,w,t,p,w,s,g p,k,s,n,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,x,s,n,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d e,b,f,g,f,n,f,w,b,w,e,?,s,k,w,w,p,w,t,p,w,s,g p,k,y,n,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d e,b,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,y,c,l e,f,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,n,v,l p,k,y,e,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p p,k,s,e,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d p,k,y,n,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p p,k,y,e,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p p,k,y,n,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d e,x,s,g,f,n,f,w,b,w,e,?,k,k,w,w,p,w,t,p,w,s,g p,k,y,n,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d e,f,y,c,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,v,p e,b,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,n,o,p,n,v,l p,k,s,e,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l p,k,s,n,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d p,k,y,n,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p e,b,f,g,f,n,f,w,b,g,e,?,s,k,w,w,p,w,t,p,w,s,g p,k,y,n,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p e,b,f,w,f,n,f,w,b,p,e,?,k,k,w,w,p,w,t,p,w,s,g p,k,s,e,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l e,x,s,w,f,n,f,w,b,p,e,?,s,k,w,w,p,w,t,p,w,s,g p,k,y,e,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l p,k,y,e,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d e,x,s,w,f,n,f,w,b,w,e,?,k,s,w,w,p,w,t,p,w,n,g p,k,y,e,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d p,k,y,n,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p e,k,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,o,v,l e,k,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,n,v,l p,k,s,e,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l p,k,s,e,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p e,k,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,n,o,p,n,c,l p,k,s,n,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d p,k,s,e,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d p,k,y,e,f,s,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d p,k,y,e,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d p,k,y,e,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l e,k,f,w,f,n,f,w,b,w,e,?,s,k,w,w,p,w,t,p,w,n,g e,b,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,n,v,l p,k,s,e,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d e,f,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,b,v,l e,f,y,n,f,n,f,c,b,w,e,b,y,y,n,n,p,w,t,p,w,y,p p,k,y,e,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l e,f,s,g,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,y,p e,x,s,p,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,v,p p,c,y,y,f,n,f,w,n,w,e,c,y,y,y,y,p,y,o,e,w,c,l p,k,s,e,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p p,k,y,e,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d p,k,y,e,f,m,a,c,b,y,e,c,k,y,c,c,p,w,n,n,w,c,d e,b,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,n,o,p,o,v,l p,k,s,n,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l e,x,s,w,f,n,f,w,b,g,e,?,s,k,w,w,p,w,t,p,w,s,g p,x,s,e,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l p,x,y,c,f,m,f,c,b,w,e,c,k,y,c,c,p,w,n,n,w,c,d p,f,s,n,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l e,k,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,b,c,l e,b,y,n,f,n,f,c,b,w,e,b,y,y,n,n,p,w,t,p,w,y,d p,f,s,n,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d p,k,s,n,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p e,b,s,g,f,n,f,w,b,w,e,?,k,k,w,w,p,w,t,p,w,s,g e,x,y,n,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,v,p p,f,s,n,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p e,k,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,y,c,l e,b,f,w,f,n,f,w,b,w,e,?,k,s,w,w,p,w,t,p,w,n,g e,x,f,w,f,n,f,w,b,g,e,?,s,s,w,w,p,w,t,p,w,n,g p,k,s,n,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d p,x,y,n,f,m,a,c,b,y,e,c,k,y,c,c,p,w,n,n,w,c,d p,k,y,e,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p e,x,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,b,c,l p,k,s,e,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p p,x,s,e,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l p,k,s,n,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l p,k,y,e,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d p,k,y,n,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l p,k,s,e,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d e,b,f,g,f,n,f,w,b,p,e,?,s,s,w,w,p,w,t,p,w,n,g e,k,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,y,v,l p,k,y,n,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,k,y,y,f,n,f,w,n,w,e,c,y,y,y,y,p,y,o,e,w,c,l e,k,s,w,f,n,f,w,b,p,e,?,k,s,w,w,p,w,t,p,w,n,g e,x,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,o,o,p,y,c,l p,k,s,n,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p e,k,f,g,f,n,f,w,b,p,e,?,s,k,w,w,p,w,t,p,w,s,g e,k,f,w,f,n,f,w,b,w,e,?,s,s,w,w,p,w,t,p,w,n,g e,f,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,b,c,l e,x,s,w,f,n,f,w,b,p,e,?,k,k,w,w,p,w,t,p,w,n,g e,b,s,g,f,n,f,w,b,w,e,?,k,k,w,w,p,w,t,p,w,n,g e,x,f,w,f,n,f,w,b,w,e,?,s,k,w,w,p,w,t,p,w,n,g e,k,f,w,f,n,f,w,b,p,e,?,k,s,w,w,p,w,t,p,w,n,g p,k,s,n,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d p,k,y,e,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d e,k,f,g,f,n,f,w,b,p,e,?,s,s,w,w,p,w,t,p,w,s,g e,x,s,w,f,n,f,w,b,p,e,?,s,s,w,w,p,w,t,p,w,s,g p,k,s,n,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p p,k,y,n,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,k,y,n,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p p,k,s,e,f,f,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p p,k,s,e,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l e,b,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,n,v,l p,k,s,e,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p e,x,s,g,f,n,f,w,b,p,e,?,s,s,w,w,p,w,t,p,w,n,g e,x,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,y,v,l e,b,s,w,f,n,f,w,b,w,e,?,k,k,w,w,p,w,t,p,w,n,g p,k,s,e,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p e,x,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,n,v,l p,k,s,n,f,f,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d p,k,s,e,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d p,k,y,e,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p e,b,f,w,f,n,f,w,b,p,e,?,s,s,w,w,p,w,t,p,w,s,g p,k,y,n,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d p,k,s,e,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d e,b,s,g,f,n,f,w,b,w,e,?,s,k,w,w,p,w,t,p,w,s,g p,k,s,n,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d p,x,s,n,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p p,k,y,e,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,l e,x,s,w,f,n,f,w,b,p,e,?,s,s,w,w,p,w,t,p,w,n,g e,x,s,w,f,n,f,w,b,g,e,?,k,k,w,w,p,w,t,p,w,s,g p,k,y,n,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p e,k,s,n,f,n,f,c,b,w,e,b,y,y,n,n,p,w,t,p,w,y,d p,k,s,e,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d p,k,y,e,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l e,b,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,o,v,l e,b,f,g,f,n,f,w,b,w,e,?,s,k,w,w,p,w,t,p,w,n,g p,k,s,e,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l p,k,s,n,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l p,f,y,n,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p p,f,y,n,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d e,f,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,y,c,l p,k,y,n,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d e,k,s,w,f,n,f,w,b,w,e,?,s,s,w,w,p,w,t,p,w,s,g e,b,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,b,c,l p,k,y,n,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p p,k,s,n,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p p,k,s,e,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d e,k,s,w,f,n,f,w,b,p,e,?,s,k,w,w,p,w,t,p,w,n,g p,k,y,e,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l e,x,s,w,f,n,f,w,b,w,e,?,s,s,w,w,p,w,t,p,w,s,g p,k,y,e,f,s,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d p,k,y,e,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d p,k,y,n,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d p,f,y,c,f,m,a,c,b,w,e,c,k,y,c,c,p,w,n,n,w,c,d p,x,s,n,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d e,k,f,g,f,n,f,w,b,w,e,?,k,s,w,w,p,w,t,p,w,s,g p,k,s,e,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l p,x,y,n,f,m,f,c,b,w,e,c,k,y,c,c,p,w,n,n,w,c,d p,f,y,e,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l e,k,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,n,o,p,b,c,l p,k,s,n,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p e,b,f,g,f,n,f,w,b,g,e,?,s,k,w,w,p,w,t,p,w,n,g e,b,f,w,f,n,f,w,b,p,e,?,s,k,w,w,p,w,t,p,w,n,g e,x,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,y,v,l p,k,y,n,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,l e,f,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,n,o,p,o,c,l e,x,s,w,f,n,f,w,b,g,e,?,s,s,w,w,p,w,t,p,w,n,g p,k,s,e,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l p,k,s,e,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,p e,x,s,g,f,n,f,w,b,w,e,?,k,k,w,w,p,w,t,p,w,n,g e,b,s,g,f,n,f,w,b,g,e,?,s,s,w,w,p,w,t,p,w,n,g p,k,y,n,f,f,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d p,k,y,e,f,m,f,c,b,w,e,c,k,y,c,c,p,w,n,n,w,c,d p,k,y,e,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p p,k,y,n,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p e,x,f,w,f,n,f,w,b,p,e,?,k,s,w,w,p,w,t,p,w,s,g p,k,y,e,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,l e,b,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,n,o,p,b,v,l p,k,y,n,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d p,k,s,n,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p e,b,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,n,o,p,y,v,l e,f,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,n,v,l e,k,s,g,f,n,f,w,b,w,e,?,k,k,w,w,p,w,t,p,w,n,g e,f,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,y,c,l p,k,y,e,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l e,b,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,n,o,p,b,v,l e,k,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,n,c,l p,k,y,e,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,d e,f,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,n,c,l p,k,s,e,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d e,b,f,g,f,n,f,w,b,g,e,?,k,k,w,w,p,w,t,p,w,n,g p,k,y,n,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d e,f,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,o,o,p,b,v,l p,k,s,n,f,s,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,l e,x,s,g,f,n,f,w,b,w,e,?,k,s,w,w,p,w,t,p,w,s,g e,x,s,g,f,n,f,w,b,g,e,?,k,k,w,w,p,w,t,p,w,s,g e,k,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,n,o,p,b,v,l e,x,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,n,o,p,b,c,l p,k,y,e,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d e,x,f,g,f,n,f,w,b,w,e,?,k,k,w,w,p,w,t,p,w,n,g p,k,s,n,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,k,y,e,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d p,k,y,n,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,p p,k,s,e,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d p,k,y,n,f,s,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l p,k,y,e,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l e,x,s,w,f,n,f,w,b,g,e,?,k,s,w,w,p,w,t,p,w,n,g p,k,s,n,f,s,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l p,k,s,e,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p p,k,s,e,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p e,x,f,g,f,n,f,w,b,w,e,?,s,s,w,w,p,w,t,p,w,n,g e,x,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,o,c,l e,b,s,w,f,n,f,w,b,p,e,?,k,k,w,w,p,w,t,p,w,n,g p,k,s,n,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l p,k,y,n,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l p,k,s,n,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d p,x,y,e,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p p,k,y,e,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d e,x,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,b,v,l e,x,s,g,f,n,f,w,b,g,e,?,k,s,w,w,p,w,t,p,w,s,g p,k,s,e,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,k,y,e,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l e,k,s,w,f,n,f,w,b,g,e,?,k,s,w,w,p,w,t,p,w,n,g e,b,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,b,v,l e,k,s,w,f,n,f,w,b,p,e,?,k,k,w,w,p,w,t,p,w,n,g p,k,s,e,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,d p,k,y,n,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p p,k,s,e,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,l p,k,s,n,f,y,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,d p,x,s,n,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l e,k,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,n,c,l p,k,s,n,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d p,k,s,n,f,s,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,d p,k,y,e,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l e,x,f,w,f,n,f,w,b,p,e,?,s,k,w,w,p,w,t,p,w,s,g p,f,s,e,f,y,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,k,s,n,f,y,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,l p,k,s,e,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,d e,f,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,b,v,l e,x,y,n,f,n,f,c,b,w,e,b,y,y,n,n,p,w,t,p,w,y,d p,k,y,n,f,s,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,d p,k,s,e,f,s,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,l e,b,s,w,f,n,f,w,b,g,e,?,s,k,w,w,p,w,t,p,w,s,g p,k,y,n,f,s,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p p,k,s,n,f,y,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,p e,x,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,n,c,l e,x,s,g,f,n,f,w,b,p,e,?,s,k,w,w,p,w,t,p,w,s,g e,x,s,g,f,n,f,w,b,g,e,?,k,k,w,w,p,w,t,p,w,n,g p,f,y,n,f,y,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,p p,f,y,n,f,s,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d e,f,y,g,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,v,p p,k,s,e,f,y,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d e,x,f,w,f,n,f,w,b,w,e,?,k,s,w,w,p,w,t,p,w,s,g p,k,y,n,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p p,k,s,n,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p p,x,s,e,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p e,x,f,g,f,n,f,w,b,p,e,?,k,s,w,w,p,w,t,p,w,s,g e,f,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,o,o,p,n,v,l p,x,y,e,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p e,b,f,w,f,n,f,w,b,w,e,?,s,s,w,w,p,w,t,p,w,s,g p,k,s,e,f,f,f,c,n,b,t,?,s,s,w,w,p,w,o,e,w,v,l e,x,f,g,f,n,f,w,b,p,e,?,s,s,w,w,p,w,t,p,w,s,g p,f,y,n,f,m,a,c,b,y,e,c,k,y,c,c,p,w,n,n,w,c,d e,x,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,n,o,p,o,v,l e,b,s,g,f,n,f,w,b,p,e,?,s,k,w,w,p,w,t,p,w,n,g e,b,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,o,o,p,o,v,l p,k,s,e,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,d e,f,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,o,v,l e,x,f,g,f,n,f,w,b,w,e,?,s,k,w,w,p,w,t,p,w,n,g p,k,s,n,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p e,x,f,w,f,n,f,w,b,p,e,?,s,k,w,w,p,w,t,p,w,n,g e,f,y,p,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,v,p p,k,y,e,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l e,k,f,g,f,n,f,w,b,w,e,?,s,k,w,w,p,w,t,p,w,n,g e,k,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,y,c,l p,k,s,n,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,d p,k,s,n,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l p,k,s,e,f,s,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,p p,k,y,n,f,s,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,d e,k,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,o,c,l p,k,y,n,f,s,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,p e,k,f,w,f,n,f,w,b,p,e,?,s,k,w,w,p,w,t,p,w,s,g p,k,y,e,f,f,f,c,n,b,t,?,k,k,p,w,p,w,o,e,w,v,p e,f,s,n,f,n,f,c,b,w,e,b,y,y,n,n,p,w,t,p,w,y,p p,k,s,e,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p e,x,f,g,f,n,f,w,b,w,e,?,k,k,w,w,p,w,t,p,w,s,g p,k,y,e,f,f,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,d p,k,y,e,f,y,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d p,k,s,n,f,f,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,l e,b,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,n,o,p,o,c,l e,k,s,w,f,n,f,w,b,w,e,?,s,s,w,w,p,w,t,p,w,n,g e,b,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,o,c,l e,f,y,g,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,y,p p,k,y,e,f,m,a,c,b,w,e,c,k,y,c,c,p,w,n,n,w,c,d p,x,y,e,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,d p,k,y,n,f,f,f,c,n,b,t,?,k,s,p,w,p,w,o,e,w,v,p e,k,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,y,v,l e,k,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,o,o,p,o,c,l e,x,y,c,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,v,p p,k,s,e,f,s,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l p,k,y,n,f,y,f,c,n,b,t,?,s,k,p,p,p,w,o,e,w,v,l p,k,s,e,f,s,f,c,n,b,t,?,s,s,p,w,p,w,o,e,w,v,l p,k,y,n,f,y,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d p,k,y,e,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,p e,f,s,c,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,v,p e,x,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,n,c,l e,b,f,w,f,n,f,w,b,w,e,?,s,k,w,w,p,w,t,p,w,n,g e,k,f,g,f,n,f,w,b,g,e,?,s,k,w,w,p,w,t,p,w,s,g e,f,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,o,c,l e,k,s,n,f,n,a,c,b,n,e,?,s,s,o,o,p,n,o,p,o,c,l e,k,f,w,f,n,f,w,b,g,e,?,s,s,w,w,p,w,t,p,w,n,g p,k,y,e,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,l e,b,f,w,f,n,f,w,b,g,e,?,k,k,w,w,p,w,t,p,w,s,g p,k,y,n,f,y,f,c,n,b,t,?,s,s,w,p,p,w,o,e,w,v,p p,k,y,e,f,y,f,c,n,b,t,?,k,k,w,p,p,w,o,e,w,v,d p,k,y,n,f,f,f,c,n,b,t,?,s,k,w,p,p,w,o,e,w,v,d e,x,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,y,v,l e,x,y,n,t,n,f,c,b,w,e,b,s,s,w,w,p,w,t,p,w,y,p e,b,s,w,f,n,f,w,b,p,e,?,s,k,w,w,p,w,t,p,w,n,g p,f,y,n,f,f,f,c,n,b,t,?,k,s,w,p,p,w,o,e,w,v,d p,k,s,n,f,f,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,l p,k,s,e,f,y,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p e,x,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,y,c,l e,x,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,n,o,p,n,v,l e,b,s,w,f,n,f,w,b,w,e,?,s,s,w,w,p,w,t,p,w,s,g p,x,y,e,f,f,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,p e,b,f,w,f,n,f,w,b,w,e,?,k,s,w,w,p,w,t,p,w,s,g e,b,f,w,f,n,f,w,b,g,e,?,s,k,w,w,p,w,t,p,w,n,g e,b,f,w,f,n,f,w,b,g,e,?,k,s,w,w,p,w,t,p,w,n,g e,k,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,o,v,l p,k,y,e,f,s,f,c,n,b,t,?,s,k,p,w,p,w,o,e,w,v,p e,k,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,n,o,p,o,v,l p,k,s,e,f,f,f,c,n,b,t,?,k,s,w,w,p,w,o,e,w,v,d p,k,y,c,f,m,a,c,b,y,e,c,k,y,c,c,p,w,n,n,w,c,d p,k,s,n,f,y,f,c,n,b,t,?,s,s,p,p,p,w,o,e,w,v,d e,x,s,g,f,n,f,w,b,g,e,?,s,k,w,w,p,w,t,p,w,n,g e,f,s,n,f,n,f,c,b,w,e,b,y,y,n,n,p,w,t,p,w,y,d e,k,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,n,o,p,y,c,l e,b,y,n,f,n,f,c,b,w,e,b,y,y,n,n,p,w,t,p,w,y,p p,x,s,n,f,f,f,c,n,b,t,?,k,k,p,p,p,w,o,e,w,v,l e,b,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,o,o,p,b,c,l p,f,s,n,f,y,f,c,n,b,t,?,k,k,w,w,p,w,o,e,w,v,p p,k,y,n,f,f,f,c,n,b,t,?,k,s,p,p,p,w,o,e,w,v,p e,k,s,g,f,n,f,w,b,w,e,?,k,s,w,w,p,w,t,p,w,n,g p,k,y,n,f,f,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,l e,k,f,g,f,n,f,w,b,g,e,?,k,s,w,w,p,w,t,p,w,s,g e,x,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,n,o,p,o,c,l p,k,s,e,f,y,f,c,n,b,t,?,s,k,w,w,p,w,o,e,w,v,p e,f,s,n,f,n,a,c,b,o,e,?,s,s,o,o,p,n,o,p,y,v,l 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e,x,s,n,f,n,a,c,b,y,e,?,s,s,o,o,p,o,o,p,o,c,l ================================================ FILE: lime/__init__.py ================================================ ================================================ FILE: lime/bundle.js ================================================ var lime = /******/ (function(modules) { // webpackBootstrap /******/ // The module cache /******/ var installedModules = {}; /******/ /******/ // The require function /******/ function __webpack_require__(moduleId) { /******/ /******/ // Check if module is in cache /******/ if(installedModules[moduleId]) /******/ return installedModules[moduleId].exports; /******/ /******/ // Create a new module (and put it into the cache) /******/ var module = installedModules[moduleId] = { /******/ exports: {}, /******/ id: moduleId, /******/ loaded: false /******/ }; /******/ /******/ // Execute the module function /******/ modules[moduleId].call(module.exports, module, module.exports, __webpack_require__); /******/ /******/ // Flag the module as loaded /******/ module.loaded = true; /******/ /******/ // Return the exports of the module /******/ return module.exports; /******/ } /******/ /******/ /******/ // expose the modules object (__webpack_modules__) /******/ __webpack_require__.m = modules; /******/ /******/ // expose the module cache /******/ __webpack_require__.c = installedModules; /******/ /******/ // __webpack_public_path__ /******/ __webpack_require__.p = ""; /******/ /******/ // Load entry module and return exports /******/ return __webpack_require__(0); /******/ }) /************************************************************************/ /******/ ([ /* 0 */ /***/ (function(module, exports, __webpack_require__) { /* WEBPACK VAR INJECTION */(function(global) {'use strict'; Object.defineProperty(exports, "__esModule", { value: true }); exports.PredictedValue = exports.PredictProba = exports.Barchart = exports.Explanation = undefined; var _explanation = __webpack_require__(1); var _explanation2 = _interopRequireDefault(_explanation); var _bar_chart = __webpack_require__(3); var _bar_chart2 = _interopRequireDefault(_bar_chart); var _predict_proba = __webpack_require__(6); var _predict_proba2 = _interopRequireDefault(_predict_proba); var _predicted_value = __webpack_require__(7); var _predicted_value2 = _interopRequireDefault(_predicted_value); function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { default: obj }; } if (!global._babelPolyfill) { __webpack_require__(8); } __webpack_require__(339); exports.Explanation = _explanation2.default; exports.Barchart = _bar_chart2.default; exports.PredictProba = _predict_proba2.default; exports.PredictedValue = _predicted_value2.default; //require('style-loader'); /* WEBPACK VAR INJECTION */}.call(exports, (function() { return this; }()))) /***/ }), /* 1 */ /***/ (function(module, exports, __webpack_require__) { 'use strict'; Object.defineProperty(exports, "__esModule", { value: true }); var _slicedToArray = function () { function sliceIterator(arr, i) { var _arr = []; var _n = true; var _d = false; var _e = undefined; try { for (var _i = arr[Symbol.iterator](), _s; !(_n = (_s = _i.next()).done); _n = true) { _arr.push(_s.value); if (i && _arr.length === i) break; } } catch (err) { _d = true; _e = err; } finally { try { if (!_n && _i["return"]) _i["return"](); } finally { if (_d) throw _e; } } return _arr; } return function (arr, i) { if (Array.isArray(arr)) { return arr; } else if (Symbol.iterator in Object(arr)) { return sliceIterator(arr, i); } else { throw new TypeError("Invalid attempt to destructure non-iterable instance"); } }; }(); var _d2 = __webpack_require__(2); var _d3 = _interopRequireDefault(_d2); var _bar_chart = __webpack_require__(3); var _bar_chart2 = _interopRequireDefault(_bar_chart); var _lodash = __webpack_require__(4); function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { default: obj }; } function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError("Cannot call a class as a function"); } } var Explanation = function () { function Explanation(class_names) { _classCallCheck(this, Explanation); this.names = class_names; if (class_names.length < 10) { this.colors = _d3.default.scale.category10().domain(this.names); this.colors_i = _d3.default.scale.category10().domain((0, _lodash.range)(this.names.length)); } else { this.colors = _d3.default.scale.category20().domain(this.names); this.colors_i = _d3.default.scale.category20().domain((0, _lodash.range)(this.names.length)); } } // exp: [(feature-name, weight), ...] // label: int // div: d3 selection Explanation.prototype.show = function show(exp, label, div) { var svg = div.append('svg').style('width', '100%'); var colors = ['#5F9EA0', this.colors_i(label)]; var names = ['NOT ' + this.names[label], this.names[label]]; if (this.names.length == 2) { colors = [this.colors_i(0), this.colors_i(1)]; names = this.names; } var plot = new _bar_chart2.default(svg, exp, true, names, colors, true, 10); svg.style('height', plot.svg_height + 'px'); }; // exp has all ocurrences of words, with start index and weight: // exp = [('word', 132, -0.13), ('word3', 111, 1.3) Explanation.prototype.show_raw_text = function show_raw_text(exp, label, raw, div) { var opacity = arguments.length > 4 && arguments[4] !== undefined ? arguments[4] : true; //let colors=['#5F9EA0', this.colors(this.exp['class'])]; var colors = ['#5F9EA0', this.colors_i(label)]; if (this.names.length == 2) { colors = [this.colors_i(0), this.colors_i(1)]; } var word_lists = [[], []]; var max_weight = -1; var _iteratorNormalCompletion = true; var _didIteratorError = false; var _iteratorError = undefined; try { for (var _iterator = exp[Symbol.iterator](), _step; !(_iteratorNormalCompletion = (_step = _iterator.next()).done); _iteratorNormalCompletion = true) { var _step$value = _slicedToArray(_step.value, 3), word = _step$value[0], start = _step$value[1], weight = _step$value[2]; if (weight > 0) { word_lists[1].push([start, start + word.length, weight]); } else { word_lists[0].push([start, start + word.length, -weight]); } max_weight = Math.max(max_weight, Math.abs(weight)); } } catch (err) { _didIteratorError = true; _iteratorError = err; } finally { try { if (!_iteratorNormalCompletion && _iterator.return) { _iterator.return(); } } finally { if (_didIteratorError) { throw _iteratorError; } } } if (!opacity) { max_weight = 0; } this.display_raw_text(div, raw, word_lists, colors, max_weight, true); }; // exp is list of (feature_name, value, weight) Explanation.prototype.show_raw_tabular = function show_raw_tabular(exp, label, div) { div.classed('lime', true).classed('table_div', true); var colors = ['#5F9EA0', this.colors_i(label)]; if (this.names.length == 2) { colors = [this.colors_i(0), this.colors_i(1)]; } var table = div.append('table'); var thead = table.append('tr'); thead.append('td').text('Feature'); thead.append('td').text('Value'); thead.style('color', 'black').style('font-size', '20px'); var _iteratorNormalCompletion2 = true; var _didIteratorError2 = false; var _iteratorError2 = undefined; try { for (var _iterator2 = exp[Symbol.iterator](), _step2; !(_iteratorNormalCompletion2 = (_step2 = _iterator2.next()).done); _iteratorNormalCompletion2 = true) { var _step2$value = _slicedToArray(_step2.value, 3), fname = _step2$value[0], value = _step2$value[1], weight = _step2$value[2]; var tr = table.append('tr'); tr.style('border-style', 'hidden'); tr.append('td').text(fname); tr.append('td').text(value); if (weight > 0) { tr.style('background-color', colors[1]); } else if (weight < 0) { tr.style('background-color', colors[0]); } else { tr.style('color', 'black'); } } } catch (err) { _didIteratorError2 = true; _iteratorError2 = err; } finally { try { if (!_iteratorNormalCompletion2 && _iterator2.return) { _iterator2.return(); } } finally { if (_didIteratorError2) { throw _iteratorError2; } } } }; Explanation.prototype.hexToRgb = function hexToRgb(hex) { var result = /^#?([a-f\d]{2})([a-f\d]{2})([a-f\d]{2})$/i.exec(hex); return result ? { r: parseInt(result[1], 16), g: parseInt(result[2], 16), b: parseInt(result[3], 16) } : null; }; Explanation.prototype.applyAlpha = function applyAlpha(hex, alpha) { var components = this.hexToRgb(hex); return 'rgba(' + components.r + "," + components.g + "," + components.b + "," + alpha.toFixed(3) + ")"; }; // sord_lists is an array of arrays, of length (colors). if with_positions is true, // word_lists is an array of [start,end] positions instead Explanation.prototype.display_raw_text = function display_raw_text(div, raw_text) { var word_lists = arguments.length > 2 && arguments[2] !== undefined ? arguments[2] : []; var colors = arguments.length > 3 && arguments[3] !== undefined ? arguments[3] : []; var max_weight = arguments.length > 4 && arguments[4] !== undefined ? arguments[4] : 1; var positions = arguments.length > 5 && arguments[5] !== undefined ? arguments[5] : false; div.classed('lime', true).classed('text_div', true); div.append('h3').text('Text with highlighted words'); var highlight_tag = 'span'; var text_span = div.append('span').style('white-space', 'pre-wrap').text(raw_text); var position_lists = word_lists; if (!positions) { position_lists = this.wordlists_to_positions(word_lists, raw_text); } var objects = []; var _iteratorNormalCompletion3 = true; var _didIteratorError3 = false; var _iteratorError3 = undefined; try { var _loop = function _loop() { var i = _step3.value; position_lists[i].map(function (x) { return objects.push({ 'label': i, 'start': x[0], 'end': x[1], 'alpha': max_weight === 0 ? 1 : x[2] / max_weight }); }); }; for (var _iterator3 = (0, _lodash.range)(position_lists.length)[Symbol.iterator](), _step3; !(_iteratorNormalCompletion3 = (_step3 = _iterator3.next()).done); _iteratorNormalCompletion3 = true) { _loop(); } } catch (err) { _didIteratorError3 = true; _iteratorError3 = err; } finally { try { if (!_iteratorNormalCompletion3 && _iterator3.return) { _iterator3.return(); } } finally { if (_didIteratorError3) { throw _iteratorError3; } } } objects = (0, _lodash.sortBy)(objects, function (x) { return x['start']; }); var node = text_span.node().childNodes[0]; var subtract = 0; var _iteratorNormalCompletion4 = true; var _didIteratorError4 = false; var _iteratorError4 = undefined; try { for (var _iterator4 = objects[Symbol.iterator](), _step4; !(_iteratorNormalCompletion4 = (_step4 = _iterator4.next()).done); _iteratorNormalCompletion4 = true) { var obj = _step4.value; var word = raw_text.slice(obj.start, obj.end); var start = obj.start - subtract; var end = obj.end - subtract; var match = document.createElement(highlight_tag); match.appendChild(document.createTextNode(word)); match.style.backgroundColor = this.applyAlpha(colors[obj.label], obj.alpha); var after = node.splitText(start); after.nodeValue = after.nodeValue.substring(word.length); node.parentNode.insertBefore(match, after); subtract += end; node = after; } } catch (err) { _didIteratorError4 = true; _iteratorError4 = err; } finally { try { if (!_iteratorNormalCompletion4 && _iterator4.return) { _iterator4.return(); } } finally { if (_didIteratorError4) { throw _iteratorError4; } } } }; Explanation.prototype.wordlists_to_positions = function wordlists_to_positions(word_lists, raw_text) { var ret = []; var _iteratorNormalCompletion5 = true; var _didIteratorError5 = false; var _iteratorError5 = undefined; try { for (var _iterator5 = word_lists[Symbol.iterator](), _step5; !(_iteratorNormalCompletion5 = (_step5 = _iterator5.next()).done); _iteratorNormalCompletion5 = true) { var words = _step5.value; if (words.length === 0) { ret.push([]); continue; } var re = new RegExp("\\b(" + words.join('|') + ")\\b", 'gm'); var temp = void 0; var list = []; while ((temp = re.exec(raw_text)) !== null) { list.push([temp.index, temp.index + temp[0].length]); } ret.push(list); } } catch (err) { _didIteratorError5 = true; _iteratorError5 = err; } finally { try { if (!_iteratorNormalCompletion5 && _iterator5.return) { _iterator5.return(); } } finally { if (_didIteratorError5) { throw _iteratorError5; } } } return ret; }; return Explanation; }(); exports.default = Explanation; /***/ }), /* 2 */ /***/ (function(module, exports, __webpack_require__) { var __WEBPACK_AMD_DEFINE_FACTORY__, __WEBPACK_AMD_DEFINE_RESULT__;!function() { var d3 = { version: "3.5.17" }; var d3_arraySlice = [].slice, d3_array = function(list) { return d3_arraySlice.call(list); }; var d3_document = this.document; function d3_documentElement(node) { return node && (node.ownerDocument || node.document || node).documentElement; } function d3_window(node) { return node && (node.ownerDocument && node.ownerDocument.defaultView || node.document && node || node.defaultView); } if (d3_document) { try { d3_array(d3_document.documentElement.childNodes)[0].nodeType; } catch (e) { d3_array = function(list) { var i = list.length, array = new Array(i); while (i--) array[i] = list[i]; return array; }; } } if (!Date.now) Date.now = function() { return +new Date(); }; if (d3_document) { try { d3_document.createElement("DIV").style.setProperty("opacity", 0, ""); } catch (error) { var d3_element_prototype = this.Element.prototype, d3_element_setAttribute = d3_element_prototype.setAttribute, d3_element_setAttributeNS = d3_element_prototype.setAttributeNS, d3_style_prototype = this.CSSStyleDeclaration.prototype, d3_style_setProperty = d3_style_prototype.setProperty; d3_element_prototype.setAttribute = function(name, value) { d3_element_setAttribute.call(this, name, value + ""); }; d3_element_prototype.setAttributeNS = function(space, local, value) { d3_element_setAttributeNS.call(this, space, local, value + ""); }; d3_style_prototype.setProperty = function(name, value, priority) { d3_style_setProperty.call(this, name, value + "", priority); }; } } d3.ascending = d3_ascending; function d3_ascending(a, b) { return a < b ? -1 : a > b ? 1 : a >= b ? 0 : NaN; } d3.descending = function(a, b) { return b < a ? -1 : b > a ? 1 : b >= a ? 0 : NaN; }; d3.min = function(array, f) { var i = -1, n = array.length, a, b; if (arguments.length === 1) { while (++i < n) if ((b = array[i]) != null && b >= b) { a = b; break; } while (++i < n) if ((b = array[i]) != null && a > b) a = b; } else { while (++i < n) if ((b = f.call(array, array[i], i)) != null && b >= b) { a = b; break; } while (++i < n) if ((b = f.call(array, array[i], i)) != null && a > b) a = b; } return a; }; d3.max = function(array, f) { var i = -1, n = array.length, a, b; if (arguments.length === 1) { while (++i < n) if ((b = array[i]) != null && b >= b) { a = b; break; } while (++i < n) if ((b = array[i]) != null && b > a) a = b; } else { while (++i < n) if ((b = f.call(array, array[i], i)) != null && b >= b) { a = b; break; } while (++i < n) if ((b = f.call(array, array[i], i)) != null && b > a) a = b; } return a; }; d3.extent = function(array, f) { var i = -1, n = array.length, a, b, c; if (arguments.length === 1) { while (++i < n) if ((b = array[i]) != null && b >= b) { a = c = b; break; } while (++i < n) if ((b = array[i]) != null) { if (a > b) a = b; if (c < b) c = b; } } else { while (++i < n) if ((b = f.call(array, array[i], i)) != null && b >= b) { a = c = b; break; } while (++i < n) if ((b = f.call(array, array[i], i)) != null) { if (a > b) a = b; if (c < b) c = b; } } return [ a, c ]; }; function d3_number(x) { return x === null ? NaN : +x; } function d3_numeric(x) { return !isNaN(x); } d3.sum = function(array, f) { var s = 0, n = array.length, a, i = -1; if (arguments.length === 1) { while (++i < n) if (d3_numeric(a = +array[i])) s += a; } else { while (++i < n) if (d3_numeric(a = +f.call(array, array[i], i))) s += a; } return s; }; d3.mean = function(array, f) { var s = 0, n = array.length, a, i = -1, j = n; if (arguments.length === 1) { while (++i < n) if (d3_numeric(a = d3_number(array[i]))) s += a; else --j; } else { while (++i < n) if (d3_numeric(a = d3_number(f.call(array, array[i], i)))) s += a; else --j; } if (j) return s / j; }; d3.quantile = function(values, p) { var H = (values.length - 1) * p + 1, h = Math.floor(H), v = +values[h - 1], e = H - h; return e ? v + e * (values[h] - v) : v; }; d3.median = function(array, f) { var numbers = [], n = array.length, a, i = -1; if (arguments.length === 1) { while (++i < n) if (d3_numeric(a = d3_number(array[i]))) numbers.push(a); } else { while (++i < n) if (d3_numeric(a = d3_number(f.call(array, array[i], i)))) numbers.push(a); } if (numbers.length) return d3.quantile(numbers.sort(d3_ascending), .5); }; d3.variance = function(array, f) { var n = array.length, m = 0, a, d, s = 0, i = -1, j = 0; if (arguments.length === 1) { while (++i < n) { if (d3_numeric(a = d3_number(array[i]))) { d = a - m; m += d / ++j; s += d * (a - m); } } } else { while (++i < n) { if (d3_numeric(a = d3_number(f.call(array, array[i], i)))) { d = a - m; m += d / ++j; s += d * (a - m); } } } if (j > 1) return s / (j - 1); }; d3.deviation = function() { var v = d3.variance.apply(this, arguments); return v ? Math.sqrt(v) : v; }; function d3_bisector(compare) { return { left: function(a, x, lo, hi) { if (arguments.length < 3) lo = 0; if (arguments.length < 4) hi = a.length; while (lo < hi) { var mid = lo + hi >>> 1; if (compare(a[mid], x) < 0) lo = mid + 1; else hi = mid; } return lo; }, right: function(a, x, lo, hi) { if (arguments.length < 3) lo = 0; if (arguments.length < 4) hi = a.length; while (lo < hi) { var mid = lo + hi >>> 1; if (compare(a[mid], x) > 0) hi = mid; else lo = mid + 1; } return lo; } }; } var d3_bisect = d3_bisector(d3_ascending); d3.bisectLeft = d3_bisect.left; d3.bisect = d3.bisectRight = d3_bisect.right; d3.bisector = function(f) { return d3_bisector(f.length === 1 ? function(d, x) { return d3_ascending(f(d), x); } : f); }; d3.shuffle = function(array, i0, i1) { if ((m = arguments.length) < 3) { i1 = array.length; if (m < 2) i0 = 0; } var m = i1 - i0, t, i; while (m) { i = Math.random() * m-- | 0; t = array[m + i0], array[m + i0] = array[i + i0], array[i + i0] = t; } return array; }; d3.permute = function(array, indexes) { var i = indexes.length, permutes = new Array(i); while (i--) permutes[i] = array[indexes[i]]; return permutes; }; d3.pairs = function(array) { var i = 0, n = array.length - 1, p0, p1 = array[0], pairs = new Array(n < 0 ? 0 : n); while (i < n) pairs[i] = [ p0 = p1, p1 = array[++i] ]; return pairs; }; d3.transpose = function(matrix) { if (!(n = matrix.length)) return []; for (var i = -1, m = d3.min(matrix, d3_transposeLength), transpose = new Array(m); ++i < m; ) { for (var j = -1, n, row = transpose[i] = new Array(n); ++j < n; ) { row[j] = matrix[j][i]; } } return transpose; }; function d3_transposeLength(d) { return d.length; } d3.zip = function() { return d3.transpose(arguments); }; d3.keys = function(map) { var keys = []; for (var key in map) keys.push(key); return keys; }; d3.values = function(map) { var values = []; for (var key in map) values.push(map[key]); return values; }; d3.entries = function(map) { var entries = []; for (var key in map) entries.push({ key: key, value: map[key] }); return entries; }; d3.merge = function(arrays) { var n = arrays.length, m, i = -1, j = 0, merged, array; while (++i < n) j += arrays[i].length; merged = new Array(j); while (--n >= 0) { array = arrays[n]; m = array.length; while (--m >= 0) { merged[--j] = array[m]; } } return merged; }; var abs = Math.abs; d3.range = function(start, stop, step) { if (arguments.length < 3) { step = 1; if (arguments.length < 2) { stop = start; start = 0; } } if ((stop - start) / step === Infinity) throw new Error("infinite range"); var range = [], k = d3_range_integerScale(abs(step)), i = -1, j; start *= k, stop *= k, step *= k; if (step < 0) while ((j = start + step * ++i) > stop) range.push(j / k); else while ((j = start + step * ++i) < stop) range.push(j / k); return range; }; function d3_range_integerScale(x) { var k = 1; while (x * k % 1) k *= 10; return k; } function d3_class(ctor, properties) { for (var key in properties) { Object.defineProperty(ctor.prototype, key, { value: properties[key], enumerable: false }); } } d3.map = function(object, f) { var map = new d3_Map(); if (object instanceof d3_Map) { object.forEach(function(key, value) { map.set(key, value); }); } else if (Array.isArray(object)) { var i = -1, n = object.length, o; if (arguments.length === 1) while (++i < n) map.set(i, object[i]); else while (++i < n) map.set(f.call(object, o = object[i], i), o); } else { for (var key in object) map.set(key, object[key]); } return map; }; function d3_Map() { this._ = Object.create(null); } var d3_map_proto = "__proto__", d3_map_zero = "\x00"; d3_class(d3_Map, { has: d3_map_has, get: function(key) { return this._[d3_map_escape(key)]; }, set: function(key, value) { return this._[d3_map_escape(key)] = value; }, remove: d3_map_remove, keys: d3_map_keys, values: function() { var values = []; for (var key in this._) values.push(this._[key]); return values; }, entries: function() { var entries = []; for (var key in this._) entries.push({ key: d3_map_unescape(key), value: this._[key] }); return entries; }, size: d3_map_size, empty: d3_map_empty, forEach: function(f) { for (var key in this._) f.call(this, d3_map_unescape(key), this._[key]); } }); function d3_map_escape(key) { return (key += "") === d3_map_proto || key[0] === d3_map_zero ? d3_map_zero + key : key; } function d3_map_unescape(key) { return (key += "")[0] === d3_map_zero ? key.slice(1) : key; } function d3_map_has(key) { return d3_map_escape(key) in this._; } function d3_map_remove(key) { return (key = d3_map_escape(key)) in this._ && delete this._[key]; } function d3_map_keys() { var keys = []; for (var key in this._) keys.push(d3_map_unescape(key)); return keys; } function d3_map_size() { var size = 0; for (var key in this._) ++size; return size; } function d3_map_empty() { for (var key in this._) return false; return true; } d3.nest = function() { var nest = {}, keys = [], sortKeys = [], sortValues, rollup; function map(mapType, array, depth) { if (depth >= keys.length) return rollup ? rollup.call(nest, array) : sortValues ? array.sort(sortValues) : array; var i = -1, n = array.length, key = keys[depth++], keyValue, object, setter, valuesByKey = new d3_Map(), values; while (++i < n) { if (values = valuesByKey.get(keyValue = key(object = array[i]))) { values.push(object); } else { valuesByKey.set(keyValue, [ object ]); } } if (mapType) { object = mapType(); setter = function(keyValue, values) { object.set(keyValue, map(mapType, values, depth)); }; } else { object = {}; setter = function(keyValue, values) { object[keyValue] = map(mapType, values, depth); }; } valuesByKey.forEach(setter); return object; } function entries(map, depth) { if (depth >= keys.length) return map; var array = [], sortKey = sortKeys[depth++]; map.forEach(function(key, keyMap) { array.push({ key: key, values: entries(keyMap, depth) }); }); return sortKey ? array.sort(function(a, b) { return sortKey(a.key, b.key); }) : array; } nest.map = function(array, mapType) { return map(mapType, array, 0); }; nest.entries = function(array) { return entries(map(d3.map, array, 0), 0); }; nest.key = function(d) { keys.push(d); return nest; }; nest.sortKeys = function(order) { sortKeys[keys.length - 1] = order; return nest; }; nest.sortValues = function(order) { sortValues = order; return nest; }; nest.rollup = function(f) { rollup = f; return nest; }; return nest; }; d3.set = function(array) { var set = new d3_Set(); if (array) for (var i = 0, n = array.length; i < n; ++i) set.add(array[i]); return set; }; function d3_Set() { this._ = Object.create(null); } d3_class(d3_Set, { has: d3_map_has, add: function(key) { this._[d3_map_escape(key += "")] = true; return key; }, remove: d3_map_remove, values: d3_map_keys, size: d3_map_size, empty: d3_map_empty, forEach: function(f) { for (var key in this._) f.call(this, d3_map_unescape(key)); } }); d3.behavior = {}; function d3_identity(d) { return d; } d3.rebind = function(target, source) { var i = 1, n = arguments.length, method; while (++i < n) target[method = arguments[i]] = d3_rebind(target, source, source[method]); return target; }; function d3_rebind(target, source, method) { return function() { var value = method.apply(source, arguments); return value === source ? target : value; }; } function d3_vendorSymbol(object, name) { if (name in object) return name; name = name.charAt(0).toUpperCase() + name.slice(1); for (var i = 0, n = d3_vendorPrefixes.length; i < n; ++i) { var prefixName = d3_vendorPrefixes[i] + name; if (prefixName in object) return prefixName; } } var d3_vendorPrefixes = [ "webkit", "ms", "moz", "Moz", "o", "O" ]; function d3_noop() {} d3.dispatch = function() { var dispatch = new d3_dispatch(), i = -1, n = arguments.length; while (++i < n) dispatch[arguments[i]] = d3_dispatch_event(dispatch); return dispatch; }; function d3_dispatch() {} d3_dispatch.prototype.on = function(type, listener) { var i = type.indexOf("."), name = ""; if (i >= 0) { name = type.slice(i + 1); type = type.slice(0, i); } if (type) return arguments.length < 2 ? this[type].on(name) : this[type].on(name, listener); if (arguments.length === 2) { if (listener == null) for (type in this) { if (this.hasOwnProperty(type)) this[type].on(name, null); } return this; } }; function d3_dispatch_event(dispatch) { var listeners = [], listenerByName = new d3_Map(); function event() { var z = listeners, i = -1, n = z.length, l; while (++i < n) if (l = z[i].on) l.apply(this, arguments); return dispatch; } event.on = function(name, listener) { var l = listenerByName.get(name), i; if (arguments.length < 2) return l && l.on; if (l) { l.on = null; listeners = listeners.slice(0, i = listeners.indexOf(l)).concat(listeners.slice(i + 1)); listenerByName.remove(name); } if (listener) listeners.push(listenerByName.set(name, { on: listener })); return dispatch; }; return event; } d3.event = null; function d3_eventPreventDefault() { d3.event.preventDefault(); } function d3_eventSource() { var e = d3.event, s; while (s = e.sourceEvent) e = s; return e; } function d3_eventDispatch(target) { var dispatch = new d3_dispatch(), i = 0, n = arguments.length; while (++i < n) dispatch[arguments[i]] = d3_dispatch_event(dispatch); dispatch.of = function(thiz, argumentz) { return function(e1) { try { var e0 = e1.sourceEvent = d3.event; e1.target = target; d3.event = e1; dispatch[e1.type].apply(thiz, argumentz); } finally { d3.event = e0; } }; }; return dispatch; } d3.requote = function(s) { return s.replace(d3_requote_re, "\\$&"); }; var d3_requote_re = /[\\\^\$\*\+\?\|\[\]\(\)\.\{\}]/g; var d3_subclass = {}.__proto__ ? function(object, prototype) { object.__proto__ = prototype; } : function(object, prototype) { for (var property in prototype) object[property] = prototype[property]; }; function d3_selection(groups) { d3_subclass(groups, d3_selectionPrototype); return groups; } var d3_select = function(s, n) { return n.querySelector(s); }, d3_selectAll = function(s, n) { return n.querySelectorAll(s); }, d3_selectMatches = function(n, s) { var d3_selectMatcher = n.matches || n[d3_vendorSymbol(n, "matchesSelector")]; d3_selectMatches = function(n, s) { return d3_selectMatcher.call(n, s); }; return d3_selectMatches(n, s); }; if (typeof Sizzle === "function") { d3_select = function(s, n) { return Sizzle(s, n)[0] || null; }; d3_selectAll = Sizzle; d3_selectMatches = Sizzle.matchesSelector; } d3.selection = function() { return d3.select(d3_document.documentElement); }; var d3_selectionPrototype = d3.selection.prototype = []; d3_selectionPrototype.select = function(selector) { var subgroups = [], subgroup, subnode, group, node; selector = d3_selection_selector(selector); for (var j = -1, m = this.length; ++j < m; ) { subgroups.push(subgroup = []); subgroup.parentNode = (group = this[j]).parentNode; for (var i = -1, n = group.length; ++i < n; ) { if (node = group[i]) { subgroup.push(subnode = selector.call(node, node.__data__, i, j)); if (subnode && "__data__" in node) subnode.__data__ = node.__data__; } else { subgroup.push(null); } } } return d3_selection(subgroups); }; function d3_selection_selector(selector) { return typeof selector === "function" ? selector : function() { return d3_select(selector, this); }; } d3_selectionPrototype.selectAll = function(selector) { var subgroups = [], subgroup, node; selector = d3_selection_selectorAll(selector); for (var j = -1, m = this.length; ++j < m; ) { for (var group = this[j], i = -1, n = group.length; ++i < n; ) { if (node = group[i]) { subgroups.push(subgroup = d3_array(selector.call(node, node.__data__, i, j))); subgroup.parentNode = node; } } } return d3_selection(subgroups); }; function d3_selection_selectorAll(selector) { return typeof selector === "function" ? selector : function() { return d3_selectAll(selector, this); }; } var d3_nsXhtml = "http://www.w3.org/1999/xhtml"; var d3_nsPrefix = { svg: "http://www.w3.org/2000/svg", xhtml: d3_nsXhtml, xlink: "http://www.w3.org/1999/xlink", xml: "http://www.w3.org/XML/1998/namespace", xmlns: "http://www.w3.org/2000/xmlns/" }; d3.ns = { prefix: d3_nsPrefix, qualify: function(name) { var i = name.indexOf(":"), prefix = name; if (i >= 0 && (prefix = name.slice(0, i)) !== "xmlns") name = name.slice(i + 1); return d3_nsPrefix.hasOwnProperty(prefix) ? { space: d3_nsPrefix[prefix], local: name } : name; } }; d3_selectionPrototype.attr = function(name, value) { if (arguments.length < 2) { if (typeof name === "string") { var node = this.node(); name = d3.ns.qualify(name); return name.local ? node.getAttributeNS(name.space, name.local) : node.getAttribute(name); } for (value in name) this.each(d3_selection_attr(value, name[value])); return this; } return this.each(d3_selection_attr(name, value)); }; function d3_selection_attr(name, value) { name = d3.ns.qualify(name); function attrNull() { this.removeAttribute(name); } function attrNullNS() { this.removeAttributeNS(name.space, name.local); } function attrConstant() { this.setAttribute(name, value); } function attrConstantNS() { this.setAttributeNS(name.space, name.local, value); } function attrFunction() { var x = value.apply(this, arguments); if (x == null) this.removeAttribute(name); else this.setAttribute(name, x); } function attrFunctionNS() { var x = value.apply(this, arguments); if (x == null) this.removeAttributeNS(name.space, name.local); else this.setAttributeNS(name.space, name.local, x); } return value == null ? name.local ? attrNullNS : attrNull : typeof value === "function" ? name.local ? attrFunctionNS : attrFunction : name.local ? attrConstantNS : attrConstant; } function d3_collapse(s) { return s.trim().replace(/\s+/g, " "); } d3_selectionPrototype.classed = function(name, value) { if (arguments.length < 2) { if (typeof name === "string") { var node = this.node(), n = (name = d3_selection_classes(name)).length, i = -1; if (value = node.classList) { while (++i < n) if (!value.contains(name[i])) return false; } else { value = node.getAttribute("class"); while (++i < n) if (!d3_selection_classedRe(name[i]).test(value)) return false; } return true; } for (value in name) this.each(d3_selection_classed(value, name[value])); return this; } return this.each(d3_selection_classed(name, value)); }; function d3_selection_classedRe(name) { return new RegExp("(?:^|\\s+)" + d3.requote(name) + "(?:\\s+|$)", "g"); } function d3_selection_classes(name) { return (name + "").trim().split(/^|\s+/); } function d3_selection_classed(name, value) { name = d3_selection_classes(name).map(d3_selection_classedName); var n = name.length; function classedConstant() { var i = -1; while (++i < n) name[i](this, value); } function classedFunction() { var i = -1, x = value.apply(this, arguments); while (++i < n) name[i](this, x); } return typeof value === "function" ? classedFunction : classedConstant; } function d3_selection_classedName(name) { var re = d3_selection_classedRe(name); return function(node, value) { if (c = node.classList) return value ? c.add(name) : c.remove(name); var c = node.getAttribute("class") || ""; if (value) { re.lastIndex = 0; if (!re.test(c)) node.setAttribute("class", d3_collapse(c + " " + name)); } else { node.setAttribute("class", d3_collapse(c.replace(re, " "))); } }; } d3_selectionPrototype.style = function(name, value, priority) { var n = arguments.length; if (n < 3) { if (typeof name !== "string") { if (n < 2) value = ""; for (priority in name) this.each(d3_selection_style(priority, name[priority], value)); return this; } if (n < 2) { var node = this.node(); return d3_window(node).getComputedStyle(node, null).getPropertyValue(name); } priority = ""; } return this.each(d3_selection_style(name, value, priority)); }; function d3_selection_style(name, value, priority) { function styleNull() { this.style.removeProperty(name); } function styleConstant() { this.style.setProperty(name, value, priority); } function styleFunction() { var x = value.apply(this, arguments); if (x == null) this.style.removeProperty(name); else this.style.setProperty(name, x, priority); } return value == null ? styleNull : typeof value === "function" ? styleFunction : styleConstant; } d3_selectionPrototype.property = function(name, value) { if (arguments.length < 2) { if (typeof name === "string") return this.node()[name]; for (value in name) this.each(d3_selection_property(value, name[value])); return this; } return this.each(d3_selection_property(name, value)); }; function d3_selection_property(name, value) { function propertyNull() { delete this[name]; } function propertyConstant() { this[name] = value; } function propertyFunction() { var x = value.apply(this, arguments); if (x == null) delete this[name]; else this[name] = x; } return value == null ? propertyNull : typeof value === "function" ? propertyFunction : propertyConstant; } d3_selectionPrototype.text = function(value) { return arguments.length ? this.each(typeof value === "function" ? function() { var v = value.apply(this, arguments); this.textContent = v == null ? "" : v; } : value == null ? function() { this.textContent = ""; } : function() { this.textContent = value; }) : this.node().textContent; }; d3_selectionPrototype.html = function(value) { return arguments.length ? this.each(typeof value === "function" ? function() { var v = value.apply(this, arguments); this.innerHTML = v == null ? "" : v; } : value == null ? function() { this.innerHTML = ""; } : function() { this.innerHTML = value; }) : this.node().innerHTML; }; d3_selectionPrototype.append = function(name) { name = d3_selection_creator(name); return this.select(function() { return this.appendChild(name.apply(this, arguments)); }); }; function d3_selection_creator(name) { function create() { var document = this.ownerDocument, namespace = this.namespaceURI; return namespace === d3_nsXhtml && document.documentElement.namespaceURI === d3_nsXhtml ? document.createElement(name) : document.createElementNS(namespace, name); } function createNS() { return this.ownerDocument.createElementNS(name.space, name.local); } return typeof name === "function" ? name : (name = d3.ns.qualify(name)).local ? createNS : create; } d3_selectionPrototype.insert = function(name, before) { name = d3_selection_creator(name); before = d3_selection_selector(before); return this.select(function() { return this.insertBefore(name.apply(this, arguments), before.apply(this, arguments) || null); }); }; d3_selectionPrototype.remove = function() { return this.each(d3_selectionRemove); }; function d3_selectionRemove() { var parent = this.parentNode; if (parent) parent.removeChild(this); } d3_selectionPrototype.data = function(value, key) { var i = -1, n = this.length, group, node; if (!arguments.length) { value = new Array(n = (group = this[0]).length); while (++i < n) { if (node = group[i]) { value[i] = node.__data__; } } return value; } function bind(group, groupData) { var i, n = group.length, m = groupData.length, n0 = Math.min(n, m), updateNodes = new Array(m), enterNodes = new Array(m), exitNodes = new Array(n), node, nodeData; if (key) { var nodeByKeyValue = new d3_Map(), keyValues = new Array(n), keyValue; for (i = -1; ++i < n; ) { if (node = group[i]) { if (nodeByKeyValue.has(keyValue = key.call(node, node.__data__, i))) { exitNodes[i] = node; } else { nodeByKeyValue.set(keyValue, node); } keyValues[i] = keyValue; } } for (i = -1; ++i < m; ) { if (!(node = nodeByKeyValue.get(keyValue = key.call(groupData, nodeData = groupData[i], i)))) { enterNodes[i] = d3_selection_dataNode(nodeData); } else if (node !== true) { updateNodes[i] = node; node.__data__ = nodeData; } nodeByKeyValue.set(keyValue, true); } for (i = -1; ++i < n; ) { if (i in keyValues && nodeByKeyValue.get(keyValues[i]) !== true) { exitNodes[i] = group[i]; } } } else { for (i = -1; ++i < n0; ) { node = group[i]; nodeData = groupData[i]; if (node) { node.__data__ = nodeData; updateNodes[i] = node; } else { enterNodes[i] = d3_selection_dataNode(nodeData); } } for (;i < m; ++i) { enterNodes[i] = d3_selection_dataNode(groupData[i]); } for (;i < n; ++i) { exitNodes[i] = group[i]; } } enterNodes.update = updateNodes; enterNodes.parentNode = updateNodes.parentNode = exitNodes.parentNode = group.parentNode; enter.push(enterNodes); update.push(updateNodes); exit.push(exitNodes); } var enter = d3_selection_enter([]), update = d3_selection([]), exit = d3_selection([]); if (typeof value === "function") { while (++i < n) { bind(group = this[i], value.call(group, group.parentNode.__data__, i)); } } else { while (++i < n) { bind(group = this[i], value); } } update.enter = function() { return enter; }; update.exit = function() { return exit; }; return update; }; function d3_selection_dataNode(data) { return { __data__: data }; } d3_selectionPrototype.datum = function(value) { return arguments.length ? this.property("__data__", value) : this.property("__data__"); }; d3_selectionPrototype.filter = function(filter) { var subgroups = [], subgroup, group, node; if (typeof filter !== "function") filter = d3_selection_filter(filter); for (var j = 0, m = this.length; j < m; j++) { subgroups.push(subgroup = []); subgroup.parentNode = (group = this[j]).parentNode; for (var i = 0, n = group.length; i < n; i++) { if ((node = group[i]) && filter.call(node, node.__data__, i, j)) { subgroup.push(node); } } } return d3_selection(subgroups); }; function d3_selection_filter(selector) { return function() { return d3_selectMatches(this, selector); }; } d3_selectionPrototype.order = function() { for (var j = -1, m = this.length; ++j < m; ) { for (var group = this[j], i = group.length - 1, next = group[i], node; --i >= 0; ) { if (node = group[i]) { if (next && next !== node.nextSibling) next.parentNode.insertBefore(node, next); next = node; } } } return this; }; d3_selectionPrototype.sort = function(comparator) { comparator = d3_selection_sortComparator.apply(this, arguments); for (var j = -1, m = this.length; ++j < m; ) this[j].sort(comparator); return this.order(); }; function d3_selection_sortComparator(comparator) { if (!arguments.length) comparator = d3_ascending; return function(a, b) { return a && b ? comparator(a.__data__, b.__data__) : !a - !b; }; } d3_selectionPrototype.each = function(callback) { return d3_selection_each(this, function(node, i, j) { callback.call(node, node.__data__, i, j); }); }; function d3_selection_each(groups, callback) { for (var j = 0, m = groups.length; j < m; j++) { for (var group = groups[j], i = 0, n = group.length, node; i < n; i++) { if (node = group[i]) callback(node, i, j); } } return groups; } d3_selectionPrototype.call = function(callback) { var args = d3_array(arguments); callback.apply(args[0] = this, args); return this; }; d3_selectionPrototype.empty = function() { return !this.node(); }; d3_selectionPrototype.node = function() { for (var j = 0, m = this.length; j < m; j++) { for (var group = this[j], i = 0, n = group.length; i < n; i++) { var node = group[i]; if (node) return node; } } return null; }; d3_selectionPrototype.size = function() { var n = 0; d3_selection_each(this, function() { ++n; }); return n; }; function d3_selection_enter(selection) { d3_subclass(selection, d3_selection_enterPrototype); return selection; } var d3_selection_enterPrototype = []; d3.selection.enter = d3_selection_enter; d3.selection.enter.prototype = d3_selection_enterPrototype; d3_selection_enterPrototype.append = d3_selectionPrototype.append; d3_selection_enterPrototype.empty = d3_selectionPrototype.empty; d3_selection_enterPrototype.node = d3_selectionPrototype.node; d3_selection_enterPrototype.call = d3_selectionPrototype.call; d3_selection_enterPrototype.size = d3_selectionPrototype.size; d3_selection_enterPrototype.select = function(selector) { var subgroups = [], subgroup, subnode, upgroup, group, node; for (var j = -1, m = this.length; ++j < m; ) { upgroup = (group = this[j]).update; subgroups.push(subgroup = []); subgroup.parentNode = group.parentNode; for (var i = -1, n = group.length; ++i < n; ) { if (node = group[i]) { subgroup.push(upgroup[i] = subnode = selector.call(group.parentNode, node.__data__, i, j)); subnode.__data__ = node.__data__; } else { subgroup.push(null); } } } return d3_selection(subgroups); }; d3_selection_enterPrototype.insert = function(name, before) { if (arguments.length < 2) before = d3_selection_enterInsertBefore(this); return d3_selectionPrototype.insert.call(this, name, before); }; function d3_selection_enterInsertBefore(enter) { var i0, j0; return function(d, i, j) { var group = enter[j].update, n = group.length, node; if (j != j0) j0 = j, i0 = 0; if (i >= i0) i0 = i + 1; while (!(node = group[i0]) && ++i0 < n) ; return node; }; } d3.select = function(node) { var group; if (typeof node === "string") { group = [ d3_select(node, d3_document) ]; group.parentNode = d3_document.documentElement; } else { group = [ node ]; group.parentNode = d3_documentElement(node); } return d3_selection([ group ]); }; d3.selectAll = function(nodes) { var group; if (typeof nodes === "string") { group = d3_array(d3_selectAll(nodes, d3_document)); group.parentNode = d3_document.documentElement; } else { group = d3_array(nodes); group.parentNode = null; } return d3_selection([ group ]); }; d3_selectionPrototype.on = function(type, listener, capture) { var n = arguments.length; if (n < 3) { if (typeof type !== "string") { if (n < 2) listener = false; for (capture in type) this.each(d3_selection_on(capture, type[capture], listener)); return this; } if (n < 2) return (n = this.node()["__on" + type]) && n._; capture = false; } return this.each(d3_selection_on(type, listener, capture)); }; function d3_selection_on(type, listener, capture) { var name = "__on" + type, i = type.indexOf("."), wrap = d3_selection_onListener; if (i > 0) type = type.slice(0, i); var filter = d3_selection_onFilters.get(type); if (filter) type = filter, wrap = d3_selection_onFilter; function onRemove() { var l = this[name]; if (l) { this.removeEventListener(type, l, l.$); delete this[name]; } } function onAdd() { var l = wrap(listener, d3_array(arguments)); onRemove.call(this); this.addEventListener(type, this[name] = l, l.$ = capture); l._ = listener; } function removeAll() { var re = new RegExp("^__on([^.]+)" + d3.requote(type) + "$"), match; for (var name in this) { if (match = name.match(re)) { var l = this[name]; this.removeEventListener(match[1], l, l.$); delete this[name]; } } } return i ? listener ? onAdd : onRemove : listener ? d3_noop : removeAll; } var d3_selection_onFilters = d3.map({ mouseenter: "mouseover", mouseleave: "mouseout" }); if (d3_document) { d3_selection_onFilters.forEach(function(k) { if ("on" + k in d3_document) d3_selection_onFilters.remove(k); }); } function d3_selection_onListener(listener, argumentz) { return function(e) { var o = d3.event; d3.event = e; argumentz[0] = this.__data__; try { listener.apply(this, argumentz); } finally { d3.event = o; } }; } function d3_selection_onFilter(listener, argumentz) { var l = d3_selection_onListener(listener, argumentz); return function(e) { var target = this, related = e.relatedTarget; if (!related || related !== target && !(related.compareDocumentPosition(target) & 8)) { l.call(target, e); } }; } var d3_event_dragSelect, d3_event_dragId = 0; function d3_event_dragSuppress(node) { var name = ".dragsuppress-" + ++d3_event_dragId, click = "click" + name, w = d3.select(d3_window(node)).on("touchmove" + name, d3_eventPreventDefault).on("dragstart" + name, d3_eventPreventDefault).on("selectstart" + name, d3_eventPreventDefault); if (d3_event_dragSelect == null) { d3_event_dragSelect = "onselectstart" in node ? false : d3_vendorSymbol(node.style, "userSelect"); } if (d3_event_dragSelect) { var style = d3_documentElement(node).style, select = style[d3_event_dragSelect]; style[d3_event_dragSelect] = "none"; } return function(suppressClick) { w.on(name, null); if (d3_event_dragSelect) style[d3_event_dragSelect] = select; if (suppressClick) { var off = function() { w.on(click, null); }; w.on(click, function() { d3_eventPreventDefault(); off(); }, true); setTimeout(off, 0); } }; } d3.mouse = function(container) { return d3_mousePoint(container, d3_eventSource()); }; var d3_mouse_bug44083 = this.navigator && /WebKit/.test(this.navigator.userAgent) ? -1 : 0; function d3_mousePoint(container, e) { if (e.changedTouches) e = e.changedTouches[0]; var svg = container.ownerSVGElement || container; if (svg.createSVGPoint) { var point = svg.createSVGPoint(); if (d3_mouse_bug44083 < 0) { var window = d3_window(container); if (window.scrollX || window.scrollY) { svg = d3.select("body").append("svg").style({ position: "absolute", top: 0, left: 0, margin: 0, padding: 0, border: "none" }, "important"); var ctm = svg[0][0].getScreenCTM(); d3_mouse_bug44083 = !(ctm.f || ctm.e); svg.remove(); } } if (d3_mouse_bug44083) point.x = e.pageX, point.y = e.pageY; else point.x = e.clientX, point.y = e.clientY; point = point.matrixTransform(container.getScreenCTM().inverse()); return [ point.x, point.y ]; } var rect = container.getBoundingClientRect(); return [ e.clientX - rect.left - container.clientLeft, e.clientY - rect.top - container.clientTop ]; } d3.touch = function(container, touches, identifier) { if (arguments.length < 3) identifier = touches, touches = d3_eventSource().changedTouches; if (touches) for (var i = 0, n = touches.length, touch; i < n; ++i) { if ((touch = touches[i]).identifier === identifier) { return d3_mousePoint(container, touch); } } }; d3.behavior.drag = function() { var event = d3_eventDispatch(drag, "drag", "dragstart", "dragend"), origin = null, mousedown = dragstart(d3_noop, d3.mouse, d3_window, "mousemove", "mouseup"), touchstart = dragstart(d3_behavior_dragTouchId, d3.touch, d3_identity, "touchmove", "touchend"); function drag() { this.on("mousedown.drag", mousedown).on("touchstart.drag", touchstart); } function dragstart(id, position, subject, move, end) { return function() { var that = this, target = d3.event.target.correspondingElement || d3.event.target, parent = that.parentNode, dispatch = event.of(that, arguments), dragged = 0, dragId = id(), dragName = ".drag" + (dragId == null ? "" : "-" + dragId), dragOffset, dragSubject = d3.select(subject(target)).on(move + dragName, moved).on(end + dragName, ended), dragRestore = d3_event_dragSuppress(target), position0 = position(parent, dragId); if (origin) { dragOffset = origin.apply(that, arguments); dragOffset = [ dragOffset.x - position0[0], dragOffset.y - position0[1] ]; } else { dragOffset = [ 0, 0 ]; } dispatch({ type: "dragstart" }); function moved() { var position1 = position(parent, dragId), dx, dy; if (!position1) return; dx = position1[0] - position0[0]; dy = position1[1] - position0[1]; dragged |= dx | dy; position0 = position1; dispatch({ type: "drag", x: position1[0] + dragOffset[0], y: position1[1] + dragOffset[1], dx: dx, dy: dy }); } function ended() { if (!position(parent, dragId)) return; dragSubject.on(move + dragName, null).on(end + dragName, null); dragRestore(dragged); dispatch({ type: "dragend" }); } }; } drag.origin = function(x) { if (!arguments.length) return origin; origin = x; return drag; }; return d3.rebind(drag, event, "on"); }; function d3_behavior_dragTouchId() { return d3.event.changedTouches[0].identifier; } d3.touches = function(container, touches) { if (arguments.length < 2) touches = d3_eventSource().touches; return touches ? d3_array(touches).map(function(touch) { var point = d3_mousePoint(container, touch); point.identifier = touch.identifier; return point; }) : []; }; var ε = 1e-6, ε2 = ε * ε, π = Math.PI, τ = 2 * π, τε = τ - ε, halfπ = π / 2, d3_radians = π / 180, d3_degrees = 180 / π; function d3_sgn(x) { return x > 0 ? 1 : x < 0 ? -1 : 0; } function d3_cross2d(a, b, c) { return (b[0] - a[0]) * (c[1] - a[1]) - (b[1] - a[1]) * (c[0] - a[0]); } function d3_acos(x) { return x > 1 ? 0 : x < -1 ? π : Math.acos(x); } function d3_asin(x) { return x > 1 ? halfπ : x < -1 ? -halfπ : Math.asin(x); } function d3_sinh(x) { return ((x = Math.exp(x)) - 1 / x) / 2; } function d3_cosh(x) { return ((x = Math.exp(x)) + 1 / x) / 2; } function d3_tanh(x) { return ((x = Math.exp(2 * x)) - 1) / (x + 1); } function d3_haversin(x) { return (x = Math.sin(x / 2)) * x; } var ρ = Math.SQRT2, ρ2 = 2, ρ4 = 4; d3.interpolateZoom = function(p0, p1) { var ux0 = p0[0], uy0 = p0[1], w0 = p0[2], ux1 = p1[0], uy1 = p1[1], w1 = p1[2], dx = ux1 - ux0, dy = uy1 - uy0, d2 = dx * dx + dy * dy, i, S; if (d2 < ε2) { S = Math.log(w1 / w0) / ρ; i = function(t) { return [ ux0 + t * dx, uy0 + t * dy, w0 * Math.exp(ρ * t * S) ]; }; } else { var d1 = Math.sqrt(d2), b0 = (w1 * w1 - w0 * w0 + ρ4 * d2) / (2 * w0 * ρ2 * d1), b1 = (w1 * w1 - w0 * w0 - ρ4 * d2) / (2 * w1 * ρ2 * d1), r0 = Math.log(Math.sqrt(b0 * b0 + 1) - b0), r1 = Math.log(Math.sqrt(b1 * b1 + 1) - b1); S = (r1 - r0) / ρ; i = function(t) { var s = t * S, coshr0 = d3_cosh(r0), u = w0 / (ρ2 * d1) * (coshr0 * d3_tanh(ρ * s + r0) - d3_sinh(r0)); return [ ux0 + u * dx, uy0 + u * dy, w0 * coshr0 / d3_cosh(ρ * s + r0) ]; }; } i.duration = S * 1e3; return i; }; d3.behavior.zoom = function() { var view = { x: 0, y: 0, k: 1 }, translate0, center0, center, size = [ 960, 500 ], scaleExtent = d3_behavior_zoomInfinity, duration = 250, zooming = 0, mousedown = "mousedown.zoom", mousemove = "mousemove.zoom", mouseup = "mouseup.zoom", mousewheelTimer, touchstart = "touchstart.zoom", touchtime, event = d3_eventDispatch(zoom, "zoomstart", "zoom", "zoomend"), x0, x1, y0, y1; if (!d3_behavior_zoomWheel) { d3_behavior_zoomWheel = "onwheel" in d3_document ? (d3_behavior_zoomDelta = function() { return -d3.event.deltaY * (d3.event.deltaMode ? 120 : 1); }, "wheel") : "onmousewheel" in d3_document ? (d3_behavior_zoomDelta = function() { return d3.event.wheelDelta; }, "mousewheel") : (d3_behavior_zoomDelta = function() { return -d3.event.detail; }, "MozMousePixelScroll"); } function zoom(g) { g.on(mousedown, mousedowned).on(d3_behavior_zoomWheel + ".zoom", mousewheeled).on("dblclick.zoom", dblclicked).on(touchstart, touchstarted); } zoom.event = function(g) { g.each(function() { var dispatch = event.of(this, arguments), view1 = view; if (d3_transitionInheritId) { d3.select(this).transition().each("start.zoom", function() { view = this.__chart__ || { x: 0, y: 0, k: 1 }; zoomstarted(dispatch); }).tween("zoom:zoom", function() { var dx = size[0], dy = size[1], cx = center0 ? center0[0] : dx / 2, cy = center0 ? center0[1] : dy / 2, i = d3.interpolateZoom([ (cx - view.x) / view.k, (cy - view.y) / view.k, dx / view.k ], [ (cx - view1.x) / view1.k, (cy - view1.y) / view1.k, dx / view1.k ]); return function(t) { var l = i(t), k = dx / l[2]; this.__chart__ = view = { x: cx - l[0] * k, y: cy - l[1] * k, k: k }; zoomed(dispatch); }; }).each("interrupt.zoom", function() { zoomended(dispatch); }).each("end.zoom", function() { zoomended(dispatch); }); } else { this.__chart__ = view; zoomstarted(dispatch); zoomed(dispatch); zoomended(dispatch); } }); }; zoom.translate = function(_) { if (!arguments.length) return [ view.x, view.y ]; view = { x: +_[0], y: +_[1], k: view.k }; rescale(); return zoom; }; zoom.scale = function(_) { if (!arguments.length) return view.k; view = { x: view.x, y: view.y, k: null }; scaleTo(+_); rescale(); return zoom; }; zoom.scaleExtent = function(_) { if (!arguments.length) return scaleExtent; scaleExtent = _ == null ? d3_behavior_zoomInfinity : [ +_[0], +_[1] ]; return zoom; }; zoom.center = function(_) { if (!arguments.length) return center; center = _ && [ +_[0], +_[1] ]; return zoom; }; zoom.size = function(_) { if (!arguments.length) return size; size = _ && [ +_[0], +_[1] ]; return zoom; }; zoom.duration = function(_) { if (!arguments.length) return duration; duration = +_; return zoom; }; zoom.x = function(z) { if (!arguments.length) return x1; x1 = z; x0 = z.copy(); view = { x: 0, y: 0, k: 1 }; return zoom; }; zoom.y = function(z) { if (!arguments.length) return y1; y1 = z; y0 = z.copy(); view = { x: 0, y: 0, k: 1 }; return zoom; }; function location(p) { return [ (p[0] - view.x) / view.k, (p[1] - view.y) / view.k ]; } function point(l) { return [ l[0] * view.k + view.x, l[1] * view.k + view.y ]; } function scaleTo(s) { view.k = Math.max(scaleExtent[0], Math.min(scaleExtent[1], s)); } function translateTo(p, l) { l = point(l); view.x += p[0] - l[0]; view.y += p[1] - l[1]; } function zoomTo(that, p, l, k) { that.__chart__ = { x: view.x, y: view.y, k: view.k }; scaleTo(Math.pow(2, k)); translateTo(center0 = p, l); that = d3.select(that); if (duration > 0) that = that.transition().duration(duration); that.call(zoom.event); } function rescale() { if (x1) x1.domain(x0.range().map(function(x) { return (x - view.x) / view.k; }).map(x0.invert)); if (y1) y1.domain(y0.range().map(function(y) { return (y - view.y) / view.k; }).map(y0.invert)); } function zoomstarted(dispatch) { if (!zooming++) dispatch({ type: "zoomstart" }); } function zoomed(dispatch) { rescale(); dispatch({ type: "zoom", scale: view.k, translate: [ view.x, view.y ] }); } function zoomended(dispatch) { if (!--zooming) dispatch({ type: "zoomend" }), center0 = null; } function mousedowned() { var that = this, dispatch = event.of(that, arguments), dragged = 0, subject = d3.select(d3_window(that)).on(mousemove, moved).on(mouseup, ended), location0 = location(d3.mouse(that)), dragRestore = d3_event_dragSuppress(that); d3_selection_interrupt.call(that); zoomstarted(dispatch); function moved() { dragged = 1; translateTo(d3.mouse(that), location0); zoomed(dispatch); } function ended() { subject.on(mousemove, null).on(mouseup, null); dragRestore(dragged); zoomended(dispatch); } } function touchstarted() { var that = this, dispatch = event.of(that, arguments), locations0 = {}, distance0 = 0, scale0, zoomName = ".zoom-" + d3.event.changedTouches[0].identifier, touchmove = "touchmove" + zoomName, touchend = "touchend" + zoomName, targets = [], subject = d3.select(that), dragRestore = d3_event_dragSuppress(that); started(); zoomstarted(dispatch); subject.on(mousedown, null).on(touchstart, started); function relocate() { var touches = d3.touches(that); scale0 = view.k; touches.forEach(function(t) { if (t.identifier in locations0) locations0[t.identifier] = location(t); }); return touches; } function started() { var target = d3.event.target; d3.select(target).on(touchmove, moved).on(touchend, ended); targets.push(target); var changed = d3.event.changedTouches; for (var i = 0, n = changed.length; i < n; ++i) { locations0[changed[i].identifier] = null; } var touches = relocate(), now = Date.now(); if (touches.length === 1) { if (now - touchtime < 500) { var p = touches[0]; zoomTo(that, p, locations0[p.identifier], Math.floor(Math.log(view.k) / Math.LN2) + 1); d3_eventPreventDefault(); } touchtime = now; } else if (touches.length > 1) { var p = touches[0], q = touches[1], dx = p[0] - q[0], dy = p[1] - q[1]; distance0 = dx * dx + dy * dy; } } function moved() { var touches = d3.touches(that), p0, l0, p1, l1; d3_selection_interrupt.call(that); for (var i = 0, n = touches.length; i < n; ++i, l1 = null) { p1 = touches[i]; if (l1 = locations0[p1.identifier]) { if (l0) break; p0 = p1, l0 = l1; } } if (l1) { var distance1 = (distance1 = p1[0] - p0[0]) * distance1 + (distance1 = p1[1] - p0[1]) * distance1, scale1 = distance0 && Math.sqrt(distance1 / distance0); p0 = [ (p0[0] + p1[0]) / 2, (p0[1] + p1[1]) / 2 ]; l0 = [ (l0[0] + l1[0]) / 2, (l0[1] + l1[1]) / 2 ]; scaleTo(scale1 * scale0); } touchtime = null; translateTo(p0, l0); zoomed(dispatch); } function ended() { if (d3.event.touches.length) { var changed = d3.event.changedTouches; for (var i = 0, n = changed.length; i < n; ++i) { delete locations0[changed[i].identifier]; } for (var identifier in locations0) { return void relocate(); } } d3.selectAll(targets).on(zoomName, null); subject.on(mousedown, mousedowned).on(touchstart, touchstarted); dragRestore(); zoomended(dispatch); } } function mousewheeled() { var dispatch = event.of(this, arguments); if (mousewheelTimer) clearTimeout(mousewheelTimer); else d3_selection_interrupt.call(this), translate0 = location(center0 = center || d3.mouse(this)), zoomstarted(dispatch); mousewheelTimer = setTimeout(function() { mousewheelTimer = null; zoomended(dispatch); }, 50); d3_eventPreventDefault(); scaleTo(Math.pow(2, d3_behavior_zoomDelta() * .002) * view.k); translateTo(center0, translate0); zoomed(dispatch); } function dblclicked() { var p = d3.mouse(this), k = Math.log(view.k) / Math.LN2; zoomTo(this, p, location(p), d3.event.shiftKey ? Math.ceil(k) - 1 : Math.floor(k) + 1); } return d3.rebind(zoom, event, "on"); }; var d3_behavior_zoomInfinity = [ 0, Infinity ], d3_behavior_zoomDelta, d3_behavior_zoomWheel; d3.color = d3_color; function d3_color() {} d3_color.prototype.toString = function() { return this.rgb() + ""; }; d3.hsl = d3_hsl; function d3_hsl(h, s, l) { return this instanceof d3_hsl ? void (this.h = +h, this.s = +s, this.l = +l) : arguments.length < 2 ? h instanceof d3_hsl ? new d3_hsl(h.h, h.s, h.l) : d3_rgb_parse("" + h, d3_rgb_hsl, d3_hsl) : new d3_hsl(h, s, l); } var d3_hslPrototype = d3_hsl.prototype = new d3_color(); d3_hslPrototype.brighter = function(k) { k = Math.pow(.7, arguments.length ? k : 1); return new d3_hsl(this.h, this.s, this.l / k); }; d3_hslPrototype.darker = function(k) { k = Math.pow(.7, arguments.length ? k : 1); return new d3_hsl(this.h, this.s, k * this.l); }; d3_hslPrototype.rgb = function() { return d3_hsl_rgb(this.h, this.s, this.l); }; function d3_hsl_rgb(h, s, l) { var m1, m2; h = isNaN(h) ? 0 : (h %= 360) < 0 ? h + 360 : h; s = isNaN(s) ? 0 : s < 0 ? 0 : s > 1 ? 1 : s; l = l < 0 ? 0 : l > 1 ? 1 : l; m2 = l <= .5 ? l * (1 + s) : l + s - l * s; m1 = 2 * l - m2; function v(h) { if (h > 360) h -= 360; else if (h < 0) h += 360; if (h < 60) return m1 + (m2 - m1) * h / 60; if (h < 180) return m2; if (h < 240) return m1 + (m2 - m1) * (240 - h) / 60; return m1; } function vv(h) { return Math.round(v(h) * 255); } return new d3_rgb(vv(h + 120), vv(h), vv(h - 120)); } d3.hcl = d3_hcl; function d3_hcl(h, c, l) { return this instanceof d3_hcl ? void (this.h = +h, this.c = +c, this.l = +l) : arguments.length < 2 ? h instanceof d3_hcl ? new d3_hcl(h.h, h.c, h.l) : h instanceof d3_lab ? d3_lab_hcl(h.l, h.a, h.b) : d3_lab_hcl((h = d3_rgb_lab((h = d3.rgb(h)).r, h.g, h.b)).l, h.a, h.b) : new d3_hcl(h, c, l); } var d3_hclPrototype = d3_hcl.prototype = new d3_color(); d3_hclPrototype.brighter = function(k) { return new d3_hcl(this.h, this.c, Math.min(100, this.l + d3_lab_K * (arguments.length ? k : 1))); }; d3_hclPrototype.darker = function(k) { return new d3_hcl(this.h, this.c, Math.max(0, this.l - d3_lab_K * (arguments.length ? k : 1))); }; d3_hclPrototype.rgb = function() { return d3_hcl_lab(this.h, this.c, this.l).rgb(); }; function d3_hcl_lab(h, c, l) { if (isNaN(h)) h = 0; if (isNaN(c)) c = 0; return new d3_lab(l, Math.cos(h *= d3_radians) * c, Math.sin(h) * c); } d3.lab = d3_lab; function d3_lab(l, a, b) { return this instanceof d3_lab ? void (this.l = +l, this.a = +a, this.b = +b) : arguments.length < 2 ? l instanceof d3_lab ? new d3_lab(l.l, l.a, l.b) : l instanceof d3_hcl ? d3_hcl_lab(l.h, l.c, l.l) : d3_rgb_lab((l = d3_rgb(l)).r, l.g, l.b) : new d3_lab(l, a, b); } var d3_lab_K = 18; var d3_lab_X = .95047, d3_lab_Y = 1, d3_lab_Z = 1.08883; var d3_labPrototype = d3_lab.prototype = new d3_color(); d3_labPrototype.brighter = function(k) { return new d3_lab(Math.min(100, this.l + d3_lab_K * (arguments.length ? k : 1)), this.a, this.b); }; d3_labPrototype.darker = function(k) { return new d3_lab(Math.max(0, this.l - d3_lab_K * (arguments.length ? k : 1)), this.a, this.b); }; d3_labPrototype.rgb = function() { return d3_lab_rgb(this.l, this.a, this.b); }; function d3_lab_rgb(l, a, b) { var y = (l + 16) / 116, x = y + a / 500, z = y - b / 200; x = d3_lab_xyz(x) * d3_lab_X; y = d3_lab_xyz(y) * d3_lab_Y; z = d3_lab_xyz(z) * d3_lab_Z; return new d3_rgb(d3_xyz_rgb(3.2404542 * x - 1.5371385 * y - .4985314 * z), d3_xyz_rgb(-.969266 * x + 1.8760108 * y + .041556 * z), d3_xyz_rgb(.0556434 * x - .2040259 * y + 1.0572252 * z)); } function d3_lab_hcl(l, a, b) { return l > 0 ? new d3_hcl(Math.atan2(b, a) * d3_degrees, Math.sqrt(a * a + b * b), l) : new d3_hcl(NaN, NaN, l); } function d3_lab_xyz(x) { return x > .206893034 ? x * x * x : (x - 4 / 29) / 7.787037; } function d3_xyz_lab(x) { return x > .008856 ? Math.pow(x, 1 / 3) : 7.787037 * x + 4 / 29; } function d3_xyz_rgb(r) { return Math.round(255 * (r <= .00304 ? 12.92 * r : 1.055 * Math.pow(r, 1 / 2.4) - .055)); } d3.rgb = d3_rgb; function d3_rgb(r, g, b) { return this instanceof d3_rgb ? void (this.r = ~~r, this.g = ~~g, this.b = ~~b) : arguments.length < 2 ? r instanceof d3_rgb ? new d3_rgb(r.r, r.g, r.b) : d3_rgb_parse("" + r, d3_rgb, d3_hsl_rgb) : new d3_rgb(r, g, b); } function d3_rgbNumber(value) { return new d3_rgb(value >> 16, value >> 8 & 255, value & 255); } function d3_rgbString(value) { return d3_rgbNumber(value) + ""; } var d3_rgbPrototype = d3_rgb.prototype = new d3_color(); d3_rgbPrototype.brighter = function(k) { k = Math.pow(.7, arguments.length ? k : 1); var r = this.r, g = this.g, b = this.b, i = 30; if (!r && !g && !b) return new d3_rgb(i, i, i); if (r && r < i) r = i; if (g && g < i) g = i; if (b && b < i) b = i; return new d3_rgb(Math.min(255, r / k), Math.min(255, g / k), Math.min(255, b / k)); }; d3_rgbPrototype.darker = function(k) { k = Math.pow(.7, arguments.length ? k : 1); return new d3_rgb(k * this.r, k * this.g, k * this.b); }; d3_rgbPrototype.hsl = function() { return d3_rgb_hsl(this.r, this.g, this.b); }; d3_rgbPrototype.toString = function() { return "#" + d3_rgb_hex(this.r) + d3_rgb_hex(this.g) + d3_rgb_hex(this.b); }; function d3_rgb_hex(v) { return v < 16 ? "0" + Math.max(0, v).toString(16) : Math.min(255, v).toString(16); } function d3_rgb_parse(format, rgb, hsl) { var r = 0, g = 0, b = 0, m1, m2, color; m1 = /([a-z]+)\((.*)\)/.exec(format = format.toLowerCase()); if (m1) { m2 = m1[2].split(","); switch (m1[1]) { case "hsl": { return hsl(parseFloat(m2[0]), parseFloat(m2[1]) / 100, parseFloat(m2[2]) / 100); } case "rgb": { return rgb(d3_rgb_parseNumber(m2[0]), d3_rgb_parseNumber(m2[1]), d3_rgb_parseNumber(m2[2])); } } } if (color = d3_rgb_names.get(format)) { return rgb(color.r, color.g, color.b); } if (format != null && format.charAt(0) === "#" && !isNaN(color = parseInt(format.slice(1), 16))) { if (format.length === 4) { r = (color & 3840) >> 4; r = r >> 4 | r; g = color & 240; g = g >> 4 | g; b = color & 15; b = b << 4 | b; } else if (format.length === 7) { r = (color & 16711680) >> 16; g = (color & 65280) >> 8; b = color & 255; } } return rgb(r, g, b); } function d3_rgb_hsl(r, g, b) { var min = Math.min(r /= 255, g /= 255, b /= 255), max = Math.max(r, g, b), d = max - min, h, s, l = (max + min) / 2; if (d) { s = l < .5 ? d / (max + min) : d / (2 - max - min); if (r == max) h = (g - b) / d + (g < b ? 6 : 0); else if (g == max) h = (b - r) / d + 2; else h = (r - g) / d + 4; h *= 60; } else { h = NaN; s = l > 0 && l < 1 ? 0 : h; } return new d3_hsl(h, s, l); } function d3_rgb_lab(r, g, b) { r = d3_rgb_xyz(r); g = d3_rgb_xyz(g); b = d3_rgb_xyz(b); var x = d3_xyz_lab((.4124564 * r + .3575761 * g + .1804375 * b) / d3_lab_X), y = d3_xyz_lab((.2126729 * r + .7151522 * g + .072175 * b) / d3_lab_Y), z = d3_xyz_lab((.0193339 * r + .119192 * g + .9503041 * b) / d3_lab_Z); return d3_lab(116 * y - 16, 500 * (x - y), 200 * (y - z)); } function d3_rgb_xyz(r) { return (r /= 255) <= .04045 ? r / 12.92 : Math.pow((r + .055) / 1.055, 2.4); } function d3_rgb_parseNumber(c) { var f = parseFloat(c); return c.charAt(c.length - 1) === "%" ? Math.round(f * 2.55) : f; } var d3_rgb_names = d3.map({ aliceblue: 15792383, antiquewhite: 16444375, aqua: 65535, aquamarine: 8388564, azure: 15794175, beige: 16119260, bisque: 16770244, black: 0, blanchedalmond: 16772045, blue: 255, blueviolet: 9055202, brown: 10824234, burlywood: 14596231, cadetblue: 6266528, chartreuse: 8388352, chocolate: 13789470, coral: 16744272, cornflowerblue: 6591981, cornsilk: 16775388, crimson: 14423100, cyan: 65535, darkblue: 139, darkcyan: 35723, darkgoldenrod: 12092939, darkgray: 11119017, darkgreen: 25600, darkgrey: 11119017, darkkhaki: 12433259, darkmagenta: 9109643, darkolivegreen: 5597999, darkorange: 16747520, darkorchid: 10040012, darkred: 9109504, darksalmon: 15308410, darkseagreen: 9419919, darkslateblue: 4734347, darkslategray: 3100495, darkslategrey: 3100495, darkturquoise: 52945, darkviolet: 9699539, deeppink: 16716947, deepskyblue: 49151, dimgray: 6908265, dimgrey: 6908265, dodgerblue: 2003199, firebrick: 11674146, floralwhite: 16775920, forestgreen: 2263842, fuchsia: 16711935, gainsboro: 14474460, ghostwhite: 16316671, gold: 16766720, goldenrod: 14329120, gray: 8421504, green: 32768, greenyellow: 11403055, grey: 8421504, honeydew: 15794160, hotpink: 16738740, indianred: 13458524, indigo: 4915330, ivory: 16777200, khaki: 15787660, lavender: 15132410, lavenderblush: 16773365, lawngreen: 8190976, lemonchiffon: 16775885, lightblue: 11393254, lightcoral: 15761536, lightcyan: 14745599, lightgoldenrodyellow: 16448210, lightgray: 13882323, lightgreen: 9498256, lightgrey: 13882323, lightpink: 16758465, lightsalmon: 16752762, lightseagreen: 2142890, lightskyblue: 8900346, lightslategray: 7833753, lightslategrey: 7833753, lightsteelblue: 11584734, lightyellow: 16777184, lime: 65280, limegreen: 3329330, linen: 16445670, magenta: 16711935, maroon: 8388608, mediumaquamarine: 6737322, mediumblue: 205, mediumorchid: 12211667, mediumpurple: 9662683, mediumseagreen: 3978097, mediumslateblue: 8087790, mediumspringgreen: 64154, mediumturquoise: 4772300, mediumvioletred: 13047173, midnightblue: 1644912, mintcream: 16121850, mistyrose: 16770273, moccasin: 16770229, navajowhite: 16768685, navy: 128, oldlace: 16643558, olive: 8421376, olivedrab: 7048739, orange: 16753920, orangered: 16729344, orchid: 14315734, palegoldenrod: 15657130, palegreen: 10025880, paleturquoise: 11529966, palevioletred: 14381203, papayawhip: 16773077, peachpuff: 16767673, peru: 13468991, pink: 16761035, plum: 14524637, powderblue: 11591910, purple: 8388736, rebeccapurple: 6697881, red: 16711680, rosybrown: 12357519, royalblue: 4286945, saddlebrown: 9127187, salmon: 16416882, sandybrown: 16032864, seagreen: 3050327, seashell: 16774638, sienna: 10506797, silver: 12632256, skyblue: 8900331, slateblue: 6970061, slategray: 7372944, slategrey: 7372944, snow: 16775930, springgreen: 65407, steelblue: 4620980, tan: 13808780, teal: 32896, thistle: 14204888, tomato: 16737095, turquoise: 4251856, violet: 15631086, wheat: 16113331, white: 16777215, whitesmoke: 16119285, yellow: 16776960, yellowgreen: 10145074 }); d3_rgb_names.forEach(function(key, value) { d3_rgb_names.set(key, d3_rgbNumber(value)); }); function d3_functor(v) { return typeof v === "function" ? v : function() { return v; }; } d3.functor = d3_functor; d3.xhr = d3_xhrType(d3_identity); function d3_xhrType(response) { return function(url, mimeType, callback) { if (arguments.length === 2 && typeof mimeType === "function") callback = mimeType, mimeType = null; return d3_xhr(url, mimeType, response, callback); }; } function d3_xhr(url, mimeType, response, callback) { var xhr = {}, dispatch = d3.dispatch("beforesend", "progress", "load", "error"), headers = {}, request = new XMLHttpRequest(), responseType = null; if (this.XDomainRequest && !("withCredentials" in request) && /^(http(s)?:)?\/\//.test(url)) request = new XDomainRequest(); "onload" in request ? request.onload = request.onerror = respond : request.onreadystatechange = function() { request.readyState > 3 && respond(); }; function respond() { var status = request.status, result; if (!status && d3_xhrHasResponse(request) || status >= 200 && status < 300 || status === 304) { try { result = response.call(xhr, request); } catch (e) { dispatch.error.call(xhr, e); return; } dispatch.load.call(xhr, result); } else { dispatch.error.call(xhr, request); } } request.onprogress = function(event) { var o = d3.event; d3.event = event; try { dispatch.progress.call(xhr, request); } finally { d3.event = o; } }; xhr.header = function(name, value) { name = (name + "").toLowerCase(); if (arguments.length < 2) return headers[name]; if (value == null) delete headers[name]; else headers[name] = value + ""; return xhr; }; xhr.mimeType = function(value) { if (!arguments.length) return mimeType; mimeType = value == null ? null : value + ""; return xhr; }; xhr.responseType = function(value) { if (!arguments.length) return responseType; responseType = value; return xhr; }; xhr.response = function(value) { response = value; return xhr; }; [ "get", "post" ].forEach(function(method) { xhr[method] = function() { return xhr.send.apply(xhr, [ method ].concat(d3_array(arguments))); }; }); xhr.send = function(method, data, callback) { if (arguments.length === 2 && typeof data === "function") callback = data, data = null; request.open(method, url, true); if (mimeType != null && !("accept" in headers)) headers["accept"] = mimeType + ",*/*"; if (request.setRequestHeader) for (var name in headers) request.setRequestHeader(name, headers[name]); if (mimeType != null && request.overrideMimeType) request.overrideMimeType(mimeType); if (responseType != null) request.responseType = responseType; if (callback != null) xhr.on("error", callback).on("load", function(request) { callback(null, request); }); dispatch.beforesend.call(xhr, request); request.send(data == null ? null : data); return xhr; }; xhr.abort = function() { request.abort(); return xhr; }; d3.rebind(xhr, dispatch, "on"); return callback == null ? xhr : xhr.get(d3_xhr_fixCallback(callback)); } function d3_xhr_fixCallback(callback) { return callback.length === 1 ? function(error, request) { callback(error == null ? request : null); } : callback; } function d3_xhrHasResponse(request) { var type = request.responseType; return type && type !== "text" ? request.response : request.responseText; } d3.dsv = function(delimiter, mimeType) { var reFormat = new RegExp('["' + delimiter + "\n]"), delimiterCode = delimiter.charCodeAt(0); function dsv(url, row, callback) { if (arguments.length < 3) callback = row, row = null; var xhr = d3_xhr(url, mimeType, row == null ? response : typedResponse(row), callback); xhr.row = function(_) { return arguments.length ? xhr.response((row = _) == null ? response : typedResponse(_)) : row; }; return xhr; } function response(request) { return dsv.parse(request.responseText); } function typedResponse(f) { return function(request) { return dsv.parse(request.responseText, f); }; } dsv.parse = function(text, f) { var o; return dsv.parseRows(text, function(row, i) { if (o) return o(row, i - 1); var a = new Function("d", "return {" + row.map(function(name, i) { return JSON.stringify(name) + ": d[" + i + "]"; }).join(",") + "}"); o = f ? function(row, i) { return f(a(row), i); } : a; }); }; dsv.parseRows = function(text, f) { var EOL = {}, EOF = {}, rows = [], N = text.length, I = 0, n = 0, t, eol; function token() { if (I >= N) return EOF; if (eol) return eol = false, EOL; var j = I; if (text.charCodeAt(j) === 34) { var i = j; while (i++ < N) { if (text.charCodeAt(i) === 34) { if (text.charCodeAt(i + 1) !== 34) break; ++i; } } I = i + 2; var c = text.charCodeAt(i + 1); if (c === 13) { eol = true; if (text.charCodeAt(i + 2) === 10) ++I; } else if (c === 10) { eol = true; } return text.slice(j + 1, i).replace(/""/g, '"'); } while (I < N) { var c = text.charCodeAt(I++), k = 1; if (c === 10) eol = true; else if (c === 13) { eol = true; if (text.charCodeAt(I) === 10) ++I, ++k; } else if (c !== delimiterCode) continue; return text.slice(j, I - k); } return text.slice(j); } while ((t = token()) !== EOF) { var a = []; while (t !== EOL && t !== EOF) { a.push(t); t = token(); } if (f && (a = f(a, n++)) == null) continue; rows.push(a); } return rows; }; dsv.format = function(rows) { if (Array.isArray(rows[0])) return dsv.formatRows(rows); var fieldSet = new d3_Set(), fields = []; rows.forEach(function(row) { for (var field in row) { if (!fieldSet.has(field)) { fields.push(fieldSet.add(field)); } } }); return [ fields.map(formatValue).join(delimiter) ].concat(rows.map(function(row) { return fields.map(function(field) { return formatValue(row[field]); }).join(delimiter); })).join("\n"); }; dsv.formatRows = function(rows) { return rows.map(formatRow).join("\n"); }; function formatRow(row) { return row.map(formatValue).join(delimiter); } function formatValue(text) { return reFormat.test(text) ? '"' + text.replace(/\"/g, '""') + '"' : text; } return dsv; }; d3.csv = d3.dsv(",", "text/csv"); d3.tsv = d3.dsv(" ", "text/tab-separated-values"); var d3_timer_queueHead, d3_timer_queueTail, d3_timer_interval, d3_timer_timeout, d3_timer_frame = this[d3_vendorSymbol(this, "requestAnimationFrame")] || function(callback) { setTimeout(callback, 17); }; d3.timer = function() { d3_timer.apply(this, arguments); }; function d3_timer(callback, delay, then) { var n = arguments.length; if (n < 2) delay = 0; if (n < 3) then = Date.now(); var time = then + delay, timer = { c: callback, t: time, n: null }; if (d3_timer_queueTail) d3_timer_queueTail.n = timer; else d3_timer_queueHead = timer; d3_timer_queueTail = timer; if (!d3_timer_interval) { d3_timer_timeout = clearTimeout(d3_timer_timeout); d3_timer_interval = 1; d3_timer_frame(d3_timer_step); } return timer; } function d3_timer_step() { var now = d3_timer_mark(), delay = d3_timer_sweep() - now; if (delay > 24) { if (isFinite(delay)) { clearTimeout(d3_timer_timeout); d3_timer_timeout = setTimeout(d3_timer_step, delay); } d3_timer_interval = 0; } else { d3_timer_interval = 1; d3_timer_frame(d3_timer_step); } } d3.timer.flush = function() { d3_timer_mark(); d3_timer_sweep(); }; function d3_timer_mark() { var now = Date.now(), timer = d3_timer_queueHead; while (timer) { if (now >= timer.t && timer.c(now - timer.t)) timer.c = null; timer = timer.n; } return now; } function d3_timer_sweep() { var t0, t1 = d3_timer_queueHead, time = Infinity; while (t1) { if (t1.c) { if (t1.t < time) time = t1.t; t1 = (t0 = t1).n; } else { t1 = t0 ? t0.n = t1.n : d3_timer_queueHead = t1.n; } } d3_timer_queueTail = t0; return time; } function d3_format_precision(x, p) { return p - (x ? Math.ceil(Math.log(x) / Math.LN10) : 1); } d3.round = function(x, n) { return n ? Math.round(x * (n = Math.pow(10, n))) / n : Math.round(x); }; var d3_formatPrefixes = [ "y", "z", "a", "f", "p", "n", "µ", "m", "", "k", "M", "G", "T", "P", "E", "Z", "Y" ].map(d3_formatPrefix); d3.formatPrefix = function(value, precision) { var i = 0; if (value = +value) { if (value < 0) value *= -1; if (precision) value = d3.round(value, d3_format_precision(value, precision)); i = 1 + Math.floor(1e-12 + Math.log(value) / Math.LN10); i = Math.max(-24, Math.min(24, Math.floor((i - 1) / 3) * 3)); } return d3_formatPrefixes[8 + i / 3]; }; function d3_formatPrefix(d, i) { var k = Math.pow(10, abs(8 - i) * 3); return { scale: i > 8 ? function(d) { return d / k; } : function(d) { return d * k; }, symbol: d }; } function d3_locale_numberFormat(locale) { var locale_decimal = locale.decimal, locale_thousands = locale.thousands, locale_grouping = locale.grouping, locale_currency = locale.currency, formatGroup = locale_grouping && locale_thousands ? function(value, width) { var i = value.length, t = [], j = 0, g = locale_grouping[0], length = 0; while (i > 0 && g > 0) { if (length + g + 1 > width) g = Math.max(1, width - length); t.push(value.substring(i -= g, i + g)); if ((length += g + 1) > width) break; g = locale_grouping[j = (j + 1) % locale_grouping.length]; } return t.reverse().join(locale_thousands); } : d3_identity; return function(specifier) { var match = d3_format_re.exec(specifier), fill = match[1] || " ", align = match[2] || ">", sign = match[3] || "-", symbol = match[4] || "", zfill = match[5], width = +match[6], comma = match[7], precision = match[8], type = match[9], scale = 1, prefix = "", suffix = "", integer = false, exponent = true; if (precision) precision = +precision.substring(1); if (zfill || fill === "0" && align === "=") { zfill = fill = "0"; align = "="; } switch (type) { case "n": comma = true; type = "g"; break; case "%": scale = 100; suffix = "%"; type = "f"; break; case "p": scale = 100; suffix = "%"; type = "r"; break; case "b": case "o": case "x": case "X": if (symbol === "#") prefix = "0" + type.toLowerCase(); case "c": exponent = false; case "d": integer = true; precision = 0; break; case "s": scale = -1; type = "r"; break; } if (symbol === "$") prefix = locale_currency[0], suffix = locale_currency[1]; if (type == "r" && !precision) type = "g"; if (precision != null) { if (type == "g") precision = Math.max(1, Math.min(21, precision)); else if (type == "e" || type == "f") precision = Math.max(0, Math.min(20, precision)); } type = d3_format_types.get(type) || d3_format_typeDefault; var zcomma = zfill && comma; return function(value) { var fullSuffix = suffix; if (integer && value % 1) return ""; var negative = value < 0 || value === 0 && 1 / value < 0 ? (value = -value, "-") : sign === "-" ? "" : sign; if (scale < 0) { var unit = d3.formatPrefix(value, precision); value = unit.scale(value); fullSuffix = unit.symbol + suffix; } else { value *= scale; } value = type(value, precision); var i = value.lastIndexOf("."), before, after; if (i < 0) { var j = exponent ? value.lastIndexOf("e") : -1; if (j < 0) before = value, after = ""; else before = value.substring(0, j), after = value.substring(j); } else { before = value.substring(0, i); after = locale_decimal + value.substring(i + 1); } if (!zfill && comma) before = formatGroup(before, Infinity); var length = prefix.length + before.length + after.length + (zcomma ? 0 : negative.length), padding = length < width ? new Array(length = width - length + 1).join(fill) : ""; if (zcomma) before = formatGroup(padding + before, padding.length ? width - after.length : Infinity); negative += prefix; value = before + after; return (align === "<" ? negative + value + padding : align === ">" ? padding + negative + value : align === "^" ? padding.substring(0, length >>= 1) + negative + value + padding.substring(length) : negative + (zcomma ? value : padding + value)) + fullSuffix; }; }; } var d3_format_re = /(?:([^{])?([<>=^]))?([+\- ])?([$#])?(0)?(\d+)?(,)?(\.-?\d+)?([a-z%])?/i; var d3_format_types = d3.map({ b: function(x) { return x.toString(2); }, c: function(x) { return String.fromCharCode(x); }, o: function(x) { return x.toString(8); }, x: function(x) { return x.toString(16); }, X: function(x) { return x.toString(16).toUpperCase(); }, g: function(x, p) { return x.toPrecision(p); }, e: function(x, p) { return x.toExponential(p); }, f: function(x, p) { return x.toFixed(p); }, r: function(x, p) { return (x = d3.round(x, d3_format_precision(x, p))).toFixed(Math.max(0, Math.min(20, d3_format_precision(x * (1 + 1e-15), p)))); } }); function d3_format_typeDefault(x) { return x + ""; } var d3_time = d3.time = {}, d3_date = Date; function d3_date_utc() { this._ = new Date(arguments.length > 1 ? Date.UTC.apply(this, arguments) : arguments[0]); } d3_date_utc.prototype = { getDate: function() { return this._.getUTCDate(); }, getDay: function() { return this._.getUTCDay(); }, getFullYear: function() { return this._.getUTCFullYear(); }, getHours: function() { return this._.getUTCHours(); }, getMilliseconds: function() { return this._.getUTCMilliseconds(); }, getMinutes: function() { return this._.getUTCMinutes(); }, getMonth: function() { return this._.getUTCMonth(); }, getSeconds: function() { return this._.getUTCSeconds(); }, getTime: function() { return this._.getTime(); }, getTimezoneOffset: function() { return 0; }, valueOf: function() { return this._.valueOf(); }, setDate: function() { d3_time_prototype.setUTCDate.apply(this._, arguments); }, setDay: function() { d3_time_prototype.setUTCDay.apply(this._, arguments); }, setFullYear: function() { d3_time_prototype.setUTCFullYear.apply(this._, arguments); }, setHours: function() { d3_time_prototype.setUTCHours.apply(this._, arguments); }, setMilliseconds: function() { d3_time_prototype.setUTCMilliseconds.apply(this._, arguments); }, setMinutes: function() { d3_time_prototype.setUTCMinutes.apply(this._, arguments); }, setMonth: function() { d3_time_prototype.setUTCMonth.apply(this._, arguments); }, setSeconds: function() { d3_time_prototype.setUTCSeconds.apply(this._, arguments); }, setTime: function() { d3_time_prototype.setTime.apply(this._, arguments); } }; var d3_time_prototype = Date.prototype; function d3_time_interval(local, step, number) { function round(date) { var d0 = local(date), d1 = offset(d0, 1); return date - d0 < d1 - date ? d0 : d1; } function ceil(date) { step(date = local(new d3_date(date - 1)), 1); return date; } function offset(date, k) { step(date = new d3_date(+date), k); return date; } function range(t0, t1, dt) { var time = ceil(t0), times = []; if (dt > 1) { while (time < t1) { if (!(number(time) % dt)) times.push(new Date(+time)); step(time, 1); } } else { while (time < t1) times.push(new Date(+time)), step(time, 1); } return times; } function range_utc(t0, t1, dt) { try { d3_date = d3_date_utc; var utc = new d3_date_utc(); utc._ = t0; return range(utc, t1, dt); } finally { d3_date = Date; } } local.floor = local; local.round = round; local.ceil = ceil; local.offset = offset; local.range = range; var utc = local.utc = d3_time_interval_utc(local); utc.floor = utc; utc.round = d3_time_interval_utc(round); utc.ceil = d3_time_interval_utc(ceil); utc.offset = d3_time_interval_utc(offset); utc.range = range_utc; return local; } function d3_time_interval_utc(method) { return function(date, k) { try { d3_date = d3_date_utc; var utc = new d3_date_utc(); utc._ = date; return method(utc, k)._; } finally { d3_date = Date; } }; } d3_time.year = d3_time_interval(function(date) { date = d3_time.day(date); date.setMonth(0, 1); return date; }, function(date, offset) { date.setFullYear(date.getFullYear() + offset); }, function(date) { return date.getFullYear(); }); d3_time.years = d3_time.year.range; d3_time.years.utc = d3_time.year.utc.range; d3_time.day = d3_time_interval(function(date) { var day = new d3_date(2e3, 0); day.setFullYear(date.getFullYear(), date.getMonth(), date.getDate()); return day; }, function(date, offset) { date.setDate(date.getDate() + offset); }, function(date) { return date.getDate() - 1; }); d3_time.days = d3_time.day.range; d3_time.days.utc = d3_time.day.utc.range; d3_time.dayOfYear = function(date) { var year = d3_time.year(date); return Math.floor((date - year - (date.getTimezoneOffset() - year.getTimezoneOffset()) * 6e4) / 864e5); }; [ "sunday", "monday", "tuesday", "wednesday", "thursday", "friday", "saturday" ].forEach(function(day, i) { i = 7 - i; var interval = d3_time[day] = d3_time_interval(function(date) { (date = d3_time.day(date)).setDate(date.getDate() - (date.getDay() + i) % 7); return date; }, function(date, offset) { date.setDate(date.getDate() + Math.floor(offset) * 7); }, function(date) { var day = d3_time.year(date).getDay(); return Math.floor((d3_time.dayOfYear(date) + (day + i) % 7) / 7) - (day !== i); }); d3_time[day + "s"] = interval.range; d3_time[day + "s"].utc = interval.utc.range; d3_time[day + "OfYear"] = function(date) { var day = d3_time.year(date).getDay(); return Math.floor((d3_time.dayOfYear(date) + (day + i) % 7) / 7); }; }); d3_time.week = d3_time.sunday; d3_time.weeks = d3_time.sunday.range; d3_time.weeks.utc = d3_time.sunday.utc.range; d3_time.weekOfYear = d3_time.sundayOfYear; function d3_locale_timeFormat(locale) { var locale_dateTime = locale.dateTime, locale_date = locale.date, locale_time = locale.time, locale_periods = locale.periods, locale_days = locale.days, locale_shortDays = locale.shortDays, locale_months = locale.months, locale_shortMonths = locale.shortMonths; function d3_time_format(template) { var n = template.length; function format(date) { var string = [], i = -1, j = 0, c, p, f; while (++i < n) { if (template.charCodeAt(i) === 37) { string.push(template.slice(j, i)); if ((p = d3_time_formatPads[c = template.charAt(++i)]) != null) c = template.charAt(++i); if (f = d3_time_formats[c]) c = f(date, p == null ? c === "e" ? " " : "0" : p); string.push(c); j = i + 1; } } string.push(template.slice(j, i)); return string.join(""); } format.parse = function(string) { var d = { y: 1900, m: 0, d: 1, H: 0, M: 0, S: 0, L: 0, Z: null }, i = d3_time_parse(d, template, string, 0); if (i != string.length) return null; if ("p" in d) d.H = d.H % 12 + d.p * 12; var localZ = d.Z != null && d3_date !== d3_date_utc, date = new (localZ ? d3_date_utc : d3_date)(); if ("j" in d) date.setFullYear(d.y, 0, d.j); else if ("W" in d || "U" in d) { if (!("w" in d)) d.w = "W" in d ? 1 : 0; date.setFullYear(d.y, 0, 1); date.setFullYear(d.y, 0, "W" in d ? (d.w + 6) % 7 + d.W * 7 - (date.getDay() + 5) % 7 : d.w + d.U * 7 - (date.getDay() + 6) % 7); } else date.setFullYear(d.y, d.m, d.d); date.setHours(d.H + (d.Z / 100 | 0), d.M + d.Z % 100, d.S, d.L); return localZ ? date._ : date; }; format.toString = function() { return template; }; return format; } function d3_time_parse(date, template, string, j) { var c, p, t, i = 0, n = template.length, m = string.length; while (i < n) { if (j >= m) return -1; c = template.charCodeAt(i++); if (c === 37) { t = template.charAt(i++); p = d3_time_parsers[t in d3_time_formatPads ? template.charAt(i++) : t]; if (!p || (j = p(date, string, j)) < 0) return -1; } else if (c != string.charCodeAt(j++)) { return -1; } } return j; } d3_time_format.utc = function(template) { var local = d3_time_format(template); function format(date) { try { d3_date = d3_date_utc; var utc = new d3_date(); utc._ = date; return local(utc); } finally { d3_date = Date; } } format.parse = function(string) { try { d3_date = d3_date_utc; var date = local.parse(string); return date && date._; } finally { d3_date = Date; } }; format.toString = local.toString; return format; }; d3_time_format.multi = d3_time_format.utc.multi = d3_time_formatMulti; var d3_time_periodLookup = d3.map(), d3_time_dayRe = d3_time_formatRe(locale_days), d3_time_dayLookup = d3_time_formatLookup(locale_days), d3_time_dayAbbrevRe = d3_time_formatRe(locale_shortDays), d3_time_dayAbbrevLookup = d3_time_formatLookup(locale_shortDays), d3_time_monthRe = d3_time_formatRe(locale_months), d3_time_monthLookup = d3_time_formatLookup(locale_months), d3_time_monthAbbrevRe = d3_time_formatRe(locale_shortMonths), d3_time_monthAbbrevLookup = d3_time_formatLookup(locale_shortMonths); locale_periods.forEach(function(p, i) { d3_time_periodLookup.set(p.toLowerCase(), i); }); var d3_time_formats = { a: function(d) { return locale_shortDays[d.getDay()]; }, A: function(d) { return locale_days[d.getDay()]; }, b: function(d) { return locale_shortMonths[d.getMonth()]; }, B: function(d) { return locale_months[d.getMonth()]; }, c: d3_time_format(locale_dateTime), d: function(d, p) { return d3_time_formatPad(d.getDate(), p, 2); }, e: function(d, p) { return d3_time_formatPad(d.getDate(), p, 2); }, H: function(d, p) { return d3_time_formatPad(d.getHours(), p, 2); }, I: function(d, p) { return d3_time_formatPad(d.getHours() % 12 || 12, p, 2); }, j: function(d, p) { return d3_time_formatPad(1 + d3_time.dayOfYear(d), p, 3); }, L: function(d, p) { return d3_time_formatPad(d.getMilliseconds(), p, 3); }, m: function(d, p) { return d3_time_formatPad(d.getMonth() + 1, p, 2); }, M: function(d, p) { return d3_time_formatPad(d.getMinutes(), p, 2); }, p: function(d) { return locale_periods[+(d.getHours() >= 12)]; }, S: function(d, p) { return d3_time_formatPad(d.getSeconds(), p, 2); }, U: function(d, p) { return d3_time_formatPad(d3_time.sundayOfYear(d), p, 2); }, w: function(d) { return d.getDay(); }, W: function(d, p) { return d3_time_formatPad(d3_time.mondayOfYear(d), p, 2); }, x: d3_time_format(locale_date), X: d3_time_format(locale_time), y: function(d, p) { return d3_time_formatPad(d.getFullYear() % 100, p, 2); }, Y: function(d, p) { return d3_time_formatPad(d.getFullYear() % 1e4, p, 4); }, Z: d3_time_zone, "%": function() { return "%"; } }; var d3_time_parsers = { a: d3_time_parseWeekdayAbbrev, A: d3_time_parseWeekday, b: d3_time_parseMonthAbbrev, B: d3_time_parseMonth, c: d3_time_parseLocaleFull, d: d3_time_parseDay, e: d3_time_parseDay, H: d3_time_parseHour24, I: d3_time_parseHour24, j: d3_time_parseDayOfYear, L: d3_time_parseMilliseconds, m: d3_time_parseMonthNumber, M: d3_time_parseMinutes, p: d3_time_parseAmPm, S: d3_time_parseSeconds, U: d3_time_parseWeekNumberSunday, w: d3_time_parseWeekdayNumber, W: d3_time_parseWeekNumberMonday, x: d3_time_parseLocaleDate, X: d3_time_parseLocaleTime, y: d3_time_parseYear, Y: d3_time_parseFullYear, Z: d3_time_parseZone, "%": d3_time_parseLiteralPercent }; function d3_time_parseWeekdayAbbrev(date, string, i) { d3_time_dayAbbrevRe.lastIndex = 0; var n = d3_time_dayAbbrevRe.exec(string.slice(i)); return n ? (date.w = d3_time_dayAbbrevLookup.get(n[0].toLowerCase()), i + n[0].length) : -1; } function d3_time_parseWeekday(date, string, i) { d3_time_dayRe.lastIndex = 0; var n = d3_time_dayRe.exec(string.slice(i)); return n ? (date.w = d3_time_dayLookup.get(n[0].toLowerCase()), i + n[0].length) : -1; } function d3_time_parseMonthAbbrev(date, string, i) { d3_time_monthAbbrevRe.lastIndex = 0; var n = d3_time_monthAbbrevRe.exec(string.slice(i)); return n ? (date.m = d3_time_monthAbbrevLookup.get(n[0].toLowerCase()), i + n[0].length) : -1; } function d3_time_parseMonth(date, string, i) { d3_time_monthRe.lastIndex = 0; var n = d3_time_monthRe.exec(string.slice(i)); return n ? (date.m = d3_time_monthLookup.get(n[0].toLowerCase()), i + n[0].length) : -1; } function d3_time_parseLocaleFull(date, string, i) { return d3_time_parse(date, d3_time_formats.c.toString(), string, i); } function d3_time_parseLocaleDate(date, string, i) { return d3_time_parse(date, d3_time_formats.x.toString(), string, i); } function d3_time_parseLocaleTime(date, string, i) { return d3_time_parse(date, d3_time_formats.X.toString(), string, i); } function d3_time_parseAmPm(date, string, i) { var n = d3_time_periodLookup.get(string.slice(i, i += 2).toLowerCase()); return n == null ? -1 : (date.p = n, i); } return d3_time_format; } var d3_time_formatPads = { "-": "", _: " ", "0": "0" }, d3_time_numberRe = /^\s*\d+/, d3_time_percentRe = /^%/; function d3_time_formatPad(value, fill, width) { var sign = value < 0 ? "-" : "", string = (sign ? -value : value) + "", length = string.length; return sign + (length < width ? new Array(width - length + 1).join(fill) + string : string); } function d3_time_formatRe(names) { return new RegExp("^(?:" + names.map(d3.requote).join("|") + ")", "i"); } function d3_time_formatLookup(names) { var map = new d3_Map(), i = -1, n = names.length; while (++i < n) map.set(names[i].toLowerCase(), i); return map; } function d3_time_parseWeekdayNumber(date, string, i) { d3_time_numberRe.lastIndex = 0; var n = d3_time_numberRe.exec(string.slice(i, i + 1)); return n ? (date.w = +n[0], i + n[0].length) : -1; } function d3_time_parseWeekNumberSunday(date, string, i) { d3_time_numberRe.lastIndex = 0; var n = d3_time_numberRe.exec(string.slice(i)); return n ? (date.U = +n[0], i + n[0].length) : -1; } function d3_time_parseWeekNumberMonday(date, string, i) { d3_time_numberRe.lastIndex = 0; var n = d3_time_numberRe.exec(string.slice(i)); return n ? (date.W = +n[0], i + n[0].length) : -1; } function d3_time_parseFullYear(date, string, i) { d3_time_numberRe.lastIndex = 0; var n = d3_time_numberRe.exec(string.slice(i, i + 4)); return n ? (date.y = +n[0], i + n[0].length) : -1; } function d3_time_parseYear(date, string, i) { d3_time_numberRe.lastIndex = 0; var n = d3_time_numberRe.exec(string.slice(i, i + 2)); return n ? (date.y = d3_time_expandYear(+n[0]), i + n[0].length) : -1; } function d3_time_parseZone(date, string, i) { return /^[+-]\d{4}$/.test(string = string.slice(i, i + 5)) ? (date.Z = -string, i + 5) : -1; } function d3_time_expandYear(d) { return d + (d > 68 ? 1900 : 2e3); } function d3_time_parseMonthNumber(date, string, i) { d3_time_numberRe.lastIndex = 0; var n = d3_time_numberRe.exec(string.slice(i, i + 2)); return n ? (date.m = n[0] - 1, i + n[0].length) : -1; } function d3_time_parseDay(date, string, i) { d3_time_numberRe.lastIndex = 0; var n = d3_time_numberRe.exec(string.slice(i, i + 2)); return n ? (date.d = +n[0], i + n[0].length) : -1; } function d3_time_parseDayOfYear(date, string, i) { d3_time_numberRe.lastIndex = 0; var n = d3_time_numberRe.exec(string.slice(i, i + 3)); return n ? (date.j = +n[0], i + n[0].length) : -1; } function d3_time_parseHour24(date, string, i) { d3_time_numberRe.lastIndex = 0; var n = d3_time_numberRe.exec(string.slice(i, i + 2)); return n ? (date.H = +n[0], i + n[0].length) : -1; } function d3_time_parseMinutes(date, string, i) { d3_time_numberRe.lastIndex = 0; var n = d3_time_numberRe.exec(string.slice(i, i + 2)); return n ? (date.M = +n[0], i + n[0].length) : -1; } function d3_time_parseSeconds(date, string, i) { d3_time_numberRe.lastIndex = 0; var n = d3_time_numberRe.exec(string.slice(i, i + 2)); return n ? (date.S = +n[0], i + n[0].length) : -1; } function d3_time_parseMilliseconds(date, string, i) { d3_time_numberRe.lastIndex = 0; var n = d3_time_numberRe.exec(string.slice(i, i + 3)); return n ? (date.L = +n[0], i + n[0].length) : -1; } function d3_time_zone(d) { var z = d.getTimezoneOffset(), zs = z > 0 ? "-" : "+", zh = abs(z) / 60 | 0, zm = abs(z) % 60; return zs + d3_time_formatPad(zh, "0", 2) + d3_time_formatPad(zm, "0", 2); } function d3_time_parseLiteralPercent(date, string, i) { d3_time_percentRe.lastIndex = 0; var n = d3_time_percentRe.exec(string.slice(i, i + 1)); return n ? i + n[0].length : -1; } function d3_time_formatMulti(formats) { var n = formats.length, i = -1; while (++i < n) formats[i][0] = this(formats[i][0]); return function(date) { var i = 0, f = formats[i]; while (!f[1](date)) f = formats[++i]; return f[0](date); }; } d3.locale = function(locale) { return { numberFormat: d3_locale_numberFormat(locale), timeFormat: d3_locale_timeFormat(locale) }; }; var d3_locale_enUS = d3.locale({ decimal: ".", thousands: ",", grouping: [ 3 ], currency: [ "$", "" ], dateTime: "%a %b %e %X %Y", date: "%m/%d/%Y", time: "%H:%M:%S", periods: [ "AM", "PM" ], days: [ "Sunday", "Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday" ], shortDays: [ "Sun", "Mon", "Tue", "Wed", "Thu", "Fri", "Sat" ], months: [ "January", "February", "March", "April", "May", "June", "July", "August", "September", "October", "November", "December" ], shortMonths: [ "Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec" ] }); d3.format = d3_locale_enUS.numberFormat; d3.geo = {}; function d3_adder() {} d3_adder.prototype = { s: 0, t: 0, add: function(y) { d3_adderSum(y, this.t, d3_adderTemp); d3_adderSum(d3_adderTemp.s, this.s, this); if (this.s) this.t += d3_adderTemp.t; else this.s = d3_adderTemp.t; }, reset: function() { this.s = this.t = 0; }, valueOf: function() { return this.s; } }; var d3_adderTemp = new d3_adder(); function d3_adderSum(a, b, o) { var x = o.s = a + b, bv = x - a, av = x - bv; o.t = a - av + (b - bv); } d3.geo.stream = function(object, listener) { if (object && d3_geo_streamObjectType.hasOwnProperty(object.type)) { d3_geo_streamObjectType[object.type](object, listener); } else { d3_geo_streamGeometry(object, listener); } }; function d3_geo_streamGeometry(geometry, listener) { if (geometry && d3_geo_streamGeometryType.hasOwnProperty(geometry.type)) { d3_geo_streamGeometryType[geometry.type](geometry, listener); } } var d3_geo_streamObjectType = { Feature: function(feature, listener) { d3_geo_streamGeometry(feature.geometry, listener); }, FeatureCollection: function(object, listener) { var features = object.features, i = -1, n = features.length; while (++i < n) d3_geo_streamGeometry(features[i].geometry, listener); } }; var d3_geo_streamGeometryType = { Sphere: function(object, listener) { listener.sphere(); }, Point: function(object, listener) { object = object.coordinates; listener.point(object[0], object[1], object[2]); }, MultiPoint: function(object, listener) { var coordinates = object.coordinates, i = -1, n = coordinates.length; while (++i < n) object = coordinates[i], listener.point(object[0], object[1], object[2]); }, LineString: function(object, listener) { d3_geo_streamLine(object.coordinates, listener, 0); }, MultiLineString: function(object, listener) { var coordinates = object.coordinates, i = -1, n = coordinates.length; while (++i < n) d3_geo_streamLine(coordinates[i], listener, 0); }, Polygon: function(object, listener) { d3_geo_streamPolygon(object.coordinates, listener); }, MultiPolygon: function(object, listener) { var coordinates = object.coordinates, i = -1, n = coordinates.length; while (++i < n) d3_geo_streamPolygon(coordinates[i], listener); }, GeometryCollection: function(object, listener) { var geometries = object.geometries, i = -1, n = geometries.length; while (++i < n) d3_geo_streamGeometry(geometries[i], listener); } }; function d3_geo_streamLine(coordinates, listener, closed) { var i = -1, n = coordinates.length - closed, coordinate; listener.lineStart(); while (++i < n) coordinate = coordinates[i], listener.point(coordinate[0], coordinate[1], coordinate[2]); listener.lineEnd(); } function d3_geo_streamPolygon(coordinates, listener) { var i = -1, n = coordinates.length; listener.polygonStart(); while (++i < n) d3_geo_streamLine(coordinates[i], listener, 1); listener.polygonEnd(); } d3.geo.area = function(object) { d3_geo_areaSum = 0; d3.geo.stream(object, d3_geo_area); return d3_geo_areaSum; }; var d3_geo_areaSum, d3_geo_areaRingSum = new d3_adder(); var d3_geo_area = { sphere: function() { d3_geo_areaSum += 4 * π; }, point: d3_noop, lineStart: d3_noop, lineEnd: d3_noop, polygonStart: function() { d3_geo_areaRingSum.reset(); d3_geo_area.lineStart = d3_geo_areaRingStart; }, polygonEnd: function() { var area = 2 * d3_geo_areaRingSum; d3_geo_areaSum += area < 0 ? 4 * π + area : area; d3_geo_area.lineStart = d3_geo_area.lineEnd = d3_geo_area.point = d3_noop; } }; function d3_geo_areaRingStart() { var λ00, φ00, λ0, cosφ0, sinφ0; d3_geo_area.point = function(λ, φ) { d3_geo_area.point = nextPoint; λ0 = (λ00 = λ) * d3_radians, cosφ0 = Math.cos(φ = (φ00 = φ) * d3_radians / 2 + π / 4), sinφ0 = Math.sin(φ); }; function nextPoint(λ, φ) { λ *= d3_radians; φ = φ * d3_radians / 2 + π / 4; var dλ = λ - λ0, sdλ = dλ >= 0 ? 1 : -1, adλ = sdλ * dλ, cosφ = Math.cos(φ), sinφ = Math.sin(φ), k = sinφ0 * sinφ, u = cosφ0 * cosφ + k * Math.cos(adλ), v = k * sdλ * Math.sin(adλ); d3_geo_areaRingSum.add(Math.atan2(v, u)); λ0 = λ, cosφ0 = cosφ, sinφ0 = sinφ; } d3_geo_area.lineEnd = function() { nextPoint(λ00, φ00); }; } function d3_geo_cartesian(spherical) { var λ = spherical[0], φ = spherical[1], cosφ = Math.cos(φ); return [ cosφ * Math.cos(λ), cosφ * Math.sin(λ), Math.sin(φ) ]; } function d3_geo_cartesianDot(a, b) { return a[0] * b[0] + a[1] * b[1] + a[2] * b[2]; } function d3_geo_cartesianCross(a, b) { return [ a[1] * b[2] - a[2] * b[1], a[2] * b[0] - a[0] * b[2], a[0] * b[1] - a[1] * b[0] ]; } function d3_geo_cartesianAdd(a, b) { a[0] += b[0]; a[1] += b[1]; a[2] += b[2]; } function d3_geo_cartesianScale(vector, k) { return [ vector[0] * k, vector[1] * k, vector[2] * k ]; } function d3_geo_cartesianNormalize(d) { var l = Math.sqrt(d[0] * d[0] + d[1] * d[1] + d[2] * d[2]); d[0] /= l; d[1] /= l; d[2] /= l; } function d3_geo_spherical(cartesian) { return [ Math.atan2(cartesian[1], cartesian[0]), d3_asin(cartesian[2]) ]; } function d3_geo_sphericalEqual(a, b) { return abs(a[0] - b[0]) < ε && abs(a[1] - b[1]) < ε; } d3.geo.bounds = function() { var λ0, φ0, λ1, φ1, λ_, λ__, φ__, p0, dλSum, ranges, range; var bound = { point: point, lineStart: lineStart, lineEnd: lineEnd, polygonStart: function() { bound.point = ringPoint; bound.lineStart = ringStart; bound.lineEnd = ringEnd; dλSum = 0; d3_geo_area.polygonStart(); }, polygonEnd: function() { d3_geo_area.polygonEnd(); bound.point = point; bound.lineStart = lineStart; bound.lineEnd = lineEnd; if (d3_geo_areaRingSum < 0) λ0 = -(λ1 = 180), φ0 = -(φ1 = 90); else if (dλSum > ε) φ1 = 90; else if (dλSum < -ε) φ0 = -90; range[0] = λ0, range[1] = λ1; } }; function point(λ, φ) { ranges.push(range = [ λ0 = λ, λ1 = λ ]); if (φ < φ0) φ0 = φ; if (φ > φ1) φ1 = φ; } function linePoint(λ, φ) { var p = d3_geo_cartesian([ λ * d3_radians, φ * d3_radians ]); if (p0) { var normal = d3_geo_cartesianCross(p0, p), equatorial = [ normal[1], -normal[0], 0 ], inflection = d3_geo_cartesianCross(equatorial, normal); d3_geo_cartesianNormalize(inflection); inflection = d3_geo_spherical(inflection); var dλ = λ - λ_, s = dλ > 0 ? 1 : -1, λi = inflection[0] * d3_degrees * s, antimeridian = abs(dλ) > 180; if (antimeridian ^ (s * λ_ < λi && λi < s * λ)) { var φi = inflection[1] * d3_degrees; if (φi > φ1) φ1 = φi; } else if (λi = (λi + 360) % 360 - 180, antimeridian ^ (s * λ_ < λi && λi < s * λ)) { var φi = -inflection[1] * d3_degrees; if (φi < φ0) φ0 = φi; } else { if (φ < φ0) φ0 = φ; if (φ > φ1) φ1 = φ; } if (antimeridian) { if (λ < λ_) { if (angle(λ0, λ) > angle(λ0, λ1)) λ1 = λ; } else { if (angle(λ, λ1) > angle(λ0, λ1)) λ0 = λ; } } else { if (λ1 >= λ0) { if (λ < λ0) λ0 = λ; if (λ > λ1) λ1 = λ; } else { if (λ > λ_) { if (angle(λ0, λ) > angle(λ0, λ1)) λ1 = λ; } else { if (angle(λ, λ1) > angle(λ0, λ1)) λ0 = λ; } } } } else { point(λ, φ); } p0 = p, λ_ = λ; } function lineStart() { bound.point = linePoint; } function lineEnd() { range[0] = λ0, range[1] = λ1; bound.point = point; p0 = null; } function ringPoint(λ, φ) { if (p0) { var dλ = λ - λ_; dλSum += abs(dλ) > 180 ? dλ + (dλ > 0 ? 360 : -360) : dλ; } else λ__ = λ, φ__ = φ; d3_geo_area.point(λ, φ); linePoint(λ, φ); } function ringStart() { d3_geo_area.lineStart(); } function ringEnd() { ringPoint(λ__, φ__); d3_geo_area.lineEnd(); if (abs(dλSum) > ε) λ0 = -(λ1 = 180); range[0] = λ0, range[1] = λ1; p0 = null; } function angle(λ0, λ1) { return (λ1 -= λ0) < 0 ? λ1 + 360 : λ1; } function compareRanges(a, b) { return a[0] - b[0]; } function withinRange(x, range) { return range[0] <= range[1] ? range[0] <= x && x <= range[1] : x < range[0] || range[1] < x; } return function(feature) { φ1 = λ1 = -(λ0 = φ0 = Infinity); ranges = []; d3.geo.stream(feature, bound); var n = ranges.length; if (n) { ranges.sort(compareRanges); for (var i = 1, a = ranges[0], b, merged = [ a ]; i < n; ++i) { b = ranges[i]; if (withinRange(b[0], a) || withinRange(b[1], a)) { if (angle(a[0], b[1]) > angle(a[0], a[1])) a[1] = b[1]; if (angle(b[0], a[1]) > angle(a[0], a[1])) a[0] = b[0]; } else { merged.push(a = b); } } var best = -Infinity, dλ; for (var n = merged.length - 1, i = 0, a = merged[n], b; i <= n; a = b, ++i) { b = merged[i]; if ((dλ = angle(a[1], b[0])) > best) best = dλ, λ0 = b[0], λ1 = a[1]; } } ranges = range = null; return λ0 === Infinity || φ0 === Infinity ? [ [ NaN, NaN ], [ NaN, NaN ] ] : [ [ λ0, φ0 ], [ λ1, φ1 ] ]; }; }(); d3.geo.centroid = function(object) { d3_geo_centroidW0 = d3_geo_centroidW1 = d3_geo_centroidX0 = d3_geo_centroidY0 = d3_geo_centroidZ0 = d3_geo_centroidX1 = d3_geo_centroidY1 = d3_geo_centroidZ1 = d3_geo_centroidX2 = d3_geo_centroidY2 = d3_geo_centroidZ2 = 0; d3.geo.stream(object, d3_geo_centroid); var x = d3_geo_centroidX2, y = d3_geo_centroidY2, z = d3_geo_centroidZ2, m = x * x + y * y + z * z; if (m < ε2) { x = d3_geo_centroidX1, y = d3_geo_centroidY1, z = d3_geo_centroidZ1; if (d3_geo_centroidW1 < ε) x = d3_geo_centroidX0, y = d3_geo_centroidY0, z = d3_geo_centroidZ0; m = x * x + y * y + z * z; if (m < ε2) return [ NaN, NaN ]; } return [ Math.atan2(y, x) * d3_degrees, d3_asin(z / Math.sqrt(m)) * d3_degrees ]; }; var d3_geo_centroidW0, d3_geo_centroidW1, d3_geo_centroidX0, d3_geo_centroidY0, d3_geo_centroidZ0, d3_geo_centroidX1, d3_geo_centroidY1, d3_geo_centroidZ1, d3_geo_centroidX2, d3_geo_centroidY2, d3_geo_centroidZ2; var d3_geo_centroid = { sphere: d3_noop, point: d3_geo_centroidPoint, lineStart: d3_geo_centroidLineStart, lineEnd: d3_geo_centroidLineEnd, polygonStart: function() { d3_geo_centroid.lineStart = d3_geo_centroidRingStart; }, polygonEnd: function() { d3_geo_centroid.lineStart = d3_geo_centroidLineStart; } }; function d3_geo_centroidPoint(λ, φ) { λ *= d3_radians; var cosφ = Math.cos(φ *= d3_radians); d3_geo_centroidPointXYZ(cosφ * Math.cos(λ), cosφ * Math.sin(λ), Math.sin(φ)); } function d3_geo_centroidPointXYZ(x, y, z) { ++d3_geo_centroidW0; d3_geo_centroidX0 += (x - d3_geo_centroidX0) / d3_geo_centroidW0; d3_geo_centroidY0 += (y - d3_geo_centroidY0) / d3_geo_centroidW0; d3_geo_centroidZ0 += (z - d3_geo_centroidZ0) / d3_geo_centroidW0; } function d3_geo_centroidLineStart() { var x0, y0, z0; d3_geo_centroid.point = function(λ, φ) { λ *= d3_radians; var cosφ = Math.cos(φ *= d3_radians); x0 = cosφ * Math.cos(λ); y0 = cosφ * Math.sin(λ); z0 = Math.sin(φ); d3_geo_centroid.point = nextPoint; d3_geo_centroidPointXYZ(x0, y0, z0); }; function nextPoint(λ, φ) { λ *= d3_radians; var cosφ = Math.cos(φ *= d3_radians), x = cosφ * Math.cos(λ), y = cosφ * Math.sin(λ), z = Math.sin(φ), w = Math.atan2(Math.sqrt((w = y0 * z - z0 * y) * w + (w = z0 * x - x0 * z) * w + (w = x0 * y - y0 * x) * w), x0 * x + y0 * y + z0 * z); d3_geo_centroidW1 += w; d3_geo_centroidX1 += w * (x0 + (x0 = x)); d3_geo_centroidY1 += w * (y0 + (y0 = y)); d3_geo_centroidZ1 += w * (z0 + (z0 = z)); d3_geo_centroidPointXYZ(x0, y0, z0); } } function d3_geo_centroidLineEnd() { d3_geo_centroid.point = d3_geo_centroidPoint; } function d3_geo_centroidRingStart() { var λ00, φ00, x0, y0, z0; d3_geo_centroid.point = function(λ, φ) { λ00 = λ, φ00 = φ; d3_geo_centroid.point = nextPoint; λ *= d3_radians; var cosφ = Math.cos(φ *= d3_radians); x0 = cosφ * Math.cos(λ); y0 = cosφ * Math.sin(λ); z0 = Math.sin(φ); d3_geo_centroidPointXYZ(x0, y0, z0); }; d3_geo_centroid.lineEnd = function() { nextPoint(λ00, φ00); d3_geo_centroid.lineEnd = d3_geo_centroidLineEnd; d3_geo_centroid.point = d3_geo_centroidPoint; }; function nextPoint(λ, φ) { λ *= d3_radians; var cosφ = Math.cos(φ *= d3_radians), x = cosφ * Math.cos(λ), y = cosφ * Math.sin(λ), z = Math.sin(φ), cx = y0 * z - z0 * y, cy = z0 * x - x0 * z, cz = x0 * y - y0 * x, m = Math.sqrt(cx * cx + cy * cy + cz * cz), u = x0 * x + y0 * y + z0 * z, v = m && -d3_acos(u) / m, w = Math.atan2(m, u); d3_geo_centroidX2 += v * cx; d3_geo_centroidY2 += v * cy; d3_geo_centroidZ2 += v * cz; d3_geo_centroidW1 += w; d3_geo_centroidX1 += w * (x0 + (x0 = x)); d3_geo_centroidY1 += w * (y0 + (y0 = y)); d3_geo_centroidZ1 += w * (z0 + (z0 = z)); d3_geo_centroidPointXYZ(x0, y0, z0); } } function d3_geo_compose(a, b) { function compose(x, y) { return x = a(x, y), b(x[0], x[1]); } if (a.invert && b.invert) compose.invert = function(x, y) { return x = b.invert(x, y), x && a.invert(x[0], x[1]); }; return compose; } function d3_true() { return true; } function d3_geo_clipPolygon(segments, compare, clipStartInside, interpolate, listener) { var subject = [], clip = []; segments.forEach(function(segment) { if ((n = segment.length - 1) <= 0) return; var n, p0 = segment[0], p1 = segment[n]; if (d3_geo_sphericalEqual(p0, p1)) { listener.lineStart(); for (var i = 0; i < n; ++i) listener.point((p0 = segment[i])[0], p0[1]); listener.lineEnd(); return; } var a = new d3_geo_clipPolygonIntersection(p0, segment, null, true), b = new d3_geo_clipPolygonIntersection(p0, null, a, false); a.o = b; subject.push(a); clip.push(b); a = new d3_geo_clipPolygonIntersection(p1, segment, null, false); b = new d3_geo_clipPolygonIntersection(p1, null, a, true); a.o = b; subject.push(a); clip.push(b); }); clip.sort(compare); d3_geo_clipPolygonLinkCircular(subject); d3_geo_clipPolygonLinkCircular(clip); if (!subject.length) return; for (var i = 0, entry = clipStartInside, n = clip.length; i < n; ++i) { clip[i].e = entry = !entry; } var start = subject[0], points, point; while (1) { var current = start, isSubject = true; while (current.v) if ((current = current.n) === start) return; points = current.z; listener.lineStart(); do { current.v = current.o.v = true; if (current.e) { if (isSubject) { for (var i = 0, n = points.length; i < n; ++i) listener.point((point = points[i])[0], point[1]); } else { interpolate(current.x, current.n.x, 1, listener); } current = current.n; } else { if (isSubject) { points = current.p.z; for (var i = points.length - 1; i >= 0; --i) listener.point((point = points[i])[0], point[1]); } else { interpolate(current.x, current.p.x, -1, listener); } current = current.p; } current = current.o; points = current.z; isSubject = !isSubject; } while (!current.v); listener.lineEnd(); } } function d3_geo_clipPolygonLinkCircular(array) { if (!(n = array.length)) return; var n, i = 0, a = array[0], b; while (++i < n) { a.n = b = array[i]; b.p = a; a = b; } a.n = b = array[0]; b.p = a; } function d3_geo_clipPolygonIntersection(point, points, other, entry) { this.x = point; this.z = points; this.o = other; this.e = entry; this.v = false; this.n = this.p = null; } function d3_geo_clip(pointVisible, clipLine, interpolate, clipStart) { return function(rotate, listener) { var line = clipLine(listener), rotatedClipStart = rotate.invert(clipStart[0], clipStart[1]); var clip = { point: point, lineStart: lineStart, lineEnd: lineEnd, polygonStart: function() { clip.point = pointRing; clip.lineStart = ringStart; clip.lineEnd = ringEnd; segments = []; polygon = []; }, polygonEnd: function() { clip.point = point; clip.lineStart = lineStart; clip.lineEnd = lineEnd; segments = d3.merge(segments); var clipStartInside = d3_geo_pointInPolygon(rotatedClipStart, polygon); if (segments.length) { if (!polygonStarted) listener.polygonStart(), polygonStarted = true; d3_geo_clipPolygon(segments, d3_geo_clipSort, clipStartInside, interpolate, listener); } else if (clipStartInside) { if (!polygonStarted) listener.polygonStart(), polygonStarted = true; listener.lineStart(); interpolate(null, null, 1, listener); listener.lineEnd(); } if (polygonStarted) listener.polygonEnd(), polygonStarted = false; segments = polygon = null; }, sphere: function() { listener.polygonStart(); listener.lineStart(); interpolate(null, null, 1, listener); listener.lineEnd(); listener.polygonEnd(); } }; function point(λ, φ) { var point = rotate(λ, φ); if (pointVisible(λ = point[0], φ = point[1])) listener.point(λ, φ); } function pointLine(λ, φ) { var point = rotate(λ, φ); line.point(point[0], point[1]); } function lineStart() { clip.point = pointLine; line.lineStart(); } function lineEnd() { clip.point = point; line.lineEnd(); } var segments; var buffer = d3_geo_clipBufferListener(), ringListener = clipLine(buffer), polygonStarted = false, polygon, ring; function pointRing(λ, φ) { ring.push([ λ, φ ]); var point = rotate(λ, φ); ringListener.point(point[0], point[1]); } function ringStart() { ringListener.lineStart(); ring = []; } function ringEnd() { pointRing(ring[0][0], ring[0][1]); ringListener.lineEnd(); var clean = ringListener.clean(), ringSegments = buffer.buffer(), segment, n = ringSegments.length; ring.pop(); polygon.push(ring); ring = null; if (!n) return; if (clean & 1) { segment = ringSegments[0]; var n = segment.length - 1, i = -1, point; if (n > 0) { if (!polygonStarted) listener.polygonStart(), polygonStarted = true; listener.lineStart(); while (++i < n) listener.point((point = segment[i])[0], point[1]); listener.lineEnd(); } return; } if (n > 1 && clean & 2) ringSegments.push(ringSegments.pop().concat(ringSegments.shift())); segments.push(ringSegments.filter(d3_geo_clipSegmentLength1)); } return clip; }; } function d3_geo_clipSegmentLength1(segment) { return segment.length > 1; } function d3_geo_clipBufferListener() { var lines = [], line; return { lineStart: function() { lines.push(line = []); }, point: function(λ, φ) { line.push([ λ, φ ]); }, lineEnd: d3_noop, buffer: function() { var buffer = lines; lines = []; line = null; return buffer; }, rejoin: function() { if (lines.length > 1) lines.push(lines.pop().concat(lines.shift())); } }; } function d3_geo_clipSort(a, b) { return ((a = a.x)[0] < 0 ? a[1] - halfπ - ε : halfπ - a[1]) - ((b = b.x)[0] < 0 ? b[1] - halfπ - ε : halfπ - b[1]); } var d3_geo_clipAntimeridian = d3_geo_clip(d3_true, d3_geo_clipAntimeridianLine, d3_geo_clipAntimeridianInterpolate, [ -π, -π / 2 ]); function d3_geo_clipAntimeridianLine(listener) { var λ0 = NaN, φ0 = NaN, sλ0 = NaN, clean; return { lineStart: function() { listener.lineStart(); clean = 1; }, point: function(λ1, φ1) { var sλ1 = λ1 > 0 ? π : -π, dλ = abs(λ1 - λ0); if (abs(dλ - π) < ε) { listener.point(λ0, φ0 = (φ0 + φ1) / 2 > 0 ? halfπ : -halfπ); listener.point(sλ0, φ0); listener.lineEnd(); listener.lineStart(); listener.point(sλ1, φ0); listener.point(λ1, φ0); clean = 0; } else if (sλ0 !== sλ1 && dλ >= π) { if (abs(λ0 - sλ0) < ε) λ0 -= sλ0 * ε; if (abs(λ1 - sλ1) < ε) λ1 -= sλ1 * ε; φ0 = d3_geo_clipAntimeridianIntersect(λ0, φ0, λ1, φ1); listener.point(sλ0, φ0); listener.lineEnd(); listener.lineStart(); listener.point(sλ1, φ0); clean = 0; } listener.point(λ0 = λ1, φ0 = φ1); sλ0 = sλ1; }, lineEnd: function() { listener.lineEnd(); λ0 = φ0 = NaN; }, clean: function() { return 2 - clean; } }; } function d3_geo_clipAntimeridianIntersect(λ0, φ0, λ1, φ1) { var cosφ0, cosφ1, sinλ0_λ1 = Math.sin(λ0 - λ1); return abs(sinλ0_λ1) > ε ? Math.atan((Math.sin(φ0) * (cosφ1 = Math.cos(φ1)) * Math.sin(λ1) - Math.sin(φ1) * (cosφ0 = Math.cos(φ0)) * Math.sin(λ0)) / (cosφ0 * cosφ1 * sinλ0_λ1)) : (φ0 + φ1) / 2; } function d3_geo_clipAntimeridianInterpolate(from, to, direction, listener) { var φ; if (from == null) { φ = direction * halfπ; listener.point(-π, φ); listener.point(0, φ); listener.point(π, φ); listener.point(π, 0); listener.point(π, -φ); listener.point(0, -φ); listener.point(-π, -φ); listener.point(-π, 0); listener.point(-π, φ); } else if (abs(from[0] - to[0]) > ε) { var s = from[0] < to[0] ? π : -π; φ = direction * s / 2; listener.point(-s, φ); listener.point(0, φ); listener.point(s, φ); } else { listener.point(to[0], to[1]); } } function d3_geo_pointInPolygon(point, polygon) { var meridian = point[0], parallel = point[1], meridianNormal = [ Math.sin(meridian), -Math.cos(meridian), 0 ], polarAngle = 0, winding = 0; d3_geo_areaRingSum.reset(); for (var i = 0, n = polygon.length; i < n; ++i) { var ring = polygon[i], m = ring.length; if (!m) continue; var point0 = ring[0], λ0 = point0[0], φ0 = point0[1] / 2 + π / 4, sinφ0 = Math.sin(φ0), cosφ0 = Math.cos(φ0), j = 1; while (true) { if (j === m) j = 0; point = ring[j]; var λ = point[0], φ = point[1] / 2 + π / 4, sinφ = Math.sin(φ), cosφ = Math.cos(φ), dλ = λ - λ0, sdλ = dλ >= 0 ? 1 : -1, adλ = sdλ * dλ, antimeridian = adλ > π, k = sinφ0 * sinφ; d3_geo_areaRingSum.add(Math.atan2(k * sdλ * Math.sin(adλ), cosφ0 * cosφ + k * Math.cos(adλ))); polarAngle += antimeridian ? dλ + sdλ * τ : dλ; if (antimeridian ^ λ0 >= meridian ^ λ >= meridian) { var arc = d3_geo_cartesianCross(d3_geo_cartesian(point0), d3_geo_cartesian(point)); d3_geo_cartesianNormalize(arc); var intersection = d3_geo_cartesianCross(meridianNormal, arc); d3_geo_cartesianNormalize(intersection); var φarc = (antimeridian ^ dλ >= 0 ? -1 : 1) * d3_asin(intersection[2]); if (parallel > φarc || parallel === φarc && (arc[0] || arc[1])) { winding += antimeridian ^ dλ >= 0 ? 1 : -1; } } if (!j++) break; λ0 = λ, sinφ0 = sinφ, cosφ0 = cosφ, point0 = point; } } return (polarAngle < -ε || polarAngle < ε && d3_geo_areaRingSum < -ε) ^ winding & 1; } function d3_geo_clipCircle(radius) { var cr = Math.cos(radius), smallRadius = cr > 0, notHemisphere = abs(cr) > ε, interpolate = d3_geo_circleInterpolate(radius, 6 * d3_radians); return d3_geo_clip(visible, clipLine, interpolate, smallRadius ? [ 0, -radius ] : [ -π, radius - π ]); function visible(λ, φ) { return Math.cos(λ) * Math.cos(φ) > cr; } function clipLine(listener) { var point0, c0, v0, v00, clean; return { lineStart: function() { v00 = v0 = false; clean = 1; }, point: function(λ, φ) { var point1 = [ λ, φ ], point2, v = visible(λ, φ), c = smallRadius ? v ? 0 : code(λ, φ) : v ? code(λ + (λ < 0 ? π : -π), φ) : 0; if (!point0 && (v00 = v0 = v)) listener.lineStart(); if (v !== v0) { point2 = intersect(point0, point1); if (d3_geo_sphericalEqual(point0, point2) || d3_geo_sphericalEqual(point1, point2)) { point1[0] += ε; point1[1] += ε; v = visible(point1[0], point1[1]); } } if (v !== v0) { clean = 0; if (v) { listener.lineStart(); point2 = intersect(point1, point0); listener.point(point2[0], point2[1]); } else { point2 = intersect(point0, point1); listener.point(point2[0], point2[1]); listener.lineEnd(); } point0 = point2; } else if (notHemisphere && point0 && smallRadius ^ v) { var t; if (!(c & c0) && (t = intersect(point1, point0, true))) { clean = 0; if (smallRadius) { listener.lineStart(); listener.point(t[0][0], t[0][1]); listener.point(t[1][0], t[1][1]); listener.lineEnd(); } else { listener.point(t[1][0], t[1][1]); listener.lineEnd(); listener.lineStart(); listener.point(t[0][0], t[0][1]); } } } if (v && (!point0 || !d3_geo_sphericalEqual(point0, point1))) { listener.point(point1[0], point1[1]); } point0 = point1, v0 = v, c0 = c; }, lineEnd: function() { if (v0) listener.lineEnd(); point0 = null; }, clean: function() { return clean | (v00 && v0) << 1; } }; } function intersect(a, b, two) { var pa = d3_geo_cartesian(a), pb = d3_geo_cartesian(b); var n1 = [ 1, 0, 0 ], n2 = d3_geo_cartesianCross(pa, pb), n2n2 = d3_geo_cartesianDot(n2, n2), n1n2 = n2[0], determinant = n2n2 - n1n2 * n1n2; if (!determinant) return !two && a; var c1 = cr * n2n2 / determinant, c2 = -cr * n1n2 / determinant, n1xn2 = d3_geo_cartesianCross(n1, n2), A = d3_geo_cartesianScale(n1, c1), B = d3_geo_cartesianScale(n2, c2); d3_geo_cartesianAdd(A, B); var u = n1xn2, w = d3_geo_cartesianDot(A, u), uu = d3_geo_cartesianDot(u, u), t2 = w * w - uu * (d3_geo_cartesianDot(A, A) - 1); if (t2 < 0) return; var t = Math.sqrt(t2), q = d3_geo_cartesianScale(u, (-w - t) / uu); d3_geo_cartesianAdd(q, A); q = d3_geo_spherical(q); if (!two) return q; var λ0 = a[0], λ1 = b[0], φ0 = a[1], φ1 = b[1], z; if (λ1 < λ0) z = λ0, λ0 = λ1, λ1 = z; var δλ = λ1 - λ0, polar = abs(δλ - π) < ε, meridian = polar || δλ < ε; if (!polar && φ1 < φ0) z = φ0, φ0 = φ1, φ1 = z; if (meridian ? polar ? φ0 + φ1 > 0 ^ q[1] < (abs(q[0] - λ0) < ε ? φ0 : φ1) : φ0 <= q[1] && q[1] <= φ1 : δλ > π ^ (λ0 <= q[0] && q[0] <= λ1)) { var q1 = d3_geo_cartesianScale(u, (-w + t) / uu); d3_geo_cartesianAdd(q1, A); return [ q, d3_geo_spherical(q1) ]; } } function code(λ, φ) { var r = smallRadius ? radius : π - radius, code = 0; if (λ < -r) code |= 1; else if (λ > r) code |= 2; if (φ < -r) code |= 4; else if (φ > r) code |= 8; return code; } } function d3_geom_clipLine(x0, y0, x1, y1) { return function(line) { var a = line.a, b = line.b, ax = a.x, ay = a.y, bx = b.x, by = b.y, t0 = 0, t1 = 1, dx = bx - ax, dy = by - ay, r; r = x0 - ax; if (!dx && r > 0) return; r /= dx; if (dx < 0) { if (r < t0) return; if (r < t1) t1 = r; } else if (dx > 0) { if (r > t1) return; if (r > t0) t0 = r; } r = x1 - ax; if (!dx && r < 0) return; r /= dx; if (dx < 0) { if (r > t1) return; if (r > t0) t0 = r; } else if (dx > 0) { if (r < t0) return; if (r < t1) t1 = r; } r = y0 - ay; if (!dy && r > 0) return; r /= dy; if (dy < 0) { if (r < t0) return; if (r < t1) t1 = r; } else if (dy > 0) { if (r > t1) return; if (r > t0) t0 = r; } r = y1 - ay; if (!dy && r < 0) return; r /= dy; if (dy < 0) { if (r > t1) return; if (r > t0) t0 = r; } else if (dy > 0) { if (r < t0) return; if (r < t1) t1 = r; } if (t0 > 0) line.a = { x: ax + t0 * dx, y: ay + t0 * dy }; if (t1 < 1) line.b = { x: ax + t1 * dx, y: ay + t1 * dy }; return line; }; } var d3_geo_clipExtentMAX = 1e9; d3.geo.clipExtent = function() { var x0, y0, x1, y1, stream, clip, clipExtent = { stream: function(output) { if (stream) stream.valid = false; stream = clip(output); stream.valid = true; return stream; }, extent: function(_) { if (!arguments.length) return [ [ x0, y0 ], [ x1, y1 ] ]; clip = d3_geo_clipExtent(x0 = +_[0][0], y0 = +_[0][1], x1 = +_[1][0], y1 = +_[1][1]); if (stream) stream.valid = false, stream = null; return clipExtent; } }; return clipExtent.extent([ [ 0, 0 ], [ 960, 500 ] ]); }; function d3_geo_clipExtent(x0, y0, x1, y1) { return function(listener) { var listener_ = listener, bufferListener = d3_geo_clipBufferListener(), clipLine = d3_geom_clipLine(x0, y0, x1, y1), segments, polygon, ring; var clip = { point: point, lineStart: lineStart, lineEnd: lineEnd, polygonStart: function() { listener = bufferListener; segments = []; polygon = []; clean = true; }, polygonEnd: function() { listener = listener_; segments = d3.merge(segments); var clipStartInside = insidePolygon([ x0, y1 ]), inside = clean && clipStartInside, visible = segments.length; if (inside || visible) { listener.polygonStart(); if (inside) { listener.lineStart(); interpolate(null, null, 1, listener); listener.lineEnd(); } if (visible) { d3_geo_clipPolygon(segments, compare, clipStartInside, interpolate, listener); } listener.polygonEnd(); } segments = polygon = ring = null; } }; function insidePolygon(p) { var wn = 0, n = polygon.length, y = p[1]; for (var i = 0; i < n; ++i) { for (var j = 1, v = polygon[i], m = v.length, a = v[0], b; j < m; ++j) { b = v[j]; if (a[1] <= y) { if (b[1] > y && d3_cross2d(a, b, p) > 0) ++wn; } else { if (b[1] <= y && d3_cross2d(a, b, p) < 0) --wn; } a = b; } } return wn !== 0; } function interpolate(from, to, direction, listener) { var a = 0, a1 = 0; if (from == null || (a = corner(from, direction)) !== (a1 = corner(to, direction)) || comparePoints(from, to) < 0 ^ direction > 0) { do { listener.point(a === 0 || a === 3 ? x0 : x1, a > 1 ? y1 : y0); } while ((a = (a + direction + 4) % 4) !== a1); } else { listener.point(to[0], to[1]); } } function pointVisible(x, y) { return x0 <= x && x <= x1 && y0 <= y && y <= y1; } function point(x, y) { if (pointVisible(x, y)) listener.point(x, y); } var x__, y__, v__, x_, y_, v_, first, clean; function lineStart() { clip.point = linePoint; if (polygon) polygon.push(ring = []); first = true; v_ = false; x_ = y_ = NaN; } function lineEnd() { if (segments) { linePoint(x__, y__); if (v__ && v_) bufferListener.rejoin(); segments.push(bufferListener.buffer()); } clip.point = point; if (v_) listener.lineEnd(); } function linePoint(x, y) { x = Math.max(-d3_geo_clipExtentMAX, Math.min(d3_geo_clipExtentMAX, x)); y = Math.max(-d3_geo_clipExtentMAX, Math.min(d3_geo_clipExtentMAX, y)); var v = pointVisible(x, y); if (polygon) ring.push([ x, y ]); if (first) { x__ = x, y__ = y, v__ = v; first = false; if (v) { listener.lineStart(); listener.point(x, y); } } else { if (v && v_) listener.point(x, y); else { var l = { a: { x: x_, y: y_ }, b: { x: x, y: y } }; if (clipLine(l)) { if (!v_) { listener.lineStart(); listener.point(l.a.x, l.a.y); } listener.point(l.b.x, l.b.y); if (!v) listener.lineEnd(); clean = false; } else if (v) { listener.lineStart(); listener.point(x, y); clean = false; } } } x_ = x, y_ = y, v_ = v; } return clip; }; function corner(p, direction) { return abs(p[0] - x0) < ε ? direction > 0 ? 0 : 3 : abs(p[0] - x1) < ε ? direction > 0 ? 2 : 1 : abs(p[1] - y0) < ε ? direction > 0 ? 1 : 0 : direction > 0 ? 3 : 2; } function compare(a, b) { return comparePoints(a.x, b.x); } function comparePoints(a, b) { var ca = corner(a, 1), cb = corner(b, 1); return ca !== cb ? ca - cb : ca === 0 ? b[1] - a[1] : ca === 1 ? a[0] - b[0] : ca === 2 ? a[1] - b[1] : b[0] - a[0]; } } function d3_geo_conic(projectAt) { var φ0 = 0, φ1 = π / 3, m = d3_geo_projectionMutator(projectAt), p = m(φ0, φ1); p.parallels = function(_) { if (!arguments.length) return [ φ0 / π * 180, φ1 / π * 180 ]; return m(φ0 = _[0] * π / 180, φ1 = _[1] * π / 180); }; return p; } function d3_geo_conicEqualArea(φ0, φ1) { var sinφ0 = Math.sin(φ0), n = (sinφ0 + Math.sin(φ1)) / 2, C = 1 + sinφ0 * (2 * n - sinφ0), ρ0 = Math.sqrt(C) / n; function forward(λ, φ) { var ρ = Math.sqrt(C - 2 * n * Math.sin(φ)) / n; return [ ρ * Math.sin(λ *= n), ρ0 - ρ * Math.cos(λ) ]; } forward.invert = function(x, y) { var ρ0_y = ρ0 - y; return [ Math.atan2(x, ρ0_y) / n, d3_asin((C - (x * x + ρ0_y * ρ0_y) * n * n) / (2 * n)) ]; }; return forward; } (d3.geo.conicEqualArea = function() { return d3_geo_conic(d3_geo_conicEqualArea); }).raw = d3_geo_conicEqualArea; d3.geo.albers = function() { return d3.geo.conicEqualArea().rotate([ 96, 0 ]).center([ -.6, 38.7 ]).parallels([ 29.5, 45.5 ]).scale(1070); }; d3.geo.albersUsa = function() { var lower48 = d3.geo.albers(); var alaska = d3.geo.conicEqualArea().rotate([ 154, 0 ]).center([ -2, 58.5 ]).parallels([ 55, 65 ]); var hawaii = d3.geo.conicEqualArea().rotate([ 157, 0 ]).center([ -3, 19.9 ]).parallels([ 8, 18 ]); var point, pointStream = { point: function(x, y) { point = [ x, y ]; } }, lower48Point, alaskaPoint, hawaiiPoint; function albersUsa(coordinates) { var x = coordinates[0], y = coordinates[1]; point = null; (lower48Point(x, y), point) || (alaskaPoint(x, y), point) || hawaiiPoint(x, y); return point; } albersUsa.invert = function(coordinates) { var k = lower48.scale(), t = lower48.translate(), x = (coordinates[0] - t[0]) / k, y = (coordinates[1] - t[1]) / k; return (y >= .12 && y < .234 && x >= -.425 && x < -.214 ? alaska : y >= .166 && y < .234 && x >= -.214 && x < -.115 ? hawaii : lower48).invert(coordinates); }; albersUsa.stream = function(stream) { var lower48Stream = lower48.stream(stream), alaskaStream = alaska.stream(stream), hawaiiStream = hawaii.stream(stream); return { point: function(x, y) { lower48Stream.point(x, y); alaskaStream.point(x, y); hawaiiStream.point(x, y); }, sphere: function() { lower48Stream.sphere(); alaskaStream.sphere(); hawaiiStream.sphere(); }, lineStart: function() { lower48Stream.lineStart(); alaskaStream.lineStart(); hawaiiStream.lineStart(); }, lineEnd: function() { lower48Stream.lineEnd(); alaskaStream.lineEnd(); hawaiiStream.lineEnd(); }, polygonStart: function() { lower48Stream.polygonStart(); alaskaStream.polygonStart(); hawaiiStream.polygonStart(); }, polygonEnd: function() { lower48Stream.polygonEnd(); alaskaStream.polygonEnd(); hawaiiStream.polygonEnd(); } }; }; albersUsa.precision = function(_) { if (!arguments.length) return lower48.precision(); lower48.precision(_); alaska.precision(_); hawaii.precision(_); return albersUsa; }; albersUsa.scale = function(_) { if (!arguments.length) return lower48.scale(); lower48.scale(_); alaska.scale(_ * .35); hawaii.scale(_); return albersUsa.translate(lower48.translate()); }; albersUsa.translate = function(_) { if (!arguments.length) return lower48.translate(); var k = lower48.scale(), x = +_[0], y = +_[1]; lower48Point = lower48.translate(_).clipExtent([ [ x - .455 * k, y - .238 * k ], [ x + .455 * k, y + .238 * k ] ]).stream(pointStream).point; alaskaPoint = alaska.translate([ x - .307 * k, y + .201 * k ]).clipExtent([ [ x - .425 * k + ε, y + .12 * k + ε ], [ x - .214 * k - ε, y + .234 * k - ε ] ]).stream(pointStream).point; hawaiiPoint = hawaii.translate([ x - .205 * k, y + .212 * k ]).clipExtent([ [ x - .214 * k + ε, y + .166 * k + ε ], [ x - .115 * k - ε, y + .234 * k - ε ] ]).stream(pointStream).point; return albersUsa; }; return albersUsa.scale(1070); }; var d3_geo_pathAreaSum, d3_geo_pathAreaPolygon, d3_geo_pathArea = { point: d3_noop, lineStart: d3_noop, lineEnd: d3_noop, polygonStart: function() { d3_geo_pathAreaPolygon = 0; d3_geo_pathArea.lineStart = d3_geo_pathAreaRingStart; }, polygonEnd: function() { d3_geo_pathArea.lineStart = d3_geo_pathArea.lineEnd = d3_geo_pathArea.point = d3_noop; d3_geo_pathAreaSum += abs(d3_geo_pathAreaPolygon / 2); } }; function d3_geo_pathAreaRingStart() { var x00, y00, x0, y0; d3_geo_pathArea.point = function(x, y) { d3_geo_pathArea.point = nextPoint; x00 = x0 = x, y00 = y0 = y; }; function nextPoint(x, y) { d3_geo_pathAreaPolygon += y0 * x - x0 * y; x0 = x, y0 = y; } d3_geo_pathArea.lineEnd = function() { nextPoint(x00, y00); }; } var d3_geo_pathBoundsX0, d3_geo_pathBoundsY0, d3_geo_pathBoundsX1, d3_geo_pathBoundsY1; var d3_geo_pathBounds = { point: d3_geo_pathBoundsPoint, lineStart: d3_noop, lineEnd: d3_noop, polygonStart: d3_noop, polygonEnd: d3_noop }; function d3_geo_pathBoundsPoint(x, y) { if (x < d3_geo_pathBoundsX0) d3_geo_pathBoundsX0 = x; if (x > d3_geo_pathBoundsX1) d3_geo_pathBoundsX1 = x; if (y < d3_geo_pathBoundsY0) d3_geo_pathBoundsY0 = y; if (y > d3_geo_pathBoundsY1) d3_geo_pathBoundsY1 = y; } function d3_geo_pathBuffer() { var pointCircle = d3_geo_pathBufferCircle(4.5), buffer = []; var stream = { point: point, lineStart: function() { stream.point = pointLineStart; }, lineEnd: lineEnd, polygonStart: function() { stream.lineEnd = lineEndPolygon; }, polygonEnd: function() { stream.lineEnd = lineEnd; stream.point = point; }, pointRadius: function(_) { pointCircle = d3_geo_pathBufferCircle(_); return stream; }, result: function() { if (buffer.length) { var result = buffer.join(""); buffer = []; return result; } } }; function point(x, y) { buffer.push("M", x, ",", y, pointCircle); } function pointLineStart(x, y) { buffer.push("M", x, ",", y); stream.point = pointLine; } function pointLine(x, y) { buffer.push("L", x, ",", y); } function lineEnd() { stream.point = point; } function lineEndPolygon() { buffer.push("Z"); } return stream; } function d3_geo_pathBufferCircle(radius) { return "m0," + radius + "a" + radius + "," + radius + " 0 1,1 0," + -2 * radius + "a" + radius + "," + radius + " 0 1,1 0," + 2 * radius + "z"; } var d3_geo_pathCentroid = { point: d3_geo_pathCentroidPoint, lineStart: d3_geo_pathCentroidLineStart, lineEnd: d3_geo_pathCentroidLineEnd, polygonStart: function() { d3_geo_pathCentroid.lineStart = d3_geo_pathCentroidRingStart; }, polygonEnd: function() { d3_geo_pathCentroid.point = d3_geo_pathCentroidPoint; d3_geo_pathCentroid.lineStart = d3_geo_pathCentroidLineStart; d3_geo_pathCentroid.lineEnd = d3_geo_pathCentroidLineEnd; } }; function d3_geo_pathCentroidPoint(x, y) { d3_geo_centroidX0 += x; d3_geo_centroidY0 += y; ++d3_geo_centroidZ0; } function d3_geo_pathCentroidLineStart() { var x0, y0; d3_geo_pathCentroid.point = function(x, y) { d3_geo_pathCentroid.point = nextPoint; d3_geo_pathCentroidPoint(x0 = x, y0 = y); }; function nextPoint(x, y) { var dx = x - x0, dy = y - y0, z = Math.sqrt(dx * dx + dy * dy); d3_geo_centroidX1 += z * (x0 + x) / 2; d3_geo_centroidY1 += z * (y0 + y) / 2; d3_geo_centroidZ1 += z; d3_geo_pathCentroidPoint(x0 = x, y0 = y); } } function d3_geo_pathCentroidLineEnd() { d3_geo_pathCentroid.point = d3_geo_pathCentroidPoint; } function d3_geo_pathCentroidRingStart() { var x00, y00, x0, y0; d3_geo_pathCentroid.point = function(x, y) { d3_geo_pathCentroid.point = nextPoint; d3_geo_pathCentroidPoint(x00 = x0 = x, y00 = y0 = y); }; function nextPoint(x, y) { var dx = x - x0, dy = y - y0, z = Math.sqrt(dx * dx + dy * dy); d3_geo_centroidX1 += z * (x0 + x) / 2; d3_geo_centroidY1 += z * (y0 + y) / 2; d3_geo_centroidZ1 += z; z = y0 * x - x0 * y; d3_geo_centroidX2 += z * (x0 + x); d3_geo_centroidY2 += z * (y0 + y); d3_geo_centroidZ2 += z * 3; d3_geo_pathCentroidPoint(x0 = x, y0 = y); } d3_geo_pathCentroid.lineEnd = function() { nextPoint(x00, y00); }; } function d3_geo_pathContext(context) { var pointRadius = 4.5; var stream = { point: point, lineStart: function() { stream.point = pointLineStart; }, lineEnd: lineEnd, polygonStart: function() { stream.lineEnd = lineEndPolygon; }, polygonEnd: function() { stream.lineEnd = lineEnd; stream.point = point; }, pointRadius: function(_) { pointRadius = _; return stream; }, result: d3_noop }; function point(x, y) { context.moveTo(x + pointRadius, y); context.arc(x, y, pointRadius, 0, τ); } function pointLineStart(x, y) { context.moveTo(x, y); stream.point = pointLine; } function pointLine(x, y) { context.lineTo(x, y); } function lineEnd() { stream.point = point; } function lineEndPolygon() { context.closePath(); } return stream; } function d3_geo_resample(project) { var δ2 = .5, cosMinDistance = Math.cos(30 * d3_radians), maxDepth = 16; function resample(stream) { return (maxDepth ? resampleRecursive : resampleNone)(stream); } function resampleNone(stream) { return d3_geo_transformPoint(stream, function(x, y) { x = project(x, y); stream.point(x[0], x[1]); }); } function resampleRecursive(stream) { var λ00, φ00, x00, y00, a00, b00, c00, λ0, x0, y0, a0, b0, c0; var resample = { point: point, lineStart: lineStart, lineEnd: lineEnd, polygonStart: function() { stream.polygonStart(); resample.lineStart = ringStart; }, polygonEnd: function() { stream.polygonEnd(); resample.lineStart = lineStart; } }; function point(x, y) { x = project(x, y); stream.point(x[0], x[1]); } function lineStart() { x0 = NaN; resample.point = linePoint; stream.lineStart(); } function linePoint(λ, φ) { var c = d3_geo_cartesian([ λ, φ ]), p = project(λ, φ); resampleLineTo(x0, y0, λ0, a0, b0, c0, x0 = p[0], y0 = p[1], λ0 = λ, a0 = c[0], b0 = c[1], c0 = c[2], maxDepth, stream); stream.point(x0, y0); } function lineEnd() { resample.point = point; stream.lineEnd(); } function ringStart() { lineStart(); resample.point = ringPoint; resample.lineEnd = ringEnd; } function ringPoint(λ, φ) { linePoint(λ00 = λ, φ00 = φ), x00 = x0, y00 = y0, a00 = a0, b00 = b0, c00 = c0; resample.point = linePoint; } function ringEnd() { resampleLineTo(x0, y0, λ0, a0, b0, c0, x00, y00, λ00, a00, b00, c00, maxDepth, stream); resample.lineEnd = lineEnd; lineEnd(); } return resample; } function resampleLineTo(x0, y0, λ0, a0, b0, c0, x1, y1, λ1, a1, b1, c1, depth, stream) { var dx = x1 - x0, dy = y1 - y0, d2 = dx * dx + dy * dy; if (d2 > 4 * δ2 && depth--) { var a = a0 + a1, b = b0 + b1, c = c0 + c1, m = Math.sqrt(a * a + b * b + c * c), φ2 = Math.asin(c /= m), λ2 = abs(abs(c) - 1) < ε || abs(λ0 - λ1) < ε ? (λ0 + λ1) / 2 : Math.atan2(b, a), p = project(λ2, φ2), x2 = p[0], y2 = p[1], dx2 = x2 - x0, dy2 = y2 - y0, dz = dy * dx2 - dx * dy2; if (dz * dz / d2 > δ2 || abs((dx * dx2 + dy * dy2) / d2 - .5) > .3 || a0 * a1 + b0 * b1 + c0 * c1 < cosMinDistance) { resampleLineTo(x0, y0, λ0, a0, b0, c0, x2, y2, λ2, a /= m, b /= m, c, depth, stream); stream.point(x2, y2); resampleLineTo(x2, y2, λ2, a, b, c, x1, y1, λ1, a1, b1, c1, depth, stream); } } } resample.precision = function(_) { if (!arguments.length) return Math.sqrt(δ2); maxDepth = (δ2 = _ * _) > 0 && 16; return resample; }; return resample; } d3.geo.path = function() { var pointRadius = 4.5, projection, context, projectStream, contextStream, cacheStream; function path(object) { if (object) { if (typeof pointRadius === "function") contextStream.pointRadius(+pointRadius.apply(this, arguments)); if (!cacheStream || !cacheStream.valid) cacheStream = projectStream(contextStream); d3.geo.stream(object, cacheStream); } return contextStream.result(); } path.area = function(object) { d3_geo_pathAreaSum = 0; d3.geo.stream(object, projectStream(d3_geo_pathArea)); return d3_geo_pathAreaSum; }; path.centroid = function(object) { d3_geo_centroidX0 = d3_geo_centroidY0 = d3_geo_centroidZ0 = d3_geo_centroidX1 = d3_geo_centroidY1 = d3_geo_centroidZ1 = d3_geo_centroidX2 = d3_geo_centroidY2 = d3_geo_centroidZ2 = 0; d3.geo.stream(object, projectStream(d3_geo_pathCentroid)); return d3_geo_centroidZ2 ? [ d3_geo_centroidX2 / d3_geo_centroidZ2, d3_geo_centroidY2 / d3_geo_centroidZ2 ] : d3_geo_centroidZ1 ? [ d3_geo_centroidX1 / d3_geo_centroidZ1, d3_geo_centroidY1 / d3_geo_centroidZ1 ] : d3_geo_centroidZ0 ? [ d3_geo_centroidX0 / d3_geo_centroidZ0, d3_geo_centroidY0 / d3_geo_centroidZ0 ] : [ NaN, NaN ]; }; path.bounds = function(object) { d3_geo_pathBoundsX1 = d3_geo_pathBoundsY1 = -(d3_geo_pathBoundsX0 = d3_geo_pathBoundsY0 = Infinity); d3.geo.stream(object, projectStream(d3_geo_pathBounds)); return [ [ d3_geo_pathBoundsX0, d3_geo_pathBoundsY0 ], [ d3_geo_pathBoundsX1, d3_geo_pathBoundsY1 ] ]; }; path.projection = function(_) { if (!arguments.length) return projection; projectStream = (projection = _) ? _.stream || d3_geo_pathProjectStream(_) : d3_identity; return reset(); }; path.context = function(_) { if (!arguments.length) return context; contextStream = (context = _) == null ? new d3_geo_pathBuffer() : new d3_geo_pathContext(_); if (typeof pointRadius !== "function") contextStream.pointRadius(pointRadius); return reset(); }; path.pointRadius = function(_) { if (!arguments.length) return pointRadius; pointRadius = typeof _ === "function" ? _ : (contextStream.pointRadius(+_), +_); return path; }; function reset() { cacheStream = null; return path; } return path.projection(d3.geo.albersUsa()).context(null); }; function d3_geo_pathProjectStream(project) { var resample = d3_geo_resample(function(x, y) { return project([ x * d3_degrees, y * d3_degrees ]); }); return function(stream) { return d3_geo_projectionRadians(resample(stream)); }; } d3.geo.transform = function(methods) { return { stream: function(stream) { var transform = new d3_geo_transform(stream); for (var k in methods) transform[k] = methods[k]; return transform; } }; }; function d3_geo_transform(stream) { this.stream = stream; } d3_geo_transform.prototype = { point: function(x, y) { this.stream.point(x, y); }, sphere: function() { this.stream.sphere(); }, lineStart: function() { this.stream.lineStart(); }, lineEnd: function() { this.stream.lineEnd(); }, polygonStart: function() { this.stream.polygonStart(); }, polygonEnd: function() { this.stream.polygonEnd(); } }; function d3_geo_transformPoint(stream, point) { return { point: point, sphere: function() { stream.sphere(); }, lineStart: function() { stream.lineStart(); }, lineEnd: function() { stream.lineEnd(); }, polygonStart: function() { stream.polygonStart(); }, polygonEnd: function() { stream.polygonEnd(); } }; } d3.geo.projection = d3_geo_projection; d3.geo.projectionMutator = d3_geo_projectionMutator; function d3_geo_projection(project) { return d3_geo_projectionMutator(function() { return project; })(); } function d3_geo_projectionMutator(projectAt) { var project, rotate, projectRotate, projectResample = d3_geo_resample(function(x, y) { x = project(x, y); return [ x[0] * k + δx, δy - x[1] * k ]; }), k = 150, x = 480, y = 250, λ = 0, φ = 0, δλ = 0, δφ = 0, δγ = 0, δx, δy, preclip = d3_geo_clipAntimeridian, postclip = d3_identity, clipAngle = null, clipExtent = null, stream; function projection(point) { point = projectRotate(point[0] * d3_radians, point[1] * d3_radians); return [ point[0] * k + δx, δy - point[1] * k ]; } function invert(point) { point = projectRotate.invert((point[0] - δx) / k, (δy - point[1]) / k); return point && [ point[0] * d3_degrees, point[1] * d3_degrees ]; } projection.stream = function(output) { if (stream) stream.valid = false; stream = d3_geo_projectionRadians(preclip(rotate, projectResample(postclip(output)))); stream.valid = true; return stream; }; projection.clipAngle = function(_) { if (!arguments.length) return clipAngle; preclip = _ == null ? (clipAngle = _, d3_geo_clipAntimeridian) : d3_geo_clipCircle((clipAngle = +_) * d3_radians); return invalidate(); }; projection.clipExtent = function(_) { if (!arguments.length) return clipExtent; clipExtent = _; postclip = _ ? d3_geo_clipExtent(_[0][0], _[0][1], _[1][0], _[1][1]) : d3_identity; return invalidate(); }; projection.scale = function(_) { if (!arguments.length) return k; k = +_; return reset(); }; projection.translate = function(_) { if (!arguments.length) return [ x, y ]; x = +_[0]; y = +_[1]; return reset(); }; projection.center = function(_) { if (!arguments.length) return [ λ * d3_degrees, φ * d3_degrees ]; λ = _[0] % 360 * d3_radians; φ = _[1] % 360 * d3_radians; return reset(); }; projection.rotate = function(_) { if (!arguments.length) return [ δλ * d3_degrees, δφ * d3_degrees, δγ * d3_degrees ]; δλ = _[0] % 360 * d3_radians; δφ = _[1] % 360 * d3_radians; δγ = _.length > 2 ? _[2] % 360 * d3_radians : 0; return reset(); }; d3.rebind(projection, projectResample, "precision"); function reset() { projectRotate = d3_geo_compose(rotate = d3_geo_rotation(δλ, δφ, δγ), project); var center = project(λ, φ); δx = x - center[0] * k; δy = y + center[1] * k; return invalidate(); } function invalidate() { if (stream) stream.valid = false, stream = null; return projection; } return function() { project = projectAt.apply(this, arguments); projection.invert = project.invert && invert; return reset(); }; } function d3_geo_projectionRadians(stream) { return d3_geo_transformPoint(stream, function(x, y) { stream.point(x * d3_radians, y * d3_radians); }); } function d3_geo_equirectangular(λ, φ) { return [ λ, φ ]; } (d3.geo.equirectangular = function() { return d3_geo_projection(d3_geo_equirectangular); }).raw = d3_geo_equirectangular.invert = d3_geo_equirectangular; d3.geo.rotation = function(rotate) { rotate = d3_geo_rotation(rotate[0] % 360 * d3_radians, rotate[1] * d3_radians, rotate.length > 2 ? rotate[2] * d3_radians : 0); function forward(coordinates) { coordinates = rotate(coordinates[0] * d3_radians, coordinates[1] * d3_radians); return coordinates[0] *= d3_degrees, coordinates[1] *= d3_degrees, coordinates; } forward.invert = function(coordinates) { coordinates = rotate.invert(coordinates[0] * d3_radians, coordinates[1] * d3_radians); return coordinates[0] *= d3_degrees, coordinates[1] *= d3_degrees, coordinates; }; return forward; }; function d3_geo_identityRotation(λ, φ) { return [ λ > π ? λ - τ : λ < -π ? λ + τ : λ, φ ]; } d3_geo_identityRotation.invert = d3_geo_equirectangular; function d3_geo_rotation(δλ, δφ, δγ) { return δλ ? δφ || δγ ? d3_geo_compose(d3_geo_rotationλ(δλ), d3_geo_rotationφγ(δφ, δγ)) : d3_geo_rotationλ(δλ) : δφ || δγ ? d3_geo_rotationφγ(δφ, δγ) : d3_geo_identityRotation; } function d3_geo_forwardRotationλ(δλ) { return function(λ, φ) { return λ += δλ, [ λ > π ? λ - τ : λ < -π ? λ + τ : λ, φ ]; }; } function d3_geo_rotationλ(δλ) { var rotation = d3_geo_forwardRotationλ(δλ); rotation.invert = d3_geo_forwardRotationλ(-δλ); return rotation; } function d3_geo_rotationφγ(δφ, δγ) { var cosδφ = Math.cos(δφ), sinδφ = Math.sin(δφ), cosδγ = Math.cos(δγ), sinδγ = Math.sin(δγ); function rotation(λ, φ) { var cosφ = Math.cos(φ), x = Math.cos(λ) * cosφ, y = Math.sin(λ) * cosφ, z = Math.sin(φ), k = z * cosδφ + x * sinδφ; return [ Math.atan2(y * cosδγ - k * sinδγ, x * cosδφ - z * sinδφ), d3_asin(k * cosδγ + y * sinδγ) ]; } rotation.invert = function(λ, φ) { var cosφ = Math.cos(φ), x = Math.cos(λ) * cosφ, y = Math.sin(λ) * cosφ, z = Math.sin(φ), k = z * cosδγ - y * sinδγ; return [ Math.atan2(y * cosδγ + z * sinδγ, x * cosδφ + k * sinδφ), d3_asin(k * cosδφ - x * sinδφ) ]; }; return rotation; } d3.geo.circle = function() { var origin = [ 0, 0 ], angle, precision = 6, interpolate; function circle() { var center = typeof origin === "function" ? origin.apply(this, arguments) : origin, rotate = d3_geo_rotation(-center[0] * d3_radians, -center[1] * d3_radians, 0).invert, ring = []; interpolate(null, null, 1, { point: function(x, y) { ring.push(x = rotate(x, y)); x[0] *= d3_degrees, x[1] *= d3_degrees; } }); return { type: "Polygon", coordinates: [ ring ] }; } circle.origin = function(x) { if (!arguments.length) return origin; origin = x; return circle; }; circle.angle = function(x) { if (!arguments.length) return angle; interpolate = d3_geo_circleInterpolate((angle = +x) * d3_radians, precision * d3_radians); return circle; }; circle.precision = function(_) { if (!arguments.length) return precision; interpolate = d3_geo_circleInterpolate(angle * d3_radians, (precision = +_) * d3_radians); return circle; }; return circle.angle(90); }; function d3_geo_circleInterpolate(radius, precision) { var cr = Math.cos(radius), sr = Math.sin(radius); return function(from, to, direction, listener) { var step = direction * precision; if (from != null) { from = d3_geo_circleAngle(cr, from); to = d3_geo_circleAngle(cr, to); if (direction > 0 ? from < to : from > to) from += direction * τ; } else { from = radius + direction * τ; to = radius - .5 * step; } for (var point, t = from; direction > 0 ? t > to : t < to; t -= step) { listener.point((point = d3_geo_spherical([ cr, -sr * Math.cos(t), -sr * Math.sin(t) ]))[0], point[1]); } }; } function d3_geo_circleAngle(cr, point) { var a = d3_geo_cartesian(point); a[0] -= cr; d3_geo_cartesianNormalize(a); var angle = d3_acos(-a[1]); return ((-a[2] < 0 ? -angle : angle) + 2 * Math.PI - ε) % (2 * Math.PI); } d3.geo.distance = function(a, b) { var Δλ = (b[0] - a[0]) * d3_radians, φ0 = a[1] * d3_radians, φ1 = b[1] * d3_radians, sinΔλ = Math.sin(Δλ), cosΔλ = Math.cos(Δλ), sinφ0 = Math.sin(φ0), cosφ0 = Math.cos(φ0), sinφ1 = Math.sin(φ1), cosφ1 = Math.cos(φ1), t; return Math.atan2(Math.sqrt((t = cosφ1 * sinΔλ) * t + (t = cosφ0 * sinφ1 - sinφ0 * cosφ1 * cosΔλ) * t), sinφ0 * sinφ1 + cosφ0 * cosφ1 * cosΔλ); }; d3.geo.graticule = function() { var x1, x0, X1, X0, y1, y0, Y1, Y0, dx = 10, dy = dx, DX = 90, DY = 360, x, y, X, Y, precision = 2.5; function graticule() { return { type: "MultiLineString", coordinates: lines() }; } function lines() { return d3.range(Math.ceil(X0 / DX) * DX, X1, DX).map(X).concat(d3.range(Math.ceil(Y0 / DY) * DY, Y1, DY).map(Y)).concat(d3.range(Math.ceil(x0 / dx) * dx, x1, dx).filter(function(x) { return abs(x % DX) > ε; }).map(x)).concat(d3.range(Math.ceil(y0 / dy) * dy, y1, dy).filter(function(y) { return abs(y % DY) > ε; }).map(y)); } graticule.lines = function() { return lines().map(function(coordinates) { return { type: "LineString", coordinates: coordinates }; }); }; graticule.outline = function() { return { type: "Polygon", coordinates: [ X(X0).concat(Y(Y1).slice(1), X(X1).reverse().slice(1), Y(Y0).reverse().slice(1)) ] }; }; graticule.extent = function(_) { if (!arguments.length) return graticule.minorExtent(); return graticule.majorExtent(_).minorExtent(_); }; graticule.majorExtent = function(_) { if (!arguments.length) return [ [ X0, Y0 ], [ X1, Y1 ] ]; X0 = +_[0][0], X1 = +_[1][0]; Y0 = +_[0][1], Y1 = +_[1][1]; if (X0 > X1) _ = X0, X0 = X1, X1 = _; if (Y0 > Y1) _ = Y0, Y0 = Y1, Y1 = _; return graticule.precision(precision); }; graticule.minorExtent = function(_) { if (!arguments.length) return [ [ x0, y0 ], [ x1, y1 ] ]; x0 = +_[0][0], x1 = +_[1][0]; y0 = +_[0][1], y1 = +_[1][1]; if (x0 > x1) _ = x0, x0 = x1, x1 = _; if (y0 > y1) _ = y0, y0 = y1, y1 = _; return graticule.precision(precision); }; graticule.step = function(_) { if (!arguments.length) return graticule.minorStep(); return graticule.majorStep(_).minorStep(_); }; graticule.majorStep = function(_) { if (!arguments.length) return [ DX, DY ]; DX = +_[0], DY = +_[1]; return graticule; }; graticule.minorStep = function(_) { if (!arguments.length) return [ dx, dy ]; dx = +_[0], dy = +_[1]; return graticule; }; graticule.precision = function(_) { if (!arguments.length) return precision; precision = +_; x = d3_geo_graticuleX(y0, y1, 90); y = d3_geo_graticuleY(x0, x1, precision); X = d3_geo_graticuleX(Y0, Y1, 90); Y = d3_geo_graticuleY(X0, X1, precision); return graticule; }; return graticule.majorExtent([ [ -180, -90 + ε ], [ 180, 90 - ε ] ]).minorExtent([ [ -180, -80 - ε ], [ 180, 80 + ε ] ]); }; function d3_geo_graticuleX(y0, y1, dy) { var y = d3.range(y0, y1 - ε, dy).concat(y1); return function(x) { return y.map(function(y) { return [ x, y ]; }); }; } function d3_geo_graticuleY(x0, x1, dx) { var x = d3.range(x0, x1 - ε, dx).concat(x1); return function(y) { return x.map(function(x) { return [ x, y ]; }); }; } function d3_source(d) { return d.source; } function d3_target(d) { return d.target; } d3.geo.greatArc = function() { var source = d3_source, source_, target = d3_target, target_; function greatArc() { return { type: "LineString", coordinates: [ source_ || source.apply(this, arguments), target_ || target.apply(this, arguments) ] }; } greatArc.distance = function() { return d3.geo.distance(source_ || source.apply(this, arguments), target_ || target.apply(this, arguments)); }; greatArc.source = function(_) { if (!arguments.length) return source; source = _, source_ = typeof _ === "function" ? null : _; return greatArc; }; greatArc.target = function(_) { if (!arguments.length) return target; target = _, target_ = typeof _ === "function" ? null : _; return greatArc; }; greatArc.precision = function() { return arguments.length ? greatArc : 0; }; return greatArc; }; d3.geo.interpolate = function(source, target) { return d3_geo_interpolate(source[0] * d3_radians, source[1] * d3_radians, target[0] * d3_radians, target[1] * d3_radians); }; function d3_geo_interpolate(x0, y0, x1, y1) { var cy0 = Math.cos(y0), sy0 = Math.sin(y0), cy1 = Math.cos(y1), sy1 = Math.sin(y1), kx0 = cy0 * Math.cos(x0), ky0 = cy0 * Math.sin(x0), kx1 = cy1 * Math.cos(x1), ky1 = cy1 * Math.sin(x1), d = 2 * Math.asin(Math.sqrt(d3_haversin(y1 - y0) + cy0 * cy1 * d3_haversin(x1 - x0))), k = 1 / Math.sin(d); var interpolate = d ? function(t) { var B = Math.sin(t *= d) * k, A = Math.sin(d - t) * k, x = A * kx0 + B * kx1, y = A * ky0 + B * ky1, z = A * sy0 + B * sy1; return [ Math.atan2(y, x) * d3_degrees, Math.atan2(z, Math.sqrt(x * x + y * y)) * d3_degrees ]; } : function() { return [ x0 * d3_degrees, y0 * d3_degrees ]; }; interpolate.distance = d; return interpolate; } d3.geo.length = function(object) { d3_geo_lengthSum = 0; d3.geo.stream(object, d3_geo_length); return d3_geo_lengthSum; }; var d3_geo_lengthSum; var d3_geo_length = { sphere: d3_noop, point: d3_noop, lineStart: d3_geo_lengthLineStart, lineEnd: d3_noop, polygonStart: d3_noop, polygonEnd: d3_noop }; function d3_geo_lengthLineStart() { var λ0, sinφ0, cosφ0; d3_geo_length.point = function(λ, φ) { λ0 = λ * d3_radians, sinφ0 = Math.sin(φ *= d3_radians), cosφ0 = Math.cos(φ); d3_geo_length.point = nextPoint; }; d3_geo_length.lineEnd = function() { d3_geo_length.point = d3_geo_length.lineEnd = d3_noop; }; function nextPoint(λ, φ) { var sinφ = Math.sin(φ *= d3_radians), cosφ = Math.cos(φ), t = abs((λ *= d3_radians) - λ0), cosΔλ = Math.cos(t); d3_geo_lengthSum += Math.atan2(Math.sqrt((t = cosφ * Math.sin(t)) * t + (t = cosφ0 * sinφ - sinφ0 * cosφ * cosΔλ) * t), sinφ0 * sinφ + cosφ0 * cosφ * cosΔλ); λ0 = λ, sinφ0 = sinφ, cosφ0 = cosφ; } } function d3_geo_azimuthal(scale, angle) { function azimuthal(λ, φ) { var cosλ = Math.cos(λ), cosφ = Math.cos(φ), k = scale(cosλ * cosφ); return [ k * cosφ * Math.sin(λ), k * Math.sin(φ) ]; } azimuthal.invert = function(x, y) { var ρ = Math.sqrt(x * x + y * y), c = angle(ρ), sinc = Math.sin(c), cosc = Math.cos(c); return [ Math.atan2(x * sinc, ρ * cosc), Math.asin(ρ && y * sinc / ρ) ]; }; return azimuthal; } var d3_geo_azimuthalEqualArea = d3_geo_azimuthal(function(cosλcosφ) { return Math.sqrt(2 / (1 + cosλcosφ)); }, function(ρ) { return 2 * Math.asin(ρ / 2); }); (d3.geo.azimuthalEqualArea = function() { return d3_geo_projection(d3_geo_azimuthalEqualArea); }).raw = d3_geo_azimuthalEqualArea; var d3_geo_azimuthalEquidistant = d3_geo_azimuthal(function(cosλcosφ) { var c = Math.acos(cosλcosφ); return c && c / Math.sin(c); }, d3_identity); (d3.geo.azimuthalEquidistant = function() { return d3_geo_projection(d3_geo_azimuthalEquidistant); }).raw = d3_geo_azimuthalEquidistant; function d3_geo_conicConformal(φ0, φ1) { var cosφ0 = Math.cos(φ0), t = function(φ) { return Math.tan(π / 4 + φ / 2); }, n = φ0 === φ1 ? Math.sin(φ0) : Math.log(cosφ0 / Math.cos(φ1)) / Math.log(t(φ1) / t(φ0)), F = cosφ0 * Math.pow(t(φ0), n) / n; if (!n) return d3_geo_mercator; function forward(λ, φ) { if (F > 0) { if (φ < -halfπ + ε) φ = -halfπ + ε; } else { if (φ > halfπ - ε) φ = halfπ - ε; } var ρ = F / Math.pow(t(φ), n); return [ ρ * Math.sin(n * λ), F - ρ * Math.cos(n * λ) ]; } forward.invert = function(x, y) { var ρ0_y = F - y, ρ = d3_sgn(n) * Math.sqrt(x * x + ρ0_y * ρ0_y); return [ Math.atan2(x, ρ0_y) / n, 2 * Math.atan(Math.pow(F / ρ, 1 / n)) - halfπ ]; }; return forward; } (d3.geo.conicConformal = function() { return d3_geo_conic(d3_geo_conicConformal); }).raw = d3_geo_conicConformal; function d3_geo_conicEquidistant(φ0, φ1) { var cosφ0 = Math.cos(φ0), n = φ0 === φ1 ? Math.sin(φ0) : (cosφ0 - Math.cos(φ1)) / (φ1 - φ0), G = cosφ0 / n + φ0; if (abs(n) < ε) return d3_geo_equirectangular; function forward(λ, φ) { var ρ = G - φ; return [ ρ * Math.sin(n * λ), G - ρ * Math.cos(n * λ) ]; } forward.invert = function(x, y) { var ρ0_y = G - y; return [ Math.atan2(x, ρ0_y) / n, G - d3_sgn(n) * Math.sqrt(x * x + ρ0_y * ρ0_y) ]; }; return forward; } (d3.geo.conicEquidistant = function() { return d3_geo_conic(d3_geo_conicEquidistant); }).raw = d3_geo_conicEquidistant; var d3_geo_gnomonic = d3_geo_azimuthal(function(cosλcosφ) { return 1 / cosλcosφ; }, Math.atan); (d3.geo.gnomonic = function() { return d3_geo_projection(d3_geo_gnomonic); }).raw = d3_geo_gnomonic; function d3_geo_mercator(λ, φ) { return [ λ, Math.log(Math.tan(π / 4 + φ / 2)) ]; } d3_geo_mercator.invert = function(x, y) { return [ x, 2 * Math.atan(Math.exp(y)) - halfπ ]; }; function d3_geo_mercatorProjection(project) { var m = d3_geo_projection(project), scale = m.scale, translate = m.translate, clipExtent = m.clipExtent, clipAuto; m.scale = function() { var v = scale.apply(m, arguments); return v === m ? clipAuto ? m.clipExtent(null) : m : v; }; m.translate = function() { var v = translate.apply(m, arguments); return v === m ? clipAuto ? m.clipExtent(null) : m : v; }; m.clipExtent = function(_) { var v = clipExtent.apply(m, arguments); if (v === m) { if (clipAuto = _ == null) { var k = π * scale(), t = translate(); clipExtent([ [ t[0] - k, t[1] - k ], [ t[0] + k, t[1] + k ] ]); } } else if (clipAuto) { v = null; } return v; }; return m.clipExtent(null); } (d3.geo.mercator = function() { return d3_geo_mercatorProjection(d3_geo_mercator); }).raw = d3_geo_mercator; var d3_geo_orthographic = d3_geo_azimuthal(function() { return 1; }, Math.asin); (d3.geo.orthographic = function() { return d3_geo_projection(d3_geo_orthographic); }).raw = d3_geo_orthographic; var d3_geo_stereographic = d3_geo_azimuthal(function(cosλcosφ) { return 1 / (1 + cosλcosφ); }, function(ρ) { return 2 * Math.atan(ρ); }); (d3.geo.stereographic = function() { return d3_geo_projection(d3_geo_stereographic); }).raw = d3_geo_stereographic; function d3_geo_transverseMercator(λ, φ) { return [ Math.log(Math.tan(π / 4 + φ / 2)), -λ ]; } d3_geo_transverseMercator.invert = function(x, y) { return [ -y, 2 * Math.atan(Math.exp(x)) - halfπ ]; }; (d3.geo.transverseMercator = function() { var projection = d3_geo_mercatorProjection(d3_geo_transverseMercator), center = projection.center, rotate = projection.rotate; projection.center = function(_) { return _ ? center([ -_[1], _[0] ]) : (_ = center(), [ _[1], -_[0] ]); }; projection.rotate = function(_) { return _ ? rotate([ _[0], _[1], _.length > 2 ? _[2] + 90 : 90 ]) : (_ = rotate(), [ _[0], _[1], _[2] - 90 ]); }; return rotate([ 0, 0, 90 ]); }).raw = d3_geo_transverseMercator; d3.geom = {}; function d3_geom_pointX(d) { return d[0]; } function d3_geom_pointY(d) { return d[1]; } d3.geom.hull = function(vertices) { var x = d3_geom_pointX, y = d3_geom_pointY; if (arguments.length) return hull(vertices); function hull(data) { if (data.length < 3) return []; var fx = d3_functor(x), fy = d3_functor(y), i, n = data.length, points = [], flippedPoints = []; for (i = 0; i < n; i++) { points.push([ +fx.call(this, data[i], i), +fy.call(this, data[i], i), i ]); } points.sort(d3_geom_hullOrder); for (i = 0; i < n; i++) flippedPoints.push([ points[i][0], -points[i][1] ]); var upper = d3_geom_hullUpper(points), lower = d3_geom_hullUpper(flippedPoints); var skipLeft = lower[0] === upper[0], skipRight = lower[lower.length - 1] === upper[upper.length - 1], polygon = []; for (i = upper.length - 1; i >= 0; --i) polygon.push(data[points[upper[i]][2]]); for (i = +skipLeft; i < lower.length - skipRight; ++i) polygon.push(data[points[lower[i]][2]]); return polygon; } hull.x = function(_) { return arguments.length ? (x = _, hull) : x; }; hull.y = function(_) { return arguments.length ? (y = _, hull) : y; }; return hull; }; function d3_geom_hullUpper(points) { var n = points.length, hull = [ 0, 1 ], hs = 2; for (var i = 2; i < n; i++) { while (hs > 1 && d3_cross2d(points[hull[hs - 2]], points[hull[hs - 1]], points[i]) <= 0) --hs; hull[hs++] = i; } return hull.slice(0, hs); } function d3_geom_hullOrder(a, b) { return a[0] - b[0] || a[1] - b[1]; } d3.geom.polygon = function(coordinates) { d3_subclass(coordinates, d3_geom_polygonPrototype); return coordinates; }; var d3_geom_polygonPrototype = d3.geom.polygon.prototype = []; d3_geom_polygonPrototype.area = function() { var i = -1, n = this.length, a, b = this[n - 1], area = 0; while (++i < n) { a = b; b = this[i]; area += a[1] * b[0] - a[0] * b[1]; } return area * .5; }; d3_geom_polygonPrototype.centroid = function(k) { var i = -1, n = this.length, x = 0, y = 0, a, b = this[n - 1], c; if (!arguments.length) k = -1 / (6 * this.area()); while (++i < n) { a = b; b = this[i]; c = a[0] * b[1] - b[0] * a[1]; x += (a[0] + b[0]) * c; y += (a[1] + b[1]) * c; } return [ x * k, y * k ]; }; d3_geom_polygonPrototype.clip = function(subject) { var input, closed = d3_geom_polygonClosed(subject), i = -1, n = this.length - d3_geom_polygonClosed(this), j, m, a = this[n - 1], b, c, d; while (++i < n) { input = subject.slice(); subject.length = 0; b = this[i]; c = input[(m = input.length - closed) - 1]; j = -1; while (++j < m) { d = input[j]; if (d3_geom_polygonInside(d, a, b)) { if (!d3_geom_polygonInside(c, a, b)) { subject.push(d3_geom_polygonIntersect(c, d, a, b)); } subject.push(d); } else if (d3_geom_polygonInside(c, a, b)) { subject.push(d3_geom_polygonIntersect(c, d, a, b)); } c = d; } if (closed) subject.push(subject[0]); a = b; } return subject; }; function d3_geom_polygonInside(p, a, b) { return (b[0] - a[0]) * (p[1] - a[1]) < (b[1] - a[1]) * (p[0] - a[0]); } function d3_geom_polygonIntersect(c, d, a, b) { var x1 = c[0], x3 = a[0], x21 = d[0] - x1, x43 = b[0] - x3, y1 = c[1], y3 = a[1], y21 = d[1] - y1, y43 = b[1] - y3, ua = (x43 * (y1 - y3) - y43 * (x1 - x3)) / (y43 * x21 - x43 * y21); return [ x1 + ua * x21, y1 + ua * y21 ]; } function d3_geom_polygonClosed(coordinates) { var a = coordinates[0], b = coordinates[coordinates.length - 1]; return !(a[0] - b[0] || a[1] - b[1]); } var d3_geom_voronoiEdges, d3_geom_voronoiCells, d3_geom_voronoiBeaches, d3_geom_voronoiBeachPool = [], d3_geom_voronoiFirstCircle, d3_geom_voronoiCircles, d3_geom_voronoiCirclePool = []; function d3_geom_voronoiBeach() { d3_geom_voronoiRedBlackNode(this); this.edge = this.site = this.circle = null; } function d3_geom_voronoiCreateBeach(site) { var beach = d3_geom_voronoiBeachPool.pop() || new d3_geom_voronoiBeach(); beach.site = site; return beach; } function d3_geom_voronoiDetachBeach(beach) { d3_geom_voronoiDetachCircle(beach); d3_geom_voronoiBeaches.remove(beach); d3_geom_voronoiBeachPool.push(beach); d3_geom_voronoiRedBlackNode(beach); } function d3_geom_voronoiRemoveBeach(beach) { var circle = beach.circle, x = circle.x, y = circle.cy, vertex = { x: x, y: y }, previous = beach.P, next = beach.N, disappearing = [ beach ]; d3_geom_voronoiDetachBeach(beach); var lArc = previous; while (lArc.circle && abs(x - lArc.circle.x) < ε && abs(y - lArc.circle.cy) < ε) { previous = lArc.P; disappearing.unshift(lArc); d3_geom_voronoiDetachBeach(lArc); lArc = previous; } disappearing.unshift(lArc); d3_geom_voronoiDetachCircle(lArc); var rArc = next; while (rArc.circle && abs(x - rArc.circle.x) < ε && abs(y - rArc.circle.cy) < ε) { next = rArc.N; disappearing.push(rArc); d3_geom_voronoiDetachBeach(rArc); rArc = next; } disappearing.push(rArc); d3_geom_voronoiDetachCircle(rArc); var nArcs = disappearing.length, iArc; for (iArc = 1; iArc < nArcs; ++iArc) { rArc = disappearing[iArc]; lArc = disappearing[iArc - 1]; d3_geom_voronoiSetEdgeEnd(rArc.edge, lArc.site, rArc.site, vertex); } lArc = disappearing[0]; rArc = disappearing[nArcs - 1]; rArc.edge = d3_geom_voronoiCreateEdge(lArc.site, rArc.site, null, vertex); d3_geom_voronoiAttachCircle(lArc); d3_geom_voronoiAttachCircle(rArc); } function d3_geom_voronoiAddBeach(site) { var x = site.x, directrix = site.y, lArc, rArc, dxl, dxr, node = d3_geom_voronoiBeaches._; while (node) { dxl = d3_geom_voronoiLeftBreakPoint(node, directrix) - x; if (dxl > ε) node = node.L; else { dxr = x - d3_geom_voronoiRightBreakPoint(node, directrix); if (dxr > ε) { if (!node.R) { lArc = node; break; } node = node.R; } else { if (dxl > -ε) { lArc = node.P; rArc = node; } else if (dxr > -ε) { lArc = node; rArc = node.N; } else { lArc = rArc = node; } break; } } } var newArc = d3_geom_voronoiCreateBeach(site); d3_geom_voronoiBeaches.insert(lArc, newArc); if (!lArc && !rArc) return; if (lArc === rArc) { d3_geom_voronoiDetachCircle(lArc); rArc = d3_geom_voronoiCreateBeach(lArc.site); d3_geom_voronoiBeaches.insert(newArc, rArc); newArc.edge = rArc.edge = d3_geom_voronoiCreateEdge(lArc.site, newArc.site); d3_geom_voronoiAttachCircle(lArc); d3_geom_voronoiAttachCircle(rArc); return; } if (!rArc) { newArc.edge = d3_geom_voronoiCreateEdge(lArc.site, newArc.site); return; } d3_geom_voronoiDetachCircle(lArc); d3_geom_voronoiDetachCircle(rArc); var lSite = lArc.site, ax = lSite.x, ay = lSite.y, bx = site.x - ax, by = site.y - ay, rSite = rArc.site, cx = rSite.x - ax, cy = rSite.y - ay, d = 2 * (bx * cy - by * cx), hb = bx * bx + by * by, hc = cx * cx + cy * cy, vertex = { x: (cy * hb - by * hc) / d + ax, y: (bx * hc - cx * hb) / d + ay }; d3_geom_voronoiSetEdgeEnd(rArc.edge, lSite, rSite, vertex); newArc.edge = d3_geom_voronoiCreateEdge(lSite, site, null, vertex); rArc.edge = d3_geom_voronoiCreateEdge(site, rSite, null, vertex); d3_geom_voronoiAttachCircle(lArc); d3_geom_voronoiAttachCircle(rArc); } function d3_geom_voronoiLeftBreakPoint(arc, directrix) { var site = arc.site, rfocx = site.x, rfocy = site.y, pby2 = rfocy - directrix; if (!pby2) return rfocx; var lArc = arc.P; if (!lArc) return -Infinity; site = lArc.site; var lfocx = site.x, lfocy = site.y, plby2 = lfocy - directrix; if (!plby2) return lfocx; var hl = lfocx - rfocx, aby2 = 1 / pby2 - 1 / plby2, b = hl / plby2; if (aby2) return (-b + Math.sqrt(b * b - 2 * aby2 * (hl * hl / (-2 * plby2) - lfocy + plby2 / 2 + rfocy - pby2 / 2))) / aby2 + rfocx; return (rfocx + lfocx) / 2; } function d3_geom_voronoiRightBreakPoint(arc, directrix) { var rArc = arc.N; if (rArc) return d3_geom_voronoiLeftBreakPoint(rArc, directrix); var site = arc.site; return site.y === directrix ? site.x : Infinity; } function d3_geom_voronoiCell(site) { this.site = site; this.edges = []; } d3_geom_voronoiCell.prototype.prepare = function() { var halfEdges = this.edges, iHalfEdge = halfEdges.length, edge; while (iHalfEdge--) { edge = halfEdges[iHalfEdge].edge; if (!edge.b || !edge.a) halfEdges.splice(iHalfEdge, 1); } halfEdges.sort(d3_geom_voronoiHalfEdgeOrder); return halfEdges.length; }; function d3_geom_voronoiCloseCells(extent) { var x0 = extent[0][0], x1 = extent[1][0], y0 = extent[0][1], y1 = extent[1][1], x2, y2, x3, y3, cells = d3_geom_voronoiCells, iCell = cells.length, cell, iHalfEdge, halfEdges, nHalfEdges, start, end; while (iCell--) { cell = cells[iCell]; if (!cell || !cell.prepare()) continue; halfEdges = cell.edges; nHalfEdges = halfEdges.length; iHalfEdge = 0; while (iHalfEdge < nHalfEdges) { end = halfEdges[iHalfEdge].end(), x3 = end.x, y3 = end.y; start = halfEdges[++iHalfEdge % nHalfEdges].start(), x2 = start.x, y2 = start.y; if (abs(x3 - x2) > ε || abs(y3 - y2) > ε) { halfEdges.splice(iHalfEdge, 0, new d3_geom_voronoiHalfEdge(d3_geom_voronoiCreateBorderEdge(cell.site, end, abs(x3 - x0) < ε && y1 - y3 > ε ? { x: x0, y: abs(x2 - x0) < ε ? y2 : y1 } : abs(y3 - y1) < ε && x1 - x3 > ε ? { x: abs(y2 - y1) < ε ? x2 : x1, y: y1 } : abs(x3 - x1) < ε && y3 - y0 > ε ? { x: x1, y: abs(x2 - x1) < ε ? y2 : y0 } : abs(y3 - y0) < ε && x3 - x0 > ε ? { x: abs(y2 - y0) < ε ? x2 : x0, y: y0 } : null), cell.site, null)); ++nHalfEdges; } } } } function d3_geom_voronoiHalfEdgeOrder(a, b) { return b.angle - a.angle; } function d3_geom_voronoiCircle() { d3_geom_voronoiRedBlackNode(this); this.x = this.y = this.arc = this.site = this.cy = null; } function d3_geom_voronoiAttachCircle(arc) { var lArc = arc.P, rArc = arc.N; if (!lArc || !rArc) return; var lSite = lArc.site, cSite = arc.site, rSite = rArc.site; if (lSite === rSite) return; var bx = cSite.x, by = cSite.y, ax = lSite.x - bx, ay = lSite.y - by, cx = rSite.x - bx, cy = rSite.y - by; var d = 2 * (ax * cy - ay * cx); if (d >= -ε2) return; var ha = ax * ax + ay * ay, hc = cx * cx + cy * cy, x = (cy * ha - ay * hc) / d, y = (ax * hc - cx * ha) / d, cy = y + by; var circle = d3_geom_voronoiCirclePool.pop() || new d3_geom_voronoiCircle(); circle.arc = arc; circle.site = cSite; circle.x = x + bx; circle.y = cy + Math.sqrt(x * x + y * y); circle.cy = cy; arc.circle = circle; var before = null, node = d3_geom_voronoiCircles._; while (node) { if (circle.y < node.y || circle.y === node.y && circle.x <= node.x) { if (node.L) node = node.L; else { before = node.P; break; } } else { if (node.R) node = node.R; else { before = node; break; } } } d3_geom_voronoiCircles.insert(before, circle); if (!before) d3_geom_voronoiFirstCircle = circle; } function d3_geom_voronoiDetachCircle(arc) { var circle = arc.circle; if (circle) { if (!circle.P) d3_geom_voronoiFirstCircle = circle.N; d3_geom_voronoiCircles.remove(circle); d3_geom_voronoiCirclePool.push(circle); d3_geom_voronoiRedBlackNode(circle); arc.circle = null; } } function d3_geom_voronoiClipEdges(extent) { var edges = d3_geom_voronoiEdges, clip = d3_geom_clipLine(extent[0][0], extent[0][1], extent[1][0], extent[1][1]), i = edges.length, e; while (i--) { e = edges[i]; if (!d3_geom_voronoiConnectEdge(e, extent) || !clip(e) || abs(e.a.x - e.b.x) < ε && abs(e.a.y - e.b.y) < ε) { e.a = e.b = null; edges.splice(i, 1); } } } function d3_geom_voronoiConnectEdge(edge, extent) { var vb = edge.b; if (vb) return true; var va = edge.a, x0 = extent[0][0], x1 = extent[1][0], y0 = extent[0][1], y1 = extent[1][1], lSite = edge.l, rSite = edge.r, lx = lSite.x, ly = lSite.y, rx = rSite.x, ry = rSite.y, fx = (lx + rx) / 2, fy = (ly + ry) / 2, fm, fb; if (ry === ly) { if (fx < x0 || fx >= x1) return; if (lx > rx) { if (!va) va = { x: fx, y: y0 }; else if (va.y >= y1) return; vb = { x: fx, y: y1 }; } else { if (!va) va = { x: fx, y: y1 }; else if (va.y < y0) return; vb = { x: fx, y: y0 }; } } else { fm = (lx - rx) / (ry - ly); fb = fy - fm * fx; if (fm < -1 || fm > 1) { if (lx > rx) { if (!va) va = { x: (y0 - fb) / fm, y: y0 }; else if (va.y >= y1) return; vb = { x: (y1 - fb) / fm, y: y1 }; } else { if (!va) va = { x: (y1 - fb) / fm, y: y1 }; else if (va.y < y0) return; vb = { x: (y0 - fb) / fm, y: y0 }; } } else { if (ly < ry) { if (!va) va = { x: x0, y: fm * x0 + fb }; else if (va.x >= x1) return; vb = { x: x1, y: fm * x1 + fb }; } else { if (!va) va = { x: x1, y: fm * x1 + fb }; else if (va.x < x0) return; vb = { x: x0, y: fm * x0 + fb }; } } } edge.a = va; edge.b = vb; return true; } function d3_geom_voronoiEdge(lSite, rSite) { this.l = lSite; this.r = rSite; this.a = this.b = null; } function d3_geom_voronoiCreateEdge(lSite, rSite, va, vb) { var edge = new d3_geom_voronoiEdge(lSite, rSite); d3_geom_voronoiEdges.push(edge); if (va) d3_geom_voronoiSetEdgeEnd(edge, lSite, rSite, va); if (vb) d3_geom_voronoiSetEdgeEnd(edge, rSite, lSite, vb); d3_geom_voronoiCells[lSite.i].edges.push(new d3_geom_voronoiHalfEdge(edge, lSite, rSite)); d3_geom_voronoiCells[rSite.i].edges.push(new d3_geom_voronoiHalfEdge(edge, rSite, lSite)); return edge; } function d3_geom_voronoiCreateBorderEdge(lSite, va, vb) { var edge = new d3_geom_voronoiEdge(lSite, null); edge.a = va; edge.b = vb; d3_geom_voronoiEdges.push(edge); return edge; } function d3_geom_voronoiSetEdgeEnd(edge, lSite, rSite, vertex) { if (!edge.a && !edge.b) { edge.a = vertex; edge.l = lSite; edge.r = rSite; } else if (edge.l === rSite) { edge.b = vertex; } else { edge.a = vertex; } } function d3_geom_voronoiHalfEdge(edge, lSite, rSite) { var va = edge.a, vb = edge.b; this.edge = edge; this.site = lSite; this.angle = rSite ? Math.atan2(rSite.y - lSite.y, rSite.x - lSite.x) : edge.l === lSite ? Math.atan2(vb.x - va.x, va.y - vb.y) : Math.atan2(va.x - vb.x, vb.y - va.y); } d3_geom_voronoiHalfEdge.prototype = { start: function() { return this.edge.l === this.site ? this.edge.a : this.edge.b; }, end: function() { return this.edge.l === this.site ? this.edge.b : this.edge.a; } }; function d3_geom_voronoiRedBlackTree() { this._ = null; } function d3_geom_voronoiRedBlackNode(node) { node.U = node.C = node.L = node.R = node.P = node.N = null; } d3_geom_voronoiRedBlackTree.prototype = { insert: function(after, node) { var parent, grandpa, uncle; if (after) { node.P = after; node.N = after.N; if (after.N) after.N.P = node; after.N = node; if (after.R) { after = after.R; while (after.L) after = after.L; after.L = node; } else { after.R = node; } parent = after; } else if (this._) { after = d3_geom_voronoiRedBlackFirst(this._); node.P = null; node.N = after; after.P = after.L = node; parent = after; } else { node.P = node.N = null; this._ = node; parent = null; } node.L = node.R = null; node.U = parent; node.C = true; after = node; while (parent && parent.C) { grandpa = parent.U; if (parent === grandpa.L) { uncle = grandpa.R; if (uncle && uncle.C) { parent.C = uncle.C = false; grandpa.C = true; after = grandpa; } else { if (after === parent.R) { d3_geom_voronoiRedBlackRotateLeft(this, parent); after = parent; parent = after.U; } parent.C = false; grandpa.C = true; d3_geom_voronoiRedBlackRotateRight(this, grandpa); } } else { uncle = grandpa.L; if (uncle && uncle.C) { parent.C = uncle.C = false; grandpa.C = true; after = grandpa; } else { if (after === parent.L) { d3_geom_voronoiRedBlackRotateRight(this, parent); after = parent; parent = after.U; } parent.C = false; grandpa.C = true; d3_geom_voronoiRedBlackRotateLeft(this, grandpa); } } parent = after.U; } this._.C = false; }, remove: function(node) { if (node.N) node.N.P = node.P; if (node.P) node.P.N = node.N; node.N = node.P = null; var parent = node.U, sibling, left = node.L, right = node.R, next, red; if (!left) next = right; else if (!right) next = left; else next = d3_geom_voronoiRedBlackFirst(right); if (parent) { if (parent.L === node) parent.L = next; else parent.R = next; } else { this._ = next; } if (left && right) { red = next.C; next.C = node.C; next.L = left; left.U = next; if (next !== right) { parent = next.U; next.U = node.U; node = next.R; parent.L = node; next.R = right; right.U = next; } else { next.U = parent; parent = next; node = next.R; } } else { red = node.C; node = next; } if (node) node.U = parent; if (red) return; if (node && node.C) { node.C = false; return; } do { if (node === this._) break; if (node === parent.L) { sibling = parent.R; if (sibling.C) { sibling.C = false; parent.C = true; d3_geom_voronoiRedBlackRotateLeft(this, parent); sibling = parent.R; } if (sibling.L && sibling.L.C || sibling.R && sibling.R.C) { if (!sibling.R || !sibling.R.C) { sibling.L.C = false; sibling.C = true; d3_geom_voronoiRedBlackRotateRight(this, sibling); sibling = parent.R; } sibling.C = parent.C; parent.C = sibling.R.C = false; d3_geom_voronoiRedBlackRotateLeft(this, parent); node = this._; break; } } else { sibling = parent.L; if (sibling.C) { sibling.C = false; parent.C = true; d3_geom_voronoiRedBlackRotateRight(this, parent); sibling = parent.L; } if (sibling.L && sibling.L.C || sibling.R && sibling.R.C) { if (!sibling.L || !sibling.L.C) { sibling.R.C = false; sibling.C = true; d3_geom_voronoiRedBlackRotateLeft(this, sibling); sibling = parent.L; } sibling.C = parent.C; parent.C = sibling.L.C = false; d3_geom_voronoiRedBlackRotateRight(this, parent); node = this._; break; } } sibling.C = true; node = parent; parent = parent.U; } while (!node.C); if (node) node.C = false; } }; function d3_geom_voronoiRedBlackRotateLeft(tree, node) { var p = node, q = node.R, parent = p.U; if (parent) { if (parent.L === p) parent.L = q; else parent.R = q; } else { tree._ = q; } q.U = parent; p.U = q; p.R = q.L; if (p.R) p.R.U = p; q.L = p; } function d3_geom_voronoiRedBlackRotateRight(tree, node) { var p = node, q = node.L, parent = p.U; if (parent) { if (parent.L === p) parent.L = q; else parent.R = q; } else { tree._ = q; } q.U = parent; p.U = q; p.L = q.R; if (p.L) p.L.U = p; q.R = p; } function d3_geom_voronoiRedBlackFirst(node) { while (node.L) node = node.L; return node; } function d3_geom_voronoi(sites, bbox) { var site = sites.sort(d3_geom_voronoiVertexOrder).pop(), x0, y0, circle; d3_geom_voronoiEdges = []; d3_geom_voronoiCells = new Array(sites.length); d3_geom_voronoiBeaches = new d3_geom_voronoiRedBlackTree(); d3_geom_voronoiCircles = new d3_geom_voronoiRedBlackTree(); while (true) { circle = d3_geom_voronoiFirstCircle; if (site && (!circle || site.y < circle.y || site.y === circle.y && site.x < circle.x)) { if (site.x !== x0 || site.y !== y0) { d3_geom_voronoiCells[site.i] = new d3_geom_voronoiCell(site); d3_geom_voronoiAddBeach(site); x0 = site.x, y0 = site.y; } site = sites.pop(); } else if (circle) { d3_geom_voronoiRemoveBeach(circle.arc); } else { break; } } if (bbox) d3_geom_voronoiClipEdges(bbox), d3_geom_voronoiCloseCells(bbox); var diagram = { cells: d3_geom_voronoiCells, edges: d3_geom_voronoiEdges }; d3_geom_voronoiBeaches = d3_geom_voronoiCircles = d3_geom_voronoiEdges = d3_geom_voronoiCells = null; return diagram; } function d3_geom_voronoiVertexOrder(a, b) { return b.y - a.y || b.x - a.x; } d3.geom.voronoi = function(points) { var x = d3_geom_pointX, y = d3_geom_pointY, fx = x, fy = y, clipExtent = d3_geom_voronoiClipExtent; if (points) return voronoi(points); function voronoi(data) { var polygons = new Array(data.length), x0 = clipExtent[0][0], y0 = clipExtent[0][1], x1 = clipExtent[1][0], y1 = clipExtent[1][1]; d3_geom_voronoi(sites(data), clipExtent).cells.forEach(function(cell, i) { var edges = cell.edges, site = cell.site, polygon = polygons[i] = edges.length ? edges.map(function(e) { var s = e.start(); return [ s.x, s.y ]; }) : site.x >= x0 && site.x <= x1 && site.y >= y0 && site.y <= y1 ? [ [ x0, y1 ], [ x1, y1 ], [ x1, y0 ], [ x0, y0 ] ] : []; polygon.point = data[i]; }); return polygons; } function sites(data) { return data.map(function(d, i) { return { x: Math.round(fx(d, i) / ε) * ε, y: Math.round(fy(d, i) / ε) * ε, i: i }; }); } voronoi.links = function(data) { return d3_geom_voronoi(sites(data)).edges.filter(function(edge) { return edge.l && edge.r; }).map(function(edge) { return { source: data[edge.l.i], target: data[edge.r.i] }; }); }; voronoi.triangles = function(data) { var triangles = []; d3_geom_voronoi(sites(data)).cells.forEach(function(cell, i) { var site = cell.site, edges = cell.edges.sort(d3_geom_voronoiHalfEdgeOrder), j = -1, m = edges.length, e0, s0, e1 = edges[m - 1].edge, s1 = e1.l === site ? e1.r : e1.l; while (++j < m) { e0 = e1; s0 = s1; e1 = edges[j].edge; s1 = e1.l === site ? e1.r : e1.l; if (i < s0.i && i < s1.i && d3_geom_voronoiTriangleArea(site, s0, s1) < 0) { triangles.push([ data[i], data[s0.i], data[s1.i] ]); } } }); return triangles; }; voronoi.x = function(_) { return arguments.length ? (fx = d3_functor(x = _), voronoi) : x; }; voronoi.y = function(_) { return arguments.length ? (fy = d3_functor(y = _), voronoi) : y; }; voronoi.clipExtent = function(_) { if (!arguments.length) return clipExtent === d3_geom_voronoiClipExtent ? null : clipExtent; clipExtent = _ == null ? d3_geom_voronoiClipExtent : _; return voronoi; }; voronoi.size = function(_) { if (!arguments.length) return clipExtent === d3_geom_voronoiClipExtent ? null : clipExtent && clipExtent[1]; return voronoi.clipExtent(_ && [ [ 0, 0 ], _ ]); }; return voronoi; }; var d3_geom_voronoiClipExtent = [ [ -1e6, -1e6 ], [ 1e6, 1e6 ] ]; function d3_geom_voronoiTriangleArea(a, b, c) { return (a.x - c.x) * (b.y - a.y) - (a.x - b.x) * (c.y - a.y); } d3.geom.delaunay = function(vertices) { return d3.geom.voronoi().triangles(vertices); }; d3.geom.quadtree = function(points, x1, y1, x2, y2) { var x = d3_geom_pointX, y = d3_geom_pointY, compat; if (compat = arguments.length) { x = d3_geom_quadtreeCompatX; y = d3_geom_quadtreeCompatY; if (compat === 3) { y2 = y1; x2 = x1; y1 = x1 = 0; } return quadtree(points); } function quadtree(data) { var d, fx = d3_functor(x), fy = d3_functor(y), xs, ys, i, n, x1_, y1_, x2_, y2_; if (x1 != null) { x1_ = x1, y1_ = y1, x2_ = x2, y2_ = y2; } else { x2_ = y2_ = -(x1_ = y1_ = Infinity); xs = [], ys = []; n = data.length; if (compat) for (i = 0; i < n; ++i) { d = data[i]; if (d.x < x1_) x1_ = d.x; if (d.y < y1_) y1_ = d.y; if (d.x > x2_) x2_ = d.x; if (d.y > y2_) y2_ = d.y; xs.push(d.x); ys.push(d.y); } else for (i = 0; i < n; ++i) { var x_ = +fx(d = data[i], i), y_ = +fy(d, i); if (x_ < x1_) x1_ = x_; if (y_ < y1_) y1_ = y_; if (x_ > x2_) x2_ = x_; if (y_ > y2_) y2_ = y_; xs.push(x_); ys.push(y_); } } var dx = x2_ - x1_, dy = y2_ - y1_; if (dx > dy) y2_ = y1_ + dx; else x2_ = x1_ + dy; function insert(n, d, x, y, x1, y1, x2, y2) { if (isNaN(x) || isNaN(y)) return; if (n.leaf) { var nx = n.x, ny = n.y; if (nx != null) { if (abs(nx - x) + abs(ny - y) < .01) { insertChild(n, d, x, y, x1, y1, x2, y2); } else { var nPoint = n.point; n.x = n.y = n.point = null; insertChild(n, nPoint, nx, ny, x1, y1, x2, y2); insertChild(n, d, x, y, x1, y1, x2, y2); } } else { n.x = x, n.y = y, n.point = d; } } else { insertChild(n, d, x, y, x1, y1, x2, y2); } } function insertChild(n, d, x, y, x1, y1, x2, y2) { var xm = (x1 + x2) * .5, ym = (y1 + y2) * .5, right = x >= xm, below = y >= ym, i = below << 1 | right; n.leaf = false; n = n.nodes[i] || (n.nodes[i] = d3_geom_quadtreeNode()); if (right) x1 = xm; else x2 = xm; if (below) y1 = ym; else y2 = ym; insert(n, d, x, y, x1, y1, x2, y2); } var root = d3_geom_quadtreeNode(); root.add = function(d) { insert(root, d, +fx(d, ++i), +fy(d, i), x1_, y1_, x2_, y2_); }; root.visit = function(f) { d3_geom_quadtreeVisit(f, root, x1_, y1_, x2_, y2_); }; root.find = function(point) { return d3_geom_quadtreeFind(root, point[0], point[1], x1_, y1_, x2_, y2_); }; i = -1; if (x1 == null) { while (++i < n) { insert(root, data[i], xs[i], ys[i], x1_, y1_, x2_, y2_); } --i; } else data.forEach(root.add); xs = ys = data = d = null; return root; } quadtree.x = function(_) { return arguments.length ? (x = _, quadtree) : x; }; quadtree.y = function(_) { return arguments.length ? (y = _, quadtree) : y; }; quadtree.extent = function(_) { if (!arguments.length) return x1 == null ? null : [ [ x1, y1 ], [ x2, y2 ] ]; if (_ == null) x1 = y1 = x2 = y2 = null; else x1 = +_[0][0], y1 = +_[0][1], x2 = +_[1][0], y2 = +_[1][1]; return quadtree; }; quadtree.size = function(_) { if (!arguments.length) return x1 == null ? null : [ x2 - x1, y2 - y1 ]; if (_ == null) x1 = y1 = x2 = y2 = null; else x1 = y1 = 0, x2 = +_[0], y2 = +_[1]; return quadtree; }; return quadtree; }; function d3_geom_quadtreeCompatX(d) { return d.x; } function d3_geom_quadtreeCompatY(d) { return d.y; } function d3_geom_quadtreeNode() { return { leaf: true, nodes: [], point: null, x: null, y: null }; } function d3_geom_quadtreeVisit(f, node, x1, y1, x2, y2) { if (!f(node, x1, y1, x2, y2)) { var sx = (x1 + x2) * .5, sy = (y1 + y2) * .5, children = node.nodes; if (children[0]) d3_geom_quadtreeVisit(f, children[0], x1, y1, sx, sy); if (children[1]) d3_geom_quadtreeVisit(f, children[1], sx, y1, x2, sy); if (children[2]) d3_geom_quadtreeVisit(f, children[2], x1, sy, sx, y2); if (children[3]) d3_geom_quadtreeVisit(f, children[3], sx, sy, x2, y2); } } function d3_geom_quadtreeFind(root, x, y, x0, y0, x3, y3) { var minDistance2 = Infinity, closestPoint; (function find(node, x1, y1, x2, y2) { if (x1 > x3 || y1 > y3 || x2 < x0 || y2 < y0) return; if (point = node.point) { var point, dx = x - node.x, dy = y - node.y, distance2 = dx * dx + dy * dy; if (distance2 < minDistance2) { var distance = Math.sqrt(minDistance2 = distance2); x0 = x - distance, y0 = y - distance; x3 = x + distance, y3 = y + distance; closestPoint = point; } } var children = node.nodes, xm = (x1 + x2) * .5, ym = (y1 + y2) * .5, right = x >= xm, below = y >= ym; for (var i = below << 1 | right, j = i + 4; i < j; ++i) { if (node = children[i & 3]) switch (i & 3) { case 0: find(node, x1, y1, xm, ym); break; case 1: find(node, xm, y1, x2, ym); break; case 2: find(node, x1, ym, xm, y2); break; case 3: find(node, xm, ym, x2, y2); break; } } })(root, x0, y0, x3, y3); return closestPoint; } d3.interpolateRgb = d3_interpolateRgb; function d3_interpolateRgb(a, b) { a = d3.rgb(a); b = d3.rgb(b); var ar = a.r, ag = a.g, ab = a.b, br = b.r - ar, bg = b.g - ag, bb = b.b - ab; return function(t) { return "#" + d3_rgb_hex(Math.round(ar + br * t)) + d3_rgb_hex(Math.round(ag + bg * t)) + d3_rgb_hex(Math.round(ab + bb * t)); }; } d3.interpolateObject = d3_interpolateObject; function d3_interpolateObject(a, b) { var i = {}, c = {}, k; for (k in a) { if (k in b) { i[k] = d3_interpolate(a[k], b[k]); } else { c[k] = a[k]; } } for (k in b) { if (!(k in a)) { c[k] = b[k]; } } return function(t) { for (k in i) c[k] = i[k](t); return c; }; } d3.interpolateNumber = d3_interpolateNumber; function d3_interpolateNumber(a, b) { a = +a, b = +b; return function(t) { return a * (1 - t) + b * t; }; } d3.interpolateString = d3_interpolateString; function d3_interpolateString(a, b) { var bi = d3_interpolate_numberA.lastIndex = d3_interpolate_numberB.lastIndex = 0, am, bm, bs, i = -1, s = [], q = []; a = a + "", b = b + ""; while ((am = d3_interpolate_numberA.exec(a)) && (bm = d3_interpolate_numberB.exec(b))) { if ((bs = bm.index) > bi) { bs = b.slice(bi, bs); if (s[i]) s[i] += bs; else s[++i] = bs; } if ((am = am[0]) === (bm = bm[0])) { if (s[i]) s[i] += bm; else s[++i] = bm; } else { s[++i] = null; q.push({ i: i, x: d3_interpolateNumber(am, bm) }); } bi = d3_interpolate_numberB.lastIndex; } if (bi < b.length) { bs = b.slice(bi); if (s[i]) s[i] += bs; else s[++i] = bs; } return s.length < 2 ? q[0] ? (b = q[0].x, function(t) { return b(t) + ""; }) : function() { return b; } : (b = q.length, function(t) { for (var i = 0, o; i < b; ++i) s[(o = q[i]).i] = o.x(t); return s.join(""); }); } var d3_interpolate_numberA = /[-+]?(?:\d+\.?\d*|\.?\d+)(?:[eE][-+]?\d+)?/g, d3_interpolate_numberB = new RegExp(d3_interpolate_numberA.source, "g"); d3.interpolate = d3_interpolate; function d3_interpolate(a, b) { var i = d3.interpolators.length, f; while (--i >= 0 && !(f = d3.interpolators[i](a, b))) ; return f; } d3.interpolators = [ function(a, b) { var t = typeof b; return (t === "string" ? d3_rgb_names.has(b.toLowerCase()) || /^(#|rgb\(|hsl\()/i.test(b) ? d3_interpolateRgb : d3_interpolateString : b instanceof d3_color ? d3_interpolateRgb : Array.isArray(b) ? d3_interpolateArray : t === "object" && isNaN(b) ? d3_interpolateObject : d3_interpolateNumber)(a, b); } ]; d3.interpolateArray = d3_interpolateArray; function d3_interpolateArray(a, b) { var x = [], c = [], na = a.length, nb = b.length, n0 = Math.min(a.length, b.length), i; for (i = 0; i < n0; ++i) x.push(d3_interpolate(a[i], b[i])); for (;i < na; ++i) c[i] = a[i]; for (;i < nb; ++i) c[i] = b[i]; return function(t) { for (i = 0; i < n0; ++i) c[i] = x[i](t); return c; }; } var d3_ease_default = function() { return d3_identity; }; var d3_ease = d3.map({ linear: d3_ease_default, poly: d3_ease_poly, quad: function() { return d3_ease_quad; }, cubic: function() { return d3_ease_cubic; }, sin: function() { return d3_ease_sin; }, exp: function() { return d3_ease_exp; }, circle: function() { return d3_ease_circle; }, elastic: d3_ease_elastic, back: d3_ease_back, bounce: function() { return d3_ease_bounce; } }); var d3_ease_mode = d3.map({ "in": d3_identity, out: d3_ease_reverse, "in-out": d3_ease_reflect, "out-in": function(f) { return d3_ease_reflect(d3_ease_reverse(f)); } }); d3.ease = function(name) { var i = name.indexOf("-"), t = i >= 0 ? name.slice(0, i) : name, m = i >= 0 ? name.slice(i + 1) : "in"; t = d3_ease.get(t) || d3_ease_default; m = d3_ease_mode.get(m) || d3_identity; return d3_ease_clamp(m(t.apply(null, d3_arraySlice.call(arguments, 1)))); }; function d3_ease_clamp(f) { return function(t) { return t <= 0 ? 0 : t >= 1 ? 1 : f(t); }; } function d3_ease_reverse(f) { return function(t) { return 1 - f(1 - t); }; } function d3_ease_reflect(f) { return function(t) { return .5 * (t < .5 ? f(2 * t) : 2 - f(2 - 2 * t)); }; } function d3_ease_quad(t) { return t * t; } function d3_ease_cubic(t) { return t * t * t; } function d3_ease_cubicInOut(t) { if (t <= 0) return 0; if (t >= 1) return 1; var t2 = t * t, t3 = t2 * t; return 4 * (t < .5 ? t3 : 3 * (t - t2) + t3 - .75); } function d3_ease_poly(e) { return function(t) { return Math.pow(t, e); }; } function d3_ease_sin(t) { return 1 - Math.cos(t * halfπ); } function d3_ease_exp(t) { return Math.pow(2, 10 * (t - 1)); } function d3_ease_circle(t) { return 1 - Math.sqrt(1 - t * t); } function d3_ease_elastic(a, p) { var s; if (arguments.length < 2) p = .45; if (arguments.length) s = p / τ * Math.asin(1 / a); else a = 1, s = p / 4; return function(t) { return 1 + a * Math.pow(2, -10 * t) * Math.sin((t - s) * τ / p); }; } function d3_ease_back(s) { if (!s) s = 1.70158; return function(t) { return t * t * ((s + 1) * t - s); }; } function d3_ease_bounce(t) { return t < 1 / 2.75 ? 7.5625 * t * t : t < 2 / 2.75 ? 7.5625 * (t -= 1.5 / 2.75) * t + .75 : t < 2.5 / 2.75 ? 7.5625 * (t -= 2.25 / 2.75) * t + .9375 : 7.5625 * (t -= 2.625 / 2.75) * t + .984375; } d3.interpolateHcl = d3_interpolateHcl; function d3_interpolateHcl(a, b) { a = d3.hcl(a); b = d3.hcl(b); var ah = a.h, ac = a.c, al = a.l, bh = b.h - ah, bc = b.c - ac, bl = b.l - al; if (isNaN(bc)) bc = 0, ac = isNaN(ac) ? b.c : ac; if (isNaN(bh)) bh = 0, ah = isNaN(ah) ? b.h : ah; else if (bh > 180) bh -= 360; else if (bh < -180) bh += 360; return function(t) { return d3_hcl_lab(ah + bh * t, ac + bc * t, al + bl * t) + ""; }; } d3.interpolateHsl = d3_interpolateHsl; function d3_interpolateHsl(a, b) { a = d3.hsl(a); b = d3.hsl(b); var ah = a.h, as = a.s, al = a.l, bh = b.h - ah, bs = b.s - as, bl = b.l - al; if (isNaN(bs)) bs = 0, as = isNaN(as) ? b.s : as; if (isNaN(bh)) bh = 0, ah = isNaN(ah) ? b.h : ah; else if (bh > 180) bh -= 360; else if (bh < -180) bh += 360; return function(t) { return d3_hsl_rgb(ah + bh * t, as + bs * t, al + bl * t) + ""; }; } d3.interpolateLab = d3_interpolateLab; function d3_interpolateLab(a, b) { a = d3.lab(a); b = d3.lab(b); var al = a.l, aa = a.a, ab = a.b, bl = b.l - al, ba = b.a - aa, bb = b.b - ab; return function(t) { return d3_lab_rgb(al + bl * t, aa + ba * t, ab + bb * t) + ""; }; } d3.interpolateRound = d3_interpolateRound; function d3_interpolateRound(a, b) { b -= a; return function(t) { return Math.round(a + b * t); }; } d3.transform = function(string) { var g = d3_document.createElementNS(d3.ns.prefix.svg, "g"); return (d3.transform = function(string) { if (string != null) { g.setAttribute("transform", string); var t = g.transform.baseVal.consolidate(); } return new d3_transform(t ? t.matrix : d3_transformIdentity); })(string); }; function d3_transform(m) { var r0 = [ m.a, m.b ], r1 = [ m.c, m.d ], kx = d3_transformNormalize(r0), kz = d3_transformDot(r0, r1), ky = d3_transformNormalize(d3_transformCombine(r1, r0, -kz)) || 0; if (r0[0] * r1[1] < r1[0] * r0[1]) { r0[0] *= -1; r0[1] *= -1; kx *= -1; kz *= -1; } this.rotate = (kx ? Math.atan2(r0[1], r0[0]) : Math.atan2(-r1[0], r1[1])) * d3_degrees; this.translate = [ m.e, m.f ]; this.scale = [ kx, ky ]; this.skew = ky ? Math.atan2(kz, ky) * d3_degrees : 0; } d3_transform.prototype.toString = function() { return "translate(" + this.translate + ")rotate(" + this.rotate + ")skewX(" + this.skew + ")scale(" + this.scale + ")"; }; function d3_transformDot(a, b) { return a[0] * b[0] + a[1] * b[1]; } function d3_transformNormalize(a) { var k = Math.sqrt(d3_transformDot(a, a)); if (k) { a[0] /= k; a[1] /= k; } return k; } function d3_transformCombine(a, b, k) { a[0] += k * b[0]; a[1] += k * b[1]; return a; } var d3_transformIdentity = { a: 1, b: 0, c: 0, d: 1, e: 0, f: 0 }; d3.interpolateTransform = d3_interpolateTransform; function d3_interpolateTransformPop(s) { return s.length ? s.pop() + "," : ""; } function d3_interpolateTranslate(ta, tb, s, q) { if (ta[0] !== tb[0] || ta[1] !== tb[1]) { var i = s.push("translate(", null, ",", null, ")"); q.push({ i: i - 4, x: d3_interpolateNumber(ta[0], tb[0]) }, { i: i - 2, x: d3_interpolateNumber(ta[1], tb[1]) }); } else if (tb[0] || tb[1]) { s.push("translate(" + tb + ")"); } } function d3_interpolateRotate(ra, rb, s, q) { if (ra !== rb) { if (ra - rb > 180) rb += 360; else if (rb - ra > 180) ra += 360; q.push({ i: s.push(d3_interpolateTransformPop(s) + "rotate(", null, ")") - 2, x: d3_interpolateNumber(ra, rb) }); } else if (rb) { s.push(d3_interpolateTransformPop(s) + "rotate(" + rb + ")"); } } function d3_interpolateSkew(wa, wb, s, q) { if (wa !== wb) { q.push({ i: s.push(d3_interpolateTransformPop(s) + "skewX(", null, ")") - 2, x: d3_interpolateNumber(wa, wb) }); } else if (wb) { s.push(d3_interpolateTransformPop(s) + "skewX(" + wb + ")"); } } function d3_interpolateScale(ka, kb, s, q) { if (ka[0] !== kb[0] || ka[1] !== kb[1]) { var i = s.push(d3_interpolateTransformPop(s) + "scale(", null, ",", null, ")"); q.push({ i: i - 4, x: d3_interpolateNumber(ka[0], kb[0]) }, { i: i - 2, x: d3_interpolateNumber(ka[1], kb[1]) }); } else if (kb[0] !== 1 || kb[1] !== 1) { s.push(d3_interpolateTransformPop(s) + "scale(" + kb + ")"); } } function d3_interpolateTransform(a, b) { var s = [], q = []; a = d3.transform(a), b = d3.transform(b); d3_interpolateTranslate(a.translate, b.translate, s, q); d3_interpolateRotate(a.rotate, b.rotate, s, q); d3_interpolateSkew(a.skew, b.skew, s, q); d3_interpolateScale(a.scale, b.scale, s, q); a = b = null; return function(t) { var i = -1, n = q.length, o; while (++i < n) s[(o = q[i]).i] = o.x(t); return s.join(""); }; } function d3_uninterpolateNumber(a, b) { b = (b -= a = +a) || 1 / b; return function(x) { return (x - a) / b; }; } function d3_uninterpolateClamp(a, b) { b = (b -= a = +a) || 1 / b; return function(x) { return Math.max(0, Math.min(1, (x - a) / b)); }; } d3.layout = {}; d3.layout.bundle = function() { return function(links) { var paths = [], i = -1, n = links.length; while (++i < n) paths.push(d3_layout_bundlePath(links[i])); return paths; }; }; function d3_layout_bundlePath(link) { var start = link.source, end = link.target, lca = d3_layout_bundleLeastCommonAncestor(start, end), points = [ start ]; while (start !== lca) { start = start.parent; points.push(start); } var k = points.length; while (end !== lca) { points.splice(k, 0, end); end = end.parent; } return points; } function d3_layout_bundleAncestors(node) { var ancestors = [], parent = node.parent; while (parent != null) { ancestors.push(node); node = parent; parent = parent.parent; } ancestors.push(node); return ancestors; } function d3_layout_bundleLeastCommonAncestor(a, b) { if (a === b) return a; var aNodes = d3_layout_bundleAncestors(a), bNodes = d3_layout_bundleAncestors(b), aNode = aNodes.pop(), bNode = bNodes.pop(), sharedNode = null; while (aNode === bNode) { sharedNode = aNode; aNode = aNodes.pop(); bNode = bNodes.pop(); } return sharedNode; } d3.layout.chord = function() { var chord = {}, chords, groups, matrix, n, padding = 0, sortGroups, sortSubgroups, sortChords; function relayout() { var subgroups = {}, groupSums = [], groupIndex = d3.range(n), subgroupIndex = [], k, x, x0, i, j; chords = []; groups = []; k = 0, i = -1; while (++i < n) { x = 0, j = -1; while (++j < n) { x += matrix[i][j]; } groupSums.push(x); subgroupIndex.push(d3.range(n)); k += x; } if (sortGroups) { groupIndex.sort(function(a, b) { return sortGroups(groupSums[a], groupSums[b]); }); } if (sortSubgroups) { subgroupIndex.forEach(function(d, i) { d.sort(function(a, b) { return sortSubgroups(matrix[i][a], matrix[i][b]); }); }); } k = (τ - padding * n) / k; x = 0, i = -1; while (++i < n) { x0 = x, j = -1; while (++j < n) { var di = groupIndex[i], dj = subgroupIndex[di][j], v = matrix[di][dj], a0 = x, a1 = x += v * k; subgroups[di + "-" + dj] = { index: di, subindex: dj, startAngle: a0, endAngle: a1, value: v }; } groups[di] = { index: di, startAngle: x0, endAngle: x, value: groupSums[di] }; x += padding; } i = -1; while (++i < n) { j = i - 1; while (++j < n) { var source = subgroups[i + "-" + j], target = subgroups[j + "-" + i]; if (source.value || target.value) { chords.push(source.value < target.value ? { source: target, target: source } : { source: source, target: target }); } } } if (sortChords) resort(); } function resort() { chords.sort(function(a, b) { return sortChords((a.source.value + a.target.value) / 2, (b.source.value + b.target.value) / 2); }); } chord.matrix = function(x) { if (!arguments.length) return matrix; n = (matrix = x) && matrix.length; chords = groups = null; return chord; }; chord.padding = function(x) { if (!arguments.length) return padding; padding = x; chords = groups = null; return chord; }; chord.sortGroups = function(x) { if (!arguments.length) return sortGroups; sortGroups = x; chords = groups = null; return chord; }; chord.sortSubgroups = function(x) { if (!arguments.length) return sortSubgroups; sortSubgroups = x; chords = null; return chord; }; chord.sortChords = function(x) { if (!arguments.length) return sortChords; sortChords = x; if (chords) resort(); return chord; }; chord.chords = function() { if (!chords) relayout(); return chords; }; chord.groups = function() { if (!groups) relayout(); return groups; }; return chord; }; d3.layout.force = function() { var force = {}, event = d3.dispatch("start", "tick", "end"), timer, size = [ 1, 1 ], drag, alpha, friction = .9, linkDistance = d3_layout_forceLinkDistance, linkStrength = d3_layout_forceLinkStrength, charge = -30, chargeDistance2 = d3_layout_forceChargeDistance2, gravity = .1, theta2 = .64, nodes = [], links = [], distances, strengths, charges; function repulse(node) { return function(quad, x1, _, x2) { if (quad.point !== node) { var dx = quad.cx - node.x, dy = quad.cy - node.y, dw = x2 - x1, dn = dx * dx + dy * dy; if (dw * dw / theta2 < dn) { if (dn < chargeDistance2) { var k = quad.charge / dn; node.px -= dx * k; node.py -= dy * k; } return true; } if (quad.point && dn && dn < chargeDistance2) { var k = quad.pointCharge / dn; node.px -= dx * k; node.py -= dy * k; } } return !quad.charge; }; } force.tick = function() { if ((alpha *= .99) < .005) { timer = null; event.end({ type: "end", alpha: alpha = 0 }); return true; } var n = nodes.length, m = links.length, q, i, o, s, t, l, k, x, y; for (i = 0; i < m; ++i) { o = links[i]; s = o.source; t = o.target; x = t.x - s.x; y = t.y - s.y; if (l = x * x + y * y) { l = alpha * strengths[i] * ((l = Math.sqrt(l)) - distances[i]) / l; x *= l; y *= l; t.x -= x * (k = s.weight + t.weight ? s.weight / (s.weight + t.weight) : .5); t.y -= y * k; s.x += x * (k = 1 - k); s.y += y * k; } } if (k = alpha * gravity) { x = size[0] / 2; y = size[1] / 2; i = -1; if (k) while (++i < n) { o = nodes[i]; o.x += (x - o.x) * k; o.y += (y - o.y) * k; } } if (charge) { d3_layout_forceAccumulate(q = d3.geom.quadtree(nodes), alpha, charges); i = -1; while (++i < n) { if (!(o = nodes[i]).fixed) { q.visit(repulse(o)); } } } i = -1; while (++i < n) { o = nodes[i]; if (o.fixed) { o.x = o.px; o.y = o.py; } else { o.x -= (o.px - (o.px = o.x)) * friction; o.y -= (o.py - (o.py = o.y)) * friction; } } event.tick({ type: "tick", alpha: alpha }); }; force.nodes = function(x) { if (!arguments.length) return nodes; nodes = x; return force; }; force.links = function(x) { if (!arguments.length) return links; links = x; return force; }; force.size = function(x) { if (!arguments.length) return size; size = x; return force; }; force.linkDistance = function(x) { if (!arguments.length) return linkDistance; linkDistance = typeof x === "function" ? x : +x; return force; }; force.distance = force.linkDistance; force.linkStrength = function(x) { if (!arguments.length) return linkStrength; linkStrength = typeof x === "function" ? x : +x; return force; }; force.friction = function(x) { if (!arguments.length) return friction; friction = +x; return force; }; force.charge = function(x) { if (!arguments.length) return charge; charge = typeof x === "function" ? x : +x; return force; }; force.chargeDistance = function(x) { if (!arguments.length) return Math.sqrt(chargeDistance2); chargeDistance2 = x * x; return force; }; force.gravity = function(x) { if (!arguments.length) return gravity; gravity = +x; return force; }; force.theta = function(x) { if (!arguments.length) return Math.sqrt(theta2); theta2 = x * x; return force; }; force.alpha = function(x) { if (!arguments.length) return alpha; x = +x; if (alpha) { if (x > 0) { alpha = x; } else { timer.c = null, timer.t = NaN, timer = null; event.end({ type: "end", alpha: alpha = 0 }); } } else if (x > 0) { event.start({ type: "start", alpha: alpha = x }); timer = d3_timer(force.tick); } return force; }; force.start = function() { var i, n = nodes.length, m = links.length, w = size[0], h = size[1], neighbors, o; for (i = 0; i < n; ++i) { (o = nodes[i]).index = i; o.weight = 0; } for (i = 0; i < m; ++i) { o = links[i]; if (typeof o.source == "number") o.source = nodes[o.source]; if (typeof o.target == "number") o.target = nodes[o.target]; ++o.source.weight; ++o.target.weight; } for (i = 0; i < n; ++i) { o = nodes[i]; if (isNaN(o.x)) o.x = position("x", w); if (isNaN(o.y)) o.y = position("y", h); if (isNaN(o.px)) o.px = o.x; if (isNaN(o.py)) o.py = o.y; } distances = []; if (typeof linkDistance === "function") for (i = 0; i < m; ++i) distances[i] = +linkDistance.call(this, links[i], i); else for (i = 0; i < m; ++i) distances[i] = linkDistance; strengths = []; if (typeof linkStrength === "function") for (i = 0; i < m; ++i) strengths[i] = +linkStrength.call(this, links[i], i); else for (i = 0; i < m; ++i) strengths[i] = linkStrength; charges = []; if (typeof charge === "function") for (i = 0; i < n; ++i) charges[i] = +charge.call(this, nodes[i], i); else for (i = 0; i < n; ++i) charges[i] = charge; function position(dimension, size) { if (!neighbors) { neighbors = new Array(n); for (j = 0; j < n; ++j) { neighbors[j] = []; } for (j = 0; j < m; ++j) { var o = links[j]; neighbors[o.source.index].push(o.target); neighbors[o.target.index].push(o.source); } } var candidates = neighbors[i], j = -1, l = candidates.length, x; while (++j < l) if (!isNaN(x = candidates[j][dimension])) return x; return Math.random() * size; } return force.resume(); }; force.resume = function() { return force.alpha(.1); }; force.stop = function() { return force.alpha(0); }; force.drag = function() { if (!drag) drag = d3.behavior.drag().origin(d3_identity).on("dragstart.force", d3_layout_forceDragstart).on("drag.force", dragmove).on("dragend.force", d3_layout_forceDragend); if (!arguments.length) return drag; this.on("mouseover.force", d3_layout_forceMouseover).on("mouseout.force", d3_layout_forceMouseout).call(drag); }; function dragmove(d) { d.px = d3.event.x, d.py = d3.event.y; force.resume(); } return d3.rebind(force, event, "on"); }; function d3_layout_forceDragstart(d) { d.fixed |= 2; } function d3_layout_forceDragend(d) { d.fixed &= ~6; } function d3_layout_forceMouseover(d) { d.fixed |= 4; d.px = d.x, d.py = d.y; } function d3_layout_forceMouseout(d) { d.fixed &= ~4; } function d3_layout_forceAccumulate(quad, alpha, charges) { var cx = 0, cy = 0; quad.charge = 0; if (!quad.leaf) { var nodes = quad.nodes, n = nodes.length, i = -1, c; while (++i < n) { c = nodes[i]; if (c == null) continue; d3_layout_forceAccumulate(c, alpha, charges); quad.charge += c.charge; cx += c.charge * c.cx; cy += c.charge * c.cy; } } if (quad.point) { if (!quad.leaf) { quad.point.x += Math.random() - .5; quad.point.y += Math.random() - .5; } var k = alpha * charges[quad.point.index]; quad.charge += quad.pointCharge = k; cx += k * quad.point.x; cy += k * quad.point.y; } quad.cx = cx / quad.charge; quad.cy = cy / quad.charge; } var d3_layout_forceLinkDistance = 20, d3_layout_forceLinkStrength = 1, d3_layout_forceChargeDistance2 = Infinity; d3.layout.hierarchy = function() { var sort = d3_layout_hierarchySort, children = d3_layout_hierarchyChildren, value = d3_layout_hierarchyValue; function hierarchy(root) { var stack = [ root ], nodes = [], node; root.depth = 0; while ((node = stack.pop()) != null) { nodes.push(node); if ((childs = children.call(hierarchy, node, node.depth)) && (n = childs.length)) { var n, childs, child; while (--n >= 0) { stack.push(child = childs[n]); child.parent = node; child.depth = node.depth + 1; } if (value) node.value = 0; node.children = childs; } else { if (value) node.value = +value.call(hierarchy, node, node.depth) || 0; delete node.children; } } d3_layout_hierarchyVisitAfter(root, function(node) { var childs, parent; if (sort && (childs = node.children)) childs.sort(sort); if (value && (parent = node.parent)) parent.value += node.value; }); return nodes; } hierarchy.sort = function(x) { if (!arguments.length) return sort; sort = x; return hierarchy; }; hierarchy.children = function(x) { if (!arguments.length) return children; children = x; return hierarchy; }; hierarchy.value = function(x) { if (!arguments.length) return value; value = x; return hierarchy; }; hierarchy.revalue = function(root) { if (value) { d3_layout_hierarchyVisitBefore(root, function(node) { if (node.children) node.value = 0; }); d3_layout_hierarchyVisitAfter(root, function(node) { var parent; if (!node.children) node.value = +value.call(hierarchy, node, node.depth) || 0; if (parent = node.parent) parent.value += node.value; }); } return root; }; return hierarchy; }; function d3_layout_hierarchyRebind(object, hierarchy) { d3.rebind(object, hierarchy, "sort", "children", "value"); object.nodes = object; object.links = d3_layout_hierarchyLinks; return object; } function d3_layout_hierarchyVisitBefore(node, callback) { var nodes = [ node ]; while ((node = nodes.pop()) != null) { callback(node); if ((children = node.children) && (n = children.length)) { var n, children; while (--n >= 0) nodes.push(children[n]); } } } function d3_layout_hierarchyVisitAfter(node, callback) { var nodes = [ node ], nodes2 = []; while ((node = nodes.pop()) != null) { nodes2.push(node); if ((children = node.children) && (n = children.length)) { var i = -1, n, children; while (++i < n) nodes.push(children[i]); } } while ((node = nodes2.pop()) != null) { callback(node); } } function d3_layout_hierarchyChildren(d) { return d.children; } function d3_layout_hierarchyValue(d) { return d.value; } function d3_layout_hierarchySort(a, b) { return b.value - a.value; } function d3_layout_hierarchyLinks(nodes) { return d3.merge(nodes.map(function(parent) { return (parent.children || []).map(function(child) { return { source: parent, target: child }; }); })); } d3.layout.partition = function() { var hierarchy = d3.layout.hierarchy(), size = [ 1, 1 ]; function position(node, x, dx, dy) { var children = node.children; node.x = x; node.y = node.depth * dy; node.dx = dx; node.dy = dy; if (children && (n = children.length)) { var i = -1, n, c, d; dx = node.value ? dx / node.value : 0; while (++i < n) { position(c = children[i], x, d = c.value * dx, dy); x += d; } } } function depth(node) { var children = node.children, d = 0; if (children && (n = children.length)) { var i = -1, n; while (++i < n) d = Math.max(d, depth(children[i])); } return 1 + d; } function partition(d, i) { var nodes = hierarchy.call(this, d, i); position(nodes[0], 0, size[0], size[1] / depth(nodes[0])); return nodes; } partition.size = function(x) { if (!arguments.length) return size; size = x; return partition; }; return d3_layout_hierarchyRebind(partition, hierarchy); }; d3.layout.pie = function() { var value = Number, sort = d3_layout_pieSortByValue, startAngle = 0, endAngle = τ, padAngle = 0; function pie(data) { var n = data.length, values = data.map(function(d, i) { return +value.call(pie, d, i); }), a = +(typeof startAngle === "function" ? startAngle.apply(this, arguments) : startAngle), da = (typeof endAngle === "function" ? endAngle.apply(this, arguments) : endAngle) - a, p = Math.min(Math.abs(da) / n, +(typeof padAngle === "function" ? padAngle.apply(this, arguments) : padAngle)), pa = p * (da < 0 ? -1 : 1), sum = d3.sum(values), k = sum ? (da - n * pa) / sum : 0, index = d3.range(n), arcs = [], v; if (sort != null) index.sort(sort === d3_layout_pieSortByValue ? function(i, j) { return values[j] - values[i]; } : function(i, j) { return sort(data[i], data[j]); }); index.forEach(function(i) { arcs[i] = { data: data[i], value: v = values[i], startAngle: a, endAngle: a += v * k + pa, padAngle: p }; }); return arcs; } pie.value = function(_) { if (!arguments.length) return value; value = _; return pie; }; pie.sort = function(_) { if (!arguments.length) return sort; sort = _; return pie; }; pie.startAngle = function(_) { if (!arguments.length) return startAngle; startAngle = _; return pie; }; pie.endAngle = function(_) { if (!arguments.length) return endAngle; endAngle = _; return pie; }; pie.padAngle = function(_) { if (!arguments.length) return padAngle; padAngle = _; return pie; }; return pie; }; var d3_layout_pieSortByValue = {}; d3.layout.stack = function() { var values = d3_identity, order = d3_layout_stackOrderDefault, offset = d3_layout_stackOffsetZero, out = d3_layout_stackOut, x = d3_layout_stackX, y = d3_layout_stackY; function stack(data, index) { if (!(n = data.length)) return data; var series = data.map(function(d, i) { return values.call(stack, d, i); }); var points = series.map(function(d) { return d.map(function(v, i) { return [ x.call(stack, v, i), y.call(stack, v, i) ]; }); }); var orders = order.call(stack, points, index); series = d3.permute(series, orders); points = d3.permute(points, orders); var offsets = offset.call(stack, points, index); var m = series[0].length, n, i, j, o; for (j = 0; j < m; ++j) { out.call(stack, series[0][j], o = offsets[j], points[0][j][1]); for (i = 1; i < n; ++i) { out.call(stack, series[i][j], o += points[i - 1][j][1], points[i][j][1]); } } return data; } stack.values = function(x) { if (!arguments.length) return values; values = x; return stack; }; stack.order = function(x) { if (!arguments.length) return order; order = typeof x === "function" ? x : d3_layout_stackOrders.get(x) || d3_layout_stackOrderDefault; return stack; }; stack.offset = function(x) { if (!arguments.length) return offset; offset = typeof x === "function" ? x : d3_layout_stackOffsets.get(x) || d3_layout_stackOffsetZero; return stack; }; stack.x = function(z) { if (!arguments.length) return x; x = z; return stack; }; stack.y = function(z) { if (!arguments.length) return y; y = z; return stack; }; stack.out = function(z) { if (!arguments.length) return out; out = z; return stack; }; return stack; }; function d3_layout_stackX(d) { return d.x; } function d3_layout_stackY(d) { return d.y; } function d3_layout_stackOut(d, y0, y) { d.y0 = y0; d.y = y; } var d3_layout_stackOrders = d3.map({ "inside-out": function(data) { var n = data.length, i, j, max = data.map(d3_layout_stackMaxIndex), sums = data.map(d3_layout_stackReduceSum), index = d3.range(n).sort(function(a, b) { return max[a] - max[b]; }), top = 0, bottom = 0, tops = [], bottoms = []; for (i = 0; i < n; ++i) { j = index[i]; if (top < bottom) { top += sums[j]; tops.push(j); } else { bottom += sums[j]; bottoms.push(j); } } return bottoms.reverse().concat(tops); }, reverse: function(data) { return d3.range(data.length).reverse(); }, "default": d3_layout_stackOrderDefault }); var d3_layout_stackOffsets = d3.map({ silhouette: function(data) { var n = data.length, m = data[0].length, sums = [], max = 0, i, j, o, y0 = []; for (j = 0; j < m; ++j) { for (i = 0, o = 0; i < n; i++) o += data[i][j][1]; if (o > max) max = o; sums.push(o); } for (j = 0; j < m; ++j) { y0[j] = (max - sums[j]) / 2; } return y0; }, wiggle: function(data) { var n = data.length, x = data[0], m = x.length, i, j, k, s1, s2, s3, dx, o, o0, y0 = []; y0[0] = o = o0 = 0; for (j = 1; j < m; ++j) { for (i = 0, s1 = 0; i < n; ++i) s1 += data[i][j][1]; for (i = 0, s2 = 0, dx = x[j][0] - x[j - 1][0]; i < n; ++i) { for (k = 0, s3 = (data[i][j][1] - data[i][j - 1][1]) / (2 * dx); k < i; ++k) { s3 += (data[k][j][1] - data[k][j - 1][1]) / dx; } s2 += s3 * data[i][j][1]; } y0[j] = o -= s1 ? s2 / s1 * dx : 0; if (o < o0) o0 = o; } for (j = 0; j < m; ++j) y0[j] -= o0; return y0; }, expand: function(data) { var n = data.length, m = data[0].length, k = 1 / n, i, j, o, y0 = []; for (j = 0; j < m; ++j) { for (i = 0, o = 0; i < n; i++) o += data[i][j][1]; if (o) for (i = 0; i < n; i++) data[i][j][1] /= o; else for (i = 0; i < n; i++) data[i][j][1] = k; } for (j = 0; j < m; ++j) y0[j] = 0; return y0; }, zero: d3_layout_stackOffsetZero }); function d3_layout_stackOrderDefault(data) { return d3.range(data.length); } function d3_layout_stackOffsetZero(data) { var j = -1, m = data[0].length, y0 = []; while (++j < m) y0[j] = 0; return y0; } function d3_layout_stackMaxIndex(array) { var i = 1, j = 0, v = array[0][1], k, n = array.length; for (;i < n; ++i) { if ((k = array[i][1]) > v) { j = i; v = k; } } return j; } function d3_layout_stackReduceSum(d) { return d.reduce(d3_layout_stackSum, 0); } function d3_layout_stackSum(p, d) { return p + d[1]; } d3.layout.histogram = function() { var frequency = true, valuer = Number, ranger = d3_layout_histogramRange, binner = d3_layout_histogramBinSturges; function histogram(data, i) { var bins = [], values = data.map(valuer, this), range = ranger.call(this, values, i), thresholds = binner.call(this, range, values, i), bin, i = -1, n = values.length, m = thresholds.length - 1, k = frequency ? 1 : 1 / n, x; while (++i < m) { bin = bins[i] = []; bin.dx = thresholds[i + 1] - (bin.x = thresholds[i]); bin.y = 0; } if (m > 0) { i = -1; while (++i < n) { x = values[i]; if (x >= range[0] && x <= range[1]) { bin = bins[d3.bisect(thresholds, x, 1, m) - 1]; bin.y += k; bin.push(data[i]); } } } return bins; } histogram.value = function(x) { if (!arguments.length) return valuer; valuer = x; return histogram; }; histogram.range = function(x) { if (!arguments.length) return ranger; ranger = d3_functor(x); return histogram; }; histogram.bins = function(x) { if (!arguments.length) return binner; binner = typeof x === "number" ? function(range) { return d3_layout_histogramBinFixed(range, x); } : d3_functor(x); return histogram; }; histogram.frequency = function(x) { if (!arguments.length) return frequency; frequency = !!x; return histogram; }; return histogram; }; function d3_layout_histogramBinSturges(range, values) { return d3_layout_histogramBinFixed(range, Math.ceil(Math.log(values.length) / Math.LN2 + 1)); } function d3_layout_histogramBinFixed(range, n) { var x = -1, b = +range[0], m = (range[1] - b) / n, f = []; while (++x <= n) f[x] = m * x + b; return f; } function d3_layout_histogramRange(values) { return [ d3.min(values), d3.max(values) ]; } d3.layout.pack = function() { var hierarchy = d3.layout.hierarchy().sort(d3_layout_packSort), padding = 0, size = [ 1, 1 ], radius; function pack(d, i) { var nodes = hierarchy.call(this, d, i), root = nodes[0], w = size[0], h = size[1], r = radius == null ? Math.sqrt : typeof radius === "function" ? radius : function() { return radius; }; root.x = root.y = 0; d3_layout_hierarchyVisitAfter(root, function(d) { d.r = +r(d.value); }); d3_layout_hierarchyVisitAfter(root, d3_layout_packSiblings); if (padding) { var dr = padding * (radius ? 1 : Math.max(2 * root.r / w, 2 * root.r / h)) / 2; d3_layout_hierarchyVisitAfter(root, function(d) { d.r += dr; }); d3_layout_hierarchyVisitAfter(root, d3_layout_packSiblings); d3_layout_hierarchyVisitAfter(root, function(d) { d.r -= dr; }); } d3_layout_packTransform(root, w / 2, h / 2, radius ? 1 : 1 / Math.max(2 * root.r / w, 2 * root.r / h)); return nodes; } pack.size = function(_) { if (!arguments.length) return size; size = _; return pack; }; pack.radius = function(_) { if (!arguments.length) return radius; radius = _ == null || typeof _ === "function" ? _ : +_; return pack; }; pack.padding = function(_) { if (!arguments.length) return padding; padding = +_; return pack; }; return d3_layout_hierarchyRebind(pack, hierarchy); }; function d3_layout_packSort(a, b) { return a.value - b.value; } function d3_layout_packInsert(a, b) { var c = a._pack_next; a._pack_next = b; b._pack_prev = a; b._pack_next = c; c._pack_prev = b; } function d3_layout_packSplice(a, b) { a._pack_next = b; b._pack_prev = a; } function d3_layout_packIntersects(a, b) { var dx = b.x - a.x, dy = b.y - a.y, dr = a.r + b.r; return .999 * dr * dr > dx * dx + dy * dy; } function d3_layout_packSiblings(node) { if (!(nodes = node.children) || !(n = nodes.length)) return; var nodes, xMin = Infinity, xMax = -Infinity, yMin = Infinity, yMax = -Infinity, a, b, c, i, j, k, n; function bound(node) { xMin = Math.min(node.x - node.r, xMin); xMax = Math.max(node.x + node.r, xMax); yMin = Math.min(node.y - node.r, yMin); yMax = Math.max(node.y + node.r, yMax); } nodes.forEach(d3_layout_packLink); a = nodes[0]; a.x = -a.r; a.y = 0; bound(a); if (n > 1) { b = nodes[1]; b.x = b.r; b.y = 0; bound(b); if (n > 2) { c = nodes[2]; d3_layout_packPlace(a, b, c); bound(c); d3_layout_packInsert(a, c); a._pack_prev = c; d3_layout_packInsert(c, b); b = a._pack_next; for (i = 3; i < n; i++) { d3_layout_packPlace(a, b, c = nodes[i]); var isect = 0, s1 = 1, s2 = 1; for (j = b._pack_next; j !== b; j = j._pack_next, s1++) { if (d3_layout_packIntersects(j, c)) { isect = 1; break; } } if (isect == 1) { for (k = a._pack_prev; k !== j._pack_prev; k = k._pack_prev, s2++) { if (d3_layout_packIntersects(k, c)) { break; } } } if (isect) { if (s1 < s2 || s1 == s2 && b.r < a.r) d3_layout_packSplice(a, b = j); else d3_layout_packSplice(a = k, b); i--; } else { d3_layout_packInsert(a, c); b = c; bound(c); } } } } var cx = (xMin + xMax) / 2, cy = (yMin + yMax) / 2, cr = 0; for (i = 0; i < n; i++) { c = nodes[i]; c.x -= cx; c.y -= cy; cr = Math.max(cr, c.r + Math.sqrt(c.x * c.x + c.y * c.y)); } node.r = cr; nodes.forEach(d3_layout_packUnlink); } function d3_layout_packLink(node) { node._pack_next = node._pack_prev = node; } function d3_layout_packUnlink(node) { delete node._pack_next; delete node._pack_prev; } function d3_layout_packTransform(node, x, y, k) { var children = node.children; node.x = x += k * node.x; node.y = y += k * node.y; node.r *= k; if (children) { var i = -1, n = children.length; while (++i < n) d3_layout_packTransform(children[i], x, y, k); } } function d3_layout_packPlace(a, b, c) { var db = a.r + c.r, dx = b.x - a.x, dy = b.y - a.y; if (db && (dx || dy)) { var da = b.r + c.r, dc = dx * dx + dy * dy; da *= da; db *= db; var x = .5 + (db - da) / (2 * dc), y = Math.sqrt(Math.max(0, 2 * da * (db + dc) - (db -= dc) * db - da * da)) / (2 * dc); c.x = a.x + x * dx + y * dy; c.y = a.y + x * dy - y * dx; } else { c.x = a.x + db; c.y = a.y; } } d3.layout.tree = function() { var hierarchy = d3.layout.hierarchy().sort(null).value(null), separation = d3_layout_treeSeparation, size = [ 1, 1 ], nodeSize = null; function tree(d, i) { var nodes = hierarchy.call(this, d, i), root0 = nodes[0], root1 = wrapTree(root0); d3_layout_hierarchyVisitAfter(root1, firstWalk), root1.parent.m = -root1.z; d3_layout_hierarchyVisitBefore(root1, secondWalk); if (nodeSize) d3_layout_hierarchyVisitBefore(root0, sizeNode); else { var left = root0, right = root0, bottom = root0; d3_layout_hierarchyVisitBefore(root0, function(node) { if (node.x < left.x) left = node; if (node.x > right.x) right = node; if (node.depth > bottom.depth) bottom = node; }); var tx = separation(left, right) / 2 - left.x, kx = size[0] / (right.x + separation(right, left) / 2 + tx), ky = size[1] / (bottom.depth || 1); d3_layout_hierarchyVisitBefore(root0, function(node) { node.x = (node.x + tx) * kx; node.y = node.depth * ky; }); } return nodes; } function wrapTree(root0) { var root1 = { A: null, children: [ root0 ] }, queue = [ root1 ], node1; while ((node1 = queue.pop()) != null) { for (var children = node1.children, child, i = 0, n = children.length; i < n; ++i) { queue.push((children[i] = child = { _: children[i], parent: node1, children: (child = children[i].children) && child.slice() || [], A: null, a: null, z: 0, m: 0, c: 0, s: 0, t: null, i: i }).a = child); } } return root1.children[0]; } function firstWalk(v) { var children = v.children, siblings = v.parent.children, w = v.i ? siblings[v.i - 1] : null; if (children.length) { d3_layout_treeShift(v); var midpoint = (children[0].z + children[children.length - 1].z) / 2; if (w) { v.z = w.z + separation(v._, w._); v.m = v.z - midpoint; } else { v.z = midpoint; } } else if (w) { v.z = w.z + separation(v._, w._); } v.parent.A = apportion(v, w, v.parent.A || siblings[0]); } function secondWalk(v) { v._.x = v.z + v.parent.m; v.m += v.parent.m; } function apportion(v, w, ancestor) { if (w) { var vip = v, vop = v, vim = w, vom = vip.parent.children[0], sip = vip.m, sop = vop.m, sim = vim.m, som = vom.m, shift; while (vim = d3_layout_treeRight(vim), vip = d3_layout_treeLeft(vip), vim && vip) { vom = d3_layout_treeLeft(vom); vop = d3_layout_treeRight(vop); vop.a = v; shift = vim.z + sim - vip.z - sip + separation(vim._, vip._); if (shift > 0) { d3_layout_treeMove(d3_layout_treeAncestor(vim, v, ancestor), v, shift); sip += shift; sop += shift; } sim += vim.m; sip += vip.m; som += vom.m; sop += vop.m; } if (vim && !d3_layout_treeRight(vop)) { vop.t = vim; vop.m += sim - sop; } if (vip && !d3_layout_treeLeft(vom)) { vom.t = vip; vom.m += sip - som; ancestor = v; } } return ancestor; } function sizeNode(node) { node.x *= size[0]; node.y = node.depth * size[1]; } tree.separation = function(x) { if (!arguments.length) return separation; separation = x; return tree; }; tree.size = function(x) { if (!arguments.length) return nodeSize ? null : size; nodeSize = (size = x) == null ? sizeNode : null; return tree; }; tree.nodeSize = function(x) { if (!arguments.length) return nodeSize ? size : null; nodeSize = (size = x) == null ? null : sizeNode; return tree; }; return d3_layout_hierarchyRebind(tree, hierarchy); }; function d3_layout_treeSeparation(a, b) { return a.parent == b.parent ? 1 : 2; } function d3_layout_treeLeft(v) { var children = v.children; return children.length ? children[0] : v.t; } function d3_layout_treeRight(v) { var children = v.children, n; return (n = children.length) ? children[n - 1] : v.t; } function d3_layout_treeMove(wm, wp, shift) { var change = shift / (wp.i - wm.i); wp.c -= change; wp.s += shift; wm.c += change; wp.z += shift; wp.m += shift; } function d3_layout_treeShift(v) { var shift = 0, change = 0, children = v.children, i = children.length, w; while (--i >= 0) { w = children[i]; w.z += shift; w.m += shift; shift += w.s + (change += w.c); } } function d3_layout_treeAncestor(vim, v, ancestor) { return vim.a.parent === v.parent ? vim.a : ancestor; } d3.layout.cluster = function() { var hierarchy = d3.layout.hierarchy().sort(null).value(null), separation = d3_layout_treeSeparation, size = [ 1, 1 ], nodeSize = false; function cluster(d, i) { var nodes = hierarchy.call(this, d, i), root = nodes[0], previousNode, x = 0; d3_layout_hierarchyVisitAfter(root, function(node) { var children = node.children; if (children && children.length) { node.x = d3_layout_clusterX(children); node.y = d3_layout_clusterY(children); } else { node.x = previousNode ? x += separation(node, previousNode) : 0; node.y = 0; previousNode = node; } }); var left = d3_layout_clusterLeft(root), right = d3_layout_clusterRight(root), x0 = left.x - separation(left, right) / 2, x1 = right.x + separation(right, left) / 2; d3_layout_hierarchyVisitAfter(root, nodeSize ? function(node) { node.x = (node.x - root.x) * size[0]; node.y = (root.y - node.y) * size[1]; } : function(node) { node.x = (node.x - x0) / (x1 - x0) * size[0]; node.y = (1 - (root.y ? node.y / root.y : 1)) * size[1]; }); return nodes; } cluster.separation = function(x) { if (!arguments.length) return separation; separation = x; return cluster; }; cluster.size = function(x) { if (!arguments.length) return nodeSize ? null : size; nodeSize = (size = x) == null; return cluster; }; cluster.nodeSize = function(x) { if (!arguments.length) return nodeSize ? size : null; nodeSize = (size = x) != null; return cluster; }; return d3_layout_hierarchyRebind(cluster, hierarchy); }; function d3_layout_clusterY(children) { return 1 + d3.max(children, function(child) { return child.y; }); } function d3_layout_clusterX(children) { return children.reduce(function(x, child) { return x + child.x; }, 0) / children.length; } function d3_layout_clusterLeft(node) { var children = node.children; return children && children.length ? d3_layout_clusterLeft(children[0]) : node; } function d3_layout_clusterRight(node) { var children = node.children, n; return children && (n = children.length) ? d3_layout_clusterRight(children[n - 1]) : node; } d3.layout.treemap = function() { var hierarchy = d3.layout.hierarchy(), round = Math.round, size = [ 1, 1 ], padding = null, pad = d3_layout_treemapPadNull, sticky = false, stickies, mode = "squarify", ratio = .5 * (1 + Math.sqrt(5)); function scale(children, k) { var i = -1, n = children.length, child, area; while (++i < n) { area = (child = children[i]).value * (k < 0 ? 0 : k); child.area = isNaN(area) || area <= 0 ? 0 : area; } } function squarify(node) { var children = node.children; if (children && children.length) { var rect = pad(node), row = [], remaining = children.slice(), child, best = Infinity, score, u = mode === "slice" ? rect.dx : mode === "dice" ? rect.dy : mode === "slice-dice" ? node.depth & 1 ? rect.dy : rect.dx : Math.min(rect.dx, rect.dy), n; scale(remaining, rect.dx * rect.dy / node.value); row.area = 0; while ((n = remaining.length) > 0) { row.push(child = remaining[n - 1]); row.area += child.area; if (mode !== "squarify" || (score = worst(row, u)) <= best) { remaining.pop(); best = score; } else { row.area -= row.pop().area; position(row, u, rect, false); u = Math.min(rect.dx, rect.dy); row.length = row.area = 0; best = Infinity; } } if (row.length) { position(row, u, rect, true); row.length = row.area = 0; } children.forEach(squarify); } } function stickify(node) { var children = node.children; if (children && children.length) { var rect = pad(node), remaining = children.slice(), child, row = []; scale(remaining, rect.dx * rect.dy / node.value); row.area = 0; while (child = remaining.pop()) { row.push(child); row.area += child.area; if (child.z != null) { position(row, child.z ? rect.dx : rect.dy, rect, !remaining.length); row.length = row.area = 0; } } children.forEach(stickify); } } function worst(row, u) { var s = row.area, r, rmax = 0, rmin = Infinity, i = -1, n = row.length; while (++i < n) { if (!(r = row[i].area)) continue; if (r < rmin) rmin = r; if (r > rmax) rmax = r; } s *= s; u *= u; return s ? Math.max(u * rmax * ratio / s, s / (u * rmin * ratio)) : Infinity; } function position(row, u, rect, flush) { var i = -1, n = row.length, x = rect.x, y = rect.y, v = u ? round(row.area / u) : 0, o; if (u == rect.dx) { if (flush || v > rect.dy) v = rect.dy; while (++i < n) { o = row[i]; o.x = x; o.y = y; o.dy = v; x += o.dx = Math.min(rect.x + rect.dx - x, v ? round(o.area / v) : 0); } o.z = true; o.dx += rect.x + rect.dx - x; rect.y += v; rect.dy -= v; } else { if (flush || v > rect.dx) v = rect.dx; while (++i < n) { o = row[i]; o.x = x; o.y = y; o.dx = v; y += o.dy = Math.min(rect.y + rect.dy - y, v ? round(o.area / v) : 0); } o.z = false; o.dy += rect.y + rect.dy - y; rect.x += v; rect.dx -= v; } } function treemap(d) { var nodes = stickies || hierarchy(d), root = nodes[0]; root.x = root.y = 0; if (root.value) root.dx = size[0], root.dy = size[1]; else root.dx = root.dy = 0; if (stickies) hierarchy.revalue(root); scale([ root ], root.dx * root.dy / root.value); (stickies ? stickify : squarify)(root); if (sticky) stickies = nodes; return nodes; } treemap.size = function(x) { if (!arguments.length) return size; size = x; return treemap; }; treemap.padding = function(x) { if (!arguments.length) return padding; function padFunction(node) { var p = x.call(treemap, node, node.depth); return p == null ? d3_layout_treemapPadNull(node) : d3_layout_treemapPad(node, typeof p === "number" ? [ p, p, p, p ] : p); } function padConstant(node) { return d3_layout_treemapPad(node, x); } var type; pad = (padding = x) == null ? d3_layout_treemapPadNull : (type = typeof x) === "function" ? padFunction : type === "number" ? (x = [ x, x, x, x ], padConstant) : padConstant; return treemap; }; treemap.round = function(x) { if (!arguments.length) return round != Number; round = x ? Math.round : Number; return treemap; }; treemap.sticky = function(x) { if (!arguments.length) return sticky; sticky = x; stickies = null; return treemap; }; treemap.ratio = function(x) { if (!arguments.length) return ratio; ratio = x; return treemap; }; treemap.mode = function(x) { if (!arguments.length) return mode; mode = x + ""; return treemap; }; return d3_layout_hierarchyRebind(treemap, hierarchy); }; function d3_layout_treemapPadNull(node) { return { x: node.x, y: node.y, dx: node.dx, dy: node.dy }; } function d3_layout_treemapPad(node, padding) { var x = node.x + padding[3], y = node.y + padding[0], dx = node.dx - padding[1] - padding[3], dy = node.dy - padding[0] - padding[2]; if (dx < 0) { x += dx / 2; dx = 0; } if (dy < 0) { y += dy / 2; dy = 0; } return { x: x, y: y, dx: dx, dy: dy }; } d3.random = { normal: function(µ, σ) { var n = arguments.length; if (n < 2) σ = 1; if (n < 1) µ = 0; return function() { var x, y, r; do { x = Math.random() * 2 - 1; y = Math.random() * 2 - 1; r = x * x + y * y; } while (!r || r > 1); return µ + σ * x * Math.sqrt(-2 * Math.log(r) / r); }; }, logNormal: function() { var random = d3.random.normal.apply(d3, arguments); return function() { return Math.exp(random()); }; }, bates: function(m) { var random = d3.random.irwinHall(m); return function() { return random() / m; }; }, irwinHall: function(m) { return function() { for (var s = 0, j = 0; j < m; j++) s += Math.random(); return s; }; } }; d3.scale = {}; function d3_scaleExtent(domain) { var start = domain[0], stop = domain[domain.length - 1]; return start < stop ? [ start, stop ] : [ stop, start ]; } function d3_scaleRange(scale) { return scale.rangeExtent ? scale.rangeExtent() : d3_scaleExtent(scale.range()); } function d3_scale_bilinear(domain, range, uninterpolate, interpolate) { var u = uninterpolate(domain[0], domain[1]), i = interpolate(range[0], range[1]); return function(x) { return i(u(x)); }; } function d3_scale_nice(domain, nice) { var i0 = 0, i1 = domain.length - 1, x0 = domain[i0], x1 = domain[i1], dx; if (x1 < x0) { dx = i0, i0 = i1, i1 = dx; dx = x0, x0 = x1, x1 = dx; } domain[i0] = nice.floor(x0); domain[i1] = nice.ceil(x1); return domain; } function d3_scale_niceStep(step) { return step ? { floor: function(x) { return Math.floor(x / step) * step; }, ceil: function(x) { return Math.ceil(x / step) * step; } } : d3_scale_niceIdentity; } var d3_scale_niceIdentity = { floor: d3_identity, ceil: d3_identity }; function d3_scale_polylinear(domain, range, uninterpolate, interpolate) { var u = [], i = [], j = 0, k = Math.min(domain.length, range.length) - 1; if (domain[k] < domain[0]) { domain = domain.slice().reverse(); range = range.slice().reverse(); } while (++j <= k) { u.push(uninterpolate(domain[j - 1], domain[j])); i.push(interpolate(range[j - 1], range[j])); } return function(x) { var j = d3.bisect(domain, x, 1, k) - 1; return i[j](u[j](x)); }; } d3.scale.linear = function() { return d3_scale_linear([ 0, 1 ], [ 0, 1 ], d3_interpolate, false); }; function d3_scale_linear(domain, range, interpolate, clamp) { var output, input; function rescale() { var linear = Math.min(domain.length, range.length) > 2 ? d3_scale_polylinear : d3_scale_bilinear, uninterpolate = clamp ? d3_uninterpolateClamp : d3_uninterpolateNumber; output = linear(domain, range, uninterpolate, interpolate); input = linear(range, domain, uninterpolate, d3_interpolate); return scale; } function scale(x) { return output(x); } scale.invert = function(y) { return input(y); }; scale.domain = function(x) { if (!arguments.length) return domain; domain = x.map(Number); return rescale(); }; scale.range = function(x) { if (!arguments.length) return range; range = x; return rescale(); }; scale.rangeRound = function(x) { return scale.range(x).interpolate(d3_interpolateRound); }; scale.clamp = function(x) { if (!arguments.length) return clamp; clamp = x; return rescale(); }; scale.interpolate = function(x) { if (!arguments.length) return interpolate; interpolate = x; return rescale(); }; scale.ticks = function(m) { return d3_scale_linearTicks(domain, m); }; scale.tickFormat = function(m, format) { return d3_scale_linearTickFormat(domain, m, format); }; scale.nice = function(m) { d3_scale_linearNice(domain, m); return rescale(); }; scale.copy = function() { return d3_scale_linear(domain, range, interpolate, clamp); }; return rescale(); } function d3_scale_linearRebind(scale, linear) { return d3.rebind(scale, linear, "range", "rangeRound", "interpolate", "clamp"); } function d3_scale_linearNice(domain, m) { d3_scale_nice(domain, d3_scale_niceStep(d3_scale_linearTickRange(domain, m)[2])); d3_scale_nice(domain, d3_scale_niceStep(d3_scale_linearTickRange(domain, m)[2])); return domain; } function d3_scale_linearTickRange(domain, m) { if (m == null) m = 10; var extent = d3_scaleExtent(domain), span = extent[1] - extent[0], step = Math.pow(10, Math.floor(Math.log(span / m) / Math.LN10)), err = m / span * step; if (err <= .15) step *= 10; else if (err <= .35) step *= 5; else if (err <= .75) step *= 2; extent[0] = Math.ceil(extent[0] / step) * step; extent[1] = Math.floor(extent[1] / step) * step + step * .5; extent[2] = step; return extent; } function d3_scale_linearTicks(domain, m) { return d3.range.apply(d3, d3_scale_linearTickRange(domain, m)); } function d3_scale_linearTickFormat(domain, m, format) { var range = d3_scale_linearTickRange(domain, m); if (format) { var match = d3_format_re.exec(format); match.shift(); if (match[8] === "s") { var prefix = d3.formatPrefix(Math.max(abs(range[0]), abs(range[1]))); if (!match[7]) match[7] = "." + d3_scale_linearPrecision(prefix.scale(range[2])); match[8] = "f"; format = d3.format(match.join("")); return function(d) { return format(prefix.scale(d)) + prefix.symbol; }; } if (!match[7]) match[7] = "." + d3_scale_linearFormatPrecision(match[8], range); format = match.join(""); } else { format = ",." + d3_scale_linearPrecision(range[2]) + "f"; } return d3.format(format); } var d3_scale_linearFormatSignificant = { s: 1, g: 1, p: 1, r: 1, e: 1 }; function d3_scale_linearPrecision(value) { return -Math.floor(Math.log(value) / Math.LN10 + .01); } function d3_scale_linearFormatPrecision(type, range) { var p = d3_scale_linearPrecision(range[2]); return type in d3_scale_linearFormatSignificant ? Math.abs(p - d3_scale_linearPrecision(Math.max(abs(range[0]), abs(range[1])))) + +(type !== "e") : p - (type === "%") * 2; } d3.scale.log = function() { return d3_scale_log(d3.scale.linear().domain([ 0, 1 ]), 10, true, [ 1, 10 ]); }; function d3_scale_log(linear, base, positive, domain) { function log(x) { return (positive ? Math.log(x < 0 ? 0 : x) : -Math.log(x > 0 ? 0 : -x)) / Math.log(base); } function pow(x) { return positive ? Math.pow(base, x) : -Math.pow(base, -x); } function scale(x) { return linear(log(x)); } scale.invert = function(x) { return pow(linear.invert(x)); }; scale.domain = function(x) { if (!arguments.length) return domain; positive = x[0] >= 0; linear.domain((domain = x.map(Number)).map(log)); return scale; }; scale.base = function(_) { if (!arguments.length) return base; base = +_; linear.domain(domain.map(log)); return scale; }; scale.nice = function() { var niced = d3_scale_nice(domain.map(log), positive ? Math : d3_scale_logNiceNegative); linear.domain(niced); domain = niced.map(pow); return scale; }; scale.ticks = function() { var extent = d3_scaleExtent(domain), ticks = [], u = extent[0], v = extent[1], i = Math.floor(log(u)), j = Math.ceil(log(v)), n = base % 1 ? 2 : base; if (isFinite(j - i)) { if (positive) { for (;i < j; i++) for (var k = 1; k < n; k++) ticks.push(pow(i) * k); ticks.push(pow(i)); } else { ticks.push(pow(i)); for (;i++ < j; ) for (var k = n - 1; k > 0; k--) ticks.push(pow(i) * k); } for (i = 0; ticks[i] < u; i++) {} for (j = ticks.length; ticks[j - 1] > v; j--) {} ticks = ticks.slice(i, j); } return ticks; }; scale.tickFormat = function(n, format) { if (!arguments.length) return d3_scale_logFormat; if (arguments.length < 2) format = d3_scale_logFormat; else if (typeof format !== "function") format = d3.format(format); var k = Math.max(1, base * n / scale.ticks().length); return function(d) { var i = d / pow(Math.round(log(d))); if (i * base < base - .5) i *= base; return i <= k ? format(d) : ""; }; }; scale.copy = function() { return d3_scale_log(linear.copy(), base, positive, domain); }; return d3_scale_linearRebind(scale, linear); } var d3_scale_logFormat = d3.format(".0e"), d3_scale_logNiceNegative = { floor: function(x) { return -Math.ceil(-x); }, ceil: function(x) { return -Math.floor(-x); } }; d3.scale.pow = function() { return d3_scale_pow(d3.scale.linear(), 1, [ 0, 1 ]); }; function d3_scale_pow(linear, exponent, domain) { var powp = d3_scale_powPow(exponent), powb = d3_scale_powPow(1 / exponent); function scale(x) { return linear(powp(x)); } scale.invert = function(x) { return powb(linear.invert(x)); }; scale.domain = function(x) { if (!arguments.length) return domain; linear.domain((domain = x.map(Number)).map(powp)); return scale; }; scale.ticks = function(m) { return d3_scale_linearTicks(domain, m); }; scale.tickFormat = function(m, format) { return d3_scale_linearTickFormat(domain, m, format); }; scale.nice = function(m) { return scale.domain(d3_scale_linearNice(domain, m)); }; scale.exponent = function(x) { if (!arguments.length) return exponent; powp = d3_scale_powPow(exponent = x); powb = d3_scale_powPow(1 / exponent); linear.domain(domain.map(powp)); return scale; }; scale.copy = function() { return d3_scale_pow(linear.copy(), exponent, domain); }; return d3_scale_linearRebind(scale, linear); } function d3_scale_powPow(e) { return function(x) { return x < 0 ? -Math.pow(-x, e) : Math.pow(x, e); }; } d3.scale.sqrt = function() { return d3.scale.pow().exponent(.5); }; d3.scale.ordinal = function() { return d3_scale_ordinal([], { t: "range", a: [ [] ] }); }; function d3_scale_ordinal(domain, ranger) { var index, range, rangeBand; function scale(x) { return range[((index.get(x) || (ranger.t === "range" ? index.set(x, domain.push(x)) : NaN)) - 1) % range.length]; } function steps(start, step) { return d3.range(domain.length).map(function(i) { return start + step * i; }); } scale.domain = function(x) { if (!arguments.length) return domain; domain = []; index = new d3_Map(); var i = -1, n = x.length, xi; while (++i < n) if (!index.has(xi = x[i])) index.set(xi, domain.push(xi)); return scale[ranger.t].apply(scale, ranger.a); }; scale.range = function(x) { if (!arguments.length) return range; range = x; rangeBand = 0; ranger = { t: "range", a: arguments }; return scale; }; scale.rangePoints = function(x, padding) { if (arguments.length < 2) padding = 0; var start = x[0], stop = x[1], step = domain.length < 2 ? (start = (start + stop) / 2, 0) : (stop - start) / (domain.length - 1 + padding); range = steps(start + step * padding / 2, step); rangeBand = 0; ranger = { t: "rangePoints", a: arguments }; return scale; }; scale.rangeRoundPoints = function(x, padding) { if (arguments.length < 2) padding = 0; var start = x[0], stop = x[1], step = domain.length < 2 ? (start = stop = Math.round((start + stop) / 2), 0) : (stop - start) / (domain.length - 1 + padding) | 0; range = steps(start + Math.round(step * padding / 2 + (stop - start - (domain.length - 1 + padding) * step) / 2), step); rangeBand = 0; ranger = { t: "rangeRoundPoints", a: arguments }; return scale; }; scale.rangeBands = function(x, padding, outerPadding) { if (arguments.length < 2) padding = 0; if (arguments.length < 3) outerPadding = padding; var reverse = x[1] < x[0], start = x[reverse - 0], stop = x[1 - reverse], step = (stop - start) / (domain.length - padding + 2 * outerPadding); range = steps(start + step * outerPadding, step); if (reverse) range.reverse(); rangeBand = step * (1 - padding); ranger = { t: "rangeBands", a: arguments }; return scale; }; scale.rangeRoundBands = function(x, padding, outerPadding) { if (arguments.length < 2) padding = 0; if (arguments.length < 3) outerPadding = padding; var reverse = x[1] < x[0], start = x[reverse - 0], stop = x[1 - reverse], step = Math.floor((stop - start) / (domain.length - padding + 2 * outerPadding)); range = steps(start + Math.round((stop - start - (domain.length - padding) * step) / 2), step); if (reverse) range.reverse(); rangeBand = Math.round(step * (1 - padding)); ranger = { t: "rangeRoundBands", a: arguments }; return scale; }; scale.rangeBand = function() { return rangeBand; }; scale.rangeExtent = function() { return d3_scaleExtent(ranger.a[0]); }; scale.copy = function() { return d3_scale_ordinal(domain, ranger); }; return scale.domain(domain); } d3.scale.category10 = function() { return d3.scale.ordinal().range(d3_category10); }; d3.scale.category20 = function() { return d3.scale.ordinal().range(d3_category20); }; d3.scale.category20b = function() { return d3.scale.ordinal().range(d3_category20b); }; d3.scale.category20c = function() { return d3.scale.ordinal().range(d3_category20c); }; var d3_category10 = [ 2062260, 16744206, 2924588, 14034728, 9725885, 9197131, 14907330, 8355711, 12369186, 1556175 ].map(d3_rgbString); var d3_category20 = [ 2062260, 11454440, 16744206, 16759672, 2924588, 10018698, 14034728, 16750742, 9725885, 12955861, 9197131, 12885140, 14907330, 16234194, 8355711, 13092807, 12369186, 14408589, 1556175, 10410725 ].map(d3_rgbString); var d3_category20b = [ 3750777, 5395619, 7040719, 10264286, 6519097, 9216594, 11915115, 13556636, 9202993, 12426809, 15186514, 15190932, 8666169, 11356490, 14049643, 15177372, 8077683, 10834324, 13528509, 14589654 ].map(d3_rgbString); var d3_category20c = [ 3244733, 7057110, 10406625, 13032431, 15095053, 16616764, 16625259, 16634018, 3253076, 7652470, 10607003, 13101504, 7695281, 10394312, 12369372, 14342891, 6513507, 9868950, 12434877, 14277081 ].map(d3_rgbString); d3.scale.quantile = function() { return d3_scale_quantile([], []); }; function d3_scale_quantile(domain, range) { var thresholds; function rescale() { var k = 0, q = range.length; thresholds = []; while (++k < q) thresholds[k - 1] = d3.quantile(domain, k / q); return scale; } function scale(x) { if (!isNaN(x = +x)) return range[d3.bisect(thresholds, x)]; } scale.domain = function(x) { if (!arguments.length) return domain; domain = x.map(d3_number).filter(d3_numeric).sort(d3_ascending); return rescale(); }; scale.range = function(x) { if (!arguments.length) return range; range = x; return rescale(); }; scale.quantiles = function() { return thresholds; }; scale.invertExtent = function(y) { y = range.indexOf(y); return y < 0 ? [ NaN, NaN ] : [ y > 0 ? thresholds[y - 1] : domain[0], y < thresholds.length ? thresholds[y] : domain[domain.length - 1] ]; }; scale.copy = function() { return d3_scale_quantile(domain, range); }; return rescale(); } d3.scale.quantize = function() { return d3_scale_quantize(0, 1, [ 0, 1 ]); }; function d3_scale_quantize(x0, x1, range) { var kx, i; function scale(x) { return range[Math.max(0, Math.min(i, Math.floor(kx * (x - x0))))]; } function rescale() { kx = range.length / (x1 - x0); i = range.length - 1; return scale; } scale.domain = function(x) { if (!arguments.length) return [ x0, x1 ]; x0 = +x[0]; x1 = +x[x.length - 1]; return rescale(); }; scale.range = function(x) { if (!arguments.length) return range; range = x; return rescale(); }; scale.invertExtent = function(y) { y = range.indexOf(y); y = y < 0 ? NaN : y / kx + x0; return [ y, y + 1 / kx ]; }; scale.copy = function() { return d3_scale_quantize(x0, x1, range); }; return rescale(); } d3.scale.threshold = function() { return d3_scale_threshold([ .5 ], [ 0, 1 ]); }; function d3_scale_threshold(domain, range) { function scale(x) { if (x <= x) return range[d3.bisect(domain, x)]; } scale.domain = function(_) { if (!arguments.length) return domain; domain = _; return scale; }; scale.range = function(_) { if (!arguments.length) return range; range = _; return scale; }; scale.invertExtent = function(y) { y = range.indexOf(y); return [ domain[y - 1], domain[y] ]; }; scale.copy = function() { return d3_scale_threshold(domain, range); }; return scale; } d3.scale.identity = function() { return d3_scale_identity([ 0, 1 ]); }; function d3_scale_identity(domain) { function identity(x) { return +x; } identity.invert = identity; identity.domain = identity.range = function(x) { if (!arguments.length) return domain; domain = x.map(identity); return identity; }; identity.ticks = function(m) { return d3_scale_linearTicks(domain, m); }; identity.tickFormat = function(m, format) { return d3_scale_linearTickFormat(domain, m, format); }; identity.copy = function() { return d3_scale_identity(domain); }; return identity; } d3.svg = {}; function d3_zero() { return 0; } d3.svg.arc = function() { var innerRadius = d3_svg_arcInnerRadius, outerRadius = d3_svg_arcOuterRadius, cornerRadius = d3_zero, padRadius = d3_svg_arcAuto, startAngle = d3_svg_arcStartAngle, endAngle = d3_svg_arcEndAngle, padAngle = d3_svg_arcPadAngle; function arc() { var r0 = Math.max(0, +innerRadius.apply(this, arguments)), r1 = Math.max(0, +outerRadius.apply(this, arguments)), a0 = startAngle.apply(this, arguments) - halfπ, a1 = endAngle.apply(this, arguments) - halfπ, da = Math.abs(a1 - a0), cw = a0 > a1 ? 0 : 1; if (r1 < r0) rc = r1, r1 = r0, r0 = rc; if (da >= τε) return circleSegment(r1, cw) + (r0 ? circleSegment(r0, 1 - cw) : "") + "Z"; var rc, cr, rp, ap, p0 = 0, p1 = 0, x0, y0, x1, y1, x2, y2, x3, y3, path = []; if (ap = (+padAngle.apply(this, arguments) || 0) / 2) { rp = padRadius === d3_svg_arcAuto ? Math.sqrt(r0 * r0 + r1 * r1) : +padRadius.apply(this, arguments); if (!cw) p1 *= -1; if (r1) p1 = d3_asin(rp / r1 * Math.sin(ap)); if (r0) p0 = d3_asin(rp / r0 * Math.sin(ap)); } if (r1) { x0 = r1 * Math.cos(a0 + p1); y0 = r1 * Math.sin(a0 + p1); x1 = r1 * Math.cos(a1 - p1); y1 = r1 * Math.sin(a1 - p1); var l1 = Math.abs(a1 - a0 - 2 * p1) <= π ? 0 : 1; if (p1 && d3_svg_arcSweep(x0, y0, x1, y1) === cw ^ l1) { var h1 = (a0 + a1) / 2; x0 = r1 * Math.cos(h1); y0 = r1 * Math.sin(h1); x1 = y1 = null; } } else { x0 = y0 = 0; } if (r0) { x2 = r0 * Math.cos(a1 - p0); y2 = r0 * Math.sin(a1 - p0); x3 = r0 * Math.cos(a0 + p0); y3 = r0 * Math.sin(a0 + p0); var l0 = Math.abs(a0 - a1 + 2 * p0) <= π ? 0 : 1; if (p0 && d3_svg_arcSweep(x2, y2, x3, y3) === 1 - cw ^ l0) { var h0 = (a0 + a1) / 2; x2 = r0 * Math.cos(h0); y2 = r0 * Math.sin(h0); x3 = y3 = null; } } else { x2 = y2 = 0; } if (da > ε && (rc = Math.min(Math.abs(r1 - r0) / 2, +cornerRadius.apply(this, arguments))) > .001) { cr = r0 < r1 ^ cw ? 0 : 1; var rc1 = rc, rc0 = rc; if (da < π) { var oc = x3 == null ? [ x2, y2 ] : x1 == null ? [ x0, y0 ] : d3_geom_polygonIntersect([ x0, y0 ], [ x3, y3 ], [ x1, y1 ], [ x2, y2 ]), ax = x0 - oc[0], ay = y0 - oc[1], bx = x1 - oc[0], by = y1 - oc[1], kc = 1 / Math.sin(Math.acos((ax * bx + ay * by) / (Math.sqrt(ax * ax + ay * ay) * Math.sqrt(bx * bx + by * by))) / 2), lc = Math.sqrt(oc[0] * oc[0] + oc[1] * oc[1]); rc0 = Math.min(rc, (r0 - lc) / (kc - 1)); rc1 = Math.min(rc, (r1 - lc) / (kc + 1)); } if (x1 != null) { var t30 = d3_svg_arcCornerTangents(x3 == null ? [ x2, y2 ] : [ x3, y3 ], [ x0, y0 ], r1, rc1, cw), t12 = d3_svg_arcCornerTangents([ x1, y1 ], [ x2, y2 ], r1, rc1, cw); if (rc === rc1) { path.push("M", t30[0], "A", rc1, ",", rc1, " 0 0,", cr, " ", t30[1], "A", r1, ",", r1, " 0 ", 1 - cw ^ d3_svg_arcSweep(t30[1][0], t30[1][1], t12[1][0], t12[1][1]), ",", cw, " ", t12[1], "A", rc1, ",", rc1, " 0 0,", cr, " ", t12[0]); } else { path.push("M", t30[0], "A", rc1, ",", rc1, " 0 1,", cr, " ", t12[0]); } } else { path.push("M", x0, ",", y0); } if (x3 != null) { var t03 = d3_svg_arcCornerTangents([ x0, y0 ], [ x3, y3 ], r0, -rc0, cw), t21 = d3_svg_arcCornerTangents([ x2, y2 ], x1 == null ? [ x0, y0 ] : [ x1, y1 ], r0, -rc0, cw); if (rc === rc0) { path.push("L", t21[0], "A", rc0, ",", rc0, " 0 0,", cr, " ", t21[1], "A", r0, ",", r0, " 0 ", cw ^ d3_svg_arcSweep(t21[1][0], t21[1][1], t03[1][0], t03[1][1]), ",", 1 - cw, " ", t03[1], "A", rc0, ",", rc0, " 0 0,", cr, " ", t03[0]); } else { path.push("L", t21[0], "A", rc0, ",", rc0, " 0 0,", cr, " ", t03[0]); } } else { path.push("L", x2, ",", y2); } } else { path.push("M", x0, ",", y0); if (x1 != null) path.push("A", r1, ",", r1, " 0 ", l1, ",", cw, " ", x1, ",", y1); path.push("L", x2, ",", y2); if (x3 != null) path.push("A", r0, ",", r0, " 0 ", l0, ",", 1 - cw, " ", x3, ",", y3); } path.push("Z"); return path.join(""); } function circleSegment(r1, cw) { return "M0," + r1 + "A" + r1 + "," + r1 + " 0 1," + cw + " 0," + -r1 + "A" + r1 + "," + r1 + " 0 1," + cw + " 0," + r1; } arc.innerRadius = function(v) { if (!arguments.length) return innerRadius; innerRadius = d3_functor(v); return arc; }; arc.outerRadius = function(v) { if (!arguments.length) return outerRadius; outerRadius = d3_functor(v); return arc; }; arc.cornerRadius = function(v) { if (!arguments.length) return cornerRadius; cornerRadius = d3_functor(v); return arc; }; arc.padRadius = function(v) { if (!arguments.length) return padRadius; padRadius = v == d3_svg_arcAuto ? d3_svg_arcAuto : d3_functor(v); return arc; }; arc.startAngle = function(v) { if (!arguments.length) return startAngle; startAngle = d3_functor(v); return arc; }; arc.endAngle = function(v) { if (!arguments.length) return endAngle; endAngle = d3_functor(v); return arc; }; arc.padAngle = function(v) { if (!arguments.length) return padAngle; padAngle = d3_functor(v); return arc; }; arc.centroid = function() { var r = (+innerRadius.apply(this, arguments) + +outerRadius.apply(this, arguments)) / 2, a = (+startAngle.apply(this, arguments) + +endAngle.apply(this, arguments)) / 2 - halfπ; return [ Math.cos(a) * r, Math.sin(a) * r ]; }; return arc; }; var d3_svg_arcAuto = "auto"; function d3_svg_arcInnerRadius(d) { return d.innerRadius; } function d3_svg_arcOuterRadius(d) { return d.outerRadius; } function d3_svg_arcStartAngle(d) { return d.startAngle; } function d3_svg_arcEndAngle(d) { return d.endAngle; } function d3_svg_arcPadAngle(d) { return d && d.padAngle; } function d3_svg_arcSweep(x0, y0, x1, y1) { return (x0 - x1) * y0 - (y0 - y1) * x0 > 0 ? 0 : 1; } function d3_svg_arcCornerTangents(p0, p1, r1, rc, cw) { var x01 = p0[0] - p1[0], y01 = p0[1] - p1[1], lo = (cw ? rc : -rc) / Math.sqrt(x01 * x01 + y01 * y01), ox = lo * y01, oy = -lo * x01, x1 = p0[0] + ox, y1 = p0[1] + oy, x2 = p1[0] + ox, y2 = p1[1] + oy, x3 = (x1 + x2) / 2, y3 = (y1 + y2) / 2, dx = x2 - x1, dy = y2 - y1, d2 = dx * dx + dy * dy, r = r1 - rc, D = x1 * y2 - x2 * y1, d = (dy < 0 ? -1 : 1) * Math.sqrt(Math.max(0, r * r * d2 - D * D)), cx0 = (D * dy - dx * d) / d2, cy0 = (-D * dx - dy * d) / d2, cx1 = (D * dy + dx * d) / d2, cy1 = (-D * dx + dy * d) / d2, dx0 = cx0 - x3, dy0 = cy0 - y3, dx1 = cx1 - x3, dy1 = cy1 - y3; if (dx0 * dx0 + dy0 * dy0 > dx1 * dx1 + dy1 * dy1) cx0 = cx1, cy0 = cy1; return [ [ cx0 - ox, cy0 - oy ], [ cx0 * r1 / r, cy0 * r1 / r ] ]; } function d3_svg_line(projection) { var x = d3_geom_pointX, y = d3_geom_pointY, defined = d3_true, interpolate = d3_svg_lineLinear, interpolateKey = interpolate.key, tension = .7; function line(data) { var segments = [], points = [], i = -1, n = data.length, d, fx = d3_functor(x), fy = d3_functor(y); function segment() { segments.push("M", interpolate(projection(points), tension)); } while (++i < n) { if (defined.call(this, d = data[i], i)) { points.push([ +fx.call(this, d, i), +fy.call(this, d, i) ]); } else if (points.length) { segment(); points = []; } } if (points.length) segment(); return segments.length ? segments.join("") : null; } line.x = function(_) { if (!arguments.length) return x; x = _; return line; }; line.y = function(_) { if (!arguments.length) return y; y = _; return line; }; line.defined = function(_) { if (!arguments.length) return defined; defined = _; return line; }; line.interpolate = function(_) { if (!arguments.length) return interpolateKey; if (typeof _ === "function") interpolateKey = interpolate = _; else interpolateKey = (interpolate = d3_svg_lineInterpolators.get(_) || d3_svg_lineLinear).key; return line; }; line.tension = function(_) { if (!arguments.length) return tension; tension = _; return line; }; return line; } d3.svg.line = function() { return d3_svg_line(d3_identity); }; var d3_svg_lineInterpolators = d3.map({ linear: d3_svg_lineLinear, "linear-closed": d3_svg_lineLinearClosed, step: d3_svg_lineStep, "step-before": d3_svg_lineStepBefore, "step-after": d3_svg_lineStepAfter, basis: d3_svg_lineBasis, "basis-open": d3_svg_lineBasisOpen, "basis-closed": d3_svg_lineBasisClosed, bundle: d3_svg_lineBundle, cardinal: d3_svg_lineCardinal, "cardinal-open": d3_svg_lineCardinalOpen, "cardinal-closed": d3_svg_lineCardinalClosed, monotone: d3_svg_lineMonotone }); d3_svg_lineInterpolators.forEach(function(key, value) { value.key = key; value.closed = /-closed$/.test(key); }); function d3_svg_lineLinear(points) { return points.length > 1 ? points.join("L") : points + "Z"; } function d3_svg_lineLinearClosed(points) { return points.join("L") + "Z"; } function d3_svg_lineStep(points) { var i = 0, n = points.length, p = points[0], path = [ p[0], ",", p[1] ]; while (++i < n) path.push("H", (p[0] + (p = points[i])[0]) / 2, "V", p[1]); if (n > 1) path.push("H", p[0]); return path.join(""); } function d3_svg_lineStepBefore(points) { var i = 0, n = points.length, p = points[0], path = [ p[0], ",", p[1] ]; while (++i < n) path.push("V", (p = points[i])[1], "H", p[0]); return path.join(""); } function d3_svg_lineStepAfter(points) { var i = 0, n = points.length, p = points[0], path = [ p[0], ",", p[1] ]; while (++i < n) path.push("H", (p = points[i])[0], "V", p[1]); return path.join(""); } function d3_svg_lineCardinalOpen(points, tension) { return points.length < 4 ? d3_svg_lineLinear(points) : points[1] + d3_svg_lineHermite(points.slice(1, -1), d3_svg_lineCardinalTangents(points, tension)); } function d3_svg_lineCardinalClosed(points, tension) { return points.length < 3 ? d3_svg_lineLinearClosed(points) : points[0] + d3_svg_lineHermite((points.push(points[0]), points), d3_svg_lineCardinalTangents([ points[points.length - 2] ].concat(points, [ points[1] ]), tension)); } function d3_svg_lineCardinal(points, tension) { return points.length < 3 ? d3_svg_lineLinear(points) : points[0] + d3_svg_lineHermite(points, d3_svg_lineCardinalTangents(points, tension)); } function d3_svg_lineHermite(points, tangents) { if (tangents.length < 1 || points.length != tangents.length && points.length != tangents.length + 2) { return d3_svg_lineLinear(points); } var quad = points.length != tangents.length, path = "", p0 = points[0], p = points[1], t0 = tangents[0], t = t0, pi = 1; if (quad) { path += "Q" + (p[0] - t0[0] * 2 / 3) + "," + (p[1] - t0[1] * 2 / 3) + "," + p[0] + "," + p[1]; p0 = points[1]; pi = 2; } if (tangents.length > 1) { t = tangents[1]; p = points[pi]; pi++; path += "C" + (p0[0] + t0[0]) + "," + (p0[1] + t0[1]) + "," + (p[0] - t[0]) + "," + (p[1] - t[1]) + "," + p[0] + "," + p[1]; for (var i = 2; i < tangents.length; i++, pi++) { p = points[pi]; t = tangents[i]; path += "S" + (p[0] - t[0]) + "," + (p[1] - t[1]) + "," + p[0] + "," + p[1]; } } if (quad) { var lp = points[pi]; path += "Q" + (p[0] + t[0] * 2 / 3) + "," + (p[1] + t[1] * 2 / 3) + "," + lp[0] + "," + lp[1]; } return path; } function d3_svg_lineCardinalTangents(points, tension) { var tangents = [], a = (1 - tension) / 2, p0, p1 = points[0], p2 = points[1], i = 1, n = points.length; while (++i < n) { p0 = p1; p1 = p2; p2 = points[i]; tangents.push([ a * (p2[0] - p0[0]), a * (p2[1] - p0[1]) ]); } return tangents; } function d3_svg_lineBasis(points) { if (points.length < 3) return d3_svg_lineLinear(points); var i = 1, n = points.length, pi = points[0], x0 = pi[0], y0 = pi[1], px = [ x0, x0, x0, (pi = points[1])[0] ], py = [ y0, y0, y0, pi[1] ], path = [ x0, ",", y0, "L", d3_svg_lineDot4(d3_svg_lineBasisBezier3, px), ",", d3_svg_lineDot4(d3_svg_lineBasisBezier3, py) ]; points.push(points[n - 1]); while (++i <= n) { pi = points[i]; px.shift(); px.push(pi[0]); py.shift(); py.push(pi[1]); d3_svg_lineBasisBezier(path, px, py); } points.pop(); path.push("L", pi); return path.join(""); } function d3_svg_lineBasisOpen(points) { if (points.length < 4) return d3_svg_lineLinear(points); var path = [], i = -1, n = points.length, pi, px = [ 0 ], py = [ 0 ]; while (++i < 3) { pi = points[i]; px.push(pi[0]); py.push(pi[1]); } path.push(d3_svg_lineDot4(d3_svg_lineBasisBezier3, px) + "," + d3_svg_lineDot4(d3_svg_lineBasisBezier3, py)); --i; while (++i < n) { pi = points[i]; px.shift(); px.push(pi[0]); py.shift(); py.push(pi[1]); d3_svg_lineBasisBezier(path, px, py); } return path.join(""); } function d3_svg_lineBasisClosed(points) { var path, i = -1, n = points.length, m = n + 4, pi, px = [], py = []; while (++i < 4) { pi = points[i % n]; px.push(pi[0]); py.push(pi[1]); } path = [ d3_svg_lineDot4(d3_svg_lineBasisBezier3, px), ",", d3_svg_lineDot4(d3_svg_lineBasisBezier3, py) ]; --i; while (++i < m) { pi = points[i % n]; px.shift(); px.push(pi[0]); py.shift(); py.push(pi[1]); d3_svg_lineBasisBezier(path, px, py); } return path.join(""); } function d3_svg_lineBundle(points, tension) { var n = points.length - 1; if (n) { var x0 = points[0][0], y0 = points[0][1], dx = points[n][0] - x0, dy = points[n][1] - y0, i = -1, p, t; while (++i <= n) { p = points[i]; t = i / n; p[0] = tension * p[0] + (1 - tension) * (x0 + t * dx); p[1] = tension * p[1] + (1 - tension) * (y0 + t * dy); } } return d3_svg_lineBasis(points); } function d3_svg_lineDot4(a, b) { return a[0] * b[0] + a[1] * b[1] + a[2] * b[2] + a[3] * b[3]; } var d3_svg_lineBasisBezier1 = [ 0, 2 / 3, 1 / 3, 0 ], d3_svg_lineBasisBezier2 = [ 0, 1 / 3, 2 / 3, 0 ], d3_svg_lineBasisBezier3 = [ 0, 1 / 6, 2 / 3, 1 / 6 ]; function d3_svg_lineBasisBezier(path, x, y) { path.push("C", d3_svg_lineDot4(d3_svg_lineBasisBezier1, x), ",", d3_svg_lineDot4(d3_svg_lineBasisBezier1, y), ",", d3_svg_lineDot4(d3_svg_lineBasisBezier2, x), ",", d3_svg_lineDot4(d3_svg_lineBasisBezier2, y), ",", d3_svg_lineDot4(d3_svg_lineBasisBezier3, x), ",", d3_svg_lineDot4(d3_svg_lineBasisBezier3, y)); } function d3_svg_lineSlope(p0, p1) { return (p1[1] - p0[1]) / (p1[0] - p0[0]); } function d3_svg_lineFiniteDifferences(points) { var i = 0, j = points.length - 1, m = [], p0 = points[0], p1 = points[1], d = m[0] = d3_svg_lineSlope(p0, p1); while (++i < j) { m[i] = (d + (d = d3_svg_lineSlope(p0 = p1, p1 = points[i + 1]))) / 2; } m[i] = d; return m; } function d3_svg_lineMonotoneTangents(points) { var tangents = [], d, a, b, s, m = d3_svg_lineFiniteDifferences(points), i = -1, j = points.length - 1; while (++i < j) { d = d3_svg_lineSlope(points[i], points[i + 1]); if (abs(d) < ε) { m[i] = m[i + 1] = 0; } else { a = m[i] / d; b = m[i + 1] / d; s = a * a + b * b; if (s > 9) { s = d * 3 / Math.sqrt(s); m[i] = s * a; m[i + 1] = s * b; } } } i = -1; while (++i <= j) { s = (points[Math.min(j, i + 1)][0] - points[Math.max(0, i - 1)][0]) / (6 * (1 + m[i] * m[i])); tangents.push([ s || 0, m[i] * s || 0 ]); } return tangents; } function d3_svg_lineMonotone(points) { return points.length < 3 ? d3_svg_lineLinear(points) : points[0] + d3_svg_lineHermite(points, d3_svg_lineMonotoneTangents(points)); } d3.svg.line.radial = function() { var line = d3_svg_line(d3_svg_lineRadial); line.radius = line.x, delete line.x; line.angle = line.y, delete line.y; return line; }; function d3_svg_lineRadial(points) { var point, i = -1, n = points.length, r, a; while (++i < n) { point = points[i]; r = point[0]; a = point[1] - halfπ; point[0] = r * Math.cos(a); point[1] = r * Math.sin(a); } return points; } function d3_svg_area(projection) { var x0 = d3_geom_pointX, x1 = d3_geom_pointX, y0 = 0, y1 = d3_geom_pointY, defined = d3_true, interpolate = d3_svg_lineLinear, interpolateKey = interpolate.key, interpolateReverse = interpolate, L = "L", tension = .7; function area(data) { var segments = [], points0 = [], points1 = [], i = -1, n = data.length, d, fx0 = d3_functor(x0), fy0 = d3_functor(y0), fx1 = x0 === x1 ? function() { return x; } : d3_functor(x1), fy1 = y0 === y1 ? function() { return y; } : d3_functor(y1), x, y; function segment() { segments.push("M", interpolate(projection(points1), tension), L, interpolateReverse(projection(points0.reverse()), tension), "Z"); } while (++i < n) { if (defined.call(this, d = data[i], i)) { points0.push([ x = +fx0.call(this, d, i), y = +fy0.call(this, d, i) ]); points1.push([ +fx1.call(this, d, i), +fy1.call(this, d, i) ]); } else if (points0.length) { segment(); points0 = []; points1 = []; } } if (points0.length) segment(); return segments.length ? segments.join("") : null; } area.x = function(_) { if (!arguments.length) return x1; x0 = x1 = _; return area; }; area.x0 = function(_) { if (!arguments.length) return x0; x0 = _; return area; }; area.x1 = function(_) { if (!arguments.length) return x1; x1 = _; return area; }; area.y = function(_) { if (!arguments.length) return y1; y0 = y1 = _; return area; }; area.y0 = function(_) { if (!arguments.length) return y0; y0 = _; return area; }; area.y1 = function(_) { if (!arguments.length) return y1; y1 = _; return area; }; area.defined = function(_) { if (!arguments.length) return defined; defined = _; return area; }; area.interpolate = function(_) { if (!arguments.length) return interpolateKey; if (typeof _ === "function") interpolateKey = interpolate = _; else interpolateKey = (interpolate = d3_svg_lineInterpolators.get(_) || d3_svg_lineLinear).key; interpolateReverse = interpolate.reverse || interpolate; L = interpolate.closed ? "M" : "L"; return area; }; area.tension = function(_) { if (!arguments.length) return tension; tension = _; return area; }; return area; } d3_svg_lineStepBefore.reverse = d3_svg_lineStepAfter; d3_svg_lineStepAfter.reverse = d3_svg_lineStepBefore; d3.svg.area = function() { return d3_svg_area(d3_identity); }; d3.svg.area.radial = function() { var area = d3_svg_area(d3_svg_lineRadial); area.radius = area.x, delete area.x; area.innerRadius = area.x0, delete area.x0; area.outerRadius = area.x1, delete area.x1; area.angle = area.y, delete area.y; area.startAngle = area.y0, delete area.y0; area.endAngle = area.y1, delete area.y1; return area; }; d3.svg.chord = function() { var source = d3_source, target = d3_target, radius = d3_svg_chordRadius, startAngle = d3_svg_arcStartAngle, endAngle = d3_svg_arcEndAngle; function chord(d, i) { var s = subgroup(this, source, d, i), t = subgroup(this, target, d, i); return "M" + s.p0 + arc(s.r, s.p1, s.a1 - s.a0) + (equals(s, t) ? curve(s.r, s.p1, s.r, s.p0) : curve(s.r, s.p1, t.r, t.p0) + arc(t.r, t.p1, t.a1 - t.a0) + curve(t.r, t.p1, s.r, s.p0)) + "Z"; } function subgroup(self, f, d, i) { var subgroup = f.call(self, d, i), r = radius.call(self, subgroup, i), a0 = startAngle.call(self, subgroup, i) - halfπ, a1 = endAngle.call(self, subgroup, i) - halfπ; return { r: r, a0: a0, a1: a1, p0: [ r * Math.cos(a0), r * Math.sin(a0) ], p1: [ r * Math.cos(a1), r * Math.sin(a1) ] }; } function equals(a, b) { return a.a0 == b.a0 && a.a1 == b.a1; } function arc(r, p, a) { return "A" + r + "," + r + " 0 " + +(a > π) + ",1 " + p; } function curve(r0, p0, r1, p1) { return "Q 0,0 " + p1; } chord.radius = function(v) { if (!arguments.length) return radius; radius = d3_functor(v); return chord; }; chord.source = function(v) { if (!arguments.length) return source; source = d3_functor(v); return chord; }; chord.target = function(v) { if (!arguments.length) return target; target = d3_functor(v); return chord; }; chord.startAngle = function(v) { if (!arguments.length) return startAngle; startAngle = d3_functor(v); return chord; }; chord.endAngle = function(v) { if (!arguments.length) return endAngle; endAngle = d3_functor(v); return chord; }; return chord; }; function d3_svg_chordRadius(d) { return d.radius; } d3.svg.diagonal = function() { var source = d3_source, target = d3_target, projection = d3_svg_diagonalProjection; function diagonal(d, i) { var p0 = source.call(this, d, i), p3 = target.call(this, d, i), m = (p0.y + p3.y) / 2, p = [ p0, { x: p0.x, y: m }, { x: p3.x, y: m }, p3 ]; p = p.map(projection); return "M" + p[0] + "C" + p[1] + " " + p[2] + " " + p[3]; } diagonal.source = function(x) { if (!arguments.length) return source; source = d3_functor(x); return diagonal; }; diagonal.target = function(x) { if (!arguments.length) return target; target = d3_functor(x); return diagonal; }; diagonal.projection = function(x) { if (!arguments.length) return projection; projection = x; return diagonal; }; return diagonal; }; function d3_svg_diagonalProjection(d) { return [ d.x, d.y ]; } d3.svg.diagonal.radial = function() { var diagonal = d3.svg.diagonal(), projection = d3_svg_diagonalProjection, projection_ = diagonal.projection; diagonal.projection = function(x) { return arguments.length ? projection_(d3_svg_diagonalRadialProjection(projection = x)) : projection; }; return diagonal; }; function d3_svg_diagonalRadialProjection(projection) { return function() { var d = projection.apply(this, arguments), r = d[0], a = d[1] - halfπ; return [ r * Math.cos(a), r * Math.sin(a) ]; }; } d3.svg.symbol = function() { var type = d3_svg_symbolType, size = d3_svg_symbolSize; function symbol(d, i) { return (d3_svg_symbols.get(type.call(this, d, i)) || d3_svg_symbolCircle)(size.call(this, d, i)); } symbol.type = function(x) { if (!arguments.length) return type; type = d3_functor(x); return symbol; }; symbol.size = function(x) { if (!arguments.length) return size; size = d3_functor(x); return symbol; }; return symbol; }; function d3_svg_symbolSize() { return 64; } function d3_svg_symbolType() { return "circle"; } function d3_svg_symbolCircle(size) { var r = Math.sqrt(size / π); return "M0," + r + "A" + r + "," + r + " 0 1,1 0," + -r + "A" + r + "," + r + " 0 1,1 0," + r + "Z"; } var d3_svg_symbols = d3.map({ circle: d3_svg_symbolCircle, cross: function(size) { var r = Math.sqrt(size / 5) / 2; return "M" + -3 * r + "," + -r + "H" + -r + "V" + -3 * r + "H" + r + "V" + -r + "H" + 3 * r + "V" + r + "H" + r + "V" + 3 * r + "H" + -r + "V" + r + "H" + -3 * r + "Z"; }, diamond: function(size) { var ry = Math.sqrt(size / (2 * d3_svg_symbolTan30)), rx = ry * d3_svg_symbolTan30; return "M0," + -ry + "L" + rx + ",0" + " 0," + ry + " " + -rx + ",0" + "Z"; }, square: function(size) { var r = Math.sqrt(size) / 2; return "M" + -r + "," + -r + "L" + r + "," + -r + " " + r + "," + r + " " + -r + "," + r + "Z"; }, "triangle-down": function(size) { var rx = Math.sqrt(size / d3_svg_symbolSqrt3), ry = rx * d3_svg_symbolSqrt3 / 2; return "M0," + ry + "L" + rx + "," + -ry + " " + -rx + "," + -ry + "Z"; }, "triangle-up": function(size) { var rx = Math.sqrt(size / d3_svg_symbolSqrt3), ry = rx * d3_svg_symbolSqrt3 / 2; return "M0," + -ry + "L" + rx + "," + ry + " " + -rx + "," + ry + "Z"; } }); d3.svg.symbolTypes = d3_svg_symbols.keys(); var d3_svg_symbolSqrt3 = Math.sqrt(3), d3_svg_symbolTan30 = Math.tan(30 * d3_radians); d3_selectionPrototype.transition = function(name) { var id = d3_transitionInheritId || ++d3_transitionId, ns = d3_transitionNamespace(name), subgroups = [], subgroup, node, transition = d3_transitionInherit || { time: Date.now(), ease: d3_ease_cubicInOut, delay: 0, duration: 250 }; for (var j = -1, m = this.length; ++j < m; ) { subgroups.push(subgroup = []); for (var group = this[j], i = -1, n = group.length; ++i < n; ) { if (node = group[i]) d3_transitionNode(node, i, ns, id, transition); subgroup.push(node); } } return d3_transition(subgroups, ns, id); }; d3_selectionPrototype.interrupt = function(name) { return this.each(name == null ? d3_selection_interrupt : d3_selection_interruptNS(d3_transitionNamespace(name))); }; var d3_selection_interrupt = d3_selection_interruptNS(d3_transitionNamespace()); function d3_selection_interruptNS(ns) { return function() { var lock, activeId, active; if ((lock = this[ns]) && (active = lock[activeId = lock.active])) { active.timer.c = null; active.timer.t = NaN; if (--lock.count) delete lock[activeId]; else delete this[ns]; lock.active += .5; active.event && active.event.interrupt.call(this, this.__data__, active.index); } }; } function d3_transition(groups, ns, id) { d3_subclass(groups, d3_transitionPrototype); groups.namespace = ns; groups.id = id; return groups; } var d3_transitionPrototype = [], d3_transitionId = 0, d3_transitionInheritId, d3_transitionInherit; d3_transitionPrototype.call = d3_selectionPrototype.call; d3_transitionPrototype.empty = d3_selectionPrototype.empty; d3_transitionPrototype.node = d3_selectionPrototype.node; d3_transitionPrototype.size = d3_selectionPrototype.size; d3.transition = function(selection, name) { return selection && selection.transition ? d3_transitionInheritId ? selection.transition(name) : selection : d3.selection().transition(selection); }; d3.transition.prototype = d3_transitionPrototype; d3_transitionPrototype.select = function(selector) { var id = this.id, ns = this.namespace, subgroups = [], subgroup, subnode, node; selector = d3_selection_selector(selector); for (var j = -1, m = this.length; ++j < m; ) { subgroups.push(subgroup = []); for (var group = this[j], i = -1, n = group.length; ++i < n; ) { if ((node = group[i]) && (subnode = selector.call(node, node.__data__, i, j))) { if ("__data__" in node) subnode.__data__ = node.__data__; d3_transitionNode(subnode, i, ns, id, node[ns][id]); subgroup.push(subnode); } else { subgroup.push(null); } } } return d3_transition(subgroups, ns, id); }; d3_transitionPrototype.selectAll = function(selector) { var id = this.id, ns = this.namespace, subgroups = [], subgroup, subnodes, node, subnode, transition; selector = d3_selection_selectorAll(selector); for (var j = -1, m = this.length; ++j < m; ) { for (var group = this[j], i = -1, n = group.length; ++i < n; ) { if (node = group[i]) { transition = node[ns][id]; subnodes = selector.call(node, node.__data__, i, j); subgroups.push(subgroup = []); for (var k = -1, o = subnodes.length; ++k < o; ) { if (subnode = subnodes[k]) d3_transitionNode(subnode, k, ns, id, transition); subgroup.push(subnode); } } } } return d3_transition(subgroups, ns, id); }; d3_transitionPrototype.filter = function(filter) { var subgroups = [], subgroup, group, node; if (typeof filter !== "function") filter = d3_selection_filter(filter); for (var j = 0, m = this.length; j < m; j++) { subgroups.push(subgroup = []); for (var group = this[j], i = 0, n = group.length; i < n; i++) { if ((node = group[i]) && filter.call(node, node.__data__, i, j)) { subgroup.push(node); } } } return d3_transition(subgroups, this.namespace, this.id); }; d3_transitionPrototype.tween = function(name, tween) { var id = this.id, ns = this.namespace; if (arguments.length < 2) return this.node()[ns][id].tween.get(name); return d3_selection_each(this, tween == null ? function(node) { node[ns][id].tween.remove(name); } : function(node) { node[ns][id].tween.set(name, tween); }); }; function d3_transition_tween(groups, name, value, tween) { var id = groups.id, ns = groups.namespace; return d3_selection_each(groups, typeof value === "function" ? function(node, i, j) { node[ns][id].tween.set(name, tween(value.call(node, node.__data__, i, j))); } : (value = tween(value), function(node) { node[ns][id].tween.set(name, value); })); } d3_transitionPrototype.attr = function(nameNS, value) { if (arguments.length < 2) { for (value in nameNS) this.attr(value, nameNS[value]); return this; } var interpolate = nameNS == "transform" ? d3_interpolateTransform : d3_interpolate, name = d3.ns.qualify(nameNS); function attrNull() { this.removeAttribute(name); } function attrNullNS() { this.removeAttributeNS(name.space, name.local); } function attrTween(b) { return b == null ? attrNull : (b += "", function() { var a = this.getAttribute(name), i; return a !== b && (i = interpolate(a, b), function(t) { this.setAttribute(name, i(t)); }); }); } function attrTweenNS(b) { return b == null ? attrNullNS : (b += "", function() { var a = this.getAttributeNS(name.space, name.local), i; return a !== b && (i = interpolate(a, b), function(t) { this.setAttributeNS(name.space, name.local, i(t)); }); }); } return d3_transition_tween(this, "attr." + nameNS, value, name.local ? attrTweenNS : attrTween); }; d3_transitionPrototype.attrTween = function(nameNS, tween) { var name = d3.ns.qualify(nameNS); function attrTween(d, i) { var f = tween.call(this, d, i, this.getAttribute(name)); return f && function(t) { this.setAttribute(name, f(t)); }; } function attrTweenNS(d, i) { var f = tween.call(this, d, i, this.getAttributeNS(name.space, name.local)); return f && function(t) { this.setAttributeNS(name.space, name.local, f(t)); }; } return this.tween("attr." + nameNS, name.local ? attrTweenNS : attrTween); }; d3_transitionPrototype.style = function(name, value, priority) { var n = arguments.length; if (n < 3) { if (typeof name !== "string") { if (n < 2) value = ""; for (priority in name) this.style(priority, name[priority], value); return this; } priority = ""; } function styleNull() { this.style.removeProperty(name); } function styleString(b) { return b == null ? styleNull : (b += "", function() { var a = d3_window(this).getComputedStyle(this, null).getPropertyValue(name), i; return a !== b && (i = d3_interpolate(a, b), function(t) { this.style.setProperty(name, i(t), priority); }); }); } return d3_transition_tween(this, "style." + name, value, styleString); }; d3_transitionPrototype.styleTween = function(name, tween, priority) { if (arguments.length < 3) priority = ""; function styleTween(d, i) { var f = tween.call(this, d, i, d3_window(this).getComputedStyle(this, null).getPropertyValue(name)); return f && function(t) { this.style.setProperty(name, f(t), priority); }; } return this.tween("style." + name, styleTween); }; d3_transitionPrototype.text = function(value) { return d3_transition_tween(this, "text", value, d3_transition_text); }; function d3_transition_text(b) { if (b == null) b = ""; return function() { this.textContent = b; }; } d3_transitionPrototype.remove = function() { var ns = this.namespace; return this.each("end.transition", function() { var p; if (this[ns].count < 2 && (p = this.parentNode)) p.removeChild(this); }); }; d3_transitionPrototype.ease = function(value) { var id = this.id, ns = this.namespace; if (arguments.length < 1) return this.node()[ns][id].ease; if (typeof value !== "function") value = d3.ease.apply(d3, arguments); return d3_selection_each(this, function(node) { node[ns][id].ease = value; }); }; d3_transitionPrototype.delay = function(value) { var id = this.id, ns = this.namespace; if (arguments.length < 1) return this.node()[ns][id].delay; return d3_selection_each(this, typeof value === "function" ? function(node, i, j) { node[ns][id].delay = +value.call(node, node.__data__, i, j); } : (value = +value, function(node) { node[ns][id].delay = value; })); }; d3_transitionPrototype.duration = function(value) { var id = this.id, ns = this.namespace; if (arguments.length < 1) return this.node()[ns][id].duration; return d3_selection_each(this, typeof value === "function" ? function(node, i, j) { node[ns][id].duration = Math.max(1, value.call(node, node.__data__, i, j)); } : (value = Math.max(1, value), function(node) { node[ns][id].duration = value; })); }; d3_transitionPrototype.each = function(type, listener) { var id = this.id, ns = this.namespace; if (arguments.length < 2) { var inherit = d3_transitionInherit, inheritId = d3_transitionInheritId; try { d3_transitionInheritId = id; d3_selection_each(this, function(node, i, j) { d3_transitionInherit = node[ns][id]; type.call(node, node.__data__, i, j); }); } finally { d3_transitionInherit = inherit; d3_transitionInheritId = inheritId; } } else { d3_selection_each(this, function(node) { var transition = node[ns][id]; (transition.event || (transition.event = d3.dispatch("start", "end", "interrupt"))).on(type, listener); }); } return this; }; d3_transitionPrototype.transition = function() { var id0 = this.id, id1 = ++d3_transitionId, ns = this.namespace, subgroups = [], subgroup, group, node, transition; for (var j = 0, m = this.length; j < m; j++) { subgroups.push(subgroup = []); for (var group = this[j], i = 0, n = group.length; i < n; i++) { if (node = group[i]) { transition = node[ns][id0]; d3_transitionNode(node, i, ns, id1, { time: transition.time, ease: transition.ease, delay: transition.delay + transition.duration, duration: transition.duration }); } subgroup.push(node); } } return d3_transition(subgroups, ns, id1); }; function d3_transitionNamespace(name) { return name == null ? "__transition__" : "__transition_" + name + "__"; } function d3_transitionNode(node, i, ns, id, inherit) { var lock = node[ns] || (node[ns] = { active: 0, count: 0 }), transition = lock[id], time, timer, duration, ease, tweens; function schedule(elapsed) { var delay = transition.delay; timer.t = delay + time; if (delay <= elapsed) return start(elapsed - delay); timer.c = start; } function start(elapsed) { var activeId = lock.active, active = lock[activeId]; if (active) { active.timer.c = null; active.timer.t = NaN; --lock.count; delete lock[activeId]; active.event && active.event.interrupt.call(node, node.__data__, active.index); } for (var cancelId in lock) { if (+cancelId < id) { var cancel = lock[cancelId]; cancel.timer.c = null; cancel.timer.t = NaN; --lock.count; delete lock[cancelId]; } } timer.c = tick; d3_timer(function() { if (timer.c && tick(elapsed || 1)) { timer.c = null; timer.t = NaN; } return 1; }, 0, time); lock.active = id; transition.event && transition.event.start.call(node, node.__data__, i); tweens = []; transition.tween.forEach(function(key, value) { if (value = value.call(node, node.__data__, i)) { tweens.push(value); } }); ease = transition.ease; duration = transition.duration; } function tick(elapsed) { var t = elapsed / duration, e = ease(t), n = tweens.length; while (n > 0) { tweens[--n].call(node, e); } if (t >= 1) { transition.event && transition.event.end.call(node, node.__data__, i); if (--lock.count) delete lock[id]; else delete node[ns]; return 1; } } if (!transition) { time = inherit.time; timer = d3_timer(schedule, 0, time); transition = lock[id] = { tween: new d3_Map(), time: time, timer: timer, delay: inherit.delay, duration: inherit.duration, ease: inherit.ease, index: i }; inherit = null; ++lock.count; } } d3.svg.axis = function() { var scale = d3.scale.linear(), orient = d3_svg_axisDefaultOrient, innerTickSize = 6, outerTickSize = 6, tickPadding = 3, tickArguments_ = [ 10 ], tickValues = null, tickFormat_; function axis(g) { g.each(function() { var g = d3.select(this); var scale0 = this.__chart__ || scale, scale1 = this.__chart__ = scale.copy(); var ticks = tickValues == null ? scale1.ticks ? scale1.ticks.apply(scale1, tickArguments_) : scale1.domain() : tickValues, tickFormat = tickFormat_ == null ? scale1.tickFormat ? scale1.tickFormat.apply(scale1, tickArguments_) : d3_identity : tickFormat_, tick = g.selectAll(".tick").data(ticks, scale1), tickEnter = tick.enter().insert("g", ".domain").attr("class", "tick").style("opacity", ε), tickExit = d3.transition(tick.exit()).style("opacity", ε).remove(), tickUpdate = d3.transition(tick.order()).style("opacity", 1), tickSpacing = Math.max(innerTickSize, 0) + tickPadding, tickTransform; var range = d3_scaleRange(scale1), path = g.selectAll(".domain").data([ 0 ]), pathUpdate = (path.enter().append("path").attr("class", "domain"), d3.transition(path)); tickEnter.append("line"); tickEnter.append("text"); var lineEnter = tickEnter.select("line"), lineUpdate = tickUpdate.select("line"), text = tick.select("text").text(tickFormat), textEnter = tickEnter.select("text"), textUpdate = tickUpdate.select("text"), sign = orient === "top" || orient === "left" ? -1 : 1, x1, x2, y1, y2; if (orient === "bottom" || orient === "top") { tickTransform = d3_svg_axisX, x1 = "x", y1 = "y", x2 = "x2", y2 = "y2"; text.attr("dy", sign < 0 ? "0em" : ".71em").style("text-anchor", "middle"); pathUpdate.attr("d", "M" + range[0] + "," + sign * outerTickSize + "V0H" + range[1] + "V" + sign * outerTickSize); } else { tickTransform = d3_svg_axisY, x1 = "y", y1 = "x", x2 = "y2", y2 = "x2"; text.attr("dy", ".32em").style("text-anchor", sign < 0 ? "end" : "start"); pathUpdate.attr("d", "M" + sign * outerTickSize + "," + range[0] + "H0V" + range[1] + "H" + sign * outerTickSize); } lineEnter.attr(y2, sign * innerTickSize); textEnter.attr(y1, sign * tickSpacing); lineUpdate.attr(x2, 0).attr(y2, sign * innerTickSize); textUpdate.attr(x1, 0).attr(y1, sign * tickSpacing); if (scale1.rangeBand) { var x = scale1, dx = x.rangeBand() / 2; scale0 = scale1 = function(d) { return x(d) + dx; }; } else if (scale0.rangeBand) { scale0 = scale1; } else { tickExit.call(tickTransform, scale1, scale0); } tickEnter.call(tickTransform, scale0, scale1); tickUpdate.call(tickTransform, scale1, scale1); }); } axis.scale = function(x) { if (!arguments.length) return scale; scale = x; return axis; }; axis.orient = function(x) { if (!arguments.length) return orient; orient = x in d3_svg_axisOrients ? x + "" : d3_svg_axisDefaultOrient; return axis; }; axis.ticks = function() { if (!arguments.length) return tickArguments_; tickArguments_ = d3_array(arguments); return axis; }; axis.tickValues = function(x) { if (!arguments.length) return tickValues; tickValues = x; return axis; }; axis.tickFormat = function(x) { if (!arguments.length) return tickFormat_; tickFormat_ = x; return axis; }; axis.tickSize = function(x) { var n = arguments.length; if (!n) return innerTickSize; innerTickSize = +x; outerTickSize = +arguments[n - 1]; return axis; }; axis.innerTickSize = function(x) { if (!arguments.length) return innerTickSize; innerTickSize = +x; return axis; }; axis.outerTickSize = function(x) { if (!arguments.length) return outerTickSize; outerTickSize = +x; return axis; }; axis.tickPadding = function(x) { if (!arguments.length) return tickPadding; tickPadding = +x; return axis; }; axis.tickSubdivide = function() { return arguments.length && axis; }; return axis; }; var d3_svg_axisDefaultOrient = "bottom", d3_svg_axisOrients = { top: 1, right: 1, bottom: 1, left: 1 }; function d3_svg_axisX(selection, x0, x1) { selection.attr("transform", function(d) { var v0 = x0(d); return "translate(" + (isFinite(v0) ? v0 : x1(d)) + ",0)"; }); } function d3_svg_axisY(selection, y0, y1) { selection.attr("transform", function(d) { var v0 = y0(d); return "translate(0," + (isFinite(v0) ? v0 : y1(d)) + ")"; }); } d3.svg.brush = function() { var event = d3_eventDispatch(brush, "brushstart", "brush", "brushend"), x = null, y = null, xExtent = [ 0, 0 ], yExtent = [ 0, 0 ], xExtentDomain, yExtentDomain, xClamp = true, yClamp = true, resizes = d3_svg_brushResizes[0]; function brush(g) { g.each(function() { var g = d3.select(this).style("pointer-events", "all").style("-webkit-tap-highlight-color", "rgba(0,0,0,0)").on("mousedown.brush", brushstart).on("touchstart.brush", brushstart); var background = g.selectAll(".background").data([ 0 ]); background.enter().append("rect").attr("class", "background").style("visibility", "hidden").style("cursor", "crosshair"); g.selectAll(".extent").data([ 0 ]).enter().append("rect").attr("class", "extent").style("cursor", "move"); var resize = g.selectAll(".resize").data(resizes, d3_identity); resize.exit().remove(); resize.enter().append("g").attr("class", function(d) { return "resize " + d; }).style("cursor", function(d) { return d3_svg_brushCursor[d]; }).append("rect").attr("x", function(d) { return /[ew]$/.test(d) ? -3 : null; }).attr("y", function(d) { return /^[ns]/.test(d) ? -3 : null; }).attr("width", 6).attr("height", 6).style("visibility", "hidden"); resize.style("display", brush.empty() ? "none" : null); var gUpdate = d3.transition(g), backgroundUpdate = d3.transition(background), range; if (x) { range = d3_scaleRange(x); backgroundUpdate.attr("x", range[0]).attr("width", range[1] - range[0]); redrawX(gUpdate); } if (y) { range = d3_scaleRange(y); backgroundUpdate.attr("y", range[0]).attr("height", range[1] - range[0]); redrawY(gUpdate); } redraw(gUpdate); }); } brush.event = function(g) { g.each(function() { var event_ = event.of(this, arguments), extent1 = { x: xExtent, y: yExtent, i: xExtentDomain, j: yExtentDomain }, extent0 = this.__chart__ || extent1; this.__chart__ = extent1; if (d3_transitionInheritId) { d3.select(this).transition().each("start.brush", function() { xExtentDomain = extent0.i; yExtentDomain = extent0.j; xExtent = extent0.x; yExtent = extent0.y; event_({ type: "brushstart" }); }).tween("brush:brush", function() { var xi = d3_interpolateArray(xExtent, extent1.x), yi = d3_interpolateArray(yExtent, extent1.y); xExtentDomain = yExtentDomain = null; return function(t) { xExtent = extent1.x = xi(t); yExtent = extent1.y = yi(t); event_({ type: "brush", mode: "resize" }); }; }).each("end.brush", function() { xExtentDomain = extent1.i; yExtentDomain = extent1.j; event_({ type: "brush", mode: "resize" }); event_({ type: "brushend" }); }); } else { event_({ type: "brushstart" }); event_({ type: "brush", mode: "resize" }); event_({ type: "brushend" }); } }); }; function redraw(g) { g.selectAll(".resize").attr("transform", function(d) { return "translate(" + xExtent[+/e$/.test(d)] + "," + yExtent[+/^s/.test(d)] + ")"; }); } function redrawX(g) { g.select(".extent").attr("x", xExtent[0]); g.selectAll(".extent,.n>rect,.s>rect").attr("width", xExtent[1] - xExtent[0]); } function redrawY(g) { g.select(".extent").attr("y", yExtent[0]); g.selectAll(".extent,.e>rect,.w>rect").attr("height", yExtent[1] - yExtent[0]); } function brushstart() { var target = this, eventTarget = d3.select(d3.event.target), event_ = event.of(target, arguments), g = d3.select(target), resizing = eventTarget.datum(), resizingX = !/^(n|s)$/.test(resizing) && x, resizingY = !/^(e|w)$/.test(resizing) && y, dragging = eventTarget.classed("extent"), dragRestore = d3_event_dragSuppress(target), center, origin = d3.mouse(target), offset; var w = d3.select(d3_window(target)).on("keydown.brush", keydown).on("keyup.brush", keyup); if (d3.event.changedTouches) { w.on("touchmove.brush", brushmove).on("touchend.brush", brushend); } else { w.on("mousemove.brush", brushmove).on("mouseup.brush", brushend); } g.interrupt().selectAll("*").interrupt(); if (dragging) { origin[0] = xExtent[0] - origin[0]; origin[1] = yExtent[0] - origin[1]; } else if (resizing) { var ex = +/w$/.test(resizing), ey = +/^n/.test(resizing); offset = [ xExtent[1 - ex] - origin[0], yExtent[1 - ey] - origin[1] ]; origin[0] = xExtent[ex]; origin[1] = yExtent[ey]; } else if (d3.event.altKey) center = origin.slice(); g.style("pointer-events", "none").selectAll(".resize").style("display", null); d3.select("body").style("cursor", eventTarget.style("cursor")); event_({ type: "brushstart" }); brushmove(); function keydown() { if (d3.event.keyCode == 32) { if (!dragging) { center = null; origin[0] -= xExtent[1]; origin[1] -= yExtent[1]; dragging = 2; } d3_eventPreventDefault(); } } function keyup() { if (d3.event.keyCode == 32 && dragging == 2) { origin[0] += xExtent[1]; origin[1] += yExtent[1]; dragging = 0; d3_eventPreventDefault(); } } function brushmove() { var point = d3.mouse(target), moved = false; if (offset) { point[0] += offset[0]; point[1] += offset[1]; } if (!dragging) { if (d3.event.altKey) { if (!center) center = [ (xExtent[0] + xExtent[1]) / 2, (yExtent[0] + yExtent[1]) / 2 ]; origin[0] = xExtent[+(point[0] < center[0])]; origin[1] = yExtent[+(point[1] < center[1])]; } else center = null; } if (resizingX && move1(point, x, 0)) { redrawX(g); moved = true; } if (resizingY && move1(point, y, 1)) { redrawY(g); moved = true; } if (moved) { redraw(g); event_({ type: "brush", mode: dragging ? "move" : "resize" }); } } function move1(point, scale, i) { var range = d3_scaleRange(scale), r0 = range[0], r1 = range[1], position = origin[i], extent = i ? yExtent : xExtent, size = extent[1] - extent[0], min, max; if (dragging) { r0 -= position; r1 -= size + position; } min = (i ? yClamp : xClamp) ? Math.max(r0, Math.min(r1, point[i])) : point[i]; if (dragging) { max = (min += position) + size; } else { if (center) position = Math.max(r0, Math.min(r1, 2 * center[i] - min)); if (position < min) { max = min; min = position; } else { max = position; } } if (extent[0] != min || extent[1] != max) { if (i) yExtentDomain = null; else xExtentDomain = null; extent[0] = min; extent[1] = max; return true; } } function brushend() { brushmove(); g.style("pointer-events", "all").selectAll(".resize").style("display", brush.empty() ? "none" : null); d3.select("body").style("cursor", null); w.on("mousemove.brush", null).on("mouseup.brush", null).on("touchmove.brush", null).on("touchend.brush", null).on("keydown.brush", null).on("keyup.brush", null); dragRestore(); event_({ type: "brushend" }); } } brush.x = function(z) { if (!arguments.length) return x; x = z; resizes = d3_svg_brushResizes[!x << 1 | !y]; return brush; }; brush.y = function(z) { if (!arguments.length) return y; y = z; resizes = d3_svg_brushResizes[!x << 1 | !y]; return brush; }; brush.clamp = function(z) { if (!arguments.length) return x && y ? [ xClamp, yClamp ] : x ? xClamp : y ? yClamp : null; if (x && y) xClamp = !!z[0], yClamp = !!z[1]; else if (x) xClamp = !!z; else if (y) yClamp = !!z; return brush; }; brush.extent = function(z) { var x0, x1, y0, y1, t; if (!arguments.length) { if (x) { if (xExtentDomain) { x0 = xExtentDomain[0], x1 = xExtentDomain[1]; } else { x0 = xExtent[0], x1 = xExtent[1]; if (x.invert) x0 = x.invert(x0), x1 = x.invert(x1); if (x1 < x0) t = x0, x0 = x1, x1 = t; } } if (y) { if (yExtentDomain) { y0 = yExtentDomain[0], y1 = yExtentDomain[1]; } else { y0 = yExtent[0], y1 = yExtent[1]; if (y.invert) y0 = y.invert(y0), y1 = y.invert(y1); if (y1 < y0) t = y0, y0 = y1, y1 = t; } } return x && y ? [ [ x0, y0 ], [ x1, y1 ] ] : x ? [ x0, x1 ] : y && [ y0, y1 ]; } if (x) { x0 = z[0], x1 = z[1]; if (y) x0 = x0[0], x1 = x1[0]; xExtentDomain = [ x0, x1 ]; if (x.invert) x0 = x(x0), x1 = x(x1); if (x1 < x0) t = x0, x0 = x1, x1 = t; if (x0 != xExtent[0] || x1 != xExtent[1]) xExtent = [ x0, x1 ]; } if (y) { y0 = z[0], y1 = z[1]; if (x) y0 = y0[1], y1 = y1[1]; yExtentDomain = [ y0, y1 ]; if (y.invert) y0 = y(y0), y1 = y(y1); if (y1 < y0) t = y0, y0 = y1, y1 = t; if (y0 != yExtent[0] || y1 != yExtent[1]) yExtent = [ y0, y1 ]; } return brush; }; brush.clear = function() { if (!brush.empty()) { xExtent = [ 0, 0 ], yExtent = [ 0, 0 ]; xExtentDomain = yExtentDomain = null; } return brush; }; brush.empty = function() { return !!x && xExtent[0] == xExtent[1] || !!y && yExtent[0] == yExtent[1]; }; return d3.rebind(brush, event, "on"); }; var d3_svg_brushCursor = { n: "ns-resize", e: "ew-resize", s: "ns-resize", w: "ew-resize", nw: "nwse-resize", ne: "nesw-resize", se: "nwse-resize", sw: "nesw-resize" }; var d3_svg_brushResizes = [ [ "n", "e", "s", "w", "nw", "ne", "se", "sw" ], [ "e", "w" ], [ "n", "s" ], [] ]; var d3_time_format = d3_time.format = d3_locale_enUS.timeFormat; var d3_time_formatUtc = d3_time_format.utc; var d3_time_formatIso = d3_time_formatUtc("%Y-%m-%dT%H:%M:%S.%LZ"); d3_time_format.iso = Date.prototype.toISOString && +new Date("2000-01-01T00:00:00.000Z") ? d3_time_formatIsoNative : d3_time_formatIso; function d3_time_formatIsoNative(date) { return date.toISOString(); } d3_time_formatIsoNative.parse = function(string) { var date = new Date(string); return isNaN(date) ? null : date; }; d3_time_formatIsoNative.toString = d3_time_formatIso.toString; d3_time.second = d3_time_interval(function(date) { return new d3_date(Math.floor(date / 1e3) * 1e3); }, function(date, offset) { date.setTime(date.getTime() + Math.floor(offset) * 1e3); }, function(date) { return date.getSeconds(); }); d3_time.seconds = d3_time.second.range; d3_time.seconds.utc = d3_time.second.utc.range; d3_time.minute = d3_time_interval(function(date) { return new d3_date(Math.floor(date / 6e4) * 6e4); }, function(date, offset) { date.setTime(date.getTime() + Math.floor(offset) * 6e4); }, function(date) { return date.getMinutes(); }); d3_time.minutes = d3_time.minute.range; d3_time.minutes.utc = d3_time.minute.utc.range; d3_time.hour = d3_time_interval(function(date) { var timezone = date.getTimezoneOffset() / 60; return new d3_date((Math.floor(date / 36e5 - timezone) + timezone) * 36e5); }, function(date, offset) { date.setTime(date.getTime() + Math.floor(offset) * 36e5); }, function(date) { return date.getHours(); }); d3_time.hours = d3_time.hour.range; d3_time.hours.utc = d3_time.hour.utc.range; d3_time.month = d3_time_interval(function(date) { date = d3_time.day(date); date.setDate(1); return date; }, function(date, offset) { date.setMonth(date.getMonth() + offset); }, function(date) { return date.getMonth(); }); d3_time.months = d3_time.month.range; d3_time.months.utc = d3_time.month.utc.range; function d3_time_scale(linear, methods, format) { function scale(x) { return linear(x); } scale.invert = function(x) { return d3_time_scaleDate(linear.invert(x)); }; scale.domain = function(x) { if (!arguments.length) return linear.domain().map(d3_time_scaleDate); linear.domain(x); return scale; }; function tickMethod(extent, count) { var span = extent[1] - extent[0], target = span / count, i = d3.bisect(d3_time_scaleSteps, target); return i == d3_time_scaleSteps.length ? [ methods.year, d3_scale_linearTickRange(extent.map(function(d) { return d / 31536e6; }), count)[2] ] : !i ? [ d3_time_scaleMilliseconds, d3_scale_linearTickRange(extent, count)[2] ] : methods[target / d3_time_scaleSteps[i - 1] < d3_time_scaleSteps[i] / target ? i - 1 : i]; } scale.nice = function(interval, skip) { var domain = scale.domain(), extent = d3_scaleExtent(domain), method = interval == null ? tickMethod(extent, 10) : typeof interval === "number" && tickMethod(extent, interval); if (method) interval = method[0], skip = method[1]; function skipped(date) { return !isNaN(date) && !interval.range(date, d3_time_scaleDate(+date + 1), skip).length; } return scale.domain(d3_scale_nice(domain, skip > 1 ? { floor: function(date) { while (skipped(date = interval.floor(date))) date = d3_time_scaleDate(date - 1); return date; }, ceil: function(date) { while (skipped(date = interval.ceil(date))) date = d3_time_scaleDate(+date + 1); return date; } } : interval)); }; scale.ticks = function(interval, skip) { var extent = d3_scaleExtent(scale.domain()), method = interval == null ? tickMethod(extent, 10) : typeof interval === "number" ? tickMethod(extent, interval) : !interval.range && [ { range: interval }, skip ]; if (method) interval = method[0], skip = method[1]; return interval.range(extent[0], d3_time_scaleDate(+extent[1] + 1), skip < 1 ? 1 : skip); }; scale.tickFormat = function() { return format; }; scale.copy = function() { return d3_time_scale(linear.copy(), methods, format); }; return d3_scale_linearRebind(scale, linear); } function d3_time_scaleDate(t) { return new Date(t); } var d3_time_scaleSteps = [ 1e3, 5e3, 15e3, 3e4, 6e4, 3e5, 9e5, 18e5, 36e5, 108e5, 216e5, 432e5, 864e5, 1728e5, 6048e5, 2592e6, 7776e6, 31536e6 ]; var d3_time_scaleLocalMethods = [ [ d3_time.second, 1 ], [ d3_time.second, 5 ], [ d3_time.second, 15 ], [ d3_time.second, 30 ], [ d3_time.minute, 1 ], [ d3_time.minute, 5 ], [ d3_time.minute, 15 ], [ d3_time.minute, 30 ], [ d3_time.hour, 1 ], [ d3_time.hour, 3 ], [ d3_time.hour, 6 ], [ d3_time.hour, 12 ], [ d3_time.day, 1 ], [ d3_time.day, 2 ], [ d3_time.week, 1 ], [ d3_time.month, 1 ], [ d3_time.month, 3 ], [ d3_time.year, 1 ] ]; var d3_time_scaleLocalFormat = d3_time_format.multi([ [ ".%L", function(d) { return d.getMilliseconds(); } ], [ ":%S", function(d) { return d.getSeconds(); } ], [ "%I:%M", function(d) { return d.getMinutes(); } ], [ "%I %p", function(d) { return d.getHours(); } ], [ "%a %d", function(d) { return d.getDay() && d.getDate() != 1; } ], [ "%b %d", function(d) { return d.getDate() != 1; } ], [ "%B", function(d) { return d.getMonth(); } ], [ "%Y", d3_true ] ]); var d3_time_scaleMilliseconds = { range: function(start, stop, step) { return d3.range(Math.ceil(start / step) * step, +stop, step).map(d3_time_scaleDate); }, floor: d3_identity, ceil: d3_identity }; d3_time_scaleLocalMethods.year = d3_time.year; d3_time.scale = function() { return d3_time_scale(d3.scale.linear(), d3_time_scaleLocalMethods, d3_time_scaleLocalFormat); }; var d3_time_scaleUtcMethods = d3_time_scaleLocalMethods.map(function(m) { return [ m[0].utc, m[1] ]; }); var d3_time_scaleUtcFormat = d3_time_formatUtc.multi([ [ ".%L", function(d) { return d.getUTCMilliseconds(); } ], [ ":%S", function(d) { return d.getUTCSeconds(); } ], [ "%I:%M", function(d) { return d.getUTCMinutes(); } ], [ "%I %p", function(d) { return d.getUTCHours(); } ], [ "%a %d", function(d) { return d.getUTCDay() && d.getUTCDate() != 1; } ], [ "%b %d", function(d) { return d.getUTCDate() != 1; } ], [ "%B", function(d) { return d.getUTCMonth(); } ], [ "%Y", d3_true ] ]); d3_time_scaleUtcMethods.year = d3_time.year.utc; d3_time.scale.utc = function() { return d3_time_scale(d3.scale.linear(), d3_time_scaleUtcMethods, d3_time_scaleUtcFormat); }; d3.text = d3_xhrType(function(request) { return request.responseText; }); d3.json = function(url, callback) { return d3_xhr(url, "application/json", d3_json, callback); }; function d3_json(request) { return JSON.parse(request.responseText); } d3.html = function(url, callback) { return d3_xhr(url, "text/html", d3_html, callback); }; function d3_html(request) { var range = d3_document.createRange(); range.selectNode(d3_document.body); return range.createContextualFragment(request.responseText); } d3.xml = d3_xhrType(function(request) { return request.responseXML; }); if (true) this.d3 = d3, !(__WEBPACK_AMD_DEFINE_FACTORY__ = (d3), __WEBPACK_AMD_DEFINE_RESULT__ = (typeof __WEBPACK_AMD_DEFINE_FACTORY__ === 'function' ? (__WEBPACK_AMD_DEFINE_FACTORY__.call(exports, __webpack_require__, exports, module)) : __WEBPACK_AMD_DEFINE_FACTORY__), __WEBPACK_AMD_DEFINE_RESULT__ !== undefined && (module.exports = __WEBPACK_AMD_DEFINE_RESULT__)); else if (typeof module === "object" && module.exports) module.exports = d3; else this.d3 = d3; }(); /***/ }), /* 3 */ /***/ (function(module, exports, __webpack_require__) { 'use strict'; Object.defineProperty(exports, "__esModule", { value: true }); var _d = __webpack_require__(2); var _d2 = _interopRequireDefault(_d); function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { default: obj }; } function _toConsumableArray(arr) { if (Array.isArray(arr)) { for (var i = 0, arr2 = Array(arr.length); i < arr.length; i++) { arr2[i] = arr[i]; } return arr2; } else { return Array.from(arr); } } function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError("Cannot call a class as a function"); } } var Barchart = // svg: d3 object with the svg in question // exp_array: list of (feature_name, weight) function Barchart(svg, exp_array) { var two_sided = arguments.length > 2 && arguments[2] !== undefined ? arguments[2] : true; var titles = arguments.length > 3 && arguments[3] !== undefined ? arguments[3] : undefined; var colors = arguments.length > 4 && arguments[4] !== undefined ? arguments[4] : ['red', 'green']; var show_numbers = arguments.length > 5 && arguments[5] !== undefined ? arguments[5] : false; var bar_height = arguments.length > 6 && arguments[6] !== undefined ? arguments[6] : 5; _classCallCheck(this, Barchart); var svg_width = Math.min(600, parseInt(svg.style('width'))); var bar_width = two_sided ? svg_width / 2 : svg_width; if (titles === undefined) { titles = two_sided ? ['Cons', 'Pros'] : 'Pros'; } if (show_numbers) { bar_width = bar_width - 30; } var x_offset = two_sided ? svg_width / 2 : 10; // 13.1 is +- the width of W, the widest letter. if (two_sided && titles.length == 2) { svg.append('text').attr('x', svg_width / 4).attr('y', 15).attr('font-size', '20').attr('text-anchor', 'middle').style('fill', colors[0]).text(titles[0]); svg.append('text').attr('x', svg_width / 4 * 3).attr('y', 15).attr('font-size', '20').attr('text-anchor', 'middle').style('fill', colors[1]).text(titles[1]); } else { var pos = two_sided ? svg_width / 2 : x_offset; var anchor = two_sided ? 'middle' : 'begin'; svg.append('text').attr('x', pos).attr('y', 15).attr('font-size', '20').attr('text-anchor', anchor).text(titles); } var yshift = 20; var space_between_bars = 0; var text_height = 16; var space_between_bar_and_text = 3; var total_bar_height = text_height + space_between_bar_and_text + bar_height + space_between_bars; var total_height = total_bar_height * exp_array.length; this.svg_height = total_height + yshift; var yscale = _d2.default.scale.linear().domain([0, exp_array.length]).range([yshift, yshift + total_height]); var names = exp_array.map(function (v) { return v[0]; }); var weights = exp_array.map(function (v) { return v[1]; }); var max_weight = Math.max.apply(Math, _toConsumableArray(weights.map(function (v) { return Math.abs(v); }))); var xscale = _d2.default.scale.linear().domain([0, Math.max(1, max_weight)]).range([0, bar_width]); for (var i = 0; i < exp_array.length; ++i) { var name = names[i]; var weight = weights[i]; var size = xscale(Math.abs(weight)); var to_the_right = weight > 0 || !two_sided; var text = svg.append('text').attr('x', to_the_right ? x_offset + 2 : x_offset - 2).attr('y', yscale(i) + text_height).attr('text-anchor', to_the_right ? 'begin' : 'end').attr('font-size', '14').text(name); while (text.node().getBBox()['width'] + 1 > bar_width) { var cur_text = text.text().slice(0, text.text().length - 5); text.text(cur_text + '...'); if (text === '...') { break; } } var bar = svg.append('rect').attr('height', bar_height).attr('x', to_the_right ? x_offset : x_offset - size).attr('y', text_height + yscale(i) + space_between_bar_and_text) // + bar_height) .attr('width', size).style('fill', weight > 0 ? colors[1] : colors[0]); if (show_numbers) { var bartext = svg.append('text').attr('x', to_the_right ? x_offset + size + 1 : x_offset - size - 1).attr('text-anchor', weight > 0 || !two_sided ? 'begin' : 'end').attr('y', bar_height + yscale(i) + text_height + space_between_bar_and_text).attr('font-size', '10').text(Math.abs(weight).toFixed(2)); } } var line = svg.append("line").attr("x1", x_offset).attr("x2", x_offset).attr("y1", bar_height + yshift).attr("y2", Math.max(bar_height, yscale(exp_array.length))).style("stroke-width", 2).style("stroke", "black"); }; exports.default = Barchart; /***/ }), /* 4 */ /***/ (function(module, exports, __webpack_require__) { var __WEBPACK_AMD_DEFINE_RESULT__;/* WEBPACK VAR INJECTION */(function(global, module) {/** * @license * Lodash * Copyright JS Foundation and other contributors * Released under MIT license * Based on Underscore.js 1.8.3 * Copyright Jeremy Ashkenas, DocumentCloud and Investigative Reporters & Editors */ ;(function() { /** Used as a safe reference for `undefined` in pre-ES5 environments. */ var undefined; /** Used as the semantic version number. */ var VERSION = '4.17.11'; /** Used as the size to enable large array optimizations. */ var LARGE_ARRAY_SIZE = 200; /** Error message constants. */ var CORE_ERROR_TEXT = 'Unsupported core-js use. Try https://npms.io/search?q=ponyfill.', FUNC_ERROR_TEXT = 'Expected a function'; /** Used to stand-in for `undefined` hash values. */ var HASH_UNDEFINED = '__lodash_hash_undefined__'; /** Used as the maximum memoize cache size. */ var MAX_MEMOIZE_SIZE = 500; /** Used as the internal argument placeholder. */ var PLACEHOLDER = '__lodash_placeholder__'; /** Used to compose bitmasks for cloning. */ var CLONE_DEEP_FLAG = 1, CLONE_FLAT_FLAG = 2, CLONE_SYMBOLS_FLAG = 4; /** Used to compose bitmasks for value comparisons. */ var COMPARE_PARTIAL_FLAG = 1, COMPARE_UNORDERED_FLAG = 2; /** Used to compose bitmasks for function metadata. */ var WRAP_BIND_FLAG = 1, WRAP_BIND_KEY_FLAG = 2, WRAP_CURRY_BOUND_FLAG = 4, WRAP_CURRY_FLAG = 8, WRAP_CURRY_RIGHT_FLAG = 16, WRAP_PARTIAL_FLAG = 32, WRAP_PARTIAL_RIGHT_FLAG = 64, WRAP_ARY_FLAG = 128, WRAP_REARG_FLAG = 256, WRAP_FLIP_FLAG = 512; /** Used as default options for `_.truncate`. */ var DEFAULT_TRUNC_LENGTH = 30, DEFAULT_TRUNC_OMISSION = '...'; /** Used to detect hot functions by number of calls within a span of milliseconds. */ var HOT_COUNT = 800, HOT_SPAN = 16; /** Used to indicate the type of lazy iteratees. */ var LAZY_FILTER_FLAG = 1, LAZY_MAP_FLAG = 2, LAZY_WHILE_FLAG = 3; /** Used as references for various `Number` constants. */ var INFINITY = 1 / 0, MAX_SAFE_INTEGER = 9007199254740991, MAX_INTEGER = 1.7976931348623157e+308, NAN = 0 / 0; /** Used as references for the maximum length and index of an array. */ var MAX_ARRAY_LENGTH = 4294967295, MAX_ARRAY_INDEX = MAX_ARRAY_LENGTH - 1, HALF_MAX_ARRAY_LENGTH = MAX_ARRAY_LENGTH >>> 1; /** Used to associate wrap methods with their bit flags. */ var wrapFlags = [ ['ary', WRAP_ARY_FLAG], ['bind', WRAP_BIND_FLAG], ['bindKey', WRAP_BIND_KEY_FLAG], ['curry', WRAP_CURRY_FLAG], ['curryRight', WRAP_CURRY_RIGHT_FLAG], ['flip', WRAP_FLIP_FLAG], ['partial', WRAP_PARTIAL_FLAG], ['partialRight', WRAP_PARTIAL_RIGHT_FLAG], ['rearg', WRAP_REARG_FLAG] ]; /** `Object#toString` result references. */ var argsTag = '[object Arguments]', arrayTag = '[object Array]', asyncTag = '[object AsyncFunction]', boolTag = '[object Boolean]', dateTag = '[object Date]', domExcTag = '[object DOMException]', errorTag = '[object Error]', funcTag = '[object Function]', genTag = '[object GeneratorFunction]', mapTag = '[object Map]', numberTag = '[object Number]', nullTag = '[object Null]', objectTag = '[object Object]', promiseTag = '[object Promise]', proxyTag = '[object Proxy]', regexpTag = '[object RegExp]', setTag = '[object Set]', stringTag = '[object String]', symbolTag = '[object Symbol]', undefinedTag = '[object Undefined]', weakMapTag = '[object WeakMap]', weakSetTag = '[object WeakSet]'; var arrayBufferTag = '[object ArrayBuffer]', dataViewTag = '[object DataView]', float32Tag = '[object Float32Array]', float64Tag = '[object Float64Array]', int8Tag = '[object Int8Array]', int16Tag = '[object Int16Array]', int32Tag = '[object Int32Array]', uint8Tag = '[object Uint8Array]', uint8ClampedTag = '[object Uint8ClampedArray]', uint16Tag = '[object Uint16Array]', uint32Tag = '[object Uint32Array]'; /** Used to match empty string literals in compiled template source. */ var reEmptyStringLeading = /\b__p \+= '';/g, reEmptyStringMiddle = /\b(__p \+=) '' \+/g, reEmptyStringTrailing = /(__e\(.*?\)|\b__t\)) \+\n'';/g; /** Used to match HTML entities and HTML characters. */ var reEscapedHtml = /&(?:amp|lt|gt|quot|#39);/g, reUnescapedHtml = /[&<>"']/g, reHasEscapedHtml = RegExp(reEscapedHtml.source), reHasUnescapedHtml = RegExp(reUnescapedHtml.source); /** Used to match template delimiters. */ var reEscape = /<%-([\s\S]+?)%>/g, reEvaluate = /<%([\s\S]+?)%>/g, reInterpolate = /<%=([\s\S]+?)%>/g; /** Used to match property names within property paths. */ var reIsDeepProp = /\.|\[(?:[^[\]]*|(["'])(?:(?!\1)[^\\]|\\.)*?\1)\]/, reIsPlainProp = /^\w*$/, rePropName = /[^.[\]]+|\[(?:(-?\d+(?:\.\d+)?)|(["'])((?:(?!\2)[^\\]|\\.)*?)\2)\]|(?=(?:\.|\[\])(?:\.|\[\]|$))/g; /** * Used to match `RegExp` * [syntax characters](http://ecma-international.org/ecma-262/7.0/#sec-patterns). */ var reRegExpChar = /[\\^$.*+?()[\]{}|]/g, reHasRegExpChar = RegExp(reRegExpChar.source); /** Used to match leading and trailing whitespace. */ var reTrim = /^\s+|\s+$/g, reTrimStart = /^\s+/, reTrimEnd = /\s+$/; /** Used to match wrap detail comments. */ var reWrapComment = /\{(?:\n\/\* \[wrapped with .+\] \*\/)?\n?/, reWrapDetails = /\{\n\/\* \[wrapped with (.+)\] \*/, reSplitDetails = /,? & /; /** Used to match words composed of alphanumeric characters. */ var reAsciiWord = /[^\x00-\x2f\x3a-\x40\x5b-\x60\x7b-\x7f]+/g; /** Used to match backslashes in property paths. */ var reEscapeChar = /\\(\\)?/g; /** * Used to match * [ES template delimiters](http://ecma-international.org/ecma-262/7.0/#sec-template-literal-lexical-components). */ var reEsTemplate = /\$\{([^\\}]*(?:\\.[^\\}]*)*)\}/g; /** Used to match `RegExp` flags from their coerced string values. */ var reFlags = /\w*$/; /** Used to detect bad signed hexadecimal string values. */ var reIsBadHex = /^[-+]0x[0-9a-f]+$/i; /** Used to detect binary string values. */ var reIsBinary = /^0b[01]+$/i; /** Used to detect host constructors (Safari). */ var reIsHostCtor = /^\[object .+?Constructor\]$/; /** Used to detect octal string values. */ var reIsOctal = /^0o[0-7]+$/i; /** Used to detect unsigned integer values. */ var reIsUint = /^(?:0|[1-9]\d*)$/; /** Used to match Latin Unicode letters (excluding mathematical operators). */ var reLatin = /[\xc0-\xd6\xd8-\xf6\xf8-\xff\u0100-\u017f]/g; /** Used to ensure capturing order of template delimiters. */ var reNoMatch = /($^)/; /** Used to match unescaped characters in compiled string literals. */ var reUnescapedString = /['\n\r\u2028\u2029\\]/g; /** Used to compose unicode character classes. */ var rsAstralRange = '\\ud800-\\udfff', rsComboMarksRange = '\\u0300-\\u036f', reComboHalfMarksRange = '\\ufe20-\\ufe2f', rsComboSymbolsRange = '\\u20d0-\\u20ff', rsComboRange = rsComboMarksRange + reComboHalfMarksRange + rsComboSymbolsRange, rsDingbatRange = '\\u2700-\\u27bf', rsLowerRange = 'a-z\\xdf-\\xf6\\xf8-\\xff', rsMathOpRange = '\\xac\\xb1\\xd7\\xf7', rsNonCharRange = '\\x00-\\x2f\\x3a-\\x40\\x5b-\\x60\\x7b-\\xbf', rsPunctuationRange = '\\u2000-\\u206f', rsSpaceRange = ' \\t\\x0b\\f\\xa0\\ufeff\\n\\r\\u2028\\u2029\\u1680\\u180e\\u2000\\u2001\\u2002\\u2003\\u2004\\u2005\\u2006\\u2007\\u2008\\u2009\\u200a\\u202f\\u205f\\u3000', rsUpperRange = 'A-Z\\xc0-\\xd6\\xd8-\\xde', rsVarRange = '\\ufe0e\\ufe0f', rsBreakRange = rsMathOpRange + rsNonCharRange + rsPunctuationRange + rsSpaceRange; /** Used to compose unicode capture groups. */ var rsApos = "['\u2019]", rsAstral = '[' + rsAstralRange + ']', rsBreak = '[' + rsBreakRange + ']', rsCombo = '[' + rsComboRange + ']', rsDigits = '\\d+', rsDingbat = '[' + rsDingbatRange + ']', rsLower = '[' + rsLowerRange + ']', rsMisc = '[^' + rsAstralRange + rsBreakRange + rsDigits + rsDingbatRange + rsLowerRange + rsUpperRange + ']', rsFitz = '\\ud83c[\\udffb-\\udfff]', rsModifier = '(?:' + rsCombo + '|' + rsFitz + ')', rsNonAstral = '[^' + rsAstralRange + ']', rsRegional = '(?:\\ud83c[\\udde6-\\uddff]){2}', rsSurrPair = '[\\ud800-\\udbff][\\udc00-\\udfff]', rsUpper = '[' + rsUpperRange + ']', rsZWJ = '\\u200d'; /** Used to compose unicode regexes. */ var rsMiscLower = '(?:' + rsLower + '|' + rsMisc + ')', rsMiscUpper = '(?:' + rsUpper + '|' + rsMisc + ')', rsOptContrLower = '(?:' + rsApos + '(?:d|ll|m|re|s|t|ve))?', rsOptContrUpper = '(?:' + rsApos + '(?:D|LL|M|RE|S|T|VE))?', reOptMod = rsModifier + '?', rsOptVar = '[' + rsVarRange + ']?', rsOptJoin = '(?:' + rsZWJ + '(?:' + [rsNonAstral, rsRegional, rsSurrPair].join('|') + ')' + rsOptVar + reOptMod + ')*', rsOrdLower = '\\d*(?:1st|2nd|3rd|(?![123])\\dth)(?=\\b|[A-Z_])', rsOrdUpper = '\\d*(?:1ST|2ND|3RD|(?![123])\\dTH)(?=\\b|[a-z_])', rsSeq = rsOptVar + reOptMod + rsOptJoin, rsEmoji = '(?:' + [rsDingbat, rsRegional, rsSurrPair].join('|') + ')' + rsSeq, rsSymbol = '(?:' + [rsNonAstral + rsCombo + '?', rsCombo, rsRegional, rsSurrPair, rsAstral].join('|') + ')'; /** Used to match apostrophes. */ var reApos = RegExp(rsApos, 'g'); /** * Used to match [combining diacritical marks](https://en.wikipedia.org/wiki/Combining_Diacritical_Marks) and * [combining diacritical marks for symbols](https://en.wikipedia.org/wiki/Combining_Diacritical_Marks_for_Symbols). */ var reComboMark = RegExp(rsCombo, 'g'); /** Used to match [string symbols](https://mathiasbynens.be/notes/javascript-unicode). */ var reUnicode = RegExp(rsFitz + '(?=' + rsFitz + ')|' + rsSymbol + rsSeq, 'g'); /** Used to match complex or compound words. */ var reUnicodeWord = RegExp([ rsUpper + '?' + rsLower + '+' + rsOptContrLower + '(?=' + [rsBreak, rsUpper, '$'].join('|') + ')', rsMiscUpper + '+' + rsOptContrUpper + '(?=' + [rsBreak, rsUpper + rsMiscLower, '$'].join('|') + ')', rsUpper + '?' + rsMiscLower + '+' + rsOptContrLower, rsUpper + '+' + rsOptContrUpper, rsOrdUpper, rsOrdLower, rsDigits, rsEmoji ].join('|'), 'g'); /** Used to detect strings with [zero-width joiners or code points from the astral planes](http://eev.ee/blog/2015/09/12/dark-corners-of-unicode/). */ var reHasUnicode = RegExp('[' + rsZWJ + rsAstralRange + rsComboRange + rsVarRange + ']'); /** Used to detect strings that need a more robust regexp to match words. */ var reHasUnicodeWord = /[a-z][A-Z]|[A-Z]{2}[a-z]|[0-9][a-zA-Z]|[a-zA-Z][0-9]|[^a-zA-Z0-9 ]/; /** Used to assign default `context` object properties. */ var contextProps = [ 'Array', 'Buffer', 'DataView', 'Date', 'Error', 'Float32Array', 'Float64Array', 'Function', 'Int8Array', 'Int16Array', 'Int32Array', 'Map', 'Math', 'Object', 'Promise', 'RegExp', 'Set', 'String', 'Symbol', 'TypeError', 'Uint8Array', 'Uint8ClampedArray', 'Uint16Array', 'Uint32Array', 'WeakMap', '_', 'clearTimeout', 'isFinite', 'parseInt', 'setTimeout' ]; /** Used to make template sourceURLs easier to identify. */ var templateCounter = -1; /** Used to identify `toStringTag` values of typed arrays. */ var typedArrayTags = {}; typedArrayTags[float32Tag] = typedArrayTags[float64Tag] = typedArrayTags[int8Tag] = typedArrayTags[int16Tag] = typedArrayTags[int32Tag] = typedArrayTags[uint8Tag] = typedArrayTags[uint8ClampedTag] = typedArrayTags[uint16Tag] = typedArrayTags[uint32Tag] = true; typedArrayTags[argsTag] = typedArrayTags[arrayTag] = typedArrayTags[arrayBufferTag] = typedArrayTags[boolTag] = typedArrayTags[dataViewTag] = typedArrayTags[dateTag] = typedArrayTags[errorTag] = typedArrayTags[funcTag] = typedArrayTags[mapTag] = typedArrayTags[numberTag] = typedArrayTags[objectTag] = typedArrayTags[regexpTag] = typedArrayTags[setTag] = typedArrayTags[stringTag] = typedArrayTags[weakMapTag] = false; /** Used to identify `toStringTag` values supported by `_.clone`. */ var cloneableTags = {}; cloneableTags[argsTag] = cloneableTags[arrayTag] = cloneableTags[arrayBufferTag] = cloneableTags[dataViewTag] = cloneableTags[boolTag] = cloneableTags[dateTag] = cloneableTags[float32Tag] = cloneableTags[float64Tag] = cloneableTags[int8Tag] = cloneableTags[int16Tag] = cloneableTags[int32Tag] = cloneableTags[mapTag] = cloneableTags[numberTag] = cloneableTags[objectTag] = cloneableTags[regexpTag] = cloneableTags[setTag] = cloneableTags[stringTag] = cloneableTags[symbolTag] = cloneableTags[uint8Tag] = cloneableTags[uint8ClampedTag] = cloneableTags[uint16Tag] = cloneableTags[uint32Tag] = true; cloneableTags[errorTag] = cloneableTags[funcTag] = cloneableTags[weakMapTag] = false; /** Used to map Latin Unicode letters to basic Latin letters. */ var deburredLetters = { // Latin-1 Supplement block. '\xc0': 'A', '\xc1': 'A', '\xc2': 'A', '\xc3': 'A', '\xc4': 'A', '\xc5': 'A', '\xe0': 'a', '\xe1': 'a', '\xe2': 'a', '\xe3': 'a', '\xe4': 'a', '\xe5': 'a', '\xc7': 'C', '\xe7': 'c', '\xd0': 'D', '\xf0': 'd', '\xc8': 'E', '\xc9': 'E', '\xca': 'E', '\xcb': 'E', '\xe8': 'e', '\xe9': 'e', '\xea': 'e', '\xeb': 'e', '\xcc': 'I', '\xcd': 'I', '\xce': 'I', '\xcf': 'I', '\xec': 'i', '\xed': 'i', '\xee': 'i', '\xef': 'i', '\xd1': 'N', '\xf1': 'n', '\xd2': 'O', '\xd3': 'O', '\xd4': 'O', '\xd5': 'O', '\xd6': 'O', '\xd8': 'O', '\xf2': 'o', '\xf3': 'o', '\xf4': 'o', '\xf5': 'o', '\xf6': 'o', '\xf8': 'o', '\xd9': 'U', '\xda': 'U', '\xdb': 'U', '\xdc': 'U', '\xf9': 'u', '\xfa': 'u', '\xfb': 'u', '\xfc': 'u', '\xdd': 'Y', '\xfd': 'y', '\xff': 'y', '\xc6': 'Ae', '\xe6': 'ae', '\xde': 'Th', '\xfe': 'th', '\xdf': 'ss', // Latin Extended-A block. '\u0100': 'A', '\u0102': 'A', '\u0104': 'A', '\u0101': 'a', '\u0103': 'a', '\u0105': 'a', '\u0106': 'C', '\u0108': 'C', '\u010a': 'C', '\u010c': 'C', '\u0107': 'c', '\u0109': 'c', '\u010b': 'c', '\u010d': 'c', '\u010e': 'D', '\u0110': 'D', '\u010f': 'd', '\u0111': 'd', '\u0112': 'E', '\u0114': 'E', '\u0116': 'E', '\u0118': 'E', '\u011a': 'E', '\u0113': 'e', '\u0115': 'e', '\u0117': 'e', '\u0119': 'e', '\u011b': 'e', '\u011c': 'G', '\u011e': 'G', '\u0120': 'G', '\u0122': 'G', '\u011d': 'g', '\u011f': 'g', '\u0121': 'g', '\u0123': 'g', '\u0124': 'H', '\u0126': 'H', '\u0125': 'h', '\u0127': 'h', '\u0128': 'I', '\u012a': 'I', '\u012c': 'I', '\u012e': 'I', '\u0130': 'I', '\u0129': 'i', '\u012b': 'i', '\u012d': 'i', '\u012f': 'i', '\u0131': 'i', '\u0134': 'J', '\u0135': 'j', '\u0136': 'K', '\u0137': 'k', '\u0138': 'k', '\u0139': 'L', '\u013b': 'L', '\u013d': 'L', '\u013f': 'L', '\u0141': 'L', '\u013a': 'l', '\u013c': 'l', '\u013e': 'l', '\u0140': 'l', '\u0142': 'l', '\u0143': 'N', '\u0145': 'N', '\u0147': 'N', '\u014a': 'N', '\u0144': 'n', '\u0146': 'n', '\u0148': 'n', '\u014b': 'n', '\u014c': 'O', '\u014e': 'O', '\u0150': 'O', '\u014d': 'o', '\u014f': 'o', '\u0151': 'o', '\u0154': 'R', '\u0156': 'R', '\u0158': 'R', '\u0155': 'r', '\u0157': 'r', '\u0159': 'r', '\u015a': 'S', '\u015c': 'S', '\u015e': 'S', '\u0160': 'S', '\u015b': 's', '\u015d': 's', '\u015f': 's', '\u0161': 's', '\u0162': 'T', '\u0164': 'T', '\u0166': 'T', '\u0163': 't', '\u0165': 't', '\u0167': 't', '\u0168': 'U', '\u016a': 'U', '\u016c': 'U', '\u016e': 'U', '\u0170': 'U', '\u0172': 'U', '\u0169': 'u', '\u016b': 'u', '\u016d': 'u', '\u016f': 'u', '\u0171': 'u', '\u0173': 'u', '\u0174': 'W', '\u0175': 'w', '\u0176': 'Y', '\u0177': 'y', '\u0178': 'Y', '\u0179': 'Z', '\u017b': 'Z', '\u017d': 'Z', '\u017a': 'z', '\u017c': 'z', '\u017e': 'z', '\u0132': 'IJ', '\u0133': 'ij', '\u0152': 'Oe', '\u0153': 'oe', '\u0149': "'n", '\u017f': 's' }; /** Used to map characters to HTML entities. */ var htmlEscapes = { '&': '&', '<': '<', '>': '>', '"': '"', "'": ''' }; /** Used to map HTML entities to characters. */ var htmlUnescapes = { '&': '&', '<': '<', '>': '>', '"': '"', ''': "'" }; /** Used to escape characters for inclusion in compiled string literals. */ var stringEscapes = { '\\': '\\', "'": "'", '\n': 'n', '\r': 'r', '\u2028': 'u2028', '\u2029': 'u2029' }; /** Built-in method references without a dependency on `root`. */ var freeParseFloat = parseFloat, freeParseInt = parseInt; /** Detect free variable `global` from Node.js. */ var freeGlobal = typeof global == 'object' && global && global.Object === Object && global; /** Detect free variable `self`. */ var freeSelf = typeof self == 'object' && self && self.Object === Object && self; /** Used as a reference to the global object. */ var root = freeGlobal || freeSelf || Function('return this')(); /** Detect free variable `exports`. */ var freeExports = typeof exports == 'object' && exports && !exports.nodeType && exports; /** Detect free variable `module`. */ var freeModule = freeExports && typeof module == 'object' && module && !module.nodeType && module; /** Detect the popular CommonJS extension `module.exports`. */ var moduleExports = freeModule && freeModule.exports === freeExports; /** Detect free variable `process` from Node.js. */ var freeProcess = moduleExports && freeGlobal.process; /** Used to access faster Node.js helpers. */ var nodeUtil = (function() { try { // Use `util.types` for Node.js 10+. var types = freeModule && freeModule.require && freeModule.require('util').types; if (types) { return types; } // Legacy `process.binding('util')` for Node.js < 10. return freeProcess && freeProcess.binding && freeProcess.binding('util'); } catch (e) {} }()); /* Node.js helper references. */ var nodeIsArrayBuffer = nodeUtil && nodeUtil.isArrayBuffer, nodeIsDate = nodeUtil && nodeUtil.isDate, nodeIsMap = nodeUtil && nodeUtil.isMap, nodeIsRegExp = nodeUtil && nodeUtil.isRegExp, nodeIsSet = nodeUtil && nodeUtil.isSet, nodeIsTypedArray = nodeUtil && nodeUtil.isTypedArray; /*--------------------------------------------------------------------------*/ /** * A faster alternative to `Function#apply`, this function invokes `func` * with the `this` binding of `thisArg` and the arguments of `args`. * * @private * @param {Function} func The function to invoke. * @param {*} thisArg The `this` binding of `func`. * @param {Array} args The arguments to invoke `func` with. * @returns {*} Returns the result of `func`. */ function apply(func, thisArg, args) { switch (args.length) { case 0: return func.call(thisArg); case 1: return func.call(thisArg, args[0]); case 2: return func.call(thisArg, args[0], args[1]); case 3: return func.call(thisArg, args[0], args[1], args[2]); } return func.apply(thisArg, args); } /** * A specialized version of `baseAggregator` for arrays. * * @private * @param {Array} [array] The array to iterate over. * @param {Function} setter The function to set `accumulator` values. * @param {Function} iteratee The iteratee to transform keys. * @param {Object} accumulator The initial aggregated object. * @returns {Function} Returns `accumulator`. */ function arrayAggregator(array, setter, iteratee, accumulator) { var index = -1, length = array == null ? 0 : array.length; while (++index < length) { var value = array[index]; setter(accumulator, value, iteratee(value), array); } return accumulator; } /** * A specialized version of `_.forEach` for arrays without support for * iteratee shorthands. * * @private * @param {Array} [array] The array to iterate over. * @param {Function} iteratee The function invoked per iteration. * @returns {Array} Returns `array`. */ function arrayEach(array, iteratee) { var index = -1, length = array == null ? 0 : array.length; while (++index < length) { if (iteratee(array[index], index, array) === false) { break; } } return array; } /** * A specialized version of `_.forEachRight` for arrays without support for * iteratee shorthands. * * @private * @param {Array} [array] The array to iterate over. * @param {Function} iteratee The function invoked per iteration. * @returns {Array} Returns `array`. */ function arrayEachRight(array, iteratee) { var length = array == null ? 0 : array.length; while (length--) { if (iteratee(array[length], length, array) === false) { break; } } return array; } /** * A specialized version of `_.every` for arrays without support for * iteratee shorthands. * * @private * @param {Array} [array] The array to iterate over. * @param {Function} predicate The function invoked per iteration. * @returns {boolean} Returns `true` if all elements pass the predicate check, * else `false`. */ function arrayEvery(array, predicate) { var index = -1, length = array == null ? 0 : array.length; while (++index < length) { if (!predicate(array[index], index, array)) { return false; } } return true; } /** * A specialized version of `_.filter` for arrays without support for * iteratee shorthands. * * @private * @param {Array} [array] The array to iterate over. * @param {Function} predicate The function invoked per iteration. * @returns {Array} Returns the new filtered array. */ function arrayFilter(array, predicate) { var index = -1, length = array == null ? 0 : array.length, resIndex = 0, result = []; while (++index < length) { var value = array[index]; if (predicate(value, index, array)) { result[resIndex++] = value; } } return result; } /** * A specialized version of `_.includes` for arrays without support for * specifying an index to search from. * * @private * @param {Array} [array] The array to inspect. * @param {*} target The value to search for. * @returns {boolean} Returns `true` if `target` is found, else `false`. */ function arrayIncludes(array, value) { var length = array == null ? 0 : array.length; return !!length && baseIndexOf(array, value, 0) > -1; } /** * This function is like `arrayIncludes` except that it accepts a comparator. * * @private * @param {Array} [array] The array to inspect. * @param {*} target The value to search for. * @param {Function} comparator The comparator invoked per element. * @returns {boolean} Returns `true` if `target` is found, else `false`. */ function arrayIncludesWith(array, value, comparator) { var index = -1, length = array == null ? 0 : array.length; while (++index < length) { if (comparator(value, array[index])) { return true; } } return false; } /** * A specialized version of `_.map` for arrays without support for iteratee * shorthands. * * @private * @param {Array} [array] The array to iterate over. * @param {Function} iteratee The function invoked per iteration. * @returns {Array} Returns the new mapped array. */ function arrayMap(array, iteratee) { var index = -1, length = array == null ? 0 : array.length, result = Array(length); while (++index < length) { result[index] = iteratee(array[index], index, array); } return result; } /** * Appends the elements of `values` to `array`. * * @private * @param {Array} array The array to modify. * @param {Array} values The values to append. * @returns {Array} Returns `array`. */ function arrayPush(array, values) { var index = -1, length = values.length, offset = array.length; while (++index < length) { array[offset + index] = values[index]; } return array; } /** * A specialized version of `_.reduce` for arrays without support for * iteratee shorthands. * * @private * @param {Array} [array] The array to iterate over. * @param {Function} iteratee The function invoked per iteration. * @param {*} [accumulator] The initial value. * @param {boolean} [initAccum] Specify using the first element of `array` as * the initial value. * @returns {*} Returns the accumulated value. */ function arrayReduce(array, iteratee, accumulator, initAccum) { var index = -1, length = array == null ? 0 : array.length; if (initAccum && length) { accumulator = array[++index]; } while (++index < length) { accumulator = iteratee(accumulator, array[index], index, array); } return accumulator; } /** * A specialized version of `_.reduceRight` for arrays without support for * iteratee shorthands. * * @private * @param {Array} [array] The array to iterate over. * @param {Function} iteratee The function invoked per iteration. * @param {*} [accumulator] The initial value. * @param {boolean} [initAccum] Specify using the last element of `array` as * the initial value. * @returns {*} Returns the accumulated value. */ function arrayReduceRight(array, iteratee, accumulator, initAccum) { var length = array == null ? 0 : array.length; if (initAccum && length) { accumulator = array[--length]; } while (length--) { accumulator = iteratee(accumulator, array[length], length, array); } return accumulator; } /** * A specialized version of `_.some` for arrays without support for iteratee * shorthands. * * @private * @param {Array} [array] The array to iterate over. * @param {Function} predicate The function invoked per iteration. * @returns {boolean} Returns `true` if any element passes the predicate check, * else `false`. */ function arraySome(array, predicate) { var index = -1, length = array == null ? 0 : array.length; while (++index < length) { if (predicate(array[index], index, array)) { return true; } } return false; } /** * Gets the size of an ASCII `string`. * * @private * @param {string} string The string inspect. * @returns {number} Returns the string size. */ var asciiSize = baseProperty('length'); /** * Converts an ASCII `string` to an array. * * @private * @param {string} string The string to convert. * @returns {Array} Returns the converted array. */ function asciiToArray(string) { return string.split(''); } /** * Splits an ASCII `string` into an array of its words. * * @private * @param {string} The string to inspect. * @returns {Array} Returns the words of `string`. */ function asciiWords(string) { return string.match(reAsciiWord) || []; } /** * The base implementation of methods like `_.findKey` and `_.findLastKey`, * without support for iteratee shorthands, which iterates over `collection` * using `eachFunc`. * * @private * @param {Array|Object} collection The collection to inspect. * @param {Function} predicate The function invoked per iteration. * @param {Function} eachFunc The function to iterate over `collection`. * @returns {*} Returns the found element or its key, else `undefined`. */ function baseFindKey(collection, predicate, eachFunc) { var result; eachFunc(collection, function(value, key, collection) { if (predicate(value, key, collection)) { result = key; return false; } }); return result; } /** * The base implementation of `_.findIndex` and `_.findLastIndex` without * support for iteratee shorthands. * * @private * @param {Array} array The array to inspect. * @param {Function} predicate The function invoked per iteration. * @param {number} fromIndex The index to search from. * @param {boolean} [fromRight] Specify iterating from right to left. * @returns {number} Returns the index of the matched value, else `-1`. */ function baseFindIndex(array, predicate, fromIndex, fromRight) { var length = array.length, index = fromIndex + (fromRight ? 1 : -1); while ((fromRight ? index-- : ++index < length)) { if (predicate(array[index], index, array)) { return index; } } return -1; } /** * The base implementation of `_.indexOf` without `fromIndex` bounds checks. * * @private * @param {Array} array The array to inspect. * @param {*} value The value to search for. * @param {number} fromIndex The index to search from. * @returns {number} Returns the index of the matched value, else `-1`. */ function baseIndexOf(array, value, fromIndex) { return value === value ? strictIndexOf(array, value, fromIndex) : baseFindIndex(array, baseIsNaN, fromIndex); } /** * This function is like `baseIndexOf` except that it accepts a comparator. * * @private * @param {Array} array The array to inspect. * @param {*} value The value to search for. * @param {number} fromIndex The index to search from. * @param {Function} comparator The comparator invoked per element. * @returns {number} Returns the index of the matched value, else `-1`. */ function baseIndexOfWith(array, value, fromIndex, comparator) { var index = fromIndex - 1, length = array.length; while (++index < length) { if (comparator(array[index], value)) { return index; } } return -1; } /** * The base implementation of `_.isNaN` without support for number objects. * * @private * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is `NaN`, else `false`. */ function baseIsNaN(value) { return value !== value; } /** * The base implementation of `_.mean` and `_.meanBy` without support for * iteratee shorthands. * * @private * @param {Array} array The array to iterate over. * @param {Function} iteratee The function invoked per iteration. * @returns {number} Returns the mean. */ function baseMean(array, iteratee) { var length = array == null ? 0 : array.length; return length ? (baseSum(array, iteratee) / length) : NAN; } /** * The base implementation of `_.property` without support for deep paths. * * @private * @param {string} key The key of the property to get. * @returns {Function} Returns the new accessor function. */ function baseProperty(key) { return function(object) { return object == null ? undefined : object[key]; }; } /** * The base implementation of `_.propertyOf` without support for deep paths. * * @private * @param {Object} object The object to query. * @returns {Function} Returns the new accessor function. */ function basePropertyOf(object) { return function(key) { return object == null ? undefined : object[key]; }; } /** * The base implementation of `_.reduce` and `_.reduceRight`, without support * for iteratee shorthands, which iterates over `collection` using `eachFunc`. * * @private * @param {Array|Object} collection The collection to iterate over. * @param {Function} iteratee The function invoked per iteration. * @param {*} accumulator The initial value. * @param {boolean} initAccum Specify using the first or last element of * `collection` as the initial value. * @param {Function} eachFunc The function to iterate over `collection`. * @returns {*} Returns the accumulated value. */ function baseReduce(collection, iteratee, accumulator, initAccum, eachFunc) { eachFunc(collection, function(value, index, collection) { accumulator = initAccum ? (initAccum = false, value) : iteratee(accumulator, value, index, collection); }); return accumulator; } /** * The base implementation of `_.sortBy` which uses `comparer` to define the * sort order of `array` and replaces criteria objects with their corresponding * values. * * @private * @param {Array} array The array to sort. * @param {Function} comparer The function to define sort order. * @returns {Array} Returns `array`. */ function baseSortBy(array, comparer) { var length = array.length; array.sort(comparer); while (length--) { array[length] = array[length].value; } return array; } /** * The base implementation of `_.sum` and `_.sumBy` without support for * iteratee shorthands. * * @private * @param {Array} array The array to iterate over. * @param {Function} iteratee The function invoked per iteration. * @returns {number} Returns the sum. */ function baseSum(array, iteratee) { var result, index = -1, length = array.length; while (++index < length) { var current = iteratee(array[index]); if (current !== undefined) { result = result === undefined ? current : (result + current); } } return result; } /** * The base implementation of `_.times` without support for iteratee shorthands * or max array length checks. * * @private * @param {number} n The number of times to invoke `iteratee`. * @param {Function} iteratee The function invoked per iteration. * @returns {Array} Returns the array of results. */ function baseTimes(n, iteratee) { var index = -1, result = Array(n); while (++index < n) { result[index] = iteratee(index); } return result; } /** * The base implementation of `_.toPairs` and `_.toPairsIn` which creates an array * of key-value pairs for `object` corresponding to the property names of `props`. * * @private * @param {Object} object The object to query. * @param {Array} props The property names to get values for. * @returns {Object} Returns the key-value pairs. */ function baseToPairs(object, props) { return arrayMap(props, function(key) { return [key, object[key]]; }); } /** * The base implementation of `_.unary` without support for storing metadata. * * @private * @param {Function} func The function to cap arguments for. * @returns {Function} Returns the new capped function. */ function baseUnary(func) { return function(value) { return func(value); }; } /** * The base implementation of `_.values` and `_.valuesIn` which creates an * array of `object` property values corresponding to the property names * of `props`. * * @private * @param {Object} object The object to query. * @param {Array} props The property names to get values for. * @returns {Object} Returns the array of property values. */ function baseValues(object, props) { return arrayMap(props, function(key) { return object[key]; }); } /** * Checks if a `cache` value for `key` exists. * * @private * @param {Object} cache The cache to query. * @param {string} key The key of the entry to check. * @returns {boolean} Returns `true` if an entry for `key` exists, else `false`. */ function cacheHas(cache, key) { return cache.has(key); } /** * Used by `_.trim` and `_.trimStart` to get the index of the first string symbol * that is not found in the character symbols. * * @private * @param {Array} strSymbols The string symbols to inspect. * @param {Array} chrSymbols The character symbols to find. * @returns {number} Returns the index of the first unmatched string symbol. */ function charsStartIndex(strSymbols, chrSymbols) { var index = -1, length = strSymbols.length; while (++index < length && baseIndexOf(chrSymbols, strSymbols[index], 0) > -1) {} return index; } /** * Used by `_.trim` and `_.trimEnd` to get the index of the last string symbol * that is not found in the character symbols. * * @private * @param {Array} strSymbols The string symbols to inspect. * @param {Array} chrSymbols The character symbols to find. * @returns {number} Returns the index of the last unmatched string symbol. */ function charsEndIndex(strSymbols, chrSymbols) { var index = strSymbols.length; while (index-- && baseIndexOf(chrSymbols, strSymbols[index], 0) > -1) {} return index; } /** * Gets the number of `placeholder` occurrences in `array`. * * @private * @param {Array} array The array to inspect. * @param {*} placeholder The placeholder to search for. * @returns {number} Returns the placeholder count. */ function countHolders(array, placeholder) { var length = array.length, result = 0; while (length--) { if (array[length] === placeholder) { ++result; } } return result; } /** * Used by `_.deburr` to convert Latin-1 Supplement and Latin Extended-A * letters to basic Latin letters. * * @private * @param {string} letter The matched letter to deburr. * @returns {string} Returns the deburred letter. */ var deburrLetter = basePropertyOf(deburredLetters); /** * Used by `_.escape` to convert characters to HTML entities. * * @private * @param {string} chr The matched character to escape. * @returns {string} Returns the escaped character. */ var escapeHtmlChar = basePropertyOf(htmlEscapes); /** * Used by `_.template` to escape characters for inclusion in compiled string literals. * * @private * @param {string} chr The matched character to escape. * @returns {string} Returns the escaped character. */ function escapeStringChar(chr) { return '\\' + stringEscapes[chr]; } /** * Gets the value at `key` of `object`. * * @private * @param {Object} [object] The object to query. * @param {string} key The key of the property to get. * @returns {*} Returns the property value. */ function getValue(object, key) { return object == null ? undefined : object[key]; } /** * Checks if `string` contains Unicode symbols. * * @private * @param {string} string The string to inspect. * @returns {boolean} Returns `true` if a symbol is found, else `false`. */ function hasUnicode(string) { return reHasUnicode.test(string); } /** * Checks if `string` contains a word composed of Unicode symbols. * * @private * @param {string} string The string to inspect. * @returns {boolean} Returns `true` if a word is found, else `false`. */ function hasUnicodeWord(string) { return reHasUnicodeWord.test(string); } /** * Converts `iterator` to an array. * * @private * @param {Object} iterator The iterator to convert. * @returns {Array} Returns the converted array. */ function iteratorToArray(iterator) { var data, result = []; while (!(data = iterator.next()).done) { result.push(data.value); } return result; } /** * Converts `map` to its key-value pairs. * * @private * @param {Object} map The map to convert. * @returns {Array} Returns the key-value pairs. */ function mapToArray(map) { var index = -1, result = Array(map.size); map.forEach(function(value, key) { result[++index] = [key, value]; }); return result; } /** * Creates a unary function that invokes `func` with its argument transformed. * * @private * @param {Function} func The function to wrap. * @param {Function} transform The argument transform. * @returns {Function} Returns the new function. */ function overArg(func, transform) { return function(arg) { return func(transform(arg)); }; } /** * Replaces all `placeholder` elements in `array` with an internal placeholder * and returns an array of their indexes. * * @private * @param {Array} array The array to modify. * @param {*} placeholder The placeholder to replace. * @returns {Array} Returns the new array of placeholder indexes. */ function replaceHolders(array, placeholder) { var index = -1, length = array.length, resIndex = 0, result = []; while (++index < length) { var value = array[index]; if (value === placeholder || value === PLACEHOLDER) { array[index] = PLACEHOLDER; result[resIndex++] = index; } } return result; } /** * Converts `set` to an array of its values. * * @private * @param {Object} set The set to convert. * @returns {Array} Returns the values. */ function setToArray(set) { var index = -1, result = Array(set.size); set.forEach(function(value) { result[++index] = value; }); return result; } /** * Converts `set` to its value-value pairs. * * @private * @param {Object} set The set to convert. * @returns {Array} Returns the value-value pairs. */ function setToPairs(set) { var index = -1, result = Array(set.size); set.forEach(function(value) { result[++index] = [value, value]; }); return result; } /** * A specialized version of `_.indexOf` which performs strict equality * comparisons of values, i.e. `===`. * * @private * @param {Array} array The array to inspect. * @param {*} value The value to search for. * @param {number} fromIndex The index to search from. * @returns {number} Returns the index of the matched value, else `-1`. */ function strictIndexOf(array, value, fromIndex) { var index = fromIndex - 1, length = array.length; while (++index < length) { if (array[index] === value) { return index; } } return -1; } /** * A specialized version of `_.lastIndexOf` which performs strict equality * comparisons of values, i.e. `===`. * * @private * @param {Array} array The array to inspect. * @param {*} value The value to search for. * @param {number} fromIndex The index to search from. * @returns {number} Returns the index of the matched value, else `-1`. */ function strictLastIndexOf(array, value, fromIndex) { var index = fromIndex + 1; while (index--) { if (array[index] === value) { return index; } } return index; } /** * Gets the number of symbols in `string`. * * @private * @param {string} string The string to inspect. * @returns {number} Returns the string size. */ function stringSize(string) { return hasUnicode(string) ? unicodeSize(string) : asciiSize(string); } /** * Converts `string` to an array. * * @private * @param {string} string The string to convert. * @returns {Array} Returns the converted array. */ function stringToArray(string) { return hasUnicode(string) ? unicodeToArray(string) : asciiToArray(string); } /** * Used by `_.unescape` to convert HTML entities to characters. * * @private * @param {string} chr The matched character to unescape. * @returns {string} Returns the unescaped character. */ var unescapeHtmlChar = basePropertyOf(htmlUnescapes); /** * Gets the size of a Unicode `string`. * * @private * @param {string} string The string inspect. * @returns {number} Returns the string size. */ function unicodeSize(string) { var result = reUnicode.lastIndex = 0; while (reUnicode.test(string)) { ++result; } return result; } /** * Converts a Unicode `string` to an array. * * @private * @param {string} string The string to convert. * @returns {Array} Returns the converted array. */ function unicodeToArray(string) { return string.match(reUnicode) || []; } /** * Splits a Unicode `string` into an array of its words. * * @private * @param {string} The string to inspect. * @returns {Array} Returns the words of `string`. */ function unicodeWords(string) { return string.match(reUnicodeWord) || []; } /*--------------------------------------------------------------------------*/ /** * Create a new pristine `lodash` function using the `context` object. * * @static * @memberOf _ * @since 1.1.0 * @category Util * @param {Object} [context=root] The context object. * @returns {Function} Returns a new `lodash` function. * @example * * _.mixin({ 'foo': _.constant('foo') }); * * var lodash = _.runInContext(); * lodash.mixin({ 'bar': lodash.constant('bar') }); * * _.isFunction(_.foo); * // => true * _.isFunction(_.bar); * // => false * * lodash.isFunction(lodash.foo); * // => false * lodash.isFunction(lodash.bar); * // => true * * // Create a suped-up `defer` in Node.js. * var defer = _.runInContext({ 'setTimeout': setImmediate }).defer; */ var runInContext = (function runInContext(context) { context = context == null ? root : _.defaults(root.Object(), context, _.pick(root, contextProps)); /** Built-in constructor references. */ var Array = context.Array, Date = context.Date, Error = context.Error, Function = context.Function, Math = context.Math, Object = context.Object, RegExp = context.RegExp, String = context.String, TypeError = context.TypeError; /** Used for built-in method references. */ var arrayProto = Array.prototype, funcProto = Function.prototype, objectProto = Object.prototype; /** Used to detect overreaching core-js shims. */ var coreJsData = context['__core-js_shared__']; /** Used to resolve the decompiled source of functions. */ var funcToString = funcProto.toString; /** Used to check objects for own properties. */ var hasOwnProperty = objectProto.hasOwnProperty; /** Used to generate unique IDs. */ var idCounter = 0; /** Used to detect methods masquerading as native. */ var maskSrcKey = (function() { var uid = /[^.]+$/.exec(coreJsData && coreJsData.keys && coreJsData.keys.IE_PROTO || ''); return uid ? ('Symbol(src)_1.' + uid) : ''; }()); /** * Used to resolve the * [`toStringTag`](http://ecma-international.org/ecma-262/7.0/#sec-object.prototype.tostring) * of values. */ var nativeObjectToString = objectProto.toString; /** Used to infer the `Object` constructor. */ var objectCtorString = funcToString.call(Object); /** Used to restore the original `_` reference in `_.noConflict`. */ var oldDash = root._; /** Used to detect if a method is native. */ var reIsNative = RegExp('^' + funcToString.call(hasOwnProperty).replace(reRegExpChar, '\\$&') .replace(/hasOwnProperty|(function).*?(?=\\\()| for .+?(?=\\\])/g, '$1.*?') + '$' ); /** Built-in value references. */ var Buffer = moduleExports ? context.Buffer : undefined, Symbol = context.Symbol, Uint8Array = context.Uint8Array, allocUnsafe = Buffer ? Buffer.allocUnsafe : undefined, getPrototype = overArg(Object.getPrototypeOf, Object), objectCreate = Object.create, propertyIsEnumerable = objectProto.propertyIsEnumerable, splice = arrayProto.splice, spreadableSymbol = Symbol ? Symbol.isConcatSpreadable : undefined, symIterator = Symbol ? Symbol.iterator : undefined, symToStringTag = Symbol ? Symbol.toStringTag : undefined; var defineProperty = (function() { try { var func = getNative(Object, 'defineProperty'); func({}, '', {}); return func; } catch (e) {} }()); /** Mocked built-ins. */ var ctxClearTimeout = context.clearTimeout !== root.clearTimeout && context.clearTimeout, ctxNow = Date && Date.now !== root.Date.now && Date.now, ctxSetTimeout = context.setTimeout !== root.setTimeout && context.setTimeout; /* Built-in method references for those with the same name as other `lodash` methods. */ var nativeCeil = Math.ceil, nativeFloor = Math.floor, nativeGetSymbols = Object.getOwnPropertySymbols, nativeIsBuffer = Buffer ? Buffer.isBuffer : undefined, nativeIsFinite = context.isFinite, nativeJoin = arrayProto.join, nativeKeys = overArg(Object.keys, Object), nativeMax = Math.max, nativeMin = Math.min, nativeNow = Date.now, nativeParseInt = context.parseInt, nativeRandom = Math.random, nativeReverse = arrayProto.reverse; /* Built-in method references that are verified to be native. */ var DataView = getNative(context, 'DataView'), Map = getNative(context, 'Map'), Promise = getNative(context, 'Promise'), Set = getNative(context, 'Set'), WeakMap = getNative(context, 'WeakMap'), nativeCreate = getNative(Object, 'create'); /** Used to store function metadata. */ var metaMap = WeakMap && new WeakMap; /** Used to lookup unminified function names. */ var realNames = {}; /** Used to detect maps, sets, and weakmaps. */ var dataViewCtorString = toSource(DataView), mapCtorString = toSource(Map), promiseCtorString = toSource(Promise), setCtorString = toSource(Set), weakMapCtorString = toSource(WeakMap); /** Used to convert symbols to primitives and strings. */ var symbolProto = Symbol ? Symbol.prototype : undefined, symbolValueOf = symbolProto ? symbolProto.valueOf : undefined, symbolToString = symbolProto ? symbolProto.toString : undefined; /*------------------------------------------------------------------------*/ /** * Creates a `lodash` object which wraps `value` to enable implicit method * chain sequences. Methods that operate on and return arrays, collections, * and functions can be chained together. Methods that retrieve a single value * or may return a primitive value will automatically end the chain sequence * and return the unwrapped value. Otherwise, the value must be unwrapped * with `_#value`. * * Explicit chain sequences, which must be unwrapped with `_#value`, may be * enabled using `_.chain`. * * The execution of chained methods is lazy, that is, it's deferred until * `_#value` is implicitly or explicitly called. * * Lazy evaluation allows several methods to support shortcut fusion. * Shortcut fusion is an optimization to merge iteratee calls; this avoids * the creation of intermediate arrays and can greatly reduce the number of * iteratee executions. Sections of a chain sequence qualify for shortcut * fusion if the section is applied to an array and iteratees accept only * one argument. The heuristic for whether a section qualifies for shortcut * fusion is subject to change. * * Chaining is supported in custom builds as long as the `_#value` method is * directly or indirectly included in the build. * * In addition to lodash methods, wrappers have `Array` and `String` methods. * * The wrapper `Array` methods are: * `concat`, `join`, `pop`, `push`, `shift`, `sort`, `splice`, and `unshift` * * The wrapper `String` methods are: * `replace` and `split` * * The wrapper methods that support shortcut fusion are: * `at`, `compact`, `drop`, `dropRight`, `dropWhile`, `filter`, `find`, * `findLast`, `head`, `initial`, `last`, `map`, `reject`, `reverse`, `slice`, * `tail`, `take`, `takeRight`, `takeRightWhile`, `takeWhile`, and `toArray` * * The chainable wrapper methods are: * `after`, `ary`, `assign`, `assignIn`, `assignInWith`, `assignWith`, `at`, * `before`, `bind`, `bindAll`, `bindKey`, `castArray`, `chain`, `chunk`, * `commit`, `compact`, `concat`, `conforms`, `constant`, `countBy`, `create`, * `curry`, `debounce`, `defaults`, `defaultsDeep`, `defer`, `delay`, * `difference`, `differenceBy`, `differenceWith`, `drop`, `dropRight`, * `dropRightWhile`, `dropWhile`, `extend`, `extendWith`, `fill`, `filter`, * `flatMap`, `flatMapDeep`, `flatMapDepth`, `flatten`, `flattenDeep`, * `flattenDepth`, `flip`, `flow`, `flowRight`, `fromPairs`, `functions`, * `functionsIn`, `groupBy`, `initial`, `intersection`, `intersectionBy`, * `intersectionWith`, `invert`, `invertBy`, `invokeMap`, `iteratee`, `keyBy`, * `keys`, `keysIn`, `map`, `mapKeys`, `mapValues`, `matches`, `matchesProperty`, * `memoize`, `merge`, `mergeWith`, `method`, `methodOf`, `mixin`, `negate`, * `nthArg`, `omit`, `omitBy`, `once`, `orderBy`, `over`, `overArgs`, * `overEvery`, `overSome`, `partial`, `partialRight`, `partition`, `pick`, * `pickBy`, `plant`, `property`, `propertyOf`, `pull`, `pullAll`, `pullAllBy`, * `pullAllWith`, `pullAt`, `push`, `range`, `rangeRight`, `rearg`, `reject`, * `remove`, `rest`, `reverse`, `sampleSize`, `set`, `setWith`, `shuffle`, * `slice`, `sort`, `sortBy`, `splice`, `spread`, `tail`, `take`, `takeRight`, * `takeRightWhile`, `takeWhile`, `tap`, `throttle`, `thru`, `toArray`, * `toPairs`, `toPairsIn`, `toPath`, `toPlainObject`, `transform`, `unary`, * `union`, `unionBy`, `unionWith`, `uniq`, `uniqBy`, `uniqWith`, `unset`, * `unshift`, `unzip`, `unzipWith`, `update`, `updateWith`, `values`, * `valuesIn`, `without`, `wrap`, `xor`, `xorBy`, `xorWith`, `zip`, * `zipObject`, `zipObjectDeep`, and `zipWith` * * The wrapper methods that are **not** chainable by default are: * `add`, `attempt`, `camelCase`, `capitalize`, `ceil`, `clamp`, `clone`, * `cloneDeep`, `cloneDeepWith`, `cloneWith`, `conformsTo`, `deburr`, * `defaultTo`, `divide`, `each`, `eachRight`, `endsWith`, `eq`, `escape`, * `escapeRegExp`, `every`, `find`, `findIndex`, `findKey`, `findLast`, * `findLastIndex`, `findLastKey`, `first`, `floor`, `forEach`, `forEachRight`, * `forIn`, `forInRight`, `forOwn`, `forOwnRight`, `get`, `gt`, `gte`, `has`, * `hasIn`, `head`, `identity`, `includes`, `indexOf`, `inRange`, `invoke`, * `isArguments`, `isArray`, `isArrayBuffer`, `isArrayLike`, `isArrayLikeObject`, * `isBoolean`, `isBuffer`, `isDate`, `isElement`, `isEmpty`, `isEqual`, * `isEqualWith`, `isError`, `isFinite`, `isFunction`, `isInteger`, `isLength`, * `isMap`, `isMatch`, `isMatchWith`, `isNaN`, `isNative`, `isNil`, `isNull`, * `isNumber`, `isObject`, `isObjectLike`, `isPlainObject`, `isRegExp`, * `isSafeInteger`, `isSet`, `isString`, `isUndefined`, `isTypedArray`, * `isWeakMap`, `isWeakSet`, `join`, `kebabCase`, `last`, `lastIndexOf`, * `lowerCase`, `lowerFirst`, `lt`, `lte`, `max`, `maxBy`, `mean`, `meanBy`, * `min`, `minBy`, `multiply`, `noConflict`, `noop`, `now`, `nth`, `pad`, * `padEnd`, `padStart`, `parseInt`, `pop`, `random`, `reduce`, `reduceRight`, * `repeat`, `result`, `round`, `runInContext`, `sample`, `shift`, `size`, * `snakeCase`, `some`, `sortedIndex`, `sortedIndexBy`, `sortedLastIndex`, * `sortedLastIndexBy`, `startCase`, `startsWith`, `stubArray`, `stubFalse`, * `stubObject`, `stubString`, `stubTrue`, `subtract`, `sum`, `sumBy`, * `template`, `times`, `toFinite`, `toInteger`, `toJSON`, `toLength`, * `toLower`, `toNumber`, `toSafeInteger`, `toString`, `toUpper`, `trim`, * `trimEnd`, `trimStart`, `truncate`, `unescape`, `uniqueId`, `upperCase`, * `upperFirst`, `value`, and `words` * * @name _ * @constructor * @category Seq * @param {*} value The value to wrap in a `lodash` instance. * @returns {Object} Returns the new `lodash` wrapper instance. * @example * * function square(n) { * return n * n; * } * * var wrapped = _([1, 2, 3]); * * // Returns an unwrapped value. * wrapped.reduce(_.add); * // => 6 * * // Returns a wrapped value. * var squares = wrapped.map(square); * * _.isArray(squares); * // => false * * _.isArray(squares.value()); * // => true */ function lodash(value) { if (isObjectLike(value) && !isArray(value) && !(value instanceof LazyWrapper)) { if (value instanceof LodashWrapper) { return value; } if (hasOwnProperty.call(value, '__wrapped__')) { return wrapperClone(value); } } return new LodashWrapper(value); } /** * The base implementation of `_.create` without support for assigning * properties to the created object. * * @private * @param {Object} proto The object to inherit from. * @returns {Object} Returns the new object. */ var baseCreate = (function() { function object() {} return function(proto) { if (!isObject(proto)) { return {}; } if (objectCreate) { return objectCreate(proto); } object.prototype = proto; var result = new object; object.prototype = undefined; return result; }; }()); /** * The function whose prototype chain sequence wrappers inherit from. * * @private */ function baseLodash() { // No operation performed. } /** * The base constructor for creating `lodash` wrapper objects. * * @private * @param {*} value The value to wrap. * @param {boolean} [chainAll] Enable explicit method chain sequences. */ function LodashWrapper(value, chainAll) { this.__wrapped__ = value; this.__actions__ = []; this.__chain__ = !!chainAll; this.__index__ = 0; this.__values__ = undefined; } /** * By default, the template delimiters used by lodash are like those in * embedded Ruby (ERB) as well as ES2015 template strings. Change the * following template settings to use alternative delimiters. * * @static * @memberOf _ * @type {Object} */ lodash.templateSettings = { /** * Used to detect `data` property values to be HTML-escaped. * * @memberOf _.templateSettings * @type {RegExp} */ 'escape': reEscape, /** * Used to detect code to be evaluated. * * @memberOf _.templateSettings * @type {RegExp} */ 'evaluate': reEvaluate, /** * Used to detect `data` property values to inject. * * @memberOf _.templateSettings * @type {RegExp} */ 'interpolate': reInterpolate, /** * Used to reference the data object in the template text. * * @memberOf _.templateSettings * @type {string} */ 'variable': '', /** * Used to import variables into the compiled template. * * @memberOf _.templateSettings * @type {Object} */ 'imports': { /** * A reference to the `lodash` function. * * @memberOf _.templateSettings.imports * @type {Function} */ '_': lodash } }; // Ensure wrappers are instances of `baseLodash`. lodash.prototype = baseLodash.prototype; lodash.prototype.constructor = lodash; LodashWrapper.prototype = baseCreate(baseLodash.prototype); LodashWrapper.prototype.constructor = LodashWrapper; /*------------------------------------------------------------------------*/ /** * Creates a lazy wrapper object which wraps `value` to enable lazy evaluation. * * @private * @constructor * @param {*} value The value to wrap. */ function LazyWrapper(value) { this.__wrapped__ = value; this.__actions__ = []; this.__dir__ = 1; this.__filtered__ = false; this.__iteratees__ = []; this.__takeCount__ = MAX_ARRAY_LENGTH; this.__views__ = []; } /** * Creates a clone of the lazy wrapper object. * * @private * @name clone * @memberOf LazyWrapper * @returns {Object} Returns the cloned `LazyWrapper` object. */ function lazyClone() { var result = new LazyWrapper(this.__wrapped__); result.__actions__ = copyArray(this.__actions__); result.__dir__ = this.__dir__; result.__filtered__ = this.__filtered__; result.__iteratees__ = copyArray(this.__iteratees__); result.__takeCount__ = this.__takeCount__; result.__views__ = copyArray(this.__views__); return result; } /** * Reverses the direction of lazy iteration. * * @private * @name reverse * @memberOf LazyWrapper * @returns {Object} Returns the new reversed `LazyWrapper` object. */ function lazyReverse() { if (this.__filtered__) { var result = new LazyWrapper(this); result.__dir__ = -1; result.__filtered__ = true; } else { result = this.clone(); result.__dir__ *= -1; } return result; } /** * Extracts the unwrapped value from its lazy wrapper. * * @private * @name value * @memberOf LazyWrapper * @returns {*} Returns the unwrapped value. */ function lazyValue() { var array = this.__wrapped__.value(), dir = this.__dir__, isArr = isArray(array), isRight = dir < 0, arrLength = isArr ? array.length : 0, view = getView(0, arrLength, this.__views__), start = view.start, end = view.end, length = end - start, index = isRight ? end : (start - 1), iteratees = this.__iteratees__, iterLength = iteratees.length, resIndex = 0, takeCount = nativeMin(length, this.__takeCount__); if (!isArr || (!isRight && arrLength == length && takeCount == length)) { return baseWrapperValue(array, this.__actions__); } var result = []; outer: while (length-- && resIndex < takeCount) { index += dir; var iterIndex = -1, value = array[index]; while (++iterIndex < iterLength) { var data = iteratees[iterIndex], iteratee = data.iteratee, type = data.type, computed = iteratee(value); if (type == LAZY_MAP_FLAG) { value = computed; } else if (!computed) { if (type == LAZY_FILTER_FLAG) { continue outer; } else { break outer; } } } result[resIndex++] = value; } return result; } // Ensure `LazyWrapper` is an instance of `baseLodash`. LazyWrapper.prototype = baseCreate(baseLodash.prototype); LazyWrapper.prototype.constructor = LazyWrapper; /*------------------------------------------------------------------------*/ /** * Creates a hash object. * * @private * @constructor * @param {Array} [entries] The key-value pairs to cache. */ function Hash(entries) { var index = -1, length = entries == null ? 0 : entries.length; this.clear(); while (++index < length) { var entry = entries[index]; this.set(entry[0], entry[1]); } } /** * Removes all key-value entries from the hash. * * @private * @name clear * @memberOf Hash */ function hashClear() { this.__data__ = nativeCreate ? nativeCreate(null) : {}; this.size = 0; } /** * Removes `key` and its value from the hash. * * @private * @name delete * @memberOf Hash * @param {Object} hash The hash to modify. * @param {string} key The key of the value to remove. * @returns {boolean} Returns `true` if the entry was removed, else `false`. */ function hashDelete(key) { var result = this.has(key) && delete this.__data__[key]; this.size -= result ? 1 : 0; return result; } /** * Gets the hash value for `key`. * * @private * @name get * @memberOf Hash * @param {string} key The key of the value to get. * @returns {*} Returns the entry value. */ function hashGet(key) { var data = this.__data__; if (nativeCreate) { var result = data[key]; return result === HASH_UNDEFINED ? undefined : result; } return hasOwnProperty.call(data, key) ? data[key] : undefined; } /** * Checks if a hash value for `key` exists. * * @private * @name has * @memberOf Hash * @param {string} key The key of the entry to check. * @returns {boolean} Returns `true` if an entry for `key` exists, else `false`. */ function hashHas(key) { var data = this.__data__; return nativeCreate ? (data[key] !== undefined) : hasOwnProperty.call(data, key); } /** * Sets the hash `key` to `value`. * * @private * @name set * @memberOf Hash * @param {string} key The key of the value to set. * @param {*} value The value to set. * @returns {Object} Returns the hash instance. */ function hashSet(key, value) { var data = this.__data__; this.size += this.has(key) ? 0 : 1; data[key] = (nativeCreate && value === undefined) ? HASH_UNDEFINED : value; return this; } // Add methods to `Hash`. Hash.prototype.clear = hashClear; Hash.prototype['delete'] = hashDelete; Hash.prototype.get = hashGet; Hash.prototype.has = hashHas; Hash.prototype.set = hashSet; /*------------------------------------------------------------------------*/ /** * Creates an list cache object. * * @private * @constructor * @param {Array} [entries] The key-value pairs to cache. */ function ListCache(entries) { var index = -1, length = entries == null ? 0 : entries.length; this.clear(); while (++index < length) { var entry = entries[index]; this.set(entry[0], entry[1]); } } /** * Removes all key-value entries from the list cache. * * @private * @name clear * @memberOf ListCache */ function listCacheClear() { this.__data__ = []; this.size = 0; } /** * Removes `key` and its value from the list cache. * * @private * @name delete * @memberOf ListCache * @param {string} key The key of the value to remove. * @returns {boolean} Returns `true` if the entry was removed, else `false`. */ function listCacheDelete(key) { var data = this.__data__, index = assocIndexOf(data, key); if (index < 0) { return false; } var lastIndex = data.length - 1; if (index == lastIndex) { data.pop(); } else { splice.call(data, index, 1); } --this.size; return true; } /** * Gets the list cache value for `key`. * * @private * @name get * @memberOf ListCache * @param {string} key The key of the value to get. * @returns {*} Returns the entry value. */ function listCacheGet(key) { var data = this.__data__, index = assocIndexOf(data, key); return index < 0 ? undefined : data[index][1]; } /** * Checks if a list cache value for `key` exists. * * @private * @name has * @memberOf ListCache * @param {string} key The key of the entry to check. * @returns {boolean} Returns `true` if an entry for `key` exists, else `false`. */ function listCacheHas(key) { return assocIndexOf(this.__data__, key) > -1; } /** * Sets the list cache `key` to `value`. * * @private * @name set * @memberOf ListCache * @param {string} key The key of the value to set. * @param {*} value The value to set. * @returns {Object} Returns the list cache instance. */ function listCacheSet(key, value) { var data = this.__data__, index = assocIndexOf(data, key); if (index < 0) { ++this.size; data.push([key, value]); } else { data[index][1] = value; } return this; } // Add methods to `ListCache`. ListCache.prototype.clear = listCacheClear; ListCache.prototype['delete'] = listCacheDelete; ListCache.prototype.get = listCacheGet; ListCache.prototype.has = listCacheHas; ListCache.prototype.set = listCacheSet; /*------------------------------------------------------------------------*/ /** * Creates a map cache object to store key-value pairs. * * @private * @constructor * @param {Array} [entries] The key-value pairs to cache. */ function MapCache(entries) { var index = -1, length = entries == null ? 0 : entries.length; this.clear(); while (++index < length) { var entry = entries[index]; this.set(entry[0], entry[1]); } } /** * Removes all key-value entries from the map. * * @private * @name clear * @memberOf MapCache */ function mapCacheClear() { this.size = 0; this.__data__ = { 'hash': new Hash, 'map': new (Map || ListCache), 'string': new Hash }; } /** * Removes `key` and its value from the map. * * @private * @name delete * @memberOf MapCache * @param {string} key The key of the value to remove. * @returns {boolean} Returns `true` if the entry was removed, else `false`. */ function mapCacheDelete(key) { var result = getMapData(this, key)['delete'](key); this.size -= result ? 1 : 0; return result; } /** * Gets the map value for `key`. * * @private * @name get * @memberOf MapCache * @param {string} key The key of the value to get. * @returns {*} Returns the entry value. */ function mapCacheGet(key) { return getMapData(this, key).get(key); } /** * Checks if a map value for `key` exists. * * @private * @name has * @memberOf MapCache * @param {string} key The key of the entry to check. * @returns {boolean} Returns `true` if an entry for `key` exists, else `false`. */ function mapCacheHas(key) { return getMapData(this, key).has(key); } /** * Sets the map `key` to `value`. * * @private * @name set * @memberOf MapCache * @param {string} key The key of the value to set. * @param {*} value The value to set. * @returns {Object} Returns the map cache instance. */ function mapCacheSet(key, value) { var data = getMapData(this, key), size = data.size; data.set(key, value); this.size += data.size == size ? 0 : 1; return this; } // Add methods to `MapCache`. MapCache.prototype.clear = mapCacheClear; MapCache.prototype['delete'] = mapCacheDelete; MapCache.prototype.get = mapCacheGet; MapCache.prototype.has = mapCacheHas; MapCache.prototype.set = mapCacheSet; /*------------------------------------------------------------------------*/ /** * * Creates an array cache object to store unique values. * * @private * @constructor * @param {Array} [values] The values to cache. */ function SetCache(values) { var index = -1, length = values == null ? 0 : values.length; this.__data__ = new MapCache; while (++index < length) { this.add(values[index]); } } /** * Adds `value` to the array cache. * * @private * @name add * @memberOf SetCache * @alias push * @param {*} value The value to cache. * @returns {Object} Returns the cache instance. */ function setCacheAdd(value) { this.__data__.set(value, HASH_UNDEFINED); return this; } /** * Checks if `value` is in the array cache. * * @private * @name has * @memberOf SetCache * @param {*} value The value to search for. * @returns {number} Returns `true` if `value` is found, else `false`. */ function setCacheHas(value) { return this.__data__.has(value); } // Add methods to `SetCache`. SetCache.prototype.add = SetCache.prototype.push = setCacheAdd; SetCache.prototype.has = setCacheHas; /*------------------------------------------------------------------------*/ /** * Creates a stack cache object to store key-value pairs. * * @private * @constructor * @param {Array} [entries] The key-value pairs to cache. */ function Stack(entries) { var data = this.__data__ = new ListCache(entries); this.size = data.size; } /** * Removes all key-value entries from the stack. * * @private * @name clear * @memberOf Stack */ function stackClear() { this.__data__ = new ListCache; this.size = 0; } /** * Removes `key` and its value from the stack. * * @private * @name delete * @memberOf Stack * @param {string} key The key of the value to remove. * @returns {boolean} Returns `true` if the entry was removed, else `false`. */ function stackDelete(key) { var data = this.__data__, result = data['delete'](key); this.size = data.size; return result; } /** * Gets the stack value for `key`. * * @private * @name get * @memberOf Stack * @param {string} key The key of the value to get. * @returns {*} Returns the entry value. */ function stackGet(key) { return this.__data__.get(key); } /** * Checks if a stack value for `key` exists. * * @private * @name has * @memberOf Stack * @param {string} key The key of the entry to check. * @returns {boolean} Returns `true` if an entry for `key` exists, else `false`. */ function stackHas(key) { return this.__data__.has(key); } /** * Sets the stack `key` to `value`. * * @private * @name set * @memberOf Stack * @param {string} key The key of the value to set. * @param {*} value The value to set. * @returns {Object} Returns the stack cache instance. */ function stackSet(key, value) { var data = this.__data__; if (data instanceof ListCache) { var pairs = data.__data__; if (!Map || (pairs.length < LARGE_ARRAY_SIZE - 1)) { pairs.push([key, value]); this.size = ++data.size; return this; } data = this.__data__ = new MapCache(pairs); } data.set(key, value); this.size = data.size; return this; } // Add methods to `Stack`. Stack.prototype.clear = stackClear; Stack.prototype['delete'] = stackDelete; Stack.prototype.get = stackGet; Stack.prototype.has = stackHas; Stack.prototype.set = stackSet; /*------------------------------------------------------------------------*/ /** * Creates an array of the enumerable property names of the array-like `value`. * * @private * @param {*} value The value to query. * @param {boolean} inherited Specify returning inherited property names. * @returns {Array} Returns the array of property names. */ function arrayLikeKeys(value, inherited) { var isArr = isArray(value), isArg = !isArr && isArguments(value), isBuff = !isArr && !isArg && isBuffer(value), isType = !isArr && !isArg && !isBuff && isTypedArray(value), skipIndexes = isArr || isArg || isBuff || isType, result = skipIndexes ? baseTimes(value.length, String) : [], length = result.length; for (var key in value) { if ((inherited || hasOwnProperty.call(value, key)) && !(skipIndexes && ( // Safari 9 has enumerable `arguments.length` in strict mode. key == 'length' || // Node.js 0.10 has enumerable non-index properties on buffers. (isBuff && (key == 'offset' || key == 'parent')) || // PhantomJS 2 has enumerable non-index properties on typed arrays. (isType && (key == 'buffer' || key == 'byteLength' || key == 'byteOffset')) || // Skip index properties. isIndex(key, length) ))) { result.push(key); } } return result; } /** * A specialized version of `_.sample` for arrays. * * @private * @param {Array} array The array to sample. * @returns {*} Returns the random element. */ function arraySample(array) { var length = array.length; return length ? array[baseRandom(0, length - 1)] : undefined; } /** * A specialized version of `_.sampleSize` for arrays. * * @private * @param {Array} array The array to sample. * @param {number} n The number of elements to sample. * @returns {Array} Returns the random elements. */ function arraySampleSize(array, n) { return shuffleSelf(copyArray(array), baseClamp(n, 0, array.length)); } /** * A specialized version of `_.shuffle` for arrays. * * @private * @param {Array} array The array to shuffle. * @returns {Array} Returns the new shuffled array. */ function arrayShuffle(array) { return shuffleSelf(copyArray(array)); } /** * This function is like `assignValue` except that it doesn't assign * `undefined` values. * * @private * @param {Object} object The object to modify. * @param {string} key The key of the property to assign. * @param {*} value The value to assign. */ function assignMergeValue(object, key, value) { if ((value !== undefined && !eq(object[key], value)) || (value === undefined && !(key in object))) { baseAssignValue(object, key, value); } } /** * Assigns `value` to `key` of `object` if the existing value is not equivalent * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) * for equality comparisons. * * @private * @param {Object} object The object to modify. * @param {string} key The key of the property to assign. * @param {*} value The value to assign. */ function assignValue(object, key, value) { var objValue = object[key]; if (!(hasOwnProperty.call(object, key) && eq(objValue, value)) || (value === undefined && !(key in object))) { baseAssignValue(object, key, value); } } /** * Gets the index at which the `key` is found in `array` of key-value pairs. * * @private * @param {Array} array The array to inspect. * @param {*} key The key to search for. * @returns {number} Returns the index of the matched value, else `-1`. */ function assocIndexOf(array, key) { var length = array.length; while (length--) { if (eq(array[length][0], key)) { return length; } } return -1; } /** * Aggregates elements of `collection` on `accumulator` with keys transformed * by `iteratee` and values set by `setter`. * * @private * @param {Array|Object} collection The collection to iterate over. * @param {Function} setter The function to set `accumulator` values. * @param {Function} iteratee The iteratee to transform keys. * @param {Object} accumulator The initial aggregated object. * @returns {Function} Returns `accumulator`. */ function baseAggregator(collection, setter, iteratee, accumulator) { baseEach(collection, function(value, key, collection) { setter(accumulator, value, iteratee(value), collection); }); return accumulator; } /** * The base implementation of `_.assign` without support for multiple sources * or `customizer` functions. * * @private * @param {Object} object The destination object. * @param {Object} source The source object. * @returns {Object} Returns `object`. */ function baseAssign(object, source) { return object && copyObject(source, keys(source), object); } /** * The base implementation of `_.assignIn` without support for multiple sources * or `customizer` functions. * * @private * @param {Object} object The destination object. * @param {Object} source The source object. * @returns {Object} Returns `object`. */ function baseAssignIn(object, source) { return object && copyObject(source, keysIn(source), object); } /** * The base implementation of `assignValue` and `assignMergeValue` without * value checks. * * @private * @param {Object} object The object to modify. * @param {string} key The key of the property to assign. * @param {*} value The value to assign. */ function baseAssignValue(object, key, value) { if (key == '__proto__' && defineProperty) { defineProperty(object, key, { 'configurable': true, 'enumerable': true, 'value': value, 'writable': true }); } else { object[key] = value; } } /** * The base implementation of `_.at` without support for individual paths. * * @private * @param {Object} object The object to iterate over. * @param {string[]} paths The property paths to pick. * @returns {Array} Returns the picked elements. */ function baseAt(object, paths) { var index = -1, length = paths.length, result = Array(length), skip = object == null; while (++index < length) { result[index] = skip ? undefined : get(object, paths[index]); } return result; } /** * The base implementation of `_.clamp` which doesn't coerce arguments. * * @private * @param {number} number The number to clamp. * @param {number} [lower] The lower bound. * @param {number} upper The upper bound. * @returns {number} Returns the clamped number. */ function baseClamp(number, lower, upper) { if (number === number) { if (upper !== undefined) { number = number <= upper ? number : upper; } if (lower !== undefined) { number = number >= lower ? number : lower; } } return number; } /** * The base implementation of `_.clone` and `_.cloneDeep` which tracks * traversed objects. * * @private * @param {*} value The value to clone. * @param {boolean} bitmask The bitmask flags. * 1 - Deep clone * 2 - Flatten inherited properties * 4 - Clone symbols * @param {Function} [customizer] The function to customize cloning. * @param {string} [key] The key of `value`. * @param {Object} [object] The parent object of `value`. * @param {Object} [stack] Tracks traversed objects and their clone counterparts. * @returns {*} Returns the cloned value. */ function baseClone(value, bitmask, customizer, key, object, stack) { var result, isDeep = bitmask & CLONE_DEEP_FLAG, isFlat = bitmask & CLONE_FLAT_FLAG, isFull = bitmask & CLONE_SYMBOLS_FLAG; if (customizer) { result = object ? customizer(value, key, object, stack) : customizer(value); } if (result !== undefined) { return result; } if (!isObject(value)) { return value; } var isArr = isArray(value); if (isArr) { result = initCloneArray(value); if (!isDeep) { return copyArray(value, result); } } else { var tag = getTag(value), isFunc = tag == funcTag || tag == genTag; if (isBuffer(value)) { return cloneBuffer(value, isDeep); } if (tag == objectTag || tag == argsTag || (isFunc && !object)) { result = (isFlat || isFunc) ? {} : initCloneObject(value); if (!isDeep) { return isFlat ? copySymbolsIn(value, baseAssignIn(result, value)) : copySymbols(value, baseAssign(result, value)); } } else { if (!cloneableTags[tag]) { return object ? value : {}; } result = initCloneByTag(value, tag, isDeep); } } // Check for circular references and return its corresponding clone. stack || (stack = new Stack); var stacked = stack.get(value); if (stacked) { return stacked; } stack.set(value, result); if (isSet(value)) { value.forEach(function(subValue) { result.add(baseClone(subValue, bitmask, customizer, subValue, value, stack)); }); return result; } if (isMap(value)) { value.forEach(function(subValue, key) { result.set(key, baseClone(subValue, bitmask, customizer, key, value, stack)); }); return result; } var keysFunc = isFull ? (isFlat ? getAllKeysIn : getAllKeys) : (isFlat ? keysIn : keys); var props = isArr ? undefined : keysFunc(value); arrayEach(props || value, function(subValue, key) { if (props) { key = subValue; subValue = value[key]; } // Recursively populate clone (susceptible to call stack limits). assignValue(result, key, baseClone(subValue, bitmask, customizer, key, value, stack)); }); return result; } /** * The base implementation of `_.conforms` which doesn't clone `source`. * * @private * @param {Object} source The object of property predicates to conform to. * @returns {Function} Returns the new spec function. */ function baseConforms(source) { var props = keys(source); return function(object) { return baseConformsTo(object, source, props); }; } /** * The base implementation of `_.conformsTo` which accepts `props` to check. * * @private * @param {Object} object The object to inspect. * @param {Object} source The object of property predicates to conform to. * @returns {boolean} Returns `true` if `object` conforms, else `false`. */ function baseConformsTo(object, source, props) { var length = props.length; if (object == null) { return !length; } object = Object(object); while (length--) { var key = props[length], predicate = source[key], value = object[key]; if ((value === undefined && !(key in object)) || !predicate(value)) { return false; } } return true; } /** * The base implementation of `_.delay` and `_.defer` which accepts `args` * to provide to `func`. * * @private * @param {Function} func The function to delay. * @param {number} wait The number of milliseconds to delay invocation. * @param {Array} args The arguments to provide to `func`. * @returns {number|Object} Returns the timer id or timeout object. */ function baseDelay(func, wait, args) { if (typeof func != 'function') { throw new TypeError(FUNC_ERROR_TEXT); } return setTimeout(function() { func.apply(undefined, args); }, wait); } /** * The base implementation of methods like `_.difference` without support * for excluding multiple arrays or iteratee shorthands. * * @private * @param {Array} array The array to inspect. * @param {Array} values The values to exclude. * @param {Function} [iteratee] The iteratee invoked per element. * @param {Function} [comparator] The comparator invoked per element. * @returns {Array} Returns the new array of filtered values. */ function baseDifference(array, values, iteratee, comparator) { var index = -1, includes = arrayIncludes, isCommon = true, length = array.length, result = [], valuesLength = values.length; if (!length) { return result; } if (iteratee) { values = arrayMap(values, baseUnary(iteratee)); } if (comparator) { includes = arrayIncludesWith; isCommon = false; } else if (values.length >= LARGE_ARRAY_SIZE) { includes = cacheHas; isCommon = false; values = new SetCache(values); } outer: while (++index < length) { var value = array[index], computed = iteratee == null ? value : iteratee(value); value = (comparator || value !== 0) ? value : 0; if (isCommon && computed === computed) { var valuesIndex = valuesLength; while (valuesIndex--) { if (values[valuesIndex] === computed) { continue outer; } } result.push(value); } else if (!includes(values, computed, comparator)) { result.push(value); } } return result; } /** * The base implementation of `_.forEach` without support for iteratee shorthands. * * @private * @param {Array|Object} collection The collection to iterate over. * @param {Function} iteratee The function invoked per iteration. * @returns {Array|Object} Returns `collection`. */ var baseEach = createBaseEach(baseForOwn); /** * The base implementation of `_.forEachRight` without support for iteratee shorthands. * * @private * @param {Array|Object} collection The collection to iterate over. * @param {Function} iteratee The function invoked per iteration. * @returns {Array|Object} Returns `collection`. */ var baseEachRight = createBaseEach(baseForOwnRight, true); /** * The base implementation of `_.every` without support for iteratee shorthands. * * @private * @param {Array|Object} collection The collection to iterate over. * @param {Function} predicate The function invoked per iteration. * @returns {boolean} Returns `true` if all elements pass the predicate check, * else `false` */ function baseEvery(collection, predicate) { var result = true; baseEach(collection, function(value, index, collection) { result = !!predicate(value, index, collection); return result; }); return result; } /** * The base implementation of methods like `_.max` and `_.min` which accepts a * `comparator` to determine the extremum value. * * @private * @param {Array} array The array to iterate over. * @param {Function} iteratee The iteratee invoked per iteration. * @param {Function} comparator The comparator used to compare values. * @returns {*} Returns the extremum value. */ function baseExtremum(array, iteratee, comparator) { var index = -1, length = array.length; while (++index < length) { var value = array[index], current = iteratee(value); if (current != null && (computed === undefined ? (current === current && !isSymbol(current)) : comparator(current, computed) )) { var computed = current, result = value; } } return result; } /** * The base implementation of `_.fill` without an iteratee call guard. * * @private * @param {Array} array The array to fill. * @param {*} value The value to fill `array` with. * @param {number} [start=0] The start position. * @param {number} [end=array.length] The end position. * @returns {Array} Returns `array`. */ function baseFill(array, value, start, end) { var length = array.length; start = toInteger(start); if (start < 0) { start = -start > length ? 0 : (length + start); } end = (end === undefined || end > length) ? length : toInteger(end); if (end < 0) { end += length; } end = start > end ? 0 : toLength(end); while (start < end) { array[start++] = value; } return array; } /** * The base implementation of `_.filter` without support for iteratee shorthands. * * @private * @param {Array|Object} collection The collection to iterate over. * @param {Function} predicate The function invoked per iteration. * @returns {Array} Returns the new filtered array. */ function baseFilter(collection, predicate) { var result = []; baseEach(collection, function(value, index, collection) { if (predicate(value, index, collection)) { result.push(value); } }); return result; } /** * The base implementation of `_.flatten` with support for restricting flattening. * * @private * @param {Array} array The array to flatten. * @param {number} depth The maximum recursion depth. * @param {boolean} [predicate=isFlattenable] The function invoked per iteration. * @param {boolean} [isStrict] Restrict to values that pass `predicate` checks. * @param {Array} [result=[]] The initial result value. * @returns {Array} Returns the new flattened array. */ function baseFlatten(array, depth, predicate, isStrict, result) { var index = -1, length = array.length; predicate || (predicate = isFlattenable); result || (result = []); while (++index < length) { var value = array[index]; if (depth > 0 && predicate(value)) { if (depth > 1) { // Recursively flatten arrays (susceptible to call stack limits). baseFlatten(value, depth - 1, predicate, isStrict, result); } else { arrayPush(result, value); } } else if (!isStrict) { result[result.length] = value; } } return result; } /** * The base implementation of `baseForOwn` which iterates over `object` * properties returned by `keysFunc` and invokes `iteratee` for each property. * Iteratee functions may exit iteration early by explicitly returning `false`. * * @private * @param {Object} object The object to iterate over. * @param {Function} iteratee The function invoked per iteration. * @param {Function} keysFunc The function to get the keys of `object`. * @returns {Object} Returns `object`. */ var baseFor = createBaseFor(); /** * This function is like `baseFor` except that it iterates over properties * in the opposite order. * * @private * @param {Object} object The object to iterate over. * @param {Function} iteratee The function invoked per iteration. * @param {Function} keysFunc The function to get the keys of `object`. * @returns {Object} Returns `object`. */ var baseForRight = createBaseFor(true); /** * The base implementation of `_.forOwn` without support for iteratee shorthands. * * @private * @param {Object} object The object to iterate over. * @param {Function} iteratee The function invoked per iteration. * @returns {Object} Returns `object`. */ function baseForOwn(object, iteratee) { return object && baseFor(object, iteratee, keys); } /** * The base implementation of `_.forOwnRight` without support for iteratee shorthands. * * @private * @param {Object} object The object to iterate over. * @param {Function} iteratee The function invoked per iteration. * @returns {Object} Returns `object`. */ function baseForOwnRight(object, iteratee) { return object && baseForRight(object, iteratee, keys); } /** * The base implementation of `_.functions` which creates an array of * `object` function property names filtered from `props`. * * @private * @param {Object} object The object to inspect. * @param {Array} props The property names to filter. * @returns {Array} Returns the function names. */ function baseFunctions(object, props) { return arrayFilter(props, function(key) { return isFunction(object[key]); }); } /** * The base implementation of `_.get` without support for default values. * * @private * @param {Object} object The object to query. * @param {Array|string} path The path of the property to get. * @returns {*} Returns the resolved value. */ function baseGet(object, path) { path = castPath(path, object); var index = 0, length = path.length; while (object != null && index < length) { object = object[toKey(path[index++])]; } return (index && index == length) ? object : undefined; } /** * The base implementation of `getAllKeys` and `getAllKeysIn` which uses * `keysFunc` and `symbolsFunc` to get the enumerable property names and * symbols of `object`. * * @private * @param {Object} object The object to query. * @param {Function} keysFunc The function to get the keys of `object`. * @param {Function} symbolsFunc The function to get the symbols of `object`. * @returns {Array} Returns the array of property names and symbols. */ function baseGetAllKeys(object, keysFunc, symbolsFunc) { var result = keysFunc(object); return isArray(object) ? result : arrayPush(result, symbolsFunc(object)); } /** * The base implementation of `getTag` without fallbacks for buggy environments. * * @private * @param {*} value The value to query. * @returns {string} Returns the `toStringTag`. */ function baseGetTag(value) { if (value == null) { return value === undefined ? undefinedTag : nullTag; } return (symToStringTag && symToStringTag in Object(value)) ? getRawTag(value) : objectToString(value); } /** * The base implementation of `_.gt` which doesn't coerce arguments. * * @private * @param {*} value The value to compare. * @param {*} other The other value to compare. * @returns {boolean} Returns `true` if `value` is greater than `other`, * else `false`. */ function baseGt(value, other) { return value > other; } /** * The base implementation of `_.has` without support for deep paths. * * @private * @param {Object} [object] The object to query. * @param {Array|string} key The key to check. * @returns {boolean} Returns `true` if `key` exists, else `false`. */ function baseHas(object, key) { return object != null && hasOwnProperty.call(object, key); } /** * The base implementation of `_.hasIn` without support for deep paths. * * @private * @param {Object} [object] The object to query. * @param {Array|string} key The key to check. * @returns {boolean} Returns `true` if `key` exists, else `false`. */ function baseHasIn(object, key) { return object != null && key in Object(object); } /** * The base implementation of `_.inRange` which doesn't coerce arguments. * * @private * @param {number} number The number to check. * @param {number} start The start of the range. * @param {number} end The end of the range. * @returns {boolean} Returns `true` if `number` is in the range, else `false`. */ function baseInRange(number, start, end) { return number >= nativeMin(start, end) && number < nativeMax(start, end); } /** * The base implementation of methods like `_.intersection`, without support * for iteratee shorthands, that accepts an array of arrays to inspect. * * @private * @param {Array} arrays The arrays to inspect. * @param {Function} [iteratee] The iteratee invoked per element. * @param {Function} [comparator] The comparator invoked per element. * @returns {Array} Returns the new array of shared values. */ function baseIntersection(arrays, iteratee, comparator) { var includes = comparator ? arrayIncludesWith : arrayIncludes, length = arrays[0].length, othLength = arrays.length, othIndex = othLength, caches = Array(othLength), maxLength = Infinity, result = []; while (othIndex--) { var array = arrays[othIndex]; if (othIndex && iteratee) { array = arrayMap(array, baseUnary(iteratee)); } maxLength = nativeMin(array.length, maxLength); caches[othIndex] = !comparator && (iteratee || (length >= 120 && array.length >= 120)) ? new SetCache(othIndex && array) : undefined; } array = arrays[0]; var index = -1, seen = caches[0]; outer: while (++index < length && result.length < maxLength) { var value = array[index], computed = iteratee ? iteratee(value) : value; value = (comparator || value !== 0) ? value : 0; if (!(seen ? cacheHas(seen, computed) : includes(result, computed, comparator) )) { othIndex = othLength; while (--othIndex) { var cache = caches[othIndex]; if (!(cache ? cacheHas(cache, computed) : includes(arrays[othIndex], computed, comparator)) ) { continue outer; } } if (seen) { seen.push(computed); } result.push(value); } } return result; } /** * The base implementation of `_.invert` and `_.invertBy` which inverts * `object` with values transformed by `iteratee` and set by `setter`. * * @private * @param {Object} object The object to iterate over. * @param {Function} setter The function to set `accumulator` values. * @param {Function} iteratee The iteratee to transform values. * @param {Object} accumulator The initial inverted object. * @returns {Function} Returns `accumulator`. */ function baseInverter(object, setter, iteratee, accumulator) { baseForOwn(object, function(value, key, object) { setter(accumulator, iteratee(value), key, object); }); return accumulator; } /** * The base implementation of `_.invoke` without support for individual * method arguments. * * @private * @param {Object} object The object to query. * @param {Array|string} path The path of the method to invoke. * @param {Array} args The arguments to invoke the method with. * @returns {*} Returns the result of the invoked method. */ function baseInvoke(object, path, args) { path = castPath(path, object); object = parent(object, path); var func = object == null ? object : object[toKey(last(path))]; return func == null ? undefined : apply(func, object, args); } /** * The base implementation of `_.isArguments`. * * @private * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is an `arguments` object, */ function baseIsArguments(value) { return isObjectLike(value) && baseGetTag(value) == argsTag; } /** * The base implementation of `_.isArrayBuffer` without Node.js optimizations. * * @private * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is an array buffer, else `false`. */ function baseIsArrayBuffer(value) { return isObjectLike(value) && baseGetTag(value) == arrayBufferTag; } /** * The base implementation of `_.isDate` without Node.js optimizations. * * @private * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a date object, else `false`. */ function baseIsDate(value) { return isObjectLike(value) && baseGetTag(value) == dateTag; } /** * The base implementation of `_.isEqual` which supports partial comparisons * and tracks traversed objects. * * @private * @param {*} value The value to compare. * @param {*} other The other value to compare. * @param {boolean} bitmask The bitmask flags. * 1 - Unordered comparison * 2 - Partial comparison * @param {Function} [customizer] The function to customize comparisons. * @param {Object} [stack] Tracks traversed `value` and `other` objects. * @returns {boolean} Returns `true` if the values are equivalent, else `false`. */ function baseIsEqual(value, other, bitmask, customizer, stack) { if (value === other) { return true; } if (value == null || other == null || (!isObjectLike(value) && !isObjectLike(other))) { return value !== value && other !== other; } return baseIsEqualDeep(value, other, bitmask, customizer, baseIsEqual, stack); } /** * A specialized version of `baseIsEqual` for arrays and objects which performs * deep comparisons and tracks traversed objects enabling objects with circular * references to be compared. * * @private * @param {Object} object The object to compare. * @param {Object} other The other object to compare. * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. * @param {Function} customizer The function to customize comparisons. * @param {Function} equalFunc The function to determine equivalents of values. * @param {Object} [stack] Tracks traversed `object` and `other` objects. * @returns {boolean} Returns `true` if the objects are equivalent, else `false`. */ function baseIsEqualDeep(object, other, bitmask, customizer, equalFunc, stack) { var objIsArr = isArray(object), othIsArr = isArray(other), objTag = objIsArr ? arrayTag : getTag(object), othTag = othIsArr ? arrayTag : getTag(other); objTag = objTag == argsTag ? objectTag : objTag; othTag = othTag == argsTag ? objectTag : othTag; var objIsObj = objTag == objectTag, othIsObj = othTag == objectTag, isSameTag = objTag == othTag; if (isSameTag && isBuffer(object)) { if (!isBuffer(other)) { return false; } objIsArr = true; objIsObj = false; } if (isSameTag && !objIsObj) { stack || (stack = new Stack); return (objIsArr || isTypedArray(object)) ? equalArrays(object, other, bitmask, customizer, equalFunc, stack) : equalByTag(object, other, objTag, bitmask, customizer, equalFunc, stack); } if (!(bitmask & COMPARE_PARTIAL_FLAG)) { var objIsWrapped = objIsObj && hasOwnProperty.call(object, '__wrapped__'), othIsWrapped = othIsObj && hasOwnProperty.call(other, '__wrapped__'); if (objIsWrapped || othIsWrapped) { var objUnwrapped = objIsWrapped ? object.value() : object, othUnwrapped = othIsWrapped ? other.value() : other; stack || (stack = new Stack); return equalFunc(objUnwrapped, othUnwrapped, bitmask, customizer, stack); } } if (!isSameTag) { return false; } stack || (stack = new Stack); return equalObjects(object, other, bitmask, customizer, equalFunc, stack); } /** * The base implementation of `_.isMap` without Node.js optimizations. * * @private * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a map, else `false`. */ function baseIsMap(value) { return isObjectLike(value) && getTag(value) == mapTag; } /** * The base implementation of `_.isMatch` without support for iteratee shorthands. * * @private * @param {Object} object The object to inspect. * @param {Object} source The object of property values to match. * @param {Array} matchData The property names, values, and compare flags to match. * @param {Function} [customizer] The function to customize comparisons. * @returns {boolean} Returns `true` if `object` is a match, else `false`. */ function baseIsMatch(object, source, matchData, customizer) { var index = matchData.length, length = index, noCustomizer = !customizer; if (object == null) { return !length; } object = Object(object); while (index--) { var data = matchData[index]; if ((noCustomizer && data[2]) ? data[1] !== object[data[0]] : !(data[0] in object) ) { return false; } } while (++index < length) { data = matchData[index]; var key = data[0], objValue = object[key], srcValue = data[1]; if (noCustomizer && data[2]) { if (objValue === undefined && !(key in object)) { return false; } } else { var stack = new Stack; if (customizer) { var result = customizer(objValue, srcValue, key, object, source, stack); } if (!(result === undefined ? baseIsEqual(srcValue, objValue, COMPARE_PARTIAL_FLAG | COMPARE_UNORDERED_FLAG, customizer, stack) : result )) { return false; } } } return true; } /** * The base implementation of `_.isNative` without bad shim checks. * * @private * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a native function, * else `false`. */ function baseIsNative(value) { if (!isObject(value) || isMasked(value)) { return false; } var pattern = isFunction(value) ? reIsNative : reIsHostCtor; return pattern.test(toSource(value)); } /** * The base implementation of `_.isRegExp` without Node.js optimizations. * * @private * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a regexp, else `false`. */ function baseIsRegExp(value) { return isObjectLike(value) && baseGetTag(value) == regexpTag; } /** * The base implementation of `_.isSet` without Node.js optimizations. * * @private * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a set, else `false`. */ function baseIsSet(value) { return isObjectLike(value) && getTag(value) == setTag; } /** * The base implementation of `_.isTypedArray` without Node.js optimizations. * * @private * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a typed array, else `false`. */ function baseIsTypedArray(value) { return isObjectLike(value) && isLength(value.length) && !!typedArrayTags[baseGetTag(value)]; } /** * The base implementation of `_.iteratee`. * * @private * @param {*} [value=_.identity] The value to convert to an iteratee. * @returns {Function} Returns the iteratee. */ function baseIteratee(value) { // Don't store the `typeof` result in a variable to avoid a JIT bug in Safari 9. // See https://bugs.webkit.org/show_bug.cgi?id=156034 for more details. if (typeof value == 'function') { return value; } if (value == null) { return identity; } if (typeof value == 'object') { return isArray(value) ? baseMatchesProperty(value[0], value[1]) : baseMatches(value); } return property(value); } /** * The base implementation of `_.keys` which doesn't treat sparse arrays as dense. * * @private * @param {Object} object The object to query. * @returns {Array} Returns the array of property names. */ function baseKeys(object) { if (!isPrototype(object)) { return nativeKeys(object); } var result = []; for (var key in Object(object)) { if (hasOwnProperty.call(object, key) && key != 'constructor') { result.push(key); } } return result; } /** * The base implementation of `_.keysIn` which doesn't treat sparse arrays as dense. * * @private * @param {Object} object The object to query. * @returns {Array} Returns the array of property names. */ function baseKeysIn(object) { if (!isObject(object)) { return nativeKeysIn(object); } var isProto = isPrototype(object), result = []; for (var key in object) { if (!(key == 'constructor' && (isProto || !hasOwnProperty.call(object, key)))) { result.push(key); } } return result; } /** * The base implementation of `_.lt` which doesn't coerce arguments. * * @private * @param {*} value The value to compare. * @param {*} other The other value to compare. * @returns {boolean} Returns `true` if `value` is less than `other`, * else `false`. */ function baseLt(value, other) { return value < other; } /** * The base implementation of `_.map` without support for iteratee shorthands. * * @private * @param {Array|Object} collection The collection to iterate over. * @param {Function} iteratee The function invoked per iteration. * @returns {Array} Returns the new mapped array. */ function baseMap(collection, iteratee) { var index = -1, result = isArrayLike(collection) ? Array(collection.length) : []; baseEach(collection, function(value, key, collection) { result[++index] = iteratee(value, key, collection); }); return result; } /** * The base implementation of `_.matches` which doesn't clone `source`. * * @private * @param {Object} source The object of property values to match. * @returns {Function} Returns the new spec function. */ function baseMatches(source) { var matchData = getMatchData(source); if (matchData.length == 1 && matchData[0][2]) { return matchesStrictComparable(matchData[0][0], matchData[0][1]); } return function(object) { return object === source || baseIsMatch(object, source, matchData); }; } /** * The base implementation of `_.matchesProperty` which doesn't clone `srcValue`. * * @private * @param {string} path The path of the property to get. * @param {*} srcValue The value to match. * @returns {Function} Returns the new spec function. */ function baseMatchesProperty(path, srcValue) { if (isKey(path) && isStrictComparable(srcValue)) { return matchesStrictComparable(toKey(path), srcValue); } return function(object) { var objValue = get(object, path); return (objValue === undefined && objValue === srcValue) ? hasIn(object, path) : baseIsEqual(srcValue, objValue, COMPARE_PARTIAL_FLAG | COMPARE_UNORDERED_FLAG); }; } /** * The base implementation of `_.merge` without support for multiple sources. * * @private * @param {Object} object The destination object. * @param {Object} source The source object. * @param {number} srcIndex The index of `source`. * @param {Function} [customizer] The function to customize merged values. * @param {Object} [stack] Tracks traversed source values and their merged * counterparts. */ function baseMerge(object, source, srcIndex, customizer, stack) { if (object === source) { return; } baseFor(source, function(srcValue, key) { if (isObject(srcValue)) { stack || (stack = new Stack); baseMergeDeep(object, source, key, srcIndex, baseMerge, customizer, stack); } else { var newValue = customizer ? customizer(safeGet(object, key), srcValue, (key + ''), object, source, stack) : undefined; if (newValue === undefined) { newValue = srcValue; } assignMergeValue(object, key, newValue); } }, keysIn); } /** * A specialized version of `baseMerge` for arrays and objects which performs * deep merges and tracks traversed objects enabling objects with circular * references to be merged. * * @private * @param {Object} object The destination object. * @param {Object} source The source object. * @param {string} key The key of the value to merge. * @param {number} srcIndex The index of `source`. * @param {Function} mergeFunc The function to merge values. * @param {Function} [customizer] The function to customize assigned values. * @param {Object} [stack] Tracks traversed source values and their merged * counterparts. */ function baseMergeDeep(object, source, key, srcIndex, mergeFunc, customizer, stack) { var objValue = safeGet(object, key), srcValue = safeGet(source, key), stacked = stack.get(srcValue); if (stacked) { assignMergeValue(object, key, stacked); return; } var newValue = customizer ? customizer(objValue, srcValue, (key + ''), object, source, stack) : undefined; var isCommon = newValue === undefined; if (isCommon) { var isArr = isArray(srcValue), isBuff = !isArr && isBuffer(srcValue), isTyped = !isArr && !isBuff && isTypedArray(srcValue); newValue = srcValue; if (isArr || isBuff || isTyped) { if (isArray(objValue)) { newValue = objValue; } else if (isArrayLikeObject(objValue)) { newValue = copyArray(objValue); } else if (isBuff) { isCommon = false; newValue = cloneBuffer(srcValue, true); } else if (isTyped) { isCommon = false; newValue = cloneTypedArray(srcValue, true); } else { newValue = []; } } else if (isPlainObject(srcValue) || isArguments(srcValue)) { newValue = objValue; if (isArguments(objValue)) { newValue = toPlainObject(objValue); } else if (!isObject(objValue) || isFunction(objValue)) { newValue = initCloneObject(srcValue); } } else { isCommon = false; } } if (isCommon) { // Recursively merge objects and arrays (susceptible to call stack limits). stack.set(srcValue, newValue); mergeFunc(newValue, srcValue, srcIndex, customizer, stack); stack['delete'](srcValue); } assignMergeValue(object, key, newValue); } /** * The base implementation of `_.nth` which doesn't coerce arguments. * * @private * @param {Array} array The array to query. * @param {number} n The index of the element to return. * @returns {*} Returns the nth element of `array`. */ function baseNth(array, n) { var length = array.length; if (!length) { return; } n += n < 0 ? length : 0; return isIndex(n, length) ? array[n] : undefined; } /** * The base implementation of `_.orderBy` without param guards. * * @private * @param {Array|Object} collection The collection to iterate over. * @param {Function[]|Object[]|string[]} iteratees The iteratees to sort by. * @param {string[]} orders The sort orders of `iteratees`. * @returns {Array} Returns the new sorted array. */ function baseOrderBy(collection, iteratees, orders) { var index = -1; iteratees = arrayMap(iteratees.length ? iteratees : [identity], baseUnary(getIteratee())); var result = baseMap(collection, function(value, key, collection) { var criteria = arrayMap(iteratees, function(iteratee) { return iteratee(value); }); return { 'criteria': criteria, 'index': ++index, 'value': value }; }); return baseSortBy(result, function(object, other) { return compareMultiple(object, other, orders); }); } /** * The base implementation of `_.pick` without support for individual * property identifiers. * * @private * @param {Object} object The source object. * @param {string[]} paths The property paths to pick. * @returns {Object} Returns the new object. */ function basePick(object, paths) { return basePickBy(object, paths, function(value, path) { return hasIn(object, path); }); } /** * The base implementation of `_.pickBy` without support for iteratee shorthands. * * @private * @param {Object} object The source object. * @param {string[]} paths The property paths to pick. * @param {Function} predicate The function invoked per property. * @returns {Object} Returns the new object. */ function basePickBy(object, paths, predicate) { var index = -1, length = paths.length, result = {}; while (++index < length) { var path = paths[index], value = baseGet(object, path); if (predicate(value, path)) { baseSet(result, castPath(path, object), value); } } return result; } /** * A specialized version of `baseProperty` which supports deep paths. * * @private * @param {Array|string} path The path of the property to get. * @returns {Function} Returns the new accessor function. */ function basePropertyDeep(path) { return function(object) { return baseGet(object, path); }; } /** * The base implementation of `_.pullAllBy` without support for iteratee * shorthands. * * @private * @param {Array} array The array to modify. * @param {Array} values The values to remove. * @param {Function} [iteratee] The iteratee invoked per element. * @param {Function} [comparator] The comparator invoked per element. * @returns {Array} Returns `array`. */ function basePullAll(array, values, iteratee, comparator) { var indexOf = comparator ? baseIndexOfWith : baseIndexOf, index = -1, length = values.length, seen = array; if (array === values) { values = copyArray(values); } if (iteratee) { seen = arrayMap(array, baseUnary(iteratee)); } while (++index < length) { var fromIndex = 0, value = values[index], computed = iteratee ? iteratee(value) : value; while ((fromIndex = indexOf(seen, computed, fromIndex, comparator)) > -1) { if (seen !== array) { splice.call(seen, fromIndex, 1); } splice.call(array, fromIndex, 1); } } return array; } /** * The base implementation of `_.pullAt` without support for individual * indexes or capturing the removed elements. * * @private * @param {Array} array The array to modify. * @param {number[]} indexes The indexes of elements to remove. * @returns {Array} Returns `array`. */ function basePullAt(array, indexes) { var length = array ? indexes.length : 0, lastIndex = length - 1; while (length--) { var index = indexes[length]; if (length == lastIndex || index !== previous) { var previous = index; if (isIndex(index)) { splice.call(array, index, 1); } else { baseUnset(array, index); } } } return array; } /** * The base implementation of `_.random` without support for returning * floating-point numbers. * * @private * @param {number} lower The lower bound. * @param {number} upper The upper bound. * @returns {number} Returns the random number. */ function baseRandom(lower, upper) { return lower + nativeFloor(nativeRandom() * (upper - lower + 1)); } /** * The base implementation of `_.range` and `_.rangeRight` which doesn't * coerce arguments. * * @private * @param {number} start The start of the range. * @param {number} end The end of the range. * @param {number} step The value to increment or decrement by. * @param {boolean} [fromRight] Specify iterating from right to left. * @returns {Array} Returns the range of numbers. */ function baseRange(start, end, step, fromRight) { var index = -1, length = nativeMax(nativeCeil((end - start) / (step || 1)), 0), result = Array(length); while (length--) { result[fromRight ? length : ++index] = start; start += step; } return result; } /** * The base implementation of `_.repeat` which doesn't coerce arguments. * * @private * @param {string} string The string to repeat. * @param {number} n The number of times to repeat the string. * @returns {string} Returns the repeated string. */ function baseRepeat(string, n) { var result = ''; if (!string || n < 1 || n > MAX_SAFE_INTEGER) { return result; } // Leverage the exponentiation by squaring algorithm for a faster repeat. // See https://en.wikipedia.org/wiki/Exponentiation_by_squaring for more details. do { if (n % 2) { result += string; } n = nativeFloor(n / 2); if (n) { string += string; } } while (n); return result; } /** * The base implementation of `_.rest` which doesn't validate or coerce arguments. * * @private * @param {Function} func The function to apply a rest parameter to. * @param {number} [start=func.length-1] The start position of the rest parameter. * @returns {Function} Returns the new function. */ function baseRest(func, start) { return setToString(overRest(func, start, identity), func + ''); } /** * The base implementation of `_.sample`. * * @private * @param {Array|Object} collection The collection to sample. * @returns {*} Returns the random element. */ function baseSample(collection) { return arraySample(values(collection)); } /** * The base implementation of `_.sampleSize` without param guards. * * @private * @param {Array|Object} collection The collection to sample. * @param {number} n The number of elements to sample. * @returns {Array} Returns the random elements. */ function baseSampleSize(collection, n) { var array = values(collection); return shuffleSelf(array, baseClamp(n, 0, array.length)); } /** * The base implementation of `_.set`. * * @private * @param {Object} object The object to modify. * @param {Array|string} path The path of the property to set. * @param {*} value The value to set. * @param {Function} [customizer] The function to customize path creation. * @returns {Object} Returns `object`. */ function baseSet(object, path, value, customizer) { if (!isObject(object)) { return object; } path = castPath(path, object); var index = -1, length = path.length, lastIndex = length - 1, nested = object; while (nested != null && ++index < length) { var key = toKey(path[index]), newValue = value; if (index != lastIndex) { var objValue = nested[key]; newValue = customizer ? customizer(objValue, key, nested) : undefined; if (newValue === undefined) { newValue = isObject(objValue) ? objValue : (isIndex(path[index + 1]) ? [] : {}); } } assignValue(nested, key, newValue); nested = nested[key]; } return object; } /** * The base implementation of `setData` without support for hot loop shorting. * * @private * @param {Function} func The function to associate metadata with. * @param {*} data The metadata. * @returns {Function} Returns `func`. */ var baseSetData = !metaMap ? identity : function(func, data) { metaMap.set(func, data); return func; }; /** * The base implementation of `setToString` without support for hot loop shorting. * * @private * @param {Function} func The function to modify. * @param {Function} string The `toString` result. * @returns {Function} Returns `func`. */ var baseSetToString = !defineProperty ? identity : function(func, string) { return defineProperty(func, 'toString', { 'configurable': true, 'enumerable': false, 'value': constant(string), 'writable': true }); }; /** * The base implementation of `_.shuffle`. * * @private * @param {Array|Object} collection The collection to shuffle. * @returns {Array} Returns the new shuffled array. */ function baseShuffle(collection) { return shuffleSelf(values(collection)); } /** * The base implementation of `_.slice` without an iteratee call guard. * * @private * @param {Array} array The array to slice. * @param {number} [start=0] The start position. * @param {number} [end=array.length] The end position. * @returns {Array} Returns the slice of `array`. */ function baseSlice(array, start, end) { var index = -1, length = array.length; if (start < 0) { start = -start > length ? 0 : (length + start); } end = end > length ? length : end; if (end < 0) { end += length; } length = start > end ? 0 : ((end - start) >>> 0); start >>>= 0; var result = Array(length); while (++index < length) { result[index] = array[index + start]; } return result; } /** * The base implementation of `_.some` without support for iteratee shorthands. * * @private * @param {Array|Object} collection The collection to iterate over. * @param {Function} predicate The function invoked per iteration. * @returns {boolean} Returns `true` if any element passes the predicate check, * else `false`. */ function baseSome(collection, predicate) { var result; baseEach(collection, function(value, index, collection) { result = predicate(value, index, collection); return !result; }); return !!result; } /** * The base implementation of `_.sortedIndex` and `_.sortedLastIndex` which * performs a binary search of `array` to determine the index at which `value` * should be inserted into `array` in order to maintain its sort order. * * @private * @param {Array} array The sorted array to inspect. * @param {*} value The value to evaluate. * @param {boolean} [retHighest] Specify returning the highest qualified index. * @returns {number} Returns the index at which `value` should be inserted * into `array`. */ function baseSortedIndex(array, value, retHighest) { var low = 0, high = array == null ? low : array.length; if (typeof value == 'number' && value === value && high <= HALF_MAX_ARRAY_LENGTH) { while (low < high) { var mid = (low + high) >>> 1, computed = array[mid]; if (computed !== null && !isSymbol(computed) && (retHighest ? (computed <= value) : (computed < value))) { low = mid + 1; } else { high = mid; } } return high; } return baseSortedIndexBy(array, value, identity, retHighest); } /** * The base implementation of `_.sortedIndexBy` and `_.sortedLastIndexBy` * which invokes `iteratee` for `value` and each element of `array` to compute * their sort ranking. The iteratee is invoked with one argument; (value). * * @private * @param {Array} array The sorted array to inspect. * @param {*} value The value to evaluate. * @param {Function} iteratee The iteratee invoked per element. * @param {boolean} [retHighest] Specify returning the highest qualified index. * @returns {number} Returns the index at which `value` should be inserted * into `array`. */ function baseSortedIndexBy(array, value, iteratee, retHighest) { value = iteratee(value); var low = 0, high = array == null ? 0 : array.length, valIsNaN = value !== value, valIsNull = value === null, valIsSymbol = isSymbol(value), valIsUndefined = value === undefined; while (low < high) { var mid = nativeFloor((low + high) / 2), computed = iteratee(array[mid]), othIsDefined = computed !== undefined, othIsNull = computed === null, othIsReflexive = computed === computed, othIsSymbol = isSymbol(computed); if (valIsNaN) { var setLow = retHighest || othIsReflexive; } else if (valIsUndefined) { setLow = othIsReflexive && (retHighest || othIsDefined); } else if (valIsNull) { setLow = othIsReflexive && othIsDefined && (retHighest || !othIsNull); } else if (valIsSymbol) { setLow = othIsReflexive && othIsDefined && !othIsNull && (retHighest || !othIsSymbol); } else if (othIsNull || othIsSymbol) { setLow = false; } else { setLow = retHighest ? (computed <= value) : (computed < value); } if (setLow) { low = mid + 1; } else { high = mid; } } return nativeMin(high, MAX_ARRAY_INDEX); } /** * The base implementation of `_.sortedUniq` and `_.sortedUniqBy` without * support for iteratee shorthands. * * @private * @param {Array} array The array to inspect. * @param {Function} [iteratee] The iteratee invoked per element. * @returns {Array} Returns the new duplicate free array. */ function baseSortedUniq(array, iteratee) { var index = -1, length = array.length, resIndex = 0, result = []; while (++index < length) { var value = array[index], computed = iteratee ? iteratee(value) : value; if (!index || !eq(computed, seen)) { var seen = computed; result[resIndex++] = value === 0 ? 0 : value; } } return result; } /** * The base implementation of `_.toNumber` which doesn't ensure correct * conversions of binary, hexadecimal, or octal string values. * * @private * @param {*} value The value to process. * @returns {number} Returns the number. */ function baseToNumber(value) { if (typeof value == 'number') { return value; } if (isSymbol(value)) { return NAN; } return +value; } /** * The base implementation of `_.toString` which doesn't convert nullish * values to empty strings. * * @private * @param {*} value The value to process. * @returns {string} Returns the string. */ function baseToString(value) { // Exit early for strings to avoid a performance hit in some environments. if (typeof value == 'string') { return value; } if (isArray(value)) { // Recursively convert values (susceptible to call stack limits). return arrayMap(value, baseToString) + ''; } if (isSymbol(value)) { return symbolToString ? symbolToString.call(value) : ''; } var result = (value + ''); return (result == '0' && (1 / value) == -INFINITY) ? '-0' : result; } /** * The base implementation of `_.uniqBy` without support for iteratee shorthands. * * @private * @param {Array} array The array to inspect. * @param {Function} [iteratee] The iteratee invoked per element. * @param {Function} [comparator] The comparator invoked per element. * @returns {Array} Returns the new duplicate free array. */ function baseUniq(array, iteratee, comparator) { var index = -1, includes = arrayIncludes, length = array.length, isCommon = true, result = [], seen = result; if (comparator) { isCommon = false; includes = arrayIncludesWith; } else if (length >= LARGE_ARRAY_SIZE) { var set = iteratee ? null : createSet(array); if (set) { return setToArray(set); } isCommon = false; includes = cacheHas; seen = new SetCache; } else { seen = iteratee ? [] : result; } outer: while (++index < length) { var value = array[index], computed = iteratee ? iteratee(value) : value; value = (comparator || value !== 0) ? value : 0; if (isCommon && computed === computed) { var seenIndex = seen.length; while (seenIndex--) { if (seen[seenIndex] === computed) { continue outer; } } if (iteratee) { seen.push(computed); } result.push(value); } else if (!includes(seen, computed, comparator)) { if (seen !== result) { seen.push(computed); } result.push(value); } } return result; } /** * The base implementation of `_.unset`. * * @private * @param {Object} object The object to modify. * @param {Array|string} path The property path to unset. * @returns {boolean} Returns `true` if the property is deleted, else `false`. */ function baseUnset(object, path) { path = castPath(path, object); object = parent(object, path); return object == null || delete object[toKey(last(path))]; } /** * The base implementation of `_.update`. * * @private * @param {Object} object The object to modify. * @param {Array|string} path The path of the property to update. * @param {Function} updater The function to produce the updated value. * @param {Function} [customizer] The function to customize path creation. * @returns {Object} Returns `object`. */ function baseUpdate(object, path, updater, customizer) { return baseSet(object, path, updater(baseGet(object, path)), customizer); } /** * The base implementation of methods like `_.dropWhile` and `_.takeWhile` * without support for iteratee shorthands. * * @private * @param {Array} array The array to query. * @param {Function} predicate The function invoked per iteration. * @param {boolean} [isDrop] Specify dropping elements instead of taking them. * @param {boolean} [fromRight] Specify iterating from right to left. * @returns {Array} Returns the slice of `array`. */ function baseWhile(array, predicate, isDrop, fromRight) { var length = array.length, index = fromRight ? length : -1; while ((fromRight ? index-- : ++index < length) && predicate(array[index], index, array)) {} return isDrop ? baseSlice(array, (fromRight ? 0 : index), (fromRight ? index + 1 : length)) : baseSlice(array, (fromRight ? index + 1 : 0), (fromRight ? length : index)); } /** * The base implementation of `wrapperValue` which returns the result of * performing a sequence of actions on the unwrapped `value`, where each * successive action is supplied the return value of the previous. * * @private * @param {*} value The unwrapped value. * @param {Array} actions Actions to perform to resolve the unwrapped value. * @returns {*} Returns the resolved value. */ function baseWrapperValue(value, actions) { var result = value; if (result instanceof LazyWrapper) { result = result.value(); } return arrayReduce(actions, function(result, action) { return action.func.apply(action.thisArg, arrayPush([result], action.args)); }, result); } /** * The base implementation of methods like `_.xor`, without support for * iteratee shorthands, that accepts an array of arrays to inspect. * * @private * @param {Array} arrays The arrays to inspect. * @param {Function} [iteratee] The iteratee invoked per element. * @param {Function} [comparator] The comparator invoked per element. * @returns {Array} Returns the new array of values. */ function baseXor(arrays, iteratee, comparator) { var length = arrays.length; if (length < 2) { return length ? baseUniq(arrays[0]) : []; } var index = -1, result = Array(length); while (++index < length) { var array = arrays[index], othIndex = -1; while (++othIndex < length) { if (othIndex != index) { result[index] = baseDifference(result[index] || array, arrays[othIndex], iteratee, comparator); } } } return baseUniq(baseFlatten(result, 1), iteratee, comparator); } /** * This base implementation of `_.zipObject` which assigns values using `assignFunc`. * * @private * @param {Array} props The property identifiers. * @param {Array} values The property values. * @param {Function} assignFunc The function to assign values. * @returns {Object} Returns the new object. */ function baseZipObject(props, values, assignFunc) { var index = -1, length = props.length, valsLength = values.length, result = {}; while (++index < length) { var value = index < valsLength ? values[index] : undefined; assignFunc(result, props[index], value); } return result; } /** * Casts `value` to an empty array if it's not an array like object. * * @private * @param {*} value The value to inspect. * @returns {Array|Object} Returns the cast array-like object. */ function castArrayLikeObject(value) { return isArrayLikeObject(value) ? value : []; } /** * Casts `value` to `identity` if it's not a function. * * @private * @param {*} value The value to inspect. * @returns {Function} Returns cast function. */ function castFunction(value) { return typeof value == 'function' ? value : identity; } /** * Casts `value` to a path array if it's not one. * * @private * @param {*} value The value to inspect. * @param {Object} [object] The object to query keys on. * @returns {Array} Returns the cast property path array. */ function castPath(value, object) { if (isArray(value)) { return value; } return isKey(value, object) ? [value] : stringToPath(toString(value)); } /** * A `baseRest` alias which can be replaced with `identity` by module * replacement plugins. * * @private * @type {Function} * @param {Function} func The function to apply a rest parameter to. * @returns {Function} Returns the new function. */ var castRest = baseRest; /** * Casts `array` to a slice if it's needed. * * @private * @param {Array} array The array to inspect. * @param {number} start The start position. * @param {number} [end=array.length] The end position. * @returns {Array} Returns the cast slice. */ function castSlice(array, start, end) { var length = array.length; end = end === undefined ? length : end; return (!start && end >= length) ? array : baseSlice(array, start, end); } /** * A simple wrapper around the global [`clearTimeout`](https://mdn.io/clearTimeout). * * @private * @param {number|Object} id The timer id or timeout object of the timer to clear. */ var clearTimeout = ctxClearTimeout || function(id) { return root.clearTimeout(id); }; /** * Creates a clone of `buffer`. * * @private * @param {Buffer} buffer The buffer to clone. * @param {boolean} [isDeep] Specify a deep clone. * @returns {Buffer} Returns the cloned buffer. */ function cloneBuffer(buffer, isDeep) { if (isDeep) { return buffer.slice(); } var length = buffer.length, result = allocUnsafe ? allocUnsafe(length) : new buffer.constructor(length); buffer.copy(result); return result; } /** * Creates a clone of `arrayBuffer`. * * @private * @param {ArrayBuffer} arrayBuffer The array buffer to clone. * @returns {ArrayBuffer} Returns the cloned array buffer. */ function cloneArrayBuffer(arrayBuffer) { var result = new arrayBuffer.constructor(arrayBuffer.byteLength); new Uint8Array(result).set(new Uint8Array(arrayBuffer)); return result; } /** * Creates a clone of `dataView`. * * @private * @param {Object} dataView The data view to clone. * @param {boolean} [isDeep] Specify a deep clone. * @returns {Object} Returns the cloned data view. */ function cloneDataView(dataView, isDeep) { var buffer = isDeep ? cloneArrayBuffer(dataView.buffer) : dataView.buffer; return new dataView.constructor(buffer, dataView.byteOffset, dataView.byteLength); } /** * Creates a clone of `regexp`. * * @private * @param {Object} regexp The regexp to clone. * @returns {Object} Returns the cloned regexp. */ function cloneRegExp(regexp) { var result = new regexp.constructor(regexp.source, reFlags.exec(regexp)); result.lastIndex = regexp.lastIndex; return result; } /** * Creates a clone of the `symbol` object. * * @private * @param {Object} symbol The symbol object to clone. * @returns {Object} Returns the cloned symbol object. */ function cloneSymbol(symbol) { return symbolValueOf ? Object(symbolValueOf.call(symbol)) : {}; } /** * Creates a clone of `typedArray`. * * @private * @param {Object} typedArray The typed array to clone. * @param {boolean} [isDeep] Specify a deep clone. * @returns {Object} Returns the cloned typed array. */ function cloneTypedArray(typedArray, isDeep) { var buffer = isDeep ? cloneArrayBuffer(typedArray.buffer) : typedArray.buffer; return new typedArray.constructor(buffer, typedArray.byteOffset, typedArray.length); } /** * Compares values to sort them in ascending order. * * @private * @param {*} value The value to compare. * @param {*} other The other value to compare. * @returns {number} Returns the sort order indicator for `value`. */ function compareAscending(value, other) { if (value !== other) { var valIsDefined = value !== undefined, valIsNull = value === null, valIsReflexive = value === value, valIsSymbol = isSymbol(value); var othIsDefined = other !== undefined, othIsNull = other === null, othIsReflexive = other === other, othIsSymbol = isSymbol(other); if ((!othIsNull && !othIsSymbol && !valIsSymbol && value > other) || (valIsSymbol && othIsDefined && othIsReflexive && !othIsNull && !othIsSymbol) || (valIsNull && othIsDefined && othIsReflexive) || (!valIsDefined && othIsReflexive) || !valIsReflexive) { return 1; } if ((!valIsNull && !valIsSymbol && !othIsSymbol && value < other) || (othIsSymbol && valIsDefined && valIsReflexive && !valIsNull && !valIsSymbol) || (othIsNull && valIsDefined && valIsReflexive) || (!othIsDefined && valIsReflexive) || !othIsReflexive) { return -1; } } return 0; } /** * Used by `_.orderBy` to compare multiple properties of a value to another * and stable sort them. * * If `orders` is unspecified, all values are sorted in ascending order. Otherwise, * specify an order of "desc" for descending or "asc" for ascending sort order * of corresponding values. * * @private * @param {Object} object The object to compare. * @param {Object} other The other object to compare. * @param {boolean[]|string[]} orders The order to sort by for each property. * @returns {number} Returns the sort order indicator for `object`. */ function compareMultiple(object, other, orders) { var index = -1, objCriteria = object.criteria, othCriteria = other.criteria, length = objCriteria.length, ordersLength = orders.length; while (++index < length) { var result = compareAscending(objCriteria[index], othCriteria[index]); if (result) { if (index >= ordersLength) { return result; } var order = orders[index]; return result * (order == 'desc' ? -1 : 1); } } // Fixes an `Array#sort` bug in the JS engine embedded in Adobe applications // that causes it, under certain circumstances, to provide the same value for // `object` and `other`. See https://github.com/jashkenas/underscore/pull/1247 // for more details. // // This also ensures a stable sort in V8 and other engines. // See https://bugs.chromium.org/p/v8/issues/detail?id=90 for more details. return object.index - other.index; } /** * Creates an array that is the composition of partially applied arguments, * placeholders, and provided arguments into a single array of arguments. * * @private * @param {Array} args The provided arguments. * @param {Array} partials The arguments to prepend to those provided. * @param {Array} holders The `partials` placeholder indexes. * @params {boolean} [isCurried] Specify composing for a curried function. * @returns {Array} Returns the new array of composed arguments. */ function composeArgs(args, partials, holders, isCurried) { var argsIndex = -1, argsLength = args.length, holdersLength = holders.length, leftIndex = -1, leftLength = partials.length, rangeLength = nativeMax(argsLength - holdersLength, 0), result = Array(leftLength + rangeLength), isUncurried = !isCurried; while (++leftIndex < leftLength) { result[leftIndex] = partials[leftIndex]; } while (++argsIndex < holdersLength) { if (isUncurried || argsIndex < argsLength) { result[holders[argsIndex]] = args[argsIndex]; } } while (rangeLength--) { result[leftIndex++] = args[argsIndex++]; } return result; } /** * This function is like `composeArgs` except that the arguments composition * is tailored for `_.partialRight`. * * @private * @param {Array} args The provided arguments. * @param {Array} partials The arguments to append to those provided. * @param {Array} holders The `partials` placeholder indexes. * @params {boolean} [isCurried] Specify composing for a curried function. * @returns {Array} Returns the new array of composed arguments. */ function composeArgsRight(args, partials, holders, isCurried) { var argsIndex = -1, argsLength = args.length, holdersIndex = -1, holdersLength = holders.length, rightIndex = -1, rightLength = partials.length, rangeLength = nativeMax(argsLength - holdersLength, 0), result = Array(rangeLength + rightLength), isUncurried = !isCurried; while (++argsIndex < rangeLength) { result[argsIndex] = args[argsIndex]; } var offset = argsIndex; while (++rightIndex < rightLength) { result[offset + rightIndex] = partials[rightIndex]; } while (++holdersIndex < holdersLength) { if (isUncurried || argsIndex < argsLength) { result[offset + holders[holdersIndex]] = args[argsIndex++]; } } return result; } /** * Copies the values of `source` to `array`. * * @private * @param {Array} source The array to copy values from. * @param {Array} [array=[]] The array to copy values to. * @returns {Array} Returns `array`. */ function copyArray(source, array) { var index = -1, length = source.length; array || (array = Array(length)); while (++index < length) { array[index] = source[index]; } return array; } /** * Copies properties of `source` to `object`. * * @private * @param {Object} source The object to copy properties from. * @param {Array} props The property identifiers to copy. * @param {Object} [object={}] The object to copy properties to. * @param {Function} [customizer] The function to customize copied values. * @returns {Object} Returns `object`. */ function copyObject(source, props, object, customizer) { var isNew = !object; object || (object = {}); var index = -1, length = props.length; while (++index < length) { var key = props[index]; var newValue = customizer ? customizer(object[key], source[key], key, object, source) : undefined; if (newValue === undefined) { newValue = source[key]; } if (isNew) { baseAssignValue(object, key, newValue); } else { assignValue(object, key, newValue); } } return object; } /** * Copies own symbols of `source` to `object`. * * @private * @param {Object} source The object to copy symbols from. * @param {Object} [object={}] The object to copy symbols to. * @returns {Object} Returns `object`. */ function copySymbols(source, object) { return copyObject(source, getSymbols(source), object); } /** * Copies own and inherited symbols of `source` to `object`. * * @private * @param {Object} source The object to copy symbols from. * @param {Object} [object={}] The object to copy symbols to. * @returns {Object} Returns `object`. */ function copySymbolsIn(source, object) { return copyObject(source, getSymbolsIn(source), object); } /** * Creates a function like `_.groupBy`. * * @private * @param {Function} setter The function to set accumulator values. * @param {Function} [initializer] The accumulator object initializer. * @returns {Function} Returns the new aggregator function. */ function createAggregator(setter, initializer) { return function(collection, iteratee) { var func = isArray(collection) ? arrayAggregator : baseAggregator, accumulator = initializer ? initializer() : {}; return func(collection, setter, getIteratee(iteratee, 2), accumulator); }; } /** * Creates a function like `_.assign`. * * @private * @param {Function} assigner The function to assign values. * @returns {Function} Returns the new assigner function. */ function createAssigner(assigner) { return baseRest(function(object, sources) { var index = -1, length = sources.length, customizer = length > 1 ? sources[length - 1] : undefined, guard = length > 2 ? sources[2] : undefined; customizer = (assigner.length > 3 && typeof customizer == 'function') ? (length--, customizer) : undefined; if (guard && isIterateeCall(sources[0], sources[1], guard)) { customizer = length < 3 ? undefined : customizer; length = 1; } object = Object(object); while (++index < length) { var source = sources[index]; if (source) { assigner(object, source, index, customizer); } } return object; }); } /** * Creates a `baseEach` or `baseEachRight` function. * * @private * @param {Function} eachFunc The function to iterate over a collection. * @param {boolean} [fromRight] Specify iterating from right to left. * @returns {Function} Returns the new base function. */ function createBaseEach(eachFunc, fromRight) { return function(collection, iteratee) { if (collection == null) { return collection; } if (!isArrayLike(collection)) { return eachFunc(collection, iteratee); } var length = collection.length, index = fromRight ? length : -1, iterable = Object(collection); while ((fromRight ? index-- : ++index < length)) { if (iteratee(iterable[index], index, iterable) === false) { break; } } return collection; }; } /** * Creates a base function for methods like `_.forIn` and `_.forOwn`. * * @private * @param {boolean} [fromRight] Specify iterating from right to left. * @returns {Function} Returns the new base function. */ function createBaseFor(fromRight) { return function(object, iteratee, keysFunc) { var index = -1, iterable = Object(object), props = keysFunc(object), length = props.length; while (length--) { var key = props[fromRight ? length : ++index]; if (iteratee(iterable[key], key, iterable) === false) { break; } } return object; }; } /** * Creates a function that wraps `func` to invoke it with the optional `this` * binding of `thisArg`. * * @private * @param {Function} func The function to wrap. * @param {number} bitmask The bitmask flags. See `createWrap` for more details. * @param {*} [thisArg] The `this` binding of `func`. * @returns {Function} Returns the new wrapped function. */ function createBind(func, bitmask, thisArg) { var isBind = bitmask & WRAP_BIND_FLAG, Ctor = createCtor(func); function wrapper() { var fn = (this && this !== root && this instanceof wrapper) ? Ctor : func; return fn.apply(isBind ? thisArg : this, arguments); } return wrapper; } /** * Creates a function like `_.lowerFirst`. * * @private * @param {string} methodName The name of the `String` case method to use. * @returns {Function} Returns the new case function. */ function createCaseFirst(methodName) { return function(string) { string = toString(string); var strSymbols = hasUnicode(string) ? stringToArray(string) : undefined; var chr = strSymbols ? strSymbols[0] : string.charAt(0); var trailing = strSymbols ? castSlice(strSymbols, 1).join('') : string.slice(1); return chr[methodName]() + trailing; }; } /** * Creates a function like `_.camelCase`. * * @private * @param {Function} callback The function to combine each word. * @returns {Function} Returns the new compounder function. */ function createCompounder(callback) { return function(string) { return arrayReduce(words(deburr(string).replace(reApos, '')), callback, ''); }; } /** * Creates a function that produces an instance of `Ctor` regardless of * whether it was invoked as part of a `new` expression or by `call` or `apply`. * * @private * @param {Function} Ctor The constructor to wrap. * @returns {Function} Returns the new wrapped function. */ function createCtor(Ctor) { return function() { // Use a `switch` statement to work with class constructors. See // http://ecma-international.org/ecma-262/7.0/#sec-ecmascript-function-objects-call-thisargument-argumentslist // for more details. var args = arguments; switch (args.length) { case 0: return new Ctor; case 1: return new Ctor(args[0]); case 2: return new Ctor(args[0], args[1]); case 3: return new Ctor(args[0], args[1], args[2]); case 4: return new Ctor(args[0], args[1], args[2], args[3]); case 5: return new Ctor(args[0], args[1], args[2], args[3], args[4]); case 6: return new Ctor(args[0], args[1], args[2], args[3], args[4], args[5]); case 7: return new Ctor(args[0], args[1], args[2], args[3], args[4], args[5], args[6]); } var thisBinding = baseCreate(Ctor.prototype), result = Ctor.apply(thisBinding, args); // Mimic the constructor's `return` behavior. // See https://es5.github.io/#x13.2.2 for more details. return isObject(result) ? result : thisBinding; }; } /** * Creates a function that wraps `func` to enable currying. * * @private * @param {Function} func The function to wrap. * @param {number} bitmask The bitmask flags. See `createWrap` for more details. * @param {number} arity The arity of `func`. * @returns {Function} Returns the new wrapped function. */ function createCurry(func, bitmask, arity) { var Ctor = createCtor(func); function wrapper() { var length = arguments.length, args = Array(length), index = length, placeholder = getHolder(wrapper); while (index--) { args[index] = arguments[index]; } var holders = (length < 3 && args[0] !== placeholder && args[length - 1] !== placeholder) ? [] : replaceHolders(args, placeholder); length -= holders.length; if (length < arity) { return createRecurry( func, bitmask, createHybrid, wrapper.placeholder, undefined, args, holders, undefined, undefined, arity - length); } var fn = (this && this !== root && this instanceof wrapper) ? Ctor : func; return apply(fn, this, args); } return wrapper; } /** * Creates a `_.find` or `_.findLast` function. * * @private * @param {Function} findIndexFunc The function to find the collection index. * @returns {Function} Returns the new find function. */ function createFind(findIndexFunc) { return function(collection, predicate, fromIndex) { var iterable = Object(collection); if (!isArrayLike(collection)) { var iteratee = getIteratee(predicate, 3); collection = keys(collection); predicate = function(key) { return iteratee(iterable[key], key, iterable); }; } var index = findIndexFunc(collection, predicate, fromIndex); return index > -1 ? iterable[iteratee ? collection[index] : index] : undefined; }; } /** * Creates a `_.flow` or `_.flowRight` function. * * @private * @param {boolean} [fromRight] Specify iterating from right to left. * @returns {Function} Returns the new flow function. */ function createFlow(fromRight) { return flatRest(function(funcs) { var length = funcs.length, index = length, prereq = LodashWrapper.prototype.thru; if (fromRight) { funcs.reverse(); } while (index--) { var func = funcs[index]; if (typeof func != 'function') { throw new TypeError(FUNC_ERROR_TEXT); } if (prereq && !wrapper && getFuncName(func) == 'wrapper') { var wrapper = new LodashWrapper([], true); } } index = wrapper ? index : length; while (++index < length) { func = funcs[index]; var funcName = getFuncName(func), data = funcName == 'wrapper' ? getData(func) : undefined; if (data && isLaziable(data[0]) && data[1] == (WRAP_ARY_FLAG | WRAP_CURRY_FLAG | WRAP_PARTIAL_FLAG | WRAP_REARG_FLAG) && !data[4].length && data[9] == 1 ) { wrapper = wrapper[getFuncName(data[0])].apply(wrapper, data[3]); } else { wrapper = (func.length == 1 && isLaziable(func)) ? wrapper[funcName]() : wrapper.thru(func); } } return function() { var args = arguments, value = args[0]; if (wrapper && args.length == 1 && isArray(value)) { return wrapper.plant(value).value(); } var index = 0, result = length ? funcs[index].apply(this, args) : value; while (++index < length) { result = funcs[index].call(this, result); } return result; }; }); } /** * Creates a function that wraps `func` to invoke it with optional `this` * binding of `thisArg`, partial application, and currying. * * @private * @param {Function|string} func The function or method name to wrap. * @param {number} bitmask The bitmask flags. See `createWrap` for more details. * @param {*} [thisArg] The `this` binding of `func`. * @param {Array} [partials] The arguments to prepend to those provided to * the new function. * @param {Array} [holders] The `partials` placeholder indexes. * @param {Array} [partialsRight] The arguments to append to those provided * to the new function. * @param {Array} [holdersRight] The `partialsRight` placeholder indexes. * @param {Array} [argPos] The argument positions of the new function. * @param {number} [ary] The arity cap of `func`. * @param {number} [arity] The arity of `func`. * @returns {Function} Returns the new wrapped function. */ function createHybrid(func, bitmask, thisArg, partials, holders, partialsRight, holdersRight, argPos, ary, arity) { var isAry = bitmask & WRAP_ARY_FLAG, isBind = bitmask & WRAP_BIND_FLAG, isBindKey = bitmask & WRAP_BIND_KEY_FLAG, isCurried = bitmask & (WRAP_CURRY_FLAG | WRAP_CURRY_RIGHT_FLAG), isFlip = bitmask & WRAP_FLIP_FLAG, Ctor = isBindKey ? undefined : createCtor(func); function wrapper() { var length = arguments.length, args = Array(length), index = length; while (index--) { args[index] = arguments[index]; } if (isCurried) { var placeholder = getHolder(wrapper), holdersCount = countHolders(args, placeholder); } if (partials) { args = composeArgs(args, partials, holders, isCurried); } if (partialsRight) { args = composeArgsRight(args, partialsRight, holdersRight, isCurried); } length -= holdersCount; if (isCurried && length < arity) { var newHolders = replaceHolders(args, placeholder); return createRecurry( func, bitmask, createHybrid, wrapper.placeholder, thisArg, args, newHolders, argPos, ary, arity - length ); } var thisBinding = isBind ? thisArg : this, fn = isBindKey ? thisBinding[func] : func; length = args.length; if (argPos) { args = reorder(args, argPos); } else if (isFlip && length > 1) { args.reverse(); } if (isAry && ary < length) { args.length = ary; } if (this && this !== root && this instanceof wrapper) { fn = Ctor || createCtor(fn); } return fn.apply(thisBinding, args); } return wrapper; } /** * Creates a function like `_.invertBy`. * * @private * @param {Function} setter The function to set accumulator values. * @param {Function} toIteratee The function to resolve iteratees. * @returns {Function} Returns the new inverter function. */ function createInverter(setter, toIteratee) { return function(object, iteratee) { return baseInverter(object, setter, toIteratee(iteratee), {}); }; } /** * Creates a function that performs a mathematical operation on two values. * * @private * @param {Function} operator The function to perform the operation. * @param {number} [defaultValue] The value used for `undefined` arguments. * @returns {Function} Returns the new mathematical operation function. */ function createMathOperation(operator, defaultValue) { return function(value, other) { var result; if (value === undefined && other === undefined) { return defaultValue; } if (value !== undefined) { result = value; } if (other !== undefined) { if (result === undefined) { return other; } if (typeof value == 'string' || typeof other == 'string') { value = baseToString(value); other = baseToString(other); } else { value = baseToNumber(value); other = baseToNumber(other); } result = operator(value, other); } return result; }; } /** * Creates a function like `_.over`. * * @private * @param {Function} arrayFunc The function to iterate over iteratees. * @returns {Function} Returns the new over function. */ function createOver(arrayFunc) { return flatRest(function(iteratees) { iteratees = arrayMap(iteratees, baseUnary(getIteratee())); return baseRest(function(args) { var thisArg = this; return arrayFunc(iteratees, function(iteratee) { return apply(iteratee, thisArg, args); }); }); }); } /** * Creates the padding for `string` based on `length`. The `chars` string * is truncated if the number of characters exceeds `length`. * * @private * @param {number} length The padding length. * @param {string} [chars=' '] The string used as padding. * @returns {string} Returns the padding for `string`. */ function createPadding(length, chars) { chars = chars === undefined ? ' ' : baseToString(chars); var charsLength = chars.length; if (charsLength < 2) { return charsLength ? baseRepeat(chars, length) : chars; } var result = baseRepeat(chars, nativeCeil(length / stringSize(chars))); return hasUnicode(chars) ? castSlice(stringToArray(result), 0, length).join('') : result.slice(0, length); } /** * Creates a function that wraps `func` to invoke it with the `this` binding * of `thisArg` and `partials` prepended to the arguments it receives. * * @private * @param {Function} func The function to wrap. * @param {number} bitmask The bitmask flags. See `createWrap` for more details. * @param {*} thisArg The `this` binding of `func`. * @param {Array} partials The arguments to prepend to those provided to * the new function. * @returns {Function} Returns the new wrapped function. */ function createPartial(func, bitmask, thisArg, partials) { var isBind = bitmask & WRAP_BIND_FLAG, Ctor = createCtor(func); function wrapper() { var argsIndex = -1, argsLength = arguments.length, leftIndex = -1, leftLength = partials.length, args = Array(leftLength + argsLength), fn = (this && this !== root && this instanceof wrapper) ? Ctor : func; while (++leftIndex < leftLength) { args[leftIndex] = partials[leftIndex]; } while (argsLength--) { args[leftIndex++] = arguments[++argsIndex]; } return apply(fn, isBind ? thisArg : this, args); } return wrapper; } /** * Creates a `_.range` or `_.rangeRight` function. * * @private * @param {boolean} [fromRight] Specify iterating from right to left. * @returns {Function} Returns the new range function. */ function createRange(fromRight) { return function(start, end, step) { if (step && typeof step != 'number' && isIterateeCall(start, end, step)) { end = step = undefined; } // Ensure the sign of `-0` is preserved. start = toFinite(start); if (end === undefined) { end = start; start = 0; } else { end = toFinite(end); } step = step === undefined ? (start < end ? 1 : -1) : toFinite(step); return baseRange(start, end, step, fromRight); }; } /** * Creates a function that performs a relational operation on two values. * * @private * @param {Function} operator The function to perform the operation. * @returns {Function} Returns the new relational operation function. */ function createRelationalOperation(operator) { return function(value, other) { if (!(typeof value == 'string' && typeof other == 'string')) { value = toNumber(value); other = toNumber(other); } return operator(value, other); }; } /** * Creates a function that wraps `func` to continue currying. * * @private * @param {Function} func The function to wrap. * @param {number} bitmask The bitmask flags. See `createWrap` for more details. * @param {Function} wrapFunc The function to create the `func` wrapper. * @param {*} placeholder The placeholder value. * @param {*} [thisArg] The `this` binding of `func`. * @param {Array} [partials] The arguments to prepend to those provided to * the new function. * @param {Array} [holders] The `partials` placeholder indexes. * @param {Array} [argPos] The argument positions of the new function. * @param {number} [ary] The arity cap of `func`. * @param {number} [arity] The arity of `func`. * @returns {Function} Returns the new wrapped function. */ function createRecurry(func, bitmask, wrapFunc, placeholder, thisArg, partials, holders, argPos, ary, arity) { var isCurry = bitmask & WRAP_CURRY_FLAG, newHolders = isCurry ? holders : undefined, newHoldersRight = isCurry ? undefined : holders, newPartials = isCurry ? partials : undefined, newPartialsRight = isCurry ? undefined : partials; bitmask |= (isCurry ? WRAP_PARTIAL_FLAG : WRAP_PARTIAL_RIGHT_FLAG); bitmask &= ~(isCurry ? WRAP_PARTIAL_RIGHT_FLAG : WRAP_PARTIAL_FLAG); if (!(bitmask & WRAP_CURRY_BOUND_FLAG)) { bitmask &= ~(WRAP_BIND_FLAG | WRAP_BIND_KEY_FLAG); } var newData = [ func, bitmask, thisArg, newPartials, newHolders, newPartialsRight, newHoldersRight, argPos, ary, arity ]; var result = wrapFunc.apply(undefined, newData); if (isLaziable(func)) { setData(result, newData); } result.placeholder = placeholder; return setWrapToString(result, func, bitmask); } /** * Creates a function like `_.round`. * * @private * @param {string} methodName The name of the `Math` method to use when rounding. * @returns {Function} Returns the new round function. */ function createRound(methodName) { var func = Math[methodName]; return function(number, precision) { number = toNumber(number); precision = precision == null ? 0 : nativeMin(toInteger(precision), 292); if (precision) { // Shift with exponential notation to avoid floating-point issues. // See [MDN](https://mdn.io/round#Examples) for more details. var pair = (toString(number) + 'e').split('e'), value = func(pair[0] + 'e' + (+pair[1] + precision)); pair = (toString(value) + 'e').split('e'); return +(pair[0] + 'e' + (+pair[1] - precision)); } return func(number); }; } /** * Creates a set object of `values`. * * @private * @param {Array} values The values to add to the set. * @returns {Object} Returns the new set. */ var createSet = !(Set && (1 / setToArray(new Set([,-0]))[1]) == INFINITY) ? noop : function(values) { return new Set(values); }; /** * Creates a `_.toPairs` or `_.toPairsIn` function. * * @private * @param {Function} keysFunc The function to get the keys of a given object. * @returns {Function} Returns the new pairs function. */ function createToPairs(keysFunc) { return function(object) { var tag = getTag(object); if (tag == mapTag) { return mapToArray(object); } if (tag == setTag) { return setToPairs(object); } return baseToPairs(object, keysFunc(object)); }; } /** * Creates a function that either curries or invokes `func` with optional * `this` binding and partially applied arguments. * * @private * @param {Function|string} func The function or method name to wrap. * @param {number} bitmask The bitmask flags. * 1 - `_.bind` * 2 - `_.bindKey` * 4 - `_.curry` or `_.curryRight` of a bound function * 8 - `_.curry` * 16 - `_.curryRight` * 32 - `_.partial` * 64 - `_.partialRight` * 128 - `_.rearg` * 256 - `_.ary` * 512 - `_.flip` * @param {*} [thisArg] The `this` binding of `func`. * @param {Array} [partials] The arguments to be partially applied. * @param {Array} [holders] The `partials` placeholder indexes. * @param {Array} [argPos] The argument positions of the new function. * @param {number} [ary] The arity cap of `func`. * @param {number} [arity] The arity of `func`. * @returns {Function} Returns the new wrapped function. */ function createWrap(func, bitmask, thisArg, partials, holders, argPos, ary, arity) { var isBindKey = bitmask & WRAP_BIND_KEY_FLAG; if (!isBindKey && typeof func != 'function') { throw new TypeError(FUNC_ERROR_TEXT); } var length = partials ? partials.length : 0; if (!length) { bitmask &= ~(WRAP_PARTIAL_FLAG | WRAP_PARTIAL_RIGHT_FLAG); partials = holders = undefined; } ary = ary === undefined ? ary : nativeMax(toInteger(ary), 0); arity = arity === undefined ? arity : toInteger(arity); length -= holders ? holders.length : 0; if (bitmask & WRAP_PARTIAL_RIGHT_FLAG) { var partialsRight = partials, holdersRight = holders; partials = holders = undefined; } var data = isBindKey ? undefined : getData(func); var newData = [ func, bitmask, thisArg, partials, holders, partialsRight, holdersRight, argPos, ary, arity ]; if (data) { mergeData(newData, data); } func = newData[0]; bitmask = newData[1]; thisArg = newData[2]; partials = newData[3]; holders = newData[4]; arity = newData[9] = newData[9] === undefined ? (isBindKey ? 0 : func.length) : nativeMax(newData[9] - length, 0); if (!arity && bitmask & (WRAP_CURRY_FLAG | WRAP_CURRY_RIGHT_FLAG)) { bitmask &= ~(WRAP_CURRY_FLAG | WRAP_CURRY_RIGHT_FLAG); } if (!bitmask || bitmask == WRAP_BIND_FLAG) { var result = createBind(func, bitmask, thisArg); } else if (bitmask == WRAP_CURRY_FLAG || bitmask == WRAP_CURRY_RIGHT_FLAG) { result = createCurry(func, bitmask, arity); } else if ((bitmask == WRAP_PARTIAL_FLAG || bitmask == (WRAP_BIND_FLAG | WRAP_PARTIAL_FLAG)) && !holders.length) { result = createPartial(func, bitmask, thisArg, partials); } else { result = createHybrid.apply(undefined, newData); } var setter = data ? baseSetData : setData; return setWrapToString(setter(result, newData), func, bitmask); } /** * Used by `_.defaults` to customize its `_.assignIn` use to assign properties * of source objects to the destination object for all destination properties * that resolve to `undefined`. * * @private * @param {*} objValue The destination value. * @param {*} srcValue The source value. * @param {string} key The key of the property to assign. * @param {Object} object The parent object of `objValue`. * @returns {*} Returns the value to assign. */ function customDefaultsAssignIn(objValue, srcValue, key, object) { if (objValue === undefined || (eq(objValue, objectProto[key]) && !hasOwnProperty.call(object, key))) { return srcValue; } return objValue; } /** * Used by `_.defaultsDeep` to customize its `_.merge` use to merge source * objects into destination objects that are passed thru. * * @private * @param {*} objValue The destination value. * @param {*} srcValue The source value. * @param {string} key The key of the property to merge. * @param {Object} object The parent object of `objValue`. * @param {Object} source The parent object of `srcValue`. * @param {Object} [stack] Tracks traversed source values and their merged * counterparts. * @returns {*} Returns the value to assign. */ function customDefaultsMerge(objValue, srcValue, key, object, source, stack) { if (isObject(objValue) && isObject(srcValue)) { // Recursively merge objects and arrays (susceptible to call stack limits). stack.set(srcValue, objValue); baseMerge(objValue, srcValue, undefined, customDefaultsMerge, stack); stack['delete'](srcValue); } return objValue; } /** * Used by `_.omit` to customize its `_.cloneDeep` use to only clone plain * objects. * * @private * @param {*} value The value to inspect. * @param {string} key The key of the property to inspect. * @returns {*} Returns the uncloned value or `undefined` to defer cloning to `_.cloneDeep`. */ function customOmitClone(value) { return isPlainObject(value) ? undefined : value; } /** * A specialized version of `baseIsEqualDeep` for arrays with support for * partial deep comparisons. * * @private * @param {Array} array The array to compare. * @param {Array} other The other array to compare. * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. * @param {Function} customizer The function to customize comparisons. * @param {Function} equalFunc The function to determine equivalents of values. * @param {Object} stack Tracks traversed `array` and `other` objects. * @returns {boolean} Returns `true` if the arrays are equivalent, else `false`. */ function equalArrays(array, other, bitmask, customizer, equalFunc, stack) { var isPartial = bitmask & COMPARE_PARTIAL_FLAG, arrLength = array.length, othLength = other.length; if (arrLength != othLength && !(isPartial && othLength > arrLength)) { return false; } // Assume cyclic values are equal. var stacked = stack.get(array); if (stacked && stack.get(other)) { return stacked == other; } var index = -1, result = true, seen = (bitmask & COMPARE_UNORDERED_FLAG) ? new SetCache : undefined; stack.set(array, other); stack.set(other, array); // Ignore non-index properties. while (++index < arrLength) { var arrValue = array[index], othValue = other[index]; if (customizer) { var compared = isPartial ? customizer(othValue, arrValue, index, other, array, stack) : customizer(arrValue, othValue, index, array, other, stack); } if (compared !== undefined) { if (compared) { continue; } result = false; break; } // Recursively compare arrays (susceptible to call stack limits). if (seen) { if (!arraySome(other, function(othValue, othIndex) { if (!cacheHas(seen, othIndex) && (arrValue === othValue || equalFunc(arrValue, othValue, bitmask, customizer, stack))) { return seen.push(othIndex); } })) { result = false; break; } } else if (!( arrValue === othValue || equalFunc(arrValue, othValue, bitmask, customizer, stack) )) { result = false; break; } } stack['delete'](array); stack['delete'](other); return result; } /** * A specialized version of `baseIsEqualDeep` for comparing objects of * the same `toStringTag`. * * **Note:** This function only supports comparing values with tags of * `Boolean`, `Date`, `Error`, `Number`, `RegExp`, or `String`. * * @private * @param {Object} object The object to compare. * @param {Object} other The other object to compare. * @param {string} tag The `toStringTag` of the objects to compare. * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. * @param {Function} customizer The function to customize comparisons. * @param {Function} equalFunc The function to determine equivalents of values. * @param {Object} stack Tracks traversed `object` and `other` objects. * @returns {boolean} Returns `true` if the objects are equivalent, else `false`. */ function equalByTag(object, other, tag, bitmask, customizer, equalFunc, stack) { switch (tag) { case dataViewTag: if ((object.byteLength != other.byteLength) || (object.byteOffset != other.byteOffset)) { return false; } object = object.buffer; other = other.buffer; case arrayBufferTag: if ((object.byteLength != other.byteLength) || !equalFunc(new Uint8Array(object), new Uint8Array(other))) { return false; } return true; case boolTag: case dateTag: case numberTag: // Coerce booleans to `1` or `0` and dates to milliseconds. // Invalid dates are coerced to `NaN`. return eq(+object, +other); case errorTag: return object.name == other.name && object.message == other.message; case regexpTag: case stringTag: // Coerce regexes to strings and treat strings, primitives and objects, // as equal. See http://www.ecma-international.org/ecma-262/7.0/#sec-regexp.prototype.tostring // for more details. return object == (other + ''); case mapTag: var convert = mapToArray; case setTag: var isPartial = bitmask & COMPARE_PARTIAL_FLAG; convert || (convert = setToArray); if (object.size != other.size && !isPartial) { return false; } // Assume cyclic values are equal. var stacked = stack.get(object); if (stacked) { return stacked == other; } bitmask |= COMPARE_UNORDERED_FLAG; // Recursively compare objects (susceptible to call stack limits). stack.set(object, other); var result = equalArrays(convert(object), convert(other), bitmask, customizer, equalFunc, stack); stack['delete'](object); return result; case symbolTag: if (symbolValueOf) { return symbolValueOf.call(object) == symbolValueOf.call(other); } } return false; } /** * A specialized version of `baseIsEqualDeep` for objects with support for * partial deep comparisons. * * @private * @param {Object} object The object to compare. * @param {Object} other The other object to compare. * @param {number} bitmask The bitmask flags. See `baseIsEqual` for more details. * @param {Function} customizer The function to customize comparisons. * @param {Function} equalFunc The function to determine equivalents of values. * @param {Object} stack Tracks traversed `object` and `other` objects. * @returns {boolean} Returns `true` if the objects are equivalent, else `false`. */ function equalObjects(object, other, bitmask, customizer, equalFunc, stack) { var isPartial = bitmask & COMPARE_PARTIAL_FLAG, objProps = getAllKeys(object), objLength = objProps.length, othProps = getAllKeys(other), othLength = othProps.length; if (objLength != othLength && !isPartial) { return false; } var index = objLength; while (index--) { var key = objProps[index]; if (!(isPartial ? key in other : hasOwnProperty.call(other, key))) { return false; } } // Assume cyclic values are equal. var stacked = stack.get(object); if (stacked && stack.get(other)) { return stacked == other; } var result = true; stack.set(object, other); stack.set(other, object); var skipCtor = isPartial; while (++index < objLength) { key = objProps[index]; var objValue = object[key], othValue = other[key]; if (customizer) { var compared = isPartial ? customizer(othValue, objValue, key, other, object, stack) : customizer(objValue, othValue, key, object, other, stack); } // Recursively compare objects (susceptible to call stack limits). if (!(compared === undefined ? (objValue === othValue || equalFunc(objValue, othValue, bitmask, customizer, stack)) : compared )) { result = false; break; } skipCtor || (skipCtor = key == 'constructor'); } if (result && !skipCtor) { var objCtor = object.constructor, othCtor = other.constructor; // Non `Object` object instances with different constructors are not equal. if (objCtor != othCtor && ('constructor' in object && 'constructor' in other) && !(typeof objCtor == 'function' && objCtor instanceof objCtor && typeof othCtor == 'function' && othCtor instanceof othCtor)) { result = false; } } stack['delete'](object); stack['delete'](other); return result; } /** * A specialized version of `baseRest` which flattens the rest array. * * @private * @param {Function} func The function to apply a rest parameter to. * @returns {Function} Returns the new function. */ function flatRest(func) { return setToString(overRest(func, undefined, flatten), func + ''); } /** * Creates an array of own enumerable property names and symbols of `object`. * * @private * @param {Object} object The object to query. * @returns {Array} Returns the array of property names and symbols. */ function getAllKeys(object) { return baseGetAllKeys(object, keys, getSymbols); } /** * Creates an array of own and inherited enumerable property names and * symbols of `object`. * * @private * @param {Object} object The object to query. * @returns {Array} Returns the array of property names and symbols. */ function getAllKeysIn(object) { return baseGetAllKeys(object, keysIn, getSymbolsIn); } /** * Gets metadata for `func`. * * @private * @param {Function} func The function to query. * @returns {*} Returns the metadata for `func`. */ var getData = !metaMap ? noop : function(func) { return metaMap.get(func); }; /** * Gets the name of `func`. * * @private * @param {Function} func The function to query. * @returns {string} Returns the function name. */ function getFuncName(func) { var result = (func.name + ''), array = realNames[result], length = hasOwnProperty.call(realNames, result) ? array.length : 0; while (length--) { var data = array[length], otherFunc = data.func; if (otherFunc == null || otherFunc == func) { return data.name; } } return result; } /** * Gets the argument placeholder value for `func`. * * @private * @param {Function} func The function to inspect. * @returns {*} Returns the placeholder value. */ function getHolder(func) { var object = hasOwnProperty.call(lodash, 'placeholder') ? lodash : func; return object.placeholder; } /** * Gets the appropriate "iteratee" function. If `_.iteratee` is customized, * this function returns the custom method, otherwise it returns `baseIteratee`. * If arguments are provided, the chosen function is invoked with them and * its result is returned. * * @private * @param {*} [value] The value to convert to an iteratee. * @param {number} [arity] The arity of the created iteratee. * @returns {Function} Returns the chosen function or its result. */ function getIteratee() { var result = lodash.iteratee || iteratee; result = result === iteratee ? baseIteratee : result; return arguments.length ? result(arguments[0], arguments[1]) : result; } /** * Gets the data for `map`. * * @private * @param {Object} map The map to query. * @param {string} key The reference key. * @returns {*} Returns the map data. */ function getMapData(map, key) { var data = map.__data__; return isKeyable(key) ? data[typeof key == 'string' ? 'string' : 'hash'] : data.map; } /** * Gets the property names, values, and compare flags of `object`. * * @private * @param {Object} object The object to query. * @returns {Array} Returns the match data of `object`. */ function getMatchData(object) { var result = keys(object), length = result.length; while (length--) { var key = result[length], value = object[key]; result[length] = [key, value, isStrictComparable(value)]; } return result; } /** * Gets the native function at `key` of `object`. * * @private * @param {Object} object The object to query. * @param {string} key The key of the method to get. * @returns {*} Returns the function if it's native, else `undefined`. */ function getNative(object, key) { var value = getValue(object, key); return baseIsNative(value) ? value : undefined; } /** * A specialized version of `baseGetTag` which ignores `Symbol.toStringTag` values. * * @private * @param {*} value The value to query. * @returns {string} Returns the raw `toStringTag`. */ function getRawTag(value) { var isOwn = hasOwnProperty.call(value, symToStringTag), tag = value[symToStringTag]; try { value[symToStringTag] = undefined; var unmasked = true; } catch (e) {} var result = nativeObjectToString.call(value); if (unmasked) { if (isOwn) { value[symToStringTag] = tag; } else { delete value[symToStringTag]; } } return result; } /** * Creates an array of the own enumerable symbols of `object`. * * @private * @param {Object} object The object to query. * @returns {Array} Returns the array of symbols. */ var getSymbols = !nativeGetSymbols ? stubArray : function(object) { if (object == null) { return []; } object = Object(object); return arrayFilter(nativeGetSymbols(object), function(symbol) { return propertyIsEnumerable.call(object, symbol); }); }; /** * Creates an array of the own and inherited enumerable symbols of `object`. * * @private * @param {Object} object The object to query. * @returns {Array} Returns the array of symbols. */ var getSymbolsIn = !nativeGetSymbols ? stubArray : function(object) { var result = []; while (object) { arrayPush(result, getSymbols(object)); object = getPrototype(object); } return result; }; /** * Gets the `toStringTag` of `value`. * * @private * @param {*} value The value to query. * @returns {string} Returns the `toStringTag`. */ var getTag = baseGetTag; // Fallback for data views, maps, sets, and weak maps in IE 11 and promises in Node.js < 6. if ((DataView && getTag(new DataView(new ArrayBuffer(1))) != dataViewTag) || (Map && getTag(new Map) != mapTag) || (Promise && getTag(Promise.resolve()) != promiseTag) || (Set && getTag(new Set) != setTag) || (WeakMap && getTag(new WeakMap) != weakMapTag)) { getTag = function(value) { var result = baseGetTag(value), Ctor = result == objectTag ? value.constructor : undefined, ctorString = Ctor ? toSource(Ctor) : ''; if (ctorString) { switch (ctorString) { case dataViewCtorString: return dataViewTag; case mapCtorString: return mapTag; case promiseCtorString: return promiseTag; case setCtorString: return setTag; case weakMapCtorString: return weakMapTag; } } return result; }; } /** * Gets the view, applying any `transforms` to the `start` and `end` positions. * * @private * @param {number} start The start of the view. * @param {number} end The end of the view. * @param {Array} transforms The transformations to apply to the view. * @returns {Object} Returns an object containing the `start` and `end` * positions of the view. */ function getView(start, end, transforms) { var index = -1, length = transforms.length; while (++index < length) { var data = transforms[index], size = data.size; switch (data.type) { case 'drop': start += size; break; case 'dropRight': end -= size; break; case 'take': end = nativeMin(end, start + size); break; case 'takeRight': start = nativeMax(start, end - size); break; } } return { 'start': start, 'end': end }; } /** * Extracts wrapper details from the `source` body comment. * * @private * @param {string} source The source to inspect. * @returns {Array} Returns the wrapper details. */ function getWrapDetails(source) { var match = source.match(reWrapDetails); return match ? match[1].split(reSplitDetails) : []; } /** * Checks if `path` exists on `object`. * * @private * @param {Object} object The object to query. * @param {Array|string} path The path to check. * @param {Function} hasFunc The function to check properties. * @returns {boolean} Returns `true` if `path` exists, else `false`. */ function hasPath(object, path, hasFunc) { path = castPath(path, object); var index = -1, length = path.length, result = false; while (++index < length) { var key = toKey(path[index]); if (!(result = object != null && hasFunc(object, key))) { break; } object = object[key]; } if (result || ++index != length) { return result; } length = object == null ? 0 : object.length; return !!length && isLength(length) && isIndex(key, length) && (isArray(object) || isArguments(object)); } /** * Initializes an array clone. * * @private * @param {Array} array The array to clone. * @returns {Array} Returns the initialized clone. */ function initCloneArray(array) { var length = array.length, result = new array.constructor(length); // Add properties assigned by `RegExp#exec`. if (length && typeof array[0] == 'string' && hasOwnProperty.call(array, 'index')) { result.index = array.index; result.input = array.input; } return result; } /** * Initializes an object clone. * * @private * @param {Object} object The object to clone. * @returns {Object} Returns the initialized clone. */ function initCloneObject(object) { return (typeof object.constructor == 'function' && !isPrototype(object)) ? baseCreate(getPrototype(object)) : {}; } /** * Initializes an object clone based on its `toStringTag`. * * **Note:** This function only supports cloning values with tags of * `Boolean`, `Date`, `Error`, `Map`, `Number`, `RegExp`, `Set`, or `String`. * * @private * @param {Object} object The object to clone. * @param {string} tag The `toStringTag` of the object to clone. * @param {boolean} [isDeep] Specify a deep clone. * @returns {Object} Returns the initialized clone. */ function initCloneByTag(object, tag, isDeep) { var Ctor = object.constructor; switch (tag) { case arrayBufferTag: return cloneArrayBuffer(object); case boolTag: case dateTag: return new Ctor(+object); case dataViewTag: return cloneDataView(object, isDeep); case float32Tag: case float64Tag: case int8Tag: case int16Tag: case int32Tag: case uint8Tag: case uint8ClampedTag: case uint16Tag: case uint32Tag: return cloneTypedArray(object, isDeep); case mapTag: return new Ctor; case numberTag: case stringTag: return new Ctor(object); case regexpTag: return cloneRegExp(object); case setTag: return new Ctor; case symbolTag: return cloneSymbol(object); } } /** * Inserts wrapper `details` in a comment at the top of the `source` body. * * @private * @param {string} source The source to modify. * @returns {Array} details The details to insert. * @returns {string} Returns the modified source. */ function insertWrapDetails(source, details) { var length = details.length; if (!length) { return source; } var lastIndex = length - 1; details[lastIndex] = (length > 1 ? '& ' : '') + details[lastIndex]; details = details.join(length > 2 ? ', ' : ' '); return source.replace(reWrapComment, '{\n/* [wrapped with ' + details + '] */\n'); } /** * Checks if `value` is a flattenable `arguments` object or array. * * @private * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is flattenable, else `false`. */ function isFlattenable(value) { return isArray(value) || isArguments(value) || !!(spreadableSymbol && value && value[spreadableSymbol]); } /** * Checks if `value` is a valid array-like index. * * @private * @param {*} value The value to check. * @param {number} [length=MAX_SAFE_INTEGER] The upper bounds of a valid index. * @returns {boolean} Returns `true` if `value` is a valid index, else `false`. */ function isIndex(value, length) { var type = typeof value; length = length == null ? MAX_SAFE_INTEGER : length; return !!length && (type == 'number' || (type != 'symbol' && reIsUint.test(value))) && (value > -1 && value % 1 == 0 && value < length); } /** * Checks if the given arguments are from an iteratee call. * * @private * @param {*} value The potential iteratee value argument. * @param {*} index The potential iteratee index or key argument. * @param {*} object The potential iteratee object argument. * @returns {boolean} Returns `true` if the arguments are from an iteratee call, * else `false`. */ function isIterateeCall(value, index, object) { if (!isObject(object)) { return false; } var type = typeof index; if (type == 'number' ? (isArrayLike(object) && isIndex(index, object.length)) : (type == 'string' && index in object) ) { return eq(object[index], value); } return false; } /** * Checks if `value` is a property name and not a property path. * * @private * @param {*} value The value to check. * @param {Object} [object] The object to query keys on. * @returns {boolean} Returns `true` if `value` is a property name, else `false`. */ function isKey(value, object) { if (isArray(value)) { return false; } var type = typeof value; if (type == 'number' || type == 'symbol' || type == 'boolean' || value == null || isSymbol(value)) { return true; } return reIsPlainProp.test(value) || !reIsDeepProp.test(value) || (object != null && value in Object(object)); } /** * Checks if `value` is suitable for use as unique object key. * * @private * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is suitable, else `false`. */ function isKeyable(value) { var type = typeof value; return (type == 'string' || type == 'number' || type == 'symbol' || type == 'boolean') ? (value !== '__proto__') : (value === null); } /** * Checks if `func` has a lazy counterpart. * * @private * @param {Function} func The function to check. * @returns {boolean} Returns `true` if `func` has a lazy counterpart, * else `false`. */ function isLaziable(func) { var funcName = getFuncName(func), other = lodash[funcName]; if (typeof other != 'function' || !(funcName in LazyWrapper.prototype)) { return false; } if (func === other) { return true; } var data = getData(other); return !!data && func === data[0]; } /** * Checks if `func` has its source masked. * * @private * @param {Function} func The function to check. * @returns {boolean} Returns `true` if `func` is masked, else `false`. */ function isMasked(func) { return !!maskSrcKey && (maskSrcKey in func); } /** * Checks if `func` is capable of being masked. * * @private * @param {*} value The value to check. * @returns {boolean} Returns `true` if `func` is maskable, else `false`. */ var isMaskable = coreJsData ? isFunction : stubFalse; /** * Checks if `value` is likely a prototype object. * * @private * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a prototype, else `false`. */ function isPrototype(value) { var Ctor = value && value.constructor, proto = (typeof Ctor == 'function' && Ctor.prototype) || objectProto; return value === proto; } /** * Checks if `value` is suitable for strict equality comparisons, i.e. `===`. * * @private * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` if suitable for strict * equality comparisons, else `false`. */ function isStrictComparable(value) { return value === value && !isObject(value); } /** * A specialized version of `matchesProperty` for source values suitable * for strict equality comparisons, i.e. `===`. * * @private * @param {string} key The key of the property to get. * @param {*} srcValue The value to match. * @returns {Function} Returns the new spec function. */ function matchesStrictComparable(key, srcValue) { return function(object) { if (object == null) { return false; } return object[key] === srcValue && (srcValue !== undefined || (key in Object(object))); }; } /** * A specialized version of `_.memoize` which clears the memoized function's * cache when it exceeds `MAX_MEMOIZE_SIZE`. * * @private * @param {Function} func The function to have its output memoized. * @returns {Function} Returns the new memoized function. */ function memoizeCapped(func) { var result = memoize(func, function(key) { if (cache.size === MAX_MEMOIZE_SIZE) { cache.clear(); } return key; }); var cache = result.cache; return result; } /** * Merges the function metadata of `source` into `data`. * * Merging metadata reduces the number of wrappers used to invoke a function. * This is possible because methods like `_.bind`, `_.curry`, and `_.partial` * may be applied regardless of execution order. Methods like `_.ary` and * `_.rearg` modify function arguments, making the order in which they are * executed important, preventing the merging of metadata. However, we make * an exception for a safe combined case where curried functions have `_.ary` * and or `_.rearg` applied. * * @private * @param {Array} data The destination metadata. * @param {Array} source The source metadata. * @returns {Array} Returns `data`. */ function mergeData(data, source) { var bitmask = data[1], srcBitmask = source[1], newBitmask = bitmask | srcBitmask, isCommon = newBitmask < (WRAP_BIND_FLAG | WRAP_BIND_KEY_FLAG | WRAP_ARY_FLAG); var isCombo = ((srcBitmask == WRAP_ARY_FLAG) && (bitmask == WRAP_CURRY_FLAG)) || ((srcBitmask == WRAP_ARY_FLAG) && (bitmask == WRAP_REARG_FLAG) && (data[7].length <= source[8])) || ((srcBitmask == (WRAP_ARY_FLAG | WRAP_REARG_FLAG)) && (source[7].length <= source[8]) && (bitmask == WRAP_CURRY_FLAG)); // Exit early if metadata can't be merged. if (!(isCommon || isCombo)) { return data; } // Use source `thisArg` if available. if (srcBitmask & WRAP_BIND_FLAG) { data[2] = source[2]; // Set when currying a bound function. newBitmask |= bitmask & WRAP_BIND_FLAG ? 0 : WRAP_CURRY_BOUND_FLAG; } // Compose partial arguments. var value = source[3]; if (value) { var partials = data[3]; data[3] = partials ? composeArgs(partials, value, source[4]) : value; data[4] = partials ? replaceHolders(data[3], PLACEHOLDER) : source[4]; } // Compose partial right arguments. value = source[5]; if (value) { partials = data[5]; data[5] = partials ? composeArgsRight(partials, value, source[6]) : value; data[6] = partials ? replaceHolders(data[5], PLACEHOLDER) : source[6]; } // Use source `argPos` if available. value = source[7]; if (value) { data[7] = value; } // Use source `ary` if it's smaller. if (srcBitmask & WRAP_ARY_FLAG) { data[8] = data[8] == null ? source[8] : nativeMin(data[8], source[8]); } // Use source `arity` if one is not provided. if (data[9] == null) { data[9] = source[9]; } // Use source `func` and merge bitmasks. data[0] = source[0]; data[1] = newBitmask; return data; } /** * This function is like * [`Object.keys`](http://ecma-international.org/ecma-262/7.0/#sec-object.keys) * except that it includes inherited enumerable properties. * * @private * @param {Object} object The object to query. * @returns {Array} Returns the array of property names. */ function nativeKeysIn(object) { var result = []; if (object != null) { for (var key in Object(object)) { result.push(key); } } return result; } /** * Converts `value` to a string using `Object.prototype.toString`. * * @private * @param {*} value The value to convert. * @returns {string} Returns the converted string. */ function objectToString(value) { return nativeObjectToString.call(value); } /** * A specialized version of `baseRest` which transforms the rest array. * * @private * @param {Function} func The function to apply a rest parameter to. * @param {number} [start=func.length-1] The start position of the rest parameter. * @param {Function} transform The rest array transform. * @returns {Function} Returns the new function. */ function overRest(func, start, transform) { start = nativeMax(start === undefined ? (func.length - 1) : start, 0); return function() { var args = arguments, index = -1, length = nativeMax(args.length - start, 0), array = Array(length); while (++index < length) { array[index] = args[start + index]; } index = -1; var otherArgs = Array(start + 1); while (++index < start) { otherArgs[index] = args[index]; } otherArgs[start] = transform(array); return apply(func, this, otherArgs); }; } /** * Gets the parent value at `path` of `object`. * * @private * @param {Object} object The object to query. * @param {Array} path The path to get the parent value of. * @returns {*} Returns the parent value. */ function parent(object, path) { return path.length < 2 ? object : baseGet(object, baseSlice(path, 0, -1)); } /** * Reorder `array` according to the specified indexes where the element at * the first index is assigned as the first element, the element at * the second index is assigned as the second element, and so on. * * @private * @param {Array} array The array to reorder. * @param {Array} indexes The arranged array indexes. * @returns {Array} Returns `array`. */ function reorder(array, indexes) { var arrLength = array.length, length = nativeMin(indexes.length, arrLength), oldArray = copyArray(array); while (length--) { var index = indexes[length]; array[length] = isIndex(index, arrLength) ? oldArray[index] : undefined; } return array; } /** * Gets the value at `key`, unless `key` is "__proto__". * * @private * @param {Object} object The object to query. * @param {string} key The key of the property to get. * @returns {*} Returns the property value. */ function safeGet(object, key) { if (key == '__proto__') { return; } return object[key]; } /** * Sets metadata for `func`. * * **Note:** If this function becomes hot, i.e. is invoked a lot in a short * period of time, it will trip its breaker and transition to an identity * function to avoid garbage collection pauses in V8. See * [V8 issue 2070](https://bugs.chromium.org/p/v8/issues/detail?id=2070) * for more details. * * @private * @param {Function} func The function to associate metadata with. * @param {*} data The metadata. * @returns {Function} Returns `func`. */ var setData = shortOut(baseSetData); /** * A simple wrapper around the global [`setTimeout`](https://mdn.io/setTimeout). * * @private * @param {Function} func The function to delay. * @param {number} wait The number of milliseconds to delay invocation. * @returns {number|Object} Returns the timer id or timeout object. */ var setTimeout = ctxSetTimeout || function(func, wait) { return root.setTimeout(func, wait); }; /** * Sets the `toString` method of `func` to return `string`. * * @private * @param {Function} func The function to modify. * @param {Function} string The `toString` result. * @returns {Function} Returns `func`. */ var setToString = shortOut(baseSetToString); /** * Sets the `toString` method of `wrapper` to mimic the source of `reference` * with wrapper details in a comment at the top of the source body. * * @private * @param {Function} wrapper The function to modify. * @param {Function} reference The reference function. * @param {number} bitmask The bitmask flags. See `createWrap` for more details. * @returns {Function} Returns `wrapper`. */ function setWrapToString(wrapper, reference, bitmask) { var source = (reference + ''); return setToString(wrapper, insertWrapDetails(source, updateWrapDetails(getWrapDetails(source), bitmask))); } /** * Creates a function that'll short out and invoke `identity` instead * of `func` when it's called `HOT_COUNT` or more times in `HOT_SPAN` * milliseconds. * * @private * @param {Function} func The function to restrict. * @returns {Function} Returns the new shortable function. */ function shortOut(func) { var count = 0, lastCalled = 0; return function() { var stamp = nativeNow(), remaining = HOT_SPAN - (stamp - lastCalled); lastCalled = stamp; if (remaining > 0) { if (++count >= HOT_COUNT) { return arguments[0]; } } else { count = 0; } return func.apply(undefined, arguments); }; } /** * A specialized version of `_.shuffle` which mutates and sets the size of `array`. * * @private * @param {Array} array The array to shuffle. * @param {number} [size=array.length] The size of `array`. * @returns {Array} Returns `array`. */ function shuffleSelf(array, size) { var index = -1, length = array.length, lastIndex = length - 1; size = size === undefined ? length : size; while (++index < size) { var rand = baseRandom(index, lastIndex), value = array[rand]; array[rand] = array[index]; array[index] = value; } array.length = size; return array; } /** * Converts `string` to a property path array. * * @private * @param {string} string The string to convert. * @returns {Array} Returns the property path array. */ var stringToPath = memoizeCapped(function(string) { var result = []; if (string.charCodeAt(0) === 46 /* . */) { result.push(''); } string.replace(rePropName, function(match, number, quote, subString) { result.push(quote ? subString.replace(reEscapeChar, '$1') : (number || match)); }); return result; }); /** * Converts `value` to a string key if it's not a string or symbol. * * @private * @param {*} value The value to inspect. * @returns {string|symbol} Returns the key. */ function toKey(value) { if (typeof value == 'string' || isSymbol(value)) { return value; } var result = (value + ''); return (result == '0' && (1 / value) == -INFINITY) ? '-0' : result; } /** * Converts `func` to its source code. * * @private * @param {Function} func The function to convert. * @returns {string} Returns the source code. */ function toSource(func) { if (func != null) { try { return funcToString.call(func); } catch (e) {} try { return (func + ''); } catch (e) {} } return ''; } /** * Updates wrapper `details` based on `bitmask` flags. * * @private * @returns {Array} details The details to modify. * @param {number} bitmask The bitmask flags. See `createWrap` for more details. * @returns {Array} Returns `details`. */ function updateWrapDetails(details, bitmask) { arrayEach(wrapFlags, function(pair) { var value = '_.' + pair[0]; if ((bitmask & pair[1]) && !arrayIncludes(details, value)) { details.push(value); } }); return details.sort(); } /** * Creates a clone of `wrapper`. * * @private * @param {Object} wrapper The wrapper to clone. * @returns {Object} Returns the cloned wrapper. */ function wrapperClone(wrapper) { if (wrapper instanceof LazyWrapper) { return wrapper.clone(); } var result = new LodashWrapper(wrapper.__wrapped__, wrapper.__chain__); result.__actions__ = copyArray(wrapper.__actions__); result.__index__ = wrapper.__index__; result.__values__ = wrapper.__values__; return result; } /*------------------------------------------------------------------------*/ /** * Creates an array of elements split into groups the length of `size`. * If `array` can't be split evenly, the final chunk will be the remaining * elements. * * @static * @memberOf _ * @since 3.0.0 * @category Array * @param {Array} array The array to process. * @param {number} [size=1] The length of each chunk * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. * @returns {Array} Returns the new array of chunks. * @example * * _.chunk(['a', 'b', 'c', 'd'], 2); * // => [['a', 'b'], ['c', 'd']] * * _.chunk(['a', 'b', 'c', 'd'], 3); * // => [['a', 'b', 'c'], ['d']] */ function chunk(array, size, guard) { if ((guard ? isIterateeCall(array, size, guard) : size === undefined)) { size = 1; } else { size = nativeMax(toInteger(size), 0); } var length = array == null ? 0 : array.length; if (!length || size < 1) { return []; } var index = 0, resIndex = 0, result = Array(nativeCeil(length / size)); while (index < length) { result[resIndex++] = baseSlice(array, index, (index += size)); } return result; } /** * Creates an array with all falsey values removed. The values `false`, `null`, * `0`, `""`, `undefined`, and `NaN` are falsey. * * @static * @memberOf _ * @since 0.1.0 * @category Array * @param {Array} array The array to compact. * @returns {Array} Returns the new array of filtered values. * @example * * _.compact([0, 1, false, 2, '', 3]); * // => [1, 2, 3] */ function compact(array) { var index = -1, length = array == null ? 0 : array.length, resIndex = 0, result = []; while (++index < length) { var value = array[index]; if (value) { result[resIndex++] = value; } } return result; } /** * Creates a new array concatenating `array` with any additional arrays * and/or values. * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The array to concatenate. * @param {...*} [values] The values to concatenate. * @returns {Array} Returns the new concatenated array. * @example * * var array = [1]; * var other = _.concat(array, 2, [3], [[4]]); * * console.log(other); * // => [1, 2, 3, [4]] * * console.log(array); * // => [1] */ function concat() { var length = arguments.length; if (!length) { return []; } var args = Array(length - 1), array = arguments[0], index = length; while (index--) { args[index - 1] = arguments[index]; } return arrayPush(isArray(array) ? copyArray(array) : [array], baseFlatten(args, 1)); } /** * Creates an array of `array` values not included in the other given arrays * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) * for equality comparisons. The order and references of result values are * determined by the first array. * * **Note:** Unlike `_.pullAll`, this method returns a new array. * * @static * @memberOf _ * @since 0.1.0 * @category Array * @param {Array} array The array to inspect. * @param {...Array} [values] The values to exclude. * @returns {Array} Returns the new array of filtered values. * @see _.without, _.xor * @example * * _.difference([2, 1], [2, 3]); * // => [1] */ var difference = baseRest(function(array, values) { return isArrayLikeObject(array) ? baseDifference(array, baseFlatten(values, 1, isArrayLikeObject, true)) : []; }); /** * This method is like `_.difference` except that it accepts `iteratee` which * is invoked for each element of `array` and `values` to generate the criterion * by which they're compared. The order and references of result values are * determined by the first array. The iteratee is invoked with one argument: * (value). * * **Note:** Unlike `_.pullAllBy`, this method returns a new array. * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The array to inspect. * @param {...Array} [values] The values to exclude. * @param {Function} [iteratee=_.identity] The iteratee invoked per element. * @returns {Array} Returns the new array of filtered values. * @example * * _.differenceBy([2.1, 1.2], [2.3, 3.4], Math.floor); * // => [1.2] * * // The `_.property` iteratee shorthand. * _.differenceBy([{ 'x': 2 }, { 'x': 1 }], [{ 'x': 1 }], 'x'); * // => [{ 'x': 2 }] */ var differenceBy = baseRest(function(array, values) { var iteratee = last(values); if (isArrayLikeObject(iteratee)) { iteratee = undefined; } return isArrayLikeObject(array) ? baseDifference(array, baseFlatten(values, 1, isArrayLikeObject, true), getIteratee(iteratee, 2)) : []; }); /** * This method is like `_.difference` except that it accepts `comparator` * which is invoked to compare elements of `array` to `values`. The order and * references of result values are determined by the first array. The comparator * is invoked with two arguments: (arrVal, othVal). * * **Note:** Unlike `_.pullAllWith`, this method returns a new array. * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The array to inspect. * @param {...Array} [values] The values to exclude. * @param {Function} [comparator] The comparator invoked per element. * @returns {Array} Returns the new array of filtered values. * @example * * var objects = [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }]; * * _.differenceWith(objects, [{ 'x': 1, 'y': 2 }], _.isEqual); * // => [{ 'x': 2, 'y': 1 }] */ var differenceWith = baseRest(function(array, values) { var comparator = last(values); if (isArrayLikeObject(comparator)) { comparator = undefined; } return isArrayLikeObject(array) ? baseDifference(array, baseFlatten(values, 1, isArrayLikeObject, true), undefined, comparator) : []; }); /** * Creates a slice of `array` with `n` elements dropped from the beginning. * * @static * @memberOf _ * @since 0.5.0 * @category Array * @param {Array} array The array to query. * @param {number} [n=1] The number of elements to drop. * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. * @returns {Array} Returns the slice of `array`. * @example * * _.drop([1, 2, 3]); * // => [2, 3] * * _.drop([1, 2, 3], 2); * // => [3] * * _.drop([1, 2, 3], 5); * // => [] * * _.drop([1, 2, 3], 0); * // => [1, 2, 3] */ function drop(array, n, guard) { var length = array == null ? 0 : array.length; if (!length) { return []; } n = (guard || n === undefined) ? 1 : toInteger(n); return baseSlice(array, n < 0 ? 0 : n, length); } /** * Creates a slice of `array` with `n` elements dropped from the end. * * @static * @memberOf _ * @since 3.0.0 * @category Array * @param {Array} array The array to query. * @param {number} [n=1] The number of elements to drop. * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. * @returns {Array} Returns the slice of `array`. * @example * * _.dropRight([1, 2, 3]); * // => [1, 2] * * _.dropRight([1, 2, 3], 2); * // => [1] * * _.dropRight([1, 2, 3], 5); * // => [] * * _.dropRight([1, 2, 3], 0); * // => [1, 2, 3] */ function dropRight(array, n, guard) { var length = array == null ? 0 : array.length; if (!length) { return []; } n = (guard || n === undefined) ? 1 : toInteger(n); n = length - n; return baseSlice(array, 0, n < 0 ? 0 : n); } /** * Creates a slice of `array` excluding elements dropped from the end. * Elements are dropped until `predicate` returns falsey. The predicate is * invoked with three arguments: (value, index, array). * * @static * @memberOf _ * @since 3.0.0 * @category Array * @param {Array} array The array to query. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @returns {Array} Returns the slice of `array`. * @example * * var users = [ * { 'user': 'barney', 'active': true }, * { 'user': 'fred', 'active': false }, * { 'user': 'pebbles', 'active': false } * ]; * * _.dropRightWhile(users, function(o) { return !o.active; }); * // => objects for ['barney'] * * // The `_.matches` iteratee shorthand. * _.dropRightWhile(users, { 'user': 'pebbles', 'active': false }); * // => objects for ['barney', 'fred'] * * // The `_.matchesProperty` iteratee shorthand. * _.dropRightWhile(users, ['active', false]); * // => objects for ['barney'] * * // The `_.property` iteratee shorthand. * _.dropRightWhile(users, 'active'); * // => objects for ['barney', 'fred', 'pebbles'] */ function dropRightWhile(array, predicate) { return (array && array.length) ? baseWhile(array, getIteratee(predicate, 3), true, true) : []; } /** * Creates a slice of `array` excluding elements dropped from the beginning. * Elements are dropped until `predicate` returns falsey. The predicate is * invoked with three arguments: (value, index, array). * * @static * @memberOf _ * @since 3.0.0 * @category Array * @param {Array} array The array to query. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @returns {Array} Returns the slice of `array`. * @example * * var users = [ * { 'user': 'barney', 'active': false }, * { 'user': 'fred', 'active': false }, * { 'user': 'pebbles', 'active': true } * ]; * * _.dropWhile(users, function(o) { return !o.active; }); * // => objects for ['pebbles'] * * // The `_.matches` iteratee shorthand. * _.dropWhile(users, { 'user': 'barney', 'active': false }); * // => objects for ['fred', 'pebbles'] * * // The `_.matchesProperty` iteratee shorthand. * _.dropWhile(users, ['active', false]); * // => objects for ['pebbles'] * * // The `_.property` iteratee shorthand. * _.dropWhile(users, 'active'); * // => objects for ['barney', 'fred', 'pebbles'] */ function dropWhile(array, predicate) { return (array && array.length) ? baseWhile(array, getIteratee(predicate, 3), true) : []; } /** * Fills elements of `array` with `value` from `start` up to, but not * including, `end`. * * **Note:** This method mutates `array`. * * @static * @memberOf _ * @since 3.2.0 * @category Array * @param {Array} array The array to fill. * @param {*} value The value to fill `array` with. * @param {number} [start=0] The start position. * @param {number} [end=array.length] The end position. * @returns {Array} Returns `array`. * @example * * var array = [1, 2, 3]; * * _.fill(array, 'a'); * console.log(array); * // => ['a', 'a', 'a'] * * _.fill(Array(3), 2); * // => [2, 2, 2] * * _.fill([4, 6, 8, 10], '*', 1, 3); * // => [4, '*', '*', 10] */ function fill(array, value, start, end) { var length = array == null ? 0 : array.length; if (!length) { return []; } if (start && typeof start != 'number' && isIterateeCall(array, value, start)) { start = 0; end = length; } return baseFill(array, value, start, end); } /** * This method is like `_.find` except that it returns the index of the first * element `predicate` returns truthy for instead of the element itself. * * @static * @memberOf _ * @since 1.1.0 * @category Array * @param {Array} array The array to inspect. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @param {number} [fromIndex=0] The index to search from. * @returns {number} Returns the index of the found element, else `-1`. * @example * * var users = [ * { 'user': 'barney', 'active': false }, * { 'user': 'fred', 'active': false }, * { 'user': 'pebbles', 'active': true } * ]; * * _.findIndex(users, function(o) { return o.user == 'barney'; }); * // => 0 * * // The `_.matches` iteratee shorthand. * _.findIndex(users, { 'user': 'fred', 'active': false }); * // => 1 * * // The `_.matchesProperty` iteratee shorthand. * _.findIndex(users, ['active', false]); * // => 0 * * // The `_.property` iteratee shorthand. * _.findIndex(users, 'active'); * // => 2 */ function findIndex(array, predicate, fromIndex) { var length = array == null ? 0 : array.length; if (!length) { return -1; } var index = fromIndex == null ? 0 : toInteger(fromIndex); if (index < 0) { index = nativeMax(length + index, 0); } return baseFindIndex(array, getIteratee(predicate, 3), index); } /** * This method is like `_.findIndex` except that it iterates over elements * of `collection` from right to left. * * @static * @memberOf _ * @since 2.0.0 * @category Array * @param {Array} array The array to inspect. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @param {number} [fromIndex=array.length-1] The index to search from. * @returns {number} Returns the index of the found element, else `-1`. * @example * * var users = [ * { 'user': 'barney', 'active': true }, * { 'user': 'fred', 'active': false }, * { 'user': 'pebbles', 'active': false } * ]; * * _.findLastIndex(users, function(o) { return o.user == 'pebbles'; }); * // => 2 * * // The `_.matches` iteratee shorthand. * _.findLastIndex(users, { 'user': 'barney', 'active': true }); * // => 0 * * // The `_.matchesProperty` iteratee shorthand. * _.findLastIndex(users, ['active', false]); * // => 2 * * // The `_.property` iteratee shorthand. * _.findLastIndex(users, 'active'); * // => 0 */ function findLastIndex(array, predicate, fromIndex) { var length = array == null ? 0 : array.length; if (!length) { return -1; } var index = length - 1; if (fromIndex !== undefined) { index = toInteger(fromIndex); index = fromIndex < 0 ? nativeMax(length + index, 0) : nativeMin(index, length - 1); } return baseFindIndex(array, getIteratee(predicate, 3), index, true); } /** * Flattens `array` a single level deep. * * @static * @memberOf _ * @since 0.1.0 * @category Array * @param {Array} array The array to flatten. * @returns {Array} Returns the new flattened array. * @example * * _.flatten([1, [2, [3, [4]], 5]]); * // => [1, 2, [3, [4]], 5] */ function flatten(array) { var length = array == null ? 0 : array.length; return length ? baseFlatten(array, 1) : []; } /** * Recursively flattens `array`. * * @static * @memberOf _ * @since 3.0.0 * @category Array * @param {Array} array The array to flatten. * @returns {Array} Returns the new flattened array. * @example * * _.flattenDeep([1, [2, [3, [4]], 5]]); * // => [1, 2, 3, 4, 5] */ function flattenDeep(array) { var length = array == null ? 0 : array.length; return length ? baseFlatten(array, INFINITY) : []; } /** * Recursively flatten `array` up to `depth` times. * * @static * @memberOf _ * @since 4.4.0 * @category Array * @param {Array} array The array to flatten. * @param {number} [depth=1] The maximum recursion depth. * @returns {Array} Returns the new flattened array. * @example * * var array = [1, [2, [3, [4]], 5]]; * * _.flattenDepth(array, 1); * // => [1, 2, [3, [4]], 5] * * _.flattenDepth(array, 2); * // => [1, 2, 3, [4], 5] */ function flattenDepth(array, depth) { var length = array == null ? 0 : array.length; if (!length) { return []; } depth = depth === undefined ? 1 : toInteger(depth); return baseFlatten(array, depth); } /** * The inverse of `_.toPairs`; this method returns an object composed * from key-value `pairs`. * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} pairs The key-value pairs. * @returns {Object} Returns the new object. * @example * * _.fromPairs([['a', 1], ['b', 2]]); * // => { 'a': 1, 'b': 2 } */ function fromPairs(pairs) { var index = -1, length = pairs == null ? 0 : pairs.length, result = {}; while (++index < length) { var pair = pairs[index]; result[pair[0]] = pair[1]; } return result; } /** * Gets the first element of `array`. * * @static * @memberOf _ * @since 0.1.0 * @alias first * @category Array * @param {Array} array The array to query. * @returns {*} Returns the first element of `array`. * @example * * _.head([1, 2, 3]); * // => 1 * * _.head([]); * // => undefined */ function head(array) { return (array && array.length) ? array[0] : undefined; } /** * Gets the index at which the first occurrence of `value` is found in `array` * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) * for equality comparisons. If `fromIndex` is negative, it's used as the * offset from the end of `array`. * * @static * @memberOf _ * @since 0.1.0 * @category Array * @param {Array} array The array to inspect. * @param {*} value The value to search for. * @param {number} [fromIndex=0] The index to search from. * @returns {number} Returns the index of the matched value, else `-1`. * @example * * _.indexOf([1, 2, 1, 2], 2); * // => 1 * * // Search from the `fromIndex`. * _.indexOf([1, 2, 1, 2], 2, 2); * // => 3 */ function indexOf(array, value, fromIndex) { var length = array == null ? 0 : array.length; if (!length) { return -1; } var index = fromIndex == null ? 0 : toInteger(fromIndex); if (index < 0) { index = nativeMax(length + index, 0); } return baseIndexOf(array, value, index); } /** * Gets all but the last element of `array`. * * @static * @memberOf _ * @since 0.1.0 * @category Array * @param {Array} array The array to query. * @returns {Array} Returns the slice of `array`. * @example * * _.initial([1, 2, 3]); * // => [1, 2] */ function initial(array) { var length = array == null ? 0 : array.length; return length ? baseSlice(array, 0, -1) : []; } /** * Creates an array of unique values that are included in all given arrays * using [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) * for equality comparisons. The order and references of result values are * determined by the first array. * * @static * @memberOf _ * @since 0.1.0 * @category Array * @param {...Array} [arrays] The arrays to inspect. * @returns {Array} Returns the new array of intersecting values. * @example * * _.intersection([2, 1], [2, 3]); * // => [2] */ var intersection = baseRest(function(arrays) { var mapped = arrayMap(arrays, castArrayLikeObject); return (mapped.length && mapped[0] === arrays[0]) ? baseIntersection(mapped) : []; }); /** * This method is like `_.intersection` except that it accepts `iteratee` * which is invoked for each element of each `arrays` to generate the criterion * by which they're compared. The order and references of result values are * determined by the first array. The iteratee is invoked with one argument: * (value). * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {...Array} [arrays] The arrays to inspect. * @param {Function} [iteratee=_.identity] The iteratee invoked per element. * @returns {Array} Returns the new array of intersecting values. * @example * * _.intersectionBy([2.1, 1.2], [2.3, 3.4], Math.floor); * // => [2.1] * * // The `_.property` iteratee shorthand. * _.intersectionBy([{ 'x': 1 }], [{ 'x': 2 }, { 'x': 1 }], 'x'); * // => [{ 'x': 1 }] */ var intersectionBy = baseRest(function(arrays) { var iteratee = last(arrays), mapped = arrayMap(arrays, castArrayLikeObject); if (iteratee === last(mapped)) { iteratee = undefined; } else { mapped.pop(); } return (mapped.length && mapped[0] === arrays[0]) ? baseIntersection(mapped, getIteratee(iteratee, 2)) : []; }); /** * This method is like `_.intersection` except that it accepts `comparator` * which is invoked to compare elements of `arrays`. The order and references * of result values are determined by the first array. The comparator is * invoked with two arguments: (arrVal, othVal). * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {...Array} [arrays] The arrays to inspect. * @param {Function} [comparator] The comparator invoked per element. * @returns {Array} Returns the new array of intersecting values. * @example * * var objects = [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }]; * var others = [{ 'x': 1, 'y': 1 }, { 'x': 1, 'y': 2 }]; * * _.intersectionWith(objects, others, _.isEqual); * // => [{ 'x': 1, 'y': 2 }] */ var intersectionWith = baseRest(function(arrays) { var comparator = last(arrays), mapped = arrayMap(arrays, castArrayLikeObject); comparator = typeof comparator == 'function' ? comparator : undefined; if (comparator) { mapped.pop(); } return (mapped.length && mapped[0] === arrays[0]) ? baseIntersection(mapped, undefined, comparator) : []; }); /** * Converts all elements in `array` into a string separated by `separator`. * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The array to convert. * @param {string} [separator=','] The element separator. * @returns {string} Returns the joined string. * @example * * _.join(['a', 'b', 'c'], '~'); * // => 'a~b~c' */ function join(array, separator) { return array == null ? '' : nativeJoin.call(array, separator); } /** * Gets the last element of `array`. * * @static * @memberOf _ * @since 0.1.0 * @category Array * @param {Array} array The array to query. * @returns {*} Returns the last element of `array`. * @example * * _.last([1, 2, 3]); * // => 3 */ function last(array) { var length = array == null ? 0 : array.length; return length ? array[length - 1] : undefined; } /** * This method is like `_.indexOf` except that it iterates over elements of * `array` from right to left. * * @static * @memberOf _ * @since 0.1.0 * @category Array * @param {Array} array The array to inspect. * @param {*} value The value to search for. * @param {number} [fromIndex=array.length-1] The index to search from. * @returns {number} Returns the index of the matched value, else `-1`. * @example * * _.lastIndexOf([1, 2, 1, 2], 2); * // => 3 * * // Search from the `fromIndex`. * _.lastIndexOf([1, 2, 1, 2], 2, 2); * // => 1 */ function lastIndexOf(array, value, fromIndex) { var length = array == null ? 0 : array.length; if (!length) { return -1; } var index = length; if (fromIndex !== undefined) { index = toInteger(fromIndex); index = index < 0 ? nativeMax(length + index, 0) : nativeMin(index, length - 1); } return value === value ? strictLastIndexOf(array, value, index) : baseFindIndex(array, baseIsNaN, index, true); } /** * Gets the element at index `n` of `array`. If `n` is negative, the nth * element from the end is returned. * * @static * @memberOf _ * @since 4.11.0 * @category Array * @param {Array} array The array to query. * @param {number} [n=0] The index of the element to return. * @returns {*} Returns the nth element of `array`. * @example * * var array = ['a', 'b', 'c', 'd']; * * _.nth(array, 1); * // => 'b' * * _.nth(array, -2); * // => 'c'; */ function nth(array, n) { return (array && array.length) ? baseNth(array, toInteger(n)) : undefined; } /** * Removes all given values from `array` using * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) * for equality comparisons. * * **Note:** Unlike `_.without`, this method mutates `array`. Use `_.remove` * to remove elements from an array by predicate. * * @static * @memberOf _ * @since 2.0.0 * @category Array * @param {Array} array The array to modify. * @param {...*} [values] The values to remove. * @returns {Array} Returns `array`. * @example * * var array = ['a', 'b', 'c', 'a', 'b', 'c']; * * _.pull(array, 'a', 'c'); * console.log(array); * // => ['b', 'b'] */ var pull = baseRest(pullAll); /** * This method is like `_.pull` except that it accepts an array of values to remove. * * **Note:** Unlike `_.difference`, this method mutates `array`. * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The array to modify. * @param {Array} values The values to remove. * @returns {Array} Returns `array`. * @example * * var array = ['a', 'b', 'c', 'a', 'b', 'c']; * * _.pullAll(array, ['a', 'c']); * console.log(array); * // => ['b', 'b'] */ function pullAll(array, values) { return (array && array.length && values && values.length) ? basePullAll(array, values) : array; } /** * This method is like `_.pullAll` except that it accepts `iteratee` which is * invoked for each element of `array` and `values` to generate the criterion * by which they're compared. The iteratee is invoked with one argument: (value). * * **Note:** Unlike `_.differenceBy`, this method mutates `array`. * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The array to modify. * @param {Array} values The values to remove. * @param {Function} [iteratee=_.identity] The iteratee invoked per element. * @returns {Array} Returns `array`. * @example * * var array = [{ 'x': 1 }, { 'x': 2 }, { 'x': 3 }, { 'x': 1 }]; * * _.pullAllBy(array, [{ 'x': 1 }, { 'x': 3 }], 'x'); * console.log(array); * // => [{ 'x': 2 }] */ function pullAllBy(array, values, iteratee) { return (array && array.length && values && values.length) ? basePullAll(array, values, getIteratee(iteratee, 2)) : array; } /** * This method is like `_.pullAll` except that it accepts `comparator` which * is invoked to compare elements of `array` to `values`. The comparator is * invoked with two arguments: (arrVal, othVal). * * **Note:** Unlike `_.differenceWith`, this method mutates `array`. * * @static * @memberOf _ * @since 4.6.0 * @category Array * @param {Array} array The array to modify. * @param {Array} values The values to remove. * @param {Function} [comparator] The comparator invoked per element. * @returns {Array} Returns `array`. * @example * * var array = [{ 'x': 1, 'y': 2 }, { 'x': 3, 'y': 4 }, { 'x': 5, 'y': 6 }]; * * _.pullAllWith(array, [{ 'x': 3, 'y': 4 }], _.isEqual); * console.log(array); * // => [{ 'x': 1, 'y': 2 }, { 'x': 5, 'y': 6 }] */ function pullAllWith(array, values, comparator) { return (array && array.length && values && values.length) ? basePullAll(array, values, undefined, comparator) : array; } /** * Removes elements from `array` corresponding to `indexes` and returns an * array of removed elements. * * **Note:** Unlike `_.at`, this method mutates `array`. * * @static * @memberOf _ * @since 3.0.0 * @category Array * @param {Array} array The array to modify. * @param {...(number|number[])} [indexes] The indexes of elements to remove. * @returns {Array} Returns the new array of removed elements. * @example * * var array = ['a', 'b', 'c', 'd']; * var pulled = _.pullAt(array, [1, 3]); * * console.log(array); * // => ['a', 'c'] * * console.log(pulled); * // => ['b', 'd'] */ var pullAt = flatRest(function(array, indexes) { var length = array == null ? 0 : array.length, result = baseAt(array, indexes); basePullAt(array, arrayMap(indexes, function(index) { return isIndex(index, length) ? +index : index; }).sort(compareAscending)); return result; }); /** * Removes all elements from `array` that `predicate` returns truthy for * and returns an array of the removed elements. The predicate is invoked * with three arguments: (value, index, array). * * **Note:** Unlike `_.filter`, this method mutates `array`. Use `_.pull` * to pull elements from an array by value. * * @static * @memberOf _ * @since 2.0.0 * @category Array * @param {Array} array The array to modify. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @returns {Array} Returns the new array of removed elements. * @example * * var array = [1, 2, 3, 4]; * var evens = _.remove(array, function(n) { * return n % 2 == 0; * }); * * console.log(array); * // => [1, 3] * * console.log(evens); * // => [2, 4] */ function remove(array, predicate) { var result = []; if (!(array && array.length)) { return result; } var index = -1, indexes = [], length = array.length; predicate = getIteratee(predicate, 3); while (++index < length) { var value = array[index]; if (predicate(value, index, array)) { result.push(value); indexes.push(index); } } basePullAt(array, indexes); return result; } /** * Reverses `array` so that the first element becomes the last, the second * element becomes the second to last, and so on. * * **Note:** This method mutates `array` and is based on * [`Array#reverse`](https://mdn.io/Array/reverse). * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The array to modify. * @returns {Array} Returns `array`. * @example * * var array = [1, 2, 3]; * * _.reverse(array); * // => [3, 2, 1] * * console.log(array); * // => [3, 2, 1] */ function reverse(array) { return array == null ? array : nativeReverse.call(array); } /** * Creates a slice of `array` from `start` up to, but not including, `end`. * * **Note:** This method is used instead of * [`Array#slice`](https://mdn.io/Array/slice) to ensure dense arrays are * returned. * * @static * @memberOf _ * @since 3.0.0 * @category Array * @param {Array} array The array to slice. * @param {number} [start=0] The start position. * @param {number} [end=array.length] The end position. * @returns {Array} Returns the slice of `array`. */ function slice(array, start, end) { var length = array == null ? 0 : array.length; if (!length) { return []; } if (end && typeof end != 'number' && isIterateeCall(array, start, end)) { start = 0; end = length; } else { start = start == null ? 0 : toInteger(start); end = end === undefined ? length : toInteger(end); } return baseSlice(array, start, end); } /** * Uses a binary search to determine the lowest index at which `value` * should be inserted into `array` in order to maintain its sort order. * * @static * @memberOf _ * @since 0.1.0 * @category Array * @param {Array} array The sorted array to inspect. * @param {*} value The value to evaluate. * @returns {number} Returns the index at which `value` should be inserted * into `array`. * @example * * _.sortedIndex([30, 50], 40); * // => 1 */ function sortedIndex(array, value) { return baseSortedIndex(array, value); } /** * This method is like `_.sortedIndex` except that it accepts `iteratee` * which is invoked for `value` and each element of `array` to compute their * sort ranking. The iteratee is invoked with one argument: (value). * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The sorted array to inspect. * @param {*} value The value to evaluate. * @param {Function} [iteratee=_.identity] The iteratee invoked per element. * @returns {number} Returns the index at which `value` should be inserted * into `array`. * @example * * var objects = [{ 'x': 4 }, { 'x': 5 }]; * * _.sortedIndexBy(objects, { 'x': 4 }, function(o) { return o.x; }); * // => 0 * * // The `_.property` iteratee shorthand. * _.sortedIndexBy(objects, { 'x': 4 }, 'x'); * // => 0 */ function sortedIndexBy(array, value, iteratee) { return baseSortedIndexBy(array, value, getIteratee(iteratee, 2)); } /** * This method is like `_.indexOf` except that it performs a binary * search on a sorted `array`. * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The array to inspect. * @param {*} value The value to search for. * @returns {number} Returns the index of the matched value, else `-1`. * @example * * _.sortedIndexOf([4, 5, 5, 5, 6], 5); * // => 1 */ function sortedIndexOf(array, value) { var length = array == null ? 0 : array.length; if (length) { var index = baseSortedIndex(array, value); if (index < length && eq(array[index], value)) { return index; } } return -1; } /** * This method is like `_.sortedIndex` except that it returns the highest * index at which `value` should be inserted into `array` in order to * maintain its sort order. * * @static * @memberOf _ * @since 3.0.0 * @category Array * @param {Array} array The sorted array to inspect. * @param {*} value The value to evaluate. * @returns {number} Returns the index at which `value` should be inserted * into `array`. * @example * * _.sortedLastIndex([4, 5, 5, 5, 6], 5); * // => 4 */ function sortedLastIndex(array, value) { return baseSortedIndex(array, value, true); } /** * This method is like `_.sortedLastIndex` except that it accepts `iteratee` * which is invoked for `value` and each element of `array` to compute their * sort ranking. The iteratee is invoked with one argument: (value). * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The sorted array to inspect. * @param {*} value The value to evaluate. * @param {Function} [iteratee=_.identity] The iteratee invoked per element. * @returns {number} Returns the index at which `value` should be inserted * into `array`. * @example * * var objects = [{ 'x': 4 }, { 'x': 5 }]; * * _.sortedLastIndexBy(objects, { 'x': 4 }, function(o) { return o.x; }); * // => 1 * * // The `_.property` iteratee shorthand. * _.sortedLastIndexBy(objects, { 'x': 4 }, 'x'); * // => 1 */ function sortedLastIndexBy(array, value, iteratee) { return baseSortedIndexBy(array, value, getIteratee(iteratee, 2), true); } /** * This method is like `_.lastIndexOf` except that it performs a binary * search on a sorted `array`. * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The array to inspect. * @param {*} value The value to search for. * @returns {number} Returns the index of the matched value, else `-1`. * @example * * _.sortedLastIndexOf([4, 5, 5, 5, 6], 5); * // => 3 */ function sortedLastIndexOf(array, value) { var length = array == null ? 0 : array.length; if (length) { var index = baseSortedIndex(array, value, true) - 1; if (eq(array[index], value)) { return index; } } return -1; } /** * This method is like `_.uniq` except that it's designed and optimized * for sorted arrays. * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The array to inspect. * @returns {Array} Returns the new duplicate free array. * @example * * _.sortedUniq([1, 1, 2]); * // => [1, 2] */ function sortedUniq(array) { return (array && array.length) ? baseSortedUniq(array) : []; } /** * This method is like `_.uniqBy` except that it's designed and optimized * for sorted arrays. * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The array to inspect. * @param {Function} [iteratee] The iteratee invoked per element. * @returns {Array} Returns the new duplicate free array. * @example * * _.sortedUniqBy([1.1, 1.2, 2.3, 2.4], Math.floor); * // => [1.1, 2.3] */ function sortedUniqBy(array, iteratee) { return (array && array.length) ? baseSortedUniq(array, getIteratee(iteratee, 2)) : []; } /** * Gets all but the first element of `array`. * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The array to query. * @returns {Array} Returns the slice of `array`. * @example * * _.tail([1, 2, 3]); * // => [2, 3] */ function tail(array) { var length = array == null ? 0 : array.length; return length ? baseSlice(array, 1, length) : []; } /** * Creates a slice of `array` with `n` elements taken from the beginning. * * @static * @memberOf _ * @since 0.1.0 * @category Array * @param {Array} array The array to query. * @param {number} [n=1] The number of elements to take. * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. * @returns {Array} Returns the slice of `array`. * @example * * _.take([1, 2, 3]); * // => [1] * * _.take([1, 2, 3], 2); * // => [1, 2] * * _.take([1, 2, 3], 5); * // => [1, 2, 3] * * _.take([1, 2, 3], 0); * // => [] */ function take(array, n, guard) { if (!(array && array.length)) { return []; } n = (guard || n === undefined) ? 1 : toInteger(n); return baseSlice(array, 0, n < 0 ? 0 : n); } /** * Creates a slice of `array` with `n` elements taken from the end. * * @static * @memberOf _ * @since 3.0.0 * @category Array * @param {Array} array The array to query. * @param {number} [n=1] The number of elements to take. * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. * @returns {Array} Returns the slice of `array`. * @example * * _.takeRight([1, 2, 3]); * // => [3] * * _.takeRight([1, 2, 3], 2); * // => [2, 3] * * _.takeRight([1, 2, 3], 5); * // => [1, 2, 3] * * _.takeRight([1, 2, 3], 0); * // => [] */ function takeRight(array, n, guard) { var length = array == null ? 0 : array.length; if (!length) { return []; } n = (guard || n === undefined) ? 1 : toInteger(n); n = length - n; return baseSlice(array, n < 0 ? 0 : n, length); } /** * Creates a slice of `array` with elements taken from the end. Elements are * taken until `predicate` returns falsey. The predicate is invoked with * three arguments: (value, index, array). * * @static * @memberOf _ * @since 3.0.0 * @category Array * @param {Array} array The array to query. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @returns {Array} Returns the slice of `array`. * @example * * var users = [ * { 'user': 'barney', 'active': true }, * { 'user': 'fred', 'active': false }, * { 'user': 'pebbles', 'active': false } * ]; * * _.takeRightWhile(users, function(o) { return !o.active; }); * // => objects for ['fred', 'pebbles'] * * // The `_.matches` iteratee shorthand. * _.takeRightWhile(users, { 'user': 'pebbles', 'active': false }); * // => objects for ['pebbles'] * * // The `_.matchesProperty` iteratee shorthand. * _.takeRightWhile(users, ['active', false]); * // => objects for ['fred', 'pebbles'] * * // The `_.property` iteratee shorthand. * _.takeRightWhile(users, 'active'); * // => [] */ function takeRightWhile(array, predicate) { return (array && array.length) ? baseWhile(array, getIteratee(predicate, 3), false, true) : []; } /** * Creates a slice of `array` with elements taken from the beginning. Elements * are taken until `predicate` returns falsey. The predicate is invoked with * three arguments: (value, index, array). * * @static * @memberOf _ * @since 3.0.0 * @category Array * @param {Array} array The array to query. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @returns {Array} Returns the slice of `array`. * @example * * var users = [ * { 'user': 'barney', 'active': false }, * { 'user': 'fred', 'active': false }, * { 'user': 'pebbles', 'active': true } * ]; * * _.takeWhile(users, function(o) { return !o.active; }); * // => objects for ['barney', 'fred'] * * // The `_.matches` iteratee shorthand. * _.takeWhile(users, { 'user': 'barney', 'active': false }); * // => objects for ['barney'] * * // The `_.matchesProperty` iteratee shorthand. * _.takeWhile(users, ['active', false]); * // => objects for ['barney', 'fred'] * * // The `_.property` iteratee shorthand. * _.takeWhile(users, 'active'); * // => [] */ function takeWhile(array, predicate) { return (array && array.length) ? baseWhile(array, getIteratee(predicate, 3)) : []; } /** * Creates an array of unique values, in order, from all given arrays using * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) * for equality comparisons. * * @static * @memberOf _ * @since 0.1.0 * @category Array * @param {...Array} [arrays] The arrays to inspect. * @returns {Array} Returns the new array of combined values. * @example * * _.union([2], [1, 2]); * // => [2, 1] */ var union = baseRest(function(arrays) { return baseUniq(baseFlatten(arrays, 1, isArrayLikeObject, true)); }); /** * This method is like `_.union` except that it accepts `iteratee` which is * invoked for each element of each `arrays` to generate the criterion by * which uniqueness is computed. Result values are chosen from the first * array in which the value occurs. The iteratee is invoked with one argument: * (value). * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {...Array} [arrays] The arrays to inspect. * @param {Function} [iteratee=_.identity] The iteratee invoked per element. * @returns {Array} Returns the new array of combined values. * @example * * _.unionBy([2.1], [1.2, 2.3], Math.floor); * // => [2.1, 1.2] * * // The `_.property` iteratee shorthand. * _.unionBy([{ 'x': 1 }], [{ 'x': 2 }, { 'x': 1 }], 'x'); * // => [{ 'x': 1 }, { 'x': 2 }] */ var unionBy = baseRest(function(arrays) { var iteratee = last(arrays); if (isArrayLikeObject(iteratee)) { iteratee = undefined; } return baseUniq(baseFlatten(arrays, 1, isArrayLikeObject, true), getIteratee(iteratee, 2)); }); /** * This method is like `_.union` except that it accepts `comparator` which * is invoked to compare elements of `arrays`. Result values are chosen from * the first array in which the value occurs. The comparator is invoked * with two arguments: (arrVal, othVal). * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {...Array} [arrays] The arrays to inspect. * @param {Function} [comparator] The comparator invoked per element. * @returns {Array} Returns the new array of combined values. * @example * * var objects = [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }]; * var others = [{ 'x': 1, 'y': 1 }, { 'x': 1, 'y': 2 }]; * * _.unionWith(objects, others, _.isEqual); * // => [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }, { 'x': 1, 'y': 1 }] */ var unionWith = baseRest(function(arrays) { var comparator = last(arrays); comparator = typeof comparator == 'function' ? comparator : undefined; return baseUniq(baseFlatten(arrays, 1, isArrayLikeObject, true), undefined, comparator); }); /** * Creates a duplicate-free version of an array, using * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) * for equality comparisons, in which only the first occurrence of each element * is kept. The order of result values is determined by the order they occur * in the array. * * @static * @memberOf _ * @since 0.1.0 * @category Array * @param {Array} array The array to inspect. * @returns {Array} Returns the new duplicate free array. * @example * * _.uniq([2, 1, 2]); * // => [2, 1] */ function uniq(array) { return (array && array.length) ? baseUniq(array) : []; } /** * This method is like `_.uniq` except that it accepts `iteratee` which is * invoked for each element in `array` to generate the criterion by which * uniqueness is computed. The order of result values is determined by the * order they occur in the array. The iteratee is invoked with one argument: * (value). * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The array to inspect. * @param {Function} [iteratee=_.identity] The iteratee invoked per element. * @returns {Array} Returns the new duplicate free array. * @example * * _.uniqBy([2.1, 1.2, 2.3], Math.floor); * // => [2.1, 1.2] * * // The `_.property` iteratee shorthand. * _.uniqBy([{ 'x': 1 }, { 'x': 2 }, { 'x': 1 }], 'x'); * // => [{ 'x': 1 }, { 'x': 2 }] */ function uniqBy(array, iteratee) { return (array && array.length) ? baseUniq(array, getIteratee(iteratee, 2)) : []; } /** * This method is like `_.uniq` except that it accepts `comparator` which * is invoked to compare elements of `array`. The order of result values is * determined by the order they occur in the array.The comparator is invoked * with two arguments: (arrVal, othVal). * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {Array} array The array to inspect. * @param {Function} [comparator] The comparator invoked per element. * @returns {Array} Returns the new duplicate free array. * @example * * var objects = [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }, { 'x': 1, 'y': 2 }]; * * _.uniqWith(objects, _.isEqual); * // => [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }] */ function uniqWith(array, comparator) { comparator = typeof comparator == 'function' ? comparator : undefined; return (array && array.length) ? baseUniq(array, undefined, comparator) : []; } /** * This method is like `_.zip` except that it accepts an array of grouped * elements and creates an array regrouping the elements to their pre-zip * configuration. * * @static * @memberOf _ * @since 1.2.0 * @category Array * @param {Array} array The array of grouped elements to process. * @returns {Array} Returns the new array of regrouped elements. * @example * * var zipped = _.zip(['a', 'b'], [1, 2], [true, false]); * // => [['a', 1, true], ['b', 2, false]] * * _.unzip(zipped); * // => [['a', 'b'], [1, 2], [true, false]] */ function unzip(array) { if (!(array && array.length)) { return []; } var length = 0; array = arrayFilter(array, function(group) { if (isArrayLikeObject(group)) { length = nativeMax(group.length, length); return true; } }); return baseTimes(length, function(index) { return arrayMap(array, baseProperty(index)); }); } /** * This method is like `_.unzip` except that it accepts `iteratee` to specify * how regrouped values should be combined. The iteratee is invoked with the * elements of each group: (...group). * * @static * @memberOf _ * @since 3.8.0 * @category Array * @param {Array} array The array of grouped elements to process. * @param {Function} [iteratee=_.identity] The function to combine * regrouped values. * @returns {Array} Returns the new array of regrouped elements. * @example * * var zipped = _.zip([1, 2], [10, 20], [100, 200]); * // => [[1, 10, 100], [2, 20, 200]] * * _.unzipWith(zipped, _.add); * // => [3, 30, 300] */ function unzipWith(array, iteratee) { if (!(array && array.length)) { return []; } var result = unzip(array); if (iteratee == null) { return result; } return arrayMap(result, function(group) { return apply(iteratee, undefined, group); }); } /** * Creates an array excluding all given values using * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) * for equality comparisons. * * **Note:** Unlike `_.pull`, this method returns a new array. * * @static * @memberOf _ * @since 0.1.0 * @category Array * @param {Array} array The array to inspect. * @param {...*} [values] The values to exclude. * @returns {Array} Returns the new array of filtered values. * @see _.difference, _.xor * @example * * _.without([2, 1, 2, 3], 1, 2); * // => [3] */ var without = baseRest(function(array, values) { return isArrayLikeObject(array) ? baseDifference(array, values) : []; }); /** * Creates an array of unique values that is the * [symmetric difference](https://en.wikipedia.org/wiki/Symmetric_difference) * of the given arrays. The order of result values is determined by the order * they occur in the arrays. * * @static * @memberOf _ * @since 2.4.0 * @category Array * @param {...Array} [arrays] The arrays to inspect. * @returns {Array} Returns the new array of filtered values. * @see _.difference, _.without * @example * * _.xor([2, 1], [2, 3]); * // => [1, 3] */ var xor = baseRest(function(arrays) { return baseXor(arrayFilter(arrays, isArrayLikeObject)); }); /** * This method is like `_.xor` except that it accepts `iteratee` which is * invoked for each element of each `arrays` to generate the criterion by * which by which they're compared. The order of result values is determined * by the order they occur in the arrays. The iteratee is invoked with one * argument: (value). * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {...Array} [arrays] The arrays to inspect. * @param {Function} [iteratee=_.identity] The iteratee invoked per element. * @returns {Array} Returns the new array of filtered values. * @example * * _.xorBy([2.1, 1.2], [2.3, 3.4], Math.floor); * // => [1.2, 3.4] * * // The `_.property` iteratee shorthand. * _.xorBy([{ 'x': 1 }], [{ 'x': 2 }, { 'x': 1 }], 'x'); * // => [{ 'x': 2 }] */ var xorBy = baseRest(function(arrays) { var iteratee = last(arrays); if (isArrayLikeObject(iteratee)) { iteratee = undefined; } return baseXor(arrayFilter(arrays, isArrayLikeObject), getIteratee(iteratee, 2)); }); /** * This method is like `_.xor` except that it accepts `comparator` which is * invoked to compare elements of `arrays`. The order of result values is * determined by the order they occur in the arrays. The comparator is invoked * with two arguments: (arrVal, othVal). * * @static * @memberOf _ * @since 4.0.0 * @category Array * @param {...Array} [arrays] The arrays to inspect. * @param {Function} [comparator] The comparator invoked per element. * @returns {Array} Returns the new array of filtered values. * @example * * var objects = [{ 'x': 1, 'y': 2 }, { 'x': 2, 'y': 1 }]; * var others = [{ 'x': 1, 'y': 1 }, { 'x': 1, 'y': 2 }]; * * _.xorWith(objects, others, _.isEqual); * // => [{ 'x': 2, 'y': 1 }, { 'x': 1, 'y': 1 }] */ var xorWith = baseRest(function(arrays) { var comparator = last(arrays); comparator = typeof comparator == 'function' ? comparator : undefined; return baseXor(arrayFilter(arrays, isArrayLikeObject), undefined, comparator); }); /** * Creates an array of grouped elements, the first of which contains the * first elements of the given arrays, the second of which contains the * second elements of the given arrays, and so on. * * @static * @memberOf _ * @since 0.1.0 * @category Array * @param {...Array} [arrays] The arrays to process. * @returns {Array} Returns the new array of grouped elements. * @example * * _.zip(['a', 'b'], [1, 2], [true, false]); * // => [['a', 1, true], ['b', 2, false]] */ var zip = baseRest(unzip); /** * This method is like `_.fromPairs` except that it accepts two arrays, * one of property identifiers and one of corresponding values. * * @static * @memberOf _ * @since 0.4.0 * @category Array * @param {Array} [props=[]] The property identifiers. * @param {Array} [values=[]] The property values. * @returns {Object} Returns the new object. * @example * * _.zipObject(['a', 'b'], [1, 2]); * // => { 'a': 1, 'b': 2 } */ function zipObject(props, values) { return baseZipObject(props || [], values || [], assignValue); } /** * This method is like `_.zipObject` except that it supports property paths. * * @static * @memberOf _ * @since 4.1.0 * @category Array * @param {Array} [props=[]] The property identifiers. * @param {Array} [values=[]] The property values. * @returns {Object} Returns the new object. * @example * * _.zipObjectDeep(['a.b[0].c', 'a.b[1].d'], [1, 2]); * // => { 'a': { 'b': [{ 'c': 1 }, { 'd': 2 }] } } */ function zipObjectDeep(props, values) { return baseZipObject(props || [], values || [], baseSet); } /** * This method is like `_.zip` except that it accepts `iteratee` to specify * how grouped values should be combined. The iteratee is invoked with the * elements of each group: (...group). * * @static * @memberOf _ * @since 3.8.0 * @category Array * @param {...Array} [arrays] The arrays to process. * @param {Function} [iteratee=_.identity] The function to combine * grouped values. * @returns {Array} Returns the new array of grouped elements. * @example * * _.zipWith([1, 2], [10, 20], [100, 200], function(a, b, c) { * return a + b + c; * }); * // => [111, 222] */ var zipWith = baseRest(function(arrays) { var length = arrays.length, iteratee = length > 1 ? arrays[length - 1] : undefined; iteratee = typeof iteratee == 'function' ? (arrays.pop(), iteratee) : undefined; return unzipWith(arrays, iteratee); }); /*------------------------------------------------------------------------*/ /** * Creates a `lodash` wrapper instance that wraps `value` with explicit method * chain sequences enabled. The result of such sequences must be unwrapped * with `_#value`. * * @static * @memberOf _ * @since 1.3.0 * @category Seq * @param {*} value The value to wrap. * @returns {Object} Returns the new `lodash` wrapper instance. * @example * * var users = [ * { 'user': 'barney', 'age': 36 }, * { 'user': 'fred', 'age': 40 }, * { 'user': 'pebbles', 'age': 1 } * ]; * * var youngest = _ * .chain(users) * .sortBy('age') * .map(function(o) { * return o.user + ' is ' + o.age; * }) * .head() * .value(); * // => 'pebbles is 1' */ function chain(value) { var result = lodash(value); result.__chain__ = true; return result; } /** * This method invokes `interceptor` and returns `value`. The interceptor * is invoked with one argument; (value). The purpose of this method is to * "tap into" a method chain sequence in order to modify intermediate results. * * @static * @memberOf _ * @since 0.1.0 * @category Seq * @param {*} value The value to provide to `interceptor`. * @param {Function} interceptor The function to invoke. * @returns {*} Returns `value`. * @example * * _([1, 2, 3]) * .tap(function(array) { * // Mutate input array. * array.pop(); * }) * .reverse() * .value(); * // => [2, 1] */ function tap(value, interceptor) { interceptor(value); return value; } /** * This method is like `_.tap` except that it returns the result of `interceptor`. * The purpose of this method is to "pass thru" values replacing intermediate * results in a method chain sequence. * * @static * @memberOf _ * @since 3.0.0 * @category Seq * @param {*} value The value to provide to `interceptor`. * @param {Function} interceptor The function to invoke. * @returns {*} Returns the result of `interceptor`. * @example * * _(' abc ') * .chain() * .trim() * .thru(function(value) { * return [value]; * }) * .value(); * // => ['abc'] */ function thru(value, interceptor) { return interceptor(value); } /** * This method is the wrapper version of `_.at`. * * @name at * @memberOf _ * @since 1.0.0 * @category Seq * @param {...(string|string[])} [paths] The property paths to pick. * @returns {Object} Returns the new `lodash` wrapper instance. * @example * * var object = { 'a': [{ 'b': { 'c': 3 } }, 4] }; * * _(object).at(['a[0].b.c', 'a[1]']).value(); * // => [3, 4] */ var wrapperAt = flatRest(function(paths) { var length = paths.length, start = length ? paths[0] : 0, value = this.__wrapped__, interceptor = function(object) { return baseAt(object, paths); }; if (length > 1 || this.__actions__.length || !(value instanceof LazyWrapper) || !isIndex(start)) { return this.thru(interceptor); } value = value.slice(start, +start + (length ? 1 : 0)); value.__actions__.push({ 'func': thru, 'args': [interceptor], 'thisArg': undefined }); return new LodashWrapper(value, this.__chain__).thru(function(array) { if (length && !array.length) { array.push(undefined); } return array; }); }); /** * Creates a `lodash` wrapper instance with explicit method chain sequences enabled. * * @name chain * @memberOf _ * @since 0.1.0 * @category Seq * @returns {Object} Returns the new `lodash` wrapper instance. * @example * * var users = [ * { 'user': 'barney', 'age': 36 }, * { 'user': 'fred', 'age': 40 } * ]; * * // A sequence without explicit chaining. * _(users).head(); * // => { 'user': 'barney', 'age': 36 } * * // A sequence with explicit chaining. * _(users) * .chain() * .head() * .pick('user') * .value(); * // => { 'user': 'barney' } */ function wrapperChain() { return chain(this); } /** * Executes the chain sequence and returns the wrapped result. * * @name commit * @memberOf _ * @since 3.2.0 * @category Seq * @returns {Object} Returns the new `lodash` wrapper instance. * @example * * var array = [1, 2]; * var wrapped = _(array).push(3); * * console.log(array); * // => [1, 2] * * wrapped = wrapped.commit(); * console.log(array); * // => [1, 2, 3] * * wrapped.last(); * // => 3 * * console.log(array); * // => [1, 2, 3] */ function wrapperCommit() { return new LodashWrapper(this.value(), this.__chain__); } /** * Gets the next value on a wrapped object following the * [iterator protocol](https://mdn.io/iteration_protocols#iterator). * * @name next * @memberOf _ * @since 4.0.0 * @category Seq * @returns {Object} Returns the next iterator value. * @example * * var wrapped = _([1, 2]); * * wrapped.next(); * // => { 'done': false, 'value': 1 } * * wrapped.next(); * // => { 'done': false, 'value': 2 } * * wrapped.next(); * // => { 'done': true, 'value': undefined } */ function wrapperNext() { if (this.__values__ === undefined) { this.__values__ = toArray(this.value()); } var done = this.__index__ >= this.__values__.length, value = done ? undefined : this.__values__[this.__index__++]; return { 'done': done, 'value': value }; } /** * Enables the wrapper to be iterable. * * @name Symbol.iterator * @memberOf _ * @since 4.0.0 * @category Seq * @returns {Object} Returns the wrapper object. * @example * * var wrapped = _([1, 2]); * * wrapped[Symbol.iterator]() === wrapped; * // => true * * Array.from(wrapped); * // => [1, 2] */ function wrapperToIterator() { return this; } /** * Creates a clone of the chain sequence planting `value` as the wrapped value. * * @name plant * @memberOf _ * @since 3.2.0 * @category Seq * @param {*} value The value to plant. * @returns {Object} Returns the new `lodash` wrapper instance. * @example * * function square(n) { * return n * n; * } * * var wrapped = _([1, 2]).map(square); * var other = wrapped.plant([3, 4]); * * other.value(); * // => [9, 16] * * wrapped.value(); * // => [1, 4] */ function wrapperPlant(value) { var result, parent = this; while (parent instanceof baseLodash) { var clone = wrapperClone(parent); clone.__index__ = 0; clone.__values__ = undefined; if (result) { previous.__wrapped__ = clone; } else { result = clone; } var previous = clone; parent = parent.__wrapped__; } previous.__wrapped__ = value; return result; } /** * This method is the wrapper version of `_.reverse`. * * **Note:** This method mutates the wrapped array. * * @name reverse * @memberOf _ * @since 0.1.0 * @category Seq * @returns {Object} Returns the new `lodash` wrapper instance. * @example * * var array = [1, 2, 3]; * * _(array).reverse().value() * // => [3, 2, 1] * * console.log(array); * // => [3, 2, 1] */ function wrapperReverse() { var value = this.__wrapped__; if (value instanceof LazyWrapper) { var wrapped = value; if (this.__actions__.length) { wrapped = new LazyWrapper(this); } wrapped = wrapped.reverse(); wrapped.__actions__.push({ 'func': thru, 'args': [reverse], 'thisArg': undefined }); return new LodashWrapper(wrapped, this.__chain__); } return this.thru(reverse); } /** * Executes the chain sequence to resolve the unwrapped value. * * @name value * @memberOf _ * @since 0.1.0 * @alias toJSON, valueOf * @category Seq * @returns {*} Returns the resolved unwrapped value. * @example * * _([1, 2, 3]).value(); * // => [1, 2, 3] */ function wrapperValue() { return baseWrapperValue(this.__wrapped__, this.__actions__); } /*------------------------------------------------------------------------*/ /** * Creates an object composed of keys generated from the results of running * each element of `collection` thru `iteratee`. The corresponding value of * each key is the number of times the key was returned by `iteratee`. The * iteratee is invoked with one argument: (value). * * @static * @memberOf _ * @since 0.5.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [iteratee=_.identity] The iteratee to transform keys. * @returns {Object} Returns the composed aggregate object. * @example * * _.countBy([6.1, 4.2, 6.3], Math.floor); * // => { '4': 1, '6': 2 } * * // The `_.property` iteratee shorthand. * _.countBy(['one', 'two', 'three'], 'length'); * // => { '3': 2, '5': 1 } */ var countBy = createAggregator(function(result, value, key) { if (hasOwnProperty.call(result, key)) { ++result[key]; } else { baseAssignValue(result, key, 1); } }); /** * Checks if `predicate` returns truthy for **all** elements of `collection`. * Iteration is stopped once `predicate` returns falsey. The predicate is * invoked with three arguments: (value, index|key, collection). * * **Note:** This method returns `true` for * [empty collections](https://en.wikipedia.org/wiki/Empty_set) because * [everything is true](https://en.wikipedia.org/wiki/Vacuous_truth) of * elements of empty collections. * * @static * @memberOf _ * @since 0.1.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. * @returns {boolean} Returns `true` if all elements pass the predicate check, * else `false`. * @example * * _.every([true, 1, null, 'yes'], Boolean); * // => false * * var users = [ * { 'user': 'barney', 'age': 36, 'active': false }, * { 'user': 'fred', 'age': 40, 'active': false } * ]; * * // The `_.matches` iteratee shorthand. * _.every(users, { 'user': 'barney', 'active': false }); * // => false * * // The `_.matchesProperty` iteratee shorthand. * _.every(users, ['active', false]); * // => true * * // The `_.property` iteratee shorthand. * _.every(users, 'active'); * // => false */ function every(collection, predicate, guard) { var func = isArray(collection) ? arrayEvery : baseEvery; if (guard && isIterateeCall(collection, predicate, guard)) { predicate = undefined; } return func(collection, getIteratee(predicate, 3)); } /** * Iterates over elements of `collection`, returning an array of all elements * `predicate` returns truthy for. The predicate is invoked with three * arguments: (value, index|key, collection). * * **Note:** Unlike `_.remove`, this method returns a new array. * * @static * @memberOf _ * @since 0.1.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @returns {Array} Returns the new filtered array. * @see _.reject * @example * * var users = [ * { 'user': 'barney', 'age': 36, 'active': true }, * { 'user': 'fred', 'age': 40, 'active': false } * ]; * * _.filter(users, function(o) { return !o.active; }); * // => objects for ['fred'] * * // The `_.matches` iteratee shorthand. * _.filter(users, { 'age': 36, 'active': true }); * // => objects for ['barney'] * * // The `_.matchesProperty` iteratee shorthand. * _.filter(users, ['active', false]); * // => objects for ['fred'] * * // The `_.property` iteratee shorthand. * _.filter(users, 'active'); * // => objects for ['barney'] */ function filter(collection, predicate) { var func = isArray(collection) ? arrayFilter : baseFilter; return func(collection, getIteratee(predicate, 3)); } /** * Iterates over elements of `collection`, returning the first element * `predicate` returns truthy for. The predicate is invoked with three * arguments: (value, index|key, collection). * * @static * @memberOf _ * @since 0.1.0 * @category Collection * @param {Array|Object} collection The collection to inspect. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @param {number} [fromIndex=0] The index to search from. * @returns {*} Returns the matched element, else `undefined`. * @example * * var users = [ * { 'user': 'barney', 'age': 36, 'active': true }, * { 'user': 'fred', 'age': 40, 'active': false }, * { 'user': 'pebbles', 'age': 1, 'active': true } * ]; * * _.find(users, function(o) { return o.age < 40; }); * // => object for 'barney' * * // The `_.matches` iteratee shorthand. * _.find(users, { 'age': 1, 'active': true }); * // => object for 'pebbles' * * // The `_.matchesProperty` iteratee shorthand. * _.find(users, ['active', false]); * // => object for 'fred' * * // The `_.property` iteratee shorthand. * _.find(users, 'active'); * // => object for 'barney' */ var find = createFind(findIndex); /** * This method is like `_.find` except that it iterates over elements of * `collection` from right to left. * * @static * @memberOf _ * @since 2.0.0 * @category Collection * @param {Array|Object} collection The collection to inspect. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @param {number} [fromIndex=collection.length-1] The index to search from. * @returns {*} Returns the matched element, else `undefined`. * @example * * _.findLast([1, 2, 3, 4], function(n) { * return n % 2 == 1; * }); * // => 3 */ var findLast = createFind(findLastIndex); /** * Creates a flattened array of values by running each element in `collection` * thru `iteratee` and flattening the mapped results. The iteratee is invoked * with three arguments: (value, index|key, collection). * * @static * @memberOf _ * @since 4.0.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [iteratee=_.identity] The function invoked per iteration. * @returns {Array} Returns the new flattened array. * @example * * function duplicate(n) { * return [n, n]; * } * * _.flatMap([1, 2], duplicate); * // => [1, 1, 2, 2] */ function flatMap(collection, iteratee) { return baseFlatten(map(collection, iteratee), 1); } /** * This method is like `_.flatMap` except that it recursively flattens the * mapped results. * * @static * @memberOf _ * @since 4.7.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [iteratee=_.identity] The function invoked per iteration. * @returns {Array} Returns the new flattened array. * @example * * function duplicate(n) { * return [[[n, n]]]; * } * * _.flatMapDeep([1, 2], duplicate); * // => [1, 1, 2, 2] */ function flatMapDeep(collection, iteratee) { return baseFlatten(map(collection, iteratee), INFINITY); } /** * This method is like `_.flatMap` except that it recursively flattens the * mapped results up to `depth` times. * * @static * @memberOf _ * @since 4.7.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [iteratee=_.identity] The function invoked per iteration. * @param {number} [depth=1] The maximum recursion depth. * @returns {Array} Returns the new flattened array. * @example * * function duplicate(n) { * return [[[n, n]]]; * } * * _.flatMapDepth([1, 2], duplicate, 2); * // => [[1, 1], [2, 2]] */ function flatMapDepth(collection, iteratee, depth) { depth = depth === undefined ? 1 : toInteger(depth); return baseFlatten(map(collection, iteratee), depth); } /** * Iterates over elements of `collection` and invokes `iteratee` for each element. * The iteratee is invoked with three arguments: (value, index|key, collection). * Iteratee functions may exit iteration early by explicitly returning `false`. * * **Note:** As with other "Collections" methods, objects with a "length" * property are iterated like arrays. To avoid this behavior use `_.forIn` * or `_.forOwn` for object iteration. * * @static * @memberOf _ * @since 0.1.0 * @alias each * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [iteratee=_.identity] The function invoked per iteration. * @returns {Array|Object} Returns `collection`. * @see _.forEachRight * @example * * _.forEach([1, 2], function(value) { * console.log(value); * }); * // => Logs `1` then `2`. * * _.forEach({ 'a': 1, 'b': 2 }, function(value, key) { * console.log(key); * }); * // => Logs 'a' then 'b' (iteration order is not guaranteed). */ function forEach(collection, iteratee) { var func = isArray(collection) ? arrayEach : baseEach; return func(collection, getIteratee(iteratee, 3)); } /** * This method is like `_.forEach` except that it iterates over elements of * `collection` from right to left. * * @static * @memberOf _ * @since 2.0.0 * @alias eachRight * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [iteratee=_.identity] The function invoked per iteration. * @returns {Array|Object} Returns `collection`. * @see _.forEach * @example * * _.forEachRight([1, 2], function(value) { * console.log(value); * }); * // => Logs `2` then `1`. */ function forEachRight(collection, iteratee) { var func = isArray(collection) ? arrayEachRight : baseEachRight; return func(collection, getIteratee(iteratee, 3)); } /** * Creates an object composed of keys generated from the results of running * each element of `collection` thru `iteratee`. The order of grouped values * is determined by the order they occur in `collection`. The corresponding * value of each key is an array of elements responsible for generating the * key. The iteratee is invoked with one argument: (value). * * @static * @memberOf _ * @since 0.1.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [iteratee=_.identity] The iteratee to transform keys. * @returns {Object} Returns the composed aggregate object. * @example * * _.groupBy([6.1, 4.2, 6.3], Math.floor); * // => { '4': [4.2], '6': [6.1, 6.3] } * * // The `_.property` iteratee shorthand. * _.groupBy(['one', 'two', 'three'], 'length'); * // => { '3': ['one', 'two'], '5': ['three'] } */ var groupBy = createAggregator(function(result, value, key) { if (hasOwnProperty.call(result, key)) { result[key].push(value); } else { baseAssignValue(result, key, [value]); } }); /** * Checks if `value` is in `collection`. If `collection` is a string, it's * checked for a substring of `value`, otherwise * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) * is used for equality comparisons. If `fromIndex` is negative, it's used as * the offset from the end of `collection`. * * @static * @memberOf _ * @since 0.1.0 * @category Collection * @param {Array|Object|string} collection The collection to inspect. * @param {*} value The value to search for. * @param {number} [fromIndex=0] The index to search from. * @param- {Object} [guard] Enables use as an iteratee for methods like `_.reduce`. * @returns {boolean} Returns `true` if `value` is found, else `false`. * @example * * _.includes([1, 2, 3], 1); * // => true * * _.includes([1, 2, 3], 1, 2); * // => false * * _.includes({ 'a': 1, 'b': 2 }, 1); * // => true * * _.includes('abcd', 'bc'); * // => true */ function includes(collection, value, fromIndex, guard) { collection = isArrayLike(collection) ? collection : values(collection); fromIndex = (fromIndex && !guard) ? toInteger(fromIndex) : 0; var length = collection.length; if (fromIndex < 0) { fromIndex = nativeMax(length + fromIndex, 0); } return isString(collection) ? (fromIndex <= length && collection.indexOf(value, fromIndex) > -1) : (!!length && baseIndexOf(collection, value, fromIndex) > -1); } /** * Invokes the method at `path` of each element in `collection`, returning * an array of the results of each invoked method. Any additional arguments * are provided to each invoked method. If `path` is a function, it's invoked * for, and `this` bound to, each element in `collection`. * * @static * @memberOf _ * @since 4.0.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Array|Function|string} path The path of the method to invoke or * the function invoked per iteration. * @param {...*} [args] The arguments to invoke each method with. * @returns {Array} Returns the array of results. * @example * * _.invokeMap([[5, 1, 7], [3, 2, 1]], 'sort'); * // => [[1, 5, 7], [1, 2, 3]] * * _.invokeMap([123, 456], String.prototype.split, ''); * // => [['1', '2', '3'], ['4', '5', '6']] */ var invokeMap = baseRest(function(collection, path, args) { var index = -1, isFunc = typeof path == 'function', result = isArrayLike(collection) ? Array(collection.length) : []; baseEach(collection, function(value) { result[++index] = isFunc ? apply(path, value, args) : baseInvoke(value, path, args); }); return result; }); /** * Creates an object composed of keys generated from the results of running * each element of `collection` thru `iteratee`. The corresponding value of * each key is the last element responsible for generating the key. The * iteratee is invoked with one argument: (value). * * @static * @memberOf _ * @since 4.0.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [iteratee=_.identity] The iteratee to transform keys. * @returns {Object} Returns the composed aggregate object. * @example * * var array = [ * { 'dir': 'left', 'code': 97 }, * { 'dir': 'right', 'code': 100 } * ]; * * _.keyBy(array, function(o) { * return String.fromCharCode(o.code); * }); * // => { 'a': { 'dir': 'left', 'code': 97 }, 'd': { 'dir': 'right', 'code': 100 } } * * _.keyBy(array, 'dir'); * // => { 'left': { 'dir': 'left', 'code': 97 }, 'right': { 'dir': 'right', 'code': 100 } } */ var keyBy = createAggregator(function(result, value, key) { baseAssignValue(result, key, value); }); /** * Creates an array of values by running each element in `collection` thru * `iteratee`. The iteratee is invoked with three arguments: * (value, index|key, collection). * * Many lodash methods are guarded to work as iteratees for methods like * `_.every`, `_.filter`, `_.map`, `_.mapValues`, `_.reject`, and `_.some`. * * The guarded methods are: * `ary`, `chunk`, `curry`, `curryRight`, `drop`, `dropRight`, `every`, * `fill`, `invert`, `parseInt`, `random`, `range`, `rangeRight`, `repeat`, * `sampleSize`, `slice`, `some`, `sortBy`, `split`, `take`, `takeRight`, * `template`, `trim`, `trimEnd`, `trimStart`, and `words` * * @static * @memberOf _ * @since 0.1.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [iteratee=_.identity] The function invoked per iteration. * @returns {Array} Returns the new mapped array. * @example * * function square(n) { * return n * n; * } * * _.map([4, 8], square); * // => [16, 64] * * _.map({ 'a': 4, 'b': 8 }, square); * // => [16, 64] (iteration order is not guaranteed) * * var users = [ * { 'user': 'barney' }, * { 'user': 'fred' } * ]; * * // The `_.property` iteratee shorthand. * _.map(users, 'user'); * // => ['barney', 'fred'] */ function map(collection, iteratee) { var func = isArray(collection) ? arrayMap : baseMap; return func(collection, getIteratee(iteratee, 3)); } /** * This method is like `_.sortBy` except that it allows specifying the sort * orders of the iteratees to sort by. If `orders` is unspecified, all values * are sorted in ascending order. Otherwise, specify an order of "desc" for * descending or "asc" for ascending sort order of corresponding values. * * @static * @memberOf _ * @since 4.0.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Array[]|Function[]|Object[]|string[]} [iteratees=[_.identity]] * The iteratees to sort by. * @param {string[]} [orders] The sort orders of `iteratees`. * @param- {Object} [guard] Enables use as an iteratee for methods like `_.reduce`. * @returns {Array} Returns the new sorted array. * @example * * var users = [ * { 'user': 'fred', 'age': 48 }, * { 'user': 'barney', 'age': 34 }, * { 'user': 'fred', 'age': 40 }, * { 'user': 'barney', 'age': 36 } * ]; * * // Sort by `user` in ascending order and by `age` in descending order. * _.orderBy(users, ['user', 'age'], ['asc', 'desc']); * // => objects for [['barney', 36], ['barney', 34], ['fred', 48], ['fred', 40]] */ function orderBy(collection, iteratees, orders, guard) { if (collection == null) { return []; } if (!isArray(iteratees)) { iteratees = iteratees == null ? [] : [iteratees]; } orders = guard ? undefined : orders; if (!isArray(orders)) { orders = orders == null ? [] : [orders]; } return baseOrderBy(collection, iteratees, orders); } /** * Creates an array of elements split into two groups, the first of which * contains elements `predicate` returns truthy for, the second of which * contains elements `predicate` returns falsey for. The predicate is * invoked with one argument: (value). * * @static * @memberOf _ * @since 3.0.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @returns {Array} Returns the array of grouped elements. * @example * * var users = [ * { 'user': 'barney', 'age': 36, 'active': false }, * { 'user': 'fred', 'age': 40, 'active': true }, * { 'user': 'pebbles', 'age': 1, 'active': false } * ]; * * _.partition(users, function(o) { return o.active; }); * // => objects for [['fred'], ['barney', 'pebbles']] * * // The `_.matches` iteratee shorthand. * _.partition(users, { 'age': 1, 'active': false }); * // => objects for [['pebbles'], ['barney', 'fred']] * * // The `_.matchesProperty` iteratee shorthand. * _.partition(users, ['active', false]); * // => objects for [['barney', 'pebbles'], ['fred']] * * // The `_.property` iteratee shorthand. * _.partition(users, 'active'); * // => objects for [['fred'], ['barney', 'pebbles']] */ var partition = createAggregator(function(result, value, key) { result[key ? 0 : 1].push(value); }, function() { return [[], []]; }); /** * Reduces `collection` to a value which is the accumulated result of running * each element in `collection` thru `iteratee`, where each successive * invocation is supplied the return value of the previous. If `accumulator` * is not given, the first element of `collection` is used as the initial * value. The iteratee is invoked with four arguments: * (accumulator, value, index|key, collection). * * Many lodash methods are guarded to work as iteratees for methods like * `_.reduce`, `_.reduceRight`, and `_.transform`. * * The guarded methods are: * `assign`, `defaults`, `defaultsDeep`, `includes`, `merge`, `orderBy`, * and `sortBy` * * @static * @memberOf _ * @since 0.1.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [iteratee=_.identity] The function invoked per iteration. * @param {*} [accumulator] The initial value. * @returns {*} Returns the accumulated value. * @see _.reduceRight * @example * * _.reduce([1, 2], function(sum, n) { * return sum + n; * }, 0); * // => 3 * * _.reduce({ 'a': 1, 'b': 2, 'c': 1 }, function(result, value, key) { * (result[value] || (result[value] = [])).push(key); * return result; * }, {}); * // => { '1': ['a', 'c'], '2': ['b'] } (iteration order is not guaranteed) */ function reduce(collection, iteratee, accumulator) { var func = isArray(collection) ? arrayReduce : baseReduce, initAccum = arguments.length < 3; return func(collection, getIteratee(iteratee, 4), accumulator, initAccum, baseEach); } /** * This method is like `_.reduce` except that it iterates over elements of * `collection` from right to left. * * @static * @memberOf _ * @since 0.1.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [iteratee=_.identity] The function invoked per iteration. * @param {*} [accumulator] The initial value. * @returns {*} Returns the accumulated value. * @see _.reduce * @example * * var array = [[0, 1], [2, 3], [4, 5]]; * * _.reduceRight(array, function(flattened, other) { * return flattened.concat(other); * }, []); * // => [4, 5, 2, 3, 0, 1] */ function reduceRight(collection, iteratee, accumulator) { var func = isArray(collection) ? arrayReduceRight : baseReduce, initAccum = arguments.length < 3; return func(collection, getIteratee(iteratee, 4), accumulator, initAccum, baseEachRight); } /** * The opposite of `_.filter`; this method returns the elements of `collection` * that `predicate` does **not** return truthy for. * * @static * @memberOf _ * @since 0.1.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @returns {Array} Returns the new filtered array. * @see _.filter * @example * * var users = [ * { 'user': 'barney', 'age': 36, 'active': false }, * { 'user': 'fred', 'age': 40, 'active': true } * ]; * * _.reject(users, function(o) { return !o.active; }); * // => objects for ['fred'] * * // The `_.matches` iteratee shorthand. * _.reject(users, { 'age': 40, 'active': true }); * // => objects for ['barney'] * * // The `_.matchesProperty` iteratee shorthand. * _.reject(users, ['active', false]); * // => objects for ['fred'] * * // The `_.property` iteratee shorthand. * _.reject(users, 'active'); * // => objects for ['barney'] */ function reject(collection, predicate) { var func = isArray(collection) ? arrayFilter : baseFilter; return func(collection, negate(getIteratee(predicate, 3))); } /** * Gets a random element from `collection`. * * @static * @memberOf _ * @since 2.0.0 * @category Collection * @param {Array|Object} collection The collection to sample. * @returns {*} Returns the random element. * @example * * _.sample([1, 2, 3, 4]); * // => 2 */ function sample(collection) { var func = isArray(collection) ? arraySample : baseSample; return func(collection); } /** * Gets `n` random elements at unique keys from `collection` up to the * size of `collection`. * * @static * @memberOf _ * @since 4.0.0 * @category Collection * @param {Array|Object} collection The collection to sample. * @param {number} [n=1] The number of elements to sample. * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. * @returns {Array} Returns the random elements. * @example * * _.sampleSize([1, 2, 3], 2); * // => [3, 1] * * _.sampleSize([1, 2, 3], 4); * // => [2, 3, 1] */ function sampleSize(collection, n, guard) { if ((guard ? isIterateeCall(collection, n, guard) : n === undefined)) { n = 1; } else { n = toInteger(n); } var func = isArray(collection) ? arraySampleSize : baseSampleSize; return func(collection, n); } /** * Creates an array of shuffled values, using a version of the * [Fisher-Yates shuffle](https://en.wikipedia.org/wiki/Fisher-Yates_shuffle). * * @static * @memberOf _ * @since 0.1.0 * @category Collection * @param {Array|Object} collection The collection to shuffle. * @returns {Array} Returns the new shuffled array. * @example * * _.shuffle([1, 2, 3, 4]); * // => [4, 1, 3, 2] */ function shuffle(collection) { var func = isArray(collection) ? arrayShuffle : baseShuffle; return func(collection); } /** * Gets the size of `collection` by returning its length for array-like * values or the number of own enumerable string keyed properties for objects. * * @static * @memberOf _ * @since 0.1.0 * @category Collection * @param {Array|Object|string} collection The collection to inspect. * @returns {number} Returns the collection size. * @example * * _.size([1, 2, 3]); * // => 3 * * _.size({ 'a': 1, 'b': 2 }); * // => 2 * * _.size('pebbles'); * // => 7 */ function size(collection) { if (collection == null) { return 0; } if (isArrayLike(collection)) { return isString(collection) ? stringSize(collection) : collection.length; } var tag = getTag(collection); if (tag == mapTag || tag == setTag) { return collection.size; } return baseKeys(collection).length; } /** * Checks if `predicate` returns truthy for **any** element of `collection`. * Iteration is stopped once `predicate` returns truthy. The predicate is * invoked with three arguments: (value, index|key, collection). * * @static * @memberOf _ * @since 0.1.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. * @returns {boolean} Returns `true` if any element passes the predicate check, * else `false`. * @example * * _.some([null, 0, 'yes', false], Boolean); * // => true * * var users = [ * { 'user': 'barney', 'active': true }, * { 'user': 'fred', 'active': false } * ]; * * // The `_.matches` iteratee shorthand. * _.some(users, { 'user': 'barney', 'active': false }); * // => false * * // The `_.matchesProperty` iteratee shorthand. * _.some(users, ['active', false]); * // => true * * // The `_.property` iteratee shorthand. * _.some(users, 'active'); * // => true */ function some(collection, predicate, guard) { var func = isArray(collection) ? arraySome : baseSome; if (guard && isIterateeCall(collection, predicate, guard)) { predicate = undefined; } return func(collection, getIteratee(predicate, 3)); } /** * Creates an array of elements, sorted in ascending order by the results of * running each element in a collection thru each iteratee. This method * performs a stable sort, that is, it preserves the original sort order of * equal elements. The iteratees are invoked with one argument: (value). * * @static * @memberOf _ * @since 0.1.0 * @category Collection * @param {Array|Object} collection The collection to iterate over. * @param {...(Function|Function[])} [iteratees=[_.identity]] * The iteratees to sort by. * @returns {Array} Returns the new sorted array. * @example * * var users = [ * { 'user': 'fred', 'age': 48 }, * { 'user': 'barney', 'age': 36 }, * { 'user': 'fred', 'age': 40 }, * { 'user': 'barney', 'age': 34 } * ]; * * _.sortBy(users, [function(o) { return o.user; }]); * // => objects for [['barney', 36], ['barney', 34], ['fred', 48], ['fred', 40]] * * _.sortBy(users, ['user', 'age']); * // => objects for [['barney', 34], ['barney', 36], ['fred', 40], ['fred', 48]] */ var sortBy = baseRest(function(collection, iteratees) { if (collection == null) { return []; } var length = iteratees.length; if (length > 1 && isIterateeCall(collection, iteratees[0], iteratees[1])) { iteratees = []; } else if (length > 2 && isIterateeCall(iteratees[0], iteratees[1], iteratees[2])) { iteratees = [iteratees[0]]; } return baseOrderBy(collection, baseFlatten(iteratees, 1), []); }); /*------------------------------------------------------------------------*/ /** * Gets the timestamp of the number of milliseconds that have elapsed since * the Unix epoch (1 January 1970 00:00:00 UTC). * * @static * @memberOf _ * @since 2.4.0 * @category Date * @returns {number} Returns the timestamp. * @example * * _.defer(function(stamp) { * console.log(_.now() - stamp); * }, _.now()); * // => Logs the number of milliseconds it took for the deferred invocation. */ var now = ctxNow || function() { return root.Date.now(); }; /*------------------------------------------------------------------------*/ /** * The opposite of `_.before`; this method creates a function that invokes * `func` once it's called `n` or more times. * * @static * @memberOf _ * @since 0.1.0 * @category Function * @param {number} n The number of calls before `func` is invoked. * @param {Function} func The function to restrict. * @returns {Function} Returns the new restricted function. * @example * * var saves = ['profile', 'settings']; * * var done = _.after(saves.length, function() { * console.log('done saving!'); * }); * * _.forEach(saves, function(type) { * asyncSave({ 'type': type, 'complete': done }); * }); * // => Logs 'done saving!' after the two async saves have completed. */ function after(n, func) { if (typeof func != 'function') { throw new TypeError(FUNC_ERROR_TEXT); } n = toInteger(n); return function() { if (--n < 1) { return func.apply(this, arguments); } }; } /** * Creates a function that invokes `func`, with up to `n` arguments, * ignoring any additional arguments. * * @static * @memberOf _ * @since 3.0.0 * @category Function * @param {Function} func The function to cap arguments for. * @param {number} [n=func.length] The arity cap. * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. * @returns {Function} Returns the new capped function. * @example * * _.map(['6', '8', '10'], _.ary(parseInt, 1)); * // => [6, 8, 10] */ function ary(func, n, guard) { n = guard ? undefined : n; n = (func && n == null) ? func.length : n; return createWrap(func, WRAP_ARY_FLAG, undefined, undefined, undefined, undefined, n); } /** * Creates a function that invokes `func`, with the `this` binding and arguments * of the created function, while it's called less than `n` times. Subsequent * calls to the created function return the result of the last `func` invocation. * * @static * @memberOf _ * @since 3.0.0 * @category Function * @param {number} n The number of calls at which `func` is no longer invoked. * @param {Function} func The function to restrict. * @returns {Function} Returns the new restricted function. * @example * * jQuery(element).on('click', _.before(5, addContactToList)); * // => Allows adding up to 4 contacts to the list. */ function before(n, func) { var result; if (typeof func != 'function') { throw new TypeError(FUNC_ERROR_TEXT); } n = toInteger(n); return function() { if (--n > 0) { result = func.apply(this, arguments); } if (n <= 1) { func = undefined; } return result; }; } /** * Creates a function that invokes `func` with the `this` binding of `thisArg` * and `partials` prepended to the arguments it receives. * * The `_.bind.placeholder` value, which defaults to `_` in monolithic builds, * may be used as a placeholder for partially applied arguments. * * **Note:** Unlike native `Function#bind`, this method doesn't set the "length" * property of bound functions. * * @static * @memberOf _ * @since 0.1.0 * @category Function * @param {Function} func The function to bind. * @param {*} thisArg The `this` binding of `func`. * @param {...*} [partials] The arguments to be partially applied. * @returns {Function} Returns the new bound function. * @example * * function greet(greeting, punctuation) { * return greeting + ' ' + this.user + punctuation; * } * * var object = { 'user': 'fred' }; * * var bound = _.bind(greet, object, 'hi'); * bound('!'); * // => 'hi fred!' * * // Bound with placeholders. * var bound = _.bind(greet, object, _, '!'); * bound('hi'); * // => 'hi fred!' */ var bind = baseRest(function(func, thisArg, partials) { var bitmask = WRAP_BIND_FLAG; if (partials.length) { var holders = replaceHolders(partials, getHolder(bind)); bitmask |= WRAP_PARTIAL_FLAG; } return createWrap(func, bitmask, thisArg, partials, holders); }); /** * Creates a function that invokes the method at `object[key]` with `partials` * prepended to the arguments it receives. * * This method differs from `_.bind` by allowing bound functions to reference * methods that may be redefined or don't yet exist. See * [Peter Michaux's article](http://peter.michaux.ca/articles/lazy-function-definition-pattern) * for more details. * * The `_.bindKey.placeholder` value, which defaults to `_` in monolithic * builds, may be used as a placeholder for partially applied arguments. * * @static * @memberOf _ * @since 0.10.0 * @category Function * @param {Object} object The object to invoke the method on. * @param {string} key The key of the method. * @param {...*} [partials] The arguments to be partially applied. * @returns {Function} Returns the new bound function. * @example * * var object = { * 'user': 'fred', * 'greet': function(greeting, punctuation) { * return greeting + ' ' + this.user + punctuation; * } * }; * * var bound = _.bindKey(object, 'greet', 'hi'); * bound('!'); * // => 'hi fred!' * * object.greet = function(greeting, punctuation) { * return greeting + 'ya ' + this.user + punctuation; * }; * * bound('!'); * // => 'hiya fred!' * * // Bound with placeholders. * var bound = _.bindKey(object, 'greet', _, '!'); * bound('hi'); * // => 'hiya fred!' */ var bindKey = baseRest(function(object, key, partials) { var bitmask = WRAP_BIND_FLAG | WRAP_BIND_KEY_FLAG; if (partials.length) { var holders = replaceHolders(partials, getHolder(bindKey)); bitmask |= WRAP_PARTIAL_FLAG; } return createWrap(key, bitmask, object, partials, holders); }); /** * Creates a function that accepts arguments of `func` and either invokes * `func` returning its result, if at least `arity` number of arguments have * been provided, or returns a function that accepts the remaining `func` * arguments, and so on. The arity of `func` may be specified if `func.length` * is not sufficient. * * The `_.curry.placeholder` value, which defaults to `_` in monolithic builds, * may be used as a placeholder for provided arguments. * * **Note:** This method doesn't set the "length" property of curried functions. * * @static * @memberOf _ * @since 2.0.0 * @category Function * @param {Function} func The function to curry. * @param {number} [arity=func.length] The arity of `func`. * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. * @returns {Function} Returns the new curried function. * @example * * var abc = function(a, b, c) { * return [a, b, c]; * }; * * var curried = _.curry(abc); * * curried(1)(2)(3); * // => [1, 2, 3] * * curried(1, 2)(3); * // => [1, 2, 3] * * curried(1, 2, 3); * // => [1, 2, 3] * * // Curried with placeholders. * curried(1)(_, 3)(2); * // => [1, 2, 3] */ function curry(func, arity, guard) { arity = guard ? undefined : arity; var result = createWrap(func, WRAP_CURRY_FLAG, undefined, undefined, undefined, undefined, undefined, arity); result.placeholder = curry.placeholder; return result; } /** * This method is like `_.curry` except that arguments are applied to `func` * in the manner of `_.partialRight` instead of `_.partial`. * * The `_.curryRight.placeholder` value, which defaults to `_` in monolithic * builds, may be used as a placeholder for provided arguments. * * **Note:** This method doesn't set the "length" property of curried functions. * * @static * @memberOf _ * @since 3.0.0 * @category Function * @param {Function} func The function to curry. * @param {number} [arity=func.length] The arity of `func`. * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. * @returns {Function} Returns the new curried function. * @example * * var abc = function(a, b, c) { * return [a, b, c]; * }; * * var curried = _.curryRight(abc); * * curried(3)(2)(1); * // => [1, 2, 3] * * curried(2, 3)(1); * // => [1, 2, 3] * * curried(1, 2, 3); * // => [1, 2, 3] * * // Curried with placeholders. * curried(3)(1, _)(2); * // => [1, 2, 3] */ function curryRight(func, arity, guard) { arity = guard ? undefined : arity; var result = createWrap(func, WRAP_CURRY_RIGHT_FLAG, undefined, undefined, undefined, undefined, undefined, arity); result.placeholder = curryRight.placeholder; return result; } /** * Creates a debounced function that delays invoking `func` until after `wait` * milliseconds have elapsed since the last time the debounced function was * invoked. The debounced function comes with a `cancel` method to cancel * delayed `func` invocations and a `flush` method to immediately invoke them. * Provide `options` to indicate whether `func` should be invoked on the * leading and/or trailing edge of the `wait` timeout. The `func` is invoked * with the last arguments provided to the debounced function. Subsequent * calls to the debounced function return the result of the last `func` * invocation. * * **Note:** If `leading` and `trailing` options are `true`, `func` is * invoked on the trailing edge of the timeout only if the debounced function * is invoked more than once during the `wait` timeout. * * If `wait` is `0` and `leading` is `false`, `func` invocation is deferred * until to the next tick, similar to `setTimeout` with a timeout of `0`. * * See [David Corbacho's article](https://css-tricks.com/debouncing-throttling-explained-examples/) * for details over the differences between `_.debounce` and `_.throttle`. * * @static * @memberOf _ * @since 0.1.0 * @category Function * @param {Function} func The function to debounce. * @param {number} [wait=0] The number of milliseconds to delay. * @param {Object} [options={}] The options object. * @param {boolean} [options.leading=false] * Specify invoking on the leading edge of the timeout. * @param {number} [options.maxWait] * The maximum time `func` is allowed to be delayed before it's invoked. * @param {boolean} [options.trailing=true] * Specify invoking on the trailing edge of the timeout. * @returns {Function} Returns the new debounced function. * @example * * // Avoid costly calculations while the window size is in flux. * jQuery(window).on('resize', _.debounce(calculateLayout, 150)); * * // Invoke `sendMail` when clicked, debouncing subsequent calls. * jQuery(element).on('click', _.debounce(sendMail, 300, { * 'leading': true, * 'trailing': false * })); * * // Ensure `batchLog` is invoked once after 1 second of debounced calls. * var debounced = _.debounce(batchLog, 250, { 'maxWait': 1000 }); * var source = new EventSource('/stream'); * jQuery(source).on('message', debounced); * * // Cancel the trailing debounced invocation. * jQuery(window).on('popstate', debounced.cancel); */ function debounce(func, wait, options) { var lastArgs, lastThis, maxWait, result, timerId, lastCallTime, lastInvokeTime = 0, leading = false, maxing = false, trailing = true; if (typeof func != 'function') { throw new TypeError(FUNC_ERROR_TEXT); } wait = toNumber(wait) || 0; if (isObject(options)) { leading = !!options.leading; maxing = 'maxWait' in options; maxWait = maxing ? nativeMax(toNumber(options.maxWait) || 0, wait) : maxWait; trailing = 'trailing' in options ? !!options.trailing : trailing; } function invokeFunc(time) { var args = lastArgs, thisArg = lastThis; lastArgs = lastThis = undefined; lastInvokeTime = time; result = func.apply(thisArg, args); return result; } function leadingEdge(time) { // Reset any `maxWait` timer. lastInvokeTime = time; // Start the timer for the trailing edge. timerId = setTimeout(timerExpired, wait); // Invoke the leading edge. return leading ? invokeFunc(time) : result; } function remainingWait(time) { var timeSinceLastCall = time - lastCallTime, timeSinceLastInvoke = time - lastInvokeTime, timeWaiting = wait - timeSinceLastCall; return maxing ? nativeMin(timeWaiting, maxWait - timeSinceLastInvoke) : timeWaiting; } function shouldInvoke(time) { var timeSinceLastCall = time - lastCallTime, timeSinceLastInvoke = time - lastInvokeTime; // Either this is the first call, activity has stopped and we're at the // trailing edge, the system time has gone backwards and we're treating // it as the trailing edge, or we've hit the `maxWait` limit. return (lastCallTime === undefined || (timeSinceLastCall >= wait) || (timeSinceLastCall < 0) || (maxing && timeSinceLastInvoke >= maxWait)); } function timerExpired() { var time = now(); if (shouldInvoke(time)) { return trailingEdge(time); } // Restart the timer. timerId = setTimeout(timerExpired, remainingWait(time)); } function trailingEdge(time) { timerId = undefined; // Only invoke if we have `lastArgs` which means `func` has been // debounced at least once. if (trailing && lastArgs) { return invokeFunc(time); } lastArgs = lastThis = undefined; return result; } function cancel() { if (timerId !== undefined) { clearTimeout(timerId); } lastInvokeTime = 0; lastArgs = lastCallTime = lastThis = timerId = undefined; } function flush() { return timerId === undefined ? result : trailingEdge(now()); } function debounced() { var time = now(), isInvoking = shouldInvoke(time); lastArgs = arguments; lastThis = this; lastCallTime = time; if (isInvoking) { if (timerId === undefined) { return leadingEdge(lastCallTime); } if (maxing) { // Handle invocations in a tight loop. timerId = setTimeout(timerExpired, wait); return invokeFunc(lastCallTime); } } if (timerId === undefined) { timerId = setTimeout(timerExpired, wait); } return result; } debounced.cancel = cancel; debounced.flush = flush; return debounced; } /** * Defers invoking the `func` until the current call stack has cleared. Any * additional arguments are provided to `func` when it's invoked. * * @static * @memberOf _ * @since 0.1.0 * @category Function * @param {Function} func The function to defer. * @param {...*} [args] The arguments to invoke `func` with. * @returns {number} Returns the timer id. * @example * * _.defer(function(text) { * console.log(text); * }, 'deferred'); * // => Logs 'deferred' after one millisecond. */ var defer = baseRest(function(func, args) { return baseDelay(func, 1, args); }); /** * Invokes `func` after `wait` milliseconds. Any additional arguments are * provided to `func` when it's invoked. * * @static * @memberOf _ * @since 0.1.0 * @category Function * @param {Function} func The function to delay. * @param {number} wait The number of milliseconds to delay invocation. * @param {...*} [args] The arguments to invoke `func` with. * @returns {number} Returns the timer id. * @example * * _.delay(function(text) { * console.log(text); * }, 1000, 'later'); * // => Logs 'later' after one second. */ var delay = baseRest(function(func, wait, args) { return baseDelay(func, toNumber(wait) || 0, args); }); /** * Creates a function that invokes `func` with arguments reversed. * * @static * @memberOf _ * @since 4.0.0 * @category Function * @param {Function} func The function to flip arguments for. * @returns {Function} Returns the new flipped function. * @example * * var flipped = _.flip(function() { * return _.toArray(arguments); * }); * * flipped('a', 'b', 'c', 'd'); * // => ['d', 'c', 'b', 'a'] */ function flip(func) { return createWrap(func, WRAP_FLIP_FLAG); } /** * Creates a function that memoizes the result of `func`. If `resolver` is * provided, it determines the cache key for storing the result based on the * arguments provided to the memoized function. By default, the first argument * provided to the memoized function is used as the map cache key. The `func` * is invoked with the `this` binding of the memoized function. * * **Note:** The cache is exposed as the `cache` property on the memoized * function. Its creation may be customized by replacing the `_.memoize.Cache` * constructor with one whose instances implement the * [`Map`](http://ecma-international.org/ecma-262/7.0/#sec-properties-of-the-map-prototype-object) * method interface of `clear`, `delete`, `get`, `has`, and `set`. * * @static * @memberOf _ * @since 0.1.0 * @category Function * @param {Function} func The function to have its output memoized. * @param {Function} [resolver] The function to resolve the cache key. * @returns {Function} Returns the new memoized function. * @example * * var object = { 'a': 1, 'b': 2 }; * var other = { 'c': 3, 'd': 4 }; * * var values = _.memoize(_.values); * values(object); * // => [1, 2] * * values(other); * // => [3, 4] * * object.a = 2; * values(object); * // => [1, 2] * * // Modify the result cache. * values.cache.set(object, ['a', 'b']); * values(object); * // => ['a', 'b'] * * // Replace `_.memoize.Cache`. * _.memoize.Cache = WeakMap; */ function memoize(func, resolver) { if (typeof func != 'function' || (resolver != null && typeof resolver != 'function')) { throw new TypeError(FUNC_ERROR_TEXT); } var memoized = function() { var args = arguments, key = resolver ? resolver.apply(this, args) : args[0], cache = memoized.cache; if (cache.has(key)) { return cache.get(key); } var result = func.apply(this, args); memoized.cache = cache.set(key, result) || cache; return result; }; memoized.cache = new (memoize.Cache || MapCache); return memoized; } // Expose `MapCache`. memoize.Cache = MapCache; /** * Creates a function that negates the result of the predicate `func`. The * `func` predicate is invoked with the `this` binding and arguments of the * created function. * * @static * @memberOf _ * @since 3.0.0 * @category Function * @param {Function} predicate The predicate to negate. * @returns {Function} Returns the new negated function. * @example * * function isEven(n) { * return n % 2 == 0; * } * * _.filter([1, 2, 3, 4, 5, 6], _.negate(isEven)); * // => [1, 3, 5] */ function negate(predicate) { if (typeof predicate != 'function') { throw new TypeError(FUNC_ERROR_TEXT); } return function() { var args = arguments; switch (args.length) { case 0: return !predicate.call(this); case 1: return !predicate.call(this, args[0]); case 2: return !predicate.call(this, args[0], args[1]); case 3: return !predicate.call(this, args[0], args[1], args[2]); } return !predicate.apply(this, args); }; } /** * Creates a function that is restricted to invoking `func` once. Repeat calls * to the function return the value of the first invocation. The `func` is * invoked with the `this` binding and arguments of the created function. * * @static * @memberOf _ * @since 0.1.0 * @category Function * @param {Function} func The function to restrict. * @returns {Function} Returns the new restricted function. * @example * * var initialize = _.once(createApplication); * initialize(); * initialize(); * // => `createApplication` is invoked once */ function once(func) { return before(2, func); } /** * Creates a function that invokes `func` with its arguments transformed. * * @static * @since 4.0.0 * @memberOf _ * @category Function * @param {Function} func The function to wrap. * @param {...(Function|Function[])} [transforms=[_.identity]] * The argument transforms. * @returns {Function} Returns the new function. * @example * * function doubled(n) { * return n * 2; * } * * function square(n) { * return n * n; * } * * var func = _.overArgs(function(x, y) { * return [x, y]; * }, [square, doubled]); * * func(9, 3); * // => [81, 6] * * func(10, 5); * // => [100, 10] */ var overArgs = castRest(function(func, transforms) { transforms = (transforms.length == 1 && isArray(transforms[0])) ? arrayMap(transforms[0], baseUnary(getIteratee())) : arrayMap(baseFlatten(transforms, 1), baseUnary(getIteratee())); var funcsLength = transforms.length; return baseRest(function(args) { var index = -1, length = nativeMin(args.length, funcsLength); while (++index < length) { args[index] = transforms[index].call(this, args[index]); } return apply(func, this, args); }); }); /** * Creates a function that invokes `func` with `partials` prepended to the * arguments it receives. This method is like `_.bind` except it does **not** * alter the `this` binding. * * The `_.partial.placeholder` value, which defaults to `_` in monolithic * builds, may be used as a placeholder for partially applied arguments. * * **Note:** This method doesn't set the "length" property of partially * applied functions. * * @static * @memberOf _ * @since 0.2.0 * @category Function * @param {Function} func The function to partially apply arguments to. * @param {...*} [partials] The arguments to be partially applied. * @returns {Function} Returns the new partially applied function. * @example * * function greet(greeting, name) { * return greeting + ' ' + name; * } * * var sayHelloTo = _.partial(greet, 'hello'); * sayHelloTo('fred'); * // => 'hello fred' * * // Partially applied with placeholders. * var greetFred = _.partial(greet, _, 'fred'); * greetFred('hi'); * // => 'hi fred' */ var partial = baseRest(function(func, partials) { var holders = replaceHolders(partials, getHolder(partial)); return createWrap(func, WRAP_PARTIAL_FLAG, undefined, partials, holders); }); /** * This method is like `_.partial` except that partially applied arguments * are appended to the arguments it receives. * * The `_.partialRight.placeholder` value, which defaults to `_` in monolithic * builds, may be used as a placeholder for partially applied arguments. * * **Note:** This method doesn't set the "length" property of partially * applied functions. * * @static * @memberOf _ * @since 1.0.0 * @category Function * @param {Function} func The function to partially apply arguments to. * @param {...*} [partials] The arguments to be partially applied. * @returns {Function} Returns the new partially applied function. * @example * * function greet(greeting, name) { * return greeting + ' ' + name; * } * * var greetFred = _.partialRight(greet, 'fred'); * greetFred('hi'); * // => 'hi fred' * * // Partially applied with placeholders. * var sayHelloTo = _.partialRight(greet, 'hello', _); * sayHelloTo('fred'); * // => 'hello fred' */ var partialRight = baseRest(function(func, partials) { var holders = replaceHolders(partials, getHolder(partialRight)); return createWrap(func, WRAP_PARTIAL_RIGHT_FLAG, undefined, partials, holders); }); /** * Creates a function that invokes `func` with arguments arranged according * to the specified `indexes` where the argument value at the first index is * provided as the first argument, the argument value at the second index is * provided as the second argument, and so on. * * @static * @memberOf _ * @since 3.0.0 * @category Function * @param {Function} func The function to rearrange arguments for. * @param {...(number|number[])} indexes The arranged argument indexes. * @returns {Function} Returns the new function. * @example * * var rearged = _.rearg(function(a, b, c) { * return [a, b, c]; * }, [2, 0, 1]); * * rearged('b', 'c', 'a') * // => ['a', 'b', 'c'] */ var rearg = flatRest(function(func, indexes) { return createWrap(func, WRAP_REARG_FLAG, undefined, undefined, undefined, indexes); }); /** * Creates a function that invokes `func` with the `this` binding of the * created function and arguments from `start` and beyond provided as * an array. * * **Note:** This method is based on the * [rest parameter](https://mdn.io/rest_parameters). * * @static * @memberOf _ * @since 4.0.0 * @category Function * @param {Function} func The function to apply a rest parameter to. * @param {number} [start=func.length-1] The start position of the rest parameter. * @returns {Function} Returns the new function. * @example * * var say = _.rest(function(what, names) { * return what + ' ' + _.initial(names).join(', ') + * (_.size(names) > 1 ? ', & ' : '') + _.last(names); * }); * * say('hello', 'fred', 'barney', 'pebbles'); * // => 'hello fred, barney, & pebbles' */ function rest(func, start) { if (typeof func != 'function') { throw new TypeError(FUNC_ERROR_TEXT); } start = start === undefined ? start : toInteger(start); return baseRest(func, start); } /** * Creates a function that invokes `func` with the `this` binding of the * create function and an array of arguments much like * [`Function#apply`](http://www.ecma-international.org/ecma-262/7.0/#sec-function.prototype.apply). * * **Note:** This method is based on the * [spread operator](https://mdn.io/spread_operator). * * @static * @memberOf _ * @since 3.2.0 * @category Function * @param {Function} func The function to spread arguments over. * @param {number} [start=0] The start position of the spread. * @returns {Function} Returns the new function. * @example * * var say = _.spread(function(who, what) { * return who + ' says ' + what; * }); * * say(['fred', 'hello']); * // => 'fred says hello' * * var numbers = Promise.all([ * Promise.resolve(40), * Promise.resolve(36) * ]); * * numbers.then(_.spread(function(x, y) { * return x + y; * })); * // => a Promise of 76 */ function spread(func, start) { if (typeof func != 'function') { throw new TypeError(FUNC_ERROR_TEXT); } start = start == null ? 0 : nativeMax(toInteger(start), 0); return baseRest(function(args) { var array = args[start], otherArgs = castSlice(args, 0, start); if (array) { arrayPush(otherArgs, array); } return apply(func, this, otherArgs); }); } /** * Creates a throttled function that only invokes `func` at most once per * every `wait` milliseconds. The throttled function comes with a `cancel` * method to cancel delayed `func` invocations and a `flush` method to * immediately invoke them. Provide `options` to indicate whether `func` * should be invoked on the leading and/or trailing edge of the `wait` * timeout. The `func` is invoked with the last arguments provided to the * throttled function. Subsequent calls to the throttled function return the * result of the last `func` invocation. * * **Note:** If `leading` and `trailing` options are `true`, `func` is * invoked on the trailing edge of the timeout only if the throttled function * is invoked more than once during the `wait` timeout. * * If `wait` is `0` and `leading` is `false`, `func` invocation is deferred * until to the next tick, similar to `setTimeout` with a timeout of `0`. * * See [David Corbacho's article](https://css-tricks.com/debouncing-throttling-explained-examples/) * for details over the differences between `_.throttle` and `_.debounce`. * * @static * @memberOf _ * @since 0.1.0 * @category Function * @param {Function} func The function to throttle. * @param {number} [wait=0] The number of milliseconds to throttle invocations to. * @param {Object} [options={}] The options object. * @param {boolean} [options.leading=true] * Specify invoking on the leading edge of the timeout. * @param {boolean} [options.trailing=true] * Specify invoking on the trailing edge of the timeout. * @returns {Function} Returns the new throttled function. * @example * * // Avoid excessively updating the position while scrolling. * jQuery(window).on('scroll', _.throttle(updatePosition, 100)); * * // Invoke `renewToken` when the click event is fired, but not more than once every 5 minutes. * var throttled = _.throttle(renewToken, 300000, { 'trailing': false }); * jQuery(element).on('click', throttled); * * // Cancel the trailing throttled invocation. * jQuery(window).on('popstate', throttled.cancel); */ function throttle(func, wait, options) { var leading = true, trailing = true; if (typeof func != 'function') { throw new TypeError(FUNC_ERROR_TEXT); } if (isObject(options)) { leading = 'leading' in options ? !!options.leading : leading; trailing = 'trailing' in options ? !!options.trailing : trailing; } return debounce(func, wait, { 'leading': leading, 'maxWait': wait, 'trailing': trailing }); } /** * Creates a function that accepts up to one argument, ignoring any * additional arguments. * * @static * @memberOf _ * @since 4.0.0 * @category Function * @param {Function} func The function to cap arguments for. * @returns {Function} Returns the new capped function. * @example * * _.map(['6', '8', '10'], _.unary(parseInt)); * // => [6, 8, 10] */ function unary(func) { return ary(func, 1); } /** * Creates a function that provides `value` to `wrapper` as its first * argument. Any additional arguments provided to the function are appended * to those provided to the `wrapper`. The wrapper is invoked with the `this` * binding of the created function. * * @static * @memberOf _ * @since 0.1.0 * @category Function * @param {*} value The value to wrap. * @param {Function} [wrapper=identity] The wrapper function. * @returns {Function} Returns the new function. * @example * * var p = _.wrap(_.escape, function(func, text) { * return '

' + func(text) + '

'; * }); * * p('fred, barney, & pebbles'); * // => '

fred, barney, & pebbles

' */ function wrap(value, wrapper) { return partial(castFunction(wrapper), value); } /*------------------------------------------------------------------------*/ /** * Casts `value` as an array if it's not one. * * @static * @memberOf _ * @since 4.4.0 * @category Lang * @param {*} value The value to inspect. * @returns {Array} Returns the cast array. * @example * * _.castArray(1); * // => [1] * * _.castArray({ 'a': 1 }); * // => [{ 'a': 1 }] * * _.castArray('abc'); * // => ['abc'] * * _.castArray(null); * // => [null] * * _.castArray(undefined); * // => [undefined] * * _.castArray(); * // => [] * * var array = [1, 2, 3]; * console.log(_.castArray(array) === array); * // => true */ function castArray() { if (!arguments.length) { return []; } var value = arguments[0]; return isArray(value) ? value : [value]; } /** * Creates a shallow clone of `value`. * * **Note:** This method is loosely based on the * [structured clone algorithm](https://mdn.io/Structured_clone_algorithm) * and supports cloning arrays, array buffers, booleans, date objects, maps, * numbers, `Object` objects, regexes, sets, strings, symbols, and typed * arrays. The own enumerable properties of `arguments` objects are cloned * as plain objects. An empty object is returned for uncloneable values such * as error objects, functions, DOM nodes, and WeakMaps. * * @static * @memberOf _ * @since 0.1.0 * @category Lang * @param {*} value The value to clone. * @returns {*} Returns the cloned value. * @see _.cloneDeep * @example * * var objects = [{ 'a': 1 }, { 'b': 2 }]; * * var shallow = _.clone(objects); * console.log(shallow[0] === objects[0]); * // => true */ function clone(value) { return baseClone(value, CLONE_SYMBOLS_FLAG); } /** * This method is like `_.clone` except that it accepts `customizer` which * is invoked to produce the cloned value. If `customizer` returns `undefined`, * cloning is handled by the method instead. The `customizer` is invoked with * up to four arguments; (value [, index|key, object, stack]). * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to clone. * @param {Function} [customizer] The function to customize cloning. * @returns {*} Returns the cloned value. * @see _.cloneDeepWith * @example * * function customizer(value) { * if (_.isElement(value)) { * return value.cloneNode(false); * } * } * * var el = _.cloneWith(document.body, customizer); * * console.log(el === document.body); * // => false * console.log(el.nodeName); * // => 'BODY' * console.log(el.childNodes.length); * // => 0 */ function cloneWith(value, customizer) { customizer = typeof customizer == 'function' ? customizer : undefined; return baseClone(value, CLONE_SYMBOLS_FLAG, customizer); } /** * This method is like `_.clone` except that it recursively clones `value`. * * @static * @memberOf _ * @since 1.0.0 * @category Lang * @param {*} value The value to recursively clone. * @returns {*} Returns the deep cloned value. * @see _.clone * @example * * var objects = [{ 'a': 1 }, { 'b': 2 }]; * * var deep = _.cloneDeep(objects); * console.log(deep[0] === objects[0]); * // => false */ function cloneDeep(value) { return baseClone(value, CLONE_DEEP_FLAG | CLONE_SYMBOLS_FLAG); } /** * This method is like `_.cloneWith` except that it recursively clones `value`. * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to recursively clone. * @param {Function} [customizer] The function to customize cloning. * @returns {*} Returns the deep cloned value. * @see _.cloneWith * @example * * function customizer(value) { * if (_.isElement(value)) { * return value.cloneNode(true); * } * } * * var el = _.cloneDeepWith(document.body, customizer); * * console.log(el === document.body); * // => false * console.log(el.nodeName); * // => 'BODY' * console.log(el.childNodes.length); * // => 20 */ function cloneDeepWith(value, customizer) { customizer = typeof customizer == 'function' ? customizer : undefined; return baseClone(value, CLONE_DEEP_FLAG | CLONE_SYMBOLS_FLAG, customizer); } /** * Checks if `object` conforms to `source` by invoking the predicate * properties of `source` with the corresponding property values of `object`. * * **Note:** This method is equivalent to `_.conforms` when `source` is * partially applied. * * @static * @memberOf _ * @since 4.14.0 * @category Lang * @param {Object} object The object to inspect. * @param {Object} source The object of property predicates to conform to. * @returns {boolean} Returns `true` if `object` conforms, else `false`. * @example * * var object = { 'a': 1, 'b': 2 }; * * _.conformsTo(object, { 'b': function(n) { return n > 1; } }); * // => true * * _.conformsTo(object, { 'b': function(n) { return n > 2; } }); * // => false */ function conformsTo(object, source) { return source == null || baseConformsTo(object, source, keys(source)); } /** * Performs a * [`SameValueZero`](http://ecma-international.org/ecma-262/7.0/#sec-samevaluezero) * comparison between two values to determine if they are equivalent. * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to compare. * @param {*} other The other value to compare. * @returns {boolean} Returns `true` if the values are equivalent, else `false`. * @example * * var object = { 'a': 1 }; * var other = { 'a': 1 }; * * _.eq(object, object); * // => true * * _.eq(object, other); * // => false * * _.eq('a', 'a'); * // => true * * _.eq('a', Object('a')); * // => false * * _.eq(NaN, NaN); * // => true */ function eq(value, other) { return value === other || (value !== value && other !== other); } /** * Checks if `value` is greater than `other`. * * @static * @memberOf _ * @since 3.9.0 * @category Lang * @param {*} value The value to compare. * @param {*} other The other value to compare. * @returns {boolean} Returns `true` if `value` is greater than `other`, * else `false`. * @see _.lt * @example * * _.gt(3, 1); * // => true * * _.gt(3, 3); * // => false * * _.gt(1, 3); * // => false */ var gt = createRelationalOperation(baseGt); /** * Checks if `value` is greater than or equal to `other`. * * @static * @memberOf _ * @since 3.9.0 * @category Lang * @param {*} value The value to compare. * @param {*} other The other value to compare. * @returns {boolean} Returns `true` if `value` is greater than or equal to * `other`, else `false`. * @see _.lte * @example * * _.gte(3, 1); * // => true * * _.gte(3, 3); * // => true * * _.gte(1, 3); * // => false */ var gte = createRelationalOperation(function(value, other) { return value >= other; }); /** * Checks if `value` is likely an `arguments` object. * * @static * @memberOf _ * @since 0.1.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is an `arguments` object, * else `false`. * @example * * _.isArguments(function() { return arguments; }()); * // => true * * _.isArguments([1, 2, 3]); * // => false */ var isArguments = baseIsArguments(function() { return arguments; }()) ? baseIsArguments : function(value) { return isObjectLike(value) && hasOwnProperty.call(value, 'callee') && !propertyIsEnumerable.call(value, 'callee'); }; /** * Checks if `value` is classified as an `Array` object. * * @static * @memberOf _ * @since 0.1.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is an array, else `false`. * @example * * _.isArray([1, 2, 3]); * // => true * * _.isArray(document.body.children); * // => false * * _.isArray('abc'); * // => false * * _.isArray(_.noop); * // => false */ var isArray = Array.isArray; /** * Checks if `value` is classified as an `ArrayBuffer` object. * * @static * @memberOf _ * @since 4.3.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is an array buffer, else `false`. * @example * * _.isArrayBuffer(new ArrayBuffer(2)); * // => true * * _.isArrayBuffer(new Array(2)); * // => false */ var isArrayBuffer = nodeIsArrayBuffer ? baseUnary(nodeIsArrayBuffer) : baseIsArrayBuffer; /** * Checks if `value` is array-like. A value is considered array-like if it's * not a function and has a `value.length` that's an integer greater than or * equal to `0` and less than or equal to `Number.MAX_SAFE_INTEGER`. * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is array-like, else `false`. * @example * * _.isArrayLike([1, 2, 3]); * // => true * * _.isArrayLike(document.body.children); * // => true * * _.isArrayLike('abc'); * // => true * * _.isArrayLike(_.noop); * // => false */ function isArrayLike(value) { return value != null && isLength(value.length) && !isFunction(value); } /** * This method is like `_.isArrayLike` except that it also checks if `value` * is an object. * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is an array-like object, * else `false`. * @example * * _.isArrayLikeObject([1, 2, 3]); * // => true * * _.isArrayLikeObject(document.body.children); * // => true * * _.isArrayLikeObject('abc'); * // => false * * _.isArrayLikeObject(_.noop); * // => false */ function isArrayLikeObject(value) { return isObjectLike(value) && isArrayLike(value); } /** * Checks if `value` is classified as a boolean primitive or object. * * @static * @memberOf _ * @since 0.1.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a boolean, else `false`. * @example * * _.isBoolean(false); * // => true * * _.isBoolean(null); * // => false */ function isBoolean(value) { return value === true || value === false || (isObjectLike(value) && baseGetTag(value) == boolTag); } /** * Checks if `value` is a buffer. * * @static * @memberOf _ * @since 4.3.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a buffer, else `false`. * @example * * _.isBuffer(new Buffer(2)); * // => true * * _.isBuffer(new Uint8Array(2)); * // => false */ var isBuffer = nativeIsBuffer || stubFalse; /** * Checks if `value` is classified as a `Date` object. * * @static * @memberOf _ * @since 0.1.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a date object, else `false`. * @example * * _.isDate(new Date); * // => true * * _.isDate('Mon April 23 2012'); * // => false */ var isDate = nodeIsDate ? baseUnary(nodeIsDate) : baseIsDate; /** * Checks if `value` is likely a DOM element. * * @static * @memberOf _ * @since 0.1.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a DOM element, else `false`. * @example * * _.isElement(document.body); * // => true * * _.isElement(''); * // => false */ function isElement(value) { return isObjectLike(value) && value.nodeType === 1 && !isPlainObject(value); } /** * Checks if `value` is an empty object, collection, map, or set. * * Objects are considered empty if they have no own enumerable string keyed * properties. * * Array-like values such as `arguments` objects, arrays, buffers, strings, or * jQuery-like collections are considered empty if they have a `length` of `0`. * Similarly, maps and sets are considered empty if they have a `size` of `0`. * * @static * @memberOf _ * @since 0.1.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is empty, else `false`. * @example * * _.isEmpty(null); * // => true * * _.isEmpty(true); * // => true * * _.isEmpty(1); * // => true * * _.isEmpty([1, 2, 3]); * // => false * * _.isEmpty({ 'a': 1 }); * // => false */ function isEmpty(value) { if (value == null) { return true; } if (isArrayLike(value) && (isArray(value) || typeof value == 'string' || typeof value.splice == 'function' || isBuffer(value) || isTypedArray(value) || isArguments(value))) { return !value.length; } var tag = getTag(value); if (tag == mapTag || tag == setTag) { return !value.size; } if (isPrototype(value)) { return !baseKeys(value).length; } for (var key in value) { if (hasOwnProperty.call(value, key)) { return false; } } return true; } /** * Performs a deep comparison between two values to determine if they are * equivalent. * * **Note:** This method supports comparing arrays, array buffers, booleans, * date objects, error objects, maps, numbers, `Object` objects, regexes, * sets, strings, symbols, and typed arrays. `Object` objects are compared * by their own, not inherited, enumerable properties. Functions and DOM * nodes are compared by strict equality, i.e. `===`. * * @static * @memberOf _ * @since 0.1.0 * @category Lang * @param {*} value The value to compare. * @param {*} other The other value to compare. * @returns {boolean} Returns `true` if the values are equivalent, else `false`. * @example * * var object = { 'a': 1 }; * var other = { 'a': 1 }; * * _.isEqual(object, other); * // => true * * object === other; * // => false */ function isEqual(value, other) { return baseIsEqual(value, other); } /** * This method is like `_.isEqual` except that it accepts `customizer` which * is invoked to compare values. If `customizer` returns `undefined`, comparisons * are handled by the method instead. The `customizer` is invoked with up to * six arguments: (objValue, othValue [, index|key, object, other, stack]). * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to compare. * @param {*} other The other value to compare. * @param {Function} [customizer] The function to customize comparisons. * @returns {boolean} Returns `true` if the values are equivalent, else `false`. * @example * * function isGreeting(value) { * return /^h(?:i|ello)$/.test(value); * } * * function customizer(objValue, othValue) { * if (isGreeting(objValue) && isGreeting(othValue)) { * return true; * } * } * * var array = ['hello', 'goodbye']; * var other = ['hi', 'goodbye']; * * _.isEqualWith(array, other, customizer); * // => true */ function isEqualWith(value, other, customizer) { customizer = typeof customizer == 'function' ? customizer : undefined; var result = customizer ? customizer(value, other) : undefined; return result === undefined ? baseIsEqual(value, other, undefined, customizer) : !!result; } /** * Checks if `value` is an `Error`, `EvalError`, `RangeError`, `ReferenceError`, * `SyntaxError`, `TypeError`, or `URIError` object. * * @static * @memberOf _ * @since 3.0.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is an error object, else `false`. * @example * * _.isError(new Error); * // => true * * _.isError(Error); * // => false */ function isError(value) { if (!isObjectLike(value)) { return false; } var tag = baseGetTag(value); return tag == errorTag || tag == domExcTag || (typeof value.message == 'string' && typeof value.name == 'string' && !isPlainObject(value)); } /** * Checks if `value` is a finite primitive number. * * **Note:** This method is based on * [`Number.isFinite`](https://mdn.io/Number/isFinite). * * @static * @memberOf _ * @since 0.1.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a finite number, else `false`. * @example * * _.isFinite(3); * // => true * * _.isFinite(Number.MIN_VALUE); * // => true * * _.isFinite(Infinity); * // => false * * _.isFinite('3'); * // => false */ function isFinite(value) { return typeof value == 'number' && nativeIsFinite(value); } /** * Checks if `value` is classified as a `Function` object. * * @static * @memberOf _ * @since 0.1.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a function, else `false`. * @example * * _.isFunction(_); * // => true * * _.isFunction(/abc/); * // => false */ function isFunction(value) { if (!isObject(value)) { return false; } // The use of `Object#toString` avoids issues with the `typeof` operator // in Safari 9 which returns 'object' for typed arrays and other constructors. var tag = baseGetTag(value); return tag == funcTag || tag == genTag || tag == asyncTag || tag == proxyTag; } /** * Checks if `value` is an integer. * * **Note:** This method is based on * [`Number.isInteger`](https://mdn.io/Number/isInteger). * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is an integer, else `false`. * @example * * _.isInteger(3); * // => true * * _.isInteger(Number.MIN_VALUE); * // => false * * _.isInteger(Infinity); * // => false * * _.isInteger('3'); * // => false */ function isInteger(value) { return typeof value == 'number' && value == toInteger(value); } /** * Checks if `value` is a valid array-like length. * * **Note:** This method is loosely based on * [`ToLength`](http://ecma-international.org/ecma-262/7.0/#sec-tolength). * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a valid length, else `false`. * @example * * _.isLength(3); * // => true * * _.isLength(Number.MIN_VALUE); * // => false * * _.isLength(Infinity); * // => false * * _.isLength('3'); * // => false */ function isLength(value) { return typeof value == 'number' && value > -1 && value % 1 == 0 && value <= MAX_SAFE_INTEGER; } /** * Checks if `value` is the * [language type](http://www.ecma-international.org/ecma-262/7.0/#sec-ecmascript-language-types) * of `Object`. (e.g. arrays, functions, objects, regexes, `new Number(0)`, and `new String('')`) * * @static * @memberOf _ * @since 0.1.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is an object, else `false`. * @example * * _.isObject({}); * // => true * * _.isObject([1, 2, 3]); * // => true * * _.isObject(_.noop); * // => true * * _.isObject(null); * // => false */ function isObject(value) { var type = typeof value; return value != null && (type == 'object' || type == 'function'); } /** * Checks if `value` is object-like. A value is object-like if it's not `null` * and has a `typeof` result of "object". * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is object-like, else `false`. * @example * * _.isObjectLike({}); * // => true * * _.isObjectLike([1, 2, 3]); * // => true * * _.isObjectLike(_.noop); * // => false * * _.isObjectLike(null); * // => false */ function isObjectLike(value) { return value != null && typeof value == 'object'; } /** * Checks if `value` is classified as a `Map` object. * * @static * @memberOf _ * @since 4.3.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a map, else `false`. * @example * * _.isMap(new Map); * // => true * * _.isMap(new WeakMap); * // => false */ var isMap = nodeIsMap ? baseUnary(nodeIsMap) : baseIsMap; /** * Performs a partial deep comparison between `object` and `source` to * determine if `object` contains equivalent property values. * * **Note:** This method is equivalent to `_.matches` when `source` is * partially applied. * * Partial comparisons will match empty array and empty object `source` * values against any array or object value, respectively. See `_.isEqual` * for a list of supported value comparisons. * * @static * @memberOf _ * @since 3.0.0 * @category Lang * @param {Object} object The object to inspect. * @param {Object} source The object of property values to match. * @returns {boolean} Returns `true` if `object` is a match, else `false`. * @example * * var object = { 'a': 1, 'b': 2 }; * * _.isMatch(object, { 'b': 2 }); * // => true * * _.isMatch(object, { 'b': 1 }); * // => false */ function isMatch(object, source) { return object === source || baseIsMatch(object, source, getMatchData(source)); } /** * This method is like `_.isMatch` except that it accepts `customizer` which * is invoked to compare values. If `customizer` returns `undefined`, comparisons * are handled by the method instead. The `customizer` is invoked with five * arguments: (objValue, srcValue, index|key, object, source). * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {Object} object The object to inspect. * @param {Object} source The object of property values to match. * @param {Function} [customizer] The function to customize comparisons. * @returns {boolean} Returns `true` if `object` is a match, else `false`. * @example * * function isGreeting(value) { * return /^h(?:i|ello)$/.test(value); * } * * function customizer(objValue, srcValue) { * if (isGreeting(objValue) && isGreeting(srcValue)) { * return true; * } * } * * var object = { 'greeting': 'hello' }; * var source = { 'greeting': 'hi' }; * * _.isMatchWith(object, source, customizer); * // => true */ function isMatchWith(object, source, customizer) { customizer = typeof customizer == 'function' ? customizer : undefined; return baseIsMatch(object, source, getMatchData(source), customizer); } /** * Checks if `value` is `NaN`. * * **Note:** This method is based on * [`Number.isNaN`](https://mdn.io/Number/isNaN) and is not the same as * global [`isNaN`](https://mdn.io/isNaN) which returns `true` for * `undefined` and other non-number values. * * @static * @memberOf _ * @since 0.1.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is `NaN`, else `false`. * @example * * _.isNaN(NaN); * // => true * * _.isNaN(new Number(NaN)); * // => true * * isNaN(undefined); * // => true * * _.isNaN(undefined); * // => false */ function isNaN(value) { // An `NaN` primitive is the only value that is not equal to itself. // Perform the `toStringTag` check first to avoid errors with some // ActiveX objects in IE. return isNumber(value) && value != +value; } /** * Checks if `value` is a pristine native function. * * **Note:** This method can't reliably detect native functions in the presence * of the core-js package because core-js circumvents this kind of detection. * Despite multiple requests, the core-js maintainer has made it clear: any * attempt to fix the detection will be obstructed. As a result, we're left * with little choice but to throw an error. Unfortunately, this also affects * packages, like [babel-polyfill](https://www.npmjs.com/package/babel-polyfill), * which rely on core-js. * * @static * @memberOf _ * @since 3.0.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a native function, * else `false`. * @example * * _.isNative(Array.prototype.push); * // => true * * _.isNative(_); * // => false */ function isNative(value) { if (isMaskable(value)) { throw new Error(CORE_ERROR_TEXT); } return baseIsNative(value); } /** * Checks if `value` is `null`. * * @static * @memberOf _ * @since 0.1.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is `null`, else `false`. * @example * * _.isNull(null); * // => true * * _.isNull(void 0); * // => false */ function isNull(value) { return value === null; } /** * Checks if `value` is `null` or `undefined`. * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is nullish, else `false`. * @example * * _.isNil(null); * // => true * * _.isNil(void 0); * // => true * * _.isNil(NaN); * // => false */ function isNil(value) { return value == null; } /** * Checks if `value` is classified as a `Number` primitive or object. * * **Note:** To exclude `Infinity`, `-Infinity`, and `NaN`, which are * classified as numbers, use the `_.isFinite` method. * * @static * @memberOf _ * @since 0.1.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a number, else `false`. * @example * * _.isNumber(3); * // => true * * _.isNumber(Number.MIN_VALUE); * // => true * * _.isNumber(Infinity); * // => true * * _.isNumber('3'); * // => false */ function isNumber(value) { return typeof value == 'number' || (isObjectLike(value) && baseGetTag(value) == numberTag); } /** * Checks if `value` is a plain object, that is, an object created by the * `Object` constructor or one with a `[[Prototype]]` of `null`. * * @static * @memberOf _ * @since 0.8.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a plain object, else `false`. * @example * * function Foo() { * this.a = 1; * } * * _.isPlainObject(new Foo); * // => false * * _.isPlainObject([1, 2, 3]); * // => false * * _.isPlainObject({ 'x': 0, 'y': 0 }); * // => true * * _.isPlainObject(Object.create(null)); * // => true */ function isPlainObject(value) { if (!isObjectLike(value) || baseGetTag(value) != objectTag) { return false; } var proto = getPrototype(value); if (proto === null) { return true; } var Ctor = hasOwnProperty.call(proto, 'constructor') && proto.constructor; return typeof Ctor == 'function' && Ctor instanceof Ctor && funcToString.call(Ctor) == objectCtorString; } /** * Checks if `value` is classified as a `RegExp` object. * * @static * @memberOf _ * @since 0.1.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a regexp, else `false`. * @example * * _.isRegExp(/abc/); * // => true * * _.isRegExp('/abc/'); * // => false */ var isRegExp = nodeIsRegExp ? baseUnary(nodeIsRegExp) : baseIsRegExp; /** * Checks if `value` is a safe integer. An integer is safe if it's an IEEE-754 * double precision number which isn't the result of a rounded unsafe integer. * * **Note:** This method is based on * [`Number.isSafeInteger`](https://mdn.io/Number/isSafeInteger). * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a safe integer, else `false`. * @example * * _.isSafeInteger(3); * // => true * * _.isSafeInteger(Number.MIN_VALUE); * // => false * * _.isSafeInteger(Infinity); * // => false * * _.isSafeInteger('3'); * // => false */ function isSafeInteger(value) { return isInteger(value) && value >= -MAX_SAFE_INTEGER && value <= MAX_SAFE_INTEGER; } /** * Checks if `value` is classified as a `Set` object. * * @static * @memberOf _ * @since 4.3.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a set, else `false`. * @example * * _.isSet(new Set); * // => true * * _.isSet(new WeakSet); * // => false */ var isSet = nodeIsSet ? baseUnary(nodeIsSet) : baseIsSet; /** * Checks if `value` is classified as a `String` primitive or object. * * @static * @since 0.1.0 * @memberOf _ * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a string, else `false`. * @example * * _.isString('abc'); * // => true * * _.isString(1); * // => false */ function isString(value) { return typeof value == 'string' || (!isArray(value) && isObjectLike(value) && baseGetTag(value) == stringTag); } /** * Checks if `value` is classified as a `Symbol` primitive or object. * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a symbol, else `false`. * @example * * _.isSymbol(Symbol.iterator); * // => true * * _.isSymbol('abc'); * // => false */ function isSymbol(value) { return typeof value == 'symbol' || (isObjectLike(value) && baseGetTag(value) == symbolTag); } /** * Checks if `value` is classified as a typed array. * * @static * @memberOf _ * @since 3.0.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a typed array, else `false`. * @example * * _.isTypedArray(new Uint8Array); * // => true * * _.isTypedArray([]); * // => false */ var isTypedArray = nodeIsTypedArray ? baseUnary(nodeIsTypedArray) : baseIsTypedArray; /** * Checks if `value` is `undefined`. * * @static * @since 0.1.0 * @memberOf _ * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is `undefined`, else `false`. * @example * * _.isUndefined(void 0); * // => true * * _.isUndefined(null); * // => false */ function isUndefined(value) { return value === undefined; } /** * Checks if `value` is classified as a `WeakMap` object. * * @static * @memberOf _ * @since 4.3.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a weak map, else `false`. * @example * * _.isWeakMap(new WeakMap); * // => true * * _.isWeakMap(new Map); * // => false */ function isWeakMap(value) { return isObjectLike(value) && getTag(value) == weakMapTag; } /** * Checks if `value` is classified as a `WeakSet` object. * * @static * @memberOf _ * @since 4.3.0 * @category Lang * @param {*} value The value to check. * @returns {boolean} Returns `true` if `value` is a weak set, else `false`. * @example * * _.isWeakSet(new WeakSet); * // => true * * _.isWeakSet(new Set); * // => false */ function isWeakSet(value) { return isObjectLike(value) && baseGetTag(value) == weakSetTag; } /** * Checks if `value` is less than `other`. * * @static * @memberOf _ * @since 3.9.0 * @category Lang * @param {*} value The value to compare. * @param {*} other The other value to compare. * @returns {boolean} Returns `true` if `value` is less than `other`, * else `false`. * @see _.gt * @example * * _.lt(1, 3); * // => true * * _.lt(3, 3); * // => false * * _.lt(3, 1); * // => false */ var lt = createRelationalOperation(baseLt); /** * Checks if `value` is less than or equal to `other`. * * @static * @memberOf _ * @since 3.9.0 * @category Lang * @param {*} value The value to compare. * @param {*} other The other value to compare. * @returns {boolean} Returns `true` if `value` is less than or equal to * `other`, else `false`. * @see _.gte * @example * * _.lte(1, 3); * // => true * * _.lte(3, 3); * // => true * * _.lte(3, 1); * // => false */ var lte = createRelationalOperation(function(value, other) { return value <= other; }); /** * Converts `value` to an array. * * @static * @since 0.1.0 * @memberOf _ * @category Lang * @param {*} value The value to convert. * @returns {Array} Returns the converted array. * @example * * _.toArray({ 'a': 1, 'b': 2 }); * // => [1, 2] * * _.toArray('abc'); * // => ['a', 'b', 'c'] * * _.toArray(1); * // => [] * * _.toArray(null); * // => [] */ function toArray(value) { if (!value) { return []; } if (isArrayLike(value)) { return isString(value) ? stringToArray(value) : copyArray(value); } if (symIterator && value[symIterator]) { return iteratorToArray(value[symIterator]()); } var tag = getTag(value), func = tag == mapTag ? mapToArray : (tag == setTag ? setToArray : values); return func(value); } /** * Converts `value` to a finite number. * * @static * @memberOf _ * @since 4.12.0 * @category Lang * @param {*} value The value to convert. * @returns {number} Returns the converted number. * @example * * _.toFinite(3.2); * // => 3.2 * * _.toFinite(Number.MIN_VALUE); * // => 5e-324 * * _.toFinite(Infinity); * // => 1.7976931348623157e+308 * * _.toFinite('3.2'); * // => 3.2 */ function toFinite(value) { if (!value) { return value === 0 ? value : 0; } value = toNumber(value); if (value === INFINITY || value === -INFINITY) { var sign = (value < 0 ? -1 : 1); return sign * MAX_INTEGER; } return value === value ? value : 0; } /** * Converts `value` to an integer. * * **Note:** This method is loosely based on * [`ToInteger`](http://www.ecma-international.org/ecma-262/7.0/#sec-tointeger). * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to convert. * @returns {number} Returns the converted integer. * @example * * _.toInteger(3.2); * // => 3 * * _.toInteger(Number.MIN_VALUE); * // => 0 * * _.toInteger(Infinity); * // => 1.7976931348623157e+308 * * _.toInteger('3.2'); * // => 3 */ function toInteger(value) { var result = toFinite(value), remainder = result % 1; return result === result ? (remainder ? result - remainder : result) : 0; } /** * Converts `value` to an integer suitable for use as the length of an * array-like object. * * **Note:** This method is based on * [`ToLength`](http://ecma-international.org/ecma-262/7.0/#sec-tolength). * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to convert. * @returns {number} Returns the converted integer. * @example * * _.toLength(3.2); * // => 3 * * _.toLength(Number.MIN_VALUE); * // => 0 * * _.toLength(Infinity); * // => 4294967295 * * _.toLength('3.2'); * // => 3 */ function toLength(value) { return value ? baseClamp(toInteger(value), 0, MAX_ARRAY_LENGTH) : 0; } /** * Converts `value` to a number. * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to process. * @returns {number} Returns the number. * @example * * _.toNumber(3.2); * // => 3.2 * * _.toNumber(Number.MIN_VALUE); * // => 5e-324 * * _.toNumber(Infinity); * // => Infinity * * _.toNumber('3.2'); * // => 3.2 */ function toNumber(value) { if (typeof value == 'number') { return value; } if (isSymbol(value)) { return NAN; } if (isObject(value)) { var other = typeof value.valueOf == 'function' ? value.valueOf() : value; value = isObject(other) ? (other + '') : other; } if (typeof value != 'string') { return value === 0 ? value : +value; } value = value.replace(reTrim, ''); var isBinary = reIsBinary.test(value); return (isBinary || reIsOctal.test(value)) ? freeParseInt(value.slice(2), isBinary ? 2 : 8) : (reIsBadHex.test(value) ? NAN : +value); } /** * Converts `value` to a plain object flattening inherited enumerable string * keyed properties of `value` to own properties of the plain object. * * @static * @memberOf _ * @since 3.0.0 * @category Lang * @param {*} value The value to convert. * @returns {Object} Returns the converted plain object. * @example * * function Foo() { * this.b = 2; * } * * Foo.prototype.c = 3; * * _.assign({ 'a': 1 }, new Foo); * // => { 'a': 1, 'b': 2 } * * _.assign({ 'a': 1 }, _.toPlainObject(new Foo)); * // => { 'a': 1, 'b': 2, 'c': 3 } */ function toPlainObject(value) { return copyObject(value, keysIn(value)); } /** * Converts `value` to a safe integer. A safe integer can be compared and * represented correctly. * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to convert. * @returns {number} Returns the converted integer. * @example * * _.toSafeInteger(3.2); * // => 3 * * _.toSafeInteger(Number.MIN_VALUE); * // => 0 * * _.toSafeInteger(Infinity); * // => 9007199254740991 * * _.toSafeInteger('3.2'); * // => 3 */ function toSafeInteger(value) { return value ? baseClamp(toInteger(value), -MAX_SAFE_INTEGER, MAX_SAFE_INTEGER) : (value === 0 ? value : 0); } /** * Converts `value` to a string. An empty string is returned for `null` * and `undefined` values. The sign of `-0` is preserved. * * @static * @memberOf _ * @since 4.0.0 * @category Lang * @param {*} value The value to convert. * @returns {string} Returns the converted string. * @example * * _.toString(null); * // => '' * * _.toString(-0); * // => '-0' * * _.toString([1, 2, 3]); * // => '1,2,3' */ function toString(value) { return value == null ? '' : baseToString(value); } /*------------------------------------------------------------------------*/ /** * Assigns own enumerable string keyed properties of source objects to the * destination object. Source objects are applied from left to right. * Subsequent sources overwrite property assignments of previous sources. * * **Note:** This method mutates `object` and is loosely based on * [`Object.assign`](https://mdn.io/Object/assign). * * @static * @memberOf _ * @since 0.10.0 * @category Object * @param {Object} object The destination object. * @param {...Object} [sources] The source objects. * @returns {Object} Returns `object`. * @see _.assignIn * @example * * function Foo() { * this.a = 1; * } * * function Bar() { * this.c = 3; * } * * Foo.prototype.b = 2; * Bar.prototype.d = 4; * * _.assign({ 'a': 0 }, new Foo, new Bar); * // => { 'a': 1, 'c': 3 } */ var assign = createAssigner(function(object, source) { if (isPrototype(source) || isArrayLike(source)) { copyObject(source, keys(source), object); return; } for (var key in source) { if (hasOwnProperty.call(source, key)) { assignValue(object, key, source[key]); } } }); /** * This method is like `_.assign` except that it iterates over own and * inherited source properties. * * **Note:** This method mutates `object`. * * @static * @memberOf _ * @since 4.0.0 * @alias extend * @category Object * @param {Object} object The destination object. * @param {...Object} [sources] The source objects. * @returns {Object} Returns `object`. * @see _.assign * @example * * function Foo() { * this.a = 1; * } * * function Bar() { * this.c = 3; * } * * Foo.prototype.b = 2; * Bar.prototype.d = 4; * * _.assignIn({ 'a': 0 }, new Foo, new Bar); * // => { 'a': 1, 'b': 2, 'c': 3, 'd': 4 } */ var assignIn = createAssigner(function(object, source) { copyObject(source, keysIn(source), object); }); /** * This method is like `_.assignIn` except that it accepts `customizer` * which is invoked to produce the assigned values. If `customizer` returns * `undefined`, assignment is handled by the method instead. The `customizer` * is invoked with five arguments: (objValue, srcValue, key, object, source). * * **Note:** This method mutates `object`. * * @static * @memberOf _ * @since 4.0.0 * @alias extendWith * @category Object * @param {Object} object The destination object. * @param {...Object} sources The source objects. * @param {Function} [customizer] The function to customize assigned values. * @returns {Object} Returns `object`. * @see _.assignWith * @example * * function customizer(objValue, srcValue) { * return _.isUndefined(objValue) ? srcValue : objValue; * } * * var defaults = _.partialRight(_.assignInWith, customizer); * * defaults({ 'a': 1 }, { 'b': 2 }, { 'a': 3 }); * // => { 'a': 1, 'b': 2 } */ var assignInWith = createAssigner(function(object, source, srcIndex, customizer) { copyObject(source, keysIn(source), object, customizer); }); /** * This method is like `_.assign` except that it accepts `customizer` * which is invoked to produce the assigned values. If `customizer` returns * `undefined`, assignment is handled by the method instead. The `customizer` * is invoked with five arguments: (objValue, srcValue, key, object, source). * * **Note:** This method mutates `object`. * * @static * @memberOf _ * @since 4.0.0 * @category Object * @param {Object} object The destination object. * @param {...Object} sources The source objects. * @param {Function} [customizer] The function to customize assigned values. * @returns {Object} Returns `object`. * @see _.assignInWith * @example * * function customizer(objValue, srcValue) { * return _.isUndefined(objValue) ? srcValue : objValue; * } * * var defaults = _.partialRight(_.assignWith, customizer); * * defaults({ 'a': 1 }, { 'b': 2 }, { 'a': 3 }); * // => { 'a': 1, 'b': 2 } */ var assignWith = createAssigner(function(object, source, srcIndex, customizer) { copyObject(source, keys(source), object, customizer); }); /** * Creates an array of values corresponding to `paths` of `object`. * * @static * @memberOf _ * @since 1.0.0 * @category Object * @param {Object} object The object to iterate over. * @param {...(string|string[])} [paths] The property paths to pick. * @returns {Array} Returns the picked values. * @example * * var object = { 'a': [{ 'b': { 'c': 3 } }, 4] }; * * _.at(object, ['a[0].b.c', 'a[1]']); * // => [3, 4] */ var at = flatRest(baseAt); /** * Creates an object that inherits from the `prototype` object. If a * `properties` object is given, its own enumerable string keyed properties * are assigned to the created object. * * @static * @memberOf _ * @since 2.3.0 * @category Object * @param {Object} prototype The object to inherit from. * @param {Object} [properties] The properties to assign to the object. * @returns {Object} Returns the new object. * @example * * function Shape() { * this.x = 0; * this.y = 0; * } * * function Circle() { * Shape.call(this); * } * * Circle.prototype = _.create(Shape.prototype, { * 'constructor': Circle * }); * * var circle = new Circle; * circle instanceof Circle; * // => true * * circle instanceof Shape; * // => true */ function create(prototype, properties) { var result = baseCreate(prototype); return properties == null ? result : baseAssign(result, properties); } /** * Assigns own and inherited enumerable string keyed properties of source * objects to the destination object for all destination properties that * resolve to `undefined`. Source objects are applied from left to right. * Once a property is set, additional values of the same property are ignored. * * **Note:** This method mutates `object`. * * @static * @since 0.1.0 * @memberOf _ * @category Object * @param {Object} object The destination object. * @param {...Object} [sources] The source objects. * @returns {Object} Returns `object`. * @see _.defaultsDeep * @example * * _.defaults({ 'a': 1 }, { 'b': 2 }, { 'a': 3 }); * // => { 'a': 1, 'b': 2 } */ var defaults = baseRest(function(object, sources) { object = Object(object); var index = -1; var length = sources.length; var guard = length > 2 ? sources[2] : undefined; if (guard && isIterateeCall(sources[0], sources[1], guard)) { length = 1; } while (++index < length) { var source = sources[index]; var props = keysIn(source); var propsIndex = -1; var propsLength = props.length; while (++propsIndex < propsLength) { var key = props[propsIndex]; var value = object[key]; if (value === undefined || (eq(value, objectProto[key]) && !hasOwnProperty.call(object, key))) { object[key] = source[key]; } } } return object; }); /** * This method is like `_.defaults` except that it recursively assigns * default properties. * * **Note:** This method mutates `object`. * * @static * @memberOf _ * @since 3.10.0 * @category Object * @param {Object} object The destination object. * @param {...Object} [sources] The source objects. * @returns {Object} Returns `object`. * @see _.defaults * @example * * _.defaultsDeep({ 'a': { 'b': 2 } }, { 'a': { 'b': 1, 'c': 3 } }); * // => { 'a': { 'b': 2, 'c': 3 } } */ var defaultsDeep = baseRest(function(args) { args.push(undefined, customDefaultsMerge); return apply(mergeWith, undefined, args); }); /** * This method is like `_.find` except that it returns the key of the first * element `predicate` returns truthy for instead of the element itself. * * @static * @memberOf _ * @since 1.1.0 * @category Object * @param {Object} object The object to inspect. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @returns {string|undefined} Returns the key of the matched element, * else `undefined`. * @example * * var users = { * 'barney': { 'age': 36, 'active': true }, * 'fred': { 'age': 40, 'active': false }, * 'pebbles': { 'age': 1, 'active': true } * }; * * _.findKey(users, function(o) { return o.age < 40; }); * // => 'barney' (iteration order is not guaranteed) * * // The `_.matches` iteratee shorthand. * _.findKey(users, { 'age': 1, 'active': true }); * // => 'pebbles' * * // The `_.matchesProperty` iteratee shorthand. * _.findKey(users, ['active', false]); * // => 'fred' * * // The `_.property` iteratee shorthand. * _.findKey(users, 'active'); * // => 'barney' */ function findKey(object, predicate) { return baseFindKey(object, getIteratee(predicate, 3), baseForOwn); } /** * This method is like `_.findKey` except that it iterates over elements of * a collection in the opposite order. * * @static * @memberOf _ * @since 2.0.0 * @category Object * @param {Object} object The object to inspect. * @param {Function} [predicate=_.identity] The function invoked per iteration. * @returns {string|undefined} Returns the key of the matched element, * else `undefined`. * @example * * var users = { * 'barney': { 'age': 36, 'active': true }, * 'fred': { 'age': 40, 'active': false }, * 'pebbles': { 'age': 1, 'active': true } * }; * * _.findLastKey(users, function(o) { return o.age < 40; }); * // => returns 'pebbles' assuming `_.findKey` returns 'barney' * * // The `_.matches` iteratee shorthand. * _.findLastKey(users, { 'age': 36, 'active': true }); * // => 'barney' * * // The `_.matchesProperty` iteratee shorthand. * _.findLastKey(users, ['active', false]); * // => 'fred' * * // The `_.property` iteratee shorthand. * _.findLastKey(users, 'active'); * // => 'pebbles' */ function findLastKey(object, predicate) { return baseFindKey(object, getIteratee(predicate, 3), baseForOwnRight); } /** * Iterates over own and inherited enumerable string keyed properties of an * object and invokes `iteratee` for each property. The iteratee is invoked * with three arguments: (value, key, object). Iteratee functions may exit * iteration early by explicitly returning `false`. * * @static * @memberOf _ * @since 0.3.0 * @category Object * @param {Object} object The object to iterate over. * @param {Function} [iteratee=_.identity] The function invoked per iteration. * @returns {Object} Returns `object`. * @see _.forInRight * @example * * function Foo() { * this.a = 1; * this.b = 2; * } * * Foo.prototype.c = 3; * * _.forIn(new Foo, function(value, key) { * console.log(key); * }); * // => Logs 'a', 'b', then 'c' (iteration order is not guaranteed). */ function forIn(object, iteratee) { return object == null ? object : baseFor(object, getIteratee(iteratee, 3), keysIn); } /** * This method is like `_.forIn` except that it iterates over properties of * `object` in the opposite order. * * @static * @memberOf _ * @since 2.0.0 * @category Object * @param {Object} object The object to iterate over. * @param {Function} [iteratee=_.identity] The function invoked per iteration. * @returns {Object} Returns `object`. * @see _.forIn * @example * * function Foo() { * this.a = 1; * this.b = 2; * } * * Foo.prototype.c = 3; * * _.forInRight(new Foo, function(value, key) { * console.log(key); * }); * // => Logs 'c', 'b', then 'a' assuming `_.forIn` logs 'a', 'b', then 'c'. */ function forInRight(object, iteratee) { return object == null ? object : baseForRight(object, getIteratee(iteratee, 3), keysIn); } /** * Iterates over own enumerable string keyed properties of an object and * invokes `iteratee` for each property. The iteratee is invoked with three * arguments: (value, key, object). Iteratee functions may exit iteration * early by explicitly returning `false`. * * @static * @memberOf _ * @since 0.3.0 * @category Object * @param {Object} object The object to iterate over. * @param {Function} [iteratee=_.identity] The function invoked per iteration. * @returns {Object} Returns `object`. * @see _.forOwnRight * @example * * function Foo() { * this.a = 1; * this.b = 2; * } * * Foo.prototype.c = 3; * * _.forOwn(new Foo, function(value, key) { * console.log(key); * }); * // => Logs 'a' then 'b' (iteration order is not guaranteed). */ function forOwn(object, iteratee) { return object && baseForOwn(object, getIteratee(iteratee, 3)); } /** * This method is like `_.forOwn` except that it iterates over properties of * `object` in the opposite order. * * @static * @memberOf _ * @since 2.0.0 * @category Object * @param {Object} object The object to iterate over. * @param {Function} [iteratee=_.identity] The function invoked per iteration. * @returns {Object} Returns `object`. * @see _.forOwn * @example * * function Foo() { * this.a = 1; * this.b = 2; * } * * Foo.prototype.c = 3; * * _.forOwnRight(new Foo, function(value, key) { * console.log(key); * }); * // => Logs 'b' then 'a' assuming `_.forOwn` logs 'a' then 'b'. */ function forOwnRight(object, iteratee) { return object && baseForOwnRight(object, getIteratee(iteratee, 3)); } /** * Creates an array of function property names from own enumerable properties * of `object`. * * @static * @since 0.1.0 * @memberOf _ * @category Object * @param {Object} object The object to inspect. * @returns {Array} Returns the function names. * @see _.functionsIn * @example * * function Foo() { * this.a = _.constant('a'); * this.b = _.constant('b'); * } * * Foo.prototype.c = _.constant('c'); * * _.functions(new Foo); * // => ['a', 'b'] */ function functions(object) { return object == null ? [] : baseFunctions(object, keys(object)); } /** * Creates an array of function property names from own and inherited * enumerable properties of `object`. * * @static * @memberOf _ * @since 4.0.0 * @category Object * @param {Object} object The object to inspect. * @returns {Array} Returns the function names. * @see _.functions * @example * * function Foo() { * this.a = _.constant('a'); * this.b = _.constant('b'); * } * * Foo.prototype.c = _.constant('c'); * * _.functionsIn(new Foo); * // => ['a', 'b', 'c'] */ function functionsIn(object) { return object == null ? [] : baseFunctions(object, keysIn(object)); } /** * Gets the value at `path` of `object`. If the resolved value is * `undefined`, the `defaultValue` is returned in its place. * * @static * @memberOf _ * @since 3.7.0 * @category Object * @param {Object} object The object to query. * @param {Array|string} path The path of the property to get. * @param {*} [defaultValue] The value returned for `undefined` resolved values. * @returns {*} Returns the resolved value. * @example * * var object = { 'a': [{ 'b': { 'c': 3 } }] }; * * _.get(object, 'a[0].b.c'); * // => 3 * * _.get(object, ['a', '0', 'b', 'c']); * // => 3 * * _.get(object, 'a.b.c', 'default'); * // => 'default' */ function get(object, path, defaultValue) { var result = object == null ? undefined : baseGet(object, path); return result === undefined ? defaultValue : result; } /** * Checks if `path` is a direct property of `object`. * * @static * @since 0.1.0 * @memberOf _ * @category Object * @param {Object} object The object to query. * @param {Array|string} path The path to check. * @returns {boolean} Returns `true` if `path` exists, else `false`. * @example * * var object = { 'a': { 'b': 2 } }; * var other = _.create({ 'a': _.create({ 'b': 2 }) }); * * _.has(object, 'a'); * // => true * * _.has(object, 'a.b'); * // => true * * _.has(object, ['a', 'b']); * // => true * * _.has(other, 'a'); * // => false */ function has(object, path) { return object != null && hasPath(object, path, baseHas); } /** * Checks if `path` is a direct or inherited property of `object`. * * @static * @memberOf _ * @since 4.0.0 * @category Object * @param {Object} object The object to query. * @param {Array|string} path The path to check. * @returns {boolean} Returns `true` if `path` exists, else `false`. * @example * * var object = _.create({ 'a': _.create({ 'b': 2 }) }); * * _.hasIn(object, 'a'); * // => true * * _.hasIn(object, 'a.b'); * // => true * * _.hasIn(object, ['a', 'b']); * // => true * * _.hasIn(object, 'b'); * // => false */ function hasIn(object, path) { return object != null && hasPath(object, path, baseHasIn); } /** * Creates an object composed of the inverted keys and values of `object`. * If `object` contains duplicate values, subsequent values overwrite * property assignments of previous values. * * @static * @memberOf _ * @since 0.7.0 * @category Object * @param {Object} object The object to invert. * @returns {Object} Returns the new inverted object. * @example * * var object = { 'a': 1, 'b': 2, 'c': 1 }; * * _.invert(object); * // => { '1': 'c', '2': 'b' } */ var invert = createInverter(function(result, value, key) { if (value != null && typeof value.toString != 'function') { value = nativeObjectToString.call(value); } result[value] = key; }, constant(identity)); /** * This method is like `_.invert` except that the inverted object is generated * from the results of running each element of `object` thru `iteratee`. The * corresponding inverted value of each inverted key is an array of keys * responsible for generating the inverted value. The iteratee is invoked * with one argument: (value). * * @static * @memberOf _ * @since 4.1.0 * @category Object * @param {Object} object The object to invert. * @param {Function} [iteratee=_.identity] The iteratee invoked per element. * @returns {Object} Returns the new inverted object. * @example * * var object = { 'a': 1, 'b': 2, 'c': 1 }; * * _.invertBy(object); * // => { '1': ['a', 'c'], '2': ['b'] } * * _.invertBy(object, function(value) { * return 'group' + value; * }); * // => { 'group1': ['a', 'c'], 'group2': ['b'] } */ var invertBy = createInverter(function(result, value, key) { if (value != null && typeof value.toString != 'function') { value = nativeObjectToString.call(value); } if (hasOwnProperty.call(result, value)) { result[value].push(key); } else { result[value] = [key]; } }, getIteratee); /** * Invokes the method at `path` of `object`. * * @static * @memberOf _ * @since 4.0.0 * @category Object * @param {Object} object The object to query. * @param {Array|string} path The path of the method to invoke. * @param {...*} [args] The arguments to invoke the method with. * @returns {*} Returns the result of the invoked method. * @example * * var object = { 'a': [{ 'b': { 'c': [1, 2, 3, 4] } }] }; * * _.invoke(object, 'a[0].b.c.slice', 1, 3); * // => [2, 3] */ var invoke = baseRest(baseInvoke); /** * Creates an array of the own enumerable property names of `object`. * * **Note:** Non-object values are coerced to objects. See the * [ES spec](http://ecma-international.org/ecma-262/7.0/#sec-object.keys) * for more details. * * @static * @since 0.1.0 * @memberOf _ * @category Object * @param {Object} object The object to query. * @returns {Array} Returns the array of property names. * @example * * function Foo() { * this.a = 1; * this.b = 2; * } * * Foo.prototype.c = 3; * * _.keys(new Foo); * // => ['a', 'b'] (iteration order is not guaranteed) * * _.keys('hi'); * // => ['0', '1'] */ function keys(object) { return isArrayLike(object) ? arrayLikeKeys(object) : baseKeys(object); } /** * Creates an array of the own and inherited enumerable property names of `object`. * * **Note:** Non-object values are coerced to objects. * * @static * @memberOf _ * @since 3.0.0 * @category Object * @param {Object} object The object to query. * @returns {Array} Returns the array of property names. * @example * * function Foo() { * this.a = 1; * this.b = 2; * } * * Foo.prototype.c = 3; * * _.keysIn(new Foo); * // => ['a', 'b', 'c'] (iteration order is not guaranteed) */ function keysIn(object) { return isArrayLike(object) ? arrayLikeKeys(object, true) : baseKeysIn(object); } /** * The opposite of `_.mapValues`; this method creates an object with the * same values as `object` and keys generated by running each own enumerable * string keyed property of `object` thru `iteratee`. The iteratee is invoked * with three arguments: (value, key, object). * * @static * @memberOf _ * @since 3.8.0 * @category Object * @param {Object} object The object to iterate over. * @param {Function} [iteratee=_.identity] The function invoked per iteration. * @returns {Object} Returns the new mapped object. * @see _.mapValues * @example * * _.mapKeys({ 'a': 1, 'b': 2 }, function(value, key) { * return key + value; * }); * // => { 'a1': 1, 'b2': 2 } */ function mapKeys(object, iteratee) { var result = {}; iteratee = getIteratee(iteratee, 3); baseForOwn(object, function(value, key, object) { baseAssignValue(result, iteratee(value, key, object), value); }); return result; } /** * Creates an object with the same keys as `object` and values generated * by running each own enumerable string keyed property of `object` thru * `iteratee`. The iteratee is invoked with three arguments: * (value, key, object). * * @static * @memberOf _ * @since 2.4.0 * @category Object * @param {Object} object The object to iterate over. * @param {Function} [iteratee=_.identity] The function invoked per iteration. * @returns {Object} Returns the new mapped object. * @see _.mapKeys * @example * * var users = { * 'fred': { 'user': 'fred', 'age': 40 }, * 'pebbles': { 'user': 'pebbles', 'age': 1 } * }; * * _.mapValues(users, function(o) { return o.age; }); * // => { 'fred': 40, 'pebbles': 1 } (iteration order is not guaranteed) * * // The `_.property` iteratee shorthand. * _.mapValues(users, 'age'); * // => { 'fred': 40, 'pebbles': 1 } (iteration order is not guaranteed) */ function mapValues(object, iteratee) { var result = {}; iteratee = getIteratee(iteratee, 3); baseForOwn(object, function(value, key, object) { baseAssignValue(result, key, iteratee(value, key, object)); }); return result; } /** * This method is like `_.assign` except that it recursively merges own and * inherited enumerable string keyed properties of source objects into the * destination object. Source properties that resolve to `undefined` are * skipped if a destination value exists. Array and plain object properties * are merged recursively. Other objects and value types are overridden by * assignment. Source objects are applied from left to right. Subsequent * sources overwrite property assignments of previous sources. * * **Note:** This method mutates `object`. * * @static * @memberOf _ * @since 0.5.0 * @category Object * @param {Object} object The destination object. * @param {...Object} [sources] The source objects. * @returns {Object} Returns `object`. * @example * * var object = { * 'a': [{ 'b': 2 }, { 'd': 4 }] * }; * * var other = { * 'a': [{ 'c': 3 }, { 'e': 5 }] * }; * * _.merge(object, other); * // => { 'a': [{ 'b': 2, 'c': 3 }, { 'd': 4, 'e': 5 }] } */ var merge = createAssigner(function(object, source, srcIndex) { baseMerge(object, source, srcIndex); }); /** * This method is like `_.merge` except that it accepts `customizer` which * is invoked to produce the merged values of the destination and source * properties. If `customizer` returns `undefined`, merging is handled by the * method instead. The `customizer` is invoked with six arguments: * (objValue, srcValue, key, object, source, stack). * * **Note:** This method mutates `object`. * * @static * @memberOf _ * @since 4.0.0 * @category Object * @param {Object} object The destination object. * @param {...Object} sources The source objects. * @param {Function} customizer The function to customize assigned values. * @returns {Object} Returns `object`. * @example * * function customizer(objValue, srcValue) { * if (_.isArray(objValue)) { * return objValue.concat(srcValue); * } * } * * var object = { 'a': [1], 'b': [2] }; * var other = { 'a': [3], 'b': [4] }; * * _.mergeWith(object, other, customizer); * // => { 'a': [1, 3], 'b': [2, 4] } */ var mergeWith = createAssigner(function(object, source, srcIndex, customizer) { baseMerge(object, source, srcIndex, customizer); }); /** * The opposite of `_.pick`; this method creates an object composed of the * own and inherited enumerable property paths of `object` that are not omitted. * * **Note:** This method is considerably slower than `_.pick`. * * @static * @since 0.1.0 * @memberOf _ * @category Object * @param {Object} object The source object. * @param {...(string|string[])} [paths] The property paths to omit. * @returns {Object} Returns the new object. * @example * * var object = { 'a': 1, 'b': '2', 'c': 3 }; * * _.omit(object, ['a', 'c']); * // => { 'b': '2' } */ var omit = flatRest(function(object, paths) { var result = {}; if (object == null) { return result; } var isDeep = false; paths = arrayMap(paths, function(path) { path = castPath(path, object); isDeep || (isDeep = path.length > 1); return path; }); copyObject(object, getAllKeysIn(object), result); if (isDeep) { result = baseClone(result, CLONE_DEEP_FLAG | CLONE_FLAT_FLAG | CLONE_SYMBOLS_FLAG, customOmitClone); } var length = paths.length; while (length--) { baseUnset(result, paths[length]); } return result; }); /** * The opposite of `_.pickBy`; this method creates an object composed of * the own and inherited enumerable string keyed properties of `object` that * `predicate` doesn't return truthy for. The predicate is invoked with two * arguments: (value, key). * * @static * @memberOf _ * @since 4.0.0 * @category Object * @param {Object} object The source object. * @param {Function} [predicate=_.identity] The function invoked per property. * @returns {Object} Returns the new object. * @example * * var object = { 'a': 1, 'b': '2', 'c': 3 }; * * _.omitBy(object, _.isNumber); * // => { 'b': '2' } */ function omitBy(object, predicate) { return pickBy(object, negate(getIteratee(predicate))); } /** * Creates an object composed of the picked `object` properties. * * @static * @since 0.1.0 * @memberOf _ * @category Object * @param {Object} object The source object. * @param {...(string|string[])} [paths] The property paths to pick. * @returns {Object} Returns the new object. * @example * * var object = { 'a': 1, 'b': '2', 'c': 3 }; * * _.pick(object, ['a', 'c']); * // => { 'a': 1, 'c': 3 } */ var pick = flatRest(function(object, paths) { return object == null ? {} : basePick(object, paths); }); /** * Creates an object composed of the `object` properties `predicate` returns * truthy for. The predicate is invoked with two arguments: (value, key). * * @static * @memberOf _ * @since 4.0.0 * @category Object * @param {Object} object The source object. * @param {Function} [predicate=_.identity] The function invoked per property. * @returns {Object} Returns the new object. * @example * * var object = { 'a': 1, 'b': '2', 'c': 3 }; * * _.pickBy(object, _.isNumber); * // => { 'a': 1, 'c': 3 } */ function pickBy(object, predicate) { if (object == null) { return {}; } var props = arrayMap(getAllKeysIn(object), function(prop) { return [prop]; }); predicate = getIteratee(predicate); return basePickBy(object, props, function(value, path) { return predicate(value, path[0]); }); } /** * This method is like `_.get` except that if the resolved value is a * function it's invoked with the `this` binding of its parent object and * its result is returned. * * @static * @since 0.1.0 * @memberOf _ * @category Object * @param {Object} object The object to query. * @param {Array|string} path The path of the property to resolve. * @param {*} [defaultValue] The value returned for `undefined` resolved values. * @returns {*} Returns the resolved value. * @example * * var object = { 'a': [{ 'b': { 'c1': 3, 'c2': _.constant(4) } }] }; * * _.result(object, 'a[0].b.c1'); * // => 3 * * _.result(object, 'a[0].b.c2'); * // => 4 * * _.result(object, 'a[0].b.c3', 'default'); * // => 'default' * * _.result(object, 'a[0].b.c3', _.constant('default')); * // => 'default' */ function result(object, path, defaultValue) { path = castPath(path, object); var index = -1, length = path.length; // Ensure the loop is entered when path is empty. if (!length) { length = 1; object = undefined; } while (++index < length) { var value = object == null ? undefined : object[toKey(path[index])]; if (value === undefined) { index = length; value = defaultValue; } object = isFunction(value) ? value.call(object) : value; } return object; } /** * Sets the value at `path` of `object`. If a portion of `path` doesn't exist, * it's created. Arrays are created for missing index properties while objects * are created for all other missing properties. Use `_.setWith` to customize * `path` creation. * * **Note:** This method mutates `object`. * * @static * @memberOf _ * @since 3.7.0 * @category Object * @param {Object} object The object to modify. * @param {Array|string} path The path of the property to set. * @param {*} value The value to set. * @returns {Object} Returns `object`. * @example * * var object = { 'a': [{ 'b': { 'c': 3 } }] }; * * _.set(object, 'a[0].b.c', 4); * console.log(object.a[0].b.c); * // => 4 * * _.set(object, ['x', '0', 'y', 'z'], 5); * console.log(object.x[0].y.z); * // => 5 */ function set(object, path, value) { return object == null ? object : baseSet(object, path, value); } /** * This method is like `_.set` except that it accepts `customizer` which is * invoked to produce the objects of `path`. If `customizer` returns `undefined` * path creation is handled by the method instead. The `customizer` is invoked * with three arguments: (nsValue, key, nsObject). * * **Note:** This method mutates `object`. * * @static * @memberOf _ * @since 4.0.0 * @category Object * @param {Object} object The object to modify. * @param {Array|string} path The path of the property to set. * @param {*} value The value to set. * @param {Function} [customizer] The function to customize assigned values. * @returns {Object} Returns `object`. * @example * * var object = {}; * * _.setWith(object, '[0][1]', 'a', Object); * // => { '0': { '1': 'a' } } */ function setWith(object, path, value, customizer) { customizer = typeof customizer == 'function' ? customizer : undefined; return object == null ? object : baseSet(object, path, value, customizer); } /** * Creates an array of own enumerable string keyed-value pairs for `object` * which can be consumed by `_.fromPairs`. If `object` is a map or set, its * entries are returned. * * @static * @memberOf _ * @since 4.0.0 * @alias entries * @category Object * @param {Object} object The object to query. * @returns {Array} Returns the key-value pairs. * @example * * function Foo() { * this.a = 1; * this.b = 2; * } * * Foo.prototype.c = 3; * * _.toPairs(new Foo); * // => [['a', 1], ['b', 2]] (iteration order is not guaranteed) */ var toPairs = createToPairs(keys); /** * Creates an array of own and inherited enumerable string keyed-value pairs * for `object` which can be consumed by `_.fromPairs`. If `object` is a map * or set, its entries are returned. * * @static * @memberOf _ * @since 4.0.0 * @alias entriesIn * @category Object * @param {Object} object The object to query. * @returns {Array} Returns the key-value pairs. * @example * * function Foo() { * this.a = 1; * this.b = 2; * } * * Foo.prototype.c = 3; * * _.toPairsIn(new Foo); * // => [['a', 1], ['b', 2], ['c', 3]] (iteration order is not guaranteed) */ var toPairsIn = createToPairs(keysIn); /** * An alternative to `_.reduce`; this method transforms `object` to a new * `accumulator` object which is the result of running each of its own * enumerable string keyed properties thru `iteratee`, with each invocation * potentially mutating the `accumulator` object. If `accumulator` is not * provided, a new object with the same `[[Prototype]]` will be used. The * iteratee is invoked with four arguments: (accumulator, value, key, object). * Iteratee functions may exit iteration early by explicitly returning `false`. * * @static * @memberOf _ * @since 1.3.0 * @category Object * @param {Object} object The object to iterate over. * @param {Function} [iteratee=_.identity] The function invoked per iteration. * @param {*} [accumulator] The custom accumulator value. * @returns {*} Returns the accumulated value. * @example * * _.transform([2, 3, 4], function(result, n) { * result.push(n *= n); * return n % 2 == 0; * }, []); * // => [4, 9] * * _.transform({ 'a': 1, 'b': 2, 'c': 1 }, function(result, value, key) { * (result[value] || (result[value] = [])).push(key); * }, {}); * // => { '1': ['a', 'c'], '2': ['b'] } */ function transform(object, iteratee, accumulator) { var isArr = isArray(object), isArrLike = isArr || isBuffer(object) || isTypedArray(object); iteratee = getIteratee(iteratee, 4); if (accumulator == null) { var Ctor = object && object.constructor; if (isArrLike) { accumulator = isArr ? new Ctor : []; } else if (isObject(object)) { accumulator = isFunction(Ctor) ? baseCreate(getPrototype(object)) : {}; } else { accumulator = {}; } } (isArrLike ? arrayEach : baseForOwn)(object, function(value, index, object) { return iteratee(accumulator, value, index, object); }); return accumulator; } /** * Removes the property at `path` of `object`. * * **Note:** This method mutates `object`. * * @static * @memberOf _ * @since 4.0.0 * @category Object * @param {Object} object The object to modify. * @param {Array|string} path The path of the property to unset. * @returns {boolean} Returns `true` if the property is deleted, else `false`. * @example * * var object = { 'a': [{ 'b': { 'c': 7 } }] }; * _.unset(object, 'a[0].b.c'); * // => true * * console.log(object); * // => { 'a': [{ 'b': {} }] }; * * _.unset(object, ['a', '0', 'b', 'c']); * // => true * * console.log(object); * // => { 'a': [{ 'b': {} }] }; */ function unset(object, path) { return object == null ? true : baseUnset(object, path); } /** * This method is like `_.set` except that accepts `updater` to produce the * value to set. Use `_.updateWith` to customize `path` creation. The `updater` * is invoked with one argument: (value). * * **Note:** This method mutates `object`. * * @static * @memberOf _ * @since 4.6.0 * @category Object * @param {Object} object The object to modify. * @param {Array|string} path The path of the property to set. * @param {Function} updater The function to produce the updated value. * @returns {Object} Returns `object`. * @example * * var object = { 'a': [{ 'b': { 'c': 3 } }] }; * * _.update(object, 'a[0].b.c', function(n) { return n * n; }); * console.log(object.a[0].b.c); * // => 9 * * _.update(object, 'x[0].y.z', function(n) { return n ? n + 1 : 0; }); * console.log(object.x[0].y.z); * // => 0 */ function update(object, path, updater) { return object == null ? object : baseUpdate(object, path, castFunction(updater)); } /** * This method is like `_.update` except that it accepts `customizer` which is * invoked to produce the objects of `path`. If `customizer` returns `undefined` * path creation is handled by the method instead. The `customizer` is invoked * with three arguments: (nsValue, key, nsObject). * * **Note:** This method mutates `object`. * * @static * @memberOf _ * @since 4.6.0 * @category Object * @param {Object} object The object to modify. * @param {Array|string} path The path of the property to set. * @param {Function} updater The function to produce the updated value. * @param {Function} [customizer] The function to customize assigned values. * @returns {Object} Returns `object`. * @example * * var object = {}; * * _.updateWith(object, '[0][1]', _.constant('a'), Object); * // => { '0': { '1': 'a' } } */ function updateWith(object, path, updater, customizer) { customizer = typeof customizer == 'function' ? customizer : undefined; return object == null ? object : baseUpdate(object, path, castFunction(updater), customizer); } /** * Creates an array of the own enumerable string keyed property values of `object`. * * **Note:** Non-object values are coerced to objects. * * @static * @since 0.1.0 * @memberOf _ * @category Object * @param {Object} object The object to query. * @returns {Array} Returns the array of property values. * @example * * function Foo() { * this.a = 1; * this.b = 2; * } * * Foo.prototype.c = 3; * * _.values(new Foo); * // => [1, 2] (iteration order is not guaranteed) * * _.values('hi'); * // => ['h', 'i'] */ function values(object) { return object == null ? [] : baseValues(object, keys(object)); } /** * Creates an array of the own and inherited enumerable string keyed property * values of `object`. * * **Note:** Non-object values are coerced to objects. * * @static * @memberOf _ * @since 3.0.0 * @category Object * @param {Object} object The object to query. * @returns {Array} Returns the array of property values. * @example * * function Foo() { * this.a = 1; * this.b = 2; * } * * Foo.prototype.c = 3; * * _.valuesIn(new Foo); * // => [1, 2, 3] (iteration order is not guaranteed) */ function valuesIn(object) { return object == null ? [] : baseValues(object, keysIn(object)); } /*------------------------------------------------------------------------*/ /** * Clamps `number` within the inclusive `lower` and `upper` bounds. * * @static * @memberOf _ * @since 4.0.0 * @category Number * @param {number} number The number to clamp. * @param {number} [lower] The lower bound. * @param {number} upper The upper bound. * @returns {number} Returns the clamped number. * @example * * _.clamp(-10, -5, 5); * // => -5 * * _.clamp(10, -5, 5); * // => 5 */ function clamp(number, lower, upper) { if (upper === undefined) { upper = lower; lower = undefined; } if (upper !== undefined) { upper = toNumber(upper); upper = upper === upper ? upper : 0; } if (lower !== undefined) { lower = toNumber(lower); lower = lower === lower ? lower : 0; } return baseClamp(toNumber(number), lower, upper); } /** * Checks if `n` is between `start` and up to, but not including, `end`. If * `end` is not specified, it's set to `start` with `start` then set to `0`. * If `start` is greater than `end` the params are swapped to support * negative ranges. * * @static * @memberOf _ * @since 3.3.0 * @category Number * @param {number} number The number to check. * @param {number} [start=0] The start of the range. * @param {number} end The end of the range. * @returns {boolean} Returns `true` if `number` is in the range, else `false`. * @see _.range, _.rangeRight * @example * * _.inRange(3, 2, 4); * // => true * * _.inRange(4, 8); * // => true * * _.inRange(4, 2); * // => false * * _.inRange(2, 2); * // => false * * _.inRange(1.2, 2); * // => true * * _.inRange(5.2, 4); * // => false * * _.inRange(-3, -2, -6); * // => true */ function inRange(number, start, end) { start = toFinite(start); if (end === undefined) { end = start; start = 0; } else { end = toFinite(end); } number = toNumber(number); return baseInRange(number, start, end); } /** * Produces a random number between the inclusive `lower` and `upper` bounds. * If only one argument is provided a number between `0` and the given number * is returned. If `floating` is `true`, or either `lower` or `upper` are * floats, a floating-point number is returned instead of an integer. * * **Note:** JavaScript follows the IEEE-754 standard for resolving * floating-point values which can produce unexpected results. * * @static * @memberOf _ * @since 0.7.0 * @category Number * @param {number} [lower=0] The lower bound. * @param {number} [upper=1] The upper bound. * @param {boolean} [floating] Specify returning a floating-point number. * @returns {number} Returns the random number. * @example * * _.random(0, 5); * // => an integer between 0 and 5 * * _.random(5); * // => also an integer between 0 and 5 * * _.random(5, true); * // => a floating-point number between 0 and 5 * * _.random(1.2, 5.2); * // => a floating-point number between 1.2 and 5.2 */ function random(lower, upper, floating) { if (floating && typeof floating != 'boolean' && isIterateeCall(lower, upper, floating)) { upper = floating = undefined; } if (floating === undefined) { if (typeof upper == 'boolean') { floating = upper; upper = undefined; } else if (typeof lower == 'boolean') { floating = lower; lower = undefined; } } if (lower === undefined && upper === undefined) { lower = 0; upper = 1; } else { lower = toFinite(lower); if (upper === undefined) { upper = lower; lower = 0; } else { upper = toFinite(upper); } } if (lower > upper) { var temp = lower; lower = upper; upper = temp; } if (floating || lower % 1 || upper % 1) { var rand = nativeRandom(); return nativeMin(lower + (rand * (upper - lower + freeParseFloat('1e-' + ((rand + '').length - 1)))), upper); } return baseRandom(lower, upper); } /*------------------------------------------------------------------------*/ /** * Converts `string` to [camel case](https://en.wikipedia.org/wiki/CamelCase). * * @static * @memberOf _ * @since 3.0.0 * @category String * @param {string} [string=''] The string to convert. * @returns {string} Returns the camel cased string. * @example * * _.camelCase('Foo Bar'); * // => 'fooBar' * * _.camelCase('--foo-bar--'); * // => 'fooBar' * * _.camelCase('__FOO_BAR__'); * // => 'fooBar' */ var camelCase = createCompounder(function(result, word, index) { word = word.toLowerCase(); return result + (index ? capitalize(word) : word); }); /** * Converts the first character of `string` to upper case and the remaining * to lower case. * * @static * @memberOf _ * @since 3.0.0 * @category String * @param {string} [string=''] The string to capitalize. * @returns {string} Returns the capitalized string. * @example * * _.capitalize('FRED'); * // => 'Fred' */ function capitalize(string) { return upperFirst(toString(string).toLowerCase()); } /** * Deburrs `string` by converting * [Latin-1 Supplement](https://en.wikipedia.org/wiki/Latin-1_Supplement_(Unicode_block)#Character_table) * and [Latin Extended-A](https://en.wikipedia.org/wiki/Latin_Extended-A) * letters to basic Latin letters and removing * [combining diacritical marks](https://en.wikipedia.org/wiki/Combining_Diacritical_Marks). * * @static * @memberOf _ * @since 3.0.0 * @category String * @param {string} [string=''] The string to deburr. * @returns {string} Returns the deburred string. * @example * * _.deburr('déjà vu'); * // => 'deja vu' */ function deburr(string) { string = toString(string); return string && string.replace(reLatin, deburrLetter).replace(reComboMark, ''); } /** * Checks if `string` ends with the given target string. * * @static * @memberOf _ * @since 3.0.0 * @category String * @param {string} [string=''] The string to inspect. * @param {string} [target] The string to search for. * @param {number} [position=string.length] The position to search up to. * @returns {boolean} Returns `true` if `string` ends with `target`, * else `false`. * @example * * _.endsWith('abc', 'c'); * // => true * * _.endsWith('abc', 'b'); * // => false * * _.endsWith('abc', 'b', 2); * // => true */ function endsWith(string, target, position) { string = toString(string); target = baseToString(target); var length = string.length; position = position === undefined ? length : baseClamp(toInteger(position), 0, length); var end = position; position -= target.length; return position >= 0 && string.slice(position, end) == target; } /** * Converts the characters "&", "<", ">", '"', and "'" in `string` to their * corresponding HTML entities. * * **Note:** No other characters are escaped. To escape additional * characters use a third-party library like [_he_](https://mths.be/he). * * Though the ">" character is escaped for symmetry, characters like * ">" and "/" don't need escaping in HTML and have no special meaning * unless they're part of a tag or unquoted attribute value. See * [Mathias Bynens's article](https://mathiasbynens.be/notes/ambiguous-ampersands) * (under "semi-related fun fact") for more details. * * When working with HTML you should always * [quote attribute values](http://wonko.com/post/html-escaping) to reduce * XSS vectors. * * @static * @since 0.1.0 * @memberOf _ * @category String * @param {string} [string=''] The string to escape. * @returns {string} Returns the escaped string. * @example * * _.escape('fred, barney, & pebbles'); * // => 'fred, barney, & pebbles' */ function escape(string) { string = toString(string); return (string && reHasUnescapedHtml.test(string)) ? string.replace(reUnescapedHtml, escapeHtmlChar) : string; } /** * Escapes the `RegExp` special characters "^", "$", "\", ".", "*", "+", * "?", "(", ")", "[", "]", "{", "}", and "|" in `string`. * * @static * @memberOf _ * @since 3.0.0 * @category String * @param {string} [string=''] The string to escape. * @returns {string} Returns the escaped string. * @example * * _.escapeRegExp('[lodash](https://lodash.com/)'); * // => '\[lodash\]\(https://lodash\.com/\)' */ function escapeRegExp(string) { string = toString(string); return (string && reHasRegExpChar.test(string)) ? string.replace(reRegExpChar, '\\$&') : string; } /** * Converts `string` to * [kebab case](https://en.wikipedia.org/wiki/Letter_case#Special_case_styles). * * @static * @memberOf _ * @since 3.0.0 * @category String * @param {string} [string=''] The string to convert. * @returns {string} Returns the kebab cased string. * @example * * _.kebabCase('Foo Bar'); * // => 'foo-bar' * * _.kebabCase('fooBar'); * // => 'foo-bar' * * _.kebabCase('__FOO_BAR__'); * // => 'foo-bar' */ var kebabCase = createCompounder(function(result, word, index) { return result + (index ? '-' : '') + word.toLowerCase(); }); /** * Converts `string`, as space separated words, to lower case. * * @static * @memberOf _ * @since 4.0.0 * @category String * @param {string} [string=''] The string to convert. * @returns {string} Returns the lower cased string. * @example * * _.lowerCase('--Foo-Bar--'); * // => 'foo bar' * * _.lowerCase('fooBar'); * // => 'foo bar' * * _.lowerCase('__FOO_BAR__'); * // => 'foo bar' */ var lowerCase = createCompounder(function(result, word, index) { return result + (index ? ' ' : '') + word.toLowerCase(); }); /** * Converts the first character of `string` to lower case. * * @static * @memberOf _ * @since 4.0.0 * @category String * @param {string} [string=''] The string to convert. * @returns {string} Returns the converted string. * @example * * _.lowerFirst('Fred'); * // => 'fred' * * _.lowerFirst('FRED'); * // => 'fRED' */ var lowerFirst = createCaseFirst('toLowerCase'); /** * Pads `string` on the left and right sides if it's shorter than `length`. * Padding characters are truncated if they can't be evenly divided by `length`. * * @static * @memberOf _ * @since 3.0.0 * @category String * @param {string} [string=''] The string to pad. * @param {number} [length=0] The padding length. * @param {string} [chars=' '] The string used as padding. * @returns {string} Returns the padded string. * @example * * _.pad('abc', 8); * // => ' abc ' * * _.pad('abc', 8, '_-'); * // => '_-abc_-_' * * _.pad('abc', 3); * // => 'abc' */ function pad(string, length, chars) { string = toString(string); length = toInteger(length); var strLength = length ? stringSize(string) : 0; if (!length || strLength >= length) { return string; } var mid = (length - strLength) / 2; return ( createPadding(nativeFloor(mid), chars) + string + createPadding(nativeCeil(mid), chars) ); } /** * Pads `string` on the right side if it's shorter than `length`. Padding * characters are truncated if they exceed `length`. * * @static * @memberOf _ * @since 4.0.0 * @category String * @param {string} [string=''] The string to pad. * @param {number} [length=0] The padding length. * @param {string} [chars=' '] The string used as padding. * @returns {string} Returns the padded string. * @example * * _.padEnd('abc', 6); * // => 'abc ' * * _.padEnd('abc', 6, '_-'); * // => 'abc_-_' * * _.padEnd('abc', 3); * // => 'abc' */ function padEnd(string, length, chars) { string = toString(string); length = toInteger(length); var strLength = length ? stringSize(string) : 0; return (length && strLength < length) ? (string + createPadding(length - strLength, chars)) : string; } /** * Pads `string` on the left side if it's shorter than `length`. Padding * characters are truncated if they exceed `length`. * * @static * @memberOf _ * @since 4.0.0 * @category String * @param {string} [string=''] The string to pad. * @param {number} [length=0] The padding length. * @param {string} [chars=' '] The string used as padding. * @returns {string} Returns the padded string. * @example * * _.padStart('abc', 6); * // => ' abc' * * _.padStart('abc', 6, '_-'); * // => '_-_abc' * * _.padStart('abc', 3); * // => 'abc' */ function padStart(string, length, chars) { string = toString(string); length = toInteger(length); var strLength = length ? stringSize(string) : 0; return (length && strLength < length) ? (createPadding(length - strLength, chars) + string) : string; } /** * Converts `string` to an integer of the specified radix. If `radix` is * `undefined` or `0`, a `radix` of `10` is used unless `value` is a * hexadecimal, in which case a `radix` of `16` is used. * * **Note:** This method aligns with the * [ES5 implementation](https://es5.github.io/#x15.1.2.2) of `parseInt`. * * @static * @memberOf _ * @since 1.1.0 * @category String * @param {string} string The string to convert. * @param {number} [radix=10] The radix to interpret `value` by. * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. * @returns {number} Returns the converted integer. * @example * * _.parseInt('08'); * // => 8 * * _.map(['6', '08', '10'], _.parseInt); * // => [6, 8, 10] */ function parseInt(string, radix, guard) { if (guard || radix == null) { radix = 0; } else if (radix) { radix = +radix; } return nativeParseInt(toString(string).replace(reTrimStart, ''), radix || 0); } /** * Repeats the given string `n` times. * * @static * @memberOf _ * @since 3.0.0 * @category String * @param {string} [string=''] The string to repeat. * @param {number} [n=1] The number of times to repeat the string. * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. * @returns {string} Returns the repeated string. * @example * * _.repeat('*', 3); * // => '***' * * _.repeat('abc', 2); * // => 'abcabc' * * _.repeat('abc', 0); * // => '' */ function repeat(string, n, guard) { if ((guard ? isIterateeCall(string, n, guard) : n === undefined)) { n = 1; } else { n = toInteger(n); } return baseRepeat(toString(string), n); } /** * Replaces matches for `pattern` in `string` with `replacement`. * * **Note:** This method is based on * [`String#replace`](https://mdn.io/String/replace). * * @static * @memberOf _ * @since 4.0.0 * @category String * @param {string} [string=''] The string to modify. * @param {RegExp|string} pattern The pattern to replace. * @param {Function|string} replacement The match replacement. * @returns {string} Returns the modified string. * @example * * _.replace('Hi Fred', 'Fred', 'Barney'); * // => 'Hi Barney' */ function replace() { var args = arguments, string = toString(args[0]); return args.length < 3 ? string : string.replace(args[1], args[2]); } /** * Converts `string` to * [snake case](https://en.wikipedia.org/wiki/Snake_case). * * @static * @memberOf _ * @since 3.0.0 * @category String * @param {string} [string=''] The string to convert. * @returns {string} Returns the snake cased string. * @example * * _.snakeCase('Foo Bar'); * // => 'foo_bar' * * _.snakeCase('fooBar'); * // => 'foo_bar' * * _.snakeCase('--FOO-BAR--'); * // => 'foo_bar' */ var snakeCase = createCompounder(function(result, word, index) { return result + (index ? '_' : '') + word.toLowerCase(); }); /** * Splits `string` by `separator`. * * **Note:** This method is based on * [`String#split`](https://mdn.io/String/split). * * @static * @memberOf _ * @since 4.0.0 * @category String * @param {string} [string=''] The string to split. * @param {RegExp|string} separator The separator pattern to split by. * @param {number} [limit] The length to truncate results to. * @returns {Array} Returns the string segments. * @example * * _.split('a-b-c', '-', 2); * // => ['a', 'b'] */ function split(string, separator, limit) { if (limit && typeof limit != 'number' && isIterateeCall(string, separator, limit)) { separator = limit = undefined; } limit = limit === undefined ? MAX_ARRAY_LENGTH : limit >>> 0; if (!limit) { return []; } string = toString(string); if (string && ( typeof separator == 'string' || (separator != null && !isRegExp(separator)) )) { separator = baseToString(separator); if (!separator && hasUnicode(string)) { return castSlice(stringToArray(string), 0, limit); } } return string.split(separator, limit); } /** * Converts `string` to * [start case](https://en.wikipedia.org/wiki/Letter_case#Stylistic_or_specialised_usage). * * @static * @memberOf _ * @since 3.1.0 * @category String * @param {string} [string=''] The string to convert. * @returns {string} Returns the start cased string. * @example * * _.startCase('--foo-bar--'); * // => 'Foo Bar' * * _.startCase('fooBar'); * // => 'Foo Bar' * * _.startCase('__FOO_BAR__'); * // => 'FOO BAR' */ var startCase = createCompounder(function(result, word, index) { return result + (index ? ' ' : '') + upperFirst(word); }); /** * Checks if `string` starts with the given target string. * * @static * @memberOf _ * @since 3.0.0 * @category String * @param {string} [string=''] The string to inspect. * @param {string} [target] The string to search for. * @param {number} [position=0] The position to search from. * @returns {boolean} Returns `true` if `string` starts with `target`, * else `false`. * @example * * _.startsWith('abc', 'a'); * // => true * * _.startsWith('abc', 'b'); * // => false * * _.startsWith('abc', 'b', 1); * // => true */ function startsWith(string, target, position) { string = toString(string); position = position == null ? 0 : baseClamp(toInteger(position), 0, string.length); target = baseToString(target); return string.slice(position, position + target.length) == target; } /** * Creates a compiled template function that can interpolate data properties * in "interpolate" delimiters, HTML-escape interpolated data properties in * "escape" delimiters, and execute JavaScript in "evaluate" delimiters. Data * properties may be accessed as free variables in the template. If a setting * object is given, it takes precedence over `_.templateSettings` values. * * **Note:** In the development build `_.template` utilizes * [sourceURLs](http://www.html5rocks.com/en/tutorials/developertools/sourcemaps/#toc-sourceurl) * for easier debugging. * * For more information on precompiling templates see * [lodash's custom builds documentation](https://lodash.com/custom-builds). * * For more information on Chrome extension sandboxes see * [Chrome's extensions documentation](https://developer.chrome.com/extensions/sandboxingEval). * * @static * @since 0.1.0 * @memberOf _ * @category String * @param {string} [string=''] The template string. * @param {Object} [options={}] The options object. * @param {RegExp} [options.escape=_.templateSettings.escape] * The HTML "escape" delimiter. * @param {RegExp} [options.evaluate=_.templateSettings.evaluate] * The "evaluate" delimiter. * @param {Object} [options.imports=_.templateSettings.imports] * An object to import into the template as free variables. * @param {RegExp} [options.interpolate=_.templateSettings.interpolate] * The "interpolate" delimiter. * @param {string} [options.sourceURL='lodash.templateSources[n]'] * The sourceURL of the compiled template. * @param {string} [options.variable='obj'] * The data object variable name. * @param- {Object} [guard] Enables use as an iteratee for methods like `_.map`. * @returns {Function} Returns the compiled template function. * @example * * // Use the "interpolate" delimiter to create a compiled template. * var compiled = _.template('hello <%= user %>!'); * compiled({ 'user': 'fred' }); * // => 'hello fred!' * * // Use the HTML "escape" delimiter to escape data property values. * var compiled = _.template('<%- value %>'); * compiled({ 'value': '''' % bundle random_id = id_generator(size=15, random_state=check_random_state(self.random_state)) out += u'''
''' % random_id predict_proba_js = '' if self.mode == "classification" and predict_proba: predict_proba_js = u''' var pp_div = top_div.append('div') .classed('lime predict_proba', true); var pp_svg = pp_div.append('svg').style('width', '100%%'); var pp = new lime.PredictProba(pp_svg, %s, %s); ''' % (jsonize([str(x) for x in self.class_names]), jsonize(list(self.predict_proba.astype(float)))) predict_value_js = '' if self.mode == "regression" and show_predicted_value: # reference self.predicted_value # (svg, predicted_value, min_value, max_value) predict_value_js = u''' var pp_div = top_div.append('div') .classed('lime predicted_value', true); var pp_svg = pp_div.append('svg').style('width', '100%%'); var pp = new lime.PredictedValue(pp_svg, %s, %s, %s); ''' % (jsonize(float(self.predicted_value)), jsonize(float(self.min_value)), jsonize(float(self.max_value))) exp_js = '''var exp_div; var exp = new lime.Explanation(%s); ''' % (jsonize([str(x) for x in self.class_names])) if self.mode == "classification": for label in labels: exp = jsonize(self.as_list(label)) exp_js += u''' exp_div = top_div.append('div').classed('lime explanation', true); exp.show(%s, %d, exp_div); ''' % (exp, label) else: exp = jsonize(self.as_list()) exp_js += u''' exp_div = top_div.append('div').classed('lime explanation', true); exp.show(%s, %s, exp_div); ''' % (exp, self.dummy_label) raw_js = '''var raw_div = top_div.append('div');''' if self.mode == "classification": html_data = self.local_exp[labels[0]] else: html_data = self.local_exp[self.dummy_label] raw_js += self.domain_mapper.visualize_instance_html( html_data, labels[0] if self.mode == "classification" else self.dummy_label, 'raw_div', 'exp', **kwargs) out += u''' ''' % (random_id, predict_proba_js, predict_value_js, exp_js, raw_js) out += u'' return out ================================================ FILE: lime/js/bar_chart.js ================================================ import d3 from 'd3'; class Barchart { // svg: d3 object with the svg in question // exp_array: list of (feature_name, weight) constructor(svg, exp_array, two_sided=true, titles=undefined, colors=['red', 'green'], show_numbers=false, bar_height=5) { let svg_width = Math.min(600, parseInt(svg.style('width'))); let bar_width = two_sided ? svg_width / 2 : svg_width; if (titles === undefined) { titles = two_sided ? ['Cons', 'Pros'] : 'Pros'; } if (show_numbers) { bar_width = bar_width - 30; } let x_offset = two_sided ? svg_width / 2 : 10; // 13.1 is +- the width of W, the widest letter. if (two_sided && titles.length == 2) { svg.append('text') .attr('x', svg_width / 4) .attr('y', 15) .attr('font-size', '20') .attr('text-anchor', 'middle') .style('fill', colors[0]) .text(titles[0]); svg.append('text') .attr('x', svg_width / 4 * 3) .attr('y', 15) .attr('font-size', '20') .attr('text-anchor', 'middle') .style('fill', colors[1]) .text(titles[1]); } else { let pos = two_sided ? svg_width / 2 : x_offset; let anchor = two_sided ? 'middle' : 'begin'; svg.append('text') .attr('x', pos) .attr('y', 15) .attr('font-size', '20') .attr('text-anchor', anchor) .text(titles); } let yshift = 20; let space_between_bars = 0; let text_height = 16; let space_between_bar_and_text = 3; let total_bar_height = text_height + space_between_bar_and_text + bar_height + space_between_bars; let total_height = (total_bar_height) * exp_array.length; this.svg_height = total_height + yshift; let yscale = d3.scale.linear() .domain([0, exp_array.length]) .range([yshift, yshift + total_height]) let names = exp_array.map(v => v[0]); let weights = exp_array.map(v => v[1]); let max_weight = Math.max(...(weights.map(v=>Math.abs(v)))); let xscale = d3.scale.linear() .domain([0,Math.max(1, max_weight)]) .range([0, bar_width]); for (var i = 0; i < exp_array.length; ++i) { let name = names[i]; let weight = weights[i]; var size = xscale(Math.abs(weight)); let to_the_right = (weight > 0 || !two_sided) let text = svg.append('text') .attr('x', to_the_right ? x_offset + 2 : x_offset - 2) .attr('y', yscale(i) + text_height) .attr('text-anchor', to_the_right ? 'begin' : 'end') .attr('font-size', '14') .text(name); while (text.node().getBBox()['width'] + 1 > bar_width) { let cur_text = text.text().slice(0, text.text().length - 5); text.text(cur_text + '...'); if (text === '...') { break; } } let bar = svg.append('rect') .attr('height', bar_height) .attr('x', to_the_right ? x_offset : x_offset - size) .attr('y', text_height + yscale(i) + space_between_bar_and_text)// + bar_height) .attr('width', size) .style('fill', weight > 0 ? colors[1] : colors[0]); if (show_numbers) { let bartext = svg.append('text') .attr('x', to_the_right ? x_offset + size + 1 : x_offset - size - 1) .attr('text-anchor', (weight > 0 || !two_sided) ? 'begin' : 'end') .attr('y', bar_height + yscale(i) + text_height + space_between_bar_and_text) .attr('font-size', '10') .text(Math.abs(weight).toFixed(2)); } } let line = svg.append("line") .attr("x1", x_offset) .attr("x2", x_offset) .attr("y1", bar_height + yshift) .attr("y2", Math.max(bar_height, yscale(exp_array.length))) .style("stroke-width",2) .style("stroke", "black"); } } export default Barchart; ================================================ FILE: lime/js/explanation.js ================================================ import d3 from 'd3'; import Barchart from './bar_chart.js'; import {range, sortBy} from 'lodash'; class Explanation { constructor(class_names) { this.names = class_names; if (class_names.length < 10) { this.colors = d3.scale.category10().domain(this.names); this.colors_i = d3.scale.category10().domain(range(this.names.length)); } else { this.colors = d3.scale.category20().domain(this.names); this.colors_i = d3.scale.category20().domain(range(this.names.length)); } } // exp: [(feature-name, weight), ...] // label: int // div: d3 selection show(exp, label, div) { let svg = div.append('svg').style('width', '100%'); let colors=['#5F9EA0', this.colors_i(label)]; let names = [`NOT ${this.names[label]}`, this.names[label]]; if (this.names.length == 2) { colors=[this.colors_i(0), this.colors_i(1)]; names = this.names; } let plot = new Barchart(svg, exp, true, names, colors, true, 10); svg.style('height', plot.svg_height + 'px'); } // exp has all ocurrences of words, with start index and weight: // exp = [('word', 132, -0.13), ('word3', 111, 1.3) show_raw_text(exp, label, raw, div, opacity=true) { //let colors=['#5F9EA0', this.colors(this.exp['class'])]; let colors=['#5F9EA0', this.colors_i(label)]; if (this.names.length == 2) { colors=[this.colors_i(0), this.colors_i(1)]; } let word_lists = [[], []]; let max_weight = -1; for (let [word, start, weight] of exp) { if (weight > 0) { word_lists[1].push([start, start + word.length, weight]); } else { word_lists[0].push([start, start + word.length, -weight]); } max_weight = Math.max(max_weight, Math.abs(weight)); } if (!opacity) { max_weight = 0; } this.display_raw_text(div, raw, word_lists, colors, max_weight, true); } // exp is list of (feature_name, value, weight) show_raw_tabular(exp, label, div) { div.classed('lime', true).classed('table_div', true); let colors=['#5F9EA0', this.colors_i(label)]; if (this.names.length == 2) { colors=[this.colors_i(0), this.colors_i(1)]; } const table = div.append('table'); const thead = table.append('tr'); thead.append('td').text('Feature'); thead.append('td').text('Value'); thead.style('color', 'black') .style('font-size', '20px'); for (let [fname, value, weight] of exp) { const tr = table.append('tr'); tr.style('border-style', 'hidden'); tr.append('td').text(fname); tr.append('td').text(value); if (weight > 0) { tr.style('background-color', colors[1]); } else if (weight < 0) { tr.style('background-color', colors[0]); } else { tr.style('color', 'black'); } } } hexToRgb(hex) { let result = /^#?([a-f\d]{2})([a-f\d]{2})([a-f\d]{2})$/i.exec(hex); return result ? { r: parseInt(result[1], 16), g: parseInt(result[2], 16), b: parseInt(result[3], 16) } : null; } applyAlpha(hex, alpha) { let components = this.hexToRgb(hex); return 'rgba(' + components.r + "," + components.g + "," + components.b + "," + alpha.toFixed(3) + ")" } // sord_lists is an array of arrays, of length (colors). if with_positions is true, // word_lists is an array of [start,end] positions instead display_raw_text(div, raw_text, word_lists=[], colors=[], max_weight=1, positions=false) { div.classed('lime', true).classed('text_div', true); div.append('h3').text('Text with highlighted words'); let highlight_tag = 'span'; let text_span = div.append('span').style('white-space', 'pre-wrap').text(raw_text); let position_lists = word_lists; if (!positions) { position_lists = this.wordlists_to_positions(word_lists, raw_text); } let objects = [] for (let i of range(position_lists.length)) { position_lists[i].map(x => objects.push({'label' : i, 'start': x[0], 'end': x[1], 'alpha': max_weight === 0 ? 1: x[2] / max_weight})); } objects = sortBy(objects, x=>x['start']); let node = text_span.node().childNodes[0]; let subtract = 0; for (let obj of objects) { let word = raw_text.slice(obj.start, obj.end); let start = obj.start - subtract; let end = obj.end - subtract; let match = document.createElement(highlight_tag); match.appendChild(document.createTextNode(word)); match.style.backgroundColor = this.applyAlpha(colors[obj.label], obj.alpha); let after = node.splitText(start); after.nodeValue = after.nodeValue.substring(word.length); node.parentNode.insertBefore(match, after); subtract += end; node = after; } } wordlists_to_positions(word_lists, raw_text) { let ret = [] for(let words of word_lists) { if (words.length === 0) { ret.push([]); continue; } let re = new RegExp("\\b(" + words.join('|') + ")\\b",'gm') let temp; let list = []; while ((temp = re.exec(raw_text)) !== null) { list.push([temp.index, temp.index + temp[0].length]); } ret.push(list); } return ret; } } export default Explanation; ================================================ FILE: lime/js/main.js ================================================ if (!global._babelPolyfill) { require('babel-polyfill') } import Explanation from './explanation.js'; import Barchart from './bar_chart.js'; import PredictProba from './predict_proba.js'; import PredictedValue from './predicted_value.js'; require('../style.css'); export {Explanation, Barchart, PredictProba, PredictedValue}; //require('style-loader'); ================================================ FILE: lime/js/predict_proba.js ================================================ import d3 from 'd3'; import {range, sortBy} from 'lodash'; class PredictProba { // svg: d3 object with the svg in question // class_names: array of class names // predict_probas: array of prediction probabilities constructor(svg, class_names, predict_probas, title='Prediction probabilities') { let width = parseInt(svg.style('width')); this.names = class_names; this.names.push('Other'); if (class_names.length < 10) { this.colors = d3.scale.category10().domain(this.names); this.colors_i = d3.scale.category10().domain(range(this.names.length)); } else { this.colors = d3.scale.category20().domain(this.names); this.colors_i = d3.scale.category20().domain(range(this.names.length)); } let [names, data] = this.map_classes(this.names, predict_probas); let bar_x = width - 125; let class_names_width = bar_x; let bar_width = width - bar_x - 32; let x_scale = d3.scale.linear().range([0, bar_width]); let bar_height = 17; let space_between_bars = 5; let bar_yshift= title === '' ? 0 : 35; let n_bars = Math.min(5, data.length); this.svg_height = n_bars * (bar_height + space_between_bars) + bar_yshift; svg.style('height', this.svg_height + 'px'); let this_object = this; if (title !== '') { svg.append('text') .text(title) .attr('x', 20) .attr('y', 20); } let bar_y = i => (bar_height + space_between_bars) * i + bar_yshift; let bar = svg.append("g"); for (let i of range(data.length)) { var color = this.colors(names[i]); if (names[i] == 'Other' && this.names.length > 20) { color = '#5F9EA0'; } let rect = bar.append("rect"); rect.attr("x", bar_x) .attr("y", bar_y(i)) .attr("height", bar_height) .attr("width", x_scale(data[i])) .style("fill", color); bar.append("rect").attr("x", bar_x) .attr("y", bar_y(i)) .attr("height", bar_height) .attr("width", bar_width - 1) .attr("fill-opacity", 0) .attr("stroke", "black"); let text = bar.append("text"); text.classed("prob_text", true); text.attr("y", bar_y(i) + bar_height - 3).attr("fill", "black").style("font", "14px tahoma, sans-serif"); text = bar.append("text"); text.attr("x", bar_x + x_scale(data[i]) + 5) .attr("y", bar_y(i) + bar_height - 3) .attr("fill", "black") .style("font", "14px tahoma, sans-serif") .text(data[i].toFixed(2)); text = bar.append("text"); text.attr("x", bar_x - 10) .attr("y", bar_y(i) + bar_height - 3) .attr("fill", "black") .attr("text-anchor", "end") .style("font", "14px tahoma, sans-serif") .text(names[i]); while (text.node().getBBox()['width'] + 1 > (class_names_width - 10)) { // TODO: ta mostrando só dois, e talvez quando hover mostrar o texto // todo let cur_text = text.text().slice(0, text.text().length - 5); text.text(cur_text + '...'); if (cur_text.length <= 3) { break } } } } map_classes(class_names, predict_proba) { if (class_names.length <= 6) { return [class_names, predict_proba]; } let class_dict = range(predict_proba.length).map(i => ({'name': class_names[i], 'prob': predict_proba[i], 'i' : i})); let sorted = sortBy(class_dict, d => -d.prob); let other = new Set(); range(4, sorted.length).map(d => other.add(sorted[d].name)); let other_prob = 0; let ret_probs = []; let ret_names = []; for (let d of range(sorted.length)) { if (other.has(sorted[d].name)) { other_prob += sorted[d].prob; } else { ret_probs.push(sorted[d].prob); ret_names.push(sorted[d].name); } }; ret_names.push("Other"); ret_probs.push(other_prob); return [ret_names, ret_probs]; } } export default PredictProba; ================================================ FILE: lime/js/predicted_value.js ================================================ import d3 from 'd3'; import {range, sortBy} from 'lodash'; class PredictedValue { // svg: d3 object with the svg in question // class_names: array of class names // predict_probas: array of prediction probabilities constructor(svg, predicted_value, min_value, max_value, title='Predicted value', log_coords = false) { if (min_value == max_value){ var width_proportion = 1.0; } else { var width_proportion = (predicted_value - min_value) / (max_value - min_value); } let width = parseInt(svg.style('width')) this.color = d3.scale.category10() this.color('predicted_value') // + 2 is due to it being a float let num_digits = Math.floor(Math.max(Math.log10(Math.abs(min_value)), Math.log10(Math.abs(max_value)))) + 2 num_digits = Math.max(num_digits, 3) let corner_width = 12 * num_digits; let corner_padding = 5.5 * num_digits; let bar_x = corner_width + corner_padding; let bar_width = width - corner_width * 2 - corner_padding * 2; let x_scale = d3.scale.linear().range([0, bar_width]); let bar_height = 17; let bar_yshift= title === '' ? 0 : 35; let n_bars = 1; let this_object = this; if (title !== '') { svg.append('text') .text(title) .attr('x', 20) .attr('y', 20); } let bar_y = bar_yshift; let bar = svg.append("g"); //filled in bar representing predicted value in range let rect = bar.append("rect"); rect.attr("x", bar_x) .attr("y", bar_y) .attr("height", bar_height) .attr("width", x_scale(width_proportion)) .style("fill", this.color); //empty box representing range bar.append("rect").attr("x", bar_x) .attr("y", bar_y) .attr("height", bar_height) .attr("width",x_scale(1)) .attr("fill-opacity", 0) .attr("stroke", "black"); let text = bar.append("text"); text.classed("prob_text", true); text.attr("y", bar_y + bar_height - 3).attr("fill", "black").style("font", "14px tahoma, sans-serif"); //text for min value text = bar.append("text"); text.attr("x", bar_x - corner_padding) .attr("y", bar_y + bar_height - 3) .attr("fill", "black") .attr("text-anchor", "end") .style("font", "14px tahoma, sans-serif") .text(min_value.toFixed(2)); //text for range min annotation let v_adjust_min_value_annotation = text.node().getBBox().height; text = bar.append("text"); text.attr("x", bar_x - corner_padding) .attr("y", bar_y + bar_height - 3 + v_adjust_min_value_annotation) .attr("fill", "black") .attr("text-anchor", "end") .style("font", "14px tahoma, sans-serif") .text("(min)"); //text for predicted value // console.log('bar height: ' + bar_height) text = bar.append("text"); text.text(predicted_value.toFixed(2)); // let h_adjust_predicted_value_text = text.node().getBBox().width / 2; let v_adjust_predicted_value_text = text.node().getBBox().height; text.attr("x", bar_x + x_scale(width_proportion)) .attr("y", bar_y + bar_height + v_adjust_predicted_value_text) .attr("fill", "black") .attr("text-anchor", "middle") .style("font", "14px tahoma, sans-serif") //text for max value text = bar.append("text"); text.text(max_value.toFixed(2)); // let h_adjust = text.node().getBBox().width; text.attr("x", bar_x + bar_width + corner_padding) .attr("y", bar_y + bar_height - 3) .attr("fill", "black") .attr("text-anchor", "begin") .style("font", "14px tahoma, sans-serif"); //text for range max annotation let v_adjust_max_value_annotation = text.node().getBBox().height; text = bar.append("text"); text.attr("x", bar_x + bar_width + corner_padding) .attr("y", bar_y + bar_height - 3 + v_adjust_min_value_annotation) .attr("fill", "black") .attr("text-anchor", "begin") .style("font", "14px tahoma, sans-serif") .text("(max)"); //readjust svg size // let svg_width = width + 1 * h_adjust; // svg.style('width', svg_width + 'px'); this.svg_height = n_bars * (bar_height) + bar_yshift + (2 * text.node().getBBox().height) + 10; svg.style('height', this.svg_height + 'px'); if (log_coords) { console.log("svg width: " + svg_width); console.log("svg height: " + this.svg_height); console.log("bar_y: " + bar_y); console.log("bar_x: " + bar_x); console.log("Min value: " + min_value); console.log("Max value: " + max_value); console.log("Pred value: " + predicted_value); } } } export default PredictedValue; ================================================ FILE: lime/lime_base.py ================================================ """ Contains abstract functionality for learning locally linear sparse model. """ import numpy as np import scipy as sp from sklearn.linear_model import Ridge, lars_path from sklearn.utils import check_random_state class LimeBase(object): """Class for learning a locally linear sparse model from perturbed data""" def __init__(self, kernel_fn, verbose=False, random_state=None): """Init function Args: kernel_fn: function that transforms an array of distances into an array of proximity values (floats). verbose: if true, print local prediction values from linear model. random_state: an integer or numpy.RandomState that will be used to generate random numbers. If None, the random state will be initialized using the internal numpy seed. """ self.kernel_fn = kernel_fn self.verbose = verbose self.random_state = check_random_state(random_state) @staticmethod def generate_lars_path(weighted_data, weighted_labels): """Generates the lars path for weighted data. Args: weighted_data: data that has been weighted by kernel weighted_label: labels, weighted by kernel Returns: (alphas, coefs), both are arrays corresponding to the regularization parameter and coefficients, respectively """ x_vector = weighted_data alphas, _, coefs = lars_path(x_vector, weighted_labels, method='lasso', verbose=False) return alphas, coefs def forward_selection(self, data, labels, weights, num_features): """Iteratively adds features to the model""" clf = Ridge(alpha=0, fit_intercept=True, random_state=self.random_state) used_features = [] for _ in range(min(num_features, data.shape[1])): max_ = -100000000 best = 0 for feature in range(data.shape[1]): if feature in used_features: continue clf.fit(data[:, used_features + [feature]], labels, sample_weight=weights) score = clf.score(data[:, used_features + [feature]], labels, sample_weight=weights) if score > max_: best = feature max_ = score used_features.append(best) return np.array(used_features) def feature_selection(self, data, labels, weights, num_features, method): """Selects features for the model. see explain_instance_with_data to understand the parameters.""" if method == 'none': return np.array(range(data.shape[1])) elif method == 'forward_selection': return self.forward_selection(data, labels, weights, num_features) elif method == 'highest_weights': clf = Ridge(alpha=0.01, fit_intercept=True, random_state=self.random_state) clf.fit(data, labels, sample_weight=weights) coef = clf.coef_ if sp.sparse.issparse(data): coef = sp.sparse.csr_matrix(clf.coef_) weighted_data = coef.multiply(data[0]) # Note: most efficient to slice the data before reversing sdata = len(weighted_data.data) argsort_data = np.abs(weighted_data.data).argsort() # Edge case where data is more sparse than requested number of feature importances # In that case, we just pad with zero-valued features if sdata < num_features: nnz_indexes = argsort_data[::-1] indices = weighted_data.indices[nnz_indexes] num_to_pad = num_features - sdata indices = np.concatenate((indices, np.zeros(num_to_pad, dtype=indices.dtype))) indices_set = set(indices) pad_counter = 0 for i in range(data.shape[1]): if i not in indices_set: indices[pad_counter + sdata] = i pad_counter += 1 if pad_counter >= num_to_pad: break else: nnz_indexes = argsort_data[sdata - num_features:sdata][::-1] indices = weighted_data.indices[nnz_indexes] return indices else: weighted_data = coef * data[0] feature_weights = sorted( zip(range(data.shape[1]), weighted_data), key=lambda x: np.abs(x[1]), reverse=True) return np.array([x[0] for x in feature_weights[:num_features]]) elif method == 'lasso_path': weighted_data = ((data - np.average(data, axis=0, weights=weights)) * np.sqrt(weights[:, np.newaxis])) weighted_labels = ((labels - np.average(labels, weights=weights)) * np.sqrt(weights)) nonzero = range(weighted_data.shape[1]) _, coefs = self.generate_lars_path(weighted_data, weighted_labels) for i in range(len(coefs.T) - 1, 0, -1): nonzero = coefs.T[i].nonzero()[0] if len(nonzero) <= num_features: break used_features = nonzero return used_features elif method == 'auto': if num_features <= 6: n_method = 'forward_selection' else: n_method = 'highest_weights' return self.feature_selection(data, labels, weights, num_features, n_method) def explain_instance_with_data(self, neighborhood_data, neighborhood_labels, distances, label, num_features, feature_selection='auto', model_regressor=None): """Takes perturbed data, labels and distances, returns explanation. Args: neighborhood_data: perturbed data, 2d array. first element is assumed to be the original data point. neighborhood_labels: corresponding perturbed labels. should have as many columns as the number of possible labels. distances: distances to original data point. label: label for which we want an explanation num_features: maximum number of features in explanation feature_selection: how to select num_features. options are: 'forward_selection': iteratively add features to the model. This is costly when num_features is high 'highest_weights': selects the features that have the highest product of absolute weight * original data point when learning with all the features 'lasso_path': chooses features based on the lasso regularization path 'none': uses all features, ignores num_features 'auto': uses forward_selection if num_features <= 6, and 'highest_weights' otherwise. model_regressor: sklearn regressor to use in explanation. Defaults to Ridge regression if None. Must have model_regressor.coef_ and 'sample_weight' as a parameter to model_regressor.fit() Returns: (intercept, exp, score, local_pred): intercept is a float. exp is a sorted list of tuples, where each tuple (x,y) corresponds to the feature id (x) and the local weight (y). The list is sorted by decreasing absolute value of y. score is the R^2 value of the returned explanation local_pred is the prediction of the explanation model on the original instance """ weights = self.kernel_fn(distances) labels_column = neighborhood_labels[:, label] used_features = self.feature_selection(neighborhood_data, labels_column, weights, num_features, feature_selection) if model_regressor is None: model_regressor = Ridge(alpha=1, fit_intercept=True, random_state=self.random_state) easy_model = model_regressor easy_model.fit(neighborhood_data[:, used_features], labels_column, sample_weight=weights) prediction_score = easy_model.score( neighborhood_data[:, used_features], labels_column, sample_weight=weights) local_pred = easy_model.predict(neighborhood_data[0, used_features].reshape(1, -1)) if self.verbose: print('Intercept', easy_model.intercept_) print('Prediction_local', local_pred,) print('Right:', neighborhood_labels[0, label]) return (easy_model.intercept_, sorted(zip(used_features, easy_model.coef_), key=lambda x: np.abs(x[1]), reverse=True), prediction_score, local_pred) ================================================ FILE: lime/lime_image.py ================================================ """ Functions for explaining classifiers that use Image data. """ import copy from functools import partial import numpy as np import sklearn from sklearn.utils import check_random_state from skimage.color import gray2rgb from tqdm.auto import tqdm from . import lime_base from .wrappers.scikit_image import SegmentationAlgorithm class ImageExplanation(object): def __init__(self, image, segments): """Init function. Args: image: 3d numpy array segments: 2d numpy array, with the output from skimage.segmentation """ self.image = image self.segments = segments self.intercept = {} self.local_exp = {} self.local_pred = {} self.score = {} def get_image_and_mask(self, label, positive_only=True, negative_only=False, hide_rest=False, num_features=5, min_weight=0.): """Init function. Args: label: label to explain positive_only: if True, only take superpixels that positively contribute to the prediction of the label. negative_only: if True, only take superpixels that negatively contribute to the prediction of the label. If false, and so is positive_only, then both negativey and positively contributions will be taken. Both can't be True at the same time hide_rest: if True, make the non-explanation part of the return image gray num_features: number of superpixels to include in explanation min_weight: minimum weight of the superpixels to include in explanation Returns: (image, mask), where image is a 3d numpy array and mask is a 2d numpy array that can be used with skimage.segmentation.mark_boundaries """ if label not in self.local_exp: raise KeyError('Label not in explanation') if positive_only & negative_only: raise ValueError("Positive_only and negative_only cannot be true at the same time.") segments = self.segments image = self.image exp = self.local_exp[label] mask = np.zeros(segments.shape, segments.dtype) if hide_rest: temp = np.zeros(self.image.shape) else: temp = self.image.copy() if positive_only: fs = [x[0] for x in exp if x[1] > 0 and x[1] > min_weight][:num_features] if negative_only: fs = [x[0] for x in exp if x[1] < 0 and abs(x[1]) > min_weight][:num_features] if positive_only or negative_only: for f in fs: temp[segments == f] = image[segments == f].copy() mask[segments == f] = 1 return temp, mask else: for f, w in exp[:num_features]: if np.abs(w) < min_weight: continue c = 0 if w < 0 else 1 mask[segments == f] = -1 if w < 0 else 1 temp[segments == f] = image[segments == f].copy() temp[segments == f, c] = np.max(image) return temp, mask class LimeImageExplainer(object): """Explains predictions on Image (i.e. matrix) data. For numerical features, perturb them by sampling from a Normal(0,1) and doing the inverse operation of mean-centering and scaling, according to the means and stds in the training data. For categorical features, perturb by sampling according to the training distribution, and making a binary feature that is 1 when the value is the same as the instance being explained.""" def __init__(self, kernel_width=.25, kernel=None, verbose=False, feature_selection='auto', random_state=None): """Init function. Args: kernel_width: kernel width for the exponential kernel. If None, defaults to sqrt(number of columns) * 0.75. kernel: similarity kernel that takes euclidean distances and kernel width as input and outputs weights in (0,1). If None, defaults to an exponential kernel. verbose: if true, print local prediction values from linear model feature_selection: feature selection method. can be 'forward_selection', 'lasso_path', 'none' or 'auto'. See function 'explain_instance_with_data' in lime_base.py for details on what each of the options does. random_state: an integer or numpy.RandomState that will be used to generate random numbers. If None, the random state will be initialized using the internal numpy seed. """ kernel_width = float(kernel_width) if kernel is None: def kernel(d, kernel_width): return np.sqrt(np.exp(-(d ** 2) / kernel_width ** 2)) kernel_fn = partial(kernel, kernel_width=kernel_width) self.random_state = check_random_state(random_state) self.feature_selection = feature_selection self.base = lime_base.LimeBase(kernel_fn, verbose, random_state=self.random_state) def explain_instance(self, image, classifier_fn, labels=(1,), hide_color=None, top_labels=5, num_features=100000, num_samples=1000, batch_size=10, segmentation_fn=None, distance_metric='cosine', model_regressor=None, random_seed=None, progress_bar=True): """Generates explanations for a prediction. First, we generate neighborhood data by randomly perturbing features from the instance (see __data_inverse). We then learn locally weighted linear models on this neighborhood data to explain each of the classes in an interpretable way (see lime_base.py). Args: image: 3 dimension RGB image. If this is only two dimensional, we will assume it's a grayscale image and call gray2rgb. classifier_fn: classifier prediction probability function, which takes a numpy array and outputs prediction probabilities. For ScikitClassifiers , this is classifier.predict_proba. labels: iterable with labels to be explained. hide_color: If not None, will hide superpixels with this color. Otherwise, use the mean pixel color of the image. top_labels: if not None, ignore labels and produce explanations for the K labels with highest prediction probabilities, where K is this parameter. num_features: maximum number of features present in explanation num_samples: size of the neighborhood to learn the linear model batch_size: batch size for model predictions distance_metric: the distance metric to use for weights. model_regressor: sklearn regressor to use in explanation. Defaults to Ridge regression in LimeBase. Must have model_regressor.coef_ and 'sample_weight' as a parameter to model_regressor.fit() segmentation_fn: SegmentationAlgorithm, wrapped skimage segmentation function random_seed: integer used as random seed for the segmentation algorithm. If None, a random integer, between 0 and 1000, will be generated using the internal random number generator. progress_bar: if True, show tqdm progress bar. Returns: An ImageExplanation object (see lime_image.py) with the corresponding explanations. """ if len(image.shape) == 2: image = gray2rgb(image) if random_seed is None: random_seed = self.random_state.randint(0, high=1000) if segmentation_fn is None: segmentation_fn = SegmentationAlgorithm('quickshift', kernel_size=4, max_dist=200, ratio=0.2, random_seed=random_seed) segments = segmentation_fn(image) fudged_image = image.copy() if hide_color is None: for x in np.unique(segments): fudged_image[segments == x] = ( np.mean(image[segments == x][:, 0]), np.mean(image[segments == x][:, 1]), np.mean(image[segments == x][:, 2])) else: fudged_image[:] = hide_color top = labels data, labels = self.data_labels(image, fudged_image, segments, classifier_fn, num_samples, batch_size=batch_size, progress_bar=progress_bar) distances = sklearn.metrics.pairwise_distances( data, data[0].reshape(1, -1), metric=distance_metric ).ravel() ret_exp = ImageExplanation(image, segments) if top_labels: top = np.argsort(labels[0])[-top_labels:] ret_exp.top_labels = list(top) ret_exp.top_labels.reverse() for label in top: (ret_exp.intercept[label], ret_exp.local_exp[label], ret_exp.score[label], ret_exp.local_pred[label]) = self.base.explain_instance_with_data( data, labels, distances, label, num_features, model_regressor=model_regressor, feature_selection=self.feature_selection) return ret_exp def data_labels(self, image, fudged_image, segments, classifier_fn, num_samples, batch_size=10, progress_bar=True): """Generates images and predictions in the neighborhood of this image. Args: image: 3d numpy array, the image fudged_image: 3d numpy array, image to replace original image when superpixel is turned off segments: segmentation of the image classifier_fn: function that takes a list of images and returns a matrix of prediction probabilities num_samples: size of the neighborhood to learn the linear model batch_size: classifier_fn will be called on batches of this size. progress_bar: if True, show tqdm progress bar. Returns: A tuple (data, labels), where: data: dense num_samples * num_superpixels labels: prediction probabilities matrix """ n_features = np.unique(segments).shape[0] data = self.random_state.randint(0, 2, num_samples * n_features)\ .reshape((num_samples, n_features)) labels = [] data[0, :] = 1 imgs = [] rows = tqdm(data) if progress_bar else data for row in rows: temp = copy.deepcopy(image) zeros = np.where(row == 0)[0] mask = np.zeros(segments.shape).astype(bool) for z in zeros: mask[segments == z] = True temp[mask] = fudged_image[mask] imgs.append(temp) if len(imgs) == batch_size: preds = classifier_fn(np.array(imgs)) labels.extend(preds) imgs = [] if len(imgs) > 0: preds = classifier_fn(np.array(imgs)) labels.extend(preds) return data, np.array(labels) ================================================ FILE: lime/lime_tabular.py ================================================ """ Functions for explaining classifiers that use tabular data (matrices). """ import collections import copy from functools import partial import json import warnings import numpy as np import scipy as sp import sklearn import sklearn.preprocessing from sklearn.utils import check_random_state from pyDOE2 import lhs from scipy.stats.distributions import norm from lime.discretize import QuartileDiscretizer from lime.discretize import DecileDiscretizer from lime.discretize import EntropyDiscretizer from lime.discretize import BaseDiscretizer from lime.discretize import StatsDiscretizer from . import explanation from . import lime_base class TableDomainMapper(explanation.DomainMapper): """Maps feature ids to names, generates table views, etc""" def __init__(self, feature_names, feature_values, scaled_row, categorical_features, discretized_feature_names=None, feature_indexes=None): """Init. Args: feature_names: list of feature names, in order feature_values: list of strings with the values of the original row scaled_row: scaled row categorical_features: list of categorical features ids (ints) feature_indexes: optional feature indexes used in the sparse case """ self.exp_feature_names = feature_names self.discretized_feature_names = discretized_feature_names self.feature_names = feature_names self.feature_values = feature_values self.feature_indexes = feature_indexes self.scaled_row = scaled_row if sp.sparse.issparse(scaled_row): self.all_categorical = False else: self.all_categorical = len(categorical_features) == len(scaled_row) self.categorical_features = categorical_features def map_exp_ids(self, exp): """Maps ids to feature names. Args: exp: list of tuples [(id, weight), (id,weight)] Returns: list of tuples (feature_name, weight) """ names = self.exp_feature_names if self.discretized_feature_names is not None: names = self.discretized_feature_names return [(names[x[0]], x[1]) for x in exp] def visualize_instance_html(self, exp, label, div_name, exp_object_name, show_table=True, show_all=False): """Shows the current example in a table format. Args: exp: list of tuples [(id, weight), (id,weight)] label: label id (integer) div_name: name of div object to be used for rendering(in js) exp_object_name: name of js explanation object show_table: if False, don't show table visualization. show_all: if True, show zero-weighted features in the table. """ if not show_table: return '' weights = [0] * len(self.feature_names) for x in exp: weights[x[0]] = x[1] if self.feature_indexes is not None: # Sparse case: only display the non-zero values and importances fnames = [self.exp_feature_names[i] for i in self.feature_indexes] fweights = [weights[i] for i in self.feature_indexes] if show_all: out_list = list(zip(fnames, self.feature_values, fweights)) else: out_dict = dict(map(lambda x: (x[0], (x[1], x[2], x[3])), zip(self.feature_indexes, fnames, self.feature_values, fweights))) out_list = [out_dict.get(x[0], (str(x[0]), 0.0, 0.0)) for x in exp] else: out_list = list(zip(self.exp_feature_names, self.feature_values, weights)) if not show_all: out_list = [out_list[x[0]] for x in exp] ret = u''' %s.show_raw_tabular(%s, %d, %s); ''' % (exp_object_name, json.dumps(out_list, ensure_ascii=False), label, div_name) return ret class LimeTabularExplainer(object): """Explains predictions on tabular (i.e. matrix) data. For numerical features, perturb them by sampling from a Normal(0,1) and doing the inverse operation of mean-centering and scaling, according to the means and stds in the training data. For categorical features, perturb by sampling according to the training distribution, and making a binary feature that is 1 when the value is the same as the instance being explained.""" def __init__(self, training_data, mode="classification", training_labels=None, feature_names=None, categorical_features=None, categorical_names=None, kernel_width=None, kernel=None, verbose=False, class_names=None, feature_selection='auto', discretize_continuous=True, discretizer='quartile', sample_around_instance=False, random_state=None, training_data_stats=None): """Init function. Args: training_data: numpy 2d array mode: "classification" or "regression" training_labels: labels for training data. Not required, but may be used by discretizer. feature_names: list of names (strings) corresponding to the columns in the training data. categorical_features: list of indices (ints) corresponding to the categorical columns. Everything else will be considered continuous. Values in these columns MUST be integers. categorical_names: map from int to list of names, where categorical_names[x][y] represents the name of the yth value of column x. kernel_width: kernel width for the exponential kernel. If None, defaults to sqrt (number of columns) * 0.75 kernel: similarity kernel that takes euclidean distances and kernel width as input and outputs weights in (0,1). If None, defaults to an exponential kernel. verbose: if true, print local prediction values from linear model class_names: list of class names, ordered according to whatever the classifier is using. If not present, class names will be '0', '1', ... feature_selection: feature selection method. can be 'forward_selection', 'lasso_path', 'none' or 'auto'. See function 'explain_instance_with_data' in lime_base.py for details on what each of the options does. discretize_continuous: if True, all non-categorical features will be discretized into quartiles. discretizer: only matters if discretize_continuous is True and data is not sparse. Options are 'quartile', 'decile', 'entropy' or a BaseDiscretizer instance. sample_around_instance: if True, will sample continuous features in perturbed samples from a normal centered at the instance being explained. Otherwise, the normal is centered on the mean of the feature data. random_state: an integer or numpy.RandomState that will be used to generate random numbers. If None, the random state will be initialized using the internal numpy seed. training_data_stats: a dict object having the details of training data statistics. If None, training data information will be used, only matters if discretize_continuous is True. Must have the following keys: means", "mins", "maxs", "stds", "feature_values", "feature_frequencies" """ self.random_state = check_random_state(random_state) self.mode = mode self.categorical_names = categorical_names or {} self.sample_around_instance = sample_around_instance self.training_data_stats = training_data_stats # Check and raise proper error in stats are supplied in non-descritized path if self.training_data_stats: self.validate_training_data_stats(self.training_data_stats) if categorical_features is None: categorical_features = [] if feature_names is None: feature_names = [str(i) for i in range(training_data.shape[1])] self.categorical_features = list(categorical_features) self.feature_names = list(feature_names) self.discretizer = None if discretize_continuous and not sp.sparse.issparse(training_data): # Set the discretizer if training data stats are provided if self.training_data_stats: discretizer = StatsDiscretizer( training_data, self.categorical_features, self.feature_names, labels=training_labels, data_stats=self.training_data_stats, random_state=self.random_state) if discretizer == 'quartile': self.discretizer = QuartileDiscretizer( training_data, self.categorical_features, self.feature_names, labels=training_labels, random_state=self.random_state) elif discretizer == 'decile': self.discretizer = DecileDiscretizer( training_data, self.categorical_features, self.feature_names, labels=training_labels, random_state=self.random_state) elif discretizer == 'entropy': self.discretizer = EntropyDiscretizer( training_data, self.categorical_features, self.feature_names, labels=training_labels, random_state=self.random_state) elif isinstance(discretizer, BaseDiscretizer): self.discretizer = discretizer else: raise ValueError('''Discretizer must be 'quartile',''' + ''' 'decile', 'entropy' or a''' + ''' BaseDiscretizer instance''') self.categorical_features = list(range(training_data.shape[1])) # Get the discretized_training_data when the stats are not provided if(self.training_data_stats is None): discretized_training_data = self.discretizer.discretize( training_data) if kernel_width is None: kernel_width = np.sqrt(training_data.shape[1]) * .75 kernel_width = float(kernel_width) if kernel is None: def kernel(d, kernel_width): return np.sqrt(np.exp(-(d ** 2) / kernel_width ** 2)) kernel_fn = partial(kernel, kernel_width=kernel_width) self.feature_selection = feature_selection self.base = lime_base.LimeBase(kernel_fn, verbose, random_state=self.random_state) self.class_names = class_names # Though set has no role to play if training data stats are provided self.scaler = sklearn.preprocessing.StandardScaler(with_mean=False) self.scaler.fit(training_data) self.feature_values = {} self.feature_frequencies = {} for feature in self.categorical_features: if training_data_stats is None: if self.discretizer is not None: column = discretized_training_data[:, feature] else: column = training_data[:, feature] feature_count = collections.Counter(column) values, frequencies = map(list, zip(*(sorted(feature_count.items())))) else: values = training_data_stats["feature_values"][feature] frequencies = training_data_stats["feature_frequencies"][feature] self.feature_values[feature] = values self.feature_frequencies[feature] = (np.array(frequencies) / float(sum(frequencies))) self.scaler.mean_[feature] = 0 self.scaler.scale_[feature] = 1 @staticmethod def convert_and_round(values): return ['%.2f' % v for v in values] @staticmethod def validate_training_data_stats(training_data_stats): """ Method to validate the structure of training data stats """ stat_keys = list(training_data_stats.keys()) valid_stat_keys = ["means", "mins", "maxs", "stds", "feature_values", "feature_frequencies"] missing_keys = list(set(valid_stat_keys) - set(stat_keys)) if len(missing_keys) > 0: raise Exception("Missing keys in training_data_stats. Details: %s" % (missing_keys)) def explain_instance(self, data_row, predict_fn, labels=(1,), top_labels=None, num_features=10, num_samples=5000, distance_metric='euclidean', model_regressor=None, sampling_method='gaussian'): """Generates explanations for a prediction. First, we generate neighborhood data by randomly perturbing features from the instance (see __data_inverse). We then learn locally weighted linear models on this neighborhood data to explain each of the classes in an interpretable way (see lime_base.py). Args: data_row: 1d numpy array or scipy.sparse matrix, corresponding to a row predict_fn: prediction function. For classifiers, this should be a function that takes a numpy array and outputs prediction probabilities. For regressors, this takes a numpy array and returns the predictions. For ScikitClassifiers, this is `classifier.predict_proba()`. For ScikitRegressors, this is `regressor.predict()`. The prediction function needs to work on multiple feature vectors (the vectors randomly perturbed from the data_row). labels: iterable with labels to be explained. top_labels: if not None, ignore labels and produce explanations for the K labels with highest prediction probabilities, where K is this parameter. num_features: maximum number of features present in explanation num_samples: size of the neighborhood to learn the linear model distance_metric: the distance metric to use for weights. model_regressor: sklearn regressor to use in explanation. Defaults to Ridge regression in LimeBase. Must have model_regressor.coef_ and 'sample_weight' as a parameter to model_regressor.fit() sampling_method: Method to sample synthetic data. Defaults to Gaussian sampling. Can also use Latin Hypercube Sampling. Returns: An Explanation object (see explanation.py) with the corresponding explanations. """ if sp.sparse.issparse(data_row) and not sp.sparse.isspmatrix_csr(data_row): # Preventative code: if sparse, convert to csr format if not in csr format already data_row = data_row.tocsr() data, inverse = self.__data_inverse(data_row, num_samples, sampling_method) if sp.sparse.issparse(data): # Note in sparse case we don't subtract mean since data would become dense scaled_data = data.multiply(self.scaler.scale_) # Multiplying with csr matrix can return a coo sparse matrix if not sp.sparse.isspmatrix_csr(scaled_data): scaled_data = scaled_data.tocsr() else: scaled_data = (data - self.scaler.mean_) / self.scaler.scale_ distances = sklearn.metrics.pairwise_distances( scaled_data, scaled_data[0].reshape(1, -1), metric=distance_metric ).ravel() yss = predict_fn(inverse) # for classification, the model needs to provide a list of tuples - classes # along with prediction probabilities if self.mode == "classification": if len(yss.shape) == 1: raise NotImplementedError("LIME does not currently support " "classifier models without probability " "scores. If this conflicts with your " "use case, please let us know: " "https://github.com/datascienceinc/lime/issues/16") elif len(yss.shape) == 2: if self.class_names is None: self.class_names = [str(x) for x in range(yss[0].shape[0])] else: self.class_names = list(self.class_names) if not np.allclose(yss.sum(axis=1), 1.0): warnings.warn(""" Prediction probabilties do not sum to 1, and thus does not constitute a probability space. Check that you classifier outputs probabilities (Not log probabilities, or actual class predictions). """) else: raise ValueError("Your model outputs " "arrays with {} dimensions".format(len(yss.shape))) # for regression, the output should be a one-dimensional array of predictions else: try: if len(yss.shape) != 1 and len(yss[0].shape) == 1: yss = np.array([v[0] for v in yss]) assert isinstance(yss, np.ndarray) and len(yss.shape) == 1 except AssertionError: raise ValueError("Your model needs to output single-dimensional \ numpyarrays, not arrays of {} dimensions".format(yss.shape)) predicted_value = yss[0] min_y = min(yss) max_y = max(yss) # add a dimension to be compatible with downstream machinery yss = yss[:, np.newaxis] feature_names = copy.deepcopy(self.feature_names) if feature_names is None: feature_names = [str(x) for x in range(data_row.shape[0])] if sp.sparse.issparse(data_row): values = self.convert_and_round(data_row.data) feature_indexes = data_row.indices else: values = self.convert_and_round(data_row) feature_indexes = None for i in self.categorical_features: if self.discretizer is not None and i in self.discretizer.lambdas: continue name = int(data_row[i]) if i in self.categorical_names: name = self.categorical_names[i][name] feature_names[i] = '%s=%s' % (feature_names[i], name) values[i] = 'True' categorical_features = self.categorical_features discretized_feature_names = None if self.discretizer is not None: categorical_features = range(data.shape[1]) discretized_instance = self.discretizer.discretize(data_row) discretized_feature_names = copy.deepcopy(feature_names) for f in self.discretizer.names: discretized_feature_names[f] = self.discretizer.names[f][int( discretized_instance[f])] domain_mapper = TableDomainMapper(feature_names, values, scaled_data[0], categorical_features=categorical_features, discretized_feature_names=discretized_feature_names, feature_indexes=feature_indexes) ret_exp = explanation.Explanation(domain_mapper, mode=self.mode, class_names=self.class_names) if self.mode == "classification": ret_exp.predict_proba = yss[0] if top_labels: labels = np.argsort(yss[0])[-top_labels:] ret_exp.top_labels = list(labels) ret_exp.top_labels.reverse() else: ret_exp.predicted_value = predicted_value ret_exp.min_value = min_y ret_exp.max_value = max_y labels = [0] for label in labels: (ret_exp.intercept[label], ret_exp.local_exp[label], ret_exp.score[label], ret_exp.local_pred[label]) = self.base.explain_instance_with_data( scaled_data, yss, distances, label, num_features, model_regressor=model_regressor, feature_selection=self.feature_selection) if self.mode == "regression": ret_exp.intercept[1] = ret_exp.intercept[0] ret_exp.local_exp[1] = [x for x in ret_exp.local_exp[0]] ret_exp.local_exp[0] = [(i, -1 * j) for i, j in ret_exp.local_exp[1]] return ret_exp def __data_inverse(self, data_row, num_samples, sampling_method): """Generates a neighborhood around a prediction. For numerical features, perturb them by sampling from a Normal(0,1) and doing the inverse operation of mean-centering and scaling, according to the means and stds in the training data. For categorical features, perturb by sampling according to the training distribution, and making a binary feature that is 1 when the value is the same as the instance being explained. Args: data_row: 1d numpy array, corresponding to a row num_samples: size of the neighborhood to learn the linear model sampling_method: 'gaussian' or 'lhs' Returns: A tuple (data, inverse), where: data: dense num_samples * K matrix, where categorical features are encoded with either 0 (not equal to the corresponding value in data_row) or 1. The first row is the original instance. inverse: same as data, except the categorical features are not binary, but categorical (as the original data) """ is_sparse = sp.sparse.issparse(data_row) if is_sparse: num_cols = data_row.shape[1] data = sp.sparse.csr_matrix((num_samples, num_cols), dtype=data_row.dtype) else: num_cols = data_row.shape[0] data = np.zeros((num_samples, num_cols)) categorical_features = range(num_cols) if self.discretizer is None: instance_sample = data_row scale = self.scaler.scale_ mean = self.scaler.mean_ if is_sparse: # Perturb only the non-zero values non_zero_indexes = data_row.nonzero()[1] num_cols = len(non_zero_indexes) instance_sample = data_row[:, non_zero_indexes] scale = scale[non_zero_indexes] mean = mean[non_zero_indexes] if sampling_method == 'gaussian': data = self.random_state.normal(0, 1, num_samples * num_cols ).reshape(num_samples, num_cols) data = np.array(data) elif sampling_method == 'lhs': data = lhs(num_cols, samples=num_samples ).reshape(num_samples, num_cols) means = np.zeros(num_cols) stdvs = np.array([1]*num_cols) for i in range(num_cols): data[:, i] = norm(loc=means[i], scale=stdvs[i]).ppf(data[:, i]) data = np.array(data) else: warnings.warn('''Invalid input for sampling_method. Defaulting to Gaussian sampling.''', UserWarning) data = self.random_state.normal(0, 1, num_samples * num_cols ).reshape(num_samples, num_cols) data = np.array(data) if self.sample_around_instance: data = data * scale + instance_sample else: data = data * scale + mean if is_sparse: if num_cols == 0: data = sp.sparse.csr_matrix((num_samples, data_row.shape[1]), dtype=data_row.dtype) else: indexes = np.tile(non_zero_indexes, num_samples) indptr = np.array( range(0, len(non_zero_indexes) * (num_samples + 1), len(non_zero_indexes))) data_1d_shape = data.shape[0] * data.shape[1] data_1d = data.reshape(data_1d_shape) data = sp.sparse.csr_matrix( (data_1d, indexes, indptr), shape=(num_samples, data_row.shape[1])) categorical_features = self.categorical_features first_row = data_row else: first_row = self.discretizer.discretize(data_row) data[0] = data_row.copy() inverse = data.copy() for column in categorical_features: values = self.feature_values[column] freqs = self.feature_frequencies[column] inverse_column = self.random_state.choice(values, size=num_samples, replace=True, p=freqs) binary_column = (inverse_column == first_row[column]).astype(int) binary_column[0] = 1 inverse_column[0] = data[0, column] data[:, column] = binary_column inverse[:, column] = inverse_column if self.discretizer is not None: inverse[1:] = self.discretizer.undiscretize(inverse[1:]) inverse[0] = data_row return data, inverse class RecurrentTabularExplainer(LimeTabularExplainer): """ An explainer for keras-style recurrent neural networks, where the input shape is (n_samples, n_timesteps, n_features). This class just extends the LimeTabularExplainer class and reshapes the training data and feature names such that they become something like (val1_t1, val1_t2, val1_t3, ..., val2_t1, ..., valn_tn) Each of the methods that take data reshape it appropriately, so you can pass in the training/testing data exactly as you would to the recurrent neural network. """ def __init__(self, training_data, mode="classification", training_labels=None, feature_names=None, categorical_features=None, categorical_names=None, kernel_width=None, kernel=None, verbose=False, class_names=None, feature_selection='auto', discretize_continuous=True, discretizer='quartile', random_state=None): """ Args: training_data: numpy 3d array with shape (n_samples, n_timesteps, n_features) mode: "classification" or "regression" training_labels: labels for training data. Not required, but may be used by discretizer. feature_names: list of names (strings) corresponding to the columns in the training data. categorical_features: list of indices (ints) corresponding to the categorical columns. Everything else will be considered continuous. Values in these columns MUST be integers. categorical_names: map from int to list of names, where categorical_names[x][y] represents the name of the yth value of column x. kernel_width: kernel width for the exponential kernel. If None, defaults to sqrt(number of columns) * 0.75 kernel: similarity kernel that takes euclidean distances and kernel width as input and outputs weights in (0,1). If None, defaults to an exponential kernel. verbose: if true, print local prediction values from linear model class_names: list of class names, ordered according to whatever the classifier is using. If not present, class names will be '0', '1', ... feature_selection: feature selection method. can be 'forward_selection', 'lasso_path', 'none' or 'auto'. See function 'explain_instance_with_data' in lime_base.py for details on what each of the options does. discretize_continuous: if True, all non-categorical features will be discretized into quartiles. discretizer: only matters if discretize_continuous is True. Options are 'quartile', 'decile', 'entropy' or a BaseDiscretizer instance. random_state: an integer or numpy.RandomState that will be used to generate random numbers. If None, the random state will be initialized using the internal numpy seed. """ # Reshape X n_samples, n_timesteps, n_features = training_data.shape training_data = np.transpose(training_data, axes=(0, 2, 1)).reshape( n_samples, n_timesteps * n_features) self.n_timesteps = n_timesteps self.n_features = n_features if feature_names is None: feature_names = ['feature%d' % i for i in range(n_features)] # Update the feature names feature_names = ['{}_t-{}'.format(n, n_timesteps - (i + 1)) for n in feature_names for i in range(n_timesteps)] # Send off the the super class to do its magic. super(RecurrentTabularExplainer, self).__init__( training_data, mode=mode, training_labels=training_labels, feature_names=feature_names, categorical_features=categorical_features, categorical_names=categorical_names, kernel_width=kernel_width, kernel=kernel, verbose=verbose, class_names=class_names, feature_selection=feature_selection, discretize_continuous=discretize_continuous, discretizer=discretizer, random_state=random_state) def _make_predict_proba(self, func): """ The predict_proba method will expect 3d arrays, but we are reshaping them to 2D so that LIME works correctly. This wraps the function you give in explain_instance to first reshape the data to have the shape the the keras-style network expects. """ def predict_proba(X): n_samples = X.shape[0] new_shape = (n_samples, self.n_features, self.n_timesteps) X = np.transpose(X.reshape(new_shape), axes=(0, 2, 1)) return func(X) return predict_proba def explain_instance(self, data_row, classifier_fn, labels=(1,), top_labels=None, num_features=10, num_samples=5000, distance_metric='euclidean', model_regressor=None): """Generates explanations for a prediction. First, we generate neighborhood data by randomly perturbing features from the instance (see __data_inverse). We then learn locally weighted linear models on this neighborhood data to explain each of the classes in an interpretable way (see lime_base.py). Args: data_row: 2d numpy array, corresponding to a row classifier_fn: classifier prediction probability function, which takes a numpy array and outputs prediction probabilities. For ScikitClassifiers , this is classifier.predict_proba. labels: iterable with labels to be explained. top_labels: if not None, ignore labels and produce explanations for the K labels with highest prediction probabilities, where K is this parameter. num_features: maximum number of features present in explanation num_samples: size of the neighborhood to learn the linear model distance_metric: the distance metric to use for weights. model_regressor: sklearn regressor to use in explanation. Defaults to Ridge regression in LimeBase. Must have model_regressor.coef_ and 'sample_weight' as a parameter to model_regressor.fit() Returns: An Explanation object (see explanation.py) with the corresponding explanations. """ # Flatten input so that the normal explainer can handle it data_row = data_row.T.reshape(self.n_timesteps * self.n_features) # Wrap the classifier to reshape input classifier_fn = self._make_predict_proba(classifier_fn) return super(RecurrentTabularExplainer, self).explain_instance( data_row, classifier_fn, labels=labels, top_labels=top_labels, num_features=num_features, num_samples=num_samples, distance_metric=distance_metric, model_regressor=model_regressor) ================================================ FILE: lime/lime_text.py ================================================ """ Functions for explaining text classifiers. """ from functools import partial import itertools import json import re import numpy as np import scipy as sp import sklearn from sklearn.utils import check_random_state from . import explanation from . import lime_base class TextDomainMapper(explanation.DomainMapper): """Maps feature ids to words or word-positions""" def __init__(self, indexed_string): """Initializer. Args: indexed_string: lime_text.IndexedString, original string """ self.indexed_string = indexed_string def map_exp_ids(self, exp, positions=False): """Maps ids to words or word-position strings. Args: exp: list of tuples [(id, weight), (id,weight)] positions: if True, also return word positions Returns: list of tuples (word, weight), or (word_positions, weight) if examples: ('bad', 1) or ('bad_3-6-12', 1) """ if positions: exp = [('%s_%s' % ( self.indexed_string.word(x[0]), '-'.join( map(str, self.indexed_string.string_position(x[0])))), x[1]) for x in exp] else: exp = [(self.indexed_string.word(x[0]), x[1]) for x in exp] return exp def visualize_instance_html(self, exp, label, div_name, exp_object_name, text=True, opacity=True): """Adds text with highlighted words to visualization. Args: exp: list of tuples [(id, weight), (id,weight)] label: label id (integer) div_name: name of div object to be used for rendering(in js) exp_object_name: name of js explanation object text: if False, return empty opacity: if True, fade colors according to weight """ if not text: return u'' text = (self.indexed_string.raw_string() .encode('utf-8', 'xmlcharrefreplace').decode('utf-8')) text = re.sub(r'[<>&]', '|', text) exp = [(self.indexed_string.word(x[0]), self.indexed_string.string_position(x[0]), x[1]) for x in exp] all_occurrences = list(itertools.chain.from_iterable( [itertools.product([x[0]], x[1], [x[2]]) for x in exp])) all_occurrences = [(x[0], int(x[1]), x[2]) for x in all_occurrences] ret = ''' %s.show_raw_text(%s, %d, %s, %s, %s); ''' % (exp_object_name, json.dumps(all_occurrences), label, json.dumps(text), div_name, json.dumps(opacity)) return ret class IndexedString(object): """String with various indexes.""" def __init__(self, raw_string, split_expression=r'\W+', bow=True, mask_string=None): """Initializer. Args: raw_string: string with raw text in it split_expression: Regex string or callable. If regex string, will be used with re.split. If callable, the function should return a list of tokens. bow: if True, a word is the same everywhere in the text - i.e. we will index multiple occurrences of the same word. If False, order matters, so that the same word will have different ids according to position. mask_string: If not None, replace words with this if bow=False if None, default value is UNKWORDZ """ self.raw = raw_string self.mask_string = 'UNKWORDZ' if mask_string is None else mask_string if callable(split_expression): tokens = split_expression(self.raw) self.as_list = self._segment_with_tokens(self.raw, tokens) tokens = set(tokens) def non_word(string): return string not in tokens else: # with the split_expression as a non-capturing group (?:), we don't need to filter out # the separator character from the split results. splitter = re.compile(r'(%s)|$' % split_expression) self.as_list = [s for s in splitter.split(self.raw) if s] non_word = splitter.match self.as_np = np.array(self.as_list) self.string_start = np.hstack( ([0], np.cumsum([len(x) for x in self.as_np[:-1]]))) vocab = {} self.inverse_vocab = [] self.positions = [] self.bow = bow non_vocab = set() for i, word in enumerate(self.as_np): if word in non_vocab: continue if non_word(word): non_vocab.add(word) continue if bow: if word not in vocab: vocab[word] = len(vocab) self.inverse_vocab.append(word) self.positions.append([]) idx_word = vocab[word] self.positions[idx_word].append(i) else: self.inverse_vocab.append(word) self.positions.append(i) if not bow: self.positions = np.array(self.positions) def raw_string(self): """Returns the original raw string""" return self.raw def num_words(self): """Returns the number of tokens in the vocabulary for this document.""" return len(self.inverse_vocab) def word(self, id_): """Returns the word that corresponds to id_ (int)""" return self.inverse_vocab[id_] def string_position(self, id_): """Returns a np array with indices to id_ (int) occurrences""" if self.bow: return self.string_start[self.positions[id_]] else: return self.string_start[[self.positions[id_]]] def inverse_removing(self, words_to_remove): """Returns a string after removing the appropriate words. If self.bow is false, replaces word with UNKWORDZ instead of removing it. Args: words_to_remove: list of ids (ints) to remove Returns: original raw string with appropriate words removed. """ mask = np.ones(self.as_np.shape[0], dtype='bool') mask[self.__get_idxs(words_to_remove)] = False if not self.bow: return ''.join( [self.as_list[i] if mask[i] else self.mask_string for i in range(mask.shape[0])]) return ''.join([self.as_list[v] for v in mask.nonzero()[0]]) @staticmethod def _segment_with_tokens(text, tokens): """Segment a string around the tokens created by a passed-in tokenizer""" list_form = [] text_ptr = 0 for token in tokens: inter_token_string = [] while not text[text_ptr:].startswith(token): inter_token_string.append(text[text_ptr]) text_ptr += 1 if text_ptr >= len(text): raise ValueError("Tokenization produced tokens that do not belong in string!") text_ptr += len(token) if inter_token_string: list_form.append(''.join(inter_token_string)) list_form.append(token) if text_ptr < len(text): list_form.append(text[text_ptr:]) return list_form def __get_idxs(self, words): """Returns indexes to appropriate words.""" if self.bow: return list(itertools.chain.from_iterable( [self.positions[z] for z in words])) else: return self.positions[words] class IndexedCharacters(object): """String with various indexes.""" def __init__(self, raw_string, bow=True, mask_string=None): """Initializer. Args: raw_string: string with raw text in it bow: if True, a char is the same everywhere in the text - i.e. we will index multiple occurrences of the same character. If False, order matters, so that the same word will have different ids according to position. mask_string: If not None, replace characters with this if bow=False if None, default value is chr(0) """ self.raw = raw_string self.as_list = list(self.raw) self.as_np = np.array(self.as_list) self.mask_string = chr(0) if mask_string is None else mask_string self.string_start = np.arange(len(self.raw)) vocab = {} self.inverse_vocab = [] self.positions = [] self.bow = bow non_vocab = set() for i, char in enumerate(self.as_np): if char in non_vocab: continue if bow: if char not in vocab: vocab[char] = len(vocab) self.inverse_vocab.append(char) self.positions.append([]) idx_char = vocab[char] self.positions[idx_char].append(i) else: self.inverse_vocab.append(char) self.positions.append(i) if not bow: self.positions = np.array(self.positions) def raw_string(self): """Returns the original raw string""" return self.raw def num_words(self): """Returns the number of tokens in the vocabulary for this document.""" return len(self.inverse_vocab) def word(self, id_): """Returns the word that corresponds to id_ (int)""" return self.inverse_vocab[id_] def string_position(self, id_): """Returns a np array with indices to id_ (int) occurrences""" if self.bow: return self.string_start[self.positions[id_]] else: return self.string_start[[self.positions[id_]]] def inverse_removing(self, words_to_remove): """Returns a string after removing the appropriate words. If self.bow is false, replaces word with UNKWORDZ instead of removing it. Args: words_to_remove: list of ids (ints) to remove Returns: original raw string with appropriate words removed. """ mask = np.ones(self.as_np.shape[0], dtype='bool') mask[self.__get_idxs(words_to_remove)] = False if not self.bow: return ''.join( [self.as_list[i] if mask[i] else self.mask_string for i in range(mask.shape[0])]) return ''.join([self.as_list[v] for v in mask.nonzero()[0]]) def __get_idxs(self, words): """Returns indexes to appropriate words.""" if self.bow: return list(itertools.chain.from_iterable( [self.positions[z] for z in words])) else: return self.positions[words] class LimeTextExplainer(object): """Explains text classifiers. Currently, we are using an exponential kernel on cosine distance, and restricting explanations to words that are present in documents.""" def __init__(self, kernel_width=25, kernel=None, verbose=False, class_names=None, feature_selection='auto', split_expression=r'\W+', bow=True, mask_string=None, random_state=None, char_level=False): """Init function. Args: kernel_width: kernel width for the exponential kernel. kernel: similarity kernel that takes euclidean distances and kernel width as input and outputs weights in (0,1). If None, defaults to an exponential kernel. verbose: if true, print local prediction values from linear model class_names: list of class names, ordered according to whatever the classifier is using. If not present, class names will be '0', '1', ... feature_selection: feature selection method. can be 'forward_selection', 'lasso_path', 'none' or 'auto'. See function 'explain_instance_with_data' in lime_base.py for details on what each of the options does. split_expression: Regex string or callable. If regex string, will be used with re.split. If callable, the function should return a list of tokens. bow: if True (bag of words), will perturb input data by removing all occurrences of individual words or characters. Explanations will be in terms of these words. Otherwise, will explain in terms of word-positions, so that a word may be important the first time it appears and unimportant the second. Only set to false if the classifier uses word order in some way (bigrams, etc), or if you set char_level=True. mask_string: String used to mask tokens or characters if bow=False if None, will be 'UNKWORDZ' if char_level=False, chr(0) otherwise. random_state: an integer or numpy.RandomState that will be used to generate random numbers. If None, the random state will be initialized using the internal numpy seed. char_level: an boolean identifying that we treat each character as an independent occurence in the string """ if kernel is None: def kernel(d, kernel_width): return np.sqrt(np.exp(-(d ** 2) / kernel_width ** 2)) kernel_fn = partial(kernel, kernel_width=kernel_width) self.random_state = check_random_state(random_state) self.base = lime_base.LimeBase(kernel_fn, verbose, random_state=self.random_state) self.class_names = class_names self.vocabulary = None self.feature_selection = feature_selection self.bow = bow self.mask_string = mask_string self.split_expression = split_expression self.char_level = char_level def explain_instance(self, text_instance, classifier_fn, labels=(1,), top_labels=None, num_features=10, num_samples=5000, distance_metric='cosine', model_regressor=None): """Generates explanations for a prediction. First, we generate neighborhood data by randomly hiding features from the instance (see __data_labels_distance_mapping). We then learn locally weighted linear models on this neighborhood data to explain each of the classes in an interpretable way (see lime_base.py). Args: text_instance: raw text string to be explained. classifier_fn: classifier prediction probability function, which takes a list of d strings and outputs a (d, k) numpy array with prediction probabilities, where k is the number of classes. For ScikitClassifiers , this is classifier.predict_proba. labels: iterable with labels to be explained. top_labels: if not None, ignore labels and produce explanations for the K labels with highest prediction probabilities, where K is this parameter. num_features: maximum number of features present in explanation num_samples: size of the neighborhood to learn the linear model distance_metric: the distance metric to use for sample weighting, defaults to cosine similarity model_regressor: sklearn regressor to use in explanation. Defaults to Ridge regression in LimeBase. Must have model_regressor.coef_ and 'sample_weight' as a parameter to model_regressor.fit() Returns: An Explanation object (see explanation.py) with the corresponding explanations. """ indexed_string = (IndexedCharacters( text_instance, bow=self.bow, mask_string=self.mask_string) if self.char_level else IndexedString(text_instance, bow=self.bow, split_expression=self.split_expression, mask_string=self.mask_string)) domain_mapper = TextDomainMapper(indexed_string) data, yss, distances = self.__data_labels_distances( indexed_string, classifier_fn, num_samples, distance_metric=distance_metric) if self.class_names is None: self.class_names = [str(x) for x in range(yss[0].shape[0])] ret_exp = explanation.Explanation(domain_mapper=domain_mapper, class_names=self.class_names, random_state=self.random_state) ret_exp.predict_proba = yss[0] if top_labels: labels = np.argsort(yss[0])[-top_labels:] ret_exp.top_labels = list(labels) ret_exp.top_labels.reverse() for label in labels: (ret_exp.intercept[label], ret_exp.local_exp[label], ret_exp.score[label], ret_exp.local_pred[label]) = self.base.explain_instance_with_data( data, yss, distances, label, num_features, model_regressor=model_regressor, feature_selection=self.feature_selection) return ret_exp def __data_labels_distances(self, indexed_string, classifier_fn, num_samples, distance_metric='cosine'): """Generates a neighborhood around a prediction. Generates neighborhood data by randomly removing words from the instance, and predicting with the classifier. Uses cosine distance to compute distances between original and perturbed instances. Args: indexed_string: document (IndexedString) to be explained, classifier_fn: classifier prediction probability function, which takes a string and outputs prediction probabilities. For ScikitClassifier, this is classifier.predict_proba. num_samples: size of the neighborhood to learn the linear model distance_metric: the distance metric to use for sample weighting, defaults to cosine similarity. Returns: A tuple (data, labels, distances), where: data: dense num_samples * K binary matrix, where K is the number of tokens in indexed_string. The first row is the original instance, and thus a row of ones. labels: num_samples * L matrix, where L is the number of target labels distances: cosine distance between the original instance and each perturbed instance (computed in the binary 'data' matrix), times 100. """ def distance_fn(x): return sklearn.metrics.pairwise.pairwise_distances( x, x[0], metric=distance_metric).ravel() * 100 doc_size = indexed_string.num_words() sample = self.random_state.randint(1, doc_size + 1, num_samples - 1) data = np.ones((num_samples, doc_size)) data[0] = np.ones(doc_size) features_range = range(doc_size) inverse_data = [indexed_string.raw_string()] for i, size in enumerate(sample, start=1): inactive = self.random_state.choice(features_range, size, replace=False) data[i, inactive] = 0 inverse_data.append(indexed_string.inverse_removing(inactive)) labels = classifier_fn(inverse_data) distances = distance_fn(sp.sparse.csr_matrix(data)) return data, labels, distances ================================================ FILE: lime/package.json ================================================ { "name": "lime", "version": "1.0.0", "description": "", "main": "main.js", "scripts": { "build": "webpack", "watch": "webpack --watch", "start": "webpack-dev-server --hot --inline", "lint": "eslint js" }, "repository": { "type": "git", "url": "git+https://github.com/marcotcr/lime.git" }, "author": "Marco Tulio Ribeiro ", "license": "TODO", "bugs": { "url": "https://github.com/marcotcr/lime/issues" }, "homepage": "https://github.com/marcotcr/lime#readme", "devDependencies": { "babel-cli": "^6.8.0", "babel-core": "^6.17.0", "babel-eslint": "^6.1.0", "babel-loader": "^6.2.4", "babel-polyfill": "^6.16.0", "babel-preset-es2015": "^6.0.15", "babel-preset-es2015-ie": "^6.6.2", "css-loader": "^0.23.1", "eslint": "^6.6.0", "node-libs-browser": "^0.5.3", "style-loader": "^0.13.1", "webpack": "^1.13.0", "webpack-dev-server": "^1.14.1" }, "dependencies": { "d3": "^3.5.17", "lodash": "^4.11.2" }, "eslintConfig": { "parser": "babel-eslint", "parserOptions": { "ecmaVersion": 6, "sourceType": "module", "ecmaFeatures": { "jsx": true } }, "extends": "eslint:recommended" } } ================================================ FILE: lime/style.css ================================================ .lime { all: initial; } .lime.top_div { display: flex; flex-wrap: wrap; } .lime.predict_proba { width: 245px; } .lime.predicted_value { width: 245px; } .lime.explanation { width: 350px; } .lime.text_div { max-height:300px; flex: 1 0 300px; overflow:scroll; } .lime.table_div { max-height:300px; flex: 1 0 300px; overflow:scroll; } .lime.table_div table { border-collapse: collapse; color: white; border-style: hidden; margin: 0 auto; } ================================================ FILE: lime/submodular_pick.py ================================================ import numpy as np import warnings class SubmodularPick(object): """Class for submodular pick Saves a representative sample of explanation objects using SP-LIME, as well as saving all generated explanations First, a collection of candidate explanations are generated (see explain_instance). From these candidates, num_exps_desired are chosen using submodular pick. (see marcotcr et al paper).""" def __init__(self, explainer, data, predict_fn, method='sample', sample_size=1000, num_exps_desired=5, num_features=10, **kwargs): """ Args: data: a numpy array where each row is a single input into predict_fn predict_fn: prediction function. For classifiers, this should be a function that takes a numpy array and outputs prediction probabilities. For regressors, this takes a numpy array and returns the predictions. For ScikitClassifiers, this is `classifier.predict_proba()`. For ScikitRegressors, this is `regressor.predict()`. The prediction function needs to work on multiple feature vectors (the vectors randomly perturbed from the data_row). method: The method to use to generate candidate explanations method == 'sample' will sample the data uniformly at random. The sample size is given by sample_size. Otherwise if method == 'full' then explanations will be generated for the entire data. l sample_size: The number of instances to explain if method == 'sample' num_exps_desired: The number of explanation objects returned num_features: maximum number of features present in explanation Sets value: sp_explanations: A list of explanation objects that has a high coverage explanations: All the candidate explanations saved for potential future use. """ top_labels = kwargs.get('top_labels', 1) if 'top_labels' in kwargs: del kwargs['top_labels'] # Parse args if method == 'sample': if sample_size > len(data): warnings.warn("""Requested sample size larger than size of input data. Using all data""") sample_size = len(data) all_indices = np.arange(len(data)) np.random.shuffle(all_indices) sample_indices = all_indices[:sample_size] elif method == 'full': sample_indices = np.arange(len(data)) else: raise ValueError('Method must be \'sample\' or \'full\'') # Generate Explanations self.explanations = [] for i in sample_indices: self.explanations.append( explainer.explain_instance( data[i], predict_fn, num_features=num_features, top_labels=top_labels, **kwargs)) # Error handling try: num_exps_desired = int(num_exps_desired) except TypeError: return("Requested number of explanations should be an integer") if num_exps_desired > len(self.explanations): warnings.warn("""Requested number of explanations larger than total number of explanations, returning all explanations instead.""") num_exps_desired = min(num_exps_desired, len(self.explanations)) # Find all the explanation model features used. Defines the dimension d' features_dict = {} feature_iter = 0 for exp in self.explanations: labels = exp.available_labels() if exp.mode == 'classification' else [1] for label in labels: for feature, _ in exp.as_list(label=label): if feature not in features_dict.keys(): features_dict[feature] = (feature_iter) feature_iter += 1 d_prime = len(features_dict.keys()) # Create the n x d' dimensional 'explanation matrix', W W = np.zeros((len(self.explanations), d_prime)) for i, exp in enumerate(self.explanations): labels = exp.available_labels() if exp.mode == 'classification' else [1] for label in labels: for feature, value in exp.as_list(label): W[i, features_dict[feature]] += value # Create the global importance vector, I_j described in the paper importance = np.sum(abs(W), axis=0)**.5 # Now run the SP-LIME greedy algorithm remaining_indices = set(range(len(self.explanations))) V = [] for _ in range(num_exps_desired): best = 0 best_ind = None current = 0 for i in remaining_indices: current = np.dot( (np.sum(abs(W)[V + [i]], axis=0) > 0), importance ) # coverage function if current >= best: best = current best_ind = i V.append(best_ind) remaining_indices -= {best_ind} self.sp_explanations = [self.explanations[i] for i in V] self.V = V ================================================ FILE: lime/test_table.html ================================================
================================================ FILE: lime/tests/__init__.py ================================================ ================================================ FILE: lime/tests/test_discretize.py ================================================ import unittest from unittest import TestCase import numpy as np from sklearn.datasets import load_iris from lime.discretize import QuartileDiscretizer, DecileDiscretizer, EntropyDiscretizer class TestDiscretize(TestCase): def setUp(self): iris = load_iris() self.feature_names = iris.feature_names self.x = iris.data self.y = iris.target def check_random_state_for_discretizer_class(self, DiscretizerClass): # ---------------------------------------------------------------------- # -----------Check if the same random_state produces the same----------- # -------------results for different discretizer instances.------------- # ---------------------------------------------------------------------- discretizer = DiscretizerClass(self.x, [], self.feature_names, self.y, random_state=10) x_1 = discretizer.undiscretize(discretizer.discretize(self.x)) discretizer = DiscretizerClass(self.x, [], self.feature_names, self.y, random_state=10) x_2 = discretizer.undiscretize(discretizer.discretize(self.x)) self.assertEqual((x_1 == x_2).sum(), x_1.shape[0] * x_1.shape[1]) discretizer = DiscretizerClass(self.x, [], self.feature_names, self.y, random_state=np.random.RandomState(10)) x_1 = discretizer.undiscretize(discretizer.discretize(self.x)) discretizer = DiscretizerClass(self.x, [], self.feature_names, self.y, random_state=np.random.RandomState(10)) x_2 = discretizer.undiscretize(discretizer.discretize(self.x)) self.assertEqual((x_1 == x_2).sum(), x_1.shape[0] * x_1.shape[1]) # ---------------------------------------------------------------------- # ---------Check if two different random_state values produces---------- # -------different results for different discretizers instances.-------- # ---------------------------------------------------------------------- discretizer = DiscretizerClass(self.x, [], self.feature_names, self.y, random_state=10) x_1 = discretizer.undiscretize(discretizer.discretize(self.x)) discretizer = DiscretizerClass(self.x, [], self.feature_names, self.y, random_state=20) x_2 = discretizer.undiscretize(discretizer.discretize(self.x)) self.assertFalse((x_1 == x_2).sum() == x_1.shape[0] * x_1.shape[1]) discretizer = DiscretizerClass(self.x, [], self.feature_names, self.y, random_state=np.random.RandomState(10)) x_1 = discretizer.undiscretize(discretizer.discretize(self.x)) discretizer = DiscretizerClass(self.x, [], self.feature_names, self.y, random_state=np.random.RandomState(20)) x_2 = discretizer.undiscretize(discretizer.discretize(self.x)) self.assertFalse((x_1 == x_2).sum() == x_1.shape[0] * x_1.shape[1]) def test_random_state(self): self.check_random_state_for_discretizer_class(QuartileDiscretizer) self.check_random_state_for_discretizer_class(DecileDiscretizer) self.check_random_state_for_discretizer_class(EntropyDiscretizer) def test_feature_names_1(self): self.maxDiff = None discretizer = QuartileDiscretizer(self.x, [], self.feature_names, self.y, random_state=10) self.assertDictEqual( {0: ['sepal length (cm) <= 5.10', '5.10 < sepal length (cm) <= 5.80', '5.80 < sepal length (cm) <= 6.40', 'sepal length (cm) > 6.40'], 1: ['sepal width (cm) <= 2.80', '2.80 < sepal width (cm) <= 3.00', '3.00 < sepal width (cm) <= 3.30', 'sepal width (cm) > 3.30'], 2: ['petal length (cm) <= 1.60', '1.60 < petal length (cm) <= 4.35', '4.35 < petal length (cm) <= 5.10', 'petal length (cm) > 5.10'], 3: ['petal width (cm) <= 0.30', '0.30 < petal width (cm) <= 1.30', '1.30 < petal width (cm) <= 1.80', 'petal width (cm) > 1.80']}, discretizer.names) def test_feature_names_2(self): self.maxDiff = None discretizer = DecileDiscretizer(self.x, [], self.feature_names, self.y, random_state=10) self.assertDictEqual( {0: ['sepal length (cm) <= 4.80', '4.80 < sepal length (cm) <= 5.00', '5.00 < sepal length (cm) <= 5.27', '5.27 < sepal length (cm) <= 5.60', '5.60 < sepal length (cm) <= 5.80', '5.80 < sepal length (cm) <= 6.10', '6.10 < sepal length (cm) <= 6.30', '6.30 < sepal length (cm) <= 6.52', '6.52 < sepal length (cm) <= 6.90', 'sepal length (cm) > 6.90'], 1: ['sepal width (cm) <= 2.50', '2.50 < sepal width (cm) <= 2.70', '2.70 < sepal width (cm) <= 2.80', '2.80 < sepal width (cm) <= 3.00', '3.00 < sepal width (cm) <= 3.10', '3.10 < sepal width (cm) <= 3.20', '3.20 < sepal width (cm) <= 3.40', '3.40 < sepal width (cm) <= 3.61', 'sepal width (cm) > 3.61'], 2: ['petal length (cm) <= 1.40', '1.40 < petal length (cm) <= 1.50', '1.50 < petal length (cm) <= 1.70', '1.70 < petal length (cm) <= 3.90', '3.90 < petal length (cm) <= 4.35', '4.35 < petal length (cm) <= 4.64', '4.64 < petal length (cm) <= 5.00', '5.00 < petal length (cm) <= 5.32', '5.32 < petal length (cm) <= 5.80', 'petal length (cm) > 5.80'], 3: ['petal width (cm) <= 0.20', '0.20 < petal width (cm) <= 0.40', '0.40 < petal width (cm) <= 1.16', '1.16 < petal width (cm) <= 1.30', '1.30 < petal width (cm) <= 1.50', '1.50 < petal width (cm) <= 1.80', '1.80 < petal width (cm) <= 1.90', '1.90 < petal width (cm) <= 2.20', 'petal width (cm) > 2.20']}, discretizer.names) def test_feature_names_3(self): self.maxDiff = None discretizer = EntropyDiscretizer(self.x, [], self.feature_names, self.y, random_state=10) self.assertDictEqual( {0: ['sepal length (cm) <= 4.85', '4.85 < sepal length (cm) <= 5.45', '5.45 < sepal length (cm) <= 5.55', '5.55 < sepal length (cm) <= 5.85', '5.85 < sepal length (cm) <= 6.15', '6.15 < sepal length (cm) <= 7.05', 'sepal length (cm) > 7.05'], 1: ['sepal width (cm) <= 2.45', '2.45 < sepal width (cm) <= 2.95', '2.95 < sepal width (cm) <= 3.05', '3.05 < sepal width (cm) <= 3.35', '3.35 < sepal width (cm) <= 3.45', '3.45 < sepal width (cm) <= 3.55', 'sepal width (cm) > 3.55'], 2: ['petal length (cm) <= 2.45', '2.45 < petal length (cm) <= 4.45', '4.45 < petal length (cm) <= 4.75', '4.75 < petal length (cm) <= 5.15', 'petal length (cm) > 5.15'], 3: ['petal width (cm) <= 0.80', '0.80 < petal width (cm) <= 1.35', '1.35 < petal width (cm) <= 1.75', '1.75 < petal width (cm) <= 1.85', 'petal width (cm) > 1.85']}, discretizer.names) if __name__ == '__main__': unittest.main() ================================================ FILE: lime/tests/test_generic_utils.py ================================================ import unittest import sys from lime.utils.generic_utils import has_arg class TestGenericUtils(unittest.TestCase): def test_has_arg(self): # fn is callable / is not callable class FooNotCallable: def __init__(self, word): self.message = word class FooCallable: def __init__(self, word): self.message = word def __call__(self, message): return message def positional_argument_call(self, arg1): return self.message def multiple_positional_arguments_call(self, *args): res = [] for a in args: res.append(a) return res def keyword_argument_call(self, filter_=True): res = self.message if filter_: res = 'KO' return res def multiple_keyword_arguments_call(self, arg1='1', arg2='2'): return self.message + arg1 + arg2 def undefined_keyword_arguments_call(self, **kwargs): res = self.message for a in kwargs: res = res + a return a foo_callable = FooCallable('OK') self.assertTrue(has_arg(foo_callable, 'message')) if sys.version_info < (3,): foo_not_callable = FooNotCallable('KO') self.assertFalse(has_arg(foo_not_callable, 'message')) elif sys.version_info < (3, 6): with self.assertRaises(TypeError): foo_not_callable = FooNotCallable('KO') has_arg(foo_not_callable, 'message') # Python 2, argument in / not in valid arguments / keyword arguments if sys.version_info < (3,): self.assertFalse(has_arg(foo_callable, 'invalid_arg')) self.assertTrue(has_arg(foo_callable.positional_argument_call, 'arg1')) self.assertFalse(has_arg(foo_callable.multiple_positional_arguments_call, 'argX')) self.assertFalse(has_arg(foo_callable.keyword_argument_call, 'argX')) self.assertTrue(has_arg(foo_callable.keyword_argument_call, 'filter_')) self.assertTrue(has_arg(foo_callable.multiple_keyword_arguments_call, 'arg2')) self.assertFalse(has_arg(foo_callable.multiple_keyword_arguments_call, 'arg3')) self.assertFalse(has_arg(foo_callable.undefined_keyword_arguments_call, 'argX')) # Python 3, argument in / not in valid arguments / keyword arguments elif sys.version_info < (3, 6): self.assertFalse(has_arg(foo_callable, 'invalid_arg')) self.assertTrue(has_arg(foo_callable.positional_argument_call, 'arg1')) self.assertFalse(has_arg(foo_callable.multiple_positional_arguments_call, 'argX')) self.assertFalse(has_arg(foo_callable.keyword_argument_call, 'argX')) self.assertTrue(has_arg(foo_callable.keyword_argument_call, 'filter_')) self.assertTrue(has_arg(foo_callable.multiple_keyword_arguments_call, 'arg2')) self.assertFalse(has_arg(foo_callable.multiple_keyword_arguments_call, 'arg3')) self.assertFalse(has_arg(foo_callable.undefined_keyword_arguments_call, 'argX')) else: self.assertFalse(has_arg(foo_callable, 'invalid_arg')) self.assertTrue(has_arg(foo_callable.positional_argument_call, 'arg1')) self.assertFalse(has_arg(foo_callable.multiple_positional_arguments_call, 'argX')) self.assertFalse(has_arg(foo_callable.keyword_argument_call, 'argX')) self.assertTrue(has_arg(foo_callable.keyword_argument_call, 'filter_')) self.assertTrue(has_arg(foo_callable.multiple_keyword_arguments_call, 'arg2')) self.assertFalse(has_arg(foo_callable.multiple_keyword_arguments_call, 'arg3')) self.assertFalse(has_arg(foo_callable.undefined_keyword_arguments_call, 'argX')) # argname is None self.assertFalse(has_arg(foo_callable, None)) if __name__ == '__main__': unittest.main() ================================================ FILE: lime/tests/test_lime_tabular.py ================================================ import unittest import numpy as np import collections import sklearn # noqa import sklearn.datasets import sklearn.ensemble import sklearn.linear_model # noqa from numpy.testing import assert_array_equal from sklearn.datasets import load_iris, make_classification, make_multilabel_classification from sklearn.ensemble import RandomForestClassifier from sklearn.linear_model import LinearRegression from lime.discretize import QuartileDiscretizer, DecileDiscretizer, EntropyDiscretizer try: from sklearn.model_selection import train_test_split except ImportError: # Deprecated in scikit-learn version 0.18, removed in 0.20 from sklearn.cross_validation import train_test_split from lime.lime_tabular import LimeTabularExplainer class TestLimeTabular(unittest.TestCase): def setUp(self): iris = load_iris() self.feature_names = iris.feature_names self.target_names = iris.target_names (self.train, self.test, self.labels_train, self.labels_test) = train_test_split(iris.data, iris.target, train_size=0.80) def test_lime_explainer_good_regressor(self): np.random.seed(1) rf = RandomForestClassifier(n_estimators=500) rf.fit(self.train, self.labels_train) i = np.random.randint(0, self.test.shape[0]) explainer = LimeTabularExplainer(self.train, mode="classification", feature_names=self.feature_names, class_names=self.target_names, discretize_continuous=True) exp = explainer.explain_instance(self.test[i], rf.predict_proba, num_features=2, model_regressor=LinearRegression()) self.assertIsNotNone(exp) keys = [x[0] for x in exp.as_list()] self.assertEqual(1, sum([1 if 'petal width' in x else 0 for x in keys]), "Petal Width is a major feature") self.assertEqual(1, sum([1 if 'petal length' in x else 0 for x in keys]), "Petal Length is a major feature") def test_lime_explainer_good_regressor_synthetic_data(self): X, y = make_classification(n_samples=1000, n_features=20, n_informative=2, n_redundant=2, random_state=10) rf = RandomForestClassifier(n_estimators=500) rf.fit(X, y) instance = np.random.randint(0, X.shape[0]) feature_names = ["feature" + str(i) for i in range(20)] explainer = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True) exp = explainer.explain_instance(X[instance], rf.predict_proba) self.assertIsNotNone(exp) self.assertEqual(10, len(exp.as_list())) def test_lime_explainer_sparse_synthetic_data(self): n_features = 20 X, y = make_multilabel_classification(n_samples=100, sparse=True, n_features=n_features, n_classes=1, n_labels=2) rf = RandomForestClassifier(n_estimators=500) rf.fit(X, y) instance = np.random.randint(0, X.shape[0]) feature_names = ["feature" + str(i) for i in range(n_features)] explainer = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True) exp = explainer.explain_instance(X[instance], rf.predict_proba) self.assertIsNotNone(exp) self.assertEqual(10, len(exp.as_list())) def test_lime_explainer_no_regressor(self): np.random.seed(1) rf = RandomForestClassifier(n_estimators=500) rf.fit(self.train, self.labels_train) i = np.random.randint(0, self.test.shape[0]) explainer = LimeTabularExplainer(self.train, feature_names=self.feature_names, class_names=self.target_names, discretize_continuous=True) exp = explainer.explain_instance(self.test[i], rf.predict_proba, num_features=2) self.assertIsNotNone(exp) keys = [x[0] for x in exp.as_list()] self.assertEqual(1, sum([1 if 'petal width' in x else 0 for x in keys]), "Petal Width is a major feature") self.assertEqual(1, sum([1 if 'petal length' in x else 0 for x in keys]), "Petal Length is a major feature") def test_lime_explainer_entropy_discretizer(self): np.random.seed(1) rf = RandomForestClassifier(n_estimators=500) rf.fit(self.train, self.labels_train) i = np.random.randint(0, self.test.shape[0]) explainer = LimeTabularExplainer(self.train, feature_names=self.feature_names, class_names=self.target_names, training_labels=self.labels_train, discretize_continuous=True, discretizer='entropy') exp = explainer.explain_instance(self.test[i], rf.predict_proba, num_features=2) self.assertIsNotNone(exp) keys = [x[0] for x in exp.as_list()] print(keys) self.assertEqual(1, sum([1 if 'petal width' in x else 0 for x in keys]), "Petal Width is a major feature") self.assertEqual(1, sum([1 if 'petal length' in x else 0 for x in keys]), "Petal Length is a major feature") def test_lime_tabular_explainer_equal_random_state(self): X, y = make_classification(n_samples=1000, n_features=20, n_informative=2, n_redundant=2, random_state=10) rf = RandomForestClassifier(n_estimators=500, random_state=10) rf.fit(X, y) instance = np.random.RandomState(10).randint(0, X.shape[0]) feature_names = ["feature" + str(i) for i in range(20)] # ---------------------------------------------------------------------- # -------------------------Quartile Discretizer------------------------- # ---------------------------------------------------------------------- discretizer = QuartileDiscretizer(X, [], feature_names, y, random_state=10) explainer_1 = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True, discretizer=discretizer, random_state=10) exp_1 = explainer_1.explain_instance(X[instance], rf.predict_proba, num_samples=500) discretizer = QuartileDiscretizer(X, [], feature_names, y, random_state=10) explainer_2 = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True, discretizer=discretizer, random_state=10) exp_2 = explainer_2.explain_instance(X[instance], rf.predict_proba, num_samples=500) self.assertDictEqual(exp_1.as_map(), exp_2.as_map()) # ---------------------------------------------------------------------- # --------------------------Decile Discretizer-------------------------- # ---------------------------------------------------------------------- discretizer = DecileDiscretizer(X, [], feature_names, y, random_state=10) explainer_1 = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True, discretizer=discretizer, random_state=10) exp_1 = explainer_1.explain_instance(X[instance], rf.predict_proba, num_samples=500) discretizer = DecileDiscretizer(X, [], feature_names, y, random_state=10) explainer_2 = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True, discretizer=discretizer, random_state=10) exp_2 = explainer_2.explain_instance(X[instance], rf.predict_proba, num_samples=500) self.assertDictEqual(exp_1.as_map(), exp_2.as_map()) # ---------------------------------------------------------------------- # -------------------------Entropy Discretizer-------------------------- # ---------------------------------------------------------------------- discretizer = EntropyDiscretizer(X, [], feature_names, y, random_state=10) explainer_1 = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True, discretizer=discretizer, random_state=10) exp_1 = explainer_1.explain_instance(X[instance], rf.predict_proba, num_samples=500) discretizer = EntropyDiscretizer(X, [], feature_names, y, random_state=10) explainer_2 = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True, discretizer=discretizer, random_state=10) exp_2 = explainer_2.explain_instance(X[instance], rf.predict_proba, num_samples=500) self.assertDictEqual(exp_1.as_map(), exp_2.as_map()) def test_lime_tabular_explainer_not_equal_random_state(self): X, y = make_classification(n_samples=1000, n_features=20, n_informative=2, n_redundant=2, random_state=10) rf = RandomForestClassifier(n_estimators=500, random_state=10) rf.fit(X, y) instance = np.random.RandomState(10).randint(0, X.shape[0]) feature_names = ["feature" + str(i) for i in range(20)] # ---------------------------------------------------------------------- # -------------------------Quartile Discretizer------------------------- # ---------------------------------------------------------------------- # ---------------------------------[1]---------------------------------- discretizer = QuartileDiscretizer(X, [], feature_names, y, random_state=20) explainer_1 = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True, discretizer=discretizer, random_state=10) exp_1 = explainer_1.explain_instance(X[instance], rf.predict_proba, num_samples=500) discretizer = QuartileDiscretizer(X, [], feature_names, y, random_state=10) explainer_2 = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True, discretizer=discretizer, random_state=10) exp_2 = explainer_2.explain_instance(X[instance], rf.predict_proba, num_samples=500) self.assertTrue(exp_1.as_map() != exp_2.as_map()) # ---------------------------------[2]---------------------------------- discretizer = QuartileDiscretizer(X, [], feature_names, y, random_state=20) explainer_1 = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True, discretizer=discretizer, random_state=20) exp_1 = explainer_1.explain_instance(X[instance], rf.predict_proba, num_samples=500) discretizer = QuartileDiscretizer(X, [], feature_names, y, random_state=10) explainer_2 = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True, discretizer=discretizer, random_state=10) exp_2 = explainer_2.explain_instance(X[instance], rf.predict_proba, num_samples=500) self.assertTrue(exp_1.as_map() != exp_2.as_map()) # ---------------------------------[3]---------------------------------- discretizer = QuartileDiscretizer(X, [], feature_names, y, random_state=20) explainer_1 = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True, discretizer=discretizer, random_state=20) exp_1 = explainer_1.explain_instance(X[instance], rf.predict_proba, num_samples=500) discretizer = QuartileDiscretizer(X, [], feature_names, y, random_state=20) explainer_2 = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True, discretizer=discretizer, random_state=10) exp_2 = explainer_2.explain_instance(X[instance], rf.predict_proba, num_samples=500) self.assertTrue(exp_1.as_map() != exp_2.as_map()) # ---------------------------------[4]---------------------------------- discretizer = QuartileDiscretizer(X, [], feature_names, y, random_state=20) explainer_1 = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True, discretizer=discretizer, random_state=20) exp_1 = explainer_1.explain_instance(X[instance], rf.predict_proba, num_samples=500) discretizer = QuartileDiscretizer(X, [], feature_names, y, random_state=20) explainer_2 = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True, discretizer=discretizer, random_state=20) exp_2 = explainer_2.explain_instance(X[instance], rf.predict_proba, num_samples=500) self.assertFalse(exp_1.as_map() != exp_2.as_map()) # ---------------------------------------------------------------------- # --------------------------Decile Discretizer-------------------------- # ---------------------------------------------------------------------- # ---------------------------------[1]---------------------------------- discretizer = DecileDiscretizer(X, [], feature_names, y, random_state=20) explainer_1 = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True, discretizer=discretizer, random_state=10) exp_1 = explainer_1.explain_instance(X[instance], rf.predict_proba, num_samples=500) discretizer = DecileDiscretizer(X, [], feature_names, y, random_state=10) explainer_2 = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True, discretizer=discretizer, random_state=10) exp_2 = explainer_2.explain_instance(X[instance], rf.predict_proba, num_samples=500) self.assertTrue(exp_1.as_map() != exp_2.as_map()) # ---------------------------------[2]---------------------------------- discretizer = DecileDiscretizer(X, [], feature_names, y, random_state=20) explainer_1 = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True, discretizer=discretizer, random_state=20) exp_1 = explainer_1.explain_instance(X[instance], rf.predict_proba, num_samples=500) discretizer = DecileDiscretizer(X, [], feature_names, y, random_state=10) explainer_2 = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True, discretizer=discretizer, random_state=10) exp_2 = explainer_2.explain_instance(X[instance], rf.predict_proba, num_samples=500) self.assertTrue(exp_1.as_map() != exp_2.as_map()) # ---------------------------------[3]---------------------------------- discretizer = DecileDiscretizer(X, [], feature_names, y, random_state=20) explainer_1 = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True, discretizer=discretizer, random_state=20) exp_1 = explainer_1.explain_instance(X[instance], rf.predict_proba, num_samples=500) discretizer = DecileDiscretizer(X, [], feature_names, y, random_state=20) explainer_2 = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True, discretizer=discretizer, random_state=10) exp_2 = explainer_2.explain_instance(X[instance], rf.predict_proba, num_samples=500) self.assertTrue(exp_1.as_map() != exp_2.as_map()) # ---------------------------------[4]---------------------------------- discretizer = DecileDiscretizer(X, [], feature_names, y, random_state=20) explainer_1 = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True, discretizer=discretizer, random_state=20) exp_1 = explainer_1.explain_instance(X[instance], rf.predict_proba, num_samples=500) discretizer = DecileDiscretizer(X, [], feature_names, y, random_state=20) explainer_2 = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True, discretizer=discretizer, random_state=20) exp_2 = explainer_2.explain_instance(X[instance], rf.predict_proba, num_samples=500) self.assertFalse(exp_1.as_map() != exp_2.as_map()) # ---------------------------------------------------------------------- # --------------------------Entropy Discretizer------------------------- # ---------------------------------------------------------------------- # ---------------------------------[1]---------------------------------- discretizer = EntropyDiscretizer(X, [], feature_names, y, random_state=20) explainer_1 = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True, discretizer=discretizer, random_state=10) exp_1 = explainer_1.explain_instance(X[instance], rf.predict_proba, num_samples=500) discretizer = EntropyDiscretizer(X, [], feature_names, y, random_state=10) explainer_2 = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True, discretizer=discretizer, random_state=10) exp_2 = explainer_2.explain_instance(X[instance], rf.predict_proba, num_samples=500) self.assertTrue(exp_1.as_map() != exp_2.as_map()) # ---------------------------------[2]---------------------------------- discretizer = EntropyDiscretizer(X, [], feature_names, y, random_state=20) explainer_1 = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True, discretizer=discretizer, random_state=20) exp_1 = explainer_1.explain_instance(X[instance], rf.predict_proba, num_samples=500) discretizer = EntropyDiscretizer(X, [], feature_names, y, random_state=10) explainer_2 = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True, discretizer=discretizer, random_state=10) exp_2 = explainer_2.explain_instance(X[instance], rf.predict_proba, num_samples=500) self.assertTrue(exp_1.as_map() != exp_2.as_map()) # ---------------------------------[3]---------------------------------- discretizer = EntropyDiscretizer(X, [], feature_names, y, random_state=20) explainer_1 = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True, discretizer=discretizer, random_state=20) exp_1 = explainer_1.explain_instance(X[instance], rf.predict_proba, num_samples=500) discretizer = EntropyDiscretizer(X, [], feature_names, y, random_state=20) explainer_2 = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True, discretizer=discretizer, random_state=10) exp_2 = explainer_2.explain_instance(X[instance], rf.predict_proba, num_samples=500) self.assertTrue(exp_1.as_map() != exp_2.as_map()) # ---------------------------------[4]---------------------------------- discretizer = EntropyDiscretizer(X, [], feature_names, y, random_state=20) explainer_1 = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True, discretizer=discretizer, random_state=20) exp_1 = explainer_1.explain_instance(X[instance], rf.predict_proba, num_samples=500) discretizer = EntropyDiscretizer(X, [], feature_names, y, random_state=20) explainer_2 = LimeTabularExplainer(X, feature_names=feature_names, discretize_continuous=True, discretizer=discretizer, random_state=20) exp_2 = explainer_2.explain_instance(X[instance], rf.predict_proba, num_samples=500) self.assertFalse(exp_1.as_map() != exp_2.as_map()) def testFeatureNamesAndCategoricalFeats(self): training_data = np.array([[0., 1.], [1., 0.]]) explainer = LimeTabularExplainer(training_data=training_data) self.assertEqual(explainer.feature_names, ['0', '1']) self.assertEqual(explainer.categorical_features, [0, 1]) explainer = LimeTabularExplainer( training_data=training_data, feature_names=np.array(['one', 'two']) ) self.assertEqual(explainer.feature_names, ['one', 'two']) explainer = LimeTabularExplainer( training_data=training_data, categorical_features=np.array([0]), discretize_continuous=False ) self.assertEqual(explainer.categorical_features, [0]) def testFeatureValues(self): training_data = np.array([ [0, 0, 2], [1, 1, 0], [0, 2, 2], [1, 3, 0] ]) explainer = LimeTabularExplainer( training_data=training_data, categorical_features=[0, 1, 2] ) self.assertEqual(set(explainer.feature_values[0]), {0, 1}) self.assertEqual(set(explainer.feature_values[1]), {0, 1, 2, 3}) self.assertEqual(set(explainer.feature_values[2]), {0, 2}) assert_array_equal(explainer.feature_frequencies[0], np.array([.5, .5])) assert_array_equal(explainer.feature_frequencies[1], np.array([.25, .25, .25, .25])) assert_array_equal(explainer.feature_frequencies[2], np.array([.5, .5])) def test_lime_explainer_with_data_stats(self): np.random.seed(1) rf = RandomForestClassifier(n_estimators=500) rf.fit(self.train, self.labels_train) i = np.random.randint(0, self.test.shape[0]) # Generate stats using a quartile descritizer descritizer = QuartileDiscretizer(self.train, [], self.feature_names, self.target_names, random_state=20) d_means = descritizer.means d_stds = descritizer.stds d_mins = descritizer.mins d_maxs = descritizer.maxs d_bins = descritizer.bins(self.train, self.target_names) # Compute feature values and frequencies of all columns cat_features = np.arange(self.train.shape[1]) discretized_training_data = descritizer.discretize(self.train) feature_values = {} feature_frequencies = {} for feature in cat_features: column = discretized_training_data[:, feature] feature_count = collections.Counter(column) values, frequencies = map(list, zip(*(feature_count.items()))) feature_values[feature] = values feature_frequencies[feature] = frequencies # Convert bins to list from array d_bins_revised = {} index = 0 for bin in d_bins: d_bins_revised[index] = bin.tolist() index = index+1 # Descritized stats data_stats = {} data_stats["means"] = d_means data_stats["stds"] = d_stds data_stats["maxs"] = d_maxs data_stats["mins"] = d_mins data_stats["bins"] = d_bins_revised data_stats["feature_values"] = feature_values data_stats["feature_frequencies"] = feature_frequencies data = np.zeros((2, len(self.feature_names))) explainer = LimeTabularExplainer( data, feature_names=self.feature_names, random_state=10, training_data_stats=data_stats, training_labels=self.target_names) exp = explainer.explain_instance(self.test[i], rf.predict_proba, num_features=2, model_regressor=LinearRegression()) self.assertIsNotNone(exp) keys = [x[0] for x in exp.as_list()] self.assertEqual(1, sum([1 if 'petal width' in x else 0 for x in keys]), "Petal Width is a major feature") self.assertEqual(1, sum([1 if 'petal length' in x else 0 for x in keys]), "Petal Length is a major feature") if __name__ == '__main__': unittest.main() ================================================ FILE: lime/tests/test_lime_text.py ================================================ import re import unittest import sklearn # noqa from sklearn.datasets import fetch_20newsgroups from sklearn.feature_extraction.text import TfidfVectorizer from sklearn.metrics import f1_score from sklearn.naive_bayes import MultinomialNB from sklearn.pipeline import make_pipeline import numpy as np from lime.lime_text import LimeTextExplainer from lime.lime_text import IndexedCharacters, IndexedString class TestLimeText(unittest.TestCase): def test_lime_text_explainer_good_regressor(self): categories = ['alt.atheism', 'soc.religion.christian'] newsgroups_train = fetch_20newsgroups(subset='train', categories=categories) newsgroups_test = fetch_20newsgroups(subset='test', categories=categories) class_names = ['atheism', 'christian'] vectorizer = TfidfVectorizer(lowercase=False) train_vectors = vectorizer.fit_transform(newsgroups_train.data) test_vectors = vectorizer.transform(newsgroups_test.data) nb = MultinomialNB(alpha=.01) nb.fit(train_vectors, newsgroups_train.target) pred = nb.predict(test_vectors) f1_score(newsgroups_test.target, pred, average='weighted') c = make_pipeline(vectorizer, nb) explainer = LimeTextExplainer(class_names=class_names) idx = 83 exp = explainer.explain_instance(newsgroups_test.data[idx], c.predict_proba, num_features=6) self.assertIsNotNone(exp) self.assertEqual(6, len(exp.as_list())) def test_lime_text_tabular_equal_random_state(self): categories = ['alt.atheism', 'soc.religion.christian'] newsgroups_train = fetch_20newsgroups(subset='train', categories=categories) newsgroups_test = fetch_20newsgroups(subset='test', categories=categories) class_names = ['atheism', 'christian'] vectorizer = TfidfVectorizer(lowercase=False) train_vectors = vectorizer.fit_transform(newsgroups_train.data) test_vectors = vectorizer.transform(newsgroups_test.data) nb = MultinomialNB(alpha=.01) nb.fit(train_vectors, newsgroups_train.target) pred = nb.predict(test_vectors) f1_score(newsgroups_test.target, pred, average='weighted') c = make_pipeline(vectorizer, nb) explainer = LimeTextExplainer(class_names=class_names, random_state=10) exp_1 = explainer.explain_instance(newsgroups_test.data[83], c.predict_proba, num_features=6) explainer = LimeTextExplainer(class_names=class_names, random_state=10) exp_2 = explainer.explain_instance(newsgroups_test.data[83], c.predict_proba, num_features=6) self.assertTrue(exp_1.as_map() == exp_2.as_map()) def test_lime_text_tabular_not_equal_random_state(self): categories = ['alt.atheism', 'soc.religion.christian'] newsgroups_train = fetch_20newsgroups(subset='train', categories=categories) newsgroups_test = fetch_20newsgroups(subset='test', categories=categories) class_names = ['atheism', 'christian'] vectorizer = TfidfVectorizer(lowercase=False) train_vectors = vectorizer.fit_transform(newsgroups_train.data) test_vectors = vectorizer.transform(newsgroups_test.data) nb = MultinomialNB(alpha=.01) nb.fit(train_vectors, newsgroups_train.target) pred = nb.predict(test_vectors) f1_score(newsgroups_test.target, pred, average='weighted') c = make_pipeline(vectorizer, nb) explainer = LimeTextExplainer( class_names=class_names, random_state=10) exp_1 = explainer.explain_instance(newsgroups_test.data[83], c.predict_proba, num_features=6) explainer = LimeTextExplainer( class_names=class_names, random_state=20) exp_2 = explainer.explain_instance(newsgroups_test.data[83], c.predict_proba, num_features=6) self.assertFalse(exp_1.as_map() == exp_2.as_map()) def test_indexed_characters_bow(self): s = 'Please, take your time' inverse_vocab = ['P', 'l', 'e', 'a', 's', ',', ' ', 't', 'k', 'y', 'o', 'u', 'r', 'i', 'm'] positions = [[0], [1], [2, 5, 11, 21], [3, 9], [4], [6], [7, 12, 17], [8, 18], [10], [13], [14], [15], [16], [19], [20]] ic = IndexedCharacters(s) self.assertTrue(np.array_equal(ic.as_np, np.array(list(s)))) self.assertTrue(np.array_equal(ic.string_start, np.arange(len(s)))) self.assertTrue(ic.inverse_vocab == inverse_vocab) self.assertTrue(ic.positions == positions) def test_indexed_characters_not_bow(self): s = 'Please, take your time' ic = IndexedCharacters(s, bow=False) self.assertTrue(np.array_equal(ic.as_np, np.array(list(s)))) self.assertTrue(np.array_equal(ic.string_start, np.arange(len(s)))) self.assertTrue(ic.inverse_vocab == list(s)) self.assertTrue(np.array_equal(ic.positions, np.arange(len(s)))) def test_indexed_string_regex(self): s = 'Please, take your time. Please' tokenized_string = np.array( ['Please', ', ', 'take', ' ', 'your', ' ', 'time', '. ', 'Please']) inverse_vocab = ['Please', 'take', 'your', 'time'] start_positions = [0, 6, 8, 12, 13, 17, 18, 22, 24] positions = [[0, 8], [2], [4], [6]] indexed_string = IndexedString(s) self.assertTrue(np.array_equal(indexed_string.as_np, tokenized_string)) self.assertTrue(np.array_equal(indexed_string.string_start, start_positions)) self.assertTrue(indexed_string.inverse_vocab == inverse_vocab) self.assertTrue(np.array_equal(indexed_string.positions, positions)) def test_indexed_string_callable(self): s = 'aabbccddaa' def tokenizer(string): return [string[i] + string[i + 1] for i in range(0, len(string) - 1, 2)] tokenized_string = np.array(['aa', 'bb', 'cc', 'dd', 'aa']) inverse_vocab = ['aa', 'bb', 'cc', 'dd'] start_positions = [0, 2, 4, 6, 8] positions = [[0, 4], [1], [2], [3]] indexed_string = IndexedString(s, tokenizer) self.assertTrue(np.array_equal(indexed_string.as_np, tokenized_string)) self.assertTrue(np.array_equal(indexed_string.string_start, start_positions)) self.assertTrue(indexed_string.inverse_vocab == inverse_vocab) self.assertTrue(np.array_equal(indexed_string.positions, positions)) def test_indexed_string_inverse_removing_tokenizer(self): s = 'This is a good movie. This, it is a great movie.' def tokenizer(string): return re.split(r'(?:\W+)|$', string) indexed_string = IndexedString(s, tokenizer) self.assertEqual(s, indexed_string.inverse_removing([])) def test_indexed_string_inverse_removing_regex(self): s = 'This is a good movie. This is a great movie' indexed_string = IndexedString(s) self.assertEqual(s, indexed_string.inverse_removing([])) if __name__ == '__main__': unittest.main() ================================================ FILE: lime/tests/test_scikit_image.py ================================================ import unittest from lime.wrappers.scikit_image import BaseWrapper from lime.wrappers.scikit_image import SegmentationAlgorithm from skimage.segmentation import quickshift from skimage.data import chelsea from skimage.util import img_as_float import numpy as np class TestBaseWrapper(unittest.TestCase): def test_base_wrapper(self): obj_with_params = BaseWrapper(a=10, b='message') obj_without_params = BaseWrapper() def foo_fn(): return 'bar' obj_with_fn = BaseWrapper(foo_fn) self.assertEqual(obj_with_params.target_params, {'a': 10, 'b': 'message'}) self.assertEqual(obj_without_params.target_params, {}) self.assertEqual(obj_with_fn.target_fn(), 'bar') def test__check_params(self): def bar_fn(a): return str(a) class Pipo(): def __init__(self): self.name = 'pipo' def __call__(self, message): return message pipo = Pipo() obj_with_valid_fn = BaseWrapper(bar_fn, a=10, b='message') obj_with_valid_callable_fn = BaseWrapper(pipo, c=10, d='message') obj_with_invalid_fn = BaseWrapper([1, 2, 3], fn_name='invalid') # target_fn is not a callable or function/method with self.assertRaises(AttributeError): obj_with_invalid_fn._check_params('fn_name') # parameters is not in target_fn args with self.assertRaises(ValueError): obj_with_valid_fn._check_params(['c']) obj_with_valid_callable_fn._check_params(['e']) # params is in target_fn args try: obj_with_valid_fn._check_params(['a']) obj_with_valid_callable_fn._check_params(['message']) except Exception: self.fail("_check_params() raised an unexpected exception") # params is not a dict or list with self.assertRaises(TypeError): obj_with_valid_fn._check_params(None) with self.assertRaises(TypeError): obj_with_valid_fn._check_params('param_name') def test_set_params(self): class Pipo(): def __init__(self): self.name = 'pipo' def __call__(self, message): return message pipo = Pipo() obj = BaseWrapper(pipo) # argument is set accordingly obj.set_params(message='OK') self.assertEqual(obj.target_params, {'message': 'OK'}) self.assertEqual(obj.target_fn(**obj.target_params), 'OK') # invalid argument is passed try: obj = BaseWrapper(Pipo()) obj.set_params(invalid='KO') except Exception: self.assertEqual(obj.target_params, {}) def test_filter_params(self): # right arguments are kept and wrong dismmissed def baz_fn(a, b, c=True): if c: return a + b else: return a obj_ = BaseWrapper(baz_fn, a=10, b=100, d=1000) self.assertEqual(obj_.filter_params(baz_fn), {'a': 10, 'b': 100}) # target_params is overriden using 'override' argument self.assertEqual(obj_.filter_params(baz_fn, override={'c': False}), {'a': 10, 'b': 100, 'c': False}) class TestSegmentationAlgorithm(unittest.TestCase): def test_instanciate_segmentation_algorithm(self): img = img_as_float(chelsea()[::2, ::2]) # wrapped functions provide the same result fn = SegmentationAlgorithm('quickshift', kernel_size=3, max_dist=6, ratio=0.5, random_seed=133) fn_result = fn(img) original_result = quickshift(img, kernel_size=3, max_dist=6, ratio=0.5, random_seed=133) # same segments self.assertTrue(np.array_equal(fn_result, original_result)) def test_instanciate_slic(self): pass def test_instanciate_felzenszwalb(self): pass if __name__ == '__main__': unittest.main() ================================================ FILE: lime/utils/__init__.py ================================================ ================================================ FILE: lime/utils/generic_utils.py ================================================ import sys import inspect import types def has_arg(fn, arg_name): """Checks if a callable accepts a given keyword argument. Args: fn: callable to inspect arg_name: string, keyword argument name to check Returns: bool, whether `fn` accepts a `arg_name` keyword argument. """ if sys.version_info < (3,): if isinstance(fn, types.FunctionType) or isinstance(fn, types.MethodType): arg_spec = inspect.getargspec(fn) else: try: arg_spec = inspect.getargspec(fn.__call__) except AttributeError: return False return (arg_name in arg_spec.args) elif sys.version_info < (3, 6): arg_spec = inspect.getfullargspec(fn) return (arg_name in arg_spec.args or arg_name in arg_spec.kwonlyargs) else: try: signature = inspect.signature(fn) except ValueError: # handling Cython signature = inspect.signature(fn.__call__) parameter = signature.parameters.get(arg_name) if parameter is None: return False return (parameter.kind in (inspect.Parameter.POSITIONAL_OR_KEYWORD, inspect.Parameter.KEYWORD_ONLY)) ================================================ FILE: lime/webpack.config.js ================================================ var path = require('path'); var webpack = require('webpack'); module.exports = { entry: './js/main.js', output: { path: __dirname, filename: 'bundle.js', library: 'lime' }, module: { loaders: [ { loader: 'babel-loader', test: path.join(__dirname, 'js'), query: { presets: 'es2015-ie', }, }, { test: /\.css$/, loaders: ['style-loader', 'css-loader'], } ] }, plugins: [ // Avoid publishing files when compilation fails new webpack.NoErrorsPlugin() ], stats: { // Nice colored output colors: true }, // Create Sourcemaps for the bundle devtool: 'source-map', }; ================================================ FILE: lime/wrappers/__init__.py ================================================ ================================================ FILE: lime/wrappers/scikit_image.py ================================================ import types from lime.utils.generic_utils import has_arg from skimage.segmentation import felzenszwalb, slic, quickshift class BaseWrapper(object): """Base class for LIME Scikit-Image wrapper Args: target_fn: callable function or class instance target_params: dict, parameters to pass to the target_fn 'target_params' takes parameters required to instanciate the desired Scikit-Image class/model """ def __init__(self, target_fn=None, **target_params): self.target_fn = target_fn self.target_params = target_params def _check_params(self, parameters): """Checks for mistakes in 'parameters' Args : parameters: dict, parameters to be checked Raises : ValueError: if any parameter is not a valid argument for the target function or the target function is not defined TypeError: if argument parameters is not iterable """ a_valid_fn = [] if self.target_fn is None: if callable(self): a_valid_fn.append(self.__call__) else: raise TypeError('invalid argument: tested object is not callable,\ please provide a valid target_fn') elif isinstance(self.target_fn, types.FunctionType) \ or isinstance(self.target_fn, types.MethodType): a_valid_fn.append(self.target_fn) else: a_valid_fn.append(self.target_fn.__call__) if not isinstance(parameters, str): for p in parameters: for fn in a_valid_fn: if has_arg(fn, p): pass else: raise ValueError('{} is not a valid parameter'.format(p)) else: raise TypeError('invalid argument: list or dictionnary expected') def set_params(self, **params): """Sets the parameters of this estimator. Args: **params: Dictionary of parameter names mapped to their values. Raises : ValueError: if any parameter is not a valid argument for the target function """ self._check_params(params) self.target_params = params def filter_params(self, fn, override=None): """Filters `target_params` and return those in `fn`'s arguments. Args: fn : arbitrary function override: dict, values to override target_params Returns: result : dict, dictionary containing variables in both target_params and fn's arguments. """ override = override or {} result = {} for name, value in self.target_params.items(): if has_arg(fn, name): result.update({name: value}) result.update(override) return result class SegmentationAlgorithm(BaseWrapper): """ Define the image segmentation function based on Scikit-Image implementation and a set of provided parameters Args: algo_type: string, segmentation algorithm among the following: 'quickshift', 'slic', 'felzenszwalb' target_params: dict, algorithm parameters (valid model paramters as define in Scikit-Image documentation) """ def __init__(self, algo_type, **target_params): self.algo_type = algo_type if (self.algo_type == 'quickshift'): BaseWrapper.__init__(self, quickshift, **target_params) kwargs = self.filter_params(quickshift) self.set_params(**kwargs) elif (self.algo_type == 'felzenszwalb'): BaseWrapper.__init__(self, felzenszwalb, **target_params) kwargs = self.filter_params(felzenszwalb) self.set_params(**kwargs) elif (self.algo_type == 'slic'): BaseWrapper.__init__(self, slic, **target_params) kwargs = self.filter_params(slic) self.set_params(**kwargs) def __call__(self, *args): return self.target_fn(args[0], **self.target_params) ================================================ FILE: setup.cfg ================================================ [flake8] max-line-length = 100 ================================================ FILE: setup.py ================================================ from setuptools import setup, find_packages setup(name='lime', version='0.2.0.1', description='Local Interpretable Model-Agnostic Explanations for machine learning classifiers', url='http://github.com/marcotcr/lime', author='Marco Tulio Ribeiro', author_email='marcotcr@gmail.com', license='BSD', packages=find_packages(exclude=['js', 'node_modules', 'tests']), python_requires='>=3.5', install_requires=[ 'matplotlib', 'numpy', 'scipy', 'tqdm >= 4.29.1', 'scikit-learn>=0.18', 'scikit-image>=0.12', 'pyDOE2==1.3.0' ], extras_require={ 'dev': ['pytest', 'flake8'], }, include_package_data=True, zip_safe=False)