SYMBOL INDEX (325 symbols across 16 files)

FILE: examples/loan_replan.py
  function get_EPEI (line 27) | def get_EPEI(num):
  function get_MIRD (line 46) | def get_MIRD(num):
  function get_MCEP (line 65) | def get_MCEP(num):
  function get_MCEI (line 85) | def get_MCEI(num):
  function get_MCAT (line 106) | def get_MCAT(num, pay):
  function get_BFTO (line 120) | def get_BFTO(num):

FILE: examples/rule_test.py
  function cv (line 22) | def cv(x):
  function cv_type (line 31) | def cv_type(x):
  function get_trend (line 43) | def get_trend(data, method=np.mean, key='', flag=['高', '低']):
  function calculate_var_lift (line 106) | def calculate_var_lift(data, data_sub, hit_flag, target, cut_point, dire...
  function calculate_var_odds (line 127) | def calculate_var_odds(data, data_sub, hit_flag, target, cut_point, dire...
  function get_month_odds (line 157) | def get_month_odds(data, rule_name, rule_type, cut_point, target, rule_l...
  function get_weeks_hit (line 445) | def get_weeks_hit(data, rule_name, rule_type, cut_point, target, rule_li...
  function get_days_hit (line 603) | def get_days_hit(data, rule_name, rule_type, cut_point, target, rule_lim...
  function get_mths_result (line 761) | def get_mths_result(data, rule_name, rule_type, var, cut_point, target, ...
  function get_weeks_result (line 813) | def get_weeks_result(data, rule_name, rule_type, var, cut_point, target,...
  function get_days_result (line 862) | def get_days_result(data, rule_name, rule_type, var, cut_point, target, ...
  function rule_combine_results (line 903) | def rule_combine_results(data, rules_dict, rule_all, use_credit_flag, ci...
  function std_result_output_01 (line 1065) | def std_result_output_01(wb, sheetname, data, offset):
  function rule_combine_results_01 (line 1200) | def rule_combine_results_01(data, rule_all, use_credit_flag, cut_point, ...
  function get_same_len (line 1351) | def get_same_len(x):
  function get_max_len (line 1369) | def get_max_len(data, nrows, ncols, max_len=60):
  function description_output (line 1398) | def description_output(wb, sheetname, df1, df2, offset, base_lift):
  function add_combine_plot (line 1546) | def add_combine_plot(wb, ws, column, label_x_start=1 + 6, x_start=1 + 6 ...
  function add_plot (line 1605) | def add_plot(wb, ws, column, label_x_start=1 + 6, x_start=1 + 6 + 1, x_e...
  function std_result_output (line 1631) | def std_result_output(data, freq):

FILE: scorecardpipeline/auto_eda.py
  function auto_eda_sweetviz (line 18) | def auto_eda_sweetviz(all_data, target=None, save="model_report/auto_eda...

FILE: scorecardpipeline/auto_report.py
  function auto_data_testing_report (line 23) | def auto_data_testing_report(data: pd.DataFrame, features=None, target="...

FILE: scorecardpipeline/excel_writer.py
  class ExcelWriter (line 30) | class ExcelWriter:
    method __init__ (line 32) | def __init__(self, style_excel=None, style_sheet_name="初始化", mode="rep...
    method add_conditional_formatting (line 65) | def add_conditional_formatting(self, worksheet, start_space, end_space...
    method set_column_width (line 77) | def set_column_width(worksheet, column, width):
    method set_number_format (line 88) | def set_number_format(worksheet, space, _format):
    method set_freeze_panes (line 107) | def set_freeze_panes(self, worksheet, space):
    method get_sheet_by_name (line 122) | def get_sheet_by_name(self, name):
    method move_sheet (line 136) | def move_sheet(self, worksheet, offset: int = 0, index: int = None):
    method insert_hyperlink2sheet (line 152) | def insert_hyperlink2sheet(self, worksheet, insert_space, hyperlink=No...
    method insert_value2sheet (line 192) | def insert_value2sheet(self, worksheet, insert_space, value="", style=...
    method insert_pic2sheet (line 248) | def insert_pic2sheet(self, worksheet, fig, insert_space, figsize=(600,...
    method insert_rows (line 271) | def insert_rows(self, worksheet, row, row_index, col_index, merge_rows...
    method insert_df2sheet (line 319) | def insert_df2sheet(self, worksheet, data, insert_space, merge_column=...
    method merge_cells (line 481) | def merge_cells(self, worksheet, start, end):
    method check_contain_chinese (line 527) | def check_contain_chinese(check_str):
    method astype_insertvalue (line 543) | def astype_insertvalue(value, decimal_point=4):
    method calc_continuous_cnt (line 559) | def calc_continuous_cnt(list_, index_=0):
    method itlubber_border (line 592) | def itlubber_border(border, color, white=False):
    method get_cell_space (line 617) | def get_cell_space(space):
    method calculate_rgba_color (line 646) | def calculate_rgba_color(hex_color, opacity, prefix="#"):
    method init_style (line 660) | def init_style(self, font, fontsize, theme_color):
    method save (line 749) | def save(self, filename, close=True):
  function dataframe2excel (line 787) | def dataframe2excel(data, excel_writer, sheet_name=None, title=None, hea...

FILE: scorecardpipeline/feature_engineering.py
  class NumExprDerive (line 13) | class NumExprDerive(BaseEstimator, TransformerMixin):
    method __init__ (line 24) | def __init__(self, derivings=None):
    method fit (line 30) | def fit(self, X, y=None):
    method _check_keywords (line 35) | def _check_keywords(self):
    method _get_context (line 51) | def _get_context(X, feature_names=None):
    method _transform_frame (line 56) | def _transform_frame(self, X):
    method _transform_ndarray (line 72) | def _transform_ndarray(self, X):
    method transform (line 83) | def transform(self, X):
    method _more_tags (line 88) | def _more_tags(self):

FILE: scorecardpipeline/feature_selection.py
  class SelectorMixin (line 43) | class SelectorMixin(BaseEstimator, TransformerMixin):
    method __init__ (line 45) | def __init__(self):
    method transform (line 51) | def transform(self, x):
    method __call__ (line 55) | def __call__(self, *args, **kwargs):
    method fit (line 59) | def fit(self, x, y=None):
  class TypeSelector (line 63) | class TypeSelector(SelectorMixin):
    method __init__ (line 65) | def __init__(self, dtype_include=None, dtype_exclude=None, exclude=None):
    method fit (line 71) | def fit(self, x: pd.DataFrame, y=None, **fit_params):
  class RegexSelector (line 97) | class RegexSelector(SelectorMixin):
    method __init__ (line 98) | def __init__(self, pattern=None, exclude=None):
    method fit (line 106) | def fit(self, x: pd.DataFrame, y=None, **fit_params):
  function value_ratio (line 127) | def value_ratio(x, value):
  function mode_ratio (line 134) | def mode_ratio(x, dropna=True):
  class NullSelector (line 142) | class NullSelector(SelectorMixin):
    method __init__ (line 144) | def __init__(self, threshold=0.95, missing_values=np.nan, exclude=None...
    method fit (line 155) | def fit(self, x: pd.DataFrame, y=None):
  class ModeSelector (line 174) | class ModeSelector(SelectorMixin):
    method __init__ (line 176) | def __init__(self, threshold=0.95, exclude=None, dropna=True, n_jobs=N...
    method fit (line 188) | def fit(self, x: pd.DataFrame, y=None):
  class CardinalitySelector (line 207) | class CardinalitySelector(SelectorMixin):
    method __init__ (line 218) | def __init__(self, threshold=10, exclude=None, dropna=True):
    method fit (line 224) | def fit(self, x, y=None, **fit_params):
  function IV (line 242) | def IV(x, y, regularization=1.0):
  function _IV (line 270) | def _IV(x, y, regularization=1.0, n_jobs=None):
  class InformationValueSelector (line 281) | class InformationValueSelector(SelectorMixin):
    method __init__ (line 283) | def __init__(self, threshold=0.02, target="target", regularization=1.0...
    method fit (line 297) | def fit(self, x: pd.DataFrame, y=None):
  function LIFT (line 324) | def LIFT(y_pred, y_true):
  class LiftSelector (line 353) | class LiftSelector(SelectorMixin):
    method __init__ (line 363) | def __init__(self, target="target", threshold=3.0, n_jobs=None, method...
    method fit (line 379) | def fit(self, x: pd.DataFrame, y=None, **fit_params):
  class VarianceSelector (line 411) | class VarianceSelector(SelectorMixin):
    method __init__ (line 414) | def __init__(self, threshold=0.0, exclude=None):
    method fit (line 422) | def fit(self, x, y=None):
  function VIF (line 454) | def VIF(x, n_jobs=None, missing=-1):
  class VIFSelector (line 464) | class VIFSelector(SelectorMixin):
    method __init__ (line 466) | def __init__(self, threshold=4.0, exclude=None, missing=-1, n_jobs=None):
    method fit (line 483) | def fit(self, x: pd.DataFrame, y=None):
  class CorrSelector (line 500) | class CorrSelector(SelectorMixin):
    method __init__ (line 501) | def __init__(self, threshold=0.7, method="pearson", weights=None, excl...
    method fit (line 512) | def fit(self, x: pd.DataFrame, y=None):
  function _psi_score (line 584) | def _psi_score(expected, actual):
  function PSI (line 601) | def PSI(train, test, n_jobs=None, verbose=0, pre_dispatch='2*n_jobs'):
  class PSISelector (line 607) | class PSISelector(SelectorMixin):
    method __init__ (line 609) | def __init__(self, threshold=0.1, cv=None, method=None, exclude=None, ...
    method fit (line 623) | def fit(self, x: pd.DataFrame, y=None, groups=None):
  class NullImportanceSelector (line 658) | class NullImportanceSelector(SelectorMixin):
    method __init__ (line 660) | def __init__(self, estimator, target="target", threshold=1.0, norm_ord...
    method _feature_score_v0 (line 671) | def _feature_score_v0(actual_importances, null_importances):
    method _feature_score_v1 (line 675) | def _feature_score_v1(actual_importances, null_importances):
    method _feature_score_v2 (line 681) | def _feature_score_v2(actual_importances, null_importances):
    method fit (line 685) | def fit(self, x: pd.DataFrame, y=None):
  class TargetPermutationSelector (line 742) | class TargetPermutationSelector(NullImportanceSelector):
    method __init__ (line 744) | def __init__(self, estimator, target="target", threshold=1.0, norm_ord...
  class ExhaustiveSelector (line 748) | class ExhaustiveSelector(SelectorMixin, MetaEstimatorMixin):
    method __init__ (line 774) | def __init__(self, estimator, min_features=1, max_features=1, scoring=...
    method _validate_params (line 795) | def _validate_params(self, x, y):
    method _calc_score (line 808) | def _calc_score(estimator, x, y, indices, groups=None, scoring=None, c...
    method ncr (line 828) | def ncr(n, r):
    method _calc_confidence (line 843) | def _calc_confidence(scores, confidence=0.95):
    method fit (line 848) | def fit(self, X, y, groups=None, **fit_params):
    method _get_support_mask (line 898) | def _get_support_mask(self):
  class BorutaSelector (line 903) | class BorutaSelector(SelectorMixin):
    method __init__ (line 905) | def __init__(self):
  class MICSelector (line 910) | class MICSelector(SelectorMixin):
  class FeatureImportanceSelector (line 914) | class FeatureImportanceSelector(SelectorMixin):
  class StabilitySelector (line 918) | class StabilitySelector(SelectorMixin):
  class REFSelector (line 922) | class REFSelector(SelectorMixin):
  class SequentialFeatureSelector (line 926) | class SequentialFeatureSelector(SelectorMixin):

FILE: scorecardpipeline/financial.py
  class NoRealSolutionError (line 31) | class NoRealSolutionError(Exception):
  class IterationsExceededError (line 35) | class IterationsExceededError(Exception):
  function _convert_when (line 39) | def _convert_when(when):
  function _return_ufunc_like (line 50) | def _return_ufunc_like(array):
  function _is_object_array (line 59) | def _is_object_array(array):
  function _use_decimal_dtype (line 63) | def _use_decimal_dtype(*arrays):
  function _to_decimal_array_1d (line 67) | def _to_decimal_array_1d(array):
  function _to_decimal_array_2d (line 71) | def _to_decimal_array_2d(array):
  function _get_output_array_shape (line 76) | def _get_output_array_shape(*arrays):
  function fv (line 80) | def fv(rate, nper, pmt, pv, when='end'):
  function pmt (line 187) | def pmt(rate, nper, pv, fv=0, when='end'):
  function nper (line 281) | def nper(rate, pmt, pv, fv=0, when='end'):
  function _value_like (line 356) | def _value_like(arr, value):
  function ipmt (line 363) | def ipmt(rate, per, nper, pv, fv=0, when='end'):
  function _rbl (line 475) | def _rbl(rate, per, pmt, pv, when):
  function ppmt (line 486) | def ppmt(rate, per, nper, pv, fv=0, when='end'):
  function pv (line 514) | def pv(rate, nper, pmt, fv=0, when='end'):
  function _g_div_gp (line 615) | def _g_div_gp(r, n, p, x, y, w):
  function rate (line 635) | def rate(
  function irr (line 730) | def irr(values, *, guess=None, tol=1e-12, maxiter=100, raise_exceptions=...
  function _npv_native (line 860) | def _npv_native(rates, values, out):
  function _npv_decimal (line 871) | def _npv_decimal(rates, values, out):
  function npv (line 880) | def npv(rate, values):
  function mirr (line 1001) | def mirr(values, finance_rate, reinvest_rate, *, raise_exceptions=False):

FILE: scorecardpipeline/logger.py
  function init_logger (line 7) | def init_logger(filename=None, stream=True, fmt="[ %(asctime)s ][ %(leve...

FILE: scorecardpipeline/model.py
  class ITLubberLogisticRegression (line 28) | class ITLubberLogisticRegression(LogisticRegression):
    method __init__ (line 30) | def __init__(self, target="target", penalty="l2", calculate_stats=True...
    method fit (line 84) | def fit(self, x, sample_weight=None, **kwargs):
    method decision_function (line 147) | def decision_function(self, x):
    method corr (line 163) | def corr(self, data, save=None, annot=True):
    method report (line 172) | def report(self, data):
    method summary (line 184) | def summary(self):
    method summary2 (line 238) | def summary2(self, feature_map={}):
    method convert_sparse_matrix (line 253) | def convert_sparse_matrix(x):
    method plot_weights (line 260) | def plot_weights(self, save=None, figsize=(15, 8), fontsize=14, color=...
  class ScoreCard (line 302) | class ScoreCard(toad.ScoreCard, TransformerMixin):
    method __init__ (line 304) | def __init__(self, target="target", pdo=60, rate=2, base_odds=35, base...
    method fit (line 334) | def fit(self, x):
    method transform (line 366) | def transform(self, x):
    method _check_rules (line 375) | def _check_rules(self, combiner, transer):
    method score_clip (line 412) | def score_clip(score, clip=50):
    method scorecard_scale (line 424) | def scorecard_scale(self):
    method format_bins (line 443) | def format_bins(self, bins, index=False, ellipsis=None, decimal=4):
    method scorecard_points (line 487) | def scorecard_points(self, feature_map={}):
    method scorecard2pmml (line 500) | def scorecard2pmml(self, pmml: str = 'scorecard.pmml', debug: bool = F...
    method KS_bucket (line 591) | def KS_bucket(y_pred, y_true, bucket=10, method="quantile"):
    method KS (line 604) | def KS(y_pred, y_true):
    method AUC (line 615) | def AUC(y_pred, y_true):
    method perf_eva (line 626) | def perf_eva(y_pred, y_true, title="", plot_type=["ks", "roc"], save=N...
    method ks_plot (line 650) | def ks_plot(score, y_true, title="", fontsize=14, figsize=(16, 8), sav...
    method PSI (line 664) | def PSI(y_pred_train, y_pred_oot):
    method perf_psi (line 674) | def perf_psi(y_pred_train, y_pred_oot, y_true_train, y_true_oot, keys=...
    method score_hist (line 699) | def score_hist(score, y_true, figsize=(15, 10), bins=20, save=None, **...
    method _format_rule (line 711) | def _format_rule(self, rule, decimal=4, **kwargs):
    method class_steps (line 724) | def class_steps(pipeline, query):
    method feature_bin_stats (line 734) | def feature_bin_stats(self, data, feature, rules={}, method='step', ma...

FILE: scorecardpipeline/processing.py
  function drop_identical (line 24) | def drop_identical(frame, threshold=0.95, return_drop=False, exclude=Non...
  function drop_corr (line 62) | def drop_corr(frame, target=None, threshold=0.7, by='IV', return_drop=Fa...
  function select (line 131) | def select(frame, target='target', empty=0.95, iv=0.02, corr=0.7, identi...
  class FeatureSelection (line 175) | class FeatureSelection(TransformerMixin, BaseEstimator):
    method __init__ (line 177) | def __init__(self, target="target", empty=0.95, iv=0.02, corr=0.7, exc...
    method fit (line 204) | def fit(self, x, y=None):
    method transform (line 230) | def transform(self, x, y=None):
  class StepwiseSelection (line 240) | class StepwiseSelection(TransformerMixin, BaseEstimator):
    method __init__ (line 242) | def __init__(self, target="target", estimator="ols", direction="both",...
    method fit (line 273) | def fit(self, x, y=None):
    method transform (line 293) | def transform(self, x, y=None):
  class FeatureImportanceSelector (line 303) | class FeatureImportanceSelector(BaseEstimator, TransformerMixin):
    method __init__ (line 305) | def __init__(self, top_k=126, target="target", selector="catboost", pa...
    method fit (line 325) | def fit(self, x, y=None):
    method transform (line 351) | def transform(self, x, y=None):
    method catboost_selector (line 360) | def catboost_selector(self, x, y, cat_features=None):
  class Combiner (line 394) | class Combiner(TransformerMixin, BaseEstimator):
    method __init__ (line 396) | def __init__(self, target="target", method='chi', empty_separate=True,...
    method update (line 429) | def update(self, rules):
    method optbinning_bins (line 441) | def optbinning_bins(feature, data=None, target="target", min_n_bins=2,...
    method fit (line 490) | def fit(self, x: pd.DataFrame, y=None):
    method check_rules (line 528) | def check_rules(self, feature=None):
    method transform (line 548) | def transform(self, x, y=None, labels=False):
    method export (line 558) | def export(self, to_json=None):
    method load (line 567) | def load(self, from_json):
    method feature_bin_stats (line 578) | def feature_bin_stats(cls, data, feature, target="target", rules=None,...
    method bin_plot (line 726) | def bin_plot(self, data, x, rule={}, desc="", result=False, save=None,...
    method proportion_plot (line 744) | def proportion_plot(self, data, x, transform=False, labels=False, keys...
    method corr_plot (line 758) | def corr_plot(self, data, transform=False, figure_size=(20, 15), save=...
    method badrate_plot (line 771) | def badrate_plot(self, data, date_column, feature, labels=True):
    method rules (line 782) | def rules(self):
    method rules (line 787) | def rules(self, value):
    method __len__ (line 794) | def __len__(self):
    method __contains__ (line 801) | def __contains__(self, key):
    method __getitem__ (line 809) | def __getitem__(self, key):
    method __setitem__ (line 817) | def __setitem__(self, key, value):
    method __iter__ (line 825) | def __iter__(self):
  function feature_bin_stats (line 833) | def feature_bin_stats(data, feature, target="target", overdue=None, dpd=...
  class WOETransformer (line 936) | class WOETransformer(TransformerMixin, BaseEstimator):
    method __init__ (line 938) | def __init__(self, target="target", exclude=None):
    method fit (line 948) | def fit(self, x, y=None):
    method transform (line 957) | def transform(self, x, y=None):
    method export (line 966) | def export(self, to_json=None):
    method load (line 975) | def load(self, from_json):
    method rules (line 986) | def rules(self):
    method rules (line 991) | def rules(self, value):
    method __len__ (line 994) | def __len__(self):
    method __contains__ (line 997) | def __contains__(self, key):
    method __getitem__ (line 1000) | def __getitem__(self, key):
    method __setitem__ (line 1003) | def __setitem__(self, key, value):
    method __iter__ (line 1006) | def __iter__(self):
  function feature_efficiency_analysis (line 1010) | def feature_efficiency_analysis(data, feature, overdue=["MOB1"], dpd=[7,...

FILE: scorecardpipeline/rule.py
  function _get_context (line 23) | def _get_context(X, feature_names):
  function _apply_expr_on_array (line 27) | def _apply_expr_on_array(expr, X, feature_names):
  function get_columns_from_query (line 32) | def get_columns_from_query(query_str):
  class RuleState (line 59) | class RuleState(str, Enum):
  class RuleStateError (line 64) | class RuleStateError(RuntimeError):
  class RuleUnAppliedError (line 68) | class RuleUnAppliedError(RuleStateError):
  function json2expr (line 81) | def json2expr(data, max_index, feature_list):
  class Rule (line 107) | class Rule:
    method __init__ (line 108) | def __init__(self, expr):  # expr 既可以传递字符串，也可以传递dict
    method __str__ (line 131) | def __str__(self):
    method __repr__ (line 134) | def __repr__(self):
    method predict (line 137) | def predict(self, X: DataFrame, part=""):  # dict预测对应part_dict 、字符串表达式...
    method report (line 171) | def report(self, datasets: pd.DataFrame, target="target", overdue=None...
    method result (line 275) | def result(self):
    method __eq__ (line 280) | def __eq__(self, other):
    method __or__ (line 291) | def __or__(self, other):
    method __and__ (line 360) | def __and__(self, other):
    method __xor__ (line 429) | def __xor__(self, other):
    method __mul__ (line 441) | def __mul__(self, other):
    method __invert__ (line 444) | def __invert__(self):
    method save (line 453) | def save(report, excel_writer, sheet_name=None, merge_column=None, per...
  function ruleset_report (line 475) | def ruleset_report(datasets: pd.DataFrame, rules: List[Rule], target="ta...
  function bin_table_badrate_prediction (line 504) | def bin_table_badrate_prediction(group, amount=None):
  function sawpin_badrate_prediction_by_score (line 519) | def sawpin_badrate_prediction_by_score(base: pd.DataFrame, test: pd.Data...

FILE: scorecardpipeline/rule_extraction.py
  class DecisionTreeRuleExtractor (line 28) | class DecisionTreeRuleExtractor:
    method __init__ (line 29) | def __init__(self, target="target", labels=["positive", "negative"], f...
    method encode_cat_features (line 65) | def encode_cat_features(self, X, y):
    method get_dt_rules (line 86) | def get_dt_rules(self, tree):
    method select_dt_rules (line 106) | def select_dt_rules(self, decision_tree, x, y, lift=0., max_samples=1....
    method query_dt_rules (line 193) | def query_dt_rules(self, x, y, parsed_rules=None):
    method insert_dt_rules (line 206) | def insert_dt_rules(self, parsed_rules, end_row, start_col, save=None,...
    method fit (line 219) | def fit(self, x, y=None, max_depth=2, lift=0., max_samples=1., min_sco...
    method transform (line 267) | def transform(self, x, y=None):
    method report (line 279) | def report(self, valid=None, sheet="组合策略汇总", save=None):

FILE: scorecardpipeline/scorecard.py
  class BaseScoreTransformer (line 19) | class BaseScoreTransformer(BaseEstimator, TransformerMixin):
    method __init__ (line 20) | def __init__(self, down_lmt=300, up_lmt=1000, greater_is_better=True, ...
    method predict (line 27) | def predict(self, x):
    method score_clip (line 31) | def score_clip(score, clip=50):
  class StandardScoreTransformer (line 44) | class StandardScoreTransformer(BaseScoreTransformer):
    method __init__ (line 47) | def __init__(self, base_score=660, pdo=75, rate=2, bad_rate=0.15, down...
    method fit (line 54) | def fit(self, X, y=None, **fit_params):
    method scorecard_scale (line 78) | def scorecard_scale(self):
    method _transform (line 96) | def _transform(self, X):
    method transform (line 107) | def transform(self, X):
    method predict (line 115) | def predict(self, X):
    method _inverse_transform (line 129) | def _inverse_transform(self, X):
    method inverse_transform (line 139) | def inverse_transform(self, X):
    method _more_tags (line 147) | def _more_tags(self):
  class NPRoundStandardScoreTransformer (line 153) | class NPRoundStandardScoreTransformer(StandardScoreTransformer):
    method __init__ (line 155) | def __init__(self, base_score=660, pdo=75, bad_rate=0.15, down_lmt=300...
    method _transform (line 160) | def _transform(self, X):
  class RoundStandardScoreTransformer (line 167) | class RoundStandardScoreTransformer(StandardScoreTransformer):
    method __init__ (line 170) | def __init__(self, base_score=660, pdo=75, bad_rate=0.15, down_lmt=300...
    method _transform (line 175) | def _transform(self, X):
  class BoxCoxScoreTransformer (line 182) | class BoxCoxScoreTransformer(BaseScoreTransformer):
    method __init__ (line 183) | def __init__(self, down_lmt=300, up_lmt=1000, greater_is_better=True, ...
    method _box_cox_optimize (line 187) | def _box_cox_optimize(x):
    method fit (line 196) | def fit(self, X, y=None, **fit_params):
    method _transform (line 209) | def _transform(self, X):
    method transform (line 220) | def transform(self, X):
    method predict (line 228) | def predict(self, X):
    method _inverse_transform (line 254) | def _inverse_transform(self, X):
    method inverse_transform (line 266) | def inverse_transform(self, X):
    method _box_cox_inverse_tranform (line 275) | def _box_cox_inverse_tranform(x, lmbda):

FILE: scorecardpipeline/utils.py
  function seed_everything (line 34) | def seed_everything(seed: int, freeze_torch=False):
  function init_setting (line 53) | def init_setting(font_path=None, seed=None, freeze_torch=False, logger=F...
  function load_pickle (line 100) | def load_pickle(file, engine="joblib"):
  function save_pickle (line 121) | def save_pickle(obj, file, engine="joblib"):
  function feature_describe (line 141) | def feature_describe(data, feature=None, percentiles=None, missing=None,...
  function groupby_feature_describe (line 183) | def groupby_feature_describe(data, by=None, n_jobs=-1, **kwargs):
  function germancredit (line 213) | def germancredit():
  function round_float (line 248) | def round_float(num, decimal=4):
  function feature_bins (line 263) | def feature_bins(bins, decimal=4):
  function extract_feature_bin (line 300) | def extract_feature_bin(bin_var):
  function inverse_feature_bins (line 319) | def inverse_feature_bins(feature_table, bin_col="分箱"):
  function bin_plot (line 350) | def bin_plot(feature_table, desc="", figsize=(10, 6), colors=["#2639E9",...
  function corr_plot (line 408) | def corr_plot(data, figure_size=(16, 8), fontsize=16, mask=False, save=N...
  function ks_plot (line 464) | def ks_plot(score, target, title="", fontsize=14, figsize=(16, 8), save=...
  function hist_plot (line 575) | def hist_plot(score, y_true=None, figsize=(15, 10), bins=30, save=None, ...
  function psi_plot (line 639) | def psi_plot(expected, actual, labels=["预期", "实际"], desc="", save=None, ...
  function csi_plot (line 709) | def csi_plot(expected, actual, score_bins, labels=["预期", "实际"], desc="",...
  function dataframe_plot (line 779) | def dataframe_plot(df, row_height=0.4, font_size=14, header_color='#2639...
  function distribution_plot (line 835) | def distribution_plot(data, date="date", target="target", save=None, fig...
  function sample_lift_transformer (line 897) | def sample_lift_transformer(df, rule, target='target', sample_rate=0.7):
  function tasks_executor (line 931) | def tasks_executor(tasks, n_jobs=-1, pool="thread"):
  function monotonic_bad_rate_binning (line 961) | def monotonic_bad_rate_binning(df, feature, target, target_rates, greate...

FILE: setup.py
  function get_version (line 8) | def get_version():
  function get_requirements (line 13) | def get_requirements(stage=None):