Copy disabled (too large)
Download .txt
Showing preview only (12,760K chars total). Download the full file to get everything.
Repository: hemansnation/Data-Analyst-Roadmap
Branch: main
Commit: a4a08e040f94
Files: 110
Total size: 56.5 MB
Directory structure:
gitextract_mu6uxmva/
├── July Cohort 2023/
│ └── 1_Python Programming/
│ ├── .ipynb_checkpoints/
│ │ ├── 01_Python Basics-checkpoint.ipynb
│ │ ├── 02_03_While Loop and List-checkpoint.ipynb
│ │ ├── 04_Strings and For loop-checkpoint.ipynb
│ │ └── 05_Dictionary Tuples and Set-checkpoint.ipynb
│ ├── 01_Python Basics.ipynb
│ ├── 02_03_While Loop and List.ipynb
│ ├── 04_Strings and For loop.ipynb
│ └── 05_Dictionary Tuples and Set.ipynb
├── March Cohort 2023/
│ ├── .ipynb_checkpoints/
│ │ ├── 0_Python Basics-checkpoint.ipynb
│ │ ├── 13_14_Object Orientation-checkpoint.ipynb
│ │ ├── 1_While Loops and Logic Building-checkpoint.ipynb
│ │ ├── 2_List and Strings-checkpoint.ipynb
│ │ ├── 3_For Loop Dictionary Tuple and Sets-checkpoint.ipynb
│ │ ├── 4_Functions-checkpoint.ipynb
│ │ └── 5_Modules and Packages-checkpoint.ipynb
│ ├── 0_Python Basics.ipynb
│ ├── 10_11_EDA Project/
│ │ ├── .ipynb_checkpoints/
│ │ │ └── 10_11_EDA Project-checkpoint.ipynb
│ │ ├── 10_11_EDA Project.ipynb
│ │ ├── titanic.csv
│ │ └── titanic_cleaned.csv
│ ├── 10_Matplotlib/
│ │ ├── .ipynb_checkpoints/
│ │ │ └── 10_Matplotlib-checkpoint.ipynb
│ │ └── 10_Matplotlib.ipynb
│ ├── 12_15_16_17_18_Statistics/
│ │ ├── .ipynb_checkpoints/
│ │ │ ├── 12_15_Statistics-checkpoint.ipynb
│ │ │ ├── 16_17_Statistics and Regression-checkpoint.ipynb
│ │ │ └── 18_Hypothesis Testing-checkpoint.ipynb
│ │ ├── 12_15_Statistics.ipynb
│ │ ├── 16_17_Statistics and Regression.ipynb
│ │ ├── 18_Hypothesis Testing.ipynb
│ │ ├── datasets/
│ │ │ ├── Birthweight_reduced_kg_R.csv
│ │ │ ├── CarPrice_Assignment.csv
│ │ │ ├── Crime_R.csv
│ │ │ ├── IPL2013.csv
│ │ │ ├── SP_500_1987.csv
│ │ │ ├── data_loan.csv
│ │ │ └── forbes.csv
│ │ ├── sample_submission.csv
│ │ ├── test.csv
│ │ └── train.csv
│ ├── 13_14_Object Orientation.ipynb
│ ├── 19_20_Machine Learning/
│ │ ├── .ipynb_checkpoints/
│ │ │ ├── 19_Machine Learning and Linear Regression with One variable-checkpoint.ipynb
│ │ │ └── 20_Logistic Regression-checkpoint.ipynb
│ │ ├── 19_Machine Learning and Linear Regression with One variable.ipynb
│ │ ├── 20_Logistic Regression.ipynb
│ │ ├── areas.csv
│ │ ├── homeprices.csv
│ │ ├── insurance_data.csv
│ │ └── spend.xlsx
│ ├── 1_While Loops and Logic Building.ipynb
│ ├── 21_EDA and Data Viz/
│ │ ├── .ipynb_checkpoints/
│ │ │ └── 21_EDA and Data Visualization-checkpoint.ipynb
│ │ ├── 21_EDA and Data Visualization.ipynb
│ │ └── itunes_data.csv
│ ├── 22_23_Time Series Forecasting/
│ │ ├── .ipynb_checkpoints/
│ │ │ ├── 22_Forecasting-checkpoint.ipynb
│ │ │ └── 23_ARIMA-checkpoint.ipynb
│ │ ├── 22_Forecasting.ipynb
│ │ ├── 23_ARIMA.ipynb
│ │ ├── store.xls
│ │ ├── vimana.csv
│ │ └── wsb.csv
│ ├── 24_SQL/
│ │ └── SQLqueriesQandA.sql
│ ├── 2_List and Strings.ipynb
│ ├── 3_For Loop Dictionary Tuple and Sets.ipynb
│ ├── 4_Functions.ipynb
│ ├── 5_Modules and Packages.ipynb
│ ├── 5_Modules-Packages/
│ │ ├── main.py
│ │ ├── rose.py
│ │ └── statsmeme/
│ │ ├── __init__.py
│ │ ├── descriptive.py
│ │ └── inferential.py
│ ├── 6_VirtualEnvironmentAndFlask/
│ │ ├── application.py
│ │ └── templates/
│ │ └── index.html
│ ├── 7_NumPy/
│ │ ├── .ipynb_checkpoints/
│ │ │ └── 7_NumPy-checkpoint.ipynb
│ │ └── 7_NumPy.ipynb
│ └── 8_9_Pandas/
│ ├── .ipynb_checkpoints/
│ │ └── 8_9_Pandas-checkpoint.ipynb
│ ├── 8_9_Pandas.ipynb
│ ├── Data Cleaning With Pandas/
│ │ ├── Data Cleaning with Python and Pandas_ Detecting Missing Values.html
│ │ └── Data Cleaning with Python and Pandas_ Detecting Missing Values_files/
│ │ ├── analytics.js.download
│ │ ├── comment-reply.min.js.download
│ │ ├── common.js.download
│ │ ├── css
│ │ ├── css(1)
│ │ ├── css(2)
│ │ ├── custom.js(1).download
│ │ ├── custom.js.download
│ │ ├── custom.min.js.download
│ │ ├── form.js.download
│ │ ├── frontend.min.js.download
│ │ ├── idle-timer.min.js(1).download
│ │ ├── idle-timer.min.js.download
│ │ ├── jquery-migrate.min.js.download
│ │ ├── jquery.js.download
│ │ ├── jquery.uniform.min.js.download
│ │ ├── linkid.js.download
│ │ ├── prism-js.min.js.download
│ │ ├── style(1).css
│ │ ├── style(2).css
│ │ ├── style(3).css
│ │ ├── style.css
│ │ ├── wp-embed.min.js.download
│ │ └── wp-emoji-release.min.js.download
│ ├── indore.csv
│ ├── nyc_weather.csv
│ ├── stock_data.csv
│ ├── stocks_weather.xlsx
│ ├── weather_by_cities.csv
│ ├── weather_data.csv
│ ├── weather_data.xlsx
│ ├── weather_data2.csv
│ ├── weather_datamissing.csv
│ └── weather_datamissing_regex.csv
└── README.md
================================================
FILE CONTENTS
================================================
================================================
FILE: July Cohort 2023/1_Python Programming/.ipynb_checkpoints/01_Python Basics-checkpoint.ipynb
================================================
{
"cells": [
{
"cell_type": "markdown",
"id": "5effdff7",
"metadata": {},
"source": [
"# Python Basics"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "d04e5b22",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello User\n"
]
}
],
"source": [
"print(\"Hello User\")"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "b0091bf1",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello\n",
"User\n"
]
}
],
"source": [
"print(\"Hello\")\n",
"print(\"User\")"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "fb83814b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello\n",
"User\n"
]
}
],
"source": [
"print(\"Hello\\nUser\") # \\n -> new line character"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "791c342a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello\tUser\n"
]
}
],
"source": [
"print(\"Hello\\tUser\") # \\t -> horizontal tab - 8 spaces"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9fad4ea5",
"metadata": {},
"outputs": [],
"source": [
"# binary language -> 101010111 -> bits\n",
"\n",
"0 -> low voltage, no-charge, false, off\n",
"1 -> high voltage, charge, true, on"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a1885e98",
"metadata": {},
"outputs": [],
"source": [
"bits > numbers > character > instructions > program > software"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "cbe99e7d",
"metadata": {},
"outputs": [],
"source": [
"source code ---------> Byte Code --------> output\n",
" .c compile .bak run .exe\n",
" .cpp .obj\n",
" .java .javac\n",
" .py .pyc"
]
},
{
"cell_type": "markdown",
"id": "8a713554",
"metadata": {},
"source": [
"# Variables"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "5c20abe8",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10\n"
]
}
],
"source": [
"a = 10\n",
"\n",
"print(a)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "995009df",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"45.13\n"
]
}
],
"source": [
"b = 45.13\n",
"\n",
"print(b)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "17194c9e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"India\n"
]
}
],
"source": [
"a = \"India\"\n",
"\n",
"print(a)"
]
},
{
"cell_type": "markdown",
"id": "9141a786",
"metadata": {},
"source": [
"# Data Types"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "6ba6bfd9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10\n",
"<class 'int'>\n"
]
}
],
"source": [
"a = 10\n",
"\n",
"print(a)\n",
"\n",
"print(type(a))"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "a6e1a232",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10.65\n",
"<class 'float'>\n"
]
}
],
"source": [
"b = 10.65\n",
"\n",
"print(b)\n",
"\n",
"print(type(b))"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "1298d5d3",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"colors\n",
"<class 'str'>\n"
]
}
],
"source": [
"c = \"colors\"\n",
"\n",
"print(c)\n",
"\n",
"print(type(c))"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "47c38fa9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"colors\n",
"<class 'str'>\n"
]
}
],
"source": [
"c = 'colors'\n",
"\n",
"print(c)\n",
"\n",
"print(type(c))"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "0acb14e3",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"it's an apple\n"
]
}
],
"source": [
"x = \"it's an apple\"\n",
"\n",
"print(x)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "fb2beb48",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"it\"s an apple\n"
]
}
],
"source": [
"x = 'it\"s an apple'\n",
"\n",
"print(x)"
]
},
{
"cell_type": "markdown",
"id": "814feca5",
"metadata": {},
"source": [
"# Input Function"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "437ffd33",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10\n",
"10\n"
]
}
],
"source": [
"a = input()\n",
"\n",
"print(a)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "8c71996c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter Your Name: Himanshu\n",
"Himanshu\n"
]
}
],
"source": [
"a = input(\"Enter Your Name: \")\n",
"\n",
"print(a)"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "792f782d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter Your Name: Himanshu\n",
"Hello! How are you? Himanshu\n"
]
}
],
"source": [
"a = input(\"Enter Your Name: \")\n",
"\n",
"print(\"Hello! How are you?\", a)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "8ab7e6a7",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello Him\n"
]
}
],
"source": [
"print(\"Hello Him\")"
]
},
{
"cell_type": "markdown",
"id": "84b26329",
"metadata": {},
"source": [
"# Questions"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "376a1bc0",
"metadata": {},
"outputs": [],
"source": [
"Your Name\n",
"------8-------College/Company\n",
"------------16-------------Country"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f60668a8",
"metadata": {},
"outputs": [],
"source": [
"*\n",
"**\n",
"***"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7c2fa48a",
"metadata": {},
"outputs": [],
"source": [
"--4--*\n",
"*----8----*\n",
"--4--*"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "2650f9ed",
"metadata": {},
"outputs": [],
"source": [
" *\n",
"* *\n",
" *"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.12"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
================================================
FILE: July Cohort 2023/1_Python Programming/.ipynb_checkpoints/02_03_While Loop and List-checkpoint.ipynb
================================================
{
"cells": [
{
"cell_type": "markdown",
"id": "13c6ac1c",
"metadata": {},
"source": [
"# While Loop"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "0290b931",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Himanshu\n",
"Himanshu\n"
]
}
],
"source": [
"print(\"Himanshu\")\n",
"print(\"Himanshu\")"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "aab5a9d5",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"True\n"
]
}
],
"source": [
"i = 1\n",
"\n",
"print(i <= 5)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "be002b98",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"False\n"
]
}
],
"source": [
"print(i >= 5)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "903683b3",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"True\n"
]
}
],
"source": [
"print(i >= 1)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "76da14cf",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Himanshu\n",
"Himanshu\n",
"Himanshu\n",
"Himanshu\n",
"Himanshu\n"
]
}
],
"source": [
"i = 1\n",
"\n",
"while i <= 5:\n",
" print(\"Himanshu\")\n",
" i = i + 1 # i = 1, 2, 3, 4, 5, 6"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "145ad944",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1\n",
"2\n",
"3\n",
"4\n",
"5\n"
]
}
],
"source": [
"i = 1\n",
"\n",
"while i <= 5:\n",
" print(i)\n",
" i = i + 1"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "cdad3efc",
"metadata": {},
"outputs": [],
"source": [
"1\n",
"2\n",
"3\n",
"4\n",
"5\n",
"6\n",
"7\n",
"8\n",
"9\n",
"10"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "d7d2dfab",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1\n",
"2\n",
"3\n",
"4\n",
"5\n",
"6\n",
"7\n",
"8\n",
"9\n",
"10\n"
]
}
],
"source": [
"i = 1\n",
"\n",
"while i <= 10:\n",
" print(i)\n",
" i = i + 1"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "a103c74c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello\n",
"World\n"
]
}
],
"source": [
"print(\"Hello\")\n",
"print(\"World\")"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "5df8d4f6",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello\n",
"World\n"
]
}
],
"source": [
"print(\"Hello\", end=\"\\n\")\n",
"print(\"World\")"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "c89f0b40",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello+World\n"
]
}
],
"source": [
"print(\"Hello\", end=\"+\")\n",
"print(\"World\")"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "8a0e5ca8",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello World\n"
]
}
],
"source": [
"print(\"Hello\", end=\" \")\n",
"print(\"World\")"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "bce809e5",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello @@@ World\n"
]
}
],
"source": [
"print(\"Hello\", end=\" @@@ \")\n",
"print(\"World\")"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "54435a01",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello@World$"
]
}
],
"source": [
"print(\"Hello\", end=\"@\")\n",
"print(\"World\", end=\"$\")"
]
},
{
"cell_type": "markdown",
"id": "95e933ab",
"metadata": {},
"source": [
"### print the following series of numbers"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7a728f28",
"metadata": {},
"outputs": [],
"source": [
"1 2 3 4 5 6 7 8 9 10"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "35896fd2",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1 2 3 4 5 6 7 8 9 10 "
]
}
],
"source": [
"i = 1\n",
"\n",
"while i <= 10:\n",
" print(i, end=\" \")\n",
" i = i + 1"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "284eda1a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"100\n",
"10\n"
]
}
],
"source": [
"a = 10\n",
"\n",
"print(a * a)\n",
"\n",
"print(a)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d1cabe31",
"metadata": {},
"outputs": [],
"source": [
"1 4 9 16 25 36 49 64 81 100"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "32f564a1",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1 4 9 16 25 36 49 64 81 100 "
]
}
],
"source": [
"i = 1\n",
"\n",
"while i <= 10:\n",
" print(i*i, end=\" \")\n",
" i = i + 1"
]
},
{
"cell_type": "markdown",
"id": "49b1b14e",
"metadata": {},
"source": [
"**Write a program to enter 5 values from user and print them.**"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "a1cd06ee",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter your number: 10\n",
"10\n",
"Enter your number: 20\n",
"20\n",
"Enter your number: 30\n",
"30\n",
"Enter your number: 40\n",
"40\n",
"Enter your number: 50\n",
"50\n"
]
}
],
"source": [
"i = 1\n",
"\n",
"while i <= 5:\n",
" a = input(\"Enter your number: \")\n",
" print(a)\n",
" i = i + 1\n",
" # 1 + 1"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "a1b92062",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"3.5"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"7 / 2"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "b1e0fc38",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"1"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"7 % 2 # modulo - return the reminder"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "7279d00f",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"10 % 2"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "7ba7e050",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"3"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"11 % 4"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "3c3ea69f",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"3"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"7 // 2 # floor division"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "e378bbe4",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"2"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"15 // 7"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "5947157a",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"3"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"153 % 10"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "07a156bd",
"metadata": {},
"outputs": [],
"source": [
"15)7(\n",
" 7"
]
},
{
"cell_type": "markdown",
"id": "d490f9d3",
"metadata": {},
"source": [
"**Write a program to enter a number from user and print reverse of it.**"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7959c4e2",
"metadata": {},
"outputs": [],
"source": [
"153\n",
"\n",
"351"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "960cfd0b",
"metadata": {},
"outputs": [],
"source": [
"153 % 10 = 3\n",
"153 // 10 = 15\n",
"\n",
"15 % 10 = 5\n",
"15 // 10 = 1\n",
"\n",
"1 % 10 = 1\n",
"1 // 10 = 0"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "3597feec",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter your number: 10\n",
"10\n",
"<class 'str'>\n"
]
}
],
"source": [
"n = input(\"Enter your number: \")\n",
"\n",
"print(n)\n",
"\n",
"print(type(n))"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "71b967e4",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter your number: 10\n",
"10\n",
"<class 'int'>\n"
]
}
],
"source": [
"n = int(input(\"Enter your number: \"))\n",
"\n",
"print(n)\n",
"\n",
"print(type(n))"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "5759b2ec",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter a number: 153\n",
"351"
]
}
],
"source": [
"n = int(input(\"Enter a number: \"))\n",
"\n",
"while n > 0:\n",
" r = n % 10 # r = 3, 5, 1\n",
" print(r, end=\"\") # 351\n",
" n = n // 10 # n = 153, 15, 1, 0"
]
},
{
"cell_type": "markdown",
"id": "adf5586f",
"metadata": {},
"source": [
"**Write a program to enter a number from user and print sum of its individual digits**"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "cbd3db08",
"metadata": {},
"outputs": [],
"source": [
"153\n",
"\n",
"1 + 5 + 3\n",
"\n",
"9"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "1d76dd47",
"metadata": {},
"outputs": [],
"source": [
"0 = s\n",
"3 = s + 3 = s\n",
"5 = s + 5 = s\n",
"1"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "52deeb6d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter a number: 153\n",
"Sum = 9\n"
]
}
],
"source": [
"n = int(input(\"Enter a number: \"))\n",
"s = 0\n",
"\n",
"while n > 0:\n",
" r = n % 10\n",
" s = s + r # s = 0, 3, 8, 9\n",
" n = n // 10\n",
"\n",
"print(\"Sum =\", s)"
]
},
{
"cell_type": "markdown",
"id": "c2bb6d4f",
"metadata": {},
"source": [
"# Day 3"
]
},
{
"cell_type": "markdown",
"id": "f4cb0aee",
"metadata": {},
"source": [
"**Write a program to reverse a number**"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "85d9cb69",
"metadata": {},
"outputs": [],
"source": [
"153\n",
"\n",
"351 - this should be a whole number"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "f31986e9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter a number: 153\n",
"351\n",
"702\n"
]
}
],
"source": [
"n = int(input(\"Enter a number: \"))\n",
"s = 0\n",
"\n",
"while n > 0:\n",
" r = n % 10 # r = 3, 5, 1\n",
" s = s*10 + r # s = 0, 3, 35, 351\n",
" n = n // 10 # n = 153, 15, 1, 0\n",
"\n",
"print(s)\n",
"print(s * 2)"
]
},
{
"cell_type": "markdown",
"id": "949c7e7d",
"metadata": {},
"source": [
"**Write a program to enter a number from user and check if it palindrome or not**"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "4fbfc3b5",
"metadata": {},
"outputs": [],
"source": [
"121\n",
"\n",
"121\n",
"\n",
"153 = 351 - not a palindrome number"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "4855f13b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter a number: 121\n",
"Not a Palindrome\n"
]
}
],
"source": [
"n = int(input(\"Enter a number: \"))\n",
"s = 0\n",
"\n",
"while n > 0:\n",
" r = n % 10 # r = 3, 5, 1\n",
" s = s*10 + r # s = 0, 3, 35, 351\n",
" n = n // 10 # n = 153, 15, 1, 0\n",
"\n",
"if s == n:\n",
" print(\"Palindrome\")\n",
"else:\n",
" print(\"Not a Palindrome\")"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "90712f12",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter a number: 1234321\n",
"Palindrome\n"
]
}
],
"source": [
"n = int(input(\"Enter a number: \"))\n",
"temp = n\n",
"s = 0\n",
"\n",
"while n > 0:\n",
" r = n % 10 # r = 3, 5, 1\n",
" s = s*10 + r # s = 0, 3, 35, 351\n",
" n = n // 10 # n = 153, 15, 1, 0\n",
"\n",
"if s == temp:\n",
" print(\"Palindrome\")\n",
"else:\n",
" print(\"Not a Palindrome\")"
]
},
{
"cell_type": "markdown",
"id": "e1a01ec1",
"metadata": {},
"source": [
"**Write a program to enter a number from user and check if it is armstrong or not**"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "20722f78",
"metadata": {},
"outputs": [],
"source": [
"153\n",
"\n",
"cube(1) + cube(5) + cube(3)\n",
"\n",
"370\n",
"\n",
"371"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "50334900",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter a number: 371\n",
"Armstrong\n"
]
}
],
"source": [
"n = int(input(\"Enter a number: \"))\n",
"temp = n\n",
"s = 0\n",
"\n",
"while n > 0:\n",
" r = n % 10 # r = 3, 5, 1\n",
" s = s + (r*r*r) # s = 0, 27, 152, 153\n",
" n = n // 10 # n = 153, 15, 1, 0\n",
"\n",
"if s == temp:\n",
" print(\"Armstrong\")\n",
"else:\n",
" print(\"Not an Armstrong\")"
]
},
{
"cell_type": "markdown",
"id": "f93f4400",
"metadata": {},
"source": [
"**Write a program to enter a number from user and print its individual digits on seperate line**"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "5ef97f05",
"metadata": {},
"outputs": [],
"source": [
"153\n",
"\n",
"1\n",
"5\n",
"3"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "e3d62d35",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter a number: 153\n",
"3\n",
"5\n",
"1\n"
]
}
],
"source": [
"n = int(input(\"Enter a number: \"))\n",
"s = 0\n",
"\n",
"while n > 0:\n",
" r = n % 10 # r = 3, 5, 1\n",
" print(r) # s = 0, 27, 152, 153\n",
" n = n // 10 # n = 153, 15, 1, 0\n"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "a5bbc5c8",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter a number: 153\n",
"1\n",
"5\n",
"3\n"
]
}
],
"source": [
"n = int(input(\"Enter a number: \"))\n",
"s = 0\n",
"\n",
"while n > 0:\n",
" r = n % 10 # r = 3, 5, 1\n",
" s = s*10 + r # s = 0, 27, 152, 153\n",
" n = n // 10 # n = 153, 15, 1, 0\n",
"\n",
"while s > 0:\n",
" r = s % 10\n",
" print(r)\n",
" s = s // 10"
]
},
{
"cell_type": "markdown",
"id": "decf806e",
"metadata": {},
"source": [
"# List\n",
"\n",
"collection of different type of elements"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9b33c6ed",
"metadata": {},
"outputs": [],
"source": [
"a = 10 # int\n",
"b = 20\n",
"c = 30"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "366b6a7a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[10, 'A', 'India', 10.6]\n",
"<class 'list'>\n"
]
}
],
"source": [
"l = [10, \"A\", \"India\", 10.6]\n",
"\n",
"print(l)\n",
"\n",
"print(type(l))"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "1af4f02d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10\n"
]
}
],
"source": [
"l = [10, \"A\", \"India\", 10.6]\n",
"# 0 1 2 3\n",
"\n",
"print(l[0])"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "ced31696",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10.6\n"
]
}
],
"source": [
"print(l[3])"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "0c0905a0",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"India\n"
]
}
],
"source": [
"print(l[2])"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "1fe65d17",
"metadata": {},
"outputs": [
{
"ename": "IndexError",
"evalue": "list index out of range",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mIndexError\u001b[0m Traceback (most recent call last)",
"Input \u001b[1;32mIn [16]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[43ml\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m5\u001b[39;49m\u001b[43m]\u001b[49m)\n",
"\u001b[1;31mIndexError\u001b[0m: list index out of range"
]
}
],
"source": [
"print(l[5])"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "c21b0555",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'int'>\n"
]
}
],
"source": [
"l = [10, \"A\", \"India\", 10.6]\n",
"# 0 1 2 3\n",
"\n",
"print(type(l[0]))"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "e9319c1c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[200, 'A', 'India', 10.6]\n"
]
}
],
"source": [
"l[0] = 200\n",
"\n",
"print(l)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "f8fe43a4",
"metadata": {},
"outputs": [
{
"ename": "IndexError",
"evalue": "list assignment index out of range",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mIndexError\u001b[0m Traceback (most recent call last)",
"Input \u001b[1;32mIn [19]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[0m l[\u001b[38;5;241m5\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1000\u001b[39m\n",
"\u001b[1;31mIndexError\u001b[0m: list assignment index out of range"
]
}
],
"source": [
"l[5] = 1000"
]
},
{
"cell_type": "markdown",
"id": "2aec1fac",
"metadata": {},
"source": [
"### negative index"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "d86147ba",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10.6\n"
]
}
],
"source": [
"# -4 -3 -2 -1\n",
"l = [10, \"A\", \"India\", 10.6]\n",
"# 0 1 2 3\n",
"\n",
"print(l[-1])"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "c3288372",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10.6\n"
]
}
],
"source": [
"print(l[3])"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "393bd2e7",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10\n",
"10\n"
]
}
],
"source": [
"print(l[0])\n",
"\n",
"print(l[-4])"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "07f8d2b4",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"India\n"
]
}
],
"source": [
"print(l[-2])"
]
},
{
"cell_type": "markdown",
"id": "18ef7bed",
"metadata": {},
"source": [
"# List Slicing"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "f556294d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[11, 22, 33, 44, 10, 24, 36, 68, 99, 81, 100]\n"
]
}
],
"source": [
"# -11-10 -9 -8 -7 -6 -5 -4 -3 -2 -1\n",
"l = [11,22,33,44,10,24,36,68,99,81,100]\n",
"# 0 1 2 3 4 5 6 7 8 9 10\n",
"\n",
"print(l)"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "61499c7e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[22, 33, 44, 10, 24, 36]\n"
]
}
],
"source": [
"print(l[1:7]) # l[start : end]"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "696ceede",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[11, 22, 33, 44, 10, 24, 36, 68, 99, 81, 100]\n"
]
}
],
"source": [
"print(l)"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "9c790873",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[10, 24, 36, 68, 99, 81]\n"
]
}
],
"source": [
"# -11-10 -9 -8 -7 -6 -5 -4 -3 -2 -1\n",
"l = [11,22,33,44,10,24,36,68,99,81,100]\n",
"# 0 1 2 3 4 5 6 7 8 9 10\n",
"\n",
"print(l[4:10])"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "88f74cab",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[99, 81]\n"
]
}
],
"source": [
"print(l[8:10])"
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "59a8810d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[11]\n"
]
}
],
"source": [
"print(l[0:1])"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "da404e2d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[22, 33, 44, 10, 24, 36, 68, 99, 81, 100]\n"
]
}
],
"source": [
"print(l[1:])"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "411185c6",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[99, 81, 100]\n"
]
}
],
"source": [
"print(l[8:])"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "f3427d62",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[11, 22, 33, 44, 10, 24, 36, 68, 99, 81, 100]\n"
]
}
],
"source": [
"print(l[:])"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "8cb04435",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[11, 22, 33, 44, 10]\n"
]
}
],
"source": [
"print(l[:5])"
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "07b3d8c8",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[11, 22, 33, 44, 10, 24, 36]\n"
]
}
],
"source": [
"# -11-10 -9 -8 -7 -6 -5 -4 -3 -2 -1\n",
"l = [11,22,33,44,10,24,36,68,99,81,100]\n",
"# 0 1 2 3 4 5 6 7 8 9 10\n",
"\n",
"print(l[0:-4])"
]
},
{
"cell_type": "code",
"execution_count": 35,
"id": "6b72269e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[33, 44, 10, 24, 36, 68, 99]\n"
]
}
],
"source": [
"print(l[2:-2])"
]
},
{
"cell_type": "code",
"execution_count": 36,
"id": "34eb2422",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[]\n"
]
}
],
"source": [
"print(l[2:0])"
]
},
{
"cell_type": "code",
"execution_count": 37,
"id": "ea9e9d22",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[]\n"
]
}
],
"source": [
"print(l[0:0])"
]
},
{
"cell_type": "code",
"execution_count": 38,
"id": "d4d6dc2c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[24, 36, 68, 99, 81, 100]\n"
]
}
],
"source": [
"print(l[5:15])"
]
},
{
"cell_type": "code",
"execution_count": 39,
"id": "327f5a53",
"metadata": {},
"outputs": [
{
"ename": "IndexError",
"evalue": "list index out of range",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mIndexError\u001b[0m Traceback (most recent call last)",
"Input \u001b[1;32mIn [39]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[43ml\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m15\u001b[39;49m\u001b[43m]\u001b[49m)\n",
"\u001b[1;31mIndexError\u001b[0m: list index out of range"
]
}
],
"source": [
"print(l[15])"
]
},
{
"cell_type": "code",
"execution_count": 40,
"id": "1654f679",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[22, 33, 44]\n"
]
}
],
"source": [
"# -11-10 -9 -8 -7 -6 -5 -4 -3 -2 -1\n",
"l = [11,22,33,44,10,24,36,68,99,81,100]\n",
"# 0 1 2 3 4 5 6 7 8 9 10\n",
"\n",
"print(l[1:4])"
]
},
{
"cell_type": "code",
"execution_count": 41,
"id": "ef550430",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[]\n"
]
}
],
"source": [
"print(l[4:1])"
]
},
{
"cell_type": "code",
"execution_count": 42,
"id": "64a79df5",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[68, 99, 81]\n"
]
}
],
"source": [
"print(l[-4:-1])"
]
},
{
"cell_type": "code",
"execution_count": 43,
"id": "70fecd4e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[]\n"
]
}
],
"source": [
"print(l[-1:-4])"
]
},
{
"cell_type": "markdown",
"id": "a2b17316",
"metadata": {},
"source": [
"## steps"
]
},
{
"cell_type": "code",
"execution_count": 44,
"id": "e9af568f",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[11, 33, 10, 36, 99, 100]\n"
]
}
],
"source": [
"# -11-10 -9 -8 -7 -6 -5 -4 -3 -2 -1\n",
"l = [11,22,33,44,10,24,36,68,99,81,100]\n",
"# 0 1 2 3 4 5 6 7 8 9 10\n",
"\n",
"print(l[0:11:2]) # l[start : end : steps]"
]
},
{
"cell_type": "code",
"execution_count": 45,
"id": "d0127e99",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[11, 44, 36, 81]\n"
]
}
],
"source": [
"print(l[0:11:3])"
]
},
{
"cell_type": "code",
"execution_count": 46,
"id": "75e4fefa",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[11, 22, 33, 44, 10, 24, 36, 68, 99, 81, 100]\n"
]
}
],
"source": [
"print(l[::])"
]
},
{
"cell_type": "code",
"execution_count": 47,
"id": "3449b6af",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[11, 22, 33, 44, 10, 24, 36, 68, 99, 81, 100]\n"
]
}
],
"source": [
"print(l[::1])"
]
},
{
"cell_type": "code",
"execution_count": 48,
"id": "2e6345c0",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[100, 81, 99, 68, 36, 24, 10, 44, 33, 22, 11]\n"
]
}
],
"source": [
"print(l[::-1]) # reverse"
]
},
{
"cell_type": "code",
"execution_count": 49,
"id": "f284f488",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[]\n"
]
}
],
"source": [
"# -11-10 -9 -8 -7 -6 -5 -4 -3 -2 -1\n",
"l = [11,22,33,44,10,24,36,68,99,81,100]\n",
"# 0 1 2 3 4 5 6 7 8 9 10\n",
"\n",
"print(l[4:8:-1])"
]
},
{
"cell_type": "code",
"execution_count": 50,
"id": "1f16a88d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[99, 68, 36, 24]\n"
]
}
],
"source": [
"print(l[8:4:-1])"
]
},
{
"cell_type": "code",
"execution_count": 51,
"id": "11575dee",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[100, 99, 36, 10, 33, 11]\n"
]
}
],
"source": [
"print(l[::-2])"
]
},
{
"cell_type": "code",
"execution_count": 52,
"id": "1a639620",
"metadata": {},
"outputs": [
{
"ename": "ValueError",
"evalue": "slice step cannot be zero",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mValueError\u001b[0m Traceback (most recent call last)",
"Input \u001b[1;32mIn [52]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[43ml\u001b[49m\u001b[43m[\u001b[49m\u001b[43m:\u001b[49m\u001b[43m:\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m)\n",
"\u001b[1;31mValueError\u001b[0m: slice step cannot be zero"
]
}
],
"source": [
"print(l[::0])"
]
},
{
"cell_type": "markdown",
"id": "20862888",
"metadata": {},
"source": [
"## list functions"
]
},
{
"cell_type": "code",
"execution_count": 53,
"id": "8aa952c9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"5\n"
]
}
],
"source": [
"l = [10,20,30,40,50]\n",
"\n",
"print(len(l))"
]
},
{
"cell_type": "code",
"execution_count": 54,
"id": "74856061",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"4\n"
]
}
],
"source": [
"print(len(l) - 1)"
]
},
{
"cell_type": "code",
"execution_count": 55,
"id": "250b458e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"150\n"
]
}
],
"source": [
"print(sum(l))"
]
},
{
"cell_type": "code",
"execution_count": 56,
"id": "7ea78614",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"50\n"
]
}
],
"source": [
"print(max(l))"
]
},
{
"cell_type": "code",
"execution_count": 57,
"id": "bad8aadc",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10\n"
]
}
],
"source": [
"print(min(l))"
]
},
{
"cell_type": "code",
"execution_count": 58,
"id": "27a21618",
"metadata": {},
"outputs": [
{
"ename": "TypeError",
"evalue": "unsupported operand type(s) for +: 'int' and 'str'",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)",
"Input \u001b[1;32mIn [58]\u001b[0m, in \u001b[0;36m<cell line: 3>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m l \u001b[38;5;241m=\u001b[39m [\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mA\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;241m10\u001b[39m,\u001b[38;5;241m20\u001b[39m,\u001b[38;5;241m30\u001b[39m]\n\u001b[1;32m----> 3\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;28;43msum\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43ml\u001b[49m\u001b[43m)\u001b[49m)\n",
"\u001b[1;31mTypeError\u001b[0m: unsupported operand type(s) for +: 'int' and 'str'"
]
}
],
"source": [
"l = [\"A\", 10,20,30]\n",
"\n",
"print(sum(l))"
]
},
{
"cell_type": "code",
"execution_count": 59,
"id": "a176b651",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"4\n"
]
}
],
"source": [
"print(len(l))"
]
},
{
"cell_type": "markdown",
"id": "1ee80d7b",
"metadata": {},
"source": [
"# List methods"
]
},
{
"cell_type": "code",
"execution_count": 61,
"id": "e802bef5",
"metadata": {},
"outputs": [],
"source": [
"# help(print)"
]
},
{
"cell_type": "code",
"execution_count": 63,
"id": "5a500f31",
"metadata": {
"scrolled": false
},
"outputs": [],
"source": [
"# help(list)"
]
},
{
"cell_type": "code",
"execution_count": 64,
"id": "0538c1e8",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[10, 20, 30, 40]\n"
]
}
],
"source": [
"l = [10,20,30]\n",
"\n",
"l.append(40)\n",
"\n",
"print(l)"
]
},
{
"cell_type": "code",
"execution_count": 65,
"id": "ed712c2b",
"metadata": {},
"outputs": [],
"source": [
"l.append(\"India\")"
]
},
{
"cell_type": "code",
"execution_count": 66,
"id": "265b8be2",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[10, 20, 30, 40, 'India']\n"
]
}
],
"source": [
"print(l)"
]
},
{
"cell_type": "code",
"execution_count": 67,
"id": "ea15af1f",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"4\n"
]
}
],
"source": [
"print(l.index('India'))"
]
},
{
"cell_type": "code",
"execution_count": 68,
"id": "c422ce83",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0\n"
]
}
],
"source": [
"print(l.index(10))"
]
},
{
"cell_type": "code",
"execution_count": 69,
"id": "0e88a9f3",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[10, 20, 30, 40, 'India']\n"
]
}
],
"source": [
"print(l)"
]
},
{
"cell_type": "code",
"execution_count": 72,
"id": "e3042d8a",
"metadata": {},
"outputs": [],
"source": [
"l.reverse()"
]
},
{
"cell_type": "code",
"execution_count": 73,
"id": "02a28ba4",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[10, 20, 30, 40, 'India']\n"
]
}
],
"source": [
"print(l)"
]
},
{
"cell_type": "code",
"execution_count": 74,
"id": "7c861f47",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['India', 40, 30, 20, 10]\n"
]
}
],
"source": [
"print(l[::-1])"
]
},
{
"cell_type": "code",
"execution_count": 75,
"id": "e1210f8f",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[10, 20, 30, 40, 'India']\n"
]
}
],
"source": [
"print(l)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "ef9c13af",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.12"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
================================================
FILE: July Cohort 2023/1_Python Programming/.ipynb_checkpoints/04_Strings and For loop-checkpoint.ipynb
================================================
{
"cells": [
{
"cell_type": "markdown",
"id": "89086545",
"metadata": {},
"source": [
"# Strings\n",
"\n",
"set of characters\n"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "663dd2fc",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"hello\n"
]
}
],
"source": [
"# -1\n",
"s = 'hello'\n",
"# 01234\n",
"\n",
"print(s)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "d1f891e2",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"h\n"
]
}
],
"source": [
"print(s[0])"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "549cabfa",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"o\n"
]
}
],
"source": [
"print(s[4])"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "e9b26f8e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"o\n"
]
}
],
"source": [
"print(s[-1])"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "bef31594",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"l\n"
]
}
],
"source": [
"print(s[-2])"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "00f3823f",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'str'>\n"
]
}
],
"source": [
"print(type(s))"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "7326e7a9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'str'>\n"
]
}
],
"source": [
"print(type(s[0]))"
]
},
{
"cell_type": "markdown",
"id": "4899cd30",
"metadata": {},
"source": [
"# string slicing"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "12c56ed2",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"commu\n"
]
}
],
"source": [
"s = 'communication'\n",
"# 0123456789\n",
"\n",
"print(s[0:5])"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "781ea5cd",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"noitacinummoc\n"
]
}
],
"source": [
"print(s[::-1])"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "90aa93d3",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"omm\n"
]
}
],
"source": [
"print(s[1:4])"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "5c24d8b3",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n"
]
}
],
"source": [
"s = 'communication'\n",
"# 0123456789\n",
"\n",
"print(s[4:1])"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "a8f6af2e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'str'>\n"
]
}
],
"source": [
"s = ''\n",
"\n",
"print(type(s))"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "2d3570c7",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"noitacin\n"
]
}
],
"source": [
"s = 'communication'\n",
"# 0123456789\n",
"\n",
"print(s[-1:-9:-1])"
]
},
{
"cell_type": "markdown",
"id": "ef70cbf4",
"metadata": {},
"source": [
"# String Functions"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "f12266cf",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"13\n"
]
}
],
"source": [
"s = 'communication'\n",
"\n",
"print(len(s))"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "50320c72",
"metadata": {},
"outputs": [
{
"ename": "TypeError",
"evalue": "unsupported operand type(s) for +: 'int' and 'str'",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)",
"Input \u001b[1;32mIn [15]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;28;43msum\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43ms\u001b[49m\u001b[43m)\u001b[49m)\n",
"\u001b[1;31mTypeError\u001b[0m: unsupported operand type(s) for +: 'int' and 'str'"
]
}
],
"source": [
"print(sum(s)) # s = 0"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "55b002c3",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"u\n"
]
}
],
"source": [
"print(max(s))"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "7ccced34",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"a\n"
]
}
],
"source": [
"print(min(s))"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8b30e14f",
"metadata": {},
"outputs": [],
"source": [
"# ASCII\n",
"\n",
"'A' -> 65\n",
"'B' -> 66\n",
"'Z' -> 90\n",
"\n",
"'a' -> 97\n",
"'z' -> 122\n",
"\n",
"' ' -> 32 -> space"
]
},
{
"cell_type": "markdown",
"id": "afa17626",
"metadata": {},
"source": [
"## string methods\n"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "e3ef73fb",
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"# help(str)"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "53f436a8",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"False"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"'raj123' == 'RAJ123'"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "9a9f840d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"raj123\n"
]
}
],
"source": [
"s = 'RAJ123'\n",
"\n",
"print(s.casefold())"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "4e6cd479",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"INDIA\n"
]
}
],
"source": [
"s = 'India'\n",
"\n",
"print(s.upper())"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "76b04479",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"india\n"
]
}
],
"source": [
"print(s.lower())"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "2e8f43e5",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['This', 'is', 'an', 'apple']\n"
]
}
],
"source": [
"# split\n",
"\n",
"s = 'This is an apple'\n",
"\n",
"print(s.split(\" \"))"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "94237ec7",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['H', 'llo Us', 'r']\n"
]
}
],
"source": [
"s = \"Hello User\"\n",
"\n",
"print(s.split(\"e\"))"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "42a71402",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"This+is+an+apple\n"
]
}
],
"source": [
"# join\n",
"\n",
"l = ['This', 'is', 'an', 'apple']\n",
"\n",
"a = \"+\"\n",
"\n",
"print(a.join(l))"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "6ef43d06",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"This is an apple\n"
]
}
],
"source": [
"# join\n",
"\n",
"l = ['This', 'is', 'an', 'apple']\n",
"\n",
"a = \" \"\n",
"\n",
"print(a.join(l))\n",
"# \" \".join(l)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "dae0d39a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ThisisanApple\n"
]
}
],
"source": [
"# remove all the spaces from the string\n",
"\n",
"s = \"This is an Apple\"\n",
"\n",
"l = s.split(\" \")\n",
"\n",
"x = \"\".join(l)\n",
"\n",
"print(x)"
]
},
{
"cell_type": "markdown",
"id": "5e18c7bc",
"metadata": {},
"source": [
"**Write a program to enter a string from user and print the biggest word from the para**"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "fc9ffad3",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "08b8681d",
"metadata": {},
"source": [
"# range function"
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "cd95ff5d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"range(0, 5)\n"
]
}
],
"source": [
"n = range(5) # this will create a series of numbers from 0 to 4\n",
"\n",
"print(n)"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "5faa24f2",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'range'>\n"
]
}
],
"source": [
"print(type(n))"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "b9b1b6fa",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[0, 1, 2, 3, 4]\n"
]
}
],
"source": [
"n = list(range(5))\n",
"\n",
"print(n)"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "00bf5fc9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[3, 4, 5, 6, 7]\n"
]
}
],
"source": [
"n = list(range(3,8))\n",
"\n",
"print(n)"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "85f51f76",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"True\n"
]
}
],
"source": [
"print(range(20) == range(0,20))"
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "cf56e7cc",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[5, 7, 9, 11, 13, 15, 17, 19]\n"
]
}
],
"source": [
"n = list(range(5,20,2)) # range(start, end, steps)\n",
"\n",
"print(n)"
]
},
{
"cell_type": "markdown",
"id": "9a9e11b2",
"metadata": {},
"source": [
"## for loop"
]
},
{
"cell_type": "code",
"execution_count": 35,
"id": "eb461d52",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"False\n"
]
}
],
"source": [
"l = [\"A\", \"B\", \"C\", \"D\"]\n",
"\n",
"print(\"Z\" in l)"
]
},
{
"cell_type": "code",
"execution_count": 36,
"id": "f3d37b0a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"A\n",
"B\n",
"C\n",
"D\n"
]
}
],
"source": [
"l = [\"A\", \"B\", \"C\", \"D\"]\n",
"# i\n",
"\n",
"# \"B\" in l\n",
"for i in l:\n",
" print(i)"
]
},
{
"cell_type": "code",
"execution_count": 37,
"id": "15a3f0ba",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"A\n",
"Hi\n",
"B\n",
"Hi\n",
"C\n",
"Hi\n",
"D\n",
"Hi\n"
]
}
],
"source": [
"l = [\"A\", \"B\", \"C\", \"D\"]\n",
"# i\n",
"\n",
"# \"B\" in l\n",
"for i in l:\n",
" print(i)\n",
" print(\"Hi\")"
]
},
{
"cell_type": "code",
"execution_count": 40,
"id": "59f4f57f",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"a\n",
"b\n",
"c\n",
"d\n"
]
}
],
"source": [
"s = 'abcd'\n",
"\n",
"for i in s:\n",
" print(i)"
]
},
{
"cell_type": "code",
"execution_count": 42,
"id": "be302d25",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"AB\n",
"ab\n"
]
}
],
"source": [
"x = 'ab'\n",
"\n",
"print(x.upper())\n",
"\n",
"print(x)"
]
},
{
"cell_type": "code",
"execution_count": 43,
"id": "b3a22f15",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['ab', 'cd']\n"
]
}
],
"source": [
"x = ['ab', 'cd']\n",
"\n",
"for i in x:\n",
" i.upper() # 'ab'.upper() -> 'AB'\n",
" \n",
"print(x)"
]
},
{
"cell_type": "code",
"execution_count": 44,
"id": "4e0873d9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"AB\n",
"CD\n",
"['ab', 'cd']\n"
]
}
],
"source": [
"x = ['ab', 'cd']\n",
"\n",
"for i in x:\n",
" print(i.upper()) # 'ab'.upper() -> 'AB'\n",
" \n",
"print(x)"
]
},
{
"cell_type": "code",
"execution_count": 45,
"id": "77e96be5",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"a\n",
"b\n",
"c\n",
"d\n"
]
}
],
"source": [
"x = 'abcd'\n",
"\n",
"for i in x:\n",
" print(i)\n",
" x.upper()\n"
]
},
{
"cell_type": "code",
"execution_count": 46,
"id": "d6c07e4d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0\n",
"1\n",
"2\n",
"3\n",
"4\n"
]
}
],
"source": [
"# i\n",
"# 0,1,2,3,4\n",
"for i in range(5):\n",
" print(i)"
]
},
{
"cell_type": "code",
"execution_count": 47,
"id": "bba46637",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"5\n",
"6\n",
"7\n",
"8\n",
"9\n"
]
}
],
"source": [
"for i in range(5,10):\n",
" print(i)"
]
},
{
"cell_type": "code",
"execution_count": 48,
"id": "fdb6483c",
"metadata": {},
"outputs": [
{
"ename": "TypeError",
"evalue": "'str' object cannot be interpreted as an integer",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)",
"Input \u001b[1;32mIn [48]\u001b[0m, in \u001b[0;36m<cell line: 3>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m x \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mabcd\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m----> 3\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28;43mrange\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[43m)\u001b[49m:\n\u001b[0;32m 4\u001b[0m \u001b[38;5;28mprint\u001b[39m(i)\n",
"\u001b[1;31mTypeError\u001b[0m: 'str' object cannot be interpreted as an integer"
]
}
],
"source": [
"x = 'abcd'\n",
"\n",
"for i in range(x):\n",
" print(i)"
]
},
{
"cell_type": "code",
"execution_count": 49,
"id": "dac1b7e1",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0\n",
"1\n",
"2\n",
"3\n"
]
}
],
"source": [
"x = 'abcd'\n",
"\n",
"# 0,1,2,3\n",
"for i in range(len(x)):\n",
" print(i)"
]
},
{
"cell_type": "code",
"execution_count": 50,
"id": "ce020a17",
"metadata": {},
"outputs": [
{
"ename": "AttributeError",
"evalue": "'int' object has no attribute 'upper'",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)",
"Input \u001b[1;32mIn [50]\u001b[0m, in \u001b[0;36m<cell line: 4>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 3\u001b[0m \u001b[38;5;66;03m# 0,1,2,3\u001b[39;00m\n\u001b[0;32m 4\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;28mlen\u001b[39m(x)):\n\u001b[1;32m----> 5\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[43mi\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mupper\u001b[49m())\n",
"\u001b[1;31mAttributeError\u001b[0m: 'int' object has no attribute 'upper'"
]
}
],
"source": [
"x = 'abcd'\n",
"\n",
"# 0,1,2,3\n",
"for i in range(len(x)):\n",
" print(i.upper())"
]
},
{
"cell_type": "code",
"execution_count": 51,
"id": "e4b348f0",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"abcd\n"
]
}
],
"source": [
"x = 'abcd'\n",
"\n",
"# 0,1,2,3\n",
"for i in range(len(x)):\n",
" x[i].upper()\n",
"\n",
"print(x)"
]
},
{
"cell_type": "code",
"execution_count": 52,
"id": "e4afa49b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"A\n",
"B\n",
"C\n",
"D\n",
"abcd\n"
]
}
],
"source": [
"x = 'abcd'\n",
"\n",
"# 0,1,2,3\n",
"for i in range(len(x)):\n",
" print(x[i].upper())\n",
"\n",
"print(x)"
]
},
{
"cell_type": "code",
"execution_count": 53,
"id": "9d691550",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"a\n",
"a\n",
"a\n",
"a\n"
]
}
],
"source": [
"x = 'abcd'\n",
"\n",
"# 0,1,2,3\n",
"for i in range(len(x)):\n",
" x = 'a' # x = 'abcd', 'a', 'a'\n",
" print(x)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9fe9971b",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.12"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
================================================
FILE: July Cohort 2023/1_Python Programming/.ipynb_checkpoints/05_Dictionary Tuples and Set-checkpoint.ipynb
================================================
{
"cells": [
{
"cell_type": "markdown",
"id": "34a4e5e6",
"metadata": {},
"source": [
"# Dictionary"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "cb73a69f",
"metadata": {},
"outputs": [],
"source": [
"# { key : value }\n",
"\n",
"unordered data structures"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "9c5ff7b6",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'ravi': 24, 'shyam': 21, 'roy': 41}\n"
]
}
],
"source": [
"ages = {\"ravi\":24, \"shyam\": 21, \"roy\": 41}\n",
"\n",
"print(ages)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "fc51983d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'dict'>\n"
]
}
],
"source": [
"print(type(ages))"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "45957197",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"24\n"
]
}
],
"source": [
"print(ages['ravi'])"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "8587855f",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"41\n"
]
}
],
"source": [
"print(ages['roy'])"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "bcc42db7",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[255, 0, 0]\n"
]
}
],
"source": [
"color = {\n",
" \"red\": [255,0,0],\n",
" \"green\": [0,255,0],\n",
" \"blue\": [0,0,255]\n",
"}\n",
"print(color['red'])"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "f28a6d43",
"metadata": {},
"outputs": [
{
"ename": "KeyError",
"evalue": "'yellow'",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mKeyError\u001b[0m Traceback (most recent call last)",
"Input \u001b[1;32mIn [7]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[43mcolor\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43myellow\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m)\n",
"\u001b[1;31mKeyError\u001b[0m: 'yellow'"
]
}
],
"source": [
"print(color['yellow'])"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "98fd771e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{}\n",
"<class 'dict'>\n"
]
}
],
"source": [
"d = {}\n",
"print(d)\n",
"print(type(d))"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "02b6f0ff",
"metadata": {},
"outputs": [
{
"ename": "TypeError",
"evalue": "unhashable type: 'list'",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)",
"Input \u001b[1;32mIn [9]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[0m d \u001b[38;5;241m=\u001b[39m {[\u001b[38;5;241m1\u001b[39m,\u001b[38;5;241m2\u001b[39m]:\u001b[38;5;241m10\u001b[39m, \u001b[38;5;241m2\u001b[39m:\u001b[38;5;241m2\u001b[39m, \u001b[38;5;241m3\u001b[39m:\u001b[38;5;241m3\u001b[39m}\n\u001b[0;32m 2\u001b[0m \u001b[38;5;28mprint\u001b[39m(d)\n",
"\u001b[1;31mTypeError\u001b[0m: unhashable type: 'list'"
]
}
],
"source": [
"d = {[1,2]:10, 2:2, 3:3}\n",
"print(d)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "080bd938",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[100, 20]\n"
]
}
],
"source": [
"# list are mutable objects\n",
"\n",
"l = [10,20]\n",
"l[0] = 100\n",
"print(l)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "0efe853a",
"metadata": {},
"outputs": [
{
"ename": "TypeError",
"evalue": "'str' object does not support item assignment",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)",
"Input \u001b[1;32mIn [11]\u001b[0m, in \u001b[0;36m<cell line: 4>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[38;5;66;03m# strings are immutable objects\u001b[39;00m\n\u001b[0;32m 3\u001b[0m s \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mindore\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m----> 4\u001b[0m s[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mA\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 5\u001b[0m \u001b[38;5;28mprint\u001b[39m(s)\n",
"\u001b[1;31mTypeError\u001b[0m: 'str' object does not support item assignment"
]
}
],
"source": [
"# strings are immutable objects\n",
"\n",
"s = 'indore'\n",
"s[0] = \"A\"\n",
"print(s)"
]
},
{
"cell_type": "markdown",
"id": "6de43fed",
"metadata": {},
"source": [
"# Dictionary Functions"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "da7184d8",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"4\n"
]
}
],
"source": [
"d = {1:11, 2:41, 13:9, 14:16}\n",
"\n",
"print(len(d))"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "2439c0d6",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"30\n"
]
}
],
"source": [
"print(sum(d))"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "3842f621",
"metadata": {},
"outputs": [
{
"ename": "TypeError",
"evalue": "unsupported operand type(s) for +: 'int' and 'str'",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)",
"Input \u001b[1;32mIn [14]\u001b[0m, in \u001b[0;36m<cell line: 3>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m a \u001b[38;5;241m=\u001b[39m {\u001b[38;5;241m1\u001b[39m:\u001b[38;5;241m2\u001b[39m, \u001b[38;5;241m3\u001b[39m:\u001b[38;5;241m4\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhi\u001b[39m\u001b[38;5;124m\"\u001b[39m:\u001b[38;5;241m16\u001b[39m}\n\u001b[1;32m----> 3\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;28;43msum\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43ma\u001b[49m\u001b[43m)\u001b[49m)\n",
"\u001b[1;31mTypeError\u001b[0m: unsupported operand type(s) for +: 'int' and 'str'"
]
}
],
"source": [
"a = {1:2, 3:4, \"hi\":16}\n",
"\n",
"print(sum(a))"
]
},
{
"cell_type": "markdown",
"id": "72a7d21d",
"metadata": {},
"source": [
"# Dictionary Methods"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "dda87168",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{1: 'Apple', 'orange': [2, 3, 4], '2': '23'}\n"
]
}
],
"source": [
"pair = {1:\"Apple\", \"orange\": [2,3,4], \"2\":\"23\"}\n",
"\n",
"print(pair)"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "031cb949",
"metadata": {
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[2, 3, 4]\n"
]
}
],
"source": [
"# get\n",
"# help(dict)\n",
"\n",
"print(pair.get(\"orange\"))"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "cba8f060",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"None\n"
]
}
],
"source": [
"print(pair.get(7))"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "32604209",
"metadata": {},
"outputs": [],
"source": [
"None ==> NULL ==> nothing"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "d7d265af",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Apple\n"
]
}
],
"source": [
"print(pair.get(1,\"Element not found\"))"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "ff1c3065",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Element not found\n"
]
}
],
"source": [
"print(pair.get(10,\"Element not found\"))"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "a75186b5",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{1: 'Apple', 'orange': [2, 3, 4], '2': '23'}\n",
"{}\n"
]
}
],
"source": [
"# clear\n",
"\n",
"p = {1:\"Apple\", \"orange\": [2,3,4], \"2\":\"23\"}\n",
"\n",
"print(p)\n",
"p.clear()\n",
"print(p)"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "d153a547",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"dict_keys([1, 2, 3])\n"
]
}
],
"source": [
"# keys\n",
"\n",
"r = {1:\"A\", 2:'Zara', 3:\"Maza\"}\n",
"\n",
"print(r.keys())"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "b0c31ff7",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[1, 2, 3]\n"
]
}
],
"source": [
"print(list(r.keys()))"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "0afa95ad",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"dict_values(['A', 'Zara', 'Maza'])\n"
]
}
],
"source": [
"# values\n",
"\n",
"r = {1:\"A\", 2:'Zara', 3:\"Maza\"}\n",
"\n",
"print(r.values())"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "9c024e2a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['A', 'Zara', 'Maza']\n"
]
}
],
"source": [
"print(list(r.values()))"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "4d0c19d7",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{3: 'Maza', 2: 'Zara'}\n",
"2\n"
]
}
],
"source": [
"r = {3:\"A\", 2:'Zara', 3:\"Maza\"}\n",
"\n",
"print(r)\n",
"\n",
"print(len(r))"
]
},
{
"cell_type": "markdown",
"id": "104a3ab9",
"metadata": {},
"source": [
"# Question\n",
"\n",
"print the following series"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7f5a1e63",
"metadata": {},
"outputs": [],
"source": [
"{1:1, 2:4, 3:9, 4:16, .........10:100}"
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "7c6a9d9a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{1: 2, 3: 'Hi'}\n"
]
}
],
"source": [
"a = {1:2}\n",
"a[3] = \"Hi\"\n",
"print(a)"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "e1ec63ea",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{1: 1, 2: 4, 3: 9, 4: 16, 5: 25, 6: 36, 7: 49, 8: 64, 9: 81, 10: 100}\n"
]
}
],
"source": [
"d = {}\n",
"\n",
"for i in range(1,11):\n",
" d[i] = i * i\n",
"\n",
"print(d)"
]
},
{
"cell_type": "markdown",
"id": "ae9ad8ce",
"metadata": {},
"source": [
"# Tuples"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "926d2c80",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(4, 3, 5, 6)\n",
"<class 'tuple'>\n"
]
}
],
"source": [
"t = (4,3,5,6)\n",
"# 0 1 2 3\n",
"\n",
"print(t)\n",
"\n",
"print(type(t))"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "0184a528",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"4\n"
]
}
],
"source": [
"print(t[0])"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "67632ef3",
"metadata": {},
"outputs": [
{
"ename": "TypeError",
"evalue": "'tuple' object does not support item assignment",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)",
"Input \u001b[1;32mIn [33]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[0m t[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m11\u001b[39m\n",
"\u001b[1;31mTypeError\u001b[0m: 'tuple' object does not support item assignment"
]
}
],
"source": [
"t[0] = 11 # tuple are immutable objects"
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "b6045c0f",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"('one', 'two', 'three')\n"
]
}
],
"source": [
"t = \"one\", \"two\", \"three\"\n",
"\n",
"print(t)"
]
},
{
"cell_type": "code",
"execution_count": 35,
"id": "ffa2af8b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'tuple'>\n"
]
}
],
"source": [
"print(type(t))"
]
},
{
"cell_type": "code",
"execution_count": 36,
"id": "2efc8510",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10\n",
"<class 'int'>\n"
]
}
],
"source": [
"t = (10)\n",
"print(t)\n",
"print(type(t))"
]
},
{
"cell_type": "code",
"execution_count": 37,
"id": "da1bb799",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(10,)\n",
"<class 'tuple'>\n"
]
}
],
"source": [
"t = (10,)\n",
"print(t)\n",
"print(type(t))"
]
},
{
"cell_type": "markdown",
"id": "4cae5690",
"metadata": {},
"source": [
"# Tuple unpacking"
]
},
{
"cell_type": "code",
"execution_count": 38,
"id": "58a607f3",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1\n",
"2\n",
"3\n"
]
}
],
"source": [
"n = (1,2,3)\n",
"\n",
"a,b,c = n\n",
"\n",
"print(a)\n",
"print(b)\n",
"print(c)"
]
},
{
"cell_type": "markdown",
"id": "b276c6bf",
"metadata": {},
"source": [
"# Tuple Slicing"
]
},
{
"cell_type": "code",
"execution_count": 39,
"id": "92e79ee4",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(11, 22, 33, 44, 55, 66, 77, 88, 99, 100)\n"
]
}
],
"source": [
"# -1\n",
"t = (11,22,33,44,55,66,77,88,99,100)\n",
"# 0 1 \n",
"\n",
"print(t)"
]
},
{
"cell_type": "code",
"execution_count": 40,
"id": "57630079",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(44, 55)\n"
]
}
],
"source": [
"print(t[3:5])"
]
},
{
"cell_type": "code",
"execution_count": 41,
"id": "fec889a9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(11, 22, 33, 44, 55, 66)\n"
]
}
],
"source": [
"print(t[:6])"
]
},
{
"cell_type": "code",
"execution_count": 42,
"id": "503f8dba",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(33, 44, 55, 66)\n"
]
}
],
"source": [
"print(t[-8:-4])"
]
},
{
"cell_type": "code",
"execution_count": 43,
"id": "a0ba748f",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"()\n"
]
}
],
"source": [
"print(t[-4:-8])"
]
},
{
"cell_type": "code",
"execution_count": 44,
"id": "fa4cc944",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(100, 99, 88, 77, 66, 55, 44, 33, 22, 11)\n"
]
}
],
"source": [
"print(t[::-1])"
]
},
{
"cell_type": "markdown",
"id": "9b4af08a",
"metadata": {},
"source": [
"# Tuple Methods"
]
},
{
"cell_type": "code",
"execution_count": 45,
"id": "7bbdf0aa",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"3\n"
]
}
],
"source": [
"# count\n",
"\n",
"t = (2,3,4,5,5,6,6,4,4,)\n",
"\n",
"print(t.count(4))\n"
]
},
{
"cell_type": "code",
"execution_count": 46,
"id": "ad80d733",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"2\n"
]
}
],
"source": [
"# index\n",
"\n",
"t = (2,3,4,5,5,6,6,4,4,)\n",
"\n",
"print(t.index(4))"
]
},
{
"cell_type": "code",
"execution_count": 47,
"id": "df41de26",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Help on built-in function index:\n",
"\n",
"index(value, start=0, stop=9223372036854775807, /) method of builtins.tuple instance\n",
" Return first index of value.\n",
" \n",
" Raises ValueError if the value is not present.\n",
"\n"
]
}
],
"source": [
"help(t.index)"
]
},
{
"cell_type": "code",
"execution_count": 48,
"id": "86d6e3a9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"7\n"
]
}
],
"source": [
"# index\n",
"\n",
"t = (2,3,4,5,5,6,6,4,4,)\n",
"\n",
"print(t.index(4, 5))"
]
},
{
"cell_type": "markdown",
"id": "ff55ace0",
"metadata": {},
"source": [
"# Tuple functions"
]
},
{
"cell_type": "code",
"execution_count": 49,
"id": "d2e05c64",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"5\n"
]
}
],
"source": [
"t = (2,3,4,5,6)\n",
"\n",
"print(len(t))"
]
},
{
"cell_type": "code",
"execution_count": 50,
"id": "2f71a91b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"20\n"
]
}
],
"source": [
"print(sum(t))"
]
},
{
"cell_type": "code",
"execution_count": 51,
"id": "f9c6d5a3",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"6\n"
]
}
],
"source": [
"print(max(t))"
]
},
{
"cell_type": "markdown",
"id": "23dad4a2",
"metadata": {},
"source": [
"# Question"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "c1ee0321",
"metadata": {},
"outputs": [],
"source": [
"# remove i from this tuple\n",
"\n",
"t = ('a', 'e','i', 'o', 'u')"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.12"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
================================================
FILE: July Cohort 2023/1_Python Programming/01_Python Basics.ipynb
================================================
{
"cells": [
{
"cell_type": "markdown",
"id": "5effdff7",
"metadata": {},
"source": [
"# Python Basics"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "d04e5b22",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello User\n"
]
}
],
"source": [
"print(\"Hello User\")"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "b0091bf1",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello\n",
"User\n"
]
}
],
"source": [
"print(\"Hello\")\n",
"print(\"User\")"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "fb83814b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello\n",
"User\n"
]
}
],
"source": [
"print(\"Hello\\nUser\") # \\n -> new line character"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "791c342a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello\tUser\n"
]
}
],
"source": [
"print(\"Hello\\tUser\") # \\t -> horizontal tab - 8 spaces"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9fad4ea5",
"metadata": {},
"outputs": [],
"source": [
"# binary language -> 101010111 -> bits\n",
"\n",
"0 -> low voltage, no-charge, false, off\n",
"1 -> high voltage, charge, true, on"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a1885e98",
"metadata": {},
"outputs": [],
"source": [
"bits > numbers > character > instructions > program > software"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "cbe99e7d",
"metadata": {},
"outputs": [],
"source": [
"source code ---------> Byte Code --------> output\n",
" .c compile .bak run .exe\n",
" .cpp .obj\n",
" .java .javac\n",
" .py .pyc"
]
},
{
"cell_type": "markdown",
"id": "8a713554",
"metadata": {},
"source": [
"# Variables"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "5c20abe8",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10\n"
]
}
],
"source": [
"a = 10\n",
"\n",
"print(a)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "995009df",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"45.13\n"
]
}
],
"source": [
"b = 45.13\n",
"\n",
"print(b)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "17194c9e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"India\n"
]
}
],
"source": [
"a = \"India\"\n",
"\n",
"print(a)"
]
},
{
"cell_type": "markdown",
"id": "9141a786",
"metadata": {},
"source": [
"# Data Types"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "6ba6bfd9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10\n",
"<class 'int'>\n"
]
}
],
"source": [
"a = 10\n",
"\n",
"print(a)\n",
"\n",
"print(type(a))"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "a6e1a232",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10.65\n",
"<class 'float'>\n"
]
}
],
"source": [
"b = 10.65\n",
"\n",
"print(b)\n",
"\n",
"print(type(b))"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "1298d5d3",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"colors\n",
"<class 'str'>\n"
]
}
],
"source": [
"c = \"colors\"\n",
"\n",
"print(c)\n",
"\n",
"print(type(c))"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "47c38fa9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"colors\n",
"<class 'str'>\n"
]
}
],
"source": [
"c = 'colors'\n",
"\n",
"print(c)\n",
"\n",
"print(type(c))"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "0acb14e3",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"it's an apple\n"
]
}
],
"source": [
"x = \"it's an apple\"\n",
"\n",
"print(x)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "fb2beb48",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"it\"s an apple\n"
]
}
],
"source": [
"x = 'it\"s an apple'\n",
"\n",
"print(x)"
]
},
{
"cell_type": "markdown",
"id": "814feca5",
"metadata": {},
"source": [
"# Input Function"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "437ffd33",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10\n",
"10\n"
]
}
],
"source": [
"a = input()\n",
"\n",
"print(a)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "8c71996c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter Your Name: Himanshu\n",
"Himanshu\n"
]
}
],
"source": [
"a = input(\"Enter Your Name: \")\n",
"\n",
"print(a)"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "792f782d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter Your Name: Himanshu\n",
"Hello! How are you? Himanshu\n"
]
}
],
"source": [
"a = input(\"Enter Your Name: \")\n",
"\n",
"print(\"Hello! How are you?\", a)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "8ab7e6a7",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello Him\n"
]
}
],
"source": [
"print(\"Hello Him\")"
]
},
{
"cell_type": "markdown",
"id": "84b26329",
"metadata": {},
"source": [
"# Questions"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "376a1bc0",
"metadata": {},
"outputs": [],
"source": [
"Your Name\n",
"------8-------College/Company\n",
"------------16-------------Country"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f60668a8",
"metadata": {},
"outputs": [],
"source": [
"*\n",
"**\n",
"***"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7c2fa48a",
"metadata": {},
"outputs": [],
"source": [
"--4--*\n",
"*----8----*\n",
"--4--*"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "2650f9ed",
"metadata": {},
"outputs": [],
"source": [
" *\n",
"* *\n",
" *"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.12"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
================================================
FILE: July Cohort 2023/1_Python Programming/02_03_While Loop and List.ipynb
================================================
{
"cells": [
{
"cell_type": "markdown",
"id": "13c6ac1c",
"metadata": {},
"source": [
"# While Loop"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "0290b931",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Himanshu\n",
"Himanshu\n"
]
}
],
"source": [
"print(\"Himanshu\")\n",
"print(\"Himanshu\")"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "aab5a9d5",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"True\n"
]
}
],
"source": [
"i = 1\n",
"\n",
"print(i <= 5)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "be002b98",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"False\n"
]
}
],
"source": [
"print(i >= 5)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "903683b3",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"True\n"
]
}
],
"source": [
"print(i >= 1)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "76da14cf",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Himanshu\n",
"Himanshu\n",
"Himanshu\n",
"Himanshu\n",
"Himanshu\n"
]
}
],
"source": [
"i = 1\n",
"\n",
"while i <= 5:\n",
" print(\"Himanshu\")\n",
" i = i + 1 # i = 1, 2, 3, 4, 5, 6"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "145ad944",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1\n",
"2\n",
"3\n",
"4\n",
"5\n"
]
}
],
"source": [
"i = 1\n",
"\n",
"while i <= 5:\n",
" print(i)\n",
" i = i + 1"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "cdad3efc",
"metadata": {},
"outputs": [],
"source": [
"1\n",
"2\n",
"3\n",
"4\n",
"5\n",
"6\n",
"7\n",
"8\n",
"9\n",
"10"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "d7d2dfab",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1\n",
"2\n",
"3\n",
"4\n",
"5\n",
"6\n",
"7\n",
"8\n",
"9\n",
"10\n"
]
}
],
"source": [
"i = 1\n",
"\n",
"while i <= 10:\n",
" print(i)\n",
" i = i + 1"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "a103c74c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello\n",
"World\n"
]
}
],
"source": [
"print(\"Hello\")\n",
"print(\"World\")"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "5df8d4f6",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello\n",
"World\n"
]
}
],
"source": [
"print(\"Hello\", end=\"\\n\")\n",
"print(\"World\")"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "c89f0b40",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello+World\n"
]
}
],
"source": [
"print(\"Hello\", end=\"+\")\n",
"print(\"World\")"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "8a0e5ca8",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello World\n"
]
}
],
"source": [
"print(\"Hello\", end=\" \")\n",
"print(\"World\")"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "bce809e5",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello @@@ World\n"
]
}
],
"source": [
"print(\"Hello\", end=\" @@@ \")\n",
"print(\"World\")"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "54435a01",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello@World$"
]
}
],
"source": [
"print(\"Hello\", end=\"@\")\n",
"print(\"World\", end=\"$\")"
]
},
{
"cell_type": "markdown",
"id": "95e933ab",
"metadata": {},
"source": [
"### print the following series of numbers"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7a728f28",
"metadata": {},
"outputs": [],
"source": [
"1 2 3 4 5 6 7 8 9 10"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "35896fd2",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1 2 3 4 5 6 7 8 9 10 "
]
}
],
"source": [
"i = 1\n",
"\n",
"while i <= 10:\n",
" print(i, end=\" \")\n",
" i = i + 1"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "284eda1a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"100\n",
"10\n"
]
}
],
"source": [
"a = 10\n",
"\n",
"print(a * a)\n",
"\n",
"print(a)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d1cabe31",
"metadata": {},
"outputs": [],
"source": [
"1 4 9 16 25 36 49 64 81 100"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "32f564a1",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1 4 9 16 25 36 49 64 81 100 "
]
}
],
"source": [
"i = 1\n",
"\n",
"while i <= 10:\n",
" print(i*i, end=\" \")\n",
" i = i + 1"
]
},
{
"cell_type": "markdown",
"id": "49b1b14e",
"metadata": {},
"source": [
"**Write a program to enter 5 values from user and print them.**"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "a1cd06ee",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter your number: 10\n",
"10\n",
"Enter your number: 20\n",
"20\n",
"Enter your number: 30\n",
"30\n",
"Enter your number: 40\n",
"40\n",
"Enter your number: 50\n",
"50\n"
]
}
],
"source": [
"i = 1\n",
"\n",
"while i <= 5:\n",
" a = input(\"Enter your number: \")\n",
" print(a)\n",
" i = i + 1\n",
" # 1 + 1"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "a1b92062",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"3.5"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"7 / 2"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "b1e0fc38",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"1"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"7 % 2 # modulo - return the reminder"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "7279d00f",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"10 % 2"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "7ba7e050",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"3"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"11 % 4"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "3c3ea69f",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"3"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"7 // 2 # floor division"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "e378bbe4",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"2"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"15 // 7"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "5947157a",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"3"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"153 % 10"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "07a156bd",
"metadata": {},
"outputs": [],
"source": [
"15)7(\n",
" 7"
]
},
{
"cell_type": "markdown",
"id": "d490f9d3",
"metadata": {},
"source": [
"**Write a program to enter a number from user and print reverse of it.**"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7959c4e2",
"metadata": {},
"outputs": [],
"source": [
"153\n",
"\n",
"351"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "960cfd0b",
"metadata": {},
"outputs": [],
"source": [
"153 % 10 = 3\n",
"153 // 10 = 15\n",
"\n",
"15 % 10 = 5\n",
"15 // 10 = 1\n",
"\n",
"1 % 10 = 1\n",
"1 // 10 = 0"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "3597feec",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter your number: 10\n",
"10\n",
"<class 'str'>\n"
]
}
],
"source": [
"n = input(\"Enter your number: \")\n",
"\n",
"print(n)\n",
"\n",
"print(type(n))"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "71b967e4",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter your number: 10\n",
"10\n",
"<class 'int'>\n"
]
}
],
"source": [
"n = int(input(\"Enter your number: \"))\n",
"\n",
"print(n)\n",
"\n",
"print(type(n))"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "5759b2ec",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter a number: 153\n",
"351"
]
}
],
"source": [
"n = int(input(\"Enter a number: \"))\n",
"\n",
"while n > 0:\n",
" r = n % 10 # r = 3, 5, 1\n",
" print(r, end=\"\") # 351\n",
" n = n // 10 # n = 153, 15, 1, 0"
]
},
{
"cell_type": "markdown",
"id": "adf5586f",
"metadata": {},
"source": [
"**Write a program to enter a number from user and print sum of its individual digits**"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "cbd3db08",
"metadata": {},
"outputs": [],
"source": [
"153\n",
"\n",
"1 + 5 + 3\n",
"\n",
"9"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "1d76dd47",
"metadata": {},
"outputs": [],
"source": [
"0 = s\n",
"3 = s + 3 = s\n",
"5 = s + 5 = s\n",
"1"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "52deeb6d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter a number: 153\n",
"Sum = 9\n"
]
}
],
"source": [
"n = int(input(\"Enter a number: \"))\n",
"s = 0\n",
"\n",
"while n > 0:\n",
" r = n % 10\n",
" s = s + r # s = 0, 3, 8, 9\n",
" n = n // 10\n",
"\n",
"print(\"Sum =\", s)"
]
},
{
"cell_type": "markdown",
"id": "c2bb6d4f",
"metadata": {},
"source": [
"# Day 3"
]
},
{
"cell_type": "markdown",
"id": "f4cb0aee",
"metadata": {},
"source": [
"**Write a program to reverse a number**"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "85d9cb69",
"metadata": {},
"outputs": [],
"source": [
"153\n",
"\n",
"351 - this should be a whole number"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "f31986e9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter a number: 153\n",
"351\n",
"702\n"
]
}
],
"source": [
"n = int(input(\"Enter a number: \"))\n",
"s = 0\n",
"\n",
"while n > 0:\n",
" r = n % 10 # r = 3, 5, 1\n",
" s = s*10 + r # s = 0, 3, 35, 351\n",
" n = n // 10 # n = 153, 15, 1, 0\n",
"\n",
"print(s)\n",
"print(s * 2)"
]
},
{
"cell_type": "markdown",
"id": "949c7e7d",
"metadata": {},
"source": [
"**Write a program to enter a number from user and check if it palindrome or not**"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "4fbfc3b5",
"metadata": {},
"outputs": [],
"source": [
"121\n",
"\n",
"121\n",
"\n",
"153 = 351 - not a palindrome number"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "4855f13b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter a number: 121\n",
"Not a Palindrome\n"
]
}
],
"source": [
"n = int(input(\"Enter a number: \"))\n",
"s = 0\n",
"\n",
"while n > 0:\n",
" r = n % 10 # r = 3, 5, 1\n",
" s = s*10 + r # s = 0, 3, 35, 351\n",
" n = n // 10 # n = 153, 15, 1, 0\n",
"\n",
"if s == n:\n",
" print(\"Palindrome\")\n",
"else:\n",
" print(\"Not a Palindrome\")"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "90712f12",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter a number: 1234321\n",
"Palindrome\n"
]
}
],
"source": [
"n = int(input(\"Enter a number: \"))\n",
"temp = n\n",
"s = 0\n",
"\n",
"while n > 0:\n",
" r = n % 10 # r = 3, 5, 1\n",
" s = s*10 + r # s = 0, 3, 35, 351\n",
" n = n // 10 # n = 153, 15, 1, 0\n",
"\n",
"if s == temp:\n",
" print(\"Palindrome\")\n",
"else:\n",
" print(\"Not a Palindrome\")"
]
},
{
"cell_type": "markdown",
"id": "e1a01ec1",
"metadata": {},
"source": [
"**Write a program to enter a number from user and check if it is armstrong or not**"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "20722f78",
"metadata": {},
"outputs": [],
"source": [
"153\n",
"\n",
"cube(1) + cube(5) + cube(3)\n",
"\n",
"370\n",
"\n",
"371"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "50334900",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter a number: 371\n",
"Armstrong\n"
]
}
],
"source": [
"n = int(input(\"Enter a number: \"))\n",
"temp = n\n",
"s = 0\n",
"\n",
"while n > 0:\n",
" r = n % 10 # r = 3, 5, 1\n",
" s = s + (r*r*r) # s = 0, 27, 152, 153\n",
" n = n // 10 # n = 153, 15, 1, 0\n",
"\n",
"if s == temp:\n",
" print(\"Armstrong\")\n",
"else:\n",
" print(\"Not an Armstrong\")"
]
},
{
"cell_type": "markdown",
"id": "f93f4400",
"metadata": {},
"source": [
"**Write a program to enter a number from user and print its individual digits on seperate line**"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "5ef97f05",
"metadata": {},
"outputs": [],
"source": [
"153\n",
"\n",
"1\n",
"5\n",
"3"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "e3d62d35",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter a number: 153\n",
"3\n",
"5\n",
"1\n"
]
}
],
"source": [
"n = int(input(\"Enter a number: \"))\n",
"s = 0\n",
"\n",
"while n > 0:\n",
" r = n % 10 # r = 3, 5, 1\n",
" print(r) # s = 0, 27, 152, 153\n",
" n = n // 10 # n = 153, 15, 1, 0\n"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "a5bbc5c8",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter a number: 153\n",
"1\n",
"5\n",
"3\n"
]
}
],
"source": [
"n = int(input(\"Enter a number: \"))\n",
"s = 0\n",
"\n",
"while n > 0:\n",
" r = n % 10 # r = 3, 5, 1\n",
" s = s*10 + r # s = 0, 27, 152, 153\n",
" n = n // 10 # n = 153, 15, 1, 0\n",
"\n",
"while s > 0:\n",
" r = s % 10\n",
" print(r)\n",
" s = s // 10"
]
},
{
"cell_type": "markdown",
"id": "decf806e",
"metadata": {},
"source": [
"# List\n",
"\n",
"collection of different type of elements"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9b33c6ed",
"metadata": {},
"outputs": [],
"source": [
"a = 10 # int\n",
"b = 20\n",
"c = 30"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "366b6a7a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[10, 'A', 'India', 10.6]\n",
"<class 'list'>\n"
]
}
],
"source": [
"l = [10, \"A\", \"India\", 10.6]\n",
"\n",
"print(l)\n",
"\n",
"print(type(l))"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "1af4f02d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10\n"
]
}
],
"source": [
"l = [10, \"A\", \"India\", 10.6]\n",
"# 0 1 2 3\n",
"\n",
"print(l[0])"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "ced31696",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10.6\n"
]
}
],
"source": [
"print(l[3])"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "0c0905a0",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"India\n"
]
}
],
"source": [
"print(l[2])"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "1fe65d17",
"metadata": {},
"outputs": [
{
"ename": "IndexError",
"evalue": "list index out of range",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mIndexError\u001b[0m Traceback (most recent call last)",
"Input \u001b[1;32mIn [16]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[43ml\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m5\u001b[39;49m\u001b[43m]\u001b[49m)\n",
"\u001b[1;31mIndexError\u001b[0m: list index out of range"
]
}
],
"source": [
"print(l[5])"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "c21b0555",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'int'>\n"
]
}
],
"source": [
"l = [10, \"A\", \"India\", 10.6]\n",
"# 0 1 2 3\n",
"\n",
"print(type(l[0]))"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "e9319c1c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[200, 'A', 'India', 10.6]\n"
]
}
],
"source": [
"l[0] = 200\n",
"\n",
"print(l)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "f8fe43a4",
"metadata": {},
"outputs": [
{
"ename": "IndexError",
"evalue": "list assignment index out of range",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mIndexError\u001b[0m Traceback (most recent call last)",
"Input \u001b[1;32mIn [19]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[0m l[\u001b[38;5;241m5\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1000\u001b[39m\n",
"\u001b[1;31mIndexError\u001b[0m: list assignment index out of range"
]
}
],
"source": [
"l[5] = 1000"
]
},
{
"cell_type": "markdown",
"id": "2aec1fac",
"metadata": {},
"source": [
"### negative index"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "d86147ba",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10.6\n"
]
}
],
"source": [
"# -4 -3 -2 -1\n",
"l = [10, \"A\", \"India\", 10.6]\n",
"# 0 1 2 3\n",
"\n",
"print(l[-1])"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "c3288372",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10.6\n"
]
}
],
"source": [
"print(l[3])"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "393bd2e7",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10\n",
"10\n"
]
}
],
"source": [
"print(l[0])\n",
"\n",
"print(l[-4])"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "07f8d2b4",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"India\n"
]
}
],
"source": [
"print(l[-2])"
]
},
{
"cell_type": "markdown",
"id": "18ef7bed",
"metadata": {},
"source": [
"# List Slicing"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "f556294d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[11, 22, 33, 44, 10, 24, 36, 68, 99, 81, 100]\n"
]
}
],
"source": [
"# -11-10 -9 -8 -7 -6 -5 -4 -3 -2 -1\n",
"l = [11,22,33,44,10,24,36,68,99,81,100]\n",
"# 0 1 2 3 4 5 6 7 8 9 10\n",
"\n",
"print(l)"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "61499c7e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[22, 33, 44, 10, 24, 36]\n"
]
}
],
"source": [
"print(l[1:7]) # l[start : end]"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "696ceede",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[11, 22, 33, 44, 10, 24, 36, 68, 99, 81, 100]\n"
]
}
],
"source": [
"print(l)"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "9c790873",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[10, 24, 36, 68, 99, 81]\n"
]
}
],
"source": [
"# -11-10 -9 -8 -7 -6 -5 -4 -3 -2 -1\n",
"l = [11,22,33,44,10,24,36,68,99,81,100]\n",
"# 0 1 2 3 4 5 6 7 8 9 10\n",
"\n",
"print(l[4:10])"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "88f74cab",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[99, 81]\n"
]
}
],
"source": [
"print(l[8:10])"
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "59a8810d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[11]\n"
]
}
],
"source": [
"print(l[0:1])"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "da404e2d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[22, 33, 44, 10, 24, 36, 68, 99, 81, 100]\n"
]
}
],
"source": [
"print(l[1:])"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "411185c6",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[99, 81, 100]\n"
]
}
],
"source": [
"print(l[8:])"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "f3427d62",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[11, 22, 33, 44, 10, 24, 36, 68, 99, 81, 100]\n"
]
}
],
"source": [
"print(l[:])"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "8cb04435",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[11, 22, 33, 44, 10]\n"
]
}
],
"source": [
"print(l[:5])"
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "07b3d8c8",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[11, 22, 33, 44, 10, 24, 36]\n"
]
}
],
"source": [
"# -11-10 -9 -8 -7 -6 -5 -4 -3 -2 -1\n",
"l = [11,22,33,44,10,24,36,68,99,81,100]\n",
"# 0 1 2 3 4 5 6 7 8 9 10\n",
"\n",
"print(l[0:-4])"
]
},
{
"cell_type": "code",
"execution_count": 35,
"id": "6b72269e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[33, 44, 10, 24, 36, 68, 99]\n"
]
}
],
"source": [
"print(l[2:-2])"
]
},
{
"cell_type": "code",
"execution_count": 36,
"id": "34eb2422",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[]\n"
]
}
],
"source": [
"print(l[2:0])"
]
},
{
"cell_type": "code",
"execution_count": 37,
"id": "ea9e9d22",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[]\n"
]
}
],
"source": [
"print(l[0:0])"
]
},
{
"cell_type": "code",
"execution_count": 38,
"id": "d4d6dc2c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[24, 36, 68, 99, 81, 100]\n"
]
}
],
"source": [
"print(l[5:15])"
]
},
{
"cell_type": "code",
"execution_count": 39,
"id": "327f5a53",
"metadata": {},
"outputs": [
{
"ename": "IndexError",
"evalue": "list index out of range",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mIndexError\u001b[0m Traceback (most recent call last)",
"Input \u001b[1;32mIn [39]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[43ml\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m15\u001b[39;49m\u001b[43m]\u001b[49m)\n",
"\u001b[1;31mIndexError\u001b[0m: list index out of range"
]
}
],
"source": [
"print(l[15])"
]
},
{
"cell_type": "code",
"execution_count": 40,
"id": "1654f679",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[22, 33, 44]\n"
]
}
],
"source": [
"# -11-10 -9 -8 -7 -6 -5 -4 -3 -2 -1\n",
"l = [11,22,33,44,10,24,36,68,99,81,100]\n",
"# 0 1 2 3 4 5 6 7 8 9 10\n",
"\n",
"print(l[1:4])"
]
},
{
"cell_type": "code",
"execution_count": 41,
"id": "ef550430",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[]\n"
]
}
],
"source": [
"print(l[4:1])"
]
},
{
"cell_type": "code",
"execution_count": 42,
"id": "64a79df5",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[68, 99, 81]\n"
]
}
],
"source": [
"print(l[-4:-1])"
]
},
{
"cell_type": "code",
"execution_count": 43,
"id": "70fecd4e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[]\n"
]
}
],
"source": [
"print(l[-1:-4])"
]
},
{
"cell_type": "markdown",
"id": "a2b17316",
"metadata": {},
"source": [
"## steps"
]
},
{
"cell_type": "code",
"execution_count": 44,
"id": "e9af568f",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[11, 33, 10, 36, 99, 100]\n"
]
}
],
"source": [
"# -11-10 -9 -8 -7 -6 -5 -4 -3 -2 -1\n",
"l = [11,22,33,44,10,24,36,68,99,81,100]\n",
"# 0 1 2 3 4 5 6 7 8 9 10\n",
"\n",
"print(l[0:11:2]) # l[start : end : steps]"
]
},
{
"cell_type": "code",
"execution_count": 45,
"id": "d0127e99",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[11, 44, 36, 81]\n"
]
}
],
"source": [
"print(l[0:11:3])"
]
},
{
"cell_type": "code",
"execution_count": 46,
"id": "75e4fefa",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[11, 22, 33, 44, 10, 24, 36, 68, 99, 81, 100]\n"
]
}
],
"source": [
"print(l[::])"
]
},
{
"cell_type": "code",
"execution_count": 47,
"id": "3449b6af",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[11, 22, 33, 44, 10, 24, 36, 68, 99, 81, 100]\n"
]
}
],
"source": [
"print(l[::1])"
]
},
{
"cell_type": "code",
"execution_count": 48,
"id": "2e6345c0",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[100, 81, 99, 68, 36, 24, 10, 44, 33, 22, 11]\n"
]
}
],
"source": [
"print(l[::-1]) # reverse"
]
},
{
"cell_type": "code",
"execution_count": 49,
"id": "f284f488",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[]\n"
]
}
],
"source": [
"# -11-10 -9 -8 -7 -6 -5 -4 -3 -2 -1\n",
"l = [11,22,33,44,10,24,36,68,99,81,100]\n",
"# 0 1 2 3 4 5 6 7 8 9 10\n",
"\n",
"print(l[4:8:-1])"
]
},
{
"cell_type": "code",
"execution_count": 50,
"id": "1f16a88d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[99, 68, 36, 24]\n"
]
}
],
"source": [
"print(l[8:4:-1])"
]
},
{
"cell_type": "code",
"execution_count": 51,
"id": "11575dee",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[100, 99, 36, 10, 33, 11]\n"
]
}
],
"source": [
"print(l[::-2])"
]
},
{
"cell_type": "code",
"execution_count": 52,
"id": "1a639620",
"metadata": {},
"outputs": [
{
"ename": "ValueError",
"evalue": "slice step cannot be zero",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mValueError\u001b[0m Traceback (most recent call last)",
"Input \u001b[1;32mIn [52]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[43ml\u001b[49m\u001b[43m[\u001b[49m\u001b[43m:\u001b[49m\u001b[43m:\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m)\n",
"\u001b[1;31mValueError\u001b[0m: slice step cannot be zero"
]
}
],
"source": [
"print(l[::0])"
]
},
{
"cell_type": "markdown",
"id": "20862888",
"metadata": {},
"source": [
"## list functions"
]
},
{
"cell_type": "code",
"execution_count": 53,
"id": "8aa952c9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"5\n"
]
}
],
"source": [
"l = [10,20,30,40,50]\n",
"\n",
"print(len(l))"
]
},
{
"cell_type": "code",
"execution_count": 54,
"id": "74856061",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"4\n"
]
}
],
"source": [
"print(len(l) - 1)"
]
},
{
"cell_type": "code",
"execution_count": 55,
"id": "250b458e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"150\n"
]
}
],
"source": [
"print(sum(l))"
]
},
{
"cell_type": "code",
"execution_count": 56,
"id": "7ea78614",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"50\n"
]
}
],
"source": [
"print(max(l))"
]
},
{
"cell_type": "code",
"execution_count": 57,
"id": "bad8aadc",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10\n"
]
}
],
"source": [
"print(min(l))"
]
},
{
"cell_type": "code",
"execution_count": 58,
"id": "27a21618",
"metadata": {},
"outputs": [
{
"ename": "TypeError",
"evalue": "unsupported operand type(s) for +: 'int' and 'str'",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)",
"Input \u001b[1;32mIn [58]\u001b[0m, in \u001b[0;36m<cell line: 3>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m l \u001b[38;5;241m=\u001b[39m [\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mA\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;241m10\u001b[39m,\u001b[38;5;241m20\u001b[39m,\u001b[38;5;241m30\u001b[39m]\n\u001b[1;32m----> 3\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;28;43msum\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43ml\u001b[49m\u001b[43m)\u001b[49m)\n",
"\u001b[1;31mTypeError\u001b[0m: unsupported operand type(s) for +: 'int' and 'str'"
]
}
],
"source": [
"l = [\"A\", 10,20,30]\n",
"\n",
"print(sum(l))"
]
},
{
"cell_type": "code",
"execution_count": 59,
"id": "a176b651",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"4\n"
]
}
],
"source": [
"print(len(l))"
]
},
{
"cell_type": "markdown",
"id": "1ee80d7b",
"metadata": {},
"source": [
"# List methods"
]
},
{
"cell_type": "code",
"execution_count": 61,
"id": "e802bef5",
"metadata": {},
"outputs": [],
"source": [
"# help(print)"
]
},
{
"cell_type": "code",
"execution_count": 63,
"id": "5a500f31",
"metadata": {
"scrolled": false
},
"outputs": [],
"source": [
"# help(list)"
]
},
{
"cell_type": "code",
"execution_count": 64,
"id": "0538c1e8",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[10, 20, 30, 40]\n"
]
}
],
"source": [
"l = [10,20,30]\n",
"\n",
"l.append(40)\n",
"\n",
"print(l)"
]
},
{
"cell_type": "code",
"execution_count": 65,
"id": "ed712c2b",
"metadata": {},
"outputs": [],
"source": [
"l.append(\"India\")"
]
},
{
"cell_type": "code",
"execution_count": 66,
"id": "265b8be2",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[10, 20, 30, 40, 'India']\n"
]
}
],
"source": [
"print(l)"
]
},
{
"cell_type": "code",
"execution_count": 67,
"id": "ea15af1f",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"4\n"
]
}
],
"source": [
"print(l.index('India'))"
]
},
{
"cell_type": "code",
"execution_count": 68,
"id": "c422ce83",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0\n"
]
}
],
"source": [
"print(l.index(10))"
]
},
{
"cell_type": "code",
"execution_count": 69,
"id": "0e88a9f3",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[10, 20, 30, 40, 'India']\n"
]
}
],
"source": [
"print(l)"
]
},
{
"cell_type": "code",
"execution_count": 72,
"id": "e3042d8a",
"metadata": {},
"outputs": [],
"source": [
"l.reverse()"
]
},
{
"cell_type": "code",
"execution_count": 73,
"id": "02a28ba4",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[10, 20, 30, 40, 'India']\n"
]
}
],
"source": [
"print(l)"
]
},
{
"cell_type": "code",
"execution_count": 74,
"id": "7c861f47",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['India', 40, 30, 20, 10]\n"
]
}
],
"source": [
"print(l[::-1])"
]
},
{
"cell_type": "code",
"execution_count": 75,
"id": "e1210f8f",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[10, 20, 30, 40, 'India']\n"
]
}
],
"source": [
"print(l)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "ef9c13af",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.12"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
================================================
FILE: July Cohort 2023/1_Python Programming/04_Strings and For loop.ipynb
================================================
{
"cells": [
{
"cell_type": "markdown",
"id": "89086545",
"metadata": {},
"source": [
"# Strings\n",
"\n",
"set of characters\n"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "663dd2fc",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"hello\n"
]
}
],
"source": [
"# -1\n",
"s = 'hello'\n",
"# 01234\n",
"\n",
"print(s)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "d1f891e2",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"h\n"
]
}
],
"source": [
"print(s[0])"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "549cabfa",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"o\n"
]
}
],
"source": [
"print(s[4])"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "e9b26f8e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"o\n"
]
}
],
"source": [
"print(s[-1])"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "bef31594",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"l\n"
]
}
],
"source": [
"print(s[-2])"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "00f3823f",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'str'>\n"
]
}
],
"source": [
"print(type(s))"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "7326e7a9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'str'>\n"
]
}
],
"source": [
"print(type(s[0]))"
]
},
{
"cell_type": "markdown",
"id": "4899cd30",
"metadata": {},
"source": [
"# string slicing"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "12c56ed2",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"commu\n"
]
}
],
"source": [
"s = 'communication'\n",
"# 0123456789\n",
"\n",
"print(s[0:5])"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "781ea5cd",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"noitacinummoc\n"
]
}
],
"source": [
"print(s[::-1])"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "90aa93d3",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"omm\n"
]
}
],
"source": [
"print(s[1:4])"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "5c24d8b3",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n"
]
}
],
"source": [
"s = 'communication'\n",
"# 0123456789\n",
"\n",
"print(s[4:1])"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "a8f6af2e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'str'>\n"
]
}
],
"source": [
"s = ''\n",
"\n",
"print(type(s))"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "2d3570c7",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"noitacin\n"
]
}
],
"source": [
"s = 'communication'\n",
"# 0123456789\n",
"\n",
"print(s[-1:-9:-1])"
]
},
{
"cell_type": "markdown",
"id": "ef70cbf4",
"metadata": {},
"source": [
"# String Functions"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "f12266cf",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"13\n"
]
}
],
"source": [
"s = 'communication'\n",
"\n",
"print(len(s))"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "50320c72",
"metadata": {},
"outputs": [
{
"ename": "TypeError",
"evalue": "unsupported operand type(s) for +: 'int' and 'str'",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)",
"Input \u001b[1;32mIn [15]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;28;43msum\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43ms\u001b[49m\u001b[43m)\u001b[49m)\n",
"\u001b[1;31mTypeError\u001b[0m: unsupported operand type(s) for +: 'int' and 'str'"
]
}
],
"source": [
"print(sum(s)) # s = 0"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "55b002c3",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"u\n"
]
}
],
"source": [
"print(max(s))"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "7ccced34",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"a\n"
]
}
],
"source": [
"print(min(s))"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8b30e14f",
"metadata": {},
"outputs": [],
"source": [
"# ASCII\n",
"\n",
"'A' -> 65\n",
"'B' -> 66\n",
"'Z' -> 90\n",
"\n",
"'a' -> 97\n",
"'z' -> 122\n",
"\n",
"' ' -> 32 -> space"
]
},
{
"cell_type": "markdown",
"id": "afa17626",
"metadata": {},
"source": [
"## string methods\n"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "e3ef73fb",
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"# help(str)"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "53f436a8",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"False"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"'raj123' == 'RAJ123'"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "9a9f840d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"raj123\n"
]
}
],
"source": [
"s = 'RAJ123'\n",
"\n",
"print(s.casefold())"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "4e6cd479",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"INDIA\n"
]
}
],
"source": [
"s = 'India'\n",
"\n",
"print(s.upper())"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "76b04479",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"india\n"
]
}
],
"source": [
"print(s.lower())"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "2e8f43e5",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['This', 'is', 'an', 'apple']\n"
]
}
],
"source": [
"# split\n",
"\n",
"s = 'This is an apple'\n",
"\n",
"print(s.split(\" \"))"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "94237ec7",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['H', 'llo Us', 'r']\n"
]
}
],
"source": [
"s = \"Hello User\"\n",
"\n",
"print(s.split(\"e\"))"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "42a71402",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"This+is+an+apple\n"
]
}
],
"source": [
"# join\n",
"\n",
"l = ['This', 'is', 'an', 'apple']\n",
"\n",
"a = \"+\"\n",
"\n",
"print(a.join(l))"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "6ef43d06",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"This is an apple\n"
]
}
],
"source": [
"# join\n",
"\n",
"l = ['This', 'is', 'an', 'apple']\n",
"\n",
"a = \" \"\n",
"\n",
"print(a.join(l))\n",
"# \" \".join(l)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "dae0d39a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ThisisanApple\n"
]
}
],
"source": [
"# remove all the spaces from the string\n",
"\n",
"s = \"This is an Apple\"\n",
"\n",
"l = s.split(\" \")\n",
"\n",
"x = \"\".join(l)\n",
"\n",
"print(x)"
]
},
{
"cell_type": "markdown",
"id": "5e18c7bc",
"metadata": {},
"source": [
"**Write a program to enter a string from user and print the biggest word from the para**"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "fc9ffad3",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "08b8681d",
"metadata": {},
"source": [
"# range function"
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "cd95ff5d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"range(0, 5)\n"
]
}
],
"source": [
"n = range(5) # this will create a series of numbers from 0 to 4\n",
"\n",
"print(n)"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "5faa24f2",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'range'>\n"
]
}
],
"source": [
"print(type(n))"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "b9b1b6fa",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[0, 1, 2, 3, 4]\n"
]
}
],
"source": [
"n = list(range(5))\n",
"\n",
"print(n)"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "00bf5fc9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[3, 4, 5, 6, 7]\n"
]
}
],
"source": [
"n = list(range(3,8))\n",
"\n",
"print(n)"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "85f51f76",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"True\n"
]
}
],
"source": [
"print(range(20) == range(0,20))"
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "cf56e7cc",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[5, 7, 9, 11, 13, 15, 17, 19]\n"
]
}
],
"source": [
"n = list(range(5,20,2)) # range(start, end, steps)\n",
"\n",
"print(n)"
]
},
{
"cell_type": "markdown",
"id": "9a9e11b2",
"metadata": {},
"source": [
"## for loop"
]
},
{
"cell_type": "code",
"execution_count": 35,
"id": "eb461d52",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"False\n"
]
}
],
"source": [
"l = [\"A\", \"B\", \"C\", \"D\"]\n",
"\n",
"print(\"Z\" in l)"
]
},
{
"cell_type": "code",
"execution_count": 36,
"id": "f3d37b0a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"A\n",
"B\n",
"C\n",
"D\n"
]
}
],
"source": [
"l = [\"A\", \"B\", \"C\", \"D\"]\n",
"# i\n",
"\n",
"# \"B\" in l\n",
"for i in l:\n",
" print(i)"
]
},
{
"cell_type": "code",
"execution_count": 37,
"id": "15a3f0ba",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"A\n",
"Hi\n",
"B\n",
"Hi\n",
"C\n",
"Hi\n",
"D\n",
"Hi\n"
]
}
],
"source": [
"l = [\"A\", \"B\", \"C\", \"D\"]\n",
"# i\n",
"\n",
"# \"B\" in l\n",
"for i in l:\n",
" print(i)\n",
" print(\"Hi\")"
]
},
{
"cell_type": "code",
"execution_count": 40,
"id": "59f4f57f",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"a\n",
"b\n",
"c\n",
"d\n"
]
}
],
"source": [
"s = 'abcd'\n",
"\n",
"for i in s:\n",
" print(i)"
]
},
{
"cell_type": "code",
"execution_count": 42,
"id": "be302d25",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"AB\n",
"ab\n"
]
}
],
"source": [
"x = 'ab'\n",
"\n",
"print(x.upper())\n",
"\n",
"print(x)"
]
},
{
"cell_type": "code",
"execution_count": 43,
"id": "b3a22f15",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['ab', 'cd']\n"
]
}
],
"source": [
"x = ['ab', 'cd']\n",
"\n",
"for i in x:\n",
" i.upper() # 'ab'.upper() -> 'AB'\n",
" \n",
"print(x)"
]
},
{
"cell_type": "code",
"execution_count": 44,
"id": "4e0873d9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"AB\n",
"CD\n",
"['ab', 'cd']\n"
]
}
],
"source": [
"x = ['ab', 'cd']\n",
"\n",
"for i in x:\n",
" print(i.upper()) # 'ab'.upper() -> 'AB'\n",
" \n",
"print(x)"
]
},
{
"cell_type": "code",
"execution_count": 45,
"id": "77e96be5",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"a\n",
"b\n",
"c\n",
"d\n"
]
}
],
"source": [
"x = 'abcd'\n",
"\n",
"for i in x:\n",
" print(i)\n",
" x.upper()\n"
]
},
{
"cell_type": "code",
"execution_count": 46,
"id": "d6c07e4d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0\n",
"1\n",
"2\n",
"3\n",
"4\n"
]
}
],
"source": [
"# i\n",
"# 0,1,2,3,4\n",
"for i in range(5):\n",
" print(i)"
]
},
{
"cell_type": "code",
"execution_count": 47,
"id": "bba46637",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"5\n",
"6\n",
"7\n",
"8\n",
"9\n"
]
}
],
"source": [
"for i in range(5,10):\n",
" print(i)"
]
},
{
"cell_type": "code",
"execution_count": 48,
"id": "fdb6483c",
"metadata": {},
"outputs": [
{
"ename": "TypeError",
"evalue": "'str' object cannot be interpreted as an integer",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)",
"Input \u001b[1;32mIn [48]\u001b[0m, in \u001b[0;36m<cell line: 3>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m x \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mabcd\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m----> 3\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28;43mrange\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[43m)\u001b[49m:\n\u001b[0;32m 4\u001b[0m \u001b[38;5;28mprint\u001b[39m(i)\n",
"\u001b[1;31mTypeError\u001b[0m: 'str' object cannot be interpreted as an integer"
]
}
],
"source": [
"x = 'abcd'\n",
"\n",
"for i in range(x):\n",
" print(i)"
]
},
{
"cell_type": "code",
"execution_count": 49,
"id": "dac1b7e1",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0\n",
"1\n",
"2\n",
"3\n"
]
}
],
"source": [
"x = 'abcd'\n",
"\n",
"# 0,1,2,3\n",
"for i in range(len(x)):\n",
" print(i)"
]
},
{
"cell_type": "code",
"execution_count": 50,
"id": "ce020a17",
"metadata": {},
"outputs": [
{
"ename": "AttributeError",
"evalue": "'int' object has no attribute 'upper'",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)",
"Input \u001b[1;32mIn [50]\u001b[0m, in \u001b[0;36m<cell line: 4>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 3\u001b[0m \u001b[38;5;66;03m# 0,1,2,3\u001b[39;00m\n\u001b[0;32m 4\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;28mlen\u001b[39m(x)):\n\u001b[1;32m----> 5\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[43mi\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mupper\u001b[49m())\n",
"\u001b[1;31mAttributeError\u001b[0m: 'int' object has no attribute 'upper'"
]
}
],
"source": [
"x = 'abcd'\n",
"\n",
"# 0,1,2,3\n",
"for i in range(len(x)):\n",
" print(i.upper())"
]
},
{
"cell_type": "code",
"execution_count": 51,
"id": "e4b348f0",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"abcd\n"
]
}
],
"source": [
"x = 'abcd'\n",
"\n",
"# 0,1,2,3\n",
"for i in range(len(x)):\n",
" x[i].upper()\n",
"\n",
"print(x)"
]
},
{
"cell_type": "code",
"execution_count": 52,
"id": "e4afa49b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"A\n",
"B\n",
"C\n",
"D\n",
"abcd\n"
]
}
],
"source": [
"x = 'abcd'\n",
"\n",
"# 0,1,2,3\n",
"for i in range(len(x)):\n",
" print(x[i].upper())\n",
"\n",
"print(x)"
]
},
{
"cell_type": "code",
"execution_count": 53,
"id": "9d691550",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"a\n",
"a\n",
"a\n",
"a\n"
]
}
],
"source": [
"x = 'abcd'\n",
"\n",
"# 0,1,2,3\n",
"for i in range(len(x)):\n",
" x = 'a' # x = 'abcd', 'a', 'a'\n",
" print(x)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9fe9971b",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.12"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
================================================
FILE: July Cohort 2023/1_Python Programming/05_Dictionary Tuples and Set.ipynb
================================================
{
"cells": [
{
"cell_type": "markdown",
"id": "0d853ca0",
"metadata": {},
"source": [
"# Dictionary"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "28ba2c85",
"metadata": {},
"outputs": [],
"source": [
"# { key : value }\n",
"\n",
"unordered data structures"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "de03adfa",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'ravi': 24, 'shyam': 21, 'roy': 41}\n"
]
}
],
"source": [
"ages = {\"ravi\":24, \"shyam\": 21, \"roy\": 41}\n",
"\n",
"print(ages)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "1507411b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'dict'>\n"
]
}
],
"source": [
"print(type(ages))"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "3a6e0c6d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"24\n"
]
}
],
"source": [
"print(ages['ravi'])"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "9c495fe7",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"41\n"
]
}
],
"source": [
"print(ages['roy'])"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "dc9434fb",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[255, 0, 0]\n"
]
}
],
"source": [
"color = {\n",
" \"red\": [255,0,0],\n",
" \"green\": [0,255,0],\n",
" \"blue\": [0,0,255]\n",
"}\n",
"print(color['red'])"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "28854643",
"metadata": {},
"outputs": [
{
"ename": "KeyError",
"evalue": "'yellow'",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mKeyError\u001b[0m Traceback (most recent call last)",
"Input \u001b[1;32mIn [7]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[43mcolor\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43myellow\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m)\n",
"\u001b[1;31mKeyError\u001b[0m: 'yellow'"
]
}
],
"source": [
"print(color['yellow'])"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "f12d89ad",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{}\n",
"<class 'dict'>\n"
]
}
],
"source": [
"d = {}\n",
"print(d)\n",
"print(type(d))"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "0d0ceafe",
"metadata": {},
"outputs": [
{
"ename": "TypeError",
"evalue": "unhashable type: 'list'",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)",
"Input \u001b[1;32mIn [9]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[0m d \u001b[38;5;241m=\u001b[39m {[\u001b[38;5;241m1\u001b[39m,\u001b[38;5;241m2\u001b[39m]:\u001b[38;5;241m10\u001b[39m, \u001b[38;5;241m2\u001b[39m:\u001b[38;5;241m2\u001b[39m, \u001b[38;5;241m3\u001b[39m:\u001b[38;5;241m3\u001b[39m}\n\u001b[0;32m 2\u001b[0m \u001b[38;5;28mprint\u001b[39m(d)\n",
"\u001b[1;31mTypeError\u001b[0m: unhashable type: 'list'"
]
}
],
"source": [
"d = {[1,2]:10, 2:2, 3:3}\n",
"print(d)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "8a6b2ca9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[100, 20]\n"
]
}
],
"source": [
"# list are mutable objects\n",
"\n",
"l = [10,20]\n",
"l[0] = 100\n",
"print(l)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "bc14edbb",
"metadata": {},
"outputs": [
{
"ename": "TypeError",
"evalue": "'str' object does not support item assignment",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)",
"Input \u001b[1;32mIn [11]\u001b[0m, in \u001b[0;36m<cell line: 4>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[38;5;66;03m# strings are immutable objects\u001b[39;00m\n\u001b[0;32m 3\u001b[0m s \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mindore\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m----> 4\u001b[0m s[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mA\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 5\u001b[0m \u001b[38;5;28mprint\u001b[39m(s)\n",
"\u001b[1;31mTypeError\u001b[0m: 'str' object does not support item assignment"
]
}
],
"source": [
"# strings are immutable objects\n",
"\n",
"s = 'indore'\n",
"s[0] = \"A\"\n",
"print(s)"
]
},
{
"cell_type": "markdown",
"id": "498704a8",
"metadata": {},
"source": [
"# Dictionary Functions"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "a88930aa",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"4\n"
]
}
],
"source": [
"d = {1:11, 2:41, 13:9, 14:16}\n",
"\n",
"print(len(d))"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "71aca243",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"30\n"
]
}
],
"source": [
"print(sum(d))"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "a9c23606",
"metadata": {},
"outputs": [
{
"ename": "TypeError",
"evalue": "unsupported operand type(s) for +: 'int' and 'str'",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)",
"Input \u001b[1;32mIn [14]\u001b[0m, in \u001b[0;36m<cell line: 3>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m a \u001b[38;5;241m=\u001b[39m {\u001b[38;5;241m1\u001b[39m:\u001b[38;5;241m2\u001b[39m, \u001b[38;5;241m3\u001b[39m:\u001b[38;5;241m4\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhi\u001b[39m\u001b[38;5;124m\"\u001b[39m:\u001b[38;5;241m16\u001b[39m}\n\u001b[1;32m----> 3\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;28;43msum\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43ma\u001b[49m\u001b[43m)\u001b[49m)\n",
"\u001b[1;31mTypeError\u001b[0m: unsupported operand type(s) for +: 'int' and 'str'"
]
}
],
"source": [
"a = {1:2, 3:4, \"hi\":16}\n",
"\n",
"print(sum(a))"
]
},
{
"cell_type": "markdown",
"id": "6afd220b",
"metadata": {},
"source": [
"# Dictionary Methods"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "4d319b95",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{1: 'Apple', 'orange': [2, 3, 4], '2': '23'}\n"
]
}
],
"source": [
"pair = {1:\"Apple\", \"orange\": [2,3,4], \"2\":\"23\"}\n",
"\n",
"print(pair)"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "b53ea8e9",
"metadata": {
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[2, 3, 4]\n"
]
}
],
"source": [
"# get\n",
"# help(dict)\n",
"\n",
"print(pair.get(\"orange\"))"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "e3b011f8",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"None\n"
]
}
],
"source": [
"print(pair.get(7))"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "80c5249a",
"metadata": {},
"outputs": [],
"source": [
"None ==> NULL ==> nothing"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "8ece5b51",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Apple\n"
]
}
],
"source": [
"print(pair.get(1,\"Element not found\"))"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "af462093",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Element not found\n"
]
}
],
"source": [
"print(pair.get(10,\"Element not found\"))"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "61e47d6e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{1: 'Apple', 'orange': [2, 3, 4], '2': '23'}\n",
"{}\n"
]
}
],
"source": [
"# clear\n",
"\n",
"p = {1:\"Apple\", \"orange\": [2,3,4], \"2\":\"23\"}\n",
"\n",
"print(p)\n",
"p.clear()\n",
"print(p)"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "bcf864f7",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"dict_keys([1, 2, 3])\n"
]
}
],
"source": [
"# keys\n",
"\n",
"r = {1:\"A\", 2:'Zara', 3:\"Maza\"}\n",
"\n",
"print(r.keys())"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "4d8f44be",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[1, 2, 3]\n"
]
}
],
"source": [
"print(list(r.keys()))"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "13318e6e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"dict_values(['A', 'Zara', 'Maza'])\n"
]
}
],
"source": [
"# values\n",
"\n",
"r = {1:\"A\", 2:'Zara', 3:\"Maza\"}\n",
"\n",
"print(r.values())"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "e29dc425",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['A', 'Zara', 'Maza']\n"
]
}
],
"source": [
"print(list(r.values()))"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "4e7dbf29",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{3: 'Maza', 2: 'Zara'}\n",
"2\n"
]
}
],
"source": [
"r = {3:\"A\", 2:'Zara', 3:\"Maza\"}\n",
"\n",
"print(r)\n",
"\n",
"print(len(r))"
]
},
{
"cell_type": "markdown",
"id": "ec79a1b8",
"metadata": {},
"source": [
"# Question\n",
"\n",
"print the following series"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "e205896b",
"metadata": {},
"outputs": [],
"source": [
"{1:1, 2:4, 3:9, 4:16, .........10:100}"
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "5abc247e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{1: 2, 3: 'Hi'}\n"
]
}
],
"source": [
"a = {1:2}\n",
"a[3] = \"Hi\"\n",
"print(a)"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "7aea4934",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{1: 1, 2: 4, 3: 9, 4: 16, 5: 25, 6: 36, 7: 49, 8: 64, 9: 81, 10: 100}\n"
]
}
],
"source": [
"d = {}\n",
"\n",
"for i in range(1,11):\n",
" d[i] = i * i\n",
"\n",
"print(d)"
]
},
{
"cell_type": "markdown",
"id": "323a152e",
"metadata": {},
"source": [
"# Tuples"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "5a6a2fc7",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(4, 3, 5, 6)\n",
"<class 'tuple'>\n"
]
}
],
"source": [
"t = (4,3,5,6)\n",
"# 0 1 2 3\n",
"\n",
"print(t)\n",
"\n",
"print(type(t))"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "d5b5852c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"4\n"
]
}
],
"source": [
"print(t[0])"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "519de1e2",
"metadata": {},
"outputs": [
{
"ename": "TypeError",
"evalue": "'tuple' object does not support item assignment",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)",
"Input \u001b[1;32mIn [33]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[0m t[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m11\u001b[39m\n",
"\u001b[1;31mTypeError\u001b[0m: 'tuple' object does not support item assignment"
]
}
],
"source": [
"t[0] = 11 # tuple are immutable objects"
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "d44d0e73",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"('one', 'two', 'three')\n"
]
}
],
"source": [
"t = \"one\", \"two\", \"three\"\n",
"\n",
"print(t)"
]
},
{
"cell_type": "code",
"execution_count": 35,
"id": "85ca1c88",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'tuple'>\n"
]
}
],
"source": [
"print(type(t))"
]
},
{
"cell_type": "code",
"execution_count": 36,
"id": "88548f84",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10\n",
"<class 'int'>\n"
]
}
],
"source": [
"t = (10)\n",
"print(t)\n",
"print(type(t))"
]
},
{
"cell_type": "code",
"execution_count": 37,
"id": "0605b55a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(10,)\n",
"<class 'tuple'>\n"
]
}
],
"source": [
"t = (10,)\n",
"print(t)\n",
"print(type(t))"
]
},
{
"cell_type": "markdown",
"id": "954aa392",
"metadata": {},
"source": [
"# Tuple unpacking"
]
},
{
"cell_type": "code",
"execution_count": 38,
"id": "a77b3c9c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1\n",
"2\n",
"3\n"
]
}
],
"source": [
"n = (1,2,3)\n",
"\n",
"a,b,c = n\n",
"\n",
"print(a)\n",
"print(b)\n",
"print(c)"
]
},
{
"cell_type": "markdown",
"id": "bda16a06",
"metadata": {},
"source": [
"# Tuple Slicing"
]
},
{
"cell_type": "code",
"execution_count": 39,
"id": "1c2a8096",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(11, 22, 33, 44, 55, 66, 77, 88, 99, 100)\n"
]
}
],
"source": [
"# -1\n",
"t = (11,22,33,44,55,66,77,88,99,100)\n",
"# 0 1 \n",
"\n",
"print(t)"
]
},
{
"cell_type": "code",
"execution_count": 40,
"id": "14c17710",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(44, 55)\n"
]
}
],
"source": [
"print(t[3:5])"
]
},
{
"cell_type": "code",
"execution_count": 41,
"id": "febf2d84",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(11, 22, 33, 44, 55, 66)\n"
]
}
],
"source": [
"print(t[:6])"
]
},
{
"cell_type": "code",
"execution_count": 42,
"id": "e98f6a1e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(33, 44, 55, 66)\n"
]
}
],
"source": [
"print(t[-8:-4])"
]
},
{
"cell_type": "code",
"execution_count": 43,
"id": "c1de1350",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"()\n"
]
}
],
"source": [
"print(t[-4:-8])"
]
},
{
"cell_type": "code",
"execution_count": 44,
"id": "3f3523ca",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(100, 99, 88, 77, 66, 55, 44, 33, 22, 11)\n"
]
}
],
"source": [
"print(t[::-1])"
]
},
{
"cell_type": "markdown",
"id": "9119181e",
"metadata": {},
"source": [
"# Tuple Methods"
]
},
{
"cell_type": "code",
"execution_count": 45,
"id": "da140ca3",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"3\n"
]
}
],
"source": [
"# count\n",
"\n",
"t = (2,3,4,5,5,6,6,4,4,)\n",
"\n",
"print(t.count(4))\n"
]
},
{
"cell_type": "code",
"execution_count": 46,
"id": "c35b8ce9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"2\n"
]
}
],
"source": [
"# index\n",
"\n",
"t = (2,3,4,5,5,6,6,4,4,)\n",
"\n",
"print(t.index(4))"
]
},
{
"cell_type": "code",
"execution_count": 47,
"id": "1e8caefa",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Help on built-in function index:\n",
"\n",
"index(value, start=0, stop=9223372036854775807, /) method of builtins.tuple instance\n",
" Return first index of value.\n",
" \n",
" Raises ValueError if the value is not present.\n",
"\n"
]
}
],
"source": [
"help(t.index)"
]
},
{
"cell_type": "code",
"execution_count": 48,
"id": "15dafa64",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"7\n"
]
}
],
"source": [
"# index\n",
"\n",
"t = (2,3,4,5,5,6,6,4,4,)\n",
"\n",
"print(t.index(4, 5))"
]
},
{
"cell_type": "markdown",
"id": "a9ef4027",
"metadata": {},
"source": [
"# Tuple functions"
]
},
{
"cell_type": "code",
"execution_count": 49,
"id": "22c1684e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"5\n"
]
}
],
"source": [
"t = (2,3,4,5,6)\n",
"\n",
"print(len(t))"
]
},
{
"cell_type": "code",
"execution_count": 50,
"id": "9f1bfd43",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"20\n"
]
}
],
"source": [
"print(sum(t))"
]
},
{
"cell_type": "code",
"execution_count": 51,
"id": "89a4ca0e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"6\n"
]
}
],
"source": [
"print(max(t))"
]
},
{
"cell_type": "markdown",
"id": "505a27fe",
"metadata": {},
"source": [
"# Question"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f36b7876",
"metadata": {},
"outputs": [],
"source": [
"# remove i from this tuple\n",
"\n",
"t = ('a', 'e','i', 'o', 'u')"
]
},
{
"cell_type": "markdown",
"id": "90775705",
"metadata": {},
"source": [
"# Sets\n",
"\n",
"unordered and unindex\n",
"\n",
"sets are mutable"
]
},
{
"cell_type": "code",
"execution_count": 52,
"id": "7ee80027",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{1, 2, 3, 4, 5, 6}\n",
"<class 'set'>\n"
]
}
],
"source": [
"n = {1,2,3,4,5,6,6,6}\n",
"\n",
"print(n)\n",
"\n",
"print(type(n))"
]
},
{
"cell_type": "code",
"execution_count": 53,
"id": "6fef6ded",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'set'>\n"
]
}
],
"source": [
"s = set()\n",
"\n",
"print(type(s))"
]
},
{
"cell_type": "code",
"execution_count": 54,
"id": "a23d23ac",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{10, 'a', 'b'}\n"
]
}
],
"source": [
"n = set(['a','b',10])\n",
"print(n)"
]
},
{
"cell_type": "code",
"execution_count": 55,
"id": "1a660809",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"True\n"
]
}
],
"source": [
"s = ['a','b',10]\n",
"\n",
"print(10 in s)"
]
},
{
"cell_type": "code",
"execution_count": 56,
"id": "6997ba95",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10\n",
"a\n",
"b\n"
]
}
],
"source": [
"for i in n:\n",
" print(i)"
]
},
{
"cell_type": "markdown",
"id": "1f38bc03",
"metadata": {},
"source": [
"# Set operations\n",
"\n",
"#### union"
]
},
{
"cell_type": "code",
"execution_count": 57,
"id": "cde829c8",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{1, 2, 3, 4, 5, 6, 7, 8, 9}\n"
]
}
],
"source": [
"f = {1,2,3,4,5,6}\n",
"s = {4,5,6,7,8,9}\n",
"\n",
"print(f | s) # union"
]
},
{
"cell_type": "markdown",
"id": "4f9ef43c",
"metadata": {},
"source": [
"#### intersection"
]
},
{
"cell_type": "code",
"execution_count": 58,
"id": "58b28ca7",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{4, 5, 6}\n"
]
}
],
"source": [
"f = {1,2,3,4,5,6}\n",
"s = {4,5,6,7,8,9}\n",
"\n",
"print(f & s) # intersection"
]
},
{
"cell_type": "markdown",
"id": "69c8e095",
"metadata": {},
"source": [
"#### difference"
]
},
{
"cell_type": "code",
"execution_count": 59,
"id": "81b857d2",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{1, 2, 3}\n"
]
}
],
"source": [
"f = {1,2,3,4,5,6}\n",
"s = {4,5,6,7,8,9}\n",
"\n",
"print(f - s) # difference"
]
},
{
"cell_type": "code",
"execution_count": 60,
"id": "d9eaa143",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{8, 9, 7}\n"
]
}
],
"source": [
"f = {1,2,3,4,5,6}\n",
"s = {4,5,6,7,8,9}\n",
"\n",
"print(s - f) # difference"
]
},
{
"cell_type": "markdown",
"id": "17db78c6",
"metadata": {},
"source": [
"#### symmetric"
]
},
{
"cell_type": "code",
"execution_count": 61,
"id": "0200b5d0",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{1, 2, 3, 7, 8, 9}\n"
]
}
],
"source": [
"f = {1,2,3,4,5,6}\n",
"s = {4,5,6,7,8,9}\n",
"\n",
"print(f ^ s) # symmetric"
]
},
{
"cell_type": "markdown",
"id": "64ddb35d",
"metadata": {},
"source": [
"# set functions"
]
},
{
"cell_type": "code",
"execution_count": 62,
"id": "000b5af4",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"6\n",
"21\n",
"6\n"
]
}
],
"source": [
"s = {1,2,3,4,5,6}\n",
"\n",
"print(len(s))\n",
"print(sum(s))\n",
"print(max(s))"
]
},
{
"cell_type": "markdown",
"id": "d07deba1",
"metadata": {},
"source": [
"# set methods\n",
"\n",
"#### add"
]
},
{
"cell_type": "code",
"execution_count": 66,
"id": "784b2205",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{1, 2, 3, 4, 5, 6}\n",
"{1, 2, 3, 4, 5, 6, -7}\n"
]
}
],
"source": [
"n = {1,2,1,3,4,5,6}\n",
"\n",
"print(n)\n",
"\n",
"n.add(-7)\n",
"\n",
"print(n)"
]
},
{
"cell_type": "markdown",
"id": "e78cb535",
"metadata": {},
"source": [
"#### clear"
]
},
{
"cell_type": "code",
"execution_count": 67,
"id": "c948c4ff",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{1, 2, 3, 4, 5, 6, -7}\n",
"set()\n"
]
}
],
"source": [
"print(n)\n",
"n.clear()\n",
"print(n)"
]
},
{
"cell_type": "code",
"execution_count": 68,
"id": "a5ac2b2e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{1, 4, 5, 6}\n"
]
}
],
"source": [
"s = {1,2,3,4,5,6}\n",
"\n",
"s.remove(3)\n",
"s.remove(2)\n",
"\n",
"print(s)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "5fdb4232",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.12"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
================================================
FILE: March Cohort 2023/.ipynb_checkpoints/0_Python Basics-checkpoint.ipynb
================================================
{
"cells": [
{
"cell_type": "markdown",
"id": "1dd9932f",
"metadata": {},
"source": [
"# Python Basics\n",
"\n",
"we are working on print function in python"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "3ca45a0a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello World\n"
]
}
],
"source": [
"print(\"Hello World\")"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "e2a86f94",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello\n",
"World\n"
]
}
],
"source": [
"print(\"Hello\")\n",
"print(\"World\")"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "07db254e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello\n",
"World\n"
]
}
],
"source": [
"print(\"Hello\\nWorld\") # \\n -> new line character"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "46c947b9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello\tWorld\n"
]
}
],
"source": [
"print(\"Hello\\tWorld\") # \\t -> horizontal tab"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "fd07c92b",
"metadata": {},
"outputs": [],
"source": [
"# 8 spaces - \\t"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "960ceae0",
"metadata": {},
"outputs": [],
"source": [
"# binary language -> 1010110\n",
"\n",
"0 -> low voltage, no-charge\n",
"\n",
"1 -> high voltage, charge\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "10a75868",
"metadata": {},
"outputs": [],
"source": [
"bits > numbers > character > instructions > program > software"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "459a661b",
"metadata": {},
"outputs": [],
"source": [
"compiler\n",
"\n",
"interpreter -> python"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "991396e2",
"metadata": {},
"outputs": [],
"source": [
"source code -------> Byte code -----> Output\n",
" .c compile .bak Run .exe\n",
" .cpp .obj\n",
" .java .javac\n",
" .py .pyc"
]
},
{
"cell_type": "markdown",
"id": "9de76aa4",
"metadata": {},
"source": [
"# Variables"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "ca83f18c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10\n"
]
}
],
"source": [
"a = 10\n",
"\n",
"print(a)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "3a7bac6d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"45.13\n"
]
}
],
"source": [
"b = 45.13\n",
"\n",
"print(b)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "124cb33b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"India\n"
]
}
],
"source": [
"a = \"India\"\n",
"\n",
"print(a)"
]
},
{
"cell_type": "markdown",
"id": "406d111f",
"metadata": {},
"source": [
"# Data type"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "707a85a0",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10\n",
"<class 'int'>\n"
]
}
],
"source": [
"a = 10\n",
"\n",
"print(a)\n",
"\n",
"print(type(a))"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "bc9295ca",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10.65\n",
"<class 'float'>\n"
]
}
],
"source": [
"b = 10.65\n",
"\n",
"print(b)\n",
"\n",
"print(type(b))"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "5632508a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Screen\n",
"<class 'str'>\n"
]
}
],
"source": [
"c = \"Screen\"\n",
"\n",
"print(c)\n",
"\n",
"print(type(c))"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "644ec54c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"meet\n",
"<class 'str'>\n"
]
}
],
"source": [
"d = 'meet'\n",
"\n",
"print(d)\n",
"\n",
"print(type(d))"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "43f33389",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"it's an apple\n"
]
}
],
"source": [
"x = \"it's an apple\"\n",
"\n",
"print(x)"
]
},
{
"cell_type": "markdown",
"id": "e04549b7",
"metadata": {},
"source": [
"# Type Conversion"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "321b1438",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10.56\n",
"<class 'float'>\n",
"10\n",
"<class 'int'>\n"
]
}
],
"source": [
"a = 10.56\n",
"\n",
"print(a)\n",
"\n",
"print(type(a))\n",
"\n",
"b = int(a)\n",
"\n",
"print(b)\n",
"\n",
"print(type(b))"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "873230fd",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"100\n",
"<class 'str'>\n",
"100.0\n",
"<class 'float'>\n"
]
}
],
"source": [
"a = \"100\"\n",
"\n",
"print(a)\n",
"\n",
"print(type(a))\n",
"\n",
"b = float(a)\n",
"\n",
"print(b)\n",
"\n",
"print(type(b))"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "83db42ca",
"metadata": {},
"outputs": [],
"source": [
"int()\n",
"float()\n",
"str()\n",
"bool()\n",
"list()\n",
"dict()\n",
"tuple()\n",
"set()"
]
},
{
"cell_type": "markdown",
"id": "a54b3b8f",
"metadata": {},
"source": [
"# Input function"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "127dd9ee",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10\n",
"10\n"
]
}
],
"source": [
"a = input()\n",
"\n",
"print(a)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "6c872d87",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter Your Name: Himanshu\n",
"Himanshu\n"
]
}
],
"source": [
"a = input(\"Enter Your Name: \")\n",
"\n",
"print(a)"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "f332e9d1",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter Your Name: Himanshu\n",
"Hello! How are you? Himanshu\n"
]
}
],
"source": [
"a = input(\"Enter Your Name: \")\n",
"\n",
"print(\"Hello! How are you?\", a)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "076ba3aa",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.12"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
================================================
FILE: March Cohort 2023/.ipynb_checkpoints/13_14_Object Orientation-checkpoint.ipynb
================================================
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "f956ae23",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'int'>\n"
]
}
],
"source": [
"a = 10\n",
"\n",
"print(type(a))"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "a8e19eec",
"metadata": {
"scrolled": false
},
"outputs": [],
"source": [
"# help(int)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "02596f25",
"metadata": {},
"outputs": [],
"source": [
"int a = 10; # 2 bytes - 16 bits\n",
"\n",
"struct car{\n",
" int cust_id; # 2 bytes\n",
" char name[10];# 10 bytes\n",
" float price; # 4 bytes\n",
"}\n",
"\n",
"struct car c1;\n",
" int a;"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "73d30a38",
"metadata": {},
"outputs": [],
"source": [
"bit>numbers>characters>instructions>function(program)>class>modules>package>library>framework>software"
]
},
{
"cell_type": "markdown",
"id": "8ae18de9",
"metadata": {},
"source": [
"# Object Orientation\n",
"\n",
"7 properties of OOP\n",
"\n",
"1. Class\n",
" Updated version of structures (struct -- C programming)\n",
" collection of variables and methods\n",
" class is a blueprint.\n",
"2. Object\n",
" Run time or real time entity.\n",
" hash code/virtual code - ID(python)\n",
" \n",
"3. Abstraction and Encapsulation\n",
" Abstraction - showing only essential features without showing any background details.\n",
" Encapsulation - wrapping up of data in a single unit.\n",
" \n",
"4. Inheritance\n",
" Acquiring properties of one class into another.\n",
" code reusability\n",
" - single level\n",
" - multi level\n",
" - heirarchical\n",
" - multiple\n",
" - hybride\n",
" \n",
"5. Polymorphism\n",
" same name multiple functionalities\n",
" - method overloading\n",
" - method overriding\n",
" \n",
"6. Dynamic Memory Allocation\n",
" run time memory allocation\n",
" \n",
"7. Message Passing\n",
" Communication between objects"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "d69e271e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"2207057668688\n"
]
}
],
"source": [
"a = 10\n",
"\n",
"print(id(a))"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "cb563
gitextract_mu6uxmva/ ├── July Cohort 2023/ │ └── 1_Python Programming/ │ ├── .ipynb_checkpoints/ │ │ ├── 01_Python Basics-checkpoint.ipynb │ │ ├── 02_03_While Loop and List-checkpoint.ipynb │ │ ├── 04_Strings and For loop-checkpoint.ipynb │ │ └── 05_Dictionary Tuples and Set-checkpoint.ipynb │ ├── 01_Python Basics.ipynb │ ├── 02_03_While Loop and List.ipynb │ ├── 04_Strings and For loop.ipynb │ └── 05_Dictionary Tuples and Set.ipynb ├── March Cohort 2023/ │ ├── .ipynb_checkpoints/ │ │ ├── 0_Python Basics-checkpoint.ipynb │ │ ├── 13_14_Object Orientation-checkpoint.ipynb │ │ ├── 1_While Loops and Logic Building-checkpoint.ipynb │ │ ├── 2_List and Strings-checkpoint.ipynb │ │ ├── 3_For Loop Dictionary Tuple and Sets-checkpoint.ipynb │ │ ├── 4_Functions-checkpoint.ipynb │ │ └── 5_Modules and Packages-checkpoint.ipynb │ ├── 0_Python Basics.ipynb │ ├── 10_11_EDA Project/ │ │ ├── .ipynb_checkpoints/ │ │ │ └── 10_11_EDA Project-checkpoint.ipynb │ │ ├── 10_11_EDA Project.ipynb │ │ ├── titanic.csv │ │ └── titanic_cleaned.csv │ ├── 10_Matplotlib/ │ │ ├── .ipynb_checkpoints/ │ │ │ └── 10_Matplotlib-checkpoint.ipynb │ │ └── 10_Matplotlib.ipynb │ ├── 12_15_16_17_18_Statistics/ │ │ ├── .ipynb_checkpoints/ │ │ │ ├── 12_15_Statistics-checkpoint.ipynb │ │ │ ├── 16_17_Statistics and Regression-checkpoint.ipynb │ │ │ └── 18_Hypothesis Testing-checkpoint.ipynb │ │ ├── 12_15_Statistics.ipynb │ │ ├── 16_17_Statistics and Regression.ipynb │ │ ├── 18_Hypothesis Testing.ipynb │ │ ├── datasets/ │ │ │ ├── Birthweight_reduced_kg_R.csv │ │ │ ├── CarPrice_Assignment.csv │ │ │ ├── Crime_R.csv │ │ │ ├── IPL2013.csv │ │ │ ├── SP_500_1987.csv │ │ │ ├── data_loan.csv │ │ │ └── forbes.csv │ │ ├── sample_submission.csv │ │ ├── test.csv │ │ └── train.csv │ ├── 13_14_Object Orientation.ipynb │ ├── 19_20_Machine Learning/ │ │ ├── .ipynb_checkpoints/ │ │ │ ├── 19_Machine Learning and Linear Regression with One variable-checkpoint.ipynb │ │ │ └── 20_Logistic Regression-checkpoint.ipynb │ │ ├── 19_Machine Learning and Linear Regression with One variable.ipynb │ │ ├── 20_Logistic Regression.ipynb │ │ ├── areas.csv │ │ ├── homeprices.csv │ │ ├── insurance_data.csv │ │ └── spend.xlsx │ ├── 1_While Loops and Logic Building.ipynb │ ├── 21_EDA and Data Viz/ │ │ ├── .ipynb_checkpoints/ │ │ │ └── 21_EDA and Data Visualization-checkpoint.ipynb │ │ ├── 21_EDA and Data Visualization.ipynb │ │ └── itunes_data.csv │ ├── 22_23_Time Series Forecasting/ │ │ ├── .ipynb_checkpoints/ │ │ │ ├── 22_Forecasting-checkpoint.ipynb │ │ │ └── 23_ARIMA-checkpoint.ipynb │ │ ├── 22_Forecasting.ipynb │ │ ├── 23_ARIMA.ipynb │ │ ├── store.xls │ │ ├── vimana.csv │ │ └── wsb.csv │ ├── 24_SQL/ │ │ └── SQLqueriesQandA.sql │ ├── 2_List and Strings.ipynb │ ├── 3_For Loop Dictionary Tuple and Sets.ipynb │ ├── 4_Functions.ipynb │ ├── 5_Modules and Packages.ipynb │ ├── 5_Modules-Packages/ │ │ ├── main.py │ │ ├── rose.py │ │ └── statsmeme/ │ │ ├── __init__.py │ │ ├── descriptive.py │ │ └── inferential.py │ ├── 6_VirtualEnvironmentAndFlask/ │ │ ├── application.py │ │ └── templates/ │ │ └── index.html │ ├── 7_NumPy/ │ │ ├── .ipynb_checkpoints/ │ │ │ └── 7_NumPy-checkpoint.ipynb │ │ └── 7_NumPy.ipynb │ └── 8_9_Pandas/ │ ├── .ipynb_checkpoints/ │ │ └── 8_9_Pandas-checkpoint.ipynb │ ├── 8_9_Pandas.ipynb │ ├── Data Cleaning With Pandas/ │ │ ├── Data Cleaning with Python and Pandas_ Detecting Missing Values.html │ │ └── Data Cleaning with Python and Pandas_ Detecting Missing Values_files/ │ │ ├── analytics.js.download │ │ ├── comment-reply.min.js.download │ │ ├── common.js.download │ │ ├── css │ │ ├── css(1) │ │ ├── css(2) │ │ ├── custom.js(1).download │ │ ├── custom.js.download │ │ ├── custom.min.js.download │ │ ├── form.js.download │ │ ├── frontend.min.js.download │ │ ├── idle-timer.min.js(1).download │ │ ├── idle-timer.min.js.download │ │ ├── jquery-migrate.min.js.download │ │ ├── jquery.js.download │ │ ├── jquery.uniform.min.js.download │ │ ├── linkid.js.download │ │ ├── prism-js.min.js.download │ │ ├── style(1).css │ │ ├── style(2).css │ │ ├── style(3).css │ │ ├── style.css │ │ ├── wp-embed.min.js.download │ │ └── wp-emoji-release.min.js.download │ ├── indore.csv │ ├── nyc_weather.csv │ ├── stock_data.csv │ ├── stocks_weather.xlsx │ ├── weather_by_cities.csv │ ├── weather_data.csv │ ├── weather_data.xlsx │ ├── weather_data2.csv │ ├── weather_datamissing.csv │ └── weather_datamissing_regex.csv └── README.md
SYMBOL INDEX (10 symbols across 5 files) FILE: March Cohort 2023/24_SQL/SQLqueriesQandA.sql type Bonus (line 29) | CREATE TABLE Bonus ( type Title (line 47) | CREATE TABLE Title ( FILE: March Cohort 2023/5_Modules-Packages/rose.py function color (line 3) | def color(): function flower (line 6) | def flower(): FILE: March Cohort 2023/5_Modules-Packages/statsmeme/descriptive.py function mean (line 1) | def mean(l): function mode (line 6) | def mode(): FILE: March Cohort 2023/5_Modules-Packages/statsmeme/inferential.py function models (line 1) | def models(): FILE: March Cohort 2023/6_VirtualEnvironmentAndFlask/application.py function hello (line 25) | def hello(): function home (line 29) | def home(): function profile (line 34) | def profile():
Copy disabled (too large)
Download .json
Condensed preview — 110 files, each showing path, character count, and a content snippet. Download the .json file for the full structured content (13,379K chars).
[
{
"path": "July Cohort 2023/1_Python Programming/.ipynb_checkpoints/01_Python Basics-checkpoint.ipynb",
"chars": 8117,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"5effdff7\",\n \"metadata\": {},\n \"source\": [\n \"# Python Basic"
},
{
"path": "July Cohort 2023/1_Python Programming/.ipynb_checkpoints/02_03_While Loop and List-checkpoint.ipynb",
"chars": 40288,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"13c6ac1c\",\n \"metadata\": {},\n \"source\": [\n \"# While Loop\"\n"
},
{
"path": "July Cohort 2023/1_Python Programming/.ipynb_checkpoints/04_Strings and For loop-checkpoint.ipynb",
"chars": 20524,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"89086545\",\n \"metadata\": {},\n \"source\": [\n \"# Strings\\n\",\n"
},
{
"path": "July Cohort 2023/1_Python Programming/.ipynb_checkpoints/05_Dictionary Tuples and Set-checkpoint.ipynb",
"chars": 21460,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"34a4e5e6\",\n \"metadata\": {},\n \"source\": [\n \"# Dictionary\"\n"
},
{
"path": "July Cohort 2023/1_Python Programming/01_Python Basics.ipynb",
"chars": 8117,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"5effdff7\",\n \"metadata\": {},\n \"source\": [\n \"# Python Basic"
},
{
"path": "July Cohort 2023/1_Python Programming/02_03_While Loop and List.ipynb",
"chars": 40288,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"13c6ac1c\",\n \"metadata\": {},\n \"source\": [\n \"# While Loop\"\n"
},
{
"path": "July Cohort 2023/1_Python Programming/04_Strings and For loop.ipynb",
"chars": 20524,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"89086545\",\n \"metadata\": {},\n \"source\": [\n \"# Strings\\n\",\n"
},
{
"path": "July Cohort 2023/1_Python Programming/05_Dictionary Tuples and Set.ipynb",
"chars": 27458,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"0d853ca0\",\n \"metadata\": {},\n \"source\": [\n \"# Dictionary\"\n"
},
{
"path": "March Cohort 2023/.ipynb_checkpoints/0_Python Basics-checkpoint.ipynb",
"chars": 8494,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"1dd9932f\",\n \"metadata\": {},\n \"source\": [\n \"# Python Basic"
},
{
"path": "March Cohort 2023/.ipynb_checkpoints/13_14_Object Orientation-checkpoint.ipynb",
"chars": 24313,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"id\": \"f956ae23\",\n \"metadata\": {},\n \"outputs\":"
},
{
"path": "March Cohort 2023/.ipynb_checkpoints/1_While Loops and Logic Building-checkpoint.ipynb",
"chars": 16031,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"dfbc28de\",\n \"metadata\": {},\n \"source\": [\n \"# While Loop\"\n"
},
{
"path": "March Cohort 2023/.ipynb_checkpoints/2_List and Strings-checkpoint.ipynb",
"chars": 56513,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"f18f8832\",\n \"metadata\": {},\n \"source\": [\n \"# List\\n\",\n "
},
{
"path": "March Cohort 2023/.ipynb_checkpoints/3_For Loop Dictionary Tuple and Sets-checkpoint.ipynb",
"chars": 40635,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"958dd5a9\",\n \"metadata\": {},\n \"source\": [\n \"# Range functi"
},
{
"path": "March Cohort 2023/.ipynb_checkpoints/4_Functions-checkpoint.ipynb",
"chars": 27546,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"a98c255e\",\n \"metadata\": {},\n \"source\": [\n \"# Functions\"\n "
},
{
"path": "March Cohort 2023/.ipynb_checkpoints/5_Modules and Packages-checkpoint.ipynb",
"chars": 11019,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"507b0a7e\",\n \"metadata\": {},\n \"source\": [\n \"# OS\\n\",\n \""
},
{
"path": "March Cohort 2023/0_Python Basics.ipynb",
"chars": 8494,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"1dd9932f\",\n \"metadata\": {},\n \"source\": [\n \"# Python Basic"
},
{
"path": "March Cohort 2023/10_11_EDA Project/.ipynb_checkpoints/10_11_EDA Project-checkpoint.ipynb",
"chars": 121477,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"373ae802\",\n \"metadata\": {},\n \"source\": [\n \"# Titanic Surv"
},
{
"path": "March Cohort 2023/10_11_EDA Project/10_11_EDA Project.ipynb",
"chars": 121477,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"373ae802\",\n \"metadata\": {},\n \"source\": [\n \"# Titanic Surv"
},
{
"path": "March Cohort 2023/10_11_EDA Project/titanic.csv",
"chars": 60305,
"preview": "PassengerId,Survived,Pclass,Name,Gender,Age,SibSp,Parch,Ticket,Fare,Cabin,Embarked\n1,0,3,\"Braund, Mr. Owen Harris\",male,"
},
{
"path": "March Cohort 2023/10_11_EDA Project/titanic_cleaned.csv",
"chars": 45537,
"preview": "Survived,Pclass,Age,Fare,male,C,Q,S,SibSp_0,SibSp_1,SibSp_2,SibSp_3,SibSp_4,SibSp_5,SibSp_8,Parch_0,Parch_1,Parch_2,Parc"
},
{
"path": "March Cohort 2023/10_Matplotlib/.ipynb_checkpoints/10_Matplotlib-checkpoint.ipynb",
"chars": 72,
"preview": "{\n \"cells\": [],\n \"metadata\": {},\n \"nbformat\": 4,\n \"nbformat_minor\": 5\n}\n"
},
{
"path": "March Cohort 2023/10_Matplotlib/10_Matplotlib.ipynb",
"chars": 340703,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"d32aa7c4\",\n \"metadata\": {},\n \"source\": [\n \"# Matplotlib B"
},
{
"path": "March Cohort 2023/12_15_16_17_18_Statistics/.ipynb_checkpoints/12_15_Statistics-checkpoint.ipynb",
"chars": 297860,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"df89b0c5\",\n \"metadata\": {},\n \"source\": [\n \"# Statistics\\n"
},
{
"path": "March Cohort 2023/12_15_16_17_18_Statistics/.ipynb_checkpoints/16_17_Statistics and Regression-checkpoint.ipynb",
"chars": 344689,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"103790af\",\n \"metadata\": {},\n \"source\": [\n \"# Multiple Lin"
},
{
"path": "March Cohort 2023/12_15_16_17_18_Statistics/.ipynb_checkpoints/18_Hypothesis Testing-checkpoint.ipynb",
"chars": 14313,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"c585a495\",\n \"metadata\": {},\n \"source\": [\n \"# Hypothesis T"
},
{
"path": "March Cohort 2023/12_15_16_17_18_Statistics/12_15_Statistics.ipynb",
"chars": 297860,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"df89b0c5\",\n \"metadata\": {},\n \"source\": [\n \"# Statistics\\n"
},
{
"path": "March Cohort 2023/12_15_16_17_18_Statistics/16_17_Statistics and Regression.ipynb",
"chars": 344689,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"103790af\",\n \"metadata\": {},\n \"source\": [\n \"# Multiple Lin"
},
{
"path": "March Cohort 2023/12_15_16_17_18_Statistics/18_Hypothesis Testing.ipynb",
"chars": 14313,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"c585a495\",\n \"metadata\": {},\n \"source\": [\n \"# Hypothesis T"
},
{
"path": "March Cohort 2023/12_15_16_17_18_Statistics/datasets/Birthweight_reduced_kg_R.csv",
"chars": 2182,
"preview": "ID,Length,Birthweight,Headcirc,Gestation,smoker,mage,mnocig,mheight,mppwt,fage,fedyrs,fnocig,fheight,lowbwt,mage35\n1360"
},
{
"path": "March Cohort 2023/12_15_16_17_18_Statistics/datasets/CarPrice_Assignment.csv",
"chars": 26511,
"preview": "car_ID,symboling,CarName,fueltype,aspiration,doornumber,carbody,drivewheel,enginelocation,wheelbase,carlength,carwidth,c"
},
{
"path": "March Cohort 2023/12_15_16_17_18_Statistics/datasets/Crime_R.csv",
"chars": 4831,
"preview": "CrimeRate,Youth,Southern,Education,ExpenditureYear0,LabourForce,Males,MoreMales,StateSize,YouthUnemployment,MatureUnemp"
},
{
"path": "March Cohort 2023/12_15_16_17_18_Statistics/datasets/IPL2013.csv",
"chars": 15531,
"preview": "Sl.NO.,PLAYER NAME,AGE,COUNTRY,TEAM,PLAYING ROLE,T-RUNS,T-WKTS,ODI-RUNS-S,ODI-SR-B,ODI-WKTS,ODI-SR-BL,CAPTAINCY EXP,RUNS"
},
{
"path": "March Cohort 2023/12_15_16_17_18_Statistics/datasets/SP_500_1987.csv",
"chars": 15482,
"preview": "Date,Open,High,Low,Close,AdjClose,Volume\n31-Dec-1986,243.37,244.03,241.28,242.17,242.17,\"13,92,00,000\"\n2-Jan-1987,242.17"
},
{
"path": "March Cohort 2023/12_15_16_17_18_Statistics/datasets/data_loan.csv",
"chars": 248774,
"preview": "ID,Default,Loan_type,Gender,Age,Degree,Income,Credit_score,Loan_length,Signers,Citizenship\n1,0,Car ,Female,30,HS ,1"
},
{
"path": "March Cohort 2023/12_15_16_17_18_Statistics/datasets/forbes.csv",
"chars": 150956,
"preview": "Rank,Company,Country,Sales,Profits,Assets,Market Value,Sector,Industry\n1,ICBC,China,151.4,42,3473.2,229.8,Financials,Maj"
},
{
"path": "March Cohort 2023/12_15_16_17_18_Statistics/sample_submission.csv",
"chars": 3363144,
"preview": "id,cost\n360336,99.615\n360337,99.615\n360338,99.615\n360339,99.615\n360340,99.615\n360341,99.615\n360342,99.615\n360343,99.615\n"
},
{
"path": "March Cohort 2023/13_14_Object Orientation.ipynb",
"chars": 24313,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"id\": \"f956ae23\",\n \"metadata\": {},\n \"outputs\":"
},
{
"path": "March Cohort 2023/19_20_Machine Learning/.ipynb_checkpoints/19_Machine Learning and Linear Regression with One variable-checkpoint.ipynb",
"chars": 61294,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"7242d236\",\n \"metadata\": {},\n \"source\": [\n \"# Machine Lear"
},
{
"path": "March Cohort 2023/19_20_Machine Learning/.ipynb_checkpoints/20_Logistic Regression-checkpoint.ipynb",
"chars": 75152,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"c71657c4\",\n \"metadata\": {},\n \"source\": [\n \"# Logistic Reg"
},
{
"path": "March Cohort 2023/19_20_Machine Learning/19_Machine Learning and Linear Regression with One variable.ipynb",
"chars": 61294,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"7242d236\",\n \"metadata\": {},\n \"source\": [\n \"# Machine Lear"
},
{
"path": "March Cohort 2023/19_20_Machine Learning/20_Logistic Regression.ipynb",
"chars": 75152,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"c71657c4\",\n \"metadata\": {},\n \"source\": [\n \"# Logistic Reg"
},
{
"path": "March Cohort 2023/19_20_Machine Learning/areas.csv",
"chars": 70,
"preview": "area\n1000\n1500\n2300\n3540\n4120\n4560\n5490\n3460\n4750\n2300\n9000\n8600\n7100\n"
},
{
"path": "March Cohort 2023/19_20_Machine Learning/homeprices.csv",
"chars": 71,
"preview": "area,price\n2600,550000\n3000,565000\n3200,610000\n3600,680000\n4000,725000\n"
},
{
"path": "March Cohort 2023/19_20_Machine Learning/insurance_data.csv",
"chars": 155,
"preview": "age,bought_insurance\n22,0\n25,0\n47,1\n52,0\n46,1\n56,1\n55,0\n60,1\n62,1\n61,1\n18,0\n28,0\n27,0\n29,0\n49,1\n55,1\n25,1\n58,1\n19,0\n18,0"
},
{
"path": "March Cohort 2023/1_While Loops and Logic Building.ipynb",
"chars": 16031,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"dfbc28de\",\n \"metadata\": {},\n \"source\": [\n \"# While Loop\"\n"
},
{
"path": "March Cohort 2023/21_EDA and Data Viz/.ipynb_checkpoints/21_EDA and Data Visualization-checkpoint.ipynb",
"chars": 1498766,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"343be340\",\n \"metadata\": {},\n \"source\": [\n \"# EDA\"\n ]\n "
},
{
"path": "March Cohort 2023/21_EDA and Data Viz/21_EDA and Data Visualization.ipynb",
"chars": 1498766,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"343be340\",\n \"metadata\": {},\n \"source\": [\n \"# EDA\"\n ]\n "
},
{
"path": "March Cohort 2023/21_EDA and Data Viz/itunes_data.csv",
"chars": 343699,
"preview": "Track,Composer,Milliseconds,Bytes,UnitPrice,Genre,Album,Artist\nFor Those About To Rock (We Salute You),\"Angus Young, Mal"
},
{
"path": "March Cohort 2023/22_23_Time Series Forecasting/.ipynb_checkpoints/22_Forecasting-checkpoint.ipynb",
"chars": 168774,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"12c7b612\",\n \"metadata\": {},\n \"source\": [\n \"# Time series "
},
{
"path": "March Cohort 2023/22_23_Time Series Forecasting/.ipynb_checkpoints/23_ARIMA-checkpoint.ipynb",
"chars": 163019,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"5e5ca069\",\n \"metadata\": {},\n \"source\": [\n \"# Auto Regress"
},
{
"path": "March Cohort 2023/22_23_Time Series Forecasting/22_Forecasting.ipynb",
"chars": 168774,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"12c7b612\",\n \"metadata\": {},\n \"source\": [\n \"# Time series "
},
{
"path": "March Cohort 2023/22_23_Time Series Forecasting/23_ARIMA.ipynb",
"chars": 163019,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"5e5ca069\",\n \"metadata\": {},\n \"source\": [\n \"# Auto Regress"
},
{
"path": "March Cohort 2023/22_23_Time Series Forecasting/vimana.csv",
"chars": 262,
"preview": "Month,demand\n1,457\n2,439\n3,404\n4,392\n5,403\n6,371\n7,382\n8,358\n9,594\n10,482\n11,574\n12,704\n13,486\n14,509\n15,537\n16,407\n17,5"
},
{
"path": "March Cohort 2023/22_23_Time Series Forecasting/wsb.csv",
"chars": 865,
"preview": "Month,Sale Quantity,Promotion Expenses,Competition Promotion\r1,3002666,105,1\r2,4401553,145,0\r3,3205279,118,1\r4,4245349,1"
},
{
"path": "March Cohort 2023/24_SQL/SQLqueriesQandA.sql",
"chars": 7733,
"preview": "-- DROP DATABASE ORG;\n\nCREATE DATABASE ORG;\nSHOW DATABASES;\nUSE ORG;\n\n-- drop table Worker;\n\nCREATE TABLE Worker (\n\tWORK"
},
{
"path": "March Cohort 2023/2_List and Strings.ipynb",
"chars": 56513,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"f18f8832\",\n \"metadata\": {},\n \"source\": [\n \"# List\\n\",\n "
},
{
"path": "March Cohort 2023/3_For Loop Dictionary Tuple and Sets.ipynb",
"chars": 40635,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"958dd5a9\",\n \"metadata\": {},\n \"source\": [\n \"# Range functi"
},
{
"path": "March Cohort 2023/4_Functions.ipynb",
"chars": 27546,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"a98c255e\",\n \"metadata\": {},\n \"source\": [\n \"# Functions\"\n "
},
{
"path": "March Cohort 2023/5_Modules and Packages.ipynb",
"chars": 11019,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"507b0a7e\",\n \"metadata\": {},\n \"source\": [\n \"# OS\\n\",\n \""
},
{
"path": "March Cohort 2023/5_Modules-Packages/main.py",
"chars": 241,
"preview": "# import rose\n\n# print(rose.pie)\n\n# print(rose.color())\n\nfrom statsmeme import descriptive\n\nprint(descriptive.mode())\n\nf"
},
{
"path": "March Cohort 2023/5_Modules-Packages/rose.py",
"chars": 97,
"preview": "pie = 3000\n\ndef color():\n return \"red\"\n\ndef flower():\n return \"color of the flower is blue\""
},
{
"path": "March Cohort 2023/5_Modules-Packages/statsmeme/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "March Cohort 2023/5_Modules-Packages/statsmeme/descriptive.py",
"chars": 122,
"preview": "def mean(l):\n m = sum(l)/len(l)\n return m\n\n\ndef mode():\n return \"this is mode function from descriptive stats\""
},
{
"path": "March Cohort 2023/5_Modules-Packages/statsmeme/inferential.py",
"chars": 55,
"preview": "def models():\n return \"models from inferetial stats\""
},
{
"path": "March Cohort 2023/6_VirtualEnvironmentAndFlask/application.py",
"chars": 976,
"preview": "from flask import Flask, render_template\nimport requests\nfrom bs4 import BeautifulSoup\n\napp = Flask(__name__) # __main_"
},
{
"path": "March Cohort 2023/6_VirtualEnvironmentAndFlask/templates/index.html",
"chars": 300,
"preview": "<html lang=\"en\">\n<head>\n <meta charset=\"UTF-8\">\n <meta http-equiv=\"X-UA-Compatible\" content=\"IE=edge\">\n <meta n"
},
{
"path": "March Cohort 2023/7_NumPy/.ipynb_checkpoints/7_NumPy-checkpoint.ipynb",
"chars": 18020,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"26f54c18\",\n \"metadata\": {},\n \"source\": [\n \"# NumPy\\n\",\n "
},
{
"path": "March Cohort 2023/7_NumPy/7_NumPy.ipynb",
"chars": 18020,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"26f54c18\",\n \"metadata\": {},\n \"source\": [\n \"# NumPy\\n\",\n "
},
{
"path": "March Cohort 2023/8_9_Pandas/.ipynb_checkpoints/8_9_Pandas-checkpoint.ipynb",
"chars": 225487,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"a6a858e0\",\n \"metadata\": {},\n \"source\": [\n \"# Pandas\"\n ]"
},
{
"path": "March Cohort 2023/8_9_Pandas/8_9_Pandas.ipynb",
"chars": 225487,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"id\": \"a6a858e0\",\n \"metadata\": {},\n \"source\": [\n \"# Pandas\"\n ]"
},
{
"path": "March Cohort 2023/8_9_Pandas/Data Cleaning With Pandas/Data Cleaning with Python and Pandas_ Detecting Missing Values.html",
"chars": 155384,
"preview": "<!DOCTYPE html>\n<!-- saved from url=(0059)https://www.dataoptimal.com/data-cleaning-with-python-2018/ -->\n<html lang=\"en"
},
{
"path": "March Cohort 2023/8_9_Pandas/Data Cleaning With Pandas/Data Cleaning with Python and Pandas_ Detecting Missing Values_files/analytics.js.download",
"chars": 44130,
"preview": "(function(){var k=this,l=function(a,b){a=a.split(\".\");var c=k;a[0]in c||\"undefined\"==typeof c.execScript||c.execScript(\""
},
{
"path": "March Cohort 2023/8_9_Pandas/Data Cleaning With Pandas/Data Cleaning with Python and Pandas_ Detecting Missing Values_files/comment-reply.min.js.download",
"chars": 2234,
"preview": "window.addComment=function(a){function b(){c(),g()}function c(a){if(t&&(m=j(r.cancelReplyId),n=j(r.commentFormId),m)){m."
},
{
"path": "March Cohort 2023/8_9_Pandas/Data Cleaning With Pandas/Data Cleaning with Python and Pandas_ Detecting Missing Values_files/common.js.download",
"chars": 1360,
"preview": "(function($){\n\t$(document).ready( function(){\n\t\tvar user_agent = navigator.userAgent;\n\t\tvar is_opera_edge;\n\t\tvar browser"
},
{
"path": "March Cohort 2023/8_9_Pandas/Data Cleaning With Pandas/Data Cleaning with Python and Pandas_ Detecting Missing Values_files/css",
"chars": 4750,
"preview": "/* cyrillic-ext */\n@font-face {\n font-family: 'Open Sans';\n font-style: normal;\n font-weight: 400;\n src: local('Open"
},
{
"path": "March Cohort 2023/8_9_Pandas/Data Cleaning With Pandas/Data Cleaning with Python and Pandas_ Detecting Missing Values_files/css(1)",
"chars": 24443,
"preview": "/* cyrillic-ext */\n@font-face {\n font-family: 'Open Sans';\n font-style: italic;\n font-weight: 300;\n src: local('Open"
},
{
"path": "March Cohort 2023/8_9_Pandas/Data Cleaning With Pandas/Data Cleaning with Python and Pandas_ Detecting Missing Values_files/css(2)",
"chars": 3068,
"preview": "/* latin-ext */\n@font-face {\n font-family: 'Karla';\n font-style: italic;\n font-weight: 400;\n src: local('Karla Itali"
},
{
"path": "March Cohort 2023/8_9_Pandas/Data Cleaning With Pandas/Data Cleaning with Python and Pandas_ Detecting Missing Values_files/custom.js(1).download",
"chars": 26019,
"preview": "(function($){\n\t$(document).ready(function() {\n\t\tvar $locked_containers = [];\n\n\t\t$( '.et_bloom_make_form_visible' ).remov"
},
{
"path": "March Cohort 2023/8_9_Pandas/Data Cleaning With Pandas/Data Cleaning with Python and Pandas_ Detecting Missing Values_files/custom.js.download",
"chars": 26371,
"preview": "(function($){\n\t$(document).ready(function() {\n\t\tvar all_networks_opened = 0;\n\n\t\t// fix the \"on media\" wrapper inside the"
},
{
"path": "March Cohort 2023/8_9_Pandas/Data Cleaning With Pandas/Data Cleaning with Python and Pandas_ Detecting Missing Values_files/custom.min.js.download",
"chars": 264205,
"preview": "/*! ET et_shortcodes_frontend.js */\n!function($){$.fn.et_shortcodes_switcher=function(options){options=$.extend({slides:"
},
{
"path": "March Cohort 2023/8_9_Pandas/Data Cleaning With Pandas/Data Cleaning with Python and Pandas_ Detecting Missing Values_files/form.js.download",
"chars": 700,
"preview": "var ak_js = document.getElementById( \"ak_js\" );\n\nif ( ! ak_js ) {\n\tak_js = document.createElement( 'input' );\n\tak_js.set"
},
{
"path": "March Cohort 2023/8_9_Pandas/Data Cleaning With Pandas/Data Cleaning with Python and Pandas_ Detecting Missing Values_files/frontend.min.js.download",
"chars": 8363,
"preview": ";var MonsterInsights=function(){var t=[],a='';this.setLastClicked=function(e,n,i){e=typeof e!=='undefined'?e:[];n=typeof"
},
{
"path": "March Cohort 2023/8_9_Pandas/Data Cleaning With Pandas/Data Cleaning with Python and Pandas_ Detecting Missing Values_files/idle-timer.min.js(1).download",
"chars": 2518,
"preview": "/*! Idle Timer v1.0.1 2014-03-21 | https://github.com/thorst/jquery-idletimer | (c) 2014 Paul Irish | Licensed MIT */\n!f"
},
{
"path": "March Cohort 2023/8_9_Pandas/Data Cleaning With Pandas/Data Cleaning with Python and Pandas_ Detecting Missing Values_files/idle-timer.min.js.download",
"chars": 2518,
"preview": "/*! Idle Timer v1.0.1 2014-03-21 | https://github.com/thorst/jquery-idletimer | (c) 2014 Paul Irish | Licensed MIT */\n!f"
},
{
"path": "March Cohort 2023/8_9_Pandas/Data Cleaning With Pandas/Data Cleaning with Python and Pandas_ Detecting Missing Values_files/jquery-migrate.min.js.download",
"chars": 10056,
"preview": "/*! jQuery Migrate v1.4.1 | (c) jQuery Foundation and other contributors | jquery.org/license */\n\"undefined\"==typeof jQu"
},
{
"path": "March Cohort 2023/8_9_Pandas/Data Cleaning With Pandas/Data Cleaning with Python and Pandas_ Detecting Missing Values_files/jquery.js.download",
"chars": 97183,
"preview": "/*! jQuery v1.12.4 | (c) jQuery Foundation | jquery.org/license */\n!function(a,b){\"object\"==typeof module&&\"object\"==typ"
},
{
"path": "March Cohort 2023/8_9_Pandas/Data Cleaning With Pandas/Data Cleaning with Python and Pandas_ Detecting Missing Values_files/jquery.uniform.min.js.download",
"chars": 8308,
"preview": "(function(e,t){\"use strict\";function n(e){var t=Array.prototype.slice.call(arguments,1);return e.prop?e.prop.apply(e,t):"
},
{
"path": "March Cohort 2023/8_9_Pandas/Data Cleaning With Pandas/Data Cleaning with Python and Pandas_ Detecting Missing Values_files/linkid.js.download",
"chars": 1569,
"preview": "(function(){var e=window,h=document,k=\"replace\";var m=function(a,c,d,b,g){c=encodeURIComponent(c)[k](/\\(/g,\"%28\")[k](/\\)"
},
{
"path": "March Cohort 2023/8_9_Pandas/Data Cleaning With Pandas/Data Cleaning with Python and Pandas_ Detecting Missing Values_files/prism-js.min.js.download",
"chars": 22424,
"preview": "/* http://prismjs.com/download.html?themes=prism */\nvar _self=\"undefined\"!=typeof window?window:\"undefined\"!=typeof Work"
},
{
"path": "March Cohort 2023/8_9_Pandas/Data Cleaning With Pandas/Data Cleaning with Python and Pandas_ Detecting Missing Values_files/style(1).css",
"chars": 632481,
"preview": "/*!\nTheme Name: Divi\nTheme URI: http://www.elegantthemes.com/gallery/divi/\nVersion: 3.21\nDescription: Smart. Flexible. B"
},
{
"path": "March Cohort 2023/8_9_Pandas/Data Cleaning With Pandas/Data Cleaning with Python and Pandas_ Detecting Missing Values_files/style(2).css",
"chars": 466,
"preview": "/*\nTheme Name: Divi Child theme of Divi\nTheme URI: \nDescription: Child theme of Divi theme for the Divi theme\nAuthor: <a"
},
{
"path": "March Cohort 2023/8_9_Pandas/Data Cleaning With Pandas/Data Cleaning with Python and Pandas_ Detecting Missing Values_files/style(3).css",
"chars": 94428,
"preview": "/*------------------------------------------------*/\n/*--------------------[RESET]---------------------*/\n/*------------"
},
{
"path": "March Cohort 2023/8_9_Pandas/Data Cleaning With Pandas/Data Cleaning with Python and Pandas_ Detecting Missing Values_files/style.css",
"chars": 116076,
"preview": "/*------------------------------------------------*/\n/*-----------------[RESET]------------------------*/\n/*------------"
},
{
"path": "March Cohort 2023/8_9_Pandas/Data Cleaning With Pandas/Data Cleaning with Python and Pandas_ Detecting Missing Values_files/wp-embed.min.js.download",
"chars": 1403,
"preview": "!function(a,b){\"use strict\";function c(){if(!e){e=!0;var a,c,d,f,g=-1!==navigator.appVersion.indexOf(\"MSIE 10\"),h=!!navi"
},
{
"path": "March Cohort 2023/8_9_Pandas/Data Cleaning With Pandas/Data Cleaning with Python and Pandas_ Detecting Missing Values_files/wp-emoji-release.min.js.download",
"chars": 12034,
"preview": "// Source: wp-includes/js/twemoji.min.js\nvar twemoji=function(){\"use strict\";function a(a,b){return document.createTextN"
},
{
"path": "March Cohort 2023/8_9_Pandas/indore.csv",
"chars": 97,
"preview": ",day,temperature,windspeed,event\n0,1/1/2023,32,6,Rain\n1,1/2/2023,35,7,Sunny\n2,1/3/2023,32,6,Snow\n"
},
{
"path": "March Cohort 2023/8_9_Pandas/nyc_weather.csv",
"chars": 1368,
"preview": "EST,Temperature,DewPoint,Humidity,Sea Level PressureIn,VisibilityMiles,WindSpeedMPH,PrecipitationIn,CloudCover,Events,Wi"
},
{
"path": "March Cohort 2023/8_9_Pandas/stock_data.csv",
"chars": 178,
"preview": "tickers,eps,revenue,price,people\nGOOGL,27.82,87,845,larry page\nWMT,4.61,484,65,n.a.\nMSFT,-1,85,64,bill gates\nRIL ,not av"
},
{
"path": "March Cohort 2023/8_9_Pandas/weather_by_cities.csv",
"chars": 367,
"preview": "day,city,temperature,windspeed,event\n1/1/2017,new york,32,6,Rain\n1/2/2017,new york,36,7,Sunny\n1/3/2017,new york,28,12,Sn"
},
{
"path": "March Cohort 2023/8_9_Pandas/weather_data.csv",
"chars": 148,
"preview": "day,temperature,windspeed,event\n1/1/2017,32,6,Rain\n1/2/2017,35,7,Sunny\n1/3/2017,28,2,Snow\n1/4/2017,24,7,Snow\n1/5/2017,32"
},
{
"path": "March Cohort 2023/8_9_Pandas/weather_data2.csv",
"chars": 191,
"preview": "day,temperature,windspeed,event\n1/1/2017,32,6,Rain\n1/4/2017,,9,Sunny\n1/5/2017,28,,Snow\n1/6/2017,,7,\n1/7/2017,32,,Rain\n1/"
},
{
"path": "March Cohort 2023/8_9_Pandas/weather_datamissing.csv",
"chars": 179,
"preview": "day,temperature,windspeed,event\n1/1/2017,32,6,Rain\n1/2/2017,-99999,7,Sunny\n1/3/2017,28,-99999,Snow\n1/4/2017,-99999,7,0\n1"
},
{
"path": "March Cohort 2023/8_9_Pandas/weather_datamissing_regex.csv",
"chars": 239,
"preview": "day,temperature,windspeed,event,speed\n01-01-2017,32C,6,Rain,45kmph\n01-02-2017,-99999,7,Sunny,40km\n01-03-2017,28F,-99999,"
},
{
"path": "README.md",
"chars": 3614,
"preview": "# Data-Analyst-Roadmap\nData-Analyst-Roadmap for Students and Professionals\n\n![](https://github.com/hemansnation/Data-Ana"
}
]
// ... and 6 more files (download for full content)
About this extraction
This page contains the full source code of the hemansnation/Data-Analyst-Roadmap GitHub repository, extracted and formatted as plain text for AI agents and large language models (LLMs). The extraction includes 110 files (56.5 MB), approximately 3.2M tokens, and a symbol index with 10 extracted functions, classes, methods, constants, and types. Use this with OpenClaw, Claude, ChatGPT, Cursor, Windsurf, or any other AI tool that accepts text input. You can copy the full output to your clipboard or download it as a .txt file.
Extracted by GitExtract — free GitHub repo to text converter for AI. Built by Nikandr Surkov.