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added few examples on pandas_pivot_table.ipynb #11

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added few examples on pandas_pivot_table.ipynb #11

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217 changes: 217 additions & 0 deletions Code/.ipynb_checkpoints/Convert normal Distribution-checkpoint.ipynb
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139 changes: 139 additions & 0 deletions Code/.ipynb_checkpoints/Pandas Apply-checkpoint.ipynb
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Original file line number Diff line number Diff line change
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Pandas Apply"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"# import pandas\n",
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"#Import dataset\n",
"loan = pd.read_csv('../Data/loan_train.csv', index_col = 'Loan_ID')"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"# Define function\n",
"def missing(x):\n",
" return sum(x.isnull())"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Missing values per column\n"
]
},
{
"data": {
"text/plain": [
"Gender 13\n",
"Married 3\n",
"Dependents 15\n",
"Education 0\n",
"Self_Employed 32\n",
"dtype: int64"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Apply per column\n",
"print('Missing values per column')\n",
"loan.apply(missing, axis = 0).head()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Missing values per row\n"
]
},
{
"data": {
"text/plain": [
"Loan_ID\n",
"LP001002 1\n",
"LP001003 0\n",
"LP001005 0\n",
"LP001006 0\n",
"LP001008 0\n",
"dtype: int64"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Apply per row\n",
"print('Missing values per row')\n",
"loan.apply(missing, axis = 1).head()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.7.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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