614 lines
20 KiB
Plaintext
614 lines
20 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"collapsed": true
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},
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"source": [
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"# Opérations\n",
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"\n",
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"Il y a beaucoup d'opérations avec pandas qui vous seront vraiment utiles, mais elles n'entraient dans aucune case. Montrons-les ici dans ce notebook:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [
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{
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"output_type": "execute_result",
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"data": {
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"text/plain": [
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" col1 col2 col3\n",
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"0 1 444 abc\n",
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"1 2 555 def\n",
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"2 3 666 ghi\n",
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"3 4 444 xyz"
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],
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"text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>col1</th>\n <th>col2</th>\n <th>col3</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>1</td>\n <td>444</td>\n <td>abc</td>\n </tr>\n <tr>\n <th>1</th>\n <td>2</td>\n <td>555</td>\n <td>def</td>\n </tr>\n <tr>\n <th>2</th>\n <td>3</td>\n <td>666</td>\n <td>ghi</td>\n </tr>\n <tr>\n <th>3</th>\n <td>4</td>\n <td>444</td>\n <td>xyz</td>\n </tr>\n </tbody>\n</table>\n</div>"
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},
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"metadata": {},
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"execution_count": 1
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}
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],
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"source": [
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"import pandas as pd\n",
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"df = pd.DataFrame({'col1':[1,2,3,4],'col2':[444,555,666,444],'col3':['abc','def','ghi','xyz']})\n",
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"df.head()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Informations sur les valeurs uniques"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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{
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"output_type": "execute_result",
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"data": {
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"text/plain": [
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"array([444, 555, 666], dtype=int64)"
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]
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},
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"metadata": {},
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"execution_count": 2
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}
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],
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"source": [
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"df['col2'].unique()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"output_type": "execute_result",
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"data": {
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"text/plain": [
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"3"
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]
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},
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"metadata": {},
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"execution_count": 3
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}
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],
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"source": [
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"df['col2'].nunique()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"output_type": "execute_result",
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"data": {
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"text/plain": [
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"444 2\n",
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"555 1\n",
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"666 1\n",
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"Name: col2, dtype: int64"
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]
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},
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"metadata": {},
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"execution_count": 4
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}
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],
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"source": [
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"df['col2'].value_counts()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Sélection des données"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Sélection à partir d'un DataFrame en utilisant des critères \n",
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"# de plusieurs colonnes\n",
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"newdf = df[(df['col1']>2) & (df['col2']==444)]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [
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{
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"output_type": "execute_result",
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"data": {
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"text/plain": [
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" col1 col2 col3\n",
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"3 4 444 xyz"
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],
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"text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>col1</th>\n <th>col2</th>\n <th>col3</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>3</th>\n <td>4</td>\n <td>444</td>\n <td>xyz</td>\n </tr>\n </tbody>\n</table>\n</div>"
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},
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"metadata": {},
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"execution_count": 6
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}
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],
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"source": [
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"newdf"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Appliquer des Fonctions"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"def times2(x):\n",
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" return x*2"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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"outputs": [
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{
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"output_type": "execute_result",
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"data": {
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"text/plain": [
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"0 2\n",
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"1 4\n",
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"2 6\n",
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"3 8\n",
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"Name: col1, dtype: int64"
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]
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},
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"metadata": {},
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"execution_count": 8
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}
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],
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"source": [
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"df['col1'].apply(times2)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {},
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"outputs": [
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{
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"output_type": "execute_result",
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"data": {
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"text/plain": [
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"0 3\n",
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"1 3\n",
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"2 3\n",
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"3 3\n",
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"Name: col3, dtype: int64"
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]
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},
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"metadata": {},
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"execution_count": 9
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}
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],
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"source": [
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"df['col3'].apply(len)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {},
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"outputs": [
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{
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"output_type": "execute_result",
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"data": {
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"text/plain": [
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"10"
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]
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},
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"metadata": {},
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"execution_count": 10
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}
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],
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"source": [
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"df['col1'].sum()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Suppression définitive d'une colonne**"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"metadata": {},
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"outputs": [],
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"source": [
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"del df['col1']"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"metadata": {},
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"outputs": [
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{
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"output_type": "execute_result",
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"data": {
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"text/plain": [
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" col2 col3\n",
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"0 444 abc\n",
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"1 555 def\n",
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"2 666 ghi\n",
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"3 444 xyz"
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],
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"text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>col2</th>\n <th>col3</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>444</td>\n <td>abc</td>\n </tr>\n <tr>\n <th>1</th>\n <td>555</td>\n <td>def</td>\n </tr>\n <tr>\n <th>2</th>\n <td>666</td>\n <td>ghi</td>\n </tr>\n <tr>\n <th>3</th>\n <td>444</td>\n <td>xyz</td>\n </tr>\n </tbody>\n</table>\n</div>"
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},
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"metadata": {},
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"execution_count": 12
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}
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],
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"source": [
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"df"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Obtenir les noms des colonnes et des index :**"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"metadata": {},
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"outputs": [
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{
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"output_type": "execute_result",
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"data": {
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"text/plain": [
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"Index(['col2', 'col3'], dtype='object')"
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]
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},
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"metadata": {},
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"execution_count": 13
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}
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],
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"source": [
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"df.columns"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"metadata": {},
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"outputs": [
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{
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"output_type": "execute_result",
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"data": {
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"text/plain": [
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"RangeIndex(start=0, stop=4, step=1)"
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]
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},
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"metadata": {},
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"execution_count": 14
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}
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],
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"source": [
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"df.index"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Trier un DataFrame :**"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"metadata": {},
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||
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"outputs": [
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{
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||
|
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"output_type": "execute_result",
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||
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"data": {
|
||
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"text/plain": [
|
||
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" col2 col3\n",
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"0 444 abc\n",
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"1 555 def\n",
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"2 666 ghi\n",
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|
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"3 444 xyz"
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|
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],
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||
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"text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>col2</th>\n <th>col3</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>444</td>\n <td>abc</td>\n </tr>\n <tr>\n <th>1</th>\n <td>555</td>\n <td>def</td>\n </tr>\n <tr>\n <th>2</th>\n <td>666</td>\n <td>ghi</td>\n </tr>\n <tr>\n <th>3</th>\n <td>444</td>\n <td>xyz</td>\n </tr>\n </tbody>\n</table>\n</div>"
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},
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||
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"metadata": {},
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||
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"execution_count": 15
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}
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||
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],
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"source": [
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"df"
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]
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},
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{
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||
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"cell_type": "code",
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||
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"execution_count": 16,
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||
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"metadata": {},
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||
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"outputs": [
|
||
|
|
{
|
||
|
|
"output_type": "execute_result",
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
" col2 col3\n",
|
||
|
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"0 444 abc\n",
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|
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"3 444 xyz\n",
|
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|
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"1 555 def\n",
|
||
|
|
"2 666 ghi"
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|
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],
|
||
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"text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>col2</th>\n <th>col3</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>444</td>\n <td>abc</td>\n </tr>\n <tr>\n <th>3</th>\n <td>444</td>\n <td>xyz</td>\n </tr>\n <tr>\n <th>1</th>\n <td>555</td>\n <td>def</td>\n </tr>\n <tr>\n <th>2</th>\n <td>666</td>\n <td>ghi</td>\n </tr>\n </tbody>\n</table>\n</div>"
|
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},
|
||
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"metadata": {},
|
||
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|
"execution_count": 16
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"df.sort_values(by='col2') #inplace=False par défaut"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
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|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"**Recherche de valeurs nulles ou vérification des valeurs nulles**"
|
||
|
|
]
|
||
|
|
},
|
||
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{
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||
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"execution_count": 17,
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"metadata": {},
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||
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"outputs": [
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{
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||
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"output_type": "execute_result",
|
||
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"data": {
|
||
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"text/plain": [
|
||
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" col2 col3\n",
|
||
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"0 False False\n",
|
||
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"1 False False\n",
|
||
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"2 False False\n",
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||
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"3 False False"
|
||
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],
|
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"text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>col2</th>\n <th>col3</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>False</td>\n <td>False</td>\n </tr>\n <tr>\n <th>1</th>\n <td>False</td>\n <td>False</td>\n </tr>\n <tr>\n <th>2</th>\n <td>False</td>\n <td>False</td>\n </tr>\n <tr>\n <th>3</th>\n <td>False</td>\n <td>False</td>\n </tr>\n </tbody>\n</table>\n</div>"
|
||
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|
},
|
||
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|
"metadata": {},
|
||
|
|
"execution_count": 17
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"df.isnull()"
|
||
|
|
]
|
||
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|
},
|
||
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|
{
|
||
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"cell_type": "code",
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||
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"execution_count": 18,
|
||
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"metadata": {},
|
||
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"outputs": [
|
||
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|
{
|
||
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"output_type": "execute_result",
|
||
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"data": {
|
||
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"text/plain": [
|
||
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" col2 col3\n",
|
||
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|
"0 444 abc\n",
|
||
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|
"1 555 def\n",
|
||
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"2 666 ghi\n",
|
||
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|
"3 444 xyz"
|
||
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|
],
|
||
|
|
"text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>col2</th>\n <th>col3</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>444</td>\n <td>abc</td>\n </tr>\n <tr>\n <th>1</th>\n <td>555</td>\n <td>def</td>\n </tr>\n <tr>\n <th>2</th>\n <td>666</td>\n <td>ghi</td>\n </tr>\n <tr>\n <th>3</th>\n <td>444</td>\n <td>xyz</td>\n </tr>\n </tbody>\n</table>\n</div>"
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"execution_count": 18
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"# Supprimer les lignes contenant des valeurs NaN\n",
|
||
|
|
"df.dropna()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"**Remplir les valeurs NaN avec autre chose :**"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 19,
|
||
|
|
"metadata": {
|
||
|
|
"collapsed": true
|
||
|
|
},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"import numpy as np"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 20,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"output_type": "execute_result",
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
" col1 col2 col3\n",
|
||
|
|
"0 1.0 NaN abc\n",
|
||
|
|
"1 2.0 555.0 def\n",
|
||
|
|
"2 3.0 666.0 ghi\n",
|
||
|
|
"3 NaN 444.0 xyz"
|
||
|
|
],
|
||
|
|
"text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>col1</th>\n <th>col2</th>\n <th>col3</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>1.0</td>\n <td>NaN</td>\n <td>abc</td>\n </tr>\n <tr>\n <th>1</th>\n <td>2.0</td>\n <td>555.0</td>\n <td>def</td>\n </tr>\n <tr>\n <th>2</th>\n <td>3.0</td>\n <td>666.0</td>\n <td>ghi</td>\n </tr>\n <tr>\n <th>3</th>\n <td>NaN</td>\n <td>444.0</td>\n <td>xyz</td>\n </tr>\n </tbody>\n</table>\n</div>"
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"execution_count": 20
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"df = pd.DataFrame({'col1':[1,2,3,np.nan],\n",
|
||
|
|
" 'col2':[np.nan,555,666,444],\n",
|
||
|
|
" 'col3':['abc','def','ghi','xyz']})\n",
|
||
|
|
"df.head()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 21,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"output_type": "execute_result",
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
" col1 col2 col3\n",
|
||
|
|
"0 1 FILL abc\n",
|
||
|
|
"1 2 555 def\n",
|
||
|
|
"2 3 666 ghi\n",
|
||
|
|
"3 FILL 444 xyz"
|
||
|
|
],
|
||
|
|
"text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>col1</th>\n <th>col2</th>\n <th>col3</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>1</td>\n <td>FILL</td>\n <td>abc</td>\n </tr>\n <tr>\n <th>1</th>\n <td>2</td>\n <td>555</td>\n <td>def</td>\n </tr>\n <tr>\n <th>2</th>\n <td>3</td>\n <td>666</td>\n <td>ghi</td>\n </tr>\n <tr>\n <th>3</th>\n <td>FILL</td>\n <td>444</td>\n <td>xyz</td>\n </tr>\n </tbody>\n</table>\n</div>"
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"execution_count": 21
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"df.fillna('FILL')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 22,
|
||
|
|
"metadata": {
|
||
|
|
"collapsed": true
|
||
|
|
},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"data = {'A':['foo','foo','foo','bar','bar','bar'],\n",
|
||
|
|
" 'B':['one','one','two','two','one','one'],\n",
|
||
|
|
" 'C':['x','y','x','y','x','y'],\n",
|
||
|
|
" 'D':[1,3,2,5,4,1]}\n",
|
||
|
|
"\n",
|
||
|
|
"df = pd.DataFrame(data)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 23,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"output_type": "execute_result",
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
" A B C D\n",
|
||
|
|
"0 foo one x 1\n",
|
||
|
|
"1 foo one y 3\n",
|
||
|
|
"2 foo two x 2\n",
|
||
|
|
"3 bar two y 5\n",
|
||
|
|
"4 bar one x 4\n",
|
||
|
|
"5 bar one y 1"
|
||
|
|
],
|
||
|
|
"text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>A</th>\n <th>B</th>\n <th>C</th>\n <th>D</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>foo</td>\n <td>one</td>\n <td>x</td>\n <td>1</td>\n </tr>\n <tr>\n <th>1</th>\n <td>foo</td>\n <td>one</td>\n <td>y</td>\n <td>3</td>\n </tr>\n <tr>\n <th>2</th>\n <td>foo</td>\n <td>two</td>\n <td>x</td>\n <td>2</td>\n </tr>\n <tr>\n <th>3</th>\n <td>bar</td>\n <td>two</td>\n <td>y</td>\n <td>5</td>\n </tr>\n <tr>\n <th>4</th>\n <td>bar</td>\n <td>one</td>\n <td>x</td>\n <td>4</td>\n </tr>\n <tr>\n <th>5</th>\n <td>bar</td>\n <td>one</td>\n <td>y</td>\n <td>1</td>\n </tr>\n </tbody>\n</table>\n</div>"
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"execution_count": 23
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"df"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 24,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"output_type": "execute_result",
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"C x y\n",
|
||
|
|
"A B \n",
|
||
|
|
"bar one 4.0 1.0\n",
|
||
|
|
" two NaN 5.0\n",
|
||
|
|
"foo one 1.0 3.0\n",
|
||
|
|
" two 2.0 NaN"
|
||
|
|
],
|
||
|
|
"text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>C</th>\n <th>x</th>\n <th>y</th>\n </tr>\n <tr>\n <th>A</th>\n <th>B</th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th rowspan=\"2\" valign=\"top\">bar</th>\n <th>one</th>\n <td>4.0</td>\n <td>1.0</td>\n </tr>\n <tr>\n <th>two</th>\n <td>NaN</td>\n <td>5.0</td>\n </tr>\n <tr>\n <th rowspan=\"2\" valign=\"top\">foo</th>\n <th>one</th>\n <td>1.0</td>\n <td>3.0</td>\n </tr>\n <tr>\n <th>two</th>\n <td>2.0</td>\n <td>NaN</td>\n </tr>\n </tbody>\n</table>\n</div>"
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"execution_count": 24
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"df.pivot_table(values='D',index=['A', 'B'],columns=['C'])"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"# Bon travail!"
|
||
|
|
]
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"metadata": {
|
||
|
|
"kernelspec": {
|
||
|
|
"name": "python3",
|
||
|
|
"display_name": "Python 3.7.9 64-bit ('pyfinance': conda)",
|
||
|
|
"metadata": {
|
||
|
|
"interpreter": {
|
||
|
|
"hash": "e89404a230d8800c54ad520c7b67d1bd9bb833a07b37dd3e521a178a3dc34904"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"language_info": {
|
||
|
|
"codemirror_mode": {
|
||
|
|
"name": "ipython",
|
||
|
|
"version": 3
|
||
|
|
},
|
||
|
|
"file_extension": ".py",
|
||
|
|
"mimetype": "text/x-python",
|
||
|
|
"name": "python",
|
||
|
|
"nbconvert_exporter": "python",
|
||
|
|
"pygments_lexer": "ipython3",
|
||
|
|
"version": "3.7.9-final"
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"nbformat": 4,
|
||
|
|
"nbformat_minor": 1
|
||
|
|
}
|