{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# Opérations\n",
    "\n",
    "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:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "   col1  col2 col3\n",
       "0     1   444  abc\n",
       "1     2   555  def\n",
       "2     3   666  ghi\n",
       "3     4   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>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>"
     },
     "metadata": {},
     "execution_count": 1
    }
   ],
   "source": [
    "import pandas as pd\n",
    "df = pd.DataFrame({'col1':[1,2,3,4],'col2':[444,555,666,444],'col3':['abc','def','ghi','xyz']})\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Informations sur les valeurs uniques"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "array([444, 555, 666], dtype=int64)"
      ]
     },
     "metadata": {},
     "execution_count": 2
    }
   ],
   "source": [
    "df['col2'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "metadata": {},
     "execution_count": 3
    }
   ],
   "source": [
    "df['col2'].nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "444    2\n",
       "555    1\n",
       "666    1\n",
       "Name: col2, dtype: int64"
      ]
     },
     "metadata": {},
     "execution_count": 4
    }
   ],
   "source": [
    "df['col2'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Sélection des données"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Sélection à partir d'un DataFrame en utilisant des critères \n",
    "# de plusieurs colonnes\n",
    "newdf = df[(df['col1']>2) & (df['col2']==444)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "   col1  col2 col3\n",
       "3     4   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>3</th>\n      <td>4</td>\n      <td>444</td>\n      <td>xyz</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "metadata": {},
     "execution_count": 6
    }
   ],
   "source": [
    "newdf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Appliquer des Fonctions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def times2(x):\n",
    "    return x*2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "0    2\n",
       "1    4\n",
       "2    6\n",
       "3    8\n",
       "Name: col1, dtype: int64"
      ]
     },
     "metadata": {},
     "execution_count": 8
    }
   ],
   "source": [
    "df['col1'].apply(times2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "0    3\n",
       "1    3\n",
       "2    3\n",
       "3    3\n",
       "Name: col3, dtype: int64"
      ]
     },
     "metadata": {},
     "execution_count": 9
    }
   ],
   "source": [
    "df['col3'].apply(len)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "10"
      ]
     },
     "metadata": {},
     "execution_count": 10
    }
   ],
   "source": [
    "df['col1'].sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Suppression définitive d'une colonne**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "del df['col1']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "   col2 col3\n",
       "0   444  abc\n",
       "1   555  def\n",
       "2   666  ghi\n",
       "3   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>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": 12
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Obtenir les noms des colonnes et des index :**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "Index(['col2', 'col3'], dtype='object')"
      ]
     },
     "metadata": {},
     "execution_count": 13
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "RangeIndex(start=0, stop=4, step=1)"
      ]
     },
     "metadata": {},
     "execution_count": 14
    }
   ],
   "source": [
    "df.index"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Trier un DataFrame :**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "   col2 col3\n",
       "0   444  abc\n",
       "1   555  def\n",
       "2   666  ghi\n",
       "3   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>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": 15
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "   col2 col3\n",
       "0   444  abc\n",
       "3   444  xyz\n",
       "1   555  def\n",
       "2   666  ghi"
      ],
      "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>"
     },
     "metadata": {},
     "execution_count": 16
    }
   ],
   "source": [
    "df.sort_values(by='col2') #inplace=False par défaut"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Recherche de valeurs nulles ou vérification des valeurs nulles**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "    col2   col3\n",
       "0  False  False\n",
       "1  False  False\n",
       "2  False  False\n",
       "3  False  False"
      ],
      "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>"
     },
     "metadata": {},
     "execution_count": 17
    }
   ],
   "source": [
    "df.isnull()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "   col2 col3\n",
       "0   444  abc\n",
       "1   555  def\n",
       "2   666  ghi\n",
       "3   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>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!"
   ]
  }
 ],
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   "name": "python3",
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