Tutoriel_pandas_en_francais.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introduction à pandas\n",
    "### Ou comment devenir un ninja des données\n",
    "-----"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![Logo de pandas](https://pandas.pydata.org/docs/_static/pandas.svg)\n",
    "Tutoriel sur [pandas](http://pandas.pydata.org/) ([documentation](http://pandas.pydata.org/pandas-docs/stable/index.html)), bibliothèque python permettant d'analyser et d'interroger rapidement des données; particulièrement utile lorsqu'on a des fichiers volumineux qu'un tableur comme *Excel*, *Calc* ou *Google Sheets* a de la difficulté à avaler. Contenu préparé pour le [EDM5240](https://www.gitbook.com/book/jhroy/edm5240-h2017/details), cours de journalisme informatique de l'[Université du Québec à Montréal](http://uqam.ca/) (mars 2017; mis à jour en mars 2019), plus récemment changé pour [EDM4466 (Journalisme de données II)](https://journalisme-uqam.gitbook.io/edm4466-h2020/).<br>\n",
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Le premier bloc de code, ci-dessous, ressemble au début des scripts que vous avez réalisés jusqu'à maintenant. Il s'agit d'importer les modules dont nous aurons besoin. On leur donne même un surnom. C'est ainsi que **```pandas```** devient **```pd```**, par exemple.\n",
    "<br>\n",
    "La ligne **```%matplotlib inline```** sert simplement à demander à notre carnet d'afficher des graphiques dans la page lorsqu'on souhaitera en créer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib as mp"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On peut changer les options d'affichage de pandas avec la fonction ```.set_option```.<br>\n",
    "Ici, on demande que l'affichage des nombres ne soit **pas** en notation scientifique, comme il l'est par défaut."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.options.display.float_format = \"{:.2f}\".format"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ci-dessous, on lit [deux des fichiers que je vous ai donnés](http://bit.ly/jhroypandas).<br>\n",
    "On les mets chacun dans une variable. J'ai choisi de baptiser l'une de ces variables ```md``` puisque le fichier indiqué comprend des données sur l'ensemble des membres du Collège des médecins, et l'autre ```mil``` puisque le fichier indiqué contient, pour sa part, des données sur les contrats octroyés par le ministère de la Défense nationale.<br>\n",
    "Pour pandas, cette structure de données, qui consiste en un tableau à deux dimensions, est appelé un _**dataframe**_.<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "md = pd.read_csv(\"cmq.csv\")\n",
    "mil = pd.read_csv(\"militaires.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pour connaître le type des variables que contient notre tableau, on peut utiliser la fonction ```.dtypes```.<p>\n",
    "Dans pandas, les principaux types de variables sont&nbsp;:\n",
    "\n",
    "* ```int``` -> nombres entiers\n",
    "* ```float``` -> nombres décimaux\n",
    "* ```object``` -> chaînes de caractères\n",
    "* ```datetime``` -> dates\n",
    "* ```bool``` -> vrai ou faux\n",
    "\n",
    "Ces types sont parfois suivis d'un nombre qui indique la taille, en caractères, maximale des variables de ce type."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "num                object\n",
       "annee               int64\n",
       "prenom             object\n",
       "nom                object\n",
       "genre              object\n",
       "specialite1        object\n",
       "specialite2        object\n",
       "specialite3        object\n",
       "statut             object\n",
       "dateChangStatut    object\n",
       "typePermis         object\n",
       "ville              object\n",
       "prov               object\n",
       "pays               object\n",
       "dtype: object"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "md.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "annee            int64\n",
       "trimestre        int64\n",
       "date            object\n",
       "fournisseur     object\n",
       "description     object\n",
       "montant        float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mil.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exploration simple de nos données\n",
    "-----"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pour afficher simplement le contenu de notre variable, il n'est pas nécessaire d'écrire ```print(md)```.<br>Écrire le nom de la variable suffit.<br>\n",
    "Cela produit un immense tableau avec les 30 premières et les 30 dernières lignes de notre fichier."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
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       "      <th></th>\n",
       "      <th>num</th>\n",
       "      <th>annee</th>\n",
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       "      <th>specialite1</th>\n",
       "      <th>specialite2</th>\n",
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       "      <th>pays</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>#30001</td>\n",
       "      <td>1930</td>\n",
       "      <td>Lucien</td>\n",
       "      <td>Amyot</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>1981-12-29</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Montréal</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>#30002</td>\n",
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       "      <td>Wilfrid</td>\n",
       "      <td>Audet</td>\n",
       "      <td>M</td>\n",
       "      <td>Inconnue</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Démission</td>\n",
       "      <td>1987-10-01</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Alma</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>#30003</td>\n",
       "      <td>1930</td>\n",
       "      <td>A. T.</td>\n",
       "      <td>Batshaw</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>1983-11-11</td>\n",
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       "      <td>Montréal</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>#30005</td>\n",
       "      <td>1930</td>\n",
       "      <td>Maurice</td>\n",
       "      <td>Beaudry</td>\n",
       "      <td>M</td>\n",
       "      <td>Dermatologie</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>1989-02-12</td>\n",
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       "      <td>Québec</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>#30006</td>\n",
       "      <td>1930</td>\n",
       "      <td>P. E.</td>\n",
       "      <td>Belleau</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine interne</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>1986-05-31</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35104</th>\n",
       "      <td>#16893</td>\n",
       "      <td>2016</td>\n",
       "      <td>Sébastien</td>\n",
       "      <td>David</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35105</th>\n",
       "      <td>#16894</td>\n",
       "      <td>2016</td>\n",
       "      <td>Guillaume Patrick Jean</td>\n",
       "      <td>Berthier</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Restrictif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35106</th>\n",
       "      <td>#16895</td>\n",
       "      <td>2016</td>\n",
       "      <td>Miriam</td>\n",
       "      <td>Banoub</td>\n",
       "      <td>F</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
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       "    <tr>\n",
       "      <th>35107</th>\n",
       "      <td>#16896</td>\n",
       "      <td>2016</td>\n",
       "      <td>Anne-Sophie</td>\n",
       "      <td>Lemay</td>\n",
       "      <td>F</td>\n",
       "      <td>Hématologie</td>\n",
       "      <td>Oncologie médicale</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35108</th>\n",
       "      <td>#16897</td>\n",
       "      <td>2016</td>\n",
       "      <td>Mohamed Ali</td>\n",
       "      <td>Abla</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>35109 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          num  annee                  prenom       nom genre  \\\n",
       "0      #30001   1930                  Lucien     Amyot     M   \n",
       "1      #30002   1930                 Wilfrid     Audet     M   \n",
       "2      #30003   1930                   A. T.   Batshaw     M   \n",
       "3      #30005   1930                 Maurice   Beaudry     M   \n",
       "4      #30006   1930                   P. E.   Belleau     M   \n",
       "...       ...    ...                     ...       ...   ...   \n",
       "35104  #16893   2016               Sébastien     David     M   \n",
       "35105  #16894   2016  Guillaume Patrick Jean  Berthier     M   \n",
       "35106  #16895   2016                  Miriam    Banoub     F   \n",
       "35107  #16896   2016             Anne-Sophie     Lemay     F   \n",
       "35108  #16897   2016             Mohamed Ali      Abla     M   \n",
       "\n",
       "               specialite1         specialite2 specialite3  \\\n",
       "0      Médecine de famille                 NaN         NaN   \n",
       "1                 Inconnue                 NaN         NaN   \n",
       "2      Médecine de famille                 NaN         NaN   \n",
       "3             Dermatologie                 NaN         NaN   \n",
       "4         Médecine interne                 NaN         NaN   \n",
       "...                    ...                 ...         ...   \n",
       "35104  Médecine de famille                 NaN         NaN   \n",
       "35105  Médecine de famille                 NaN         NaN   \n",
       "35106  Médecine de famille                 NaN         NaN   \n",
       "35107          Hématologie  Oncologie médicale         NaN   \n",
       "35108  Médecine de famille                 NaN         NaN   \n",
       "\n",
       "                   statut dateChangStatut  typePermis     ville    prov  \\\n",
       "0      Retrait pour décès      1981-12-29    Régulier  Montréal  Québec   \n",
       "1               Démission      1987-10-01    Régulier      Alma  Québec   \n",
       "2      Retrait pour décès      1983-11-11    Régulier  Montréal  Québec   \n",
       "3      Retrait pour décès      1989-02-12    Régulier    Québec  Québec   \n",
       "4      Retrait pour décès      1986-05-31    Régulier    Québec  Québec   \n",
       "...                   ...             ...         ...       ...     ...   \n",
       "35104     Inscrit - Actif             NaN    Régulier       NaN  Québec   \n",
       "35105     Inscrit - Actif             NaN  Restrictif       NaN  Québec   \n",
       "35106     Inscrit - Actif             NaN    Régulier       NaN  Québec   \n",
       "35107     Inscrit - Actif             NaN    Régulier       NaN  Québec   \n",
       "35108     Inscrit - Actif             NaN    Régulier       NaN  Québec   \n",
       "\n",
       "         pays  \n",
       "0      Canada  \n",
       "1      Canada  \n",
       "2      Canada  \n",
       "3      Canada  \n",
       "4      Canada  \n",
       "...       ...  \n",
       "35104  Canada  \n",
       "35105  Canada  \n",
       "35106  Canada  \n",
       "35107  Canada  \n",
       "35108  Canada  \n",
       "\n",
       "[35109 rows x 14 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "md"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pour avoir un aperçu des dimensions de de votre tableau, utilisez plutôt la fonction ```.shape```."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(35109, 14)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "md.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pour consulter les premières ou les dernières lignes de votre tableau, vous pouvez vous servir de fonctions qui ressemblent à ce qu'on a vu dans [Unix](http://bit.ly/jhroyunix), au début de la session, ```.head()``` et ```.tail()```."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
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       "      <td>#30001</td>\n",
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       "      <td>Lucien</td>\n",
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       "      <td>1930</td>\n",
       "      <td>Wilfrid</td>\n",
       "      <td>Audet</td>\n",
       "      <td>M</td>\n",
       "      <td>Inconnue</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>#30003</td>\n",
       "      <td>1930</td>\n",
       "      <td>A. T.</td>\n",
       "      <td>Batshaw</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>1983-11-11</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Montréal</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>#30005</td>\n",
       "      <td>1930</td>\n",
       "      <td>Maurice</td>\n",
       "      <td>Beaudry</td>\n",
       "      <td>M</td>\n",
       "      <td>Dermatologie</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>1989-02-12</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>#30006</td>\n",
       "      <td>1930</td>\n",
       "      <td>P. E.</td>\n",
       "      <td>Belleau</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine interne</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>1986-05-31</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      num  annee   prenom      nom genre          specialite1 specialite2  \\\n",
       "0  #30001   1930   Lucien    Amyot     M  Médecine de famille         NaN   \n",
       "1  #30002   1930  Wilfrid    Audet     M             Inconnue         NaN   \n",
       "2  #30003   1930    A. T.  Batshaw     M  Médecine de famille         NaN   \n",
       "3  #30005   1930  Maurice  Beaudry     M         Dermatologie         NaN   \n",
       "4  #30006   1930    P. E.  Belleau     M     Médecine interne         NaN   \n",
       "\n",
       "  specialite3              statut dateChangStatut typePermis     ville  \\\n",
       "0         NaN  Retrait pour décès      1981-12-29   Régulier  Montréal   \n",
       "1         NaN           Démission      1987-10-01   Régulier      Alma   \n",
       "2         NaN  Retrait pour décès      1983-11-11   Régulier  Montréal   \n",
       "3         NaN  Retrait pour décès      1989-02-12   Régulier    Québec   \n",
       "4         NaN  Retrait pour décès      1986-05-31   Régulier    Québec   \n",
       "\n",
       "     prov    pays  \n",
       "0  Québec  Canada  \n",
       "1  Québec  Canada  \n",
       "2  Québec  Canada  \n",
       "3  Québec  Canada  \n",
       "4  Québec  Canada  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "md.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>annee</th>\n",
       "      <th>trimestre</th>\n",
       "      <th>date</th>\n",
       "      <th>fournisseur</th>\n",
       "      <th>description</th>\n",
       "      <th>montant</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>165947</th>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>30-12-2016</td>\n",
       "      <td>NB Harrison Inc</td>\n",
       "      <td>Opérations de parachutage</td>\n",
       "      <td>30700.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165948</th>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>30-12-2016</td>\n",
       "      <td>Clint Clawson</td>\n",
       "      <td>Opérations de parachutage</td>\n",
       "      <td>41250.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165949</th>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>30-12-2016</td>\n",
       "      <td>The Goodyear Tire &amp; Rubber Company</td>\n",
       "      <td>Pneumatiques et chambres à air d'aéronefs</td>\n",
       "      <td>282000.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165950</th>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>30-12-2016</td>\n",
       "      <td>Imperial Oil Limited</td>\n",
       "      <td>Combustible d'aviation</td>\n",
       "      <td>315315.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165951</th>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "      <td>30-12-2016</td>\n",
       "      <td>S.M.I. Support Measures Inc.</td>\n",
       "      <td>Antennes, guides d'ondes et équipement connexe...</td>\n",
       "      <td>630000.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        annee  trimestre        date                         fournisseur  \\\n",
       "165947   2016          3  30-12-2016                     NB Harrison Inc   \n",
       "165948   2016          3  30-12-2016                       Clint Clawson   \n",
       "165949   2016          3  30-12-2016  The Goodyear Tire & Rubber Company   \n",
       "165950   2016          3  30-12-2016                Imperial Oil Limited   \n",
       "165951   2016          3  30-12-2016        S.M.I. Support Measures Inc.   \n",
       "\n",
       "                                              description   montant  \n",
       "165947                          Opérations de parachutage  30700.00  \n",
       "165948                          Opérations de parachutage  41250.00  \n",
       "165949          Pneumatiques et chambres à air d'aéronefs 282000.00  \n",
       "165950                             Combustible d'aviation 315315.20  \n",
       "165951  Antennes, guides d'ondes et équipement connexe... 630000.00  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mil.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pour consulter un intervalle précis de lignes, vous pouvez vous servir des crochets. Vous reconnaissez cette syntaxe puisque pandas, c'est du python!<br>\n",
    "C'est ainsi que, ci-dessous, je demande à afficher les lignes 1000 à 1009 de mon fichier (comme en python, la limite supérieure est exclue de mon intervalle)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
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       "        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>num</th>\n",
       "      <th>annee</th>\n",
       "      <th>prenom</th>\n",
       "      <th>nom</th>\n",
       "      <th>genre</th>\n",
       "      <th>specialite1</th>\n",
       "      <th>specialite2</th>\n",
       "      <th>specialite3</th>\n",
       "      <th>statut</th>\n",
       "      <th>dateChangStatut</th>\n",
       "      <th>typePermis</th>\n",
       "      <th>ville</th>\n",
       "      <th>prov</th>\n",
       "      <th>pays</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1000</th>\n",
       "      <td>#44048</td>\n",
       "      <td>1944</td>\n",
       "      <td>Paul H.</td>\n",
       "      <td>Niloff</td>\n",
       "      <td>M</td>\n",
       "      <td>Chirurgie générale</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>1992-02-12</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Montréal</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1001</th>\n",
       "      <td>#44049</td>\n",
       "      <td>1944</td>\n",
       "      <td>Walter C.</td>\n",
       "      <td>Lloyd-Smith</td>\n",
       "      <td>M</td>\n",
       "      <td>Chirurgie générale</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Démission</td>\n",
       "      <td>1999-07-01</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Sillery</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1002</th>\n",
       "      <td>#44050</td>\n",
       "      <td>1944</td>\n",
       "      <td>Jean-Benoit</td>\n",
       "      <td>Bechard</td>\n",
       "      <td>M</td>\n",
       "      <td>Chirurgie générale</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>2008-05-02</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Saint-Lambert</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1003</th>\n",
       "      <td>#44051</td>\n",
       "      <td>1944</td>\n",
       "      <td>H. F.</td>\n",
       "      <td>Brickman</td>\n",
       "      <td>F</td>\n",
       "      <td>Pédiatrie</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Radié pour non-paiement de cotisation</td>\n",
       "      <td>1964-08-31</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inconnu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1004</th>\n",
       "      <td>#44052</td>\n",
       "      <td>1944</td>\n",
       "      <td>E. R.</td>\n",
       "      <td>Mackenzie-Harpur</td>\n",
       "      <td>F</td>\n",
       "      <td>Biochimie médicale</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>2001-02-18</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Montréal</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1005</th>\n",
       "      <td>#44054</td>\n",
       "      <td>1944</td>\n",
       "      <td>Claude</td>\n",
       "      <td>Dubé</td>\n",
       "      <td>M</td>\n",
       "      <td>Ophtalmologie</td>\n",
       "      <td>Oto-rhino-laryngologie / chirurgie cervico-fac...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>1982-09-22</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Montréal</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1006</th>\n",
       "      <td>#44055</td>\n",
       "      <td>1944</td>\n",
       "      <td>Alban</td>\n",
       "      <td>Damphousse</td>\n",
       "      <td>M</td>\n",
       "      <td>Chirurgie générale</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>1981-11-03</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Montréal</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1007</th>\n",
       "      <td>#44056</td>\n",
       "      <td>1944</td>\n",
       "      <td>James L.</td>\n",
       "      <td>Mc Callum</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine interne</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>1999-04-12</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Bellefeuille</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1008</th>\n",
       "      <td>#44057</td>\n",
       "      <td>1944</td>\n",
       "      <td>Samuel A.</td>\n",
       "      <td>Macdonald</td>\n",
       "      <td>M</td>\n",
       "      <td>Urologie</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>1995-04-02</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Saint-Laurent</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1009</th>\n",
       "      <td>#44061</td>\n",
       "      <td>1944</td>\n",
       "      <td>Léon</td>\n",
       "      <td>Leclerc</td>\n",
       "      <td>M</td>\n",
       "      <td>Inconnue</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Démission</td>\n",
       "      <td>1987-09-30</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Sillery</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         num  annee       prenom               nom genre         specialite1  \\\n",
       "1000  #44048   1944      Paul H.            Niloff     M  Chirurgie générale   \n",
       "1001  #44049   1944    Walter C.       Lloyd-Smith     M  Chirurgie générale   \n",
       "1002  #44050   1944  Jean-Benoit           Bechard     M  Chirurgie générale   \n",
       "1003  #44051   1944        H. F.          Brickman     F           Pédiatrie   \n",
       "1004  #44052   1944        E. R.  Mackenzie-Harpur     F  Biochimie médicale   \n",
       "1005  #44054   1944       Claude              Dubé     M       Ophtalmologie   \n",
       "1006  #44055   1944        Alban        Damphousse     M  Chirurgie générale   \n",
       "1007  #44056   1944     James L.         Mc Callum     M    Médecine interne   \n",
       "1008  #44057   1944    Samuel A.         Macdonald     M            Urologie   \n",
       "1009  #44061   1944         Léon           Leclerc     M            Inconnue   \n",
       "\n",
       "                                            specialite2 specialite3  \\\n",
       "1000                                                NaN         NaN   \n",
       "1001                                                NaN         NaN   \n",
       "1002                                                NaN         NaN   \n",
       "1003                                                NaN         NaN   \n",
       "1004                                                NaN         NaN   \n",
       "1005  Oto-rhino-laryngologie / chirurgie cervico-fac...         NaN   \n",
       "1006                                                NaN         NaN   \n",
       "1007                                                NaN         NaN   \n",
       "1008                                                NaN         NaN   \n",
       "1009                                                NaN         NaN   \n",
       "\n",
       "                                     statut dateChangStatut typePermis  \\\n",
       "1000                     Retrait pour décès      1992-02-12   Régulier   \n",
       "1001                              Démission      1999-07-01   Régulier   \n",
       "1002                     Retrait pour décès      2008-05-02   Régulier   \n",
       "1003  Radié pour non-paiement de cotisation      1964-08-31   Régulier   \n",
       "1004                     Retrait pour décès      2001-02-18   Régulier   \n",
       "1005                     Retrait pour décès      1982-09-22   Régulier   \n",
       "1006                     Retrait pour décès      1981-11-03   Régulier   \n",
       "1007                     Retrait pour décès      1999-04-12   Régulier   \n",
       "1008                     Retrait pour décès      1995-04-02   Régulier   \n",
       "1009                              Démission      1987-09-30   Régulier   \n",
       "\n",
       "              ville    prov     pays  \n",
       "1000       Montréal  Québec   Canada  \n",
       "1001        Sillery  Québec   Canada  \n",
       "1002  Saint-Lambert  Québec   Canada  \n",
       "1003            NaN     NaN  Inconnu  \n",
       "1004       Montréal  Québec   Canada  \n",
       "1005       Montréal  Québec   Canada  \n",
       "1006       Montréal  Québec   Canada  \n",
       "1007   Bellefeuille  Québec   Canada  \n",
       "1008  Saint-Laurent  Québec   Canada  \n",
       "1009        Sillery  Québec   Canada  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "md[1000:1010]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pour faire afficher un nombre limité de colonnes, on peut ajouter une liste du nom des colonnes qu'on souhaite.<br>\n",
    "Il faut cependant le faire avec la fonction ```.loc```."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>nom</th>\n",
       "      <th>prenom</th>\n",
       "      <th>num</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7000</th>\n",
       "      <td>Behroozi</td>\n",
       "      <td>Cyrus</td>\n",
       "      <td>#67360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7001</th>\n",
       "      <td>Diez</td>\n",
       "      <td>Garcia Pablo</td>\n",
       "      <td>#67361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7002</th>\n",
       "      <td>Coles</td>\n",
       "      <td>Duval</td>\n",
       "      <td>#67362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7003</th>\n",
       "      <td>Pritchard</td>\n",
       "      <td>Élizabeth</td>\n",
       "      <td>#67363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7004</th>\n",
       "      <td>Braithwaite</td>\n",
       "      <td>Desmond</td>\n",
       "      <td>#67364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7005</th>\n",
       "      <td>Freeman</td>\n",
       "      <td>Lincoln C.</td>\n",
       "      <td>#67365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7006</th>\n",
       "      <td>Murat</td>\n",
       "      <td>Paul</td>\n",
       "      <td>#67366</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7007</th>\n",
       "      <td>Khoury-Haddad</td>\n",
       "      <td>Albert</td>\n",
       "      <td>#67367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7008</th>\n",
       "      <td>Clecner</td>\n",
       "      <td>Bya</td>\n",
       "      <td>#67368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7009</th>\n",
       "      <td>Papapetropoulos</td>\n",
       "      <td>D.</td>\n",
       "      <td>#67369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7010</th>\n",
       "      <td>Gabriel</td>\n",
       "      <td>Chafik N.</td>\n",
       "      <td>#67370</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  nom        prenom     num\n",
       "7000         Behroozi         Cyrus  #67360\n",
       "7001             Diez  Garcia Pablo  #67361\n",
       "7002            Coles         Duval  #67362\n",
       "7003        Pritchard     Élizabeth  #67363\n",
       "7004      Braithwaite       Desmond  #67364\n",
       "7005          Freeman    Lincoln C.  #67365\n",
       "7006            Murat          Paul  #67366\n",
       "7007    Khoury-Haddad        Albert  #67367\n",
       "7008          Clecner           Bya  #67368\n",
       "7009  Papapetropoulos            D.  #67369\n",
       "7010          Gabriel     Chafik N.  #67370"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "md.loc[7000:7010,[\"nom\",\"prenom\",\"num\"]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On peut aussi utiliser, au lieu du nom des colonnes, le numéro d'index des colonnes qu'on souhaite afficher.<br>\n",
    "Il faut alors utiliser la fonction ```.iloc```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>fournisseur</th>\n",
       "      <th>description</th>\n",
       "      <th>montant</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>100000</th>\n",
       "      <td>MLS USA Corporation</td>\n",
       "      <td>Articles divers (Comprend seulement ces articl...</td>\n",
       "      <td>158732.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100001</th>\n",
       "      <td>Turtle Island Staffing</td>\n",
       "      <td>Services d'aide temporaire, soutien administra...</td>\n",
       "      <td>46782.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100002</th>\n",
       "      <td>IMPERIAL OIL</td>\n",
       "      <td>MAZOUT</td>\n",
       "      <td>14329.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100003</th>\n",
       "      <td>IMPERIAL OIL</td>\n",
       "      <td>MAZOUT</td>\n",
       "      <td>14663.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100004</th>\n",
       "      <td>Valley Refrigeration Limited</td>\n",
       "      <td>Travaux professionnels spéciaux de construction</td>\n",
       "      <td>73989.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100005</th>\n",
       "      <td>Centaur Products inc.</td>\n",
       "      <td>Travaux de construction pour édifices</td>\n",
       "      <td>74294.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100006</th>\n",
       "      <td>Tayco Paving Company</td>\n",
       "      <td>Travaux de construction - génie civil</td>\n",
       "      <td>195725.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100007</th>\n",
       "      <td>MCM Architects Inc.</td>\n",
       "      <td>Services d'architecture et d'ingénierie - Cons...</td>\n",
       "      <td>71851.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100008</th>\n",
       "      <td>Shamrock Building Services Ltd</td>\n",
       "      <td>Travaux de construction pour édifices</td>\n",
       "      <td>168400.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100009</th>\n",
       "      <td>SNC-Lavalin Environment Inc.  (Victoria)</td>\n",
       "      <td>Services environnementaux</td>\n",
       "      <td>71765.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100010</th>\n",
       "      <td>LVM Inc.   (Montreal)</td>\n",
       "      <td>Services environnementaux</td>\n",
       "      <td>13731.94</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     fournisseur  \\\n",
       "100000                       MLS USA Corporation   \n",
       "100001                    Turtle Island Staffing   \n",
       "100002                              IMPERIAL OIL   \n",
       "100003                              IMPERIAL OIL   \n",
       "100004              Valley Refrigeration Limited   \n",
       "100005                     Centaur Products inc.   \n",
       "100006                      Tayco Paving Company   \n",
       "100007                       MCM Architects Inc.   \n",
       "100008            Shamrock Building Services Ltd   \n",
       "100009  SNC-Lavalin Environment Inc.  (Victoria)   \n",
       "100010                     LVM Inc.   (Montreal)   \n",
       "\n",
       "                                              description   montant  \n",
       "100000  Articles divers (Comprend seulement ces articl... 158732.13  \n",
       "100001  Services d'aide temporaire, soutien administra...  46782.00  \n",
       "100002                                             MAZOUT  14329.30  \n",
       "100003                                             MAZOUT  14663.55  \n",
       "100004    Travaux professionnels spéciaux de construction  73989.47  \n",
       "100005              Travaux de construction pour édifices  74294.00  \n",
       "100006              Travaux de construction - génie civil 195725.00  \n",
       "100007  Services d'architecture et d'ingénierie - Cons...  71851.00  \n",
       "100008              Travaux de construction pour édifices 168400.00  \n",
       "100009                          Services environnementaux  71765.00  \n",
       "100010                          Services environnementaux  13731.94  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mil.iloc[100000:100011,3:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Si on souhaite compter combien il y a d'éléments dans chacune de nos colonnes, on peut utiliser la fonction ```.count()```.<br>\n",
    "Employons-la avec nos deux fichiers.\n",
    "\n",
    "On constate qu'avec les médecins, il nous manque parfois de l'information. Cela peut faire du sens, comme pour les colonnes ```specialite2``` et ```specialite3```, puisque ce ne sont pas tous les médecins qui ont deux ou trois spécialités. Mais cela peut aussi vouloir dire qu'il y a des données manquantes. Ainsi, on n'a pas la ville dans laquelle excercent tous les médecins."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "num                35109\n",
       "annee              35109\n",
       "prenom             35108\n",
       "nom                35109\n",
       "genre              35109\n",
       "specialite1        35109\n",
       "specialite2         3467\n",
       "specialite3          224\n",
       "statut             35109\n",
       "dateChangStatut    11412\n",
       "typePermis         35109\n",
       "ville              33715\n",
       "prov               34133\n",
       "pays               35109\n",
       "dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "md.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "annee          165952\n",
       "trimestre      165952\n",
       "date           165952\n",
       "fournisseur    165952\n",
       "description    165945\n",
       "montant        165952\n",
       "dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mil.count()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Opérations sur les colonnes\n",
    "-----"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Il est souvent utile de connaître le nom des colonnes de notre fichier.<br>\n",
    "Pour ce faire, entrez la fonction ```.columns```."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['num', 'annee', 'prenom', 'nom', 'genre', 'specialite1', 'specialite2',\n",
       "       'specialite3', 'statut', 'dateChangStatut', 'typePermis', 'ville',\n",
       "       'prov', 'pays'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "md.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Vous remarquez que le nom de chaque colonne se trouve dans une liste. On peut se servir de cette liste pour renommer nos colonnes dans le cas où elles ont des noms barbares. Il suffit de dire que ```md.columns``` est égal à une liste dans laquelle on mettra nos nouveaux noms de colonnes.<br>\n",
    "C'est ainsi que la commande ci-dessous, par exemple, me permet de rebaptiser la colonne ```dateChangStatut``` par ```date```."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "md.columns = ['num', 'annee', 'prenom', 'nom', 'genre', 'specialite1', 'specialite2',\n",
    "       'specialite3', 'statut', 'date', 'typePermis', 'ville',\n",
    "       'prov', 'pays']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "En invoquant la fonction ```.columns```, je constate que le nom de la colonne a changé."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['num', 'annee', 'prenom', 'nom', 'genre', 'specialite1', 'specialite2',\n",
       "       'specialite3', 'statut', 'date', 'typePermis', 'ville', 'prov', 'pays'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "md.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ce n'est pas le cas ici, mais il arrive fréquemment, lorsqu'on travaille avec des données ouvertes, qu'il y a beaucoup de colonnes. Cela peut rendre les données difficiles à lire, sans compter que ça peut taxer la mémoire de notre ordi. Il est possible de supprimer des colonnes contenant des informations superflues.\n",
    "\n",
    "Si, par exemple, dans le fichier de médecins, vous souhaitiez vous débarasser de la colonne ```ville```, ce serait avec la fonction ```.drop()``` que vous vous y prendriez.\n",
    "\n",
    "Cette fonction prend deux arguments. Le premier est la colonne (ou les colonnes) que vous souhaitez rayer de la surface de la Terre. Lorsqu'il y a plusieurs colonnes, il faut les mettre dans une liste&nbsp;: ```[\"colonne_1\", \"colonne_2\", \"colonne_3\"]```. Le second indique si ce sont des colonnes que vous souhaitez supprimer ou des lignes. Dans le cas de colonnes, l'argument doit être ```1```, dans le cas de lignes, c'est ```0```. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "md = md.drop(\"ville\", 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['num', 'annee', 'prenom', 'nom', 'genre', 'specialite1', 'specialite2',\n",
       "       'specialite3', 'statut', 'date', 'typePermis', 'prov', 'pays'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "md.columns # La colonne «ville» a disparu!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Il est utile de simplifier les noms des colonnes puisqu'on peut faire afficher le contenu d'une colonne de notre choix simplement en ajoutant son nom à notre nom de variable.<br>\n",
    "On obtient alors non plus un _**dataframe**_, mais une structure de données unidimentionnelle que pandas appelle une _**serie**_.\n",
    "\n",
    "Voici un exemple avec le genre des médecins&nbsp;:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        M\n",
       "1        M\n",
       "2        M\n",
       "3        M\n",
       "4        M\n",
       "        ..\n",
       "35104    M\n",
       "35105    M\n",
       "35106    F\n",
       "35107    F\n",
       "35108    M\n",
       "Name: genre, Length: 35109, dtype: object"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "md.genre"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Opérations de base\n",
    "-----"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Cette sélection de colonnes est utile pour effectuer une série d'opérations de base qu'on va maintenant aborder.<br>\n",
    "Si on a une colonne qui contient des nombres, on peut en afficher la valeur maximale ou minimale à l'aide des fonctions ```.max()``` et ```.min()```.<br>\n",
    "Voici un exemple avec la colonne ```montant``` de notre fichier de données sur les contrats militaires."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9975000.0"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mil.montant.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mil.montant.min()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On peut aussi effectuer des calculs simples sur ces colonnes.<br>\n",
    "Ici, on effectue :\n",
    "* une somme avec la fonction ```.sum()```\n",
    "* une moyenne avec la fonction ```.mean()```\n",
    "\n",
    "Et on trouve la médiane avec la fonction ```.median()```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "27163294776.26"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mil.montant.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "163681.63551063047"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mil.montant.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "28984.5"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mil.montant.median()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Dans les cas où vous avez plusieurs colonnes composées de nombres, il peut être intéressant de réunir toutes ces informations à l'intérieur d'un seul et même tableau.<br>\n",
    "C'est ce que nous permet de faire la fonction ```.describe()```."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>annee</th>\n",
       "      <th>trimestre</th>\n",
       "      <th>montant</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>165952.00</td>\n",
       "      <td>165952.00</td>\n",
       "      <td>165952.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2010.87</td>\n",
       "      <td>2.57</td>\n",
       "      <td>163681.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.27</td>\n",
       "      <td>1.11</td>\n",
       "      <td>595860.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2004.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2009.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>15754.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2011.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>28984.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2014.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>86231.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2016.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>9975000.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          annee  trimestre    montant\n",
       "count 165952.00  165952.00  165952.00\n",
       "mean    2010.87       2.57  163681.64\n",
       "std        3.27       1.11  595860.66\n",
       "min     2004.00       1.00       0.00\n",
       "25%     2009.00       2.00   15754.75\n",
       "50%     2011.00       3.00   28984.50\n",
       "75%     2014.00       4.00   86231.00\n",
       "max     2016.00       4.00 9975000.00"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mil.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Regroupements\n",
    "-----"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "La meilleure façon d'interroger des données est d'y effectuer différents regroupements.<br>\n",
    "Dans notre fichier sur les médecins, par exemple, on a une colonne appelée ```genre``` qui nous dit si un médecin est un homme ou une femme. Cette information est représentée par deux valeurs&nbsp;: \"M\" ou \"F\".\n",
    "\n",
    "La fonction ```value_counts()``` nous permet de compter combien il y a d'occurences de chacune de ces valeurs, donc de compter le nombre d'hommes et de femmes dans notre tableau."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "M    22441\n",
       "F    12668\n",
       "Name: genre, dtype: int64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "md.genre.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Si on veut, plutôt, calculer le pourcentage de chacune de ces valeurs, on peut se rappeler que pandas est du bon vieux python et utiliser la fonction ```len()``` dans la formule suivante&nbsp;:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "M   63.92\n",
       "F   36.08\n",
       "Name: genre, dtype: float64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "md.genre.value_counts() / len(md.genre)*100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "63,92% des médecins inscrits au tableau du Collège des médecins, donc, sont des hommes; 36,08% des femmes.\n",
    "\n",
    "-----\n",
    "On peut faire la même chose avec toutes les variables et, en combinant les fonctions ```.value_counts()``` et ```.head()```, choisir de n'afficher qu'un nombre restreint de valeurs quand on en a plusieurs. Dans notre fichier de contrats militaires, par exemple, la formule ci-dessous nous permet d'identifier quel sont les 10 fournisseurs qui ont obtenu le plus grand nombre de contrats du ministère de la Défense."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SIMEX DEFENCE INC. / DEFENSE SIMEX INC.                         1910\n",
       "IMPERIAL OIL                                                    1608\n",
       "Unisource Technology Inc                                        1315\n",
       "FORD MOTOR COMPANY OF CANADA, LIMITED/FORD DU CANADA LIMITEE     957\n",
       "Calian Ltd                                                       950\n",
       "General Motors of Canada Limited                                 772\n",
       "J.H.T. ELECTRONICS LTD.                                          714\n",
       "BLUEWAVE ENERGY                                                  634\n",
       "WORLD FUEL SERVICES                                              628\n",
       "Imperial Oil Limited                                             601\n",
       "Name: fournisseur, dtype: int64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mil.fournisseur.value_counts().head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Vous remarquerez cependant, ici, que le 2e et le 10e fournisseur sont la même entreprise, mais écrite d'une manière différente («IMPERIAL OIL» dans un cas, «Imperial Oil Limited» dans l'autre).<br>\n",
    "Ici, donc, avant d'utiliser pandas, il serait préférable d'effectuer d'abord un nettoyage de nos données avec [OpenRefine](http://openrefine.org/).\n",
    "![](https://avatars0.githubusercontent.com/u/2538880?v=3&s=200)\n",
    "\n",
    "-----"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Nettoyage simple avec ```.str.replace()```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Si vos données ne requièrent pas de nettoyage trop complexe, vous pouvez utiliser la fonction ```.str.replace()```.\n",
    "\n",
    "C'est l'une des nombreuses fonctions permettant de traiter du texte (chaînes de caractères ou *strings*, d'où le «.str») dans pandas.\n",
    "\n",
    "Dans la variable ```md```, par exemple, la première colonne contient le numéro de permis de tous les médecins. Ce numéro est précédé d'un dièse ou *hashtag* (#). Vous voulez anéantir ce caractère superfétatoire. Voici comment faire."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>num</th>\n",
       "      <th>annee</th>\n",
       "      <th>prenom</th>\n",
       "      <th>nom</th>\n",
       "      <th>genre</th>\n",
       "      <th>specialite1</th>\n",
       "      <th>specialite2</th>\n",
       "      <th>specialite3</th>\n",
       "      <th>statut</th>\n",
       "      <th>date</th>\n",
       "      <th>typePermis</th>\n",
       "      <th>prov</th>\n",
       "      <th>pays</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>30001</td>\n",
       "      <td>1930</td>\n",
       "      <td>Lucien</td>\n",
       "      <td>Amyot</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>1981-12-29</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>30002</td>\n",
       "      <td>1930</td>\n",
       "      <td>Wilfrid</td>\n",
       "      <td>Audet</td>\n",
       "      <td>M</td>\n",
       "      <td>Inconnue</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Démission</td>\n",
       "      <td>1987-10-01</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>30003</td>\n",
       "      <td>1930</td>\n",
       "      <td>A. T.</td>\n",
       "      <td>Batshaw</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>1983-11-11</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>30005</td>\n",
       "      <td>1930</td>\n",
       "      <td>Maurice</td>\n",
       "      <td>Beaudry</td>\n",
       "      <td>M</td>\n",
       "      <td>Dermatologie</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>1989-02-12</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>30006</td>\n",
       "      <td>1930</td>\n",
       "      <td>P. E.</td>\n",
       "      <td>Belleau</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine interne</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>1986-05-31</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35104</th>\n",
       "      <td>16893</td>\n",
       "      <td>2016</td>\n",
       "      <td>Sébastien</td>\n",
       "      <td>David</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35105</th>\n",
       "      <td>16894</td>\n",
       "      <td>2016</td>\n",
       "      <td>Guillaume Patrick Jean</td>\n",
       "      <td>Berthier</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Restrictif</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35106</th>\n",
       "      <td>16895</td>\n",
       "      <td>2016</td>\n",
       "      <td>Miriam</td>\n",
       "      <td>Banoub</td>\n",
       "      <td>F</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35107</th>\n",
       "      <td>16896</td>\n",
       "      <td>2016</td>\n",
       "      <td>Anne-Sophie</td>\n",
       "      <td>Lemay</td>\n",
       "      <td>F</td>\n",
       "      <td>Hématologie</td>\n",
       "      <td>Oncologie médicale</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35108</th>\n",
       "      <td>16897</td>\n",
       "      <td>2016</td>\n",
       "      <td>Mohamed Ali</td>\n",
       "      <td>Abla</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>35109 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         num  annee                  prenom       nom genre  \\\n",
       "0      30001   1930                  Lucien     Amyot     M   \n",
       "1      30002   1930                 Wilfrid     Audet     M   \n",
       "2      30003   1930                   A. T.   Batshaw     M   \n",
       "3      30005   1930                 Maurice   Beaudry     M   \n",
       "4      30006   1930                   P. E.   Belleau     M   \n",
       "...      ...    ...                     ...       ...   ...   \n",
       "35104  16893   2016               Sébastien     David     M   \n",
       "35105  16894   2016  Guillaume Patrick Jean  Berthier     M   \n",
       "35106  16895   2016                  Miriam    Banoub     F   \n",
       "35107  16896   2016             Anne-Sophie     Lemay     F   \n",
       "35108  16897   2016             Mohamed Ali      Abla     M   \n",
       "\n",
       "               specialite1         specialite2 specialite3  \\\n",
       "0      Médecine de famille                 NaN         NaN   \n",
       "1                 Inconnue                 NaN         NaN   \n",
       "2      Médecine de famille                 NaN         NaN   \n",
       "3             Dermatologie                 NaN         NaN   \n",
       "4         Médecine interne                 NaN         NaN   \n",
       "...                    ...                 ...         ...   \n",
       "35104  Médecine de famille                 NaN         NaN   \n",
       "35105  Médecine de famille                 NaN         NaN   \n",
       "35106  Médecine de famille                 NaN         NaN   \n",
       "35107          Hématologie  Oncologie médicale         NaN   \n",
       "35108  Médecine de famille                 NaN         NaN   \n",
       "\n",
       "                   statut        date  typePermis    prov    pays  \n",
       "0      Retrait pour décès  1981-12-29    Régulier  Québec  Canada  \n",
       "1               Démission  1987-10-01    Régulier  Québec  Canada  \n",
       "2      Retrait pour décès  1983-11-11    Régulier  Québec  Canada  \n",
       "3      Retrait pour décès  1989-02-12    Régulier  Québec  Canada  \n",
       "4      Retrait pour décès  1986-05-31    Régulier  Québec  Canada  \n",
       "...                   ...         ...         ...     ...     ...  \n",
       "35104     Inscrit - Actif         NaN    Régulier  Québec  Canada  \n",
       "35105     Inscrit - Actif         NaN  Restrictif  Québec  Canada  \n",
       "35106     Inscrit - Actif         NaN    Régulier  Québec  Canada  \n",
       "35107     Inscrit - Actif         NaN    Régulier  Québec  Canada  \n",
       "35108     Inscrit - Actif         NaN    Régulier  Québec  Canada  \n",
       "\n",
       "[35109 rows x 13 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "md.num = md.num.str.replace(\"#\",\"\")\n",
    "md"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### ATTENTION"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Les fonctions ```.str``` n'agissent que sur des *series*.\n",
    "\n",
    "Ainsi, si vous écrivez la ligne de code suivante&nbsp;:\n",
    "\n",
    "```md = md.num.str.replace(\"#\",\"\")```\n",
    "\n",
    "Votre *dataframe* ```md``` va être remplacé **au complet** par une simple *serie* ne contenant que les numéros de permis des médecins.\n",
    "\n",
    "On peut éviter ce fâcheux contretemps en demandant à ```str.replace()``` de ne transformer que la colonne ```md.num```, comme je l'ai fait quelques cellules plus haut."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "-----"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Dans pandas, il existe une autre fonction qui permet d'effectuer des regroupements.<br>\n",
    "Il s'agit de la fonction **```.groupby()```**\n",
    "\n",
    "On peut alors se demander quelle est la différence entre&nbsp;:\n",
    "\n",
    "* ```mil.fournisseur.value_counts()``` et\n",
    "* ```mil.groupby(\"fournisseur\")```\n",
    "\n",
    "La différence est simple. Il faut se souvenir que pandas travaille avec deux grandes structures de données, les *series* et les *dataframes*.\n",
    "\n",
    "Quand on fait ```mil.fournisseur```, on crée une *series* à partir de ```mil```. C'est tout simplement une liste de valeurs. Et la fonction ```.value_counts()``` ne fait que dénombrer ces valeurs. Il faut aussi savoir que cette fonction ne s'applique qu'à des *series*.\n",
    "\n",
    "Quand on fait ```mil.groupby(\"fournisseurs\")``` on crée en fait autant de *dataframes* qu'il y a de fournisseurs. La fonction ```.value_counts()``` ne fonctionne plus. Mais on peut tout de même effectuer des calculs ou des regroupements en fonction des autres colonnes qui se trouvent toujours dans nos *dataframe*, une structure de données plus complexe qu'une *series*."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "C'est ainsi que s'il est intéressant de connaître le nombre de contrats que chaque fournisseur a obtenu, il est encore plus pertinent de savoir qui sont les fournisseurs qui ont décroché les contrats les plus lucratifs.\n",
    "\n",
    "La fonction ```.groupby()```, combinée à d'autres fonctions qu'on a vues antérieurement, va nous permettre de trouver la réponse.\n",
    "\n",
    "La formule ci-dessous enchaîne cinq opérations&nbsp;:\n",
    "\n",
    "* Un *groupby* avec ```mil``` en fonction de la colonne ```fournisseur```\n",
    "* On transforme chacun des *dataframes* ainsi créés en un *serie* extrait de la colonne ```montant```\n",
    "* On fait, avec la fonction ```.sum()```, la somme des montants de chacune de ces *series*\n",
    "* On les ordonne en ordre décroissant avec la fonction ```.sort_values()``` et le paramètre ```ascending=**False**```\n",
    "* On affiche les 10 premiers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "fournisseur\n",
       "General Dynamics Ordnance and Tactical Systems - Canada Inc   720145247.00\n",
       "UNITED STATES DEPARTMENT OF THE NAVY (NAVAIR)                 275029944.00\n",
       "SIMEX DEFENCE INC. / DEFENSE SIMEX INC.                       225237149.00\n",
       "UNITED STATES DEPARTMENT OF THE ARMY (USASAC)                 203107502.00\n",
       "Lockheed Martin Canada Inc.                                   190692963.53\n",
       "UNITED STATES DEPARTMENT OF THE AIR FORCE (AFSAC)             154954999.00\n",
       "Calian Ltd.                                                   152633588.67\n",
       "Valcom Consulting Group Inc.                                  151766430.97\n",
       "RHEINMETALL CANADA INC.                                       140351196.40\n",
       "NATO SEASPARROW SURFACE       MISSILE SYSTEM PROJECT          125042079.00\n",
       "Name: montant, dtype: float64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mil.groupby(\"fournisseur\").montant.sum().sort_values(ascending=False).head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Regroupements conditionnels"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On a vu, plus haut, comment sélectionner une partie d'un tableau en fonction des numéros de lignes ou de colonnes.<br>\n",
    "Il est aussi possible de faire des sélections en fonction d'une valeur donnée. Par exemple, si, dans nos médecins, on souhait ne choisir que le groupe des médecins qui ont été radiés de leur ordre professionnel. On pourrait commencer par examiner la colonne ```statut``` pour voir quelles sont les différentes valeurs qu'elle contient. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Inscrit - Actif                                            21017\n",
       "Démission                                                   4623\n",
       "Retrait pour décès                                          3877\n",
       "Inscrit - Retraité                                          2415\n",
       "Radié pour non paiement de cotisation                       2085\n",
       "Expiration                                                   630\n",
       "Inscrit - Actif (l'exercice de ce membre est limité)         184\n",
       "Radié pour non-paiement de cotisation                         88\n",
       "Inscrit - Retraité (l'exercice de ce membre est limité)       71\n",
       "Radié                                                         67\n",
       "Retrait                                                       29\n",
       "Inscrit - Inactif                                             10\n",
       "Non inscrit                                                    9\n",
       "Révocation                                                     4\n",
       "Name: statut, dtype: int64"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "md.statut.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On remarque qu'il y a 67 médecins dont le statut est «**Radié**» et 88 dont le statut est «**Radié pour non-paiement de cotisation**». On ne s'intéresse qu'aux premiers.\n",
    "\n",
    "On va donc créer une variable que je vais appeler ```rad``` et je vais y mettre uniquement les médecins dont le statut est «Radié» avec la formule suivante&nbsp;:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "rad = md.statut == \"Radié\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Je peux maintenant utiliser le sous-ensemble ```rad``` de mon tableau ```md``` pour effectuer toutes les opérations qu'on a vues jusqu'à maintenant.<br>\n",
    "Il faut seulement se souvenir que ce sous-ensemble est désigné ainsi&nbsp;: **```md[rad]```**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>num</th>\n",
       "      <th>annee</th>\n",
       "      <th>prenom</th>\n",
       "      <th>nom</th>\n",
       "      <th>genre</th>\n",
       "      <th>specialite1</th>\n",
       "      <th>specialite2</th>\n",
       "      <th>specialite3</th>\n",
       "      <th>statut</th>\n",
       "      <th>date</th>\n",
       "      <th>typePermis</th>\n",
       "      <th>prov</th>\n",
       "      <th>pays</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1375</th>\n",
       "      <td>48004</td>\n",
       "      <td>1948</td>\n",
       "      <td>Alphonse</td>\n",
       "      <td>Bardari</td>\n",
       "      <td>M</td>\n",
       "      <td>Chirurgie générale</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Radié</td>\n",
       "      <td>1994-10-19</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1661</th>\n",
       "      <td>49130</td>\n",
       "      <td>1949</td>\n",
       "      <td>Jacques</td>\n",
       "      <td>Pettigrew</td>\n",
       "      <td>M</td>\n",
       "      <td>Chirurgie générale</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Radié</td>\n",
       "      <td>1993-06-17</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2512</th>\n",
       "      <td>53150</td>\n",
       "      <td>1953</td>\n",
       "      <td>J.-C.</td>\n",
       "      <td>Paquette</td>\n",
       "      <td>M</td>\n",
       "      <td>Inconnue</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Radié</td>\n",
       "      <td>1989-08-16</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2761</th>\n",
       "      <td>54174</td>\n",
       "      <td>1954</td>\n",
       "      <td>Philippe</td>\n",
       "      <td>Moreault</td>\n",
       "      <td>M</td>\n",
       "      <td>Psychiatrie</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Radié</td>\n",
       "      <td>1996-04-08</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3057</th>\n",
       "      <td>55201</td>\n",
       "      <td>1955</td>\n",
       "      <td>Claude</td>\n",
       "      <td>Saint-Laurent</td>\n",
       "      <td>M</td>\n",
       "      <td>Psychiatrie</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Radié</td>\n",
       "      <td>1998-07-30</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21622</th>\n",
       "      <td>93100</td>\n",
       "      <td>1993</td>\n",
       "      <td>Serge</td>\n",
       "      <td>Grégoire</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Radié</td>\n",
       "      <td>2016-05-12</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22819</th>\n",
       "      <td>95451</td>\n",
       "      <td>1995</td>\n",
       "      <td>Jocelyn</td>\n",
       "      <td>Lussier</td>\n",
       "      <td>M</td>\n",
       "      <td>Pédiatrie</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Radié</td>\n",
       "      <td>2009-12-21</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23026</th>\n",
       "      <td>96203</td>\n",
       "      <td>1996</td>\n",
       "      <td>Éric</td>\n",
       "      <td>Bergeron</td>\n",
       "      <td>M</td>\n",
       "      <td>Chirurgie générale</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Radié</td>\n",
       "      <td>2016-04-28</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24024</th>\n",
       "      <td>98262</td>\n",
       "      <td>1998</td>\n",
       "      <td>Yves</td>\n",
       "      <td>Tremblay</td>\n",
       "      <td>M</td>\n",
       "      <td>Chirurgie générale</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Radié</td>\n",
       "      <td>2016-04-30</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27378</th>\n",
       "      <td>05358</td>\n",
       "      <td>2005</td>\n",
       "      <td>Walif</td>\n",
       "      <td>Chbeir</td>\n",
       "      <td>M</td>\n",
       "      <td>Radiologie diagnostique</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Radié</td>\n",
       "      <td>2015-04-10</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>67 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         num  annee    prenom            nom genre              specialite1  \\\n",
       "1375   48004   1948  Alphonse        Bardari     M       Chirurgie générale   \n",
       "1661   49130   1949   Jacques      Pettigrew     M       Chirurgie générale   \n",
       "2512   53150   1953     J.-C.       Paquette     M                 Inconnue   \n",
       "2761   54174   1954  Philippe       Moreault     M              Psychiatrie   \n",
       "3057   55201   1955    Claude  Saint-Laurent     M              Psychiatrie   \n",
       "...      ...    ...       ...            ...   ...                      ...   \n",
       "21622  93100   1993     Serge       Grégoire     M      Médecine de famille   \n",
       "22819  95451   1995   Jocelyn        Lussier     M                Pédiatrie   \n",
       "23026  96203   1996      Éric       Bergeron     M       Chirurgie générale   \n",
       "24024  98262   1998      Yves       Tremblay     M       Chirurgie générale   \n",
       "27378  05358   2005     Walif         Chbeir     M  Radiologie diagnostique   \n",
       "\n",
       "      specialite2 specialite3 statut        date typePermis    prov    pays  \n",
       "1375          NaN         NaN  Radié  1994-10-19   Régulier  Québec  Canada  \n",
       "1661          NaN         NaN  Radié  1993-06-17   Régulier  Québec  Canada  \n",
       "2512          NaN         NaN  Radié  1989-08-16   Régulier  Québec  Canada  \n",
       "2761          NaN         NaN  Radié  1996-04-08   Régulier  Québec  Canada  \n",
       "3057          NaN         NaN  Radié  1998-07-30   Régulier  Québec  Canada  \n",
       "...           ...         ...    ...         ...        ...     ...     ...  \n",
       "21622         NaN         NaN  Radié  2016-05-12   Régulier  Québec  Canada  \n",
       "22819         NaN         NaN  Radié  2009-12-21   Régulier  Québec  Canada  \n",
       "23026         NaN         NaN  Radié  2016-04-28   Régulier  Québec  Canada  \n",
       "24024         NaN         NaN  Radié  2016-04-30   Régulier  Québec  Canada  \n",
       "27378         NaN         NaN  Radié  2015-04-10   Régulier  Québec  Canada  \n",
       "\n",
       "[67 rows x 13 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "md[rad]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Je peux donc examiner quelles sont, par exemples, les spécialités les plus courantes dans le sous-ensemble des médecins radiés."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Inconnue                      29\n",
       "Médecine de famille           10\n",
       "Psychiatrie                    8\n",
       "Chirurgie générale             6\n",
       "Chirurgie plastique            3\n",
       "Obstétrique et gynécologie     3\n",
       "Cardiologie                    2\n",
       "Médecine interne               2\n",
       "Urologie                       1\n",
       "Radiologie diagnostique        1\n",
       "Pédiatrie                      1\n",
       "Ophtalmologie                  1\n",
       "Name: specialite1, dtype: int64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "md[rad].specialite1.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On peut également construire des sous-ensembles de façon plus souple en se basant sur la présence d'une chaîne de caractères donnés.<br>\n",
    "Par exemple, dans nos contrats militaires, vous avez peut-être remarqué qu'il y en a plusieurs qui ont été octroyés à différentes composantes des forces armées américaines. Il y a entre autres&nbsp;:\n",
    "\n",
    "* UNITED STATES DEPARTMENT OF THE ARMY\n",
    "* UNITED STATES DEPARTMENT OF THE NAVY\n",
    "* UNITED STATES DEPARTMENT OF THE AIR FORCE\n",
    "\n",
    "Si on souhaite créer un sous-ensemble regroupant tous les contrats dont le nom du fournisseur contient les mots «UNITED STATES», on peut utiliser la fonction ```str.contains()``` de la façon suivante&nbsp;:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "us = mil.fournisseur.str.contains(\"UNITED STATES\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On peut ensuite faire un décompte des différents noms de fournisseurs qu'on a ainsi regroupés pour constater qu'il y a plusieurs agences américaines à qui la défense canadienne a octroyé des contrats."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "UNITED STATES DEPARTMENT OF THE ARMY (USASAC)         152\n",
       "UNITED STATES DEPARTMENT OF THE AIR FORCE (AFSAC)     131\n",
       "UNITED STATES DEPARTMENT OF THE NAVY (NAVAIR)         120\n",
       "UNITED STATES DEPARTMENT OF THE NAVY (NAVSEA)          72\n",
       "UNITED STATES DEPARTMENT OF THE AIR FORCE (AFSAT)      68\n",
       "UNITED STATES DEPARTMENT OF THE ARMY (TRADOC)          60\n",
       "UNITED STATES DEPARTMENT OF THE NAVY (NETSAFA)         55\n",
       "UNITED STATES DEPARTMENT OF THE NAVY (NAVICP)          39\n",
       "UNITED STATES DEPARTMENT OF THE NAVY (MISC)            35\n",
       "UNITED STATES DEPARTMENT OF THE NAVY (SPAWAR)          26\n",
       "UNITED STATES DEPARTMENT OF THE AIR FORCE (SAF/IA)      4\n",
       "Name: fournisseur, dtype: int64"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mil[us].fournisseur.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Et quelle est la valeur totale des contrats que ces agences ont obtenu entre 2004 et 2016?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1069596099.0"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mil[us].montant.sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Cette somme représente quelle proportion du total qui a été octroyé en contrats par le ministère de la Défense au cours de la même période?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.9376522907478764"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mil[us].montant.sum() / mil.montant.sum() * 100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Attention!\n",
    "\n",
    "La fonction ```str.contains()``` est sensible à la casse. Ainsi, si on revient à nos médecins, la formule\n",
    "\n",
    "* ```md.statut.str.contains(\"Actif\")```\n",
    "\n",
    "Ne donnera pas les mêmes résultats que\n",
    "\n",
    "* ```md.statut.str.contains(\"actif\")```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "actifs = md.statut.str.contains(\"actif\")\n",
    "len(md[actifs])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "21201"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "actifs = md.statut.str.contains(\"Actif\")\n",
    "len(md[actifs])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "La première ne regroupe que 10 médecins, tandis que la seconde en compte 21&nbsp;201!<br>\n",
    "Pourquoi?\n",
    "\n",
    "Parce que la première ne regroupe que les médecins dont le statut contient la chaîne «actif» avec un «a» minuscule, à savoir&nbsp;:\n",
    "\n",
    "* Inscrit - Inactif\n",
    "\n",
    "La seconde comprend les médecins dont les statuts contiennent la même chaîne, mais avec un «A» majuscule, c'est-à-dire&nbsp;:\n",
    "\n",
    "* Inscrit - Actif\n",
    "* Inscrit - Actif (l'exercice de ce membre est limité)\n",
    "\n",
    "-----"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "À partir de notre sous-ensemble de médecins actifs, on peut aussi créer d'autres sous-ensembles. La formule ci-dessous sélectionne les médecins de famille dans ce groupe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "famille = md[actifs].specialite1 == \"Médecine de famille\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mais attention, si vous voulez afficher le sous-ensemble que vous venez de créer, vous pourriez être tenté d'écrire ceci&nbsp;:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "//anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:1: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    },
    {
     "ename": "IndexingError",
     "evalue": "Unalignable boolean Series provided as indexer (index of the boolean Series and of the indexed object do not match).",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mIndexingError\u001b[0m                             Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-43-3f2f0abd82e6>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmd\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mfamille\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m//anaconda3/lib/python3.7/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   2789\u001b[0m         \u001b[0;31m# Do we have a (boolean) 1d indexer?\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2790\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mcom\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_bool_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2791\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_bool_array\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2792\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2793\u001b[0m         \u001b[0;31m# We are left with two options: a single key, and a collection of keys,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m//anaconda3/lib/python3.7/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m_getitem_bool_array\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   2841\u001b[0m         \u001b[0;31m# check_bool_indexer will throw exception if Series key cannot\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2842\u001b[0m         \u001b[0;31m# be reindexed to match DataFrame rows\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2843\u001b[0;31m         \u001b[0mkey\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcheck_bool_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2844\u001b[0m         \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnonzero\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2845\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_take_with_is_copy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m//anaconda3/lib/python3.7/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36mcheck_bool_indexer\u001b[0;34m(index, key)\u001b[0m\n\u001b[1;32m   2314\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mmask\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0many\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2315\u001b[0m             raise IndexingError(\n\u001b[0;32m-> 2316\u001b[0;31m                 \u001b[0;34m\"Unalignable boolean Series provided as \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2317\u001b[0m                 \u001b[0;34m\"indexer (index of the boolean Series and of \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2318\u001b[0m                 \u001b[0;34m\"the indexed object do not match).\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mIndexingError\u001b[0m: Unalignable boolean Series provided as indexer (index of the boolean Series and of the indexed object do not match)."
     ]
    }
   ],
   "source": [
    "md[famille]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Vous obtiendrez un message d'erreur tout aussi mystérieux qu'il peut être contrariant.\n",
    "\n",
    "Il faut se souvenir que «famille» a été créé à partir de «actifs», il n'existe qu'en fonction du sous-ensemble ```md[actifs]```, et il faudra simplement enchaîner les deux sous-ensembles ainsi&nbsp;:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>num</th>\n",
       "      <th>annee</th>\n",
       "      <th>prenom</th>\n",
       "      <th>nom</th>\n",
       "      <th>genre</th>\n",
       "      <th>specialite1</th>\n",
       "      <th>specialite2</th>\n",
       "      <th>specialite3</th>\n",
       "      <th>statut</th>\n",
       "      <th>date</th>\n",
       "      <th>typePermis</th>\n",
       "      <th>prov</th>\n",
       "      <th>pays</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4181</th>\n",
       "      <td>59140</td>\n",
       "      <td>1959</td>\n",
       "      <td>Henri</td>\n",
       "      <td>Lecoq</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif (l'exercice de ce membre est l...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4284</th>\n",
       "      <td>59258</td>\n",
       "      <td>1959</td>\n",
       "      <td>Erwin B.</td>\n",
       "      <td>Nichols</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4384</th>\n",
       "      <td>60023</td>\n",
       "      <td>1960</td>\n",
       "      <td>Gilles</td>\n",
       "      <td>Aubin</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4476</th>\n",
       "      <td>60118</td>\n",
       "      <td>1960</td>\n",
       "      <td>Paul-Émile</td>\n",
       "      <td>Godin</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4481</th>\n",
       "      <td>60123</td>\n",
       "      <td>1960</td>\n",
       "      <td>Paulin</td>\n",
       "      <td>Hébert</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif (l'exercice de ce membre est l...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>35103</th>\n",
       "      <td>16892</td>\n",
       "      <td>2016</td>\n",
       "      <td>Steve</td>\n",
       "      <td>Lauwaët</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35104</th>\n",
       "      <td>16893</td>\n",
       "      <td>2016</td>\n",
       "      <td>Sébastien</td>\n",
       "      <td>David</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35105</th>\n",
       "      <td>16894</td>\n",
       "      <td>2016</td>\n",
       "      <td>Guillaume Patrick Jean</td>\n",
       "      <td>Berthier</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Restrictif</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35106</th>\n",
       "      <td>16895</td>\n",
       "      <td>2016</td>\n",
       "      <td>Miriam</td>\n",
       "      <td>Banoub</td>\n",
       "      <td>F</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35108</th>\n",
       "      <td>16897</td>\n",
       "      <td>2016</td>\n",
       "      <td>Mohamed Ali</td>\n",
       "      <td>Abla</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10107 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         num  annee                  prenom       nom genre  \\\n",
       "4181   59140   1959                   Henri     Lecoq     M   \n",
       "4284   59258   1959                Erwin B.   Nichols     M   \n",
       "4384   60023   1960                  Gilles     Aubin     M   \n",
       "4476   60118   1960              Paul-Émile     Godin     M   \n",
       "4481   60123   1960                  Paulin    Hébert     M   \n",
       "...      ...    ...                     ...       ...   ...   \n",
       "35103  16892   2016                   Steve   Lauwaët     M   \n",
       "35104  16893   2016               Sébastien     David     M   \n",
       "35105  16894   2016  Guillaume Patrick Jean  Berthier     M   \n",
       "35106  16895   2016                  Miriam    Banoub     F   \n",
       "35108  16897   2016             Mohamed Ali      Abla     M   \n",
       "\n",
       "               specialite1 specialite2 specialite3  \\\n",
       "4181   Médecine de famille         NaN         NaN   \n",
       "4284   Médecine de famille         NaN         NaN   \n",
       "4384   Médecine de famille         NaN         NaN   \n",
       "4476   Médecine de famille         NaN         NaN   \n",
       "4481   Médecine de famille         NaN         NaN   \n",
       "...                    ...         ...         ...   \n",
       "35103  Médecine de famille         NaN         NaN   \n",
       "35104  Médecine de famille         NaN         NaN   \n",
       "35105  Médecine de famille         NaN         NaN   \n",
       "35106  Médecine de famille         NaN         NaN   \n",
       "35108  Médecine de famille         NaN         NaN   \n",
       "\n",
       "                                                  statut date  typePermis  \\\n",
       "4181   Inscrit - Actif (l'exercice de ce membre est l...  NaN    Régulier   \n",
       "4284                                     Inscrit - Actif  NaN    Régulier   \n",
       "4384                                     Inscrit - Actif  NaN    Régulier   \n",
       "4476                                     Inscrit - Actif  NaN    Régulier   \n",
       "4481   Inscrit - Actif (l'exercice de ce membre est l...  NaN    Régulier   \n",
       "...                                                  ...  ...         ...   \n",
       "35103                                    Inscrit - Actif  NaN    Régulier   \n",
       "35104                                    Inscrit - Actif  NaN    Régulier   \n",
       "35105                                    Inscrit - Actif  NaN  Restrictif   \n",
       "35106                                    Inscrit - Actif  NaN    Régulier   \n",
       "35108                                    Inscrit - Actif  NaN    Régulier   \n",
       "\n",
       "          prov    pays  \n",
       "4181    Québec  Canada  \n",
       "4284   Ontario  Canada  \n",
       "4384    Québec  Canada  \n",
       "4476    Québec  Canada  \n",
       "4481    Québec  Canada  \n",
       "...        ...     ...  \n",
       "35103   Québec  Canada  \n",
       "35104   Québec  Canada  \n",
       "35105   Québec  Canada  \n",
       "35106   Québec  Canada  \n",
       "35108   Québec  Canada  \n",
       "\n",
       "[10107 rows x 13 columns]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "md[actifs][famille]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Une autre façon d'arriver exactement au même résultat est d'effectuer de façon indépendante vos deux regroupements.<br>\n",
    "On pourra créer un sous-ensemble des médecins de famille à partir de l'ensemble des médecins&nbsp;:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "famille = md.specialite1 == \"Médecine de famille\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Et là, écrire ```md[famille]``` va fonctionner (ce sous-ensemble regroupe 13&nbsp;150 médecins)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>num</th>\n",
       "      <th>annee</th>\n",
       "      <th>prenom</th>\n",
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       "      <th>date</th>\n",
       "      <th>typePermis</th>\n",
       "      <th>prov</th>\n",
       "      <th>pays</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>30001</td>\n",
       "      <td>1930</td>\n",
       "      <td>Lucien</td>\n",
       "      <td>Amyot</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>1981-12-29</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>30003</td>\n",
       "      <td>1930</td>\n",
       "      <td>A. T.</td>\n",
       "      <td>Batshaw</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>1983-11-11</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>30008</td>\n",
       "      <td>1930</td>\n",
       "      <td>Antoni</td>\n",
       "      <td>Blais</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>1983-06-30</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>30012</td>\n",
       "      <td>1930</td>\n",
       "      <td>Lyla</td>\n",
       "      <td>Brown</td>\n",
       "      <td>F</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>1994-06-07</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>30017</td>\n",
       "      <td>1930</td>\n",
       "      <td>Rémi</td>\n",
       "      <td>Desjardins</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>1989-09-23</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35103</th>\n",
       "      <td>16892</td>\n",
       "      <td>2016</td>\n",
       "      <td>Steve</td>\n",
       "      <td>Lauwaët</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35104</th>\n",
       "      <td>16893</td>\n",
       "      <td>2016</td>\n",
       "      <td>Sébastien</td>\n",
       "      <td>David</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35105</th>\n",
       "      <td>16894</td>\n",
       "      <td>2016</td>\n",
       "      <td>Guillaume Patrick Jean</td>\n",
       "      <td>Berthier</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Restrictif</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35106</th>\n",
       "      <td>16895</td>\n",
       "      <td>2016</td>\n",
       "      <td>Miriam</td>\n",
       "      <td>Banoub</td>\n",
       "      <td>F</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35108</th>\n",
       "      <td>16897</td>\n",
       "      <td>2016</td>\n",
       "      <td>Mohamed Ali</td>\n",
       "      <td>Abla</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>13150 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         num  annee                  prenom         nom genre  \\\n",
       "0      30001   1930                  Lucien       Amyot     M   \n",
       "2      30003   1930                   A. T.     Batshaw     M   \n",
       "5      30008   1930                  Antoni       Blais     M   \n",
       "6      30012   1930                    Lyla       Brown     F   \n",
       "9      30017   1930                    Rémi  Desjardins     M   \n",
       "...      ...    ...                     ...         ...   ...   \n",
       "35103  16892   2016                   Steve     Lauwaët     M   \n",
       "35104  16893   2016               Sébastien       David     M   \n",
       "35105  16894   2016  Guillaume Patrick Jean    Berthier     M   \n",
       "35106  16895   2016                  Miriam      Banoub     F   \n",
       "35108  16897   2016             Mohamed Ali        Abla     M   \n",
       "\n",
       "               specialite1 specialite2 specialite3              statut  \\\n",
       "0      Médecine de famille         NaN         NaN  Retrait pour décès   \n",
       "2      Médecine de famille         NaN         NaN  Retrait pour décès   \n",
       "5      Médecine de famille         NaN         NaN  Retrait pour décès   \n",
       "6      Médecine de famille         NaN         NaN  Retrait pour décès   \n",
       "9      Médecine de famille         NaN         NaN  Retrait pour décès   \n",
       "...                    ...         ...         ...                 ...   \n",
       "35103  Médecine de famille         NaN         NaN     Inscrit - Actif   \n",
       "35104  Médecine de famille         NaN         NaN     Inscrit - Actif   \n",
       "35105  Médecine de famille         NaN         NaN     Inscrit - Actif   \n",
       "35106  Médecine de famille         NaN         NaN     Inscrit - Actif   \n",
       "35108  Médecine de famille         NaN         NaN     Inscrit - Actif   \n",
       "\n",
       "             date  typePermis    prov    pays  \n",
       "0      1981-12-29    Régulier  Québec  Canada  \n",
       "2      1983-11-11    Régulier  Québec  Canada  \n",
       "5      1983-06-30    Régulier  Québec  Canada  \n",
       "6      1994-06-07    Régulier  Québec  Canada  \n",
       "9      1989-09-23    Régulier  Québec  Canada  \n",
       "...           ...         ...     ...     ...  \n",
       "35103         NaN    Régulier  Québec  Canada  \n",
       "35104         NaN    Régulier  Québec  Canada  \n",
       "35105         NaN  Restrictif  Québec  Canada  \n",
       "35106         NaN    Régulier  Québec  Canada  \n",
       "35108         NaN    Régulier  Québec  Canada  \n",
       "\n",
       "[13150 rows x 13 columns]"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "md[famille]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Puis, pour faire une intersection avec nos 21&nbsp;201 médecins actifs, il vous suffira d'écrire ceci&nbsp;:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>num</th>\n",
       "      <th>annee</th>\n",
       "      <th>prenom</th>\n",
       "      <th>nom</th>\n",
       "      <th>genre</th>\n",
       "      <th>specialite1</th>\n",
       "      <th>specialite2</th>\n",
       "      <th>specialite3</th>\n",
       "      <th>statut</th>\n",
       "      <th>date</th>\n",
       "      <th>typePermis</th>\n",
       "      <th>prov</th>\n",
       "      <th>pays</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4181</th>\n",
       "      <td>59140</td>\n",
       "      <td>1959</td>\n",
       "      <td>Henri</td>\n",
       "      <td>Lecoq</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif (l'exercice de ce membre est l...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4284</th>\n",
       "      <td>59258</td>\n",
       "      <td>1959</td>\n",
       "      <td>Erwin B.</td>\n",
       "      <td>Nichols</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4384</th>\n",
       "      <td>60023</td>\n",
       "      <td>1960</td>\n",
       "      <td>Gilles</td>\n",
       "      <td>Aubin</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4476</th>\n",
       "      <td>60118</td>\n",
       "      <td>1960</td>\n",
       "      <td>Paul-Émile</td>\n",
       "      <td>Godin</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4481</th>\n",
       "      <td>60123</td>\n",
       "      <td>1960</td>\n",
       "      <td>Paulin</td>\n",
       "      <td>Hébert</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif (l'exercice de ce membre est l...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35103</th>\n",
       "      <td>16892</td>\n",
       "      <td>2016</td>\n",
       "      <td>Steve</td>\n",
       "      <td>Lauwaët</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35104</th>\n",
       "      <td>16893</td>\n",
       "      <td>2016</td>\n",
       "      <td>Sébastien</td>\n",
       "      <td>David</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35105</th>\n",
       "      <td>16894</td>\n",
       "      <td>2016</td>\n",
       "      <td>Guillaume Patrick Jean</td>\n",
       "      <td>Berthier</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Restrictif</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35106</th>\n",
       "      <td>16895</td>\n",
       "      <td>2016</td>\n",
       "      <td>Miriam</td>\n",
       "      <td>Banoub</td>\n",
       "      <td>F</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35108</th>\n",
       "      <td>16897</td>\n",
       "      <td>2016</td>\n",
       "      <td>Mohamed Ali</td>\n",
       "      <td>Abla</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10107 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         num  annee                  prenom       nom genre  \\\n",
       "4181   59140   1959                   Henri     Lecoq     M   \n",
       "4284   59258   1959                Erwin B.   Nichols     M   \n",
       "4384   60023   1960                  Gilles     Aubin     M   \n",
       "4476   60118   1960              Paul-Émile     Godin     M   \n",
       "4481   60123   1960                  Paulin    Hébert     M   \n",
       "...      ...    ...                     ...       ...   ...   \n",
       "35103  16892   2016                   Steve   Lauwaët     M   \n",
       "35104  16893   2016               Sébastien     David     M   \n",
       "35105  16894   2016  Guillaume Patrick Jean  Berthier     M   \n",
       "35106  16895   2016                  Miriam    Banoub     F   \n",
       "35108  16897   2016             Mohamed Ali      Abla     M   \n",
       "\n",
       "               specialite1 specialite2 specialite3  \\\n",
       "4181   Médecine de famille         NaN         NaN   \n",
       "4284   Médecine de famille         NaN         NaN   \n",
       "4384   Médecine de famille         NaN         NaN   \n",
       "4476   Médecine de famille         NaN         NaN   \n",
       "4481   Médecine de famille         NaN         NaN   \n",
       "...                    ...         ...         ...   \n",
       "35103  Médecine de famille         NaN         NaN   \n",
       "35104  Médecine de famille         NaN         NaN   \n",
       "35105  Médecine de famille         NaN         NaN   \n",
       "35106  Médecine de famille         NaN         NaN   \n",
       "35108  Médecine de famille         NaN         NaN   \n",
       "\n",
       "                                                  statut date  typePermis  \\\n",
       "4181   Inscrit - Actif (l'exercice de ce membre est l...  NaN    Régulier   \n",
       "4284                                     Inscrit - Actif  NaN    Régulier   \n",
       "4384                                     Inscrit - Actif  NaN    Régulier   \n",
       "4476                                     Inscrit - Actif  NaN    Régulier   \n",
       "4481   Inscrit - Actif (l'exercice de ce membre est l...  NaN    Régulier   \n",
       "...                                                  ...  ...         ...   \n",
       "35103                                    Inscrit - Actif  NaN    Régulier   \n",
       "35104                                    Inscrit - Actif  NaN    Régulier   \n",
       "35105                                    Inscrit - Actif  NaN  Restrictif   \n",
       "35106                                    Inscrit - Actif  NaN    Régulier   \n",
       "35108                                    Inscrit - Actif  NaN    Régulier   \n",
       "\n",
       "          prov    pays  \n",
       "4181    Québec  Canada  \n",
       "4284   Ontario  Canada  \n",
       "4384    Québec  Canada  \n",
       "4476    Québec  Canada  \n",
       "4481    Québec  Canada  \n",
       "...        ...     ...  \n",
       "35103   Québec  Canada  \n",
       "35104   Québec  Canada  \n",
       "35105   Québec  Canada  \n",
       "35106   Québec  Canada  \n",
       "35108   Québec  Canada  \n",
       "\n",
       "[10107 rows x 13 columns]"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "md[actifs & famille]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Et voilà!<br>\n",
    "On sait que, dans l'ensemble des 35&nbsp;109 membres et ex-membres du Collège des médecins, on a 10&nbsp;107 médecins actifs qui sont des médecins de famille.\n",
    "\n",
    "Maintenant, dans ce sous-groupe, quelle est la répartition homme/femme?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "F    5610\n",
       "M    4497\n",
       "Name: genre, dtype: int64"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "md[famille & actifs].genre.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ce qui représente quelles proportions?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "F   55.51\n",
       "M   44.49\n",
       "Name: genre, dtype: float64"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "md[famille & actifs].genre.value_counts() / len(md[famille & actifs]) * 100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On a peut-être une nouvelle, ici. Chez les médecins de famille actifs, au Québec, il y a une majorité de femmes (55,5%, contre 44,5% chez les hommes)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On peut même faire des sous-ensembles encore plus pointus. Par exemple, quelle est la répartition homme/femme des membres du Collège des médecins qui sont chirurgiens, actifs, ayant obtenu leur diplôme depuis 2000 et pratiquant au Québec?\n",
    "\n",
    "On a déjà notre sous-ensemble des médecins actifs. On va en créer trois autres.\n",
    "\n",
    "D'abord les médecins pratiquant au Québec."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>num</th>\n",
       "      <th>annee</th>\n",
       "      <th>prenom</th>\n",
       "      <th>nom</th>\n",
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       "      <th>pays</th>\n",
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       "      <th>0</th>\n",
       "      <td>30001</td>\n",
       "      <td>1930</td>\n",
       "      <td>Lucien</td>\n",
       "      <td>Amyot</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>30002</td>\n",
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       "      <td>Wilfrid</td>\n",
       "      <td>Audet</td>\n",
       "      <td>M</td>\n",
       "      <td>Inconnue</td>\n",
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       "      <td>Démission</td>\n",
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       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>30003</td>\n",
       "      <td>1930</td>\n",
       "      <td>A. T.</td>\n",
       "      <td>Batshaw</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>1983-11-11</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>30005</td>\n",
       "      <td>1930</td>\n",
       "      <td>Maurice</td>\n",
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       "      <td>M</td>\n",
       "      <td>Dermatologie</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>P. E.</td>\n",
       "      <td>Belleau</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine interne</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>1986-05-31</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
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       "      <th>35104</th>\n",
       "      <td>16893</td>\n",
       "      <td>2016</td>\n",
       "      <td>Sébastien</td>\n",
       "      <td>David</td>\n",
       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
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       "    <tr>\n",
       "      <th>35105</th>\n",
       "      <td>16894</td>\n",
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       "      <td>Guillaume Patrick Jean</td>\n",
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       "      <td>M</td>\n",
       "      <td>Médecine de famille</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Restrictif</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
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       "    <tr>\n",
       "      <th>35106</th>\n",
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       "      <td>Miriam</td>\n",
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       "      <td>Médecine de famille</td>\n",
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       "      <td>Anne-Sophie</td>\n",
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       "      <td>F</td>\n",
       "      <td>Hématologie</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
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       "      <th>35108</th>\n",
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       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
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       "<p>29794 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         num  annee                  prenom       nom genre  \\\n",
       "0      30001   1930                  Lucien     Amyot     M   \n",
       "1      30002   1930                 Wilfrid     Audet     M   \n",
       "2      30003   1930                   A. T.   Batshaw     M   \n",
       "3      30005   1930                 Maurice   Beaudry     M   \n",
       "4      30006   1930                   P. E.   Belleau     M   \n",
       "...      ...    ...                     ...       ...   ...   \n",
       "35104  16893   2016               Sébastien     David     M   \n",
       "35105  16894   2016  Guillaume Patrick Jean  Berthier     M   \n",
       "35106  16895   2016                  Miriam    Banoub     F   \n",
       "35107  16896   2016             Anne-Sophie     Lemay     F   \n",
       "35108  16897   2016             Mohamed Ali      Abla     M   \n",
       "\n",
       "               specialite1         specialite2 specialite3  \\\n",
       "0      Médecine de famille                 NaN         NaN   \n",
       "1                 Inconnue                 NaN         NaN   \n",
       "2      Médecine de famille                 NaN         NaN   \n",
       "3             Dermatologie                 NaN         NaN   \n",
       "4         Médecine interne                 NaN         NaN   \n",
       "...                    ...                 ...         ...   \n",
       "35104  Médecine de famille                 NaN         NaN   \n",
       "35105  Médecine de famille                 NaN         NaN   \n",
       "35106  Médecine de famille                 NaN         NaN   \n",
       "35107          Hématologie  Oncologie médicale         NaN   \n",
       "35108  Médecine de famille                 NaN         NaN   \n",
       "\n",
       "                   statut        date  typePermis    prov    pays  \n",
       "0      Retrait pour décès  1981-12-29    Régulier  Québec  Canada  \n",
       "1               Démission  1987-10-01    Régulier  Québec  Canada  \n",
       "2      Retrait pour décès  1983-11-11    Régulier  Québec  Canada  \n",
       "3      Retrait pour décès  1989-02-12    Régulier  Québec  Canada  \n",
       "4      Retrait pour décès  1986-05-31    Régulier  Québec  Canada  \n",
       "...                   ...         ...         ...     ...     ...  \n",
       "35104     Inscrit - Actif         NaN    Régulier  Québec  Canada  \n",
       "35105     Inscrit - Actif         NaN  Restrictif  Québec  Canada  \n",
       "35106     Inscrit - Actif         NaN    Régulier  Québec  Canada  \n",
       "35107     Inscrit - Actif         NaN    Régulier  Québec  Canada  \n",
       "35108     Inscrit - Actif         NaN    Régulier  Québec  Canada  \n",
       "\n",
       "[29794 rows x 13 columns]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qc = md.prov == \"Québec\"\n",
    "md[qc]\n",
    "# Sous-ensemble de 29 794 médecins"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ensuite, les médecins ayant intégré la profession depuis 2000.<br>\n",
    "Au lieu d'utiliser ```==```, on va se servir d'un autre opérateur qui peut s'appliquer à des nombres."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
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       "      <th>24699</th>\n",
       "      <td>00002</td>\n",
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       "      <td>00005</td>\n",
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       "      <td>Geneviève</td>\n",
       "      <td>Morin</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
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       "      <td>Médecine de famille</td>\n",
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       "    </tr>\n",
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       "</table>\n",
       "<p>10411 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         num  annee                  prenom       nom genre  \\\n",
       "24698  00001   2000            Themistocles   Assimes     M   \n",
       "24699  00002   2000                   Brian   Cameron     M   \n",
       "24700  00003   2000                François   Gaumont     M   \n",
       "24701  00004   2000                Nathalie     Hache     F   \n",
       "24702  00005   2000               Geneviève     Morin     F   \n",
       "...      ...    ...                     ...       ...   ...   \n",
       "35104  16893   2016               Sébastien     David     M   \n",
       "35105  16894   2016  Guillaume Patrick Jean  Berthier     M   \n",
       "35106  16895   2016                  Miriam    Banoub     F   \n",
       "35107  16896   2016             Anne-Sophie     Lemay     F   \n",
       "35108  16897   2016             Mohamed Ali      Abla     M   \n",
       "\n",
       "               specialite1          specialite2 specialite3           statut  \\\n",
       "24698     Médecine interne          Cardiologie         NaN        Démission   \n",
       "24699             Inconnue                  NaN         NaN       Expiration   \n",
       "24700   Médecine d'urgence  Médecine de famille         NaN  Inscrit - Actif   \n",
       "24701  Médecine de famille                  NaN         NaN  Inscrit - Actif   \n",
       "24702  Médecine de famille                  NaN         NaN  Inscrit - Actif   \n",
       "...                    ...                  ...         ...              ...   \n",
       "35104  Médecine de famille                  NaN         NaN  Inscrit - Actif   \n",
       "35105  Médecine de famille                  NaN         NaN  Inscrit - Actif   \n",
       "35106  Médecine de famille                  NaN         NaN  Inscrit - Actif   \n",
       "35107          Hématologie   Oncologie médicale         NaN  Inscrit - Actif   \n",
       "35108  Médecine de famille                  NaN         NaN  Inscrit - Actif   \n",
       "\n",
       "             date  typePermis        prov        pays  \n",
       "24698  2001-07-01    Régulier  Californie  États-Unis  \n",
       "24699  2001-01-11  Temporaire      Québec      Canada  \n",
       "24700         NaN    Régulier      Québec      Canada  \n",
       "24701         NaN    Régulier      Québec      Canada  \n",
       "24702         NaN    Régulier      Québec      Canada  \n",
       "...           ...         ...         ...         ...  \n",
       "35104         NaN    Régulier      Québec      Canada  \n",
       "35105         NaN  Restrictif      Québec      Canada  \n",
       "35106         NaN    Régulier      Québec      Canada  \n",
       "35107         NaN    Régulier      Québec      Canada  \n",
       "35108         NaN    Régulier      Québec      Canada  \n",
       "\n",
       "[10411 rows x 13 columns]"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "depuis2000 = md.annee >= 2000\n",
    "md[depuis2000]\n",
    "# Ce sous-ensemble compte 10411 médecins"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ensuite, on va identifier les chirurgiens.<br>\n",
    "Ici, on va se servir de la fonction ```.str.contains()``` pour réunir tous les MD dont la spécialité contient l'expression «hirurgie», ce qui permet de repérer autant «C**hirurgie** générale» que «Neuroc**hirurgie**»."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\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>num</th>\n",
       "      <th>annee</th>\n",
       "      <th>prenom</th>\n",
       "      <th>nom</th>\n",
       "      <th>genre</th>\n",
       "      <th>specialite1</th>\n",
       "      <th>specialite2</th>\n",
       "      <th>specialite3</th>\n",
       "      <th>statut</th>\n",
       "      <th>date</th>\n",
       "      <th>typePermis</th>\n",
       "      <th>prov</th>\n",
       "      <th>pays</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>30014</td>\n",
       "      <td>1930</td>\n",
       "      <td>Alphonse</td>\n",
       "      <td>Couturier</td>\n",
       "      <td>M</td>\n",
       "      <td>Chirurgie générale</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>1995-08-11</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>30015</td>\n",
       "      <td>1930</td>\n",
       "      <td>Guy</td>\n",
       "      <td>D'Argencourt</td>\n",
       "      <td>M</td>\n",
       "      <td>Chirurgie générale</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Radié pour non-paiement de cotisation</td>\n",
       "      <td>1988-11-30</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>30063</td>\n",
       "      <td>1930</td>\n",
       "      <td>Arthur M.</td>\n",
       "      <td>Vineberg</td>\n",
       "      <td>M</td>\n",
       "      <td>Chirurgie générale</td>\n",
       "      <td>Chirurgie thoracique</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>1988-03-26</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>30072</td>\n",
       "      <td>1930</td>\n",
       "      <td>Maurice</td>\n",
       "      <td>Berne</td>\n",
       "      <td>M</td>\n",
       "      <td>Oto-rhino-laryngologie / chirurgie cervico-fac...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>1993-06-24</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>30080</td>\n",
       "      <td>1930</td>\n",
       "      <td>C. Emerson</td>\n",
       "      <td>Brooks</td>\n",
       "      <td>M</td>\n",
       "      <td>Chirurgie générale</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Démission</td>\n",
       "      <td>1977-06-30</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35028</th>\n",
       "      <td>16795</td>\n",
       "      <td>2016</td>\n",
       "      <td>Mohamed Akli</td>\n",
       "      <td>Zetchi</td>\n",
       "      <td>M</td>\n",
       "      <td>Neurochirurgie</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35031</th>\n",
       "      <td>16799</td>\n",
       "      <td>2016</td>\n",
       "      <td>Sara</td>\n",
       "      <td>Langlais</td>\n",
       "      <td>F</td>\n",
       "      <td>Chirurgie générale</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35034</th>\n",
       "      <td>16802</td>\n",
       "      <td>2016</td>\n",
       "      <td>Gabrielle</td>\n",
       "      <td>Roy</td>\n",
       "      <td>F</td>\n",
       "      <td>Chirurgie générale</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35060</th>\n",
       "      <td>16838</td>\n",
       "      <td>2016</td>\n",
       "      <td>Hussein</td>\n",
       "      <td>Wissanji</td>\n",
       "      <td>M</td>\n",
       "      <td>Chirurgie générale</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35061</th>\n",
       "      <td>16839</td>\n",
       "      <td>2016</td>\n",
       "      <td>Sébastien</td>\n",
       "      <td>Lachance</td>\n",
       "      <td>M</td>\n",
       "      <td>Chirurgie générale</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3259 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         num  annee        prenom           nom genre  \\\n",
       "7      30014   1930      Alphonse     Couturier     M   \n",
       "8      30015   1930           Guy  D'Argencourt     M   \n",
       "30     30063   1930     Arthur M.      Vineberg     M   \n",
       "33     30072   1930       Maurice         Berne     M   \n",
       "38     30080   1930    C. Emerson        Brooks     M   \n",
       "...      ...    ...           ...           ...   ...   \n",
       "35028  16795   2016  Mohamed Akli        Zetchi     M   \n",
       "35031  16799   2016          Sara      Langlais     F   \n",
       "35034  16802   2016     Gabrielle           Roy     F   \n",
       "35060  16838   2016       Hussein      Wissanji     M   \n",
       "35061  16839   2016     Sébastien      Lachance     M   \n",
       "\n",
       "                                             specialite1  \\\n",
       "7                                     Chirurgie générale   \n",
       "8                                     Chirurgie générale   \n",
       "30                                    Chirurgie générale   \n",
       "33     Oto-rhino-laryngologie / chirurgie cervico-fac...   \n",
       "38                                    Chirurgie générale   \n",
       "...                                                  ...   \n",
       "35028                                     Neurochirurgie   \n",
       "35031                                 Chirurgie générale   \n",
       "35034                                 Chirurgie générale   \n",
       "35060                                 Chirurgie générale   \n",
       "35061                                 Chirurgie générale   \n",
       "\n",
       "                specialite2 specialite3  \\\n",
       "7                       NaN         NaN   \n",
       "8                       NaN         NaN   \n",
       "30     Chirurgie thoracique         NaN   \n",
       "33                      NaN         NaN   \n",
       "38                      NaN         NaN   \n",
       "...                     ...         ...   \n",
       "35028                   NaN         NaN   \n",
       "35031                   NaN         NaN   \n",
       "35034                   NaN         NaN   \n",
       "35060                   NaN         NaN   \n",
       "35061                   NaN         NaN   \n",
       "\n",
       "                                      statut        date typePermis     prov  \\\n",
       "7                         Retrait pour décès  1995-08-11   Régulier   Québec   \n",
       "8      Radié pour non-paiement de cotisation  1988-11-30   Régulier   Québec   \n",
       "30                        Retrait pour décès  1988-03-26   Régulier   Québec   \n",
       "33                        Retrait pour décès  1993-06-24   Régulier   Québec   \n",
       "38                                 Démission  1977-06-30   Régulier   Québec   \n",
       "...                                      ...         ...        ...      ...   \n",
       "35028                        Inscrit - Actif         NaN   Régulier  Ontario   \n",
       "35031                        Inscrit - Actif         NaN   Régulier   Québec   \n",
       "35034                        Inscrit - Actif         NaN   Régulier   Québec   \n",
       "35060                        Inscrit - Actif         NaN   Régulier   Québec   \n",
       "35061                        Inscrit - Actif         NaN   Régulier   Québec   \n",
       "\n",
       "         pays  \n",
       "7      Canada  \n",
       "8      Canada  \n",
       "30     Canada  \n",
       "33     Canada  \n",
       "38     Canada  \n",
       "...       ...  \n",
       "35028  Canada  \n",
       "35031  Canada  \n",
       "35034  Canada  \n",
       "35060  Canada  \n",
       "35061  Canada  \n",
       "\n",
       "[3259 rows x 13 columns]"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chir1 = md.specialite1.str.contains(\"hirurgie\")\n",
    "md[chir1]\n",
    "# On en obtient 3 259"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Il faut également vérifier les médecins dont la 2e ou 3e spécialité est la chirurgie, car on a trois colonnes de spécialités.<br>\n",
    "Il faudra cependant ajouter un paramètre à la fonction ```.str.contains``` qui va faire en sorte d'ignorer les médecins qui n'ont aucune 2e ou 3e spécialité avec l'argument ```na=False```."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>num</th>\n",
       "      <th>annee</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>30042</td>\n",
       "      <td>1930</td>\n",
       "      <td>Marcel</td>\n",
       "      <td>Ostiguy</td>\n",
       "      <td>M</td>\n",
       "      <td>Ophtalmologie</td>\n",
       "      <td>Oto-rhino-laryngologie / chirurgie cervico-fac...</td>\n",
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       "      <th>30</th>\n",
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       "      <td>Retrait pour décès</td>\n",
       "      <td>1988-03-26</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>31050</td>\n",
       "      <td>1931</td>\n",
       "      <td>Gérard</td>\n",
       "      <td>Rolland</td>\n",
       "      <td>M</td>\n",
       "      <td>Chirurgie générale</td>\n",
       "      <td>Chirurgie thoracique</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>1989-10-28</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>31059</td>\n",
       "      <td>1931</td>\n",
       "      <td>L. J.</td>\n",
       "      <td>Tessier</td>\n",
       "      <td>M</td>\n",
       "      <td>Ophtalmologie</td>\n",
       "      <td>Oto-rhino-laryngologie / chirurgie cervico-fac...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>2002-12-26</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>32011</td>\n",
       "      <td>1932</td>\n",
       "      <td>J. A.</td>\n",
       "      <td>Bohemier</td>\n",
       "      <td>M</td>\n",
       "      <td>Ophtalmologie</td>\n",
       "      <td>Oto-rhino-laryngologie / chirurgie cervico-fac...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>1996-04-01</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31776</th>\n",
       "      <td>12698</td>\n",
       "      <td>2012</td>\n",
       "      <td>Heather</td>\n",
       "      <td>Gill</td>\n",
       "      <td>F</td>\n",
       "      <td>Chirurgie générale</td>\n",
       "      <td>Chirurgie vasculaire</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32003</th>\n",
       "      <td>13111</td>\n",
       "      <td>2013</td>\n",
       "      <td>Dominique</td>\n",
       "      <td>Boudreau</td>\n",
       "      <td>F</td>\n",
       "      <td>Chirurgie générale</td>\n",
       "      <td>Chirurgie générale oncologique</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33100</th>\n",
       "      <td>14430</td>\n",
       "      <td>2014</td>\n",
       "      <td>Mireille</td>\n",
       "      <td>Méthot</td>\n",
       "      <td>F</td>\n",
       "      <td>Chirurgie générale</td>\n",
       "      <td>Chirurgie vasculaire</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33151</th>\n",
       "      <td>14481</td>\n",
       "      <td>2014</td>\n",
       "      <td>Ricardo</td>\n",
       "      <td>Ruz</td>\n",
       "      <td>M</td>\n",
       "      <td>Chirurgie générale</td>\n",
       "      <td>Chirurgie vasculaire</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34481</th>\n",
       "      <td>16207</td>\n",
       "      <td>2016</td>\n",
       "      <td>Mai-Kim</td>\n",
       "      <td>Gervais</td>\n",
       "      <td>F</td>\n",
       "      <td>Chirurgie générale</td>\n",
       "      <td>Chirurgie générale oncologique</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>268 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         num  annee     prenom       nom genre         specialite1  \\\n",
       "19     30042   1930     Marcel   Ostiguy     M       Ophtalmologie   \n",
       "30     30063   1930  Arthur M.  Vineberg     M  Chirurgie générale   \n",
       "69     31050   1931     Gérard   Rolland     M  Chirurgie générale   \n",
       "74     31059   1931      L. J.   Tessier     M       Ophtalmologie   \n",
       "99     32011   1932      J. A.  Bohemier     M       Ophtalmologie   \n",
       "...      ...    ...        ...       ...   ...                 ...   \n",
       "31776  12698   2012    Heather      Gill     F  Chirurgie générale   \n",
       "32003  13111   2013  Dominique  Boudreau     F  Chirurgie générale   \n",
       "33100  14430   2014   Mireille    Méthot     F  Chirurgie générale   \n",
       "33151  14481   2014    Ricardo       Ruz     M  Chirurgie générale   \n",
       "34481  16207   2016    Mai-Kim   Gervais     F  Chirurgie générale   \n",
       "\n",
       "                                             specialite2 specialite3  \\\n",
       "19     Oto-rhino-laryngologie / chirurgie cervico-fac...         NaN   \n",
       "30                                  Chirurgie thoracique         NaN   \n",
       "69                                  Chirurgie thoracique         NaN   \n",
       "74     Oto-rhino-laryngologie / chirurgie cervico-fac...         NaN   \n",
       "99     Oto-rhino-laryngologie / chirurgie cervico-fac...         NaN   \n",
       "...                                                  ...         ...   \n",
       "31776                               Chirurgie vasculaire         NaN   \n",
       "32003                     Chirurgie générale oncologique         NaN   \n",
       "33100                               Chirurgie vasculaire         NaN   \n",
       "33151                               Chirurgie vasculaire         NaN   \n",
       "34481                     Chirurgie générale oncologique         NaN   \n",
       "\n",
       "                   statut        date typePermis    prov    pays  \n",
       "19     Retrait pour décès  1994-10-15   Régulier  Québec  Canada  \n",
       "30     Retrait pour décès  1988-03-26   Régulier  Québec  Canada  \n",
       "69     Retrait pour décès  1989-10-28   Régulier  Québec  Canada  \n",
       "74     Retrait pour décès  2002-12-26   Régulier  Québec  Canada  \n",
       "99     Retrait pour décès  1996-04-01   Régulier  Québec  Canada  \n",
       "...                   ...         ...        ...     ...     ...  \n",
       "31776     Inscrit - Actif         NaN   Régulier  Québec  Canada  \n",
       "32003     Inscrit - Actif         NaN   Régulier  Québec  Canada  \n",
       "33100     Inscrit - Actif         NaN   Régulier  Québec  Canada  \n",
       "33151     Inscrit - Actif         NaN   Régulier  Québec  Canada  \n",
       "34481     Inscrit - Actif         NaN   Régulier  Québec  Canada  \n",
       "\n",
       "[268 rows x 13 columns]"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chir2 = md.specialite2.str.contains(\"hirurgie\", na=False)\n",
    "md[chir2]\n",
    "# On obtient ici 268 médecins"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>num</th>\n",
       "      <th>annee</th>\n",
       "      <th>prenom</th>\n",
       "      <th>nom</th>\n",
       "      <th>genre</th>\n",
       "      <th>specialite1</th>\n",
       "      <th>specialite2</th>\n",
       "      <th>specialite3</th>\n",
       "      <th>statut</th>\n",
       "      <th>date</th>\n",
       "      <th>typePermis</th>\n",
       "      <th>prov</th>\n",
       "      <th>pays</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>313</th>\n",
       "      <td>36013</td>\n",
       "      <td>1936</td>\n",
       "      <td>J. Ernest</td>\n",
       "      <td>Bousquet</td>\n",
       "      <td>M</td>\n",
       "      <td>Chirurgie thoracique</td>\n",
       "      <td>Pneumologie</td>\n",
       "      <td>Chirurgie générale</td>\n",
       "      <td>Retrait pour décès</td>\n",
       "      <td>1983-11-06</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10671</th>\n",
       "      <td>74293</td>\n",
       "      <td>1974</td>\n",
       "      <td>Pierre</td>\n",
       "      <td>Michaud</td>\n",
       "      <td>M</td>\n",
       "      <td>Chirurgie générale</td>\n",
       "      <td>Chirurgie thoracique</td>\n",
       "      <td>Chirurgie vasculaire</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12161</th>\n",
       "      <td>76365</td>\n",
       "      <td>1976</td>\n",
       "      <td>Louise</td>\n",
       "      <td>Choiniere</td>\n",
       "      <td>F</td>\n",
       "      <td>Chirurgie générale</td>\n",
       "      <td>Chirurgie cardio-vasculaire et thoracique</td>\n",
       "      <td>Chirurgie thoracique</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16006</th>\n",
       "      <td>82154</td>\n",
       "      <td>1982</td>\n",
       "      <td>Rosaire</td>\n",
       "      <td>Vaillancourt</td>\n",
       "      <td>M</td>\n",
       "      <td>Chirurgie générale</td>\n",
       "      <td>Chirurgie cardio-vasculaire et thoracique</td>\n",
       "      <td>Chirurgie thoracique</td>\n",
       "      <td>Inscrit - Actif</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Régulier</td>\n",
       "      <td>Québec</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         num  annee     prenom           nom genre           specialite1  \\\n",
       "313    36013   1936  J. Ernest      Bousquet     M  Chirurgie thoracique   \n",
       "10671  74293   1974     Pierre       Michaud     M    Chirurgie générale   \n",
       "12161  76365   1976     Louise     Choiniere     F    Chirurgie générale   \n",
       "16006  82154   1982    Rosaire  Vaillancourt     M    Chirurgie générale   \n",
       "\n",
       "                                     specialite2           specialite3  \\\n",
       "313                                  Pneumologie    Chirurgie générale   \n",
       "10671                       Chirurgie thoracique  Chirurgie vasculaire   \n",
       "12161  Chirurgie cardio-vasculaire et thoracique  Chirurgie thoracique   \n",
       "16006  Chirurgie cardio-vasculaire et thoracique  Chirurgie thoracique   \n",
       "\n",
       "                   statut        date typePermis    prov    pays  \n",
       "313    Retrait pour décès  1983-11-06   Régulier  Québec  Canada  \n",
       "10671     Inscrit - Actif         NaN   Régulier  Québec  Canada  \n",
       "12161     Inscrit - Actif         NaN   Régulier  Québec  Canada  \n",
       "16006     Inscrit - Actif         NaN   Régulier  Québec  Canada  "
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chir3 = md.specialite3.str.contains(\"hirurgie\", na=False)\n",
    "md[chir3]\n",
    "# Quatre médecins dans ce sous-ensemble"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Si on veut les réunir tous et y voir la répartition homme/femme, la formule ci-dessous les combine de la façon suivante&nbsp;:\n",
    "\n",
    "Médecins actifs **ET**<br>\n",
    "pratiquant au Québec **ET**<br>\n",
    "depuis 2000 **ET**<br>\n",
    "dont la spécialité&nbsp;1 **OU** la spécialité&nbsp;2 **OU** la spécialité&nbsp;3 est une forme ou une autre de chirurgie."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "M    482\n",
       "F    280\n",
       "Name: genre, dtype: int64"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "md[actifs & qc & depuis2000 & (chir1 | chir2 | chir3)].genre.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Au tout début de notre carnet, on a importé cette bibliothèque au nom affeux, **matplotlib**.<br>\n",
    "On va s'en servir pour créer des graphiques. Pour ce faire, il suffit d'ajouter la fonction ```.plot()``` à la fin d'une formule."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x118e64278>"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "md[famille & actifs].genre.value_counts().plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ce n'est pas très évocateur. On peut heureusement changer le type de graphique pour, par exemple, choisir un graphique en pointes de tarte. Il suffit d'ajouter, à la fonction ```.plot()``` l'argument ```kind``` auquel on donne la valeur de ```pie```.<br>\n",
    "On peut aussi donner un titre à notre graphique avec l'argument ```title```."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x118ea5198>"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "md[famille & actifs].genre.value_counts().plot(kind=\"pie\", title=\"Majorité de femmes médecin de famille au Québec\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Un autre type de graphique intéressant est l'histogramme.<br>\n",
    "Pour tracer l'évolution du nombre de médecins ayant intégré la profession médicale au cours des ans, on pourrait faire un histogramme de notre tableau ```md``` en fonction de la colonne ```annee``` avec la formule suivante&nbsp;:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1172bc4e0>"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "md.annee.hist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mais voilà qui ne raconte pas grand-chose. C'est que par défaut, l'histogramme trace 10 barres, ce qui fait que chaque barre de notre histogramme regroupe 7 ou 8 années.<br>\n",
    "Les barres, c'est que ce matplotlib appelle des *«bins»*. On peut ainsi spécifier le nombre de ces *bins* avec un argument qui s'appelle... vous l'aurez deviné... ```bins```\n",
    "\n",
    "Ici, comme nos données couvrent 87 années, on va créer 87 barres.<br>\n",
    "Chacune représente le nombre de médecins qui ont obtenu leur permis de pratique au cours d'une année donnée."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1194ec940>"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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DP1uvWvpb79f/W7JNRIwAIwCDg4NRKpUaCaXrlctlemVdmnH3DOP521df4v6xbHM7uaXU8POKoLpt2mnaz2HsYtVM544p6VTbtFP159CMcrmcWwxNtXBEvCqpDKwDFktaEBGXgBXA6VRtAlgJTEhaACwCXsktYusa3plr1htm3Ecg6b2pJ4CkhcAvA8eBJ4DbU7WtwL40vT/Nk5Z/PRoZf7KuNHl9IH/pm/WuRnoEy4A9aT/B24CHI+JRSc8Co5J+F/g2sDvV3w38saRxsp7AHS2I28zMcjJjIoiIo8DP1Sl/AbihTvkPgc25RGc9yb0Ls+7iS0yYmRWcE4GZWcE5EZiZFVxvH6BrTfP4vVnxOBFYw5wkzHqTh4bMzArOicDMrOCcCMzMCs77CAqienzfd58ys2ruEZiZFZwTgZlZwTkRmJkVnPcRmM8PMCs49wjMzArOPYIe5V/5ZtYo9wjMzAqukVtVrpT0hKTjkp6RdF8qXyrpgKQT6e+SVC5JD0oal3RU0ppWr4SZmc1eIz2CS8D2iPhZspvW3yvpA8BO4GBErAIOpnmAW4FV6TEMPJR71GZmlpsZE0FEnImIp9L0D8huXL8c2AjsSdX2AJvS9EZgb2QOAYslLcs9cjMzy0VT+wgkDZDdv/hJoD8izkCWLICrU7XlwPeqnjaRyszMrAs1fNSQpD7gT4GPR8T3JU1ZtU5Z1Hm9YbKhI/r7+ymXy42G0tUqlUpXrMv21ZemXFYb33R189K/sD3vMx91qm2qt4Nu/WyKsN3M9vuiUqnkFkNDiUDS28mSwBci4kup+KykZRFxJg39nEvlE8DKqqevAE7XvmZEjAAjAIODg1EqlWa3Bl2mXC7TDety9zSHj57cUmq4bl62r77E/WM+WrmeTrVN9XbQjm1gNoqw3dT+PzYqzx+cjRw1JGA3cDwifq9q0X5ga5reCuyrKr8rHT20DrgwOYRkZmbdp5FU+yHgTmBM0tOp7F8Au4CHJW0DXgQ2p2WPAxuAceA14J5cI7Y588lmZlZtxkQQEd+k/rg/wPo69QO4d45xmZlZm/T24FuPq/1l7xvOmNls+BITZmYF5x5BD/HYv5nNhnsEZmYF5x5Bh/hm8mbWLdwjMDMrOCcCM7OCcyIwMys4JwIzs4JzIjAzKzgnAjOzgvPho13Ol5GwVvEJiDbJPQIzs4JzIjAzKzgnAjOzgnMiMDMrOCcCM7OCa+SexZ+XdE7SsaqypZIOSDqR/i5J5ZL0oKRxSUclrWll8GZmNneN9Aj+M3BLTdlO4GBErAIOpnmAW4FV6TEMPJRPmGZm1iozJoKI+AbwSk3xRmBPmt4DbKoq3xuZQ8BiScvyCtbMzPKn7F7zM1SSBoBHI+LaNP9qRCyuWn4+IpZIehTYlW54j6SDwI6IOFznNYfJeg309/evHR0dzWF1Oq9SqdDX1zdjvbFTF348vXr5oobq1datXdbN+hfC2dc7HUV3cttMrQhtM93//3QqlQpDQ0NHImJwrjHkfWax6pTVzTQRMQKMAAwODkapVMo5lM4ol8tMrst0N5+5u/qszrGL07ziT35EJ7eU6r9Gl9u++hL3j/lE9nrcNlMrQttU/083o1wu5xbDbFv4rKRlEXEmDf2cS+UTwMqqeiuA03MJ0H6SLwtgZnmb7eGj+4GtaXorsK+q/K509NA64EJEnJljjGZm1kIz9ggkfREoAVdJmgA+BewCHpa0DXgR2JyqPw5sAMaB14B7WhBz1xrY+RjbV1+aV0M2ZmYzJoKI+OgUi9bXqRvAvXMNyszM2sdnFpuZFZwTgZlZwfX2cVnTaOaGL9MdqdPojWJ8tI+ZdavCJoLp+EvbzIrEiSDxl7+ZFZUTwRw5gZjZfNdziWC6yzr4S9vM7K181JCZWcE5EZiZFdy8HxqabrjHQ0FmZjNzj8DMrOCcCMzMCs6JwMys4JwIzMwKzonAzKzgnAjMzAquJYlA0i2SviNpXNLOVryHmZnlI/dEIOky4A+BW4EPAB+V9IG838fMzPLRih7BDcB4RLwQEW8Ao8DGFryPmZnlQNlthnN8Qel24JaI+I00fydwY0T8Zk29YWA4zb4f+E6ugXTOVcBLnQ6iC7ldpua2mZrbZmpXAVdGxHvn+kKtuMSE6pS9JdtExAgw0oL37yhJhyNisNNxdBu3y9TcNlNz20wttc1AHq/ViqGhCWBl1fwK4HQL3sfMzHLQikTwLWCVpGskXQ7cAexvwfuYmVkOch8aiohLkn4T+BpwGfD5iHgm7/fpYj033JUTt8vU3DZTc9tMLbe2yX1nsZmZzS8+s9jMrOCcCMzMCs6JYAaSPi/pnKRjVWXXSfoLSWOS/rukd9c856ckVSR9oqqs5y670WzbSPpgWvZMWv7OVL42zY9LelBSvUOQ55Vm2kbS2yXtSeXHJX2y6jk9td1IWinpibSez0i6L5UvlXRA0on0d0kqV9omxiUdlbSm6rW2pvonJG3t1DrlZRZtsyW1yVFJfy7puqrXam67iQg/pnkAvwisAY5VlX0L+KU0/THg39Q850+BPwE+keYvA54Hfhq4HPhL4AOdXrd2tg3ZgQlHgevS/HuAy9L0/wJ+nuwclK8At3Z63drcNr8OjKbpK4CTwEAvbjfAMmBNmn4X8F2yS9F8BtiZyncCn07TG9I2IWAd8GQqXwq8kP4uSdNLOr1+bW6bX5hcZ7JL+ky2TdPbjXsEM4iIbwCv1BS/H/hGmj4A/MPJBZI2kW2U1UdK9eRlN5psmw8DRyPiL9NzX46IH0laBrw7Iv4isq14L7Cp9dG3VpNtE8CVkhYAC4E3gO/Tg9tNRJyJiKfS9A+A48BysvXak6rt4c1tYCOwNzKHgMVpm/kV4EBEvBIR58na85Y2rkrumm2biPjztO4Ah8jO2YJZbDdOBLNzDPhImt5MOoFO0pXADuB3auovB75XNT+RynpR3bYBfgYISV+T9JSkf57Kl5O1x6Qits0jwEXgDPAi8B8j4hV6fLuRNAD8HPAk0B8RZyD7QgSuTtWmagO3zU/aRtZzglm0jRPB7HwMuFfSEbIu3Bup/HeAByKiUlO/octu9Iip2mYB8HeALenvP5C0HrcNZL/gfgT8LeAaYLukn6aH20ZSH9kQ6scj4vvTVa1TFtOUz3tNtM1k/ZvIEsGOyaI61aZtm1Zca6jnRcRzZEMdSPoZ4La06EbgdkmfARYD/0/SD4EjFOSyG9O0zQTwPyLipbTscbIx9P/Cm11aKGbb/Drw1Yj4G+CcpP8JDJL9quu57UbS28m+6L4QEV9KxWclLYuIM2no51wqn+qSNRNAqaa83Mq426HJtkHSB4HPke1XezkVN32ZH/cIZkHS1env24B/BfwRQET83YgYiOxCUL8P/LuI+CwFuuzGVG1Ddqb5ByVdkcbCfwl4NnV1fyBpXTpa6C5gXwdCb7lp2uZF4OZ0hMyVZDtFn6MHt5v0Ge8GjkfE71Ut2g9MHvmzlTe3gf3AXalt1gEX0jbzNeDDkpako2g+nMrmrWbbRtJPAV8C7oyI71bVb3676fSe8m5/AF8kG7v9G7JMuw24j2yP/neBXaQztGue969JRw2l+Q2p/vPAv+z0enWibYB/RLYT/RjwmarywVT2PPDZeu053x7NtA3QR3aU2TPAs8A/69XthmxYMMiOIHs6PTaQHUV2EDiR/i5N9UV2o6vngTFgsOq1PgaMp8c9nV63DrTN54DzVXUPz3a78SUmzMwKzkNDZmYF50RgZlZwTgRmZgXnRGBmVnBOBGZmBedEYGZWcE4EZmYF9/8BgbEvOKANjFMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "md.annee.hist(bins=87)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Il remarque une chute au début des années 1990. Elle correspond à une politique du gouvernement québécois qui avait limité le nombre d'inscriptions dans les facultés de médecine quelques années auparavant.\n",
    "\n",
    "Inspiré par ce graphique, vous pourriez avoir envie de voir combien d'hommes et de femmes sont devenus médecin au fil des ans afin de visualiser la féminisation de la profession médicale. Pour ce faire, il suffirait de modifier la formule ci-dessus en ajoutant un ```groupby``` par ```genre```, puis l'argument ```alpha``` à la fonction ```.hist()``` pour faire en sorte que nos barres aient une transparence de 50%."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "genre\n",
       "F    AxesSubplot(0.125,0.125;0.775x0.755)\n",
       "M    AxesSubplot(0.125,0.125;0.775x0.755)\n",
       "Name: annee, dtype: object"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "md.groupby(\"genre\").annee.hist(bins=87,alpha=0.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Le graphique ci-dessus raconte une histoire avec les données.\n",
    "\n",
    "On y voit que jusqu'en 1970, les hommes (en jaune) étaient clairement majoritaires dans la profession.<br>\n",
    "À partir de 1970 semble s'opérer un renversement. Le nombre d'hommes diminue progressivement pour, dès 1990, devenir inférieur au nombre de femmes (en bleu).<br>\n",
    "Aujourd'hui, les deux tiers des recrues, en médecine, chaque année, sont des femmes.\n",
    "\n",
    "-----"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "En terminant, faisons aussi un graphique avec nos données de contrats.<br>\n",
    "Calculons la somme des contrats octroyés chaque année, créons un diagramme à barres horizontales (```kind=\"barh\"```) et donnons une couleur de camouflage (*teal*) à nos barres."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1175088d0>"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "mil.groupby(\"annee\").montant.sum().plot(kind=\"barh\",color=\"teal\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Voilà! J'espère que, grâce à pandas, vous aurez un peu de plaisir à explorer vos données!"
   ]
  },
  {
   "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": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}