{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Manipulation de données avec pandas (exercices)\n",
    "\n",
    "[pandas](https://pandas.pydata.org/) est la librairie incontournable pour manipuler les données. Elle permet de manipuler aussi bien les données sous forme de tables qu'elle peut récupérer ou exporter en différents formats. Elle permet également de créer facilement des graphes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Enoncé\n",
    "\n",
    "La librairie [pandas](https://pandas.pydata.org/) implémente la classe [DataFrame](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html). C'est une structure de table, chaque colonne porte un nom et contient un seul type de données. C'est très similaire au langage [SQL](https://fr.wikipedia.org/wiki/Structured_Query_Language)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Création d'un dataframe\n",
    "\n",
    "Il existe une grande variété pour créer un DataFrame. Voici les deux principaux. Le premier : une liste de dictionnaires. Chaque clé est le nom de la colonne."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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>col1</th>\n",
       "      <th>col2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.5</td>\n",
       "      <td>schtroumph</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.6</td>\n",
       "      <td>schtroumphette</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   col1            col2\n",
       "0   0.5      schtroumph\n",
       "1   0.6  schtroumphette"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pandas import DataFrame\n",
    "\n",
    "rows = [{\"col1\": 0.5, \"col2\": \"schtroumph\"}, {\"col1\": 0.6, \"col2\": \"schtroumphette\"}]\n",
    "DataFrame(rows)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "La lecture depuis un fichier :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "text = \"\"\"col1,col2\n",
    "0.5,alpha\n",
    "0.6,beta\n",
    "\"\"\"\n",
    "\n",
    "with open(\"data.csv\", \"w\", encoding=\"utf-8\") as f:\n",
    "    f.write(text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>col1</th>\n",
       "      <th>col2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.5</td>\n",
       "      <td>alpha</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.6</td>\n",
       "      <td>beta</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   col1   col2\n",
       "0   0.5  alpha\n",
       "1   0.6   beta"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pandas import read_csv\n",
    "\n",
    "df = read_csv(\"data.csv\")\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### La maîtrise des index\n",
    "\n",
    "Les index fonctionnent à peu près comme [numpy](https://numpy.org/) mais offre plus d'options puisque les colonnes mais aussi les lignes ont un nom.\n",
    "\n",
    "Accès par colonne"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>col1</th>\n",
       "      <th>col2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.5</td>\n",
       "      <td>alpha</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.6</td>\n",
       "      <td>beta</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   col1   col2\n",
       "0   0.5  alpha\n",
       "1   0.6   beta"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    0.5\n",
       "1    0.6\n",
       "Name: col1, dtype: float64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"col1\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Les colonnes disponibles :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['col1', 'col2'], dtype='object')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>col1</th>\n",
       "      <th>col2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.5</td>\n",
       "      <td>alpha</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.6</td>\n",
       "      <td>beta</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   col1   col2\n",
       "0   0.5  alpha\n",
       "1   0.6   beta"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[[\"col1\", \"col2\"]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Accès par ligne (uniquement avec ``:``). On se sert principalement de l'opérateur ``:`` pour les lignes."
   ]
  },
  {
   "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>col1</th>\n",
       "      <th>col2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.5</td>\n",
       "      <td>alpha</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   col1   col2\n",
       "0   0.5  alpha"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[:1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Accès par positions avec [loc](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.loc.html)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[0, \"col1\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Accès par positions entières avec [iloc](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.iloc.html)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[0, 0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### La maîtrise des index des lignes\n",
    "\n",
    "La création d'un dataframe donne l'impression que les index des lignes sont des entiers mais cela peut être changer"
   ]
  },
  {
   "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>col1</th>\n",
       "      <th>col2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.5</td>\n",
       "      <td>alpha</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.6</td>\n",
       "      <td>beta</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   col1   col2\n",
       "0   0.5  alpha\n",
       "1   0.6   beta"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>col1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>col2</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>alpha</th>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beta</th>\n",
       "      <td>0.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       col1\n",
       "col2       \n",
       "alpha   0.5\n",
       "beta    0.6"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfi = df.set_index(\"col2\")\n",
    "dfi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfi.loc[\"alpha\", \"col1\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Il faut se souvenir de cette particularité lors de la fusion de tables."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### La maîtrise des index des colonnes\n",
    "\n",
    "Les colonnes sont nommées."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['col1', 'col2'], dtype='object')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On peut les renommer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>valeur</th>\n",
       "      <th>nom</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.5</td>\n",
       "      <td>alpha</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.6</td>\n",
       "      <td>beta</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   valeur    nom\n",
       "0     0.5  alpha\n",
       "1     0.6   beta"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns = [\"valeur\", \"nom\"]\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "L'opérateur ``:`` peut également servir pour les colonnes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>valeur</th>\n",
       "      <th>nom</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.5</td>\n",
       "      <td>alpha</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.6</td>\n",
       "      <td>beta</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   valeur    nom\n",
       "0     0.5  alpha\n",
       "1     0.6   beta"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[:, \"valeur\":\"nom\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Lien vers numpy\n",
    "\n",
    "[pandas](https://pandas.pydata.org/) utilise [numpy](https://numpy.org/) pour stocker les données. Il est possible de récupérer des matrices depuis des DataFrame avec [values](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.values.html)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.5, 'alpha'],\n",
       "       [0.6, 'beta']], dtype=object)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.5],\n",
       "       [0.6]])"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[[\"valeur\"]].values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### La maîtrise du nan\n",
    "\n",
    "[nan](https://numpy.org/doc/stable/reference/constants.html) est une convention pour désigner une valeur manquante."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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>col1</th>\n",
       "      <th>col2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.5</td>\n",
       "      <td>schtroumph</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>schtroumphette</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   col1            col2\n",
       "0   0.5      schtroumph\n",
       "1   NaN  schtroumphette"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rows = [{\"col1\": 0.5, \"col2\": \"schtroumph\"}, {\"col2\": \"schtroumphette\"}]\n",
    "DataFrame(rows)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### La maîtrise des types\n",
    "\n",
    "Un dataframe est défini par ses dimensions et chaque colonne a un type potentiellement différent."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "valeur    float64\n",
       "nom        object\n",
       "dtype: object"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On peut changer un type, donc convertir toutes les valeurs d'une colonne vers un autre type."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    0.5\n",
       "1    0.6\n",
       "Name: valeur, dtype: float32"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy\n",
    "\n",
    "df[\"valeur\"].astype(numpy.float32)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    0\n",
       "1    0\n",
       "Name: valeur, dtype: int32"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy\n",
    "\n",
    "df[\"valeur\"].astype(numpy.int32)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Création de colonnes\n",
    "\n",
    "On peut facilement créer de nouvelles colonnes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>valeur</th>\n",
       "      <th>nom</th>\n",
       "      <th>sup055</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.5</td>\n",
       "      <td>alpha</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.6</td>\n",
       "      <td>beta</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   valeur    nom  sup055\n",
       "0     0.5  alpha   False\n",
       "1     0.6   beta    True"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"sup055\"] = df[\"valeur\"] >= 0.55\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "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>valeur</th>\n",
       "      <th>nom</th>\n",
       "      <th>sup055</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.5</td>\n",
       "      <td>alpha</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.6</td>\n",
       "      <td>beta</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   valeur    nom  sup055\n",
       "0     0.5  alpha       0\n",
       "1     0.6   beta       1"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"sup055\"] = (df[\"valeur\"] >= 0.55).astype(numpy.int64)\n",
    "df"
   ]
  },
  {
   "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>valeur</th>\n",
       "      <th>nom</th>\n",
       "      <th>sup055</th>\n",
       "      <th>sup055+</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.5</td>\n",
       "      <td>alpha</td>\n",
       "      <td>0</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.6</td>\n",
       "      <td>beta</td>\n",
       "      <td>1</td>\n",
       "      <td>1.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   valeur    nom  sup055  sup055+\n",
       "0     0.5  alpha       0      0.5\n",
       "1     0.6   beta       1      1.6"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"sup055+\"] = df[\"valeur\"] + df[\"sup055\"]\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Modifications de valeurs\n",
    "\n",
    "On peut les modifier une à une en utilisant les index. Les notations sont souvent intuitives. Elles ne seront pas toutes détaillées. Ci-dessous un moyen de modifer certaines valeurs selon une condition."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "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>valeur</th>\n",
       "      <th>nom</th>\n",
       "      <th>sup055</th>\n",
       "      <th>sup055+</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.5</td>\n",
       "      <td>alpha</td>\n",
       "      <td>0</td>\n",
       "      <td>1000.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.6</td>\n",
       "      <td>beta</td>\n",
       "      <td>1</td>\n",
       "      <td>1.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   valeur    nom  sup055  sup055+\n",
       "0     0.5  alpha       0   1000.5\n",
       "1     0.6   beta       1      1.6"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[df[\"nom\"] == \"alpha\", \"sup055+\"] += 1000\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Une erreur ou warning fréquent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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>col1</th>\n",
       "      <th>col2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.5</td>\n",
       "      <td>schtroumph</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.5</td>\n",
       "      <td>schtroumphette</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   col1            col2\n",
       "0   0.5      schtroumph\n",
       "1   1.5  schtroumphette"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rows = [{\"col1\": 0.5, \"col2\": \"schtroumph\"}, {\"col1\": 1.5, \"col2\": \"schtroumphette\"}]\n",
    "df = DataFrame(rows)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "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>col1</th>\n",
       "      <th>col2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.5</td>\n",
       "      <td>schtroumphette</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   col1            col2\n",
       "1   1.5  schtroumphette"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = df[df[\"col1\"] > 1.0]\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_5653/164517544.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df1[\"col3\"] = df1[\"col1\"] + 1.0\n"
     ]
    },
    {
     "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>col1</th>\n",
       "      <th>col2</th>\n",
       "      <th>col3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.5</td>\n",
       "      <td>schtroumphette</td>\n",
       "      <td>2.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   col1            col2  col3\n",
       "1   1.5  schtroumphette   2.5"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "try:\n",
    "    df1[\"col3\"] = df1[\"col1\"] + 1.0\n",
    "except Exception as e:\n",
    "    # un warning ou une exception selon la version de pandas installée\n",
    "    print(e)\n",
    "df1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "``A value is trying to be set on a copy of a slice from a DataFrame.`` : Par défaut, l'instruction ``df[df['col1'] > 1.]`` ne crée pas un nouveau DataFrame, elle crée ce qu'on appelle une vue pour éviter de copier les données. Le résultat ne contient que l'index des lignes qui ont été sélectionnées et un lien vers le dataframe original. L'avertissement stipule que *pandas* ne peut pas modifier le dataframe original mais qu'il doit effectuer une copie."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "La solution pour faire disparaître ce warning est de copier le dataframe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = df1.copy()\n",
    "df2[\"col3\"] = df2[\"col1\"] + 1.0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### La maîtrise des fonctions\n",
    "\n",
    "Les fonctions de pandas créent par défaut un nouveau dataframe plutôt que de modifier un dataframe existant. Cela explique pourquoi parfois la mémoire se retrouve congestionnée. La page [10 minutes to pandas](https://pandas.pydata.org/pandas-docs/stable/user_guide/10min.html) est un bon début.\n",
    "\n",
    "* **création** : [read_csv](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html), [read_excel](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_excel.html)\n",
    "* **index** : [set_index](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.set_index.html), [reset_index](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.reset_index.html)\n",
    "* **utilitaires** : [astype](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.astype.html), [isna](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.isna.html), [fillna](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.fillna.html), [to_datetime](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.to_datetime.html), [dtypes](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.dtypes.html), [shape](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.shape.html), [values](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.values.html), [head](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.head.html), [tail](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.tail.html), [isin](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.isin.html), [T](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.T.html), [drop](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.drop.html)\n",
    "* **concaténation** : [concat](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.concat.html)\n",
    "* **SQL** : [filter](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.filter.html), [groupby](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.groupby.html), [join](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.join.html), [merge](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.merge.html), [pivot](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.pivot.html), [pivot_table](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.pivot_table.html)\n",
    "* **calcul** : [sum](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.sum.html), [cumsum](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.cumsum.html), [quantile](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.quantile.html), [var](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.var.html)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### On récupère les données du COVID par région et par âge et premier graphe\n",
    "\n",
    "A cette adresse : [Données hospitalières relatives à l'épidémie de COVID-19](https://www.data.gouv.fr/en/datasets/donnees-hospitalieres-relatives-a-lepidemie-de-covid-19/)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "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>reg</th>\n",
       "      <th>cl_age90</th>\n",
       "      <th>jour</th>\n",
       "      <th>hosp</th>\n",
       "      <th>rea</th>\n",
       "      <th>HospConv</th>\n",
       "      <th>SSR_USLD</th>\n",
       "      <th>autres</th>\n",
       "      <th>rad</th>\n",
       "      <th>dc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>219577</th>\n",
       "      <td>94</td>\n",
       "      <td>59</td>\n",
       "      <td>2023-03-31</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>387</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219578</th>\n",
       "      <td>94</td>\n",
       "      <td>69</td>\n",
       "      <td>2023-03-31</td>\n",
       "      <td>16</td>\n",
       "      <td>1</td>\n",
       "      <td>8.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>536</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219579</th>\n",
       "      <td>94</td>\n",
       "      <td>79</td>\n",
       "      <td>2023-03-31</td>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>14.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>810</td>\n",
       "      <td>129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219580</th>\n",
       "      <td>94</td>\n",
       "      <td>89</td>\n",
       "      <td>2023-03-31</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>888</td>\n",
       "      <td>199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219581</th>\n",
       "      <td>94</td>\n",
       "      <td>90</td>\n",
       "      <td>2023-03-31</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>388</td>\n",
       "      <td>121</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        reg  cl_age90        jour  hosp  rea  HospConv  SSR_USLD  autres  rad  \\\n",
       "219577   94        59  2023-03-31     1    0       0.0       1.0     0.0  387   \n",
       "219578   94        69  2023-03-31    16    1       8.0       5.0     2.0  536   \n",
       "219579   94        79  2023-03-31    29    1      14.0      13.0     1.0  810   \n",
       "219580   94        89  2023-03-31    35    0      24.0      11.0     0.0  888   \n",
       "219581   94        90  2023-03-31    18    0       6.0      12.0     0.0  388   \n",
       "\n",
       "         dc  \n",
       "219577   14  \n",
       "219578   48  \n",
       "219579  129  \n",
       "219580  199  \n",
       "219581  121  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# https://www.data.gouv.fr/en/datasets/r/63352e38-d353-4b54-bfd1-f1b3ee1cabd7\n",
    "from pandas import read_csv\n",
    "\n",
    "url = \"https://www.data.gouv.fr/en/datasets/r/08c18e08-6780-452d-9b8c-ae244ad529b3\"\n",
    "covid = read_csv(url, sep=\";\")\n",
    "covid.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "reg           int64\n",
       "cl_age90      int64\n",
       "jour         object\n",
       "hosp          int64\n",
       "rea           int64\n",
       "HospConv    float64\n",
       "SSR_USLD    float64\n",
       "autres      float64\n",
       "rad           int64\n",
       "dc            int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "covid.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Les dates sont considérées comme des chaînes de caractères. Il est plus simple pour réaliser des opérations de convertir la colonne sous forme de dates."
   ]
  },
  {
   "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>reg</th>\n",
       "      <th>cl_age90</th>\n",
       "      <th>jour</th>\n",
       "      <th>hosp</th>\n",
       "      <th>rea</th>\n",
       "      <th>HospConv</th>\n",
       "      <th>SSR_USLD</th>\n",
       "      <th>autres</th>\n",
       "      <th>rad</th>\n",
       "      <th>dc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>219577</th>\n",
       "      <td>94</td>\n",
       "      <td>59</td>\n",
       "      <td>2023-03-31</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>387</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219578</th>\n",
       "      <td>94</td>\n",
       "      <td>69</td>\n",
       "      <td>2023-03-31</td>\n",
       "      <td>16</td>\n",
       "      <td>1</td>\n",
       "      <td>8.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>536</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219579</th>\n",
       "      <td>94</td>\n",
       "      <td>79</td>\n",
       "      <td>2023-03-31</td>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>14.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>810</td>\n",
       "      <td>129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219580</th>\n",
       "      <td>94</td>\n",
       "      <td>89</td>\n",
       "      <td>2023-03-31</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>888</td>\n",
       "      <td>199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219581</th>\n",
       "      <td>94</td>\n",
       "      <td>90</td>\n",
       "      <td>2023-03-31</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>388</td>\n",
       "      <td>121</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        reg  cl_age90       jour  hosp  rea  HospConv  SSR_USLD  autres  rad  \\\n",
       "219577   94        59 2023-03-31     1    0       0.0       1.0     0.0  387   \n",
       "219578   94        69 2023-03-31    16    1       8.0       5.0     2.0  536   \n",
       "219579   94        79 2023-03-31    29    1      14.0      13.0     1.0  810   \n",
       "219580   94        89 2023-03-31    35    0      24.0      11.0     0.0  888   \n",
       "219581   94        90 2023-03-31    18    0       6.0      12.0     0.0  388   \n",
       "\n",
       "         dc  \n",
       "219577   14  \n",
       "219578   48  \n",
       "219579  129  \n",
       "219580  199  \n",
       "219581  121  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pandas import to_datetime\n",
    "\n",
    "covid[\"jour\"] = to_datetime(covid[\"jour\"])\n",
    "covid.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "reg                  int64\n",
       "cl_age90             int64\n",
       "jour        datetime64[ns]\n",
       "hosp                 int64\n",
       "rea                  int64\n",
       "HospConv           float64\n",
       "SSR_USLD           float64\n",
       "autres             float64\n",
       "rad                  int64\n",
       "dc                   int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "covid.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On supprime les colonnes relatives aux régions et à l'âge puis on aggrège par jour."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "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>hosp</th>\n",
       "      <th>rea</th>\n",
       "      <th>HospConv</th>\n",
       "      <th>SSR_USLD</th>\n",
       "      <th>autres</th>\n",
       "      <th>rad</th>\n",
       "      <th>dc</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>jour</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-03-27</th>\n",
       "      <td>26110</td>\n",
       "      <td>1452</td>\n",
       "      <td>14586.0</td>\n",
       "      <td>9311.0</td>\n",
       "      <td>761.0</td>\n",
       "      <td>1717663</td>\n",
       "      <td>271176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-28</th>\n",
       "      <td>26239</td>\n",
       "      <td>1435</td>\n",
       "      <td>14707.0</td>\n",
       "      <td>9336.0</td>\n",
       "      <td>761.0</td>\n",
       "      <td>1718630</td>\n",
       "      <td>271254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-29</th>\n",
       "      <td>26255</td>\n",
       "      <td>1465</td>\n",
       "      <td>14704.0</td>\n",
       "      <td>9323.0</td>\n",
       "      <td>763.0</td>\n",
       "      <td>1719634</td>\n",
       "      <td>271322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-30</th>\n",
       "      <td>26253</td>\n",
       "      <td>1460</td>\n",
       "      <td>14680.0</td>\n",
       "      <td>9344.0</td>\n",
       "      <td>769.0</td>\n",
       "      <td>1720370</td>\n",
       "      <td>271394</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-31</th>\n",
       "      <td>26174</td>\n",
       "      <td>1413</td>\n",
       "      <td>14658.0</td>\n",
       "      <td>9354.0</td>\n",
       "      <td>749.0</td>\n",
       "      <td>1721380</td>\n",
       "      <td>271456</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             hosp   rea  HospConv  SSR_USLD  autres      rad      dc\n",
       "jour                                                                \n",
       "2023-03-27  26110  1452   14586.0    9311.0   761.0  1717663  271176\n",
       "2023-03-28  26239  1435   14707.0    9336.0   761.0  1718630  271254\n",
       "2023-03-29  26255  1465   14704.0    9323.0   763.0  1719634  271322\n",
       "2023-03-30  26253  1460   14680.0    9344.0   769.0  1720370  271394\n",
       "2023-03-31  26174  1413   14658.0    9354.0   749.0  1721380  271456"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agg_par_jour = covid.drop([\"reg\", \"cl_age90\"], axis=1).groupby(\"jour\").sum()\n",
    "agg_par_jour.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "agg_par_jour.plot(title=\"Evolution des hospitalisations par jour\", figsize=(14, 4));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Avec échelle logarithmique."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "agg_par_jour.plot(\n",
    "    title=\"Evolution des hospitalisations par jour\", figsize=(14, 4), logy=True\n",
    ");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Q1 : refaire le graphique précédent pour votre classe d'âge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Q2 : faire de même avec les séries différenciées"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Q3 : faire de même avec des séries lissées sur sur 7 jours"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Q4 : fusion de tables par départements"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Réponses"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Q1 : refaire le graphique précédent pour votre classe d'âge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{0, 9, 19, 29, 39, 49, 59, 69, 79, 89, 90}"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "set(covid[\"cl_age90\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "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>hosp</th>\n",
       "      <th>rea</th>\n",
       "      <th>HospConv</th>\n",
       "      <th>SSR_USLD</th>\n",
       "      <th>autres</th>\n",
       "      <th>rad</th>\n",
       "      <th>dc</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>jour</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-03-27</th>\n",
       "      <td>372</td>\n",
       "      <td>29</td>\n",
       "      <td>180.0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>57846</td>\n",
       "      <td>1554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-28</th>\n",
       "      <td>377</td>\n",
       "      <td>29</td>\n",
       "      <td>184.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>57859</td>\n",
       "      <td>1554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-29</th>\n",
       "      <td>374</td>\n",
       "      <td>32</td>\n",
       "      <td>177.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>57877</td>\n",
       "      <td>1554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-30</th>\n",
       "      <td>375</td>\n",
       "      <td>34</td>\n",
       "      <td>175.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>57889</td>\n",
       "      <td>1554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-31</th>\n",
       "      <td>373</td>\n",
       "      <td>33</td>\n",
       "      <td>177.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>57900</td>\n",
       "      <td>1554</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            hosp  rea  HospConv  SSR_USLD  autres    rad    dc\n",
       "jour                                                          \n",
       "2023-03-27   372   29     180.0     110.0    53.0  57846  1554\n",
       "2023-03-28   377   29     184.0     111.0    53.0  57859  1554\n",
       "2023-03-29   374   32     177.0     109.0    56.0  57877  1554\n",
       "2023-03-30   375   34     175.0     111.0    55.0  57889  1554\n",
       "2023-03-31   373   33     177.0     109.0    54.0  57900  1554"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "covid49 = covid[covid.cl_age90 == 49]\n",
    "agg_par_jour49 = covid49.drop([\"reg\", \"cl_age90\"], axis=1).groupby(\"jour\").sum()\n",
    "agg_par_jour49.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "agg_par_jour49.plot(\n",
    "    title=\"Evolution des hospitalisations par jour\\nage=49\", figsize=(14, 4), logy=True\n",
    ");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Q2 : faire de même avec les séries différenciées"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "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>reg</th>\n",
       "      <th>cl_age90</th>\n",
       "      <th>jour</th>\n",
       "      <th>hosp</th>\n",
       "      <th>rea</th>\n",
       "      <th>HospConv</th>\n",
       "      <th>SSR_USLD</th>\n",
       "      <th>autres</th>\n",
       "      <th>rad</th>\n",
       "      <th>dc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>219577</th>\n",
       "      <td>94</td>\n",
       "      <td>59</td>\n",
       "      <td>2023-03-31</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>387</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219578</th>\n",
       "      <td>94</td>\n",
       "      <td>69</td>\n",
       "      <td>2023-03-31</td>\n",
       "      <td>16</td>\n",
       "      <td>1</td>\n",
       "      <td>8.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>536</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219579</th>\n",
       "      <td>94</td>\n",
       "      <td>79</td>\n",
       "      <td>2023-03-31</td>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>14.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>810</td>\n",
       "      <td>129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219580</th>\n",
       "      <td>94</td>\n",
       "      <td>89</td>\n",
       "      <td>2023-03-31</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>888</td>\n",
       "      <td>199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219581</th>\n",
       "      <td>94</td>\n",
       "      <td>90</td>\n",
       "      <td>2023-03-31</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>388</td>\n",
       "      <td>121</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        reg  cl_age90       jour  hosp  rea  HospConv  SSR_USLD  autres  rad  \\\n",
       "219577   94        59 2023-03-31     1    0       0.0       1.0     0.0  387   \n",
       "219578   94        69 2023-03-31    16    1       8.0       5.0     2.0  536   \n",
       "219579   94        79 2023-03-31    29    1      14.0      13.0     1.0  810   \n",
       "219580   94        89 2023-03-31    35    0      24.0      11.0     0.0  888   \n",
       "219581   94        90 2023-03-31    18    0       6.0      12.0     0.0  388   \n",
       "\n",
       "         dc  \n",
       "219577   14  \n",
       "219578   48  \n",
       "219579  129  \n",
       "219580  199  \n",
       "219581  121  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "covid.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "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>hosp</th>\n",
       "      <th>rea</th>\n",
       "      <th>HospConv</th>\n",
       "      <th>SSR_USLD</th>\n",
       "      <th>autres</th>\n",
       "      <th>rad</th>\n",
       "      <th>dc</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>jour</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-03-30</th>\n",
       "      <td>-2.0</td>\n",
       "      <td>-5.0</td>\n",
       "      <td>-24.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>736.0</td>\n",
       "      <td>72.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-31</th>\n",
       "      <td>-79.0</td>\n",
       "      <td>-47.0</td>\n",
       "      <td>-22.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>-20.0</td>\n",
       "      <td>1010.0</td>\n",
       "      <td>62.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            hosp   rea  HospConv  SSR_USLD  autres     rad    dc\n",
       "jour                                                            \n",
       "2023-03-30  -2.0  -5.0     -24.0      21.0     6.0   736.0  72.0\n",
       "2023-03-31 -79.0 -47.0     -22.0      10.0   -20.0  1010.0  62.0"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "diff = covid.drop([\"reg\", \"cl_age90\"], axis=1).groupby([\"jour\"]).sum().diff()\n",
    "diff.tail(n=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "diff.plot(title=\"Séries différenciées\", figsize=(14, 4));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Q3 : faire de même avec des séries lissées sur sur 7 jours"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Rolling [window=7,center=False,axis=0,method=single]"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "diff.rolling(7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "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>hosp</th>\n",
       "      <th>rea</th>\n",
       "      <th>HospConv</th>\n",
       "      <th>SSR_USLD</th>\n",
       "      <th>autres</th>\n",
       "      <th>rad</th>\n",
       "      <th>dc</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>jour</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-03-30</th>\n",
       "      <td>45.0</td>\n",
       "      <td>-2.000000</td>\n",
       "      <td>34.857143</td>\n",
       "      <td>4.142857</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>701.571429</td>\n",
       "      <td>52.857143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-31</th>\n",
       "      <td>12.0</td>\n",
       "      <td>-12.142857</td>\n",
       "      <td>18.142857</td>\n",
       "      <td>3.142857</td>\n",
       "      <td>2.857143</td>\n",
       "      <td>719.571429</td>\n",
       "      <td>57.428571</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            hosp        rea   HospConv  SSR_USLD    autres         rad  \\\n",
       "jour                                                                     \n",
       "2023-03-30  45.0  -2.000000  34.857143  4.142857  8.000000  701.571429   \n",
       "2023-03-31  12.0 -12.142857  18.142857  3.142857  2.857143  719.571429   \n",
       "\n",
       "                   dc  \n",
       "jour                   \n",
       "2023-03-30  52.857143  \n",
       "2023-03-31  57.428571  "
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "roll = diff.rolling(7).mean()\n",
    "roll.tail(n=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "roll.plot(title=\"Séries différenciées lissées\", figsize=(14, 4));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Petit aparté\n",
    "\n",
    "On veut savoir combien de temps les gens restent à l'hôpital avant de sortir, en supposant que le temps de guérison est à peu près identique au temps passé lorsque l'issue est tout autre. Je pensais calculer les corrélations entre la série des décès et celles de réanimations décalées de plusieurs jours en me disant qu'un pic de corrélation pourrait indiquer une sorte de durée moyenne de réanimation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "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>hosp</th>\n",
       "      <th>rea</th>\n",
       "      <th>HospConv</th>\n",
       "      <th>SSR_USLD</th>\n",
       "      <th>autres</th>\n",
       "      <th>rad</th>\n",
       "      <th>dc</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>jour</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-03-30</th>\n",
       "      <td>1.714286</td>\n",
       "      <td>0.142857</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>0.714286</td>\n",
       "      <td>1.857143</td>\n",
       "      <td>11.285714</td>\n",
       "      <td>0.285714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-31</th>\n",
       "      <td>1.571429</td>\n",
       "      <td>0.285714</td>\n",
       "      <td>-0.285714</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.571429</td>\n",
       "      <td>10.714286</td>\n",
       "      <td>0.285714</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                hosp       rea  HospConv  SSR_USLD    autres        rad  \\\n",
       "jour                                                                      \n",
       "2023-03-30  1.714286  0.142857 -1.000000  0.714286  1.857143  11.285714   \n",
       "2023-03-31  1.571429  0.285714 -0.285714  0.000000  1.571429  10.714286   \n",
       "\n",
       "                  dc  \n",
       "jour                  \n",
       "2023-03-30  0.285714  \n",
       "2023-03-31  0.285714  "
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = agg_par_jour49.diff().rolling(7).mean()\n",
    "data.tail(n=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_last = data.tail(n=90)\n",
    "cor = []\n",
    "for i in range(0, 35):\n",
    "    ts = DataFrame(\n",
    "        dict(\n",
    "            rea=data_last.rea,\n",
    "            dc=data_last.dc,\n",
    "            dclag=data_last[\"dc\"].shift(i),\n",
    "            realag=data_last[\"rea\"].shift(i),\n",
    "        )\n",
    "    )\n",
    "    ts_cor = ts.corr()\n",
    "    cor.append(dict(delay=i, corr_dc=ts_cor.iloc[1, 3], corr_rea=ts_cor.iloc[0, 3]))\n",
    "DataFrame(cor).set_index(\"delay\").plot(title=\"Corrélation entre décès et réanimation\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Il apparaît que ces corrélations sont très différentes selon qu'on les calcule sur les dernières données et les premières semaines. Cela semblerait indiquer que les données médicales sont très différentes. On pourrait chercher plusieurs jours mais le plus simple serait sans de générer des données artificielles avec un modèle [SIR](https://fr.wikipedia.org/wiki/Mod%C3%A8les_compartimentaux_en_%C3%A9pid%C3%A9miologie) et vérifier si ce raisonnement tient la route sur des données propres."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Q4 : fusion de tables par départements\n",
    "\n",
    "On récupère deux jeux de données :\n",
    "* [Données hospitalières relatives à l'épidémie de COVID-19](https://www.data.gouv.fr/en/datasets/donnees-hospitalieres-relatives-a-lepidemie-de-covid-19/)\n",
    "* [Indicateurs de suivi de l’épidémie de COVID-19](https://www.data.gouv.fr/fr/datasets/indicateurs-de-suivi-de-lepidemie-de-covid-19/)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "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>dep</th>\n",
       "      <th>sexe</th>\n",
       "      <th>jour</th>\n",
       "      <th>hosp</th>\n",
       "      <th>rea</th>\n",
       "      <th>HospConv</th>\n",
       "      <th>SSR_USLD</th>\n",
       "      <th>autres</th>\n",
       "      <th>rad</th>\n",
       "      <th>dc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>338240</th>\n",
       "      <td>976</td>\n",
       "      <td>0</td>\n",
       "      <td>2023-03-31</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1766</td>\n",
       "      <td>163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338241</th>\n",
       "      <td>976</td>\n",
       "      <td>1</td>\n",
       "      <td>2023-03-31</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>739</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338242</th>\n",
       "      <td>976</td>\n",
       "      <td>2</td>\n",
       "      <td>2023-03-31</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1002</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338243</th>\n",
       "      <td>978</td>\n",
       "      <td>0</td>\n",
       "      <td>2023-03-31</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338244</th>\n",
       "      <td>978</td>\n",
       "      <td>1</td>\n",
       "      <td>2023-03-31</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        dep  sexe        jour  hosp  rea  HospConv  SSR_USLD  autres   rad  \\\n",
       "338240  976     0  2023-03-31     0    0       0.0       0.0     0.0  1766   \n",
       "338241  976     1  2023-03-31     0    0       0.0       0.0     0.0   739   \n",
       "338242  976     2  2023-03-31     0    0       0.0       0.0     0.0  1002   \n",
       "338243  978     0  2023-03-31     0    0       0.0       0.0     0.0     0   \n",
       "338244  978     1  2023-03-31     0    0       0.0       0.0     0.0     0   \n",
       "\n",
       "         dc  \n",
       "338240  163  \n",
       "338241  100  \n",
       "338242   61  \n",
       "338243    0  \n",
       "338244    0  "
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hosp = read_csv(\n",
    "    \"https://www.data.gouv.fr/en/datasets/r/63352e38-d353-4b54-bfd1-f1b3ee1cabd7\",\n",
    "    sep=\";\",\n",
    ")\n",
    "hosp.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_5653/1911493942.py:1: DtypeWarning: Columns (1) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  indic = read_csv(\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>extract_date</th>\n",
       "      <th>departement</th>\n",
       "      <th>region</th>\n",
       "      <th>libelle_reg</th>\n",
       "      <th>libelle_dep</th>\n",
       "      <th>tx_incid</th>\n",
       "      <th>R</th>\n",
       "      <th>taux_occupation_sae</th>\n",
       "      <th>tx_pos</th>\n",
       "      <th>tx_incid_couleur</th>\n",
       "      <th>R_couleur</th>\n",
       "      <th>taux_occupation_sae_couleur</th>\n",
       "      <th>tx_pos_couleur</th>\n",
       "      <th>nb_orange</th>\n",
       "      <th>nb_rouge</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>90390</th>\n",
       "      <td>2020-08-22</td>\n",
       "      <td>84</td>\n",
       "      <td>93</td>\n",
       "      <td>Provence Alpes Côte d'Azur</td>\n",
       "      <td>Vaucluse</td>\n",
       "      <td>44.21</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.3</td>\n",
       "      <td>3.721489</td>\n",
       "      <td>orange</td>\n",
       "      <td>NaN</td>\n",
       "      <td>vert</td>\n",
       "      <td>vert</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>90391</th>\n",
       "      <td>2020-08-23</td>\n",
       "      <td>84</td>\n",
       "      <td>93</td>\n",
       "      <td>Provence Alpes Côte d'Azur</td>\n",
       "      <td>Vaucluse</td>\n",
       "      <td>44.21</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.7</td>\n",
       "      <td>3.719256</td>\n",
       "      <td>orange</td>\n",
       "      <td>NaN</td>\n",
       "      <td>vert</td>\n",
       "      <td>vert</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90392</th>\n",
       "      <td>2020-08-28</td>\n",
       "      <td>84</td>\n",
       "      <td>93</td>\n",
       "      <td>Provence Alpes Côte d'Azur</td>\n",
       "      <td>Vaucluse</td>\n",
       "      <td>60.61</td>\n",
       "      <td>1.37</td>\n",
       "      <td>9.3</td>\n",
       "      <td>4.524887</td>\n",
       "      <td>rouge</td>\n",
       "      <td>orange</td>\n",
       "      <td>vert</td>\n",
       "      <td>vert</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90393</th>\n",
       "      <td>2020-08-29</td>\n",
       "      <td>84</td>\n",
       "      <td>93</td>\n",
       "      <td>Provence Alpes Côte d'Azur</td>\n",
       "      <td>Vaucluse</td>\n",
       "      <td>61.14</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.1</td>\n",
       "      <td>4.566028</td>\n",
       "      <td>rouge</td>\n",
       "      <td>NaN</td>\n",
       "      <td>vert</td>\n",
       "      <td>vert</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90394</th>\n",
       "      <td>2020-08-30</td>\n",
       "      <td>84</td>\n",
       "      <td>93</td>\n",
       "      <td>Provence Alpes Côte d'Azur</td>\n",
       "      <td>Vaucluse</td>\n",
       "      <td>61.50</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.1</td>\n",
       "      <td>4.570747</td>\n",
       "      <td>rouge</td>\n",
       "      <td>NaN</td>\n",
       "      <td>vert</td>\n",
       "      <td>vert</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      extract_date departement  region                  libelle_reg  \\\n",
       "90390   2020-08-22          84      93  Provence Alpes Côte d'Azur   \n",
       "90391   2020-08-23          84      93  Provence Alpes Côte d'Azur   \n",
       "90392   2020-08-28          84      93  Provence Alpes Côte d'Azur   \n",
       "90393   2020-08-29          84      93  Provence Alpes Côte d'Azur   \n",
       "90394   2020-08-30          84      93  Provence Alpes Côte d'Azur   \n",
       "\n",
       "      libelle_dep  tx_incid     R  taux_occupation_sae    tx_pos  \\\n",
       "90390    Vaucluse     44.21   NaN                  6.3  3.721489   \n",
       "90391    Vaucluse     44.21   NaN                  6.7  3.719256   \n",
       "90392    Vaucluse     60.61  1.37                  9.3  4.524887   \n",
       "90393    Vaucluse     61.14   NaN                  9.1  4.566028   \n",
       "90394    Vaucluse     61.50   NaN                  9.1  4.570747   \n",
       "\n",
       "      tx_incid_couleur R_couleur taux_occupation_sae_couleur tx_pos_couleur  \\\n",
       "90390           orange       NaN                        vert           vert   \n",
       "90391           orange       NaN                        vert           vert   \n",
       "90392            rouge    orange                        vert           vert   \n",
       "90393            rouge       NaN                        vert           vert   \n",
       "90394            rouge       NaN                        vert           vert   \n",
       "\n",
       "       nb_orange  nb_rouge  \n",
       "90390          1         0  \n",
       "90391          1         0  \n",
       "90392          1         1  \n",
       "90393          0         1  \n",
       "90394          0         1  "
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "indic = read_csv(\n",
    "    \"https://www.data.gouv.fr/fr/datasets/r/4acad602-d8b1-4516-bc71-7d5574d5f33e\",\n",
    "    encoding=\"ISO-8859-1\",\n",
    ")\n",
    "indic.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Le code suivant explique comment trouver la valeur ``ISO-8859-1``."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import chardet\n",
    "# with open(\"indicateurs-covid19-dep.csv\", \"rb\") as f:\n",
    "#     content = f.read()\n",
    "# chardet.detect(content)  # {'encoding': 'ISO-8859-1', 'confidence': 0.73, 'language': ''}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Q5 : une carte ?\n",
    "\n",
    "Tracer une carte n'est jamais simple. Il faut tout d'abord récupérer les coordonnées des départements : [Contours des départements français issus d'OpenStreetMap](https://www.data.gouv.fr/en/datasets/contours-des-departements-francais-issus-d-openstreetmap/). Ensuite... de ces fichiers ont été extraits les barycentres de chaque département français : [departement_french_2018.csv](https://github.com/sdpython/teachpyx/raw/main/_data/departement_french_2018.csv). Ce qui suit est une approximation de carte : on suppose que là où se trouve, les coordonnées longitude et latitude ne sont pas trop éloignées de ce qu'elles pourraient être si elles étaient projetées sur une sphère."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>code_insee</th>\n",
       "      <th>nom</th>\n",
       "      <th>nuts3</th>\n",
       "      <th>wikipedia</th>\n",
       "      <th>surf_km2</th>\n",
       "      <th>DEPLONG</th>\n",
       "      <th>DEPLAT</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>56</td>\n",
       "      <td>Morbihan</td>\n",
       "      <td>FR524</td>\n",
       "      <td>fr:Morbihan</td>\n",
       "      <td>6870.0</td>\n",
       "      <td>-2.812320</td>\n",
       "      <td>47.846846</td>\n",
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       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>25</td>\n",
       "      <td>Doubs</td>\n",
       "      <td>FR431</td>\n",
       "      <td>fr:Doubs (département)</td>\n",
       "      <td>5256.0</td>\n",
       "      <td>6.362722</td>\n",
       "      <td>47.165964</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>39</td>\n",
       "      <td>Jura</td>\n",
       "      <td>FR432</td>\n",
       "      <td>fr:Jura (département)</td>\n",
       "      <td>5049.0</td>\n",
       "      <td>5.697361</td>\n",
       "      <td>46.729368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>07</td>\n",
       "      <td>Ardèche</td>\n",
       "      <td>FR712</td>\n",
       "      <td>fr:Ardèche (département)</td>\n",
       "      <td>5566.0</td>\n",
       "      <td>4.425582</td>\n",
       "      <td>44.752771</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>30</td>\n",
       "      <td>Gard</td>\n",
       "      <td>FR812</td>\n",
       "      <td>fr:Gard</td>\n",
       "      <td>5875.0</td>\n",
       "      <td>4.179861</td>\n",
       "      <td>43.993601</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    code_insee       nom  nuts3                 wikipedia  surf_km2   DEPLONG  \\\n",
       "97          56  Morbihan  FR524               fr:Morbihan    6870.0 -2.812320   \n",
       "98          25     Doubs  FR431    fr:Doubs (département)    5256.0  6.362722   \n",
       "99          39      Jura  FR432     fr:Jura (département)    5049.0  5.697361   \n",
       "100         07   Ardèche  FR712  fr:Ardèche (département)    5566.0  4.425582   \n",
       "101         30      Gard  FR812                   fr:Gard    5875.0  4.179861   \n",
       "\n",
       "        DEPLAT  \n",
       "97   47.846846  \n",
       "98   47.165964  \n",
       "99   46.729368  \n",
       "100  44.752771  \n",
       "101  43.993601  "
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dep_pos = read_csv(\n",
    "    \"https://github.com/sdpython/teachpyx/raw/main/_data/departement_french_2018.csv\"\n",
    ")\n",
    "dep_pos.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2022-08-29'"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "last_extract_date = max(set(indic.extract_date))\n",
    "last_extract_date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
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       "      <td>10.9</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>45.051247</td>\n",
       "      <td>10.9</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>26</td>\n",
       "      <td>Drôme</td>\n",
       "      <td>5.167364</td>\n",
       "      <td>44.685239</td>\n",
       "      <td>10.9</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>67</th>\n",
       "      <td>23</td>\n",
       "      <td>Creuse</td>\n",
       "      <td>2.018230</td>\n",
       "      <td>46.090620</td>\n",
       "      <td>18.7</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>68</th>\n",
       "      <td>24</td>\n",
       "      <td>Dordogne</td>\n",
       "      <td>0.741203</td>\n",
       "      <td>45.104948</td>\n",
       "      <td>18.7</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>33</td>\n",
       "      <td>Gironde</td>\n",
       "      <td>-0.575870</td>\n",
       "      <td>44.823614</td>\n",
       "      <td>18.7</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>40</td>\n",
       "      <td>Landes</td>\n",
       "      <td>-0.783793</td>\n",
       "      <td>43.965855</td>\n",
       "      <td>18.7</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>47</td>\n",
       "      <td>Lot-et-Garonne</td>\n",
       "      <td>0.460747</td>\n",
       "      <td>44.367964</td>\n",
       "      <td>18.7</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>67 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   code_insee             nom   DEPLONG     DEPLAT  taux_occupation_sae   R\n",
       "0          01             Ain  5.348764  46.099799                 10.9 NaN\n",
       "1          03          Allier  3.187644  46.393637                 10.9 NaN\n",
       "2          07         Ardèche  4.425582  44.752771                 10.9 NaN\n",
       "3          15          Cantal  2.669045  45.051247                 10.9 NaN\n",
       "4          26           Drôme  5.167364  44.685239                 10.9 NaN\n",
       "..        ...             ...       ...        ...                  ...  ..\n",
       "67         23          Creuse  2.018230  46.090620                 18.7 NaN\n",
       "68         24        Dordogne  0.741203  45.104948                 18.7 NaN\n",
       "69         33         Gironde -0.575870  44.823614                 18.7 NaN\n",
       "70         40          Landes -0.783793  43.965855                 18.7 NaN\n",
       "71         47  Lot-et-Garonne  0.460747  44.367964                 18.7 NaN\n",
       "\n",
       "[67 rows x 6 columns]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "indic_last = indic[indic.extract_date == last_extract_date]\n",
    "merge = indic_last.merge(dep_pos, left_on=\"departement\", right_on=\"code_insee\")\n",
    "final = merge[[\"code_insee\", \"nom\", \"DEPLONG\", \"DEPLAT\", \"taux_occupation_sae\", \"R\"]]\n",
    "metro = final[final.DEPLAT > 40]\n",
    "metro"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1400x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "fig, ax = plt.subplots(1, 2, figsize=(14, 4))\n",
    "bigR1 = metro.R >= 1\n",
    "bigR2 = metro.R >= 1.4\n",
    "ax[0].scatter(\n",
    "    metro.loc[bigR2, \"DEPLONG\"], metro.loc[bigR2, \"DEPLAT\"], c=\"red\", label=\"R>=1.4\"\n",
    ")\n",
    "ax[0].scatter(\n",
    "    metro.loc[bigR1 & ~bigR2, \"DEPLONG\"],\n",
    "    metro.loc[bigR1 & ~bigR2, \"DEPLAT\"],\n",
    "    c=\"orange\",\n",
    "    label=\"1.3>=R>=1\",\n",
    ")\n",
    "ax[0].scatter(\n",
    "    metro.loc[~bigR1, \"DEPLONG\"], metro.loc[~bigR1, \"DEPLAT\"], c=\"blue\", label=\"R<1\"\n",
    ")\n",
    "ax[0].legend()\n",
    "\n",
    "bigR1 = metro.taux_occupation_sae >= 25\n",
    "bigR2 = metro.taux_occupation_sae >= 45\n",
    "ax[1].scatter(\n",
    "    metro.loc[bigR2, \"DEPLONG\"], metro.loc[bigR2, \"DEPLAT\"], c=\"red\", label=\"SAE>=45\"\n",
    ")\n",
    "ax[1].scatter(\n",
    "    metro.loc[bigR1 & ~bigR2, \"DEPLONG\"],\n",
    "    metro.loc[bigR1 & ~bigR2, \"DEPLAT\"],\n",
    "    c=\"orange\",\n",
    "    label=\"45>SAE>=25\",\n",
    ")\n",
    "ax[1].scatter(\n",
    "    metro.loc[~bigR1, \"DEPLONG\"], metro.loc[~bigR1, \"DEPLAT\"], c=\"blue\", label=\"SAE<25\"\n",
    ")\n",
    "ax[1].legend();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "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>code_insee</th>\n",
       "      <th>nom</th>\n",
       "      <th>DEPLONG</th>\n",
       "      <th>DEPLAT</th>\n",
       "      <th>taux_occupation_sae</th>\n",
       "      <th>R</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>08</td>\n",
       "      <td>Ardennes</td>\n",
       "      <td>4.640751</td>\n",
       "      <td>49.616226</td>\n",
       "      <td>13.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   code_insee       nom   DEPLONG     DEPLAT  taux_occupation_sae   R\n",
       "31         08  Ardennes  4.640751  49.616226                 13.5 NaN"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metro[metro.nom == \"Ardennes\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}