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 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1400x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Télécharger les données\n",
    "url = \"https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv\"\n",
    "data = pd.read_csv(url)\n",
    "\n",
    "# Exclure Hong Kong des données de la Chine\n",
    "data_ex_china = data[~((data['Country/Region'] == 'China') & (data['Province/State'] == 'Hong Kong SAR'))]\n",
    "\n",
    "# Filtrer les territoires d'outre-mer pour la France et le Royaume-Uni\n",
    "france_excl = ['French Guiana', 'Guadeloupe', 'Martinique', 'Mayotte', 'Reunion', 'Saint Barthelemy', 'Saint Pierre and Miquelon']\n",
    "uk_excl = ['Anguilla', 'Bermuda', 'British Virgin Islands', 'Cayman Islands', 'Channel Islands', 'Falkland Islands (Malvinas)', 'Gibraltar', 'Isle of Man', 'Montserrat', 'Saint Helena', 'Turks and Caicos Islands']\n",
    "\n",
    "# Filtrer les données pour exclure ces territoires\n",
    "data_ex_terri = data_ex_china[\n",
    "    ~((data_ex_china['Country/Region'] == 'France') & (data_ex_china['Province/State'].isin(france_excl))) &\n",
    "    ~((data_ex_china['Country/Region'] == 'United Kingdom') & (data_ex_china['Province/State'].isin(uk_excl)))\n",
    "]\n",
    "\n",
    "# Filtrer les données pour les pays d'intérêt (en excluant les territoires)\n",
    "countries = [\n",
    "    \"Belgium\", \"China\", \"France\", \"Germany\", \"Iran\", \"Italy\", \"Japan\",\n",
    "    \"Korea, South\", \"Netherlands\", \"Portugal\", \"Spain\", \"United Kingdom\", \"US\", \"Hong Kong SAR\"\n",
    "]\n",
    "\n",
    "data_filtered = data_ex_terri[data_ex_terri['Country/Region'].isin(countries)]\n",
    "\n",
    "# Agréger les données par pays (somme des provinces)\n",
    "data_grouped = data_filtered.groupby(\"Country/Region\").sum().reset_index()\n",
    "\n",
    "# Supprimer les colonnes non nécessaires\n",
    "data_grouped = data_grouped.drop(columns=[\"Lat\", \"Long\"])\n",
    "\n",
    "# Transposer les données pour avoir les dates en lignes\n",
    "data_transposed = data_grouped.set_index(\"Country/Region\").T\n",
    "\n",
    "# Tracer les graphiques\n",
    "plt.figure(figsize=(14, 8))\n",
    "\n",
    "# Graphique à échelle linéaire\n",
    "plt.subplot(2, 1, 1)\n",
    "for country in countries:\n",
    "    if country in data_transposed.columns:\n",
    "        plt.plot(data_transposed.index, data_transposed[country], label=country)\n",
    "plt.title('Nombre cumulé de cas de COVID-19 (Échelle linéaire)')\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('Nombre cumulé de cas')\n",
    "plt.legend()\n",
    "plt.xticks(rotation=90)\n",
    "\n",
    "# Graphique à échelle logarithmique\n",
    "plt.subplot(2, 1, 2)\n",
    "for country in countries:\n",
    "    if country in data_transposed.columns:\n",
    "        plt.plot(data_transposed.index, data_transposed[country], label=country)\n",
    "plt.yscale('log')\n",
    "plt.title('Nombre cumulé de cas de COVID-19 (Échelle logarithmique)')\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('Nombre cumulé de cas (échelle logarithmique)')\n",
    "plt.legend()\n",
    "plt.xticks(rotation=90)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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