"* Graphique exemple de [South Chine Morning Post](https://www.scmp.com/coronavirus?src=homepage_covid_widget). Datant du 20 Mai 2020.\n",
"* Données brutes utilisées dans ce document : [time_series_covid19_confirmed_global.csv](https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv)\n",
"\n"
"\n",
"\n",
"On procède à un test afin de savoir si les données sont disponibles en local ou si l'ont doit utiliser l'URL."
"| Province/State | gives data for a specific regions |\n",
"| Country/Region | the country or the region to which the data are corresponding |\n",
"| Lat | latitude |\n",
"| Long | longitude |\n",
"| 1/22/20 | from here it gives the number citizens having the covid19 |"
]
},
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"cell_type": "markdown",
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"Les données manquantes corresponde aux pays qui ne sont pas représenté à travers différentes provinces et états les composants.\n",
"Cependant, nous ne sommes pas dépendant de ces données, seul les données relatives au pays suivant nous intéresse. \n",
"\n",
"* Belgique \n",
"* Chine - toutes les provinces sauf Hong-Kong (China), Hong Kong (China, Hong-Kong)\n",
"* France métropolitaine\n",
"* Allemagne\n",
"* Iran\n",
"* Italie\n",
"* Japon\n",
"* Corée du Sud\n",
"* Hollande\n",
"* Portugal \n",
"* Espagne\n",
"* Royaume-Unis\n",
"* États-Unis\n",
"\n",
"## Regroupement des données à inclure dans l'étude\n",
"\n",
"Ici nous utilisons la méthode [*loc*](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.loc.html) de pandas pour extraire des données brutes les lignes correspondantes aux pays cités ci-dessus.\n",
"\n",
"Afin de ne pas rendre le *code* illisible le processus est divisé en de multiples étapes. (toutes ces étapes peuvent être regroupé en une expression logique."
]
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" <td>56511</td>\n",
" <td>56810</td>\n",
" <td>57092</td>\n",
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