diff --git a/module3/exo2/exercice_fr.ipynb b/module3/exo2/exercice_fr.ipynb
index 0bbbe371b01e359e381e43239412d77bf53fb1fb..05143c312e7a17f4096a113ae23a5f6bb1f1ebac 100644
--- a/module3/exo2/exercice_fr.ipynb
+++ b/module3/exo2/exercice_fr.ipynb
@@ -1,5 +1,964 @@
{
- "cells": [],
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "#
Incidence du syndrome grippal"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 33,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "%matplotlib inline\n",
+ "import matplotlib.pyplot as plt\n",
+ "import pandas as pd\n",
+ "import isoweek"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Nous recuperons les données sur le site via le site en pointant sur un fichier au format .csv Pour la lecture des données ...."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 35,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " week | \n",
+ " indicator | \n",
+ " inc | \n",
+ " inc_low | \n",
+ " inc_up | \n",
+ " inc100 | \n",
+ " inc100_low | \n",
+ " inc100_up | \n",
+ " geo_insee | \n",
+ " geo_name | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 0 | \n",
+ " 202052 | \n",
+ " 3 | \n",
+ " 18546 | \n",
+ " 13789.0 | \n",
+ " 23303.0 | \n",
+ " 28 | \n",
+ " 21.0 | \n",
+ " 35.0 | \n",
+ " FR | \n",
+ " France | \n",
+ "
\n",
+ " \n",
+ " 1 | \n",
+ " 202051 | \n",
+ " 3 | \n",
+ " 21032 | \n",
+ " 16856.0 | \n",
+ " 25208.0 | \n",
+ " 32 | \n",
+ " 26.0 | \n",
+ " 38.0 | \n",
+ " FR | \n",
+ " France | \n",
+ "
\n",
+ " \n",
+ " 2 | \n",
+ " 202050 | \n",
+ " 3 | \n",
+ " 16845 | \n",
+ " 13220.0 | \n",
+ " 20470.0 | \n",
+ " 26 | \n",
+ " 20.0 | \n",
+ " 32.0 | \n",
+ " FR | \n",
+ " France | \n",
+ "
\n",
+ " \n",
+ " 3 | \n",
+ " 202049 | \n",
+ " 3 | \n",
+ " 12939 | \n",
+ " 9923.0 | \n",
+ " 15955.0 | \n",
+ " 20 | \n",
+ " 15.0 | \n",
+ " 25.0 | \n",
+ " FR | \n",
+ " France | \n",
+ "
\n",
+ " \n",
+ " 4 | \n",
+ " 202048 | \n",
+ " 3 | \n",
+ " 13804 | \n",
+ " 10641.0 | \n",
+ " 16967.0 | \n",
+ " 21 | \n",
+ " 16.0 | \n",
+ " 26.0 | \n",
+ " FR | \n",
+ " France | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " week indicator inc inc_low inc_up inc100 inc100_low inc100_up \\\n",
+ "0 202052 3 18546 13789.0 23303.0 28 21.0 35.0 \n",
+ "1 202051 3 21032 16856.0 25208.0 32 26.0 38.0 \n",
+ "2 202050 3 16845 13220.0 20470.0 26 20.0 32.0 \n",
+ "3 202049 3 12939 9923.0 15955.0 20 15.0 25.0 \n",
+ "4 202048 3 13804 10641.0 16967.0 21 16.0 26.0 \n",
+ "\n",
+ " geo_insee geo_name \n",
+ "0 FR France \n",
+ "1 FR France \n",
+ "2 FR France \n",
+ "3 FR France \n",
+ "4 FR France "
+ ]
+ },
+ "execution_count": 35,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\"\n",
+ "raw_data = pd.read_csv(data_url, skiprows=1)\n",
+ "raw_data.head()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 36,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " week | \n",
+ " indicator | \n",
+ " inc | \n",
+ " inc_low | \n",
+ " inc_up | \n",
+ " inc100 | \n",
+ " inc100_low | \n",
+ " inc100_up | \n",
+ " geo_insee | \n",
+ " geo_name | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 1882 | \n",
+ " 198448 | \n",
+ " 3 | \n",
+ " 78620 | \n",
+ " 60634.0 | \n",
+ " 96606.0 | \n",
+ " 143 | \n",
+ " 110.0 | \n",
+ " 176.0 | \n",
+ " FR | \n",
+ " France | \n",
+ "
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+ " \n",
+ " 1883 | \n",
+ " 198447 | \n",
+ " 3 | \n",
+ " 72029 | \n",
+ " 54274.0 | \n",
+ " 89784.0 | \n",
+ " 131 | \n",
+ " 99.0 | \n",
+ " 163.0 | \n",
+ " FR | \n",
+ " France | \n",
+ "
\n",
+ " \n",
+ " 1884 | \n",
+ " 198446 | \n",
+ " 3 | \n",
+ " 87330 | \n",
+ " 67686.0 | \n",
+ " 106974.0 | \n",
+ " 159 | \n",
+ " 123.0 | \n",
+ " 195.0 | \n",
+ " FR | \n",
+ " France | \n",
+ "
\n",
+ " \n",
+ " 1885 | \n",
+ " 198445 | \n",
+ " 3 | \n",
+ " 135223 | \n",
+ " 101414.0 | \n",
+ " 169032.0 | \n",
+ " 246 | \n",
+ " 184.0 | \n",
+ " 308.0 | \n",
+ " FR | \n",
+ " France | \n",
+ "
\n",
+ " \n",
+ " 1886 | \n",
+ " 198444 | \n",
+ " 3 | \n",
+ " 68422 | \n",
+ " 20056.0 | \n",
+ " 116788.0 | \n",
+ " 125 | \n",
+ " 37.0 | \n",
+ " 213.0 | \n",
+ " FR | \n",
+ " France | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " week indicator inc inc_low inc_up inc100 inc100_low \\\n",
+ "1882 198448 3 78620 60634.0 96606.0 143 110.0 \n",
+ "1883 198447 3 72029 54274.0 89784.0 131 99.0 \n",
+ "1884 198446 3 87330 67686.0 106974.0 159 123.0 \n",
+ "1885 198445 3 135223 101414.0 169032.0 246 184.0 \n",
+ "1886 198444 3 68422 20056.0 116788.0 125 37.0 \n",
+ "\n",
+ " inc100_up geo_insee geo_name \n",
+ "1882 176.0 FR France \n",
+ "1883 163.0 FR France \n",
+ "1884 195.0 FR France \n",
+ "1885 308.0 FR France \n",
+ "1886 213.0 FR France "
+ ]
+ },
+ "execution_count": 36,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "raw_data.tail()\n",
+ "#raw_data.columns"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "On fait une recherche de donnée manquante dans la dataframe.On visuallise les lignes de donnée manquantes"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 37,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " week | \n",
+ " indicator | \n",
+ " inc | \n",
+ " inc_low | \n",
+ " inc_up | \n",
+ " inc100 | \n",
+ " inc100_low | \n",
+ " inc100_up | \n",
+ " geo_insee | \n",
+ " geo_name | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 1650 | \n",
+ " 198919 | \n",
+ " 3 | \n",
+ " 0 | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " 0 | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " FR | \n",
+ " France | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " week indicator inc inc_low inc_up inc100 inc100_low inc100_up \\\n",
+ "1650 198919 3 0 NaN NaN 0 NaN NaN \n",
+ "\n",
+ " geo_insee geo_name \n",
+ "1650 FR France "
+ ]
+ },
+ "execution_count": 37,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "raw_data[raw_data.isnull().any(axis=1)]"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Nous travaillerons sur une dataframe dont les lignes manquantes seront supprimées, nous testons que sur cette nouvelle dataframe il y a bien aucun elements manquant sur une ligne;"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 42,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " week | \n",
+ " indicator | \n",
+ " inc | \n",
+ " inc_low | \n",
+ " inc_up | \n",
+ " inc100 | \n",
+ " inc100_low | \n",
+ " inc100_up | \n",
+ " geo_insee | \n",
+ " geo_name | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 0 | \n",
+ " 202052 | \n",
+ " 3 | \n",
+ " 18546 | \n",
+ " 13789.0 | \n",
+ " 23303.0 | \n",
+ " 28 | \n",
+ " 21.0 | \n",
+ " 35.0 | \n",
+ " FR | \n",
+ " France | \n",
+ "
\n",
+ " \n",
+ " 1 | \n",
+ " 202051 | \n",
+ " 3 | \n",
+ " 21032 | \n",
+ " 16856.0 | \n",
+ " 25208.0 | \n",
+ " 32 | \n",
+ " 26.0 | \n",
+ " 38.0 | \n",
+ " FR | \n",
+ " France | \n",
+ "
\n",
+ " \n",
+ " 2 | \n",
+ " 202050 | \n",
+ " 3 | \n",
+ " 16845 | \n",
+ " 13220.0 | \n",
+ " 20470.0 | \n",
+ " 26 | \n",
+ " 20.0 | \n",
+ " 32.0 | \n",
+ " FR | \n",
+ " France | \n",
+ "
\n",
+ " \n",
+ " 3 | \n",
+ " 202049 | \n",
+ " 3 | \n",
+ " 12939 | \n",
+ " 9923.0 | \n",
+ " 15955.0 | \n",
+ " 20 | \n",
+ " 15.0 | \n",
+ " 25.0 | \n",
+ " FR | \n",
+ " France | \n",
+ "
\n",
+ " \n",
+ " 4 | \n",
+ " 202048 | \n",
+ " 3 | \n",
+ " 13804 | \n",
+ " 10641.0 | \n",
+ " 16967.0 | \n",
+ " 21 | \n",
+ " 16.0 | \n",
+ " 26.0 | \n",
+ " FR | \n",
+ " France | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " week indicator inc inc_low inc_up inc100 inc100_low inc100_up \\\n",
+ "0 202052 3 18546 13789.0 23303.0 28 21.0 35.0 \n",
+ "1 202051 3 21032 16856.0 25208.0 32 26.0 38.0 \n",
+ "2 202050 3 16845 13220.0 20470.0 26 20.0 32.0 \n",
+ "3 202049 3 12939 9923.0 15955.0 20 15.0 25.0 \n",
+ "4 202048 3 13804 10641.0 16967.0 21 16.0 26.0 \n",
+ "\n",
+ " geo_insee geo_name \n",
+ "0 FR France \n",
+ "1 FR France \n",
+ "2 FR France \n",
+ "3 FR France \n",
+ "4 FR France "
+ ]
+ },
+ "execution_count": 42,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "data = raw_data.dropna().copy()\n",
+ "data.head()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 43,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " week | \n",
+ " indicator | \n",
+ " inc | \n",
+ " inc_low | \n",
+ " inc_up | \n",
+ " inc100 | \n",
+ " inc100_low | \n",
+ " inc100_up | \n",
+ " geo_insee | \n",
+ " geo_name | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ "Empty DataFrame\n",
+ "Columns: [week, indicator, inc, inc_low, inc_up, inc100, inc100_low, inc100_up, geo_insee, geo_name]\n",
+ "Index: []"
+ ]
+ },
+ "execution_count": 43,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "data[data.isnull().any(axis=1)]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 52,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "year_and_week_int = 198501\n",
+ "year_and_week_str = str(year_and_week_int)\n",
+ "year = int(year_and_week_str[:4])\n",
+ "week = int(year_and_week_str[4:6])\n",
+ "\n",
+ "w = isoweek.Week(year,week)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Premeière jour de cette semaine 1985 01"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 53,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "1984-12-31\n"
+ ]
+ }
+ ],
+ "source": [
+ "print(w.day(0))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 55,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "Period('1984-12-31/1985-01-06', 'W-SUN')"
+ ]
+ },
+ "execution_count": 55,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "pd.Period(w.day(0),'W')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 57,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def convert_week(year_and_week_int):\n",
+ " year_and_week_str = str(year_and_week_int)\n",
+ " year = int(year_and_week_str[:4])\n",
+ " week = int(year_and_week_str[4:6])\n",
+ " w = isoweek.Week(year,week)\n",
+ " return pd.Period(w.day(0),'W')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "On ajoute une nouvelle colonne dans notre jeux de données, cette collonne represente une pérriode.\n",
+ "On aura notre jeux de données en ordre inverse, nous lui appliquons une fonction de trie pour obtenir un ordre chronologique. "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 61,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " week | \n",
+ " indicator | \n",
+ " inc | \n",
+ " inc_low | \n",
+ " inc_up | \n",
+ " inc100 | \n",
+ " inc100_low | \n",
+ " inc100_up | \n",
+ " geo_insee | \n",
+ " geo_name | \n",
+ " period | \n",
+ "
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+ " \n",
+ " \n",
+ " \n",
+ " 0 | \n",
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+ " 18546 | \n",
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+ " 28 | \n",
+ " 21.0 | \n",
+ " 35.0 | \n",
+ " FR | \n",
+ " France | \n",
+ " 2020-12-21/2020-12-27 | \n",
+ "
\n",
+ " \n",
+ " 1 | \n",
+ " 202051 | \n",
+ " 3 | \n",
+ " 21032 | \n",
+ " 16856.0 | \n",
+ " 25208.0 | \n",
+ " 32 | \n",
+ " 26.0 | \n",
+ " 38.0 | \n",
+ " FR | \n",
+ " France | \n",
+ " 2020-12-14/2020-12-20 | \n",
+ "
\n",
+ " \n",
+ " 2 | \n",
+ " 202050 | \n",
+ " 3 | \n",
+ " 16845 | \n",
+ " 13220.0 | \n",
+ " 20470.0 | \n",
+ " 26 | \n",
+ " 20.0 | \n",
+ " 32.0 | \n",
+ " FR | \n",
+ " France | \n",
+ " 2020-12-07/2020-12-13 | \n",
+ "
\n",
+ " \n",
+ " 3 | \n",
+ " 202049 | \n",
+ " 3 | \n",
+ " 12939 | \n",
+ " 9923.0 | \n",
+ " 15955.0 | \n",
+ " 20 | \n",
+ " 15.0 | \n",
+ " 25.0 | \n",
+ " FR | \n",
+ " France | \n",
+ " 2020-11-30/2020-12-06 | \n",
+ "
\n",
+ " \n",
+ " 4 | \n",
+ " 202048 | \n",
+ " 3 | \n",
+ " 13804 | \n",
+ " 10641.0 | \n",
+ " 16967.0 | \n",
+ " 21 | \n",
+ " 16.0 | \n",
+ " 26.0 | \n",
+ " FR | \n",
+ " France | \n",
+ " 2020-11-23/2020-11-29 | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " week indicator inc inc_low inc_up inc100 inc100_low inc100_up \\\n",
+ "0 202052 3 18546 13789.0 23303.0 28 21.0 35.0 \n",
+ "1 202051 3 21032 16856.0 25208.0 32 26.0 38.0 \n",
+ "2 202050 3 16845 13220.0 20470.0 26 20.0 32.0 \n",
+ "3 202049 3 12939 9923.0 15955.0 20 15.0 25.0 \n",
+ "4 202048 3 13804 10641.0 16967.0 21 16.0 26.0 \n",
+ "\n",
+ " geo_insee geo_name period \n",
+ "0 FR France 2020-12-21/2020-12-27 \n",
+ "1 FR France 2020-12-14/2020-12-20 \n",
+ "2 FR France 2020-12-07/2020-12-13 \n",
+ "3 FR France 2020-11-30/2020-12-06 \n",
+ "4 FR France 2020-11-23/2020-11-29 "
+ ]
+ },
+ "execution_count": 61,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "data['period'] = [convert_week(yw) for yw in data['week']]\n",
+ "data.head()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 62,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "sorted_data = data.set_index('period').sort_index()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 63,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " week | \n",
+ " indicator | \n",
+ " inc | \n",
+ " inc_low | \n",
+ " inc_up | \n",
+ " inc100 | \n",
+ " inc100_low | \n",
+ " inc100_up | \n",
+ " geo_insee | \n",
+ " geo_name | \n",
+ "
\n",
+ " \n",
+ " period | \n",
+ " | \n",
+ " | \n",
+ " | \n",
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+ " | \n",
+ " | \n",
+ " | \n",
+ " | \n",
+ " | \n",
+ " | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 1984-10-29/1984-11-04 | \n",
+ " 198444 | \n",
+ " 3 | \n",
+ " 68422 | \n",
+ " 20056.0 | \n",
+ " 116788.0 | \n",
+ " 125 | \n",
+ " 37.0 | \n",
+ " 213.0 | \n",
+ " FR | \n",
+ " France | \n",
+ "
\n",
+ " \n",
+ " 1984-11-05/1984-11-11 | \n",
+ " 198445 | \n",
+ " 3 | \n",
+ " 135223 | \n",
+ " 101414.0 | \n",
+ " 169032.0 | \n",
+ " 246 | \n",
+ " 184.0 | \n",
+ " 308.0 | \n",
+ " FR | \n",
+ " France | \n",
+ "
\n",
+ " \n",
+ " 1984-11-12/1984-11-18 | \n",
+ " 198446 | \n",
+ " 3 | \n",
+ " 87330 | \n",
+ " 67686.0 | \n",
+ " 106974.0 | \n",
+ " 159 | \n",
+ " 123.0 | \n",
+ " 195.0 | \n",
+ " FR | \n",
+ " France | \n",
+ "
\n",
+ " \n",
+ " 1984-11-19/1984-11-25 | \n",
+ " 198447 | \n",
+ " 3 | \n",
+ " 72029 | \n",
+ " 54274.0 | \n",
+ " 89784.0 | \n",
+ " 131 | \n",
+ " 99.0 | \n",
+ " 163.0 | \n",
+ " FR | \n",
+ " France | \n",
+ "
\n",
+ " \n",
+ " 1984-11-26/1984-12-02 | \n",
+ " 198448 | \n",
+ " 3 | \n",
+ " 78620 | \n",
+ " 60634.0 | \n",
+ " 96606.0 | \n",
+ " 143 | \n",
+ " 110.0 | \n",
+ " 176.0 | \n",
+ " FR | \n",
+ " France | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " week indicator inc inc_low inc_up inc100 \\\n",
+ "period \n",
+ "1984-10-29/1984-11-04 198444 3 68422 20056.0 116788.0 125 \n",
+ "1984-11-05/1984-11-11 198445 3 135223 101414.0 169032.0 246 \n",
+ "1984-11-12/1984-11-18 198446 3 87330 67686.0 106974.0 159 \n",
+ "1984-11-19/1984-11-25 198447 3 72029 54274.0 89784.0 131 \n",
+ "1984-11-26/1984-12-02 198448 3 78620 60634.0 96606.0 143 \n",
+ "\n",
+ " inc100_low inc100_up geo_insee geo_name \n",
+ "period \n",
+ "1984-10-29/1984-11-04 37.0 213.0 FR France \n",
+ "1984-11-05/1984-11-11 184.0 308.0 FR France \n",
+ "1984-11-12/1984-11-18 123.0 195.0 FR France \n",
+ "1984-11-19/1984-11-25 99.0 163.0 FR France \n",
+ "1984-11-26/1984-12-02 110.0 176.0 FR France "
+ ]
+ },
+ "execution_count": 63,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "sorted_data.head()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
@@ -16,10 +975,9 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.6.3"
+ "version": "3.6.4"
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"nbformat": 4,
"nbformat_minor": 2
}
-