From c9c7a81e0e0a43bbafc258e40ef37fa7e140357a Mon Sep 17 00:00:00 2001
From: 6870d61c58e6946ec72c57da6f214d2e
 <6870d61c58e6946ec72c57da6f214d2e@app-learninglab.inria.fr>
Date: Sun, 31 Jan 2021 16:22:19 +0000
Subject: [PATCH] =?UTF-8?q?Notebook=20modifi=C3=A9=20selon=20les=20consign?=
 =?UTF-8?q?es=20de=20l'exercice=2003-1?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 module3/exo1/incidence.csv     | 1892 ++++++++++++++++++++++++
 module3/exo3/.ipynb            | 2516 ++++++++++++++++++++++++++++++++
 module3/exo3/exercice_fr.ipynb | 2514 ++++++++++++++++++++++++++++++-
 module3/exo3/incidence.csv     | 1892 ++++++++++++++++++++++++
 4 files changed, 8810 insertions(+), 4 deletions(-)
 create mode 100644 module3/exo1/incidence.csv
 create mode 100644 module3/exo3/.ipynb
 create mode 100644 module3/exo3/incidence.csv

diff --git a/module3/exo1/incidence.csv b/module3/exo1/incidence.csv
new file mode 100644
index 0000000..ee7afbc
--- /dev/null
+++ b/module3/exo1/incidence.csv
@@ -0,0 +1,1892 @@
+,week,indicator,inc,inc_low,inc_up,inc100,inc100_low,inc100_up,geo_insee,geo_name
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+1555,199114,3,27862,21583.0,34141.0,49,38.0,60.0,FR,France
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+1757,198721,3,17619,12649.0,22589.0,32,23.0,41.0,FR,France
+1758,198720,3,10344,6454.0,14234.0,19,12.0,26.0,FR,France
+1759,198719,3,12539,7943.0,17135.0,23,15.0,31.0,FR,France
+1760,198718,3,16095,10330.0,21860.0,29,19.0,39.0,FR,France
+1761,198717,3,21256,14850.0,27662.0,38,26.0,50.0,FR,France
+1762,198716,3,32416,25100.0,39732.0,58,45.0,71.0,FR,France
+1763,198715,3,44292,36456.0,52128.0,80,66.0,94.0,FR,France
+1764,198714,3,50642,41866.0,59418.0,91,75.0,107.0,FR,France
+1765,198713,3,62246,52749.0,71743.0,112,95.0,129.0,FR,France
+1766,198712,3,59625,50653.0,68597.0,107,91.0,123.0,FR,France
+1767,198711,3,53561,45035.0,62087.0,96,81.0,111.0,FR,France
+1768,198710,3,93067,80519.0,105615.0,167,144.0,190.0,FR,France
+1769,198709,3,147006,133519.0,160493.0,264,240.0,288.0,FR,France
+1770,198708,3,217779,202179.0,233379.0,391,363.0,419.0,FR,France
+1771,198707,3,288180,270718.0,305642.0,518,487.0,549.0,FR,France
+1772,198706,3,296702,279051.0,314353.0,533,501.0,565.0,FR,France
+1773,198705,3,236046,219483.0,252609.0,424,394.0,454.0,FR,France
+1774,198704,3,158333,143625.0,173041.0,285,259.0,311.0,FR,France
+1775,198703,3,103841,91699.0,115983.0,187,165.0,209.0,FR,France
+1776,198702,3,74213,64014.0,84412.0,133,115.0,151.0,FR,France
+1777,198701,3,69745,59207.0,80283.0,125,106.0,144.0,FR,France
+1778,198652,3,76263,64958.0,87568.0,138,118.0,158.0,FR,France
+1779,198651,3,72920,63047.0,82793.0,132,114.0,150.0,FR,France
+1780,198650,3,73413,64019.0,82807.0,133,116.0,150.0,FR,France
+1781,198649,3,56296,48229.0,64363.0,102,87.0,117.0,FR,France
+1782,198648,3,46031,38578.0,53484.0,83,70.0,96.0,FR,France
+1783,198647,3,36740,29710.0,43770.0,66,53.0,79.0,FR,France
+1784,198646,3,32134,25327.0,38941.0,58,46.0,70.0,FR,France
+1785,198645,3,38964,31382.0,46546.0,70,56.0,84.0,FR,France
+1786,198644,3,28646,22048.0,35244.0,52,40.0,64.0,FR,France
+1787,198643,3,27532,20842.0,34222.0,50,38.0,62.0,FR,France
+1788,198642,3,31815,25124.0,38506.0,57,45.0,69.0,FR,France
+1789,198641,3,32864,25939.0,39789.0,59,47.0,71.0,FR,France
+1790,198640,3,33516,26776.0,40256.0,60,48.0,72.0,FR,France
+1791,198639,3,28665,22477.0,34853.0,52,41.0,63.0,FR,France
+1792,198638,3,26615,20479.0,32751.0,48,37.0,59.0,FR,France
+1793,198637,3,15998,10802.0,21194.0,29,20.0,38.0,FR,France
+1794,198636,3,9182,4982.0,13382.0,17,9.0,25.0,FR,France
+1795,198635,3,10587,4470.0,16704.0,19,8.0,30.0,FR,France
+1796,198634,3,5762,858.0,10666.0,10,1.0,19.0,FR,France
+1797,198633,3,3115,554.0,5676.0,6,1.0,11.0,FR,France
+1798,198632,3,1027,0.0,2311.0,2,0.0,4.0,FR,France
+1799,198631,3,2247,0.0,4574.0,4,0.0,8.0,FR,France
+1800,198630,3,2346,141.0,4551.0,4,0.0,8.0,FR,France
+1801,198629,3,3654,931.0,6377.0,7,2.0,12.0,FR,France
+1802,198628,3,2327,0.0,5318.0,4,0.0,9.0,FR,France
+1803,198627,3,7529,3353.0,11705.0,14,6.0,22.0,FR,France
+1804,198626,3,8778,5106.0,12450.0,16,9.0,23.0,FR,France
+1805,198625,3,11075,6804.0,15346.0,20,12.0,28.0,FR,France
+1806,198624,3,11160,7252.0,15068.0,20,13.0,27.0,FR,France
+1807,198623,3,14372,9896.0,18848.0,26,18.0,34.0,FR,France
+1808,198622,3,9717,5594.0,13840.0,18,11.0,25.0,FR,France
+1809,198621,3,14460,9575.0,19345.0,26,17.0,35.0,FR,France
+1810,198620,3,17133,12106.0,22160.0,31,22.0,40.0,FR,France
+1811,198619,3,22177,16008.0,28346.0,40,29.0,51.0,FR,France
+1812,198618,3,31736,24115.0,39357.0,57,43.0,71.0,FR,France
+1813,198617,3,34874,27440.0,42308.0,63,50.0,76.0,FR,France
+1814,198616,3,41196,32894.0,49498.0,74,59.0,89.0,FR,France
+1815,198615,3,42659,33537.0,51781.0,77,61.0,93.0,FR,France
+1816,198614,3,49792,39728.0,59856.0,90,72.0,108.0,FR,France
+1817,198613,3,87249,63562.0,110936.0,157,114.0,200.0,FR,France
+1818,198612,3,124777,97237.0,152317.0,225,175.0,275.0,FR,France
+1819,198611,3,168146,151035.0,185257.0,303,272.0,334.0,FR,France
+1820,198610,3,257305,231225.0,283385.0,464,417.0,511.0,FR,France
+1821,198609,3,321140,296644.0,345636.0,580,536.0,624.0,FR,France
+1822,198608,3,448786,419219.0,478353.0,810,757.0,863.0,FR,France
+1823,198607,3,490723,460150.0,521296.0,886,831.0,941.0,FR,France
+1824,198606,3,439300,411764.0,466836.0,793,743.0,843.0,FR,France
+1825,198605,3,364727,339868.0,389586.0,658,613.0,703.0,FR,France
+1826,198604,3,348509,322464.0,374554.0,629,582.0,676.0,FR,France
+1827,198603,3,271539,248654.0,294424.0,490,449.0,531.0,FR,France
+1828,198602,3,178138,159344.0,196932.0,322,288.0,356.0,FR,France
+1829,198601,3,112614,96539.0,128689.0,203,174.0,232.0,FR,France
+1830,198552,3,86452,72250.0,100654.0,157,131.0,183.0,FR,France
+1831,198551,3,114666,99538.0,129794.0,208,181.0,235.0,FR,France
+1832,198550,3,86031,73604.0,98458.0,156,133.0,179.0,FR,France
+1833,198549,3,65931,55326.0,76536.0,120,101.0,139.0,FR,France
+1834,198548,3,68291,57581.0,79001.0,124,105.0,143.0,FR,France
+1835,198547,3,66177,55221.0,77133.0,120,100.0,140.0,FR,France
+1836,198546,3,70534,58788.0,82280.0,128,107.0,149.0,FR,France
+1837,198545,3,57514,47167.0,67861.0,104,85.0,123.0,FR,France
+1838,198544,3,67356,55744.0,78968.0,122,101.0,143.0,FR,France
+1839,198543,3,87402,74208.0,100596.0,158,134.0,182.0,FR,France
+1840,198542,3,76218,64604.0,87832.0,138,117.0,159.0,FR,France
+1841,198541,3,45712,36755.0,54669.0,83,67.0,99.0,FR,France
+1842,198540,3,49739,40335.0,59143.0,90,73.0,107.0,FR,France
+1843,198539,3,39819,31234.0,48404.0,72,56.0,88.0,FR,France
+1844,198538,3,27605,20614.0,34596.0,50,37.0,63.0,FR,France
+1845,198537,3,22219,15626.0,28812.0,40,28.0,52.0,FR,France
+1846,198536,3,27986,18992.0,36980.0,51,35.0,67.0,FR,France
+1847,198535,3,30215,18546.0,41884.0,55,34.0,76.0,FR,France
+1848,198534,3,40389,24786.0,55992.0,73,45.0,101.0,FR,France
+1849,198533,3,22611,8819.0,36403.0,41,16.0,66.0,FR,France
+1850,198532,3,7488,1851.0,13125.0,14,4.0,24.0,FR,France
+1851,198531,3,16958,8479.0,25437.0,31,16.0,46.0,FR,France
+1852,198530,3,11598,5507.0,17689.0,21,10.0,32.0,FR,France
+1853,198529,3,13054,6474.0,19634.0,24,12.0,36.0,FR,France
+1854,198528,3,14588,7659.0,21517.0,26,13.0,39.0,FR,France
+1855,198527,3,19670,11761.0,27579.0,36,22.0,50.0,FR,France
+1856,198526,3,18609,12637.0,24581.0,34,23.0,45.0,FR,France
+1857,198525,3,19362,12454.0,26270.0,35,22.0,48.0,FR,France
+1858,198524,3,19855,13577.0,26133.0,36,25.0,47.0,FR,France
+1859,198523,3,19373,10010.0,28736.0,35,18.0,52.0,FR,France
+1860,198522,3,24099,17190.0,31008.0,44,31.0,57.0,FR,France
+1861,198521,3,26096,19621.0,32571.0,47,35.0,59.0,FR,France
+1862,198520,3,27896,20885.0,34907.0,51,38.0,64.0,FR,France
+1863,198519,3,43154,32821.0,53487.0,78,59.0,97.0,FR,France
+1864,198518,3,40555,29935.0,51175.0,74,55.0,93.0,FR,France
+1865,198517,3,34053,24366.0,43740.0,62,44.0,80.0,FR,France
+1866,198516,3,50362,36451.0,64273.0,91,66.0,116.0,FR,France
+1867,198515,3,63881,45538.0,82224.0,116,83.0,149.0,FR,France
+1868,198514,3,134545,114400.0,154690.0,244,207.0,281.0,FR,France
+1869,198513,3,197206,176080.0,218332.0,357,319.0,395.0,FR,France
+1870,198512,3,245240,223304.0,267176.0,445,405.0,485.0,FR,France
+1871,198511,3,276205,252399.0,300011.0,501,458.0,544.0,FR,France
+1872,198510,3,353231,326279.0,380183.0,640,591.0,689.0,FR,France
+1873,198509,3,369895,341109.0,398681.0,670,618.0,722.0,FR,France
+1874,198508,3,389886,359529.0,420243.0,707,652.0,762.0,FR,France
+1875,198507,3,471852,432599.0,511105.0,855,784.0,926.0,FR,France
+1876,198506,3,565825,518011.0,613639.0,1026,939.0,1113.0,FR,France
+1877,198505,3,637302,592795.0,681809.0,1155,1074.0,1236.0,FR,France
+1878,198504,3,424937,390794.0,459080.0,770,708.0,832.0,FR,France
+1879,198503,3,213901,174689.0,253113.0,388,317.0,459.0,FR,France
+1880,198502,3,97586,80949.0,114223.0,177,147.0,207.0,FR,France
+1881,198501,3,85489,65918.0,105060.0,155,120.0,190.0,FR,France
+1882,198452,3,84830,60602.0,109058.0,154,110.0,198.0,FR,France
+1883,198451,3,101726,80242.0,123210.0,185,146.0,224.0,FR,France
+1884,198450,3,123680,101401.0,145959.0,225,184.0,266.0,FR,France
+1885,198449,3,101073,81684.0,120462.0,184,149.0,219.0,FR,France
+1886,198448,3,78620,60634.0,96606.0,143,110.0,176.0,FR,France
+1887,198447,3,72029,54274.0,89784.0,131,99.0,163.0,FR,France
+1888,198446,3,87330,67686.0,106974.0,159,123.0,195.0,FR,France
+1889,198445,3,135223,101414.0,169032.0,246,184.0,308.0,FR,France
+1890,198444,3,68422,20056.0,116788.0,125,37.0,213.0,FR,France
diff --git a/module3/exo3/.ipynb b/module3/exo3/.ipynb
new file mode 100644
index 0000000..61344c1
--- /dev/null
+++ b/module3/exo3/.ipynb
@@ -0,0 +1,2516 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Incidence du syndrome grippal"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import pandas as pd\n",
+    "import isoweek\n",
+    "import os\n",
+    "from os import path"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Les données de l'incidence du syndrome grippal sont disponibles du site Web du [Réseau Sentinelles](http://www.sentiweb.fr/). Nous les récupérons sous forme d'un fichier en format CSV dont chaque ligne correspond à une semaine de la période demandée. Nous téléchargeons toujours le jeu de données complet, qui commence en 1984 et se termine avec une semaine récente."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Voici l'explication des colonnes données [sur le site d'origine](https://ns.sentiweb.fr/incidence/csv-schema-v1.json):\n",
+    "\n",
+    "| Nom de colonne | Libellé de colonne                                                                                                                |\n",
+    "|----------------|-----------------------------------------------------------------------------------------------------------------------------------|\n",
+    "| week           | Semaine calendaire (ISO 8601)                                                                                                     |\n",
+    "| indicator      | Code de l'indicateur de surveillance                                                                                              |\n",
+    "| inc            | Estimation de l'incidence de consultations en nombre de cas                                                                       |\n",
+    "| inc_low        | Estimation de la borne inférieure de l'IC95% du nombre de cas de consultation                                                     |\n",
+    "| inc_up         | Estimation de la borne supérieure de l'IC95% du nombre de cas de consultation                                                     |\n",
+    "| inc100         | Estimation du taux d'incidence du nombre de cas de consultation (en cas pour 100,000 habitants)                                   |\n",
+    "| inc100_low     | Estimation de la borne inférieure de l'IC95% du taux d'incidence du nombre de cas de consultation (en cas pour 100,000 habitants) |\n",
+    "| inc100_up      | Estimation de la borne supérieure de l'IC95% du taux d'incidence du nombre de cas de consultation (en cas pour 100,000 habitants) |\n",
+    "| geo_insee      | Code de la zone géographique concernée (Code INSEE) http://www.insee.fr/fr/methodes/nomenclatures/cog/                            |\n",
+    "| geo_name       | Libellé de la zone géographique (ce libellé peut être modifié sans préavis)                                                       |\n",
+    "\n",
+    "La première ligne du fichier CSV est un commentaire, que nous ignorons en précisant `skiprows=1`."
+   ]
+  },
+  {
+   "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>week</th>\n",
+       "      <th>indicator</th>\n",
+       "      <th>inc</th>\n",
+       "      <th>inc_low</th>\n",
+       "      <th>inc_up</th>\n",
+       "      <th>inc100</th>\n",
+       "      <th>inc100_low</th>\n",
+       "      <th>inc100_up</th>\n",
+       "      <th>geo_insee</th>\n",
+       "      <th>geo_name</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>202103</td>\n",
+       "      <td>3</td>\n",
+       "      <td>28139</td>\n",
+       "      <td>22926.0</td>\n",
+       "      <td>33352.0</td>\n",
+       "      <td>43</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>202102</td>\n",
+       "      <td>3</td>\n",
+       "      <td>18010</td>\n",
+       "      <td>14474.0</td>\n",
+       "      <td>21546.0</td>\n",
+       "      <td>27</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>202101</td>\n",
+       "      <td>3</td>\n",
+       "      <td>21809</td>\n",
+       "      <td>17786.0</td>\n",
+       "      <td>25832.0</td>\n",
+       "      <td>33</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>202053</td>\n",
+       "      <td>3</td>\n",
+       "      <td>21220</td>\n",
+       "      <td>16498.0</td>\n",
+       "      <td>25942.0</td>\n",
+       "      <td>32</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>202052</td>\n",
+       "      <td>3</td>\n",
+       "      <td>16428</td>\n",
+       "      <td>12285.0</td>\n",
+       "      <td>20571.0</td>\n",
+       "      <td>25</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>31.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>202051</td>\n",
+       "      <td>3</td>\n",
+       "      <td>21619</td>\n",
+       "      <td>17370.0</td>\n",
+       "      <td>25868.0</td>\n",
+       "      <td>33</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>202050</td>\n",
+       "      <td>3</td>\n",
+       "      <td>16845</td>\n",
+       "      <td>13220.0</td>\n",
+       "      <td>20470.0</td>\n",
+       "      <td>26</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>202049</td>\n",
+       "      <td>3</td>\n",
+       "      <td>12939</td>\n",
+       "      <td>9923.0</td>\n",
+       "      <td>15955.0</td>\n",
+       "      <td>20</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>202048</td>\n",
+       "      <td>3</td>\n",
+       "      <td>13804</td>\n",
+       "      <td>10641.0</td>\n",
+       "      <td>16967.0</td>\n",
+       "      <td>21</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>202047</td>\n",
+       "      <td>3</td>\n",
+       "      <td>19085</td>\n",
+       "      <td>15285.0</td>\n",
+       "      <td>22885.0</td>\n",
+       "      <td>29</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>202046</td>\n",
+       "      <td>3</td>\n",
+       "      <td>24801</td>\n",
+       "      <td>20503.0</td>\n",
+       "      <td>29099.0</td>\n",
+       "      <td>38</td>\n",
+       "      <td>31.0</td>\n",
+       "      <td>45.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>202045</td>\n",
+       "      <td>3</td>\n",
+       "      <td>42516</td>\n",
+       "      <td>36857.0</td>\n",
+       "      <td>48175.0</td>\n",
+       "      <td>65</td>\n",
+       "      <td>56.0</td>\n",
+       "      <td>74.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>202044</td>\n",
+       "      <td>3</td>\n",
+       "      <td>44567</td>\n",
+       "      <td>38521.0</td>\n",
+       "      <td>50613.0</td>\n",
+       "      <td>68</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>77.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>202043</td>\n",
+       "      <td>3</td>\n",
+       "      <td>43737</td>\n",
+       "      <td>37523.0</td>\n",
+       "      <td>49951.0</td>\n",
+       "      <td>66</td>\n",
+       "      <td>57.0</td>\n",
+       "      <td>75.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>202042</td>\n",
+       "      <td>3</td>\n",
+       "      <td>35145</td>\n",
+       "      <td>29812.0</td>\n",
+       "      <td>40478.0</td>\n",
+       "      <td>53</td>\n",
+       "      <td>45.0</td>\n",
+       "      <td>61.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>202041</td>\n",
+       "      <td>3</td>\n",
+       "      <td>27877</td>\n",
+       "      <td>23206.0</td>\n",
+       "      <td>32548.0</td>\n",
+       "      <td>42</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>49.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>202040</td>\n",
+       "      <td>3</td>\n",
+       "      <td>20443</td>\n",
+       "      <td>16381.0</td>\n",
+       "      <td>24505.0</td>\n",
+       "      <td>31</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>37.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>202039</td>\n",
+       "      <td>3</td>\n",
+       "      <td>19810</td>\n",
+       "      <td>15900.0</td>\n",
+       "      <td>23720.0</td>\n",
+       "      <td>30</td>\n",
+       "      <td>24.0</td>\n",
+       "      <td>36.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>202038</td>\n",
+       "      <td>3</td>\n",
+       "      <td>25562</td>\n",
+       "      <td>21142.0</td>\n",
+       "      <td>29982.0</td>\n",
+       "      <td>39</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>46.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>202037</td>\n",
+       "      <td>3</td>\n",
+       "      <td>18485</td>\n",
+       "      <td>14649.0</td>\n",
+       "      <td>22321.0</td>\n",
+       "      <td>28</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>34.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>202036</td>\n",
+       "      <td>3</td>\n",
+       "      <td>10390</td>\n",
+       "      <td>7646.0</td>\n",
+       "      <td>13134.0</td>\n",
+       "      <td>16</td>\n",
+       "      <td>12.0</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>202035</td>\n",
+       "      <td>3</td>\n",
+       "      <td>9918</td>\n",
+       "      <td>6842.0</td>\n",
+       "      <td>12994.0</td>\n",
+       "      <td>15</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>202034</td>\n",
+       "      <td>3</td>\n",
+       "      <td>6084</td>\n",
+       "      <td>3090.0</td>\n",
+       "      <td>9078.0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>202033</td>\n",
+       "      <td>3</td>\n",
+       "      <td>6106</td>\n",
+       "      <td>3411.0</td>\n",
+       "      <td>8801.0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>202032</td>\n",
+       "      <td>3</td>\n",
+       "      <td>5918</td>\n",
+       "      <td>3330.0</td>\n",
+       "      <td>8506.0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>202031</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4351</td>\n",
+       "      <td>2269.0</td>\n",
+       "      <td>6433.0</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>202030</td>\n",
+       "      <td>3</td>\n",
+       "      <td>8179</td>\n",
+       "      <td>5442.0</td>\n",
+       "      <td>10916.0</td>\n",
+       "      <td>12</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>202029</td>\n",
+       "      <td>3</td>\n",
+       "      <td>8687</td>\n",
+       "      <td>5860.0</td>\n",
+       "      <td>11514.0</td>\n",
+       "      <td>13</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>202028</td>\n",
+       "      <td>3</td>\n",
+       "      <td>8340</td>\n",
+       "      <td>5701.0</td>\n",
+       "      <td>10979.0</td>\n",
+       "      <td>13</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>202027</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4066</td>\n",
+       "      <td>2406.0</td>\n",
+       "      <td>5726.0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1861</th>\n",
+       "      <td>198521</td>\n",
+       "      <td>3</td>\n",
+       "      <td>26096</td>\n",
+       "      <td>19621.0</td>\n",
+       "      <td>32571.0</td>\n",
+       "      <td>47</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1862</th>\n",
+       "      <td>198520</td>\n",
+       "      <td>3</td>\n",
+       "      <td>27896</td>\n",
+       "      <td>20885.0</td>\n",
+       "      <td>34907.0</td>\n",
+       "      <td>51</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>64.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1863</th>\n",
+       "      <td>198519</td>\n",
+       "      <td>3</td>\n",
+       "      <td>43154</td>\n",
+       "      <td>32821.0</td>\n",
+       "      <td>53487.0</td>\n",
+       "      <td>78</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>97.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1864</th>\n",
+       "      <td>198518</td>\n",
+       "      <td>3</td>\n",
+       "      <td>40555</td>\n",
+       "      <td>29935.0</td>\n",
+       "      <td>51175.0</td>\n",
+       "      <td>74</td>\n",
+       "      <td>55.0</td>\n",
+       "      <td>93.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1865</th>\n",
+       "      <td>198517</td>\n",
+       "      <td>3</td>\n",
+       "      <td>34053</td>\n",
+       "      <td>24366.0</td>\n",
+       "      <td>43740.0</td>\n",
+       "      <td>62</td>\n",
+       "      <td>44.0</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1866</th>\n",
+       "      <td>198516</td>\n",
+       "      <td>3</td>\n",
+       "      <td>50362</td>\n",
+       "      <td>36451.0</td>\n",
+       "      <td>64273.0</td>\n",
+       "      <td>91</td>\n",
+       "      <td>66.0</td>\n",
+       "      <td>116.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1867</th>\n",
+       "      <td>198515</td>\n",
+       "      <td>3</td>\n",
+       "      <td>63881</td>\n",
+       "      <td>45538.0</td>\n",
+       "      <td>82224.0</td>\n",
+       "      <td>116</td>\n",
+       "      <td>83.0</td>\n",
+       "      <td>149.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1868</th>\n",
+       "      <td>198514</td>\n",
+       "      <td>3</td>\n",
+       "      <td>134545</td>\n",
+       "      <td>114400.0</td>\n",
+       "      <td>154690.0</td>\n",
+       "      <td>244</td>\n",
+       "      <td>207.0</td>\n",
+       "      <td>281.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1869</th>\n",
+       "      <td>198513</td>\n",
+       "      <td>3</td>\n",
+       "      <td>197206</td>\n",
+       "      <td>176080.0</td>\n",
+       "      <td>218332.0</td>\n",
+       "      <td>357</td>\n",
+       "      <td>319.0</td>\n",
+       "      <td>395.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1870</th>\n",
+       "      <td>198512</td>\n",
+       "      <td>3</td>\n",
+       "      <td>245240</td>\n",
+       "      <td>223304.0</td>\n",
+       "      <td>267176.0</td>\n",
+       "      <td>445</td>\n",
+       "      <td>405.0</td>\n",
+       "      <td>485.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1871</th>\n",
+       "      <td>198511</td>\n",
+       "      <td>3</td>\n",
+       "      <td>276205</td>\n",
+       "      <td>252399.0</td>\n",
+       "      <td>300011.0</td>\n",
+       "      <td>501</td>\n",
+       "      <td>458.0</td>\n",
+       "      <td>544.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1872</th>\n",
+       "      <td>198510</td>\n",
+       "      <td>3</td>\n",
+       "      <td>353231</td>\n",
+       "      <td>326279.0</td>\n",
+       "      <td>380183.0</td>\n",
+       "      <td>640</td>\n",
+       "      <td>591.0</td>\n",
+       "      <td>689.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1873</th>\n",
+       "      <td>198509</td>\n",
+       "      <td>3</td>\n",
+       "      <td>369895</td>\n",
+       "      <td>341109.0</td>\n",
+       "      <td>398681.0</td>\n",
+       "      <td>670</td>\n",
+       "      <td>618.0</td>\n",
+       "      <td>722.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1874</th>\n",
+       "      <td>198508</td>\n",
+       "      <td>3</td>\n",
+       "      <td>389886</td>\n",
+       "      <td>359529.0</td>\n",
+       "      <td>420243.0</td>\n",
+       "      <td>707</td>\n",
+       "      <td>652.0</td>\n",
+       "      <td>762.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1875</th>\n",
+       "      <td>198507</td>\n",
+       "      <td>3</td>\n",
+       "      <td>471852</td>\n",
+       "      <td>432599.0</td>\n",
+       "      <td>511105.0</td>\n",
+       "      <td>855</td>\n",
+       "      <td>784.0</td>\n",
+       "      <td>926.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1876</th>\n",
+       "      <td>198506</td>\n",
+       "      <td>3</td>\n",
+       "      <td>565825</td>\n",
+       "      <td>518011.0</td>\n",
+       "      <td>613639.0</td>\n",
+       "      <td>1026</td>\n",
+       "      <td>939.0</td>\n",
+       "      <td>1113.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1877</th>\n",
+       "      <td>198505</td>\n",
+       "      <td>3</td>\n",
+       "      <td>637302</td>\n",
+       "      <td>592795.0</td>\n",
+       "      <td>681809.0</td>\n",
+       "      <td>1155</td>\n",
+       "      <td>1074.0</td>\n",
+       "      <td>1236.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1878</th>\n",
+       "      <td>198504</td>\n",
+       "      <td>3</td>\n",
+       "      <td>424937</td>\n",
+       "      <td>390794.0</td>\n",
+       "      <td>459080.0</td>\n",
+       "      <td>770</td>\n",
+       "      <td>708.0</td>\n",
+       "      <td>832.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1879</th>\n",
+       "      <td>198503</td>\n",
+       "      <td>3</td>\n",
+       "      <td>213901</td>\n",
+       "      <td>174689.0</td>\n",
+       "      <td>253113.0</td>\n",
+       "      <td>388</td>\n",
+       "      <td>317.0</td>\n",
+       "      <td>459.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1880</th>\n",
+       "      <td>198502</td>\n",
+       "      <td>3</td>\n",
+       "      <td>97586</td>\n",
+       "      <td>80949.0</td>\n",
+       "      <td>114223.0</td>\n",
+       "      <td>177</td>\n",
+       "      <td>147.0</td>\n",
+       "      <td>207.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1881</th>\n",
+       "      <td>198501</td>\n",
+       "      <td>3</td>\n",
+       "      <td>85489</td>\n",
+       "      <td>65918.0</td>\n",
+       "      <td>105060.0</td>\n",
+       "      <td>155</td>\n",
+       "      <td>120.0</td>\n",
+       "      <td>190.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1882</th>\n",
+       "      <td>198452</td>\n",
+       "      <td>3</td>\n",
+       "      <td>84830</td>\n",
+       "      <td>60602.0</td>\n",
+       "      <td>109058.0</td>\n",
+       "      <td>154</td>\n",
+       "      <td>110.0</td>\n",
+       "      <td>198.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1883</th>\n",
+       "      <td>198451</td>\n",
+       "      <td>3</td>\n",
+       "      <td>101726</td>\n",
+       "      <td>80242.0</td>\n",
+       "      <td>123210.0</td>\n",
+       "      <td>185</td>\n",
+       "      <td>146.0</td>\n",
+       "      <td>224.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1884</th>\n",
+       "      <td>198450</td>\n",
+       "      <td>3</td>\n",
+       "      <td>123680</td>\n",
+       "      <td>101401.0</td>\n",
+       "      <td>145959.0</td>\n",
+       "      <td>225</td>\n",
+       "      <td>184.0</td>\n",
+       "      <td>266.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1885</th>\n",
+       "      <td>198449</td>\n",
+       "      <td>3</td>\n",
+       "      <td>101073</td>\n",
+       "      <td>81684.0</td>\n",
+       "      <td>120462.0</td>\n",
+       "      <td>184</td>\n",
+       "      <td>149.0</td>\n",
+       "      <td>219.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1886</th>\n",
+       "      <td>198448</td>\n",
+       "      <td>3</td>\n",
+       "      <td>78620</td>\n",
+       "      <td>60634.0</td>\n",
+       "      <td>96606.0</td>\n",
+       "      <td>143</td>\n",
+       "      <td>110.0</td>\n",
+       "      <td>176.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1887</th>\n",
+       "      <td>198447</td>\n",
+       "      <td>3</td>\n",
+       "      <td>72029</td>\n",
+       "      <td>54274.0</td>\n",
+       "      <td>89784.0</td>\n",
+       "      <td>131</td>\n",
+       "      <td>99.0</td>\n",
+       "      <td>163.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1888</th>\n",
+       "      <td>198446</td>\n",
+       "      <td>3</td>\n",
+       "      <td>87330</td>\n",
+       "      <td>67686.0</td>\n",
+       "      <td>106974.0</td>\n",
+       "      <td>159</td>\n",
+       "      <td>123.0</td>\n",
+       "      <td>195.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1889</th>\n",
+       "      <td>198445</td>\n",
+       "      <td>3</td>\n",
+       "      <td>135223</td>\n",
+       "      <td>101414.0</td>\n",
+       "      <td>169032.0</td>\n",
+       "      <td>246</td>\n",
+       "      <td>184.0</td>\n",
+       "      <td>308.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1890</th>\n",
+       "      <td>198444</td>\n",
+       "      <td>3</td>\n",
+       "      <td>68422</td>\n",
+       "      <td>20056.0</td>\n",
+       "      <td>116788.0</td>\n",
+       "      <td>125</td>\n",
+       "      <td>37.0</td>\n",
+       "      <td>213.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1891 rows × 10 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        week  indicator     inc   inc_low    inc_up  inc100  inc100_low  \\\n",
+       "0     202103          3   28139   22926.0   33352.0      43        35.0   \n",
+       "1     202102          3   18010   14474.0   21546.0      27        22.0   \n",
+       "2     202101          3   21809   17786.0   25832.0      33        27.0   \n",
+       "3     202053          3   21220   16498.0   25942.0      32        25.0   \n",
+       "4     202052          3   16428   12285.0   20571.0      25        19.0   \n",
+       "5     202051          3   21619   17370.0   25868.0      33        27.0   \n",
+       "6     202050          3   16845   13220.0   20470.0      26        20.0   \n",
+       "7     202049          3   12939    9923.0   15955.0      20        15.0   \n",
+       "8     202048          3   13804   10641.0   16967.0      21        16.0   \n",
+       "9     202047          3   19085   15285.0   22885.0      29        23.0   \n",
+       "10    202046          3   24801   20503.0   29099.0      38        31.0   \n",
+       "11    202045          3   42516   36857.0   48175.0      65        56.0   \n",
+       "12    202044          3   44567   38521.0   50613.0      68        59.0   \n",
+       "13    202043          3   43737   37523.0   49951.0      66        57.0   \n",
+       "14    202042          3   35145   29812.0   40478.0      53        45.0   \n",
+       "15    202041          3   27877   23206.0   32548.0      42        35.0   \n",
+       "16    202040          3   20443   16381.0   24505.0      31        25.0   \n",
+       "17    202039          3   19810   15900.0   23720.0      30        24.0   \n",
+       "18    202038          3   25562   21142.0   29982.0      39        32.0   \n",
+       "19    202037          3   18485   14649.0   22321.0      28        22.0   \n",
+       "20    202036          3   10390    7646.0   13134.0      16        12.0   \n",
+       "21    202035          3    9918    6842.0   12994.0      15        10.0   \n",
+       "22    202034          3    6084    3090.0    9078.0       9         4.0   \n",
+       "23    202033          3    6106    3411.0    8801.0       9         5.0   \n",
+       "24    202032          3    5918    3330.0    8506.0       9         5.0   \n",
+       "25    202031          3    4351    2269.0    6433.0       7         4.0   \n",
+       "26    202030          3    8179    5442.0   10916.0      12         8.0   \n",
+       "27    202029          3    8687    5860.0   11514.0      13         9.0   \n",
+       "28    202028          3    8340    5701.0   10979.0      13         9.0   \n",
+       "29    202027          3    4066    2406.0    5726.0       6         3.0   \n",
+       "...      ...        ...     ...       ...       ...     ...         ...   \n",
+       "1861  198521          3   26096   19621.0   32571.0      47        35.0   \n",
+       "1862  198520          3   27896   20885.0   34907.0      51        38.0   \n",
+       "1863  198519          3   43154   32821.0   53487.0      78        59.0   \n",
+       "1864  198518          3   40555   29935.0   51175.0      74        55.0   \n",
+       "1865  198517          3   34053   24366.0   43740.0      62        44.0   \n",
+       "1866  198516          3   50362   36451.0   64273.0      91        66.0   \n",
+       "1867  198515          3   63881   45538.0   82224.0     116        83.0   \n",
+       "1868  198514          3  134545  114400.0  154690.0     244       207.0   \n",
+       "1869  198513          3  197206  176080.0  218332.0     357       319.0   \n",
+       "1870  198512          3  245240  223304.0  267176.0     445       405.0   \n",
+       "1871  198511          3  276205  252399.0  300011.0     501       458.0   \n",
+       "1872  198510          3  353231  326279.0  380183.0     640       591.0   \n",
+       "1873  198509          3  369895  341109.0  398681.0     670       618.0   \n",
+       "1874  198508          3  389886  359529.0  420243.0     707       652.0   \n",
+       "1875  198507          3  471852  432599.0  511105.0     855       784.0   \n",
+       "1876  198506          3  565825  518011.0  613639.0    1026       939.0   \n",
+       "1877  198505          3  637302  592795.0  681809.0    1155      1074.0   \n",
+       "1878  198504          3  424937  390794.0  459080.0     770       708.0   \n",
+       "1879  198503          3  213901  174689.0  253113.0     388       317.0   \n",
+       "1880  198502          3   97586   80949.0  114223.0     177       147.0   \n",
+       "1881  198501          3   85489   65918.0  105060.0     155       120.0   \n",
+       "1882  198452          3   84830   60602.0  109058.0     154       110.0   \n",
+       "1883  198451          3  101726   80242.0  123210.0     185       146.0   \n",
+       "1884  198450          3  123680  101401.0  145959.0     225       184.0   \n",
+       "1885  198449          3  101073   81684.0  120462.0     184       149.0   \n",
+       "1886  198448          3   78620   60634.0   96606.0     143       110.0   \n",
+       "1887  198447          3   72029   54274.0   89784.0     131        99.0   \n",
+       "1888  198446          3   87330   67686.0  106974.0     159       123.0   \n",
+       "1889  198445          3  135223  101414.0  169032.0     246       184.0   \n",
+       "1890  198444          3   68422   20056.0  116788.0     125        37.0   \n",
+       "\n",
+       "      inc100_up geo_insee geo_name  \n",
+       "0          51.0        FR   France  \n",
+       "1          32.0        FR   France  \n",
+       "2          39.0        FR   France  \n",
+       "3          39.0        FR   France  \n",
+       "4          31.0        FR   France  \n",
+       "5          39.0        FR   France  \n",
+       "6          32.0        FR   France  \n",
+       "7          25.0        FR   France  \n",
+       "8          26.0        FR   France  \n",
+       "9          35.0        FR   France  \n",
+       "10         45.0        FR   France  \n",
+       "11         74.0        FR   France  \n",
+       "12         77.0        FR   France  \n",
+       "13         75.0        FR   France  \n",
+       "14         61.0        FR   France  \n",
+       "15         49.0        FR   France  \n",
+       "16         37.0        FR   France  \n",
+       "17         36.0        FR   France  \n",
+       "18         46.0        FR   France  \n",
+       "19         34.0        FR   France  \n",
+       "20         20.0        FR   France  \n",
+       "21         20.0        FR   France  \n",
+       "22         14.0        FR   France  \n",
+       "23         13.0        FR   France  \n",
+       "24         13.0        FR   France  \n",
+       "25         10.0        FR   France  \n",
+       "26         16.0        FR   France  \n",
+       "27         17.0        FR   France  \n",
+       "28         17.0        FR   France  \n",
+       "29          9.0        FR   France  \n",
+       "...         ...       ...      ...  \n",
+       "1861       59.0        FR   France  \n",
+       "1862       64.0        FR   France  \n",
+       "1863       97.0        FR   France  \n",
+       "1864       93.0        FR   France  \n",
+       "1865       80.0        FR   France  \n",
+       "1866      116.0        FR   France  \n",
+       "1867      149.0        FR   France  \n",
+       "1868      281.0        FR   France  \n",
+       "1869      395.0        FR   France  \n",
+       "1870      485.0        FR   France  \n",
+       "1871      544.0        FR   France  \n",
+       "1872      689.0        FR   France  \n",
+       "1873      722.0        FR   France  \n",
+       "1874      762.0        FR   France  \n",
+       "1875      926.0        FR   France  \n",
+       "1876     1113.0        FR   France  \n",
+       "1877     1236.0        FR   France  \n",
+       "1878      832.0        FR   France  \n",
+       "1879      459.0        FR   France  \n",
+       "1880      207.0        FR   France  \n",
+       "1881      190.0        FR   France  \n",
+       "1882      198.0        FR   France  \n",
+       "1883      224.0        FR   France  \n",
+       "1884      266.0        FR   France  \n",
+       "1885      219.0        FR   France  \n",
+       "1886      176.0        FR   France  \n",
+       "1887      163.0        FR   France  \n",
+       "1888      195.0        FR   France  \n",
+       "1889      308.0        FR   France  \n",
+       "1890      213.0        FR   France  \n",
+       "\n",
+       "[1891 rows x 10 columns]"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "if (path.exists(\"incidence.csv\")):\n",
+    "    raw_data = pd.read_csv(\"incidence.csv\", index_col = 0)\n",
+    "else:\n",
+    "    raw_data = pd.read_csv(data_url, skiprows=1)\n",
+    "    raw_data.to_csv(\"incidence.csv\")\n",
+    "raw_data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Y a-t-il des points manquants dans ce jeux de données ? Oui, la semaine 19 de l'année 1989 n'a pas de valeurs associées."
+   ]
+  },
+  {
+   "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>week</th>\n",
+       "      <th>indicator</th>\n",
+       "      <th>inc</th>\n",
+       "      <th>inc_low</th>\n",
+       "      <th>inc_up</th>\n",
+       "      <th>inc100</th>\n",
+       "      <th>inc100_low</th>\n",
+       "      <th>inc100_up</th>\n",
+       "      <th>geo_insee</th>\n",
+       "      <th>geo_name</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1652</th>\n",
+       "      <td>198919</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        week  indicator  inc  inc_low  inc_up  inc100  inc100_low  inc100_up  \\\n",
+       "1652  198919          3    0      NaN     NaN       0         NaN        NaN   \n",
+       "\n",
+       "     geo_insee geo_name  \n",
+       "1652        FR   France  "
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data[raw_data.isnull().any(axis=1)]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Nous éliminons ce point, ce qui n'a pas d'impact fort sur notre analyse qui est assez simple."
+   ]
+  },
+  {
+   "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>week</th>\n",
+       "      <th>indicator</th>\n",
+       "      <th>inc</th>\n",
+       "      <th>inc_low</th>\n",
+       "      <th>inc_up</th>\n",
+       "      <th>inc100</th>\n",
+       "      <th>inc100_low</th>\n",
+       "      <th>inc100_up</th>\n",
+       "      <th>geo_insee</th>\n",
+       "      <th>geo_name</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>202101</td>\n",
+       "      <td>3</td>\n",
+       "      <td>30168</td>\n",
+       "      <td>24407.0</td>\n",
+       "      <td>35929.0</td>\n",
+       "      <td>46</td>\n",
+       "      <td>37.0</td>\n",
+       "      <td>55.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>202053</td>\n",
+       "      <td>3</td>\n",
+       "      <td>21449</td>\n",
+       "      <td>16669.0</td>\n",
+       "      <td>26229.0</td>\n",
+       "      <td>33</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>202052</td>\n",
+       "      <td>3</td>\n",
+       "      <td>16428</td>\n",
+       "      <td>12285.0</td>\n",
+       "      <td>20571.0</td>\n",
+       "      <td>25</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>31.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>202051</td>\n",
+       "      <td>3</td>\n",
+       "      <td>21619</td>\n",
+       "      <td>17370.0</td>\n",
+       "      <td>25868.0</td>\n",
+       "      <td>33</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>202050</td>\n",
+       "      <td>3</td>\n",
+       "      <td>16845</td>\n",
+       "      <td>13220.0</td>\n",
+       "      <td>20470.0</td>\n",
+       "      <td>26</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>202049</td>\n",
+       "      <td>3</td>\n",
+       "      <td>12939</td>\n",
+       "      <td>9923.0</td>\n",
+       "      <td>15955.0</td>\n",
+       "      <td>20</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>202048</td>\n",
+       "      <td>3</td>\n",
+       "      <td>13804</td>\n",
+       "      <td>10641.0</td>\n",
+       "      <td>16967.0</td>\n",
+       "      <td>21</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>202047</td>\n",
+       "      <td>3</td>\n",
+       "      <td>19085</td>\n",
+       "      <td>15285.0</td>\n",
+       "      <td>22885.0</td>\n",
+       "      <td>29</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>202046</td>\n",
+       "      <td>3</td>\n",
+       "      <td>24801</td>\n",
+       "      <td>20503.0</td>\n",
+       "      <td>29099.0</td>\n",
+       "      <td>38</td>\n",
+       "      <td>31.0</td>\n",
+       "      <td>45.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>202045</td>\n",
+       "      <td>3</td>\n",
+       "      <td>42516</td>\n",
+       "      <td>36857.0</td>\n",
+       "      <td>48175.0</td>\n",
+       "      <td>65</td>\n",
+       "      <td>56.0</td>\n",
+       "      <td>74.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>202044</td>\n",
+       "      <td>3</td>\n",
+       "      <td>44567</td>\n",
+       "      <td>38521.0</td>\n",
+       "      <td>50613.0</td>\n",
+       "      <td>68</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>77.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>202043</td>\n",
+       "      <td>3</td>\n",
+       "      <td>43737</td>\n",
+       "      <td>37523.0</td>\n",
+       "      <td>49951.0</td>\n",
+       "      <td>66</td>\n",
+       "      <td>57.0</td>\n",
+       "      <td>75.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>202042</td>\n",
+       "      <td>3</td>\n",
+       "      <td>35145</td>\n",
+       "      <td>29812.0</td>\n",
+       "      <td>40478.0</td>\n",
+       "      <td>53</td>\n",
+       "      <td>45.0</td>\n",
+       "      <td>61.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>202041</td>\n",
+       "      <td>3</td>\n",
+       "      <td>27877</td>\n",
+       "      <td>23206.0</td>\n",
+       "      <td>32548.0</td>\n",
+       "      <td>42</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>49.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>202040</td>\n",
+       "      <td>3</td>\n",
+       "      <td>20443</td>\n",
+       "      <td>16381.0</td>\n",
+       "      <td>24505.0</td>\n",
+       "      <td>31</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>37.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>202039</td>\n",
+       "      <td>3</td>\n",
+       "      <td>19810</td>\n",
+       "      <td>15900.0</td>\n",
+       "      <td>23720.0</td>\n",
+       "      <td>30</td>\n",
+       "      <td>24.0</td>\n",
+       "      <td>36.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>202038</td>\n",
+       "      <td>3</td>\n",
+       "      <td>25562</td>\n",
+       "      <td>21142.0</td>\n",
+       "      <td>29982.0</td>\n",
+       "      <td>39</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>46.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>202037</td>\n",
+       "      <td>3</td>\n",
+       "      <td>18485</td>\n",
+       "      <td>14649.0</td>\n",
+       "      <td>22321.0</td>\n",
+       "      <td>28</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>34.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>202036</td>\n",
+       "      <td>3</td>\n",
+       "      <td>10390</td>\n",
+       "      <td>7646.0</td>\n",
+       "      <td>13134.0</td>\n",
+       "      <td>16</td>\n",
+       "      <td>12.0</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>202035</td>\n",
+       "      <td>3</td>\n",
+       "      <td>9918</td>\n",
+       "      <td>6842.0</td>\n",
+       "      <td>12994.0</td>\n",
+       "      <td>15</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>202034</td>\n",
+       "      <td>3</td>\n",
+       "      <td>6084</td>\n",
+       "      <td>3090.0</td>\n",
+       "      <td>9078.0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>202033</td>\n",
+       "      <td>3</td>\n",
+       "      <td>6106</td>\n",
+       "      <td>3411.0</td>\n",
+       "      <td>8801.0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>202032</td>\n",
+       "      <td>3</td>\n",
+       "      <td>5918</td>\n",
+       "      <td>3330.0</td>\n",
+       "      <td>8506.0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>202031</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4351</td>\n",
+       "      <td>2269.0</td>\n",
+       "      <td>6433.0</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>202030</td>\n",
+       "      <td>3</td>\n",
+       "      <td>8179</td>\n",
+       "      <td>5442.0</td>\n",
+       "      <td>10916.0</td>\n",
+       "      <td>12</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>202029</td>\n",
+       "      <td>3</td>\n",
+       "      <td>8687</td>\n",
+       "      <td>5860.0</td>\n",
+       "      <td>11514.0</td>\n",
+       "      <td>13</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>202028</td>\n",
+       "      <td>3</td>\n",
+       "      <td>8340</td>\n",
+       "      <td>5701.0</td>\n",
+       "      <td>10979.0</td>\n",
+       "      <td>13</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>202027</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4066</td>\n",
+       "      <td>2406.0</td>\n",
+       "      <td>5726.0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>202026</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4039</td>\n",
+       "      <td>2389.0</td>\n",
+       "      <td>5689.0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>202025</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2853</td>\n",
+       "      <td>1488.0</td>\n",
+       "      <td>4218.0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1859</th>\n",
+       "      <td>198521</td>\n",
+       "      <td>3</td>\n",
+       "      <td>26096</td>\n",
+       "      <td>19621.0</td>\n",
+       "      <td>32571.0</td>\n",
+       "      <td>47</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1860</th>\n",
+       "      <td>198520</td>\n",
+       "      <td>3</td>\n",
+       "      <td>27896</td>\n",
+       "      <td>20885.0</td>\n",
+       "      <td>34907.0</td>\n",
+       "      <td>51</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>64.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1861</th>\n",
+       "      <td>198519</td>\n",
+       "      <td>3</td>\n",
+       "      <td>43154</td>\n",
+       "      <td>32821.0</td>\n",
+       "      <td>53487.0</td>\n",
+       "      <td>78</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>97.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1862</th>\n",
+       "      <td>198518</td>\n",
+       "      <td>3</td>\n",
+       "      <td>40555</td>\n",
+       "      <td>29935.0</td>\n",
+       "      <td>51175.0</td>\n",
+       "      <td>74</td>\n",
+       "      <td>55.0</td>\n",
+       "      <td>93.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1863</th>\n",
+       "      <td>198517</td>\n",
+       "      <td>3</td>\n",
+       "      <td>34053</td>\n",
+       "      <td>24366.0</td>\n",
+       "      <td>43740.0</td>\n",
+       "      <td>62</td>\n",
+       "      <td>44.0</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1864</th>\n",
+       "      <td>198516</td>\n",
+       "      <td>3</td>\n",
+       "      <td>50362</td>\n",
+       "      <td>36451.0</td>\n",
+       "      <td>64273.0</td>\n",
+       "      <td>91</td>\n",
+       "      <td>66.0</td>\n",
+       "      <td>116.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1865</th>\n",
+       "      <td>198515</td>\n",
+       "      <td>3</td>\n",
+       "      <td>63881</td>\n",
+       "      <td>45538.0</td>\n",
+       "      <td>82224.0</td>\n",
+       "      <td>116</td>\n",
+       "      <td>83.0</td>\n",
+       "      <td>149.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1866</th>\n",
+       "      <td>198514</td>\n",
+       "      <td>3</td>\n",
+       "      <td>134545</td>\n",
+       "      <td>114400.0</td>\n",
+       "      <td>154690.0</td>\n",
+       "      <td>244</td>\n",
+       "      <td>207.0</td>\n",
+       "      <td>281.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1867</th>\n",
+       "      <td>198513</td>\n",
+       "      <td>3</td>\n",
+       "      <td>197206</td>\n",
+       "      <td>176080.0</td>\n",
+       "      <td>218332.0</td>\n",
+       "      <td>357</td>\n",
+       "      <td>319.0</td>\n",
+       "      <td>395.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1868</th>\n",
+       "      <td>198512</td>\n",
+       "      <td>3</td>\n",
+       "      <td>245240</td>\n",
+       "      <td>223304.0</td>\n",
+       "      <td>267176.0</td>\n",
+       "      <td>445</td>\n",
+       "      <td>405.0</td>\n",
+       "      <td>485.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1869</th>\n",
+       "      <td>198511</td>\n",
+       "      <td>3</td>\n",
+       "      <td>276205</td>\n",
+       "      <td>252399.0</td>\n",
+       "      <td>300011.0</td>\n",
+       "      <td>501</td>\n",
+       "      <td>458.0</td>\n",
+       "      <td>544.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1870</th>\n",
+       "      <td>198510</td>\n",
+       "      <td>3</td>\n",
+       "      <td>353231</td>\n",
+       "      <td>326279.0</td>\n",
+       "      <td>380183.0</td>\n",
+       "      <td>640</td>\n",
+       "      <td>591.0</td>\n",
+       "      <td>689.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1871</th>\n",
+       "      <td>198509</td>\n",
+       "      <td>3</td>\n",
+       "      <td>369895</td>\n",
+       "      <td>341109.0</td>\n",
+       "      <td>398681.0</td>\n",
+       "      <td>670</td>\n",
+       "      <td>618.0</td>\n",
+       "      <td>722.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1872</th>\n",
+       "      <td>198508</td>\n",
+       "      <td>3</td>\n",
+       "      <td>389886</td>\n",
+       "      <td>359529.0</td>\n",
+       "      <td>420243.0</td>\n",
+       "      <td>707</td>\n",
+       "      <td>652.0</td>\n",
+       "      <td>762.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1873</th>\n",
+       "      <td>198507</td>\n",
+       "      <td>3</td>\n",
+       "      <td>471852</td>\n",
+       "      <td>432599.0</td>\n",
+       "      <td>511105.0</td>\n",
+       "      <td>855</td>\n",
+       "      <td>784.0</td>\n",
+       "      <td>926.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1874</th>\n",
+       "      <td>198506</td>\n",
+       "      <td>3</td>\n",
+       "      <td>565825</td>\n",
+       "      <td>518011.0</td>\n",
+       "      <td>613639.0</td>\n",
+       "      <td>1026</td>\n",
+       "      <td>939.0</td>\n",
+       "      <td>1113.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1875</th>\n",
+       "      <td>198505</td>\n",
+       "      <td>3</td>\n",
+       "      <td>637302</td>\n",
+       "      <td>592795.0</td>\n",
+       "      <td>681809.0</td>\n",
+       "      <td>1155</td>\n",
+       "      <td>1074.0</td>\n",
+       "      <td>1236.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1876</th>\n",
+       "      <td>198504</td>\n",
+       "      <td>3</td>\n",
+       "      <td>424937</td>\n",
+       "      <td>390794.0</td>\n",
+       "      <td>459080.0</td>\n",
+       "      <td>770</td>\n",
+       "      <td>708.0</td>\n",
+       "      <td>832.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1877</th>\n",
+       "      <td>198503</td>\n",
+       "      <td>3</td>\n",
+       "      <td>213901</td>\n",
+       "      <td>174689.0</td>\n",
+       "      <td>253113.0</td>\n",
+       "      <td>388</td>\n",
+       "      <td>317.0</td>\n",
+       "      <td>459.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1878</th>\n",
+       "      <td>198502</td>\n",
+       "      <td>3</td>\n",
+       "      <td>97586</td>\n",
+       "      <td>80949.0</td>\n",
+       "      <td>114223.0</td>\n",
+       "      <td>177</td>\n",
+       "      <td>147.0</td>\n",
+       "      <td>207.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1879</th>\n",
+       "      <td>198501</td>\n",
+       "      <td>3</td>\n",
+       "      <td>85489</td>\n",
+       "      <td>65918.0</td>\n",
+       "      <td>105060.0</td>\n",
+       "      <td>155</td>\n",
+       "      <td>120.0</td>\n",
+       "      <td>190.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1880</th>\n",
+       "      <td>198452</td>\n",
+       "      <td>3</td>\n",
+       "      <td>84830</td>\n",
+       "      <td>60602.0</td>\n",
+       "      <td>109058.0</td>\n",
+       "      <td>154</td>\n",
+       "      <td>110.0</td>\n",
+       "      <td>198.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1881</th>\n",
+       "      <td>198451</td>\n",
+       "      <td>3</td>\n",
+       "      <td>101726</td>\n",
+       "      <td>80242.0</td>\n",
+       "      <td>123210.0</td>\n",
+       "      <td>185</td>\n",
+       "      <td>146.0</td>\n",
+       "      <td>224.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1882</th>\n",
+       "      <td>198450</td>\n",
+       "      <td>3</td>\n",
+       "      <td>123680</td>\n",
+       "      <td>101401.0</td>\n",
+       "      <td>145959.0</td>\n",
+       "      <td>225</td>\n",
+       "      <td>184.0</td>\n",
+       "      <td>266.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1883</th>\n",
+       "      <td>198449</td>\n",
+       "      <td>3</td>\n",
+       "      <td>101073</td>\n",
+       "      <td>81684.0</td>\n",
+       "      <td>120462.0</td>\n",
+       "      <td>184</td>\n",
+       "      <td>149.0</td>\n",
+       "      <td>219.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1884</th>\n",
+       "      <td>198448</td>\n",
+       "      <td>3</td>\n",
+       "      <td>78620</td>\n",
+       "      <td>60634.0</td>\n",
+       "      <td>96606.0</td>\n",
+       "      <td>143</td>\n",
+       "      <td>110.0</td>\n",
+       "      <td>176.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1885</th>\n",
+       "      <td>198447</td>\n",
+       "      <td>3</td>\n",
+       "      <td>72029</td>\n",
+       "      <td>54274.0</td>\n",
+       "      <td>89784.0</td>\n",
+       "      <td>131</td>\n",
+       "      <td>99.0</td>\n",
+       "      <td>163.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1886</th>\n",
+       "      <td>198446</td>\n",
+       "      <td>3</td>\n",
+       "      <td>87330</td>\n",
+       "      <td>67686.0</td>\n",
+       "      <td>106974.0</td>\n",
+       "      <td>159</td>\n",
+       "      <td>123.0</td>\n",
+       "      <td>195.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1887</th>\n",
+       "      <td>198445</td>\n",
+       "      <td>3</td>\n",
+       "      <td>135223</td>\n",
+       "      <td>101414.0</td>\n",
+       "      <td>169032.0</td>\n",
+       "      <td>246</td>\n",
+       "      <td>184.0</td>\n",
+       "      <td>308.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1888</th>\n",
+       "      <td>198444</td>\n",
+       "      <td>3</td>\n",
+       "      <td>68422</td>\n",
+       "      <td>20056.0</td>\n",
+       "      <td>116788.0</td>\n",
+       "      <td>125</td>\n",
+       "      <td>37.0</td>\n",
+       "      <td>213.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1888 rows × 10 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        week  indicator     inc   inc_low    inc_up  inc100  inc100_low  \\\n",
+       "0     202101          3   30168   24407.0   35929.0      46        37.0   \n",
+       "1     202053          3   21449   16669.0   26229.0      33        26.0   \n",
+       "2     202052          3   16428   12285.0   20571.0      25        19.0   \n",
+       "3     202051          3   21619   17370.0   25868.0      33        27.0   \n",
+       "4     202050          3   16845   13220.0   20470.0      26        20.0   \n",
+       "5     202049          3   12939    9923.0   15955.0      20        15.0   \n",
+       "6     202048          3   13804   10641.0   16967.0      21        16.0   \n",
+       "7     202047          3   19085   15285.0   22885.0      29        23.0   \n",
+       "8     202046          3   24801   20503.0   29099.0      38        31.0   \n",
+       "9     202045          3   42516   36857.0   48175.0      65        56.0   \n",
+       "10    202044          3   44567   38521.0   50613.0      68        59.0   \n",
+       "11    202043          3   43737   37523.0   49951.0      66        57.0   \n",
+       "12    202042          3   35145   29812.0   40478.0      53        45.0   \n",
+       "13    202041          3   27877   23206.0   32548.0      42        35.0   \n",
+       "14    202040          3   20443   16381.0   24505.0      31        25.0   \n",
+       "15    202039          3   19810   15900.0   23720.0      30        24.0   \n",
+       "16    202038          3   25562   21142.0   29982.0      39        32.0   \n",
+       "17    202037          3   18485   14649.0   22321.0      28        22.0   \n",
+       "18    202036          3   10390    7646.0   13134.0      16        12.0   \n",
+       "19    202035          3    9918    6842.0   12994.0      15        10.0   \n",
+       "20    202034          3    6084    3090.0    9078.0       9         4.0   \n",
+       "21    202033          3    6106    3411.0    8801.0       9         5.0   \n",
+       "22    202032          3    5918    3330.0    8506.0       9         5.0   \n",
+       "23    202031          3    4351    2269.0    6433.0       7         4.0   \n",
+       "24    202030          3    8179    5442.0   10916.0      12         8.0   \n",
+       "25    202029          3    8687    5860.0   11514.0      13         9.0   \n",
+       "26    202028          3    8340    5701.0   10979.0      13         9.0   \n",
+       "27    202027          3    4066    2406.0    5726.0       6         3.0   \n",
+       "28    202026          3    4039    2389.0    5689.0       6         3.0   \n",
+       "29    202025          3    2853    1488.0    4218.0       4         2.0   \n",
+       "...      ...        ...     ...       ...       ...     ...         ...   \n",
+       "1859  198521          3   26096   19621.0   32571.0      47        35.0   \n",
+       "1860  198520          3   27896   20885.0   34907.0      51        38.0   \n",
+       "1861  198519          3   43154   32821.0   53487.0      78        59.0   \n",
+       "1862  198518          3   40555   29935.0   51175.0      74        55.0   \n",
+       "1863  198517          3   34053   24366.0   43740.0      62        44.0   \n",
+       "1864  198516          3   50362   36451.0   64273.0      91        66.0   \n",
+       "1865  198515          3   63881   45538.0   82224.0     116        83.0   \n",
+       "1866  198514          3  134545  114400.0  154690.0     244       207.0   \n",
+       "1867  198513          3  197206  176080.0  218332.0     357       319.0   \n",
+       "1868  198512          3  245240  223304.0  267176.0     445       405.0   \n",
+       "1869  198511          3  276205  252399.0  300011.0     501       458.0   \n",
+       "1870  198510          3  353231  326279.0  380183.0     640       591.0   \n",
+       "1871  198509          3  369895  341109.0  398681.0     670       618.0   \n",
+       "1872  198508          3  389886  359529.0  420243.0     707       652.0   \n",
+       "1873  198507          3  471852  432599.0  511105.0     855       784.0   \n",
+       "1874  198506          3  565825  518011.0  613639.0    1026       939.0   \n",
+       "1875  198505          3  637302  592795.0  681809.0    1155      1074.0   \n",
+       "1876  198504          3  424937  390794.0  459080.0     770       708.0   \n",
+       "1877  198503          3  213901  174689.0  253113.0     388       317.0   \n",
+       "1878  198502          3   97586   80949.0  114223.0     177       147.0   \n",
+       "1879  198501          3   85489   65918.0  105060.0     155       120.0   \n",
+       "1880  198452          3   84830   60602.0  109058.0     154       110.0   \n",
+       "1881  198451          3  101726   80242.0  123210.0     185       146.0   \n",
+       "1882  198450          3  123680  101401.0  145959.0     225       184.0   \n",
+       "1883  198449          3  101073   81684.0  120462.0     184       149.0   \n",
+       "1884  198448          3   78620   60634.0   96606.0     143       110.0   \n",
+       "1885  198447          3   72029   54274.0   89784.0     131        99.0   \n",
+       "1886  198446          3   87330   67686.0  106974.0     159       123.0   \n",
+       "1887  198445          3  135223  101414.0  169032.0     246       184.0   \n",
+       "1888  198444          3   68422   20056.0  116788.0     125        37.0   \n",
+       "\n",
+       "      inc100_up geo_insee geo_name  \n",
+       "0          55.0        FR   France  \n",
+       "1          40.0        FR   France  \n",
+       "2          31.0        FR   France  \n",
+       "3          39.0        FR   France  \n",
+       "4          32.0        FR   France  \n",
+       "5          25.0        FR   France  \n",
+       "6          26.0        FR   France  \n",
+       "7          35.0        FR   France  \n",
+       "8          45.0        FR   France  \n",
+       "9          74.0        FR   France  \n",
+       "10         77.0        FR   France  \n",
+       "11         75.0        FR   France  \n",
+       "12         61.0        FR   France  \n",
+       "13         49.0        FR   France  \n",
+       "14         37.0        FR   France  \n",
+       "15         36.0        FR   France  \n",
+       "16         46.0        FR   France  \n",
+       "17         34.0        FR   France  \n",
+       "18         20.0        FR   France  \n",
+       "19         20.0        FR   France  \n",
+       "20         14.0        FR   France  \n",
+       "21         13.0        FR   France  \n",
+       "22         13.0        FR   France  \n",
+       "23         10.0        FR   France  \n",
+       "24         16.0        FR   France  \n",
+       "25         17.0        FR   France  \n",
+       "26         17.0        FR   France  \n",
+       "27          9.0        FR   France  \n",
+       "28          9.0        FR   France  \n",
+       "29          6.0        FR   France  \n",
+       "...         ...       ...      ...  \n",
+       "1859       59.0        FR   France  \n",
+       "1860       64.0        FR   France  \n",
+       "1861       97.0        FR   France  \n",
+       "1862       93.0        FR   France  \n",
+       "1863       80.0        FR   France  \n",
+       "1864      116.0        FR   France  \n",
+       "1865      149.0        FR   France  \n",
+       "1866      281.0        FR   France  \n",
+       "1867      395.0        FR   France  \n",
+       "1868      485.0        FR   France  \n",
+       "1869      544.0        FR   France  \n",
+       "1870      689.0        FR   France  \n",
+       "1871      722.0        FR   France  \n",
+       "1872      762.0        FR   France  \n",
+       "1873      926.0        FR   France  \n",
+       "1874     1113.0        FR   France  \n",
+       "1875     1236.0        FR   France  \n",
+       "1876      832.0        FR   France  \n",
+       "1877      459.0        FR   France  \n",
+       "1878      207.0        FR   France  \n",
+       "1879      190.0        FR   France  \n",
+       "1880      198.0        FR   France  \n",
+       "1881      224.0        FR   France  \n",
+       "1882      266.0        FR   France  \n",
+       "1883      219.0        FR   France  \n",
+       "1884      176.0        FR   France  \n",
+       "1885      163.0        FR   France  \n",
+       "1886      195.0        FR   France  \n",
+       "1887      308.0        FR   France  \n",
+       "1888      213.0        FR   France  \n",
+       "\n",
+       "[1888 rows x 10 columns]"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data = raw_data.dropna().copy()\n",
+    "data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Nos données utilisent une convention inhabituelle: le numéro de\n",
+    "semaine est collé à l'année, donnant l'impression qu'il s'agit\n",
+    "de nombre entier. C'est comme ça que Pandas les interprète.\n",
+    "  \n",
+    "Un deuxième problème est que Pandas ne comprend pas les numéros de\n",
+    "semaine.  Il faut lui fournir les dates de début et de fin de\n",
+    "semaine. Nous utilisons pour cela la bibliothèque `isoweek`.\n",
+    "\n",
+    "Comme la conversion des semaines est devenu assez complexe, nous\n",
+    "écrivons une petite fonction Python pour cela. Ensuite, nous\n",
+    "l'appliquons à tous les points de nos donnés. Les résultats vont\n",
+    "dans une nouvelle colonne 'period'."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "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:])\n",
+    "    w = isoweek.Week(year, week)\n",
+    "    return pd.Period(w.day(0), 'W')\n",
+    "\n",
+    "data['period'] = [convert_week(yw) for yw in data['week']]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Il restent deux petites modifications à faire.\n",
+    "\n",
+    "Premièrement, nous définissons les périodes d'observation\n",
+    "comme nouvel index de notre jeu de données. Ceci en fait\n",
+    "une suite chronologique, ce qui sera pratique par la suite.\n",
+    "\n",
+    "Deuxièmement, nous trions les points par période, dans\n",
+    "le sens chronologique."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sorted_data = data.set_index('period').sort_index()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Nous vérifions la cohérence des données. Entre la fin d'une période et\n",
+    "le début de la période qui suit, la différence temporelle doit être\n",
+    "zéro, ou au moins très faible. Nous laissons une \"marge d'erreur\"\n",
+    "d'une seconde.\n",
+    "\n",
+    "Ceci s'avère tout à fait juste sauf pour deux périodes consécutives\n",
+    "entre lesquelles il manque une semaine.\n",
+    "\n",
+    "Nous reconnaissons ces dates: c'est la semaine sans observations\n",
+    "que nous avions supprimées !"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1989-05-01/1989-05-07 1989-05-15/1989-05-21\n"
+     ]
+    }
+   ],
+   "source": [
+    "periods = sorted_data.index\n",
+    "for p1, p2 in zip(periods[:-1], periods[1:]):\n",
+    "    delta = p2.to_timestamp() - p1.end_time\n",
+    "    if delta > pd.Timedelta('1s'):\n",
+    "        print(p1, p2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Un premier regard sur les données !"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fe9a05bf7b8>"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sorted_data['inc'].plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Un zoom sur les dernières années montre mieux la situation des pics en hiver. Le creux des incidences se trouve en été."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fe99e339b00>"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sorted_data['inc'][-200:].plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Etude de l'incidence annuelle"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Etant donné que le pic de l'épidémie se situe en hiver, à cheval\n",
+    "entre deux années civiles, nous définissons la période de référence\n",
+    "entre deux minima de l'incidence, du 1er août de l'année $N$ au\n",
+    "1er août de l'année $N+1$.\n",
+    "\n",
+    "Notre tâche est un peu compliquée par le fait que l'année ne comporte\n",
+    "pas un nombre entier de semaines. Nous modifions donc un peu nos périodes\n",
+    "de référence: à la place du 1er août de chaque année, nous utilisons le\n",
+    "premier jour de la semaine qui contient le 1er août.\n",
+    "\n",
+    "Comme l'incidence de syndrome grippal est très faible en été, cette\n",
+    "modification ne risque pas de fausser nos conclusions.\n",
+    "\n",
+    "Encore un petit détail: les données commencent en octobre 1984, ce qui\n",
+    "rend la première année incomplète. Nous commençons donc l'analyse en 1985."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "first_august_week = [pd.Period(pd.Timestamp(y, 8, 1), 'W')\n",
+    "                     for y in range(1985,\n",
+    "                                    sorted_data.index[-1].year)]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "En partant de cette liste des semaines qui contiennent un 1er août, nous obtenons nos intervalles d'environ un an comme les périodes entre deux semaines adjacentes dans cette liste. Nous calculons les sommes des incidences hebdomadaires pour toutes ces périodes.\n",
+    "\n",
+    "Nous vérifions également que ces périodes contiennent entre 51 et 52 semaines, pour nous protéger contre des éventuelles erreurs dans notre code."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "year = []\n",
+    "yearly_incidence = []\n",
+    "for week1, week2 in zip(first_august_week[:-1],\n",
+    "                        first_august_week[1:]):\n",
+    "    one_year = sorted_data['inc'][week1:week2-1]\n",
+    "    assert abs(len(one_year)-52) < 2\n",
+    "    yearly_incidence.append(one_year.sum())\n",
+    "    year.append(week2.year)\n",
+    "yearly_incidence = pd.Series(data=yearly_incidence, index=year)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Voici les incidences annuelles."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fe99e2be978>"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "yearly_incidence.plot(style='*')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Une liste triée permet de plus facilement répérer les valeurs les plus élevées (à la fin)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2014    1600941\n",
+       "1991    1659249\n",
+       "1995    1840410\n",
+       "2020    2042389\n",
+       "2012    2175217\n",
+       "2003    2234584\n",
+       "2019    2254386\n",
+       "2006    2307352\n",
+       "2017    2321583\n",
+       "2001    2529279\n",
+       "1992    2574578\n",
+       "1993    2703886\n",
+       "2018    2705325\n",
+       "1988    2765617\n",
+       "2007    2780164\n",
+       "1987    2855570\n",
+       "2016    2856393\n",
+       "2011    2857040\n",
+       "2008    2973918\n",
+       "1998    3034904\n",
+       "2002    3125418\n",
+       "2009    3444020\n",
+       "1994    3514763\n",
+       "1996    3539413\n",
+       "2004    3567744\n",
+       "1997    3620066\n",
+       "2015    3654892\n",
+       "2000    3826372\n",
+       "2005    3835025\n",
+       "1999    3908112\n",
+       "2010    4111392\n",
+       "2013    4182691\n",
+       "1986    5115251\n",
+       "1990    5235827\n",
+       "1989    5466192\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "yearly_incidence.sort_values()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Enfin, un histogramme montre bien que les épidémies fortes, qui touchent environ 10% de la population\n",
+    "  française, sont assez rares: il y en eu trois au cours des 35 dernières années."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fe99e237400>"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "yearly_incidence.hist(xrot=20)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/module3/exo3/exercice_fr.ipynb b/module3/exo3/exercice_fr.ipynb
index 0bbbe37..89a215b 100644
--- a/module3/exo3/exercice_fr.ipynb
+++ b/module3/exo3/exercice_fr.ipynb
@@ -1,5 +1,2512 @@
 {
- "cells": [],
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Incidence du syndrome grippal"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import pandas as pd\n",
+    "import isoweek\n",
+    "import os\n",
+    "from os import path"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Les données de l'incidence du syndrome grippal sont disponibles du site Web du [Réseau Sentinelles](http://www.sentiweb.fr/). Nous les récupérons sous forme d'un fichier en format CSV dont chaque ligne correspond à une semaine de la période demandée. Nous téléchargeons toujours le jeu de données complet, qui commence en 1984 et se termine avec une semaine récente."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Voici l'explication des colonnes données [sur le site d'origine](https://ns.sentiweb.fr/incidence/csv-schema-v1.json):\n",
+    "\n",
+    "| Nom de colonne | Libellé de colonne                                                                                                                |\n",
+    "|----------------|-----------------------------------------------------------------------------------------------------------------------------------|\n",
+    "| week           | Semaine calendaire (ISO 8601)                                                                                                     |\n",
+    "| indicator      | Code de l'indicateur de surveillance                                                                                              |\n",
+    "| inc            | Estimation de l'incidence de consultations en nombre de cas                                                                       |\n",
+    "| inc_low        | Estimation de la borne inférieure de l'IC95% du nombre de cas de consultation                                                     |\n",
+    "| inc_up         | Estimation de la borne supérieure de l'IC95% du nombre de cas de consultation                                                     |\n",
+    "| inc100         | Estimation du taux d'incidence du nombre de cas de consultation (en cas pour 100,000 habitants)                                   |\n",
+    "| inc100_low     | Estimation de la borne inférieure de l'IC95% du taux d'incidence du nombre de cas de consultation (en cas pour 100,000 habitants) |\n",
+    "| inc100_up      | Estimation de la borne supérieure de l'IC95% du taux d'incidence du nombre de cas de consultation (en cas pour 100,000 habitants) |\n",
+    "| geo_insee      | Code de la zone géographique concernée (Code INSEE) http://www.insee.fr/fr/methodes/nomenclatures/cog/                            |\n",
+    "| geo_name       | Libellé de la zone géographique (ce libellé peut être modifié sans préavis)                                                       |\n",
+    "\n",
+    "La première ligne du fichier CSV est un commentaire, que nous ignorons en précisant `skiprows=1`."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Pour éviter de télécharger les données à chaque fois, on vérifie si le fichier existe ou non.\n",
+    "Si c'est le cas, on charge la version locale.\n",
+    "Si ce n'est pas le cas, on le télécharge en utilisant l'URL indiquée plus haut, puis on le sauvegarde pour une utilsation ultérieure.\n",
+    "Ceci permet:\n",
+    "- de gagner du temps lors de la prochaine utilisation du notebook\n",
+    "- de travailler hors ligne\n",
+    "- de travailler avec la même version des données\n",
+    "\n",
+    "Le désavantage est qu'on ne travaillera pas forcément avec le jeu le plus récent des données. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "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>week</th>\n",
+       "      <th>indicator</th>\n",
+       "      <th>inc</th>\n",
+       "      <th>inc_low</th>\n",
+       "      <th>inc_up</th>\n",
+       "      <th>inc100</th>\n",
+       "      <th>inc100_low</th>\n",
+       "      <th>inc100_up</th>\n",
+       "      <th>geo_insee</th>\n",
+       "      <th>geo_name</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>202103</td>\n",
+       "      <td>3</td>\n",
+       "      <td>28139</td>\n",
+       "      <td>22926.0</td>\n",
+       "      <td>33352.0</td>\n",
+       "      <td>43</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>202102</td>\n",
+       "      <td>3</td>\n",
+       "      <td>18010</td>\n",
+       "      <td>14474.0</td>\n",
+       "      <td>21546.0</td>\n",
+       "      <td>27</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>202101</td>\n",
+       "      <td>3</td>\n",
+       "      <td>21809</td>\n",
+       "      <td>17786.0</td>\n",
+       "      <td>25832.0</td>\n",
+       "      <td>33</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>202053</td>\n",
+       "      <td>3</td>\n",
+       "      <td>21220</td>\n",
+       "      <td>16498.0</td>\n",
+       "      <td>25942.0</td>\n",
+       "      <td>32</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>202052</td>\n",
+       "      <td>3</td>\n",
+       "      <td>16428</td>\n",
+       "      <td>12285.0</td>\n",
+       "      <td>20571.0</td>\n",
+       "      <td>25</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>31.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>202051</td>\n",
+       "      <td>3</td>\n",
+       "      <td>21619</td>\n",
+       "      <td>17370.0</td>\n",
+       "      <td>25868.0</td>\n",
+       "      <td>33</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>202050</td>\n",
+       "      <td>3</td>\n",
+       "      <td>16845</td>\n",
+       "      <td>13220.0</td>\n",
+       "      <td>20470.0</td>\n",
+       "      <td>26</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>202049</td>\n",
+       "      <td>3</td>\n",
+       "      <td>12939</td>\n",
+       "      <td>9923.0</td>\n",
+       "      <td>15955.0</td>\n",
+       "      <td>20</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>202048</td>\n",
+       "      <td>3</td>\n",
+       "      <td>13804</td>\n",
+       "      <td>10641.0</td>\n",
+       "      <td>16967.0</td>\n",
+       "      <td>21</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>202047</td>\n",
+       "      <td>3</td>\n",
+       "      <td>19085</td>\n",
+       "      <td>15285.0</td>\n",
+       "      <td>22885.0</td>\n",
+       "      <td>29</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>202046</td>\n",
+       "      <td>3</td>\n",
+       "      <td>24801</td>\n",
+       "      <td>20503.0</td>\n",
+       "      <td>29099.0</td>\n",
+       "      <td>38</td>\n",
+       "      <td>31.0</td>\n",
+       "      <td>45.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>202045</td>\n",
+       "      <td>3</td>\n",
+       "      <td>42516</td>\n",
+       "      <td>36857.0</td>\n",
+       "      <td>48175.0</td>\n",
+       "      <td>65</td>\n",
+       "      <td>56.0</td>\n",
+       "      <td>74.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>202044</td>\n",
+       "      <td>3</td>\n",
+       "      <td>44567</td>\n",
+       "      <td>38521.0</td>\n",
+       "      <td>50613.0</td>\n",
+       "      <td>68</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>77.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>202043</td>\n",
+       "      <td>3</td>\n",
+       "      <td>43737</td>\n",
+       "      <td>37523.0</td>\n",
+       "      <td>49951.0</td>\n",
+       "      <td>66</td>\n",
+       "      <td>57.0</td>\n",
+       "      <td>75.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>202042</td>\n",
+       "      <td>3</td>\n",
+       "      <td>35145</td>\n",
+       "      <td>29812.0</td>\n",
+       "      <td>40478.0</td>\n",
+       "      <td>53</td>\n",
+       "      <td>45.0</td>\n",
+       "      <td>61.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>202041</td>\n",
+       "      <td>3</td>\n",
+       "      <td>27877</td>\n",
+       "      <td>23206.0</td>\n",
+       "      <td>32548.0</td>\n",
+       "      <td>42</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>49.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>202040</td>\n",
+       "      <td>3</td>\n",
+       "      <td>20443</td>\n",
+       "      <td>16381.0</td>\n",
+       "      <td>24505.0</td>\n",
+       "      <td>31</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>37.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>202039</td>\n",
+       "      <td>3</td>\n",
+       "      <td>19810</td>\n",
+       "      <td>15900.0</td>\n",
+       "      <td>23720.0</td>\n",
+       "      <td>30</td>\n",
+       "      <td>24.0</td>\n",
+       "      <td>36.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>202038</td>\n",
+       "      <td>3</td>\n",
+       "      <td>25562</td>\n",
+       "      <td>21142.0</td>\n",
+       "      <td>29982.0</td>\n",
+       "      <td>39</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>46.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>202037</td>\n",
+       "      <td>3</td>\n",
+       "      <td>18485</td>\n",
+       "      <td>14649.0</td>\n",
+       "      <td>22321.0</td>\n",
+       "      <td>28</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>34.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>202036</td>\n",
+       "      <td>3</td>\n",
+       "      <td>10390</td>\n",
+       "      <td>7646.0</td>\n",
+       "      <td>13134.0</td>\n",
+       "      <td>16</td>\n",
+       "      <td>12.0</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>202035</td>\n",
+       "      <td>3</td>\n",
+       "      <td>9918</td>\n",
+       "      <td>6842.0</td>\n",
+       "      <td>12994.0</td>\n",
+       "      <td>15</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>202034</td>\n",
+       "      <td>3</td>\n",
+       "      <td>6084</td>\n",
+       "      <td>3090.0</td>\n",
+       "      <td>9078.0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>202033</td>\n",
+       "      <td>3</td>\n",
+       "      <td>6106</td>\n",
+       "      <td>3411.0</td>\n",
+       "      <td>8801.0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>202032</td>\n",
+       "      <td>3</td>\n",
+       "      <td>5918</td>\n",
+       "      <td>3330.0</td>\n",
+       "      <td>8506.0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>202031</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4351</td>\n",
+       "      <td>2269.0</td>\n",
+       "      <td>6433.0</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>202030</td>\n",
+       "      <td>3</td>\n",
+       "      <td>8179</td>\n",
+       "      <td>5442.0</td>\n",
+       "      <td>10916.0</td>\n",
+       "      <td>12</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>202029</td>\n",
+       "      <td>3</td>\n",
+       "      <td>8687</td>\n",
+       "      <td>5860.0</td>\n",
+       "      <td>11514.0</td>\n",
+       "      <td>13</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>202028</td>\n",
+       "      <td>3</td>\n",
+       "      <td>8340</td>\n",
+       "      <td>5701.0</td>\n",
+       "      <td>10979.0</td>\n",
+       "      <td>13</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>202027</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4066</td>\n",
+       "      <td>2406.0</td>\n",
+       "      <td>5726.0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1861</th>\n",
+       "      <td>198521</td>\n",
+       "      <td>3</td>\n",
+       "      <td>26096</td>\n",
+       "      <td>19621.0</td>\n",
+       "      <td>32571.0</td>\n",
+       "      <td>47</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1862</th>\n",
+       "      <td>198520</td>\n",
+       "      <td>3</td>\n",
+       "      <td>27896</td>\n",
+       "      <td>20885.0</td>\n",
+       "      <td>34907.0</td>\n",
+       "      <td>51</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>64.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1863</th>\n",
+       "      <td>198519</td>\n",
+       "      <td>3</td>\n",
+       "      <td>43154</td>\n",
+       "      <td>32821.0</td>\n",
+       "      <td>53487.0</td>\n",
+       "      <td>78</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>97.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1864</th>\n",
+       "      <td>198518</td>\n",
+       "      <td>3</td>\n",
+       "      <td>40555</td>\n",
+       "      <td>29935.0</td>\n",
+       "      <td>51175.0</td>\n",
+       "      <td>74</td>\n",
+       "      <td>55.0</td>\n",
+       "      <td>93.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1865</th>\n",
+       "      <td>198517</td>\n",
+       "      <td>3</td>\n",
+       "      <td>34053</td>\n",
+       "      <td>24366.0</td>\n",
+       "      <td>43740.0</td>\n",
+       "      <td>62</td>\n",
+       "      <td>44.0</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1866</th>\n",
+       "      <td>198516</td>\n",
+       "      <td>3</td>\n",
+       "      <td>50362</td>\n",
+       "      <td>36451.0</td>\n",
+       "      <td>64273.0</td>\n",
+       "      <td>91</td>\n",
+       "      <td>66.0</td>\n",
+       "      <td>116.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1867</th>\n",
+       "      <td>198515</td>\n",
+       "      <td>3</td>\n",
+       "      <td>63881</td>\n",
+       "      <td>45538.0</td>\n",
+       "      <td>82224.0</td>\n",
+       "      <td>116</td>\n",
+       "      <td>83.0</td>\n",
+       "      <td>149.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1868</th>\n",
+       "      <td>198514</td>\n",
+       "      <td>3</td>\n",
+       "      <td>134545</td>\n",
+       "      <td>114400.0</td>\n",
+       "      <td>154690.0</td>\n",
+       "      <td>244</td>\n",
+       "      <td>207.0</td>\n",
+       "      <td>281.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1869</th>\n",
+       "      <td>198513</td>\n",
+       "      <td>3</td>\n",
+       "      <td>197206</td>\n",
+       "      <td>176080.0</td>\n",
+       "      <td>218332.0</td>\n",
+       "      <td>357</td>\n",
+       "      <td>319.0</td>\n",
+       "      <td>395.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1870</th>\n",
+       "      <td>198512</td>\n",
+       "      <td>3</td>\n",
+       "      <td>245240</td>\n",
+       "      <td>223304.0</td>\n",
+       "      <td>267176.0</td>\n",
+       "      <td>445</td>\n",
+       "      <td>405.0</td>\n",
+       "      <td>485.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1871</th>\n",
+       "      <td>198511</td>\n",
+       "      <td>3</td>\n",
+       "      <td>276205</td>\n",
+       "      <td>252399.0</td>\n",
+       "      <td>300011.0</td>\n",
+       "      <td>501</td>\n",
+       "      <td>458.0</td>\n",
+       "      <td>544.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1872</th>\n",
+       "      <td>198510</td>\n",
+       "      <td>3</td>\n",
+       "      <td>353231</td>\n",
+       "      <td>326279.0</td>\n",
+       "      <td>380183.0</td>\n",
+       "      <td>640</td>\n",
+       "      <td>591.0</td>\n",
+       "      <td>689.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1873</th>\n",
+       "      <td>198509</td>\n",
+       "      <td>3</td>\n",
+       "      <td>369895</td>\n",
+       "      <td>341109.0</td>\n",
+       "      <td>398681.0</td>\n",
+       "      <td>670</td>\n",
+       "      <td>618.0</td>\n",
+       "      <td>722.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1874</th>\n",
+       "      <td>198508</td>\n",
+       "      <td>3</td>\n",
+       "      <td>389886</td>\n",
+       "      <td>359529.0</td>\n",
+       "      <td>420243.0</td>\n",
+       "      <td>707</td>\n",
+       "      <td>652.0</td>\n",
+       "      <td>762.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1875</th>\n",
+       "      <td>198507</td>\n",
+       "      <td>3</td>\n",
+       "      <td>471852</td>\n",
+       "      <td>432599.0</td>\n",
+       "      <td>511105.0</td>\n",
+       "      <td>855</td>\n",
+       "      <td>784.0</td>\n",
+       "      <td>926.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1876</th>\n",
+       "      <td>198506</td>\n",
+       "      <td>3</td>\n",
+       "      <td>565825</td>\n",
+       "      <td>518011.0</td>\n",
+       "      <td>613639.0</td>\n",
+       "      <td>1026</td>\n",
+       "      <td>939.0</td>\n",
+       "      <td>1113.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1877</th>\n",
+       "      <td>198505</td>\n",
+       "      <td>3</td>\n",
+       "      <td>637302</td>\n",
+       "      <td>592795.0</td>\n",
+       "      <td>681809.0</td>\n",
+       "      <td>1155</td>\n",
+       "      <td>1074.0</td>\n",
+       "      <td>1236.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1878</th>\n",
+       "      <td>198504</td>\n",
+       "      <td>3</td>\n",
+       "      <td>424937</td>\n",
+       "      <td>390794.0</td>\n",
+       "      <td>459080.0</td>\n",
+       "      <td>770</td>\n",
+       "      <td>708.0</td>\n",
+       "      <td>832.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1879</th>\n",
+       "      <td>198503</td>\n",
+       "      <td>3</td>\n",
+       "      <td>213901</td>\n",
+       "      <td>174689.0</td>\n",
+       "      <td>253113.0</td>\n",
+       "      <td>388</td>\n",
+       "      <td>317.0</td>\n",
+       "      <td>459.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1880</th>\n",
+       "      <td>198502</td>\n",
+       "      <td>3</td>\n",
+       "      <td>97586</td>\n",
+       "      <td>80949.0</td>\n",
+       "      <td>114223.0</td>\n",
+       "      <td>177</td>\n",
+       "      <td>147.0</td>\n",
+       "      <td>207.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1881</th>\n",
+       "      <td>198501</td>\n",
+       "      <td>3</td>\n",
+       "      <td>85489</td>\n",
+       "      <td>65918.0</td>\n",
+       "      <td>105060.0</td>\n",
+       "      <td>155</td>\n",
+       "      <td>120.0</td>\n",
+       "      <td>190.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1882</th>\n",
+       "      <td>198452</td>\n",
+       "      <td>3</td>\n",
+       "      <td>84830</td>\n",
+       "      <td>60602.0</td>\n",
+       "      <td>109058.0</td>\n",
+       "      <td>154</td>\n",
+       "      <td>110.0</td>\n",
+       "      <td>198.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1883</th>\n",
+       "      <td>198451</td>\n",
+       "      <td>3</td>\n",
+       "      <td>101726</td>\n",
+       "      <td>80242.0</td>\n",
+       "      <td>123210.0</td>\n",
+       "      <td>185</td>\n",
+       "      <td>146.0</td>\n",
+       "      <td>224.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1884</th>\n",
+       "      <td>198450</td>\n",
+       "      <td>3</td>\n",
+       "      <td>123680</td>\n",
+       "      <td>101401.0</td>\n",
+       "      <td>145959.0</td>\n",
+       "      <td>225</td>\n",
+       "      <td>184.0</td>\n",
+       "      <td>266.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1885</th>\n",
+       "      <td>198449</td>\n",
+       "      <td>3</td>\n",
+       "      <td>101073</td>\n",
+       "      <td>81684.0</td>\n",
+       "      <td>120462.0</td>\n",
+       "      <td>184</td>\n",
+       "      <td>149.0</td>\n",
+       "      <td>219.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1886</th>\n",
+       "      <td>198448</td>\n",
+       "      <td>3</td>\n",
+       "      <td>78620</td>\n",
+       "      <td>60634.0</td>\n",
+       "      <td>96606.0</td>\n",
+       "      <td>143</td>\n",
+       "      <td>110.0</td>\n",
+       "      <td>176.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1887</th>\n",
+       "      <td>198447</td>\n",
+       "      <td>3</td>\n",
+       "      <td>72029</td>\n",
+       "      <td>54274.0</td>\n",
+       "      <td>89784.0</td>\n",
+       "      <td>131</td>\n",
+       "      <td>99.0</td>\n",
+       "      <td>163.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1888</th>\n",
+       "      <td>198446</td>\n",
+       "      <td>3</td>\n",
+       "      <td>87330</td>\n",
+       "      <td>67686.0</td>\n",
+       "      <td>106974.0</td>\n",
+       "      <td>159</td>\n",
+       "      <td>123.0</td>\n",
+       "      <td>195.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1889</th>\n",
+       "      <td>198445</td>\n",
+       "      <td>3</td>\n",
+       "      <td>135223</td>\n",
+       "      <td>101414.0</td>\n",
+       "      <td>169032.0</td>\n",
+       "      <td>246</td>\n",
+       "      <td>184.0</td>\n",
+       "      <td>308.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1890</th>\n",
+       "      <td>198444</td>\n",
+       "      <td>3</td>\n",
+       "      <td>68422</td>\n",
+       "      <td>20056.0</td>\n",
+       "      <td>116788.0</td>\n",
+       "      <td>125</td>\n",
+       "      <td>37.0</td>\n",
+       "      <td>213.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1891 rows × 10 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        week  indicator     inc   inc_low    inc_up  inc100  inc100_low  \\\n",
+       "0     202103          3   28139   22926.0   33352.0      43        35.0   \n",
+       "1     202102          3   18010   14474.0   21546.0      27        22.0   \n",
+       "2     202101          3   21809   17786.0   25832.0      33        27.0   \n",
+       "3     202053          3   21220   16498.0   25942.0      32        25.0   \n",
+       "4     202052          3   16428   12285.0   20571.0      25        19.0   \n",
+       "5     202051          3   21619   17370.0   25868.0      33        27.0   \n",
+       "6     202050          3   16845   13220.0   20470.0      26        20.0   \n",
+       "7     202049          3   12939    9923.0   15955.0      20        15.0   \n",
+       "8     202048          3   13804   10641.0   16967.0      21        16.0   \n",
+       "9     202047          3   19085   15285.0   22885.0      29        23.0   \n",
+       "10    202046          3   24801   20503.0   29099.0      38        31.0   \n",
+       "11    202045          3   42516   36857.0   48175.0      65        56.0   \n",
+       "12    202044          3   44567   38521.0   50613.0      68        59.0   \n",
+       "13    202043          3   43737   37523.0   49951.0      66        57.0   \n",
+       "14    202042          3   35145   29812.0   40478.0      53        45.0   \n",
+       "15    202041          3   27877   23206.0   32548.0      42        35.0   \n",
+       "16    202040          3   20443   16381.0   24505.0      31        25.0   \n",
+       "17    202039          3   19810   15900.0   23720.0      30        24.0   \n",
+       "18    202038          3   25562   21142.0   29982.0      39        32.0   \n",
+       "19    202037          3   18485   14649.0   22321.0      28        22.0   \n",
+       "20    202036          3   10390    7646.0   13134.0      16        12.0   \n",
+       "21    202035          3    9918    6842.0   12994.0      15        10.0   \n",
+       "22    202034          3    6084    3090.0    9078.0       9         4.0   \n",
+       "23    202033          3    6106    3411.0    8801.0       9         5.0   \n",
+       "24    202032          3    5918    3330.0    8506.0       9         5.0   \n",
+       "25    202031          3    4351    2269.0    6433.0       7         4.0   \n",
+       "26    202030          3    8179    5442.0   10916.0      12         8.0   \n",
+       "27    202029          3    8687    5860.0   11514.0      13         9.0   \n",
+       "28    202028          3    8340    5701.0   10979.0      13         9.0   \n",
+       "29    202027          3    4066    2406.0    5726.0       6         3.0   \n",
+       "...      ...        ...     ...       ...       ...     ...         ...   \n",
+       "1861  198521          3   26096   19621.0   32571.0      47        35.0   \n",
+       "1862  198520          3   27896   20885.0   34907.0      51        38.0   \n",
+       "1863  198519          3   43154   32821.0   53487.0      78        59.0   \n",
+       "1864  198518          3   40555   29935.0   51175.0      74        55.0   \n",
+       "1865  198517          3   34053   24366.0   43740.0      62        44.0   \n",
+       "1866  198516          3   50362   36451.0   64273.0      91        66.0   \n",
+       "1867  198515          3   63881   45538.0   82224.0     116        83.0   \n",
+       "1868  198514          3  134545  114400.0  154690.0     244       207.0   \n",
+       "1869  198513          3  197206  176080.0  218332.0     357       319.0   \n",
+       "1870  198512          3  245240  223304.0  267176.0     445       405.0   \n",
+       "1871  198511          3  276205  252399.0  300011.0     501       458.0   \n",
+       "1872  198510          3  353231  326279.0  380183.0     640       591.0   \n",
+       "1873  198509          3  369895  341109.0  398681.0     670       618.0   \n",
+       "1874  198508          3  389886  359529.0  420243.0     707       652.0   \n",
+       "1875  198507          3  471852  432599.0  511105.0     855       784.0   \n",
+       "1876  198506          3  565825  518011.0  613639.0    1026       939.0   \n",
+       "1877  198505          3  637302  592795.0  681809.0    1155      1074.0   \n",
+       "1878  198504          3  424937  390794.0  459080.0     770       708.0   \n",
+       "1879  198503          3  213901  174689.0  253113.0     388       317.0   \n",
+       "1880  198502          3   97586   80949.0  114223.0     177       147.0   \n",
+       "1881  198501          3   85489   65918.0  105060.0     155       120.0   \n",
+       "1882  198452          3   84830   60602.0  109058.0     154       110.0   \n",
+       "1883  198451          3  101726   80242.0  123210.0     185       146.0   \n",
+       "1884  198450          3  123680  101401.0  145959.0     225       184.0   \n",
+       "1885  198449          3  101073   81684.0  120462.0     184       149.0   \n",
+       "1886  198448          3   78620   60634.0   96606.0     143       110.0   \n",
+       "1887  198447          3   72029   54274.0   89784.0     131        99.0   \n",
+       "1888  198446          3   87330   67686.0  106974.0     159       123.0   \n",
+       "1889  198445          3  135223  101414.0  169032.0     246       184.0   \n",
+       "1890  198444          3   68422   20056.0  116788.0     125        37.0   \n",
+       "\n",
+       "      inc100_up geo_insee geo_name  \n",
+       "0          51.0        FR   France  \n",
+       "1          32.0        FR   France  \n",
+       "2          39.0        FR   France  \n",
+       "3          39.0        FR   France  \n",
+       "4          31.0        FR   France  \n",
+       "5          39.0        FR   France  \n",
+       "6          32.0        FR   France  \n",
+       "7          25.0        FR   France  \n",
+       "8          26.0        FR   France  \n",
+       "9          35.0        FR   France  \n",
+       "10         45.0        FR   France  \n",
+       "11         74.0        FR   France  \n",
+       "12         77.0        FR   France  \n",
+       "13         75.0        FR   France  \n",
+       "14         61.0        FR   France  \n",
+       "15         49.0        FR   France  \n",
+       "16         37.0        FR   France  \n",
+       "17         36.0        FR   France  \n",
+       "18         46.0        FR   France  \n",
+       "19         34.0        FR   France  \n",
+       "20         20.0        FR   France  \n",
+       "21         20.0        FR   France  \n",
+       "22         14.0        FR   France  \n",
+       "23         13.0        FR   France  \n",
+       "24         13.0        FR   France  \n",
+       "25         10.0        FR   France  \n",
+       "26         16.0        FR   France  \n",
+       "27         17.0        FR   France  \n",
+       "28         17.0        FR   France  \n",
+       "29          9.0        FR   France  \n",
+       "...         ...       ...      ...  \n",
+       "1861       59.0        FR   France  \n",
+       "1862       64.0        FR   France  \n",
+       "1863       97.0        FR   France  \n",
+       "1864       93.0        FR   France  \n",
+       "1865       80.0        FR   France  \n",
+       "1866      116.0        FR   France  \n",
+       "1867      149.0        FR   France  \n",
+       "1868      281.0        FR   France  \n",
+       "1869      395.0        FR   France  \n",
+       "1870      485.0        FR   France  \n",
+       "1871      544.0        FR   France  \n",
+       "1872      689.0        FR   France  \n",
+       "1873      722.0        FR   France  \n",
+       "1874      762.0        FR   France  \n",
+       "1875      926.0        FR   France  \n",
+       "1876     1113.0        FR   France  \n",
+       "1877     1236.0        FR   France  \n",
+       "1878      832.0        FR   France  \n",
+       "1879      459.0        FR   France  \n",
+       "1880      207.0        FR   France  \n",
+       "1881      190.0        FR   France  \n",
+       "1882      198.0        FR   France  \n",
+       "1883      224.0        FR   France  \n",
+       "1884      266.0        FR   France  \n",
+       "1885      219.0        FR   France  \n",
+       "1886      176.0        FR   France  \n",
+       "1887      163.0        FR   France  \n",
+       "1888      195.0        FR   France  \n",
+       "1889      308.0        FR   France  \n",
+       "1890      213.0        FR   France  \n",
+       "\n",
+       "[1891 rows x 10 columns]"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "if (path.exists(\"incidence.csv\")):\n",
+    "    raw_data = pd.read_csv(\"incidence.csv\", index_col = 0)\n",
+    "else:\n",
+    "    raw_data = pd.read_csv(data_url, skiprows=1)\n",
+    "    raw_data.to_csv(\"incidence.csv\")\n",
+    "raw_data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Y a-t-il des points manquants dans ce jeux de données ? Oui, la semaine 19 de l'année 1989 n'a pas de valeurs associées."
+   ]
+  },
+  {
+   "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>week</th>\n",
+       "      <th>indicator</th>\n",
+       "      <th>inc</th>\n",
+       "      <th>inc_low</th>\n",
+       "      <th>inc_up</th>\n",
+       "      <th>inc100</th>\n",
+       "      <th>inc100_low</th>\n",
+       "      <th>inc100_up</th>\n",
+       "      <th>geo_insee</th>\n",
+       "      <th>geo_name</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1652</th>\n",
+       "      <td>198919</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        week  indicator  inc  inc_low  inc_up  inc100  inc100_low  inc100_up  \\\n",
+       "1652  198919          3    0      NaN     NaN       0         NaN        NaN   \n",
+       "\n",
+       "     geo_insee geo_name  \n",
+       "1652        FR   France  "
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data[raw_data.isnull().any(axis=1)]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Nous éliminons ce point, ce qui n'a pas d'impact fort sur notre analyse qui est assez simple."
+   ]
+  },
+  {
+   "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>week</th>\n",
+       "      <th>indicator</th>\n",
+       "      <th>inc</th>\n",
+       "      <th>inc_low</th>\n",
+       "      <th>inc_up</th>\n",
+       "      <th>inc100</th>\n",
+       "      <th>inc100_low</th>\n",
+       "      <th>inc100_up</th>\n",
+       "      <th>geo_insee</th>\n",
+       "      <th>geo_name</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>202101</td>\n",
+       "      <td>3</td>\n",
+       "      <td>30168</td>\n",
+       "      <td>24407.0</td>\n",
+       "      <td>35929.0</td>\n",
+       "      <td>46</td>\n",
+       "      <td>37.0</td>\n",
+       "      <td>55.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>202053</td>\n",
+       "      <td>3</td>\n",
+       "      <td>21449</td>\n",
+       "      <td>16669.0</td>\n",
+       "      <td>26229.0</td>\n",
+       "      <td>33</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>202052</td>\n",
+       "      <td>3</td>\n",
+       "      <td>16428</td>\n",
+       "      <td>12285.0</td>\n",
+       "      <td>20571.0</td>\n",
+       "      <td>25</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>31.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>202051</td>\n",
+       "      <td>3</td>\n",
+       "      <td>21619</td>\n",
+       "      <td>17370.0</td>\n",
+       "      <td>25868.0</td>\n",
+       "      <td>33</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>202050</td>\n",
+       "      <td>3</td>\n",
+       "      <td>16845</td>\n",
+       "      <td>13220.0</td>\n",
+       "      <td>20470.0</td>\n",
+       "      <td>26</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>202049</td>\n",
+       "      <td>3</td>\n",
+       "      <td>12939</td>\n",
+       "      <td>9923.0</td>\n",
+       "      <td>15955.0</td>\n",
+       "      <td>20</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>202048</td>\n",
+       "      <td>3</td>\n",
+       "      <td>13804</td>\n",
+       "      <td>10641.0</td>\n",
+       "      <td>16967.0</td>\n",
+       "      <td>21</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>202047</td>\n",
+       "      <td>3</td>\n",
+       "      <td>19085</td>\n",
+       "      <td>15285.0</td>\n",
+       "      <td>22885.0</td>\n",
+       "      <td>29</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>202046</td>\n",
+       "      <td>3</td>\n",
+       "      <td>24801</td>\n",
+       "      <td>20503.0</td>\n",
+       "      <td>29099.0</td>\n",
+       "      <td>38</td>\n",
+       "      <td>31.0</td>\n",
+       "      <td>45.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>202045</td>\n",
+       "      <td>3</td>\n",
+       "      <td>42516</td>\n",
+       "      <td>36857.0</td>\n",
+       "      <td>48175.0</td>\n",
+       "      <td>65</td>\n",
+       "      <td>56.0</td>\n",
+       "      <td>74.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>202044</td>\n",
+       "      <td>3</td>\n",
+       "      <td>44567</td>\n",
+       "      <td>38521.0</td>\n",
+       "      <td>50613.0</td>\n",
+       "      <td>68</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>77.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>202043</td>\n",
+       "      <td>3</td>\n",
+       "      <td>43737</td>\n",
+       "      <td>37523.0</td>\n",
+       "      <td>49951.0</td>\n",
+       "      <td>66</td>\n",
+       "      <td>57.0</td>\n",
+       "      <td>75.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>202042</td>\n",
+       "      <td>3</td>\n",
+       "      <td>35145</td>\n",
+       "      <td>29812.0</td>\n",
+       "      <td>40478.0</td>\n",
+       "      <td>53</td>\n",
+       "      <td>45.0</td>\n",
+       "      <td>61.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>202041</td>\n",
+       "      <td>3</td>\n",
+       "      <td>27877</td>\n",
+       "      <td>23206.0</td>\n",
+       "      <td>32548.0</td>\n",
+       "      <td>42</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>49.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>202040</td>\n",
+       "      <td>3</td>\n",
+       "      <td>20443</td>\n",
+       "      <td>16381.0</td>\n",
+       "      <td>24505.0</td>\n",
+       "      <td>31</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>37.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>202039</td>\n",
+       "      <td>3</td>\n",
+       "      <td>19810</td>\n",
+       "      <td>15900.0</td>\n",
+       "      <td>23720.0</td>\n",
+       "      <td>30</td>\n",
+       "      <td>24.0</td>\n",
+       "      <td>36.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>202038</td>\n",
+       "      <td>3</td>\n",
+       "      <td>25562</td>\n",
+       "      <td>21142.0</td>\n",
+       "      <td>29982.0</td>\n",
+       "      <td>39</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>46.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>202037</td>\n",
+       "      <td>3</td>\n",
+       "      <td>18485</td>\n",
+       "      <td>14649.0</td>\n",
+       "      <td>22321.0</td>\n",
+       "      <td>28</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>34.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>202036</td>\n",
+       "      <td>3</td>\n",
+       "      <td>10390</td>\n",
+       "      <td>7646.0</td>\n",
+       "      <td>13134.0</td>\n",
+       "      <td>16</td>\n",
+       "      <td>12.0</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>202035</td>\n",
+       "      <td>3</td>\n",
+       "      <td>9918</td>\n",
+       "      <td>6842.0</td>\n",
+       "      <td>12994.0</td>\n",
+       "      <td>15</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>202034</td>\n",
+       "      <td>3</td>\n",
+       "      <td>6084</td>\n",
+       "      <td>3090.0</td>\n",
+       "      <td>9078.0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>202033</td>\n",
+       "      <td>3</td>\n",
+       "      <td>6106</td>\n",
+       "      <td>3411.0</td>\n",
+       "      <td>8801.0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>202032</td>\n",
+       "      <td>3</td>\n",
+       "      <td>5918</td>\n",
+       "      <td>3330.0</td>\n",
+       "      <td>8506.0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>202031</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4351</td>\n",
+       "      <td>2269.0</td>\n",
+       "      <td>6433.0</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>202030</td>\n",
+       "      <td>3</td>\n",
+       "      <td>8179</td>\n",
+       "      <td>5442.0</td>\n",
+       "      <td>10916.0</td>\n",
+       "      <td>12</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>202029</td>\n",
+       "      <td>3</td>\n",
+       "      <td>8687</td>\n",
+       "      <td>5860.0</td>\n",
+       "      <td>11514.0</td>\n",
+       "      <td>13</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>202028</td>\n",
+       "      <td>3</td>\n",
+       "      <td>8340</td>\n",
+       "      <td>5701.0</td>\n",
+       "      <td>10979.0</td>\n",
+       "      <td>13</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>202027</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4066</td>\n",
+       "      <td>2406.0</td>\n",
+       "      <td>5726.0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>202026</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4039</td>\n",
+       "      <td>2389.0</td>\n",
+       "      <td>5689.0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>202025</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2853</td>\n",
+       "      <td>1488.0</td>\n",
+       "      <td>4218.0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1859</th>\n",
+       "      <td>198521</td>\n",
+       "      <td>3</td>\n",
+       "      <td>26096</td>\n",
+       "      <td>19621.0</td>\n",
+       "      <td>32571.0</td>\n",
+       "      <td>47</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1860</th>\n",
+       "      <td>198520</td>\n",
+       "      <td>3</td>\n",
+       "      <td>27896</td>\n",
+       "      <td>20885.0</td>\n",
+       "      <td>34907.0</td>\n",
+       "      <td>51</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>64.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1861</th>\n",
+       "      <td>198519</td>\n",
+       "      <td>3</td>\n",
+       "      <td>43154</td>\n",
+       "      <td>32821.0</td>\n",
+       "      <td>53487.0</td>\n",
+       "      <td>78</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>97.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1862</th>\n",
+       "      <td>198518</td>\n",
+       "      <td>3</td>\n",
+       "      <td>40555</td>\n",
+       "      <td>29935.0</td>\n",
+       "      <td>51175.0</td>\n",
+       "      <td>74</td>\n",
+       "      <td>55.0</td>\n",
+       "      <td>93.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1863</th>\n",
+       "      <td>198517</td>\n",
+       "      <td>3</td>\n",
+       "      <td>34053</td>\n",
+       "      <td>24366.0</td>\n",
+       "      <td>43740.0</td>\n",
+       "      <td>62</td>\n",
+       "      <td>44.0</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1864</th>\n",
+       "      <td>198516</td>\n",
+       "      <td>3</td>\n",
+       "      <td>50362</td>\n",
+       "      <td>36451.0</td>\n",
+       "      <td>64273.0</td>\n",
+       "      <td>91</td>\n",
+       "      <td>66.0</td>\n",
+       "      <td>116.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1865</th>\n",
+       "      <td>198515</td>\n",
+       "      <td>3</td>\n",
+       "      <td>63881</td>\n",
+       "      <td>45538.0</td>\n",
+       "      <td>82224.0</td>\n",
+       "      <td>116</td>\n",
+       "      <td>83.0</td>\n",
+       "      <td>149.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1866</th>\n",
+       "      <td>198514</td>\n",
+       "      <td>3</td>\n",
+       "      <td>134545</td>\n",
+       "      <td>114400.0</td>\n",
+       "      <td>154690.0</td>\n",
+       "      <td>244</td>\n",
+       "      <td>207.0</td>\n",
+       "      <td>281.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1867</th>\n",
+       "      <td>198513</td>\n",
+       "      <td>3</td>\n",
+       "      <td>197206</td>\n",
+       "      <td>176080.0</td>\n",
+       "      <td>218332.0</td>\n",
+       "      <td>357</td>\n",
+       "      <td>319.0</td>\n",
+       "      <td>395.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1868</th>\n",
+       "      <td>198512</td>\n",
+       "      <td>3</td>\n",
+       "      <td>245240</td>\n",
+       "      <td>223304.0</td>\n",
+       "      <td>267176.0</td>\n",
+       "      <td>445</td>\n",
+       "      <td>405.0</td>\n",
+       "      <td>485.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1869</th>\n",
+       "      <td>198511</td>\n",
+       "      <td>3</td>\n",
+       "      <td>276205</td>\n",
+       "      <td>252399.0</td>\n",
+       "      <td>300011.0</td>\n",
+       "      <td>501</td>\n",
+       "      <td>458.0</td>\n",
+       "      <td>544.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1870</th>\n",
+       "      <td>198510</td>\n",
+       "      <td>3</td>\n",
+       "      <td>353231</td>\n",
+       "      <td>326279.0</td>\n",
+       "      <td>380183.0</td>\n",
+       "      <td>640</td>\n",
+       "      <td>591.0</td>\n",
+       "      <td>689.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1871</th>\n",
+       "      <td>198509</td>\n",
+       "      <td>3</td>\n",
+       "      <td>369895</td>\n",
+       "      <td>341109.0</td>\n",
+       "      <td>398681.0</td>\n",
+       "      <td>670</td>\n",
+       "      <td>618.0</td>\n",
+       "      <td>722.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1872</th>\n",
+       "      <td>198508</td>\n",
+       "      <td>3</td>\n",
+       "      <td>389886</td>\n",
+       "      <td>359529.0</td>\n",
+       "      <td>420243.0</td>\n",
+       "      <td>707</td>\n",
+       "      <td>652.0</td>\n",
+       "      <td>762.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1873</th>\n",
+       "      <td>198507</td>\n",
+       "      <td>3</td>\n",
+       "      <td>471852</td>\n",
+       "      <td>432599.0</td>\n",
+       "      <td>511105.0</td>\n",
+       "      <td>855</td>\n",
+       "      <td>784.0</td>\n",
+       "      <td>926.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1874</th>\n",
+       "      <td>198506</td>\n",
+       "      <td>3</td>\n",
+       "      <td>565825</td>\n",
+       "      <td>518011.0</td>\n",
+       "      <td>613639.0</td>\n",
+       "      <td>1026</td>\n",
+       "      <td>939.0</td>\n",
+       "      <td>1113.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1875</th>\n",
+       "      <td>198505</td>\n",
+       "      <td>3</td>\n",
+       "      <td>637302</td>\n",
+       "      <td>592795.0</td>\n",
+       "      <td>681809.0</td>\n",
+       "      <td>1155</td>\n",
+       "      <td>1074.0</td>\n",
+       "      <td>1236.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1876</th>\n",
+       "      <td>198504</td>\n",
+       "      <td>3</td>\n",
+       "      <td>424937</td>\n",
+       "      <td>390794.0</td>\n",
+       "      <td>459080.0</td>\n",
+       "      <td>770</td>\n",
+       "      <td>708.0</td>\n",
+       "      <td>832.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1877</th>\n",
+       "      <td>198503</td>\n",
+       "      <td>3</td>\n",
+       "      <td>213901</td>\n",
+       "      <td>174689.0</td>\n",
+       "      <td>253113.0</td>\n",
+       "      <td>388</td>\n",
+       "      <td>317.0</td>\n",
+       "      <td>459.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1878</th>\n",
+       "      <td>198502</td>\n",
+       "      <td>3</td>\n",
+       "      <td>97586</td>\n",
+       "      <td>80949.0</td>\n",
+       "      <td>114223.0</td>\n",
+       "      <td>177</td>\n",
+       "      <td>147.0</td>\n",
+       "      <td>207.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1879</th>\n",
+       "      <td>198501</td>\n",
+       "      <td>3</td>\n",
+       "      <td>85489</td>\n",
+       "      <td>65918.0</td>\n",
+       "      <td>105060.0</td>\n",
+       "      <td>155</td>\n",
+       "      <td>120.0</td>\n",
+       "      <td>190.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1880</th>\n",
+       "      <td>198452</td>\n",
+       "      <td>3</td>\n",
+       "      <td>84830</td>\n",
+       "      <td>60602.0</td>\n",
+       "      <td>109058.0</td>\n",
+       "      <td>154</td>\n",
+       "      <td>110.0</td>\n",
+       "      <td>198.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1881</th>\n",
+       "      <td>198451</td>\n",
+       "      <td>3</td>\n",
+       "      <td>101726</td>\n",
+       "      <td>80242.0</td>\n",
+       "      <td>123210.0</td>\n",
+       "      <td>185</td>\n",
+       "      <td>146.0</td>\n",
+       "      <td>224.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1882</th>\n",
+       "      <td>198450</td>\n",
+       "      <td>3</td>\n",
+       "      <td>123680</td>\n",
+       "      <td>101401.0</td>\n",
+       "      <td>145959.0</td>\n",
+       "      <td>225</td>\n",
+       "      <td>184.0</td>\n",
+       "      <td>266.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1883</th>\n",
+       "      <td>198449</td>\n",
+       "      <td>3</td>\n",
+       "      <td>101073</td>\n",
+       "      <td>81684.0</td>\n",
+       "      <td>120462.0</td>\n",
+       "      <td>184</td>\n",
+       "      <td>149.0</td>\n",
+       "      <td>219.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1884</th>\n",
+       "      <td>198448</td>\n",
+       "      <td>3</td>\n",
+       "      <td>78620</td>\n",
+       "      <td>60634.0</td>\n",
+       "      <td>96606.0</td>\n",
+       "      <td>143</td>\n",
+       "      <td>110.0</td>\n",
+       "      <td>176.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1885</th>\n",
+       "      <td>198447</td>\n",
+       "      <td>3</td>\n",
+       "      <td>72029</td>\n",
+       "      <td>54274.0</td>\n",
+       "      <td>89784.0</td>\n",
+       "      <td>131</td>\n",
+       "      <td>99.0</td>\n",
+       "      <td>163.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1886</th>\n",
+       "      <td>198446</td>\n",
+       "      <td>3</td>\n",
+       "      <td>87330</td>\n",
+       "      <td>67686.0</td>\n",
+       "      <td>106974.0</td>\n",
+       "      <td>159</td>\n",
+       "      <td>123.0</td>\n",
+       "      <td>195.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1887</th>\n",
+       "      <td>198445</td>\n",
+       "      <td>3</td>\n",
+       "      <td>135223</td>\n",
+       "      <td>101414.0</td>\n",
+       "      <td>169032.0</td>\n",
+       "      <td>246</td>\n",
+       "      <td>184.0</td>\n",
+       "      <td>308.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1888</th>\n",
+       "      <td>198444</td>\n",
+       "      <td>3</td>\n",
+       "      <td>68422</td>\n",
+       "      <td>20056.0</td>\n",
+       "      <td>116788.0</td>\n",
+       "      <td>125</td>\n",
+       "      <td>37.0</td>\n",
+       "      <td>213.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1888 rows × 10 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        week  indicator     inc   inc_low    inc_up  inc100  inc100_low  \\\n",
+       "0     202101          3   30168   24407.0   35929.0      46        37.0   \n",
+       "1     202053          3   21449   16669.0   26229.0      33        26.0   \n",
+       "2     202052          3   16428   12285.0   20571.0      25        19.0   \n",
+       "3     202051          3   21619   17370.0   25868.0      33        27.0   \n",
+       "4     202050          3   16845   13220.0   20470.0      26        20.0   \n",
+       "5     202049          3   12939    9923.0   15955.0      20        15.0   \n",
+       "6     202048          3   13804   10641.0   16967.0      21        16.0   \n",
+       "7     202047          3   19085   15285.0   22885.0      29        23.0   \n",
+       "8     202046          3   24801   20503.0   29099.0      38        31.0   \n",
+       "9     202045          3   42516   36857.0   48175.0      65        56.0   \n",
+       "10    202044          3   44567   38521.0   50613.0      68        59.0   \n",
+       "11    202043          3   43737   37523.0   49951.0      66        57.0   \n",
+       "12    202042          3   35145   29812.0   40478.0      53        45.0   \n",
+       "13    202041          3   27877   23206.0   32548.0      42        35.0   \n",
+       "14    202040          3   20443   16381.0   24505.0      31        25.0   \n",
+       "15    202039          3   19810   15900.0   23720.0      30        24.0   \n",
+       "16    202038          3   25562   21142.0   29982.0      39        32.0   \n",
+       "17    202037          3   18485   14649.0   22321.0      28        22.0   \n",
+       "18    202036          3   10390    7646.0   13134.0      16        12.0   \n",
+       "19    202035          3    9918    6842.0   12994.0      15        10.0   \n",
+       "20    202034          3    6084    3090.0    9078.0       9         4.0   \n",
+       "21    202033          3    6106    3411.0    8801.0       9         5.0   \n",
+       "22    202032          3    5918    3330.0    8506.0       9         5.0   \n",
+       "23    202031          3    4351    2269.0    6433.0       7         4.0   \n",
+       "24    202030          3    8179    5442.0   10916.0      12         8.0   \n",
+       "25    202029          3    8687    5860.0   11514.0      13         9.0   \n",
+       "26    202028          3    8340    5701.0   10979.0      13         9.0   \n",
+       "27    202027          3    4066    2406.0    5726.0       6         3.0   \n",
+       "28    202026          3    4039    2389.0    5689.0       6         3.0   \n",
+       "29    202025          3    2853    1488.0    4218.0       4         2.0   \n",
+       "...      ...        ...     ...       ...       ...     ...         ...   \n",
+       "1859  198521          3   26096   19621.0   32571.0      47        35.0   \n",
+       "1860  198520          3   27896   20885.0   34907.0      51        38.0   \n",
+       "1861  198519          3   43154   32821.0   53487.0      78        59.0   \n",
+       "1862  198518          3   40555   29935.0   51175.0      74        55.0   \n",
+       "1863  198517          3   34053   24366.0   43740.0      62        44.0   \n",
+       "1864  198516          3   50362   36451.0   64273.0      91        66.0   \n",
+       "1865  198515          3   63881   45538.0   82224.0     116        83.0   \n",
+       "1866  198514          3  134545  114400.0  154690.0     244       207.0   \n",
+       "1867  198513          3  197206  176080.0  218332.0     357       319.0   \n",
+       "1868  198512          3  245240  223304.0  267176.0     445       405.0   \n",
+       "1869  198511          3  276205  252399.0  300011.0     501       458.0   \n",
+       "1870  198510          3  353231  326279.0  380183.0     640       591.0   \n",
+       "1871  198509          3  369895  341109.0  398681.0     670       618.0   \n",
+       "1872  198508          3  389886  359529.0  420243.0     707       652.0   \n",
+       "1873  198507          3  471852  432599.0  511105.0     855       784.0   \n",
+       "1874  198506          3  565825  518011.0  613639.0    1026       939.0   \n",
+       "1875  198505          3  637302  592795.0  681809.0    1155      1074.0   \n",
+       "1876  198504          3  424937  390794.0  459080.0     770       708.0   \n",
+       "1877  198503          3  213901  174689.0  253113.0     388       317.0   \n",
+       "1878  198502          3   97586   80949.0  114223.0     177       147.0   \n",
+       "1879  198501          3   85489   65918.0  105060.0     155       120.0   \n",
+       "1880  198452          3   84830   60602.0  109058.0     154       110.0   \n",
+       "1881  198451          3  101726   80242.0  123210.0     185       146.0   \n",
+       "1882  198450          3  123680  101401.0  145959.0     225       184.0   \n",
+       "1883  198449          3  101073   81684.0  120462.0     184       149.0   \n",
+       "1884  198448          3   78620   60634.0   96606.0     143       110.0   \n",
+       "1885  198447          3   72029   54274.0   89784.0     131        99.0   \n",
+       "1886  198446          3   87330   67686.0  106974.0     159       123.0   \n",
+       "1887  198445          3  135223  101414.0  169032.0     246       184.0   \n",
+       "1888  198444          3   68422   20056.0  116788.0     125        37.0   \n",
+       "\n",
+       "      inc100_up geo_insee geo_name  \n",
+       "0          55.0        FR   France  \n",
+       "1          40.0        FR   France  \n",
+       "2          31.0        FR   France  \n",
+       "3          39.0        FR   France  \n",
+       "4          32.0        FR   France  \n",
+       "5          25.0        FR   France  \n",
+       "6          26.0        FR   France  \n",
+       "7          35.0        FR   France  \n",
+       "8          45.0        FR   France  \n",
+       "9          74.0        FR   France  \n",
+       "10         77.0        FR   France  \n",
+       "11         75.0        FR   France  \n",
+       "12         61.0        FR   France  \n",
+       "13         49.0        FR   France  \n",
+       "14         37.0        FR   France  \n",
+       "15         36.0        FR   France  \n",
+       "16         46.0        FR   France  \n",
+       "17         34.0        FR   France  \n",
+       "18         20.0        FR   France  \n",
+       "19         20.0        FR   France  \n",
+       "20         14.0        FR   France  \n",
+       "21         13.0        FR   France  \n",
+       "22         13.0        FR   France  \n",
+       "23         10.0        FR   France  \n",
+       "24         16.0        FR   France  \n",
+       "25         17.0        FR   France  \n",
+       "26         17.0        FR   France  \n",
+       "27          9.0        FR   France  \n",
+       "28          9.0        FR   France  \n",
+       "29          6.0        FR   France  \n",
+       "...         ...       ...      ...  \n",
+       "1859       59.0        FR   France  \n",
+       "1860       64.0        FR   France  \n",
+       "1861       97.0        FR   France  \n",
+       "1862       93.0        FR   France  \n",
+       "1863       80.0        FR   France  \n",
+       "1864      116.0        FR   France  \n",
+       "1865      149.0        FR   France  \n",
+       "1866      281.0        FR   France  \n",
+       "1867      395.0        FR   France  \n",
+       "1868      485.0        FR   France  \n",
+       "1869      544.0        FR   France  \n",
+       "1870      689.0        FR   France  \n",
+       "1871      722.0        FR   France  \n",
+       "1872      762.0        FR   France  \n",
+       "1873      926.0        FR   France  \n",
+       "1874     1113.0        FR   France  \n",
+       "1875     1236.0        FR   France  \n",
+       "1876      832.0        FR   France  \n",
+       "1877      459.0        FR   France  \n",
+       "1878      207.0        FR   France  \n",
+       "1879      190.0        FR   France  \n",
+       "1880      198.0        FR   France  \n",
+       "1881      224.0        FR   France  \n",
+       "1882      266.0        FR   France  \n",
+       "1883      219.0        FR   France  \n",
+       "1884      176.0        FR   France  \n",
+       "1885      163.0        FR   France  \n",
+       "1886      195.0        FR   France  \n",
+       "1887      308.0        FR   France  \n",
+       "1888      213.0        FR   France  \n",
+       "\n",
+       "[1888 rows x 10 columns]"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data = raw_data.dropna().copy()\n",
+    "data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Nos données utilisent une convention inhabituelle: le numéro de\n",
+    "semaine est collé à l'année, donnant l'impression qu'il s'agit\n",
+    "de nombre entier. C'est comme ça que Pandas les interprète.\n",
+    "  \n",
+    "Un deuxième problème est que Pandas ne comprend pas les numéros de\n",
+    "semaine.  Il faut lui fournir les dates de début et de fin de\n",
+    "semaine. Nous utilisons pour cela la bibliothèque `isoweek`.\n",
+    "\n",
+    "Comme la conversion des semaines est devenu assez complexe, nous\n",
+    "écrivons une petite fonction Python pour cela. Ensuite, nous\n",
+    "l'appliquons à tous les points de nos donnés. Les résultats vont\n",
+    "dans une nouvelle colonne 'period'."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "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:])\n",
+    "    w = isoweek.Week(year, week)\n",
+    "    return pd.Period(w.day(0), 'W')\n",
+    "\n",
+    "data['period'] = [convert_week(yw) for yw in data['week']]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Il restent deux petites modifications à faire.\n",
+    "\n",
+    "Premièrement, nous définissons les périodes d'observation\n",
+    "comme nouvel index de notre jeu de données. Ceci en fait\n",
+    "une suite chronologique, ce qui sera pratique par la suite.\n",
+    "\n",
+    "Deuxièmement, nous trions les points par période, dans\n",
+    "le sens chronologique."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sorted_data = data.set_index('period').sort_index()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Nous vérifions la cohérence des données. Entre la fin d'une période et\n",
+    "le début de la période qui suit, la différence temporelle doit être\n",
+    "zéro, ou au moins très faible. Nous laissons une \"marge d'erreur\"\n",
+    "d'une seconde.\n",
+    "\n",
+    "Ceci s'avère tout à fait juste sauf pour deux périodes consécutives\n",
+    "entre lesquelles il manque une semaine.\n",
+    "\n",
+    "Nous reconnaissons ces dates: c'est la semaine sans observations\n",
+    "que nous avions supprimées !"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1989-05-01/1989-05-07 1989-05-15/1989-05-21\n"
+     ]
+    }
+   ],
+   "source": [
+    "periods = sorted_data.index\n",
+    "for p1, p2 in zip(periods[:-1], periods[1:]):\n",
+    "    delta = p2.to_timestamp() - p1.end_time\n",
+    "    if delta > pd.Timedelta('1s'):\n",
+    "        print(p1, p2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Un premier regard sur les données !"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fe9a05bf7b8>"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sorted_data['inc'].plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Un zoom sur les dernières années montre mieux la situation des pics en hiver. Le creux des incidences se trouve en été."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fe99e339b00>"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sorted_data['inc'][-200:].plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Etude de l'incidence annuelle"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Etant donné que le pic de l'épidémie se situe en hiver, à cheval\n",
+    "entre deux années civiles, nous définissons la période de référence\n",
+    "entre deux minima de l'incidence, du 1er août de l'année $N$ au\n",
+    "1er août de l'année $N+1$.\n",
+    "\n",
+    "Notre tâche est un peu compliquée par le fait que l'année ne comporte\n",
+    "pas un nombre entier de semaines. Nous modifions donc un peu nos périodes\n",
+    "de référence: à la place du 1er août de chaque année, nous utilisons le\n",
+    "premier jour de la semaine qui contient le 1er août.\n",
+    "\n",
+    "Comme l'incidence de syndrome grippal est très faible en été, cette\n",
+    "modification ne risque pas de fausser nos conclusions.\n",
+    "\n",
+    "Encore un petit détail: les données commencent en octobre 1984, ce qui\n",
+    "rend la première année incomplète. Nous commençons donc l'analyse en 1985."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "first_august_week = [pd.Period(pd.Timestamp(y, 8, 1), 'W')\n",
+    "                     for y in range(1985,\n",
+    "                                    sorted_data.index[-1].year)]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "En partant de cette liste des semaines qui contiennent un 1er août, nous obtenons nos intervalles d'environ un an comme les périodes entre deux semaines adjacentes dans cette liste. Nous calculons les sommes des incidences hebdomadaires pour toutes ces périodes.\n",
+    "\n",
+    "Nous vérifions également que ces périodes contiennent entre 51 et 52 semaines, pour nous protéger contre des éventuelles erreurs dans notre code."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "year = []\n",
+    "yearly_incidence = []\n",
+    "for week1, week2 in zip(first_august_week[:-1],\n",
+    "                        first_august_week[1:]):\n",
+    "    one_year = sorted_data['inc'][week1:week2-1]\n",
+    "    assert abs(len(one_year)-52) < 2\n",
+    "    yearly_incidence.append(one_year.sum())\n",
+    "    year.append(week2.year)\n",
+    "yearly_incidence = pd.Series(data=yearly_incidence, index=year)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Voici les incidences annuelles."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fe99e2be978>"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "yearly_incidence.plot(style='*')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Une liste triée permet de plus facilement répérer les valeurs les plus élevées (à la fin)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2014    1600941\n",
+       "1991    1659249\n",
+       "1995    1840410\n",
+       "2020    2042389\n",
+       "2012    2175217\n",
+       "2003    2234584\n",
+       "2019    2254386\n",
+       "2006    2307352\n",
+       "2017    2321583\n",
+       "2001    2529279\n",
+       "1992    2574578\n",
+       "1993    2703886\n",
+       "2018    2705325\n",
+       "1988    2765617\n",
+       "2007    2780164\n",
+       "1987    2855570\n",
+       "2016    2856393\n",
+       "2011    2857040\n",
+       "2008    2973918\n",
+       "1998    3034904\n",
+       "2002    3125418\n",
+       "2009    3444020\n",
+       "1994    3514763\n",
+       "1996    3539413\n",
+       "2004    3567744\n",
+       "1997    3620066\n",
+       "2015    3654892\n",
+       "2000    3826372\n",
+       "2005    3835025\n",
+       "1999    3908112\n",
+       "2010    4111392\n",
+       "2013    4182691\n",
+       "1986    5115251\n",
+       "1990    5235827\n",
+       "1989    5466192\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "yearly_incidence.sort_values()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Enfin, un histogramme montre bien que les épidémies fortes, qui touchent environ 10% de la population\n",
+    "  française, sont assez rares: il y en eu trois au cours des 35 dernières années."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fe99e237400>"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "yearly_incidence.hist(xrot=20)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
  "metadata": {
   "kernelspec": {
    "display_name": "Python 3",
@@ -16,10 +2523,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 1
 }
-
diff --git a/module3/exo3/incidence.csv b/module3/exo3/incidence.csv
new file mode 100644
index 0000000..ee7afbc
--- /dev/null
+++ b/module3/exo3/incidence.csv
@@ -0,0 +1,1892 @@
+,week,indicator,inc,inc_low,inc_up,inc100,inc100_low,inc100_up,geo_insee,geo_name
+0,202103,3,28139,22926.0,33352.0,43,35.0,51.0,FR,France
+1,202102,3,18010,14474.0,21546.0,27,22.0,32.0,FR,France
+2,202101,3,21809,17786.0,25832.0,33,27.0,39.0,FR,France
+3,202053,3,21220,16498.0,25942.0,32,25.0,39.0,FR,France
+4,202052,3,16428,12285.0,20571.0,25,19.0,31.0,FR,France
+5,202051,3,21619,17370.0,25868.0,33,27.0,39.0,FR,France
+6,202050,3,16845,13220.0,20470.0,26,20.0,32.0,FR,France
+7,202049,3,12939,9923.0,15955.0,20,15.0,25.0,FR,France
+8,202048,3,13804,10641.0,16967.0,21,16.0,26.0,FR,France
+9,202047,3,19085,15285.0,22885.0,29,23.0,35.0,FR,France
+10,202046,3,24801,20503.0,29099.0,38,31.0,45.0,FR,France
+11,202045,3,42516,36857.0,48175.0,65,56.0,74.0,FR,France
+12,202044,3,44567,38521.0,50613.0,68,59.0,77.0,FR,France
+13,202043,3,43737,37523.0,49951.0,66,57.0,75.0,FR,France
+14,202042,3,35145,29812.0,40478.0,53,45.0,61.0,FR,France
+15,202041,3,27877,23206.0,32548.0,42,35.0,49.0,FR,France
+16,202040,3,20443,16381.0,24505.0,31,25.0,37.0,FR,France
+17,202039,3,19810,15900.0,23720.0,30,24.0,36.0,FR,France
+18,202038,3,25562,21142.0,29982.0,39,32.0,46.0,FR,France
+19,202037,3,18485,14649.0,22321.0,28,22.0,34.0,FR,France
+20,202036,3,10390,7646.0,13134.0,16,12.0,20.0,FR,France
+21,202035,3,9918,6842.0,12994.0,15,10.0,20.0,FR,France
+22,202034,3,6084,3090.0,9078.0,9,4.0,14.0,FR,France
+23,202033,3,6106,3411.0,8801.0,9,5.0,13.0,FR,France
+24,202032,3,5918,3330.0,8506.0,9,5.0,13.0,FR,France
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+1793,198637,3,15998,10802.0,21194.0,29,20.0,38.0,FR,France
+1794,198636,3,9182,4982.0,13382.0,17,9.0,25.0,FR,France
+1795,198635,3,10587,4470.0,16704.0,19,8.0,30.0,FR,France
+1796,198634,3,5762,858.0,10666.0,10,1.0,19.0,FR,France
+1797,198633,3,3115,554.0,5676.0,6,1.0,11.0,FR,France
+1798,198632,3,1027,0.0,2311.0,2,0.0,4.0,FR,France
+1799,198631,3,2247,0.0,4574.0,4,0.0,8.0,FR,France
+1800,198630,3,2346,141.0,4551.0,4,0.0,8.0,FR,France
+1801,198629,3,3654,931.0,6377.0,7,2.0,12.0,FR,France
+1802,198628,3,2327,0.0,5318.0,4,0.0,9.0,FR,France
+1803,198627,3,7529,3353.0,11705.0,14,6.0,22.0,FR,France
+1804,198626,3,8778,5106.0,12450.0,16,9.0,23.0,FR,France
+1805,198625,3,11075,6804.0,15346.0,20,12.0,28.0,FR,France
+1806,198624,3,11160,7252.0,15068.0,20,13.0,27.0,FR,France
+1807,198623,3,14372,9896.0,18848.0,26,18.0,34.0,FR,France
+1808,198622,3,9717,5594.0,13840.0,18,11.0,25.0,FR,France
+1809,198621,3,14460,9575.0,19345.0,26,17.0,35.0,FR,France
+1810,198620,3,17133,12106.0,22160.0,31,22.0,40.0,FR,France
+1811,198619,3,22177,16008.0,28346.0,40,29.0,51.0,FR,France
+1812,198618,3,31736,24115.0,39357.0,57,43.0,71.0,FR,France
+1813,198617,3,34874,27440.0,42308.0,63,50.0,76.0,FR,France
+1814,198616,3,41196,32894.0,49498.0,74,59.0,89.0,FR,France
+1815,198615,3,42659,33537.0,51781.0,77,61.0,93.0,FR,France
+1816,198614,3,49792,39728.0,59856.0,90,72.0,108.0,FR,France
+1817,198613,3,87249,63562.0,110936.0,157,114.0,200.0,FR,France
+1818,198612,3,124777,97237.0,152317.0,225,175.0,275.0,FR,France
+1819,198611,3,168146,151035.0,185257.0,303,272.0,334.0,FR,France
+1820,198610,3,257305,231225.0,283385.0,464,417.0,511.0,FR,France
+1821,198609,3,321140,296644.0,345636.0,580,536.0,624.0,FR,France
+1822,198608,3,448786,419219.0,478353.0,810,757.0,863.0,FR,France
+1823,198607,3,490723,460150.0,521296.0,886,831.0,941.0,FR,France
+1824,198606,3,439300,411764.0,466836.0,793,743.0,843.0,FR,France
+1825,198605,3,364727,339868.0,389586.0,658,613.0,703.0,FR,France
+1826,198604,3,348509,322464.0,374554.0,629,582.0,676.0,FR,France
+1827,198603,3,271539,248654.0,294424.0,490,449.0,531.0,FR,France
+1828,198602,3,178138,159344.0,196932.0,322,288.0,356.0,FR,France
+1829,198601,3,112614,96539.0,128689.0,203,174.0,232.0,FR,France
+1830,198552,3,86452,72250.0,100654.0,157,131.0,183.0,FR,France
+1831,198551,3,114666,99538.0,129794.0,208,181.0,235.0,FR,France
+1832,198550,3,86031,73604.0,98458.0,156,133.0,179.0,FR,France
+1833,198549,3,65931,55326.0,76536.0,120,101.0,139.0,FR,France
+1834,198548,3,68291,57581.0,79001.0,124,105.0,143.0,FR,France
+1835,198547,3,66177,55221.0,77133.0,120,100.0,140.0,FR,France
+1836,198546,3,70534,58788.0,82280.0,128,107.0,149.0,FR,France
+1837,198545,3,57514,47167.0,67861.0,104,85.0,123.0,FR,France
+1838,198544,3,67356,55744.0,78968.0,122,101.0,143.0,FR,France
+1839,198543,3,87402,74208.0,100596.0,158,134.0,182.0,FR,France
+1840,198542,3,76218,64604.0,87832.0,138,117.0,159.0,FR,France
+1841,198541,3,45712,36755.0,54669.0,83,67.0,99.0,FR,France
+1842,198540,3,49739,40335.0,59143.0,90,73.0,107.0,FR,France
+1843,198539,3,39819,31234.0,48404.0,72,56.0,88.0,FR,France
+1844,198538,3,27605,20614.0,34596.0,50,37.0,63.0,FR,France
+1845,198537,3,22219,15626.0,28812.0,40,28.0,52.0,FR,France
+1846,198536,3,27986,18992.0,36980.0,51,35.0,67.0,FR,France
+1847,198535,3,30215,18546.0,41884.0,55,34.0,76.0,FR,France
+1848,198534,3,40389,24786.0,55992.0,73,45.0,101.0,FR,France
+1849,198533,3,22611,8819.0,36403.0,41,16.0,66.0,FR,France
+1850,198532,3,7488,1851.0,13125.0,14,4.0,24.0,FR,France
+1851,198531,3,16958,8479.0,25437.0,31,16.0,46.0,FR,France
+1852,198530,3,11598,5507.0,17689.0,21,10.0,32.0,FR,France
+1853,198529,3,13054,6474.0,19634.0,24,12.0,36.0,FR,France
+1854,198528,3,14588,7659.0,21517.0,26,13.0,39.0,FR,France
+1855,198527,3,19670,11761.0,27579.0,36,22.0,50.0,FR,France
+1856,198526,3,18609,12637.0,24581.0,34,23.0,45.0,FR,France
+1857,198525,3,19362,12454.0,26270.0,35,22.0,48.0,FR,France
+1858,198524,3,19855,13577.0,26133.0,36,25.0,47.0,FR,France
+1859,198523,3,19373,10010.0,28736.0,35,18.0,52.0,FR,France
+1860,198522,3,24099,17190.0,31008.0,44,31.0,57.0,FR,France
+1861,198521,3,26096,19621.0,32571.0,47,35.0,59.0,FR,France
+1862,198520,3,27896,20885.0,34907.0,51,38.0,64.0,FR,France
+1863,198519,3,43154,32821.0,53487.0,78,59.0,97.0,FR,France
+1864,198518,3,40555,29935.0,51175.0,74,55.0,93.0,FR,France
+1865,198517,3,34053,24366.0,43740.0,62,44.0,80.0,FR,France
+1866,198516,3,50362,36451.0,64273.0,91,66.0,116.0,FR,France
+1867,198515,3,63881,45538.0,82224.0,116,83.0,149.0,FR,France
+1868,198514,3,134545,114400.0,154690.0,244,207.0,281.0,FR,France
+1869,198513,3,197206,176080.0,218332.0,357,319.0,395.0,FR,France
+1870,198512,3,245240,223304.0,267176.0,445,405.0,485.0,FR,France
+1871,198511,3,276205,252399.0,300011.0,501,458.0,544.0,FR,France
+1872,198510,3,353231,326279.0,380183.0,640,591.0,689.0,FR,France
+1873,198509,3,369895,341109.0,398681.0,670,618.0,722.0,FR,France
+1874,198508,3,389886,359529.0,420243.0,707,652.0,762.0,FR,France
+1875,198507,3,471852,432599.0,511105.0,855,784.0,926.0,FR,France
+1876,198506,3,565825,518011.0,613639.0,1026,939.0,1113.0,FR,France
+1877,198505,3,637302,592795.0,681809.0,1155,1074.0,1236.0,FR,France
+1878,198504,3,424937,390794.0,459080.0,770,708.0,832.0,FR,France
+1879,198503,3,213901,174689.0,253113.0,388,317.0,459.0,FR,France
+1880,198502,3,97586,80949.0,114223.0,177,147.0,207.0,FR,France
+1881,198501,3,85489,65918.0,105060.0,155,120.0,190.0,FR,France
+1882,198452,3,84830,60602.0,109058.0,154,110.0,198.0,FR,France
+1883,198451,3,101726,80242.0,123210.0,185,146.0,224.0,FR,France
+1884,198450,3,123680,101401.0,145959.0,225,184.0,266.0,FR,France
+1885,198449,3,101073,81684.0,120462.0,184,149.0,219.0,FR,France
+1886,198448,3,78620,60634.0,96606.0,143,110.0,176.0,FR,France
+1887,198447,3,72029,54274.0,89784.0,131,99.0,163.0,FR,France
+1888,198446,3,87330,67686.0,106974.0,159,123.0,195.0,FR,France
+1889,198445,3,135223,101414.0,169032.0,246,184.0,308.0,FR,France
+1890,198444,3,68422,20056.0,116788.0,125,37.0,213.0,FR,France
-- 
2.18.1