From e58195d2cbd62868567a41c1f177249492fe8ce2 Mon Sep 17 00:00:00 2001
From: 269f2cc5a36d63b5f4ed2df8fc9d5af1
 <269f2cc5a36d63b5f4ed2df8fc9d5af1@app-learninglab.inria.fr>
Date: Mon, 9 Dec 2024 09:31:36 +0000
Subject: [PATCH] final

---
 module3/exo2/data.csv       | 1776 +++++++++++++++++++++++++++++++++++
 module3/exo2/exercice.ipynb | 1444 +++++++++++++++++++++++++++-
 2 files changed, 3217 insertions(+), 3 deletions(-)
 create mode 100644 module3/exo2/data.csv

diff --git a/module3/exo2/data.csv b/module3/exo2/data.csv
new file mode 100644
index 0000000..214eec2
--- /dev/null
+++ b/module3/exo2/data.csv
@@ -0,0 +1,1776 @@
+# {"source":"r&#233;seau Sentinelles, INSERM, Sorbonne Universit&#233;, https:\/\/www.sentiweb.fr","meta":{"period":[199049,202448],"geo":["PAY",0],"geo_ref":"insee","indicator":"7","type":"all","conf_int":true,"compact":false,"age_group":false,"span":"all"},"date":"2024-12-04T17:31:27+01:00","bundle":"1733329874"}
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+199512,7,15875,12429,19321,27,21,33,FR,France
+199511,7,12844,9644,16044,22,16,28,FR,France
+199510,7,15346,11782,18910,27,21,33,FR,France
+199509,7,14754,11260,18248,26,20,32,FR,France
+199508,7,14521,11077,17965,25,19,31,FR,France
+199507,7,14315,10809,17821,25,19,31,FR,France
+199506,7,18089,14383,21795,31,25,37,FR,France
+199505,7,13414,10176,16652,23,17,29,FR,France
+199504,7,15743,12316,19170,27,21,33,FR,France
+199503,7,13763,10614,16912,24,19,29,FR,France
+199502,7,11495,8490,14500,20,15,25,FR,France
+199501,7,13733,10266,17200,24,18,30,FR,France
+199452,7,12696,9453,15939,22,16,28,FR,France
+199451,7,10390,7458,13322,18,13,23,FR,France
+199450,7,8048,5524,10572,14,10,18,FR,France
+199449,7,8212,5651,10773,14,10,18,FR,France
+199448,7,6481,4250,8712,11,7,15,FR,France
+199447,7,7140,4666,9614,12,8,16,FR,France
+199446,7,5021,2972,7070,9,5,13,FR,France
+199445,7,6759,4267,9251,12,8,16,FR,France
+199444,7,9276,5996,12556,16,10,22,FR,France
+199443,7,5622,3091,8153,10,6,14,FR,France
+199442,7,5848,3383,8313,10,6,14,FR,France
+199441,7,4921,2796,7046,9,5,13,FR,France
+199440,7,5936,3694,8178,10,6,14,FR,France
+199439,7,4090,2080,6100,7,4,10,FR,France
+199438,7,2734,1164,4304,5,2,8,FR,France
+199437,7,4364,1957,6771,8,4,12,FR,France
+199436,7,1991,509,3473,3,0,6,FR,France
+199435,7,3676,1494,5858,6,2,10,FR,France
+199434,7,6830,3728,9932,12,7,17,FR,France
+199433,7,6933,3534,10332,12,6,18,FR,France
+199432,7,4851,2299,7403,8,4,12,FR,France
+199431,7,7346,3935,10757,13,7,19,FR,France
+199430,7,17674,12807,22541,31,23,39,FR,France
+199429,7,17175,12461,21889,30,22,38,FR,France
+199428,7,16743,12021,21465,29,21,37,FR,France
+199427,7,22335,17343,27327,39,30,48,FR,France
+199426,7,23679,18832,28526,41,33,49,FR,France
+199425,7,24951,20263,29639,43,35,51,FR,France
+199424,7,29139,22549,35729,51,40,62,FR,France
+199423,7,13583,3641,23525,24,7,41,FR,France
+199422,7,16336,4640,28032,28,8,48,FR,France
+199421,7,16477,11025,21929,29,20,38,FR,France
+199420,7,12872,9458,16286,22,16,28,FR,France
+199419,7,13769,10440,17098,24,18,30,FR,France
+199418,7,13066,9917,16215,23,18,28,FR,France
+199417,7,18648,14838,22458,32,25,39,FR,France
+199416,7,17629,13660,21598,31,24,38,FR,France
+199415,7,23128,18550,27706,40,32,48,FR,France
+199414,7,20128,15971,24285,35,28,42,FR,France
+199413,7,16259,12721,19797,28,22,34,FR,France
+199412,7,15215,11581,18849,26,20,32,FR,France
+199411,7,16439,12812,20066,29,23,35,FR,France
+199410,7,20681,16433,24929,36,29,43,FR,France
+199409,7,22652,17519,27785,39,30,48,FR,France
+199408,7,22067,17044,27090,38,29,47,FR,France
+199407,7,15332,11563,19101,27,20,34,FR,France
+199406,7,15321,11710,18932,27,21,33,FR,France
+199405,7,15264,11523,19005,27,21,33,FR,France
+199404,7,10871,7697,14045,19,13,25,FR,France
+199403,7,10882,7808,13956,19,14,24,FR,France
+199402,7,11834,8348,15320,21,15,27,FR,France
+199401,7,11104,8142,14066,19,14,24,FR,France
+199352,7,9874,6746,13002,17,12,22,FR,France
+199351,7,9565,6818,12312,17,12,22,FR,France
+199350,7,6195,4181,8209,11,7,15,FR,France
+199349,7,10095,7443,12747,18,13,23,FR,France
+199348,7,6413,4261,8565,11,7,15,FR,France
+199347,7,7543,4934,10152,13,8,18,FR,France
+199346,7,7862,5175,10549,14,9,19,FR,France
+199345,7,5648,3511,7785,10,6,14,FR,France
+199344,7,6964,4509,9419,12,8,16,FR,France
+199343,7,5976,3632,8320,10,6,14,FR,France
+199342,7,7669,4853,10485,13,8,18,FR,France
+199341,7,9657,6648,12666,17,12,22,FR,France
+199340,7,5725,3082,8368,10,5,15,FR,France
+199339,7,5520,3207,7833,10,6,14,FR,France
+199338,7,2179,888,3470,4,2,6,FR,France
+199337,7,1762,557,2967,3,1,5,FR,France
+199336,7,3214,1526,4902,6,3,9,FR,France
+199335,7,2335,910,3760,4,2,6,FR,France
+199334,7,3770,1712,5828,7,3,11,FR,France
+199333,7,5925,3250,8600,10,5,15,FR,France
+199332,7,12711,8079,17343,22,14,30,FR,France
+199331,7,12481,7874,17088,22,14,30,FR,France
+199330,7,12584,8619,16549,22,15,29,FR,France
+199329,7,13179,8991,17367,23,16,30,FR,France
+199328,7,15293,11335,19251,27,20,34,FR,France
+199327,7,14134,9791,18477,25,17,33,FR,France
+199326,7,17937,13577,22297,31,23,39,FR,France
+199325,7,19581,14916,24246,34,26,42,FR,France
+199324,7,18285,13450,23120,32,24,40,FR,France
+199323,7,16003,11927,20079,28,21,35,FR,France
+199322,7,12652,8597,16707,22,15,29,FR,France
+199321,7,15218,10970,19466,27,20,34,FR,France
+199320,7,11343,7655,15031,20,14,26,FR,France
+199319,7,12086,8856,15316,21,15,27,FR,France
+199318,7,18898,14305,23491,33,25,41,FR,France
+199317,7,14969,10565,19373,26,18,34,FR,France
+199316,7,15102,11226,18978,26,19,33,FR,France
+199315,7,15058,11183,18933,26,19,33,FR,France
+199314,7,12425,9045,15805,22,16,28,FR,France
+199313,7,12266,8927,15605,21,15,27,FR,France
+199312,7,10821,7884,13758,19,14,24,FR,France
+199311,7,11021,8006,14036,19,14,24,FR,France
+199310,7,15847,12158,19536,28,22,34,FR,France
+199309,7,15084,11059,19109,26,19,33,FR,France
+199308,7,16967,12936,20998,30,23,37,FR,France
+199307,7,16057,12350,19764,28,22,34,FR,France
+199306,7,15887,12275,19499,28,22,34,FR,France
+199305,7,15954,12443,19465,28,22,34,FR,France
+199304,7,12374,9426,15322,22,17,27,FR,France
+199303,7,15283,11831,18735,27,21,33,FR,France
+199302,7,13366,10262,16470,23,18,28,FR,France
+199301,7,18678,14977,22379,33,27,39,FR,France
+199253,7,17829,13827,21831,31,24,38,FR,France
+199252,7,14330,10582,18078,25,18,32,FR,France
+199251,7,14635,11262,18008,26,20,32,FR,France
+199250,7,15252,11566,18938,27,21,33,FR,France
+199249,7,14411,11187,17635,25,19,31,FR,France
+199248,7,10048,7396,12700,18,13,23,FR,France
+199247,7,13069,9752,16386,23,17,29,FR,France
+199246,7,6900,4727,9073,12,8,16,FR,France
+199245,7,10791,7794,13788,19,14,24,FR,France
+199244,7,10205,7482,12928,18,13,23,FR,France
+199243,7,7196,4908,9484,13,9,17,FR,France
+199242,7,5748,3738,7758,10,6,14,FR,France
+199241,7,3587,2045,5129,6,3,9,FR,France
+199240,7,5654,3442,7866,10,6,14,FR,France
+199239,7,4747,2751,6743,8,5,11,FR,France
+199238,7,2842,1306,4378,5,2,8,FR,France
+199237,7,4103,2203,6003,7,4,10,FR,France
+199236,7,2801,1200,4402,5,2,8,FR,France
+199235,7,6428,3717,9139,11,6,16,FR,France
+199234,7,7517,4190,10844,13,7,19,FR,France
+199233,7,9951,5955,13947,17,10,24,FR,France
+199232,7,16090,11337,20843,28,20,36,FR,France
+199231,7,17156,12441,21871,30,22,38,FR,France
+199230,7,21780,16301,27259,38,28,48,FR,France
+199229,7,18926,13397,24455,33,23,43,FR,France
+199228,7,28144,20384,35904,49,35,63,FR,France
+199227,7,29388,22331,36445,51,39,63,FR,France
+199226,7,27933,21686,34180,49,38,60,FR,France
+199225,7,26446,21153,31739,46,37,55,FR,France
+199224,7,19614,14769,24459,34,26,42,FR,France
+199223,7,23628,17852,29404,41,31,51,FR,France
+199222,7,20438,14868,26008,36,26,46,FR,France
+199221,7,22595,17395,27795,40,31,49,FR,France
+199220,7,21092,15963,26221,37,28,46,FR,France
+199219,7,19210,13934,24486,34,25,43,FR,France
+199218,7,30273,22605,37941,53,40,66,FR,France
+199217,7,19162,14251,24073,34,25,43,FR,France
+199216,7,15583,11158,20008,27,19,35,FR,France
+199215,7,15473,10723,20223,27,19,35,FR,France
+199214,7,14455,10040,18870,25,17,33,FR,France
+199213,7,17146,12105,22187,30,21,39,FR,France
+199212,7,15838,10923,20753,28,19,37,FR,France
+199211,7,20003,13824,26182,35,24,46,FR,France
+199210,7,22906,16060,29752,40,28,52,FR,France
+199209,7,21824,15687,27961,38,27,49,FR,France
+199208,7,15243,10265,20221,27,18,36,FR,France
+199207,7,22633,16160,29106,40,29,51,FR,France
+199206,7,17009,12219,21799,30,22,38,FR,France
+199205,7,15997,11590,20404,28,20,36,FR,France
+199204,7,20690,15075,26305,36,26,46,FR,France
+199203,7,18586,12684,24488,33,23,43,FR,France
+199202,7,16588,10590,22586,29,18,40,FR,France
+199201,7,23607,16552,30662,41,29,53,FR,France
+199152,7,15184,10392,19976,27,19,35,FR,France
+199151,7,15043,10624,19462,26,18,34,FR,France
+199150,7,14115,9737,18493,25,17,33,FR,France
+199149,7,13304,8548,18060,23,15,31,FR,France
+199148,7,15370,10164,20576,27,18,36,FR,France
+199147,7,12813,8139,17487,23,15,31,FR,France
+199146,7,6453,3123,9783,11,5,17,FR,France
+199145,7,8048,4083,12013,14,7,21,FR,France
+199144,7,9882,5623,14141,17,10,24,FR,France
+199143,7,14307,8645,19969,25,15,35,FR,France
+199142,7,6419,3334,9504,11,6,16,FR,France
+199141,7,6168,3113,9223,11,6,16,FR,France
+199140,7,3615,1159,6071,6,2,10,FR,France
+199139,7,3105,472,5738,5,0,10,FR,France
+199138,7,4446,1435,7457,8,3,13,FR,France
+199137,7,1457,0,3262,3,0,6,FR,France
+199136,7,3053,29,6077,5,0,10,FR,France
+199135,7,805,0,2556,1,0,4,FR,France
+199134,7,5512,856,10168,10,2,18,FR,France
+199133,7,7347,2903,11791,13,5,21,FR,France
+199132,7,16099,7334,24864,28,13,43,FR,France
+199131,7,16803,8145,25461,30,15,45,FR,France
+199130,7,15915,6368,25462,28,11,45,FR,France
+199129,7,23744,14703,32785,42,26,58,FR,France
+199128,7,24222,15617,32827,43,28,58,FR,France
+199127,7,20309,12868,27750,36,23,49,FR,France
+199126,7,17608,11304,23912,31,20,42,FR,France
+199125,7,16169,10700,21638,28,18,38,FR,France
+199124,7,16171,10071,22271,28,17,39,FR,France
+199123,7,11947,7671,16223,21,13,29,FR,France
+199122,7,15452,9953,20951,27,17,37,FR,France
+199121,7,14903,8975,20831,26,16,36,FR,France
+199120,7,19053,12742,25364,34,23,45,FR,France
+199119,7,16739,11246,22232,29,19,39,FR,France
+199118,7,21385,13882,28888,38,25,51,FR,France
+199117,7,13462,8877,18047,24,16,32,FR,France
+199116,7,14857,10068,19646,26,18,34,FR,France
+199115,7,13975,9781,18169,25,18,32,FR,France
+199114,7,12265,7684,16846,22,14,30,FR,France
+199113,7,9567,6041,13093,17,11,23,FR,France
+199112,7,10864,7331,14397,19,13,25,FR,France
+199111,7,15574,11184,19964,27,19,35,FR,France
+199110,7,16643,11372,21914,29,20,38,FR,France
+199109,7,13741,8780,18702,24,15,33,FR,France
+199108,7,13289,8813,17765,23,15,31,FR,France
+199107,7,12337,8077,16597,22,15,29,FR,France
+199106,7,10877,7013,14741,19,12,26,FR,France
+199105,7,10442,6544,14340,18,11,25,FR,France
+199104,7,7913,4563,11263,14,8,20,FR,France
+199103,7,15387,10484,20290,27,18,36,FR,France
+199102,7,16277,11046,21508,29,20,38,FR,France
+199101,7,15565,10271,20859,27,18,36,FR,France
+199052,7,19375,13295,25455,34,23,45,FR,France
+199051,7,19080,13807,24353,34,25,43,FR,France
+199050,7,11079,6660,15498,20,12,28,FR,France
+199049,7,1143,0,2610,2,0,5,FR,France
diff --git a/module3/exo2/exercice.ipynb b/module3/exo2/exercice.ipynb
index 0bbbe37..9b013fc 100644
--- a/module3/exo2/exercice.ipynb
+++ b/module3/exo2/exercice.ipynb
@@ -1,5 +1,1444 @@
 {
- "cells": [],
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import pandas as pd\n",
+    "import isoweek"
+   ]
+  },
+  {
+   "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": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import urllib.request\n",
+    "import os\n",
+    "\n",
+    "data_url = \"http://www.sentiweb.fr/datasets/all/inc-7-PAY.csv\"\n",
+    "data = \"data.csv\"\n",
+    "\n",
+    "if not os.path.exists(data):\n",
+    "    urllib.request.urlretrieve(data_url, \"data.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": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>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>202448</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4218</td>\n",
+       "      <td>1335</td>\n",
+       "      <td>7101</td>\n",
+       "      <td>6</td>\n",
+       "      <td>2</td>\n",
+       "      <td>10</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>202447</td>\n",
+       "      <td>7</td>\n",
+       "      <td>1965</td>\n",
+       "      <td>738</td>\n",
+       "      <td>3192</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>202446</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2260</td>\n",
+       "      <td>863</td>\n",
+       "      <td>3657</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>202445</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2713</td>\n",
+       "      <td>1216</td>\n",
+       "      <td>4210</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2</td>\n",
+       "      <td>6</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>202444</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2135</td>\n",
+       "      <td>676</td>\n",
+       "      <td>3594</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>202443</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2124</td>\n",
+       "      <td>641</td>\n",
+       "      <td>3607</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>202442</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2621</td>\n",
+       "      <td>1246</td>\n",
+       "      <td>3996</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2</td>\n",
+       "      <td>6</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>202441</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2035</td>\n",
+       "      <td>381</td>\n",
+       "      <td>3689</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>202440</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2125</td>\n",
+       "      <td>725</td>\n",
+       "      <td>3525</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>202439</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2898</td>\n",
+       "      <td>1333</td>\n",
+       "      <td>4463</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2</td>\n",
+       "      <td>6</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>202438</td>\n",
+       "      <td>7</td>\n",
+       "      <td>751</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1513</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>202437</td>\n",
+       "      <td>7</td>\n",
+       "      <td>916</td>\n",
+       "      <td>28</td>\n",
+       "      <td>1804</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>202436</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2235</td>\n",
+       "      <td>870</td>\n",
+       "      <td>3600</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>202435</td>\n",
+       "      <td>7</td>\n",
+       "      <td>1620</td>\n",
+       "      <td>285</td>\n",
+       "      <td>2955</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>202434</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2560</td>\n",
+       "      <td>622</td>\n",
+       "      <td>4498</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1</td>\n",
+       "      <td>7</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>202433</td>\n",
+       "      <td>7</td>\n",
+       "      <td>1971</td>\n",
+       "      <td>536</td>\n",
+       "      <td>3406</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>202432</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4399</td>\n",
+       "      <td>1944</td>\n",
+       "      <td>6854</td>\n",
+       "      <td>7</td>\n",
+       "      <td>3</td>\n",
+       "      <td>11</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>202431</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4500</td>\n",
+       "      <td>2213</td>\n",
+       "      <td>6787</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4</td>\n",
+       "      <td>10</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>202430</td>\n",
+       "      <td>7</td>\n",
+       "      <td>7004</td>\n",
+       "      <td>4278</td>\n",
+       "      <td>9730</td>\n",
+       "      <td>11</td>\n",
+       "      <td>7</td>\n",
+       "      <td>15</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>202429</td>\n",
+       "      <td>7</td>\n",
+       "      <td>9270</td>\n",
+       "      <td>6303</td>\n",
+       "      <td>12237</td>\n",
+       "      <td>14</td>\n",
+       "      <td>10</td>\n",
+       "      <td>18</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>202428</td>\n",
+       "      <td>7</td>\n",
+       "      <td>9364</td>\n",
+       "      <td>6498</td>\n",
+       "      <td>12230</td>\n",
+       "      <td>14</td>\n",
+       "      <td>10</td>\n",
+       "      <td>18</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>202427</td>\n",
+       "      <td>7</td>\n",
+       "      <td>10247</td>\n",
+       "      <td>7090</td>\n",
+       "      <td>13404</td>\n",
+       "      <td>15</td>\n",
+       "      <td>10</td>\n",
+       "      <td>20</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>202426</td>\n",
+       "      <td>7</td>\n",
+       "      <td>14368</td>\n",
+       "      <td>10399</td>\n",
+       "      <td>18337</td>\n",
+       "      <td>22</td>\n",
+       "      <td>16</td>\n",
+       "      <td>28</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>202425</td>\n",
+       "      <td>7</td>\n",
+       "      <td>11174</td>\n",
+       "      <td>8039</td>\n",
+       "      <td>14309</td>\n",
+       "      <td>17</td>\n",
+       "      <td>12</td>\n",
+       "      <td>22</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>202424</td>\n",
+       "      <td>7</td>\n",
+       "      <td>12621</td>\n",
+       "      <td>9357</td>\n",
+       "      <td>15885</td>\n",
+       "      <td>19</td>\n",
+       "      <td>14</td>\n",
+       "      <td>24</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>202423</td>\n",
+       "      <td>7</td>\n",
+       "      <td>14657</td>\n",
+       "      <td>11339</td>\n",
+       "      <td>17975</td>\n",
+       "      <td>22</td>\n",
+       "      <td>17</td>\n",
+       "      <td>27</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>202422</td>\n",
+       "      <td>7</td>\n",
+       "      <td>11628</td>\n",
+       "      <td>8361</td>\n",
+       "      <td>14895</td>\n",
+       "      <td>17</td>\n",
+       "      <td>12</td>\n",
+       "      <td>22</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>202421</td>\n",
+       "      <td>7</td>\n",
+       "      <td>9701</td>\n",
+       "      <td>6851</td>\n",
+       "      <td>12551</td>\n",
+       "      <td>15</td>\n",
+       "      <td>11</td>\n",
+       "      <td>19</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>202420</td>\n",
+       "      <td>7</td>\n",
+       "      <td>13661</td>\n",
+       "      <td>10209</td>\n",
+       "      <td>17113</td>\n",
+       "      <td>20</td>\n",
+       "      <td>15</td>\n",
+       "      <td>25</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>202419</td>\n",
+       "      <td>7</td>\n",
+       "      <td>10083</td>\n",
+       "      <td>6413</td>\n",
+       "      <td>13753</td>\n",
+       "      <td>15</td>\n",
+       "      <td>9</td>\n",
+       "      <td>21</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>1744</th>\n",
+       "      <td>199126</td>\n",
+       "      <td>7</td>\n",
+       "      <td>17608</td>\n",
+       "      <td>11304</td>\n",
+       "      <td>23912</td>\n",
+       "      <td>31</td>\n",
+       "      <td>20</td>\n",
+       "      <td>42</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1745</th>\n",
+       "      <td>199125</td>\n",
+       "      <td>7</td>\n",
+       "      <td>16169</td>\n",
+       "      <td>10700</td>\n",
+       "      <td>21638</td>\n",
+       "      <td>28</td>\n",
+       "      <td>18</td>\n",
+       "      <td>38</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1746</th>\n",
+       "      <td>199124</td>\n",
+       "      <td>7</td>\n",
+       "      <td>16171</td>\n",
+       "      <td>10071</td>\n",
+       "      <td>22271</td>\n",
+       "      <td>28</td>\n",
+       "      <td>17</td>\n",
+       "      <td>39</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1747</th>\n",
+       "      <td>199123</td>\n",
+       "      <td>7</td>\n",
+       "      <td>11947</td>\n",
+       "      <td>7671</td>\n",
+       "      <td>16223</td>\n",
+       "      <td>21</td>\n",
+       "      <td>13</td>\n",
+       "      <td>29</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1748</th>\n",
+       "      <td>199122</td>\n",
+       "      <td>7</td>\n",
+       "      <td>15452</td>\n",
+       "      <td>9953</td>\n",
+       "      <td>20951</td>\n",
+       "      <td>27</td>\n",
+       "      <td>17</td>\n",
+       "      <td>37</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1749</th>\n",
+       "      <td>199121</td>\n",
+       "      <td>7</td>\n",
+       "      <td>14903</td>\n",
+       "      <td>8975</td>\n",
+       "      <td>20831</td>\n",
+       "      <td>26</td>\n",
+       "      <td>16</td>\n",
+       "      <td>36</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1750</th>\n",
+       "      <td>199120</td>\n",
+       "      <td>7</td>\n",
+       "      <td>19053</td>\n",
+       "      <td>12742</td>\n",
+       "      <td>25364</td>\n",
+       "      <td>34</td>\n",
+       "      <td>23</td>\n",
+       "      <td>45</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1751</th>\n",
+       "      <td>199119</td>\n",
+       "      <td>7</td>\n",
+       "      <td>16739</td>\n",
+       "      <td>11246</td>\n",
+       "      <td>22232</td>\n",
+       "      <td>29</td>\n",
+       "      <td>19</td>\n",
+       "      <td>39</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1752</th>\n",
+       "      <td>199118</td>\n",
+       "      <td>7</td>\n",
+       "      <td>21385</td>\n",
+       "      <td>13882</td>\n",
+       "      <td>28888</td>\n",
+       "      <td>38</td>\n",
+       "      <td>25</td>\n",
+       "      <td>51</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1753</th>\n",
+       "      <td>199117</td>\n",
+       "      <td>7</td>\n",
+       "      <td>13462</td>\n",
+       "      <td>8877</td>\n",
+       "      <td>18047</td>\n",
+       "      <td>24</td>\n",
+       "      <td>16</td>\n",
+       "      <td>32</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1754</th>\n",
+       "      <td>199116</td>\n",
+       "      <td>7</td>\n",
+       "      <td>14857</td>\n",
+       "      <td>10068</td>\n",
+       "      <td>19646</td>\n",
+       "      <td>26</td>\n",
+       "      <td>18</td>\n",
+       "      <td>34</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1755</th>\n",
+       "      <td>199115</td>\n",
+       "      <td>7</td>\n",
+       "      <td>13975</td>\n",
+       "      <td>9781</td>\n",
+       "      <td>18169</td>\n",
+       "      <td>25</td>\n",
+       "      <td>18</td>\n",
+       "      <td>32</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1756</th>\n",
+       "      <td>199114</td>\n",
+       "      <td>7</td>\n",
+       "      <td>12265</td>\n",
+       "      <td>7684</td>\n",
+       "      <td>16846</td>\n",
+       "      <td>22</td>\n",
+       "      <td>14</td>\n",
+       "      <td>30</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1757</th>\n",
+       "      <td>199113</td>\n",
+       "      <td>7</td>\n",
+       "      <td>9567</td>\n",
+       "      <td>6041</td>\n",
+       "      <td>13093</td>\n",
+       "      <td>17</td>\n",
+       "      <td>11</td>\n",
+       "      <td>23</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1758</th>\n",
+       "      <td>199112</td>\n",
+       "      <td>7</td>\n",
+       "      <td>10864</td>\n",
+       "      <td>7331</td>\n",
+       "      <td>14397</td>\n",
+       "      <td>19</td>\n",
+       "      <td>13</td>\n",
+       "      <td>25</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1759</th>\n",
+       "      <td>199111</td>\n",
+       "      <td>7</td>\n",
+       "      <td>15574</td>\n",
+       "      <td>11184</td>\n",
+       "      <td>19964</td>\n",
+       "      <td>27</td>\n",
+       "      <td>19</td>\n",
+       "      <td>35</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1760</th>\n",
+       "      <td>199110</td>\n",
+       "      <td>7</td>\n",
+       "      <td>16643</td>\n",
+       "      <td>11372</td>\n",
+       "      <td>21914</td>\n",
+       "      <td>29</td>\n",
+       "      <td>20</td>\n",
+       "      <td>38</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1761</th>\n",
+       "      <td>199109</td>\n",
+       "      <td>7</td>\n",
+       "      <td>13741</td>\n",
+       "      <td>8780</td>\n",
+       "      <td>18702</td>\n",
+       "      <td>24</td>\n",
+       "      <td>15</td>\n",
+       "      <td>33</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1762</th>\n",
+       "      <td>199108</td>\n",
+       "      <td>7</td>\n",
+       "      <td>13289</td>\n",
+       "      <td>8813</td>\n",
+       "      <td>17765</td>\n",
+       "      <td>23</td>\n",
+       "      <td>15</td>\n",
+       "      <td>31</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1763</th>\n",
+       "      <td>199107</td>\n",
+       "      <td>7</td>\n",
+       "      <td>12337</td>\n",
+       "      <td>8077</td>\n",
+       "      <td>16597</td>\n",
+       "      <td>22</td>\n",
+       "      <td>15</td>\n",
+       "      <td>29</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1764</th>\n",
+       "      <td>199106</td>\n",
+       "      <td>7</td>\n",
+       "      <td>10877</td>\n",
+       "      <td>7013</td>\n",
+       "      <td>14741</td>\n",
+       "      <td>19</td>\n",
+       "      <td>12</td>\n",
+       "      <td>26</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1765</th>\n",
+       "      <td>199105</td>\n",
+       "      <td>7</td>\n",
+       "      <td>10442</td>\n",
+       "      <td>6544</td>\n",
+       "      <td>14340</td>\n",
+       "      <td>18</td>\n",
+       "      <td>11</td>\n",
+       "      <td>25</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1766</th>\n",
+       "      <td>199104</td>\n",
+       "      <td>7</td>\n",
+       "      <td>7913</td>\n",
+       "      <td>4563</td>\n",
+       "      <td>11263</td>\n",
+       "      <td>14</td>\n",
+       "      <td>8</td>\n",
+       "      <td>20</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1767</th>\n",
+       "      <td>199103</td>\n",
+       "      <td>7</td>\n",
+       "      <td>15387</td>\n",
+       "      <td>10484</td>\n",
+       "      <td>20290</td>\n",
+       "      <td>27</td>\n",
+       "      <td>18</td>\n",
+       "      <td>36</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1768</th>\n",
+       "      <td>199102</td>\n",
+       "      <td>7</td>\n",
+       "      <td>16277</td>\n",
+       "      <td>11046</td>\n",
+       "      <td>21508</td>\n",
+       "      <td>29</td>\n",
+       "      <td>20</td>\n",
+       "      <td>38</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1769</th>\n",
+       "      <td>199101</td>\n",
+       "      <td>7</td>\n",
+       "      <td>15565</td>\n",
+       "      <td>10271</td>\n",
+       "      <td>20859</td>\n",
+       "      <td>27</td>\n",
+       "      <td>18</td>\n",
+       "      <td>36</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1770</th>\n",
+       "      <td>199052</td>\n",
+       "      <td>7</td>\n",
+       "      <td>19375</td>\n",
+       "      <td>13295</td>\n",
+       "      <td>25455</td>\n",
+       "      <td>34</td>\n",
+       "      <td>23</td>\n",
+       "      <td>45</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1771</th>\n",
+       "      <td>199051</td>\n",
+       "      <td>7</td>\n",
+       "      <td>19080</td>\n",
+       "      <td>13807</td>\n",
+       "      <td>24353</td>\n",
+       "      <td>34</td>\n",
+       "      <td>25</td>\n",
+       "      <td>43</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1772</th>\n",
+       "      <td>199050</td>\n",
+       "      <td>7</td>\n",
+       "      <td>11079</td>\n",
+       "      <td>6660</td>\n",
+       "      <td>15498</td>\n",
+       "      <td>20</td>\n",
+       "      <td>12</td>\n",
+       "      <td>28</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1773</th>\n",
+       "      <td>199049</td>\n",
+       "      <td>7</td>\n",
+       "      <td>1143</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2610</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>5</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1774 rows × 10 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        week  indicator    inc  inc_low  inc_up  inc100  inc100_low  \\\n",
+       "0     202448          7   4218     1335    7101       6           2   \n",
+       "1     202447          7   1965      738    3192       3           1   \n",
+       "2     202446          7   2260      863    3657       3           1   \n",
+       "3     202445          7   2713     1216    4210       4           2   \n",
+       "4     202444          7   2135      676    3594       3           1   \n",
+       "5     202443          7   2124      641    3607       3           1   \n",
+       "6     202442          7   2621     1246    3996       4           2   \n",
+       "7     202441          7   2035      381    3689       3           1   \n",
+       "8     202440          7   2125      725    3525       3           1   \n",
+       "9     202439          7   2898     1333    4463       4           2   \n",
+       "10    202438          7    751        0    1513       1           0   \n",
+       "11    202437          7    916       28    1804       1           0   \n",
+       "12    202436          7   2235      870    3600       3           1   \n",
+       "13    202435          7   1620      285    2955       2           0   \n",
+       "14    202434          7   2560      622    4498       4           1   \n",
+       "15    202433          7   1971      536    3406       3           1   \n",
+       "16    202432          7   4399     1944    6854       7           3   \n",
+       "17    202431          7   4500     2213    6787       7           4   \n",
+       "18    202430          7   7004     4278    9730      11           7   \n",
+       "19    202429          7   9270     6303   12237      14          10   \n",
+       "20    202428          7   9364     6498   12230      14          10   \n",
+       "21    202427          7  10247     7090   13404      15          10   \n",
+       "22    202426          7  14368    10399   18337      22          16   \n",
+       "23    202425          7  11174     8039   14309      17          12   \n",
+       "24    202424          7  12621     9357   15885      19          14   \n",
+       "25    202423          7  14657    11339   17975      22          17   \n",
+       "26    202422          7  11628     8361   14895      17          12   \n",
+       "27    202421          7   9701     6851   12551      15          11   \n",
+       "28    202420          7  13661    10209   17113      20          15   \n",
+       "29    202419          7  10083     6413   13753      15           9   \n",
+       "...      ...        ...    ...      ...     ...     ...         ...   \n",
+       "1744  199126          7  17608    11304   23912      31          20   \n",
+       "1745  199125          7  16169    10700   21638      28          18   \n",
+       "1746  199124          7  16171    10071   22271      28          17   \n",
+       "1747  199123          7  11947     7671   16223      21          13   \n",
+       "1748  199122          7  15452     9953   20951      27          17   \n",
+       "1749  199121          7  14903     8975   20831      26          16   \n",
+       "1750  199120          7  19053    12742   25364      34          23   \n",
+       "1751  199119          7  16739    11246   22232      29          19   \n",
+       "1752  199118          7  21385    13882   28888      38          25   \n",
+       "1753  199117          7  13462     8877   18047      24          16   \n",
+       "1754  199116          7  14857    10068   19646      26          18   \n",
+       "1755  199115          7  13975     9781   18169      25          18   \n",
+       "1756  199114          7  12265     7684   16846      22          14   \n",
+       "1757  199113          7   9567     6041   13093      17          11   \n",
+       "1758  199112          7  10864     7331   14397      19          13   \n",
+       "1759  199111          7  15574    11184   19964      27          19   \n",
+       "1760  199110          7  16643    11372   21914      29          20   \n",
+       "1761  199109          7  13741     8780   18702      24          15   \n",
+       "1762  199108          7  13289     8813   17765      23          15   \n",
+       "1763  199107          7  12337     8077   16597      22          15   \n",
+       "1764  199106          7  10877     7013   14741      19          12   \n",
+       "1765  199105          7  10442     6544   14340      18          11   \n",
+       "1766  199104          7   7913     4563   11263      14           8   \n",
+       "1767  199103          7  15387    10484   20290      27          18   \n",
+       "1768  199102          7  16277    11046   21508      29          20   \n",
+       "1769  199101          7  15565    10271   20859      27          18   \n",
+       "1770  199052          7  19375    13295   25455      34          23   \n",
+       "1771  199051          7  19080    13807   24353      34          25   \n",
+       "1772  199050          7  11079     6660   15498      20          12   \n",
+       "1773  199049          7   1143        0    2610       2           0   \n",
+       "\n",
+       "      inc100_up geo_insee geo_name  \n",
+       "0            10        FR   France  \n",
+       "1             5        FR   France  \n",
+       "2             5        FR   France  \n",
+       "3             6        FR   France  \n",
+       "4             5        FR   France  \n",
+       "5             5        FR   France  \n",
+       "6             6        FR   France  \n",
+       "7             5        FR   France  \n",
+       "8             5        FR   France  \n",
+       "9             6        FR   France  \n",
+       "10            2        FR   France  \n",
+       "11            2        FR   France  \n",
+       "12            5        FR   France  \n",
+       "13            4        FR   France  \n",
+       "14            7        FR   France  \n",
+       "15            5        FR   France  \n",
+       "16           11        FR   France  \n",
+       "17           10        FR   France  \n",
+       "18           15        FR   France  \n",
+       "19           18        FR   France  \n",
+       "20           18        FR   France  \n",
+       "21           20        FR   France  \n",
+       "22           28        FR   France  \n",
+       "23           22        FR   France  \n",
+       "24           24        FR   France  \n",
+       "25           27        FR   France  \n",
+       "26           22        FR   France  \n",
+       "27           19        FR   France  \n",
+       "28           25        FR   France  \n",
+       "29           21        FR   France  \n",
+       "...         ...       ...      ...  \n",
+       "1744         42        FR   France  \n",
+       "1745         38        FR   France  \n",
+       "1746         39        FR   France  \n",
+       "1747         29        FR   France  \n",
+       "1748         37        FR   France  \n",
+       "1749         36        FR   France  \n",
+       "1750         45        FR   France  \n",
+       "1751         39        FR   France  \n",
+       "1752         51        FR   France  \n",
+       "1753         32        FR   France  \n",
+       "1754         34        FR   France  \n",
+       "1755         32        FR   France  \n",
+       "1756         30        FR   France  \n",
+       "1757         23        FR   France  \n",
+       "1758         25        FR   France  \n",
+       "1759         35        FR   France  \n",
+       "1760         38        FR   France  \n",
+       "1761         33        FR   France  \n",
+       "1762         31        FR   France  \n",
+       "1763         29        FR   France  \n",
+       "1764         26        FR   France  \n",
+       "1765         25        FR   France  \n",
+       "1766         20        FR   France  \n",
+       "1767         36        FR   France  \n",
+       "1768         38        FR   France  \n",
+       "1769         36        FR   France  \n",
+       "1770         45        FR   France  \n",
+       "1771         43        FR   France  \n",
+       "1772         28        FR   France  \n",
+       "1773          5        FR   France  \n",
+       "\n",
+       "[1774 rows x 10 columns]"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data = pd.read_csv(data, skiprows=1)\n",
+    "raw_data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Y a-t-il des points manquants dans ce jeux de données ? Non."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "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",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "Empty DataFrame\n",
+       "Columns: [week, indicator, inc, inc_low, inc_up, inc100, inc100_low, inc100_up, geo_insee, geo_name]\n",
+       "Index: []"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data[raw_data.isnull().any(axis=1)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data = raw_data.dropna().copy()\n",
+    "data\n",
+    "\n",
+    "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 jeux 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": 23,
+   "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 le début de la période qui suit, la différence temporelle doit être zéro, ou au moins très faible. Nous laissons une \"marge d'erreur\" d'une seconde.\n",
+    "\n",
+    "Ceci s'avère tout à fait juste sauf pour deux périodes consécutives entre lesquelles il manque une semaine.\n",
+    "\n",
+    "Nous reconnaissons ces dates: c'est la semaine sans observations que nous avions supprimées !"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [],
+   "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": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fd782a878d0>"
+      ]
+     },
+     "execution_count": 25,
+     "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 printemps. Le creux des incidences se trouve en automne."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fd7803dc550>"
+      ]
+     },
+     "execution_count": 26,
+     "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\n",
+    "\n",
+    "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 septembre de l'année $N$ au\n",
+    "1er septembre 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 septembre de chaque année, nous utilisons le\n",
+    "premier jour de la semaine qui contient le 1er septembre.\n",
+    "\n",
+    "Comme l'incidence de syndrome grippal est très faible en automne, cette\n",
+    "modification ne risque pas de fausser nos conclusions.\n",
+    "\n",
+    "Encore un petit détail: les données commencent an decembre 1990, ce qui\n",
+    "rend la première année incomplète. Nous commençons donc l'analyse à partir du 1er septembre 1991."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "first_september_week = [pd.Period(pd.Timestamp(y, 9, 1), 'W')\n",
+    "                     for y in range(1991,\n",
+    "                                    sorted_data.index[-1].year)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "year = []\n",
+    "yearly_incidence = []\n",
+    "for week1, week2 in zip(first_september_week[:-1],\n",
+    "                        first_september_week[1:]):\n",
+    "    one_year = sorted_data['inc'][week1:week2-1]\n",
+    "    assert abs(len(one_year)-52) < 2, (print(len(one_year), week1, week2, \"\\n\", one_year))\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": 39,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fd7803538d0>"
+      ]
+     },
+     "execution_count": 39,
+     "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": 40,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2020    221186\n",
+       "2023    366227\n",
+       "2021    376290\n",
+       "2002    516689\n",
+       "2018    542312\n",
+       "2017    551041\n",
+       "1996    564901\n",
+       "2019    584066\n",
+       "2015    604382\n",
+       "2000    617597\n",
+       "2001    619041\n",
+       "2012    624573\n",
+       "2005    628464\n",
+       "2006    632833\n",
+       "2022    641397\n",
+       "2011    642368\n",
+       "1993    643387\n",
+       "1995    652478\n",
+       "1994    661409\n",
+       "1998    677775\n",
+       "1997    683434\n",
+       "2014    685769\n",
+       "2013    698332\n",
+       "2007    717352\n",
+       "2008    749478\n",
+       "1999    756456\n",
+       "2003    758363\n",
+       "2004    777388\n",
+       "2016    782114\n",
+       "2010    829911\n",
+       "1992    832939\n",
+       "2009    842373\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 40,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "yearly_incidence.sort_values()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Enfin, un histogramme montre bien que les épidémies fortes, qui touchent environ 10% de la population française, sont assez rares: il y en eu trois au cours des 35 dernières années."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fd78029e160>"
+      ]
+     },
+     "execution_count": 41,
+     "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": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
  "metadata": {
   "kernelspec": {
    "display_name": "Python 3",
@@ -16,10 +1455,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 2
 }
-
-- 
2.18.1