From 194c9e5c232ea7e081594d68cf374d5b04d8ab0c Mon Sep 17 00:00:00 2001
From: 7404ea6678ce6fbf3a726e36f2bf2079
 <7404ea6678ce6fbf3a726e36f2bf2079@app-learninglab.inria.fr>
Date: Mon, 23 Sep 2024 20:51:20 +0000
Subject: [PATCH] Begin exercise 2 of module 3 and add data_file

---
 module3/exo2/exercice.ipynb      | 1390 ++++++++++++++++++++++-
 module3/exo2/incidence-PAY-7.csv | 1765 ++++++++++++++++++++++++++++++
 2 files changed, 3152 insertions(+), 3 deletions(-)
 create mode 100644 module3/exo2/incidence-PAY-7.csv

diff --git a/module3/exo2/exercice.ipynb b/module3/exo2/exercice.ipynb
index 0bbbe37..8727049 100644
--- a/module3/exo2/exercice.ipynb
+++ b/module3/exo2/exercice.ipynb
@@ -1,5 +1,1390 @@
 {
- "cells": [],
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Analyse de l'incidence de la varicelle"
+   ]
+  },
+  {
+   "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"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Les données de l'incidence de la varicelle sont disponibles sur le 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 1990 et se termine avec une semaine récente."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data_url = \"https://www.sentiweb.fr/datasets/all/inc-7-PAY.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>202437</td>\n",
+       "      <td>7</td>\n",
+       "      <td>604</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1385</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>1</th>\n",
+       "      <td>202436</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2180</td>\n",
+       "      <td>835</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>2</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>3</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>4</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>5</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>6</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>7</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>8</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>9</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>10</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>11</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>12</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>13</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>14</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>15</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>16</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>17</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>18</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>19</th>\n",
+       "      <td>202418</td>\n",
+       "      <td>7</td>\n",
+       "      <td>13438</td>\n",
+       "      <td>9514</td>\n",
+       "      <td>17362</td>\n",
+       "      <td>20</td>\n",
+       "      <td>14</td>\n",
+       "      <td>26</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>202417</td>\n",
+       "      <td>7</td>\n",
+       "      <td>15303</td>\n",
+       "      <td>11219</td>\n",
+       "      <td>19387</td>\n",
+       "      <td>23</td>\n",
+       "      <td>17</td>\n",
+       "      <td>29</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>202416</td>\n",
+       "      <td>7</td>\n",
+       "      <td>18138</td>\n",
+       "      <td>13540</td>\n",
+       "      <td>22736</td>\n",
+       "      <td>27</td>\n",
+       "      <td>20</td>\n",
+       "      <td>34</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>202415</td>\n",
+       "      <td>7</td>\n",
+       "      <td>24929</td>\n",
+       "      <td>17315</td>\n",
+       "      <td>32543</td>\n",
+       "      <td>37</td>\n",
+       "      <td>26</td>\n",
+       "      <td>48</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>202414</td>\n",
+       "      <td>7</td>\n",
+       "      <td>16181</td>\n",
+       "      <td>12544</td>\n",
+       "      <td>19818</td>\n",
+       "      <td>24</td>\n",
+       "      <td>19</td>\n",
+       "      <td>29</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>202413</td>\n",
+       "      <td>7</td>\n",
+       "      <td>18322</td>\n",
+       "      <td>14206</td>\n",
+       "      <td>22438</td>\n",
+       "      <td>27</td>\n",
+       "      <td>21</td>\n",
+       "      <td>33</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>202412</td>\n",
+       "      <td>7</td>\n",
+       "      <td>12818</td>\n",
+       "      <td>9128</td>\n",
+       "      <td>16508</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>26</th>\n",
+       "      <td>202411</td>\n",
+       "      <td>7</td>\n",
+       "      <td>15973</td>\n",
+       "      <td>12400</td>\n",
+       "      <td>19546</td>\n",
+       "      <td>24</td>\n",
+       "      <td>19</td>\n",
+       "      <td>29</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>202410</td>\n",
+       "      <td>7</td>\n",
+       "      <td>14301</td>\n",
+       "      <td>10761</td>\n",
+       "      <td>17841</td>\n",
+       "      <td>21</td>\n",
+       "      <td>16</td>\n",
+       "      <td>26</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>202409</td>\n",
+       "      <td>7</td>\n",
+       "      <td>14337</td>\n",
+       "      <td>10871</td>\n",
+       "      <td>17803</td>\n",
+       "      <td>21</td>\n",
+       "      <td>16</td>\n",
+       "      <td>26</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>202408</td>\n",
+       "      <td>7</td>\n",
+       "      <td>15899</td>\n",
+       "      <td>11991</td>\n",
+       "      <td>19807</td>\n",
+       "      <td>24</td>\n",
+       "      <td>18</td>\n",
+       "      <td>30</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>1733</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>1734</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>1735</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>1736</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>1737</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>1738</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>1739</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>1740</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>1741</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>1742</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>1743</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>1744</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>1745</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>1746</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>1747</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>1748</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>1749</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>1750</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>1751</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>1752</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>1753</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>1754</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>1755</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>1756</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>1757</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>1758</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>1759</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>1760</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>1761</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>1762</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>1763 rows × 10 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        week  indicator    inc  inc_low  inc_up  inc100  inc100_low  \\\n",
+       "0     202437          7    604        0    1385       1           0   \n",
+       "1     202436          7   2180      835    3525       3           1   \n",
+       "2     202435          7   1620      285    2955       2           0   \n",
+       "3     202434          7   2560      622    4498       4           1   \n",
+       "4     202433          7   1971      536    3406       3           1   \n",
+       "5     202432          7   4399     1944    6854       7           3   \n",
+       "6     202431          7   4500     2213    6787       7           4   \n",
+       "7     202430          7   7004     4278    9730      11           7   \n",
+       "8     202429          7   9270     6303   12237      14          10   \n",
+       "9     202428          7   9364     6498   12230      14          10   \n",
+       "10    202427          7  10247     7090   13404      15          10   \n",
+       "11    202426          7  14368    10399   18337      22          16   \n",
+       "12    202425          7  11174     8039   14309      17          12   \n",
+       "13    202424          7  12621     9357   15885      19          14   \n",
+       "14    202423          7  14657    11339   17975      22          17   \n",
+       "15    202422          7  11628     8361   14895      17          12   \n",
+       "16    202421          7   9701     6851   12551      15          11   \n",
+       "17    202420          7  13661    10209   17113      20          15   \n",
+       "18    202419          7  10083     6413   13753      15           9   \n",
+       "19    202418          7  13438     9514   17362      20          14   \n",
+       "20    202417          7  15303    11219   19387      23          17   \n",
+       "21    202416          7  18138    13540   22736      27          20   \n",
+       "22    202415          7  24929    17315   32543      37          26   \n",
+       "23    202414          7  16181    12544   19818      24          19   \n",
+       "24    202413          7  18322    14206   22438      27          21   \n",
+       "25    202412          7  12818     9128   16508      19          13   \n",
+       "26    202411          7  15973    12400   19546      24          19   \n",
+       "27    202410          7  14301    10761   17841      21          16   \n",
+       "28    202409          7  14337    10871   17803      21          16   \n",
+       "29    202408          7  15899    11991   19807      24          18   \n",
+       "...      ...        ...    ...      ...     ...     ...         ...   \n",
+       "1733  199126          7  17608    11304   23912      31          20   \n",
+       "1734  199125          7  16169    10700   21638      28          18   \n",
+       "1735  199124          7  16171    10071   22271      28          17   \n",
+       "1736  199123          7  11947     7671   16223      21          13   \n",
+       "1737  199122          7  15452     9953   20951      27          17   \n",
+       "1738  199121          7  14903     8975   20831      26          16   \n",
+       "1739  199120          7  19053    12742   25364      34          23   \n",
+       "1740  199119          7  16739    11246   22232      29          19   \n",
+       "1741  199118          7  21385    13882   28888      38          25   \n",
+       "1742  199117          7  13462     8877   18047      24          16   \n",
+       "1743  199116          7  14857    10068   19646      26          18   \n",
+       "1744  199115          7  13975     9781   18169      25          18   \n",
+       "1745  199114          7  12265     7684   16846      22          14   \n",
+       "1746  199113          7   9567     6041   13093      17          11   \n",
+       "1747  199112          7  10864     7331   14397      19          13   \n",
+       "1748  199111          7  15574    11184   19964      27          19   \n",
+       "1749  199110          7  16643    11372   21914      29          20   \n",
+       "1750  199109          7  13741     8780   18702      24          15   \n",
+       "1751  199108          7  13289     8813   17765      23          15   \n",
+       "1752  199107          7  12337     8077   16597      22          15   \n",
+       "1753  199106          7  10877     7013   14741      19          12   \n",
+       "1754  199105          7  10442     6544   14340      18          11   \n",
+       "1755  199104          7   7913     4563   11263      14           8   \n",
+       "1756  199103          7  15387    10484   20290      27          18   \n",
+       "1757  199102          7  16277    11046   21508      29          20   \n",
+       "1758  199101          7  15565    10271   20859      27          18   \n",
+       "1759  199052          7  19375    13295   25455      34          23   \n",
+       "1760  199051          7  19080    13807   24353      34          25   \n",
+       "1761  199050          7  11079     6660   15498      20          12   \n",
+       "1762  199049          7   1143        0    2610       2           0   \n",
+       "\n",
+       "      inc100_up geo_insee geo_name  \n",
+       "0             2        FR   France  \n",
+       "1             5        FR   France  \n",
+       "2             4        FR   France  \n",
+       "3             7        FR   France  \n",
+       "4             5        FR   France  \n",
+       "5            11        FR   France  \n",
+       "6            10        FR   France  \n",
+       "7            15        FR   France  \n",
+       "8            18        FR   France  \n",
+       "9            18        FR   France  \n",
+       "10           20        FR   France  \n",
+       "11           28        FR   France  \n",
+       "12           22        FR   France  \n",
+       "13           24        FR   France  \n",
+       "14           27        FR   France  \n",
+       "15           22        FR   France  \n",
+       "16           19        FR   France  \n",
+       "17           25        FR   France  \n",
+       "18           21        FR   France  \n",
+       "19           26        FR   France  \n",
+       "20           29        FR   France  \n",
+       "21           34        FR   France  \n",
+       "22           48        FR   France  \n",
+       "23           29        FR   France  \n",
+       "24           33        FR   France  \n",
+       "25           25        FR   France  \n",
+       "26           29        FR   France  \n",
+       "27           26        FR   France  \n",
+       "28           26        FR   France  \n",
+       "29           30        FR   France  \n",
+       "...         ...       ...      ...  \n",
+       "1733         42        FR   France  \n",
+       "1734         38        FR   France  \n",
+       "1735         39        FR   France  \n",
+       "1736         29        FR   France  \n",
+       "1737         37        FR   France  \n",
+       "1738         36        FR   France  \n",
+       "1739         45        FR   France  \n",
+       "1740         39        FR   France  \n",
+       "1741         51        FR   France  \n",
+       "1742         32        FR   France  \n",
+       "1743         34        FR   France  \n",
+       "1744         32        FR   France  \n",
+       "1745         30        FR   France  \n",
+       "1746         23        FR   France  \n",
+       "1747         25        FR   France  \n",
+       "1748         35        FR   France  \n",
+       "1749         38        FR   France  \n",
+       "1750         33        FR   France  \n",
+       "1751         31        FR   France  \n",
+       "1752         29        FR   France  \n",
+       "1753         26        FR   France  \n",
+       "1754         25        FR   France  \n",
+       "1755         20        FR   France  \n",
+       "1756         36        FR   France  \n",
+       "1757         38        FR   France  \n",
+       "1758         36        FR   France  \n",
+       "1759         45        FR   France  \n",
+       "1760         43        FR   France  \n",
+       "1761         28        FR   France  \n",
+       "1762          5        FR   France  \n",
+       "\n",
+       "[1763 rows x 10 columns]"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from os import path as pth\n",
+    "import requests\n",
+    "# Si le fichier csv des données d'incidence existe en local\n",
+    "# il n'est pas nécessaire de le télécharger par l'URL\n",
+    "local_filename = \"incidence-PAY-7.csv\"\n",
+    "if pth.exists(local_filename):\n",
+    "  # Le fichier existe en local dans le dossier courant\n",
+    "  raw_data = pd.read_csv(local_filename, skiprows=1)\n",
+    "else:\n",
+    "  # le fichier de données n'existe pas en local,\n",
+    "  # nous allons télécharger les données et les écrire\n",
+    "  # dans un fichier en local\n",
+    "  # Téléchargement des données\n",
+    "  response = requests.get(data_url)\n",
+    "  # Ecriture des données téléchargées dans le fichier local\n",
+    "  with open(local_filename, \"wb\") as f:\n",
+    "    f.write(response.content)\n",
+    "  raw_data = pd.read_csv(local_filename, skiprows=1)\n",
+    "raw_data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Y a-t-il des points manquants dans ce jeux de données ?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "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": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data[raw_data.isnull().any(axis=1)]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Non, il n'y a pas de données manquantes dans ce jeux de données"
+   ]
+  },
+  {
+   "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": 8,
+   "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",
+    "raw_data['period'] = [convert_week(yw) for yw in raw_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": 19,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sorted_data = raw_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."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "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": [
+    "Les données sont cohérentes, nous traçons le graphe représentants ces dernières sur toute la durée disponible."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f155e596860>"
+      ]
+     },
+     "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": [
+    "sorted_data['inc'].plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Faisons un zoom sur une plus petite partie des données pour observer leur comportement de plus près sur une période par trop étendue."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f155c3f6cc0>"
+      ]
+     },
+     "execution_count": 15,
+     "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": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f155c3729e8>"
+      ]
+     },
+     "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": [
+    "sorted_data['inc'][-100:].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f155c322f28>"
+      ]
+     },
+     "execution_count": 17,
+     "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:-100].plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Etude de l'incidence annuelle"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "La période creuse pour la varicelle semble plus être située sur le mois de septembre (contrairement à l'incidence de la varicelle qui semblait avoir une période creuse au mois d'août).\n",
+    "\n",
+    "Pour la varicelle, le pic de l'épidémie se situe au printemps.\n",
+    "Cependant, son pic est bien moins marqué que celui de la grippe,\n",
+    "et son incidence s'étale largement entre deux années civiles.\n",
+    "En effet, la période creuse semble se trouver au mois de septembre.\n",
+    "Nous définissons donc la période de référence entre deux minima de l'incidence,\n",
+    "du 1er septembre de l'année $N$ au 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 été, cette\n",
+    "modification ne risque pas de fausser nos conclusions.\n",
+    "\n",
+    "Encore un petit détail: les données commencent an octobre 1990, ce qui\n",
+    "rend la première année incomplète. Nous commençons donc l'analyse en 1985."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
  "metadata": {
   "kernelspec": {
    "display_name": "Python 3",
@@ -16,10 +1401,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 2
 }
-
diff --git a/module3/exo2/incidence-PAY-7.csv b/module3/exo2/incidence-PAY-7.csv
new file mode 100644
index 0000000..40fab74
--- /dev/null
+++ b/module3/exo2/incidence-PAY-7.csv
@@ -0,0 +1,1765 @@
+# {"source":"r&#233;seau Sentinelles, INSERM, Sorbonne Universit&#233;, https:\/\/www.sentiweb.fr","meta":{"period":[199049,202437],"geo":["PAY",0],"geo_ref":"insee","indicator":"7","type":"all","conf_int":true,"compact":false,"age_group":false,"span":"all"},"date":"2024-09-18T17:05:00+02:00","bundle":"1726671888"}
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+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
-- 
2.18.1