diff --git a/module3/exo2/exercice.ipynb b/module3/exo2/exercice.ipynb
index 0bbbe371b01e359e381e43239412d77bf53fb1fb..95f8d37bfd49907f505a46831389ab61b09f76eb 100644
--- a/module3/exo2/exercice.ipynb
+++ b/module3/exo2/exercice.ipynb
@@ -1,5 +1,1433 @@
 {
- "cells": [],
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Incidence de la varicelle"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import pandas as pd\n",
+    "import isoweek\n",
+    "from pathlib import Path"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Les données de l'incidence de la varicelle 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 1990 et se termine avec une semaine récente.\n",
+    "\n",
+    "Les données sont téléchargées le fichier local CSV contenant les données n'est pas présent. Dans le cas contraire, une simple lecture du fichier CSV est réalisée."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "DATA_FILE_PATH = Path(\"./incidence_varicelle.csv\")\n",
+    "\n",
+    "if not DATA_FILE_PATH.exists():\n",
+    "    data_url = \"https://www.sentiweb.fr/datasets/all/inc-7-PAY.csv\"\n",
+    "    raw_data = pd.read_csv(data_url, skiprows=1)\n",
+    "    raw_data.to_csv(DATA_FILE_PATH)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "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>202624</td>\n",
+       "      <td>7</td>\n",
+       "      <td>9145</td>\n",
+       "      <td>5530</td>\n",
+       "      <td>12760</td>\n",
+       "      <td>14</td>\n",
+       "      <td>9</td>\n",
+       "      <td>19</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>202623</td>\n",
+       "      <td>7</td>\n",
+       "      <td>9642</td>\n",
+       "      <td>6825</td>\n",
+       "      <td>12459</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>2</th>\n",
+       "      <td>202622</td>\n",
+       "      <td>7</td>\n",
+       "      <td>12431</td>\n",
+       "      <td>8837</td>\n",
+       "      <td>16025</td>\n",
+       "      <td>18</td>\n",
+       "      <td>13</td>\n",
+       "      <td>23</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>202621</td>\n",
+       "      <td>7</td>\n",
+       "      <td>9372</td>\n",
+       "      <td>6524</td>\n",
+       "      <td>12220</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>4</th>\n",
+       "      <td>202620</td>\n",
+       "      <td>7</td>\n",
+       "      <td>7191</td>\n",
+       "      <td>4114</td>\n",
+       "      <td>10268</td>\n",
+       "      <td>11</td>\n",
+       "      <td>6</td>\n",
+       "      <td>16</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>202619</td>\n",
+       "      <td>7</td>\n",
+       "      <td>9608</td>\n",
+       "      <td>6293</td>\n",
+       "      <td>12923</td>\n",
+       "      <td>14</td>\n",
+       "      <td>9</td>\n",
+       "      <td>19</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>202618</td>\n",
+       "      <td>7</td>\n",
+       "      <td>8927</td>\n",
+       "      <td>5444</td>\n",
+       "      <td>12410</td>\n",
+       "      <td>13</td>\n",
+       "      <td>8</td>\n",
+       "      <td>18</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>202617</td>\n",
+       "      <td>7</td>\n",
+       "      <td>11063</td>\n",
+       "      <td>7549</td>\n",
+       "      <td>14577</td>\n",
+       "      <td>16</td>\n",
+       "      <td>11</td>\n",
+       "      <td>21</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>202616</td>\n",
+       "      <td>7</td>\n",
+       "      <td>12983</td>\n",
+       "      <td>9199</td>\n",
+       "      <td>16767</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>9</th>\n",
+       "      <td>202615</td>\n",
+       "      <td>7</td>\n",
+       "      <td>10309</td>\n",
+       "      <td>7243</td>\n",
+       "      <td>13375</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>10</th>\n",
+       "      <td>202614</td>\n",
+       "      <td>7</td>\n",
+       "      <td>9121</td>\n",
+       "      <td>6015</td>\n",
+       "      <td>12227</td>\n",
+       "      <td>14</td>\n",
+       "      <td>9</td>\n",
+       "      <td>19</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>202613</td>\n",
+       "      <td>7</td>\n",
+       "      <td>11395</td>\n",
+       "      <td>8060</td>\n",
+       "      <td>14730</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>12</th>\n",
+       "      <td>202612</td>\n",
+       "      <td>7</td>\n",
+       "      <td>9105</td>\n",
+       "      <td>6415</td>\n",
+       "      <td>11795</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>13</th>\n",
+       "      <td>202611</td>\n",
+       "      <td>7</td>\n",
+       "      <td>6263</td>\n",
+       "      <td>4119</td>\n",
+       "      <td>8407</td>\n",
+       "      <td>9</td>\n",
+       "      <td>6</td>\n",
+       "      <td>12</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>202610</td>\n",
+       "      <td>7</td>\n",
+       "      <td>8335</td>\n",
+       "      <td>5601</td>\n",
+       "      <td>11069</td>\n",
+       "      <td>12</td>\n",
+       "      <td>8</td>\n",
+       "      <td>16</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>202609</td>\n",
+       "      <td>7</td>\n",
+       "      <td>7675</td>\n",
+       "      <td>5300</td>\n",
+       "      <td>10050</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>16</th>\n",
+       "      <td>202608</td>\n",
+       "      <td>7</td>\n",
+       "      <td>9604</td>\n",
+       "      <td>6238</td>\n",
+       "      <td>12970</td>\n",
+       "      <td>14</td>\n",
+       "      <td>9</td>\n",
+       "      <td>19</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>202607</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4169</td>\n",
+       "      <td>2493</td>\n",
+       "      <td>5845</td>\n",
+       "      <td>6</td>\n",
+       "      <td>4</td>\n",
+       "      <td>8</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>202606</td>\n",
+       "      <td>7</td>\n",
+       "      <td>6912</td>\n",
+       "      <td>4557</td>\n",
+       "      <td>9267</td>\n",
+       "      <td>10</td>\n",
+       "      <td>7</td>\n",
+       "      <td>13</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>202605</td>\n",
+       "      <td>7</td>\n",
+       "      <td>7524</td>\n",
+       "      <td>5071</td>\n",
+       "      <td>9977</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>20</th>\n",
+       "      <td>202604</td>\n",
+       "      <td>7</td>\n",
+       "      <td>5822</td>\n",
+       "      <td>3831</td>\n",
+       "      <td>7813</td>\n",
+       "      <td>9</td>\n",
+       "      <td>6</td>\n",
+       "      <td>12</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>202603</td>\n",
+       "      <td>7</td>\n",
+       "      <td>3572</td>\n",
+       "      <td>1896</td>\n",
+       "      <td>5248</td>\n",
+       "      <td>5</td>\n",
+       "      <td>3</td>\n",
+       "      <td>7</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>202602</td>\n",
+       "      <td>7</td>\n",
+       "      <td>5764</td>\n",
+       "      <td>3629</td>\n",
+       "      <td>7899</td>\n",
+       "      <td>9</td>\n",
+       "      <td>6</td>\n",
+       "      <td>12</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>202601</td>\n",
+       "      <td>7</td>\n",
+       "      <td>11418</td>\n",
+       "      <td>7109</td>\n",
+       "      <td>15727</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>24</th>\n",
+       "      <td>202552</td>\n",
+       "      <td>7</td>\n",
+       "      <td>5461</td>\n",
+       "      <td>2313</td>\n",
+       "      <td>8609</td>\n",
+       "      <td>8</td>\n",
+       "      <td>3</td>\n",
+       "      <td>13</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>202551</td>\n",
+       "      <td>7</td>\n",
+       "      <td>7788</td>\n",
+       "      <td>5045</td>\n",
+       "      <td>10531</td>\n",
+       "      <td>12</td>\n",
+       "      <td>8</td>\n",
+       "      <td>16</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>202550</td>\n",
+       "      <td>7</td>\n",
+       "      <td>6847</td>\n",
+       "      <td>4038</td>\n",
+       "      <td>9656</td>\n",
+       "      <td>10</td>\n",
+       "      <td>6</td>\n",
+       "      <td>14</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>202549</td>\n",
+       "      <td>7</td>\n",
+       "      <td>6295</td>\n",
+       "      <td>3591</td>\n",
+       "      <td>8999</td>\n",
+       "      <td>9</td>\n",
+       "      <td>5</td>\n",
+       "      <td>13</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>202548</td>\n",
+       "      <td>7</td>\n",
+       "      <td>5147</td>\n",
+       "      <td>3260</td>\n",
+       "      <td>7034</td>\n",
+       "      <td>8</td>\n",
+       "      <td>5</td>\n",
+       "      <td>11</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>202547</td>\n",
+       "      <td>7</td>\n",
+       "      <td>5150</td>\n",
+       "      <td>3258</td>\n",
+       "      <td>7042</td>\n",
+       "      <td>8</td>\n",
+       "      <td>5</td>\n",
+       "      <td>11</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>1824</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>1825</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>1826</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>1827</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>1828</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>1829</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>1830</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>1831</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>1832</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>1833</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>1834</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>1835</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>1836</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>1837</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>1838</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>1839</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>1840</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>1841</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>1842</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>1843</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>1844</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>1845</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>1846</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>1847</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>1848</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>1849</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>1850</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>1851</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>1852</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>1853</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>1854 rows × 10 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        week  indicator    inc  inc_low  inc_up  inc100  inc100_low  \\\n",
+       "0     202624          7   9145     5530   12760      14           9   \n",
+       "1     202623          7   9642     6825   12459      14          10   \n",
+       "2     202622          7  12431     8837   16025      18          13   \n",
+       "3     202621          7   9372     6524   12220      14          10   \n",
+       "4     202620          7   7191     4114   10268      11           6   \n",
+       "5     202619          7   9608     6293   12923      14           9   \n",
+       "6     202618          7   8927     5444   12410      13           8   \n",
+       "7     202617          7  11063     7549   14577      16          11   \n",
+       "8     202616          7  12983     9199   16767      19          13   \n",
+       "9     202615          7  10309     7243   13375      15          10   \n",
+       "10    202614          7   9121     6015   12227      14           9   \n",
+       "11    202613          7  11395     8060   14730      17          12   \n",
+       "12    202612          7   9105     6415   11795      14          10   \n",
+       "13    202611          7   6263     4119    8407       9           6   \n",
+       "14    202610          7   8335     5601   11069      12           8   \n",
+       "15    202609          7   7675     5300   10050      11           7   \n",
+       "16    202608          7   9604     6238   12970      14           9   \n",
+       "17    202607          7   4169     2493    5845       6           4   \n",
+       "18    202606          7   6912     4557    9267      10           7   \n",
+       "19    202605          7   7524     5071    9977      11           7   \n",
+       "20    202604          7   5822     3831    7813       9           6   \n",
+       "21    202603          7   3572     1896    5248       5           3   \n",
+       "22    202602          7   5764     3629    7899       9           6   \n",
+       "23    202601          7  11418     7109   15727      17          11   \n",
+       "24    202552          7   5461     2313    8609       8           3   \n",
+       "25    202551          7   7788     5045   10531      12           8   \n",
+       "26    202550          7   6847     4038    9656      10           6   \n",
+       "27    202549          7   6295     3591    8999       9           5   \n",
+       "28    202548          7   5147     3260    7034       8           5   \n",
+       "29    202547          7   5150     3258    7042       8           5   \n",
+       "...      ...        ...    ...      ...     ...     ...         ...   \n",
+       "1824  199126          7  17608    11304   23912      31          20   \n",
+       "1825  199125          7  16169    10700   21638      28          18   \n",
+       "1826  199124          7  16171    10071   22271      28          17   \n",
+       "1827  199123          7  11947     7671   16223      21          13   \n",
+       "1828  199122          7  15452     9953   20951      27          17   \n",
+       "1829  199121          7  14903     8975   20831      26          16   \n",
+       "1830  199120          7  19053    12742   25364      34          23   \n",
+       "1831  199119          7  16739    11246   22232      29          19   \n",
+       "1832  199118          7  21385    13882   28888      38          25   \n",
+       "1833  199117          7  13462     8877   18047      24          16   \n",
+       "1834  199116          7  14857    10068   19646      26          18   \n",
+       "1835  199115          7  13975     9781   18169      25          18   \n",
+       "1836  199114          7  12265     7684   16846      22          14   \n",
+       "1837  199113          7   9567     6041   13093      17          11   \n",
+       "1838  199112          7  10864     7331   14397      19          13   \n",
+       "1839  199111          7  15574    11184   19964      27          19   \n",
+       "1840  199110          7  16643    11372   21914      29          20   \n",
+       "1841  199109          7  13741     8780   18702      24          15   \n",
+       "1842  199108          7  13289     8813   17765      23          15   \n",
+       "1843  199107          7  12337     8077   16597      22          15   \n",
+       "1844  199106          7  10877     7013   14741      19          12   \n",
+       "1845  199105          7  10442     6544   14340      18          11   \n",
+       "1846  199104          7   7913     4563   11263      14           8   \n",
+       "1847  199103          7  15387    10484   20290      27          18   \n",
+       "1848  199102          7  16277    11046   21508      29          20   \n",
+       "1849  199101          7  15565    10271   20859      27          18   \n",
+       "1850  199052          7  19375    13295   25455      34          23   \n",
+       "1851  199051          7  19080    13807   24353      34          25   \n",
+       "1852  199050          7  11079     6660   15498      20          12   \n",
+       "1853  199049          7   1143        0    2610       2           0   \n",
+       "\n",
+       "      inc100_up geo_insee geo_name  \n",
+       "0            19        FR   France  \n",
+       "1            18        FR   France  \n",
+       "2            23        FR   France  \n",
+       "3            18        FR   France  \n",
+       "4            16        FR   France  \n",
+       "5            19        FR   France  \n",
+       "6            18        FR   France  \n",
+       "7            21        FR   France  \n",
+       "8            25        FR   France  \n",
+       "9            20        FR   France  \n",
+       "10           19        FR   France  \n",
+       "11           22        FR   France  \n",
+       "12           18        FR   France  \n",
+       "13           12        FR   France  \n",
+       "14           16        FR   France  \n",
+       "15           15        FR   France  \n",
+       "16           19        FR   France  \n",
+       "17            8        FR   France  \n",
+       "18           13        FR   France  \n",
+       "19           15        FR   France  \n",
+       "20           12        FR   France  \n",
+       "21            7        FR   France  \n",
+       "22           12        FR   France  \n",
+       "23           23        FR   France  \n",
+       "24           13        FR   France  \n",
+       "25           16        FR   France  \n",
+       "26           14        FR   France  \n",
+       "27           13        FR   France  \n",
+       "28           11        FR   France  \n",
+       "29           11        FR   France  \n",
+       "...         ...       ...      ...  \n",
+       "1824         42        FR   France  \n",
+       "1825         38        FR   France  \n",
+       "1826         39        FR   France  \n",
+       "1827         29        FR   France  \n",
+       "1828         37        FR   France  \n",
+       "1829         36        FR   France  \n",
+       "1830         45        FR   France  \n",
+       "1831         39        FR   France  \n",
+       "1832         51        FR   France  \n",
+       "1833         32        FR   France  \n",
+       "1834         34        FR   France  \n",
+       "1835         32        FR   France  \n",
+       "1836         30        FR   France  \n",
+       "1837         23        FR   France  \n",
+       "1838         25        FR   France  \n",
+       "1839         35        FR   France  \n",
+       "1840         38        FR   France  \n",
+       "1841         33        FR   France  \n",
+       "1842         31        FR   France  \n",
+       "1843         29        FR   France  \n",
+       "1844         26        FR   France  \n",
+       "1845         25        FR   France  \n",
+       "1846         20        FR   France  \n",
+       "1847         36        FR   France  \n",
+       "1848         38        FR   France  \n",
+       "1849         36        FR   France  \n",
+       "1850         45        FR   France  \n",
+       "1851         43        FR   France  \n",
+       "1852         28        FR   France  \n",
+       "1853          5        FR   France  \n",
+       "\n",
+       "[1854 rows x 10 columns]"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data = pd.read_csv(data_url, encoding = 'iso-8859-1', skiprows=1)\n",
+    "raw_data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Y a-t-il des points manquants dans ce jeux de données ? Non aucune donnée manquante n'est constatée, nous faisons une copie au cas où à l'avenir des données seraient manquantes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "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": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data[raw_data.isnull().any(axis=1)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data = raw_data.dropna().copy()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Nos données utilisent une convention inhabituelle: le numéro de semaine est collé à l'année, donnant l'impression qu'il s'agit 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 semaine.  Il faut lui fournir les dates de début et de fin de semaine. Nous utilisons pour cela la bibliothèque `isoweek`.\n",
+    "\n",
+    "Comme la conversion des semaines est devenu assez complexe, nous écrivons une petite fonction Python pour cela. Ensuite, nous\n",
+    "l'appliquons à tous les points de nos donnés. Les résultats vont dans une nouvelle colonne 'period'."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def convert_week(year_and_week_int):\n",
+    "    year_and_week_str = str(year_and_week_int)\n",
+    "    year = int(year_and_week_str[:4])\n",
+    "    week = int(year_and_week_str[4:])\n",
+    "    w = isoweek.Week(year, week)\n",
+    "    return pd.Period(w.day(0), 'W')\n",
+    "\n",
+    "data['period'] = [convert_week(yw) for yw in data['week']]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Il restent deux petites modifications à faire.\n",
+    "\n",
+    "Premièrement, nous définissons les périodes d'observation 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 le sens chronologique."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "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",
+    "Aucune incohérence n'est constatée"
+   ]
+  },
+  {
+   "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": [
+    "Un premier regard sur les données !"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f8e32941240>"
+      ]
+     },
+     "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": [
+    " Un zoom sur les dernières années montre mieux la situation des pics en hiver avec un creux des incidences vers septembre"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f8e3065e940>"
+      ]
+     },
+     "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'][-600:].plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Etude de l'incidence annuelle"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Etant donné que le pic de l'épidémie se situe en hiver, à cheval entre deux années civiles, nous définissons la période de référence entre deux minima de l'incidence, 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 pas un nombre entier de semaines. Nous modifions donc un peu nos périodes de référence: à la place du 1er septembre de chaque année, nous utilisons le premier jour de la semaine qui contient le 1er septembre.\n",
+    "\n",
+    "Comme l'incidence de la varicelle est très faible en septembre, cette modification ne risque pas de fausser nos conclusions.\n",
+    "\n",
+    "Encore un petit détail: les données commencent an octobre 1990, ce qui rend la première année incomplète. Nous commençons donc l'analyse en 1991."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "first_sept_week = [pd.Period(pd.Timestamp(y, 9, 1), 'W')\n",
+    "                     for y in range(1991,\n",
+    "                                    sorted_data.index[-1].year)]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "En partant de cette liste des semaines qui contiennent un 1er septembre, nous obtenons nos intervalles d'environ un an comme les périodes entre deux semaines adjacentes dans cette liste. Nous calculons les sommes des incidences hebdomadaires pour toutes ces périodes.\n",
+    "\n",
+    "Nous vérifions également que ces périodes contiennent entre 51 et 52 semaines, pour nous protéger contre des éventuelles erreurs dans notre code."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "year = []\n",
+    "yearly_incidence = []\n",
+    "for week1, week2 in zip(first_sept_week[:-1],\n",
+    "                        first_sept_week[1:]):\n",
+    "    one_year = sorted_data['inc'][week1:week2-1]\n",
+    "    assert abs(len(one_year)-52) < 2\n",
+    "    yearly_incidence.append(one_year.sum())\n",
+    "    year.append(week2.year)\n",
+    "yearly_incidence = pd.Series(data=yearly_incidence, index=year)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f8e3059a4a8>"
+      ]
+     },
+     "execution_count": 20,
+     "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": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2025    217405\n",
+       "2020    221186\n",
+       "2023    366227\n",
+       "2021    376290\n",
+       "2024    479258\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": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "yearly_incidence.sort_values()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "L'histogramme montre que les épidémies fortes, qui touchent environ 1,2% de la population française sont rares."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f8e30635fd0>"
+      ]
+     },
+     "execution_count": 22,
+     "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)"
+   ]
+  }
+ ],
  "metadata": {
   "kernelspec": {
    "display_name": "Python 3",
@@ -16,10 +1444,9 @@
    "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_varicelle.csv b/module3/exo2/incidence_varicelle.csv
new file mode 100644
index 0000000000000000000000000000000000000000..72c46c2a831eb233ed1b3e9e0b3ac4db034510e9
--- /dev/null
+++ b/module3/exo2/incidence_varicelle.csv
@@ -0,0 +1,1855 @@
+,week,indicator,inc,inc_low,inc_up,inc100,inc100_low,inc100_up,geo_insee,geo_name
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+950,200813,7,20308,13107,27509,33,21,45,FR,France
+951,200812,7,22462,15587,29337,37,26,48,FR,France
+952,200811,7,20505,13958,27052,33,22,44,FR,France
+953,200810,7,18078,11784,24372,29,19,39,FR,France
+954,200809,7,20474,14073,26875,33,23,43,FR,France
+955,200808,7,21441,15042,27840,35,25,45,FR,France
+956,200807,7,17894,12348,23440,29,20,38,FR,France
+957,200806,7,16310,11091,21529,27,18,36,FR,France
+958,200805,7,16684,11106,22262,27,18,36,FR,France
+959,200804,7,20997,14662,27332,34,24,44,FR,France
+960,200803,7,19263,11093,27433,31,18,44,FR,France
+961,200802,7,20501,13032,27970,33,21,45,FR,France
+962,200801,7,20780,14093,27467,34,23,45,FR,France
+963,200752,7,18010,11329,24691,29,18,40,FR,France
+964,200751,7,20052,12509,27595,33,21,45,FR,France
+965,200750,7,19059,12513,25605,31,20,42,FR,France
+966,200749,7,18394,12805,23983,30,21,39,FR,France
+967,200748,7,10765,5871,15659,18,10,26,FR,France
+968,200747,7,10703,1791,19615,17,2,32,FR,France
+969,200746,7,12318,4207,20429,20,7,33,FR,France
+970,200745,7,12352,0,29660,20,0,48,FR,France
+971,200744,7,7897,3419,12375,13,6,20,FR,France
+972,200743,7,5788,2306,9270,9,3,15,FR,France
+973,200742,7,5993,2329,9657,10,4,16,FR,France
+974,200741,7,7130,0,17274,12,0,29,FR,France
+975,200740,7,8146,940,15352,13,1,25,FR,France
+976,200739,7,3916,500,7332,6,0,12,FR,France
+977,200738,7,2691,462,4920,4,0,8,FR,France
+978,200737,7,4100,1263,6937,7,2,12,FR,France
+979,200736,7,1580,0,3223,3,0,6,FR,France
+980,200735,7,3471,0,7162,6,0,12,FR,France
+981,200734,7,3333,0,6764,5,0,11,FR,France
+982,200733,7,3241,451,6031,5,0,10,FR,France
+983,200732,7,7321,2112,12530,12,4,20,FR,France
+984,200731,7,9932,3688,16176,16,6,26,FR,France
+985,200730,7,9879,3616,16142,16,6,26,FR,France
+986,200729,7,17227,7803,26651,28,13,43,FR,France
+987,200728,7,14874,7763,21985,24,12,36,FR,France
+988,200727,7,13500,7382,19618,22,12,32,FR,France
+989,200726,7,15454,9522,21386,25,15,35,FR,France
+990,200725,7,20567,13847,27287,34,23,45,FR,France
+991,200724,7,26470,18336,34604,43,30,56,FR,France
+992,200723,7,23443,15824,31062,38,26,50,FR,France
+993,200722,7,18811,11559,26063,31,19,43,FR,France
+994,200721,7,15325,9347,21303,25,15,35,FR,France
+995,200720,7,17507,11589,23425,29,19,39,FR,France
+996,200719,7,22692,15113,30271,37,25,49,FR,France
+997,200718,7,20630,13394,27866,34,22,46,FR,France
+998,200717,7,23755,14388,33122,39,24,54,FR,France
+999,200716,7,23388,16188,30588,38,26,50,FR,France
+1000,200715,7,25695,17711,33679,42,29,55,FR,France
+1001,200714,7,16974,9959,23989,28,17,39,FR,France
+1002,200713,7,24625,16598,32652,40,27,53,FR,France
+1003,200712,7,20303,11331,29275,33,18,48,FR,France
+1004,200711,7,33056,21724,44388,54,36,72,FR,France
+1005,200710,7,20775,12182,29368,34,20,48,FR,France
+1006,200709,7,18750,12252,25248,31,20,42,FR,France
+1007,200708,7,19458,12998,25918,32,21,43,FR,France
+1008,200707,7,20978,14822,27134,34,24,44,FR,France
+1009,200706,7,14466,9375,19557,24,16,32,FR,France
+1010,200705,7,15339,9771,20907,25,16,34,FR,France
+1011,200704,7,19661,13333,25989,32,22,42,FR,France
+1012,200703,7,16211,10323,22099,26,16,36,FR,France
+1013,200702,7,15631,10037,21225,25,16,34,FR,France
+1014,200701,7,16483,10582,22384,27,17,37,FR,France
+1015,200652,7,20472,13371,27573,34,22,46,FR,France
+1016,200651,7,20557,12905,28209,34,21,47,FR,France
+1017,200650,7,11364,6541,16187,19,11,27,FR,France
+1018,200649,7,12518,6273,18763,21,11,31,FR,France
+1019,200648,7,8028,2783,13273,13,4,22,FR,France
+1020,200647,7,6240,2268,10212,10,3,17,FR,France
+1021,200646,7,4953,1841,8065,8,3,13,FR,France
+1022,200645,7,4064,1178,6950,7,2,12,FR,France
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+1025,200642,7,2885,539,5231,5,1,9,FR,France
+1026,200641,7,4405,123,8687,7,0,14,FR,France
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+1033,200634,7,1149,0,2623,2,0,4,FR,France
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+1036,200631,7,6255,754,11756,10,1,19,FR,France
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+1038,200629,7,6227,2488,9966,10,4,16,FR,France
+1039,200628,7,13044,6388,19700,21,10,32,FR,France
+1040,200627,7,18263,9407,27119,30,15,45,FR,France
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+1044,200623,7,12338,7512,17164,20,12,28,FR,France
+1045,200622,7,12669,7540,17798,21,13,29,FR,France
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+1047,200620,7,10366,6001,14731,17,10,24,FR,France
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+1049,200618,7,11495,6482,16508,19,11,27,FR,France
+1050,200617,7,16230,9656,22804,27,16,38,FR,France
+1051,200616,7,17624,10886,24362,29,18,40,FR,France
+1052,200615,7,18171,11485,24857,30,19,41,FR,France
+1053,200614,7,19218,13041,25395,31,21,41,FR,France
+1054,200613,7,16805,11064,22546,28,19,37,FR,France
+1055,200612,7,17604,12029,23179,29,20,38,FR,France
+1056,200611,7,15789,10289,21289,26,17,35,FR,France
+1057,200610,7,16775,11238,22312,27,18,36,FR,France
+1058,200609,7,16734,11153,22315,27,18,36,FR,France
+1059,200608,7,16964,11317,22611,28,19,37,FR,France
+1060,200607,7,11878,7047,16709,19,11,27,FR,France
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+1062,200605,7,16029,10665,21393,26,17,35,FR,France
+1063,200604,7,11400,7136,15664,19,12,26,FR,France
+1064,200603,7,15577,10494,20660,26,18,34,FR,France
+1065,200602,7,10313,6274,14352,17,10,24,FR,France
+1066,200601,7,20058,13481,26635,33,22,44,FR,France
+1067,200552,7,16588,9246,23930,27,15,39,FR,France
+1068,200551,7,27150,14219,40081,45,24,66,FR,France
+1069,200550,7,14340,8527,20153,24,14,34,FR,France
+1070,200549,7,12056,6953,17159,20,12,28,FR,France
+1071,200548,7,15056,8846,21266,25,15,35,FR,France
+1072,200547,7,14805,7691,21919,24,12,36,FR,France
+1073,200546,7,8390,2583,14197,14,4,24,FR,France
+1074,200545,7,11513,3776,19250,19,6,32,FR,France
+1075,200544,7,10086,2788,17384,17,5,29,FR,France
+1076,200543,7,9316,2080,16552,15,3,27,FR,France
+1077,200542,7,8373,3760,12986,14,6,22,FR,France
+1078,200541,7,11587,6045,17129,19,10,28,FR,France
+1079,200540,7,12374,6622,18126,20,11,29,FR,France
+1080,200539,7,4450,1509,7391,7,2,12,FR,France
+1081,200538,7,2272,67,4477,4,0,8,FR,France
+1082,200537,7,1677,0,3664,3,0,6,FR,France
+1083,200536,7,3369,510,6228,6,1,11,FR,France
+1084,200535,7,3124,482,5766,5,1,9,FR,France
+1085,200534,7,6673,1394,11952,11,2,20,FR,France
+1086,200533,7,8588,1696,15480,14,3,25,FR,France
+1087,200532,7,7859,2362,13356,13,4,22,FR,France
+1088,200531,7,9570,3334,15806,16,6,26,FR,France
+1089,200530,7,6172,0,13912,10,0,23,FR,France
+1090,200529,7,12452,5092,19812,21,9,33,FR,France
+1091,200528,7,18277,5762,30792,30,9,51,FR,France
+1092,200527,7,17547,9967,25127,29,16,42,FR,France
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+1094,200525,7,14089,8408,19770,23,14,32,FR,France
+1095,200524,7,15632,9553,21711,26,16,36,FR,France
+1096,200523,7,20069,12360,27778,33,20,46,FR,France
+1097,200522,7,20392,9119,31665,34,15,53,FR,France
+1098,200521,7,13623,8254,18992,22,13,31,FR,France
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+1100,200519,7,12622,7407,17837,21,12,30,FR,France
+1101,200518,7,10630,5706,15554,18,10,26,FR,France
+1102,200517,7,14979,8429,21529,25,14,36,FR,France
+1103,200516,7,11520,6566,16474,19,11,27,FR,France
+1104,200515,7,9114,4530,13698,15,7,23,FR,France
+1105,200514,7,16876,10333,23419,28,17,39,FR,France
+1106,200513,7,12513,7324,17702,21,12,30,FR,France
+1107,200512,7,15395,9108,21682,25,15,35,FR,France
+1108,200511,7,12702,7588,17816,21,13,29,FR,France
+1109,200510,7,11279,6465,16093,19,11,27,FR,France
+1110,200509,7,13085,7767,18403,22,13,31,FR,France
+1111,200508,7,10359,6162,14556,17,10,24,FR,France
+1112,200507,7,18640,12932,24348,31,22,40,FR,France
+1113,200506,7,11814,7295,16333,20,13,27,FR,France
+1114,200505,7,15387,10293,20481,25,17,33,FR,France
+1115,200504,7,12525,7897,17153,21,13,29,FR,France
+1116,200503,7,15946,10225,21667,26,17,35,FR,France
+1117,200502,7,12669,7600,17738,21,13,29,FR,France
+1118,200501,7,14192,8841,19543,23,14,32,FR,France
+1119,200453,7,17869,11244,24494,30,19,41,FR,France
+1120,200452,7,16974,10864,23084,28,18,38,FR,France
+1121,200451,7,14890,9250,20530,25,16,34,FR,France
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+1123,200449,7,16219,8194,24244,27,14,40,FR,France
+1124,200448,7,7162,2532,11792,12,4,20,FR,France
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+1126,200446,7,6806,2939,10673,11,5,17,FR,France
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+1131,200441,7,5061,1296,8826,8,2,14,FR,France
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+1133,200439,7,5226,1044,9408,9,2,16,FR,France
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+1135,200437,7,4351,537,8165,7,1,13,FR,France
+1136,200436,7,5121,1260,8982,9,3,15,FR,France
+1137,200435,7,7279,2610,11948,12,4,20,FR,France
+1138,200434,7,6425,1962,10888,11,4,18,FR,France
+1139,200433,7,11183,5394,16972,19,9,29,FR,France
+1140,200432,7,15854,7918,23790,26,13,39,FR,France
+1141,200431,7,17793,5261,30325,30,9,51,FR,France
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+1143,200429,7,34645,23193,46097,58,39,77,FR,France
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+1145,200427,7,21322,8377,34267,35,13,57,FR,France
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+1148,200424,7,26142,17142,35142,43,28,58,FR,France
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+1150,200422,7,16119,9794,22444,27,16,38,FR,France
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+1158,200414,7,24610,16629,32591,41,28,54,FR,France
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+1167,200405,7,12869,7824,17914,21,13,29,FR,France
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+1169,200403,7,6442,3015,9869,11,5,17,FR,France
+1170,200402,7,11126,6305,15947,18,10,26,FR,France
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+1172,200352,7,4920,0,22288,8,0,37,FR,France
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+1174,200350,7,9805,5520,14090,16,9,23,FR,France
+1175,200349,7,11685,7721,15649,20,13,27,FR,France
+1176,200348,7,6201,3319,9083,10,5,15,FR,France
+1177,200347,7,4897,1842,7952,8,3,13,FR,France
+1178,200346,7,4596,1236,7956,8,2,14,FR,France
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+1180,200344,7,3469,894,6044,6,2,10,FR,France
+1181,200343,7,4671,1766,7576,8,3,13,FR,France
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+1183,200341,7,3179,427,5931,5,0,10,FR,France
+1184,200340,7,6983,2852,11114,12,5,19,FR,France
+1185,200339,7,952,0,2308,2,0,4,FR,France
+1186,200338,7,1628,0,3406,3,0,6,FR,France
+1187,200337,7,2995,0,6029,5,0,10,FR,France
+1188,200336,7,3595,0,7784,6,0,13,FR,France
+1189,200335,7,1340,0,4253,2,0,7,FR,France
+1190,200334,7,3842,0,10414,6,0,17,FR,France
+1191,200333,7,7269,0,18830,12,0,31,FR,France
+1192,200332,7,2908,0,6463,5,0,11,FR,France
+1193,200331,7,2053,0,4640,3,0,7,FR,France
+1194,200330,7,5106,259,9953,9,1,17,FR,France
+1195,200329,7,8195,0,21289,14,0,36,FR,France
+1196,200328,7,9002,3511,14493,15,6,24,FR,France
+1197,200327,7,4902,1397,8407,8,2,14,FR,France
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+1199,200325,7,8190,3460,12920,14,6,22,FR,France
+1200,200324,7,33803,13366,54240,56,22,90,FR,France
+1201,200323,7,14278,6733,21823,24,11,37,FR,France
+1202,200322,7,13397,7140,19654,22,12,32,FR,France
+1203,200321,7,12113,3506,20720,20,6,34,FR,France
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+1208,200316,7,20007,12091,27923,33,20,46,FR,France
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+1210,200314,7,19148,10594,27702,32,18,46,FR,France
+1211,200313,7,27087,16490,37684,45,27,63,FR,France
+1212,200312,7,24322,15256,33388,41,26,56,FR,France
+1213,200311,7,21652,12929,30375,36,21,51,FR,France
+1214,200310,7,29033,19506,38560,49,33,65,FR,France
+1215,200309,7,28198,17625,38771,47,29,65,FR,France
+1216,200308,7,36298,22548,50048,61,38,84,FR,France
+1217,200307,7,27050,14994,39106,45,25,65,FR,France
+1218,200306,7,25101,14828,35374,42,25,59,FR,France
+1219,200305,7,15588,7493,23683,26,12,40,FR,France
+1220,200304,7,17141,9713,24569,29,17,41,FR,France
+1221,200303,7,18329,11799,24859,31,20,42,FR,France
+1222,200302,7,18829,10035,27623,31,16,46,FR,France
+1223,200301,7,22582,11488,33676,38,19,57,FR,France
+1224,200252,7,20417,12258,28576,34,20,48,FR,France
+1225,200251,7,22444,14164,30724,38,24,52,FR,France
+1226,200250,7,10873,6406,15340,18,10,26,FR,France
+1227,200249,7,16468,2559,30377,28,5,51,FR,France
+1228,200248,7,10264,4123,16405,17,7,27,FR,France
+1229,200247,7,12129,4283,19975,20,7,33,FR,France
+1230,200246,7,5507,1186,9828,9,2,16,FR,France
+1231,200245,7,9335,4813,13857,16,8,24,FR,France
+1232,200244,7,9388,2462,16314,16,4,28,FR,France
+1233,200243,7,10756,4601,16911,18,8,28,FR,France
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