diff --git a/module3/exo2/exercice.ipynb b/module3/exo2/exercice.ipynb
index 0bbbe371b01e359e381e43239412d77bf53fb1fb..66ff6431288e183f9247c69b073c39eda33434ba 100644
--- a/module3/exo2/exercice.ipynb
+++ b/module3/exo2/exercice.ipynb
@@ -1,5 +1,1458 @@
 {
- "cells": [],
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Incidence de la varicelle"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "import os\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 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 1991 et se termine avec une semaine récente.\n",
+    "\n",
+    "Pour nous protéger contre une éventuelle disparition ou modification du serveur du Réseau Sentinelles, nous faisons une copie locale de ce jeux de données.\n",
+    "\n",
+    "Il est inutile et même risquée de télécharger les données à chaque exécution, car dans le cas d'une panne nous pourrions remplacer nos données par un fichier défectueux. Pour cette raison, nous téléchargeons les données seulement si la copie locale n'existe pas."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Data imported via the local file.\n"
+     ]
+    },
+    {
+     "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>Unnamed: 0</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>0</td>\n",
+       "      <td>202137</td>\n",
+       "      <td>7</td>\n",
+       "      <td>1984</td>\n",
+       "      <td>761</td>\n",
+       "      <td>3207</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>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>202136</td>\n",
+       "      <td>7</td>\n",
+       "      <td>3441</td>\n",
+       "      <td>1730</td>\n",
+       "      <td>5152</td>\n",
+       "      <td>5</td>\n",
+       "      <td>2</td>\n",
+       "      <td>8</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2</td>\n",
+       "      <td>202135</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2562</td>\n",
+       "      <td>1107</td>\n",
+       "      <td>4017</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2</td>\n",
+       "      <td>6</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3</td>\n",
+       "      <td>202134</td>\n",
+       "      <td>7</td>\n",
+       "      <td>1429</td>\n",
+       "      <td>378</td>\n",
+       "      <td>2480</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>4</th>\n",
+       "      <td>4</td>\n",
+       "      <td>202133</td>\n",
+       "      <td>7</td>\n",
+       "      <td>3829</td>\n",
+       "      <td>1830</td>\n",
+       "      <td>5828</td>\n",
+       "      <td>6</td>\n",
+       "      <td>3</td>\n",
+       "      <td>9</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>5</td>\n",
+       "      <td>202132</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4108</td>\n",
+       "      <td>1895</td>\n",
+       "      <td>6321</td>\n",
+       "      <td>6</td>\n",
+       "      <td>3</td>\n",
+       "      <td>9</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>6</td>\n",
+       "      <td>202131</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4793</td>\n",
+       "      <td>2301</td>\n",
+       "      <td>7285</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>7</th>\n",
+       "      <td>7</td>\n",
+       "      <td>202130</td>\n",
+       "      <td>7</td>\n",
+       "      <td>7190</td>\n",
+       "      <td>4191</td>\n",
+       "      <td>10189</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>8</th>\n",
+       "      <td>8</td>\n",
+       "      <td>202129</td>\n",
+       "      <td>7</td>\n",
+       "      <td>6800</td>\n",
+       "      <td>4109</td>\n",
+       "      <td>9491</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>9</th>\n",
+       "      <td>9</td>\n",
+       "      <td>202128</td>\n",
+       "      <td>7</td>\n",
+       "      <td>9734</td>\n",
+       "      <td>0</td>\n",
+       "      <td>21731</td>\n",
+       "      <td>15</td>\n",
+       "      <td>0</td>\n",
+       "      <td>33</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>10</td>\n",
+       "      <td>202127</td>\n",
+       "      <td>7</td>\n",
+       "      <td>9026</td>\n",
+       "      <td>4316</td>\n",
+       "      <td>13736</td>\n",
+       "      <td>14</td>\n",
+       "      <td>7</td>\n",
+       "      <td>21</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>11</td>\n",
+       "      <td>202126</td>\n",
+       "      <td>7</td>\n",
+       "      <td>7284</td>\n",
+       "      <td>4108</td>\n",
+       "      <td>10460</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>12</th>\n",
+       "      <td>12</td>\n",
+       "      <td>202125</td>\n",
+       "      <td>7</td>\n",
+       "      <td>9351</td>\n",
+       "      <td>6540</td>\n",
+       "      <td>12162</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>13</td>\n",
+       "      <td>202124</td>\n",
+       "      <td>7</td>\n",
+       "      <td>12034</td>\n",
+       "      <td>8937</td>\n",
+       "      <td>15131</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>14</th>\n",
+       "      <td>14</td>\n",
+       "      <td>202123</td>\n",
+       "      <td>7</td>\n",
+       "      <td>9116</td>\n",
+       "      <td>6420</td>\n",
+       "      <td>11812</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>15</th>\n",
+       "      <td>15</td>\n",
+       "      <td>202122</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4817</td>\n",
+       "      <td>2752</td>\n",
+       "      <td>6882</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>16</th>\n",
+       "      <td>16</td>\n",
+       "      <td>202121</td>\n",
+       "      <td>7</td>\n",
+       "      <td>6092</td>\n",
+       "      <td>3458</td>\n",
+       "      <td>8726</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>17</th>\n",
+       "      <td>17</td>\n",
+       "      <td>202120</td>\n",
+       "      <td>7</td>\n",
+       "      <td>7485</td>\n",
+       "      <td>4601</td>\n",
+       "      <td>10369</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>18</th>\n",
+       "      <td>18</td>\n",
+       "      <td>202119</td>\n",
+       "      <td>7</td>\n",
+       "      <td>6654</td>\n",
+       "      <td>4370</td>\n",
+       "      <td>8938</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>19</td>\n",
+       "      <td>202118</td>\n",
+       "      <td>7</td>\n",
+       "      <td>3912</td>\n",
+       "      <td>2110</td>\n",
+       "      <td>5714</td>\n",
+       "      <td>6</td>\n",
+       "      <td>3</td>\n",
+       "      <td>9</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>20</td>\n",
+       "      <td>202117</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4686</td>\n",
+       "      <td>2878</td>\n",
+       "      <td>6494</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>21</th>\n",
+       "      <td>21</td>\n",
+       "      <td>202116</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4780</td>\n",
+       "      <td>2891</td>\n",
+       "      <td>6669</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>22</th>\n",
+       "      <td>22</td>\n",
+       "      <td>202115</td>\n",
+       "      <td>7</td>\n",
+       "      <td>11215</td>\n",
+       "      <td>7627</td>\n",
+       "      <td>14803</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>23</th>\n",
+       "      <td>23</td>\n",
+       "      <td>202114</td>\n",
+       "      <td>7</td>\n",
+       "      <td>11197</td>\n",
+       "      <td>7994</td>\n",
+       "      <td>14400</td>\n",
+       "      <td>17</td>\n",
+       "      <td>12</td>\n",
+       "      <td>22</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>24</td>\n",
+       "      <td>202113</td>\n",
+       "      <td>7</td>\n",
+       "      <td>9714</td>\n",
+       "      <td>6289</td>\n",
+       "      <td>13139</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>25</th>\n",
+       "      <td>25</td>\n",
+       "      <td>202112</td>\n",
+       "      <td>7</td>\n",
+       "      <td>11520</td>\n",
+       "      <td>8415</td>\n",
+       "      <td>14625</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>26</th>\n",
+       "      <td>26</td>\n",
+       "      <td>202111</td>\n",
+       "      <td>7</td>\n",
+       "      <td>9386</td>\n",
+       "      <td>6678</td>\n",
+       "      <td>12094</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>27</th>\n",
+       "      <td>27</td>\n",
+       "      <td>202110</td>\n",
+       "      <td>7</td>\n",
+       "      <td>9056</td>\n",
+       "      <td>6452</td>\n",
+       "      <td>11660</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>28</th>\n",
+       "      <td>28</td>\n",
+       "      <td>202109</td>\n",
+       "      <td>7</td>\n",
+       "      <td>10988</td>\n",
+       "      <td>7938</td>\n",
+       "      <td>14038</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>29</th>\n",
+       "      <td>29</td>\n",
+       "      <td>202108</td>\n",
+       "      <td>7</td>\n",
+       "      <td>11281</td>\n",
+       "      <td>8361</td>\n",
+       "      <td>14201</td>\n",
+       "      <td>17</td>\n",
+       "      <td>13</td>\n",
+       "      <td>21</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1577</th>\n",
+       "      <td>1577</td>\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>1578</th>\n",
+       "      <td>1578</td>\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>1579</th>\n",
+       "      <td>1579</td>\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>1580</th>\n",
+       "      <td>1580</td>\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>1581</th>\n",
+       "      <td>1581</td>\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>1582</th>\n",
+       "      <td>1582</td>\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>1583</th>\n",
+       "      <td>1583</td>\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>1584</th>\n",
+       "      <td>1584</td>\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>1585</th>\n",
+       "      <td>1585</td>\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>1586</th>\n",
+       "      <td>1586</td>\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>1587</th>\n",
+       "      <td>1587</td>\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>1588</th>\n",
+       "      <td>1588</td>\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>1589</th>\n",
+       "      <td>1589</td>\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>1590</th>\n",
+       "      <td>1590</td>\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>1591</th>\n",
+       "      <td>1591</td>\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>1592</th>\n",
+       "      <td>1592</td>\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>1593</th>\n",
+       "      <td>1593</td>\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>1594</th>\n",
+       "      <td>1594</td>\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>1595</th>\n",
+       "      <td>1595</td>\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>1596</th>\n",
+       "      <td>1596</td>\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>1597</th>\n",
+       "      <td>1597</td>\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>1598</th>\n",
+       "      <td>1598</td>\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>1599</th>\n",
+       "      <td>1599</td>\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>1600</th>\n",
+       "      <td>1600</td>\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>1601</th>\n",
+       "      <td>1601</td>\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>1602</th>\n",
+       "      <td>1602</td>\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>1603</th>\n",
+       "      <td>1603</td>\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>1604</th>\n",
+       "      <td>1604</td>\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>1605</th>\n",
+       "      <td>1605</td>\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>1606</th>\n",
+       "      <td>1606</td>\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>1607 rows × 11 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      Unnamed: 0    week  indicator    inc  inc_low  inc_up  inc100  \\\n",
+       "0              0  202137          7   1984      761    3207       3   \n",
+       "1              1  202136          7   3441     1730    5152       5   \n",
+       "2              2  202135          7   2562     1107    4017       4   \n",
+       "3              3  202134          7   1429      378    2480       2   \n",
+       "4              4  202133          7   3829     1830    5828       6   \n",
+       "5              5  202132          7   4108     1895    6321       6   \n",
+       "6              6  202131          7   4793     2301    7285       7   \n",
+       "7              7  202130          7   7190     4191   10189      11   \n",
+       "8              8  202129          7   6800     4109    9491      10   \n",
+       "9              9  202128          7   9734        0   21731      15   \n",
+       "10            10  202127          7   9026     4316   13736      14   \n",
+       "11            11  202126          7   7284     4108   10460      11   \n",
+       "12            12  202125          7   9351     6540   12162      14   \n",
+       "13            13  202124          7  12034     8937   15131      18   \n",
+       "14            14  202123          7   9116     6420   11812      14   \n",
+       "15            15  202122          7   4817     2752    6882       7   \n",
+       "16            16  202121          7   6092     3458    8726       9   \n",
+       "17            17  202120          7   7485     4601   10369      11   \n",
+       "18            18  202119          7   6654     4370    8938      10   \n",
+       "19            19  202118          7   3912     2110    5714       6   \n",
+       "20            20  202117          7   4686     2878    6494       7   \n",
+       "21            21  202116          7   4780     2891    6669       7   \n",
+       "22            22  202115          7  11215     7627   14803      17   \n",
+       "23            23  202114          7  11197     7994   14400      17   \n",
+       "24            24  202113          7   9714     6289   13139      15   \n",
+       "25            25  202112          7  11520     8415   14625      17   \n",
+       "26            26  202111          7   9386     6678   12094      14   \n",
+       "27            27  202110          7   9056     6452   11660      14   \n",
+       "28            28  202109          7  10988     7938   14038      17   \n",
+       "29            29  202108          7  11281     8361   14201      17   \n",
+       "...          ...     ...        ...    ...      ...     ...     ...   \n",
+       "1577        1577  199126          7  17608    11304   23912      31   \n",
+       "1578        1578  199125          7  16169    10700   21638      28   \n",
+       "1579        1579  199124          7  16171    10071   22271      28   \n",
+       "1580        1580  199123          7  11947     7671   16223      21   \n",
+       "1581        1581  199122          7  15452     9953   20951      27   \n",
+       "1582        1582  199121          7  14903     8975   20831      26   \n",
+       "1583        1583  199120          7  19053    12742   25364      34   \n",
+       "1584        1584  199119          7  16739    11246   22232      29   \n",
+       "1585        1585  199118          7  21385    13882   28888      38   \n",
+       "1586        1586  199117          7  13462     8877   18047      24   \n",
+       "1587        1587  199116          7  14857    10068   19646      26   \n",
+       "1588        1588  199115          7  13975     9781   18169      25   \n",
+       "1589        1589  199114          7  12265     7684   16846      22   \n",
+       "1590        1590  199113          7   9567     6041   13093      17   \n",
+       "1591        1591  199112          7  10864     7331   14397      19   \n",
+       "1592        1592  199111          7  15574    11184   19964      27   \n",
+       "1593        1593  199110          7  16643    11372   21914      29   \n",
+       "1594        1594  199109          7  13741     8780   18702      24   \n",
+       "1595        1595  199108          7  13289     8813   17765      23   \n",
+       "1596        1596  199107          7  12337     8077   16597      22   \n",
+       "1597        1597  199106          7  10877     7013   14741      19   \n",
+       "1598        1598  199105          7  10442     6544   14340      18   \n",
+       "1599        1599  199104          7   7913     4563   11263      14   \n",
+       "1600        1600  199103          7  15387    10484   20290      27   \n",
+       "1601        1601  199102          7  16277    11046   21508      29   \n",
+       "1602        1602  199101          7  15565    10271   20859      27   \n",
+       "1603        1603  199052          7  19375    13295   25455      34   \n",
+       "1604        1604  199051          7  19080    13807   24353      34   \n",
+       "1605        1605  199050          7  11079     6660   15498      20   \n",
+       "1606        1606  199049          7   1143        0    2610       2   \n",
+       "\n",
+       "      inc100_low  inc100_up geo_insee geo_name  \n",
+       "0              1          5        FR   France  \n",
+       "1              2          8        FR   France  \n",
+       "2              2          6        FR   France  \n",
+       "3              0          4        FR   France  \n",
+       "4              3          9        FR   France  \n",
+       "5              3          9        FR   France  \n",
+       "6              3         11        FR   France  \n",
+       "7              6         16        FR   France  \n",
+       "8              6         14        FR   France  \n",
+       "9              0         33        FR   France  \n",
+       "10             7         21        FR   France  \n",
+       "11             6         16        FR   France  \n",
+       "12            10         18        FR   France  \n",
+       "13            13         23        FR   France  \n",
+       "14            10         18        FR   France  \n",
+       "15             4         10        FR   France  \n",
+       "16             5         13        FR   France  \n",
+       "17             7         15        FR   France  \n",
+       "18             7         13        FR   France  \n",
+       "19             3          9        FR   France  \n",
+       "20             4         10        FR   France  \n",
+       "21             4         10        FR   France  \n",
+       "22            12         22        FR   France  \n",
+       "23            12         22        FR   France  \n",
+       "24            10         20        FR   France  \n",
+       "25            12         22        FR   France  \n",
+       "26            10         18        FR   France  \n",
+       "27            10         18        FR   France  \n",
+       "28            12         22        FR   France  \n",
+       "29            13         21        FR   France  \n",
+       "...          ...        ...       ...      ...  \n",
+       "1577          20         42        FR   France  \n",
+       "1578          18         38        FR   France  \n",
+       "1579          17         39        FR   France  \n",
+       "1580          13         29        FR   France  \n",
+       "1581          17         37        FR   France  \n",
+       "1582          16         36        FR   France  \n",
+       "1583          23         45        FR   France  \n",
+       "1584          19         39        FR   France  \n",
+       "1585          25         51        FR   France  \n",
+       "1586          16         32        FR   France  \n",
+       "1587          18         34        FR   France  \n",
+       "1588          18         32        FR   France  \n",
+       "1589          14         30        FR   France  \n",
+       "1590          11         23        FR   France  \n",
+       "1591          13         25        FR   France  \n",
+       "1592          19         35        FR   France  \n",
+       "1593          20         38        FR   France  \n",
+       "1594          15         33        FR   France  \n",
+       "1595          15         31        FR   France  \n",
+       "1596          15         29        FR   France  \n",
+       "1597          12         26        FR   France  \n",
+       "1598          11         25        FR   France  \n",
+       "1599           8         20        FR   France  \n",
+       "1600          18         36        FR   France  \n",
+       "1601          20         38        FR   France  \n",
+       "1602          18         36        FR   France  \n",
+       "1603          23         45        FR   France  \n",
+       "1604          25         43        FR   France  \n",
+       "1605          12         28        FR   France  \n",
+       "1606           0          5        FR   France  \n",
+       "\n",
+       "[1607 rows x 11 columns]"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-7.csv\"\n",
+    "file_name = \"incidence-PAY-7.csv\"\n",
+    "\n",
+    "if os.path.isfile(file_name):\n",
+    "    raw_data = pd.read_csv(file_name)\n",
+    "    print(\"Data imported via the local file.\")\n",
+    "else:\n",
+    "    raw_data = pd.read_csv(data_url, skiprows=1)\n",
+    "    print(\"Data downloaded via the url.\")\n",
+    "    raw_data.to_csv(file_name)\n",
+    "    print(\"Data saved locally.\")\n",
+    "    \n",
+    "raw_data"
+   ]
+  },
+  {
+   "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)                                                       |"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Nous vérifions si il y a des point manquants dans ce jeux de données. Ce n'est pas le cas."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "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>Unnamed: 0</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: [Unnamed: 0, week, indicator, inc, inc_low, inc_up, inc100, inc100_low, inc100_up, geo_insee, geo_name]\n",
+       "Index: []"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data[raw_data.isnull().any(axis=1)]"
+   ]
+  },
+  {
+   "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": 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 = raw_data.copy()\n",
+    "data['period'] = [convert_week(yw) for yw in data['week']]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    " Il restent deux petites modifications à faire.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": 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\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. Aucune incohérence est détectée."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "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": [
+    " Nous affichons l'incidence en fonction du temps."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f71db0f8128>"
+      ]
+     },
+     "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'].plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Un zoom sur les dernières années montre des creux d'incidences vers septembre."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f71d8f5dda0>"
+      ]
+     },
+     "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:].plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Etude de l'incidence annuelle"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Etant donné que le pic de l'épidémie se situe en hiver, à cheval\n",
+    "entre deux années civiles, nous définissons la période de référence\n",
+    "entre deux minima de l'incidence, du 1er août de l'année N au\n",
+    "1er août de l'année N+1. 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.Comme l'incidence de syndrome grippal est très faible en été, cette\n",
+    "modification ne risque pas de fausser nos conclusions.Encore un petit détail: les données commencent an décembre 1990, ce qui rend la première année incomplète. Nous commençons donc l'analyse en 1991."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "first_september_week = [pd.Period(pd.Timestamp(y, 9, 1), 'W')\n",
+    "                     for y in range(1991,\n",
+    "                                    sorted_data.index[-1].year)]"
+   ]
+  },
+  {
+   "cell_type": "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.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": 25,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "year = []\n",
+    "yearly_incidence = []\n",
+    "for week1, week2 in zip(first_september_week[:-1],\n",
+    "                        first_september_week[1:]):\n",
+    "    one_year = sorted_data['inc'][week1:week2-1]\n",
+    "    assert abs(len(one_year)-52) < 2\n",
+    "    yearly_incidence.append(one_year.sum())\n",
+    "    year.append(week2.year)\n",
+    "yearly_incidence = pd.Series(data=yearly_incidence, index=year)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Voici les incidences annuelles."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f71d8ee0ac8>"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "yearly_incidence.plot(style='*')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "On affiche le incidences minimum et maximum.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Year: 2009 ,Incidence max: 842373\n",
+      "Year: 2020 ,Incidence min: 221186\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Year:\",yearly_incidence.idxmax(),\",Incidence max:\",yearly_incidence.max())\n",
+    "print(\"Year:\",yearly_incidence.idxmin(),\",Incidence min:\",yearly_incidence.min())"
+   ]
+  }
+ ],
  "metadata": {
   "kernelspec": {
    "display_name": "Python 3",
@@ -16,10 +1469,9 @@
    "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 0000000000000000000000000000000000000000..00d9c59d6789968a4ba721cc79fd0d7e11a2adef
--- /dev/null
+++ b/module3/exo2/incidence-PAY-7.csv
@@ -0,0 +1,1608 @@
+,week,indicator,inc,inc_low,inc_up,inc100,inc100_low,inc100_up,geo_insee,geo_name
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+24,202113,7,9714,6289,13139,15,10,20,FR,France
+25,202112,7,11520,8415,14625,17,12,22,FR,France
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+27,202110,7,9056,6452,11660,14,10,18,FR,France
+28,202109,7,10988,7938,14038,17,12,22,FR,France
+29,202108,7,11281,8361,14201,17,13,21,FR,France
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+35,202102,7,7795,5430,10160,12,8,16,FR,France
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+38,202052,7,12012,8285,15739,18,12,24,FR,France
+39,202051,7,10564,7574,13554,16,11,21,FR,France
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+41,202049,7,5026,3145,6907,8,5,11,FR,France
+42,202048,7,6683,4312,9054,10,6,14,FR,France
+43,202047,7,4999,2963,7035,8,5,11,FR,France
+44,202046,7,3752,1963,5541,6,3,9,FR,France
+45,202045,7,3696,2016,5376,6,3,9,FR,France
+46,202044,7,4391,2375,6407,7,4,10,FR,France
+47,202043,7,4376,2505,6247,7,4,10,FR,France
+48,202042,7,4000,1979,6021,6,3,9,FR,France
+49,202041,7,3961,2099,5823,6,3,9,FR,France
+50,202040,7,2078,675,3481,3,1,5,FR,France
+51,202039,7,1049,237,1861,2,1,3,FR,France
+52,202038,7,2251,781,3721,3,1,5,FR,France
+53,202037,7,1584,405,2763,2,0,4,FR,France
+54,202036,7,919,100,1738,1,0,2,FR,France
+55,202035,7,828,0,1694,1,0,2,FR,France
+56,202034,7,2272,371,4173,3,0,6,FR,France
+57,202033,7,1284,177,2391,2,0,4,FR,France
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+69,202021,7,602,36,1168,1,0,2,FR,France
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+71,202019,7,310,0,753,0,0,1,FR,France
+72,202018,7,849,98,1600,1,0,2,FR,France
+73,202017,7,272,0,658,0,0,1,FR,France
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+81,202009,7,13631,10544,16718,21,16,26,FR,France
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+83,202007,7,8959,6574,11344,14,10,18,FR,France
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+153,201841,7,2956,1207,4705,4,1,7,FR,France
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+155,201839,7,2584,870,4298,4,1,7,FR,France
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+191,201803,7,7972,5473,10471,12,8,16,FR,France
+192,201802,7,10976,7974,13978,17,12,22,FR,France
+193,201801,7,11471,8430,14512,17,12,22,FR,France
+194,201752,7,11120,7732,14508,17,12,22,FR,France
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+231,201715,7,16400,11762,21038,25,18,32,FR,France
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+233,201713,7,21702,16488,26916,33,25,41,FR,France
+234,201712,7,18534,14161,22907,28,21,35,FR,France
+235,201711,7,18361,12709,24013,28,19,37,FR,France
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+239,201707,7,10991,7538,14444,17,12,22,FR,France
+240,201706,7,9627,6502,12752,15,10,20,FR,France
+241,201705,7,8885,6064,11706,14,10,18,FR,France
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+286,201612,7,19129,14501,23757,29,22,36,FR,France
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