diff --git a/module3/exo2/exercice.ipynb b/module3/exo2/exercice.ipynb
index 0bbbe371b01e359e381e43239412d77bf53fb1fb..9cd1fc94c469cd8618289ba4a8094d1a7773228a 100644
--- a/module3/exo2/exercice.ipynb
+++ b/module3/exo2/exercice.ipynb
@@ -1,5 +1,1448 @@
 {
- "cells": [],
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import pandas as pd\n",
+    "import isoweek\n",
+    "import os\n",
+    "import urllib"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Téléchargement et traitement des données"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "On télécharge les données du [Réseau sentinelles](http://www.sentiweb.fr/datasets) sur la varicelle en France depuis 1991."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-7.csv\"\n",
+    "data_file = \"incidence-PAY-7.csv\"\n",
+    "\n",
+    "# Test if file exists locally, if not, download it\n",
+    "\n",
+    "if not os.path.exists(data_file):\n",
+    "    urllib.request.urlretrieve(data_url, data_file)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>indicator</th>\n",
+       "      <th>inc</th>\n",
+       "      <th>inc_low</th>\n",
+       "      <th>inc_up</th>\n",
+       "      <th>inc100</th>\n",
+       "      <th>inc100_low</th>\n",
+       "      <th>inc100_up</th>\n",
+       "      <th>geo_insee</th>\n",
+       "      <th>geo_name</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>202120</td>\n",
+       "      <td>7</td>\n",
+       "      <td>8071</td>\n",
+       "      <td>4426</td>\n",
+       "      <td>11716</td>\n",
+       "      <td>12</td>\n",
+       "      <td>6</td>\n",
+       "      <td>18</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>202119</td>\n",
+       "      <td>7</td>\n",
+       "      <td>6662</td>\n",
+       "      <td>4376</td>\n",
+       "      <td>8948</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>2</th>\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>3</th>\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>4</th>\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>5</th>\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>6</th>\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>7</th>\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>8</th>\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>9</th>\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>10</th>\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>11</th>\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>12</th>\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>13</th>\n",
+       "      <td>202107</td>\n",
+       "      <td>7</td>\n",
+       "      <td>13561</td>\n",
+       "      <td>10315</td>\n",
+       "      <td>16807</td>\n",
+       "      <td>21</td>\n",
+       "      <td>16</td>\n",
+       "      <td>26</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>202106</td>\n",
+       "      <td>7</td>\n",
+       "      <td>13401</td>\n",
+       "      <td>9810</td>\n",
+       "      <td>16992</td>\n",
+       "      <td>20</td>\n",
+       "      <td>15</td>\n",
+       "      <td>25</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>202105</td>\n",
+       "      <td>7</td>\n",
+       "      <td>12210</td>\n",
+       "      <td>8988</td>\n",
+       "      <td>15432</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>16</th>\n",
+       "      <td>202104</td>\n",
+       "      <td>7</td>\n",
+       "      <td>12026</td>\n",
+       "      <td>8826</td>\n",
+       "      <td>15226</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>17</th>\n",
+       "      <td>202103</td>\n",
+       "      <td>7</td>\n",
+       "      <td>8913</td>\n",
+       "      <td>6375</td>\n",
+       "      <td>11451</td>\n",
+       "      <td>13</td>\n",
+       "      <td>9</td>\n",
+       "      <td>17</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>202102</td>\n",
+       "      <td>7</td>\n",
+       "      <td>7795</td>\n",
+       "      <td>5430</td>\n",
+       "      <td>10160</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>19</th>\n",
+       "      <td>202101</td>\n",
+       "      <td>7</td>\n",
+       "      <td>10525</td>\n",
+       "      <td>7750</td>\n",
+       "      <td>13300</td>\n",
+       "      <td>16</td>\n",
+       "      <td>12</td>\n",
+       "      <td>20</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>202053</td>\n",
+       "      <td>7</td>\n",
+       "      <td>11978</td>\n",
+       "      <td>8406</td>\n",
+       "      <td>15550</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>21</th>\n",
+       "      <td>202052</td>\n",
+       "      <td>7</td>\n",
+       "      <td>12012</td>\n",
+       "      <td>8285</td>\n",
+       "      <td>15739</td>\n",
+       "      <td>18</td>\n",
+       "      <td>12</td>\n",
+       "      <td>24</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>202051</td>\n",
+       "      <td>7</td>\n",
+       "      <td>10564</td>\n",
+       "      <td>7574</td>\n",
+       "      <td>13554</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>23</th>\n",
+       "      <td>202050</td>\n",
+       "      <td>7</td>\n",
+       "      <td>7063</td>\n",
+       "      <td>4744</td>\n",
+       "      <td>9382</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>24</th>\n",
+       "      <td>202049</td>\n",
+       "      <td>7</td>\n",
+       "      <td>5026</td>\n",
+       "      <td>3145</td>\n",
+       "      <td>6907</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>25</th>\n",
+       "      <td>202048</td>\n",
+       "      <td>7</td>\n",
+       "      <td>6683</td>\n",
+       "      <td>4312</td>\n",
+       "      <td>9054</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>26</th>\n",
+       "      <td>202047</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4999</td>\n",
+       "      <td>2963</td>\n",
+       "      <td>7035</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>27</th>\n",
+       "      <td>202046</td>\n",
+       "      <td>7</td>\n",
+       "      <td>3752</td>\n",
+       "      <td>1963</td>\n",
+       "      <td>5541</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>28</th>\n",
+       "      <td>202045</td>\n",
+       "      <td>7</td>\n",
+       "      <td>3696</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>5376</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>29</th>\n",
+       "      <td>202044</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4391</td>\n",
+       "      <td>2375</td>\n",
+       "      <td>6407</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>...</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>1560</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>1561</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>1562</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>1563</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>1564</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>1565</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>1566</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>1567</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>1568</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>1569</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>1570</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>1571</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>1572</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>1573</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>1574</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>1575</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>1576</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>1577</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>1578</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>1579</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>1580</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>1581</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>1582</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>1583</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>1584</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>1585</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>1586</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>1587</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>1588</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>1589</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>1590 rows × 10 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        week  indicator    inc  inc_low  inc_up  inc100  inc100_low  \\\n",
+       "0     202120          7   8071     4426   11716      12           6   \n",
+       "1     202119          7   6662     4376    8948      10           7   \n",
+       "2     202118          7   3912     2110    5714       6           3   \n",
+       "3     202117          7   4686     2878    6494       7           4   \n",
+       "4     202116          7   4780     2891    6669       7           4   \n",
+       "5     202115          7  11215     7627   14803      17          12   \n",
+       "6     202114          7  11197     7994   14400      17          12   \n",
+       "7     202113          7   9714     6289   13139      15          10   \n",
+       "8     202112          7  11520     8415   14625      17          12   \n",
+       "9     202111          7   9386     6678   12094      14          10   \n",
+       "10    202110          7   9056     6452   11660      14          10   \n",
+       "11    202109          7  10988     7938   14038      17          12   \n",
+       "12    202108          7  11281     8361   14201      17          13   \n",
+       "13    202107          7  13561    10315   16807      21          16   \n",
+       "14    202106          7  13401     9810   16992      20          15   \n",
+       "15    202105          7  12210     8988   15432      18          13   \n",
+       "16    202104          7  12026     8826   15226      18          13   \n",
+       "17    202103          7   8913     6375   11451      13           9   \n",
+       "18    202102          7   7795     5430   10160      12           8   \n",
+       "19    202101          7  10525     7750   13300      16          12   \n",
+       "20    202053          7  11978     8406   15550      18          13   \n",
+       "21    202052          7  12012     8285   15739      18          12   \n",
+       "22    202051          7  10564     7574   13554      16          11   \n",
+       "23    202050          7   7063     4744    9382      11           7   \n",
+       "24    202049          7   5026     3145    6907       8           5   \n",
+       "25    202048          7   6683     4312    9054      10           6   \n",
+       "26    202047          7   4999     2963    7035       8           5   \n",
+       "27    202046          7   3752     1963    5541       6           3   \n",
+       "28    202045          7   3696     2016    5376       6           3   \n",
+       "29    202044          7   4391     2375    6407       7           4   \n",
+       "...      ...        ...    ...      ...     ...     ...         ...   \n",
+       "1560  199126          7  17608    11304   23912      31          20   \n",
+       "1561  199125          7  16169    10700   21638      28          18   \n",
+       "1562  199124          7  16171    10071   22271      28          17   \n",
+       "1563  199123          7  11947     7671   16223      21          13   \n",
+       "1564  199122          7  15452     9953   20951      27          17   \n",
+       "1565  199121          7  14903     8975   20831      26          16   \n",
+       "1566  199120          7  19053    12742   25364      34          23   \n",
+       "1567  199119          7  16739    11246   22232      29          19   \n",
+       "1568  199118          7  21385    13882   28888      38          25   \n",
+       "1569  199117          7  13462     8877   18047      24          16   \n",
+       "1570  199116          7  14857    10068   19646      26          18   \n",
+       "1571  199115          7  13975     9781   18169      25          18   \n",
+       "1572  199114          7  12265     7684   16846      22          14   \n",
+       "1573  199113          7   9567     6041   13093      17          11   \n",
+       "1574  199112          7  10864     7331   14397      19          13   \n",
+       "1575  199111          7  15574    11184   19964      27          19   \n",
+       "1576  199110          7  16643    11372   21914      29          20   \n",
+       "1577  199109          7  13741     8780   18702      24          15   \n",
+       "1578  199108          7  13289     8813   17765      23          15   \n",
+       "1579  199107          7  12337     8077   16597      22          15   \n",
+       "1580  199106          7  10877     7013   14741      19          12   \n",
+       "1581  199105          7  10442     6544   14340      18          11   \n",
+       "1582  199104          7   7913     4563   11263      14           8   \n",
+       "1583  199103          7  15387    10484   20290      27          18   \n",
+       "1584  199102          7  16277    11046   21508      29          20   \n",
+       "1585  199101          7  15565    10271   20859      27          18   \n",
+       "1586  199052          7  19375    13295   25455      34          23   \n",
+       "1587  199051          7  19080    13807   24353      34          25   \n",
+       "1588  199050          7  11079     6660   15498      20          12   \n",
+       "1589  199049          7   1143        0    2610       2           0   \n",
+       "\n",
+       "      inc100_up geo_insee geo_name  \n",
+       "0            18        FR   France  \n",
+       "1            13        FR   France  \n",
+       "2             9        FR   France  \n",
+       "3            10        FR   France  \n",
+       "4            10        FR   France  \n",
+       "5            22        FR   France  \n",
+       "6            22        FR   France  \n",
+       "7            20        FR   France  \n",
+       "8            22        FR   France  \n",
+       "9            18        FR   France  \n",
+       "10           18        FR   France  \n",
+       "11           22        FR   France  \n",
+       "12           21        FR   France  \n",
+       "13           26        FR   France  \n",
+       "14           25        FR   France  \n",
+       "15           23        FR   France  \n",
+       "16           23        FR   France  \n",
+       "17           17        FR   France  \n",
+       "18           16        FR   France  \n",
+       "19           20        FR   France  \n",
+       "20           23        FR   France  \n",
+       "21           24        FR   France  \n",
+       "22           21        FR   France  \n",
+       "23           15        FR   France  \n",
+       "24           11        FR   France  \n",
+       "25           14        FR   France  \n",
+       "26           11        FR   France  \n",
+       "27            9        FR   France  \n",
+       "28            9        FR   France  \n",
+       "29           10        FR   France  \n",
+       "...         ...       ...      ...  \n",
+       "1560         42        FR   France  \n",
+       "1561         38        FR   France  \n",
+       "1562         39        FR   France  \n",
+       "1563         29        FR   France  \n",
+       "1564         37        FR   France  \n",
+       "1565         36        FR   France  \n",
+       "1566         45        FR   France  \n",
+       "1567         39        FR   France  \n",
+       "1568         51        FR   France  \n",
+       "1569         32        FR   France  \n",
+       "1570         34        FR   France  \n",
+       "1571         32        FR   France  \n",
+       "1572         30        FR   France  \n",
+       "1573         23        FR   France  \n",
+       "1574         25        FR   France  \n",
+       "1575         35        FR   France  \n",
+       "1576         38        FR   France  \n",
+       "1577         33        FR   France  \n",
+       "1578         31        FR   France  \n",
+       "1579         29        FR   France  \n",
+       "1580         26        FR   France  \n",
+       "1581         25        FR   France  \n",
+       "1582         20        FR   France  \n",
+       "1583         36        FR   France  \n",
+       "1584         38        FR   France  \n",
+       "1585         36        FR   France  \n",
+       "1586         45        FR   France  \n",
+       "1587         43        FR   France  \n",
+       "1588         28        FR   France  \n",
+       "1589          5        FR   France  \n",
+       "\n",
+       "[1590 rows x 10 columns]"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data = pd.read_csv(data_file, skiprows=1)\n",
+    "raw_data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Données manquantes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>indicator</th>\n",
+       "      <th>inc</th>\n",
+       "      <th>inc_low</th>\n",
+       "      <th>inc_up</th>\n",
+       "      <th>inc100</th>\n",
+       "      <th>inc100_low</th>\n",
+       "      <th>inc100_up</th>\n",
+       "      <th>geo_insee</th>\n",
+       "      <th>geo_name</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "Empty DataFrame\n",
+       "Columns: [week, indicator, inc, inc_low, inc_up, inc100, inc100_low, inc100_up, geo_insee, geo_name]\n",
+       "Index: []"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data[raw_data.isnull().any(axis=1)]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Pas de données manquantes!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data = raw_data.copy()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Conversion des semaines"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def convert_week(year_and_week_int):\n",
+    "    year_and_week_str = str(year_and_week_int)\n",
+    "    year = int(year_and_week_str[:4])\n",
+    "    week = int(year_and_week_str[4:])\n",
+    "    w = isoweek.Week(year, week)\n",
+    "    return pd.Period(w.day(0), 'W')\n",
+    "\n",
+    "data['period'] = [convert_week(yw) for yw in data['week']]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Tri des données"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sorted_data = data.set_index('period').sort_index()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "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": [
+    "Pas de périodes de plus de une semaine!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f25e31a1f98>"
+      ]
+     },
+     "execution_count": 12,
+     "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": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f25e292fac8>"
+      ]
+     },
+     "execution_count": 13,
+     "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": [
+    "Les pics semblent être vers le début de l'année, alors que les creux plutôt vers la fin de l'été, mais l'évolution est très irrégulière"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Étude de l'incidence annuelle"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "On définit le 1er septembre comme le début de l'année, car il correspond à la période creuse."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "first_september_week = [pd.Period(pd.Timestamp(y, 9, 1), 'W')\n",
+    "                     for y in range(1991,\n",
+    "                                    sorted_data.index[-1].year)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[Period('1991-08-26/1991-09-01', 'W-SUN'),\n",
+       " Period('1992-08-31/1992-09-06', 'W-SUN'),\n",
+       " Period('1993-08-30/1993-09-05', 'W-SUN'),\n",
+       " Period('1994-08-29/1994-09-04', 'W-SUN'),\n",
+       " Period('1995-08-28/1995-09-03', 'W-SUN'),\n",
+       " Period('1996-08-26/1996-09-01', 'W-SUN'),\n",
+       " Period('1997-09-01/1997-09-07', 'W-SUN'),\n",
+       " Period('1998-08-31/1998-09-06', 'W-SUN'),\n",
+       " Period('1999-08-30/1999-09-05', 'W-SUN'),\n",
+       " Period('2000-08-28/2000-09-03', 'W-SUN'),\n",
+       " Period('2001-08-27/2001-09-02', 'W-SUN'),\n",
+       " Period('2002-08-26/2002-09-01', 'W-SUN'),\n",
+       " Period('2003-09-01/2003-09-07', 'W-SUN'),\n",
+       " Period('2004-08-30/2004-09-05', 'W-SUN'),\n",
+       " Period('2005-08-29/2005-09-04', 'W-SUN'),\n",
+       " Period('2006-08-28/2006-09-03', 'W-SUN'),\n",
+       " Period('2007-08-27/2007-09-02', 'W-SUN'),\n",
+       " Period('2008-09-01/2008-09-07', 'W-SUN'),\n",
+       " Period('2009-08-31/2009-09-06', 'W-SUN'),\n",
+       " Period('2010-08-30/2010-09-05', 'W-SUN'),\n",
+       " Period('2011-08-29/2011-09-04', 'W-SUN'),\n",
+       " Period('2012-08-27/2012-09-02', 'W-SUN'),\n",
+       " Period('2013-08-26/2013-09-01', 'W-SUN'),\n",
+       " Period('2014-09-01/2014-09-07', 'W-SUN'),\n",
+       " Period('2015-08-31/2015-09-06', 'W-SUN'),\n",
+       " Period('2016-08-29/2016-09-04', 'W-SUN'),\n",
+       " Period('2017-08-28/2017-09-03', 'W-SUN'),\n",
+       " Period('2018-08-27/2018-09-02', 'W-SUN'),\n",
+       " Period('2019-08-26/2019-09-01', 'W-SUN'),\n",
+       " Period('2020-08-31/2020-09-06', 'W-SUN')]"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "first_september_week"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "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": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f25e2db0518>"
+      ]
+     },
+     "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": [
+       "2020    221186\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",
+       "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": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f25e2701be0>"
+      ]
+     },
+     "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)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
  "metadata": {
   "kernelspec": {
    "display_name": "Python 3",
@@ -16,10 +1459,9 @@
    "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..c7356bb876ed05b25d622c69890a5abc2da6dd04
--- /dev/null
+++ b/module3/exo2/incidence-PAY-7.csv
@@ -0,0 +1,1592 @@
+# @source="réseau Sentinelles, INSERM, Sorbonne Université, http://www.sentiweb.fr", @meta={"period":[199049,202120],"geo":["PAY","1"],"geo_ref":"insee","indicator":"7","type":"all","conf_int":true,"compact":false}, @date=2021-06-01T00:58:51+02:00
+week,indicator,inc,inc_low,inc_up,inc100,inc100_low,inc100_up,geo_insee,geo_name
+202120,7,8071,4426,11716,12,6,18,FR,France
+202119,7,6662,4376,8948,10,7,13,FR,France
+202118,7,3912,2110,5714,6,3,9,FR,France
+202117,7,4686,2878,6494,7,4,10,FR,France
+202116,7,4780,2891,6669,7,4,10,FR,France
+202115,7,11215,7627,14803,17,12,22,FR,France
+202114,7,11197,7994,14400,17,12,22,FR,France
+202113,7,9714,6289,13139,15,10,20,FR,France
+202112,7,11520,8415,14625,17,12,22,FR,France
+202111,7,9386,6678,12094,14,10,18,FR,France
+202110,7,9056,6452,11660,14,10,18,FR,France
+202109,7,10988,7938,14038,17,12,22,FR,France
+202108,7,11281,8361,14201,17,13,21,FR,France
+202107,7,13561,10315,16807,21,16,26,FR,France
+202106,7,13401,9810,16992,20,15,25,FR,France
+202105,7,12210,8988,15432,18,13,23,FR,France
+202104,7,12026,8826,15226,18,13,23,FR,France
+202103,7,8913,6375,11451,13,9,17,FR,France
+202102,7,7795,5430,10160,12,8,16,FR,France
+202101,7,10525,7750,13300,16,12,20,FR,France
+202053,7,11978,8406,15550,18,13,23,FR,France
+202052,7,12012,8285,15739,18,12,24,FR,France
+202051,7,10564,7574,13554,16,11,21,FR,France
+202050,7,7063,4744,9382,11,7,15,FR,France
+202049,7,5026,3145,6907,8,5,11,FR,France
+202048,7,6683,4312,9054,10,6,14,FR,France
+202047,7,4999,2963,7035,8,5,11,FR,France
+202046,7,3752,1963,5541,6,3,9,FR,France
+202045,7,3696,2016,5376,6,3,9,FR,France
+202044,7,4391,2375,6407,7,4,10,FR,France
+202043,7,4376,2505,6247,7,4,10,FR,France
+202042,7,4000,1979,6021,6,3,9,FR,France
+202041,7,3961,2099,5823,6,3,9,FR,France
+202040,7,2078,675,3481,3,1,5,FR,France
+202039,7,1049,237,1861,2,1,3,FR,France
+202038,7,2251,781,3721,3,1,5,FR,France
+202037,7,1584,405,2763,2,0,4,FR,France
+202036,7,919,100,1738,1,0,2,FR,France
+202035,7,828,0,1694,1,0,2,FR,France
+202034,7,2272,371,4173,3,0,6,FR,France
+202033,7,1284,177,2391,2,0,4,FR,France
+202032,7,2650,689,4611,4,1,7,FR,France
+202031,7,1303,100,2506,2,0,4,FR,France
+202030,7,1385,75,2695,2,0,4,FR,France
+202029,7,841,10,1672,1,0,2,FR,France
+202028,7,728,0,1515,1,0,2,FR,France
+202027,7,986,149,1823,1,0,2,FR,France
+202026,7,694,0,1454,1,0,2,FR,France
+202025,7,228,0,597,0,0,1,FR,France
+202024,7,388,0,959,1,0,2,FR,France
+202023,7,558,1,1115,1,0,2,FR,France
+202022,7,277,0,633,0,0,1,FR,France
+202021,7,602,36,1168,1,0,2,FR,France
+202020,7,824,20,1628,1,0,2,FR,France
+202019,7,310,0,753,0,0,1,FR,France
+202018,7,849,98,1600,1,0,2,FR,France
+202017,7,272,0,658,0,0,1,FR,France
+202016,7,758,78,1438,1,0,2,FR,France
+202015,7,1918,675,3161,3,1,5,FR,France
+202014,7,3879,2227,5531,6,3,9,FR,France
+202013,7,7326,5236,9416,11,8,14,FR,France
+202012,7,8123,5790,10456,12,8,16,FR,France
+202011,7,10198,7568,12828,15,11,19,FR,France
+202010,7,9011,6691,11331,14,10,18,FR,France
+202009,7,13631,10544,16718,21,16,26,FR,France
+202008,7,10424,7708,13140,16,12,20,FR,France
+202007,7,8959,6574,11344,14,10,18,FR,France
+202006,7,9264,6925,11603,14,10,18,FR,France
+202005,7,8505,6314,10696,13,10,16,FR,France
+202004,7,7991,5831,10151,12,9,15,FR,France
+202003,7,5968,4100,7836,9,6,12,FR,France
+202002,7,6534,4530,8538,10,7,13,FR,France
+202001,7,9835,7019,12651,15,11,19,FR,France
+201952,7,7941,5246,10636,12,8,16,FR,France
+201951,7,5823,3675,7971,9,6,12,FR,France
+201950,7,6424,4276,8572,10,7,13,FR,France
+201949,7,6621,4540,8702,10,7,13,FR,France
+201948,7,5542,3383,7701,8,5,11,FR,France
+201947,7,7536,5058,10014,11,7,15,FR,France
+201946,7,2638,1316,3960,4,2,6,FR,France
+201945,7,4492,2615,6369,7,4,10,FR,France
+201944,7,5728,3627,7829,9,6,12,FR,France
+201943,7,4834,2751,6917,7,4,10,FR,France
+201942,7,6279,3989,8569,10,7,13,FR,France
+201941,7,4130,2030,6230,6,3,9,FR,France
+201940,7,4211,2218,6204,6,3,9,FR,France
+201939,7,3137,1310,4964,5,2,8,FR,France
+201938,7,3078,1416,4740,5,2,8,FR,France
+201937,7,970,162,1778,1,0,2,FR,France
+201936,7,1277,263,2291,2,0,4,FR,France
+201935,7,922,0,1857,1,0,2,FR,France
+201934,7,1997,605,3389,3,1,5,FR,France
+201933,7,3279,1103,5455,5,2,8,FR,France
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