diff --git a/module3/exo2/analyse-varicelle.ipynb b/module3/exo2/analyse-varicelle.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..51747322a3e4a2ff242647404671560bfa5b56d9
--- /dev/null
+++ b/module3/exo2/analyse-varicelle.ipynb
@@ -0,0 +1,1355 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Incidence de la Varicelle"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import pandas as pd\n",
+    "import isoweek"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-7.csv\"\n",
+    "data_file = \"inc-7-PAY.csv\"\n",
+    "\n",
+    "import os\n",
+    "import urllib.request\n",
+    "if not os.path.exists(data_file):\n",
+    "    urllib.request.urlretrieve(data_url, data_file)"
+   ]
+  },
+  {
+   "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",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>202444</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2354</td>\n",
+       "      <td>489</td>\n",
+       "      <td>4219</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1</td>\n",
+       "      <td>7</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>202443</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2130</td>\n",
+       "      <td>625</td>\n",
+       "      <td>3635</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>202442</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2621</td>\n",
+       "      <td>1246</td>\n",
+       "      <td>3996</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2</td>\n",
+       "      <td>6</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>202441</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2035</td>\n",
+       "      <td>381</td>\n",
+       "      <td>3689</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>202440</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2125</td>\n",
+       "      <td>725</td>\n",
+       "      <td>3525</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>202439</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2898</td>\n",
+       "      <td>1333</td>\n",
+       "      <td>4463</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2</td>\n",
+       "      <td>6</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>202438</td>\n",
+       "      <td>7</td>\n",
+       "      <td>751</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1513</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>202437</td>\n",
+       "      <td>7</td>\n",
+       "      <td>916</td>\n",
+       "      <td>28</td>\n",
+       "      <td>1804</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>202436</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2235</td>\n",
+       "      <td>870</td>\n",
+       "      <td>3600</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>202435</td>\n",
+       "      <td>7</td>\n",
+       "      <td>1620</td>\n",
+       "      <td>285</td>\n",
+       "      <td>2955</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>202434</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2560</td>\n",
+       "      <td>622</td>\n",
+       "      <td>4498</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1</td>\n",
+       "      <td>7</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>202433</td>\n",
+       "      <td>7</td>\n",
+       "      <td>1971</td>\n",
+       "      <td>536</td>\n",
+       "      <td>3406</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>202432</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4399</td>\n",
+       "      <td>1944</td>\n",
+       "      <td>6854</td>\n",
+       "      <td>7</td>\n",
+       "      <td>3</td>\n",
+       "      <td>11</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>202431</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4500</td>\n",
+       "      <td>2213</td>\n",
+       "      <td>6787</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4</td>\n",
+       "      <td>10</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>202430</td>\n",
+       "      <td>7</td>\n",
+       "      <td>7004</td>\n",
+       "      <td>4278</td>\n",
+       "      <td>9730</td>\n",
+       "      <td>11</td>\n",
+       "      <td>7</td>\n",
+       "      <td>15</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>202429</td>\n",
+       "      <td>7</td>\n",
+       "      <td>9270</td>\n",
+       "      <td>6303</td>\n",
+       "      <td>12237</td>\n",
+       "      <td>14</td>\n",
+       "      <td>10</td>\n",
+       "      <td>18</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>202428</td>\n",
+       "      <td>7</td>\n",
+       "      <td>9364</td>\n",
+       "      <td>6498</td>\n",
+       "      <td>12230</td>\n",
+       "      <td>14</td>\n",
+       "      <td>10</td>\n",
+       "      <td>18</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>202427</td>\n",
+       "      <td>7</td>\n",
+       "      <td>10247</td>\n",
+       "      <td>7090</td>\n",
+       "      <td>13404</td>\n",
+       "      <td>15</td>\n",
+       "      <td>10</td>\n",
+       "      <td>20</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>202426</td>\n",
+       "      <td>7</td>\n",
+       "      <td>14368</td>\n",
+       "      <td>10399</td>\n",
+       "      <td>18337</td>\n",
+       "      <td>22</td>\n",
+       "      <td>16</td>\n",
+       "      <td>28</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>202425</td>\n",
+       "      <td>7</td>\n",
+       "      <td>11174</td>\n",
+       "      <td>8039</td>\n",
+       "      <td>14309</td>\n",
+       "      <td>17</td>\n",
+       "      <td>12</td>\n",
+       "      <td>22</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>202424</td>\n",
+       "      <td>7</td>\n",
+       "      <td>12621</td>\n",
+       "      <td>9357</td>\n",
+       "      <td>15885</td>\n",
+       "      <td>19</td>\n",
+       "      <td>14</td>\n",
+       "      <td>24</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>202423</td>\n",
+       "      <td>7</td>\n",
+       "      <td>14657</td>\n",
+       "      <td>11339</td>\n",
+       "      <td>17975</td>\n",
+       "      <td>22</td>\n",
+       "      <td>17</td>\n",
+       "      <td>27</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>202422</td>\n",
+       "      <td>7</td>\n",
+       "      <td>11628</td>\n",
+       "      <td>8361</td>\n",
+       "      <td>14895</td>\n",
+       "      <td>17</td>\n",
+       "      <td>12</td>\n",
+       "      <td>22</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>202421</td>\n",
+       "      <td>7</td>\n",
+       "      <td>9701</td>\n",
+       "      <td>6851</td>\n",
+       "      <td>12551</td>\n",
+       "      <td>15</td>\n",
+       "      <td>11</td>\n",
+       "      <td>19</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>202420</td>\n",
+       "      <td>7</td>\n",
+       "      <td>13661</td>\n",
+       "      <td>10209</td>\n",
+       "      <td>17113</td>\n",
+       "      <td>20</td>\n",
+       "      <td>15</td>\n",
+       "      <td>25</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>202419</td>\n",
+       "      <td>7</td>\n",
+       "      <td>10083</td>\n",
+       "      <td>6413</td>\n",
+       "      <td>13753</td>\n",
+       "      <td>15</td>\n",
+       "      <td>9</td>\n",
+       "      <td>21</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>202418</td>\n",
+       "      <td>7</td>\n",
+       "      <td>13438</td>\n",
+       "      <td>9514</td>\n",
+       "      <td>17362</td>\n",
+       "      <td>20</td>\n",
+       "      <td>14</td>\n",
+       "      <td>26</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>202417</td>\n",
+       "      <td>7</td>\n",
+       "      <td>15303</td>\n",
+       "      <td>11219</td>\n",
+       "      <td>19387</td>\n",
+       "      <td>23</td>\n",
+       "      <td>17</td>\n",
+       "      <td>29</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>202416</td>\n",
+       "      <td>7</td>\n",
+       "      <td>18138</td>\n",
+       "      <td>13540</td>\n",
+       "      <td>22736</td>\n",
+       "      <td>27</td>\n",
+       "      <td>20</td>\n",
+       "      <td>34</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>202415</td>\n",
+       "      <td>7</td>\n",
+       "      <td>24929</td>\n",
+       "      <td>17315</td>\n",
+       "      <td>32543</td>\n",
+       "      <td>37</td>\n",
+       "      <td>26</td>\n",
+       "      <td>48</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</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>1740</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>1741</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>1742</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>1743</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>1744</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>1745</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>1746</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>1747</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>1748</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>1749</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>1750</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>1751</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>1752</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>1753</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>1754</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>1755</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>1756</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>1757</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>1758</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>1759</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>1760</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>1761</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>1762</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>1763</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>1764</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>1765</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>1766</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>1767</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>1768</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>1769</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>1770 rows × 10 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        week  indicator    inc  inc_low  inc_up  inc100  inc100_low  \\\n",
+       "0     202444          7   2354      489    4219       4           1   \n",
+       "1     202443          7   2130      625    3635       3           1   \n",
+       "2     202442          7   2621     1246    3996       4           2   \n",
+       "3     202441          7   2035      381    3689       3           1   \n",
+       "4     202440          7   2125      725    3525       3           1   \n",
+       "5     202439          7   2898     1333    4463       4           2   \n",
+       "6     202438          7    751        0    1513       1           0   \n",
+       "7     202437          7    916       28    1804       1           0   \n",
+       "8     202436          7   2235      870    3600       3           1   \n",
+       "9     202435          7   1620      285    2955       2           0   \n",
+       "10    202434          7   2560      622    4498       4           1   \n",
+       "11    202433          7   1971      536    3406       3           1   \n",
+       "12    202432          7   4399     1944    6854       7           3   \n",
+       "13    202431          7   4500     2213    6787       7           4   \n",
+       "14    202430          7   7004     4278    9730      11           7   \n",
+       "15    202429          7   9270     6303   12237      14          10   \n",
+       "16    202428          7   9364     6498   12230      14          10   \n",
+       "17    202427          7  10247     7090   13404      15          10   \n",
+       "18    202426          7  14368    10399   18337      22          16   \n",
+       "19    202425          7  11174     8039   14309      17          12   \n",
+       "20    202424          7  12621     9357   15885      19          14   \n",
+       "21    202423          7  14657    11339   17975      22          17   \n",
+       "22    202422          7  11628     8361   14895      17          12   \n",
+       "23    202421          7   9701     6851   12551      15          11   \n",
+       "24    202420          7  13661    10209   17113      20          15   \n",
+       "25    202419          7  10083     6413   13753      15           9   \n",
+       "26    202418          7  13438     9514   17362      20          14   \n",
+       "27    202417          7  15303    11219   19387      23          17   \n",
+       "28    202416          7  18138    13540   22736      27          20   \n",
+       "29    202415          7  24929    17315   32543      37          26   \n",
+       "...      ...        ...    ...      ...     ...     ...         ...   \n",
+       "1740  199126          7  17608    11304   23912      31          20   \n",
+       "1741  199125          7  16169    10700   21638      28          18   \n",
+       "1742  199124          7  16171    10071   22271      28          17   \n",
+       "1743  199123          7  11947     7671   16223      21          13   \n",
+       "1744  199122          7  15452     9953   20951      27          17   \n",
+       "1745  199121          7  14903     8975   20831      26          16   \n",
+       "1746  199120          7  19053    12742   25364      34          23   \n",
+       "1747  199119          7  16739    11246   22232      29          19   \n",
+       "1748  199118          7  21385    13882   28888      38          25   \n",
+       "1749  199117          7  13462     8877   18047      24          16   \n",
+       "1750  199116          7  14857    10068   19646      26          18   \n",
+       "1751  199115          7  13975     9781   18169      25          18   \n",
+       "1752  199114          7  12265     7684   16846      22          14   \n",
+       "1753  199113          7   9567     6041   13093      17          11   \n",
+       "1754  199112          7  10864     7331   14397      19          13   \n",
+       "1755  199111          7  15574    11184   19964      27          19   \n",
+       "1756  199110          7  16643    11372   21914      29          20   \n",
+       "1757  199109          7  13741     8780   18702      24          15   \n",
+       "1758  199108          7  13289     8813   17765      23          15   \n",
+       "1759  199107          7  12337     8077   16597      22          15   \n",
+       "1760  199106          7  10877     7013   14741      19          12   \n",
+       "1761  199105          7  10442     6544   14340      18          11   \n",
+       "1762  199104          7   7913     4563   11263      14           8   \n",
+       "1763  199103          7  15387    10484   20290      27          18   \n",
+       "1764  199102          7  16277    11046   21508      29          20   \n",
+       "1765  199101          7  15565    10271   20859      27          18   \n",
+       "1766  199052          7  19375    13295   25455      34          23   \n",
+       "1767  199051          7  19080    13807   24353      34          25   \n",
+       "1768  199050          7  11079     6660   15498      20          12   \n",
+       "1769  199049          7   1143        0    2610       2           0   \n",
+       "\n",
+       "      inc100_up geo_insee geo_name  \n",
+       "0             7        FR   France  \n",
+       "1             5        FR   France  \n",
+       "2             6        FR   France  \n",
+       "3             5        FR   France  \n",
+       "4             5        FR   France  \n",
+       "5             6        FR   France  \n",
+       "6             2        FR   France  \n",
+       "7             2        FR   France  \n",
+       "8             5        FR   France  \n",
+       "9             4        FR   France  \n",
+       "10            7        FR   France  \n",
+       "11            5        FR   France  \n",
+       "12           11        FR   France  \n",
+       "13           10        FR   France  \n",
+       "14           15        FR   France  \n",
+       "15           18        FR   France  \n",
+       "16           18        FR   France  \n",
+       "17           20        FR   France  \n",
+       "18           28        FR   France  \n",
+       "19           22        FR   France  \n",
+       "20           24        FR   France  \n",
+       "21           27        FR   France  \n",
+       "22           22        FR   France  \n",
+       "23           19        FR   France  \n",
+       "24           25        FR   France  \n",
+       "25           21        FR   France  \n",
+       "26           26        FR   France  \n",
+       "27           29        FR   France  \n",
+       "28           34        FR   France  \n",
+       "29           48        FR   France  \n",
+       "...         ...       ...      ...  \n",
+       "1740         42        FR   France  \n",
+       "1741         38        FR   France  \n",
+       "1742         39        FR   France  \n",
+       "1743         29        FR   France  \n",
+       "1744         37        FR   France  \n",
+       "1745         36        FR   France  \n",
+       "1746         45        FR   France  \n",
+       "1747         39        FR   France  \n",
+       "1748         51        FR   France  \n",
+       "1749         32        FR   France  \n",
+       "1750         34        FR   France  \n",
+       "1751         32        FR   France  \n",
+       "1752         30        FR   France  \n",
+       "1753         23        FR   France  \n",
+       "1754         25        FR   France  \n",
+       "1755         35        FR   France  \n",
+       "1756         38        FR   France  \n",
+       "1757         33        FR   France  \n",
+       "1758         31        FR   France  \n",
+       "1759         29        FR   France  \n",
+       "1760         26        FR   France  \n",
+       "1761         25        FR   France  \n",
+       "1762         20        FR   France  \n",
+       "1763         36        FR   France  \n",
+       "1764         38        FR   France  \n",
+       "1765         36        FR   France  \n",
+       "1766         45        FR   France  \n",
+       "1767         43        FR   France  \n",
+       "1768         28        FR   France  \n",
+       "1769          5        FR   France  \n",
+       "\n",
+       "[1770 rows x 10 columns]"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data = pd.read_csv(data_file, encoding = 'iso-8859-1', skiprows=1)\n",
+    "raw_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>indicator</th>\n",
+       "      <th>inc</th>\n",
+       "      <th>inc_low</th>\n",
+       "      <th>inc_up</th>\n",
+       "      <th>inc100</th>\n",
+       "      <th>inc100_low</th>\n",
+       "      <th>inc100_up</th>\n",
+       "      <th>geo_insee</th>\n",
+       "      <th>geo_name</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "  </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": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data[raw_data.isnull().any(axis=1)]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Aucune donnée manquante alors pas besoin de modifier les données."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def convert_week(year_and_week_int):\n",
+    "    year_and_week_str = str(year_and_week_int)\n",
+    "    year = int(year_and_week_str[:4])\n",
+    "    week = int(year_and_week_str[4:])\n",
+    "    w = isoweek.Week(year, week)\n",
+    "    return pd.Period(w.day(0), 'W')\n",
+    "\n",
+    "raw_data['period'] = [convert_week(yw) for yw in raw_data['week']]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sorted_data = raw_data.set_index('period').sort_index()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "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": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f8fbe4f40f0>"
+      ]
+     },
+     "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']=sorted_data['inc'].astype(int)\n",
+    "sorted_data['inc'].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f8fbc3c6550>"
+      ]
+     },
+     "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": [
+    "On choisi ici le premier septembre comme début de chaque période annuelle. Et nous commençons en 1991 car les données commancent la 49ème semaine de 1990."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "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": 15,
+   "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": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f8fbc351048>"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "yearly_incidence.plot(style='*')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2020    221186\n",
+       "2023    366227\n",
+       "2021    376290\n",
+       "2002    516689\n",
+       "2018    542312\n",
+       "2017    551041\n",
+       "1996    564901\n",
+       "2019    584066\n",
+       "2015    604382\n",
+       "2000    617597\n",
+       "2001    619041\n",
+       "2012    624573\n",
+       "2005    628464\n",
+       "2006    632833\n",
+       "2022    641397\n",
+       "2011    642368\n",
+       "1993    643387\n",
+       "1995    652478\n",
+       "1994    661409\n",
+       "1998    677775\n",
+       "1997    683434\n",
+       "2014    685769\n",
+       "2013    698332\n",
+       "2007    717352\n",
+       "2008    749478\n",
+       "1999    756456\n",
+       "2003    758363\n",
+       "2004    777388\n",
+       "2016    782114\n",
+       "2010    829911\n",
+       "1992    832939\n",
+       "2009    842373\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "yearly_incidence.sort_values()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f8fbc30dd30>"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "yearly_incidence.hist(xrot=20)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/module3/exo2/exercice.ipynb b/module3/exo2/exercice.ipynb
deleted file mode 100644
index 0bbbe371b01e359e381e43239412d77bf53fb1fb..0000000000000000000000000000000000000000
--- a/module3/exo2/exercice.ipynb
+++ /dev/null
@@ -1,25 +0,0 @@
-{
- "cells": [],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.6.3"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
-
diff --git a/module3/exo2/inc-7-PAY.csv b/module3/exo2/inc-7-PAY.csv
new file mode 100644
index 0000000000000000000000000000000000000000..bb57be1a8171ffd9923d29833465f454694614c4
--- /dev/null
+++ b/module3/exo2/inc-7-PAY.csv
@@ -0,0 +1,1772 @@
+# {"source":"r&#233;seau Sentinelles, INSERM, Sorbonne Universit&#233;, https:\/\/www.sentiweb.fr","meta":{"period":[199049,202444],"geo":["PAY",0],"geo_ref":"insee","indicator":"7","type":"all","conf_int":true,"compact":false,"age_group":false,"span":"all"},"date":"2024-11-06T17:58:52+01:00","bundle":"1730912319"}
+week,indicator,inc,inc_low,inc_up,inc100,inc100_low,inc100_up,geo_insee,geo_name
+202444,7,2354,489,4219,4,1,7,FR,France
+202443,7,2130,625,3635,3,1,5,FR,France
+202442,7,2621,1246,3996,4,2,6,FR,France
+202441,7,2035,381,3689,3,1,5,FR,France
+202440,7,2125,725,3525,3,1,5,FR,France
+202439,7,2898,1333,4463,4,2,6,FR,France
+202438,7,751,0,1513,1,0,2,FR,France
+202437,7,916,28,1804,1,0,2,FR,France
+202436,7,2235,870,3600,3,1,5,FR,France
+202435,7,1620,285,2955,2,0,4,FR,France
+202434,7,2560,622,4498,4,1,7,FR,France
+202433,7,1971,536,3406,3,1,5,FR,France
+202432,7,4399,1944,6854,7,3,11,FR,France
+202431,7,4500,2213,6787,7,4,10,FR,France
+202430,7,7004,4278,9730,11,7,15,FR,France
+202429,7,9270,6303,12237,14,10,18,FR,France
+202428,7,9364,6498,12230,14,10,18,FR,France
+202427,7,10247,7090,13404,15,10,20,FR,France
+202426,7,14368,10399,18337,22,16,28,FR,France
+202425,7,11174,8039,14309,17,12,22,FR,France
+202424,7,12621,9357,15885,19,14,24,FR,France
+202423,7,14657,11339,17975,22,17,27,FR,France
+202422,7,11628,8361,14895,17,12,22,FR,France
+202421,7,9701,6851,12551,15,11,19,FR,France
+202420,7,13661,10209,17113,20,15,25,FR,France
+202419,7,10083,6413,13753,15,9,21,FR,France
+202418,7,13438,9514,17362,20,14,26,FR,France
+202417,7,15303,11219,19387,23,17,29,FR,France
+202416,7,18138,13540,22736,27,20,34,FR,France
+202415,7,24929,17315,32543,37,26,48,FR,France
+202414,7,16181,12544,19818,24,19,29,FR,France
+202413,7,18322,14206,22438,27,21,33,FR,France
+202412,7,12818,9128,16508,19,13,25,FR,France
+202411,7,15973,12400,19546,24,19,29,FR,France
+202410,7,14301,10761,17841,21,16,26,FR,France
+202409,7,14337,10871,17803,21,16,26,FR,France
+202408,7,15899,11991,19807,24,18,30,FR,France
+202407,7,11294,8226,14362,17,12,22,FR,France
+202406,7,12174,9020,15328,18,13,23,FR,France
+202405,7,8814,6110,11518,13,9,17,FR,France
+202404,7,9504,6566,12442,14,10,18,FR,France
+202403,7,6948,4633,9263,10,7,13,FR,France
+202402,7,7125,4852,9398,11,8,14,FR,France
+202401,7,13305,9214,17396,20,14,26,FR,France
+202352,7,11636,7354,15918,18,12,24,FR,France
+202351,7,6912,4227,9597,10,6,14,FR,France
+202350,7,8799,6215,11383,13,9,17,FR,France
+202349,7,7817,5362,10272,12,8,16,FR,France
+202348,7,7351,4749,9953,11,7,15,FR,France
+202347,7,6537,4277,8797,10,7,13,FR,France
+202346,7,5229,2973,7485,8,5,11,FR,France
+202345,7,5007,2675,7339,8,4,12,FR,France
+202344,7,3688,1664,5712,6,3,9,FR,France
+202343,7,3891,1675,6107,6,3,9,FR,France
+202342,7,3968,1212,6724,6,2,10,FR,France
+202341,7,3356,1764,4948,5,3,7,FR,France
+202340,7,2845,1410,4280,4,2,6,FR,France
+202339,7,1739,629,2849,3,1,5,FR,France
+202338,7,1663,274,3052,3,1,5,FR,France
+202337,7,1122,223,2021,2,1,3,FR,France
+202336,7,726,10,1442,1,0,2,FR,France
+202335,7,961,96,1826,1,0,2,FR,France
+202334,7,1168,9,2327,2,0,4,FR,France
+202333,7,3308,1184,5432,5,2,8,FR,France
+202332,7,7996,1120,14872,12,2,22,FR,France
+202331,7,3318,1398,5238,5,2,8,FR,France
+202330,7,5821,3269,8373,9,5,13,FR,France
+202329,7,13558,8297,18819,20,12,28,FR,France
+202328,7,6700,4043,9357,10,6,14,FR,France
+202327,7,7253,4599,9907,11,7,15,FR,France
+202326,7,9192,6223,12161,14,10,18,FR,France
+202325,7,11498,8257,14739,17,12,22,FR,France
+202324,7,11115,7968,14262,17,12,22,FR,France
+202323,7,12563,6134,18992,19,9,29,FR,France
+202322,7,12184,8125,16243,18,12,24,FR,France
+202321,7,11349,7598,15100,17,11,23,FR,France
+202320,7,9000,4615,13385,14,7,21,FR,France
+202319,7,9344,6091,12597,14,9,19,FR,France
+202318,7,10671,7291,14051,16,11,21,FR,France
+202317,7,9184,6162,12206,14,9,19,FR,France
+202316,7,11387,8014,14760,17,12,22,FR,France
+202315,7,14040,7613,20467,21,11,31,FR,France
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+199909,7,11125,6841,15409,19,12,26,FR,France
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+199907,7,13655,9263,18047,23,15,31,FR,France
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+199905,7,16838,11942,21734,29,21,37,FR,France
+199904,7,17056,12124,21988,29,21,37,FR,France
+199903,7,18805,13967,23643,32,24,40,FR,France
+199902,7,14863,10135,19591,25,17,33,FR,France
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+199853,7,24797,17975,31619,43,31,55,FR,France
+199852,7,23616,16902,30330,41,29,53,FR,France
+199851,7,13919,9478,18360,24,16,32,FR,France
+199850,7,20556,15164,25948,35,26,44,FR,France
+199849,7,16232,11327,21137,28,20,36,FR,France
+199848,7,11998,7691,16305,21,14,28,FR,France
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+199846,7,7646,4419,10873,13,7,19,FR,France
+199845,7,15930,10713,21147,27,18,36,FR,France
+199844,7,14145,9390,18900,24,16,32,FR,France
+199843,7,16707,11447,21967,29,20,38,FR,France
+199842,7,12475,7806,17144,21,13,29,FR,France
+199841,7,13018,8151,17885,22,14,30,FR,France
+199840,7,7396,3653,11139,13,7,19,FR,France
+199839,7,4467,1896,7038,8,4,12,FR,France
+199838,7,3421,1176,5666,6,2,10,FR,France
+199837,7,4489,2136,6842,8,4,12,FR,France
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+199834,7,7235,3191,11279,12,5,19,FR,France
+199833,7,11431,6018,16844,20,11,29,FR,France
+199832,7,20493,9237,31749,35,16,54,FR,France
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+199732,7,12349,6916,17782,21,12,30,FR,France
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