diff --git a/module3/exo1/analyse-syndrome-grippal.ipynb b/module3/exo1/analyse-syndrome-grippal.ipynb
index dc400db07b527cfde48184b9b1f6d95eae200081..aef8b2bfc4812da8551cec0636dae9da2e11caa0 100644
--- a/module3/exo1/analyse-syndrome-grippal.ipynb
+++ b/module3/exo1/analyse-syndrome-grippal.ipynb
@@ -44,48 +44,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "incidence-PAY-3.csv\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Extraire le nom du fichier à rechercher dans le répertoire courant.\n",
-    "data_url_split = data_url.strip().split('/')\n",
-    "nom_fich = data_url_split[len(data_url_split)-1:len(data_url_split)]\n",
-    "print(nom_fich[0])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 6,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Les données sont présentes dans le répertoire.\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
-    "# Vérifier la présence du fichier dans le répertoire courant.\n",
-    "try:\n",
-    "    with open(nom_fich[0], \"r\", encoding='utf-8') as entree:\n",
-    "        pass\n",
-    "except FileNotFoundError as e:\n",
-    "    raw_data = pd.read_csv(data_url, skiprows=0)\n",
-    "    raw_data.to_csv(nom_fich[0])\n",
-    "    print('Les données ont été copiées dans le répertoire.')\n",
-    "else:\n",
-    "    print('Les données sont présentes dans le répertoire.')"
+    "data_file = \"syndrome-grippal.csv\"\n",
+    "\n",
+    "import os\n",
+    "import urllib.request\n",
+    "\n",
+    "if not os.path.exists(data_file):\n",
+    "    urllib.request.urlretrieve(data_url, data_file)\n"
    ]
   },
   {
@@ -112,7 +81,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -136,23 +105,34 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>0</th>\n",
-       "      <th>202039</th>\n",
-       "      <th>3</th>\n",
-       "      <th>26891</th>\n",
-       "      <th>21449.0</th>\n",
-       "      <th>32333.0</th>\n",
-       "      <th>41</th>\n",
-       "      <th>33.0</th>\n",
-       "      <th>49.0</th>\n",
-       "      <th>FR</th>\n",
-       "      <th>France</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>1</td>\n",
+       "      <td>202039</td>\n",
+       "      <td>3</td>\n",
+       "      <td>26891</td>\n",
+       "      <td>21449.0</td>\n",
+       "      <td>32333.0</td>\n",
+       "      <td>41</td>\n",
+       "      <td>33.0</td>\n",
+       "      <td>49.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
        "      <td>202038</td>\n",
        "      <td>3</td>\n",
        "      <td>25578</td>\n",
@@ -165,8 +145,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>2</td>\n",
+       "      <th>2</th>\n",
        "      <td>202037</td>\n",
        "      <td>3</td>\n",
        "      <td>18485</td>\n",
@@ -179,8 +158,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>3</td>\n",
+       "      <th>3</th>\n",
        "      <td>202036</td>\n",
        "      <td>3</td>\n",
        "      <td>10390</td>\n",
@@ -193,8 +171,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>4</td>\n",
+       "      <th>4</th>\n",
        "      <td>202035</td>\n",
        "      <td>3</td>\n",
        "      <td>9918</td>\n",
@@ -207,8 +184,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>5</td>\n",
+       "      <th>5</th>\n",
        "      <td>202034</td>\n",
        "      <td>3</td>\n",
        "      <td>6084</td>\n",
@@ -221,8 +197,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>6</td>\n",
+       "      <th>6</th>\n",
        "      <td>202033</td>\n",
        "      <td>3</td>\n",
        "      <td>6106</td>\n",
@@ -235,8 +210,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>7</td>\n",
+       "      <th>7</th>\n",
        "      <td>202032</td>\n",
        "      <td>3</td>\n",
        "      <td>5918</td>\n",
@@ -249,8 +223,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>8</td>\n",
+       "      <th>8</th>\n",
        "      <td>202031</td>\n",
        "      <td>3</td>\n",
        "      <td>4351</td>\n",
@@ -263,8 +236,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>9</td>\n",
+       "      <th>9</th>\n",
        "      <td>202030</td>\n",
        "      <td>3</td>\n",
        "      <td>8179</td>\n",
@@ -277,8 +249,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>10</td>\n",
+       "      <th>10</th>\n",
        "      <td>202029</td>\n",
        "      <td>3</td>\n",
        "      <td>8687</td>\n",
@@ -291,8 +262,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>10</th>\n",
-       "      <td>11</td>\n",
+       "      <th>11</th>\n",
        "      <td>202028</td>\n",
        "      <td>3</td>\n",
        "      <td>8340</td>\n",
@@ -305,8 +275,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>11</th>\n",
-       "      <td>12</td>\n",
+       "      <th>12</th>\n",
        "      <td>202027</td>\n",
        "      <td>3</td>\n",
        "      <td>4066</td>\n",
@@ -319,8 +288,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>12</th>\n",
-       "      <td>13</td>\n",
+       "      <th>13</th>\n",
        "      <td>202026</td>\n",
        "      <td>3</td>\n",
        "      <td>4039</td>\n",
@@ -333,8 +301,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>13</th>\n",
-       "      <td>14</td>\n",
+       "      <th>14</th>\n",
        "      <td>202025</td>\n",
        "      <td>3</td>\n",
        "      <td>2853</td>\n",
@@ -347,8 +314,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>14</th>\n",
-       "      <td>15</td>\n",
+       "      <th>15</th>\n",
        "      <td>202024</td>\n",
        "      <td>3</td>\n",
        "      <td>3058</td>\n",
@@ -361,8 +327,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>15</th>\n",
-       "      <td>16</td>\n",
+       "      <th>16</th>\n",
        "      <td>202023</td>\n",
        "      <td>3</td>\n",
        "      <td>4168</td>\n",
@@ -375,8 +340,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>16</th>\n",
-       "      <td>17</td>\n",
+       "      <th>17</th>\n",
        "      <td>202022</td>\n",
        "      <td>3</td>\n",
        "      <td>3580</td>\n",
@@ -389,8 +353,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>17</th>\n",
-       "      <td>18</td>\n",
+       "      <th>18</th>\n",
        "      <td>202021</td>\n",
        "      <td>3</td>\n",
        "      <td>6114</td>\n",
@@ -403,8 +366,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>18</th>\n",
-       "      <td>19</td>\n",
+       "      <th>19</th>\n",
        "      <td>202020</td>\n",
        "      <td>3</td>\n",
        "      <td>9315</td>\n",
@@ -417,8 +379,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>19</th>\n",
-       "      <td>20</td>\n",
+       "      <th>20</th>\n",
        "      <td>202019</td>\n",
        "      <td>3</td>\n",
        "      <td>11679</td>\n",
@@ -431,8 +392,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>20</th>\n",
-       "      <td>21</td>\n",
+       "      <th>21</th>\n",
        "      <td>202018</td>\n",
        "      <td>3</td>\n",
        "      <td>16398</td>\n",
@@ -445,8 +405,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>21</th>\n",
-       "      <td>22</td>\n",
+       "      <th>22</th>\n",
        "      <td>202017</td>\n",
        "      <td>3</td>\n",
        "      <td>18082</td>\n",
@@ -459,8 +418,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>22</th>\n",
-       "      <td>23</td>\n",
+       "      <th>23</th>\n",
        "      <td>202016</td>\n",
        "      <td>3</td>\n",
        "      <td>24165</td>\n",
@@ -473,8 +431,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>23</th>\n",
-       "      <td>24</td>\n",
+       "      <th>24</th>\n",
        "      <td>202015</td>\n",
        "      <td>3</td>\n",
        "      <td>41049</td>\n",
@@ -487,8 +444,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>24</th>\n",
-       "      <td>25</td>\n",
+       "      <th>25</th>\n",
        "      <td>202014</td>\n",
        "      <td>3</td>\n",
        "      <td>71666</td>\n",
@@ -501,8 +457,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>25</th>\n",
-       "      <td>26</td>\n",
+       "      <th>26</th>\n",
        "      <td>202013</td>\n",
        "      <td>3</td>\n",
        "      <td>107742</td>\n",
@@ -515,8 +470,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>26</th>\n",
-       "      <td>27</td>\n",
+       "      <th>27</th>\n",
        "      <td>202012</td>\n",
        "      <td>3</td>\n",
        "      <td>107283</td>\n",
@@ -529,8 +483,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>27</th>\n",
-       "      <td>28</td>\n",
+       "      <th>28</th>\n",
        "      <td>202011</td>\n",
        "      <td>3</td>\n",
        "      <td>101704</td>\n",
@@ -543,8 +496,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>28</th>\n",
-       "      <td>29</td>\n",
+       "      <th>29</th>\n",
        "      <td>202010</td>\n",
        "      <td>3</td>\n",
        "      <td>104977</td>\n",
@@ -557,20 +509,6 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>29</th>\n",
-       "      <td>30</td>\n",
-       "      <td>202009</td>\n",
-       "      <td>3</td>\n",
-       "      <td>110696</td>\n",
-       "      <td>102066.0</td>\n",
-       "      <td>119326.0</td>\n",
-       "      <td>168</td>\n",
-       "      <td>155.0</td>\n",
-       "      <td>181.0</td>\n",
-       "      <td>FR</td>\n",
-       "      <td>France</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
        "      <th>...</th>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
@@ -582,11 +520,9 @@
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
-       "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1843</th>\n",
-       "      <td>1844</td>\n",
+       "      <th>1844</th>\n",
        "      <td>198521</td>\n",
        "      <td>3</td>\n",
        "      <td>26096</td>\n",
@@ -599,8 +535,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1844</th>\n",
-       "      <td>1845</td>\n",
+       "      <th>1845</th>\n",
        "      <td>198520</td>\n",
        "      <td>3</td>\n",
        "      <td>27896</td>\n",
@@ -613,8 +548,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1845</th>\n",
-       "      <td>1846</td>\n",
+       "      <th>1846</th>\n",
        "      <td>198519</td>\n",
        "      <td>3</td>\n",
        "      <td>43154</td>\n",
@@ -627,8 +561,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1846</th>\n",
-       "      <td>1847</td>\n",
+       "      <th>1847</th>\n",
        "      <td>198518</td>\n",
        "      <td>3</td>\n",
        "      <td>40555</td>\n",
@@ -641,8 +574,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1847</th>\n",
-       "      <td>1848</td>\n",
+       "      <th>1848</th>\n",
        "      <td>198517</td>\n",
        "      <td>3</td>\n",
        "      <td>34053</td>\n",
@@ -655,8 +587,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1848</th>\n",
-       "      <td>1849</td>\n",
+       "      <th>1849</th>\n",
        "      <td>198516</td>\n",
        "      <td>3</td>\n",
        "      <td>50362</td>\n",
@@ -669,8 +600,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1849</th>\n",
-       "      <td>1850</td>\n",
+       "      <th>1850</th>\n",
        "      <td>198515</td>\n",
        "      <td>3</td>\n",
        "      <td>63881</td>\n",
@@ -683,8 +613,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1850</th>\n",
-       "      <td>1851</td>\n",
+       "      <th>1851</th>\n",
        "      <td>198514</td>\n",
        "      <td>3</td>\n",
        "      <td>134545</td>\n",
@@ -697,8 +626,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1851</th>\n",
-       "      <td>1852</td>\n",
+       "      <th>1852</th>\n",
        "      <td>198513</td>\n",
        "      <td>3</td>\n",
        "      <td>197206</td>\n",
@@ -711,8 +639,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1852</th>\n",
-       "      <td>1853</td>\n",
+       "      <th>1853</th>\n",
        "      <td>198512</td>\n",
        "      <td>3</td>\n",
        "      <td>245240</td>\n",
@@ -725,8 +652,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1853</th>\n",
-       "      <td>1854</td>\n",
+       "      <th>1854</th>\n",
        "      <td>198511</td>\n",
        "      <td>3</td>\n",
        "      <td>276205</td>\n",
@@ -739,8 +665,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1854</th>\n",
-       "      <td>1855</td>\n",
+       "      <th>1855</th>\n",
        "      <td>198510</td>\n",
        "      <td>3</td>\n",
        "      <td>353231</td>\n",
@@ -753,8 +678,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1855</th>\n",
-       "      <td>1856</td>\n",
+       "      <th>1856</th>\n",
        "      <td>198509</td>\n",
        "      <td>3</td>\n",
        "      <td>369895</td>\n",
@@ -767,8 +691,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1856</th>\n",
-       "      <td>1857</td>\n",
+       "      <th>1857</th>\n",
        "      <td>198508</td>\n",
        "      <td>3</td>\n",
        "      <td>389886</td>\n",
@@ -781,8 +704,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1857</th>\n",
-       "      <td>1858</td>\n",
+       "      <th>1858</th>\n",
        "      <td>198507</td>\n",
        "      <td>3</td>\n",
        "      <td>471852</td>\n",
@@ -795,8 +717,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1858</th>\n",
-       "      <td>1859</td>\n",
+       "      <th>1859</th>\n",
        "      <td>198506</td>\n",
        "      <td>3</td>\n",
        "      <td>565825</td>\n",
@@ -809,8 +730,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1859</th>\n",
-       "      <td>1860</td>\n",
+       "      <th>1860</th>\n",
        "      <td>198505</td>\n",
        "      <td>3</td>\n",
        "      <td>637302</td>\n",
@@ -823,8 +743,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1860</th>\n",
-       "      <td>1861</td>\n",
+       "      <th>1861</th>\n",
        "      <td>198504</td>\n",
        "      <td>3</td>\n",
        "      <td>424937</td>\n",
@@ -837,8 +756,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1861</th>\n",
-       "      <td>1862</td>\n",
+       "      <th>1862</th>\n",
        "      <td>198503</td>\n",
        "      <td>3</td>\n",
        "      <td>213901</td>\n",
@@ -851,8 +769,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1862</th>\n",
-       "      <td>1863</td>\n",
+       "      <th>1863</th>\n",
        "      <td>198502</td>\n",
        "      <td>3</td>\n",
        "      <td>97586</td>\n",
@@ -865,8 +782,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1863</th>\n",
-       "      <td>1864</td>\n",
+       "      <th>1864</th>\n",
        "      <td>198501</td>\n",
        "      <td>3</td>\n",
        "      <td>85489</td>\n",
@@ -879,8 +795,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1864</th>\n",
-       "      <td>1865</td>\n",
+       "      <th>1865</th>\n",
        "      <td>198452</td>\n",
        "      <td>3</td>\n",
        "      <td>84830</td>\n",
@@ -893,8 +808,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1865</th>\n",
-       "      <td>1866</td>\n",
+       "      <th>1866</th>\n",
        "      <td>198451</td>\n",
        "      <td>3</td>\n",
        "      <td>101726</td>\n",
@@ -907,8 +821,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1866</th>\n",
-       "      <td>1867</td>\n",
+       "      <th>1867</th>\n",
        "      <td>198450</td>\n",
        "      <td>3</td>\n",
        "      <td>123680</td>\n",
@@ -921,8 +834,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1867</th>\n",
-       "      <td>1868</td>\n",
+       "      <th>1868</th>\n",
        "      <td>198449</td>\n",
        "      <td>3</td>\n",
        "      <td>101073</td>\n",
@@ -935,8 +847,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1868</th>\n",
-       "      <td>1869</td>\n",
+       "      <th>1869</th>\n",
        "      <td>198448</td>\n",
        "      <td>3</td>\n",
        "      <td>78620</td>\n",
@@ -949,8 +860,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1869</th>\n",
-       "      <td>1870</td>\n",
+       "      <th>1870</th>\n",
        "      <td>198447</td>\n",
        "      <td>3</td>\n",
        "      <td>72029</td>\n",
@@ -963,8 +873,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1870</th>\n",
-       "      <td>1871</td>\n",
+       "      <th>1871</th>\n",
        "      <td>198446</td>\n",
        "      <td>3</td>\n",
        "      <td>87330</td>\n",
@@ -977,8 +886,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1871</th>\n",
-       "      <td>1872</td>\n",
+       "      <th>1872</th>\n",
        "      <td>198445</td>\n",
        "      <td>3</td>\n",
        "      <td>135223</td>\n",
@@ -991,8 +899,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1872</th>\n",
-       "      <td>1873</td>\n",
+       "      <th>1873</th>\n",
        "      <td>198444</td>\n",
        "      <td>3</td>\n",
        "      <td>68422</td>\n",
@@ -1006,146 +913,146 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>1873 rows × 11 columns</p>\n",
+       "<p>1874 rows × 10 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "         0  202039  3   26891   21449.0   32333.0    41    33.0    49.0  FR  \\\n",
-       "0        1  202038  3   25578   21135.0   30021.0    39    32.0    46.0  FR   \n",
-       "1        2  202037  3   18485   14649.0   22321.0    28    22.0    34.0  FR   \n",
-       "2        3  202036  3   10390    7646.0   13134.0    16    12.0    20.0  FR   \n",
-       "3        4  202035  3    9918    6842.0   12994.0    15    10.0    20.0  FR   \n",
-       "4        5  202034  3    6084    3090.0    9078.0     9     4.0    14.0  FR   \n",
-       "5        6  202033  3    6106    3411.0    8801.0     9     5.0    13.0  FR   \n",
-       "6        7  202032  3    5918    3330.0    8506.0     9     5.0    13.0  FR   \n",
-       "7        8  202031  3    4351    2269.0    6433.0     7     4.0    10.0  FR   \n",
-       "8        9  202030  3    8179    5442.0   10916.0    12     8.0    16.0  FR   \n",
-       "9       10  202029  3    8687    5860.0   11514.0    13     9.0    17.0  FR   \n",
-       "10      11  202028  3    8340    5701.0   10979.0    13     9.0    17.0  FR   \n",
-       "11      12  202027  3    4066    2406.0    5726.0     6     3.0     9.0  FR   \n",
-       "12      13  202026  3    4039    2389.0    5689.0     6     3.0     9.0  FR   \n",
-       "13      14  202025  3    2853    1488.0    4218.0     4     2.0     6.0  FR   \n",
-       "14      15  202024  3    3058    1690.0    4426.0     5     3.0     7.0  FR   \n",
-       "15      16  202023  3    4168    2468.0    5868.0     6     3.0     9.0  FR   \n",
-       "16      17  202022  3    3580    1947.0    5213.0     5     3.0     7.0  FR   \n",
-       "17      18  202021  3    6114    4026.0    8202.0     9     6.0    12.0  FR   \n",
-       "18      19  202020  3    9315    6775.0   11855.0    14    10.0    18.0  FR   \n",
-       "19      20  202019  3   11679    8722.0   14636.0    18    14.0    22.0  FR   \n",
-       "20      21  202018  3   16398   12851.0   19945.0    25    20.0    30.0  FR   \n",
-       "21      22  202017  3   18082   14454.0   21710.0    27    21.0    33.0  FR   \n",
-       "22      23  202016  3   24165   19893.0   28437.0    37    31.0    43.0  FR   \n",
-       "23      24  202015  3   41049   35377.0   46721.0    62    53.0    71.0  FR   \n",
-       "24      25  202014  3   71666   64531.0   78801.0   109    98.0   120.0  FR   \n",
-       "25      26  202013  3  107742   99187.0  116297.0   164   151.0   177.0  FR   \n",
-       "26      27  202012  3  107283   98610.0  115956.0   163   150.0   176.0  FR   \n",
-       "27      28  202011  3  101704   93652.0  109756.0   154   142.0   166.0  FR   \n",
-       "28      29  202010  3  104977   96650.0  113304.0   159   146.0   172.0  FR   \n",
-       "29      30  202009  3  110696  102066.0  119326.0   168   155.0   181.0  FR   \n",
-       "...    ...     ... ..     ...       ...       ...   ...     ...     ...  ..   \n",
-       "1843  1844  198521  3   26096   19621.0   32571.0    47    35.0    59.0  FR   \n",
-       "1844  1845  198520  3   27896   20885.0   34907.0    51    38.0    64.0  FR   \n",
-       "1845  1846  198519  3   43154   32821.0   53487.0    78    59.0    97.0  FR   \n",
-       "1846  1847  198518  3   40555   29935.0   51175.0    74    55.0    93.0  FR   \n",
-       "1847  1848  198517  3   34053   24366.0   43740.0    62    44.0    80.0  FR   \n",
-       "1848  1849  198516  3   50362   36451.0   64273.0    91    66.0   116.0  FR   \n",
-       "1849  1850  198515  3   63881   45538.0   82224.0   116    83.0   149.0  FR   \n",
-       "1850  1851  198514  3  134545  114400.0  154690.0   244   207.0   281.0  FR   \n",
-       "1851  1852  198513  3  197206  176080.0  218332.0   357   319.0   395.0  FR   \n",
-       "1852  1853  198512  3  245240  223304.0  267176.0   445   405.0   485.0  FR   \n",
-       "1853  1854  198511  3  276205  252399.0  300011.0   501   458.0   544.0  FR   \n",
-       "1854  1855  198510  3  353231  326279.0  380183.0   640   591.0   689.0  FR   \n",
-       "1855  1856  198509  3  369895  341109.0  398681.0   670   618.0   722.0  FR   \n",
-       "1856  1857  198508  3  389886  359529.0  420243.0   707   652.0   762.0  FR   \n",
-       "1857  1858  198507  3  471852  432599.0  511105.0   855   784.0   926.0  FR   \n",
-       "1858  1859  198506  3  565825  518011.0  613639.0  1026   939.0  1113.0  FR   \n",
-       "1859  1860  198505  3  637302  592795.0  681809.0  1155  1074.0  1236.0  FR   \n",
-       "1860  1861  198504  3  424937  390794.0  459080.0   770   708.0   832.0  FR   \n",
-       "1861  1862  198503  3  213901  174689.0  253113.0   388   317.0   459.0  FR   \n",
-       "1862  1863  198502  3   97586   80949.0  114223.0   177   147.0   207.0  FR   \n",
-       "1863  1864  198501  3   85489   65918.0  105060.0   155   120.0   190.0  FR   \n",
-       "1864  1865  198452  3   84830   60602.0  109058.0   154   110.0   198.0  FR   \n",
-       "1865  1866  198451  3  101726   80242.0  123210.0   185   146.0   224.0  FR   \n",
-       "1866  1867  198450  3  123680  101401.0  145959.0   225   184.0   266.0  FR   \n",
-       "1867  1868  198449  3  101073   81684.0  120462.0   184   149.0   219.0  FR   \n",
-       "1868  1869  198448  3   78620   60634.0   96606.0   143   110.0   176.0  FR   \n",
-       "1869  1870  198447  3   72029   54274.0   89784.0   131    99.0   163.0  FR   \n",
-       "1870  1871  198446  3   87330   67686.0  106974.0   159   123.0   195.0  FR   \n",
-       "1871  1872  198445  3  135223  101414.0  169032.0   246   184.0   308.0  FR   \n",
-       "1872  1873  198444  3   68422   20056.0  116788.0   125    37.0   213.0  FR   \n",
+       "        week  indicator     inc   inc_low    inc_up  inc100  inc100_low  \\\n",
+       "0     202039          3   26891   21449.0   32333.0      41        33.0   \n",
+       "1     202038          3   25578   21135.0   30021.0      39        32.0   \n",
+       "2     202037          3   18485   14649.0   22321.0      28        22.0   \n",
+       "3     202036          3   10390    7646.0   13134.0      16        12.0   \n",
+       "4     202035          3    9918    6842.0   12994.0      15        10.0   \n",
+       "5     202034          3    6084    3090.0    9078.0       9         4.0   \n",
+       "6     202033          3    6106    3411.0    8801.0       9         5.0   \n",
+       "7     202032          3    5918    3330.0    8506.0       9         5.0   \n",
+       "8     202031          3    4351    2269.0    6433.0       7         4.0   \n",
+       "9     202030          3    8179    5442.0   10916.0      12         8.0   \n",
+       "10    202029          3    8687    5860.0   11514.0      13         9.0   \n",
+       "11    202028          3    8340    5701.0   10979.0      13         9.0   \n",
+       "12    202027          3    4066    2406.0    5726.0       6         3.0   \n",
+       "13    202026          3    4039    2389.0    5689.0       6         3.0   \n",
+       "14    202025          3    2853    1488.0    4218.0       4         2.0   \n",
+       "15    202024          3    3058    1690.0    4426.0       5         3.0   \n",
+       "16    202023          3    4168    2468.0    5868.0       6         3.0   \n",
+       "17    202022          3    3580    1947.0    5213.0       5         3.0   \n",
+       "18    202021          3    6114    4026.0    8202.0       9         6.0   \n",
+       "19    202020          3    9315    6775.0   11855.0      14        10.0   \n",
+       "20    202019          3   11679    8722.0   14636.0      18        14.0   \n",
+       "21    202018          3   16398   12851.0   19945.0      25        20.0   \n",
+       "22    202017          3   18082   14454.0   21710.0      27        21.0   \n",
+       "23    202016          3   24165   19893.0   28437.0      37        31.0   \n",
+       "24    202015          3   41049   35377.0   46721.0      62        53.0   \n",
+       "25    202014          3   71666   64531.0   78801.0     109        98.0   \n",
+       "26    202013          3  107742   99187.0  116297.0     164       151.0   \n",
+       "27    202012          3  107283   98610.0  115956.0     163       150.0   \n",
+       "28    202011          3  101704   93652.0  109756.0     154       142.0   \n",
+       "29    202010          3  104977   96650.0  113304.0     159       146.0   \n",
+       "...      ...        ...     ...       ...       ...     ...         ...   \n",
+       "1844  198521          3   26096   19621.0   32571.0      47        35.0   \n",
+       "1845  198520          3   27896   20885.0   34907.0      51        38.0   \n",
+       "1846  198519          3   43154   32821.0   53487.0      78        59.0   \n",
+       "1847  198518          3   40555   29935.0   51175.0      74        55.0   \n",
+       "1848  198517          3   34053   24366.0   43740.0      62        44.0   \n",
+       "1849  198516          3   50362   36451.0   64273.0      91        66.0   \n",
+       "1850  198515          3   63881   45538.0   82224.0     116        83.0   \n",
+       "1851  198514          3  134545  114400.0  154690.0     244       207.0   \n",
+       "1852  198513          3  197206  176080.0  218332.0     357       319.0   \n",
+       "1853  198512          3  245240  223304.0  267176.0     445       405.0   \n",
+       "1854  198511          3  276205  252399.0  300011.0     501       458.0   \n",
+       "1855  198510          3  353231  326279.0  380183.0     640       591.0   \n",
+       "1856  198509          3  369895  341109.0  398681.0     670       618.0   \n",
+       "1857  198508          3  389886  359529.0  420243.0     707       652.0   \n",
+       "1858  198507          3  471852  432599.0  511105.0     855       784.0   \n",
+       "1859  198506          3  565825  518011.0  613639.0    1026       939.0   \n",
+       "1860  198505          3  637302  592795.0  681809.0    1155      1074.0   \n",
+       "1861  198504          3  424937  390794.0  459080.0     770       708.0   \n",
+       "1862  198503          3  213901  174689.0  253113.0     388       317.0   \n",
+       "1863  198502          3   97586   80949.0  114223.0     177       147.0   \n",
+       "1864  198501          3   85489   65918.0  105060.0     155       120.0   \n",
+       "1865  198452          3   84830   60602.0  109058.0     154       110.0   \n",
+       "1866  198451          3  101726   80242.0  123210.0     185       146.0   \n",
+       "1867  198450          3  123680  101401.0  145959.0     225       184.0   \n",
+       "1868  198449          3  101073   81684.0  120462.0     184       149.0   \n",
+       "1869  198448          3   78620   60634.0   96606.0     143       110.0   \n",
+       "1870  198447          3   72029   54274.0   89784.0     131        99.0   \n",
+       "1871  198446          3   87330   67686.0  106974.0     159       123.0   \n",
+       "1872  198445          3  135223  101414.0  169032.0     246       184.0   \n",
+       "1873  198444          3   68422   20056.0  116788.0     125        37.0   \n",
        "\n",
-       "      France  \n",
-       "0     France  \n",
-       "1     France  \n",
-       "2     France  \n",
-       "3     France  \n",
-       "4     France  \n",
-       "5     France  \n",
-       "6     France  \n",
-       "7     France  \n",
-       "8     France  \n",
-       "9     France  \n",
-       "10    France  \n",
-       "11    France  \n",
-       "12    France  \n",
-       "13    France  \n",
-       "14    France  \n",
-       "15    France  \n",
-       "16    France  \n",
-       "17    France  \n",
-       "18    France  \n",
-       "19    France  \n",
-       "20    France  \n",
-       "21    France  \n",
-       "22    France  \n",
-       "23    France  \n",
-       "24    France  \n",
-       "25    France  \n",
-       "26    France  \n",
-       "27    France  \n",
-       "28    France  \n",
-       "29    France  \n",
-       "...      ...  \n",
-       "1843  France  \n",
-       "1844  France  \n",
-       "1845  France  \n",
-       "1846  France  \n",
-       "1847  France  \n",
-       "1848  France  \n",
-       "1849  France  \n",
-       "1850  France  \n",
-       "1851  France  \n",
-       "1852  France  \n",
-       "1853  France  \n",
-       "1854  France  \n",
-       "1855  France  \n",
-       "1856  France  \n",
-       "1857  France  \n",
-       "1858  France  \n",
-       "1859  France  \n",
-       "1860  France  \n",
-       "1861  France  \n",
-       "1862  France  \n",
-       "1863  France  \n",
-       "1864  France  \n",
-       "1865  France  \n",
-       "1866  France  \n",
-       "1867  France  \n",
-       "1868  France  \n",
-       "1869  France  \n",
-       "1870  France  \n",
-       "1871  France  \n",
-       "1872  France  \n",
+       "      inc100_up geo_insee geo_name  \n",
+       "0          49.0        FR   France  \n",
+       "1          46.0        FR   France  \n",
+       "2          34.0        FR   France  \n",
+       "3          20.0        FR   France  \n",
+       "4          20.0        FR   France  \n",
+       "5          14.0        FR   France  \n",
+       "6          13.0        FR   France  \n",
+       "7          13.0        FR   France  \n",
+       "8          10.0        FR   France  \n",
+       "9          16.0        FR   France  \n",
+       "10         17.0        FR   France  \n",
+       "11         17.0        FR   France  \n",
+       "12          9.0        FR   France  \n",
+       "13          9.0        FR   France  \n",
+       "14          6.0        FR   France  \n",
+       "15          7.0        FR   France  \n",
+       "16          9.0        FR   France  \n",
+       "17          7.0        FR   France  \n",
+       "18         12.0        FR   France  \n",
+       "19         18.0        FR   France  \n",
+       "20         22.0        FR   France  \n",
+       "21         30.0        FR   France  \n",
+       "22         33.0        FR   France  \n",
+       "23         43.0        FR   France  \n",
+       "24         71.0        FR   France  \n",
+       "25        120.0        FR   France  \n",
+       "26        177.0        FR   France  \n",
+       "27        176.0        FR   France  \n",
+       "28        166.0        FR   France  \n",
+       "29        172.0        FR   France  \n",
+       "...         ...       ...      ...  \n",
+       "1844       59.0        FR   France  \n",
+       "1845       64.0        FR   France  \n",
+       "1846       97.0        FR   France  \n",
+       "1847       93.0        FR   France  \n",
+       "1848       80.0        FR   France  \n",
+       "1849      116.0        FR   France  \n",
+       "1850      149.0        FR   France  \n",
+       "1851      281.0        FR   France  \n",
+       "1852      395.0        FR   France  \n",
+       "1853      485.0        FR   France  \n",
+       "1854      544.0        FR   France  \n",
+       "1855      689.0        FR   France  \n",
+       "1856      722.0        FR   France  \n",
+       "1857      762.0        FR   France  \n",
+       "1858      926.0        FR   France  \n",
+       "1859     1113.0        FR   France  \n",
+       "1860     1236.0        FR   France  \n",
+       "1861      832.0        FR   France  \n",
+       "1862      459.0        FR   France  \n",
+       "1863      207.0        FR   France  \n",
+       "1864      190.0        FR   France  \n",
+       "1865      198.0        FR   France  \n",
+       "1866      224.0        FR   France  \n",
+       "1867      266.0        FR   France  \n",
+       "1868      219.0        FR   France  \n",
+       "1869      176.0        FR   France  \n",
+       "1870      163.0        FR   France  \n",
+       "1871      195.0        FR   France  \n",
+       "1872      308.0        FR   France  \n",
+       "1873      213.0        FR   France  \n",
        "\n",
-       "[1873 rows x 11 columns]"
+       "[1874 rows x 10 columns]"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "raw_data = pd.read_csv(nom_fich[0], skiprows=1)\n",
+    "raw_data = pd.read_csv(data_file, skiprows=1)\n",
     "raw_data"
    ]
   },
@@ -1158,7 +1065,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -1182,23 +1089,21 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>0</th>\n",
-       "      <th>202039</th>\n",
-       "      <th>3</th>\n",
-       "      <th>26891</th>\n",
-       "      <th>21449.0</th>\n",
-       "      <th>32333.0</th>\n",
-       "      <th>41</th>\n",
-       "      <th>33.0</th>\n",
-       "      <th>49.0</th>\n",
-       "      <th>FR</th>\n",
-       "      <th>France</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>1636</th>\n",
-       "      <td>1637</td>\n",
+       "      <th>1637</th>\n",
        "      <td>198919</td>\n",
        "      <td>3</td>\n",
        "      <td>0</td>\n",
@@ -1215,11 +1120,14 @@
        "</div>"
       ],
       "text/plain": [
-       "         0  202039  3  26891  21449.0  32333.0  41  33.0  49.0  FR  France\n",
-       "1636  1637  198919  3      0      NaN      NaN   0   NaN   NaN  FR  France"
+       "        week  indicator  inc  inc_low  inc_up  inc100  inc100_low  inc100_up  \\\n",
+       "1637  198919          3    0      NaN     NaN       0         NaN        NaN   \n",
+       "\n",
+       "     geo_insee geo_name  \n",
+       "1637        FR   France  "
       ]
      },
-     "execution_count": 6,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1237,7 +1145,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -1261,23 +1169,34 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>0</th>\n",
-       "      <th>202039</th>\n",
-       "      <th>3</th>\n",
-       "      <th>26891</th>\n",
-       "      <th>21449.0</th>\n",
-       "      <th>32333.0</th>\n",
-       "      <th>41</th>\n",
-       "      <th>33.0</th>\n",
-       "      <th>49.0</th>\n",
-       "      <th>FR</th>\n",
-       "      <th>France</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>1</td>\n",
+       "      <td>202039</td>\n",
+       "      <td>3</td>\n",
+       "      <td>26891</td>\n",
+       "      <td>21449.0</td>\n",
+       "      <td>32333.0</td>\n",
+       "      <td>41</td>\n",
+       "      <td>33.0</td>\n",
+       "      <td>49.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
        "      <td>202038</td>\n",
        "      <td>3</td>\n",
        "      <td>25578</td>\n",
@@ -1290,8 +1209,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>2</td>\n",
+       "      <th>2</th>\n",
        "      <td>202037</td>\n",
        "      <td>3</td>\n",
        "      <td>18485</td>\n",
@@ -1304,8 +1222,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>3</td>\n",
+       "      <th>3</th>\n",
        "      <td>202036</td>\n",
        "      <td>3</td>\n",
        "      <td>10390</td>\n",
@@ -1318,8 +1235,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>4</td>\n",
+       "      <th>4</th>\n",
        "      <td>202035</td>\n",
        "      <td>3</td>\n",
        "      <td>9918</td>\n",
@@ -1332,8 +1248,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>5</td>\n",
+       "      <th>5</th>\n",
        "      <td>202034</td>\n",
        "      <td>3</td>\n",
        "      <td>6084</td>\n",
@@ -1346,8 +1261,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>6</td>\n",
+       "      <th>6</th>\n",
        "      <td>202033</td>\n",
        "      <td>3</td>\n",
        "      <td>6106</td>\n",
@@ -1360,8 +1274,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>7</td>\n",
+       "      <th>7</th>\n",
        "      <td>202032</td>\n",
        "      <td>3</td>\n",
        "      <td>5918</td>\n",
@@ -1374,8 +1287,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>8</td>\n",
+       "      <th>8</th>\n",
        "      <td>202031</td>\n",
        "      <td>3</td>\n",
        "      <td>4351</td>\n",
@@ -1388,8 +1300,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>9</td>\n",
+       "      <th>9</th>\n",
        "      <td>202030</td>\n",
        "      <td>3</td>\n",
        "      <td>8179</td>\n",
@@ -1402,8 +1313,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>10</td>\n",
+       "      <th>10</th>\n",
        "      <td>202029</td>\n",
        "      <td>3</td>\n",
        "      <td>8687</td>\n",
@@ -1416,8 +1326,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>10</th>\n",
-       "      <td>11</td>\n",
+       "      <th>11</th>\n",
        "      <td>202028</td>\n",
        "      <td>3</td>\n",
        "      <td>8340</td>\n",
@@ -1430,8 +1339,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>11</th>\n",
-       "      <td>12</td>\n",
+       "      <th>12</th>\n",
        "      <td>202027</td>\n",
        "      <td>3</td>\n",
        "      <td>4066</td>\n",
@@ -1444,8 +1352,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>12</th>\n",
-       "      <td>13</td>\n",
+       "      <th>13</th>\n",
        "      <td>202026</td>\n",
        "      <td>3</td>\n",
        "      <td>4039</td>\n",
@@ -1458,8 +1365,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>13</th>\n",
-       "      <td>14</td>\n",
+       "      <th>14</th>\n",
        "      <td>202025</td>\n",
        "      <td>3</td>\n",
        "      <td>2853</td>\n",
@@ -1472,8 +1378,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>14</th>\n",
-       "      <td>15</td>\n",
+       "      <th>15</th>\n",
        "      <td>202024</td>\n",
        "      <td>3</td>\n",
        "      <td>3058</td>\n",
@@ -1486,8 +1391,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>15</th>\n",
-       "      <td>16</td>\n",
+       "      <th>16</th>\n",
        "      <td>202023</td>\n",
        "      <td>3</td>\n",
        "      <td>4168</td>\n",
@@ -1500,8 +1404,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>16</th>\n",
-       "      <td>17</td>\n",
+       "      <th>17</th>\n",
        "      <td>202022</td>\n",
        "      <td>3</td>\n",
        "      <td>3580</td>\n",
@@ -1514,8 +1417,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>17</th>\n",
-       "      <td>18</td>\n",
+       "      <th>18</th>\n",
        "      <td>202021</td>\n",
        "      <td>3</td>\n",
        "      <td>6114</td>\n",
@@ -1528,8 +1430,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>18</th>\n",
-       "      <td>19</td>\n",
+       "      <th>19</th>\n",
        "      <td>202020</td>\n",
        "      <td>3</td>\n",
        "      <td>9315</td>\n",
@@ -1542,8 +1443,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>19</th>\n",
-       "      <td>20</td>\n",
+       "      <th>20</th>\n",
        "      <td>202019</td>\n",
        "      <td>3</td>\n",
        "      <td>11679</td>\n",
@@ -1556,8 +1456,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>20</th>\n",
-       "      <td>21</td>\n",
+       "      <th>21</th>\n",
        "      <td>202018</td>\n",
        "      <td>3</td>\n",
        "      <td>16398</td>\n",
@@ -1570,8 +1469,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>21</th>\n",
-       "      <td>22</td>\n",
+       "      <th>22</th>\n",
        "      <td>202017</td>\n",
        "      <td>3</td>\n",
        "      <td>18082</td>\n",
@@ -1584,8 +1482,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>22</th>\n",
-       "      <td>23</td>\n",
+       "      <th>23</th>\n",
        "      <td>202016</td>\n",
        "      <td>3</td>\n",
        "      <td>24165</td>\n",
@@ -1598,8 +1495,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>23</th>\n",
-       "      <td>24</td>\n",
+       "      <th>24</th>\n",
        "      <td>202015</td>\n",
        "      <td>3</td>\n",
        "      <td>41049</td>\n",
@@ -1612,8 +1508,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>24</th>\n",
-       "      <td>25</td>\n",
+       "      <th>25</th>\n",
        "      <td>202014</td>\n",
        "      <td>3</td>\n",
        "      <td>71666</td>\n",
@@ -1626,8 +1521,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>25</th>\n",
-       "      <td>26</td>\n",
+       "      <th>26</th>\n",
        "      <td>202013</td>\n",
        "      <td>3</td>\n",
        "      <td>107742</td>\n",
@@ -1640,8 +1534,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>26</th>\n",
-       "      <td>27</td>\n",
+       "      <th>27</th>\n",
        "      <td>202012</td>\n",
        "      <td>3</td>\n",
        "      <td>107283</td>\n",
@@ -1654,8 +1547,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>27</th>\n",
-       "      <td>28</td>\n",
+       "      <th>28</th>\n",
        "      <td>202011</td>\n",
        "      <td>3</td>\n",
        "      <td>101704</td>\n",
@@ -1668,8 +1560,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>28</th>\n",
-       "      <td>29</td>\n",
+       "      <th>29</th>\n",
        "      <td>202010</td>\n",
        "      <td>3</td>\n",
        "      <td>104977</td>\n",
@@ -1682,20 +1573,6 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>29</th>\n",
-       "      <td>30</td>\n",
-       "      <td>202009</td>\n",
-       "      <td>3</td>\n",
-       "      <td>110696</td>\n",
-       "      <td>102066.0</td>\n",
-       "      <td>119326.0</td>\n",
-       "      <td>168</td>\n",
-       "      <td>155.0</td>\n",
-       "      <td>181.0</td>\n",
-       "      <td>FR</td>\n",
-       "      <td>France</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
        "      <th>...</th>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
@@ -1707,11 +1584,9 @@
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
-       "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1843</th>\n",
-       "      <td>1844</td>\n",
+       "      <th>1844</th>\n",
        "      <td>198521</td>\n",
        "      <td>3</td>\n",
        "      <td>26096</td>\n",
@@ -1724,8 +1599,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1844</th>\n",
-       "      <td>1845</td>\n",
+       "      <th>1845</th>\n",
        "      <td>198520</td>\n",
        "      <td>3</td>\n",
        "      <td>27896</td>\n",
@@ -1738,8 +1612,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1845</th>\n",
-       "      <td>1846</td>\n",
+       "      <th>1846</th>\n",
        "      <td>198519</td>\n",
        "      <td>3</td>\n",
        "      <td>43154</td>\n",
@@ -1752,8 +1625,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1846</th>\n",
-       "      <td>1847</td>\n",
+       "      <th>1847</th>\n",
        "      <td>198518</td>\n",
        "      <td>3</td>\n",
        "      <td>40555</td>\n",
@@ -1766,8 +1638,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1847</th>\n",
-       "      <td>1848</td>\n",
+       "      <th>1848</th>\n",
        "      <td>198517</td>\n",
        "      <td>3</td>\n",
        "      <td>34053</td>\n",
@@ -1780,8 +1651,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1848</th>\n",
-       "      <td>1849</td>\n",
+       "      <th>1849</th>\n",
        "      <td>198516</td>\n",
        "      <td>3</td>\n",
        "      <td>50362</td>\n",
@@ -1794,8 +1664,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1849</th>\n",
-       "      <td>1850</td>\n",
+       "      <th>1850</th>\n",
        "      <td>198515</td>\n",
        "      <td>3</td>\n",
        "      <td>63881</td>\n",
@@ -1808,8 +1677,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1850</th>\n",
-       "      <td>1851</td>\n",
+       "      <th>1851</th>\n",
        "      <td>198514</td>\n",
        "      <td>3</td>\n",
        "      <td>134545</td>\n",
@@ -1822,8 +1690,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1851</th>\n",
-       "      <td>1852</td>\n",
+       "      <th>1852</th>\n",
        "      <td>198513</td>\n",
        "      <td>3</td>\n",
        "      <td>197206</td>\n",
@@ -1836,8 +1703,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1852</th>\n",
-       "      <td>1853</td>\n",
+       "      <th>1853</th>\n",
        "      <td>198512</td>\n",
        "      <td>3</td>\n",
        "      <td>245240</td>\n",
@@ -1850,8 +1716,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1853</th>\n",
-       "      <td>1854</td>\n",
+       "      <th>1854</th>\n",
        "      <td>198511</td>\n",
        "      <td>3</td>\n",
        "      <td>276205</td>\n",
@@ -1864,8 +1729,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1854</th>\n",
-       "      <td>1855</td>\n",
+       "      <th>1855</th>\n",
        "      <td>198510</td>\n",
        "      <td>3</td>\n",
        "      <td>353231</td>\n",
@@ -1878,8 +1742,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1855</th>\n",
-       "      <td>1856</td>\n",
+       "      <th>1856</th>\n",
        "      <td>198509</td>\n",
        "      <td>3</td>\n",
        "      <td>369895</td>\n",
@@ -1892,8 +1755,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1856</th>\n",
-       "      <td>1857</td>\n",
+       "      <th>1857</th>\n",
        "      <td>198508</td>\n",
        "      <td>3</td>\n",
        "      <td>389886</td>\n",
@@ -1906,8 +1768,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1857</th>\n",
-       "      <td>1858</td>\n",
+       "      <th>1858</th>\n",
        "      <td>198507</td>\n",
        "      <td>3</td>\n",
        "      <td>471852</td>\n",
@@ -1920,8 +1781,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1858</th>\n",
-       "      <td>1859</td>\n",
+       "      <th>1859</th>\n",
        "      <td>198506</td>\n",
        "      <td>3</td>\n",
        "      <td>565825</td>\n",
@@ -1934,8 +1794,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1859</th>\n",
-       "      <td>1860</td>\n",
+       "      <th>1860</th>\n",
        "      <td>198505</td>\n",
        "      <td>3</td>\n",
        "      <td>637302</td>\n",
@@ -1948,8 +1807,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1860</th>\n",
-       "      <td>1861</td>\n",
+       "      <th>1861</th>\n",
        "      <td>198504</td>\n",
        "      <td>3</td>\n",
        "      <td>424937</td>\n",
@@ -1962,8 +1820,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1861</th>\n",
-       "      <td>1862</td>\n",
+       "      <th>1862</th>\n",
        "      <td>198503</td>\n",
        "      <td>3</td>\n",
        "      <td>213901</td>\n",
@@ -1976,8 +1833,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1862</th>\n",
-       "      <td>1863</td>\n",
+       "      <th>1863</th>\n",
        "      <td>198502</td>\n",
        "      <td>3</td>\n",
        "      <td>97586</td>\n",
@@ -1990,8 +1846,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1863</th>\n",
-       "      <td>1864</td>\n",
+       "      <th>1864</th>\n",
        "      <td>198501</td>\n",
        "      <td>3</td>\n",
        "      <td>85489</td>\n",
@@ -2004,8 +1859,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1864</th>\n",
-       "      <td>1865</td>\n",
+       "      <th>1865</th>\n",
        "      <td>198452</td>\n",
        "      <td>3</td>\n",
        "      <td>84830</td>\n",
@@ -2018,8 +1872,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1865</th>\n",
-       "      <td>1866</td>\n",
+       "      <th>1866</th>\n",
        "      <td>198451</td>\n",
        "      <td>3</td>\n",
        "      <td>101726</td>\n",
@@ -2032,8 +1885,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1866</th>\n",
-       "      <td>1867</td>\n",
+       "      <th>1867</th>\n",
        "      <td>198450</td>\n",
        "      <td>3</td>\n",
        "      <td>123680</td>\n",
@@ -2046,8 +1898,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1867</th>\n",
-       "      <td>1868</td>\n",
+       "      <th>1868</th>\n",
        "      <td>198449</td>\n",
        "      <td>3</td>\n",
        "      <td>101073</td>\n",
@@ -2060,8 +1911,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1868</th>\n",
-       "      <td>1869</td>\n",
+       "      <th>1869</th>\n",
        "      <td>198448</td>\n",
        "      <td>3</td>\n",
        "      <td>78620</td>\n",
@@ -2074,8 +1924,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1869</th>\n",
-       "      <td>1870</td>\n",
+       "      <th>1870</th>\n",
        "      <td>198447</td>\n",
        "      <td>3</td>\n",
        "      <td>72029</td>\n",
@@ -2088,8 +1937,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1870</th>\n",
-       "      <td>1871</td>\n",
+       "      <th>1871</th>\n",
        "      <td>198446</td>\n",
        "      <td>3</td>\n",
        "      <td>87330</td>\n",
@@ -2102,8 +1950,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1871</th>\n",
-       "      <td>1872</td>\n",
+       "      <th>1872</th>\n",
        "      <td>198445</td>\n",
        "      <td>3</td>\n",
        "      <td>135223</td>\n",
@@ -2116,8 +1963,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1872</th>\n",
-       "      <td>1873</td>\n",
+       "      <th>1873</th>\n",
        "      <td>198444</td>\n",
        "      <td>3</td>\n",
        "      <td>68422</td>\n",
@@ -2131,140 +1977,140 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>1872 rows × 11 columns</p>\n",
+       "<p>1873 rows × 10 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "         0  202039  3   26891   21449.0   32333.0    41    33.0    49.0  FR  \\\n",
-       "0        1  202038  3   25578   21135.0   30021.0    39    32.0    46.0  FR   \n",
-       "1        2  202037  3   18485   14649.0   22321.0    28    22.0    34.0  FR   \n",
-       "2        3  202036  3   10390    7646.0   13134.0    16    12.0    20.0  FR   \n",
-       "3        4  202035  3    9918    6842.0   12994.0    15    10.0    20.0  FR   \n",
-       "4        5  202034  3    6084    3090.0    9078.0     9     4.0    14.0  FR   \n",
-       "5        6  202033  3    6106    3411.0    8801.0     9     5.0    13.0  FR   \n",
-       "6        7  202032  3    5918    3330.0    8506.0     9     5.0    13.0  FR   \n",
-       "7        8  202031  3    4351    2269.0    6433.0     7     4.0    10.0  FR   \n",
-       "8        9  202030  3    8179    5442.0   10916.0    12     8.0    16.0  FR   \n",
-       "9       10  202029  3    8687    5860.0   11514.0    13     9.0    17.0  FR   \n",
-       "10      11  202028  3    8340    5701.0   10979.0    13     9.0    17.0  FR   \n",
-       "11      12  202027  3    4066    2406.0    5726.0     6     3.0     9.0  FR   \n",
-       "12      13  202026  3    4039    2389.0    5689.0     6     3.0     9.0  FR   \n",
-       "13      14  202025  3    2853    1488.0    4218.0     4     2.0     6.0  FR   \n",
-       "14      15  202024  3    3058    1690.0    4426.0     5     3.0     7.0  FR   \n",
-       "15      16  202023  3    4168    2468.0    5868.0     6     3.0     9.0  FR   \n",
-       "16      17  202022  3    3580    1947.0    5213.0     5     3.0     7.0  FR   \n",
-       "17      18  202021  3    6114    4026.0    8202.0     9     6.0    12.0  FR   \n",
-       "18      19  202020  3    9315    6775.0   11855.0    14    10.0    18.0  FR   \n",
-       "19      20  202019  3   11679    8722.0   14636.0    18    14.0    22.0  FR   \n",
-       "20      21  202018  3   16398   12851.0   19945.0    25    20.0    30.0  FR   \n",
-       "21      22  202017  3   18082   14454.0   21710.0    27    21.0    33.0  FR   \n",
-       "22      23  202016  3   24165   19893.0   28437.0    37    31.0    43.0  FR   \n",
-       "23      24  202015  3   41049   35377.0   46721.0    62    53.0    71.0  FR   \n",
-       "24      25  202014  3   71666   64531.0   78801.0   109    98.0   120.0  FR   \n",
-       "25      26  202013  3  107742   99187.0  116297.0   164   151.0   177.0  FR   \n",
-       "26      27  202012  3  107283   98610.0  115956.0   163   150.0   176.0  FR   \n",
-       "27      28  202011  3  101704   93652.0  109756.0   154   142.0   166.0  FR   \n",
-       "28      29  202010  3  104977   96650.0  113304.0   159   146.0   172.0  FR   \n",
-       "29      30  202009  3  110696  102066.0  119326.0   168   155.0   181.0  FR   \n",
-       "...    ...     ... ..     ...       ...       ...   ...     ...     ...  ..   \n",
-       "1843  1844  198521  3   26096   19621.0   32571.0    47    35.0    59.0  FR   \n",
-       "1844  1845  198520  3   27896   20885.0   34907.0    51    38.0    64.0  FR   \n",
-       "1845  1846  198519  3   43154   32821.0   53487.0    78    59.0    97.0  FR   \n",
-       "1846  1847  198518  3   40555   29935.0   51175.0    74    55.0    93.0  FR   \n",
-       "1847  1848  198517  3   34053   24366.0   43740.0    62    44.0    80.0  FR   \n",
-       "1848  1849  198516  3   50362   36451.0   64273.0    91    66.0   116.0  FR   \n",
-       "1849  1850  198515  3   63881   45538.0   82224.0   116    83.0   149.0  FR   \n",
-       "1850  1851  198514  3  134545  114400.0  154690.0   244   207.0   281.0  FR   \n",
-       "1851  1852  198513  3  197206  176080.0  218332.0   357   319.0   395.0  FR   \n",
-       "1852  1853  198512  3  245240  223304.0  267176.0   445   405.0   485.0  FR   \n",
-       "1853  1854  198511  3  276205  252399.0  300011.0   501   458.0   544.0  FR   \n",
-       "1854  1855  198510  3  353231  326279.0  380183.0   640   591.0   689.0  FR   \n",
-       "1855  1856  198509  3  369895  341109.0  398681.0   670   618.0   722.0  FR   \n",
-       "1856  1857  198508  3  389886  359529.0  420243.0   707   652.0   762.0  FR   \n",
-       "1857  1858  198507  3  471852  432599.0  511105.0   855   784.0   926.0  FR   \n",
-       "1858  1859  198506  3  565825  518011.0  613639.0  1026   939.0  1113.0  FR   \n",
-       "1859  1860  198505  3  637302  592795.0  681809.0  1155  1074.0  1236.0  FR   \n",
-       "1860  1861  198504  3  424937  390794.0  459080.0   770   708.0   832.0  FR   \n",
-       "1861  1862  198503  3  213901  174689.0  253113.0   388   317.0   459.0  FR   \n",
-       "1862  1863  198502  3   97586   80949.0  114223.0   177   147.0   207.0  FR   \n",
-       "1863  1864  198501  3   85489   65918.0  105060.0   155   120.0   190.0  FR   \n",
-       "1864  1865  198452  3   84830   60602.0  109058.0   154   110.0   198.0  FR   \n",
-       "1865  1866  198451  3  101726   80242.0  123210.0   185   146.0   224.0  FR   \n",
-       "1866  1867  198450  3  123680  101401.0  145959.0   225   184.0   266.0  FR   \n",
-       "1867  1868  198449  3  101073   81684.0  120462.0   184   149.0   219.0  FR   \n",
-       "1868  1869  198448  3   78620   60634.0   96606.0   143   110.0   176.0  FR   \n",
-       "1869  1870  198447  3   72029   54274.0   89784.0   131    99.0   163.0  FR   \n",
-       "1870  1871  198446  3   87330   67686.0  106974.0   159   123.0   195.0  FR   \n",
-       "1871  1872  198445  3  135223  101414.0  169032.0   246   184.0   308.0  FR   \n",
-       "1872  1873  198444  3   68422   20056.0  116788.0   125    37.0   213.0  FR   \n",
+       "        week  indicator     inc   inc_low    inc_up  inc100  inc100_low  \\\n",
+       "0     202039          3   26891   21449.0   32333.0      41        33.0   \n",
+       "1     202038          3   25578   21135.0   30021.0      39        32.0   \n",
+       "2     202037          3   18485   14649.0   22321.0      28        22.0   \n",
+       "3     202036          3   10390    7646.0   13134.0      16        12.0   \n",
+       "4     202035          3    9918    6842.0   12994.0      15        10.0   \n",
+       "5     202034          3    6084    3090.0    9078.0       9         4.0   \n",
+       "6     202033          3    6106    3411.0    8801.0       9         5.0   \n",
+       "7     202032          3    5918    3330.0    8506.0       9         5.0   \n",
+       "8     202031          3    4351    2269.0    6433.0       7         4.0   \n",
+       "9     202030          3    8179    5442.0   10916.0      12         8.0   \n",
+       "10    202029          3    8687    5860.0   11514.0      13         9.0   \n",
+       "11    202028          3    8340    5701.0   10979.0      13         9.0   \n",
+       "12    202027          3    4066    2406.0    5726.0       6         3.0   \n",
+       "13    202026          3    4039    2389.0    5689.0       6         3.0   \n",
+       "14    202025          3    2853    1488.0    4218.0       4         2.0   \n",
+       "15    202024          3    3058    1690.0    4426.0       5         3.0   \n",
+       "16    202023          3    4168    2468.0    5868.0       6         3.0   \n",
+       "17    202022          3    3580    1947.0    5213.0       5         3.0   \n",
+       "18    202021          3    6114    4026.0    8202.0       9         6.0   \n",
+       "19    202020          3    9315    6775.0   11855.0      14        10.0   \n",
+       "20    202019          3   11679    8722.0   14636.0      18        14.0   \n",
+       "21    202018          3   16398   12851.0   19945.0      25        20.0   \n",
+       "22    202017          3   18082   14454.0   21710.0      27        21.0   \n",
+       "23    202016          3   24165   19893.0   28437.0      37        31.0   \n",
+       "24    202015          3   41049   35377.0   46721.0      62        53.0   \n",
+       "25    202014          3   71666   64531.0   78801.0     109        98.0   \n",
+       "26    202013          3  107742   99187.0  116297.0     164       151.0   \n",
+       "27    202012          3  107283   98610.0  115956.0     163       150.0   \n",
+       "28    202011          3  101704   93652.0  109756.0     154       142.0   \n",
+       "29    202010          3  104977   96650.0  113304.0     159       146.0   \n",
+       "...      ...        ...     ...       ...       ...     ...         ...   \n",
+       "1844  198521          3   26096   19621.0   32571.0      47        35.0   \n",
+       "1845  198520          3   27896   20885.0   34907.0      51        38.0   \n",
+       "1846  198519          3   43154   32821.0   53487.0      78        59.0   \n",
+       "1847  198518          3   40555   29935.0   51175.0      74        55.0   \n",
+       "1848  198517          3   34053   24366.0   43740.0      62        44.0   \n",
+       "1849  198516          3   50362   36451.0   64273.0      91        66.0   \n",
+       "1850  198515          3   63881   45538.0   82224.0     116        83.0   \n",
+       "1851  198514          3  134545  114400.0  154690.0     244       207.0   \n",
+       "1852  198513          3  197206  176080.0  218332.0     357       319.0   \n",
+       "1853  198512          3  245240  223304.0  267176.0     445       405.0   \n",
+       "1854  198511          3  276205  252399.0  300011.0     501       458.0   \n",
+       "1855  198510          3  353231  326279.0  380183.0     640       591.0   \n",
+       "1856  198509          3  369895  341109.0  398681.0     670       618.0   \n",
+       "1857  198508          3  389886  359529.0  420243.0     707       652.0   \n",
+       "1858  198507          3  471852  432599.0  511105.0     855       784.0   \n",
+       "1859  198506          3  565825  518011.0  613639.0    1026       939.0   \n",
+       "1860  198505          3  637302  592795.0  681809.0    1155      1074.0   \n",
+       "1861  198504          3  424937  390794.0  459080.0     770       708.0   \n",
+       "1862  198503          3  213901  174689.0  253113.0     388       317.0   \n",
+       "1863  198502          3   97586   80949.0  114223.0     177       147.0   \n",
+       "1864  198501          3   85489   65918.0  105060.0     155       120.0   \n",
+       "1865  198452          3   84830   60602.0  109058.0     154       110.0   \n",
+       "1866  198451          3  101726   80242.0  123210.0     185       146.0   \n",
+       "1867  198450          3  123680  101401.0  145959.0     225       184.0   \n",
+       "1868  198449          3  101073   81684.0  120462.0     184       149.0   \n",
+       "1869  198448          3   78620   60634.0   96606.0     143       110.0   \n",
+       "1870  198447          3   72029   54274.0   89784.0     131        99.0   \n",
+       "1871  198446          3   87330   67686.0  106974.0     159       123.0   \n",
+       "1872  198445          3  135223  101414.0  169032.0     246       184.0   \n",
+       "1873  198444          3   68422   20056.0  116788.0     125        37.0   \n",
        "\n",
-       "      France  \n",
-       "0     France  \n",
-       "1     France  \n",
-       "2     France  \n",
-       "3     France  \n",
-       "4     France  \n",
-       "5     France  \n",
-       "6     France  \n",
-       "7     France  \n",
-       "8     France  \n",
-       "9     France  \n",
-       "10    France  \n",
-       "11    France  \n",
-       "12    France  \n",
-       "13    France  \n",
-       "14    France  \n",
-       "15    France  \n",
-       "16    France  \n",
-       "17    France  \n",
-       "18    France  \n",
-       "19    France  \n",
-       "20    France  \n",
-       "21    France  \n",
-       "22    France  \n",
-       "23    France  \n",
-       "24    France  \n",
-       "25    France  \n",
-       "26    France  \n",
-       "27    France  \n",
-       "28    France  \n",
-       "29    France  \n",
-       "...      ...  \n",
-       "1843  France  \n",
-       "1844  France  \n",
-       "1845  France  \n",
-       "1846  France  \n",
-       "1847  France  \n",
-       "1848  France  \n",
-       "1849  France  \n",
-       "1850  France  \n",
-       "1851  France  \n",
-       "1852  France  \n",
-       "1853  France  \n",
-       "1854  France  \n",
-       "1855  France  \n",
-       "1856  France  \n",
-       "1857  France  \n",
-       "1858  France  \n",
-       "1859  France  \n",
-       "1860  France  \n",
-       "1861  France  \n",
-       "1862  France  \n",
-       "1863  France  \n",
-       "1864  France  \n",
-       "1865  France  \n",
-       "1866  France  \n",
-       "1867  France  \n",
-       "1868  France  \n",
-       "1869  France  \n",
-       "1870  France  \n",
-       "1871  France  \n",
-       "1872  France  \n",
+       "      inc100_up geo_insee geo_name  \n",
+       "0          49.0        FR   France  \n",
+       "1          46.0        FR   France  \n",
+       "2          34.0        FR   France  \n",
+       "3          20.0        FR   France  \n",
+       "4          20.0        FR   France  \n",
+       "5          14.0        FR   France  \n",
+       "6          13.0        FR   France  \n",
+       "7          13.0        FR   France  \n",
+       "8          10.0        FR   France  \n",
+       "9          16.0        FR   France  \n",
+       "10         17.0        FR   France  \n",
+       "11         17.0        FR   France  \n",
+       "12          9.0        FR   France  \n",
+       "13          9.0        FR   France  \n",
+       "14          6.0        FR   France  \n",
+       "15          7.0        FR   France  \n",
+       "16          9.0        FR   France  \n",
+       "17          7.0        FR   France  \n",
+       "18         12.0        FR   France  \n",
+       "19         18.0        FR   France  \n",
+       "20         22.0        FR   France  \n",
+       "21         30.0        FR   France  \n",
+       "22         33.0        FR   France  \n",
+       "23         43.0        FR   France  \n",
+       "24         71.0        FR   France  \n",
+       "25        120.0        FR   France  \n",
+       "26        177.0        FR   France  \n",
+       "27        176.0        FR   France  \n",
+       "28        166.0        FR   France  \n",
+       "29        172.0        FR   France  \n",
+       "...         ...       ...      ...  \n",
+       "1844       59.0        FR   France  \n",
+       "1845       64.0        FR   France  \n",
+       "1846       97.0        FR   France  \n",
+       "1847       93.0        FR   France  \n",
+       "1848       80.0        FR   France  \n",
+       "1849      116.0        FR   France  \n",
+       "1850      149.0        FR   France  \n",
+       "1851      281.0        FR   France  \n",
+       "1852      395.0        FR   France  \n",
+       "1853      485.0        FR   France  \n",
+       "1854      544.0        FR   France  \n",
+       "1855      689.0        FR   France  \n",
+       "1856      722.0        FR   France  \n",
+       "1857      762.0        FR   France  \n",
+       "1858      926.0        FR   France  \n",
+       "1859     1113.0        FR   France  \n",
+       "1860     1236.0        FR   France  \n",
+       "1861      832.0        FR   France  \n",
+       "1862      459.0        FR   France  \n",
+       "1863      207.0        FR   France  \n",
+       "1864      190.0        FR   France  \n",
+       "1865      198.0        FR   France  \n",
+       "1866      224.0        FR   France  \n",
+       "1867      266.0        FR   France  \n",
+       "1868      219.0        FR   France  \n",
+       "1869      176.0        FR   France  \n",
+       "1870      163.0        FR   France  \n",
+       "1871      195.0        FR   France  \n",
+       "1872      308.0        FR   France  \n",
+       "1873      213.0        FR   France  \n",
        "\n",
-       "[1872 rows x 11 columns]"
+       "[1873 rows x 10 columns]"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2294,38 +2140,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 11,
    "metadata": {},
-   "outputs": [
-    {
-     "ename": "KeyError",
-     "evalue": "'week'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
-      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   2524\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2525\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2526\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
-      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
-      "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
-      "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
-      "\u001b[0;31mKeyError\u001b[0m: 'week'",
-      "\nDuring handling of the above exception, another exception occurred:\n",
-      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-8-4f9c04a6e476>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      6\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mPeriod\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mw\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mday\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'W'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      7\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 8\u001b[0;31m \u001b[0mdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'period'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mconvert_week\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0myw\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0myw\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'week'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   2137\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2138\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2139\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2140\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2141\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_getitem_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m_getitem_column\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   2144\u001b[0m         \u001b[0;31m# get column\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2145\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_unique\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2146\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_item_cache\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2147\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2148\u001b[0m         \u001b[0;31m# duplicate columns & possible reduce dimensionality\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m_get_item_cache\u001b[0;34m(self, item)\u001b[0m\n\u001b[1;32m   1840\u001b[0m         \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcache\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1841\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mres\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1842\u001b[0;31m             \u001b[0mvalues\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1843\u001b[0m             \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_box_item_values\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalues\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1844\u001b[0m             \u001b[0mcache\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mres\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/internals.py\u001b[0m in \u001b[0;36mget\u001b[0;34m(self, item, fastpath)\u001b[0m\n\u001b[1;32m   3841\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3842\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misna\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3843\u001b[0;31m                 \u001b[0mloc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3844\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3845\u001b[0m                 \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0misna\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   2525\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2526\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2527\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_maybe_cast_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2528\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2529\u001b[0m         \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtolerance\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtolerance\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
-      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
-      "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
-      "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
-      "\u001b[0;31mKeyError\u001b[0m: 'week'"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "def convert_week(year_and_week_int):\n",
     "    year_and_week_str = str(year_and_week_int)\n",
@@ -2353,7 +2170,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2378,9 +2195,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1989-05-01/1989-05-07 1989-05-15/1989-05-21\n"
+     ]
+    }
+   ],
    "source": [
     "periods = sorted_data.index\n",
     "for p1, p2 in zip(periods[:-1], periods[1:]):\n",
@@ -2398,9 +2223,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 14,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fadd37ddb00>"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "sorted_data['inc'].plot()"
    ]
@@ -2414,9 +2262,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fadd16a0198>"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "sorted_data['inc'][-200:].plot()"
    ]
@@ -2451,7 +2322,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2471,7 +2342,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2495,9 +2366,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 18,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fadd38d43c8>"
+      ]
+     },
+     "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.plot(style='*')"
    ]
@@ -2511,9 +2405,54 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 19,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2014    1600941\n",
+       "1991    1659249\n",
+       "1995    1840410\n",
+       "2012    2175217\n",
+       "2003    2234584\n",
+       "2019    2254386\n",
+       "2006    2307352\n",
+       "2017    2321583\n",
+       "2001    2529279\n",
+       "1992    2574578\n",
+       "1993    2703886\n",
+       "2018    2705325\n",
+       "1988    2765617\n",
+       "2007    2780164\n",
+       "1987    2855570\n",
+       "2016    2856393\n",
+       "2011    2857040\n",
+       "2008    2973918\n",
+       "1998    3034904\n",
+       "2002    3125418\n",
+       "2009    3444020\n",
+       "1994    3514763\n",
+       "1996    3539413\n",
+       "2004    3567744\n",
+       "1997    3620066\n",
+       "2015    3654892\n",
+       "2000    3826372\n",
+       "2005    3835025\n",
+       "1999    3908112\n",
+       "2010    4111392\n",
+       "2013    4182691\n",
+       "1986    5115251\n",
+       "1990    5235827\n",
+       "1989    5466192\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "yearly_incidence.sort_values()"
    ]
@@ -2528,9 +2467,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 20,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fadd15960b8>"
+      ]
+     },
+     "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.hist(xrot=20)"
    ]
diff --git a/module3/exo1/syndrome-grippal.csv b/module3/exo1/syndrome-grippal.csv
new file mode 100644
index 0000000000000000000000000000000000000000..4565d1e9a75ca6483ef1c7a76cfbfc2bfcb2cabb
--- /dev/null
+++ b/module3/exo1/syndrome-grippal.csv
@@ -0,0 +1,1876 @@
+# @source="réseau Sentinelles, INSERM, Sorbonne Université, http://www.sentiweb.fr", @meta={"period":[198444,202039],"geo":["PAY","1"],"geo_ref":"insee","indicator":"3","type":"all","conf_int":true,"compact":false}, @date=2020-09-30T18:14:31+02:00
+week,indicator,inc,inc_low,inc_up,inc100,inc100_low,inc100_up,geo_insee,geo_name
+202039,3,26891,21449,32333,41,33,49,FR,France
+202038,3,25578,21135,30021,39,32,46,FR,France
+202037,3,18485,14649,22321,28,22,34,FR,France
+202036,3,10390,7646,13134,16,12,20,FR,France
+202035,3,9918,6842,12994,15,10,20,FR,France
+202034,3,6084,3090,9078,9,4,14,FR,France
+202033,3,6106,3411,8801,9,5,13,FR,France
+202032,3,5918,3330,8506,9,5,13,FR,France
+202031,3,4351,2269,6433,7,4,10,FR,France
+202030,3,8179,5442,10916,12,8,16,FR,France
+202029,3,8687,5860,11514,13,9,17,FR,France
+202028,3,8340,5701,10979,13,9,17,FR,France
+202027,3,4066,2406,5726,6,3,9,FR,France
+202026,3,4039,2389,5689,6,3,9,FR,France
+202025,3,2853,1488,4218,4,2,6,FR,France
+202024,3,3058,1690,4426,5,3,7,FR,France
+202023,3,4168,2468,5868,6,3,9,FR,France
+202022,3,3580,1947,5213,5,3,7,FR,France
+202021,3,6114,4026,8202,9,6,12,FR,France
+202020,3,9315,6775,11855,14,10,18,FR,France
+202019,3,11679,8722,14636,18,14,22,FR,France
+202018,3,16398,12851,19945,25,20,30,FR,France
+202017,3,18082,14454,21710,27,21,33,FR,France
+202016,3,24165,19893,28437,37,31,43,FR,France
+202015,3,41049,35377,46721,62,53,71,FR,France
+202014,3,71666,64531,78801,109,98,120,FR,France
+202013,3,107742,99187,116297,164,151,177,FR,France
+202012,3,107283,98610,115956,163,150,176,FR,France
+202011,3,101704,93652,109756,154,142,166,FR,France
+202010,3,104977,96650,113304,159,146,172,FR,France
+202009,3,110696,102066,119326,168,155,181,FR,France
+202008,3,143753,133984,153522,218,203,233,FR,France
+202007,3,183610,172812,194408,279,263,295,FR,France
+202006,3,206669,195481,217857,314,297,331,FR,France
+202005,3,187957,177445,198469,285,269,301,FR,France
+202004,3,122331,113492,131170,186,173,199,FR,France
+202003,3,78413,71330,85496,119,108,130,FR,France
+202002,3,53614,47654,59574,81,72,90,FR,France
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+200913,3,27737,20781,34693,44,33,55,FR,France
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+199608,3,19046,14850,23242,33,26,40,FR,France
+199607,3,23041,18338,27744,40,32,48,FR,France
+199606,3,21810,17153,26467,38,30,46,FR,France
+199605,3,25275,20410,30140,44,36,52,FR,France
+199604,3,43359,36948,49770,75,64,86,FR,France
+199603,3,54691,48016,61366,94,82,106,FR,France
+199602,3,105606,96106,115106,182,166,198,FR,France
+199601,3,223830,209274,238386,386,361,411,FR,France
+199552,3,397122,378252,415992,688,655,721,FR,France
+199551,3,749988,725434,774542,1299,1256,1342,FR,France
+199550,3,604926,583100,626752,1047,1009,1085,FR,France
+199549,3,375500,358200,392800,650,620,680,FR,France
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+199547,3,120472,110526,130418,209,192,226,FR,France
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+199544,3,13168,9820,16516,23,17,29,FR,France
+199543,3,16188,12389,19987,28,21,35,FR,France
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+199541,3,14980,10851,19109,26,19,33,FR,France
+199540,3,16245,11610,20880,28,20,36,FR,France
+199539,3,18499,13844,23154,32,24,40,FR,France
+199538,3,13123,9410,16836,23,17,29,FR,France
+199537,3,4895,2666,7124,8,4,12,FR,France
+199536,3,3659,1574,5744,6,2,10,FR,France
+199535,3,2496,644,4348,4,1,7,FR,France
+199534,3,1887,214,3560,3,0,6,FR,France
+199533,3,905,0,2007,2,0,4,FR,France
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+199531,3,1946,92,3800,3,0,6,FR,France
+199530,3,1898,46,3750,3,0,6,FR,France
+199529,3,2148,687,3609,4,1,7,FR,France
+199528,3,3312,1430,5194,6,3,9,FR,France
+199527,3,4853,2683,7023,8,4,12,FR,France
+199526,3,4986,2911,7061,9,5,13,FR,France
+199525,3,4571,2520,6622,8,4,12,FR,France
+199524,3,8058,5054,11062,14,9,19,FR,France
+199523,3,13820,9801,17839,24,17,31,FR,France
+199522,3,14124,9999,18249,24,17,31,FR,France
+199521,3,11931,8655,15207,21,15,27,FR,France
+199520,3,18846,14311,23381,33,25,41,FR,France
+199519,3,26261,21488,31034,45,37,53,FR,France
+199518,3,39231,33258,45204,68,58,78,FR,France
+199517,3,88640,79343,97937,153,137,169,FR,France
+199516,3,140488,129439,151537,243,224,262,FR,France
+199515,3,181007,169110,192904,313,292,334,FR,France
+199514,3,248704,235144,262264,431,408,454,FR,France
+199513,3,209839,197191,222487,363,341,385,FR,France
+199512,3,122434,112497,132371,212,195,229,FR,France
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+199509,3,39696,33259,46133,69,58,80,FR,France
+199508,3,38008,32225,43791,66,56,76,FR,France
+199507,3,30550,25479,35621,53,44,62,FR,France
+199506,3,37351,32007,42695,65,56,74,FR,France
+199505,3,27876,23218,32534,48,40,56,FR,France
+199504,3,27643,22818,32468,48,40,56,FR,France
+199503,3,24844,20391,29297,43,35,51,FR,France
+199502,3,23480,19249,27711,41,34,48,FR,France
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+199452,3,22036,17495,26577,38,30,46,FR,France
+199451,3,26912,21750,32074,47,38,56,FR,France
+199450,3,28831,23470,34192,50,41,59,FR,France
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+199447,3,15206,11578,18834,26,20,32,FR,France
+199446,3,14252,10525,17979,25,19,31,FR,France
+199445,3,12152,8448,15856,21,15,27,FR,France
+199444,3,11307,7688,14926,20,14,26,FR,France
+199443,3,11254,8002,14506,20,14,26,FR,France
+199442,3,14406,10653,18159,25,18,32,FR,France
+199441,3,14073,10341,17805,24,18,30,FR,France
+199440,3,15962,11850,20074,28,21,35,FR,France
+199439,3,15878,11643,20113,28,21,35,FR,France
+199438,3,15366,11100,19632,27,20,34,FR,France
+199437,3,5949,3561,8337,10,6,14,FR,France
+199436,3,2806,1133,4479,5,2,8,FR,France
+199435,3,4556,2358,6754,8,4,12,FR,France
+199434,3,3459,1444,5474,6,2,10,FR,France
+199433,3,4272,977,7567,7,1,13,FR,France
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+199431,3,5027,1580,8474,9,3,15,FR,France
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+199429,3,1188,0,2384,2,0,4,FR,France
+199428,3,1581,316,2846,3,1,5,FR,France
+199427,3,713,0,1459,1,0,2,FR,France
+199426,3,990,80,1900,2,0,4,FR,France
+199425,3,5431,3222,7640,9,5,13,FR,France
+199424,3,6288,3723,8853,11,7,15,FR,France
+199423,3,6440,1052,11828,11,2,20,FR,France
+199422,3,845,0,2449,1,0,4,FR,France
+199421,3,2197,395,3999,4,1,7,FR,France
+199420,3,2217,852,3582,4,2,6,FR,France
+199419,3,1483,406,2560,3,1,5,FR,France
+199418,3,3705,1940,5470,6,3,9,FR,France
+199417,3,2288,1064,3512,4,2,6,FR,France
+199416,3,5156,3176,7136,9,6,12,FR,France
+199415,3,6952,4678,9226,12,8,16,FR,France
+199414,3,4671,2784,6558,8,5,11,FR,France
+199413,3,3343,1641,5045,6,3,9,FR,France
+199412,3,4305,2412,6198,7,4,10,FR,France
+199411,3,5399,3327,7471,9,5,13,FR,France
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+199409,3,5635,3251,8019,10,6,14,FR,France
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+199407,3,14639,11188,18090,25,19,31,FR,France
+199406,3,17308,13395,21221,30,23,37,FR,France
+199405,3,18489,14290,22688,32,25,39,FR,France
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+199403,3,29882,24817,34947,52,43,61,FR,France
+199402,3,47402,41415,53389,82,72,92,FR,France
+199401,3,118119,108182,128056,205,188,222,FR,France
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+199349,3,898045,873419,922671,1565,1522,1608,FR,France
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+199347,3,241371,226769,255973,421,396,446,FR,France
+199346,3,76034,68003,84065,133,119,147,FR,France
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+199342,3,19187,14893,23481,33,26,40,FR,France
+199341,3,18285,14384,22186,32,25,39,FR,France
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+199338,3,10492,7329,13655,18,12,24,FR,France
+199337,3,7023,4503,9543,12,8,16,FR,France
+199336,3,4361,2445,6277,8,5,11,FR,France
+199335,3,5589,3066,8112,10,6,14,FR,France
+199334,3,2984,1209,4759,5,2,8,FR,France
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+199327,3,2574,918,4230,4,1,7,FR,France
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+199318,3,5027,3075,6979,9,6,12,FR,France
+199317,3,8111,5138,11084,14,9,19,FR,France
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+199315,3,22181,17147,27215,39,30,48,FR,France
+199314,3,38266,30865,45667,67,54,80,FR,France
+199313,3,62987,54506,71468,110,95,125,FR,France
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+199301,3,75288,67244,83332,131,117,145,FR,France
+199253,3,56622,49107,64137,99,86,112,FR,France
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+199251,3,41156,35024,47288,72,61,83,FR,France
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+199248,3,32392,27499,37285,57,48,66,FR,France
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+199245,3,22023,17804,26242,39,32,46,FR,France
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+199241,3,24091,19953,28229,42,35,49,FR,France
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+199239,3,13535,10301,16769,24,18,30,FR,France
+199238,3,9837,7106,12568,17,12,22,FR,France
+199237,3,7480,5130,9830,13,9,17,FR,France
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+199231,3,4233,1733,6733,7,3,11,FR,France
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+199221,3,5059,2889,7229,9,5,13,FR,France
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+199211,3,11689,7575,15803,20,13,27,FR,France
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+199126,3,6376,3324,9428,11,6,16,FR,France
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+199124,3,8223,4660,11786,14,8,20,FR,France
+199123,3,6801,3596,10006,12,6,18,FR,France
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+199121,3,6391,3385,9397,11,6,16,FR,France
+199120,3,8633,4683,12583,15,8,22,FR,France
+199119,3,7785,3986,11584,14,7,21,FR,France
+199118,3,10856,6457,15255,19,11,27,FR,France
+199117,3,15603,10950,20256,27,19,35,FR,France
+199116,3,15665,11184,20146,28,20,36,FR,France
+199115,3,15062,10715,19409,26,18,34,FR,France
+199114,3,27862,21583,34141,49,38,60,FR,France
+199113,3,32179,25829,38529,57,46,68,FR,France
+199112,3,27873,22312,33434,49,39,59,FR,France
+199111,3,46186,38876,53496,81,68,94,FR,France
+199110,3,88750,77784,99716,156,137,175,FR,France
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+199108,3,216369,198630,234108,381,350,412,FR,France
+199107,3,208836,191789,225883,367,337,397,FR,France
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+199102,3,29759,22044,37474,52,38,66,FR,France
+199101,3,42927,33706,52148,76,60,92,FR,France
+199052,3,41262,31607,50917,73,56,90,FR,France
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+199033,3,0,0,0,0,0,0,FR,France
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+199028,3,959,0,2252,2,0,4,FR,France
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+199026,3,7236,2651,11821,13,5,21,FR,France
+199025,3,7879,3136,12622,14,6,22,FR,France
+199024,3,5727,2460,8994,10,4,16,FR,France
+199023,3,3655,1043,6267,6,1,11,FR,France
+199022,3,4196,1292,7100,7,2,12,FR,France
+199021,3,1004,0,2367,2,0,4,FR,France
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+199019,3,5897,2440,9354,10,4,16,FR,France
+199018,3,1738,141,3335,3,0,6,FR,France
+199017,3,5278,2197,8359,9,4,14,FR,France
+199016,3,8129,3754,12504,14,6,22,FR,France
+199015,3,11707,5831,17583,21,11,31,FR,France
+199014,3,12862,8177,17547,23,15,31,FR,France
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