diff --git a/module3/exo2/exercice.ipynb b/module3/exo2/exercice.ipynb
index 0bbbe371b01e359e381e43239412d77bf53fb1fb..0be82d6496e3150eb422dbc9953e7e7198040788 100644
--- a/module3/exo2/exercice.ipynb
+++ b/module3/exo2/exercice.ipynb
@@ -1,5 +1,1464 @@
 {
- "cells": [],
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Incidence de la varicelle"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import pandas as pd\n",
+    "import isoweek\n",
+    "import os\n",
+    "from os import path"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Les données de l'incidence du syndrome grippal sont disponibles du site Web du [Réseau Sentinelles](http://www.sentiweb.fr/). Nous les récupérons sous forme d'un fichier en format CSV dont chaque ligne correspond à une semaine de la période demandée. Nous téléchargeons toujours le jeu de données complet, qui commence en 1991 et se termine avec une semaine récente."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-7.csv\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>indicator</th>\n",
+       "      <th>inc</th>\n",
+       "      <th>inc_low</th>\n",
+       "      <th>inc_up</th>\n",
+       "      <th>inc100</th>\n",
+       "      <th>inc100_low</th>\n",
+       "      <th>inc100_up</th>\n",
+       "      <th>geo_insee</th>\n",
+       "      <th>geo_name</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>202103</td>\n",
+       "      <td>7</td>\n",
+       "      <td>9306</td>\n",
+       "      <td>6327</td>\n",
+       "      <td>12285</td>\n",
+       "      <td>14</td>\n",
+       "      <td>9</td>\n",
+       "      <td>19</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>202102</td>\n",
+       "      <td>7</td>\n",
+       "      <td>7846</td>\n",
+       "      <td>5464</td>\n",
+       "      <td>10228</td>\n",
+       "      <td>12</td>\n",
+       "      <td>8</td>\n",
+       "      <td>16</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>202101</td>\n",
+       "      <td>7</td>\n",
+       "      <td>10531</td>\n",
+       "      <td>7755</td>\n",
+       "      <td>13307</td>\n",
+       "      <td>16</td>\n",
+       "      <td>12</td>\n",
+       "      <td>20</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>202053</td>\n",
+       "      <td>7</td>\n",
+       "      <td>11978</td>\n",
+       "      <td>8406</td>\n",
+       "      <td>15550</td>\n",
+       "      <td>18</td>\n",
+       "      <td>13</td>\n",
+       "      <td>23</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>202052</td>\n",
+       "      <td>7</td>\n",
+       "      <td>12012</td>\n",
+       "      <td>8285</td>\n",
+       "      <td>15739</td>\n",
+       "      <td>18</td>\n",
+       "      <td>12</td>\n",
+       "      <td>24</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>202051</td>\n",
+       "      <td>7</td>\n",
+       "      <td>10564</td>\n",
+       "      <td>7574</td>\n",
+       "      <td>13554</td>\n",
+       "      <td>16</td>\n",
+       "      <td>11</td>\n",
+       "      <td>21</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>202050</td>\n",
+       "      <td>7</td>\n",
+       "      <td>7063</td>\n",
+       "      <td>4744</td>\n",
+       "      <td>9382</td>\n",
+       "      <td>11</td>\n",
+       "      <td>7</td>\n",
+       "      <td>15</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>202049</td>\n",
+       "      <td>7</td>\n",
+       "      <td>5026</td>\n",
+       "      <td>3145</td>\n",
+       "      <td>6907</td>\n",
+       "      <td>8</td>\n",
+       "      <td>5</td>\n",
+       "      <td>11</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>202048</td>\n",
+       "      <td>7</td>\n",
+       "      <td>6683</td>\n",
+       "      <td>4312</td>\n",
+       "      <td>9054</td>\n",
+       "      <td>10</td>\n",
+       "      <td>6</td>\n",
+       "      <td>14</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>202047</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4999</td>\n",
+       "      <td>2963</td>\n",
+       "      <td>7035</td>\n",
+       "      <td>8</td>\n",
+       "      <td>5</td>\n",
+       "      <td>11</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>202046</td>\n",
+       "      <td>7</td>\n",
+       "      <td>3752</td>\n",
+       "      <td>1963</td>\n",
+       "      <td>5541</td>\n",
+       "      <td>6</td>\n",
+       "      <td>3</td>\n",
+       "      <td>9</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>202045</td>\n",
+       "      <td>7</td>\n",
+       "      <td>3696</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>5376</td>\n",
+       "      <td>6</td>\n",
+       "      <td>3</td>\n",
+       "      <td>9</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>202044</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4391</td>\n",
+       "      <td>2375</td>\n",
+       "      <td>6407</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4</td>\n",
+       "      <td>10</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>202043</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4376</td>\n",
+       "      <td>2505</td>\n",
+       "      <td>6247</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4</td>\n",
+       "      <td>10</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>202042</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4000</td>\n",
+       "      <td>1979</td>\n",
+       "      <td>6021</td>\n",
+       "      <td>6</td>\n",
+       "      <td>3</td>\n",
+       "      <td>9</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>202041</td>\n",
+       "      <td>7</td>\n",
+       "      <td>3961</td>\n",
+       "      <td>2099</td>\n",
+       "      <td>5823</td>\n",
+       "      <td>6</td>\n",
+       "      <td>3</td>\n",
+       "      <td>9</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>202040</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2078</td>\n",
+       "      <td>675</td>\n",
+       "      <td>3481</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>202039</td>\n",
+       "      <td>7</td>\n",
+       "      <td>1049</td>\n",
+       "      <td>237</td>\n",
+       "      <td>1861</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>202038</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2253</td>\n",
+       "      <td>782</td>\n",
+       "      <td>3724</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>202037</td>\n",
+       "      <td>7</td>\n",
+       "      <td>1584</td>\n",
+       "      <td>405</td>\n",
+       "      <td>2763</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>202036</td>\n",
+       "      <td>7</td>\n",
+       "      <td>919</td>\n",
+       "      <td>100</td>\n",
+       "      <td>1738</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>202035</td>\n",
+       "      <td>7</td>\n",
+       "      <td>828</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1694</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>202034</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2272</td>\n",
+       "      <td>371</td>\n",
+       "      <td>4173</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>202033</td>\n",
+       "      <td>7</td>\n",
+       "      <td>1284</td>\n",
+       "      <td>177</td>\n",
+       "      <td>2391</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>202032</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2650</td>\n",
+       "      <td>689</td>\n",
+       "      <td>4611</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1</td>\n",
+       "      <td>7</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>202031</td>\n",
+       "      <td>7</td>\n",
+       "      <td>1303</td>\n",
+       "      <td>100</td>\n",
+       "      <td>2506</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>202030</td>\n",
+       "      <td>7</td>\n",
+       "      <td>1385</td>\n",
+       "      <td>75</td>\n",
+       "      <td>2695</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>202029</td>\n",
+       "      <td>7</td>\n",
+       "      <td>841</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1672</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>202028</td>\n",
+       "      <td>7</td>\n",
+       "      <td>728</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1515</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>202027</td>\n",
+       "      <td>7</td>\n",
+       "      <td>986</td>\n",
+       "      <td>149</td>\n",
+       "      <td>1823</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1543</th>\n",
+       "      <td>199126</td>\n",
+       "      <td>7</td>\n",
+       "      <td>17608</td>\n",
+       "      <td>11304</td>\n",
+       "      <td>23912</td>\n",
+       "      <td>31</td>\n",
+       "      <td>20</td>\n",
+       "      <td>42</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1544</th>\n",
+       "      <td>199125</td>\n",
+       "      <td>7</td>\n",
+       "      <td>16169</td>\n",
+       "      <td>10700</td>\n",
+       "      <td>21638</td>\n",
+       "      <td>28</td>\n",
+       "      <td>18</td>\n",
+       "      <td>38</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1545</th>\n",
+       "      <td>199124</td>\n",
+       "      <td>7</td>\n",
+       "      <td>16171</td>\n",
+       "      <td>10071</td>\n",
+       "      <td>22271</td>\n",
+       "      <td>28</td>\n",
+       "      <td>17</td>\n",
+       "      <td>39</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1546</th>\n",
+       "      <td>199123</td>\n",
+       "      <td>7</td>\n",
+       "      <td>11947</td>\n",
+       "      <td>7671</td>\n",
+       "      <td>16223</td>\n",
+       "      <td>21</td>\n",
+       "      <td>13</td>\n",
+       "      <td>29</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1547</th>\n",
+       "      <td>199122</td>\n",
+       "      <td>7</td>\n",
+       "      <td>15452</td>\n",
+       "      <td>9953</td>\n",
+       "      <td>20951</td>\n",
+       "      <td>27</td>\n",
+       "      <td>17</td>\n",
+       "      <td>37</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1548</th>\n",
+       "      <td>199121</td>\n",
+       "      <td>7</td>\n",
+       "      <td>14903</td>\n",
+       "      <td>8975</td>\n",
+       "      <td>20831</td>\n",
+       "      <td>26</td>\n",
+       "      <td>16</td>\n",
+       "      <td>36</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1549</th>\n",
+       "      <td>199120</td>\n",
+       "      <td>7</td>\n",
+       "      <td>19053</td>\n",
+       "      <td>12742</td>\n",
+       "      <td>25364</td>\n",
+       "      <td>34</td>\n",
+       "      <td>23</td>\n",
+       "      <td>45</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1550</th>\n",
+       "      <td>199119</td>\n",
+       "      <td>7</td>\n",
+       "      <td>16739</td>\n",
+       "      <td>11246</td>\n",
+       "      <td>22232</td>\n",
+       "      <td>29</td>\n",
+       "      <td>19</td>\n",
+       "      <td>39</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1551</th>\n",
+       "      <td>199118</td>\n",
+       "      <td>7</td>\n",
+       "      <td>21385</td>\n",
+       "      <td>13882</td>\n",
+       "      <td>28888</td>\n",
+       "      <td>38</td>\n",
+       "      <td>25</td>\n",
+       "      <td>51</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1552</th>\n",
+       "      <td>199117</td>\n",
+       "      <td>7</td>\n",
+       "      <td>13462</td>\n",
+       "      <td>8877</td>\n",
+       "      <td>18047</td>\n",
+       "      <td>24</td>\n",
+       "      <td>16</td>\n",
+       "      <td>32</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1553</th>\n",
+       "      <td>199116</td>\n",
+       "      <td>7</td>\n",
+       "      <td>14857</td>\n",
+       "      <td>10068</td>\n",
+       "      <td>19646</td>\n",
+       "      <td>26</td>\n",
+       "      <td>18</td>\n",
+       "      <td>34</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1554</th>\n",
+       "      <td>199115</td>\n",
+       "      <td>7</td>\n",
+       "      <td>13975</td>\n",
+       "      <td>9781</td>\n",
+       "      <td>18169</td>\n",
+       "      <td>25</td>\n",
+       "      <td>18</td>\n",
+       "      <td>32</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1555</th>\n",
+       "      <td>199114</td>\n",
+       "      <td>7</td>\n",
+       "      <td>12265</td>\n",
+       "      <td>7684</td>\n",
+       "      <td>16846</td>\n",
+       "      <td>22</td>\n",
+       "      <td>14</td>\n",
+       "      <td>30</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1556</th>\n",
+       "      <td>199113</td>\n",
+       "      <td>7</td>\n",
+       "      <td>9567</td>\n",
+       "      <td>6041</td>\n",
+       "      <td>13093</td>\n",
+       "      <td>17</td>\n",
+       "      <td>11</td>\n",
+       "      <td>23</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1557</th>\n",
+       "      <td>199112</td>\n",
+       "      <td>7</td>\n",
+       "      <td>10864</td>\n",
+       "      <td>7331</td>\n",
+       "      <td>14397</td>\n",
+       "      <td>19</td>\n",
+       "      <td>13</td>\n",
+       "      <td>25</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1558</th>\n",
+       "      <td>199111</td>\n",
+       "      <td>7</td>\n",
+       "      <td>15574</td>\n",
+       "      <td>11184</td>\n",
+       "      <td>19964</td>\n",
+       "      <td>27</td>\n",
+       "      <td>19</td>\n",
+       "      <td>35</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1559</th>\n",
+       "      <td>199110</td>\n",
+       "      <td>7</td>\n",
+       "      <td>16643</td>\n",
+       "      <td>11372</td>\n",
+       "      <td>21914</td>\n",
+       "      <td>29</td>\n",
+       "      <td>20</td>\n",
+       "      <td>38</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1560</th>\n",
+       "      <td>199109</td>\n",
+       "      <td>7</td>\n",
+       "      <td>13741</td>\n",
+       "      <td>8780</td>\n",
+       "      <td>18702</td>\n",
+       "      <td>24</td>\n",
+       "      <td>15</td>\n",
+       "      <td>33</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1561</th>\n",
+       "      <td>199108</td>\n",
+       "      <td>7</td>\n",
+       "      <td>13289</td>\n",
+       "      <td>8813</td>\n",
+       "      <td>17765</td>\n",
+       "      <td>23</td>\n",
+       "      <td>15</td>\n",
+       "      <td>31</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1562</th>\n",
+       "      <td>199107</td>\n",
+       "      <td>7</td>\n",
+       "      <td>12337</td>\n",
+       "      <td>8077</td>\n",
+       "      <td>16597</td>\n",
+       "      <td>22</td>\n",
+       "      <td>15</td>\n",
+       "      <td>29</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1563</th>\n",
+       "      <td>199106</td>\n",
+       "      <td>7</td>\n",
+       "      <td>10877</td>\n",
+       "      <td>7013</td>\n",
+       "      <td>14741</td>\n",
+       "      <td>19</td>\n",
+       "      <td>12</td>\n",
+       "      <td>26</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1564</th>\n",
+       "      <td>199105</td>\n",
+       "      <td>7</td>\n",
+       "      <td>10442</td>\n",
+       "      <td>6544</td>\n",
+       "      <td>14340</td>\n",
+       "      <td>18</td>\n",
+       "      <td>11</td>\n",
+       "      <td>25</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1565</th>\n",
+       "      <td>199104</td>\n",
+       "      <td>7</td>\n",
+       "      <td>7913</td>\n",
+       "      <td>4563</td>\n",
+       "      <td>11263</td>\n",
+       "      <td>14</td>\n",
+       "      <td>8</td>\n",
+       "      <td>20</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1566</th>\n",
+       "      <td>199103</td>\n",
+       "      <td>7</td>\n",
+       "      <td>15387</td>\n",
+       "      <td>10484</td>\n",
+       "      <td>20290</td>\n",
+       "      <td>27</td>\n",
+       "      <td>18</td>\n",
+       "      <td>36</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1567</th>\n",
+       "      <td>199102</td>\n",
+       "      <td>7</td>\n",
+       "      <td>16277</td>\n",
+       "      <td>11046</td>\n",
+       "      <td>21508</td>\n",
+       "      <td>29</td>\n",
+       "      <td>20</td>\n",
+       "      <td>38</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1568</th>\n",
+       "      <td>199101</td>\n",
+       "      <td>7</td>\n",
+       "      <td>15565</td>\n",
+       "      <td>10271</td>\n",
+       "      <td>20859</td>\n",
+       "      <td>27</td>\n",
+       "      <td>18</td>\n",
+       "      <td>36</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1569</th>\n",
+       "      <td>199052</td>\n",
+       "      <td>7</td>\n",
+       "      <td>19375</td>\n",
+       "      <td>13295</td>\n",
+       "      <td>25455</td>\n",
+       "      <td>34</td>\n",
+       "      <td>23</td>\n",
+       "      <td>45</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1570</th>\n",
+       "      <td>199051</td>\n",
+       "      <td>7</td>\n",
+       "      <td>19080</td>\n",
+       "      <td>13807</td>\n",
+       "      <td>24353</td>\n",
+       "      <td>34</td>\n",
+       "      <td>25</td>\n",
+       "      <td>43</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1571</th>\n",
+       "      <td>199050</td>\n",
+       "      <td>7</td>\n",
+       "      <td>11079</td>\n",
+       "      <td>6660</td>\n",
+       "      <td>15498</td>\n",
+       "      <td>20</td>\n",
+       "      <td>12</td>\n",
+       "      <td>28</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1572</th>\n",
+       "      <td>199049</td>\n",
+       "      <td>7</td>\n",
+       "      <td>1143</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2610</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>5</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1573 rows × 10 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        week  indicator    inc  inc_low  inc_up  inc100  inc100_low  \\\n",
+       "0     202103          7   9306     6327   12285      14           9   \n",
+       "1     202102          7   7846     5464   10228      12           8   \n",
+       "2     202101          7  10531     7755   13307      16          12   \n",
+       "3     202053          7  11978     8406   15550      18          13   \n",
+       "4     202052          7  12012     8285   15739      18          12   \n",
+       "5     202051          7  10564     7574   13554      16          11   \n",
+       "6     202050          7   7063     4744    9382      11           7   \n",
+       "7     202049          7   5026     3145    6907       8           5   \n",
+       "8     202048          7   6683     4312    9054      10           6   \n",
+       "9     202047          7   4999     2963    7035       8           5   \n",
+       "10    202046          7   3752     1963    5541       6           3   \n",
+       "11    202045          7   3696     2016    5376       6           3   \n",
+       "12    202044          7   4391     2375    6407       7           4   \n",
+       "13    202043          7   4376     2505    6247       7           4   \n",
+       "14    202042          7   4000     1979    6021       6           3   \n",
+       "15    202041          7   3961     2099    5823       6           3   \n",
+       "16    202040          7   2078      675    3481       3           1   \n",
+       "17    202039          7   1049      237    1861       2           1   \n",
+       "18    202038          7   2253      782    3724       3           1   \n",
+       "19    202037          7   1584      405    2763       2           0   \n",
+       "20    202036          7    919      100    1738       1           0   \n",
+       "21    202035          7    828        0    1694       1           0   \n",
+       "22    202034          7   2272      371    4173       3           0   \n",
+       "23    202033          7   1284      177    2391       2           0   \n",
+       "24    202032          7   2650      689    4611       4           1   \n",
+       "25    202031          7   1303      100    2506       2           0   \n",
+       "26    202030          7   1385       75    2695       2           0   \n",
+       "27    202029          7    841       10    1672       1           0   \n",
+       "28    202028          7    728        0    1515       1           0   \n",
+       "29    202027          7    986      149    1823       1           0   \n",
+       "...      ...        ...    ...      ...     ...     ...         ...   \n",
+       "1543  199126          7  17608    11304   23912      31          20   \n",
+       "1544  199125          7  16169    10700   21638      28          18   \n",
+       "1545  199124          7  16171    10071   22271      28          17   \n",
+       "1546  199123          7  11947     7671   16223      21          13   \n",
+       "1547  199122          7  15452     9953   20951      27          17   \n",
+       "1548  199121          7  14903     8975   20831      26          16   \n",
+       "1549  199120          7  19053    12742   25364      34          23   \n",
+       "1550  199119          7  16739    11246   22232      29          19   \n",
+       "1551  199118          7  21385    13882   28888      38          25   \n",
+       "1552  199117          7  13462     8877   18047      24          16   \n",
+       "1553  199116          7  14857    10068   19646      26          18   \n",
+       "1554  199115          7  13975     9781   18169      25          18   \n",
+       "1555  199114          7  12265     7684   16846      22          14   \n",
+       "1556  199113          7   9567     6041   13093      17          11   \n",
+       "1557  199112          7  10864     7331   14397      19          13   \n",
+       "1558  199111          7  15574    11184   19964      27          19   \n",
+       "1559  199110          7  16643    11372   21914      29          20   \n",
+       "1560  199109          7  13741     8780   18702      24          15   \n",
+       "1561  199108          7  13289     8813   17765      23          15   \n",
+       "1562  199107          7  12337     8077   16597      22          15   \n",
+       "1563  199106          7  10877     7013   14741      19          12   \n",
+       "1564  199105          7  10442     6544   14340      18          11   \n",
+       "1565  199104          7   7913     4563   11263      14           8   \n",
+       "1566  199103          7  15387    10484   20290      27          18   \n",
+       "1567  199102          7  16277    11046   21508      29          20   \n",
+       "1568  199101          7  15565    10271   20859      27          18   \n",
+       "1569  199052          7  19375    13295   25455      34          23   \n",
+       "1570  199051          7  19080    13807   24353      34          25   \n",
+       "1571  199050          7  11079     6660   15498      20          12   \n",
+       "1572  199049          7   1143        0    2610       2           0   \n",
+       "\n",
+       "      inc100_up geo_insee geo_name  \n",
+       "0            19        FR   France  \n",
+       "1            16        FR   France  \n",
+       "2            20        FR   France  \n",
+       "3            23        FR   France  \n",
+       "4            24        FR   France  \n",
+       "5            21        FR   France  \n",
+       "6            15        FR   France  \n",
+       "7            11        FR   France  \n",
+       "8            14        FR   France  \n",
+       "9            11        FR   France  \n",
+       "10            9        FR   France  \n",
+       "11            9        FR   France  \n",
+       "12           10        FR   France  \n",
+       "13           10        FR   France  \n",
+       "14            9        FR   France  \n",
+       "15            9        FR   France  \n",
+       "16            5        FR   France  \n",
+       "17            3        FR   France  \n",
+       "18            5        FR   France  \n",
+       "19            4        FR   France  \n",
+       "20            2        FR   France  \n",
+       "21            2        FR   France  \n",
+       "22            6        FR   France  \n",
+       "23            4        FR   France  \n",
+       "24            7        FR   France  \n",
+       "25            4        FR   France  \n",
+       "26            4        FR   France  \n",
+       "27            2        FR   France  \n",
+       "28            2        FR   France  \n",
+       "29            2        FR   France  \n",
+       "...         ...       ...      ...  \n",
+       "1543         42        FR   France  \n",
+       "1544         38        FR   France  \n",
+       "1545         39        FR   France  \n",
+       "1546         29        FR   France  \n",
+       "1547         37        FR   France  \n",
+       "1548         36        FR   France  \n",
+       "1549         45        FR   France  \n",
+       "1550         39        FR   France  \n",
+       "1551         51        FR   France  \n",
+       "1552         32        FR   France  \n",
+       "1553         34        FR   France  \n",
+       "1554         32        FR   France  \n",
+       "1555         30        FR   France  \n",
+       "1556         23        FR   France  \n",
+       "1557         25        FR   France  \n",
+       "1558         35        FR   France  \n",
+       "1559         38        FR   France  \n",
+       "1560         33        FR   France  \n",
+       "1561         31        FR   France  \n",
+       "1562         29        FR   France  \n",
+       "1563         26        FR   France  \n",
+       "1564         25        FR   France  \n",
+       "1565         20        FR   France  \n",
+       "1566         36        FR   France  \n",
+       "1567         38        FR   France  \n",
+       "1568         36        FR   France  \n",
+       "1569         45        FR   France  \n",
+       "1570         43        FR   France  \n",
+       "1571         28        FR   France  \n",
+       "1572          5        FR   France  \n",
+       "\n",
+       "[1573 rows x 10 columns]"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "if (path.exists(\"incidence_varicelle.csv\")):\n",
+    "    raw_data = pd.read_csv(\"incidence_varicelle.csv\", index_col = 0)\n",
+    "else:\n",
+    "    raw_data = pd.read_csv(data_url, skiprows=1)\n",
+    "    raw_data.to_csv(\"incidence_varicelle.csv\")\n",
+    "raw_data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Y a-t-il des points manquants dans ce jeux de données ? NON"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>indicator</th>\n",
+       "      <th>inc</th>\n",
+       "      <th>inc_low</th>\n",
+       "      <th>inc_up</th>\n",
+       "      <th>inc100</th>\n",
+       "      <th>inc100_low</th>\n",
+       "      <th>inc100_up</th>\n",
+       "      <th>geo_insee</th>\n",
+       "      <th>geo_name</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "Empty DataFrame\n",
+       "Columns: [week, indicator, inc, inc_low, inc_up, inc100, inc100_low, inc100_up, geo_insee, geo_name]\n",
+       "Index: []"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data[raw_data.isnull().any(axis=1)]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Nos données utilisent une convention inhabituelle: le numéro de\n",
+    "semaine est collé à l'année, donnant l'impression qu'il s'agit\n",
+    "de nombre entier. C'est comme ça que Pandas les interprète.\n",
+    "  \n",
+    "Un deuxième problème est que Pandas ne comprend pas les numéros de\n",
+    "semaine.  Il faut lui fournir les dates de début et de fin de\n",
+    "semaine. Nous utilisons pour cela la bibliothèque `isoweek`.\n",
+    "\n",
+    "Comme la conversion des semaines est devenu assez complexe, nous\n",
+    "écrivons une petite fonction Python pour cela. Ensuite, nous\n",
+    "l'appliquons à tous les points de nos donnés. Les résultats vont\n",
+    "dans une nouvelle colonne 'period'."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def convert_week(year_and_week_int):\n",
+    "    year_and_week_str = str(year_and_week_int)\n",
+    "    year = int(year_and_week_str[:4])\n",
+    "    week = int(year_and_week_str[4:])\n",
+    "    w = isoweek.Week(year, week)\n",
+    "    return pd.Period(w.day(0), 'W')\n",
+    "\n",
+    "raw_data['period'] = [convert_week(yw) for yw in raw_data['week']]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Il reste deux petites modifications à faire.\n",
+    "\n",
+    "Premièrement, nous définissons les périodes d'observation\n",
+    "comme nouvel index de notre jeu de données. Ceci en fait\n",
+    "une suite chronologique, ce qui sera pratique par la suite.\n",
+    "\n",
+    "Deuxièmement, nous trions les points selon la période, dans le sens chronologique."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sorted_data = raw_data.set_index('period').sort_index()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Nous vérifions la cohérence des données. Entre la fin d'une période et\n",
+    "le début de la période qui suit, la différence temporelle doit être\n",
+    "zéro, ou au moins très faible. Nous laissons une \"marge d'erreur\"\n",
+    "d'une seconde.\n",
+    "\n",
+    "Ceci s'avère juste sur l'ensemble des donnée, contrairement à l'exemple de la grippe."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "periods = sorted_data.index\n",
+    "for p1, p2 in zip(periods[:-1], periods[1:]):\n",
+    "    delta = p2.to_timestamp() - p1.end_time\n",
+    "    if delta > pd.Timedelta('1s'):\n",
+    "        print(p1, p2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Représentation graphique sur toute la période de suivi"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fb8973f2240>"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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u7jkewGxe9HUiepOIfktEA3nZKACy59IaXjaK/1bLY+cwxtoA7AAwOM3YOhqZzqHrw0dksK15Px5uiqZrGjGDLf+y7yKbZh6l2S6Va7LZUfP6Vy8uxfLNzXjpXf84VNWAIJri/tSaf0caeBMHIuoL4FEA/8gY24lARHQYgEkA1gP4haiqOZ1Zym3nqGOYQURNRNS0adMm36G3CzrNlLWLTOb/e2Mtlm7cVfV2fRczH8bSp61vPPAG/umRyNGuHD2FDu3xmGzEKFGXV/3Fnxanek4dNb2EsUChw8PAxu9httkyw+vJEFEdAsLwO8bYYwDAGNvAGCsyxkoA/hvAFF59DYAx0umjAazj5aM15bFziKgAYACARHQxxtgdjLHJjLHJQ4cO9bvCdkLniZU6pdsE/vHBeTjnly9Xvd1qLk4+bW3cGVeazkshugn7SX2G/VzTBiAN5yBHZf3sf8921JbH0zETTPigzF25Da+t0AcSbA+IexiGNO8im62uCB9rJQJwJ4BFjLFfSuUjpWoXAXiL/34CwHRugXQIAsXzHMbYegC7iOgU3uYlAB6XzrmU//4UgBdYF3tqXUUB0tE6h3c37MJnfj0Lq7ZEYanb89FU8/rKaemS387xrmtbrH371t1L0y1IMwflsXWUSW8aCGOBu19dgYtvn9Xu/bUWS5j6i5cwc1GQblfcn8xayQwfzuE0AF8AcLZitvpTbpb6JoCzAHwLABhjCwE8BOBtAM8AuJIxVuRtXQHgNwiU1O8BEDGG7wQwmIiWArgawLVVuboU2LGnFS+/6y+q6izS1dGT+ZG5azB7+VY8uzBKU1ot0YsO1Wy6M7cXvgRUV6saBJIMv13oOLFSxz6cbc378d6mZml+ZWE0XHB6SDPGXoF+fj1lOecGADdoypsAHK0p3wfgYtdY2hPfeOAN/PndTWi6/hwM6duQON5VplBHz+Uw3IC0asuhoauOahIHj8bayyau2qImoDyxUldFWm5m8fu7cMiQPqgvlKejMOmoukH4rU5D5iHNIWLLbPU0rav2Iu1rUtfhOx1hEiktWS2cOKjv21ML1mO3Z5IbE6p6fZ1A0dX8CC7o6pnuQRqF9LLN5Xlcd9T0SsN9vr9jH87795fxvScWlt2fOldDsVLGORiREQeOfo0BE7Vzr18grmor7vZ77qQ6mjjoFiTBOdTno+nz7oZd+NrvXsd3Hik/xDaQfj33ySHdGfCfH/46h45ARymk04hHRXC8ShTX6j0VYr9M52BGRhw4xEIny0K/fG8Txl77JABdPofq9u9LHMYN61vdjj0hX6+OOIi0mGs4B1YudMSvXAV4p9o0VNC1adgdsXB31C1LJyILvivZGKlzoT31Zj0FGXHgiNIkRmXPvb3BXL/K/bvk+CccdAAAYGDv+ir3bIfuJRaseFqx9mOvr3HW0ROHdP10NCoZXxqxUrnrWZpgAx11q9NMndAst4IFXRUfiaa6mFFkl0JGHDjEC+kvK65sUq3bvhezl0WJ6V3EQTA0HSlWevW9zbjtpfcS5eVe+9UPzXdX0jSt681ncdENs5pRWapiypri3I549j7P9sXFG7F66x5nvWpB9tkoF6r4SBCajIEwI8vnwMHC7+Rs2by7JRSbqPXLxVk/fylU7AJu4sBSEq9q4L5ZKxP9A8lrl30gKoXuZS0xhnwZniadqnNoB4V0uc8+lSmrR53L7noNhRxh6Y0fdVc2IA2RFsShEv2Aeu9EDK3OcmbtDsg4B47whdTMlck/fh4z34nHgKl0kW5RiIHLtC/kbCrrtmzI1yv/fvGdjTjjZy/i6bfeTx4sp58qKmg7ipBqx1zBk2KGqTCoT3kixTQj8b1nHSmzf2/zbgB2rubNNdvx4Zv/bLSWUwnLzr1BvcyU1YyMOHCUzLTBgPJfjp8/uzhRphILFWGO3w6kDjGCED8CINj9vb1+J4Dg5UyD9Tv0imvdmlPOQrtldwteWtzeQd2Su9806TmDev6ERWwQOssooVIUSwwbdu4D4M/NzFy0AZfd9VpwvuWm/uzZxXh3w27MXblN37dyrpi3Gd9gRkYcBJiQQfpNl0oW6V+9uDRR5rJWijiHzp/O8rXnUtr1C3z+N/p4PzqlYzn3+sQfP5/a1v/IEf3Sd2RAJToH06b8p88Em4q0Wd7SVW+/+fWzZxfj5BtnYuOufVZ9zbML38fYa5/E2u17sVx6hjZmpYE7x7W0FrXHTVxHppA2IyMOHKHOwXfHV+X+3TqHdurY1qfUme6+BPmeRd102LzbP45/R72/5XoVm+5NueeaNig7uA9O2nGmUWSbqu7Y24q9+/ULry9e5KLZLY5n/3BTYNW2cO0O9G+sk8Zmvo6GQpBPbMZ9c7VWcaa9V0YbzMiIA0damX7VPaQdDXaGziEuVtIrpElXqG3Lb+RaU9Z2vGpZMZpPuSVvt9AbjstNa3GVRj9gqnncD/6EM3/+olcbJpNTedi+3t59GyObGSvnUBctZdc+uiBx3KTMzmIrmZERB45Ipu+746vupHI1F5nadv5klocQcQ72cVVivdNhnENaeY0F/hyoToxmP7mQcpwtrf5aV1vXG3b65YT+v3lr3ZU8L0HmkmzWSnVSXgidbsJoAeY3jJpERhw40u7Mb3z6nar271pMQmOqDhUrJfsPyqM/YgfoHL/63+jo5f9iVxv5lLShKsPSipXsp+RzhC27/RZqwN/7HqjO5sM3PpllFOGvGLdh9SuJztEREbNjob78tRVb8VDTau2xWkFGHFR4vhvzV6dPCmODawEUu6HOctrREQoi8tY5+IuV7H1XCtv6n1asZENFXtOaK94nKVrnrd6OE3/8PF5fpbfMqQSuYb/h0afPRsfnThP5hxp09WnkOgzFF98+C9+uME6YiuWbm8M8Ft0BNU8cXn53Eyb+6zPYtY/bPXeS2MZf59Bx4zPG+EmhRA3P8e/VexzVRlpFr656mGHMN4e0pky3jn3m18mEOO+sr36aVte9vujWVxNl727Yhbkr0wXFK0dfYzvFdbdT0oaqY932vTjr5y/h36oscWhP1Dxx+MVz76J5fzEM2d1ZIn3n5O4EP4cYYh7S0W/VlNUkl1bHbboMLeeguej2UAZ3BuegJbSamzB/zY4KR+SHcjYfH775ZXzytoh4OfVPKfrwVb776ux8ywV+8sw7WLmlvPDnMoSo7W9SyJyujponDoloq50yCrfYpaMV0Ss2N+P5RVHgQZP+QRUrvc+dnFRU4j/SnpcuP/9yiYNueL5Dvn/OKmedpRv1HEK7WEtV4V6bnpe80KfJTaE7P9GnY+DlWivd9tJ7mHHvXPfgeiAy4qDMt86yBnLvfEQ9e8XZy7bggz99IQw1bsKOPa1YZwmvfdGtf439f9OwcxW3r1o6GL0pa8cgrYmoVczhOY+eXLA+Uabeg3N++XKaYVWEat9rk4zd91bL98J6Spmcg89j6oo5uDsCGXFQ/ncW5+BSNPtaU33mjr9h9VZ3ToUzf/4iTr3pBePxbXviSY/+LOXX3rYnskbRLajakBCeNzattVI1iXlHJtbcs78Nry7drD3me0ldNRGoPPzv/6H87G1A+U6p6rwwxVDyab95f2XZDdP211XgJA5ENIaIXiSiRUS0kIi+ycsHEdFzRLSEfw+UzrmOiJYS0WIiOk8qP5GIFvBjtxBfWYiogYge5OWziWhs9S/VeH2x/5318NwK6eC7WuNTF38f3DJzCQDgC3fOARDs/rT5HnQhMNTXN4Wyu13FSp6mkjqEu/4yuJ3f/GU5/t4UQsTzgttDrFSNey238eI7waZi+579IRfBmP/Y5UXeasqqDPwNhZM1xWXy2VzsqdAzvLvCh3NoA3ANY+woAKcAuJKIJgC4FsBMxth4ADP5f/Bj0wFMBDANwK1ElOdt3QZgBoDx/DONl18OYBtjbByAmwH8pArX5oVkhreuKVYKQ3Z3EG+jexF/9UIyJpTufdW9iL4KaS1x6KBrLuT8GekNO/dhu4XAup7nmm3mMOe+5srlyO1dqMa9jhks8Fs66YfPYcnG3WG579hnL5etoGw6hzhUkWklTnC1mkrU+TYwxtYzxl7nv3cBWARgFIALANzDq90D4EL++wIADzDGWhhjywEsBTCFiEYC6M8Ym8WCle5e5RzR1iMAppJOXtEB6KoKaTG5O3We6p6I5jHpWHjfYfuG7G6PyVGXwgvONTvXOtKl2hfH6IJ3lMHhVYJq743KIWDyGO5+dUXUlqUpNUSI+p6YQnr4cGltxerdlO5EZlLpHLi453gAswEMZ4ytBwICAmAYrzYKgOxauIaXjeK/1fLYOYyxNgA7AAzW9D+DiJqIqGnTpk3q4bKQVEhXpdnUcHUrdi9dTWape1/bNNShIie4Drrm5WmiuDLtz1Bc99X77BYuNiZFvgffe+Itc8X2ECtVow2NNZsKn63fvbNWePe5bFP82anEwGyt5G67tQpJHzpnq1sZvIkDEfUF8CiAf2SM7bRV1ZQxS7ntnHgBY3cwxiYzxiYPHTrUNWQvqDubzgqJ7XQiCw/7j68SEZmWSdCVaQor4Rw6OvCejHfe93cqc42opc0lpzavFvI92FJxKIp0qLZYtZxIt2IEf1miV9jroFoUJdKCptBxlVOnJ8KLOBBRHQLC8DvG2GO8eAMXFYF/i8wqawCMkU4fDWAdLx+tKY+dQ0QFAAMApHO5LBftxDl84ta/4jSNNZA5ppC9vbQ5rtPWLQcEvdjAR+dggt772lLfr9kQ1drBVepJb1euRr9tQfOquRn90QUTg76r2CZQ3THaAg6qR1RiYTZlrdGV3wM+1koE4E4Aixhjv5QOPQHgUv77UgCPS+XTuQXSIQgUz3O46GkXEZ3C27xEOUe09SkAL7B2fGqfuu1V/BdPuNNepqyvr9qulTubQ1JU31qpnAXMNg41gBsDsF+zQ9ay8KpCOsXL2hVfYNeQXDtmm7+d/Nz2GpLXAOn9MqzjEQOqirWS3cKIsXRcgUDBohNS+1Hnqjwnzzg8kjr4XO7gMtOz6rBrXyuWbdrtrtgF4MM5nAbgCwDOJqJ5/PNRADcBOJeIlgA4l/8HY2whgIcAvA3gGQBXMsbEDL8CwG8QKKnfA/A0L78TwGAiWgrganDLp/YAYwxNK7fhZ5pUneK4DZW+j2msdGSI3XgaEYtujd7XWgyTrqhoK5ZwyHVP4WfP6uO/qGMslRi+/4e3k2NNERUz0YdHvzLunbXSq10fTDywf+z/yAGNxrquqyECrn30TaMzok1RK1+vlTg4xpAGYRiUalgrxXQO1RtlnUVRo95PNXmWPP/qJMrsMy/POWq47xCNEONbs20vzv7FnyturyNQcFVgjL0C8zycajjnBgA3aMqbABytKd8H4GLXWKqBnfviDi3q1HDNle9/fCK+94TdsWexRXZtNqmzdyzbiPtC1+YP/rAQ98/RhyIWwQf/52+rgpfaWw8Sh1as5PgvUK00oTKmHjkMMw0EUV67vjF1PL4iKZJty5rJ+kWgtcjwwGvmkM++YqVKs6/5Il9mulcd5CZ0HFK5BCgN55C0Xor+y+34kK40yZJM6ArpfdOi5jykE4oq5b/tIdYXcjjziIAlHT2wV+yYkHFubd6P8/7dHO7A9PLZDCJKJRaJlczVvPp6d4OZpd3dEhCHvg3OPQMAYFeL3nNUv8BXYK3kuOqx1z5pjb1/0yeP9eq73DShLuiu3daXvJDts4qV/Mewx+HlG8bIqvIapuOQyu0jjR+K+p7LUqZCPt2yZ5u733v8Lfzr4xaLsrCN+P8bn1qUagydgZojDuqDVne5tombJ8LBg/tg9MBemHLIoLD84abVGP8vT2P11j3Yvc/+EpoWOht7K4+xUp2DbRckwgT0acgb6/hA7yHtB18/BxW22Pu+i6i6ZuhEImf9/CU81LQ6nvzIMb4WR35wFf46B/82r3lovvV4faF6S4HIdQ3ox1juTjyNH4q6QZH/y2IlH7GX7d28Z9ZKL9Gm2sQdLy9zntPZqD3ioPxPcA6WeSvmVI4oVu+x14O0iCu37HGHKzYppC3nyIttGuWsrqot2cg+bhnTUMhXJM/WvfwJD2nDZTwydw3+MH8ddu6LFpiKLYOsx6Kj6m5ed6+Xb26SrTsyAAAgAElEQVTGtx95M9WYdLt/e1azCDbiEDvHMZ5F623W50ADJw7VYBzW74gMMXTDsnFDNqTZ8aubvrhYKd2y5+MD5xL/qfOlmsS4vdD1R1hlqJM1wTlYzhUWHTlSWH9usdNYl/MIg2EqN58oL7a25lXRgZZzsMx0Ub9S6YqPr4Jp0Xvs9bW46v438E8PRzvdShcsX6VogjhY6srH/vsv9l1g8/4iLr79VbwiWejYFdJ+nGI1w2c0FPKJvsvF/raoDd1cKDdWUZqQ6gknOFkh7dA5uETPOlzxO7vTo3ofetdXxp13BGqPOCivvLqRtu0IxeKRI4rJxsWOu7Eu706Xaaihdrt66x4c/8M/YdWWPSgW5cXC3EPTingKR92c1nkvq2NIs+TobM+19zDlmrN+R5QXQhs+o2wKZj4vyTlA+a9/Dmu22UNlrN22F6+t2IZvPTRP6stc33d9lodb6Zpu4xx8CcYX7pyN/5y5JJYHRAdfbkhFfSWcg2GB1zpxWrgOE15xmOaq3beXfquaqDnioM7+xKSx6Rz4G00K59DCJ3shT97+Cq7yh+euwbY9rXjsjTUx931T6zv2tuKS386JF2qJg+9+2A8+IiQAeMFgLWSCvPiXs5uVd5m+/ICq75QJ+aZdLfiBZLabRmyeVqwktz1+WF+vPird7wsxR1onRBl/WbIZv3ju3cS41Of3jfvfKGeIVpGtuoAnN33R71aHnCghXfC4AQf0rnPUSE9wOhs1RxzUR5IUK9k4B/EdJwL7JTNTJ+dgmBRPaZK+iDbjOgd9uzqZp24CtlqUo3H7dGM1J3T9/vavy63nqCID+W85r1EhpnSMyjfvNoejOGRIn9h/eU047aYXYkHg0oxKt1O2cT7y/RvaryG8F74K2evPPypVf0AkVtJdVyULWTmE3ewgaTsn/j9JLPxEdUByDfAhji6Rl28gwK6E2iMOjodkV0hLYiVpjRXnlBiziiIA85LyipL4RZ5qvjoHFbqX2pbHQa5diTy7nN2n+nLlY5xD+jGUk/Jz5IC4ebK8oKget2u369Oh6pBaIc3iv/O5aN7JkJ+vOs9+ajDffeEdvchH2P7rn135C9n+Yqlq5rG2cdiIARAn0O6UvP79ms5JjM8z1lNXQu0RB1XnkEIhbRIrhbkWWLKFhNTK06pRzs3so3PQhikA8NqKrXh0bhQM1ybvjS1KFQgqtCoHx9uj6i7k66ncWsnfeUqGzbLrUkmE96HD7UEgdfGRbGPaJVlqMbCQKKj3KLZBkdsmwqdPGqOV0evCVnztzMMSucCjPhju+usK41hd2Lu/VBULqLGDe9s5B+W/ShzM1m9uPwwv4uA4rjrf2nR/XQW1Rxwc8kTbPBD26oFCWi9rd7bv+aqEiwdjsYmUlnO4+PZZuObh+WgrlvD/HrbbuldLDqr1VXCckyQOlXEOjvffC772+P172eXN+zTxp2xEaYbkpc1YdG9Ubsj5vAxxjVR8e9qR4XxTjz+5YD1uelofTsUH+1qLXqKlTbtanHVsrbgW9J1726Rj8nm6uWrnQnz6l/HY62vw5XubUrfZ2ag94qD8T7J75oe2lYdPrsuTVtTzoyffxhur4ukJ1fbSLnQ797XFTP/K9XNYvGEXHpm7xlxZqV8JndDOe0d7qu15XOeQPNmlE5HPKVd/Ip5xpfJhrVjJ81zGIhPqfI7iFkpKPbXt2D3kFUzitohziF+ry7PaBV+fhn972u4xXF/IWee+ekwl7C2yWEkq98pa6PX49ZV27G3FjU8liWs1QnK0N2qPOKiySeW/T4KRhkI+NulFE3OWb8W3H4176pbDosq4+9UV+NTtrxrbs0Gu26/BZU0RXxhMOXdXeCTE0b3ErutOKqTtnEN7G3tMGNk/FCup+obkWOyD2acRK8nXN7x/A44Y3k/fNlh4b/K5XIzDipnWahan2D3k30biYBi7fGlXnHmYoZYZnz/lYC9uNy7SjGPK2EEY2q/B+sxdCl/5nywu9PHm99nl6wwdFq7bgeN+8Cds3p3kirqBsVItEofo97HffxYbdsYfnC32kEBDXS4WEsEmKkqj05Ah7xDlxcU0qXQvtw8halohpc3w4BzO/PlLzjY9InYH9aSKeWV7n89VT6xUDuNQyAe+LKUSS+QGSPTlaEtvrRT9PmJEf1w1dZy+bQbUhVwViy34pjVLVMnH6gaVXfb1tns9dnBvXHPu4dbzZRRyhN71+YoXwo8eMwIEvShXwKWQlgnp0H4N0XkeccBMGyUVt74Uz7G+YrM5T3h3QM0RBxmqkkiFKblIwDm4F2zAX6ykmlGakC5kN9P+lvGp22eFi1+1NjP6nAzJevLLZLMuSitWenPN9hjxtplxmo6I8bSVWCL8s2aAIU45dFDisM7MWB2TSUHNEOUT2LmvLTYn40YRcluiDySOm/zITAppGYVcDoP7NlhqJNtk8JuzNu5LiNN8dQ6jDuil3ZSNHdwb//ulk/HtaUeGHso+EYTnLN9qNU4Q+Okzi2M5XNy+D10bNUcc0uxiJo4aoC0POAe9DDPRnzKnfJPcmBatZxfavU/jbUa/bbuuZh5dtVqsrl7lkCxdtD4Kba46oMlWNWnFs8+97X+PTCiExKHkdpqSrm14/2QOCB1xUPUBJtrIGMPgvgFxmHzwwCgpD9z3JafhvlQOLYJQSJs53UKerJ7dyRbJe07ZquVyBFKiEiTOlzrK5yjGEWza1YLH563Dii17cOq4IejbUMBzV38Ix44e4J2zfOVWPy5A1m306gYhMmyoPeKQZn9smNmNhbw1faMMX7FSJesyYwzPaUIWxImDu52QgFTo2l9OTgbfWEO+7cXbTo8R3OehtcicZoeusYiNhDwO9RwTd1NigSjo+avPwB2XTMbRB0YbFrNZMyX6C8VKDoW0DXX5XLqpQcH75vOsXHVyZK8kHwlin0X/T71pZqL+qAN64fRxQ/TGBpqiZkN4ehu6g17BhtojDmlog6E8n/P3uPQVK1UykZ556338y++TMeVtTlK6vqsmVrL0YYJvlFIBnZJQjgbq27YJkw8eGPZT6UvuE9XTyDkgWOzHDeuHvg0F/PqSE6NjUrs6bkmn1DfpHEipp5YDATeVxjmSxAVUiFKJgWDf4MhzPUcU69bE+eVzZBArJct8uVe5WldMb5sGtUccHMeH95eUVYaHG0w+v4XX11RWnZBqjBob3t+p99aN6xzM54tD4jrmr95uruwBX4usJw0hQ1TomtP1MXvZ1mRFlOftnZPESi64LlfLSSnnG/UijMVG378xkmOLe7BrXyuukuIViaZyin6iWGJ4z5C/WPSvzkP5X10+l4oNC3UOPpyD/Fup31ZiXKzk3uCIfn3moAi9r76/undF1977O+xe8t3AWtUKJ3Egot8S0UYieksq+z4RrVVySotj1xHRUiJaTETnSeUnEtECfuwW4rORiBqI6EFePpuIxlb3EuOwLeSD+9THXj6jZRD5P3jfuH6VbDKM3Ij025adTkx81xAG+SZa93y5Yqd4ypMF2ise/h+vOh2PX3latJNn7mcT3yjEjzUUcnh91TYkoJih2jkH/TExt9Q5pvVzAPAfM5fg8XnrtG2ZOAcZ9YVcKjIb6Bz8JratXrEUmPPqLJBESt4SAz49eTQW/XBaIvaZCcLowGbZZCv75XP6PPQC3SG4ng0+b9jdAKZpym9mjE3in6cAgIgmAJgOYCI/51YiElqZ2wDMADCef0SblwPYxhgbB+BmAD8p81q84FJ8ieP/+vhbWLguniBlAPeEJSXZz5ZmczA31cZ51Ra9Yqsi4mAq92w03Nlaqo86oJczTETYXhnEwbor1JQ1aIiDWETlBazp+nPsYiXl4NGjBuC4MQeE4pcSc+upbDb6LW2lWPhxXT3GzNZajJlFQeL5mgiLKlZ6faWGSHH4pAntVZ9PFSpdpCH3slayHGsrsYTjKRAkhjrv31/Gi4s3AmCoy+f4GGFNuysg7rnPBu4nTycJwUNNSadSOX98N6cNbuLAGHsZgJ5fT+ICAA8wxloYY8sBLAUwhYhGAujPGJvFghl9L4ALpXPu4b8fATCV0szAlLA9sLy04xCp/xrrolskfge6saDeuxt2wYbvKE5xs5ZtSTvkEB8cPwR9NBYQJiLgy90IuavtJc7nUuwCyxA02zmH1M2FGJLC9FKGWHB1wRRtWLrR7ScDxK+ptVjC6eOG4IPjhyTqlRSxknoM0CxmUoDIqD9mdeYKw2dYxtmnvpCSczCLlY4/6AClI3M7xRJDIZdLmJOKzduyTc0oMUmcpoh9jeOTnnFsKJpT56yIL4EtmpAoAPC1370utdO9qUMlvPnXiehNLnYayMtGAZAzva/hZaP4b7U8dg5jrA3ADgCDKxiXA44FUCm75ANj8cerTgcQOSPJCq9dDl+J3YqVQ1uxhLo84f4vn5Jq1ECQ7MTXIQfwZ2vFomHbbakWIDqYdmJAZP1jQhoHJ6D9d2UUcg7uZUYc37SrxZmOMzonarWlrYRCPocfX3h0sh5zi5V87kWJMevciTgHc53efFfuC8Fh61q87LRDvNsplhgKeTIqlgNldeQg6DJ7FRBmveXEP9tuiW4s0ON1DgbcBuAwAJMArAfwC16umzrMUm47JwEimkFETUTUtGnTpnQjFg3bOIdc0tNmcJ/60F5ZEAdfhReQvLhgh0OYOKq/Mi53e/WFnLddNgDsdhCucEycKNhGQJQknCoEcdBdy6TRep8RgapyDqqDmWVBMx0SC41OYalCHDYpe23nAFH8IV1uY2YZZdiGMrwXuFmz7DsS7OArW60a61ISB5gX2jQcSFuJoT6fMxoHCPFVFFLf71pDnYNSd/VWe2Y/ANi2JxIlnzZOv5etJLJxV0BZxIExtoExVmSMlQD8N4Ap/NAaAGOkqqMBrOPlozXlsXOIqABgAAxiLMbYHYyxyYyxyUOH+sm/E21Yjuk4h171+TDvski2IqwcAHdgMVVCJhye0uQrFqjL64OPmSahb67eUDzh2Fm6Xri8tKCqcAUas+scdNesG6PJTLMMayVJ5ODeAQYVWlye1IkzAghv+zqN8oAxZuEc9OLAlVyvdfIh0aJVKvlch0asJJX4JhsKQWbimpz/5sEVSyUt5yCu/wd/eDvmaOhrMBLqlZTKn7ztVV31GLZKesaJB+o3PjXJOXAdgsBFAIQl0xMApnMLpEMQKJ7nMMbWA9hFRKdwfcIlAB6XzrmU//4UgBdYOwrrbC2LHYcsT2ysy4eWMXKICzExXQuw+mIL9ld9zXyuuL6Q0wcKM5zrSxwinYMZDh8kAJFXsd5O3EUczMd8Z0N4T5UTytFgyQppF+kW3aXpRh7iYUODeWVSStu8p6MxRhBE6oaLjsbJhwwK+7M9g/AeSVXe3bALD0tK13yOUuU+1jSZ7E/UsdzithLDnpYitjbvj2VMlM/ZXyzFknFVYq3kgz0t0btlym3d3a2VCq4KRHQ/gDMBDCGiNQC+B+BMIpqE4LmvAPAVAGCMLSSihwC8DaANwJWMMXEXr0Bg+dQLwNP8AwB3AriPiJYi4BimV+PCTHApXdtKDF+6J4q93lDI4ZAhfXD7508M2cecFOjFFZQtmb0rKEuzcxIwipUM9X29OsXOyTaXyUPJl8+LnVjymO0F3Nda1EauFNCNq/11DsG3j0JaHHYtnDGnRDDUF3K47x+mYMKBgYhRJ1YKFNL6diOdQ3yAYnPTUMjjiBH9MHv5VjDYCbDOz+HDN8fNn9Nm1yO+SOvun9qU7R4XiwzruIPjrS8txUePGZkYa9Bf1K8f5xB8m+pef/5ROHRoH/zD3U2JY/KzNJlVd3eFtJM4MMY+qym+01L/BgA3aMqbACQ0boyxfQAudo2jWrBzDoG4SI7rI/QM044eEZbJOgfX7uDQRF7iQEyQZuckIHYogaghbqaog28s/kjmah5EzsM8MOIcNH1Yzn3CYHsvoBcruW+YzrTVF5HOwd2T7w6xWdptggXjOvnQSPSjC/RoV0jrOb7LTz80/E1SXZtzo4+fQ57HOPJFuIfStJkQt1ru8ogBjVjFYxvJO3Z1rLJ/h88zEe+2aYPXt6GAwX0iazf5vZNbNxMH5xC6NGrPQ9ox+dVJqmMZZb21a4cidoVy/zmiJHGwNwMgkvn6Wlfs94nbILVn3VlCH2pARiSKSdZ79HVzoiHX8uvL9auRRSksT08eSNpVOjkHsYN3XIe8CDEkF/2CRqavqydgslb6+HGR1Jcsz0SGT1TWvEYcam1TMzb5mIx33tebhN/++RNw2WmHoKEuMApZJuUTUedFQ8zU3D2+ftzhVU4hKkPl8OU2Za7ALFZyj6Ero/aIg9OWP15Wp3W2ilz5XayjupCXDAppGSZzSLFDSTjtGIbgE2ZYPt8uVjJnRBP2+SHnoFRzcTCuKKqvLo3nPW5pK1qzs4U6gArcZWLWSk7i5SauQFwpzzTiooIamtZQTz4GJMenb8c+NlOaUBlqJjoXhCjSlYgIiJToQPydOW/iCG9xVmMhH7btw1kKp9YdJrNUilt8mUKk69YItb4PGGN48LVVRh+KjkbtEQcX56ASB81uTpjOAe4JoFrpCIV0QucgVXv1Pb2jnGCDfSedbypC8TLaXiiipIeqSJoSKgINpqyX3fWatf/nF220Hv/1y8ti/4+4/hl89/GFxvoJWbS1dT18neD6NUSS2bQpXNWFNp7gKBIZWcIuIaxkaCdR14CIc7DPAV/eYfpJY8IdvFbnYFl59mtycRjIY+xfY11EHHw8pPs2Bs+u2bR5YfpseurvBgPnoJsPtigDT7/1Pr7z6AL8+/NLjHU6EjVHHGzQxbrXsYxynHrXJFR378LPQe7p05NHQ55upkUm4hz8FiGTLPU/pk+K/Q+tlaxipSQXJCxhxGJk0jnMXu7rYF8ZxF1VFzCrn4PhWMwJznJfDh/RT+Ii/cfKoF/wRFgQmZtTOaDnvnVGOLbgO96GrLvwWfQhjcWXiNgwemAv3HDRMVKyn3RwpWUVULM4NnJ/JF8/JNc1FxkzipXk9p3EW8LRin+TjB17Aw5mqyblaGeg5oiDWyEdr3DcmAM09aKXzeX4pNpmCz8HeUIF/guOgQOoy5nESvqTTcShTiF4wo/DNIQR/RuRyyWJg7poCc6hs034xLOpROfgK1bKSVxkGqcn3aIPAF87cxxvS9RLhs8YP7xfzHJN7Tev011ohvadaUdi3r+eG/zx0DlI1azoXZ/nGwZzsp/3d5it03TzVvcIX3gnznE2FiInVZ8p6IonVSzFAyKaAiz2a9Tb9egY92+dczgOGtQbhw41Z35sv+BB6VB7xMFlsy79/sChgxMLKRB3srn1pfes7any9lJJKKTjuzufZUWckowiqa/fZgk3IEPIOE1EpqEuBwIZ40KJ80w6h46C+rJX8pL5ipXk3MY+ogwBBn3MpFx4DXaxkuwFrI5PxwHrLqGxLocDegeRdkNuy1NxbUMUxiLoWTevbBsIZ1pWA2Sxkpc1myGelEDJYhUoft71xZMwfng/4/kqCvkcJo05oFPMs9Oi9oiD7QEoOw7Ti+DrZAMEkRvlukIhDQCnjxvCu423Z2paNq+UYRqJK72lgPDQNfWb11hXAUkiU8ilE3v5Kho/f8pBXvUE0rxjphHEneAs58c4B38wg1xJtpIS9fRERDKKUI7J91UsgLpnUo7zVxoNTqhz0ByzEgdPsZIKkRc65+nnQAohVqFyDjLEOQcN7m3MNW8agknsFXK8XYRzcPo59DS45ozfjiOdmdrb63eGLvZC5wAA9/zDFJQYw4/++Lai7Ir+PfetMzCsfyPW79gbJrPx7dskVlInX8g5GK49Z7BvV80fdaaYJkw+eCDe9gxS17veT+mr9p7G8FJWLAOqE5y5ncCKyz02Fe9u2KUN2qg6owW5HjT3HmYnOJO/hArZwEB9lqbdu8/CJXNuJoW0iasFgG2aEPg+T7JXXTqdg4CpZkAcDJwD/60zLhH4ziPxiMwDe9eF59g5h65BHWqQc3CIlbx2HPodvAly7oESY6GlRj5HQV5e6CceEMiXB/Sqw5Ej+oe7GJdYSSwOPlnMAE/OwXK+GE4+hc6hb2PB+wUuxUxAzfVcMmQbhB29QNwJzqZzCEQY81dvx8Nzzb4cKkwWaQKMAWu27QmCwGnFStECI1/vZyaPiXla2xZz2VhCVc7e/Lw+E6HPsrXYEcYe0HMHzS1teGvtjtQKbIFeoUI6LeegPy5HegXimycxdwlmDnivEnfthWvODPvVcw7xcXU2ao84WI6Rctw0aXST6hMnjEo81J9+8tjEuSXGEjJhX4WpyVRUXbwemBGEAzeJlU44aGDsvwge+Od3o0i3Zx4RmdzlDPbtokgs3uK6ZJpk8kco5PxeYCDOKdlOEbdFWH1UsgGLJfvh7X5E8pIXEPqnC/7rr05/jQsmHejdLwD86oWlAPQ5IuQFRp4Oh4+Iy79ttyDOOcTn1tptpnzcacRKZj8HXbKmr/7PXHzsP1/BqAOS4d19+u0VipUQuynjhvU1ji+ASawUX6hj81DijnzFowP7RPod7doiEZyugNojDjaxhKeVQ7irlMq+e/4EXMktTQR6N+R5n1GZiK1kG5dpCCY5uDpm8SKZnOCG9W+M/ReB2uQUkjJ3ks/pxyz6EbtAIVaSh6PungTS6G3iubDN54gh3z9nVTA+r9YDqJcXKqRL0dKmuwdpriONBU2JsdAZUs0JAvCshaHOoby9tvyM1WXSKC9P0X74Pmka+/wpB8f+HzG8X5ipzjdgpIpedXqdg2mD4sU5aHxPAMTmRJpghME55XMO9/1tJZ53bEKqhRokDsmy0QODnUqQI1meAIZJxb/lB5zTOIlFykBev8Twh/nrsHZ7clfmw7GEYiWlwuPz1mrryZxDIvOWBF3YcfnadGKlkQMawzJBhOq5h6p8rsnBqFd93ptzUBX6Ks4/dqTxmC8S+ooY58B3dIaX1p8DcleUxTu2qKHyAhgXSSpz0CZW0ukcDEP83MkHadtz6YAMtCFmBXjE8H6hQxoQ6DuOGTUAd112UqwtF2TOQb7XprAvqp5FRanEYhyOXC/2fqQMSOjSOdiEuN/9v7fwpXuTgQDbA7VHHDRl35l2JN747rkY2LveKPuXkdOYbFIuiDsvQ3VAendjIItV4/6TIs8yLSKm+PMrlLzUYmGTFdJvrIoHXZNZd10egi+eekisPXVR+NIHDw3fWEGE6vPJt02nePyP6ZNw8KDeies0vWTy5b6yZHPieENKz3GBbc378foqfTA62ZJFtKrzbpWzAqp4+psfjP33GZ28YAnrL909zJE+1LrvLRh1QC989qTICkw161QX/e985MjY+Hz6U3Otm1BXiHNfLW1FjB/WF2cdMcx9soReod5I4RxMxMERMqTIGIb0bcCHJwxP1pPFSmk5h5yBc3BsQjoatUccNBOhLp/DwD713v4GAirnoMr4c8puzGQ6GMhmI4h6arRH2THLhA9PGB72awufIWevatFwDudOGI4bLzoGgD4aJyF6uVpDziG+SL+/Y18s4brABZNGhQuHvCj86rPHa8cq2lu4bgcuvye5ayLDfXG9ZEFien1dnc5BhAtR+zDtno9Q7N99xE+yIlwYLugMC/I5QpHPNzUUeHx8+pvw12vPxkGDe0sV7WMUC6C6q3VdEQPDkg12R9H6fODQJ9ra11pKRjr1WDAjPweF2zTYZaibNxViExZGzpWq3fXqCt4XaZ0O7dDr20KxUsrW2gs1SByST0VY9yT8DQxt6GXPusU/br1jU3DL/QpW9rErTo33wZ9WkTGUSgxvrtmOjTv3xeocf9DAcHy2XBM/vvAYzLzmQxjQq86YzU54cbqslUQ/QlTAEIgGTvm3mbjsbn1cJTHGOVJojUbFYkhA3FZT3l5BDL/9aNx00GXKqvMHUNtkkmBEt9CaRARB/fj/NIxNiUWcg25TUcjlQuJv43Z9Fxp5rHv2t+GPb66PHQ/vldKgM4EQA76jPBcVaobDva1FYxhsVztA8pmYN2UBbJxDrB6fBzv2tIb6IBvncP4xI7Xlwa3UcQ58XF2Edcj8HBApUhOcg+OlN+kcvnjqWHzs2JHYwu21RTWTc48iVQrbOVzZecohse9+dQV++Me38YkTRsXqyKItmy15fSGHw4b2RUMhZ0xvKXZOuVxy8SSK7oO4rnpJvPO72SuNfQfXEnzf8kIUZMz0Trh23OE4UnrWmswUgzaTnINueASL2IIIRwzvF5p2yvX6NRYwckCj9hw+oHBB1lmdFfIkcRTuDY0L8kKpC/yWDzdQcdgejXDU0+nYZNQXctjbWoy1rVozpfFZUcU25eocxOuq6mNOuvH5qC8iYxBBk5i0Lq9/58p9du2FGuQckmVih0bKcaNTmEZ5R9Ju4LChfTB57KAEh2HaoauLotiJq85MssjhXb7gLNvUHKsjW0P5+DkUcmTcWYmXyhSqWezkRajkOilonMviJIzD5LGeu3QJuhAngFus5MM5lCSdg9ac1yFXl8+R6w3uU4+jRiaDsMm7VDE+ndVZIUch8Z+/ekesXW2DDsi7VV0GwVCspNwE27MJFMPuvuvyuUQ7KudgeMRayCFNALO1krg5ps2HaEO1ToxFjUWccxjSNxI9mu5Nv8YCmlvakibpLsOHDk4QUXvEQbPgh7si8gtjIRYSOUlIjghTeJTS/jxOvHjGYpK0cGezIX2VF1jpq63Icz4YiEOxFI1Z3S0f0Lsu3Mn4JPuxOQwJoqFLTkQAjhsdeH0L23o5U5273+Bbfh4H9K7HnZdOxp941FEB1zsh8kkAwDvvR17Xl5021nqejXOIOcGFnEPyrZX9DWwgZaE0mTTLG4+IyCfbr8vn0FYqoVhiuObh+QACP4xPnjDaORYbGJj2fufK4RxypL03fepVh8NgkyDXrM/H63xn2pG2YccgSwBa2sTeQEsAACAASURBVIpG8apukydDzH+dpCDqTB9q3dZuv8YCSgxoNmygTFxSa5rgXVWAkzgQ0W+JaCMRvSWVDSKi54hoCf8eKB27joiWEtFiIjpPKj+RiBbwY7cQ34IQUQMRPcjLZxPR2OpeogId55An2+EExGSRk/LkiHDhpFF4+KsfwN8dd2Csnpgkwub/vstPVtqLBwprLZW0+YRFUYlFu0o5BMUvLj4Onzv54HBy+ST7yeWSi/mtnzsBAHDKoYNx3sTh+OEFRycWMiLC184ah1e+cxa+//GJOH3ckDAGEoObQIQOc0q1qUcNx2FD405LrsX3TMmq5Rv3vxH+ltNlasdgMUGMLMPsO7p0VozSbpYxIycijg/qE2wyfnjBxES9POccZO7w/GNHJjYUvpDFSi5fIBku73HbsxMKe5E8S+Y2RVY3gcF9G3DlWYd5mY3KOocjrn8GOzVhSkS/tmsIiQP/r7sUNYimLMIycw7Bc91tGJcJ8kawI/JT+3AOdwOYppRdC2AmY2w8gJn8P4hoAoDpACbyc24lIrEFuA3ADADj+Ue0eTmAbYyxcQBuBvCTci/GB7pbGuraFOG/kRnlk0GOjROE4SacNHZQeFxlR4VYqZeieFXFWcUiQ53mJZAXDt1L8skTRyOfo8hayYdz4Cz4XO6ABABnHxksto11efz6C5NxyBB9eOF8jjB6YG8M7deA//nSyRjE8+36sL86s1wx4dVrc70HsnxaJmKuwHI2UYW8WwzFSkqduy47Kbx/pjVLTlajetjqHQv5cQT3f2DvOnxGMjkVKOQDhbR8jaFnuASR7cwFuV+rmEy5C7ZbnKd40h3B1RzKif9DX/kAnvnHD2rvnT49r5/DoW8OaduiH5SHGuLgv2ZFUIcuPw/TGMS1qVy/0l0Cctu+QTUrgZM4MMZeBqBma7kAwD389z0ALpTKH2CMtTDGlgNYCmAKEY0E0J8xNosFd/xe5RzR1iMAphKZbk/l0D0vscF27XQExOBkz1XtkBV2dAtP4pGwyqE4IWorMS3nIO9mbbbV4pBPjBuRD3uFlJtXm+AowTno2wLcC4x8visvNeB+0ePhz6Pfcha/l//prMR5pqBq8rFYDmkCPjtlTFjnwAG9OOeVXOhPPSwwf7zxoqNx0tiBOHx4v4Qzn25RlBcsNbaPjJVbmvHndzdh0froGesW6i85uKeoXyFG87BAkuCqKz/f+kIOd192Eu75hykAgAG9Rcyw5Huns1byj5nk+R47xEriHQwv2cA5yJDbMo1V6OZUAxVxr0xhWHwITzVRrs5hOGNsPQDwb8HXjwKwWqq3hpeN4r/V8tg5jLE2ADsADEY7QUf9ZfZRPmrapYiXWgSsM0F+0Xfta8UNTy0CoOMc4tShtVjSRtaMiZUsttWCbZXR35CQRHjaxiyvNH37SCtkj3DX1NVxDqp1loCosnl3MkHM366bahynyFUAIG7TzxGTFavj4/daDrxHIPzbJ47FYdzEN0eQOIc4IRKiw+MPGoiHv3oqGqTkPME1GaKtStyhHMFXhTAGkONh6Ti2+kIOw/sn/TOS/fLrdQTj6K3oC674n7kAgtwnf/j66bFj+Zyqw2M484hhPBJBvG916PoMjFE7NgSm4dYqvL04Z88Yw9bm/eG78q1zDw/bk+upfckoajhhALj0AweHv4WzqKoLEeeu2hp3ahWQ75FvCuBKUG2FtG4mM0u57Zxk40QziKiJiJo2bdqkq+KEbtKEERaVSWW6/WLxVD2iE/XCmcNiNvqqPDVQoEW9tRWZNvy1WCiKzJx0HgCG90+aSJogFKrO3blPW9KCamrvYzzUhc5Rr48UNvsMyRtZtPXNB+Yl2huhmIOmiXNj475kzuGx14PwJOoiITzHGRC7QXUFSojGAr1SBNPCLzi42cu3QmQNtEFerG1Olr5wcQ6TeGZE4WH/16VBdNnLThuLg4fECbAa48g4Po24SL9Bibgbm9my0DmoxFKktY36BW8vqPfAa6txwo+ew859bfjiqWPRl89Hmyd1Uswm7+6jcjmWlLCuk4nDo3PXhDHBTIiZ53Zh4rCBi4rAv4Wr6RoAY6R6owGs4+WjNeWxc4ioAGAAkmIsAABj7A7G2GTG2OShQ82Jum3Q3dKIOMQVwybZuc3+XIaYfH96e0PMdlwVK6k6h9ZSKTSvlSFb0IgcDCaonIJpByrkuO6kNu4FJq7UTB6feuQw/OrvA2V3RGCDiocP10fODNrzfxFSCSSlukmxUvC9YkszHuGhuFUZtRDJLdvUHFvETboEdRetW/g/xKPh1udzYdZAHb5xdhDksVVaJM3+Ftpicx2bzoEIHzl6RIKDGD2wd2KsqmOoaY7pHAm1IjdeNn/Ndhx+/dPGMQqdg7zxuOrscXjwKx/Q1he1Zi6KPOZlPZbOsi48prympiCR8q3REYdrHp6PNYZIuLr2ujJxeALApfz3pQAel8qncwukQxAonudw0dMuIjqF6xMuUc4RbX0KwAusHVXxuqZHDwx2PGKRdsnDCyFxcImVgnq//vMyPPq6Oda/jjWt03AOsoWP6w7pFNa3f/4E/Mf0SbGyHFcauiab2pxuvYkU8HrRRPxlCeqKF/iAXknz3vA8j/HZxmVC/B7G29cnN4oTtBwRnuSexLKI0XRvVHm0buEf3CduJ2/iHKZPCZTU8hw0zQkvrk+y+VebueuLJ8X+53KUeDeCVLJI1POJqEuaY3rLoOC7acW25MFYe0G/8pyxKf/FBcuWX3EjB/OY1FZVc2Ud6kKFdLplTr6eLkEciOh+ALMAHEFEa4jocgA3ATiXiJYAOJf/B2NsIYCHALwN4BkAVzLGxBb3CgC/QaCkfg+AIP13AhhMREsBXA1u+dRekG/p6IG9MOdfpkbWOHwnGCbLMXAGPuEpgnrpx3XHy+/hjVXbtYu7nOxn4oH9tcfUMcqYdvRIXDAp7lEtxEpueuzBOfAqpnkrl6uJi2y7Wzl8tQxdkvZe9foQHKZ2TRDDkcel2rsbRVi6XS+Su0rd/MhJeiWbzkH0LfuymD2B/Z+dTmQzRRHHBFZI8b4a6/KJ+7G/rRTLRWEOKOlrQh7pY1T875ci83BhJCAv9rr3STZlfXze2pjFnizitKVaFdf8/NUfCuJdlaK5Gn+nov7rC37rhwq5ud+/4Z9Yqlw4w2cwxj5rODRVV8gYuwHADZryJgBHa8r3AbjYNY6qQbrB+RxhWL9IZi0Uw4VcDq3FopE6C32A01TUkzjIMZ1ufOodAMCRI5LK2dCrWDNJ/3BVXBnoY10k6jG4Hc0S75amwVhgQM0Y1XAjgC9x0Jd//axxibKDBvXG35ZppZIJxPRLCbEGH5/0jMUQhbLUFDbBZNUS4xxKTLto56X7IgffS7YXfMsLjGm+GscpQd5EP7kgiqt0yqGDYgslwIP+KTesoPGiX7guTtBtYiV1TmuN/ywc/eSxg6R6ga4jnpNEQxz4N2NJfVYswZKNc+DHxg3rG/b3ypLNOGpkfyMx1ImVfCBfT1ofiXJQ0x7SSceu4LjgHEwvWz6nN0VT4asIDJWaEnQKaXnxVeedyFEdjVEdix4igqWLTU0jy5d9A2T88IJob6ByDjZFstlqLHmOz/v2Eo/GGo9mqm9bl/Pgt188Cd84e5w2Y5mureBkpT+DWEneANhMWXUJnUw6Mp+FxMRd6OawEEXK6NNQcBoDGDk1SoZR0YuVyHhM7lo3p10+JSr2SKFubFeluz/i3TXZq5RNHBwWhdVG7QXe04g2BITOQZiJmszFBPFwBXrzfX6i33gfOoV08F0suQwO/a12dKas+jEqhNTRp9zcn751BkYMaER/ycRWJ783wSiO0NxgH/vv2cu34swjhnnFRIrHpwoKxw7pg6s/fESq8apxhoxiJcWU1Uwcgm9ZrGSi79sM0Wx18NH25XPRczvx4IHYubcVfRsKTo98E/Hynauilin5UVRPp3PQtWcmNjM+GPmHUGxT5uZw6vI5zF62BbOWbdHWC3UOBsnDoQanU7nvtNnnykHtcQ4x4qDjHODBOfgRB29fPk09nZ9DfFdpb1JcWxiO3Ci7RuJF0tbzEU0ImbxCvPo31sUIgzy+tgrESroX3mXFBUSe6vIYTaaUsuiwknSgajj4EtMTt0isZA6xAej1XtXIhOeTclQVKwnTadd8t+kcfMYuE04VFKsXvMeykYBe5xB86675uDFR5kT53qjxkPTEgfCZO/4WK5Otu4RYstWwfpi4Apn2ps0+Vw5qjzhIvxO26PwFDjNwGfhC8QKbQl2H7aXgHID4zsolVrr1paXWNsViXqd6eSbGKDgH1xjdOgw5XIiNQ5PLhK+IbWExLRw6P4XmFh/iEPQpP96kWCn4lrnHSkIWCCWpgGnhDxXSJWYUPcnjk/1nKiIOEmHXlcvI5yKFdFspCuXiWq9OHzdEW65GUXWO0SFWIq4w/wp30AvGZtc5yOjboJqBR/XUTZT8XojYYgMUy7v//fLJGDkgEkHWORTSJg5Mp7NrT9QecdCYU0b/g0Uiyt2rb0OInaomVtIsRDqlqixWWr3VbhOd5BzMfduc1qKK9sPy+BI6BwshESIPm6msUVStuag9hpzVMvbyOvZw00mZvo/54IwzDtXnaVAWQNPCL+bept0teHLBeuMcEtcue41XYt5IRNrcHh84NBmsIE9R7pI2yZvfRuA/deLomCOYDJVw2sYIqOKVIOCg3LdQ/ssWbtqdtkHnkJiLUj2VeMp1PzP5IG1fpx4WJ4ounYNJnB1XsGurVBW1Rxyk30adg8MDWrwMbhFGOuruWqBtbLUKsat2pTAUliKuYHkJEZzm2uQEOTGfBm1d5b+lb9P16kRvPpxDK79WuVW1CzG+VplzcHjEHzNqAP75o0cZfCTi/ZUYs+ptfvbsYgDAzr16YicufacUbO9jxx5oHZ8LOuJwpcYiLCdxDsWSPgikiqH9GsxKb8696ghRrF9pcyRw1dnj8V/csTJqLzlndKIaU/Ri9Xpk51PVUipGlESmRse7ZNM5FHJkJBo2kXh7oPaIg3SDTx+vsLlit+1QSOdD4lAthbQgRlF/Hzl6hKa9aPF1tsn7diU/Dyw7fMRKfiBOYTftbImXJfqNF44YELf8Eaa8veryRhGMLq1os4VzCP0i+LWqHsu68cmmrEVPj3j9sSiUBGOB965Wr6Q0YrKIC3UOnGA1XX8OJhyYTB6UBg11+cSGx6QXEYtkW4kZky3JsM2fYMow9JO8+nV3WlzzA6+tTpTF6yXP170H4QYgQRz011Nicc5hSN/62Dsu1gWZMF11dpK41ls4h0F96o2JsmTClMafp1zUnLWSmDZ3fOFETD1qeOyIeM6yrbkOQifh1jn4Lak6++3jDzogUU92kHJBvDTRy23btSV3RCqemL8u9t8o7kDwEm3mKVKBZLA2eXwC1300nszl/513BM6ZMBw/f3axkXDpInfqspipfQqhl40gqosv4A52ZnvaOcGWIppX+pwd8VbMSlw+Pu5l69oE+KCxLhcmpLJBOHsB/pyDbaebIz9fG9HEVmlumSy+1Pumo1/iVFU8PFYJ0hi9x9F78m+fOAafnRIPpa5bN+TMcAJi8ykU0rIotH+vOmxp3g/Gkn4w4pomjTkAn548Bu2NmuUcxgzqrQmOFnyH6RmNnEPw7RIree+2+XdMIa3ZvUThM/wsSoBol6LLPgdEJpauIIIyLjp+FC48fpT2WPCisxir3rs+uQdRX2o1Um1dPoeTeKpVk5WQnjiYn4kaBiHmBGeoK1srudKu2jYDgmgG7QjioN/1yjCJ+1Q9lUt86IOGQt654QEQC4vRVtJHEE6cY6kirJVi+kBNPXF/Y5ZEOlUCJUN72yLgquKdX3/hxHg9/i0rpHXEWOekqsuxEYbf4W1N+Ndnw2P9GwsolpiWYxRz4epzD/fi1ipF7REH/q2dVHwaqN67KgTb6dpledtvKy86AG1sJVmm724zqDu0XwNu+sQxuPuyKcYxMsbCRXDqkcO09WTceNExWpEOEFzDm2t2OL3HE8YAhnpBsni/uDZAlG1P2yc/4+m33se+1mKcyCZ0DkFdmWOqxFFQEE0gEhXV6XxZlFXUrIwPvgXBqgbnUJ/PeZkC5yniHNqKcc5h3LC+Yea6h78aBbqzEk5uXWRzSgSi5x0PimfQ7xjEhLr2ZPHOtIkjMFjZ7Yt3saWtFFq42c2Qo7637dmfqBdG89U8XJFieK9GtBQSpg4wYwVqkTjw52HzbAzFPA4nuGqZsgpiI09SXWrDaDfrw/oH34UcYfqUgxKhraM2g12WWLBu/fwJ2nrD+kUvjGty/mXJZqfy1qT0049Pb01VienmfbNWWjkB3XCGakQEsXMsx2a+sxFvrd2J1mIpJJy24IoCJu41Eitx4lCFBUMWF9kQcA6S7kTaxT5/9YdwyQfGJsZk18cExMBlKSwrhtWyeL0kUV2wdoe2XyAuVmqsSy6JIjDn6q17QrGSbuMeGbJEnZsMCvIa0RcQcdA6s2nRbEcoo4FaJA4icYvm/opF37XmRApp9y7LB2KSvLQ4ylGxRJPFzdf5DtDpHPQQlh1tRYaBvevQUNBzBN/92ITEOGwQC6CprslcMDm+YCH64R/eThyTI5h+7czDnGOSDWxveGoRvvXgfOmYOr7kgE412OnLY3VhT0sxJO62bH8CJl1QpBNJv5s0pX3NUXyBPkwT2BCIRwcuGhTrQNyazKlzYG4nQ53vicnYQV14d2rEO2KDKG/KdByxcOBs3l/EE/PWhX0k+pXESoLIfPy4kYZr0We1E1yRjkhHAR+1TVYdNaeQjjiHJMTL6to7qZzDrZ/T77Z9KbyQS1732IKwrFUzOaJInG7iIBYqlzxYLL5bm/db5Zj1mhDGNogXTpfRC0hmq7N5cDPG0LRye6z8uW+dEcvuNmqgPs6RjDSMRjkvoM8p+9qK4eKm4xxUSZOJS1S5yDRiJZ2BQNC3X45m8UhnL9uCrc37jYQpHyMO5vYCfYxHwinehryYa90XNAuvlgPTtDdmUDJjoOyYePPz7wLQE2PZu33UAb1w5Mj+OPMIvZhWZ24LINyc6TYFwm9Dt6loD9QeceDfunepLgyY5djBCOLQWsLw/g346DH63UEl3J/ObDKXgnMQ645rR5kjYP7q7Zi/eru1nrzIe+2QucxUtwACwAjPbHW6RDAAMF5JKepDiNMIodT2/vOzxzvP8Xnee/cXw3o2owMB01SU9U9Ebg4x1odpMae4WMn0nIUY9O9/MxuAeQMiX59tzgREKe6xfs5RyUVVtCHL47U+NJo+vizFSoraC77lvAq6eRmKi6SJqFdII6xn824HOOegebgiS6Tu/f/xk0GaYdM7VW3UnlgpfMAanQN/uvu4uEhOVRmvF4mVdC+4gC9x0O3WPnKMzs8BvF9/sZKbOPgNMq11hJCdPjBDn31LJ9vVwTfujs9V2No59bC4A5Z6Ww40RGCNj8GPaAp5ss5aKY14SFR1cQ1fPHWscp6BS1N0DqZW1algspRKo3NQOQc5/3c4Pt7Ie5uaY2M21ZNxzOgBiTJRS+bEtc9Eo2i2KaSFct32KPNcb7NuezzSgdiE2UzLM4V0O0Orc+ATY9XWPTjl0EG4QzFpE4icXewPqhLF0bkThifKRHs2W/6wLh+XjxOcD3RmozqIMNb7iyV8/LgDzY5Znv3qRAQ6eHEOlnZuUTiDhkI+RsB8XkgvzqG1GCrCdQTXO1ijVNfFNRyh5AaxcQ6m1JYy1Hv9/o592nq+Oocgppl7E6Azt9Y7Eka/6/KEH3HrqUS/ilIf0N8bnYmq7r2SFdJFZg63HvQdtHfqTS/EygVRsBkGdIQZK1CDxMGmcxDsGmPAhJEDjOaaMrdgk+nrjjykyWOreydsOaR15nHJusG3a1HzXYx8WdlPnjAKRIHoy6RvCMbn157QOTjh0ZytHd2zPklKIGO6jb+TMpDZLun7H58QjkGYQDcYCK7vzlBUc+mV1MOmDYNqrWTihNTxvbM+aTyh1nP5OTC4Iw3v0lnwWRZzIAgp/gVuPaVC1JJ1Drp7qeMcXETElv8bMItLhVTARhwyzqGdEFkrmcVKgJ69FJAfju1B6fpQUy4GY0rCtiO6f87qWLluEfYVK/lOM9/dCvFJ39JWsnIbvv3qLE9M9VxIG5fOZ+d72rgh+CAPw2ITK40b1i8cg1gATJZhvsplMb9c9dVxmSShDAyvr4p0T6Zm1Tmlc/QC4u+QU/7uwTnoLI5sYTEA8z2W68liJV3ojFwuSRxcfg7MIVbKkZ4AHM8d/Kycg0/8/Cqg9hTSHpwDYF9U5UVjiZxO0NJeWvjKUudef441DEO1dA6mXa6pvZbWovWctMmI3PXcdXxyFciQFwrbfRTHbJcUeWdH3q8mvYvczk2fOMbZpss7Wh2X6Vp8U0+qz+7Ks/RmxL473EjnYK+3cVdLoky3Z5EXT9scFERTVnBrOQcNcbCKlZg9UZOoqxLD2f88NTQMsRHKanjD+6AiEkREK4hoARHNI6ImXjaIiJ4joiX8e6BU/zoiWkpEi4noPKn8RN7OUiK6hdIIXlMiJA46nYO8GDisK3wgL9oHDmjE/V8+xTomF0S/8o58YO96DOhVl6hLnpyD7ybEl3MQ3e1rK9o5B2+dQ/JFGa0xW/VpL0WEEABx4u7a+TrHwI+VWJRPwsg58Js4qE89pivxe2SIdtx6JbL+F/DlrOQ5dfSo/kaxjfw+2eXvfn4O5000B6OUIc+7BoNoOOg3+JYT+FhNVGOB78zceknoHCyvjE6XNrx/ozPoJwDUdSOx0lmMsUmMscn8/7UAZjLGxgOYyf+DiCYAmA5gIoBpAG4lIvHkbgMwA8B4/plWhXFpEdkqmSm/+luFTywZIP4QP33SGHzgMH1IYt8drWhONmU1sv5V1jn4KqQFAWstMqvOwbdfVTZ75Ih++Mu3z0qOLx8tAj/4u4naOr6Z3ATi88E+RsAuVpK9e79yXxOAyGwx0a9QNHuuATYRKJDcAJgW6kQiG0M9udQUwTQ45q9zAIA31yS9mGWcdeQwDO8f91LXzW95I9PoMW/lwHc2zkE2Pe1VZ44XJrzH7RuK+Hz8xAmjeHmSS0mgY2hDu+gcLgBwD/99D4ALpfIHGGMtjLHlAJYCmEJEIwH0Z4zNYsHdulc6p+oQD0T33OQyGwHwZZdlzqEasW9swcNMddPuKk3w1zlEv+UQzLZ6NqimrJ8/5WDtNR81MrLIOXpUf60zU0qVQyzLmutFB9yxlcQYxHvfaOAcBIH1fTY2c2ogSbRM81fl0Hx6t70nMc7Larjh/26o81lPHKIyEwEGoue1x8U5hGKlqKy+YBc/ucRKOcWnpA8PTimepVX/knYil4lKiQMD8CcimktEM3jZcMbYegDg38KbZRQAWZO6hpeN4r/V8gSIaAYRNRFR06ZNm3RVvAZsgvwwbZPZl3MoeL4cvhtadeLaxTaUGIMOu/b5JZ+3cQEy5Hs41hCmQa3nak9+UUwEJ/bsHATTF7kY5+DeLNiDywXf8rWYFi7RlWu807iYxaXb8tU5JDkHa7NBWw65etiWpQ11OHdddpKxrnqPXWKlYf3MzpZanYPWuCP4fm9TpF/UB/yjmM+GnVuKi5WEebOg87bAlf01YuT2QKXE4TTG2AkAPgLgSiI6w1JXd6uYpTxZyNgdjLHJjLHJQ4fqHdScsOgc5IlWDc6hzlPm+neT4hm8Vtx0vrPtgwf3xsIfnGc8Lua4a4FZJjkUTRmbtKQS8BYrSd2ZTIHVejYEETuD6LIA8HFDtrP4s9OP9W7DovPLTx+nLe9V5/f8IrGSGZFCOipzmbK67pFI+OIS0aljNy3oqpz75EP0YlD5dLv41d9DWsZZhpATuv5076m8kRnazxwsUQzJZcpKRMhRPELvIYPNcaeKJYZiKZmPQUYuF/fbCGORCb2FZsc4on8jPjN5jPW9qiYqIg6MsXX8eyOA3wOYAmADFxWBf2/k1dcAkDNUjAawjpeP1pS3C2ymrDnPSe8rLy/ErJ/M9U44aGBoDjn9JHMSD3kx6VWXt4p6RBA/XXRXGfKl/Opz5hARvpZX8kJkU5z5ihKEWIkAfHbKGCMH5rNgqSE3BD5xwmhtufwS2ji/XMg5GKtAkA75pTe95JGC236PBHFYvrnZWk8lDhdP1l+vrMv6+lnjEgmYBORx2ThT+ZZVK5Ko+hh0z0V+L6ybPD4ml4c0EJ9T504YbpwPuVyQJa/kSIKUI4pFXo0SQFHsv4zWYgl1GnFWe6Fs4kBEfYion/gN4MMA3gLwBIBLebVLATzOfz8BYDoRNRDRIQgUz3O46GkXEZ3CrZQukc6pOmymrPKkr4ajia+HKBC50e+z5SMgwiRuBz3YkLxHQNjS66K7xtqUfuuS8gj4BvuKLxyVWysJk78graaf8jPNs7PVrfPUGYn1xIdzmLloY1hmEtVFEXUtDcLfvFge+oqbzk9kQBSQ59744X2Nmw8fEV7Qr1zPPL40hENdlHXPpU66L9YFOkco5OIGD6Z3ILbpsflAURAzqbXEHISTYmFwBNdmUkj/7+xVPEOcscmqoxI/h+EAfs8nQAHA/zLGniGi1wA8RESXA1gF4GIAYIwtJKKHALwNoA3AlYwxMRuvAHA3gF4AnuafdoEt8F61dzrk+RIBUbyYFxfbdSmRmaM9t4Ba3wR5XNVRmvv1LXdlCiEd1Atks63FkneokjTEwRShFFBNWc1tiL5txFDUebBJyn9saFSMf+9+R76QFNyXD+LJpvwcGNP4MpiQZh+mzlFdhOJ8irlQX8ihTdI5qBkJde24NinFUhAt1+aslqO4DkNN5KMSh3/+fRCx2eRw2B4omzgwxpYBSAhrGWNbAEw1nHMDgBs05U0Aji53LGlgS/Yjv6w+SU/SwNvCyVFPtDO4j51z8G1Pfteqwfn77rDkehdMPsdEWgAAEsVJREFU0usRgnqBCWFbkTnai377GgwALuIg6Rw8xErWUCrikMe0auamlZt3J52+ZPiaQPuKQfs2FMLFx3Yt8prna6jgO4aPHauPcBz2rbSjBq4DVBNaN3GQrZV6WeaDgEuU1lYqocRc9ShGHMKMfpIjnQ4+EZmrhRoOn5E8Jr8P1SYOvo5zrnrC1tqXOLiT/fi/SF79xRZpv93nVWePt7QnxEolh5iqTLGS5Zp9xUqiOx/OxmdB95173s6Tns/19s9HgSZtnIPcns1UVIaNiKyXAvf96u/1uVHCvpV7rMsZXvCMdKAbl8lrXSYgNo5g57423DtrJQBzQEIg+UwEA6TjHGT/ilaPXC7VQu0RB0+dgy1kbjnwFdm4dr2Cje5r8SGQ4buzA6qjZ6EyOAeXmWixxNBaZFYFt684Kw18YwPlPTgHFTYrmjTtAHZ/EsDfZ0oOa+17D02+Gips1m4bd5kXURXqdP7slKQBR5rnL4/rqrPHeb0vvlEF3lpndupTp5OaC1wmDnLK3aNHJUOPtxdqL7aS+KHlHNLL3//uOLNIJN62VzWnX4KwdvF1SrOFDwDiu5JqrKm+i74vk0IUycJ9ZPquflXY8jTUx8RK5jYiebF7fGLPYSMA2/akkyt/65zDrcfLIZYukYiAL+dgm6/yrtwFlUgP0yXnkeq49niCOAzsXYdrPnyE9zh8YNtQ9FcyIao6B9mqTZi5njdxuPNZVxM1xzmI2eLKIOUjewSAb0/zm1C+YiUXURJcpS9H4LJoiefjtfd9+emH4IaL7KoheVhWpWYKJzghZ/VdsNIshjYxxmcks2Lbi/5QU+DDuXrrHmMdcbq4330aKt+X2bz9Zbg2HDr0sViuyfdClpvrIJ6FjXMQTmhf/ZA7D7iPiEx+/q5Ir0LnlI6A+irhzfWGKWFA1JzrshOcmDMnjR2UKuNfpahZzsHlBOcr0/ddpH05EdfDFwuC7wvvElGk0a1892MTnHWqbQ6cz1GUc9mmw5AOpRHLjBhg9qAdPbA3etfn/Xe2lm7VRa0qxMHdLYDynsNwSxrXI6VQJXsd9+agQb2xfHOz9T0RJrTnTdSb2MrwuRb53XARhwMH9MJba3dia7M7R4qAtxm2pZ6aQ72omrLGOAdzcqj2RM1xDnadQ/RbFwGyEnhHP3VUFJPId6K4XiafXAlpEBM5eNrh2+DrjSsTX9/dlQ/Xd+NFx2BE/0arV+r15x8FIF2IiL4N5va+ftY457gAOcKw/XrLWVT69zITr8OG9g1/2/IlyNDFIhL4EE/HO8ojFasPUR3Z392OQBhJ1fEaXPcRvUOgCjEXAGDigWb9gPpuCJ2DIGyyuDcSq3Yc1wDUJHGweUinX2AG9PaLc+JrMTLIwbGk1TnYdoBye9WCb/gM//bSK7h9OQcfP4ELjx+Fv/3zVCthOogH+bPdSTG8kZxT+cknj3XWdUHsLl1zNa2COzjHV6fla61kngvfPOdwvPYv52j1ByqGWRT5AgN614Umsa7p7btpO3yE3rtehTxP/kUiFCpU4hDqHPjDFwRhyYZdWMgV2x2V5EegdsVKmmNp7v38730YdXny3jn5EodfGOL8CIjJbtuJAcAHxw/BX5Zsxj+dZ98dCx3GC9d8yGt8LshK42oQB/kqfT2ufe91S5u/ItSGkFDboixLCunGuhxGD0xGjQ3r8u+RFpEXEOUS7+PQj/ku9PFz/O6hizsUfhODLB79+RxZrbdk+Mb4Eou0y3TYd2/kLT6W7ptt/ov7Nrx/AzbsbMGFx/OQ3YpC+tybXw7P6WjOofaIg2fgPRd0CXZs8N2hu8JiCLNFm2UMANx56UnY11Z0LtBpOREXZHPTaugcZI9Qq2NWGZxDtRyKxEtrW4jEiFodnrNAREg+PdkcZwv/v71zDZKiugLwd5YVIoKAuBABV0B3iRtUVhC1eCkRI0oJFaNiVIimQkyMEZMfPqLJD5LSWNHylcRYBkqjRsuKJmhMLGOilsSgIvhAxBc+UEtjFEGNi7AnP/o22zuP7p6lZ7p79nxVU9Nzp6f7nj49fe4999xzCRiHCFdLTx4qcXvO580Kj565Zn47t658nRERhi4u/t/o4uP254wpY8ru17XwTiKn7fb/WPyV8Hk5EP188KMIh/Tvy4rzZxaFQ5caC4ybwiYpep9byb2XnCFdRcMcloI3SFQr74dHj2PUkF3Zt6l8ygnwWliF4XKl6xUdCVQJSd/AQaMaPjGrazuuUUrKOMQ5n//Q2Lqts1vun1L4di5qcaJvTxtLv8aG0Gy60OWOSyj3XTf2C4w/lGJqy5785rSJsaPT4tKvsSE8VNq9R/3r/Eu8ZF54FF7wPgxzf/l1iuoJ+T2R7Z1KY5+GHden1HrVPj1xD+4Mvc84hIxIV2N10tnjvYHtKN+s382M0v+M1iYePX9mqFuiEvx7sCeuh1IkfQWDmSvjhrKG6TH4ByuVl6cn+EYmPEW5d96ObZ2J/ckPHTuU9T+bzZCIcSq/l1mNaJekJhxWStyZ/7F77BHX0O+lReFfjwERvTn/eVA42bbUJDgfMw41ohqtqFJsdovpRLXi7zlnKpfMaauKgQqjK/opmfP6f8ajymT+rJRg6z40HUfM6q+8qCvtV8fnyRgHP5yzXNI26Krf1u2dkQ/p4KpxSeA/cOL0JCul1vdr3KvSELPrsCOdTsTx/OSQV508IXQ//1pHGgfXGOwsMAJha0jXah2HHXWp6dkyQFgoa6VrDMdh8VGtvPb+GtqbB4fu1zp8IK1l1huoJtt3zJtIpp3QGTKm0xOCg8bhie3inXDogK7uflI9B7/lHpbaIFi9yJXb3HtSkWT+A+fIcT1cICuDREWaTW3ZkztXbWRcRJRRXHfv2KYBvLDkmMgHtN9ziNKxP7BeaAR8d1NHCZdn3MH4pOh9xiFksZ+Ec+0B3qzGFRfMTP7ACeG3XJLqsvoGNqkecLeeQ8LRGklFKx02dih3LDqMSSG+/+D9FpUeY177SJau2MCJE8MHpOMyYvCu/OnsKbTttXsix0sT315GRSHNnTCSaS1NkaHh8yc38+AL7zEhovEG8Vruvrsryt3mRzkW9hxEhH6NDXRs217UWE1qwaS49D7jENJzSDrmPw/491tSxsG/15PyRQdb90n7zJNMf3zo2NJLavoEL0dUTv699+jP6p8cnUS1duAvEpV3/udmU8cJIY8yDOCt6rbh0mMTc4/5bqWo+9///u0SmVv7NjbQ8Xln0Qp/tfbg9boxh7D0GX7Y25diTnipB+767hTOPnLfxB7mu7mZv2ELu1dCcFwgqW711fM9v3Gprnu1iLswT144oczSqtVmk+t1DYk5+TQOSY6b+D2aqACPzSENhH6Nfdi6vZMXC1ZxrPXYf6/rOcwe/0Vahw8o2fLo3OESqa8/chgHjBrULVXzzjKjtYnLTziQ40MW8KmEYM8hanbsa5cdF+uY+zv3Si3dLCkF9VTM9acdzOv/LZ9A0OeKkw6KnLBZDc6b1cqbH37K5DHh4btpsSNHUowV6MrxwScd3LbyDW5b+Ua38lqm64ZeaBz2Gbob+wwtPUfAT8I2rz2ZB1tvREQ46ZBkfOXQ3fWTVPhu6/CB3HvO1MjByiQJtk7vPWdqzc5bKceMD1+JLW0m7D2Yf/zoiLSrURY/CikqIeGcA0fw7ubPOPmQ5qLvSo19/vrUg2NnY0iKzBgHETkGuBroA9yoqpfVug57DujHC0uOSSRhnBHNjQsmMTpk/WiAxUe1cNYtTwHJxtTXuhUW7Iy2DA+fOGbkF78BEzVDuk+DsGh6dIpyEdhwabwecdJkwjiISB/gV8AsYCPwhIgsV9Xna12XWscS92aOaoueC5H1lmxcgvdVrVuARu0YP3IQ132jnemtyYQNzxw3LJHj9IRMGAdgMvCyqr4KICK3A3OBmhsHI3vcv3h67GVRs0rUpCijfphz4M65pdubB7P6jU0AtI1IL/w4K3fsSODNwOeNwKEp1cXIGLUcG6gml37tAPYbZi4lI5y7vzcF8NJ1R7ldq0lWjEPJCctFO4ksAhYBNDcXD+QYRpY5ZbLds0Z8WlLImBAkKyOvG4FgiMso4O3CnVT1BlWdpKqTmprqJxWAYRhG1siKcXgCaBGRMSLSF5gPLE+5ToZhGL2WTLiVVHWbiHwfuB8vlHWpqq5NuVqGYRi9lkwYBwBVvQ+4L+16GIZhGNlxKxmGYRgZwoyDYRiGUYQZB8MwDKMIMw6GYRhGEVKNpTFrgYhsAdaX+KoZeKNEeSGDgI8yvF9cOapx7rRk6W1yVLJv1mXJuhzVOHdedTJOVaNn2KlqLl/Ak2XK/xPz9zdkfL9YctSTLL1NjnqSJety1JMsO3vecs/Owlc9upU2xdzvnozvF1eOapw7LVl6mxyV7Jt1WbIuRzXOXS86KUme3UpPquqkuOV5o17kgPqRpV7kgPqRpV7kgNrJEvc8ee453FBhed6oFzmgfmSpFzmgfmSpFzmgdrLEOk9uew6GYRhG9chzz8EwDMOoEpk3DiKyVETeE5HnAmUHichjIvKsiNwjIru78r4issyVPy0iRwR+M9GVvywi10hwxff8yfKQiKwXkTXuVdO1BEVkbxH5p4isE5G1InKuK99DRB4QkZfc+5DAby501369iHw1UJ6aXhKWI1c6EZGhbv+PReS6gmPlRicRcuRNJ7NEZJW79qtEZGbgWLXXSdwwsLRewHTgYOC5QNkTwAy3fSawxG2fDSxz28OAVUCD+/w4cDjewkJ/BWbnWJaHgEkp6mQv4GC3PRB4EWgDLgcucOUXAL9w223A00A/YAzwCtAnbb0kLEfedLIbMBU4C7iu4Fh50kmYHHnTSTswwm2PB95KUyeZ7zmo6iPABwXF44BH3PYDwAluuw140P3uPbzQsEkishewu6o+pt6VvhmYV+26F5KELDWoZiSq+o6qPuW2twDr8JZ6nQvc5Ha7ia5rPBe4XVU7VHUD8DIwOW29JCVHreobRqWyqOonqvoo8FnwOHnTSTk5skAPZFmtqv4iZ2uBL4hIv7R0knnjUIbngOPd9ol0rSL3NDBXRBpFZAww0X03Em+1OZ+NriwLVCqLzzLXVb6klt3+QkRkNF6LZyUwXFXfAe+PgdfjgdJrhI8kQ3rZSTl88qSTcuRNJ1HkVScnAKtVtYOUdJJX43AmcLaIrMLrrm115UvxLtyTwFXAv4BtxFyjOiUqlQXgVFU9AJjmXqfXtMYOERkA/BFYrKqbw3YtUaYh5TUlATkgfzope4gSZVnWSRi51ImIfBn4BfAdv6jEblXXSS6Ng6q+oKpHq+pE4A94vl9UdZuqnqeqE1R1LjAYeAnvITsqcIiSa1SnQQ9kQVXfcu9bgNtIwbUhIrvg3fC3qupdrvhd1wX23RPvufJya4SnrpeE5MijTsqRN52UJY86EZFRwN3AAlV9xRWnopNcGgc/6kBEGoCLgevd5/4ispvbngVsU9XnXddti4gc5rqWC4A/p1P77lQqi3Mz7enKdwHm4LmmallnAX4HrFPVKwNfLQcWuu2FdF3j5cB85z8dA7QAj6etl6TkyKlOSpJDnZQ7Tu50IiKDgb8AF6rqCn/n1HRS7RHvnX3htabfAT7Hs6DfAs7FG/l/EbiMrsl8o/Eyta4D/g7sEzjOJLyb4xXgOv83eZMFLzpjFfAM3qDV1biImRrKMRWvW/sMsMa9jgWG4g2iv+Te9wj85sfu2q8nEGmRpl6SkiPHOnkNL0DiY3c/tuVUJ0Vy5FEneI3DTwL7rgGGpaUTmyFtGIZhFJFLt5JhGIZRXcw4GIZhGEWYcTAMwzCKMONgGIZhFGHGwTAMwyjCjINhVAEROUtEFlSw/2gJZOs1jLRpTLsChlFviEijql6fdj0MY2cw42AYJXCJ0v6GlyitHW+S4gJgf+BKYADwPvBNVX1HRB7Cy381BVguIgOBj1X1lyIyAW/me3+8SUxnquqHIjIRL4fWp8CjtZPOMKIxt5JhlGcccIOqHghsxltj41rg6+rlwloK/Dyw/2BVnaGqVxQc52bgfHecZ4GfuvJlwA9U9fBqCmEYPcF6DoZRnje1K8fNLcBFeIuwPOCyP/fBS4fic0fhAURkEJ7ReNgV3QTcWaL898Ds5EUwjJ5hxsEwylOYW2YLsDakpf9JBceWEsc3jMxgbiXDKE+ziPiG4BTg30CTXyYiu7jc+2VR1Y+AD0Vkmis6HXhYVTcBH4nIVFd+avLVN4yeYz0HwyjPOmChiPwWL4PmtcD9wDXOLdSItxDT2ojjLASuF5H+wKvAGa78DGCpiHzqjmsYmcGyshpGCVy00r2qOj7lqhhGKphbyTAMwyjCeg6GYRhGEdZzMAzDMIow42AYhmEUYcbBMAzDKMKMg2EYhlGEGQfDMAyjCDMOhmEYRhH/ByHKMUFyg+DxAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sorted_data['inc'].plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Zoom sur les quatre dernières années\n",
+    "200 semaines ~4 ans"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fb8952c10f0>"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sorted_data['inc'][-200:].plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Le pic est beaucoup plus large que celui de la grippe.\\\n",
+    "Le creux tombe pendant l'été. Août ou septembre ?\\\n",
+    "Zoom plus poussé :"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fb8952a8780>"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sorted_data['inc'][-200:-100].plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "hideCode": true
+   },
+   "source": [
+    "Le creux est donc plutôt vers septembre.\\\n",
+    "Ca tombe bien, il est demandé les périodes d'étude au 1er septembre ;-)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Etude de l'incidence annuelle"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Etant donné que le pic de l'épidémie se situe en septembre, nous définissons la période de référence\n",
+    "entre le 1er septembre de l'année $N$ et le 1er septembre de l'année $N+1$.\n",
+    "\n",
+    "Notre tâche est un peu compliquée par le fait que l'année ne comporte\n",
+    "pas un nombre entier de semaines. Nous modifions donc un peu nos périodes\n",
+    "de référence: à la place du 1er septembre de chaque année, nous utilisons le\n",
+    "premier jour de la semaine qui contient le 1er septembre.\n",
+    "\n",
+    "L'incidence de la varicelle en cette période est plus faible que le reste de l'année, mais pas aussi faible que dan l'exemple de la grippe. Il faudra vérifieir si cette modification fausser nos conclusions.\n",
+    "\n",
+    "Les données commencent fin 1990, ce qui rend la première année incomplète. Nous commençons donc l'analyse en septembre 1991."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "first_sept_week = [pd.Period(pd.Timestamp(y, 9, 1), 'W')\n",
+    "                     for y in range(1991,\n",
+    "                                    sorted_data.index[-1].year)]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "En partant de cette liste des semaines qui contiennent un 1er septembre, nous obtenons nos intervalles d'environ un an comme les périodes entre deux semaines adjacentes dans cette liste. Nous calculons les sommes des incidences hebdomadaires pour toutes ces périodes.\n",
+    "\n",
+    "Nous vérifions également que ces périodes contiennent entre 51 et 52 semaines, pour nous protéger contre des éventuelles erreurs dans notre code."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "year = []\n",
+    "yearly_incidence = []\n",
+    "for week1, week2 in zip(first_sept_week[:-1],\n",
+    "                        first_sept_week[1:]):\n",
+    "    one_year = sorted_data['inc'][week1:week2-1]\n",
+    "    assert abs(len(one_year)-52) < 2\n",
+    "    yearly_incidence.append(one_year.sum())\n",
+    "    year.append(week2.year)\n",
+    "yearly_incidence = pd.Series(data=yearly_incidence, index=year)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Voici les incidences annuelles :"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fb8951bd2b0>"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "yearly_incidence.plot(style='*')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Une liste triée permet de plus facilement répérer les valeurs les plus faibles (au début) et les plus élevées (à la fin)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2020    221186\n",
+       "2002    516689\n",
+       "2018    542312\n",
+       "2017    551041\n",
+       "1996    564901\n",
+       "2019    584066\n",
+       "2015    604382\n",
+       "2000    617597\n",
+       "2001    619041\n",
+       "2012    624573\n",
+       "2005    628464\n",
+       "2006    632833\n",
+       "2011    642368\n",
+       "1993    643387\n",
+       "1995    652478\n",
+       "1994    661409\n",
+       "1998    677775\n",
+       "1997    683434\n",
+       "2014    685769\n",
+       "2013    698332\n",
+       "2007    717352\n",
+       "2008    749478\n",
+       "1999    756456\n",
+       "2003    758363\n",
+       "2004    777388\n",
+       "2016    782114\n",
+       "2010    829911\n",
+       "1992    832939\n",
+       "2009    842373\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "yearly_incidence.sort_values()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Attention, il y a un piège - l'année 2020 n'est pas complète, puisqu'elle s'étende du 1er sept 2020 au 1er sept 2021.\n",
+    "Les bonnes réponses sont donc 2009 pour la plus forte, 2002 pour la plus faible."
+   ]
+  }
+ ],
  "metadata": {
   "kernelspec": {
    "display_name": "Python 3",
@@ -16,10 +1475,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 2
 }
-
diff --git a/module3/exo2/incidence_varicelle.csv b/module3/exo2/incidence_varicelle.csv
new file mode 100644
index 0000000000000000000000000000000000000000..8ae86a753feac0f874d74e05f654a370f8a490ba
--- /dev/null
+++ b/module3/exo2/incidence_varicelle.csv
@@ -0,0 +1,1574 @@
+,week,indicator,inc,inc_low,inc_up,inc100,inc100_low,inc100_up,geo_insee,geo_name
+0,202103,7,9306,6327,12285,14,9,19,FR,France
+1,202102,7,7846,5464,10228,12,8,16,FR,France
+2,202101,7,10531,7755,13307,16,12,20,FR,France
+3,202053,7,11978,8406,15550,18,13,23,FR,France
+4,202052,7,12012,8285,15739,18,12,24,FR,France
+5,202051,7,10564,7574,13554,16,11,21,FR,France
+6,202050,7,7063,4744,9382,11,7,15,FR,France
+7,202049,7,5026,3145,6907,8,5,11,FR,France
+8,202048,7,6683,4312,9054,10,6,14,FR,France
+9,202047,7,4999,2963,7035,8,5,11,FR,France
+10,202046,7,3752,1963,5541,6,3,9,FR,France
+11,202045,7,3696,2016,5376,6,3,9,FR,France
+12,202044,7,4391,2375,6407,7,4,10,FR,France
+13,202043,7,4376,2505,6247,7,4,10,FR,France
+14,202042,7,4000,1979,6021,6,3,9,FR,France
+15,202041,7,3961,2099,5823,6,3,9,FR,France
+16,202040,7,2078,675,3481,3,1,5,FR,France
+17,202039,7,1049,237,1861,2,1,3,FR,France
+18,202038,7,2253,782,3724,3,1,5,FR,France
+19,202037,7,1584,405,2763,2,0,4,FR,France
+20,202036,7,919,100,1738,1,0,2,FR,France
+21,202035,7,828,0,1694,1,0,2,FR,France
+22,202034,7,2272,371,4173,3,0,6,FR,France
+23,202033,7,1284,177,2391,2,0,4,FR,France
+24,202032,7,2650,689,4611,4,1,7,FR,France
+25,202031,7,1303,100,2506,2,0,4,FR,France
+26,202030,7,1385,75,2695,2,0,4,FR,France
+27,202029,7,841,10,1672,1,0,2,FR,France
+28,202028,7,728,0,1515,1,0,2,FR,France
+29,202027,7,986,149,1823,1,0,2,FR,France
+30,202026,7,694,0,1454,1,0,2,FR,France
+31,202025,7,228,0,597,0,0,1,FR,France
+32,202024,7,388,0,959,1,0,2,FR,France
+33,202023,7,558,1,1115,1,0,2,FR,France
+34,202022,7,277,0,633,0,0,1,FR,France
+35,202021,7,602,36,1168,1,0,2,FR,France
+36,202020,7,824,20,1628,1,0,2,FR,France
+37,202019,7,310,0,753,0,0,1,FR,France
+38,202018,7,849,98,1600,1,0,2,FR,France
+39,202017,7,272,0,658,0,0,1,FR,France
+40,202016,7,758,78,1438,1,0,2,FR,France
+41,202015,7,1918,675,3161,3,1,5,FR,France
+42,202014,7,3879,2227,5531,6,3,9,FR,France
+43,202013,7,7326,5236,9416,11,8,14,FR,France
+44,202012,7,8123,5790,10456,12,8,16,FR,France
+45,202011,7,10198,7568,12828,15,11,19,FR,France
+46,202010,7,9011,6691,11331,14,10,18,FR,France
+47,202009,7,13631,10544,16718,21,16,26,FR,France
+48,202008,7,10424,7708,13140,16,12,20,FR,France
+49,202007,7,8959,6574,11344,14,10,18,FR,France
+50,202006,7,9264,6925,11603,14,10,18,FR,France
+51,202005,7,8505,6314,10696,13,10,16,FR,France
+52,202004,7,7991,5831,10151,12,9,15,FR,France
+53,202003,7,5968,4100,7836,9,6,12,FR,France
+54,202002,7,6534,4530,8538,10,7,13,FR,France
+55,202001,7,9835,7019,12651,15,11,19,FR,France
+56,201952,7,7941,5246,10636,12,8,16,FR,France
+57,201951,7,5823,3675,7971,9,6,12,FR,France
+58,201950,7,6424,4276,8572,10,7,13,FR,France
+59,201949,7,6621,4540,8702,10,7,13,FR,France
+60,201948,7,5542,3383,7701,8,5,11,FR,France
+61,201947,7,7536,5058,10014,11,7,15,FR,France
+62,201946,7,2638,1316,3960,4,2,6,FR,France
+63,201945,7,4492,2615,6369,7,4,10,FR,France
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+65,201943,7,4834,2751,6917,7,4,10,FR,France
+66,201942,7,6279,3989,8569,10,7,13,FR,France
+67,201941,7,4130,2030,6230,6,3,9,FR,France
+68,201940,7,4211,2218,6204,6,3,9,FR,France
+69,201939,7,3137,1310,4964,5,2,8,FR,France
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+74,201934,7,1997,605,3389,3,1,5,FR,France
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+107,201901,7,15951,12224,19678,24,18,30,FR,France
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+115,201845,7,7479,4820,10138,11,7,15,FR,France
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+120,201840,7,3858,1827,5889,6,3,9,FR,France
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+125,201835,7,872,0,1916,1,0,3,FR,France
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+153,201807,7,13453,10096,16810,20,15,25,FR,France
+154,201806,7,15491,11679,19303,24,18,30,FR,France
+155,201805,7,15078,11374,18782,23,17,29,FR,France
+156,201804,7,14562,10973,18151,22,17,27,FR,France
+157,201803,7,7972,5473,10471,12,8,16,FR,France
+158,201802,7,10976,7974,13978,17,12,22,FR,France
+159,201801,7,11471,8430,14512,17,12,22,FR,France
+160,201752,7,11120,7732,14508,17,12,22,FR,France
+161,201751,7,8055,5279,10831,12,8,16,FR,France
+162,201750,7,10095,7184,13006,15,11,19,FR,France
+163,201749,7,11214,8103,14325,17,12,22,FR,France
+164,201748,7,8686,5706,11666,13,8,18,FR,France
+165,201747,7,8741,5969,11513,13,9,17,FR,France
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+170,201742,7,4490,2218,6762,7,4,10,FR,France
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+172,201740,7,4902,2504,7300,8,4,12,FR,France
+173,201739,7,2901,917,4885,4,1,7,FR,France
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+180,201732,7,4194,1599,6789,6,2,10,FR,France
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+183,201729,7,15320,10560,20080,24,17,31,FR,France
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+185,201727,7,12000,7980,16020,18,12,24,FR,France
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+191,201721,7,21160,15647,26673,32,24,40,FR,France
+192,201720,7,19412,14439,24385,30,22,38,FR,France
+193,201719,7,20724,15468,25980,32,24,40,FR,France
+194,201718,7,14497,10154,18840,22,15,29,FR,France
+195,201717,7,17548,12284,22812,27,19,35,FR,France
+196,201716,7,14963,10491,19435,23,16,30,FR,France
+197,201715,7,16400,11762,21038,25,18,32,FR,France
+198,201714,7,18892,13332,24452,29,20,38,FR,France
+199,201713,7,21702,16488,26916,33,25,41,FR,France
+200,201712,7,18534,14161,22907,28,21,35,FR,France
+201,201711,7,18361,12709,24013,28,19,37,FR,France
+202,201710,7,10218,6896,13540,16,11,21,FR,France
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+205,201707,7,10991,7538,14444,17,12,22,FR,France
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+207,201705,7,8885,6064,11706,14,10,18,FR,France
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+218,201646,7,4683,2458,6908,7,4,10,FR,France
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+226,201638,7,2550,0,5121,4,0,8,FR,France
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+228,201636,7,1621,33,3209,2,0,4,FR,France
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+235,201629,7,15769,9829,21709,24,15,33,FR,France
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+240,201624,7,16465,11779,21151,25,18,32,FR,France
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+278,201539,7,5142,2663,7621,8,4,12,FR,France
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+281,201536,7,3852,1413,6291,6,2,10,FR,France
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+1432,199332,7,12711,8079,17343,22,14,30,FR,France
+1433,199331,7,12481,7874,17088,22,14,30,FR,France
+1434,199330,7,12584,8619,16549,22,15,29,FR,France
+1435,199329,7,13179,8991,17367,23,16,30,FR,France
+1436,199328,7,15293,11335,19251,27,20,34,FR,France
+1437,199327,7,14134,9791,18477,25,17,33,FR,France
+1438,199326,7,17937,13577,22297,31,23,39,FR,France
+1439,199325,7,19581,14916,24246,34,26,42,FR,France
+1440,199324,7,18285,13450,23120,32,24,40,FR,France
+1441,199323,7,16003,11927,20079,28,21,35,FR,France
+1442,199322,7,12652,8597,16707,22,15,29,FR,France
+1443,199321,7,15218,10970,19466,27,20,34,FR,France
+1444,199320,7,11343,7655,15031,20,14,26,FR,France
+1445,199319,7,12086,8856,15316,21,15,27,FR,France
+1446,199318,7,18898,14305,23491,33,25,41,FR,France
+1447,199317,7,14969,10565,19373,26,18,34,FR,France
+1448,199316,7,15102,11226,18978,26,19,33,FR,France
+1449,199315,7,15058,11183,18933,26,19,33,FR,France
+1450,199314,7,12425,9045,15805,22,16,28,FR,France
+1451,199313,7,12266,8927,15605,21,15,27,FR,France
+1452,199312,7,10821,7884,13758,19,14,24,FR,France
+1453,199311,7,11021,8006,14036,19,14,24,FR,France
+1454,199310,7,15847,12158,19536,28,22,34,FR,France
+1455,199309,7,15084,11059,19109,26,19,33,FR,France
+1456,199308,7,16967,12936,20998,30,23,37,FR,France
+1457,199307,7,16057,12350,19764,28,22,34,FR,France
+1458,199306,7,15887,12275,19499,28,22,34,FR,France
+1459,199305,7,15954,12443,19465,28,22,34,FR,France
+1460,199304,7,12374,9426,15322,22,17,27,FR,France
+1461,199303,7,15283,11831,18735,27,21,33,FR,France
+1462,199302,7,13366,10262,16470,23,18,28,FR,France
+1463,199301,7,18678,14977,22379,33,27,39,FR,France
+1464,199253,7,17829,13827,21831,31,24,38,FR,France
+1465,199252,7,14330,10582,18078,25,18,32,FR,France
+1466,199251,7,14635,11262,18008,26,20,32,FR,France
+1467,199250,7,15252,11566,18938,27,21,33,FR,France
+1468,199249,7,14411,11187,17635,25,19,31,FR,France
+1469,199248,7,10048,7396,12700,18,13,23,FR,France
+1470,199247,7,13069,9752,16386,23,17,29,FR,France
+1471,199246,7,6900,4727,9073,12,8,16,FR,France
+1472,199245,7,10791,7794,13788,19,14,24,FR,France
+1473,199244,7,10205,7482,12928,18,13,23,FR,France
+1474,199243,7,7196,4908,9484,13,9,17,FR,France
+1475,199242,7,5748,3738,7758,10,6,14,FR,France
+1476,199241,7,3587,2045,5129,6,3,9,FR,France
+1477,199240,7,5654,3442,7866,10,6,14,FR,France
+1478,199239,7,4747,2751,6743,8,5,11,FR,France
+1479,199238,7,2842,1306,4378,5,2,8,FR,France
+1480,199237,7,4103,2203,6003,7,4,10,FR,France
+1481,199236,7,2801,1200,4402,5,2,8,FR,France
+1482,199235,7,6428,3717,9139,11,6,16,FR,France
+1483,199234,7,7517,4190,10844,13,7,19,FR,France
+1484,199233,7,9951,5955,13947,17,10,24,FR,France
+1485,199232,7,16090,11337,20843,28,20,36,FR,France
+1486,199231,7,17156,12441,21871,30,22,38,FR,France
+1487,199230,7,21780,16301,27259,38,28,48,FR,France
+1488,199229,7,18926,13397,24455,33,23,43,FR,France
+1489,199228,7,28144,20384,35904,49,35,63,FR,France
+1490,199227,7,29388,22331,36445,51,39,63,FR,France
+1491,199226,7,27933,21686,34180,49,38,60,FR,France
+1492,199225,7,26446,21153,31739,46,37,55,FR,France
+1493,199224,7,19614,14769,24459,34,26,42,FR,France
+1494,199223,7,23628,17852,29404,41,31,51,FR,France
+1495,199222,7,20438,14868,26008,36,26,46,FR,France
+1496,199221,7,22595,17395,27795,40,31,49,FR,France
+1497,199220,7,21092,15963,26221,37,28,46,FR,France
+1498,199219,7,19210,13934,24486,34,25,43,FR,France
+1499,199218,7,30273,22605,37941,53,40,66,FR,France
+1500,199217,7,19162,14251,24073,34,25,43,FR,France
+1501,199216,7,15583,11158,20008,27,19,35,FR,France
+1502,199215,7,15473,10723,20223,27,19,35,FR,France
+1503,199214,7,14455,10040,18870,25,17,33,FR,France
+1504,199213,7,17146,12105,22187,30,21,39,FR,France
+1505,199212,7,15838,10923,20753,28,19,37,FR,France
+1506,199211,7,20003,13824,26182,35,24,46,FR,France
+1507,199210,7,22906,16060,29752,40,28,52,FR,France
+1508,199209,7,21824,15687,27961,38,27,49,FR,France
+1509,199208,7,15243,10265,20221,27,18,36,FR,France
+1510,199207,7,22633,16160,29106,40,29,51,FR,France
+1511,199206,7,17009,12219,21799,30,22,38,FR,France
+1512,199205,7,15997,11590,20404,28,20,36,FR,France
+1513,199204,7,20690,15075,26305,36,26,46,FR,France
+1514,199203,7,18586,12684,24488,33,23,43,FR,France
+1515,199202,7,16588,10590,22586,29,18,40,FR,France
+1516,199201,7,23607,16552,30662,41,29,53,FR,France
+1517,199152,7,15184,10392,19976,27,19,35,FR,France
+1518,199151,7,15043,10624,19462,26,18,34,FR,France
+1519,199150,7,14115,9737,18493,25,17,33,FR,France
+1520,199149,7,13304,8548,18060,23,15,31,FR,France
+1521,199148,7,15370,10164,20576,27,18,36,FR,France
+1522,199147,7,12813,8139,17487,23,15,31,FR,France
+1523,199146,7,6453,3123,9783,11,5,17,FR,France
+1524,199145,7,8048,4083,12013,14,7,21,FR,France
+1525,199144,7,9882,5623,14141,17,10,24,FR,France
+1526,199143,7,14307,8645,19969,25,15,35,FR,France
+1527,199142,7,6419,3334,9504,11,6,16,FR,France
+1528,199141,7,6168,3113,9223,11,6,16,FR,France
+1529,199140,7,3615,1159,6071,6,2,10,FR,France
+1530,199139,7,3105,472,5738,5,0,10,FR,France
+1531,199138,7,4446,1435,7457,8,3,13,FR,France
+1532,199137,7,1457,0,3262,3,0,6,FR,France
+1533,199136,7,3053,29,6077,5,0,10,FR,France
+1534,199135,7,805,0,2556,1,0,4,FR,France
+1535,199134,7,5512,856,10168,10,2,18,FR,France
+1536,199133,7,7347,2903,11791,13,5,21,FR,France
+1537,199132,7,16099,7334,24864,28,13,43,FR,France
+1538,199131,7,16803,8145,25461,30,15,45,FR,France
+1539,199130,7,15915,6368,25462,28,11,45,FR,France
+1540,199129,7,23744,14703,32785,42,26,58,FR,France
+1541,199128,7,24222,15617,32827,43,28,58,FR,France
+1542,199127,7,20309,12868,27750,36,23,49,FR,France
+1543,199126,7,17608,11304,23912,31,20,42,FR,France
+1544,199125,7,16169,10700,21638,28,18,38,FR,France
+1545,199124,7,16171,10071,22271,28,17,39,FR,France
+1546,199123,7,11947,7671,16223,21,13,29,FR,France
+1547,199122,7,15452,9953,20951,27,17,37,FR,France
+1548,199121,7,14903,8975,20831,26,16,36,FR,France
+1549,199120,7,19053,12742,25364,34,23,45,FR,France
+1550,199119,7,16739,11246,22232,29,19,39,FR,France
+1551,199118,7,21385,13882,28888,38,25,51,FR,France
+1552,199117,7,13462,8877,18047,24,16,32,FR,France
+1553,199116,7,14857,10068,19646,26,18,34,FR,France
+1554,199115,7,13975,9781,18169,25,18,32,FR,France
+1555,199114,7,12265,7684,16846,22,14,30,FR,France
+1556,199113,7,9567,6041,13093,17,11,23,FR,France
+1557,199112,7,10864,7331,14397,19,13,25,FR,France
+1558,199111,7,15574,11184,19964,27,19,35,FR,France
+1559,199110,7,16643,11372,21914,29,20,38,FR,France
+1560,199109,7,13741,8780,18702,24,15,33,FR,France
+1561,199108,7,13289,8813,17765,23,15,31,FR,France
+1562,199107,7,12337,8077,16597,22,15,29,FR,France
+1563,199106,7,10877,7013,14741,19,12,26,FR,France
+1564,199105,7,10442,6544,14340,18,11,25,FR,France
+1565,199104,7,7913,4563,11263,14,8,20,FR,France
+1566,199103,7,15387,10484,20290,27,18,36,FR,France
+1567,199102,7,16277,11046,21508,29,20,38,FR,France
+1568,199101,7,15565,10271,20859,27,18,36,FR,France
+1569,199052,7,19375,13295,25455,34,23,45,FR,France
+1570,199051,7,19080,13807,24353,34,25,43,FR,France
+1571,199050,7,11079,6660,15498,20,12,28,FR,France
+1572,199049,7,1143,0,2610,2,0,5,FR,France
diff --git a/module3/exo3/exercice_fr.ipynb b/module3/exo3/exercice_fr.ipynb
index 89a215b4dd59c056c1069e9169bf63811ba07e50..438e917f50444378c452e0a1b7c59b924d96fc87 100644
--- a/module3/exo3/exercice_fr.ipynb
+++ b/module3/exo3/exercice_fr.ipynb
@@ -2157,7 +2157,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Il restent deux petites modifications à faire.\n",
+    "Il reste deux petites modifications à faire.\n",
     "\n",
     "Premièrement, nous définissons les périodes d'observation\n",
     "comme nouvel index de notre jeu de données. Ceci en fait\n",