diff --git a/module3/exo1/analyse-syndrome-grippal.ipynb b/module3/exo1/analyse-syndrome-grippal.ipynb
index e25423d19c099b6725c80fb5eab1b2fe9d52e907..29bb4a361728804c312c35116449c8429245a1a8 100644
--- a/module3/exo1/analyse-syndrome-grippal.ipynb
+++ b/module3/exo1/analyse-syndrome-grippal.ipynb
@@ -61,7 +61,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [
     {
@@ -1026,7 +1026,7 @@
        "[1883 rows x 10 columns]"
       ]
      },
-     "execution_count": 26,
+     "execution_count": 28,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1034,7 +1034,6 @@
    "source": [
     "path_to_file = \"Donnee_Grippe_France\"\n",
     "csv_file = \"incidence-PAY-3.csv\"\n",
-    "\n",
     "if os.path.exists(os.path.join(path_to_file,csv_file)):\n",
     "    raw_data = pd.read_csv(os.path.join(path_to_file,csv_file), skiprows=1)\n",
     "else: \n",
@@ -1046,54 +1045,1074 @@
     "raw_data"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Le code ci-dessus permet de vérifier l'existence du fichier de donnee 'csv_file' dans le dossier 'path_to_file'. Si ceux-ci n'existent pas ils sont créés et la fichier et lu depuis la sauvegarde locale."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Y a-t-il des points manquants dans ce jeux de données ? Oui, la semaine 19 de l'année 1989 n'a pas de valeurs associées."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "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>1646</th>\n",
+       "      <td>198919</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        week  indicator  inc  inc_low  inc_up  inc100  inc100_low  inc100_up  \\\n",
+       "1646  198919          3    0      NaN     NaN       0         NaN        NaN   \n",
+       "\n",
+       "     geo_insee geo_name  \n",
+       "1646        FR   France  "
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data[raw_data.isnull().any(axis=1)]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Nous éliminons ce point, ce qui n'a pas d'impact fort sur notre analyse qui est assez simple."
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 40,
    "metadata": {
-    "scrolled": true
+    "scrolled": false
    },
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "total 84\r\n",
-      "-rw-r--r-- 1 jovyan users 84773 Dec  4 16:27 incidence-PAY-3.csv\r\n"
-     ]
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>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>202048</td>\n",
+       "      <td>3</td>\n",
+       "      <td>29410</td>\n",
+       "      <td>23486.0</td>\n",
+       "      <td>35334.0</td>\n",
+       "      <td>45</td>\n",
+       "      <td>36.0</td>\n",
+       "      <td>54.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>202047</td>\n",
+       "      <td>3</td>\n",
+       "      <td>19180</td>\n",
+       "      <td>15348.0</td>\n",
+       "      <td>23012.0</td>\n",
+       "      <td>29</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>202046</td>\n",
+       "      <td>3</td>\n",
+       "      <td>24801</td>\n",
+       "      <td>20503.0</td>\n",
+       "      <td>29099.0</td>\n",
+       "      <td>38</td>\n",
+       "      <td>31.0</td>\n",
+       "      <td>45.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>202045</td>\n",
+       "      <td>3</td>\n",
+       "      <td>42516</td>\n",
+       "      <td>36857.0</td>\n",
+       "      <td>48175.0</td>\n",
+       "      <td>65</td>\n",
+       "      <td>56.0</td>\n",
+       "      <td>74.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>202044</td>\n",
+       "      <td>3</td>\n",
+       "      <td>44567</td>\n",
+       "      <td>38521.0</td>\n",
+       "      <td>50613.0</td>\n",
+       "      <td>68</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>77.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>202043</td>\n",
+       "      <td>3</td>\n",
+       "      <td>43737</td>\n",
+       "      <td>37523.0</td>\n",
+       "      <td>49951.0</td>\n",
+       "      <td>66</td>\n",
+       "      <td>57.0</td>\n",
+       "      <td>75.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>202042</td>\n",
+       "      <td>3</td>\n",
+       "      <td>35145</td>\n",
+       "      <td>29812.0</td>\n",
+       "      <td>40478.0</td>\n",
+       "      <td>53</td>\n",
+       "      <td>45.0</td>\n",
+       "      <td>61.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>202041</td>\n",
+       "      <td>3</td>\n",
+       "      <td>27877</td>\n",
+       "      <td>23206.0</td>\n",
+       "      <td>32548.0</td>\n",
+       "      <td>42</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>49.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>202040</td>\n",
+       "      <td>3</td>\n",
+       "      <td>20443</td>\n",
+       "      <td>16381.0</td>\n",
+       "      <td>24505.0</td>\n",
+       "      <td>31</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>37.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>202039</td>\n",
+       "      <td>3</td>\n",
+       "      <td>19810</td>\n",
+       "      <td>15900.0</td>\n",
+       "      <td>23720.0</td>\n",
+       "      <td>30</td>\n",
+       "      <td>24.0</td>\n",
+       "      <td>36.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>202038</td>\n",
+       "      <td>3</td>\n",
+       "      <td>25562</td>\n",
+       "      <td>21142.0</td>\n",
+       "      <td>29982.0</td>\n",
+       "      <td>39</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>46.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>202037</td>\n",
+       "      <td>3</td>\n",
+       "      <td>18485</td>\n",
+       "      <td>14649.0</td>\n",
+       "      <td>22321.0</td>\n",
+       "      <td>28</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>34.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>202036</td>\n",
+       "      <td>3</td>\n",
+       "      <td>10390</td>\n",
+       "      <td>7646.0</td>\n",
+       "      <td>13134.0</td>\n",
+       "      <td>16</td>\n",
+       "      <td>12.0</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>202035</td>\n",
+       "      <td>3</td>\n",
+       "      <td>9918</td>\n",
+       "      <td>6842.0</td>\n",
+       "      <td>12994.0</td>\n",
+       "      <td>15</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>202034</td>\n",
+       "      <td>3</td>\n",
+       "      <td>6084</td>\n",
+       "      <td>3090.0</td>\n",
+       "      <td>9078.0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>202033</td>\n",
+       "      <td>3</td>\n",
+       "      <td>6106</td>\n",
+       "      <td>3411.0</td>\n",
+       "      <td>8801.0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>202032</td>\n",
+       "      <td>3</td>\n",
+       "      <td>5918</td>\n",
+       "      <td>3330.0</td>\n",
+       "      <td>8506.0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>202031</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4351</td>\n",
+       "      <td>2269.0</td>\n",
+       "      <td>6433.0</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>202030</td>\n",
+       "      <td>3</td>\n",
+       "      <td>8179</td>\n",
+       "      <td>5442.0</td>\n",
+       "      <td>10916.0</td>\n",
+       "      <td>12</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>202029</td>\n",
+       "      <td>3</td>\n",
+       "      <td>8687</td>\n",
+       "      <td>5860.0</td>\n",
+       "      <td>11514.0</td>\n",
+       "      <td>13</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>202028</td>\n",
+       "      <td>3</td>\n",
+       "      <td>8340</td>\n",
+       "      <td>5701.0</td>\n",
+       "      <td>10979.0</td>\n",
+       "      <td>13</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>202027</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4066</td>\n",
+       "      <td>2406.0</td>\n",
+       "      <td>5726.0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>202026</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4039</td>\n",
+       "      <td>2389.0</td>\n",
+       "      <td>5689.0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>202025</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2853</td>\n",
+       "      <td>1488.0</td>\n",
+       "      <td>4218.0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>202024</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3058</td>\n",
+       "      <td>1690.0</td>\n",
+       "      <td>4426.0</td>\n",
+       "      <td>5</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>202023</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4168</td>\n",
+       "      <td>2468.0</td>\n",
+       "      <td>5868.0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>202022</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3580</td>\n",
+       "      <td>1947.0</td>\n",
+       "      <td>5213.0</td>\n",
+       "      <td>5</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>202021</td>\n",
+       "      <td>3</td>\n",
+       "      <td>6114</td>\n",
+       "      <td>4026.0</td>\n",
+       "      <td>8202.0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>12.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>202020</td>\n",
+       "      <td>3</td>\n",
+       "      <td>9315</td>\n",
+       "      <td>6775.0</td>\n",
+       "      <td>11855.0</td>\n",
+       "      <td>14</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>202019</td>\n",
+       "      <td>3</td>\n",
+       "      <td>11679</td>\n",
+       "      <td>8722.0</td>\n",
+       "      <td>14636.0</td>\n",
+       "      <td>18</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>22.0</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>1853</th>\n",
+       "      <td>198521</td>\n",
+       "      <td>3</td>\n",
+       "      <td>26096</td>\n",
+       "      <td>19621.0</td>\n",
+       "      <td>32571.0</td>\n",
+       "      <td>47</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1854</th>\n",
+       "      <td>198520</td>\n",
+       "      <td>3</td>\n",
+       "      <td>27896</td>\n",
+       "      <td>20885.0</td>\n",
+       "      <td>34907.0</td>\n",
+       "      <td>51</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>64.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1855</th>\n",
+       "      <td>198519</td>\n",
+       "      <td>3</td>\n",
+       "      <td>43154</td>\n",
+       "      <td>32821.0</td>\n",
+       "      <td>53487.0</td>\n",
+       "      <td>78</td>\n",
+       "      <td>59.0</td>\n",
+       "      <td>97.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1856</th>\n",
+       "      <td>198518</td>\n",
+       "      <td>3</td>\n",
+       "      <td>40555</td>\n",
+       "      <td>29935.0</td>\n",
+       "      <td>51175.0</td>\n",
+       "      <td>74</td>\n",
+       "      <td>55.0</td>\n",
+       "      <td>93.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1857</th>\n",
+       "      <td>198517</td>\n",
+       "      <td>3</td>\n",
+       "      <td>34053</td>\n",
+       "      <td>24366.0</td>\n",
+       "      <td>43740.0</td>\n",
+       "      <td>62</td>\n",
+       "      <td>44.0</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1858</th>\n",
+       "      <td>198516</td>\n",
+       "      <td>3</td>\n",
+       "      <td>50362</td>\n",
+       "      <td>36451.0</td>\n",
+       "      <td>64273.0</td>\n",
+       "      <td>91</td>\n",
+       "      <td>66.0</td>\n",
+       "      <td>116.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1859</th>\n",
+       "      <td>198515</td>\n",
+       "      <td>3</td>\n",
+       "      <td>63881</td>\n",
+       "      <td>45538.0</td>\n",
+       "      <td>82224.0</td>\n",
+       "      <td>116</td>\n",
+       "      <td>83.0</td>\n",
+       "      <td>149.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1860</th>\n",
+       "      <td>198514</td>\n",
+       "      <td>3</td>\n",
+       "      <td>134545</td>\n",
+       "      <td>114400.0</td>\n",
+       "      <td>154690.0</td>\n",
+       "      <td>244</td>\n",
+       "      <td>207.0</td>\n",
+       "      <td>281.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1861</th>\n",
+       "      <td>198513</td>\n",
+       "      <td>3</td>\n",
+       "      <td>197206</td>\n",
+       "      <td>176080.0</td>\n",
+       "      <td>218332.0</td>\n",
+       "      <td>357</td>\n",
+       "      <td>319.0</td>\n",
+       "      <td>395.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1862</th>\n",
+       "      <td>198512</td>\n",
+       "      <td>3</td>\n",
+       "      <td>245240</td>\n",
+       "      <td>223304.0</td>\n",
+       "      <td>267176.0</td>\n",
+       "      <td>445</td>\n",
+       "      <td>405.0</td>\n",
+       "      <td>485.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1863</th>\n",
+       "      <td>198511</td>\n",
+       "      <td>3</td>\n",
+       "      <td>276205</td>\n",
+       "      <td>252399.0</td>\n",
+       "      <td>300011.0</td>\n",
+       "      <td>501</td>\n",
+       "      <td>458.0</td>\n",
+       "      <td>544.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1864</th>\n",
+       "      <td>198510</td>\n",
+       "      <td>3</td>\n",
+       "      <td>353231</td>\n",
+       "      <td>326279.0</td>\n",
+       "      <td>380183.0</td>\n",
+       "      <td>640</td>\n",
+       "      <td>591.0</td>\n",
+       "      <td>689.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1865</th>\n",
+       "      <td>198509</td>\n",
+       "      <td>3</td>\n",
+       "      <td>369895</td>\n",
+       "      <td>341109.0</td>\n",
+       "      <td>398681.0</td>\n",
+       "      <td>670</td>\n",
+       "      <td>618.0</td>\n",
+       "      <td>722.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1866</th>\n",
+       "      <td>198508</td>\n",
+       "      <td>3</td>\n",
+       "      <td>389886</td>\n",
+       "      <td>359529.0</td>\n",
+       "      <td>420243.0</td>\n",
+       "      <td>707</td>\n",
+       "      <td>652.0</td>\n",
+       "      <td>762.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1867</th>\n",
+       "      <td>198507</td>\n",
+       "      <td>3</td>\n",
+       "      <td>471852</td>\n",
+       "      <td>432599.0</td>\n",
+       "      <td>511105.0</td>\n",
+       "      <td>855</td>\n",
+       "      <td>784.0</td>\n",
+       "      <td>926.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1868</th>\n",
+       "      <td>198506</td>\n",
+       "      <td>3</td>\n",
+       "      <td>565825</td>\n",
+       "      <td>518011.0</td>\n",
+       "      <td>613639.0</td>\n",
+       "      <td>1026</td>\n",
+       "      <td>939.0</td>\n",
+       "      <td>1113.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1869</th>\n",
+       "      <td>198505</td>\n",
+       "      <td>3</td>\n",
+       "      <td>637302</td>\n",
+       "      <td>592795.0</td>\n",
+       "      <td>681809.0</td>\n",
+       "      <td>1155</td>\n",
+       "      <td>1074.0</td>\n",
+       "      <td>1236.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1870</th>\n",
+       "      <td>198504</td>\n",
+       "      <td>3</td>\n",
+       "      <td>424937</td>\n",
+       "      <td>390794.0</td>\n",
+       "      <td>459080.0</td>\n",
+       "      <td>770</td>\n",
+       "      <td>708.0</td>\n",
+       "      <td>832.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1871</th>\n",
+       "      <td>198503</td>\n",
+       "      <td>3</td>\n",
+       "      <td>213901</td>\n",
+       "      <td>174689.0</td>\n",
+       "      <td>253113.0</td>\n",
+       "      <td>388</td>\n",
+       "      <td>317.0</td>\n",
+       "      <td>459.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1872</th>\n",
+       "      <td>198502</td>\n",
+       "      <td>3</td>\n",
+       "      <td>97586</td>\n",
+       "      <td>80949.0</td>\n",
+       "      <td>114223.0</td>\n",
+       "      <td>177</td>\n",
+       "      <td>147.0</td>\n",
+       "      <td>207.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1873</th>\n",
+       "      <td>198501</td>\n",
+       "      <td>3</td>\n",
+       "      <td>85489</td>\n",
+       "      <td>65918.0</td>\n",
+       "      <td>105060.0</td>\n",
+       "      <td>155</td>\n",
+       "      <td>120.0</td>\n",
+       "      <td>190.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1874</th>\n",
+       "      <td>198452</td>\n",
+       "      <td>3</td>\n",
+       "      <td>84830</td>\n",
+       "      <td>60602.0</td>\n",
+       "      <td>109058.0</td>\n",
+       "      <td>154</td>\n",
+       "      <td>110.0</td>\n",
+       "      <td>198.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1875</th>\n",
+       "      <td>198451</td>\n",
+       "      <td>3</td>\n",
+       "      <td>101726</td>\n",
+       "      <td>80242.0</td>\n",
+       "      <td>123210.0</td>\n",
+       "      <td>185</td>\n",
+       "      <td>146.0</td>\n",
+       "      <td>224.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1876</th>\n",
+       "      <td>198450</td>\n",
+       "      <td>3</td>\n",
+       "      <td>123680</td>\n",
+       "      <td>101401.0</td>\n",
+       "      <td>145959.0</td>\n",
+       "      <td>225</td>\n",
+       "      <td>184.0</td>\n",
+       "      <td>266.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1877</th>\n",
+       "      <td>198449</td>\n",
+       "      <td>3</td>\n",
+       "      <td>101073</td>\n",
+       "      <td>81684.0</td>\n",
+       "      <td>120462.0</td>\n",
+       "      <td>184</td>\n",
+       "      <td>149.0</td>\n",
+       "      <td>219.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1878</th>\n",
+       "      <td>198448</td>\n",
+       "      <td>3</td>\n",
+       "      <td>78620</td>\n",
+       "      <td>60634.0</td>\n",
+       "      <td>96606.0</td>\n",
+       "      <td>143</td>\n",
+       "      <td>110.0</td>\n",
+       "      <td>176.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1879</th>\n",
+       "      <td>198447</td>\n",
+       "      <td>3</td>\n",
+       "      <td>72029</td>\n",
+       "      <td>54274.0</td>\n",
+       "      <td>89784.0</td>\n",
+       "      <td>131</td>\n",
+       "      <td>99.0</td>\n",
+       "      <td>163.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1880</th>\n",
+       "      <td>198446</td>\n",
+       "      <td>3</td>\n",
+       "      <td>87330</td>\n",
+       "      <td>67686.0</td>\n",
+       "      <td>106974.0</td>\n",
+       "      <td>159</td>\n",
+       "      <td>123.0</td>\n",
+       "      <td>195.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1881</th>\n",
+       "      <td>198445</td>\n",
+       "      <td>3</td>\n",
+       "      <td>135223</td>\n",
+       "      <td>101414.0</td>\n",
+       "      <td>169032.0</td>\n",
+       "      <td>246</td>\n",
+       "      <td>184.0</td>\n",
+       "      <td>308.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1882</th>\n",
+       "      <td>198444</td>\n",
+       "      <td>3</td>\n",
+       "      <td>68422</td>\n",
+       "      <td>20056.0</td>\n",
+       "      <td>116788.0</td>\n",
+       "      <td>125</td>\n",
+       "      <td>37.0</td>\n",
+       "      <td>213.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1882 rows × 10 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        week  indicator     inc   inc_low    inc_up  inc100  inc100_low  \\\n",
+       "0     202048          3   29410   23486.0   35334.0      45        36.0   \n",
+       "1     202047          3   19180   15348.0   23012.0      29        23.0   \n",
+       "2     202046          3   24801   20503.0   29099.0      38        31.0   \n",
+       "3     202045          3   42516   36857.0   48175.0      65        56.0   \n",
+       "4     202044          3   44567   38521.0   50613.0      68        59.0   \n",
+       "5     202043          3   43737   37523.0   49951.0      66        57.0   \n",
+       "6     202042          3   35145   29812.0   40478.0      53        45.0   \n",
+       "7     202041          3   27877   23206.0   32548.0      42        35.0   \n",
+       "8     202040          3   20443   16381.0   24505.0      31        25.0   \n",
+       "9     202039          3   19810   15900.0   23720.0      30        24.0   \n",
+       "10    202038          3   25562   21142.0   29982.0      39        32.0   \n",
+       "11    202037          3   18485   14649.0   22321.0      28        22.0   \n",
+       "12    202036          3   10390    7646.0   13134.0      16        12.0   \n",
+       "13    202035          3    9918    6842.0   12994.0      15        10.0   \n",
+       "14    202034          3    6084    3090.0    9078.0       9         4.0   \n",
+       "15    202033          3    6106    3411.0    8801.0       9         5.0   \n",
+       "16    202032          3    5918    3330.0    8506.0       9         5.0   \n",
+       "17    202031          3    4351    2269.0    6433.0       7         4.0   \n",
+       "18    202030          3    8179    5442.0   10916.0      12         8.0   \n",
+       "19    202029          3    8687    5860.0   11514.0      13         9.0   \n",
+       "20    202028          3    8340    5701.0   10979.0      13         9.0   \n",
+       "21    202027          3    4066    2406.0    5726.0       6         3.0   \n",
+       "22    202026          3    4039    2389.0    5689.0       6         3.0   \n",
+       "23    202025          3    2853    1488.0    4218.0       4         2.0   \n",
+       "24    202024          3    3058    1690.0    4426.0       5         3.0   \n",
+       "25    202023          3    4168    2468.0    5868.0       6         3.0   \n",
+       "26    202022          3    3580    1947.0    5213.0       5         3.0   \n",
+       "27    202021          3    6114    4026.0    8202.0       9         6.0   \n",
+       "28    202020          3    9315    6775.0   11855.0      14        10.0   \n",
+       "29    202019          3   11679    8722.0   14636.0      18        14.0   \n",
+       "...      ...        ...     ...       ...       ...     ...         ...   \n",
+       "1853  198521          3   26096   19621.0   32571.0      47        35.0   \n",
+       "1854  198520          3   27896   20885.0   34907.0      51        38.0   \n",
+       "1855  198519          3   43154   32821.0   53487.0      78        59.0   \n",
+       "1856  198518          3   40555   29935.0   51175.0      74        55.0   \n",
+       "1857  198517          3   34053   24366.0   43740.0      62        44.0   \n",
+       "1858  198516          3   50362   36451.0   64273.0      91        66.0   \n",
+       "1859  198515          3   63881   45538.0   82224.0     116        83.0   \n",
+       "1860  198514          3  134545  114400.0  154690.0     244       207.0   \n",
+       "1861  198513          3  197206  176080.0  218332.0     357       319.0   \n",
+       "1862  198512          3  245240  223304.0  267176.0     445       405.0   \n",
+       "1863  198511          3  276205  252399.0  300011.0     501       458.0   \n",
+       "1864  198510          3  353231  326279.0  380183.0     640       591.0   \n",
+       "1865  198509          3  369895  341109.0  398681.0     670       618.0   \n",
+       "1866  198508          3  389886  359529.0  420243.0     707       652.0   \n",
+       "1867  198507          3  471852  432599.0  511105.0     855       784.0   \n",
+       "1868  198506          3  565825  518011.0  613639.0    1026       939.0   \n",
+       "1869  198505          3  637302  592795.0  681809.0    1155      1074.0   \n",
+       "1870  198504          3  424937  390794.0  459080.0     770       708.0   \n",
+       "1871  198503          3  213901  174689.0  253113.0     388       317.0   \n",
+       "1872  198502          3   97586   80949.0  114223.0     177       147.0   \n",
+       "1873  198501          3   85489   65918.0  105060.0     155       120.0   \n",
+       "1874  198452          3   84830   60602.0  109058.0     154       110.0   \n",
+       "1875  198451          3  101726   80242.0  123210.0     185       146.0   \n",
+       "1876  198450          3  123680  101401.0  145959.0     225       184.0   \n",
+       "1877  198449          3  101073   81684.0  120462.0     184       149.0   \n",
+       "1878  198448          3   78620   60634.0   96606.0     143       110.0   \n",
+       "1879  198447          3   72029   54274.0   89784.0     131        99.0   \n",
+       "1880  198446          3   87330   67686.0  106974.0     159       123.0   \n",
+       "1881  198445          3  135223  101414.0  169032.0     246       184.0   \n",
+       "1882  198444          3   68422   20056.0  116788.0     125        37.0   \n",
+       "\n",
+       "      inc100_up geo_insee geo_name  \n",
+       "0          54.0        FR   France  \n",
+       "1          35.0        FR   France  \n",
+       "2          45.0        FR   France  \n",
+       "3          74.0        FR   France  \n",
+       "4          77.0        FR   France  \n",
+       "5          75.0        FR   France  \n",
+       "6          61.0        FR   France  \n",
+       "7          49.0        FR   France  \n",
+       "8          37.0        FR   France  \n",
+       "9          36.0        FR   France  \n",
+       "10         46.0        FR   France  \n",
+       "11         34.0        FR   France  \n",
+       "12         20.0        FR   France  \n",
+       "13         20.0        FR   France  \n",
+       "14         14.0        FR   France  \n",
+       "15         13.0        FR   France  \n",
+       "16         13.0        FR   France  \n",
+       "17         10.0        FR   France  \n",
+       "18         16.0        FR   France  \n",
+       "19         17.0        FR   France  \n",
+       "20         17.0        FR   France  \n",
+       "21          9.0        FR   France  \n",
+       "22          9.0        FR   France  \n",
+       "23          6.0        FR   France  \n",
+       "24          7.0        FR   France  \n",
+       "25          9.0        FR   France  \n",
+       "26          7.0        FR   France  \n",
+       "27         12.0        FR   France  \n",
+       "28         18.0        FR   France  \n",
+       "29         22.0        FR   France  \n",
+       "...         ...       ...      ...  \n",
+       "1853       59.0        FR   France  \n",
+       "1854       64.0        FR   France  \n",
+       "1855       97.0        FR   France  \n",
+       "1856       93.0        FR   France  \n",
+       "1857       80.0        FR   France  \n",
+       "1858      116.0        FR   France  \n",
+       "1859      149.0        FR   France  \n",
+       "1860      281.0        FR   France  \n",
+       "1861      395.0        FR   France  \n",
+       "1862      485.0        FR   France  \n",
+       "1863      544.0        FR   France  \n",
+       "1864      689.0        FR   France  \n",
+       "1865      722.0        FR   France  \n",
+       "1866      762.0        FR   France  \n",
+       "1867      926.0        FR   France  \n",
+       "1868     1113.0        FR   France  \n",
+       "1869     1236.0        FR   France  \n",
+       "1870      832.0        FR   France  \n",
+       "1871      459.0        FR   France  \n",
+       "1872      207.0        FR   France  \n",
+       "1873      190.0        FR   France  \n",
+       "1874      198.0        FR   France  \n",
+       "1875      224.0        FR   France  \n",
+       "1876      266.0        FR   France  \n",
+       "1877      219.0        FR   France  \n",
+       "1878      176.0        FR   France  \n",
+       "1879      163.0        FR   France  \n",
+       "1880      195.0        FR   France  \n",
+       "1881      308.0        FR   France  \n",
+       "1882      213.0        FR   France  \n",
+       "\n",
+       "[1882 rows x 10 columns]"
+      ]
+     },
+     "execution_count": 40,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
-   "source": [
-    "ls -l Donnee_Grippe_France/"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Y a-t-il des points manquants dans ce jeux de données ? Oui, la semaine 19 de l'année 1989 n'a pas de valeurs associées."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "raw_data[raw_data.isnull().any(axis=1)]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Nous éliminons ce point, ce qui n'a pas d'impact fort sur notre analyse qui est assez simple."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
    "source": [
     "data = raw_data.dropna().copy()\n",
     "data"
@@ -1119,7 +2138,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 41,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1149,10 +2168,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 42,
+   "metadata": {},
    "outputs": [],
    "source": [
     "sorted_data = data.set_index('period').sort_index()"
@@ -1176,9 +2193,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 43,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1989-05-01/1989-05-07 1989-05-15/1989-05-21\n"
+     ]
+    }
+   ],
    "source": [
     "periods = sorted_data.index\n",
     "for p1, p2 in zip(periods[:-1], periods[1:]):\n",
@@ -1196,9 +2221,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 44,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fb575032240>"
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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+pg40lP3pvdYDidj+swJqFLBAKYOaCZSS5vIawYKEXrtK66FIUVLp9TLSjJSIBX8OwxUIlEw2h6fe2haeMIR6HlSrGI3DgjjQxA4WKCWgwlMb4aPeD4ahRHY9JSiSITb/TAX+i588tRL/+MuX8czbla0aWo155F5bvwfLNvdUnE8DfCah8KDZ0uBxKCUQI0JWiJpNDlnCQPmGiAaqFDWgsdJ7TUvfSDIW3HpU4pRfv2sAALCtZ7DsPAD7cHAhRNmTZn7kp38FUP40L+q6+0EVZApgDaUEVHsTZPJ68JUNeHlN1db6qkuqHuVV4fVU5FQyxItciUBRWVfqA7E1t9bSd18vnfo3N+zFcd96Ajv6hirOi4WjHSxQSkD1vIJMXl994HVc/PMFI3J9q4GNasXGGn4BVVtT3vWhVJbPQNpZOLQ1FTxuYjhT/oViqu5U6Ne3fa/14LyvdQnu/Os76BnM4Jnl5ZsZeWmE0mCBUgKxOlhe15Y6aE+qRqW32j/shIS2GARKXL74SuZwi8XCOyM22GsotasA9dIGNyed5q0ewr33F1iglIDqZdZucshS5vKqIVU3eVV2wUGpobQk/QVKFNPZqM5IpWW1FRT10KEw3evq7X0YGM6O+PWbEs77VO+3EurgcTYELFBKIF7jMR6lzeW1/3wClY9DkWHDBh9KFGbEuGvyqlCgWPZlavv+pVPe58jAcBZn//AZXPO7N0a8FM2yg7B3IF12HnWibDUMLFBKwA0bbgANen8YKR9VlJebX0jrUcl1lMmrUme5rcmspk55VxsrPrZprxPtVo3VJ7vHtwIA1vHEjlWDBUoJuHbweg4bpmgb2XKI4tI25Y/KKR92en4VzPKvocyllYacN4JTPkguq3m+mqowz5eK2oviW9iPFP6KYIFSArEGmtakAYoYSFUnwpQXCzNvVCIM8o79Sk1elj6UutCii8uqvp1q1M9ILsE2r5JggVICNuNQRpL9aT2UUoR2pY2TelZGkxd505VDVJFP9iav2kd5+RVB7atG6VzhVYVrMQ4sUEqg1hMvWjXU9TAOJQqTV0lpqxU5VfumqRGc8hTglHcFSsOoKCqr2r/7RoAFSgkoDaWSOZ2qRf2XMJiSTF5RaSgh9o16mDne3ocywgWxwK+o1RR0UZjXwuoE44UFSgnEQ0bKj/QcX1YfRjV7gMFFqDAP+1wqbaTUszKZpdz50RpITNfy/QeFWVfTDCUK/jMjDwuUEqCQSJ1KHa5R4H5EtfShNFhUTTV7/dUSSnVQFf1NXup/FcqX11Aaqz42MixQSkAtl2HUUEa41lkpKLIMjRCJFhVRmbxMRDGwMSrTiW0R6sMpX1yGampOUVyqXqaRaRRYoJRA2FiCelietR7U/Cg+ZJsGMR8xFI1T3hzkFd3Ynmq1p/XQofD3oahjI1++egii2N+oWKAQUZyIXiWi/5W/u4hoHhGtkP/HaWmvI6KVRLSciOZq+08mojflsVtI2paIqImIfiv3v0hE3do5l8lrrCCiyyq9DxtiIdNnjLTJy2qwn0xSDw1KJVTTKW/d66+DsR22wrOWrz8/ENTHh5Krng/FFV5VuBbjEIWG8iUAy7Tf1wKYL4SYCWC+/A0iOhrAJQBmATgPwM+ISM3GdyuAKwDMlH/nyf2XA9gthDgMwM0AbpJ5dQG4HsCpAOYAuF4XXCNFfsVG/+O1WnhLRxRtNCYlhQ1XLFCUU95fR6mHJQFKpaZlDRqHAvOxqIlCQ9mfFqyLgooEChFNB3ABgP/Wdl8I4C65fReAj2j77xNCDAkh3gGwEsAcIpoCoEMIsUA4b+3ugnNUXg8COEdqL3MBzBNC7BJC7AYwD3khNGLkNRT/rmo9LA1cDz6Uak29ElVDH+pDsUxXDex9KCNbjiCCJiitbtiw3IikPlaex/5ApRrKfwC4BoDewk4WQmwGAPl/ktw/DcB6Ld0GuW+a3C7c7zlHCJEBsBfA+IC8RpT8jLH+x0fah2JTqVWS/3ruHeztL3+W1VpjF4BgnzaIagxsjMq5a1uC2jrlzUsAR+X3siHKK9RDZ6IRKFugENGHAGwTQrxie4rPPhGwv9xzvBcluoKIFhLRwu3by1+5zcnL+W/6WOvBKa/z82dX1eS6UTQWJbWHIx7lFc1MwdWkHkw0fvVAfTvV8EepZ1DtqYBGgre29OC+l9bVtAw2VKKhvBvAh4loDYD7AJxNRL8CsFWasSD/b5PpNwCYoZ0/HcAmuX+6z37POUSUANAJYFdAXkUIIW4XQswWQsyeOHFieXcqCXPKj7iGYvNh1L4dqZrJy01b4U3bXquysOFosC9rRBcsgyATYTXb5SinAKq1gD7vP57DtQ+9WdMy2FC2QBFCXCeEmC6E6IbjbH9SCPH3AB4BoKKuLgPwsNx+BMAlMnLrYDjO95ekWayXiE6T/pFLC85ReV0kryEAPAHgXCIaJ53x58p9I0p+PZQaCRQreVIHEiUCqjv1SrDfqREXLauHoo6GqVfydSOKEo1+EiOQ540A7ieiywGsA3AxAAghlhDR/QCWAsgAuEoIodbm/ByAXwJoAfCY/AOAOwDcQ0Qr4Wgml8i8dhHRdwC8LNN9WwixawTuxRejyasOvmK9COX2ijfuGcCKrb0484hJ4Yn9ylDmdcvNo3IfiswnJKNqa16+51umG8mGO5cT2NIziKljW3yPB5mGqzk5ZCRXGCVh+NUiEoEihHgawNNyeyeAcwzpbgBwg8/+hQCO8dk/CCmQfI7dCeDOcstcDqpOmTSRepjLK4p6f8Etz2FPfxprbrygrPOjGQBon0flUV52tvZGalRGsqw/eWolfjTvbTzztTNx0Pg2Yzq/EriLoo1Q2XRYQ6k+PFK+BFSdqtXARhuiMHntkdFhjTLBZFQDG8NeXxSv1zTWxRbbex3JV/fs205wy9aeId/jQWM3qjk4NJoZG1Retf+2GwEWKCWgKtVQxjAOZcSd8hZpdJNXhZ7gcgVkJCavUnwoFV7LHb0dKlCqq3kZcrBKNaImL5l3LKR+BflQqjmwsZJOVr3NPFHvgo0FShn0DWV899dDpdNLUGlxhg2CM7QMQt8uVyhVzyufl5vB+dTDOBRbRrJvk1/h0jSzQMDUK6rHXwWjl61vLDiP+jJ51Us5TLBAKQFVMfuH/QVKPc3lFQUmTawUyi1PKYM4K3fKy0Yj5HYjmb4+IvNcGNXQUOIGFSV4ZoFqaihR5BEcAVht6m2sWyEsUEpA9aoGhrO+x0fcKV9iqnJ7xamEUy3K1VD0MpT7RKo7OeTIO+XzEyaWnUVJjKRpxBUoISuS+fpQXA1l5IliMS+301In7Xi9CDYTLFBKQL1LkyZS770HW1RDkSnTgxq1ycuUR1TjQ2xNI5W8XnU/Fa8uaZluJKuimnrILE/MU69U1Yei/kdi8qqPb7teymGCBUoJhEV5jbhAsTED6U75MkeiKEtGFBE5jaCh2NrJK+n15+ewqg4jqS3bPgf/qVfyR0caV/Os4L2p8tZLQ17vfVYWKCWgKqZRoNRBpYuiBEFO1VLLULYPxSKP6HwoKp8Qk1cFX3O+t1yhhmLtQ6noMvJawR0nU1nyAxvNeVbTh1KJMLANKa8W9W4FYYFSArXWUGwiY6JcAyIKAVluNI9+H2E5VN5I26kPlbzeqEwn1tpBBO/OdL/qHsLqh9/hava5oojQikLLiZJ6KYcJFiilUGMfSimRT0D5TvmgNcFt8PpQyitDFH4YW2wb+4qEQZV7ulFcx3S/YT1/m/VQqvEYojBXVXN2ZBvqXEFhgVIKpWgolTaCW3sGyzovisacQtZ9CS1DxNPXh2so4fktWLUT1z30hu8x28ijenDu2p4dhc3fOMWQ28iWfg1XGaxCT9ud5qWi96b+10dLziavUYT6CEwail7pKnnvz7y9Had+dz7+vHSr9/oW50ZR3WIhsypXg1KEks3H/sn/egH3vrTeEMpq1/BU1tOF1TWiIppR/f77s65w9D/u+lB8ElRTQxmNPhQ2eY0i8hqKf9ddFzSVVOLFG/cCAF5Zt7vkc/UKV77Jq0KnfOQmr5C0JeQbtEZHuMmrhAuZrlFhy2T7PCMZ1Gd4sqr6m01e5jE3tuX62gOv44q7F9olNhDFoMR686HUQ+BPECxQSqCUcSiVVOJEzH8hr2rVpUrHd3jNVWXm4dku3flrohK7fhS2+Go1B+W/u3At29bkFbRiY1jxHnhlA/5UoKGXSt5cVUkedkLp3Jufwa9eWFv+hazLM+KXqAgWKCWgPpAw2zJgduJt6x3Eiq29gddRU1pksubaY+oxecehlEdQ2GeplK+h6P6okLQVmsfc+wy7TgQ93cp9KHbnl/vu9PPClroONXn5aSgheUdJFP6afHmD0729tQ9f//3isq5x1a8X4XevbLBKO9KzcVQKC5QScDUUQ0Ov7zd9MO//4TP4wM3PBl4n7mooXqlUrdUYKWSp4zA8o9zLLIPVeWX4JfzS2kd52V+n6LoB1y8roxCi0FBMWajnYDK/iICbrcWKjZVpKN68fNNU2Mg/+uZmXP3A65blYYEyagiztXud8v5pegadiSWDKmEi7ryWQtOajV8hCqETswwbfmPDHqzdua+4DJ5yVt6wRYn/KoLBZpgoetXVnsKj3OeXs3h3YdpWfpqZgPwjeAyZbA6/eXEdMiHhiJGYKgOySFcxppijvEYhZh9KfjvsvQ+k/SeYBLS5tAJMXiY8Fb9Mr7xyqoZV3q8+8Dpunvd2cHnKKoGlUz4gmsiE3z25I78NpRUR9HSjiDgCSgkbLjf/cA1F1X/Tcw+aeSA/EWfl3PPCWvzr/7yJewy+i0rCm12UNhaQR7qM77Rc6lyesEAphdCpV7SeSlgPMShaw51LqyCNMGx7y2j6YU/M0ocykM6i3zDzcoVFKM0pX0K+Qb1m0/26uwNu5rE3N+OaB81mi0ocxOVoG1EEVJjyUBqB0Wkf4GMp1a/hpwErdsuVRdUKo0XliMTkFa5ZpiNY5sGWeok2M8ECpQTUqzSp2LqgCevdZwN6NTaKhdEcEUHfzzZsOJsV4WvAlCtQLDQUd4qYkDLoC6L5Pbcwk5dNw/S5Xy/C/QvNjtVKwk/LCcMuW0PRr2VIo9552FLYQRF1tvx15c7QNGGdq2hMleY0VTV5sUAZPah3aZ4cMr8d9kEHVQzjLMEWlSkKk5ci7EPM5ATSPsI1mrBhzfRiTOMQVs5//vUidzvQrm8adxFBw5TvmZdxblnXq/y5GzUUd3JI03fg2ryKKHU9lGTcXIfDancUYcM2GlWYyevPS7fijQ17yi+ERr1MAWMiUesCNBLqYzP7UEoweVnU8sIUViav0FzDIcuR8pmc8F2Ey8YOH4bVeSJfjiD0jzmo12w0eVXJdGLCO1Gm3fnlCj+vU94/TVjYsNK+gwIgwspH5Fy/Mid0+VqhwqYzEWby+qwcoLnmxgvKLke+PKyhjBpCNZQSnPKBH4obZRVeluIDRdmUTIzMCyTpZLK50Ma83Oqvfzhh5r0wp6u+smDgOufG6L3g4zbktanyz3XKYHeOqScrhMCDr2wwrsZZyvgfk5at9vsdti2/emNB9ct9rab3FjKi3wabzoSflq7YN+S/XLii1IABFiijCPUqMzkROCcUEG7rDBIoJkFgU5ei8aE4/0P9QDYmrwicw2E28jChpq997tfQhkUelaJdmCOfKtFQSj7FeJ0/L9uGrz7wOn5kiM6zGdiYL5epY2VuhG1Hylc6/Q8QHL5snwdCyxFk8tq0ZyAw/1J9Ihw2PIrwRsAUH/dMvWLRGIdeL0A4mENcQ7MNJWb5MTs+FB+zhmHbxDcfXhwYIWUqhtod9iwTsTANxdzwCCE0527gZZyymLQp4f1fCuUMFDU9E9UBWLPDED1lIcjDrhEUhm3rQ3E1lKDgFbXUsOF4FL4vq3EoARpK0PAAoHQBUefyhAVKaeTfpt9663pP2cb/UMLlnJ8lfhiVrodSrlNex6bIdy9YWxQh5Q1/9j/PXegpTEOJhwiUnLqmj3AsocceVJZKpl4ppz1MG8rR1uS4TfsMphjv9EHBFzb6UHLmRtgVMiH3FLOYrSGsflcixBVWPpSAb8BkWlSUWjY2eY0iPI2LTz3RP8AwgRE6gGhWAAAgAElEQVT0oYT1yG3TlNubyYfjmtMIIQJMXnqPukyTl8V5rk8r5CPTfSh+SQOn1SjBpwAELW3g/e/Hlr2D+O/nVhcJtnJMiCZHsYqaMjWCpbwtk8BRna0wAR0Iqbzs60Hx/vKFeCl5BJm8wgRKqSavep/Li6O8SkB/lc5HE/cc1ytH6BiOgIphmpnWSqnxtj7hJ/hgY79W5fczSQjjD3u8PhRDr1/+D3XKh5i88iYts4nGdLwQ0/iivOnEnMcX730VL63ZhTOPmIjDJo3Jl6+MhzhsEBhh5kyb6YPCjued4X7HzOYwHZsZr8MUcLd+VCRQVB7mNEo4x3wKZHoPCjZ57cfojUHQFB6m46a0hZiiimx6pxaWolBsPmbVc/T7YEpZD96ElWYgD4T1YhOxfDUv1VFcSgPrlCW45x+UhbK39w157e42AQpOuvxRk4YSZiYM8xPqmHrX6hn4Cm/LvJVSaTP9kHHdFqVdVDB2w6YjoASKXs8U4SavUgVKfUsUFiglIKBV9EoFSlDvPyTqCAhS8/Pb5VY+G6e8uv+wKK+ypwAxbOu4ZqSQZx2zdMr72vxLaGABs3CzMZ00J53PcaBgOhtbjU/P2mTSCtIenOx1QR6mofjvVzLA77BNA+0cl3kFSIMwH0ok4d6laCg+rWn0GgoLlFGDEObFrwr3hZu8zBXNPB5C7/kHm4GcfMzX37x3AI8v3ux7LB82bD5fmXbCTF5lT4FvIZTCBpoq4lot91+W1nwdm/EwpvQ6QWY1RVIWtHhhNbtnqOc9bOjZZ0Ma9FIEqDls2OxDyZu8gnFNqhX4UMLmHLPBai4v+azjPhKuko6lb/o6t3mVLVCIaAYRPUVEy4hoCRF9Se7vIqJ5RLRC/h+nnXMdEa0kouVENFfbfzIRvSmP3ULSiE9ETUT0W7n/RSLq1s65TF5jBRFdVu59lIIQwlVrKzd5mY+5H11BFlZ1z9LcdNGtC3Dlrxb5fvQ2PhRl1vDrgemNdvkdqnDhbOuU965T45ePuZGzWTRNJ2zxtcDxrGpAa0FJvNqaOQP9iFFDUSYvC4ES1uyHDfD1u4Q+6DFIUGZDygnk66mJdMCIfVtK0VDiPk6UsGlZSi1anSsoFWkoGQBXCyGOAnAagKuI6GgA1wKYL4SYCWC+/A157BIAswCcB+BnRKS82rcCuALATPl3ntx/OYDdQojDANwM4CaZVxeA6wGcCmAOgOt1wTVSCOSjZHwFSoiPRcdka3fyyV+v8PruttFkkSfoQ9ooB1z5ldP1oQTcgzrP1+RlWYYgPD1l46hvdTz4GkOaHbvUkfKlOuVNZS3F/FKo9QlLH4BePrPJSzbUxnIGC19vWv/92QAfivd5GvLN5cf+BE2iqjClyPtyzOd+65ElOOb6JwLyDtboAGCeXKrYT6AEWSKc49FoKEII/Ozpldi9b7ik/KKmbIEihNgshFgkt3sBLAMwDcCFAO6Sye4C8BG5fSGA+4QQQ0KIdwCsBDCHiKYA6BBCLBDOW7u74ByV14MAzpHay1wA84QQu4QQuwHMQ14IjRhCAKmE/+JXgLdhC6soQfXMzuRlLmNoIg2/HqDNEsBpTYsqNtHkt8vV0G0acrU/zCwyHCpQzNqDzRrrOmE9/0ANBf4hvbZzo9n4UPJjRCzqWJhACRvY6HPY5hvRn6HVeC0D6axZsCl++fwa45gc51z135zHY4u3APAXKJUMH/Avj3/6F9/Zhe8/vhzXPfRmSflFTSQ+FGmKOhHAiwAmCyE2A47QATBJJpsGYL122ga5b5rcLtzvOUcIkQGwF8D4gLz8ynYFES0kooXbt28v7wYlOY/JK2RgY5gZJkCimByXpfgVgtLo+FVod1BZkElC6zkGNYDl2nxLMR+GaSinHzo+Xza/Rk7u8+0kaLsq86GE93QVQSt1BqGnG84EC4ywkN+gNGHHg6ZesfEz2r77IMEFRGPyKiVSLFaGD6XUogVpdQCwZ6BBNRQFEbUD+B2ALwsheoKS+uwTAfvLPce7U4jbhRCzhRCzJ06cGFC8cIQAEtLkFaahhFXA4A9FXq/o+nr+wT1hwLJH7WfyslgCWBeIhX4U/bTyl6IN7ymr/eFhw2HjUJx9fp2EUsOGje/FzcN8rnruxQJaL2vAtT1OeZMPxfkf5usp3PbDHDYsG/qAqVeC8rftmIWttOk65S0+BONATwsNRZGMFzenYT6Ukgc2GtIr7aicVV6jpCKBQkRJOMLk10KIh+TurdKMBfl/m9y/AcAM7fTpADbJ/dN99nvOIaIEgE4AuwLyGlFyQiBliMQBCnwoYR9j4DiUcGFhNReYRd0KEnw2vUPAx+ZfolALy9/0LG0nXPT2is35+H2MpfgUgMrL6lcO23E9+jHTOJTQqedLMHmZjpuCSpzrhj9Pz7sPaCDdezFklAkoRyGmObfCFl8DgCMmO4NQm5LFzWnYkhZRmbwScbMpvppUEuVFAO4AsEwI8SPt0CMALpPblwF4WNt/iYzcOhiO8/0laRbrJaLTZJ6XFpyj8roIwJPSz/IEgHOJaJx0xp8r940oQphDOwHvy6xkcki34hUk0X/aROnYjLD2M73ZrISYtjR5lWtusJl1QO0N65Xpt+F3T0EmLxszo46551+cn4kgDSUIOw0lWLCVNH19SEPudw0bc5ansxLUqQnxoSnfmc17Mw8EVf/NeSgfjF+SsPn9wgZLF1JJsE81qGTqlXcD+DSAN4noNbnvXwHcCOB+IrocwDoAFwOAEGIJEd0PYCmcCLGrhBCqW/A5AL8E0ALgMfkHOALrHiJaCUczuUTmtYuIvgPgZZnu20KIXRXcixU5IZBM2Jm8Qp1xgaq8879QINiEsOpn2DRefuWIBYy1yZdRa7wKPsawBtyGnIVwDguBVXgbSbMWEhYKXonGZzOwUYXBFk7saGtCtNFg1X6bNX3COiRhwRJ+h7Mh7wLwNoo20/+Y7mXIFSjGLLRrmjot4e9NCRTf+qN1djI5gUS84LiWb+9gGmNbU4HlNBVDmfcqcBdFQtkCRQjxF5in0znHcM4NAG7w2b8QwDE++wchBZLPsTsB3Glb3ijwOuXL633ZHDd9kJ4Gw6qHGV67/BpA5VwMEor6R1/sRC6tEfYtl/Df9l5HHi9BePtHcjn//Xp3pQxWDUpjY4vPT9le6JOye4jeiLRgTSlMSOtpzdfwL0eQhrJsc97NatTmtNsP1FBywRqKmnHASkMJmVkgKItMQDRZOqT+6M9g5bY+zO7uKkpjo8WUYt4bSXikfAkI5Meh+JlZsjnhHq9kckiT3Vb/aeNotKlbvhqKbNmefdscFaeXP8hEU4rJyxRSGuZADtMGwxzBroZieKdB5xalD/WhhGZR7EMxbBdio6HkcsHlCLtfjwkwRAvyO/rquvxyzGFzgTl5BYzXypnfG5D3i9hUQZPZ1Mb3FdSYZwM6XoXn7Bv29+PYBDKob7DG8oQFii1qoSXlQ/HtbYQ47XWCGkE3EqfgGjY9lZJt/gH+hxffMVsRg3woKLEMioyhMauk12+TV5BgCtNuivIKey8BebhRXrlCDSX8uoD33sLGeNgEfoQ71UMESqgp0n+/R0OxcMobNRQpUGwiqcJ8D0HvPsj05vGhhHRYBoYt1qgxCeEaR3cpWKBYot5jMiCaIpsTSCbMAqcwrfGY+ugDbOlGkxcEOluSAIBjpnYGlsGUj1U0k0dD8Z5QaqitX542voug6CydMBOcOy9ZqA/FQkCHaFNlRXnZDmz0uV6p5QjzcdhEMoaNDylMV4i1D8X1ffnPeF2SU75MDUUIERyEkA1+Xvq+fUP+GkpYlCIQvAZNNWGBYomqLPmpV/zt7UpDCWvkbHwoRRqKHj0V0BPuHt8KwH+glU05rBo97f6LTF4eDSU0K988cxYNl62GEmbGURFRhb6L4nMDL+OkNwp68/XdNPJQsQ/FL6dibDSUXEBvujAPvxQ2gj4b0MCarmW6RqAPJaAjoN5pKh6DEOENrdnk5fw3d2r8t918S4jy6jeGLuvX8C9I2HiXasECxRL1upRT3uRDUVOz+DUstiGCKllhGk/0VEDDpaKFbMKGg8Jobc8L9KGUIFFMGkpYiGspPhS/+1XRQOXOIG0ThJCP8jKX050frVAzNZ/iQe/jmNqXsHEoYdF1Nr4tWwexycpkOydeXkMxv1O1JEBYNTSFWYcJR73u+6UJCl5x8s9vm0xeHrOrhVZXS1igWOJqKAmzj0Qf+Bg0Tbrp/MJjhRXUxukqhHCd6jbab1ivyVSBvT6UQsFn36vXr2XqzZkjkoKP+13D75ko00iYyct0mbueX+Ob3q+sNgs1FWootrM32zQ86lWFRYEB4RqKrz+qhCAGG39AuT4U9U5bUnFPWhN+2qmTd7DZLOx5hA3S1I8//Jr/2Gyb70l9gzW2eLFAsWH9rn7MX+YM+HdNXr69EZEf+BhWuWxMXkU9Vb3BMJc3bFpvv2uZ9hU6iBUeDSUTZPIqT3uw+Yhsx6EEffRCCLc3G+aUNwmD32sNQVg4t5WGUtDw2I5+9tjrAzocQHiEllNW/zqez6v4fP14YbnP+eHTAIApnc3OtSwaaZupV/zu1RUoSUeghNVD0zNWz9TsuwgW4pkQH4pep5Zs8p+5ymZCzYxbztpKFF5T3oIP3vIcegcddTQZMA4lp5m8Qs0FAS/eDe0sDJ7SG98gk5e2HYb/AE3teFagyaeWeFX5QqFj30s12cv1DmNYr99mpHwiRsjkRFHD4C6OFCNkcwJCCI9AtjF5ecweYRpKwFtRpq5CE6Leew66U5vZBdxGuEzzXVjj5hmtX9DRWLV9HwCgWTXyRi3KruNlo6E0WwoU0ziUvPku+HkmYmThQ/Hx0Wn5Th/XEngNIOi9cthww6CECZCfHNLX3i5EJOulpA0fvZUPRoQvjeopU0ijYGqsPSPlK5jLy2TastEM1OdjY1pRk+cVplW281aDacRbPv/89cbIqBmE5OGcq0xeZWooFj3ZfNiwfx4ek1dIAxmmwZjWU29KBPs19EbaamCjjzAYKhAo4Sav4Hpu1lCk8z8RC30eQSbVwye3ByyKpm+bOjW1FiUOLFBKJGgJ4ExWBK6XYmvyUmp2kcnLomIJaE55izoWNnjNZPLSP8BCk5fnAwj5kE1rX5iEi991wp3yeVNkYXlUo6cESmFenqgmQ/9P/5iNct5tyM1lVc+08Jnrzzronaq8iQKemSzgcCaHvQPp4jKEhOyW4jMwObqbQhp5db+pRCxwYGPGFShmDSVv8jJmI/MK1lDCNL5k3CBQQjob6pS2poQ7sr8QG/Mvhw03KAnDwEYhBN7a0uv2hP16DLZzfZkqscnfUFgO1ylfdpRXuODz9rzKnxzS+8H5f3xhPpQwoZXLaTMcGAVKoui6+u9UPBb6MetlMpY1SKAYGkg9/6B36mncQkxvALC9d6i4DLrwCriGXzkLj5s0lOaQsVpqvyNQfJN40g35JBrOOo2zcsqH1RFTDz9sCnz1DJxnHpxvUBRhe1PCOOOxzffoOuV9j1YPFiglkjd5efc/v2onAOCvK53/fmp4mD01n84/jNVmHEpWM+/YECZQzCv/5fdXYvLSe7HGkfKmxjHAhu5JJ7RwboNAUT3ZwkbSNb/Eydj7S2fCP3j1uAI7EirKq1BD0c7Rza+F6MLPxuHdO1i6huIxaYWM2zEJlKDZJvRrNFlqKH4zBQ8VvNdyF7wLC4HOamUtK2xYntOWSiCdFb7fm83gWrfe1liisEApEdcpX/BidxWs5exXMbw9DfM1VMULMnmZTRr5AY3lhw1rZTH13LTzik1e9hqK3oPLZP3PCzLvATZhw/mlmwvfi+rJtjUpk5f3eJjTFQAGM/meZZhpJCiAQD2Lwt6yXuagJV5dgZLw7y0Xls9POHmu7VPUIKe7XgYg36gXMpRRkzYayqjdR+AURUqg+GkoFk554ek4Bb+3MOGXjFO4idD3W5MCRUa++GkpNh00VW9X79iH3768zj9RFWCBUiKuc7dIe8iTiseKBqcB9hpKPlSxUKBoja/RpCFcP49NZ8V/6pW8lmPsuXmm5TbfS1hjb7Ix20R5qaKHhg0LbQaDgrzcnqzJ5KWZX0yNyp7+fE8/zBlu0vj0cwu12zCHcuE1EjJiLegagH+DH+Yj0cvvJ1BUXUjEyChQ+uQUI2Hm1FQ8Fhy8Isvipynl36vynZmvA/gL+lxOn1bFvwxeH0qxBpE2aOD5853/7bJDM+jjR7HxveoC8TcvskBpGEymE70iJeLkq4brH2CwhmIyeeUJGkdQksnLd5VCuA2w0basaygVmLxMH1wp41D6h7MYNNifVbpUwt/prhqe1mSwUz4RM/tQpspxFUFlzY8xCTd19hc0KrYT/+W0xs0kZPU6OJQpfmbekd/F5w+m9fN9tHC5qyUVx7BP/gDwgaMmyfxNddjJpCkRDxQoQSYvV0NJmE1e+rPw6xQpzTNGQcIvH+UFFFsFMlm7VV6VhlL47gHvczKbvPLlP+mgcb5pqgELFAv0Brot5a9C6z+T8VigGg6E+VD8e0VWczUJbQ4vC5uXSUNxo9WMpgBzT7UUp/ywwf9gN+UJMKHdWZBo3a5+4zUcAamWHSgweRVEeZmc8smE2Ydy6KR2dDQ7DULY1BhB4Z3qvReaT0sNG3ZMXqaebJiGEdx4qUikRIwCNZSWZLxIc2hLxfGZdx+M0w4ZDyCoU+T8b0qWr6EUjpT3u5Zefr97UY37uNYUhrO5QKe6aUBzOifcpYGDZqUIMnnZzGuXyQl0NCcwtjVprdGOBCxQLIhrAzv8pnK49elV+PJvX3N/Jw0mL49ACWho1YcSOCYiIEJGBQ5Ymbz8THNZ4c6BZAobHsrkQOQI28Lenf6zlAFlJvNX0L1O7nC0A78Q2Hx5wp3yrdLkUNgRcBuMmNnkNZTOYUJ7k5Pe1Ot2/SMBHYmsQaAEqbN+ZY2TWUPR8vLTMDIhGkq/nG9qbGvSN7pKPaPWVLyokU7nnBVPVVh72HooqXiwD0UJZz9hoO4zyIcy5NFQzMJzXFtKpi9u7NV5pqCOTDaHpoQ5TFqP8gJMGor/tk46m0MiHkNTIoahtF19GQlYoFigV/x3HTqhaN8df3nH3f7V5aciaTJ5ZfOVJagXsbNv2DeNtzdvKGtOWM0ynM/Tv5dq+kAUfUMZtKUSzr0GLAgVPuWFv5C10caEcBo2ANjbbxYo6WzObVgKy6oc020hYcOmsFDAaWjCBtDZ+FDUs9jdP1zSctIK1Yi2JM2mouFM/t0O+fSGvaHEPo2sPKezJel7vtvAphLIieJOQjIWczX+sMgpJ2w4vOPlp/WpsimLgl8aj8nL572oe+2Sy/IO+jTUWfd+nesUakvOTBPhY9OUQPEz3YY59lWaRIzQlCjWDKsJCxQL1Av94LEHuD1i/cUmNJPY4Qe0G01e3/3jW0V5FpLLOeNZgOLG2NT4es7XHOo2UV7+kTr5BtjUO+4fyqKtKe57r97JJcOurzWchph9033khHDX4A7SUHQBWWhq/MK9iwDA+NHrYcNGDSWTc6PEwpzh6awIDP1sTcWRE8Ae7X5sZ5JVjWZTMm58ZsPZHMZI85yfhnLLkyvdbX8NxWnwxkozUCHqPlsLGlghhOvfU59L2LMK9aEEmbzkvk7Z4fBrqHWNw0/g5O/VnIeqs6p+FWtlOVfbDxvYqF9Tx0ZbH87mkIzHkErEfDWpasECpQSOntLhNtZ6HdZ9LM3JuOOU96k8r6zd7W6bep2/f22ju11YAdPZnCu8gsZmxEM0FL1B8/sYM1nhjmb2uw8A6BvOoK0p4US0BUQllWTy0n0oNhoKgLFyMbFAgRKgoaisTaO33cgpua6GH8OZHDpbHMHm1yAA4VNwqIWaVIdl054Brfx2GkraQkNJZ3JolwLFNE4kX6bifXm/QjIwbNgVKAUTbybjhFgs2OSlj+0I1lCEm95kylSLzfkLlGCnvDLvdbUpDcUcxNCS8jeZOubjAJOX8Goofj4U0xx3nntJ59CSiqMpEQt9ryMJCxQL3nf4RADA5848LN+7MnwMTYmY08gGvNQDOpqNds5lm50ZR8e1Jn1GdefV5yDTSl5DCbejm0xebo/dqKE4Jq9EnIqjkiy0C4V3HizNfh8ilFSPd5zUUPqGzAP+0lnHrxT3Caf9xOwZAJzOQmHZ9d8pg4aSyeawesc+xKQ/aZ+hHPp1gwavzZzUDiBfDwrLNG2s/wSCgD72IiDKK5tDayqOGJnHiSj87let2dHZkgoUKKoRdWdydifhjLkm2bDJIZ1xKOYy6vW4aHyR9PGNaXYEip+g9wyq9RHaSoAoH4pfY6+egRIIfhN75rVf8/NSGq7fmii6adHUQRtIZ9GSjEsNhQVKXfPdjx2LZ752JuIxx6GYiJGn4ugVrSnhmIFMU3xc/YHDsaVnEI++udm3V/Vfzzn+mI+fNL2oR5TJ5VwTzz7j+tN5jcnUlg8OawLF0Li1GHr0in3S5NXelMCaHfu85dSFRAkDG73TVOTT+I+HUA2X44g0NeSA89ySsZjz3go+6nQuh2ljW/LjbgxrkSQMTvnHl2wBAPxp6Va0NyWMgk0P5/Z7pqq+HCRX29TvR5Xp7CMnBc7VpDuig6K8kvEYmhJxX9PI1M5mnHTgWAD+z71/OItEjNDeFA+09xdqKOq5J+OkhaT7N3yeEf8BGoo+91VhIzqUySEVj7n12E8Y6GM+gkxeQT4U9cyVQCkUspmcCAwMUPenzJB+gk+/N9P7Hxh2BAo75RuAaWNbcND4Nvd3e3PC88GryvCFsw8DIMehFHwsSn1u1eaC39Pvjeb5yv35SLHmpPPBekfz5tww2cJIIEVQRJNCH9nt18vU7b6mHqJyyh86sb2oEQ2bkdZzLUNkl3cKEPN5yXgMbQENOeD0PhNxpyNQOO5mMJ1FczLmhn0WOVWV+cUQwqrvam9KGKdGSWdzmpA2h+t2yB71Pq1hybi92ERg71Pl25yIB45DScVjaEr692T701nXnu9H/3AWLak4xjQn0TeUKRJcmQKB4q6GqS0ToMJoTfeSyQY/c8BpWPuHM645qjBAYCiTQyoRc01RfsKvR3tX/iavgiivIA1FmRF96k9TQAi+Ol91FH0Fn7bP9F4H0lk0p+JIJeK+0XfVggVKGbQ3JdCnVca1O50xEF9+/+EAnEausKHeLaOQxkkHn7PPKxQefWMzAOCC46bIuYG8jfNgOoe2pgQOGt+KNzfs9S1bVuR7RKZoD10YFpYzlxMQInza7+19Q5jQ3oT2pkRRr8pm9t18Wn8fyrBsEABg1bY+dF/7KJ5evi2fNpv3bbQ1xY2+C3WNRIyQ8NEcB6XtWZkc+oeyBced3+1NCd9ebFLzn23cM4DfLdpQ1MgOprNIZwXGtSWL7lmhOhetTQnEY+R2QAC4dW1cazJwAKfqsbc3J4zrqA9nnedq6skODGddYeDXGXht/R5AOI7qnAB6CwR5zhUo3qglpaEk4rG8OczQk1Ydnvam4kgxxVAmh5zQ/RsFJi9palL34jeTr94J8Xu3quxd8r0N+mh06vtpc01exX7PoG9JaYkdzUkQ+ZdTF7ym72kwnUVLUr1Xdso3FK2pOJ5dsR2A96NVJo0xTQlP7wcAdu1zwjG72lK45/I5cl/ekfzvf1jibg8M58NQVaX+5V/fwStrd6NvKINjpnZidYGZCQCeXr4NQuQjlvRJCxVCCJz9w2fc34VCR334aoSx34eWzuawo28Ikzub0ZwqNn3oDUDYGApPT1z37WRzmNCWAhEwb9lWAMBDi/IBC7oJpS0VoqHkBBLxWJGpEpDPOhF3TRaF+QxpNnI/QeA3K8Gflm71/F4tF5Ya39Yk77P4mX7+N68CcEx4B3Q0Y/2uvFN+W+8QOluSGNMcrKH830eXAchrzH4NmDJ5pRKxonefzTmrVyotqSiAISfw2vo96B3KuALj+ZU7PGmUYJ/c4dxrj5yA0u0AxMitn6ZopJ6BDFKJmOsf8+u1L9nkdKi6DGn2DWXQnIwHmrzU5JitqbhvPdUj2gB/k9eQa/Lyj/IKCxseyuQQI6cetxvqseoAEvlrWqqsyoeiv1chBG59ehVWbO31PS9qWKCUwdtb+7CjbxhLNu3FNx5eDAB492Hj3eMzulqxenufp5f55FtO73pCe5Pbq1JCBgB+8dc17naM4JqcVAPyrT8sldfuxdjWZFFUUzqbwz/84mUAjr0/Rv494UJTWeEHoHroHS1Og+H3ob21uRdCOMEFLcl4Ua/KdnZcAJ6KXqihNCfj6GxJuhFPqnFwypX3bbQ3JYw+FCGEa9ZKxIud8oMZx4RjFihZJ9AiURzNNjCcxRX3vAIAOOuIifiiNHkOpL15fPCW5wAAU8c6EVzbfKaNf239HgCOIB/fnnIbYif9ICaNaUJ7kxOo0e/jP9Pv37Qmz4bd/Vi8sQdpOdiusEF3e+TSrFr4XnW/nXonn/v1It80B3Q6wQNqTJVqnFtlJBLg38gDjhDqaE645iq/Xvs1D74BIK/lF+a1bHMPDp88xhV8PQPFz6zX1fxSvo39ym19GN+W0nwoxeVYu2MfmhIxd2BrkVNeC8E3Da5sSsRBRGhv9lo+FH+Wy49PH9di/J4G0lk3ykvX/JZv7cVNj7+Fr8nnNdKwQKmAgeEsfvWCMxHbhSdMc/fP7h6HoUwO70gtYsveQfz0qVUAgPHtKU2gOI1GYSMXI3JH1xZW4i+dczjGNCfRO5j2aEd6I6V8An4CZc1O7xQlhWa3XfK3Cl/16xHPW+o4ot9/1CS0puLoL/D1ZHI5xGOEtlQ8MJx3KJPF3QvWur8HPE5Spyc9rjXl9pRVA6OOA46/qs0gUIQQ+Pb/LkVOONE+iVisqNc9mHY+aGUDLxIoacd04jxP77mrtve52184ZyYufVc3ALMQPWGG4+x+a4v/2uEAEIsVTxpQtVUAABtKSURBVN2zrXcIkzqaMHGM02j5rWOiP2clHAvLcYPUYF5bt8fX5KUa/QlSkyo0I+rP5rxjDgDgCFKdfbJDcuy0TsQoH62mtIExzQm0NyUwvi2F5Vv64EfPQBodzclA7eJIGZV39blHOGkKyrpmZz8Om9SOVCKGiWOaPGHYit7BtBPUkSzW1gBHaHZPaNP8MD4dtP5hTGhvck1eej7ZnEA6K1yhZookUz4lkw/uz1JDP6Cj2XfJgS17B7G9dwjN0imvl2HznkEAwXUuSliglMG7DnW0Ed1co9RzAOiWDvx1svH+/hP5AY2TxzS7aVVj/tCiDZ78Y5R3XKpKfMiENnzg6Mm48n2HYEyzY8/XG/stewfd7VY5PsTvI1m702sqe/i1Te62EAJX3/+6c72JbYgRsLPP23g9vXwbbnlyJaaNbcGkjmY0y0F0elnSWWfUbmdL0jMTr07/cAa3zF/h/k7EyBVmKo9UIuYOKgO8AkXdWyoeM0ZX7egbdjW/ZDwmR/V7n8m+oQzamhzTSIzg6SG+9M4urNjWi+akE7lX+Dx1YZyUmhJgDmGeMa4VzcmYawLzoykRl2HnTuMzmM7i1XV7sHtfOlCgvLxml7utTF564zOYzrrl/dSpBzoCpaCzoDovY1sde36hkFbP5pZPnohjpnWiJRnHzMljPGnUNaZ0NqOrLeX6Dv/1fxbLsiVBRDhyyhj8rqDeK3oGMxjTknT9H4WCbcmmva6/UZnW9I7XYDorxwY5daerNYU9A8VBLIs39uCAjmYkYzFfTXxLzyAmdzS55t9CwSaEwEOLNmLfcCYfuaY9U6VJBpkg9w6k3XKOafavx7OmduD46Z2yI1l8/LqHHO1jw+4BR/PUyrmlZ1A+k5yvUI0aFihl8N2PHgsAeHPDHnef0joA4EAZ+rlWTliowmpPPHAsYjFCczKOtlQcSzf34IXVO7FALs6liMfyGooyS/QMZjChPQUicici1M0iW3vyAqW9KY5kIobd+4aLHLMqgED1loG8H+gvK3e4phfHNNeE7QUCRZnVNsrKqRolvbL2DWUwpjmBztaUUUP57cvrXa3t82cdhnFtKezWzHEDw1lXM9D3KZSg6mxNoq0p7vaMdfSPcyiTxdjWlNvgZXMCP31qJdbt6sf4tiYQUVG02N/etgB/XbkTTckYUnEqanR082Fc8w18//HlABxz4d/etsBNM3fWAege3+ZqrgrV0Exob8LZR05CMhFzbfMbdjvv66Dxre6sxs+8vd1z/k+eXIEv3edECH79gqMwpslpoFTjs7VnECd8+094YbUjdP7lvCPRkooXhZ6rhrutKYEJ7U3Y1jvoOa4c8KqBbGuKFzWAW3sG0dmSRHMyjskdzXhbmjSVpnKA1HzVQnSFHRxAaSgJNKf8G/INu/N1rcUnjapzekNdaPLqG8pgweqdOPHAcUjEqUh7WLmtFxt3D2DSmGa0NycQI2BvgTb/9lZHw9rTn3bNjHqnQx8ECvj7jHSB0t6cLApyUPmrCUj9BIpaRfb8Yw4o8qHo6+dUY9JIFihl0D2hDdPGtuAHf3rb3XdgV6u73dGcxLjWpDsD7t6BNI6d1okHr3yXm6arPYVH39iMS25/AcdN7wSQH2QXi5EbdaQ0j97BtDtIS/3X56/SNZTu8W3YtW8Yv39tk2eesdufXYUfz1+Bg8a34vdXvRtfOmcmgLwWpAuFSWOaMXFMk29vGADmzpoMIN8gKB9RLifwmxfXYUffMCa0p7Clx79XpGzrAHD1uYdjfFsKO2UD/daWHixYvRNtTQls0GYR1htiFRU1rjWFMc1JbOkZ9DTwQ5ksLv/ly+7vvzluKia0N2HBqp1YtrkHf1m5A//vCafhHy99BmMMms6efWl3biq9165rX4OZrDvpIQBs6xnEDX9chpfecRrx9x81GbEY4eipHVi0brcnEuyu59cAAK6ZewSak3GktLngtvY4z/+yd3XjMDno8T+fXOnpKOj18PIzDtY0FKes85dtc9/xsdM6EYsRuse3YdW2Pjefldt6Mfc/ngXg+KpmjGvxNNwA8MV7X3WfE+BEcvX7CBSlNcw+aByWb+n1NGRTCwZmbiy4xt0L1uC19XvQ0ZJ0lxTQOxL9wxn8k/RbXXDslLxZTKbZ0TeEU787H0BeeHW0JNE75O3YXHTr8wCA46Z3Ynx7E1Ztzz+LHX1DeP+PnsVQJofJHc2IxwhdbSls1+rs+l39+NG85e5vJRT0OqG+/wljmpCKx9x1YHT29OcFSkdzomgowWA6i417BjChvQmdLckiEzUA7N43jFlTO/DRE6ehozmBwXQO/cOZIjOg3ukdKRpaoBDReUS0nIhWEtG11bz2Z8442N3+u1MPdM0Riq62FH7z4jr0DWWwfvcA3nXoeE9EkC4MlFngmGmOXThOwCndXRjTnMAfXt+E4UwOQ5mc+yGrBvADNz+LxxdvRjqbw9beQaTiMbz8b+/HiQfm10N49M3N7raaS0yNtlZ+kj/KNKpn58xZ1oRJY5o8PpecjKl/3+ET8eNLTgQA/POZjiNa3f9tz6520x83vRNLNvV4hN2G3f045YY/4ydPrURrKo4l/z4XRM5o+3lLtyKdzeHCn/wVgNMTv+WTJyIZJxzY1Yo1Wm92ySanx9vVmsJ75UwGJ31nntsoXPu7N91IuF9/9lTM6GrFxDGO8/X8Hz+HxRvzYddqbI/ui9Eb/N6hDKZI7eC2Z1fjORnhp3/cJ0x3NL7bP30yAOCC//yLJ9BiRpfzzE/p7sKe/jROueHPWLtzHz59x4v49v86ARfHzXA6FroP5S8yimpyR7NHYN34+FtF5QQAInI7HEqD1TWNT5zidFpmTmpHz2DGFeL3vrTeTTO5oxnTx7Vi/e78u3/k9U2ugJk0ptl9XoWN5LNv73BNut0T2tA3lMH/vOpE5335/TPdb+CJL78XQF6LV/fyzYedaMedfUOu9qEL8fN//Jy7fe35R7qNpNKkn1yWDy2fNs555mOaE1i8sQfd1z6K3sE01uzY586Xd9z0Tpx1xESs2dnvdp7WanVevffxbU0e8+8X7n0VTyxxfBs/vuQEdMmIRJXHcCaHT97+AgBgzsFdaG2Ke+4jlxP46gOv47X1e9xnMm1cCzbvGfR0FpQp87CJ7ZjR1YrewYyn45TO5vDGxr047ZDxICLXBLlo7R7X3AUApx3S5ZoQR5KGFShEFAfwUwDnAzgawCeJ6OhqXf9yTaAUChMg7/w+/XvzMZzJuUJAceQBHe72j+evwMQxTa6j8djpY9GcjOPYaZ34/WubcPjXHwMAjJeRJDMn5e3WV/5qEf7514vw4MINmDgm77j967VnA3B6Ts+v3OExjymT3fukQ/XqB17H4o17sbVnCM3JGH76qZNARJjS2YyV2/rw+GJH4Czd3IOhTA5/c/xUN3JF9a5+9cJaLFq3GwvlB3DzJ47H3FkHQAjHiT+UcRbBWryxx/3orpl7hOvMVHOUPbdiu9uYfuSEqZjd3YUVN3wQF54wFet39WNn3xBeemcXfjTP6ZWPa0u6U+MAwGYpvPR509TocxWJA8DVTgDg1IMdn9iY5oTbwF7/SD6MG8hPEHjL/BX49B0vYcveQbc3+r9fOMOdn+pUudZHoWY3a6ojLCbJ97Nz3zBuevwtPLciH3Z72ERHA2lJxrFiWx+efGurqwHOGOft2d/2zGpc/PPn8bpmdv3Hd3cDyDekv5QCTZkS586ajA+fMFU+N6c+vrDaMT0t1HwwR0/twIyuFmzaM4hn396OXE7g/pcdgdPZknRNuh3NCaze4fTs1+/qx23PrMJAOosV2xxTUPcEx5f41Qccv5w+C/bMSe3obEniscVO3fjz0q2eNW229w7hwK5WJGLkeZeqsT+goxkzuloxpjmJjuYENu4eQDYn8KDml5khrQZKYwMcLffMHzzt/j75oC63nAvldX74p3zdOOsIZzGwiWOasGmvI1D39A+7puGPnTQNF54wDcl4DF2tKVewPb5kixs5NmlMM5LxGO55Ya1rNn1z4148+IpTVuV/mdjehOFszjV77RvK4EqpjZ07azIOlfVjtQwGEULgE7ctwHAmh2OnOfXrjMMmIB4jPPjKelwtB0r/+rOn4r4rTvd0SEYK85DY+mcOgJVCiNUAQET3AbgQwNJqFeCWT56IL977qkcjUDzy+Xfjglv+4pod1KJCip/83Ym49I6X3J7SsdM6cUp3F/74xffgqCmOwPjEKTPwvOZf6Z7gfCAHdDbjF/9wCv5RmnTmyXEPEzShNW1sC/7m+Kn4w+ub8PTy7ZjT3QUA+N7HjnU/oGljW9A9vhVrdvbjQ//5FwDA4ZPb3Yr3lQ8cjvteXo8rf+UNDX3v4RPcbSVQXl6zGx/7mWNGOH56Jz56Yn7qmG88vATfeNjbQF9z3hH41KkHub/v+swcvOf7T+HKexYhHiN85vRufP1D+f7BOUdNxn8+uRKnf+9JdwGvU7rHub3x98ycgOdW7MC7bnwSnS35sOrp41owfZzz3FS0jeKg8a145Koz3Blpx7am8ORb29B97aNumrZUHGcdOaloFbzTvjff3T5Gfsz689D55oeOxsdPcqIAD9BWd/zjm1vc7de++QHXFn7SQePw0Ksb8ZlfLgTg+N7Usde/eS6O//afADjP/KPymf/2itNcYabK8NKaXZ57ue3Ts7X7cp7F53/zKjbvGcTrcqDsV891BudOG9uKbE7g0jtfcs9JJWJ4/fpz3d8nHTQOtz69Cgdf90fP/d76dycBcExeOle89xB3OxYjnDFzAh59YzOO+PrjnnSpRAw3ffw4jG1N4dRDunDbs6s9mi8A/OIfT/Hkdc8La3HPC/mIwXe+90G3Huudtw9L7RcAHrzydADAQVLw/HNBCPRb3znPMyhx8cYefPqOF13B+C/nHYnPviffscwKx9yrL8H7rb9x6vB5sw7APS+sxWfvXohkPOZ+swDwRWl6Vu/tuG/9Cdedf6R0+Gdx2KR2jG1N4ZCJznd73UNv4p/POhT7hrJYtM4RbKce4nzfbU0JHDF5DH6vBdvM7q7eCo4Nq6EAmAZgvfZ7g9xXNT58/FQs+sYHPD1kxaypnW5FaW9K4LjpYz3HJ41pxu8+5/hUknHCdz5yDACnd6g+hAtPmIZLpIli9kHj3LVYAOCsIydhyb/PxSfnzHD3XXv+UZ5rnKJVpJdkD/SUgsr1yBfOwIWy1woAR2gf3+SOZtfPoiDKmzwAxyn64eOnetJ84pQDATij7T8550D48bn3Heo6MgGnN3nWERMxnM0hnRU4d9YBnvTHTO3AIRPa3OMT2lN4QPNJ3fr3J7vamRIm37/oODx3zVlumr85fgouPnm6+/vik6e7wgQAPnjslKJyLv73ufjJp05CR3PSk5dC+TV09ICHlmQcnznjYPedHj2lwxXuihs/dqw7eA4APnqitxrrE0J2tiZxz+VzPD47AJhdkOesqR2e38rkpjhFS3/DH51w4q9fcBQ+f7bzvt8zcwIKUb4RhfL56Xzl/Ye7gm1McxJPXv0+nDBjLJ752plu46z40d8eX3R+UyKGZd8+z72fr8jZJ3Tu/6fTcdSU/P2dc+Rkz/Frzz/S0xt/78zi7/P7Fx3nXkOfVknxjQ8d7SnvlWceCgB4bsUONyji8jMO9gSN/NsHvd/fR0+chn94tyNwPi/HKD29fLsrTMa3pfDcNWe5HRK9jfjeY29h+dZeXHDcFPziHxzheWBXK8a2JrFiWx++8tvX8fXfL0ZbKo7nrz0bUzrz7/fS0/MdtR9cfLwb4FMNKGiyuXqGiC4GMFcI8Vn5+9MA5gghvlCQ7goAVwDAgQceePLatWuL8hopMtkc/vDGJsya2onDC8IrFf3DGbQk4xWpo08v34YTZoz1NEqAoxLf9fwadLYmcdszq/GZMw7G3/o0AgDw/Kod2LB7AB86bkpRTz4jV4MbymSRisd8y5rJ5rBscy9mTe1wzT+KvQNp3PjYWxhMZ/HhE6bi3YdO8AgTvbz/8+pGjG1N4uyCRgJwntWCVTvx52Xb8Mk5M4qE9PbeIWztGcTTy7fhuOljXd9KIVv2DmLJpr0464hJRWUdTGcRI8KL7+zEGYdN8L3X3fuG8eGf/gUXnTQDl7/nYDdcWGdbzyCu+d0buGbukTi6oHEHHP/Gc2/vwL7hDD5+0vSiEfd7+9NYt6sfi9btxvnHHuAR4jqrt/ehrSnh+sMUmWwOw9kc5i/bhr4h5xp+z/yVtbvx8Vufx9xZk/GTT53kaSD39A9j6eYe3PT4cjQlYvjuR48tEqAb9wzg4dc24rRDxiOdyeGkg8Z58ggjnc1hyaYeZHM5/OH1zbj63MNdrVN/Fks392Dp5h58as6BnvBxwHlnq7fvQzxGaE3FXVOXzpNvbUVHcxIrt/Whe0JbkcUgmxPY0TeE5kQcW3sHcciENlcrVAghsHrHPjz11jZ0taXwsZOmw4+X1+zC9t4hzJ11gOe93vvSOqzY2ofp41pw7qzJ6GhJurMS6OV8YfUuvGfmBAymczjnSG8d3bJ3EH9augXLNvfi0IlteM/MiTjigOK2RZ+6KAqI6BUhxOzQdA0sUE4H8C0hxFz5+zoAEEJ8z3TO7NmzxcKFC6tUQoZhmNGBrUBpZJPXywBmEtHBRJQCcAmAR2pcJoZhmP2WhnXKCyEyRPR5AE8AiAO4UwixJOQ0hmEYZoRoWIECAEKIPwL4Y2hChmEYZsRpZJMXwzAMU0ewQGEYhmEigQUKwzAMEwksUBiGYZhIYIHCMAzDRELDDmwsByLqBbA8IEkngL0Bxw8EsC7guE0eYcejyiOsrNUoR6OU0yZNNd59o5QzijwapZxA5XW0UcoZlOYIIYT/dB86Qoj95g/AwpDjt4cc325xjbA8Ao9HmEdgWatRjkYpZ728+0YpZ0T32hDltCnraClnUJqwtlP9scnLyx9Cju8JOW6TR9jxqPIIK2s1ytEo5bRJU4133yjljCKPRiknUHkdbZRy2qYxsr+ZvBYKi/loRur8atIoZeVyRguXM3oapawjWU7bvPc3DeX2Gp9fTRqlrFzOaOFyRk+jlHUky2mV936loTAMwzAjx/6moTAMwzAjxH4vUIjoTiLaRkSLtX3HE9ECInqTiP5ARB1yf5KI7pL7l6k1WOSxp4loORG9Jv8m1bCcKSL6hdz/OhGdqZ1zsty/kohuoYgXmo6wnCP9PGcQ0VPyPS4hoi/J/V1ENI+IVsj/47RzrpPPbTkRzdX2j9gzjbicI/ZMSy0nEY2X6fuI6CcFeY10HY2yrPX0TD9ARK/IZ/cKEZ2t5TWiz9TFJhRsNP8BeC+AkwAs1va9DOB9cvszAL4jtz8F4D653QpgDYBu+ftpALPrpJxXAfiF3J4E4BUAMfn7JQCnAyAAjwE4v07LOdLPcwqAk+T2GABvAzgawPcBXCv3XwvgJrl9NIDXATQBOBjAKgDxkX6mEZdzxJ5pGeVsA3AGgCsB/KQgr5Guo1GWtZ6e6YkApsrtYwBsrNYzVX/7vYYihHgWwK6C3UcAeFZuzwPwcZUcQBsRJQC0ABgG0FOH5TwawHx53jY44YSziWgKgA4hxALh1LK7AXyk3soZZXlMCCE2CyEWye1eAMsATANwIYC7ZLK7kH8+F8LpTAwJId4BsBLAnJF+plGVM6ryRFVOIcQ+IcRfAAzq+VSpjkZS1pGmjHK+KoTYJPcvAdBMRE3VeKaK/V6gGFgM4MNy+2IAaiH2BwHsA7AZzojUHwgh9MbzF1Lt/caIqZR25XwdwIVElCCigwGcLI9NA7BBO3+D3Fdv5VRU5XkSUTec3t2LACYLITYDzgcNR3MCnOe0XjtNPbuqPdMKy6kY8WdqWU4TVa2jFZZVUY/P9OMAXhVCDKGKz5QFij+fAXAVEb0CR9UclvvnAMgCmArHnHA1ER0ij/2dEOJYAO+Rf5+uYTnvhFNpFgL4DwDPA8jAUXcLqUaYX6nlBKr0PImoHcDvAHxZCBGkbZqeXVWeaQTlBKrwTEsopzELn30jUkcjKCtQh8+UiGYBuAnAP6ldPslG5JmyQPFBCPGWEOJcIcTJAO6FY4cGHB/K40KItDTR/BXSRCOE2Cj/9wL4DapjZvAtpxAiI4T4ihDiBCHEhQDGAlgBp/GermUxHcCmwnzroJxVeZ5ElITzof5aCPGQ3L1VmgiU+WWb3L8BXu1JPbsRf6YRlXPEn2mJ5TRRlToaUVnr7pkS0XQA/wPgUiGEareq9t2zQPFBRWoQUQzA1wH8XB5aB+BscmgDcBqAt6TJZoI8JwngQ3DMPDUpJxG1yvKBiD4AICOEWCrV414iOk2q5pcCeLjeylmN5ynv/w4Ay4QQP9IOPQLgMrl9GfLP5xEAl0ib9MEAZgJ4aaSfaVTlHOlnWkY5falGHY2qrPX2TIloLIBHAVwnhPirSlzV7z5qL3+j/cHpMW8GkIYjyS8H8CU4ERVvA7gR+QGg7QAegOPwWgrgayIfBfIKgDfksR9DRtbUqJzdcGZVXgbgzwAO0vKZDafSrwLwE3VOPZWzSs/zDDhq/xsAXpN/HwQwHk6gwAr5v0s759/kc1sOLUpmJJ9pVOUc6WdaZjnXwAng6JN15egq1dFIylpvzxROZ22flvY1AJOq8UzVH4+UZxiGYSKBTV4MwzBMJLBAYRiGYSKBBQrDMAwTCSxQGIZhmEhggcIwDMNEAgsUhqkTiOhKIrq0hPTdpM3qzDC1JlHrAjAM4wySE0L8PDwlw9QvLFAYJiLkBH6Pw5nA70Q4AzkvBXAUgB/BGRi7A8A/CCE2E9HTcOYvezeAR4hoDIA+IcQPiOgEODMKtMIZjPYZIcRuIjoZzhxo/QD+Ur27Y5hw2OTFMNFyBIDbhRDHwVna4CoA/wngIuHMZXYngBu09GOFEO8TQvywIJ+7AfyLzOdNANfL/b8A8EUhxOkjeRMMUw6soTBMtKwX+XmUfgXgX+EsdjRPzmwehzM1jeK3hRkQUSccQfOM3HUXgAd89t8D4Pzob4FhyoMFCsNES+FcRr0AlgRoFPtKyJt88meYuoFNXgwTLQcSkRIenwTwAoCJah8RJeV6FUb+f3t3jIJAEINR+AWsPItH0JOILHslbbTZU9hYegix8wq6jW0sdnpBAmvxvjJFmO4nYZjJzBF4RsSmlXbANTNfwBgR61bf1h9f+p0TilTrDnQRcWJ6DfYAXIB9W1ktmD4Tu33p0wHHiFgCD6Bv9R4YIuLd+kp/w9eGpSLtltc5M1czH0WahSsvSVIJJxRJUgknFElSCQNFklTCQJEklTBQJEklDBRJUgkDRZJU4gMytwnULXDDQAAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "sorted_data['inc'].plot()"
    ]
@@ -1212,9 +2260,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 45,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fb558349748>"
+      ]
+     },
+     "execution_count": 45,
+     "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()"
    ]
@@ -1249,10 +2320,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 46,
+   "metadata": {},
    "outputs": [],
    "source": [
     "first_august_week = [pd.Period(pd.Timestamp(y, 8, 1), 'W')\n",
@@ -1271,7 +2340,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 47,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1295,9 +2364,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 48,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fb558790208>"
+      ]
+     },
+     "execution_count": 48,
+     "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='*')"
    ]
@@ -1311,9 +2403,54 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 49,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2014    1600941\n",
+       "1991    1659249\n",
+       "1995    1840410\n",
+       "2012    2175217\n",
+       "2003    2234584\n",
+       "2019    2254386\n",
+       "2006    2307352\n",
+       "2017    2321583\n",
+       "2001    2529279\n",
+       "1992    2574578\n",
+       "1993    2703886\n",
+       "2018    2705325\n",
+       "1988    2765617\n",
+       "2007    2780164\n",
+       "1987    2855570\n",
+       "2016    2856393\n",
+       "2011    2857040\n",
+       "2008    2973918\n",
+       "1998    3034904\n",
+       "2002    3125418\n",
+       "2009    3444020\n",
+       "1994    3514763\n",
+       "1996    3539413\n",
+       "2004    3567744\n",
+       "1997    3620066\n",
+       "2015    3654892\n",
+       "2000    3826372\n",
+       "2005    3835025\n",
+       "1999    3908112\n",
+       "2010    4111392\n",
+       "2013    4182691\n",
+       "1986    5115251\n",
+       "1990    5235827\n",
+       "1989    5466192\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 49,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "yearly_incidence.sort_values()"
    ]
@@ -1328,9 +2465,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 50,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fb575162240>"
+      ]
+     },
+     "execution_count": 50,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "yearly_incidence.hist(xrot=20)"
    ]
@@ -1338,9 +2498,14 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
    "outputs": [],
    "source": []
   }