diff --git a/module2/exo1/toy_notebook_fr.ipynb b/module2/exo1/toy_notebook_fr.ipynb
index 8aecc1952c1c4acaa2715c1fb7b906921884c7c3..fd3af4c04ec36c0a2c63abb63b245c63e7cf4bf4 100644
--- a/module2/exo1/toy_notebook_fr.ipynb
+++ b/module2/exo1/toy_notebook_fr.ipynb
@@ -123,23 +123,49 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [
     {
-     "data": {
-      "text/plain": [
-       "3.112"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
+     "ename": "ERROR",
+     "evalue": "Error in np.mean(accept): could not find function \"np.mean\"\n",
+     "output_type": "error",
+     "traceback": [
+      "Error in np.mean(accept): could not find function \"np.mean\"\nTraceback:\n"
+     ]
     }
    ],
    "source": [
     "4*np.mean(accept)"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
diff --git a/module2/exo2/exercice.ipynb b/module2/exo2/exercice.ipynb
index 0bbbe371b01e359e381e43239412d77bf53fb1fb..8119153d353a94c8e5b62f2e783422dee4ccc3ee 100644
--- a/module2/exo2/exercice.ipynb
+++ b/module2/exo2/exercice.ipynb
@@ -1,5 +1,289 @@
 {
- "cells": [],
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Exercie 02-2"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Calcul avec numpy\n",
+    "Calculer la moyenne et l'écart-type, le min, la médiane et le max des données suivantes :\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "donn= [14.0, 7.6, 11.2, 12.8, 12.5, 9.9, 14.9, 9.4, 16.9, 10.2, 14.9, 18.1, 7.3, 9.8, 10.9,12.2, 9.9, 2.9, 2.8, 15.4, 15.7, 9.7, 13.1, 13.2, 12.3, 11.7, 16.0, 12.4, 17.9, 12.2, 16.2, 18.7, 8.9, 11.9, 12.1, 14.6, 12.1, 4.7, 3.9, 16.9, 16.8, 11.3, 14.4, 15.7, 14.0, 13.6, 18.0, 13.6, 19.9, 13.7, 17.0, 20.5, 9.9, 12.5, 13.2, 16.1, 13.5, 6.3, 6.4, 17.6, 19.1, 12.8, 15.5, 16.3, 15.2, 14.6, 19.1, 14.4, 21.4, 15.1, 19.6, 21.7, 11.3, 15.0, 14.3, 16.8, 14.0, 6.8, 8.2, 19.9, 20.4, 14.6, 16.4, 18.7, 16.8, 15.8, 20.4, 15.8, 22.4, 16.2, 20.3, 23.4, 12.1, 15.5, 15.4, 18.4, 15.7, 10.2, 8.9, 21.0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x = np.array(donn  )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([14. ,  7.6, 11.2, 12.8, 12.5,  9.9, 14.9,  9.4, 16.9, 10.2, 14.9,\n",
+       "       18.1,  7.3,  9.8, 10.9, 12.2,  9.9,  2.9,  2.8, 15.4, 15.7,  9.7,\n",
+       "       13.1, 13.2, 12.3, 11.7, 16. , 12.4, 17.9, 12.2, 16.2, 18.7,  8.9,\n",
+       "       11.9, 12.1, 14.6, 12.1,  4.7,  3.9, 16.9, 16.8, 11.3, 14.4, 15.7,\n",
+       "       14. , 13.6, 18. , 13.6, 19.9, 13.7, 17. , 20.5,  9.9, 12.5, 13.2,\n",
+       "       16.1, 13.5,  6.3,  6.4, 17.6, 19.1, 12.8, 15.5, 16.3, 15.2, 14.6,\n",
+       "       19.1, 14.4, 21.4, 15.1, 19.6, 21.7, 11.3, 15. , 14.3, 16.8, 14. ,\n",
+       "        6.8,  8.2, 19.9, 20.4, 14.6, 16.4, 18.7, 16.8, 15.8, 20.4, 15.8,\n",
+       "       22.4, 16.2, 20.3, 23.4, 12.1, 15.5, 15.4, 18.4, 15.7, 10.2,  8.9,\n",
+       "       21. ])"
+      ]
+     },
+     "execution_count": 50,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "14.113000000000001"
+      ]
+     },
+     "execution_count": 59,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.mean(x)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2.8"
+      ]
+     },
+     "execution_count": 62,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x.min()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "23.4"
+      ]
+     },
+     "execution_count": 63,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x.max()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "14.5"
+      ]
+     },
+     "execution_count": 64,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.median(x)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# conseillé par l'exo"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "4.334094455301447"
+      ]
+     },
+     "execution_count": 66,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.std(x, ddof=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#attention correction"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "4.312369534258399"
+      ]
+     },
+     "execution_count": 58,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.std(x, ddof=0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
  "metadata": {
   "kernelspec": {
    "display_name": "Python 3",
@@ -16,10 +300,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 2
 }
-
diff --git a/module2/exo3/exercice.ipynb b/module2/exo3/exercice.ipynb
index 0bbbe371b01e359e381e43239412d77bf53fb1fb..561b00276effddc585b865ff5bcee1531ff71fde 100644
--- a/module2/exo3/exercice.ipynb
+++ b/module2/exo3/exercice.ipynb
@@ -1,5 +1,235 @@
 {
- "cells": [],
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "donn= [14.0, 7.6, 11.2, 12.8, 12.5, 9.9, 14.9, 9.4, 16.9, 10.2, 14.9, 18.1, 7.3, 9.8, 10.9,12.2, 9.9, 2.9, 2.8, 15.4, 15.7, 9.7, 13.1, 13.2, 12.3, 11.7, 16.0, 12.4, 17.9, 12.2, 16.2, 18.7, 8.9, 11.9, 12.1, 14.6, 12.1, 4.7, 3.9, 16.9, 16.8, 11.3, 14.4, 15.7, 14.0, 13.6, 18.0, 13.6, 19.9, 13.7, 17.0, 20.5, 9.9, 12.5, 13.2, 16.1, 13.5, 6.3, 6.4, 17.6, 19.1, 12.8, 15.5, 16.3, 15.2, 14.6, 19.1, 14.4, 21.4, 15.1, 19.6, 21.7, 11.3, 15.0, 14.3, 16.8, 14.0, 6.8, 8.2, 19.9, 20.4, 14.6, 16.4, 18.7, 16.8, 15.8, 20.4, 15.8, 22.4, 16.2, 20.3, 23.4, 12.1, 15.5, 15.4, 18.4, 15.7, 10.2, 8.9, 21.0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "y = np.array(donn  )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x = np.arange(1, np.shape(y)[0]+1 )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "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": [
+    "fig= plt.figure()\n",
+    "ax = fig.add_subplot(111)\n",
+    "ax.plot(x, y, color='lightblue', linewidth=2)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 432x288 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure()\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([ 4.,  3.,  5.,  9., 16., 20., 22.,  9.,  8.,  4.]),\n",
+       " array([ 2.8 ,  4.86,  6.92,  8.98, 11.04, 13.1 , 15.16, 17.22, 19.28,\n",
+       "        21.34, 23.4 ]),\n",
+       " <a list of 10 Patch objects>)"
+      ]
+     },
+     "execution_count": 40,
+     "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": [
+    "fig = plt.figure()\n",
+    "#ax = fig.add_subplot(111)\n",
+    "plt.hist(y, bins=10)\n",
+    "#ax.plot(x, y, color='lightblue', linewidth=3)\n",
+    "#plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([4, 5, 5, 5, 6]), array([ 0,  5, 10, 15, 20, 25]))"
+      ]
+     },
+     "execution_count": 39,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.histogram(x, bins=[0,5,10,15,20,25])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([ 2.,  2.,  0.,  3.,  2.,  3.,  6.,  3.,  5., 11., 10., 10., 12.,\n",
+       "        10.,  4.,  5.,  4.,  4.,  2.,  2.]),\n",
+       " array([ 2.8 ,  3.83,  4.86,  5.89,  6.92,  7.95,  8.98, 10.01, 11.04,\n",
+       "        12.07, 13.1 , 14.13, 15.16, 16.19, 17.22, 18.25, 19.28, 20.31,\n",
+       "        21.34, 22.37, 23.4 ]),\n",
+       " <a list of 20 Patch objects>)"
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvIxREBQAAC5VJREFUeJzt3W+IZYdZx/Hvz2yLpo00JdNSk4zTSgiWokkZpBqpsbGyNqWpoJBgZdXC+KLVVAq61RfxjRBRq4JSWU1MwJgiaWqDrZoltkShBnfj0mw6rSl1TbdZs1sCttYXcc3ji7mRcbKzc+89Z/fOPvv9wDL3njl3zsPh7pfDuX9OqgpJ0oXvWxY9gCRpHAZdkpow6JLUhEGXpCYMuiQ1YdAlqQmDLklNGHRJasKgS1ITe87nxq644opaWVk5n5uUpAve4cOHv1ZVSzutd16DvrKywqFDh87nJiXpgpfk36ZZz1MuktSEQZekJgy6JDVh0CWpCYMuSU3sGPQkdyc5meTopmW/leQLST6X5ONJXnVux5Qk7WSaI/R7gL1blh0E3lRV3wP8C/ChkeeSJM1ox6BX1aPAc1uWPVxVpyd3/xG46hzMJkmawRjn0H8O+OsR/o4kaYBBnxRN8mvAaeC+s6yzBqwBLC8vD9mc1NLK/k/O/dhjd9484iS60M19hJ5kH/BO4KeqqrZbr6oOVNVqVa0uLe34VQSSpDnNdYSeZC/wK8APVdV/jTuSJGke07xt8X7gs8C1SY4neS/wB8BlwMEkR5L80TmeU5K0gx2P0KvqtjMsvusczCJJGsBPikpSEwZdkpow6JLUhEGXpCYMuiQ1YdAlqQmDLklNGHRJasKgS1ITBl2SmjDoktSEQZekJgZd4ELaTbxQhC52HqFLUhMGXZKaMOiS1IRBl6QmDLokNWHQJakJgy5JTRh0SWrCoEtSEwZdkpow6JLUhEGXpCYMuiQ1sWPQk9yd5GSSo5uWvTrJwSRPTX5efm7HlCTtZJoj9HuAvVuW7QceqaprgEcm9yVJC7Rj0KvqUeC5LYtvAe6d3L4XePfIc0mSZjTvBS5eW1UnAKrqRJLXbLdikjVgDWB5eXnOzUnn1pCLYyySF/XQZuf8RdGqOlBVq1W1urS0dK43J0kXrXmD/myS1wFMfp4cbyRJ0jzmDfpDwL7J7X3AJ8YZR5I0r2netng/8Fng2iTHk7wXuBN4e5KngLdP7kuSFmjHF0Wr6rZtfnXTyLNIkgbwk6KS1IRBl6QmDLokNWHQJakJgy5JTRh0SWrCoEtSEwZdkpow6JLUhEGXpCYMuiQ1YdAlqQmDLklNGHRJasKgS1ITBl2SmjDoktSEQZekJgy6JDVh0CWpCYMuSU0YdElqwqBLUhMGXZKaMOiS1MSgoCf5pSRPJjma5P4k3zrWYJKk2cwd9CRXAr8IrFbVm4BLgFvHGkySNJuhp1z2AN+WZA9wKfDM8JEkSfOYO+hV9VXgt4GngRPAf1TVw2MNJkmazZBTLpcDtwCvB74DeEWS95xhvbUkh5IcOnXq1PyTSpLOasgplx8B/rWqTlXVfwMPAj+wdaWqOlBVq1W1urS0NGBzkqSzGRL0p4G3JLk0SYCbgPVxxpIkzWrIOfTHgAeAx4EnJn/rwEhzSZJmtGfIg6vqDuCOkWaRJA3gJ0UlqQmDLklNGHRJasKgS1ITBl2SmjDoktSEQZekJgy6JDVh0CWpCYMuSU0YdElqwqBLUhMGXZKaMOiS1IRBl6QmDLokNWHQJakJgy5JTRh0SWrCoEtSEwZdkpow6JLUhEGXpCYMuiQ1YdAlqQmDLklNDAp6klcleSDJF5KsJ/n+sQaTJM1mz8DH/z7wN1X1E0leDlw6wkySpDnMHfQk3w68FfgZgKp6Hnh+nLEkSbMacoT+BuAU8KdJvhc4DNxeVd/cvFKSNWANYHl5ecDmdL6s7P/koMcfu/PmkSaRNIsh59D3AG8GPlJV1wPfBPZvXamqDlTValWtLi0tDdicJOlshgT9OHC8qh6b3H+AjcBLkhZg7qBX1b8DX0ly7WTRTcDnR5lKkjSzoe9y+QXgvsk7XL4M/OzwkSRJ8xgU9Ko6AqyONIskaQA/KSpJTRh0SWrCoEtSEwZdkpow6JLUhEGXpCYMuiQ1YdAlqQmDLklNGHRJasKgS1ITBl2Smhj6bYvSqIZeLUnnh1e12p08QpekJgy6JDVh0CWpCYMuSU0YdElqwqBLUhMGXZKaMOiS1IRBl6QmDLokNWHQJakJgy5JTQwOepJLkvxzkr8aYyBJ0nzGOEK/HVgf4e9IkgYYFPQkVwE3A38yzjiSpHkNPUL/PeCXgRdGmEWSNMDcF7hI8k7gZFUdTnLjWdZbA9YAlpeX592cpJEt8mIii9p29wtrDDlCvwF4V5JjwEeBtyX5s60rVdWBqlqtqtWlpaUBm5Mknc3cQa+qD1XVVVW1AtwK/F1VvWe0ySRJM/F96JLUxCgXia6qzwCfGeNvSZLm4xG6JDVh0CWpCYMuSU0YdElqwqBLUhMGXZKaMOiS1IRBl6QmDLokNWHQJakJgy5JTRh0SWpilC/n0vaGfJH/kC/jvxgvXiBd7DxCl6QmDLokNWHQJakJgy5JTRh0SWrCoEtSEwZdkpow6JLUhEGXpCYMuiQ1YdAlqQmDLklNGHRJamLuoCe5Osmnk6wneTLJ7WMOJkmazZCvzz0NfLCqHk9yGXA4ycGq+vxIs0mSZjD3EXpVnaiqxye3vwGsA1eONZgkaTajXOAiyQpwPfDYGX63BqwBLC8vz72NRV40YciFJobwQhHSuLp3ZPCLokleCXwM+EBVfX3r76vqQFWtVtXq0tLS0M1JkrYxKOhJXsZGzO+rqgfHGUmSNI8h73IJcBewXlUfHm8kSdI8hhyh3wD8NPC2JEcm/94x0lySpBnN/aJoVf0DkBFnkSQN4CdFJakJgy5JTRh0SWrCoEtSEwZdkpow6JLUhEGXpCYMuiQ1YdAlqQmDLklNGHRJasKgS1ITBl2SmjDoktSEQZekJgy6JDVh0CWpCYMuSU0YdElqwqBLUhMGXZKaMOiS1IRBl6QmDLokNWHQJamJQUFPsjfJF5N8Kcn+sYaSJM1u7qAnuQT4Q+DHgDcCtyV541iDSZJmM+QI/fuAL1XVl6vqeeCjwC3jjCVJmtWQoF8JfGXT/eOTZZKkBdgz4LE5w7J6yUrJGrA2ufufSb44YJsLkd/8v5tXAF9b3CQXDPfTztxH02mznzZ1ZB7fOc1KQ4J+HLh60/2rgGe2rlRVB4ADA7azayQ5VFWri55jt3M/7cx9NB3302yGnHL5J+CaJK9P8nLgVuChccaSJM1q7iP0qjqd5P3A3wKXAHdX1ZOjTSZJmsmQUy5U1aeAT400y4Wgxamj88D9tDP30XTcTzNI1Utex5QkXYD86L8kNWHQp5DkWJInkhxJcmjR8+wWSe5OcjLJ0U3LXp3kYJKnJj8vX+SMu8E2++nXk3x18pw6kuQdi5xxN0hydZJPJ1lP8mSS2yfLfU5NyaBP74er6jrfQvX/3APs3bJsP/BIVV0DPDK5f7G7h5fuJ4DfnTynrpu8HnWxOw18sKq+G3gL8L7J14n4nJqSQdfcqupR4Lkti28B7p3cvhd493kdahfaZj9pi6o6UVWPT25/A1hn49PnPqemZNCnU8DDSQ5PPvmq7b22qk7Axn9Q4DULnmc3e3+Sz01OyXgaYZMkK8D1wGP4nJqaQZ/ODVX1Zja+WfJ9Sd666IF0wfsI8F3AdcAJ4HcWO87ukeSVwMeAD1TV1xc9z4XEoE+hqp6Z/DwJfJyNb5rUmT2b5HUAk58nFzzPrlRVz1bV/1TVC8Af43MKgCQvYyPm91XVg5PFPqemZNB3kOQVSS578Tbwo8DRsz/qovYQsG9yex/wiQXOsmu9GKiJH8fnFEkC3AWsV9WHN/3K59SU/GDRDpK8gY2jctj4ZO2fV9VvLHCkXSPJ/cCNbHwj3rPAHcBfAn8BLANPAz9ZVRf1C4Lb7Kcb2TjdUsAx4OdfPE98sUryg8DfA08AL0wW/yob59F9Tk3BoEtSE55ykaQmDLokNWHQJakJgy5JTRh0SWrCoEtSEwZdkpow6JLUxP8CYTKDnKXKt8wAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure()\n",
+    "plt.hist(y, bins=20)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
  "metadata": {
   "kernelspec": {
    "display_name": "Python 3",
@@ -16,10 +246,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 2
 }
-
diff --git a/module2/exo5/exo5_fr.ipynb b/module2/exo5/exo5_fr.ipynb
index 26ad6d94fa840f788a57621b06dc6af83a848391..86ce2f8c7a09699e78da1b30c7547f0f1b5f01e7 100644
--- a/module2/exo5/exo5_fr.ipynb
+++ b/module2/exo5/exo5_fr.ipynb
@@ -40,7 +40,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [
     {
@@ -261,33 +261,33 @@
        "</div>"
       ],
       "text/plain": [
-       "         Date  Count  Temperature  Pressure  Malfunction\n",
-       "0     4/12/81      6           66        50            0\n",
-       "1    11/12/81      6           70        50            1\n",
-       "2     3/22/82      6           69        50            0\n",
-       "3    11/11/82      6           68        50            0\n",
-       "4     4/04/83      6           67        50            0\n",
-       "5     6/18/82      6           72        50            0\n",
-       "6     8/30/83      6           73       100            0\n",
-       "7    11/28/83      6           70       100            0\n",
-       "8     2/03/84      6           57       200            1\n",
-       "9     4/06/84      6           63       200            1\n",
-       "10    8/30/84      6           70       200            1\n",
-       "11   10/05/84      6           78       200            0\n",
-       "12   11/08/84      6           67       200            0\n",
-       "13    1/24/85      6           53       200            2\n",
-       "14    4/12/85      6           67       200            0\n",
-       "15    4/29/85      6           75       200            0\n",
-       "16    6/17/85      6           70       200            0\n",
-       "17  7/29/85      6           81       200            0\n",
-       "18    8/27/85      6           76       200            0\n",
-       "19   10/03/85      6           79       200            0\n",
-       "20   10/30/85      6           75       200            2\n",
-       "21   11/26/85      6           76       200            0\n",
-       "22    1/12/86      6           58       200            1"
+       "        Date  Count  Temperature  Pressure  Malfunction\n",
+       "0    4/12/81      6           66        50            0\n",
+       "1   11/12/81      6           70        50            1\n",
+       "2    3/22/82      6           69        50            0\n",
+       "3   11/11/82      6           68        50            0\n",
+       "4    4/04/83      6           67        50            0\n",
+       "5    6/18/82      6           72        50            0\n",
+       "6    8/30/83      6           73       100            0\n",
+       "7   11/28/83      6           70       100            0\n",
+       "8    2/03/84      6           57       200            1\n",
+       "9    4/06/84      6           63       200            1\n",
+       "10   8/30/84      6           70       200            1\n",
+       "11  10/05/84      6           78       200            0\n",
+       "12  11/08/84      6           67       200            0\n",
+       "13   1/24/85      6           53       200            2\n",
+       "14   4/12/85      6           67       200            0\n",
+       "15   4/29/85      6           75       200            0\n",
+       "16   6/17/85      6           70       200            0\n",
+       "17   7/29/85      6           81       200            0\n",
+       "18   8/27/85      6           76       200            0\n",
+       "19  10/03/85      6           79       200            0\n",
+       "20  10/30/85      6           75       200            2\n",
+       "21  11/26/85      6           76       200            0\n",
+       "22   1/12/86      6           58       200            1"
       ]
      },
-     "execution_count": 1,
+     "execution_count": 35,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -322,7 +322,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [
     {
@@ -351,24 +351,18 @@
        "      <th>Temperature</th>\n",
        "      <th>Pressure</th>\n",
        "      <th>Malfunction</th>\n",
+       "      <th>Frequency</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>11/12/81</td>\n",
-       "      <td>6</td>\n",
-       "      <td>70</td>\n",
-       "      <td>50</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>2/03/84</td>\n",
        "      <td>6</td>\n",
        "      <td>57</td>\n",
        "      <td>200</td>\n",
        "      <td>1</td>\n",
+       "      <td>0.166667</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
@@ -377,6 +371,7 @@
        "      <td>63</td>\n",
        "      <td>200</td>\n",
        "      <td>1</td>\n",
+       "      <td>0.166667</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
@@ -385,6 +380,25 @@
        "      <td>70</td>\n",
        "      <td>200</td>\n",
        "      <td>1</td>\n",
+       "      <td>0.166667</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>10/05/84</td>\n",
+       "      <td>6</td>\n",
+       "      <td>78</td>\n",
+       "      <td>200</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>11/08/84</td>\n",
+       "      <td>6</td>\n",
+       "      <td>67</td>\n",
+       "      <td>200</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>13</th>\n",
@@ -393,6 +407,61 @@
        "      <td>53</td>\n",
        "      <td>200</td>\n",
        "      <td>2</td>\n",
+       "      <td>0.333333</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>4/12/85</td>\n",
+       "      <td>6</td>\n",
+       "      <td>67</td>\n",
+       "      <td>200</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>4/29/85</td>\n",
+       "      <td>6</td>\n",
+       "      <td>75</td>\n",
+       "      <td>200</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>6/17/85</td>\n",
+       "      <td>6</td>\n",
+       "      <td>70</td>\n",
+       "      <td>200</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>7/29/85</td>\n",
+       "      <td>6</td>\n",
+       "      <td>81</td>\n",
+       "      <td>200</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>8/27/85</td>\n",
+       "      <td>6</td>\n",
+       "      <td>76</td>\n",
+       "      <td>200</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>10/03/85</td>\n",
+       "      <td>6</td>\n",
+       "      <td>79</td>\n",
+       "      <td>200</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>20</th>\n",
@@ -401,6 +470,16 @@
        "      <td>75</td>\n",
        "      <td>200</td>\n",
        "      <td>2</td>\n",
+       "      <td>0.333333</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>11/26/85</td>\n",
+       "      <td>6</td>\n",
+       "      <td>76</td>\n",
+       "      <td>200</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>22</th>\n",
@@ -409,29 +488,39 @@
        "      <td>58</td>\n",
        "      <td>200</td>\n",
        "      <td>1</td>\n",
+       "      <td>0.166667</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "        Date  Count  Temperature  Pressure  Malfunction\n",
-       "1   11/12/81      6           70        50            1\n",
-       "8    2/03/84      6           57       200            1\n",
-       "9    4/06/84      6           63       200            1\n",
-       "10   8/30/84      6           70       200            1\n",
-       "13   1/24/85      6           53       200            2\n",
-       "20  10/30/85      6           75       200            2\n",
-       "22   1/12/86      6           58       200            1"
+       "        Date  Count  Temperature  Pressure  Malfunction  Frequency\n",
+       "8    2/03/84      6           57       200            1   0.166667\n",
+       "9    4/06/84      6           63       200            1   0.166667\n",
+       "10   8/30/84      6           70       200            1   0.166667\n",
+       "11  10/05/84      6           78       200            0   0.000000\n",
+       "12  11/08/84      6           67       200            0   0.000000\n",
+       "13   1/24/85      6           53       200            2   0.333333\n",
+       "14   4/12/85      6           67       200            0   0.000000\n",
+       "15   4/29/85      6           75       200            0   0.000000\n",
+       "16   6/17/85      6           70       200            0   0.000000\n",
+       "17   7/29/85      6           81       200            0   0.000000\n",
+       "18   8/27/85      6           76       200            0   0.000000\n",
+       "19  10/03/85      6           79       200            0   0.000000\n",
+       "20  10/30/85      6           75       200            2   0.333333\n",
+       "21  11/26/85      6           76       200            0   0.000000\n",
+       "22   1/12/86      6           58       200            1   0.166667"
       ]
      },
-     "execution_count": 2,
+     "execution_count": 22,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "data = data[data.Malfunction>0]\n",
+    "#data = data[data.Malfunction>0]\n",
+    "#data = data[data.Pressure==200]\n",
     "data"
    ]
   },
@@ -448,12 +537,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -500,7 +589,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [
     {
@@ -509,10 +598,10 @@
        "<table class=\"simpletable\">\n",
        "<caption>Generalized Linear Model Regression Results</caption>\n",
        "<tr>\n",
-       "  <th>Dep. Variable:</th>      <td>Frequency</td>    <th>  No. Observations:  </th>  <td>     7</td>  \n",
+       "  <th>Dep. Variable:</th>      <td>Frequency</td>    <th>  No. Observations:  </th>  <td>    15</td>  \n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>Model:</th>                 <td>GLM</td>       <th>  Df Residuals:      </th>  <td>     5</td>  \n",
+       "  <th>Model:</th>                 <td>GLM</td>       <th>  Df Residuals:      </th>  <td>    13</td>  \n",
        "</tr>\n",
        "<tr>\n",
        "  <th>Model Family:</th>       <td>Binomial</td>     <th>  Df Model:          </th>  <td>     1</td>  \n",
@@ -521,16 +610,16 @@
        "  <th>Link Function:</th>        <td>logit</td>      <th>  Scale:             </th> <td>  1.0000</td> \n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>Method:</th>               <td>IRLS</td>       <th>  Log-Likelihood:    </th> <td> -2.5250</td> \n",
+       "  <th>Method:</th>               <td>IRLS</td>       <th>  Log-Likelihood:    </th> <td> -3.0868</td> \n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>Date:</th>           <td>Sat, 13 Apr 2019</td> <th>  Deviance:          </th> <td> 0.22231</td> \n",
+       "  <th>Date:</th>           <td>Wed, 06 Mar 2024</td> <th>  Deviance:          </th> <td>  1.9748</td> \n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>Time:</th>               <td>19:11:24</td>     <th>  Pearson chi2:      </th>  <td> 0.236</td>  \n",
+       "  <th>Time:</th>               <td>22:08:23</td>     <th>  Pearson chi2:      </th>  <td>  2.84</td>  \n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>No. Iterations:</th>         <td>4</td>        <th>  Covariance Type:   </th> <td>nonrobust</td>\n",
+       "  <th>No. Iterations:</th>         <td>6</td>        <th>  Covariance Type:   </th> <td>nonrobust</td>\n",
        "</tr>\n",
        "</table>\n",
        "<table class=\"simpletable\">\n",
@@ -538,10 +627,10 @@
        "       <td></td>          <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>Intercept</th>   <td>   -1.3895</td> <td>    7.828</td> <td>   -0.178</td> <td> 0.859</td> <td>  -16.732</td> <td>   13.953</td>\n",
+       "  <th>Intercept</th>   <td>    4.2756</td> <td>    7.114</td> <td>    0.601</td> <td> 0.548</td> <td>   -9.667</td> <td>   18.218</td>\n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>Temperature</th> <td>    0.0014</td> <td>    0.122</td> <td>    0.012</td> <td> 0.991</td> <td>   -0.238</td> <td>    0.240</td>\n",
+       "  <th>Temperature</th> <td>   -0.0990</td> <td>    0.110</td> <td>   -0.896</td> <td> 0.370</td> <td>   -0.315</td> <td>    0.118</td>\n",
        "</tr>\n",
        "</table>"
       ],
@@ -550,24 +639,24 @@
        "\"\"\"\n",
        "                 Generalized Linear Model Regression Results                  \n",
        "==============================================================================\n",
-       "Dep. Variable:              Frequency   No. Observations:                    7\n",
-       "Model:                            GLM   Df Residuals:                        5\n",
+       "Dep. Variable:              Frequency   No. Observations:                   15\n",
+       "Model:                            GLM   Df Residuals:                       13\n",
        "Model Family:                Binomial   Df Model:                            1\n",
        "Link Function:                  logit   Scale:                          1.0000\n",
-       "Method:                          IRLS   Log-Likelihood:                -2.5250\n",
-       "Date:                Sat, 13 Apr 2019   Deviance:                      0.22231\n",
-       "Time:                        19:11:24   Pearson chi2:                    0.236\n",
-       "No. Iterations:                     4   Covariance Type:             nonrobust\n",
+       "Method:                          IRLS   Log-Likelihood:                -3.0868\n",
+       "Date:                Wed, 06 Mar 2024   Deviance:                       1.9748\n",
+       "Time:                        22:08:23   Pearson chi2:                     2.84\n",
+       "No. Iterations:                     6   Covariance Type:             nonrobust\n",
        "===============================================================================\n",
        "                  coef    std err          z      P>|z|      [0.025      0.975]\n",
        "-------------------------------------------------------------------------------\n",
-       "Intercept      -1.3895      7.828     -0.178      0.859     -16.732      13.953\n",
-       "Temperature     0.0014      0.122      0.012      0.991      -0.238       0.240\n",
+       "Intercept       4.2756      7.114      0.601      0.548      -9.667      18.218\n",
+       "Temperature    -0.0990      0.110     -0.896      0.370      -0.315       0.118\n",
        "===============================================================================\n",
        "\"\"\""
       ]
      },
-     "execution_count": 4,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -605,12 +694,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -648,7 +737,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [
     {
@@ -686,6 +775,309 @@
     "analyse et de regarder ce jeu de données sous tous les angles afin\n",
     "d'expliquer ce qui ne va pas."
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.9533440000000001"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "1-(1-0.8**2)**3"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "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>Date</th>\n",
+       "      <th>Count</th>\n",
+       "      <th>Temperature</th>\n",
+       "      <th>Pressure</th>\n",
+       "      <th>Malfunction</th>\n",
+       "      <th>Frequency</th>\n",
+       "      <th>Success</th>\n",
+       "      <th>Intercept</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>11/12/81</td>\n",
+       "      <td>6</td>\n",
+       "      <td>70</td>\n",
+       "      <td>50</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.166667</td>\n",
+       "      <td>5</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2/03/84</td>\n",
+       "      <td>6</td>\n",
+       "      <td>57</td>\n",
+       "      <td>200</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.166667</td>\n",
+       "      <td>5</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>4/06/84</td>\n",
+       "      <td>6</td>\n",
+       "      <td>63</td>\n",
+       "      <td>200</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.166667</td>\n",
+       "      <td>5</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>8/30/84</td>\n",
+       "      <td>6</td>\n",
+       "      <td>70</td>\n",
+       "      <td>200</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.166667</td>\n",
+       "      <td>5</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>1/24/85</td>\n",
+       "      <td>6</td>\n",
+       "      <td>53</td>\n",
+       "      <td>200</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>10/30/85</td>\n",
+       "      <td>6</td>\n",
+       "      <td>75</td>\n",
+       "      <td>200</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>1/12/86</td>\n",
+       "      <td>6</td>\n",
+       "      <td>58</td>\n",
+       "      <td>200</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.166667</td>\n",
+       "      <td>5</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        Date  Count  Temperature  Pressure  Malfunction  Frequency  Success  \\\n",
+       "1   11/12/81      6           70        50            1   0.166667        5   \n",
+       "8    2/03/84      6           57       200            1   0.166667        5   \n",
+       "9    4/06/84      6           63       200            1   0.166667        5   \n",
+       "10   8/30/84      6           70       200            1   0.166667        5   \n",
+       "13   1/24/85      6           53       200            2   0.333333        4   \n",
+       "20  10/30/85      6           75       200            2   0.333333        4   \n",
+       "22   1/12/86      6           58       200            1   0.166667        5   \n",
+       "\n",
+       "    Intercept  \n",
+       "1           1  \n",
+       "8           1  \n",
+       "9           1  \n",
+       "10          1  \n",
+       "13          1  \n",
+       "20          1  \n",
+       "22          1  "
+      ]
+     },
+     "execution_count": 39,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data = data[data.Malfunction>0]\n",
+    "\n",
+    "data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [
+    {
+     "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": [
+    "%matplotlib inline\n",
+    "pd.set_option('mode.chained_assignment',None) # this removes a useless warning from pandas\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "data[\"Frequency\"]=data.Malfunction/data.Count\n",
+    "data.plot(x=\"Pressure\",y=\"Frequency\",kind=\"scatter\",ylim=[0,1])\n",
+    "plt.grid(True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<table class=\"simpletable\">\n",
+       "<caption>Generalized Linear Model Regression Results</caption>\n",
+       "<tr>\n",
+       "  <th>Dep. Variable:</th>      <td>Pressure</td>     <th>  No. Observations:  </th>   <td>     7</td>  \n",
+       "</tr>\n",
+       "<tr>\n",
+       "  <th>Model:</th>                 <td>GLM</td>       <th>  Df Residuals:      </th>   <td>     5</td>  \n",
+       "</tr>\n",
+       "<tr>\n",
+       "  <th>Model Family:</th>       <td>Binomial</td>     <th>  Df Model:          </th>   <td>     1</td>  \n",
+       "</tr>\n",
+       "<tr>\n",
+       "  <th>Link Function:</th>        <td>logit</td>      <th>  Scale:             </th>  <td>  1.0000</td> \n",
+       "</tr>\n",
+       "<tr>\n",
+       "  <th>Method:</th>               <td>IRLS</td>       <th>  Log-Likelihood:    </th>  <td>     nan</td> \n",
+       "</tr>\n",
+       "<tr>\n",
+       "  <th>Date:</th>           <td>Wed, 06 Mar 2024</td> <th>  Deviance:          </th> <td>1.0271e+05</td>\n",
+       "</tr>\n",
+       "<tr>\n",
+       "  <th>Time:</th>               <td>22:31:56</td>     <th>  Pearson chi2:      </th>  <td>1.08e+21</td> \n",
+       "</tr>\n",
+       "<tr>\n",
+       "  <th>No. Iterations:</th>         <td>2</td>        <th>  Covariance Type:   </th>  <td>nonrobust</td>\n",
+       "</tr>\n",
+       "</table>\n",
+       "<table class=\"simpletable\">\n",
+       "<tr>\n",
+       "      <td></td>         <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
+       "</tr>\n",
+       "<tr>\n",
+       "  <th>Intercept</th> <td>-5.629e+15</td> <td> 8.99e+07</td> <td>-6.26e+07</td> <td> 0.000</td> <td>-5.63e+15</td> <td>-5.63e+15</td>\n",
+       "</tr>\n",
+       "<tr>\n",
+       "  <th>Pressure</th>  <td> 6.755e+15</td> <td> 4.83e+05</td> <td>  1.4e+10</td> <td> 0.000</td> <td> 6.76e+15</td> <td> 6.76e+15</td>\n",
+       "</tr>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "<class 'statsmodels.iolib.summary.Summary'>\n",
+       "\"\"\"\n",
+       "                 Generalized Linear Model Regression Results                  \n",
+       "==============================================================================\n",
+       "Dep. Variable:               Pressure   No. Observations:                    7\n",
+       "Model:                            GLM   Df Residuals:                        5\n",
+       "Model Family:                Binomial   Df Model:                            1\n",
+       "Link Function:                  logit   Scale:                          1.0000\n",
+       "Method:                          IRLS   Log-Likelihood:                    nan\n",
+       "Date:                Wed, 06 Mar 2024   Deviance:                   1.0271e+05\n",
+       "Time:                        22:31:56   Pearson chi2:                 1.08e+21\n",
+       "No. Iterations:                     2   Covariance Type:             nonrobust\n",
+       "==============================================================================\n",
+       "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
+       "------------------------------------------------------------------------------\n",
+       "Intercept  -5.629e+15   8.99e+07  -6.26e+07      0.000   -5.63e+15   -5.63e+15\n",
+       "Pressure    6.755e+15   4.83e+05    1.4e+10      0.000    6.76e+15    6.76e+15\n",
+       "==============================================================================\n",
+       "\"\"\""
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import statsmodels.api as sm\n",
+    "\n",
+    "data[\"Success\"]=data.Count-data.Malfunction\n",
+    "data[\"Intercept\"]=1\n",
+    "\n",
+    "logmodel=sm.GLM(data['Pressure'], data[['Intercept','Pressure']], family=sm.families.Binomial(sm.families.links.logit)).fit()\n",
+    "\n",
+    "logmodel.summary()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -705,7 +1097,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.3"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,
diff --git a/module3/exo1/analyse-syndrome-grippal.ipynb b/module3/exo1/analyse-syndrome-grippal.ipynb
index 892b362a11aa025cda748c5c052ef78887efe2b8..14891bb768c2dd85ad7b57d62e46ea2849912e60 100644
--- a/module3/exo1/analyse-syndrome-grippal.ipynb
+++ b/module3/exo1/analyse-syndrome-grippal.ipynb
@@ -9,14 +9,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
     "%matplotlib inline\n",
     "import matplotlib.pyplot as plt\n",
     "import pandas as pd\n",
-    "import isoweek"
+    "import isoweek\n",
+    "import os\n",
+    "import urllib.request"
    ]
   },
   {
@@ -28,10 +30,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 4,
+   "metadata": {},
    "outputs": [],
    "source": [
     "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\""
@@ -59,9 +59,85 @@
     "La première ligne du fichier CSV est un commentaire, que nous ignorons en précisant `skiprows=1`."
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Nom du fichier local des données sentinelles"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "datalocal= \"donnsentinelles.csv\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "On télécharge les données si elles n'existent pas avant. Ici il faut éviter de télécharger un fichier brisé qui ne contiendrait plus de data."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "os.path.exists vérifie si le fichier local existe, renvoie True si oui , False sinon\n",
+    "os contient des fonctions de gestions de fichier et du système d'exploitation'\n",
+    "urllib.request contient des fonctions pour ouvrir des URL, authentification, redirection, cookies , etc.. selon\n",
+    "https://docs.python.org/fr/3.11/library/urllib.request.html\n",
+    "urllib.request.urlretrieve télécharge la page url et l'enregistre vers le nom de fichier en 2 ème position"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "déjà présent sur le serveur\n"
+     ]
+    }
+   ],
+   "source": [
+    "if not os.path.exists(datalocal):\n",
+    "    urllib.request.urlretrieve(data_url, datalocal)\n",
+    "    print(\"données téléchargées depuis le réseau Sentinelles\")\n",
+    "else:\n",
+    "    print(\"déjà présent sur le serveur\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -100,391 +176,391 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
-       "      <td>202108</td>\n",
+       "      <td>202412</td>\n",
        "      <td>3</td>\n",
-       "      <td>27492</td>\n",
-       "      <td>22140.0</td>\n",
-       "      <td>32844.0</td>\n",
-       "      <td>42</td>\n",
-       "      <td>34.0</td>\n",
-       "      <td>50.0</td>\n",
+       "      <td>46315</td>\n",
+       "      <td>38805.0</td>\n",
+       "      <td>53825.0</td>\n",
+       "      <td>69</td>\n",
+       "      <td>58.0</td>\n",
+       "      <td>80.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
-       "      <td>202107</td>\n",
+       "      <td>202411</td>\n",
        "      <td>3</td>\n",
-       "      <td>22191</td>\n",
-       "      <td>18096.0</td>\n",
-       "      <td>26286.0</td>\n",
-       "      <td>34</td>\n",
-       "      <td>28.0</td>\n",
-       "      <td>40.0</td>\n",
+       "      <td>50466</td>\n",
+       "      <td>43470.0</td>\n",
+       "      <td>57462.0</td>\n",
+       "      <td>76</td>\n",
+       "      <td>66.0</td>\n",
+       "      <td>86.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td>202106</td>\n",
+       "      <td>202410</td>\n",
        "      <td>3</td>\n",
-       "      <td>23171</td>\n",
-       "      <td>19122.0</td>\n",
-       "      <td>27220.0</td>\n",
-       "      <td>35</td>\n",
-       "      <td>29.0</td>\n",
-       "      <td>41.0</td>\n",
+       "      <td>60107</td>\n",
+       "      <td>52623.0</td>\n",
+       "      <td>67591.0</td>\n",
+       "      <td>90</td>\n",
+       "      <td>79.0</td>\n",
+       "      <td>101.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
-       "      <td>202105</td>\n",
+       "      <td>202409</td>\n",
        "      <td>3</td>\n",
-       "      <td>22426</td>\n",
-       "      <td>18445.0</td>\n",
-       "      <td>26407.0</td>\n",
-       "      <td>34</td>\n",
-       "      <td>28.0</td>\n",
-       "      <td>40.0</td>\n",
+       "      <td>71121</td>\n",
+       "      <td>62920.0</td>\n",
+       "      <td>79322.0</td>\n",
+       "      <td>107</td>\n",
+       "      <td>95.0</td>\n",
+       "      <td>119.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
-       "      <td>202104</td>\n",
+       "      <td>202408</td>\n",
        "      <td>3</td>\n",
-       "      <td>25804</td>\n",
-       "      <td>21491.0</td>\n",
-       "      <td>30117.0</td>\n",
-       "      <td>39</td>\n",
-       "      <td>32.0</td>\n",
-       "      <td>46.0</td>\n",
+       "      <td>104566</td>\n",
+       "      <td>94520.0</td>\n",
+       "      <td>114612.0</td>\n",
+       "      <td>157</td>\n",
+       "      <td>142.0</td>\n",
+       "      <td>172.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
-       "      <td>202103</td>\n",
+       "      <td>202407</td>\n",
        "      <td>3</td>\n",
-       "      <td>21810</td>\n",
-       "      <td>17894.0</td>\n",
-       "      <td>25726.0</td>\n",
-       "      <td>33</td>\n",
-       "      <td>27.0</td>\n",
-       "      <td>39.0</td>\n",
+       "      <td>138078</td>\n",
+       "      <td>127050.0</td>\n",
+       "      <td>149106.0</td>\n",
+       "      <td>207</td>\n",
+       "      <td>190.0</td>\n",
+       "      <td>224.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
-       "      <td>202102</td>\n",
+       "      <td>202406</td>\n",
        "      <td>3</td>\n",
-       "      <td>17320</td>\n",
-       "      <td>13906.0</td>\n",
-       "      <td>20734.0</td>\n",
-       "      <td>26</td>\n",
-       "      <td>21.0</td>\n",
-       "      <td>31.0</td>\n",
+       "      <td>190062</td>\n",
+       "      <td>177955.0</td>\n",
+       "      <td>202169.0</td>\n",
+       "      <td>285</td>\n",
+       "      <td>267.0</td>\n",
+       "      <td>303.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
-       "      <td>202101</td>\n",
+       "      <td>202405</td>\n",
        "      <td>3</td>\n",
-       "      <td>21799</td>\n",
-       "      <td>17778.0</td>\n",
-       "      <td>25820.0</td>\n",
-       "      <td>33</td>\n",
-       "      <td>27.0</td>\n",
-       "      <td>39.0</td>\n",
+       "      <td>216237</td>\n",
+       "      <td>203595.0</td>\n",
+       "      <td>228879.0</td>\n",
+       "      <td>324</td>\n",
+       "      <td>305.0</td>\n",
+       "      <td>343.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
-       "      <td>202053</td>\n",
+       "      <td>202404</td>\n",
        "      <td>3</td>\n",
-       "      <td>21220</td>\n",
-       "      <td>16498.0</td>\n",
-       "      <td>25942.0</td>\n",
-       "      <td>32</td>\n",
-       "      <td>25.0</td>\n",
-       "      <td>39.0</td>\n",
+       "      <td>213196</td>\n",
+       "      <td>200547.0</td>\n",
+       "      <td>225845.0</td>\n",
+       "      <td>320</td>\n",
+       "      <td>301.0</td>\n",
+       "      <td>339.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
-       "      <td>202052</td>\n",
+       "      <td>202403</td>\n",
        "      <td>3</td>\n",
-       "      <td>16428</td>\n",
-       "      <td>12285.0</td>\n",
-       "      <td>20571.0</td>\n",
-       "      <td>25</td>\n",
-       "      <td>19.0</td>\n",
-       "      <td>31.0</td>\n",
+       "      <td>163457</td>\n",
+       "      <td>152276.0</td>\n",
+       "      <td>174638.0</td>\n",
+       "      <td>245</td>\n",
+       "      <td>228.0</td>\n",
+       "      <td>262.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
-       "      <td>202051</td>\n",
+       "      <td>202402</td>\n",
        "      <td>3</td>\n",
-       "      <td>21619</td>\n",
-       "      <td>17370.0</td>\n",
-       "      <td>25868.0</td>\n",
-       "      <td>33</td>\n",
-       "      <td>27.0</td>\n",
-       "      <td>39.0</td>\n",
+       "      <td>129436</td>\n",
+       "      <td>119453.0</td>\n",
+       "      <td>139419.0</td>\n",
+       "      <td>194</td>\n",
+       "      <td>179.0</td>\n",
+       "      <td>209.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>11</th>\n",
-       "      <td>202050</td>\n",
+       "      <td>202401</td>\n",
        "      <td>3</td>\n",
-       "      <td>16845</td>\n",
-       "      <td>13220.0</td>\n",
-       "      <td>20470.0</td>\n",
-       "      <td>26</td>\n",
-       "      <td>20.0</td>\n",
-       "      <td>32.0</td>\n",
+       "      <td>120769</td>\n",
+       "      <td>109452.0</td>\n",
+       "      <td>132086.0</td>\n",
+       "      <td>181</td>\n",
+       "      <td>164.0</td>\n",
+       "      <td>198.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>12</th>\n",
-       "      <td>202049</td>\n",
+       "      <td>202352</td>\n",
        "      <td>3</td>\n",
-       "      <td>12939</td>\n",
-       "      <td>9923.0</td>\n",
-       "      <td>15955.0</td>\n",
-       "      <td>20</td>\n",
-       "      <td>15.0</td>\n",
-       "      <td>25.0</td>\n",
+       "      <td>115446</td>\n",
+       "      <td>103738.0</td>\n",
+       "      <td>127154.0</td>\n",
+       "      <td>174</td>\n",
+       "      <td>156.0</td>\n",
+       "      <td>192.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>13</th>\n",
-       "      <td>202048</td>\n",
+       "      <td>202351</td>\n",
        "      <td>3</td>\n",
-       "      <td>13804</td>\n",
-       "      <td>10641.0</td>\n",
-       "      <td>16967.0</td>\n",
-       "      <td>21</td>\n",
-       "      <td>16.0</td>\n",
-       "      <td>26.0</td>\n",
+       "      <td>148755</td>\n",
+       "      <td>136546.0</td>\n",
+       "      <td>160964.0</td>\n",
+       "      <td>224</td>\n",
+       "      <td>206.0</td>\n",
+       "      <td>242.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>14</th>\n",
-       "      <td>202047</td>\n",
+       "      <td>202350</td>\n",
        "      <td>3</td>\n",
-       "      <td>19085</td>\n",
-       "      <td>15285.0</td>\n",
-       "      <td>22885.0</td>\n",
-       "      <td>29</td>\n",
-       "      <td>23.0</td>\n",
-       "      <td>35.0</td>\n",
+       "      <td>147971</td>\n",
+       "      <td>136787.0</td>\n",
+       "      <td>159155.0</td>\n",
+       "      <td>223</td>\n",
+       "      <td>206.0</td>\n",
+       "      <td>240.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>15</th>\n",
-       "      <td>202046</td>\n",
+       "      <td>202349</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>147552</td>\n",
+       "      <td>136422.0</td>\n",
+       "      <td>158682.0</td>\n",
+       "      <td>222</td>\n",
+       "      <td>205.0</td>\n",
+       "      <td>239.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>16</th>\n",
-       "      <td>202045</td>\n",
+       "      <td>202348</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>124204</td>\n",
+       "      <td>113479.0</td>\n",
+       "      <td>134929.0</td>\n",
+       "      <td>187</td>\n",
+       "      <td>171.0</td>\n",
+       "      <td>203.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>17</th>\n",
-       "      <td>202044</td>\n",
+       "      <td>202347</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>110948</td>\n",
+       "      <td>100694.0</td>\n",
+       "      <td>121202.0</td>\n",
+       "      <td>167</td>\n",
+       "      <td>152.0</td>\n",
+       "      <td>182.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>18</th>\n",
-       "      <td>202043</td>\n",
+       "      <td>202346</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>83894</td>\n",
+       "      <td>75134.0</td>\n",
+       "      <td>92654.0</td>\n",
+       "      <td>126</td>\n",
+       "      <td>113.0</td>\n",
+       "      <td>139.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>19</th>\n",
-       "      <td>202042</td>\n",
+       "      <td>202345</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>72003</td>\n",
+       "      <td>63178.0</td>\n",
+       "      <td>80828.0</td>\n",
+       "      <td>108</td>\n",
+       "      <td>95.0</td>\n",
+       "      <td>121.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>20</th>\n",
-       "      <td>202041</td>\n",
+       "      <td>202344</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>49952</td>\n",
+       "      <td>42813.0</td>\n",
+       "      <td>57091.0</td>\n",
+       "      <td>75</td>\n",
+       "      <td>64.0</td>\n",
+       "      <td>86.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>21</th>\n",
-       "      <td>202040</td>\n",
+       "      <td>202343</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>44982</td>\n",
+       "      <td>38170.0</td>\n",
+       "      <td>51794.0</td>\n",
+       "      <td>68</td>\n",
+       "      <td>58.0</td>\n",
+       "      <td>78.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>22</th>\n",
-       "      <td>202039</td>\n",
+       "      <td>202342</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>56842</td>\n",
+       "      <td>49277.0</td>\n",
+       "      <td>64407.0</td>\n",
+       "      <td>86</td>\n",
+       "      <td>75.0</td>\n",
+       "      <td>97.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>23</th>\n",
-       "      <td>202038</td>\n",
+       "      <td>202341</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>58357</td>\n",
+       "      <td>51032.0</td>\n",
+       "      <td>65682.0</td>\n",
+       "      <td>88</td>\n",
+       "      <td>77.0</td>\n",
+       "      <td>99.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>24</th>\n",
-       "      <td>202037</td>\n",
+       "      <td>202340</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>68894</td>\n",
+       "      <td>60069.0</td>\n",
+       "      <td>77719.0</td>\n",
+       "      <td>104</td>\n",
+       "      <td>91.0</td>\n",
+       "      <td>117.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>25</th>\n",
-       "      <td>202036</td>\n",
+       "      <td>202339</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>72003</td>\n",
+       "      <td>63452.0</td>\n",
+       "      <td>80554.0</td>\n",
+       "      <td>108</td>\n",
+       "      <td>95.0</td>\n",
+       "      <td>121.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>26</th>\n",
-       "      <td>202035</td>\n",
+       "      <td>202338</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>63218</td>\n",
+       "      <td>55227.0</td>\n",
+       "      <td>71209.0</td>\n",
+       "      <td>95</td>\n",
+       "      <td>83.0</td>\n",
+       "      <td>107.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>27</th>\n",
-       "      <td>202034</td>\n",
+       "      <td>202337</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>49085</td>\n",
+       "      <td>42079.0</td>\n",
+       "      <td>56091.0</td>\n",
+       "      <td>74</td>\n",
+       "      <td>63.0</td>\n",
+       "      <td>85.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>28</th>\n",
-       "      <td>202033</td>\n",
+       "      <td>202336</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>38247</td>\n",
+       "      <td>32237.0</td>\n",
+       "      <td>44257.0</td>\n",
+       "      <td>58</td>\n",
+       "      <td>49.0</td>\n",
+       "      <td>67.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>29</th>\n",
-       "      <td>202032</td>\n",
+       "      <td>202335</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>31695</td>\n",
+       "      <td>26013.0</td>\n",
+       "      <td>37377.0</td>\n",
+       "      <td>48</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>57.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
@@ -502,7 +578,7 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1866</th>\n",
+       "      <th>2026</th>\n",
        "      <td>198521</td>\n",
        "      <td>3</td>\n",
        "      <td>26096</td>\n",
@@ -515,7 +591,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1867</th>\n",
+       "      <th>2027</th>\n",
        "      <td>198520</td>\n",
        "      <td>3</td>\n",
        "      <td>27896</td>\n",
@@ -528,7 +604,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1868</th>\n",
+       "      <th>2028</th>\n",
        "      <td>198519</td>\n",
        "      <td>3</td>\n",
        "      <td>43154</td>\n",
@@ -541,7 +617,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1869</th>\n",
+       "      <th>2029</th>\n",
        "      <td>198518</td>\n",
        "      <td>3</td>\n",
        "      <td>40555</td>\n",
@@ -554,7 +630,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1870</th>\n",
+       "      <th>2030</th>\n",
        "      <td>198517</td>\n",
        "      <td>3</td>\n",
        "      <td>34053</td>\n",
@@ -567,7 +643,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1871</th>\n",
+       "      <th>2031</th>\n",
        "      <td>198516</td>\n",
        "      <td>3</td>\n",
        "      <td>50362</td>\n",
@@ -580,7 +656,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1872</th>\n",
+       "      <th>2032</th>\n",
        "      <td>198515</td>\n",
        "      <td>3</td>\n",
        "      <td>63881</td>\n",
@@ -593,7 +669,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1873</th>\n",
+       "      <th>2033</th>\n",
        "      <td>198514</td>\n",
        "      <td>3</td>\n",
        "      <td>134545</td>\n",
@@ -606,7 +682,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1874</th>\n",
+       "      <th>2034</th>\n",
        "      <td>198513</td>\n",
        "      <td>3</td>\n",
        "      <td>197206</td>\n",
@@ -619,7 +695,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1875</th>\n",
+       "      <th>2035</th>\n",
        "      <td>198512</td>\n",
        "      <td>3</td>\n",
        "      <td>245240</td>\n",
@@ -632,7 +708,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1876</th>\n",
+       "      <th>2036</th>\n",
        "      <td>198511</td>\n",
        "      <td>3</td>\n",
        "      <td>276205</td>\n",
@@ -645,7 +721,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1877</th>\n",
+       "      <th>2037</th>\n",
        "      <td>198510</td>\n",
        "      <td>3</td>\n",
        "      <td>353231</td>\n",
@@ -658,7 +734,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1878</th>\n",
+       "      <th>2038</th>\n",
        "      <td>198509</td>\n",
        "      <td>3</td>\n",
        "      <td>369895</td>\n",
@@ -671,7 +747,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1879</th>\n",
+       "      <th>2039</th>\n",
        "      <td>198508</td>\n",
        "      <td>3</td>\n",
        "      <td>389886</td>\n",
@@ -684,7 +760,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1880</th>\n",
+       "      <th>2040</th>\n",
        "      <td>198507</td>\n",
        "      <td>3</td>\n",
        "      <td>471852</td>\n",
@@ -697,7 +773,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1881</th>\n",
+       "      <th>2041</th>\n",
        "      <td>198506</td>\n",
        "      <td>3</td>\n",
        "      <td>565825</td>\n",
@@ -710,7 +786,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1882</th>\n",
+       "      <th>2042</th>\n",
        "      <td>198505</td>\n",
        "      <td>3</td>\n",
        "      <td>637302</td>\n",
@@ -723,7 +799,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1883</th>\n",
+       "      <th>2043</th>\n",
        "      <td>198504</td>\n",
        "      <td>3</td>\n",
        "      <td>424937</td>\n",
@@ -736,7 +812,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1884</th>\n",
+       "      <th>2044</th>\n",
        "      <td>198503</td>\n",
        "      <td>3</td>\n",
        "      <td>213901</td>\n",
@@ -749,7 +825,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1885</th>\n",
+       "      <th>2045</th>\n",
        "      <td>198502</td>\n",
        "      <td>3</td>\n",
        "      <td>97586</td>\n",
@@ -762,7 +838,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1886</th>\n",
+       "      <th>2046</th>\n",
        "      <td>198501</td>\n",
        "      <td>3</td>\n",
        "      <td>85489</td>\n",
@@ -775,7 +851,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1887</th>\n",
+       "      <th>2047</th>\n",
        "      <td>198452</td>\n",
        "      <td>3</td>\n",
        "      <td>84830</td>\n",
@@ -788,7 +864,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1888</th>\n",
+       "      <th>2048</th>\n",
        "      <td>198451</td>\n",
        "      <td>3</td>\n",
        "      <td>101726</td>\n",
@@ -801,7 +877,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1889</th>\n",
+       "      <th>2049</th>\n",
        "      <td>198450</td>\n",
        "      <td>3</td>\n",
        "      <td>123680</td>\n",
@@ -814,7 +890,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1890</th>\n",
+       "      <th>2050</th>\n",
        "      <td>198449</td>\n",
        "      <td>3</td>\n",
        "      <td>101073</td>\n",
@@ -827,7 +903,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1891</th>\n",
+       "      <th>2051</th>\n",
        "      <td>198448</td>\n",
        "      <td>3</td>\n",
        "      <td>78620</td>\n",
@@ -840,7 +916,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1892</th>\n",
+       "      <th>2052</th>\n",
        "      <td>198447</td>\n",
        "      <td>3</td>\n",
        "      <td>72029</td>\n",
@@ -853,7 +929,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1893</th>\n",
+       "      <th>2053</th>\n",
        "      <td>198446</td>\n",
        "      <td>3</td>\n",
        "      <td>87330</td>\n",
@@ -866,7 +942,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1894</th>\n",
+       "      <th>2054</th>\n",
        "      <td>198445</td>\n",
        "      <td>3</td>\n",
        "      <td>135223</td>\n",
@@ -879,7 +955,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1895</th>\n",
+       "      <th>2055</th>\n",
        "      <td>198444</td>\n",
        "      <td>3</td>\n",
        "      <td>68422</td>\n",
@@ -893,146 +969,146 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>1896 rows × 10 columns</p>\n",
+       "<p>2056 rows × 10 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "        week  indicator     inc   inc_low    inc_up  inc100  inc100_low  \\\n",
-       "0     202108          3   27492   22140.0   32844.0      42        34.0   \n",
-       "1     202107          3   22191   18096.0   26286.0      34        28.0   \n",
-       "2     202106          3   23171   19122.0   27220.0      35        29.0   \n",
-       "3     202105          3   22426   18445.0   26407.0      34        28.0   \n",
-       "4     202104          3   25804   21491.0   30117.0      39        32.0   \n",
-       "5     202103          3   21810   17894.0   25726.0      33        27.0   \n",
-       "6     202102          3   17320   13906.0   20734.0      26        21.0   \n",
-       "7     202101          3   21799   17778.0   25820.0      33        27.0   \n",
-       "8     202053          3   21220   16498.0   25942.0      32        25.0   \n",
-       "9     202052          3   16428   12285.0   20571.0      25        19.0   \n",
-       "10    202051          3   21619   17370.0   25868.0      33        27.0   \n",
-       "11    202050          3   16845   13220.0   20470.0      26        20.0   \n",
-       "12    202049          3   12939    9923.0   15955.0      20        15.0   \n",
-       "13    202048          3   13804   10641.0   16967.0      21        16.0   \n",
-       "14    202047          3   19085   15285.0   22885.0      29        23.0   \n",
-       "15    202046          3   24801   20503.0   29099.0      38        31.0   \n",
-       "16    202045          3   42516   36857.0   48175.0      65        56.0   \n",
-       "17    202044          3   44567   38521.0   50613.0      68        59.0   \n",
-       "18    202043          3   43737   37523.0   49951.0      66        57.0   \n",
-       "19    202042          3   35145   29812.0   40478.0      53        45.0   \n",
-       "20    202041          3   27877   23206.0   32548.0      42        35.0   \n",
-       "21    202040          3   20443   16381.0   24505.0      31        25.0   \n",
-       "22    202039          3   19810   15900.0   23720.0      30        24.0   \n",
-       "23    202038          3   25562   21142.0   29982.0      39        32.0   \n",
-       "24    202037          3   18485   14649.0   22321.0      28        22.0   \n",
-       "25    202036          3   10390    7646.0   13134.0      16        12.0   \n",
-       "26    202035          3    9918    6842.0   12994.0      15        10.0   \n",
-       "27    202034          3    6084    3090.0    9078.0       9         4.0   \n",
-       "28    202033          3    6106    3411.0    8801.0       9         5.0   \n",
-       "29    202032          3    5918    3330.0    8506.0       9         5.0   \n",
-       "...      ...        ...     ...       ...       ...     ...         ...   \n",
-       "1866  198521          3   26096   19621.0   32571.0      47        35.0   \n",
-       "1867  198520          3   27896   20885.0   34907.0      51        38.0   \n",
-       "1868  198519          3   43154   32821.0   53487.0      78        59.0   \n",
-       "1869  198518          3   40555   29935.0   51175.0      74        55.0   \n",
-       "1870  198517          3   34053   24366.0   43740.0      62        44.0   \n",
-       "1871  198516          3   50362   36451.0   64273.0      91        66.0   \n",
-       "1872  198515          3   63881   45538.0   82224.0     116        83.0   \n",
-       "1873  198514          3  134545  114400.0  154690.0     244       207.0   \n",
-       "1874  198513          3  197206  176080.0  218332.0     357       319.0   \n",
-       "1875  198512          3  245240  223304.0  267176.0     445       405.0   \n",
-       "1876  198511          3  276205  252399.0  300011.0     501       458.0   \n",
-       "1877  198510          3  353231  326279.0  380183.0     640       591.0   \n",
-       "1878  198509          3  369895  341109.0  398681.0     670       618.0   \n",
-       "1879  198508          3  389886  359529.0  420243.0     707       652.0   \n",
-       "1880  198507          3  471852  432599.0  511105.0     855       784.0   \n",
-       "1881  198506          3  565825  518011.0  613639.0    1026       939.0   \n",
-       "1882  198505          3  637302  592795.0  681809.0    1155      1074.0   \n",
-       "1883  198504          3  424937  390794.0  459080.0     770       708.0   \n",
-       "1884  198503          3  213901  174689.0  253113.0     388       317.0   \n",
-       "1885  198502          3   97586   80949.0  114223.0     177       147.0   \n",
-       "1886  198501          3   85489   65918.0  105060.0     155       120.0   \n",
-       "1887  198452          3   84830   60602.0  109058.0     154       110.0   \n",
-       "1888  198451          3  101726   80242.0  123210.0     185       146.0   \n",
-       "1889  198450          3  123680  101401.0  145959.0     225       184.0   \n",
-       "1890  198449          3  101073   81684.0  120462.0     184       149.0   \n",
-       "1891  198448          3   78620   60634.0   96606.0     143       110.0   \n",
-       "1892  198447          3   72029   54274.0   89784.0     131        99.0   \n",
-       "1893  198446          3   87330   67686.0  106974.0     159       123.0   \n",
-       "1894  198445          3  135223  101414.0  169032.0     246       184.0   \n",
-       "1895  198444          3   68422   20056.0  116788.0     125        37.0   \n",
+       "        week  indicator     inc   inc_low    inc_up inc100  inc100_low  \\\n",
+       "0     202412          3   46315   38805.0   53825.0     69        58.0   \n",
+       "1     202411          3   50466   43470.0   57462.0     76        66.0   \n",
+       "2     202410          3   60107   52623.0   67591.0     90        79.0   \n",
+       "3     202409          3   71121   62920.0   79322.0    107        95.0   \n",
+       "4     202408          3  104566   94520.0  114612.0    157       142.0   \n",
+       "5     202407          3  138078  127050.0  149106.0    207       190.0   \n",
+       "6     202406          3  190062  177955.0  202169.0    285       267.0   \n",
+       "7     202405          3  216237  203595.0  228879.0    324       305.0   \n",
+       "8     202404          3  213196  200547.0  225845.0    320       301.0   \n",
+       "9     202403          3  163457  152276.0  174638.0    245       228.0   \n",
+       "10    202402          3  129436  119453.0  139419.0    194       179.0   \n",
+       "11    202401          3  120769  109452.0  132086.0    181       164.0   \n",
+       "12    202352          3  115446  103738.0  127154.0    174       156.0   \n",
+       "13    202351          3  148755  136546.0  160964.0    224       206.0   \n",
+       "14    202350          3  147971  136787.0  159155.0    223       206.0   \n",
+       "15    202349          3  147552  136422.0  158682.0    222       205.0   \n",
+       "16    202348          3  124204  113479.0  134929.0    187       171.0   \n",
+       "17    202347          3  110948  100694.0  121202.0    167       152.0   \n",
+       "18    202346          3   83894   75134.0   92654.0    126       113.0   \n",
+       "19    202345          3   72003   63178.0   80828.0    108        95.0   \n",
+       "20    202344          3   49952   42813.0   57091.0     75        64.0   \n",
+       "21    202343          3   44982   38170.0   51794.0     68        58.0   \n",
+       "22    202342          3   56842   49277.0   64407.0     86        75.0   \n",
+       "23    202341          3   58357   51032.0   65682.0     88        77.0   \n",
+       "24    202340          3   68894   60069.0   77719.0    104        91.0   \n",
+       "25    202339          3   72003   63452.0   80554.0    108        95.0   \n",
+       "26    202338          3   63218   55227.0   71209.0     95        83.0   \n",
+       "27    202337          3   49085   42079.0   56091.0     74        63.0   \n",
+       "28    202336          3   38247   32237.0   44257.0     58        49.0   \n",
+       "29    202335          3   31695   26013.0   37377.0     48        39.0   \n",
+       "...      ...        ...     ...       ...       ...    ...         ...   \n",
+       "2026  198521          3   26096   19621.0   32571.0     47        35.0   \n",
+       "2027  198520          3   27896   20885.0   34907.0     51        38.0   \n",
+       "2028  198519          3   43154   32821.0   53487.0     78        59.0   \n",
+       "2029  198518          3   40555   29935.0   51175.0     74        55.0   \n",
+       "2030  198517          3   34053   24366.0   43740.0     62        44.0   \n",
+       "2031  198516          3   50362   36451.0   64273.0     91        66.0   \n",
+       "2032  198515          3   63881   45538.0   82224.0    116        83.0   \n",
+       "2033  198514          3  134545  114400.0  154690.0    244       207.0   \n",
+       "2034  198513          3  197206  176080.0  218332.0    357       319.0   \n",
+       "2035  198512          3  245240  223304.0  267176.0    445       405.0   \n",
+       "2036  198511          3  276205  252399.0  300011.0    501       458.0   \n",
+       "2037  198510          3  353231  326279.0  380183.0    640       591.0   \n",
+       "2038  198509          3  369895  341109.0  398681.0    670       618.0   \n",
+       "2039  198508          3  389886  359529.0  420243.0    707       652.0   \n",
+       "2040  198507          3  471852  432599.0  511105.0    855       784.0   \n",
+       "2041  198506          3  565825  518011.0  613639.0   1026       939.0   \n",
+       "2042  198505          3  637302  592795.0  681809.0   1155      1074.0   \n",
+       "2043  198504          3  424937  390794.0  459080.0    770       708.0   \n",
+       "2044  198503          3  213901  174689.0  253113.0    388       317.0   \n",
+       "2045  198502          3   97586   80949.0  114223.0    177       147.0   \n",
+       "2046  198501          3   85489   65918.0  105060.0    155       120.0   \n",
+       "2047  198452          3   84830   60602.0  109058.0    154       110.0   \n",
+       "2048  198451          3  101726   80242.0  123210.0    185       146.0   \n",
+       "2049  198450          3  123680  101401.0  145959.0    225       184.0   \n",
+       "2050  198449          3  101073   81684.0  120462.0    184       149.0   \n",
+       "2051  198448          3   78620   60634.0   96606.0    143       110.0   \n",
+       "2052  198447          3   72029   54274.0   89784.0    131        99.0   \n",
+       "2053  198446          3   87330   67686.0  106974.0    159       123.0   \n",
+       "2054  198445          3  135223  101414.0  169032.0    246       184.0   \n",
+       "2055  198444          3   68422   20056.0  116788.0    125        37.0   \n",
        "\n",
        "      inc100_up geo_insee geo_name  \n",
-       "0          50.0        FR   France  \n",
-       "1          40.0        FR   France  \n",
-       "2          41.0        FR   France  \n",
-       "3          40.0        FR   France  \n",
-       "4          46.0        FR   France  \n",
-       "5          39.0        FR   France  \n",
-       "6          31.0        FR   France  \n",
-       "7          39.0        FR   France  \n",
-       "8          39.0        FR   France  \n",
-       "9          31.0        FR   France  \n",
-       "10         39.0        FR   France  \n",
-       "11         32.0        FR   France  \n",
-       "12         25.0        FR   France  \n",
-       "13         26.0        FR   France  \n",
-       "14         35.0        FR   France  \n",
-       "15         45.0        FR   France  \n",
-       "16         74.0        FR   France  \n",
-       "17         77.0        FR   France  \n",
-       "18         75.0        FR   France  \n",
-       "19         61.0        FR   France  \n",
-       "20         49.0        FR   France  \n",
-       "21         37.0        FR   France  \n",
-       "22         36.0        FR   France  \n",
-       "23         46.0        FR   France  \n",
-       "24         34.0        FR   France  \n",
-       "25         20.0        FR   France  \n",
-       "26         20.0        FR   France  \n",
-       "27         14.0        FR   France  \n",
-       "28         13.0        FR   France  \n",
-       "29         13.0        FR   France  \n",
+       "0          80.0        FR   France  \n",
+       "1          86.0        FR   France  \n",
+       "2         101.0        FR   France  \n",
+       "3         119.0        FR   France  \n",
+       "4         172.0        FR   France  \n",
+       "5         224.0        FR   France  \n",
+       "6         303.0        FR   France  \n",
+       "7         343.0        FR   France  \n",
+       "8         339.0        FR   France  \n",
+       "9         262.0        FR   France  \n",
+       "10        209.0        FR   France  \n",
+       "11        198.0        FR   France  \n",
+       "12        192.0        FR   France  \n",
+       "13        242.0        FR   France  \n",
+       "14        240.0        FR   France  \n",
+       "15        239.0        FR   France  \n",
+       "16        203.0        FR   France  \n",
+       "17        182.0        FR   France  \n",
+       "18        139.0        FR   France  \n",
+       "19        121.0        FR   France  \n",
+       "20         86.0        FR   France  \n",
+       "21         78.0        FR   France  \n",
+       "22         97.0        FR   France  \n",
+       "23         99.0        FR   France  \n",
+       "24        117.0        FR   France  \n",
+       "25        121.0        FR   France  \n",
+       "26        107.0        FR   France  \n",
+       "27         85.0        FR   France  \n",
+       "28         67.0        FR   France  \n",
+       "29         57.0        FR   France  \n",
        "...         ...       ...      ...  \n",
-       "1866       59.0        FR   France  \n",
-       "1867       64.0        FR   France  \n",
-       "1868       97.0        FR   France  \n",
-       "1869       93.0        FR   France  \n",
-       "1870       80.0        FR   France  \n",
-       "1871      116.0        FR   France  \n",
-       "1872      149.0        FR   France  \n",
-       "1873      281.0        FR   France  \n",
-       "1874      395.0        FR   France  \n",
-       "1875      485.0        FR   France  \n",
-       "1876      544.0        FR   France  \n",
-       "1877      689.0        FR   France  \n",
-       "1878      722.0        FR   France  \n",
-       "1879      762.0        FR   France  \n",
-       "1880      926.0        FR   France  \n",
-       "1881     1113.0        FR   France  \n",
-       "1882     1236.0        FR   France  \n",
-       "1883      832.0        FR   France  \n",
-       "1884      459.0        FR   France  \n",
-       "1885      207.0        FR   France  \n",
-       "1886      190.0        FR   France  \n",
-       "1887      198.0        FR   France  \n",
-       "1888      224.0        FR   France  \n",
-       "1889      266.0        FR   France  \n",
-       "1890      219.0        FR   France  \n",
-       "1891      176.0        FR   France  \n",
-       "1892      163.0        FR   France  \n",
-       "1893      195.0        FR   France  \n",
-       "1894      308.0        FR   France  \n",
-       "1895      213.0        FR   France  \n",
+       "2026       59.0        FR   France  \n",
+       "2027       64.0        FR   France  \n",
+       "2028       97.0        FR   France  \n",
+       "2029       93.0        FR   France  \n",
+       "2030       80.0        FR   France  \n",
+       "2031      116.0        FR   France  \n",
+       "2032      149.0        FR   France  \n",
+       "2033      281.0        FR   France  \n",
+       "2034      395.0        FR   France  \n",
+       "2035      485.0        FR   France  \n",
+       "2036      544.0        FR   France  \n",
+       "2037      689.0        FR   France  \n",
+       "2038      722.0        FR   France  \n",
+       "2039      762.0        FR   France  \n",
+       "2040      926.0        FR   France  \n",
+       "2041     1113.0        FR   France  \n",
+       "2042     1236.0        FR   France  \n",
+       "2043      832.0        FR   France  \n",
+       "2044      459.0        FR   France  \n",
+       "2045      207.0        FR   France  \n",
+       "2046      190.0        FR   France  \n",
+       "2047      198.0        FR   France  \n",
+       "2048      224.0        FR   France  \n",
+       "2049      266.0        FR   France  \n",
+       "2050      219.0        FR   France  \n",
+       "2051      176.0        FR   France  \n",
+       "2052      163.0        FR   France  \n",
+       "2053      195.0        FR   France  \n",
+       "2054      308.0        FR   France  \n",
+       "2055      213.0        FR   France  \n",
        "\n",
-       "[1896 rows x 10 columns]"
+       "[2056 rows x 10 columns]"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "raw_data = pd.read_csv(data_url, skiprows=1)\n",
+    "raw_data = pd.read_csv(datalocal, skiprows=1)\n",
     "raw_data"
    ]
   },
@@ -1379,127 +1455,1218 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>21</th>\n",
-       "      <td>21</td>\n",
-       "      <td>202040</td>\n",
+       "      <td>21</td>\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>22</th>\n",
+       "      <td>22</td>\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>23</th>\n",
+       "      <td>23</td>\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>24</th>\n",
+       "      <td>24</td>\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>25</th>\n",
+       "      <td>25</td>\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>26</th>\n",
+       "      <td>26</td>\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>27</th>\n",
+       "      <td>27</td>\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>28</th>\n",
+       "      <td>28</td>\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>29</th>\n",
+       "      <td>29</td>\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>...</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",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1866</th>\n",
+       "      <td>1866</td>\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>1867</th>\n",
+       "      <td>1867</td>\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>1868</th>\n",
+       "      <td>1868</td>\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>1869</th>\n",
+       "      <td>1869</td>\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>1870</th>\n",
+       "      <td>1870</td>\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>1871</th>\n",
+       "      <td>1871</td>\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>1872</th>\n",
+       "      <td>1872</td>\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>1873</th>\n",
+       "      <td>1873</td>\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>1874</th>\n",
+       "      <td>1874</td>\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>1875</th>\n",
+       "      <td>1875</td>\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>1876</th>\n",
+       "      <td>1876</td>\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>1877</th>\n",
+       "      <td>1877</td>\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>1878</th>\n",
+       "      <td>1878</td>\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>1879</th>\n",
+       "      <td>1879</td>\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>1880</th>\n",
+       "      <td>1880</td>\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>1881</th>\n",
+       "      <td>1881</td>\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>1882</th>\n",
+       "      <td>1882</td>\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>1883</th>\n",
+       "      <td>1883</td>\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>1884</th>\n",
+       "      <td>1884</td>\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>1885</th>\n",
+       "      <td>1885</td>\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>1886</th>\n",
+       "      <td>1886</td>\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>1887</th>\n",
+       "      <td>1887</td>\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>1888</th>\n",
+       "      <td>1888</td>\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>1889</th>\n",
+       "      <td>1889</td>\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>1890</th>\n",
+       "      <td>1890</td>\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>1891</th>\n",
+       "      <td>1891</td>\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>1892</th>\n",
+       "      <td>1892</td>\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>1893</th>\n",
+       "      <td>1893</td>\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>1894</th>\n",
+       "      <td>1894</td>\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>1895</th>\n",
+       "      <td>1895</td>\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>1896 rows × 11 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      Unnamed: 0    week  indicator     inc   inc_low    inc_up  inc100  \\\n",
+       "0              0  202108          3   27492   22140.0   32844.0      42   \n",
+       "1              1  202107          3   22191   18096.0   26286.0      34   \n",
+       "2              2  202106          3   23171   19122.0   27220.0      35   \n",
+       "3              3  202105          3   22426   18445.0   26407.0      34   \n",
+       "4              4  202104          3   25804   21491.0   30117.0      39   \n",
+       "5              5  202103          3   21810   17894.0   25726.0      33   \n",
+       "6              6  202102          3   17320   13906.0   20734.0      26   \n",
+       "7              7  202101          3   21799   17778.0   25820.0      33   \n",
+       "8              8  202053          3   21220   16498.0   25942.0      32   \n",
+       "9              9  202052          3   16428   12285.0   20571.0      25   \n",
+       "10            10  202051          3   21619   17370.0   25868.0      33   \n",
+       "11            11  202050          3   16845   13220.0   20470.0      26   \n",
+       "12            12  202049          3   12939    9923.0   15955.0      20   \n",
+       "13            13  202048          3   13804   10641.0   16967.0      21   \n",
+       "14            14  202047          3   19085   15285.0   22885.0      29   \n",
+       "15            15  202046          3   24801   20503.0   29099.0      38   \n",
+       "16            16  202045          3   42516   36857.0   48175.0      65   \n",
+       "17            17  202044          3   44567   38521.0   50613.0      68   \n",
+       "18            18  202043          3   43737   37523.0   49951.0      66   \n",
+       "19            19  202042          3   35145   29812.0   40478.0      53   \n",
+       "20            20  202041          3   27877   23206.0   32548.0      42   \n",
+       "21            21  202040          3   20443   16381.0   24505.0      31   \n",
+       "22            22  202039          3   19810   15900.0   23720.0      30   \n",
+       "23            23  202038          3   25562   21142.0   29982.0      39   \n",
+       "24            24  202037          3   18485   14649.0   22321.0      28   \n",
+       "25            25  202036          3   10390    7646.0   13134.0      16   \n",
+       "26            26  202035          3    9918    6842.0   12994.0      15   \n",
+       "27            27  202034          3    6084    3090.0    9078.0       9   \n",
+       "28            28  202033          3    6106    3411.0    8801.0       9   \n",
+       "29            29  202032          3    5918    3330.0    8506.0       9   \n",
+       "...          ...     ...        ...     ...       ...       ...     ...   \n",
+       "1866        1866  198521          3   26096   19621.0   32571.0      47   \n",
+       "1867        1867  198520          3   27896   20885.0   34907.0      51   \n",
+       "1868        1868  198519          3   43154   32821.0   53487.0      78   \n",
+       "1869        1869  198518          3   40555   29935.0   51175.0      74   \n",
+       "1870        1870  198517          3   34053   24366.0   43740.0      62   \n",
+       "1871        1871  198516          3   50362   36451.0   64273.0      91   \n",
+       "1872        1872  198515          3   63881   45538.0   82224.0     116   \n",
+       "1873        1873  198514          3  134545  114400.0  154690.0     244   \n",
+       "1874        1874  198513          3  197206  176080.0  218332.0     357   \n",
+       "1875        1875  198512          3  245240  223304.0  267176.0     445   \n",
+       "1876        1876  198511          3  276205  252399.0  300011.0     501   \n",
+       "1877        1877  198510          3  353231  326279.0  380183.0     640   \n",
+       "1878        1878  198509          3  369895  341109.0  398681.0     670   \n",
+       "1879        1879  198508          3  389886  359529.0  420243.0     707   \n",
+       "1880        1880  198507          3  471852  432599.0  511105.0     855   \n",
+       "1881        1881  198506          3  565825  518011.0  613639.0    1026   \n",
+       "1882        1882  198505          3  637302  592795.0  681809.0    1155   \n",
+       "1883        1883  198504          3  424937  390794.0  459080.0     770   \n",
+       "1884        1884  198503          3  213901  174689.0  253113.0     388   \n",
+       "1885        1885  198502          3   97586   80949.0  114223.0     177   \n",
+       "1886        1886  198501          3   85489   65918.0  105060.0     155   \n",
+       "1887        1887  198452          3   84830   60602.0  109058.0     154   \n",
+       "1888        1888  198451          3  101726   80242.0  123210.0     185   \n",
+       "1889        1889  198450          3  123680  101401.0  145959.0     225   \n",
+       "1890        1890  198449          3  101073   81684.0  120462.0     184   \n",
+       "1891        1891  198448          3   78620   60634.0   96606.0     143   \n",
+       "1892        1892  198447          3   72029   54274.0   89784.0     131   \n",
+       "1893        1893  198446          3   87330   67686.0  106974.0     159   \n",
+       "1894        1894  198445          3  135223  101414.0  169032.0     246   \n",
+       "1895        1895  198444          3   68422   20056.0  116788.0     125   \n",
+       "\n",
+       "      inc100_low  inc100_up geo_insee geo_name  \n",
+       "0           34.0       50.0        FR   France  \n",
+       "1           28.0       40.0        FR   France  \n",
+       "2           29.0       41.0        FR   France  \n",
+       "3           28.0       40.0        FR   France  \n",
+       "4           32.0       46.0        FR   France  \n",
+       "5           27.0       39.0        FR   France  \n",
+       "6           21.0       31.0        FR   France  \n",
+       "7           27.0       39.0        FR   France  \n",
+       "8           25.0       39.0        FR   France  \n",
+       "9           19.0       31.0        FR   France  \n",
+       "10          27.0       39.0        FR   France  \n",
+       "11          20.0       32.0        FR   France  \n",
+       "12          15.0       25.0        FR   France  \n",
+       "13          16.0       26.0        FR   France  \n",
+       "14          23.0       35.0        FR   France  \n",
+       "15          31.0       45.0        FR   France  \n",
+       "16          56.0       74.0        FR   France  \n",
+       "17          59.0       77.0        FR   France  \n",
+       "18          57.0       75.0        FR   France  \n",
+       "19          45.0       61.0        FR   France  \n",
+       "20          35.0       49.0        FR   France  \n",
+       "21          25.0       37.0        FR   France  \n",
+       "22          24.0       36.0        FR   France  \n",
+       "23          32.0       46.0        FR   France  \n",
+       "24          22.0       34.0        FR   France  \n",
+       "25          12.0       20.0        FR   France  \n",
+       "26          10.0       20.0        FR   France  \n",
+       "27           4.0       14.0        FR   France  \n",
+       "28           5.0       13.0        FR   France  \n",
+       "29           5.0       13.0        FR   France  \n",
+       "...          ...        ...       ...      ...  \n",
+       "1866        35.0       59.0        FR   France  \n",
+       "1867        38.0       64.0        FR   France  \n",
+       "1868        59.0       97.0        FR   France  \n",
+       "1869        55.0       93.0        FR   France  \n",
+       "1870        44.0       80.0        FR   France  \n",
+       "1871        66.0      116.0        FR   France  \n",
+       "1872        83.0      149.0        FR   France  \n",
+       "1873       207.0      281.0        FR   France  \n",
+       "1874       319.0      395.0        FR   France  \n",
+       "1875       405.0      485.0        FR   France  \n",
+       "1876       458.0      544.0        FR   France  \n",
+       "1877       591.0      689.0        FR   France  \n",
+       "1878       618.0      722.0        FR   France  \n",
+       "1879       652.0      762.0        FR   France  \n",
+       "1880       784.0      926.0        FR   France  \n",
+       "1881       939.0     1113.0        FR   France  \n",
+       "1882      1074.0     1236.0        FR   France  \n",
+       "1883       708.0      832.0        FR   France  \n",
+       "1884       317.0      459.0        FR   France  \n",
+       "1885       147.0      207.0        FR   France  \n",
+       "1886       120.0      190.0        FR   France  \n",
+       "1887       110.0      198.0        FR   France  \n",
+       "1888       146.0      224.0        FR   France  \n",
+       "1889       184.0      266.0        FR   France  \n",
+       "1890       149.0      219.0        FR   France  \n",
+       "1891       110.0      176.0        FR   France  \n",
+       "1892        99.0      163.0        FR   France  \n",
+       "1893       123.0      195.0        FR   France  \n",
+       "1894       184.0      308.0        FR   France  \n",
+       "1895        37.0      213.0        FR   France  \n",
+       "\n",
+       "[1896 rows x 11 columns]"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data.to_csv('datatelecharge.csv',)\n",
+    "raw_data2 =pd.read_csv('datatelecharge.csv')\n",
+    "raw_data2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>indicator</th>\n",
+       "      <th>inc</th>\n",
+       "      <th>inc_low</th>\n",
+       "      <th>inc_up</th>\n",
+       "      <th>inc100</th>\n",
+       "      <th>inc100_low</th>\n",
+       "      <th>inc100_up</th>\n",
+       "      <th>geo_insee</th>\n",
+       "      <th>geo_name</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1818</th>\n",
+       "      <td>198919</td>\n",
+       "      <td>3</td>\n",
+       "      <td>-</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>-</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",
+       "1818  198919          3   -      NaN     NaN      -         NaN        NaN   \n",
+       "\n",
+       "     geo_insee geo_name  \n",
+       "1818        FR   France  "
+      ]
+     },
+     "execution_count": 5,
+     "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": 6,
+   "metadata": {
+    "scrolled": true
+   },
+   "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>202411</td>\n",
+       "      <td>3</td>\n",
+       "      <td>54870</td>\n",
+       "      <td>46604.0</td>\n",
+       "      <td>63136.0</td>\n",
+       "      <td>82</td>\n",
+       "      <td>70.0</td>\n",
+       "      <td>94.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>202410</td>\n",
+       "      <td>3</td>\n",
+       "      <td>60835</td>\n",
+       "      <td>53252.0</td>\n",
+       "      <td>68418.0</td>\n",
+       "      <td>91</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>102.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>202409</td>\n",
+       "      <td>3</td>\n",
+       "      <td>71121</td>\n",
+       "      <td>62920.0</td>\n",
+       "      <td>79322.0</td>\n",
+       "      <td>107</td>\n",
+       "      <td>95.0</td>\n",
+       "      <td>119.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>202408</td>\n",
+       "      <td>3</td>\n",
+       "      <td>104566</td>\n",
+       "      <td>94520.0</td>\n",
+       "      <td>114612.0</td>\n",
+       "      <td>157</td>\n",
+       "      <td>142.0</td>\n",
+       "      <td>172.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>202407</td>\n",
+       "      <td>3</td>\n",
+       "      <td>138078</td>\n",
+       "      <td>127050.0</td>\n",
+       "      <td>149106.0</td>\n",
+       "      <td>207</td>\n",
+       "      <td>190.0</td>\n",
+       "      <td>224.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>202406</td>\n",
+       "      <td>3</td>\n",
+       "      <td>190062</td>\n",
+       "      <td>177955.0</td>\n",
+       "      <td>202169.0</td>\n",
+       "      <td>285</td>\n",
+       "      <td>267.0</td>\n",
+       "      <td>303.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>202405</td>\n",
+       "      <td>3</td>\n",
+       "      <td>216237</td>\n",
+       "      <td>203595.0</td>\n",
+       "      <td>228879.0</td>\n",
+       "      <td>324</td>\n",
+       "      <td>305.0</td>\n",
+       "      <td>343.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>202404</td>\n",
+       "      <td>3</td>\n",
+       "      <td>213196</td>\n",
+       "      <td>200547.0</td>\n",
+       "      <td>225845.0</td>\n",
+       "      <td>320</td>\n",
+       "      <td>301.0</td>\n",
+       "      <td>339.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>202403</td>\n",
+       "      <td>3</td>\n",
+       "      <td>163457</td>\n",
+       "      <td>152276.0</td>\n",
+       "      <td>174638.0</td>\n",
+       "      <td>245</td>\n",
+       "      <td>228.0</td>\n",
+       "      <td>262.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>202402</td>\n",
+       "      <td>3</td>\n",
+       "      <td>129436</td>\n",
+       "      <td>119453.0</td>\n",
+       "      <td>139419.0</td>\n",
+       "      <td>194</td>\n",
+       "      <td>179.0</td>\n",
+       "      <td>209.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>202401</td>\n",
+       "      <td>3</td>\n",
+       "      <td>120769</td>\n",
+       "      <td>109452.0</td>\n",
+       "      <td>132086.0</td>\n",
+       "      <td>181</td>\n",
+       "      <td>164.0</td>\n",
+       "      <td>198.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>202352</td>\n",
+       "      <td>3</td>\n",
+       "      <td>115446</td>\n",
+       "      <td>103738.0</td>\n",
+       "      <td>127154.0</td>\n",
+       "      <td>174</td>\n",
+       "      <td>156.0</td>\n",
+       "      <td>192.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>202351</td>\n",
+       "      <td>3</td>\n",
+       "      <td>148755</td>\n",
+       "      <td>136546.0</td>\n",
+       "      <td>160964.0</td>\n",
+       "      <td>224</td>\n",
+       "      <td>206.0</td>\n",
+       "      <td>242.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>202350</td>\n",
+       "      <td>3</td>\n",
+       "      <td>147971</td>\n",
+       "      <td>136787.0</td>\n",
+       "      <td>159155.0</td>\n",
+       "      <td>223</td>\n",
+       "      <td>206.0</td>\n",
+       "      <td>240.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>202349</td>\n",
+       "      <td>3</td>\n",
+       "      <td>147552</td>\n",
+       "      <td>136422.0</td>\n",
+       "      <td>158682.0</td>\n",
+       "      <td>222</td>\n",
+       "      <td>205.0</td>\n",
+       "      <td>239.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>202348</td>\n",
+       "      <td>3</td>\n",
+       "      <td>124204</td>\n",
+       "      <td>113479.0</td>\n",
+       "      <td>134929.0</td>\n",
+       "      <td>187</td>\n",
+       "      <td>171.0</td>\n",
+       "      <td>203.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>202347</td>\n",
+       "      <td>3</td>\n",
+       "      <td>110910</td>\n",
+       "      <td>100658.0</td>\n",
+       "      <td>121162.0</td>\n",
+       "      <td>167</td>\n",
+       "      <td>152.0</td>\n",
+       "      <td>182.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>202346</td>\n",
+       "      <td>3</td>\n",
+       "      <td>83853</td>\n",
+       "      <td>75096.0</td>\n",
+       "      <td>92610.0</td>\n",
+       "      <td>126</td>\n",
+       "      <td>113.0</td>\n",
+       "      <td>139.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>202345</td>\n",
+       "      <td>3</td>\n",
+       "      <td>72003</td>\n",
+       "      <td>63178.0</td>\n",
+       "      <td>80828.0</td>\n",
+       "      <td>108</td>\n",
+       "      <td>95.0</td>\n",
+       "      <td>121.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>202344</td>\n",
+       "      <td>3</td>\n",
+       "      <td>49952</td>\n",
+       "      <td>42813.0</td>\n",
+       "      <td>57091.0</td>\n",
+       "      <td>75</td>\n",
+       "      <td>64.0</td>\n",
+       "      <td>86.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>202343</td>\n",
+       "      <td>3</td>\n",
+       "      <td>44982</td>\n",
+       "      <td>38170.0</td>\n",
+       "      <td>51794.0</td>\n",
+       "      <td>68</td>\n",
+       "      <td>58.0</td>\n",
+       "      <td>78.0</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>202342</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>56842</td>\n",
+       "      <td>49277.0</td>\n",
+       "      <td>64407.0</td>\n",
+       "      <td>86</td>\n",
+       "      <td>75.0</td>\n",
+       "      <td>97.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>22</th>\n",
-       "      <td>22</td>\n",
-       "      <td>202039</td>\n",
+       "      <td>202341</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>58357</td>\n",
+       "      <td>51032.0</td>\n",
+       "      <td>65682.0</td>\n",
+       "      <td>88</td>\n",
+       "      <td>77.0</td>\n",
+       "      <td>99.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>23</th>\n",
-       "      <td>23</td>\n",
-       "      <td>202038</td>\n",
+       "      <td>202340</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>68894</td>\n",
+       "      <td>60069.0</td>\n",
+       "      <td>77719.0</td>\n",
+       "      <td>104</td>\n",
+       "      <td>91.0</td>\n",
+       "      <td>117.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>24</th>\n",
-       "      <td>24</td>\n",
-       "      <td>202037</td>\n",
+       "      <td>202339</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>72003</td>\n",
+       "      <td>63452.0</td>\n",
+       "      <td>80554.0</td>\n",
+       "      <td>108</td>\n",
+       "      <td>95.0</td>\n",
+       "      <td>121.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>25</th>\n",
-       "      <td>25</td>\n",
-       "      <td>202036</td>\n",
+       "      <td>202338</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>63218</td>\n",
+       "      <td>55227.0</td>\n",
+       "      <td>71209.0</td>\n",
+       "      <td>95</td>\n",
+       "      <td>83.0</td>\n",
+       "      <td>107.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>26</th>\n",
-       "      <td>26</td>\n",
-       "      <td>202035</td>\n",
+       "      <td>202337</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>49085</td>\n",
+       "      <td>42079.0</td>\n",
+       "      <td>56091.0</td>\n",
+       "      <td>74</td>\n",
+       "      <td>63.0</td>\n",
+       "      <td>85.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>27</th>\n",
-       "      <td>27</td>\n",
-       "      <td>202034</td>\n",
+       "      <td>202336</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>38247</td>\n",
+       "      <td>32237.0</td>\n",
+       "      <td>44257.0</td>\n",
+       "      <td>58</td>\n",
+       "      <td>49.0</td>\n",
+       "      <td>67.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>28</th>\n",
-       "      <td>28</td>\n",
-       "      <td>202033</td>\n",
+       "      <td>202335</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>31695</td>\n",
+       "      <td>26013.0</td>\n",
+       "      <td>37377.0</td>\n",
+       "      <td>48</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>57.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>29</th>\n",
-       "      <td>29</td>\n",
-       "      <td>202032</td>\n",
+       "      <td>202334</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>26663</td>\n",
+       "      <td>21057.0</td>\n",
+       "      <td>32269.0</td>\n",
+       "      <td>40</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>48.0</td>\n",
        "      <td>FR</td>\n",
        "      <td>France</td>\n",
        "    </tr>\n",
@@ -1515,11 +2682,9 @@
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
-       "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1866</th>\n",
-       "      <td>1866</td>\n",
+       "      <th>2025</th>\n",
        "      <td>198521</td>\n",
        "      <td>3</td>\n",
        "      <td>26096</td>\n",
@@ -1532,8 +2697,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1867</th>\n",
-       "      <td>1867</td>\n",
+       "      <th>2026</th>\n",
        "      <td>198520</td>\n",
        "      <td>3</td>\n",
        "      <td>27896</td>\n",
@@ -1546,8 +2710,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1868</th>\n",
-       "      <td>1868</td>\n",
+       "      <th>2027</th>\n",
        "      <td>198519</td>\n",
        "      <td>3</td>\n",
        "      <td>43154</td>\n",
@@ -1560,8 +2723,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1869</th>\n",
-       "      <td>1869</td>\n",
+       "      <th>2028</th>\n",
        "      <td>198518</td>\n",
        "      <td>3</td>\n",
        "      <td>40555</td>\n",
@@ -1574,8 +2736,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1870</th>\n",
-       "      <td>1870</td>\n",
+       "      <th>2029</th>\n",
        "      <td>198517</td>\n",
        "      <td>3</td>\n",
        "      <td>34053</td>\n",
@@ -1588,8 +2749,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1871</th>\n",
-       "      <td>1871</td>\n",
+       "      <th>2030</th>\n",
        "      <td>198516</td>\n",
        "      <td>3</td>\n",
        "      <td>50362</td>\n",
@@ -1602,8 +2762,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1872</th>\n",
-       "      <td>1872</td>\n",
+       "      <th>2031</th>\n",
        "      <td>198515</td>\n",
        "      <td>3</td>\n",
        "      <td>63881</td>\n",
@@ -1616,8 +2775,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1873</th>\n",
-       "      <td>1873</td>\n",
+       "      <th>2032</th>\n",
        "      <td>198514</td>\n",
        "      <td>3</td>\n",
        "      <td>134545</td>\n",
@@ -1630,8 +2788,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1874</th>\n",
-       "      <td>1874</td>\n",
+       "      <th>2033</th>\n",
        "      <td>198513</td>\n",
        "      <td>3</td>\n",
        "      <td>197206</td>\n",
@@ -1644,8 +2801,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1875</th>\n",
-       "      <td>1875</td>\n",
+       "      <th>2034</th>\n",
        "      <td>198512</td>\n",
        "      <td>3</td>\n",
        "      <td>245240</td>\n",
@@ -1658,8 +2814,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1876</th>\n",
-       "      <td>1876</td>\n",
+       "      <th>2035</th>\n",
        "      <td>198511</td>\n",
        "      <td>3</td>\n",
        "      <td>276205</td>\n",
@@ -1672,8 +2827,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1877</th>\n",
-       "      <td>1877</td>\n",
+       "      <th>2036</th>\n",
        "      <td>198510</td>\n",
        "      <td>3</td>\n",
        "      <td>353231</td>\n",
@@ -1686,8 +2840,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1878</th>\n",
-       "      <td>1878</td>\n",
+       "      <th>2037</th>\n",
        "      <td>198509</td>\n",
        "      <td>3</td>\n",
        "      <td>369895</td>\n",
@@ -1700,8 +2853,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1879</th>\n",
-       "      <td>1879</td>\n",
+       "      <th>2038</th>\n",
        "      <td>198508</td>\n",
        "      <td>3</td>\n",
        "      <td>389886</td>\n",
@@ -1714,8 +2866,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1880</th>\n",
-       "      <td>1880</td>\n",
+       "      <th>2039</th>\n",
        "      <td>198507</td>\n",
        "      <td>3</td>\n",
        "      <td>471852</td>\n",
@@ -1728,8 +2879,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1881</th>\n",
-       "      <td>1881</td>\n",
+       "      <th>2040</th>\n",
        "      <td>198506</td>\n",
        "      <td>3</td>\n",
        "      <td>565825</td>\n",
@@ -1742,8 +2892,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1882</th>\n",
-       "      <td>1882</td>\n",
+       "      <th>2041</th>\n",
        "      <td>198505</td>\n",
        "      <td>3</td>\n",
        "      <td>637302</td>\n",
@@ -1756,8 +2905,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1883</th>\n",
-       "      <td>1883</td>\n",
+       "      <th>2042</th>\n",
        "      <td>198504</td>\n",
        "      <td>3</td>\n",
        "      <td>424937</td>\n",
@@ -1770,8 +2918,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1884</th>\n",
-       "      <td>1884</td>\n",
+       "      <th>2043</th>\n",
        "      <td>198503</td>\n",
        "      <td>3</td>\n",
        "      <td>213901</td>\n",
@@ -1784,8 +2931,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1885</th>\n",
-       "      <td>1885</td>\n",
+       "      <th>2044</th>\n",
        "      <td>198502</td>\n",
        "      <td>3</td>\n",
        "      <td>97586</td>\n",
@@ -1798,8 +2944,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1886</th>\n",
-       "      <td>1886</td>\n",
+       "      <th>2045</th>\n",
        "      <td>198501</td>\n",
        "      <td>3</td>\n",
        "      <td>85489</td>\n",
@@ -1812,8 +2957,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1887</th>\n",
-       "      <td>1887</td>\n",
+       "      <th>2046</th>\n",
        "      <td>198452</td>\n",
        "      <td>3</td>\n",
        "      <td>84830</td>\n",
@@ -1826,8 +2970,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1888</th>\n",
-       "      <td>1888</td>\n",
+       "      <th>2047</th>\n",
        "      <td>198451</td>\n",
        "      <td>3</td>\n",
        "      <td>101726</td>\n",
@@ -1840,8 +2983,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1889</th>\n",
-       "      <td>1889</td>\n",
+       "      <th>2048</th>\n",
        "      <td>198450</td>\n",
        "      <td>3</td>\n",
        "      <td>123680</td>\n",
@@ -1854,8 +2996,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1890</th>\n",
-       "      <td>1890</td>\n",
+       "      <th>2049</th>\n",
        "      <td>198449</td>\n",
        "      <td>3</td>\n",
        "      <td>101073</td>\n",
@@ -1868,8 +3009,7 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1891</th>\n",
-       "      <td>1891</td>\n",
+       "      <th>2050</th>\n",
        "      <td>198448</td>\n",
        "      <td>3</td>\n",
        "      <td>78620</td>\n",
@@ -1882,205 +3022,200 @@
        "      <td>France</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1892</th>\n",
-       "      <td>1892</td>\n",
+       "      <th>2051</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>1893</th>\n",
-       "      <td>1893</td>\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>1894</th>\n",
-       "      <td>1894</td>\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>1895</th>\n",
-       "      <td>1895</td>\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>1896 rows × 11 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "      Unnamed: 0    week  indicator     inc   inc_low    inc_up  inc100  \\\n",
-       "0              0  202108          3   27492   22140.0   32844.0      42   \n",
-       "1              1  202107          3   22191   18096.0   26286.0      34   \n",
-       "2              2  202106          3   23171   19122.0   27220.0      35   \n",
-       "3              3  202105          3   22426   18445.0   26407.0      34   \n",
-       "4              4  202104          3   25804   21491.0   30117.0      39   \n",
-       "5              5  202103          3   21810   17894.0   25726.0      33   \n",
-       "6              6  202102          3   17320   13906.0   20734.0      26   \n",
-       "7              7  202101          3   21799   17778.0   25820.0      33   \n",
-       "8              8  202053          3   21220   16498.0   25942.0      32   \n",
-       "9              9  202052          3   16428   12285.0   20571.0      25   \n",
-       "10            10  202051          3   21619   17370.0   25868.0      33   \n",
-       "11            11  202050          3   16845   13220.0   20470.0      26   \n",
-       "12            12  202049          3   12939    9923.0   15955.0      20   \n",
-       "13            13  202048          3   13804   10641.0   16967.0      21   \n",
-       "14            14  202047          3   19085   15285.0   22885.0      29   \n",
-       "15            15  202046          3   24801   20503.0   29099.0      38   \n",
-       "16            16  202045          3   42516   36857.0   48175.0      65   \n",
-       "17            17  202044          3   44567   38521.0   50613.0      68   \n",
-       "18            18  202043          3   43737   37523.0   49951.0      66   \n",
-       "19            19  202042          3   35145   29812.0   40478.0      53   \n",
-       "20            20  202041          3   27877   23206.0   32548.0      42   \n",
-       "21            21  202040          3   20443   16381.0   24505.0      31   \n",
-       "22            22  202039          3   19810   15900.0   23720.0      30   \n",
-       "23            23  202038          3   25562   21142.0   29982.0      39   \n",
-       "24            24  202037          3   18485   14649.0   22321.0      28   \n",
-       "25            25  202036          3   10390    7646.0   13134.0      16   \n",
-       "26            26  202035          3    9918    6842.0   12994.0      15   \n",
-       "27            27  202034          3    6084    3090.0    9078.0       9   \n",
-       "28            28  202033          3    6106    3411.0    8801.0       9   \n",
-       "29            29  202032          3    5918    3330.0    8506.0       9   \n",
-       "...          ...     ...        ...     ...       ...       ...     ...   \n",
-       "1866        1866  198521          3   26096   19621.0   32571.0      47   \n",
-       "1867        1867  198520          3   27896   20885.0   34907.0      51   \n",
-       "1868        1868  198519          3   43154   32821.0   53487.0      78   \n",
-       "1869        1869  198518          3   40555   29935.0   51175.0      74   \n",
-       "1870        1870  198517          3   34053   24366.0   43740.0      62   \n",
-       "1871        1871  198516          3   50362   36451.0   64273.0      91   \n",
-       "1872        1872  198515          3   63881   45538.0   82224.0     116   \n",
-       "1873        1873  198514          3  134545  114400.0  154690.0     244   \n",
-       "1874        1874  198513          3  197206  176080.0  218332.0     357   \n",
-       "1875        1875  198512          3  245240  223304.0  267176.0     445   \n",
-       "1876        1876  198511          3  276205  252399.0  300011.0     501   \n",
-       "1877        1877  198510          3  353231  326279.0  380183.0     640   \n",
-       "1878        1878  198509          3  369895  341109.0  398681.0     670   \n",
-       "1879        1879  198508          3  389886  359529.0  420243.0     707   \n",
-       "1880        1880  198507          3  471852  432599.0  511105.0     855   \n",
-       "1881        1881  198506          3  565825  518011.0  613639.0    1026   \n",
-       "1882        1882  198505          3  637302  592795.0  681809.0    1155   \n",
-       "1883        1883  198504          3  424937  390794.0  459080.0     770   \n",
-       "1884        1884  198503          3  213901  174689.0  253113.0     388   \n",
-       "1885        1885  198502          3   97586   80949.0  114223.0     177   \n",
-       "1886        1886  198501          3   85489   65918.0  105060.0     155   \n",
-       "1887        1887  198452          3   84830   60602.0  109058.0     154   \n",
-       "1888        1888  198451          3  101726   80242.0  123210.0     185   \n",
-       "1889        1889  198450          3  123680  101401.0  145959.0     225   \n",
-       "1890        1890  198449          3  101073   81684.0  120462.0     184   \n",
-       "1891        1891  198448          3   78620   60634.0   96606.0     143   \n",
-       "1892        1892  198447          3   72029   54274.0   89784.0     131   \n",
-       "1893        1893  198446          3   87330   67686.0  106974.0     159   \n",
-       "1894        1894  198445          3  135223  101414.0  169032.0     246   \n",
-       "1895        1895  198444          3   68422   20056.0  116788.0     125   \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>2052</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>2053</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>2054</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>2054 rows × 10 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        week  indicator     inc   inc_low    inc_up inc100  inc100_low  \\\n",
+       "0     202411          3   54870   46604.0   63136.0     82        70.0   \n",
+       "1     202410          3   60835   53252.0   68418.0     91        80.0   \n",
+       "2     202409          3   71121   62920.0   79322.0    107        95.0   \n",
+       "3     202408          3  104566   94520.0  114612.0    157       142.0   \n",
+       "4     202407          3  138078  127050.0  149106.0    207       190.0   \n",
+       "5     202406          3  190062  177955.0  202169.0    285       267.0   \n",
+       "6     202405          3  216237  203595.0  228879.0    324       305.0   \n",
+       "7     202404          3  213196  200547.0  225845.0    320       301.0   \n",
+       "8     202403          3  163457  152276.0  174638.0    245       228.0   \n",
+       "9     202402          3  129436  119453.0  139419.0    194       179.0   \n",
+       "10    202401          3  120769  109452.0  132086.0    181       164.0   \n",
+       "11    202352          3  115446  103738.0  127154.0    174       156.0   \n",
+       "12    202351          3  148755  136546.0  160964.0    224       206.0   \n",
+       "13    202350          3  147971  136787.0  159155.0    223       206.0   \n",
+       "14    202349          3  147552  136422.0  158682.0    222       205.0   \n",
+       "15    202348          3  124204  113479.0  134929.0    187       171.0   \n",
+       "16    202347          3  110910  100658.0  121162.0    167       152.0   \n",
+       "17    202346          3   83853   75096.0   92610.0    126       113.0   \n",
+       "18    202345          3   72003   63178.0   80828.0    108        95.0   \n",
+       "19    202344          3   49952   42813.0   57091.0     75        64.0   \n",
+       "20    202343          3   44982   38170.0   51794.0     68        58.0   \n",
+       "21    202342          3   56842   49277.0   64407.0     86        75.0   \n",
+       "22    202341          3   58357   51032.0   65682.0     88        77.0   \n",
+       "23    202340          3   68894   60069.0   77719.0    104        91.0   \n",
+       "24    202339          3   72003   63452.0   80554.0    108        95.0   \n",
+       "25    202338          3   63218   55227.0   71209.0     95        83.0   \n",
+       "26    202337          3   49085   42079.0   56091.0     74        63.0   \n",
+       "27    202336          3   38247   32237.0   44257.0     58        49.0   \n",
+       "28    202335          3   31695   26013.0   37377.0     48        39.0   \n",
+       "29    202334          3   26663   21057.0   32269.0     40        32.0   \n",
+       "...      ...        ...     ...       ...       ...    ...         ...   \n",
+       "2025  198521          3   26096   19621.0   32571.0     47        35.0   \n",
+       "2026  198520          3   27896   20885.0   34907.0     51        38.0   \n",
+       "2027  198519          3   43154   32821.0   53487.0     78        59.0   \n",
+       "2028  198518          3   40555   29935.0   51175.0     74        55.0   \n",
+       "2029  198517          3   34053   24366.0   43740.0     62        44.0   \n",
+       "2030  198516          3   50362   36451.0   64273.0     91        66.0   \n",
+       "2031  198515          3   63881   45538.0   82224.0    116        83.0   \n",
+       "2032  198514          3  134545  114400.0  154690.0    244       207.0   \n",
+       "2033  198513          3  197206  176080.0  218332.0    357       319.0   \n",
+       "2034  198512          3  245240  223304.0  267176.0    445       405.0   \n",
+       "2035  198511          3  276205  252399.0  300011.0    501       458.0   \n",
+       "2036  198510          3  353231  326279.0  380183.0    640       591.0   \n",
+       "2037  198509          3  369895  341109.0  398681.0    670       618.0   \n",
+       "2038  198508          3  389886  359529.0  420243.0    707       652.0   \n",
+       "2039  198507          3  471852  432599.0  511105.0    855       784.0   \n",
+       "2040  198506          3  565825  518011.0  613639.0   1026       939.0   \n",
+       "2041  198505          3  637302  592795.0  681809.0   1155      1074.0   \n",
+       "2042  198504          3  424937  390794.0  459080.0    770       708.0   \n",
+       "2043  198503          3  213901  174689.0  253113.0    388       317.0   \n",
+       "2044  198502          3   97586   80949.0  114223.0    177       147.0   \n",
+       "2045  198501          3   85489   65918.0  105060.0    155       120.0   \n",
+       "2046  198452          3   84830   60602.0  109058.0    154       110.0   \n",
+       "2047  198451          3  101726   80242.0  123210.0    185       146.0   \n",
+       "2048  198450          3  123680  101401.0  145959.0    225       184.0   \n",
+       "2049  198449          3  101073   81684.0  120462.0    184       149.0   \n",
+       "2050  198448          3   78620   60634.0   96606.0    143       110.0   \n",
+       "2051  198447          3   72029   54274.0   89784.0    131        99.0   \n",
+       "2052  198446          3   87330   67686.0  106974.0    159       123.0   \n",
+       "2053  198445          3  135223  101414.0  169032.0    246       184.0   \n",
+       "2054  198444          3   68422   20056.0  116788.0    125        37.0   \n",
        "\n",
-       "      inc100_low  inc100_up geo_insee geo_name  \n",
-       "0           34.0       50.0        FR   France  \n",
-       "1           28.0       40.0        FR   France  \n",
-       "2           29.0       41.0        FR   France  \n",
-       "3           28.0       40.0        FR   France  \n",
-       "4           32.0       46.0        FR   France  \n",
-       "5           27.0       39.0        FR   France  \n",
-       "6           21.0       31.0        FR   France  \n",
-       "7           27.0       39.0        FR   France  \n",
-       "8           25.0       39.0        FR   France  \n",
-       "9           19.0       31.0        FR   France  \n",
-       "10          27.0       39.0        FR   France  \n",
-       "11          20.0       32.0        FR   France  \n",
-       "12          15.0       25.0        FR   France  \n",
-       "13          16.0       26.0        FR   France  \n",
-       "14          23.0       35.0        FR   France  \n",
-       "15          31.0       45.0        FR   France  \n",
-       "16          56.0       74.0        FR   France  \n",
-       "17          59.0       77.0        FR   France  \n",
-       "18          57.0       75.0        FR   France  \n",
-       "19          45.0       61.0        FR   France  \n",
-       "20          35.0       49.0        FR   France  \n",
-       "21          25.0       37.0        FR   France  \n",
-       "22          24.0       36.0        FR   France  \n",
-       "23          32.0       46.0        FR   France  \n",
-       "24          22.0       34.0        FR   France  \n",
-       "25          12.0       20.0        FR   France  \n",
-       "26          10.0       20.0        FR   France  \n",
-       "27           4.0       14.0        FR   France  \n",
-       "28           5.0       13.0        FR   France  \n",
-       "29           5.0       13.0        FR   France  \n",
-       "...          ...        ...       ...      ...  \n",
-       "1866        35.0       59.0        FR   France  \n",
-       "1867        38.0       64.0        FR   France  \n",
-       "1868        59.0       97.0        FR   France  \n",
-       "1869        55.0       93.0        FR   France  \n",
-       "1870        44.0       80.0        FR   France  \n",
-       "1871        66.0      116.0        FR   France  \n",
-       "1872        83.0      149.0        FR   France  \n",
-       "1873       207.0      281.0        FR   France  \n",
-       "1874       319.0      395.0        FR   France  \n",
-       "1875       405.0      485.0        FR   France  \n",
-       "1876       458.0      544.0        FR   France  \n",
-       "1877       591.0      689.0        FR   France  \n",
-       "1878       618.0      722.0        FR   France  \n",
-       "1879       652.0      762.0        FR   France  \n",
-       "1880       784.0      926.0        FR   France  \n",
-       "1881       939.0     1113.0        FR   France  \n",
-       "1882      1074.0     1236.0        FR   France  \n",
-       "1883       708.0      832.0        FR   France  \n",
-       "1884       317.0      459.0        FR   France  \n",
-       "1885       147.0      207.0        FR   France  \n",
-       "1886       120.0      190.0        FR   France  \n",
-       "1887       110.0      198.0        FR   France  \n",
-       "1888       146.0      224.0        FR   France  \n",
-       "1889       184.0      266.0        FR   France  \n",
-       "1890       149.0      219.0        FR   France  \n",
-       "1891       110.0      176.0        FR   France  \n",
-       "1892        99.0      163.0        FR   France  \n",
-       "1893       123.0      195.0        FR   France  \n",
-       "1894       184.0      308.0        FR   France  \n",
-       "1895        37.0      213.0        FR   France  \n",
+       "      inc100_up geo_insee geo_name  \n",
+       "0          94.0        FR   France  \n",
+       "1         102.0        FR   France  \n",
+       "2         119.0        FR   France  \n",
+       "3         172.0        FR   France  \n",
+       "4         224.0        FR   France  \n",
+       "5         303.0        FR   France  \n",
+       "6         343.0        FR   France  \n",
+       "7         339.0        FR   France  \n",
+       "8         262.0        FR   France  \n",
+       "9         209.0        FR   France  \n",
+       "10        198.0        FR   France  \n",
+       "11        192.0        FR   France  \n",
+       "12        242.0        FR   France  \n",
+       "13        240.0        FR   France  \n",
+       "14        239.0        FR   France  \n",
+       "15        203.0        FR   France  \n",
+       "16        182.0        FR   France  \n",
+       "17        139.0        FR   France  \n",
+       "18        121.0        FR   France  \n",
+       "19         86.0        FR   France  \n",
+       "20         78.0        FR   France  \n",
+       "21         97.0        FR   France  \n",
+       "22         99.0        FR   France  \n",
+       "23        117.0        FR   France  \n",
+       "24        121.0        FR   France  \n",
+       "25        107.0        FR   France  \n",
+       "26         85.0        FR   France  \n",
+       "27         67.0        FR   France  \n",
+       "28         57.0        FR   France  \n",
+       "29         48.0        FR   France  \n",
+       "...         ...       ...      ...  \n",
+       "2025       59.0        FR   France  \n",
+       "2026       64.0        FR   France  \n",
+       "2027       97.0        FR   France  \n",
+       "2028       93.0        FR   France  \n",
+       "2029       80.0        FR   France  \n",
+       "2030      116.0        FR   France  \n",
+       "2031      149.0        FR   France  \n",
+       "2032      281.0        FR   France  \n",
+       "2033      395.0        FR   France  \n",
+       "2034      485.0        FR   France  \n",
+       "2035      544.0        FR   France  \n",
+       "2036      689.0        FR   France  \n",
+       "2037      722.0        FR   France  \n",
+       "2038      762.0        FR   France  \n",
+       "2039      926.0        FR   France  \n",
+       "2040     1113.0        FR   France  \n",
+       "2041     1236.0        FR   France  \n",
+       "2042      832.0        FR   France  \n",
+       "2043      459.0        FR   France  \n",
+       "2044      207.0        FR   France  \n",
+       "2045      190.0        FR   France  \n",
+       "2046      198.0        FR   France  \n",
+       "2047      224.0        FR   France  \n",
+       "2048      266.0        FR   France  \n",
+       "2049      219.0        FR   France  \n",
+       "2050      176.0        FR   France  \n",
+       "2051      163.0        FR   France  \n",
+       "2052      195.0        FR   France  \n",
+       "2053      308.0        FR   France  \n",
+       "2054      213.0        FR   France  \n",
        "\n",
-       "[1896 rows x 11 columns]"
+       "[2054 rows x 10 columns]"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "raw_data.to_csv('datatelecharge.csv',)\n",
-    "raw_data2 =pd.read_csv('datatelecharge.csv')\n",
-    "raw_data2"
+    "data = raw_data.dropna().copy()\n",
+    "data"
    ]
   },
   {
@@ -2088,25 +3223,33 @@
    "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": [
-    "raw_data[raw_data.isnull().any(axis=1)]"
-   ]
+   "source": []
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Nous éliminons ce point, ce qui n'a pas d'impact fort sur notre analyse qui est assez simple."
+    "à cause des données manquantes, les types des valeurs sont en str et non int"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "str"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "data = raw_data.dropna().copy()\n",
-    "data"
+    "type(data.loc[1,'inc100'])\n"
    ]
   },
   {
@@ -2129,7 +3272,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2159,10 +3302,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 9,
+   "metadata": {},
    "outputs": [],
    "source": [
     "sorted_data = data.set_index('period').sort_index()"
@@ -2186,9 +3327,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 10,
    "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",
@@ -2204,11 +3353,57 @@
     "Un premier regard sur les données !"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sorted_data['inc']= sorted_data['inc'].astype(int)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "On change le type des données pour la colonne inc en int. Comme dans la vidéo"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f1f2d76e128>"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "sorted_data['inc'].plot()"
    ]
@@ -2222,9 +3417,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 20,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f1f2d69fef0>"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "sorted_data['inc'][-200:].plot()"
    ]
@@ -2259,10 +3477,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 21,
+   "metadata": {},
    "outputs": [],
    "source": [
     "first_august_week = [pd.Period(pd.Timestamp(y, 8, 1), 'W')\n",
@@ -2281,7 +3497,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2305,9 +3521,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 23,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f1f2d6a9780>"
+      ]
+     },
+     "execution_count": 23,
+     "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='*')"
    ]
@@ -2321,9 +3560,58 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 24,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2021     743449\n",
+       "2014    1600941\n",
+       "1991    1659249\n",
+       "1995    1840410\n",
+       "2020    2010315\n",
+       "2022    2060304\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",
+       "2023    2873501\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": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "yearly_incidence.sort_values()"
    ]
@@ -2338,9 +3626,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 25,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f1f2d5e8dd8>"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "yearly_incidence.hist(xrot=20)"
    ]
diff --git a/module3/exo1/donnsentinelles.csv b/module3/exo1/donnsentinelles.csv
new file mode 100644
index 0000000000000000000000000000000000000000..7318181ae33169d9d79b74965c3081b91807a645
--- /dev/null
+++ b/module3/exo1/donnsentinelles.csv
@@ -0,0 +1,2058 @@
+# @source="r&#233;seau Sentinelles, INSERM, Sorbonne Universit&#233;, https://www.sentiweb.fr", @meta={"period":[198444,202412],"geo":["PAY",1],"geo_ref":"insee","indicator":"3","type":"all","conf_int":true,"compact":false,"age_group":false}, @date=2024-03-27T17:09:52+01:00, bundle=1711555792
+week,indicator,inc,inc_low,inc_up,inc100,inc100_low,inc100_up,geo_insee,geo_name
+202412,3,46315,38805,53825,69,58,80,FR,France
+202411,3,50466,43470,57462,76,66,86,FR,France
+202410,3,60107,52623,67591,90,79,101,FR,France
+202409,3,71121,62920,79322,107,95,119,FR,France
+202408,3,104566,94520,114612,157,142,172,FR,France
+202407,3,138078,127050,149106,207,190,224,FR,France
+202406,3,190062,177955,202169,285,267,303,FR,France
+202405,3,216237,203595,228879,324,305,343,FR,France
+202404,3,213196,200547,225845,320,301,339,FR,France
+202403,3,163457,152276,174638,245,228,262,FR,France
+202402,3,129436,119453,139419,194,179,209,FR,France
+202401,3,120769,109452,132086,181,164,198,FR,France
+202352,3,115446,103738,127154,174,156,192,FR,France
+202351,3,148755,136546,160964,224,206,242,FR,France
+202350,3,147971,136787,159155,223,206,240,FR,France
+202349,3,147552,136422,158682,222,205,239,FR,France
+202348,3,124204,113479,134929,187,171,203,FR,France
+202347,3,110948,100694,121202,167,152,182,FR,France
+202346,3,83894,75134,92654,126,113,139,FR,France
+202345,3,72003,63178,80828,108,95,121,FR,France
+202344,3,49952,42813,57091,75,64,86,FR,France
+202343,3,44982,38170,51794,68,58,78,FR,France
+202342,3,56842,49277,64407,86,75,97,FR,France
+202341,3,58357,51032,65682,88,77,99,FR,France
+202340,3,68894,60069,77719,104,91,117,FR,France
+202339,3,72003,63452,80554,108,95,121,FR,France
+202338,3,63218,55227,71209,95,83,107,FR,France
+202337,3,49085,42079,56091,74,63,85,FR,France
+202336,3,38247,32237,44257,58,49,67,FR,France
+202335,3,31695,26013,37377,48,39,57,FR,France
+202334,3,26663,21057,32269,40,32,48,FR,France
+202333,3,19144,13161,25127,29,20,38,FR,France
+202332,3,14641,10285,18997,22,15,29,FR,France
+202331,3,15286,10705,19867,23,16,30,FR,France
+202330,3,13205,8647,17763,20,13,27,FR,France
+202329,3,11122,7113,15131,17,11,23,FR,France
+202328,3,9179,5703,12655,14,9,19,FR,France
+202327,3,8999,5763,12235,14,9,19,FR,France
+202326,3,9023,5934,12112,14,9,19,FR,France
+202325,3,10090,6739,13441,15,10,20,FR,France
+202324,3,11308,7639,14977,17,11,23,FR,France
+202323,3,14300,10661,17939,22,17,27,FR,France
+202322,3,18303,13822,22784,28,21,35,FR,France
+202321,3,16460,12188,20732,25,19,31,FR,France
+202320,3,16162,11963,20361,24,18,30,FR,France
+202319,3,16901,12577,21225,25,18,32,FR,France
+202318,3,19929,15402,24456,30,23,37,FR,France
+202317,3,27007,21779,32235,41,33,49,FR,France
+202316,3,27875,22767,32983,42,34,50,FR,France
+202315,3,37455,30993,43917,56,46,66,FR,France
+202314,3,48060,40671,55449,72,61,83,FR,France
+202313,3,64859,56800,72918,98,86,110,FR,France
+202312,3,72750,64499,81001,109,97,121,FR,France
+202311,3,74638,66420,82856,112,100,124,FR,France
+202310,3,76368,68243,84493,115,103,127,FR,France
+202309,3,62062,54778,69346,93,82,104,FR,France
+202308,3,76391,68065,84717,115,102,128,FR,France
+202307,3,89851,80397,99305,135,121,149,FR,France
+202306,3,97368,87636,107100,146,131,161,FR,France
+202305,3,95469,86268,104670,144,130,158,FR,France
+202304,3,74901,66916,82886,113,101,125,FR,France
+202303,3,69570,61893,77247,105,93,117,FR,France
+202302,3,78260,70090,86430,118,106,130,FR,France
+202301,3,121773,111024,132522,183,167,199,FR,France
+202252,3,155371,142004,168738,234,214,254,FR,France
+202251,3,248319,232128,264510,374,350,398,FR,France
+202250,3,234143,219402,248884,353,331,375,FR,France
+202249,3,163384,151691,175077,246,228,264,FR,France
+202248,3,121691,111744,131638,184,169,199,FR,France
+202247,3,96416,87230,105602,145,131,159,FR,France
+202246,3,67735,60075,75395,102,90,114,FR,France
+202245,3,45306,38909,51703,68,58,78,FR,France
+202244,3,34713,28880,40546,52,43,61,FR,France
+202243,3,44769,36884,52654,68,56,80,FR,France
+202242,3,47462,40773,54151,72,62,82,FR,France
+202241,3,48583,42388,54778,73,64,82,FR,France
+202240,3,41927,36115,47739,63,54,72,FR,France
+202239,3,39902,34168,45636,60,51,69,FR,France
+202238,3,28781,23733,33829,43,35,51,FR,France
+202237,3,21395,17076,25714,32,25,39,FR,France
+202236,3,14120,10487,17753,21,16,26,FR,France
+202235,3,9283,6485,12081,14,10,18,FR,France
+202234,3,7498,4731,10265,11,7,15,FR,France
+202233,3,7586,4442,10730,11,6,16,FR,France
+202232,3,12222,7749,16695,18,11,25,FR,France
+202231,3,13257,8905,17609,20,13,27,FR,France
+202230,3,15006,10738,19274,23,17,29,FR,France
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+200438,3,17483,9417,25549,29,16,42,FR,France
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+199837,3,6968,3227,10709,12,6,18,FR,France
+199836,3,3033,580,5486,5,1,9,FR,France
+199835,3,2491,0,5022,4,0,8,FR,France
+199834,3,3853,589,7117,7,1,13,FR,France
+199833,3,2934,0,6598,5,0,11,FR,France
+199832,3,1308,0,2894,2,0,5,FR,France
+199831,3,12147,0,29237,21,0,50,FR,France
+199830,3,5309,1628,8990,9,3,15,FR,France
+199829,3,6486,2465,10507,11,4,18,FR,France
+199828,3,9577,4464,14690,16,7,25,FR,France
+199827,3,12358,7158,17558,21,12,30,FR,France
+199826,3,10415,6547,14283,18,11,25,FR,France
+199825,3,18246,13050,23442,31,22,40,FR,France
+199824,3,16263,11126,21400,28,19,37,FR,France
+199823,3,8553,4911,12195,15,9,21,FR,France
+199822,3,5181,2669,7693,9,5,13,FR,France
+199821,3,4751,2416,7086,8,4,12,FR,France
+199820,3,12129,8099,16159,21,14,28,FR,France
+199819,3,24118,17906,30330,41,30,52,FR,France
+199818,3,31612,24512,38712,54,42,66,FR,France
+199817,3,61148,51894,70402,105,89,121,FR,France
+199816,3,123195,109878,136512,211,188,234,FR,France
+199815,3,171603,156715,186491,294,268,320,FR,France
+199814,3,319092,298398,339786,547,512,582,FR,France
+199813,3,298212,278513,317911,512,478,546,FR,France
+199812,3,263585,246356,280814,452,422,482,FR,France
+199811,3,220578,204894,236262,378,351,405,FR,France
+199810,3,202354,186304,218404,347,319,375,FR,France
+199809,3,227553,209970,245136,390,360,420,FR,France
+199808,3,271362,252005,290719,465,432,498,FR,France
+199807,3,190187,173694,206680,326,298,354,FR,France
+199806,3,88217,76829,99605,151,131,171,FR,France
+199805,3,45180,36970,53390,77,63,91,FR,France
+199804,3,30005,23272,36738,51,39,63,FR,France
+199803,3,23900,18221,29579,41,31,51,FR,France
+199802,3,31143,23994,38292,53,41,65,FR,France
+199801,3,24809,17786,31832,43,31,55,FR,France
+199752,3,29039,21984,36094,50,38,62,FR,France
+199751,3,34924,27737,42111,60,48,72,FR,France
+199750,3,33527,26388,40666,58,46,70,FR,France
+199749,3,15978,11147,20809,27,19,35,FR,France
+199748,3,11507,7744,15270,20,14,26,FR,France
+199747,3,11059,7151,14967,19,12,26,FR,France
+199746,3,8073,4613,11533,14,8,20,FR,France
+199745,3,18202,13113,23291,31,22,40,FR,France
+199744,3,19770,14405,25135,34,25,43,FR,France
+199743,3,16707,11945,21469,29,21,37,FR,France
+199742,3,15340,10351,20329,26,17,35,FR,France
+199741,3,16933,11941,21925,29,20,38,FR,France
+199740,3,13292,8709,17875,23,15,31,FR,France
+199739,3,10189,6279,14099,18,11,25,FR,France
+199738,3,3231,1061,5401,6,2,10,FR,France
+199737,3,4542,1949,7135,8,4,12,FR,France
+199736,3,5131,2205,8057,9,4,14,FR,France
+199735,3,1842,0,3740,3,0,6,FR,France
+199734,3,3226,0,6717,6,0,12,FR,France
+199733,3,1799,0,4368,3,0,7,FR,France
+199732,3,2086,0,4411,4,0,8,FR,France
+199731,3,1386,0,3332,2,0,5,FR,France
+199730,3,2116,0,4919,4,0,9,FR,France
+199729,3,1973,0,4347,3,0,7,FR,France
+199728,3,1560,216,2904,3,1,5,FR,France
+199727,3,2540,754,4326,4,1,7,FR,France
+199726,3,5582,2699,8465,10,5,15,FR,France
+199725,3,4012,1090,6934,7,2,12,FR,France
+199724,3,4696,1824,7568,8,3,13,FR,France
+199723,3,4709,2136,7282,8,4,12,FR,France
+199722,3,2283,665,3901,4,1,7,FR,France
+199721,3,2108,664,3552,4,2,6,FR,France
+199720,3,3257,1519,4995,6,3,9,FR,France
+199719,3,4646,2436,6856,8,4,12,FR,France
+199718,3,5246,2764,7728,9,5,13,FR,France
+199717,3,14236,9906,18566,24,17,31,FR,France
+199716,3,12169,8111,16227,21,14,28,FR,France
+199715,3,9516,6192,12840,16,10,22,FR,France
+199714,3,13602,9659,17545,23,16,30,FR,France
+199713,3,18032,13345,22719,31,23,39,FR,France
+199712,3,17199,12707,21691,30,22,38,FR,France
+199711,3,19988,15419,24557,34,26,42,FR,France
+199710,3,21903,17338,26468,38,30,46,FR,France
+199709,3,29860,24261,35459,51,41,61,FR,France
+199708,3,55445,47857,63033,95,82,108,FR,France
+199707,3,70876,62518,79234,122,108,136,FR,France
+199706,3,76906,68152,85660,132,117,147,FR,France
+199705,3,95900,86095,105705,165,148,182,FR,France
+199704,3,96896,87079,106713,167,150,184,FR,France
+199703,3,143844,131917,155771,248,227,269,FR,France
+199702,3,211578,197395,225761,364,340,388,FR,France
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+199652,3,388201,369211,407191,670,637,703,FR,France
+199651,3,640627,617388,663866,1106,1066,1146,FR,France
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+199649,3,411498,393335,429661,710,679,741,FR,France
+199648,3,195568,182563,208573,338,316,360,FR,France
+199647,3,71980,63619,80341,124,110,138,FR,France
+199646,3,32138,26358,37918,55,45,65,FR,France
+199645,3,25551,20136,30966,44,35,53,FR,France
+199644,3,10753,7230,14276,19,13,25,FR,France
+199643,3,12971,9311,16631,22,16,28,FR,France
+199642,3,11929,8472,15386,21,15,27,FR,France
+199641,3,9918,6674,13162,17,11,23,FR,France
+199640,3,10765,7067,14463,19,13,25,FR,France
+199639,3,8377,5183,11571,14,8,20,FR,France
+199638,3,9470,5965,12975,16,10,22,FR,France
+199637,3,2925,829,5021,5,1,9,FR,France
+199636,3,1122,23,2221,2,0,4,FR,France
+199635,3,1674,93,3255,3,0,6,FR,France
+199634,3,1273,122,2424,2,0,4,FR,France
+199633,3,540,0,1246,1,0,2,FR,France
+199632,3,1453,176,2730,3,1,5,FR,France
+199631,3,3010,752,5268,5,1,9,FR,France
+199630,3,2992,706,5278,5,1,9,FR,France
+199629,3,1559,144,2974,3,1,5,FR,France
+199628,3,3109,541,5677,5,1,9,FR,France
+199627,3,4456,1595,7317,8,3,13,FR,France
+199626,3,2871,1138,4604,5,2,8,FR,France
+199625,3,2308,856,3760,4,1,7,FR,France
+199624,3,2490,1067,3913,4,2,6,FR,France
+199623,3,2819,1262,4376,5,2,8,FR,France
+199622,3,4005,1984,6026,7,4,10,FR,France
+199621,3,7042,4291,9793,12,7,17,FR,France
+199620,3,10619,7365,13873,18,12,24,FR,France
+199619,3,11898,8065,15731,21,14,28,FR,France
+199618,3,18338,13352,23324,32,23,41,FR,France
+199617,3,24954,19100,30808,43,33,53,FR,France
+199616,3,29313,23868,34758,51,42,60,FR,France
+199615,3,51703,43644,59762,89,75,103,FR,France
+199614,3,44414,36774,52054,77,64,90,FR,France
+199613,3,30622,25062,36182,53,43,63,FR,France
+199612,3,31818,25852,37784,55,45,65,FR,France
+199611,3,24427,19499,29355,42,33,51,FR,France
+199610,3,20910,16198,25622,36,28,44,FR,France
+199609,3,19594,15228,23960,34,26,42,FR,France
+199608,3,19046,14850,23242,33,26,40,FR,France
+199607,3,23041,18338,27744,40,32,48,FR,France
+199606,3,21810,17153,26467,38,30,46,FR,France
+199605,3,25275,20410,30140,44,36,52,FR,France
+199604,3,43359,36948,49770,75,64,86,FR,France
+199603,3,54691,48016,61366,94,82,106,FR,France
+199602,3,105606,96106,115106,182,166,198,FR,France
+199601,3,223830,209274,238386,386,361,411,FR,France
+199552,3,397122,378252,415992,688,655,721,FR,France
+199551,3,749988,725434,774542,1299,1256,1342,FR,France
+199550,3,604926,583100,626752,1047,1009,1085,FR,France
+199549,3,375500,358200,392800,650,620,680,FR,France
+199548,3,206446,193457,219435,357,335,379,FR,France
+199547,3,120472,110526,130418,209,192,226,FR,France
+199546,3,62380,55042,69718,108,95,121,FR,France
+199545,3,29791,24523,35059,52,43,61,FR,France
+199544,3,13168,9820,16516,23,17,29,FR,France
+199543,3,16188,12389,19987,28,21,35,FR,France
+199542,3,15178,11387,18969,26,19,33,FR,France
+199541,3,14980,10851,19109,26,19,33,FR,France
+199540,3,16245,11610,20880,28,20,36,FR,France
+199539,3,18499,13844,23154,32,24,40,FR,France
+199538,3,13123,9410,16836,23,17,29,FR,France
+199537,3,4895,2666,7124,8,4,12,FR,France
+199536,3,3659,1574,5744,6,2,10,FR,France
+199535,3,2496,644,4348,4,1,7,FR,France
+199534,3,1887,214,3560,3,0,6,FR,France
+199533,3,905,0,2007,2,0,4,FR,France
+199532,3,700,0,1699,1,0,3,FR,France
+199531,3,1946,92,3800,3,0,6,FR,France
+199530,3,1898,46,3750,3,0,6,FR,France
+199529,3,2148,687,3609,4,1,7,FR,France
+199528,3,3312,1430,5194,6,3,9,FR,France
+199527,3,4853,2683,7023,8,4,12,FR,France
+199526,3,4986,2911,7061,9,5,13,FR,France
+199525,3,4571,2520,6622,8,4,12,FR,France
+199524,3,8058,5054,11062,14,9,19,FR,France
+199523,3,13820,9801,17839,24,17,31,FR,France
+199522,3,14124,9999,18249,24,17,31,FR,France
+199521,3,11931,8655,15207,21,15,27,FR,France
+199520,3,18846,14311,23381,33,25,41,FR,France
+199519,3,26261,21488,31034,45,37,53,FR,France
+199518,3,39231,33258,45204,68,58,78,FR,France
+199517,3,88640,79343,97937,153,137,169,FR,France
+199516,3,140488,129439,151537,243,224,262,FR,France
+199515,3,181007,169110,192904,313,292,334,FR,France
+199514,3,248704,235144,262264,431,408,454,FR,France
+199513,3,209839,197191,222487,363,341,385,FR,France
+199512,3,122434,112497,132371,212,195,229,FR,France
+199511,3,81730,73346,90114,142,127,157,FR,France
+199510,3,49387,42703,56071,86,74,98,FR,France
+199509,3,39696,33259,46133,69,58,80,FR,France
+199508,3,38008,32225,43791,66,56,76,FR,France
+199507,3,30550,25479,35621,53,44,62,FR,France
+199506,3,37351,32007,42695,65,56,74,FR,France
+199505,3,27876,23218,32534,48,40,56,FR,France
+199504,3,27643,22818,32468,48,40,56,FR,France
+199503,3,24844,20391,29297,43,35,51,FR,France
+199502,3,23480,19249,27711,41,34,48,FR,France
+199501,3,26556,21916,31196,46,38,54,FR,France
+199452,3,22036,17495,26577,38,30,46,FR,France
+199451,3,26912,21750,32074,47,38,56,FR,France
+199450,3,28831,23470,34192,50,41,59,FR,France
+199449,3,21161,16559,25763,37,29,45,FR,France
+199448,3,18487,14456,22518,32,25,39,FR,France
+199447,3,15206,11578,18834,26,20,32,FR,France
+199446,3,14252,10525,17979,25,19,31,FR,France
+199445,3,12152,8448,15856,21,15,27,FR,France
+199444,3,11307,7688,14926,20,14,26,FR,France
+199443,3,11254,8002,14506,20,14,26,FR,France
+199442,3,14406,10653,18159,25,18,32,FR,France
+199441,3,14073,10341,17805,24,18,30,FR,France
+199440,3,15962,11850,20074,28,21,35,FR,France
+199439,3,15878,11643,20113,28,21,35,FR,France
+199438,3,15366,11100,19632,27,20,34,FR,France
+199437,3,5949,3561,8337,10,6,14,FR,France
+199436,3,2806,1133,4479,5,2,8,FR,France
+199435,3,4556,2358,6754,8,4,12,FR,France
+199434,3,3459,1444,5474,6,2,10,FR,France
+199433,3,4272,977,7567,7,1,13,FR,France
+199432,3,4786,1613,7959,8,2,14,FR,France
+199431,3,5027,1580,8474,9,3,15,FR,France
+199430,3,2100,520,3680,4,1,7,FR,France
+199429,3,1188,0,2384,2,0,4,FR,France
+199428,3,1581,316,2846,3,1,5,FR,France
+199427,3,713,0,1459,1,0,2,FR,France
+199426,3,990,80,1900,2,0,4,FR,France
+199425,3,5431,3222,7640,9,5,13,FR,France
+199424,3,6288,3723,8853,11,7,15,FR,France
+199423,3,6440,1052,11828,11,2,20,FR,France
+199422,3,845,0,2449,1,0,4,FR,France
+199421,3,2197,395,3999,4,1,7,FR,France
+199420,3,2217,852,3582,4,2,6,FR,France
+199419,3,1483,406,2560,3,1,5,FR,France
+199418,3,3705,1940,5470,6,3,9,FR,France
+199417,3,2288,1064,3512,4,2,6,FR,France
+199416,3,5156,3176,7136,9,6,12,FR,France
+199415,3,6952,4678,9226,12,8,16,FR,France
+199414,3,4671,2784,6558,8,5,11,FR,France
+199413,3,3343,1641,5045,6,3,9,FR,France
+199412,3,4305,2412,6198,7,4,10,FR,France
+199411,3,5399,3327,7471,9,5,13,FR,France
+199410,3,4548,2529,6567,8,4,12,FR,France
+199409,3,5635,3251,8019,10,6,14,FR,France
+199408,3,9539,6652,12426,17,12,22,FR,France
+199407,3,14639,11188,18090,25,19,31,FR,France
+199406,3,17308,13395,21221,30,23,37,FR,France
+199405,3,18489,14290,22688,32,25,39,FR,France
+199404,3,23712,19048,28376,41,33,49,FR,France
+199403,3,29882,24817,34947,52,43,61,FR,France
+199402,3,47402,41415,53389,82,72,92,FR,France
+199401,3,118119,108182,128056,205,188,222,FR,France
+199352,3,233137,218608,247666,406,381,431,FR,France
+199351,3,377472,359792,395152,658,627,689,FR,France
+199350,3,627639,607097,648181,1094,1058,1130,FR,France
+199349,3,898045,873419,922671,1565,1522,1608,FR,France
+199348,3,527582,507752,547412,920,885,955,FR,France
+199347,3,241371,226769,255973,421,396,446,FR,France
+199346,3,76034,68003,84065,133,119,147,FR,France
+199345,3,32289,27022,37556,56,47,65,FR,France
+199344,3,17832,14015,21649,31,24,38,FR,France
+199343,3,15098,11333,18863,26,19,33,FR,France
+199342,3,19187,14893,23481,33,26,40,FR,France
+199341,3,18285,14384,22186,32,25,39,FR,France
+199340,3,13805,10348,17262,24,18,30,FR,France
+199339,3,14783,11173,18393,26,20,32,FR,France
+199338,3,10492,7329,13655,18,12,24,FR,France
+199337,3,7023,4503,9543,12,8,16,FR,France
+199336,3,4361,2445,6277,8,5,11,FR,France
+199335,3,5589,3066,8112,10,6,14,FR,France
+199334,3,2984,1209,4759,5,2,8,FR,France
+199333,3,3217,758,5676,6,2,10,FR,France
+199332,3,3755,1051,6459,7,2,12,FR,France
+199331,3,4163,1768,6558,7,3,11,FR,France
+199330,3,4055,1907,6203,7,3,11,FR,France
+199329,3,3714,1668,5760,6,2,10,FR,France
+199328,3,1774,484,3064,3,1,5,FR,France
+199327,3,2574,918,4230,4,1,7,FR,France
+199326,3,3048,1450,4646,5,2,8,FR,France
+199325,3,8348,5260,11436,15,10,20,FR,France
+199324,3,6624,3747,9501,12,7,17,FR,France
+199323,3,7424,4302,10546,13,8,18,FR,France
+199322,3,3432,1849,5015,6,3,9,FR,France
+199321,3,5942,3670,8214,10,6,14,FR,France
+199320,3,5137,3157,7117,9,6,12,FR,France
+199319,3,4593,2725,6461,8,5,11,FR,France
+199318,3,5027,3075,6979,9,6,12,FR,France
+199317,3,8111,5138,11084,14,9,19,FR,France
+199316,3,24932,19468,30396,43,33,53,FR,France
+199315,3,22181,17147,27215,39,30,48,FR,France
+199314,3,38266,30865,45667,67,54,80,FR,France
+199313,3,62987,54506,71468,110,95,125,FR,France
+199312,3,63493,55956,71030,111,98,124,FR,France
+199311,3,80548,72628,88468,140,126,154,FR,France
+199310,3,127910,117688,138132,223,205,241,FR,France
+199309,3,184150,171378,196922,321,299,343,FR,France
+199308,3,222932,209051,236813,389,365,413,FR,France
+199307,3,248494,234936,262052,433,409,457,FR,France
+199306,3,286939,271830,302048,500,474,526,FR,France
+199305,3,255890,241516,270264,446,421,471,FR,France
+199304,3,193107,181261,204953,337,316,358,FR,France
+199303,3,147854,137256,158452,258,240,276,FR,France
+199302,3,90269,82164,98374,157,143,171,FR,France
+199301,3,75288,67244,83332,131,117,145,FR,France
+199253,3,56622,49107,64137,99,86,112,FR,France
+199252,3,49588,42568,56608,87,75,99,FR,France
+199251,3,41156,35024,47288,72,61,83,FR,France
+199250,3,40100,34699,45501,70,61,79,FR,France
+199249,3,39146,33847,44445,69,60,78,FR,France
+199248,3,32392,27499,37285,57,48,66,FR,France
+199247,3,26276,21797,30755,46,38,54,FR,France
+199246,3,22758,18462,27054,40,32,48,FR,France
+199245,3,22023,17804,26242,39,32,46,FR,France
+199244,3,27619,22945,32293,48,40,56,FR,France
+199243,3,24969,20704,29234,44,37,51,FR,France
+199242,3,29980,25261,34699,52,44,60,FR,France
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