diff --git a/module3/exo2/exercice.ipynb b/module3/exo2/exercice.ipynb
index 0bbbe371b01e359e381e43239412d77bf53fb1fb..3a6f901a852199591b51bfb891f88cd7eda4e700 100644
--- a/module3/exo2/exercice.ipynb
+++ b/module3/exo2/exercice.ipynb
@@ -1,5 +1,921 @@
 {
- "cells": [],
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import pandas as pd\n",
+    "import isoweek"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data_url = 'http://www.sentiweb.fr/datasets/incidence-PAY-7.csv'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "On extrait les données de varicelles depuis le site du [Réseau sentinelles](http://www.sentiweb.fr/france/fr/?page=table&maladie=7).\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>indicator</th>\n",
+       "      <th>inc</th>\n",
+       "      <th>inc_low</th>\n",
+       "      <th>inc_up</th>\n",
+       "      <th>inc100</th>\n",
+       "      <th>inc100_low</th>\n",
+       "      <th>inc100_up</th>\n",
+       "      <th>geo_insee</th>\n",
+       "      <th>geo_name</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>202136</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4910</td>\n",
+       "      <td>2188</td>\n",
+       "      <td>7632</td>\n",
+       "      <td>7</td>\n",
+       "      <td>3</td>\n",
+       "      <td>11</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>202135</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2592</td>\n",
+       "      <td>1116</td>\n",
+       "      <td>4068</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2</td>\n",
+       "      <td>6</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>202134</td>\n",
+       "      <td>7</td>\n",
+       "      <td>1429</td>\n",
+       "      <td>378</td>\n",
+       "      <td>2480</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>202133</td>\n",
+       "      <td>7</td>\n",
+       "      <td>3829</td>\n",
+       "      <td>1830</td>\n",
+       "      <td>5828</td>\n",
+       "      <td>6</td>\n",
+       "      <td>3</td>\n",
+       "      <td>9</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>202132</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4108</td>\n",
+       "      <td>1895</td>\n",
+       "      <td>6321</td>\n",
+       "      <td>6</td>\n",
+       "      <td>3</td>\n",
+       "      <td>9</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",
+       "0  202136          7  4910     2188    7632       7           3         11   \n",
+       "1  202135          7  2592     1116    4068       4           2          6   \n",
+       "2  202134          7  1429      378    2480       2           0          4   \n",
+       "3  202133          7  3829     1830    5828       6           3          9   \n",
+       "4  202132          7  4108     1895    6321       6           3          9   \n",
+       "\n",
+       "  geo_insee geo_name  \n",
+       "0        FR   France  \n",
+       "1        FR   France  \n",
+       "2        FR   France  \n",
+       "3        FR   France  \n",
+       "4        FR   France  "
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data = pd.read_csv(data_url, encoding = 'iso-8859-1', skiprows=1)\n",
+    "raw_data.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>week</th>\n",
+       "      <th>indicator</th>\n",
+       "      <th>inc</th>\n",
+       "      <th>inc_low</th>\n",
+       "      <th>inc_up</th>\n",
+       "      <th>inc100</th>\n",
+       "      <th>inc100_low</th>\n",
+       "      <th>inc100_up</th>\n",
+       "      <th>geo_insee</th>\n",
+       "      <th>geo_name</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "Empty DataFrame\n",
+       "Columns: [week, indicator, inc, inc_low, inc_up, inc100, inc100_low, inc100_up, geo_insee, geo_name]\n",
+       "Index: []"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data[raw_data.isnull().any(axis=1)]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Il n'y a pas de valeurs manquantes a priori"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def convert_week(year_and_week_int):\n",
+    "    year_and_week_str = str(year_and_week_int)\n",
+    "    year = int(year_and_week_str[:4])\n",
+    "    week = int(year_and_week_str[4:])\n",
+    "    w = isoweek.Week(year, week)\n",
+    "    return pd.Period(w.day(0), 'W')\n",
+    "\n",
+    "raw_data['period'] = [convert_week(yw) for yw in raw_data['week']]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "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",
+       "      <th>period</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>202136</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4910</td>\n",
+       "      <td>2188</td>\n",
+       "      <td>7632</td>\n",
+       "      <td>7</td>\n",
+       "      <td>3</td>\n",
+       "      <td>11</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "      <td>2021-09-06/2021-09-12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>202135</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2592</td>\n",
+       "      <td>1116</td>\n",
+       "      <td>4068</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2</td>\n",
+       "      <td>6</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "      <td>2021-08-30/2021-09-05</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>202134</td>\n",
+       "      <td>7</td>\n",
+       "      <td>1429</td>\n",
+       "      <td>378</td>\n",
+       "      <td>2480</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "      <td>2021-08-23/2021-08-29</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>202133</td>\n",
+       "      <td>7</td>\n",
+       "      <td>3829</td>\n",
+       "      <td>1830</td>\n",
+       "      <td>5828</td>\n",
+       "      <td>6</td>\n",
+       "      <td>3</td>\n",
+       "      <td>9</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "      <td>2021-08-16/2021-08-22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>202132</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4108</td>\n",
+       "      <td>1895</td>\n",
+       "      <td>6321</td>\n",
+       "      <td>6</td>\n",
+       "      <td>3</td>\n",
+       "      <td>9</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "      <td>2021-08-09/2021-08-15</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     week  indicator   inc  inc_low  inc_up  inc100  inc100_low  inc100_up  \\\n",
+       "0  202136          7  4910     2188    7632       7           3         11   \n",
+       "1  202135          7  2592     1116    4068       4           2          6   \n",
+       "2  202134          7  1429      378    2480       2           0          4   \n",
+       "3  202133          7  3829     1830    5828       6           3          9   \n",
+       "4  202132          7  4108     1895    6321       6           3          9   \n",
+       "\n",
+       "  geo_insee geo_name                period  \n",
+       "0        FR   France 2021-09-06/2021-09-12  \n",
+       "1        FR   France 2021-08-30/2021-09-05  \n",
+       "2        FR   France 2021-08-23/2021-08-29  \n",
+       "3        FR   France 2021-08-16/2021-08-22  \n",
+       "4        FR   France 2021-08-09/2021-08-15  "
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "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",
+       "    <tr>\n",
+       "      <th>period</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1990-12-03/1990-12-09</th>\n",
+       "      <td>199049</td>\n",
+       "      <td>7</td>\n",
+       "      <td>1143</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2610</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>5</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1990-12-10/1990-12-16</th>\n",
+       "      <td>199050</td>\n",
+       "      <td>7</td>\n",
+       "      <td>11079</td>\n",
+       "      <td>6660</td>\n",
+       "      <td>15498</td>\n",
+       "      <td>20</td>\n",
+       "      <td>12</td>\n",
+       "      <td>28</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1990-12-17/1990-12-23</th>\n",
+       "      <td>199051</td>\n",
+       "      <td>7</td>\n",
+       "      <td>19080</td>\n",
+       "      <td>13807</td>\n",
+       "      <td>24353</td>\n",
+       "      <td>34</td>\n",
+       "      <td>25</td>\n",
+       "      <td>43</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1990-12-24/1990-12-30</th>\n",
+       "      <td>199052</td>\n",
+       "      <td>7</td>\n",
+       "      <td>19375</td>\n",
+       "      <td>13295</td>\n",
+       "      <td>25455</td>\n",
+       "      <td>34</td>\n",
+       "      <td>23</td>\n",
+       "      <td>45</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1990-12-31/1991-01-06</th>\n",
+       "      <td>199101</td>\n",
+       "      <td>7</td>\n",
+       "      <td>15565</td>\n",
+       "      <td>10271</td>\n",
+       "      <td>20859</td>\n",
+       "      <td>27</td>\n",
+       "      <td>18</td>\n",
+       "      <td>36</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                         week  indicator    inc  inc_low  inc_up  inc100  \\\n",
+       "period                                                                     \n",
+       "1990-12-03/1990-12-09  199049          7   1143        0    2610       2   \n",
+       "1990-12-10/1990-12-16  199050          7  11079     6660   15498      20   \n",
+       "1990-12-17/1990-12-23  199051          7  19080    13807   24353      34   \n",
+       "1990-12-24/1990-12-30  199052          7  19375    13295   25455      34   \n",
+       "1990-12-31/1991-01-06  199101          7  15565    10271   20859      27   \n",
+       "\n",
+       "                       inc100_low  inc100_up geo_insee geo_name  \n",
+       "period                                                           \n",
+       "1990-12-03/1990-12-09           0          5        FR   France  \n",
+       "1990-12-10/1990-12-16          12         28        FR   France  \n",
+       "1990-12-17/1990-12-23          25         43        FR   France  \n",
+       "1990-12-24/1990-12-30          23         45        FR   France  \n",
+       "1990-12-31/1991-01-06          18         36        FR   France  "
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sorted_data = raw_data.set_index('period').sort_index()\n",
+    "sorted_data.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "periods = sorted_data.index\n",
+    "for p1, p2 in zip(periods[:-1], periods[1:]):\n",
+    "    delta = p2.to_timestamp() - p1.end_time\n",
+    "    if delta > pd.Timedelta('1s'):\n",
+    "        print(p1, p2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa1fbb54518>"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x504 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize = [10,7])\n",
+    "sorted_data['inc'].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa1fb855668>"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x504 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize = [10,7])\n",
+    "sorted_data['inc'][-200:].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "first_september_week = [pd.Period(pd.Timestamp(y, 9, 1), 'W')\n",
+    "                     for y in range(1990,\n",
+    "                                    sorted_data.index[-1].year)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1990-08-27/1990-09-02 38\n"
+     ]
+    }
+   ],
+   "source": [
+    "year = []\n",
+    "yearly_incidence = []\n",
+    "for week1, week2 in zip(first_september_week[:-1],\n",
+    "                        first_september_week[1:]):\n",
+    "    one_year = sorted_data['inc'][week1:week2-1]\n",
+    "    \n",
+    "    if ( abs(len(one_year)-52) > 2):\n",
+    "        print(week1,len(one_year)) \n",
+    "    else:\n",
+    "        yearly_incidence.append(one_year.sum())\n",
+    "        year.append(week2.year)\n",
+    "yearly_incidence = pd.Series(data=yearly_incidence, index=year)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "L'année 90 n'est pas complète puisque les données ne correspondent qu'à 4 semaines en décembre. L'incidence de cette année n'est pas prise en compte "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "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",
+       "    <tr>\n",
+       "      <th>period</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1990-12-03/1990-12-09</th>\n",
+       "      <td>199049</td>\n",
+       "      <td>7</td>\n",
+       "      <td>1143</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2610</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>5</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1990-12-10/1990-12-16</th>\n",
+       "      <td>199050</td>\n",
+       "      <td>7</td>\n",
+       "      <td>11079</td>\n",
+       "      <td>6660</td>\n",
+       "      <td>15498</td>\n",
+       "      <td>20</td>\n",
+       "      <td>12</td>\n",
+       "      <td>28</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1990-12-17/1990-12-23</th>\n",
+       "      <td>199051</td>\n",
+       "      <td>7</td>\n",
+       "      <td>19080</td>\n",
+       "      <td>13807</td>\n",
+       "      <td>24353</td>\n",
+       "      <td>34</td>\n",
+       "      <td>25</td>\n",
+       "      <td>43</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1990-12-24/1990-12-30</th>\n",
+       "      <td>199052</td>\n",
+       "      <td>7</td>\n",
+       "      <td>19375</td>\n",
+       "      <td>13295</td>\n",
+       "      <td>25455</td>\n",
+       "      <td>34</td>\n",
+       "      <td>23</td>\n",
+       "      <td>45</td>\n",
+       "      <td>FR</td>\n",
+       "      <td>France</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                         week  indicator    inc  inc_low  inc_up  inc100  \\\n",
+       "period                                                                     \n",
+       "1990-12-03/1990-12-09  199049          7   1143        0    2610       2   \n",
+       "1990-12-10/1990-12-16  199050          7  11079     6660   15498      20   \n",
+       "1990-12-17/1990-12-23  199051          7  19080    13807   24353      34   \n",
+       "1990-12-24/1990-12-30  199052          7  19375    13295   25455      34   \n",
+       "\n",
+       "                       inc100_low  inc100_up geo_insee geo_name  \n",
+       "period                                                           \n",
+       "1990-12-03/1990-12-09           0          5        FR   France  \n",
+       "1990-12-10/1990-12-16          12         28        FR   France  \n",
+       "1990-12-17/1990-12-23          25         43        FR   France  \n",
+       "1990-12-24/1990-12-30          23         45        FR   France  "
+      ]
+     },
+     "execution_count": 40,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sorted_data[sorted_data.week<199100]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa1f2db22b0>"
+      ]
+     },
+     "execution_count": 45,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 864x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize = [12,5])\n",
+    "yearly_incidence.plot(style='*')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2020    221186\n",
+       "2002    516689\n",
+       "2018    542312\n",
+       "2017    551041\n",
+       "1996    564901\n",
+       "2019    584066\n",
+       "2015    604382\n",
+       "2000    617597\n",
+       "2001    619041\n",
+       "2012    624573\n",
+       "2005    628464\n",
+       "2006    632833\n",
+       "2011    642368\n",
+       "1993    643387\n",
+       "1995    652478\n",
+       "1994    661409\n",
+       "1998    677775\n",
+       "1997    683434\n",
+       "2014    685769\n",
+       "2013    698332\n",
+       "2007    717352\n",
+       "2008    749478\n",
+       "1999    756456\n",
+       "2003    758363\n",
+       "2004    777388\n",
+       "2016    782114\n",
+       "2010    829911\n",
+       "1992    832939\n",
+       "2009    842373\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 46,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "yearly_incidence.sort_values()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa1f3421080>"
+      ]
+     },
+     "execution_count": 47,
+     "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)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
  "metadata": {
   "kernelspec": {
    "display_name": "Python 3",
@@ -16,10 +932,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 2
 }
-
diff --git a/module3/exo3/Wheat.csv b/module3/exo3/Wheat.csv
new file mode 100644
index 0000000000000000000000000000000000000000..dd711ba97601b5737df9331d67d9b6419d1aceed
--- /dev/null
+++ b/module3/exo3/Wheat.csv
@@ -0,0 +1,54 @@
+Year,Wheat,Wages
+1565,41.0,5.0
+1570,45.0,5.05
+1575,42.0,5.08
+1580,49.0,5.12
+1585,41.5,5.15
+1590,47.0,5.25
+1595,64.0,5.54
+1600,27.0,5.61
+1605,33.0,5.69
+1610,32.0,5.78
+1615,33.0,5.94
+1620,35.0,6.01
+1625,33.0,6.12
+1630,45.0,6.22
+1635,33.0,6.3
+1640,39.0,6.37
+1645,53.0,6.45
+1650,42.0,6.5
+1655,40.5,6.6
+1660,46.5,6.75
+1665,32.0,6.8
+1670,37.0,6.9
+1675,43.0,7.0
+1680,35.0,7.3
+1685,27.0,7.6
+1690,40.0,8.0
+1695,50.0,8.5
+1700,30.0,9.0
+1705,32.0,10.0
+1710,44.0,11.0
+1715,33.0,11.75
+1720,29.0,12.5
+1725,39.0,13.0
+1730,26.0,13.3
+1735,32.0,13.6
+1740,27.0,14.0
+1745,27.5,14.5
+1750,31.0,15.0
+1755,35.5,15.7
+1760,31.0,16.5
+1765,43.0,17.6
+1770,47.0,18.5
+1775,44.0,19.5
+1780,46.0,21.0
+1785,42.0,23.0
+1790,47.5,25.5
+1795,76.0,27.5
+1800,79.0,28.5
+1805,81.0,29.5
+1810,99.0,30.0
+1815,78.0,
+1820,54.0,
+1821,54.0,
diff --git a/module3/exo3/exercice.ipynb b/module3/exo3/exercice.ipynb
index 0bbbe371b01e359e381e43239412d77bf53fb1fb..f7f0b6795436340d7f845b05305ca228fe6b29a7 100644
--- a/module3/exo3/exercice.ipynb
+++ b/module3/exo3/exercice.ipynb
@@ -1,5 +1,698 @@
 {
- "cells": [],
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Le pouvoir d'achat des ouvrier anglais"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import pandas as pd\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "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>Unnamed: 0</th>\n",
+       "      <th>Year</th>\n",
+       "      <th>Wheat</th>\n",
+       "      <th>Wages</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1565</td>\n",
+       "      <td>41.0</td>\n",
+       "      <td>5.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>1570</td>\n",
+       "      <td>45.0</td>\n",
+       "      <td>5.05</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>1575</td>\n",
+       "      <td>42.0</td>\n",
+       "      <td>5.08</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>1580</td>\n",
+       "      <td>49.0</td>\n",
+       "      <td>5.12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>1585</td>\n",
+       "      <td>41.5</td>\n",
+       "      <td>5.15</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Unnamed: 0  Year  Wheat  Wages\n",
+       "0           1  1565   41.0   5.00\n",
+       "1           2  1570   45.0   5.05\n",
+       "2           3  1575   42.0   5.08\n",
+       "3           4  1580   49.0   5.12\n",
+       "4           5  1585   41.5   5.15"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data = pd.read_csv('https://raw.githubusercontent.com/vincentarelbundock/Rdatasets/master/csv/HistData/Wheat.csv')\n",
+    "data.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "La colonne _Unnamed:0_ ne contient pas d'information intéressante, on la supprime et on sauvegarde les données en local."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "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>Year</th>\n",
+       "      <th>Wheat</th>\n",
+       "      <th>Wages</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1565</td>\n",
+       "      <td>41.0</td>\n",
+       "      <td>5.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1570</td>\n",
+       "      <td>45.0</td>\n",
+       "      <td>5.05</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1575</td>\n",
+       "      <td>42.0</td>\n",
+       "      <td>5.08</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1580</td>\n",
+       "      <td>49.0</td>\n",
+       "      <td>5.12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1585</td>\n",
+       "      <td>41.5</td>\n",
+       "      <td>5.15</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Year  Wheat  Wages\n",
+       "0  1565   41.0   5.00\n",
+       "1  1570   45.0   5.05\n",
+       "2  1575   42.0   5.08\n",
+       "3  1580   49.0   5.12\n",
+       "4  1585   41.5   5.15"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data = data[['Year', \"Wheat\", \"Wages\"]]\n",
+    "data.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data.to_csv('Wheat.csv', index = False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "## Inspection rapide des données"
+   ]
+  },
+  {
+   "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>Year</th>\n",
+       "      <th>Wheat</th>\n",
+       "      <th>Wages</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>53.000000</td>\n",
+       "      <td>53.000000</td>\n",
+       "      <td>50.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>1694.924528</td>\n",
+       "      <td>43.264151</td>\n",
+       "      <td>11.581600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>77.089571</td>\n",
+       "      <td>15.410287</td>\n",
+       "      <td>7.336287</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>1565.000000</td>\n",
+       "      <td>26.000000</td>\n",
+       "      <td>5.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>1630.000000</td>\n",
+       "      <td>33.000000</td>\n",
+       "      <td>6.145000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>1695.000000</td>\n",
+       "      <td>41.000000</td>\n",
+       "      <td>7.800000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>1760.000000</td>\n",
+       "      <td>47.000000</td>\n",
+       "      <td>14.875000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>1821.000000</td>\n",
+       "      <td>99.000000</td>\n",
+       "      <td>30.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              Year      Wheat      Wages\n",
+       "count    53.000000  53.000000  50.000000\n",
+       "mean   1694.924528  43.264151  11.581600\n",
+       "std      77.089571  15.410287   7.336287\n",
+       "min    1565.000000  26.000000   5.000000\n",
+       "25%    1630.000000  33.000000   6.145000\n",
+       "50%    1695.000000  41.000000   7.800000\n",
+       "75%    1760.000000  47.000000  14.875000\n",
+       "max    1821.000000  99.000000  30.000000"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.describe()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Year</th>\n",
+       "      <th>Wheat</th>\n",
+       "      <th>Wages</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>1815</td>\n",
+       "      <td>78.0</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>1820</td>\n",
+       "      <td>54.0</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>1821</td>\n",
+       "      <td>54.0</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    Year  Wheat  Wages\n",
+       "50  1815   78.0    NaN\n",
+       "51  1820   54.0    NaN\n",
+       "52  1821   54.0    NaN"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data[data.isnull().any(axis=1)] "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "La colonne _Wages_ contient 3 valeurs manquantes pour les 3 dernières années observées. Par souci de simpicité on ne itent pas compte de ces données."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Nombre d'observations initiales: 53 / Nombre d'observations après avoir enlevé les valeurs manquates: 50\n"
+     ]
+    }
+   ],
+   "source": [
+    "data_clean = data[data.Wages.isnull()==False]\n",
+    "print(\"Nombre d'observations initiales: {} / Nombre d'observations après avoir enlevé les valeurs manquates: {}\".format(len(data),len(data_clean)))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Visualisation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "year = data_clean.sort_values('Year').Year\n",
+    "wages = data_clean.sort_values('Year').Wages\n",
+    "wheat = data_clean.sort_values('Year').Wheat"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 1 Playfair "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1224x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=[17,6])\n",
+    "plt.bar(year, wheat, width = 4, color = 'black', alpha = 0.7)\n",
+    "plt.plot(year, wages, color ='red')\n",
+    "plt.fill_between(year, wages, color = 'blue')\n",
+    "plt.grid()\n",
+    "plt.xlabel('5 years each division', fontsize = 16)\n",
+    "plt.xticks(year[1::2])\n",
+    "plt.text(year[6], wages[6]+2, 'Weekly wages of a Good Mechanio',fontsize = 12,style='oblique',\n",
+    "        bbox={'facecolor': 'white', 'alpha' : 0.4, 'pad': 8} )\n",
+    "plt.text(1580, 70\n",
+    "         ,'Chart showing at one view\\n the price of the quarter of wheat,\\n and wages of labour by the week\\n from the year 1561 to 1821\\n William Playfair',\n",
+    "        fontsize = 12,style='italic',\n",
+    "        bbox={'facecolor': 'white', 'pad': 10})\n",
+    "plt.tick_params(axis='y', which='both', labelleft=False, labelright=True)\n",
+    "plt.ylabel(\"Price of a quarter of wheat in shilling\", fontsize = 10, labelpad=-1000 )\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 2 Modification des ordonnées"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1224x432 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig,ax1 =plt.subplots()\n",
+    "fig.set_size_inches(17,6)\n",
+    "\n",
+    "ax1.bar(year, wheat, width = 4, color = 'black', alpha = 0.7)\n",
+    "ax1.set_ylim(0,110)\n",
+    "\n",
+    "plt.ylabel(\"Price of a quarter of wheat in shilling\")\n",
+    "\n",
+    "\n",
+    "\n",
+    "ax2 = ax1.twinx()\n",
+    "ax2.plot(year, wages, color ='red')\n",
+    "ax2.fill_between(year, wages, color = 'blue', alpha = 0.5)\n",
+    "ax2.set_ylim(0,35)\n",
+    "\n",
+    "ax1.set_xticks(year[1::2])\n",
+    "ax1.set_xlabel('5 years each division', fontsize = 16)\n",
+    "plt.grid()\n",
+    "\n",
+    "plt.ylabel('Weekly wages of a Good Mechanio in shilling', color='r')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Une autre possibilité de représentation est de voir l'évolution de la proportion du prix du blé par rapport aux salaires en divisant le vecteur _wheat_ et le vecteur _wages_ par la somme de ceux-ci."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "wheat_prop = wheat/(wheat+wages)\n",
+    "wages_prop = wages/(wheat+wages)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "On peut facilement vérifier que _wheat\\_prop_ + _wages\\_prop_ nous donne un vecteur de 1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1224x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots()\n",
+    "fig.set_size_inches(17,6)\n",
+    "\n",
+    "width = 4\n",
+    "p1 = ax.bar(year, wheat_prop, width, color  ='black', label = \"Wheat Price\", alpha = 0.7\n",
+    "           )\n",
+    "p2 = ax.bar(year, wages_prop, width,color=\"blue\",\n",
+    "            bottom=wheat_prop, label = \"Weekly Wages\")\n",
+    "ax.legend(fontsize = 12)\n",
+    "ax.set_xticks(year[1::2])\n",
+    "ax.set_xlabel('5 years each division', fontsize = 16)\n",
+    "\n",
+    "ax.set_title('Proportional representation of the price of wheat and the weekly wages', fontsize = 15)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 3 Représentation du pouvoir d'achat"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "wheat_quantity_per_wages = wages/wheat"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 864x504 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=[12,7])\n",
+    "plt.plot(year , wheat_quantity_per_wages)\n",
+    "plt.grid()\n",
+    "plt.xticks(year[::4])\n",
+    "plt.xlabel('5 years each division', fontsize = 16)\n",
+    "plt.ylabel(\"Volume of wheat which can be bought from wages\", fontsize = 12)\n",
+    "plt.title(\"Pouvoir d'achat d'un ouvrier au cours du temps\" , fontsize = 20)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "On peut remarquer que si le pouvoir d'achat augmente depuis le 16e siècle, il diminue fortement vers la fin du 18e"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5,1,'Weekly salary depending on wheat price')"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x432 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=[8,6])\n",
+    "plt.scatter(wheat, wages, c=year)\n",
+    "plt.ylabel('Weekly Wages', fontsize = 16)\n",
+    "plt.xlabel(\"Wheat Price\", fontsize = 16)\n",
+    "plt.colorbar()\n",
+    "plt.title('Weekly salary depending on wheat price', fontsize=20)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "La représentation des données qui me paraît être la plus claire si on souhaite montrer que le pouvoir d'achat des ouvriers a augmenté est l'avant dernière représentation (le pouvoir d'achat). Elle est plus explicite et en représentant la quantité de blé que peut acheter un ouvrier au cours du temps, on voit très bien l'augmentation du pouvoir d'achat puis sa diminution, ce qui n'est pas si clair dans les autres représentations. Les autres représentations permettent de bien voir l'évolution du salaire mais moins celle du blé par rapport à celui ci.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
  "metadata": {
   "kernelspec": {
    "display_name": "Python 3",
@@ -16,10 +709,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 2
 }
-