diff --git a/module3/exo3/Wheat.csv b/module3/exo3/Wheat.csv
new file mode 100644
index 0000000000000000000000000000000000000000..b3eb3be85fe158a478acc24e0100ea2d8f5e722b
--- /dev/null
+++ b/module3/exo3/Wheat.csv
@@ -0,0 +1,54 @@
+rownames,Year,Wheat,Wages
+1,1565,41,5
+2,1570,45,5.05
+3,1575,42,5.08
+4,1580,49,5.12
+5,1585,41.5,5.15
+6,1590,47,5.25
+7,1595,64,5.54
+8,1600,27,5.61
+9,1605,33,5.69
+10,1610,32,5.78
+11,1615,33,5.94
+12,1620,35,6.01
+13,1625,33,6.12
+14,1630,45,6.22
+15,1635,33,6.3
+16,1640,39,6.37
+17,1645,53,6.45
+18,1650,42,6.5
+19,1655,40.5,6.6
+20,1660,46.5,6.75
+21,1665,32,6.8
+22,1670,37,6.9
+23,1675,43,7
+24,1680,35,7.3
+25,1685,27,7.6
+26,1690,40,8
+27,1695,50,8.5
+28,1700,30,9
+29,1705,32,10
+30,1710,44,11
+31,1715,33,11.75
+32,1720,29,12.5
+33,1725,39,13
+34,1730,26,13.3
+35,1735,32,13.6
+36,1740,27,14
+37,1745,27.5,14.5
+38,1750,31,15
+39,1755,35.5,15.7
+40,1760,31,16.5
+41,1765,43,17.6
+42,1770,47,18.5
+43,1775,44,19.5
+44,1780,46,21
+45,1785,42,23
+46,1790,47.5,25.5
+47,1795,76,27.5
+48,1800,79,28.5
+49,1805,81,29.5
+50,1810,99,30
+51,1815,78,
+52,1820,54,
+53,1821,54,
diff --git a/module3/exo3/exercice_fr.ipynb b/module3/exo3/exercice_fr.ipynb
index 0bbbe371b01e359e381e43239412d77bf53fb1fb..3b72649cb304bc856db1d815f51bb83c5acb6e67 100644
--- a/module3/exo3/exercice_fr.ipynb
+++ b/module3/exo3/exercice_fr.ipynb
@@ -1,5 +1,1461 @@
 {
- "cells": [],
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Sujet 2 : le pouvoir d'achat des ouvriers anglais du XVIe au XIXe siècle\n",
+    "\n",
+    "William Playfair était un des pionniers de la présentation graphique des données. Il est notamment considéré comme l'inventeur de l'histogramme. [Un de ses graphes célèbres](https://fr.wikipedia.org/wiki/William_Playfair#/media/File:Chart_Showing_at_One_View_the_Price_of_the_Quarter_of_Wheat,_and_Wages_of_Labour_by_the_Week,_from_1565_to_1821.png), tiré de son livre *A Letter on Our Agricultural Distresses, Their Causes and Remedies*, montre l'évolution du prix du blé et du salaire moyen entre 1565 et 1821. Playfair n'a pas publié les données numériques brutes qu'il a utilisées, car à son époque la réplicabilité n'était pas encore considérée comme essentielle. Des valeurs obtenues par numérisation du graphe sont aujourd'hui téléchargeables, [la version en format CSV](https://raw.githubusercontent.com/vincentarelbundock/Rdatasets/master/csv/HistData/Wheat.csv) étant la plus pratique."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Nous commeçons par importer les librairies qui nous seront utiles par la suite."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import pandas as pd\n",
+    "import os\n",
+    "import urllib.request"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Téléchargement et traitement des données\n",
+    "\n",
+    "Si nous ne disposons pas déjà du fichier csv, nous le téléchargeons à l'aide de l'URL. Si nous l'avons déjà, nous utilisons le fichier local."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Le jeu de données comporte 53 lignes.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>rownames</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",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>6</td>\n",
+       "      <td>1590</td>\n",
+       "      <td>47.0</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>7</td>\n",
+       "      <td>1595</td>\n",
+       "      <td>64.0</td>\n",
+       "      <td>5.54</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>8</td>\n",
+       "      <td>1600</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>5.61</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>9</td>\n",
+       "      <td>1605</td>\n",
+       "      <td>33.0</td>\n",
+       "      <td>5.69</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>10</td>\n",
+       "      <td>1610</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>5.78</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>11</td>\n",
+       "      <td>1615</td>\n",
+       "      <td>33.0</td>\n",
+       "      <td>5.94</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>12</td>\n",
+       "      <td>1620</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>6.01</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>13</td>\n",
+       "      <td>1625</td>\n",
+       "      <td>33.0</td>\n",
+       "      <td>6.12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>14</td>\n",
+       "      <td>1630</td>\n",
+       "      <td>45.0</td>\n",
+       "      <td>6.22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>15</td>\n",
+       "      <td>1635</td>\n",
+       "      <td>33.0</td>\n",
+       "      <td>6.30</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>16</td>\n",
+       "      <td>1640</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>6.37</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>17</td>\n",
+       "      <td>1645</td>\n",
+       "      <td>53.0</td>\n",
+       "      <td>6.45</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>18</td>\n",
+       "      <td>1650</td>\n",
+       "      <td>42.0</td>\n",
+       "      <td>6.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>19</td>\n",
+       "      <td>1655</td>\n",
+       "      <td>40.5</td>\n",
+       "      <td>6.60</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>20</td>\n",
+       "      <td>1660</td>\n",
+       "      <td>46.5</td>\n",
+       "      <td>6.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>21</td>\n",
+       "      <td>1665</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>6.80</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>22</td>\n",
+       "      <td>1670</td>\n",
+       "      <td>37.0</td>\n",
+       "      <td>6.90</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>23</td>\n",
+       "      <td>1675</td>\n",
+       "      <td>43.0</td>\n",
+       "      <td>7.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>24</td>\n",
+       "      <td>1680</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>7.30</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>25</td>\n",
+       "      <td>1685</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>7.60</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>26</td>\n",
+       "      <td>1690</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>8.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>27</td>\n",
+       "      <td>1695</td>\n",
+       "      <td>50.0</td>\n",
+       "      <td>8.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>28</td>\n",
+       "      <td>1700</td>\n",
+       "      <td>30.0</td>\n",
+       "      <td>9.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>29</td>\n",
+       "      <td>1705</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>10.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>30</td>\n",
+       "      <td>1710</td>\n",
+       "      <td>44.0</td>\n",
+       "      <td>11.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>31</td>\n",
+       "      <td>1715</td>\n",
+       "      <td>33.0</td>\n",
+       "      <td>11.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>32</td>\n",
+       "      <td>1720</td>\n",
+       "      <td>29.0</td>\n",
+       "      <td>12.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>33</td>\n",
+       "      <td>1725</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>13.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>34</td>\n",
+       "      <td>1730</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>13.30</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>35</td>\n",
+       "      <td>1735</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>13.60</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>36</td>\n",
+       "      <td>1740</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>14.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>37</td>\n",
+       "      <td>1745</td>\n",
+       "      <td>27.5</td>\n",
+       "      <td>14.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>38</td>\n",
+       "      <td>1750</td>\n",
+       "      <td>31.0</td>\n",
+       "      <td>15.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>39</td>\n",
+       "      <td>1755</td>\n",
+       "      <td>35.5</td>\n",
+       "      <td>15.70</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>40</td>\n",
+       "      <td>1760</td>\n",
+       "      <td>31.0</td>\n",
+       "      <td>16.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>41</td>\n",
+       "      <td>1765</td>\n",
+       "      <td>43.0</td>\n",
+       "      <td>17.60</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>42</td>\n",
+       "      <td>1770</td>\n",
+       "      <td>47.0</td>\n",
+       "      <td>18.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>43</td>\n",
+       "      <td>1775</td>\n",
+       "      <td>44.0</td>\n",
+       "      <td>19.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>44</td>\n",
+       "      <td>1780</td>\n",
+       "      <td>46.0</td>\n",
+       "      <td>21.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>45</td>\n",
+       "      <td>1785</td>\n",
+       "      <td>42.0</td>\n",
+       "      <td>23.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>46</td>\n",
+       "      <td>1790</td>\n",
+       "      <td>47.5</td>\n",
+       "      <td>25.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>47</td>\n",
+       "      <td>1795</td>\n",
+       "      <td>76.0</td>\n",
+       "      <td>27.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>48</td>\n",
+       "      <td>1800</td>\n",
+       "      <td>79.0</td>\n",
+       "      <td>28.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>49</td>\n",
+       "      <td>1805</td>\n",
+       "      <td>81.0</td>\n",
+       "      <td>29.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>50</td>\n",
+       "      <td>1810</td>\n",
+       "      <td>99.0</td>\n",
+       "      <td>30.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>51</td>\n",
+       "      <td>1815</td>\n",
+       "      <td>78.0</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>52</td>\n",
+       "      <td>1820</td>\n",
+       "      <td>54.0</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>53</td>\n",
+       "      <td>1821</td>\n",
+       "      <td>54.0</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    rownames  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\n",
+       "5          6  1590   47.0   5.25\n",
+       "6          7  1595   64.0   5.54\n",
+       "7          8  1600   27.0   5.61\n",
+       "8          9  1605   33.0   5.69\n",
+       "9         10  1610   32.0   5.78\n",
+       "10        11  1615   33.0   5.94\n",
+       "11        12  1620   35.0   6.01\n",
+       "12        13  1625   33.0   6.12\n",
+       "13        14  1630   45.0   6.22\n",
+       "14        15  1635   33.0   6.30\n",
+       "15        16  1640   39.0   6.37\n",
+       "16        17  1645   53.0   6.45\n",
+       "17        18  1650   42.0   6.50\n",
+       "18        19  1655   40.5   6.60\n",
+       "19        20  1660   46.5   6.75\n",
+       "20        21  1665   32.0   6.80\n",
+       "21        22  1670   37.0   6.90\n",
+       "22        23  1675   43.0   7.00\n",
+       "23        24  1680   35.0   7.30\n",
+       "24        25  1685   27.0   7.60\n",
+       "25        26  1690   40.0   8.00\n",
+       "26        27  1695   50.0   8.50\n",
+       "27        28  1700   30.0   9.00\n",
+       "28        29  1705   32.0  10.00\n",
+       "29        30  1710   44.0  11.00\n",
+       "30        31  1715   33.0  11.75\n",
+       "31        32  1720   29.0  12.50\n",
+       "32        33  1725   39.0  13.00\n",
+       "33        34  1730   26.0  13.30\n",
+       "34        35  1735   32.0  13.60\n",
+       "35        36  1740   27.0  14.00\n",
+       "36        37  1745   27.5  14.50\n",
+       "37        38  1750   31.0  15.00\n",
+       "38        39  1755   35.5  15.70\n",
+       "39        40  1760   31.0  16.50\n",
+       "40        41  1765   43.0  17.60\n",
+       "41        42  1770   47.0  18.50\n",
+       "42        43  1775   44.0  19.50\n",
+       "43        44  1780   46.0  21.00\n",
+       "44        45  1785   42.0  23.00\n",
+       "45        46  1790   47.5  25.50\n",
+       "46        47  1795   76.0  27.50\n",
+       "47        48  1800   79.0  28.50\n",
+       "48        49  1805   81.0  29.50\n",
+       "49        50  1810   99.0  30.00\n",
+       "50        51  1815   78.0    NaN\n",
+       "51        52  1820   54.0    NaN\n",
+       "52        53  1821   54.0    NaN"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_url = \"https://raw.githubusercontent.com/vincentarelbundock/Rdatasets/master/csv/HistData/Wheat.csv\"\n",
+    "data_file = \"Wheat.csv\"\n",
+    "\n",
+    "if not os.path.exists(data_file):\n",
+    "    urllib.request.urlretrieve(data_url, data_file)\n",
+    "\n",
+    "raw_data = pd.read_csv(data_file)\n",
+    "print(f\"Le jeu de données comporte {len(raw_data)} lignes.\")\n",
+    "raw_data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Nous regardons si des données sont manquantes dans le jeu de données (ce que l'on voit directement dans la sortie de la cellule ci-dessus...)."
+   ]
+  },
+  {
+   "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>rownames</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>51</td>\n",
+       "      <td>1815</td>\n",
+       "      <td>78.0</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>52</td>\n",
+       "      <td>1820</td>\n",
+       "      <td>54.0</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>53</td>\n",
+       "      <td>1821</td>\n",
+       "      <td>54.0</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    rownames  Year  Wheat  Wages\n",
+       "50        51  1815   78.0    NaN\n",
+       "51        52  1820   54.0    NaN\n",
+       "52        53  1821   54.0    NaN"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_data[raw_data.isnull().any(axis=1)]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Les \"wages\" sont manquants pour trois années (1815, 1820 et 1821). Nous supprimons donc les trois lignes correspondantes."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Le jeu de données comporte 50 lignes.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>rownames</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",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>6</td>\n",
+       "      <td>1590</td>\n",
+       "      <td>47.0</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>7</td>\n",
+       "      <td>1595</td>\n",
+       "      <td>64.0</td>\n",
+       "      <td>5.54</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>8</td>\n",
+       "      <td>1600</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>5.61</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>9</td>\n",
+       "      <td>1605</td>\n",
+       "      <td>33.0</td>\n",
+       "      <td>5.69</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>10</td>\n",
+       "      <td>1610</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>5.78</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>11</td>\n",
+       "      <td>1615</td>\n",
+       "      <td>33.0</td>\n",
+       "      <td>5.94</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>12</td>\n",
+       "      <td>1620</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>6.01</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>13</td>\n",
+       "      <td>1625</td>\n",
+       "      <td>33.0</td>\n",
+       "      <td>6.12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>14</td>\n",
+       "      <td>1630</td>\n",
+       "      <td>45.0</td>\n",
+       "      <td>6.22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>15</td>\n",
+       "      <td>1635</td>\n",
+       "      <td>33.0</td>\n",
+       "      <td>6.30</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>16</td>\n",
+       "      <td>1640</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>6.37</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>17</td>\n",
+       "      <td>1645</td>\n",
+       "      <td>53.0</td>\n",
+       "      <td>6.45</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>18</td>\n",
+       "      <td>1650</td>\n",
+       "      <td>42.0</td>\n",
+       "      <td>6.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>19</td>\n",
+       "      <td>1655</td>\n",
+       "      <td>40.5</td>\n",
+       "      <td>6.60</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>20</td>\n",
+       "      <td>1660</td>\n",
+       "      <td>46.5</td>\n",
+       "      <td>6.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>21</td>\n",
+       "      <td>1665</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>6.80</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>22</td>\n",
+       "      <td>1670</td>\n",
+       "      <td>37.0</td>\n",
+       "      <td>6.90</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>23</td>\n",
+       "      <td>1675</td>\n",
+       "      <td>43.0</td>\n",
+       "      <td>7.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>24</td>\n",
+       "      <td>1680</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>7.30</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>25</td>\n",
+       "      <td>1685</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>7.60</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>26</td>\n",
+       "      <td>1690</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>8.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>27</td>\n",
+       "      <td>1695</td>\n",
+       "      <td>50.0</td>\n",
+       "      <td>8.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>28</td>\n",
+       "      <td>1700</td>\n",
+       "      <td>30.0</td>\n",
+       "      <td>9.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>29</td>\n",
+       "      <td>1705</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>10.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>30</td>\n",
+       "      <td>1710</td>\n",
+       "      <td>44.0</td>\n",
+       "      <td>11.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>31</td>\n",
+       "      <td>1715</td>\n",
+       "      <td>33.0</td>\n",
+       "      <td>11.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>32</td>\n",
+       "      <td>1720</td>\n",
+       "      <td>29.0</td>\n",
+       "      <td>12.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>33</td>\n",
+       "      <td>1725</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>13.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>34</td>\n",
+       "      <td>1730</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>13.30</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>35</td>\n",
+       "      <td>1735</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>13.60</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>36</td>\n",
+       "      <td>1740</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>14.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>37</td>\n",
+       "      <td>1745</td>\n",
+       "      <td>27.5</td>\n",
+       "      <td>14.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>38</td>\n",
+       "      <td>1750</td>\n",
+       "      <td>31.0</td>\n",
+       "      <td>15.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>39</td>\n",
+       "      <td>1755</td>\n",
+       "      <td>35.5</td>\n",
+       "      <td>15.70</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>40</td>\n",
+       "      <td>1760</td>\n",
+       "      <td>31.0</td>\n",
+       "      <td>16.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>41</td>\n",
+       "      <td>1765</td>\n",
+       "      <td>43.0</td>\n",
+       "      <td>17.60</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>42</td>\n",
+       "      <td>1770</td>\n",
+       "      <td>47.0</td>\n",
+       "      <td>18.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>43</td>\n",
+       "      <td>1775</td>\n",
+       "      <td>44.0</td>\n",
+       "      <td>19.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>44</td>\n",
+       "      <td>1780</td>\n",
+       "      <td>46.0</td>\n",
+       "      <td>21.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>45</td>\n",
+       "      <td>1785</td>\n",
+       "      <td>42.0</td>\n",
+       "      <td>23.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>46</td>\n",
+       "      <td>1790</td>\n",
+       "      <td>47.5</td>\n",
+       "      <td>25.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>47</td>\n",
+       "      <td>1795</td>\n",
+       "      <td>76.0</td>\n",
+       "      <td>27.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>48</td>\n",
+       "      <td>1800</td>\n",
+       "      <td>79.0</td>\n",
+       "      <td>28.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>49</td>\n",
+       "      <td>1805</td>\n",
+       "      <td>81.0</td>\n",
+       "      <td>29.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>50</td>\n",
+       "      <td>1810</td>\n",
+       "      <td>99.0</td>\n",
+       "      <td>30.00</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    rownames  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\n",
+       "5          6  1590   47.0   5.25\n",
+       "6          7  1595   64.0   5.54\n",
+       "7          8  1600   27.0   5.61\n",
+       "8          9  1605   33.0   5.69\n",
+       "9         10  1610   32.0   5.78\n",
+       "10        11  1615   33.0   5.94\n",
+       "11        12  1620   35.0   6.01\n",
+       "12        13  1625   33.0   6.12\n",
+       "13        14  1630   45.0   6.22\n",
+       "14        15  1635   33.0   6.30\n",
+       "15        16  1640   39.0   6.37\n",
+       "16        17  1645   53.0   6.45\n",
+       "17        18  1650   42.0   6.50\n",
+       "18        19  1655   40.5   6.60\n",
+       "19        20  1660   46.5   6.75\n",
+       "20        21  1665   32.0   6.80\n",
+       "21        22  1670   37.0   6.90\n",
+       "22        23  1675   43.0   7.00\n",
+       "23        24  1680   35.0   7.30\n",
+       "24        25  1685   27.0   7.60\n",
+       "25        26  1690   40.0   8.00\n",
+       "26        27  1695   50.0   8.50\n",
+       "27        28  1700   30.0   9.00\n",
+       "28        29  1705   32.0  10.00\n",
+       "29        30  1710   44.0  11.00\n",
+       "30        31  1715   33.0  11.75\n",
+       "31        32  1720   29.0  12.50\n",
+       "32        33  1725   39.0  13.00\n",
+       "33        34  1730   26.0  13.30\n",
+       "34        35  1735   32.0  13.60\n",
+       "35        36  1740   27.0  14.00\n",
+       "36        37  1745   27.5  14.50\n",
+       "37        38  1750   31.0  15.00\n",
+       "38        39  1755   35.5  15.70\n",
+       "39        40  1760   31.0  16.50\n",
+       "40        41  1765   43.0  17.60\n",
+       "41        42  1770   47.0  18.50\n",
+       "42        43  1775   44.0  19.50\n",
+       "43        44  1780   46.0  21.00\n",
+       "44        45  1785   42.0  23.00\n",
+       "45        46  1790   47.5  25.50\n",
+       "46        47  1795   76.0  27.50\n",
+       "47        48  1800   79.0  28.50\n",
+       "48        49  1805   81.0  29.50\n",
+       "49        50  1810   99.0  30.00"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data = raw_data.dropna().copy()\n",
+    "print(f\"Le jeu de données comporte {len(data)} lignes.\")\n",
+    "data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Reproduction du graphe de Playfair\n",
+    "\n",
+    "Nous cherchons désormais à reproduire le graphe de Playfair à partir des données numériques.\n",
+    "\n",
+    "Nous commençons par représenter, comme Playfair, le prix du blé par des barres et les salaires par une surface bleue délimitée par une courbe rouge."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 720x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize = (10, 4))\n",
+    "\n",
+    "plt.subplot(1, 2, 1)\n",
+    "plt.bar(data['Year'], data['Wheat'], color = \"green\")\n",
+    "plt.ylabel('Wheat')\n",
+    "plt.xlabel('Year')\n",
+    "plt.title(\"Wheat vs Year\")\n",
+    "\n",
+    "plt.subplot(1, 2, 2)\n",
+    "plt.plot( data['Year'],data['Wages'], 'r-')\n",
+    "plt.fill_between(data['Year'],data['Wages'], color = 'blue')\n",
+    "plt.ylabel('Wages')\n",
+    "plt.xlabel('Year')\n",
+    "plt.title(\"Wages vs Year\")\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Nous pouvons superposer les deux de la même façon dans un seul graphique."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "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": [
+    "plt.bar(data['Year'], data['Wheat'], color = \"green\", label = \"Wheat\")\n",
+    "\n",
+    "plt.plot(data['Year'],data['Wages'], 'r-', label = \"Wages\")\n",
+    "plt.fill_between(data['Year'], data['Wages'], color = 'blue')\n",
+    "\n",
+    "plt.ylabel('Value')\n",
+    "plt.xlabel('Year')\n",
+    "\n",
+    "plt.title(\"Wheat and Wages vs Year\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Amélioration de la présentation\n",
+    "\n",
+    "Playfair a combiné les deux quantités dans un même graphique en simplifiant les unités \"shillings par quart de boisseau de blé\" et \"shillings par semaine\" à un simple \"shillings\", ce qui aujourd'hui n'est plus admissible. Nous utilisons donc deux ordonnées différentes, une à gauche et une à droite, en indiquant les unités correctes."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax1 = plt.subplots()\n",
+    "ax2 = ax1.twinx()\n",
+    "\n",
+    "ax1.set_xlabel(\"Year\")\n",
+    "ax1.set_ylabel(\"Wheat\", color=\"green\")\n",
+    "ax1.bar(data['Year'], data['Wheat'], color=\"green\")\n",
+    "ax1.tick_params(axis='y', labelcolor=\"green\")\n",
+    "ax1.set_ylim(bottom=0)  # force Wheat axis to start at 0\n",
+    "\n",
+    "ax2.set_ylabel(\"Wages\", color=\"blue\")\n",
+    "ax2.plot(data['Year'], data['Wages'], 'r-', label=\"Wages\", alpha=0.5)\n",
+    "ax2.fill_between(data['Year'], data['Wages'], color='blue', alpha=0.2)\n",
+    "ax2.tick_params(axis='y', labelcolor=\"blue\")\n",
+    "ax2.set_ylim(bottom=0)  # force Wages axis to start at 0\n",
+    "\n",
+    "plt.title(\"Wheat and Wages vs Year\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Nous pouvons également changer le style du graphique, en traçant directement les deux courbes."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax1 = plt.subplots()\n",
+    "ax2 = ax1.twinx()\n",
+    "\n",
+    "ax1.set_xlabel(\"Year\")\n",
+    "ax1.set_ylabel(\"Wheat\", color = \"green\")\n",
+    "ax1.plot(data['Year'], data['Wheat'], color = \"green\", marker = \"o\")\n",
+    "ax1.tick_params(axis = 'y', labelcolor = \"green\")\n",
+    "\n",
+    "ax2.set_ylabel('Wages', color = \"blue\")\n",
+    "ax2.plot(data['Year'], data['Wages'], color = \"blue\", marker = \"o\")\n",
+    "ax2.tick_params(axis = 'y', labelcolor = \"blue\")\n",
+    "\n",
+    "fig.tight_layout()\n",
+    "plt.title(\"Wheat and Wages vs Year\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Pouvoir d'achat\n",
+    "\n",
+    "L'objectif de Playfair était de montrer que le pouvoir d'achat des ouvriers avait augmenté au cours du temps. Nous allons essayer de mieux faire ressortir cette information, en représentantle pouvoir d'achat au cours du temps.\n",
+    "\n",
+    "Précisons que le pouvoir d'achat est défini comme la quantité de blé qu'un ouvrier peut acheter avec son salaire hebdomadaire."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "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": [
+    "purchasingPower = data['Wages'] / data['Wheat']\n",
+    "plt.scatter(data['Year'], purchasingPower)\n",
+    "plt.plot(data['Year'], purchasingPower, linestyle = \"--\")\n",
+    "plt.ylabel('Purchasing power')\n",
+    "plt.xlabel('Year')\n",
+    "plt.title(\"Purchasing power vs Year\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Nous voyons dont que le pouvoir d'achat a tendance à monter jusqu'en 1730 environ, avant d'osciler, et semble-t-il, de diminuer aux alentours de 1800."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Dans un autre graphique, nous représentons le prix du blé et le salaire sur deux axes différents, **sans l'axe du temps**.\n",
+    "\n",
+    "Nous proposons deux moyens d'indiquer la progression du temps dans ce graphique:\n",
+    "- En utilisant un dégradé de couleurs pour indiquer le temps\n",
+    "- En écrivant sur chaque point l'année correspondante (ce qui peut vite devenir peu lisible)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots()\n",
+    "\n",
+    "sc = ax.scatter(data['Wages'], data['Wheat'], c = data['Year'])\n",
+    "\n",
+    "ax.plot(data['Wages'], data['Wheat'], linestyle = '--', alpha = 0.6)\n",
+    "\n",
+    "ax.set_xlabel(\"Wages\")\n",
+    "ax.set_ylabel(\"Wheat\")\n",
+    "\n",
+    "cbar = plt.colorbar(sc, ax = ax)\n",
+    "cbar.set_label(\"Year\")\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "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, ax = plt.subplots()\n",
+    "\n",
+    "sc = ax.scatter(data['Wages'], data['Wheat'])\n",
+    "ax.plot(data['Wages'], data['Wheat'], linestyle='--', alpha=0.6)\n",
+    "\n",
+    "for i, year in enumerate(data['Year']):\n",
+    "    ax.text(data['Wages'].iloc[i], data['Wheat'].iloc[i], str(year), fontsize = 8, ha = 'right', va = 'bottom')\n",
+    "\n",
+    "ax.set_xlabel(\"Wages\")\n",
+    "ax.set_ylabel(\"Wheat\")\n",
+    "\n",
+    "plt.title(\"Wheat vs Wages\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Selon moi, les deux graphes précédents (où le temps n'est pas un des axes) sont sympathiques, mais ne sont pas les plus lisibles.\n",
+    "\n",
+    "Le graphe ci-dessous a le mérite d'être clair, mais ne permet pas de voir exactement comment le pouvoir d'achat évolue."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax1 = plt.subplots()\n",
+    "ax2 = ax1.twinx()\n",
+    "\n",
+    "ax1.set_xlabel(\"Year\")\n",
+    "ax1.set_ylabel(\"Wheat\", color = \"green\")\n",
+    "ax1.plot(data['Year'], data['Wheat'], color = \"green\", marker = \"o\")\n",
+    "ax1.tick_params(axis = 'y', labelcolor = \"green\")\n",
+    "\n",
+    "ax2.set_ylabel('Wages', color = \"blue\")\n",
+    "ax2.plot(data['Year'], data['Wages'], color = \"blue\", marker = \"o\")\n",
+    "ax2.tick_params(axis = 'y', labelcolor = \"blue\")\n",
+    "\n",
+    "fig.tight_layout()\n",
+    "plt.title(\"Wheat and Wages vs Year\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Le graphe suivant montre bien l'évolution du pouvoir d'achat. Si toutefois nous sommes intéressés par l'évolution à la fois des salaires et du prix du blé, alors mieux vaut conserver le graphe précédent."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "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": [
+    "purchasingPower = data['Wages'] / data['Wheat']\n",
+    "plt.scatter(data['Year'], purchasingPower)\n",
+    "plt.plot(data['Year'], purchasingPower, linestyle = \"--\")\n",
+    "plt.ylabel('Purchasing power')\n",
+    "plt.xlabel('Year')\n",
+    "plt.title(\"Purchasing power vs Year\")\n",
+    "plt.show()"
+   ]
+  }
+ ],
  "metadata": {
   "kernelspec": {
    "display_name": "Python 3",
@@ -16,10 +1472,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 2
 }
-