{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Sujet 2 : le pouvoir d'achat des ouvriers anglais du XVIe au XIXe siècle" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Nous commençons par importer les données." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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rownamesYearWheatWages
01156541.05.00
12157045.05.05
23157542.05.08
34158049.05.12
45158541.55.15
56159047.05.25
67159564.05.54
78160027.05.61
89160533.05.69
910161032.05.78
1011161533.05.94
1112162035.06.01
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1415163533.06.30
1516164039.06.37
1617164553.06.45
1718165042.06.50
1819165540.56.60
1920166046.56.75
2021166532.06.80
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2324168035.07.30
2425168527.07.60
2526169040.08.00
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2829170532.010.00
2930171044.011.00
3031171533.011.75
3132172029.012.50
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3334173026.013.30
3435173532.013.60
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3839175535.515.70
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\n", "
" ], "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": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "%matplotlib inline\n", "import matplotlib.pyplot as plt\n", "import pandas as pd\n", "import os\n", "import urllib.request\n", "\n", "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", "raw_data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Puis nous regardons si des données sont manquantes." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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rownamesYearWheatWages
5051181578.0NaN
5152182054.0NaN
5253182154.0NaN
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" ], "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": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "raw_data[raw_data.isnull().any(axis=1)]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Il y en a. Nous supprimons les lignes correspondantes." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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rownamesYearWheatWages
01156541.05.00
12157045.05.05
23157542.05.08
34158049.05.12
45158541.55.15
56159047.05.25
67159564.05.54
78160027.05.61
89160533.05.69
910161032.05.78
1011161533.05.94
1112162035.06.01
1213162533.06.12
1314163045.06.22
1415163533.06.30
1516164039.06.37
1617164553.06.45
1718165042.06.50
1819165540.56.60
1920166046.56.75
2021166532.06.80
2122167037.06.90
2223167543.07.00
2324168035.07.30
2425168527.07.60
2526169040.08.00
2627169550.08.50
2728170030.09.00
2829170532.010.00
2930171044.011.00
3031171533.011.75
3132172029.012.50
3233172539.013.00
3334173026.013.30
3435173532.013.60
3536174027.014.00
3637174527.514.50
3738175031.015.00
3839175535.515.70
3940176031.016.50
4041176543.017.60
4142177047.018.50
4243177544.019.50
4344178046.021.00
4445178542.023.00
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4950181099.030.00
\n", "
" ], "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": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data = raw_data.dropna().copy()\n", "data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Reproduire le graphe de Playfair\n", "\n", "On commence par représenter le prix du blé par des barres." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.bar(data['Year'],data['Wheat'])\n", "plt.ylabel('Wheat')\n", "plt.xlabel('Year')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Puis on représente les salaires par une surface bleue delimitee par une courbe rouge." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.plot( data['Year'],data['Wages'], 'r-')\n", "plt.fill_between(data['Year'],data['Wages'], color='blue')\n", "\n", "plt.ylabel('Wages')\n", "plt.xlabel('Year')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Puis on superpose les graphes." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "p1 = plt.bar(data['Year'],data['Wheat'])\n", "\n", "p2 = plt.plot(data['Year'],data['Wages'], 'r-')\n", "p2 = plt.fill_between(data['Year'],data['Wages'], color='blue')\n", "\n", "plt.ylabel('Value')\n", "plt.xlabel('Year')\n", "plt.legend([p1, p2], [\"Wheat\", \"Wages\"])\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Amélioration du graphique" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "On utilise deux axes des ordonnées pour les deux courbes." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax1 = plt.subplots()\n", "\n", "ax1.set_xlabel('Year')\n", "ax1.set_ylabel('Shillings par semaine', color='orange')\n", "\n", "ax2 = ax1.twinx()\n", "ax2.set_ylabel('shillings par quart de boisseau de blé', color='blue')\n", "\n", "p1 = plt.bar(data['Year'],data['Wheat'])\n", "p2 = plt.bar(data['Year'],data['Wages'])\n", "\n", "\n", "plt.legend([p1, p2], [\"Wheat\", \"Wages\"])\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Etude du pouvoir d'achat" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Le pouvoir d'achat est obtenu comme un quotient des revenus sur les prix." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "purchasingPower = data['Wages'] / data['Wheat']\n", "plt.plot(data['Year'], purchasingPower)\n", "plt.ylabel('Purchasing power')\n", "plt.xlabel('Year')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Nous pouvons utiliser une nouvelle représentation: salaire et prix sur un même graphe." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots()\n", "\n", "# Scatter avec couleurs = années\n", "sc = ax.scatter(data['Wages'], data['Wheat'], \n", " c=data['Year'], cmap='viridis', s=80)\n", "\n", "# Courbe reliant les points\n", "ax.plot(data['Wages'], data['Wheat'], linestyle='--', alpha=0.5)\n", "\n", "ax.set_xlabel(\"Wages\")\n", "ax.set_ylabel(\"Wheat\")\n", "\n", "# Barre de couleur pour les années\n", "cbar = plt.colorbar(sc, ax=ax)\n", "cbar.set_label(\"Year\")\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "La représentation la plus claire est selon moi celle de Playfair (dans \"Amélioration du graphique\")." ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.4" } }, "nbformat": 4, "nbformat_minor": 2 }