{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# le pouvoir d'achat des ouvriers anglais du XVIe au XIXe siècle\n", "\n", "On utilise le [jeu de données de William Playfair](https://vincentarelbundock.github.io/Rdatasets/doc/HistData/Wheat.html) pour étudier l'évolution du pouvoir d'achat des ouvriers anglais du XVIe au XIXe siècle.\n" ] }, { "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": "markdown", "metadata": {}, "source": [ "## Importation du jeu de données\n", "\n", "On importe le jeu de données d'après l'url suivant :" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Unnamed: 0YearWheatWages
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1213162533.06.12
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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
2122167037.06.90
2223167543.07.00
2324168035.07.30
2425168527.07.60
2526169040.08.00
2627169550.08.50
2728170030.09.00
2829170532.010.00
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3031171533.011.75
3132172029.012.50
3233172539.013.00
3334173026.013.30
3435173532.013.60
3536174027.014.00
3637174527.514.50
3738175031.015.00
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4142177047.018.50
4243177544.019.50
4344178046.021.00
4445178542.023.00
4546179047.525.50
4647179576.027.50
4748180079.028.50
4849180581.029.50
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5051181578.0NaN
5152182054.0NaN
5253182154.0NaN
\n", "
" ], "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\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 = pd.read_csv(data_url)\n", "data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Premier graphique \n", "\n", "Pour ce premier graphique, l'objectif est de reproduire quelque chose de similaire au [graphique produit par William Playfair](https://upload.wikimedia.org/wikipedia/commons/3/3a/Chart_Showing_at_One_View_the_Price_of_the_Quarter_of_Wheat%2C_and_Wages_of_Labour_by_the_Week%2C_from_1565_to_1821.png). \n", "On commence par créer les deux premier graphiques bruts :" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Evolution du prix du blé :" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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ZvCE8Avw+3Ule6+lnmbGeCXy06/u9wBVD2/9GN54HGfrWfr2PdSXjnOU5HTXOrv0jwC+N2H4m53OlY21tToEfA+7pxnMXcGkLczrqxzNjJalxnhkrSY0z6CWpcQa9JDXOoJekxhn0ktQ4g16SGmfQS1LjDHpJatz/AUF1+eKEYhVGAAAAAElFTkSuQmCC\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.bar(data['Year'],data['Wheat'], 5, color='grey')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Evolution du salaire hebdomadaire :" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" }, { "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'], color='r')\n", "plt.fill_between(data['Year'], data['Wages'], color='#539ecd')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "On peut maintenant superposer les deux graphiques, en ajoutant un échelle à droite et les légendes." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0,0.5,'The price of the quarter of wheat in shillings')" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig1, ax1 = plt.subplots()\n", "ax1.set_title(\"The price of the quarter of wheat and wages of labour by the week\")\n", "ax1.bar(data['Year'], data['Wheat'],5, color='grey')\n", "ax1.set_xlabel(\"Years\")\n", "\n", "ax2 = ax1.twinx()\n", "ax2.set_ylim((0,100))\n", "ax2.plot(data['Year'],data['Wages'], color='r')\n", "ax2.fill_between(data['Year'], data['Wages'], color='#539ecd')\n", "ax2.set_ylabel(\"The price of the quarter of wheat in shillings\")\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Amélioration de la présentation des données\n", "On ajuste les unités du graphique, on remplace shillings par shillings par quart de boisseau de bé ou shillings par semaine." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0,0.5,'Weekly wages (in shillings by week)')" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig1, ax1 = plt.subplots()\n", "ax1.bar(data['Year'], data['Wheat'],5, color='grey')\n", "ax1.set_title(\"The price of the quarter of wheat and wages of labour by the week\")\n", "ax1.set_xlabel(\"Years\")\n", "ax1.set_ylabel(\"Price of the quarter of wheat (in shillings by quarter of wheat)\")\n", "\n", "ax2 = ax1.twinx()\n", "ax2.set_ylim((0,100))\n", "ax2.plot(data['Year'],data['Wages'], color='r')\n", "ax2.fill_between(data['Year'], data['Wages'], color='#539ecd')\n", "ax2.set_ylabel(\"Weekly wages (in shillings by week)\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Ajustement des données pour observer l'évolution du pouvoir d'achat\n", "\n", "On souhaite représenter le pouvoir d'achat au cours du temps, défini comme la quantité de blé qu'un ouvrier peut acheter avec son salaire hebdomadaire. \n", "On crée une nouvelle colonne au tableau : la colonne Power qui représente le pouvoir d'achat de l'année, la quantité de quart de boisseaux de blé qu'un ouvrier peut acheter par semaine." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Unnamed: 0YearWheatWagesPower
01156541.05.000.121951
12157045.05.050.112222
23157542.05.080.120952
34158049.05.120.104490
45158541.55.150.124096
56159047.05.250.111702
67159564.05.540.086563
78160027.05.610.207778
89160533.05.690.172424
910161032.05.780.180625
1011161533.05.940.180000
1112162035.06.010.171714
1213162533.06.120.185455
1314163045.06.220.138222
1415163533.06.300.190909
1516164039.06.370.163333
1617164553.06.450.121698
1718165042.06.500.154762
1819165540.56.600.162963
1920166046.56.750.145161
2021166532.06.800.212500
2122167037.06.900.186486
2223167543.07.000.162791
2324168035.07.300.208571
2425168527.07.600.281481
2526169040.08.000.200000
2627169550.08.500.170000
2728170030.09.000.300000
2829170532.010.000.312500
2930171044.011.000.250000
3031171533.011.750.356061
3132172029.012.500.431034
3233172539.013.000.333333
3334173026.013.300.511538
3435173532.013.600.425000
3536174027.014.000.518519
3637174527.514.500.527273
3738175031.015.000.483871
3839175535.515.700.442254
3940176031.016.500.532258
4041176543.017.600.409302
4142177047.018.500.393617
4243177544.019.500.443182
4344178046.021.000.456522
4445178542.023.000.547619
4546179047.525.500.536842
4647179576.027.500.361842
4748180079.028.500.360759
4849180581.029.500.364198
4950181099.030.000.303030
5051181578.0NaNNaN
5152182054.0NaNNaN
5253182154.0NaNNaN
\n", "
" ], "text/plain": [ " Unnamed: 0 Year Wheat Wages Power\n", "0 1 1565 41.0 5.00 0.121951\n", "1 2 1570 45.0 5.05 0.112222\n", "2 3 1575 42.0 5.08 0.120952\n", "3 4 1580 49.0 5.12 0.104490\n", "4 5 1585 41.5 5.15 0.124096\n", "5 6 1590 47.0 5.25 0.111702\n", "6 7 1595 64.0 5.54 0.086563\n", "7 8 1600 27.0 5.61 0.207778\n", "8 9 1605 33.0 5.69 0.172424\n", "9 10 1610 32.0 5.78 0.180625\n", "10 11 1615 33.0 5.94 0.180000\n", "11 12 1620 35.0 6.01 0.171714\n", "12 13 1625 33.0 6.12 0.185455\n", "13 14 1630 45.0 6.22 0.138222\n", "14 15 1635 33.0 6.30 0.190909\n", "15 16 1640 39.0 6.37 0.163333\n", "16 17 1645 53.0 6.45 0.121698\n", "17 18 1650 42.0 6.50 0.154762\n", "18 19 1655 40.5 6.60 0.162963\n", "19 20 1660 46.5 6.75 0.145161\n", "20 21 1665 32.0 6.80 0.212500\n", "21 22 1670 37.0 6.90 0.186486\n", "22 23 1675 43.0 7.00 0.162791\n", "23 24 1680 35.0 7.30 0.208571\n", "24 25 1685 27.0 7.60 0.281481\n", "25 26 1690 40.0 8.00 0.200000\n", "26 27 1695 50.0 8.50 0.170000\n", "27 28 1700 30.0 9.00 0.300000\n", "28 29 1705 32.0 10.00 0.312500\n", "29 30 1710 44.0 11.00 0.250000\n", "30 31 1715 33.0 11.75 0.356061\n", "31 32 1720 29.0 12.50 0.431034\n", "32 33 1725 39.0 13.00 0.333333\n", "33 34 1730 26.0 13.30 0.511538\n", "34 35 1735 32.0 13.60 0.425000\n", "35 36 1740 27.0 14.00 0.518519\n", "36 37 1745 27.5 14.50 0.527273\n", "37 38 1750 31.0 15.00 0.483871\n", "38 39 1755 35.5 15.70 0.442254\n", "39 40 1760 31.0 16.50 0.532258\n", "40 41 1765 43.0 17.60 0.409302\n", "41 42 1770 47.0 18.50 0.393617\n", "42 43 1775 44.0 19.50 0.443182\n", "43 44 1780 46.0 21.00 0.456522\n", "44 45 1785 42.0 23.00 0.547619\n", "45 46 1790 47.5 25.50 0.536842\n", "46 47 1795 76.0 27.50 0.361842\n", "47 48 1800 79.0 28.50 0.360759\n", "48 49 1805 81.0 29.50 0.364198\n", "49 50 1810 99.0 30.00 0.303030\n", "50 51 1815 78.0 NaN NaN\n", "51 52 1820 54.0 NaN NaN\n", "52 53 1821 54.0 NaN NaN" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data['Power'] = data['Wages']/data['Wheat']\n", "data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "On représente maintenant l'évolution de ce pouvoir d'achat dans le temps" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0,0.5,'Buying power')" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.scatter(data['Year'],data['Power'], color='green')\n", "plt.xlabel('Year')\n", "plt.ylabel('Buying power')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Evolution du prix du blé en fonction du salaire\n", "\n", "Dans un dernier graphique, on veut montrer l'évolution du prix du blé en fonction du salaire, sans l'axe du temps. On indique la progression du temps avec la couleur : plus l'année est récente, plus la couleur du point est foncée." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0,0.5,'Price of the quarter of wheat (in shillings by quarter of wheat)')" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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nXbl9I8r5zS8I5in8hSAv06cJUn+/BVwLHJGv4Jxzrr9aunoTy9dsZpfpYxhZWdbpY0dWlXHR6QNvAc4oFcTxZnZg1v1rJD1tZpdK+na+AnPOuf6orqGZz/7g7zzywhKKi+I0J9Oc98kD+N9zjyIYdzN4ROmkzkg6VVIsvJyatW/gdmA451w3/NfP7ubh5xfT2Jxi85YmGptTXH37c8z514uFDq3XRakgTgc+SzAvYXV4+wxJZcCX8xibc871K3UNzdzx+Js0tUmmV9+Y5Nc3PV2gqPJnm01MYSf0RzvY/UTvhuOcc/1XbX0TsQ6akdZvru/jaPIvyiimscC5wPTsx5vZ2fkLyznn+p8Jo4YxsrKMletrW22PxcQR+w6+JXSiNDHdAQwHHiBYarTl4pxzQ4okrvzaiZSVJGg5kShKxKgsL+aSs48oZGh5EWUUU7mZfTPvkTjn3ABw4gdm8cCvP88v/vYUby/fwKF7TeUrp32AKWNzr+MwkEWpIO6WdKKZ/TPv0Tjn3ACw704T+fP3P1noMPIuShPThQSVRIOkzZJqJW3Od2DOOecKK8oopv4/H9w551yv67CCkLSzmb0pad9c+83s+fyF5ZxzrtA6O4P4GsHw1p/n2GfAUXmJyDnnXL/QYQVhZueG10f2XTjOOef6i86amD7R2RPN7LbeD8c551x/0VkTU0fpNSBoYvIKwjnnBrHOmpjO6stAnHPO9S+dNTF9tbMnmtkvulOgpJ2Am7I2zQS+B1wfbp8OLAFONbOa7pThnHOu5zqbKFe5jUu3mNlbZra3me0N7AfUA7cDFwMPmtmOwIPhfeeccwXSWRPTD/qg/KOBd8zsXUkn8/7ypXOARwDPAeWccwXSWRPTN8zscklXkGPlODO7oBfK/zTw1/D2eDNbGR57paRxHcQ1G5gNMHXq1F4IwTnnXC6djWJ6I7yel4+CJRUDJwHf6srzzOwa4BqA6upqX/LUOefypLMmprvC6zl5KvsE4HkzWx3eXy1pYnj2MJFgiVPnnHMFEmVFuVnAf9N+Rbmeptr4DO83LwHcCZwJXBZe39HD4zvnnOuBKOtB3AL8FvgDkN7GYyORVA4cC3wha/NlwM2SzgGWAqf0RlnOOee6J0oFkTKzq3uzUDOrB0a32baeYFSTc865fqCzUUyjwpt3SfovgrkKTS37zWxDnmNzzjlXQJ2dQcwnGN4aLs3N17P2GcEMaOecc4NUZ6OYZvRlIM455/qXba5JLekUSZXh7e9Iuk3SPvkPzTnnXCFts4IAvmtmtZIOBY4jSIPx2/yG5ZxzrtCiVBAtQ1s/DFxtZncAxfkLyTnnXH8QpYJ4T9LvgFOBf0oqifg855xzA1iUL/pTgX8Dx5vZRmAUrUc0DRoNzWlWbWpiRU0TG7ckSWc81ZNzbuja5kS5cFLbbVn3VwIr8xlUIWysT7KpPr01bW1zQ5q6pgyTRhQTi6nT5zrn3GDkTUVAJmOtKocW6YyxuTFVkJicc67QvIIAmlKZnNsNaGjOvc855wY7ryCAeCdNSJ3tc865wSzKRLlPSFooaZOkzZJqJW3ui+D6SlFcJOLtKwIBVWVR8hk659zgE+UM4nLgJDMbbmZVZlZpZlX5DqwvSWJ8VTHFcSHYehlVkaC0yE+ynHNDU5Sfx6vN7I1tP2xgS8TFpJElJNMZ0hkoToiYvHnJOTd0Rakg5km6CfgHrdN939bxUwauoniMoniho3DOucKLUkFUAfXAh7K2GVlzI5xzzg0+USbKndUXgTjnnOtfOltR7htmdrmkK6DdHDLM7ILuFippBMEa17uHxz4beAu4CZgOLAFONbOa7pbhnHOuZzo7g2jpmJ6Xh3J/DdxrZp+SVAyUA98GHjSzyyRdDFwMfDMPZTvnnIugsxXl7gqv5/RmgZKqgMOBz4fHbwaaJZ0MHBE+bA7wCF5BOOdcwXQ4yF/SNZL26GBfhaSzJZ3ejTJnAmuBP0l6QdIfJFUA48NEgC0JAcd149jOOed6SWdNTFcB3w0riVcJvtRLgR0JRjZdC9zYzTL3Bc43s2ck/ZqgOSkSSbOB2QBTp07tRvHOOeei6KyJ6UXgVEnDgGpgItAAvGFmb/WgzOXAcjN7Jrx/K0EFsVrSRDNbKWkisKaDuK4BrgGorq72BRuccy5PogxzrSPoD+gVZrZK0jJJO4UVzdHA6+HlTOCy8PqO3irTOedc1xUqE935wI3hCKZFwFkE/SE3SzoHWAqcUqDYnHPOUaAKImy+qs6x6+i+jsU551xuUdJ9t/sln2ubc865wSVKLutvRdzmnHNuEOks1cYJwInAZEm/ydpVBfhCzc45N8h11gexgiDNxknA/KzttcBF+QzKOedc4XU2D+Il4CVJfzGzZB/G5Jxzrh+IMoppuqQfA7sSzKQGwMxm5i0q55xzBRelk/pPwNUE/Q5HAtcDN+QzKOecc4UXpYIoM7MHAZnZu2Z2CXBUfsNyzjlXaFGamBolxYCFkr4MvIdnWnXOuUEvyhnEVwgW9LkA2A84gyBXknPOuUEsSrK+5wAkma9PHTAz3lqzhXfWbSGZNkaUFbHnpEpGVRQXOjTnnOs1UVJtfEDS64RLkEraS9JVeY+sH3vpvc0sWFNHc9owoKYhyROLNrC50UcDO+cGjyhNTL8CjgPWw9b5EYfnM6j+rDmV4d2aBtJtVqJIG7y1ekthgnLOuTyIUkFgZsvabErnIZYBob45TUzKuW+jn0E45waRKKOYlkk6GLBw/YYLCJubhqLy4jgZy72Q3fDSQi2v4ZxzvS/KGcQXgfOAyQTLhe4d3h+SihMxpo4sI97mJCIu2GncsMIE5ZxzeRBlFNM64PQ+iGXA2GtyFSWJGO+sqyeVMapKE+w1uYrhZUWFDs0553rNNisISWOBc4Hp2Y83s7PzF1b/FpPYdUIlu06oxMxQB30Szjk3kEVpNL8DeBx4gF7qnJa0hCBteBpImVm1pFHATQQV0RLgVDOr6Y3y8ilflYOZ8cSiGv791jrqk2l2mzCMj+8+3udaOOf6TJQKotzMvpmHso8Mm69aXAw8aGaXSbo4vJ+PcgeEW15axUML19Mcjqedu2QjL75Xy/+duCPDS70pyzmXf1E6qe+WdGLeI4GTgTnh7TnAx/JdYCZjpDOGdTAqqVBqm1I8sOD9ygEgY9CUynD/W+sLGJlzbijpbMnRWsAAAd+W1AQkw/tmZlU9KNeA+yQZ8DszuwYYb2YrCQ6+UlLeEgKmM0ZtY5pUJrgfE1SWxilqOzSpQJZvbKQoLlKZ1hVXKmO8taauQFE554aazlaUq8xjuYeY2YqwErhf0ptRnyhpNjAbYOrUqV0u2MzY1JAm+7s3Y7CpIc3I8jjxWOEriVHlRe0qBwAJxg0rKUBEzrmhKEoupuslnStp594q1MxWhNdrgNuBA4DVkiaGZU4E1nTw3GvMrNrMqseOHdvlspNpI8d3LwCNyUyXj5cP4ytLmDmqnESbyqooJo7beUyBonLODTVR+iCuAyYCV0h6R9LfJV3Y3QIlVUiqbLkNfAh4FbiT99OIn0kweqrXdVQ5bGtfXzv/sGnsMXEYiZgoiovhpQm+ePBUpo4sK3Rozg0Im7c0sbGusdBhDGhRJso9JOlRYH+CJUe/COwG/LqbZY4Hbg+HhyaAv5jZvZKeA26WdA6wFDilm8fvVKKTfob+0gcBQUqP8w+bTn1zmsZkmhHlRR3mgHLOvW/Zms385+X/ZO7r7wGwx4yx/OEbJ7LLND/77iptawSPpAeBCmAuwXyIJ8KmoYKrrq62efPmdfl5mxvSQapuM1LpDBkL2vdHVSQoLYrnIVLncmtsTnP9wwu5de4SyksSnH3MLD5avZ1PvuymZCrNrmf+npXr60iHTQISDK8o4c0bvsDwCu/DA5A038yqt/W4KPMgXiZYSW53YBOwUdJcM2voYYwFU1kao745TU39+30OZrC+LsWIcqOipOtJ9xqTaZZtaiAmsd2IMorjkRLluiEsmcrw4f+7j9eXbaShOZiD+uzCdTx5xPb85HP7Fzi6geneZxexsa5xa+UAwf92czLDzQ+/wbkf2buA0Q08UZqYLgKQNAw4C/gTMAEYsFWxJJJtF3QgGHu7sSFNeXG8S7/g3lxTy5OLa2jpUzbgmB3Hen+B69Td85bx5vJNWysHgPqmFNc99DZfOn4XpvdB8sfgLNooSgyOHzRLVm0imWo/2KS+Kcnb7/X7xAz9TpRRTF+WdBPwIsHktWuBE/IdWL41JjtoWjNyDjHtyKaGJE8uriFtRjITXFIZ4/6Fa2lKDdllM1wE97/4HluaUu22J2LiqTdX57XsVDrDd65/lrH/MYfhp17LXl++hYdeei+vZfaFfXYYTyLH2fuwsiL2mzWhABENbFF+NpQBvwB2NrOjzewHZvZQnuPKu46mOxh0qTN44botOdeHELBkw4BthXN9YPyIspwDI2KC0ZX5PUG/8HdPctU9r7GlMYUZLHhvE5/60X3Mf3ttXsvNt0P2mMKe24+jtPj9vsTiRIwJo4bxsUNnFTCygWmbFYSZ/dTMnjGz9j91Bigzo6Ikd2d0cUKdTparb0qzrraZ+rBZIJUJ1qVuXwat2kGda+uzR+yQ89duSXGco/aYlLdya+qauPGRt1s1bUHQj3bZLS/mrdy+IIm7f3wK53+imomjKhg7opxzPrwXj/3mDIp9AEqXDbkl0DJmNDSDEaM0EaMxlQlyhwDFcTG6IncivHTGeH1FHZsbUlsfP7wswdQRZby+ujZHs5Sx3Qjvg3Admzmhkj+cdyhf+u1TGEFusNGVJdz09SPz2iewbG0dxYkYTcnWFYQZvLls4LfTl5cWcenZh3Pp2YcXOpQBr7NcTCVm1tSXweSbmdGQZOsv/tLiBCVFQcK+0oQoLe74n3Lx2no2N6RaTabbWJ+itCjG9qPLeWd9/dZKIhETe02qotKXIHXb8OHq7Xj7t5/ixcUbKC2Ks8e0kXkf4jp9fCXJdPuO3FhM7D3T5wq493X2DTYX2FfSDWb22b4KKJ/Mgks2SSTiytlMlG315uZ2M60NWLO5mcN3GM0OYyp4Z309ccGOY4cN6JxJjck0jyxczysra5lYVcJxu4xl7AB+Pf1dcSLOATtGTxvzzII13PjI2zSnMpxyyAyO2nNSlyqVqvJivnjCrlxz7xvUZ3WSlxbFufgUHwbq3tdZBVEs6UzgYEmfaLvTzG7LX1j50Vkl0Ok+6zh/UzDJTkweXsbk4QO/Sam2McVXb3+dTQ1JGlMZEjFxxyurueSEWew2MZ/5G10U/3vT81xx12s0JNOYwe1zl3DSgdO45rxDu1RJ/PBzBzBhZDm/vvMVNtQ2se/2o7n87A+w27RR+QveDTidVRBfJFiLegTw0Tb7DBhwFURniVo7m9cmiaqyBJsb2vfTV5UNrmakm19YwfotzVuby1LhsN1fPryI339mT5/hW0CLV9fy6ztfozGr72BLU4o7nnmXs46ZxcE7j498rFhMXHjyHlx48h75CNUNEp2l+34CeELSPDP7Yx/GlDeSKIkbTem226F4GwMcdhhXzkvLNpPJvL9IRiwWbM/WmEzz8DsbeG1VLSD2mDiMI7YfTckAmYj01OKanPNANjYkWbel2ZuaIthQ18T/3foyd89fTiImTjtkBl8/eTfKuzFDP9v9L75Hrvq5oSnFPc8t7VIF4VwUUT6xN0i6AGgZEvAo8FszS+YvrPwpSohYzEimgy/6uKAovu21pStK4uw3fTgraxqpa0ozrDTBpBElFGd98WcyxrXPLaemPknLRO15yzaxpKaB2QcOjPw6HVVkGcPTh0TQlExz3KX3896Ghq0dwb9/YAHPLFzLPd8+ukefgfKSOLEcp8GJuKgs82VoXe+L8h9/FUEupqvCy77A1fkMKt/iMVGSCCqGRITKoUVJIsb0seXsPqWS6WPKSMTFxoYktY1B09OCdVvY3JgiO4tH2qCmPsk76+vz8VJ63Qm7jmtXScQEs8ZVMNy/hLbprnnLWLu5qdUooaZkhteXbeKZhes6eea2fWT/qTmXx43HYpxy6MweHTtf6hqaeeHtNayq2VLoUFw3RDmD2N/M9sq6/5Ckl/IVUL6ZGU0pozH1/j9WpQo8AAAgAElEQVRaUQzKi2Nd+nW3anMjT79bE65pDRXFwa+75hw5npJpY1VtMzuMqeiV15BPJ+46jjdX1/HMkhpiEhKMKCvi60dvX+jQBoTnF23ImT4jlcnwytIaDprV9UWuWoyoKOHGrx3JGT9/ZOuZRDKd4Vf/eRDbT+jJCsD58ZOb5vGTm+ZRFM65OHa/qVz33x+iotR/aAwUUSqItKTtzewdAEkzgQGbZCiZDiqHTJg3yQyaBGkzqiLOW9jSnOKJRRtIZ/2a29yUoj6ZpijePhFgUVyMHCCd2fGY+PrR27N8YwML125hbEUxu06s9LUoItp+QiVlxfF2s5SL4jGmje158r1j957Cot+fxgMvrSCZznD0npMY2Q/7hW55bCGX3zyPhuYUDc3BtgfmL+WLv36IG755XGGDc5FF+db6OvCwpEUEfbPTCLK6DkiNqWBiXPaXuBnUNxsl8QwlRdtudVu0rp5cCTaGFceJK0Uqa68I2u536oPMnL1pyogypvhM8C475QPTuOy2V2hsTm/9DMRjYtSwEo7eo3eSxVWUFnHygdN65Vj58rNb57eaYwHBAI67nl7E5vpmqsqLCxSZ64oouZgeBHYELggvO5nZw/kOLB/Mgs7WVI5mIIDatsObOtCQTLeaF2EWLD6EwXE7jWbKiFJiCtrup44s5ewDprRbX9oNTlXlxdzzP8ewz8xRJOLBJMxDdx7H3d8+inhs6HTyr6nJ3ecWi4kaXwZ0wIjU7hGm3Hg5z7HkXSoDyvnb//39UYyvLGHZxmCUSnMm+2zBqCxJcNb+U2gOCvORP0PQrElV/Pu7x1LXkCQWU4+Htw5EH9xzCrc+vrBdwsqKkgRTRg+ss+mhrGDfXpLikl6QdHd4f5Sk+yUtDK9H9naZaYOiRMcTHqL+yJ8yooyKonirygGCYbNz361hS3OK4kQsUuVgZjy7dBOXP7yYS+97h7tfX0NDcsB28bgsw8qKhmTlAPC9Mw6korSo1Rrw5SUJfvnFw4n7j6YBo9N3SoHt8lT2hcAbWfcvBh40sx2BB8P7vS4mUZzIXRNUdJKsL1s8JnafVJVz0lLGjAVrow/pu/mlVdz4/AoWb2hgZW0T/35rPZc9tDg4A3FugJo5cTjPXvlpzjx2V3bebiTHV0/jjh+cxKcO9zUZBpJOf96YmUn6B8E8iF4jaQrwYeCHwFfDzScDR4S35wCPAN/szXLjCs4iyoriiDRNWUNdhxXHKI9YQUDQDxGT2i0WlDGozTHMMZcN9UmeWLyx1czlVMbY2JDkmaUbOWzm4M6Ls6UpBYKK4qH5K3uwmzauiiu/fGShw3A9EOU/82lJ+5vZc71Y7q+AbwDZ2d/Gm9lKADNbKWlcL5YHQCIGmTQgUVacoLQoSMJXmqDTRYKyZTLG66tqWZyV3rt1GWJixNXAFm9oIB5Tu+M0p43XV28ZtBXEspoG/u+fb/HmqjoAdp9cxXdPmMWE4aUFjsw5ly3KT+YjCSqJdyS9LOkVSd3usJb0EWCNmc3v5vNnS5onad7atV1bHrEl51JRLKgsiuOivKjzFeTaenlFLctqGokpRnGs/YzjskSMGaPKO3h2a1WluftDYoKR5YNzMlFDc5ov3Pgir62o3ZoI8OXlm5h940verOZcPxPlDOKEXi7zEOAkSScCpUCVpD8DqyVNDM8eJgJrcj3ZzK4BrgGorq7u8pqeUtDU1B3JdIaVmxq3DnGtLErQkE7TlM4gwayxFew5cXjOZSRz2X50OZUlcZpTmVad3fGYOHxmr/fR9wsPvbW23evNWNBk9/jb6zl65+7PNHbO9a4o8yDeBbYDjgpv10d5XifH+5aZTTGz6cCngYfM7AzgTuDM8GFnAnd0t4x8aUxmWqXjkER5IsHIkmImVZSy/3Yju5S1NSbxlcOmMWV4CUUxUZKIUVEc59wDpzAhz4vWF8qKjY00JNufKTQl06za5OPjnetPtnkGIen7QDWwE/AnoAj4M8GZQG+6DLhZ0jnAUuCUXj5+j5UXx9svSRca3s0modEVxXz7mO1Zt6WZplSGiVUlgzqtxazxwygrirWrJIoTMXYYYLPNnRvsojQxfRzYB3gewMxWSOqVpcXM7BGC0UqY2Xrg6N44br7EY2L7sRW8s3ZLq4yt8ZiYNa6CZDrDq6tqeWfdFipKEuwzeXjkM4ExFUMj9cAhO4xmfFUp721s2JrupCguthtZzv7TRxQ4OudctigVRHM43NUAJPX/lKR5tMPYckqLYryztp6mVIaR5UXsPGEYxYkYN8x/j40NSVIZQ8Abq+s4dtYY9pjY/zJtFkoiJn77H3vxhyeX8MAb64gJjtt1HGcfMm1Qnzk5NxBFqSBulvQ7YISkc4GzgT/kN6z+SxLbjSxju5GtE9nNW7Zxa+UAwazqVMZ4YME6dh43jCKfPbpVZWmCi47egYuO3qHQoTjnOrHNCsLMfibpWGAzQT/E98zs/rxHNsC8tXZLznkREqyqbWI7z4zqnBtgonRS/8TMvgncn2ObC5V2MHrJfKnOfimdMe57eSX3v7yK4eVFnHbwNHae5E2BzmWL8s11bI5tvT03ol/LmFHXmGJLUzrnko8A+04eTlGOCXfDSuJUFMd5Z30967c05ztUF0EqneH0K5/iK9c/zy3PLONPjy7io5c/yk1z3y10aM71Kx2eQUj6EvBfwPZtZk5XAk/mO7D+YlN9ikVr67eObo3HxA7jy6koaT0Lesbocg6cNoK5727cOhGvNBFjdEUJlz28mESYUmPqiFI+t98kSos6zirr8uuu51fwwuIa6sNV39IZSGcyfOemVzhx70lU+trbzgGdNzH9BfgX8GNaZ1atNbMNeY2qn2hOZXhnTX2rxYEyaWPBqi3suV1luxQdB08fxd6ThvPe5kbKEjFWbm7izjfWbk0pAfBuTQO3vLyKz+43uS9fisty1/z3tlYO2RJx8czb6zmml1Z+c26g67CCMLNNkmqBPcIZ1EPO+rrmnPPizIIzi1HD2v/SLC+Os+OYYCTwLS+vbrc+ddrgzbX1NCbTfhZRIMNK4whyLhxVVuzviXMtOu2DMLMM8JKkqX0UT7+STOdefc6MnCOW2qrvYOGfGNDoiekK5jOHTKc0R0VQFI9x4A6jCxCRc/1TlE7qicBrkh6UdGfLJd+B9QdVZYncq8wJKjvIxJptxzEV5Hp6aVGMqlJfA6FQPrDjGL507I5B7quSOMNKEwwvK+L68w6KnGjRuaEgyrfUD/IeRT9iZmzYkmRjfZpMJkNMQbbRjBkZs7A/IcOzSzZSVZpg5thyhnfQqfmhWaN5c00dTakMaQMRzCT++O7jB/ys4XV1zdw4bznPLd1EZUmCT+49gaNnjWmVzLA/u+jEnfjMwVN5asE6KsuKOHznsZR4k59zraijYZsDQXV1tc2bN6/XjmdmLNvQRENzkI66OZUmnTGS6QwZg1QmQ0ObpqGYYN+pwztcv6G2KcXji2tYvL6B0RVFHDZjJJMH+MI4G+uTzP7by9Q1pbbmpCpNxPjoHuP5zw8MydZI5wYUSfPNrHpbj4syUe4g4ApgF6AYiANbzGzQzSpqSGZoSAaVQ3DGEGxvuc7Vb5AxWLB6CwfOGEEqY2xpTlFeFN+aWqOyJMGJ/WCNg6ZUho0NSUaWFVHchZTkufzj5VXUN6dbJSxsTGX4x8urOHWfiVSV9nyYaG1jitrGJOOrSru0oJNzrvdEaWK6kmDdhlsI0n5/Dtgxn0EVSmMyg1lwJpFKB5VBywmWWe4Oa4DNjUmeW1rDvOWbtj5m9wmVHDpjVMGbkjJm/GX+Cv71+lpaOkRO2n0cp+49sdvNQS+9t5lkjk764niMRevr2Xvy8G7HW9+c4vv/eINHF6wjHhOlRXEuPmEWx+0+vtvHdM51T6Sfkmb2NhA3s7SZ/Qk4Iq9RFUgiJoSRzvryi/IdWtuc4rnlm0hmbOuch1dX1fLs0po8RhvN7S+v5l+vr6EpnaEpFVzufHU1/3qja8u1ZpswvCTn3yWZNsZW9Gyho4tvfY3HFqwjmTYakxk21ie55M43eHHZph4d1znXdVEqiHpJxcCLki6XdBEwKFN+D8samdTy/SeJmILr4hxNHTHBhsZku2GvqYzxworNHabm6Ct3vrqapjZzMZpSxu0vr+72MT+518R2+aUS4ZoYk0d0v39lzeYmnllcQ3PbeJMZrntiSZeO1ZRKc+9LK7n+8SW8trz7lYuZMXfBWq596G0efGVVqx8Pzg12UZqYPkvQ7/Bl4CKC5Uc/mc+gCiUmMXpYEas2NSOJOEbagvHxyXQm/FLM0JyxoNIApo0u480NdTmPl0oHZyOJ7i6C3UMZM7bkmDEMQbNYd+0wtoJvHbsDv3pkMQ3JNBkz9p5cxTeP6Vn67rW1TRTFRXOq9XYD3tsYfTnSd1bXcdoVc2lMpkmljZjE4TuP5crP79OlYaxbGlOc+svHeWvFJlIZIxGLMW54CXd84wjGVg3sgQbORREl3XfLLOoGhsCQ18qyBKs3NWMEZw0JBf0QRbE4YyuLGF5RRCImmtNGSSJGPCbGrtjEqtqmdscaVpIoaAdrTGJSVQkrNrePberInqUf/8CMkRw4fQRrapsoL070yryO6WPKSaXb/0JPxMR+06KvNvfFa+ezoa65VZ/RY2+t5W9zl3LGodMjH+eyO17ltWUbaQoHJzSRYdm6NF+7fj7Xf7m3V9x1rv/Z5s8pSYslLWp76W6BkkolPSvpJUmvSfpBuH2UpPslLQyvR3a3jJ4oScSoKou3amOXRFEixpiqEkqL4iTiMcqL41u//A+bMYpEm4ogEROHzxiVl3kB76yr58rHl3DJvQu49cWV1DalOnzs2QdtR3GbM5jiuDjzgCk9jiMmMaGqtNcm/VWUJDj7sGmUFb3/sYwpSH/x+UOmRTrG0nX1LN9Q325AQUNzmr88tbRL8fz96WVbK4cWqYzx8GurafaZ8G4IiPKfnT1WthQ4BRjVgzKbgKPMrE5SEfCEpH8BnwAeNLPLJF1MkCCwIGtOTBlVyoa6JOu3JMkYVJUmGFdV3OHZwMSqUj65x0SefreGdfXNjCgt4sCpI5iSh0WC5i6p4Zqnlm5NA7JkfQMPLVzPjz+yU84Je3tPruK7x+3IzS+sZPnGBqaOLOO0fScxa2z/7EY697DpTB1VznVPvsuGLc0cMGMkXzpiJhMizh1JpjMdVsq5zk460zKSrS0LJ046N9hFaWJa32bTryQ9AXyvOwVa0Gvb0mhfFF4MOJn3R0fNAR6hQBWEJEZXFjO6sjjyc8ZXlnDy7vnNAprOGH96ZnmrTtxkxqhrTnHnq6v57P65zwp2GT+M7x9fuJHJGQvW6I5yNiWJ43cfz/HdHNY6c1wFI8qLaGjT91JaFOPk6kldOtbx+0zi9meXtapYJKieOcoTLbohIUoT075Zl2pJXyRYE6LbJMUlvQisAe43s2eA8Wa2EiC8HteTMgajlZubco6iSWfgxfdqCxBR55bVNPDVv7/GMVfM5UNXPs2P/r2Auk6aw3qDJH7zuX0oL4lTEk4ILC+Os8P4YZz9wZldOtb3PrkH44eXbl37o6w4zojyYn5+5n69Hrdz/VGUJqafZ91OAUuAU3tSqJmlgb0ljQBul7R71OdKmg3MBpg6dWildagojnc4zLKypH/9ot3cmOS8m16hrimFASkzHl6wniXrG/jdZ/bMa86m6pmjePQ7R3Lbc8tZWdPIgTuM4pjdx3c5Ed+YqlIev/Q47pq3nJferWHHiZV84oCpVHWQVsW5wSZKE9OR+SrczDZKegQ4HlgtaaKZrZQ0keDsItdzrgGugSAXU75i649Glhexw9hyFqzZ0irNRUlcnLBr/zrhuvf1tTSnM606i1MZY/nGBl5bWcvueV7/eUxlCbOP2r7HxykrjnPqwdM49eBoneTODSZRcjF9tbP9ZvaLrhQoaSyQDCuHMuAY4CfAncCZwGXh9R1dOe5QccHhM/j5w4tYWtNAPFzG9MTdxnHA1O6nt8iHd9ZuaTcCCIIO3qU1DXmvIJxzPRd1FNP+BF/gAB8FHgOWdbPMicAcSXGCPpCbzexuSXOBmyWdAywlGC3l2qgqTfCDE2axYlMjNQ1Jpo8so6Kk/60tsdP4Ch59e33OSmL66PJeKSOVznD1Q4u48aml1DWmqJ4xkv85aWd2nNCjLjLnXGib6b4l3Qd80sxqw/uVwC1mdnwfxNep3k73DUHCvtqGoN18WGmcsqJYr7aXr69v5uklG9nUmGKncRXsNamq3RyKwaCuKcVn5zzP5sbU1my4RXExa2wFV5y6R5f/pgtW1XL78yvY0pjiqF3HcfisMVx88yv86+VVNCbfr4QqSuLc87VDmdzDiYDODWa9lu4bmAo0Z91vBqZ3M65+bcOWJDVbUlvbzWsb0wwrjTOusqhXKok31tRx7bPvkckEKTxeXFHLgws3cOFh07aOuBkshpUkuPrTe3LFo4t57t2NFMViHLvLGL5wyPQu/y1vfnYZl/9rAc2pYF2Of726mj0mV/HM2xvaTVhrSmX402NL+M7Ju/Tmy3FuSIpSQdwAPCvpdoL5Ch8nmKcwqCTTmVaVAwQvtq4xTVVpvMeL2WfM+PP8lSSzepeb08baumYeX1TDMbMG31rIE6pK+eFHe/ZFvakhyU/+uaBVU1VDc5rn391IrhRXqbTxsmd+da5XRBnF9MNwpvNh4aazzOyF/IbV9+qbO5g1C9Q1pXtcQazY3JRzJm8yY7zw3uZBWUFE9eaqWq58aBFvrKplXGUJ5xw6jWN2CUZlPbtoA4m4aDt9IpnOkMrRvxGPwU4ThvVF2M4NepF6N83seeD5PMdSUJ11A/RGF0FRTGQ6WHKoqIvj8weTt1bVMvuGF7b2I9Q2prj07jep2dLMKdVTOmx6i8XExJGlrNvc3OrsojgR5+wPzuiT2J0b7IbuN1Mb5R2cIQio7IVkdOOGFTOyrIi2dU1xXBw6I3qm0sHmt48upinZ+kygMZnh6kcXk0pnOGj70TlX5StJxPjpp/fkUwcElUhMsMukSubM3p8Z/TTPlHMDTf8bH1kg8ZiYMLyYVZuag1oh/LE/Zliix2s4Q5AC4j8PnMKVT7xLUzoTJnyDfadUsd+UoTsn4I1VtTnPq1JpY/2WZsZXlfL/PrsPX7o+OIE1CybcfeGImew/YxT7zxjF907ehVTGeuV9cs69L1IFIWkasKOZPRBObku0DHsdTCpK4swYU0p9cwbDWqX07g3jhhXz/Q/twFtrt1DblGLmqHLGDoueEHAwmji8lA1b2i9eZLA1O+2+00bw6MUf5ImF66lvSnHQ9qMYl7VgTyyWe7U/51zPRJlJfS5B7qNRwPbAFOC3wNH5Da0wYjG1Wnq0t8VjYtfx3ona4j8Pnc63bnuNxqx+hNJEjJP2ntgqY2ppUZxj+lk6EecGuyjn5OcBhwCbAcxsIZ5p1fWSQ3YYzTePn8XI8iKK46IkEeNj+0ziK8f0PI+Sc65nojQxNZlZc8vkJkkJ6GA4jnPd8OE9J3DCHuPZVJ+koqR3+nyccz0X5T/xUUnfBsokHQvcAtyV37DcUBOTGFlR7JWDc/1IlP/Gi4G1wCvAF4B/At/JZ1DOOecKL8pM6gzw+/DinHNuiIgyiukQ4BJgWvh4ESwt3bX1G51zzg0oUTqp/whcBMwH0tt4rHPOuUEiSgWxycz+lfdInHPO9SsdLhgkad/w5qlAHLgNaGrZHybwKyhJa4F3e3CIMcC6XgpnIBhqrxf8NQ8V/pq7ZpqZjd3WgzqrIB7u5HlmZkd1M7B+Q9K8KKsqDRZD7fWCv+ahwl9zfnTYxGRmR4ZBzDSzRW0C8w5q55wb5KLMg7g1x7ZbejsQ55xz/UuHZxCSdgZ2A4ZL+kTWriqgNPezBpxrCh1AHxtqrxf8NQ8V/przoLM+iJOBjwEnAXdm7aoF/mZmT+U7OOecc4XTYQWx9QHSB8xsbh/F45xzrp/YZh/EYKwcJC2R9IqkFyXNK3Q8+SDpWklrJL2atW2UpPslLQyvRxYyxt7WwWu+RNJ74Xv9oqQTCxljb5O0naSHJb0h6TVJF4bbB+V73cnrHbTvs6RSSc9Keil8zT8It+f9Pd7mGcRgJGkJUG1mg3bctKTDgTrgejPbPdx2ObDBzC6TdDEw0sy+Wcg4e1MHr/kSoM7MflbI2PJF0kRgopk9L6mSIOPBx4DPMwjf605e76kM0vdZwVoLFWZWJ6kIeAK4EPgEeX6POzyDyKqZD+nNAl3fMLPHgA1tNp8MzAlvzyH4xxo0OnjNg5qZrWyZtBouA/wGMJlB+l538noHLQvUhXeLwovRB+9xZ01MZ4XXV/R2of2AAfdJmi9pdqGD6UPjzWwlBP9oDJ2VAb8s6eWwCWpQNLXkImk6sA/wDEPgvW7zemEQv8+S4pJeBNYA95tZn7zHnVUQb4RNMTuFf/SWyyuSXu7tQPrYIWa2L3ACcF7YNOEGp6sJ1lLfG1gJ/Lyw4eSHpGHA34GvmNnmQseTbzle76B+n80sbWZ7A1OAAyTt3hfldjaT+jOSJgD/JhjqOmiY2Yrweo2k24EDgMcKG1WfWC1popmtDNty1xQ6oHwzs9UttyX9Hri7gOHkRdgu/XfgRjO7Ldw8aN/rXK93KLzPAGa2UdIjwPH0wXvc6SgmM1tlZnsR1MiV4WWFmfUkQV5BSaoIO7eQVAF8CHi182cNGncCZ4a3zwTuKGAsfSL8x2nxcQbZex12YP4ReMPMfpG1a1C+1x293sH8PksaK2lEeLsMOAZ4kz54j6PMg/ggcD2whGCxoO2AM8MOwQEnzCN1e3g3AfzFzH5YwJDyQtJfgSMIMj6uBr4P/AO4GZgKLAVOMbNB06nbwWs+gqDZwQg+w19oabcdDCQdCjxOsCRwJtz8bYJ2+UH3Xnfyej/DIH2fJe1J0AkdJ/hRf7OZXSppNHl+j6NUEPOB/zCzt8L7s4C/mtl+vRmIc865/iVKsr6ilsoBwMwWEAyzcs45N4hFWVFunqQ/AjeE908nmJzinHNuEIvSxFQCnAccStAH8RhwlZk1dfpE55xzA9qQTLXhnHNu26L0QTjnnBuCvIIYYiT9UtJXsu7/W9Ifsu7/XNJXu3nsuhzbpmdnVx1oJE2UdHd4u1rSb3rhmI9IareWcPbxJX1e0pXh7Usk/Xd4+1JJx/Q0hq7GVggdfXYk7SHpugKENOREriDCSWVu4HsKOBhAUoxgzsBuWfsPBp4sQFz91VeB3wOY2TwzuyBfBUU5vpl9z8weyFcMA4GZvQJMkTS10LEMdtusICQdLOl1gqyJSNpL0lV5j8zly5OEFQRBxfAqUCtpZDggYRfgBQBJX5f0XJiD6wctB5B0Rpif/kVJv5MUzy5A0hhJcyV9uM32xyXtnXX/yXASUPZj/tmyTdILkr4X3v5fSf8paZikByU9H+YFOznrud+V9KaC3Ph/zfrVvb2kexUkZ3xcwXK6SDpF0qsK8ux3NPHzk8C94eOPyDqbuERBUrhHJC2S1O6LXUGCtevCMl6RdFHW7lPCv+ECSYe1PX5HwuN9Kry9RNIPsv4WLa9rbPg3eD58f94N35MKSfeEr/dVSad1UMwZkp4KH3OApJiCNQfGhsePSXpb0pg2sb0iaYQC6yV9Ltx+g6Rjwr/HT7M+U1/Iem7Oz1rW/pnh52H/cNNdwKc7+1u5notyBvFL4DhgPYCZvQR4crsBKsxDlQp/fR0MzCWYdfsBoBp42cyaJX0I2JEgT9XewH6SDpe0C3AaQcLDvYE0wdBnACSNB+4Bvmdm97Qp/g8E6xS0TLgsMbO2iR8fAw6TVAWkgJZ08y0zaBuBj4fJFo8Efh5+IVUTfJnvQ5AnP7uZ5Brg/HBy538DLT9wvgccF6aTaZdvTNIMoKaTEXs7E/xvHAB8X0GOoGx7A5PNbHcz2wP4U9a+hJkdAHyFYMZ3d60L/xZXE7w2wuM9FG6/nWCmLQT5e1aY2V7hehn3dnDMCjM7GPgv4FozywB/5v33+RjgpRzrqTxJ8H7tBiwCDgu3HwQ8DZwDbDKz/YH9gXMlzejos9ZyUEk7EeReOsvMngs3z8s6vsuTSE1MZraszaZ0HmJxfaflLKKlgpibdb9lrfEPhZcXgOcJvgx3BI4G9gOeU5B++GhgZvicIuBB4Btmdn+Ocm8BPhJ+kZ4NXJfjMY8T/AA5lKCiGSapHJgeTtgU8CMFGYUfIFgLYHz4+DvMrCFcJ+Au2Jr182DgljDe3wEteXueBK6TdC5BGoO2JgJrc2xvcY+ZNYVflGvCOLItAmZKukLS8UB2ltWWpHrzgemdlLEtuY5zKPA3ADO7F6gJt78CHCPpJ5IOM7NNHRzzr+FzHwOqFOQBuhb4XLj/bFpXdi1a3rvDCSqsPSRNJljUpo7g8/S58H14BhhN8Jnq6LMGMJYgx9AZZvZiVllrgEkd/1lcb4gyUW6ZpIMBk1QMXEDY3OQGrJZ+iD0ImpiWAV8j+AK7NnyMgB+b2e+ynyjpfGCOmX0rx3FTBF9UxwGPtt1pZvWS7idY6ORUWv/Kb/FcuH0RcD9BH8m5vD8583SCL439zCypICV9aRhvLjFgY3i20zaeL0o6EPgw8KKkvc1sfdZDGsJjdyT7zCJNm/8nM6uRtBfB3+M8gtd8dpvntnteF+U6Ts6/hZktkLQfcCLwY0n3mdmluR7a/qm2TNJqSUcBB5J11pjlMYLXORX4H4KkeZ8iqDha4jrfzP6d/SRJx5H7szYd2ETw+TwEeC1rdynB++PyKMoZxBcJ3vTJwHKCU8Dz8hmUy7sngY8Q/LJLhwm+RhA0M7WsQf5v4OzwFziSJksaR3CG8Knwdsu6uNPC5xjBF+DOCpZAzOUPwG+A53IlFjOzZoIvhFMJmiUeJ2g6afmSGQ6sCSuHI4GWsp/g/7d3/yByVVEcx78nKCoKsBwAAAO3SURBVKgsCxErxSiaRLEIKDZCiqCVEEGLoIhYWAhbBawsomAhFjFYBkQJgagYlOAfBBXBZSUajeIS2ELUuLYKkcimSLL+LM4Zd0zePMfszs7szO9T7Tz2vbk77+2cd8+971x4KHL93inyS59aK+B0ROyp9kZ9aRMRt0s6Iel54HeyEGW3H1jF3X3l6DdJehd4DrjnSo/1P31Bfn5U+mZz/XwjcE7SEeDllvY8Wr+/k0wJdXoar5GppqOSLssiVKbhBmCbpJ+rHd3n7mNgppOKi4jtkZNfel1rAOfJldKejIjHu95uO2NUsXVU/eedS3Wfm+4WbOM6Rf4jv3nJtqlOXlnSJzXe8GVEQK71/ISkhYjYR67Itwm4QN4wLNZ+yxHxGPBBRJwFPup+Y0nf1vamFEXHHPBA9TjmyEVSOl8yb9SxTwLfk2WPkfRNRLwPzFdbTpJ3n5DX78Fq99Vk+mUe2B8R28g7289qW3dblyLip4jYKunHtg+0h5uAQ/U5ATT1ugbhBeCtGoSeJcv1/0lWtt0fEX+R522mx/5nIuI4MM1KjweyvPQh2s/dCVbSdXPAS2SggAwwtwLfRV5UvwEP97rWqFR2nYfdwKcRsSTpPXL86dIxLltj/ZTaOAzslfRHvd4MHJD0VOuOZg3qLvZz4M4a/FzLY08pF3a/jkx3PK1av3gVx3yETGftW5NGroPI2WjLki5GxH3AwaYU2xUc917gFUlDHRyuv28W2Cnp4jDbMu76yX3u6AQH+CevevcA22RjqqY9vgg8s9bBobwaEXeR+enDqw0OAJKORdbd30i2AEer53KeHMNZlUoZzjAa2YQtwLMODoPXTw9iHtgl6Uy9vh6YrWl7ZmY2pvrpQRwAjkfEO/V6D3kXaGZmY6yvaq7Vbb+fGsyTtDDohpmZ2XD1DBARMS3pbKWULjMO69uamVlvbQHiQ0m7I+I0/35wJsgHZ25r3NHMzMZCa4qp5irfLOnX9WuSmZmNgtYnqZXR49g6tcXMzEZIP6U2vuoqsWtmZhOin+cgFoA7gF+AJVbGIHa07WdmZhtbPwHilqbtkhYH0iIzMxsJPR+Ui4hryEquW8lCbq/70XYzs8nRNs31bbLi4xzwILAoae86ts3MzIaoLUCc6tRbioirgK9rCUMzM5sAbbOYLnR+cGrJzGzytPUglslZS5Azl64FzrEyi2l6XVpoZmZD0VexPjMzmzz9PChnZmYTyAHCzMwaOUCYmVkjBwgzM2vkAGFmZo0cIMzMrNHfU8gClFWh+WUAAAAASUVORK5CYII=\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.scatter(data['Wages'],data['Wheat'], c=data['Year'], cmap = 'Blues')\n", "plt.xlabel('Weekly wages (in shillings by week)')\n", "plt.ylabel('Price of the quarter of wheat (in shillings by quarter of wheat)')\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Conclusion\n", "\n", "Parmi tous ces graphiques, le plus adapté pour moi est le graphique qui représente directement l'évolution du pouvoir d'achat dans le temps. On voit bien l'augmentation progressive du pouvoir d'achat jusqu'aux années 1700, puis une augmentation brutale jusqu'en 1730 avant une stabilisation puis une diminution. \n", "C'est le comportement global, mais en regardant chaque année, on constate que l'évolution est \"en dents de scies\" : une année à fort pouvoir d'achat est souvent suivie d'une année à plus faible pouvoir d'achat, et inversement. Grace aux autres graphiques, on comprend que ce comportement est directement du à la fluctuation forte d'une année sur l'autre du prix du blé, car le salaire est lui en constante augmentation sur la période de temps étudiée." ] } ], "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 }