{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# MOOC Recherche Reproductible\n", "\n", "# Exercice Module 3 - Document computationnel (2020.04)\n", "\n", "# **Sujet 2 : le pouvoir d'achat des ouvriers anglais du XVIe au XIXe siècle**\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Introduction\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://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), 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. \n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Objective\n", "1. Reproduire le graphe de Playfair à partir des données numériques.\n", "2. Améliorer la présentation de ces données.\n", "3. Mieux présenter l'information que le pouvoir d'achat des ouvriers avait augmenté au cours du temps." ] }, { "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": [ "## 0 Récuperation des données\n", "- Des valeurs obtenues par numérisation du graphe sont aujourd'hui téléchargeables, avec la version en format CSV sur [ce site](https://raw.githubusercontent.com/vincentarelbundock/Rdatasets/master/csv/HistData/Wheat.csv).\n", "\n", "1) Déposer le fichier csv en locale si ce fichier local n'existe pas. \n", "\n", "\n", "2) Lisez le fichier CSV local." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", " | Unnamed: 0 | \n", "Year | \n", "Wheat | \n", "Wages | \n", "
---|---|---|---|---|
0 | \n", "1 | \n", "1565 | \n", "41.0 | \n", "5.00 | \n", "
1 | \n", "2 | \n", "1570 | \n", "45.0 | \n", "5.05 | \n", "
2 | \n", "3 | \n", "1575 | \n", "42.0 | \n", "5.08 | \n", "
3 | \n", "4 | \n", "1580 | \n", "49.0 | \n", "5.12 | \n", "
4 | \n", "5 | \n", "1585 | \n", "41.5 | \n", "5.15 | \n", "
5 | \n", "6 | \n", "1590 | \n", "47.0 | \n", "5.25 | \n", "
6 | \n", "7 | \n", "1595 | \n", "64.0 | \n", "5.54 | \n", "
7 | \n", "8 | \n", "1600 | \n", "27.0 | \n", "5.61 | \n", "
8 | \n", "9 | \n", "1605 | \n", "33.0 | \n", "5.69 | \n", "
9 | \n", "10 | \n", "1610 | \n", "32.0 | \n", "5.78 | \n", "
10 | \n", "11 | \n", "1615 | \n", "33.0 | \n", "5.94 | \n", "
11 | \n", "12 | \n", "1620 | \n", "35.0 | \n", "6.01 | \n", "
12 | \n", "13 | \n", "1625 | \n", "33.0 | \n", "6.12 | \n", "
13 | \n", "14 | \n", "1630 | \n", "45.0 | \n", "6.22 | \n", "
14 | \n", "15 | \n", "1635 | \n", "33.0 | \n", "6.30 | \n", "
15 | \n", "16 | \n", "1640 | \n", "39.0 | \n", "6.37 | \n", "
16 | \n", "17 | \n", "1645 | \n", "53.0 | \n", "6.45 | \n", "
17 | \n", "18 | \n", "1650 | \n", "42.0 | \n", "6.50 | \n", "
18 | \n", "19 | \n", "1655 | \n", "40.5 | \n", "6.60 | \n", "
19 | \n", "20 | \n", "1660 | \n", "46.5 | \n", "6.75 | \n", "
20 | \n", "21 | \n", "1665 | \n", "32.0 | \n", "6.80 | \n", "
21 | \n", "22 | \n", "1670 | \n", "37.0 | \n", "6.90 | \n", "
22 | \n", "23 | \n", "1675 | \n", "43.0 | \n", "7.00 | \n", "
23 | \n", "24 | \n", "1680 | \n", "35.0 | \n", "7.30 | \n", "
24 | \n", "25 | \n", "1685 | \n", "27.0 | \n", "7.60 | \n", "
25 | \n", "26 | \n", "1690 | \n", "40.0 | \n", "8.00 | \n", "
26 | \n", "27 | \n", "1695 | \n", "50.0 | \n", "8.50 | \n", "
27 | \n", "28 | \n", "1700 | \n", "30.0 | \n", "9.00 | \n", "
28 | \n", "29 | \n", "1705 | \n", "32.0 | \n", "10.00 | \n", "
29 | \n", "30 | \n", "1710 | \n", "44.0 | \n", "11.00 | \n", "
30 | \n", "31 | \n", "1715 | \n", "33.0 | \n", "11.75 | \n", "
31 | \n", "32 | \n", "1720 | \n", "29.0 | \n", "12.50 | \n", "
32 | \n", "33 | \n", "1725 | \n", "39.0 | \n", "13.00 | \n", "
33 | \n", "34 | \n", "1730 | \n", "26.0 | \n", "13.30 | \n", "
34 | \n", "35 | \n", "1735 | \n", "32.0 | \n", "13.60 | \n", "
35 | \n", "36 | \n", "1740 | \n", "27.0 | \n", "14.00 | \n", "
36 | \n", "37 | \n", "1745 | \n", "27.5 | \n", "14.50 | \n", "
37 | \n", "38 | \n", "1750 | \n", "31.0 | \n", "15.00 | \n", "
38 | \n", "39 | \n", "1755 | \n", "35.5 | \n", "15.70 | \n", "
39 | \n", "40 | \n", "1760 | \n", "31.0 | \n", "16.50 | \n", "
40 | \n", "41 | \n", "1765 | \n", "43.0 | \n", "17.60 | \n", "
41 | \n", "42 | \n", "1770 | \n", "47.0 | \n", "18.50 | \n", "
42 | \n", "43 | \n", "1775 | \n", "44.0 | \n", "19.50 | \n", "
43 | \n", "44 | \n", "1780 | \n", "46.0 | \n", "21.00 | \n", "
44 | \n", "45 | \n", "1785 | \n", "42.0 | \n", "23.00 | \n", "
45 | \n", "46 | \n", "1790 | \n", "47.5 | \n", "25.50 | \n", "
46 | \n", "47 | \n", "1795 | \n", "76.0 | \n", "27.50 | \n", "
47 | \n", "48 | \n", "1800 | \n", "79.0 | \n", "28.50 | \n", "
48 | \n", "49 | \n", "1805 | \n", "81.0 | \n", "29.50 | \n", "
49 | \n", "50 | \n", "1810 | \n", "99.0 | \n", "30.00 | \n", "
50 | \n", "51 | \n", "1815 | \n", "78.0 | \n", "NaN | \n", "
51 | \n", "52 | \n", "1820 | \n", "54.0 | \n", "NaN | \n", "
52 | \n", "53 | \n", "1821 | \n", "54.0 | \n", "NaN | \n", "