no commit message

module3/exo3/exercice.ipynb

@@ -4,23 +4,26 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Sujet 3 : L'épidémie de choléra à Londres en 1854"
+    "# Sujet 2 : le pouvoir d'achat des ouvriers anglais du XVIe au XIXe siècle"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Paths"
+    "## Libraries"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [],
    "source": [
-    "path_data"
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "from matplotlib.pyplot import figure\n",
+    "import pandas as pd"
    ]
   },
   {
@@ -30,19 +33,176 @@
    "outputs": [],
    "source": []
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Definition des paths et chargement des données"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Unnamed: 0</th>\n",
+       "      <th>Year</th>\n",
+       "      <th>Wheat</th>\n",
+       "      <th>Wages</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1565</td>\n",
+       "      <td>41.0</td>\n",
+       "      <td>5.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>1570</td>\n",
+       "      <td>45.0</td>\n",
+       "      <td>5.05</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>1575</td>\n",
+       "      <td>42.0</td>\n",
+       "      <td>5.08</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>1580</td>\n",
+       "      <td>49.0</td>\n",
+       "      <td>5.12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>1585</td>\n",
+       "      <td>41.5</td>\n",
+       "      <td>5.15</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Unnamed: 0  Year  Wheat  Wages\n",
+       "0           1  1565   41.0   5.00\n",
+       "1           2  1570   45.0   5.05\n",
+       "2           3  1575   42.0   5.08\n",
+       "3           4  1580   49.0   5.12\n",
+       "4           5  1585   41.5   5.15"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "path_data_url = \"https://raw.githubusercontent.com/vincentarelbundock/Rdatasets/master/csv/HistData/Wheat.csv\"\n",
+    "\n",
+    "data = pd.read_csv(path_data_url)\n",
+    "\n",
+    "data.head()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "## 1: Reproduction de la figure de Playfair"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "\n",
+    "figure(num=None, figsize=(10, 6))\n",
+    "plt.rcParams.update({'font.size': 14})\n",
+    "\n",
+    "# Salaire\n",
+    "plt.plot(data.Year, data.Wages, color=\"r\")\n",
+    "plt.fill_between(data.Year, 0, data.Wages, color=\"b\", alpha=0.1)\n",
+    "\n",
+    "# Prix du blé\n",
+    "plt.bar(data.Year, data.Wheat, width=5, edgecolor=\"k\", facecolor=[0.6, 0.6, 0.6], alpha=0.3)\n",
+    "\n",
+    "plt.xlabel('5 years each division')\n",
+    "plt.ylabel('Price of the quarter of wheat in Schilings')\n",
+    "plt.tight_layout\n",
+    "plt.show()\n"
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "\n",
+    "figure(num=None, figsize=(10, 6))\n",
+    "plt.rcParams.update({'font.size': 14})\n",
+    "\n",
+    "# Salaire\n",
+    "plt.plot(data.Year, data.Wages, color=\"r\")\n",
+    "plt.fill_between(data.Year, 0, data.Wages, color=\"b\", alpha=0.1)\n",
+    "\n",
+    "# Prix du blé\n",
+    "plt.bar(data.Year, data.Wheat, width=5, edgecolor=\"k\", facecolor=[0.6, 0.6, 0.6], alpha=0.3)\n",
+    "\n",
+    "plt.xlabel('5 years each division')\n",
+    "plt.ylabel('Price of the quarter of wheat in Schilings')\n",
+    "plt.tight_layout\n",
+    "plt.show()\n",
+    "\n",
+    "\n"
+   ]
   }
  ],
  "metadata": {