From 338300a432f4ca3338bca718b5fedf65db735afc Mon Sep 17 00:00:00 2001 From: 521adc37f04e8509ebf5ce131815aa0a <521adc37f04e8509ebf5ce131815aa0a@app-learninglab.inria.fr> Date: Mon, 8 Feb 2021 10:45:47 +0000 Subject: [PATCH] =?UTF-8?q?Repr=C3=A9sentation=20graphique=20du=20prix=20d?= =?UTF-8?q?u=20bl=C3=A9=20et=20des=20salaires?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- module3/exo3/exercice.ipynb | 539 ++++++++++++++++++++++++++++++++++++ 1 file changed, 539 insertions(+) diff --git a/module3/exo3/exercice.ipynb b/module3/exo3/exercice.ipynb index c995249..9e47697 100644 --- a/module3/exo3/exercice.ipynb +++ b/module3/exo3/exercice.ipynb @@ -570,6 +570,545 @@ "data[data.isnull().any(axis = 1)]" ] }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "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" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Supprimer la ligne qui ne contient pas de données valables\n", + "# Copier les données\n", + "my_data = data.dropna().copy()\n", + "my_data" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Représentation graphique du prix du blé " + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([18., 8., 16., 3., 0., 1., 1., 2., 0., 1.]),\n", + " array([26. , 33.3, 40.6, 47.9, 55.2, 62.5, 69.8, 77.1, 84.4, 91.7, 99. ]),\n", + " )" + ] + }, + "execution_count": 41, + "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.hist(my_data[\"Wheat\"])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Représentation grahique des salaires" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 65, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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E72sJokhcOWKhm1ka8BZQP/z+f7n7PWbWDHgR6AhsBi539/zIRZWjUloKU6bgjz+OLVlCTtcTGfvL5wi5U/mDe4NOJyIRUJ1li6XAYHfvA/QFLjCz04E7gNnu3g2YHX4t0WDyZLxDB7j6anbtyueZa+7k1p//hfJKpzIUdDgRiZQjjtDd3YHC8MuU8B8HRgCDwtsnAXOB22s9oRxZZSW8/Tb07El+42a8n1tO09bdmHX1PSzuMUDTKiIJolpz6GaWDCwBugIT3D3bzFq5ew6Au+eYWcvD/OwYYAxA+/btaye1QHk5zJkD//oX/tJLWF4e879/IxPOvw5v3oeKmx8POqGI1LFqFbq7VwJ9zawp8B8zO6m6H+DuE4GJAFlZWVpHURPuVaPt8nK8fXts1y7K0o5jSe+BLL7iPLJ7nUm5rugUSVhHtcrF3feb2VzgAiDXzDLDo/NMYHckAia8oiKYNQumTqUibw9vTfgHczfso+ugUexp1Y7FPU+jLDUt6JQiEgWqs8olAygPl3kD4Dzg18B0YDQwPvw4LZJBE86cOTBhAj5zJnbwIIVN0snuN4hnF2zhYMhYPfT7QScUkShTnRF6JjApPI+eBExx91fMbAEwxcyuA7YCl0UwZ/zbtw+mT4eLL2ZvgybsnLOIDm/OY8EZF7N4wPm836UPoeR6oFUqInIY1VnlsgLod4jte4EhkQiVMHJz4aWXYOpUfM4crKKCyT/5Fa/0v4B6HQdR8pvBeJJuiCki1aMrRetaeTmkpEBuLt6mDRYKsbt1exYMu4r3Th3CuuN7QMgpt3qg1YYichRU6HWhshKeegqfNIni5i2Zdt+fmPfRPk678jbWduvLxjZdtVZcRGpMhR5pH3wA110H2dls69iDtzqdycsrc6l0mDlIpx1EpPao0CNp5kz8kksoPq4Rf/vxr5h76tCqkbiWiotIBKjQI6GsDE9J4e3WPSg559tM+X8/Yn/j9KBTiUicU6HXpuJiuOceyl9/gwfve44NBZWUjrot6FQikiC0Jq62zJ2L9+4Njz7KW827snHXAUortGhcROqORug1VVQEY8fCxInsbX08f7ljIsu69w86lYgkIBV6DVXUS+Hjtxfy7gVX8cKI6ymt3yDoSCKSoFTox6KgAMaNY/PPxvHo8v18fOtTFJv+pxSRYKmFjtZHH+EjRuBr1/Kvel3Z1edsUJmLSBRQEx2NN97Ar7iCkgrn9z//I0t7DAg6kYjIp1To1fXii/ioUeS068Kvf/JbdjRvG3QiEZEvUKFX0/qe/dk26Nv87bKbOVj/uKDjiIh8hQr967jD88+z6IwL+P3yAsquHBd0IhGRw9KFRV/nl7+Eq69m8SNPUlapG7CISHRToR/O738PDz3EnHMuZfbpw4NOIyJyRCr0Q5k0CcaO5b1Th/DkVeN0r3IRiQmaQ/+y/fsJ3XILa088jd//8EFCSclBJxIRqRYV+pcUpDXisXFPs75xS8pTUoOOIyJSbSr0TyxbRtn8d7i73WB2tuyEzoGKSKxRoQPs2oUPG0YRKRy4vw+V9RsGnUhE5Kip0AGmTMHy8njk/hf4WGUuIjFKq1wApk0jp21n1rfrHnQSEZFjpkLPz8fnzeO9vucEnUREpEZU6Pv2kXvWEBZlDQ46iYhIjWgOvUsXfnvLY2zadzDoJCIiNZLYhV5WRuH2HLbtLwk6iYhIjSX2lMucOTTq0pGTPlwSdBIRkRpL7EJ/+WXK6jdgdfteQScREamxIxa6mR1vZnPMbI2ZfWBmN4e3NzOzN8xsffgxPfJxa5cvXcqGTr0oS00LOoqISI1VZ4ReAfzc3XsCpwM3mlkv4A5gtrt3A2aHX8cOd3ztWnZmdgw6iYhIrThiobt7jrsvDT8vANYAbYERwKTw2yYBl0QqZETs2UNSfj65KnQRiRNHtcrFzDoC/YBsoJW750BV6ZtZy1pPF0lpaawY/0eWeWbQSUREakW1T4qaWSNgKnCLu398FD83xswWm9nivLy8Y8kYGY0bM+OUYWxu1THoJCIitaJahW5mKVSV+WR3/3d4c66ZZYb/PhPYfaifdfeJ7p7l7lkZGRm1kbnmNm6k8K572LBhZ9BJRERqTXVWuRjwV2CNu//uc381HRgdfj4amFb78SLkt7+lwSPjSSnR1aEiEj+qM4c+ELgKWGlmy8Pb7gTGA1PM7DpgK3BZZCLWsvx8/JlneOuMi9jTNEr+xSAiUguOWOjuPh843LckD6ndOHVgxgyspITZgy4NOomISK1KvCtFp0/nQHoG63R1qIjEmYQr9HI33s06D09KuF0XkTiXcHdbfPfhPzF5wTaoCAUdRUSkViXcMHXp9gOUqMxFJA4lVqHfdBMj/v/IoFOIiEREYhX6ypWUV3rQKUREIiJxCt2d0Jo17GzdIegkIiIRkTiFvn49SXl5bOp6ctBJREQiInEKfe5cAN7v1i/YHCIiEZI4hd61KwuGXsaOVppyEZH4lDDr0EvPHsTj29IhpJOiIhKfEqPQCwvZunoTKUm6nkhE4ldiTLm8/jrdTutNh/Urgk4iIhIxiVHo2dlU1kvho3bdg04iIhIxiVHoCxeypX13ylPqB51ERCRi4r/QS0rw7GzWdNdyRRGJb/Ff6NnZWGkp63r0DzqJiEhExf8ql969mXH3H1jeUleIikh8i/9CT0/n3z3OprikIugkIiIRFd9TLvv28fGDD5Oalxt0EhGRiIvvQp8xgya/vJPme3cFnUREJOLiu9CnTQt/IXTPoJOIiERc/Bb6wYP4rFm81+dsfSG0iCSE+G26mTOxoiIWnXZ+0ElEROpE/Bb62rUcaNaS5V11QZGIJIa4XbZ44Oe3cVPLIYSS43YXRUS+IG5H6Nmb9xNKSws6hohInYnPQr//fk644mLKynQxkYgkjvgs9LlzCRUWanWLiCSU+Gu8ykp80SI+7HRS0ElEROpU/BX6nDlYYSEbTugbdBIRkTp1xEI3s2fMbLeZrfrctmZm9oaZrQ8/pkc2ZjW5w/33c6B5K97uc27QaURE6lR1RujPAhd8adsdwGx37wbMDr+OCjtHfp/nL/spFSmpQUcREalTR1yk7e5vmVnHL20eAQwKP58EzAVur8Vcx8aMP3UZxNrGRUEnERGpc8d61U0rd88BcPccM2t5uDea2RhgDED79u2P8eOqYcsW9kz+J3lN+0ODb0Tuc0REolTET4q6+0R3z3L3rIyMjMh90LRptPifX1CvoCBynyEiEsWOtdBzzSwTIPy4u/YiHaPXX2d36/bktmwXdBIRkUAca6FPB0aHn48GptVOnGNUWorPmcOyE08PNIaISJCqs2zxBWABcIKZbTez64DxwPlmth44P/w6OAsXYsXFfHDyGYHGEBEJUnVWuXzvMH81pJazHLs1a6hMrqdb5YpIQouPe8v++Mf8pH5fitHacxFJXHFx6f/eojLyk+sHHUNEJFCxX+iLF5M0bCjH79wUdBIRkUDFfqHPn0/6O/PIT20YdBIRkUDFfqFnZ5PfvBX56RG8aElEJAbEdqG74wsXsk73PhcRifFCf/hhbPNmVvU5M+gkIiKBi+lli7tOO4ulF1zJrDNHBB1FRCRwsVnoW7eyp1lrxuU2oeDynwWdRkQkKsTelMvixXiPHrw29kGKyiqDTiMiEjVir9B//WuKUxsw7+SzCXnQYUREokdsFXppKT5rFu/2O5d9jZoFnUZEJKrEVqG/+SZWWMiy/oOCTiIiEnViq9CnTaMs7TiWde8fdBIRkagTU6tcKv/nLu5sfx7lKboRl4jIl8XUCL2gRSt2tOsSdAwRkagUO4XuTmj8eLpuWRN0EhGRqBQ7hZ6fT7P776bHumVBJxERiUqxU+jbtwOwt6nuqigiciixU+hbtgCQk9464CAiItEpdgp982YAclu0CTaHiEiUiqlCL0tN4+PG6UEnERGJSrGzDv3hh7m963AwCzqJiEhUip0RemoqOcdpdC4icjgxU+jl997HqYv+G3QMEZGoFTOFnvz4Y5y8bknQMUREolZsFPr+/STt38++5lqyKCJyOLFR6OvWAbCzdYeAg4iIRK/YKPS1awHY3FKFLiJyOLFR6Lt3U56SSm5G26CTiIhErRoVupldYGbrzGyDmd1RW6G+4he/4JZnF1JZLyViHyEiEuuOudDNLBmYAFwI9AK+Z2a9aivYl1Ukx841UCIiQajJCH0AsMHdN7p7GfC/wIjaiSUiIkerJoXeFtj2udfbw9sioiLkkfpPi4jEhZrMYxzqpipfaV0zGwOMAWjfvv0xf1hmk/oUlFaQmhwb53FFRD4vo1FqxD+jJoW+HTj+c6/bATu//CZ3nwhMBMjKyjrmYfaDw0841h8VEUkINRnuLgK6mVknM0sFvgtMr51YIiJytI55hO7uFWZ2E/AakAw84+4f1FoyERE5KjVaC+juM4GZtZRFRERqQGcYRUTihApdRCROqNBFROKECl1EJE6o0EVE4oS5190l9WaWB2w5xh9vAeypxTixQPucGLTPiaEm+9zB3TOO9KY6LfSaMLPF7p4VdI66pH1ODNrnxFAX+6wpFxGROKFCFxGJE7FU6BODDhAA7XNi0D4nhojvc8zMoYuIyNeLpRG6iIh8jZgodDPbbGYrzWy5mS0OOk8kmNkzZrbbzFZ9blszM3vDzNaHH9ODzFjbDrPP95rZjvCxXm5mFwWZsTaZ2fFmNsfM1pjZB2Z2c3h73B7nr9nneD7OaWb2npm9H97n+8LbI36cY2LKxcw2A1nuHrfrVs3sbKAQ+Lu7nxTe9giwz93Hm9kdQLq73x5kztp0mH2+Fyh090eDzBYJZpYJZLr7UjNrDCwBLgGuIU6P89fs8+XE73E2oKG7F5pZCjAfuBn4NhE+zjExQk8E7v4WsO9Lm0cAk8LPJ1H1ixA3DrPPccvdc9x9afh5AbCGqu/hjdvj/DX7HLe8SmH4ZUr4j1MHxzlWCt2B181sSfg7ShNFK3fPgapfDKBlwHnqyk1mtiI8JRM30w+fZ2YdgX5ANglynL+0zxDHx9nMks1sObAbeMPd6+Q4x0qhD3T3U4ALgRvD/1SX+PQk0AXoC+QAvw02Tu0zs0bAVOAWd/846Dx14RD7HNfH2d0r3b0vVd+1PMDMTqqLz42JQnf3neHH3cB/gAHBJqozueE5yE/mIncHnCfi3D03/MsQAp4izo51eE51KjDZ3f8d3hzXx/lQ+xzvx/kT7r4fmAtcQB0c56gvdDNrGD6Zgpk1BIYCq77+p+LGdGB0+PloYFqAWerEJ/+HD7uUODrW4ZNlfwXWuPvvPvdXcXucD7fPcX6cM8ysafh5A+A8YC11cJyjfpWLmXWmalQOVd+B+g93fyjASBFhZi8Ag6i6I1sucA/wEjAFaA9sBS5z97g5iXiYfR5E1T/DHdgMXP/JvGOsM7NvAm8DK4FQePOdVM0px+Vx/pp9/h7xe5x7U3XSM5mqQfMUd7/fzJoT4eMc9YUuIiLVE/VTLiIiUj0qdBGROKFCFxGJEyp0EZE4oUIXEYkTKnQRkTihQhcRiRMqdBGROPF/msxUM4yeE9cAAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(my_data[\"Wages\"], my_data[\"Unnamed: 0\"], \"r--\")\n", + "\n", + " \n", + "x = my_data[\"Wages\"]\n", + "y1 = my_data[\"Unnamed: 0\"]\n", + " \n", + "plt.fill_between(x, y1, color='#539ecd')" + ] + }, { "cell_type": "code", "execution_count": null, -- 2.18.1