{ "cells": [ { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "import matplotlib.pyplot as plt\n", "import pandas as pd" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "data_url = \"https://raw.githubusercontent.com/vincentarelbundock/Rdatasets/master/csv/HistData/Wheat.csv\"" ] }, { "cell_type": "code", "execution_count": 5, "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": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data = raw_data.dropna().copy()\n", "data" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "ename": "NameError", "evalue": "name 'data' is not defined", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Year'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0my1\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Wages'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0my2\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Wheat'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'r'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabel\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'Wages'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfill_between\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'b'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0malpha\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0.5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mNameError\u001b[0m: name 'data' is not defined" ] } ], "source": [ "x=data['Year']\n", "y1=data['Wages']\n", "y2=data['Wheat']\n", "plt.plot(x, y1, color='r', label = 'Wages')\n", "plt.fill_between(x, -1, y1, color='b', alpha=0.5)\n", "plt.bar(x,y2, color='k', label = 'Wheat')\n", "plt.xticks(x, rotation=90, size =20)\n", "plt.grid()\n", "plt.legend()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "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 }