bar chart

matpltlib/4_bar_chart.ipynb

@@ -0,0 +1,138 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "year=np.array([2014,2015,2016, 2017])\n",
+    "revenue=[86,93,85,89]\n",
+    "profit=[22,12,16,21]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Container object of 4 artists>"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXsAAAD8CAYAAACW/ATfAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAADdZJREFUeJzt3H+sX3ddx/Hnm95tysaP1l5uyobcajoJmsCWGyLyI4Ri\nEIa0kWQpEVJ1SeMf6lATLRqDCInTIIGogTRMcxMHc2wzrUrAWpm6aKa3XcF1ZescG2y262VGGCjg\nwts/vp/Fa/Nt7/ne7/d7z63v5yO5+Z7vOZ9zzvt+evq6n+/5nnMiM5Ek/f/2rL4LkCRNn2EvSQUY\n9pJUgGEvSQUY9pJUgGEvSQUY9pJUgGEvSQUY9pJUwMx67mzr1q05Pz+/nruUpIve0aNHv5KZs+Ns\nY13Dfn5+nqWlpfXcpSRd9CLi0XG34WkcSSrAsJekAgx7SSrAsJekAgx7SSrAsJekAgx7SSrAsJek\nAgx7SSpgXe+gVX/m9/9lr/t/5Kbret2/VJ0je0kqwLCXpAIMe0kqwLCXpAIMe0kqwLCXpAIMe0kq\nwLCXpAK8qUrS1HlTX/8c2UtSAYa9JBVg2EtSAYa9JBVg2EtSARfN1Th+my9Ja+fIXpIKMOwlqYCL\n5jSO1CdPI+pi58hekgow7CWpAMNekgow7CWpAMNekgow7CWpgE5hHxG/GBEnIuK+iPhERHxXRGyJ\niMMRcaq9bp52sZKktVk17CPiSuAXgIXM/CFgE7AH2A8cycwdwJH2XpK0AXU9jTMDfHdEzADPBv4N\n2AUstuWLwO7JlydJmoRVwz4zHwc+AHwJOA18NTP/CpjLzNOt2RlgbmpVSpLG0uU0zmYGo/jtwAuB\nyyPiHSvbZGYCeZ7190XEUkQsLS8vT6BkSdKoupzGeQPwxcxczsz/Bu4EfgR4IiK2AbTXs8NWzswD\nmbmQmQuzs7OTqluSNIIuYf8l4Icj4tkREcBO4CRwCNjb2uwFDk6nREnSuFZ96mVm3hMRtwPHgKeB\ne4EDwBXAbRFxA/AocP00C5UkrV2nRxxn5nuA95wz+1sMRvmSpA3OO2glqQDDXpIKMOwlqQDDXpIK\nMOwlqQDDXpIKMOwlqQDDXpIKMOwlqQDDXpIKMOwlqQDDXpIKMOwlqQDDXpIKMOwlqQDDXpIKMOwl\nqQDDXpIKMOwlqQDDXpIKMOwlqQDDXpIKMOwlqQDDXpIKMOwlqQDDXpIKMOwlqQDDXpIKMOwlqQDD\nXpIKMOwlqQDDXpIKMOwlqQDDXpIKMOwlqQDDXpIK6BT2EfH8iLg9Ir4QEScj4pURsSUiDkfEqfa6\nedrFSpLWpuvI/sPApzPzJcDLgJPAfuBIZu4AjrT3kqQNaNWwj4jnAa8FbgbIzG9n5n8Au4DF1mwR\n2D2tIiVJ4+kyst8OLAN/HBH3RsTHIuJyYC4zT7c2Z4C5YStHxL6IWIqIpeXl5clULUkaSZewnwGu\nBT6SmdcA3+CcUzaZmUAOWzkzD2TmQmYuzM7OjluvJGkNuoT9Y8BjmXlPe387g/B/IiK2AbTXs9Mp\nUZI0rlXDPjPPAF+OiB9os3YC9wOHgL1t3l7g4FQqlCSNbaZju58HbomIS4GHgZ9m8Ifitoi4AXgU\nuH46JUqSxtUp7DPzOLAwZNHOyZYjSZoG76CVpAIMe0kqwLCXpAIMe0kqwLCXpAIMe0kqwLCXpAIM\ne0kqwLCXpAIMe0kqwLCXpAIMe0kqwLCXpAIMe0kqwLCXpAIMe0kqwLCXpAIMe0kqwLCXpAIMe0kq\nwLCXpAIMe0kqwLCXpAIMe0kqwLCXpAIMe0kqwLCXpAIMe0kqwLCXpAIMe0kqwLCXpAIMe0kqwLCX\npAIMe0kqwLCXpAI6h31EbIqIeyPiL9r7LRFxOCJOtdfN0ytTkjSOUUb2NwInV7zfDxzJzB3AkfZe\nkrQBdQr7iLgKuA742IrZu4DFNr0I7J5saZKkSek6sv8Q8CvAd1bMm8vM0236DDA3ycIkSZOzathH\nxFuAs5l59HxtMjOBPM/6+yJiKSKWlpeX116pJGnNuozsXwW8NSIeAW4FXh8RfwI8ERHbANrr2WEr\nZ+aBzFzIzIXZ2dkJlS1JGsWqYZ+Z787MqzJzHtgD/E1mvgM4BOxtzfYCB6dWpSRpLONcZ38T8KMR\ncQp4Q3svSdqAZkZpnJl3AXe16SeBnZMvSZI0ad5BK0kFGPaSVIBhL0kFGPaSVIBhL0kFGPaSVIBh\nL0kFGPaSVIBhL0kFGPaSVIBhL0kFGPaSVIBhL0kFGPaSVIBhL0kFGPaSVIBhL0kFGPaSVIBhL0kF\nGPaSVIBhL0kFGPaSVIBhL0kFGPaSVIBhL0kFGPaSVIBhL0kFGPaSVIBhL0kFGPaSVIBhL0kFGPaS\nVIBhL0kFGPaSVIBhL0kFzPRdwEXjN5/X8/6/2u/+JV3UVh3ZR8SLIuKzEXF/RJyIiBvb/C0RcTgi\nTrXXzdMvV5K0Fl1G9k8Dv5yZxyLiOcDRiDgM/BRwJDNvioj9wH7gV6dXqiStUd+fzKH3T+erjuwz\n83RmHmvTTwEngSuBXcBia7YI7J5WkZKk8Yz0BW1EzAPXAPcAc5l5ui06A8ydZ519EbEUEUvLy8tj\nlCpJWqvOYR8RVwB3AO/KzK+tXJaZCeSw9TLzQGYuZObC7OzsWMVKktamU9hHxCUMgv6WzLyzzX4i\nIra15duAs9MpUZI0ri5X4wRwM3AyMz+4YtEhYG+b3gscnHx5kqRJ6HI1zquAdwL/EhHH27xfA24C\nbouIG4BHgeunU6IkaVyrhn1m3g3EeRbvnGw5kqRp8HEJklSAYS9JBRj2klSAD0KTLgZ93+7vg/gu\neo7sJakAw16SCjDsJakAw16SCjDsJakAw16SCjDsJakAw16SCvCmKq0PbwqSeuXIXpIKMOwlqQDD\nXpIKMOwlqQDDXpIKMOwlqQDDXpIKMOwlqQDDXpIKMOwlqQDDXpIKMOwlqQDDXpIKMOwlqQDDXpIK\nMOwlqQDDXpIKMOwlqQDDXpIKMOwlqQDDXpIKMOwlqYCxwj4ifiwiHoiIhyJi/6SKkiRN1prDPiI2\nAX8IvAl4KfD2iHjppAqTJE3OOCP7VwAPZebDmflt4FZg12TKkiRN0jhhfyXw5RXvH2vzJEkbzMy0\ndxAR+4B97e3XI+KB8zTdCnxl2vWsVfRd33tjtRb234XYf+Ox/8Y3Xh++eNzdjxP2jwMvWvH+qjbv\n/8jMA8CB1TYWEUuZuTBGPVNlfeOxvvFY33g2en0w/RrHOY3zz8COiNgeEZcCe4BDkylLkjRJax7Z\nZ+bTEfFzwGeATcAfZeaJiVUmSZqYsc7ZZ+angE9NqJZVT/X0zPrGY33jsb7xbPT6YMo1RmZOc/uS\npA3AxyVIUgWZOfYPg6tyPgvcD5wAbmzztwCHgVPtdXOb/z2t/deBPzhnW58GPte281Fg05D9zQP/\nBRxvPx9dr/pWbPMQcN8F9vlu4CHgAeCNG6m+PvsPuKv1yTP7fsG4/ddHjT334aUMPvI/CHwBeNtG\nOga71NdX/wHPWbHP4wwudfzQRum/rvWN2n+ZObGw3wZcu6LYBxk8QuF3gf1t/n7gd9r05cCrgZ8d\ncqA8t70GcAew5zy/6HmDdpr1teU/AXz8fDW0bX8OuAzYDvwrQ/5o9Vhfb/3HIEgXVtnfSP3XU419\n9uF7gfe36WcBWzfSMdixvt7675ztHgVeu5H6r2N9I/VfZk7mNE5mns7MY236KeAkg7tpdwGLrdki\nsLu1+UZm3g18c8i2vtYmZxiMEMb+UmGS9UXEFcAvAe+/wC53Abdm5rcy84sMRgev2ED1jWSS9XU0\nUv/1VONIJlzfzwC/3dp9JzOH3YjT2zHYsb6RTOPfNyKuBl4A/P2QxX32X5f6Rjbxc/YRMQ9cA9wD\nzGXm6bboDDDXcRufAc4CTwG3n6fZ9og4HhF/GxGvWcf63gf8HvCfF2iz5kdJrFN90F//ASy2ff9G\nRAy7rXCsR3GsU43QQx9GxPPb5Psi4lhEfDIihq3TyzE4Qn3Q7zEIg3uD/jTbUPkcff4f7lIfjNh/\nEw37Nqq8A3jXihE6AK3gTqP0zHwjg49FlwGvH9LkNPC9mflyBqPYj0fEc6ddX0S8HPj+zPyzLr/H\nqNaxvl76r/nJzPxB4DXt550d1ulsHWvsqw9nGNyt/g+ZeS3wj8AHVttvV+tYX5/H4DP2AJ8Yof2q\n1rG+kftvYmEfEZcw+CVvycw72+wnImJbW76NwWi9k8z8JnCQIU/SbB+tnmzTRxmcT7t6Hep7JbAQ\nEY8AdwNXR8RdQ9p1epREX/X12H9k5uPt9SkG3ysM+2g8cv+td4099uGTDD61PbP+J4Frh7Tr6xjs\nVF+fx2Br+zJgpu17mL76r1N9a+m/iYR9+5h7M3AyMz+4YtEhYG+b3ssgvC+0nStWdMwMcB2Db/PP\nbTcbg+fpExHfB+wAHp52fZn5kcx8YWbOM/hy5cHMfN2QpoeAPRFxWURsb/X900apr6/+i4iZiNja\npi8B3gLcN6TpSP3XR409HoMJ/DnwujZrJ4MrQM7V1zHYqb6++m+Ft3PhUX0v/de1vlH7D5jY1Tiv\nZvDx5PP876VAb2ZwedERBpcd/TWwZcU6jwD/zuDSo8cYfHM9x+CZO59n8B/s9xn8dQN4K/Bbbfpt\nDC5vOg4cA358Peo7Z5vzrPg2fGV97f2vM/hr+wDwpo1UX1/9x+AKhKNtOyeAD9OucBin//qosa8+\nbPNfDPxd29YRBh/nx+rD9a6vz/5ryx4GXnLOPjZE/3Wpb9T+y0zvoJWkCryDVpIKMOwlqQDDXpIK\nMOwlqQDDXpIKMOwlqQDDXpIKMOwlqYD/AVyUXYFUeRfSAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7a513a7f1ba8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.bar(year-0.2, revenue,width=0.4,align='center')\n",
+    "plt.bar(year+0.2, profit,width=0.4,align='center')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "company=['WMT','AMZN','MSFT','FB']\n",
+    "revenue=[485,136,89,27]\n",
+    "profit=[112,2,34,12]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "ypos = np.arange(len(company))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x7a513bd8d780>"
+      ]
+     },
+     "execution_count": 39,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7a513bd0d160>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.bar(ypos-0.2,revenue, width=0.4, label=\"Revenue\")\n",
+    "plt.bar(ypos+0.2,profit, width=0.4,label=\"Profit\")\n",
+    "\n",
+    "plt.xticks(ypos,company)\n",
+    "plt.ylabel(\"Revenue(Bln)\")\n",
+    "plt.title('US Stocks Comparison')\n",
+    "plt.legend()"
+   ]
+  }
+ ],
+ "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": "3.6.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}