horizontal bar.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "\n",
    "# Example data\n",
    "people = ('Tom', 'Dick', 'Harry', 'Slim', 'Jim')\n",
    "y_pos = np.arange(len(people))\n",
    "performance = 3 + 10 * np.random.rand(len(people))\n",
    "error = np.random.rand(len(people))\n",
    "\n",
    "ax.barh(y_pos, performance,align='center',\n",
    "        color='green', ecolor='black')\n",
    "ax.set_yticks(y_pos)\n",
    "ax.set_yticklabels(people)\n",
    "ax.invert_yaxis()  # labels read top-to-bottom\n",
    "ax.set_xlabel('Performance')\n",
    "ax.set_title('How fast do you want to go today?')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "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": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}