{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-29T03:06:08.729161Z",
     "start_time": "2021-06-29T03:06:08.718352Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('3.6.9', '1.19.0', '3.2.2')"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import matplotlib\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from platform import python_version\n",
    "\n",
    "python_version(), np.__version__,matplotlib.__version__"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## simple bar plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-29T03:06:13.741738Z",
     "start_time": "2021-06-29T03:06:13.589771Z"
    }
   },
   "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",
    "# generate sample data for this example\n",
    "xs = [1,2,3,4,5,6,7,8,9,10,11,12]\n",
    "ys = np.random.normal(loc=3.0,size=12)\n",
    "labels = ['jan','feb','mar','apr','may','jun','jul','aug','sept','oct','nov','dec']\n",
    "\n",
    "plt.bar(xs,ys)\n",
    "\n",
    "# HERE tell pyplot which labels correspond to which x values\n",
    "plt.xticks(xs,labels)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## horizontal bar plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-29T03:07:08.700948Z",
     "start_time": "2021-06-29T03:07:08.542725Z"
    }
   },
   "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",
    "np.random.seed(42)\n",
    "\n",
    "xs = [1,2,3,4,5,6,7,8,9,10,11,12]\n",
    "ys = np.random.normal(loc=3.0,size=12)\n",
    "labels = ['jan','feb','mar','apr','may','jun','jul','aug','sept','oct','nov','dec']\n",
    "\n",
    "plt.clf()\n",
    "plt.barh(xs,ys)\n",
    "\n",
    "# tell pyplot which labels correspond to which x values\n",
    "plt.yticks(xs,labels)\n",
    "\n",
    "plt.show()"
   ]
  }
 ],
 "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": "3.6.9"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}