{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fancy-inventory",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "published-popularity",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "powerful-bernard",
   "metadata": {},
   "outputs": [],
   "source": [
    "a=3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "hydraulic-sampling",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "macro-newark",
   "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": [
    "# importing matplotlib module \n",
    "from matplotlib import pyplot as plt \n",
    "\n",
    "# x-axis values \n",
    "x = [5, 2, 9, 4, 7] \n",
    "\n",
    "# Y-axis values \n",
    "y = [10, 5, 8, 4, 2] \n",
    "\n",
    "# Function to plot \n",
    "plt.bar(x, y) \n",
    "\n",
    "# function to show the plot \n",
    "plt.show() \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ethical-cattle",
   "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": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}