ML24.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "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",
    "\n",
    "x = [1,2,3,4,5,6,7,8,9,10]\n",
    "\n",
    "y = [2,4,5,7,6,8,9,10,12,11]\n",
    "\n",
    "plt.scatter(x,y,label=\"Stars\",color='green',marker = \"*\",s=30)\n",
    "\n",
    "plt.xlabel('x-axis')\n",
    "plt.ylabel('y-axis')\n",
    "\n",
    "plt.title('Scatter Plot')\n",
    "\n",
    "plt.legend()\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": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}