Visualization_Matplotlib.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "72016968",
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "bd296298",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sn"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5cfddf1a",
   "metadata": {},
   "source": [
    "# Matplotlib"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7262843c",
   "metadata": {},
   "source": [
    "+ The Figure is the overall window or page that everything is drawn on. It’s the top-level component of all.\n",
    "+ To the figure you add Axes. The Axes is the area on which the data is plotted.\n",
    "+ A figure can have multiple axes."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e8831598",
   "metadata": {},
   "source": [
    "<font color='blue'>Note:</font> when you see, for example, plt.xlim, you’ll call ax.set_xlim() behind the covers. \n",
    "+ All methods of an Axes object exist as a function in the pyplot module and vice versa. \n",
    "+ Mostly, you’ll use the functions of the pyplot module because they’re much cleaner, at least for simple plots!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "79587c32",
   "metadata": {},
   "source": [
    "#### Method I"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "4863ff1f",
   "metadata": {
    "scrolled": true
   },
   "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": [
    "# Method 1\n",
    "# We'll explain the \"111\" later. Basically, 1 row and 1 column.\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111) \n",
    "\n",
    "# Alternate Method\n",
    "#fig, ax = plt.subplots()\n",
    "\n",
    "ax.set(xlim=[0.5, 4.5], ylim=[-2, 8], title='An Example Axes',\n",
    "       ylabel='Y-Axis', xlabel='X-Axis')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "68551723",
   "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": [
    "fig =  plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "\n",
    "ax.set(xlim=[0,20], ylim=[-10,10], title = 'An Example Subplot',\n",
    "       ylabel = 'Y-axis', xlabel='X-label')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "5692e5ca",
   "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": [
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(121)\n",
    "ax.set(xlim=[0,20], ylim=[-10,10], title = 'An Example Axes',\n",
    "       ylabel = 'Y-axis', xlabel='X-label')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "6e443a95",
   "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": [
    "fig = plt.figure()\n",
    "ax  = fig.add_subplot(131)\n",
    "ax.set(xlim=(10,20), ylim = (-5,10), title= \"An Example of Subplot\",\n",
    "      ylabel = 'Y-axis', xlabel = 'X-label')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "203d9b03",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x648 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize = (16,9))\n",
    "ax = fig.add_subplot(211)\n",
    "ax1= fig.add_subplot(212)\n",
    "ax.set(xlim = [0,1], ylim= [-0.5,0.5])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "c0052356",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x648 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize = (16,9))\n",
    "ax = fig.add_subplot(221)\n",
    "ax1= fig.add_subplot(222)\n",
    "ax.set(xlim = [0,1], ylim= [-0.5,0.5])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "f874062e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(221)\n",
    "ax1= fig.add_subplot(222)\n",
    "ax3= fig.add_subplot(313)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d094e0de",
   "metadata": {},
   "source": [
    "#### Method II\n",
    "When you want to control individual elements\n",
    "\n",
    "Example \n",
    "+ <font color='blue'> ax.set_xlabel('Some Label', size=25) </font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "cdd39d6c",
   "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": [
    "fig = plt.figure()\n",
    "# We'll explain the \"111\" later. Basically, 1 row and 1 column.\n",
    "ax = fig.add_subplot(111) \n",
    "ax.set_xlim([0.5, 4.5])\n",
    "ax.set_ylim([-2, 8])\n",
    "ax.text(2.1,3.0,'This is a Subplot',color='red')\n",
    "\n",
    "ax.set_title('A Different Example Axes Title')\n",
    "ax.set_ylabel('Y-Axis (changed)')\n",
    "ax.set_xlabel('X-Axis (changed)')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "5db514c6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXgAAAD8CAYAAAB9y7/cAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/MnkTPAAAACXBIWXMAAAsTAAALEwEAmpwYAAAc40lEQVR4nO3deZRU1bn+8e8LNKIoqzW02FdB1Ks44BW1QzDOiIIicZ6uIhqvqIleNEYlEn/iIphERUSvcYoYHCBiREXiRHD2OtzGoFHROOGIDEEEUWTo9/fHrl40bVf3qe46p6pOPZ+1enVVnX2o123zcHrXPnubuyMiIunTrtAFiIhIPBTwIiIppYAXEUkpBbyISEop4EVEUkoBLyKSUi0GvJl1MrNXzOw1M3vTzK7IvD7azD4zszmZr8PiL1dERKKylubBm5kBnd39azOrAJ4HRgCDgK/d/Zr4yxQRkVx1aKmBh38Bvs48rch86e4oEZEi12LAA5hZe2A28O/Aje7+spkdCpxrZqcCtcCF7v5lE+cOB4YDdO7cec8dd9wxb8WLiJSD2bNnL3b3qlzPa3GIZr3GZpXAA8B5wCJgMeFqfgxQ7e4/be78mpoar62tzbVGEZGyZmaz3b0m1/NymkXj7kuBp4FB7r7A3de6ex1wG9A31zcXEZH4RJlFU5W5csfMNgQGAG+bWXWDZkcBb8RSoYiItEqUMfhqYFJmHL4dMNXdZ5jZXWbWhzBEMw84K7YqRUQkZ1Fm0bwO7N7E60NjqUhERPJCd7KKiKSUAl5EJKUU8CIiKaWAFxFJKQW8iEhKKeBFRFJKAS8iklIKeBGRlFLAi4iklAJeRCSlFPAiIimlgBcRSSkFvIhISingRURSSgEvIpJSCngRkZRSwIuIpJQCXkQkpRTwIiIppYAXEUkpBbyISEop4EVEUkoBLyKSUgp4EZGUUsCLiKSUAl5EJKUU8CIiDcyeDatXF7qK/Ggx4M2sk5m9YmavmdmbZnZF5vXNzGymmb2b+b5p/OWKiMTjhRfg0EOhpgbuuafQ1eRHlCv474D+7r4b0AcYZGb9gJHALHffHpiVeS4iUjLc4amnoH9/2GcfeOyx8PqVV8LatYWtLR9aDHgPvs48rch8OXAEMCnz+iTgyDgKFBHJN/cQ5vvuG8L9qafWP/7uu3DvvYWpLZ8ijcGbWXszmwMsBGa6+8tAN3efD5D5vnlsVYqI5IE7TJ8OffuG4ZgXXsjeduxYqKtLrrY4RAp4d1/r7n2ArYC+ZtY76huY2XAzqzWz2kWLFrWyTBGR1qurg/vugz594IgjoLa25XPeegumTYu9tFjlNIvG3ZcCTwODgAVmVg2Q+b4wyzm3unuNu9dUVVW1rVoRkRysWQN33w29e8Pxx8Prr0c7r7ISLr88DN+UsiizaKrMrDLzeENgAPA2MB0Ylmk2DHgophpFRHKyahVMnAg77QRDh8LcudHO69o1fMA6bx6MHg2bbRZnlfHrEKFNNTDJzNoT/kGY6u4zzOxFYKqZnQF8DBwXY50iIi367rsQ7L/7HXz8cfTzunWDiy6Cs8+Gzp3jqy9pLQa8u78O7N7E6/8CDoqjKBGRXHzzDdx2G1x1FXz+efTzttoKLrkEzjgDNtwwvvoKJcoVvIhIUVq+HG66CcaNg4VNfgrYtJ494Ve/gmHDYIMNYiuv4BTwIlJyli6FG26A666DJUuin7fDDnDppfCf/wkVFXFVVzwU8CJSMv71rxDq118Py5ZFP2+XXeDXv4bjjoP27WMrr+go4EWk6C1YEIZh/vAHWLEi+nm77x6C/cgjoV0ZLq2ogBeRovXZZ3D11XDrrfDtt9HP+9GP4LLL4LDDwCy++oqdAl5Eis5HH4WpjhMnhjntUe23Xwj2gw4q72Cvp4AXkaLx3nvhRqO77gp3oUY1YEAI9v32i6+2UqSAF5GCmzs3LO41ZUpuC3wNHhzG2Pv1i6+2UqaAF5GCee01+M1v4P77w0qPUR19dAj23b93C6Y0pIAXkcT93/+FYJ8+Pfo5ZnDCCTBqVFg8TFqmgBeRxLzwAowZA48/Hv2c9u3hlFPCnae9esVXWxop4EUkVvXb4o0ZA08/Hf28igo47TQYORK23Tau6tJNAS8isajfFu83v4H//d/o522wAZx5Jlx8MXTvHl995UABLyJ5VVcHDz8cgj3Kzkn1NtoIzjkHLrwQqqvjq6+cKOBFJC/Wrg2zYcaOjb5zEsAmm8C558IFF4A2fcsvBbyItMmaNfDnP4dgf/vt6OdVVsL558N//zdsumlc1ZU3BbyItMqqVeGO09/+Ft5/P/p5XbuGYZif/Qy6dImvPlHAi0iOVq6EO+7IfVu8LbYI2+KddVa6tsUrZgp4EYnkm2/Cqo5XX53btnjdu6/bFq9Tp/jqk+9TwItIs5YvD+uwjxsHixZFP2/bbcPNSaeeCh07xlefZKeAF8kX9/XXqG38vMS0dlu8Xr3WbYvXQQlTUOp+kXwYPTok4vjxIdTdw7y/yspwrIQsXhxC/YYbctsWr3fvsADYsceW17Z4xawMN7ESyTP3EO4TJoRQrw/3CRPC67ksk1hAX3wRPgTt2TNMeYwa7nvsAQ88EFaGPOEEhXsx0RW8SFuZhSt3CKE+YUJ4PGLEuiv6IvbZZ3DVVeED1JUro5/Xr1/YZOPQQ4v+P7FsmSd4dVFTU+O1udy7LFJK3Nff2bmurqiTb968MNXxjjty2xZv//1DsPfvX9T/ealiZrPdvSbX8zREI5IP9cMyDdUP1xSZd9+Fn/4Utt8ebrklergfcgg8+2xYEVJ7npYGBbxIWzUccx8xIly5jxix/ph8EXjrLTj5ZNhxx3DVHnXP0yFD4KWXwhru++4bb42SXxqDF2krszBbpuGYe/2YfGVlwS9158wJKztOm5bbvzXHHBNmxfTpE1dlMUjZVNW2anEM3sy6A3cCWwB1wK3uPsHMRgNnAvW3Plzq7o8092dpDF5SrcjC5ZVXQrA//HD0c9q1gxNPDPPYd9klvtpikaKpqo3FOQa/BrjQ3XcC+gE/N7OdM8fGu3ufzFez4S6Seo3DvEDh/vzzMHAg/OhH0cO9ffuwe9LcuXDPPSUY7imZqppvLQ7RuPt8YH7m8XIzmwtsGXdhIhKdOzz5ZNgW75lnop9XURE+cL3kEthmm/jqi12JT1WNS07TJM2sJ/As0Bv4BXAasAyoJVzlf9nEOcOB4QA9evTY86OPPmpz0SIS1G+LN2YMvPhi9PM6dYLhw8ONTVttFV99iSuxqapRxT5N0sw2Bu4Hznf3ZcBNwHZAH8IV/rimznP3W929xt1rqrRdi0he1NXBgw/CD38Ihx0WPdw7d4Zf/hI+/DBc5KYu3EtkqmpSIgW8mVUQwv0ed58G4O4L3H2tu9cBtwF94ytTRCBsizd1apjZctRRMHt2tPO6dAkfnM6bF5b73WKLOKssgBKZqpq0FsfgzcyA24G57n5tg9erM+PzAEcBb8RTooisWQNTpsCVV+a2Ld6mm67bFq+yMq7qikCRT1UtlCjTJPcBngP+QZgmCXApcBJheMaBecBZDQK/SZomKZKbVavgzjvDtngffBD9vKqqddvibbJJfPUVnSKbqpovrR2DjzKL5nmgqR7StEiRmKxcCRMnwu9/n9u2eNXV4YPT4cPLdFu8IpmqWix0J6tIEfnmm7A+zNVXw/xmfx9eX/fuMHJkmPKobfGkngJepAgsXw433gjXXpv7tniXXgpDh2pbPPk+BbxIAS1dCtdfH3ZQ+vJ7d5Fk16sXjBoFJ52kbfEkO/1oiBTA4sVhksf//E9u2+LtumtYAOyYY7RzkrRMAS+SoC++gGuugZtuCuPtUe25Z9hkY8iQ9W/UFGmOAl4kAZ9+GrbFu+223LbF22uvEOyDBpX9hBBpBQW8SIw+/HDdtnirV0c/74ADQrAfeKCCXVpPAS8Sg3/+M9ycdNddYXmBqAYODGPs++wTX21SPhTwInn05pswdizce29YDiWqIUNCsPfVik6SRwp4kTz4+9/XbYsXlVmYDTNqVIltiyclQwEv0gavvBLWYp8xI/o59dvijRoFO+/ccnuR1lLAi7TCc8+FYJ85M/o5HTqEO05/9SvYfvv4ahOpp4AXicgdZs0Kwf7ss9HP69gRTj89rBXTs2ds5Yl8jwJepAXu8OijIdhfein6eandFk9KhgJeJIu6OnjoofDh6auvRj+vc+ewDvuFF0K3bvHVJ9ISBbxII2vXwl/+EoL9jRz2KevSBc47L+yg1LVrbOWJRKaAF8lYswYmTw7b4r3zTvTzNtsshPp556V8WzwpOQp4KXurVsGkSeHO0w8/jH5eVRX88pdwzjllti2elAwFvJStlSvh9tvDtniffBL9vOpquPji8AHqRhvFV59IWyngpeysWLFuW7wvvoh+Xo8eYarj6adrWzwpDQp4KRvLlq3bFm/x4ujnbbdduDlJ2+JJqVHAS+p9+WXYFm/ChNy2xdtxx7CcwIknals8KU36sZXUWrRo3bZ4y5dHP+8//iOs7Hj00doWT0qbAl5SZ/58GDdO2+KJKOAlNT75ZN22eN99F/28H/84BPvAgdo9SdJFAS8l74MPwrZ4f/pTbtviHXhgGIrRtniSVgp4KVnvvBNuTrr77ty3xbvsMth77/hqEykGLY40mll3M3vKzOaa2ZtmNiLz+mZmNtPM3s183zT+ckVgyRIYNixsljFpUvRw/8lPwgYdjz2mcJfyEOWjpDXAhe6+E9AP+LmZ7QyMBGa5+/bArMxzkVjNnx82pL7zzmh7nprBscfCnDlhZcgf/jD2EkWKRosB7+7z3f3VzOPlwFxgS+AIYFKm2STgyJhqFAHg009h//1h7tyW27ZrByefHFaDvO8+2G23+OsTKTY5jcGbWU9gd+BloJu7z4fwj4CZbZ7lnOHAcIAePXq0qVgpX/PmQf/+LS8G1qEDnHpqWFJA2+JJuYs829fMNgbuB85392VRz3P3W929xt1rqqqqWlOjlLn33w9X7s2Fe8eOcPbZ8O67YQExhbtIxCt4M6sghPs97j4t8/ICM6vOXL1XAwvjKlLK1zvvwEEHwWefZW8zbBiMHQtbbplcXSKlIMosGgNuB+a6+7UNDk0HhmUeDwMeyn95Us7eeitcuTcX7hdfDHfcoXAXaUqUK/i9gaHAP8xsTua1S4HfAVPN7AzgY+C4WCqUsvT66zBgQFhPJpvLLoMrrtBNSiLZtBjw7v48kO2v0EH5LUckbHB98MFhvns2Y8aEu1BFJDvdySpF5ZVXwp2mS5dmb3PVVXDRRYmVJFKyFPBSNF54AQ49tPmlfa+7DkaMSKwkkZKmgJei8MwzMHhw2E4vmz/8IWxwLSLRKOCl4P72t7BOzLffNn3cLCwBfMYZydYlUuoU8FJQjz4KRx2Vff32du3CMsBDhyZalkgqKOClYKZPh+OOg1Wrmj7evj3ccw+ccEKydYmkhTYmk4L4y1/gmGOyh3uHDjB1qsJdpC0U8JK4KVPgxBNhzZqmj3fsCNOmhU2vRaT1FPCSqEmT4JRTsm/S0alTWLd9yJBk6xJJIwW8JOaPf4TTT8++UceGG8KMGTBoULJ1iaSVAl4SceONcOaZ4N708c6dw1Z6B2nxC5G8UcBL7MaPh3PPzX68Sxd44gnYb7/kahIpBwp4idXvfw+/+EX245WV4UanH/84sZJEyoYCXmIzZkzYOi+bH/wAnnxSG2GLxEU3OkneuYe12seOzd5m883DlfuuuyZXl0i5UcBLXrnDJZfA1Vdnb7PFFuHKfaedkqtLpBwp4CVv3OGCC2DChOxtttwyhPsOOyRXl0i5UsBLXtTVwc9/DjffnL3N1luHcN922+TqEilnCnhps7VrYfhwmDgxe5tttw3hvvXWydUlUu4U8NIma9aEu1Pvvjt7mx12COG+5ZbJ1SUiCnhpg9Wrwzrt996bvc3OO8OsWeGDVRFJlgJeWmXVqrAi5AMPZG+z665hKuTmmydXl4iso4CXnK1cGTbqmDEje5s99gjLD/zgB8nVJSLrU8BLTr79Fo48MoR3Nn37wuOPh2UIRKRwtFSBRLZiBRx+ePPhvvfeMHOmwl2kGOgKXiJZvhwGD4bnnsveZv/9w7DNxhsnV5eIZKcreGnRV1/BwIHNh/uAAfDIIwp3kWLSYsCb2UQzW2hmbzR4bbSZfWZmczJfh8VbphTKkiUhvF98MXubQw+Fhx+GjTZKri4RaVmUK/g/AU1tojbe3ftkvh7Jb1lSDBYvDjss1dZmb3PEEWGqZKdOydUlItG0GPDu/iywJIFapIgsWAAHHghz5mRvc+yxcN99sMEGiZUlIjloyxj8uWb2emYIZ9NsjcxsuJnVmlntokWL2vB2kpTPP4cDDoA33sje5qSTYMoUqKhIrCwRyVFrA/4mYDugDzAfGJetobvf6u417l5TVVXVyreTpHzySZgN8/bb2dsMGwZ33QUdNAdLpKi1KuDdfYG7r3X3OuA2oG9+y5JCmDcvhPt772Vvc+aZYdXI9u0TK0tEWqlVAW9m1Q2eHgU088u8lIL334f99oMPP8zepn6993aaXCtSElr8JdvMpgAHAF3N7FPgcuAAM+sDODAPOCu+EiVu77wD/fuHsfdsLrgAxo0Ds+TqEpG2aTHg3f2kJl6+PYZapADefDNMhVywIHubkSPhyisV7iKlRr9sl7HXXguzZZoL98svV7iLlCrNgyhTs2fDwQfDl19mbzN2LFx6aXI1iUh+KeDL0Msvh7Vlvvoqe5trroELL0yuJhHJPwV8mXn+eTjssLA6ZDbXXw/nnZdcTSISDwV8GXn66bCe+4oV2dvcfDOcpTlRIqmggC8TM2eGhcG+/bbp42Zw++1w+unJ1iUi8VHAl4FHHoGjj4bvvmv6eLt2MGkSnHJKsnWJSLwU8Cn30ENhg+zVq5s+3r49TJ4Mxx+fbF0iEj/Ng0+x++4LS/pmC/eKitBG4S6STrqCT6nJk2HoUKira/p4x45w//3hQ1cRSSddwadQ/Xh6tnDv1ClssadwF0k3BXzK3HZbmAnj3vTxjTaCv/4VDjkk2bpEJHkK+BS58UYYPjx7uG+8MTz2WFg5UkTSTwGfEtdeC+eem/14ly7wxBOw777J1SQihaWAT4Hf/rb5dWM23RRmzYK99kquJhEpPAV8CXOHK65ofsXHrl3hySehpia5ukSkOGiaZIlyh1//OqzVnk23bvC3v0Hv3snVJSLFQwFfgtzhoovCFnrZVFeHK/cdd0yuLhEpLgr4EuMOI0bADTdkb7PVViHct98+ubpEpPiUdsC7r7+XXOPnKVNXBz/7GdxyS/Y2PXuGcN9mm8TKEpEiVbofso4eDRdcsG7St3t4Pnp0IauKzdq18F//1Xy4b7cdPPOMwl1EgtIMeHdYuhQmTFgX8hdcEJ4vXZr9Tp8StWYNDBsGd9yRvU2vXvDss9CjR3J1iUhxK80hGjMYPz48njAhfEEYnB4/PlXDNKtXw8knh1Ufs9lllzDPvVu35OoSkeJnnuDVbk1NjdfW1ubvD3QPu1XUq6tLVbivWgUnnAAPPpi9zW67hd2aqqoSK0tEEmZms90957tZSnOIBtYNyzTUcEy+xK1cGXZhai7c99wzfKCqcBeRppRmwDcccx8xIly5jxix/ph8Cfvmm7B/6l//mr1Nv37hJqbNNkuuLhEpLaU7Bl9Zuf6Ye/2YfGVlSQ/TrFgBQ4bAU09lb7PPPmGf1U02Sa4uESk9LY7Bm9lE4HBgobv3zry2GXAv0BOYBxzv7l+29GaxjMGnaB78smUweDA8/3z2NgceGDbr6Nw5ubpEpLDiHIP/EzCo0WsjgVnuvj0wK/M8eY3DvITDfelSGDiw+XA/+GCYMUPhLiLRtBjw7v4ssKTRy0cAkzKPJwFH5res8rJkCQwYAC+9lL3N4MEwfXrYkUlEJIrWfsjazd3nA2S+b56/ksrPeefB7NnZjx95JEybFvZSFRGJKvZZNGY23Mxqzax20aJFcb9dSRo/Pvuqj8cdB1OnQseOydYkIqWvtQG/wMyqATLfF2Zr6O63unuNu9dUacJ2kzbfvOnVH08+GSZPhoqKwtQlIqWttQE/HRiWeTwMeCg/5ZSv+vXb6xcKO+00mDQJOpTmRFYRKQItBryZTQFeBHqZ2admdgbwO+BgM3sXODjzXNqofh33UaPg9tuhffscTm483bXEb/YSkbYr7bVoJBg9OsyzrL/pq/5O38rK1C6fLFJOym8tGgnKbOlkEYlOI7ylroyWThaR3GiIJi1SvnSySDnTEE05S/nSySLSOgr4UpfypZNFpPU0Bl/qUrx0soi0jcbg0yJlSyeLyDoagy93KVo6WUTyQwEvIpJSCngRkZRSwIuIpJQCXkQkpRTwIiIppYAXEUkpBbyISEop4EVEUkoBLyKSUgp4EZGUUsCLiKSUAl5EJKUU8CIiKaWAFxFJKQW8iEhKKeBFRFJKAS8iklIKeBGRlFLAi4iklAJeRCSlOrTlZDObBywH1gJrWrPrt4iIxKNNAZ9xoLsvzsOfIyIieaQhGhGRlGrrFbwDT5iZA7e4+62NG5jZcGB45ul3ZvZGG98z37oCxfYbSDHWBMVZl2qKRjVFV4x19WrNSeburX5HM/s3d//czDYHZgLnufuzzbSvLbZxetUUXTHWpZqiUU3RFWNdra2pTUM07v555vtC4AGgb1v+PBERyZ9WB7yZdTazTeofA4cAxTb8IiJSttoyBt8NeMDM6v+cye7+WAvnfG+MvgiopuiKsS7VFI1qiq4Y62pVTW0agxcRkeKlaZIiIimlgBcRSalYAt7MBpnZO2b2npmNbOK4mdn1meOvm9kecdSRY00HmNlXZjYn8/X/Yq5nopktzHZfQCH6KGJdSfdTdzN7yszmmtmbZjaiiTaF+HmKUlfSfdXJzF4xs9cyNV3RRJtE+ypiTYn2U4P3bW9mfzezGU0cK9Tfv+Zqyr2f3D2vX0B74H1gW6Aj8Bqwc6M2hwGPAgb0A17Odx2tqOkAYEacdTR6v/2APYA3shxPtI9yqCvpfqoG9sg83gT4Z6F/nnKoK+m+MmDjzOMK4GWgXyH7KmJNifZTg/f9BTC5qfcu4N+/5mrKuZ/iuILvC7zn7h+4+yrgz8ARjdocAdzpwUtApZlVx1BLLjUlysMNYUuaaZJ0H0WtK1HuPt/dX808Xg7MBbZs1CzxvopYV6Iy//1fZ55WZL4az6JItK8i1pQ4M9sKGAz8MUuTxH+mItSUszgCfkvgkwbPP+X7P/hR2iRdE8BemV8lHzWzXWKsJ4qk+ygXBeknM+sJ7E64CmyooH3VTF2QcF9lfsWfAywEZrp7wfsqQk2Q/M/UdcDFQF2W44X4mWqpJsixn+IIeGvitcb/Ykdpk09R3u9VYGt33w24AXgwxnqiSLqPoipIP5nZxsD9wPnuvqzx4SZOSaSvWqgr8b5y97Xu3gfYCuhrZr0bNUm8ryLUlGg/mdnhwEJ3n91csyZei62fItaUcz/FEfCfAt0bPN8K+LwVbRKtyd2X1f8q6e6PABVm1jXGmlqSdB9FUoh+MrMKQoje4+7TmmhSkL5qqa5C/ky5+1LgaWBQo0MF+7nKVlMB+mlv4CcW9rP4M9DfzO5u1Cbpfmqxplb1UwwfEnQAPgC2Yd0Hmrs0ajOY9T/AeCXfdbSipi1Yd+NXX+Dj+ucx1tWT7B9mJtpHOdSVaD9l/vvvBK5rpk3ifRWxrqT7qgqozDzeEHgOOLyQfRWxpsT/7jV47wNo+gPNQv79y1ZTzv2Ujw0/1uPua8zsXOBxwuyVie7+ppmdnTl+M/AI4VPq94BvgNPzXUcrajoWOMfM1gDfAid6pifjYGZTCP8ju5rZp8DlhA+gCtJHOdSVaD8RrmyGAv/IjOMCXAr0aFBTIfoqSl1J91U1MMnM2hN+O5/q7jMK+XcvYk1J91OTCtxPUWrKuZ+0VIGISErpTlYRkZRSwIuIpJQCXkQkpRTwIiIppYAXEUkpBbyISEop4EVEUur/A9Qs8mP3SL77AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "ax.set_xlim(0, 4.5)\n",
    "ax.set_ylim(5, 35)\n",
    "\n",
    "# Line Plot\n",
    "x=[1, 2, 3, 4]\n",
    "y=[10, 20, 25, 30]\n",
    "ax.plot(x, y,color='blue', linewidth=6)\n",
    "\n",
    "#Scatter Plot\n",
    "x=[0.3, 3.8, 1.2, 2.5]\n",
    "y=[11, 25, 9, 26]\n",
    "ax.scatter(x,y, marker='x', color = 'red')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e842b904",
   "metadata": {},
   "source": [
    "#### Using the pyplot methods"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "e053d095",
   "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": [
    "plt.plot([1, 2, 3, 4], [10, 20, 25, 30], color='blue', linewidth=4)\n",
    "plt.scatter([1, 3.8, 1.2, 2.5], [15, 25, 9, 26], c= ['red','blue','green','black'], marker='o')\n",
    "plt.xlim(0.5, 4.5)\n",
    "plt.text(2.0,20.2,'___________This is a line Plot',color='blue')\n",
    "plt.text(1.2,9.5,'___________This is Scatter Plot',color=\"green\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "64471b8d",
   "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": [
    "plt.plot([1, 2, 3, 4], [10, 20, 25, 30], color='blue', linewidth=4)\n",
    "plt.scatter([1, 3.8, 1.2, 2.5], [15, 25, 9, 26], c= [1,2,3,4], marker='o')\n",
    "plt.xlim(0.5, 4.5)\n",
    "plt.text(2.0,20.2,'___________This is a line Plot',color='blue')\n",
    "plt.text(1.2,9.5,'___________This is Scatter Plot',color=\"green\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e8ae398a",
   "metadata": {},
   "source": [
    "Markers\n",
    "Markers are commonly used in plot() and scatter() plots, but also show up elsewhere. There is a wide set of markers available, and custom markers can even be specified.\n",
    "\n",
    "marker\tdescription\tmarker\tdescription\tmarker\tdescription\tmarker\tdescription\n",
    "\".\"\tpoint\t\"+\"\tplus\t\",\"\tpixel\t\"x\"\tcross\n",
    "\"o\"\tcircle\t\"D\"\tdiamond\t\"d\"\tthin_diamond\t\t\n",
    "\"8\"\toctagon\t\"s\"\tsquare\t\"p\"\tpentagon\t\"*\"\tstar\n",
    "\"|\"\tvertical line\t\"_\"\thorizontal line\t\"h\"\thexagon1\t\"H\"\thexagon2\n",
    "0\ttickleft\t4\tcaretleft\t\"<\"\ttriangle_left\t\"3\"\ttri_left\n",
    "1\ttickright\t5\tcaretright\t\">\"\ttriangle_right\t\"4\"\ttri_right\n",
    "2\ttickup\t6\tcaretup\t\"^\"\ttriangle_up\t\"2\"\ttri_up\n",
    "3\ttickdown\t7\tcaretdown\t\"v\"\ttriangle_down\t\"1\"\ttri_down\n",
    "\"None\"\tnothing\tNone\tdefault\t\" \"\tnothing\t\"\"\tnothing\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e38a65f",
   "metadata": {},
   "source": [
    "## Sub Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "e7f73f8d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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RoMmEr38dJk+Gp58u+rbcEi69tFhR9hWvKLc+SVK1eblHg2LVquLbOtdd1903fjxcey0cdFBpZUmSWoghRQPuoYeK+08WL+7ue+c7iwXaxo0rry5JUmvxco8G1L/9Gxx44IYB5eST4d//3YAiSdo8hhQNiHXr4PTT4aij4Nlni76ttoJ/+Rc47zwYPbrU8iRJLcjLPWraM8/Axz4GP/1pd9/rXw/XXw9veUtpZUmSWpwhRU1ZtKi4/+SRR7r73vveYsG2HXYory5JUuvzco/67Uc/Kr6p0zOg/N//CzfeaEBReSJiQkTcGhGLI2JRRJxc6391RMyLiEdqf27fYP9JEfFQRCyJiBlDW72kngwp2mxr18KMGfChD8FzzxV9Y8bAD34A3/xm8SweqURdwBczcy/gYOBzEbE3MAP4eWbuAfy81t5ARLQBFwKTgb0pnva+95BVLmkD/nWizfLkkzBtGsyb1923++7w4x/DPvuUVpb0J5n5GPBYbXtVRCwGxgNHA4fVhn0PuA04tdfuBwJLMnMpQERcXdvvN4NeuKSX8UyK+mzhwmJ5+54BZcoU6OgwoKiaImJX4C3A3cC4WoBZH2ReW2eX8cCjPdqdtb567z09IjoiomPlypUDWrekwiZDykau734rIh6MiPsi4vqI2K7B/ssi4v6IWBgRHQNcv4bIlVfC298Oy5Z1933lK8W6KNttV1ZVUmMRsQ1wLfCFzHy2r7vV6ct6AzNzVma2Z2b72LFj+1umpI3oy5mURtd35wH7ZOa+wMPAaRt5j8Mzc2JmtjddsYbUSy/BF74AH/0oPP980bfttsXlna9+FbbwXJwqKCJGUwSUKzNz/cMZHo+IHWuv7wisqLNrJzChR3tnYPlg1iqpsU3+FZOZj2Xmr2vbq4DFwPjMvCUzu2rD7qL4ZdYwsmIFHHEEfOc73X1vehPccw8cfXR5dUkbExEBXA4szsxzerx0A3Bcbfs44Cd1dp8P7BERu0XElsDU2n6SSrBZ/w7udX23p08CNzbYLYFbImJBREzf7ApVivnzYf/94Re/6O475hi4++4iqEgVdgjwMeDdtcvMCyNiCvAN4IiIeAQ4otYmInaKiLkAtX94nQTcTPEPsmsyc1EZH0LSZny7p9H13Yj4B4pLQlc22PWQzFweEa8F5kXEg5l5e533nw5MB9hll1024yNooM2eDSeeCGvWFO0I+Kd/Kr527OUdVV1m3kH9e0sA3lNn/HJgSo/2XGDu4FQnaXP06a+cBtd3iYjjgPcDH8nMRjeXLa/9uQK4nuIrfvXGeRNayV58ET77WTj++O6Ast128LOfwd//vQFFkjS0NnkmpdH13YiYRLHGwLsyc3WDfccAW9TWKhgDHAn8fwNSuQbU8uXF4mx33tnd9+Y3F8/f2X338uqSJI1cffm3caPruxcA21JcwlkYETNhw+u7wDjgjoi4F7gH+Flm3jTwH0PN+M//LO4/6RlQpk6FX/3KgCJJKs8mz6Rs5Ppu3Wu2Pa/v1lZt3K+ZAjV4MuHii+Hkk6Gr9j2tLbaAs8+GU04p7kWRJKksLos/Qr3wQnH/yZw53X2veU3x/J33vOzWQkmShp4hZQT6/e/hL/+yWM5+vbe+Fa67Dl7/+vLqkiSpJ7+vMcLcemtx/0nPgPI3fwN33GFAkSRViyFlhMiEc88tVpB94omib9QoOP/84pLP1luXWp4kSS/j5Z4RYPVq+NSn4KqruvvGjYMf/hAOPbS8uiRJ2hhDyjC3dGmxnP1993X3HXQQXHstjK/7AHpJkqrByz3D2M03Q3v7hgFl+vTieTwGFElS1RlShqFM+PrXYfJkePrpom/LLeHSS+GSS+AVryi3PkmS+sLLPcPMqlXwiU8Ul3PWGz++aB90UHl1SZK0uQwpw8jDDxf3n/zmN919hx5a3CA7blx5dUmS1B9e7hkm/u3f4IADNgwon/88/PznBhRJUmsypLS4devgjDPgqKPg2WeLvq22gu9/H77zHRg9utTyJEnqNy/3tLBnnoGPfQx++tPuvte/vlje/q1vLa0sSZIGhCGlRS1aVNx/8sgj3X3veQ9cfTXssEN5dUmSNFC83NOCfvSj4ps6PQPK//k/cNNNBhRJ0vBhSGkha9fCjBnwoQ/Bc88Vfa98ZXH25Oyzi2fxSJI0XGwypETEhIi4NSIWR8SiiDi51v/qiJgXEY/U/ty+wf6TIuKhiFgSETMG+gOMFE8+CVOmwDe/2d23++5w113w139dXl1SFUXE7IhYEREP9Oj7QUQsrP0si4iFDfZdFhH318Z11BsjaWj05UxKF/DFzNwLOBj4XETsDcwAfp6ZewA/r7U3EBFtwIXAZGBvYFptX22G++8vlre/5ZbuvsmTYf58ePOby6tLqrA5wKSeHZn515k5MTMnAtcC121k/8NrY9sHr0RJm7LJkJKZj2Xmr2vbq4DFwHjgaOB7tWHfAz5QZ/cDgSWZuTQzXwSuru2nPlq1qjiDsmxZd98//mOxLsr2dc9dScrM24Gn6r0WEQF8GLiq3uuSqmOz7kmJiF2BtwB3A+My8zEoggzw2jq7jAce7dHurPXVe+/pEdERER0rV67cnLKGtX/8R+jsLLa32Qauvx7OPBPa2sqtS2phhwKPZ+YjDV5P4JaIWBAR0xu9iXOWNPj6HFIiYhuKU6RfyMxn+7pbnb6sNzAzZ2Vme2a2jx07tq9lDWvz58P553e3Z86ED3ygtHKk4WIaGz+LckhmvpXiMvXnIuKd9QY5Z0mDr08hJSJGUwSUKzNz/XXcxyNix9rrOwIr6uzaCUzo0d4ZWN7/ckeOri6YPr14ojHAkUfCsceWW5PU6iJiFPBB4AeNxmTm8tqfK4DrKS5bSypBX77dE8DlwOLMPKfHSzcAx9W2jwN+Umf3+cAeEbFbRGwJTK3tp0047zxYuLDY3npruPhiiHrnpSRtjvcCD2ZmZ70XI2JMRGy7fhs4Enig3lhJg68vZ1IOAT4GvLvH1/emAN8AjoiIR4Ajam0iYqeImAuQmV3AScDNFDfcXpOZiwbhcwwr//3fcPrp3e3TT4c3vKG8eqRWExFXAb8C9oyIzog4vvbSVHpd6uk5ZwHjgDsi4l7gHuBnmXnTUNUtaUObXP4rM++g/r0lAO+pM345MKVHey4wt/c41ZcJJ54Iq1cX7X33hVNOKbcmqdVk5rQG/R+v0/enOSszlwL7DWpxkvrMFWcr5gc/KJa3h+LyzqxZPslYkjQyGVIq5Omn4eSTu9snnlg8o0eSpJHIkFIhp54KK2rfkRo/Hr72tXLrkSSpTIaUivjlL+HSS7vb558Pr3pVefVIklQ2Q0oFrFlTrImy3tFHwzHHlFePJElVYEipgG9+Ex58sNjeZpsNV5mVJGmkMqSU7KGH4KyzuttnnQUTJjQeL0nSSGFIKVEmnHACvPhi0T7gAPjc58qtSZKkqjCklGjOHLjttmK7ra1YE8WnG0uSVDCklGTFCvjSl7rbp5wCEyeWVo4kSZVjSCnJKafAU08V27vuuuGzeiRJkiGlFPPmwZVXdrcvvhjGjCmvHkmSqsiQMsRWry5ull1v6lSYNKm8eiRJqipDyhA780xYurTY3m47OO+8MquRJKm6DClD6P774Z//ubv9rW/BuHHl1SNJUpWN2tSAiJgNvB9YkZn71Pp+AOxZG7Id8ExmTqyz7zJgFbAW6MrM9gGpugWtXQuf/jR0dRXtQw+FT36y3JokSaqyTYYUYA5wAfD99R2Z+dfrtyPi28D/bGT/wzPzif4WOFzMnAl3311sjx4Nl1wCW3geS5KkhjYZUjLz9ojYtd5rERHAh4F3D3Bdw8of/gCnndbdPu002Guv8uqRJKkVNPtv+UOBxzPzkQavJ3BLRCyIiOkNxgAQEdMjoiMiOlauXNlkWdXy+c/DqlXF9hvfuGFgkSRJ9TUbUqYBV23k9UMy863AZOBzEfHORgMzc1Zmtmdm+9ixY5ssqzpuuAGuu667PWsWbLVVefVII0FEzI6IFRHxQI++MyLiDxGxsPYzpcG+kyLioYhYEhEzhq5qSb31O6RExCjgg8APGo3JzOW1P1cA1wMH9vd4rWjVqg0fGPjJT8K73lVePdIIMgeotwLRuZk5sfYzt/eLEdEGXEjxD6u9gWkRsfegViqpoWbOpLwXeDAzO+u9GBFjImLb9dvAkcAD9cYOV1/+MnTW/uuMHVt85VjS4MvM24Gn+rHrgcCSzFyamS8CVwNHD2hxkvpskyElIq4CfgXsGRGdEXF87aWp9LrUExE7RcT6f52MA+6IiHuBe4CfZeZNA1d6tc2fD9/9bnf73HPh1a8urx5JAJwUEffVLgdtX+f18cCjPdqdtb6XGc730UlV0Zdv90xr0P/xOn3LgSm17aXAfk3W15K6umD6dMgs2kceCcceW25NkrgYOJPihv4zgW8DvVcrijr7Zb03y8xZwCyA9vb2umMkNceVOgbBeefBwoXF9lZbwUUXQdSb+iQNmcx8PDPXZuY64FLq3yPXCUzo0d4ZWD4U9Ul6OUPKAFu2DE4/vbt9xhmw++5lVSNpvYjYsUfzGOrfIzcf2CMidouILSkua98wFPVJerm+rDirPsqEE08snnQMsO++cMop5dYkjUS1e+kOA3aIiE7gdOCwiJhIcflmGfCZ2tidgMsyc0pmdkXEScDNQBswOzMXDf0nkASGlAF1zTVw443FdkSxJsro0eXWJI1EDe6lu7zB2D/dS1drzwVe9vVkSUPPyz0D5Omni5Vl1zvxRDjooPLqkSSp1RlSBsipp8KKFcX2TjvB175Wbj2SJLU6Q8oA+OUv4dJLu9sXXACvelV59UiSNBwYUpq0Zg185jPd7aOPhmOOKa8eSZKGC0NKk84+GxYvLra32QbOP7/ceiRJGi4MKU146CH4p3/qbp91FkyY0Hi8JEnqO0NKP2XCCSfAiy8W7QMO2PCJx5IkqTmGlH6aMwduu63Ybmsr1kRpayuzIkmShhdDSj+sXAlf+lJ3+5RTYOLE0sqRJGlYMqT0wymnwFNPFdu77rrhs3okSdLAMKRspnnz4IorutsXXwxjxpRXjyRJw9UmQ0pEzI6IFRHxQI++MyLiDxGxsPYzpcG+kyLioYhYEhEzBrLwMqxeXdwsu97UqTBpUnn1SJI0nPXlTMocoN5fxedm5sTaz8sexhURbcCFwGRgb2BaROzdTLFlO/NMWLq02N5uOzjvvDKrkSRpeNtkSMnM24Gn+vHeBwJLMnNpZr4IXA0c3Y/3qYT774d//ufu9tlnw7hx5dUjSdJw18w9KSdFxH21y0Hb13l9PPBoj3Znra+uiJgeER0R0bFy5comyhp469bB9OnQ1VW0Dz0Ujj++3JokSRru+htSLgZ2ByYCjwHfrjMm6vRlozfMzFmZ2Z6Z7WPHju1nWYNj5ky4665ie/RouOQS2MJbjiVJGlT9+qs2Mx/PzLWZuQ64lOLSTm+dQM9F4ncGlvfneGX6wx/gtNO626edBnvtVV49kiSNFP0KKRGxY4/mMcADdYbNB/aIiN0iYktgKnBDf45Xps9/Hp59tth+4xs3DCySJGnwjNrUgIi4CjgM2CEiOoHTgcMiYiLF5ZtlwGdqY3cCLsvMKZnZFREnATcDbcDszFw0GB9isNxwA1x3XXf7kktgq63Kq0eSpJFkkyElM6fV6b68wdjlwJQe7bnAy76e3ApWrdrwgYGf+AQcdlhp5UjaDBExG3g/sCIz96n1fQv4C+BF4LfAJzLzmTr7LgNWAWuBrsxsH6KyJfXi7Z8NfPnL0NlZbI8dC9/6Vrn1SNosc3j5+k7zgH0yc1/gYWBjF28Pr60BZUCRSmRIqaOjA84/v7t97rnwmteUV4+kzVNvfafMvCUzawsJcBfFzfySKsyQ0ktXF3z608XaKABHHgnHHltuTZIG3CeBGxu8lsAtEbEgIqYPYU2SetnkPSkjzXnnwcKFxfZWW8FFF0HUW/FFUkuKiH8AuoArGww5JDOXR8RrgXkR8WDtzEzv95kOTAfYZZddBq1eaSTzTEoPy5bB6ad3t08/HXbfvbRyJA2wiDiO4obaj2Rm3cUla18AIDNXANdTfx2oSi9AKQ0XhpSaTDjxxOJJxwBvfjN88Yvl1iRp4ETEJOBU4KjMXN1gzJiI2Hb9NnAk9deBkjQEDCk111wDN9auUEfApZcWS+BLaj219Z1+BewZEZ0RcTxwAbAtxSWchRExszZ2p4hYv1TCOOCOiLgXuAf4WWbeVMJHkIT3pADw9NNw8snd7RNPhIMOKq8eSc3p7/pOmbkU2G8QS5O0GTyTAsyYAY8/XmzvtBN87Wvl1iNJkgwp/PKXMGtWd/v88+FVryqvHkmSVBjRIWXNGvjMZ7rbRx0FxxxTXj2SJKnbiA4pZ58NixcX29tsAxdc4JookiRVxYgNKQ8/DGed1d0+6yyYMKG8eiRJ0oZGZEjJLC7zrFlTtA84YMMnHkuSpPKNyJAyZw7cdlux3dZW3Djb1lZmRZIkqbdNhpSImB0RKyLigR5934qIByPivoi4PiK2a7Dvsoi4v7ZwUscA1t1vK1fCl77U3f67v4OJE0srR5IkNdCXMylzgEm9+uYB+2TmvsDDwGkb2f/wzJyYme39K3FgnXIKPFV7gPvrXw9nnFFqOZJGgHt/sYi75/667DKklrPJFWcz8/aI2LVX3y09mncBfzXAdQ2KefPgiiu62xdfDGPGlFePpOFvbddavv7R7/LSCy9yVecstnyFz9uQ+mog7kn5JHBjg9cSuCUiFtQea95QREyPiI6I6Fi5cuUAlLWh55+Hz362uz11KkyePOCHkaQN3Hr1f7L6f1bz4gsvcdPs/yi7HKmlNBVSIuIfgC7gygZDDsnMtwKTgc9FxDsbvddgP/b8zDPht78ttrfbDs47b8APIUkbWNu1lstOu5Ln//gCLzy3hu995WpeXPNS2WVJLaPfISUijgPeD3wkM7PemNqDu8jMFcD1wIH9PV4z7r8fvvWt7vbZZ8O4cWVUImkkWX8WZT3Ppkibp18hJSImAacCR2Xm6gZjxkTEtuu3gSOBB+qNHUzr1sH06dDVVbTf8Q44/vihrkLSSNPzLMp6nk2RNk9fvoJ8FfArYM+I6IyI44ELgG2BebWvF8+sjd0pIubWdh0H3BER9wL3AD/LzJsG5VNsxMyZcNddxfbo0cWaKFuMyNVhJA2lO38yn6cee5qtt9lqg58/PrOa267+z7LLk1pCX77dM61O9+UNxi4HptS2lwL7NVVdk5Yvh9N6fDn6tNNgr73Kq0fSyPFnh+zJqd/727qvvfmdTkRSX2wypLSyz38enn222H7jGzcMLJI0mF79uu15z0cOLbsMqaUN2wsfN9wA117b3b7kEthqq/LqkSRJm2dYhpRVqzZ8YOAnPgGHHVZaOZIkqR+GZUj58pehs7PY3mGHDb9+LEmSWsOwCykdHXD++d3t886D17ymtHIklaDBg1FfHRHzIuKR2p/bN9h3UkQ8FBFLImLG0FUtqbdhFVK6uuDTny7WRgE48kg49thya5JUijm8/MGoM4CfZ+YewM9r7Q1ERBtwIcUq2XsD0yJi78EtVVIjwyqkfOc7sHBhsb3VVnDRRRBRakmSSpCZtwNP9eo+Gvhebft7wAfq7HogsCQzl2bmi8DVtf0klWDYhJRly+ArX+lun3467L57aeVIqp5xmfkYQO3P19YZMx54tEe7s9b3MoP9UFRJwySkZMKJJ8Lq2gL9b34zfPGL5dYkqSXVO/fa6Nlkg/pQVEnDJKRccw3ceGOxHVEsfT96dLk1SaqcxyNiR4DanyvqjOkEJvRo7wwsH4LaJNXR8iHl6afh5JO72yeeCAcfXF49kirrBuC42vZxwE/qjJkP7BERu0XElsDU2n6SStDyIWXGDHj88WJ7p53ga18rtx5J5WvwYNRvAEdExCPAEbX2Bg9Gzcwu4CTgZmAxcE1mLirjM0hq8Wf33HFHcWlnvfPPh1e9qrx6JFVDgwejArynztg/PRi11p4LzO09TtLQa9kzKWvWwPTp3e2jjoJjjimvHkmSNLBaNqScfTYsXlxsb7MNXHCBa6JIkjScbDKkVHF56YcfhrPO6m6fdRZMmNB4vCSpfy6afzeX/7qj7DI0QvXlTMocKrS8dCaccEJxuQfggAM2fOKxJGlgPPX8ai6Yfxfn3HUnz655oexyNAJtMqRUbXnp730Pbr212G5rK26cbWtr9l0lSb3N7JhPZpIkl/16QdnlaATq7z0pA7q8dF+tXLnhSrJ/93cwcWIz7yhJquep51dzxf0LWbN2LS90dXH5fy3wbIqG3GDeONvn5aWhb8/BaGuDo2vnYl7/ejjjjAGoUpL0MuvPoqzn2RSVob8hZcCXl+7LczBe/WqYPbu43DNnDowZ08/qJUkN9TyLsp5nU1SG/oaUUpeXPuyw4keSNPBuXPIIa7q62HrUqA1+Xuh6iVt+u6Ts8jSCbHLF2dry0ocBO0REJ3A6xXLS19SWmv498KHa2J2AyzJzSmZ2RcT65aXbgNkuLy1J1ffXf/Zm3rPbG+q+NvaVnsLW0NlkSHF5aUkaWUZtsQWv22bbssuQWnfFWUmSNLwZUiRJUiUZUiRJUiUZUiRJUiVFz8V6qiIiVgK/28SwHYAnhqCcKhlpn3mkfV7o22d+fWbWX0xIpejjnFVFw+13zM9TXf2atyoZUvoiIjoys73sOobSSPvMI+3zwsj8zCrPcPv/m59n+PFyjyRJqiRDiiRJqqRWDimzyi6gBCPtM4+0zwsj8zOrPMPt/29+nmGmZe9JkSRJw1srn0mRJEnDmCFFkiRVUsuFlIiYHRErIuKBsmsZChExISJujYjFEbEoIk4uu6bBFhFbRcQ9EXFv7TN/teyahkpEtEXEf0XET8uuRcPTcJtDh9scOZLnv3pa7p6UiHgn8Efg+5m5T9n1DLaI2BHYMTN/HRHbAguAD2Tmb0oubdBERABjMvOPETEauAM4OTPvKrm0QRcRpwDtwKsy8/1l16PhZ7jNocNtjhzJ8189LXcmJTNvB54qu46hkpmPZeava9urgMXA+HKrGlxZ+GOtObr201ppuh8iYmfgfcBlZdei4Wu4zaHDbY4cqfNfIy0XUkayiNgVeAtwd8mlDLraZY+FwApgXmYO+88MnAf8X2BdyXVILWm4zJEjdP6ry5DSIiJiG+Ba4AuZ+WzZ9Qy2zFybmROBnYEDI6LlT0tvTES8H1iRmQvKrkVqRcNpjhxp89/GGFJaQO265LXAlZl5Xdn1DKXMfAa4DZhUbiWD7hDgqIhYBlwNvDsirii3JKk1DNc5cgTNfw0ZUiqudhPV5cDizDyn7HqGQkSMjYjtattbA+8FHiy1qEGWmadl5s6ZuSswFfiPzPxoyWVJlTfc5siROP9tTMuFlIi4CvgVsGdEdEbE8WXXNMgOAT5G8S/rhbWfKWUXNch2BG6NiPuA+RTXZP1KrjQAhuEcOtzmSOe/HlruK8iSJGlkaLkzKZIkaWQwpEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEoypEiSpEpqKqRExOyIWBERDzR4PSLiuxGxJCLui4i3NnM8SWqGc5bUWpo9kzIHmLSR1ycDe9R+pgMXN3k8SWrGHJyzpJbRVEjJzNuBpzYy5Gjg+1m4C9guInZs5piS1F/OWVJrGTXI7z8eeLRHu7PW91jvgRExneJfLowZM2b/N73pTYNcmtSaFixY8ERmji27jmHKOUsaBP2dtwY7pESdvqw3MDNnAbMA2tvbs6OjYzDrklpWRPyu7BqGMecsaRD0d94a7G/3dAITerR3BpYP8jElqb+cs6QKGeyQcgPwN7U75g8G/iczX3baVJIqwjlLqpCmLvdExFXAYcAOEdEJnA6MBsjMmcBcYAqwBFgNfKKZ40lSM5yzpNbSVEjJzGmbeD2BzzVzDEkaKM5ZUmtxxVlJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJTYWUiJgUEQ9FxJKImFHn9f8VEf8WEfdGxKKI+EQzx5OkZjlvSa2j3yElItqAC4HJwN7AtIjYu9ewzwG/ycz9gMOAb0fElv09piQ1w3lLai3NnEk5EFiSmUsz80XgauDoXmMS2DYiAtgGeAroauKYktQM5y2phTQTUsYDj/Zod9b6eroA2AtYDtwPnJyZ65o4piQ1w3lLaiHNhJSo05e92n8OLAR2AiYCF0TEq+q+WcT0iOiIiI6VK1c2UZYkNTRg85ZzljT4mgkpncCEHu2dKf7l0dMngOuysAT4b+BN9d4sM2dlZntmto8dO7aJsiSpoQGbt5yzpMHXTEiZD+wREbvVbiqbCtzQa8zvgfcARMQ4YE9gaRPHlKRmOG9JLWRUf3fMzK6IOAm4GWgDZmfmoog4ofb6TOBMYE5E3E9xmvXUzHxiAOqWpM3mvCW1ln6HFIDMnAvM7dU3s8f2cuDIZo4hSQPJeUtqHa44K0mSKsmQIkmSKsmQIkmSKsmQIkmSKsmQIkmSKsmQIkmSKsmQIkmSKsmQIkmSKsmQIkmSKsmQIkmSKsmQIkmSKsmQIkmSKsmQIkmSKsmQIkmSKsmQIkmSKsmQIkmSKsmQIkmSKsmQIkmSKsmQIkmSKsmQIkmSKsmQIkmSKsmQIkmSKsmQIkmSKsmQIkmSKsmQIkmSKsmQIkmSKsmQIkmSKsmQIkmSKsmQIkmSKsmQIkmSKsmQIkmSKsmQIkmSKsmQIkmSKsmQIkmSKqmpkBIRkyLioYhYEhEzGow5LCIWRsSiiPhFM8eTpGY5b0mtY1R/d4yINuBC4AigE5gfETdk5m96jNkOuAiYlJm/j4jXNlmvJPWb85bUWpo5k3IgsCQzl2bmi8DVwNG9xhwLXJeZvwfIzBVNHE+SmuW8JbWQZkLKeODRHu3OWl9PbwS2j4jbImJBRPxNozeLiOkR0RERHStXrmyiLElqaMDmLecsafA1E1KiTl/2ao8C9gfeB/w58OWIeGO9N8vMWZnZnpntY8eObaIsSWpowOYt5yxp8PX7nhSKf4FM6NHeGVheZ8wTmfkc8FxE3A7sBzzcxHElqb+ct6QW0syZlPnAHhGxW0RsCUwFbug15ifAoRExKiJeCRwELG7imJLUDOctqYX0+0xKZnZFxEnAzUAbMDszF0XECbXXZ2bm4oi4CbgPWAdclpkPDEThkrS5nLek1hKZvS/Hlq+9vT07OjrKLkOqpIhYkJntZdehbs5Z0sb1d95yxVlJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJTYWUiJgUEQ9FxJKImLGRcQdExNqI+KtmjidJzXLeklpHv0NKRLQBFwKTgb2BaRGxd4Nx3wRu7u+xJGkgOG9JraWZMykHAksyc2lmvghcDRxdZ9zfAtcCK5o4liQNBOctqYU0E1LGA4/2aHfW+v4kIsYDxwAzmziOJA0U5y2phTQTUqJOX/ZqnwecmplrN/lmEdMjoiMiOlauXNlEWZLU0IDNW85Z0uAb1cS+ncCEHu2dgeW9xrQDV0cEwA7AlIjoyswf936zzJwFzAJob2/vPWlI0kAYsHnLOUsafM2ElPnAHhGxG/AHYCpwbM8Bmbnb+u2ImAP8tF5AkaQh4rwltZB+h5TM7IqIkyjufm8DZmfmoog4ofa613MlVYrzltRamjmTQmbOBeb26qv7S56ZH2/mWJI0EJy3pNbhirOSJKmSDCmSJKmSDCmSJKmSDCmSJKmSDCmSJKmSDCmSJKmSDCmSJKmSDCmSJKmSDCmSJKmSDCmSJKmSDCmSJKmSDCmSJKmSDCmSJKmSDCmSJKmSDCmSJKmSDCmSJKmSDCmSJKmSDCmSJKmSDCmSJKmSDCmSJKmSDCmSJKmSDCmSJKmSDCmSJKmSDCmSJKmSDCmSJKmSDCmSJKmSDCmSJKmSDCmSJKmSDCmSJKmSDCmSJKmSDCmSJKmSDCmSJKmSDCmSJKmSDCmSJKmSmgopETEpIh6KiCURMaPO6x+JiPtqP3dGxH7NHE+SmuW8JbWOfoeUiGgDLgQmA3sD0yJi717D/ht4V2buC5wJzOrv8SSpWc5bUmtp5kzKgcCSzFyamS8CVwNH9xyQmXdm5tO15l3Azk0cT5Ka5bwltZBmQsp44NEe7c5aXyPHAzc2ejEipkdER0R0rFy5somyJKmhAZu3nLOkwddMSIk6fVl3YMThFL/spzZ6s8yclZntmdk+duzYJsqSpIYGbN5yzpIG36gm9u0EJvRo7wws7z0oIvYFLgMmZ+aTTRxPkprlvCW1kGbOpMwH9oiI3SJiS2AqcEPPARGxC3Ad8LHMfLiJY0nSQHDeklpIv8+kZGZXRJwE3Ay0AbMzc1FEnFB7fSbwFeA1wEURAdCVme3Nly1Jm895S2otkVn3cmyp2tvbs6Ojo+wypEqKiAX+pVktzlnSxvV33nLFWUmSVEmGFEmSVEmGFEmSVEmGFEmSVEmGFEmSVEmGFEmSVEmGFEmSVEmGFEmSVEmGFEmSVEmGFEmSVEmGFEmSVEmGFEmSVEmGFEmSVEmGFEmSVEmGFEmSVEmGFEmSVEmGFEmSVEmGFEmSVEmGFEmSVEmGFEmSVEmGFEmSVEmGFEmSVEmGFEmSVEmGFEmSVEmGFEmSVEmGFEmSVEmGFEmSVEmGFEmSVEmGFEmSVEmGFEmSVEmGFEmSVEmGFEmSVEmGFEmSVElNhZSImBQRD0XEkoiYUef1iIjv1l6/LyLe2szxJKlZzltS6+h3SImINuBCYDKwNzAtIvbuNWwysEftZzpwcX+PJ0nNct6SWkszZ1IOBJZk5tLMfBG4Gji615ijge9n4S5gu4jYsYljSlIznLekFtJMSBkPPNqj3Vnr29wxkjRUnLekFjKqiX2jTl/2Y0wxMGI6xalVgDUR8UATtQ22HYAnyi5iI6yvOVWvb8+yC2hhAzZvOWcNKOtrXtVr7Ne81UxI6QQm9GjvDCzvxxgAMnMWMAsgIjoys72J2gaV9TXH+poTER1l19DCBmzecs4aONbXvKrX2N95q5nLPfOBPSJit4jYEpgK3NBrzA3A39Tulj8Y+J/MfKyJY0pSM5y3pBbS7zMpmdkVEScBNwNtwOzMXBQRJ9RenwnMBaYAS4DVwCeaL1mS+sd5S2otzVzuITPnUvxC9+yb2WM7gc/1461nNVPXELC+5lhfc6peX6UN0rxV9f9NrK85Va8Pql9jv+qL4vdRkiSpWlwWX5IkVVJpIaXqS1P3ob6P1Oq6LyLujIj9hrK+vtTYY9wBEbE2Iv6qavVFxGERsTAiFkXEL6pUX0T8r4j4t4i4t1bfkN6bEBGzI2JFo6+2lv07MhI5bw1ufT3GOWf1o75hOWdl5pD/UNyw9lvgDcCWwL3A3r3GTAFupFiz4GDg7orV93Zg+9r25KGsr6819hj3HxTX4P+qSvUB2wG/AXaptV9bsfr+HvhmbXss8BSw5RDW+E7grcADDV4v7XdkJP44bw1+fT3GOWf1r75hN2eVdSal6ktTb7K+zLwzM5+uNe+iWEthKPXlvyHA3wLXAiuGsjj6Vt+xwHWZ+XuAzBzKGvtSXwLbRkQA21D8wncNVYGZeXvtmI24fPvQct4a5PpqnLP6X9+wm7PKCilVX5p6c499PEU6HEqbrDEixgPHADMZen35b/hGYPuIuC0iFkTE3wxZdX2r7wJgL4qFvO4HTs7MdUNTXp+4fPvQct5qjnNWc0bknNXUV5CbMKBL6g+CzVnO/3CKX/Z3DGpFdQ5dp693jecBp2bm2iJYD6m+1DcK2B94D7A18KuIuCszHx7s4uhbfX8OLATeDewOzIuIX2bms4NcW1+V+TsyEjlvNcc5qzkjcs4qK6QM6JL6g6BPx46IfYHLgMmZ+eQQ1bZeX2psB66u/bLvAEyJiK7M/HFF6usEnsjM54DnIuJ2YD9gKH7h+1LfJ4BvZHExdUlE/DfwJuCeIaivL8r8HRmJnLea45w1+PUNvzlrqG6o6XXzzChgKbAb3TcA/VmvMe9jwxts7qlYfbtQrEj59qr+N+w1fg5DexNaX/4b7gX8vDb2lcADwD4Vqu9i4Iza9jjgD8AOQ/y/8640vgmttN+RkfjjvDX49fUa75y1+fUNuzmrlDMpWfGlqftY31eA1wAX1VJ/Vw7hw536WGNp+lJfZi6OiJuA+4B1wGWZOSRPku3jf78zgTkRcT/FL9WpmTlkTxmNiKuAw4AdIqITOB0Y3aM+l28fQs5bQ1JfaZyzmjcYc5YrzkqSpEpyxVlJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJhhRJklRJ/z9w84Yx7Cd9AAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 648x648 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(2, 2, figsize=(9, 9))\n",
    "fig.subplots_adjust(wspace=0.5, hspace=0.3)\n",
    "(ax1,ax2),(ax3,ax4) = axes\n",
    "ax1.plot([1, 2, 3, 4], [10, 20, 25, 30], color='blue', linewidth=3)\n",
    "ax2.scatter([0.3, 3.8, 1.2, 2.5], [11, 25, 9, 26], c=[1, 2, 3, 5], marker='^')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "55c7ed16",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(2, 2, figsize=(9, 9))\n",
    "fig.subplots_adjust(wspace=0.3, hspace=0.2)\n",
    "(ax1,ax2),(ax3,ax4) = axes\n",
    "ax1.plot([1, 2, 3, 4], [10, 20, 25, 30], color='blue', linewidth=3)\n",
    "ax2.scatter([0.3, 3.8, 1.2, 2.5], [11, 25, 9, 26], c=[1, 2, 3, 5], marker='^')\n",
    "ax3.scatter([2, 4, 6, 8, 10], [2, 4, 6, 8, 10], c=[1, 2, 3, 5, 4], marker='x')\n",
    "ax4.scatter([0.3, 3.8, 1.2, 2.5], [11, 25, 9, 26], c=[6, 7, 9, 11], marker='o')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "460817fb",
   "metadata": {},
   "source": [
    "# Categorical Vs Numeric"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e43f4a1d",
   "metadata": {},
   "source": [
    "### a. Bar Chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "24d12cb8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Brand</th>\n",
       "      <th>Cars Listings</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Audi</td>\n",
       "      <td>419</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BMW</td>\n",
       "      <td>636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Mercedes-Benz</td>\n",
       "      <td>820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Mitsubishi</td>\n",
       "      <td>306</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Renault</td>\n",
       "      <td>438</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Volkswagen</td>\n",
       "      <td>875</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Brand  Cars Listings\n",
       "0           Audi            419\n",
       "1            BMW            636\n",
       "2  Mercedes-Benz            820\n",
       "3     Mitsubishi            306\n",
       "4        Renault            438\n",
       "5         Toyota            509\n",
       "6     Volkswagen            875"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_used_cars = pd.read_csv(\"C:/Users/Moin Dalvi/Documents/EXcelR Study and Assignment Material/Data Science/Visualization/CSV files/bar_chart_data.csv\")\n",
    "df_used_cars"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ddb215ac",
   "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": [
    "# Set the size of the chart\n",
    "plt.figure(figsize = (6, 4)) \n",
    "#figsize=plt.figaspect(9/6)\n",
    "\n",
    "\n",
    "# To create a bar chart with matplotlib you can use the 'bar' function.\n",
    "plt.bar(x = df_used_cars[\"Brand\"], #specify the x axis\n",
    "        height = df_used_cars[\"Cars Listings\"], #specify the y axis\n",
    "        color = \"#F5DEB3\") # the color for the bars\n",
    "\n",
    "# rotate and format the labels for the x-axis\n",
    "plt.xticks( rotation = 90,fontsize = 12) \n",
    "plt.title(\"Cars Listings by Brand\", fontsize = 16, fontweight = \"bold\") \n",
    "plt.ylabel(\"Number of Listings\", fontsize = 13 ) \n",
    "\n",
    "# you can export your chart as a picture\n",
    "#plt.savefig(\"Used Cars Bar.png\") \n",
    "\n",
    "# depending on which environment you're using without this line you're chart may not display properly.\n",
    "plt.show() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "34646744",
   "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": [
    "plt.figure(figsize = (6,4))\n",
    "plt.bar(df_used_cars['Brand'], df_used_cars['Cars Listings'], color='black')\n",
    "plt.xticks(rotation = 90, fontsize = 14)\n",
    "plt.title('Cars Listing by Brand', fontsize = 16, fontweight ='bold')\n",
    "plt.xlabel(\"Different Car Brands\", fontsize = 14, color = 'red')\n",
    "plt.ylabel('Numbers of Listings', fontsize = 13)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bcfbd1bd",
   "metadata": {},
   "source": [
    "### b. Horizontal Bar Chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "8e6ca940",
   "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": [
    "plt.figure(figsize = (6,4))\n",
    "plt.barh(df_used_cars['Brand'], df_used_cars['Cars Listings'], color='blue')\n",
    "plt.xticks(rotation = 90, fontsize = 12)\n",
    "plt.yticks(fontsize=14)\n",
    "plt.title('Cars Listing by Brand', fontsize = 16, fontweight ='bold')\n",
    "plt.xlabel(\"Numbers of Listings\", fontsize = 14, color = 'red')\n",
    "plt.ylabel('Different Car Brands', fontsize = 13, color = 'red' )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "76f4345b",
   "metadata": {},
   "source": [
    "### c. Pie Chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4632999c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Engine Fuel Type</th>\n",
       "      <th>Number of Cars</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Diesel</td>\n",
       "      <td>2019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Gas</td>\n",
       "      <td>613</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Other</td>\n",
       "      <td>154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Petrol</td>\n",
       "      <td>1559</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Engine Fuel Type  Number of Cars\n",
       "0           Diesel            2019\n",
       "1              Gas             613\n",
       "2            Other             154\n",
       "3           Petrol            1559"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_fuel_engine_type = pd.read_csv(\"C:/Users/Moin Dalvi/Documents/EXcelR Study and Assignment Material/Data Science/Visualization/CSV files/pie_chart_data.csv\")\n",
    "df_fuel_engine_type "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "48ab99ec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Engine Fuel Type</th>\n",
       "      <th>Number of Cars</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Diesel</td>\n",
       "      <td>2019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Gas</td>\n",
       "      <td>613</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Other</td>\n",
       "      <td>154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Petrol</td>\n",
       "      <td>1559</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Engine Fuel Type  Number of Cars\n",
       "0           Diesel            2019\n",
       "1              Gas             613\n",
       "2            Other             154\n",
       "3           Petrol            1559"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "file = pd.read_csv(\"C:/Users/Moin Dalvi/Documents/EXcelR Study and Assignment Material/Data Science/Visualization/CSV files/pie_chart_data.csv\")\n",
    "file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "7b418e12",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,8))\n",
    "plt.pie(file['Number of Cars'],\n",
    "        labels=file['Engine Fuel Type'].values,\n",
    "        explode=[0.2,0.0,0.0,0.0],\n",
    "        autopct='%.1f%%',\n",
    "        textprops={'size':'x-large',\n",
    "                  'fontweight':'bold',\n",
    "                  'rotation':'45',\n",
    "                  'color':'y'}\n",
    "        )\n",
    "plt.legend(loc='lower right')\n",
    "plt.title('Cars by Engine Fuel Type', fontsize = 18, fontweight = 'bold')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7083cb1b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<svg  width=\"330\" height=\"55\"><rect x=\"0\" y=\"0\" width=\"55\" height=\"55\" style=\"fill:#5302a3;stroke-width:2;stroke:rgb(255,255,255)\"/><rect x=\"55\" y=\"0\" width=\"55\" height=\"55\" style=\"fill:#8b0aa5;stroke-width:2;stroke:rgb(255,255,255)\"/><rect x=\"110\" y=\"0\" width=\"55\" height=\"55\" style=\"fill:#b83289;stroke-width:2;stroke:rgb(255,255,255)\"/><rect x=\"165\" y=\"0\" width=\"55\" height=\"55\" style=\"fill:#db5c68;stroke-width:2;stroke:rgb(255,255,255)\"/><rect x=\"220\" y=\"0\" width=\"55\" height=\"55\" style=\"fill:#f48849;stroke-width:2;stroke:rgb(255,255,255)\"/><rect x=\"275\" y=\"0\" width=\"55\" height=\"55\" style=\"fill:#febd2a;stroke-width:2;stroke:rgb(255,255,255)\"/></svg>"
      ],
      "text/plain": [
       "[(0.32515, 0.006915, 0.639512),\n",
       " (0.546157, 0.038954, 0.64701),\n",
       " (0.723444, 0.196158, 0.538981),\n",
       " (0.85975, 0.360588, 0.406917),\n",
       " (0.95547, 0.533093, 0.28549),\n",
       " (0.994495, 0.74088, 0.166335)]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sn.set_palette('plasma')\n",
    "sn.color_palette()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "3ef18dc2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (6,6))\n",
    "plt.pie(df_fuel_engine_type['Number of Cars'],\n",
    "       labels = df_fuel_engine_type[\"Engine Fuel Type\"].values,\n",
    "       explode = [0,0,0.1,0],\n",
    "       autopct = '%.2f%%',\n",
    "       textprops = {'size' : 'large',\n",
    "                    'fontweight' : 'bold',\n",
    "                   'rotation' : '45',\n",
    "                   'color' : 'y'})\n",
    "# Uses Labels\n",
    "plt.legend(loc= 'upper right')\n",
    "plt.title('Cars by Engine fuel Type', fontsize = 18, fontweight = 'bold')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "03f59ca4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (8,8))\n",
    "plt.pie(df_fuel_engine_type['Number of Cars'],\n",
    "       labels=df_fuel_engine_type['Engine Fuel Type'],\n",
    "       explode = [0.0,0.0,0.2,0.0],\n",
    "       autopct= '%.0f%%',\n",
    "       shadow= True,\n",
    "       startangle= 140,\n",
    "       textprops = {'size':'x-large',\n",
    "                   'fontweight':'bold',\n",
    "                    'rotation':'0',\n",
    "                   'color':'black'})\n",
    "plt.legend(loc= 'upper left')\n",
    "plt.title('Cars by Engine fuel Type', fontsize = 18, fontweight = 'bold')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "680ac0c3",
   "metadata": {},
   "source": [
    "# Input Data: Univariate (1D Series)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fbf1b53e",
   "metadata": {},
   "source": [
    "### a.Histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "7bcef4ca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Building Type</th>\n",
       "      <th>Year of sale</th>\n",
       "      <th>Month of sale</th>\n",
       "      <th>Type of property</th>\n",
       "      <th>Property #</th>\n",
       "      <th>Area (ft.)</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1030</td>\n",
       "      <td>1</td>\n",
       "      <td>2005.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>30</td>\n",
       "      <td>743.09</td>\n",
       "      <td>246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1029</td>\n",
       "      <td>1</td>\n",
       "      <td>2005.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>29</td>\n",
       "      <td>756.21</td>\n",
       "      <td>246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2002</td>\n",
       "      <td>2</td>\n",
       "      <td>2007.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>2</td>\n",
       "      <td>587.28</td>\n",
       "      <td>209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2031</td>\n",
       "      <td>2</td>\n",
       "      <td>2007.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>31</td>\n",
       "      <td>1604.75</td>\n",
       "      <td>453</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1049</td>\n",
       "      <td>1</td>\n",
       "      <td>2004.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>49</td>\n",
       "      <td>1375.45</td>\n",
       "      <td>467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>262</th>\n",
       "      <td>5044</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>44</td>\n",
       "      <td>1238.58</td>\n",
       "      <td>323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>263</th>\n",
       "      <td>5047</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>47</td>\n",
       "      <td>794.52</td>\n",
       "      <td>279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>264</th>\n",
       "      <td>5048</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>48</td>\n",
       "      <td>1013.27</td>\n",
       "      <td>288</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>265</th>\n",
       "      <td>5050</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>50</td>\n",
       "      <td>1074.71</td>\n",
       "      <td>366</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>266</th>\n",
       "      <td>5051</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Apartment</td>\n",
       "      <td>51</td>\n",
       "      <td>789.25</td>\n",
       "      <td>199</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>267 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       ID  Building Type  Year of sale  Month of sale Type of property  \\\n",
       "0    1030              1        2005.0           11.0        Apartment   \n",
       "1    1029              1        2005.0           10.0        Apartment   \n",
       "2    2002              2        2007.0            7.0        Apartment   \n",
       "3    2031              2        2007.0           12.0        Apartment   \n",
       "4    1049              1        2004.0           11.0        Apartment   \n",
       "..    ...            ...           ...            ...              ...   \n",
       "262  5044              5           NaN            NaN        Apartment   \n",
       "263  5047              5           NaN            NaN        Apartment   \n",
       "264  5048              5           NaN            NaN        Apartment   \n",
       "265  5050              5           NaN            NaN        Apartment   \n",
       "266  5051              5           NaN            NaN        Apartment   \n",
       "\n",
       "     Property #  Area (ft.)  Price  \n",
       "0            30      743.09    246  \n",
       "1            29      756.21    246  \n",
       "2             2      587.28    209  \n",
       "3            31     1604.75    453  \n",
       "4            49     1375.45    467  \n",
       "..          ...         ...    ...  \n",
       "262          44     1238.58    323  \n",
       "263          47      794.52    279  \n",
       "264          48     1013.27    288  \n",
       "265          50     1074.71    366  \n",
       "266          51      789.25    199  \n",
       "\n",
       "[267 rows x 8 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_real_estate = pd.read_csv(\"C:/Users/Moin Dalvi/Documents/EXcelR Study and Assignment Material/Data Science/Visualization/CSV files/histogram_data.csv\")\n",
    "df_real_estate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "id": "167a31d1",
   "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": [
    "#sn.set_style(\"white\") # override the default matplotlib style, to avoid the grey background and grid\n",
    "plt.figure(figsize = (6, 4)) # determine the size of the figure\n",
    "\n",
    "plt.hist(df_real_estate[\"Price\"], # the variable on which to create the histogram\n",
    "         bins = 10, # create a histogram with 8 bins\n",
    "         color = \"#7FFF00\",\n",
    "        edgecolor='black')\n",
    "plt.title(\"Distribution of Real Estate Prices\", fontsize = 14, weight = \"bold\")\n",
    "plt.xlabel(\"Price in (000's $)\")\n",
    "plt.ylabel(\"Number of Properties\")\n",
    "sn.despine(top = False, right = False) # removes the top and right border of our graph\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4d0fd772",
   "metadata": {},
   "outputs": [],
   "source": [
    "for direction in [\"xzero\", \"yzero\"]:\n",
    "    # adds arrows at the ends of each axis\n",
    "    ax.axis[direction].set_axisline_style(\"-|>\")\n",
    "\n",
    "    # adds X and Y-axis from the origin\n",
    "    ax.axis[direction].set_visible(True)\n",
    "\n",
    "for direction in [\"left\", \"right\", \"bottom\", \"top\"]:\n",
    "    # hides borders\n",
    "    ax.axis[direction].set_visible(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0df2a0b6",
   "metadata": {},
   "source": [
    "### b. BoxPlot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1f571655",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,4))\n",
    "plt.boxplot(x='Price', data=df_real_estate)\n",
    "plt.title(\"Box plot\") \n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b446c0ab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (8,4))\n",
    "plt.boxplot('Price', data = df_real_estate)\n",
    "plt.title('Box_plot')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8488a998",
   "metadata": {},
   "source": [
    "# Input Data: Bivariate (2D Series)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "02a82eef",
   "metadata": {},
   "outputs": [],
   "source": [
    "years = [1950, 1960, 1970, 1980, 1990, 2000, 2010]\n",
    "gdp = [300.2, 543.3, 1075.9, 2862.5, 5979.6, 10289.7, 14958.3]\n",
    "\n",
    "\n",
    "# create a line chart, years on x-axis, gdp on y-axis\n",
    "#plt.plot(years, gdp, color='green', marker='x', linestyle='dashed')\n",
    "plt.plot(gdp, years, color='midnightblue', marker='o', linestyle='solid')\n",
    "\n",
    "\n",
    "# add a title\n",
    "plt.title(\"Nominal GDP\")\n",
    "\n",
    "# add a label to the y-axis\n",
    "plt.ylabel(\"Billions of $\")\n",
    "plt.xlabel(\"Year\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "a11f3c1f",
   "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": [
    "years = [1950, 1960, 1970, 1980, 1990, 2000, 2010]\n",
    "gdp = [300.2, 543.3, 1075.9, 2862.5, 5979.6, 10289.7, 14958.3]\n",
    "plt.plot(years, gdp,  color = 'black', marker ='X', linestyle = 'solid')\n",
    "plt.title('Nominal GDP')\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Billions of $')\n",
    "sn.despine(right = True, top = True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "b13bb0dd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize= (9,5))\n",
    "\n",
    "scatter  = plt.scatter(df_real_estate['Area (ft.)'],\n",
    "                       df_real_estate['Price'],\n",
    "                       alpha = 0.6)\n",
    "plt.title('Relationship between Area and Price of California Real Estate',\n",
    "          fontsize = 14,\n",
    "          weight = 'bold')\n",
    "plt.xlabel(\"Area (sq. ft.)\", weight = 'bold')\n",
    "plt.ylabel(\"price (000's of $)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "3f53e164",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize= (9,5))\n",
    "\n",
    "scatter  = plt.scatter(df_real_estate['Area (ft.)'],\n",
    "                       df_real_estate['Price'],\n",
    "                       alpha = 0.6,\n",
    "                      c = df_real_estate['Building Type'])\n",
    "plt.title('Relationship between Area and Price of California Real Estate',\n",
    "          fontsize = 14,\n",
    "          weight = 'bold')\n",
    "plt.xlabel(\"Area (sq. ft.)\", weight = 'bold')\n",
    "plt.ylabel(\"price (000's of $)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "76a5135b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize= (9,5))\n",
    "\n",
    "scatter  = plt.scatter(df_real_estate['Area (ft.)'],\n",
    "                       df_real_estate['Price'],\n",
    "                       alpha = 0.6,\n",
    "                      c = df_real_estate['Building Type'],\n",
    "                      cmap = 'viridis')\n",
    "plt.title('Relationship between Area and Price of California Real Estate',\n",
    "          fontsize = 14,\n",
    "          weight = 'bold')\n",
    "plt.xlabel(\"Area (sq. ft.)\", weight = 'bold')\n",
    "plt.ylabel(\"price (000's of $)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e6eae32d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "195ca7e6",
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   "execution_count": null,
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   "execution_count": null,
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 ],
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  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
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  "language_info": {
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   "file_extension": ".py",
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   "nbconvert_exporter": "python",
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}