Data Analysis/Matplotlib/introduction-to-matplotlib.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introduction to Matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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();"
   ]
  },
  {
   "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": [
    "plt.plot()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1ee56583d90>]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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": [
    "x = [1,2,3,4]\n",
    "y = [11,22,33,44]\n",
    "plt.plot(x,y);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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": [
    "# 1st method\n",
    "fig = plt.figure() #creates figure\n",
    "ax = fig.add_subplot() #adds some axes\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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": [
    "# 2nd method\n",
    "fig = plt.figure() #creates figure\n",
    "ax = fig.add_axes([1,1,1,1])\n",
    "ax.plot(x,y) #add some data\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(matplotlib.figure.Figure, matplotlib.axes._subplots.AxesSubplot)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "# 3rd method (to use)\n",
    "fig,ax = plt.subplots()\n",
    "ax.plot(x,[50,100,200,250]);# add some data\n",
    "type(fig),type(ax)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Matplotlib example workflow"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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DRzV1TILiOzTyOhK+A8ULAIAQtXHXIQ1Jz9a+4hJNS0lQXLuGXkfCaVC8AAAIQet2HtSQ8dkqLi1TVmqSereu73UkVADFCwCAELO6YL+GpOeovNwpKzVJ57Ss53UkVBDFCwCAELJ8+z4NTc9RVJRpZlqSujav63UkVALFCwCAELF4S5GGT8hRjWrRykxNVKemdbyOhEqK8joAAAA4vQWb9io5PVu1qlfTrHFJlK4QxYgXAABBLn/Dbo2amKcGtWOUlZqkNg1reR0JZ4jiBQBAEMtZu0ujJ+epeb1YZaYmqmX9ml5HwlngUCMAAEHq69U7NXJSrlo1qKlZaUmUrjDAiBcAAEHosxUFGjctXx2b1Nb0sYlqUqeG15FQBSheAAAEmY+X7tCPZ8xVl2Z1NH1sohrVru51JFQRDjUCABBEPli8TXdMz9c5LesqKzWJ0hVmGPECACBIvLNgq346a776t22gSaMHqV5sjNeRUMUoXgAABIHX8zfrgdcWKL5DI00cNUh1avAWHY74WwUAwGOz8jbqoTcW6dxOjZUxMl61qvP2HK44xwsAAA9Ny96gn7++SBd2baqJowZRusIcf7sAAHhk4lfr9Ni7S3XZOc304tABqlEt2utI8DOKFwAAHvj752v0538u11W9W+jZwXGqXo2DUJGA4gUAQIA9N3uVnvpopa7r10pP395P1aIpXZGC4gUAQIA45/TURyv1/CerdXNcaz1xWz9FR5nXsRBAFC8AAALAOac/f7BcL3++Vj+Mb6s/3tyH0hWBKF4AAPiZc06PvbtUk75er2FJ7fTY9b0VRemKSBQvAAD8qLzc6TfvLNb07I0afX4H/ebanjKjdEUqihcAAH5SVu708BuLNGvOJo37fic9dGUPSleEo3gBAOAHZeVOD7y6QG/M26K7L+min17ejdIFihcAAFWtpKxc972yQP9YsFX3X95NP7m0q9eRECQoXgAAVKGjpeW6O2uePliyXb+4qofGfb+z15EQRCheAABUkSOlZbpzxlx9vKxAv7m2p8Zc0NHrSAgyFC8AAKpAcUmZxk3L1+crC/W7G3treFJ7ryMhCFG8AAA4S4eOlip16hx9s2aX/nJLH/1wUDuvIyFIUbwAADgLB46UaszkPM1Zv1t/va2fbh7QxutICGIULwAAztC+4hKNmpirBZuL9OzgOF3Xr5XXkRDkKF4AAJyBokMlGjExR0u27tOLyXG6sndLryMhBFC8AACopN0Hj2pYRo5WFxzQ34cN1GU9m3sdCSGC4gUAQCXsPHBEwzJytG7nQY0fMVAXdW/mdSSEEIoXAAAVVLCvWMkZOdq855Amjhqk87s08ToSQgzFCwCACthWdFjJ6Tnasa9YU0YnKLFTY68jIQRRvAAAOI1Nuw8pOSNbew+WaFpKgga2b+R1JIQoihcAAN9hw66DSk7P0f7iEk0fm6h+bRt4HQkhjOIFAMAprCk8oKHpOTpSWqbM1CT1bl3f60gIcRQvAABOYtWO/RqSniPJKSstST1a1PM6EsIAxQsAgBMs27ZPwzJyFBVlykpNUpdmdb2OhDAR5XUAAACCyeItRRqSnq2Y6CjNSqN0oWox4gUAgM/8TXs1YkKO6sbGKCs1Se0a1/I6EsIMxQsAAElz1u/WqEl5alS7ujJTE9WmIaULVY/iBQCIeN+u2aWUKXlqUS9WmalJalE/1utICFOc4wUAiGhfrdqp0ZNz1bpBTc0cR+mCf1G8AAAR69MVBRozJU8dGtdWVlqSmtWldMG/ONQIAIhIHy3doTtnzFW3FnU0bUyiGtau7nUkRACKFwAg4ry/aJvuzpqnXq3ra+qYBNWvGeN1JEQIihcAIKK8PX+L7ntlgfq3baDJowepbiylC4HDOV4AgIjxWv5m/XTWfMW3b6ipYxIoXQg4RrwAABFhZu5G/eLNRTq/cxOlj4hXzerRXkdCBGLECwAQ9qZ+u14PvbFI3+/WVBkjKV3wDiNeAICwlvHlWv3+vWW6vGdzvZAcpxrVKF3wDsULABC2XvpstR7/YIWu7tNCzw6OU0w0B3rgLYoXACAsPfvxKj398Upd36+Vnrq9n6pRuhAEKF4AgLDinNNfP1ypFz5drVsGtNHjt/ZVdJR5HQuQRPECAIQR55z+9M/lGv/FWg1JaKs/3NhHUZQuBBGKFwAgLDjn9Og/lmryN+s14tz2euS6XpQuBB2/HfA2s1gzyzWzBWa2xMwe9U1/xMy2mNl83+1qf2UAAESG8nKnX761WJO/Wa+UCzrq0espXQhO/hzxOiLpEufcATOLkfSVmf3TN+9p59yTflw3ACBClJU7PfT6Qr2av1k/uqizHryiu8woXQhOfitezjkn6YDvYYzv5vy1PgBA5CktK9cDry3Um/O26J5Lu+rey7pSuhDU/PrZWjOLNrP5kgokfeScy/HNusvMFprZRDNreIrnppnZHDObU1hY6M+YAIAQVFJWrntmzdeb87bogSu666eXd6N0Iej5tXg558qcc/0ltZGUYGa9Jf1NUmdJ/SVtk/TXUzx3vHMu3jkX37RpU3/GBACEmKOl5borc67eW7hND1/dQ3de3MXrSECFBORqcs65vZI+k3Slc26Hr5CVS0qXlBCIDACA8FBcUqY7pufrX0t26LfX9VTahZ29jgRUmD8/1djUzBr47teUdJmk5WbW8rjFbpK02F8ZAADhpbikTKlT5+iT5QX6w029Nfr8jl5HAirFn59qbClpiplF61jBe8U5966ZTTOz/jp2ov16SeP8mAEAECYOHS1VyuQ5yl63S4/f2le3x7f1OhJQaf78VONCSXEnmT7cX+sEAISnA0dKNWZSnuZs2K2nbu+nm+LaeB0JOCNcuR4AENSKDpdo1KRcLdxcpOeGxOnavq28jgScMYoXACBo7T10VCMm5mrZtn16MXmAruzdwutIwFmheAEAgtLug0c1LCNHqwsO6O/DBurSc5p7HQk4axQvAEDQKdx/REMzsrVh1yFljIzXhd24niPCA8ULABBUduwrVnJ6trbuLdakUYN0XpcmXkcCqgzFCwAQNLbuPazk9GwV7j+iKWMSlNCxkdeRgCpF8QIABIVNuw9pSHq2ig6VaGpKoga2P+lX+QIhjeIFAPDc+p0HlZyerYNHyzQjNVF92zTwOhLgFxQvAICnVhcc0NCMbJWUOWWmJqpXq/peRwL8huIFAPDMiu37NTQjR5JTVmqSureo63UkwK8oXgAATyzduk/DJuSoWpQpM/VcdWlWx+tIgN9FeR0AABB5Fm0u0pD0bNWoFqVZ4yhdiByMeAEAAmruxj0aOTFX9WvGKCs1SW0b1fI6EhAwjHgBAAImb/1uDc/IUaPa1TVr3LmULkQcRrwAAAHxzZqdSpk8Ry0bxCpzbJJa1I/1OhIQcIx4AQD87ouVhRo9KU9tGtbUzDRKFyIXI14AAL/6dHmBxk3PV+emdTQ9JUGN69TwOhLgGYoXAMBv/rVku+7KnKseLeppWkqCGtSq7nUkwFMULwCAX7y3cJvumTlPvVvX15QxCapfM8brSIDnOMcLAFDl3pq3RT/Jmqu4dg00LYXSBfwbI14AgCr16pxNevD1hUrq2FgZI+NVuwZvNcC/8a8BAFBlMnM26uE3F+l7XZto/PB41awe7XUkIKhQvAAAVWLKN+v123eW6JIezfTS0AGKjaF0ASeieAEAzlrGl2v1+/eW6Qc9m+uF5AGqXo1TiIGToXgBAM7Ki5+u1hP/WqFr+rTUM4P7Kyaa0gWcCsULAHBGnHN6dvYqPfPxKt3Yv5WevK2fqlG6gO9E8QIAVJpzTk/8a4Ve+myNbh3YRn+5pa+io8zrWEDQo3gBACrFOac/vLdMGV+t05CEdvrDjb0VRekCKoTiBQCoMOecHnlniaZ8u0Ejz22vR67vJTNKF1BRFC8AQIWUlzv98q3FysrdqNTvddTDV59D6QIqieIFADitsnKnn7++UK/lb9adF3fWz37QndIFnAGKFwDgO5WWlev+Vxfo7flb9dPLuunuS7tQuoAzRPECAJxSSVm57p05X+8t2qYHruiuOy/u4nUkIKRRvAAAJ3WktEx3Zc7TR0t36FfXnKOx3+vkdSQg5FG8AAD/o7ikTD+anq9PVxTq0et7aeR5HbyOBIQFihcA4L8cPlqmtGlz9NXqnfrjTX2UnNjO60hA2KB4AQD+4+CRUqVMyVPOut16/Ja+ui2+rdeRgLBC8QIASJL2F5do9KQ8zd24R0/f3l83xrX2OhIQdiheAAAVHS7RyIm5WrylSM8PGaBr+rb0OhIQliheABDh9h46quETcrV8+z69NHSAftCrhdeRgLBF8QKACLbrwBENzcjR2p0HNX54vC7u0czrSEBYo3gBQIQq2F+soek52rj7kCaMjNf3ujb1OhIQ9iheABCBthcVKzk9W9uKijVp9CCd17mJ15GAiEDxAoAIs2XvYSWnZ2vXgaOampKgQR0aeR0JiBgULwCIIJt2H9KQ9GwVHS7RtJQExbVr6HUkIKJQvAAgQqzbeVDJ6dk6dLRMmWOT1KdNfa8jARGH4gUAEWB1wQElp2ertNwpKzVJPVvV8zoSEJEoXgAQ5lZs36+hGdmSTDPTktSteV2vIwERK8rrAAAA/1mytUiDx3+r6CjTrHGULsBrjHgBQJhauHmvhk/IVe3q0cpMTVKHJrW9jgREPIoXAISh/A17NGpirurXilFWapLaNqrldSQAongBQNjJXbdboyflqmndGspMTVKrBjW9jgTAh+IFAGHkm9U7lTJljlo1iFVmapKa14v1OhKA43ByPQCEic9XFmr05Dy1a1RLM9POpXQBQYgRLwAIA7OX7dCPps9Vl2Z1NH1sohrVru51JAAnwYgXAIS4DxZv1x3T89WjZV1lplK6gGDGiBcAhLB3F27VPTPnq2+b+poyJkH1YmO8jgTgOzDiBQAh6s15m3V31jwNbNdQ01ISKV1ACGDECwBC0Ct5m/TzNxYqqWNjTRgVr1rV+XUOhAJGvAAgxEzP3qAHX1+oC7o00cRRgyhdQAjhXysAhJBJX6/To/9Yqkt6NNNLQwcoNiba60gAKoHiBQAhYvwXa/TH95fril7N9fyQAapejYMWQKiheAFACHjhk1V68sOVurZvSz39w/6KiaZ0AaGI4gUAQcw5p6c/XqXnZq/STXGt9cStfVWN0gWELIoXAAQp55we/9cK/e2zNbptYBv9+Za+io4yr2MBOAsULwAIQs45/f69ZZrw1ToNTWyn393QW1GULiDk+W282sxizSzXzBaY2RIze9Q3vZGZfWRmq3w/G/orAwCEovJyp9++s0QTvlqnUed10O9vpHQB4cKfJwockXSJc66fpP6SrjSzJEkPSZrtnOsqabbvMQBAx0rXw28u0tRvNyjtwk767XU9ZUbpAsKF34qXO+aA72GM7+Yk3SBpim/6FEk3+isDAISSsnKnB15bqJl5m3TXxV30i6t6ULqAMOPXj8aYWbSZzZdUIOkj51yOpObOuW2S5PvZ7BTPTTOzOWY2p7Cw0J8xAcBzpWXluu+V+Xp97mbdd3k3/eyK7pQuIAz5tXg558qcc/0ltZGUYGa9K/Hc8c65eOdcfNOmTf2WEQC8VlJWrrtnztPb87fq51f20N2XdvU6EgA/CcjFYJxzeyV9JulKSTvMrKUk+X4WBCIDAASjI6Vl+tH0uXp/0Xb96ppz9KOLOnsdCYAf+fNTjU3NrIHvfk1Jl0laLukdSSN9i42U9La/MgBAMCsuKdO4afn6eNkOPXZDL439XievIwHwM39ex6ulpClmFq1jBe8V59y7ZvatpFfMLEXSRkm3+TEDAASlw0fLlDp1jr5es1N/urmPhiS08zoSgADwW/Fyzi2UFHeS6bskXeqv9QJAsDt4pFQpU/KUu263nri1n24d2MbrSAAChCvXA0AA7S8u0ehJeZq3aa+e/mF/3dC/tdeRAAQQxQsAAqToUIlGTMrVki1Fen5InK7u09LrSAACjOIFAAGw5+BRDZ+YoxXb9+uloQP0g14tvI4EwAMULwDws50HjmhYRo7W7jyo8SPidXH3k143GkAEoHgBgB8V7CvW0IwcbdpzSBNHDtIFXZt4HQmAhyheAOAn24uKlZyere37ijV5dIKSOjX2OhIAj1G8AMAPNu85pOT0HO0+eFRTxyQovkMjryMBCAIULwCoYht3HdKQ9GztKy7RtJQExbVr6HUkAEGC4gUAVWjdzoNKTs/W4ZIyZaUmqXfr+l5HAhBEKF4AUEVWF+zXkPQclZc7ZaUm6ZyW9byOBCDIULwAoAos375PQ9NzZGaamZakrs3reh0JQBCK8joAAIS6xVuKNGR8tqpFm2aNo3QBODVGvADgLCzYtFfDJ+SobmyMMlMT1b5xba8jAQhiFC8AOEP5G3Zr1MQ8Nagdo6zUJLVpWMvrSACCHMULAM5AztpdGj05T83rxSozNVEt69f0OhKAEMA5XgBQSV+v3qmRk3LVsn6sZqUlUboAVBgjXgBQCZ+tKNC4afnq0Li2po9NVNO6NbyOBCCEULwAoII+XrpDP54xV12a1dH0sYlqVLu615EAhBgONQJABXyweJvumJ6vc1rWVVZqEqULwBmheAHAabyzYKvuzJynvm3qa9rYRNWvFeN1JAAh6rTFy8weN7N6ZhZjZrPNbKeZDQtEOADw2htzN+vemfM0sH1DTU1JVL1YSheAM1eREa8fOOf2SbpW0mZJ3SQ94NdUABAEXsnbpPtfXaCkTo01efQg1anBabEAzk5Fite//3t3taQs59xuP+YBgKAwLXuDHnx9oS7s2lQTRw1SreqULgBnryK/Sf5hZsslHZb0YzNrKqnYv7EAwDsTv1qnx95dqsvOaaYXhw5QjWrRXkcCECZOO+LlnHtI0rmS4p1zJZIOSrrB38EAwAsvf75Gj727VFf2aqGXhg6kdAGoUqcc8TKzS5xzn5jZzcdNO36RN/wZDAAC7fnZq/TXj1bqun6t9NTt/RQTzQe/AVSt7zrU+H1Jn0i67iTznCheAMKEc05Pf7RSz32yWjfHtdYTt/VTdJSd/okAUEmnLF7Oud/6fo4OXBwACCznnP78wXK9/Pla/TC+rf54cx9KFwC/qch1vKaZWf3jHrc3s9n+jQUA/uec02PvLtXLn6/VsKR2+hOlC4CfVeRTjV9JyjGz+yS11rFreN3v11QA4Gfl5U6/eWexpmdv1OjzO+g31/Y88TxWAKhypy1ezrmXzWyJpE8l7ZQU55zb7vdkAOAn5eVOD7+5SDPzNmnc9zvpoSt7ULoABERFDjUOlzRR0ghJkyW9b2b9/JwLAPyirNzpZ68t0My8Tbr7ki6ULgABVZFDjbdIusA5VyApy8zelDRFUn9/BgOAqlZSVq77XlmgfyzYqvsu76a7L+3qdSQAEaYihxpvPOFxrpkl+C0RAPjB0dJy3TNznv65eLseuqqH7vh+Z68jAYhApy1eZhYrKUVSL0mxx80a469QAFCVjpSW6c4Zc/XxsgL9+tqeSrmgo9eRAESoilyWeZqkFpKukPS5pDaS9vszFABUleKSMqVNzdfHywr0uxt7U7oAeKoixauLc+7Xkg4656ZIukZSH//GAoCzd+hoqVKm5OmLVYX6yy19NDypvdeRAES4ipxcX+L7udfMekvaLqmD3xIBQBU4cKRUYybnac763frrbf1084A2XkcCgAoVr/Fm1lDSryS9I6mOpF/7NRUAnIV9xSUaNTFXCzYX6ZnBcbq+XyuvIwGApIp9qjHDd/cLSZ38GwcAzk7RoRKNmJijJVv36YUhcbqqT0uvIwHAf1TkHK//MLN3/RUEAM7W7oNHlZyRrWXb9uvvwwZSugAEnYocajxea7+kAICztPPAEQ3LyNHanQc1fsRAXdS9mdeRAOB/VOQrg+4yswa+h/P8GwcAKq9gX7EGj8/W+l0HNWnUIEoXgKBVkRGvFpLmmNlcSRPNzJxzzs+5AKBCthUdVnJ6jnbsK9bk0QlK6tTY60gAcEqnHfFyzv1KUldJEySNkrTKzP5oZnzfBgBPbd5zSD98OVs79x/RtBRKF4DgV6GT630jXNt9t1JJDSW9ZmaP+zEbAJzShl0H9cOXs7X30FFNG5uoge0beR0JAE6rIt/VeLekkZJ2SsqQ9IBzrsTMoiStkvSgfyMCwH9bU3hAQ9NzVFxapszUJPVuXd/rSABQIRU5x6uJpJudcxuOn+icKzeza/0TCwBObtWO/UrOyFF5udPMtCT1aFHP60gAUGEVuYDqb75j3rKqjQMAp7Zs2z4Ny8hRVJRpZlqSujav63UkAKiUSl1AFQC8snhLkYakZysmOkqzKF0AQlRlL6AKAAE3f9NejZiQo7qxMcpKTVK7xrW8jgQAZ4TiBSCozVm/W6Mm5alR7erKTE1Um4aULgChi0ONAIJW9tpdGjExV83q1tCscUmULgAhjxEvAEHpq1U7NXZqnto2rKUZYxPVrF6s15EA4KxRvAAEnU9XFGjctHx1alJb08cmqkmdGl5HAoAqQfECEFQ+WrpDd86Yq67N62h6SqIa1q7udSQAqDIULwBB45+LtuknWfPUq3V9TR2doPq1YryOBABViuIFICi8PX+L7ntlgfq3baDJowepbiylC0D44VONADz3Wv5m/XTWfMW3b6ipYxIoXQDCFiNeADw1M3ejfvHmIp3fuYnSR8SrZvVoryMBgN8w4gXAM9O+Xa+H3likC7s2VcZISheA8MeIFwBPTPhqnX737lJddk5zvTg0TjWqUboAhD+KF4CA+9tna/SXD5brqt4t9OzgOFWvxuA7gMhA8QIQUM/NXqWnPlqp6/u10lO391O1aEoXgMhB8QIQEM45PfXRSj3/yWrdPKC1nri1n6KjzOtYABBQfvuvppm1NbNPzWyZmS0xs3t80x8xsy1mNt93u9pfGQAEB+ec/vzP5Xr+k9UaPKitnqR0AYhQ/hzxKpV0v3NurpnVlZRvZh/55j3tnHvSj+sGECScc3rs3aWa9PV6DU9qr0ev76UoSheACOW34uWc2yZpm+/+fjNbJqm1v9YHIPiUlzv9+u3FmpGzUSkXdNSvrjlHZpQuAJErIGe1mlkHSXGScnyT7jKzhWY20cwanuI5aWY2x8zmFBYWBiImgCpUVu700BsLNSNno+74fmdKFwAoAMXLzOpIel3Svc65fZL+JqmzpP46NiL215M9zzk33jkX75yLb9q0qb9jAqhCpWXl+tmrC/TKnM26+9Ku+vmV3SldACA/f6rRzGJ0rHTNcM69IUnOuR3HzU+X9K4/MwAIrJKycv101ny9u3CbfvaDbrrrkq5eRwKAoOHPTzWapAmSljnnnjpuesvjFrtJ0mJ/ZQAQWEdLy3VX5ly9u3CbHr66B6ULAE7gzxGv8yUNl7TIzOb7pj0saYiZ9ZfkJK2XNM6PGQAESHFJme6cMVezlxfot9f11OjzO3odCQCCjj8/1fiVpJOd1PG+v9YJwBvFJWVKm5avL1YW6vc39tawpPZeRwKAoMSV6wGclUNHSzV2yhx9u3aXHr+lr24f1NbrSAAQtCheAM7YgSOlGjMpT3M27NZTt/fTTXFtvI4EAEGN4gXgjOwrLtGoiblasLlIzw6O03X9WnkdCQCCHsULQKXtPXRUIybmatm2fXoxOU5X9m55+icBACheACpn98GjGpaRo9UFB/T3YQN16TnNvY4EACGD4gWgwgr3H9GwjByt33VQ6SPj9f1ufKsEAFQGxQtAhezYV6zk9Gxt3VusSaMG6bwuTbyOBAAhh+IF4LS27j2s5PRsFe4/oiljEpTQsZHXkQAgJFG8AHynTbsPKTkjW3sPlmhqSqIGtm/odSQACFkULwCntGHXQSWn52h/cYmmj01Uv7YNvI4EACGN4gXgpNYUHlByeraOlpYrKy1JvVrV9zoSAIQ8iheA/7Fyx34lp+dIcpqZdq66t6jrdSQACAtRXgcAEFyWbt2nweOzFWXSzLQkShcAVCFGvAD8x6LNRRo2IUe1qkcrMzVJHZvU9joSAIQVihcASdK8jXs0YmKu6sXGaGZakto2quV1JAAIOxQvAMpbv1ujJ+WpcZ3qykxNUusGNb2OBABhiXO8gAj37ZpdGjkxV83q1tCstHMpXQDgRxQvIIJ9uapQoyfnqnWDmpo5Lkkt6sd6HQkAwhqHGoEI9enyAo2bnq9OTWprxthENa5Tw+tIABD2KF5ABPpwyXbdmTlX3VvU1bQxiWpYu7rXkQAgIlC8gAjz3sJtumfmPPVuXV9TxiSofs0YryMBQMTgHC8ggrw9f4t+kjVX/ds20LQUShcABBojXkCEeC1/sx54bYESOzbShJGDVLsG//wBIND4zQtEgKzcjXr4zUW6oEsTjR8er5rVo72OBAARiUONQJib+u16/eKNRbqoW1Olj6B0AYCXGPECwljGl2v1+/eW6fKezfVCcpxqVKN0AYCXKF5AmHrps9V6/IMVurpPCz07OE4x0QxwA4DXKF5AmHHO6bnZq/X0xyt1Q/9W+utt/VSN0gUAQYHiBYQR55ye/HCFXvx0jW4d2EZ/uaWvoqPM61gAAB+KFxAmnHP64/vLlP7lOg1JaKs/3NhHUZQuAAgqFC8gDDjn9Og/lmryN+s14tz2euS6XpQuAAhCFC8gxJWXO/3q7cXKzNmosRd01C+vOUdmlC4ACEYULyCElZU7PfT6Qr2av1k/vqizHriiO6ULAIIYxQsIUaVl5frZqwv01vytuveyrrrn0q6ULgAIchQvIASVlJXr3pnz9d6ibXrgiu668+IuXkcCAFQAxQsIMUdLy3VX5lx9uHSHfnn1OUq9sJPXkQAAFUTxAkJIcUmZfjxjrj5ZXqBHruupUed39DoSAKASKF5AiDh8tExp0+boy1U79ceb+ig5sZ3XkQAAlUTxAkLAoaOlSpk8R9nrdunxW/vq9vi2XkcCAJwBihcQ5A4cKdXoSbnK37BHT93eTzfFtfE6EgDgDFG8gCBWdLhEoyblauHmIj03JE7X9m3ldSQAwFmgeAFBau+hoxo+IVfLt+/TS0MH6IpeLbyOBAA4SxQvIAjtOnBEwybkak3hAb08fKAu6dHc60gAgCpA8QKCTMH+Yg3LyNGGXYeUMSJeF3Zr6nUkAEAVoXgBQWTHvmINSc/Wtr3FmjRqkM7r0sTrSACAKkTxAoLE1r2HlZyercL9RzRlTIISOjbyOhIAoIpRvIAgsGn3IQ1Jz1bR4RJNG5uoAe0aeh0JAOAHFC/AY+t3HlRyerYOHi3TjLGJ6tumgdeRAAB+QvECPLS64ICS07NVWu6UmZqoXq3qex0JAOBHFC/AIyu279fQjGxJpqzUJHVvUdfrSAAAP6N4AR5YunWfhk3IUbUoU2Zqkro0q+N1JABAAER5HQCINAs379WQ9GzFVovSK+POpXQBQARhxAsIoLkb92jkhFzVrxWjrNQktW1Uy+tIAIAAongBAZK3frdGTcxVk7o1lJmapNYNanodCQAQYBQvIAC+WbNTKZPnqGWDWGWlJql5vVivIwEAPMA5XoCffbGyUKMn5alto5qalXYupQsAIhgjXoAffbJ8h+6YNledm9XR9JQENa5Tw+tIAAAPUbwAP/lg8Xb9JGuuerSop2kpCWpQq7rXkQAAHuNQI+AH7y7cqjsz56p36/qaPjaR0gUAkMSIF1Dl3pq3Rfe9Ml8D2zfUpNEJqlODf2YAgGN4RwCq0CtzNunnry9UUsfGmjAqXrWq808MAPD/ONQIVJEZORv04GsLdUGXJpo4ahClCwDwP3hnAKrA5K/X6ZF/LNUlPZrppaEDFBsT7XUkAEAQongBZyn9i7X6w/vL9IOezfVC8gBVr8ZAMgDg5ChewFl48dPVeuJfK3RN35Z65of9FRNN6QIAnBrFCzgDzjk98/EqPTt7lW6Ka60nbu2rapQuAMBp+O2dwszamtmnZrbMzJaY2T2+6Y3M7CMzW+X72dBfGQB/cM7p8X+t0LOzV+m2gW305G39KF0AgArx57tFqaT7nXPnSEqSdKeZ9ZT0kKTZzrmukmb7HgMhwTmnP7y3TH/7bI2SE9vpL7f0VXSUeR0LABAi/Fa8nHPbnHNzfff3S1omqbWkGyRN8S02RdKN/soAVKXycqdH3lmijK/WadR5HfSHG3sritIFAKiEgJzjZWYdJMVJypHU3Dm3TTpWzsys2SmekyYpTZLatWsXiJjAKZWXO/3yrUXKyt2ktAs76RdX9ZAZpQsAUDl+PzHFzOpIel3Svc65fRV9nnNuvHMu3jkX37RpU/8FBE6jrNzpgdcWKit3k+68uDOlCwBwxvxavMwsRsdK1wzn3Bu+yTvMrKVvfktJBf7MAJyN0rJy3ffKfL0+d7N+elk3/ewH3SldAIAz5s9PNZqkCZKWOeeeOm7WO5JG+u6PlPS2vzIAZ6OkrFx3z5ynt+dv1YNXdtc9l3WldAEAzoo/z/E6X9JwSYvMbL5v2sOS/izpFTNLkbRR0m1+zACckSOlZborc54+WrpDv7rmHI39XievIwEAwoDfipdz7itJpxoeuNRf6wXOVnFJmX40PV+frijUYzf00ohzO3gdCQAQJrhyPXCcw0fLlDp1jr5es1N/urmPhiTwiVoAQNWheAE+B4+UKmVKnnLW7dbjt/TVbfFtvY4EAAgzFC9A0v7iEo2elKd5m/bqmR/21w39W3sdCQAQhiheiHhFh0s0cmKuFm8p0vND4nR1n5ZeRwIAhCmKFyLanoNHNXxijlZs36+Xhg7QD3q18DoSACCMUbwQsXYeOKJhGTlau/Ogxg+P18U9TvrtVQAAVBmKFyJSwf5iDU3P0aY9hzRhZLy+15WvpQIA+B/FCxFne1GxktOztX1fsSaNStC5nRt7HQkAECEoXogoW/YeVnJ6tnYdOKqpYxIU36GR15EAABGE4oWIsXHXIQ1Jz9a+4hJNS0lQXLuGXkcCAEQYihciwrqdB5Wcnq3DJWXKHJukPm3qex0JABCBKF4Ie6sL9is5PUel5U6ZY5PUs1U9ryMBACIUxQthbcX2/RqakS3JNDMtSd2a1/U6EgAggkV5HQDwl8VbijR4/LeKjjLNGkfpAgB4jxEvhKUFm/Zq+IQc1Y2NUWZqoto3ru11JAAAKF4IP/kb9mjUxFw1qB2jzLFJatuolteRAACQRPFCmMlZu0tjJuepWb1YzRibqFYNanodCQCA/6B4IWx8vXqnxk6Zo1YNYpWVmqRm9WK9jgQAwH/h5HqEhc9XFmrM5Dy1a1RLM9POpXQBAIISI14IeR8v3aEfz5irLs3qaPrYRDWqXd3rSAAAnBQjXghpHyzepjum56tHy7rKTKV0AQCCGyNeCFn/WLBV986ar35t6mvymATVi43xOhIAAN+J4oWQ9MbczfrZqwsU36GRJo4apDo12JUBAMGPdyuEnFfyNunnbyzUuZ0aK2NkvGpVZzcGAIQG3rEQUqZnb9Cv3lqsC7s11fjhAxUbE+11JAAAKoyT6xEyJn29Tr96a7Eu7dGM0gUACEmMeCEkvPz5Gv3pn8t1Za8Wem5InKpX4/8MAIDQQ/FC0Ht+9ir99aOVuq5fKz11ez/FRFO6AAChieKFoOWc09MfrdRzn6zWzXGt9fitfVWN0gUACGEULwQl55z+8sEK/f3zNbo9vo3+dHNfRUeZ17EAADgrFC8EHeecfvfuMk38ep2GJbXTY9f3VhSlCwAQBiheCCrl5U6/fWeJpmVv0OjzO+g31/aUGaULABAeKF4IGuXlTg+/uUgz8zZp3IWd9NBVPShdAICwQvFCUCgrd3rgtQV6Y+4W/eSSLrrv8m6ULgBA2KF4wXOlZeX66SsL9I8FW3Xf5d1096VdvY4EAIBfULzgqaOl5bpn5jz9c/F2PXRVD93x/c5eRwIAwG8oXvDMkdIy3Tljrj5eVqBfX9tTKRd09DoSAAB+RfGCJ4pLyjRuWr4+X1mo393QS8PP7eB1JAAA/I7ihYA7fLRMY6fm6Zs1u/Tnm/tocEI7ryMBABAQFC8E1MEjpRozOU9563fryVv76ZaBbbyOBABAwFC8EDD7iks0elKe5m/aq2cGx+n6fq28jgQAQEBRvBAQRYdKNGJijpZs3acXhsTpqj4tvY4EAEDAUbzgd7sPHtXwCTlateOA/j5soC7r2dzrSAAAeILiBb/aeeCIhmXkaO3Ogxo/YqAu6t7M60gAAHiG4gW/KdhXrOSMHG3ec0iTRg3S+V2aeB0JAABPUbzgF9uKDis5PUc79hVr8ugEJXVq7HUkAAA8R/FCldu855CS03O0++BRTUtJ0MD2jbyOBABAUKB4oUpt3HVIQ9Kztb+4RNPHJqp/2wZeRwIAIGhQvFBl1hYeUHJ6jopLy5SZmqTeret7HQkAgKBC8UKVWLVjv5IzclRe7jQzLUk9WtTzOhIAAEEnyusACH3Ltu3T4PHZkkTpAgDgO1C8cFYWbynSkPRsxURHaVZakro2r+t1JAAAghbFC2ds/qa9Sk7PVu3q1TRrXJI6Na3jdSQAAIIa53jhjORv2K2RE/PUqHZ1ZaYmqk3DWl5HAgAg6DHihUrLXrtLwyfkqlndGpo1LonSBQBABTHihUr5atVOjZ2apzYNaylzbKKa1Yv1OhIAACGDES9U2KcrCjRmSp46NK6tmWlJlC4AACqJES9UyEdLd+jOGXPVtXkdTU9JVMPa1b2OBABAyKF44bT+uWibfpI1T71a19fU0QmqXyvG60gAAIQkihe+09vzt+i+Vxaof9sGmjx6kOrGUroAADhTnOOFU3otf7N+Omu+BrZvqKljEihdAACcJUa8cFIzczfqF28u0nmdGyt9RLxqVWdXAQDgbPFuiv8x7dv1+vXbS/T9bk318vCBio2J9joSAABhgeKF/zLhq3X63btLddk5zfXi0DjVqEbpAgCgqlC88B9/+2yN/vLBcl3Vu4WeHRyn6tU4BRAAgKpE8YIk6bnZq/TURyt1fb9Weur2fqoWTekCAKCq+e3d1cwmmlmBmS0+btojZrbFzOb7blf7a/2oGOec/vrhCj310UrdPKC1nv5hf0oXAAB+4s932MmSrjzJ9Kedc/19t/f9uH6chnNOf/7ncj3/yWoNHtRWT97aT9FR5nUsAADClt+Kl3PuC0m7/fX6ODvOOT327lK9/MVaDU9qrz/e1EdRlC4AAPzKi2NKd5nZQt+hyIanWsjM0sxsjpnNKSwsDGS+sFde7vSrtxZr0tfrNeb8jnrshl6ULgAAAiDQxetvkjpL6i9pm6S/nmpB59x451y8cy6+adOmAYoX/srKnR56Y6Fm5GzUHd/vrF9fe47MKF0AAARCQD/V6Jzb8e/7ZpYu6d1Arj/SlZaV64HXFurNeVt096Vd9dPLulK6AAAIoICOeJlZy+Me3iRp8amWRdUqKSvXvbPm6815W/SzH3TTfZd3o3QBABBgfhvxMrMsSRdJamJmmyX9VtJFZtZfkpO0XtI4f60f/+9oabl+kjVX/1qyQw9f3UNpF3b2OhIAABHJb8XLOTfkJJMn+Gt9OLnikjLdOWOuZi8v0G+v66nR53f0OhIAABGLK9eHseKSMqVNy9cXKwv1+xt7a1hSe68jAQAQ0SheYerQ0VKNnTJH367dpcdv6avbB7X1OhIAABGP4hWGDhwp1ZhJeZqzYbeeur2fbopr43UkAAAgilfY2VdcolETc7Vgc5GeHRyn6/q18joSAADwoXiFkb2HjmrExFwt27ZPLybH6creLU//JAAAEDAUrzCx++BRDcvI0eqCA/r7sIG69JzmXkcCAAAnoHiFgcL9RzQsI0frdx1U+sh4fb8bX7EEAEAwoniFuB37ipWcnq2te4s1adQgndelideRAADAKVC8QtjWvYeVnJ6twv1HNGVMghI6NvI6EgAA+A4UrxC1afchJWdka+/BEk1NSdTA9g29jgQAAE6D4hWCNuw6qOT0HO0vLtH0sYnq17aB15EAAEAFULxCzJrCA0pOz9bR0nJlpSWpV6v6XkcCAAAVRPEKISt37Fdyeo4kp5lp56p7i7peRwIAAJVA8QoRS7fu07AJOaoWZcpMPVddmtXxOhIAAKikKK8D4PQWbS7SkPRs1agWpVnjKF0AAIQqRryC3LyNezRiYq7qxcZoZlqS2jaq5XUkAABwhiheQSxv/W6NnpSnxnWqKzM1Sa0b1PQ6EgAAOAscagxS367ZpZETc9Wsbg3NSjuX0gUAQBigeAWhL1cVavTkXLVuUFMzxyWpRf1YryMBAIAqwKHGIPPp8gKNm56vTk1qa8bYRDWuU8PrSAAAoIpQvILIh0u2687Muereoq6mjUlUw9rVvY4EAACqEMUrSLy3cJvumTlPvVvX15QxCapfM8brSAAAoIpxjlcQeHv+Fv0ka676t22gaSmULgAAwhUjXh57LX+zHnhtgRI7NtKEkYNUuwZ/JQAAhCve5T2UlbtRD7+5SBd0aaLxw+NVs3q015EAAIAfcajRI1O/Xa9fvLFIF3VrqvQRlC4AACIBI14eyPhyrX7/3jJd3rO5XkiOU41qlC4AACIBxSvAXvx0tZ741wpd06elnhncXzHRDDoCABApKF4B4pzTs7NX6ZmPV+mG/q3019v6qRqlCwCAiELxCgDnnJ78cIVe/HSNbh3YRn+5pa+io8zrWAAAIMAoXn7mnNMf31+m9C/XaUhCO/3hxt6KonQBABCRKF5+5JzTo/9YqsnfrNfIc9vrket7yYzSBQBApKJ4+Ul5udMv31qsrNyNGntBR/3ymnMoXQAARDiKlx+UlTv9/PWFei1/s358UWc9cEV3ShcAAKB4VbXSsnL97NUFemv+Vt17WVfdc2lXShcAAJBE8apSJWXlunfmfL23aJseuKK77ry4i9eRAABAEKF4VZEjpWX6SeY8fbh0h3559TlKvbCT15EAAECQoXhVgeKSMv14xlx9srxAj1zXU6PO7+h1JAAAEIQoXmfp8NEypU2boy9X7dQfb+qj5MR2XkcCAABBiuJ1Fg4dLVXK5DnKXrdLj9/aV7fHt/U6EgAACGIUrzO0v7hEYybnKX/DHj19e3/dGNfa60gAACDIUbzOQNHhEo2cmKtFW4r03JA4Xdu3ldeRAABACKB4VdLeQ0c1fEKulm/fp5eGDtAVvVp4HQkAAIQIilcl7DpwRMMm5GpN4QG9PHygLunR3OtIAAAghFC8Kqhgf7GGZeRow65DyhgRrwu7NfU6EgAACDEUrwrYXlSs5IxsbdtbrEmjB+m8zk28jgQAAEIQxes0tuw9rOT0bO3cf0RTxiQooWMjryMBAIAQRfH6Dpt2H9KQ9GwVHS7RtLGJGtCuodeRAABACKN4ncL6nQeVnJ6tg0fLlDk2SX3a1Pc6EgAACHEUr5NYXXBAyenZKi13ykpNUs9W9byOBAAAwgDF6wQrtu/X0IxsSaaZaUnq1ryu15EAAECYiPI6QDBZsrVIg8d/qyijdAEAgKrHiJfPws17NXxCrmpXj1ZmapI6NKntdSQAABBmKF6S5m7co5ETclW/VoyyUpPUtlEtryMBAIAwRPGStHnPYTWtW0PTxyaqVYOaXscBAABhiuIl6fp+rXRFr+aqUS3a6ygAACCMcXK9D6ULAAD4G8ULAAAgQCheAAAAAULxAgAACBCKFwAAQIBQvAAAAAKE4gUAABAgFC8AAIAAoXgBAAAECMULAAAgQPxWvMxsopkVmNni46Y1MrOPzGyV72dDf60fAAAg2PhzxGuypCtPmPaQpNnOua6SZvseAwAARAS/FS/n3BeSdp8w+QZJU3z3p0i60V/rBwAACDaBPseruXNumyT5fjY71YJmlmZmc8xsTmFhYcACAgAA+EvQnlzvnBvvnIt3zsU3bdrU6zgAAABnLdDFa4eZtZQk38+CAK8fAADAM4EuXu9IGum7P1LS2wFePwAAgGf8eTmJLEnfSupuZpvNLEXSnyVdbmarJF3uewwAABARqvnrhZ1zQ04x61J/rRMAACCYBe3J9QAAAOGG4gUAABAgFC8AAIAAoXgBAAAEiDnnvM5wWmZWKGmDn1fTRNJOP68j0rBNqxbbs+qxTasW27PqsU2rXiC2aXvn3Emv/h4SxSsQzGyOcy7e6xzhhG1atdieVY9tWrXYnlWPbVr1vN6mHGoEAAAIEIoXAABAgFC8/t94rwOEIbZp1WJ7Vj22adVie1Y9tmnV83Sbco4XAABAgDDiBQAAECAULwAAgACJqOJlZhPNrMDMFp9ivpnZc2a22swWmtmAQGcMNRXYpheZWZGZzffdfhPojKHEzNqa2admtszMlpjZPSdZhv20Eiq4TdlPK8jMYs0s18wW+LbnoydZhn20Eiq4TdlHK8nMos1snpm9e5J5nu2j1QK1oiAxWdILkqaeYv5Vkrr6bomS/ub7iVObrO/eppL0pXPu2sDECXmlku53zs01s7qS8s3sI+fc0uOWYT+tnIpsU4n9tKKOSLrEOXfAzGIkfWVm/3TOZR+3DPto5VRkm0rso5V1j6RlkuqdZJ5n+2hEjXg5576QtPs7FrlB0lR3TLakBmbWMjDpQlMFtikqwTm3zTk313d/v4790mh9wmLsp5VQwW2KCvLtdwd8D2N8txM/pcU+WgkV3KaoBDNrI+kaSRmnWMSzfTSiilcFtJa06bjHm8Uv6Kpwrm8I/Z9m1svrMKHCzDpIipOUc8Is9tMz9B3bVGI/rTDfIZz5kgokfeScYx89SxXYphL7aGU8I+lBSeWnmO/ZPkrx+m92kmn8r+PszNWx76zqJ+l5SW95Gyc0mFkdSa9Lutc5t+/E2Sd5CvvpaZxmm7KfVoJzrsw5119SG0kJZtb7hEXYRyupAtuUfbSCzOxaSQXOufzvWuwk0wKyj1K8/ttmSW2Pe9xG0laPsoQF59y+fw+hO+felxRjZk08jhXUfOd4vC5phnPujZMswn5aSafbpuynZ8Y5t1fSZ5KuPGEW++gZOtU2ZR+tlPMlXW9m6yXNlHSJmU0/YRnP9lGK1397R9II36cdkiQVOee2eR0qlJlZCzMz3/0EHdvndnmbKnj5ttUEScucc0+dYjH200qoyDZlP604M2tqZg1892tKukzS8hMWYx+thIpsU/bRinPO/cI518Y510HSYEmfOOeGnbCYZ/toRH2q0cyyJF0kqYmZbZb0Wx07iVHOub9Lel/S1ZJWSzokabQ3SUNHBbbprZJ+ZGalkg5LGuz4uoTvcr6k4ZIW+c73kKSHJbWT2E/PUEW2KftpxbWUNMXMonXszf8V59y7ZnaHxD56hiqyTdlHz1Kw7KN8ZRAAAECAcKgRAAAgQCheAAAAAULxAgAACBCKFwAAQIBQvAAAAAKE4gUAJzCzO8xshNc5AIQfLicBAAAQIIx4AQhpZjbIzBaaWayZ1TazJSd+z52ZXWdmOWY2z8w+NrPmvunPmdlvfPevMLMvzCzKzB4xs5/5pt9tZkt965gZ+D8hgHDCiBeAkGdmv5cUK6mmpM3OuT+dML+hpL3OOWdmYyWd45y738xqScqTdJekv0u62jm3xswekXTAOfekmW2V1NE5d8TMGvi+Sw8AzkhEfWUQgLD1mI4VqGJJd59kfhtJs8yspaTqktZJknPukJmlSvpC0k+dc2tO8tyFkmaY2VuS3qr66AAiCYcaAYSDRpLqSKorKdbM/mBm84/7bsbnJb3gnOsjaZyOjY79Wx8d+7LhVqd47WskvShpoKR8M+M/rADOGMULQDgYL+nXkmZI+otz7pfOuf7Ouf6++fUlbfHdH/nvJ5lZe0n3S4qTdJWZJR7/omYWJamtc+5TSQ9KaqBjBQ8Azgj/cwMQ0nyXfSh1zmWaWbSkb8zsEufcJ8ct9oikV81si6RsSR3NzCRNkPQz59xWM0uRNNnMBh33vGhJ082sviST9DTneAE4G5xcDwAAECAcagQAAAgQihcAAECAULwAAAAChOIFAAAQIBQvAACAAKF4AQAABAjFCwAAIED+D8ximvoaIlo9AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 0. import matplotlib\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# 1. prepare data\n",
    "x = np.array([1,2,3,4])\n",
    "y = np.array([11,22,33,44])\n",
    "\n",
    "# 2. setup plot\n",
    "fig,ax = plt.subplots(figsize=(10,10))\n",
    "\n",
    "# 3. plot data\n",
    "ax.plot(x,y)\n",
    "\n",
    "# 4. customize plot\n",
    "ax.set(title=\"Simple plot\",xlabel=\"x-axis\",ylabel=\"y-axis\")\n",
    "\n",
    "# save and show\n",
    "fig.savefig(\"same-plot.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Making figures with NumPy arrays\n",
    "\n",
    "* Line plot\n",
    "* Scatter plot\n",
    "* Bar plot\n",
    "* Histogram\n",
    "* Subplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.        , 0.1010101 , 0.2020202 , 0.3030303 , 0.4040404 ,\n",
       "       0.50505051, 0.60606061, 0.70707071, 0.80808081, 0.90909091])"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create some data\n",
    "x = np.linspace(0,10,100)\n",
    "x[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1ee56637100>]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "# Plot data\n",
    "fig, ax = plt.subplots()\n",
    "ax.plot(x,x**2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x1ee56686970>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "# same data\n",
    "fig,ax = plt.subplots()\n",
    "ax.scatter(x,np.exp(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x1ee566e7b80>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "# another scatter plot\n",
    "fig, ax = plt.subplots()\n",
    "ax.scatter(x,np.sin(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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": [
    "# make plot from dict\n",
    "nut_butter_prices = {\"Almond butter\":10, \"Peanut butter\": 8,\"Cashew butter\":12}\n",
    "fig,ax = plt.subplots()\n",
    "ax.bar(nut_butter_prices.keys(),nut_butter_prices.values())\n",
    "ax.set(title=\"Bhupend's Butter Store\",ylabel=\"Price($)\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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,ax = plt.subplots()\n",
    "ax.barh(list(nut_butter_prices.keys()),list(nut_butter_prices.values()));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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": [
    "# make some data for histogram\n",
    "x = np.random.randn(1000)\n",
    "fig,ax=plt.subplots()\n",
    "ax.hist(x);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Two options for subplots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# subplots option 1\n",
    "fig,((ax1,ax2),(ax3,ax4)) = plt.subplots(nrows=2,ncols=2,figsize=(10,5))\n",
    "\n",
    "# plot to each diff axis\n",
    "ax1.plot(x,x/2)\n",
    "ax2.scatter(np.random.random(10),np.random.random(10))\n",
    "ax3.bar(nut_butter_prices.keys(),nut_butter_prices.values())\n",
    "ax4.hist(np.random.random(100));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# subplots option 2\n",
    "fig,ax = plt.subplots(nrows=2,ncols=2,figsize=(10,5))\n",
    "\n",
    "# plot to each diff index\n",
    "ax[0,0].plot(x,x/2)\n",
    "ax[0,1].scatter(np.random.random(10),np.random.random(10))\n",
    "ax[1,0].bar(nut_butter_prices.keys(),nut_butter_prices.values())\n",
    "ax[1,1].hist(np.random.random(100));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting from pandas DataFrames"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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>Make</th>\n",
       "      <th>Colour</th>\n",
       "      <th>Odometer (KM)</th>\n",
       "      <th>Doors</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>White</td>\n",
       "      <td>150043</td>\n",
       "      <td>4</td>\n",
       "      <td>$4,000.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Honda</td>\n",
       "      <td>Red</td>\n",
       "      <td>87899</td>\n",
       "      <td>4</td>\n",
       "      <td>$5,000.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>Blue</td>\n",
       "      <td>32549</td>\n",
       "      <td>3</td>\n",
       "      <td>$7,000.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BMW</td>\n",
       "      <td>Black</td>\n",
       "      <td>11179</td>\n",
       "      <td>5</td>\n",
       "      <td>$22,000.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Nissan</td>\n",
       "      <td>White</td>\n",
       "      <td>213095</td>\n",
       "      <td>4</td>\n",
       "      <td>$3,500.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>Green</td>\n",
       "      <td>99213</td>\n",
       "      <td>4</td>\n",
       "      <td>$4,500.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Honda</td>\n",
       "      <td>Blue</td>\n",
       "      <td>45698</td>\n",
       "      <td>4</td>\n",
       "      <td>$7,500.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Honda</td>\n",
       "      <td>Blue</td>\n",
       "      <td>54738</td>\n",
       "      <td>4</td>\n",
       "      <td>$7,000.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>White</td>\n",
       "      <td>60000</td>\n",
       "      <td>4</td>\n",
       "      <td>$6,250.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Nissan</td>\n",
       "      <td>White</td>\n",
       "      <td>31600</td>\n",
       "      <td>4</td>\n",
       "      <td>$9,700.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Make Colour  Odometer (KM)  Doors       Price\n",
       "0  Toyota  White         150043      4   $4,000.00\n",
       "1   Honda    Red          87899      4   $5,000.00\n",
       "2  Toyota   Blue          32549      3   $7,000.00\n",
       "3     BMW  Black          11179      5  $22,000.00\n",
       "4  Nissan  White         213095      4   $3,500.00\n",
       "5  Toyota  Green          99213      4   $4,500.00\n",
       "6   Honda   Blue          45698      4   $7,500.00\n",
       "7   Honda   Blue          54738      4   $7,000.00\n",
       "8  Toyota  White          60000      4   $6,250.00\n",
       "9  Nissan  White          31600      4   $9,700.00"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# make dataframe\n",
    "car_sales = pd.read_csv(\"car-sales.csv\")\n",
    "car_sales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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zrXMYbTc8g22dpReL/vuyXfjCn6RO90YXyqIpMdlXhy3WqIEoLOrrYFjWF6r2GPtm81vrcKZBvnwqbDaG7505R/l7XLUnZwWJvaoF3L19Pkyoi1841aPuZtVY6VJuCnYbM0wVVefdk4ZNPJYz8kKAaDTBwXpve48preve3tqNU+94AwDwn3WlVwi0XZV5YOTJz1bFPUVKZShC4ZpC8MHOXsW4q2PyA7KCaCIjny2Pfe1o/Pdps1Dpzp2WTY9qAXfFrj4cNqUu5WvU4RqbjSk3CluC6K1LFX4cDlCNjR7LGXkhJTqS4CS79L5l+OpfV8Rtf2dbN55asy/jz+uWS7h/9PR6ZZvDxtCZB33tfGJj6ilvfFxzksrDWrpQUp4IkyefdwZ8IVx8z3v45kOrAGjDNbt6pKyzapPCEUumNuCbp8yE22mHX1dB2jnkx5sfdWX8nt0qiYRgOIp5E2tTvsbjtOPGcw7Gf582CwCUmXWi8KHaeydPPh7LGflUnrygc0hrhC+/fzm+9ciajD7rxQ0HsPhnL2P5jh74VTeVt7d1Y8mtr+D1LZ1JXl1cqL0gI0/e5bDh1INbcMsF8zBrvJRHT0Y+/wgjtXpPPwBtuOazf5Q0hcyOOXudds31AACf/+P7+Pyf3s94dtejS8VMtegq+Mrx0/DNU2amta+6nqMQYV6rYzkjXykb+USevGDJLa9kra/yhuyZbGof1AgiLdsh6XZ89x9rNZ12ihl1VWOihbv7v3AELj/yIDjlpg5hCtfkHWHkRfqqkbpiupWsY8XjtMUtvO6QZQ66MxQv07fyTNfIq/nsUVOSPq/W7RmlvghxWM7ICwGidA7Wzf+OL559as0+BMKRtGKKQpHR47QjYLDQ1D0cVLynYkedjupIFNwUz8sLWWHKrsk7Q7KRF7OoYX/8dXBQY0XctlxS4XLESQ+Lqmh9j+BU9AwHNTelWq+xLHIyLltyUNLnv3fWHLzw7RMAUEzeCMsZeeHJpzPtMsqZ/dYja3Deb9/GwT96PuXrRXrXcCCsaTlWiqin2al+W9GejcI1+Ufx5OXfXp8nf90ZszFOVZVsBq31XgTDUXSoDLoomOrMsFCxeziIpkoXKuWq2oYE2vfJSNSrVlDhcmByg7SmRDH5eCyXJy+mc6IXaTK8CXS0P+pILwXSLhuz/tFQnH51qaHu4ZqqxizmyZf2b2JFFCMve9H6G3Kicz6XTGuS1mR2dA1jfK10QxGzv0yNaO9IAI1Vbtx56SK0D/jHZOQTtfxT43XawZjxzKfcsZyR9zjtSbvHO2xM8TCF5oZI+avxOOK0PpIhXtfvK331xUFfCK31Xlx5wjRFpjUR4oIOkSefd4TnbpfvxHpZA72CqBkIR2tIZdCFznumMuA9I0E0VrlwRFvDmMeTypMHpHDknPE1+N1r23DMjEYcMz09SYdywHLhGgAYV+NJGPtTn+QiFVAsTk3XqSumQpywfUlmDUe01Sd8rljoHQnimQ/bUVfhxOePbtMswhrBGIPdxhAhWYO8EYpEcc5db+H59QcAxGZbQ/6wJi/ek0LSIBeIGLo6xCdu9xkb+eHgmLx3NV6nHQdPqMGdlyxMup/Iwb/svuX4/evbsvrMUsKSRr6pyp1wFT8a5aiXPY2WGkmhTrT+mtGcmZEXIQwjQbQXvn0CjmirL4lWhA+/vxsAsH7fYNqvcdgYLbzmkY5BPzbsH1SacauNfFNVTIkxH+EakX2lNvLCk/dlcD1wztE9HNCMfywwxvDct45X6jcS8ZXjpymPb39+C/V9lbGkka/yOBIuDgYjUVy6ZArG13hQ4bLDH4oooR29J3/Hi1uSfo7IwNGHhu77/GLMHl+N5mp3SXSpEoJjE2vTX7Bz2m2kXZNH9GJ84QjH61s6sa/fp5GXSNTPNZc4ZU9e3W1JTOrSvR5+9NR6fPcf6xAIRxM2Gs81U5sqNWJrq+RGI+WONY2829jI944EEYpwOGwMTgdDKMJx6h1vKI2n9Z78Xa9KU7Z/rNiD7Qba6OKEPaAz8qfNHQcA8DjiK/+KEbGo/LevHJn2a+w2RiqUeSSky+4KRzn++p7Uik/dXyEvRl5eeA+qbvLiWjEy8it29mJTu3aW+Nf3duHxVXsBAI1ZevKZoNax2bA//ZlrKWNZI2+0in/XK1sBAB2DAQz5w3hi9T7s7fMpz09JkD983T/X4fTfvBm33aecuMbGzO20l0S4RtwwJ9amFocSOO2MUijziFF2lxCS+/apscrPvIZrVDceEdo0MvKfuuc9nHXnWwnfL1+ePKCdESVK3ig3LGnkK90OjBgUNXwsV91985QZhimWRs0PorKhMlJU1N9I5k6owUNfjXm7dRVOdA8HsLevuDtVjQTCsLHMFu0q3Q5FEIswH6NivH39PswaV4VLl8QqPlNpyecCpy4mH41yxSHSV8KqC6YS0ViVRyOvepwrkbVix5JGvsptRzAS1WhRR6IcK3f14fIjp6C13thj9zrt+NG5czXbQglCDit39WHQH0abyvv/1qkzNalXFx/eCs6Be97YjrYbnsEHO3uz+VoFYyQQQaXbkVETlrkTarCeeu3mjYBBWLBnOIgKl0MjDd3WWGn6WPTZNeqQpX7hdSCNFoP5DNeoT/F/rNyLG5/8MG+fbVUsaeSFR6725vtGgxgOhDWSuHq8Tju+dNxUXHRYq7It0eLh/W/tAACccUhM90If75zaVImmKjf+vkzKTnnuwwMZfhNrsGxHT8aiVlMaKnBggKa7+UK9yClmXAO+EJx2ppEFyEdMXtRJiJi8upBuWJexom5SEgxHwTmP8+7z2fyHQevIiGu3nDHNyDPGfsIY28cYWyP/Ozvd14oTWR3/E+GZuorEUz/h8Zw4u1nZpl/QUrZHpDZ3x8yIee762CFjDJNU3eGTNSC2Mls7h5W+renicdoRCEeVcJdgT+9oSertFxq1rMZBDZK3PhwIw2m3weu04/NHH4Qnrz42L2NhjMFpZ7jrla14aWOHJuyhl1loH4itic268Tn8Y+XeOMfKk8dG29QxNB6zf/3fcM4Xyv+eTfdFYuFH7d30j0pVqXVJvAKb7IGct2AivvYJKWdWHUNUl+kP+UOY0VKlWcg6ZGJN3HuOU3WLt2V4Bg36Q2nFLM0kFIkiEuWY1pTZNF/caO+VZzyCs+98C9c8tLrg36vUUBv5yao0QIfdBsYYbl46Dwsn1+VtPMJQf+exNRpPXm/k9+tme8992B4XCzfq5mQWRuty5Y4lwzVicUmdcRDz5NOb+o2rlnLC+0ZjkgUdqqKnAV8INV6nZipsFLNWd6nJ5FztGgpg/k9exDUPr07/RSYgZkOZTvO98jG47bnNmu2i1L3UBd3yjTomf6Rq1uVMUZ1sNkP+sKII21TljpNZ2NoxpPl7f78fWzu12/JJcx7j/8WC2Ub+GsbYOsbYnxhjhvoAjLErGWMrGGMrurokfXcjT375x1ITalEifcKsZkxpqMA9nz3c8IOr5FLwvpHYSdmlMvJDfqnhr1G/UzUnzIqFfoSgWTqI9K1n1rWn/RozECmgmZbDp7opUOZCbhE345PntOBUuU4DsEaIUCyujqtxx3nyq3f3a5IXtnQM4VP3vJfX8ak55eCWgn22VcnKyDPGXmaMrTf4txTAHwBMB7AQQDuAXxu9B+f8Xs75Ys754uZmyaAK71rtLa7bO4CZLVVKZs1fv7QEb15/kiJxoKdGNvLqpgXqGP+gL4QaryOlkW9rip3Ad72yFW03PJN0f4FVOtSI7+zO0JNPFZkaLYFKYCvxzrYe1Hgc+P3lh2kWKp15DHUkYtXufgCSptRQIKwJe/aOBHH4QWMXH8s1Fy+ejDeuO1FJhW6t98atK5UbWZ1BnPNTOefzDP49xTnv4JxHOOdRAPcBWJLu+woj36Vq8TccCBs2S6hNYOTHy4U/33lsrbJN3DQiUY6hQBi1unCN4VgMLrJgGqEKq+haizBApuGaVIVQ5Mnnlj19o1gwuQ4ep11RVwWsYeQ3y9Ws42StqHN/+7bynHCWDp2UundrvjiosRLHTG/CpUsmY2+fD9c+tqbQQyooZmbXTFD9eQGA9Yn21SO866v+vkppqD0cCKPKYFGlLkGnmVY5K0ZdBPXe9h48sXqvEleUwjXJjZ/RolE6ucHW8eTlcE2GGQ5GxWPqxVYy8rll0BdS0lzdDpvSkzdVF698sK9fyqBpkde5Nh+QYu7CWarxOPH3L6cvmZEvhA79U2ukbLBM+9OWCma6Cbczxj5kjK0DcBKAa9N9ocseM7yiE82QP6zE2dWIhVi9l29USn3PG9tx7aNrFSOtX3g1wugiS8fIqzMSCpmJMtaFVyMFSnWmEvXSzC1qSWHGmNIhzZnH9MNEKEa+RruoKRp01HidCWfUhUS9nrFsRw9m/vA5rN5dfqJlpp1BnPPPcc4P5ZzP55yfzzlPewVSbXifWL0PgHRCVRsU9Hicdtx16SI8cuVRmu2MMXzuKOPekELwqdabeuHV6CYwkEaTEXW4ZrSAXm9s4TUzI3/R4bGCMiH7LCSdgfjydiI7Bv1StpdA9E0odHZNtcehZLbpZ9JCyjefxU5jRSRArCxDZcrCuwkGqA3rH9/+GD3DAQQjUcNwDQCcv2AiJhiIbyWKZ364TyrXr/GkXng18uS7h42N/MpdvbjpyfXgnGsMeyF1rYUxzlTYSn3hPihXDd75ykex96VwTc4IhqPwh6JKs2wgNoNNdK6ZzVnzpEpwoQVvt7G4OhFlRmwww7Ya4hq0Qvgr31jeyAPA1/++CgA0C1Lp4HQYH9Btcg/YGq8zpZ6LUUx+ywHjPOBvPbIGf1u2C3t6fZrFWbUHnG/EhTgWb+u8BVKbQPETPfz+HuW5Uu+Jm09ELUedQYhRL4OdL+66dBHW/vh0JXutqcqF42dqW+oNqsKeRjx59bF4/bsnmjrOdBHhx56R0m/1qceSRl7vXQut6kxDDonu2v+SQ0CJTk41an3qP12xGAAMtemBmJTvhv0DmkWeQnryB+Sy87HETO/49AK4HDbc++YOJZbZJCsKUjFU7tgpq6u21sfPRgvVTN1pt6HW69S026yrcOG/Tp4BxiRlykFVAgMAPPAlKYFuZksVbrvwUCycXIe2DCutc4pqWUk4O4WaGRUSSxr5ep0+jThWmRb0pLo+hHf700/Ow1MJdEHUIZ+T54zDgsl16E3gDdR4pWlr90hQ4+nqqwTzBeccv3pRCrFUj6Hc22m3obXei+FAGBf8/l0AwPkLpBZsZOSzo33Ah8/evxzr9w3gc396HwAw2cDI64uP8s3aPVJos0PuuVztcYJzYCQYVmaowoFYOLkOjZUu3HLBobhEJY9cKC4/UlqTc9ltyjVrldTmfGJJI69vNC3S+Twp0h31qBtRf+W4qfju6bNwxTFtyrZK2Uv53FEHYUECXRD9bKChwqmRSlAj0jH7RoKWCNeoP9c2xlikPkQmbmTp1AoQifnk3e/g7W3dOPe3byMYjmJSnRfTmmKdzf551dEAjBf+84nQc7rns4cBiFWSD/nDKk9e2lbrdWLlTadlLIZnFlMaK/C1T0xDMBLFRjkaYJXU5nxi2RWTt793Eo77xWsAYouHYy3oufGcgzVNfv/y7k4Axlo1evT71Fe48FGHcbhGhGj6RoMIRaJw2qUWhYUK15jRsV4cAyP9cyI9IlGueMaC68+crbkRL25rwP+cfwhOnlPYMv17Pns4dvaMYNEUSZVEpHkOB8LoGg7AZbcp6Z5W5DOLJ+P/3oiJ7A0XeGZUCCzpyQNAa30F/vzFIwBAWfxJlQmjR5Qz62cGP116CC5clLzzeyLqK13oHQka5r6Lm1H/aAjBcBSNlVJmwmAaefVm8H9vSie3iJWOBbXHfsz0RmUmRJ782FFrKAmM1oe+cEybRpGyENRXuhQDD8TSKIf8Iezr82FinWfMs8R8ME3V9/nIqQ2KwF45YVkjDwAnzW7BtOZKZWU8U/2VkGzk9SGXzx3dhjs+s3BMY5pQ64EvFDEMwYi0wv39Pjy5Zj96R4PwOG0Fi6uKArFjpjeO+T3UPW5/dfECeJx2OO2MYvJZ0G9QZ1EMueYAlFqVIX8Y+/p9mn4LVuUbJ07H5AYvJtZ5MRwwdrhe3tgR14y8VLC0kQekOLy4+2a88BoRnnzuvqbIgNhj0PdVePLLP5baBAbDUdgYw8ubOnL2+ZngC0bwmcWTs9I/6RmOeZ3jaqSydpfdVpaefCTK8dtXtma9kG7UnzjT9aZCUSuvyfSPhjDgCyVt4mMVrj9zDt66/mRUuu2GvaMB4Ct/XZG0GXkxY30jrzLsmcbkI9zYk88GIXxm1AneKPY+Goxge9dI3mPYkShH93AgrhQ9U0TziCevPlYJe7md9rKMyT+3vh2/fukj/PKFLVm9j2iAoz4vx2V5nPKFKDpsH/AjEIoWzc0JkORSEnWKK2Usb+TVebqZGvkvHzcVjZUunDinOfXOSfjemXPw5yuk9QGRbeLXNTTmnBvGWsXFq9/fbHqGA4hyoKU6O+Px6NeOwnVnzNZ0JeodCZZl70xxDLPN0LhKLu6bIofTLj68Na/NrrOh0u1AXYUT+/pH4Q9FMp5dFxKngyFgkFdd6l3OLH+ERIcnwFh0LBkHT6jByptOU9TzxsrXT5yOk+QsByE9rPdkhwLhuNJ0ALjmpBkA8r9QKcrim7P87oum1ONq+TvoMVKq/PJfPsBPnt6Q1WcWA9EoxwPv7swq73rxQdKCZrrdzqxCS7UbXUMB2cgXkydvQygSxV5dqLXU15csb+Rb5ewCt8NmiRNKaU2oOzGEFz9Fp4Yp8pzzLQOws0eqojQjDCDkDoxCNq9s7lRSVEsNtcf3yuZO/PjpDfjVi5mFbiJRDqed4apPTMdUOS9e3/ja6lS4HHh9SxdGgsXlybvsNnAOHPeL1/DihgPK9lIvkLL8ERJVgFbRgo558trxdMp5z1MajI18IM+qja9u6kRDpQvzTGjmcNiUOgBAIM8hqEIjbDwDQ6/ccSzTvOvXt3QiFOGY3lyJiXXSLMtofcfK7O/3Ked/McXk1bLN6/YOKI8LqRKbD6xv5GWjaZUOXiKNM86TH9Ya+YWT67D8B6co2vj59uR3945iZkuVKZ2FxIzKX0KLr89+2J4yhU5kT7208QBW7eoHoF0zSgdhXM5bMBHja4rTyKvPZSvMrtNFfS1wlbDNSIn3RrC8kRcpizNaqlLsmR/cDuOYvOhgJfKGJzdUYFyNR9k/3zH59gE/JtWZk8Os/AY6T75QYlrZEo1yfOPBVSlT6ITHN+gP49EVkiJnphLOnUN+NFW54XHacbAsGXDZkcZ9D6xKRBVeKqpwjcqTV6+19pa4aJl165FlJtV5cd0Zs3He/ImFHgoAKe2NsfhwTf9oCIxByRuOymeRq0BGvnPIj5aa7BZdE5HIk0+Ug2x10pXzNeqGle5MaTQYxoW/fxcHBv2KWmmNx4mdt52T/kAtgrr/b6YFioXEpVKUVQcGVu/pB5D5DbtYsPxtmDGGq0+aEbegWSgYY3A74ouBAuEIPA477LLWDS+gkY9EOUIRbpqXJd5X78kPq4xgMaWliU5hqTCK3epbQW45MIRfv7gl7vuv2zuAzQeG0D8aQmOV9QuIkqHOqkrUyMeKaMI1qsMjZuHFNCvJhNL8VibjstviPHl/KAq306Y02BACmMrCax5DGeKGYpaCoVDb9OsWk/tV6pyX3bfclM82A7W2ULKQk5GR/9uyXRqj96W/fIDfvroNfbqqVrW0RXURdFJKRkRlIac3WyOMmg6JYvLiuI4EIoZpwcUOGfkxYFTxKTx5UcSohGvs+ffkxWe5Tcp8UDx53XdSN2R4b0ePKZ9tBuripv4kYnKJmpdrbhLRmBKpGnWhXDF5v0bcdM7ByuOphWwKkiHq81V9PYoF9WAkij1pzuqKiayMPGPsYsbYBsZYlDG2WPfc9xlj2xhjWxhjZ2Q3TGvhdtjiQhX+UBQepw1HT2vC5AYv/uuUmcq+QH6NfCAinbRme/J6z9ao4rcYUHvZfUnawyVKtesbDWJb5zD29fuU9Yoe3WKeWvKiyl1cxU96rjh2Kj7++dnYdstZBde7zwR1PrzamKtnpDu6jWXEi5lsj9B6ABcCeFO9kTE2F8AlAA4BcCaA3zPGSmZVo9LlULy/7uEA3t3ejUA4ArfDjtoKJ966/mQlPz1RaMNMFE/ehPRJQCr4YgzY2qHtdStaDRYbasGxRD1A/712P17a2KG0PwRiTWf6RkM49Y43cOxtryp542phN0Db+LyYDGMiGGOG/Y+tjDpV8vUtXdjdIxn60WBEkf/oGylcq06zyOoocc43cc6NSv6WAniEcx7gnH8MYBuAsYuaW4war0Px/q748/u47L7lGA6EDRduRCedX76wJWHbwFxjdky+xuPElIYKbNYZ+Vc2d+KQiTU4dFItpllwGh+KRA1j7mpP3pfAW//RU+sBQBNrn9IofUf1WoSQKFi2owc/f24THv1A0vhR3+RFT1civ1y+5CCcM38C/nzFEQhHOTa2SzULvlAEE+R0420J+jcXM2bdiicB2KP6e6+8LQ7G2JWMsRWMsRVdXV0mDSe3VHucyvR7e6d0we7r8xnGwMUiW+dQADc9ud60MT3w7k6lwbgoVjHTY6zzOjXVnqPBMFbv7seCyXWYM75aiXNahUc/2I2ZP3wOF/7h3bjn1B5eoqK1w2WdGfXCnFe+qatvEkKp84H3duH/3tiB7z3+IQCtkT9xdnaCecTYqK1w4u7LDsNcuT5BrCH5ghE0ywJxf3h9O17f0lmwMZpBSivAGHuZMbbe4N/SZC8z2Ga4bM05v5dzvphzvri5uThO/mpPzJMXPU/39PkUXRs16hX9RAt32TLgC+HHT2/AF//8AYBYaqPLxOl0pduhWbC87p/rpO0uOypcdssZ+XvlLlnqcnYA2NY5hCdX71f+Vq+d9I4ElWMmOjddoOooJgy6ehFen1Uj8IUimFDrwZafnYnPHDE5m69CZEm9XMsi1k18oQgq3TEHbX9/cVUgpyKlFeCcn8o5n2fw76kkL9sLQH0mtwLYn2DfoqPa48Du3lHc++Z21MidciJRnjKbxaxsFxFbFF5mPjz5KrdDs5C1elcfAKlBi8dlTxj2KBRzxkveW40ufXHp797R3KzURv6wn76Ec+96G4DkiU9rrsRvVB3Fvn+2lGWiztoYSNDk3ReKwuu0w+2wp9VbmDAPl8OGWq8TPSMBdA0FsKtnFFVuB06bOw5A5m1GrY5Z3+ZpAJcwxtyMsakAZgJ436TPyjsNsidw67ObdYUhKYy8ScUWQjpVLAqaHZMHpLUGdZji+JnSLOyak2fA67QjEI5aKudYeNtC8bFzyI/ZNz6HEd3NSB+u2dE9gpc3dmDFzj6lYfX5CybiujNmY9a4agDaUEyiFExfsLhkeUudao8DDy7fjSNueRkA0Fztxs8+OQ9AaWkyAdmnUF7AGNsL4GgAzzDGXgAAzvkGAI8B2AjgeQBXc85L5perVbU826FaRBMLcXqWLpQkGczyEERoZK0cisiLkXc7NLHskWAY05oqUeV2KH1AM1VoNBPhbQs105U7+wx1xDsHA1i/TxvS+cpfV6BzKKAsrN916SJcfdIM5XgOadYmjE/zYmuwUepUuhwaJyQUiXW5yneDH7PJNrvmCc55K+fczTkfxzk/Q/XcLZzz6Zzz2Zzz57IfqnVYJEvt6jmowVh64c5LFqGtscK0k0dtrJbv6FG8VjOnnWJdQlwow4EwKuUin3o5w0RfEFRIxDpFOMpx1p1vafRX1Pzm5Y9w7m/fxrbO+CwLvScu1lt+++q2hJ/rsDFwztE7EkSFq7iLoEoJ/az6yKmNyrZ8pjvnA3ItxsBhU+rx1NXHxm1P1k+1UhfDziXqOLI/HFUW/+pNbLLc1liJSJQrzUlGAmGlklOkESarHs036sXRTe2DKfVqnl/fHrctUwGry46cgnCUY2+fDxvbB3H09MaMXk+Yh7pK+aLDWnHCrGbFKfrlC1uwvz9/NR+cc1PlpsnIj5EFk+vw7H8dr9lW501sVPXZKLlEbeRddpuSj9+QYbvETBDx6G2dwwhFotjZM6qkiwolTit58vpZ1Ord/Un3/9WLH8VtS1c7/tIlU/D1E6fjULkgbssBqZ5gerP1agfKFXXRmzhv1Qviv3st8ews19z92jYceesrcW0JcwUZ+SwQ+baCZL06q9wOLP+417BlXrao39MfjsihAbupC33iwvAFI9jRNYKuoQCOn9kEQMqhB4CBBOmEhSBO/38o3nNy2pNnvaTbBWnRlDp878w5SlOQLXLRWG0SJ4DIL0Mp1ovMTD/W8+yHUitCs6ptychnyZ2XLFQe1yfxnEVY4/bnM+sJmg6acE0wgr6RoKmhGiCmI+4PRfDw+1JV50S5alB48v0W8uSN2jVW6jzzVBd2up68yMIZJxv5zbInX2wNu8sFm0FKq8OWnzRXzjk2yh3JbCZZYzLyWbJ0Yaw4Rm801Ajhq3S1yzNBLWPsD0cw6A8rxTtm4ZHjl9u7hpXG3SKbp9YrFl6t4cnv6R1F+4DWc+8c8qPK48DO287BtafOwl++eETKbCSjFNhjZ8TH2UVhTWuDdNNbvVuqISAjbx0evfIo5Tw1sufOPOXKi4YlgHkihmTkc8DDXz0Kz33r+KRFLiILpdYE46tWxPSHohgOhFBtspyt8OTve+vj2DY5nGG3MdR4HHENNQrFixs74rZFOZRsoG+dOhMnzm5Jmf3CDAq5H/zKUThqWoNmm3hfofGzt09axDN7dkWkz5HTGvH4148BoHXU5rdK6yjRPNV4qPsK62eb4UgUK3ZmH+IlI58Djp7eiIMn1CTdR5wzZmiJByNRZXrZMejHSCCiCKOZhcfA01GnbNZXuiyz8Co0fe749ALNdv2NMFVP3EQNRf58xRI89NUjlb8rVDM6oW7odtioGMpizGipws7bzsGhsmEHJIcNgGlJEnrUCQF6T/7et3bgU/e8h9k3Pp9VpzUy8nniR+fNBWCOJx8MR5XwzP++vBUf7htImAeeK4xkZtXhjBqPE4O+EO5/a0dSjfZ80DkYwJzx1RrjC8R/B9GEfVyCVNhEv6nXZdfcvNWPxW9CoZrioNLtwLSmSnQP56c3gjonX+3J7+gaxgvrDyh/f/EvH+Die+LF9dKBjHyeuPjwVtPeOxCOxrWUe/Oj/Ct6qrV5PE4bXtvShZ89swnfenRN3seipmckgMYqV5xomr4iV/QASHQjTibT4FCtmqnDPuI3SZZeS1iLQ1trsXJXn6mNfv77sbW4+qFVCGiMfOzxyb9+Q6lgByT9+w929o3ps8jI5wnGGJx2ppTV55JASGo9KPKyC4V64VLdCnDN7rGdnLmidySIxkq3kkUhFtr26QpezlswAYB27AAU4SrR2s8IteaN2pMXGTu15MkXDWfNm4Du4SDe3maeo/T4qr14Zl07/Kobib7bXK6gOus84rTbTDHyvlAEXpcdR09vxIey7sqfrzgi55+TCnVMXu2hFFoLpHc4iIZKF86bPxG1XieOmd6EWTc+h1MObtHs11Ltwe2fmo9Z46rxybvfAQDsuPVsbD4whJc2duATs1qM3h4AcOikWnzq8FbMb63VpFqKaf9R06jatVg4eIJU6Nefh+wwdbgmUS+DbCEjn0dcDpuigphL/KEIvE47KlQLe8fJhUn5JJFWTiGVdaNRjuFgGNUeB2w2hhNnS4Z69U2nocJANfTTi7Va7zYbw9yJNdj80zOTLpzabQy/unhB3HZx4R48vjqbr0HkETETS1UwNVaeXL1Pedwx6IfLbkMwEtU4RhUuu6HYXTgSzbjtIoVr8ojTbjNUPswW4clXqMIEzjxU7D3xjWM0f6tj8upFSqNik3zhC0XAVemSgvpKV0b6/mPNjBE3df3nE9ZFZKaZlWHz4PJdyuMXNnQojsCobORX7+5LqGaql8ZOBzLyeaRrKICH39+N/6zbj/+sy10PFV9Q9uTTrMjMFYum1OMziydjWlMlWqrdGlmAKFcb+bwOC2981IUH5AItIQo3FiN7RFt91mMRaZdk5IsHt8MOl91mmidvdC5UuuzoHpLWgn74ROI2oWPpLkdnXgG45qHVAIDjZzTnZEHOH4rCUwAjDwC/+NR8w+3qTBRbDqz8J+9+B7t6RrD6R6en3PcLf5L603zhmDbFG0vV0EXP5p+emZPSdjGjMaM+gjCPKo8Dj3ywG985bVbO+zKIfgtqWmo86JD1lJI1FxqLki158gVENAPPFilcY7OUXrkw8pccMRm+YCSrYg4AWLOnP2OZBM45RgLS9LYyw9/G47RnHPs0Qiy0ZypTTBSW3pEg+kdD+L83tuf8vfUaSf/7mYVoqXaja1BapPeHokpGl54DA5nn75ORLyAjOWrsLcI1ybRz8s3ph4wHIHko4SjHzh5zZFSTMRwIK79xoTxp4bWZ2aWLMI9Xt3RiOBDG5/64HLt6RlK/IA2GdM7dnAnVaKnxoHPIj7tf24ZN7YOodjvw+8sPw7WnztLsOxbtKzrz8oi+o1QumohwzuELSf1D01VJzAe3XnAo3vv+yThd9kje295jyud0Dvrx/X+tM9T36B8NKXFVs2UeEnHf5w/HTefOxfhaT0E+n8iO1bv78cqmDry1tduwx8BY0Mf667wutFS7sbNnFL98QVKprXQ7cPahE/DVE6Yq+zlsjIy81XniG8fioa/ENE6GA9lryw/JN4oaj9NSi3suhw0Tar2Y0ii1RBzLghEghX0u+P07CZ//wRPr8fD7e/DutvibiDTllhazCiUO1lpfgS8fNzX1joSluO6M2crjXLcD1GftNFa5FI0jgXBK1BlgkxsqsCffRp4xdjFjbANjLMoYW6za3sYY8zHG1sj/7snmc0oJ9aJKLjx50ZijtsJpybivyN1PlBKWitFgOGkXpwODUtWqmMWoS9H7RoNKQQtVnBKZcPVJM5THYl0nV0li+nCN026Lax0qwot21eL/5IaKgnjy6wFcCOBNg+e2c84Xyv+uyvJzSpJc5OH2q/q5WsmTFzjsNrgctjEb+bCueEwvAdsrSxAIb0stb9w3GkTfaBAOGzNdepkoXYTmUa7KGIf84bj03HHV2nCeeg3p6pOm4zOLJ6OhwokBXwgDvhB++cLmtKvnszrzOeebACTVUSe0NFbG7ti58OT7fZKRq6twFiSFMh2k6r2xfVf9iRwIRzVrD6KAxBcURj6mO3Pto2tx2ZFTUFfhpHOUGDO5Looa8oexaEo9Fk2pV1pmJvLkAeC6M+YAAG54fB12947ioj+8i22dw5g1rlqjhZ8IM2PyUxljqxljbzDGjk+9e3nQ1lSJp685FkCOwjWy51rrdSqyAhcuSn3g80mly6FMeTNFr+ehj4+Kv8VM4dZnN2ue39w+aIq8M1H6XHnCNACx6zQXboI/FEEwEkWt14kfnH0wjp/ZDABo1nnyRrNycX1v65T6I4QiPK2EhpRGnjH2MmNsvcG/pUle1g5gCud8EYDvAHiIMWbYVYMxdiVjbAVjbEVXV/7lcQvB/NY6OO0sJwuvo/J7VLjsYIxh7Y9Px+0JCpQKhddlhy80Vk9eO0l+SdflSYifjYYiGA2G8ermTgDAHFkrZv2+QerIRIwJkasu6jPW7e3P+j1FZo1eGrzW68RfvngEFsgNTFyO+FuKXlrj0Q9249L7luHZD9uTfmZKI885P5VzPs/g31NJXhPgnPfIj1cC2A5gVoJ97+WcL+acL25ubk41nJKh0u3IiScvwiCiEKrW68xJEU8uqXI7MOjLLlxzmJx++sB7O5Xn1AVWvmAYe3pj0sE//eQ8ANJMgBp2EGNBJDKIpjc7e0azbgsoQj96Iw8AJ85uUZr/GIUX9QKA+/ulCtlU3rwp1oAx1swYs8uPpwGYCWCHGZ9VrEghjBwY+VDMk7cqE2o9aB/wpd7RAJEtc+UJ03BQY4VGeE0t9nZgIIB9/VLmwd2XHYYaVel4HXnyxBgQnrN6MT+UpKdAOojMmmq3sePRKncnM0oUiOiqxsUNI1WbzawWXhljFwD4LYBmAM8wxtZwzs8AcAKAmxljYQARAFdxznuz+axSo9rjyGpBh3OOK/+2Evv6fGAsscyvFZhY58XrW7rAOc94AVR48m6HHcdMb8TjK/chEuWw25gmY+dP73yMP70jNRWfPb5a83s0VJKRJzJHnEOiRwMghQ+zSdRKFK4R3HTuXBw1rRGHHxQvjqfvVCVuPsk6lgHZZ9c8AeAJg+2PA3g8m/cudarcjqxU7gZ9YSU+XSnH463KuBo3fKEIRoKRtOUFolGOruGAIvDltEvaPMFIFHe8tAXXnTFHmQnVeBwYVP2WXpddUzMwkapNiTFgJBQWDEcB4xbAaSE8+UQV2BUuR8KMmUQy5amKtazr/pU4DZWulNOsZPSqXuu1kDCZEWLaG8igcvB3r23Dkbe+gp3dkl6I086UxdTlO6RJochfPqixUvt5DpsmfDW5oWLsgyfKFrc9PgSaTWe3SJTjGw+uAgBNODFdErUHVIeTjCAjXyAaq1xxvUQzoXckpkZn5Xg8EJv2ZtIwRWQMXPfPdQAAp8OGiw6TmqFPb64CEEttE9IJAq/LrgnXTJP3J4hMUHvywsHIprl3z3AAIrLSXJ35dCCRNlU/GXlr0ljpRt9ocMyr9b0jsQNr9ewRob+RrpHf1jmMzQeGNNtcdhtsNoaZLVWK5yIKoObrGph7HNrwVVsjefJE5qglgcWCaDZ9WMVrqz2OMXUa++/TZ+HSJVPitvtSVJOTkS8QjVUuRKI85VRL8FHHkCb2trcvpmExx+L9Q2OefAR9I0E8lyKv92fPbIzb5pC7TtXJpd1ArBXakqkNyn52G1OalLxzw8l4+ppjLb1eQVgXdbMbkaGVTbhG1HzcvPSQMb2+2uPEtafOjNueanZBRr5AiIyPnpHUTQAG/SGc/ps3ccPj65Rtm9oHlceHTKw1epllENPeQCiK6/65Dl9/cBV2do/g+n+uxbbOobj9Dwz447aJ1Mm6Che6h6XfTFl49Trxg7Ol0m+1OZ9U58X81rocfhOiXBHZMNmEa8RrXQax/nRxG8wAUo3J2it2JUxTlRST6x4OYkZL8n27hiSj9v7HsSzU9gE/WqrdOGFWMz69eLJp48wFIlzz2pZOvLxJygj68dMb8MZHXdjYPoj/fFOreiG+rxqRN3zIxBq8vKkDl923TMmgqfU6x9xomyDSQTR/ycaTV4x8FunOHoOMn1RhUDLyBUJ48r0jqRdfu2WjpzZkA74Q5k6swa8uXmDOAHOIOKn/9+WtyrY3PpIkLJy66txQJIre0SCOm9GEt7d1AwC+c9ostNRIaZBzxteAc+BdVZWf2sjb8901nCgLamRPPpPkAT3BiBRezMbI61sHSu9L4RpLMrHWC7uN4YOdqWvEuuTwhMthw9o9/Tjh9tewu3cUdUUivJWsUEtv5Ad8IXCuTXtUd9QyykpQv8f8VmuHrojipEbx5McuaxBQwjVjN7uMMfzli0fg+W+nr/lInnyBqK1wYkFrrSa2noh9fZIkQJXbgTtf2ao0DigWdUV1d5v452InfM9wQGmc3FTlUu0Te72+g45g4eQ6zBpXhZ998tBsh0sQcYiYfCgXMfksq9NPnN2i0W1KBXnyBaTC5TD0DFbt7tN4+Bv2x24E6lzZ4jHyiU8z9XM/f24z7ntLkiZoVEkRqOOQYi1Dz6xx1Xjx2k9gtsUzjYjiRMTks0qhDAuJjuzNLmMMK288FTeec3DKfcnIFxCnnRku5Fz4+3dx8T3vAZBKll/YcAAAsL/fp7TTA4DGBAbPatQn0Y5RpzeqnRP1d1OvRegLQm65YF4ORkgQyRG1KKly0pMhbhDZevKCxip3WjIhZOQLiNNui0t/+s5jazR/D/hCCISjaKx0Yf+AX9OCbCxVc4Ug2YxDXa2rDlWqPXZPknBPpcUlHYjSQDHyWTT1DuYgJq8nnRsGGfkC4nTYNNO/cCSKf63ap9lHKFWKBUV1EVSi0IUVefzrR+O2C+Pj5RUqI62WeWiuduGHZx+MLx07FZMbvAnfN1GpN0HkgiVtUqGdcFSy8uRzFJNXk857kRtUQFx2myZc02sgWKbos8jZJst2xGL142qKx8gfflADDptSjwFfCLPGV+OJVfuw/OMezfcflpUkGQPG13rxVbn9mp75rbVYt1eSf6X8eMJM/vzFI9A+4FOckbE2pAdiswBvDs/ZdGay5MkXEJfdhlA4FoAxqlwTnryRkmJrfXFpsjDG8LVPTMdJs1tw16WL4HXaNd/ZF4rg5Dkt+Pjn5ySNNT74lSOVx9l26iGIZFS6HZjRUg27jcHlsGF0jG0sAanDlI1B6f6UC46e3ginPXltCBn5AuJ0aBdejYy86OGqN+hNVa6iL/xxObQzGV8okpaXU+1x4qx54wGkbphAELmiwmXPKlzTMxJEXUVur1uP046W6uT9EihcU0D0C68rdvVpng9FohiRe7i2NUlG/tOLW3H7pxZklCdrVfTf3x+KGDZqMOJ/zj8EDZUunDCrfPoCE4WlwmnPKlzTOxI0pUtZoi5TAjLyBcRljy28dgz6cf0/12mef2ljh3JS1Xqd2HjzGYqnWwrKik67DR/LTUEAycinG69sqfHglguo8InIHxVuB3Z0DeO5D9tx1qETMn5932gQ9SbIgqdqQELhmgKiDleItmAAcPS0RgDA8+sPaNKuKlyOkjDuanZ0j6B/NIhwJIpBfzini1IEkUvG13iwanc/vv7gqpT9maNRjl+9sAX7+2MN7IcDYaWoKpek8uTJyBcQp92GKJfiyurQ8tc+IWWVzB5fbUralVW4TG6A0D0cwLWPrUUwHC36dQaidFEb7LV7+vH8+gNx+/zsPxvxm5c+wt+W7cLvXtuGax9dozw3EoigMpsu4Akw1cgzxn7JGNvMGFvHGHuCMVaneu77jLFtjLEtjLEzsvmcUkUIa4UiUU3/RpGTG4pEc14lZyXGyw22b3tuM/69dj8AYHvXcCGHRBAJuf7MOcrjy+9fjqv+vjIuWeL+tz/Gna9sxY+f3gAAGFI1mB8OhFHlzv1M9fyFE5M+n63leAnAPM75fAAfAfg+ADDG5gK4BMAhAM4E8HvGGM3DdYjUp0A4qqmkczvscNikzJtcKNdZlXq5287LmzqVbUJSmCCsxplyRpeaQDj5QqyYoHcPB9A1FDClQvvkOeOSPp+V5eCcv8g5F7eqZQBa5cdLATzCOQ9wzj8GsA3Akmw+qxQR1ZoPLd+NHSoP1u20wWFnCEU4guEoXHZbycXiAaC+Mj4+mY7gEkEUire/d5Lmb7W+vJHBD8sz8e/+Yy0AYG+fL24fs8nlbeVLAB6VH0+CZPQFe+VtcTDGrgRwJQBMmRLfpLaUEbotv3h+s2a7y25T0gttjJVkqAZAXMHT/NZajcwBQViN8bqZptrI943E92sWoVcRhuz3pW4SlGtSWg/G2MuMsfUG/5aq9vkhgDCAB8Umg7cyTOzmnN/LOV/MOV/c3FxeOc9ep7FBczttcNltCEejCEYiJWvk9d+LCpsIq+Ow2zSievqKbT0RuZ5FFCz95PyxNfHOhpRuE+f81GTPM8a+AOBcAKfwWIXOXgDqxqOtAPaPdZClSmWCRZjmKjecsuQBBy/JeDwQv85ARp4oBqo9DqV+RR2i0cuGHzujEf2jknc/EgjjjEPGYc74mvwNVCbb7JozAXwPwPmc81HVU08DuIQx5maMTQUwE8D72XxWKVJhoKC48sZTwRhTJA9CEV6ynrzDboM6YzJMRp4oAtS57uqsOH2mTY3HiWA4iluf3YTNB4ZMSZ9Mh2w/9XcA3ABekhcGl3HOr+Kcb2CMPQZgI6QwztWc87HXA5coegXFR648SmmW4bRJ1bCcl2b6pEBt1g+dRP1ZCevTWOnCNvmxWipc78k75Yr2e9/cAQCKV59vsjLynPMZSZ67BcAt2bx/qaOXn1HrwztlGeJItDTTJwXiN7hg0STcSjIFRBGgvk6TefIuh03TE3bQV4RGnsiO1nptM4xmtZF3MIQjHMFING3RrmLmmOmN1ACEKApqVfoz2pi81mtzOWzYP+BX/j6osdL8wRlQ+tbDwtRVuPDU1ccqf9d4Y/dch82GvX0+9AwH0VCRe+U6q0Gpk0SxUK8x8onDNeoZ+MyWKty8NP+ZNQAZ+YKjXoxRFzyt2dOPLR1D2No5hMaqcjDy5MUTxUG9yul6Z1u38jioM/Ju1VrasTOaCrbwSka+wKSSHg1FuLIYW8pQqIYoFupURn5rR6xS3SgmL1CLm+UbMvIFprHKjR+cPQe3XzRfs/2mc+cqj8dVl76RN0PTgyDMYNGUOuVx90hAeZwsXFObw5Z/mUJXlgW48oTpcdvU6YQXHNYa93ypQZ48USxMb67Chv85A7c/vxlPrN6nbI8z8rInP6nOi5vOm4tCQZ68RRG6Lo2VroJ6AWYjmoS4S7gWgCg9Kt0ONFa5MegPK8Y9qMuuccie/ElzmlN2bzITurIsijDythJvovHIlUfhrHnjFW15gigWRLKAX9as0cfkpzVJKZM9w/kXJVND4RqL4nFJ99+Jdd4UexY3CybX4Q+fPbzQwyCIjHE7hZGPotoTM/afO+ogNFa5cPzMJnzx2DZccUxbAUdJRt6ytFR78IuLDsVJs1sKPRSCIAwQIUZREDXoD8Flt+HmpYco6dA/Pq8wufFqyMhbmM8cUV76+gRRTHhUnjwADPrCqPE6Ldfgh2LyBEEQYyDOk/eFNFXrVoGMPEEQxBjQe/IDvpAlM+HIyBMEQYwBo5g8GXmCIIgSQXjyAZUnX8h8+ESQkScIghgDek+ewjUEQRAlhPDkfaEIOOcYJCNPEARROlR7pEyagdEQbn12E6Iclsyusd6ICIIgigBh5F/b0oU3PuoCAIrJEwRBlApuhx0epw1bDgwp20QIx0pkZeQZY79kjG1mjK1jjD3BGKuTt7cxxnyMsTXyv3tyMlqCIAgLUeNx4sBgrI+rFdVUsx3RSwDmcc7nA/gIwPdVz23nnC+U/12V5ecQBEFYjhrdQqur1Iw85/xFznlY/nMZgNLvbkEQBCFTqWt2U3JGXseXADyn+nsqY2w1Y+wNxtjxiV7EGLuSMbaCMbaiq6srh8MhCIIwF7cuBq9u+WcVUmbXMMZeBjDe4Kkfcs6fkvf5IYAwgAfl59oBTOGc9zDGDgfwJGPsEM75oP5NOOf3ArgXABYvXsz1zxMEQVgV/UKr3uhbgZRGnnN+arLnGWNfAHAugFM451x+TQBAQH68kjG2HcAsACuyHjFBEIRF8Dq1nrsVPflss2vOBPA9AOdzzkdV25sZY3b58TQAMwHsyOazCIIgrIbek7diTD7bYqjfAXADeEkWyl8mZ9KcAOBmxlgYQATAVZzz3iw/iyAIwlJ4HLpwTakZec75jATbHwfweDbvTRAEYXU8unCNFY289UZEEARRJOjDNXabtVr/AWTkCYIgxow+m6bCZT05MOuNiCAIokgQxVCXLpmM7505B16X9VIoyZMnCIIYI3UVkqxBMMxRV+Eq8GiMISNPEAQxRrxyeMYfihR4JIkhI08QBDFGvKruUFaFjDxBEMQYOXRSLQDgosOsq81IC68EQRBjZHytBztvO6fQw0gKefIEQRAlDBl5giCIEoaMPEEQRAlDRp4gCKKEISNPEARRwpCRJwiCKGHIyBMEQZQwZOQJgiBKGCa3ZbUEjLEhAFvS3L0WwEAO9slkPzPes1zH2ASgO0fvWWq/TSl9di6PcyH3K+Rnp7PfbM55teEznHPL/AOwIoN9783FPpnsZ8Z7lvEY0zrWuTzORfTblNJn5+w4l+Bvk7P9kv3OxRyu+XeO9slkPzPes1zHmC65PM6Z7FuOx8+s9yzE5xbDb5OX39pq4ZoVnPPFhR4HYT50rMsDOs75IdnvbDVP/t5CD4DIG3SsywM6zvkh4e9sKU+eIAiCyC1W8+RLGsbYcIrnX2eM0dS2BKBjXR4Uw3EmI08QBFHCFMTIp7r7lTKMsRMZY/9R/f07xtgVBRySaZTzcQboWJcLVj/O5MkTBEGUMAUz8oyxKsbYK4yxVYyxDxljS+XtbYyxTYyx+xhjGxhjLzLGvIUaJ5EddJzLBzrW1qSQnrwfwAWc88MAnATg14wxJj83E8DdnPNDAPQDuKgwQzSFMLS/u6dQA8kT5XqcATrW5XKsLX2cC2nkGYBbGWPrALwMYBKAcfJzH3PO18iPVwJoy/vozGMXgLmMMTdjrBbAKYUekMmU63EG6FiXy7G29HF2FPCzLwfQDOBwznmIMbYTsTtgQLVfBEDRT+0YYw4AAc75HsbYYwDWAdgKYHVhR2Y6ZXWcATrWKJNjXSzHuZBGvhZAp3wynATgoAKOJR8cAmA7AHDOrwdwvX4HzvmJeR5TPii34wzQsS6XY10UxznvRl7c/QA8CODfjLEVANYA2JzvseQLxthVAP4LwLcLPJS8UY7HGaBjjTI51sV0nPMua8AYWwDgPs75krx+MJFX6DiXD3SsrU1eF17lu9/DAG7M5+cS+YWOc/lAx9r6kEAZQRBECWOqJ88Ym8wYe00uhNjAGPuWvL2BMfYSY2yr/H+9vP00xthKuZBiJWPsZNV73cIY21PO5dNWJlfHmjFWwRh7hjG2WX6f2wr5vQgtOb6mn2eMrZXf5x7GmL1Q36ukSbf11Vj+AZgA4DD5cTWAjwDMBXA7gBvk7TcA+IX8eBGAifLjeQD2qd7rKPn9hs0cM/0r7LEGUAHgJPmxC8BbAM4q9Pejf7k9zvLfNfL/DMDjAC4p9PcrxX+mevKc83bO+Sr58RCATZAKJJYCeEDe7QEAn5T3Wc053y9v3wDAwxhzy88t45y3mzleYuzk6lhzzkc556/J+wQBrALQmrcvQiQlx9f0oLzdAemGTrFjE8jbwitjrA3SXX05gHHCYMv/txi85CIAqznnAYPnCAuTq2PNGKsDcB6AV8wcLzE2cnGcGWMvAOgEMATgn2aPuRzJi5FnjFVBmo59W3X3Trb/IQB+AeBrZo+NyC25OtZy7vXDAO7inO8wY6zE2MnVceacnwEpBOQGcLLBS4ksMd3IM8ackE6GBznn/5I3dzDGJsjPT4B0Jxf7twJ4AsDnOefbzR4fkTtyfKzvBbCVc/6/pg+cyIhcX9Occz+ApyGFfIgcY3Z2DQPwRwCbOOd3qJ56GsAX5MdfAPCUvH8dgGcAfJ9z/o6ZYyNySy6PNWPsZ5BK5L9t7qiJTMnVcWaSLLG4KTgAnI0SrpAtJKbmyTPGjoOUHfEhgKi8+QeQYniPAZgCYDeAiznnvYyxGwF8H5LIj+B0znknY+x2AJcBmAhgP4D7Oec/MW3wREbk6lhDWoDbA+mCF7Hb33HO7zf9SxApyeFxZgD+AylMYwfwKoBrOefhfHyPcoKKoQiCIEoYav9HEARRwpCRJwiCKGHIyBMEQZQwZOQJgiBKGDLyBEEQJQwZeYIgiBKGjDxBEEQJQ0aeIAiihPl/UpZAsX76nC0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ts = pd.Series(np.random.randn(1000),index=pd.date_range('1/1/2021',periods=1000))\n",
    "ts = ts.cumsum()\n",
    "ts.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>Make</th>\n",
       "      <th>Colour</th>\n",
       "      <th>Odometer (KM)</th>\n",
       "      <th>Doors</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>White</td>\n",
       "      <td>150043</td>\n",
       "      <td>4</td>\n",
       "      <td>$4,000.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Honda</td>\n",
       "      <td>Red</td>\n",
       "      <td>87899</td>\n",
       "      <td>4</td>\n",
       "      <td>$5,000.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>Blue</td>\n",
       "      <td>32549</td>\n",
       "      <td>3</td>\n",
       "      <td>$7,000.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BMW</td>\n",
       "      <td>Black</td>\n",
       "      <td>11179</td>\n",
       "      <td>5</td>\n",
       "      <td>$22,000.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Nissan</td>\n",
       "      <td>White</td>\n",
       "      <td>213095</td>\n",
       "      <td>4</td>\n",
       "      <td>$3,500.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>Green</td>\n",
       "      <td>99213</td>\n",
       "      <td>4</td>\n",
       "      <td>$4,500.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Honda</td>\n",
       "      <td>Blue</td>\n",
       "      <td>45698</td>\n",
       "      <td>4</td>\n",
       "      <td>$7,500.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Honda</td>\n",
       "      <td>Blue</td>\n",
       "      <td>54738</td>\n",
       "      <td>4</td>\n",
       "      <td>$7,000.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>White</td>\n",
       "      <td>60000</td>\n",
       "      <td>4</td>\n",
       "      <td>$6,250.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Nissan</td>\n",
       "      <td>White</td>\n",
       "      <td>31600</td>\n",
       "      <td>4</td>\n",
       "      <td>$9,700.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Make Colour  Odometer (KM)  Doors       Price\n",
       "0  Toyota  White         150043      4   $4,000.00\n",
       "1   Honda    Red          87899      4   $5,000.00\n",
       "2  Toyota   Blue          32549      3   $7,000.00\n",
       "3     BMW  Black          11179      5  $22,000.00\n",
       "4  Nissan  White         213095      4   $3,500.00\n",
       "5  Toyota  Green          99213      4   $4,500.00\n",
       "6   Honda   Blue          45698      4   $7,500.00\n",
       "7   Honda   Blue          54738      4   $7,000.00\n",
       "8  Toyota  White          60000      4   $6,250.00\n",
       "9  Nissan  White          31600      4   $9,700.00"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_sales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": true
   },
   "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>Make</th>\n",
       "      <th>Colour</th>\n",
       "      <th>Odometer (KM)</th>\n",
       "      <th>Doors</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>White</td>\n",
       "      <td>150043</td>\n",
       "      <td>4</td>\n",
       "      <td>400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Honda</td>\n",
       "      <td>Red</td>\n",
       "      <td>87899</td>\n",
       "      <td>4</td>\n",
       "      <td>500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>Blue</td>\n",
       "      <td>32549</td>\n",
       "      <td>3</td>\n",
       "      <td>700000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BMW</td>\n",
       "      <td>Black</td>\n",
       "      <td>11179</td>\n",
       "      <td>5</td>\n",
       "      <td>2200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Nissan</td>\n",
       "      <td>White</td>\n",
       "      <td>213095</td>\n",
       "      <td>4</td>\n",
       "      <td>350000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>Green</td>\n",
       "      <td>99213</td>\n",
       "      <td>4</td>\n",
       "      <td>450000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Honda</td>\n",
       "      <td>Blue</td>\n",
       "      <td>45698</td>\n",
       "      <td>4</td>\n",
       "      <td>750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Honda</td>\n",
       "      <td>Blue</td>\n",
       "      <td>54738</td>\n",
       "      <td>4</td>\n",
       "      <td>700000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>White</td>\n",
       "      <td>60000</td>\n",
       "      <td>4</td>\n",
       "      <td>625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Nissan</td>\n",
       "      <td>White</td>\n",
       "      <td>31600</td>\n",
       "      <td>4</td>\n",
       "      <td>970000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Make Colour  Odometer (KM)  Doors    Price\n",
       "0  Toyota  White         150043      4   400000\n",
       "1   Honda    Red          87899      4   500000\n",
       "2  Toyota   Blue          32549      3   700000\n",
       "3     BMW  Black          11179      5  2200000\n",
       "4  Nissan  White         213095      4   350000\n",
       "5  Toyota  Green          99213      4   450000\n",
       "6   Honda   Blue          45698      4   750000\n",
       "7   Honda   Blue          54738      4   700000\n",
       "8  Toyota  White          60000      4   625000\n",
       "9  Nissan  White          31600      4   970000"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_sales[\"Price\"] = car_sales[\"Price\"].str.replace(\"[\\$\\,\\.]\",\"\")\n",
    "car_sales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Remove last to zeros\n",
    "car_sales[\"Price\"] = car_sales[\"Price\"].str[:-2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
       "      <th>Make</th>\n",
       "      <th>Colour</th>\n",
       "      <th>Odometer (KM)</th>\n",
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       "      <th>Price</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>White</td>\n",
       "      <td>150043</td>\n",
       "      <td>4</td>\n",
       "      <td>4000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Honda</td>\n",
       "      <td>Red</td>\n",
       "      <td>87899</td>\n",
       "      <td>4</td>\n",
       "      <td>5000</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>Blue</td>\n",
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       "      <td>7000</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BMW</td>\n",
       "      <td>Black</td>\n",
       "      <td>11179</td>\n",
       "      <td>5</td>\n",
       "      <td>22000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Nissan</td>\n",
       "      <td>White</td>\n",
       "      <td>213095</td>\n",
       "      <td>4</td>\n",
       "      <td>3500</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Toyota</td>\n",
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       "      <td>99213</td>\n",
       "      <td>4</td>\n",
       "      <td>4500</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Honda</td>\n",
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       "      <td>45698</td>\n",
       "      <td>4</td>\n",
       "      <td>7500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Honda</td>\n",
       "      <td>Blue</td>\n",
       "      <td>54738</td>\n",
       "      <td>4</td>\n",
       "      <td>7000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>White</td>\n",
       "      <td>60000</td>\n",
       "      <td>4</td>\n",
       "      <td>6250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Nissan</td>\n",
       "      <td>White</td>\n",
       "      <td>31600</td>\n",
       "      <td>4</td>\n",
       "      <td>9700</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Make Colour  Odometer (KM)  Doors  Price\n",
       "0  Toyota  White         150043      4   4000\n",
       "1   Honda    Red          87899      4   5000\n",
       "2  Toyota   Blue          32549      3   7000\n",
       "3     BMW  Black          11179      5  22000\n",
       "4  Nissan  White         213095      4   3500\n",
       "5  Toyota  Green          99213      4   4500\n",
       "6   Honda   Blue          45698      4   7500\n",
       "7   Honda   Blue          54738      4   7000\n",
       "8  Toyota  White          60000      4   6250\n",
       "9  Nissan  White          31600      4   9700"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_sales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "car_sales[\"Sale Date\"] = pd.date_range(\"1/1/2021\",periods=len(car_sales))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>Colour</th>\n",
       "      <th>Odometer (KM)</th>\n",
       "      <th>Doors</th>\n",
       "      <th>Price</th>\n",
       "      <th>Sale Date</th>\n",
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       "      <td>Toyota</td>\n",
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       "      <td>4000</td>\n",
       "      <td>2021-01-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Honda</td>\n",
       "      <td>Red</td>\n",
       "      <td>87899</td>\n",
       "      <td>4</td>\n",
       "      <td>5000</td>\n",
       "      <td>2021-01-02</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>Blue</td>\n",
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       "      <td>BMW</td>\n",
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       "      <td>5</td>\n",
       "      <td>22000</td>\n",
       "      <td>2021-01-04</td>\n",
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       "      <th>4</th>\n",
       "      <td>Nissan</td>\n",
       "      <td>White</td>\n",
       "      <td>213095</td>\n",
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       "      <td>3500</td>\n",
       "      <td>2021-01-05</td>\n",
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       "      <td>Toyota</td>\n",
       "      <td>Green</td>\n",
       "      <td>99213</td>\n",
       "      <td>4</td>\n",
       "      <td>4500</td>\n",
       "      <td>2021-01-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Honda</td>\n",
       "      <td>Blue</td>\n",
       "      <td>45698</td>\n",
       "      <td>4</td>\n",
       "      <td>7500</td>\n",
       "      <td>2021-01-07</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Honda</td>\n",
       "      <td>Blue</td>\n",
       "      <td>54738</td>\n",
       "      <td>4</td>\n",
       "      <td>7000</td>\n",
       "      <td>2021-01-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>White</td>\n",
       "      <td>60000</td>\n",
       "      <td>4</td>\n",
       "      <td>6250</td>\n",
       "      <td>2021-01-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Nissan</td>\n",
       "      <td>White</td>\n",
       "      <td>31600</td>\n",
       "      <td>4</td>\n",
       "      <td>9700</td>\n",
       "      <td>2021-01-10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Make Colour  Odometer (KM)  Doors  Price  Sale Date\n",
       "0  Toyota  White         150043      4   4000 2021-01-01\n",
       "1   Honda    Red          87899      4   5000 2021-01-02\n",
       "2  Toyota   Blue          32549      3   7000 2021-01-03\n",
       "3     BMW  Black          11179      5  22000 2021-01-04\n",
       "4  Nissan  White         213095      4   3500 2021-01-05\n",
       "5  Toyota  Green          99213      4   4500 2021-01-06\n",
       "6   Honda   Blue          45698      4   7500 2021-01-07\n",
       "7   Honda   Blue          54738      4   7000 2021-01-08\n",
       "8  Toyota  White          60000      4   6250 2021-01-09\n",
       "9  Nissan  White          31600      4   9700 2021-01-10"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_sales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>Colour</th>\n",
       "      <th>Odometer (KM)</th>\n",
       "      <th>Doors</th>\n",
       "      <th>Price</th>\n",
       "      <th>Sale Date</th>\n",
       "      <th>Total Sales</th>\n",
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       "      <td>Toyota</td>\n",
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       "      <td>9000</td>\n",
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       "      <th>2</th>\n",
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       "      <td>2021-01-03</td>\n",
       "      <td>16000</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BMW</td>\n",
       "      <td>Black</td>\n",
       "      <td>11179</td>\n",
       "      <td>5</td>\n",
       "      <td>22000</td>\n",
       "      <td>2021-01-04</td>\n",
       "      <td>38000</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Nissan</td>\n",
       "      <td>White</td>\n",
       "      <td>213095</td>\n",
       "      <td>4</td>\n",
       "      <td>3500</td>\n",
       "      <td>2021-01-05</td>\n",
       "      <td>41500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>Green</td>\n",
       "      <td>99213</td>\n",
       "      <td>4</td>\n",
       "      <td>4500</td>\n",
       "      <td>2021-01-06</td>\n",
       "      <td>46000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Honda</td>\n",
       "      <td>Blue</td>\n",
       "      <td>45698</td>\n",
       "      <td>4</td>\n",
       "      <td>7500</td>\n",
       "      <td>2021-01-07</td>\n",
       "      <td>53500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Honda</td>\n",
       "      <td>Blue</td>\n",
       "      <td>54738</td>\n",
       "      <td>4</td>\n",
       "      <td>7000</td>\n",
       "      <td>2021-01-08</td>\n",
       "      <td>60500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>White</td>\n",
       "      <td>60000</td>\n",
       "      <td>4</td>\n",
       "      <td>6250</td>\n",
       "      <td>2021-01-09</td>\n",
       "      <td>66750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Nissan</td>\n",
       "      <td>White</td>\n",
       "      <td>31600</td>\n",
       "      <td>4</td>\n",
       "      <td>9700</td>\n",
       "      <td>2021-01-10</td>\n",
       "      <td>76450</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Make Colour  Odometer (KM)  Doors  Price  Sale Date  Total Sales\n",
       "0  Toyota  White         150043      4   4000 2021-01-01         4000\n",
       "1   Honda    Red          87899      4   5000 2021-01-02         9000\n",
       "2  Toyota   Blue          32549      3   7000 2021-01-03        16000\n",
       "3     BMW  Black          11179      5  22000 2021-01-04        38000\n",
       "4  Nissan  White         213095      4   3500 2021-01-05        41500\n",
       "5  Toyota  Green          99213      4   4500 2021-01-06        46000\n",
       "6   Honda   Blue          45698      4   7500 2021-01-07        53500\n",
       "7   Honda   Blue          54738      4   7000 2021-01-08        60500\n",
       "8  Toyota  White          60000      4   6250 2021-01-09        66750\n",
       "9  Nissan  White          31600      4   9700 2021-01-10        76450"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_sales[\"Total Sales\"] = car_sales[\"Price\"].astype(int).cumsum()\n",
    "car_sales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Sale Date'>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "# plot total sales\n",
    "car_sales.plot(x=\"Sale Date\",y=\"Total Sales\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Odometer (KM)', ylabel='Price'>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "# price to int from str\n",
    "car_sales[\"Price\"] = car_sales[\"Price\"].astype(int)\n",
    "\n",
    "# plot scatter plot\n",
    "car_sales.plot(x=\"Odometer (KM)\",y=\"Price\",kind=\"scatter\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "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>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "      <th>d</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.706528</td>\n",
       "      <td>0.041617</td>\n",
       "      <td>0.233130</td>\n",
       "      <td>0.928113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.271208</td>\n",
       "      <td>0.714835</td>\n",
       "      <td>0.322221</td>\n",
       "      <td>0.644175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.519335</td>\n",
       "      <td>0.579414</td>\n",
       "      <td>0.793689</td>\n",
       "      <td>0.046671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.828491</td>\n",
       "      <td>0.864654</td>\n",
       "      <td>0.090794</td>\n",
       "      <td>0.088486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.683652</td>\n",
       "      <td>0.482635</td>\n",
       "      <td>0.248157</td>\n",
       "      <td>0.364589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.226603</td>\n",
       "      <td>0.641077</td>\n",
       "      <td>0.189172</td>\n",
       "      <td>0.737285</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.058073</td>\n",
       "      <td>0.101133</td>\n",
       "      <td>0.076771</td>\n",
       "      <td>0.025669</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.389439</td>\n",
       "      <td>0.285053</td>\n",
       "      <td>0.376308</td>\n",
       "      <td>0.254788</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.942507</td>\n",
       "      <td>0.006348</td>\n",
       "      <td>0.269943</td>\n",
       "      <td>0.207652</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.421755</td>\n",
       "      <td>0.918335</td>\n",
       "      <td>0.183819</td>\n",
       "      <td>0.672341</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          a         b         c         d\n",
       "0  0.706528  0.041617  0.233130  0.928113\n",
       "1  0.271208  0.714835  0.322221  0.644175\n",
       "2  0.519335  0.579414  0.793689  0.046671\n",
       "3  0.828491  0.864654  0.090794  0.088486\n",
       "4  0.683652  0.482635  0.248157  0.364589\n",
       "5  0.226603  0.641077  0.189172  0.737285\n",
       "6  0.058073  0.101133  0.076771  0.025669\n",
       "7  0.389439  0.285053  0.376308  0.254788\n",
       "8  0.942507  0.006348  0.269943  0.207652\n",
       "9  0.421755  0.918335  0.183819  0.672341"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# bar graph\n",
    "x= np.random.rand(10,4)\n",
    "\n",
    "# into dataframe\n",
    "df = pd.DataFrame(x,columns=[\"a\",\"b\",\"c\",\"d\"])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD1CAYAAABA+A6aAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8vihELAAAACXBIWXMAAAsTAAALEwEAmpwYAAASkUlEQVR4nO3dfZDV1X3H8fc3iG6IShSoTVhwaWoQjKiADxMfU22CsdXYMBO1MdSpZUxjk/7TkSmdlpmMHTOx09aplmESok5bGZOGBiNqYhxTNdgA0UAQUGIIbMgDQoNJxMbVb/+41/budWEv7n3aw/s1s+M9v99vz/m6u3z27Pk93MhMJEmj31s6XYAkqTkMdEkqhIEuSYUw0CWpEAa6JBXCQJekQhzRqYEnTpyYfX19nRpekkal9evXv5CZk4ba17FA7+vrY926dZ0aXpJGpYj44YH2ueQiSYUw0CWpEAa6JBWiY2voktQpr7zyCv39/bz88sudLuWAenp66O3tZezYsQ1/joEu6bDT39/PMcccQ19fHxHR6XLeIDPZs2cP/f39TJs2reHPc8lF0mHn5ZdfZsKECV0Z5gARwYQJEw75LwgDXdJhqVvD/HVvpj4DXZIK4Rq6pFGvb9H9b9i2/ZbLRvT5I3EoYzeTM3RJ6oAPfehDzJkzh1NOOYVly5Y1pU9n6JLUAcuXL+f4449n//79nHnmmXz4wx9mwoQJI+rTQJekDrjttttYuXIlADt37uS5554z0GttPnnGoPaMLZs7VIkkHdijjz7Kww8/zJo1axg3bhwXXXRRU25ycg1dktps3759HHfccYwbN44tW7bw5JNPNqXfomboktRVdj01uP3OMwCYN28eS5cuZdasWUyfPp1zzjmnKcMZ6JIOe+2+zPCoo47igQceaHq/LrlIUiEMdEkqhIEuSYUw0CWpEAa6JBXCQJekQhjoktRm27dv5z3veU/T+/U6dElaMr7J/e1rbn8NcoYuSR0wMDDAggULmDVrFvPnz+ell14acZ8Gut68JeMHf0hq2NatW1m4cCEbNmzg2GOP5Y477hhxnwa6JHXAlClTOPfccwH46Ec/yuOPPz7iPg10SeqA+jeBbsabVhvoktQBO3bsYM2aNQDcc889nHfeeSPu00CXpA6YMWMGd911F7NmzWLv3r18/OMfH3GfXrYoSW2+zLCvr49nnnmm6f06Q5ekQhjoklQIl1zUsL5F9w9qb+/pUCGShuQMXZIKYaBLUiEaCvSImBcRWyNiW0QsGmL/+Ii4LyK+GxGbIuK65pcqSTqYYQM9IsYAtwOXAjOBqyNiZt1hnwCeyczTgIuAv4uII5tcqyTpIBo5KXoWsC0znweIiBXAFUDtRZQJHBOVe1ePBvYCA02uVZJa4tS7Tm1qfxsXbGxqf41qZMllMrCzpt1f3Vbrn4AZwC5gI/CpzHytKRVKUoHuvvtuZs2axWmnnca1117blD4bmaEP9cSYrGt/AHga+B3gXcDXI+KxzHxxUEcRC4GFAFOnTj3kYiWpBJs2beLmm2/miSeeYOLEiezdu7cp/TYS6P3AlJp2L5WZeK3rgFsyM4FtEfED4GTg27UHZeYyYBnA3Llz638paATq/2Ts1J98kob3yCOPMH/+fCZOnAjA8ccf35R+G1lyWQucFBHTqic6rwJW1R2zA7gYICJOAKYDzzelQkkqTGY25XG59YYN9MwcAG4EHgI2A/dm5qaIuCEibqge9mngvRGxEfgGcFNmvtD0aiWpABdffDH33nsve/bsAWjrkguZuRpYXbdtac3rXcD7m1KRJBXulFNOYfHixVx44YWMGTOGM844gzvvvHPE/fosF0mHvU6cc1qwYAELFixoap/e+i9JhTDQJakQBrokFcJAl6RCGOiSVAgDXZIKYaBLUoctWbKEW2+9dcT9eB261CabT54xqD1jy+YOVaJ69d+bkerU99YZuiR1wM0338z06dO55JJL2Lp1a1P6dIYuSW22fv16VqxYwVNPPcXAwACzZ89mzpw5I+7XQJekNnvssce48sorGTduHACXX355U/p1yUWSOqAjj89VnSXjB39I0iG64IILWLlyJfv37+cXv/gF9913X1P6dclFktps9uzZfOQjH+H000/nxBNP5Pzzz29Kv10d6H2L7h/U3n7LZR2qRFLJOnGZ4eLFi1m8eHFT+3TJRZIKYaBLUiEMdEkqhIEu6bCUmZ0u4aDeTH1dfVJUqld/ohw8Wa5D19PTw549e5gwYUJLrgcfqcxkz5499PT0HNLnGeiSDju9vb309/eze/fu1g70858Nbu9r/Gqanp4eent7D2k4A13SYWfs2LFMmzat9QMtOaeuva+lwxnoktQhQz22dyTXxHtSVJIKYaBLUiEMdEkqhIEuSYUw0CWpEF7l0gK+GbCkTjDQpWaof7OTFl9vLA3FJRdJKoSBLkmFMNAlqRAGuiQVoqFAj4h5EbE1IrZFxKIDHHNRRDwdEZsi4pvNLVOSNJxhr3KJiDHA7cDvAv3A2ohYlZnP1BzzduAOYF5m7oiI32hRvZKkA2hkhn4WsC0zn8/MXwMrgCvqjrkG+HJm7gDIzLqHAEuSWq2RQJ8M7Kxp91e31Xo3cFxEPBoR6yPiY80qUJLUmEZuLBrq/Znq3+zuCGAOcDHwVmBNRDyZmc8O6ihiIbAQYOrUqYderSTpgBqZofcDU2ravcCuIY55MDN/lZkvAP8JnFbfUWYuy8y5mTl30qRJb7ZmSdIQGgn0tcBJETEtIo4ErgJW1R3zFeD8iDgiIsYBZwM+wESS2mjYJZfMHIiIG4GHgDHA8szcFBE3VPcvzczNEfEgsAF4DfhcZn6vlYVLkgZr6OFcmbkaWF23bWld+7PAZ5tXmg6q/mFQ0zwnIR3uvFNUkgphoEtSIQx0SSqEgS5JhTDQJakQBrokFcJAl6RCGOiSVAgDXZIKYaBLUiEMdEkqhIEuSYVo6OFc6ry+RfcPam/v6VAhkrqWM3RJKoSBLkmFMNAlqRAGuiQVwkCXpEIY6JJUCANdkgrhdega/erfMHvJvs7UIXWYM3RJKoSBLkmFMNAlqRAGuiQVwkCXpEIY6JJUCANdkgphoEtSIQx0SSqEgS5JhTDQJakQBrokFcJAl6RC+LRFSWqSvkX3D2pv72nv+A3N0CNiXkRsjYhtEbHoIMedGRGvRsT85pUoSWrEsIEeEWOA24FLgZnA1REx8wDHfQZ4qNlFSpKG18gM/SxgW2Y+n5m/BlYAVwxx3J8B/w78rIn1SZIa1EigTwZ21rT7q9v+T0RMBq4EljavNEnSoWgk0GOIbVnX/gfgpsx89aAdRSyMiHURsW737t0NlihJakQjV7n0A1Nq2r3Arrpj5gIrIgJgIvDBiBjIzP+oPSgzlwHLAObOnVv/S0GSNAKNBPpa4KSImAb8CLgKuKb2gMyc9vrriLgT+Gp9mEsq0xsu1bvlsg5VomEDPTMHIuJGKlevjAGWZ+amiLihut91c0nqAg3dWJSZq4HVdduGDPLM/KORlyVJOlTeKSqppU6969RB7Y0LNnaokvL5LBdJKoQzdBVv88kzBrVnbNncoUqk1nKGLkmFMNAlqRAGuiQVwkCXpEIY6JJUCANdkgphoEtSIQx0SSqEgS5JhfBO0RGqf04FwL0dqEOSnKFLUiEMdEkqhIEuSYUw0CWpEAa6JBXCQJekQhjoklQIr0OX1FxLxg9uT5vamToOQ87QJakQBrokFcIll2H0Lbp/UHt7T4cKkTQi9Y/p2LhgY4cqaR1n6JJUCANdkgrhkoukttp88ow3bJuxZXMHKimPM3RJKoQzdBWn/uSXz6fX4cIZuiQVwkCXpEKM6iUX/7SWpP/nDF2SCjGqZ+hSp3gHsbqRM3RJKkRDgR4R8yJia0Rsi4hFQ+z/w4jYUP34VkSc1vxSJUkHM2ygR8QY4HbgUmAmcHVEzKw77AfAhZk5C/g0sKzZhUqSDq6RNfSzgG2Z+TxARKwArgCeef2AzPxWzfFPAr3NLFKSmq3+EQQlPH6gkSWXycDOmnZ/dduB/DHwwFA7ImJhRKyLiHW7d+9uvEpJ0rAaCfQYYlsOeWDE+6gE+k1D7c/MZZk5NzPnTpo0qfEqJUnDamTJpR+YUtPuBXbVHxQRs4DPAZdm5p7mlCdJalQjgb4WOCkipgE/Aq4Crqk9ICKmAl8Grs3MZ5tepTTK1N/FDN7JrNYbNtAzcyAibgQeAsYAyzNzU0TcUN2/FPhrYAJwR0QADGTm3NaVLUmjT6sfV9LQnaKZuRpYXbdtac3r64Hrm1uaJOlQeKeoJBXCQJekQhjoklQIA12SCmGgS1IhDHRJKoSBLkmFMNAlqRAGuiQVwkCXpEIY6JJUCANdkgphoEtSIQx0SSqEgS5JhTDQJakQDb3BhaRRYsn4uva+ztShjnCGLkmFcIauphnqjZE3LtjYgUqkw5OBrpbafPKMQe0ZWzZ3qBKpfC65SFIhDHRJKoRLLlLB6s9reE6jbM7QJakQBrokFcJAl6RCuIYujVJ9i+5/w7btPR0oRF3DGbokFcIZeqG8oUc6/IyuQK9/8NC0qZ2pQ5K6kEsuklQIA12SCmGgS1IhRtcauqQR8WR52ZyhS1IhGgr0iJgXEVsjYltELBpif0TEbdX9GyJidvNLlSQdzLCBHhFjgNuBS4GZwNURMbPusEuBk6ofC4F/bnKdkqRhNLKGfhawLTOfB4iIFcAVwDM1x1wB3J2ZCTwZEW+PiHdk5o+bXrEkNeIwvG8lKhl8kAMi5gPzMvP6avta4OzMvLHmmK8Ct2Tm49X2N4CbMnNdXV8LqczgAaYDW0dY/0TghRH2MVLdUAN0Rx3dUAN0Rx3dUAN0Rx3dUAN0Rx3NqOHEzJw01I5GZugxxLb63wKNHENmLgOWNTBmQyJiXWbObVZ/o7WGbqmjG2roljq6oYZuqaMbauiWOlpdQyMnRfuBKTXtXmDXmzhGktRCjQT6WuCkiJgWEUcCVwGr6o5ZBXyserXLOcA+188lqb2GXXLJzIGIuBF4CBgDLM/MTRFxQ3X/UmA18EFgG/AScF3rSh6kacs3I9ANNUB31NENNUB31NENNUB31NENNUB31NHSGoY9KSpJGh28U1SSCmGgS1IhDHRJKsSoetpiRJxM5a7UyVSuc98FrMrMw+6RcdWvxWTgvzLzlzXb52Xmg22q4SwgM3Nt9XEQ84Atmbm6HeMfoKa7M/NjnRq/WsN5VO6w/l5mfq2N454NbM7MFyPircAiYDaVu7r/NjP3taGGTwIrM3Nnq8c6SA2vX423KzMfjohrgPcCm4FlmflKG2t5F3Allcu6B4DngHta9b0YNSdFI+Im4GpgBZXr3qFyvftVwIrMvKVTtb0uIq7LzC+0YZxPAp+g8gN6OvCpzPxKdd93MrPlD0eLiL+h8gyfI4CvA2cDjwKXAA9l5s1tqKH+8tkA3gc8ApCZl7e6hmod387Ms6qv/4TK92Yl8H7gvnb9bEbEJuC06pVpy6hccfYl4OLq9j9oQw37gF8B3wfuAb6YmbtbPW5dDf9K5edyHPBz4Gjgy1S+DpGZC9pUxyeB3we+SeUqwKeB/6YS8H+amY82fdDMHBUfwLPA2CG2Hwk81+n6qrXsaNM4G4Gjq6/7gHVUQh3gqTbWMIbKP5oXgWOr298KbGhTDd8B/gW4CLiw+t8fV19f2Mbv+1M1r9cCk6qv3wZsbGMdm2u/NnX7nm7X14LKUu77gc8Du4EHgQXAMW2qYUP1v0cAPwXGVNvRrp/N6ngba8YeBzxafT21Vf9OR9OSy2vAO4Ef1m1/R3VfW0TEhgPtAk5oUxljsrrMkpnbI+Ii4EsRcSJDP4ahFQYy81XgpYj4fma+WK1nf0S06/sxF/gUsBj4i8x8OiL2Z+Y32zT+694SEcdRCbLI6ow0M38VEQNtrON7NX8lfjci5mbmuoh4N9CuZYbMzNeArwFfi4ixVP6Suxq4FRjyGSRN9pbqssvbqATpeGAvcBQwtg3j1zoCeLU69jEAmbmj+nVpyWCjxZ8D34iI54DX1+emAr8N3HigT2qBE4APUPnTqVYA32pTDT+JiNMz82mAzPxlRPwesBw4tU01/DoixmXmS8Cc1zdGxHja9Au2Ghx/HxFfrP73p3TmZ3o8sJ7Kz0BGxG9m5k8i4mja9wsW4HrgHyPir6g8AGpNROyk8u/l+jbVMOj/Nyvr1auAVdV1/Xb4PLCFyl+Qi4EvRsTzwDlUlmzb5XPA2oh4ErgA+AxAREyi8gum6UbNGjpARLyFysmmyVR+cPqBtdWZYrtq+Dzwhaw+WbJu379l5jVtqKGXygz5J0PsOzczn2hDDUdl5v8MsX0i8I7M3NjqGoYY+zLg3Mz8y3aPPZSIGAeckJk/aPO4xwC/ReWXW39m/rSNY787M59t13gHqeOdAJm5KyLeTuXczo7M/Hab6zgFmEHlBPmWlo83mgJdknRgXocuSYUw0CWpEAa6JBXCQJekQhjoklSI/wXX9ofh3LtodgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot.bar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "df.plot(kind=\"bar\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "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>Make</th>\n",
       "      <th>Colour</th>\n",
       "      <th>Odometer (KM)</th>\n",
       "      <th>Doors</th>\n",
       "      <th>Price</th>\n",
       "      <th>Sale Date</th>\n",
       "      <th>Total Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>White</td>\n",
       "      <td>150043</td>\n",
       "      <td>4</td>\n",
       "      <td>4000</td>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>4000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Honda</td>\n",
       "      <td>Red</td>\n",
       "      <td>87899</td>\n",
       "      <td>4</td>\n",
       "      <td>5000</td>\n",
       "      <td>2021-01-02</td>\n",
       "      <td>9000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>Blue</td>\n",
       "      <td>32549</td>\n",
       "      <td>3</td>\n",
       "      <td>7000</td>\n",
       "      <td>2021-01-03</td>\n",
       "      <td>16000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BMW</td>\n",
       "      <td>Black</td>\n",
       "      <td>11179</td>\n",
       "      <td>5</td>\n",
       "      <td>22000</td>\n",
       "      <td>2021-01-04</td>\n",
       "      <td>38000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Nissan</td>\n",
       "      <td>White</td>\n",
       "      <td>213095</td>\n",
       "      <td>4</td>\n",
       "      <td>3500</td>\n",
       "      <td>2021-01-05</td>\n",
       "      <td>41500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>Green</td>\n",
       "      <td>99213</td>\n",
       "      <td>4</td>\n",
       "      <td>4500</td>\n",
       "      <td>2021-01-06</td>\n",
       "      <td>46000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Honda</td>\n",
       "      <td>Blue</td>\n",
       "      <td>45698</td>\n",
       "      <td>4</td>\n",
       "      <td>7500</td>\n",
       "      <td>2021-01-07</td>\n",
       "      <td>53500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Honda</td>\n",
       "      <td>Blue</td>\n",
       "      <td>54738</td>\n",
       "      <td>4</td>\n",
       "      <td>7000</td>\n",
       "      <td>2021-01-08</td>\n",
       "      <td>60500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>White</td>\n",
       "      <td>60000</td>\n",
       "      <td>4</td>\n",
       "      <td>6250</td>\n",
       "      <td>2021-01-09</td>\n",
       "      <td>66750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Nissan</td>\n",
       "      <td>White</td>\n",
       "      <td>31600</td>\n",
       "      <td>4</td>\n",
       "      <td>9700</td>\n",
       "      <td>2021-01-10</td>\n",
       "      <td>76450</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Make Colour  Odometer (KM)  Doors  Price  Sale Date  Total Sales\n",
       "0  Toyota  White         150043      4   4000 2021-01-01         4000\n",
       "1   Honda    Red          87899      4   5000 2021-01-02         9000\n",
       "2  Toyota   Blue          32549      3   7000 2021-01-03        16000\n",
       "3     BMW  Black          11179      5  22000 2021-01-04        38000\n",
       "4  Nissan  White         213095      4   3500 2021-01-05        41500\n",
       "5  Toyota  Green          99213      4   4500 2021-01-06        46000\n",
       "6   Honda   Blue          45698      4   7500 2021-01-07        53500\n",
       "7   Honda   Blue          54738      4   7000 2021-01-08        60500\n",
       "8  Toyota  White          60000      4   6250 2021-01-09        66750\n",
       "9  Nissan  White          31600      4   9700 2021-01-10        76450"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_sales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Make'>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "car_sales.plot(x=\"Make\",y=\"Odometer (KM)\",kind=\"bar\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Frequency'>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "# histograms\n",
    "car_sales[\"Odometer (KM)\"].plot.hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Frequency'>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "car_sales[\"Odometer (KM)\"].plot(kind=\"hist\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Frequency'>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "car_sales[\"Odometer (KM)\"].plot.hist(bins=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "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>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>cp</th>\n",
       "      <th>trestbps</th>\n",
       "      <th>chol</th>\n",
       "      <th>fbs</th>\n",
       "      <th>restecg</th>\n",
       "      <th>thalach</th>\n",
       "      <th>exang</th>\n",
       "      <th>oldpeak</th>\n",
       "      <th>slope</th>\n",
       "      <th>ca</th>\n",
       "      <th>thal</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>63</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>145</td>\n",
       "      <td>233</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>150</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>130</td>\n",
       "      <td>250</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>187</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>130</td>\n",
       "      <td>204</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>172</td>\n",
       "      <td>0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>56</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>120</td>\n",
       "      <td>236</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>178</td>\n",
       "      <td>0</td>\n",
       "      <td>0.8</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>57</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>120</td>\n",
       "      <td>354</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>163</td>\n",
       "      <td>1</td>\n",
       "      <td>0.6</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age  sex  cp  trestbps  chol  fbs  restecg  thalach  exang  oldpeak  slope  \\\n",
       "0   63    1   3       145   233    1        0      150      0      2.3      0   \n",
       "1   37    1   2       130   250    0        1      187      0      3.5      0   \n",
       "2   41    0   1       130   204    0        0      172      0      1.4      2   \n",
       "3   56    1   1       120   236    0        1      178      0      0.8      2   \n",
       "4   57    0   0       120   354    0        1      163      1      0.6      2   \n",
       "\n",
       "   ca  thal  target  \n",
       "0   0     1       1  \n",
       "1   0     2       1  \n",
       "2   0     2       1  \n",
       "3   0     2       1  \n",
       "4   0     2       1  "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# another dataset\n",
    "heart_disease = pd.read_csv(\"heart-disease.csv\")\n",
    "heart_disease.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Frequency'>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "# histogram of age\n",
    "heart_disease[\"age\"].plot.hist(bins=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "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>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>cp</th>\n",
       "      <th>trestbps</th>\n",
       "      <th>chol</th>\n",
       "      <th>fbs</th>\n",
       "      <th>restecg</th>\n",
       "      <th>thalach</th>\n",
       "      <th>exang</th>\n",
       "      <th>oldpeak</th>\n",
       "      <th>slope</th>\n",
       "      <th>ca</th>\n",
       "      <th>thal</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>63</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>145</td>\n",
       "      <td>233</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>150</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>130</td>\n",
       "      <td>250</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>187</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>130</td>\n",
       "      <td>204</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>172</td>\n",
       "      <td>0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>56</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>120</td>\n",
       "      <td>236</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>178</td>\n",
       "      <td>0</td>\n",
       "      <td>0.8</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>57</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>120</td>\n",
       "      <td>354</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>163</td>\n",
       "      <td>1</td>\n",
       "      <td>0.6</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age  sex  cp  trestbps  chol  fbs  restecg  thalach  exang  oldpeak  slope  \\\n",
       "0   63    1   3       145   233    1        0      150      0      2.3      0   \n",
       "1   37    1   2       130   250    0        1      187      0      3.5      0   \n",
       "2   41    0   1       130   204    0        0      172      0      1.4      2   \n",
       "3   56    1   1       120   236    0        1      178      0      0.8      2   \n",
       "4   57    0   0       120   354    0        1      163      1      0.6      2   \n",
       "\n",
       "   ca  thal  target  \n",
       "0   0     1       1  \n",
       "1   0     2       1  \n",
       "2   0     2       1  \n",
       "3   0     2       1  \n",
       "4   0     2       1  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "heart_disease.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x2160 with 14 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "heart_disease.plot.hist(figsize=(10,30),subplots=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* OO method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "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>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>cp</th>\n",
       "      <th>trestbps</th>\n",
       "      <th>chol</th>\n",
       "      <th>fbs</th>\n",
       "      <th>restecg</th>\n",
       "      <th>thalach</th>\n",
       "      <th>exang</th>\n",
       "      <th>oldpeak</th>\n",
       "      <th>slope</th>\n",
       "      <th>ca</th>\n",
       "      <th>thal</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>63</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>145</td>\n",
       "      <td>233</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>150</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>130</td>\n",
       "      <td>250</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>187</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>130</td>\n",
       "      <td>204</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>172</td>\n",
       "      <td>0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>56</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>120</td>\n",
       "      <td>236</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>178</td>\n",
       "      <td>0</td>\n",
       "      <td>0.8</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>57</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>120</td>\n",
       "      <td>354</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>163</td>\n",
       "      <td>1</td>\n",
       "      <td>0.6</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age  sex  cp  trestbps  chol  fbs  restecg  thalach  exang  oldpeak  slope  \\\n",
       "0   63    1   3       145   233    1        0      150      0      2.3      0   \n",
       "1   37    1   2       130   250    0        1      187      0      3.5      0   \n",
       "2   41    0   1       130   204    0        0      172      0      1.4      2   \n",
       "3   56    1   1       120   236    0        1      178      0      0.8      2   \n",
       "4   57    0   0       120   354    0        1      163      1      0.6      2   \n",
       "\n",
       "   ca  thal  target  \n",
       "0   0     1       1  \n",
       "1   0     2       1  \n",
       "2   0     2       1  \n",
       "3   0     2       1  \n",
       "4   0     2       1  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "heart_disease.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "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>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>cp</th>\n",
       "      <th>trestbps</th>\n",
       "      <th>chol</th>\n",
       "      <th>fbs</th>\n",
       "      <th>restecg</th>\n",
       "      <th>thalach</th>\n",
       "      <th>exang</th>\n",
       "      <th>oldpeak</th>\n",
       "      <th>slope</th>\n",
       "      <th>ca</th>\n",
       "      <th>thal</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>63</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>145</td>\n",
       "      <td>233</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>150</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>56</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>120</td>\n",
       "      <td>236</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>178</td>\n",
       "      <td>0</td>\n",
       "      <td>0.8</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>57</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>120</td>\n",
       "      <td>354</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>163</td>\n",
       "      <td>1</td>\n",
       "      <td>0.6</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>57</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>140</td>\n",
       "      <td>192</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>148</td>\n",
       "      <td>0</td>\n",
       "      <td>0.4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>56</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>140</td>\n",
       "      <td>294</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>153</td>\n",
       "      <td>0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age  sex  cp  trestbps  chol  fbs  restecg  thalach  exang  oldpeak  slope  \\\n",
       "0   63    1   3       145   233    1        0      150      0      2.3      0   \n",
       "3   56    1   1       120   236    0        1      178      0      0.8      2   \n",
       "4   57    0   0       120   354    0        1      163      1      0.6      2   \n",
       "5   57    1   0       140   192    0        1      148      0      0.4      1   \n",
       "6   56    0   1       140   294    0        0      153      0      1.3      1   \n",
       "\n",
       "   ca  thal  target  \n",
       "0   0     1       1  \n",
       "3   0     2       1  \n",
       "4   0     2       1  \n",
       "5   0     1       1  \n",
       "6   0     2       1  "
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "over_50 = heart_disease[heart_disease[\"age\"]>50]\n",
    "over_50.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='age', ylabel='chol'>"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Pyplot method\n",
    "over_50.plot(kind=\"scatter\",x=\"age\",y=\"chol\",c=\"target\",figsize=(10,6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='age', ylabel='chol'>"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# OO method\n",
    "fig, ax = plt.subplots(figsize=(10,6))\n",
    "over_50.plot(kind=\"scatter\",x=\"age\",y=\"chol\",c=\"target\",ax=ax)\n",
    "\n",
    "#ax.set_xlim([45,100])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0], dtype=int64)"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "over_50.target.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x1ee58ac2160>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# OO method from scratch\n",
    "fig,ax = plt.subplots(figsize=(10,6))\n",
    "\n",
    "# Plot the data\n",
    "scatter = ax.scatter(x=over_50[\"age\"],y=over_50[\"chol\"],c=over_50[\"target\"])\n",
    "\n",
    "# Customize\n",
    "ax.set(title=\"Heart Disease and Cholesterol Level\",xlabel=\"Age\",ylabel=\"Cholesterol\")\n",
    "\n",
    "# Legend\n",
    "ax.legend(*scatter.legend_elements(),title=\"Target\")\n",
    "\n",
    "# Horizontal line\n",
    "ax.axhline(over_50[\"chol\"].mean(),ls=\"--\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "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>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>cp</th>\n",
       "      <th>trestbps</th>\n",
       "      <th>chol</th>\n",
       "      <th>fbs</th>\n",
       "      <th>restecg</th>\n",
       "      <th>thalach</th>\n",
       "      <th>exang</th>\n",
       "      <th>oldpeak</th>\n",
       "      <th>slope</th>\n",
       "      <th>ca</th>\n",
       "      <th>thal</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>63</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>145</td>\n",
       "      <td>233</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>150</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>56</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>120</td>\n",
       "      <td>236</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>178</td>\n",
       "      <td>0</td>\n",
       "      <td>0.8</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>57</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>120</td>\n",
       "      <td>354</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>163</td>\n",
       "      <td>1</td>\n",
       "      <td>0.6</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>57</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>140</td>\n",
       "      <td>192</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>148</td>\n",
       "      <td>0</td>\n",
       "      <td>0.4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>56</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>140</td>\n",
       "      <td>294</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>153</td>\n",
       "      <td>0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age  sex  cp  trestbps  chol  fbs  restecg  thalach  exang  oldpeak  slope  \\\n",
       "0   63    1   3       145   233    1        0      150      0      2.3      0   \n",
       "3   56    1   1       120   236    0        1      178      0      0.8      2   \n",
       "4   57    0   0       120   354    0        1      163      1      0.6      2   \n",
       "5   57    1   0       140   192    0        1      148      0      0.4      1   \n",
       "6   56    0   1       140   294    0        0      153      0      1.3      1   \n",
       "\n",
       "   ca  thal  target  \n",
       "0   0     1       1  \n",
       "3   0     2       1  \n",
       "4   0     2       1  \n",
       "5   0     1       1  \n",
       "6   0     2       1  "
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "over_50.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0.98, 'Heart Disease Analysis')"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# subplot of chol, age, thalach\n",
    "fig,(ax0,ax1) = plt.subplots(nrows=2,ncols=1,figsize=(10,10),sharex=True)\n",
    "\n",
    "\n",
    "# ax0\n",
    "# Add data\n",
    "scatter = ax0.scatter(x=over_50[\"age\"],y=over_50[\"chol\"],c=over_50[\"target\"])\n",
    "\n",
    "# customize \n",
    "ax0.set(title=\"Heart Disease and Cholesterol Levels\",ylabel=\"Cholesterol\")\n",
    "\n",
    "# legend  \n",
    "ax0.legend(*scatter.legend_elements(),title=\"Target\")\n",
    "\n",
    "# meanline\n",
    "ax0.axhline(y=over_50[\"chol\"].mean(),ls=\"--\")\n",
    "\n",
    "\n",
    "# ax1\n",
    "# add data\n",
    "scatter = ax1.scatter(x=over_50[\"age\"],y=over_50[\"thalach\"],c=over_50[\"target\"])\n",
    "\n",
    "# customize\n",
    "ax1.set(title=\"Heart Disease and Max Heart Rate\",xlabel=\"Age\",ylabel=\"Max Heart Rate\")\n",
    "\n",
    "# legend\n",
    "ax1.legend(*scatter.legend_elements(),title=\"Target\")\n",
    "\n",
    "# meanline\n",
    "ax1.axhline(y=over_50[\"thalach\"].mean(),ls=\"--\")\n",
    "\n",
    "\n",
    "# fig title\n",
    "fig.suptitle(\"Heart Disease Analysis\",fontsize=16,fontweight=\"bold\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Customize Matplotlib plots and styling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Solarize_Light2',\n",
       " '_classic_test_patch',\n",
       " 'bmh',\n",
       " 'classic',\n",
       " 'dark_background',\n",
       " 'fast',\n",
       " 'fivethirtyeight',\n",
       " 'ggplot',\n",
       " 'grayscale',\n",
       " 'seaborn',\n",
       " 'seaborn-bright',\n",
       " 'seaborn-colorblind',\n",
       " 'seaborn-dark',\n",
       " 'seaborn-dark-palette',\n",
       " 'seaborn-darkgrid',\n",
       " 'seaborn-deep',\n",
       " 'seaborn-muted',\n",
       " 'seaborn-notebook',\n",
       " 'seaborn-paper',\n",
       " 'seaborn-pastel',\n",
       " 'seaborn-poster',\n",
       " 'seaborn-talk',\n",
       " 'seaborn-ticks',\n",
       " 'seaborn-white',\n",
       " 'seaborn-whitegrid',\n",
       " 'tableau-colorblind10']"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# See the diff styles available\n",
    "plt.style.available"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "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>Make</th>\n",
       "      <th>Colour</th>\n",
       "      <th>Odometer (KM)</th>\n",
       "      <th>Doors</th>\n",
       "      <th>Price</th>\n",
       "      <th>Sale Date</th>\n",
       "      <th>Total Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>White</td>\n",
       "      <td>150043</td>\n",
       "      <td>4</td>\n",
       "      <td>4000</td>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>4000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Honda</td>\n",
       "      <td>Red</td>\n",
       "      <td>87899</td>\n",
       "      <td>4</td>\n",
       "      <td>5000</td>\n",
       "      <td>2021-01-02</td>\n",
       "      <td>9000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>Blue</td>\n",
       "      <td>32549</td>\n",
       "      <td>3</td>\n",
       "      <td>7000</td>\n",
       "      <td>2021-01-03</td>\n",
       "      <td>16000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BMW</td>\n",
       "      <td>Black</td>\n",
       "      <td>11179</td>\n",
       "      <td>5</td>\n",
       "      <td>22000</td>\n",
       "      <td>2021-01-04</td>\n",
       "      <td>38000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Nissan</td>\n",
       "      <td>White</td>\n",
       "      <td>213095</td>\n",
       "      <td>4</td>\n",
       "      <td>3500</td>\n",
       "      <td>2021-01-05</td>\n",
       "      <td>41500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Make Colour  Odometer (KM)  Doors  Price  Sale Date  Total Sales\n",
       "0  Toyota  White         150043      4   4000 2021-01-01         4000\n",
       "1   Honda    Red          87899      4   5000 2021-01-02         9000\n",
       "2  Toyota   Blue          32549      3   7000 2021-01-03        16000\n",
       "3     BMW  Black          11179      5  22000 2021-01-04        38000\n",
       "4  Nissan  White         213095      4   3500 2021-01-05        41500"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_sales.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "car_sales[\"Price\"].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.style.use(\"seaborn-whitegrid\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "car_sales[\"Price\"].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.style.use(\"seaborn\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "car_sales[\"Price\"].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Odometer (KM)', ylabel='Price'>"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "car_sales.plot(x=\"Odometer (KM)\",y=\"Price\",kind=\"scatter\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.style.use(\"ggplot\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "car_sales[\"Price\"].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 2.42809833,  1.31053279, -0.97633501, -1.80392954],\n",
       "       [-0.13018882,  0.48693015, -0.20482206,  0.88788228],\n",
       "       [-0.15919383, -1.32852558,  0.4223383 , -1.56004693],\n",
       "       [ 0.18446687, -0.3212591 ,  1.69716454, -0.37385224],\n",
       "       [ 0.78837764,  0.19496881,  1.69176548, -0.56132999],\n",
       "       [ 0.0419019 , -1.40567021, -0.05910017, -0.75323257],\n",
       "       [ 0.00974994,  0.6886965 , -1.18435872,  0.12073458],\n",
       "       [-1.3912679 ,  1.34136452,  1.33858956,  1.26470243],\n",
       "       [ 1.13391243, -0.2013165 , -1.60899408, -0.98578072],\n",
       "       [ 0.45973483, -1.25753927,  0.0695243 , -0.45790861]])"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# random data\n",
    "x = np.random.randn(10,4)\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "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>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "      <th>d</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2.428098</td>\n",
       "      <td>1.310533</td>\n",
       "      <td>-0.976335</td>\n",
       "      <td>-1.803930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.130189</td>\n",
       "      <td>0.486930</td>\n",
       "      <td>-0.204822</td>\n",
       "      <td>0.887882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.159194</td>\n",
       "      <td>-1.328526</td>\n",
       "      <td>0.422338</td>\n",
       "      <td>-1.560047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.184467</td>\n",
       "      <td>-0.321259</td>\n",
       "      <td>1.697165</td>\n",
       "      <td>-0.373852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.788378</td>\n",
       "      <td>0.194969</td>\n",
       "      <td>1.691765</td>\n",
       "      <td>-0.561330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.041902</td>\n",
       "      <td>-1.405670</td>\n",
       "      <td>-0.059100</td>\n",
       "      <td>-0.753233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.009750</td>\n",
       "      <td>0.688696</td>\n",
       "      <td>-1.184359</td>\n",
       "      <td>0.120735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>-1.391268</td>\n",
       "      <td>1.341365</td>\n",
       "      <td>1.338590</td>\n",
       "      <td>1.264702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1.133912</td>\n",
       "      <td>-0.201316</td>\n",
       "      <td>-1.608994</td>\n",
       "      <td>-0.985781</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.459735</td>\n",
       "      <td>-1.257539</td>\n",
       "      <td>0.069524</td>\n",
       "      <td>-0.457909</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          a         b         c         d\n",
       "0  2.428098  1.310533 -0.976335 -1.803930\n",
       "1 -0.130189  0.486930 -0.204822  0.887882\n",
       "2 -0.159194 -1.328526  0.422338 -1.560047\n",
       "3  0.184467 -0.321259  1.697165 -0.373852\n",
       "4  0.788378  0.194969  1.691765 -0.561330\n",
       "5  0.041902 -1.405670 -0.059100 -0.753233\n",
       "6  0.009750  0.688696 -1.184359  0.120735\n",
       "7 -1.391268  1.341365  1.338590  1.264702\n",
       "8  1.133912 -0.201316 -1.608994 -0.985781\n",
       "9  0.459735 -1.257539  0.069524 -0.457909"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(x, columns=[\"a\",\"b\",\"c\",\"d\"])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "matplotlib.axes._subplots.AxesSubplot"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = df.plot(kind=\"bar\")\n",
    "type(ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# customize using set\n",
    "ax = df.plot(kind=\"bar\")\n",
    "\n",
    "ax.set(title=\"Random Number Bar Graph from dataframe\",xlabel=\"Row number\",ylabel=\"Random number\")\n",
    "\n",
    "ax.legend().set_visible(True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x1ee580630a0>"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# set the style\n",
    "plt.style.use(\"seaborn-whitegrid\")\n",
    "\n",
    "# OO method from scratch\n",
    "fig,ax = plt.subplots(figsize=(10,6))\n",
    "\n",
    "# Plot the data\n",
    "scatter = ax.scatter(x=over_50[\"age\"],y=over_50[\"chol\"],c=over_50[\"target\"],cmap=\"winter\")\n",
    "\n",
    "# Customize\n",
    "ax.set(title=\"Heart Disease and Cholesterol Level\",xlabel=\"Age\",ylabel=\"Cholesterol\")\n",
    "\n",
    "# Legend\n",
    "ax.legend(*scatter.legend_elements(),title=\"Target\")\n",
    "\n",
    "# Horizontal line\n",
    "ax.axhline(over_50[\"chol\"].mean(),ls=\"--\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0.98, 'Heart Disease Analysis')"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# customizing the y and x\n",
    "\n",
    "# subplot of chol, age, thalach\n",
    "fig,(ax0,ax1) = plt.subplots(nrows=2,ncols=1,figsize=(10,10),sharex=True)\n",
    "\n",
    "\n",
    "# ax0\n",
    "# Add data\n",
    "scatter = ax0.scatter(x=over_50[\"age\"],y=over_50[\"chol\"],c=over_50[\"target\"],cmap=\"winter\")\n",
    "\n",
    "# customize \n",
    "ax0.set(title=\"Heart Disease and Cholesterol Levels\",ylabel=\"Cholesterol\")\n",
    "\n",
    "#change x,y axis limit\n",
    "ax0.set_xlim([50,80])\n",
    "#ax0.set_ylim([60,200])\n",
    "\n",
    "# legend  \n",
    "ax0.legend(*scatter.legend_elements(),title=\"Target\")\n",
    "\n",
    "# meanline\n",
    "ax0.axhline(y=over_50[\"chol\"].mean(),ls=\"--\")\n",
    "\n",
    "\n",
    "# ax1\n",
    "# add data\n",
    "scatter = ax1.scatter(x=over_50[\"age\"],y=over_50[\"thalach\"],c=over_50[\"target\"],cmap=\"winter\")\n",
    "\n",
    "# customize\n",
    "ax1.set(title=\"Heart Disease and Max Heart Rate\",xlabel=\"Age\",ylabel=\"Max Heart Rate\")\n",
    "\n",
    "#change x,y axis limit\n",
    "ax1.set_xlim([50,80])\n",
    "ax1.set_ylim([60,200])\n",
    "\n",
    "# legend\n",
    "ax1.legend(*scatter.legend_elements(),title=\"Target\")\n",
    "\n",
    "# meanline\n",
    "ax1.axhline(y=over_50[\"thalach\"].mean(),ls=\"--\")\n",
    "\n",
    "\n",
    "# fig title\n",
    "fig.suptitle(\"Heart Disease Analysis\",fontsize=16,fontweight=\"bold\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig.savefig(\"heart-disease-analysis.png\")"
   ]
  },
  {
   "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": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}