sample-project/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(); #add ; to remove []"
   ]
  },
  {
   "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 0x10ed45510>]"
      ]
     },
     "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]) # assume x = [0, 1, 2, 3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x10ee0bb90>]"
      ]
     },
     "execution_count": 6,
     "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": [
    "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": [
    "plt.plot();"
   ]
  },
  {
   "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": [
    "# 1st method\n",
    "fig = plt.figure() # creates a figure\n",
    "ax = fig.add_subplot() # adds some axes\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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 a 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": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(matplotlib.figure.Figure, matplotlib.axes._subplots.AxesSubplot)"
      ]
     },
     "execution_count": 10,
     "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 (recommended)\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": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 0. import matplotlib and get it ready for plotting in Jupyter\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# 1. Prepare data\n",
    "x = [1, 2, 3, 4]\n",
    "y = [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=\"Sample Simple Plot\", xlabel=\"x-axis\", ylabel=\"y-axis\")\n",
    "\n",
    "# 5. Save & show\n",
    "fig.savefig(\"images/simple-plot.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"images/anatomy-of-a-matplotlib-plot-1.png\" />"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"images/anatomy-of-a-matplotlib-plot-2.png\" />"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Making figures with NumPy arrays\n",
    "\n",
    "We want:\n",
    "* Line plot\n",
    "* Scatter plot\n",
    "* Bar plot\n",
    "* Histogram\n",
    "* Subplots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create an array\n",
    "x = np.linspace(0, 10, 100)\n",
    "x[0:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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7U3NYu6uUx0b05I6hWV5HkhBQuYs0InlFZYydsoyCg8d4YdQALuvZxutIEiIqd5FGImf7fsZPy6GJGbMmDKF/ZkuvI0kIqdxFGoG/r9nLfXNWkZ6cwJSxA+mQ0tTrSBJiKneRCOac4/mPt/HkO5vJ7tCSF+/MpmXTWK9jST1QuYtEqKoaHz//6zpezcnn2r7tePLGPlrEuhFRuYtEoIPlVfxg5nI+yy3hnm935r5Lu+pSx0ZG5S4SYXaUHGHslGXk7y/nqZv6cuOADK8jiQdU7iIRZEleCd+fvhwHTB83mMGdUryOJB5RuYtEiDnL8vnvv62lfatEJo8eSFZrXRHTmAU8kYSZRZnZSjOb7/+8o5ktMbNcM3vVzHRqXiSEanyOx+dv4Gevr2FIpxT++oNhKnYJvNyBe4GNx33+G+Bp51xn4AAwLgj7EJGTqF3Aehkvffolo4d24OUxA2mREON1LGkAAip3M8sArgJe8n9uwLeBuf6nTAVGBrIPETm5L4uPcN1zn7FoazGPjezFL0b0IlqzOopfoGPufwB+BvxzLa4UoNQ5V+3/fBdw0iXTzWwCMAEgMzMzwBgijcuirUX8cMYKopoYr4wbzNBzdeJU/lWd/5k3s6uBQufc8rp8v3NuonMu2zmXnZqaWtcYIo2Kc44XP8lj9OSltG2RwJt3f0PFLicVyJH7MOBaM7sSiAeaA88AyWYW7T96zwB2Bx5TRI5V1fDQvLX8deVuhvdsw+9u7qtVk+SU6nzk7px7yDmX4ZzLAm4FPnDO3Q58CNzof9po4I2AU4o0crtLj3LTC1/wt1W7uf+yrjw/SsvhydcLxU/HA8BsM3scWAlMCsE+RBqNz3OLuXvWSqqqfbx4RzaX9EjzOpKEgaCUu3PuI+Aj/+M8YFAwXlekMXPO8dKiL/n1PzZybmoz/nLHADqlNvM6loQJ/b9OpAEqq6jmgblr+PvavVzRqw2/vakvzTQMI2dBPy0iDUxuYRnfn76cvKIyHrqiOxMu7KQZHeWsqdxFGpD5a/bwwNw1xMdEMX38YC44t7XXkSRMqdxFGoDKah+/ensjUz7fTv/MZJ67vT9tWyR4HUvCmMpdxGN7So/yw5krWLmzlO8O68hDV3YnRtMISIBU7iIe+nBTIffNWUV1jeO57/Tnqj5tvY4kEULlLuKB6hofT727hRc+3kaPts157vb+dNQ0vRJEKneRera79Cj3zFrJ8h0H+M7gTP736h5auFqCTuUuUo/e27CP+19bTXWNj2dv68e1fdt5HUkilMpdpB5UVNfw67c3MeXz7fRs15w/fUfDMBJaKneREMstLOOeWSvZsPcQYy7I4qEruxMXrWEYCS2Vu0iIOOd4dVk+v3hrA/ExTZg0OpuLz9OkX1I/VO4iIVBaXslD89byj3UFDO2UwtO3nE+bFvFex5JGROUuEmSfbyvmJ6+upuRIBQ9d0Z3vfbMTTZpobhipXyp3kSCpqK7hd+9u4cVFeXRMacqLdw6jd0YLr2NJI6VyFwmCzQWHuXf2SjYVHGbUkEwevvI8EmP110u8o58+kQDU+ByTPs3jqQVbaJ4QzeQx2Xy7u06aivdU7iJ1lL+/nJ/OWc3S7fu5vGcav7quNynN4ryOJQKo3EXOmnOOGUt28qu3NxJlxu9u6sv1/dO1oIY0KCp3kbOwp/QoD7y+hkVbi/lml9Y8cUMf0pM177o0PCp3kTPgnGP2snx++feN+Jzj8ZG9uH1wpo7WpcFSuYucxq4D5Tw0by2LthYztFMKv7mhD5kpiV7HEvlaKneRU/D5HK8s3sFv3tmEAY+P7MV3BmXqhiQJCyp3kZPILSzjwdfXkLPjABd2TeVX1/Uio6WO1iV8qNxFjlNZ7eOFj7fxpw9ySYiN0pUwErZU7iJ+y3cc4KF5a9iyr4yr+7TlkWt6kpqk69YlPKncpdE7eLSKJ9/ZxMylO2nbPF53mUpEULlLo+Wc4601e3n0rQ3sP1LBd4d15L5Lu9IsTn8tJPzpp1gapbyiMv73jfV8mltM7/QWTBk7kF7pmsFRIofKXRqVo5U1/PmjXP7ycR5xMU14dERPbh/cgShd3igRps7lbmbtgWlAGuCAic65Z8ysFfAqkAVsB252zh0IPKpI3TnnWLB+H4/N38Du0qOMPL8dD191HuckaXUkiUyBHLlXAz91zq0wsyRguZm9B4wBFjrnnjCzB4EHgQcCjypSN7mFZTw6fwOfbCmiW1oSsycMYUinFK9jiYRUncvdObcX2Ot/fNjMNgLpwAjgIv/TpgIfoXIXDxw6VsWz729lyufbSYiJ4n+u7sGdQzsQE9XE62giIReUMXczywL6AUuANH/xAxRQO2xzsu+ZAEwAyMzMDEYMEaB2AY3XcvJ56t3NlByp5OYB7bn/8m66Zl0alYDL3cyaAa8DP3bOHTr+Tj7nnDMzd7Lvc85NBCYCZGdnn/Q5Imfri20lPDZ/Axv2HmJAh5ZMHjOQPhnJXscSqXcBlbuZxVBb7DOcc/P8m/eZWVvn3F4zawsUBhpS5HTyisp44h+beHfDPtKTE/jjbf24uk9bTRsgjVYgV8sYMAnY6Jz7/XFfehMYDTzh//hGQAlFvsb+I5U8u3Ar0xfvIC66Cf91eTfGfaMj8TFRXkcT8VQgR+7DgDuAtWa2yr/tYWpLfY6ZjQN2ADcHFlHk3x2trGHyZ1/ywkfbOFJZza2DMrnvkq4aVxfxC+RqmU+BU/2f9+K6vq7I16mu8TF3+S6efn8L+w5VcMl5aTwwvBtd0pK8jibSoOgOVQkLzjn+sa6ApxZsJq/4CP0yk/nTd/ozMKuV19FEGiSVuzRozjk+2lLE797dzLrdh+hyTjMm3jGAS3uk6WSpyNdQuUuD9fm2Yn7/7hZydhwgo2UCT93Ul+v6pWseGJEzoHKXBmdxXglPv7eFJV/uJ615HI+P7MXN2e2JjdadpSJnSuUuDYJzjsV5+3l24Va+yCshNSmOR67pwW2DMnVZo0gdqNzFU845Ps0t5o8Lc1m6fT+pSXH8/KrzGDWkg0pdJAAqd/GEz+d4f+M+nvswl9W7DtKmeTy/uLYntwxsr1IXCQKVu9Srqhofb67aw18+2caWfWVktkrk19f35vr+6cRFq9RFgkXlLvWirKKaV5flM2lRHnsOHqNbWhJ/uOV8ru7TlmhNwSsSdCp3Cal9h47x8mfbmbFkB4ePVTMoqxW/vK43F3VL1XXqIiGkcpeQWLvrIJM+zWP+mr34nOOKXm0Z/82O9Mts6XU0kUZB5S5BU1XjY8H6AqZ+vp1l2w/QLC6aO4dmMeaCLDJTEr2OJ9KoqNwlYEWHK5i9dCczluyk4NAx2rdK4OdXncctA9uTFB/jdTyRRknlLnXinGPZ9gO8sngH76zbS1WN45tdWvP4yF58q/s5miJAxGMqdzkrpeWVvL5iN7OW7iS3sIyk+GjuGJLF7UMyOTe1mdfxRMRP5S6n5fM5vsgr4dVl+byzvoDKah/nt0/myRv6cHXftiTG6sdIpKHR30o5pfz95cxbsZu5K/LJ33+U5vHR3DqwPbcOzKRHu+ZexxORr6Fyl39x+FgV/1hbwLyVu1ictx8zGNophfsv68blPdtoagCRMKFyFyqqa/hkSzFvrNrNexv2UVHtIyslkZ9e2pXr+qeT0VKXMYqEG5V7I1Vd42Nx3n7eWr2Hf6zby6Fj1bRMjOGWge25rl8657dP1h2kImFM5d6IVNX4WJxXwttr97Jg/T72H6mkaWwUl/dswzXnt+MbnVsTo3leRCKCyj3ClVdWs2hrMQvWF/D+hn0cOlZNYmwUl5yXxpW923JRt1SNo4tEIJV7BNp36Bgfbirk/Y37WLS1mIpqH83jo7mkRxrDe7bhwq4qdJFIp3KPADU+x6r8Uj7eXMgHmwtZt/sQAOnJCdw2KJNLe6QxqGMrDbmINCIq9zCVv7+cz3KLWZRbzKdbizl4tIomBv0yW/Jfl3fj4vPOoVtakk6KijRSKvcwUXj4GF9sK2FxXglfbCthe0k5AGnN47i0RxoXdUvlG51bk5wY63FSEWkIVO4NkHOO/P1Hydmxn6Vf1v7KKz4CQFJcNIM7teLOoVl8s0trOp/TTEfnIvJvVO4NwNHKGtbuPsiq/AOs3FlKzo4DFB2uACApPppBWa24ZWB7hp6bQs92LTTjooiclsq9nh2trGFjwSHW7znE2l2lrNl1kK2FZdT4HADtWyUw7NwUBmS1YkBmS7q1SVKZi8hZU7mHiM/n2F16lM0Fh9m87zCbCg6zce8h8orK8Pc4LRNj6J2RzCXnpXF++2TOz0ymdbM4b4OLSERQuQfo4NEqdpaU82XJEfKKysgrOsK2ojK2FZVxrMr31fMyWibQvU0SV/ZuS892zenZrjnpyQkaLxeRkAhJuZvZcOAZIAp4yTn3RCj2E2o1PkfJkQr2Haxgz8GjFBw8xp7So+w6cJT8A+Xs3F9OaXnVV883g3YtEuiU2pQhnTrQ5ZxmdElrRte0JC03JyL1KujlbmZRwHPApcAuYJmZvemc2xDsfZ2pqhof5RU1lFdVc6SihsPHqjh8rJrDx6opPVpJaXkVB45Usr+8kpKySkqOVFB4qIKSI5VfjYX/U2x0EzKSE0hvmcCVvdvSoVUiHVKaktU6kayUprrzU0QahFAcuQ8Ccp1zeQBmNhsYAQS93Ocsy2fiojx8zuFc7ZF2dY2Pap+jqsZHRXXtrxML+mTiY5qQ0jSOlGaxtG4WR4+2zTknKZ5zmsfRpnk8bVsk0DY5nlaJsTTRCU4RaeBCUe7pQP5xn+8CBp/4JDObAEwAyMzMrNOOkhNj/HdhQhMzmhhERzUhuokRHWXER0cRF9OE+OgoEmKjaBoXTWJsFEnx0TSPjyEpPobkxBhaJMToiFtEIopnJ1SdcxOBiQDZ2dmnP7Q+ict6tuGynm2CmktEJBKEYiap3UD74z7P8G8TEZF6EopyXwZ0MbOOZhYL3Aq8GYL9iIjIKQR9WMY5V21mdwMLqL0UcrJzbn2w9yMiIqcWkjF359zbwNuheG0RETk9rd4gIhKBVO4iIhFI5S4iEoFU7iIiEcicq9P9Q8ENYVYE7Kjjt7cGioMYJxzoPTcOes+NQyDvuYNzLvVkX2gQ5R4IM8txzmV7naM+6T03DnrPjUOo3rOGZUREIpDKXUQkAkVCuU/0OoAH9J4bB73nxiEk7znsx9xFROTfRcKRu4iInEDlLiISgcK63M1suJltNrNcM3vQ6zyhZmbtzexDM9tgZuvN7F6vM9UHM4sys5VmNt/rLPXBzJLNbK6ZbTKzjWY21OtMoWZm9/l/pteZ2Swzi/c6U7CZ2WQzKzSzdcdta2Vm75nZVv/HlsHaX9iW+3ELcV8B9ABuM7Me3qYKuWrgp865HsAQ4IeN4D0D3Ats9DpEPXoGeMc51x3oS4S/dzNLB+4Bsp1zvaidKvxWb1OFxBRg+AnbHgQWOue6AAv9nwdF2JY7xy3E7ZyrBP65EHfEcs7tdc6t8D8+TO1f+nRvU4WWmWUAVwEveZ2lPphZC+BCYBKAc67SOVfqbap6EQ0kmFk0kAjs8ThP0DnnPgH2n7B5BDDV/3gqMDJY+wvncj/ZQtwRXXTHM7MsoB+wxNskIfcH4GeAz+sg9aQjUAS87B+KesnMmnodKpScc7uBp4CdwF7goHPuXW9T1Zs059xe/+MCIC1YLxzO5d5omVkz4HXgx865Q17nCRUzuxoodM4t9zpLPYoG+gPPO+f6AUcI4n/VGyL/OPMIav9hawc0NbNR3qaqf672uvSgXZsezuXeKBfiNrMYaot9hnNuntd5QmwYcK2Zbad22O3bZjbd20ghtwvY5Zz75//I5lJb9pHsEuBL51yRc64KmAdc4HGm+rLPzNoC+D8WBuuFw7ncG91C3GZm1I7FbnTO/d7rPKHmnHvIOZfhnMui9s/3A+dcRB/ROecKgHwz6+bfdDGwwcNI9WEnMMTMEv0/4xcT4SeRj/MmMNr/eDTwRrBeOCRrqNaHRroQ9zDgDmCtma3yb3vYv2atRI4fATP8By15wFiP84SUc26Jmc0FVlB7RdhKInAaAjObBVwEtDazXcAjwBPAHDMbR+205zcHbX+afgcb+dMAAAAzSURBVEBEJPKE87CMiIicgspdRCQCqdxFRCKQyl1EJAKp3EVEIpDKXUQkAqncRUQi0P8D/kkVdzalkcwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the data and create a line plot\n",
    "fig, ax = plt.subplots()\n",
    "ax.plot(x, x**2);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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": [
    "# Use same data to make a scatter\n",
    "fig, ax = plt.subplots()\n",
    "ax.scatter(x, np.exp(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": [
    "# Another scatter plot\n",
    "fig, ax = plt.subplots()\n",
    "ax.scatter(x, np.sin(x));"
   ]
  },
  {
   "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": [
    "# Make a Bar plot from dictionary\n",
    "nut_butter_prices = {\"Almond butter\": 10,\n",
    "                     \"Peanut butter\": 8,\n",
    "                     \"Cashew butter\": 12}\n",
    "fig, ax = plt.subplots()\n",
    "ax.bar(nut_butter_prices.keys(), nut_butter_prices.values())\n",
    "ax.set(title=\"Dan's Nut Butter Store\", ylabel=\"Price ($)\");"
   ]
  },
  {
   "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 a horizontal bar plot\n",
    "fig, ax = plt.subplots()\n",
    "ax.barh(list(nut_butter_prices.keys()), list(nut_butter_prices.values()));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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 a Histogram plot\n",
    "x = np.random.randn(1000) # Make some data from a normal distribution\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "ax.hist(x);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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 = np.random.random(1000) # random data from random distribution\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "ax.hist(x);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Two options for subplots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "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: Create multiple subplots\n",
    "fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(nrows=2, \n",
    "                                             ncols=2, \n",
    "                                             figsize=(10, 5))\n",
    "\n",
    "# Plot data to each different 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.randn(1000));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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lxWf+6ED6bdIjo6zMzErXOO7KZxdasVxkWVmsXruOnc+Zwvtr1uXFZ//kYDbbaIOMsjIzK6+jhvd3UWVFK6nIkjQSuJjklhRXRMSFzeafDnwLWAMsA74ZEc+Vsk6rLatWr2XHn9z+ofjccw+hV4/uGWRkZmZWG9pdZEnqClwKHExyp/oHJU2KiMdzms0GGiLiXUknAb8Aji4lYasNb61azS7n3vGh+BPnj6RH964ZZGRmZlZbSunJ2hNYGBHPAEi6HhgFNBVZETEtp/0M4KslrM9qwOvvvM/u50/Ni/Xo3oW55x5K965dMsrKzMys9pRSZPUHXsiZXgzstZ72JwD/KGF9lqHl777Pwb+ezrK33muKbbVpD+794Wfp2kUZZmZmZlabqjLwXdJXgQZg//W0GQOMARg4cGA10rIiLHvrPQ67+B5effuD4mrnrTfh76fui+TiyszMrCWlFFlLgAE509uksTySDgLOAvaPiPeaz28UEROACQANDQ1RQl5WBi8uX8mBv7o773owpx+8A/994OAMszIzM6sfpRRZDwKDJW1HUlyNBo7NbSBpOPA7YGRELC1hXVYli159hxG/vCsv9uMjPsG39vtYNgmZVVBrZ0jntPsCcBOwR0TMqmKKZlbH2l1kRcQaSacAU0h2UBMjYp6k84BZETEJGA9sDPw5PbT0fEQcWYa8rcyefOUtDvn19LzYhf+5C6P39KFb65iKPEMaSb2A04CZ1c/SzOpZSWOyImIyMLlZ7OycxweVsnyrvLmLV/Afl9ybF7t49DBGDfPF9qzDa/UM6dT5wM+BsdVNz8zqna/43kk9uOh1vnT5/Xmx33+9gYN36pdRRmZV1+oZ0pJ2BwZExG2SXGSZWZu4yOpkpj+5jK9PfCAv9qcT9mLfwX0yysisNknqAlwEHF9EW58dbWYf4iKrk5gy72W+88eH8mI3nfgpGgZtnlFGZplr7QzpXsBQ4K50TOmWwCRJRzYf/O6zo82sEBdZHdyts5fw3RseyYv9/dR9Gdp/04wyMqsZ6z1DOiJWAE1dvJLuAs7w2YVmViwXWR3UtTOf50e3zM2LTf3eZxjcr1dGGZnVliLPkDYzazcXWR3M76c/wwWT5+fF7h47gm232CijjMxqV2tnSDeLj6hGTmbWcbjI6gAigovvfIrf/POpptjGG3Zj6umfYatNe2aYmZmZWeflIquORQQX3DafK+59tinWb5MNue2/96PPxhtmmJmZmZm5yKpD69YFZ906l+se+OASP9v33YibT9qHTT/SPcPMzMzMrJGLrDqyZu06vnfjo/zt0RebYrtusynXfntvNt7Qb6WZmVkt8X/mOvDemrWc+MeHmLZgWVPs09tvwcTj96BH964ZZmZmZmYtcZFVw1a+v5bjJj7AA4teb4odvFM/Lj12dzbo1iXDzMzMzKw1LrJq0FurVnP072bw+EtvNsU+P7w/v/zSbnTtogwzMzMz61hunb2E8VMW8OLylWzduydjDx3CUcP7l2XZLrJqyBvvvM+oS+/j+dffbYp9de+BnHfkULq4uDIzMyurW2cvYdzNc1m5ei0AS5avZNzNyYW8y1FolVRkSRoJXExyteQrIuLCZvM/A/wG2BUYHRE3lbK+jmrpW6s47Df38No77zfFTtx/e344cgjpPdPMzMyszMZPWdBUYDVauXot46csyLbIktQVuBQ4GFgMPChpUkQ8ntPseZI72J9RSpId1ZLlK/nsL+/ivTXrmmLfP3gHTj1wcIZZmZmZdQ4vLl/ZpnhbldKTtSewMCKeAZB0PTAKaCqyImJROm9doQV0Vs+++g4H/PKuvNjZn9uJb+67XTYJmZm1opLjVsyysnXvniwpUFBt3bs8d0sppcjqD7yQM70Y2Ku9C5M0BhgDMHDgwBLSql0LXn6LQ38zPS/28y/swtF7dMzXa2YdQ6XHrZhlZeyhQ/I+2wA9u3dl7KFDyrL8mhn4HhETgAkADQ0NkXE6ZfXoC8sZdel9ebHfHjOcI3fbOqOMzMyKV+lxK2ZZafz81uLZhUuAATnT26QxSz3w7Ot8+Xf358Wu+HoDB+3UL6OMzMzartLjVsyydNTw/hX7slBKkfUgMFjSdiTF1Wjg2LJkVefufnIZx018IC92zbf2Yp+P98koIzOrZbU+3qnS41asdLX+Geqs2l1kRcQaSacAU0gu4TAxIuZJOg+YFRGTJO0B3AJsBvyHpJ9GxM5lybwG3f7Yy5z4p4fyYn856VN8ctvNM8rIzGpdPYx3qvS4FStNPXyGOquSxmRFxGRgcrPY2TmPHyQ5jNih3TJ7Md+74dG82N9P3Zeh/TfNKCMzK0YR1/o7HfgWsAZYBnwzIp4rZw71MN6p0uNWrDT18BnqrGpm4Hs9+tOM5/jxrY/lxf55+mf4+Ed7ZZSRmRWryGv9zQYaIuJdSScBvwCOLmce9TLeqZLjVqw09fIZ6oxcZLXDhOlP87PJTzRNS3D3GQcwcIuPZJiVmbVRMdf6m5bTfgbw1XIn4fFOVip/hmpXl6wTqBcRwUVTn2TQmbc1FVi9enTj/nGf5dn/OcIFlln9KXStv/V11ZwA/KPcSYw9dAg9u3fNi3m8k7WFP0O1yz1ZrYgIzv/7fCbe92xTbKtNe/C3U/elz8YbZpiZmVWLpK8CDcD+Lcxv98WUa3G8k89Uqy+1+BmyhIusFqxbF4y7eS43zPrgi+7HP7oxfznx02z6ke4ZZmZmZVLUtf4kHQScBewfEe8VWlCpF1OupfFOPlOtPtXSZ8g+4CKrmTVr13HaDY9w25yXmmK7DejNtd/ai4029OYy60BavdafpOHA74CREbG0+ilWn89UMysfVw2p99as5Tt/fIi7Fixriu3z8S248rg96NHsWLeZ1b9irvUHjAc2Bv4sCeD5iDgys6SrwGeqmZVPpy+y3n1/DV+/8gFmPfdGU+yQnfpxybG7s0E3nxdg1pEVca2/g6qeVMZ8pppZ+XTaIuutVav50uX388TLbzXF/nP3/oz/4m507aIMMzMzy46v7m5WPp2uyHrjnfc58tJ7eeH1D76pfW3vbfnpkTvTxcWVmXVyPlOtc/OZpeXVaYqspW+uYuTF9/D6O+83xU4asT0/OHQI6VgLMzPDZ6p1Vj6ztPw6fJG1+I13+eyv7ub9NeuaYmccsgOnfHZwhlmZmVk964g9Pj6ztPw6bJH17KvvcMAv78qLnfMfO/GNfbbLJiEzM+sQOmqPj88sLb+Siqwi7mC/IfAH4JPAa8DREbGolHW25omX32Tkb+7Ji/3iC7vy5T0GtPAMMzOz4nXUHh+fWVp+7S6yiryD/QnAGxHxcUmjgZ9T5jvYN3rkheUcdel9ebFLjh3O53bduhKrMzOzTqqj9vj4zNLyK6Unq9U72KfT56aPbwIukaSIaPNtJ1oy85nXOHrCjLzYlcc1cOAn+pVrFWZmZk06ao+Pzywtv1KKrEJ3sN+rpTbp1ZVXAFsAr5aw3iZfn/gA05/84Art135rLz798T7lWLSZmVlBHbnHx2eWllfNDHxvz13shw3ozfQnl/GXkz7NJ7fdrJLpmZmZAe7xseKVUmQVcwf7xjaLJXUDNiUZAP8h7bmL/ekH78DpB+/QxrTNzMxK4x4fK0YpN+druoO9pA1I7mA/qVmbScBx6eMvAv8q53gsMzMzs1rV7p6sIu9gfyXwR0kLgddJCjEzMzOzDq+kMVlF3MF+FfClUtZhZmZmVo9KOVxoZmZmZi1QLQ6RkrQMeK7I5n0o0yUhqqxe84b6zd15V1+xuW8bEX0rnUw1tHH/Vcvq+XPXEr+m+lCPr6ngPqwmi6y2kDQrIhqyzqOt6jVvqN/cnXf11XPunV1HfO/8mupDR3pNPlxoZmZmVgEusszMzMwqoCMUWROyTqCd6jVvqN/cnXf11XPunV1HfO/8mupDh3lNdT8my8zMzKwWdYSeLDMzM7OaUzdFlqSRkhZIWijpzALzN5R0Qzp/pqRB1c/yw4rI+3RJj0uaI+lOSdtmkWdzreWd0+4LkkJSzZwJUkzukr6cbvd5kq6tdo6FFPFZGShpmqTZ6efl8CzybE7SRElLJT3WwnxJ+m36uuZI2r3aOVph9bp/ak09779aUq/7tfWp131em0REzf+Q3LbnaeBjwAbAo8BOzdr8F3B5+ng0cEOd5H0A8JH08Un1knfarhcwHZgBNGSddxu2+WBgNrBZOv3ROsl7AnBS+ngnYFHWeae5fAbYHXishfmHA/8ABOwNzMw6Z//U7/6pHK8rbVdz+68S36ua26+V4TXV5D6vLT/10pO1J7AwIp6JiPeB64FRzdqMAq5OH98EHChJVcyxkFbzjohpEfFuOjkD2KbKORZSzPYGOB/4ObCqmsm1opjcvw1cGhFvAETE0irnWEgxeQewSfp4U+DFKubXooiYTnJv0paMAv4QiRlAb0lbVSc7W4963T+1pp73Xy2p1/3a+tTtPq8t6qXI6g+8kDO9OI0VbBMRa4AVwBZVya5lxeSd6wSSb/xZazXv9JDPgIi4rZqJFaGYbb4DsIOk+yTNkDSyatm1rJi8zwW+KmkxyT1DT61OaiVr69+BVUe97p9aU8/7r5bU635tfTryPq9JSTeItvKR9FWgAdg/61xaI6kLcBFwfMaptFc3kq71ESTfzKdL2iUilmeaVeuOAa6KiF9J+hTwR0lDI2Jd1olZx1ZP+6fWdID9V0vqdb+2PnW/z6uXnqwlwICc6W3SWME2krqRdC2+VpXsWlZM3kg6CDgLODIi3qtSbuvTWt69gKHAXZIWkYyzmVQjg0eL2eaLgUkRsToingWeJNk5ZamYvE8AbgSIiPuBHiT3+Kp1Rf0dWNXV6/6pNfW8/2pJve7X1qcj7/M+kPWgsGJ+SCr0Z4Dt+GCA3M7N2pxM/sD3G+sk7+Ekg/8GZ51vW/Ju1v4uamTgaJHbfCRwdfq4D0mX9RZ1kPc/gOPTx58gGZ+grLd5ms8gWh74fgT5A98fyDpf/9Tv/qkcr6tZ+5rZf5X4XtXcfq0Mr6lm93lFv86sE2jDG3I4SWX+NHBWGjuP5NsVJBXun4GFwAPAx7LOuci8/wm8AjyS/kzKOudi8m7WtqZ2UkVsc5EcLngcmAuMzjrnIvPeCbgv3Rk9AhySdc5pXtcBLwGrSb5NnwCcCJyYs70vTV/X3Fr6rHT2n3rdP5X6upq1ran9VwnvVU3u10p8TTW5z2vLj6/4bmZmZlYB9TImy8zMzKyuuMgyMzMzqwAXWWZmZmYV4CLLzMzMrAJcZJmZmZlVQKtFlqSJkpZKeiwnNl7SE+ldsW+R1LuF5y6SNFfSI5JmlTNxMzMzs1pWTE/WVSQXOcs1FRgaEbuSXONi3Hqef0BEDIuIWr6arpmZmVlZtVpkRcR04PVmsTsiuQkz1M+d2c3MzMyqphw3iP4mcEML8wK4Q1IAv4uICcUssE+fPjFo0KAypGZm9eChhx56NSL6Zp1HOXj/Zdb5tLQPK6nIknQWsAa4poUm+0bEEkkfBaZKeiLtGSu0rDHAGICBAwcya5aHcJl1FpKeyzqHchk0aJD3X2adTEv7sHafXSjpeOBzwFeihXvzRMSS9PdS4BZgz5aWFxETIqIhIhr69u0QX2jNzMysE2tXkSVpJPADkps4vttCm40k9Wp8DBwCPFaorZlZNUgaIGmapMclzZN0Who/V9KS9EzoRyQdnvOccZIWSlog6dDssjezetPq4UJJ1wEjgD6SFgPnkJxNuCHJIUCAGRFxoqStgSsi4nCgH3BLOr8bcG1E3F6RV2FmVpw1wPcj4uH0S+BDkqam834dEb/MbSxpJ2A0sDOwNfBPSTtExNqqZm1mdanVIisijikQvrKFti8Ch6ePnwF2Kyk7M7MyioiXgJfSx29Jmg/0X89TRgHXR8R7wLOSFpIMe7i/4smaWd0rx9mFZpZj0Jm3ZZ1CTVh04RFZp7BekgYBw4GZwD7AKZK+Dswi6e16g6QAm5HztMWsvyizGlfJv89a/8xb9fm2OmbW6UjaGPgL8N2IeBO4DNgeGEbS0/WrNi5vjKRZkmYtW7as7PmaWX1yT5aZdSqSupMUWNdExM0AEfFKzvzfA39PJ5cAA3Kevk0ay5NeA/CxqCYAABVySURBVHACQENDQ8Gzra3jcy+ZNeeeLDPrNJSciXMlMD8iLsqJb5XT7PN8cCb0JGC0pA0lbQcMBh6oVr5mVt/ck2Vmnck+wNeAuZIeSWM/Ao6RNIzkLhWLgO8ARMQ8STcCj5OcmXiyzyw0s2K5yDKzTiMi7gVUYNbk9TznAuCCiiVlZh2WDxeamZmZVYCLLDMzM7MKcJFlZmZmVgEusszMzMwqwEWWmZmZWQW4yDIzMzOrABdZZmZmZhXgIsvMzMysAlxkmZmZmVWAiywzMzOzCiiqyJI0UdJSSY/lxDaXNFXSU+nvzVp47nFpm6ckHVeuxM3MzMxqWbE9WVcBI5vFzgTujIjBwJ3pdB5JmwPnAHsBewLntFSMmZmZmXUkRRVZETEdeL1ZeBRwdfr4auCoAk89FJgaEa9HxBvAVD5crJmZmZl1OKWMyeoXES+lj18G+hVo0x94IWd6cRozMzMz69C6lWMhERGSopRlSBoDjAEYOHBg0c8bdOZtpay2w1h04RFZp2BmZmY5SunJekXSVgDp76UF2iwBBuRMb5PGPiQiJkREQ0Q09O3bt4S0zMwKkzRA0jRJj0uaJ+m0NF7wRB4lfitpoaQ5knbP9hWYWT0ppciaBDSeLXgc8NcCbaYAh0jaLN1pHZLGzMyysAb4fkTsBOwNnCxpJ1o+kecwYHD6Mwa4rPopm1m9KvYSDtcB9wNDJC2WdAJwIXCwpKeAg9JpJDVIugIgIl4HzgceTH/OS2NmZlUXES9FxMPp47eA+STjRFs6kWcU8IdIzAB6N/bgm5m1pqgxWRFxTAuzDizQdhbwrZzpicDEdmVnZlYhkgYBw4GZtHwiT0sn77yUE2v3mFIz69h8xXcz63QkbQz8BfhuRLyZOy8iAmjTiTweU2pmhbjIMrNORVJ3kgLrmoi4OQ23dCJP0SfvmJk15yLLzDoNSQKuBOZHxEU5s1o6kWcS8PX0LMO9gRU5hxXNzNarLNfJMjOrE/sAXwPmSnokjf2I5MSdG9OTep4DvpzOmwwcDiwE3gW+Ud10zayeucgys04jIu4F1MLsQifyBHByRZMysw7LhwvNzMzMKsBFlpmZmVkFuMgyMzMzqwAXWWZmZmYV4CLLzMzMrAJ8dqGZmdWUQWfelnUKZmXhniwzMzOzCnCRZWZmZlYBLrLMzMzMKsBjsgzwGIhGiy48IusUzMysg2h3T5akIZIeyfl5U9J3m7UZIWlFTpuzS0/ZzMzMrPa1uycrIhYAwwAkdQWWALcUaHpPRHyuvesxMzMzq0flGpN1IPB0RDxXpuWZmZmZ1bVyFVmjgetamPcpSY9K+oekncu0PjMzM7OaVnKRJWkD4EjgzwVmPwxsGxG7Af8L3Lqe5YyRNEvSrGXLlpWalpnZh0iaKGmppMdyYudKWpIzdvTwnHnjJC2UtEDSodlkbWb1qhw9WYcBD0fEK81nRMSbEfF2+ngy0F1Sn0ILiYgJEdEQEQ19+/YtQ1pmZh9yFTCyQPzXETEs/ZkMIGknkl76ndPn/F86/tTMrCjlKLKOoYVDhZK2lKT08Z7p+l4rwzrNzNosIqYDrxfZfBRwfUS8FxHPAguBPSuWnJl1OCUVWZI2Ag4Gbs6JnSjpxHTyi8Bjkh4FfguMjogoZZ1mZhVwiqQ56eHEzdJYf+CFnDaL05iZWVFKKrIi4p2I2CIiVuTELo+Iy9PHl0TEzhGxW0TsHRH/LjVhM7MyuwzYnuSSNC8Bv2rrAjym1MwK8W11zKxTi4hXImJtRKwDfs8HhwSXAANymm6Txgotw2NKzexDXGSZWacmaaucyc8DjWceTgJGS9pQ0nbAYOCBaudnZvXL9y40s05D0nXACKCPpMXAOcAIScOAABYB3wGIiHmSbgQeB9YAJ0fE2izyNrP65CLLzDqNiDimQPjK9bS/ALigchmZWUfmw4VmZmZmFeAiy8zMzKwCfLjQzMysxg0687aKLXvRhUdUbNmdnXuyzMzMzCrARZaZmZlZBbjIMjMzM6sAF1lmZmZmFeAiy8zMzKwCXGSZmZmZVYCLLDMzM7MKcJFlZmZmVgEusszMzMwqoOQiS9IiSXMlPSJpVoH5kvRbSQslzZG0e6nrNDMzM6t15bqtzgER8WoL8w4DBqc/ewGXpb/NzMzMOqxqHC4cBfwhEjOA3pK2qsJ6zczySJooaamkx3Jim0uaKump9Pdmady98GZWknIUWQHcIekhSWMKzO8PvJAzvTiNmZlV21XAyGaxM4E7I2IwcGc6Dfm98GNIeuHNzIpWjiJr34jYnWSHdLKkz7RnIZLGSJoladayZcvKkJaZWb6ImA683iw8Crg6fXw1cFRO3L3wZtZuJRdZEbEk/b0UuAXYs1mTJcCAnOlt0ljz5UyIiIaIaOjbt2+paZmZFatfRLyUPn4Z6Jc+di+8mZWkpCJL0kaSejU+Bg4BHmvWbBLw9XR8w97AipwdmplZzYiIIBkC0SbuiTezQko9u7AfcIukxmVdGxG3SzoRICIuByYDhwMLgXeBb5S4TjOzcnpF0lYR8VJ6OHBpGi+qFx6SnnhgAkBDQ0ObizQz65hKKrIi4hlgtwLxy3MeB3ByKesxM6ugScBxwIXp77/mxE+RdD3JZWfcC29mbVKu62SZmdU8SdcBI4A+khYD55AUVzdKOgF4Dvhy2ty98GZWEhdZZtZpRMQxLcw6sEBb98KbWUl870IzMzOzCnCRZWZmZlYBLrLMzMzMKsBFlpmZmVkFeOC7mZm12aAzb8s6BbOa554sMzMzswpwkWVmZmZWAS6yzMzMzCrARZaZmZlZBbjIMjMzM6sAF1lmZmZmFeAiy8zMzKwCXGSZmZmZVUC7iyxJAyRNk/S4pHmSTivQZoSkFZIeSX/OLi1dMzMzs/pQyhXf1wDfj4iHJfUCHpI0NSIeb9bunoj4XAnrMTMzM6s77S6yIuIl4KX08VuS5gP9geZFlplZzZO0CHgLWAusiYgGSZsDNwCDgEXAlyPijaxyNLP6UpYxWZIGAcOBmQVmf0rSo5L+IWnncqzPzKxCDoiIYRHRkE6fCdwZEYOBO9NpM7OilHyDaEkbA38BvhsRbzab/TCwbUS8Lelw4FZgcAvLGQOMARg4cGCpaZmZlcMoYET6+GrgLuCHWSVjVgmVvNn3oguPqNiy60FJPVmSupMUWNdExM3N50fEmxHxdvp4MtBdUp9Cy4qICRHREBENffv2LSUtM7P2COAOSQ+lX/oA+qVDIwBeBvoVeqKkMZJmSZq1bNmyauRqZnWg3T1ZkgRcCcyPiItaaLMl8EpEhKQ9SYq619q7TjOzCto3IpZI+igwVdITuTPT/VgUemJETAAmADQ0NBRsY2adTymHC/cBvgbMlfRIGvsRMBAgIi4HvgicJGkNsBIYHRHeAZlZzYmIJenvpZJuAfYEXpG0VUS8JGkrYGmmSZpZXSnl7MJ7AbXS5hLgkvauw8ysGiRtBHRJz5TeCDgEOA+YBBwHXJj+/mt2WZpZvSl54LuZWQfQD7glGQVBN+DaiLhd0oPAjZJOAJ4DvpxhjmZWZ1xkmVmnFxHPALsViL8GHFj9jMysI/C9C83MzMwqwEWWmZmZWQW4yDIzMzOrABdZZmZmZhXgIsvMzMysAlxkmZmZmVWAiywzMzOzCnCRZWZmZlYBvhipmVkHNejM27JOwTq5Sn4GF114RMWWXS7uyTIzMzOrABdZZmZmZhXgIsvMzMysAlxkmZmZmVWAiywzMzOzCiipyJI0UtICSQslnVlg/oaSbkjnz5Q0qJT1mZlVW2v7OTOzlrT7Eg6SugKXAgcDi4EHJU2KiMdzmp0AvBERH5c0Gvg5cHQpCZuZVUuR+7l28yUWzNqvHi4PUUpP1p7Awoh4JiLeB64HRjVrMwq4On18E3CgJJWwTjOzaipmP2dmVlApRVZ/4IWc6cVprGCbiFgDrAC2KGGdZmbVVMx+zsysoJq54rukMcCYdPJtSQuyzKeN+gCvZpmAfp7l2svG27F86m1bbluhNKqiwvuvzN/LHLWSi/PI5zzylZxHO/4XFNyHlVJkLQEG5Exvk8YKtVksqRuwKfBaoYVFxARgQgn5ZEbSrIhoyDqPeuftWD7elmVTzH6uovuvWnovayUX5+E86iEPKO1w4YPAYEnbSdoAGA1MatZmEnBc+viLwL8iIkpYp5lZNRWznzMzK6jdPVkRsUbSKcAUoCswMSLmSToPmBURk4ArgT9KWgi8TrKDMjOrCy3t5zJOy8zqREljsiJiMjC5WezsnMergC+Vso46UZeHOWuQt2P5eFuWSaH9XJXV0ntZK7k4j3zOI1+t5IF89M7MzMys/HxbHTMzM7MKqOsiS9JRkkLSjjmxQZIeq3Ied0n60JkMkhZJ6tOG5QySdGzO9DBJh5crz1bWvVbSI5Iek/RnSR+p0np7S/qvFua1+b2UNELSp3Omj5K0U6l5FrHeLSVdL+lpSQ9Jmixph3Ysp02fmTYuu262p+WTdL6kOenf6B2Sts4oj/GSnkhzuUVS74zy+JKkeZLWFdr3VmH9NXGrJUkTJS2t9v+8AnkMkDRN0uPp+3JaRnn0kPSApEfTPH6aRR656rrIAo4B7k1/dwSDgGNzpocBbSqy0ktltMfKiBgWEUOB94ET27mctuoNFCyy2mkE8Omc6aOANhUFbd2G6V0MbgHuiojtI+KTwDigX1uWU6NGUOXtaQWNj4hdI2IY8Hfg7NaeUCFTgaERsSvwJMnnPAuPAf8JTK/2inNutXQYyd/CMRl+8bgKGJnRunOtAb4fETsBewMnZ7RN3gM+GxG7kfz/HClp7wzyaFK3RZakjYF9Se6PWPCsRUnHS7pV0tS0h+AUSadLmi1phqTN03bD0unGb2ebpfG7JP08rYyflLRfGu+Z9lrMl3QL0HM9qf5A0tx0GR9Pn3+VpC/m5Pl2+vBCYL/02+oPgfOAo9PpoyVtlH5zeSB9DaNyXuckSf8C7mz/Vm1yD9CY61fT9T0i6XfpDgZJl0ma1fzbQrqdfyrp4fR175jGz5V0Rk67x5TcMPxCYPt0+eML5NJN0jXptr5JaQ9bbo+PpIb0vRpEUhx+L13e/sCRwPh0evv053YlvU335OR3laTLJc0EftHG7XUAsDoiLm8MRMSjEXGPpI0l3ZmzPRrfs40k3ZZ+43pMUu49PU8tsP1aeu9vk7Rr+ni2pLPTx+dJ+nadbk9rJiLezJncCMhkMG1E3JHevQNgBsl1w7LIY35EZHXB6pq51VJETCc5cz9TEfFSRDycPn4LmE8Gd0aIROP/0+7pT6YDz+u2yCL5UN8eEU8Cr0n6ZAvthpJ849kDuAB4NyKGA/cDX0/b/AH4YfrtbC5wTs7zu0XEnsB3c+Inpcv5RBprad0AKyJiF+AS4DetvKYzgXvSHqWfk3xbvSGdvgE4i+RaY3uS/GMfL2mj9Lm7A1+MiP1bWcd6Kel1OAyYK+kTJDf03if9Br0W+Era9Kz0Ym+7Avs3/qNPvRoRuwOXAWewfmcCT6evcWyB+UOA/0u39Zusp9crIhYBlwO/Tpd3N8k1jcam00+TnHVyatrbdAbwfzmL2Ab4dESc3krOzQ0FHmph3irg8+n2OAD4lSSRfPt8MSJ2S3sPb895TqHt19J7fw9JYb4pybfJfdL2+1H4W349bE8rQNIFkl4g+RvMqicr1zeBf2SdRAZ8q6X1SL+cDQdmZrT+rpIeAZYCUyMikzwa1XORdQzJNwjS3y0dMpwWEW9FxDKSeyf+LY3PBQal/5x6p/9AILmh9Wdynn9z+vshksN5pPP/BBARc4A568nzupzfn2rlNbXmEODM9AN0F9ADGJjOmxoRpXyj6ZkudxbwPMk1zg4kKSAfTOcdCHwsbf9lSQ8Ds4GdyT+EVGibtdcLEXFf+vhPJL2X7aKk9/PTwJ/T1/M7YKucJn+OiLXtzrSF1QI/kzQH+CfJzrgfyefvYCU9pftFxIqc5xTafi299/eQfB73AW4DNk57p7Zr4Zt+vW/PDkvSP9NezeY/owAi4qyIGABcA5ySVR5pm7NIivprsszDaku6T/gL8N1mva9VExFr006BbYA9JQ3NIo9GdTlWQslhvs8Cu0gKkosEhqRCPSHv5TxelzO9juJef2P7tUW2by4KPF5DWuBK6gJsUOSyBHyh+T9PSXsB77Qjt1wr0w9m7nIFXB0R45rFtyPptdgjIt6QdBXJP/1GhbZZ02tO5bZfn+ZdvR/ahm1YVhdgefPXmaO923AeyR0NCvkK0Bf4ZESslrQI6BERT0ranWTM3f+TdGdEnJc+p9D2a+m93wBoAJ4hGS/TB/g2Lfes1cP27JQi4qAim15Dct2uc1prWIk8JB0PfA44sJJ38GjD9qi2om611NlI6k5SYF0TETe31r7SImK5pGkkRw0yOzGgXnuyvgj8MSK2jYhB6be7Z0kOkbRJ2oPwhtLxVsDXgLvX8xRIDsMcC5BWybuup+3ROb/vTx8v4oNDjEeSHDcGeAvolfPc5tNTSMbrKF338FbyLNWdwBclfTRd3+aStgU2IfkHukJSP5LDi61ZRHJIk7S42C6NN3+NzQ2U1NgDeCzJiQ6Ny2vchl/Iad/iNky/WT0r6UtpHpK0WxG5t+ZfwIZKbhJMuuxd08/UpsDStMA6gPQmokrODns3Iv4EjCfdNutR8L1Px4S8QHLR3/tJerbOoOUBwfWwPa0ZSYNzJkcBT2SUx0jgB8CREfFuFjnUAN9qqZl0v3QlMD8iLsowj75Kz3iV1BM4mIz+VhrVa5F1DMnZXLn+QvvPMjyOZIzLHJIzEs5rpf1lJIdl5qdtW+o1ANgsXe5pwPfS2O9JxjE9SnIIsfEb/xxgrZLB0N8DpgE7pYOMjwbOJynI5kial05XTEQ8DvwYuCN9DVOBrSLiUZLDhE8A1wL3tbyUJn8BNk/zPoXkzCQi4jXgvvQwQKGB7wtIzlSZD2xGsu0BfgpcLGkWSY9Po78Bn0+32X4kh5LHKhkUvj1Jz9IJ6bafRxkGrKbf5j8PHKTkEg7zgP8BXibpdWiQNJdkDGDjH/wuwAPpYbZzgP/XymrW997fQ1LIrUwfb5P+LqTmt6cVdGH6NzKH5NBxJqfIk4wt7QVMTT8Tl7f2hEqQ9HlJi0n2n7dJmlKtdacD/xtvtTQfuDGrWy1Juo7ky9UQSYslnZBFHiTDFb4GfDb9XDyiKl1+qJmtgGnp38mDJMNo/p5BHk18xXczMzOzCqjXniwzMzOzmuYiy8zMzKwCXGSZmZmZVYCLLDMzM7MKcJFlZmZmVgEusszMzMwqwEWWmZmZWQW4yDIzMzOrgP8fH/5zstKu/0UAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x360 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Subplots Option 2: Create multiple subplots\n",
    "fig, ax = plt.subplots(nrows=2, ncols=2, figsize=(10, 5))\n",
    "\n",
    "# Plot to each different 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.randn(1000));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting From Pandas DataFrames"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2020-01-01   -1.332356\n",
       "2020-01-02   -0.287589\n",
       "2020-01-03    1.431161\n",
       "2020-01-04   -0.908645\n",
       "2020-01-05   -0.482421\n",
       "                ...   \n",
       "2022-09-22   -0.115854\n",
       "2022-09-23   -0.087526\n",
       "2022-09-24    1.717662\n",
       "2022-09-25   -0.001745\n",
       "2022-09-26   -1.264427\n",
       "Freq: D, Length: 1000, dtype: float64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Start with some dummy data\n",
    "ts = pd.Series(np.random.randn(1000),\n",
    "               index=pd.date_range('1/1/2020', periods=1000))\n",
    "ts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2020-01-01    -1.332356\n",
       "2020-01-02    -1.619945\n",
       "2020-01-03    -0.188784\n",
       "2020-01-04    -1.097428\n",
       "2020-01-05    -1.579850\n",
       "                ...    \n",
       "2022-09-22    19.880561\n",
       "2022-09-23    19.793035\n",
       "2022-09-24    21.510696\n",
       "2022-09-25    21.508951\n",
       "2022-09-26    20.244524\n",
       "Freq: D, Length: 1000, dtype: float64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# What does cumsum() do?\n",
    "ts.cumsum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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": [
    "ts.cumsum().plot();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "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": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Make a dataframe\n",
    "car_sales = pd.read_csv(\"data/car-sales.csv\")\n",
    "car_sales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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>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": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remove price column symbols\n",
    "car_sales[\"Price\"] = car_sales[\"Price\"].str.replace('[\\$\\,\\.]', '')\n",
    "car_sales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "str"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(car_sales[\"Price\"][0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <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>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",
       "    </tr>\n",
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       "      <th>2</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>Blue</td>\n",
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       "      <td>3</td>\n",
       "      <td>7000</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",
       "    </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",
       "    </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",
       "    </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",
       "    </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": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remove last two zeros from price\n",
    "#  4    0   0   0   0   0\n",
    "# [-6][-5][-4][-3][-2][-1]\n",
    "car_sales[\"Price\"] = car_sales[\"Price\"].str[:-2]\n",
    "car_sales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "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",
       "    </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>2020-01-01</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>2020-01-02</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>2020-01-03</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>2020-01-04</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>2020-01-05</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>2020-01-06</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>2020-01-07</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>2020-01-08</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>2020-01-09</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>2020-01-10</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 2020-01-01\n",
       "1   Honda    Red          87899      4   5000 2020-01-02\n",
       "2  Toyota   Blue          32549      3   7000 2020-01-03\n",
       "3     BMW  Black          11179      5  22000 2020-01-04\n",
       "4  Nissan  White         213095      4   3500 2020-01-05\n",
       "5  Toyota  Green          99213      4   4500 2020-01-06\n",
       "6   Honda   Blue          45698      4   7500 2020-01-07\n",
       "7   Honda   Blue          54738      4   7000 2020-01-08\n",
       "8  Toyota  White          60000      4   6250 2020-01-09\n",
       "9  Nissan  White          31600      4   9700 2020-01-10"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_sales[\"Sale Date\"] = pd.date_range(\"1/1/2020\", periods=len(car_sales))\n",
    "car_sales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "str"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(car_sales[\"Price\"][0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</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",
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       "  <tbody>\n",
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       "      <td>Toyota</td>\n",
       "      <td>White</td>\n",
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       "      <td>4000</td>\n",
       "      <td>2020-01-01</td>\n",
       "      <td>4000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Honda</td>\n",
       "      <td>Red</td>\n",
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       "      <td>4</td>\n",
       "      <td>5000</td>\n",
       "      <td>2020-01-02</td>\n",
       "      <td>9000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>Blue</td>\n",
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       "      <td>3</td>\n",
       "      <td>7000</td>\n",
       "      <td>2020-01-03</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>2020-01-04</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>2020-01-05</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>2020-01-06</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>2020-01-07</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>2020-01-08</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>2020-01-09</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>2020-01-10</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 2020-01-01         4000\n",
       "1   Honda    Red          87899      4   5000 2020-01-02         9000\n",
       "2  Toyota   Blue          32549      3   7000 2020-01-03        16000\n",
       "3     BMW  Black          11179      5  22000 2020-01-04        38000\n",
       "4  Nissan  White         213095      4   3500 2020-01-05        41500\n",
       "5  Toyota  Green          99213      4   4500 2020-01-06        46000\n",
       "6   Honda   Blue          45698      4   7500 2020-01-07        53500\n",
       "7   Honda   Blue          54738      4   7000 2020-01-08        60500\n",
       "8  Toyota  White          60000      4   6250 2020-01-09        66750\n",
       "9  Nissan  White          31600      4   9700 2020-01-10        76450"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_sales[\"Total Sales\"] = car_sales[\"Price\"].astype(int).cumsum()\n",
    "car_sales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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": [
    "car_sales.plot(x=\"Sale Date\", y=\"Total Sales\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "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": [
    "# Reassign price column to int\n",
    "car_sales[\"Price\"] = car_sales[\"Price\"].astype(int)\n",
    "\n",
    "# Plot scatter plot with price column as numeric \n",
    "car_sales.plot(x=\"Odometer (KM)\", y=\"Price\", kind=\"scatter\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.28935532, 0.50764867, 0.113841  , 0.50550045],\n",
       "       [0.33903291, 0.72671371, 0.44091028, 0.39334373],\n",
       "       [0.62549298, 0.78834493, 0.04568043, 0.72285603],\n",
       "       [0.65879685, 0.8676787 , 0.69404619, 0.72142006],\n",
       "       [0.2454816 , 0.62641846, 0.39441045, 0.96206985],\n",
       "       [0.25662021, 0.36313212, 0.68360765, 0.295223  ],\n",
       "       [0.15407443, 0.29668428, 0.69532234, 0.60155566],\n",
       "       [0.71708849, 0.49402775, 0.39226192, 0.39598317],\n",
       "       [0.36931004, 0.07770044, 0.71037479, 0.2613777 ],\n",
       "       [0.18031297, 0.4737071 , 0.48633   , 0.55564642]])"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# How aboute a bar graph?\n",
    "x = np.random.rand(10, 4)\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "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>0.289355</td>\n",
       "      <td>0.507649</td>\n",
       "      <td>0.113841</td>\n",
       "      <td>0.505500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.339033</td>\n",
       "      <td>0.726714</td>\n",
       "      <td>0.440910</td>\n",
       "      <td>0.393344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.625493</td>\n",
       "      <td>0.788345</td>\n",
       "      <td>0.045680</td>\n",
       "      <td>0.722856</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.658797</td>\n",
       "      <td>0.867679</td>\n",
       "      <td>0.694046</td>\n",
       "      <td>0.721420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.245482</td>\n",
       "      <td>0.626418</td>\n",
       "      <td>0.394410</td>\n",
       "      <td>0.962070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.256620</td>\n",
       "      <td>0.363132</td>\n",
       "      <td>0.683608</td>\n",
       "      <td>0.295223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.154074</td>\n",
       "      <td>0.296684</td>\n",
       "      <td>0.695322</td>\n",
       "      <td>0.601556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.717088</td>\n",
       "      <td>0.494028</td>\n",
       "      <td>0.392262</td>\n",
       "      <td>0.395983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.369310</td>\n",
       "      <td>0.077700</td>\n",
       "      <td>0.710375</td>\n",
       "      <td>0.261378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.180313</td>\n",
       "      <td>0.473707</td>\n",
       "      <td>0.486330</td>\n",
       "      <td>0.555646</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          a         b         c         d\n",
       "0  0.289355  0.507649  0.113841  0.505500\n",
       "1  0.339033  0.726714  0.440910  0.393344\n",
       "2  0.625493  0.788345  0.045680  0.722856\n",
       "3  0.658797  0.867679  0.694046  0.721420\n",
       "4  0.245482  0.626418  0.394410  0.962070\n",
       "5  0.256620  0.363132  0.683608  0.295223\n",
       "6  0.154074  0.296684  0.695322  0.601556\n",
       "7  0.717088  0.494028  0.392262  0.395983\n",
       "8  0.369310  0.077700  0.710375  0.261378\n",
       "9  0.180313  0.473707  0.486330  0.555646"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(x, columns=['a', 'b', 'c', 'd'])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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": [
    "df.plot.bar();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "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": [
    "# Can do the same thing with 'kind' keyword\n",
    "df.plot(kind='bar');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "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>2020-01-01</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>2020-01-02</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>2020-01-03</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>2020-01-04</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>2020-01-05</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>2020-01-06</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>2020-01-07</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>2020-01-08</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>2020-01-09</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>2020-01-10</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 2020-01-01         4000\n",
       "1   Honda    Red          87899      4   5000 2020-01-02         9000\n",
       "2  Toyota   Blue          32549      3   7000 2020-01-03        16000\n",
       "3     BMW  Black          11179      5  22000 2020-01-04        38000\n",
       "4  Nissan  White         213095      4   3500 2020-01-05        41500\n",
       "5  Toyota  Green          99213      4   4500 2020-01-06        46000\n",
       "6   Honda   Blue          45698      4   7500 2020-01-07        53500\n",
       "7   Honda   Blue          54738      4   7000 2020-01-08        60500\n",
       "8  Toyota  White          60000      4   6250 2020-01-09        66750\n",
       "9  Nissan  White          31600      4   9700 2020-01-10        76450"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_sales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "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": [
    "car_sales.plot(x='Make', y='Odometer (KM)', kind='bar');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "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": [
    "# How about Histograms?\n",
    "car_sales[\"Odometer (KM)\"].plot.hist();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "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": [
    "# bins=10 default , bin width = 25,car_sales[\"Price\"].plot.hist(bins=10);000\n",
    "car_sales[\"Odometer (KM)\"].plot(kind=\"hist\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "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": [
    "# Default number of bins is 10, bin width = 12,500\n",
    "car_sales[\"Odometer (KM)\"].plot.hist(bins=20);"
   ]
  },
  {
   "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": [
    "# Let's try with another dataset\n",
    "heart_disease = pd.read_csv(\"data/heart-disease.csv\")\n",
    "heart_disease.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "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": [
    "# Create a histogram of age\n",
    "# outliner: 3 std away\n",
    "heart_disease[\"age\"].plot.hist(bins=50);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "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": [
    "### Which one should you use? (pyplpt vs matplotlib OO method?)\n",
    "* When plotting something quickly, okay to use pyplot method\n",
    "* When plotting something more advanced, use the OO method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "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": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "over_50 = heart_disease[heart_disease[\"age\"] > 50]\n",
    "over_50.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "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",
    "# c: change colur of plot base on target value [0,1]\n",
    "over_50.plot(kind='scatter', \n",
    "             x='age', \n",
    "             y='chol', \n",
    "             c='target', \n",
    "             figsize=(10, 6));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "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', \n",
    "             x=\"age\", \n",
    "             y=\"chol\", \n",
    "             c='target', \n",
    "             ax=ax);\n",
    "ax.set_xlim([45, 100]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "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])"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "over_50.target.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 0])"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "over_50.target.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "# Make a bit more of a complicated plot\n",
    "\n",
    "# Create the plot\n",
    "fig, ax = plt.subplots(figsize=(10, 6))\n",
    "\n",
    "# Plot the data\n",
    "scatter = ax.scatter(over_50[\"age\"], \n",
    "                     over_50[\"chol\"], \n",
    "                     c=over_50[\"target\"])\n",
    "\n",
    "# Customize the plot\n",
    "ax.set(title=\"Heart Disease and Cholesterol Levels\",\n",
    "       xlabel=\"Age\",\n",
    "       ylabel=\"Cholesterol\");\n",
    "\n",
    "# Add a legend\n",
    "ax.legend(*scatter.legend_elements(), title=\"Target\");\n",
    "\n",
    "# Add a horizontal line\n",
    "ax.axhline(over_50[\"chol\"].mean(), linestyle=\"--\");"
   ]
  },
  {
   "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>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": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "over_50.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Setup plot (2 rows, 1 column)\n",
    "fig, (ax0, ax1) = plt.subplots(nrows=2, # 2 rows\n",
    "                               ncols=1, \n",
    "                               sharex=True, \n",
    "                               figsize=(10, 8))\n",
    "\n",
    "# Add data for ax0\n",
    "scatter = ax0.scatter(x=over_50[\"age\"], \n",
    "                      y=over_50[\"chol\"], \n",
    "                      c=over_50[\"target\"])\n",
    "# Customize ax0\n",
    "ax0.set(title=\"Heart Disease and Cholesterol Levels\",\n",
    "#         xlabel=\"Age\",\n",
    "        ylabel=\"Cholesterol\")\n",
    "ax0.legend(*scatter.legend_elements(), title=\"Target\")\n",
    "\n",
    "# Setup a mean line\n",
    "ax0.axhline(y=over_50[\"chol\"].mean(), \n",
    "            color='b', \n",
    "            linestyle='--', \n",
    "            label=\"Average\")\n",
    "\n",
    "# Add data for ax1\n",
    "scatter = ax1.scatter(over_50[\"age\"], \n",
    "                      over_50[\"thalach\"], \n",
    "                      c=over_50[\"target\"])\n",
    "\n",
    "# Customize ax1\n",
    "ax1.set(title=\"Heart Disease and Max Heart Rate Levels\",\n",
    "        xlabel=\"Age\",\n",
    "        ylabel=\"Max Heart Rate\")\n",
    "ax1.legend(*scatter.legend_elements(), title=\"Target\")\n",
    "\n",
    "# Setup a mean line\n",
    "ax1.axhline(y=over_50[\"thalach\"].mean(), \n",
    "            color='b', \n",
    "            linestyle='--', \n",
    "            label=\"Average\")\n",
    "\n",
    "# Title the figure\n",
    "fig.suptitle('Heart Disease Analysis', fontsize=16, fontweight='bold');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"images/anatomy-of-a-matplotlib-plot-1.png\" />"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"images/anatomy-of-a-matplotlib-plot-2.png\" />"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Customizing Matplotlib Plots and getting stylish"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['seaborn-dark',\n",
       " 'seaborn-darkgrid',\n",
       " 'seaborn-ticks',\n",
       " 'fivethirtyeight',\n",
       " 'seaborn-whitegrid',\n",
       " 'classic',\n",
       " '_classic_test',\n",
       " 'fast',\n",
       " 'seaborn-talk',\n",
       " 'seaborn-dark-palette',\n",
       " 'seaborn-bright',\n",
       " 'seaborn-pastel',\n",
       " 'grayscale',\n",
       " 'seaborn-notebook',\n",
       " 'ggplot',\n",
       " 'seaborn-colorblind',\n",
       " 'seaborn-muted',\n",
       " 'seaborn',\n",
       " 'Solarize_Light2',\n",
       " 'seaborn-paper',\n",
       " 'bmh',\n",
       " 'tableau-colorblind10',\n",
       " 'seaborn-white',\n",
       " 'dark_background',\n",
       " 'seaborn-poster',\n",
       " 'seaborn-deep']"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plt.style.available"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "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>2020-01-01</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>2020-01-02</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>2020-01-03</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>2020-01-04</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>2020-01-05</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 2020-01-01         4000\n",
       "1   Honda    Red          87899      4   5000 2020-01-02         9000\n",
       "2  Toyota   Blue          32549      3   7000 2020-01-03        16000\n",
       "3     BMW  Black          11179      5  22000 2020-01-04        38000\n",
       "4  Nissan  White         213095      4   3500 2020-01-05        41500"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_sales.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "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": [
    "# Plot before changing style\n",
    "car_sales[\"Price\"].plot();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Change the style... \n",
    "plt.style.use('seaborn-whitegrid')\n",
    "car_sales[\"Price\"].plot();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('seaborn')\n",
    "car_sales[\"Price\"].plot();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "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": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('ggplot')\n",
    "car_sales[\"Price\"].plot();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.73062617, -0.33588419, -1.40485452,  0.65796286],\n",
       "       [ 1.05458782,  1.63553221, -1.24992178,  2.00580302],\n",
       "       [-0.42690415, -0.64757609,  0.43485563, -0.84336775],\n",
       "       [ 1.07462573, -1.10143564,  2.22992981, -0.65415938],\n",
       "       [ 0.01160173,  1.74875014,  0.80706437, -0.48286591],\n",
       "       [-0.49871777, -1.10867039, -2.02061471, -1.1960317 ],\n",
       "       [ 0.00795966,  0.37570893, -0.557209  ,  0.82929428],\n",
       "       [-0.13959995, -0.94133975,  2.33271061,  1.01163635],\n",
       "       [-0.30127354,  0.18736883,  0.85110471,  0.41563922],\n",
       "       [ 0.27912911,  0.70500321,  1.93142954, -0.16130256]])"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create some 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>0.730626</td>\n",
       "      <td>-0.335884</td>\n",
       "      <td>-1.404855</td>\n",
       "      <td>0.657963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.054588</td>\n",
       "      <td>1.635532</td>\n",
       "      <td>-1.249922</td>\n",
       "      <td>2.005803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.426904</td>\n",
       "      <td>-0.647576</td>\n",
       "      <td>0.434856</td>\n",
       "      <td>-0.843368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.074626</td>\n",
       "      <td>-1.101436</td>\n",
       "      <td>2.229930</td>\n",
       "      <td>-0.654159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.011602</td>\n",
       "      <td>1.748750</td>\n",
       "      <td>0.807064</td>\n",
       "      <td>-0.482866</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>-0.498718</td>\n",
       "      <td>-1.108670</td>\n",
       "      <td>-2.020615</td>\n",
       "      <td>-1.196032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.007960</td>\n",
       "      <td>0.375709</td>\n",
       "      <td>-0.557209</td>\n",
       "      <td>0.829294</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>-0.139600</td>\n",
       "      <td>-0.941340</td>\n",
       "      <td>2.332711</td>\n",
       "      <td>1.011636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>-0.301274</td>\n",
       "      <td>0.187369</td>\n",
       "      <td>0.851105</td>\n",
       "      <td>0.415639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.279129</td>\n",
       "      <td>0.705003</td>\n",
       "      <td>1.931430</td>\n",
       "      <td>-0.161303</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          a         b         c         d\n",
       "0  0.730626 -0.335884 -1.404855  0.657963\n",
       "1  1.054588  1.635532 -1.249922  2.005803\n",
       "2 -0.426904 -0.647576  0.434856 -0.843368\n",
       "3  1.074626 -1.101436  2.229930 -0.654159\n",
       "4  0.011602  1.748750  0.807064 -0.482866\n",
       "5 -0.498718 -1.108670 -2.020615 -1.196032\n",
       "6  0.007960  0.375709 -0.557209  0.829294\n",
       "7 -0.139600 -0.941340  2.332711  1.011636\n",
       "8 -0.301274  0.187369  0.851105  0.415639\n",
       "9  0.279129  0.705003  1.931430 -0.161303"
      ]
     },
     "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": {
      "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');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "matplotlib.axes._subplots.AxesSubplot"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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DBg0k3dy7/uOPPyRJJUqUkLe3t/bs2ZNpr2vPnj2qWrVqAazhzT20kSNHatCgQfL19VWjRo0k3SzS5ORkGYZhLfCzZ89ajwrkRXp6uo4cOWK9gGjPnj0qUqSIKlWqpGrVqumLL76Qj4+P9Zfn3r17NW/ePE2cOPFfreOt1yY9PV3ff/+9Tpw4oV27dlmX88UXX2Qaz5Zy5crp6aef1syZM/XYY49lKbwLFy7cdvolS5aoVatW1vP50s2PZGVcfmpqqo4cOWLdw923b5+KFCmiBx98UPHx8bnKeSeqVaumzz//XNevX7eW+a1z99WqVcv35WW0YsUK+fj4qH79+jp06JC2b9+uLVu2WPdab91T4Nb2yfgHZW7Gz4uFCxcqNDRUAwcOtM7r1KlTql27dp7mV61aNZ06dSrTHw7Lly/XsWPHNHLkyDznRM64EO0uVK5cOQ0ePFjffPONtmzZohIlSqh48eLavHmzzpw5o127dmnAgAEyDCNXh6NdXFz0yiuvaPbs2dqyZYtiY2MVHh6eaU+mT58+mjNnjr744gudPHlSM2bM0A8//KCXX365wNazdevWevTRR3Xu3DnrsNq1a+vGjRuaN2+ezpw5o7lz52a62C4vXFxcFB4erv3792v79u2KjIxU9+7dVaRIEbVr106urq4aNmyYjhw5ot27dys8PFypqanWw6a5denSJeu/w4cPKyIiQvfcc48aN26sChUqKDU1VV988YXOnTunzZs3691335WkXL2Gt4waNUoWi0UvvPCCNm3apDNnzui3337T+++/rwEDBsjPzy/Hz0N7e3tr//79OnjwoE6cOKGpU6dq27ZtWZY/atQoHTx4UD/99JMmTZqkZ599NsuV8Pmlbdu2KlKkiIYOHaojR45o586dGjFihJo2barq1avn23KuXr2qS5cu6eLFi4qNjdXMmTO1ePFijRgxQm5ubipfvrzc3Ny0YcMGnTt3Tj/88IOGDRsm6X+vj5eXl86dO6ezZ8/mavy88Pb21o4dO3T06FHFxsbq7bff1tGjR/M8z169eumbb75RdHS0Tp06pf/3//6fIiMjVaFChTxnxO2xp32X6tKli1atWqV3331XjzzyiN5//31FRkbqs88+k7e3t9q3b69SpUrp4MGDuZpfaGioUlJSFBERoevXr+vll1/WqVOnrM9369ZNSUlJmjRpkv766y/5+fkpOjraevV6QYmIiMh0s4oqVaooPDxcH374oWbPnq2WLVuqR48embLeqWLFiqlz587q06eP0tLS1KFDB+tHyLy8vLRgwQJNmDBBzz77rIoVK6bmzZsrPDz8jpZx5coVNWvWTNLNPxJKliypwMBALViwQMWLF1e9evX05ptv6v3331dCQoKqVKmiYcOGady4cTp48GCu9yrLlCmjlStXasmSJZo1a5ZOnz4tFxcX+fv7Kzw8XJ06dZKnp2emTwbcEhYWphEjRqhbt24qUqSI9eNvM2bMyHRovU2bNgoNDZVhGOrUqZMGDRp0R9viThQrVkzz58/Xu+++qy5dusjLy0tPPfWUhgwZkq/LGTp0qKSbr025cuXk7++vuXPnqmnTppJungoZO3asZs2apVmzZun+++9X165d9emnn+rgwYN67LHH1LFjR23ZskVt2rTRli1bbI6fFyNHjtSoUaPUuXNnlSxZUk2aNFHfvn21adOmPM2vdu3aioqKUlRUlGbMmKHy5curX79+Cg0NzdP8YJuL8W+OtQBALu3YsUPdu3fX7t27Vbx4cUfHAUyJw+MAAJgEpQ0AgElweBwAAJNgTxsAAJOgtAEAMAlKGwAAkzDF57TPnz+f7/P09fUtkPkWJLNlNlteicz2YLa8EpntwWx5pYLL7Ovrm+Nz7GkDAGASlDYAACZBaQMAYBKUNgAAJkFpAwBgEpQ2AAAmQWkDAGASpvicti3p/2l3x9Ocuc1zbvPW5j0MAAAFhD1tAABMolDsadtbYmKiJk+erMTERMXFxalDhw5q3769o2MBAAo5SjsPzp07p5CQED322GOKi4vTG2+8QWkDAAocpZ0HZcuW1WeffabvvvtOXl5eSktLc3QkAMBdgNLOg5UrVyogIEDt27fXnj17tGPHDkdHAoBM5kw9lGVY2+fLOCAJ8hOlnQdNmzZVVFSUtm7dqhIlSsjNzU0pKSny9PR0dDQAQCFWKEo7Lx/R+jdfqVa/fn0tXLgwT9MCAJBXfOQLAACToLQBADAJShsAAJMoFOe0gfyS3RW3ElfdAnAO7GkDAGASlDYAACZRKA6Pt192OA9T5TzN5y/533bKjRs36vTp0+rTp08elgsAQN6wpw0AgElQ2nl08OBBDRo0SP369dP27dsdHQcAcBcoFIfHHaFYsWKaMGGCrly5oldffVXBwcFydeVvIABAwaFl8qh27dpycXFR2bJlVbx4cV29etXRkQAAhRylnUe///67JCk+Pl7JyckqXbq0gxMBAAo7Do/n0Y0bNzRo0CAlJydr0KBBcnFxcXQkAEAhVyhK29ZHtLLzb77l6+mnn9bTTz+dp2kBAMgru5Z2WlqaZs+erUuXLik1NVWdO3dWUFCQPSMAAGBadi3t7777TiVLltSAAQOUkJCgIUOGUNoAAOSSXUu7SZMmaty4sSTJMAy5ubnZc/EAAJiaXUu7aNGikqTk5GRNmTJFL7zwgj0XXyhFRUVlOzwsLMzOSQAABc3uF6LFxcXpvffeU8uWLdWsWbNcTePr61sgWQpqvgUpt5mdZd2cJUfuXcl2qLOvh7Pn+yez5ZXMmDnre9nZ18HZ82XH3pntWtpXrlzR+PHj1atXL9WpUyfX0+X1Ku/b+TdXjzvKnWR2hnUz4zbOiTOvh9m2s9nySubMnB1nXgczbuOCyny7PwTsWtqrV69WQkKCVq1apVWrVkmSRowYIU9Pz38133Urst87ur2cp2n7fJm8hwEAoIDYtbR79uypnj172nORAAAUGoXi5ir2duPGDUVGRurPP/9UamqqBg4cqICAAEfHAgDY0Zyph7IMK+gjtZR2Hqxdu1Y+Pj7673//q7Nnz+qnn36itAEABY4vDMmDM2fOqFatWpKkihUrqkuXLg5OBAC4G1DaeVC5cmXrt3ydP39e48aNc3AiAMDdgMPjedCuXTtFRkZq4MCBslgsev311x0dCQBwFygUpZ2XE///5vN1np6eGjVqVJ6mBQAgrzg8DgCASVDaAACYBKUNAIBJUNoAAJgEpQ0AgEkUiqvHgbtB+2WHsx2+c4j5vs4QQN4UitKOiorK1/mFhYXletyUlBR1795dy5cvz9cMAAD8E4fHAQAwiUKxp21vycnJeuedd5SQkHDbLysHACA/saedB2vXrtWDDz6oadOmqW3bto6OAwC4S1DaeXDmzBn5+/tLkmrVqiV3dw5YAAAKHqWdB1WqVNGhQze//Dw2NlZpaWkOTgQAuBuwi5gH7dq107vvvqsBAwaocuXK8vT0zNf589EeAEB2CkVp38lHtG75t9/yNXr06DxNCwBAXnF4HAAAk6C0AQAwCUobAACToLQBADAJShsAAJOgtAEAMAlKGwAAk6C0AQAwCUobAACToLQBADAJShsAAJOgtAEAMAlKGwAAk6C0AQAwCUobAACToLQBADAJShsAAJOgtAEAMAlKGwAAk6C0AQAwCUobAACToLQBADAJShsAAJOgtAEAMAlKGwAAk6C0AQAwCUobAACToLQBADAJShsAAJOgtAEAMAlKGwAAk6C0AQAwCUobAACTcHd0AKCgpf+nXZZhbvPWOiAJAPw7DtnTjo2N1ejRox2xaAAATMvue9qff/65tm3bpqJFi9p70U4pu71APTHJ/kEAAE7P7nvaFSpU0FtvvWXvxQIAYHp239Nu3LixLl68aO/FAsBdLyoqKtvhYWFhdk6CvDLFhWi+vr6mmu+dOHOH4+c2szOsm+QcObLbxjnnupLtUGdYD+lwjs84R77cM1teyYyZs38vZ8dZ1s1ZcuRe1m1c0OtgitI+f/58vs/T19e3QOZb0HKb2RnWzZm38Z3mctb1uMXZ82XkzO+LnJgx851whnUrLNs4P9bhdsXP57QBADAJh5S2t7e3xo8f74hFAwBgWuxpAwBgEpQ2AAAmQWkDAGASlDYAACZhs7R37txpjxwAAMAGm5/T/uSTT9SwYUN7ZAEA3KXmTD2U7fC2z5excxLnZrO0K1eurJiYGPn7+2f6ko+qVasWaDAAAJCZzdKOjY1VbGysvvrqK+swFxcXzZgxo0CDAYAz4z7ecASbpT1z5kx75ACQR9kdVuSQIlA42bwQ7fr165o/f77Gjh2rhIQEzZ07V9evX7dHNgAAkIHN0l6wYIG8vLz0999/y8PDQ0lJSZozZ449sgEAgAxslvbJkyf14osvys3NTUWKFFFYWJhOnjxph2gAACAjm6Xt6pp5FIvFkmUYAAAoeDYvRHvooYe0dOlSpaSkaO/evdq4caMCAgLske2Opf+nXZZhbvPWOiAJAAD5z2Zpv/TSS1qzZo28vLy0fPlyBQYGqnPnzvbIBgCAw7Vfdjjb4b3dfeycJBel7e7uri5duqhNmzZyc3OTp6enPXIBAIB/sFnaf/zxh2bMmKHjx49Lkvz9/fXaa6/p3nvvLfBwAADgf2yW9ty5c9W8eXONGTNGkrR582bNmTNHI0eOLPBwjpDdXY64wxEAwBnYvAw8MTFRLVq0kLu7u9zd3dWqVStduXLFHtkAAEAGNkvbx8dHsbGx1senTp1ShQoVCjQUAADIKsfD44MHD5aLi4uSk5P13//+V5UrV5arq6tOnjypihUr2jMjAADQbUo7NDTUnjkAAIANOZZ2rVq1rP+/cuWKEhIS7BIIAABkz+bV44sXL9amTZvk5eUlwzAk3fw+7Q8//LDAwwEAgP+xWdo///yz5syZo5IlS9ojDwAAyIHNq8fvu+8+FS9e3B5ZAADAbdjc027VqpUiIiIUEBAgd/f/jd6lS5cCDQYAADKzWdorV65UmTJllJSUZI88AAAgBzZLOyUlReHh4fbIAgAAbsPmOe2KFSvq1KlT9sgCAABuw+ae9uXLlzV8+HB5e3vLw8PDOvy9994r0GAAACAzm6XdtWtXe+RAITRn6qFsh7d9voydkwBA4WCztCtXrmyPHAAAZMHXJWdms7Szuwd52bJlFR0dXSCBAABA9myW9ooVK6z/T0tL044dO7gwDQAAB7BZ2plGdnfXI488onXr1nGuG0Ch037Z4WyH7xzia+ckQPZslnbGb/cyDEPHjh1TYmJigYYCAABZ3fE57VKlSqlnz54FFggAAGTvjs5pAwAAx7FZ2jdu3ND27dszHSaXpGeeeabAQgEAgKxslvbUqVN1+fJlVa5cWS4uLvbIBAAAsmGztM+fP6+pU6fKzc3NHnkAAHCY9P+0yzrwiUn2D5IDm18Ycs8999gjBwAAsCFXtzEdM2aM6tWrJ09PT+twzmkDAGBfNks7OTlZPj4+unDhgj3yAACAHNgs7VdffdUeOQAAgA02z2kDAADncEf3HgcA4N/K7h7vvd19HJDEfNjTBgDAJGzuaaekpGjnzp1Z7oj21FNPFVgoAACQlc3SjoyMVGJiory9vTMNp7QBALAvm6UdHx+vqVOn2iMLAAC4DZvntCtVqqQrV67YIwsAALgNm3vaTZo00RtvvKHKlStnuv94REREgQYDAACZ2SztpUuXqmPHjqpQoYI98gAAgBzYLO1ixYqpffv2+bZAi8WiDz/8UKdOnZKHh4f69esnHx8+nwcAgC02z2k3aNBAGzdu1OXLl5WQkGD9l1c7d+5Uamqqxo8fr65du2rJkiV5nhcAAHcTm3vaGzZsUFpamhYuXJhp+IoVK/K0wMOHD6tevXqSJD8/Px07dixP8wEA4G7jYhiGYc8FRkdHKzg4WPXr15ck9e/fXzNmzMh0kVt+ajh5a7bDc7plXt83axVIjvwwZ+qhLMPsnfdMm6Bsh3fK5kvidw4JyXbc4cOHZxk2ceLEfxfsDuX0vnDmzHciu7xSwWW+k/dFTj97J/7MetTNWbZxYfnZs7ecMlfa8Iudk9hPQf/s2dzTtlgsWrdunfbu3au0tDQFBgaqY8eOeS7ZYgwgP4IAABHpSURBVMWKKTk52frYMAyb8zp//nyelpUX9lxWfnD2vLnN50zrYbbMvr6+psucW86c19mz3cn7wt6yy+XMeXNSUD97vr6+OT5n85z2xx9/rF9//VWtWrXSM888o99//10fffRRrhf+TzVr1tSePXskSUeOHFHlypXzPC8AAO4mNve09+3bpwkTJsjd/eaoDRo00JAhQ/K8wEaNGmn//v16++23ZRgG39cNAEAu5erw+K3CliQPD49/df7Z1dVVffr0yfP0AADcrWweHq9SpYoWLVqkCxcu6MKFC1q8eLEeeOABe2QDAAAZ2NzTDg0N1YIFCzRq1ChZLBYFBgaqV69e9sgGAAAysFnaXl5eev311+2RBQAA3EaOpT1mzJjbTsgXhgAAYF85lvZTTz0lSfr555+VlJSkkJAQubq6atu2bSpevLjdAgIAJLd5a7N/Ytlh+waBQ+VY2o0bN5YkrVu3TuPGjZOr681r1ho0aKC3337bPukAADCRsLCwAp2/zavHr169qtTUVOvj69ev/6svDAEAAHlj80K0Zs2aacSIEQoODpZhGPrpp5/UokULe2QDAAAZ2Czt559/XlWrVtWBAwfk4uKi7t27W7/sAwAA2I/N0pZu3mDl3nvv1a0vBDt+/LiqVq1aoMEAAEBmNkt76dKl2rhxo0qXLm0d5uLiohkzZhRoMAAAkJnN0t6+fbuioqJUrlw5e+QBAAA5sHn1+L333kthAwDgBGzuadeuXVtLly5VUFCQPD09rcM5pw0AgH3ZLO1vvvlG0s3D5LdwThsAYEuOd3FDntks7ZkzZ9ojBwAAsMFmaV+9elXbtm3T9evXJUkWi0UXLlwo8Fu15ZfPX/LPdvi6FVfsnAQAgH/HZmlPnTpVnp6eOnv2rOrUqaMDBw7I3z/7IgQAAAXH5tXjcXFxCg8PV/369fX0009r3LhxunDhgj2yAQCADGyWdpkyZSRJPj4+OnPmjMqVKyeLxVLgwQAAQGY2D4+XKlVKa9eulZ+fn1auXKlixYopKSnJHtkAAEAGNve0+/TpI3d3d/n7+6tq1apauXKlXnrpJXtkAwAAGdjc0y5durRat24tSerWrZskaf/+/QWbCk4rx89dLjts3yAAcBfKsbSPHz+uBQsWqESJEnr11VdVqlQpxcXFadGiRdqzZ4+WLVtmz5wAANz1ciztDz/8UE2aNFFcXJxiYmLk5+en6Oho+fn5afLkyfbMCAAAdJvSTkpKUtu2bWWxWDRw4EBt375dffv21SOPPGLPfAAA4P+XY2kXKVJEkuTq6qqUlBSFh4erSpUq9soF4F8wyx0LAdyZHEvbMAzr/0uVKkVhA8gRFygC9nHb0k5ISLA+zvh/SSpRokTBpQIAAFnkWNqnT59WaGio9XHG/0vSihUrCi4VAADIIsfSppQB4Ka+b9bS+fPnHR0DsH1HNAAA4BwobQAATILSBgDAJChtAABMgtIGAMAkbH7LF5Abn7/k7+gIBYo7jAFwBuxpAwBgEpQ2AAAmQWkDAGASlDYAACZBaQMAYBKUNgAAJkFpAwBgEpQ2AAAmQWkDAGASlDYAACZBaQMAYBLcexx2x328ASBv2NMGAMAkKG0AAEyC0gYAwCQobQAATILSBgDAJBxy9fjPP/+s7du3a+DAgY5YPAAUGp+/5O/oCLAju5f2woULtW/fPlWpUsXeiwYAwNTsfni8Zs2a6t27t70XCwCA6RXYnvbWrVu1YcOGTMP69++vpk2b6uDBgwW1WAAACq0CK+2QkBCFhITky7x8fX3zZT6ZXbHjsvJL1szOndeZ8x3O8RnnzZwz582c83bODWdaL2fKkltmy2y2vJL9M5viNqbnz58vlMvKD86c19fX16nz5cRsmc26nXPDWdbLjNvYbJnNllcquMy3+0OAj3wBAGASDtnTDggIUEBAgCMWDQCAabGnDQCASVDaAACYhCkuRAPyG3eRAmBGlDaAApPdH0frVmT/cUsAtnF4HAAAk6C0AQAwCUobAACToLQBADAJLkQD4BTCwsIcHQFweuxpAwBgEpQ2AAAmweFxE+n7Zi3TfQsOACD/sKcNAIBJUNoAAJgEpQ0AgElQ2gAAmASlDQCASVDaAACYBKUNAIBJUNoAAJgEpQ0AgEnctXdE4+5iAACzYU8bAACToLQBADAJShsAAJOgtAEAMAlKGwAAk6C0AQAwCUobAACToLQBADAJShsAAJOgtAEAMAlKGwAAk6C0AQAwCUobAACToLQBADAJShsAAJOgtAEAMAlKGwAAk6C0AQAwCUobAACToLQBADAJShsAAJOgtAEAMAlKGwAAk6C0AQAwCUobAACToLQBADAJShsAAJOgtAEAMAlKGwAAk6C0AQAwCUobAACToLQBADAJShsAAJNwt+fCkpKSFBUVpeTkZKWlpalHjx7y8/OzZwQAAEzLrqW9fv161alTR23atNH58+c1bdo0RUZG2jMCAACmZdfSbtOmjTw8PCRJ6enp1v8DAADbXAzDMApixlu3btWGDRsyDevfv7+qV6+uK1eu6N1339Urr7yiWrVqFcTiATipOVMPZTu875v8LgBsKbDSzsnp06f1wQcf6OWXX1b9+vVzNc358+fzPYevr2+BzLcgmS2z2fJKZLaHdSuuZDu87fNl7Jwk98y2jSXzZTZbXqngMvv6+ub4nF0Pj589e1ZTpkzRG2+8oSpVqthz0QCcRN83a5nulzPgLOxa2h9//LFSU1O1aNEiSZKXl5eGDh1qzwgAAJiWXUubggYAIO+4uQoAACZBaQMAYBKUNgAAJkFpAwBgEpQ2AAAmQWkDAGASlDYAACZBaQMAYBKUNgAAJkFpAwBgEnb/li8AAJA37GkDAGASlDYAACZBaQMAYBKUNgAAJkFpAwBgEpQ2AAAmQWkDAGASd11pWywWR0e4q6Smpjo6Qq6lpKSYKu/ff//t6Ah3xGKxKD4+3nQ/g1evXpWz384iKSnJ0RH+lbS0NKWkpDg6Rq458v1wV9xc5c8//9TixYt1/Phxubm5yWKxqHLlyurRo4d8fX0dHa9Q+OWXX7RgwQK5ubnpxRdfVNOmTSVJY8aMUUREhIPTZe/s2bP6+OOPVaJECTVr1kxz5syRq6urXnnlFT388MOOjpfF+fPnMz2eOXOmXnvtNUly2vfx7Nmz1b9/f8XGxioqKkolS5ZUcnKy+vfvLz8/P0fHy9bXX3+tv/76Sw0aNFBUVJQ8PDyUkpKi0NBQ1a1b19HxstWtWzf16tVLISEhjo6SK+fPn9cnn3wid3d3tWrVSjNnzlR6erq6du1q/d3hbC5cuKD58+fr3Llzunz5sqpWrSpvb2/16NFDZcqUsVsOd7styYGio6PVtWtX1ahRwzrsyJEjmj17tsaNG+fAZIXH6tWrNWnSJBmGoSlTpiglJUVPPPGEo2Pd1rx58/T888/r4sWLmjJliqZNmyYPDw9NmDDBKUt73LhxKlKkiMqWLSvp5i++efPmSZLT/mF08eJFSdLy5cs1YsQI3XfffYqPj9e0adM0ZswYB6fL3pdffqmIiAhNmjRJQ4cOla+vr+Lj4zV58mSnLe0HHnhAJ06c0JgxY/Tss8+qVq1ajo50W3PmzFHnzp2VlJSkyMhITZ48WV5eXho3bpzTlvb8+fPVs2dP+fr66siRI/rll1/UuHFjzZ49W+Hh4XbLcVeUdmpqaqbCluS0f+XfMmbMmCyHag3DkIuLi9555x0HpcqZu7u7SpQoIUkaOnSoxo4dq3vvvdfBqW7PYrGoVq1aqlWrlg4ePKjSpUtLklxdnfOs0cSJEzVv3jy1bNlSdevWdeqjGP/k6uqq++67T5JUrlw5pz7c7ObmpqJFi6po0aKqUKGCpJuZnZmnp6dCQ0N17NgxrV69WvPnz1edOnXk7e2t1q1bOzpeFhaLRXXr1pVhGPrkk0+s29fd3XkrKSkpyXpEy8/PT8uWLVPXrl2VmJho1xzOu4Xy0QMPPKBZs2apXr168vLy0vXr17V7925VrlzZ0dFy1LVrV82ZM0dvvfWW3NzcHB3HpvLly2vx4sV6/vnnVaxYMQ0ePFjjx4936nNtvr6+io6OVp8+fayHmdesWWPXQ113onTp0nrzzTf10Ucf6ejRo46OkytJSUkaNmyYbty4oa1bt6pZs2ZasmSJU/9BFxQUpEmTJqlSpUqaOHGiAgMDtW/fPtWuXdvR0WyqVq2a3nrrLSUlJenQoUNZTqk4i/Lly+uDDz5Qenq6ihYtqk8++UReXl5O+7MnSRUqVNDcuXNVv3597dq1S1WrVtXu3btVpEgRu+a4K85pG4ahnTt36vDhw0pKSpKXl5dq1qypRo0aycXFxdHxcrR27Vr5+PioUaNGjo5iU3p6ur777js1adLE+ia+cuWK1qxZo1deecWx4XJgsVi0a9cuNWzY0Dps27ZtCg4OtvsP4p365ptv9PXXXzvtIeaMUlNTderUKXl6esrX11dbt25VSEiIU+9VHTp0SHv37tW1a9dUsmRJ+fv7q0GDBo6OlaNvvvnG6U9HZZSenq49e/bovvvuU9GiRbVhwwaVKFFCrVu3VtGiRR0dL1tpaWnasmWLzp49qypVqigkJERHjx7Vfffdp5IlS9otx11R2gAAFAbOefIOAABkQWkDAGASzntSCbiLPffcc6pUqZJcXV3l4uKiGzduyMvLS71791a1atUcHS/XVq5cqWvXrik0NNTRUYBCgdIGnFRERIRKlSplfbx27VotWLBA48ePd2AqAI5EaQMmkJ6erri4OOtn4dPS0rRkyRIdOHBArq6uqlGjhnr06KGvv/5aR48eVVhYmNLS0hQaGqoePXooJCREhw8f1uLFizVhwoRM837ttdf0+OOP69dff1VcXJyaNm2qbt266eDBg1qwYIHef/99Scr0eOXKlfrzzz/1559/6vLly6pevboCAwP17bff6uLFi3rppZfUrFkzSdK5c+cUERGhhIQEValSRb1791axYsUUHx+v+fPnKy4uTunp6WratKk6deqkixcvKiIiQvfff78uXbqk0aNHW28oA9ztKG3ASY0ZM0aurq66evWqPDw81KBBA7366quSpJiYGOtdulxdXRUdHa2PPvpIHTt21OrVq2UYhn7//XcVKVJEBw4cUEhIiPUOTtm5fv26xo4dq/j4eA0YMEAtW7a0me/w4cOaPHmy3N3d1bdvX91zzz0aM2aMdu7cqaVLl1pL+8KFC5o4caJKliyp6dOna9WqVerWrZumT5+uNm3aKCgoSCkpKZowYYJ8fHxUvXp1/fXXXwoLC9NDDz2UfxsUKAS4EA1wUhEREZo8ebKGDx+uGzduqGbNmta7tu3Zs0ctW7aUu7u7XF1d1apVK+3du1fly5dXuXLldOzYMe3du1cdOnTQoUOHrPcqCA4OznZZtz6rXq5cOZUuXVoJCQk289WpU0deXl7y9PRUuXLlVK9ePUk3b0KRcfpGjRqpVKlScnFxUfPmzXXgwAFdv35dhw4d0ooVKzRkyBCNHDlScXFxOnnypKSbdyVz9rsWAo7Anjbg5B588EH16NFD0dHRqlGjhry9vbPcBtQwDKWnp0uSgoODtWfPHu3fv1/Dhw/XDz/8oB9//FGenp7y8fHJdhmenp7W/7u4uFhvmZtxOWlpaZmm8fDwyPQ4pzv3ZbwtrGEY1i/tkaR33nnHeiObq1evytPTU1evXpW7u7sp7gQI2Bt72oAJNGvWTH5+flq0aJEkKTAwUF9++aXS0tJksVi0ceNG1alTR9LNPdvvv/9eFotFZcuWVd26dbV06dIcD43npFSpUoqLi9Pff/9t3VPPi127dikhIUEWi0Vbtmyx3k64Ro0aWr9+vSQpMTFRo0aNyvMygLsFe9qASYSGhuqtt97S3r171blzZy1ZskRDhw5Venq6qlevrl69ekmSKlasKEnWe2UHBgZq1apVOR4az0nFihXVokULDR8+XGXLls3zbTzvv/9+RUZGKiEhQf7+/urQoYMkKSwsTAsWLNDgwYOVlpamRx55RI8++qj1m8EAZMVtTAEAMAkOjwMAYBKUNgAAJkFpAwBgEpQ2AAAmQWkDAGASlDYAACZBaQMAYBKUNgAAJvH/AZCQ0mbfejDqAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = df.plot(kind='bar')\n",
    "ax.set(title=\"Random Number Bar Graph from DataFrame\", \n",
    "       xlabel=\"Row number\", \n",
    "       ylabel=\"Random number\")\n",
    "ax.legend().set_visible(True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.style.use('seaborn-whitegrid')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create the plot\n",
    "fig, ax = plt.subplots(figsize=(10, 6))\n",
    "\n",
    "# Plot the data\n",
    "scatter = ax.scatter(over_50[\"age\"], \n",
    "                     over_50[\"chol\"], \n",
    "                     c=over_50[\"target\"],\n",
    "                     cmap=\"winter\") # this changes the color scheme\n",
    "\n",
    "# Customize the plot\n",
    "ax.set(title=\"Heart Disease and Cholesterol Levels\",\n",
    "       xlabel=\"Age\",\n",
    "       ylabel=\"Cholesterol\");\n",
    "\n",
    "# Add a legend\n",
    "ax.legend(*scatter.legend_elements(), title=\"Target\");\n",
    "\n",
    "# Add a horizontal line\n",
    "ax.axhline(over_50[\"chol\"].mean(), linestyle=\"--\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.style.use('seaborn-whitegrid')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Customizing the y and x axis limitations\n",
    "\n",
    "# Setup plot (2 rows, 1 column)\n",
    "fig, (ax0, ax1) = plt.subplots(nrows=2, # 2 rows\n",
    "                               ncols=1, \n",
    "                               sharex=True, \n",
    "                               figsize=(10, 8))\n",
    "\n",
    "# Add data for ax0\n",
    "scatter = ax0.scatter(x=over_50[\"age\"], \n",
    "                      y=over_50[\"chol\"], \n",
    "                      c=over_50[\"target\"],\n",
    "                      cmap=\"winter\") # this changes the color scheme\n",
    "# Customize ax0\n",
    "ax0.set(title=\"Heart Disease and Cholesterol Levels\",\n",
    "#         xlabel=\"Age\",\n",
    "        ylabel=\"Cholesterol\")\n",
    "# change the x axis limit\n",
    "ax0.set_xlim([50, 80])\n",
    "ax0.legend(*scatter.legend_elements(), title=\"Target\")\n",
    "\n",
    "# Setup a mean line\n",
    "ax0.axhline(y=over_50[\"chol\"].mean(), \n",
    "            color='r', \n",
    "            linestyle='--', \n",
    "            label=\"Average\")\n",
    "\n",
    "# Add data for ax1\n",
    "scatter = ax1.scatter(over_50[\"age\"], \n",
    "                      over_50[\"thalach\"], \n",
    "                      c=over_50[\"target\"],\n",
    "                      cmap=\"winter\") # this changes the color scheme\n",
    "\n",
    "# Customize ax1\n",
    "ax1.set(title=\"Heart Disease and Max Heart Rate Levels\",\n",
    "        xlabel=\"Age\",\n",
    "        ylabel=\"Max Heart Rate\")\n",
    "# change the x axis limit\n",
    "ax1.set_xlim([50, 80])\n",
    "ax1.set_ylim([60, 200])\n",
    "ax1.legend(*scatter.legend_elements(), title=\"Target\")\n",
    "\n",
    "# Setup a mean line\n",
    "ax1.axhline(y=over_50[\"thalach\"].mean(), \n",
    "            color='r', \n",
    "            linestyle='--', \n",
    "            label=\"Average\")\n",
    "\n",
    "# Title the figure\n",
    "fig.suptitle('Heart Disease Analysis', fontsize=16, fontweight='bold');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig.savefig(\"images/heart-disease-analysis-plot-saved.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Potential function\n",
    "\n",
    "def plotting_workflow(data):\n",
    "    # 1. Manipulate data\n",
    "    \n",
    "    # 2. Create plot\n",
    "    \n",
    "    # 3. Plot data\n",
    "    \n",
    "    # 4. Customize plot\n",
    "    \n",
    "    # 5. Save plot\n",
    "    \n",
    "    # 6. Return plot\n",
    "    \n",
    "    return plot"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}