PyBer_ride_data.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>Month</th>\n",
       "      <th>Avg. Fare ($USD)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Jan</td>\n",
       "      <td>10.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Feb</td>\n",
       "      <td>23.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Mar</td>\n",
       "      <td>39.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>April</td>\n",
       "      <td>35.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>May</td>\n",
       "      <td>32.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>June</td>\n",
       "      <td>27.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>July</td>\n",
       "      <td>43.82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Aug</td>\n",
       "      <td>10.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Sept</td>\n",
       "      <td>11.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Oct</td>\n",
       "      <td>27.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Nov</td>\n",
       "      <td>20.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Dec</td>\n",
       "      <td>20.09</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Month  Avg. Fare ($USD)\n",
       "0     Jan             10.02\n",
       "1     Feb             23.24\n",
       "2     Mar             39.20\n",
       "3   April             35.42\n",
       "4     May             32.34\n",
       "5    June             27.04\n",
       "6    July             43.82\n",
       "7     Aug             10.56\n",
       "8    Sept             11.85\n",
       "9     Oct             27.90\n",
       "10    Nov             20.71\n",
       "11    Dec             20.09"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load in csv\n",
    "pyber_ride_df = pd.read_csv(\"Resources/PyBer_ride_data.csv\")\n",
    "pyber_ride_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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3lsISO3OsaQyK7dc6N8B5IbOprRO7lhIqH9AE7gebD1XQ1ulg2cT+fUSfY03jtbsWMi4rif9Yu5NH3i7WeXEPO1vbQvHZ+n5Vn/TUXUqo0yjKBzSB+8GGYhtJsVHMsbq3wq+nISlxvPCV+dw4ZwRPbjjsrBdv0nlxTykscV6bcHf5/PlytRZc+ZAmcB9zOAwFxTYuH59BdOTA/vpjoyL52fVT+cnqKWw5VMF1T27m4FmdF/eEwhI7WcmxjB9gT5qhqXFERYjWgiuf0ATuYx+ersNW33rR6hN3iAg3z8th3Z3zaWrrZPVvt/CGzotfko5OB5tK+18+2FN3KaEmcOUDmsB9LL+4HBFYMv7SEniX2a558fFDkvja2p38/C2dFx+o3SdrqG/puOSfjdWSwLEKnQNX3qcJ3McKim3MHDmYtMQYjz1nVnIcf10zn5vmjuC3Gw9z+3M6Lz4QhSV2IiOEBWPSL+l5nF0JtZRQeZ8mcB+y1bWw91St2+WD/eGcF5/GT1dP5b3DFVz7xGaKz9Z5/HVCWWGJnRkjUkmJj+775IvITU+ksa0Te4OWEirv0gTuQxsOOiscvJHAu3x+3kj+umY+ze2dXP/b93h9r86Lu6OioZW9p2oHXD7YU45rg+PjWkqovEwTuA/lF9kYmhLHhCHe3XVnVo5zXnzCkCS+/v928rDOi/dpU1f3wQGWD/bU1QBLd6hX3qYJ3EdaOzrZfKiCZRMzB1zh0B9ZyXGsWzOfm+aO5HcbD/Ol57ZR09Tm9dcNVoUH7VgSY5gyNOWSn2tYajxREaI71Cuv0wTuI1uPVNHU1skVF+g+6A1d9eI/XT2V9w9XcN0TW3RevBcOh+Hd0gouH5dBRMSl/+caFRnB8MHxWomivE4TuI8UFNuIi44YUIOkS+WcF7+MlvZOVj/5Hq/sOe3zGALZ/tO1VDW2eWT+u4s1XTc4Vt7XZwIXkTgR+UBE9ojIhyLygOv4cyJyVER2u77yvB5tkDLGkF9czsIx6W7vr+hps3IG89pdC5k0NJn/XLeLr6/dqQ2XXAoP2hGhe2ckT7DqBsfKB9wZgbcCy4wx04E84GoRme+6725jTJ7ra7eXYgx6h2wNnKxqvuDmDb6S6aoXv/uq8bxzoJxPPl7ISztPhX2S2VhiZ+qwFCyDYj32nFZLAg2tHVQ06HUH5T19JnDj1OC6Ge36Cu/f+H7KL/Z++aC7oiMj+PrSMbzxzUWMzhjEf/1tD196bhtlNc3+Ds0vapva2XWi2qPTJwA5rkoUvZCpvMmtOXARiRSR3YANeMcYs9V1109EZK+IPC4ivQ5fRGSNiGwXke12u90zUQeZgiIbk4cmMyQlzt+hdBuTOYi/feUy7r92Eh8crWL5Y4X8+d/HcYRZueHmQxU4TP82L3aH1aKlhMr73ErgxphOY0weMByYKyJTgHuBCcAcIA347gUe+5QxZrYxZnZGhmd/SYJBTVMb249XBcTo+3yREcJtC3J5+1uXM2PkYP5n/X5ufPrfYZV0CktsJMdFkTci1aPPO3xwPJERoot5lFf1qwrFGFMDbACuNsaccU2vtAJ/BOZ6Ib6gV1hix2ECY/rkQkakJfDnO+by8xumUXSmjqt/+S6/LzxMR6fD36F5lTGGwhI7i8ZmEDXA1r4XEt1VSqhTKMqL3KlCyRCRVNf38cAngWIRyXYdE2AVsN97YQav/CIblsQYpg9P9XcoFyUifHbOCP71X4tZPC6Dn71ZzPW/e4+iM6FbN36wvJ7yulaPT590cW5wrAlceY87w45sYIOI7AW24ZwDfw1YKyL7gH1AOvBj74UZnDo6HWw8aGPphEyPLBDxhazkOH5/yyye+PwMyqqbufY3m3nsnRJaOzr9HZrHbTzovCZzudcSeALHK7SUUHlPn7u2GmP2AjN6Ob7MKxGFkJ0naqhr6bjkzRt8TURYMW0oC0an86PXDvDr/FLe2n+Gh2+YxoyRg/0dnscUHrQzYUiS1y4uW9MTqW/toLKxjXQPligq1UVXYnpRfnE50ZHCQg8uEPGlwYkxPP65PP542xzqWzq44Xfv8ePXDtDcFvyj8YbWDrYfr/JI86oL6apE0VJC5S2awL2ooMjGvFwLSXGX1l/a35ZOyOSf376cm+aO5A+bj3LVL9/lvcMV/g7rkrx/uJL2TuO1+W/4qK3sUe2JorxEE7iXnKhsotTWENDVJ/2RFBfNT1ZPZd2d8xGBzz+9lXtf2kddS3Du/FNYYiMhJpLZOWlee43hgxNcpYQ6AlfeoQncSwqKywG4YmJoJPAul4228NY3L2fN5aN4YdsJlj/2LvlF5f4Oq1+MMWw8aOcTo9OJifLer0BMVATDUuM5prXgyks0gXtJfrGNURmJ5LjmQUNJfEwk3//URF762gJS4qO54/ntfPOvu6hqDI6+H0cqGjlV3ezV+e8u1vREjoXRwijlW5rAvaChtYOtR6qCrvqkv/JGpPLqXQv51pVjeWPfGa58rJBX9pwO+LK5Qlf54BIvzn93sVoSOKYbHCsv0QTuBZtLK2jrdPi9+6AvxERF8K0rx/HaXYsYMTie/1y3izv/tIOztS3+Du2CCkvsjMpIZERagtdfy2pJpL6lI2g+najgogncCwqKy0mKi2K2NXRqpvsyfkgSL31tAT/41EQ2ldr55OOF/PWDEwE38mxp7+TfRyq9Wn3SkzXd+Z+EzoMrb9AE7mEOh2HDQTuLx2UQ7eH+GoEuMkK48/JRvP2ty5mUncz3XtrHzX/YyqnqwEleW49W0drh8FkCz9FacOVF4ZVhfGD/6Vrs9a0hV33SH9b0RNbdOZ+frJ7C3lO13PT0v7HVB8aUysaDNmKjIpg/yjdb240YnECEoBcylVdoAvew/CIbEQKLx4VvAgeIiBBunpfDX748j4r6Nm5/bhsNrR3+DovCEjvzRll8trVdTFQEwwZrKaHyDk3gHlZQbGPmyMGkJcb4O5SAkDcilSdvnkHRmXr+4y87aOvwX4vak1VNHLE3+mz6pIt2JVTeogncg8rrWthXVsuyMJ4+6c2yCVn8bPVUNpVW8L2/7/Xbhc3CElf5oA/qv3uyWhI5WqGlhMrz+uxGqNy3IYD2vgw0n50zgrN1LTz2TglZKXF89+oJPo+hsMTO8MHxjEr37eKqHEsC9S0dVDe16ycz5VGawD0ov9jGsNR4xmcl+TuUgHTXsjGcqW3hdxsPMyQ5jls/YfXZa7d1OHjvUAWrZgzDuQeJ7+S6/sM4VtmoCVx5lE6heEhLeyebSytYNiHT5wkiWIgID66czJUTs7j/1Q95c98Zn7329uNVNLZ1+nz+G7SUUHmPJnAP+feRSprbO3X+uw9RkRH85qYZzBiRyjdf2M0HR6t88rqFJXaiIoRPjPF9b/YRafFEiLaVVZ6nCdxDNhTbiI+O5DIf1RcHs/iYSJ65dQ7DB8fz5ee3UVJe7/XXLDxoZ7Z1MINifT9rGBsVydDUeB2BK4/TBO4Bxhjyi20sGJPus/riYDc4MYbnvzSX2OhIbn32A87UNnvttcrrWig+W8+S8f77dJSrXQmVF2gC94BSWwOnqpvDevXlQIxIS+C5Lzm3a7vt2W3UNntnc4iu8kF/zH93ybEk6GIe5XF9JnARiRORD0Rkj4h8KCIPuI7nishWETkkIi+ISNheXs8vcpYPLvXjCC9YTR6awu9vmcWRigbW/Gk7rR2e32+z8KCdzKRYJgzxX3WQ1ZJIbXM7NU3alVB5jjsj8FZgmTFmOpAHXC0i84GHgceNMWOAauAOr0UZ4AqKy5kyLNlru5uHugVj0vnFZ6az9WgV//W3PTgcnlvw0tHpYFOps7mYP6uDujY4PqrTKMqD+kzgxqnBdTPa9WWAZcCLruPPA6u8EWCgq25sY8fxapbp6PuSrMwbxvc/NYHX957hwdcPeGzV4p5TNdS1dPhk952L6Wore1ynUZQHuXVJXkQigR3AGOBJ4DBQY4zp6k50Chh2gceuAdYAjBw58lLjDTiFJXYcBpZNDP3NG7ztzkWjOFPbwh+3HCM7JY41l4++5OcsPGgnQmDRGP8m8BFpCYjoCFx5llsXMY0xncaYPGA4MBdwex20MeYpY8xsY8zsjAz//hJ5Q36xjfRBMUwbluLvUIKeiPA/10zimmnZ/PSNYl7eXXbJz1lYYmfGyMGkJER7IMKBi42KZGiKlhIqz+pXFYoxpgbYAFwGpIpI1wh+OHDpv21Bpr3TQeFBG0vHZxIRoasvPSEiQnj0M9OZl5vGd/53D1sOVQz4uSobWtlbVuvX6pOerOkJHNUpFOVB7lShZIhIquv7eOCTQBHORP5p12m3Ai97KcaAteN4NXUtHVo+6GFx0ZE89cXZjM4YxFf+vIMPT9cO6Hk2lVZgjH/LB3uyWhJ1BK48yp0ReDawQUT2AtuAd4wxrwHfBf5LRA4BFuAZ74UZmDYU24iOFBaODYwEEUpS4qN57ktzSY6L4rY/buNkVf9HroUldtISY5gaINNbVksiNU1aSqg8x50qlL3GmBnGmGnGmCnGmB+5jh8xxsw1xowxxnzGGNPq/XADS36xjfmjLH5Znh0OhqTE8dztc2lt7+TWP35AdT92dnc4DO+W2Fk0Nj1gpres3V0JdRpFeYauxByg45WNHLI1aO9vLxuXlcQfbp3Dqepm7nh+G81t7i30+fB0HZWNbT7fvOFirJauUkKdRlGeoQl8gAp08wafmZubxq9vzGPXyRruWreLjs6+t2UrLHH+fBYF0PSWlhIqT9MEPkAFxTZGZyR293pW3nX1lGzuv3Yy/yoq539e/rDPhT6FJXamDkshfVCsjyLsW1x0VymhTqEoz9AEPgANrR38+0glV+jiHZ+69RNW/mPJaNZ9cILfFBy64Hm1ze3sPFETMNUnPTmbWukIXHmGJvAB2Fxqp73T6PSJH9xz1XiunzmMx94p4W/bTvZ6zpZDFXQ6jN+Xz/fGqm1llQdpAh+A/CIbyXFRzMoZ7O9Qwo6I8PAN01g0Np17/7GPguLyj51TeNBOUlwUM0ak+j7APlgtCVQ3tVPb5J3WucHKVtfCtmO+2Z0plGgC7yeHw7DhoI3F4zOJjtS/Pn+Ijozgd1+YxcTsJL6+dhe7T9Z032eModBVPhgVgD+frq6EOo1yrofeLOZzv3+fPT1+lqpvgfcvPMDtK6uloqGNK3T6xK8GxUbx7G1zSE+K4fbntnVXdpSUN3C2riUg57+hZy24JvAuna5BkcPAPS/u9UpP+FClCbyf8ottREjgLM8OZ5lJcfzp9nkA3PrsB9jrW7vLBy8P0J/PSFcp4THd4Ljb7pPVVDe1c/3MYRwsr+fJDYf9HVLQ0ATeTwXF5czKGczgxLDdgCig5KYn8uxtc7DXt3L7c9t4a/9ZxmclkZ0S7+/QehUXHUl2cpwu5ukhv8hGZITwwxWTuX7GMH674dCA+9+EG03g/XC2toX9ZXUsm6Dlg4Ekb0QqT948gwNn6pzlgwFYfdJTjiVRp1B6KCi2MSvH2fL3vmsnkZoQwz0v7qXdjQVb4U4TeD9sOKirLwPVsglZ/HT1FGKjIvg/U4b4O5yLsqYnaj8Ul9M1zRSfre++ppSaEMOPV03hw9N1/L5Qp1L6ol2Y+iG/yMaw1HjGZQ3ydyiqF5+bM5JVM4YRGxXp71AuympJoKqxjdrmdlLi/bvRhL/11pLi6ilDuGZaNr/OP8TyyUMYl+W/zagDnY7A3dTS3smWQxVcMTHTr5vjqosL9OQNH1Wi6Dy4syXziLR4xmSeOyj60XWTGRQXxd0v7nWr90240gTupvePVNLc3qnTJ+qSfVQLHt7TKC3tnWw5XMGy8R8fFFkGxXL/dZPZc7KGZ7cc9VOEgU8TuJsKimzER0cyf5TF36GoIDcyzdVWNsyX1L9/uJKWdscFNwS/dlo2yydl8eg/Szhib/BxdMFBE7gbjDEUFNtYODaduOjA/4iuAlt8TCTZKXEcDfMplPzicuKjI5mXm9br/SLCj1c5L0zf8+JeHI6Ld6AMR5rA3VBS3kBZTbOuvlQek2NJCOu2ssYYNhTb+xwUZSbHcd+1k9l+vJo/vX/MdwEGCU3gbsh3NUxaqglceUhumHclPFheT1lNs1vXlG6YOYwl4zN4+K2DnAjj//R6owncDQVFNqYOSyErOc7foagQkWNJpLKxjbqW8OxK2FU+uHR83wlcRPjp6qlERgjf/fvePjfzCCd9JnARGSEiG0TkgIh8KCLfdB2/X0TKRGS36+tT3g/X96oa29h5olpH38qjuipRjodpT5SCIhuThyYzJMW9QdHQ1Hh+cM1E3j9Syf/74ISXowse7ozAO4D/NsZMAuYDXxeRSa77HjfG5Lm+3vBalH5UWOLskqbz38qTrOnOSpRwXFJf7RoU9fd36sY5I1gwxsLP3iimrKbZS9EFlz4TuDHmjDFmp+v7eqAIGObtwAJFfpGN9EGxTB2W4u9QVAjJSQvfxTyFJXYcpv/XlESEh66fhsMY7n1pn06l0M85cBGxAjOAra5D3xCRvSLyrIj0uj2NiKwRke0ist1ut19atD7W3umgsMTOsgkZRETo6kvlOfExkQxJjuNoGE6hFBTbsCTGMH14ar8fOyItge9ePYF3S+y8uOOU54MLMm4ncBEZBPwd+JYxpg74HTAayAPOAI/29jhjzFPGmNnGmNkZGYHdJe58249VU9/Sod0HlVc4SwnDawTe4RoULRmfOeBB0S3zc5hrTePB1w5QXtfi4QiDi1sJXESicSbvtcaYlwCMMeXGmE5jjAN4GpjrvTD9Y8NBGzGRESwcm+7vUFQIyk0Pv7ayO0/UUNvcfkktKSIihIc/PY3WDgc/+Ed4T6W4U4UiwDNAkTHmsR7Hs3ucthrY7/nw/Cu/qJx5o9IYFKtNG5Xn5VgSqWhooz6MSgkLim1ERQiLxl3aoCg3PZHvLB/Pv4psvLLntIeiCz7ujMAXALcAy84rGfy5iOwTkb3AUuDb3gzU145VNHLY3qjVJ8prrBZXT5QwWpxSUFzOHGsayXGX3kb39oW55I1I5YevfIi9vtUD0QUfd6pQNhtjxBgzrWfJoDHmFmPMVNfx64wxZ3wRsK981KdY57+Vd4TbBscnq5ooKW/giomeGRRFRgiPfHoaTa2d/PCVkJsAcIuuxLyAgmIbYzIHMdI1SlLK03LCbATetaOVJxfFjc1K4ptXjuWNfWd5Y19IjSHdogm8F/Ut7Ww9WqnTJ8qrEmKiyEqO5WiY9EQpKLZhtSQwyvXJw1PWXD6KKcOSue/l/VQ3tnn0uQOdJvBebC6toL3T6OYNyutyLIlhUUrY1NbBe4crWTrB8ztaRUdG8Minp1PT1M4Dr37o0ecOdJrAe5FfbCM5LopZOb2uTVLKY3ItiWGxmOe9Q5W0dTi4wkvXlCZmJ/P1pWNYv/s0/zpQ7pXXCESawM/T0elgQ7GNxeMziYrUvx7lXTnpCVQ0tNLQ2uHvULwqv9hGYkwkcy+weYMnfH3pGCYMSeIH6/dR2xwepZmaoc6z+VAFlY1trJiW3ffJSl2i7q6EITyN4ty8wcaisRnERHkv5cREOadSKhra+MnrB7z2OoFEE/h51u8qIyU+miXjg2vZvwpO3Rsch/A0yoEzdZyta/HJNaWpw1NYc/ko/rb9FIUlwdV7aSA0gffQ2NrB2x+W86mp2cRG6d6Xyvu6SglDuRZ8g2tNxZIJvhkUffOKsYzOSOTev+8N+VWumsB7eOdAOc3tnayeETbdcpWfJcZGkZkUG9LbqxUU25g2PIXMJN/saBUXHcnPPz2dM3UtPPRmsU9e0180gffwj11lDEuNZ7ZWnygfsloSQ3YxT2VDK7tO1vi8JHdWzmDuWJDL2q0neO9whU9f25c0gbvY61vZVGpnZd5Q7f2tfMqanhCyUyiFJXaMwS9rKv57+XislgS+9/d9NLWFZpWPJnCX1/aexmHQ6RPlczmWRGz1rTSGYClhfrGNjKRYpgz1/Y5W8TGRPHzDNE5UNfHI2wd9/vq+oAncZf2uMiZlJzM2K8nfoagw81EpYWhNo7R3Oni3xM7S8f7b0WreKAtfvCyH5947xvZjVX6JwZs0gQNH7A3sOVWro2/lF6G6wfFHO1r5tyXFd6+ewNCUeO55cS8t7Z1+jcXTNIED63efRgSuyxvq71BUGMqxhGZb2Q0HbURHCgvH+ndNRWJsFA/fMI0jFY08/q8Sv8biaWGfwI0xrN9VxidGW8hK9k2Zk1I9DYqNIiMESwnzi8qZl2sJiB2tFo5N56a5I3j63SPsPlnj73A8JuwT+K6TNZyoamJVnk6fKP+xWhI4FkJz4McrnTta+Xv6pKd7PzWRzKQ47nlxD60doTGVEvYJfP2uMmKjIrh6yhB/h6LCWKi1lf1oR6vASeDJcdH87PqplJQ38ETBIX+H4xFhncDbOx28tvcMV07KIskDe/QpNVC56YmU17WGTL1yQbGNURmJ3dvGBYqlEzK5fuYwfrvxMK/uOc3RikbaOhz+DmvA/D855UebSu1UNbaxWqdPlJ/13F5tYnayn6O5NI2tHWw9UsUXL8vxdyi9um/FJN4/XMld63YBIALZyXEMT0tgZFoCIwYnMNIS7/wzLYGMpFiPb0LhKX0mcBEZAfwJyAIM8JQx5lcikga8AFiBY8BnjTHV3gvV8/6x6zSpCdFcPk47Dyr/+qgrYWPQJ/DNhypo63SwzEObF3taakIM//z25RSfredEZRMnq5s4UdXEyaomNpdWcLau5Zzz46IjGD64K7nHMyItgRFdyT4twa8Xad155Q7gv40xO0UkCdghIu8AtwH5xpiHROR7wPeA73ovVM9qaO3gnQNn+fSs4V7tUayUOz7aoT74L2RuKLaRFBvFHKv3Nm+4VElx0cyxpvUaY0t7J2U1zZyoauJUVVdyd97edrSK+vNWzKYlxjiT+uD47qTeNZLPTo0j2osbw/SZwI0xZ4Azru/rRaQIGAasBJa4Tnse2EgQJfC395+lpd2hi3dUQBgUG0X6oNigv5BpjKGg2Mbl4zK8mri8KS46ktEZgxidMehj9xljqG1u707oJ6qcI/iTVU3sL6vlrf1n6XCY7vMjI4TslDhGpiVw91XjmTHSs43y+jX2FxErMAPYCmS5kjvAWZxTLEFj/e4yRqTFM9PDf6FKDZTVkhD0O9R/eLoOW30rSwOo+sSTRITUhBhSE2KYOvzj/V06HYazdS3dUzMnXVMzJ6qaiPRCOwG3E7iIDAL+DnzLGFPXc1LfGGNExFzgcWuANQAjR468tGg9xFbXwpZDFXx96ZiAvTihwk+OJZEth4K79Wl+kQ0RwnZHq8gIYVhqPMNS47kMi9dfz63POCISjTN5rzXGvOQ6XC4i2a77swFbb481xjxljJltjJmdkREYP9RX9jg7D67U6hMVQHLTEzhb10JzW/AuMik4aGP68FTSB8X6O5Sw0GcCF+cQ9RmgyBjzWI+7XgFudX1/K/Cy58Pzjpd3n2bqsBTGZH58jkspf+nqiXK8KjinUez1rew5WcMVITp9EojcGYEvAG4BlonIbtfXp4CHgE+KSClwpet2wDtkq2dfWS2r9OKlCjC56R+VEgajjQedH8JDdf47ELlThbIZuNBE8RWeDcf71u86TYTAtdOz/R2KUucY2b3BcXCWEhYU28hKjmXy0OCuYw8mwVnnM0DGGNbvLmPBmHSfbbCqlLuS46KxJMYEZSlhW4eDTaUVLJuQqYUBPhRWCXzH8WpOVTdr7bcKWNb0xKAsJdx2rIqG1g6WjtfpE18KqwS+fncZcdERLJ+snQdVYMqxJATl1moFxTZioiJYMCbd36GElbBJ4G0dzs6DyycNCYgG80r1JteSyJna4CslLCi2MX+UhUT93fKpsEnghSV2apradfpEBbQcVyXKiargGYUfrWjkaEWjlg/6Qdgk8PW7y0hLjGHhWP2IpwJXbhDujxmImzeEi7BI4PUt7fzrQDnXTssO2gY7Kjx0lxIG0YXMguJyxmYOYkRagr9DCTthkc3e2n+W1g4HK3X6RAW4lPho0hJjgqYWvL6lnQ+OVuno20/CIoGv311GjiWBGSNS/R2KUn2yWhKCZgS+ubSC9k6jCdxPQj6Bn61t4b3DlazKG6YLDFRQsAbRBscFxTaS46KYlaNtmf0h5BP4q3tOYwza+0QFDWt6IqdrW2hpD+xSQofDsOGgjcXjM4nSa0t+EfJ/6//YVcb0EandjYKUCnRdGxwHeinhvrJaKhraWDYhMNpEh6OQTuAl5fUcOFPH6ryh/g5FKbcFS1fC/GIbEQKLx+n8t7+EdAJfv6uMyAhhxXRN4Cp45KQFRy34hmIbM0YOJi0xxt+hhK2QTeAOh+Hl3adZNDZddwdRQSUlIZrBCdEBXUpoq2thX1mtVp/4Wcgm8O3HqymraWaVbpumgpA1PTGgp1A2HNTVl4EgZBP4P3aVkRATyfLJWf4ORal+c5YSBu4IPL/IxtCUOCYMSfJ3KGEtJBN4a0cnr+89zVWTh5AQo93RVPCxWhI5XdsckKWErR2dbD5UwVLdvMHvQjKBbzxop66lg5VafaKClDU9AWPgZACWEn5wtIqmtk6umKjTJ/4Wkgl8/a4y0gfFsFCby6sgldPdlTDwEnh+kY3YqAguG6W/X/4Wcgm8trmd/GIbK6YN1dVhKmh1t5UNsAuZxhgKim18YrSF+JhIf4cT9vrMcCLyrIjYRGR/j2P3i0iZiOx2fX3Ku2G67639Z2jrcOjGDSqopSREk5oQHXC14IftjZyoamLZRC0OCATuDFGfA67u5fjjxpg819cbng1r4P6xq4xR6YlMG57i71CUuiSBWImyQTdvCCh9JnBjzLtAlQ9iuWSna5rZerSKldp5UIUAqyUh4Haozy8uZ8KQJIalxvs7FMWlzYF/Q0T2uqZYLthLUkTWiMh2Edlut9sv4eX69kp350GtPlHBz9mVsJnWjsAoJaxtbmf7sWqW6ug7YAw0gf8OGA3kAWeARy90ojHmKWPMbGPM7IwM73YtW7+rjJkjU7uv4CsVzKyWxIAqJdxUaqfDYXTz4gAyoARujCk3xnQaYxzA08Bcz4bVf0Vn6ig+W699v1XIyOneHzMwEnhBsY3UhGhmjNTNGwLFgBK4iGT3uLka2H+hc31l/e4yoiKEa6Zm932yUkGgu61sAFSidDoMGw/aWTIug8gIvb4UKPpcZy4i64AlQLqInAJ+CCwRkTzAAMeAr3gvxL45HIZXdp/m8nEZWLTzoAoRqQkxpMQHRinhnlM1VDW26fx3gOkzgRtjburl8DNeiGXAth6t4kxtC/d+aqK/Q1HKo6zpgVFKWFBkIzJCWDxOd98JJCGxVPHl3WUkxkTySV1coEJMoJQSFhTbmDVyMKkJunlDIAn6BN7S3snr+85w1ZQhurRXhRyrJZHTNf4tJTxb28KBM3Us0+ZVASfoE/iGYhv1LR26dF6FJGt6Ag4DJ6ua/RZDga6+DFhBn8DX7y4jIymWT4zWzmgq9HStaTjuxwuZBcU2hg+OZ2zmIL/FoHoX1Am8pqmNDcV2rps+VEubVEjK9XNb2Zb2TrYcqmCZbt4QkII6gb+x7yxtndp5UIWu1IRokuOi/NZW9t9HKmlu79TpkwAV1Al8/e4yRmckMnlosr9DUcorRITc9ES/1YIXFNuIj45k/iiLX15fXVzQJvBT1U18cLSK1TO086AKbTkW/yTwrs0bFoyxEBetFV6BKGgT+Ct7TgOwMk+nT1Ros1oSKKtupq3D4dPXLbU1cKq6mWUTdH1FoArKBG6M4R87y5idM5gRaQn+Dkcpr7KmJzpLCat9eyGzq3xw6QRdfRmogjKBHzhTR6mtQTsPqrDgr1LCgiIbk7KTyU7RzRsCVVAm8Jd3nyY6UjsPqvDQ3ZXQR21lm9o6yC8qZ8eJaq0+CXB9NrMKNJ0Ow8u7y1g8LpPBidqXQYW+wQnRJMVFee1CpsNhOHCmjndL7WwqqWDH8WraOh0kxUbp7lYBLugS+NYjlZTXtXLfCp0+UeHho1JCz43Az9Q2s6m0gs2lFWw+VEFVYxsAE7OTuW2BlUVj05ljTdPqkwAXdAn8H7vKGBQbxRXaWEeFkRxLIntO1gz48U1tHWw9WsWmkgo2ldoptTUAkJEUy5JxGSwal86CMelkJsV5KGLlC0GVwFvaO3lz/1n+z5QhOjJQYcVqSeD1vadp63AQE9X3pasLTYvERkUwNzeNz84ewaJx6YzPStJ1FEEsqBJ4fpGNhlbtPKjCj9XiLCUsq2nuvqh5vq5pkU2lFWw5b1rkSwusLBqbwWzrYB38hJCgSuD/2FVGVnIs83RZrwoz1vSuDY4buxN4U1sHW49UuZL2edMi4zO4fGwGC8akk5Gk2wyGqqBJ4NWNbRSW2PjSglztPKjCjtVVC15YYqfobN3HpkXmjbLotEgYCpoE/vq+M7R3GlbmaVmTCj9piTEkxUXx3HvHAJ0WUU7u7Er/LLACsBljpriOpQEvAFacu9J/1hhT7b0wYf2uMsZlDWJStnYeVOFHRPj1jTOoaW5j4ZgMnRZRgHsrMZ8Drj7v2PeAfGPMWCDfddtrTlY1sf14Nau086AKY0snZLJ6xnBN3qpbnwncGPMuUHXe4ZXA867vnwdWeTasc728uwyA66br9IlSSnUZaC+ULGPMGdf3Z4EL9psUkTUisl1Ettvt9gG9WGZSHJ+dPZzhg7XzoFJKdRFjTN8niViB13rMgdcYY1J73F9tjBnc1/PMnj3bbN++feDRKqVUGBKRHcaY2ecfH+gIvFxEsl1PnA3YLiU4pZRS/TfQBP4KcKvr+1uBlz0TjlJKKXf1mcBFZB3wPjBeRE6JyB3AQ8AnRaQUuNJ1WymllA/1WQdujLnpAndd4eFYlFJK9UNQ7sijlFJKE7hSSgUtTeBKKRWkNIErpVSQcmshj8deTMQOHB/gw9OBCg+GE2hC+f3pewteofz+gum95RhjMs4/6NMEfilEZHtvK5FCRSi/P31vwSuU318ovDedQlFKqSClCVwppYJUMCXwp/wdgJeF8vvT9xa8Qvn9Bf17C5o5cKWUUucKphG4UkqpHjSBK6VUkAq4BC4iDf6OwdNExIjIX3rcjhIRu4i85s+4PCGU31uXvv5NishGEQmqcjQR+YGIfCgie0Vkt4jMG8BzLBGRT3gjvkvl+nf5aI/b3xGR+/0YklcEXAIPUY3AFBGJd93+JFDWnycQkT47R/rJJb835VsichmwAphpjJmGsyX0yQE81RIgIBM40ApcLyLp/g7EmwIygYvIIBHJF5GdIrJPRFa6jltFpEhEnnaNHv7ZI3EEujeAa1zf3wSs67pDROaKyPsisktE3hOR8a7jt4nIKyJSAOT7PmS3DeS9vSsieT3O2ywi030ZdH+4Rpuv9bj9hIjcdt45t4vIL3vcvlNEHvddlG7LBiqMMa0AxpgKY8xpEZklIoUiskNE3u6x69ZGEfmVa6S+3/UztQJfBb7tOr7If2+nVx04q0y+ff4drjxS4Pr0kS8iI0UkRUSOi0iE65xEETkpItG+Drw/AjKBAy3AamPMTGAp8KiIiOu+scCTxpjJQA1wg39C7Le/AjeKSBwwDdja475iYJExZgZwH/DTHvfNBD5tjFnss0j7byDv7RngNgARGQfEGWP2+Cxi7/gbcG2PX/ovAc/6MZ4L+ScwQkRKROS3IrLYFfNvcP5bm4Uz7p/0eEyCMSYP+BrwrDHmGPB/gceNMXnGmE2+fQtueRK4WURSzjv+G+B516ePtcCvjTG1wG6g6/dsBfC2MabdV8EORKB+LBfgpyJyOeAAhvHRzvdHjTG7Xd/vAKw+j24AjDF7XaOWm3COWHtKAZ4XkbGAAXr+r/+OMabKN1EOzADf2/8C/yMidwO3A8/5JlrvMcY0uD4trRCRIiDaGLPP33GdzxXnLGARzgHSC8CPgSnAO66xUiRwpsfD1rke+66IJItIqk+DHgBjTJ2I/An4T6C5x12XAde7vv8z8HPX9y8AnwM2ADcCv/VRqAMWqAn8ZiADmGWMaReRY0Cc677WHud1AsEyhQLOvUR/gXPu0NLj+IPABmPMalci3NjjvkZfBXeJ+vXejDFNIvIOsBL4LDDLl8EOQAfnfmKNu8B5fwC+j/OTxx+9HdRAGWM6cf4sNorIPuDrwIfGmMsu9JA+bgeqXwI7ce9n8QrOgWMazn+PBV6MyyMCdQolBbC5kvdSIMffAXnIs8ADvYzKUvjowt9tPo3Icwby3v4A/BrYZoyp9m54l+w4MElEYl2jz163FDTGbAVGAJ+nx7WAQCIi412fiLrkAUVAhusCJyISLSKTe5zzOdfxhUCta8qhHkjyTdQD4/r0+jfgjh6H38M5wgbnYHGT69wGYBvwK+A1139yAS2gErir0qIV57zUbNfI4Is4RzNBzxhzyhjz617u+jnwMxHZReB+Krqogbw3Y8wOoI4AHql2/Zs0xpzEmQj2u/7cdZGH/Q3YEsD/KQ3COa11QET2ApNwXp/4NPCwiOzBOR/cs8KkxfUz/L98lAxfBVYH6EXMnh7F2Tq2y13Al1zv/Rbgmz3uewH4guvPgBdQS+ldVQhPG2Pm+jsW5X0iMhTnx/gJxhiHn8Pp1UD+TbqqVR43xgRy5ZDbRGQj8B1jzHZ/x6LOFTAjcBH5Ks6PnP+fv2NR3iciX8RZrfKDAE7e/fo3KSKpIlICNIdK8laBLaBG4EoppdwXMCNwpZRS/aMJXCmlgpQmcKWUClKawFVIEQ93R3RdmPxaj9tLBvpcSnmaJnAVajzdHTEVZ/8PpQKOJnAVii7WHTFNRNa7OtH9W0SmuY7fLyLPujrvHRGR/3Q95CFgtGuxyiOuY4NE5EURKRaRtT0arSnlU5rAVSi6WHfEB4Bdrk503wf+1OO+CcBVwFzgh64Ofd8DDrs67t3tOm8G8C2cKxhHAQu8+F6UuiBN4CrkGGP24uxS2Vt3xIU4O9BhjCkALCKS7LrvdWNMqzGmArDxUQfM833gah3gwLnk3OrRN6CUm4Ky74ZSbrhQd8SLOb/T5YV+P9w9Tymv0hG4ClUX6o64CWcHOkRkCc6daeou8jwB33FPhS8dOaiQZIw5hbNV7fnuB551daJrAm7t43kqRWSLiOwH3gRe93SsSg2U9kJRSqkgpVMoSikVpDSBK6VUkNIErpRSQUoTuFJKBSlN4EopFaQ0gSulVJDSBK6UUkHq/wfmpXIX9fX/ggAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pyber_ride_df.plot(x=\"Month\", y=\"Avg. Fare ($USD)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Set x-axis and tick locations.\n",
    "x_axis = np.arange(len(pyber_ride_df))\n",
    "tick_locations = [value for value in x_axis]\n",
    "# Plot the data.\n",
    "pyber_ride_df.plot(x=\"Month\", y=\"Avg. Fare ($USD)\")\n",
    "plt.xticks(tick_locations, pyber_ride_df[\"Month\"])\n",
    "plt.show()"
   ]
  },
  {
   "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": [
    "pyber_ride_df.plot.bar(x=\"Month\", y=\"Avg. Fare ($USD)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pyber_ride_df.plot(x=\"Month\", y=\"Avg. Fare ($USD)\", kind='bar')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "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": [
    "y = pyber_ride_df[\"Avg. Fare ($USD)\"]\n",
    "# Get the standard deviation of the values in the y-axis.\n",
    "stdev = statistics.stdev(y)\n",
    "pyber_ride_df.plot(x=\"Month\", y=\"Avg. Fare ($USD)\", kind='bar', yerr=stdev, capsize=3, color='skyblue')\n",
    "plt.yticks(np.arange(0, 51, step=5.0))\n",
    "plt.xticks(rotation='horizontal')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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