gas_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.dates as mdates\n",
    "from matplotlib.dates import DateFormatter\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "link = \"https://raw.githubusercontent.com/peter-ehmann/Gas_Mileage_Analysis/master/gas_log.csv\"\n",
    "local = \"~/Documents/Programming/Gas/gas_log.csv\"\n",
    "data = pd.read_csv(link,\n",
    "                   parse_dates=[\"date\"],\n",
    "                   index_col=[\"date\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "data[\"mpg\"] = data[\"miles\"]/data[\"gallons\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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",
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       "    }\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>company</th>\n",
       "      <th>town</th>\n",
       "      <th>state</th>\n",
       "      <th>zip</th>\n",
       "      <th>gallons</th>\n",
       "      <th>price</th>\n",
       "      <th>sale</th>\n",
       "      <th>miles</th>\n",
       "      <th>time</th>\n",
       "      <th>product</th>\n",
       "      <th>fillup</th>\n",
       "      <th>mpg</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-05-20</th>\n",
       "      <td>Delta</td>\n",
       "      <td>Long Valley</td>\n",
       "      <td>NJ</td>\n",
       "      <td>7853</td>\n",
       "      <td>7.332</td>\n",
       "      <td>2.979</td>\n",
       "      <td>21.84</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20:13:00</td>\n",
       "      <td>unleaded</td>\n",
       "      <td>yes</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-25</th>\n",
       "      <td>Delta</td>\n",
       "      <td>Long Valley</td>\n",
       "      <td>NJ</td>\n",
       "      <td>7853</td>\n",
       "      <td>9.607</td>\n",
       "      <td>2.979</td>\n",
       "      <td>28.62</td>\n",
       "      <td>229.0</td>\n",
       "      <td>12:20:00</td>\n",
       "      <td>unleaded</td>\n",
       "      <td>yes</td>\n",
       "      <td>23.836786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-02</th>\n",
       "      <td>7-Eleven</td>\n",
       "      <td>Somerset</td>\n",
       "      <td>NJ</td>\n",
       "      <td>7883</td>\n",
       "      <td>7.172</td>\n",
       "      <td>2.739</td>\n",
       "      <td>19.64</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14:43:00</td>\n",
       "      <td>regular</td>\n",
       "      <td>yes</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-21</th>\n",
       "      <td>Wawa</td>\n",
       "      <td>Elkton</td>\n",
       "      <td>MD</td>\n",
       "      <td>21921</td>\n",
       "      <td>7.347</td>\n",
       "      <td>2.449</td>\n",
       "      <td>17.99</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20:46:12</td>\n",
       "      <td>unleaded</td>\n",
       "      <td>yes</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-25</th>\n",
       "      <td>Wawa</td>\n",
       "      <td>Hacketstown</td>\n",
       "      <td>NJ</td>\n",
       "      <td>7840</td>\n",
       "      <td>8.273</td>\n",
       "      <td>2.639</td>\n",
       "      <td>21.83</td>\n",
       "      <td>204.0</td>\n",
       "      <td>16:05:26</td>\n",
       "      <td>unleaded</td>\n",
       "      <td>yes</td>\n",
       "      <td>24.658528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-28</th>\n",
       "      <td>Wawa</td>\n",
       "      <td>Hacketstown</td>\n",
       "      <td>NJ</td>\n",
       "      <td>7840</td>\n",
       "      <td>7.954</td>\n",
       "      <td>2.759</td>\n",
       "      <td>21.95</td>\n",
       "      <td>184.0</td>\n",
       "      <td>17:16:42</td>\n",
       "      <td>unleaded</td>\n",
       "      <td>yes</td>\n",
       "      <td>23.133015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-03</th>\n",
       "      <td>BP</td>\n",
       "      <td>Ledgewood</td>\n",
       "      <td>NJ</td>\n",
       "      <td>7852</td>\n",
       "      <td>7.905</td>\n",
       "      <td>2.619</td>\n",
       "      <td>20.70</td>\n",
       "      <td>172.6</td>\n",
       "      <td>10:26:00</td>\n",
       "      <td>unleaded</td>\n",
       "      <td>yes</td>\n",
       "      <td>21.834282</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-12</th>\n",
       "      <td>Phillip</td>\n",
       "      <td>Long Valley</td>\n",
       "      <td>NJ</td>\n",
       "      <td>7853</td>\n",
       "      <td>5.844</td>\n",
       "      <td>2.979</td>\n",
       "      <td>14.43</td>\n",
       "      <td>160.9</td>\n",
       "      <td>10:16:00</td>\n",
       "      <td>regular</td>\n",
       "      <td>yes</td>\n",
       "      <td>27.532512</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-26</th>\n",
       "      <td>Wawa</td>\n",
       "      <td>Elkton</td>\n",
       "      <td>MD</td>\n",
       "      <td>21921</td>\n",
       "      <td>14.173</td>\n",
       "      <td>2.469</td>\n",
       "      <td>34.99</td>\n",
       "      <td>414.7</td>\n",
       "      <td>21:40:47</td>\n",
       "      <td>unleaded</td>\n",
       "      <td>yes</td>\n",
       "      <td>29.259860</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-27</th>\n",
       "      <td>QuickChek</td>\n",
       "      <td>North Brunswick</td>\n",
       "      <td>NJ</td>\n",
       "      <td>8902</td>\n",
       "      <td>4.510</td>\n",
       "      <td>2.559</td>\n",
       "      <td>11.54</td>\n",
       "      <td>138.2</td>\n",
       "      <td>19:29:55</td>\n",
       "      <td>regular</td>\n",
       "      <td>yes</td>\n",
       "      <td>30.643016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-02</th>\n",
       "      <td>Wawa</td>\n",
       "      <td>Elkton</td>\n",
       "      <td>MD</td>\n",
       "      <td>21921</td>\n",
       "      <td>10.947</td>\n",
       "      <td>2.499</td>\n",
       "      <td>27.36</td>\n",
       "      <td>325.8</td>\n",
       "      <td>20:33:53</td>\n",
       "      <td>unleaded</td>\n",
       "      <td>yes</td>\n",
       "      <td>29.761579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-04</th>\n",
       "      <td>Wawa</td>\n",
       "      <td>Somerset</td>\n",
       "      <td>NJ</td>\n",
       "      <td>8873</td>\n",
       "      <td>3.800</td>\n",
       "      <td>2.539</td>\n",
       "      <td>9.65</td>\n",
       "      <td>116.7</td>\n",
       "      <td>20:57:51</td>\n",
       "      <td>unleaded</td>\n",
       "      <td>yes</td>\n",
       "      <td>30.710526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-08-14</th>\n",
       "      <td>Lukoil</td>\n",
       "      <td>Highland Park</td>\n",
       "      <td>NJ</td>\n",
       "      <td>8904</td>\n",
       "      <td>13.918</td>\n",
       "      <td>2.559</td>\n",
       "      <td>35.62</td>\n",
       "      <td>427.5</td>\n",
       "      <td>15:51:00</td>\n",
       "      <td>unleaded</td>\n",
       "      <td>yes</td>\n",
       "      <td>30.715620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-09-01</th>\n",
       "      <td>Wawa</td>\n",
       "      <td>Hacketstown</td>\n",
       "      <td>NJ</td>\n",
       "      <td>7840</td>\n",
       "      <td>7.816</td>\n",
       "      <td>2.459</td>\n",
       "      <td>19.22</td>\n",
       "      <td>201.6</td>\n",
       "      <td>13:43:30</td>\n",
       "      <td>unleaded</td>\n",
       "      <td>yes</td>\n",
       "      <td>25.793245</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-09-14</th>\n",
       "      <td>Delta</td>\n",
       "      <td>Long Valley</td>\n",
       "      <td>NJ</td>\n",
       "      <td>7853</td>\n",
       "      <td>7.812</td>\n",
       "      <td>2.779</td>\n",
       "      <td>21.71</td>\n",
       "      <td>192.6</td>\n",
       "      <td>20:28:00</td>\n",
       "      <td>unleaded</td>\n",
       "      <td>yes</td>\n",
       "      <td>24.654378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-10-01</th>\n",
       "      <td>Wawa</td>\n",
       "      <td>Hacketstown</td>\n",
       "      <td>NJ</td>\n",
       "      <td>7840</td>\n",
       "      <td>13.916</td>\n",
       "      <td>2.419</td>\n",
       "      <td>33.66</td>\n",
       "      <td>350.7</td>\n",
       "      <td>11:46:59</td>\n",
       "      <td>unleaded</td>\n",
       "      <td>yes</td>\n",
       "      <td>25.201207</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-10-11</th>\n",
       "      <td>Wawa</td>\n",
       "      <td>Hacketstown</td>\n",
       "      <td>NJ</td>\n",
       "      <td>7840</td>\n",
       "      <td>5.412</td>\n",
       "      <td>2.379</td>\n",
       "      <td>12.88</td>\n",
       "      <td>118.7</td>\n",
       "      <td>14:53:52</td>\n",
       "      <td>unleaded</td>\n",
       "      <td>yes</td>\n",
       "      <td>21.932742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-11-02</th>\n",
       "      <td>Wawa</td>\n",
       "      <td>Somerset</td>\n",
       "      <td>NJ</td>\n",
       "      <td>8873</td>\n",
       "      <td>14.441</td>\n",
       "      <td>2.499</td>\n",
       "      <td>46.09</td>\n",
       "      <td>356.1</td>\n",
       "      <td>09:09:38</td>\n",
       "      <td>unleaded</td>\n",
       "      <td>yes</td>\n",
       "      <td>24.658957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-11-08</th>\n",
       "      <td>Wawa</td>\n",
       "      <td>Hacketstown</td>\n",
       "      <td>NJ</td>\n",
       "      <td>7840</td>\n",
       "      <td>7.515</td>\n",
       "      <td>2.459</td>\n",
       "      <td>18.48</td>\n",
       "      <td>186.2</td>\n",
       "      <td>15:51:54</td>\n",
       "      <td>unleaded</td>\n",
       "      <td>yes</td>\n",
       "      <td>24.777112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-11-22</th>\n",
       "      <td>Delta</td>\n",
       "      <td>Long Valley</td>\n",
       "      <td>NJ</td>\n",
       "      <td>7853</td>\n",
       "      <td>11.226</td>\n",
       "      <td>2.679</td>\n",
       "      <td>30.07</td>\n",
       "      <td>255.8</td>\n",
       "      <td>20:21:00</td>\n",
       "      <td>unleaded</td>\n",
       "      <td>yes</td>\n",
       "      <td>22.786389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-11-29</th>\n",
       "      <td>Wawa</td>\n",
       "      <td>Hacketstown</td>\n",
       "      <td>NJ</td>\n",
       "      <td>7840</td>\n",
       "      <td>14.186</td>\n",
       "      <td>2.379</td>\n",
       "      <td>33.75</td>\n",
       "      <td>381.2</td>\n",
       "      <td>07:48:44</td>\n",
       "      <td>unleaded</td>\n",
       "      <td>yes</td>\n",
       "      <td>26.871564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-13</th>\n",
       "      <td>Wawa</td>\n",
       "      <td>Hacketstown</td>\n",
       "      <td>NJ</td>\n",
       "      <td>7840</td>\n",
       "      <td>13.604</td>\n",
       "      <td>2.359</td>\n",
       "      <td>32.09</td>\n",
       "      <td>304.5</td>\n",
       "      <td>13:33:32</td>\n",
       "      <td>unleaded</td>\n",
       "      <td>yes</td>\n",
       "      <td>22.383123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-18</th>\n",
       "      <td>Wawa</td>\n",
       "      <td>Hacketstown</td>\n",
       "      <td>NJ</td>\n",
       "      <td>7840</td>\n",
       "      <td>7.144</td>\n",
       "      <td>2.359</td>\n",
       "      <td>16.85</td>\n",
       "      <td>170.1</td>\n",
       "      <td>13:34:59</td>\n",
       "      <td>unleaded</td>\n",
       "      <td>yes</td>\n",
       "      <td>23.810190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-23</th>\n",
       "      <td>Exxon</td>\n",
       "      <td>Randolph</td>\n",
       "      <td>NJ</td>\n",
       "      <td>7869</td>\n",
       "      <td>5.497</td>\n",
       "      <td>2.699</td>\n",
       "      <td>14.84</td>\n",
       "      <td>140.2</td>\n",
       "      <td>11:13:22</td>\n",
       "      <td>regular</td>\n",
       "      <td>yes</td>\n",
       "      <td>25.504821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-02</th>\n",
       "      <td>Wawa</td>\n",
       "      <td>Hacketstown</td>\n",
       "      <td>NJ</td>\n",
       "      <td>7840</td>\n",
       "      <td>8.450</td>\n",
       "      <td>2.519</td>\n",
       "      <td>21.29</td>\n",
       "      <td>240.5</td>\n",
       "      <td>16:19:07</td>\n",
       "      <td>unleaded</td>\n",
       "      <td>yes</td>\n",
       "      <td>28.461538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-08</th>\n",
       "      <td>Wawa</td>\n",
       "      <td>Somerset</td>\n",
       "      <td>NJ</td>\n",
       "      <td>8873</td>\n",
       "      <td>13.787</td>\n",
       "      <td>2.539</td>\n",
       "      <td>35.01</td>\n",
       "      <td>374.7</td>\n",
       "      <td>15:39:07</td>\n",
       "      <td>unleaded</td>\n",
       "      <td>yes</td>\n",
       "      <td>27.177776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-30</th>\n",
       "      <td>Delta</td>\n",
       "      <td>Randolph</td>\n",
       "      <td>NJ</td>\n",
       "      <td>7869</td>\n",
       "      <td>18.427</td>\n",
       "      <td>2.599</td>\n",
       "      <td>36.20</td>\n",
       "      <td>442.5</td>\n",
       "      <td>14:15:00</td>\n",
       "      <td>unleaded</td>\n",
       "      <td>yes</td>\n",
       "      <td>24.013676</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-20</th>\n",
       "      <td>Wawa</td>\n",
       "      <td>Piscataway</td>\n",
       "      <td>NJ</td>\n",
       "      <td>8854</td>\n",
       "      <td>10.124</td>\n",
       "      <td>2.339</td>\n",
       "      <td>23.68</td>\n",
       "      <td>209.9</td>\n",
       "      <td>15:28:04</td>\n",
       "      <td>unleaded</td>\n",
       "      <td>yes</td>\n",
       "      <td>20.732912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-23</th>\n",
       "      <td>Citgo</td>\n",
       "      <td>Lisbon</td>\n",
       "      <td>CT</td>\n",
       "      <td>6351</td>\n",
       "      <td>8.643</td>\n",
       "      <td>2.379</td>\n",
       "      <td>20.56</td>\n",
       "      <td>231.3</td>\n",
       "      <td>11:50:00</td>\n",
       "      <td>regular</td>\n",
       "      <td>yes</td>\n",
       "      <td>26.761541</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              company             town state    zip  gallons  price   sale  \\\n",
       "date                                                                         \n",
       "2019-05-20      Delta      Long Valley    NJ   7853    7.332  2.979  21.84   \n",
       "2019-05-25      Delta      Long Valley    NJ   7853    9.607  2.979  28.62   \n",
       "2019-06-02   7-Eleven         Somerset    NJ   7883    7.172  2.739  19.64   \n",
       "2019-06-21       Wawa           Elkton    MD  21921    7.347  2.449  17.99   \n",
       "2019-06-25       Wawa      Hacketstown    NJ   7840    8.273  2.639  21.83   \n",
       "2019-06-28       Wawa      Hacketstown    NJ   7840    7.954  2.759  21.95   \n",
       "2019-07-03         BP        Ledgewood    NJ   7852    7.905  2.619  20.70   \n",
       "2019-07-12    Phillip      Long Valley    NJ   7853    5.844  2.979  14.43   \n",
       "2019-07-26       Wawa           Elkton    MD  21921   14.173  2.469  34.99   \n",
       "2019-07-27  QuickChek  North Brunswick    NJ   8902    4.510  2.559  11.54   \n",
       "2019-08-02       Wawa           Elkton    MD  21921   10.947  2.499  27.36   \n",
       "2019-08-04       Wawa         Somerset    NJ   8873    3.800  2.539   9.65   \n",
       "2019-08-14     Lukoil    Highland Park    NJ   8904   13.918  2.559  35.62   \n",
       "2019-09-01       Wawa      Hacketstown    NJ   7840    7.816  2.459  19.22   \n",
       "2019-09-14      Delta      Long Valley    NJ   7853    7.812  2.779  21.71   \n",
       "2019-10-01       Wawa      Hacketstown    NJ   7840   13.916  2.419  33.66   \n",
       "2019-10-11       Wawa      Hacketstown    NJ   7840    5.412  2.379  12.88   \n",
       "2019-11-02       Wawa         Somerset    NJ   8873   14.441  2.499  46.09   \n",
       "2019-11-08       Wawa      Hacketstown    NJ   7840    7.515  2.459  18.48   \n",
       "2019-11-22      Delta      Long Valley    NJ   7853   11.226  2.679  30.07   \n",
       "2019-11-29       Wawa      Hacketstown    NJ   7840   14.186  2.379  33.75   \n",
       "2019-12-13       Wawa      Hacketstown    NJ   7840   13.604  2.359  32.09   \n",
       "2019-12-18       Wawa      Hacketstown    NJ   7840    7.144  2.359  16.85   \n",
       "2019-12-23      Exxon         Randolph    NJ   7869    5.497  2.699  14.84   \n",
       "2020-01-02       Wawa      Hacketstown    NJ   7840    8.450  2.519  21.29   \n",
       "2020-01-08       Wawa         Somerset    NJ   8873   13.787  2.539  35.01   \n",
       "2020-01-30      Delta         Randolph    NJ   7869   18.427  2.599  36.20   \n",
       "2020-02-20       Wawa       Piscataway    NJ   8854   10.124  2.339  23.68   \n",
       "2020-02-23      Citgo           Lisbon    CT   6351    8.643  2.379  20.56   \n",
       "\n",
       "            miles      time   product fillup        mpg  \n",
       "date                                                     \n",
       "2019-05-20    NaN  20:13:00  unleaded    yes        NaN  \n",
       "2019-05-25  229.0  12:20:00  unleaded    yes  23.836786  \n",
       "2019-06-02    NaN  14:43:00   regular    yes        NaN  \n",
       "2019-06-21    NaN  20:46:12  unleaded    yes        NaN  \n",
       "2019-06-25  204.0  16:05:26  unleaded    yes  24.658528  \n",
       "2019-06-28  184.0  17:16:42  unleaded    yes  23.133015  \n",
       "2019-07-03  172.6  10:26:00  unleaded    yes  21.834282  \n",
       "2019-07-12  160.9  10:16:00   regular    yes  27.532512  \n",
       "2019-07-26  414.7  21:40:47  unleaded    yes  29.259860  \n",
       "2019-07-27  138.2  19:29:55   regular    yes  30.643016  \n",
       "2019-08-02  325.8  20:33:53  unleaded    yes  29.761579  \n",
       "2019-08-04  116.7  20:57:51  unleaded    yes  30.710526  \n",
       "2019-08-14  427.5  15:51:00  unleaded    yes  30.715620  \n",
       "2019-09-01  201.6  13:43:30  unleaded    yes  25.793245  \n",
       "2019-09-14  192.6  20:28:00  unleaded    yes  24.654378  \n",
       "2019-10-01  350.7  11:46:59  unleaded    yes  25.201207  \n",
       "2019-10-11  118.7  14:53:52  unleaded    yes  21.932742  \n",
       "2019-11-02  356.1  09:09:38  unleaded    yes  24.658957  \n",
       "2019-11-08  186.2  15:51:54  unleaded    yes  24.777112  \n",
       "2019-11-22  255.8  20:21:00  unleaded    yes  22.786389  \n",
       "2019-11-29  381.2  07:48:44  unleaded    yes  26.871564  \n",
       "2019-12-13  304.5  13:33:32  unleaded    yes  22.383123  \n",
       "2019-12-18  170.1  13:34:59  unleaded    yes  23.810190  \n",
       "2019-12-23  140.2  11:13:22   regular    yes  25.504821  \n",
       "2020-01-02  240.5  16:19:07  unleaded    yes  28.461538  \n",
       "2020-01-08  374.7  15:39:07  unleaded    yes  27.177776  \n",
       "2020-01-30  442.5  14:15:00  unleaded    yes  24.013676  \n",
       "2020-02-20  209.9  15:28:04  unleaded    yes  20.732912  \n",
       "2020-02-23  231.3  11:50:00   regular    yes  26.761541  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = data.dropna(subset=[\"miles\"])\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(10, 7))\n",
    "\n",
    "ax.plot(df.index.values,\n",
    "        df[\"mpg\"], \"-o\",\n",
    "        color=\"purple\")\n",
    "\n",
    "ax.set(#xlabel=\"Date\",\n",
    "       #ylabel=\"Miles Per Gallon\",\n",
    "       title=\"Miles Per Gallon over Time\")\n",
    "\n",
    "ax.xaxis.set_major_locator(mdates.WeekdayLocator(interval=5))\n",
    "ax.xaxis.set_major_formatter(DateFormatter(\"%m/%d\"))\n",
    "\n",
    "plt.savefig(\"./figures/mpg_time.png\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>company</th>\n",
       "      <th>town</th>\n",
       "      <th>state</th>\n",
       "      <th>zip</th>\n",
       "      <th>gallons</th>\n",
       "      <th>price</th>\n",
       "      <th>sale</th>\n",
       "      <th>miles</th>\n",
       "      <th>time</th>\n",
       "      <th>product</th>\n",
       "      <th>fillup</th>\n",
       "      <th>mpg</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-05-25</th>\n",
       "      <td>Delta</td>\n",
       "      <td>Long Valley</td>\n",
       "      <td>NJ</td>\n",
       "      <td>7853</td>\n",
       "      <td>9.607</td>\n",
       "      <td>2.979</td>\n",
       "      <td>28.62</td>\n",
       "      <td>229.0</td>\n",
       "      <td>12:20:00</td>\n",
       "      <td>unleaded</td>\n",
       "      <td>yes</td>\n",
       "      <td>23.836786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-25</th>\n",
       "      <td>Wawa</td>\n",
       "      <td>Hacketstown</td>\n",
       "      <td>NJ</td>\n",
       "      <td>7840</td>\n",
       "      <td>8.273</td>\n",
       "      <td>2.639</td>\n",
       "      <td>21.83</td>\n",
       "      <td>204.0</td>\n",
       "      <td>16:05:26</td>\n",
       "      <td>unleaded</td>\n",
       "      <td>yes</td>\n",
       "      <td>24.658528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-28</th>\n",
       "      <td>Wawa</td>\n",
       "      <td>Hacketstown</td>\n",
       "      <td>NJ</td>\n",
       "      <td>7840</td>\n",
       "      <td>7.954</td>\n",
       "      <td>2.759</td>\n",
       "      <td>21.95</td>\n",
       "      <td>184.0</td>\n",
       "      <td>17:16:42</td>\n",
       "      <td>unleaded</td>\n",
       "      <td>yes</td>\n",
       "      <td>23.133015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-03</th>\n",
       "      <td>BP</td>\n",
       "      <td>Ledgewood</td>\n",
       "      <td>NJ</td>\n",
       "      <td>7852</td>\n",
       "      <td>7.905</td>\n",
       "      <td>2.619</td>\n",
       "      <td>20.70</td>\n",
       "      <td>172.6</td>\n",
       "      <td>10:26:00</td>\n",
       "      <td>unleaded</td>\n",
       "      <td>yes</td>\n",
       "      <td>21.834282</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-12</th>\n",
       "      <td>Phillip</td>\n",
       "      <td>Long Valley</td>\n",
       "      <td>NJ</td>\n",
       "      <td>7853</td>\n",
       "      <td>5.844</td>\n",
       "      <td>2.979</td>\n",
       "      <td>14.43</td>\n",
       "      <td>160.9</td>\n",
       "      <td>10:16:00</td>\n",
       "      <td>regular</td>\n",
       "      <td>yes</td>\n",
       "      <td>27.532512</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            company         town state   zip  gallons  price   sale  miles  \\\n",
       "date                                                                         \n",
       "2019-05-25    Delta  Long Valley    NJ  7853    9.607  2.979  28.62  229.0   \n",
       "2019-06-25     Wawa  Hacketstown    NJ  7840    8.273  2.639  21.83  204.0   \n",
       "2019-06-28     Wawa  Hacketstown    NJ  7840    7.954  2.759  21.95  184.0   \n",
       "2019-07-03       BP    Ledgewood    NJ  7852    7.905  2.619  20.70  172.6   \n",
       "2019-07-12  Phillip  Long Valley    NJ  7853    5.844  2.979  14.43  160.9   \n",
       "\n",
       "                time   product fillup        mpg  \n",
       "date                                              \n",
       "2019-05-25  12:20:00  unleaded    yes  23.836786  \n",
       "2019-06-25  16:05:26  unleaded    yes  24.658528  \n",
       "2019-06-28  17:16:42  unleaded    yes  23.133015  \n",
       "2019-07-03  10:26:00  unleaded    yes  21.834282  \n",
       "2019-07-12  10:16:00   regular    yes  27.532512  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}