tip_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "2193a718-3085-4c9a-92da-326b4e8a477b",
   "metadata": {},
   "source": [
    "# NYC Trips: Tip Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8d9ccee7-a467-43e6-ad11-9bb7065193f1",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from taxitools import utils"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3575a0a0-124b-4514-875f-a332cf67a677",
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>VendorID</th>\n",
       "      <th>lpep_pickup_datetime</th>\n",
       "      <th>lpep_dropoff_datetime</th>\n",
       "      <th>store_and_fwd_flag</th>\n",
       "      <th>RatecodeID</th>\n",
       "      <th>PULocationID</th>\n",
       "      <th>DOLocationID</th>\n",
       "      <th>passenger_count</th>\n",
       "      <th>trip_distance</th>\n",
       "      <th>fare_amount</th>\n",
       "      <th>...</th>\n",
       "      <th>total_amount</th>\n",
       "      <th>payment_type</th>\n",
       "      <th>trip_type</th>\n",
       "      <th>congestion_surcharge</th>\n",
       "      <th>day_of_week</th>\n",
       "      <th>day_of_month</th>\n",
       "      <th>hour_of_day</th>\n",
       "      <th>trip_duration</th>\n",
       "      <th>total_without_tip</th>\n",
       "      <th>fare_per_mile</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2021-07-01 00:30:52</td>\n",
       "      <td>2021-07-01 00:35:36</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>74</td>\n",
       "      <td>168</td>\n",
       "      <td>1</td>\n",
       "      <td>1.20</td>\n",
       "      <td>6.00</td>\n",
       "      <td>...</td>\n",
       "      <td>7.30</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>284.0</td>\n",
       "      <td>7.30</td>\n",
       "      <td>6.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2021-07-01 00:25:36</td>\n",
       "      <td>2021-07-01 01:01:31</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>116</td>\n",
       "      <td>265</td>\n",
       "      <td>2</td>\n",
       "      <td>13.69</td>\n",
       "      <td>42.00</td>\n",
       "      <td>...</td>\n",
       "      <td>43.30</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2155.0</td>\n",
       "      <td>43.30</td>\n",
       "      <td>3.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>2021-07-01 00:05:58</td>\n",
       "      <td>2021-07-01 00:12:00</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>97</td>\n",
       "      <td>33</td>\n",
       "      <td>1</td>\n",
       "      <td>0.95</td>\n",
       "      <td>6.50</td>\n",
       "      <td>...</td>\n",
       "      <td>10.14</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>362.0</td>\n",
       "      <td>7.80</td>\n",
       "      <td>8.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>2021-07-01 00:41:40</td>\n",
       "      <td>2021-07-01 00:47:23</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>74</td>\n",
       "      <td>42</td>\n",
       "      <td>1</td>\n",
       "      <td>1.24</td>\n",
       "      <td>6.50</td>\n",
       "      <td>...</td>\n",
       "      <td>7.80</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>343.0</td>\n",
       "      <td>7.80</td>\n",
       "      <td>6.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>2021-07-01 00:51:32</td>\n",
       "      <td>2021-07-01 00:58:46</td>\n",
       "      <td>N</td>\n",
       "      <td>1</td>\n",
       "      <td>42</td>\n",
       "      <td>244</td>\n",
       "      <td>1</td>\n",
       "      <td>1.10</td>\n",
       "      <td>7.00</td>\n",
       "      <td>...</td>\n",
       "      <td>8.30</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>434.0</td>\n",
       "      <td>8.30</td>\n",
       "      <td>7.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79965</th>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>2021-07-02 07:59:00</td>\n",
       "      <td>2021-07-02 08:33:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>218</td>\n",
       "      <td>169</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>18.04</td>\n",
       "      <td>50.24</td>\n",
       "      <td>...</td>\n",
       "      <td>59.84</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>2040.0</td>\n",
       "      <td>59.84</td>\n",
       "      <td>3.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79966</th>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>2021-07-02 07:02:00</td>\n",
       "      <td>2021-07-02 07:18:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>74</td>\n",
       "      <td>137</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>5.56</td>\n",
       "      <td>19.16</td>\n",
       "      <td>...</td>\n",
       "      <td>25.87</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>960.0</td>\n",
       "      <td>22.21</td>\n",
       "      <td>3.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79967</th>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>2021-07-02 07:53:00</td>\n",
       "      <td>2021-07-02 08:15:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>69</td>\n",
       "      <td>75</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>5.13</td>\n",
       "      <td>22.45</td>\n",
       "      <td>...</td>\n",
       "      <td>22.75</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>1320.0</td>\n",
       "      <td>22.75</td>\n",
       "      <td>4.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79968</th>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>2021-07-02 07:58:00</td>\n",
       "      <td>2021-07-02 08:30:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>117</td>\n",
       "      <td>82</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>12.58</td>\n",
       "      <td>48.62</td>\n",
       "      <td>...</td>\n",
       "      <td>54.12</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>1920.0</td>\n",
       "      <td>54.12</td>\n",
       "      <td>4.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79969</th>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>2021-07-02 07:00:00</td>\n",
       "      <td>2021-07-02 07:26:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>218</td>\n",
       "      <td>196</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>11.32</td>\n",
       "      <td>45.84</td>\n",
       "      <td>...</td>\n",
       "      <td>48.89</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>1560.0</td>\n",
       "      <td>48.89</td>\n",
       "      <td>4.32</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>79970 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       VendorID lpep_pickup_datetime lpep_dropoff_datetime store_and_fwd_flag  \\\n",
       "0             1  2021-07-01 00:30:52   2021-07-01 00:35:36                  N   \n",
       "1             2  2021-07-01 00:25:36   2021-07-01 01:01:31                  N   \n",
       "2             2  2021-07-01 00:05:58   2021-07-01 00:12:00                  N   \n",
       "3             2  2021-07-01 00:41:40   2021-07-01 00:47:23                  N   \n",
       "4             2  2021-07-01 00:51:32   2021-07-01 00:58:46                  N   \n",
       "...         ...                  ...                   ...                ...   \n",
       "79965      <NA>  2021-07-02 07:59:00   2021-07-02 08:33:00                NaN   \n",
       "79966      <NA>  2021-07-02 07:02:00   2021-07-02 07:18:00                NaN   \n",
       "79967      <NA>  2021-07-02 07:53:00   2021-07-02 08:15:00                NaN   \n",
       "79968      <NA>  2021-07-02 07:58:00   2021-07-02 08:30:00                NaN   \n",
       "79969      <NA>  2021-07-02 07:00:00   2021-07-02 07:26:00                NaN   \n",
       "\n",
       "       RatecodeID  PULocationID  DOLocationID  passenger_count  trip_distance  \\\n",
       "0               1            74           168                1           1.20   \n",
       "1               1           116           265                2          13.69   \n",
       "2               1            97            33                1           0.95   \n",
       "3               1            74            42                1           1.24   \n",
       "4               1            42           244                1           1.10   \n",
       "...           ...           ...           ...              ...            ...   \n",
       "79965        <NA>           218           169             <NA>          18.04   \n",
       "79966        <NA>            74           137             <NA>           5.56   \n",
       "79967        <NA>            69            75             <NA>           5.13   \n",
       "79968        <NA>           117            82             <NA>          12.58   \n",
       "79969        <NA>           218           196             <NA>          11.32   \n",
       "\n",
       "       fare_amount  ...  total_amount  payment_type  trip_type  \\\n",
       "0             6.00  ...          7.30             2          1   \n",
       "1            42.00  ...         43.30             2          1   \n",
       "2             6.50  ...         10.14             1          1   \n",
       "3             6.50  ...          7.80             2          1   \n",
       "4             7.00  ...          8.30             2          1   \n",
       "...            ...  ...           ...           ...        ...   \n",
       "79965        50.24  ...         59.84          <NA>       <NA>   \n",
       "79966        19.16  ...         25.87          <NA>       <NA>   \n",
       "79967        22.45  ...         22.75          <NA>       <NA>   \n",
       "79968        48.62  ...         54.12          <NA>       <NA>   \n",
       "79969        45.84  ...         48.89          <NA>       <NA>   \n",
       "\n",
       "       congestion_surcharge  day_of_week  day_of_month  hour_of_day  \\\n",
       "0                       0.0            3             1            0   \n",
       "1                       0.0            3             1            0   \n",
       "2                       0.0            3             1            0   \n",
       "3                       0.0            3             1            0   \n",
       "4                       0.0            3             1            0   \n",
       "...                     ...          ...           ...          ...   \n",
       "79965                   NaN            4             2            7   \n",
       "79966                   NaN            4             2            7   \n",
       "79967                   NaN            4             2            7   \n",
       "79968                   NaN            4             2            7   \n",
       "79969                   NaN            4             2            7   \n",
       "\n",
       "       trip_duration  total_without_tip  fare_per_mile  \n",
       "0              284.0               7.30           6.08  \n",
       "1             2155.0              43.30           3.16  \n",
       "2              362.0               7.80           8.21  \n",
       "3              343.0               7.80           6.29  \n",
       "4              434.0               8.30           7.55  \n",
       "...              ...                ...            ...  \n",
       "79965         2040.0              59.84           3.32  \n",
       "79966          960.0              22.21           3.99  \n",
       "79967         1320.0              22.75           4.43  \n",
       "79968         1920.0              54.12           4.30  \n",
       "79969         1560.0              48.89           4.32  \n",
       "\n",
       "[79970 rows x 25 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = utils.open_taxi_clean_df()\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "02073bcf-2d64-4be2-9b4d-27266cff30ad",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>VendorID</th>\n",
       "      <th>RatecodeID</th>\n",
       "      <th>PULocationID</th>\n",
       "      <th>DOLocationID</th>\n",
       "      <th>passenger_count</th>\n",
       "      <th>trip_distance</th>\n",
       "      <th>fare_amount</th>\n",
       "      <th>extra</th>\n",
       "      <th>mta_tax</th>\n",
       "      <th>tip_amount</th>\n",
       "      <th>...</th>\n",
       "      <th>total_amount</th>\n",
       "      <th>payment_type</th>\n",
       "      <th>trip_type</th>\n",
       "      <th>congestion_surcharge</th>\n",
       "      <th>day_of_week</th>\n",
       "      <th>day_of_month</th>\n",
       "      <th>hour_of_day</th>\n",
       "      <th>trip_duration</th>\n",
       "      <th>total_without_tip</th>\n",
       "      <th>fare_per_mile</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>48106.000000</td>\n",
       "      <td>48106.000000</td>\n",
       "      <td>79970.000000</td>\n",
       "      <td>79970.000000</td>\n",
       "      <td>48106.000000</td>\n",
       "      <td>79970.000000</td>\n",
       "      <td>79970.000000</td>\n",
       "      <td>79970.000000</td>\n",
       "      <td>79970.000000</td>\n",
       "      <td>79970.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>79970.000000</td>\n",
       "      <td>48106.000000</td>\n",
       "      <td>48106.000000</td>\n",
       "      <td>48106.000000</td>\n",
       "      <td>79970.000000</td>\n",
       "      <td>79970.000000</td>\n",
       "      <td>79970.000000</td>\n",
       "      <td>79970.000000</td>\n",
       "      <td>79970.000000</td>\n",
       "      <td>79970.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.876627</td>\n",
       "      <td>1.111046</td>\n",
       "      <td>107.175616</td>\n",
       "      <td>132.764262</td>\n",
       "      <td>1.321228</td>\n",
       "      <td>203.368217</td>\n",
       "      <td>20.544204</td>\n",
       "      <td>1.188638</td>\n",
       "      <td>0.294585</td>\n",
       "      <td>1.079694</td>\n",
       "      <td>...</td>\n",
       "      <td>24.435212</td>\n",
       "      <td>1.423087</td>\n",
       "      <td>1.022866</td>\n",
       "      <td>0.681739</td>\n",
       "      <td>3.002063</td>\n",
       "      <td>16.177104</td>\n",
       "      <td>13.246755</td>\n",
       "      <td>1472.306165</td>\n",
       "      <td>23.355518</td>\n",
       "      <td>12.454450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.328869</td>\n",
       "      <td>0.647572</td>\n",
       "      <td>69.793481</td>\n",
       "      <td>77.020361</td>\n",
       "      <td>1.006507</td>\n",
       "      <td>4506.677352</td>\n",
       "      <td>15.454022</td>\n",
       "      <td>1.371409</td>\n",
       "      <td>0.245994</td>\n",
       "      <td>2.323399</td>\n",
       "      <td>...</td>\n",
       "      <td>17.143430</td>\n",
       "      <td>0.503143</td>\n",
       "      <td>0.149478</td>\n",
       "      <td>1.187436</td>\n",
       "      <td>1.850509</td>\n",
       "      <td>8.992790</td>\n",
       "      <td>4.932357</td>\n",
       "      <td>4680.007349</td>\n",
       "      <td>16.892298</td>\n",
       "      <td>103.603567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>0.080000</td>\n",
       "      <td>-2.750000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.380000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.380000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>55.000000</td>\n",
       "      <td>69.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.480000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>11.800000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>539.000000</td>\n",
       "      <td>10.800000</td>\n",
       "      <td>4.290000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>75.000000</td>\n",
       "      <td>132.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.900000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>19.880000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>901.000000</td>\n",
       "      <td>18.550000</td>\n",
       "      <td>5.620000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>166.000000</td>\n",
       "      <td>203.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.430000</td>\n",
       "      <td>27.000000</td>\n",
       "      <td>2.750000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>1.750000</td>\n",
       "      <td>...</td>\n",
       "      <td>31.350000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>1560.000000</td>\n",
       "      <td>30.300000</td>\n",
       "      <td>7.520000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>265.000000</td>\n",
       "      <td>265.000000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>260517.930000</td>\n",
       "      <td>359.500000</td>\n",
       "      <td>8.250000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>87.710000</td>\n",
       "      <td>...</td>\n",
       "      <td>443.370000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.750000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>86326.000000</td>\n",
       "      <td>369.800000</td>\n",
       "      <td>7898.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           VendorID    RatecodeID  PULocationID  DOLocationID  \\\n",
       "count  48106.000000  48106.000000  79970.000000  79970.000000   \n",
       "mean       1.876627      1.111046    107.175616    132.764262   \n",
       "std        0.328869      0.647572     69.793481     77.020361   \n",
       "min        1.000000      1.000000      3.000000      1.000000   \n",
       "25%        2.000000      1.000000     55.000000     69.000000   \n",
       "50%        2.000000      1.000000     75.000000    132.000000   \n",
       "75%        2.000000      1.000000    166.000000    203.000000   \n",
       "max        2.000000      5.000000    265.000000    265.000000   \n",
       "\n",
       "       passenger_count  trip_distance   fare_amount         extra  \\\n",
       "count     48106.000000   79970.000000  79970.000000  79970.000000   \n",
       "mean          1.321228     203.368217     20.544204      1.188638   \n",
       "std           1.006507    4506.677352     15.454022      1.371409   \n",
       "min           0.000000       0.010000      0.080000     -2.750000   \n",
       "25%           1.000000       1.480000      9.000000      0.000000   \n",
       "50%           1.000000       2.900000     16.000000      0.500000   \n",
       "75%           1.000000       6.430000     27.000000      2.750000   \n",
       "max          32.000000  260517.930000    359.500000      8.250000   \n",
       "\n",
       "            mta_tax    tip_amount  ...  total_amount  payment_type  \\\n",
       "count  79970.000000  79970.000000  ...  79970.000000  48106.000000   \n",
       "mean       0.294585      1.079694  ...     24.435212      1.423087   \n",
       "std        0.245994      2.323399  ...     17.143430      0.503143   \n",
       "min        0.000000      0.000000  ...      0.380000      1.000000   \n",
       "25%        0.000000      0.000000  ...     11.800000      1.000000   \n",
       "50%        0.500000      0.000000  ...     19.880000      1.000000   \n",
       "75%        0.500000      1.750000  ...     31.350000      2.000000   \n",
       "max        0.500000     87.710000  ...    443.370000      5.000000   \n",
       "\n",
       "          trip_type  congestion_surcharge   day_of_week  day_of_month  \\\n",
       "count  48106.000000          48106.000000  79970.000000  79970.000000   \n",
       "mean       1.022866              0.681739      3.002063     16.177104   \n",
       "std        0.149478              1.187436      1.850509      8.992790   \n",
       "min        1.000000              0.000000      0.000000      1.000000   \n",
       "25%        1.000000              0.000000      1.000000      8.000000   \n",
       "50%        1.000000              0.000000      3.000000     16.000000   \n",
       "75%        1.000000              0.000000      4.000000     24.000000   \n",
       "max        2.000000              2.750000      6.000000     31.000000   \n",
       "\n",
       "        hour_of_day  trip_duration  total_without_tip  fare_per_mile  \n",
       "count  79970.000000   79970.000000       79970.000000   79970.000000  \n",
       "mean      13.246755    1472.306165          23.355518      12.454450  \n",
       "std        4.932357    4680.007349          16.892298     103.603567  \n",
       "min        0.000000       0.000000           0.380000       0.000000  \n",
       "25%       10.000000     539.000000          10.800000       4.290000  \n",
       "50%       13.000000     901.000000          18.550000       5.620000  \n",
       "75%       17.000000    1560.000000          30.300000       7.520000  \n",
       "max       23.000000   86326.000000         369.800000    7898.000000  \n",
       "\n",
       "[8 rows x 22 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0d2fab5-aff2-4d57-82f0-f006d84a59dc",
   "metadata": {},
   "source": [
    "## Filtering Out Unwanted Values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "567e740d-c8b2-4c9c-88a5-e52bd5ee7fcb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['VendorID', 'lpep_pickup_datetime', 'lpep_dropoff_datetime',\n",
       "       'store_and_fwd_flag', 'RatecodeID', 'PULocationID', 'DOLocationID',\n",
       "       'passenger_count', 'trip_distance', 'fare_amount', 'extra', 'mta_tax',\n",
       "       'tip_amount', 'tolls_amount', 'improvement_surcharge', 'total_amount',\n",
       "       'payment_type', 'trip_type', 'congestion_surcharge', 'day_of_week',\n",
       "       'day_of_month', 'hour_of_day', 'trip_duration', 'total_without_tip',\n",
       "       'fare_per_mile'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df[df.tip_amount > 0]\n",
    "df = df[df.passenger_count.notnull()]\n",
    "df.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a593dec5-5a0f-4fec-8e4a-eeb49734a1b1",
   "metadata": {},
   "source": [
    "## Groupby Averages, Unique Values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d8d4c141-6bfa-40a4-85ca-c77638f37532",
   "metadata": {},
   "outputs": [],
   "source": [
    "distance_avgs = utils.aggregateAndGroup(df,'trip_distance', 'tip_amount',np.mean) \n",
    "fare_avgs = utils.aggregateAndGroup(df,'fare_amount','tip_amount',np.mean)\n",
    "day_avgs = utils.aggregateAndGroup(df,'day_of_week','tip_amount',np.mean)\n",
    "totalfare_avgs = utils.aggregateAndGroup(df,'day_of_week','total_amount',np.mean)\n",
    "\n",
    "\n",
    "# duration_avgs = df.groupby('trip_duration').mean()\n",
    "# passenger_avgs = df.groupby('passenger_count').mean()\n",
    "# vendor_avgs = df.groupby('VendorID').mean()\n",
    "\n",
    "\n",
    "def unique_values(col_name):\n",
    "    output = df[col_name].unique()\n",
    "    output.sort()\n",
    "    return output\n",
    "\n",
    "tips = unique_values('tip_amount')\n",
    "distances = unique_values('trip_distance')\n",
    "fare_amounts = unique_values('fare_amount')\n",
    "days = unique_values('day_of_week')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bda74b9b-b75b-4eb2-8138-3bad7fa95ec5",
   "metadata": {},
   "source": [
    "## Line Graph: Distance vs Tips"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "4482ec45-9977-44f5-b71f-f0d197ae2c9a",
   "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 = distances\n",
    "y = distance_avgs['tip_amount']\n",
    "plt.plot(x,y)\n",
    "plt.xlabel('Trip Distance (Miles)')\n",
    "plt.ylabel('Average Tip Amount (Dollars)')\n",
    "plt.title('Distance vs Avg Tips') \n",
    "plt.xlim([0,40])\n",
    "plt.ylim([0,70])\n",
    "plt.savefig('figures/distance_tips_line')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e9e44183-4997-4bef-bc43-dfd40b08e801",
   "metadata": {},
   "source": [
    "## Scatter Plot: Distance vs Tips"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "3da12b61-d75d-4b04-aa32-4a870b5a4147",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jovyan/envs/hw7env/lib/python3.9/site-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0.6918874573178135"
      ]
     },
     "execution_count": 7,
     "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 = df['trip_distance']\n",
    "y = df['tip_amount']\n",
    "sns.regplot(x, y, scatter_kws={\"color\": \"lightblue\"}, line_kws={\"color\": \"black\"})\n",
    "plt.xlabel('Trip Distance (Miles)')\n",
    "plt.ylabel('Tip Amount (Dollars)')\n",
    "plt.title('Distance vs Tips')\n",
    "plt.xlim([0,40])\n",
    "plt.ylim([0,35])\n",
    "plt.savefig('figures/distance_tips_scatter')\n",
    "np.corrcoef(x,y)[0][1]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b163e50e-e449-4e51-83bc-5b7b058c84de",
   "metadata": {},
   "source": [
    "## Line Graph: Total Fare Amount vs Average Tip Amount"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e0df4ae9-3d00-4d7a-9b28-d47b46cd030f",
   "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 = fare_amounts\n",
    "y = fare_avgs['tip_amount']\n",
    "plt.plot(x,y)\n",
    "plt.xlabel('Total Fare Amount (Dollars)')\n",
    "plt.ylabel('Average Tip Amount (Dollars)')\n",
    "plt.title('Total Fare vs Avg Tip')\n",
    "plt.xlim([0,160])\n",
    "plt.ylim([0,60])\n",
    "plt.savefig('figures/total__fare_line')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "187a9a8e-9074-4579-9fec-51d9dc00e772",
   "metadata": {},
   "source": [
    "## Scatter Plot: Total Fare Amount vs Tip Amount"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8a44130d-29e0-4918-8a78-63b08450da43",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jovyan/envs/hw7env/lib/python3.9/site-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0.8154835771318032"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = df['total_amount']\n",
    "y = df['tip_amount']\n",
    "sns.regplot(x, y, scatter_kws={\"color\": \"lightblue\"}, line_kws={\"color\": \"black\"})\n",
    "plt.xlabel('Total Fare Amount (Dollars)')\n",
    "plt.ylabel('Tip Amount (Dollars)')\n",
    "plt.title('Total Fare vs Tips')\n",
    "plt.xlim([0,100])\n",
    "plt.ylim([0,30])\n",
    "plt.savefig('figures/total__fare_scatter')\n",
    "np.corrcoef(x,y)[0][1]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "107d12db-8dcd-4c31-92c3-ab84dee768d3",
   "metadata": {},
   "source": [
    "## Scatter Plot: Total Fare vs Tip as a % of Total Fare "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "b3b6ab96-702d-4e71-86f1-86e5f5c8b00a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jovyan/envs/hw7env/lib/python3.9/site-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "-0.0034155244881577274"
      ]
     },
     "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": [
    "x = df['total_amount'] \n",
    "y = df['tip_amount'] / df['total_amount']\n",
    "sns.regplot(x, y, scatter_kws={\"color\": \"lightblue\"}, line_kws={\"color\": \"black\"})\n",
    "plt.xlabel('Total Fare Amount (Dollars)')\n",
    "plt.ylabel('Tip as % of Total Fare')\n",
    "plt.title('Total Fare vs Tip Share of Total Fare')\n",
    "plt.xlim([0,100])\n",
    "plt.ylim([0,2])\n",
    "plt.savefig('figures/tipfare_relationship_scatter')\n",
    "np.corrcoef(x,y)[0][1]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b1863dbc-eafd-4026-8a3b-ba4f88f52830",
   "metadata": {},
   "source": [
    "## Bar Graph (Tip Share by Day of Week)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "8817e9ac-b230-4ab5-852d-24810510484d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Tip as % of Total Fare')"
      ]
     },
     "execution_count": 11,
     "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 = days\n",
    "y = day_avgs['tip_amount'] / totalfare_avgs['total_amount']\n",
    "plt.bar(x,y)\n",
    "plt.xlabel('Day of Week')\n",
    "plt.ylabel('Tip as % of Total Fare')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "03ea75c5-51eb-46cb-ac48-ac3975ef583b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "IPython - hw7env",
   "language": "python",
   "name": "hw7env"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}