TestModel.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from sklearn.model_selection import train_test_split\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "from sklearn.linear_model import LinearRegression, LogisticRegression, LassoCV, RidgeCV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv(\"data/taxi_final_final.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Additional Cleaning "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Unnamed: 0.1</th>\n",
       "      <th>vendor_id</th>\n",
       "      <th>pickup_datetime</th>\n",
       "      <th>dropoff_datetime</th>\n",
       "      <th>passenger_count</th>\n",
       "      <th>trip_distance</th>\n",
       "      <th>pickup_longitude</th>\n",
       "      <th>pickup_latitude</th>\n",
       "      <th>dropoff_longitude</th>\n",
       "      <th>...</th>\n",
       "      <th>fare_amount</th>\n",
       "      <th>surcharge</th>\n",
       "      <th>mta_tax</th>\n",
       "      <th>tip_amount</th>\n",
       "      <th>tolls_amount</th>\n",
       "      <th>total_amount</th>\n",
       "      <th>duration</th>\n",
       "      <th>geometry</th>\n",
       "      <th>Man</th>\n",
       "      <th>Location</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 20:45:25</td>\n",
       "      <td>2014-01-09 20:52:31</td>\n",
       "      <td>1</td>\n",
       "      <td>0.7</td>\n",
       "      <td>-73.994770</td>\n",
       "      <td>40.736828</td>\n",
       "      <td>-73.982227</td>\n",
       "      <td>...</td>\n",
       "      <td>6.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.40</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.90</td>\n",
       "      <td>426</td>\n",
       "      <td>POINT (-73.98222699999998 40.73179)</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 20:46:12</td>\n",
       "      <td>2014-01-09 20:55:12</td>\n",
       "      <td>1</td>\n",
       "      <td>1.4</td>\n",
       "      <td>-73.982392</td>\n",
       "      <td>40.773382</td>\n",
       "      <td>-73.960449</td>\n",
       "      <td>...</td>\n",
       "      <td>8.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.90</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.40</td>\n",
       "      <td>540</td>\n",
       "      <td>POINT (-73.96044899999998 40.763995)</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 20:44:47</td>\n",
       "      <td>2014-01-09 20:59:46</td>\n",
       "      <td>2</td>\n",
       "      <td>2.3</td>\n",
       "      <td>-73.988570</td>\n",
       "      <td>40.739406</td>\n",
       "      <td>-73.986626</td>\n",
       "      <td>...</td>\n",
       "      <td>11.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.50</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.00</td>\n",
       "      <td>899</td>\n",
       "      <td>POINT (-73.986626 40.765217)</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 20:44:57</td>\n",
       "      <td>2014-01-09 20:51:40</td>\n",
       "      <td>1</td>\n",
       "      <td>1.7</td>\n",
       "      <td>-73.960213</td>\n",
       "      <td>40.770464</td>\n",
       "      <td>-73.979863</td>\n",
       "      <td>...</td>\n",
       "      <td>7.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.70</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.20</td>\n",
       "      <td>403</td>\n",
       "      <td>POINT (-73.97986299999998 40.77705)</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 20:47:09</td>\n",
       "      <td>2014-01-09 20:53:32</td>\n",
       "      <td>1</td>\n",
       "      <td>0.9</td>\n",
       "      <td>-73.995371</td>\n",
       "      <td>40.717248</td>\n",
       "      <td>-73.984367</td>\n",
       "      <td>...</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.75</td>\n",
       "      <td>383</td>\n",
       "      <td>POINT (-73.98436700000001 40.720524)</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  Unnamed: 0.1 vendor_id      pickup_datetime  \\\n",
       "0           0             0       CMT  2014-01-09 20:45:25   \n",
       "1           1             1       CMT  2014-01-09 20:46:12   \n",
       "2           2             2       CMT  2014-01-09 20:44:47   \n",
       "3           3             3       CMT  2014-01-09 20:44:57   \n",
       "4           4             4       CMT  2014-01-09 20:47:09   \n",
       "\n",
       "      dropoff_datetime  passenger_count  trip_distance  pickup_longitude  \\\n",
       "0  2014-01-09 20:52:31                1            0.7        -73.994770   \n",
       "1  2014-01-09 20:55:12                1            1.4        -73.982392   \n",
       "2  2014-01-09 20:59:46                2            2.3        -73.988570   \n",
       "3  2014-01-09 20:51:40                1            1.7        -73.960213   \n",
       "4  2014-01-09 20:53:32                1            0.9        -73.995371   \n",
       "\n",
       "   pickup_latitude  dropoff_longitude  ...  fare_amount surcharge  mta_tax  \\\n",
       "0        40.736828         -73.982227  ...          6.5       0.5      0.5   \n",
       "1        40.773382         -73.960449  ...          8.5       0.5      0.5   \n",
       "2        40.739406         -73.986626  ...         11.5       0.5      0.5   \n",
       "3        40.770464         -73.979863  ...          7.5       0.5      0.5   \n",
       "4        40.717248         -73.984367  ...          6.0       0.5      0.5   \n",
       "\n",
       "   tip_amount  tolls_amount  total_amount  duration  \\\n",
       "0        1.40           0.0          8.90       426   \n",
       "1        1.90           0.0         11.40       540   \n",
       "2        1.50           0.0         14.00       899   \n",
       "3        1.70           0.0         10.20       403   \n",
       "4        1.75           0.0          8.75       383   \n",
       "\n",
       "                               geometry  Man Location  \n",
       "0   POINT (-73.98222699999998 40.73179)    1        5  \n",
       "1  POINT (-73.96044899999998 40.763995)    1        4  \n",
       "2          POINT (-73.986626 40.765217)    1        5  \n",
       "3   POINT (-73.97986299999998 40.77705)    1        5  \n",
       "4  POINT (-73.98436700000001 40.720524)    1        5  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "del data[\"Unnamed: 0\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "del data[\"Unnamed: 0.1\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "del data[\"Man\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "del data[\"geometry\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>vendor_id</th>\n",
       "      <th>pickup_datetime</th>\n",
       "      <th>dropoff_datetime</th>\n",
       "      <th>passenger_count</th>\n",
       "      <th>trip_distance</th>\n",
       "      <th>pickup_longitude</th>\n",
       "      <th>pickup_latitude</th>\n",
       "      <th>dropoff_longitude</th>\n",
       "      <th>dropoff_latitude</th>\n",
       "      <th>payment_type</th>\n",
       "      <th>fare_amount</th>\n",
       "      <th>surcharge</th>\n",
       "      <th>mta_tax</th>\n",
       "      <th>tip_amount</th>\n",
       "      <th>tolls_amount</th>\n",
       "      <th>total_amount</th>\n",
       "      <th>duration</th>\n",
       "      <th>Location</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 20:45:25</td>\n",
       "      <td>2014-01-09 20:52:31</td>\n",
       "      <td>1</td>\n",
       "      <td>0.7</td>\n",
       "      <td>-73.994770</td>\n",
       "      <td>40.736828</td>\n",
       "      <td>-73.982227</td>\n",
       "      <td>40.731790</td>\n",
       "      <td>CRD</td>\n",
       "      <td>6.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.40</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.90</td>\n",
       "      <td>426</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 20:46:12</td>\n",
       "      <td>2014-01-09 20:55:12</td>\n",
       "      <td>1</td>\n",
       "      <td>1.4</td>\n",
       "      <td>-73.982392</td>\n",
       "      <td>40.773382</td>\n",
       "      <td>-73.960449</td>\n",
       "      <td>40.763995</td>\n",
       "      <td>CRD</td>\n",
       "      <td>8.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.90</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.40</td>\n",
       "      <td>540</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 20:44:47</td>\n",
       "      <td>2014-01-09 20:59:46</td>\n",
       "      <td>2</td>\n",
       "      <td>2.3</td>\n",
       "      <td>-73.988570</td>\n",
       "      <td>40.739406</td>\n",
       "      <td>-73.986626</td>\n",
       "      <td>40.765217</td>\n",
       "      <td>CRD</td>\n",
       "      <td>11.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.50</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.00</td>\n",
       "      <td>899</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 20:44:57</td>\n",
       "      <td>2014-01-09 20:51:40</td>\n",
       "      <td>1</td>\n",
       "      <td>1.7</td>\n",
       "      <td>-73.960213</td>\n",
       "      <td>40.770464</td>\n",
       "      <td>-73.979863</td>\n",
       "      <td>40.777050</td>\n",
       "      <td>CRD</td>\n",
       "      <td>7.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.70</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.20</td>\n",
       "      <td>403</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 20:47:09</td>\n",
       "      <td>2014-01-09 20:53:32</td>\n",
       "      <td>1</td>\n",
       "      <td>0.9</td>\n",
       "      <td>-73.995371</td>\n",
       "      <td>40.717248</td>\n",
       "      <td>-73.984367</td>\n",
       "      <td>40.720524</td>\n",
       "      <td>CRD</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.75</td>\n",
       "      <td>383</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  vendor_id      pickup_datetime     dropoff_datetime  passenger_count  \\\n",
       "0       CMT  2014-01-09 20:45:25  2014-01-09 20:52:31                1   \n",
       "1       CMT  2014-01-09 20:46:12  2014-01-09 20:55:12                1   \n",
       "2       CMT  2014-01-09 20:44:47  2014-01-09 20:59:46                2   \n",
       "3       CMT  2014-01-09 20:44:57  2014-01-09 20:51:40                1   \n",
       "4       CMT  2014-01-09 20:47:09  2014-01-09 20:53:32                1   \n",
       "\n",
       "   trip_distance  pickup_longitude  pickup_latitude  dropoff_longitude  \\\n",
       "0            0.7        -73.994770        40.736828         -73.982227   \n",
       "1            1.4        -73.982392        40.773382         -73.960449   \n",
       "2            2.3        -73.988570        40.739406         -73.986626   \n",
       "3            1.7        -73.960213        40.770464         -73.979863   \n",
       "4            0.9        -73.995371        40.717248         -73.984367   \n",
       "\n",
       "   dropoff_latitude payment_type  fare_amount  surcharge  mta_tax  tip_amount  \\\n",
       "0         40.731790          CRD          6.5        0.5      0.5        1.40   \n",
       "1         40.763995          CRD          8.5        0.5      0.5        1.90   \n",
       "2         40.765217          CRD         11.5        0.5      0.5        1.50   \n",
       "3         40.777050          CRD          7.5        0.5      0.5        1.70   \n",
       "4         40.720524          CRD          6.0        0.5      0.5        1.75   \n",
       "\n",
       "   tolls_amount  total_amount  duration  Location  \n",
       "0           0.0          8.90       426         5  \n",
       "1           0.0         11.40       540         4  \n",
       "2           0.0         14.00       899         5  \n",
       "3           0.0         10.20       403         5  \n",
       "4           0.0          8.75       383         5  "
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(6564770, 18)"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Add time of day column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['pickup_datetime'] =  pd.to_datetime(data['pickup_datetime'], format='%Y-%m-%d %H:%M:%S.%f')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "data[\"hour\"]= data.pickup_datetime.apply(lambda x: x.hour)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(701, 19)"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data.duration >=3600].shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The ones that are longer than an hour are so insignificant so its fair to assume that pickup time of day will be the same as dropoff"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>vendor_id</th>\n",
       "      <th>pickup_datetime</th>\n",
       "      <th>dropoff_datetime</th>\n",
       "      <th>passenger_count</th>\n",
       "      <th>trip_distance</th>\n",
       "      <th>pickup_longitude</th>\n",
       "      <th>pickup_latitude</th>\n",
       "      <th>dropoff_longitude</th>\n",
       "      <th>dropoff_latitude</th>\n",
       "      <th>payment_type</th>\n",
       "      <th>fare_amount</th>\n",
       "      <th>surcharge</th>\n",
       "      <th>mta_tax</th>\n",
       "      <th>tip_amount</th>\n",
       "      <th>tolls_amount</th>\n",
       "      <th>total_amount</th>\n",
       "      <th>duration</th>\n",
       "      <th>Location</th>\n",
       "      <th>hour</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 20:45:25</td>\n",
       "      <td>2014-01-09 20:52:31</td>\n",
       "      <td>1</td>\n",
       "      <td>0.7</td>\n",
       "      <td>-73.994770</td>\n",
       "      <td>40.736828</td>\n",
       "      <td>-73.982227</td>\n",
       "      <td>40.731790</td>\n",
       "      <td>CRD</td>\n",
       "      <td>6.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.40</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.90</td>\n",
       "      <td>426</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 20:46:12</td>\n",
       "      <td>2014-01-09 20:55:12</td>\n",
       "      <td>1</td>\n",
       "      <td>1.4</td>\n",
       "      <td>-73.982392</td>\n",
       "      <td>40.773382</td>\n",
       "      <td>-73.960449</td>\n",
       "      <td>40.763995</td>\n",
       "      <td>CRD</td>\n",
       "      <td>8.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.90</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.40</td>\n",
       "      <td>540</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 20:44:47</td>\n",
       "      <td>2014-01-09 20:59:46</td>\n",
       "      <td>2</td>\n",
       "      <td>2.3</td>\n",
       "      <td>-73.988570</td>\n",
       "      <td>40.739406</td>\n",
       "      <td>-73.986626</td>\n",
       "      <td>40.765217</td>\n",
       "      <td>CRD</td>\n",
       "      <td>11.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.50</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.00</td>\n",
       "      <td>899</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 20:44:57</td>\n",
       "      <td>2014-01-09 20:51:40</td>\n",
       "      <td>1</td>\n",
       "      <td>1.7</td>\n",
       "      <td>-73.960213</td>\n",
       "      <td>40.770464</td>\n",
       "      <td>-73.979863</td>\n",
       "      <td>40.777050</td>\n",
       "      <td>CRD</td>\n",
       "      <td>7.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.70</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.20</td>\n",
       "      <td>403</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 20:47:09</td>\n",
       "      <td>2014-01-09 20:53:32</td>\n",
       "      <td>1</td>\n",
       "      <td>0.9</td>\n",
       "      <td>-73.995371</td>\n",
       "      <td>40.717248</td>\n",
       "      <td>-73.984367</td>\n",
       "      <td>40.720524</td>\n",
       "      <td>CRD</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.75</td>\n",
       "      <td>383</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  vendor_id     pickup_datetime     dropoff_datetime  passenger_count  \\\n",
       "0       CMT 2014-01-09 20:45:25  2014-01-09 20:52:31                1   \n",
       "1       CMT 2014-01-09 20:46:12  2014-01-09 20:55:12                1   \n",
       "2       CMT 2014-01-09 20:44:47  2014-01-09 20:59:46                2   \n",
       "3       CMT 2014-01-09 20:44:57  2014-01-09 20:51:40                1   \n",
       "4       CMT 2014-01-09 20:47:09  2014-01-09 20:53:32                1   \n",
       "\n",
       "   trip_distance  pickup_longitude  pickup_latitude  dropoff_longitude  \\\n",
       "0            0.7        -73.994770        40.736828         -73.982227   \n",
       "1            1.4        -73.982392        40.773382         -73.960449   \n",
       "2            2.3        -73.988570        40.739406         -73.986626   \n",
       "3            1.7        -73.960213        40.770464         -73.979863   \n",
       "4            0.9        -73.995371        40.717248         -73.984367   \n",
       "\n",
       "   dropoff_latitude payment_type  fare_amount  surcharge  mta_tax  tip_amount  \\\n",
       "0         40.731790          CRD          6.5        0.5      0.5        1.40   \n",
       "1         40.763995          CRD          8.5        0.5      0.5        1.90   \n",
       "2         40.765217          CRD         11.5        0.5      0.5        1.50   \n",
       "3         40.777050          CRD          7.5        0.5      0.5        1.70   \n",
       "4         40.720524          CRD          6.0        0.5      0.5        1.75   \n",
       "\n",
       "   tolls_amount  total_amount  duration  Location  hour  \n",
       "0           0.0          8.90       426         5    20  \n",
       "1           0.0         11.40       540         4    20  \n",
       "2           0.0         14.00       899         5    20  \n",
       "3           0.0         10.20       403         5    20  \n",
       "4           0.0          8.75       383         5    20  "
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "b = [0,4,8,12,16,20,24]\n",
    "l = ['Late Night', 'Early Morning','Morning','Noon','Eve','Night']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "data[\"time_of_day\"] = pd.cut(data[\"hour\"], bins=b, labels=l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.time_of_day.fillna(\"Late Night\", inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "vendor_id            False\n",
       "pickup_datetime      False\n",
       "dropoff_datetime     False\n",
       "passenger_count      False\n",
       "trip_distance        False\n",
       "pickup_longitude     False\n",
       "pickup_latitude      False\n",
       "dropoff_longitude    False\n",
       "dropoff_latitude     False\n",
       "payment_type         False\n",
       "fare_amount          False\n",
       "surcharge            False\n",
       "mta_tax              False\n",
       "tip_amount           False\n",
       "tolls_amount         False\n",
       "total_amount         False\n",
       "duration             False\n",
       "Location             False\n",
       "hour                 False\n",
       "time_of_day          False\n",
       "dtype: bool"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isnull().any(axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "def time_to_numeric(x):\n",
    "    if x=='Late Night':\n",
    "        return 6\n",
    "    if x=='Early Morning':\n",
    "        return 1\n",
    "    if x=='Morning':\n",
    "        return 2\n",
    "    if x=='Noon':\n",
    "        return 3\n",
    "    if x=='Eve':\n",
    "        return 4\n",
    "    if x=='Night':\n",
    "        return 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "data[\"time_of_day\"] = data[\"time_of_day\"].apply(time_to_numeric)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "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>vendor_id</th>\n",
       "      <th>pickup_datetime</th>\n",
       "      <th>dropoff_datetime</th>\n",
       "      <th>passenger_count</th>\n",
       "      <th>trip_distance</th>\n",
       "      <th>pickup_longitude</th>\n",
       "      <th>pickup_latitude</th>\n",
       "      <th>dropoff_longitude</th>\n",
       "      <th>dropoff_latitude</th>\n",
       "      <th>payment_type</th>\n",
       "      <th>fare_amount</th>\n",
       "      <th>surcharge</th>\n",
       "      <th>mta_tax</th>\n",
       "      <th>tip_amount</th>\n",
       "      <th>tolls_amount</th>\n",
       "      <th>total_amount</th>\n",
       "      <th>duration</th>\n",
       "      <th>Location</th>\n",
       "      <th>hour</th>\n",
       "      <th>time_of_day</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 20:45:25</td>\n",
       "      <td>2014-01-09 20:52:31</td>\n",
       "      <td>1</td>\n",
       "      <td>0.7</td>\n",
       "      <td>-73.994770</td>\n",
       "      <td>40.736828</td>\n",
       "      <td>-73.982227</td>\n",
       "      <td>40.731790</td>\n",
       "      <td>CRD</td>\n",
       "      <td>6.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.40</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.90</td>\n",
       "      <td>426</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 20:46:12</td>\n",
       "      <td>2014-01-09 20:55:12</td>\n",
       "      <td>1</td>\n",
       "      <td>1.4</td>\n",
       "      <td>-73.982392</td>\n",
       "      <td>40.773382</td>\n",
       "      <td>-73.960449</td>\n",
       "      <td>40.763995</td>\n",
       "      <td>CRD</td>\n",
       "      <td>8.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.90</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.40</td>\n",
       "      <td>540</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 20:44:47</td>\n",
       "      <td>2014-01-09 20:59:46</td>\n",
       "      <td>2</td>\n",
       "      <td>2.3</td>\n",
       "      <td>-73.988570</td>\n",
       "      <td>40.739406</td>\n",
       "      <td>-73.986626</td>\n",
       "      <td>40.765217</td>\n",
       "      <td>CRD</td>\n",
       "      <td>11.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.50</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.00</td>\n",
       "      <td>899</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 20:44:57</td>\n",
       "      <td>2014-01-09 20:51:40</td>\n",
       "      <td>1</td>\n",
       "      <td>1.7</td>\n",
       "      <td>-73.960213</td>\n",
       "      <td>40.770464</td>\n",
       "      <td>-73.979863</td>\n",
       "      <td>40.777050</td>\n",
       "      <td>CRD</td>\n",
       "      <td>7.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.70</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.20</td>\n",
       "      <td>403</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 20:47:09</td>\n",
       "      <td>2014-01-09 20:53:32</td>\n",
       "      <td>1</td>\n",
       "      <td>0.9</td>\n",
       "      <td>-73.995371</td>\n",
       "      <td>40.717248</td>\n",
       "      <td>-73.984367</td>\n",
       "      <td>40.720524</td>\n",
       "      <td>CRD</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.75</td>\n",
       "      <td>383</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 20:45:07</td>\n",
       "      <td>2014-01-09 20:51:01</td>\n",
       "      <td>1</td>\n",
       "      <td>0.9</td>\n",
       "      <td>-73.983811</td>\n",
       "      <td>40.749655</td>\n",
       "      <td>-73.989747</td>\n",
       "      <td>40.756575</td>\n",
       "      <td>CRD</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.40</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.40</td>\n",
       "      <td>354</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 20:43:23</td>\n",
       "      <td>2014-01-09 20:52:07</td>\n",
       "      <td>1</td>\n",
       "      <td>2.1</td>\n",
       "      <td>-73.979906</td>\n",
       "      <td>40.745850</td>\n",
       "      <td>-73.959090</td>\n",
       "      <td>40.773639</td>\n",
       "      <td>CRD</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>2.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.00</td>\n",
       "      <td>524</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 20:43:04</td>\n",
       "      <td>2014-01-09 20:54:29</td>\n",
       "      <td>1</td>\n",
       "      <td>3.4</td>\n",
       "      <td>-73.981147</td>\n",
       "      <td>40.758918</td>\n",
       "      <td>-73.942510</td>\n",
       "      <td>40.785975</td>\n",
       "      <td>CRD</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>2.60</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15.60</td>\n",
       "      <td>685</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 20:50:23</td>\n",
       "      <td>2014-01-09 20:58:10</td>\n",
       "      <td>1</td>\n",
       "      <td>2.3</td>\n",
       "      <td>-73.955193</td>\n",
       "      <td>40.765468</td>\n",
       "      <td>-73.979023</td>\n",
       "      <td>40.740578</td>\n",
       "      <td>CRD</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.00</td>\n",
       "      <td>467</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 20:48:04</td>\n",
       "      <td>2014-01-09 21:01:37</td>\n",
       "      <td>1</td>\n",
       "      <td>3.3</td>\n",
       "      <td>-73.991782</td>\n",
       "      <td>40.748911</td>\n",
       "      <td>-73.988359</td>\n",
       "      <td>40.714205</td>\n",
       "      <td>CRD</td>\n",
       "      <td>12.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>4.05</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.55</td>\n",
       "      <td>813</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 20:47:49</td>\n",
       "      <td>2014-01-09 20:56:11</td>\n",
       "      <td>2</td>\n",
       "      <td>1.8</td>\n",
       "      <td>-73.965717</td>\n",
       "      <td>40.758675</td>\n",
       "      <td>-73.984059</td>\n",
       "      <td>40.737448</td>\n",
       "      <td>CRD</td>\n",
       "      <td>8.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.90</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.40</td>\n",
       "      <td>502</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 20:48:47</td>\n",
       "      <td>2014-01-09 20:56:52</td>\n",
       "      <td>2</td>\n",
       "      <td>1.4</td>\n",
       "      <td>-73.977009</td>\n",
       "      <td>40.751620</td>\n",
       "      <td>-73.982643</td>\n",
       "      <td>40.766574</td>\n",
       "      <td>CRD</td>\n",
       "      <td>7.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.70</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.20</td>\n",
       "      <td>485</td>\n",
       "      <td>3</td>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 20:47:51</td>\n",
       "      <td>2014-01-09 21:02:31</td>\n",
       "      <td>3</td>\n",
       "      <td>2.6</td>\n",
       "      <td>-73.977656</td>\n",
       "      <td>40.753680</td>\n",
       "      <td>-73.952249</td>\n",
       "      <td>40.777676</td>\n",
       "      <td>CRD</td>\n",
       "      <td>12.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.50</td>\n",
       "      <td>880</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 16:51:35</td>\n",
       "      <td>2014-01-09 17:00:17</td>\n",
       "      <td>1</td>\n",
       "      <td>1.7</td>\n",
       "      <td>-74.007503</td>\n",
       "      <td>40.725992</td>\n",
       "      <td>-73.988182</td>\n",
       "      <td>40.734583</td>\n",
       "      <td>CRD</td>\n",
       "      <td>8.5</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>2.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.00</td>\n",
       "      <td>522</td>\n",
       "      <td>5</td>\n",
       "      <td>16</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 16:43:29</td>\n",
       "      <td>2014-01-09 16:59:15</td>\n",
       "      <td>1</td>\n",
       "      <td>4.7</td>\n",
       "      <td>-74.014866</td>\n",
       "      <td>40.709353</td>\n",
       "      <td>-73.986084</td>\n",
       "      <td>40.759081</td>\n",
       "      <td>CRD</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>4.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21.50</td>\n",
       "      <td>946</td>\n",
       "      <td>5</td>\n",
       "      <td>16</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 16:46:50</td>\n",
       "      <td>2014-01-09 16:56:41</td>\n",
       "      <td>1</td>\n",
       "      <td>1.6</td>\n",
       "      <td>-73.967675</td>\n",
       "      <td>40.763109</td>\n",
       "      <td>-73.952591</td>\n",
       "      <td>40.778186</td>\n",
       "      <td>CRD</td>\n",
       "      <td>9.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>2.10</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.60</td>\n",
       "      <td>591</td>\n",
       "      <td>4</td>\n",
       "      <td>16</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 16:42:16</td>\n",
       "      <td>2014-01-09 16:58:42</td>\n",
       "      <td>1</td>\n",
       "      <td>2.1</td>\n",
       "      <td>-73.988810</td>\n",
       "      <td>40.751013</td>\n",
       "      <td>-73.996002</td>\n",
       "      <td>40.726658</td>\n",
       "      <td>CRD</td>\n",
       "      <td>12.5</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>3.50</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.50</td>\n",
       "      <td>986</td>\n",
       "      <td>2</td>\n",
       "      <td>16</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 16:43:37</td>\n",
       "      <td>2014-01-09 16:56:23</td>\n",
       "      <td>1</td>\n",
       "      <td>1.6</td>\n",
       "      <td>-73.970117</td>\n",
       "      <td>40.752862</td>\n",
       "      <td>-73.954138</td>\n",
       "      <td>40.764081</td>\n",
       "      <td>CRD</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.50</td>\n",
       "      <td>766</td>\n",
       "      <td>4</td>\n",
       "      <td>16</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 16:46:36</td>\n",
       "      <td>2014-01-09 16:52:44</td>\n",
       "      <td>1</td>\n",
       "      <td>1.3</td>\n",
       "      <td>-73.991542</td>\n",
       "      <td>40.738918</td>\n",
       "      <td>-73.994747</td>\n",
       "      <td>40.724134</td>\n",
       "      <td>CRD</td>\n",
       "      <td>6.5</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>2.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.00</td>\n",
       "      <td>368</td>\n",
       "      <td>5</td>\n",
       "      <td>16</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>CMT</td>\n",
       "      <td>2014-01-09 16:49:16</td>\n",
       "      <td>2014-01-09 17:01:00</td>\n",
       "      <td>1</td>\n",
       "      <td>1.3</td>\n",
       "      <td>-73.960639</td>\n",
       "      <td>40.768772</td>\n",
       "      <td>-73.976677</td>\n",
       "      <td>40.765340</td>\n",
       "      <td>CRD</td>\n",
       "      <td>9.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>2.10</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.60</td>\n",
       "      <td>704</td>\n",
       "      <td>3</td>\n",
       "      <td>16</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   vendor_id     pickup_datetime     dropoff_datetime  passenger_count  \\\n",
       "0        CMT 2014-01-09 20:45:25  2014-01-09 20:52:31                1   \n",
       "1        CMT 2014-01-09 20:46:12  2014-01-09 20:55:12                1   \n",
       "2        CMT 2014-01-09 20:44:47  2014-01-09 20:59:46                2   \n",
       "3        CMT 2014-01-09 20:44:57  2014-01-09 20:51:40                1   \n",
       "4        CMT 2014-01-09 20:47:09  2014-01-09 20:53:32                1   \n",
       "5        CMT 2014-01-09 20:45:07  2014-01-09 20:51:01                1   \n",
       "6        CMT 2014-01-09 20:43:23  2014-01-09 20:52:07                1   \n",
       "7        CMT 2014-01-09 20:43:04  2014-01-09 20:54:29                1   \n",
       "8        CMT 2014-01-09 20:50:23  2014-01-09 20:58:10                1   \n",
       "9        CMT 2014-01-09 20:48:04  2014-01-09 21:01:37                1   \n",
       "10       CMT 2014-01-09 20:47:49  2014-01-09 20:56:11                2   \n",
       "11       CMT 2014-01-09 20:48:47  2014-01-09 20:56:52                2   \n",
       "12       CMT 2014-01-09 20:47:51  2014-01-09 21:02:31                3   \n",
       "13       CMT 2014-01-09 16:51:35  2014-01-09 17:00:17                1   \n",
       "14       CMT 2014-01-09 16:43:29  2014-01-09 16:59:15                1   \n",
       "15       CMT 2014-01-09 16:46:50  2014-01-09 16:56:41                1   \n",
       "16       CMT 2014-01-09 16:42:16  2014-01-09 16:58:42                1   \n",
       "17       CMT 2014-01-09 16:43:37  2014-01-09 16:56:23                1   \n",
       "18       CMT 2014-01-09 16:46:36  2014-01-09 16:52:44                1   \n",
       "19       CMT 2014-01-09 16:49:16  2014-01-09 17:01:00                1   \n",
       "\n",
       "    trip_distance  pickup_longitude  pickup_latitude  dropoff_longitude  \\\n",
       "0             0.7        -73.994770        40.736828         -73.982227   \n",
       "1             1.4        -73.982392        40.773382         -73.960449   \n",
       "2             2.3        -73.988570        40.739406         -73.986626   \n",
       "3             1.7        -73.960213        40.770464         -73.979863   \n",
       "4             0.9        -73.995371        40.717248         -73.984367   \n",
       "5             0.9        -73.983811        40.749655         -73.989747   \n",
       "6             2.1        -73.979906        40.745850         -73.959090   \n",
       "7             3.4        -73.981147        40.758918         -73.942510   \n",
       "8             2.3        -73.955193        40.765468         -73.979023   \n",
       "9             3.3        -73.991782        40.748911         -73.988359   \n",
       "10            1.8        -73.965717        40.758675         -73.984059   \n",
       "11            1.4        -73.977009        40.751620         -73.982643   \n",
       "12            2.6        -73.977656        40.753680         -73.952249   \n",
       "13            1.7        -74.007503        40.725992         -73.988182   \n",
       "14            4.7        -74.014866        40.709353         -73.986084   \n",
       "15            1.6        -73.967675        40.763109         -73.952591   \n",
       "16            2.1        -73.988810        40.751013         -73.996002   \n",
       "17            1.6        -73.970117        40.752862         -73.954138   \n",
       "18            1.3        -73.991542        40.738918         -73.994747   \n",
       "19            1.3        -73.960639        40.768772         -73.976677   \n",
       "\n",
       "    dropoff_latitude payment_type  fare_amount  surcharge  mta_tax  \\\n",
       "0          40.731790          CRD          6.5        0.5      0.5   \n",
       "1          40.763995          CRD          8.5        0.5      0.5   \n",
       "2          40.765217          CRD         11.5        0.5      0.5   \n",
       "3          40.777050          CRD          7.5        0.5      0.5   \n",
       "4          40.720524          CRD          6.0        0.5      0.5   \n",
       "5          40.756575          CRD          6.0        0.5      0.5   \n",
       "6          40.773639          CRD          9.0        0.5      0.5   \n",
       "7          40.785975          CRD         12.0        0.5      0.5   \n",
       "8          40.740578          CRD          9.0        0.5      0.5   \n",
       "9          40.714205          CRD         12.5        0.5      0.5   \n",
       "10         40.737448          CRD          8.5        0.5      0.5   \n",
       "11         40.766574          CRD          7.5        0.5      0.5   \n",
       "12         40.777676          CRD         12.5        0.5      0.5   \n",
       "13         40.734583          CRD          8.5        1.0      0.5   \n",
       "14         40.759081          CRD         16.0        1.0      0.5   \n",
       "15         40.778186          CRD          9.0        1.0      0.5   \n",
       "16         40.726658          CRD         12.5        1.0      0.5   \n",
       "17         40.764081          CRD         10.0        1.0      0.5   \n",
       "18         40.724134          CRD          6.5        1.0      0.5   \n",
       "19         40.765340          CRD          9.0        1.0      0.5   \n",
       "\n",
       "    tip_amount  tolls_amount  total_amount  duration  Location  hour  \\\n",
       "0         1.40           0.0          8.90       426         5    20   \n",
       "1         1.90           0.0         11.40       540         4    20   \n",
       "2         1.50           0.0         14.00       899         5    20   \n",
       "3         1.70           0.0         10.20       403         5    20   \n",
       "4         1.75           0.0          8.75       383         5    20   \n",
       "5         1.40           0.0          8.40       354         5    20   \n",
       "6         2.00           0.0         12.00       524         4    20   \n",
       "7         2.60           0.0         15.60       685         5    20   \n",
       "8         1.00           0.0         11.00       467         5    20   \n",
       "9         4.05           0.0         17.55       813         5    20   \n",
       "10        1.90           0.0         11.40       502         5    20   \n",
       "11        1.70           0.0         10.20       485         3    20   \n",
       "12        1.00           0.0         14.50       880         4    20   \n",
       "13        2.00           0.0         12.00       522         5    16   \n",
       "14        4.00           0.0         21.50       946         5    16   \n",
       "15        2.10           0.0         12.60       591         4    16   \n",
       "16        3.50           0.0         17.50       986         2    16   \n",
       "17        1.00           0.0         12.50       766         4    16   \n",
       "18        2.00           0.0         10.00       368         5    16   \n",
       "19        2.10           0.0         12.60       704         3    16   \n",
       "\n",
       "   time_of_day  \n",
       "0            4  \n",
       "1            4  \n",
       "2            4  \n",
       "3            4  \n",
       "4            4  \n",
       "5            4  \n",
       "6            4  \n",
       "7            4  \n",
       "8            4  \n",
       "9            4  \n",
       "10           4  \n",
       "11           4  \n",
       "12           4  \n",
       "13           3  \n",
       "14           3  \n",
       "15           3  \n",
       "16           3  \n",
       "17           3  \n",
       "18           3  \n",
       "19           3  "
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "del data[\"hour\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Adding Vendor ID column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CMT    3347258\n",
       "VTS    3217512\n",
       "Name: vendor_id, dtype: int64"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.vendor_id.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "vendor_changes = {\"vendor_id\": {\"CMT\": 1, \"VTS\":2}}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.replace(vendor_changes, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "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>vendor_id</th>\n",
       "      <th>pickup_datetime</th>\n",
       "      <th>dropoff_datetime</th>\n",
       "      <th>passenger_count</th>\n",
       "      <th>trip_distance</th>\n",
       "      <th>pickup_longitude</th>\n",
       "      <th>pickup_latitude</th>\n",
       "      <th>dropoff_longitude</th>\n",
       "      <th>dropoff_latitude</th>\n",
       "      <th>payment_type</th>\n",
       "      <th>fare_amount</th>\n",
       "      <th>surcharge</th>\n",
       "      <th>mta_tax</th>\n",
       "      <th>tip_amount</th>\n",
       "      <th>tolls_amount</th>\n",
       "      <th>total_amount</th>\n",
       "      <th>duration</th>\n",
       "      <th>Location</th>\n",
       "      <th>time_of_day</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2014-01-09 20:45:25</td>\n",
       "      <td>2014-01-09 20:52:31</td>\n",
       "      <td>1</td>\n",
       "      <td>0.7</td>\n",
       "      <td>-73.994770</td>\n",
       "      <td>40.736828</td>\n",
       "      <td>-73.982227</td>\n",
       "      <td>40.731790</td>\n",
       "      <td>CRD</td>\n",
       "      <td>6.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.40</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.90</td>\n",
       "      <td>426</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2014-01-09 20:46:12</td>\n",
       "      <td>2014-01-09 20:55:12</td>\n",
       "      <td>1</td>\n",
       "      <td>1.4</td>\n",
       "      <td>-73.982392</td>\n",
       "      <td>40.773382</td>\n",
       "      <td>-73.960449</td>\n",
       "      <td>40.763995</td>\n",
       "      <td>CRD</td>\n",
       "      <td>8.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.90</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.40</td>\n",
       "      <td>540</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>2014-01-09 20:44:47</td>\n",
       "      <td>2014-01-09 20:59:46</td>\n",
       "      <td>2</td>\n",
       "      <td>2.3</td>\n",
       "      <td>-73.988570</td>\n",
       "      <td>40.739406</td>\n",
       "      <td>-73.986626</td>\n",
       "      <td>40.765217</td>\n",
       "      <td>CRD</td>\n",
       "      <td>11.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.50</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.00</td>\n",
       "      <td>899</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>2014-01-09 20:44:57</td>\n",
       "      <td>2014-01-09 20:51:40</td>\n",
       "      <td>1</td>\n",
       "      <td>1.7</td>\n",
       "      <td>-73.960213</td>\n",
       "      <td>40.770464</td>\n",
       "      <td>-73.979863</td>\n",
       "      <td>40.777050</td>\n",
       "      <td>CRD</td>\n",
       "      <td>7.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.70</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.20</td>\n",
       "      <td>403</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>2014-01-09 20:47:09</td>\n",
       "      <td>2014-01-09 20:53:32</td>\n",
       "      <td>1</td>\n",
       "      <td>0.9</td>\n",
       "      <td>-73.995371</td>\n",
       "      <td>40.717248</td>\n",
       "      <td>-73.984367</td>\n",
       "      <td>40.720524</td>\n",
       "      <td>CRD</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.75</td>\n",
       "      <td>383</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   vendor_id     pickup_datetime     dropoff_datetime  passenger_count  \\\n",
       "0          1 2014-01-09 20:45:25  2014-01-09 20:52:31                1   \n",
       "1          1 2014-01-09 20:46:12  2014-01-09 20:55:12                1   \n",
       "2          1 2014-01-09 20:44:47  2014-01-09 20:59:46                2   \n",
       "3          1 2014-01-09 20:44:57  2014-01-09 20:51:40                1   \n",
       "4          1 2014-01-09 20:47:09  2014-01-09 20:53:32                1   \n",
       "\n",
       "   trip_distance  pickup_longitude  pickup_latitude  dropoff_longitude  \\\n",
       "0            0.7        -73.994770        40.736828         -73.982227   \n",
       "1            1.4        -73.982392        40.773382         -73.960449   \n",
       "2            2.3        -73.988570        40.739406         -73.986626   \n",
       "3            1.7        -73.960213        40.770464         -73.979863   \n",
       "4            0.9        -73.995371        40.717248         -73.984367   \n",
       "\n",
       "   dropoff_latitude payment_type  fare_amount  surcharge  mta_tax  tip_amount  \\\n",
       "0         40.731790          CRD          6.5        0.5      0.5        1.40   \n",
       "1         40.763995          CRD          8.5        0.5      0.5        1.90   \n",
       "2         40.765217          CRD         11.5        0.5      0.5        1.50   \n",
       "3         40.777050          CRD          7.5        0.5      0.5        1.70   \n",
       "4         40.720524          CRD          6.0        0.5      0.5        1.75   \n",
       "\n",
       "   tolls_amount  total_amount  duration  Location time_of_day  \n",
       "0           0.0          8.90       426         5           4  \n",
       "1           0.0         11.40       540         4           4  \n",
       "2           0.0         14.00       899         5           4  \n",
       "3           0.0         10.20       403         5           4  \n",
       "4           0.0          8.75       383         5           4  "
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Add payment type dummy variables "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['CRD', 'UNK', 'NOC', 'DIS', 'CSH'], dtype=object)"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unique_types = data.payment_type.unique()\n",
    "unique_types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "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>vendor_id</th>\n",
       "      <th>pickup_datetime</th>\n",
       "      <th>dropoff_datetime</th>\n",
       "      <th>passenger_count</th>\n",
       "      <th>trip_distance</th>\n",
       "      <th>pickup_longitude</th>\n",
       "      <th>pickup_latitude</th>\n",
       "      <th>dropoff_longitude</th>\n",
       "      <th>dropoff_latitude</th>\n",
       "      <th>fare_amount</th>\n",
       "      <th>...</th>\n",
       "      <th>tolls_amount</th>\n",
       "      <th>total_amount</th>\n",
       "      <th>duration</th>\n",
       "      <th>Location</th>\n",
       "      <th>time_of_day</th>\n",
       "      <th>CRD</th>\n",
       "      <th>UNK</th>\n",
       "      <th>NOC</th>\n",
       "      <th>DIS</th>\n",
       "      <th>CSH</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2014-01-09 20:45:25</td>\n",
       "      <td>2014-01-09 20:52:31</td>\n",
       "      <td>1</td>\n",
       "      <td>0.7</td>\n",
       "      <td>-73.994770</td>\n",
       "      <td>40.736828</td>\n",
       "      <td>-73.982227</td>\n",
       "      <td>40.731790</td>\n",
       "      <td>6.5</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.90</td>\n",
       "      <td>426</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2014-01-09 20:46:12</td>\n",
       "      <td>2014-01-09 20:55:12</td>\n",
       "      <td>1</td>\n",
       "      <td>1.4</td>\n",
       "      <td>-73.982392</td>\n",
       "      <td>40.773382</td>\n",
       "      <td>-73.960449</td>\n",
       "      <td>40.763995</td>\n",
       "      <td>8.5</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.40</td>\n",
       "      <td>540</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>2014-01-09 20:44:47</td>\n",
       "      <td>2014-01-09 20:59:46</td>\n",
       "      <td>2</td>\n",
       "      <td>2.3</td>\n",
       "      <td>-73.988570</td>\n",
       "      <td>40.739406</td>\n",
       "      <td>-73.986626</td>\n",
       "      <td>40.765217</td>\n",
       "      <td>11.5</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.00</td>\n",
       "      <td>899</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>2014-01-09 20:44:57</td>\n",
       "      <td>2014-01-09 20:51:40</td>\n",
       "      <td>1</td>\n",
       "      <td>1.7</td>\n",
       "      <td>-73.960213</td>\n",
       "      <td>40.770464</td>\n",
       "      <td>-73.979863</td>\n",
       "      <td>40.777050</td>\n",
       "      <td>7.5</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.20</td>\n",
       "      <td>403</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>2014-01-09 20:47:09</td>\n",
       "      <td>2014-01-09 20:53:32</td>\n",
       "      <td>1</td>\n",
       "      <td>0.9</td>\n",
       "      <td>-73.995371</td>\n",
       "      <td>40.717248</td>\n",
       "      <td>-73.984367</td>\n",
       "      <td>40.720524</td>\n",
       "      <td>6.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.75</td>\n",
       "      <td>383</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   vendor_id     pickup_datetime     dropoff_datetime  passenger_count  \\\n",
       "0          1 2014-01-09 20:45:25  2014-01-09 20:52:31                1   \n",
       "1          1 2014-01-09 20:46:12  2014-01-09 20:55:12                1   \n",
       "2          1 2014-01-09 20:44:47  2014-01-09 20:59:46                2   \n",
       "3          1 2014-01-09 20:44:57  2014-01-09 20:51:40                1   \n",
       "4          1 2014-01-09 20:47:09  2014-01-09 20:53:32                1   \n",
       "\n",
       "   trip_distance  pickup_longitude  pickup_latitude  dropoff_longitude  \\\n",
       "0            0.7        -73.994770        40.736828         -73.982227   \n",
       "1            1.4        -73.982392        40.773382         -73.960449   \n",
       "2            2.3        -73.988570        40.739406         -73.986626   \n",
       "3            1.7        -73.960213        40.770464         -73.979863   \n",
       "4            0.9        -73.995371        40.717248         -73.984367   \n",
       "\n",
       "   dropoff_latitude  fare_amount  ...  tolls_amount  total_amount  duration  \\\n",
       "0         40.731790          6.5  ...           0.0          8.90       426   \n",
       "1         40.763995          8.5  ...           0.0         11.40       540   \n",
       "2         40.765217         11.5  ...           0.0         14.00       899   \n",
       "3         40.777050          7.5  ...           0.0         10.20       403   \n",
       "4         40.720524          6.0  ...           0.0          8.75       383   \n",
       "\n",
       "   Location  time_of_day  CRD  UNK NOC  DIS  CSH  \n",
       "0         5            4    1    0   0    0    0  \n",
       "1         4            4    1    0   0    0    0  \n",
       "2         5            4    1    0   0    0    0  \n",
       "3         5            4    1    0   0    0    0  \n",
       "4         5            4    1    0   0    0    0  \n",
       "\n",
       "[5 rows x 23 columns]"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for unique in unique_types:\n",
    "    data[unique] = data.payment_type.apply(lambda x: 1 if x == unique else 0)\n",
    "data = data.drop(columns=['payment_type'])\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Building the initial models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['vendor_id', 'pickup_datetime', 'dropoff_datetime', 'passenger_count',\n",
       "       'trip_distance', 'pickup_longitude', 'pickup_latitude',\n",
       "       'dropoff_longitude', 'dropoff_latitude', 'payment_type', 'fare_amount',\n",
       "       'surcharge', 'mta_tax', 'tip_amount', 'tolls_amount', 'total_amount',\n",
       "       'duration', 'Location', 'time_of_day'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train, x_test, y_train, y_test = train_test_split(data.drop(columns=['tip_amount','pickup_longitude', 'pickup_latitude',\n",
    "       'dropoff_longitude', 'dropoff_latitude','pickup_datetime','dropoff_datetime','total_amount','mta_tax']), data['tip_amount'], test_size=0.30, random_state=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "linreg = LinearRegression()\n",
    "linreg.fit(x_train, y_train)\n",
    "\n",
    "train_score = linreg.score(x_train, y_train)\n",
    "test_score = linreg.score(x_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The train score is 0.4028823741921212 and the test score is 0.40329731485470804\n",
      "\n",
      "\n",
      "vendor_id         -0.058388\n",
      "passenger_count    0.000416\n",
      "trip_distance      0.007268\n",
      "payment_type      -0.451624\n",
      "fare_amount        0.139867\n",
      "surcharge          0.131413\n",
      "tolls_amount       0.251448\n",
      "duration           0.000080\n",
      "Location           0.000117\n",
      "time_of_day        0.002589\n",
      "Intercept          0.925256\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "print('The train score is {} and the test score is {}'.format(train_score, test_score))\n",
    "print('\\n')\n",
    "betas = pd.Series(linreg.coef_, index=x_train.columns)\n",
    "betas = betas.append(pd.Series({\"Intercept\": linreg.intercept_}))\n",
    "print(betas)\n",
    "\n",
    "#without vendor, 39.31 and 39.38\n",
    "#with is 39.42 and 39.49\n",
    "#Now with encoded payment type score is 40.30 and 40.33"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\sklearn\\model_selection\\_split.py:2053: FutureWarning: You should specify a value for 'cv' instead of relying on the default value. The default value will change from 3 to 5 in version 0.22.\n",
      "  warnings.warn(CV_WARNING, FutureWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The train score is 0.37246235511267184 and the test score is 0.37271795665210605\n",
      "\n",
      "\n",
      "vendor_id         -0.000000\n",
      "passenger_count   -0.000000\n",
      "trip_distance      0.000000\n",
      "payment_type      -0.000000\n",
      "fare_amount        0.072324\n",
      "surcharge          0.000000\n",
      "tolls_amount      -0.000000\n",
      "duration           0.000736\n",
      "Location           0.000000\n",
      "time_of_day        0.000000\n",
      "Intercept          0.653600\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "# Fit the model\n",
    "lasso = LassoCV()\n",
    "lasso.fit(x_train, y_train)\n",
    "\n",
    "# calculate the score\n",
    "train_score = lasso.score(x_train, y_train)\n",
    "test_score = lasso.score(x_test, y_test)\n",
    "\n",
    "print('The train score is {} and the test score is {}'.format(train_score, test_score)) \n",
    "\n",
    "# calculate betas\n",
    "print('\\n')\n",
    "betas = pd.Series(lasso.coef_, index= x_train.columns)\n",
    "betas = betas.append(pd.Series({\"Intercept\": lasso.intercept_}))\n",
    "print(betas)\n",
    "              "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cart and RFT then feature engineering "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## CART MODEL "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4.94"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.tip_amount.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.tree import export_graphviz\n",
    "from subprocess import call\n",
    "from IPython.display import SVG\n",
    "#from graphviz import Source"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('float64')"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import preprocessing\n",
    "from sklearn import utils"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [],
   "source": [
    "lab_enc = preprocessing.LabelEncoder()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_train_enc = lab_enc.fit_transform(y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_test_enc = lab_enc.fit_transform(y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "continuous\n"
     ]
    }
   ],
   "source": [
    "print(utils.multiclass.type_of_target(y_train))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "continuous\n"
     ]
    }
   ],
   "source": [
    "print(utils.multiclass.type_of_target(y_train.astype('category')))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "multiclass\n"
     ]
    }
   ],
   "source": [
    "print(utils.multiclass.type_of_target(y_train_enc))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "Unknown label type: 'continuous'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-80-b34f7417c4d6>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;31m# Train the CART model\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[0mcart_model\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mDecisionTreeClassifier\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrandom_state\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m3\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mmax_depth\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m3\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mcart_model\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx_train\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my_train\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      4\u001b[0m \u001b[0mtrain_score\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcart_model\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mscore\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx_train\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my_train\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[0mtest_score\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcart_model\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mscore\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx_test\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my_test\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\sklearn\\tree\\tree.py\u001b[0m in \u001b[0;36mfit\u001b[1;34m(self, X, y, sample_weight, check_input, X_idx_sorted)\u001b[0m\n\u001b[0;32m    799\u001b[0m             \u001b[0msample_weight\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msample_weight\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    800\u001b[0m             \u001b[0mcheck_input\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mcheck_input\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 801\u001b[1;33m             X_idx_sorted=X_idx_sorted)\n\u001b[0m\u001b[0;32m    802\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    803\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\sklearn\\tree\\tree.py\u001b[0m in \u001b[0;36mfit\u001b[1;34m(self, X, y, sample_weight, check_input, X_idx_sorted)\u001b[0m\n\u001b[0;32m    138\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    139\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mis_classification\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 140\u001b[1;33m             \u001b[0mcheck_classification_targets\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    141\u001b[0m             \u001b[0my\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcopy\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    142\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\sklearn\\utils\\multiclass.py\u001b[0m in \u001b[0;36mcheck_classification_targets\u001b[1;34m(y)\u001b[0m\n\u001b[0;32m    169\u001b[0m     if y_type not in ['binary', 'multiclass', 'multiclass-multioutput',\n\u001b[0;32m    170\u001b[0m                       'multilabel-indicator', 'multilabel-sequences']:\n\u001b[1;32m--> 171\u001b[1;33m         \u001b[1;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Unknown label type: %r\"\u001b[0m \u001b[1;33m%\u001b[0m \u001b[0my_type\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    172\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    173\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mValueError\u001b[0m: Unknown label type: 'continuous'"
     ]
    }
   ],
   "source": [
    "# Train the CART model\n",
    "cart_model = DecisionTreeClassifier(random_state=3,max_depth=3)\n",
    "cart_model.fit(x_train, y_train)\n",
    "train_score = cart_model.score(x_train, y_train)\n",
    "test_score = cart_model.score(x_test, y_test)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Train the CART model\n",
    "cart_model = DecisionTreeClassifier(random_state=3,max_depth=3)\n",
    "cart_model.fit(x_train, y_train_enc)\n",
    "train_score = cart_model.score(x_train, y_train_enc)\n",
    "test_score = cart_model.score(x_test, y_test_enc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The score of this model over training data is 0.204 and 0.000 over the testing data\n"
     ]
    }
   ],
   "source": [
    "# Print out summary of model performance \n",
    "print('The score of this model over training data is {:.3f} and {:.3f} over the testing data'.format(train_score, test_score))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Visualize the decision tree\n",
    "cart_graph = Source(export_graphviz(cart_model,\n",
    "                   feature_names = df.columns[1:],\n",
    "                   rounded = True, proportion = False, \n",
    "                  filled = True))\n",
    "SVG(cart_graph.pipe(format='svg'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Random Forest Model "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "Unknown label type: 'continuous'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-86-59e499c67d2d>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      4\u001b[0m rfc_model = RandomForestClassifier(n_estimators=50, max_features=0.2,\n\u001b[0;32m      5\u001b[0m                                    max_depth=3,random_state=3)\n\u001b[1;32m----> 6\u001b[1;33m \u001b[0mrfc_model\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx_train\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my_train\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\sklearn\\ensemble\\forest.py\u001b[0m in \u001b[0;36mfit\u001b[1;34m(self, X, y, sample_weight)\u001b[0m\n\u001b[0;32m    274\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mn_outputs_\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    275\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 276\u001b[1;33m         \u001b[0my\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mexpanded_class_weight\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_validate_y_class_weight\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    277\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    278\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"dtype\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m!=\u001b[0m \u001b[0mDOUBLE\u001b[0m \u001b[1;32mor\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mflags\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcontiguous\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\sklearn\\ensemble\\forest.py\u001b[0m in \u001b[0;36m_validate_y_class_weight\u001b[1;34m(self, y)\u001b[0m\n\u001b[0;32m    474\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    475\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_validate_y_class_weight\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 476\u001b[1;33m         \u001b[0mcheck_classification_targets\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    477\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    478\u001b[0m         \u001b[0my\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcopy\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\sklearn\\utils\\multiclass.py\u001b[0m in \u001b[0;36mcheck_classification_targets\u001b[1;34m(y)\u001b[0m\n\u001b[0;32m    169\u001b[0m     if y_type not in ['binary', 'multiclass', 'multiclass-multioutput',\n\u001b[0;32m    170\u001b[0m                       'multilabel-indicator', 'multilabel-sequences']:\n\u001b[1;32m--> 171\u001b[1;33m         \u001b[1;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Unknown label type: %r\"\u001b[0m \u001b[1;33m%\u001b[0m \u001b[0my_type\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    172\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    173\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mValueError\u001b[0m: Unknown label type: 'continuous'"
     ]
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "\n",
    "# Train the CART model\n",
    "rfc_model = RandomForestClassifier(n_estimators=50, max_features=0.2,\n",
    "                                   max_depth=3,random_state=3)\n",
    "rfc_model.fit(x_train, y_train)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model Engineering "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>vendor_id</th>\n",
       "      <th>pickup_datetime</th>\n",
       "      <th>dropoff_datetime</th>\n",
       "      <th>passenger_count</th>\n",
       "      <th>trip_distance</th>\n",
       "      <th>pickup_longitude</th>\n",
       "      <th>pickup_latitude</th>\n",
       "      <th>dropoff_longitude</th>\n",
       "      <th>dropoff_latitude</th>\n",
       "      <th>payment_type</th>\n",
       "      <th>fare_amount</th>\n",
       "      <th>surcharge</th>\n",
       "      <th>mta_tax</th>\n",
       "      <th>tip_amount</th>\n",
       "      <th>tolls_amount</th>\n",
       "      <th>total_amount</th>\n",
       "      <th>duration</th>\n",
       "      <th>Location</th>\n",
       "      <th>time_of_day</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2014-01-09 20:45:25</td>\n",
       "      <td>2014-01-09 20:52:31</td>\n",
       "      <td>1</td>\n",
       "      <td>0.7</td>\n",
       "      <td>-73.994770</td>\n",
       "      <td>40.736828</td>\n",
       "      <td>-73.982227</td>\n",
       "      <td>40.731790</td>\n",
       "      <td>CRD</td>\n",
       "      <td>6.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.40</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.90</td>\n",
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       "      <td>5</td>\n",
       "      <td>4</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2014-01-09 20:46:12</td>\n",
       "      <td>2014-01-09 20:55:12</td>\n",
       "      <td>1</td>\n",
       "      <td>1.4</td>\n",
       "      <td>-73.982392</td>\n",
       "      <td>40.773382</td>\n",
       "      <td>-73.960449</td>\n",
       "      <td>40.763995</td>\n",
       "      <td>CRD</td>\n",
       "      <td>8.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.90</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.40</td>\n",
       "      <td>540</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>2014-01-09 20:44:47</td>\n",
       "      <td>2014-01-09 20:59:46</td>\n",
       "      <td>2</td>\n",
       "      <td>2.3</td>\n",
       "      <td>-73.988570</td>\n",
       "      <td>40.739406</td>\n",
       "      <td>-73.986626</td>\n",
       "      <td>40.765217</td>\n",
       "      <td>CRD</td>\n",
       "      <td>11.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.50</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.00</td>\n",
       "      <td>899</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>2014-01-09 20:44:57</td>\n",
       "      <td>2014-01-09 20:51:40</td>\n",
       "      <td>1</td>\n",
       "      <td>1.7</td>\n",
       "      <td>-73.960213</td>\n",
       "      <td>40.770464</td>\n",
       "      <td>-73.979863</td>\n",
       "      <td>40.777050</td>\n",
       "      <td>CRD</td>\n",
       "      <td>7.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.70</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.20</td>\n",
       "      <td>403</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>2014-01-09 20:47:09</td>\n",
       "      <td>2014-01-09 20:53:32</td>\n",
       "      <td>1</td>\n",
       "      <td>0.9</td>\n",
       "      <td>-73.995371</td>\n",
       "      <td>40.717248</td>\n",
       "      <td>-73.984367</td>\n",
       "      <td>40.720524</td>\n",
       "      <td>CRD</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.75</td>\n",
       "      <td>383</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   vendor_id     pickup_datetime     dropoff_datetime  passenger_count  \\\n",
       "0          1 2014-01-09 20:45:25  2014-01-09 20:52:31                1   \n",
       "1          1 2014-01-09 20:46:12  2014-01-09 20:55:12                1   \n",
       "2          1 2014-01-09 20:44:47  2014-01-09 20:59:46                2   \n",
       "3          1 2014-01-09 20:44:57  2014-01-09 20:51:40                1   \n",
       "4          1 2014-01-09 20:47:09  2014-01-09 20:53:32                1   \n",
       "\n",
       "   trip_distance  pickup_longitude  pickup_latitude  dropoff_longitude  \\\n",
       "0            0.7        -73.994770        40.736828         -73.982227   \n",
       "1            1.4        -73.982392        40.773382         -73.960449   \n",
       "2            2.3        -73.988570        40.739406         -73.986626   \n",
       "3            1.7        -73.960213        40.770464         -73.979863   \n",
       "4            0.9        -73.995371        40.717248         -73.984367   \n",
       "\n",
       "   dropoff_latitude payment_type  fare_amount  surcharge  mta_tax  tip_amount  \\\n",
       "0         40.731790          CRD          6.5        0.5      0.5        1.40   \n",
       "1         40.763995          CRD          8.5        0.5      0.5        1.90   \n",
       "2         40.765217          CRD         11.5        0.5      0.5        1.50   \n",
       "3         40.777050          CRD          7.5        0.5      0.5        1.70   \n",
       "4         40.720524          CRD          6.0        0.5      0.5        1.75   \n",
       "\n",
       "   tolls_amount  total_amount  duration  Location time_of_day  \n",
       "0           0.0          8.90       426         5           4  \n",
       "1           0.0         11.40       540         4           4  \n",
       "2           0.0         14.00       899         5           4  \n",
       "3           0.0         10.20       403         5           4  \n",
       "4           0.0          8.75       383         5           4  "
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CRD    6483990\n",
       "UNK      53321\n",
       "NOC      21242\n",
       "DIS       6018\n",
       "CSH        199\n",
       "Name: payment_type, dtype: int64"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.payment_type.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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