NYC_CitiBike_Challenge.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "   tripduration                 starttime                  stoptime  \\\n",
       "0           393  2019-08-01 00:00:01.4680  2019-08-01 00:06:35.3780   \n",
       "1           627  2019-08-01 00:00:01.9290  2019-08-01 00:10:29.7840   \n",
       "2          1132  2019-08-01 00:00:04.0480  2019-08-01 00:18:56.1650   \n",
       "3          1780  2019-08-01 00:00:04.1630  2019-08-01 00:29:44.7940   \n",
       "4          1517  2019-08-01 00:00:05.4580  2019-08-01 00:25:23.4550   \n",
       "\n",
       "   start station id              start station name  start station latitude  \\\n",
       "0             531.0          Forsyth St & Broome St               40.718939   \n",
       "1             274.0  Lafayette Ave & Fort Greene Pl               40.686919   \n",
       "2            2000.0        Front St & Washington St               40.702551   \n",
       "3             479.0                 9 Ave & W 45 St               40.760193   \n",
       "4            3312.0                 1 Ave & E 94 St               40.781721   \n",
       "\n",
       "   start station longitude  end station id            end station name  \\\n",
       "0               -73.992663           408.0       Market St & Cherry St   \n",
       "1               -73.976682          3409.0        Bergen St & Smith St   \n",
       "2               -73.989402          3388.0     President St & Henry St   \n",
       "3               -73.991255           473.0  Rivington St & Chrystie St   \n",
       "4               -73.945940          3312.0             1 Ave & E 94 St   \n",
       "\n",
       "   end station latitude  end station longitude  bikeid    usertype  \\\n",
       "0             40.710762             -73.994004   35305  Subscriber   \n",
       "1             40.686744             -73.990632   38822  Subscriber   \n",
       "2             40.682800             -73.999904   18373  Subscriber   \n",
       "3             40.721101             -73.991925   25002  Subscriber   \n",
       "4             40.781721             -73.945940   31198  Subscriber   \n",
       "\n",
       "   birth year  gender  \n",
       "0        1996       2  \n",
       "1        1998       2  \n",
       "2        1988       1  \n",
       "3        1988       1  \n",
       "4        1965       2  "
      ],
      "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>tripduration</th>\n      <th>starttime</th>\n      <th>stoptime</th>\n      <th>start station id</th>\n      <th>start station name</th>\n      <th>start station latitude</th>\n      <th>start station longitude</th>\n      <th>end station id</th>\n      <th>end station name</th>\n      <th>end station latitude</th>\n      <th>end station longitude</th>\n      <th>bikeid</th>\n      <th>usertype</th>\n      <th>birth year</th>\n      <th>gender</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>393</td>\n      <td>2019-08-01 00:00:01.4680</td>\n      <td>2019-08-01 00:06:35.3780</td>\n      <td>531.0</td>\n      <td>Forsyth St &amp; Broome St</td>\n      <td>40.718939</td>\n      <td>-73.992663</td>\n      <td>408.0</td>\n      <td>Market St &amp; Cherry St</td>\n      <td>40.710762</td>\n      <td>-73.994004</td>\n      <td>35305</td>\n      <td>Subscriber</td>\n      <td>1996</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>627</td>\n      <td>2019-08-01 00:00:01.9290</td>\n      <td>2019-08-01 00:10:29.7840</td>\n      <td>274.0</td>\n      <td>Lafayette Ave &amp; Fort Greene Pl</td>\n      <td>40.686919</td>\n      <td>-73.976682</td>\n      <td>3409.0</td>\n      <td>Bergen St &amp; Smith St</td>\n      <td>40.686744</td>\n      <td>-73.990632</td>\n      <td>38822</td>\n      <td>Subscriber</td>\n      <td>1998</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1132</td>\n      <td>2019-08-01 00:00:04.0480</td>\n      <td>2019-08-01 00:18:56.1650</td>\n      <td>2000.0</td>\n      <td>Front St &amp; Washington St</td>\n      <td>40.702551</td>\n      <td>-73.989402</td>\n      <td>3388.0</td>\n      <td>President St &amp; Henry St</td>\n      <td>40.682800</td>\n      <td>-73.999904</td>\n      <td>18373</td>\n      <td>Subscriber</td>\n      <td>1988</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>1780</td>\n      <td>2019-08-01 00:00:04.1630</td>\n      <td>2019-08-01 00:29:44.7940</td>\n      <td>479.0</td>\n      <td>9 Ave &amp; W 45 St</td>\n      <td>40.760193</td>\n      <td>-73.991255</td>\n      <td>473.0</td>\n      <td>Rivington St &amp; Chrystie St</td>\n      <td>40.721101</td>\n      <td>-73.991925</td>\n      <td>25002</td>\n      <td>Subscriber</td>\n      <td>1988</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>1517</td>\n      <td>2019-08-01 00:00:05.4580</td>\n      <td>2019-08-01 00:25:23.4550</td>\n      <td>3312.0</td>\n      <td>1 Ave &amp; E 94 St</td>\n      <td>40.781721</td>\n      <td>-73.945940</td>\n      <td>3312.0</td>\n      <td>1 Ave &amp; E 94 St</td>\n      <td>40.781721</td>\n      <td>-73.945940</td>\n      <td>31198</td>\n      <td>Subscriber</td>\n      <td>1965</td>\n      <td>2</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "metadata": {},
     "execution_count": 4
    }
   ],
   "source": [
    "# 1. Create a DataFrame for the 201908-citibike-tripdata data. \n",
    "df = pd.read_csv('201908-citibike-tripdata.csv')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "   tripduration                 starttime                  stoptime  \\\n",
       "0           393  2019-08-01 00:00:01.4680  2019-08-01 00:06:35.3780   \n",
       "1           627  2019-08-01 00:00:01.9290  2019-08-01 00:10:29.7840   \n",
       "2          1132  2019-08-01 00:00:04.0480  2019-08-01 00:18:56.1650   \n",
       "3          1780  2019-08-01 00:00:04.1630  2019-08-01 00:29:44.7940   \n",
       "4          1517  2019-08-01 00:00:05.4580  2019-08-01 00:25:23.4550   \n",
       "\n",
       "   start station id              start station name  start station latitude  \\\n",
       "0             531.0          Forsyth St & Broome St               40.718939   \n",
       "1             274.0  Lafayette Ave & Fort Greene Pl               40.686919   \n",
       "2            2000.0        Front St & Washington St               40.702551   \n",
       "3             479.0                 9 Ave & W 45 St               40.760193   \n",
       "4            3312.0                 1 Ave & E 94 St               40.781721   \n",
       "\n",
       "   start station longitude  end station id            end station name  \\\n",
       "0               -73.992663           408.0       Market St & Cherry St   \n",
       "1               -73.976682          3409.0        Bergen St & Smith St   \n",
       "2               -73.989402          3388.0     President St & Henry St   \n",
       "3               -73.991255           473.0  Rivington St & Chrystie St   \n",
       "4               -73.945940          3312.0             1 Ave & E 94 St   \n",
       "\n",
       "   end station latitude  end station longitude  bikeid    usertype  \\\n",
       "0             40.710762             -73.994004   35305  Subscriber   \n",
       "1             40.686744             -73.990632   38822  Subscriber   \n",
       "2             40.682800             -73.999904   18373  Subscriber   \n",
       "3             40.721101             -73.991925   25002  Subscriber   \n",
       "4             40.781721             -73.945940   31198  Subscriber   \n",
       "\n",
       "   birth year  gender  \n",
       "0        1996       2  \n",
       "1        1998       2  \n",
       "2        1988       1  \n",
       "3        1988       1  \n",
       "4        1965       2  "
      ],
      "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>tripduration</th>\n      <th>starttime</th>\n      <th>stoptime</th>\n      <th>start station id</th>\n      <th>start station name</th>\n      <th>start station latitude</th>\n      <th>start station longitude</th>\n      <th>end station id</th>\n      <th>end station name</th>\n      <th>end station latitude</th>\n      <th>end station longitude</th>\n      <th>bikeid</th>\n      <th>usertype</th>\n      <th>birth year</th>\n      <th>gender</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>393</td>\n      <td>2019-08-01 00:00:01.4680</td>\n      <td>2019-08-01 00:06:35.3780</td>\n      <td>531.0</td>\n      <td>Forsyth St &amp; Broome St</td>\n      <td>40.718939</td>\n      <td>-73.992663</td>\n      <td>408.0</td>\n      <td>Market St &amp; Cherry St</td>\n      <td>40.710762</td>\n      <td>-73.994004</td>\n      <td>35305</td>\n      <td>Subscriber</td>\n      <td>1996</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>627</td>\n      <td>2019-08-01 00:00:01.9290</td>\n      <td>2019-08-01 00:10:29.7840</td>\n      <td>274.0</td>\n      <td>Lafayette Ave &amp; Fort Greene Pl</td>\n      <td>40.686919</td>\n      <td>-73.976682</td>\n      <td>3409.0</td>\n      <td>Bergen St &amp; Smith St</td>\n      <td>40.686744</td>\n      <td>-73.990632</td>\n      <td>38822</td>\n      <td>Subscriber</td>\n      <td>1998</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1132</td>\n      <td>2019-08-01 00:00:04.0480</td>\n      <td>2019-08-01 00:18:56.1650</td>\n      <td>2000.0</td>\n      <td>Front St &amp; Washington St</td>\n      <td>40.702551</td>\n      <td>-73.989402</td>\n      <td>3388.0</td>\n      <td>President St &amp; Henry St</td>\n      <td>40.682800</td>\n      <td>-73.999904</td>\n      <td>18373</td>\n      <td>Subscriber</td>\n      <td>1988</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>1780</td>\n      <td>2019-08-01 00:00:04.1630</td>\n      <td>2019-08-01 00:29:44.7940</td>\n      <td>479.0</td>\n      <td>9 Ave &amp; W 45 St</td>\n      <td>40.760193</td>\n      <td>-73.991255</td>\n      <td>473.0</td>\n      <td>Rivington St &amp; Chrystie St</td>\n      <td>40.721101</td>\n      <td>-73.991925</td>\n      <td>25002</td>\n      <td>Subscriber</td>\n      <td>1988</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>1517</td>\n      <td>2019-08-01 00:00:05.4580</td>\n      <td>2019-08-01 00:25:23.4550</td>\n      <td>3312.0</td>\n      <td>1 Ave &amp; E 94 St</td>\n      <td>40.781721</td>\n      <td>-73.945940</td>\n      <td>3312.0</td>\n      <td>1 Ave &amp; E 94 St</td>\n      <td>40.781721</td>\n      <td>-73.945940</td>\n      <td>31198</td>\n      <td>Subscriber</td>\n      <td>1965</td>\n      <td>2</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "metadata": {},
     "execution_count": 5
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "tripduration                 int64\n",
       "starttime                   object\n",
       "stoptime                    object\n",
       "start station id           float64\n",
       "start station name          object\n",
       "start station latitude     float64\n",
       "start station longitude    float64\n",
       "end station id             float64\n",
       "end station name            object\n",
       "end station latitude       float64\n",
       "end station longitude      float64\n",
       "bikeid                       int64\n",
       "usertype                    object\n",
       "birth year                   int64\n",
       "gender                       int64\n",
       "dtype: object"
      ]
     },
     "metadata": {},
     "execution_count": 3
    }
   ],
   "source": [
    "# 2. Check the datatypes of your columns. \n",
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 3. Convert the 'tripduration' column to datetime datatype.\n",
    "df['tripduration'] = pd.to_datetime(df['tripduration'], unit='s')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "tripduration               datetime64[ns]\n",
       "starttime                          object\n",
       "stoptime                           object\n",
       "start station id                  float64\n",
       "start station name                 object\n",
       "start station latitude            float64\n",
       "start station longitude           float64\n",
       "end station id                    float64\n",
       "end station name                   object\n",
       "end station latitude              float64\n",
       "end station longitude             float64\n",
       "bikeid                              int64\n",
       "usertype                           object\n",
       "birth year                          int64\n",
       "gender                              int64\n",
       "dtype: object"
      ]
     },
     "metadata": {},
     "execution_count": 7
    }
   ],
   "source": [
    "# 4. Check the datatypes of your columns. \n",
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 5. Export the Dataframe as a new CSV file without the index.\n",
    "df.to_csv('2019-08-citibike-tripdata-updated.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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