udacity_project.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Ford GoBike System Data\n",
    "\n",
    "\n",
    "## by Sarita Machado\n",
    "\n",
    "\n",
    "> This data set includes information about individual rides made in a bike-sharing system covering the greater San Francisco Bay area."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "# import all packages and set plots to be embedded inline\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sb\n",
    "import glob\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "> Load in your dataset and describe its properties through the questions below.\n",
    "Try and motivate your exploration goals through this section."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "data_files = ['C:/Users/sarita.machado/Downloads/New folder/Data Visualisation/Trip Data/201801-fordgobike-tripdata.csv',\n",
    "              'C:/Users/sarita.machado/Downloads/New folder/Data Visualisation/Trip Data/201802-fordgobike-tripdata.csv',\n",
    "              'C:/Users/sarita.machado/Downloads/New folder/Data Visualisation/Trip Data/201803-fordgobike-tripdata.csv',\n",
    "              'C:/Users/sarita.machado/Downloads/New folder/Data Visualisation/Trip Data/201804-fordgobike-tripdata.csv',\n",
    "              'C:/Users/sarita.machado/Downloads/New folder/Data Visualisation/Trip Data/201805-fordgobike-tripdata.csv',\n",
    "              'C:/Users/sarita.machado/Downloads/New folder/Data Visualisation/Trip Data/201806-fordgobike-tripdata.csv',\n",
    "              'C:/Users/sarita.machado/Downloads/New folder/Data Visualisation/Trip Data/201807-fordgobike-tripdata.csv',\n",
    "              'C:/Users/sarita.machado/Downloads/New folder/Data Visualisation/Trip Data/201808-fordgobike-tripdata.csv',\n",
    "              'C:/Users/sarita.machado/Downloads/New folder/Data Visualisation/Trip Data/201809-fordgobike-tripdata.csv',\n",
    "              'C:/Users/sarita.machado/Downloads/New folder/Data Visualisation/Trip Data/201810-fordgobike-tripdata.csv',\n",
    "              'C:/Users/sarita.machado/Downloads/New folder/Data Visualisation/Trip Data/201811-fordgobike-tripdata.csv',\n",
    "               'C:/Users/sarita.machado/Downloads/New folder/Data Visualisation/Trip Data/201812-fordgobike-tripdata.csv']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "bike_data = pd.concat([pd.read_csv(f,) for f in glob.glob(\"C:/Users/sarita.machado/Downloads/New folder/Data Visualisation/Trip Data\" + \"/*.csv\")],ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "duration_sec                 int64\n",
       "start_time                  object\n",
       "end_time                    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",
       "bike_id                      int64\n",
       "user_type                   object\n",
       "member_birth_year          float64\n",
       "member_gender               object\n",
       "bike_share_for_all_trip     object\n",
       "dtype: object"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Checking if the data is correctly imported\n",
    "bike_data.head()\n",
    "bike_data.shape\n",
    "bike_data.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### What is the structure of your dataset?\n",
    "\n",
    "> My Data set contains trip data of users in San Francisco Bay Area with fields as :-\n",
    "Trip Duration (seconds),Start Time and Date,End Time and Date,Start Station ID,Start Station Name,Start Station Latitude,Start Station Longitude,End Station ID,End Station Name,End Station Latitude,End Station Longitude,Bike ID,User Type (Subscriber or Customer – “Subscriber” = Member or “Customer” = Casual),Member Year of Birth,Member Gender\n",
    "> There are 1863721 records of trip in the dataset. Most variables are numeric in nature, but the variables user_type,station names are cateogrical in nature\n",
    "\n",
    "### What is/are the main feature(s) of interest in your dataset?\n",
    "\n",
    ">  I am interested in figuring out the factors which influence the trip duration\n",
    "\n",
    "### What features in the dataset do you think will help support your investigation into your feature(s) of interest?\n",
    "\n",
    "> 1. Trip Duration\n",
    "> 2. User Type \n",
    "> 3. Start Date and End Date\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Data Wrangling\n",
    "\n",
    "> In this section, I would like to do some data wrangling steps before getting started with the exploration\n",
    "> 1. Convert the duration in seconds to hours\n",
    "> 2. Delete bike share for all trip column\n",
    "> 3. Delete values where the station id is null\n",
    "> 4. Convert the end and start station id to int\n",
    "> 5. Segregate the start_time into indvidual fields like start_date and start_time\n",
    "> 6. Segregate the end_time into indvidual fields like end_date and end_time\n",
    "> 7. Extract day and month from start date, end date "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "#### 1. Convert the duration in seconds to hours"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "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>duration_sec</th>\n",
       "      <th>start_time</th>\n",
       "      <th>end_time</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>bike_id</th>\n",
       "      <th>user_type</th>\n",
       "      <th>member_birth_year</th>\n",
       "      <th>member_gender</th>\n",
       "      <th>bike_share_for_all_trip</th>\n",
       "      <th>duration_min</th>\n",
       "      <th>duration_hr</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>75284</td>\n",
       "      <td>2018-01-31 22:52:35.2390</td>\n",
       "      <td>2018-02-01 19:47:19.8240</td>\n",
       "      <td>120.0</td>\n",
       "      <td>Mission Dolores Park</td>\n",
       "      <td>37.761420</td>\n",
       "      <td>-122.426435</td>\n",
       "      <td>285.0</td>\n",
       "      <td>Webster St at O'Farrell St</td>\n",
       "      <td>37.783521</td>\n",
       "      <td>-122.431158</td>\n",
       "      <td>2765</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1986.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>1254.733333</td>\n",
       "      <td>20.912222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>85422</td>\n",
       "      <td>2018-01-31 16:13:34.3510</td>\n",
       "      <td>2018-02-01 15:57:17.3100</td>\n",
       "      <td>15.0</td>\n",
       "      <td>San Francisco Ferry Building (Harry Bridges Pl...</td>\n",
       "      <td>37.795392</td>\n",
       "      <td>-122.394203</td>\n",
       "      <td>15.0</td>\n",
       "      <td>San Francisco Ferry Building (Harry Bridges Pl...</td>\n",
       "      <td>37.795392</td>\n",
       "      <td>-122.394203</td>\n",
       "      <td>2815</td>\n",
       "      <td>Customer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No</td>\n",
       "      <td>1423.700000</td>\n",
       "      <td>23.728333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>71576</td>\n",
       "      <td>2018-01-31 14:23:55.8890</td>\n",
       "      <td>2018-02-01 10:16:52.1160</td>\n",
       "      <td>304.0</td>\n",
       "      <td>Jackson St at 5th St</td>\n",
       "      <td>37.348759</td>\n",
       "      <td>-121.894798</td>\n",
       "      <td>296.0</td>\n",
       "      <td>5th St at Virginia St</td>\n",
       "      <td>37.325998</td>\n",
       "      <td>-121.877120</td>\n",
       "      <td>3039</td>\n",
       "      <td>Customer</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>1192.933333</td>\n",
       "      <td>19.882222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>61076</td>\n",
       "      <td>2018-01-31 14:53:23.5620</td>\n",
       "      <td>2018-02-01 07:51:20.5000</td>\n",
       "      <td>75.0</td>\n",
       "      <td>Market St at Franklin St</td>\n",
       "      <td>37.773793</td>\n",
       "      <td>-122.421239</td>\n",
       "      <td>47.0</td>\n",
       "      <td>4th St at Harrison St</td>\n",
       "      <td>37.780955</td>\n",
       "      <td>-122.399749</td>\n",
       "      <td>321</td>\n",
       "      <td>Customer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No</td>\n",
       "      <td>1017.933333</td>\n",
       "      <td>16.965556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>39966</td>\n",
       "      <td>2018-01-31 19:52:24.6670</td>\n",
       "      <td>2018-02-01 06:58:31.0530</td>\n",
       "      <td>74.0</td>\n",
       "      <td>Laguna St at Hayes St</td>\n",
       "      <td>37.776435</td>\n",
       "      <td>-122.426244</td>\n",
       "      <td>19.0</td>\n",
       "      <td>Post St at Kearny St</td>\n",
       "      <td>37.788975</td>\n",
       "      <td>-122.403452</td>\n",
       "      <td>617</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1991.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>666.100000</td>\n",
       "      <td>11.101667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   duration_sec                start_time                  end_time  \\\n",
       "0         75284  2018-01-31 22:52:35.2390  2018-02-01 19:47:19.8240   \n",
       "1         85422  2018-01-31 16:13:34.3510  2018-02-01 15:57:17.3100   \n",
       "2         71576  2018-01-31 14:23:55.8890  2018-02-01 10:16:52.1160   \n",
       "3         61076  2018-01-31 14:53:23.5620  2018-02-01 07:51:20.5000   \n",
       "4         39966  2018-01-31 19:52:24.6670  2018-02-01 06:58:31.0530   \n",
       "\n",
       "   start_station_id                                 start_station_name  \\\n",
       "0             120.0                               Mission Dolores Park   \n",
       "1              15.0  San Francisco Ferry Building (Harry Bridges Pl...   \n",
       "2             304.0                               Jackson St at 5th St   \n",
       "3              75.0                           Market St at Franklin St   \n",
       "4              74.0                              Laguna St at Hayes St   \n",
       "\n",
       "   start_station_latitude  start_station_longitude  end_station_id  \\\n",
       "0               37.761420              -122.426435           285.0   \n",
       "1               37.795392              -122.394203            15.0   \n",
       "2               37.348759              -121.894798           296.0   \n",
       "3               37.773793              -122.421239            47.0   \n",
       "4               37.776435              -122.426244            19.0   \n",
       "\n",
       "                                    end_station_name  end_station_latitude  \\\n",
       "0                         Webster St at O'Farrell St             37.783521   \n",
       "1  San Francisco Ferry Building (Harry Bridges Pl...             37.795392   \n",
       "2                              5th St at Virginia St             37.325998   \n",
       "3                              4th St at Harrison St             37.780955   \n",
       "4                               Post St at Kearny St             37.788975   \n",
       "\n",
       "   end_station_longitude  bike_id   user_type  member_birth_year  \\\n",
       "0            -122.431158     2765  Subscriber             1986.0   \n",
       "1            -122.394203     2815    Customer                NaN   \n",
       "2            -121.877120     3039    Customer             1996.0   \n",
       "3            -122.399749      321    Customer                NaN   \n",
       "4            -122.403452      617  Subscriber             1991.0   \n",
       "\n",
       "  member_gender bike_share_for_all_trip  duration_min  duration_hr  \n",
       "0          Male                      No   1254.733333    20.912222  \n",
       "1           NaN                      No   1423.700000    23.728333  \n",
       "2          Male                      No   1192.933333    19.882222  \n",
       "3           NaN                      No   1017.933333    16.965556  \n",
       "4          Male                      No    666.100000    11.101667  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bike_data['duration_min']=bike_data['duration_sec']/60\n",
    "bike_data['duration_hr']=bike_data['duration_min']/60\n",
    "bike_data['duration_min']=bike_data['duration_min'].astype(float)\n",
    "bike_data['duration_hr']=bike_data['duration_hr'].astype(float)\n",
    "bike_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "#### 2. Delete bike share for all trip column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "bike_data.drop(columns='bike_share_for_all_trip',inplace=True,axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "#### 3. Delete values where the station id is null"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "#bike_data['start_station_id']=bike_data['start_station_id'].astype(int)\n",
    "bike_data[bike_data['start_station_id'].isna()]\n",
    "bike_data.dropna(subset=['start_station_id'],inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "#### 4. Convert the end and start station id to int"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "bike_data['start_station_id']=bike_data['start_station_id'].astype(int)\n",
    "bike_data['end_station_id']=bike_data['end_station_id'].astype(int)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "#### 5. Segregate the start_time into indvidual fields like start_date and start_time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "bike_data['start_date'] = pd.to_datetime(bike_data['start_time']).dt.date\n",
    "bike_data['start_time'] = pd.to_datetime(bike_data['start_time']).dt.time"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "#### 6. Segregate the end_time into indvidual fields like end_date and end_time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "bike_data['end_date'] = pd.to_datetime(bike_data['end_time']).dt.date\n",
    "bike_data['end_time'] = pd.to_datetime(bike_data['end_time']).dt.time\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "#### 7.Extract day and month from start date, end date "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>duration_sec</th>\n",
       "      <th>start_time</th>\n",
       "      <th>end_time</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>...</th>\n",
       "      <th>user_type</th>\n",
       "      <th>member_birth_year</th>\n",
       "      <th>member_gender</th>\n",
       "      <th>duration_min</th>\n",
       "      <th>duration_hr</th>\n",
       "      <th>start_date</th>\n",
       "      <th>end_date</th>\n",
       "      <th>start_date1</th>\n",
       "      <th>day</th>\n",
       "      <th>month</th>\n",
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       "      <th>0</th>\n",
       "      <td>75284</td>\n",
       "      <td>22:52:35.239000</td>\n",
       "      <td>19:47:19.824000</td>\n",
       "      <td>120</td>\n",
       "      <td>Mission Dolores Park</td>\n",
       "      <td>37.761420</td>\n",
       "      <td>-122.426435</td>\n",
       "      <td>285</td>\n",
       "      <td>Webster St at O'Farrell St</td>\n",
       "      <td>37.783521</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1986.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>1254.733333</td>\n",
       "      <td>20.912222</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-02-01</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>85422</td>\n",
       "      <td>16:13:34.351000</td>\n",
       "      <td>15:57:17.310000</td>\n",
       "      <td>15</td>\n",
       "      <td>San Francisco Ferry Building (Harry Bridges Pl...</td>\n",
       "      <td>37.795392</td>\n",
       "      <td>-122.394203</td>\n",
       "      <td>15</td>\n",
       "      <td>San Francisco Ferry Building (Harry Bridges Pl...</td>\n",
       "      <td>37.795392</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1423.700000</td>\n",
       "      <td>23.728333</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-02-01</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   duration_sec       start_time         end_time  start_station_id  \\\n",
       "0         75284  22:52:35.239000  19:47:19.824000               120   \n",
       "1         85422  16:13:34.351000  15:57:17.310000                15   \n",
       "\n",
       "                                  start_station_name  start_station_latitude  \\\n",
       "0                               Mission Dolores Park               37.761420   \n",
       "1  San Francisco Ferry Building (Harry Bridges Pl...               37.795392   \n",
       "\n",
       "   start_station_longitude  end_station_id  \\\n",
       "0              -122.426435             285   \n",
       "1              -122.394203              15   \n",
       "\n",
       "                                    end_station_name  end_station_latitude  \\\n",
       "0                         Webster St at O'Farrell St             37.783521   \n",
       "1  San Francisco Ferry Building (Harry Bridges Pl...             37.795392   \n",
       "\n",
       "   ...    user_type  member_birth_year member_gender  duration_min  \\\n",
       "0  ...   Subscriber             1986.0          Male   1254.733333   \n",
       "1  ...     Customer                NaN           NaN   1423.700000   \n",
       "\n",
       "  duration_hr  start_date    end_date start_date1 day month  \n",
       "0   20.912222  2018-01-31  2018-02-01  2018-01-31  31     1  \n",
       "1   23.728333  2018-01-31  2018-02-01  2018-01-31  31     1  \n",
       "\n",
       "[2 rows x 22 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##Assumption made: The day and month in consideration for bike usage is the start date \n",
    "bike_data['start_date1'] =  pd.to_datetime(bike_data['start_date'], format='%Y-%m-%d')\n",
    "bike_data['day'] = bike_data['start_date1'].apply(lambda r:r.day).astype(int)\n",
    "bike_data['month'] = bike_data['start_date1'].apply(lambda r:r.month).astype(int)\n",
    "#bike_data.head(2)\n",
    "bike_data.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "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>duration_sec</th>\n",
       "      <th>start_time</th>\n",
       "      <th>end_time</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>...</th>\n",
       "      <th>user_type</th>\n",
       "      <th>member_birth_year</th>\n",
       "      <th>member_gender</th>\n",
       "      <th>duration_min</th>\n",
       "      <th>duration_hr</th>\n",
       "      <th>start_date</th>\n",
       "      <th>end_date</th>\n",
       "      <th>start_date1</th>\n",
       "      <th>day</th>\n",
       "      <th>month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>75284</td>\n",
       "      <td>22:52:35.239000</td>\n",
       "      <td>19:47:19.824000</td>\n",
       "      <td>120</td>\n",
       "      <td>Mission Dolores Park</td>\n",
       "      <td>37.761420</td>\n",
       "      <td>-122.426435</td>\n",
       "      <td>285</td>\n",
       "      <td>Webster St at O'Farrell St</td>\n",
       "      <td>37.783521</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1986.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>1254.733333</td>\n",
       "      <td>20.912222</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-02-01</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>85422</td>\n",
       "      <td>16:13:34.351000</td>\n",
       "      <td>15:57:17.310000</td>\n",
       "      <td>15</td>\n",
       "      <td>San Francisco Ferry Building (Harry Bridges Pl...</td>\n",
       "      <td>37.795392</td>\n",
       "      <td>-122.394203</td>\n",
       "      <td>15</td>\n",
       "      <td>San Francisco Ferry Building (Harry Bridges Pl...</td>\n",
       "      <td>37.795392</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1423.700000</td>\n",
       "      <td>23.728333</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-02-01</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>71576</td>\n",
       "      <td>14:23:55.889000</td>\n",
       "      <td>10:16:52.116000</td>\n",
       "      <td>304</td>\n",
       "      <td>Jackson St at 5th St</td>\n",
       "      <td>37.348759</td>\n",
       "      <td>-121.894798</td>\n",
       "      <td>296</td>\n",
       "      <td>5th St at Virginia St</td>\n",
       "      <td>37.325998</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>1192.933333</td>\n",
       "      <td>19.882222</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-02-01</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>61076</td>\n",
       "      <td>14:53:23.562000</td>\n",
       "      <td>07:51:20.500000</td>\n",
       "      <td>75</td>\n",
       "      <td>Market St at Franklin St</td>\n",
       "      <td>37.773793</td>\n",
       "      <td>-122.421239</td>\n",
       "      <td>47</td>\n",
       "      <td>4th St at Harrison St</td>\n",
       "      <td>37.780955</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1017.933333</td>\n",
       "      <td>16.965556</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-02-01</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>39966</td>\n",
       "      <td>19:52:24.667000</td>\n",
       "      <td>06:58:31.053000</td>\n",
       "      <td>74</td>\n",
       "      <td>Laguna St at Hayes St</td>\n",
       "      <td>37.776435</td>\n",
       "      <td>-122.426244</td>\n",
       "      <td>19</td>\n",
       "      <td>Post St at Kearny St</td>\n",
       "      <td>37.788975</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1991.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>666.100000</td>\n",
       "      <td>11.101667</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-02-01</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6477</td>\n",
       "      <td>22:58:44.867000</td>\n",
       "      <td>00:46:41.908000</td>\n",
       "      <td>236</td>\n",
       "      <td>Market St at 8th St</td>\n",
       "      <td>37.803686</td>\n",
       "      <td>-122.282497</td>\n",
       "      <td>160</td>\n",
       "      <td>West Oakland BART Station</td>\n",
       "      <td>37.805318</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>107.950000</td>\n",
       "      <td>1.799167</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-02-01</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>453</td>\n",
       "      <td>23:53:53.632000</td>\n",
       "      <td>00:01:26.805000</td>\n",
       "      <td>110</td>\n",
       "      <td>17th &amp; Folsom Street Park (17th St at Folsom St)</td>\n",
       "      <td>37.763708</td>\n",
       "      <td>-122.415204</td>\n",
       "      <td>134</td>\n",
       "      <td>Valencia St at 24th St</td>\n",
       "      <td>37.752428</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1988.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>7.550000</td>\n",
       "      <td>0.125833</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-02-01</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>180</td>\n",
       "      <td>23:52:09.903000</td>\n",
       "      <td>23:55:10.807000</td>\n",
       "      <td>81</td>\n",
       "      <td>Berry St at 4th St</td>\n",
       "      <td>37.775880</td>\n",
       "      <td>-122.393170</td>\n",
       "      <td>93</td>\n",
       "      <td>4th St at Mission Bay Blvd S</td>\n",
       "      <td>37.770407</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1980.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.050000</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>996</td>\n",
       "      <td>23:34:56.004000</td>\n",
       "      <td>23:51:32.674000</td>\n",
       "      <td>134</td>\n",
       "      <td>Valencia St at 24th St</td>\n",
       "      <td>37.752428</td>\n",
       "      <td>-122.420628</td>\n",
       "      <td>4</td>\n",
       "      <td>Cyril Magnin St at Ellis St</td>\n",
       "      <td>37.785881</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1987.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>16.600000</td>\n",
       "      <td>0.276667</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>825</td>\n",
       "      <td>23:34:14.027000</td>\n",
       "      <td>23:47:59.809000</td>\n",
       "      <td>305</td>\n",
       "      <td>Ryland Park</td>\n",
       "      <td>37.342725</td>\n",
       "      <td>-121.895617</td>\n",
       "      <td>317</td>\n",
       "      <td>San Salvador St at 9th St</td>\n",
       "      <td>37.333955</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Female</td>\n",
       "      <td>13.750000</td>\n",
       "      <td>0.229167</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1316</td>\n",
       "      <td>23:24:00.416000</td>\n",
       "      <td>23:45:56.824000</td>\n",
       "      <td>98</td>\n",
       "      <td>Valencia St at 16th St</td>\n",
       "      <td>37.765052</td>\n",
       "      <td>-122.421866</td>\n",
       "      <td>4</td>\n",
       "      <td>Cyril Magnin St at Ellis St</td>\n",
       "      <td>37.785881</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21.933333</td>\n",
       "      <td>0.365556</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>432</td>\n",
       "      <td>23:34:26.484000</td>\n",
       "      <td>23:41:39.297000</td>\n",
       "      <td>89</td>\n",
       "      <td>Division St at Potrero Ave</td>\n",
       "      <td>37.769218</td>\n",
       "      <td>-122.407646</td>\n",
       "      <td>43</td>\n",
       "      <td>San Francisco Public Library (Grove St at Hyde...</td>\n",
       "      <td>37.778768</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>7.200000</td>\n",
       "      <td>0.120000</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>12 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    duration_sec       start_time         end_time  start_station_id  \\\n",
       "0          75284  22:52:35.239000  19:47:19.824000               120   \n",
       "1          85422  16:13:34.351000  15:57:17.310000                15   \n",
       "2          71576  14:23:55.889000  10:16:52.116000               304   \n",
       "3          61076  14:53:23.562000  07:51:20.500000                75   \n",
       "4          39966  19:52:24.667000  06:58:31.053000                74   \n",
       "5           6477  22:58:44.867000  00:46:41.908000               236   \n",
       "6            453  23:53:53.632000  00:01:26.805000               110   \n",
       "7            180  23:52:09.903000  23:55:10.807000                81   \n",
       "8            996  23:34:56.004000  23:51:32.674000               134   \n",
       "9            825  23:34:14.027000  23:47:59.809000               305   \n",
       "10          1316  23:24:00.416000  23:45:56.824000                98   \n",
       "11           432  23:34:26.484000  23:41:39.297000                89   \n",
       "\n",
       "                                   start_station_name  start_station_latitude  \\\n",
       "0                                Mission Dolores Park               37.761420   \n",
       "1   San Francisco Ferry Building (Harry Bridges Pl...               37.795392   \n",
       "2                                Jackson St at 5th St               37.348759   \n",
       "3                            Market St at Franklin St               37.773793   \n",
       "4                               Laguna St at Hayes St               37.776435   \n",
       "5                                 Market St at 8th St               37.803686   \n",
       "6    17th & Folsom Street Park (17th St at Folsom St)               37.763708   \n",
       "7                                  Berry St at 4th St               37.775880   \n",
       "8                              Valencia St at 24th St               37.752428   \n",
       "9                                         Ryland Park               37.342725   \n",
       "10                             Valencia St at 16th St               37.765052   \n",
       "11                         Division St at Potrero Ave               37.769218   \n",
       "\n",
       "    start_station_longitude  end_station_id  \\\n",
       "0               -122.426435             285   \n",
       "1               -122.394203              15   \n",
       "2               -121.894798             296   \n",
       "3               -122.421239              47   \n",
       "4               -122.426244              19   \n",
       "5               -122.282497             160   \n",
       "6               -122.415204             134   \n",
       "7               -122.393170              93   \n",
       "8               -122.420628               4   \n",
       "9               -121.895617             317   \n",
       "10              -122.421866               4   \n",
       "11              -122.407646              43   \n",
       "\n",
       "                                     end_station_name  end_station_latitude  \\\n",
       "0                          Webster St at O'Farrell St             37.783521   \n",
       "1   San Francisco Ferry Building (Harry Bridges Pl...             37.795392   \n",
       "2                               5th St at Virginia St             37.325998   \n",
       "3                               4th St at Harrison St             37.780955   \n",
       "4                                Post St at Kearny St             37.788975   \n",
       "5                           West Oakland BART Station             37.805318   \n",
       "6                              Valencia St at 24th St             37.752428   \n",
       "7                        4th St at Mission Bay Blvd S             37.770407   \n",
       "8                         Cyril Magnin St at Ellis St             37.785881   \n",
       "9                           San Salvador St at 9th St             37.333955   \n",
       "10                        Cyril Magnin St at Ellis St             37.785881   \n",
       "11  San Francisco Public Library (Grove St at Hyde...             37.778768   \n",
       "\n",
       "    ...    user_type  member_birth_year member_gender  duration_min  \\\n",
       "0   ...   Subscriber             1986.0          Male   1254.733333   \n",
       "1   ...     Customer                NaN           NaN   1423.700000   \n",
       "2   ...     Customer             1996.0          Male   1192.933333   \n",
       "3   ...     Customer                NaN           NaN   1017.933333   \n",
       "4   ...   Subscriber             1991.0          Male    666.100000   \n",
       "5   ...     Customer                NaN           NaN    107.950000   \n",
       "6   ...   Subscriber             1988.0          Male      7.550000   \n",
       "7   ...   Subscriber             1980.0          Male      3.000000   \n",
       "8   ...   Subscriber             1987.0          Male     16.600000   \n",
       "9   ...   Subscriber             1994.0        Female     13.750000   \n",
       "10  ...     Customer                NaN           NaN     21.933333   \n",
       "11  ...   Subscriber             1993.0          Male      7.200000   \n",
       "\n",
       "   duration_hr  start_date    end_date start_date1 day month  \n",
       "0    20.912222  2018-01-31  2018-02-01  2018-01-31  31     1  \n",
       "1    23.728333  2018-01-31  2018-02-01  2018-01-31  31     1  \n",
       "2    19.882222  2018-01-31  2018-02-01  2018-01-31  31     1  \n",
       "3    16.965556  2018-01-31  2018-02-01  2018-01-31  31     1  \n",
       "4    11.101667  2018-01-31  2018-02-01  2018-01-31  31     1  \n",
       "5     1.799167  2018-01-31  2018-02-01  2018-01-31  31     1  \n",
       "6     0.125833  2018-01-31  2018-02-01  2018-01-31  31     1  \n",
       "7     0.050000  2018-01-31  2018-01-31  2018-01-31  31     1  \n",
       "8     0.276667  2018-01-31  2018-01-31  2018-01-31  31     1  \n",
       "9     0.229167  2018-01-31  2018-01-31  2018-01-31  31     1  \n",
       "10    0.365556  2018-01-31  2018-01-31  2018-01-31  31     1  \n",
       "11    0.120000  2018-01-31  2018-01-31  2018-01-31  31     1  \n",
       "\n",
       "[12 rows x 22 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bike_data.head(12)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Univariate Exploration\n",
    "\n",
    "> In this section, investigate distributions of individual variables. If\n",
    "you see unusual points or outliers, take a deeper look to clean things up\n",
    "and prepare yourself to look at relationships between variables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    1.851950e+06\n",
       "mean     2.369443e-01\n",
       "std      6.498473e-01\n",
       "min      1.694444e-02\n",
       "25%      9.722222e-02\n",
       "50%      1.541667e-01\n",
       "75%      2.416667e-01\n",
       "max      2.399056e+01\n",
       "Name: duration_hr, dtype: float64"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bike_data.duration_hr.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Exploring the Time spent on the bike in Hours"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bins = np.arange(0, bike_data['duration_hr'].max()+1, 1)\n",
    "plt.hist(data = bike_data, x = 'duration_hr', bins = bins)\n",
    "plt.xlabel('Time Duration in Hours (hr)')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "#### This hist plot indicates we have outliers since we have values greater 3 hours on the x-axis.These values are not seen on the histplot.The code in the next slide shows the outliers present"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "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>duration_sec</th>\n",
       "      <th>start_time</th>\n",
       "      <th>end_time</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>...</th>\n",
       "      <th>user_type</th>\n",
       "      <th>member_birth_year</th>\n",
       "      <th>member_gender</th>\n",
       "      <th>duration_min</th>\n",
       "      <th>duration_hr</th>\n",
       "      <th>start_date</th>\n",
       "      <th>end_date</th>\n",
       "      <th>start_date1</th>\n",
       "      <th>day</th>\n",
       "      <th>month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>75284</td>\n",
       "      <td>22:52:35.239000</td>\n",
       "      <td>19:47:19.824000</td>\n",
       "      <td>120</td>\n",
       "      <td>Mission Dolores Park</td>\n",
       "      <td>37.761420</td>\n",
       "      <td>-122.426435</td>\n",
       "      <td>285</td>\n",
       "      <td>Webster St at O'Farrell St</td>\n",
       "      <td>37.783521</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1986.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>1254.733333</td>\n",
       "      <td>20.912222</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-02-01</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>85422</td>\n",
       "      <td>16:13:34.351000</td>\n",
       "      <td>15:57:17.310000</td>\n",
       "      <td>15</td>\n",
       "      <td>San Francisco Ferry Building (Harry Bridges Pl...</td>\n",
       "      <td>37.795392</td>\n",
       "      <td>-122.394203</td>\n",
       "      <td>15</td>\n",
       "      <td>San Francisco Ferry Building (Harry Bridges Pl...</td>\n",
       "      <td>37.795392</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1423.700000</td>\n",
       "      <td>23.728333</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-02-01</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>71576</td>\n",
       "      <td>14:23:55.889000</td>\n",
       "      <td>10:16:52.116000</td>\n",
       "      <td>304</td>\n",
       "      <td>Jackson St at 5th St</td>\n",
       "      <td>37.348759</td>\n",
       "      <td>-121.894798</td>\n",
       "      <td>296</td>\n",
       "      <td>5th St at Virginia St</td>\n",
       "      <td>37.325998</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>1192.933333</td>\n",
       "      <td>19.882222</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-02-01</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>61076</td>\n",
       "      <td>14:53:23.562000</td>\n",
       "      <td>07:51:20.500000</td>\n",
       "      <td>75</td>\n",
       "      <td>Market St at Franklin St</td>\n",
       "      <td>37.773793</td>\n",
       "      <td>-122.421239</td>\n",
       "      <td>47</td>\n",
       "      <td>4th St at Harrison St</td>\n",
       "      <td>37.780955</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1017.933333</td>\n",
       "      <td>16.965556</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-02-01</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>39966</td>\n",
       "      <td>19:52:24.667000</td>\n",
       "      <td>06:58:31.053000</td>\n",
       "      <td>74</td>\n",
       "      <td>Laguna St at Hayes St</td>\n",
       "      <td>37.776435</td>\n",
       "      <td>-122.426244</td>\n",
       "      <td>19</td>\n",
       "      <td>Post St at Kearny St</td>\n",
       "      <td>37.788975</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1991.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>666.100000</td>\n",
       "      <td>11.101667</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-02-01</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>14366</td>\n",
       "      <td>18:09:22.537000</td>\n",
       "      <td>22:08:49.392000</td>\n",
       "      <td>250</td>\n",
       "      <td>North Berkeley BART Station</td>\n",
       "      <td>37.874014</td>\n",
       "      <td>-122.283019</td>\n",
       "      <td>259</td>\n",
       "      <td>Addison St at Fourth St</td>\n",
       "      <td>37.866249</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1979.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>239.433333</td>\n",
       "      <td>3.990556</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>12167</td>\n",
       "      <td>18:45:53.099000</td>\n",
       "      <td>22:08:40.150000</td>\n",
       "      <td>64</td>\n",
       "      <td>5th St at Brannan St</td>\n",
       "      <td>37.776754</td>\n",
       "      <td>-122.399018</td>\n",
       "      <td>58</td>\n",
       "      <td>Market St at 10th St</td>\n",
       "      <td>37.776619</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>1989.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>202.783333</td>\n",
       "      <td>3.379722</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>655</th>\n",
       "      <td>20927</td>\n",
       "      <td>13:18:38.739000</td>\n",
       "      <td>19:07:25.778000</td>\n",
       "      <td>15</td>\n",
       "      <td>San Francisco Ferry Building (Harry Bridges Pl...</td>\n",
       "      <td>37.795392</td>\n",
       "      <td>-122.394203</td>\n",
       "      <td>6</td>\n",
       "      <td>The Embarcadero at Sansome St</td>\n",
       "      <td>37.804770</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>348.783333</td>\n",
       "      <td>5.813056</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>657</th>\n",
       "      <td>20944</td>\n",
       "      <td>13:18:09.755000</td>\n",
       "      <td>19:07:14.091000</td>\n",
       "      <td>15</td>\n",
       "      <td>San Francisco Ferry Building (Harry Bridges Pl...</td>\n",
       "      <td>37.795392</td>\n",
       "      <td>-122.394203</td>\n",
       "      <td>6</td>\n",
       "      <td>The Embarcadero at Sansome St</td>\n",
       "      <td>37.804770</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>349.066667</td>\n",
       "      <td>5.817778</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>746</th>\n",
       "      <td>46259</td>\n",
       "      <td>06:01:40.813000</td>\n",
       "      <td>18:52:39.958000</td>\n",
       "      <td>41</td>\n",
       "      <td>Golden Gate Ave at Polk St</td>\n",
       "      <td>37.781270</td>\n",
       "      <td>-122.418740</td>\n",
       "      <td>5</td>\n",
       "      <td>Powell St BART Station (Market St at 5th St)</td>\n",
       "      <td>37.783899</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>770.983333</td>\n",
       "      <td>12.849722</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>981</th>\n",
       "      <td>18145</td>\n",
       "      <td>13:18:31.940000</td>\n",
       "      <td>18:20:57.074000</td>\n",
       "      <td>15</td>\n",
       "      <td>San Francisco Ferry Building (Harry Bridges Pl...</td>\n",
       "      <td>37.795392</td>\n",
       "      <td>-122.394203</td>\n",
       "      <td>6</td>\n",
       "      <td>The Embarcadero at Sansome St</td>\n",
       "      <td>37.804770</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>302.416667</td>\n",
       "      <td>5.040278</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1451</th>\n",
       "      <td>13828</td>\n",
       "      <td>13:39:29.230000</td>\n",
       "      <td>17:29:57.944000</td>\n",
       "      <td>6</td>\n",
       "      <td>The Embarcadero at Sansome St</td>\n",
       "      <td>37.804770</td>\n",
       "      <td>-122.403234</td>\n",
       "      <td>6</td>\n",
       "      <td>The Embarcadero at Sansome St</td>\n",
       "      <td>37.804770</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>230.466667</td>\n",
       "      <td>3.841111</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1746</th>\n",
       "      <td>21691</td>\n",
       "      <td>10:55:41.396000</td>\n",
       "      <td>16:57:13.193000</td>\n",
       "      <td>4</td>\n",
       "      <td>Cyril Magnin St at Ellis St</td>\n",
       "      <td>37.785881</td>\n",
       "      <td>-122.408915</td>\n",
       "      <td>4</td>\n",
       "      <td>Cyril Magnin St at Ellis St</td>\n",
       "      <td>37.785881</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1965.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>361.516667</td>\n",
       "      <td>6.025278</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1837</th>\n",
       "      <td>71995</td>\n",
       "      <td>20:40:36.399000</td>\n",
       "      <td>16:40:31.807000</td>\n",
       "      <td>17</td>\n",
       "      <td>Embarcadero BART Station (Beale St at Market St)</td>\n",
       "      <td>37.792251</td>\n",
       "      <td>-122.397086</td>\n",
       "      <td>30</td>\n",
       "      <td>San Francisco Caltrain (Townsend St at 4th St)</td>\n",
       "      <td>37.776598</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1199.916667</td>\n",
       "      <td>19.998611</td>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>30</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2029</th>\n",
       "      <td>13248</td>\n",
       "      <td>12:10:10.555000</td>\n",
       "      <td>15:50:58.873000</td>\n",
       "      <td>274</td>\n",
       "      <td>Oregon St at Adeline St</td>\n",
       "      <td>37.857567</td>\n",
       "      <td>-122.267558</td>\n",
       "      <td>246</td>\n",
       "      <td>Berkeley Civic Center</td>\n",
       "      <td>37.869060</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>220.800000</td>\n",
       "      <td>3.680000</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2036</th>\n",
       "      <td>13517</td>\n",
       "      <td>12:04:06.048000</td>\n",
       "      <td>15:49:23.320000</td>\n",
       "      <td>114</td>\n",
       "      <td>Rhode Island St at 17th St</td>\n",
       "      <td>37.764478</td>\n",
       "      <td>-122.402570</td>\n",
       "      <td>100</td>\n",
       "      <td>Bryant St at 15th St</td>\n",
       "      <td>37.767100</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>1990.0</td>\n",
       "      <td>Female</td>\n",
       "      <td>225.283333</td>\n",
       "      <td>3.754722</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2228</th>\n",
       "      <td>85546</td>\n",
       "      <td>14:45:44.480000</td>\n",
       "      <td>14:31:31.053000</td>\n",
       "      <td>6</td>\n",
       "      <td>The Embarcadero at Sansome St</td>\n",
       "      <td>37.804770</td>\n",
       "      <td>-122.403234</td>\n",
       "      <td>24</td>\n",
       "      <td>Spear St at Folsom St</td>\n",
       "      <td>37.789677</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1425.766667</td>\n",
       "      <td>23.762778</td>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>30</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2266</th>\n",
       "      <td>21562</td>\n",
       "      <td>08:11:44.204000</td>\n",
       "      <td>14:11:06.973000</td>\n",
       "      <td>72</td>\n",
       "      <td>Page St at Scott St</td>\n",
       "      <td>37.772406</td>\n",
       "      <td>-122.435650</td>\n",
       "      <td>36</td>\n",
       "      <td>Folsom St at 3rd St</td>\n",
       "      <td>37.783830</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>1989.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>359.366667</td>\n",
       "      <td>5.989444</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2619</th>\n",
       "      <td>14727</td>\n",
       "      <td>08:04:46.972000</td>\n",
       "      <td>12:10:13.981000</td>\n",
       "      <td>132</td>\n",
       "      <td>24th St at Chattanooga St</td>\n",
       "      <td>37.751819</td>\n",
       "      <td>-122.426614</td>\n",
       "      <td>97</td>\n",
       "      <td>14th St at Mission St</td>\n",
       "      <td>37.768265</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1968.0</td>\n",
       "      <td>Female</td>\n",
       "      <td>245.450000</td>\n",
       "      <td>4.090833</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2669</th>\n",
       "      <td>14966</td>\n",
       "      <td>07:47:49.807000</td>\n",
       "      <td>11:57:16.484000</td>\n",
       "      <td>247</td>\n",
       "      <td>Fulton St at Bancroft Way</td>\n",
       "      <td>37.867789</td>\n",
       "      <td>-122.265896</td>\n",
       "      <td>243</td>\n",
       "      <td>Bancroft Way at College Ave</td>\n",
       "      <td>37.869360</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1998.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>249.433333</td>\n",
       "      <td>4.157222</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3036</th>\n",
       "      <td>61742</td>\n",
       "      <td>16:47:11.806000</td>\n",
       "      <td>09:56:14.639000</td>\n",
       "      <td>95</td>\n",
       "      <td>Sanchez St at 15th St</td>\n",
       "      <td>37.766219</td>\n",
       "      <td>-122.431060</td>\n",
       "      <td>106</td>\n",
       "      <td>Sanchez St at 17th St</td>\n",
       "      <td>37.763242</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1029.033333</td>\n",
       "      <td>17.150556</td>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>30</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4120</th>\n",
       "      <td>72642</td>\n",
       "      <td>11:48:05.260000</td>\n",
       "      <td>07:58:47.482000</td>\n",
       "      <td>53</td>\n",
       "      <td>Grove St at Divisadero</td>\n",
       "      <td>37.775946</td>\n",
       "      <td>-122.437777</td>\n",
       "      <td>70</td>\n",
       "      <td>Central Ave at Fell St</td>\n",
       "      <td>37.773311</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1210.700000</td>\n",
       "      <td>20.178333</td>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>30</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4153</th>\n",
       "      <td>44553</td>\n",
       "      <td>19:31:40.884000</td>\n",
       "      <td>07:54:14.815000</td>\n",
       "      <td>145</td>\n",
       "      <td>29th St at Church St</td>\n",
       "      <td>37.743684</td>\n",
       "      <td>-122.426806</td>\n",
       "      <td>145</td>\n",
       "      <td>29th St at Church St</td>\n",
       "      <td>37.743684</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>742.550000</td>\n",
       "      <td>12.375833</td>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>30</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4188</th>\n",
       "      <td>52846</td>\n",
       "      <td>17:07:56.667000</td>\n",
       "      <td>07:48:42.829000</td>\n",
       "      <td>30</td>\n",
       "      <td>San Francisco Caltrain (Townsend St at 4th St)</td>\n",
       "      <td>37.776598</td>\n",
       "      <td>-122.395282</td>\n",
       "      <td>99</td>\n",
       "      <td>Folsom St at 15th St</td>\n",
       "      <td>37.767037</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1978.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>880.766667</td>\n",
       "      <td>14.679444</td>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>30</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4202</th>\n",
       "      <td>71840</td>\n",
       "      <td>11:47:56.859000</td>\n",
       "      <td>07:45:17.280000</td>\n",
       "      <td>53</td>\n",
       "      <td>Grove St at Divisadero</td>\n",
       "      <td>37.775946</td>\n",
       "      <td>-122.437777</td>\n",
       "      <td>70</td>\n",
       "      <td>Central Ave at Fell St</td>\n",
       "      <td>37.773311</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1197.333333</td>\n",
       "      <td>19.955556</td>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>30</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4467</th>\n",
       "      <td>28319</td>\n",
       "      <td>17:47:08.863000</td>\n",
       "      <td>01:39:08.261000</td>\n",
       "      <td>130</td>\n",
       "      <td>22nd St Caltrain Station</td>\n",
       "      <td>37.757369</td>\n",
       "      <td>-122.392057</td>\n",
       "      <td>144</td>\n",
       "      <td>Precita Park</td>\n",
       "      <td>37.747300</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>471.983333</td>\n",
       "      <td>7.866389</td>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>30</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4632</th>\n",
       "      <td>13758</td>\n",
       "      <td>17:42:12.166000</td>\n",
       "      <td>21:31:30.897000</td>\n",
       "      <td>180</td>\n",
       "      <td>Telegraph Ave at 23rd St</td>\n",
       "      <td>37.812678</td>\n",
       "      <td>-122.268773</td>\n",
       "      <td>197</td>\n",
       "      <td>El Embarcadero at Grand Ave</td>\n",
       "      <td>37.808848</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1966.0</td>\n",
       "      <td>Female</td>\n",
       "      <td>229.300000</td>\n",
       "      <td>3.821667</td>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>30</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5277</th>\n",
       "      <td>39798</td>\n",
       "      <td>07:45:59.881000</td>\n",
       "      <td>18:49:18.409000</td>\n",
       "      <td>189</td>\n",
       "      <td>Genoa St at 55th St</td>\n",
       "      <td>37.839649</td>\n",
       "      <td>-122.271756</td>\n",
       "      <td>190</td>\n",
       "      <td>West St at 40th St</td>\n",
       "      <td>37.830223</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>663.300000</td>\n",
       "      <td>11.055000</td>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>30</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5535</th>\n",
       "      <td>17905</td>\n",
       "      <td>13:18:37.604000</td>\n",
       "      <td>18:17:02.888000</td>\n",
       "      <td>41</td>\n",
       "      <td>Golden Gate Ave at Polk St</td>\n",
       "      <td>37.781270</td>\n",
       "      <td>-122.418740</td>\n",
       "      <td>41</td>\n",
       "      <td>Golden Gate Ave at Polk St</td>\n",
       "      <td>37.781270</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>298.416667</td>\n",
       "      <td>4.973611</td>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>30</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5539</th>\n",
       "      <td>17879</td>\n",
       "      <td>13:18:50.445000</td>\n",
       "      <td>18:16:49.982000</td>\n",
       "      <td>41</td>\n",
       "      <td>Golden Gate Ave at Polk St</td>\n",
       "      <td>37.781270</td>\n",
       "      <td>-122.418740</td>\n",
       "      <td>41</td>\n",
       "      <td>Golden Gate Ave at Polk St</td>\n",
       "      <td>37.781270</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>297.983333</td>\n",
       "      <td>4.966389</td>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>30</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1849711</th>\n",
       "      <td>15490</td>\n",
       "      <td>08:52:01.594000</td>\n",
       "      <td>13:10:12.165000</td>\n",
       "      <td>116</td>\n",
       "      <td>Mississippi St at 17th St</td>\n",
       "      <td>37.764802</td>\n",
       "      <td>-122.394771</td>\n",
       "      <td>130</td>\n",
       "      <td>22nd St Caltrain Station</td>\n",
       "      <td>37.757718</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1991.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>258.166667</td>\n",
       "      <td>4.302778</td>\n",
       "      <td>2018-12-04</td>\n",
       "      <td>2018-12-04</td>\n",
       "      <td>2018-12-04</td>\n",
       "      <td>4</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1851920</th>\n",
       "      <td>51880</td>\n",
       "      <td>17:48:36.199000</td>\n",
       "      <td>08:13:16.863000</td>\n",
       "      <td>8</td>\n",
       "      <td>The Embarcadero at Vallejo St</td>\n",
       "      <td>37.799953</td>\n",
       "      <td>-122.398525</td>\n",
       "      <td>22</td>\n",
       "      <td>Howard St at Beale St</td>\n",
       "      <td>37.789756</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1968.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>864.666667</td>\n",
       "      <td>14.411111</td>\n",
       "      <td>2018-12-03</td>\n",
       "      <td>2018-12-04</td>\n",
       "      <td>2018-12-03</td>\n",
       "      <td>3</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1852651</th>\n",
       "      <td>15106</td>\n",
       "      <td>20:31:26.043000</td>\n",
       "      <td>00:43:12.419000</td>\n",
       "      <td>166</td>\n",
       "      <td>College Ave at Alcatraz Ave</td>\n",
       "      <td>37.851376</td>\n",
       "      <td>-122.252523</td>\n",
       "      <td>243</td>\n",
       "      <td>Bancroft Way at College Ave</td>\n",
       "      <td>37.869360</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>251.766667</td>\n",
       "      <td>4.196111</td>\n",
       "      <td>2018-12-03</td>\n",
       "      <td>2018-12-04</td>\n",
       "      <td>2018-12-03</td>\n",
       "      <td>3</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1854017</th>\n",
       "      <td>31798</td>\n",
       "      <td>09:16:17.412000</td>\n",
       "      <td>18:06:16.141000</td>\n",
       "      <td>19</td>\n",
       "      <td>Post St at Kearny St</td>\n",
       "      <td>37.788975</td>\n",
       "      <td>-122.403452</td>\n",
       "      <td>67</td>\n",
       "      <td>San Francisco Caltrain Station 2  (Townsend St...</td>\n",
       "      <td>37.776639</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1990.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>529.966667</td>\n",
       "      <td>8.832778</td>\n",
       "      <td>2018-12-03</td>\n",
       "      <td>2018-12-03</td>\n",
       "      <td>2018-12-03</td>\n",
       "      <td>3</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1854078</th>\n",
       "      <td>12271</td>\n",
       "      <td>14:35:33.159000</td>\n",
       "      <td>18:00:04.660000</td>\n",
       "      <td>339</td>\n",
       "      <td>Jackson St at 11th St</td>\n",
       "      <td>37.800002</td>\n",
       "      <td>-122.266438</td>\n",
       "      <td>194</td>\n",
       "      <td>Lakeshore Ave at Trestle Glen Rd</td>\n",
       "      <td>37.811081</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1952.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>204.516667</td>\n",
       "      <td>3.408611</td>\n",
       "      <td>2018-12-03</td>\n",
       "      <td>2018-12-03</td>\n",
       "      <td>2018-12-03</td>\n",
       "      <td>3</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1854226</th>\n",
       "      <td>29583</td>\n",
       "      <td>09:36:31.226000</td>\n",
       "      <td>17:49:34.716000</td>\n",
       "      <td>67</td>\n",
       "      <td>San Francisco Caltrain Station 2  (Townsend St...</td>\n",
       "      <td>37.776639</td>\n",
       "      <td>-122.395526</td>\n",
       "      <td>30</td>\n",
       "      <td>San Francisco Caltrain (Townsend St at 4th St)</td>\n",
       "      <td>37.776598</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1965.0</td>\n",
       "      <td>Female</td>\n",
       "      <td>493.050000</td>\n",
       "      <td>8.217500</td>\n",
       "      <td>2018-12-03</td>\n",
       "      <td>2018-12-03</td>\n",
       "      <td>2018-12-03</td>\n",
       "      <td>3</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1855287</th>\n",
       "      <td>32609</td>\n",
       "      <td>06:44:20.943000</td>\n",
       "      <td>15:47:49.950000</td>\n",
       "      <td>296</td>\n",
       "      <td>5th St at Virginia St</td>\n",
       "      <td>37.325998</td>\n",
       "      <td>-121.877120</td>\n",
       "      <td>312</td>\n",
       "      <td>San Jose Diridon Station</td>\n",
       "      <td>37.329732</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>543.483333</td>\n",
       "      <td>9.058056</td>\n",
       "      <td>2018-12-03</td>\n",
       "      <td>2018-12-03</td>\n",
       "      <td>2018-12-03</td>\n",
       "      <td>3</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1855989</th>\n",
       "      <td>72522</td>\n",
       "      <td>15:55:02.642000</td>\n",
       "      <td>12:03:44.691000</td>\n",
       "      <td>310</td>\n",
       "      <td>San Fernando St at 4th St</td>\n",
       "      <td>37.335885</td>\n",
       "      <td>-121.885660</td>\n",
       "      <td>289</td>\n",
       "      <td>5th St at Taylor St</td>\n",
       "      <td>37.351017</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1208.700000</td>\n",
       "      <td>20.145000</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-03</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1856356</th>\n",
       "      <td>48399</td>\n",
       "      <td>20:43:52.085000</td>\n",
       "      <td>10:10:31.917000</td>\n",
       "      <td>96</td>\n",
       "      <td>Dolores St at 15th St</td>\n",
       "      <td>37.766210</td>\n",
       "      <td>-122.426614</td>\n",
       "      <td>44</td>\n",
       "      <td>Civic Center/UN Plaza BART Station (Market St ...</td>\n",
       "      <td>37.781074</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>806.650000</td>\n",
       "      <td>13.444167</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-03</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1857390</th>\n",
       "      <td>55866</td>\n",
       "      <td>17:14:49.460000</td>\n",
       "      <td>08:45:55.794000</td>\n",
       "      <td>243</td>\n",
       "      <td>Bancroft Way at College Ave</td>\n",
       "      <td>37.869360</td>\n",
       "      <td>-122.254337</td>\n",
       "      <td>274</td>\n",
       "      <td>Oregon St at Adeline St</td>\n",
       "      <td>37.857567</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1962.0</td>\n",
       "      <td>Female</td>\n",
       "      <td>931.100000</td>\n",
       "      <td>15.518333</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-03</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1857957</th>\n",
       "      <td>55925</td>\n",
       "      <td>16:31:43.563000</td>\n",
       "      <td>08:03:49.067000</td>\n",
       "      <td>137</td>\n",
       "      <td>Jersey St at Castro St</td>\n",
       "      <td>37.750506</td>\n",
       "      <td>-122.433950</td>\n",
       "      <td>121</td>\n",
       "      <td>Mission Playground</td>\n",
       "      <td>37.759210</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>1987.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>932.083333</td>\n",
       "      <td>15.534722</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-03</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1858601</th>\n",
       "      <td>14898</td>\n",
       "      <td>19:21:51.929000</td>\n",
       "      <td>23:30:10.086000</td>\n",
       "      <td>15</td>\n",
       "      <td>San Francisco Ferry Building (Harry Bridges Pl...</td>\n",
       "      <td>37.795392</td>\n",
       "      <td>-122.394203</td>\n",
       "      <td>17</td>\n",
       "      <td>Embarcadero BART Station (Beale St at Market St)</td>\n",
       "      <td>37.792251</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1991.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>248.300000</td>\n",
       "      <td>4.138333</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1858744</th>\n",
       "      <td>27345</td>\n",
       "      <td>13:35:27.097000</td>\n",
       "      <td>21:11:12.704000</td>\n",
       "      <td>4</td>\n",
       "      <td>Cyril Magnin St at Ellis St</td>\n",
       "      <td>37.785881</td>\n",
       "      <td>-122.408915</td>\n",
       "      <td>371</td>\n",
       "      <td>Lombard St at Columbus Ave</td>\n",
       "      <td>37.802746</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>Female</td>\n",
       "      <td>455.750000</td>\n",
       "      <td>7.595833</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1858883</th>\n",
       "      <td>19625</td>\n",
       "      <td>14:10:35.885000</td>\n",
       "      <td>19:37:41.851000</td>\n",
       "      <td>5</td>\n",
       "      <td>Powell St BART Station (Market St at 5th St)</td>\n",
       "      <td>37.783899</td>\n",
       "      <td>-122.408445</td>\n",
       "      <td>41</td>\n",
       "      <td>Golden Gate Ave at Polk St</td>\n",
       "      <td>37.781270</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1995.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>327.083333</td>\n",
       "      <td>5.451389</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1858884</th>\n",
       "      <td>21054</td>\n",
       "      <td>13:46:41.177000</td>\n",
       "      <td>19:37:35.716000</td>\n",
       "      <td>41</td>\n",
       "      <td>Golden Gate Ave at Polk St</td>\n",
       "      <td>37.781270</td>\n",
       "      <td>-122.418740</td>\n",
       "      <td>41</td>\n",
       "      <td>Golden Gate Ave at Polk St</td>\n",
       "      <td>37.781270</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1989.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>350.900000</td>\n",
       "      <td>5.848333</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1859098</th>\n",
       "      <td>14165</td>\n",
       "      <td>14:11:46.527000</td>\n",
       "      <td>18:07:51.881000</td>\n",
       "      <td>5</td>\n",
       "      <td>Powell St BART Station (Market St at 5th St)</td>\n",
       "      <td>37.783899</td>\n",
       "      <td>-122.408445</td>\n",
       "      <td>5</td>\n",
       "      <td>Powell St BART Station (Market St at 5th St)</td>\n",
       "      <td>37.783899</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>Female</td>\n",
       "      <td>236.083333</td>\n",
       "      <td>3.934722</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1859393</th>\n",
       "      <td>18099</td>\n",
       "      <td>11:31:59.453000</td>\n",
       "      <td>16:33:38.541000</td>\n",
       "      <td>52</td>\n",
       "      <td>McAllister St at Baker St</td>\n",
       "      <td>37.777416</td>\n",
       "      <td>-122.441838</td>\n",
       "      <td>371</td>\n",
       "      <td>Lombard St at Columbus Ave</td>\n",
       "      <td>37.802746</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>301.650000</td>\n",
       "      <td>5.027500</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1859395</th>\n",
       "      <td>18100</td>\n",
       "      <td>11:31:43.824000</td>\n",
       "      <td>16:33:24.772000</td>\n",
       "      <td>52</td>\n",
       "      <td>McAllister St at Baker St</td>\n",
       "      <td>37.777416</td>\n",
       "      <td>-122.441838</td>\n",
       "      <td>371</td>\n",
       "      <td>Lombard St at Columbus Ave</td>\n",
       "      <td>37.802746</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>301.666667</td>\n",
       "      <td>5.027778</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1859396</th>\n",
       "      <td>18055</td>\n",
       "      <td>11:32:25.741000</td>\n",
       "      <td>16:33:20.914000</td>\n",
       "      <td>52</td>\n",
       "      <td>McAllister St at Baker St</td>\n",
       "      <td>37.777416</td>\n",
       "      <td>-122.441838</td>\n",
       "      <td>371</td>\n",
       "      <td>Lombard St at Columbus Ave</td>\n",
       "      <td>37.802746</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>300.916667</td>\n",
       "      <td>5.015278</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1859583</th>\n",
       "      <td>11544</td>\n",
       "      <td>12:34:56.088000</td>\n",
       "      <td>15:47:20.798000</td>\n",
       "      <td>370</td>\n",
       "      <td>Jones St at Post St</td>\n",
       "      <td>37.787327</td>\n",
       "      <td>-122.413278</td>\n",
       "      <td>369</td>\n",
       "      <td>Hyde St at Post St</td>\n",
       "      <td>37.787349</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1987.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>192.400000</td>\n",
       "      <td>3.206667</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1859584</th>\n",
       "      <td>11497</td>\n",
       "      <td>12:35:42.716000</td>\n",
       "      <td>15:47:20.031000</td>\n",
       "      <td>370</td>\n",
       "      <td>Jones St at Post St</td>\n",
       "      <td>37.787327</td>\n",
       "      <td>-122.413278</td>\n",
       "      <td>369</td>\n",
       "      <td>Hyde St at Post St</td>\n",
       "      <td>37.787349</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1968.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>191.616667</td>\n",
       "      <td>3.193611</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1859585</th>\n",
       "      <td>11550</td>\n",
       "      <td>12:34:46.756000</td>\n",
       "      <td>15:47:17.574000</td>\n",
       "      <td>370</td>\n",
       "      <td>Jones St at Post St</td>\n",
       "      <td>37.787327</td>\n",
       "      <td>-122.413278</td>\n",
       "      <td>369</td>\n",
       "      <td>Hyde St at Post St</td>\n",
       "      <td>37.787349</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1988.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>192.500000</td>\n",
       "      <td>3.208333</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1859696</th>\n",
       "      <td>21696</td>\n",
       "      <td>09:16:57.566000</td>\n",
       "      <td>15:18:34.371000</td>\n",
       "      <td>377</td>\n",
       "      <td>Fell St at Stanyan St</td>\n",
       "      <td>37.771917</td>\n",
       "      <td>-122.453704</td>\n",
       "      <td>377</td>\n",
       "      <td>Fell St at Stanyan St</td>\n",
       "      <td>37.771917</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>361.600000</td>\n",
       "      <td>6.026667</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1859697</th>\n",
       "      <td>20780</td>\n",
       "      <td>09:31:23.601000</td>\n",
       "      <td>15:17:44.287000</td>\n",
       "      <td>377</td>\n",
       "      <td>Fell St at Stanyan St</td>\n",
       "      <td>37.771917</td>\n",
       "      <td>-122.453704</td>\n",
       "      <td>377</td>\n",
       "      <td>Fell St at Stanyan St</td>\n",
       "      <td>37.771917</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>346.333333</td>\n",
       "      <td>5.772222</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1861073</th>\n",
       "      <td>23824</td>\n",
       "      <td>21:42:02.811000</td>\n",
       "      <td>04:19:07.122000</td>\n",
       "      <td>323</td>\n",
       "      <td>Broadway at Kearny</td>\n",
       "      <td>37.798014</td>\n",
       "      <td>-122.405950</td>\n",
       "      <td>44</td>\n",
       "      <td>Civic Center/UN Plaza BART Station (Market St ...</td>\n",
       "      <td>37.781074</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1982.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>397.066667</td>\n",
       "      <td>6.617778</td>\n",
       "      <td>2018-12-01</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-01</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1861122</th>\n",
       "      <td>14082</td>\n",
       "      <td>22:17:38.472000</td>\n",
       "      <td>02:12:21.431000</td>\n",
       "      <td>193</td>\n",
       "      <td>Grand Ave at Santa Clara Ave</td>\n",
       "      <td>37.812744</td>\n",
       "      <td>-122.247215</td>\n",
       "      <td>193</td>\n",
       "      <td>Grand Ave at Santa Clara Ave</td>\n",
       "      <td>37.812744</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>1991.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>234.700000</td>\n",
       "      <td>3.911667</td>\n",
       "      <td>2018-12-01</td>\n",
       "      <td>2018-12-02</td>\n",
       "      <td>2018-12-01</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1861356</th>\n",
       "      <td>11657</td>\n",
       "      <td>18:55:42.895000</td>\n",
       "      <td>22:10:00.547000</td>\n",
       "      <td>324</td>\n",
       "      <td>Union Square (Powell St at Post St)</td>\n",
       "      <td>37.788300</td>\n",
       "      <td>-122.408531</td>\n",
       "      <td>41</td>\n",
       "      <td>Golden Gate Ave at Polk St</td>\n",
       "      <td>37.781270</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1991.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>194.283333</td>\n",
       "      <td>3.238056</td>\n",
       "      <td>2018-12-01</td>\n",
       "      <td>2018-12-01</td>\n",
       "      <td>2018-12-01</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1861731</th>\n",
       "      <td>14036</td>\n",
       "      <td>14:54:39.407000</td>\n",
       "      <td>18:48:36.005000</td>\n",
       "      <td>15</td>\n",
       "      <td>San Francisco Ferry Building (Harry Bridges Pl...</td>\n",
       "      <td>37.795392</td>\n",
       "      <td>-122.394203</td>\n",
       "      <td>15</td>\n",
       "      <td>San Francisco Ferry Building (Harry Bridges Pl...</td>\n",
       "      <td>37.795392</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>233.933333</td>\n",
       "      <td>3.898889</td>\n",
       "      <td>2018-12-01</td>\n",
       "      <td>2018-12-01</td>\n",
       "      <td>2018-12-01</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1861822</th>\n",
       "      <td>12990</td>\n",
       "      <td>14:40:22.159000</td>\n",
       "      <td>18:16:52.421000</td>\n",
       "      <td>284</td>\n",
       "      <td>Yerba Buena Center for the Arts (Howard St at ...</td>\n",
       "      <td>37.784872</td>\n",
       "      <td>-122.400876</td>\n",
       "      <td>324</td>\n",
       "      <td>Union Square (Powell St at Post St)</td>\n",
       "      <td>37.788300</td>\n",
       "      <td>...</td>\n",
       "      <td>Subscriber</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>216.500000</td>\n",
       "      <td>3.608333</td>\n",
       "      <td>2018-12-01</td>\n",
       "      <td>2018-12-01</td>\n",
       "      <td>2018-12-01</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1862616</th>\n",
       "      <td>22957</td>\n",
       "      <td>08:19:06.257000</td>\n",
       "      <td>14:41:44.031000</td>\n",
       "      <td>370</td>\n",
       "      <td>Jones St at Post St</td>\n",
       "      <td>37.787327</td>\n",
       "      <td>-122.413278</td>\n",
       "      <td>5</td>\n",
       "      <td>Powell St BART Station (Market St at 5th St)</td>\n",
       "      <td>37.783899</td>\n",
       "      <td>...</td>\n",
       "      <td>Customer</td>\n",
       "      <td>1988.0</td>\n",
       "      <td>Female</td>\n",
       "      <td>382.616667</td>\n",
       "      <td>6.376944</td>\n",
       "      <td>2018-12-01</td>\n",
       "      <td>2018-12-01</td>\n",
       "      <td>2018-12-01</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7893 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         duration_sec       start_time         end_time  start_station_id  \\\n",
       "0               75284  22:52:35.239000  19:47:19.824000               120   \n",
       "1               85422  16:13:34.351000  15:57:17.310000                15   \n",
       "2               71576  14:23:55.889000  10:16:52.116000               304   \n",
       "3               61076  14:53:23.562000  07:51:20.500000                75   \n",
       "4               39966  19:52:24.667000  06:58:31.053000                74   \n",
       "85              14366  18:09:22.537000  22:08:49.392000               250   \n",
       "86              12167  18:45:53.099000  22:08:40.150000                64   \n",
       "655             20927  13:18:38.739000  19:07:25.778000                15   \n",
       "657             20944  13:18:09.755000  19:07:14.091000                15   \n",
       "746             46259  06:01:40.813000  18:52:39.958000                41   \n",
       "981             18145  13:18:31.940000  18:20:57.074000                15   \n",
       "1451            13828  13:39:29.230000  17:29:57.944000                 6   \n",
       "1746            21691  10:55:41.396000  16:57:13.193000                 4   \n",
       "1837            71995  20:40:36.399000  16:40:31.807000                17   \n",
       "2029            13248  12:10:10.555000  15:50:58.873000               274   \n",
       "2036            13517  12:04:06.048000  15:49:23.320000               114   \n",
       "2228            85546  14:45:44.480000  14:31:31.053000                 6   \n",
       "2266            21562  08:11:44.204000  14:11:06.973000                72   \n",
       "2619            14727  08:04:46.972000  12:10:13.981000               132   \n",
       "2669            14966  07:47:49.807000  11:57:16.484000               247   \n",
       "3036            61742  16:47:11.806000  09:56:14.639000                95   \n",
       "4120            72642  11:48:05.260000  07:58:47.482000                53   \n",
       "4153            44553  19:31:40.884000  07:54:14.815000               145   \n",
       "4188            52846  17:07:56.667000  07:48:42.829000                30   \n",
       "4202            71840  11:47:56.859000  07:45:17.280000                53   \n",
       "4467            28319  17:47:08.863000  01:39:08.261000               130   \n",
       "4632            13758  17:42:12.166000  21:31:30.897000               180   \n",
       "5277            39798  07:45:59.881000  18:49:18.409000               189   \n",
       "5535            17905  13:18:37.604000  18:17:02.888000                41   \n",
       "5539            17879  13:18:50.445000  18:16:49.982000                41   \n",
       "...               ...              ...              ...               ...   \n",
       "1849711         15490  08:52:01.594000  13:10:12.165000               116   \n",
       "1851920         51880  17:48:36.199000  08:13:16.863000                 8   \n",
       "1852651         15106  20:31:26.043000  00:43:12.419000               166   \n",
       "1854017         31798  09:16:17.412000  18:06:16.141000                19   \n",
       "1854078         12271  14:35:33.159000  18:00:04.660000               339   \n",
       "1854226         29583  09:36:31.226000  17:49:34.716000                67   \n",
       "1855287         32609  06:44:20.943000  15:47:49.950000               296   \n",
       "1855989         72522  15:55:02.642000  12:03:44.691000               310   \n",
       "1856356         48399  20:43:52.085000  10:10:31.917000                96   \n",
       "1857390         55866  17:14:49.460000  08:45:55.794000               243   \n",
       "1857957         55925  16:31:43.563000  08:03:49.067000               137   \n",
       "1858601         14898  19:21:51.929000  23:30:10.086000                15   \n",
       "1858744         27345  13:35:27.097000  21:11:12.704000                 4   \n",
       "1858883         19625  14:10:35.885000  19:37:41.851000                 5   \n",
       "1858884         21054  13:46:41.177000  19:37:35.716000                41   \n",
       "1859098         14165  14:11:46.527000  18:07:51.881000                 5   \n",
       "1859393         18099  11:31:59.453000  16:33:38.541000                52   \n",
       "1859395         18100  11:31:43.824000  16:33:24.772000                52   \n",
       "1859396         18055  11:32:25.741000  16:33:20.914000                52   \n",
       "1859583         11544  12:34:56.088000  15:47:20.798000               370   \n",
       "1859584         11497  12:35:42.716000  15:47:20.031000               370   \n",
       "1859585         11550  12:34:46.756000  15:47:17.574000               370   \n",
       "1859696         21696  09:16:57.566000  15:18:34.371000               377   \n",
       "1859697         20780  09:31:23.601000  15:17:44.287000               377   \n",
       "1861073         23824  21:42:02.811000  04:19:07.122000               323   \n",
       "1861122         14082  22:17:38.472000  02:12:21.431000               193   \n",
       "1861356         11657  18:55:42.895000  22:10:00.547000               324   \n",
       "1861731         14036  14:54:39.407000  18:48:36.005000                15   \n",
       "1861822         12990  14:40:22.159000  18:16:52.421000               284   \n",
       "1862616         22957  08:19:06.257000  14:41:44.031000               370   \n",
       "\n",
       "                                        start_station_name  \\\n",
       "0                                     Mission Dolores Park   \n",
       "1        San Francisco Ferry Building (Harry Bridges Pl...   \n",
       "2                                     Jackson St at 5th St   \n",
       "3                                 Market St at Franklin St   \n",
       "4                                    Laguna St at Hayes St   \n",
       "85                             North Berkeley BART Station   \n",
       "86                                    5th St at Brannan St   \n",
       "655      San Francisco Ferry Building (Harry Bridges Pl...   \n",
       "657      San Francisco Ferry Building (Harry Bridges Pl...   \n",
       "746                             Golden Gate Ave at Polk St   \n",
       "981      San Francisco Ferry Building (Harry Bridges Pl...   \n",
       "1451                         The Embarcadero at Sansome St   \n",
       "1746                           Cyril Magnin St at Ellis St   \n",
       "1837      Embarcadero BART Station (Beale St at Market St)   \n",
       "2029                               Oregon St at Adeline St   \n",
       "2036                            Rhode Island St at 17th St   \n",
       "2228                         The Embarcadero at Sansome St   \n",
       "2266                                   Page St at Scott St   \n",
       "2619                             24th St at Chattanooga St   \n",
       "2669                             Fulton St at Bancroft Way   \n",
       "3036                                 Sanchez St at 15th St   \n",
       "4120                                Grove St at Divisadero   \n",
       "4153                                  29th St at Church St   \n",
       "4188        San Francisco Caltrain (Townsend St at 4th St)   \n",
       "4202                                Grove St at Divisadero   \n",
       "4467                              22nd St Caltrain Station   \n",
       "4632                              Telegraph Ave at 23rd St   \n",
       "5277                                   Genoa St at 55th St   \n",
       "5535                            Golden Gate Ave at Polk St   \n",
       "5539                            Golden Gate Ave at Polk St   \n",
       "...                                                    ...   \n",
       "1849711                          Mississippi St at 17th St   \n",
       "1851920                      The Embarcadero at Vallejo St   \n",
       "1852651                        College Ave at Alcatraz Ave   \n",
       "1854017                               Post St at Kearny St   \n",
       "1854078                              Jackson St at 11th St   \n",
       "1854226  San Francisco Caltrain Station 2  (Townsend St...   \n",
       "1855287                              5th St at Virginia St   \n",
       "1855989                          San Fernando St at 4th St   \n",
       "1856356                              Dolores St at 15th St   \n",
       "1857390                        Bancroft Way at College Ave   \n",
       "1857957                             Jersey St at Castro St   \n",
       "1858601  San Francisco Ferry Building (Harry Bridges Pl...   \n",
       "1858744                        Cyril Magnin St at Ellis St   \n",
       "1858883       Powell St BART Station (Market St at 5th St)   \n",
       "1858884                         Golden Gate Ave at Polk St   \n",
       "1859098       Powell St BART Station (Market St at 5th St)   \n",
       "1859393                          McAllister St at Baker St   \n",
       "1859395                          McAllister St at Baker St   \n",
       "1859396                          McAllister St at Baker St   \n",
       "1859583                                Jones St at Post St   \n",
       "1859584                                Jones St at Post St   \n",
       "1859585                                Jones St at Post St   \n",
       "1859696                              Fell St at Stanyan St   \n",
       "1859697                              Fell St at Stanyan St   \n",
       "1861073                                 Broadway at Kearny   \n",
       "1861122                       Grand Ave at Santa Clara Ave   \n",
       "1861356                Union Square (Powell St at Post St)   \n",
       "1861731  San Francisco Ferry Building (Harry Bridges Pl...   \n",
       "1861822  Yerba Buena Center for the Arts (Howard St at ...   \n",
       "1862616                                Jones St at Post St   \n",
       "\n",
       "         start_station_latitude  start_station_longitude  end_station_id  \\\n",
       "0                     37.761420              -122.426435             285   \n",
       "1                     37.795392              -122.394203              15   \n",
       "2                     37.348759              -121.894798             296   \n",
       "3                     37.773793              -122.421239              47   \n",
       "4                     37.776435              -122.426244              19   \n",
       "85                    37.874014              -122.283019             259   \n",
       "86                    37.776754              -122.399018              58   \n",
       "655                   37.795392              -122.394203               6   \n",
       "657                   37.795392              -122.394203               6   \n",
       "746                   37.781270              -122.418740               5   \n",
       "981                   37.795392              -122.394203               6   \n",
       "1451                  37.804770              -122.403234               6   \n",
       "1746                  37.785881              -122.408915               4   \n",
       "1837                  37.792251              -122.397086              30   \n",
       "2029                  37.857567              -122.267558             246   \n",
       "2036                  37.764478              -122.402570             100   \n",
       "2228                  37.804770              -122.403234              24   \n",
       "2266                  37.772406              -122.435650              36   \n",
       "2619                  37.751819              -122.426614              97   \n",
       "2669                  37.867789              -122.265896             243   \n",
       "3036                  37.766219              -122.431060             106   \n",
       "4120                  37.775946              -122.437777              70   \n",
       "4153                  37.743684              -122.426806             145   \n",
       "4188                  37.776598              -122.395282              99   \n",
       "4202                  37.775946              -122.437777              70   \n",
       "4467                  37.757369              -122.392057             144   \n",
       "4632                  37.812678              -122.268773             197   \n",
       "5277                  37.839649              -122.271756             190   \n",
       "5535                  37.781270              -122.418740              41   \n",
       "5539                  37.781270              -122.418740              41   \n",
       "...                         ...                      ...             ...   \n",
       "1849711               37.764802              -122.394771             130   \n",
       "1851920               37.799953              -122.398525              22   \n",
       "1852651               37.851376              -122.252523             243   \n",
       "1854017               37.788975              -122.403452              67   \n",
       "1854078               37.800002              -122.266438             194   \n",
       "1854226               37.776639              -122.395526              30   \n",
       "1855287               37.325998              -121.877120             312   \n",
       "1855989               37.335885              -121.885660             289   \n",
       "1856356               37.766210              -122.426614              44   \n",
       "1857390               37.869360              -122.254337             274   \n",
       "1857957               37.750506              -122.433950             121   \n",
       "1858601               37.795392              -122.394203              17   \n",
       "1858744               37.785881              -122.408915             371   \n",
       "1858883               37.783899              -122.408445              41   \n",
       "1858884               37.781270              -122.418740              41   \n",
       "1859098               37.783899              -122.408445               5   \n",
       "1859393               37.777416              -122.441838             371   \n",
       "1859395               37.777416              -122.441838             371   \n",
       "1859396               37.777416              -122.441838             371   \n",
       "1859583               37.787327              -122.413278             369   \n",
       "1859584               37.787327              -122.413278             369   \n",
       "1859585               37.787327              -122.413278             369   \n",
       "1859696               37.771917              -122.453704             377   \n",
       "1859697               37.771917              -122.453704             377   \n",
       "1861073               37.798014              -122.405950              44   \n",
       "1861122               37.812744              -122.247215             193   \n",
       "1861356               37.788300              -122.408531              41   \n",
       "1861731               37.795392              -122.394203              15   \n",
       "1861822               37.784872              -122.400876             324   \n",
       "1862616               37.787327              -122.413278               5   \n",
       "\n",
       "                                          end_station_name  \\\n",
       "0                               Webster St at O'Farrell St   \n",
       "1        San Francisco Ferry Building (Harry Bridges Pl...   \n",
       "2                                    5th St at Virginia St   \n",
       "3                                    4th St at Harrison St   \n",
       "4                                     Post St at Kearny St   \n",
       "85                                 Addison St at Fourth St   \n",
       "86                                    Market St at 10th St   \n",
       "655                          The Embarcadero at Sansome St   \n",
       "657                          The Embarcadero at Sansome St   \n",
       "746           Powell St BART Station (Market St at 5th St)   \n",
       "981                          The Embarcadero at Sansome St   \n",
       "1451                         The Embarcadero at Sansome St   \n",
       "1746                           Cyril Magnin St at Ellis St   \n",
       "1837        San Francisco Caltrain (Townsend St at 4th St)   \n",
       "2029                                 Berkeley Civic Center   \n",
       "2036                                  Bryant St at 15th St   \n",
       "2228                                 Spear St at Folsom St   \n",
       "2266                                   Folsom St at 3rd St   \n",
       "2619                                 14th St at Mission St   \n",
       "2669                           Bancroft Way at College Ave   \n",
       "3036                                 Sanchez St at 17th St   \n",
       "4120                                Central Ave at Fell St   \n",
       "4153                                  29th St at Church St   \n",
       "4188                                  Folsom St at 15th St   \n",
       "4202                                Central Ave at Fell St   \n",
       "4467                                          Precita Park   \n",
       "4632                           El Embarcadero at Grand Ave   \n",
       "5277                                    West St at 40th St   \n",
       "5535                            Golden Gate Ave at Polk St   \n",
       "5539                            Golden Gate Ave at Polk St   \n",
       "...                                                    ...   \n",
       "1849711                           22nd St Caltrain Station   \n",
       "1851920                              Howard St at Beale St   \n",
       "1852651                        Bancroft Way at College Ave   \n",
       "1854017  San Francisco Caltrain Station 2  (Townsend St...   \n",
       "1854078                   Lakeshore Ave at Trestle Glen Rd   \n",
       "1854226     San Francisco Caltrain (Townsend St at 4th St)   \n",
       "1855287                           San Jose Diridon Station   \n",
       "1855989                                5th St at Taylor St   \n",
       "1856356  Civic Center/UN Plaza BART Station (Market St ...   \n",
       "1857390                            Oregon St at Adeline St   \n",
       "1857957                                 Mission Playground   \n",
       "1858601   Embarcadero BART Station (Beale St at Market St)   \n",
       "1858744                         Lombard St at Columbus Ave   \n",
       "1858883                         Golden Gate Ave at Polk St   \n",
       "1858884                         Golden Gate Ave at Polk St   \n",
       "1859098       Powell St BART Station (Market St at 5th St)   \n",
       "1859393                         Lombard St at Columbus Ave   \n",
       "1859395                         Lombard St at Columbus Ave   \n",
       "1859396                         Lombard St at Columbus Ave   \n",
       "1859583                                 Hyde St at Post St   \n",
       "1859584                                 Hyde St at Post St   \n",
       "1859585                                 Hyde St at Post St   \n",
       "1859696                              Fell St at Stanyan St   \n",
       "1859697                              Fell St at Stanyan St   \n",
       "1861073  Civic Center/UN Plaza BART Station (Market St ...   \n",
       "1861122                       Grand Ave at Santa Clara Ave   \n",
       "1861356                         Golden Gate Ave at Polk St   \n",
       "1861731  San Francisco Ferry Building (Harry Bridges Pl...   \n",
       "1861822                Union Square (Powell St at Post St)   \n",
       "1862616       Powell St BART Station (Market St at 5th St)   \n",
       "\n",
       "         end_station_latitude  ...    user_type  member_birth_year  \\\n",
       "0                   37.783521  ...   Subscriber             1986.0   \n",
       "1                   37.795392  ...     Customer                NaN   \n",
       "2                   37.325998  ...     Customer             1996.0   \n",
       "3                   37.780955  ...     Customer                NaN   \n",
       "4                   37.788975  ...   Subscriber             1991.0   \n",
       "85                  37.866249  ...   Subscriber             1979.0   \n",
       "86                  37.776619  ...     Customer             1989.0   \n",
       "655                 37.804770  ...     Customer                NaN   \n",
       "657                 37.804770  ...     Customer                NaN   \n",
       "746                 37.783899  ...     Customer                NaN   \n",
       "981                 37.804770  ...     Customer                NaN   \n",
       "1451                37.804770  ...     Customer                NaN   \n",
       "1746                37.785881  ...   Subscriber             1965.0   \n",
       "1837                37.776598  ...     Customer                NaN   \n",
       "2029                37.869060  ...     Customer             1993.0   \n",
       "2036                37.767100  ...     Customer             1990.0   \n",
       "2228                37.789677  ...     Customer                NaN   \n",
       "2266                37.783830  ...     Customer             1989.0   \n",
       "2619                37.768265  ...   Subscriber             1968.0   \n",
       "2669                37.869360  ...   Subscriber             1998.0   \n",
       "3036                37.763242  ...     Customer                NaN   \n",
       "4120                37.773311  ...     Customer                NaN   \n",
       "4153                37.743684  ...     Customer                NaN   \n",
       "4188                37.767037  ...   Subscriber             1978.0   \n",
       "4202                37.773311  ...     Customer                NaN   \n",
       "4467                37.747300  ...     Customer                NaN   \n",
       "4632                37.808848  ...   Subscriber             1966.0   \n",
       "5277                37.830223  ...     Customer                NaN   \n",
       "5535                37.781270  ...     Customer                NaN   \n",
       "5539                37.781270  ...     Customer                NaN   \n",
       "...                       ...  ...          ...                ...   \n",
       "1849711             37.757718  ...   Subscriber             1991.0   \n",
       "1851920             37.789756  ...   Subscriber             1968.0   \n",
       "1852651             37.869360  ...     Customer                NaN   \n",
       "1854017             37.776639  ...   Subscriber             1990.0   \n",
       "1854078             37.811081  ...   Subscriber             1952.0   \n",
       "1854226             37.776598  ...   Subscriber             1965.0   \n",
       "1855287             37.329732  ...     Customer             1985.0   \n",
       "1855989             37.351017  ...     Customer                NaN   \n",
       "1856356             37.781074  ...     Customer             1994.0   \n",
       "1857390             37.857567  ...   Subscriber             1962.0   \n",
       "1857957             37.759210  ...     Customer             1987.0   \n",
       "1858601             37.792251  ...   Subscriber             1991.0   \n",
       "1858744             37.802746  ...     Customer             1997.0   \n",
       "1858883             37.781270  ...   Subscriber             1995.0   \n",
       "1858884             37.781270  ...   Subscriber             1989.0   \n",
       "1859098             37.783899  ...   Subscriber             1997.0   \n",
       "1859393             37.802746  ...     Customer             1985.0   \n",
       "1859395             37.802746  ...     Customer             1985.0   \n",
       "1859396             37.802746  ...     Customer             1985.0   \n",
       "1859583             37.787349  ...   Subscriber             1987.0   \n",
       "1859584             37.787349  ...   Subscriber             1968.0   \n",
       "1859585             37.787349  ...   Subscriber             1988.0   \n",
       "1859696             37.771917  ...     Customer                NaN   \n",
       "1859697             37.771917  ...     Customer                NaN   \n",
       "1861073             37.781074  ...   Subscriber             1982.0   \n",
       "1861122             37.812744  ...     Customer             1991.0   \n",
       "1861356             37.781270  ...   Subscriber             1991.0   \n",
       "1861731             37.795392  ...     Customer                NaN   \n",
       "1861822             37.788300  ...   Subscriber             1993.0   \n",
       "1862616             37.783899  ...     Customer             1988.0   \n",
       "\n",
       "        member_gender  duration_min duration_hr  start_date    end_date  \\\n",
       "0                Male   1254.733333   20.912222  2018-01-31  2018-02-01   \n",
       "1                 NaN   1423.700000   23.728333  2018-01-31  2018-02-01   \n",
       "2                Male   1192.933333   19.882222  2018-01-31  2018-02-01   \n",
       "3                 NaN   1017.933333   16.965556  2018-01-31  2018-02-01   \n",
       "4                Male    666.100000   11.101667  2018-01-31  2018-02-01   \n",
       "85               Male    239.433333    3.990556  2018-01-31  2018-01-31   \n",
       "86               Male    202.783333    3.379722  2018-01-31  2018-01-31   \n",
       "655               NaN    348.783333    5.813056  2018-01-31  2018-01-31   \n",
       "657               NaN    349.066667    5.817778  2018-01-31  2018-01-31   \n",
       "746               NaN    770.983333   12.849722  2018-01-31  2018-01-31   \n",
       "981               NaN    302.416667    5.040278  2018-01-31  2018-01-31   \n",
       "1451              NaN    230.466667    3.841111  2018-01-31  2018-01-31   \n",
       "1746             Male    361.516667    6.025278  2018-01-31  2018-01-31   \n",
       "1837              NaN   1199.916667   19.998611  2018-01-30  2018-01-31   \n",
       "2029             Male    220.800000    3.680000  2018-01-31  2018-01-31   \n",
       "2036           Female    225.283333    3.754722  2018-01-31  2018-01-31   \n",
       "2228              NaN   1425.766667   23.762778  2018-01-30  2018-01-31   \n",
       "2266             Male    359.366667    5.989444  2018-01-31  2018-01-31   \n",
       "2619           Female    245.450000    4.090833  2018-01-31  2018-01-31   \n",
       "2669             Male    249.433333    4.157222  2018-01-31  2018-01-31   \n",
       "3036              NaN   1029.033333   17.150556  2018-01-30  2018-01-31   \n",
       "4120              NaN   1210.700000   20.178333  2018-01-30  2018-01-31   \n",
       "4153              NaN    742.550000   12.375833  2018-01-30  2018-01-31   \n",
       "4188             Male    880.766667   14.679444  2018-01-30  2018-01-31   \n",
       "4202              NaN   1197.333333   19.955556  2018-01-30  2018-01-31   \n",
       "4467              NaN    471.983333    7.866389  2018-01-30  2018-01-31   \n",
       "4632           Female    229.300000    3.821667  2018-01-30  2018-01-30   \n",
       "5277              NaN    663.300000   11.055000  2018-01-30  2018-01-30   \n",
       "5535              NaN    298.416667    4.973611  2018-01-30  2018-01-30   \n",
       "5539              NaN    297.983333    4.966389  2018-01-30  2018-01-30   \n",
       "...               ...           ...         ...         ...         ...   \n",
       "1849711          Male    258.166667    4.302778  2018-12-04  2018-12-04   \n",
       "1851920          Male    864.666667   14.411111  2018-12-03  2018-12-04   \n",
       "1852651           NaN    251.766667    4.196111  2018-12-03  2018-12-04   \n",
       "1854017          Male    529.966667    8.832778  2018-12-03  2018-12-03   \n",
       "1854078          Male    204.516667    3.408611  2018-12-03  2018-12-03   \n",
       "1854226        Female    493.050000    8.217500  2018-12-03  2018-12-03   \n",
       "1855287          Male    543.483333    9.058056  2018-12-03  2018-12-03   \n",
       "1855989           NaN   1208.700000   20.145000  2018-12-02  2018-12-03   \n",
       "1856356          Male    806.650000   13.444167  2018-12-02  2018-12-03   \n",
       "1857390        Female    931.100000   15.518333  2018-12-02  2018-12-03   \n",
       "1857957          Male    932.083333   15.534722  2018-12-02  2018-12-03   \n",
       "1858601          Male    248.300000    4.138333  2018-12-02  2018-12-02   \n",
       "1858744        Female    455.750000    7.595833  2018-12-02  2018-12-02   \n",
       "1858883          Male    327.083333    5.451389  2018-12-02  2018-12-02   \n",
       "1858884          Male    350.900000    5.848333  2018-12-02  2018-12-02   \n",
       "1859098        Female    236.083333    3.934722  2018-12-02  2018-12-02   \n",
       "1859393          Male    301.650000    5.027500  2018-12-02  2018-12-02   \n",
       "1859395          Male    301.666667    5.027778  2018-12-02  2018-12-02   \n",
       "1859396          Male    300.916667    5.015278  2018-12-02  2018-12-02   \n",
       "1859583          Male    192.400000    3.206667  2018-12-02  2018-12-02   \n",
       "1859584          Male    191.616667    3.193611  2018-12-02  2018-12-02   \n",
       "1859585          Male    192.500000    3.208333  2018-12-02  2018-12-02   \n",
       "1859696           NaN    361.600000    6.026667  2018-12-02  2018-12-02   \n",
       "1859697           NaN    346.333333    5.772222  2018-12-02  2018-12-02   \n",
       "1861073          Male    397.066667    6.617778  2018-12-01  2018-12-02   \n",
       "1861122          Male    234.700000    3.911667  2018-12-01  2018-12-02   \n",
       "1861356          Male    194.283333    3.238056  2018-12-01  2018-12-01   \n",
       "1861731           NaN    233.933333    3.898889  2018-12-01  2018-12-01   \n",
       "1861822          Male    216.500000    3.608333  2018-12-01  2018-12-01   \n",
       "1862616        Female    382.616667    6.376944  2018-12-01  2018-12-01   \n",
       "\n",
       "        start_date1 day month  \n",
       "0        2018-01-31  31     1  \n",
       "1        2018-01-31  31     1  \n",
       "2        2018-01-31  31     1  \n",
       "3        2018-01-31  31     1  \n",
       "4        2018-01-31  31     1  \n",
       "85       2018-01-31  31     1  \n",
       "86       2018-01-31  31     1  \n",
       "655      2018-01-31  31     1  \n",
       "657      2018-01-31  31     1  \n",
       "746      2018-01-31  31     1  \n",
       "981      2018-01-31  31     1  \n",
       "1451     2018-01-31  31     1  \n",
       "1746     2018-01-31  31     1  \n",
       "1837     2018-01-30  30     1  \n",
       "2029     2018-01-31  31     1  \n",
       "2036     2018-01-31  31     1  \n",
       "2228     2018-01-30  30     1  \n",
       "2266     2018-01-31  31     1  \n",
       "2619     2018-01-31  31     1  \n",
       "2669     2018-01-31  31     1  \n",
       "3036     2018-01-30  30     1  \n",
       "4120     2018-01-30  30     1  \n",
       "4153     2018-01-30  30     1  \n",
       "4188     2018-01-30  30     1  \n",
       "4202     2018-01-30  30     1  \n",
       "4467     2018-01-30  30     1  \n",
       "4632     2018-01-30  30     1  \n",
       "5277     2018-01-30  30     1  \n",
       "5535     2018-01-30  30     1  \n",
       "5539     2018-01-30  30     1  \n",
       "...             ...  ..   ...  \n",
       "1849711  2018-12-04   4    12  \n",
       "1851920  2018-12-03   3    12  \n",
       "1852651  2018-12-03   3    12  \n",
       "1854017  2018-12-03   3    12  \n",
       "1854078  2018-12-03   3    12  \n",
       "1854226  2018-12-03   3    12  \n",
       "1855287  2018-12-03   3    12  \n",
       "1855989  2018-12-02   2    12  \n",
       "1856356  2018-12-02   2    12  \n",
       "1857390  2018-12-02   2    12  \n",
       "1857957  2018-12-02   2    12  \n",
       "1858601  2018-12-02   2    12  \n",
       "1858744  2018-12-02   2    12  \n",
       "1858883  2018-12-02   2    12  \n",
       "1858884  2018-12-02   2    12  \n",
       "1859098  2018-12-02   2    12  \n",
       "1859393  2018-12-02   2    12  \n",
       "1859395  2018-12-02   2    12  \n",
       "1859396  2018-12-02   2    12  \n",
       "1859583  2018-12-02   2    12  \n",
       "1859584  2018-12-02   2    12  \n",
       "1859585  2018-12-02   2    12  \n",
       "1859696  2018-12-02   2    12  \n",
       "1859697  2018-12-02   2    12  \n",
       "1861073  2018-12-01   1    12  \n",
       "1861122  2018-12-01   1    12  \n",
       "1861356  2018-12-01   1    12  \n",
       "1861731  2018-12-01   1    12  \n",
       "1861822  2018-12-01   1    12  \n",
       "1862616  2018-12-01   1    12  \n",
       "\n",
       "[7893 rows x 22 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "low_outliers = (bike_data['duration_hr'] >3)\n",
    "bike_data.loc[low_outliers]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Exploring the Time spent on the bike in Minutes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reached\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bins = np.arange(0, bike_data['duration_min'].max()+1, 1)\n",
    "#sb.countplot(data=bike_data,x='duration_hr', color=sb.color_palette()[0])\n",
    "plt.hist(data = bike_data, x = 'duration_min', bins = bins)\n",
    "plt.xlim([0,40])\n",
    "print(\"Reached\")\n",
    "plt.xlabel('Time Duration in Minutes (min)')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### This slide indicates the data points of subcriber vis-a-vis customer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x24dd1a6b908>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sb.countplot(data=bike_data,x='user_type')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### This slide indicates the data points in a month-wise fashion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x24da8d0a8d0>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sb.countplot(data=bike_data,x='month', color=sb.color_palette()[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### This slide indicates the data points in a day-wise fashion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x24da8d0ac18>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZUAAAEKCAYAAADaa8itAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAAHaJJREFUeJzt3X+0FeV97/H3JyARjQSMR0M4WGxLvDG2/uAU6U3zo5Ii2FZMGrL0JoEovfR61Wp6kwavXcVovNc0aa2miVkuRcGmURJrpbkYpCQmvbf+APyBIrEcFeUEFBLwR+OqFvO9f8xzZHvOzOx9YOZsDufzWmuvPfPMd555Zj/77O+eeWbPUURgZmZWhbe0uwFmZnbgcFIxM7PKOKmYmVllnFTMzKwyTipmZlYZJxUzM6uMk4qZmVWmtqQi6VhJDzc8XpJ0saTDJa2StCk9j0vxknStpG5J6yWd3FDXvBS/SdK8hvIpkh5N61wrSXXtj5mZNVdbUomIJyLixIg4EZgCvALcASwEVkfEZGB1mgeYBUxOjwXAdQCSDgcWAacAU4FFvYkoxSxoWG9mXftjZmbNjRyk7UwHnoyIZyTNBj6UypcA9wCfB2YDSyP7if99ksZKGp9iV0XETgBJq4CZku4BxkTEval8KXAmcFdZQ4444oiYNGlSpTtnZnYgW7du3U8joqOV2MFKKmcB30rTR0XENoCI2CbpyFQ+AdjSsE5PKisr78kpLzVp0iTWrl27N/tgZjYsSXqm1djaB+oljQLOAL7dLDSnLPaiPK8NCyStlbR2x44dTZphZmZ7azCu/poFPBgRz6f559NpLdLz9lTeA0xsWK8T2NqkvDOnvJ+IuD4iuiKiq6OjpSM4MzPbC4ORVM5mz6kvgOVA7xVc84A7G8rnpqvApgEvptNkK4EZksalAfoZwMq07GVJ09JVX3Mb6jIzszaodUxF0iHA7wB/1FB8FbBM0nzgWWBOKl8BnA50k10pdg5AROyUdAWwJsVd3jtoD5wH3AyMJhugLx2kNzOzemm4/T+Vrq6u8EC9mVnrJK2LiK5WYv2LejMzq4yTipmZVcZJxczMKuOkYmZmlRmsX9Sb1W7K55Y2jVn35bmD0BKz4ctHKmZmVhknFTMzq4yTipmZVcZJxczMKuOkYmZmlXFSMTOzyviSYhuWfPmxXwOrh49UzMysMj5SMTNrQbMjOx/VZXykYmZmlfGRyjC0P5xL97c+swOTk8oBxB/UZtZuTir7uaGUKOo6AhpKr4HZcOcxFTMzq4yPVMz2c/vDGJi1brj3l5OKWRPD/UPCbCCcVMysKY9rWatqTSqSxgI3AMcDAZwLPAHcBkwCNgMfj4hdkgRcA5wOvAJ8OiIeTPXMA/4sVfvFiFiSyqcANwOjgRXARRERVbXf31DNzAam7oH6a4DvRcR/Ak4ANgILgdURMRlYneYBZgGT02MBcB2ApMOBRcApwFRgkaRxaZ3rUmzvejNr3h8zMytRW1KRNAb4AHAjQES8FhEvALOBJSlsCXBmmp4NLI3MfcBYSeOB04BVEbEzInYBq4CZadmYiLg3HZ0sbajLzMzaoM7TX78M7ABuknQCsA64CDgqIrYBRMQ2SUem+AnAlob1e1JZWXlPTrnZsOVTtgbtHQOrM6mMBE4GLoyI+yVdw55TXXmUUxZ7Ud6/YmkB2Wkyjj766LI2Wx/+kDKzgahzTKUH6ImI+9P8d8iSzPPp1BXpeXtD/MSG9TuBrU3KO3PK+4mI6yOiKyK6Ojo69mmnzMysWG1JJSKeA7ZIOjYVTQceB5YD81LZPODONL0cmKvMNODFdJpsJTBD0rg0QD8DWJmWvSxpWrpybG5DXWZm1gZ1/07lQuCbkkYBTwHnkCWyZZLmA88Cc1LsCrLLibvJLik+ByAidkq6AliT4i6PiJ1p+jz2XFJ8V3qYmVmb1JpUIuJhoCtn0fSc2ADOL6hnMbA4p3wt2W9gzIYc/6Cw/dwH1fMv6isykAFtD36b2YHKdyk2M7PK+EjFzKxNDsSzFk4qZrbfOxA/fA9UTipmFfLAr9VlqCRWJxUzO6AMlQ/fA5UH6s3MrDJOKmZmVplhefrL573N6uO/r+HNRypmZlYZJxUzM6uMk4qZmVVmWI6pmFn7+dLfA5OPVMzMrDJOKmZmVhknFTMzq4yTipmZVcZJxczMKuOkYmZmlXFSMTOzyjipmJlZZZxUzMysMrUmFUmbJT0q6WFJa1PZ4ZJWSdqUnselckm6VlK3pPWSTm6oZ16K3yRpXkP5lFR/d1pXde6PmZmVG4wjld+OiBMjoivNLwRWR8RkYHWaB5gFTE6PBcB1kCUhYBFwCjAVWNSbiFLMgob1Zta/O2ZmVqQdp79mA0vS9BLgzIbypZG5DxgraTxwGrAqInZGxC5gFTAzLRsTEfdGRABLG+oyM7M2qDupBHC3pHWSFqSyoyJiG0B6PjKVTwC2NKzbk8rKyntyys3MrE3qvkvx+yJiq6QjgVWSflwSmzceEntR3r/iLKEtADj66KM5orzNZma2l2o9UomIrel5O3AH2ZjI8+nUFel5ewrvASY2rN4JbG1S3plTnteO6yOiKyK6Ojo69nW3zMysQG1JRdKhkg7rnQZmAI8By4HeK7jmAXem6eXA3HQV2DTgxXR6bCUwQ9K4NEA/A1iZlr0saVq66mtuQ11mZtYGdZ7+Ogq4I13lOxL4u4j4nqQ1wDJJ84FngTkpfgVwOtANvAKcAxAROyVdAaxJcZdHxM40fR5wMzAauCs9zMysTWpLKhHxFHBCTvnPgOk55QGcX1DXYmBxTvla4Ph9bqyZmVXCv6g3M7PKOKmYmVllnFTMzKwyTipmZlYZJxUzM6uMk4qZmVXGScXMzCrjpGJmZpVxUjEzs8o4qZiZWWWcVMzMrDJOKmZmVhknFTMzq4yTipmZVcZJxczMKuOkYmZmlXFSMTOzyjipmJlZZZxUzMysMk4qZmZWGScVMzOrjJOKmZlVpvakImmEpIckfTfNHyPpfkmbJN0maVQqf2ua707LJzXUcUkqf0LSaQ3lM1NZt6SFde+LmZmVG4wjlYuAjQ3zXwKujojJwC5gfiqfD+yKiF8Frk5xSDoOOAt4LzAT+HpKVCOArwGzgOOAs1OsmZm1Sa1JRVIn8LvADWlewKnAd1LIEuDMND07zZOWT0/xs4FbI+LViHga6Aampkd3RDwVEa8Bt6ZYMzNrk7qPVP4a+FPgF2n+HcALEbE7zfcAE9L0BGALQFr+Yop/o7zPOkXl/UhaIGmtpLU7duzY130yM7MCtSUVSb8HbI+IdY3FOaHRZNlAy/sXRlwfEV0R0dXR0VHSajMz2xcja6z7fcAZkk4HDgbGkB25jJU0Mh2NdAJbU3wPMBHokTQSeDuws6G8V+M6ReVmZtYGLR2pSFrdSlmjiLgkIjojYhLZQPv3I+ITwA+Aj6WwecCdaXp5mict/35ERCo/K10ddgwwGXgAWANMTleTjUrbWN7K/piZWT1Kj1QkHQwcAhwhaRx7TjmNAd61l9v8PHCrpC8CDwE3pvIbgVskdZMdoZwFEBEbJC0DHgd2A+dHxOupfRcAK4ERwOKI2LCXbTIzswo0O/31R8DFZAlkHXuSyktkl/O2JCLuAe5J00+RXbnVN+bfgTkF618JXJlTvgJY0Wo7zMysXqVJJSKuAa6RdGFEfHWQ2mRmZkNUSwP1EfFVSf8ZmNS4TkQsraldZmY2BLWUVCTdAvwK8DDweioOwEnFzGwIm/K58o/xdV+eO6D6Wr2kuAs4Ll2NZWZmlqvVHz8+BryzzoaYmdnQ1+qRyhHA45IeAF7tLYyIM2pplZmZDUmtJpXL6myEmZkdGFq9+uuHdTfEzMyGvlav/nqZPTdrHAUcBPw8IsbU1TAzMxt6Wj1SOaxxXtKZ5Pwq3szMhre9uvV9RPwD2T/bMjMze0Orp78+2jD7FrLfrfg3K2Zm9iatXv31+w3Tu4HN+F/3mplZH62OqZxTd0PMzGzoa/WfdHVKukPSdknPS7pdUmfdjTMzs6Gl1YH6m8j+q+K7gAnAP6YyMzOzN7SaVDoi4qaI2J0eNwMdNbbLzMyGoFaTyk8lfVLSiPT4JPCzOhtmZmZDT6tJ5Vzg48BzwDbgY4AH783M7E1avaT4CmBeROwCkHQ48BWyZGNmZga0fqTy670JBSAidgIn1dMkMzMbqlpNKm+RNK53Jh2ptHqUY2Zmw0SrSeUvgX+RdIWky4F/Af6ibAVJB0t6QNIjkjZI+kIqP0bS/ZI2SbpN0qhU/tY0352WT2qo65JU/oSk0xrKZ6aybkkLB7brZmZWtZaSSkQsBf4AeB7YAXw0Im5pstqrwKkRcQJwIjBT0jTgS8DVETEZ2AXMT/HzgV0R8avA1SkOSccBZwHvBWYCX++9Cg34GjALOA44O8WamVmbtHwKKyIeBx4fQHwA/5ZmD0qPILu78X9J5UvI/qvkdWT3ErsslX8H+BtJSuW3RsSrwNOSutlz2/3uiHgKQNKtKbblNpqZWbX26tb3rUpHFA8D24FVwJPACxGxO4X0kP1Cn/S8BSAtfxF4R2N5n3WKyvPasUDSWklrd+zYUcWumZlZjlqTSkS8HhEnAp1kRxfvyQtLzypYNtDyvHZcHxFdEdHV0eEbAZiZ1aXWpNIrIl4A7gGmAWMl9Z526wS2pukeYCJAWv52YGdjeZ91isrNzKxNaksqkjokjU3To4EPAxuBH5D9Ih9gHnBnml6e5knLv5/GZZYDZ6Wrw44BJgMPAGuAyelqslFkg/nL69ofMzNrrs7fmowHlqSrtN4CLIuI70p6HLhV0heBh4AbU/yNwC1pIH4nWZIgIjZIWkY2AL8bOD8iXgeQdAGwEhgBLI6IDTXuj5mZNVFbUomI9eT86j5drTU1p/zfgTkFdV0JXJlTvgJYsc+NNTOzSgzKmIqZmQ0PTipmZlYZJxUzM6uMk4qZmVXGScXMzCrjpGJmZpVxUjEzs8o4qZiZWWWcVMzMrDJOKmZmVhknFTMzq4yTipmZVcZJxczMKuOkYmZmlXFSMTOzyjipmJlZZZxUzMysMk4qZmZWGScVMzOrjJOKmZlVxknFzMwqU1tSkTRR0g8kbZS0QdJFqfxwSaskbUrP41K5JF0rqVvSekknN9Q1L8VvkjSvoXyKpEfTOtdKUl37Y2ZmzdV5pLIb+B8R8R5gGnC+pOOAhcDqiJgMrE7zALOAyemxALgOsiQELAJOAaYCi3oTUYpZ0LDezBr3x8zMmqgtqUTEtoh4ME2/DGwEJgCzgSUpbAlwZpqeDSyNzH3AWEnjgdOAVRGxMyJ2AauAmWnZmIi4NyICWNpQl5mZtcGgjKlImgScBNwPHBUR2yBLPMCRKWwCsKVhtZ5UVlbek1NuZmZtUntSkfQ24Hbg4oh4qSw0pyz2ojyvDQskrZW0dseOHc2abGZme6nWpCLpILKE8s2I+PtU/Hw6dUV63p7Ke4CJDat3AlublHfmlPcTEddHRFdEdHV0dOzbTpmZWaE6r/4ScCOwMSL+qmHRcqD3Cq55wJ0N5XPTVWDTgBfT6bGVwAxJ49IA/QxgZVr2sqRpaVtzG+oyM7M2GFlj3e8DPgU8KunhVPY/gauAZZLmA88Cc9KyFcDpQDfwCnAOQETslHQFsCbFXR4RO9P0ecDNwGjgrvQwM7M2qS2pRMT/JX/cA2B6TnwA5xfUtRhYnFO+Fjh+H5ppZmYV8i/qzcysMk4qZmZWGScVMzOrjJOKmZlVxknFzMwq46RiZmaVcVIxM7PKOKmYmVllnFTMzKwyTipmZlYZJxUzM6uMk4qZmVXGScXMzCrjpGJmZpVxUjEzs8o4qZiZWWWcVMzMrDJOKmZmVhknFTMzq4yTipmZVcZJxczMKuOkYmZmlaktqUhaLGm7pMcayg6XtErSpvQ8LpVL0rWSuiWtl3RywzrzUvwmSfMayqdIejStc60k1bUvZmbWmjqPVG4GZvYpWwisjojJwOo0DzALmJweC4DrIEtCwCLgFGAqsKg3EaWYBQ3r9d2WmZkNstqSSkT8CNjZp3g2sCRNLwHObChfGpn7gLGSxgOnAasiYmdE7AJWATPTsjERcW9EBLC0oS4zM2uTwR5TOSoitgGk5yNT+QRgS0NcTyorK+/JKTczszbaXwbq88ZDYi/K8yuXFkhaK2ntjh079rKJZmbWzGAnlefTqSvS8/ZU3gNMbIjrBLY2Ke/MKc8VEddHRFdEdHV0dOzzTpiZWb7BTirLgd4ruOYBdzaUz01XgU0DXkynx1YCMySNSwP0M4CVadnLkqalq77mNtRlZmZtMrKuiiV9C/gQcISkHrKruK4ClkmaDzwLzEnhK4DTgW7gFeAcgIjYKekKYE2Kuzwiegf/zyO7wmw0cFd6mJlZG9WWVCLi7IJF03NiAzi/oJ7FwOKc8rXA8fvSRjMzq9b+MlBvZmYHACcVMzOrjJOKmZlVxknFzMwq46RiZmaVcVIxM7PKOKmYmVllnFTMzKwyTipmZlYZJxUzM6uMk4qZmVXGScXMzCrjpGJmZpVxUjEzs8o4qZiZWWWcVMzMrDJOKmZmVhknFTMzq4yTipmZVcZJxczMKuOkYmZmlXFSMTOzygz5pCJppqQnJHVLWtju9piZDWdDOqlIGgF8DZgFHAecLem49rbKzGz4GtJJBZgKdEfEUxHxGnArMLvNbTIzG7aGelKZAGxpmO9JZWZm1gaKiHa3Ya9JmgOcFhF/mOY/BUyNiAv7xC0AFqTZY4En+lR1BPDTFjdbR2y7t19XbLu3X1dsu7dfV2y7t19XbLu3X1fsYG7/lyKio6W1I2LIPoDfBFY2zF8CXLIX9axtZ2y7t+/98n7tD9v3fg29/cp7DPXTX2uAyZKOkTQKOAtY3uY2mZkNWyPb3YB9ERG7JV0ArARGAIsjYkObm2VmNmwN6aQCEBErgBX7WM31bY5t9/brim339uuKbff264pt9/brim339uuKbff2cw3pgXozM9u/DPUxFTMz25/syyj/UH8Ai4HtwGNN4iYCPwA2AhuAi0piDwYeAB5JsV9ooR0jgIeA7zaJ2ww8CjxMkys0gLHAd4Afp3b/Zk7Msamu3sdLwMUldX4m7dNjwLeAg0tiL0pxG/rWmfe6A4cDq4BN6XlcSeycVO8vgK4m9X45vQbrgTvS65IXd0WKeRi4G3hXs/cI8FkggCNKtn8Z8JOG1/j0snqBC8kued8A/EVJvbc11Lk5PefFnQjc1/ueIbvkvqjOE4B703vsH4ExZe//nD47viCuX3+V1JnXX0Wx/fqsKDavz0rq7dtnc4vq7NtfJXXm9VdRbL8+K4nt12cUfAYBxwD3p/66DTisIO4CoJuG9/aAPlf39gP5QHgAHwBOpnlSGQ+cnKYPA/4VOK4gVsDb0vRBqROnNan/T4C/o7Wk0lInA0uAP0zTo4CxTeJHAM+RXY+et3wC8DQwOs0vAz5dEHs8WUI5hGzc7p+AyWWve/qDXJimFwJfKol9D1lCvIc3J5W82BnAyDT9pfTIixvTMP3HwDfK3iPpj3wl8Ax7kkpevZcBn23lvQf8dnqt3prmj2zlfQr8JfDnBXXeDcxK06cD95Rsfw3wwTR9LnBF2fs/p8/+piCuX3+V1JnXX0Wx/fqsKDavz0rqfVOflcT166+y7ef0V1G9/fqsJLZfn1HwGUT2N3tWKv8GcF5B3EnAJAbwedP4GNanvyLiR8DOFuK2RcSDafplsm8Lub/cj8y/pdmD0qNw4EpSJ/C7wA0Da30xSWPIPjRuTG16LSJeaLLadODJiHimJGYkMFrSSLKEsbUg7j3AfRHxSkTsBn4IfKR3YcHrPpssEZKezyyKjYiNEdH3B6xFsXenNkD27a+zIO6lhtlDSX1W8h65GvhTGvq21fdTSex5wFUR8WqK2d6sXkkCPg58qyAuyL69Aryd1GcFsccCP0rTq4A/SLFF7/++ffY7eXF5/VVUZ0F/FcX267Mmf6tv6rNW/65L4vr1V7M6+/RXUWy/PiuJ7ddnJZ9Bp5KdvejtrzPz4iLioYjY3Pd1aNWwTip7Q9Ikskx+f0nMCEkPk51eWBURhbHAX5O90X/RwuYDuFvSunSXgCK/DOwAbpL0kKQbJB3apO6zyE5p5W844ifAV4BngW3AixFxd0H4Y8AHJL1D0iFk37YmNtn+URGxLW1rG9m3vqqdC9xVtFDSlZK2AJ8g+yZZFHcG8JOIeKTF7V4gab2kxZLGlcS9G3i/pPsl/VDSb7RQ9/uB5yNiU8Hyi4Evp/36CtkPhIs8BpyRpueQ02d93v+FfdbK30kLsf36q29sWZ81xjbrs5w25PZZn7jS/irYr9z+6hNb2md9YnP7rO9nEPAk8EJDwu4BJgzws6olTioDIOltwO1kYwQvFcVFxOsRcSLQCUyVdHxBfb8HbI+IdS024X0RcTLZXZnPl/SBgriRZKc2rouIk4Cfk52eyJV+OHoG8O2SmHFk30yPITt3faikT+bFRsRGstMWq4DvkZ2z3Z0XO1gkXZra8M2imIi4NCImppgLCuo5BLiUkqTTx3XAr5CdJ99GduqjyEhgHNkpiM8By9I32zJnU/JlgOzb9GfSfn2GdPRa4Fyy99U6slMsrzUubPX932pcWWxef+XFFvVZY2yqp7DPcurN7bOcuML+KnkN+vVXTmxhn+XE5vZZ388gsrMHfUWrn1UDMpBzZQfig+zcYemYSuw557gS+JMB1r+InHPqadn/JvvGsJlsPOMV4G9brPeyknrfCWxumH8/8H9K6poN3N1ke3OAGxvm5wJfb7Gt/wv472WvO9lg5/g0PR54olkf0WdMpSgWmEc2mHlIK/0O/FKftr0RC/wa2be6zemxm+zo7Z0t1Nt3n/vOfw/4UMP8k0BHyX6NBJ4nO0VUVOeL7PnpgICXWnwN3g08UPb+z+uzvLii/iqKLeiv0r+/xj7rG1vWZy3UO4nsaCBv/3P7q2S/8vorr97cPmuhrW/qs4byRWRJ76fsGa960y2uGuIax5I24zGVeqRvHzcCGyPir5rEdkgam6ZHAx8mu5qln4i4JCI6I2IS2emn70dE7rd/SYdKOqx3mmxA87GCep8Dtkg6NhVNBx4vaXazb7uQ/RFOk3RIej2mk53XzSXpyPR8NPDRFupfTvZhQnq+s0l8SyTNBD4PnBERr5TETW6YPYPiPns0Io6MiEmp33rIBlCfK6h3fMPsRyjos+QfyM57I+ndZBdYlN0E8MPAjyOipyRmK/DBNH0q2ZU/uRr67C3An5EN5pa9//P6rNW/k9w68/qrJLZfn+XFFvUZ2Qd8Xr15fZa3X0X9VfQavKm/Sl7Xfn1W8hr067OCz6CNZFePfSytOg9Y3epn1YAMNAsdSA+yD7ptwH+QvdHmF8T9Ftl4Ru/li29cGpoT++tklwevJ3sz/nmLbfkQJVd/kY2TPMKey/8ubVLfiWSXI64ne/OPK4g7BPgZ8PYW2viF9KZ7DLiFdNVLQew/kyWyR4DpzV534B3AarIPvdXA4SWxH0nTr5J9MKwsie0m+/cIvf32jYK429N+rSe7NHNCK+8RGr7NFdR7C9nlnuvJPoTHl8SOAv42teNB4NSyNgA3A/+tyev6W8C61A/3A1NKYi8iu6roX4Gr2PNtOff9n9Nnswri+vVXSZ15/VUU26/PimLz+qyk3r59Nrsgrl9/lW0/p7+Ktt+vz0pi+/UZBZ9BZJ8hD6TX+Nup3ry4P079tZsswd0wkM9V/6LezMwq49NfZmZWGScVMzOrjJOKmZlVxknFzMwq46RiZmaVcVIxawNJl0n6bLvbYVY1JxUzM6uMk4rZIJF0qaQnJP0T2d1lkfRfJa2R9Iik29MdCw6T9LSkg1LMGEmbe+fN9mdOKmaDQNIUslvxnER225reO9r+fUT8RkScQHYrjfmR3dr8HrJ/iUBa7/aI+I/BbbXZwDmpmA2O9wN3RPY/Zl4iu/0HwPGS/lnSo2S3b39vKr8BOCdNnwPcNKitNdtLTipmgyfvnkg3AxdExK+R3VvtYICI+H/AJEkfBEZERNmNKM32G04qZoPjR8BHJI1Od5v+/VR+GLAtjZd8os86S8lu/OijFBsyfENJs0GS/vHUXLL/kd5Ddhfnn5P9589nyO6Me1hEfDrFvxN4muzOxs3+HbTZfsFJxWw/JeljwOyI+FS722LWqpHtboCZ9Sfpq2T/n+T0drfFbCB8pGJmZpXxQL2ZmVXGScXMzCrjpGJmZpVxUjEzs8o4qZiZWWWcVMzMrDL/H4+Co6UZer4CAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sb.countplot(data=bike_data,x='day', color=sb.color_palette()[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "> Make sure that, after every plot or related series of plots, that you\n",
    "include a Markdown cell with comments about what you observed, and what\n",
    "you plan on investigating next."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Discuss the distribution(s) of your variable(s) of interest. Were there any unusual points? Did you need to perform any transformations?\n",
    "\n",
    "> I did not have to perform any transformation.\n",
    "\n",
    "### Of the features you investigated, were there any unusual distributions? Did you perform any operations on the data to tidy, adjust, or change the form of the data? If so, why did you do this?\n",
    "\n",
    "> Yes I had to tidy the data as well as perform some operations\n",
    "I did some data erangling on the start_time and end_time to extract date and time. From there I etracted the month and day for the trip data. This was done as I wanted to understand the influence of factors like month and day on the duration that the bike is ridden"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Bivariate Exploration\n",
    "\n",
    "> In this section, investigate relationships between pairs of variables in your\n",
    "data. Make sure the variables that you cover here have been introduced in some\n",
    "fashion in the previous section (univariate exploration)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Understanding the relation between the various variables "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "numeric_vars = ['day','month','duration_min','member_birth_year']\n",
    "plt.figure(figsize = [8, 5])\n",
    "sb.heatmap(bike_data[numeric_vars].corr(), annot = True, fmt = '.3f',cmap = 'vlag_r', center = 0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Investigating the relation between the user_type(Customer/Subscriber) and the time that the user spends on the bike"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 720x720 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "np.random.seed(2018)\n",
    "samples = np.random.choice(bike_data.shape[0], 2000, replace = False)\n",
    "bike_data_samp = bike_data.reindex(samples)\n",
    "\n",
    "def boxgrid(x, y, **kwargs):\n",
    "    \"\"\" Quick hack for creating box plots with seaborn's PairGrid. \"\"\"\n",
    "    default_color = sb.color_palette()[0]\n",
    "    sb.boxplot(x, y, color = default_color)\n",
    "\n",
    "plt.figure(figsize = [10, 10])\n",
    "g = sb.PairGrid(data = bike_data_samp, y_vars = 'duration_hr', x_vars = 'user_type',\n",
    "                size = 10, aspect = 1.5)\n",
    "g.map(boxgrid)\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Investigating the relation between the daywise usage of bike in minutes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# since there's only three subplots to create, using the full data should be fine.\n",
    "plt.figure(figsize = [8, 8])\n",
    "sb.barplot(data = bike_data_samp, x = 'day', y = 'duration_min', palette = 'Blues')\n",
    "plt.xticks(rotation=90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Investigating the relation between the month-wise usage of bike in minutes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = [10, 10])\n",
    "#month_order=bike_data_samp['month'].value_counts.index\n",
    "sb.barplot(data = bike_data_samp, x = 'month', y = 'duration_min')\n",
    "plt.xticks(rotation=90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "#plt.scatter(data = bike_data_samp, x = 'start_station_id', y = 'end_station_id',c='duration_min', alpha = 1/10, cmap='viridis_r')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Talk about some of the relationships you observed in this part of the investigation. How did the feature(s) of interest vary with other features in the dataset?\n",
    "\n",
    "> Yes. In the univariate exploration, the number of subscribers who used bikes were more than customers. However, in the bivariate exploration, the avearge time spent by customers were more than subscribers\n",
    "> Another interesting feature, is the duration (in min) spent on the bike gradually reduces over the months\n",
    "### Did you observe any interesting relationships between the other features (not the main feature(s) of interest)?\n",
    "\n",
    "> Since most of the values are discrete in nature. I did not observer a correlation between the other features"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Multivariate Exploration\n",
    "\n",
    "> Create plots of three or more variables to investigate your data even\n",
    "further. Make sure that your investigations are justified, and follow from\n",
    "your work in the previous sections."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "### We are trying to understand the relation between the month, time spent on bike and a day-wise view"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "def hist2dgrid(x, y, **kwargs):\n",
    "    \"\"\" Quick hack for creating heat maps with seaborn's PairGrid. \"\"\"\n",
    "    palette = kwargs.pop('color')\n",
    "    #bins_x = np.arange(cuberoot_trans(.2), cuberoot_trans(3.5)+.05, .05)\n",
    "    #bins_y = np.arange(2.4, 4.3+0.1, 0.1)\n",
    "    plt.hist2d(x, y, cmap = palette, cmin = 0.5)\n",
    "    #plt.xticks(cuberoot_trans(np.array(carat_ticks)), carat_ticks)\n",
    "    #plt.yticks(log_trans(np.array([500, 1e3, 2e3, 5e3, 1e4, 2e4])), [500, '1k', '2k', '5k', '10k', '20k'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x864 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create faceted heat maps on months of the year\n",
    "g = sb.FacetGrid(data = bike_data_samp, col = 'month', col_wrap = 3, size = 3)\n",
    "g.map(hist2dgrid, 'day', 'duration_min', color = 'inferno_r')\n",
    "g.set_xlabels('Months')\n",
    "g.set_ylabels('Duration')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\sarita.machado\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\seaborn\\axisgrid.py:703: UserWarning: Using the pointplot function without specifying `order` is likely to produce an incorrect plot.\n",
      "  warnings.warn(warning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "([<matplotlib.axis.XTick at 0x24d82efab38>,\n",
       "  <matplotlib.axis.XTick at 0x24d82a8d3c8>,\n",
       "  <matplotlib.axis.XTick at 0x24dc7d21320>,\n",
       "  <matplotlib.axis.XTick at 0x24dc85393c8>,\n",
       "  <matplotlib.axis.XTick at 0x24dc8539860>,\n",
       "  <matplotlib.axis.XTick at 0x24dc8539b00>,\n",
       "  <matplotlib.axis.XTick at 0x24de108b3c8>,\n",
       "  <matplotlib.axis.XTick at 0x24dbea764a8>,\n",
       "  <matplotlib.axis.XTick at 0x24dbea76da0>,\n",
       "  <matplotlib.axis.XTick at 0x24dbea7c2b0>,\n",
       "  <matplotlib.axis.XTick at 0x24dbea7c780>,\n",
       "  <matplotlib.axis.XTick at 0x24dbea7cc50>,\n",
       "  <matplotlib.axis.XTick at 0x24dbea7c8d0>,\n",
       "  <matplotlib.axis.XTick at 0x24dbea76d68>,\n",
       "  <matplotlib.axis.XTick at 0x24dbf91b2e8>,\n",
       "  <matplotlib.axis.XTick at 0x24dbf91b908>,\n",
       "  <matplotlib.axis.XTick at 0x24dbf91be10>,\n",
       "  <matplotlib.axis.XTick at 0x24dbf92f358>,\n",
       "  <matplotlib.axis.XTick at 0x24dbf92f860>,\n",
       "  <matplotlib.axis.XTick at 0x24dbf92fd68>,\n",
       "  <matplotlib.axis.XTick at 0x24dbf9202b0>,\n",
       "  <matplotlib.axis.XTick at 0x24dbf9207b8>,\n",
       "  <matplotlib.axis.XTick at 0x24dbf92f940>,\n",
       "  <matplotlib.axis.XTick at 0x24dbf91b320>,\n",
       "  <matplotlib.axis.XTick at 0x24dbf9200b8>,\n",
       "  <matplotlib.axis.XTick at 0x24dbf9160b8>,\n",
       "  <matplotlib.axis.XTick at 0x24dbea6ce10>,\n",
       "  <matplotlib.axis.XTick at 0x24dbf92f908>,\n",
       "  <matplotlib.axis.XTick at 0x24dc78ad7b8>,\n",
       "  <matplotlib.axis.XTick at 0x24dc8b1c550>,\n",
       "  <matplotlib.axis.XTick at 0x24daabe51d0>],\n",
       " <a list of 31 Text xticklabel objects>)"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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NT+zF0nVL1OcDhBmH0ez3tup/X13X6Tr/c9l4XXTsAGWnJkS0zWZ/QG+tLdUPXlypmkafctMS9N4Pz+5WSu4PWL29rlTzVpeorsmniQOzdOWUQd3+R2ho9uudDWXaX9usEbmpOmlYdmuo8PHWfbr3jQ1atqP93TAuOW6A7jx3lIb1TY3683buq9ODb2/Uvz7dpbZf6+MGZekH54/WKU43Hmutlu+s0KbSamWlxOuMUXlKTuhercL6kio98eF2Ld9RocR4j84fn69rpg5WVkpkf7+2/rmiSL+bv1lbnQun5HiPfv2lY/XFSQOj3lZxZb1mv7dNb6wpUUNzQJMGZ+nrpw7T1OE5stZq2Y5yPfnRDr2+uljNB53gTx6cpeumD9UFx+Yr0Runhma/nv+kUL9+bZ0afQGlJMRp9qwpOnlEX9U0+vTM4h16bNE27a050DXIY6SLJg7QbWeN0Jj8oycdjhVrrYrK69XkD2hwdoriD7H5c22jT7VNPuWkdn2SfrQKBKwufOS9dkFrWxdN7K/ff3XyYS5VbAQCVm+sKdFLy4u0p6ZJw3JSdM20ITpxaPbhKkLMwoxlO8p1+aMfhu2q+Mw3purkEdF18aysb9bcT3dpQ0nwGHLJcQUanZ/ezVIHx2nYXFajRG+cRualdSvE/sv72/TLf68NuewnF4/TTacO63b5Pk+stVpXXK2bn1qqovL6iN4T5zHKS09Uv4wk9ctIVH5GkvplJgWfM5KUmujVNX/+WLVN/pDvv+rEQbr7yxMjLuPmsmp9bfYSlVS1r2AYmpOip78xTQVZyWHe2bnKumY1+QPqm5bQrQqev36wTT9/JfR3LDslQQu/d2ZUg7FvKq3WT+au1sdbD9yV7txx/fTLS8e3q8iKVJMvoPnrSrVtX636piVq5oR8ZXTjYnpjabW+/sTS1hZOUnAHddOpw/Sji8b2WuXYoo17dONfP2lXadfify6boGunDemFUgXNfm+rfvP6evnblC0t0avfXT3piGhxXtXQrO17a5WRFK8hOSnd/hsu21GuPy/aqvnrSxWwUl56ov7+zem92iL5Kae7XCgTCjI097ZT3XaeR5hxJNpf26Q315To0Xe3tOtG0Zm89ESbQGbBAAAgAElEQVSN7Z+hMf3TNTY/Q2P7Z2h4bmq7i5i9NY26bs6SDrXmw/qm6skbT9Kg7Mj/ueqafLrxr5+0O6hIUmpinObMOlHThudEvC1Jevmz3frpv1arov5Arf2ofmm6fcZIPf9Jod7btLfd+mePydP3zhvdI82iNpRU6743N+ittaXt5p9yTI6umTpEf3hns1bvOvA7y0jy6qdfGK/LT4guNJi3uljffmZFhwPLoOxkPX/zdA2I4oTjyY+266dz14RcFm3t4dY9Nbrijx9pX23HO8F8aXKB1hdXd/jOJMV7dOlxBbp2+hBNKMgMud2z7ntH2/bWaljfVC383pntljU0+/XC0kL96d2trS1LWpwztp++ffYxOt6ptVlZVKG/Ly1ScWWDBvZJ1pVTBnX7715W3aAXlxVpS1mtslPjddmkAo0fELr8bvX22lLd9+aB1kt56Ym66dRh+sZpw6O+6NlUWq175m3QAudAnJueqOumDdE3zxxxyAHJoSrcX6fnPynUtr21yk1P1JcmF2jiwO7V9PWEDzbv1TWzF4ddbiR9cNfZUf2fS8EAeu3uKvkCVmP7px9STWujz6/FW/erttGncQMyNCQn+hDY5w/o28+s0Lw1JR2W3XnOKN1xzsiot1nb6NOrq4pVuL9OeemJunjiAPXpPKCPWZjxnWdX6JXPdod9z/ThOZo9a4pSEyP7O3ywea+++bdlqm5oPzjyDacM1U8vHhfVSXKzP6D739yov328o3Ww5WF9U/XDmaM1c0L/iLdT3dCsab+eH/ZiOjUhTot/dI7SIvwZW+ytadTC9WVq8AU0eXDWIe1bff6Almzfr4q6Zo3ql65j8g5fy71mf0BLtu3XW2tL9dba0g7HqFiLM9Kd545STlqiUhO9Sk/0Ki3Jq9QEr9KTvEpN9Cot0asEr0eBgNX5Dy0Ke0v0k4Zl64Vbpkf1+R9t2acH3tqgT7YHK4+G5qToljNG6KoTB0X8fQ0ErE65Z0GHFpxtXX/yUH1t2mBlJicoMzm+0y4QhfvrdMn/va/yEIO8D8lJ0cvfPjWqlm9Lt+/Xbc8sbzfeWkpCnH5xyXhdEUXLpPomv86+/52wP+ePLxobdfejnhAIWJ11/zthryESvR4t/u8Z3apIO1RvrS3VN54MfR2W6PXozTtP79axqSfUNvr0q9fW6aVlRWr0BVstHFuQqR9fNFZTo7yumfvpLt35/KcdWtdnJcfruVumRV1xF+zeXaZ3N+6RtVbTR+Ro5oRgJWI02zjttws7/b+cM2uKZoztF1XZ6pucyui6Jo3ITdPUNpXR3VHd0Kw91Y3qm54YScBImHGkKKtu0BtrSjVvdbE+3rq/XVrZXQlxHh2Tl9YacLzy2W6t3FUZct1jCzL18rdPifjL11mTy8zkeL3/w7Mibi72wea9+trsxZ0O2tnipGHZ+sH5ozUlBjWAy3eW6955G/TR1sjGgPjL9VN09pjI/uEr65o1/e75qgtz8njO2DzNnnVip9sIBKx8AavK+madee/CTk9E3/7PM5SRFK84j5HHGOdZIf++18z+WB9sjuxnHpKTomunDdEVJwzqskalszCjRZMvoH+t2KU/vLNZ2w866J42sq/6piXqnys6Diz6/fNH67azjomozC3mrS7WHc992nqAatGdi4oj1eurinXr08tD/i/deMow/fQL4yLe1sbSan350Q87XIRJwVYG/3f1pKh/Z4u37tNLy4tUWtWowdkp+sqJg8KGYZ15YWmh/uulVfIfdDy68ZRh+snF3asJW72rUmt3Vyk10aszRudGdCHX7A9oQ0m1lu8s1/OfFGrN7o7dq9oampOiE4dma3R+usbkZ2h0fnqnLdmeWbxTD8/f2HrCnZ7k1Q2nDNMdM0ZGXXPy4rIi/ea1de1Cy3PG5um3lx8Xccs+qfMafUn6+zenR9VCY8H6Ut3x3KftvmeJXo/+59IJuvLEsBcVMQszzrh3YUSVCGmJ3mCte2aSUwN/oOY9OC9RAWt17gOLwu73o60d/e7zn+ofIfaHkvToNZN1wbEHAg1rg8eK0qpGlVY1qLSqQWXVwenPiir0WWHoc4EWF07I13nj8zUkJ0XD+qZ2etFjrdV9b27QY4u2tmu5d/KIHP3u6knKSYuuteYba0r0s7lr2rU0OHlEjh648njlZ0Y3cLQ/YPXKZ7v1wtLC1kD8KycO0oUT+rcLd6samvXOhj16e22pFm4oC7nf68yJQ/vopGHZrb/vksoGlVQ1RL2daCR4PUr0err8jF9cMl7HDsxU39REZaclKDUhLuw+cuGGMn39r0s77Fsl6fYZI/Xdc0e1vm5o9mtXRb0K99epqLxeheV1Ktpfr6LyOu3YX9fl3eUOlpoQp6yUBGUkxysrOV5ZKcFHRnK8lmzdrxWFFWHf+73zRum2s46JaN+/u6Je5z74rmobO/5fGkl/+/rU1pa5bVlr1egLqLrBp5pGn2oafHrls1167L1tHdZt0S8jUR/88OyoB4etrG/WqqJKeeOMjh+UFVXraWutXltdrNueXtHper+4ZJxmnXz4W2Bd+cePtGT7/rDLbzxlqH76hfERb6/JF9CTH23XM0t2OoF4kr58wkDdcvrwiENnKbiv+NrsxSGvAeLjjJ67ebpOGNInom1V1gcD44O7kbWYPDhL/7j1lIjLtq+mUdc//olWHXQNNzw3VU/dNDVk66tAwGp3Zb22763Ttn212ranVmt2V2rxtvC/e0kq6JOsmePzNSI3TSNyUzUiL005qeFbZ839dJd+OneNKg+qjP6/r07WqH7RtUDcU92oX7+2Tv9euVvNfiuvx2jmhHz9+KJxne37CTPaWr6zXM8u3qnC8uA/w+UnDNRpI/t268R4ybb9euLD7VpXUqWMpHhdPLG/vjp1cLtateLKes1bXaLXV5Xokx37FepXGx9nOjTrb3HS0GydNrKv1pdUa11JlbbtrQ25jUidNTpXfdMSZSVZK9mWSyJ74O4g1lo1+63mrS4JebBrW7ax/dPl8Rh5PUZxHo/zHHx9YL7R04t3aNvezk8eJxRk6Pvnj9Hp3fx7RMpaqw8279O9b6zXZ0Wdn+wNyErSNVOHqNkfcB5WTb7gtM9v1ewPqMlZtm1vnTaWhm5+3iI/I0lWVn4ntPD7g8++QEC+gD2kv20Lj9FBAYfp8naqkjRjTJ6unT5Ep0cxkGEkYUYLf8Dq1VXF+v2CzdrQxe+pxd9umqpTR0bW3HvHvlqd88C7Yf+X7v7SsbrqpMERbatFsMvQDq0sqlBKQpzOH5+vq04aHHVtZgt/wGrHvlp5jOnWQHz+gNUZ9y7stCn0i98MtgAyRjLO/j84LcmZ1/L6zuc/06JNe8JuK5rm9tZa/fzlNXrio44B6F0XjNE3zxgR0XYkae3uKl38u/fCjiV03xXHRdVqqrSqQd95doWWtDnApybE6fvnj9b1p7Q/0SuratDynRVaUViuFTsqtHJXRbs+p92Rk5qg0fnpTsCRrtH5GRrVL00vLSvST8K0vpo1fYh+cemEiD/j9VXF+tbTy0MuO25gpl761skdTrb9AauKuiaV1zWrvK5J5bVNKq9r0j3z1mt/bfiLlLH56bp66mBlJgcvQjIPerRt0bO5rEYXPvKemnwdf4dG0jPfmKbpI0LWhsUszLjg4fe0LsSYP93R1Z21slLidcvpwxUfFzw+euM8io8z8no88saZ1vnxcR7tqqjXj8M0DZaCLQZPG5mrsurgRXRpVWPI32t3ZaXEa0hOqoblpGho31QNzUnV0L6pGpaTqmc/2am7X18f8n3HD8rSP289OeLj9oeb9+prcxaH/P8enpuqV79zWsTdPP0Bq9ufXaFXVxV3WPalyQW685xRWrC+TG+vK9XHW/eFPD5kJHl19pg8nTO2n/6xvEgLNnTcJxZkJeuft56svIyOJ9t1TT6VVjWqpDIYKJVUNej1VcVdnl/EUqLXo5zUBOWkJSo7NUE5aQnKSU1QdmqC5ry/TXtrOrbSbHHe+H7aV9Okwv11KqtuDLteb/AYKTk+TskJcUqKj+s47bzeUNKxtWlbuWmJOnZgpmoafKpu9Km6obk1vAjVZaMr04fnaOKgTI3KC+7nR+Smhf0ON/sD+u289Xrq4x2tx5Y+KfG67axjdNOpwzr8HwUCVtv21Wr1rkqt2V2l1bsqtXpXpaoiDNFG90vX5CF9NHlwliYP6aPhfVPD/q82+wN6bVWxXl1ZrJpGnyYUZOqaqYO7bEXh8we0ZU+tVjlle+LD7Z3uF42kYbmpGpKdosHZKRqUnaIhOanOdHK76yifP6Cbn1qmBevLOmxn4sBMPfuNaREHGm+vLdXXw7QYkaTR+em69cwRqm/yq6HZr/rmgBqa/a2P+ma/GpoDqm/2a/ve2rCtpVpcetwADclJaT1OZqUktB4ns1KCzy0h1g2PL9HCEPseSRrXP0M/uXistu2t0/Z9tdq2t1bb99Zqx/66HjsGZCbHB4ON3DSNyEtrDToK99fr+seXhPx75qYn6q07T4+49U9lfbO++PsPWrvOtzUoO1lzbzs1XMULYUaLh9/epAff3thh/lemDNJvvnRsVBcW4WquxvXP0H1XHqcPNu3V66uLtXxn6JR50uAsXTAhXxdM6K+aRp+u+8sS7TnooDFpcJb+esNJ7ZrV1Tf5tbG0WuuKq4IBR3GV1hVXRbxTO1KNyU/Xa7efdlhHWbfW6rLff9CrJxxHimj777aIJsxoEXDGYfn9ws1d/u7zM5I0dXi2jIItTlq/HQddlBsjfVZUqQ1hxjKQpEHOQLi56YkRHfhe+Wy37nz+0w4nNiPz0vTszdPUN4qaSGut/rZ4px5duFm7naZ/Q3NSdMc5I7sc/8Raq5KqBm0pq9W7G/foz+9tjfhzD1XftEQdPyhLWSnx6pMSPBBnpcQrKzmhtUYtKyVBfVLiNW91sb77wsqw23r+5mmt47M0+gLBMToa/app9KmuKVgLVtvoV22TT88tKdTyneVhtzUwK1k//cK44ElByoGL6OT4jrWRzf6ALn7k/bAB2h0zjlFGcoJW7CzXip0Vh9Tc3OsxSvR6wraoaqvlu9vZefMfrpms3PTEYPBsg9FzIJhCtwbSAWsVsFY/+ucq7aoI36x02vBspSR424QWze1qWXpSSkJcMOhIild5XVOnF0TH5KbpqpOCTds9RvI4z9dOHxqzMOOR+Zv0wFsdzwVaTCzI1MDsZOfitFFl1Q1hQ9KjRVehzS2nD9fo/HR5THC/LB3YZ7fMa9lX3//mxk4vAm6fcYwunjhACXEexXuD4U9iXJzivUYJcR7FeUzr//nzn+zUD19aFfXPM7BPss4d10/njuunE4dmtwZwzf6AZr+3TX/7eEfrviA9yav53z0jZJARzpY9NZpx/7thl48fkKEfXThW1Y0+1TYG93/VDQemWy6saxp9KiqvbzdWw5EgI8mrQdkp2l1RH7JbSIvLjh+gvmmJqqxvVkV9syrrmlVR36TK+maV1zX3aBh3JDEmeOegkXnpGp2fplH90jUyL10j8lL1s7lr9NwnhSHf998XjNEZo/OCgcXuSq3ZVaU1uysjOqZEqk9KvCYNPhBuHDcwS6mJXtU2+nT940taux61iI8z+t3VkzVzQnBAUZ8/oE1lNa3BxepdlVpbXHXIoX9buemJGuwEHbWNPr15UBfxtr42dbBmTuivqobgMa2qvrnNtC/43BCcX1Re36Hlbm9L8HqUnugN2Q28u+KM6bQyuqv9eTTrfnFSgS48tr/iPFKcx6M4pyI1+Gg/74Wlhfrrh9vDbuuKEwbq8hMGtlYSN/kCavJbXXLcAMIMSfpwy1599c/h+zrfe/nEiPvQbdlTo3PufzfiL4IU3LFNGdJHF0zor5kT8jv0qa5uaNa/VuzS3a+vV22TX3npifrwrsiarVlrVVzZoBeWFuqhtzdFUaojx+mjcvXkjScd9s+95amlemNN+J1kTxveN1VJ8XHyxh1owdJSQxfXpiVLXZO/wxgiBzvTaSYfsMGWHv6AWqdbnn0Bq4Zmv1Z2ERp0dwT/7oQZLay1Ov6Xb8XsgqozKQlxyktPVG7LIy1ReRlJyk0Lvo6PM7rxr5+oKcwFzCXHDdAjV0+K+PP+b8Em3fdm6IunX31xgq6ZOkQNzX7t2FenLXtqtKWsJvi8p1Zb9tSEbcJ+JOnqgJcU71F8nEd1Tf4e6WIXSnycaW0tkJEUDDhqGn0dBhWOlNdjNH5AhiYN7qNJg7M0eXAfPbdkp37/zpaQ6z/4leN06XEF2lVRr/Ul1dpQUuU8V2vr3tqY/dyfR9vvvihmYUZlXbMu+f37IbuaDMhM0svfObVdWBkIWO2va1JJZUOwVURlY7BlRGWDFm4oO+y11ykJccrPSFJeRmJr95cDg1EGu7/kpSfppic+CXtb7SlD+uiuC8Zo+746bd9bq237arVjX622762LqCVfbzJGio/zKDHOo/pmf8Q16ccNzNS54/rpnHH9NLpfeqctSay1OvO+4HgE3Tm+SdLdr6/XH9/tuK9ITYzTC7dMj3i8kZpGn6b+6u2wF7QZSV5997xRqqzzaV9to/bVNmlfTaP21zZpX02wtVW0u57k+DgNyk7WoD4pGtgnWYOyUzSwT7DWfGCflNZKtmU79uuqxz4OGfZNHZatZ74xrdPucg3NflU4weoPXvys0wqOQX2SNSIvrU2tufNoCqi+yaf6Zn/UP2eaMzZJWlLwOT0p+AjOj1dakldlVQ1hwwep89bVB4sz0qHmonEeo5F5aZpQkKkVO8u1ZU/oW9imJ3l1/KCs1ltPh+Mx0pj8DAWsDTu4tTfO6NLjCrRlT43WFVd1GQh4TOdB/dCcFDX5AiquauiRFsm9oaufMdby0hNbW84N7ZuqYX2DLeqGZKdq7qe7dNc/Qoe8xw/K0jNfn6od+1vON2ud880abd1TG7bbTG/qzvlA793jKQxjzExJD0uKkzTbWnt3tNv4Wye325KkX7yyRv9YvksBp/ZLTo1XsPbLKtDSDcO5TWYk31+PkaYNz9EFE/J1/vj8TlP99KR4XTt9qN5cW9p6O9VI+98ZYzQgK1nfPGOEnvxoh/aHSfcSvUav33G6MpPjWw/iLTUlwWnT2pDHGGnWnCWd9l98+utTNTg7JXgh3XLx7G+5iA44F9jBx69fW6fVnfQ1Pz3CrgQ97dSRuZ2GGaP6penXXzxW8XHBC7EEr2mdjneaC7dMV9Q16ZR7FoQ9qE0bnq3nbo58kK6v/OmjsP3epg7L1l9viDz86az5WnJ8nC49fkDE22prYJ/kds/RMCY4GnxvhBl1Tf7gSXyEg+8e7JWVu2VllZEUr0RvnJLiPUqKj1Oit/1zUrxHTb5ApyHjz+au0Z/e3aqi8roeOTCeOSpXBX2SW2vuJevU7AeXW+d1wFr9e2VxpyclCXEeNfkjq8XoqugNzYEerbkJpdlvtbemqdMm1J3pl5GoyYP7aLITXkwoyOzQj/l7549Wbnqi/rRoa+sAWynxcbr/yuNaxzMY5DSbPXfcgfF2Gn1+bSmr1YbSYMDx4ea9WrWrZ7o6RCMz+UArm+zUYAub7JQE9UlNUJ/WVjYlmtvJAJnfP2+Uxg3IVGV9c9hHlfNcWtXQqyd8oWSmxOuFW6brl/9eqzdWl7ReDKckxOnv3zq5Q6srj8eob1qiM7/9Behrzhg24Zw0tI++d/4Y+fwBNQds8NnvdC10uir6nPkrd1Xq70uLwm4rOd6jhd87S/0yEiPq0vHwVZN0/eNLOozzMn5Ahv7wtcnKS0/qMDaVtcH/oR0tTZn31WplYaXe29x5uH44WRvsQx9JrX5SvEc/uXicZozpF9VYHMGWQoeWp/1w5mgN75uqOe9va20ZlpoQp3/eekpU/czTEr368cXj9F8hLk48Rvrt5RM7HRzW74zDta+mUVvKanTrM8s7/Z+89/KJuvyEgRF9x04Ykq0nb5yqX/57bWvXLWOCLZ5/cvG4Lsf9SYqPU35mnPIzk/S980fr2jlLQq7n9RjNuf7ETn9v1lo1+QNqaArosfe26PcLQ4fOknT++H569JoTImoNHAhY7dxfFzIY9Bhp9qwTNWVIH20uq9HG0mptKqvRhpJqbSqtbm2J2SLaICMhzqPR+emaUJChCQWZmjAgU6Pz01uPS8WV9frqnxd3uFV4n5R4PXXTVE0oyFQgYLV5T42W7yjXsh3lWn5QABKw6rRLjiT5/FYvLQ+9b0r0ejS2f4aOLchsLWe8x+jLf/woZIgyIjdVL3/7VKUmelvHZNm5v04799UFn9tM98SFtTFqrdxo8gU63BGorazkeP3sC+OUnOANdl/yetp1Y0qM9yg5Pvi60RfQ9N/MDxsUTRmSpQeunOS0SmpqPTZW1B04Pra8bvkddOaCCfm6aGJ/DXO6AHbWwviqkwartsmvB9/a2C6cPnN0rh648nilJHo1tn/wRhJtBQJWxVUNrRVqm8tq9PTinZ2W60h1RLXMMMbESdoo6VxJRZI+kXS1tTbs6GShamJmPrQobOIYC3ddMEZXnDAw6kGxDtWLy4r0vb9/FnLZjy4cq2+cHvmIy58WVujqxz4OuTO5/uSh+vklkQ/es3jrPn31z4tDNnvqn5mkef9xelSjVPeU2kafZj68SIX7OzYtN5Iev+FEnTk68ltIPb14h370z459nrNTEvTCN6fpmLzIT2DKqhp03V+WdPjejslP1xM3nqR+UTR53VVRryv/+FGHJvRej9FDVx2viyd2L8w4VL+bv0n3d9Lc+/vnjdK1Jw8NXoi3GePFtjazt60X7fNWF4cdf0CSxg3I0ElDs7WnOthsfE91o/ZUN/Zo882elp7k1TGtfReD/Rf/sbxI88IEcMP7puqt754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\n",
      "text/plain": [
       "<Figure size 1080x2160 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bin_edges = np.arange(0,31,1)\n",
    "g=sb.FacetGrid(data=bike_data_samp, col='month', col_wrap=2, size=5,aspect = 1.5)\n",
    "g.map(sb.pointplot,'day', 'duration_min')\n",
    "#plt.xticks(rotation=90)\n",
    "\n",
    "plt.xticks([1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31], ['1','2','3','4','5','6','7','8','9','10','11','12','13','14','15','16','17','18','19','20','21','22','23','24','25','26','27','28','29','30','31'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Talk about some of the relationships you observed in this part of the investigation. Were there features that strengthened each other in terms of looking at your feature(s) of interest?\n",
    "\n",
    "> In the bi-variate plot, we seen that month 3 and 9 show a spike in the time spent on bike. The plothist2D and the point plot drawn as part of mutivariate exploration indicate he sudden spikes are due to the large value of outliers. The outliers are represented as error bar in the point plot \n",
    "\n",
    "### Were there any interesting or surprising interactions between features?\n",
    "\n",
    "> Since there is very less correlation between the variables as checked in hetmap in bivariate exploration. WEe dont see any interesting interaction "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "> At the end of your report, make sure that you export the notebook as an\n",
    "html file from the `File > Download as... > HTML` menu. Make sure you keep\n",
    "track of where the exported file goes, so you can put it in the same folder\n",
    "as this notebook for project submission. Also, make sure you remove all of\n",
    "the quote-formatted guide notes like this one before you finish your report!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "celltoolbar": "Slideshow",
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}