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GoBike-SystemData-Analysis

by Victoria Perez Mola

Introduction

Bay Wheels's trip data Analysis using Jupyter Notebook.

Dataset

The dataset chosen to perform the analysis is the Ford GoBike System Data. This data set includes information about individual rides made in a bike-sharing system covering the greater San Francisco Bay area. Each trip is anonymized and includes:

  • 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)

Data Wrangling

  • fields start_time and end_time changed to datetime
  • start_station_id and end_station_id changed tocategorical variables
  • user_type should changed to category value: Suscriber, Customer
  • Creatin of columns to store the start time hour, start time day of the week and start time month

Summary of Findings

After recolecting the data and performing a data exploration, these are the main findings:

  • The majority of the rentals occur at peak times (8am and 5pm) and during weekdays
  • During weekends the peak tends to be less pronounced and most rentals take place between 1 and 3 pm
  • Although the amount of rentals is not stable along the year, there's no clear seasonal impact on it
  • On average people ride 13 min, this varies between weekdays and weekends, being slightly longer over the last ones
  • The suscriber demad is high during the weekdays but has a huge decrease during weekends
  • The casual customer demand is more stable, yet it increases during weekends.

Key Insights for Presentation

There are two clear patterns of behaviour among the users. Subscribers use the system heavily on working days and during peak times. On the other side, customers have a more steady demand over the week, but it increases during the weekend. Combined with the big decrease of the suscriber's demand, the customers represent a great share of the total rides that take place during Saturday and Sunday. Customers also tendo to use the bikes along the day, mostly around noon during the weekends rather that two pronounced peaks as seen in the working days.

While suscribers seem to be using the bikes for work commute, customers use it for leisurepurposes.