/Ford-GoBike-System-EDA

Ford GoBike System Dataset is a dataset that contains trip data from Lyft's bike service for public use. Variables include trip duration, start time, end time with date, start station and end station names, start and end coordinates, and customer type.

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Ford GoBike System Exploratory data analysis (EDA) Repost

by sahil patni

Dataset

  • Ford GoBike System Dateset is a dateset that contains trip data from lyft's bike service for public use. Variables including, trip duration, start time and end time with date, start station and end station names, start and end coordinates, customer type.

  • This data set includes information about individual rides made in a bike-sharing system covering the greater San Francisco Bay area from November, 2017 to December, 2017. https://www.lyft.com/bikes/bay-wheels

Summary of Findings

  • The number of trips peaked around 8-9am and 17-18pm during a day, there were more trips on work days (Mon-Fri) compared to weekends. Summar time was the most popular season of a year, likely due to the weather. The riding trips tend to be shorter on Monday through Friday compared to weekends. It indicates a pretty stable and efficient usage of the bike sharing system on normal work days, while more casual flexible use on weekends.

  • There are a lot more subscriber usage than customers overall. The riding habit/pattern varies a lot between subscribers and customers. Subscribers use the bike sharing system for work commnute thus most trips were on work days (Mon-Fri) and especially during rush hours (when going to work in the morning and getting off work in the afternoon), whereas customers tend to ride for fun in the afternoon or early evenings over weekends. Subscriber usage peaks out on typical rush hours when people go to work in the morning and getting off work in the afternoon, which strengthened their usage purpose and goal of riding. Similar pattern was not observed among customers who tend to ride most in the afternoon or early evening for a different purpose than the subscribers.

Key Insights for Presentation

  • Different usage pattern/habit between the two type of riders are seen from the exploration. Subscribers use the system heavily on work days i.e. Monday through Friday whereas customers ride a lot on weekends, especially in the afternoon. Many trips concentrated around 8-9am and 17-18pm on work days for subscribers, yet customers tend to use more in the late afternoon around 17pm Monday to Friday. The efficient/short period of usage for subscribers corresponds to their high concentration on rush hours Monday through Friday, indicating the use is primarily for work commute. The more relaxing and flexible pattern of customer use shows that they're taking advantage of the bike sharing system quite differently from the subscribers, heavily over weekends and in the afternoon, for city tour or leisure purpose probabl