Ford_GoBike_2019

Data analysis and visualization for bike renting company

(Ford GoBike System Data)

by (Maged Mohamed)

Dataset

This data set includes information about individual rides made in a bike-sharing system covering the greater San Francisco Bay area
The file taken from the classroom has only data for February, 2019.
After doing some research I found that Ford GoBike company name has changed. The following quoted from Wikipedia:

Tracing the new company name, I found the rest of the data for the whole year of 2019. download link
The twelve months datasets are uploaded in the folder \Data

Summary of Findings

• Trips increase at rush hours (8 and 17 o'clock)
• Examining the weekday we can see that trips is reduced during the weekends but they take longer time.
• Trips are more in spring and summer more than the rest of the year.
• Bike traffic is more at day than at night. Still at 3 o'clock the average duration tends to be high.
• Customers only represent 20% of the trip count but they tend to rider longer.
• Around 1/3 of the system's total bikes makes less than 100 trips per year.
• Top start stations and top end stations are the almost the same. This means that bikes are usually looping between such stations.

Key Insights for Presentation

For the presentation, I focused on the relationship between trip duration and time aspects. I tried to clearly represent the instances where more trips does not mean longer trips. I indicated the above in the user_type, weekday, hour