This data consist of information about a bike-sharing(Ford GoBike) system covering San Francisco Bay area for the month of February in 2019. This program is a shared transport service where bicycles are available for shared use. It includes information about members of this program which includes duration of their trips,age,gender,bike_id. The dataset can be found here
During exploration,I wanted to investigate factors that characterize two groups of members in the dataset: user type(subscriber or regular customer) and members who use bike-share for all their trips.
I found out with the help of pie charts that subscribers make up a large chunk of members with approximately 91%.
Members who use bike-share for all trips only make about 9.9% while members who do make up a bigger proportion of 90.1%
Using boxplots, The median age of subscribers who use bike-share for all trips is around 28 years.
In other supporting features, the ages of members were as high as 141 years. I only included ages below 80 years for analysis.
Males make up a larger part of members Sundays and saturdays recorded the least count of bike-share rides although those days recorded the highest average trip duration.
Rush hours for bike-share are 8am and 5pm by non-subscribers,it is the same for subscribers although they make up a smaller number.
Using bar chart,there isn't any significant average difference of trip duration between members who use bike-share for all trips and those who do not.Rather, there is a marginal increase for members who do not use bike-share for all trips.
Both user types did longer trips during the hours of 3am although non subscribers(customer) did a significantly higher rate throughout the month.
Members use bike-share throughout the day
Both user types(subscribers and customers) generally do not use bike-share for all trips although just small number of subscribers of about 2000 use bike-share for all trips. Apparently, customers do not use bike-share for all trips.
Members who Do Not use bike-share for all trips did longer trips than members who use bike_share for all trips throughout the month.