This data set includes information about individual rides in Feb 2019 made in a bike-sharing system covering the greater San Francisco Bay area.
91% are subscribers and only 9% are normal customers. Three out of four users are male. Users are mostly between age 25-35.
By looking at hourly bike usage, on weekdays, peaks occur at around 8:00 a.m. and 5:00 p.m, suggesting bikes are more likely to be used for commuting to work. On weekends, hourly usage follow a bell shape during the day with peak around 1:00 p.m, but overall with much lower usage then on weekdays. The pattern remains when separate by member's type. The weekly bike usage shows that weekends only have about half the ridership compare to weekdays. The average riding duration is short, with distribution of riding duration is right-skewed and peak at around 5 minutes. The distribution on weekend rides show similar pattern, suggesting even on weekend, people use the bike for commuting rather than for leisure.
For the presentation, I focus on user's demographic and bike usage pattern. First, I present the member's type, gender distribution and age, to provide the audience of who's using GoBike frequently.
Then I present the hourly bike usage on weekdays and weekends, to show the riding pattern. Then present the Day-of-week bike usage to show how the bikes are used more ofter during weekdays. By showing Riding duration on weekday/weekend, the audience can understand users do not use the bike for leisurely ride, even on weekend. Finally by presenting Hourly bike usage by member's type, audience will know that there are no distinctive differece between member and non-member.