Over the past decade, bicycle-sharing systems has become a hit. Many people are using bike sharing system to rent bikes for short term basis for leisure or health. Through this project, I will be using the data provided by Motivate, a bike share system provider to uncover bike share usage patterns for three major cities across United States: Chicago, New York City, and Washington, DC.
The following statistical analysis have been done using the datasets(.csv files) provided for the mentioned cities.
- most common month
- most common day of week
- most common hour of day
- most common start station
- most common end station
- most common trip from start to end (i.e., most frequent combination of start station and end station)
- total travel time
- average travel time
- counts of each user type
- counts of each gender (only available for NYC and Chicago)
- earliest, most recent, most common year of birth (only available for NYC and Chicago)