Using the data provided by Motivate, I was able to compare the system usage between three large cities: Chicago, New York City, and Washington, DC in interactive experience. A deep analysis was performed on the dataset to provide the following useful information:

#1 Popular times of travel (i.e., occurs most often in the start time)

most common month

most common day of week

most common hour of day

#2 Popular stations and trip

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)

#3 Trip duration

total travel time

average travel time

#4 User info

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)