In this project, I used data provided by Motivate, a bike share system provider for many major cities in the United States, to uncover the bike share usage patterns. I compared the system usage between three large cities: Chicago, New York City, and Washington, DC.
Python is used to explore data related to bike share systems for three major cities in the United States—Chicago, New York City, and Washington.
The Datasets Randomly selected data for the first six months of 2017 are provided for all three cities. All three of the data files contain the same core six (6) columns:
Start Time (e.g., 2017-01-01 00:07:57) End Time (e.g., 2017-01-01 00:20:53) Trip Duration (in seconds - e.g., 776) Start Station (e.g., Broadway & Barry Ave) End Station (e.g., Sedgwick St & North Ave) User Type (Subscriber or Customer)
The Chicago and New York City files also have the following two columns: Gender Birth Year