Over the past decade, bicycle-sharing systems have been growing in number and popularity in cities across the world. Bicycle-sharing systems allow users to rent bicycles on a very short-term basis for a price.
Bicycle sharing systems and technologies also provide a wealth of data that can be used to explore how these bike-sharing systems are used.
This project utilizes bike share data to compare bike usage patterns among three large cities: Chicago, New York City, and Washington, DC. The data is imported into an interactive program takes in raw user input to create an interactive terminal experience to compute and present descriptive statistics.
Data provided by Motivate, a bike share system provided, for the first six months of 2017 are used for Chicago, New York City and Washington.
The data files used can be accessed here:
Run the interactive program in the terminal with the following command:
python bikeshare.py
18-Sep-21