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Write Python code to import US bike share data and answer interesting questions about it by computing descriptive statistics
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Explore US Bikeshare Data.ipynb

Bike Share Data


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. This allows people to borrow a bike from point A and return it at point B, though they can also return it to the same location if they'd like to just go for a ride. Regardless, each bike can serve several users per day.

In this project, the main objective is to use data provided by Motivate, a bike share system provider for many major cities in the United States, to uncover bike share usage patterns. To compare the system usage between three large cities: Chicago, New York City, and Washington, DC.

This project was completed as part of Udacity's Data Analyst Nanodegree certification.


A terminal Python application for simple data summaries.


  • PyCharm
  • Jupyter Lab
  • Python, libraries: pandas, numpy, time


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