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Python: Exploring US Bikeshare Data 🚲

Introduction

In this project I use 'Python' to explore data related to bike share systems for three major cities in the United-States: Chicago, New York City, and Washington.

The program provides a comfortable interface for users to draw various statistics from the data. This allows to uncover intersting bike share usage patterns.

The Datasets

Randomly selected data for the first six months of 2017 are provided for all three cities. All three of the data files are in CSV format, and 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