First, we parsed and analyzed the large (~2.5gb) JSON file of ride data given to us by Polaris by breaking it down and using the pandas library in Python. The main feature of our web app is a script that selects a random ride from the dataset and plots its geographic coordinates on Google Maps, creating a visualization of the path of the ride. We also created a map that shows the "average" ride taken across subsets of the data. Django was used as our web runtime environment for Python along with the Google Maps API, and HTML, CSS, and Bootstrap were used to design the front end.

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