What it does

This program creates a Fourier Transform of the commits over time data from a given repository. The resulting figure that you see below is a intensity versus frequency graph of that data. It is generated by binning 100,000 data points into intervals of 1 hour. It should be noted that this graph does not show user-specific visits, and therefore does not predict the number of programmers committing at a certain frequency. Rather, it shows us the frequency of the events that draw significantly more (or less) commits. For example, a spike at the one month frequency does not mean that there are many once-a-month committers, but instead that there is some external factor that attracts more commits each month.

How we built it

Python and Dash.

Challenges we ran into

Reading the data from repository pages.

Accomplishments that we're proud of

Graphing using Dash and applying Fourier Transforms.

What we learned

Coding in Python and Dash.

What's next for GitHub Commit Frequency Analysis

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