Bicycle Noodling
I have built a large reserve of activity data from over ten years of tracking with platforms like Strava. In these projects, I transform .fit files into a readable format — turning raw metrics into a foundation for exploring patterns, spotting problems, and uncovering opportunities for further analysis.
Background
What is a .fit file? What is FTP? All these questions answered and more, for those of us who are not obsessed about riding bicycles faster.
Noodling
Working with six .fit files downloaded from the TrainerRoad application, I use the fitparse library to extract the raw data. Each file is cleaned, validated, and transformed into a structured Pandas DataFrame. The result is a single .csv file containing all six activities, ready for use in future analysis.
The original dataset created in phase 1 needed a few changes to make it easier to work with. I also added data which was not contained in the original .fit file to aid fitness tracking in visualisations. And to test my work, I created the first basic visualisation of this project using the Seaborn and Matplotlib libraries.
Further exploration of the activity data in Tableau which provided me with ideas for visualisations.