I have two GPX files (from a race I ran twice, obtained via the Strava API) and I would like to be able to compare the effort across both. The sampling frequency is irregular however (i.e. data is not recorded every second, or every meter), so a straightforward comparison is not possible and I would need to standardize the data first. Preferably, I would resample the data so that I have data points for every 10 meters for example.
I'm using Pandas, so I'm currently standardizing a single file by inserting rows for every 10 meters and interpolating the heartrate, duration, lat/lng, etc from the surrounding data points. This works, but doesn't make the data comparable across files, as the recording does not start at the exact same location.
An alternative is first standardizing the course coordinates using something like geohashing and then trying to map both efforts to this standardized course. Since coordinates can not be easily sorted, I'm not sure how to do that correctly however.
Any pointers are appreciated, thanks!