A Power BI report aiming to improve the analysis of activities recorded in Strava. Data extraction takes place in R. The main questions that the report currently sets out to answer are:
- Which segements do I ride the most?
- Are my segment times improving?
- How are my segment times compared to the KOM/QOM across a whole activity?
- The Monthly Activities comparison graph on the Strava app is cool, but what is this month looking like compared to all previous months? And how does my distance compare, not just my movement time?
-
To use the report on your own account you'll need the following:
- A Strava API application
- An R installation (R Studio is recommended)
- A Power BI installation
-
Create
credentials.yamlin the repo's top-level directory, and include the API application's client ID and secret as follows:
client_id: xxxxx
secret: xxxxx-
Run
scrape_efforts.R -
Open the
Strava Stats.pbitPower BI template and analyse away! (To adjust which activity types are being displayed, open the 'filters' pane; by default this is set to 'not Run') -
If you would like to refresh your efforts, simply re-run
scrape_efforts.Rthen refresh your Power BI report. If you would also like KOM times to be refreshed, deletekoms.csv; note that will take a fair amount of time, so it's recommened that you only do this once every so often.
Some R code taken from bldavies/stravadata