The pelotonR Package Debut!

 

Today marks the debut of my first open source package: pelotonR! I created the pelotonR package because I love my Peloton, and I love data. Naturally I wanted to marry the two worlds.

When I first set out to get my hands my Peloton data, it proved a little trickier than I had hoped. The APIs are unsupported and only partially documented by the community, the results are in json format and the calls require paging. After I worked through all the hurdles and was able to graph my data, I thought it would be a good idea to make this data accessible to others.

The package offers a set of easy to use functions which allow the user to:

• Pull general Peloton data in a variety of formats

• Authenticate with the Peloton API

• Pull user-specific data in a variety of formats when authenticated.

• Gather full data sets in one function call without having to handle paged API calls.

• Gather joined data sets in one function call.

Tutorial

I have written a full tutorial showing how to use the package on my github. In the tutorial I show you how to pull oodles of Peloton data.

The Data: The data sets include: Peloton metadata, live ride data, instructor data, user workout stats and user workout history joined with all other data sets

The Visualizations: In the tutorial, I also get you started with graphing the data in R. With so many amazing R data visualization packages, the graphing possibilities are endless.

Great Minds Think Alike

At the time of writing this blog, I realize there are a few other Peloton R packages out there. I haven’t had the chance to check them out yet but if you’re looking to round the bases on R peloton packages, I encourage you to check give them a try. Particularly they both seem to have some interesting performance data!

• bweiher/pelotonR

• elliotpalmer/pelotonr

Thank you

Thank you for reading about my new package to gather Peloton data through R. Please remember that the full tutorial is available at https://lgellis.github.io/pelotonR/.

Please reach out to me on twitter to let me know if you like the package and share your findings.