Strava data computations and visualisations

This repository uses sports activity data from Strava and generates several outputs/visualisations. Hava a look.

Preliminary remarks: To access the material in its entirety, you need to have a working installation of R and Python3 installed.

Data import

There are two methods elaboraed here to get your Strava data.

1. Request your archive

1. Request your Strava archive via E-Mail. In your Strava account: Settings -> My Account -> Download or Delete Your Account (Get started) -> Request Your Archive.
2. Wait for the E-Mail and download the archive.
3. Fork and download this repository.
4. Copy the activities folder and activities.csv file into the data folder in this repository.
5. Open the makefile.R (in the code folder) and set the working directory to the folder where you have your code and data folders located. Change the python_path variable to the location where you have python3 installed.
6. Change import = 0 to import = 1. Save and run the file. This can take a while.
7. Cool, your data is now loaded and ready to be processed.

2. Scrape information through the Strava API

More on this soon.

Passed

Passed is a programm that automatically recognises if you have already climbed a mountain pass in Switzerland, France or Italy (with the bike obviously...). Since there is a myraid of passes, it is challenging to keep track of your stats. This programm approaches this challenge systematically and automatically. If you want to know your Stats, switch the variable passed to 1 (0 by default) in the makefile.R. Note: Since data is already loaded, change import to 0. You also want to switch scrape to 1 to get fresh pass data. If switched on, this will scrape pass info from quäldich.de. There is a working file provided within this folder. Thus, scraping pass info is not required. Have a look at your stats in the plot folder.

Ridges

More to come soon.

Maps

More to come soon.

Cumulative distances

More to come soon.