In today’s blogpost I will look at historical data from the Tour de France. This data was used in the Tidytuesday series back in April, but I thought I’d take a closer look at it now as I currently suffer from Tour de France withdrawal symptoms (a July without Tour de France is like December without Christmas).
First, let’s load the data and have a look at the structure.
Today I will look at how to connect to the Strava-API and do some quick analysis on the activity data.
To start using the Strava-API, start by registering a developer app at strava.com. After doing this, you will get your API credentials, including your personal secret and client id. Here, I have added my secret to keyring using key_set before fetching it in the code below.
A few days ago I returned home after a lovely trip to Toulouse, where I attended the annual useR-conference, which is the largest or second largest R-conference in the world with more than 1000 participants (rstudio::conf seems to be about the same size).
In this blog post, I will recap what I have experienced and learned during the trip.
Day 0 - The curse strikes again First, we need to start with some back-story: I have been to France the last two years on cycling camps, and both years there were issues with the flights to France.