Data science and women's cycling: a follow up

I read with great interest Amelia Barber’s post that combined her loves of women’s cycling and data science (link). Since reading her post and writing a brief reply (link), I have been investigating some Union Cycliste International result data.

I did find some women’s road race data available for download (link) and took the opportunity to download the results of the Liège-Bastogne-Liège race at the end of April 2019.

Like Amelia, I am interested in how I might use R with race data to make women’s road cycling more visible. In this race I appear to have a number of visualisations that report chronological age. It is one of the column headings in the data set.

My first attempts include:

These are very basic visualisations of the data but they are for me a start in a public conversation about how we share the available data. The UCI has five pages of women’s road race data going back to October 2018 (link). I sense that an important conversation to have about these data will be web scraping and the possibilities afforded.

I look forward to sharing my analyses on GitHub (link).


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