Although I am not an avid European football fan, I sometimes have the chance to watch a match – and even more so during these days! ⚽️
Now that I’ve been following the German Bundesliga for some seasons (more irregularly than regularly), I was curious to see which players are part of the national teams.
This is a late version of a TidyTuesday. I started working on it a while ago and could not finish it – but here you go! The TidyTuesday was about Broadway musicals with a dataset by Playbill.
When the GDPR regulations went into full force in May 2018, it came a bit like a shock. While people tried to make everything as GDPR-proof as possible, it felt as if no one really knew what is enough and how hard how hard possible fines would hit.
It’s time for TidyTuesday again! As a kid, when Lance Armstrong and Jan Ullrich were competing over the title, I would spend a good part of my summer holidays watching the Tour de France and being impressed by the fascinating and (fast changing) landscape the stages have to offer.
This week’s TidyTuesday was all about traumatic brain injuries with data by the CDC. Dennis Hammerschmidt and I looked at how different levels of severity in traumatic brain injuries change over time and across military services.
And here comes the next edition of TidyTuesday. This week was all about the series The Office. The schrute package, were the data was partially based on, offers all scripts from the writers and I was wondering if also The Office writers have their pet words that they frequently use.
Playing around with the data for TidyTuesday is like joining a mini hackathon — lots of fun, some manageable challenges, and so many new insights! I wonder why I have never done it before.
This blog post kicks off our new blog Methods Bites!
The blog post by Richard Traunmüller and me provides illustrative examples from Richard Traunmüller’s one-day workshop in the MZES Social Science Data Lab in Fall 2016.