Radio edit: an improved scraping of and look at Radio Swiss classic program

Last week I published a post about scraping Radio Swiss Classic program. After that, Bob Rudis wrote an extremely useful post improving my code a lot and teaching me cool stuff. I don’t know why I forgot to add pauses between requests… Really bad behaviour! I will use his code today for re-scraping the data.

Why re-scrape the data? I mentioned broken links in my post. In fact, each time I hit a broken page, Radio Swiss Classic webmaster received an email. That person received a lot of emails because of me. They repaired the bug explaining these broken pages and contacted me because someone had turned me in (I feel super famous or spied on now), very kindly mentioning they had fixed all pages, and not holding any grudge against me. So let’s scrape everything again!

Extracting notable deaths from Wikipedia

I like Wikipedia. My husband likes it even more, he included it in his PhD thesis acknowledgements! I appreciate the efforts done for sharing knowledge, and also the apparently random stuff you can find on the website. In particular, I’ve been intrigued by the monthly lists of notable deaths such as this one. Who are people (or dogs, yes, dogs) whose life was deemed notable enough to be listed there? Also, using the numbers of such deaths, can I judge whether 2016 was really worse than previous years? The first step in answering these questions was to scrape the data. I’ll describe the process in this post. In another post I’ll have a look at my study population and in a third post I’ll analyse the time series of death counts.