A plot against the CatterPlots complot
In these terrible times, we R people have more important subjects to debate/care about than ggplot2
vs. base R graphics (isn’t even worth discussing anyway, ggplot2
is clearly the best alternative). Or so I thought until I saw CatterPlots
trending on Twitter this week and even being featured on Revolutions blog. It was cool because plots with cats are cool, but looking more closely at the syntax of CatterPlots
, I couldn’t but realize it was probably a complot to make us all like base R graphics syntax again! So let me show you how to make a cute plot with the awesome ggplot2
extension emojifont
.
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.
Were there more notable deaths than expected in 2016?
After exploring my study population of Wikipedia deaths, I want to analyse the time series of monthly counts of notable deaths. This is not a random interest of mine, my PhD thesis was about monitoring time series of count, the application being weekly number of reported cases of various diseases.
Who were the notable dead of Wikipedia?
As described in my last post, I extracted all notable deaths from Wikipedia over the 2004-2016 period. In this post I want to explore this study population. Who were the notable dead?
The animals of #actuallivingscientists
These last days a trending Twitter hashtag was “#actuallivingscientist”, whose origin can be find in this convo and whose original goal was to allow scientists to present themselves to everyone, a sort of #scicomm action. A great initiative, because we need science and we need everyone to know how it’s done, by actual human beings.
I didn’t tweet with the hashtag, but I consider myself a scientist with more or less experience in different fields – and my last post was about the scientist I married. In my timeline thanks to Auriel Fournier there were many tweets of ecologists studying animals. I’d like to say cute animals but some were carcasses… But still, it made me want to quantify which animals were the most present in the tweets. Any bet?