At the end of the last post, we had our data in a file named defective. The data contains all the injuries caused by car accidents where a road sign, signal or marking was obscured or not working properly from 2010 […]
Welcome to the third edition of Seen Elsewhere, my round-up of good stuff I’ve seen in the field of R and data journalism this week.
One of the most detailed UK government datasets I’ve ever seen is the STATS19 data from the Department for Transport. This is the collated reports of road accidents in Great Britain in which at least one person was injured or […]
Summary: October was this site’s first full month of operation. I think the stats for September have disappeared – I think I enabled the stats on WordPress a few days later, so as far as I know this is just October’s data. […]
You might have noticed the site looks different to how it did before. I changed themes to the Tribute theme on WordPress. I find this theme handles my featured images better, which allows me to show the thumbnails on the homepage. All […]
Welcome back to Seen Elsewhere, my round-up of good stuff I’ve seen in R and data journalism this week.
Walking through what’s left of the heart of the Jungle. The camp ‘Main St’ pic.twitter.com/8tYau41NST — Gavin Lee (@GavinLeeBBC) October 26, 2016 With the Calais Jungle being broken up and most of the migrants there sent elsewhere in France, it seems a good […]
The last post came in for some criticism on /r/rstats, in particular from /u/fang_xianfu, who argued it merely showed that London has more people than the rest of the country.
In our previous two–part series we looked at the melt function from the reshape2 package. The creator of the package, Hadley Wickham, pointed me towards tidyr and the gather function as a better alternative instead.