Primary Plotting

My wife tricked me into a partial-weekend project to try to get all the primary/caucus results to-date on a map (the whole us). This is challenging since not all states use counties as boundaries for aggregate results. I’m still piecing together some shapefiles for the primary/caucus summation boundaries for a couple remaining states but I… Continue reading

Replicating NatGeo’s “Proper” Earthquake Map in R

I saw [this post](http://news.nationalgeographic.com/2015/10/151003-datapoints-what-earthquake-maps-should-really-look-like/) over at NatGeo over the weekend and felt compelled to replicate this: ![](http://news.nationalgeographic.com/content/dam/news/rights-exempt/nat-geo-staff-graphics-illustrations/2015/10/Earthquakes/logarith_big.jpg) with ggplot2. [Three shapefiles later](http://rud.is/dl/quakefiles.tgz) and we have it close enough to toss into a post (and I really don’t believe the continent names are necessary). I can only imagine how many mouse clicks that would be in… Continue reading

Three New #rstats Twitter Bots To Follow

I engage with the Stack[Overflow|Exchange] community quite a bit and was super-happy @treycausey made the [Stack Overflow #rstats bot](https://twitter.com/StackOverflowR) (@StackOverflowR) since I’m also on Twitter alot (mostly hanging out in #rstats these days). However, #rstats questions exist in other Stack watering holes, like the [Geographic Information Systems Stack Exchange](http://gis.stackexchange.com/questions/tagged/r). [Cross Validated](http://stats.stackexchange.com/questions/tagged/r) and the fledgling [Data… Continue reading

Faceted “World Population by Income” Choropleths in ggplot

Poynter did a nice interactive piece on world population by income (i.e. “How Many Live on How Much, and Where”). I’m always on the lookout for optimized shapefiles and clean data (I’m teaching a data science certificate program starting this Fall) and the speed of the site load and the easy availability of the data… Continue reading

Power Outage Impact Choropleths In 5 Steps in R (featuring rvest & RStudio “Projects”)

I and @awpiii were trading news about the power outages in Maine & New Hampshire last night and he tweeted the link to the @PSNH [Outage Map](http://www.psnh.com/outage/). As if the Bing Maps tiles weren’t bad enough, the use of a categorical color scale instead of a sequential one[[1](http://earthobservatory.nasa.gov/blogs/elegantfigures/2011/05/20/qualitative-vs-sequential-color-scales/)] caused sufficient angst that I whipped up… Continue reading