In two lunchsessions on the 11th and 14th of February, I will give an informal introduction on how to make thematic maps in R. The formula is show and tell: not a full course as such, but rather going together through worked examples showing what is possible, how to do the most common steps, and where you can find information to further apply and teach yourself. We’ll discuss (dis)advantages of popular spatial packages in R, and the examples focus on common maps e.g. for Belgium and the EU.
The material is structured in the form of Rmarkdown-documents, with code you can run interspersed with comments, tips, and links to further documentation and tutorials.
HIVA – KU Leuven, campus Social Sciences, Parkstraat 47 Leuven: room 00.14 (“Library”, ground floor).
In the last few years the R ecosystem has seen a sizeable expansion of applied spatial analysis and visualisation packages. This allows researchers without a GIS-background or specialized software to more easily integrate spatial data into their work(flow).
Using these packages, the show-and-tell sessions focus on how to make thematic maps – more specifically choroplet maps. In these maptypes areas are colored in proportion to the measurement of a variable being displayed on the map, such as income or unemployment rates. The worked examples demonistrate the quickest routes for getting your data in R and on a map, with a focus on showing how spatial data can be integrated in a familiar tidyverse data-analysis workflow.
The examples demonstrate mainly static maps, but interactive thematic maps are included as well. R packages demonistrated are primary:
Intended audience is basic R users (or those interested in seeing what R can do), who wish integrate spatial data into their “regular” (exploratory) data-analysis workflow, or who need a quick map. More advanced GIS-topics such as projection fall outside of the scope.
The worked examples and code are provided in advance in the form of online (Rmarkdown) documents and downloadable material you can run and adapt yourself.