Geospatial data are an important component of social science and humanities data visualization and analysis. The R programming language is a great platform for exploring these data and integrating them into a research project.
Geospatial Data in R, part 2: Geoprocessing and analysis
Part two of this two part workshop series will dive deeper into data driven mapping in R. We will discuss color palettes and data classification as methods for communicating information with maps. We will also introduce basic methods for processing spatial data that are the building blocks of spatial analysis. Note, this workshop focuses on vector spatial data.
Knowledge Requirements: Basic knowledge of geospatial data is expected. R experience equivalent to the D-Lab R Fundamentals workshop series is required to follow along with the tutorial. Knowledge of ggplot helpful.
Technology Requirements: Bring a laptop with R, RStudio and the following R packages installed: sp, rgdal, rgeos, ggplot2, ggmap, leaflet, RColorBrewer, classInt, and tmap.
