Creation of Statistical Maps in R: the case of the Cantonal Human Development Index for Costa Rica

Abstract

Statistical maps are thematic representations for the graphing of statistical information from administrative units. For the representation of maps, there is a wide range of software, generally high cost and few free software for representation. R is free computational statistical and graphing software available for research. The objective of the article is to present a routine for the graphing of statistical maps using R and its different libraries, through the case of the Cantonal Human Development Index (HDI). R and the ggplot2, ggspatial, sf, rgdal, plyr, ggrepel and readxl libraries were obtained. The base map was obtained from a vector map in GeoJSON format and the information at the canton level was obtained from an EXCEL spreadsheet, with information from the Cantonal Human Development Atlas, 2021. The vector map information was integrated with EXCEL and did the graphical representation in R. In the generated map, the cantons of Santa Ana, Escazú and Belén have the highest HDI values among all the cantons and, in general, the cantons of Heredia are the ones with the highest values as a whole. The canton of Matina in the province of Limón has the lowest HDI in the country. The resulting map in R is a high-resolution graph that can be exported to the most popular graphic formats JPG, TIFF, PNG, BMP, thus being R a free software alternative to generate high resolution statistical maps.