Visualization of statistical data has long been recognized as an important part of understanding data, interpreting results, and communicating findings and results of scientific research. Choropleth mapping features are accessible in various software solutions. We argue that the R ecosystem, which is traditionally perceived as an open-source scripting language for statistics and data science, offers a balanced and relatively easy to use solution to most common geospatial data visualization needs. The geofi R package, developed as part of the rOpenGov community project for open government data R packages, provides tools to facilitate access to Finnish geospatial datasets in a fast and user-friendly manner. The ease of linking geospatial information from the geofi package to statistical data downloaded with pxweb and sotkaweb packages is demonstrated by the R Shiny app “Tilastot kartalle” (Engl. “Statistics on the map”). For future development, there we recognize two main challenges. First, the boundaries of existing administrative areas are not drawn with explorative data analysis in mind and therefore using them as a starting point for thematic mapping can lead to misleading results. Second, public data sources currently used offer mainly statistical datasets and geospatial data from the last 15 years, making historical choropleth maps harder to make. In our presentation we will explain how collaborative development practices can mitigate for these challenges.