Maps are important in official statistics. Statistical researchers and data scientists use maps to explore and analyse spatial data, to share their findings, and to communicate statistical output to the general public. Traditionally, maps are made with specialized desktop GIS tools, such as ArcGIS, QGIS, and GRASS. Although the set of features and functionalities of these tools are impressive, there are some main drawbacks, especially when it comes down to reproducing maps. During the last decade, R has become a very powerful and mature alternative for spatial data analysis and visualisation, with the advantage of reproducible scripts. Moreover, working with spatial data has become much easier; you don't need a master in computer science to create maps with R. In this presentation, we illustrate how easy mapping has become using some state-of-the-art R packages.