I have been using R (a free statistics and graphics software package) now for the past four years or so and I have seen it become an increasingly powerful method of both analysing and visualising spatial data. Crucially, more and more people are writing accessible tutorials (see here) for beginners and intermediate users and the development of packages such as ggplot2 have made it simpler than ever to produce fantastic graphics. You don’t get the interactivity you would with conventional GIS software such as ArcGIS when you produce the visualisation but you are much more flexible in terms of the combinations of plot types and the ease with which they can be combined. It is, for example, time consuming to produce multivariate symbols (such as those varying in size and colour) in ArcGIS but with R it is as simple* as one line of code. I have, for example, been able to add subtle transitions in the lines of the migration map above. Unless you have massive files, plotting happens quickly and can be easily saved to vector formats for tweaking in a graphics package.
R’s utilisation has been tempered by its relatively sparse documentation and challenging usability. The R community is increasingly aware of this with packages such as DeducerSpatial providing a graphical user interface to some of R’s spatial data functionality. More and more tutorials are appearing and people have been inspired by some high profile maps made with R (see here) so I am confident that it will be increasingly seen as the engine for slightly glossier analysis and visualisation packages.
R can’t do everything- I find