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Since the first edition of this book was drafted and subsequently published, there have been a number of developments in the handling of data and spatial data in R. The use of R has exploded, and it is now a common tool taught at undergraduate and postgraduate level in many courses. This is due to a number of interrelated factors. Perhaps the most critical of these from a scientific point of view is that R is free and open source, which means that the code and functions used to manipulate data are transparent and can be integrated by the user, rather than being simply presented as black boxes as is common in many commercial software packages. Additionally, R is underpinned by a core statistical functionality that provides the basis for rigorous analysis and confident package development. Finally, R provides a dynamic analysis environment in which new packages are constantly developed, refined and updated …