The arcgisbinding package resolves the challenge of working with ArcGIS datasets by introducing to R a set of functions and classes that facilitate reading, writing, and manipulating ArcGIS datasets in the R programming language. However, it can be a challenge to integrate with other data types or software environments. While the language and environment have evolved over the past two decades to incorporate many other capabilities, this initial focus provides R with almost every statistical model and data manipulation technique that you would need for modern data analysis.
R is different from many other programming languages, in that it was developed primarily for data analysis and computational statistics. Learning how to incorporate ArcGIS datasets into your R scripts to perform data analysis will greatly extend the possibilities that exist for analyzing both spatial and non-spatial data. Before you can create these tools, you need to develop an understanding of how to work with the arcgisbinding package that is installed by the R-ArcGIS bridge. You can use R in conjunction with ArcGIS to develop tools that can broaden the functionality of ArcGIS. The R user community has seen substantial growth in recent years, and is expected to continue growing due to the increasing popularity of statistical data analysis.
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