Data manipulation and aggregation is one of the classic tasks anyone working with data will come across. We of course can perform data transformation and aggregation with base R, but when speed and memory efficiency come into play, data.table is my package of choice.
In this post we will look at of the fresh and very useful functionality that came to data.table only last year – grouping sets, enabling us, for example, to create pivot table-like reports with sub-totals and grand total quickly and easily.
Grouping sets are also available in SQL dialects and tend to be something people tend not to be aware of. This is a shame because they’re quite powerful, and Jozef shows how powerful they can be in R.