Compatibility with dplyr

This page lays out the compatibility between rsample and dplyr. The rset objects from rsample are a specific subclass of tibbles, hence standard dplyr operations like joins as well row or column modifications work. However, whether the operation returns an rset or a tibble depends on the details of the operation.

The overarching principle is that any operation which leaves the specific characteristics of an rset intact will return an rset. If an operation modifies any of the following characteristics, the result will be a tibble rather than an rset:

• Rows: The number of rows needs to remain unchanged to retain the rset property. For example, you can't have a 10-fold CV object without 10 rows. The order of the rows can be changed though and the object remains an rset.

• Columns: The splits column and the id column(s) are required for an rset and need to remain untouched. They cannot be dropped, renamed, or modified if the result should remain an rset.

Joins

The following affect all of the dplyr joins, such as left_join(), right_join(), full_join(), and inner_join().

The resulting object is an rset if the number of rows is unaffected. Rows can be reordered but not added or removed, otherwise the resulting object is a tibble.

operation	same rows, possibly reordered	add or remove rows
join(rset, tbl)	rset	tibble

Row Operations

The resulting object is an rset if the number of rows is unaffected. Rows can be reordered but not added or removed, otherwise the resulting object is a tibble.

operation	same rows, possibly reordered	add or remove rows
rset[ind,]	rset	tibble
slice(rset)	rset	tibble
filter(rset)	rset	tibble
arrange(rset)	rset	tibble

Column Operations

The resulting object is an rset if the required splits and id columns remain unaltered. Otherwise the resulting object is a tibble.

operation	required columns unaltered	required columns removed, renamed, or modified
rset[,ind]	rset	tibble
select(rset)	rset	tibble
rename(rset)	rset	tibble
mutate(rset)	rset	tibble