dplyr: How to use group_by inside a function?

by

For programming, group_by_ is the counterpart to group_by:

library(dplyr)

mytable <- function(x, ...) x %>% group_by_(...) %>% summarise(n = n())
mytable(iris, "Species")
# or iris %>% mytable("Species")

which gives:

     Species  n
1     setosa 50
2 versicolor 50
3  virginica 50

Update At the time this was written dplyr used %.% which is what was originally used above but now %>% is favored so have changed above to that to keep this relevant.

Update 2 regroup is now deprecated, use group_by_ instead.

Update 3 group_by_(list(...)) now becomes group_by_(...) in new version of dplyr as per Roberto’s comment.

Update 4 Added minor variation suggested in comments.

Update 5: With rlang/tidyeval it is now possible to do this:

library(rlang)
mytable <- function(x, ...) {
  group_ <- syms(...)
  x %>% 
    group_by(!!!group_) %>% 
    summarise(n = n())
}
mytable(iris, "Species")

or passing Species unevaluated, i.e. no quotes around it:

library(rlang)
mytable <- function(x, ...) {
  group_ <- enquos(...)
  x %>% 
    group_by(!!!group_) %>% 
    summarise(n = n())
}
mytable(iris, Species)

Update 6: There is now a {{…}} notation that works if there is just one grouping variable:

mytable <- function(x, group) {
  x %>% 
    group_by({{group}}) %>% 
    summarise(n = n())
}
mytable(iris, Species)

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