group_by_all: Group by a selection of variables
In olascodgreat/samife: A Grammar of Data Manipulation

Description Usage Arguments See Also Examples

These scoped variants of group_by() group a data frame by a selection of variables. Like group_by(), they have optional mutate semantics.

group_by_all(.tbl, .funs = list(), ...)

group_by_at(.tbl, .vars, .funs = list(), ..., .add = FALSE)

group_by_if(.tbl, .predicate, .funs = list(), ..., .add = FALSE)

`.tbl`	A `tbl` object.
`.funs`	List of function calls generated by `funs()`, or a character vector of function names, or simply a function. Bare formulas are passed to `rlang::as_function()` to create purrr-style lambda functions. Note that these lambda prevent hybrid evaluation from happening and it is thus more efficient to supply functions like `mean()` directly rather than in a lambda-formula.
`...`	Additional arguments for the function calls in `.funs`. These are evaluated only once, with tidy dots support.
`.vars`	A list of columns generated by `vars()`, a character vector of column names, a numeric vector of column positions, or `NULL`.
`.add`	Passed to the `add` argument of `group_by()`.
`.predicate`	A predicate function to be applied to the columns or a logical vector. The variables for which `.predicate` is or returns `TRUE` are selected. This argument is passed to `rlang::as_function()` and thus supports quosure-style lambda functions and strings representing function names.

Other grouping functions: group_by, group_indices, group_rows, group_size, groups

# Group a data frame by all variables:
group_by_all(mtcars)

# Group by variables selected with a predicate:
group_by_if(iris, is.factor)

# Group by variables selected by name:
group_by_at(mtcars, vars(vs, am))

# Like group_by(), the scoped variants have optional mutate
# semantics. This provide a shortcut for group_by() + mutate():
d <- tibble(x=c(1,1,2,2), y=c(1,2,1,2))
group_by_all(d, as.factor)
group_by_if(iris, is.factor, as.character)