distinct_all
Select distinct rows by a selection of variables
Description
![[Superseded]](../help/figures/lifecycle-superseded.svg)
Scoped verbs (_if, _at, _all) have been superseded by the use of
across() in an existing verb. See vignette("colwise") for details.
These scoped variants of distinct() extract distinct rows by a
selection of variables. Like distinct(), you can modify the
variables before ordering with the .funs argument.
Usage
distinct_all(.tbl, .funs = list(), ..., .keep_all = FALSE) distinct_at(.tbl, .vars, .funs = list(), ..., .keep_all = FALSE) distinct_if(.tbl, .predicate, .funs = list(), ..., .keep_all = FALSE)
Arguments
.tbl |
A |
.funs |
A function |
... |
Additional arguments for the function calls in
|
.keep_all |
If |
.vars |
A list of columns generated by |
.predicate |
A predicate function to be applied to the columns
or a logical vector. The variables for which |
Grouping variables
The grouping variables that are part of the selection are taken into account to determine distinct rows.
Examples
df <- tibble(x = rep(2:5, each = 2) / 2, y = rep(2:3, each = 4) / 2) distinct_all(df) # -> distinct(df, across()) distinct_at(df, vars(x,y)) # -> distinct(df, across(c(x, y))) distinct_if(df, is.numeric) # -> distinct(df, across(where(is.numeric))) # You can supply a function that will be applied before extracting the distinct values # The variables of the sorted tibble keep their original values. distinct_all(df, round) # -> distinct(df, across(everything(), round))