distinct_all: Select distinct rows by a selection of variables
In olascodgreat/samife: A Grammar of Data Manipulation

Description Usage Arguments Examples

These scoped variants of distinct() extract distinct rows by a selection of variables. Like distinct(), you can modify the variables before ordering with funs().

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

distinct_at(.tbl, .vars, .funs = list(), ...)

distinct_if(.tbl, .predicate, .funs = list(), ...)

`.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`.
`.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.

df <- data_frame(x = rep(2:5, each = 2) / 2, y = rep(2:3, each = 4) / 2)
df
distinct_all(df)
distinct_at(df, vars(x,y))
distinct_if(df, 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)
arrange_all(df, funs(round(.)))