1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
|
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/colwise-filter.R
\name{filter_all}
\alias{filter_all}
\alias{filter_if}
\alias{filter_at}
\title{Filter within a selection of variables}
\usage{
filter_all(.tbl, .vars_predicate, .preserve = FALSE)
filter_if(.tbl, .predicate, .vars_predicate, .preserve = FALSE)
filter_at(.tbl, .vars, .vars_predicate, .preserve = FALSE)
}
\arguments{
\item{.tbl}{A \code{tbl} object.}
\item{.vars_predicate}{A quoted predicate expression as returned by
\code{\link[=all_vars]{all_vars()}} or \code{\link[=any_vars]{any_vars()}}.
Can also be a function or purrr-like formula. In this case, the
intersection of the results is taken by default and there's
currently no way to request the union.}
\item{.preserve}{when \code{FALSE} (the default), the grouping structure
is recalculated based on the resulting data, otherwise it is kept as is.}
\item{.predicate}{A predicate function to be applied to the columns
or a logical vector. The variables for which \code{.predicate} is or
returns \code{TRUE} are selected. This argument is passed to
\code{\link[rlang:as_function]{rlang::as_function()}} and thus supports quosure-style lambda
functions and strings representing function names.}
\item{.vars}{A list of columns generated by \code{\link[=vars]{vars()}},
a character vector of column names, a numeric vector of column
positions, or \code{NULL}.}
}
\description{
\ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#superseded}{\figure{lifecycle-superseded.svg}{options: alt='[Superseded]'}}}{\strong{[Superseded]}}
Scoped verbs (\verb{_if}, \verb{_at}, \verb{_all}) have been superseded by the use of
\code{\link[=if_all]{if_all()}} or \code{\link[=if_any]{if_any()}} in an existing verb. See \code{vignette("colwise")} for
details.
These \link{scoped} filtering verbs apply a predicate expression to a
selection of variables. The predicate expression should be quoted
with \code{\link[=all_vars]{all_vars()}} or \code{\link[=any_vars]{any_vars()}} and should mention the pronoun
\code{.} to refer to variables.
}
\section{Grouping variables}{
The grouping variables that are part of the selection are taken
into account to determine filtered rows.
}
\examples{
# While filter() accepts expressions with specific variables, the
# scoped filter verbs take an expression with the pronoun `.` and
# replicate it over all variables. This expression should be quoted
# with all_vars() or any_vars():
all_vars(is.na(.))
any_vars(is.na(.))
# You can take the intersection of the replicated expressions:
filter_all(mtcars, all_vars(. > 150))
# ->
filter(mtcars, if_all(everything(), ~ .x > 150))
# Or the union:
filter_all(mtcars, any_vars(. > 150))
# ->
filter(mtcars, if_any(everything(), ~ . > 150))
# You can vary the selection of columns on which to apply the
# predicate. filter_at() takes a vars() specification:
filter_at(mtcars, vars(starts_with("d")), any_vars((. \%\% 2) == 0))
# ->
filter(mtcars, if_any(starts_with("d"), ~ (.x \%\% 2) == 0))
# And filter_if() selects variables with a predicate function:
filter_if(mtcars, ~ all(floor(.) == .), all_vars(. != 0))
# ->
is_int <- function(x) all(floor(x) == x)
filter(mtcars, if_all(where(is_int), ~ .x != 0))
}
\keyword{internal}
|
