Keep Rows/Columns Using a Predicate

Keeps rows/columns in an array-like object using a predicate function.

Usage

keep(x, ...)

keep_cols(x, ...)

keep_rows(x, ...)

# S4 method for ANY
keep(
  x,
  f,
  margin = 1,
  negate = FALSE,
  all = FALSE,
  na.rm = FALSE,
  verbose = getOption("arkhe.verbose"),
  ...
)

# S4 method for ANY
keep_rows(
  x,
  f,
  negate = FALSE,
  all = FALSE,
  na.rm = FALSE,
  verbose = getOption("arkhe.verbose"),
  ...
)

# S4 method for ANY
keep_cols(
  x,
  f,
  negate = FALSE,
  all = FALSE,
  na.rm = FALSE,
  verbose = getOption("arkhe.verbose"),
  ...
)

Arguments

x

An R object (should be a matrix or a data.frame).

...

Further arguments to be passed to f.

f

A predicate function.

margin

A length-one numeric vector giving the subscripts which the function will be applied over (1 indicates rows, 2 indicates columns).

negate

A logical scalar: should the negation of f be used instead of f?

all

A logical scalar. If TRUE, only the rows/columns whose values all meet the condition defined by f are considered. If FALSE (the default), only rows/columns where at least one value validates the condition defined by f are considered.

na.rm

A logical scalar: should NA values be stripped before the computation proceeds?

verbose

A logical scalar: should R report extra information on progress?

See also

Other data preparation tools: append(), assign(), compact(), count(), detect(), discard(), get(), seek()

Author

N. Frerebeau

Examples

## Create a data matrix
X <- matrix(sample(1:10, 25, TRUE), nrow = 5, ncol = 5)

## Add NA
k <- sample(1:25, 3, FALSE)
X[k] <- NA
X
#>      [,1] [,2] [,3] [,4] [,5]
#> [1,]    4    5    2    6    8
#> [2,]    6   10    1    8    8
#> [3,]   NA    5   10    6    3
#> [4,]    8   NA    3    4    5
#> [5,]    8   10   NA    4    4

## Keep row without any NA
keep(X, f = is.na, margin = 1, negate = TRUE, all = TRUE)
#>      [,1] [,2] [,3] [,4] [,5]
#> [1,]    4    5    2    6    8
#> [2,]    6   10    1    8    8
## Keep row without any NA
keep(X, f = is.na, margin = 2, negate = TRUE, all = TRUE)
#>      [,1] [,2]
#> [1,]    6    8
#> [2,]    8    8
#> [3,]    6    3
#> [4,]    4    5
#> [5,]    4    4