Remove Rows/Columns Using a Predicate

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

Usage

discard(x, ...)

discard_cols(x, ...)

discard_rows(x, ...)

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

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

# S4 method for ANY
discard_cols(
  x,
  f,
  negate = FALSE,
  all = 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.

verbose

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

See also

Other data cleaning tools: compact(), count(), detect(), empty, infinite, keep(), missing, remove_constant(), zero

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,]    3    6   NA    9    3
#> [2,]    2    5    5    8   NA
#> [3,]    7    3    4    4    9
#> [4,]    1    4    5   NA    2
#> [5,]    8    5    1   10    5

## Remove row with any NA
discard(X, f = is.na, margin = 1, all = FALSE)
#>      [,1] [,2] [,3] [,4] [,5]
#> [1,]    7    3    4    4    9
#> [2,]    8    5    1   10    5
## Remove column with any NA
discard(X, f = is.na, margin = 2, all = FALSE)
#>      [,1] [,2]
#> [1,]    3    6
#> [2,]    2    5
#> [3,]    7    3
#> [4,]    1    4
#> [5,]    8    5