Skip to contents

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

Usage

compact(x, ...)

compact_cols(x, ...)

compact_rows(x, ...)

# S4 method for ANY
compact(x, margin = 1)

# S4 method for ANY
compact_cols(x)

# S4 method for ANY
compact_rows(x)

Arguments

x

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

...

Currently not used.

margin

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

Details

A row/column is empty if it contains only NA, zeros (if of type numeric) or zero length character strings (if of type character).

See also

Other data cleaning tools: count(), detect(), discard(), infinite, keep(), missing, zero

Author

N. Frerebeau

Examples

## Create a count 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    1    6    6    5
#> [2,]    5    3    8    5    9
#> [3,]   NA    2   10   NA    3
#> [4,]   NA   10    8    9    8
#> [5,]    2   10   10    4    8

## Count missing values in rows
count(X, f = is.na, margin = 1)
#> [1] 0 0 2 1 0
## Count non-missing values in columns
count(X, f = is.na, margin = 2, negate = TRUE)
#> [1] 3 5 5 4 5

## Find row with NA
detect(X, f = is.na, margin = 1)
#> [1] FALSE FALSE  TRUE  TRUE FALSE
## Find column without any NA
detect(X, f = is.na, margin = 2, negate = TRUE, all = TRUE)
#> [1] FALSE  TRUE  TRUE FALSE  TRUE

## Keep row without any NA
keep(X, f = is.na, margin = 1, negate = TRUE, all = TRUE)
#>      [,1] [,2] [,3] [,4] [,5]
#> [1,]    4    1    6    6    5
#> [2,]    5    3    8    5    9
#> [3,]    2   10   10    4    8
## Keep row without any NA
keep(X, f = is.na, margin = 2, negate = TRUE, all = TRUE)
#>      [,1] [,2] [,3]
#> [1,]    1    6    5
#> [2,]    3    8    9
#> [3,]    2   10    3
#> [4,]   10    8    8
#> [5,]   10   10    8

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

## Replace NA with zeros
replace_NA(X, value = 0)
#>      [,1] [,2] [,3] [,4] [,5]
#> [1,]    4    1    6    6    5
#> [2,]    5    3    8    5    9
#> [3,]    0    2   10    0    3
#> [4,]    0   10    8    9    8
#> [5,]    2   10   10    4    8