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).

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

N. Frerebeau

Examples

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

k <- sample(1:25, 3, FALSE)
X[k] <- NA
X
#>      [,1] [,2] [,3] [,4] [,5]
#> [1,]    5   NA    4   NA    7
#> [2,]    7    8    6    4    6
#> [3,]   NA    7    6    1    4
#> [4,]   10    6    2    7    1
#> [5,]    4    2    2    4    4

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

## Find row with NA
detect(X, f = is.na, margin = 1)
#> [1]  TRUE FALSE  TRUE FALSE FALSE
## Find column without any NA
detect(X, f = is.na, margin = 2, negate = TRUE, all = TRUE)
#> [1] FALSE FALSE  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,]    7    8    6    4    6
#> [2,]   10    6    2    7    1
#> [3,]    4    2    2    4    4
## Keep row without any NA
keep(X, f = is.na, margin = 2, negate = TRUE, all = TRUE)
#>      [,1] [,2]
#> [1,]    4    7
#> [2,]    6    6
#> [3,]    6    4
#> [4,]    2    1
#> [5,]    2    4

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

## Replace NA with zeros
replace_NA(X, value = 0)
#>      [,1] [,2] [,3] [,4] [,5]
#> [1,]    5    0    4    0    7
#> [2,]    7    8    6    4    6
#> [3,]    0    7    6    1    4
#> [4,]   10    6    2    7    1
#> [5,]    4    2    2    4    4