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

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

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

## Keep row without any NA
keep(X, f = is.na, margin = 1, negate = TRUE, all = TRUE)
#>      [,1] [,2] [,3] [,4] [,5]
#> [1,]    9    6    3    7   10
#> [2,]    1    9    1    5    3
#> [3,]    3    4   10    2    3
## Keep row without any NA
keep(X, f = is.na, margin = 2, negate = TRUE, all = TRUE)
#>      [,1] [,2]
#> [1,]    9    7
#> [2,]    1    5
#> [3,]    9   10
#> [4,]    3    2
#> [5,]   10    5

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

## Replace NA with zeros
replace_NA(X, value = 0)
#>      [,1] [,2] [,3] [,4] [,5]
#> [1,]    9    6    3    7   10
#> [2,]    1    9    1    5    3
#> [3,]    9    0    0   10    2
#> [4,]    3    4   10    2    3
#> [5,]   10    7   10    5    0