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 adata.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
).
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,] 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