Removes rows/columns that contain missing values.
Usage
remove_NA(x, ...)
# S4 method for class 'ANY'
remove_NA(x, margin = 1, all = FALSE, verbose = getOption("arkhe.verbose"))
Arguments
- x
An R object (should be a
matrix
or adata.frame
).- ...
Currently not used.
- margin
A length-one
numeric
vector giving the subscripts which the function will be applied over (1
indicates rows,2
indicates columns).- all
A
logical
scalar. IfTRUE
, only the rows/columns whose values all meet the condition defined byf
are considered. IfFALSE
(the default), only rows/columns where at least one value validates the condition defined byf
are considered.- verbose
A
logical
scalar: should R report extra information on progress?
See also
Other data cleaning tools:
clean_whitespace()
,
remove_Inf()
,
remove_constant()
,
remove_empty()
,
remove_zero()
,
replace_Inf()
,
replace_NA()
,
replace_empty()
,
replace_zero()
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,] 6 3 4 3 2
#> [2,] 7 3 NA 9 NA
#> [3,] 2 2 3 5 4
#> [4,] 3 2 9 5 1
#> [5,] 2 5 7 NA 5
## Remove rows with NA
remove_NA(X, margin = 1)
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 6 3 4 3 2
#> [2,] 2 2 3 5 4
#> [3,] 3 2 9 5 1
## Replace NA with zeros
replace_NA(X, value = 0)
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 6 3 4 3 2
#> [2,] 7 3 0 9 0
#> [3,] 2 2 3 5 4
#> [4,] 3 2 9 5 1
#> [5,] 2 5 7 0 5