Counts values by rows/columns using a predicate function.
Usage
count(x, f, ...)
# S4 method for matrix,`function`
count(x, f, margin = 1, negate = FALSE)
# S4 method for data.frame,`function`
count(x, f, margin = 1, negate = FALSE)
Arguments
- x
An object (should be a
matrix
or adata.frame
).- f
A predicate
function
.- ...
Currently not used.
- margin
A vector giving the subscripts which the function will be applied over (
1
indicates rows,2
indicates columns).- negate
A
logical
scalar: should the negation off
be used instead off
?
Value
A numeric
vector.
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,] 6 4 8 2 9
#> [2,] 6 NA 6 3 3
#> [3,] 1 NA 5 5 8
#> [4,] 6 9 10 6 8
#> [5,] NA 6 6 6 2
## Count missing values in rows
count(X, f = is.na, margin = 1)
#> [1] 0 1 1 0 1
## Count non-missing values in columns
count(X, f = is.na, margin = 2, negate = TRUE)
#> [1] 4 3 5 5 5
## Find row with NA
detect(X, f = is.na, margin = 1)
#> [1] FALSE TRUE TRUE FALSE TRUE
## Find column without any NA
detect(X, f = is.na, margin = 2, negate = TRUE, all = TRUE)
#> [1] FALSE FALSE TRUE TRUE TRUE
## Keep row without any NA
keep(X, f = is.na, margin = 1, negate = TRUE, all = TRUE)
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 6 4 8 2 9
#> [2,] 6 9 10 6 8
## Keep row without any NA
keep(X, f = is.na, margin = 2, negate = TRUE, all = TRUE)
#> [,1] [,2] [,3]
#> [1,] 8 2 9
#> [2,] 6 3 3
#> [3,] 5 5 8
#> [4,] 10 6 8
#> [5,] 6 6 2
## Remove row with any NA
discard(X, f = is.na, margin = 1, all = FALSE)
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 6 4 8 2 9
#> [2,] 6 9 10 6 8
## Remove column with any NA
discard(X, f = is.na, margin = 2, all = FALSE)
#> [,1] [,2] [,3]
#> [1,] 8 2 9
#> [2,] 6 3 3
#> [3,] 5 5 8
#> [4,] 10 6 8
#> [5,] 6 6 2
## Replace NA with zeros
replace_NA(X, value = 0)
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 6 4 8 2 9
#> [2,] 6 0 6 3 3
#> [3,] 1 0 5 5 8
#> [4,] 6 9 10 6 8
#> [5,] 0 6 6 6 2