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,] 8 10 2 NA 1
#> [2,] 9 7 NA 2 8
#> [3,] 8 6 10 7 3
#> [4,] NA 4 8 6 9
#> [5,] 8 4 9 7 2
## Count missing values in rows
count(X, f = is.na, margin = 1)
#> [1] 1 1 0 1 0
## Count non-missing values in columns
count(X, f = is.na, margin = 2, negate = TRUE)
#> [1] 4 5 4 4 5
## Find row with NA
detect(X, f = is.na, margin = 1)
#> [1] TRUE TRUE FALSE TRUE FALSE
## Find column without any NA
detect(X, f = is.na, margin = 2, negate = TRUE, all = TRUE)
#> [1] FALSE TRUE FALSE FALSE TRUE
## Keep row without any NA
keep(X, f = is.na, margin = 1, negate = TRUE, all = TRUE)
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 8 6 10 7 3
#> [2,] 8 4 9 7 2
## Keep row without any NA
keep(X, f = is.na, margin = 2, negate = TRUE, all = TRUE)
#> [,1] [,2]
#> [1,] 10 1
#> [2,] 7 8
#> [3,] 6 3
#> [4,] 4 9
#> [5,] 4 2
## Remove row with any NA
discard(X, f = is.na, margin = 1, all = FALSE)
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 8 6 10 7 3
#> [2,] 8 4 9 7 2
## Remove column with any NA
discard(X, f = is.na, margin = 2, all = FALSE)
#> [,1] [,2]
#> [1,] 10 1
#> [2,] 7 8
#> [3,] 6 3
#> [4,] 4 9
#> [5,] 4 2
## Replace NA with zeros
replace_NA(X, value = 0)
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 8 10 2 0 1
#> [2,] 9 7 0 2 8
#> [3,] 8 6 10 7 3
#> [4,] 0 4 8 6 9
#> [5,] 8 4 9 7 2