Supported are atomic types (see is.atomic), lists and data frames.
Missingness is defined as NA or NaN for atomic types and data frame columns,
NULL is defined as missing for lists. allMissing applied to a data.frame returns TRUE if at least one column has
only non-missing values. If you want to perform the less frequent check that there is not a single
non-missing observation present in the data.frame, use all(sapply(df, allMissing))
instead.
Usage
allMissing(x)
anyMissing(x)
Arguments
x
[ANY]
Object to check.
Value
[logical(1)] Returns TRUE if any (anyMissing) or all (allMissing)
elements of x are missing (see details), FALSE otherwise.
Examples
allMissing(1:2)
allMissing(c(1, NA))
allMissing(c(NA, NA))
x = data.frame(a = 1:2, b = NA)
# Note how allMissing combines the results for data frames:
allMissing(x)
all(sapply(x, allMissing))
anyMissing(c(1, 1))
anyMissing(c(1, NA))
anyMissing(list(1, NULL))