Check if an object contains missing values
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.
allMissing(x) anyMissing(x)
x |
[ |
[logical(1)
] Returns TRUE
if any (anyMissing
) or all (allMissing
)
elements of x
are missing (see details), FALSE
otherwise.
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)) x = iris x[, "Species"] = NA anyMissing(x) allMissing(x)
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