Fastest way to detect if vector has at least 1 NA?

What is the fastest way to detect if a vector has at least 1 NA in R? I've been using:

sum( is.na( data ) ) > 0

But that requires examining each element, coercion, and the sum function.

Solution 1:

I'm thinking:

any(is.na(data))

should be slightly faster.

Solution 2:

As of R 3.1.0 anyNA() is the way to do this. On atomic vectors this will stop after the first NA instead of going through the entire vector as would be the case with any(is.na()). Additionally, this avoids creating an intermediate logical vector with is.na that is immediately discarded. Borrowing Joran's example:

x <- y <- runif(1e7)
x[1e4] <- NA
y[1e7] <- NA
microbenchmark::microbenchmark(any(is.na(x)), anyNA(x), any(is.na(y)), anyNA(y), times=10)
# Unit: microseconds
#           expr        min         lq        mean      median         uq
#  any(is.na(x))  13444.674  13509.454  21191.9025  13639.3065  13917.592
#       anyNA(x)      6.840     13.187     13.5283     14.1705     14.774
#  any(is.na(y)) 165030.942 168258.159 178954.6499 169966.1440 197591.168
#       anyNA(y)   7193.784   7285.107   7694.1785   7497.9265   7865.064

Notice how it is substantially faster even when we modify the last value of the vector; this is in part because of the avoidance of the intermediate logical vector.

Solution 3:

We mention this in some of our Rcpp presentations and actually have some benchmarks which show a pretty large gain from embedded C++ with Rcpp over the R solution because

• a vectorised R solution still computes every single element of the vector expression

• if your goal is to just satisfy any(), then you can abort after the first match -- which is what our Rcpp sugar (in essence: some C++ template magic to make C++ expressions look more like R expressions, see this vignette for more) solution does.

So by getting a compiled specialised solution to work, we do indeed get a fast solution. I should add that while I have not compared this to the solutions offered in this SO question here, I am reasonably confident about the performance.

Edit And the Rcpp package contains examples in the directory sugarPerformance. It has an increase of the several thousand of the 'sugar-can-abort-soon' over 'R-computes-full-vector-expression' for any(), but I should add that that case does not involve is.na() but a simple boolean expression.