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
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.