> d <- data.frame(x = c(1,2,3,NA,5), y = c(1,NA,3,4,5)) > d x y 1 1 1 2 2 NA 3 3 3 4 NA 4 5 5 5 > complete.cases(d) [1] TRUE FALSE TRUE FALSE TRUE > use <- complete.cases(d) > d[use, ] x y 1 1 1 3 3 3 5 5 5 >
-roger
ivo welch wrote:
dear R wizards: an operation I execute often is the deletion of all observations (in a matrix or data set) that have at least one NA. (I now need this operation for kde2d, because its internal quantile call complains; could this be considered a buglet?) usually, my data sets are small enough for speed not to matter, and there I do not care whether my method is pretty inefficient (ok, I admit it: I use the sum() function and test whether the result is NA)---but now I have some bigger data sets. Is there a recommended method of doing NA elimination most efficiently? sincerely, /iaw
---
ivo welch
professor of finance and economics
brown / nber / yale
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