Aggregate by NA in R

Question

Does anybody know how to aggregate by NA in R.

If you take the example below

a <- matrix(1,5,2)
a[1:2,2] <- NA
a[3:5,2] <- 2
aggregate(a[,1]         


        

Answer 1

The addNA solution of Rich doesn't require any substantial change to the aggregate syntax, so I think it's the best solution. I'll point out that another option, which produces output similar to table (and thus can be coerced into a data.frame structure similar to that of aggregate) is xtabs.

xtabs(a[, 1] ~ a[, 2], addNA=T)

Gives:

  Group.1 x
1       2 3
2     2

Another "trick" I see is assigning a missing code to these data. We all like the NA output of R, but assigning a missing code to a grouping variable is a good coding exercise. We take it so that it has one more digit than the largest value in the dataset and is of the form -999...99.

codemiss <- function(x) -10^(floor(log(max(abs(x), na.rm=T), base=10))+2)-1

works in general.

Then you get

a[, 2][is.na(a[, 2])] <- codemiss(a[, 2])

And:

aggregate(a[, 1], list(a[, 2]), sum)

Gives you:

  Group.1 x
1     -99 2
2       2 3