Combining two vectors element-by-element - r

Question

I have 2 vectors, such as these:
A <- c(1,2,NA,NA,NA,NA,7)
B <- c(NA,NA,3,4,NA,NA,7)
I would like to combine them so that the resulting vector is
1,2,3,4,NA,NA,-1
That is
when only 1 value (say X) in either vector at position i exists (the other being NA) the new vector should take the value X at position i.
when both values are NA at position i, the new vector should take the value NA at position i
when both vectors have a value at position i, the new vector should take the value -1 at position i.
I can easily do this with a loop, but it is very slow on a large dataset so can anyone provide a fast way to do this ?

Answer 1

These commands create the vector:
X <- A
X[is.na(A)] <- B[is.na(A)]
X[is.na(B)] <- A[is.na(B)]
X[!is.na(A & B)] <- -1
#[1] 1 2 3 4 NA NA -1

Answer 2

A <- c(1,2,NA,NA,NA,NA,7)
B <- c(NA,NA,3,4,NA,NA,7)
C <- rowMeans(cbind(A,B),na.rm=TRUE)
C[which(!is.na(A*B))]<- -1
#[1] 1 2 3 4 NaN NaN -1
Benchmarks:
Unit: microseconds
expr min lq median uq max
1 Roland(A, B) 17.863 19.095 19.710 20.019 68.985
2 Sven(A, B) 11.703 13.243 14.167 14.783 100.398

Answer 3

A bit late to the party, but here is another option defining a function that works by applying rules to the two vectors cbind-ed together.
# get the data
A <- c(1,2,NA,NA,NA,NA,7)
B <- c(NA,NA,3,4,NA,NA,7)
# define the function
process <- function(A,B) {
x <- cbind(A,B)
apply(x,1,function(x) {
if(sum(is.na(x))==1) {na.omit(x)} else
if(all(is.na(x))) {NA} else
if(!any(is.na(x))) {-1}
})
}
# call the function
process(A,B)
#[1] 1 2 3 4 NA NA -1
The main benefit of using a function is that it is easier to update the rules or the inputs to apply the code to new data.