Question

Let’s say I have this vector

v <- c(1:100) 

And I want to get this:

b[1] = sum (v[c(1:10)])
b[2] = sum (v[c(11:20)])
...
...

I can do a loop to solve this, but I am pretty sure there is a “R way” that should be something like:

b <- groupedSum(v, 10) 

where b will be a vector which will have each group of 10 summed
What is the R way?

Answer 1

> tapply( v, (seq_along(v)-1) %/% 10, sum)
  0   1   2   3   4   5   6   7   8   9 
 55 155 255 355 455 555 655 755 855 955

If there were NA’s in there you might need to add na.rm=TRUE to the argument list after sum.

Comments: I think Tyler’s approach is more complete because it provided better documentation. It suffers from needing to work around the vagaries of the cut() function which I have always felt had the wrong defaults. In order to create a grouping that captures all of 1:100 he needs to use a 101 element vector. But that’s not Tyler’s fault. Send him any further votes, his answer is better.

If gsk can use by-objects without running into class difficulties, he’s a better man than I. The output looks like a list but it’s really something different. Using his example:

> is.list(by(v,idx,sum))
[1] FALSE
> is.matrix(by(v,idx,sum))
[1] FALSE
> is.vector(by(v,idx,sum))
[1] FALSE

I think by-objects are sort of like named vectors and sort of like matrices but the failure to inherit matrix class has always confused the heck out of me.