Reputation: 1491
My problem is somewhat related to this question.
I have a data as below
V1 V2
.. 1
.. 2
.. 1
.. 3
I need to calculate variance of data in V1
for each value of V2
cumulatively (This means that for a particular value of V2
say n
,all the rows of V1
having corresponding V2
less than n
need to be included.
Will ddply
help in such a case?
Upvotes: 2
Views: 216
Reputation: 226332
I don't think ddply
will help since it is built on the concept of taking non-overlapping subsets of a data frame.
d <- data.frame(V1=runif(1000),V2=sample(1:10,size=1000,replace=TRUE))
u <- sort(unique(d$V2))
ans <- sapply(u,function(x) {
with(d,var(V1[V2<=x]))
})
names(ans) <- u
I don't know if there's a more efficient way to do this ...
Upvotes: 4