Aggregating by a grouping
One possibility is:
x
[1] "A" "B" "C" "D" "A" "C" "D" "B"
y
[1] 10 11 9 8 12 4 5 7
basic_map
[[1]] [1] "A" "B" [[2]] [1] "C" "D"
a <- which(sapply(basic_map,function(u) x %in%
u),arr.ind=TRUE)
aggregate(y,list(a[order(a[,1]),2]),sum)
Group.1 x 1 1 40 2 2 26
--- "Kondamani, Arjun (GMI - NY Corporate Bonds)"
<arjun_kondamani at ml.com> wrote:
Suppose I have:
Book Value
A 10
B 11
C 9
D 8
A 12
C 4
D 5
B 7
I want to summarize above not by Book but by
groupings of Books as in
(below)
I have a list ... basic_map <-
list(c("A",B"),c("C,D"))
Big_names <- c("A1", "A2")
Names(basic_map) <- big_names
So I want to get :
A1 40
A2 26
How do I use tapply AND the list to get my custom
groupings?
thx
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