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locate the needed columns
2 messages · Hui Du, Weidong Gu
If the pattern is characterized by capital letters as your sample
suggests. The following code may help
df<-list()
names(d) = c("A.x", "B.x", "C.x", "A.y", "B.y", "C.y")
group.v<-matrix(NA,nrow=3,ncol=2) ### you may need to modify nrow and ncol
for (i in 1:3) {
group.v[i,]<-names(d)[grep(LETTERS[i],names(d))]
df[i]<-d[,names(d)%in% group.v[i]]
}
Weidong Gu
On Tue, Aug 30, 2011 at 2:31 PM, Hui Du <Hui.Du at dataventures.com> wrote:
Hi All,
? ? ? ? ? ? ? ?I have a data frame, whose colnames like "A.x, B.x, C.x, A.y, B.y, C.y". There could be many columns like this pattern. I want to compare data in columns A.x with A.y, B.x with B.y and C.x with C.y etc.
Suppose my data frame is d,
names(d) = c("A.x", "B.x", "C.x", "A.y", "B.y", "C.y");
If I want to
D1 = data.frame(d$A.x, d$A.y);
D2 = data.frame(d$B.x, d$B.y); etc. or do other operation for each pair,
What is elegant way to do it rather than use a loop?
Thanks.
HXD
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