On May 16, 2011, at 10:25 AM, Assu wrote:
Hi all
I have a data frame with duplicate columns and i want to remove
duplicates
by adding rows in each group of duplicates, but have lots of NA's.
Data:
dfrm <- data.frame(a = 1:4, b= 1:4, cc= 1:4, dd=1:10, ee=1:4)
names(dfrm) <- c("a", "a", "b", "b", "b")
dfrm[3,2:3]<-NA
dfrm
a a b b b
1 1 1 1 1 1
2 2 2 2 2 2
3 NA NA NA 3 3
4 4 4 4 4 4
I did: sapply(unique(names(dfrm)),function(x){
rowSums(dfrm[ ,grep(x, names(dfrm)),drop=FALSE])})
which works. However, I want rowSums conditional:
1) if there is at least one value non NA in a row of each group of
duplicates, apply rowSums to get the value independently of the
existence of
other NA's in the group row.
2) if all values in a row of duplicates are NA, I get NA
In my data dfrm I would get
a b
1 2 3
2 4 6
3 NA 6
4 8 12
Can't use na.rm=TRUE or FALSE.
I tried: sapply(unique(names(dfrm)),function(x) ifelse(any(!
is.na(dfrm[
,grep(x, names(dfrm))])), rowSums(dfrm[ ,grep(x,
names(dfrm)),drop=FALSE],na.rm=TRUE),NA))
and it doesn't work.
Can someone please help me?
Thanks in advance.
You didn't like the answer I posted last night on SO?
sapply(unique(names(dfrm)),
function(x) apply(dfrm[grep(x, names(dfrm))], 1,
function(y) if ( all(is.na(y)) ) {NA} else { sum(y,
na.rm=TRUE) }
) )
--
David.
--
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--
David Winsemius, MD
Heritage Laboratories
West Hartford, CT
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