Hi Michael,
regarding your second question you could use the `reshape()' function, i.e.,
dat <- data.frame(ID=rep(1:2, each=2), Val=seq(5,20,5))
######
dat$time <- unlist(lapply(split(dat$ID, dat$ID), function(x) 1:length(x)), use.names=FALSE)
reshape(dat, direction="wide", idvar="ID", v.names="Val")
I hope it helps.
Best, Dimitris
---- Dimitris Rizopoulos Ph.D. Student Biostatistical Centre School of Public Health Catholic University of Leuven
Address: Kapucijnenvoer 35, Leuven, Belgium Tel: +32/16/336899 Fax: +32/16/337015 Web: http://www.med.kuleuven.ac.be/biostat http://www.student.kuleuven.ac.be/~m0390867/dimitris.htm
----- Original Message ----- From: "michael watson (IAH-C)" <[EMAIL PROTECTED]>
To: <[EMAIL PROTECTED]>
Sent: Wednesday, December 01, 2004 12:50 PM
Subject: [R] Data Frame Manipulations
Hi
I have used merge() to merge two data frames, very much like performing
a SQL join. Now I want to do a few different SQL-style things and I
wondered if there were functions to do it...
Is there a "group by" style function? For example if I merge() two data
frames and end up with multiple rows for each "id", and want to take the
average of the values of a particular column? I know I can probably put
something together using merge() and by() and then munging the results
together myself, but is there something in R to perform this
automatically?
The second thing I'd like to do is like a cross-tab query; that is when
after a merge() I end up with multiple rows for a particular "id", and
want to cross-tab the data so that the multiple values become columns
and I end up with one row for each "id" again e.g.
ID Val 1 5 1 10 2 15 2 20
Becomes
ID Val1 Val2 1 5 10 2 15 20
Thanks in advance!
Mick
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