[R] Data Frame Manipulations

[Dimitris Rizopoulos]

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)" <michael.watson at bbsrc.ac.uk>
To: <r-help at stat.math.ethz.ch>
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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