AC -
The easiest way I can think of is to create a time variable,
so reshape will know which observation to call 1, 2, or 3.
data$time = unlist(sapply(split(data,data$id),function(x)1:nrow(x)))
or
data$time = unlist(tapply(data$id,data$id,function(x)1:length(x))
Then
reshape(data,idvar=c('id','author'),timevar='time',direction='wide')
should give you what you want.
- Phil Spector
Statistical Computing Facility
Department of Statistics
UC Berkeley
spec...@stat.berkeley.edu
On Sun, 4 Oct 2009, AC Del Re wrote:
Dear R Community,
I am attempting to transpose a dataset from rows to columns but am stuck. I
have tried using reshape() with little luck, possibly due to the categorical
nature of the data. For example:
id<-c(1,2,2,3,3,3)
author<-c("j","k","k","l","l","l")
tmt<-c("cbt","act","dbt","act","act","cbt")
alliance<-c("wai","other","calpas","wai","itas","other")
data<-as.data.frame(cbind(id,author,tmt,alliance))
data
id author tmt alliance
1 1 j cbt wai
2 2 k act other
3 2 k dbt calpas
4 3 l act wai
5 3 l act itas
6 3 l cbt other
I would like the data to be in the following format:
id author tmt.1 tmt.2 alliance.1 alliance.2 alliance.3
1 j cbt NA wai NA NA
2 k act dbt other calpas NA
3 l act act wai itas other
I tried:
wide <- reshape(data, idvar=c("id","author"), direction="wide")
Error in `[.data.frame`(data, , timevar) : undefined columns selected
If I specify all columns, it gives the following format (which is not
desired):
wide <- reshape(data, idvar=c("id","author"),
+ direction="wide", *v.names="tmt", timevar="alliance"*)
wide
id author tmt.wai tmt.other tmt.calpas tmt.itas
1 1 j cbt <NA> <NA> <NA>
2 2 k <NA> act dbt <NA>
4 3 l act cbt <NA> act
Any help is much appreciated!
AC
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