[R] data manipulation

[Jean Eid]

I am sure all this work but If you want exaclty the output to be the way
you mentioned do this

temp<-read.table("yourfile", as.is=T, header=T)
temp1<-temp[, 1:3]
temp2<-temp[, c(1,2,4)]
colnames(temp1)[3]<-"X"
colnames(temp2)[3]<-"X"
temp3<-merge(temp1, temp2, all=T)
temp3$type<-toupper(substr(temp3$X, 1,2))


after which you can generate factors and such..
note the as.is=T in read.table keeps the variables X1, X2, as characters.
This is done for substr...


P.S. I am sure you can use reshape instead of the second to the fifth
commands above

?reshape

Jean

On Thu, 8 Sep 2005, Sebastian Luque wrote:

> Marc Bernard <bernarduse1 at yahoo.fr> wrote:
> > Dear All,
>
> > I would be grateful if you can help me. My problem is the following:
> > I have a data set like:
>
> > ID  time      X1          X2
> > 1    1          x111      x211
> > 1    2          x112      x212
> > 2    1          x121      x221
> > 2    2          x122      x222
> > 2    3          x123      x223
>
> > where X1 and X2 are 2 covariates and "time" is the time of observation and ID
> > 	indicates the cluster.
>
> > I want to merge the above data by creating a new variable "X" and "type" as
> > 	follows:
>
> > ID   time    X            type
> > 1     1      x111         X1
> > 1     2      x112         X1
> > 1     1      x211         X2
> > 1     2      x212         X2
> > 2     1      x121         X1
> > 2     2      x122         X1
> > 2     3      x123         X1
> > 2     1      x221         X2
> > 2     2      x222         X2
> > 2     3      x223         X2
>
>
> > Where "type" is a factor variable indicating if the observation is related to
> > 	X1 or X2...
>
>
> Say your original data is in dataframe df, then this might do what you
> want:
>
> R> newdf <- rbind(df[, 1:3], df[, c(1, 2, 4)])
> R> names(newdf)[3] <- "X"
> R> newdf$type <- substr(c(df[[3]], df[[4]]), 1, 2)
>
> Cheers,
>
> --
> Sebastian P. Luque
>
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