If I understand you right,
library(reshape2)
dcast(melt(TestData, id.var = "Subject", measure.var = "Drug"), Subject ~ value)
Michael
On Tue, Mar 20, 2012 at 9:50 AM, Paul Miller <pjmiller...@yahoo.com> wrote:
> Hello All,
>
> I was wondering if it's possible to reshape data from long to wide in R
> without using a "timevar". I've pasted some sample data below along with some
> code. The data are sorted by Subject and Drug. I want to transpose the Drug
> variable into multiple columns in alphabetical order.
>
> My data have a variable called "RowNo" that functions almost like a "timevar"
> but not quite. In Subject 6, Erlotinib has a RowNo value of 3 whereas
> Paclitaxel has a RowNo value of 2. So if I use reshape as in the first bit of
> code below, the columns for drug don't transpose in alphabetical order. That
> is, Paclitaxel appears in Drug.2 and Erlotinib appears in Drug.3 when it
> should be the other way around.
>
> The next two bits of code represent a couple of other things I've tried. The
> cast function almost works but unfortunately makes a separate column for each
> drug (at least the way I'm using it). The unstack function works almost
> perfectly but to my surprise creates a list instead of a dataframe (which I
> understand is a different kind of list). Thought it might take a single line
> of code to convert the former structure to the latter but this appears not to
> be the case.
>
> So can I get what I want without adding a timevar to my data? And if do need
> a timevar, what's the best way to add it?
>
> Thanks,
>
> Paul
>
> connection <- textConnection("
> 005 1 Gemcitabine
> 005 2 Erlotinib
> 006 1 Gemcitabine
> 006 3 Erlotinib
> 006 2 Paclitaxel
> 009 1 Gemcitabine
> 009 2 Erlotinib
> 010 1 Gemcitabine
> 010 2 Erlotinib
> 010 3 Herceptin
> ")
>
> TestData <- data.frame(scan(connection, list(Subject = 0, RowNo = 0, Drug =
> "")))
> TestData$Subject <- as.integer(TestData$Subject)
> TestData$RowNo <- as.integer(TestData$RowNo)
> TestData$Drug <- as.character(TestData$Drug)
>
> require(reshape)
>
> Transpose <- reshape(TestData, direction="wide", idvar="Subject",
> timevar="RowNo", v.names="Drug")
> Transpose
>
> Transpose <- melt(TestData, id.var="Subject", measure.var="Drug")
> Transpose <- cast(Transpose, Subject ~ value)
> Transpose
>
> Transpose <- unstack(TestData, Drug ~ Subject)
> Transpose
>
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