Hi,
I guess you are not talking about the melt() method.
dat1<-read.table(text="
Year Route Point Sp1 Sp2 Sp3
2004 123 123-1 0 1 0
2004 123 123-2 0 1 1
2004 123 123-10 1 1 0
",header=TRUE,sep="",stringsAsFactors=FALSE)
#If all the Sp columns are located next to another as shown in your
example dataset, then you can also try this:
name1<-unlist(strsplit(paste(colnames(dat1)[4:6],collapse=" ")," "))
reshape(dat1,varying=4:6,v.name
="Sp-value",times=name1,timevar="Sp-name",idvar=c("Year","Route","Point"),direction="long")
A.K.
----- Original Message -----
From: Rui Barradas <ruipbarra...@sapo.pt>
To: agoijman <agoij...@cnia.inta.gov.ar>
Cc: r-help@r-project.org
Sent: Sunday, October 7, 2012 2:32 PM
Subject: Re: [R] Presence/ absence data from matrix to single column
Hello,
I haven't been following this thread but apparently the answer to your
worries is no.
You can use a combination of names() and grep() to sort it out.
something like
#nms <- names(adat)
nms <- c("Year", "Route", "Point", paste0("Sp", 1:250))
pattern <- "^Sp[[:digit:]]+$"
whichCols <- grep(pattern, nms)
whichNames <- nms[whichCols]
reshape(..., varying = whichCols, times = whichNames, ...)
Hope this helps,
Rui Barradas
Em 07-10-2012 15:35, agoijman escreveu:
The problem with that, is that I just wrote an example of my database,
but I
have around 250 species and more than 500 sites. In the approach you show
me, it looks like I have to enter every species name and sites
individually,
right?
--
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