R help - Aug 2011 - Labelling all variables at once (using Hmisc label)

I have a dataset and a list of labels. I simply want to apply the labels to the
variables, all at once. The only way I was able to do it was using a loop:

    for (i in 1:length(data))  label(data[,i]) <- data.labels[i]

I'd like to find the non-loop way to do it, using apply or the like... Any
help appreciated.
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On Mon, Aug 15, 2011 at 3:53 PM, Monsieur Do <nonaupourriel at yahoo.ca>
wrote:
> I have a dataset and a list of labels. I simply want to apply the labels to
the variables, all at once. The only way I was able to do it was using a loop:
>
>     for (i in 1:length(data))  label(data[,i]) <- data.labels[i]
>
> I'd like to find the non-loop way to do it, using apply or the like...
Any help appreciated.
Would you not be better off with names()?
> data <- 1:10
> data.labels <- letters[1:10]
> names(data) <- data.labels
> data
 a  b  c  d  e  f  g  h  i  j
 1  2  3  4  5  6  7  8  9 10

What are you trying to do with label() that names() doesn't accomplish?

-- 
Sarah Goslee
http://www.functionaldiversity.org

The labels can contain much more than just names. In my case, they are variable
descriptions (items from a questionnaire). I need to keep the names as they are,
hence the need for Hmisc's labels.

On Mon, Aug 15, 2011 at 3:53 PM, Monsieur Do <nonaupourriel@yahoo.ca>
wrote:
> I have a dataset and a list of labels. I simply want
to apply the labels to the variables, all at once. The only way I was able to
do it was using a loop:
> 
>     for (i in
1:length(data))  label(data[,i]) <-
data.labels[i]
> 
> I'd like to find the non-loop way to do it, using
apply or the like... Any help appreciated.
 
Would you not be better off with names()?
 
> data <- 1:10
> data.labels <- letters[1:10]
> names(data) <- data.labels
> data
 a  b  c  d  e  f  g  h  i  j
 1  2  3  4  5  6  7  8  9 10
 
What are you trying to do with label() that names()
doesn't accomplish?
 
-- 
Sarah Goslee
http://www.functionaldiversity.org
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I did read the help page before posting, but didn't find the direct way...
My function here works fine. But just for learning purposes, I'd like to be
able to avoid the loop...

with.labels <- function(x, labels=NULL, csvfile=NULL) {
if(!is.null(csvfile)) labels <- read.csv(csvfile, sep="\t",
header=F, stringsAsFactors=F)[,1]
for(i in 1:length(x)) label(x[,i]) <- labels[i]
if(length(labels) != length(x)) cat("Warning: data and labels are not of
same length\n")
return(x)
}

Thanks
> Message: 11
> Date: Tue, 16 Aug 2011 04:22:07 -0700 (PDT)
> From:
Frank Harrell <f.harrell@vanderbilt.edu>
> To:
r-help@r-project.org
> Subject:
Re: [R] Labelling all variables at once (using Hmisc
label)
> Message-ID:
<1313493727519-3746928.post@n4.nabble.com>
> Content-Type:
text/plain; charset=UTF-8
> 
> Do
require(Hmisc); ?label to see the help file for label.  It will show
you
> how to
do this:
>  
> Monsieur
Do wrote:
> >
I have a dataset and a list of labels. I simply want
> > to
apply the labels to the variables, all at once. The only way I was
able
> > to do
it was using a loop:
> >
> > for (i in 1:length(data)) label(data[,i]) <-data.labels[i]
> >
> > I'd like to find the non-loop way to do it, using
> >
apply or the like... Any help appreciated.
> >
> -----
> Frank
Harrell
> Department
of Biostatistics, Vanderbilt University
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Indeed, as David pointed out, all the portion that used courier font (all the
good stuff) was absent from the email posting. 


Thanks for your answers.
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Sorry about the nabble problem.  At any rate, do require(Hmisc) then ?label
to see how to associate a vector of labels with all the variables in a data
frame at once.
Frank

do999 wrote:
> 
> Indeed, as David pointed out, all the portion that used courier font (all
> the good stuff) was absent from the email posting.?
> 
> 
> Thanks for your answers.
> 	[[alternative HTML version deleted]]
> 
> 
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
> 

-----
Frank Harrell
Department of Biostatistics, Vanderbilt University
--
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