R help - Apr 2009 - "factorise" variables in a data.frame

Dear list,

I often need to convert several variables from numeric or integer into  
factors (before plotting, for instance), as in the following example,


d <- data.frame(
	x = seq(1, 10),
	y = seq(1, 10),
	z = rnorm(10),
	a = letters[1:10])
	

d2 <-
within(d, {
	x = factor(x)
	y = factor(y)
	 })
	
str(d)
str(d2)


I'd like to write a function factorise() which takes a data.frame and  
a vector of variable names, and returns the original data.frame with  
the desired variables converted to factor,

factorise <- function(d, f)
***ply(d, f, factor) # some apply function

also, perhaps a defactorise() function doing the reverse operation  
with as.numeric.

I played with the plyr package and the base apply family for a while  
but can't find any concise construct.

Best regards,

baptiste



_____________________________

Baptiste Augui?

School of Physics
University of Exeter
Stocker Road,
Exeter, Devon,
EX4 4QL, UK

Phone: +44 1392 264187

http://newton.ex.ac.uk/research/emag

baptiste auguie wrote:
> Dear list,
>
> I often need to convert several variables from numeric or integer into
> factors (before plotting, for instance), as in the following example,
>
>
> d <- data.frame(
>     x = seq(1, 10),
>     y = seq(1, 10),
>     z = rnorm(10),
>     a = letters[1:10])
>     
>
> d2 <-
> within(d, {
>     x = factor(x)
>     y = factor(y)
>      })
>     
> str(d)
> str(d2)
>
>
> I'd like to write a function factorise() which takes a data.frame and
> a vector of variable names, and returns the original data.frame with
> the desired variables converted to factor,
>
would this not be good enough:

    # dummy data
    data = data.frame(x=1:10, y=1:10)

    # a factorizer
    factorize = function(data, columns=names(data)) {
       data[columns] = lapply(data[columns], as.factor)
       data }

    sapply(factorize(data, 'x'), is)
    # $x "factor" ...
    # $y "integer" ...
    lapply(factorize(data), is)
    # $x "factor" ...
    # $y "factor" ...
  
> factorise <- function(d, f)
> ***ply(d, f, factor) # some apply function
>
> also, perhaps a defactorise() function doing the reverse operation
> with as.numeric.
then, perhaps,

    # an izer
    ize = function(data, columns=names(data), izer=as.factor) {
       data[columns] = lapply(data[columns], izer)
       data }

    ize(data, 'x', as.logical)
   
or even

    ize = function(izer)
       function(data, columns=names(data)) {
          data[columns] = lapply(data[columns], izer)
          data }

    logicalize = ize(as.logical)
    characterize = ize(as.character)
   
    lapply(logicalize(data), is)
    # $x "logical" ...
    # $y "logical" ...
    lapply(characterize(data, 'x'), is)
    # $x "character" ...
    # $y "integer" ...

etc.
   
vQ