Excellent!

I felt it was fairly trivial but i can be quite dense on Friday mornings.

I really like the generalisation.

Many thanks,

baptiste


On 3 Apr 2009, at 12:11, Wacek Kusnierczyk wrote:

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

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_____________________________

Baptiste AuguiƩ

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

Phone: +44 1392 264187

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

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