sortLevels {ff}

Factor level manipulation

Description

appendLevels combines levels without sorting such that levels of the first argument will not require re-coding.
recodeLevels is a generic for recoding a factor to a desired set of levels - also has a method for large ff objects
sortLevels is a generic for level sorting and recoding of single factors or of all factors of a ffdf dataframe.

Usage

appendLevels(...)
recodeLevels(x, lev)
## S3 method for class 'factor'
recodeLevels(x, lev)
## S3 method for class 'ff'
recodeLevels(x, lev)
sortLevels(x)
## S3 method for class 'factor'
sortLevels(x)
## S3 method for class 'ff'
sortLevels(x)
## S3 method for class 'ffdf'
sortLevels(x)

Arguments

...

character vector of levels or is.factor objects from which the level attribute is taken

x

a factor or ff factor or a ffdf dataframe (sortLevels only)

lev

a character vector of levels

Details

When reading a long file with categorical columns the final set of factor levels is only known once the complete file has been read. When a file is so large that we read it in chunks, the new levels need to be added incrementally. rbind.data.frame sorts combined levels, which requires recoding. For ff factors this would require recoding of all previous chunks at the next chunk - potentially on disk, which is too expensive. Therefore read.table.ffdf will simply appendLevels without sorting, and the recodeLevels and sortLevels generics provide a convenient means for sorting and recoding levels after all chunks have been read.

Value

appendLevels returns a vector of combined levels, recodeLevels and sortLevels return the input object with changed levels. Do read the note!

Note

You need to re-assign the return value not only for ram- but also for ff-objects. Remember ff's hybrid copying semantics: LimWarn. If you forget to re-assign the returned object, you will end up with ff objects that have their integer codes re-coded to the new levels but still carry the old levels as a virtual attribute.

Author(s)

Jens Oehlschlägel

See Also

read.table.ffdf, levels.ff

Examples

  message("Let's create a factor with little levels")
  x <- ff(letters[4:6], levels=letters[4:6])
  message("Let's interpret the same ff file without levels in order to see the codes")
  y <- x
  levels(y) <- NULL

  levels(x)
  data.frame(factor=x[], codes=y[], stringsAsFactors = TRUE)

  levels(x) <- appendLevels(levels(x), letters)
  levels(x)
  data.frame(factor=x[], codes=y[], stringsAsFactors = TRUE)

  x <- sortLevels(x) # implicit recoding is chunked were necessary
  levels(x)
  data.frame(factor=x[], codes=y[], stringsAsFactors = TRUE)

  message("NEVER forget to reassign the result of recodeLevels or sortLevels, 
look at the following mess")
  recodeLevels(x, rev(levels(x)))
  message("NOW the codings have changed, but not the levels, the result is wrong data")
  levels(x)
  data.frame(factor=x[], codes=y[], stringsAsFactors = TRUE)

  rm(x);gc()

## Not run: 
 n <- 5e7

 message("reading a factor from a file ist as fast ...")
 system.time(
 fx <- ff(factor(letters[1:25]), length=n)
 )
 system.time(x <- fx[])
 str(x)
 rm(x); gc()


 message("... as creating it in-RAM (R-2.11.1) which is theoretically impossible ...")
 system.time({
 x <- integer(n)
 x[] <- 1:25
 levels(x) <- letters[1:25]
 class(x) <- "factor"
 })
 str(x)
 rm(x); gc()


 message("... but is possible if we avoid some  unnecessary copying that is triggered 
by assignment functions")
 system.time({
 x <- integer(n)
 x[] <- 1:25
 setattr(x, "levels", letters[1:25])
 setattr(x, "class", "factor")
 })
 str(x)
 rm(x); gc()

 rm(n)

## End(Not run)