dummies (version 1.03)

dummy: Flexible, efficient creation of dummy variables.

Description

This package flexibly and efficiently creates dummy variables for a variety of structures.

Usage

dummy(x, data = NULL, sep = "", drop = TRUE, fun = as.integer)
dummy.data.frame(data, all = TRUE, dummy.classes = getOption("dummy.classes"), ...)

Arguments

x

a single variable or variable _name_

data

an object such as a data.frame or matrix that has colnames

drop

when x or data[,x] is a factor, whether to produce dummy variables only the used levles. By default only the used levels are retained. Default is TRUE.

sep

For the names of the created dummy variables, sep is the character used between the variable name and the value.

fun

Function used to coerce values in the resulting matrix or frame.

dummy.classes

( For dummy.data.frame only ) The classes for which dummy variables are created. By default, these are factor, and character and are set globally by options('dummy.classes' ).

all

( For dummy.data.frame only ). Whether to return columns that are not dummy classes. The default is TRUE and returns all classes. Non dummy classes are untouched.

...

arguments passed to other functions

Value

• dummy returns a matrix with the number of rows equal to the that of given variable. By default, the matrix contains integers, but the exact type can be affected by fun argument. Rownames are retained if the supplied variable has associate row names.

  dummy.data.frame returns a data.frame in which variables are expanded to dummy variables if they are one of the dummy classes. The columns are return in the same order as the input with dummy variable columns replacing the original column.

Details

dummy take a single variable OR the name of single variable with data frame coerces. It coerces the variable to a factor and returns a matrix of dummy variables using model.matrix. If the data has rownames, these are retained.

Optionally, dummy can create dummies for unused levels.

If there is only one level for the variable, a warning is issued before creating the dummy variable with all the same value.

A seperator, sep, can be specified for the seperator between the variable name and the value for the construction of new variable names. The default is to provide no seperator.

The type of values returned can be affected using the fun argument.

dummy.data.frame takes a data.frame or matrix and returns a data.frame in which all columns of the dummy.classes are expanded as dummy.variables. Dummy classes can be specified globally via options('dummy.classes'). Columns that are not defined dummy.classes are untouched and are passed through. If the argument all is FALSE. The data.frame with contain only the new dummy variables By default, all columns of the object are returned and are returned in the order of the variables were in in the original data.frame.

References

http://wiki.r-project.org/rwiki/doku.php?id=tips:data-manip:create_indicator

http://tolstoy.newcastle.edu.au/R/help/00b/1199.html

http://tolstoy.newcastle.edu.au/R/help/03a/6409.html

http://tolstoy.newcastle.edu.au/R/help/01c/0580.html

See Also

model.frame, model.matrix, factor

Examples

letters <- c( "a", "a", "b", "c", "d", "e", "f", "g", "h", "b", "b" )
  dummy( as.character(letters) )
  dummy( letters[1:6] )
  
  l <- as.factor(letters)[ c(1:3,1:6,4:6) ]
  dummy(l)
  dummy(l, drop=FALSE)
  dummy(l, sep=":")
  dummy(l, sep="::", fun=as.logical)
  
  # TESTING NAS
  l <- c( NA, l, NA)
  dummy(l)
  dummy(l,sep=":")
  
  
  dummy(iris$Species)
  dummy(iris$Species[ c(1:3,51:53,101:103) ] )
  dummy(iris$Species[ c(1:3,51:53,101:103) ], sep=":" )
  dummy(iris$Species[ c(1:3,51:53) ], sep=":", drop=FALSE )     
  

  # TESTING TRAP FOR ONE LEVEL
  dummy( as.factor(letters)[c(1,1,1,1)] )
  dummy( as.factor(letters)[c(1,1,2,2)] )
  dummy( as.factor(letters)[c(1,1,1,1)] , drop = FALSE )   

  
  dummy.data.frame(iris)
  dummy.data.frame(iris, all=FALSE)