memisc (version 0.99.31.8)

xapply: Apply a function to ranges of variables

Description

xapply evaluates an expression given as second argument by substituting in variables. The results are collected in a list or array in a similar way as done by Sapply or lapply.

Usage

xapply(...,.sorted,simplify=TRUE,USE.NAMES=TRUE,.outer=FALSE)

Arguments

...

tagged and untagged arguments. The tagged arguments define the 'variables' that are looped over, the first untagged argument defines the expression wich is evaluated.

.sorted

an optional logical value; relevant only when a range of variable is specified using the column operator ":". Decises whether variable names should be sorted alphabetically before the range of variables are created.

If this argument missing, its default value is TRUE, if xapply() is called in the global environment, otherwise it is FALSE.

simplify

a logical value; should the result be simplifies in Sapply?

USE.NAMES

a logical value or a positive integer. If an integer, determines which variable is used to name the highest dimension of the result (its columns, in case is it a matrix). If TRUE, the first variable is used.

.outer

an optional logical value; if TRUE, each combination of the variables is used to evaluate the expression, if FALSE (the default) then the variables all need to have the same length and the corresponding values of the variables are used in the evaluation of the expression.

Examples

x <- 1:3
y <- -(1:3)
z <- c("Uri","Schwyz","Unterwalden")
print(x)
print(y)
print(z)
foreach(var=c(x,y,z),          # assigns names
  names(var) <- letters[1:3]   # to the elements of x, y, and z
  )
print(x)
print(y)
print(z)

ds <- data.set(
        a = c(1,2,3,2,3,8,9),
        b = c(2,8,3,2,1,8,9),
        c = c(1,3,2,1,2,8,8)
      )
print(ds)
ds <- within(ds,{ 
      description(a) <- "First item in questionnaire"
      description(b) <- "Second item in questionnaire"
      description(c) <- "Third item in questionnaire"
      
      wording(a) <- "What number do you like first?"
      wording(b) <- "What number do you like second?"
      wording(c) <- "What number do you like third?"

      foreach(x=a:c,{ # Lazy data documentation:
        labels(x) <- c(    # a,b,c get value labels in one statement
                         one = 1,
                         two = 2,
                       three = 3,
                "don't know" = 8,
         "refused to answer" = 9)
        missing.values(x) <- c(8,9)
        })
      })
      
codebook(ds)

# The colon-operator respects the order of the variables
# in the data set, if .sorted=FALSE
with(ds[c(3,1,2)],
     xapply(x=a:c,
            description(x)
            ))

# Since .sorted=TRUE, the colon operator creates a range 
# of alphabetically sorted variables.
with(ds[c(3,1,2)],
     xapply(x=a:c,
            description(x),
            .sorted=TRUE
            ))

# The variables in reverse order
with(ds,
     xapply(x=c:a,
             description(x)
            ))

# The colon operator can be combined with the 
# concatenation function
with(ds,
     xapply(x=c(a:b,c,c,b:a),
             description(x)
            ))

# Variables can also be selected by regular expressions.
with(ds,
     xapply(x=rx("[a-b]"),
             description(x)
            ))

# Demonstrating the effects of the 'USE.NAMES' argument.
with(ds,
     xapply(x=a:c,mean(x)))

with(ds,
     xapply(x=a:c,mean(x),
     USE.NAMES=FALSE))

t(with(ds,
      xapply(i=1:3,
             x=a:c,
             c(Index=i,
               Mean=mean(x)),
      USE.NAMES=2)))

# Result with 'simplify=FALSE'
with(ds,
     xapply(x=a:c,mean(x),
     simplify=FALSE))

# It is also possible to loop over functions:
xapply(fun=c(exp,log),
       fun(1))

# Two demonstrations for '.outer=TRUE'
with(ds,
      xapply(x=a:c,
             y=a:c,
             cov(x,y),
             .outer=TRUE))

with(ds,
      xapply(x=a:c,
             y=a:c,
             fun=c(cov,cor),
             fun(x,y),
             .outer=TRUE))