R: Apply a Function by Groups

gapply {nlme}

R Documentation

Apply a Function by Groups

Description

Applies the function to the distinct sets of rows of the data frame defined by groups.

Usage

gapply(object, which, FUN, form, level, groups, ...)

Arguments

`object`	an object to which the function will be applied - usually a `groupedData` object or a `data.frame`. Must inherit from class `"data.frame"`.
`which`	an optional character or positive integer vector specifying which columns of `object` should be used with `FUN`. Defaults to all columns in `object`.
`FUN`	function to apply to the distinct sets of rows of the data frame `object` defined by the values of `groups`.
`form`	an optional one-sided formula that defines the groups. When this formula is given the right-hand side is evaluated in `object`, converted to a factor if necessary, and the unique levels are used to define the groups. Defaults to `formula(object)`.
`level`	an optional positive integer giving the level of grouping to be used in an object with multiple nested grouping levels. Defaults to the highest or innermost level of grouping.
`groups`	an optional factor that will be used to split the rows into groups. Defaults to `getGroups(object, form, level)`.
`...`	optional additional arguments to the summary function `FUN`. Often it is helpful to specify `na.rm = TRUE`.

Value

Returns a data frame with as many rows as there are levels in the groups argument.

Author(s)

José Pinheiro and Douglas Bates bates@stat.wisc.edu

References

Pinheiro, J.C., and Bates, D.M. (2000) "Mixed-Effects Models in S and S-PLUS", Springer, esp. sec. 3.4.

Examples

## Find number of non-missing "conc" observations for each Subject
gapply( Phenobarb, FUN = function(x) sum(!is.na(x$conc)) )

# Pinheiro and Bates, p. 127 
table( gapply(Quinidine, "conc", function(x) sum(!is.na(x))) )
changeRecords <- gapply( Quinidine, FUN = function(frm)
    any(is.na(frm[["conc"]]) & is.na(frm[["dose"]])) )

[Package nlme version 3.1-166 Index]