Function to calculate groupwise summary statistics

summaryBy(doBy)

R Documentation

Function to calculate groupwise summary statistics

Description

Function to calculate groupwise summary statistics, much like the summary procedure of SAS

Usage

summaryBy(formula, data = parent.frame(), id = NULL, FUN = mean,
keep.names=FALSE, p2d=FALSE, order=TRUE, ...)

Arguments

formula	A formula object, see examples below
data	A data frame
id	A formula specifying variables which data are not grouped by but which should appear in the output. See examples below.
FUN	A list of functions to be applied, see examples below.
keep.names	If TRUE and if there is only ONE function in FUN, then the variables in the output will have the same name as the variables in the input, see 'examples'.
p2d	Should parentheses in output variable names be replaced by dots?
order	Should the resulting dataframe be ordered according to the variables on the right hand side of the formula? (using orderBy
...	Additional arguments to FUN. This could for example be NA actions.

Details

Extra arguments ('...') are passed onto the functions in FUN. Hence care must be taken that all functions in FUN accept these arguments - OR one can explicitly write a functions which get around this. This can particularly be an issue in connection with handling NAs. See examples below.

Some code for this function has been suggested by Jim Robison-Cox.

Value

A data frame

Author(s)

Søren Højsgaard, [email protected]

See Also

orderBy, transformBy, splitBy, lapplyBy,

Examples

data(dietox)
dietox12    <- subset(dietox,Time==12)

summaryBy(Weight+Feed~Evit+Cu,      data=dietox12,
   FUN=c(mean,var,length))  

summaryBy(Weight+Feed~Evit+Cu+Time, data=subset(dietox,Time>1),
   FUN=c(mean,var,length))  

## Calculations on transformed data:

summaryBy(log(Weight)+Feed~Evit+Cu, data=dietox12)  

## Calculations on all numerical variables (not mentioned elsewhere): 

summaryBy(.~Evit+Cu,                data=dietox12,
   id=~Litter, FUN=mean)

## There are missing values in the 'airquality' data, so we remove these
## before calculating mean and variance with 'na.rm=TRUE'. However the
## length function does not accept any such argument. Hence we get
## around this by defining our own summary function in which length is
## not supplied with this argument while mean and var are:

sumfun <- function(x, ...){
  c(m=mean(x, ...), v=var(x, ...), l=length(x))
}
summaryBy(Ozone+Solar.R~Month, data=airquality, FUN=sumfun, na.rm=TRUE)

## Using '.' on the right hand side of a formula means to stratify by
## all variables not used elsewhere:

data(warpbreaks)
summaryBy(breaks ~ wool+tension, warpbreaks)
summaryBy(breaks ~., warpbreaks)
summaryBy(.~ wool+tension, warpbreaks)

## Keep the names of the variables (works only if FUN only returns one
## value):

summaryBy(Ozone+Wind~Month, data=airquality,FUN=c(mean),na.rm=TRUE,
  keep.names=TRUE)

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