Fast rollup of rows from a data.frame (uses data.table for speed)

aggregate.data.table.r

#' aggregate.data.table
#' 
#' Use to quickly aggregate rows from a data.frame
#'
#' @param   x           data.table
#' @param   by          list of columns to use for grouping
#' @param   FUN         summary function
#' @param   \dots       further arguments to summary function
#' @param   is.value    determines which of the remaining columns should be aggregated (numeric, POSIXct, character, etc.)
#' @author              David Holstius \email{david.holstius@berkeley.edu}
#' @export
aggregate.data.table <- function(x, by, FUN=mean, ..., is.value=is.numeric) {
    value_columns <- names(x)[which(sapply(x, is.value))]
    x[,lapply(.SD,FUN,...),eval(substitute(by)),.SDcols=value_columns]
}
 
# Example 1
library(data.table)
data(diamonds, package='ggplot2')
dt <- data.table(diamonds)
aggregate(dt, by=list(cut)) # defaults to arithmetic mean

# Example 2
GM <- function (x, ...) exp(mean(log(x), ...)) # geometric mean
aggregate(dt, by=list(cut, color), FUN=GM, na.rm=TRUE)