Another way to view R profiling Data

proftable.R

proftable <- function(file) {
  require(plyr)
  sample.interval <- as.numeric(strsplit(readLines(file, 1), "=")[[1L]][2L])/1e+06
  profdata <- as.matrix(read.table(file, header=FALSE, sep=" ", colClasses="character", skip=1, fill=TRUE, na.strings=""))
  total.time <- nrow(profdata)*sample.interval
  stacktable <- data.frame(table(aaply(profdata, 1, function(x) paste(rev(na.omit(x)), collapse=" > "))))
  names(stacktable) <- c("Stack","PctTime")
  stacktable$PctTime <- 100*stacktable$PctTime/nrow(profdata)
  stacktable <- stacktable[order(stacktable$PctTime, decreasing=TRUE), c("PctTime", "Stack")]
  rownames(stacktable) <- NULL
  attr(stacktable, "total.time") <- total.time
  print(stacktable, row.names=FALSE, right=FALSE, digits=3)
  cat(paste("\nTotal Time:", total.time, "seconds"))
  invisible(stacktable)
}