Say it in R with by, apply and friends

gistfile1.r

## Markus Gesmann, January 2012
## Please install the following R packages first:
## data.table, doBy, plyr, reshape, sqldf, e.g. via
## install.packages(c("data.table", "doBy", "plyr", "reshape", "sqldf"))

f <- function(x) x^2
sapply(1:10, f)

do.call("rbind", as.list(
  by(iris, list(Species=iris$Species), function(x){
    y <- subset(x, select= -Species)
    apply(y, 2, mean)
  }
)))


iris.x <- subset(iris, select= -Species)
iris.s <- subset(iris, select= Species)
aggregate(iris.x, iris.s, mean)

aggregate( . ~ Species, iris, mean)

apply(iris.x, 2, function(x) tapply(x, iris.s, mean))

sapply(split(iris.x, iris.s), function(x) apply(x, 2, mean))

library(plyr)
ddply(iris, "Species", function(x){
    y <- subset(x, select= -Species)
    apply(y, 2, mean)
  })

ddply(iris, "Species", function(x) colMeans(subset(x, select= -Species)))

library(reshape)
cast(melt(iris, id.vars='Species'),formula=Species ~ variable,mean)

library(doBy)
summaryBy(Sepal.Length + Sepal.Width + Petal.Length + Petal.Width ~ Species, data=iris, FUN=mean)


library(sqldf)
sqldf("select Species, avg(Sepal_Length), avg(Sepal_Width), 
    avg(Petal_Length), avg(Petal_Width) from iris 
    group by Species")


library(data.table)
iris.dt <- data.table(iris)
iris.dt[,lapply(.SD,mean),by="Species",.SDcols=1:4]

apply(iris3, c(3,2), mean)