# apply()
mat <- matrix(1:200,nrow=10)
  rownames(mat) <- letters[1:10]
  colnames(mat) <- 1:20
mat
  ans <- apply(mat,MARGIN=1,mean)
ans
 ans2 <- apply(mat,MARGIN=2,mean)
ans2

# by()
data(iris)
head(iris)
attach(iris)

by(iris[,1:4],Species,colMeans)

# tapply( ) (works better for one variable at a time, by( ) is more efficient for more than one numeric variable at a time)
tapply(Sepal.Length,Species,mean)

# aggregate()
aggregate(Sepal.Length~Species,data=iris,mean)
aggregate(.~Species,data=iris,mean)