ave function in R is one of those little helper function I feel I should be using more. Investigating its source code showed me another twist about R and the “[” function. But first let’s look at
The top of
ave’s help page reads:
Group Averages Over Level Combinations of Factors
Subsets of x are averaged, where each subset consist of those observations with the same factor levels.
As an example I look at revenue data by product and shop.
revenue <- c(30,20, 23, 17)To answer the question “Which shop sells proportionally more bread?” I need to divide the revenue vector by the sum of revenue per shop, which can be calculated easily by
product <- factor(c(“bread”, “cake”, “bread”, “cake”))
shop <- gl(2,2, labels=c(“shop_1”, “shop_2”))
In other words,
(shop_revenue <- ave(revenue, shop, FUN=sum))
#  50 50 40 40
(revenue_split_in_shop <- revenue/shop_revenue)
#  0.600 0.400 0.575 0.425 # Shop 1 sells more bread than cake
avehas to split the revenue vector by shop and apply the
sumfunction to it. Well that’s exactly what it does. Here is the source code of
However, and this is what intrigued me, if I don’t provide a grouping variable (
# Copyright © 1995-2012 The R Core Team
ave <- function (x, …, FUN = mean)
x <- FUN(x)
g <- interaction(…)
split(x,g) <- lapply(split(x, g), FUN)
missing(…)) it will apply the function
xitself and write its output to
x. That’s actually what the help file to
avementioned in its description. So what does it do? Here is an example again:
I get the sum of revenue repeated as many time as the vector has elements, not just once, as with
#  90 90 90 90
sum(revenue). The trick is that the output of
FUN(x)is written into
x, which of course is output of a function call itself “[“(x).
I think it is the following sentence in the help file of
“[”(see ?”[“), which explains it: Subsetting (except by an empty index) will drop all attributes except names, dim and dimnames.
So there we are. I feel less inclined to use
avemore, as it is just short for the usual
split, lapplyroutine, but I learned something new about the subtleties of R.