The Art of R Programming

What actually happens in that nestedifelse()? Let’s take a careful look.

First, for the sake of concreteness, let’s find what the formal argument names

are in the functionifelse():

> args(ifelse)

function (test, yes, no)

NULL

Remember, for each element oftestthat is true, the function evaluates to

the corresponding element inyes. Similarly, iftest[i]is false, the function

evaluates tono[i]. All values so generated are returned together in a vector.

In our case here, R will execute the outerifelse()call first, in whichtest

isg=="M", andyesis 1 (recycled);nowill (later) be the result of executing

ifelse(g=="F",2,3). Now sincetest[1]is true, we generateyes[1], which is 1.

So, the first element of the return value of our outer call will be 1.

Next R will evaluatetest[2]. That is false, so R needs to findno[2].

R now needs to execute the innerifelse()call. It hasn’t done so before,

because it hasn’t needed it until now. R uses the principle oflazy evalu-

ation, meaning that an expression is not computed until it is needed.

R will now evaluateifelse(g=="F",2,3), yielding (3,2,2,3,3,3,2); this isno

for the outerifelse()call, so the latter’s second return element will be the

second element of (3,2,2,3,3,3,2), which is 2.

When the outerifelse()call gets totest[4], it will see that value to be

false and thus will returnno[4]. Since R had already computedno, it has the

value needed, which is 3.

Remember that the vectors involved could be columns in matrices, which

is a very common scenario. Say our abalone data is stored in the matrixab,

with gender in the first column. Then if we wish to recode as in the preced-

ing example, we could do it this way:

> ab[,1] <- ifelse(ab[,1] == "M",1,ifelse(ab[,1] == "F",2,3))

Suppose we wish to form subgroups according to gender. We could use

which()to find the element numbers corresponding to M, F, and I:

> m <- which(g == "M")

> f <- which(g == "F")

> i <- which(g == "I")

>m

[1]156

>f

[1]237

>i

[1] 4

52 Chapter 2