The answers here are good, but they are missing an important point. Let me try and describe it.
R is a functional language and does not like to mutate its objects. But it does allow assignment statements, using replacement functions:
levels(x) <- y
is equivalent to
x <- `levels<-`(x, y)
The trick is, this rewriting is done by <-
; it is not done by levels<-
. levels<-
is just a regular function that takes an input and gives an output; it does not mutate anything.
One consequence of that is that, according to the above rule, <-
must be recursive:
levels(factor(x)) <- y
is
factor(x) <- `levels<-`(factor(x), y)
is
x <- `factor<-`(x, `levels<-`(factor(x), y))
It’s kind of beautiful that this pure-functional transformation (up until the very end, where the assignment happens) is equivalent to what an assignment would be in an imperative language. If I remember correctly this construct in functional languages is called a lens.
But then, once you have defined replacement functions like levels<-
, you get another, unexpected windfall: you don’t just have the ability to make assignments, you have a handy function that takes in a factor, and gives out another factor with different levels. There’s really nothing “assignment” about it!
So, the code you’re describing is just making use of this other interpretation of levels<-
. I admit that the name levels<-
is a little confusing because it suggests an assignment, but this is not what is going on. The code is simply setting up a sort of pipeline:
-
Start with
dat$product
-
Convert it to a factor
-
Change the levels
-
Store that in
res
Personally, I think that line of code is beautiful 😉