It seems unlikely you meant this as stated. How is it possible to "evaluate a function" when you define it? Certainly you need to give it arguments, and that can only happen when you call it.
I can pass an argument but R won’t try to evaluate unless it needs it. This can be beneficial when only some of a function’s branches need the argument. You can pass a solver for the traveling salesman problem but R won’t waste CPU cycles until it reaches a point where it has to solve the TSP to get an answer. Maybe the first branch of the function is a feasibility check, and the TSP will be skipped for something else.
This is a little harder to explain for data frames, but you can create R functions that act a little like generators in python. This can help with memory management where instead of a gigantic matrix you have a function that generates the part of the matrix that you need.
Welcome to R!
If you look at attempts to do this stuff in python---e.g. patsy, which emulates R's formula DSL, and there's another project that emulates dplyr I don't recall the name of---you see they have to resort to parsing and eval'ing strings instead of working on expressions (language objects that represent ASTs), which is not nearly as nice or safe.
Edit: But just to emphasize your surprise -- yes, you can definitely be surprised by delayed evaluation in many contexts if you're used to more traditional languages.
> y <- 10
> wat <- function(x=10*y) { y = -y; x }
> wat()
[1] -1000
> y <- 10
> less_wat <- function(x=10*y) { force(x); y = -y; x }
> less_wat()
[1] 1000