A clearer explanation is the lazy evaluation here: http://adv-r.had.co.nz/Functions.html#function-arguments

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.