Everything being a vector is one of the best things about R. You can write a function that looks sensible for scalars: in_circle <- function(x, y) { x^2

Everything being a vector is one of the best things about R. You can write a function that looks sensible for scalars: in_circle <- function(x, y) { x^2 + y^2 <= 1 } It works as you would expect: > in_circle(.2, .3) [1] TRUE > in_circle(1, 1) [1] FALSE But you can also evaluate `in_circle` for multiple points with a single function call. You can pass in vectors as arguments, and you'll get back the results as a vector: > in_circle(c(.2, 1), c(.3, 1)) [1] TRUE FALSE Since the columns of a data frame, a tibble, or a data table are all vectors, it becomes very natural to apply simple functions to them. With tibbles: > data <- tibble(a = c(.2, 1), b = c(.3, 1)) > data # A tibble: 2 × 2 a b <dbl> <dbl> 1 0.2 0.3 2 1 1 > data %>% mutate(inside = in_circle(a, b)) # A tibble: 2 × 3 a b inside <dbl> <dbl> <lgl> 1 0.2 0.3 TRUE 2 1 1 FALSE