2.3 R Scripts

1. A script is code you keep

A script is a file of R code. Comments are fine. There is no YAML header and no formatted prose. The usual extension is .R.

Create one with File → New File → R Script. Type:

mean(c(2, 3, 4, 5))

## [1] 3.5

Ctrl+Enter (Windows) or Cmd+Enter (Mac) sends the current line, or the selection, to the console. The Run button does the same.

Save project scripts in an R/ folder, as in note 1.3. If the file holds one function, name the file after the function (geo_mean.R). If it holds several helpers, use a short collective name (my_utils.R).

A script is the right place for a function you will call from more than one Quarto document. Copy-paste means every fix has to be repeated.

2. Write the function once

Suppose several writeups need a geometric mean. Put the function in R/geo_mean.R:

#' Geometric mean of a positive numeric vector
#'
#' Uses log(), mean(), and exp().
#'
#' @param x A vector of positive numbers.
#'
#' @return A single numeric value.
#'
#' @examples
#' geo_mean(c(1, 6, 2, 5))
geo_mean <- function(x) {
  stopifnot(is.numeric(x))
  x |>
    log() |>
    mean() |>
    exp()
}

If you prefer %>%, load magrittr or tidyverse in the script (or in the file that sources it) before you call geo_mean().

The three classroom functions from note 2.2 are the same kind of file: one function, Roxygen header, then the body. Download them and save them as R/add_half.R, R/fib.R, and R/rep_even.R:

• add_half.R
• fib.R
• rep_even.R

3. source() makes the function available

source() runs a script in the current session. After that, the functions it defined are objects you can call.

Use a relative path from the project, the same rule as note 1.3:

source("R/geo_mean.R")

geo_mean(c(1, 6, 2, 5))

source("R/fib.R")
fib(7)
# [1] 13

From a Quarto file in analysis/, the relative path might be ../R/geo_mean.R. here::here("R", "geo_mean.R") is another reliable option once you are in an RStudio project.

If the script uses %>% or ggplot(), those packages must be loaded in the session. Either put library(...) at the top of the script, or load the packages in the document before source(). Packages are the durable way to manage those dependencies. DATA 413/613 is the course that builds them.

4. Practice

Write a function that takes a numeric vector and returns TRUE where the value is between 0.1 and 0.5, inclusive of the endpoints if you like, and FALSE otherwise.

1. Save it in R/ under a name that matches the function.
2. In a Quarto document (or an R script) in another folder, source() that file with a relative path.
3. Call it on c(0, 0.2, 0.4, 0.7).

5. This week, in one place

By the end of Week 2 you should be able to:

• use |> or %>% for a sequence of steps
• write a function: small example first, name it, give arguments and defaults, return a value, check inputs, document it
• branch with if / else / else if, or switch() when one argument picks among named options
• save the function in an .R script and source() it from another file

Functions and helpers from this week include function(), set.seed(), rnorm(), sort(), diff(), round(), mean(), range(), stopifnot(), any(), all(), &&, ||, switch(), source(), fib(), rep_even(), and add_half(). For floating-point equality, dplyr::near() is safer than ==.