Documenting other objects


Datasets are stored in data/, not as regular R objects in the package. This means you need to document them in a slightly different way: instead of documenting the data directly, you quote the dataset’s name.

#' Prices of over 50,000 round cut diamonds
#' A dataset containing the prices and other attributes of almost 54,000
#'  diamonds. The variables are as follows:
#' @format A data frame with 53940 rows and 10 variables:
#' \describe{
#'   \item{price}{price in US dollars ($326--$18,823)}
#'   \item{carat}{weight of the diamond (0.2--5.01)}
#'   \item{cut}{quality of the cut (Fair, Good, Very Good, Premium, Ideal)}
#'   \item{color}{diamond colour, from D (best) to J (worst)}
#'   \item{clarity}{a measurement of how clear the diamond is (I1 (worst), SI2,
#'     SI1, VS2, VS1, VVS2, VVS1, IF (best))}
#'   \item{x}{length in mm (0--10.74)}
#'   \item{y}{width in mm (0--58.9)}
#'   \item{z}{depth in mm (0--31.8)}
#'   \item{depth}{total depth percentage = z / mean(x, y) = 2 * z / (x + y) (43--79)}
#'   \item{table}{width of top of diamond relative to widest point (43--95)}
#' }
#' @source {ggplot2} tidyverse R package.

Note the use of two additional tags that are particularly useful for documenting data:


As well as documenting every object inside the package, you can also document the package itself by documenting the special sentinel "_PACKAGE". This automatically includes information parsed from the DESCRIPTION, including title, description, list of authors, and useful URLs.

We recommend placing package documentation in {pkgname}-package.R, and have @keywords internal. Use usethis::use_package_doc() to set up automatically.

Here’s an example:

#' @keywords internal 

Package documentation is a good place to put # Package options that documents options used by the package.

Some notes:



S4 generics are also functions, so document them as such.

Document S4 classes by adding a roxygen block before setClass(). Use @slot to document the slots of the class. Here’s a simple example:

#' An S4 class to represent a bank account
#' @slot balance A length-one numeric vector
Account <- setClass("Account",
  slots = list(balance = "numeric")

S4 methods are a little more complicated. Unlike S3 methods, all S4 methods must be documented. You can document them in three places:

Use either @rdname or @describeIn to control where method documentation goes. See the next section for more details.


roxygen2 automatically generates additional sections for an R6 class:

An example from the R6 tutorial:

#' R6 Class Representing a Person
#' @description
#' A person has a name and a hair color.
#' @details
#' A person can also greet you.

Person <- R6::R6Class("Person",
public = list(

    #' @field name First or full name of the person.
    name = NULL,

    #' @field hair Hair color of the person.
    hair = NULL,

    #' @description
    #' Create a new person object.
    #' @param name Name.
    #' @param hair Hair color.
    #' @return A new `Person` object.
    initialize = function(name = NA, hair = NA) {
      self$name <- name
      self$hair <- hair

    #' @description
    #' Change hair color.
    #' @param val New hair color.
    #' @examples
    #' P <- Person("Ann", "black")
    #' P$hair
    #' P$set_hair("red")
    #' P$hair
    set_hair = function(val) {
      self$hair <- val

    #' @description
    #' Say hi.
    greet = function() {
      cat(paste0("Hello, my name is ", self$name, ".\n"))