Making Packages in R


Teaching: 30 min
Exercises: 0 min
  • How do I collect my code together so I can reuse it and share it?

  • How do I make my own packages?

  • Describe the required structure of R packages.

  • Create the required structure of a simple R package.

  • Write documentation comments that can be automatically compiled to R’s native help and documentation format.

Why should you make your own R packages?

Reproducible research!

An R package is the basic unit of reusable code. If you want to reuse code later or want others to be able to use your code, you should put it in a package.

An R package requires four components:

There are other optional components. Read the “R packages” book for much more information.


Package: Package name
Title: Brief package description
Description: Longer package description
Version: Version number(major.minor.patch)
Author: Name and email of package creator
Maintainer: Name and email of package maintainer (who to contact with issues)
License: Abbreviation for an open source license

The package name can only contain letters and numbers and has to start with a letter.

.R files

Functions don’t all have to be in one file or each in separate files. How you organize them is up to you. Suggestion: organize in a logical manner so that you know which file holds which functions.

Making your first R package

Let’s turn our temperature conversion functions into an R package.

fahrenheit_to_kelvin <- function(temp_F) {
    # Converts Fahrenheit to Kelvin
    temp_K <- ((temp_F - 32) * (5/9)) + 273.15
kelvin_to_celsius <- function(temp_K) {
  # Converts Kelvin to Celsius
  temp_C <- temp_K - 273.15
fahrenheit_to_celsius <- function(temp_F) {
  # Converts Fahrenheit to Celsius using fahrenheit_to_kelvin() and kelvin_to_celsius()
  temp_K <- fahrenheit_to_kelvin(temp_F)
	temp_C <- kelvin_to_celsius(temp_K)

We will use the devtools and roxygen2 packages, which make creating packages in R relatively simple. Both can be installed from CRAN like this:

install.packages(c("devtools", "roxygen2"))  # installations can be `c`ombined

Set your working directory, and then use the create function to start making your package. Keep the name simple and unique.


Add our functions to the R directory. Place each function into a separate R script and add documentation like this:

#' Converts Fahrenheit to Kelvin
#' This function converts input temperatures in Fahrenheit to Kelvin.
#' @param temp_F The temperature in Fahrenheit.
#' @return The temperature in Kelvin.
#' @export
#' @examples
#' fahrenheit_to_kelvin(32)

fahrenheit_to_kelvin <- function(temp_F) {
  temp_K <- ((temp_F - 32) * (5/9)) + 273.15

The roxygen2 package reads lines that begin with #' as comments to create the documentation for your package. Descriptive tags are preceded with the @ symbol. For example, @param has information about the input parameters for the function. Now, we will use roxygen2 to convert our documentation to the standard R format.


Take a look at the package directory now. The /man directory has a .Rd file for each .R file with properly formatted documentation.

Overall, your package directory should look something like this:

R Package Structure

Now, let’s load the package and take a look at the documentation.



Notice there is now a tempConvert environment that is the parent environment to the global environment.


Now that our package is loaded, let’s try out some of the functions.

[1] 0
[1] 373.15
[1] 0

Creating a Package for Distribution

  1. Create some new functions for your tempConvert package to convert from Kelvin to Fahrenheit or from Celsius to Kelvin or Fahrenheit.
  2. Create a package for our analyze function so that it will be easy to load when more data arrives.

Key Points

  • A package is the basic unit of reusability in R.

  • Every package must have a DESCRIPTION file and an R directory containing code. These are created by us.

  • A NAMESPACE file is needed as well, and a man directory containing documentation, but both can be autogenerated.