Why Write an R Package?

“If you copy-paste the same function twice, it belongs in a package.”
— Hadley Wickham (probably)

Many R users start with scripts — one-off analyses or dashboards — and over time accumulate useful snippets, functions, and workflows. Turning these into a package gives them a reusable, shareable, and maintainable home.

Avoid Copy-Paste Chaos

If you find yourself reusing the same:

  • helper_functions.R file
  • chunk of mutate() + case_when()
  • custom plotting function
    …across multiple projects, it’s time to package it.

Instead of copy-pasting code:

source("../old-project/scripts/helpers.R")

You could just do:

library(mytools)

Much cleaner.

Make Code Shareable

Packages are the standard unit of collaboration in R. Anyone can install them with:

devtools::install_github("yourname/mypackage")

This makes it easy to:

  • Share functions with teammates
  • Help others reproduce your work
  • Document your thinking for future you

A package is documentation and code bundled together.

Improve Reliability

When you make an R package, you gain tools to:

  • Write tests for your functions
  • Ensure every exported function is documented
  • Catch problems early with devtools::check()

These are things many data analysts skip in scripts — but they’re built into the package workflow.

Packages Are for Everyone

You don’t need to be a software engineer or CRAN contributor to make a useful package.

Packages are for:

  • Personal toolkits
  • Team utilities
  • Data documentation
  • Course materials
  • Dashboards and Shiny apps
  • Publishing open source code

TL;DR: Why Package?

Without a package With a package
Copy-paste code Reusable functions
No docs or tests Auto-generated help files
Code scattered in scripts Clean, versioned structure
Hard to share devtools::install_github()

🛠️ Coming Up

We’ll walk through creating your first package from scratch using {usethis} and {devtools} — no manual setup required.

Next: 👉 Create a New Package