R Package Development: Share and Reuse Your Code

Writing functional R code is a great start, but packaging that code is what makes it truly reusable, reliable, and ready for others to use. Transitioning from loose scripts to structured packages is the key to scaling your data science workflows and collaborating effectively. In this text-only course, you will learn how to turn your R functions into professional, distributable packages that adhere to community standards. You will master the foundational structure of an R package, write clean documentation, and implement robust testing to ensure your code works seamlessly across different environments. What you'll learn: - Understand the core anatomy and essential metadata files of a standard R package - Generate package templates and manage dependencies efficiently using modern development tools - Write inline documentation and comprehensive user guides using roxygen2 to create clear help files - Implement automated unit tests with testthat to ensure code reliability and catch bugs early - Configure basic continuous integration workflows to automatically check your package across different platforms - Prepare and validate your package for distribution and sharing with the wider R community You will start by exploring the fundamental concepts of package anatomy before moving step-by-step through creating, documenting, testing, and checking your package using written explanations and practical code examples. This course is designed for R users and data scientists who can write basic R functions and want to learn how to organize, document, and share their work professionally. No prior package development experience is required. Start building your first R package today and elevate your data science workflow.