Daniel Sabanés Bové, a statistician from Roche and Google and founder of Arconis consulting, discusses the transformative power of creating R packages for code reuse and collaboration. He shares insights on overcoming common coding challenges and emphasizes that starting to write packages might happen sooner than you think. With tools like usethis and testthat, Sabanés walks through his process from idea to launch. He also highlights the vibrant R community, filled with creativity, collaboration, and fun elements like hex stickers.
Creating R packages enhances code reuse and collaboration, addressing common challenges like documentation and readability to improve overall code quality.
A systematic approach to package development, starting with careful planning and prototyping, ensures effective organization and ongoing functionality as projects evolve.
Deep dives
The Importance of Creating R Packages
Creating R packages is essential for reusing code effectively and improving code reliability. One significant challenge in code reuse is the lack of documentation, which makes it difficult to understand the purpose and function of the code later on. Additionally, inconsistent coding styles and the use of vague variable names can further hinder code readability and maintenance. By encapsulating frequently used functions into packages, statisticians can not only enhance code organization but also streamline collaboration within teams.
Steps for Developing an R Package
Developing an R package should begin with careful planning rather than jumping straight into coding. A schematic pencil-and-paper outline can help clarify the package's structure, expected functions, and interactions between functionalities. Once the planning phase is complete, a prototype can be created using existing functions to validate the initial ideas. Subsequently, the actual coding for the package can be undertaken, which should include an organized structure for tests to ensure ongoing functionality as the code evolves.
Utilizing Community Resources for Package Development
Making an R package accessible to a broader audience often involves leveraging platforms like GitHub for sharing and collaboration. Engaging with social media, such as LinkedIn, is also a viable means for promoting the package to the community. Additionally, traditional methods like publishing in journals or presenting at conferences can enhance visibility and encourage user engagement. Resources such as the OpenStats Guide can provide valuable checklists and best practices for packaging development, making the process more efficient.
✔ Why creating R packages is a game-changer for code reuse and collaboration.
✔ The most common challenges we face when reusing code—and how packages help solve them.
✔ When it actually makes sense to start writing a package (spoiler: earlier than you think).
✔ Useful tools like usethis, testthat, and RStudio features that simplify the process.
✔ Daniel’s step-by-step approach—from sketching ideas on paper to launching the finished package.
✔ How to write meaningful tests to keep your code working as your project evolves.
✔ Where and how to share your package with others—GitHub, social media, conferences, and even journals.
✔ The fun side of the R community: hex stickers, open-source collaboration, and more.
✔ How Daniel’s team at Arconis can help if you want expert support with your package development.
Why You Should Listen
If you work in biostatistics, health economics, or market access, this episode is packed with practical insights to help you collaborate more effectively. Whether you're a statistician looking to better support HTA submissions or a market access professional trying to understand statistical challenges, you’ll walk away with actionable strategies that can make a real difference.
Join the Conversation: Did you find this episode helpful? Share it with your colleagues and let me know your thoughts! Connect with me on LinkedIn and be part of the discussion.
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