Efficient R Programming

Preface

Efficient R Programming is about increasing the amount of work you can do with R in a given amount of time. It’s about both computational and programmer efficiency. There are many excellent R resources about topics such as visualization (e.g., Chang 2012), data science (e.g., Grolemund and Wickham 2016), and package development (e.g., Wickham 2015). There are even more resources on how to use R in particular domains, including Bayesian statistics, machine learning, and geographic information systems. However, there are very few unified resources on how to simply make R work effectively. Hints, tips, and decades of community knowledge on the subject are scattered across hundreds of internet pages, email threads, and discussion forums, making it challenging for R users to understand how to write efficient code.

In our teaching we have found that this issue applies to beginners and experienced users alike. Whether it’s a question of understanding how to use R’s vector objects to avoid for loops, knowing how to set up your .Rprofile and .Renviron files, or the ability to harness R’s excellent C++ interface to do the heavy lifting, the concept of efficiency is key. The book aims to distill tips, warnings, and tricks of the trade into a single, cohesive whole that provides a useful resource to R programmers of all stripes for years to come.

The content of the book reflects the questions that our students from a range of disciplines, skill levels, and industries have asked over ...