Hadley is Chief Scientist at RStudio, an Adjunct Professor of Statistics at the University of Auckland, and author of many popular R packages including ggplot2, dplyr, and tidyr, among others. His passion is building tools (both computational and cognitive) that make data science easier, faster, and more fun. Hadley recently co-authored a book with Garrett Grolemund called R for Data Science.
Charlotte is an Assistant Professor in the Department of Statistics at Oregon State University and an avid R programmer with a passion for teaching. Her interests lie in spatiotemporal data, statistical graphics and computing, and environmental statistics.
Functions are a fundamental building block of the R language. You've probably used dozens (or even hundreds) of functions written by others, but in order to take your R game to the next level, you'll need to learn to write your own functions. This course will teach you the fundamentals of writing functions in R so that, among other things, you can make your code more readable, avoid coding errors, and automate repetitive tasks.
Before we embark, we'll make sure you’re ready for this course by reviewing some of the prerequisites. You'll review the syntax of writing a function in R, the basic data types in R, subsetting and writing for loops. It won't all be review, we'll introduce you to a few new things that will be helpful throughout the course.
Writing your own functions is one way to reduce duplication in your code. In this chapter, you'll learn when to write a function, how to get started and what to keep in mind when you are writing. You'll also learn to appreciate that functions have two audiences: the computer (which runs the code) and humans (who need to be able to understand the code).
You already know how to use a for loop. The goal of this chapter is to teach you how to use the map functions in the purrr package which remove the code that's duplicated across multiple for loops. After completing this chapter you'll be able to solve new iteration problems with greater ease (faster and with fewer bugs).
Now you've seen how useful the map functions are for reducing duplication, we'll introduce you to a few more functions in purrr that allow you to handle more complicated inputs and outputs. In particular, you'll learn how to deal with functions that might return an error, how to iterate over multiple arguments and how to iterate over functions that have no output at all.
In this chapter we'll focus on writing functions that don't surprise you or your users. We'll expose you to some functions that work 95% of the time, and 5% of the time fail in surprising ways. You'll learn which functions you should avoid using inside a function and which you should use with care.