R Packages, 2nd Edition

Chapter 5. The Package Within

This part of the book ends the same way it started, with the development of a small toy package. Chapter 1 established the basic mechanics, workflow, and tooling of package development, but it said practically nothing about the R code inside the package. This chapter focuses primarily on the package’s R code and how it differs from R code in a script.

Starting with a data analysis script, you learn how to find the package that lurks within. You’ll isolate and then extract reusable data and logic from the script, put this into an R package, and then use that package in a much simplified script. We’ve included a few rookie mistakes along the way, in order to highlight special considerations for the R code inside a package.

Note that the section headers incorporate the NATO phonetic alphabet (alfa, bravo, etc.) and have no specific meaning. They are just a convenient way to mark our progress toward a working package. It is fine to follow along just by reading, and this chapter is completely self-contained (i.e., it’s not a prerequisite for material later in the book). But if you wish to see the state of specific files along the way, they can be found in the source files for the book.

Alfa: A Script That Works

Let’s consider data-cleaning.R, a fictional data analysis script for a group that collects reports from people who went for a swim:

Where did you swim and how hot was it outside?

Their data usually comes as a CSV file, such as swim.csv:

name,where,temp ...