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Defensive R Programming

via Datacamp


Learn defensive programming in R to make your code more robust.

Writing R scripts is easy. Writing good R code is hard. In this course, we'll discuss defensive programming - a set of standard techniques that will help reduce bugs and aid working in teams. We examine techniques for avoiding common errors and also how to handle the inevitable error that arises in our code. The course will conclude looking at when to make the transition from script to project to package.


Avoiding Conflict
-In this first chapter, you'll learn what defensive programming is, and how to use existing packages for increased efficiency. You will then learn to manage the packages loaded in your environment and the potential conflicts that may arise.

Early warning systems
-Programming is simpler when you get feedback on your code execution. In R, we use messages, warnings and errors to signal to keep the user informed. This chapter will discuss when and where you should use these communication tools.

Preparing your defenses
-We can avoid making mistakes using a consistent programming approach. In this chapter, we will introduce you to R best practices.

Creating a Battle Plan
-Creating a script is nice, but working on a project with several scripts and assets requires structure. This final chapter will teach you good organization practices, so you can go from script to package with an optimal workflow.

Taught by

Colin Gillespie

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