R Tutorial: Introduction to package building

Want to learn more? Take the full course at https://learn.datacamp.com/courses/developing-r-packages at your own pace. More than a video, you'll learn hands-on coding & quickly apply skills to your daily work. --- Hi, I'm Aimee Gott and I'm Nicola Crane. We are data science consultants at Mango Solutions and we will be your instructors for this introduction to package building course. Whether you want to share code across your business, with the rest of the R community or just want a structured way to develop code for yourself, R packages are a great way to do this. In this course we will show you how you can easily create your own R packages from the basics to writing documentation and even testing your code. R packages can contain a variety of objects such as functions and data. In addition they also contain help documentation which typically includes examples of how to use individual functions. They can also include vignettes, which are longer descriptions or user guides of how to work with the package and they can include tests for functions in the package, as well as much more. All of this is included in the package in a strictly defined structure. But, you don't have to include all of this. In fact, there are only 4 things that must be in a package. Firstly, the R directory, where you put all of your R code. Then there's the man directory where all of the documentation is stored. The NAMESPACE file contains information about functions that your package imports from other packages, and functions that your package makes available to its users. Finally, the DESCRIPTION file contains metadata about your package, like who wrote it, what it does, its current version, and what its dependencies are. Thankfully, we don't need to create all of this by hand. In this course we are going to use some packages designed specifically to make package building more accessible, starting with the devtools package, that will help us to ensure we stick to the right package