The way experts got that way is by actually building things, often very basic things, and you deserve the same chance to learn by tinkering. But there are plenty of good reasons to make your own package, even if there is relevant prior work. If you are looking for ways to increase your R mastery, you should still educate yourself about the landscape. Silge, Nash, and Graves organized a survey and sessions around this at useR! 2017 and their write up for the R Journal ( Silge, Nash, and Graves 2018) provides a comprehensive roundup of resources. If all you care about is the existence of a product, then your main goal is to navigate the space of existing packages.

Process: greater mastery of R will make you more effective in your work.

Product: your life will be better when this functionality is implemented formally, in a package.

How should you decide whether something is package-worthy? There’s no definitive answer, but it’s helpful to appreciate at least two types of payoff: Many packages are born out of one person’s frustration at some common task that should be easier.

5.1 Create a package 5.1.1 Survey the existing landscape Having peeked under the hood of R packages and libraries in Chapter 4, here we provide the basic workflows for creating a package and moving it through the different states that come up during development.

Creating an r package