R Packages, 2/e

R Packages, 2/eTurn your R code into packages that others can easily install and use. With this fully updated edition, developers and data scientists will learn how to bundle reusable R functions, sample data, and documentation together applying the package development philosophy used the team that maintains the "tidyverse" suite of packages. In the process, you'll learn how to automate common development tasks using a set of R packages, including devtools, use

Turn your R code into packages that others can easily install and use. With this fully updated edition, developers and data scientists will learn how to bundle reusable R functions, sample data, and documentation together applying the package development philosophy used the team that maintains the "tidyverse" suite of packages. In the process, you'll learn how to automate common development tasks using a set of R packages, including devtools, use this, test that, and roxygen2.Authors Hadley Wickham and Jennifer Bryan from Posit (formerly known as RStudio) help you create packages quickly, then teach you how to get better over time. You'll be able to focus on what you want your package to do as you progressively develop greater mastery of the structure of a package.With this book, you will: Learn the key components of an R package, including code, documentation, and tests Streamline your development process with devtools and the RStudio IDE Get tips on effective habits such as organizing functions into files Get caught up on important new features in the devtools ecosystem Learn about the art and science of unit testing, using features in the third edition of test that Turn your existing documentation into a beautiful and user friendly website with pkgdown Gain an appreciation of the benefits of modern code hosting platforms, such as GitHub About the AuthorHadley Wickham is Chief Scientist at RStudio and a member of the R Foundation. He builds tools (both computational and cognitive) that make data science easier, faster, and more fun. His work includes packages for data science (ggplot2, dplyr, tidyr), data ingest (readr, readxl, haven), and principled software development (roxygen2, testthat, devtools). He is also a writer, educator, and frequent speaker promoting the use of R for data science. Jennifer Bryan is a Software Engineer at RStudio and a member of the R Foundation. She part of the tidyverse team that collectively maintains >150 R packages. Jennifer maintains packages for importing tabular data (readxl, googlesheets4, readr, vroom), working with Google APIs (googledrive, gargle, gmailr), and simplifying development workflows (reprex, usethis, devtools). In her first career, Jennifer was an Associate Professor of Statistics at the University of British Columbia, where she created courses and programs in what we now know as data science.