R Packages: Organize, Test, Document, and Share Your Code (Hadley Wickham)

 
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R Packages: Organize, Test, Document, and Share Your Code (Hadley Wickham)

Create simply downloadable packages from your R code for other people to use. This useful guide demonstrates how to use author Hadley Wickham's package-building methodology to group together reusable R functions, example data, and documentation.

You will use the R packages dev tools, roxygen, and test that to automate typical development activities throughout the process. Best practices that Hadley has picked up over the years of using this programming language are encapsulated in Devtools.

This book, which is ideal for developers, data scientists, and programmers with a variety of backgrounds, begins with the fundamentals and demonstrates how to develop your package authoring over time. You'll discover that thinking about package structure distracts you from what you want your package to do.

  • Learn about the most useful components of an R package, including vignettes and unit tests
  • Automate anything you can, taking advantage of the years of development experience embodied in dev tools
  • Get tips on good styles, such as organizing functions into files
  • Streamline your development process with dev tools
  • Learn the best way to submit your package to the Comprehensive R Archive Network (CRAN)
  • Learn from a well-respected member of the R community who created 30 R packages, including ggplot2, dplyr, and tidyr

This book's objective is to teach you how to create packages so that you can create your own instead of merely using others'.

Why create a package? You have code that you wish to share with others, which is a strong argument. Because they already understand how to utilize packages, other users will find it simple to use your code if you package it. Any R user can easily download, install, and learn how to use your code if it is contained in a package.

Ebook Details

About the Authors
Hadley Wickham is the R Foundation's Chief Scientist and the Chief Scientist of RStudio. He creates computational and cognitive technologies that make data science simpler, quicker, and more enjoyable. His work involves data ingest (reader, readxl, haven), data science (ggplot2, dplyr, tidyr), and principled software development (roxygen2, testthat, devtools). 
Published
Published Date / Year
1 edition (April 13, 2015)
Hardcover
202 pages
eBook Format
HTML
ISBN-10
1466586966
ISBN-13
978-1466586963

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