R Packages: Organize, Test, Document, and Share Your Code
Language: English
Published by O'Reilly Media, 2015
- Softcover
- Used
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- Title
- R Packages: Organize, Test, Document, and Share Your Code
- Author
- Wickham, Hadley
- Publisher
- O'Reilly Media
- Publication year
- 2015
- Condition
- Good
- Dust jacket
- No Jacket
- Binding
- Paperback
- Language
- English
- ISBN 10
- 1491910593
- ISBN 13
- 9781491910597
- Item weight
- 0.8 pounds
Turn your R code into packages that others can easily download and use. This practical book shows you how to bundle reusable R functions, sample data, and documentation together by applying author Hadley Wickham’s package development philosophy. In the process, you’ll work with devtools, roxygen, and testthat, a set of R packages that automate common development tasks. Devtools encapsulates best practices that Hadley has learned from years of working with this programming language.
Ideal for developers, data scientists, and programmers with various backgrounds, this book starts you with the basics and shows you how to improve your package writing over time. You’ll learn to focus on what you want your package to do, rather than think about package structure.
- 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 devtools
- Get tips on good style, such as organizing functions into files
- Streamline your development process with devtools
- 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
"Synopsis" may belong to another edition of this title.
About the Author
Hadley Wickham is an Assistant Professor and the Dobelman FamilyJunior Chair in Statistics at Rice University. He is an active memberof the R community, has written and contributed to over 30 R packages, and won the John Chambers Award for Statistical Computing for his work developing tools for data reshaping and visualization. His research focuses on how to make data analysis better, faster and easier, with a particular emphasis on the use of visualization to better understand data and models.
"About the title" may belong to another edition of this title.
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