Hadley Wickham

R Packages (eBook, PDF)

• Format: PDF

Produktbeschreibung

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 Wickhams package development philosophy. In the process, youll 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. Youll 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 testsAutomate anything you can, taking advantage of the years of development experience embodied in devtoolsGet tips on good style, such as organizing functions into filesStreamline your development process with devtoolsLearn 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

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: O'Reilly Media
• Seitenzahl: 202
• Erscheinungstermin: 26. März 2015
• Englisch
• ISBN-13: 9781491910566
• Artikelnr.: 42554951

Autorenporträt

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.