Dynamic Documents with R and knitr

Yihui Xie is currently a software engineer at RStudio. He got his PhD from the Department of Statistics, Iowa State University. He is interested in interactive statistical graphics, statistical computing, and web applications. He is an active R user and the author of several R packages, such as animation, formatR, Rd2roxygen, and knitr, among which the animation package won the 2009 John M. Chambers Statistical Software Award (ASA). He is also the author of the book "Dynamic Documents with R and knitr". In 2006 he founded the "Capital of Statistics", which has grown into a large online community on statistics in China. He initiated the first Chinese R conference in 2008 and has been organizing R conferences in China since then. During his PhD training at the Iowa State University, he won the Vince Sposito.

• Introduction. Reproducible Research. A First Look. Editors. Document Formats. Text Output. Graphics. Cache. Cross Reference. Hooks. Language Engines. Tricks and Solutions. Publishing Reports. R Markdown. Applications. Other Tools. Appendix. Bibliography. Index.

"… a gold mine of ideas: things I had no idea knitr could do (integrate with different languages like Python), and tricks to get around some of the awkward things I needed to do (moving all the code to an appendix for tech-fearful readers). It also explains all the guts of the system and is especially informative about how knitr can cache results of time-intensive calculations, so that they do not have to be rerun each time you compile the document if the precedents have not changed. The book is well written …"—MAA Reviews, December 2015Praise for the First Edition:"After reading Dynamic Documents with R and knitr, … I became a fan of this package and its flexibility. The book is written in a conversational style that gives a clear and practical introduction to knitr for both beginners and advanced users. … Compared with Sweave, knitr is more powerful. … Furthermore, knitr is more flexible than Sweave. … Most impressively, caching can be incorporated in a simple way by knitr. … The book is readable with a clear overall structure. … this book allows us to enhance our knowledge of knitr’s usage and quickly find what we want."—The American Statistician, February 2015"The book provides a systematic description of the package [knitr], including its concepts, design principles, and philosophy. It also has many examples, well-thought-out advice, and useful tips and tricks. … The book is well written. It has introductory material useful for novices as well as advice for more seasoned users, all explained in conversational English without unnecessary technical jargon. … While I have been using Sweave and then knitr for several years, I still learned many new useful things from the book. … the book deserves a place on the bookshelves of both new and experienced R and TeX users."—Boris Veytsman, TUGboat, Volume 35, 2014"If you are looking to learn how to use knitr, this book is for you. There are a limited number of resources for learning knitr because the package is relatively new and the documentation produced by Xie is so good. … I think this book will continue to be the best resource about knitr …easy to understand … this is a great read and handy desk reference for the regular knitr user."—Journal of Statistical Software, January 2014"Three recent books have significantly influenced how I use R in reproducible work: Dynamic Documents with R and knitr by Yihui Xie, Reproducible Research with R and RStudio by Christopher Gandrud, and Implementing Reproducible Research edited by Victoria Stodden, Friedrich Leisch, and Roger D. Peng … I recommend all three books to R users at any level. There really is something here for everyone."—Richard Layton, PhD, PE, Rose-Hulman Institute of Technology, Terre Haute, Indiana, USA