Dynamic Documents with R and knitr

Dynamic Documents with R and knitr

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ISBN 9781482203530
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  • Makes it easier to write reports
  • Illustrates the extensibility of the popular knitr package, which was created by the author for doing reproducible research
  • Presents good and bad research practices
  • Offers the option of using R, Python, LaTeX, Markdown, and other programs and languages


The cut-and-paste approach to writing statistical reports is not only tedious and laborious, but also can be harmful to scientific research, because it is inconvenient to reproduce the results. Dynamic Documents with R and knitr introduces a new approach via dynamic documents, i.e. integrating computing directly with reporting. A comprehensive guide to the R package knitr, the book covers examples, document editors, basic usage, detailed explanations of a wide range of options, tricks and solutions, extensions, and complete applications of this package.

The book provides an overview of dynamic documents, introducing the idea of literate programming. It then explains the importance of dynamic documents to scientific research and its impact on reproducible research. Building on this, the author covers basic concepts, common text editors that support knitr, and the syntax for different document formats such as LaTeX, HTML, and Markdown before going on to discuss core functionality, how to control text and graphics output, caching mechanisms that can reduce computation time, and reuse of source code. He then explores advanced topics such as chunk hooks, integrating other languages such as Python and awk into one report in the knitr framework, and useful tricks that make it easier to write documents with knitr. Discussions of how to publish reports in a variety of formats, applications, and other tools complete the coverage.

Suitable for both beginners and advanced users, this book shows you how to write reports in simple languages such as Markdown. The reports range from homework, projects, exams, books, blogs, and web pages to any documents related to statistical graphics, computing, and data analysis. While familiarity with LaTeX and HTML is helpful, the book requires no prior experience with advanced programs or languages. For beginners, the text provides enough features to get started on basic applications. For power users, the last several chapters enable an understanding of the extensibility of the knitr package.

Table of Contents


Reproducible Research
Good and Bad Practices

A First Look
Minimal Examples
Quick Reporting
Extracting R Code

Other Editors

Document Formats
Input Syntax
Document Formats
Output Renderers
R Scripts

Text Output
Inline Output
Chunk Output

Graphical Devices
Plot Recording
Plot Rearrangement
Plot Size in Output
Extra Output Options
The tikz Device
Figure Environment
Figure Path

Write Cache
When to Update Cache
Side Effects
Chunk Dependencies

Cross Reference 79
Chunk Reference
Code Externalization
Child Documents

Chunk Hooks

Language Engines
Languages and Tools

Tricks and Solutions
Chunk Options
Package Options
Multilingual Support

Publishing Reports
HTML5 Slides

Web Site and Blogging
Package Vignettes

Other Tools
Other R Packages
Python Packages
More Tools

A.4 Syntax

Author Bio(s)

Editorial Reviews

"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

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