R Markdown: The Definitive Guide is the first official book authored by the core R Markdown developers that provides a comprehensive and accurate reference to the R Markdown ecosystem. With R Markdown, you can easily create reproducible data analysis reports, presentations, dashboards, interactive applications, books, dissertations, websites, and journal articles, while enjoying the simplicity of Markdown and the great power of R and other languages.
In this book, you will learn
Basics: Syntax of Markdown and R code chunks, how to generate figures and tables, and how to use other computing languages
Built-in output formats of R Markdown: PDF/HTML/Word/RTF/Markdown documents and ioslides/Slidy/Beamer/PowerPoint presentations
Extensions and applications: Dashboards, Tufte handouts, xaringan/reveal.js presentations, websites, books, journal articles, and interactive tutorials
Advanced topics: Parameterized reports, HTML widgets, document templates, custom output formats, and Shiny documents.
Yihui Xie is a software engineer at RStudio. He has authored and co-authored several R packages, including knitr, rmarkdown, bookdown, blogdown, shiny, xaringan, and animation. He has published three other books, Dynamic Documents with R and knitr, bookdown: Authoring Books and Technical Documents with R Markdown, and blogdown: Creating Websites with R Markdown.
J.J. Allaire is the founder of RStudio and the creator of the RStudio IDE. He is an author of several packages in the R Markdown ecosystem including rmarkdown, flexdashboard, learnr, and radix.
Garrett Grolemund is the co-author of R for Data Science and author of Hands-On Programming with R. He wrote the lubridate R package and works for RStudio as an advocate who trains engineers to do data science with R and the Tidyverse. "The manuscript offers a detailed documentation of the R Markdown document format and its related packages for R (e.g. knitr, rmarkdown, flexdashboard, shiny). These packages form an important ecosystem for reproducible research using R and are widely used across academia and the private sector. All the authors have been key contributors to developing the core R Markdown packages and are knowledgable about the inner workings of these functions and all the available options to customize published documents...The target audience for this manuscript would be experienced R users who frequently use R Markdown to generate publications for a variety of mediums (articles, books, information dashboards, interactive web applications, etc.)...While this book is strongly related to the author's previous book (Dynamic Documents with R and knitr), a wider range of readers should find this new manuscript useful for its focus on the broad range of output formats generated by R Markdown and how to customize those outputs." ~Benjamin Soltoff, Department of Computational Social Science, University of Chicago
"A main strength of the software described herein is that it facilitates reproducible documents incorporating analyses and figures. The first topics covered in chapters 6-13 include handout and presentation formats that could be used effectively for teaching or presenting statistical results. The other topics focus on larger scale documents such as complex websites, books, and academic journal articles. From academic teaching and research to industry and other settings, the material covered by this book allows statisticians and data scientists to disseminate results in a highly effective manner." ~David Whitney, Department of Biostatistics, University of Washington
"This book will be a valuable reference for students, academics, and professionals using R - that is to say, any one in a wide (and growing) variety of fields focused on practical data analysis including statistics, machine learning, the social sciences, etc. There is increasing awareness that nearly any occasion calling for analysis code also calls for some amount of corresponding documentation, explanation, and/or interpretation. Rapid improvement in tools for R markdown has made integrating code and text less and less of a chore, and therefore more and more common - even among users new to R. R markdown is a popular choice now for a range of formats including blog posts, user manuals, books, dissertations, and undergraduate homework assignments. I personally use R markdown for nearly all of my website content, presentations, research papers, and to generate reports for the clients of my statistical consulting business. Because of its many applications, however, the ecosystem of R markdown tools has become unwieldy, and many tutorials reference outdated techniques or unnecessary workarounds. A definitive guide has been long needed." ~Rose Hartman, UnderstandingData
"This book is so far the most comprehensive reference for the R Markdown format and its associated extensions and tools. On a high level, Part I and II (Chapter 1-4) of this book cover the basic use of the R Markdown document and the knitr and rmarkdown packages, which are helpful for new users to quickly get started. Part III (Chapter 5-13) introduces a lot of new developments and powerful tools for R Markdown, including creating presentations, authoring books, building websites, writing journal articles, etc. In my personal point of view this is the most attractive part of this book, as it opens a new world for users who have only used R Markdown to create ordinary documents." ~Yixuan Qui, Department of Statistics, Purdue University
"This book represents a valuable contribution to the target field due to its exploration of a wide range of features in the markdown language. If other books on this topic exist, this one has the advantage that the authors have already made significant contributions to the markdown language in the R platform and certainly have a comprehensive understanding of the topic...I recommend this book for publication because the topic is sophisticated and complex, and the interested audience will certainly be satisfied with the clarity of presentation and the depth that the authors reach in their exploratory examples" ~Jon Katz, data analyst
R Markdown: The Definitive Guide
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