Dynamic Documents With R and Knitr (Chapman & Hall/CRC The R Series)

I think that its safe to say that many of us who use Knitr are grateful for the work that Yihui Xie (the author) and others have done to make Knitr available to the R community. Knitr is a very important resource for creating and publishing reproducible research. Which makes this review a challenge since I want to thank the author for his work, but I'm not that wild about the book.I have been using Knitr for several months, on two projects, one in finance (models for predicting portfolio return using value factors) and one in machine learning. I find that when I work on a large analysis code it is easy to get lost in the code and forget what the pieces do. By including the LaTex text along with the R code I not only get reproducible research, but I get code that is easier to follow (although the mix of LaTex and R has its own problems).The result is also very attractive. The PDF documents that can be produced with Knitr are much more attractive than documents created with Open Office or Word.Dynamic Documents with R and Knitr has some good introductory chapters that help you get started. There are a few good guides to creating Knitr documents. If this short book were not $56.95 and if the author got to keep a significant fraction of the money, I would be happier with the book. But it is a short book that is very expensive and my suspicion is that the author only gets a tiny fraction of the cost of the book.What would have been more useful is a book that included the introductory chapters and then had more Knitr cookbook recipes. There are a some useful pointers but I am constantly looking on-line rather than in the book to answer questions about "how do I do X with Knitr and LaTex". Any significant Knitr paper will have been the result of many searches for material that can't be found in the book.

Yihui Xie has done a great service for those of us interested in producing reproducible analyses. This book shows how to create attractive documents that include "code chunks" that produce the figures and statistical analyses using the Open Source statistical/data analysis language "R" and the "knitr" package (also Open Source) that he wrote.This approach was pioneered by Donald Knuth of Stanford. Knitr is extremely powerful, able to generate documents in HTML ready for the web or as PDF ready for a client (or to turn in for a class assignment). The document source files (R markdown .Rmd files or LaTeX/Sweave .Rnw files) can be given to a coworker or friend to let them "see the math." It is also a great way to avoid the embarrassment that comes with the errors that so easily creep in when using software like Excel and revisions are much less painful (no point/click/copy/paste or worry that you are using the wrong version of a file.Happily, the publisher has finally released a Kindle edition. This is especially important for software books where revisions limit the useful life. I found the book to be helpful. Even though much of the information is available online, I also purchased the book to support the author for the work he has done building a quality product that he released Open Source and supports with what appears to be tireless energy. Disclaimer: I have no financial interest in this. I am simply a happy user of knitr and R with the Open Source R-Studio IDE and think this is a good way to support the authors of the tools I use.

Good HOWTO, clunky writing -- nothing much more to say. The author's web site lacks examples, and it's obvious that he put all his effort in setting the examples for the book.If you are using R for creating dashboards, scientific papers, or Big Data reports, this book is a great investment. It assumes you're a rather technical person, and have enough experience in R. Its reliance on Emacs as the programmers editor of choice was also a turn off. A more rounded book would've either left the editor's choice to the developer, or would've covered Vim and a modern editor (TextMate, Sublime Text) in more depth, since the examples do rely on heavy automation.knitr is a great way of producing beautiful documents without resorting to LaTeX for the graphs and other elements at which R programming excels.This review was for a rental version of the book (via Kindle).Cheers!

I've read through the first couple of chapters and Xie's writing is excellent and the examples are simple and clear. I think this book will be very helpful as I build my workflow for my masters thesis.However, the print quality of my copy of the book is very poor. It looks like something printed on a laser printer in "toner saver" mode and with dead spots on the drum (leaving streaks through parts of the text). Code samples are difficult to read because the text is light colored on streaky gray backgrounds. This is definitely not the quality I expect in a $60 book.In contrast my copy of "Analyzing Baseball Data with R" has very high quality printing, with crisp figures and code samples that are much easier to read. It's as if C&H decided to go cheap on printing this book. I saw the same problem with "Reproducible Research" by Christopher Gandrud, and his comment in his review section provided information to contact the publisher for a replacement. I hope that will work for this book too.

knitr comes packaged with RStudio but is also part of LyX and other editors.knitr allows you to incorporate R, Python and other live code snippets in a document. I use LaTeX and I find that the combination is a huge step up from the prior world of cut and paste. Of course MATLAB isn't part of the system, being a closed commercial system, but I compensate by using the {listings} package and pulling in pdf versions of graphs.knitr is an indispensible tool and this book is a very helpful guide to its use.

Nice and concise, though I would have liked a bit more detail and examples when it came to hooks.

In spite of this Book being specific for the use of the R package knitr; it has the big advantage of working as well as a gentle introduction to R.Knitr package aims is to make it easier for the user to document his work. This consists to create a unique record to contain the product of an analysis and how was done at same time. On top of it, this principle would be the stepping stone to create dynamic reports: reports which required to be done monthly for example (because more or different data is available in a time frame fashion), and/or reports for several units which presents similar data (e.g. schools, branches, cities, airlines, etc).Is very practical and clear for a novice user. I recommend this book with no doubt.

I accidentally bought the kindle version and I am wishing I had the book. The subject matter is good though much of it is available online electronically in various places, which is why I am regretting having an electronic rather than a physical copy. I also haven't found a kindle reader platform I get on with yet.