Paul Teetor

I picked up this book with the intention of learning intermediate R. I was past the novice stage of learning the language, but I was still short of learning Advanced R. This book gave me the confidence to read R code more quickly and to understand more nuance in this (fun) language.

This book is written by a quant (Wall Street data analyst) who has Masters degrees in both statistics and computer science. I find his statistics section interesting and most helpful. His visualization section is show more dated as it should use ggplot instead of R's native plotting techniques.

He analyzes several helpful methods; figuring out those methods constitutes the learning part of the book. The short script (this is a computer cookbook after all) were helpful to extend my knowledge and agility with the language.

The statistics section consists of a plethora of helpful analytical techniques to get what you want out of R. The information in this section is unique to me and as such new/useful. It tells me what techniques to use for certain types of data (e.g., normal vs. non-normal). Short of a statistics textbook, that's all you can ask for from a computer script cookbook.

So this book served its purpose well. I would not classify it as essential R reading, however. There are other texts which are more important. Some of the scripts are obvious, but this book provided good reading while I was eating lunch for a couple of weeks. show less

I agree that this is not a book for the beginners, but nevertheless it started with the very basics. I was impressed about it though it is from a Cookbook series.

The approach in the book is: if this is your problem, here's the solution, followed by a discussion which provides great amount of detail about the concept or function. This format allows the book to be used as a reference guide as well as it will assist us to jump to a point directly. The book illustrates plenty of functions of R show more in this fashion.

There are parts of the book that educate us about Statistics itself, but prior knowledge of some Statistics is a must if you want to make the best of this book.

The author shows examples from a variety of libraries - MASS, Cars93, zoo, XML to name a few. Enthusiastic readers will explore the data sets in these libraries and become more hands-on. The chapter on Useful Tricks exposed many of the "helper" functions. These add to the convenience while working with R.

The code samples for the book seemed incomplete when I downloaded them. But this worked for my benefit in the sense that I spent more time actually writing the code or creating the data myself - helped me get a little more comfortable around it's syntax. Blessing in disguise I guess. show less

Imprescindible reference for anyone using R. Is true that you can find all this information in internet, and specifically in http://stackoverflow.com/, but here is full of useful recipes to usual problems.