Robert Kabacoff - R in Action: Data Analysis and Graphics with R

For online information and ordering of this and other Manning books, please visit www.manning.com. The publisher offers discounts on this book when ordered in quantity. For more information, please contact

Special Sales DepartmentManning Publications Co.20 Baldwin RoadPO Box 761Shelter Island, NY 11964Email: orders@manning.com

2015 by Manning Publications Co. All rights reserved.

No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by means electronic, mechanical, photocopying, or otherwise, without prior written permission of the publisher.

Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in the book, and Manning Publications was aware of a trademark claim, the designations have been printed in initial caps or all caps.

Recognizing the importance of preserving what has been written, it is Mannings policy to have the books we publish printed on acid-free paper, and we exert our best efforts to that end. Recognizing also our responsibility to conserve the resources of our planet, Manning books are printed on paper that is at least 15 percent recycled and processed without elemental chlorine.

Manning Publications Co.20 Baldwin RoadPO Box 761Shelter Island, NY 11964

Development editor: Jennifer StoutCopyeditor: Tiffany TaylorProofreader: Toma MulliganTypesetter: Marija TudorCover designer: Marija Tudor

ISBN: 9781617291388

Printed in the United States of America

1 2 3 4 5 6 7 8 9 10 EBM 20 19 18 17 16 15

Lucid and engagingthis is without doubt the fun way to learn R!

Amos A. Folarin, University College London

Be prepared to quickly raise the bar with the sheer quality that R can produce.

Patrick Breen, Rogers Communications Inc.

An excellent introduction and reference on R from the author of the best R website.

Christopher Williams, University of Idaho

Thorough and readable. A great R companion for the student or researcher.

Samuel McQuillin, University of South Carolina

Finally, a comprehensive introduction to R for programmers.

Philipp K. Janert, Author of Gnuplot in Action

Essential reading for anybody moving to R for the first time.

Charles Malpas, University of Melbourne

One of the quickest routes to R proficiency. You can buy the book on Friday and have a working program by Monday.

Elizabeth Ostrowski, Baylor College of Medicine

One usually buys a book to solve the problems they know they have. This book solves problems you didnt know you had.

Carles Fenollosa, Barcelona Supercomputing Center

Clear, precise, and comes with a lot of explanations and examples...the book can be used by beginners and professionals alike, and even for teaching R!

Atef Ouni, Tunisian National Institute of Statistics

A great balance of targeted tutorials and in-depth examples.

Landon Cox, 360VL Inc.

What is the use of a book, without pictures or conversations?

Alice, Alices Adventures in Wonderland

Its wondrous, with treasures to satiate desires both subtle and gross; but its not for the timid.

Q, Q Who? Stark Trek: The Next Generation

When I began writing this book, I spent quite a bit of time searching for a good quote to start things off. I ended up with two. R is a wonderfully flexible platform and language for exploring, visualizing, and understanding data. I chose the quote from Alices Adventures in Wonderland to capture the flavor of statistical analysis todayan interactive process of exploration, visualization, and interpretation.

The second quote reflects the generally held notion that R is difficult to learn. What I hope to show you is that is doesnt have to be. R is broad and powerful, with so many analytic and graphic functions available (more than 50,000 at last count) that it easily intimidates both novice and experienced users alike. But there is rhyme and reason to the apparent madness. With guidelines and instructions, you can navigate the tremendous resources available, selecting the tools you need to accomplish your work with style, elegance, efficiencyand more than a little coolness.

I first encountered R several years ago, when applying for a new statistical consulting position. The prospective employer asked in the pre-interview material if I was conversant in R. Following the standard advice of recruiters, I immediately said yes, and set off to learn it. I was an experienced statistician and researcher, had 25 years experience as an SAS and SPSS programmer, and was fluent in a half dozen programming languages. How hard could it be? Famous last words.

As I tried to learn the language (as fast as possible, with an interview looming), I found either tomes on the underlying structure of the language or dense treatises on specific advanced statistical methods, written by and for subject-matter experts. The online help was written in a spartan style that was more reference than tutorial. Every time I thought I had a handle on the overall organization and capabilities of R, I found something new that made me feel ignorant and small.

To make sense of it all, I approached R as a data scientist. I thought about what it takes to successfully process, analyze, and understand data, including

• Accessing the data (getting the data into the application from multiple sources)
• Cleaning the data (coding missing data, fixing or deleting miscoded data, transforming variables into more useful formats)
• Annotating the data (in order to remember what each piece represents)
• Summarizing the data (getting descriptive statistics to help characterize the data)
• Visualizing the data (because a picture really is worth a thousand words)
• Modeling the data (uncovering relationships and testing hypotheses)
• Preparing the results (creating publication-quality tables and graphs)

Then I tried to understand how I could use R to accomplish each of these tasks. Because I learn best by teaching, I eventually created a website (www.statmethods.net) to document what I had learned.

Then, about a year later, Marjan Bace, Mannings publisher, called and asked if I would like to write a book on R. I had already written 50 journal articles, 4 technical manuals, numerous book chapters, and a book on research methodology, so how hard could it be? At the risk of sounding repetitivefamous last words.

A year after the first edition came out in 2011, I started working on the second edition. The R platform is evolving, and I wanted to describe these new developments. I also wanted to expand the coverage of predictive analytics and data miningimportant topics in the world of big data. Finally, I wanted to add chapters on advanced data visualization, software development, and dynamic report writing.

The book youre holding is the one that I wished I had so many years ago. I have tried to provide you with a guide to R that will allow you to quickly access the power of this great open source endeavor, without all the frustration and angst. I hope you enjoy it.