This book was written for statisticians, computer scientists, geographers, researchers, and others interested in visualizing data. It presents a unique foundation for producing almost every quantitative graphic found in scientific journals, newspapers, statistical packages, and data visualization systems. While the tangible results of this work have been several visualization software libraries, this book focuses on the deep structures involved in producing quantitative graphics from data. What are the rules that underlie the production of pie charts, bar charts, scatterplots, function plots, maps, mosaics, and radar charts? Those less interested in the theoretical and mathematical foundations can still get a sense of the richness and structure of the system by examining the numerous and often unique color graphics it can produce. The second edition is almost twice the size of the original, with six new chapters and substantial revision. Much of the added material makes this book suitable for survey courses in visualization and statistical graphics. "This fascinating book deconstructs the process of producing graphics and in doing so raises many fascinating questions on the nature and representation of information...This second edition is almost twice the size of the original, with six new chapters and substantial revisions." Short Book Reviews of the International Statistical Institute, December 2005 "When the first edidtion of this book appeared in 2000 it was much praised. I called it a tour de force of the highest order. (Wainer, 2001), Edward Wegman (2000) argued that it was destined to become a classic. Now, six years later this very fine book has been much improved." Howard Wainer for Psychometrika "...The second edition is an impressive expansion beyond a quite remarkable first edition. The text remains dense and even more encyclopedic, but it is a pleasure to read, whether a novice or an expert in graphics...this book is a bargain...The second edition is a must-have volume for anyone interested in graphics." Thomas E. Bradstreet for the Journal of the American Statistical Association, December 2006 "I find myself still thinking about the book and its ideas, several weeks after I finished reading it. I love that kind of book." Mark Bailey for Techometrics, Vol. 49, No. 1, February 2007 "Warts and all, The Grammar of Graphics is a richly rewarding work, an outstanding achievement by one of the leaders of statistical graphics. Seek it out." Nicholas J. Cox for the Journal of Statistical Software, January 2007

This book was written for statisticians, computer scientists, geographers, researchers, and others interested in visualizing data. It presents a unique foundation for producing almost every quantitative graphic found in scientific journals, newspapers, statistical packages, and data visualization systems. While the tangible results of this work have been several visualization software libraries, this book focuses on the deep structures involved in producing quantitative graphics from data. What are the rules that underlie the production of pie charts, bar charts, scatterplots, function plots, maps, mosaics, and radar charts? Those less interested in the theoretical and mathematical foundations can still get a sense of the richness and structure of the system by examining the numerous and often unique color graphics it can produce. The second edition is almost twice the size of the original, with six new chapters and substantial revision. Much of the added material makes this book suitable for survey courses in visualization and statistical graphics.

This fascinating book deconstructs the process of producing graphics and in doing so raises many fascinating questions on the nature and representation of information...This second edition is almost twice the size of the original, with six new chapters and substantial revisions. Short Book Reviews of the International Statistical Institute, December 2005

When the first edidtion of this book appeared in 2000 it was much praised. I called it a tour de force of the highest order. (Wainer, 2001), Edward Wegman (2000) argued that it was destined to become a classic. Now, six years later this very fine book has been muchimproved. Howard Wainer for Psychometrika

This book was written for statisticians, computer scientists, geographers, research and applied scientists, and others interested in visualizing data. It presents a unique foundation for producing almost every quantitative graphic found in scientific journals, newspapers, statistical packages, and data visualization systems. This foundation was designed for a distributed computing environment (Internet, Intranet, client-server), with special attention given to conserving computer code and system resources. While the tangible result of this work is a Java production graphics library (GPL) developed in collaboration with Dan Rope and Dan Carr, this book focuses on the deep structures involved in producing quantitative graphics from data. What are the rules that underly the production of pie charts, bar charts, scatterplots, function plots, maps, mosaics, radar charts? These rules are abstracted from the work of Bertin, Cleveland, Kosslyn, MacEachren, Pinker, Tufte, Tukey, Tobler, and other theorists of quantitative graphics. Those less interested in the theoretical and mathematical foundations can still get a sense of the richness and structure of the system by examining the numerous and often unique color graphics it can produce. Leland Wilkinson is Senior VP, SYSTAT Products at SPSS Inc. and Adjunct Professor of Statistics at Northwestern University. He wrote the SYSTAT statistical package and founded SYSTAT Inc. in 1984. Wilkinson joined SPSS in a 1994 acquisition and now works on research and development of graphical applications for data mining and statistics. He is a Fellow of the ASA and an Associate Editor of The American Statistician. In addition to journal articles and theoriginal SYSTAT computer program and manuals, Wilkinson is the author (with Grant Blank and Chris Gruber) of Desktop Data Analysis with SYSTAT.

Introduction.- How to Make a Pie.- Data.- Variables.- Algebra.- Scales.- Statistics.- Geometry.- Coordinates.- Aesthetics.- Facets.- Guides.- Space.- Time.- Uncertainty.- Analysis.- Control.- Automation.- Reader.- Coda.