Handbook of Data Visualization

1. Front Matter

   Pages I-XIII

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2. Data Visualization

   1. Front Matter

      Pages 1-1

      PDF

   2. Introduction

      • Antony Unwin, Chun-houh Chen, Wolfgang Härdle

      Pages 3-12

3. Principles

   1. Front Matter

      Pages 13-13

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   2. A Brief History of Data Visualization

      • Michael Friendly

      Pages 15-56

   3. Good Graphics?

      • Antony Unwin

      Pages 57-78

   4. Static Graphics

      • Paul Murrell

      Pages 79-101

   5. Data Visualization Through Their Graph Representations

      • George Michailidis

      Pages 103-120

   6. Graph-theoretic Graphics

      • Lelend Wilkinson

      Pages 121-150

   7. High-dimensional Data Visualization

      • Martin Theus

      Pages 151-178

   8. Multivariate Data Glyphs: Principles and Practice

      • Matthew O. Ward

      Pages 179-198

   9. Linked Views for Visual Exploration

      • Adalbert Wilhelm

      Pages 199-215

   10. Linked Data Views

       • Graham Wills

       Pages 217-241

   11. Visualizing Trees and Forests

       • Simon Urbanek

       Pages 243-264

4. Methodologies

   1. Front Matter

      Pages 265-265

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   2. Interactive Linked Micromap Plots for the Display of Geographically Referenced Statistical Data

      • Jürgen Symanzik, Daniel B. Carr

      Pages 267-294

   3. Grand Tours, Projection Pursuit Guided Tours, and Manual Controls

      • Dianne Cook, Andreas Buja, Eun-Kyung Lee, Hadley Wickham

      Pages 295-314

   4. Multidimensional Scaling

      • Michael A. A. Cox, Trevor F. Cox

      Pages 315-347

   5. Huge Multidimensional Data Visualization: Back to the Virtue of Principal Coordinates and Dendrograms in the New Computer Age

      • Francesco Palumbo, Domenico Vistocco, Alain Morineau

      Pages 349-387

   6. Multivariate Visualization by Density Estimation

      • Michael C. Minnotte, Stephan R. Sain, DavidW. Scott

      Pages 389-413

Antony Unwin, Chun-houh Chen, Wolfgang K. Härdle 1. 1 Computational Statistics and Data Visualization . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Data Visualization and Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Presentation and Exploratory Graphics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Graphics and Computing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1. 2 The Chapters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Summary and Overview; Part II. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Summary and Overview; Part III. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Summary and Overview; Part IV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 The Authors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 1. 3 Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 4 Antony Unwin, Chun-houh Chen, Wolfgang K. Härdle Computational Statistics 1. 1 and DataVisualization Tis book is the third volume of the Handbook of Computational Statistics and c- ers the ?eld of data visualization. In line with the companion volumes, it contains a collection of chapters by experts in the ?eld to present readers with an up-to-date and comprehensive overview of the state of the art. Data visualization is an active area of application and research, and this is a good time to gather together a summary of current knowledge. Graphic displays are ofen very e?ective at communicating information. Tey are also very ofen not e?ective at communicating information. Two important reasons for this state of a?airs are that graphics can be produced with a few clicks of the mouse without any thought and the design of graphics is not taken seriously in many scienti?c textbooks.

• Analysis
• Cluster analysis
• Fitting
• Java
• Projection pursuit
• XML
• best fit
• computer
• data analysis
• multidimensional scaling
• statistics
• visualization

From the reviews:

"This handbook shows hundreds of ways to visualize data by using modern, high-quality statistical graphics. … It is most enjoyable to see such a large number of specialists sharing their insights of these methods within one volume. This book really feeds the imagination of the reader. High-dimensionally recommended!" (Kimmo Vehkalahti, International Statistical Review, Vol. 76 (3), 2008)

• Academia Sinica, Institute of Statistical Science, Taipei, Taiwan, Province of China

  Chun-houh Chen

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