¡°Finally! A data visualization guide that is simultaneously practical and elegant. Healy combines the beauty and insight of Tufte with the concrete helpfulness of Stack Exchange. Data Visualization is brimming with insights into how quantitative analysts can use visualization as a tool for understanding and communication. A must-read for anyone who works with data.¡±¡ªElizabeth Bruch, University of Michigan
¡°Healy¡¯s fun and readable book is unusual in covering the ¡®why do¡¯ as well as the ¡®how to¡¯ of data visualization, demonstrating how dataviz is a key step in all stages of social science¡ªfrom theory construction to measurement to modeling and interpretation of analyses¡ªand giving readers the tools to integrate visualization into their own work.¡±¡ªAndrew Gelman, author of Red State, Blue State, Rich State, Poor State: Why Americans Vote the Way They Do
¡°Data Visualization is a brilliant book that not only teaches the reader how to visualize data but also carefully considers why data visualization is essential for good social science. The book is broadly relevant, beautifully rendered, and engagingly written. It is easily accessible for students at any level and will be an incredible teaching resource for courses on research methods, statistics, and data visualization. It is packed full of clear-headed and sage insights.¡±¡ªBecky Pettit, University of Texas at Austin
¡°Healy provides a unique introduction to the process of visualizing quantitative data, offering a remarkably coherent treatment that will appeal to novices and advanced analysts alike. There is no other book quite like this.¡±¡ªThomas J. Leeper, London School of Economics
¡°Kieran Healy has written a wonderful book that fills an important niche in an increasingly crowded landscape of materials about software in R. Data Visualization is clear, beautifully formatted, and full of careful insights.¡±¡ªBrandon Stewart, Princeton University
¡°Healy¡¯s prose is clear and direct. I came away from this book with a much better understanding of both visualizations and R.¡±¡ªNeal Caren, University of North Carolina, Chapel Hill
¡°Innovative and extraordinarily well-written.¡±¡ªJeremy Freese, Stanford University
1 Look at Data
2 Get Started
3 Make a Plot
4 Show the Right Numbers
5 Graph Tables, Add Labels, Make Notes
6 Work with Models
7 Draw Maps
8 Refine Your Plots
Acknowledgments
Appendix