The must-have primer on how to create effective graphics from data-now fully revised and updated Since it was first published, Data Visualization has been established as the essential hands-on introduction to the principles and practice of data visualization. Now updated to reflect the latest advances in software and methods, it explains what makes some graphs succeed while others fail, how to make high-quality figures from data using powerful and reproducible techniques, and how to think about data visualization in an honest and effective way. Kieran Healy carefully builds the reader's expertise in ggplot2, a versatile visualization library for the R programming language. Through a series of worked examples, he then demonstrates how to create plots piece by piece, beginning with summaries of single variables and moving on to more complex graphics. Good graphics are essential to communicating ideas and a great way to better understand data. Data Visualization provides the practical skills students and practitioners need to visualize quantitative data, along with a strong understanding of the logic behind effective graphs.

• Every chapter has been updated to reflect the continuing development of R and ggplot2
• Features new material on working with models and geographic data, new and updated datasets, and an extensively revised appendix
• Shows how the "tidyverse" of data analysis tools makes working with R easier and more consistent
• Topics include plotting continuous and categorical variables; layering information on graphics; producing effective "small multiple" plots; grouping, summarizing, and transforming data for plotting; creating maps; working with the output of statistical models; and refining plots to make them more comprehensible
• Includes a library of datasets, code, and functions