Kieran Healy, Data Visualization for Social Science.

Data Visualization for Social Science
Data Visualization for Social Science is a practical introduction to data visualization using R and ggplot2. The main goal of this book is to introduce you to both the ideas and the methods of data visualization in a clear, sensible, and reproducible way.

Through a series of worked examples, the book shows you how to build plots piece by piece, beginning with scatterplots and summaries of single variables, then moving on to more complex graphics. Topics covered include plotting continuous and categorical variables, layering information on graphics; faceting grouped data to produce effective “small multiple” plots; transforming data to easily produce visual summaries on the graph such as trend lines, linear fits, error ranges, and boxplots; creating maps, and also some alternatives to maps worth considering when presenting country- or state-level data. Plotting estimates from statistical models and from complex survey designs are also covered. The book then explores the process of refining plots to accomplish common tasks such as highlighting key features of the data, labeling particular items of interest, annotating plots, and changing their overall appearance. Finally it discussesa some strategies for presenting graphical results in different formats, and to different sorts of audiences.

Learning how to visualize data effectively is more than just knowing how to write code that produces figures from data. This book will teach you how to do that. But it will also teach you how to think about the information you want to show, and how to consider the audience you are showing it to—including the most common case, when the audience is yourself.

This book is currently in progress. A draft version of the manuscript is available as a website, at

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I am Associate Professor of Sociology at Duke University. I’m affiliated with the Kenan Institute for Ethics, the Markets and Management Studies program, and the Duke Network Analysis Center.



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