Yau - Data points: visualization that means something

Executive Editor:

Carol Long

Senior Project Editor:

Adaobi Obi Tulton

Technical Editor:

Jen Lowe

Production Editor:

Kathleen Wisor

Copy Editor:

Apostrophe Editing Services

Editorial Manager:

Mary Beth Wakefield

Freelancer Editorial Manager:

Rosemarie Graham

Associate Director of Marketing:

David Mayhew

Marketing Manager:

Ashley Zurcher

Business Manager:

Amy Knies

Production Manager:

Tim Tate

Vice President and Executive Group Publisher:

Richard Swadley

Vice President and Executive Publisher:

Neil Edde

Associate Publisher:

Jim Minatel

Project Coordinator, Cover:

Katie Crocker

Compositor:

James D. Kramer, Happenstance Type-O-Rama

Proofreader:

James Saturino, Word One

Indexer:

Johnna VanHoose Dinse

Cover Designer:

Ryan Sneed

Cover Image:

Nathan Yau

Chapter Photographs:

Serena Yau

Published by
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Copyright 2013 by John Wiley & Sons, Inc., Indianapolis, Indiana

Published simultaneously in Canada

ISBN: 978-1-118-46219-5

ISBN: 978-1-118-46222-5 (ebk)

ISBN: 978-1-118-65493-4 (ebk)

ISBN: 978-1-118-65493-4 (ebk)

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To Bea

Nathan Yau has written and created graphics for FlowingData since 2007, a site on visualization, statistics, and design and believes that visualization is a medium that can be used as both a tool and a way to express data. He is the author of Visualize This: The FlowingData Guide to Design, Visualization, and Statistics, also published by Wiley.

Yau has a masters degree in statistics from the University of California, Los Angeles, and has a Ph.D. in statistics with a focus on visualization and personal data. He is a statistician.

Jen Lowe is an Associate Research Scholar at the Spatial Information Design Lab at Columbia University where she experiments with new forms of data visualization and communication. She has a bachelors degree in applied mathematics and a masters degree in information science. She has publications in applied meteorology and astronomy in journals such as the Journal of Atmospheric and Oceanic Technology, and has spoken internationally on the relationship between data, visualization, and identity. A sucker for a good argument, shell nearly always side with complexity.

Thank you to everyone I spoke to and received feedback from in the process of writing this book. You provided valuable insight and gave me fresh perspectives. Thank you to those who graciously let me feature their beautiful work.

Thank you to FlowingData readers who continue to support and always give me something to be excited about. This book would not exist without you.

Thank you to Wiley Publishing for helping me write a book worth reading and to Jen Lowe for making sure my words meant something.

Thank you to Serena Yau for taking pictures.

Thank you to the statisticians, computer scientists, data scientists, designers, and everyone else involved in this hodge-podge data world for making it fun and always keeping it interesting.

Thank you to all those who have taught me.

Thank you to my wife, my parents, and all other family and friends for their support and encouragement.

What is good visualization? It is a representation of data that helps you see what you otherwise would have been blind to if you looked only at the naked source. It enables you to see trends, patterns, and outliers that tell you about yourself and what surrounds you. The best visualization evokes that moment of bliss when seeing something for the first time, knowing that what you see has been right in front of you, just slightly hidden. Sometimes it is a simple bar graph, and other times the visualization is complex because the data requires it.

A data set is a snapshot in time that captures something that moves and changes. Collectively, data points form aggregates and statistical summaries that can tell you what to expect. These are your means, medians, and standard deviations. They describe the world, countries, and populations and enable you to compare and contrast things. When you push down on the data, you get details about the individuals and objects within the population. These are the stories that make a data set human and relatable.