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Designing Data Visualizations 1st Edition

by Noah Iliinsky (Author), Julie Steele (Author)
3.3 3.3 out of 5 stars 39 ratings
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Data visualization is an efficient and effective medium for communicating large amounts of information, but the design process can often seem like an unexplainable creative endeavor. This concise book aims to demystify the design process by showing you how to use a linear decision-making process to encode your information visually.

Delve into different kinds of visualization, including infographics and visual art, and explore the influences at work in each one. Then learn how to apply these concepts to your design process.

  • Learn data visualization classifications, including explanatory, exploratory, and hybrid
  • Discover how three fundamental influences―the designer, the reader, and the data―shape what you create
  • Learn how to describe the specific goal of your visualization and identify the supporting data
  • Decide the spatial position of your visual entities with axes
  • Encode the various dimensions of your data with appropriate visual properties, such as shape and color
  • See visualization best practices and suggestions for encoding various specific data types

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  1. ISBN-10
    1449312284
  2. ISBN-13
    978-1449312282
  3. Edition
    1st
  4. Publisher
    O'Reilly Media
  5. Publication date
    November 1, 2011
  6. Language
    English
  7. Dimensions
    7 x 0.24 x 9.19 inches
  8. Print length
    108 pages
  9. See all details
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3.3 out of 5 stars
39 global ratings

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Top reviews from the United States

  • JayD
    5.0 out of 5 stars Outstanding
    Reviewed in the United States on March 1, 2012
    This book is about as comprehensive an introductory text as you can find in a slim volume. Yes there are more detailed books like 'Semiology of Graphics' but even if you have read those, this is a handy back pocket reference.

    Sure, it would better if the illustrations were in colour but to be honest that does not reduce the potency of the information within the book or the easy way in which it is explained.
    2 people found this helpful
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  • fish
    4.0 out of 5 stars Good, quick overview
    Reviewed in the United States on December 28, 2012
    Verified Purchase
    Well-done principles of data-viz - probably better on the Kindle so you can see the color illustrations. A great resource to go along with other how-to books such as Nathan Yao's "Visualize This."
    2 people found this helpful
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  • Carol
    1.0 out of 5 stars Pictures without colors
    Reviewed in the United States on October 10, 2022
    Verified Purchase
    I bought this book for a class on visualizations. The graphs in this book were uncolored….how are you going to a book on visualizations and have your graphics gray scaled? Weak!
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  • Easy Writer
    2.0 out of 5 stars Hastily Tossed Together
    Reviewed in the United States on November 18, 2012
    Verified Purchase
    This book reads like a set of the author's notes, then hastily thrown together into a book. The ideas themselves are generally correct. But they are written at too abstract a level. The author should have followed up with more examples to make the ideas concrete.

    In addition, the book is shamefully short - just 84 pages plus appendix materials. It was frustrating, then, when the author skims over important materials like color theory or a review of Bill Cleveland's research with the apologetic "it would be too much to cover in this short book". Here's an idea - make the book LONGER!

    Very disappointed to finish this book in about 2 hours and not much of what was covered was memorable. Not worth your time or money.
    7 people found this helpful
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  • hardcoreUFO
    3.0 out of 5 stars O'Reilly ruined this book
    Reviewed in the United States on October 17, 2011
    The goals of this volume are completely undermined by the publisher's choice to print greyscale figures. Entire sections on color and color selection are rendered useless because of this. There is no excuse, in 2011, to print a data visualization book (or any other book, for that matter) in greyscale and B&W. O'Reilly should know better.
    40 people found this helpful
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  • Karl S.
    4.0 out of 5 stars A fine introduction
    Reviewed in the United States on March 29, 2012
    Illinksy's Designing Data Visualizations is a fine introduction to the field. Most valuable is his description of the different stakeholders in this field of design, their needs, and how to approach the process data visualization design for each data / user scenario. The usual suspects --- color, shape, and the requisite destruction of the pie chart --- all appear, as well. Overall, this book is a perfect introduction for the amateur designer and sound review for others.
    One person found this helpful
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  • JYB
    1.0 out of 5 stars Too bad ...
    Reviewed in the United States on December 15, 2011
    I am very disappointed by this book.
    It deals with graphics and design, including colors ... but it is printed in black and white!
    Very useful to judge the "good" or "wrong" color of any logo or diagram (p. 36) ...
    In addition, the print quality is poor: some diagrams are illegible (p. 44, 46).
    17 people found this helpful
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  • P. Grey
    2.0 out of 5 stars It’s in black and white
    Reviewed in the United States on June 29, 2021
    Verified Purchase
    The book is informative enough but it’s a visualization book in black and white. How can a book that guides readers to create appropriate visualizations not contain appropriate visualizations? There’s one section that details the colors for internet browsers but the image doesn’t contain colors so the section is pointless. If this had accurate visualizations it would be a great data visualization book.
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  • Sergey Khabarov
    3.0 out of 5 stars Content is fine for beginners, but the print quality is poor
    Reviewed in Germany on July 3, 2023
    Verified Purchase
    Good points:
    - An idea about the visualisation types (exploratory vs explanatory) and why they need different approach;
    - Good overview of the ways to code values, which one is better in what situation;
    - Overview of common chart types, pros and cons.

    Bad points:
    - Very short;
    - Quite simple;
    - Black and white print, while many illustration demand color (for example, it is funny to read about the color schemes with only B/W examples;
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  • Vanderson
    2.0 out of 5 stars Deveria ser colorido
    Reviewed in Brazil on September 18, 2018
    Verified Purchase
    O livro é cheio de exemplos que citam cor, mas todo impresso em preto e branco. Não recomendo, até porque é um livro caro.
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  • Sanjiv Kumar
    5.0 out of 5 stars Data Visualisation Designer’s handbook
    Reviewed in India on September 29, 2019
    Verified Purchase
    This is an important book for data visualisation designers!
    Report
  • Gabrio
    1.0 out of 5 stars Assolutamente inutile; non ci si può concentrare per 2/3 ...
    Reviewed in Italy on December 17, 2014
    Verified Purchase
    Assolutamente inutile; non ci si può concentrare per 2/3 del libro sull'efficacia comunicativa dei colori nei grafici e poi stampare gli stessi in bianco e nero!

    E il restante 1/3? Pochi e frammentari consigli piuttosto banali esposti in modo impreciso.

    Si salva solo la ricca bibliografia, ma decisamente non vale i soldi spesi
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  • brainchild
    1.0 out of 5 stars I would not pay for this again
    Reviewed in the United Kingdom on June 20, 2012
    Verified Purchase
    I understand that data visualization is a hot topic at the moment. So it is not surprising that publishers cannot wait to capitalize on this attention. However, while many recent books on visualization seem to have been hastily written, I found this one especially disappointing.

    For example:

    Contrary to their own advice ("Are you using color to represent quantity? Stop it.", p. 92), the authors reserve considerable space for discussing color. That's weird, but what is even weirder is that some of these discussions are illustrated with color scales and samples -- which are actually printed in grey scales! Having read the book, I can understand why the publishers may not have wanted to invest more in the manuscript than necessary. But that does not make it less problematic.

    More importantly for me, I got increasingly annoyed by the verbosity and use of boilerplate language. Take this "tip" from page 49: "Consider the following challenge. For every visualization you see, ask yourself these two questions: Are the axes all well defined? Are they used effectively? Unfortunately, the answer to these is often 'no'. Better use of axes will be the first step to improvement." Yes, this all makes sense, doesn't it? Who wouldn't want to have their axes "well defined" and "used effectively"? So how can I do this? Ah, right, I am supposed to start with "better use of axes". Thank you, question answered.

    This may come across as sarcastic, but this is the style that much of the book is written in. This is somewhat ironic. The authors talk a lot about how crucial it is for designers of visualizations to reduce the noise and focus on the story or message. However, they do not seem to have applied the same principles to their own text.

    Against this backdrop, the typos and use of unexplained acronyms (e.g. "TMI", p. 23) seem rather minor.

    In my opinion, this text should be made freely available as a pdf. Relevant graphics would at least appear in color. In addition, the authors could take advantage of feedback, proofread the text and prepare the manuscript for more formal publication. Personally, I expect a book on "visualization" to show at least a minimum standard of "verbalisation".
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