Data Points: Visualization That Means Something [Paperback] Author: Nathan Yau | Language: English | ISBN:
111846219X | Format: PDF, EPUB
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A fresh look at visualization from the author of Visualize This
Whether it's statistical charts, geographic maps, or the snappy graphical statistics you see on your favorite news sites, the art of data graphics or visualization is fast becoming a movement of its own. In Data Points: Visualization That Means Something, author Nathan Yau presents an intriguing complement to his bestseller Visualize This, this time focusing on the graphics side of data analysis. Using examples from art, design, business, statistics, cartography, and online media, he explores both standard-and not so standard-concepts and ideas about illustrating data.
- Shares intriguing ideas from Nathan Yau, author of Visualize This and creator of flowingdata.com, with over 66,000 subscribers
- Focuses on visualization, data graphics that help viewers see trends and patterns they might not otherwise see in a table
- Includes examples from the author's own illustrations, as well as from professionals in statistics, art, design, business, computer science, cartography, and more
- Examines standard rules across all visualization applications, then explores when and where you can break those rules
Create visualizations that register at all levels, with Data Points: Visualization That Means Something.
Direct download links available for Data Points: Visualization That Means Something [Paperback] Epub Free
- Paperback: 320 pages
- Publisher: Wiley; 1 edition (April 15, 2013)
- Language: English
- ISBN-10: 111846219X
- ISBN-13: 978-1118462195
- Product Dimensions: 9.2 x 7.4 x 0.6 inches
- Shipping Weight: 1.6 pounds (View shipping rates and policies)
Introduction xi
1 Understanding Data 1
2 Visualization: The Medium 43
3 Representing Data 91
4 Exploring Data Visually 135
5 Visualizing with Clarity 201
6 Designing for an Audience 241
7 Where to Go from Here 277
Index 291
The review trends of Yau's last book have already started with this edition: "too basic." Maybe we could graph the stats of those reviews, then look at the very topmost band of readers to find the "perfect" audience, vs. the large body of outliers who will trash this as oversimplistic. So, get into alpha, and visualize a bell curve, with "perfect for me" on Y and age/experience on x:
DON'T BUY IF:
--You're in the heavily skewed, lightly shaded, experienced right side of the curve, with even good basic experience in data presentation. I'd include any mid level manager who has decent powerpoints in this group. The colorful pictures are gorgeous, as in Visualize This: The FlowingData Guide to Design, Visualization, and Statistics, and if you have a LOT of disposable income, you "could" buy it just for the pictorial ideas (paper is coated matte, images are 4 color, very high quality book production wise). If you're a post undergrad freshman, you might find the advice too basic. There also are a lot of discussions of data "types" but very little about psych. For example, starting a presentation with the statment "My purpose here is to INFORM" often gets audience hackles down if they're resistant to being sold or convinced-- not much of that is covered here.
--You're a graphic artist or graphic pro, unless, again, you're just looking for pictorial and presentation ideas, and not advice (the illustrations, as in the last edition, are stunning).
BUY IF:
--You're very new to data presentation and aren't even sure whether red goes with green or tables are better than scatters in a given situation.
Many people drawn to this book will find it entertaining and informative. Yau covers a wide range of data graphics from unconventional data art to more conventional statistical graphics. As you would expect, there are numerous examples, often excellent and mostly in color. The tone is informal and enthusiastic. If you want something very light as an overview of or introduction to visualization, this is quite a good choice. If you want a more serious but not strongly technical book on what to do with your data, Naomi Robbins' "Creating more effective graphs" is my best recommendation. At a deeper or wider level, nothing has superseded the works of Edward Tufte, William S. Cleveland, and Leland Wilkinson on statistical graphics.
Yau is broad-minded on many of the debates that now bedevil graphics. He stands aside from the mutual incomprehension or even hostility often seen between groups dedicated to "data art", information graphics or "infographics", and statistical or scientific graphics. He gives some examples of data art, but is not especially articulate on what we are expected to see or on how it should be evaluated. He is not dogmatic on many smaller points, such as whether pie charts should just be avoided. I do not see, however, how citing research that shows that people are poor at comparing angles is consistent with his indulgence. The overall attitude is liberal, even anarchist: anybody's "rules" are just suggestions, not absolute rules.
There is a marked downside to the informality. I found Yau's book to be rambling and unstructured and to lack a clear roadmap. Bluntly put, the graphics are of higher quality than the commentary, which is usually sensible but often banal.
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