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Visualize This: The FlowingData Guide to Design, Visualization, and Statistics 1st Edition
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Data doesn?t decrease; it is ever-increasing and can be overwhelming to organize in a way that makes sense to its intended audience. Wouldn?t it be wonderful if we could actually visualize data in such a way that we could maximize its potential and tell a story in a clear, concise manner? Thanks to the creative genius of Nathan Yau, we can. With this full-color book, data visualization guru and author Nathan Yau uses step-by-step tutorials to show you how to visualize and tell stories with data. He explains how to gather, parse, and format data and then design high quality graphics that help you explore and present patterns, outliers, and relationships.
- Presents a unique approach to visualizing and telling stories with data, from a data visualization expert and the creator of flowingdata.com, Nathan Yau
- Offers step-by-step tutorials and practical design tips for creating statistical graphics, geographical maps, and information design to find meaning in the numbers
- Details tools that can be used to visualize data-native graphics for the Web, such as ActionScript, Flash libraries, PHP, and JavaScript and tools to design graphics for print, such as R and Illustrator
- Contains numerous examples and descriptions of patterns and outliers and explains how to show them
Visualize This demonstrates how to explain data visually so that you can present your information in a way that is easy to understand and appealing.
From the Author: Telling Stories with Data
Author Nathan Yau A common mistake in data design is to approach a project with a visual layout before looking at your data. This leads to graphics that lack context and provide little value. Visualize This teaches you a data-first approach. Explore what your data has to say first, and you can design graphics that mean something.
Visualization and data design all come easier with practice, and you can advance your skills with every new dataset and project. To begin though, you need a proper foundation and know what tools are available to you (but not let them bog you down). I wrote Visualize This with that in mind.
You'll be exposed to a variety of software and code and jump right into real-world datasets so that you can learn visualization by doing, and most importantly be able to apply what you learn to your own data.
Three Data Visualization Steps:
1) Ask a Question
(Click Graphic to See Larger Version)
When you get a dataset, it sometimes is a challenge figuring out where to start, especially when it's a large dataset. Approach your data with a simple curiosity or a question that you want answered, and go from there.
2) Explore Your Data
(Click Graphic to See Larger Version)
A simple curiosity often leads to more questions, which are a good guide for what stories to dig into. What variables are related to each other? Can you see changes over time? Are there any features in the data that stand out? Find out all you can about your data, because the more you know what's behind the numbers, the better story you can tell.
3) Visualize Your Data
(Click Graphic to See Larger Version)
Once you know the important parts of your data, you can design graphics the best way you see fit. Use shapes, colors, and sizes that make sense and help tell your story clearly to readers. While the base of your charts and graphs will share many of the same properties – bars, slices, dots, and lines – the final design elements will and should vary by your unique dataset.
- ISBN-100470944889
- ISBN-13978-0470944882
- Edition1st
- PublisherWiley
- Publication dateJuly 20, 2011
- LanguageEnglish
- Dimensions7.3 x 0.7 x 9 inches
- Print length384 pages
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Editorial Reviews
From the Inside Flap
Our world is awash in data. To mean anything, it must be presented in a way that enables us to interpret, analyze, and apply the information. One of the best ways to do that is visually.
Nathan Yau is a pioneer of this innovative approach. In this book, he offers you dozens of ideas for telling your story with data presented in creative, visual ways. Open the book, open your mind, and discover an almost endless variety of ways to give your data new dimensions.
Learn to present data with visual representations that allow your audience to see the unexpected
Find the stories your data can tell
Explore different data sources and determine effective formats for presentation
Experiment with and compare different visualization tools
Look for trends and patterns in your data and select appropriate ways to chart them
Establish clear goals to guide your visualizations
Visit the companion web site at www.wiley.com/go/visualizethis for code samples, data files you can download, and interactive examples to show you how visualization works
From the Back Cover
Our world is awash in data. To mean anything, it must be presented in a way that enables us to interpret, analyze, and apply the information. One of the best ways to do that is visually.
Nathan Yau is a pioneer of this innovative approach. In this book, he offers you dozens of ideas for telling your story with data presented in creative, visual ways. Open the book, open your mind, and discover an almost endless variety of ways to give your data new dimensions.
Learn to present data with visual representations that allow your audience to see the unexpected
Find the stories your data can tell
Explore different data sources and determine effective formats for presentation
Experiment with and compare different visualization tools
Look for trends and patterns in your data and select appropriate ways to chart them
Establish clear goals to guide your visualizations
Visit the companion web site at www.wiley.com/go/visualizethis for code samples, data files you can download, and interactive examples to show you how visualization works
About the Author
Product details
- Publisher : Wiley; 1st edition (July 20, 2011)
- Language : English
- Paperback : 384 pages
- ISBN-10 : 0470944889
- ISBN-13 : 978-0470944882
- Item Weight : 1.65 pounds
- Dimensions : 7.3 x 0.7 x 9 inches
- Best Sellers Rank: #579,066 in Books (See Top 100 in Books)
- #141 in User Experience & Website Usability
- #264 in Data Modeling & Design (Books)
- #1,823 in Computer Science (Books)
- Customer Reviews:
About the author

My name is Nathan Yau, and I'm the one writing for FlowingData. I have a Ph.D. in statistics from UCLA, with a focus in data visualization. I'm most interested in personal data collection, data for non-professionals, and information design.
I want to make data available and useful to those who aren't necessarily data experts; I think visualization plays a major role in this.
When I'm not playing with data, I'm usually cooking, eating, watching basketball, or hanging out with my wife.
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The book describes several visualization methods. For each topic, Yau starts with a quick overview of the technique. He then follows with programming details (for example using R). He eventually shows the way from standard R graphics to nice visualizations using Illustrator. The book is thus very practical, with few place for theoretical concepts.
Yau provides several good advices such as the importance to question your data. The books contains tips and tricks for preparing and programming graphics. It is sometimes more of a R user manual than a general book on the topic. To be noted the excellent Chapter 7, about visualizing multi-dimensional data. This book is a must-have for people who want to prepare nice graphics in R. For expert users, the book is too straightforward (out of the last few chapters). For others, it’s a nice non-theoretical journey in the world of data visualization.
First, every example uses Adobe Illustrator to make the visualization look as good as they do. In order to complete the exercises, you must have Illustrator. Nathan does explain that it can be obtained at a discount or you can an older version, but it's still a pretty big financial investment. If I hadn't been able to dig up a old copy, Illustrator 9, I would have been out of luck. Even with my outdated copy, not everything worked for me. If he had included at least a couple of examples with the open source Inkscape, this would have been a 5 star rating.
The second thing I would have liked to see a little different is more statistical info to go along with the visualizations. We often visualize data to help make decisions. Nathan shows how to display a LOESS line to see the best fit for the curve, but he stops there. Maybe discussing R² ( correlation coefficient) analysis to determine whether the values are are a good match would help me feel better about analyzing the data beyond just visualization.
That said, this is an extremely well written book and easily deserves 4 stars. Dig up an old copy of Illustrator (preferably CSx versions) and enjoy this book.
There is very little to complain about here except the fact that the author shows off Illustrator instead of its less expensive competitors. I had avoided Illustrator because of cost and the nasty learning curve but now, thanks to this book, I am using it to edit my SAS and R graphics that were "almost perfect." Happily this book has great examples for showing how to manipulate/clean up scientific graphics without getting bogged down in the endless complexity that is Illustrator.
So, this is all around beautiful, friendly and worth every cent if you need to make high quality graphics.
* teaches how to scrape data from web pages
* teaches the nuts and bolts
* teaches you how to do it - not just a textbook approach of what visualization is
* super applied
* makes it easy to extract value
* feels like you are being tutored rather than just taught about it
Top reviews from other countries
Good points about the book:
The layout and graphics in the book and clean and inviting and the author gives suggestions on how to label and present graphs and charts to make sure the audience understand them (this is all fairly standard stuff, but if the target audience is non-analysts then these points need to be reiterated). He also clearly explains when certain graphs will/won’t work; this isn’t ground-breaking stuff (I found myself agreeing with most of what he says) and for the seasoned analyst this is probably too basic, but it’s useful to get an idea of where a different type of graph/chart might work for your analysis. It gave me some great ideas for a big project I am working on.
Bad points about the book:
At times, it felt like the main focus was an intro to R. If you’ve got a decent background in R this book will no doubt be too basic for you and you are better off downloading a trial for Adobe or getting Inkscape and fiddling around with your graphs to make them look more interesting – if this is what you want to do.
The writing style is very informal and a bit too ‘chatty’ for my liking (perhaps all books are heading this way?) I imagine this approach would work in a video format or for a lecture, but in a book I prefer a more formal style. The casual language in the book didn’t work for me.
Things I am not sure about:
I am not entirely sure who this book is aimed at – analysts or non-analysts, or both? If you’ve got an analytical background, the content might be too simplistic for you, but if you want fresh ideas because the presentation of your analysis feels a bit stale then this book will help.
Buy this book if you’ve got an analytical background and are wanting to learn how to do very basic data analysis in R and then improve the graphs in Adobe (as the first 6 chapters do a lot of this!) As others have said, plenty of code is provided so you can plot basic graphs in R. If you want to practice examples, there are links to the datasets on the author’s website so you can easily read the data into R and create the output yourself. If you're a non analyst, you might want to get a more technical book first before you reach for this so you're clear on the basics (e.g. what a histogram is and how you interpret it).
This book will open your eyes to what is possible once you move away from Microsoft Excel. As a professional analyst and data modeller, I have been using Excel for years but was growing frustrated with its limitations. In this book, Nathan Yau uses R, Python and Adobe Illustrator (though I personally prefer the open-source Inkscape equivalent) to show just what can be achieved with a little imagination and creativity.
I have given this five stars. Although it would have been nice to have more complex walk-throughs from raw data to final graphic as suggested in other reviews, to do so would have required the reader to have a solid foundation in R and Python programming. To include the required learning material in these programming languages so as to bring the reader up to speed as a programmer, as well as containing the excellent material it already does contain, would have required a book three or four times the thickness. If we were then to add a needed introductory statistics course into the book as well...
I think therefore to penalise the book for focusing purely on the creation of great looking graphics is a bit harsh especially when it says "Visualise", "design" and "visualisation" in the title.
That said there is a plethora of free PDF guides to R and Python (and Inkscape) legally available for download from the internet and of a high, publishable quality. These guides will take the reader from basic programming to intermediate level and beyond. See the documentation page on the R website or google "A Byte of Python" for an excellent, and free, beginners guide to Python programming.
So all in all this book will not teach you how to be a great R/Python programmer or statistician for that matter, but it will give you more than enough inspiration to motivate you away from Excel charts and towards teaching yourself powerful professional techniques that will make your presentations/reports stand out and make you a great data visualiser.
A simply beautiful book.













