Visualize This: The FlowingData Guide to Design, Visualization, and Statistics
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Visualize This: The FlowingData Guide to Design, Visualization, and Statistics

3.76 of 5 stars 3.76  ·  rating details  ·  421 ratings  ·  24 reviews
Practical data design tips from a data visualization expert of the modern age

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 t

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Kindle Edition, 384 pages
Published (first published June 13th 2011)
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Uroš
This is a BEGINNERS guide to (mostly) static data graphics design for websites and newspapers. Don't expect a lot about both data science (statistics and data analysis) and data art (artistic visualization, animation, interactive video, etc).

Pros:
- Very practical, with a lot of code
- Good combination of statistics and design practice
- Online examples
- Clear writing style
- Useful design tips

Cons:
- Lacks subtlety and depth in terms of both science and art
- Lacks materials about animation and inter...more
Alyson Hurt
Targeted toward beginners who don't fear code, this is a useful introduction to the world of data visualization, from data collection/research to display. Coming at the book from a graphic/web design background, I found the code examples most useful – particularly those relating to the statistical software R, which I've always found a bit intimidating.

Note: Some of the software/frameworks cited are out of date: Protovis is now D3.js, and Flex Builder is now Flash Builder (and most folks are movi...more
Chris
Decided to quickly read this over the weekend. The last few chapters are relatively good with some quick examples on how to use R and Python to produce visualizations. There is also a good example of SVG-style graphics and with very limited skill set. You could easily set up many of those graphics by manipulating a few XML files. The first part of this book was ok. This book is more practical, which I find better than the book data point, which is just theory. Nathan Yau also presents his backgr...more
Jake Losh
Visualize This: The FlowingData Guide to Design, Visualization, and Statistics is a worthy effort to make a primer on data visualization. You'll learn all the tricks of the trade for finding data, cleaning data, making a graphic and cleaning the graphic to make it fit to print. If you're already a data nut or a fan of Nathan Yau's blog, you'll likely enjoy the ride.

In some sense, though, the book tries to do too much in too small a space. Aside from the core content revolving around data viz, yo...more
This Is Not The Michael You're Looking For
Visualize This is a book about designing visualizations for data ("graphs" more or less, although there are visualizations which are not, strictly speaking, graphs). The focus of the book was not what I expected; given that the author is a graduate student in statistics, I expected the book to have more of a scientific focus. Instead, it is mostly focused on designing visualizations for websites and/or newspapers and magazines. While there can be a lot of overlap between these tasks and more dir...more
Jonathan Jeckell
Sep 02, 2012 Jonathan Jeckell rated it 4 of 5 stars  ·  review of another edition
Recommended to Jonathan by: Sky Gerrond
This is a nice supplement to the Tufte series, focusing exclusively on data, numeric, and statistical graphics, including animations. Edward Tufte even referred to this book during his One Day Seminar. Unlike Tufte, this contains a lot of detailed, step-by-step directions to obtain data and how to build the graphics he shows in the book. While I love the practical directions, rather than just showing us the graphic and letting us ponder how to make something like it, I wish there was a greater s...more
Gina
Yau is best when he talks about data and how to acquire it and about how to present various types of data. He is fixated on the notion that people need to code their own visualizations, preferably using R, an open source program that is quite good but not for the faint of heart. The documentation is spotty, and while I gamely carried out multiple exercises from the book, there were errors in the coding one was instructed to use, and multiple gaps that assumed readers would have greater knowledge...more
Brian Kelly
Recently started reading this. It's a good book though a little bit dated at this point.

My main issue is that it's pretty much a workbook - you're meant to use apps and write programs as you read the book and information about how to better display different types of information is sprinkled through that. I would've liked that information to be more separate from the actual "exercises". This made it hard to read on the train.
Ariadna73
10-19-2011: This book is a wealth of good resources for visualization. I felt like a kid in a candy store. It must be read in front of a computer with internet connection. There are so many different places where we can find data and ideas to visualize it! I loved this book!



09-18-2011: This book has been a nice surprise: I was expecting another boring recount of graphics and enless tables; but this one is really well written and entertaining. I have been reading it with real attention and I have...more
vanch
good book for freshman to learn data analysis
Leslie Valencia
Great hands on book about data visualization. It helps to know a little bit about stats and visualization before starting, but this book does a great job of explaining how to put some very advanced and interesting visualizations together, and how to use various software and programming languages to get the visualizations you want. As someone who isn't a programmer, this is was a super helpful guide in getting started in the world of R in particular. Love it. Will keep and reference again for man...more
Derrick Schneider
This book is a great hands-on start to the world of data visualization. Yau provides exercises that use a wide variety of tools, giving breadth that allows you to be smarter about which toolset you use for any given visualization task. Along the way, he also discusses the theory behind different visualizations -- when to use them and how.
S.M.
I'd recommend this to anyone who is working with large data sets and needs a quick intro into good visualization techniques. Of course, it is not a substitute for years of work with R or gnuplot but does a great job of explaining what a good data visualization is expected to be. Oh and did I mention I own a signed copy of the book? :D
Mick Bordet
A very easy read, but after racing through it in two days, I know that this is a book that will also be used as a reference. Some very useful insights into producing clear visualisations and interesting starter code for various systems. I did skip over the sections on using flash, but everything else was very useful.
Ryan
Far and away one of the best reads of this type of book in years. I'm a data visualization geek, and his method of presenting ideas (compelling examples, hands-on code and data, and humor) make it a joy. I devoured this book and have used its techniques a number of times. Go Nathan!
Eric Bell
Nice book on data visualization, but could have been much shorter, and contained much less code. We need a book written like this book that shares less about the how to the obtain the data and more on the thinking about and visualizing the data.
Sean
Thorough, enlightening, and I had no idea that there were programming exercises. If you want to do anything with data visualization, read this after you read the Tuftebooks.
Gina Enk
I read this at the request of a friend who is looking to incorporate storytelling into her statistics classes. My take away? Two great creative comp lessons!
Mark
An attractive book. You can learn several things from it, but I don't think you're going to pick up Python or Adobe Illustrator or any Statistics from it.
Lochana Menikarachchi
I think I expected too much from this introductory text (Most readers will realize that they already know most of the stuff). Not for experienced folks.
Patrick
Yau explores techniques and tools for data visualization with a nice balance of free and commercial software, examples, and styles.
Hunter Hustus
Good complement to other approaches. Along with Tufte, a must-read for my staff.
Jack
Fantastic introduction to the principles and techniques of modern data visualisation.
Genie
Some good information here but too focused on R as a tool, for my tastes.
Martina Skender
Martina Skender marked it as to-read
Sep 16, 2014
Tatjana
Tatjana marked it as to-read
Sep 15, 2014
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dubious 1 4 Feb 07, 2013 01:45PM  
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