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

3.88  ·  Rating details ·  1,109 ratings  ·  50 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 ...more
Paperback, 358 pages
Published July 20th 2011 by Wiley (first published June 13th 2011)
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 ·  1,109 ratings  ·  50 reviews

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Feb 14, 2012 rated it liked it
Shelves: non-fiction
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).

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

- Lacks subtlety and depth in terms of both science and art
- Lacks materials about animation and inter
Chelsea Lawson
Aug 01, 2015 rated it it was amazing
Nathan Yau is the BEST. I have been trying to learn R on my own for some time now and it has been quite frustrating. The documentation on is written in such an esoteric way. I wish it were a wiki so that people could provide more examples or make it sound more like plain English. Anyway, Visualize This covered everything I was looking for to learn basic data visualization in R, from timelines to proportions/relationships and maps, as well as some instruction for Illustrator/In ...more
Yerzhan Karatay
Aug 28, 2020 rated it liked it
Shelves: data-science
Nathan Yau's Visualize This basically lives up to its full name, it's a broad guide to design, data visualization tools, and methods, I must say that the broadness compensates the depth as I took several notes of the tools that I could use in personal projects.

Nathan Yau constantly reminds the reader about the importance of programming as it provides one with the best opportunities, and goes through data handling (including how to web-scrape), visualizing time series, proportions, relationships
Alyson Hurt
Dec 29, 2012 rated it liked it
Shelves: design, datavis
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
Michael Scott
TODO full review:
+ Reads like a primer on information-visualization techniques, plus a primer on interesting software to use the information-visualization techniques in practice. Also comes with various links to meaningful datasets.
+ The visuals are rich, interesting, and correctly executed. There is little of the egregious visualization that have annoyed Stephen Few and William S. Cleveland or, for a stricter take, Edward R. Tufte.
+++ The data sources focus on data provided by (1) universities
Sep 06, 2019 rated it liked it
Good, but not the first book you should read on data visualization (probably start with Cole Knaflic's Storytelling with Data first).

The book has lots of good examples; everyone will probably learn something from it. For me, the most valuable parts were: (1) an overview of data visualization tools from someone who has tried many of them (including Adobe Illustrator, which should have been on my radar long before I read this), (2) a good walkthrough on scraping data from the web, which is someth
Cyrus Molavi
Jan 26, 2017 rated it it was amazing
Shelves: own
This was a very complete book. It reads very much like a textbook or workbook. A concept is introduced, a challenge is laid out, and then the author walks through the steps of getting there while the reader works through the problem actively. Data and code is made available for download to use while following along. It dives into pragmatic uses of Python, R, CSS, Illustrator, XML, and a variety of visualizations. This is the depth of coding and design that I'm interested in as an analyst, and th ...more
Lukas Rubikas
May 05, 2020 rated it liked it
I feel some of the tools mentioned here (Pyhton 2, Flash, Protovis) are outdated but the practices mentioned here are applicable regardless. This book is much more focused on hands-on approach than Storytelling with Data: A Data Visualization Guide for Business Professionals but I liked it, especially the hands-on bits on putting finishing touch on your graphs with Adobe Illiustrator as I'm yet to learn how to adapt this widely popular tool for my needs.

It's good for beginners interested in data
Sep 24, 2020 rated it it was ok
I'm a huge fan of Nathan Yau's blog which is also why I picked up this book.

Unfortunately, the target audience for this one seem to be everyone on the other end of the spectrum from myself - i.e. anyone but data science/analytics people working with immense and non-static datasets.

*If this was my introduction to dataviz: 5 stars*

Great for:
- tips for transferring your ad hoc reporting from excel to any other environment (Tableau, js etc)
- learning dataviz in R
- understanding the where when why
Jun 26, 2018 rated it liked it
I didn’t learn a ton from this book, but there were a few interesting examples. Also it feels a bit dated with some of the examples and technologies employed (though that’s the nature of the discipline).
Alok Pepakayala
Great read to finish in one go, most of the code examples and tech stack is outdated for today but still holds its value and the author keeps the prose skinny to the bone. Its a cross between a textbook and coffee table flip through.
Sweemeng Ng
Jan 23, 2019 rated it really liked it
Some of the tools is out dated. But it is still good insight on what is going on behind making data viz.
Kevin Goldsmith
Jul 10, 2020 rated it liked it
Good introductory book, but the code examples and discussion have not aged well.
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 09, 2011 rated it really liked it
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
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
Jul 04, 2012 rated it liked it
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
Yahia El gamal
May 15, 2015 rated it liked it
Shelves: data-related
The idea of writing this book is really good. Having a book to fill the gap between heavy-on-code tutorials of a visualization tool(s) and purely theoretical, conceptual, have-no-idea-how-to-create-those-examples books. But the book fails in the former side.

I would have at least given it 4 stars if it used a proper set of tools. The book is using base-r for plotting (which no one who is taking visualization seriously should use in the presence of ggplot). And is using Flash (Action Script stuff)
Jan 26, 2012 rated it it was amazing
Shelves: data-analysis
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
Mar 01, 2014 rated it really liked it
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
Jan 05, 2017 rated it liked it
Great beginner text, but potentially a little dated now (flash anyone?). The narrative and observations however are well communicated and timeless. A little put off by the constant jumping between tool sets. includes R and python (horray!) but also provis, illustrator and tableau and *cough* action script and flash. Further complicated by the fact he keeps pushing the reader to take the output of all these tools and 'perk them up' in illustrator at the end of every chapter. 2009 was a while ago, ...more
Mar 01, 2013 rated it it was amazing
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
Jan 26, 2014 rated it it was ok
Shelves: technical
It's probably an OK book for people who has not done any data visualization before. But then, even so, you might want to pick up another book that is better organized in the basics and foundational knowledge than this one, which is pieced together by examples where no obvious logic can be detected on how they are really put together, even with those chapter titles. I recommend anybody from any level to try to skip this book. It's no better than the blog posts that are already freely available at ...more
Brian Kelly
May 04, 2014 rated it liked it
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.
Dec 17, 2011 rated it really liked it
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 ...more
Derrick Schneider
Jan 29, 2012 rated it really liked it
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.
Mick Bordet
Mar 17, 2012 rated it really liked it
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.
Tyler Simonds
Nov 16, 2013 marked it as stopped-reading
Shelves: non-fiction
Outdated already. I started this book, and the first major chunk is just about different programs and websites related to data visualization. I spent over an hour installing Python and troubleshooting because the author's directions weren't very clear and didn't quite work. (Though back in 2011 it may have been easier.) Got stuck :P ...more
Jun 07, 2015 rated it it was amazing
A very good beginner's guide to data visualization, with an easy-to-read and fun writing style.
I liked that the author touches all basic concepts with concrete examples and I think this book can be a good source of inspiration for digging deeper later on. The programming code is also very useful, as well as the tips and notes that the writer gives.
Eric Bell
Jan 13, 2013 rated it liked it
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.
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dubious 1 6 Feb 07, 2013 11:45PM  

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