This is the depth of coding and design that I'm interested in as an analyst, and th This was a very complete book.
This is the depth of coding and design that I'm interested in as an analyst, and this book was perfectly tailored for this function. I'll be keeping it as a reference for when I want to pull out the skills I now have some practice with but might need a refresher on.
One thing I might add is that it's starting to age; there are sections that introduce outdated tools, some code no longer works with updates to languages, and there is the odd broken link.
Jun 26, Eric rated it liked it. 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. While there can be a lot of overlap between these tasks and more dir Visualize This is a book about designing visualizations for data "graphs" more or less, although there are visualizations which are not, strictly speaking, graphs.
While there can be a lot of overlap between these tasks and more directly scientific output, the focus made the book less useful and interesting to me than I had hoped it would be. In some sense, the book is schizophrenic. It talks a lot about visual design, but is more holistic than anything one might consider to be visualization theory.
Since it's not a textbook on their use, I question how useful these examples are for the greater purpose of learning. It tries to be both and, therefore, somewhat fails at both.
It is also a bit overly redundant at times; since many of the chapters were explicitly designed to allow a reader to jump in and read independent of the rest, the same basic tasks and ideas are often introduced in multiple chapters, which is frustrating to someone who sits down to read it cover-to-cover.
This is not to imply the book does not contain useful information, it certainly does. It introduces a decent variety of graph styles, many of which are likely unfamiliar to readers. It does discuss valuable resources of which the reader may be unaware, such as Inkscape a free, open-source alternative to Adobe Illustrator and 0to When it does slip into visualization theory the advice is solid and to the point e. Although I was clearly disappointed in the text and have many criticisms, in the end it has enough advantages to be a worthwhile read, particularly for those who are complete newcomers to visualization or who have a particular interest in data visualization for the web.
Dec 01, Jake Losh rated it liked it Shelves: 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 Visualize This: Aside from the core content revolving around data viz, you'll also get lengthy tutorials on how to write scripts i. It demonstrates nicely how the role of an infographic maker really straddles multiple departments and disciplines, but it also muddles the core of the book somewhat.
The book is using base-r for plotting which no one who is taking visualization seriously should use in the presence of ggplot. The book introduces several interesting stepping stones of the process of showing your data more attractively to audience or telling you story better some times at all even. Aside from the core content revolving around data viz, yo Visualize This: Permissions Request permission to reuse content from this site. Dec 17, S. There is too much buffering. Pranav Shukla Get to grips with the new features introduced in Elastic Stack 6.
I found myself constantly skimming through these parts. It would have been great if those parts had been left to the appendices or suggested readings pages. I applaud Nathan Yau for this ambitious undertaking and would highly recommend the book to any of his blog's frequent readers, but would caution that those without any programming or graphic design background be patient and take it slow when reading the book. That's probably best for all of us, in any event. Sep 09, Jonathan Jeckell rated it really liked it Recommended to Jonathan by: 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 This is a nice supplement to the Tufte series, focusing exclusively on data, numeric, and statistical graphics, including animations.
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 seperation in the text between this and how the chart works, when to use it, etc. Because the book is deeply imbued with lines of code and screenshots from Flash editors, you can't just read this book in a linear fashion to see different types of ways of portraying data and their relative merits.
It's more useful as a handbook or reference unless you are good at skimming over parts you aren't ready to experiment with on your own. I'm also a little concerned about how some of the specific instructions will age, and how soon some of this code will hit an expiration date. The code was generic enough that someone with a little programming knowledge can apply it to another they are familiar with, and command line languages can be fairly durable; it's the GUI shots, especially for proprietary software that mostly worries me.
Concerns about the longevity of the usefulness of the practical application tips and the tight integration with the rest of the text aside, this is a very useful book if you work with data or numeric visualization or need to understand complex data better. Jul 04, Gina 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 Yau is best when he talks about data and how to acquire it and about how to present various types of data. 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 than they might.
Small pullout boxes indicating where to go online to get additional information were not always helpful. I was reminded of a book I reviewed for the New York Times at the outset of the internet, just before graphical user interfaces burst on the scene. It was a well done book, too, but made obsolete almost as soon as the review was published. I suspect the same is happening now with visualizations, as new "black box" sites come online every month allowing users to create visualizations from existing datasets, without have to get down and get messy with code.
Not that there's anything wrong with code, just that most people do not have time for it. May 15, Yahia El gamal rated it liked it Shelves: 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 The idea of writing this book is really good. And is using Flash Action Script stuff for interactive graph Which is already dead, and no one who is taking interactive visualization seriously should use in the presence of D3.
I would urge the author to rewrite the book using proper tools, it would be an invaluable book. Having that said, the book is very useful. I think it made me think a little more clearly about the readability and interpretability of the graphics I produce. I recommended this book with a a note, don't follow the code, implement the same graphics with proper tools and you will learn a lot. Jan 26, Ariadna73 rated it it was amazing Shelves: 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! 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 I have been reading it with real attention and I have not skipped a single paragraph since the begining.
I'll see if it continues this wonderful way Check my blog entry out: Mar 01, Chris 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 Decided to quickly read this over the weekend.
Nathan Yau also presents his background in data journalism a bit better in this book. Overall, not a bad book, though intermediate Python and R programmers will probably not pick that much up maybe a few libraries. Jan 05, David 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. 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. Mar 01, Leslie 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. Would you like to change to the site?
Visualize This: The FlowingData Guide to Design, Visualization, and Statistics [ Nathan Yau] on uzotoqadoh.tk *FREE* shipping on qualifying offers. Practical. Visualize This: The FlowingData Guide to Design, Visualization, and Statistics Nathan Yau is a PhD candidate in Statistics at UCLA and a lifelong data junkie.
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.
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. Request an Evaluation Copy for this title. Visualization That Means Something.