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Data Points: Visualization That Means Something (Anglais) Broché – 12 avril 2013

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Description du produit

Revue de presse

A detailed handbook, Data Points is espe­cially useful for those working on scientific data visualization, guiding the reader through fascinat­ing examples of data, graph­ics, context, presentation and analytics. But this is more than a mere how–to manual. Yau reminds us that the real purpose of most visualiza­tion work is to communicate data to pragmatic ends. (Nature, May 2013)

Ultimately, I would recommend this book for anyone interested in the process of design and analysis. It is about making sense of data and that is becoming a crucial skill in this digital age. (Madia Information & Technology Journal, August 2013)

Data Points opens an exciting view of information blending data analysis, visual interaction, and digital storytelling the visuals are stunning. (Managing Information, October 2013)

Présentation de l'éditeur

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, 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.

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Format: Broché Achat vérifié
Le livre est inspirant mais ULTRA basique. Si vous connaissez son blog, vous y trouverez rien de neuf. Il s'adresse aux personnes qui ont l'habitude de travailler avec des graphiques basiques et on envie de se faire une idée sur les alternatives plus sexy (i.e. qui suscitent les émotions et la curiosité).
Pour ma part se fut une lecture plaisante et parfois amusante mais où j'ai très peu appris.... J'attendais beaucoup plus de cette lecture....
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Commentaires client les plus utiles sur (beta) (Peut contenir des commentaires issus du programme Early Reviewer Rewards) 3.9 étoiles sur 5 33 commentaires
120 internautes sur 130 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 Perfect for the RIGHT AUDIENCE! But Pros Beware... 9 avril 2013
Par Let's Compare Options Preptorial - Publié sur
Format: Broché Achat vérifié
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:


--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).


--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.

--You're, again, looking for VISUAL ideas to supercharge your presentations, NOT programming tips or even English advice on details. ONE EXCEPTION to this volume compared to Yau's last book: there ARE a good number of example visuals by artists other than Yau (although his are still astonishing), and in THOSE CASES, the author does give the website. In some cases, these are just bigger online pictures of the graphics, in others, there actually is an explanation of the techniques.

Now, for the good stuff. If you KNOW that this book is NOT for pros, you won't buy it, then downstar it because you're disappointed. JUST DON'T WASTE YOUR MONEY if you are looking for comparisons between R and visual basic, steps on translating LaTex and PostScript to .jpg, etc. The level of technical advice amounts to: "R is being used by more and more researchers and statisticians" (and that not until p. 283 of 290). There ARE a number of examples of open source and other software like indiemapper, GeoCommons, ArcGIS, Gephi, Imageplot, Treemap, Tilemill, etc. but the author only mentions them, and leaves you the autodidactic task of figuring out, for example, which do and don't work with Python, RSS, PHP, HTML5 and other pertinent questions pros would ask. But think about this: if you ARE very new to presentation, these tips WILL be eye openers and of great value, as you could surf for hours and not be able to compare or value what's worth it and not. At least beginners get a head start on what this very experienced statistician and author USED throughout the book.

The biggest problem I saw with previous reviews is that the purchasers seemed to expect detailed explanations of how the author created the stunning graphics. This is NOT that book. The software is still not always mentioned with each visual, and steps are really NEVER given that detail "how to" get that effect, let alone scripting, code, or even pseudocode. The book is truly more of a coffee table text showing best practices, as an artist would, but not giving a tutorial on techniques. I know you've watched some tutorials on YouTube that are really "show off" steps by the programmer, with no real intention to show you how to do it. This isn't that bad, as it does have many important "rules of thumb," especially on mistakes to avoid if you're a novice.

So, people who say this is a must buy, or people who say this is a waste of money are both wrong. The solution to that axis of opinion is an intesecting plane visual-- if you're relatively new, don't expect technical detail, and love to get visual ideas and inspiration, you won't go wrong with this volume. If you're expecting to learn tricks and tips in R vs. Excel, get dashboard and data texts on those specific programs instead, and you'll be much happier. Expect a lot of beauty, but not how to get there!!!

Library Picks reviews only for the benefit of Amazon shoppers and has nothing to do with Amazon, the authors, manufacturers or publishers of the items we review. We always buy the items we review for the sake of objectivity, and although we search for gems, are not shy about trashing an item if it's a waste of time or money for Amazon shoppers. If the reviewer identifies herself, her job or her field, it is only as a point of reference to help you gauge the background and any biases.
2 internautes sur 2 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 Helpful Book 26 décembre 2013
Par L. M. Keefer - Publié sur
Format: Broché Achat vérifié
Bought this book for my son who requested it. He is a game designer and uses data to discern information about players. He also uses data to present ideas to clients and his boss, co-workers, etc. so wanted something with ideas on different ways to do that. Primarily, he uses data to make other people care about what he's found, and make the data easier to digest, he says.

He found helpful ideas in this book. The graphics are wonderful, quality of the book visually is excellent. The author has a PhD in statistics from UCLA and has a site at FlowingData. Some of the content in this book includes: *discover what data is and what you can learn from it *learn how to explore your data, find the story, and bring it to life *understand visualization that lets you present and express meaning in data *tap into your creative side and determine the most effective way to tell your story *compare tools for exploration and analysis *allow data, the story, and your goals to dictate visualization techniques with geometry, charts, maps, color, art and humor.

This book was helpful for his needs, and he is pleased with it.
2 internautes sur 2 ont trouvé ce commentaire utile 
3.0 étoiles sur 5 Some good ideas and examples 12 juillet 2013
Par Keith Aspinall - Publié sur
Format: Format Kindle Achat vérifié
I enjoyed reading this book overall - it has some very good basics of graphic treatment for data, and studying it would greatly improve the average quality of data display. I had one smallish concern and one larger one. The smaller is that the quality of the kindle ebook graphics were not adequate to read many of the best examples included, however, many were sourced well so I could go to the original works on the web. The bigger one is that this is too much a journeymans book, and misses the opportunity to apply and perhaps go beyond some of the truly inspiring and thoughtful aspects of Edward Tufte's earlier works. Given the avalanche of data we are creating (referred to in this book), it is quite disappointing on new creative ways to deal with their display.

A solidly useful work, hence three stars, but misses its full potential
1 internautes sur 1 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 A great book for beginners and intermediate learners of Visualization 2 mai 2013
Par gnomic - Publié sur
Format: Broché Achat vérifié
This book is packed with information. It starts with the big picture of Visualization and plenty of examples, but quickly focuses on practical information showing what works, what doesn't, and why. I've read it once and am going through it again to pick up the information that I missed the first time. I've had the book for a month, and already 2 people have borrowed it from me and plan to buy a copy for themself.

I also have Yau's first book. This is a better book, both from writing technique and organization and content perspective. The first book had specific code examples, where this book focuses more on high-level concepts that can be applied to all graphics.

I would like to see a one-page tear-out "cheat sheet" summary of the recommendations in future editions.

Obviously recommended. -- also check out if you want to see excerpts and style.
3.0 étoiles sur 5 A solid guide to better presentations with data 14 avril 2016
Par David S. Saunders - Publié sur
Format: Format Kindle Achat vérifié
If you're just starting out in business, our new product manager or a fresh MBA, this is a really good guide for building effective presentations and for new ways to think about data to help ensure that it makes the impact you intend to. If you are been doing data visualization for years, you may not find a lot of new material in here. At the end of the book, there's a chapter on the wide variety of data tools available today. A surprising number of them were brand-new to me and a few of them I put to use right away.
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