DATA POINTS VISUALIZATION THAT MEANS SOMETHING PDF
Data Points: Visualization That Means Something. ExECUTIVE EDITOR: Carol Long. SENIOR PROJECT EDITOR: Adaobi Obi Tulton. TECHNICAL EDITOR: Jen . Data Points: Visualization That Means Something [Nathan Yau] on resourceone.info *FREE* shipping on qualifying offers. A fresh look at visualization from the. In Data Points: Visualization That Means Something, author Nathan Yau presents an intriguing complement to his bestseller Visualize This, this time focusing on.
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Data Points book. Read 35 reviews from the world's largest community for readers. A fresh look at visualization from the author of Visualize ThisWhethe. [PDF] DOWNLOADData Points: Visualization That Means this book Data Points : Visualization That Means Something A fresh look at. When you visualize data, you represent it with a combination of visual cues that are top right of a two-dimensional space mean something different than dots in.
It is so well organized and provides exactly the sort of foundation I was looking for to data visualization.
I've already started noticing new sorts of things when I look at infographics. Data Points gives a good overview of the "spectrum that stretches from statistical graphics to data art," and provides a lot of useful generalized advice. I plan to read Visualize T Yes, as commenters have alluded to, some of the charts are a little small. I plan to read Visualize This next since it seems to be more hands-on and in-depth.
However, it is not as good as many others books on the topic: Tufte is my pick for the best The Visual Display of Quantitative Information , and his book is much better produced than Data Points. Data Points often has illegible plots, blurry printing on some figures, an inconvenient choice of book binding for dual-page printing, and a rushed feeling when it comes to organization, layout, and narrative.
Tufte, b This book is a good summary and overview of the current state of data visualization. Tufte, by contrast, clearly spent ages laying out every page and even admits to adjusting his phrasing so that his sentences lined up nicely on the printed page.
There is also very little how-to; if you know a bit about data viz, you may with to skim Stephen Few's books Intelligent Dashboard Design is good, especially the last chapter, and is nearly as well-produced as Tufte's books. Yau's work seems more intended for a web-centric audience, and would likely be better served as an online resource which it may well be or an interactive e-book. Data Points' main strength lies in its visual breadth.
Physically, the book and graphs are beautiful; there are some really beautiful graphs Nathan Yau is the heir to Edward Tufte when it comes to data visualization and graphics so anyone who is serious about that field needs to read his work. Physically, the book and graphs are beautiful; there are some really beautiful graphs here wind map, for one. So, nothing earth shaking but helpful around the margins. I am going to go try out some star charts tomorrow, for instance.
Most people would probably get something from the book.
Data Points: Visualization That Means Something
Jul 19, Robert Muller rated it really liked it. This is a beautifully produced book with lots of great ideas for visualizing data.
I personally thought the balance was a little off--there's almost nothing about how to actually create some of these quite complex graphics I think there's another book by the same author that goes deeper into this.
It's also a little light on the analytic and exploratory aspects of graphics as opposed to the communicative and visual aspects. But the charts showing how to compose graphics from the basic componen This is a beautifully produced book with lots of great ideas for visualizing data.
But the charts showing how to compose graphics from the basic components are worth the price of the book. I would also highly recommend Bertin's Semiology of Graphics, which does much the same thing but with a much more comprehensive theory underlying the choices. Jan 28, Ilinalta rated it really liked it. A great resource and textbook for learning how to analyze data and how to design visualizations to help communicate what the data is trying to say.
The writing has a great voice, which made it entertaining to read. And all the examples were inspiring, intriguing, and insightful.
It's pretty difficult to fully finish reading a textbook, but I did my best. I got the information I needed from it and that's good enough for me. Not to mention, I took a class on the fundamentals that Nathan Yau discus A great resource and textbook for learning how to analyze data and how to design visualizations to help communicate what the data is trying to say.
Not to mention, I took a class on the fundamentals that Nathan Yau discuss, so much of this book was review for me. Sep 09, waitsforsleep rated it liked it. This book is a good-enough collection of data viz common sense.
The glossy print and vast collection of interesting charts are nice however I was disappointed that the xkcd radiation chart did not get a mention. The fact that the author did not appear to follow his own advice regarding flow of narrative was ironic. The book had me flipping forward multiple times to see the chart that was being talked about. The discussion about tools was too brief and left me wanting. All in all its a good-enough This book is a good-enough collection of data viz common sense.
All in all its a good-enough primer for anyone interested in visualization. Feb 17, Chris rated it really liked it. I think this leans Edward Tufte, but with a more statistic type mindset and a little less art driven.
The book is also split into sections a bit better.
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It's mostly focused on how to interpret data and visualize it. Part of two books I've purchased, the other one being visualize this. It lacked some organization issues and felt like I occasionally was reading the same thing. Overall, not a bad read, though a lot of overlap with Edward Tufte and Stephen Few. Aug 16, Nelson Minar rated it liked it. Good solid introduction to the art of data visualization. Lots of nice examples and exploration of the various questions a data designer should ask themselves.
It's an introductory book, I felt I knew most of what I was reading already and I'm no expert. But it's not a hands-on book in any way, it's something you passively read and learn from. So for someone learning visualization this needs to be paired with implementation exercises.
Aug 21, Christopher rated it liked it.
I agree with the author maybe 50 per cent of the time. Many of the examples aren't my cup of tea. Notwithstanding the above, the book is interesting and puts forward a mostly common sense approach..
I wouldn't rely on it wholly but think the book wd complement the current collection of texts on the topic.
Apr 28, Jordan Munn rated it really liked it. Nice exploration of and discussion around the process of creating data visualizations. While there's nothing super mind-blowing in the book, I appreciated the willingness to talk through the thought process and resulting effects of different variations on the same basic visualization.
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The discussion, even around really basic fundamentals, contained some thoughtful and nuanced observations. Jul 22, Sergii Khomenko rated it really liked it. Lots of really nice looking data visualisations, explained core concept of human-understandable visualisations and other topics. Good introduction into data visualisation world with good ideas and historical insights.
May 14, Gavin rated it liked it. Great book about the fundamentals of data visualization. Even for seasoned data visualization artists, there are several useful ideas about how to think about data visualization and infographics.
Jun 16, Finlay rated it liked it Shelves: A good, solid, overview of creating meaningful visualizations. There is much more detail in books like "Grammar of Graphics", "Semiology of Graphics", or any of Tufte's work, but this one pulls the basics together in one place, with good looking examples.
Jun 27, vanch rated it really liked it. Jul 06, Matthew rated it liked it. Good, but I skimmed through several sections that weren't really all that new or interesting to me. Oct 17, Stanley rated it really liked it. Easy to read and very easy on the eyes. A simple and practical introduction to do-it-yourself visualization.
Nice introduction. Apr 16, Oliver Bogler rated it liked it. Nicely illustrated and good at covering the basics. Gives some good advice. Quite a bit of it felt fairly intuitive, but perhaps useful to the novice. May 04, Lisa rated it it was amazing. One of the best data visualization books out there for those just beginning to explore what data visualization can do. Nov 05, Sean rated it liked it. Slightly redundant after reading Visualize This, but still very enlightening.
Again, cool results can be had with the programming examples in the book, sometimes surprising in their coolness. O'Reilly Media, Visualization is the graphic presentation of data - portrayals meant to reveal complex information at a glance.
Think of the familiar map of the New York City subway system, or a diagram of the human brain. Successful visualizations are beautiful not only for their aesthetic design, but also for elegant layers of detail that efficiently generate Springer, This book was written for statisticians, computer scientists, geographers, researchers, and others interested in visualizing data.
It presents a unique foundation for producing almost every quantitative graphic found inA typical use of bar charts would be visitor traffic from top referral websites. Use multi-axes charts if you want to: Display a line chart and a column chart with the same X-axis. Countless innovations fail because their champions use PowerPoint the way Microsoft wants them to, instead of the right way.
John Tukey  Professor Edward Tufte explained that users of information displays are executing particular analytical tasks such as making comparisons. Nathan Yau has a PhD in statistics and is a statistical consultant who helps clients make use of their data through visualization. Bubble Charts A bubble chart is a great option if you need to add another dimension to a scatter plot chart.
It can get messy very quickly. Description Evaluation Copy FlowingData.