PDF Ebook Visualizing Data: Exploring and Explaining Data with the Processing Environment
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Visualizing Data: Exploring and Explaining Data with the Processing Environment
PDF Ebook Visualizing Data: Exploring and Explaining Data with the Processing Environment
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About the Author
Ben Fry received his doctorate from the Aesthetics + Computation Group at the MIT Media Laboratory and was the 2006-2007 Nierenberg Chair of Design for the Carnegie Mellon School of Design. He worked with Casey Reas to develop Processing, which won a Golden Nica from the Prix Ars Electronica in 2005. Ben's work has received a New Media Fellowship from the Rockefeller Foundation, and been shown at the Museum of Modern Art, Ars Electronica, the 2002 Whitney Biennial and the 2003 Cooper Hewitt Design Triennial.
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Product details
Paperback: 384 pages
Publisher: O'Reilly Media; 1 edition (January 11, 2008)
Language: English
ISBN-10: 0596514557
ISBN-13: 978-0596514556
Product Dimensions:
7 x 0.6 x 9.2 inches
Shipping Weight: 1.6 pounds (View shipping rates and policies)
Average Customer Review:
4.2 out of 5 stars
31 customer reviews
Amazon Best Sellers Rank:
#119,806 in Books (See Top 100 in Books)
IF you are using the Processing IDE and API, and if you are new to producing graphicaldisplays of data, then I can think of no better book for you than this one. It discussesthe why as well as the how, and provides code examples and some images of the results.What I liked about this book, beside the concrete examples, are the discussions abouthow to think about each step of the process from selecting the data through to the finalstep of refining the display. There are issues that are not obvious to the graphicaldisplay newbie, and they are brought up, and a good approach given.On the other hand, if you are a programmer who is already writing sophisticatedgraphical displays, and looking for a language neutral book on general design, thenthis will probably not be a satisfying purchase.
You know this is a book on Processing, and gives great copy and paste examples. The only thing I don't like, is that some of the examples don't work. Like handling different tabs or sketches that use the same function code like, public draw() in the umbrella host sketch and draw() on the other sketch, because the program won't work.
It's important to remember that this book is not as general as it first appears. The discussions in it can be applied to another environment like Matlab or R, but not the examples. However, it is not merely a Processing tutorial. It does a good job of layout out the stages that one must go through in the process of creating a visualization from a dataset. Fry lays out the basic steps at the beginning, then goes through them repeatedly in a number of very different applications. Following along is relatively easy, though I really wish the author had provided a single URL to go get everything rather than give out URLs piecemeal throughout the book.I should repeat that this is not merely a Processing tutorial. If it were, it would fall short on a number of counts, including using a number of commands without adequately explaining them, and omitting discussion of things that a Processing programmer is likely to need to know. This is still a good introduction to the language, though (it was my introduction) and offers enough insight into what the language and environment can do without getting too bogged down in the mechanics or design philosophy.
Processing captured my attention a few months back. I'm a UXer / wannabe artist who is new to programming, and I was immediately smitten with the visual art and data visualizations that I saw for Processing. I thought that this could be the tool fun enough and visual enough to teach me the principles of programming while making useful things relevant to my work. I've read several books on Processing, and, while I've found all of them helpful and fun (especially in regard to learning the ins and outs of the language and environment), this one has helped me put my skills to the test more than the others, mostly because I can't help but imagine different possibilities as I work through the tutorials. There are better ways and worse ways to represent data, and there are clear objectives that I'm trying to reach, unlike my experiences with visual art and Processing where I can let myself get away with almost anything. Luckily, Fry's got it figured out, and the examples are both pleasant looking and fun to interact with. Going through this book has been a joy, and I'm building my repertoire of code that I'm sure will prove useful in future projects. Maybe after I learn a bit more I'll be able to create art with confidence, but, for now, this is a lot of fun.
If you are looking at getting into the processing programming language, this book is tops. If you are looking to learn more about how to generally visualize data (types, best practice, etc) then this book may not be it.I bought the book after reading the first chapter at Adobe MAX 2008 and then just ordered it from Amazon. To my surprise (both good and a little disappointing) the book was truly about the processing programming language.Overall the book is very well written and I got to dabble a little in the coding to create some of the visuals. Once I figure out the things on my plate (work and personal) I will probably come back and try to see if processing is right for me and my projects.
Processing looks like a very powerful tool and this book serves as a good introduction to both programming and computer visuals. It's nicely paced but if you are a professional software engineer looking to harness processing you will find yourself skimming the whole book in search for advanced material.In particular the use of java for a whole lot of tasks including text parsing and data mining leads to very tedious and verbose code where a few lines of perl or awk would have done the job.Overall this is a good book if you are somewhat new to programming. Else this will make for too short a read.
Very lucidly written, easy to understand. Even though I've moved on from Processing, I'm still benefiting from the basics of data organization and setup that are essential before we can actually visualize it. Specifically, it gives a fairly good idea of how data frames should be constructed and what functions it should have that make them versatile, once they've been setup.
works perfectly
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