Visualizing Data : Exploring and Explaining Data with the Processing Environment - Ben Fry

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Visualizing Data

Exploring and Explaining Data with the Processing Environment

By: Ben Fry

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4 January 2008

At a Glance

No. of Pages
366

Dimensions(cm)
23.5 x 17.5 x 2

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Enormous quantities of data go unused or underused today, simply because people can't visualize the quantities and relationships in it. Using a downloadable programming environment developed by the author, Visualizing Data demonstrates methods for representing data accurately on the Web and elsewhere, complete with user interaction, animation, and more.

How do the 3.1 billion A, C, G and T letters of the human genome compare to those of a chimp or a mouse? What do the paths that millions of visitors take through a web site look like? With Visualizing Data, you learn how to answer complex questions like these with thoroughly interactive displays. We're not talking about cookie-cutter charts and graphs. This book teaches you how to design entire interfaces around large, complex data sets with the help of a powerful new design and prototyping tool called "Processing".

Used by many researchers and companies to convey specific data in a clear and understandable manner, the Processing beta is available free. With this tool and Visualizing Data as a guide, you'll learn basic visualization principles, how to choose the right kind of display for your purposes, and how to provide interactive features that will bring users to your site over and over. This book teaches you:

The seven stages of visualizing data -- acquire, parse, filter, mine, represent, refine, and interact
How all data problems begin with a question and end with a narrative construct that provides a clear answer without extraneous details
Several example projects with the code to make them work
Positive and negative points of each representation discussed. The focus is on customization so that each one best suits what you want to convey about your data set

The book does not provide ready-made "visualizations" that can be plugged into any data set. Instead, with chapters divided by types of data rather than types of display, you'll learn how each visualization conveys the unique properties of the data it represents -- why the data was collected, what's interesting about it, and what stories it can tell. Visualizing Data teaches you how to answer questions, not simply display information.

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You Can Find This Book In

Non-Fiction Mathematics Probability & Statistics Computing & I.T.Digital Lifestyle & Online World: Consumer & User Guides Internet Guides & Online Services Graphical & Digital Media Applications 3D Graphics & Modelling Databases Data Capture & Analysis Computer Programming & Software Development Software Engineering

Operating Systems O'Reilly Booktopia Publisher Services John Wiley & Sons Publishers UK

Preface	p. vii
The Seven Stages of Visualizing Data	p. 1
Why Data Display Requires Planning	p. 2
An Example	p. 6
Iteration and Combination	p. 14
Principles	p. 15
Onward	p. 18
Getting Started with Processing	p. 19
Sketching with Processing	p. 20
Exporting and Distributing Your Work	p. 23
Examples and Reference	p. 24
Functions	p. 27
Sketching and Scripting	p. 28
Ready?	p. 30
Mapping	p. 31
Drawing a Map	p. 31
Locations on a Map	p. 32
Data on a Map	p. 34
Using Your Own Data	p. 51
Next Steps	p. 53
Time Series	p. 54
Milk, Tea, and Coffee (Acquire and Parse)	p. 55
Cleaning the Table (Filter and Mine)	p. 55
A Simple Plot (Represent and Refine)	p. 57
Labeling the Current Data Set (Refine and Interact)	p. 59
Drawing Axis Labels (Refine)	p. 62
Choosing a Proper Representation (Represent and Refine)	p. 73
Using Rollovers to Highlight Points (Interact)	p. 76
Ways to Connect Points (Refine)	p. 77
Text Labels As Tabbed Panes (Interact)	p. 83
Interpolation Between Data Sets (Interact)	p. 87
End of the Series	p. 92
Connections and Correlations	p. 94
Changing Data Sources	p. 94
Problem Statement	p. 95
Preprocessing	p. 96
Using the Preprocessed Data (Acquire, Parse, Filter, Mine)	p. 111
Displaying the Results (Represent)	p. 118
Returning to the Question (Refine)	p. 121
Sophisticated Sorting: Using Salary As a Tiebreaker (Mine)	p. 126
Moving to Multiple Days (Interact)	p. 127
Smoothing Out the Interaction (Refine)	p. 132
Deployment Considerations (Acquire, Parse, Filter)	p. 133
Scatterplot Maps	p. 145
Preprocessing	p. 145
Loading the Data (Acquire and Parse)	p. 155
Drawing a Scatterplot of Zip Codes (Mine and Represent)	p. 157
Highlighting Points While Typing (Refine and Interact)	p. 158
Show the Currently Selected Point (Refine)	p. 162
Progressively Dimming and Brightening Points (Refine)	p. 165
Zooming In (Interact)	p. 167
Changing How Points Are Drawn When Zooming (Refine)	p. 177
Deployment Issues (Acquire and Refine)	p. 178
Next Steps	p. 180
Trees, Hierarchies, and Recursion	p. 182
Using Recursion to Build a Directory Tree	p. 182
Using a Queue to Load Asynchronously (Interact)	p. 186
An Introduction to Treemaps	p. 189
Which Files Are Using the Most Space?	p. 194
Viewing Folder Contents (Interact)	p. 199
Improving the Treemap Display (Refine)	p. 201
Flying Through Files (Interact)	p. 208
Next Steps	p. 219
Networks and Graphs	p. 220
Simple Graph Demo	p. 220
A More Complicated Graph	p. 229
Approaching Network Problems	p. 240
Advanced Graph Example	p. 242
Mining Additional Information	p. 262
Acquiring Data	p. 264
Where to Find Data	p. 265
Tools for Acquiring Data from the Internet	p. 266
Locating Files for Use with Processing	p. 268
Loading Text Data	p. 270
Dealing with Files and Folders	p. 276
Listing Files in a Folder	p. 277
Asynchronous Image Downloads	p. 281
Using openStream() As a Bridge to Java	p. 284
Dealing with Byte Arrays	p. 284
Advanced Web Techniques	p. 284
Using a Database	p. 288
Dealing with a Large Number of Files	p. 295
Parsing Data	p. 296
Levels of Effort	p. 296
Tools for Gathering Clues	p. 298
Text Is Best	p. 299
Text Markup Languages	p. 303
Regular Expressions (regexps)	p. 316
Grammars and BNF Notation	p. 316
Compressed Data	p. 317
Vectors and Geometry	p. 320
Binary Data Formats	p. 325
Advanced Detective Work	p. 328
Integrating Processing with Java	p. 331
Programming Modes	p. 331
Additional Source Files (Tabs)	p. 334
The Preprocessor	p. 335
API Structure	p. 336
Embedding PApplet into Java Applications	p. 338
Using Java Code in a Processing Sketch	p. 342
Using Libraries	p. 343
Building with the Source for processing.core	p. 343
Bibliography	p. 345
Index	p. 349
Table of Contents provided by Ingram. All Rights Reserved.

Visualizing Data

Exploring and Explaining Data with the Processing Environment

At a Glance

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