Visualizing Data by Fry, Ben -- Read -- Imperial Library of Trantor

Index

Visualizing Data

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The Audience for This Book Background Information Overview of the Book Safari® Books Online Acknowledgments Conventions Used in This Book Using Code Examples We'd Like to Hear from You

1. The Seven Stages of Visualizing Data

Why Data Display Requires Planning

Too Much Information Data Collection Thinking About Data Data Never Stays the Same What Is the Question? A Combination of Many Disciplines Process

An Example

What Is the Question?

Acquire Parse Filter Mine Represent Refine Interact

Iteration and Combination Principles

Each Project Has Unique Requirements Avoid the All-You-Can-Eat Buffet Know Your Audience

Onward

2. Getting Started with Processing

Sketching with Processing

Hello World Hello Mouse

Exporting and Distributing Your Work

Saving Your Work

Examples and Reference

More About the size( ) Method Loading and Displaying Data

Functions

Libraries Add New Features

Sketching and Scripting

Don't Start by Trying to Build a Cathedral

Ready?

3. Mapping

Drawing a Map

Explanation of the Processing Code

Locations on a Map Data on a Map

Two-Sided Data Ranges Provide More Information with a Mouse Rollover (Interact) Updating Values over Time (Acquire, Mine) Smooth Interpolation of Values over Time (Refine)

Using Your Own Data

Taking Data from the User

Next Steps

4. Time Series

Milk, Tea, and Coffee (Acquire and Parse) Cleaning the Table (Filter and Mine) A Simple Plot (Represent and Refine) Labeling the Current Data Set (Refine and Interact) Drawing Axis Labels (Refine)

Year Labels Labeling Volume on the Vertical Axis Bringing It All Together and Titling Both Axes

Choosing a Proper Representation (Represent and Refine) Using Rollovers to Highlight Points (Interact) Ways to Connect Points (Refine)

Showing Data As an Area Further Refinements and Erasing Elements Discrete Values with a Bar Chart (Represent)

Text Labels As Tabbed Panes (Interact)

Adding the Necessary Variables Drawing Tabs Instead of a Single Title Handling Mouse Input Better Tab Images (Refine)

Interpolation Between Data Sets (Interact) End of the Series

5. Connections and Correlations

Changing Data Sources Problem Statement Preprocessing

Retrieving Win/Loss Data (Acquire)

Data source for baseball statistics

Unpacking the Win/Loss files (Mine and Filter)

Introducing regular expressions

Retrieving Team Logos (Acquire, Refine) Retrieving Salary Data (Acquire, Parse, Filter)

Using the Preprocessed Data (Acquire, Parse, Filter, Mine)

Team Names and Codes Team Salaries Win-Loss Standings Team Logos Finishing the Setup

Displaying the Results (Represent) Returning to the Question (Refine)

Highlighting the Lines A Better Typeface for Numeric Data A Word About Typography

Sophisticated Sorting: Using Salary As a Tiebreaker (Mine) Moving to Multiple Days (Interact)

Drawing the Dates Load Standings for the Entire Season Switching Between Dates Checking Our Progress

Smoothing Out the Interaction (Refine) Deployment Considerations (Acquire, Parse, Filter)

6. Scatterplot Maps

Preprocessing

Data from the U.S. Census Bureau (Acquire) Dealing with the Zip Code Database File (Parse and Filter) Building the Preprocessor

What about a binary data file or a database?

Loading the Data (Acquire and Parse) Drawing a Scatterplot of Zip Codes (Mine and Represent) Highlighting Points While Typing (Refine and Interact) Show the Currently Selected Point (Refine) Progressively Dimming and Brightening Points (Refine) Zooming In (Interact) Changing How Points Are Drawn When Zooming (Refine) Deployment Issues (Acquire and Refine) Next Steps

7. Trees, Hierarchies, and Recursion

Using Recursion to Build a Directory Tree

Caveats When Dealing with Files (Filter) Recursively Printing Tree Contents (Represent)

Using a Queue to Load Asynchronously (Interact)

Showing Progress (Represent)

An Introduction to Treemaps

A Simple Treemap Library A Simple Treemap Example

Which Files Are Using the Most Space?

Reading the Directory Structure (Acquire, Parse, Filter, Mine, Represent)

Viewing Folder Contents (Interact) Improving the Treemap Display (Refine)

Maintaining Context (Refine) Making Colors More Useful (Mine, Refine)

Flying Through Files (Interact)

Updating FileItem for zoom Updating FolderItem Adding a Folder Selection Dialog (Interact)

Next Steps

8. Networks and Graphs

Simple Graph Demo

Porting from Java to Processing Interacting with Nodes

A More Complicated Graph

Using Text As Input (Acquire) Reading a Book (Parse) Removing Stop Words (Filter) Smarter Addition of Nodes and Edges (Mine) Viewing the Book (Represent and Refine) Saving an Image in a Vector Format Checking Our Work

Approaching Network Problems Advanced Graph Example

Getting Started with Java IDEs

Step-by-step instructions if you're new to Eclipse

Obtaining a Web Server Logfile (Acquire) Reading Apache Logfiles (Parse) A Look at the Other Source Files Moving from Processing to Java

Helpful additions in Java 1.5 (J2SE 5.0) and later

Reading and Cleaning the Data (Acquire, Parse, Filter)

Filtering site addresses and aliases Filtering for useful page information

Bringing It All Together (Mine and Represent)

Mining unused nodes: Maintaining performance and readability

Depicting Branches and Nodes (Represent and Refine) Playing with Data (Interact) Drawing Node Names (Represent and Refine) Drawing Visitor Paths (Represent and Refine)

Mining Additional Information

9. Acquiring Data

Where to Find Data

Data Acquisition Ethics

Tools for Acquiring Data from the Internet

Wget and cURL NcFTP and Links

Locating Files for Use with Processing

The Data Folder Uniform Resource Locator (URL) Absolute Path to a Local File Specifying Output Locations

Loading Text Data

Files Too Large for loadStrings( ) Reading Files Progressively Reading Files Asynchronously with a Thread Parsing Large Files As They Are Acquired

Dealing with Files and Folders

Using the Java File Object to Locate Files

Listing Files in a Folder

Listing files with a filter class Sorting file lists

Handling Numbered File Sequences

Asynchronous Image Downloads Using openStream( ) As a Bridge to Java Dealing with Byte Arrays Advanced Web Techniques

Handling Web Forms Pretending to Be a Web Browser

Using a Database

Getting Started with MySQL Using MySQL with Processing Other Database Options Performance Aspects of Databases in Interactive Applications

Dealing with a Large Number of Files

10. Parsing Data

Levels of Effort Tools for Gathering Clues Text Is Best

Tab-Separated Values (TSV) Comma-Separated Values (CSV) Text with Fixed Column Widths

Text Markup Languages

HyperText Markup Language (HTML)

Embedding Tidy into a sketch Is a parser necessary? Using Swing's built-in HTML parser Parsing and manipulating tables from HTML files Other HTML parser libraries Writing a custom HTML parser

Extensible Markup Language (XML)

Cleaning up XML Example: Using the Processing XML library to read geocoding data Other methods for parsing XML

JavaScript Object Notation (JSON)

Regular Expressions (regexps) Grammars and BNF Notation Compressed Data

GZIP Streams (GZ)

PKZip files (ZIP) Other compression formats

Vectors and Geometry

Scalable Vector Graphics (SVG) OBJ and AutoCAD DXF PostScript (PS) and Portable Document Format (PDF) Shapefile and Well-Known Text

Binary Data Formats

Excel Spreadsheets (XLS) dBASE/xBase (DBF) Arbitrary Binary Formats Bit Shifting DataInputStream

Advanced Detective Work

Watching Network Traffic

11. Integrating Processing with Java

Programming Modes

Basic Continuous Java

Additional Source Files (Tabs)

Using .java Source Files

The Preprocessor API Structure

Event Handling The size( ) Method The main( ) Method The frame Object

Embedding PApplet into Java Applications

Two Models for Updating the Screen Embedding in a Swing Application

Using Java Code in a Processing Sketch

Using the Code Folder to Add .jar Files to a Sketch Packaging Code into Libraries

Using Libraries Building with the Source for processing.core

Bibliography

Acquire and Parse

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