visualizing data（PDF download）

Preface

When I show visualization projects to an audience, one of the most common ques- tions is,"How do you do this?" Other books about data visualization do exist. but the most prominent ones are often collections of academic papers; in any case,few explain how to actually build representations. Books from the field of design that offer advice for creating visualizations see the field only in terms of static displays, ignoning the possibility of dynamic,software-based visualizations. A number spend most of their time dissecting what's wrong with given representations—sometimes providing solutions, but more often not.

In this book,I wanted to offer something for people who want to get started build- ing their own visualizations, something to use as ajumping-off point for more com- plicated work. I don't cover everything, but I've tried to provide enough background so that you'll know where to go next.

I wrote this book because I wanted to have a way to make the ideas from Computational Information Design, my Ph.D.dissertation, more accessible to a wider audience. More specifically,I wanted to see these ideas actually applied, rather than limited to an academic document on a shelf. My dissertation covered the process of getting from data to understanding; in other words,from considering a pile of infor- mation to presenting it usefully, in a way that can be easily understood and inter- acted with. This process is covered in Chapterl,and used throughout the book as a framework for working through visualizations.

Most of the examples in this book are written from scratch. Rather than relying on toolkits or libraries that produce charts or graphs, instead you learn how to create them using a little math, some lines and rectangles, and bits of text. Many readers may have tried some toolkits and found them lacking, particulary because they want to customize the display of their information. A tool that has generic uses will pro- duce only generic displays, which can be disappointing if the displays do not suit your data set. Data can take many interesting forms that require unique types of dis- play and interaction;this book aims to open up your imagination in ways that collec- tions of bar and pie charts cannot.

This book uses Processing (http:/processingorg),a simple programming environ- ment and API that I co-developed with Casey Reas of UCLA.Processing's program- ming environment makes it easy to sit down and "sketch"code to produce visual images quickly.Once you outgrow the environment,it's possible to use a regular Java IDE to write Processing code because the APIis based onJava. Processingis free to download and open source.It has been in development since 2001,and we've had about 100,000 people try it out in the last 12 months. Today Processing is used by tens of thousands of people for all manners of work. When I began writing this book, I debated which language and API to use. It could have been based on Java, but I realized I would have found myself re-implementing the Processing API to make things simple. It could have been based on Actionscript and Flash.but Flash is expensive to buy and tends to break down when dealing with larger data sets. Other scripting languages such as Python and Ruby are useful, but their execution speeds don't keep up with Java.In the end,Processing was the right combination of cost, ease of use, and execution speed.

The Audience for This Book

In the spring of 2007,I co-taught an Information Visualization couse at Carnegie Mellon. Our 30 students ranged from a freshman in the art school to a Ph.D.candi date in computer science. In between were graduate students from the School of Design and various other undergrads. Their skill levels were enormously vanied, but that was less important than their level of curiosity, and students who were curious and willing to put in some work managed to overcome the technical difficulties (for the art and design students)or the visual demands(for those with an engineering background).

This book is targeted at a similar range of backgrounds, if less academic. I'm trying to address people who want to ask questions, play with data,and gain an under- standing of how to communicate information to others. For instance, the book is for web designers who want to build more complex visualizations than their tools will allow. It's also for software engineers who want to become adept at writing software that represents data—that calls on them to try out new skills, even if they have some background in building Uls. None of this is rocket science, but it isn't always obvi ous how to get started.

Fundamentally,this book is for people who have a data set, a curiosity to explore it, and an idea of what they want to communicate about it. The set of people who visu- alize data is growing extremely quickly as we deal with more and more information. Even more important. the audience has moyed far bevond those who are experts in visualization.By making these ideas accessible to a wide range of people, we should see some truly amazing things in the next decade.

Background Information

Because the audience for this book includes both programmers and non- programmers, the matenial varies in complexity. Beginners should be able to pick it up and get through the first few chapters,but they may find themselves lost as we get into more complicated programming topics.If you're looking for a gentler introduc- tion to programming with Processing, other books are available(including one writ- ten by Casey Reas and me)that are more suited to learning the concepts from scratch, though they don't cover the specifics of visualizing data. Chapters l-4 can be understood by someone without any programming background, but the later chapters quickly become more difficult.

You'll be most successful with this book if you have some familianity with writing code—whether it's Java, C++,or Actionscript. This is not an advanced text by any means, but a little background in writing code will go a long way toward understand. ing the concepts.

Overview of the Book

Chapter l, The Seven Stages of Visualizing Data, covers the process for developing a useful visualization, from acquiring data to interacting with it.This is the framework we'll use as we attack problems in later chapters.

Chapter 2, Getting Started with Processing, is a basic introduction to the Processing environment and syntax. It provides a bit of background on the structure of the API and the philosophy behind the project's development.

Chapters 3 through 8 cover example projects that get progressively more complicated.

Chapter3, Mapping, plots data points on a map,our fist introduction to reading data from the disk and representing it on the screen.

Chapter 4, Time Series,covers several methods of plotting charts that represent how data changes over time.

Chapter5, Connections and Correlations, is the first chapter that really delves into how we acquire andparse a data set. The example in this chapter reads data from the MLB.com web site and produces an image correlating player salaries and team per- formance over the course of a baseball season. It's an in-depth example illustrating how to scrape data from a web site that lacks an official API.These techniques can be applied to many other projects,even ifyou're not interested in baseball

Chapter 6,Scatterplot Maps,answers the question,"How dozip codes relate togeog- raphy?"by developing a project that allows users to progressively refine a U.S.map as they type a zip code.

Chapter7,Trees, Hierarchies, and Recursion, discusses trees and hierarchies.It cov- ers recursion,an important topic when dealing with tree structures, and treemaps,a useful representation for certain kinds of tree data.

Chapter 8,Networks and Graphs, is about networks of infommation, also called graphs. The first half discusses ways to produce a representation of cnnections betwen many nodes in a network, and the second half shows an example of doing the same with web site traffic data to see how a site is used over time. The latter project also covers how tointegrate Processing with Eclipse,a Java IDE.

The last three chapters contain reference material,including more background and techniques for acquiring and parsing data.

Chapter9, Acquiring Data, is a kind of cookbook that covers all sorts of practical techniques,from reading data from files,to spoofing a web browser,to storing data in databases.

Chapter 10,Parsing Data,is also written in cookbook-style, with examples that illus- trate the detective work involved in parsing data.Examples include parsing HTML tables,XML, compressed data, and SVG shapes. It even includes a basic example of watching a network connection to understand how an undocumented data protocol works.

Chapter ll,Integrating Processing with Java,covers the specifics of how the Process- ing API integrates with Java.It's more of an appendix aimed at advanced Java pro- grammers who want touse the API with their own projects.

CHAPTER 1

TheSeven Stages of Visualizing Data

What do the paths that millions of visitors take through a web site look like? How do the 3.1 billion A, C, G,and T letters of the human genome compare to those of the chimp or the mouse? Out of a few hundred thousand files on your computer's hard disk,which ones are taking up the most space,and how often do you use them? By applying methods from the fields of computer science, statistics, data mining, graphic design, and visualization, we can begin to answer these questions in a mean- ingful way that also makes the answers accessible to others.

All of the previous questions involve a large quantity of data, which makes it extremely difficult to gain a "big picture"understanding of its meaning. The prob- lem is further compounded by the data's continually changing nature, which can result from new information being added or older information continuously being refined. This deluge of data necessitates new software-based tools. and its complex- ity requires extra consideration. Whenever we analyze data,our goal is to highlight its features in order of their importance, reveal patterns, and simultaneously show features that exist across multiple dimensions.

This book shows you how to make use of data as a resource that you might other- wise never tap. 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 again.You'll also learn to program in Process- ing,a simple but powerful environment that lets you quickly carry out the tech- niques in this book.You'll find Processing a good basis for designing interfaces around large data sets,but even if you move to other visualization tools,the ways of thinking presented here will serve you as long as human beings continue to process information the same way they've always done.

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