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Wring more out of the data with a scientific approach to
analysis
Graph Analysis and Visualization brings graph theory out
of the lab and into the real world. Using sophisticated methods and
tools that span analysis functions, this guide shows you how to
exploit graph and network analytic techniques to enable the
discovery of new business insights and opportunities. Published in
full color, the book describes the process of creating powerful
visualizations using a rich and engaging set of examples from
sports, finance, marketing, security, social media, and more. You
will find practical guidance toward pattern identification and
using various data sources, including Big Data, plus clear
instruction on the use of software and programming. The companion
website offers data sets, full code examples in Python, and links
to all the tools covered in the book.
Science has already reaped the benefit of network and graph
theory, which has powered breakthroughs in physics, economics,
genetics, and more. This book brings those proven techniques into
the world of business, finance, strategy, and design, helping
extract more information from data and better communicate the
results to decision-makers.
Study graphical examples of networks using clear and insightful
visualizations
Analyze specifically-curated, easy-to-use data sets from
various industries
Learn the software tools and programming languages that extract
insights from data
Code examples using the popular Python programming
language
There is a tremendous body of scientific work on network and
graph theory, but very little of it directly applies to analyst
functions outside of the core sciences - until now. Written
for those seeking empirically based, systematic analysis methods
and powerful tools that apply outside the lab, Graph Analysis
and Visualization is a thorough, authoritative resource.
Auteur
Richard Brath is actively involved in the research,
design, and development of data visualization and visual analytics
for both research and commercial applications for some of the
world's largest companies and top software vendors. His
solutions range from rich, interactive visualizations for mobile
devices, to large multi-touch, multi-screen installations and
web-based analytical visualizations for business applications.
David Jonker is a designer and developer of visualization
platforms and applications for web-based, distributed, desktop, and
mobile use. He created visualization products for NASDAQ MarketSite
real-time broadcast in Times Square, and is currently a lead on the
DARPA XDATA program, developing new tools and technologies for
making sense of Big Data. Brath and Jonker are partners at a
leading visual analytics firm. Between them they have presented at
more than 30 industry conferences, and have published numerous
articles and research papers.
Résumé
Wring more out of the data with a scientific approach to analysis
Graph Analysis and Visualization brings graph theory out of the lab and into the real world. Using sophisticated methods and tools that span analysis functions, this guide shows you how to exploit graph and network analytic techniques to enable the discovery of new business insights and opportunities. Published in full color, the book describes the process of creating powerful visualizations using a rich and engaging set of examples from sports, finance, marketing, security, social media, and more. You will find practical guidance toward pattern identification and using various data sources, including Big Data, plus clear instruction on the use of software and programming. The companion website offers data sets, full code examples in Python, and links to all the tools covered in the book.
Science has already reaped the benefit of network and graph theory, which has powered breakthroughs in physics, economics, genetics, and more. This book brings those proven techniques into the world of business, finance, strategy, and design, helping extract more information from data and better communicate the results to decision-makers.
Contenu
Introduction xvii
PART 1 Overview
Chapter 1 Why Graphs? 3
Chapter 2 A Graph for Every Problem 27
PART 2 Process and Tools
Chapter 3 Data--Collect, Clean, and Connect 55
Chapter 4 Stats and Layout 87
Chapter 5 Visual Attributes 125
Chapter 6 Explore and Explain 157
Chapter 7 Point-and-Click Graph Tools 187
Chapter 8 Lightweight Programming 223
PART 3 Visual Analysis of Graphs
Chapter 9 Relationships 275
Chapter 10 Hierarchies 293
Chapter 11 Communities 315
Chapter 12 Flows 351
Chapter 13 Spatial Networks 389
PART 4 Advanced Techniques
Chapter 14 Big Data 419
Chapter 15 Dynamic Graphs 449
Chapter 16 Design 473
Glossary 497
Index 501