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Mathematica Data Visualization
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Table of Contents
Mathematica Data Visualization
Credits
About the Author
About the Reviewers
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Free access for Packt account holders
Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Downloading the example code
Downloading the color images of this book
Errata
Piracy
Questions
1. Visualization as a Tool to Understand Data
The importance of visualization
Types of datasets
Tables
Scalar fields
Time series
Graphs
Text
Cartographic data
Mathematica as a tool for visualization
Getting started with Mathematica
Creating and selecting cells
Evaluating a cell
Suppressing output from a cell
Cell formatting
Commenting
Aborting evaluation
Upcoming chapters
Further reading
Summary
2. Dissecting Data Using Mathematica
Data structures and core languages
Introducing lists
Nested lists
Matrices
Constructing lists programmatically
Table entries with multiple elements
Accessing elements from a list
Applying set operations on lists
Functions and conditionals
Declaring and using functions
Conditionals
Further core language
Data importing and basic plots
Importing data into Mathematica
SetDirectory[] and NotebookDirectory[]
Loading the dataset
Basic plotting functions
ListPlot
Styling our plots
Plot legends
3D point plots
Log plots
Further reading
Summary
3. Time Series and Scientific Visualization
Periodic patterns in time series
Sector charts
Simulating Internet activity
SectorChart and its options
Interactive visualization of financial data
The DateListPlot function
Adding interactivity – preliminaries
Intermission – Graphics and Show
Adding interactivity – Dynamic and Refresh
Isocontour and molecular visualization
Introduction to isocontours
Example project – protein molecule visualization
Loading and visualizing the protein molecule
Preparing the isocontour plots
Adding interactivity – manipulate
Isosurface and styling
Thinking like a visualization scientist – isovalue analysis
Further reading
Summary
4. Statistical and Information Visualization
Statistical visualization
The swiss bank notes dataset
Histograms and charts
Histogram
PairedHistogram
Histogram3D
PieChart
BubbleChart
Choosing appropriate plots
A glimpse of high-dimensional data
Similarity maps
Projecting information to low dimensions
Visualizing genuine and counterfeit clusters
Similarity map for smaller datasets
Things that can (and will) go wrong
Employing the wrong distance metric
Choosing a misleading color map
Text visualization
A modified word cloud
Cleaning the data
The basic algorithm
Code and explanation
Graphs and networks
A basic graph visualization
Representing graphs in Mathematica
Visualizing the Les Misérables network
Highlighting centrality measures
Other graph layouts
3D layouts
Chord diagrams
Code and explanation
Tweaking the visualization
Further reading
Summary
5. Maps and Aesthetics
Map visualization
The GeoGraphics package
A map of our current location
Plotting a path on the map
Interactivity in GeoGraphics
Anatomy of a map visualization engine
The visual interface
Code and explanation
Aesthetics in visualization
Choosing the right color map
The rainbow color map is misleading
Understanding hue and luminance
Some better color maps
Designing the right interface
Deploying Mathematica visualizations
Looking forward
Further reading
Summary
Index
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Mathematica Data Visualization
Copyright © 2014 Packt Publishing
All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.
Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.
Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.
First published: September 2014
Production reference: 1180914
Published by Packt Publishing Ltd.
Livery Place
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Birmingham B3 2PB, UK.
ISBN 978-1-78328-299-9
www.packtpub.com
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Author
Nazmus Saquib
Reviewers
Roger J. Brown
Wenjun Deng
Kristjan Kannike
Commissioning Editor
Akram Hussain
Acquisition Editor
Mohammad Rizvi
Content Development Editor
Anila Vincent
Technical Editors
Venu Manthena
Aman Preet Singh
Copy Editors
Sayanee Mukherjee
Alfida Paiva
Project Coordinator
Neha Bhatnagar
Proofreaders
Martin Diver
Maria Gould
Indexers
Monica Ajmera Mehta
Tejal Soni
Production Coordinator
Manu Joseph
Cover Work
Manu Joseph
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Nazmus Saquib is a researcher at the MIT Media Lab in Cambridge, MA, where he works on data visualization, machine learning, and social computing projects. He has a bachelor's degree in Physics and a master's degree in Computational Engineering and Applied Mathematics. Saquib has been programming 3D games since middle school. As a result, he has developed and maintains a keen interest in game engines, graphics, and visualization. Throughout his academic years, he worked on a wide range of research projects, including acoustics, particle physics, augmented reality, social data mining, and uncertainty quantification. Saquib is also interested in the applications of creative computing in education and social welfare.
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Roger J. Brown is the President of IMOJIM, Inc., one of the oldest commercial investment firms in San Diego, which is now completing its fifth decade. His experience includes numerous consulting and expert witness assignments, and ownership or origination of loans on various properties in seven states of the US. He obtained his PhD in Finance from Pennsylvania State University in 2000, writing his dissertation on Levy-stable (non-normal, and heavy-tailed) return distributions. He is the author of Private Real...
