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Mathematica Data Visualization

Book Description

Create and prototype interactive data visualizations using Mathematica

In Detail

Mathematica, developed and maintained by Wolfram Research, is a trusted and popular tool used to analyze and visualize data.

This book begins by introducing you to the Mathematica environment and the basics of dataset loading and cleaning. You will then learn about the different kinds of widely used datasets so that you are comfortable with the later chapters. Then, in the subsequent chapters, you will learn about time series, scientific, statistical, information, and map visualizations. Each topic is demonstrated by walking you through an example project. Along the way, the dynamic interactivity and graphics packages are also introduced. Finally, the book ends with a brief discussion of color maps and aesthetics issues.

Using this book, you will learn how to build visualizations from scratch, quickly and efficiently.

What You Will Learn

  • Understand some widely used datasets in science, engineering, finance, statistics, and business
  • Write Mathematica programs to create stunning, interactive, and beautiful visualizations
  • Create time series visualizations in different scenarios to find underlying patterns in time series data
  • Build a protein molecule visualization tool and create basic isocontour and isosurface visualizations in Mathematica
  • Create statistical plots and charts and learn the basics of visualizing high dimensional datasets
  • Develop a word frequency visualization tool
  • Build graph network visualizations and interactive chord charts

Table of Contents

  1. Mathematica Data Visualization
    1. Table of Contents
    2. Mathematica Data Visualization
    3. Credits
    4. About the Author
    5. About the Reviewers
    6. www.PacktPub.com
      1. Support files, eBooks, discount offers, and more
        1. Why subscribe?
        2. Free access for Packt account holders
    7. Preface
      1. What this book covers
      2. What you need for this book
      3. Who this book is for
      4. Conventions
      5. Reader feedback
      6. Customer support
        1. Downloading the example code
        2. Downloading the color images of this book
        3. Errata
        4. Piracy
        5. Questions
    8. 1. Visualization as a Tool to Understand Data
      1. The importance of visualization
      2. Types of datasets
        1. Tables
        2. Scalar fields
        3. Time series
        4. Graphs
        5. Text
        6. Cartographic data
      3. Mathematica as a tool for visualization
      4. Getting started with Mathematica
        1. Creating and selecting cells
        2. Evaluating a cell
        3. Suppressing output from a cell
        4. Cell formatting
        5. Commenting
        6. Aborting evaluation
      5. Upcoming chapters
      6. Further reading
      7. Summary
    9. 2. Dissecting Data Using Mathematica
      1. Data structures and core languages
        1. Introducing lists
          1. Nested lists
          2. Matrices
          3. Constructing lists programmatically
            1. Table entries with multiple elements
          4. Accessing elements from a list
          5. Applying set operations on lists
        2. Functions and conditionals
          1. Declaring and using functions
          2. Conditionals
          3. Further core language
      2. Data importing and basic plots
        1. Importing data into Mathematica
          1. SetDirectory[] and NotebookDirectory[]
          2. Loading the dataset
        2. Basic plotting functions
          1. ListPlot
          2. Styling our plots
          3. Plot legends
          4. 3D point plots
          5. Log plots
      3. Further reading
      4. Summary
    10. 3. Time Series and Scientific Visualization
      1. Periodic patterns in time series
        1. Sector charts
        2. Simulating Internet activity
        3. SectorChart and its options
      2. Interactive visualization of financial data
        1. The DateListPlot function
        2. Adding interactivity – preliminaries
        3. Intermission – Graphics and Show
        4. Adding interactivity – Dynamic and Refresh
      3. Isocontour and molecular visualization
        1. Introduction to isocontours
        2. Example project – protein molecule visualization
          1. Loading and visualizing the protein molecule
          2. Preparing the isocontour plots
          3. Adding interactivity – manipulate
          4. Isosurface and styling
          5. Thinking like a visualization scientist – isovalue analysis
      4. Further reading
      5. Summary
    11. 4. Statistical and Information Visualization
      1. Statistical visualization
        1. The swiss bank notes dataset
        2. Histograms and charts
          1. Histogram
          2. PairedHistogram
          3. Histogram3D
          4. PieChart
          5. BubbleChart
        3. Choosing appropriate plots
        4. A glimpse of high-dimensional data
          1. Similarity maps
          2. Projecting information to low dimensions
          3. Visualizing genuine and counterfeit clusters
          4. Similarity map for smaller datasets
          5. Things that can (and will) go wrong
            1. Employing the wrong distance metric
            2. Choosing a misleading color map
      2. Text visualization
        1. A modified word cloud
          1. Cleaning the data
          2. The basic algorithm
        2. Code and explanation
      3. Graphs and networks
        1. A basic graph visualization
          1. Representing graphs in Mathematica
          2. Visualizing the Les Misérables network
          3. Highlighting centrality measures
          4. Other graph layouts
          5. 3D layouts
        2. Chord diagrams
          1. Code and explanation
          2. Tweaking the visualization
      4. Further reading
      5. Summary
    12. 5. Maps and Aesthetics
      1. Map visualization
        1. The GeoGraphics package
          1. A map of our current location
          2. Plotting a path on the map
          3. Interactivity in GeoGraphics
        2. Anatomy of a map visualization engine
          1. The visual interface
          2. Code and explanation
      2. Aesthetics in visualization
        1. Choosing the right color map
          1. The rainbow color map is misleading
          2. Understanding hue and luminance
          3. Some better color maps
        2. Designing the right interface
      3. Deploying Mathematica visualizations
      4. Looking forward
      5. Further reading
      6. Summary
    13. Index