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JavaScript and jQuery for Data Analysis and Visualization

Book Description

Go beyond design concepts—build dynamic data visualizations using JavaScript

JavaScript and jQuery for Data Analysis and Visualization goes beyond design concepts to show readers how to build dynamic, best-of-breed visualizations using JavaScript—the most popular language for web programming.

The authors show data analysts, developers, and web designers how they can put the power and flexibility of modern JavaScript libraries to work to analyze data and then present it using best-of-breed visualizations. They also demonstrate the use of each technique with real-world use cases, showing how to apply the appropriate JavaScript and jQuery libraries to achieve the desired visualization.

All of the key techniques and tools are explained in this full-color, step-by-step guide. The companion website includes all sample codes used to generate the visualizations in the book, data sets, and links to the libraries and other resources covered.

  • Go beyond basic design concepts and get a firm grasp of visualization approaches and techniques using JavaScript and jQuery

  • Discover detailed, step-by-step directions for building specific types of data visualizations in this full-color guide

  • Learn more about the core JavaScript and jQuery libraries that enable analysis and visualization

  • Find compelling stories in complex data, and create amazing visualizations cost-effectively

  • Let JavaScript and jQuery for Data Analysis and Visualization be the resource that guides you through the myriad strategies and solutions for combining analysis and visualization with stunning results.

    Table of Contents

    1. PART I: The Beauty of Numbers Made Visible
    2. Chapter 1: The World of Data Visualization
      1. Bringing Numbers to Life
      2. Applications of Data Visualization
      3. Web Professionals: In the Thick of It
      4. What Tech Brings to the Table
      5. Summary
    3. Chapter 2: Working with the Essentials of Analysis
      1. Key Analytic Concepts
      2. Working with Sampled Data
      3. Detecting Patterns with Data Mining
      4. Projecting Future Trends
      5. Summary
    4. Chapter 3: Building a Visualization Foundation
      1. Exploring the Visual Data Spectrum
      2. Making Use of the HTML5 Canvas
      3. Integrating SVG
      4. Summary
    5. Part II: Working with JavaScript for Analysis
    6. Chapter 4: Integrating Existing Data
      1. Reading Data from Standard Text Files
      2. Incorporating XML Data
      3. Displaying JSON Content
      4. Summary
    7. Chapter 5: Acquiring Data Interactively
      1. Using HTML5 Form Controls
      2. Maximizing Mobile Forms
      3. Summary
    8. Chapter 6: Validating Your Data
      1. Server-Side Versus Client-Side Validation
      2. Native HTML5 Validation
      3. jQuery Validation Engine
      4. Summary
    9. Chapter 7: Examining and Sorting Data Tables
      1. Outputting Basic Table Data
      2. Assuring Maximum Readability
      3. Including Computations
      4. Using the DataTables Library
      5. Relating a Data Table to a Chart
      6. Summary
    10. Chapter 8: Statistical Analysis on the Client Side
      1. Statistical Analysis with jStat
      2. Rendering Probability Distributions with Flot
      3. Summary
    11. Part III: Visualizing Data Programmatically
    12. Chapter 9: Exploring Charting Tools
      1. Creating HTML5 Canvas Charts
      2. Starting with Google Charts
      3. Summary
    13. Chapter 10: Building Custom Charts with Raphaël
      1. Introducing Raphaël
      2. Working with GRaphaël
      3. Extending Raphaël to Create Custom Charts
      4. Summary
    14. Chapter 11: Introducing D3
      1. Getting Started
      2. D3 Helper Functions
      3. D3 Helper Layouts
      4. Summary
    15. Chapter 12: Incorporating Symbols
      1. Working with SVG Symbols with D3
      2. Canvas Symbols with Ignite UI igDataChart
      3. Summary
    16. Chapter 13: Mapping Global, Regional, and Local Data
      1. Working with Google Maps
      2. Customizing Maps with Iconography
      3. Plotting Data on Choropleth Maps
      4. Summary
    17. Chapter 14: Charting Time Series with Ignite UI igDataChart
      1. Working with Stocks
      2. Implementing Ignite UI igDataChart
      3. Plotting Real-Time Data
      4. Plotting Massive Data
      5. Summary
    18. Part IV: Interactive Analysis and Visualization Projects
    19. Chapter 15: Building an Interconnected Dashboard
      1. The U.S. Census API
      2. Rendering Charts
      3. Creating the Dashboard
      4. Connecting Components with Backbone
      5. Next Steps
      6. Summary
    20. Chapter 16: D3 in Practice
      1. Making D3 Look Perfect
      2. Working with Axes
      3. Working with the Voronoi Map
      4. Making Reusable Visualizations
      5. Summary
    21. Introduction
      1. What's in This Book
      2. Who This Book Is For
      3. Conventions
      4. Companion Website
      5. Errata
      6. p2p.wrox.com
    22. Advertisement
    23. End User License Agreement