JavaScript and jQuery for Data Analysis and Visualization E-Book

Jon Raasch

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 512

Veröffentlichungsjahr: 2014

Beschreibung

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.

Leseprobe

Table of Contents

PART I: The Beauty of Numbers Made Visible

Chapter 1: The World of Data Visualization

Bringing Numbers to Life

Applications of Data Visualization

Web Professionals: In the Thick of It

What Tech Brings to the Table

Summary

Chapter 2: Working with the Essentials of Analysis

Key Analytic Concepts

Working with Sampled Data

Detecting Patterns with Data Mining

Projecting Future Trends

Summary

Chapter 3: Building a Visualization Foundation

Exploring the Visual Data Spectrum

Making Use of the HTML5 Canvas

Integrating SVG

Summary

Part II: Working with JavaScript for Analysis

Chapter 4: Integrating Existing Data

Reading Data from Standard Text Files

Incorporating XML Data

Displaying JSON Content

Summary

Chapter 5: Acquiring Data Interactively

Using HTML5 Form Controls

Maximizing Mobile Forms

Summary

Chapter 6: Validating Your Data

Server-Side Versus Client-Side Validation

Native HTML5 Validation

jQuery Validation Engine

Summary

Chapter 7: Examining and Sorting Data Tables

Outputting Basic Table Data

Assuring Maximum Readability

Including Computations

Using the DataTables Library

Relating a Data Table to a Chart

Summary

Chapter 8: Statistical Analysis on the Client Side

Statistical Analysis with jStat

Rendering Probability Distributions with Flot

Summary

Part III: Visualizing Data Programmatically

Chapter 9: Exploring Charting Tools

Creating HTML5 Canvas Charts

Starting with Google Charts

Summary

Chapter 10: Building Custom Charts with Raphaël

Introducing Raphaël

Working with GRaphaël

Extending Raphaël to Create Custom Charts

Summary

Chapter 11: Introducing D3

Getting Started

D3 Helper Functions

D3 Helper Layouts

Summary

Chapter 12: Incorporating Symbols

Working with SVG Symbols with D3

Canvas Symbols with Ignite UI igDataChart

Summary

Chapter 13: Mapping Global, Regional, and Local Data

Working with Google Maps

Customizing Maps with Iconography

Plotting Data on Choropleth Maps

Summary

Chapter 14: Charting Time Series with Ignite UI igDataChart

Working with Stocks

Implementing Ignite UI igDataChart

Plotting Real-Time Data

Plotting Massive Data

Summary

Part IV: Interactive Analysis and Visualization Projects

Chapter 15: Building an Interconnected Dashboard

The U.S. Census API

Rendering Charts

Creating the Dashboard

Connecting Components with Backbone

Next Steps

Summary

Chapter 16: D3 in Practice

Making D3 Look Perfect

Working with Axes

Working with the Voronoi Map

Making Reusable Visualizations

Summary

Introduction

What's in This Book

Who This Book Is For

Conventions

Companion Website

Errata

p2p.wrox.com

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End User License Agreement

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Guide

Cover

Table of Contents

PART I: The Beauty of Numbers Made Visible

Begin Reading

List of Illustrations

Figure 1.1

Figure 1.2

Figure 1.3

Figure 1.4

Figure 1.5

Figure 1.6

Figure 2.1

Figure 2.2

Figure 2.3

Figure 3.1

Figure 3.2

Figure 3.3

Figure 3.4

Figure 3.5

Figure 3.6

Figure 3.7

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Figure 3.9

Figure 3.10

Figure 3.11

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Figure 3.25

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Figure 3.32

Figure 4.1

Figure 4.2

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Figure 16.1

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List of Tables

Table 2.1

Table 2.2

Table 2.3

Table 2.4

Table 3.1

Table 3.2

PART IThe Beauty of Numbers Made Visible

Chapter 1: The World of Data Visualization

Chapter 2: Working with the Essentials of Analysis

Chapter 3: Building a Visualization Foundation

Chapter 1The World of Data Visualization

What's in This Chapter

Overview of chart design options

Comparison of different business applications for data visualization

Rundown of technological advancements that have made data visualization what it is today

When thinking about data visualization, it's hard to resist the comparison to natural metamorphosis. Consider raw data as the caterpillar: functional, multi-faceted, able to get from here to there, but a little ungainly and really appreciated only by a select few. After data is transformed via visualization, it becomes the butterfly: sleek, agile, and highly recognizable to the point of inspiring and evoking an emotional response. The world of data visualization is an ecosystem unto itself, constantly spawning new nodes of details that—under the proper nourishing conditions—evolve into relatable depictions that consolidate concepts into an understandable, and hopefully compelling, form.

And where does the web professional fit in this metaphor? Why, they are the spinners and caretakers of the cocoon that transforms raw numbers into meaningful representation, of course. Putting the linguistic paraphrasing aside, web designers and developers are a vital component in visualizing data. Naturally, the current and evolving technological landscape has made this role possible—and increasingly efficient.

Overall, JavaScript and jQuery for Data Analysis and Visualization serves as a practical field guide to the robust world of data visualization, from the acquisition and nurturing of data to its transfiguration into the optimal visual format. This chapter is intended to provide an overview of the present environment, highlighting its capabilities and limitations and discussing how you, the web professional, are a key player in visualizing data.

Bringing Numbers to Life

Appreciating numeric data can be a challenge. Data visualization with relational graphics and evocative imagery helps make raw data meaningful. But before you can transform the data into a meaningful representation, you have to get it first.

Acquiring the Data

The data sphere is enormous and growing dramatically, if not exponentially, every day. Data is streaming in from everywhere—and when you consider that the Mars Rover, Curiosity, continually sends its data findings back to Earth, you understand that “everywhere” is no exaggeration.

With the tremendous amount of data already available, its acquisition is often just a matter of logistics. If the information is in a non-digital form—that is, written records—it will need to be transcribed into the proper format. Should the desired data be accessible digitally, it may need to be converted from its current structure to one compatible with the display or visualization application.