JavaScript and jQuery for Data Analysis and Visualization

Jon Raasch, Graham Murray, Vadim Ogievetsky, Joseph Lowery

• Publisher: Wrox
• Year: 2014
• ISBN:
  9781118847220
• Edition: 1
• Topic: Computer Science
• Subtopic: Data Warehousing
• Index: Computer Science

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.

PART I
The 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 1
The World of Data Visualization

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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

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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.

When your information is in the proper format, you next need to ensure it is exactly the data you need and nothing more. The wealth of data available today makes targeting your data selection, typically through a process known as filtering, pretty much a requirement in all situations. Even when organizations fine-tune their data input from the beginning, changes in the sample or desired output over time will force a filtering adjustment.

Why is it so important to restrict your data stream? One clear reason is processing efficiency. Working with an overload of unnecessary information increases application execution time—which corresponds directly to increased bandwidth and, thus, costs. Additionally, filtering makes raw data more meaningful. Focused information is easier to analyze and also more easily digested by end users.

Visualizing the Data

In a sense, the most difficult aspect of data visualization is deciding exactly how the information should be depicted. The web designer must select the optimum representation that communicates the data in the clearest, most desired manner with the highest degree of...