Data visualization is an efficient and effective medium for communicating large amounts of information, but the design process can often seem like an unexplainable creative endeavor. This concise book aims to demystify the design process by showing you how to use a linear decision-making process to encode your information visually.

Delve into different kinds of visualization, including infographics and visual art, and explore the influences at work in each one. Then learn how to apply these concepts to your design process.

Learn data visualization classifications, including explanatory, exploratory, and hybrid
Discover how three fundamental influences--the designer, the reader, and the data--shape what you create
Learn how to describe the specific goal of your visualization and identify the supporting data
Decide the spatial position of your visual entities with axes
Encode the various dimensions of your data with appropriate visual properties, such as shape and color
See visualization best practices and suggestions for encoding various specific data types

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Julie Steele is an Editor at O'Reilly currently working on titles related to Python, SQL, PHP, web frameworks and CMS, databases (relational and non-relational), big data and cloud computing, and data visualization. She's also interested in data transparency and open government, and recently completed a master's degree in political science at Rutgers University. Noah Illinsky has spent the last several years thinking about effective approaches to creating diagrams and other types of information visualization. He also works in interface and interaction design, all from a functional and user-centered perspective. Before becoming a designer he was a programmer for several years. He has a master's in Technical Communication from the University of Washington, and a bachelor's in Physics from Reed College.

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Designing Data Visualizations

Steele, Julie; Iliinsky, Noah

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