9781449312282-1449312284-Designing Data Visualizations

Designing Data Visualizations

ISBN-13: 9781449312282
ISBN-10: 1449312284
Edition: 1
Author: Noah Iliinsky, Julia Steele
Publication date: 2011
Publisher: O'Reilly Media
Format: Paperback 108 pages
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Book details

ISBN-13: 9781449312282
ISBN-10: 1449312284
Edition: 1
Author: Noah Iliinsky, Julia Steele
Publication date: 2011
Publisher: O'Reilly Media
Format: Paperback 108 pages

Summary

Designing Data Visualizations (ISBN-13: 9781449312282 and ISBN-10: 1449312284), written by authors Noah Iliinsky, Julia Steele, was published by O'Reilly Media in 2011. With an overall rating of 3.9 stars, it's a notable title among other Data Modeling & Design (Databases & Big Data, Graphics & Design, Graphics & Multimedia, Programming, Software Design, Testing & Engineering, User Experience & Usability, Web Development & Design) books. You can easily purchase or rent Designing Data Visualizations (Paperback, Used) from BooksRun, along with many other new and used Data Modeling & Design books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

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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