- Data Visualization: Principles and Practice, Second Edition by Alexandru C Telea
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Watch fullscreen. Focusing on those techniques and methods with the broadest applicability across fields, the second edition of Data Visualization: Principles and Practice provides a streamlined introduction to various visualization techniques. The book illustrates a wide variety of applications of data visualizations, illustrating the range of problems that can be tackled by such methods, and emphasizes the strong connections between visualization and related disciplines such as imaging and computer graphics.
It covers a wide range of sub-topics in data visualization: data representation; visualization of scalar, vector, tensor, and volumetric data; image processing and domain modeling techniques; and information visualization.
Data Visualization - Principles and Practice
Exercises covering the topics discussed in the book, as well as datasets and source code, are also provided as additional online resources. For Free. Although it sounds similar, enlightening is a different concept from insightful. Cairo says this quality is composed of the previous four: truthful, functional, beautiful, and insightful. Enlightenment means that every important component has been successfully combined to produce a new and valuable revelation.
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Cairo also poses the question of whether social responsibility is a dimension to consider in ethical data visualization. Who can judge whether the suppression or selective release of specific scientific knowledge is harmful or helpful? Most importantly, have the intention to create meaningful visualization and to identify deception and unethical work.
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A data scientist is responsible for putting the right information in front of the right audience, in a way that adapts to their skillset and purposes. Sign in. Get started. Data visualization and The Truthful Art. Anthony Figueroa Follow. Towards Data Science Sharing concepts, ideas, and codes. CTO at Rootstrap. I lead tech strategy of a top digital product agency, applying agile methodologies and experience. Passionate about solving complex problems.
Towards Data Science Follow. Sharing concepts, ideas, and codes. Write the first response.
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