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  • Format: ePub

Effective visualization is the best way to communicate information from the increasingly large and complex datasets in the natural and social sciences. But with the increasing power of visualization software today, scientists, engineers, and business analysts often have to navigate a bewildering array of visualization choices and options.This practical book takes you through many commonly encountered visualization problems, and it provides guidelines on how to turn large datasets into clear and compelling figures. What visualization type is best for the story you want to tell? How do you make…mehr

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Produktbeschreibung
Effective visualization is the best way to communicate information from the increasingly large and complex datasets in the natural and social sciences. But with the increasing power of visualization software today, scientists, engineers, and business analysts often have to navigate a bewildering array of visualization choices and options.This practical book takes you through many commonly encountered visualization problems, and it provides guidelines on how to turn large datasets into clear and compelling figures. What visualization type is best for the story you want to tell? How do you make informative figures that are visually pleasing? Author Claus O. Wilke teaches you the elements most critical to successful data visualization.Explore the basic concepts of color as a tool to highlight, distinguish, or represent a valueUnderstand the importance of redundant coding to ensure you provide key information in multiple waysUse the books visualizations directory, a graphical guide to commonly used types of data visualizationsGet extensive examples of good and bad figuresLearn how to use figures in a document or report and how employ them effectively to tell a compelling story

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Autorenporträt
Professor and scientist, with background in theoretical and computational biology, theoretical physics, and evolutionary biology. Author or co-author of over 140 scientific publications, covering topics in computational biology, mathematical modeling, simulation, bioinformatics, genomics, evolutionary biology, protein biochemistry, virology, population genetics, and statistics.