Title: Fundamentals of Data Visualization: A Primer on Making Informative and Compelling Figures
Publisher: O'Reilly Media (edition 1)
Publication Date: 2019
Language: English
ISBN 10: 1492031089
ISBN 13: 9781492031086
Binding: Paperback
Edition: 1.
Condition: Fair

About this title

Synopsis

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 value
Understand the importance of redundant coding to ensure you provide key information in multiple ways
Use the book's visualizations directory, a graphical guide to commonly used types of data visualizations
Get extensive examples of good and bad figures
Learn how to use figures in a document or report and how employ them effectively to tell a compelling story

About the Author

Claus O. Wilke is a professor of Integrative Biology at The University of Texas at Austin. He holds a PhD in theoretical physics from the Ruhr-University Bochum, Germany. Claus is the author or coauthor of over 170 scientific publications, covering topics in computational biology, mathematical modeling, bioinformatics, evolutionary biology, protein biochemistry, virology, and statistics. He has also authored several popular R packages used for data visualization, such as cowplot and ggridges, and he is a contributor to the package ggplot2.

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