Fundamentals of Data Visualization: A Primer on Making Informative and Compelling Figures

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

• Practical Time Series Analysis: Prediction with Statistics and Machine Learning
• Data Visualization: A Practical Introduction
• Data Science from Scratch: First Principles with Python
• Hands-On Unsupervised Learning Using Python: How to Build Applied Machine Learning Solutions from Unlabeled Data
• How Charts Lie: Getting Smarter about Visual Information
• Advanced R, Second Edition (Chapman & Hall/CRC The R Series)
• Generative Deep Learning: Teaching Machines to Paint, Write, Compose, and Play
• The Truthful Art: Data, Charts, and Maps for Communication (Voices That Matter)
• R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
• The Functional Art: An introduction to information graphics and visualization (Voices That Matter)