Book description
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
Publisher resources
Table of contents
- Preface
- 1. Introduction
- I. From Data to Visualization
- 2. Visualizing Data: Mapping Data onto Aesthetics
- 3. Coordinate Systems and Axes
- 4. Color Scales
- 5. Directory of Visualizations
- 6. Visualizing Amounts
- 7. Visualizing Distributions: Histograms and Density Plots
- 8. Visualizing Distributions: Empirical Cumulative Distribution Functions and Q-Q Plots
- 9. Visualizing Many Distributions at Once
- 10. Visualizing Proportions
- 11. Visualizing Nested Proportions
- 12. Visualizing Associations Among Two or More Quantitative Variables
- 13. Visualizing Time Series and Other Functions of an Independent Variable
- 14. Visualizing Trends
- 15. Visualizing Geospatial Data
- 16. Visualizing Uncertainty
- II. Principles of Figure Design
- 17. The Principle of Proportional Ink
- 18. Handling Overlapping Points
- 19. Common Pitfalls of Color Use
- 20. Redundant Coding
- 21. Multipanel Figures
- 22. Titles, Captions, and Tables
- 23. Balance the Data and the Context
- 24. Use Larger Axis Labels
- 25. Avoid Line Drawings
- 26. Don’t Go 3D
- III. Miscellaneous Topics
- 27. Understanding the Most Commonly Used Image File Formats
- 28. Choosing the Right Visualization Software
- 29. Telling a Story and Making a Point
- Annotated Bibliography
- Technical Notes
- References
- Index
Product information
- Title: Fundamentals of Data Visualization
- Author(s):
- Release date: April 2019
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781492031086
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