Fundamentals of data visualization : a primer on making informative and compelling figures

Includes bibliographical references (pages 357-359) and index.

Introduction : ugly, bad, and wrong figures Part 1. From data to visualization. Visualizing data : mapping data onto aesthetics -- Coordinate systems and axes -- Color scales -- Directory of visualizations -- Visualizing amounts -- Visualizing distributions : histograms and density plots -- Visualizing distributions : empirical cumulative distribution functions and Q-Q plots -- Visualizing many distributions at once -- Visualizing proportions -- Visualizing nested proportions -- Visualizing associations among two or more quantitative variables -- Visualizing time series and other functions of an independent variable -- Visualizing trends -- Visualizing geospatial data -- Visualizing uncertainty -- Part 2. Principles of figure design. The principle of proportional ink -- Handling overlapping points -- Common pitfalls of color use -- Redundant coding -- Multipanel figures -- Titles, captions, and tables -- Balance the data and the context -- Use larger axis labels -- Avoid line drawings -- Don't go 3D -- Part 3. Miscellaneous topics. Understanding the most commonly used image file formats -- Choosing the right visualization software -- Telling a story and making a point.

"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."--Provided by publisher