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Explore the critical intersection of color theory and data visualization in this 26-minute PyCon US talk that challenges common assumptions about color palettes. Learn why even the most aesthetically pleasing visualizations might inadvertently introduce bias through color choices. Understand how contextual color interpretation affects viewer perception, as proximity to other colors can make hues appear darker, lighter, more prominent or subdued. Dive into fundamental color theory based on Josef Albers' work, discover the concept of color weight, and gain practical techniques for evaluating palette selections. Find out why designer-created palettes, despite their beauty, might compromise data integrity, and master strategies for creating visualizations that remain both unbiased and visually appealing. Apply these tool-agnostic principles with any data visualization package that allows custom color palette specification.
