data-visualizationlisted

# Data Visualization Data visualization is the translation of data into visual form for the purpose of communication, exploration, or analysis. A good visualization reveals what the data has to say; a bad one obscures or distorts it. This skill covers the principles, techniques, and design decisions involved in creating honest, effective data displays, drawing primarily on Edward Tufte's principles, Leland Wilkinson's Grammar of Graphics, and Jacques Bertin's visual semiology. **Agent affinity:** tufte (design principles, critique), nightingale (routing visualization tasks), cairo (pedagogy of visual literacy) **Concept IDs:** data-chart-types, data-visual-design, data-misleading-graphs, data-data-storytelling ## Core Principles ### Tufte's Principles Edward Tufte's work established the foundational principles of honest data display: 1. **Data-ink ratio.** Maximize the proportion of ink devoted to data. Every element that does not convey data is potential chartjunk -- decorative gridlines, 3D effects, gradient fills, clip art. 2. **Chartjunk.** Visual elements that do not represent data: moiré patterns, heavy gridlines, unnecessary ornamentation, 3D perspective on 2D data. Remove it. 3. **Lie factor.** The ratio of the visual effect to the numerical effect. A bar chart where a 2x increase in data is represented by a 4x increase in area has a lie factor of 2. Lie factor should be between 0.95 and 1.05. 4. **Small multiples.** Repeating the same chart structure across