| name | data-visualization |
| description | Grammar of graphics, chart type selection, color theory, interactive visualization, dashboards, and the principles of honest, effective data display. Covers Tufte's data-ink ratio, Bertin's visual variables, perceptual principles, accessibility, small multiples, annotation, and the full workflow from exploratory plots to publication-quality graphics. Use when creating charts, designing dashboards, critiquing visualizations, or choosing how to display data. |
| type | skill |
| category | data-science |
| status | stable |
| origin | tibsfox |
| modified | false |
| first_seen | "2026-04-12T00:00:00.000Z" |
| first_path | examples/skills/data-science/data-visualization/SKILL.md |
| superseded_by | null |
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:
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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.
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Chartjunk. Visual elements that do not represent data: moiré patterns, heavy gridlines, unnecessary ornamentation, 3D perspective on 2D data. Remove it.
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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.
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Small multiples. Repeating the same chart structure across panels to show variation across a categorical variable. More effective than animation or overlapping colors for showing change.
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Data density. The amount of data per unit area of the graphic. High data density is efficient -- sparklines, for example, embed a time series in the space of a word.
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Micro/macro readings. A good visualization works at both levels: the overall pattern is visible at a glance (macro), and individual data points can be read precisely (micro).
Bertin's Visual Variables
Jacques Bertin (1967) identified the fundamental visual channels available for encoding data:
| Variable | Data type | Effectiveness | Notes |
|---|
| Position | Quantitative | Highest | Most accurately perceived; always the first choice for the most important variable |
