edmundmiller/dotfiles/tufte-viz

Tufte Visualization Ideation

Apply Edward Tufte's principles to design clear, honest, high-density data visualizations.

For a chart review or the former tufte-test request, read the seven-check review workflow. Prefer a rendered chart; label uncertainty when reviewing only code. All seven checks must pass. Fix only failed areas when asked to iterate. Designing a chart uses the workflow below; it does not require a separate review skill.

Workflow

For new visualizations:

1. Clarify the data story

• What comparisons matter?
• What's the key insight to communicate?
• Who's the audience?

1. Select approach using Tufte principles:

• High comparison need → Small multiples
• Dense data → Consider data tables, sparklines
• Time-series → Line charts with minimal grid
• Part-to-whole → Avoid pie charts; prefer bar/table

1. Design with data-ink in mind

• Start minimal, add only what's necessary
• Every element must earn its ink
• Default to grayscale; use color purposefully

1. Apply the Tufte test using the review workflow.

For critiquing visualizations:

1. Check graphical integrity

• Calculate lie factor if proportions seem off
• Verify baselines and scales
• Look for 3D distortion

1. Identify chartjunk

• Decorative elements
• Heavy grids
• Unnecessary 3D effects
• Moiré patterns

1. Evaluate data-ink ratio

• What can be erased?
• What's redundant?

1. Suggest improvements with specific before/after recommendations

Key Principles Reference

• references/tufte-principles.md — core principles from _Visual Display of Quantitative Information_: lie factor, data-ink, chartjunk, small multiples, integrity.
• references/analytical-design.md — extensions from _Envisioning Information_, _Visual Explanations_, and _Beautiful Evidence_: the 6 principles of analytical design, sparklines, layering & separation, micro/macro, range-frames, causality, confections. Load when designing dashboards, dense displays, sparklines, or explanatory graphics.

For a specific failed review check, read its detailed rule: data-ink, 3D effects, direct labeling, axes, color, annotations, or integrity. The rubric summarizes the pass rule.

Quick checklist:

• [ ] Lie Factor ≈ 1.0 (no visual distortion)
• [ ] Maximum data-ink ratio
• [ ] Zero chartjunk
• [ ] Clear labeling
• [ ] Answers "compared to what?"
• [ ] Shows causality or mechanism where relevant
• [ ] Multivariate (not over-reduced)
• [ ] Words, numbers, images integrated — not segregated
• [ ] Reveals multiple levels of detail (micro + macro)
• [ ] Layering: primary data dominates, secondary recedes
• [ ] Appropriate data density