Doc Add Chart

Table of Contents

1. When to use this skill

When designing or evaluating any data display — charts, dashboards, tables, reports, inline graphics. Use it before writing visualisation code and when reviewing existing displays for clarity or integrity.

2. How to use this skill

2.1. For new visualisations

  1. Clarify the data story — what comparisons matter? What is the key insight? Who is the audience?
  2. Select approach using Tufte principles:
    • High comparison need → small multiples.
    • Dense data → data tables, sparklines.
    • Time-series → line charts with minimal grid.
    • Part-to-whole → avoid pie charts; prefer bar/table.
  3. Design with data-ink in mind — start minimal, add only what is necessary. Every element must earn its ink. Default to greyscale; use colour purposefully.
  4. Apply the Tufte Test — see Tufte's Principles for Data Visualisation.

2.2. For critiquing visualisations

  1. Check graphical integrity — calculate lie factor if proportions seem off; verify baselines and scales; look for 3D distortion.
  2. Identify chartjunk — decorative elements, heavy grids, unnecessary 3D effects, moiré patterns.
  3. Evaluate data-ink ratio — what can be erased? What is redundant?
  4. Apply the six analytical design principles — see Analytical Design, Sparklines, and Layering.
  5. Suggest improvements with specific before/after recommendations.

3. Key principles reference

  • Tufte's Principles for Data Visualisation — core principles from The Visual Display of Quantitative Information: lie factor, data-ink ratio, chartjunk, small multiples, graphical integrity, and the 7-question Tufte Test.
  • Analytical Design, Sparklines, and Layering — extensions from Envisioning Information, Visual Explanations, and Beautiful Evidence: the six principles of analytical design, sparklines, layering and separation, micro/macro, range-frames, causality, confections. Load when designing dashboards, dense displays, sparklines, or explanatory graphics.

4. Quick checklist

  • [ ] Lie Factor ≈ 1.0 (no visual distortion).
  • [ ] Maximum data-ink ratio.
  • [ ] Zero chartjunk.
  • [ ] Clear labelling.
  • [ ] 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.

5. Recipes

This skill runs no commands: it is judgement applied to a chart someone else renders.

6. Reference

Emacs 29.3 (Org mode 9.6.15)