Data Visualization

Design, implement, critique, or validate charts and quantitative visualizations with correct encodings, annotations, accessibility, and source context. Use for chart, graph, data visualization, visualizing metrics, dashboard chart, or figure review.

yigityildiz0 5b3079a 1020 B Updated

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Data Visualization

Choose the chart that makes the decision-relevant comparison easiest to see.

  1. Identify the audience, decision, measure, comparison, uncertainty, and source date.
  2. Choose a simple encoding: position/length before color/area; avoid charts that exaggerate tiny differences.
  3. Label units, denominators, time window, filters, sample size where relevant, and uncertainty or data gaps.
  4. Use accessible contrast, non-color cues, readable annotations, and a text alternative or concise finding.
  5. Validate the data transformation and visually inspect the rendered output.

Do not use misleading truncated axes, decorative 3D, unlabelled dual axes, or color-only meaning without a reasoned exception.

yigityildiz0/universal-ai-skill-library/tree/main/skills/common/data-visualization commit 5b3079a9ae

Frequently asked questions

npx skillmds@latest add yigityildiz0/data-visualization