Statistical Visualization

statistical-visualization

Trigger Boundary

Statistical result visualization with Matplotlib and Plotly. For publication-ready figure palettes, venue figure QA, and manuscript figure styling, use the scientific-visualization plugin.

Use this aggregate Codex App skill when the task matches one of the source workflows below.

Source Workflows

• matplotlib: Low-level plotting library for full customization. Use when you need fine-grained control over every plot element, creating novel plot types, or integrating with specific scientific workflows. Reference: _src/mpl/source.md
• plotly: Interactive visualization library. Use when you need hover info, zoom, pan, or web-embeddable charts. Best for dashboards, exploratory analysis, and presentations. For static publication figures use matplotlib or scientific-visualization. Reference: _src/plotly/source.md

Workflow

1. Choose the source workflow whose trigger boundary best matches the user request.
2. Read that source workflow's source.md before acting.
3. Load only the needed files under that workflow's copied references, scripts, assets, or evals.
4. Follow the source workflow unless the current project gives stricter instructions.