Individual skill
seaborn
Statistical visualization with pandas integration. Use for quick exploration of distributions, relationships, and categorical comparisons with attractive defaults. Best for box plots, violin plots, pair plots, heatmaps. Built on matplotlib. For interactive plots use plotly; for publication styling use scientific-visualization.
plugins/KalarisLabs/research-agent-skills/skills/seaborn/SKILL.md
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# Seaborn Statistical Visualization
## Overview
Seaborn is a Python visualization library for creating publication-quality statistical graphics. Use this skill for dataset-oriented plotting, multivariate analysis, automatic statistical estimation, and complex multi-panel figures with minimal code.
## Environment and Installation
Current upstream documentation is for seaborn 0.13.2. Official docs support Python 3.8+ with mandatory NumPy, pandas, and matplotlib dependencies; scipy, statsmodels, and fastcluster are optional for some advanced statistics and clustering workflows.
```bash
# Reproducible install for examples in this skill
uv pip install "seaborn==0.13.2"
