Individual skill
seaborn
Creates Seaborn statistical visualizations with pandas integration for distributions, relationships, categorical comparisons, regression displays, pair plots, and heatmaps. Supports function and objects interfaces with explicit aggregation, uncertainty, and missing-data handling. Best suited to static exploratory plots; plotly covers interactive figures and scientific-visualization covers publication styling.
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
Reviewed 2026-10-01 against the current stable [Seaborn 0.13.2 documentation](https://seaborn.pydata.org/api.html) and released source. Native synthetic checks used Python 3.13, Seaborn 0.13.2, Matplotlib 3.11.2, pandas 3.0.6, NumPy 2.5.3, SciPy 1.18.1, and statsmodels 0.15.0. 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. The tested stack emits upstream pandas Copy-on-Write and Matplotlib deprecation warnings; successful current plots do not guarantee compatibility with future pandas 4 or Matplotlib 3.13.
```bash
# Reproducible install for examples in this skill
uv pip install "seaborn==0.13.2"
