Individual skill

seaborn

Statistical visualization library integrated with pandas; use it when you need fast EDA of distributions, relationships, and categorical comparisons (e.g., box/violin/pair plots and heatmaps) with strong default aesthetics on top of matplotlib.

scientific-skills/Data Analysis/seaborn/SKILL.md

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> **Source**: [https://github.com/aipoch/medical-research-skills](https://github.com/aipoch/medical-research-skills)

## When to Use

- Exploring relationships between variables in a DataFrame (e.g., scatter/line plots with `hue`, `size`, `style`).
- Comparing distributions across categories (e.g., box/violin/swarm plots for groups).
- Inspecting univariate/bivariate distributions (histograms, KDE, ECDF; joint and pairwise views).
- Visualizing correlation matrices or other rectangular data (heatmaps, clustered heatmaps).
- Building faceted "small multiples" quickly (split by `row`/`col` using figure-level APIs).

## Key Features

- **DataFrame-first API**: Works naturally with pandas "long-form/tidy" data and named columns.
- **Semantic mappings**: Encode extra dimensions via `hue`, `size`, `style`, and faceting (`row`, `col`).
- **Statistical awareness**: Built-in aggregation and uncertainty display (e.g., confidence intervals / error bars).