# Seaborn

> 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.

- Skill: `francostino/seaborn-2` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add francostino/seaborn-2`
- Raw SKILL.md: https://api.skillmd.com/api/skills/francostino/seaborn-2/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- License: BSD-3-Clause license
- Author: FrancoStino (https://skillmd.com/u/francostino)
- Updated: 2026-09-21
- Page: https://skillmd.com/skills/francostino/seaborn-2

---


# Seaborn Statistical Visualization

## Detailed Guide

Read [the detailed guide](references/detailed-guide.md) before executing this skill. It retains the complete procedure and reference material. Treat its safety, prerequisites, and validation requirements as mandatory. For focused work, load the relevant sections; for end-to-end work, read the guide completely.

## When to Use
- You need publication-quality statistical graphics directly from tabular datasets.
- You are exploring multivariate relationships, distributions, or grouped comparisons with minimal plotting code.
- You want seaborn's dataset-oriented API and statistical defaults on top of matplotlib.

## Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.