Alterlab Seaborn
技能 已验证 活跃Part of the AlterLab Academic Skills suite. 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.
To enable quick and attractive statistical data exploration and visualization using Python, integrating seamlessly with pandas DataFrames.
功能
- Statistical visualization with pandas integration
- Supports box plots, violin plots, pair plots, heatmaps
- Offers both function and declarative object interfaces
- Built on matplotlib with attractive defaults
- Provides extensive documentation and examples
使用场景
- Quickly exploring data distributions and relationships
- Creating attractive default visualizations for academic research
- Generating publication-quality statistical graphics
- Performing multivariate analysis with minimal code
非目标
- Interactive plots (use plotly instead)
- Publication styling beyond attractive defaults (use scientific-visualization for precise styling)
- Directly manipulating raw data beyond what's needed for plotting
安装
npx skills add AlterLab-IEU/AlterLab-Academic-Skills通过 npx 运行 Vercel skills CLI(skills.sh)— 需要本地安装 Node.js,以及至少一个兼容 skills 的智能体(Claude Code、Cursor、Codex 等)。前提是仓库遵循 agentskills.io 格式。
质量评分
已验证类似扩展
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