seaborn
Seaborn statistical data visualization. Use for statistical plots.
Install
npx skillscat add g1joshi/agent-skills/seaborn Install via the SkillsCat registry.
About this skill
This skill provides a high-level interface for creating statistical data visualizations using Seaborn. It simplifies the process of generating complex plots like heatmaps and regression lines directly from Pandas DataFrames. It should be used for exploratory data analysis and visualizing statistical relationships through a grammar-of-graphics approach.
SKILL.md
Seaborn
Seaborn is a high-level wrapper around Matplotlib. It makes statistical plots (violins, heatmaps, pairs) easy.
When to Use
- Exploratory Data Analysis (EDA): Quickly understanding distributions.
- Statistical Relationships: "Show me the regression line with confidence intervals".
- Pandas Models: Works natively with DataFrames (long-form).
Core Concepts
Objects Interface (so)
New in v0.12+. A grammar-of-graphics style API (like ggplot2) : so.Plot(df, x="time", y="val").add(so.Line()).
Themes
sns.set_theme().
Best Practices (2025)
Do:
- Use the Objects Interface: For composable, complex plots.
- Use
relplot,displot,catplot: The figure-level functions are more flexible thanscatterplot.
Don't:
- Don't iterate: Seaborn handles "hue" and "col" (faceting) automatically.
References
Categories
Install
npx skillscat add g1joshi/agent-skills/seaborn Install via the SkillsCat registry.