Can I create multi-panel figures with this skill?

Yes, it covers figure-level functions and grid objects like FacetGrid and PairGrid for creating complex, multi-plot layouts easily.

What is the advantage of using the Seaborn skill over Matplotlib?

Seaborn provides a higher-level interface that produces more aesthetically pleasing plots with less code, specifically optimized for statistical data and DataFrames.

Does this skill support the modern seaborn.objects interface?

Yes, it includes comprehensive guidance for the modern, declarative, and composable API similar to ggplot2.

How does the skill handle different data formats?

The skill provides patterns for working with both 'long-form' (tidy) and 'wide-form' data, including instructions on when to use each for specific plot types.

Seaborn Statistical Visualization

Name: Seaborn Statistical Visualization
Author: K-Dense-AI

byK-Dense-AI

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2,188

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Data Science & ML

Generates publication-quality statistical graphics and complex data visualizations using the Seaborn Python library.

This skill empowers Claude to create sophisticated statistical visualizations by leveraging the Seaborn library's dataset-oriented API. It provides structured guidance for generating relational, distribution, categorical, and regression plots with aesthetic defaults and automatic statistical estimation. Whether you need quick exploratory analysis or complex multi-panel figures for publication, this skill helps Claude select the correct plotting interfaces and ensures data is structured correctly for optimal visualization results.

Key Features

01Automatic semantic mapping of data variables to visual properties like hue and size

02Support for both traditional function-based and modern declarative object-oriented interfaces

03Advanced multi-panel plotting via FacetGrid, PairGrid, and JointGrid

042,188 GitHub stars

05Integrated handling of both long-form (tidy) and wide-form data structures

06Statistical awareness with built-in aggregation and error estimation

Use Cases

01Creating publication-ready correlation matrices and heatmaps for exploratory data analysis

02Comparing statistical distributions across categories with violin, box, and swarm plots

03Visualizing multivariate relationships across datasets using faceted scatter and line plots

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add k-dense-ai/claude-scientific-skills seaborn

For use in Claude.ai and ChatGPT

Download Skill