What is the Seaborn Claude Code Skill?

It is a specialized capability that enables Claude to provide expert-level guidance, code generation, and debugging for the Seaborn Python library, focusing on statistical data visualization.

Does this skill support the modern Seaborn Objects interface?

Yes, it includes comprehensive support for both the traditional function interface and the modern, declarative 'seaborn.objects' API for composable visualizations.

Can I use this skill to create figures for academic publications?

Absolutely. Seaborn is specifically designed to produce publication-quality graphics with professional aesthetic defaults and sophisticated color palettes.

What kind of data structures does this skill work best with?

While it supports various formats, it is optimized for 'long-form' or 'tidy' data where every variable is a column and every observation is a row, typically stored in a Pandas DataFrame.

Seaborn Statistical Visualization

Name: Seaborn Statistical Visualization
Author: Zehong-Wang

byZehong-Wang

0•

Data Science & ML

Creates publication-quality statistical graphics and complex multi-panel data visualizations with minimal Python code.

Seaborn is a powerful Python library built on top of Matplotlib that simplifies the creation of informative and aesthetically pleasing statistical graphics. This skill provides Claude with deep expertise in dataset-oriented plotting, allowing it to automatically map data variables to visual properties, perform statistical estimation, and generate sophisticated multi-facet figures. Whether performing exploratory data analysis (EDA) or preparing figures for academic publication, this skill enables efficient multivariate analysis and high-level declarative visualization using both traditional function interfaces and the modern objects API.

Key Features

01Dataset-oriented API for direct integration with Pandas DataFrames

02Advanced categorical and distribution plots including violin, boxen, and KDE

030 GitHub stars

04Automatic statistical estimation and aggregation with confidence intervals

05Complex multi-panel figures through FacetGrid, PairGrid, and JointGrid

06Publication-ready aesthetic themes and colorblind-friendly palettes

Use Cases

01Exploratory data analysis to uncover patterns and correlations in large datasets

02Visualizing complex multivariate relationships using faceted subplots and regression models

03Generating high-quality statistical figures for research papers and technical reports

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add zehong-wang/kosmos seaborn

For use in Claude.ai and ChatGPT

Download Skill