Does this skill support both Matplotlib and Seaborn?

Yes, it provides integrated guidance for both libraries, using Seaborn for high-level statistical plotting and Matplotlib for fine-grained customization.

Does it follow the Matplotlib object-oriented interface?

Yes, the skill prioritizes the recommended object-oriented interface over the pyplot state-machine for better code maintainability and explicit control.

How does it handle color accessibility?

It emphasizes the use of perceptually uniform and colorblind-friendly colormaps like viridis, plasma, and cividis to ensure data is readable by everyone.

Can I create publication-ready figures with this skill?

Absolutely. The skill includes best practices for high-DPI exports, vector formats (PDF/SVG), and professional academic styling configurations.

Python Data Visualization

Name: Python Data Visualization
Author: tbhb

bytbhb

Data Science & ML

Generates publication-quality charts and statistical visualizations using Matplotlib and Seaborn.

About

This skill empowers Claude to create sophisticated data visualizations by providing domain-specific expertise in Matplotlib and Seaborn. It streamlines the creation of publication-ready figures, statistical graphics, and exploratory data analysis plots using industry best practices like the object-oriented interface and tidy data principles. Whether you are building complex multi-panel layouts, heatmaps, or time-series charts, this skill ensures consistent styling, accessible colormaps, and optimized export formats for professional, academic, or business intelligence projects.

Key Features

Creates advanced statistical visualizations with Seaborn
Generates Matplotlib object-oriented code for precise plot control
0 GitHub stars
Provides templates for multi-panel layouts and faceted small multiples
Implements accessible and perceptually uniform colormaps
Configures publication-quality figures with high-resolution export settings

Use Cases

Automating exploratory data analysis and visualization from Pandas DataFrames
Creating statistical graphics and figures for research papers and publications
Building consistent visual reports and dashboards for data-driven decision making

About

Key Features

Creates advanced statistical visualizations with Seaborn
Generates Matplotlib object-oriented code for precise plot control
0 GitHub stars
Provides templates for multi-panel layouts and faceted small multiples
Implements accessible and perceptually uniform colormaps
Configures publication-quality figures with high-resolution export settings

Use Cases

Automating exploratory data analysis and visualization from Pandas DataFrames
Creating statistical graphics and figures for research papers and publications
Building consistent visual reports and dashboards for data-driven decision making