Is this skill only useful for cosmology?

While it includes specialized overrides for cosmology (like Healpix and power spectra), it uses universal design principles applicable to any quantitative or scientific field.

Can it help me prepare figures for a research paper?

Yes, its 'Analytical Mode' is specifically designed to meet peer-review standards, focusing on precision, high data-ink ratios, and black-and-white compatibility.

How does it handle colorblind accessibility?

The skill enforces the use of colorblind-safe palettes like Viridis and employs redundant encoding (using both shape and color) to ensure data remains interpretable.

Which libraries does this skill support?

The skill is optimized for Matplotlib, Seaborn, and Plotly, with a preference for Seaborn to achieve cleaner defaults and better statistical primitives.

Scientific Data Visualization

Name: Scientific Data Visualization
Author: cailmdaley

bycailmdaley

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Data Science & ML

Transforms complex datasets into publication-quality figures and interactive visualizations using established design principles and domain-specific conventions.

This skill empowers Claude to design and implement sophisticated data visualizations following the frameworks of Tufte, Cleveland, and Wilke. While highly specialized for observational cosmology—including power spectra, covariance matrices, and Healpix sky maps—it excels at creating clear, accessible graphics for both peer-reviewed papers and public outreach. By automating the selection of optimal encodings, color palettes, and layout structures, it ensures every chart maximizes the data-ink ratio while maintaining accessibility and scientific accuracy across Matplotlib, Seaborn, and Plotly.

Key Features

014 GitHub stars

02Implements expert design frameworks from Tufte, Cleveland, and Wilke for maximum clarity.

03Optimized integration with Matplotlib, Seaborn, and Plotly for Python workflows.

04Specialized support for cosmology-specific plots like triangle plots and power spectra.

05Automatic mode switching between rigorous analytical papers and high-impact outreach.

06Built-in accessibility checks for colorblind safety and redundant encoding.

Use Cases

01Visualizing high-dimensional parameter posteriors and correlation matrices for statistical analysis.

02Creating engaging, accessible data stories for presentations and public outreach materials.

03Generating publication-ready figures for scientific journals with strict formatting requirements.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add cailmdaley/skills data-visualization

For use in Claude.ai and ChatGPT

Download Skill