How does the skill help with chart selection?

It includes a logic-driven guide that recommends specific charts based on whether you are showing trends, comparisons, rankings, distributions, or correlations.

Does it follow data visualization best practices?

Yes, it enforces industry standards such as starting bar charts at zero, avoiding 3D effects, using purposeful color theory, and ensuring high contrast for readability.

Are the generated charts accessible?

Absolutely. The skill prioritizes accessibility by utilizing colorblind-friendly palettes, recommending direct labeling over legends, and providing screen reader considerations.

Which Python libraries does this skill support?

The skill provides optimized code patterns and styling for Matplotlib, Seaborn, and Plotly, covering both static and interactive visualization needs.

Data Visualization & Charting

Name: Data Visualization & Charting
Author: anthropics

byanthropics

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8,000

•

データサイエンスとML

Generates professional, accessible, and insightful data visualizations using Python's leading charting libraries like Matplotlib and Seaborn.

The Data Visualization skill empowers users to transform raw data into clear, publication-quality figures using Python libraries such as Matplotlib, Seaborn, and Plotly. It provides expert guidance on choosing the most effective chart type based on data relationships—ranging from simple time-series lines to complex heatmaps and small multiples. By enforcing rigorous design principles and accessibility standards, this skill ensures that every visualization is not only aesthetically pleasing but also scientifically accurate and readable for all audiences, including those with color vision deficiencies.

主な機能

01Production-ready Python code patterns for Matplotlib, Seaborn, and Plotly

02Built-in colorblind-friendly palettes and accessibility checklists

038,000 GitHub stars

04Support for interactive visualizations and complex multi-panel layouts

05Expert chart selection logic based on specific data relationships and goals

06Professional styling configurations for publication-quality output

ユースケース

01Performing exploratory data analysis with interactive Plotly visualizations

02Transforming raw CSV or JSON data into executive-level reporting dashboards

03Creating publication-ready academic figures with proper axis formatting and annotations

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add anthropics/knowledge-work-plugins data-visualization

For use in Claude.ai and ChatGPT

Download Skill