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SkillHub ClubAnalyze Data & AIData / AI

matplotlib

This skill provides detailed guidance for using matplotlib, covering both pyplot and object-oriented interfaces. It includes practical examples for common plot types, troubleshooting tips for frequent issues, and best practices for creating publication-quality figures. The documentation helps users understand when to choose matplotlib over alternatives like seaborn or plotly.

Packaged view

This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.

Stars
15,354
Hot score
99
Updated
March 20, 2026
Overall rating
A8.9
Composite score
8.1
Best-practice grade
N/A

Install command

npx @skill-hub/cli install k-dense-ai-claude-scientific-skills-matplotlib
data-visualizationpythonscientific-computingplottingcharts

Repository

K-Dense-AI/claude-scientific-skills

Skill path: scientific-skills/matplotlib

This skill provides detailed guidance for using matplotlib, covering both pyplot and object-oriented interfaces. It includes practical examples for common plot types, troubleshooting tips for frequent issues, and best practices for creating publication-quality figures. The documentation helps users understand when to choose matplotlib over alternatives like seaborn or plotly.

Open repository

Best for

Primary workflow: Analyze Data & AI.

Technical facets: Data / AI.

Target audience: Data teams looking for install-ready agent workflows..

License: Unknown.

Original source

Catalog source: SkillHub Club.

Repository owner: K-Dense-AI.

This is still a mirrored public skill entry. Review the repository before installing into production workflows.

What it helps with

  • Install matplotlib into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
  • Review https://github.com/K-Dense-AI/claude-scientific-skills before adding matplotlib to shared team environments
  • Use matplotlib for data workflows

Works across

Claude CodeCodex CLIGemini CLIOpenCode

Favorites: 0.

Sub-skills: 0.

Aggregator: No.