Matplotlib

The foundational Python plotting library, best used when you need full control over every visual element or you're building custom plot types that higher-level tools can't handle. The skill walks you through both the pyplot interface and the object-oriented API, though it strongly recommends the latter for anything beyond quick exploration. You get solid coverage of the entire plotting hierarchy (Figure, Axes, Artist objects), subplot layouts with GridSpec, and export settings for publication-quality output. Honestly, if you just need statistical plots, reach for seaborn instead. But when you're wrestling with multi-panel scientific figures or need pixel-perfect customization for a journal, this is what you use.

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GitHub stars: 56.6K
last updated: Aug 21, 2026

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Install

$ npx -y skills add k-dense-ai/scientific-agent-skills --skill matplotlib --agent claude-code

Installs into .claude/skills of the current project.

Files

Matplotlib

Overview

Matplotlib is Python's foundational visualization library for creating static, animated, and interactive plots. This skill provides guidance on using matplotlib effectively, covering both the pyplot interface (MATLAB-style) and the object-oriented API (Figure/Axes), along with best practices for creating publication-quality visualizations.

When to Use This Skill

This skill should be used when:

Creating any type of plot or chart (line, scatter, bar, histogram, heatmap, contour, etc.)
Generating scientific or statistical visualizations
Customizing plot appearance (colors, styles, labels, legends)
Creating multi-panel figures with subplots
Exporting visualizations to various formats (PNG, PDF, SVG, etc.)
Building interactive plots or animations
Working with 3D visualizations
Integrating plots into Jupyter notebooks or GUI applications