Matplotlib

This is the plotting library you'll use for pretty much any data visualization in Python. The skill covers both the pyplot interface and the object-oriented API, though it strongly recommends the latter for anything beyond quick exploration. You get clear guidance on the full range of plot types (line, scatter, bar, heatmaps, 3D), subplot layouts including the flexible mosaic approach, and exporting at the right DPI for your target medium. The styling section is practical, covering colormaps, rcParams, and annotations. If you're making charts in Python, whether for notebooks, papers, or dashboards, you're probably using matplotlib, and this gives you the patterns to do it cleanly.

skills.sh installs: 1.1K
GitHub stars: 33.2K
last updated: Aug 21, 2026

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Install

$ npx -y skills add davila7/claude-code-templates --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