Data & ReproStatistics & Data AnalysisK-Dense-AI/claude-scientific-skillsData & Reproduction

Matplotlib

Maintainer K-Dense Inc. · Last updated April 1, 2026

Matplotlib is Python's foundational visuali.

Claude CodeOpenClawNanoClawAnalysisReproductionmatplotlibdocument-processingpackagedata analysis & visualization

Original source

K-Dense-AI/claude-scientific-skills

https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/matplotlib

Maintainer: K-Dense Inc.
License: https://github.com/matplotlib/matplotlib/tree/main/LICENSE
Last updated: April 1, 2026

Skill Snapshot

Key Details From SKILL.md

2 min

Key Notes

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.
fig, ax = plt.subplots(figsize=(10, 6)).

Source Doc

Excerpt From SKILL.md

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

The Matplotlib Hierarchy

Matplotlib uses a hierarchical structure of objects:

Figure - The top-level container for all plot elements
Axes - The actual plotting area where data is displayed (one Figure can contain multiple Axes)
Artist - Everything visible on the figure (lines, text, ticks, etc.)
Axis - The number line objects (x-axis, y-axis) that handle ticks and labels

Two Interfaces

1. pyplot Interface (Implicit, MATLAB-style)

Convenient for quick, simple plots
Maintains state automatically
Good for interactive work and simple scripts

2. Object-Oriented Interface (Explicit)

Recommended for most use cases
More explicit control over figure and axes
Better for complex figures with multiple subplots
Easier to maintain and debug

Use cases

Creating any type of plot or chart (line, scatter, bar, histogram, heatmap, contour, etc.).
Generating scientific or statistical visuali.

Not for

Do not rely on this catalog entry alone for installation or maintenance details.

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