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Matplotlib

Maintainer K-Dense Inc. · Last updated March 31, 2026

Matplotlib is Python's foundational visuali.

Claude CodeOpenClawNanoClawAnalysisWritingmatplotlibdocument-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
March 31, 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:

  1. Figure - The top-level container for all plot elements
  2. Axes - The actual plotting area where data is displayed (one Figure can contain multiple Axes)
  3. Artist - Everything visible on the figure (lines, text, ticks, etc.)
  4. 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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