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数据与复现科学可视化与传播K-Dense-AI/claude-scientific-skills数据与复现
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Matplotlib

维护者 K-Dense Inc. · 最近更新 2026年3月31日

Matplotlib is Python's foundational visuali。

Claude CodeOpenClawNanoClaw分析处理写作整理matplotlibdocument-processingpackagedata analysis & visualization

原始来源

K-Dense-AI/claude-scientific-skills

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

维护者
K-Dense Inc.
许可
https://github.com/matplotlib/matplotlib/tree/main/LICENSE
最近更新
2026年3月31日

技能摘要

来自 SKILL.md 的关键信息

2 min

核心说明

  • Matplotlib is Python's foundational visualization 库 ，用于 creating static，animated，、 interactive plots. This skill provides guidance on ，使用 matplotlib effectively，covering both pyplot interface (MATLAB-style) 、 object-oriented API (Figure/Axes)，along ，支持 best practices ，用于 creating publication-quality visualizations。
  • fig，ax = plt.subplots(figsize=(10，6))。

原始文档

SKILL.md 摘录

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

适用场景

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

不适用场景

  • Do not rely on this catalog entry alone ，用于 installation 或 maintenance details。

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