matplotlib
Foundational Python plotting library for creating static, animated, and interactive visualizations across scientific, statistical, and publication workflows.
- Supports two interfaces: pyplot (MATLAB-style, quick exploration) and object-oriented (recommended for production code with explicit Figure/Axes control)
- Covers 10+ plot types including line, scatter, bar, histogram, heatmap, contour, box, violin, and 3D plots with customizable colors, styles, labels, and legends
- Exports to PNG, PDF, and SVG formats at configurable DPI (72–300) with options for transparency and tight bounding boxes
- Includes subplot management via regular grids, mosaic layouts, and GridSpec for complex multi-panel figures; integrates with NumPy, Pandas, Seaborn, and Jupyter notebooks
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
Core Concepts
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