matplotlib

Topics in the source

• Matplotlib
• Overview
• When to Use This Skill
• Core Concepts
• The Matplotlib Hierarchy
• Two Interfaces
• Common Workflows
• 1. Basic Plot Creation

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. 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 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 1. pyplot Interfac

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