matplotliblisted

# 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 ### 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)** ```python import matplotlib.pyplot as plt plt.plot([1, 2, 3, 4]) plt.ylabel('some numbers') plt.show() ``` - C