Matplotlib Deep Dive

python
Run Inline
import matplotlib.pyplot as plt
import numpy as np
# Create figure and axes
fig, axes = plt.subplots(2, 2, figsize=(10, 8))
# Custom styling
plt.style.use('seaborn-v0_8-whitegrid')
# Annotations
x = np.linspace(0, 10, 100)
axes[0, 0].plot(x, np.sin(x), label='sin(x)')
axes[0, 0].annotate('Peak', xy=(np.pi/2, 1),
                     xytext=(np.pi/2, 1.2),
                     arrowprops=dict(arrowstyle='->'))
axes[0, 0].legend()
axes[0, 0].set_title('Sine Wave')
axes[0, 0].set_xlabel('x')
axes[0, 0].set_ylabel('sin(x)')
# Tight layout
plt.tight_layout()
plt.show()

Matplotlib Best Practices

• Use plt.subplots() (the OO API) instead of plt.plot() (pyplot)
• Always include axis labels and titles
• Use fig.tight_layout() to prevent overlapping
• Set appropriate figure sizes
• Export to SVG/PDF for vector graphics in publications Join Discord PreviousAccessible DesignNextTool Comparison