How to make more than 10 subplots in a figure using Matplotlib?

Creating more than 10 subplots in a single figure is common when visualizing multiple datasets or comparing different plots. Matplotlib's subplots() function makes this straightforward by arranging plots in a grid layout.

Basic Grid Layout

Use nrows and ncols parameters to create a grid of subplots ?

import matplotlib.pyplot as plt
import numpy as np

# Set figure size for better visibility
plt.rcParams["figure.figsize"] = [12, 8]
plt.rcParams["figure.autolayout"] = True

# Create 4x3 grid (12 subplots)
rows = 4
cols = 3

fig, axes = plt.subplots(nrows=rows, ncols=cols)

# Add sample plots to each subplot
for i in range(rows):
    for j in range(cols):
        x = np.linspace(0, 10, 50)
        y = np.sin(x + i + j)
        axes[i, j].plot(x, y)
        axes[i, j].set_title(f'Plot {i*cols + j + 1}')

plt.show()

Customizing Large Subplot Grids

For better organization with many subplots, adjust spacing and add meaningful titles ?

import matplotlib.pyplot as plt
import numpy as np

# Create 3x5 grid (15 subplots)
fig, axes = plt.subplots(3, 5, figsize=(15, 9))

# Sample data for demonstration
x = np.linspace(0, 2*np.pi, 100)

# Flatten axes for easier iteration
axes_flat = axes.flatten()

for i, ax in enumerate(axes_flat):
    # Different function for each subplot
    if i % 3 == 0:
        y = np.sin(x * (i+1))
    elif i % 3 == 1:
        y = np.cos(x * (i+1))
    else:
        y = np.tan(x * (i+1) * 0.5)
    
    ax.plot(x, y)
    ax.set_title(f'Subplot {i+1}')
    ax.grid(True)

# Adjust spacing between subplots
plt.tight_layout(pad=2.0)
plt.show()

Using subplot_mosaic for Complex Layouts

For irregular grid layouts with more than 10 subplots, use subplot_mosaic() ?

import matplotlib.pyplot as plt
import numpy as np

# Define complex layout with named subplots
mosaic = [
    ['A', 'A', 'B', 'C'],
    ['D', 'E', 'F', 'G'], 
    ['H', 'I', 'J', 'K'],
    ['L', 'M', 'N', 'O']
]

fig, axes = plt.subplot_mosaic(mosaic, figsize=(12, 10))

# Add data to each named subplot
plot_names = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O']
x = np.linspace(0, 10, 50)

for i, name in enumerate(plot_names):
    y = np.sin(x + i) * np.exp(-x/10)
    axes[name].plot(x, y)
    axes[name].set_title(f'Plot {name}')

plt.tight_layout()
plt.show()

Key Considerations

Conclusion

Use subplots(nrows, ncols) for regular grids with many subplots. Adjust figure size proportionally and use tight_layout() for proper spacing. Consider subplot_mosaic() for complex irregular layouts.