Manipulation on vertical space in Matplotlib subplots

To manipulate vertical space in Matplotlib subplots, we can use the hspace parameter in the subplots_adjust() method. This allows us to control the spacing between subplot rows.

Understanding hspace Parameter

The hspace parameter controls the height of padding between subplots as a fraction of the average subplot height. Values greater than 1.0 create more space, while values less than 1.0 reduce space.

Basic Example with Vertical Space Adjustment

Let's create a 2×2 subplot layout and adjust the vertical spacing ?

import numpy as np
import matplotlib.pyplot as plt

# Set figure size
plt.rcParams["figure.figsize"] = [7.50, 3.50]
plt.rcParams["figure.autolayout"] = True

# Create data
x = np.linspace(0, 2 * np.pi, 400)
y = np.sin(x ** 2)

# Create subplots
fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(nrows=2, ncols=2)

# Plot data in each subplot
ax1.plot(x, y)
ax1.set_title('Subplot 1')

ax2.plot(x, np.cos(x))
ax2.set_title('Subplot 2')

ax3.plot(x, np.tan(x))
ax3.set_title('Subplot 3')

ax4.plot(x, y * 2)
ax4.set_title('Subplot 4')

# Adjust vertical space
fig.subplots_adjust(hspace=1)

plt.show()

Comparing Different hspace Values

Here's how different hspace values affect vertical spacing ?

import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(0, 10, 100)

# Create figure with multiple examples
fig = plt.figure(figsize=(12, 8))

# Example 1: hspace = 0.2 (tight spacing)
plt.subplot(1, 3, 1)
fig1, axes1 = plt.subplots(3, 1, figsize=(4, 6))
for i, ax in enumerate(axes1):
    ax.plot(x, np.sin(x + i))
    ax.set_title(f'Plot {i+1}')
fig1.subplots_adjust(hspace=0.2)
plt.title('hspace=0.2')

# Example 2: hspace = 0.5 (medium spacing)  
fig2, axes2 = plt.subplots(3, 1, figsize=(4, 6))
for i, ax in enumerate(axes2):
    ax.plot(x, np.cos(x + i))
    ax.set_title(f'Plot {i+1}')
fig2.subplots_adjust(hspace=0.5)

# Example 3: hspace = 1.0 (large spacing)
fig3, axes3 = plt.subplots(3, 1, figsize=(4, 6))  
for i, ax in enumerate(axes3):
    ax.plot(x, np.tan(x + i))
    ax.set_title(f'Plot {i+1}')
fig3.subplots_adjust(hspace=1.0)

plt.show()

Key Parameters

Complete Example with Multiple Adjustments

import numpy as np
import matplotlib.pyplot as plt

# Create data
x = np.linspace(0, 2 * np.pi, 100)
y1 = np.sin(x)
y2 = np.cos(x)
y3 = np.tan(x)
y4 = np.sin(2 * x)

# Create subplots
fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(nrows=2, ncols=2, figsize=(10, 8))

# Plot data
ax1.plot(x, y1, 'r-')
ax1.set_title('sin(x)')

ax2.plot(x, y2, 'g-')
ax2.set_title('cos(x)')

ax3.plot(x, y3, 'b-')
ax3.set_title('tan(x)')
ax3.set_ylim(-5, 5)

ax4.plot(x, y4, 'm-')
ax4.set_title('sin(2x)')

# Adjust both vertical and horizontal spacing
fig.subplots_adjust(hspace=0.8, wspace=0.4, top=0.9, bottom=0.1)

plt.show()

Conclusion

Use fig.subplots_adjust(hspace=value) to control vertical spacing between subplot rows. Values around 0.2-0.5 work well for most cases, while larger values like 1.0 provide generous spacing for complex plots with titles and labels.