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When creating multiple subplots in Matplotlib, adjusting spacing is crucial to avoid overlapping labels, titles, and axes. There are several effective ways to control subplot spacing.
Using tight_layout()
Steps:
Create your subplots with plt.subplots() or plt.subplot().
Call fig.tight_layout() (or plt.tight_layout()) after plotting.
Optionally, adjust padding with the pad parameter.
import matplotlib.pyplot as pltimport numpy as npx = np.linspace(0, 10, 100)fig, ax = plt.subplots(2, 2, figsize=(6, 6))for i in range(2):for j in range(2):ax[i, j].plot(x, np.sin(x + i + j))fig.tight_layout(pad=3.0) # Adjust paddingplt.show()Copied!✕CopyThis method automatically adjusts subplot parameters to prevent overlaps.
Using subplots_adjust()
Steps:
After creating subplots, call plt.subplots_adjust() or fig.subplots_adjust().
Modify parameters like: wspace (width space between subplots) hspace (height space between subplots) Margins: left, right, top, bottom
Improve subplot size/spacing with many subplots - Stack Overflow
I need to generate a whole bunch of vertically-stacked plots in matplotlib. The result will be saved using savefig and viewed on a webpage, so I don't care how tall the final image is, as long as the subplots …
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Code sample
fig, axes = plt.subplots(nrows=4, ncols=4)fig.tight_layout() # Or equivalently, "plt.tight_layout()"plt.show()Subplots spacings and margins — Matplotlib 3.10.8 …
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- In some cases you may also have titles for each of your subplots. Unfortunately even the tight_layout()function tends to cause the subplot titles to overlap: The way to resolve this issue is by increasing the height padding between subplots using the h_padargument:
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Matplotlib provides several methods to control subplot spacing, including tight_layout() and subplots_adjust(). This tutorial explores these methods with …
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