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Set the same limits on existing subplots
For axes that already exist and should remain independent, call set_xlim and set_ylim on every axes object. The bounds are specified as pairs in data coordinates:
import matplotlib.pyplot as plt
import numpy as np
fig, axs = plt.subplots(2, 2)
for ax in axs.flat:
ax.set_xlim(0, 10)
ax.set_ylim(-1, 1)
plt.show()axs.flat iterates across the axes whether they are arranged in one or multiple dimensions. The shape returned by plt.subplots depends on the grid and its squeeze option: with the default, a one-panel call can return a single Axes, not an array. For consistent array handling, create the grid with squeeze=False, or handle the single axes separately. See the Matplotlib pyplot.subplots API.
Use axes methods rather than plt.xlim or plt.ylim inside a loop. Those pyplot functions act on the current axes, while ax.set_xlim and ax.set_ylim explicitly target the axes in each iteration. See the Matplotlib set_xlim reference and set_ylim reference.
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Share axes when panels should stay synchronized
If you are creating the subplots and want a limit change in one panel to affect the others, pass the sharing options to plt.subplots:
fig, axs = plt.subplots(2, 2, sharex=True, sharey=True)
for ax in axs.flat:
ax.plot(x, y)
for ax in axs.flat:
ax.set_xlim(0, 10)
ax.set_ylim(-1, 1)
plt.show()Here, the loop sets the desired bounds, and the shared-axis configuration keeps the corresponding limits linked. Matplotlib documents that autoscaling considers data on all axes in a shared group; limit changes, including interactive zoom and pan, affect all of them. This is useful for direct visual comparisons, but means a change made through one panel is not isolated. See the Matplotlib shared-axis example.
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Choose which panels share each dimension
The x and y sharing options are independent. Set only the dimension that needs to align: for example, sharex=True with sharey=False keeps time aligned while allowing each subplot its own vertical scale. Matplotlib also supports sharing within rows or columns.
| Option | Effect |
|---|---|
True or 'all' |
Share the axis across all subplots. |
'row' |
Share within each row. |
'col' |
Share within each column. |
False or 'none' |
Keep the axes independent. |
These settings are available separately as sharex and sharey in plt.subplots. Sharing is a creation-time choice; if axes already exist independently, use the setters to give them matching bounds without linking them.
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Understand autoscaling after setting limits
Calling set_xlim or set_ylim sets explicit bounds and disables autoscaling for that axis by default. If you later want Matplotlib to calculate bounds from the plotted data again, use Axes.autoscale for the relevant axis. Consult the Matplotlib autoscaling guide for the behavior and controls.
In short, use shared axes for panels that should remain linked, and per-axes setters for matching bounds that are only an initial condition. A common x range such as 0 to 4 is set with ax.set_xlim(0, 4) in the loop, or on one member of a shared-x group.
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