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To give every Matplotlib subplot the same axis limits, either create the subplots with shared axes or set the limits on each Axes in a loop. Use shared axes when panels should stay synchronized as you zoom or pan; set limits individually when the panels should remain independent.
Choose between shared axes and individual limits
| Approach | Best for | What happens after zooming or panning |
|---|---|---|
sharex and/or sharey in plt.subplots |
Panels that should share limits for the selected dimensions. | Limits stay synchronized across each shared group. |
set_xlim and/or set_ylim on each Axes |
Matching initial ranges while keeping panels independent. | Later changes to one Axes do not automatically change the others. |
Share limits when creating the subplots
Pass sharex=True and sharey=True to plt.subplots to share both dimensions across all panels. Use just one option if only that dimension should match. Matplotlib supports sharing by all subplots, by column, or by row; True is equivalent to 'all', while False is equivalent to 'none'. See the pyplot.subplots API.
import matplotlib.pyplot as plt
fig, axs = plt.subplots(2, 2, sharex=True, sharey=True)
for ax in axs.flat:
ax.plot([0, 1, 2], [0, 1, 0])
plt.show()For more selective grouping, use sharex='col' or sharey='row'. This is useful when, for example, plots in each column should use the same x range but different columns should not be linked.
Shared axes synchronize limits and interactive navigation: Matplotlib’s shared-axis example explains that autoscaling considers data on all shared Axes, and limit changes—including interactive zooming and panning—affect the group.
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Set the same bounds on existing independent subplots
If the Axes already exist and should remain independent, call set_xlim and set_ylim on each one. The bounds are supplied as pairs in data coordinates.
import matplotlib.pyplot as plt
fig, axs = plt.subplots(2, 2)
for ax in axs.flat:
ax.plot([0, 2, 5, 10], [-1, 0, 0.5, 1])
ax.set_xlim(0, 10)
ax.set_ylim(-1, 1)
plt.show()For an x range of 0 to 4 on every panel, use ax.set_xlim(0, 4) inside the loop. To match only x limits, omit set_ylim; to match only y limits, omit set_xlim. The official references document these setters for x limits and y limits.
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Handle the shape of the Axes result
For a 2-by-2 grid, axs is an array, so axs.flat visits each Axes. For a one-subplot layout, plt.subplots returns a single Axes by default rather than an array. You can handle that case separately or request squeeze=False to keep the result two-dimensional. The return shape depends on the grid dimensions and the squeeze setting, as described in the subplots API.
Understand what manual limits do to autoscaling
Calling set_xlim or set_ylim disables autoscaling for that axis by default. If you later want Matplotlib to recalculate bounds from the data, use Axes.autoscale; the autoscaling guide describes how it re-enables autoscaling and adjusts limits to fit the data.
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Target the intended Axes explicitly
Prefer ax.set_xlim(...) and ax.set_ylim(...) inside a loop. The pyplot functions plt.xlim and plt.ylim operate on the current Axes, so their target depends on pyplot state. The pyplot.ylim reference documents this current-Axes behavior.
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