Use ax.set_xlim(left, right) and ax.set_ylim(bottom, top) to set fixed axis ranges on a Matplotlib Axes. If your code uses pyplot’s current Axes instead, use plt.xlim(...) and plt.ylim(...). Explicit limits normally turn off autoscaling for the axis you set, so later data may fall outside the visible range.
Set the x- and y-axis ranges with an Axes object
When you create a plot with plt.subplots(), keep the returned Axes object and set its limits directly:
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.plot(x, y)
ax.set_xlim(0, 10) # Show x values from 0 to 10
ax.set_ylim(-1, 1) # Show y values from -1 to 1
The arguments give the two ends of the visible data-coordinate range. In set_xlim, they are the left and right endpoints; in set_ylim, they are the bottom and top endpoints. See the Axes.set_ylim API documentation and Axes.set_xlim API documentation.
Choose between Axes methods and pyplot
Both styles set limits, but they target the plot differently. Prefer Axes methods when you have an Axes object, especially if a figure contains multiple subplots; pyplot functions act on the current Axes.
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| Approach | Example | Targets |
|---|---|---|
| Axes methods | ax.set_xlim(0, 10)ax.set_ylim(-1, 1) |
The specific Axes referenced by ax. |
| Pyplot functions | plt.xlim(0, 10)plt.ylim(-1, 1) |
The current Axes. Calling plt.ylim() or plt.xlim() without arguments returns the current limits. |
For a compact alternative, ax.set(xlim=(0, 10), ylim=(-1, 1)) sets both ranges on one Axes. Pyplot’s plt.axis([xmin, xmax, ymin, ymax]) also sets both, in that order. See the pyplot.axis documentation.
Understand what happens to autoscaling
Matplotlib’s autoscaling adjusts axis limits to keep plotted data visible. Setting explicit limits turns autoscaling off for the affected axis by default. If you add data later, it may extend beyond the displayed window. To return to a data-based view, call ax.autoscale(); Matplotlib documents this as re-enabling autoscaling and recalculating the limits. See the Matplotlib autoscaling guide.
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You can change only one endpoint instead of supplying both. For example, ax.set_ylim(top=5) changes the top while leaving the bottom unchanged; plt.ylim(bottom=1) changes only the bottom limit on the current Axes. The auto parameter of Axes.set_ylim controls autoscaling behavior; consult the API reference for its options.
Use margins for automatic padding, not fixed bounds
If you want space around the data while retaining an automatically calculated range, set margins rather than hard limits. Matplotlib’s documented default margins are 0.05 on both x and y—5% of the data span. For example, ax.margins(x=0.1, y=0.2) requests 10% x and 20% y margins. The values are documented in the autoscaling guide.
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Some artists, including images drawn with imshow, have sticky edges that can suppress outward margin expansion at a data boundary. If you need margins to apply there, set ax.use_sticky_edges = False for that Axes.
Reverse an axis when the data direction calls for it
Give the endpoints in reverse order to reverse the axis direction. For example, ax.set_ylim(5000, 0) places 5000 at the bottom and 0 at the top, a documented arrangement for ocean depth. The range is still explicit; only its direction changes. See the set_ylim reference.
Do not confuse axis limits with aspect modes
Pyplot’s plt.axis also supports modes such as 'equal', 'scaled', 'tight', 'auto', 'image', and 'square'. These control axis presentation or aspect behavior rather than simply specifying a fixed x/y window. In particular, equal aspect can change limits to achieve equal scaling, so it may not preserve the fixed ranges you set. Use explicit limits for a numeric window and an aspect mode only when its scaling behavior is intended; see the axis mode reference.
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Check the installed Matplotlib version for pinned code
The linked stable documentation surfaced version labels 3.11.1 for the autoscaling guide and 3.11.2 for API and user-guide pages on October 4, 2026. If a project pins Matplotlib to a particular release, verify the relevant API against that installed version.
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