PC Slower Than It Used to Be?
A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11Outdated Drivers Are Slowing You Down
One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchxlim does not make a Matplotlib axis logarithmic; it sets the visible x-range. Set the scale with ax.set_xscale("log") or plt.xscale("log"), then use set_xlim or xlim only when you want fixed bounds.
Make the x-axis logarithmic
For an object-oriented plot, call set_xscale("log") on the same Axes that contains the plot:
As an Amazon Associate I earn from qualifying purchases.
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.plot(x, y)
ax.set_xscale("log")
plt.show()With pyplot’s current-axes workflow, the equivalent call is plt.xscale("log"). Matplotlib’s pyplot.xscale reference describes this function as setting the x-axis scale; it also documents that keyword arguments are passed to the selected scale class.
Set the visible range separately with xlim
If you want to restrict the displayed range, set positive lower and upper bounds after choosing the logarithmic scale:
#1 Best Overall
ax.set_xscale("log")
ax.set_xlim(0.1, 1000)Use plt.xlim(0.1, 1000) instead when working with pyplot’s current axes. For more control, pyplot accepts a pair as plt.xlim((left, right)), or lets you change one side with plt.xlim(left=...) or plt.xlim(right=...). The Matplotlib 3.6.0 xlim reference documents these forms and states that setting limits turns x-axis autoscaling off.
Keep autoscaling or fix the bounds
Leave out xlim or set_xlim if Matplotlib should choose the displayed x-range from the plotted data. Once you set explicit limits, the range is fixed rather than autoscaled; remove that call or update its values when you want a different view.
Use positive values on an ordinary log axis
A conventional logarithmic x-axis requires positive x-values and positive displayed bounds. If your data or bounds include zero or negative values, they are not part of an ordinary log domain. Matplotlib’s older 3.3.4 loglog reference discusses masking or clipping nonpositive values, but that page concerns loglog and is not a current guarantee for xscale. Check the documentation for the Matplotlib version installed in your project before relying on scale-specific options.
Troubleshoot a scale or range that seems unchanged
- The axis still appears linear: Set the scale on the Axes that actually holds the plot, or ensure
plt.xscale("log")is called while that axes is current. - The range does not follow new data: An explicit
xlimorset_xlimcall disables x-axis autoscaling. Remove it or set new bounds. - Only one edge needs adjustment: In pyplot, supply just
left=orright=toplt.xlim.
Choose scale options for your Matplotlib version
The stable pyplot.xscale documentation is labeled for Matplotlib 3.11.1 and shows scale selection through xscale(value, **kwargs). The linked xlim reference is for Matplotlib 3.6.0, while the cited discussion of nonpositive values is from Matplotlib 3.3.4. For non-default log bases or handling nonpositive values, consult the API documentation matching the version you have installed rather than assuming older option defaults still apply.
Quick Recap
Rank #4
Rank #3
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
