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Matplotlib uses separate colors for a figure’s outer canvas and each Axes’ plotting area. Set them independently with fig.set_facecolor() and ax.set_facecolor(); when saving, choose the export background with savefig options.
Figure versus Axes: which background are you changing?
The Figure is the top-level container for the plot, including the space around the plotting area. An Axes is the rectangular area where the data is drawn. Each has its own facecolor, so changing one does not automatically change the other. Matplotlib’s background customization example shows both settings together.
Set the inner and outer colors for one plot
Use the object-oriented pattern from plt.subplots() to keep the two targets clear:
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
fig.set_facecolor("lightblue") # outer Figure canvas
ax.set_facecolor("whitesmoke") # inner Axes plotting area
ax.plot([1, 2, 3], [2, 1, 3])
plt.show()fig.patch.set_facecolor("lightblue") is an equivalent direct way to set the Figure patch. Likewise, ax.patch.set_facecolor("whitesmoke") sets the Axes patch; ax.set_facecolor() is the direct Axes method. These APIs are documented in the Figure API and Axes set_facecolor API.
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Use the same background color for both regions
To make the plotting rectangle and surrounding canvas match, set both objects to the same color:
fig, ax = plt.subplots()
fig.set_facecolor("#f2f2f2")
ax.set_facecolor("#f2f2f2")Set colors across multiple subplots
A Figure can contain several Axes. Set the Figure color once, then set the color on every Axes that should have a custom plotting-area background:
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fig, axes = plt.subplots(1, 2)
fig.set_facecolor("lightblue")
for ax in axes:
ax.set_facecolor("whitesmoke")Each Axes has its own facecolor setting; coloring one does not color its neighboring Axes. The shared outer margin belongs to the Figure.
Choose defaults for future plots
For a repeated look across plots, set Matplotlib’s configuration parameters rather than calling setters on each object. The configuration reference documents figure.facecolor for the Figure and axes.facecolor for Axes. Use per-object setters when only one particular chart needs the change; use configuration or a style when it should become a reusable default.
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Keep the background when saving, or make it transparent
Interactive display and file export have separate controls. The savefig API includes a facecolor argument; its auto value uses the current Figure facecolor. To specify that color explicitly:
fig.savefig("plot.png", facecolor=fig.get_facecolor())For a transparent export, use transparent=True:
fig.savefig("plot.png", transparent=True)The configuration reference also documents savefig.transparent as a default setting. If the saved file looks different from the displayed plot, check the arguments passed to savefig, the applicable configuration, and the target file format. The result of combining explicit facecolor and transparency options can depend on the call arguments and Matplotlib version, so check that version’s API documentation when using both.
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Documentation version
The linked Matplotlib stable documentation was identified as version 3.11.2 when checked. API details may change in later releases; consult the documentation for the version installed in your environment if behavior differs.
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