[python] How to change plot background color?

I am making a scatter plot in matplotlib and need to change the background of the actual plot to black. I know how to change the face color of the plot using:

fig = plt.figure()
fig.patch.set_facecolor('xkcd:mint green')

enter image description here

My issue is that this changes the color of the space around the plot. How to I change the actual background color of the plot?

This question is related to python matplotlib

The answer is


If you already have axes object, just like in Nick T's answer, you can also use

 ax.patch.set_facecolor('black')

simpler answer:

ax = plt.axes()
ax.set_facecolor('silver')

Use the set_facecolor(color) method of the axes object, which you've created one of the following ways:

  • You created a figure and axis/es together

    fig, ax = plt.subplots(nrows=1, ncols=1)
    
  • You created a figure, then axis/es later

    fig = plt.figure()
    ax = fig.add_subplot(1, 1, 1) # nrows, ncols, index
    
  • You used the stateful API (if you're doing anything more than a few lines, and especially if you have multiple plots, the object-oriented methods above make life easier because you can refer to specific figures, plot on certain axes, and customize either)

    plt.plot(...)
    ax = plt.gca()
    

Then you can use set_facecolor:

ax.set_facecolor('xkcd:salmon')
ax.set_facecolor((1.0, 0.47, 0.42))

example plot with pink background on the axes

As a refresher for what colors can be:

matplotlib.colors

Matplotlib recognizes the following formats to specify a color:

  • an RGB or RGBA tuple of float values in [0, 1] (e.g., (0.1, 0.2, 0.5) or (0.1, 0.2, 0.5, 0.3));
  • a hex RGB or RGBA string (e.g., '#0F0F0F' or '#0F0F0F0F');
  • a string representation of a float value in [0, 1] inclusive for gray level (e.g., '0.5');
  • one of {'b', 'g', 'r', 'c', 'm', 'y', 'k', 'w'};
  • a X11/CSS4 color name;
  • a name from the xkcd color survey; prefixed with 'xkcd:' (e.g., 'xkcd:sky blue');
  • one of {'tab:blue', 'tab:orange', 'tab:green', 'tab:red', 'tab:purple', 'tab:brown', 'tab:pink', 'tab:gray', 'tab:olive', 'tab:cyan'} which are the Tableau Colors from the ‘T10’ categorical palette (which is the default color cycle);
  • a “CN” color spec, i.e. 'C' followed by a single digit, which is an index into the default property cycle (matplotlib.rcParams['axes.prop_cycle']); the indexing occurs at artist creation time and defaults to black if the cycle does not include color.

All string specifications of color, other than “CN”, are case-insensitive.


Something like this? Use the axisbg keyword to subplot:

>>> from matplotlib.figure import Figure
>>> from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
>>> figure = Figure()
>>> canvas = FigureCanvas(figure)
>>> axes = figure.add_subplot(1, 1, 1, axisbg='red')
>>> axes.plot([1,2,3])
[<matplotlib.lines.Line2D object at 0x2827e50>]
>>> canvas.print_figure('red-bg.png')

(Granted, not a scatter plot, and not a black background.)

enter image description here


One method is to manually set the default for the axis background color within your script (see Customizing matplotlib):

import matplotlib.pyplot as plt
plt.rcParams['axes.facecolor'] = 'black'

This is in contrast to Nick T's method which changes the background color for a specific axes object. Resetting the defaults is useful if you're making multiple different plots with similar styles and don't want to keep changing different axes objects.

Note: The equivalent for

fig = plt.figure()
fig.patch.set_facecolor('black')

from your question is:

plt.rcParams['figure.facecolor'] = 'black'

One suggestion in other answers is to use ax.set_axis_bgcolor("red"). This however is deprecated, and doesn't work on MatPlotLib >= v2.0.

There is also the suggestion to use ax.patch.set_facecolor("red") (works on both MatPlotLib v1.5 & v2.2). While this works fine, an even easier solution for v2.0+ is to use

ax.set_facecolor("red")


The easiest thing is probably to provide the color when you create the plot :

fig1 = plt.figure(facecolor=(1, 1, 1))

or

fig1, (ax1, ax2) = plt.subplots(nrows=1, ncols=2, facecolor=(1, 1, 1))