Customizing Plot Background Colors in Matplotlib

Matplotlib is a powerful Python library for creating visualizations. A crucial aspect of creating effective plots is customizing their appearance, including the background color. This tutorial will guide you through various methods to change the background color of your plots, both for individual axes and for all plots within your script.

Understanding the Different Backgrounds

Before diving into the code, it’s important to understand that Matplotlib has two main background areas:

Figure Background: This is the overall canvas or area surrounding your plot.
Axes Background: This is the area within the plot where the data is displayed – the actual plotting area. Often, users intend to modify the axes background, not the overall figure background.

Changing the Axes Background Color

The most common requirement is to change the background color of the plotting area itself (the axes). Here’s how you can achieve this:

Using ax.set_facecolor():

If you’ve already created an axes object (typically named ax), you can directly use the set_facecolor() method:

import matplotlib.pyplot as plt

fig, ax = plt.subplots()  # Create a figure and an axes object

ax.set_facecolor('xkcd:salmon') #Set the face color of the axes to salmon

# Example Plot
ax.plot([1, 2, 3, 4], [5, 6, 7, 8])

plt.show()

You can also specify colors using other formats, such as RGB tuples or hex codes:

ax.set_facecolor((0.8, 0.8, 0.8))  # Light Gray
ax.set_facecolor('#E6E6E6')          # Light Gray (Hex code)

Using ax.patch.set_facecolor():

Another approach is to access the patch object associated with the axes and set its face color:

import matplotlib.pyplot as plt

fig, ax = plt.subplots()
ax.patch.set_facecolor('silver')
ax.plot([1, 2, 3, 4], [5, 6, 7, 8])
plt.show()

Changing the Figure Background Color

To change the background color of the entire figure (the canvas surrounding the plot), use the following approach:

import matplotlib.pyplot as plt

fig = plt.figure()
fig.patch.set_facecolor('black') # Set figure background to black

ax = fig.add_subplot(1, 1, 1)  # Add an axes to the figure
ax.plot([1, 2, 3, 4], [5, 6, 7, 8])

plt.show()

Setting Default Background Colors for All Plots

If you want to consistently change the background color for all plots in your script, you can modify the Matplotlib runtime configuration parameters (rcParams):

import matplotlib.pyplot as plt

plt.rcParams['figure.facecolor'] = 'black'  # Set default figure background color
plt.rcParams['axes.facecolor'] = 'lightgrey' #Set the default axes background color

# Subsequent plots will automatically have these background colors
fig, ax = plt.subplots()
ax.plot([1, 2, 3, 4], [5, 6, 7, 8])
plt.show()

Using rcParams is particularly useful when creating a series of plots with a consistent style.

Color Specifications

Matplotlib offers a wide range of ways to specify colors:

RGB/RGBA Tuples: (0.1, 0.2, 0.5) (RGB) or (0.1, 0.2, 0.5, 0.3) (RGBA – includes transparency) with values between 0 and 1.
Hex Codes: '#0F0F0F' (RGB) or '#0F0F0F0F' (RGBA)
Grayscale: A float between 0 and 1 (e.g., '0.5')
Named Colors: 'red', 'green', 'blue', etc.
xkcd Colors: 'xkcd:sky blue', (requires internet access)
Tablo Colors: 'tab:blue', 'tab:orange', etc.

Refer to the Matplotlib documentation for a complete list of available color options: https://matplotlib.org/api/colors_api.html