Matplotlib - Stylesheets

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What are StyleSheets?

In Matplotlib library stylesheets are predefined sets of aesthetic configurations that control the overall appearance of plots. They offer a convenient way to change the look and feel of our plots with minimal effort.

A stylesheet consists of predefined settings for various elements of a plot such as colors, line styles, fonts, grid styles and much more. Matplotlib provides a collection of built-in stylesheets that allow us to quickly apply different visual themes to our plots.

The default style is used when no specific style is set but Matplotlib includes several other styles like gplot, seaborn, bmh, dark_background and more. These stylesheets offer different color schemes, line styles, font settings and overall aesthetics.

Matplotlib provides a variety of built-in stylesheets. Here's an overview of how you can work with them −

Viewing Available Stylesheets

Matplotlib provides different stylesheets that change the overall appearance of plots and altering elements such as colors, line styles, font sizes etc. Stylesheets offer a quick and easy way to change the aesthetics of our visualizations.

Syntax

We can check the available stylesheets using the below syntax.

plt.style.available

Example

Here in this example we are using the plt.style.available to get all the available stylesheets in the Matplotlib library.

import matplotlib.pyplot as plt
# List available stylesheets
print("Available stylesheets:", plt.style.available)

Output

Available stylesheets: [
   'Solarize_Light2', '_classic_test_patch', 
   '_mpl-gallery', '_mpl-gallery-nogrid', 'bmh', 'classic', 
   'dark_background', 'fast', 'fivethirtyeight', 
   'ggplot', 'grayscale', 'seaborn', 'seaborn-bright',
   'seaborn-colorblind', 'seaborn-dark',
   'seaborn-dark-palette', 'seaborn-darkgrid',
   'seaborn-deep', 'seaborn-muted', 'seaborn-notebook',
   'seaborn-paper', 'seaborn-pastel', 'seaborn-poster',
   'seaborn-talk', 'seaborn-ticks', 'seaborn-white',
   'seaborn-whitegrid', 'tableau-colorblind10']

Using Stylesheets

Absolutely to use the Matplotlib stylesheets is straightforward. We can apply a specific style to our plots. Here's the syntax.

Syntax

plt.style.use('stylesheet_name')

Where,

• plt.style.use() − This is used to use the defined stylesheets to the entire plot.

• stylesheet_name − This is the name of the stylesheet that we want to apply.

Example

In this example we are using the stylesheet ggplot by employing the plt.style.use('ggplot') before creating our plot.

import matplotlib.pyplot as plt
# Using a specific stylesheet
plt.style.use('ggplot')  # Example: Using the 'ggplot' style
x = [10,30,20,50]
y = [30,23,45,10]
plt.plot(x,y)
plt.title("Plot with ggplot style sheet")
plt.show()

Output

Applying Stylesheet Temporarily

If we want to apply a stylesheet temporarily to a specific block of code without affecting other plots we can use with plt.style.context('stylesheet_name').

This temporary context applies the specified style only within the block of code indented under the with statement.

Example

In this example we are setting the stylesheet to seaborn-dark by using the plt.style.context() functin available in matplotlib library.

import matplotlib.pyplot as plt
x = [10,30,20,50]
y = [30,23,45,10]
with plt.style.context('seaborn-dark'):
   # Code for a plot with 'seaborn-dark' style
   plt.plot(x, y)
   plt.title('Seaborn-Dark Style')
   plt.show()  # The 'seaborn-dark' style will only affect this plot

Output

Creating Custom Stylesheets

We can also create our custom stylesheets by defining a .mplstyle file or using a Python dictionary specifying the style parameters −

Example

In this example we are creating the custom stylesheets by using the dictionary.

import matplotlib.pyplot as plt
# Define a custom style using a dictionary
custom_style = {
   'lines.linewidth': 10,
   'lines.color': 'red',
   'axes.labelsize': 30,
   # Add more style configurations as needed
}
# Use the custom style
plt.style.use(custom_style)
x = [10,30,20,50]
y = [30,23,45,10]
plt.plot(x,y)
plt.title("Plot with custom style sheet")
plt.show()

Output

Stylesheets offer an efficient way to maintain consistency across multiple plots or to experiment with various visual styles easily. We can select stylesheets that best suit our preferences or the specific requirements of our data visualization.