In this tutorial, we will learn how to change the background theme or style of a plot made with matplotlib. Matplotlib offers a number of ready to use styles to use for matplotlib plots. We will first learn how to find the available style options and then learn to set a matplotlib style of interest to a plot.
Let us get started with loading the modules needed for making a plot with matplotlib. Matplotlib’s styles can be used after importing style from matplotlib.
1 2 3 | import matplotlib.pyplot as pltimport numpy as npfrom matplotlib import style |
How to list all available matplotlib styles
Matplotlib has over 20 different styling options for making matplotlib plots. By using plt.style.available statement we can print all available styles.
1 2 3 | print(plt.style.available)['Solarize_Light2', '_classic_test_patch', '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'] |
By default, Matplotlib uses “default” style. Here we will learn how to change the default matplotlib style of a scatter plot made with matplotlib. We will generate data for making a scatter plot using Numpy’s random module.
1 2 3 4 | from numpy.random import default_rngrng = default_rng()x = rng.normal(12.0, 3, 100)y = x + rng.normal(2,1,100) |
To make scatter plot in Matplotlib, we use scatter() function.
1 2 3 4 5 6 7 8 | plt.scatter(x,y)plt.xlabel("x", size=14)plt.ylabel("y", size=14)plt.title("Default Matplotlib Style Scatter plot")plt.savefig("Default_matplotlib_style_scatterplot.png", format='png',dpi=150) |
Our scatter plot made with default matplotlib style looks like.
Changing Matplotlib Style using plt.style.use: Example 1
We can change matplotlib’s style using plt.style.use() function. Here we change the theme to ggplot2 style.
1 2 3 4 5 6 7 8 9 10 | plt.style.use('ggplot')plt.scatter(x,y)plt.xlabel("x", size=14)plt.ylabel("y", size=14)plt.title("ggplot style in Matplotlib")plt.tight_layout()plt.savefig("Change_matplotlib_style_to_ggplot_scatterplot.png", format='png',dpi=150) |
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Changing Matplotlib Style using plt.style.use: Example 2
Here is another example, where we change Matplotlib plotting style to fivethirtyeight style.
1 2 3 4 5 6 7 8 9 | plt.style.use('fivethirtyeight')plt.scatter(x,y)plt.xlabel("x", size=14)plt.ylabel("y", size=14)plt.title("fivthirtyeight style in Matplotlib")plt.savefig("Change_matplotlib_style_scatterplot_to_538.png", format='png',dpi=150) |
