How to Use Bold Font in Matplotlib (With Examples)

Matplotlib is a plotting library for Python that allows users to create visualizations with ease. In order to make text bold in Matplotlib, you must use the fontweight parameter and set it to ‘bold’. The fontweight parameter is available within the text() function, which allows you to add text to a plot. Examples of how to use this parameter are provided within this article.


You can use the weight argument to create a bold font in Matplotlib.

This argument is commonly used with titles and annotated text in Matplotlib:

Method 1: Use Bold Font in Title

plt.title('My Title', weight='bold')

Method 2: Use Bold Font in Annotated Text

plt.text(6, 10, 'some text', weight='bold')

The following examples show how to use each method in practice.

Example 1: Use Bold Font in Title

The following code shows how to create a scatterplot with a title in Matplotlib that uses regular font:

import matplotlib.pyplot as plt

#create data
x = [3, 6, 8, 12, 14]
y = [4, 9, 14, 12, 9]

#create scatterplot
plt.scatter(x, y)

#add title
plt.title('My Title', fontsize=22)

And the following code shows how to create a scatterplot with a title in Matplotlib and use the weight argument to enable bold font:

import matplotlib.pyplot as plt

#create data
x = [3, 6, 8, 12, 14]
y = [4, 9, 14, 12, 9]

#create scatterplot
plt.scatter(x, y)

#add title
plt.title('My Title', fontsize=22, weight='bold')

Matplotlib bold font in title

Example 2: Use Bold Font in Annotated Text

The following code shows how to use the weight argument to enable bold font in an annotated text in a Matplotlib scatterplot:

import matplotlib.pyplot as plt

#create data
x = [3, 6, 8, 12, 14]
y = [4, 9, 14, 12, 9]

#create scatterplot
plt.scatter(x, y)

#add regular text
plt.text(6, 10, 'Normal Font',  fontsize=16)

#add bold text
plt.text(10, 10, 'Bold Font', fontsize=16, weight='bold')

Matplotlib bold font in annotated text

Notice the difference between the normal font and the bold font.

The following tutorials explain how to perform other common tasks in Matplotlib:

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