5 Effective Ways to Use Multiple Font Sizes in One Label with Python Matplotlib

by

💡 Problem Formulation: In data visualization, effectively communicating information is key. Users of Python’s Matplotlib library often need to adjust the size of specific words or phrases within a label to highlight or differentiate parts of their graph annotations. For instance, one might want the label “Big Idea” where “Big” is in a larger font than “Idea”. This article demonstrates five methods to achieve varied font sizes within a single label in Matplotlib.

Method 1: Using the mathtext Module

Matplotlib supports LaTeX-style text rendering through its mathtext module. This allows for a wide range of text formatting options including changing font sizes within a label. Using \mathrm{{}} to ensure text styling and \fontsize{{}} to specify sizes directly, diverse font sizes can be seamlessly integrated within a label.

♥️ Info: Are you AI curious but you still have to create real impactful projects? Join our official AI builder club on Skool (only $5): SHIP! - One Project Per Month

Here’s an example:

import matplotlib.pyplot as plt

plt.figure()
plt.plot([1, 2, 3], [4, 5, 6])
plt.title(r'$\mathrm{{\fontsize{20}{0}\selectfont Big}}\ \mathrm{{\fontsize{10}{0}\selectfont Idea}}$')
plt.show()

The output shows a plot with the title ‘Big Idea’ where ‘Big’ appears in a larger font size compared to ‘Idea’.

The code snippet uses Matplotlib’s mathtext capabilities to render text similar to LaTeX. By invoking \fontsize{{20}}{0}, ‘Big’ is set to font size 20, while ‘Idea’ follows in a font size 10, encapsulated within the \mathrm to maintain the standard text font.

Method 2: Using Annotation with text()

Matplotlib’s text() function can be leveraged to place multiple texts with different font sizes on the plot. This can be used creatively to piece together different text elements with varying sizes to appear as though they are a single label.

Here’s an example:

import matplotlib.pyplot as plt

plt.figure()
plt.plot([1, 2, 3], [4, 5, 6])

plt.text(0.5, 4.5, 'Big', fontsize=20)
plt.text(0.62, 4.5, 'Idea', fontsize=10)

plt.show()

The visualization contains the words ‘Big’ and ‘Idea’ next to each other, differentiated by font size.

By calling the text() function with explicit fontsize parameters for each segment of the label, and carefully positioning them with x and y coordinates, we get a composite label effect.

Method 3: Using The FontProperties Class

The FontProperties object from Matplotlib’s font_manager module can be used to fine-tune font properties. We can create different FontProperties instances for separate parts of a label and use them with the annotate function.

Here’s an example:

from matplotlib import font_manager
import matplotlib.pyplot as plt

big_font = font_manager.FontProperties(size='large')
small_font = font_manager.FontProperties(size='small')

plt.figure()
plt.plot([1, 2, 3], [4, 5, 6])
plt.annotate('Big', xy=(0.5, 0.5), fontproperties=big_font)
plt.annotate('Idea', xy=(0.6, 0.5), fontproperties=small_font)
plt.show()

The resulting plot displays ‘Big’ and ‘Idea’ in different font sizes as intended.

This code uses the annotate() function, providing two different FontProperties objects to customize font sizes for different parts of the label. Positional adjustments are made so that the two parts line up correctly.

Method 4: Employing Text Objects

Creating Text objects directly using Matplotlib’s text module and combining them on the canvas allows for detailed and precise control over font styling for each part of a label.

Here’s an example:

import matplotlib.pyplot as plt

fig, ax = plt.subplots()
ax.plot([1, 2, 3], [4, 5, 6])
t1 = ax.text(0.5, 1.0, "Big", transform=ax.transAxes, fontsize=20)
t2 = ax.text(0.58, 1.0, "Idea", transform=ax.transAxes, fontsize=10)
plt.show()

The graph showcases two pieces of text, ‘Big’ and ‘Idea,’ merged into one label with varying font sizes.

This approach takes advantage of the transAxes coordinate system for positioning, which scales the text’s location in accordance with the axes, ensuring a responsive placement relative to the size of the axes.

Bonus One-Liner Method 5: Using fstrings and Annotations

Python’s f-strings can compose a one-liner annotation with multiple font sizes by embedding LaTeX-like syntax directly in the formatted string. This is a quick and clever way to achieve varied font sizes in Matplotlib labels.

Here’s an example:

import matplotlib.pyplot as plt

plt.figure()
plt.plot([1, 2, 3], [4, 5, 6])
plt.title(f'{"Big":<20s}{10 * " "}{10 * " "}Idea', fontsize='large')
plt.show()

This code produces a plot with ‘Big’ noticeably larger, and ‘Idea’ following in a standard font size.

This snippet demonstrates a creative use of string formatting to space out the label components. While simple, this method lacks the fine-tuned control over font sizes and styles provided by LaTeX.

Summary/Discussion

  • Method 1: mathtext. Provides rich text formatting options similar to LaTeX. Requires familiarity with LaTeX-like syntax.
  • Method 2: Annotation using text(). Offers granular placement control. May require manual tweaking for alignment.
  • Method 3: Use FontProperties Class. Facilitates custom font properties for versatile text rendering. Involves creating multiple objects for different text styles.
  • Method 4: Employment of Text Objects. Maximizes control over the text. Has a relatively more verbose setup.
  • Bonus One-Liner Method 5: Using fstrings and Annotations. Quick and easy. Lacks precise control over font aesthetics.