5 Best Ways to Change Fonts in Matplotlib Python

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πŸ’‘ Problem Formulation: When customizing plots, Matplotlib users often need to change the font to suit the aesthetics of a presentation or to adhere to specific guidelines. For instance, one may want to shift from the default font to a serif variety like ‘Times New Roman’ for a more formal look in a bar graph representing annual sales data.

Method 1: Use rcParams to Set Global Font Properties

Matplotlib’s rcParams is a dictionary to configure and customize all properties of Matplotlib. By altering the rcParams, users can set global font properties that affect all text elements in a plot. This method is particularly useful when consistency across multiple plots is required.

Here’s an example:

import matplotlib.pyplot as plt

plt.rcParams['font.family'] = 'sans-serif'
plt.rcParams['font.sans-serif'] = ['Arial']
plt.plot([1, 2, 3], [4, 5, 6])
plt.title('Arial Font Example')
plt.show()

The output will display a line plot with the title ‘Arial Font Example’ in Arial font.

This code snippet sets the font for all the text in the plot to Arialβ€”including the title, labels, and ticksβ€”by modifying rcParams directly, which applies globally to all Matplotlib plots within the session.

Method 2: Use Font Properties to Change Individual Text Elements

For more granular control, Matplotlib allows users to alter font properties of individual text elements via the fontdict parameter. This method gives flexibility to change the font of specific elements like titles, axis labels, or text annotations without affecting other elements.

Here’s an example:

import matplotlib.pyplot as plt

font = {'family': 'serif', 
        'color':  'darkred', 
        'weight': 'normal', 
        'size': 16,
       }

plt.plot([1, 2, 3], [4, 5, 6])
plt.title('Serif Font Example', fontdict=font)
plt.show()

The output is a line plot with the title ‘Serif Font Example’ displayed using a serif font with other specified properties.

This snippet demonstrates changing the title font by creating a font dictionary and passing it to the title’s fontdict parameter. This approach does not affect the font settings of other text elements in the plot.

Method 3: Use the Font Manager

For advanced font management, Matplotlib provides a FontProperties utility through matplotlib.font_manager. This utility is capable of loading fonts that are not installed as system fonts, hence allowing the use of custom fonts or direct specification of font files.

Here’s an example:

from matplotlib import font_manager
import matplotlib.pyplot as plt

font_path = '/path/to/font.ttf'
font_prop = font_manager.FontProperties(fname=font_path)

plt.plot([1, 2, 3], [4, 5, 6])
plt.title('Custom Font Example', fontproperties=font_prop)
plt.show()

This will produce a line plot with the title ‘Custom Font Example’ using the font specified by the file path.

The code above uses FontProperties to load a font directly from a file, allowing users to use a specific font that may not be installed on the system.

Method 4: Set Font Properties for All Text Elements with Text Properties

When you need to apply font settings to each individual text element but want to keep those settings consistent, you can set text properties for all text at once. This is a convenient shortcut that avoids repetitive code.

Here’s an example:

import matplotlib.pyplot as plt

text_options = {'family' : 'monospace',
                'weight' : 'bold',
                'size'   : 'large'}

plt.plot([1, 2, 3], [4, 5, 6])
plt.title('Monospace Bold Font', **text_options)
plt.xlabel('X Axis', **text_options)
plt.ylabel('Y Axis', **text_options)
plt.show()

The output will be a plot with ‘Monospace Bold Font’ as the title and axis labels in monospace, bold font.

By creating a dictionary of font options and unpacking it into the text properties of various elements, the same styling is easily replicated across the title, x-label, and y-label of the plot.

Bonus One-Liner Method 5: Use setp() Function

For a quick, one-line method to set font properties of multiple text elements, use the setp() function. This function provides a way to configure a list of Matplotlib objects on the fly.

Here’s an example:

import matplotlib.pyplot as plt

plt.plot([1, 2, 3], [4, 5, 6])
title_text = plt.title('Quick Setp Example')
plt.setp(title_text, fontname='Comic Sans MS', color='blue')
plt.show()

The output will show a line plot with the title ‘Quick Setp Example’ rendered in Comic Sans MS font in blue.

This demonstrates the setp() function’s convenience, which updates the title’s font and color in a single line after the title has been created.

Summary/Discussion

  • Method 1: rcParams. Global setting. Easy. Limited fine control.
  • Method 2: Font Properties with fontdict. Individual element control. Flexible. Requires multiple steps for each element.
  • Method 3: Font Manager. Advanced handling of fonts. Versatile. Requires knowledge about font file paths.
  • Method 4: Set Text Properties. Consistency in multiple elements. Efficient. Still requires individual element calls.
  • Bonus Method 5: Use setp() Function. Quick updates. Simple. Limited to already created objects.