How to change legend fontsize with matplotlib.pyplot

Manoeuvring legend customization

Matplotlib houses an array of customization options for expert navigation through your plot legends.

Set rowing speed for single plot

The prop keyword enables you to use font properties for individual legend size control, like rowing a single boat:

from matplotlib.font_manager import FontProperties

# ... your plotting code ...

plt.legend(prop=FontProperties(size=6))  # Small but mighty!
plt.show()
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Uniform style with the matplotlibrc file

To create uniformity in your plot styling habits, define font properties in the matplotlibrc file:

# An example of setting in matplotlibrc file
legend.fontsize: 10  # fontsize: Patrick, I look 10!
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Loading this configuration ensures all Created Plots of the Caribbean have the same legend font size.

The duel of text and title font sizes

To highlight the difference between the size of the legend text and its title, you can use dual parameters:

# ... your plotting code ...

plt.legend(fontsize='medium', title_fontsize='large', title="Legend Title")  # Like coffee sizes at Starbucks!
plt.show()
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Quill sizes for speedy plotting

Like quills for speedy writing, matplotlib accepts named sizes - 'small', 'medium', 'large' for quicker prototyping:

# ... your plotting code ...

plt.legend(fontsize='small')  # Fun size!
plt.show()
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Mastering legend configuration

Immerse yourself in these additional insights into legend navigation.

The Globe-trotter vs The Stay-at-home

It's crucial to understand the difference between setting font sizes globally vs locally:

• Global: Influences all the plot legends of the world! Or at least in the session or matplotlibrc file.
• Local: The hermit approach — only affects the specific legend object at hand.

Plotting the ship course

For complex plots (think Titanic!), you might fiddle with multiple conditions:

• Different legends warrant different font sizes.
• Visibility varies based on data density in the plot.
• You might need to adjust the spacing or symbols (handles) in the legend.

You can steer the ship using rcParams:

import matplotlib.pyplot as plt

plt.rc('legend', fontsize='small')  # Diminutive yet discernible!
plt.rc('legend', handlelength=2)  # Compact handles, like economy class legroom!
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From plot pitfalls to masterpieces

Some typical mistakes and ways to overcome them:

• Matplotlib version compatibility: Ensure your codes are similar to your library version.
• The readability vs aesthetics debate: Finding an optimal balance for plot efficiency.
• Legend overcrowding: Like a crowded party, consider another information source, like annotations or a guide.