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Practice

Styling and Themes

Matplotlib comes with several built-in styles that let you quickly change the overall appearance of your plots.

You can also customize individual elements to match your preferred visual style, brand identity, or presentation theme.


Using Built-in Styles​

Use plt.style.use("style_name") to apply a visual theme across all plots in your session.

Applying a Built-in Style
import matplotlib.pyplot as plt

plt.style.use("ggplot")  # Apply the ggplot theme

x = [1, 2, 3, 4]
y = [10, 20, 15, 25]

plt.plot(x, y)
plt.title("Styled Plot with ggplot")
plt.show()

Popular style names include:

  • "ggplot"
  • "seaborn"
  • "bmh"
  • "dark_background"
  • "fivethirtyeight"

Listing Available Styles​

To see what's available, run:

List Available Styles
print(plt.style.available)

Customizing Individual Elements​

You can override specific elements, even when using a theme:

Customize Colors and Line Width
plt.plot(x, y, color="purple", linewidth=3)

This approach helps maintain a consistent overall look while highlighting specific data or adjusting key visual elements.

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