Styling and Themes

Matplotlib includes several built-in styles that allow you to quickly change the appearance of your plots.
You can also fine-tune individual elements to match your preferred look, branding, or presentation theme.

Use plt.style.use("style_name") to apply a theme globally.

Copy
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"

To see what’s available, run:

Copy
print(plt.style.available)

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

Copy
plt.plot(x, y, color="purple", linewidth=3)

This is useful when you want to maintain a consistent style while adjusting key visuals.

You’ve now explored styling, subplots, labels, and saving — next up is the final quiz to review everything you’ve learned about Matplotlib.