Using Seaborn charts in Matplotlib multi-chart layouts
Seaborn basics
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Published Oct 7 2025
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Guide Sections
Guide Comments
ChartsGraphsMatplotlibNumPyPandasPythonSeabornVisualisation
Seaborn has two types of charts. Some are Axes level charts and some are Figure level charts.
Type | Description | Examples |
Axes-level | Draw on a specific Matplotlib |
|
Figure-level | Create their own entire Figure (often with multiple subplots/facets) — not easily embedded in an existing layout |
|
Axes-level plots return a Matplotlib Axes object, meaning you can:
- Combine them into multi-plot layouts
- Add annotations, titles, or shared axes
- Overlay or compose them with other Matplotlib plots
Example:
import seaborn as sns
import matplotlib.pyplot as plt
tips = sns.load_dataset("tips")
fig, axs = plt.subplots(2, 2, figsize=(10, 8))
sns.scatterplot(data=tips, x="total_bill", y="tip", ax=axs[0, 0])
sns.boxplot(data=tips, x="day", y="total_bill", ax=axs[0, 1])
sns.violinplot(data=tips, x="smoker", y="tip", ax=axs[1, 0])
sns.heatmap(tips.corr(numeric_only=True), annot=True, ax=axs[1, 1])
plt.tight_layout()
plt.show()
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Each subplot is a Seaborn plot embedded into a Matplotlib dashboard. You can freely mix Seaborn and Matplotlib plots.
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