Using Seaborn charts in Matplotlib multi-chart layouts

Seaborn basics

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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 `Axes` — you can place them in subplots or dashboards	`sns.scatterplot()`, `sns.lineplot()`, `sns.barplot()`, `sns.boxplot()`, `sns.violinplot()`, `sns.heatmap()`, etc.
Figure-level	Create their own entire Figure (often with multiple subplots/facets) — not easily embedded in an existing layout	`sns.relplot()`, `sns.catplot()`, `sns.displot()`, `sns.lmplot()`, `sns.pairplot()`, `sns.jointplot()`, `sns.clustermap()`

Axes-level plots return a Matplotlib Axes object, meaning you can:

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()

Each subplot is a Seaborn plot embedded into a Matplotlib dashboard. You can freely mix Seaborn and Matplotlib plots.