Seaborn figure-level vs axes-level in Matplotlib - Visual Side-by-Side Comparison

Concept Flow - Seaborn figure-level vs axes-level

Start: Choose plot type

↓

Is plot figure-level?

Yes→Create new Figure + Axes internally

↓

Return Figure object

↓

Is plot axes-level?

Yes→Use existing Axes object

↓

Return Axes object

↓

Error: Unknown plot type

Decide if the plot creates a new figure (figure-level) or uses an existing axes (axes-level). Figure-level plots manage the whole figure, axes-level plots draw on given axes.

Execution Sample

Matplotlib

import seaborn as sns
import matplotlib.pyplot as plt

# Figure-level plot
sns.catplot(data=tips, x='day', y='total_bill')

# Axes-level plot
fig, ax = plt.subplots()
sns.boxplot(data=tips, x='day', y='total_bill', ax=ax)

Shows how figure-level plot creates its own figure, axes-level plot uses existing axes.

Execution Table

Step	Action	Plot Type	Figure Created	Axes Used	Return Object
1	Call sns.catplot()	Figure-level	Yes (new Figure)	New Axes created internally	FacetGrid (figure-level object)
2	Plot draws internally	Figure-level	Yes	Internal Axes	FacetGrid object manages figure and axes
3	Call plt.subplots()	Setup	Yes (new Figure)	New Axes returned	Figure and Axes objects
4	Call sns.boxplot() with ax=ax	Axes-level	No (uses existing Figure)	Existing Axes passed in	Axes object
5	Plot draws on passed Axes	Axes-level	No	Existing Axes	Axes object
6	End of plotting	-	-	-	-

💡 Execution stops after plots are drawn and objects returned.

Variable Tracker

Variable	Start	After sns.catplot()	After plt.subplots()	After sns.boxplot()
fig	None	Created internally by catplot	Created by plt.subplots()	Same as plt.subplots() figure
ax	None	Created internally by catplot	Created by plt.subplots()	Passed to sns.boxplot()
plot_obj	None	FacetGrid object returned	None	Axes object returned

Key Moments - 2 Insights

Why does sns.catplot() create a new figure while sns.boxplot() can use an existing axes?

sns.catplot() is a figure-level function that manages the whole figure and creates it internally (see execution_table step 1). sns.boxplot() is axes-level and draws on an existing axes passed via the ax parameter (see step 4).

What object type is returned by figure-level vs axes-level plots?

Figure-level plots like sns.catplot() return a FacetGrid object that manages figure and axes (step 2). Axes-level plots like sns.boxplot() return the Axes object they draw on (step 5).

Visual Quiz - 3 Questions

Look at the execution table, what is created internally by sns.catplot() at step 1?

A Only a new Figure

B A new Figure and Axes

C Only a new Axes

D No new objects

💡 Hint

Check the 'Figure Created' and 'Axes Used' columns at step 1 in the execution_table.

At which step does sns.boxplot() use an existing Axes object?

A Step 4

B Step 2

C Step 1

D Step 3

💡 Hint

Look at the 'Axes Used' column for sns.boxplot() in the execution_table.

If you do not pass ax to sns.boxplot(), what will happen?

A It will create a new figure and axes internally

B It will raise an error

C It will plot on the last active axes

D It will return a FacetGrid object

💡 Hint

Axes-level plots use existing axes or the current active axes if none is passed.

Concept Snapshot

Seaborn plots are either figure-level or axes-level.
Figure-level plots (e.g., catplot) create and manage their own figure and axes.
Axes-level plots (e.g., boxplot) draw on existing matplotlib axes passed via ax.
Figure-level returns a FacetGrid object; axes-level returns the Axes object.
Use figure-level for complex multi-plot layouts; axes-level for simple single plots.

Full Transcript

This visual execution trace shows the difference between Seaborn figure-level and axes-level plots. Figure-level plots like catplot create a new figure and axes internally and return a FacetGrid object that manages them. Axes-level plots like boxplot require an existing matplotlib axes object passed via the ax parameter and return that axes after drawing. The execution table traces calls and object creation step-by-step. Variable tracking shows how figure and axes variables change. Key moments clarify why figure-level plots create new figures and what objects are returned. The quiz tests understanding of which objects are created and used at each step. The concept snapshot summarizes the main differences and usage tips.