Customizing Seaborn plots with Matplotlib - Step-by-Step Execution

Concept Flow - Customizing Seaborn plots with Matplotlib

Create Seaborn plot

↓

Access Matplotlib figure/axes

↓

Apply Matplotlib customizations

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Render updated plot

Start by making a Seaborn plot, then use Matplotlib commands on its figure or axes to customize, and finally show the updated plot.

Execution Sample

Matplotlib

import seaborn as sns
import matplotlib.pyplot as plt

ax = sns.scatterplot(x=[1,2,3], y=[4,5,6])
ax.set_title('Custom Title')
plt.show()

This code creates a scatter plot with Seaborn and changes the plot title using Matplotlib.

Execution Table

Step	Action	Object Affected	Result
1	Call sns.scatterplot with x and y data	Axes object (ax)	Scatter plot created on ax
2	Call ax.set_title('Custom Title')	Axes object (ax)	Title of plot set to 'Custom Title'
3	Call plt.show()	Figure	Plot window opens showing scatter plot with custom title
4	End of script	-	Plot displayed with customizations applied

💡 Plot is shown and script ends

Variable Tracker

Variable	Start	After Step 1	After Step 2	Final
ax	None	Axes with scatter plot	Axes with scatter plot and title set	Axes with scatter plot and title set

Key Moments - 2 Insights

Why do we use ax.set_title instead of sns.scatterplot's parameters to set the title?

Seaborn creates the plot and returns the Matplotlib Axes object. Customizations like title changes are done on this Axes using Matplotlib methods, as shown in step 2 of the execution_table.

Can we customize other parts of the plot after creating it with Seaborn?

Yes, once you have the Axes object (ax), you can use any Matplotlib method to customize labels, ticks, legends, colors, etc., as the plot is a Matplotlib figure under the hood.

Visual Quiz - 3 Questions

Look at the execution_table, what does the variable 'ax' contain after Step 1?

A A Matplotlib figure object

B A Matplotlib Axes object with the scatter plot

C A Seaborn plot object

D An empty variable

💡 Hint

Check the 'Object Affected' and 'Result' columns in Step 1 of execution_table

At which step is the plot title changed to 'Custom Title'?

A Step 2

B Step 3

C Step 1

D Step 4

💡 Hint

Look at the 'Action' column in execution_table for when ax.set_title is called

If we skip calling plt.show(), what happens according to the execution_table?

A The plot title is not set

B The plot window still opens

C The plot is created but not displayed

D The script crashes

💡 Hint

Step 3 shows plt.show() opens the plot window; skipping it means no display

Concept Snapshot

Create a Seaborn plot and save its Axes object.
Use Matplotlib methods on this Axes to customize titles, labels, and more.
Call plt.show() to display the final customized plot.
Seaborn plots are Matplotlib figures underneath, so Matplotlib commands work.
This lets you combine easy plotting with flexible customization.

Full Transcript

This lesson shows how to customize Seaborn plots using Matplotlib. First, you create a plot with Seaborn, which returns a Matplotlib Axes object. Then, you use Matplotlib commands on this Axes to change the title or other parts of the plot. Finally, you call plt.show() to display the plot with your customizations. This works because Seaborn builds on Matplotlib, so you can mix both easily.