Combining Seaborn and Matplotlib - Step-by-Step Execution

Concept Flow - Combining Seaborn and Matplotlib

Import libraries

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Create Matplotlib figure and axes

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Use Seaborn to plot on Matplotlib axes

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Customize plot with Matplotlib commands

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Show combined plot

First, import libraries, then create a Matplotlib figure and axes. Next, plot with Seaborn on those axes. Finally, customize with Matplotlib and display the plot.

Execution Sample

Matplotlib

import matplotlib.pyplot as plt
import seaborn as sns

fig, ax = plt.subplots()
sns.histplot(data=[1,2,2,3,3,3], ax=ax)
ax.set_title('Combined Plot')
plt.show()

This code creates a histogram using Seaborn on a Matplotlib axis, then adds a title with Matplotlib and shows the plot.

Execution Table

Step	Action	Object Created/Modified	Result/Output
1	Import matplotlib.pyplot as plt	plt module	Ready to create figures and axes
2	Import seaborn as sns	sns module	Ready to use seaborn plotting functions
3	Create figure and axes with plt.subplots()	fig, ax	Empty plot area ready
4	Call sns.histplot with data and ax=ax	ax	Histogram drawn on ax
5	Set title with ax.set_title('Combined Plot')	ax	Title added to plot
6	Call plt.show()	fig	Plot window displayed with combined plot

💡 Plot displayed and script ends

Variable Tracker

Variable	Start	After Step 3	After Step 4	After Step 5	Final
fig	None	Figure object created	Figure unchanged	Figure unchanged	Figure shown
ax	None	Axes object created	Histogram drawn on ax	Title set on ax	Axes shown with plot and title

Key Moments - 2 Insights

Why do we pass ax=ax to sns.histplot?

Passing ax=ax tells Seaborn to draw the plot on the existing Matplotlib axes, so we can combine Seaborn and Matplotlib commands on the same plot (see execution_table step 4).

Can we add Matplotlib customizations after Seaborn plotting?

Yes, after Seaborn draws on the axes, we can use Matplotlib commands like ax.set_title to customize the plot (see execution_table step 5).

Visual Quiz - 3 Questions

Look at the execution table, what object is created at step 3?

A Matplotlib figure and axes

B Seaborn histogram plot

C Plot title

D Data array

💡 Hint

Check the 'Object Created/Modified' column at step 3 in the execution_table.

At which step is the histogram actually drawn on the axes?

A Step 2

B Step 4

C Step 3

D Step 5

💡 Hint

Look for when sns.histplot is called with ax=ax in the execution_table.

If we skip ax=ax in sns.histplot, what happens?

A Plot title is automatically added

B Plot appears on the same axes as Matplotlib commands

C Seaborn creates its own figure and axes separately

D Code will raise an error

💡 Hint

Think about how Seaborn behaves when no axes are provided, based on the concept flow.

Concept Snapshot

Combining Seaborn and Matplotlib:
- Import both libraries
- Create Matplotlib figure and axes
- Pass axes to Seaborn plotting function with ax=ax
- Use Matplotlib commands to customize plot
- Show plot with plt.show()

Full Transcript

This lesson shows how to combine Seaborn and Matplotlib plotting. First, we import matplotlib.pyplot as plt and seaborn as sns. Then, we create a figure and axes using plt.subplots(). Next, we call a Seaborn plotting function like sns.histplot and pass the Matplotlib axes with ax=ax so the plot draws on that axes. After that, we can customize the plot using Matplotlib commands such as ax.set_title to add a title. Finally, we display the combined plot with plt.show(). This approach lets us use Seaborn's easy plotting with Matplotlib's flexible customization on the same figure.