Combining Seaborn and Matplotlib - Step-by-Step Execution

Concept Flow - Combining Seaborn and Matplotlib

Import libraries

↓

Create Matplotlib figure and axes

↓

Use Seaborn to plot on Matplotlib axes

↓

Customize plot with Matplotlib commands

↓

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.

Practice

1. What is the main reason to combine Seaborn and Matplotlib in a plot?

easy

A. Seaborn and Matplotlib cannot be used together

B. Because Seaborn cannot create any plots on its own

C. Matplotlib is only for 3D plots, so Seaborn is needed for 2D

D. To use Seaborn's easy plotting and Matplotlib's customization features

Solution

1. Step 1: Understand Seaborn's strength

   Seaborn creates beautiful and easy statistical plots quickly.

2. Step 2: Understand Matplotlib's strength

   Matplotlib allows detailed customization like adding titles, labels, and lines.

3. Final Answer:

   To use Seaborn's easy plotting and Matplotlib's customization features -> Option D

4. Quick Check:

   Seaborn + Matplotlib = Easy + Customization [OK]

Hint: Seaborn plots, Matplotlib customizes [OK]

Common Mistakes:

• Thinking Seaborn can't plot alone
• Believing Matplotlib is only for 3D
• Assuming they can't be combined

2. Which of the following code snippets correctly adds a title to a Seaborn plot using Matplotlib?

easy

A. import seaborn as sns
import matplotlib.pyplot as plt
sns.histplot(data)
plt.title('Histogram')

B. import seaborn as sns
sns.histplot(data).title('Histogram')

C. import matplotlib.pyplot as plt
plt.histplot(data)
plt.set_title('Histogram')

D. import seaborn as sns
sns.histplot(data)
plt.setTitle('Histogram')

Solution

1. Step 1: Identify correct Seaborn and Matplotlib usage

   Seaborn creates the plot, Matplotlib's plt.title() adds the title.

2. Step 2: Check syntax correctness

   import seaborn as sns
   import matplotlib.pyplot as plt
   sns.histplot(data)
   plt.title('Histogram')

   uses sns.histplot(data) then plt.title('Histogram'), which is correct.

3. Final Answer:

   import seaborn as sns import matplotlib.pyplot as plt sns.histplot(data) plt.title('Histogram') -> Option A

4. Quick Check:

   Seaborn plot + plt.title() = Correct [OK]

Hint: Use plt.title() after Seaborn plot [OK]

Common Mistakes:

• Calling title() directly on Seaborn plot object
• Using plt.set_title() instead of plt.title()
• Misspelling method names like setTitle

3. What will be the output of this code?

import seaborn as sns
import matplotlib.pyplot as plt

sns.scatterplot(x=[1,2,3], y=[4,5,6])
plt.xlabel('X axis')
plt.ylabel('Y axis')
plt.title('Scatter Plot')
plt.show()

medium

A. A scatter plot with labeled X axis, Y axis, and title

B. A scatter plot without any labels or title

C. An error because plt.xlabel() cannot be used with Seaborn

D. A line plot instead of scatter plot

Solution

1. Step 1: Understand the plot creation

   sns.scatterplot creates a scatter plot with given x and y points.

2. Step 2: Check Matplotlib label and title additions

   plt.xlabel, plt.ylabel, and plt.title add labels and title correctly.

3. Final Answer:

   A scatter plot with labeled X axis, Y axis, and title -> Option A

4. Quick Check:

   Seaborn plot + plt labels = Labeled plot [OK]

Hint: Matplotlib labels work after Seaborn plot [OK]

Common Mistakes:

• Expecting errors using plt.xlabel with Seaborn
• Confusing scatterplot with line plot
• Forgetting plt.show() to display plot

4. Identify the error in this code that tries to combine Seaborn and Matplotlib:

import seaborn as sns
import matplotlib.pyplot as plt

sns.boxplot(data=[1,2,3,4,5])
plt.xlabel('Values')
plt.title('Boxplot')
plt.show()

medium

A. plt.xlabel() causes error because boxplot has no x-axis

B. No error; code runs and shows labeled boxplot

C. Missing plt.figure() before plotting causes error

D. sns.boxplot requires x and y parameters, so data alone causes error

Solution

1. Step 1: Check sns.boxplot usage

   Passing data as a list is valid for sns.boxplot; it plots distribution.

2. Step 2: Check Matplotlib label usage

   plt.xlabel('Values') adds label to x-axis; plt.title adds title; no error occurs.

3. Final Answer:

   No error; code runs and shows labeled boxplot -> Option B

4. Quick Check:

   Seaborn boxplot + plt labels = Works fine [OK]

Hint: Boxplot accepts data list; plt.xlabel works [OK]

Common Mistakes:

• Thinking plt.xlabel errors without x parameter
• Assuming plt.figure() is mandatory before plot
• Believing sns.boxplot needs x and y always

5. You want to create a Seaborn barplot and add a horizontal line at y=5 using Matplotlib. Which code correctly does this?

hard

A. import seaborn as sns
import matplotlib.pyplot as plt
sns.barplot(x=['A','B'], y=[3,7])
plt.hline(y=5, color='red')
plt.show()

B. import seaborn as sns
import matplotlib.pyplot as plt
sns.barplot(x=['A','B'], y=[3,7])
plt.lineh(y=5, color='red')
plt.show()

C. import seaborn as sns
import matplotlib.pyplot as plt
sns.barplot(x=['A','B'], y=[3,7])
plt.axhline(y=5, color='red')
plt.show()

D. import seaborn as sns
import matplotlib.pyplot as plt
sns.barplot(x=['A','B'], y=[3,7])
plt.axline(y=5, color='red')
plt.show()

Solution

1. Step 1: Create barplot with Seaborn

   sns.barplot with x and y lists creates the bar chart correctly.

2. Step 2: Add horizontal line with Matplotlib

   plt.axhline(y=5, color='red') adds a horizontal line at y=5; other options are invalid methods.

3. Final Answer:

   import seaborn as sns import matplotlib.pyplot as plt sns.barplot(x=['A','B'], y=[3,7]) plt.axhline(y=5, color='red') plt.show() -> Option C

4. Quick Check:

   Use plt.axhline() for horizontal line [OK]

Hint: Use plt.axhline() for horizontal lines [OK]

Common Mistakes:

• Using plt.lineh or plt.hline which don't exist
• Confusing plt.axline with plt.axhline
• Forgetting plt.show() to display plot