How to Use Matplotlib with Seaborn for Data Visualization

You can use seaborn to create statistical plots easily and customize them with matplotlib functions. First, import both libraries, then create a plot with seaborn and adjust it using matplotlib commands like plt.title() or plt.xlabel().

Syntax

To use matplotlib with seaborn, first import both libraries. Use seaborn functions to create plots, then use matplotlib functions to customize them.

• import seaborn as sns: imports seaborn for plotting.
• import matplotlib.pyplot as plt: imports matplotlib's plotting interface.
• sns.plot_function(data): creates a seaborn plot.
• plt.function(): modifies the plot (title, labels, limits).
• plt.show(): displays the final plot.

python

import seaborn as sns
import matplotlib.pyplot as plt

sns.scatterplot(data=dataframe, x='x_column', y='y_column')
plt.title('My Plot Title')
plt.xlabel('X Axis Label')
plt.ylabel('Y Axis Label')
plt.show()

Example

This example shows how to create a scatter plot with seaborn and customize it with matplotlib by adding a title and axis labels.

python

import seaborn as sns
import matplotlib.pyplot as plt

# Load example dataset
iris = sns.load_dataset('iris')

# Create scatter plot with seaborn
sns.scatterplot(data=iris, x='sepal_length', y='sepal_width', hue='species')

# Customize plot with matplotlib
plt.title('Iris Sepal Dimensions')
plt.xlabel('Sepal Length (cm)')
plt.ylabel('Sepal Width (cm)')

# Show the plot
plt.show()

Output

A scatter plot showing iris sepal length vs sepal width with points colored by species, titled 'Iris Sepal Dimensions' with labeled axes.

Common Pitfalls

Common mistakes when using matplotlib with seaborn include:

• Not calling plt.show() to display the plot.
• Calling seaborn plotting functions after plt.show(), which resets the figure.
• Trying to customize plots before creating them with seaborn.
• Overlapping commands that reset the plot unintentionally.

Always create the seaborn plot first, then customize with matplotlib, and finally call plt.show().

python

import seaborn as sns
import matplotlib.pyplot as plt

# Wrong order example
plt.title('Wrong Order')  # This does nothing because no plot exists yet
sns.scatterplot(data=sns.load_dataset('iris'), x='sepal_length', y='sepal_width')
plt.show()

# Correct order example
sns.scatterplot(data=sns.load_dataset('iris'), x='sepal_length', y='sepal_width')
plt.title('Correct Order')
plt.show()

Output

First plot shows no title; second plot shows title 'Correct Order'.

Quick Reference

Tips for using matplotlib with seaborn:

• Import seaborn as sns and matplotlib.pyplot as plt.
• Create plots with seaborn functions like sns.scatterplot(), sns.barplot(), etc.
• Use matplotlib functions like plt.title(), plt.xlabel(), plt.ylabel(), and plt.legend() to customize.
• Call plt.show() once after all customizations to display the plot.

Key Takeaways

Use seaborn to create plots and matplotlib to customize them.

Always call plt.show() after all plotting and customization commands.

Create the seaborn plot before applying matplotlib customizations.

Import seaborn as sns and matplotlib.pyplot as plt for standard usage.

Matplotlib functions control titles, labels, legends, and figure display.