What is Seaborn?

Seaborn is a Python visualization library built on top of Matplotlib.

It provides:

• Better default styles
• High-level charts for statistics
• Easy integration with Pandas DataFrames

Seaborn is especially useful in EDA because you can quickly create informative plots with fewer lines of code.

Install and import

import seaborn as sns
import matplotlib.pyplot as plt
 
print(sns.__version__)

import seaborn as sns
import matplotlib.pyplot as plt
 
print(sns.__version__)

Seaborn’s core idea

Most Seaborn functions work well with tidy (long) data:

• One row per observation
• One column per variable

That’s why Pandas reshaping (meltmelt, pivot_tablepivot_table) is useful.

A first Seaborn plot

import seaborn as sns
import matplotlib.pyplot as plt
 
x = [1, 2, 3, 4, 5]
y = [1, 4, 9, 16, 25]
 
sns.lineplot(x=x, y=y)
plt.title("Seaborn line plot")
plt.tight_layout()
plt.show()

import seaborn as sns
import matplotlib.pyplot as plt
 
x = [1, 2, 3, 4, 5]
y = [1, 4, 9, 16, 25]
 
sns.lineplot(x=x, y=y)
plt.title("Seaborn line plot")
plt.tight_layout()
plt.show()

Why analysts like Seaborn

• Built-in confidence intervals and aggregations in some plots
• Simple API for categorical comparisons
• Great for quickly exploring distributions and relationships