Seaborn for Statistical Plots

Seaborn is a Python data visualisation library built on top of Matplotlib. It provides a high-level interface for drawing attractive, informative statistical graphics with less code. Seaborn integrates closely with Pandas DataFrames and includes built-in themes, colour palettes, and functions for common statistical visualisations.

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Installation and Setup

pip install seaborn

import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np

# Set the default theme
sns.set_theme(style="whitegrid")

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Seaborn vs Matplotlib

Feature	Matplotlib	Seaborn
Level of abstraction	Low-level — you control every element	High-level — sensible defaults
Code verbosity	More code for styled plots	Less code for attractive plots
Statistical features	Manual	Built-in (confidence intervals, regression lines)
DataFrame integration	Requires manual column access	Native support for column names
Customisation	Unlimited	Customise via Matplotlib underneath

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Built-in Datasets

Seaborn comes with several built-in datasets for practice:

# List available datasets
print(sns.get_dataset_names())

# Load a dataset
tips = sns.load_dataset("tips")
print(tips.head())