Seaborn provides statistical data visualization tools and plotting functions for Python.

seaborn.pydata.org
Seaborn homepage screenshot

About Seaborn

Seaborn is a Python library for statistical data visualization. It is built on matplotlib and provides a high-level interface for drawing statistical graphics. The homepage lists plot types for relational, distribution, categorical, and regression data, along with multi-plot grids, figure theming, and color palettes.

The homepage links to an installation page, an example gallery, tutorials, an API reference, and a GitHub repository for source code and bug reports. The source does not state licensing terms or pricing. The homepage lists version 0.13.2 of the documentation.

Key features

  • New Objects API for building statistical plots
  • Relational plots for showing relationships between variables
  • Distribution plots for examining how data values are spread
  • Categorical plots for comparing values across category groups
  • Regression plots for fitting and displaying trends in data
  • Multi-plot grids for arranging several related figures together
Best for: Python users who need statistical charts and already work with matplotlib.
Good for
  • Built on matplotlib, the widely used Python plotting library
  • Offers a high-level interface for statistical graphics
  • Includes an example gallery, tutorials, and an API reference
Watch out for
  • The source describes it as a Python library, so it is limited to Python use

Seaborn at a glance

Type
Online tool
Pricing
Not confirmed. Check the site
Platforms
Web
Open source
Not stated
Language
English
Last checked
Oct 6, 2026 · Online when checked
Listed
Oct 5, 2026

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Seaborn FAQ

Where can I find installation instructions?
The homepage links to an installation page that explains how to download the package and get started.
Where should I ask general support questions?
The homepage says general support questions are best directed to Stack Overflow, which has a dedicated channel for seaborn.
Where can I see the code or report a bug?
The homepage directs users to the GitHub repository for viewing the code and reporting bugs.
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