Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics. Add the seaborn-0.12.x tag for questions about seaborn.objects.
Seaborn is a library for making statistical graphics in Python. It is built on top of matplotlib and is tightly integrated with the PyData stack, including support for numpy and pandas data structures, and statistical routines from scipy and statsmodels.
Here is some of the functionality that seaborn offers:
- A dataset-oriented API for examining relationships between multiple variables
- Convenient views onto the overall structure of complex datasets
- Specialized support for using categorical variables to show observations or aggregate statistics
- Options for visualizing univariate or bivariate distributions and for comparing them between subsets of data
- Automatic estimation and plotting of linear regression models for different kinds of dependent variables
- High-level abstractions for structuring multi-plot grids that let you easily build complex visualizations
- Concise control over matplotlib figure styling with several built-in themes
- Tools for choosing color palettes that faithfully reveal patterns in your data
This tag should be used for seaborn related questions. Since seaborn heavily builds on top of matplotlib, and since many seaborn related problems can be come by using standard matplotlib techniques, it is advisable to additionally add the matplotlib tag to any seaborn question as well.
It is traditionally imported with:
import seaborn as sns
Example gallery:
