Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics.

An introduction to seaborn # Seaborn is a library for making statistical graphics in Python. It builds on top of matplotlib and integrates closely with pandas data structures. Seaborn helps you explore and …

The seaborn codebase is pure Python, and the library should generally install without issue. Occasionally, difficulties will arise because the dependencies include compiled code and link to …

User guide and tutorial # An introduction to seaborn A high-level API for statistical graphics Multivariate views on complex datasets Opinionated defaults and flexible customization

API reference # Objects interface # Plot object # Mark objects # Dot marks

seaborn.lineplot(data=None, *, x=None, y=None, hue=None, size=None, style=None, units=None, weights=None, palette=None, hue_order=None, hue_norm=None, sizes=None, size_order=None, …

Most of your interactions with seaborn will happen through a set of plotting functions. Later chapters in the tutorial will explore the specific features offered by each function.

Matplotlib offers good support for making figures with multiple axes; seaborn builds on top of this to directly link the structure of the plot to the structure of your dataset.

seaborn.clustermap # seaborn.clustermap(data, *, pivot_kws=None, method='average', metric='euclidean', z_score=None, standard_scale=None, figsize=(10, 10), cbar_kws=None, …

When None or False, seaborn defers to the existing Axes scale. legendbool If False, suppress the legend for semantic variables. palettestring, list, dict, or matplotlib.colors.Colormap Method for …