Seaborn - Statistical Data Visualization

Seaborn helps you explore and understand your data through beautiful, informative statistical plots. It automates complex tasks like calculating confidence intervals, aggregating data, and creating faceted grids.

When to Use

• Visualizing complex relationships between multiple variables (relplot)
• Examining univariate and bivariate distributions (displot, kdeplot)
• Comparing categories with statistical summaries (catplot, boxplot, violinplot)
• Visualizing linear regression models and their uncertainty (regplot, lmplot)
• Creating heatmaps and cluster maps for large matrices
• Building multi-plot grids based on data subsets (FacetGrid)
• Setting high-level aesthetic themes for Matplotlib figures

Reference Documentation

Official docs: https://seaborn.pydata.org/
Example gallery: https://seaborn.pydata.org/examples/index.html
Search patterns: sns.load_dataset, sns.relplot, sns.catplot, sns.set_theme, sns.heatmap