seaborn-statistical-visualization
Seaborn — Statistical Visualization
Overview
Seaborn is a Python visualization library for creating publication-quality statistical graphics with minimal code. It works directly with pandas DataFrames, provides automatic statistical estimation (means, CIs, KDE), and offers attractive default themes. Built on matplotlib for full customization access.
When to Use
- Creating distribution plots (histograms, KDE, violin plots, box plots) for data exploration
- Visualizing relationships between variables with automatic trend fitting and confidence intervals
- Comparing distributions across categorical groups (treatment vs control, tissue types)
- Generating correlation heatmaps and clustered heatmaps
- Quick exploratory data analysis with
pairplotfor all pairwise relationships - Multi-panel figures with automatic faceting by categorical variables
- For interactive plots with hover/zoom, use plotly instead
- For low-level figure control or custom layouts, use matplotlib directly
Prerequisites
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