Seaborn Statistical Visualization
Overview
Seaborn is a Python visualization library for creating publication-quality statistical graphics. Use this skill for dataset-oriented plotting, multivariate analysis, automatic statistical estimation, and complex multi-panel figures with minimal code.
Environment and Installation
Current upstream documentation is for seaborn 0.13.2. Official docs support Python 3.8+ with mandatory NumPy, pandas, and matplotlib dependencies; scipy, statsmodels, and fastcluster are optional for some advanced statistics and clustering workflows.
# Reproducible install for examples in this skill
uv pip install "seaborn==0.13.2"
# Include optional statistical dependencies when needed
uv pip install "seaborn[stats]==0.13.2"
Recommended imports:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import seaborn.objects as so
sns.load_dataset() downloads public example data when it is not cached. For private, regulated, or offline work, load local files explicitly with pandas and pass the resulting DataFrame to seaborn.
Design Philosophy
Seaborn follows these core principles:…
