seaborn

1# Seaborn Statistical Visualization
2 
3## Overview
4 
5Seaborn 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.
6 
7## Design Philosophy
8 
9Seaborn follows these core principles:
10 
111. **Dataset-oriented**: Work directly with DataFrames and named variables rather than abstract coordinates
122. **Semantic mapping**: Automatically translate data values into visual properties (colors, sizes, styles)
133. **Statistical awareness**: Built-in aggregation, error estimation, and confidence intervals
144. **Aesthetic defaults**: Publication-ready themes and color palettes out of the box
155. **Matplotlib integration**: Full compatibility with matplotlib customization when needed
16 
17## Quick Start
18 
19```python
20import seaborn as sns
21import matplotlib.pyplot as plt
22import pandas as pd
23 
24# Load example dataset
25df = sns.load_dataset('tips')
26 
27# Create a simple visualization
28sns.scatterplot(data=df, x='total_bill', y='tip', hue='day')
29plt.show()
30```
31 
32## Core Plotting Interfaces
33 
34### Function Interface (Traditional)
35 
36The function interface provides specialized plotting functions organized by visualization type. Each category has **axes-level** functions (plot to single axes) and **figure-level** functions (manage entire figure with faceting).
37 
38**When to use:**
39- Quick exploratory analysis
40- Single-purpose visualizations
41…