Seaborn Tutorial for Data Visualization

Seaborn is a powerful Python library for creating statistical visualizations. Built on top of Matplotlib, it simplifies plotting with a high-level interface.

Getting Started

  • Install Seaborn: 
    pip install seaborn
    📌 Seaborn官方文档 for detailed installation guides and API references.

Basic Example: Scatter Plot

import seaborn as sns
sns.scatterplot(x='x', y='y', data=sns.load_dataset("tips"))
Scatter Plot Example

Advanced Features

  • Regression Plots: Use sns.regplot() for linear regression analysis.
  • Heatmaps: Visualize correlations with sns.heatmap().
  • Categorical Plots: Compare groups using sns.barplot() or sns.boxplot().
Regression Analysis

Tips for Effective Visualization

  • Always use descriptive labels and titles.
  • Customize colors with sns.set_palette().
  • Explore Seaborn Gallery for more examples and styling options.

📊 Seaborn Tutorial: Categorical Data to dive deeper into bar plots and box plots.