Visualization Demonstrations with Seaborn

Introduction

This project presents a series of Seaborn-based visualization demonstrations using the Palmer Penguins dataset. The goal is to show how Seaborn can be used to create clear, elegant, and insight‑driven visualizations for data analysis.

The accompanying Jupyter notebooks walk through essential visualization topics such as distributions, categorical comparisons, pairwise relationships, and advanced plotting techniques.

Run Online with Binder

You can run the entire project directly in your browser with no installation required:

https://mybinder.org/v2/gh/sagivba/penguins-visualization-project/HEAD

After Binder loads (may take ~1 minute):

1. The JupyterLab interface will open.
2. Navigate to the notebooks/ directory.
3. Open and run the notebooks in order:
   • 01_data_loading.ipynb
   • 02_data_exploration.ipynb
   • 03_basic_visualization.ipynb
   • 04_advanced_visualization.ipynb

What Is Binder?

Binder is a cloud service that converts any public GitHub repository into an executable environment. It automatically builds a Docker image based on configuration files such as requirements.txt and launches an interactive Jupyter environment where notebooks can be run instantly.

Binder allows you to:

• Run code without installing anything locally
• Share reproducible environments through a simple link
• Experiment freely with temporary interactive sessions

This project provides practical demonstrations of Seaborn’s visualization capabilities and serves as a hands‑on introduction to creating expressive and informative plots. It is ideal for learners who want to explore data visually and understand Seaborn’s core plotting functions.

---