This content originally appeared on DEV Community and was authored by Nivesh Bansal
Data visualization is one of the most powerful skills for Data Science, Machine Learning, AI, and Analytics.
I recently created a complete Seaborn tutorial with full source code covering almost all major plots in Python. Whether you are a student, developer, or data enthusiast, this guide will help you understand Seaborn from scratch with step-by-step examples.
Full GitHub Repository (Day 01 & Day 02 Source Code):
Repo – All Source Code
Topics Covered in This Seaborn Tutorial
Scatter Plots
Line Plots
Bar Plots
Box Plots
Violin Plots
Distribution Plots
Pair Plots
Heatmaps
Categorical Plots
Advanced Styling & Themes
Why Learn Seaborn?
Seaborn is a Python data visualization library built on top of Matplotlib, making it simple to create beautiful, statistical, and publication-ready plots.
It is widely used in Data Analytics, Machine Learning, and AI projects for:
- Exploring datasets
- Identifying hidden patterns
- Improving model insights
- Making reports more professional
Who Should Read This Post?
This project is perfect for:
- Data Science Students learning visualization
- Machine Learning Beginners exploring datasets
- Python Developers building projects
- AI & Analytics Enthusiasts wanting better insights
Why This Repository Stands Out
- Covers all basic to advanced plots in Seaborn
- Organized into Day 01 & Day 02 lessons
- Fully documented Python source code
- Beginner-friendly but useful for professionals too
GitHub Repository
Repo – All Source Code
Don’t forget to star the repo and share your feedback!
Final Thoughts
Data visualization is not just about making graphs — it’s about telling a story with data.
With this Seaborn tutorial, you’ll gain the confidence to explore datasets visually and enhance your Data Science, AI, and Machine Learning journey.
This content originally appeared on DEV Community and was authored by Nivesh Bansal