📊 Matplotlib Exercises with Solutions

A curated collection of Matplotlib Exercises(Leetcode style with answer + explanations) designed to help you master data visualization through hands-on problem solving.

Instead of following tutorials, you'll solve carefully structured plotting problems ranging from beginner to advanced levels. Each challenge focuses on a specific Matplotlib concept and encourages independent problem-solving before reviewing the reference solution.

Whether you're preparing for data science interviews, strengthening your Python skills or becoming a Machine Learning Engineer, this repository provides practical exercises that mirror real-world visualization tasks.

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✨ Features

• 📈 50+ progressively organized coding challenges
• 🟢 Easy → 🟡 Medium → 🔴 Hard difficulty levels
• 📝 Clear and professional problem statements
• 💡 Real-world visualization scenarios
• ✅ Reference solutions for self-review
• 🖼️ Expected output image for comparison
• 🎯 Focus on writing clean and maintainable Matplotlib code

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📂 Repository Structure

matplotlib exercises with solutions/
│
├── Easy/
│   ├── 001_monthly_sales_trend/
│   │   ├── README.md
│   │   ├── solution.py
│   │   └── output.png
│   │
│   ├── 002_website_traffic_analysis/
│   └── ...
│
├── Medium/
│   └── ...
│
├── Hard/
│   └── ...
│
└── README.md

Each exercise directory contains:

File	Description
README.md	Problem statement, requirements, constraints and expected output
solution.py	Reference implementation
output.png	Expected visualization

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🎯 Difficulty Levels

Level	Description
🟢 Easy	Basic plotting, labels, titles, legends, grids and customization
🟡 Medium	Multiple plots, subplots, styling, annotations and layout management
🔴 Hard	Advanced visualization techniques, complex layouts, statistical plots, 3D graphics, and real-world challenges

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📚 Topics Covered

• Line Plots
• Scatter Plots
• Bar Charts
• Histograms
• Pie Charts
• Box Plots
• Error Bars
• Subplots
• Figure & Axes Customization
• Legends
• Grids
• Tick Formatting
• Colors & Styles
• Annotations
• Time Series Visualization
• Statistical Visualization
• 3D Plotting
• Real-World Visualization Problems

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🚀 Getting Started

Prerequisites

• Python 3.9+
• Matplotlib

Install Matplotlib:

pip install matplotlib

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💻 How to Practice

For the best learning experience:

1. Read the problem statement in README.md.
2. Solve the challenge on your own.
3. Compare your visualization with output.png.
4. Review solution.py only if needed.

Note: Try to solve each problem without using the reference solution. The goal is to develop problem-solving skills rather than memorizing code.

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🎓 Who Is This Repository For?

This repository is ideal for:

• Python Developers
• Data Science Students
• Machine Learning Engineers
• Data Analysts
• Anyone learning Matplotlib through practice

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🤝 Contributing

Contributions are welcome.

You can contribute by:

• Adding new challenges
• Improving existing problems
• Enhancing reference solutions
• Fixing bugs
• Improving documentation

Please open an issue or submit a pull request.

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📄 License

This project is licensed under the MIT License.

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⭐ Support

If you find this repository helpful, consider giving it a Star.

Happy Coding! 🚀