This comprehensive 20-chapter guide teaches you how to understand, prevent, and fix Python errors. Each chapter focuses on a specific topic with real-world examples, common mistakes, and best practices.
Perfect for: Beginners to intermediate Python programmers who want to write better, more robust code.
- Variables and Data Types - Foundation errors (NameError, TypeError, ValueError)
- Operators and Expressions - Math and logic errors
- Strings and String Methods - String manipulation errors
- Lists and List Methods - List operation errors
- Dictionaries and Sets - KeyError and set operations
- Tuples and Immutability - Tuple errors
- Conditional Statements - Logic and comparison errors
- Loops - Iteration errors
- Functions - Parameter and return errors
- File I/O - File operation errors
- Regular Expressions (Regex) - Pattern matching errors
- Pandas Basics - DataFrame errors
- Pandas Advanced - Complex data manipulation
- NumPy - Array operation errors
- Matplotlib - Visualization errors
- Object-Oriented Programming (OOP) - Class and method errors
- Modules and Imports - Import system errors
- Exception Handling - Best practices for catching errors
- Debugging Techniques - Tools and strategies
- Testing and Code Quality - Preventing errors before they happen
- Understand error messages - Read tracebacks like a pro
- Prevent common errors - Write better code from the start
- Debug efficiently - Find and fix bugs quickly
- Write tests - Catch errors before production
- Use best practices - Industry-standard coding patterns
Start with Chapter 1 and work through sequentially. Each chapter builds on previous concepts.
Jump to specific chapters based on your needs. Each chapter is self-contained with complete examples.
Use the error index to quickly find solutions to specific errors you encounter.
- ✅ 500+ code examples - Real-world scenarios
- ✅ Practice problems - Test your understanding
- ✅ Complete solutions - Detailed explanations
- ✅ Best practices - Industry standards
- ✅ Prevention patterns - Stop errors before they happen
Each chapter includes:
- Introduction - What you'll learn
- Error Types - Specific errors covered
- Code Examples - Wrong and correct approaches
- Practice Problems - Test yourself
- Key Takeaways - Summary and best practices
- Python 3.7 or higher
- Basic understanding of programming concepts (helpful but not required)
For chapters 11-15:
- pandas
- numpy
- matplotlib
pip install pandas numpy matplotlibQuick reference for finding solutions to specific errors:
AttributeError- Ch 6, 14, 16, 17FileNotFoundError- Ch 10ImportError- Ch 17IndexError- Ch 1, 4, 14IndentationError- Ch 7
KeyError- Ch 5, 12, 13ModuleNotFoundError- Ch 17NameError- Ch 1
RecursionError- Ch 16SyntaxError- Ch 2, 7TypeError- Ch 1, 2, 4, 6, 14, 16ValueError- Ch 1, 3, 12, 15ZeroDivisionError- Ch 2
- Week 1-2: Chapters 1-5 (Basic types and collections)
- Week 3: Chapters 6-8 (Control flow)
- Week 4: Chapters 9-10 (Functions and files)
- Week 5: Chapters 18-20 (Error handling and testing)
- Week 6: Practice and review
- Week 1: Chapters 11-15 (Libraries)
- Week 2: Chapters 16-17 (OOP and imports)
- Week 3: Chapters 18-20 (Professional practices)
Jump directly to error types you're encountering
Found an error or want to improve an example? Contributions welcome!
This guide is provided for educational purposes. Feel free to use and share with attribution.
Created for Python learners everywhere. Special thanks to the Python community for their invaluable documentation and resources.
- Download all chapters - Get the complete guide
- Start with Chapter 1 - Build your foundation
- Code along - Type out examples yourself
- Do practice problems - Test your knowledge
- Keep as reference - Return when you encounter errors
If you find this guide helpful:
- ⭐ Star the repository
- 📢 Share with other Python learners
- 💬 Provide feedback for improvements
Ready to master Python errors? Start with Chapter 1: Variables and Data Types!
Happy coding! 🐍