Efficient Python for Data Scientists

Efficient Python for Data Scientists is your practical companion to mastering the art of writing clean, optimized, and high-performing Python code for data science. In this book, you'll explore actionable insights and strategies to transform your Python workflows, streamline data analysis, and maximize the potential of libraries like Pandas.

Through nine meticulously crafted chapters, this book covers everything from foundational principles of clean code and efficiency to advanced techniques like caching and vectorization. You'll learn how to write better functions, avoid common pitfalls, and elevate your data exploration process using tools like Pandas Profiling.

Whether you're an aspiring data scientist or a seasoned professional, this book equips you with:

● Clear guidelines for writing clean and maintainable Python code.

● Techniques to measure and optimize code efficiency effectively.

● Practical advice for using Pandas to handle data tasks faster and smarter.

● Proven methods to avoid common coding mistakes and improve productivity.

Each chapter is packed with examples, tips, and tricks, ensuring you have a hands-on learning experience. Dive into Efficient Python for Data Scientists and take the next step toward writing Python code that is not just functional but exceptional.

Table of Contents:

1. Three Principles to Write Python Clean Code
2. Defining & Measuring Code Efficiency
3. Optimizing Your Python Code
4. 5 Tips to Write Efficient Python Functions
5. How to Use Caching to Speed Up Your Python Code & LLM Application?
6. Best Practices To Use Pandas Efficiently As A Data Scientist
7. Make Your Pandas Code 1000 Times Faster With This Trick
8. Data Exploration Becomes Easier & Better With Pandas Profiling
9. Top 10 Pandas Mistakes to Steer Clear of in Your Code