How to Handle Large CSV Files In Chunks? | Python Pandas Tutorial For Data Engineering

Welcome to ITVersity’s ‘Data Analysis Using Pandas’ series, your ultimate guide to mastering Python and Pandas for data analysis! In this video, we dive into an advanced and essential technique for handling large CSV files in Pandas by processing data in chunks. Working with massive datasets can often lead to memory issues, but with Pandas’ chunksize parameter, you can efficiently load and analyze large-scale data without overwhelming your system.

*What You’ll Learn in This Video:*

✅ Techniques for loading large datasets in smaller, manageable chunks.
✅ Practical examples of iterating through chunks using Python generators for efficient processing.
✅ Applying data transformations and business logic to chunks of data in real-world scenarios.

*Why This Skill Matters:*

Handling large datasets is a critical skill for data scientists, data engineers, and anyone working in big data analysis. This tutorial equips you to process and analyze large-scale data efficiently, even in environments with memory constraints.

Continue Your Learning Journey with Pandas! 🚀

*Resources:*
Ready to kickstart your coding journey? Join Python for Beginners: Learn Python with Hands-on Projects and master Python by building real-world projects from day one!

🔔 Subscribe to ITVersity for tutorials on Python, Pandas, and Data Engineering:

*What’s Next?*
Stay tuned as we dive deeper into practical workflows and real-world scenarios involving chunk-based data processing in upcoming videos.

Connect with Us:

#DataEngineering #Pandas #Python #Analytics #DataAnalysis #Programming

[karthikb.s.k.]

Nice sir . What configuration of Mackbook are you using please let me know.