How can I efficiently handle large datasets in Python for data analysis

I am working on a project that involves analyzing large datasets in Python. However, I’m encountering performance issues and memory limitations when dealing with these large datasets. What are some efficient approaches or best practices for handling large datasets in Python?

Techniques to read and process large datasets efficiently
Memory management strategies to avoid out-of-memory errors
Optimized libraries or frameworks for handling large datasets
Strategies for parallel processing or distributed computing
Any insights or recommendations on these topics would be greatly appreciated. Thank you!

Provide a detailed description of the steps you took or the approaches you attempted to address the issue.