Dask vs Pandas: Best Practices for Data Analysis

What are the main differences between Dask and Pandas?

Dask is designed for parallel computing and can handle larger-than-memory datasets, while Pandas is great for in-memory data manipulation.

When should I use Dask instead of Pandas?

Use Dask when working with large datasets that don't fit into memory or when you need to perform parallel computations.

Can you give me some best practices for using Dask?

Sure! Some best practices include using Dask's delayed functions for lazy evaluation, optimizing your task graph, and monitoring performance with Dask's dashboard.

Are there any specific scenarios where Pandas is preferred?

Yes, Pandas is preferred for smaller datasets where performance is not an issue, and for tasks that require complex data manipulation.