How can I use Dask with Pandas for large datasets?

How can I use Dask with Pandas for large datasets?

You can use Dask to parallelize your Pandas operations, which is great for handling large datasets that don't fit into memory.

Can you show me a simple example of how to do that?

Sure! First, install Dask with pip install dask. Then, you can read a large CSV file using Dask like this: import dask.dataframe as dd; df = dd.read_csv('large_file.csv').

What operations can I perform on a Dask DataFrame?

You can perform many of the same operations as with Pandas, like filtering, grouping, and aggregating. Just remember to call .compute() to execute the operations.

Are there any limitations I should be aware of?

Yes, some Pandas functions may not be supported in Dask, and you should be cautious with operations that require shuffling data.