How can I optimize my groupby operations in pandas?

How can I optimize my groupby operations in pandas?

To optimize groupby operations in pandas, consider using the agg() function to apply multiple aggregations at once.

Are there any specific techniques to speed up large DataFrame groupby operations?

Yes, you can use the numba library to compile your functions, or consider using dask for parallel processing.

What about memory usage? Any tips?

To reduce memory usage, try using astype() to downcast your data types and avoid unnecessary copies of your DataFrame.

Can you give an example of using agg() with groupby?

Sure! You can do something like df.groupby('column').agg({'col1': 'sum', 'col2': 'mean'}) to aggregate multiple columns.