Feature Type

• Adding new functionality to pandas

• Changing existing functionality in pandas

• Removing existing functionality in pandas

Problem Description

Currently the pivot_table has an aggfunc parameter which is used to do a groupby aggregation here. However, no additional arguments can be passed into that agg call. I'm specifically referring to the *args which can be specified in (df/series) groupby.agg function. It would be very useful if pivot_table could accept additional arguments for the aggfunc.

Feature Description

I'm not 100% sure, but I think it would be something like this:

1. Add a **aggfunc_args or aggfunc_args: dict parameter to the pivot_table function.
2. Do the same for the __internal_pivot_table function
3. Change the line here, from agged = grouped.agg(aggfunc) to agged = grouped.agg(aggfunc, **aggfunc_args).
4. Update the docs

Alternative Solutions

The same functionality can currently be achieved by specifying a custom function as aggfunc, but using that is much slower. My use case is pretty much the same as this.
Instead of using pd.pivot_table(... , aggfunc=lambda x: x.sum(min_count=1)), I would like to be able to do pd.pivot_table(... , aggfunc=sum, min_count=1) or similiar.

Additional Context

No response