OK, I've changed the logic and would like to ask about keyword.

Considering #3729, I preferred to `dropna` as a keyword, and now it uses `dropna`. But looks better to use `exclude_missing` because `pivot_table` already has `dropna` for different purpose (to exclude index/columns from result which values are all NaN).

Is it OK to add `exclude_missing` to `Dataframe.groupby` and `pivot_table` as new keyword?

Also, I think default should be `dropna=True` based on current behavior which exclude `NaT` as `nan`.