Numpy supports NaT for both datetime64 as well as timedelta64, and when converting K vectors of timestamp/timespan, nulls are converted to NaT as expected
Ideally, we would have this behavior without the up/down cast.
The conversion is also problematic in the reverse. NaT from numpy arrays are incorrectly converted into K. NaT from datetime64 gets converted to 1970.01.01, while NaT from timedelta64 gets converted to 0
Numpy supports NaT for both datetime64 as well as timedelta64, and when converting K vectors of timestamp/timespan, nulls are converted to NaT as expected
but when converting K arrays of type minute, time, second, date, or month, nulls are not handled properly:
If I upcast before the conversion and then downcast, everything works as expected, but this seems unnecessarily hacky.
Ideally, we would have this behavior without the up/down cast.
The conversion is also problematic in the reverse. NaT from numpy arrays are incorrectly converted into K. NaT from datetime64 gets converted to 1970.01.01, while NaT from timedelta64 gets converted to 0