Fix #59772: tz_aware NaT raises exception on to_numpy #61302
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Pandas series with NaT (not a time) localized, raised an exception when converting to a numpy array Fixed by removing localization from the NaT's
mroeschke
requested changes
Apr 17, 2025
| @@ -592,7 +592,17 @@ def to_numpy( | |||
| ------- | |||
| numpy.ndarray | |||
| """ | |||
| result = np.asarray(self, dtype=dtype) | |||
| if dtype == "datetime64" and self.dtype.kind == "M": | |||
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This fix is too specific. I think the TypeError raised in the original issue should be root caused first.
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Fix error when converting tz-aware Series with NaT to NumPy array
Previously, converting a Series of timezone-aware pd.NaT to a NumPy array using
.to_numpy("datetime64[ns]") would raise an exception.
It would happen because it could not be converted to datetime64 as a tz-aware value.
This is now fixed by removing the timezone localization from NaT values before the conversion.