BUG: Non unitless np NaT arithmetic with non-nano #52821
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mroeschke
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Numeric Operations
pandas/core/ops/array_ops.py
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| @@ -533,7 +538,11 @@ def maybe_prepare_scalar_for_op(obj, shape: Shape): | |||
| from pandas.core.arrays import DatetimeArray | |||
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| # Avoid possible ambiguities with pd.NaT | |||
| obj = obj.astype("datetime64[ns]") | |||
| # GH 52295 | |||
| if is_unitless(obj.dtype) or not is_supported_unit( | |||
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i think in non-supported unit cases we'd want to use the closest-to-supported? could just handle the unitless case here?
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Good call. We also need to handle the unsupported NaT case here too though
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thx @mroeschke |
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Owee, I'm MrMeeseeks, Look at me. There seem to be a conflict, please backport manually. Here are approximate instructions:
And apply the correct labels and milestones. Congratulations — you did some good work! Hopefully your backport PR will be tested by the continuous integration and merged soon! Remember to remove the If these instructions are inaccurate, feel free to suggest an improvement. |
(cherry picked from commit eb9a3e8)
…ic with non-nano) (#52847) BUG: Non unitless np NaT arithmetic with non-nano (#52821) (cherry picked from commit eb9a3e8) Co-authored-by: Matthew Roeschke <[email protected]>
datetime&timedeltabinary operations inpandas-2.0#52295 (Replace xxxx with the GitHub issue number)doc/source/whatsnew/vX.X.X.rstfile if fixing a bug or adding a new feature.