BUG: Fix multiplying Timedelta Series with a pandas nullable dtype Series #58375
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mroeschke
added
Numeric Operations
| @@ -365,6 +365,7 @@ Timedelta | |||
| ^^^^^^^^^ | |||
| - Accuracy improvement in :meth:`Timedelta.to_pytimedelta` to round microseconds consistently for large nanosecond based Timedelta (:issue:`57841`) | |||
| - Bug in :meth:`DataFrame.cumsum` which was raising ``IndexError`` if dtype is ``timedelta64[ns]`` (:issue:`57956`) | |||
| - Bug in :meth:`TimedeltaArray._simple_new` which was raising ``AssertionError`` When multiplying a Series with a timedelta64 dtype with another Series that uses any of the pandas nullable dtypes ``('Int8', 'Int16', 'Int32', 'Int64', 'UInt8', 'UInt16', 'UInt32', 'UInt64', 'Float32', 'Float64', or 'boolean')`` (:issue:`58054`) | |||
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don't reference _simple_new or even TimedeltaArray, just the relevant dtypes in Series/DataFrame
| @@ -492,6 +494,16 @@ def __mul__(self, other) -> Self: | |||
| result = np.array(result) | |||
| return type(self)._simple_new(result, dtype=result.dtype) | |||
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| if is_bool_dtype(other.dtype) or is_numeric_dtype(other.dtype): | |||
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instead of doing this here, check for BaseMaskedArray and return NotImplemented
| td_series = Series([timedelta(hours=1)]) | ||
| other = Series([True]) | ||
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| pandas_types = [ |
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use a fixture or pytest.mark.parametrize
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Thanks for the pull request, but it appears to have gone stale. If interested in continuing, please merge in the main branch, address any review comments and/or failing tests, and we can reopen. |
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doc/source/whatsnew/vX.X.X.rstfile if fixing a bug or adding a new feature.Tests were added, but raise an error. Does anyone know how to fix it?
This is my first pull request, please let me know if I need to change anything :)