BUG: Take method of NumpyExtensionArray now returns another extension array with the correct dtype. #62502
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…take method to return correct dtype.
rhshadrach added Bug ExtensionArray 
| Several tests are currently failing due to a new version of |
pandas/core/arrays/_mixins.py Outdated
| fill_value=fill_value, | ||
| axis=axis, | ||
| ) | ||
| if self.dtype in [ |
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Do this on the NumpySemantics instead of this mixin
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I'm not sure what you mean by "Numpy semantics". I changed the condition to check the numpy_dtype so it can be compared to a list of bare Numpy dtypes. I'm not sure if this is what you meant. Can you clarify?
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woops, meant to write NumpyExtensionArray. Implement a take method there along the lines of
def take(...) if self.dtype.kind in "iub": ... else: return super().take(...) | | ||
| | ||
| @pytest.mark.parametrize("dtype", [np.uint32, np.uint64, np.int32, np.int64]) | ||
| def test_take_assigns_correct_dtype(dtype): |
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Comment pointing back to the motivating GH issue
| indices, allow_fill=allow_fill, fill_value=fill_value, axis=axis | ||
| ) | ||
| # See GH#62448. | ||
| if self.dtype.numpy_dtype in [ |
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do this check before the super call, and just check self.dtype.kind in "iub"
| # TODO: Add the smaller width dtypes to the parameter sets of these tests. | ||
| @pytest.mark.parametrize( | ||
| "dtype", | ||
| [np.uint8, np.uint16, np.uint32, np.uint64, np.int8, np.int16, np.int32, np.int64], |
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can you also test bool dtype
3 participants
In the edge case when called with integer arrays and asked to access non-existent entries (to be replaced with NaN), the
takemethod ofNumpyExtensionArrayproduces arrays whose dtypes don't match their underlying data.Specifically,
takepromotes the underlying data to a floating-point type, but doesn't promote the dtype of the extension array to match.These changes ensure that the result of this method has the correct dtype for its data.
doc/source/whatsnew/vX.X.X.rstfile if fixing a bug or adding a new feature.