Convert ArrowExtensionArray to proper NumPy dtype #56290
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mroeschke
reviewed
Dec 5, 2023
pandas/core/arrays/_utils.py
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| from pandas.core.dtypes.common import is_numeric_dtype | ||
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| def _to_numpy_dtype_inference(arr, dtype, na_value, hasna): |
mroeschke
reviewed
Dec 5, 2023
| @@ -58,6 +58,7 @@ | |||
| "_iLocIndexer", | |||
| # TODO(3.0): GH#55043 - remove upon removal of ArrayManager | |||
| "_get_option", | |||
| "_to_numpy_dtype_inference", | |||
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Since the original method is in core, probably can remove the leading _
lukemanley
reviewed
Dec 5, 2023
| @@ -1501,8 +1511,8 @@ def test_to_numpy_int_with_na(): | |||
| data = [1, None] | |||
| arr = pd.array(data, dtype="int64[pyarrow]") | |||
| result = arr.to_numpy() | |||
| expected = np.array([1, pd.NA], dtype=object) | |||
| assert isinstance(result[0], int) | |||
| expected = np.array([1, np.nan]) | |||
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Does this mean that ArrowExentionArray.to_numpy is now lossy for integer types if there are NA's since it will now be converted to float?
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I'm a little surprised it doesn't break more tests as I think there are still a number of places that try to round-trip through numpy
# Conflicts: # doc/source/whatsnew/v2.2.0.rst
# Conflicts: # doc/source/whatsnew/v2.2.0.rst # pandas/core/arrays/arrow/array.py # pandas/tests/extension/test_arrow.py
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cc @mroeschke this should be ready as well |
# Conflicts: # pandas/core/arrays/arrow/array.py
jorisvandenbossche
approved these changes
Dec 21, 2023
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np.logfails with missing pyarrow values #56285 (Replace xxxx with the GitHub issue number)doc/source/whatsnew/vX.X.X.rstfile if fixing a bug or adding a new feature.As discussed on the other pr