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Ensure conversion to "native" types for integer EA #31328

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Ensure conversion to "native" types for integer EA #31328

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a7bda74
add .item() to__iter__ and add tests
rushabh-v Jan 26, 2020
0b01ace
rum black pandas
rushabh-v Jan 26, 2020
735224a
add __iter__ to IntegerArray
rushabh-v Jan 26, 2020
9dac007
use isinstance
rushabh-v Feb 9, 2020
b098f4f
parametrize
rushabh-v Feb 9, 2020
a5d64c4
add whatsnew
rushabh-v Feb 9, 2020
151fdc6
Merge branch 'master' of https://github.com/pandas-dev/pandas into EA…
rushabh-v Mar 15, 2020
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2 changes: 1 addition & 1 deletion doc/source/whatsnew/v1.1.0.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -382,7 +382,7 @@ Sparse
ExtensionArray
^^^^^^^^^^^^^^

-
- integer EA will now return objects of native type only when iterated. (:issue:`29738`)
-


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7 changes: 7 additions & 0 deletions pandas/core/arrays/integer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -354,6 +354,13 @@ def __init__(self, values: np.ndarray, mask: np.ndarray, copy: bool = False):
)
super().__init__(values, mask, copy=copy)

def __iter__(self):
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I think we could actually move this to base masked and/or the base EA interface (maybe)

for i in range(len(self)):
if self._mask[i]:
yield self.dtype.na_value
else:
yield self._data[i].item()

@classmethod
def _from_sequence(cls, scalars, dtype=None, copy: bool = False) -> "IntegerArray":
return integer_array(scalars, dtype=dtype, copy=copy)
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18 changes: 18 additions & 0 deletions pandas/tests/arrays/test_integer.py
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Expand Up @@ -793,6 +793,24 @@ def test_integer_array_constructor_copy():
assert result._mask is not mask


@pytest.mark.parametrize(
"data",
[
pd.Series([1, 2], dtype="int64").tolist()[0],
pd.Series([1, 2], dtype="Int64").tolist()[0],
pd.Series([1, 2], dtype="int64").to_dict()[0],
pd.Series([1, 2], dtype="Int64").to_dict()[0],
list(pd.Series([1, 2], dtype="int64").iteritems())[0][1],
list(pd.Series([1, 2], dtype="Int64").iteritems())[0][1],
list(iter(pd.Series([1, 2], dtype="int64")))[0],
list(iter(pd.Series([1, 2], dtype="Int64")))[0],
],
)
def test_integer_Series_iter_return_native(data):
# GH 29738
assert isinstance(data, int)


@pytest.mark.parametrize(
"values",
[
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