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BUG: pandas int extension dtypes has no attribute byteorder #57173

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Merged
merged 5 commits into from
Feb 1, 2024
Merged

BUG: pandas int extension dtypes has no attribute byteorder #57173

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7dcbc6a
support nullable integers in from_dataframe
MarcoGorelli Jan 31, 2024
2d4ec3a
gh issue number
MarcoGorelli Jan 31, 2024
6210ba9
use BaseMaskedDtype
MarcoGorelli Feb 1, 2024
20463c9
only skip if int8[pyarrow]
MarcoGorelli Feb 1, 2024
024a4c5
Merge remote-tracking branch 'upstream/main' into nullable-interchange
MarcoGorelli Feb 1, 2024
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v2.2.1.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -29,6 +29,7 @@ Fixed regressions

Bug fixes
~~~~~~~~~
- Fixed bug in :func:`pandas.api.interchange.from_dataframe` which was raising for Nullable integers (:issue:`55069`)
- Fixed bug in :meth:`DataFrame.__getitem__` for empty :class:`DataFrame` with Copy-on-Write enabled (:issue:`57130`)

.. ---------------------------------------------------------------------------
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7 changes: 6 additions & 1 deletion pandas/core/interchange/column.py
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Expand Up @@ -15,7 +15,10 @@
)

import pandas as pd
from pandas.api.types import is_string_dtype
from pandas.api.types import (
is_extension_array_dtype,
is_string_dtype,
)
from pandas.core.interchange.buffer import PandasBuffer
from pandas.core.interchange.dataframe_protocol import (
Column,
Expand Down Expand Up @@ -143,6 +146,8 @@ def _dtype_from_pandasdtype(self, dtype) -> tuple[DtypeKind, int, str, str]:
byteorder = dtype.numpy_dtype.byteorder
elif isinstance(dtype, DatetimeTZDtype):
byteorder = dtype.base.byteorder # type: ignore[union-attr]
elif is_extension_array_dtype(dtype):
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Could you check BaseMaskedDtype instead?

byteorder = dtype.numpy_dtype.byteorder
else:
byteorder = dtype.byteorder

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10 changes: 10 additions & 0 deletions pandas/tests/interchange/test_impl.py
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Expand Up @@ -392,3 +392,13 @@ def test_large_string():
result = pd.api.interchange.from_dataframe(df.__dataframe__())
expected = pd.DataFrame({"a": ["x"]}, dtype="object")
tm.assert_frame_equal(result, expected)


@pytest.mark.parametrize("dtype", ["Int8", "Int8[pyarrow]"])
def test_nullable_integers(dtype: str) -> None:
# https://github.com/pandas-dev/pandas/issues/55069
pytest.importorskip("pyarrow")
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We only need to skip for the second case no? Any reason we don't just use pytest.param("Int8[pyarrow], marks=td.skip_if_no("pyarrow"))?

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because I didn't know you could do that 🙈

df = pd.DataFrame({"a": [1]}, dtype=dtype)
expected = pd.DataFrame({"a": [1]}, dtype="int8")
result = pd.api.interchange.from_dataframe(df.__dataframe__())
tm.assert_frame_equal(result, expected)