BUG: pandas int extension dtypes has no attribute byteorder (pandas-dev#57173)

* support nullable integers in from_dataframe

* gh issue number

* use BaseMaskedDtype

* only skip if int8[pyarrow]

Author: MarcoGorelli

doc/source/whatsnew/v2.2.1.rst

@@ -30,6 +30,7 @@ Fixed regressions
 
 Bug fixes
 ~~~~~~~~~
+- Fixed bug in :func:`pandas.api.interchange.from_dataframe` which was raising for Nullable integers (:issue:`55069`)
 - Fixed bug in :func:`pandas.api.interchange.from_dataframe` which was raising for empty inputs (:issue:`56700`)
 - Fixed bug in :meth:`DataFrame.__getitem__` for empty :class:`DataFrame` with Copy-on-Write enabled (:issue:`57130`)
 

pandas/core/interchange/column.py

@@ -11,6 +11,7 @@
 
 from pandas.core.dtypes.dtypes import (
     ArrowDtype,
+    BaseMaskedDtype,
     DatetimeTZDtype,
 )
 
@@ -143,6 +144,8 @@ 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 isinstance(dtype, BaseMaskedDtype):
+            byteorder = dtype.numpy_dtype.byteorder
         else:
             byteorder = dtype.byteorder
 

pandas/tests/interchange/test_impl.py

@@ -8,6 +8,7 @@
     is_ci_environment,
     is_platform_windows,
 )
+import pandas.util._test_decorators as td
 
 import pandas as pd
 import pandas._testing as tm
@@ -394,6 +395,17 @@ def test_large_string():
     tm.assert_frame_equal(result, expected)
 
 
+@pytest.mark.parametrize(
+    "dtype", ["Int8", pytest.param("Int8[pyarrow]", marks=td.skip_if_no("pyarrow"))]
+)
+def test_nullable_integers(dtype: str) -> None:
+    # https://github.com/pandas-dev/pandas/issues/55069
+    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)
+
+
 def test_empty_dataframe():
     # https://github.com/pandas-dev/pandas/issues/56700
     df = pd.DataFrame({"a": []}, dtype="int8")