BUG: Assignment of pyarrow arrays yield unexpected dtypes

pandas/core/frame.py

@@ -48,10 +48,17 @@
 )
 from pandas._libs.hashtable import duplicated
 from pandas._libs.lib import is_range_indexer
-from pandas.compat import PYPY
+from pandas.compat import (
+    PYPY,
+    pa_version_under10p1,
+)
 from pandas.compat._constants import REF_COUNT
 from pandas.compat._optional import import_optional_dependency
 from pandas.compat.numpy import function as nv
+
+if not pa_version_under10p1:
+    import pyarrow as pa
+
 from pandas.errors import (
     ChainedAssignmentError,
     InvalidIndexError,
@@ -5058,7 +5065,12 @@ def _sanitize_column(self, value) -> tuple[ArrayLike, BlockValuesRefs | None]:
 
         if is_list_like(value):
             com.require_length_match(value, self.index)
-        return sanitize_array(value, self.index, copy=True, allow_2d=True), None
+
+        if not pa_version_under10p1 and isinstance(value, pa.lib._PandasConvertible):
+            dtype = ArrowDtype(value.type)
+        else:
+            dtype = None
+        return sanitize_array(value, self.index, dtype, copy=True, allow_2d=True), None
 
     @property
     def _series(self):

pandas/tests/extension/test_arrow.py

@@ -1125,6 +1125,14 @@ def test_comp_masked_numpy(self, masked_dtype, comparison_op):
         expected = pd.Series(exp, dtype=ArrowDtype(pa.bool_()))
         tm.assert_series_equal(result, expected)
 
+    def test_assign_column_in_dataframe(self, data):
+        df = pd.DataFrame(data=data, columns=["A"], dtype=data.dtype)
+        df["B"] = pa.array(data, type=data.dtype.pyarrow_dtype)
+        result = df.dtypes
+        expected = pd.Series({"A": data.dtype, "B": data.dtype})
+
+        tm.assert_series_equal(result, expected)
+
 
 class TestLogicalOps:
     """Various Series and DataFrame logical ops methods."""