BUG: Assignment of pyarrow arrays yield unexpected dtypes

doc/source/whatsnew/v3.0.0.rst

@@ -646,6 +646,7 @@ Conversion
 - Bug in :meth:`DataFrame.update` bool dtype being converted to object (:issue:`55509`)
 - Bug in :meth:`Series.astype` might modify read-only array inplace when casting to a string dtype (:issue:`57212`)
 - Bug in :meth:`Series.reindex` not maintaining ``float32`` type when a ``reindex`` introduces a missing value (:issue:`45857`)
+- Bug in :meth:`sanitize_array` was not taking into account pyarrow arrays. (:issue:`56994`)
 
 Strings
 ^^^^^^^

pandas/core/construction.py

@@ -23,6 +23,7 @@
     get_supported_dtype,
     is_supported_dtype,
 )
+from pandas.compat import pa_version_under10p1
 
 from pandas.core.dtypes.base import ExtensionDtype
 from pandas.core.dtypes.cast import (
@@ -40,7 +41,10 @@
     is_object_dtype,
     pandas_dtype,
 )
-from pandas.core.dtypes.dtypes import NumpyEADtype
+from pandas.core.dtypes.dtypes import (
+    ArrowDtype,
+    NumpyEADtype,
+)
 from pandas.core.dtypes.generic import (
     ABCDataFrame,
     ABCExtensionArray,
@@ -51,6 +55,9 @@
 
 import pandas.core.common as com
 
+if not pa_version_under10p1:
+    pass
+
 if TYPE_CHECKING:
     from collections.abc import Sequence
 
@@ -549,6 +556,9 @@ def sanitize_array(
     np.ndarray or ExtensionArray
     """
     original_dtype = dtype
+    if not pa_version_under10p1 and lib.is_pyarrow_array(data) and dtype is None:
+        dtype = ArrowDtype(data.type)
+
     if isinstance(data, ma.MaskedArray):
         data = sanitize_masked_array(data)
 

pandas/tests/extension/test_arrow.py

@@ -1085,6 +1085,14 @@ 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."""