Initial commit

Author: AlenkaF

python/pyarrow/array.pxi

@@ -2308,6 +2308,13 @@ cdef _array_like_to_pandas(obj, options, types_mapper):
         dtype = "object"
     elif types_mapper:
         dtype = types_mapper(original_type)
+    elif _pandas_api.uses_string_dtype() and (
+        original_type.id == _Type_STRING or
+        original_type.id == _Type_LARGE_STRING or
+        original_type.id == _Type_STRING_VIEW
+    ):
+        # for pandas 3.0+, use pandas' new default string dtype
+        dtype = _pandas_api.pd.StringDtype(na_value=np.nan)
     else:
         dtype = None
 

python/pyarrow/tests/test_pandas.py

@@ -4651,6 +4651,29 @@ def test_chunked_array_to_pandas_types_mapper():
     assert result.dtype == np.dtype("int64")
 
 
+@pytest.mark.parametrize(
+    "string_type", [pa.string(), pa.large_string(), pa.string_view()]
+)
+@pytest.mark.parametrize("data", [[], [None]])
+def test_array_to_pandas_string_dtype(string_type, data):
+    # GH-49002
+    if Version(pd.__version__) < Version("3.0.0"):
+        pytest.skip("PyArrow backed string dtype missing")
+
+    arr = pa.array(data, type=string_type)
+    result = arr.to_pandas()
+    assert result.dtype == pd.StringDtype(na_value=np.nan)
+
+    arr = pa.chunked_array([data], type=string_type)
+    result = arr.to_pandas()
+    assert result.dtype == pd.StringDtype(na_value=np.nan)
+
+    # Test types_mapper takes precedence
+    types_mapper = {string_type: None}.get
+    result = arr.to_pandas(types_mapper=types_mapper)
+    assert result.dtype == np.dtype("object")
+
+
 # ----------------------------------------------------------------------
 # Legacy metadata compatibility tests