add specific tests

Author: jorisvandenbossche

pandas/core/arrays/string_.py

@@ -285,16 +285,14 @@ def construct_array_type(  # type: ignore[override]
             return ArrowStringArrayNumpySemantics
 
     def _get_common_dtype(self, dtypes: list[DtypeObj]) -> DtypeObj | None:
-        allowed_numpy_kinds = {"S", "U"}
-
         storages = set()
         na_values = set()
 
         for dtype in dtypes:
             if isinstance(dtype, StringDtype):
                 storages.add(dtype.storage)
                 na_values.add(dtype.na_value)
-            elif isinstance(dtype, np.dtype) and dtype.kind in allowed_numpy_kinds:
+            elif isinstance(dtype, np.dtype) and dtype.kind == "U":
                 continue
             else:
                 return None

pandas/tests/arrays/string_/test_concat.py

@@ -0,0 +1,68 @@
+import numpy as np
+import pytest
+
+from pandas.compat import HAS_PYARROW
+
+from pandas.core.dtypes.cast import find_common_type
+
+import pandas as pd
+import pandas._testing as tm
+
+
+@pytest.mark.parametrize(
+    "to_concat_dtypes, result_dtype",
+    [
+        # same types
+        ([("pyarrow", pd.NA), ("pyarrow", pd.NA)], ("pyarrow", pd.NA)),
+        ([("pyarrow", np.nan), ("pyarrow", np.nan)], ("pyarrow", np.nan)),
+        ([("python", pd.NA), ("python", pd.NA)], ("python", pd.NA)),
+        ([("python", np.nan), ("python", np.nan)], ("python", np.nan)),
+        # pyarrow preference
+        ([("pyarrow", pd.NA), ("python", pd.NA)], ("pyarrow", pd.NA)),
+        # NA preference
+        ([("python", pd.NA), ("python", np.nan)], ("python", pd.NA)),
+    ],
+)
+def test_concat_series(request, to_concat_dtypes, result_dtype):
+    if any(storage == "pyarrow" for storage, _ in to_concat_dtypes) and not HAS_PYARROW:
+        pytest.skip("Could not import 'pyarrow'")
+
+    ser_list = [
+        pd.Series(["a", "b", None], dtype=pd.StringDtype(storage, na_value))
+        for storage, na_value in to_concat_dtypes
+    ]
+
+    result = pd.concat(ser_list, ignore_index=True)
+    expected = pd.Series(
+        ["a", "b", None, "a", "b", None], dtype=pd.StringDtype(*result_dtype)
+    )
+    tm.assert_series_equal(result, expected)
+
+    # order doesn't matter for result
+    result = pd.concat(ser_list[::1], ignore_index=True)
+    tm.assert_series_equal(result, expected)
+
+
+def test_concat_with_object(string_dtype_arguments):
+    # _get_common_dtype cannot inspect values, so object dtype with strings still
+    # results in object dtype
+    result = pd.concat(
+        [
+            pd.Series(["a", "b", None], dtype=pd.StringDtype(*string_dtype_arguments)),
+            pd.Series(["a", "b", None], dtype=object),
+        ]
+    )
+    assert result.dtype == np.dtype("object")
+
+
+def test_concat_with_numpy(string_dtype_arguments):
+    # common type with a numpy string dtype always preserves the pandas string dtype
+    dtype = pd.StringDtype(*string_dtype_arguments)
+    assert find_common_type([dtype, np.dtype("U")]) == dtype
+    assert find_common_type([np.dtype("U"), dtype]) == dtype
+    assert find_common_type([dtype, np.dtype("U10")]) == dtype
+    assert find_common_type([np.dtype("U10"), dtype]) == dtype
+
+    # with any other numpy dtype -> object
+    assert find_common_type([dtype, np.dtype("S")]) == np.dtype("object")
+    assert find_common_type([dtype, np.dtype("int64")]) == np.dtype("object")