Preserve ArrowDtype in Series.struct.fields

python/cudf/cudf/core/accessors/struct.py

@@ -9,7 +9,6 @@
 from cudf.core.column.struct import StructColumn
 from cudf.core.dtype.validators import is_dtype_obj_struct
 from cudf.core.dtypes import StructDtype
-from cudf.utils.dtypes import get_dtype_of_same_kind
 
 if TYPE_CHECKING:
     from cudf.core.dataframe import DataFrame
@@ -64,26 +63,18 @@ def field(self, key) -> Series | Index:
         field_keys = list(struct_dtype_fields.keys())
         if key in struct_dtype_fields:
             pos = field_keys.index(key)
-            assert isinstance(self._column, StructColumn)
-            return self._return_or_inplace(
-                self._column._get_sliced_child(pos)._with_type_metadata(
-                    get_dtype_of_same_kind(
-                        self._column.dtype, struct_dtype_fields[key]
-                    )
-                )
-            )
         elif isinstance(key, int):
-            try:
-                assert isinstance(self._column, StructColumn)
-                return self._return_or_inplace(
-                    self._column._get_sliced_child(key)
-                )
-            except IndexError as err:
-                raise IndexError(f"Index {key} out of range") from err
+            pos = key
         else:
             raise KeyError(
                 f"Field '{key}' is not found in the set of existing keys."
             )
+        assert isinstance(self._column, StructColumn)
+        try:
+            result = self._column._get_sliced_child(pos)
+        except IndexError as err:
+            raise IndexError(f"Index {key} out of range") from err
+        return self._return_or_inplace(result)
 
     def explode(self) -> DataFrame:
         """

python/cudf/cudf/core/column/struct.py

@@ -2,7 +2,7 @@
 # SPDX-License-Identifier: Apache-2.0
 from __future__ import annotations
 
-from typing import TYPE_CHECKING, Any, cast
+from typing import TYPE_CHECKING, Any
 
 import pandas as pd
 import pyarrow as pa
@@ -13,7 +13,10 @@
 from cudf.core.column.column import ColumnBase
 from cudf.core.dtype.validators import is_dtype_obj_struct
 from cudf.core.dtypes import StructDtype
-from cudf.utils.dtypes import dtype_from_pylibcudf_column
+from cudf.utils.dtypes import (
+    dtype_from_pylibcudf_column,
+    get_dtype_of_same_kind,
+)
 from cudf.utils.scalar import (
     maybe_nested_pa_scalar_to_py,
     pa_scalar_to_plc_scalar,
@@ -75,16 +78,31 @@ def _validate_args(  # type: ignore[override]
         return plc_column, dtype
 
     def _get_sliced_child(self, idx: int) -> ColumnBase:
-        """Get a child column properly sliced to match the parent's view."""
+        """
+        Get a child column properly sliced to match the parent's view.
+
+        Parameters
+        ----------
+        idx : int
+            The positional index of the child column to get.
+
+        Returns
+        -------
+        ColumnBase
+            The child column at positional index `idx`.
+        """
         if idx < 0 or idx >= self.plc_column.num_children():
             raise IndexError(
                 f"Index {idx} out of range for {self.plc_column.num_children()} children"
             )
 
         sliced_plc_col = self.plc_column.struct_view().get_sliced_child(idx)
-        dtype = cast(StructDtype, self.dtype)
-        sub_dtype = list(dtype.fields.values())[idx]
-        return ColumnBase.create(sliced_plc_col, sub_dtype)
+        sub_dtype = list(
+            StructDtype.from_struct_dtype(self.dtype).fields.values()
+        )[idx]
+        return ColumnBase.create(
+            sliced_plc_col, get_dtype_of_same_kind(self.dtype, sub_dtype)
+        )
 
     def _prep_pandas_compat_repr(self) -> StringColumn | Self:
         """

python/cudf/cudf/core/dataframe.py

@@ -2092,10 +2092,7 @@ def _concat(
                 out.index.dtype, CategoricalDtype
             ):
                 out = out.set_index(out.index)
-        for name, col in out._column_labels_and_values:
-            out._data[name] = col._with_type_metadata(
-                tables[0]._data[name].dtype,
-            )
+        out = out._copy_type_metadata(tables[0])
 
         # Reassign index and column names
         if objs[0]._data.multiindex: