TimedeltaIndex constructor raises an AttributeError. (#9884)

Fixes: #9829

This PR fixes `TimedeltaIndex` constructor invocation by handling `NaT` values replacement with `nulls`.

Authors:
  - Sheilah Kirui (https://github.com/skirui-source)

Approvers:
  - Bradley Dice (https://github.com/bdice)
  - GALI PREM SAGAR (https://github.com/galipremsagar)

URL: #9884

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

@@ -1652,6 +1652,27 @@ def build_struct_column(
     return cast("cudf.core.column.StructColumn", result)
 
 
+def _make_copy_replacing_NaT_with_null(column):
+    """Return a copy with NaT values replaced with nulls."""
+    if np.issubdtype(column.dtype, np.timedelta64):
+        na_value = np.timedelta64("NaT", column.time_unit)
+    elif np.issubdtype(column.dtype, np.datetime64):
+        na_value = np.datetime64("NaT", column.time_unit)
+    else:
+        raise ValueError("This type does not support replacing NaT with null.")
+
+    null = column_empty_like(column, masked=True, newsize=1)
+    out_col = cudf._lib.replace.replace(
+        column,
+        build_column(
+            Buffer(np.array([na_value], dtype=column.dtype).view("|u1")),
+            dtype=column.dtype,
+        ),
+        null,
+    )
+    return out_col
+
+
 def as_column(
     arbitrary: Any,
     nan_as_null: bool = None,
@@ -1753,9 +1774,7 @@ def as_column(
                 col = col.set_mask(mask)
         elif np.issubdtype(col.dtype, np.datetime64):
             if nan_as_null or (mask is None and nan_as_null is None):
-                # Ignore typing error since this method is only defined for
-                # DatetimeColumn, not the ColumnBase class.
-                col = col._make_copy_with_na_as_null()  # type: ignore
+                col = _make_copy_replacing_NaT_with_null(col)
         return col
 
     elif isinstance(arbitrary, (pa.Array, pa.ChunkedArray)):
@@ -1886,7 +1905,7 @@ def as_column(
             mask = None
             if nan_as_null is None or nan_as_null is True:
                 data = build_column(buffer, dtype=arbitrary.dtype)
-                data = data._make_copy_with_na_as_null()
+                data = _make_copy_replacing_NaT_with_null(data)
                 mask = data.mask
 
             data = cudf.core.column.datetime.DatetimeColumn(
@@ -1904,7 +1923,7 @@ def as_column(
             mask = None
             if nan_as_null is None or nan_as_null is True:
                 data = build_column(buffer, dtype=arbitrary.dtype)
-                data = data._make_copy_with_na_as_null()
+                data = _make_copy_replacing_NaT_with_null(data)
                 mask = data.mask
 
             data = cudf.core.column.timedelta.TimeDeltaColumn(

python/cudf/cudf/core/column/datetime.py

@@ -20,13 +20,7 @@
 from cudf.api.types import is_scalar
 from cudf.core._compat import PANDAS_GE_120
 from cudf.core.buffer import Buffer
-from cudf.core.column import (
-    ColumnBase,
-    as_column,
-    column,
-    column_empty_like,
-    string,
-)
+from cudf.core.column import ColumnBase, as_column, column, string
 from cudf.utils.utils import _fillna_natwise
 
 if PANDAS_GE_120:
@@ -493,20 +487,6 @@ def can_cast_safely(self, to_dtype: Dtype) -> bool:
         else:
             return False
 
-    def _make_copy_with_na_as_null(self):
-        """Return a copy with NaN values replaced with nulls."""
-        null = column_empty_like(self, masked=True, newsize=1)
-        na_value = np.datetime64("nat", self.time_unit)
-        out_col = cudf._lib.replace.replace(
-            self,
-            column.build_column(
-                Buffer(np.array([na_value], dtype=self.dtype).view("|u1")),
-                dtype=self.dtype,
-            ),
-            null,
-        )
-        return out_col
-
 
 def binop_offset(lhs, rhs, op):
     if rhs._is_no_op:

python/cudf/cudf/tests/test_timedelta.py

@@ -1406,3 +1406,13 @@ def test_error_values():
         match="TimeDelta Arrays is not yet implemented in cudf",
     ):
         s.values
+
+
+@pytest.mark.parametrize("dtype", utils.TIMEDELTA_TYPES)
+@pytest.mark.parametrize("name", [None, "delta-index"])
+def test_create_TimedeltaIndex(dtype, name):
+    gdi = cudf.TimedeltaIndex(
+        [1132223, 2023232, 342234324, 4234324], dtype=dtype, name=name
+    )
+    pdi = gdi.to_pandas()
+    assert_eq(pdi, gdi)