address review

python/cudf/cudf/core/frame.py

@@ -1490,28 +1490,27 @@ def interpolate(
             )
 
         data = self
-        columns = {}
 
         if not isinstance(data._index, cudf.RangeIndex):
             perm_sort = data._index.argsort()
             data = data._gather(perm_sort)
 
         interpolator = cudf.core.algorithms.get_column_interpolator(method)
+        columns = {}
         for colname, col in data._data.items():
             if col.nullable:
                 col = col.astype("float64").fillna(np.nan)
 
             # Interpolation methods may or may not need the index
-            result = interpolator(col, index=data._index)
-            columns[colname] = result
-
-        result = self.__class__(ColumnAccessor(columns), index=data._index)
+            columns[colname] = interpolator(col, index=data._index)
 
-        if not isinstance(data._index, cudf.RangeIndex):
-            # that which was once sorted, now is not
-            result = result._gather(perm_sort.argsort())
+        result = self._from_data(columns, index=data._index)
 
-        return result
+        return (
+            result
+            if isinstance(data._index, cudf.RangeIndex)
+            else result._gather(perm_sort.argsort())
+        )
 
     def _quantiles(
         self,

python/cudf/cudf/tests/test_interpolate.py

@@ -16,7 +16,10 @@
 @pytest.mark.parametrize("method", ["linear"])
 @pytest.mark.parametrize("axis", [0])
 def test_interpolate_dataframe(data, method, axis):
-    # doesn't seem to work with NAs just yet
+    # Pandas interpolate methods do not seem to work
+    # with nullable dtypes yet, so this method treats
+    # NAs as NaNs
+    # https://github.com/pandas-dev/pandas/issues/40252
     gdf = cudf.DataFrame(data)
     pdf = gdf.to_pandas()