Reverts

Author: rhshadrach

pandas/core/missing.py

@@ -314,19 +314,16 @@ def get_interp_index(method, index: Index) -> Index:
         # prior default
         from pandas import Index
 
-        index = Index(range(len(index)))
-
-        # if isinstance(index.dtype, DatetimeTZDtype) or lib.is_np_dtype(
-        #     index.dtype, "mM"
-        # ):
-        #     # Convert datetime-like indexes to int64
-        #     index = Index(index.view("i8"))
-        #
-        # elif not is_numeric_dtype(index.dtype):
-        #     # We keep behavior consistent with prior versions of pandas for
-        #     # non-numeric, non-datetime indexes
-        #     index = Index(range(len(index)))
-
+        if isinstance(index.dtype, DatetimeTZDtype) or lib.is_np_dtype(
+            index.dtype, "mM"
+        ):
+            # Convert datetime-like indexes to int64
+            index = Index(index.view("i8"))
+
+        elif not is_numeric_dtype(index.dtype):
+            # We keep behavior consistent with prior versions of pandas for
+            # non-numeric, non-datetime indexes
+            index = Index(range(len(index)))
     else:
         methods = {"index", "values", "nearest", "time"}
         is_numeric_or_datetime = (

pandas/tests/resample/test_time_grouper.py

@@ -412,15 +412,8 @@ def test_groupby_resample_interpolate_with_apply_syntax_off_grid(groupy_test_df)
     with resampling that results in missing anchor points when interpolating.
     See GH#21351."""
     # GH#21351
-    print(groupy_test_df)
-
-    def foo(x):
-        print(x)
-        return x.resample("265h").interpolate(method="linear")
-
     result = groupy_test_df.groupby("volume").apply(
-        # lambda x: x.resample("265h").interpolate(method="linear")
-        foo
+        lambda x: x.resample("265h").interpolate(method="linear")
     )
 
     volume = [50, 50, 60]