Fixup docstring

Author: rhshadrach

pandas/core/missing.py

@@ -314,16 +314,19 @@ def get_interp_index(method, index: Index) -> Index:
         # prior default
         from pandas import 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)))
+        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/io/pytables.py

@@ -377,18 +377,18 @@ def read_hdf(
     object
         The selected object. Return type depends on the object stored.
 
+    See Also
+    --------
+    DataFrame.to_hdf : Write a HDF file from a DataFrame.
+    HDFStore : Low-level access to HDF files.
+
     Notes
     -----
     When ``errors="surrogatepass"``, ``pd.options.future.infer_string`` is true,
     and PyArrow is installed, if a UTF-16 surrogate is encountered when decoding
     to UTF-8, the resulting dtype will be
     ``pd.StringDtype(storage="python", na_value=np.nan)``.
 
-    See Also
-    --------
-    DataFrame.to_hdf : Write a HDF file from a DataFrame.
-    HDFStore : Low-level access to HDF files.
-
     Examples
     --------
     >>> df = pd.DataFrame([[1, 1.0, "a"]], columns=["x", "y", "z"])  # doctest: +SKIP

pandas/tests/resample/test_time_grouper.py

@@ -412,8 +412,15 @@ 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")
+        # lambda x: x.resample("265h").interpolate(method="linear")
+        foo
     )
 
     volume = [50, 50, 60]