diff --git a/pandas/_libs/reduction.pyx b/pandas/_libs/reduction.pyx
index 43d253f632f0f..b27072aa66708 100644
--- a/pandas/_libs/reduction.pyx
+++ b/pandas/_libs/reduction.pyx
@@ -309,8 +309,7 @@ cdef class SeriesGrouper(_BaseGrouper):
     def __init__(self, object series, object f, object labels,
                  Py_ssize_t ngroups, object dummy):
 
-        # in practice we always pass either obj[:0] or the
-        #  safer obj._get_values(slice(None, 0))
+        # in practice we always pass obj.iloc[:0] or equivalent
         assert dummy is not None
 
         if len(series) == 0:
diff --git a/pandas/core/groupby/ops.py b/pandas/core/groupby/ops.py
index 761353ca5a6ca..4e593ce543ea6 100644
--- a/pandas/core/groupby/ops.py
+++ b/pandas/core/groupby/ops.py
@@ -658,7 +658,7 @@ def _aggregate_series_fast(self, obj: Series, func):
         group_index, _, ngroups = self.group_info
 
         # avoids object / Series creation overhead
-        dummy = obj._get_values(slice(None, 0))
+        dummy = obj.iloc[:0]
         indexer = get_group_index_sorter(group_index, ngroups)
         obj = obj.take(indexer)
         group_index = algorithms.take_nd(group_index, indexer, allow_fill=False)
@@ -780,7 +780,11 @@ def get_iterator(self, data: FrameOrSeries, axis: int = 0):
         Generator yielding sequence of (name, subsetted object)
         for each group
         """
-        slicer = lambda start, edge: data._slice(slice(start, edge), axis=axis)
+        if axis == 0:
+            slicer = lambda start, edge: data.iloc[start:edge]
+        else:
+            slicer = lambda start, edge: data.iloc[:, start:edge]
+
         length = len(data.axes[axis])
 
         start = 0
@@ -919,7 +923,7 @@ def _chop(self, sdata, slice_obj: slice) -> NDFrame:
 
 class SeriesSplitter(DataSplitter):
     def _chop(self, sdata: Series, slice_obj: slice) -> Series:
-        return sdata._get_values(slice_obj)
+        return sdata.iloc[slice_obj]
 
 
 class FrameSplitter(DataSplitter):
@@ -934,7 +938,7 @@ def _chop(self, sdata: DataFrame, slice_obj: slice) -> DataFrame:
         if self.axis == 0:
             return sdata.iloc[slice_obj]
         else:
-            return sdata._slice(slice_obj, axis=1)
+            return sdata.iloc[:, slice_obj]
 
 
 def get_splitter(data: FrameOrSeries, *args, **kwargs) -> DataSplitter:
diff --git a/pandas/tests/groupby/test_bin_groupby.py b/pandas/tests/groupby/test_bin_groupby.py
index ad71f73e80e64..ff74d374e5e3f 100644
--- a/pandas/tests/groupby/test_bin_groupby.py
+++ b/pandas/tests/groupby/test_bin_groupby.py
@@ -11,7 +11,7 @@
 
 def test_series_grouper():
     obj = Series(np.random.randn(10))
-    dummy = obj[:0]
+    dummy = obj.iloc[:0]
 
     labels = np.array([-1, -1, -1, 0, 0, 0, 1, 1, 1, 1], dtype=np.int64)
 
@@ -28,7 +28,7 @@ def test_series_grouper():
 def test_series_grouper_requires_nonempty_raises():
     # GH#29500
     obj = Series(np.random.randn(10))
-    dummy = obj[:0]
+    dummy = obj.iloc[:0]
     labels = np.array([-1, -1, -1, 0, 0, 0, 1, 1, 1, 1], dtype=np.int64)
 
     with pytest.raises(ValueError, match="SeriesGrouper requires non-empty `series`"):