diff --git a/modin/core/execution/ray/implementations/cudf_on_ray/partitioning/partition_manager.py b/modin/core/execution/ray/implementations/cudf_on_ray/partitioning/partition_manager.py
index 038ff0c96c8..3a3cbc6d167 100644
--- a/modin/core/execution/ray/implementations/cudf_on_ray/partitioning/partition_manager.py
+++ b/modin/core/execution/ray/implementations/cudf_on_ray/partitioning/partition_manager.py
@@ -125,7 +125,7 @@ def from_pandas(cls, df, return_dims=False):
         num_splits = GpuCount.get()
         put_func = cls._partition_class.put
         # For now, we default to row partitioning
-        pandas_dfs = split_result_of_axis_func_pandas(0, num_splits, df)
+        pandas_dfs = list(split_result_of_axis_func_pandas(0, num_splits, df))
         keys = [
             put_func(cls._get_gpu_managers()[i], pandas_dfs[i])
             for i in range(num_splits)
diff --git a/modin/core/execution/ray/implementations/pandas_on_ray/partitioning/virtual_partition.py b/modin/core/execution/ray/implementations/pandas_on_ray/partitioning/virtual_partition.py
index 12036abb76f..e04e6e29f1e 100644
--- a/modin/core/execution/ray/implementations/pandas_on_ray/partitioning/virtual_partition.py
+++ b/modin/core/execution/ray/implementations/pandas_on_ray/partitioning/virtual_partition.py
@@ -324,13 +324,12 @@ def _deploy_ray_func(
     if not extract_metadata:
         for item in result:
             yield item
-        return
-
-    ip = get_node_ip_address()
-    for r in result:
-        if isinstance(r, pandas.DataFrame):
-            for item in [r, len(r), len(r.columns), ip]:
-                yield item
-        else:
-            for item in [r, None, None, ip]:
-                yield item
+    else:
+        ip = get_node_ip_address()
+        for r in result:
+            if isinstance(r, pandas.DataFrame):
+                for item in [r, len(r), len(r.columns), ip]:
+                    yield item
+            else:
+                for item in [r, None, None, ip]:
+                    yield item
diff --git a/modin/core/storage_formats/cudf/parser.py b/modin/core/storage_formats/cudf/parser.py
index ac206cfacb8..c0dcf207451 100644
--- a/modin/core/storage_formats/cudf/parser.py
+++ b/modin/core/storage_formats/cudf/parser.py
@@ -39,9 +39,7 @@ def _split_result_for_readers(axis, num_splits, df):  # pragma: no cover
     Returns:
         A list of pandas DataFrames.
     """
-    splits = split_result_of_axis_func_pandas(axis, num_splits, df)
-    if not isinstance(splits, list):
-        splits = [splits]
+    splits = list(split_result_of_axis_func_pandas(axis, num_splits, df))
     return splits
 
 
diff --git a/modin/core/storage_formats/pandas/parsers.py b/modin/core/storage_formats/pandas/parsers.py
index f76ef71d128..8f5b6087f16 100644
--- a/modin/core/storage_formats/pandas/parsers.py
+++ b/modin/core/storage_formats/pandas/parsers.py
@@ -113,9 +113,7 @@ def _split_result_for_readers(axis, num_splits, df):  # pragma: no cover
     list
         A list of pandas DataFrames.
     """
-    splits = split_result_of_axis_func_pandas(axis, num_splits, df)
-    if not isinstance(splits, list):
-        splits = [splits]
+    splits = list(split_result_of_axis_func_pandas(axis, num_splits, df))
     return splits
 
 
diff --git a/modin/core/storage_formats/pandas/utils.py b/modin/core/storage_formats/pandas/utils.py
index 553f8b78f1b..1cc38e8fbd9 100644
--- a/modin/core/storage_formats/pandas/utils.py
+++ b/modin/core/storage_formats/pandas/utils.py
@@ -81,30 +81,29 @@ def split_result_of_axis_func_pandas(axis, num_splits, result, length_list=None)
     """
     if num_splits == 1:
         yield result
-        return
-
-    if length_list is None:
-        length_list = get_length_list(result.shape[axis], num_splits)
-    # Inserting the first "zero" to properly compute cumsum indexing slices
-    length_list = np.insert(length_list, obj=0, values=[0])
-
-    sums = np.cumsum(length_list)
-    axis = 0 if isinstance(result, pandas.Series) else axis
-
-    for i in range(len(sums) - 1):
-        # We do this to restore block partitioning
-        if axis == 0:
-            chunk = result.iloc[sums[i] : sums[i + 1]]
-        else:
-            chunk = result.iloc[:, sums[i] : sums[i + 1]]
-
-        # Sliced MultiIndex still stores all encoded values of the original index, explicitly
-        # asking it to drop unused values in order to save memory.
-        if isinstance(chunk.axes[axis], pandas.MultiIndex):
-            chunk = chunk.set_axis(
-                chunk.axes[axis].remove_unused_levels(), axis=axis, copy=False
-            )
-        yield chunk
+    else:
+        if length_list is None:
+            length_list = get_length_list(result.shape[axis], num_splits)
+        # Inserting the first "zero" to properly compute cumsum indexing slices
+        length_list = np.insert(length_list, obj=0, values=[0])
+
+        sums = np.cumsum(length_list)
+        axis = 0 if isinstance(result, pandas.Series) else axis
+
+        for i in range(len(sums) - 1):
+            # We do this to restore block partitioning
+            if axis == 0:
+                chunk = result.iloc[sums[i] : sums[i + 1]]
+            else:
+                chunk = result.iloc[:, sums[i] : sums[i + 1]]
+
+            # Sliced MultiIndex still stores all encoded values of the original index, explicitly
+            # asking it to drop unused values in order to save memory.
+            if isinstance(chunk.axes[axis], pandas.MultiIndex):
+                chunk = chunk.set_axis(
+                    chunk.axes[axis].remove_unused_levels(), axis=axis, copy=False
+                )
+            yield chunk
 
 
 def get_length_list(axis_len: int, num_splits: int) -> list: