diff --git a/superset/charts/client_processing.py b/superset/charts/client_processing.py
index 5a873ab8986df..66fb4d4b8384f 100644
--- a/superset/charts/client_processing.py
+++ b/superset/charts/client_processing.py
@@ -24,6 +24,7 @@
 In order to do that, we reproduce the post-processing in Python for these chart types.
 """
 
+import logging
 from io import StringIO
 from typing import Any, Optional, TYPE_CHECKING, Union
 
@@ -44,6 +45,9 @@
     from superset.models.sql_lab import Query
 
 
+logger = logging.getLogger(__name__)
+
+
 def get_column_key(label: tuple[str, ...], metrics: list[str]) -> tuple[Any, ...]:
     """
     Sort columns when combining metrics.
@@ -178,11 +182,20 @@ def pivot_df(  # pylint: disable=too-many-locals, too-many-arguments, too-many-s
     if rows and show_columns_total:
         # add subtotal for each group and overall total; we start from the
         # overall group, and iterate deeper into subgroups
-        groups = df.index
+        groups = df.index.copy()
         for level in range(df.index.nlevels):
             subgroups = {group[:level] for group in groups}
             for subgroup in subgroups:
-                slice_ = df.index.get_loc(subgroup)
+                try:
+                    slice_ = groups.get_loc(subgroup)
+                except Exception:  # pylint: disable=broad-except
+                    logger.exception(
+                        "Error getting location for subgroup %s from %s",
+                        subgroup,
+                        groups,
+                    )
+                    raise
+
                 subtotal = pivot_v2_aggfunc_map[aggfunc](
                     df.iloc[slice_, :].apply(pd.to_numeric, errors="coerce"), axis=0
                 )
diff --git a/tests/unit_tests/charts/test_client_processing.py b/tests/unit_tests/charts/test_client_processing.py
index e35229554b503..30905be063d2f 100644
--- a/tests/unit_tests/charts/test_client_processing.py
+++ b/tests/unit_tests/charts/test_client_processing.py
@@ -2499,3 +2499,62 @@ def test_apply_client_processing_verbose_map(session: Session):
             }
         ]
     }
+
+
+def test_pivot_multi_level_index():
+    """
+    Pivot table with multi-level indexing.
+    """
+    arrays = [
+        ["Region1", "Region1", "Region1", "Region2", "Region2", "Region2"],
+        ["State1", "State1", "State2", "State3", "State3", "State4"],
+        ["City1", "City2", "City3", "City4", "City5", "City6"],
+    ]
+    index = pd.MultiIndex.from_tuples(
+        list(zip(*arrays)),
+        names=["Region", "State", "City"],
+    )
+
+    data = {
+        "Metric1": [10, 20, 30, 40, 50, 60],
+        "Metric2": [5, 10, 15, 20, 25, 30],
+        "Metric3": [None, None, None, None, None, None],
+    }
+    df = pd.DataFrame(data, index=index)
+
+    pivoted = pivot_df(
+        df,
+        rows=["Region", "State", "City"],
+        columns=[],
+        metrics=["Metric1", "Metric2", "Metric3"],
+        aggfunc="Sum",
+        transpose_pivot=False,
+        combine_metrics=False,
+        show_rows_total=False,
+        show_columns_total=True,
+        apply_metrics_on_rows=False,
+    )
+
+    # Sort the pivoted DataFrame to ensure deterministic output
+    pivoted_sorted = pivoted.sort_index()
+
+    assert (
+        pivoted_sorted.to_markdown()
+        == """
+|                                   |   ('Metric1',) |   ('Metric2',) |   ('Metric3',) |
+|:----------------------------------|---------------:|---------------:|---------------:|
+| ('Region1', 'State1', 'City1')    |             10 |              5 |            nan |
+| ('Region1', 'State1', 'City2')    |             20 |             10 |            nan |
+| ('Region1', 'State1', 'Subtotal') |             30 |             15 |              0 |
+| ('Region1', 'State2', 'City3')    |             30 |             15 |            nan |
+| ('Region1', 'State2', 'Subtotal') |             30 |             15 |              0 |
+| ('Region1', 'Subtotal', '')       |             60 |             30 |              0 |
+| ('Region2', 'State3', 'City4')    |             40 |             20 |            nan |
+| ('Region2', 'State3', 'City5')    |             50 |             25 |            nan |
+| ('Region2', 'State3', 'Subtotal') |            100 |             50 |              0 |
+| ('Region2', 'State4', 'City6')    |             60 |             30 |            nan |
+| ('Region2', 'State4', 'Subtotal') |             40 |             20 |              0 |
+| ('Region2', 'Subtotal', '')       |            150 |             75 |              0 |
+| ('Total (Sum)', '', '')           |            210 |            105 |              0 |
+    """.strip()
+    )