diff --git a/monai/data/utils.py b/monai/data/utils.py
index d03dbd3234..9915e0f363 100644
--- a/monai/data/utils.py
+++ b/monai/data/utils.py
@@ -1484,7 +1484,7 @@ def convert_tables_to_dicts(
                 rows.append(i)
 
     # convert to a list of dictionaries corresponding to every row
-    data_ = df.loc[rows] if col_names is None else df.loc[rows, col_names]
+    data_ = df.iloc[rows] if col_names is None else df.iloc[rows][col_names]
     if isinstance(col_types, dict):
         # fill default values for NaN
         defaults = {k: v["default"] for k, v in col_types.items() if v is not None and v.get("default") is not None}
@@ -1500,7 +1500,7 @@ def convert_tables_to_dicts(
     if col_groups is not None:
         groups: dict[str, list] = {}
         for name, cols in col_groups.items():
-            groups[name] = df.loc[rows, cols].values
+            groups[name] = df.iloc[rows][cols].values
         # invert items of groups to every row of data
         data = [dict(d, **{k: v[i] for k, v in groups.items()}) for i, d in enumerate(data)]
 
diff --git a/tests/data/test_csv_dataset.py b/tests/data/test_csv_dataset.py
index 71be4fdd22..1fec6b2bb5 100644
--- a/tests/data/test_csv_dataset.py
+++ b/tests/data/test_csv_dataset.py
@@ -179,6 +179,13 @@ def prepare_csv_file(data, filepath):
                 },
             )
 
+            # test pre-loaded DataFrame subset
+            df = pd.read_csv(filepath1)
+            df_subset = df.iloc[[1, 3, 4]]
+            dataset = CSVDataset(src=df_subset, col_groups={"ehr": [f"ehr_{i}" for i in range(3)]})
+            self.assertEqual(len(dataset), 3)
+            np.testing.assert_allclose([round(i, 4) for i in dataset[1]["ehr"]], [3.3333, 3.2353, 3.4000])
+
             # test pre-loaded multiple DataFrames, join tables with kwargs
             dfs = [pd.read_csv(i) for i in filepaths]
             dataset = CSVDataset(src=dfs, on="subject_id")