diff --git a/tests/pandas/test_pandas.py b/tests/pandas/test_pandas.py
index bb2d5f713..78af798aa 100644
--- a/tests/pandas/test_pandas.py
+++ b/tests/pandas/test_pandas.py
@@ -24,6 +24,7 @@ def generate_pandas_dataframe(
     n_features: int = 1,
     index_name: Optional[str] = None,
     indexes: Optional[Union[int, List]] = None,
+    str_values: Optional[List[str]] = None,
     index_position: int = 0,
     include_nan: bool = True,
     float_min: float = -10.0,
@@ -46,6 +47,7 @@ def generate_pandas_dataframe(
         index_name (Optional[str]): The index's name. Default to None ("index").
         indexes (Optional[Union[int, List]]): Custom indexes to consider. Default to None (5 rows,
             indexed from 1 to 5).
+        str_values (Optional[List[str]]): The list of string values to consider. Default to None.
         index_position (int): The index's column position in the data-frame. Default to 0.
         include_nan (bool): If NaN values should be put in the data-frame. If True, they are
             inserted in the first row. Default to True.
@@ -75,6 +77,10 @@ def generate_pandas_dataframe(
     if isinstance(indexes, int):
         indexes = list(range(1, indexes + 1))
 
+    assert str_values is None or len(str_values) == len(
+        indexes
+    ), "Parameter 'str_values' must either be None or a list of length equal to 'indexes'."
+
     if index_name is None:
         index_name = "index"
 
@@ -102,11 +108,16 @@ def generate_pandas_dataframe(
 
     # Add a column with string values (including NaN or not)
     if dtype in ["str", "mixed"]:
-        str_values = ["apple", "orange", "watermelon", "cherry", "banana"]
+        str_values_default = ["apple", "orange", "watermelon", "cherry", "banana"]
 
         for i in range(1, n_features + 1):
             column_name = f"{feat_name}_str_{i}"
-            columns[column_name] = list(numpy.random.choice(str_values, size=(len(indexes),)))
+            rand_str_values = (
+                list(numpy.random.choice(str_values_default, size=(len(indexes),)))
+                if str_values is None
+                else str_values
+            )
+            columns[column_name] = rand_str_values
 
             if include_nan:
                 columns[column_name][0] = numpy.nan
@@ -694,8 +705,17 @@ def check_invalid_schema_values():
 
         client = ClientEngine(keys_path=keys_path)
 
+    # Fix the string values to consider in order to avoid flaky tests (one of the checks requires to
+    # have a data-frame with at least 2 unique string values)
+    str_values = ["apple", "orange", "watermelon", "cherry", "banana"]
+
     pandas_df = generate_pandas_dataframe(
-        feat_name=feat_name, index_name=selected_column, float_min=float_min, float_max=float_max
+        feat_name=feat_name,
+        index_name=selected_column,
+        indexes=len(str_values),
+        str_values=str_values,
+        float_min=float_min,
+        float_max=float_max,
     )
 
     schema_int_column = {f"{feat_name}_int_1": {None: None}}