diff --git a/src/haddock/libs/libinteractive.py b/src/haddock/libs/libinteractive.py
index ac6760d7d..1f9c3f860 100644
--- a/src/haddock/libs/libinteractive.py
+++ b/src/haddock/libs/libinteractive.py
@@ -9,6 +9,7 @@
 from haddock.libs.libplots import read_capri_table
 from haddock.modules import get_module_steps_folders
 
+
 def handle_ss_file(
         df_ss: pd.DataFrame,
         ) -> tuple[pd.DataFrame, dict]:
@@ -35,16 +36,17 @@ def handle_ss_file(
     df_ss_grouped = df_ss.groupby("cluster_id")
     # calculate the mean and standard deviation of the first 4 elements
     # of each group
-    new_values = np.zeros((len(df_ss_grouped), 3))
+    new_values = []
     # loop over df_ss_grouped with enumerate
-    for i, clt_id in enumerate(df_ss_grouped):
+    for clt_id in df_ss_grouped:
         ave_score = np.mean(clt_id[1]["score"].iloc[:4])
         std_score = np.std(clt_id[1]["score"].iloc[:4])
-        new_values[i] = [ave_score, std_score, clt_id[0]]
+        new_values.append([ave_score, std_score, clt_id[0]])
     # get the index that sorts the array by the first column
-    clt_ranks = np.argsort(new_values[:, 0])
+    new_values_arr = np.array(new_values)
+    clt_ranks = np.argsort(new_values_arr[:, 0])
     # the ranked clusters are the third column of the new_values array
-    clt_sorted = new_values[clt_ranks, 2]
+    clt_sorted = new_values_arr[clt_ranks, 2]
     clt_ranks_dict = {clt_sorted[i]: i + 1 for i in range(len(clt_sorted))}
     # adjust clustering values if there are clusters
     if list(np.unique(df_ss["cluster_id"])) != ["-"]:
diff --git a/tests/test_libinteractive.py b/tests/test_libinteractive.py
index a0a6cf4bb..085036735 100644
--- a/tests/test_libinteractive.py
+++ b/tests/test_libinteractive.py
@@ -1,6 +1,6 @@
 import tempfile
 from haddock.libs.libplots import read_capri_table 
-from haddock.libs.libinteractive import handle_ss_file, rewrite_capri_tables, look_for_capri, handle_clt_file
+from haddock.libs.libinteractive import handle_ss_file, look_for_capri, handle_clt_file
 import pytest
 from pathlib import Path
 import numpy as np
@@ -26,7 +26,18 @@ def test_handle_ss_file(example_capri_df_ss):
     assert clt_ranks_dict[16] == 1
     assert clt_ranks_dict[1] == 2
     assert clt_ranks_dict[34] == 39
-    
+
+
+def test_handle_ss_file_unclustered(example_capri_df_ss):
+    """Test handle_ss_file function with unclustered data."""
+    df_ss = example_capri_df_ss.copy()
+    df_ss['cluster_id'] = '-'
+    df_ss['cluster_ranking'] = "-"
+    df_ss['model-cluster_ranking'] = "-"
+    df_ss, clt_ranks_dict = handle_ss_file(df_ss)
+    assert clt_ranks_dict == {"-": 1}
+    assert df_ss['cluster_ranking'].values[0] == "-"
+
 
 def test_handle_clt_file(example_capri_df_ss):
     """Test handle_clt_file function."""