diff --git a/analysis/data/loaders.py b/analysis/data/loaders.py
index 702561ca46aab3310bd90fa7eba1fd20d7db613f..32e428e7a2a076d87cd0734af34983739fa0654c 100644
--- a/analysis/data/loaders.py
+++ b/analysis/data/loaders.py
@@ -119,8 +119,7 @@ def _get_root_from_dataframe(frame, kwargs):
     # Variables
     var_list = list(frame.columns)
     # Raise an error if some weights are not loaded.
-    if not set(weights_to_normalize+weights_not_to_normalize).issubset(set(var_list)):
-        print
+    if var_list and not set(weights_to_normalize+weights_not_to_normalize).issubset(set(var_list)):
         raise ValueError("Missing weights in the list of variables read from input file.")
     acc_var = ''
     # Acceptance specified
diff --git a/tests/test_data.py b/tests/test_data.py
index febc18c0c04442f25c750f8a54e7b7a229ca6469..08ef32ab11dc41efa5e7c1bd679df0883736d352 100644
--- a/tests/test_data.py
+++ b/tests/test_data.py
@@ -47,7 +47,7 @@ def test_load_with_weights(pandas_weights):
                          'tree': 'ds',
                          'output-format': 'root',
                          'input-type': 'pandas',
-                         'weights': 'half'})
+                         'weights-to-normalize': 'half'})
         assert data.isWeighted()
         assert data.sumEntries() == 1000.0  # Correct normalization
         data.get(0)
@@ -58,32 +58,18 @@ def test_load_with_weights(pandas_weights):
                          'tree': 'ds',
                          'output-format': 'root',
                          'input-type': 'pandas',
-                         'weights': ['half', 'quarter'],
-                         'weight_var': 'weight'})
+                         'weights-to-normalize': ['half', 'quarter']})
         assert data.isWeighted()
         assert data.sumEntries() == 1000.0  # Correct normalization
         data.get(0)
         assert data.weight() == 1.0  # Since all weights are equal
-        # This should fail
-        try:
-            data = get_data({'name': 'Test',
-                             'source': file_name,
-                             'tree': 'ds',
-                             'output-format': 'root',
-                             'input-type': 'pandas',
-                             'weights': ['half', 'quarter']})
-        except KeyError:
-            pass
-        else:
-            assert False
         # And now product of the three to make sure it's not chance
         data = get_data({'name': 'Test',
                          'source': file_name,
                          'tree': 'ds',
                          'output-format': 'root',
                          'input-type': 'pandas',
-                         'weights': ['half', 'quarter', 'asym'],
-                         'weight_var': 'weight'})
+                         'weights-to-normalize': ['half', 'quarter', 'asym']})
         if not data.isWeighted():
             return False
         # Correct normalization