diff --git a/tests/units/utilities/test_dataframe_functions.py b/tests/units/utilities/test_dataframe_functions.py
index f498ee032..8181a976e 100644
--- a/tests/units/utilities/test_dataframe_functions.py
+++ b/tests/units/utilities/test_dataframe_functions.py
@@ -138,6 +138,15 @@ def test_with_wrong_input(self):
         self.assertRaises(ValueError, dataframe_functions._normalize_input_to_internal_representation, test_df,
                           None, None, None, "value")
 
+        test_df = pd.DataFrame([{"id": 0}])
+        self.assertRaises(ValueError, dataframe_functions._normalize_input_to_internal_representation, test_df,
+                          "id", None, None, None)
+
+        test_df = pd.DataFrame([{"id": 0, "sort": 0}])
+        self.assertRaises(ValueError, dataframe_functions._normalize_input_to_internal_representation, test_df,
+                          "id", "sort", None, None)
+
+
     def test_wide_dataframe_order_preserved_with_sort_column(self):
         """ verifies that the order of the sort column from a wide time series container is preserved
         """
diff --git a/tsfresh/utilities/dataframe_functions.py b/tsfresh/utilities/dataframe_functions.py
index 381cc7177..8d9a59cbc 100644
--- a/tsfresh/utilities/dataframe_functions.py
+++ b/tsfresh/utilities/dataframe_functions.py
@@ -321,12 +321,14 @@ def _normalize_input_to_internal_representation(timeseries_container, column_id,
         column_kind = "_variables"
         column_value = "_values"
 
+        if not set(timeseries_container.columns) - {column_id}:
+            raise ValueError("There is no column with values in your data!")
+
         timeseries_container.index.name = 'index'
         timeseries_container = pd.melt(timeseries_container.reset_index(),
                                        id_vars=['index', column_id],
                                        value_name=column_value, var_name=column_kind)
         timeseries_container = timeseries_container.set_index('index')
-
         timeseries_container[column_sort] = np.tile(sort, (len(timeseries_container) // len(sort)))
 
     # Check kind column