diff --git a/src/g5505_file_reader.py b/src/g5505_file_reader.py
index a00a817..e237eb2 100644
--- a/src/g5505_file_reader.py
+++ b/src/g5505_file_reader.py
@@ -165,7 +165,7 @@ def read_txt_files_as_dict(filename : str , work_with_copy : bool = True ):
             if table_header in line.decode(file_encoding):   
                 list_of_substrings = line.decode(file_encoding).split(separator)             
                 data_start = True  
-                column_names = [str(i)+'_'+name for i, name in enumerate(list_of_substrings)]
+                column_names = [str(i)+'_'+name.strip() for i, name in enumerate(list_of_substrings)]
                 #column_names = []
                 #for i, name in enumerate(list_of_substrings):
                 #    column_names.append(str(i)+'_'+name) 
@@ -270,29 +270,19 @@ def read_txt_files_as_dict(filename : str , work_with_copy : bool = True ):
             except ValueError as err:
                 print(err)
 
-            #dataset = {}
-            #numerical_variables= [item.encode("utf-8") for item in numerical_variables]
-            #dataset['name'] = 'numerical_variable_names'
-            #dataset['data'] = np.array(numerical_variables).reshape((1,len(numerical_variables)))
-            #dataset['shape'] = dataset['data'].shape
-            #dataset['dtype'] = type(dataset['data'])
-            #file_dict['datasets'].append(dataset)            
-        
+       
         if categorical_variables:
             dataset = {}
             dataset['name'] = 'table_categorical_variables'
             dataset['data'] = dataframe_to_np_structured_array(df_categorical_attrs) #df_categorical_attrs.loc[:,categorical_variables].to_numpy()
             dataset['shape'] = dataset['data'].shape
             dataset['dtype'] = type(dataset['data'])
-            file_dict['datasets'].append(dataset)    
+            if 'timestamps' in categorical_variables:
+                dataset['attributes'] = {'timestamps': metadata.parse_attribute({'unit':'YYYY-MM-DD HH:MM:SS.ffffff'})}
+            file_dict['datasets'].append(dataset) 
+ 
+
 
-        #    dataset = {}
-        #    categorical_variables = [item.encode("utf-8") for item in categorical_variables]
-        #    dataset['name'] = 'categorial_variable_names'
-        #    dataset['data'] = np.array(categorical_variables).reshape((1,len(categorical_variables)))
-        #    dataset['shape'] = dataset['data'].shape
-        #    dataset['dtype'] = type(dataset['data'])
-        #    file_dict['datasets'].append(dataset)    
 
     except:
         return {}