diff --git a/etl/epc/DataProcessor.py b/etl/epc/DataProcessor.py
index 8dbdbeb9..9fc66bab 100644
--- a/etl/epc/DataProcessor.py
+++ b/etl/epc/DataProcessor.py
@@ -217,7 +217,7 @@ class DataProcessor:
 
         if not self.is_newdata:
             # We have some odd cases with missing constituency so we fill
-            self.data = self.data.fillna({"CONSTITUENCY": df["CONSTITUENCY"].mode().values[0]})
+            self.data = self.data.fillna({"CONSTITUENCY": self.data["CONSTITUENCY"].mode().values[0]})
 
             self.cleaning_averages = self.make_cleaning_averages()
             # We apply averages cleaning to the data
diff --git a/etl/epc/property_change_app.py b/etl/epc/property_change_app.py
index a7f9db12..0f425906 100644
--- a/etl/epc/property_change_app.py
+++ b/etl/epc/property_change_app.py
@@ -438,9 +438,8 @@ def app():
         data_processor.pre_process()
         
         df = data_processor.data
-        cleaning_averages = data_processor.cleaning_averages
 
-        cleaning_dataset.append(cleaning_averages)
+        cleaning_dataset.append(data_processor.cleaning_averages)
 
         data_by_urpn = []
         for uprn, property_data in df.groupby("UPRN", observed=True):