diff --git a/etl/epc/DataProcessor.py b/etl/epc/DataProcessor.py
index 801a9456..4987a23e 100644
--- a/etl/epc/DataProcessor.py
+++ b/etl/epc/DataProcessor.py
@@ -135,6 +135,7 @@ class EPCDataProcessor:
         self.fill_invalid_constituency_fields(ignore_step=ignore_step)
 
         self.make_cleaning_averages(ignore_step=ignore_step)
+        self.add_local_authority_to_cleaning_average(ignore_step=ignore_step)
 
         # TODO: check if this has impact on training dataset
         cleaned_data = self.apply_averages_cleaning(
@@ -152,7 +153,6 @@ class EPCDataProcessor:
         
         self.data = self.data if cleaned_data is None else cleaned_data
 
-        self.add_local_authority_to_cleaning_average(ignore_step=ignore_step)
         self.cast_cleaning_averages_columns_to_lower(ignore_step=ignore_step)
         self.cast_data_columns_to_lower()
 
diff --git a/etl/epc/Pipeline.py b/etl/epc/Pipeline.py
index ea484e56..168f7f71 100644
--- a/etl/epc/Pipeline.py
+++ b/etl/epc/Pipeline.py
@@ -123,7 +123,7 @@ class EPCPipeline:
 
         data = self.epc_data_processor.data
 
-        
+
 
         epc_records = [EPCRecord(**x, run_mode="newdata") for x in data.to_dict(orient='records')]
         
@@ -137,23 +137,23 @@ class EPCPipeline:
         for directory in tqdm(self.directories):
             self.process_directory(directory)
 
-        # save_dataframe_to_s3_parquet(
-        #     df=self.compiled_dataset,
-        #     bucket_name=self.epc_bucket_name,
-        #     file_key=self.epc_compiled_dataset_key,
-        # )
+        save_dataframe_to_s3_parquet(
+            df=self.compiled_dataset,
+            bucket_name=self.epc_bucket_name,
+            file_key=self.epc_compiled_dataset_key,
+        )
 
-        # save_dataframe_to_s3_parquet(
-        #     df=pd.concat(self.compiled_all_equal_rows),
-        #     bucket_name=self.epc_bucket_name,
-        #     file_key=self.epc_all_equal_rows_key,
-        # )
+        save_dataframe_to_s3_parquet(
+            df=pd.DataFrame(self.compiled_all_equal_rows),
+            bucket_name=self.epc_bucket_name,
+            file_key=self.epc_all_equal_rows_key,
+        )
 
-        # save_dataframe_to_s3_parquet(
-        #     df=pd.concat(self.compiled_cleaning_averages),
-        #     bucket_name=self.epc_bucket_name,
-        #     file_key=self.epc_cleaning_dataset_key,
-        # ) 
+        save_dataframe_to_s3_parquet(
+            df=pd.concat(self.compiled_cleaning_averages),
+            bucket_name=self.epc_bucket_name,
+            file_key=self.epc_cleaning_dataset_key,
+        ) 
     
     def process_directory(self, directory: Path):
         """
diff --git a/etl/epc/property_change_app.py b/etl/epc/property_change_app.py
index 3dc6e39b..5486ee99 100644
--- a/etl/epc/property_change_app.py
+++ b/etl/epc/property_change_app.py
@@ -18,16 +18,16 @@ def main():
     epc_pipeline.run()
 
     # For testing
-    dataset_df = epc_pipeline.compiled_dataset
-    dataset_df.to_parquet("refactor_datasets/dataset.parquet")
-    pd.DataFrame(epc_pipeline.compiled_all_equal_rows).to_parquet("refactor_datasets/all_equal_rows.parquet")
-    pd.concat(epc_pipeline.compiled_cleaning_averages).to_parquet("refactor_datasets/cleaning_averages.parquet")
+    # dataset_df = epc_pipeline.compiled_dataset
+    # dataset_df.to_parquet("refactor_datasets/dataset.parquet")
+    # pd.DataFrame(epc_pipeline.compiled_all_equal_rows).to_parquet("refactor_datasets/all_equal_rows.parquet")
+    # pd.concat(epc_pipeline.compiled_cleaning_averages).to_parquet("refactor_datasets/cleaning_averages.parquet")
 
-    from utils.s3 import read_dataframe_from_s3_parquet
-    dataset = read_dataframe_from_s3_parquet(
-        bucket_name="retrofit-data-dev",
-        file_key="sap_change_model/dataset_test.parquet",
-    )
+    # from utils.s3 import read_dataframe_from_s3_parquet
+    # dataset = read_dataframe_from_s3_parquet(
+    #     bucket_name="retrofit-data-dev",
+    #     file_key="sap_change_model/dataset_test.parquet",
+    # )
 
 
 if __name__ == "__main__":