diff --git a/etl/epc/DataProcessor.py b/etl/epc/DataProcessor.py
index 0587fdbe..8adac8df 100644
--- a/etl/epc/DataProcessor.py
+++ b/etl/epc/DataProcessor.py
@@ -5,6 +5,9 @@ from BaseUtility import Definitions
 from etl.epc.settings import (
     DATA_PROCESSOR_SETTINGS,
     EARLIEST_EPC_DATE,
+    IGNORED_TRANSACTION_TYPES,
+    IGNORED_FLOOR_LEVELS,
+    IGNORED_PROPERTY_TYPES,
     FULLY_GLAZED_DESCRIPTIONS,
     AVERAGE_FIXED_FEATURES,
     BUILT_FORM_REMAP,
@@ -416,9 +419,9 @@ class DataProcessor:
 
         self.data = self.data[~pd.isnull(self.data["UPRN"])]
         self.data = self.data[self.data["LODGEMENT_DATE"] >= EARLIEST_EPC_DATE]
-        self.data = self.data[self.data["TRANSACTION_TYPE"] != "new dwelling"]
+        self.data = self.data[self.data["TRANSACTION_TYPE"] != IGNORED_TRANSACTION_TYPES]
         self.data = self.data[
-            ~self.data["FLOOR_LEVEL"].isin(["top floor", "mid floor"])
+            ~self.data["FLOOR_LEVEL"].isin(IGNORED_FLOOR_LEVELS)
         ]
         self.data = self.data[self.data[RDSAP_RESPONSE] <= MAX_SAP_SCORE]
 
@@ -430,7 +433,7 @@ class DataProcessor:
         # Because park homes are surveyed unusually (for example, we don't have u-values to
         # look up for their different components, they need to be collected in survey and aren't reflected in
         # EPCs) we'll ignore them from the model
-        self.data = self.data[self.data["PROPERTY_TYPE"] != "Park home"]
+        self.data = self.data[self.data["PROPERTY_TYPE"] != IGNORED_PROPERTY_TYPES]
 
     def clean_multi_glaze_proportion(self) -> None:
         """
diff --git a/etl/epc/property_change_app.py b/etl/epc/property_change_app.py
index 4f49f6da..18228cb2 100644
--- a/etl/epc/property_change_app.py
+++ b/etl/epc/property_change_app.py
@@ -28,7 +28,7 @@ from recommendations.recommendation_utils import (
 DATA_DIRECTORY = Path(__file__).parent / "local_data" / "all-domestic-certificates"
 
 
-def get_cleaned():
+def get_cleaned_description_mapping():
     """
     This function will retrieve the cleaned dataset from s3 which has the cleaned
     descriptions for the epc dataset
@@ -404,7 +404,7 @@ def app():
     # Data glossary:
     # https://epc.opendatacommunities.org/docs/guidance#glossary
 
-    cleaned_lookup = get_cleaned()
+    cleaned_lookup = get_cleaned_description_mapping()
 
     # List all subdirectories
     directories = [entry for entry in DATA_DIRECTORY.iterdir() if entry.is_dir()]
diff --git a/etl/epc/requirements.txt b/etl/epc/requirements.txt
index e69de29b..9f972bde 100644
--- a/etl/epc/requirements.txt
+++ b/etl/epc/requirements.txt
@@ -0,0 +1,4 @@
+pandas==2.1.3
+tqdm==4.66.1
+msgpack==1.0.7
+boto3==1.29.6
\ No newline at end of file
diff --git a/etl/epc/settings.py b/etl/epc/settings.py
index 60c079a5..eb8eb641 100644
--- a/etl/epc/settings.py
+++ b/etl/epc/settings.py
@@ -155,6 +155,10 @@ MANDATORY_FIXED_FEATURES = ["PROPERTY_TYPE", "BUILT_FORM", "CONSTITUENCY"]
 # and Wales from 31 July 2014
 EARLIEST_EPC_DATE = "2014-08-01"
 
+IGNORED_TRANSACTION_TYPES = "new dwelling"
+IGNORED_FLOOR_LEVELS = ["top floor", "mid floor"]
+IGNORED_PROPERTY_TYPES = "Park home"
+
 RDSAP_RESPONSE = "CURRENT_ENERGY_EFFICIENCY"
 HEAT_DEMAND_RESPONSE = "ENERGY_CONSUMPTION_CURRENT"
 CARBON_RESPONSE = "CO2_EMISSIONS_CURRENT"