tidying up code

etl/customers/stonewater/Wave 3 Preparation.py

@@ -2366,10 +2366,8 @@ def propsed_wave_3_sample():
 
     results = pd.concat(results)
 
-    results[
-        pd.isnull(results["Package Ref"]) & (results["Current EPC Band"] == "D")
-        ]["Postal Region"]
-    results[resul]
+    if (pd.isnull(results["Package Ref"]) & (~results["Current EPC Band"].isin(["A", "B", "C"]))).sum():
+        raise ValueError("Missing Package Refs")
 
     # Check if there are missings in current epc band, current sap rating or any of the survey attributes
     for c in (
@@ -2442,27 +2440,6 @@ def propsed_wave_3_sample():
     ].sum()
     print("Total needing survey:", total_needing_survey)
 
-    # Look for postcodes that have no loss
-    unselected_streets = street_summary[
-        ~street_summary["Selected"]
-    ]["Street and Region"].values
-
-    postcode_summary = results[
-        results["Street and Region"].isin(unselected_streets)
-    ].pivot_table(
-        index='Postcode',
-        columns='Confidence Tier',
-        aggfunc='size',
-        fill_value=0
-    ).reset_index()
-
-    postcode_summary["Gain"] = postcode_summary[gain_columns].sum(axis=1)
-    postcode_summary["Loss"] = postcode_summary[loss_columns].sum(axis=1)
-
-    no_loss_postcodes = postcode_summary[postcode_summary["Loss"] == 0].sort_values("Gain", ascending=False)
-    total_bid_size = bid_size + no_loss_postcodes["Gain"].sum()
-    print(total_bid_size)
-
     # Label final outputs
     # We create a summary of packages by street
     results["Package Ref"] = results["Package Ref"].fillna("Incomplete")