fix issue with empty strings

data/src/data_utils/negligent_devs.py

@@ -58,18 +58,38 @@ def create_standardized_address(row):
 
 def negligent_devs(primary_featurelayer):
     devs = primary_featurelayer.gdf
-    city_owners = devs.loc[~devs["city_owner_agency"].isna()].copy()
-    non_city_owners = devs.loc[devs["city_owner_agency"].isna()].copy()
+
+    print("Columns in 'devs' DataFrame:", devs.columns)
+
+    print("Initial properties data:")
+    print(devs[['opa_id', 'city_owner_agency', 'mailing_street']].head(10))
+
+    city_owners = devs.loc[~devs["city_owner_agency"].isna() & (devs["city_owner_agency"] != "")].copy()
+    non_city_owners = devs.loc[devs["city_owner_agency"].isna() | (devs["city_owner_agency"] == "")].copy()
+
+    print(f"City owners shape: {city_owners.shape}, Non-city owners shape: {non_city_owners.shape}")
+
+    # Log before standardizing addresses
+    print("Non-city owners mailing streets before standardization:")
+    print(non_city_owners[['opa_id', 'mailing_street']].head(10))
 
     non_city_owners.loc[:, "mailing_street"] = (
         non_city_owners["mailing_street"].astype(str).apply(standardize_street)
     )
 
+    print("Non-city owners mailing streets after standardization:")
+    print(non_city_owners[['opa_id', 'mailing_street']].head(10))
+
     for term in ["ST", "AVE", "RD", "BLVD"]:
         non_city_owners.loc[:, "mailing_street"] = non_city_owners[
             "mailing_street"
         ].replace(regex={f"{term}.*": term})
 
+    # Log after applying term replacement
+    print("Non-city owners mailing streets after term replacement:")
+    print(non_city_owners[['opa_id', 'mailing_street']].head(10))
+
+    # Fill missing address components
     non_city_owners.loc[:, "mailing_address_1"] = non_city_owners[
         "mailing_address_1"
     ].fillna("")
@@ -84,33 +104,52 @@ def negligent_devs(primary_featurelayer):
     ].fillna("")
     non_city_owners.loc[:, "mailing_zip"] = non_city_owners["mailing_zip"].fillna("")
 
+    # Log addresses before creating standardized address
+    print("Non-city owners mailing details before creating standardized address:")
+    print(non_city_owners[['opa_id', 'mailing_street', 'mailing_city_state', 'mailing_zip']].head(10))
+
     non_city_owners.loc[:, "standardized_address"] = non_city_owners.apply(
         create_standardized_address, axis=1
     )
 
+    # Log standardized addresses and counts
+    print("Standardized addresses with counts:")
     address_counts = (
         non_city_owners.groupby("standardized_address")
         .size()
         .reset_index(name="property_count")
     )
+    print(address_counts.head(10))
+
     sorted_address_counts = address_counts.sort_values(
         by="property_count", ascending=False
     )
+    print("Top standardized addresses by property count:")
+    print(sorted_address_counts.head(10))
 
     non_city_owners = non_city_owners.merge(
         sorted_address_counts, on="standardized_address", how="left"
     )
 
+    # Log merged data for city owners
     city_owner_counts = (
         city_owners.groupby("city_owner_agency")
         .size()
         .reset_index(name="property_count")
     )
+    print("City owner counts:")
+    print(city_owner_counts.head(10))
+
     city_owners = city_owners.merge(
         city_owner_counts, on="city_owner_agency", how="left"
     )
 
     devs_combined = pd.concat([city_owners, non_city_owners], axis=0)
+
+    # Final check on the merged data before updating primary_featurelayer
+    print("Combined data with property counts:")
+    print(devs_combined[['opa_id', 'property_count']].head(10))
+
     primary_featurelayer.gdf = primary_featurelayer.gdf.merge(
         devs_combined[["opa_id", "property_count"]], on="opa_id", how="left"
     )
@@ -119,6 +158,9 @@ def negligent_devs(primary_featurelayer):
     )
     primary_featurelayer.gdf.loc[:, "negligent_dev"] = (
         primary_featurelayer.gdf["n_properties_owned"] > 5
-    ) & (primary_featurelayer.gdf["city_owner_agency"].isna())
+    ) & (primary_featurelayer.gdf["city_owner_agency"].isna() | (primary_featurelayer.gdf["city_owner_agency"] == ""))
+
+    print("Final feature layer data with negligent_dev flag:")
+    print(primary_featurelayer.gdf[['opa_id', 'n_properties_owned', 'negligent_dev']].head(10))
 
     return primary_featurelayer