remove cleaned layer task

dags/etl_food_security.py

@@ -56,37 +56,6 @@ def task_staging_integration():
     df      = staging.run()
     print(f"Staging integrated: {len(df):,} rows")
 
-def task_cleaned_layer():
-    from bigquery_config import get_bigquery_client
-    from bigquery_cleaned_layer import (
-        load_staging_data,
-        standardize_country_names_asean,
-        assign_pillar,
-        assign_direction,
-        CleanedDataLoader
-    )
-    import pandas as pd
-
-    client     = get_bigquery_client()
-    df_staging = load_staging_data(client)
-
-    df_staging, _ = standardize_country_names_asean(df_staging, country_column='country')
-
-    critical_columns = list(df_staging.columns)
-    df_no_missing    = df_staging.dropna(subset=critical_columns)
-
-    df_cleaned = df_no_missing.drop_duplicates(
-        subset=['indicator_standardized', 'country', 'year'],
-        keep='first'
-    )
-
-    df_cleaned['pillar']    = df_cleaned['indicator_standardized'].apply(assign_pillar)
-    df_cleaned['direction'] = df_cleaned['indicator_standardized'].apply(assign_direction)
-
-    loader      = CleanedDataLoader(client, load_mode='full_refresh')
-    final_count = loader.run(df_cleaned)
-    print(f"Cleaned loaded: {final_count:,} rows")
-
 with DAG(
     dag_id           = "etl_food_security_bigquery",
     start_date       = datetime(2026, 3, 1),
@@ -121,7 +90,4 @@ with DAG(
         python_callable= task_staging_integration
     )
 
-    cleaned = PythonOperator(
+    verify >> load_fao >> load_wb >> load_unicef >> staging
-        task_id        = "cleaned_layer_to_silver",
-        python_callable= task_cleaned_layer
-    )