_load_table_as_df_normalized.py

def _load_table_as_df_normalized(bucket_name, file_name, tableSchema, tableName):
  """
  Source data file must be outer JSON
  """
  blob = CS.get_bucket(bucket_name).blob(file_name)
  body = json.loads(blob.download_as_string())
  table_id = BQ.dataset(BQ_DATASET).table(tableName)

  schema = create_schema_from_yaml(tableSchema) 
  job_config.schema = schema

  df = pandas.io.json.json_normalize(data=body, record_path='addresses', 
                           meta=[ 'id'	,'first_name',	'last_name',	'dob']
                           , record_prefix='addresses_'
                           ,errors='ignore')

  df = df[['id','first_name','last_name','dob','addresses_status','addresses_address','addresses_city','addresses_state','addresses_zip','addresses_numberOfYears']]

  load_job = BQ.load_table_from_dataframe(
       df,
       table_id,
       job_config=job_config,
       ) 

  load_job.result()
  print("Job finished.")