code: def test_aggregate_with_pandas_udaf_without_keys(self):
      t = self.t_env.from_elements(
          [(1, 2, 3), (2, 1, 3), (1, 5, 4), (1, 8, 6), (2, 3, 4)],
          DataTypes.ROW(
              [
                  DataTypes.FIELD("a", DataTypes.TINYINT()),
                  DataTypes.FIELD("b", DataTypes.SMALLINT()),
                  DataTypes.FIELD("c", DataTypes.INT()),
              ]
          ),
      )
  
      sink_table_ddl = """
              CREATE TABLE Results_test_aggregate_with_pandas_udaf_without_keys(
                  a FLOAT,
                  b INT
              ) WITH ('connector'='test-sink')
          """
      self.t_env.execute_sql(sink_table_ddl)
      pandas_udaf = udaf(
          lambda pd: Row(pd.b.mean(), pd.b.max()),
          result_type=DataTypes.ROW(
              [
                  DataTypes.FIELD("a", DataTypes.FLOAT()),
                  DataTypes.FIELD("b", DataTypes.INT()),
              ]
          ),
          func_type="pandas",
      )
      t.select(t.b).aggregate(pandas_udaf.alias("a", "b")).select(
          t.a, t.b
      ).execute_insert(
          "Results_test_aggregate_with_pandas_udaf_without_keys"
      ).wait()
      actual = source_sink_utils.results()
      self.assert_equals(actual, ["+I[3.8, 8]"])
  
imports: import unittest
  from pandas.testing import assert_frame_equal
  from pyflink.common import Row
  from pyflink.table import expressions, ListView
  from pyflink.table.types import DataTypes
  from pyflink.table.udf import udf, udtf, udaf, AggregateFunction, TableAggregateFunction, udtaf
  from pyflink.testing import source_sink_utils
  from pyflink.testing.test_case_utils import PyFlinkBatchTableTestCase, PyFlinkStreamTableTestCase
label_desc: Use image node_id 2 for calling the BatchRowBasedOperationITTests obj's underlying member method code with example usage: obj.test_aggregate_with_pandas_udaf_without_keys() without return types