code: def test_groupby_arrow_multi_agg(ray_start_regular_shared, num_parts):
      seed = int(time.time())
      print(
          f"Seeding RNG for test_groupby_arrow_multi_agg with: {seed}"
      )
      random.seed(seed)
      xs = list(range(100))
      random.shuffle(xs)
      df = pd.DataFrame({"A": [x % 3 for x in xs], "B": xs})
      agg_ds = (
          ray.data.from_pandas(df)
          .repartition(num_parts)
          .groupby("A")
          .aggregate(
              Count(),
              Sum("B"),
              Min("B"),
              Max("B"),
              Mean("B"),
              Std("B"),
              Quantile("B"),
          )
      )
      assert agg_ds.count() == 3
      agg_df = agg_ds.to_pandas()
      expected_grouped = df.groupby("A")["B"]
      np.testing.assert_array_equal(
          agg_df["count()"].to_numpy(), [34, 33, 33]
      )
      for agg in ["sum", "min", "max", "mean", "quantile", "std"]:
          result = agg_df[f"{agg}(B)"].to_numpy()
          expected = getattr(expected_grouped, agg)().to_numpy()
          if agg == "std":
              np.testing.assert_array_almost_equal(result, expected)
          else:
              np.testing.assert_array_equal(result, expected)
      # Test built-in global std aggregation
      df = pd.DataFrame({"A": xs})
  
      result_row = (
          ray.data.from_pandas(df)
          .repartition(num_parts)
          .aggregate(
              Sum("A"),
              Min("A"),
              Max("A"),
              Mean("A"),
              Std("A"),
              Quantile("A"),
          )
      )
      for agg in ["sum", "min", "max", "mean", "quantile", "std"]:
          result = result_row[f"{agg}(A)"]
          expected = getattr(df["A"], agg)()
          if agg == "std":
              assert math.isclose(result, expected)
          else:
              assert result == expected
  
imports: import itertools
  import math
  import random
  import time
  from unittest.mock import patch
  import numpy
  import pandas
  import pyarrow
  import pytest
  import ray
  from ray.data.aggregate import AggregateFn, Count, Max, Mean, Min, Quantile, Std, Sum
  from ray.data.context import DataContext
  from ray.data.tests.conftest import *
  from ray.data.tests.util import column_udf, named_values
  from ray.tests.conftest import *
label_desc: Use image node_id 27 for calling a global function with example usage: test_groupby_arrow_multi_agg(ray_start_regular_shared, num_parts) without return types