code: def test_groupby_quantile_with_arraylike_q_and_int_columns(
      frame_size, groupby, q
  ):
      # GH30289
      nrow, ncol = frame_size
      df = DataFrame(
          np.array([ncol * [_ % 4] for _ in range(nrow)]),
          columns=range(ncol),
      )
  
      idx_levels = [np.arange(min(nrow, 4))] * len(groupby) + [q]
      idx_codes = [[x for x in range(min(nrow, 4)) for _ in q]] * len(
          groupby
      ) + [list(range(len(q))) * min(nrow, 4)]
      expected_index = pd.MultiIndex(
          levels=idx_levels, codes=idx_codes, names=groupby + [None]
      )
      expected_values = [
          [float(x)] * (ncol - len(groupby))
          for x in range(min(nrow, 4))
          for _ in q
      ]
      expected_columns = [x for x in range(ncol) if x not in groupby]
      expected = DataFrame(
          expected_values,
          index=expected_index,
          columns=expected_columns,
      )
      result = df.groupby(groupby).quantile(q)
  
      tm.assert_frame_equal(result, expected)
  
imports: import numpy
  import pytest
  import pandas
  from pandas import DataFrame, Index
  import pandas._testing
label_desc: Use image node_id 6 for calling a global function with example usage: test_groupby_quantile_with_arraylike_q_and_int_columns(frame_size, groupby, q) without return types