code: def test_pivot_multi_values():
      # from Pandas docs:
      # https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.pivot.html
      pdf = pd.DataFrame(
          {
              "foo": ["one", "one", "one", "two", "two", "two"],
              "bar": ["A", "B", "C", "A", "B", "C"],
              "baz": [1, 2, 3, 4, 5, 6],
              "zoo": ["x", "y", "z", "q", "w", "t"],
          }
      )
      gdf = cudf.from_pandas(pdf)
      assert_eq(
          pdf.pivot(index="foo", columns="bar", values=["baz", "zoo"]),
          gdf.pivot(index="foo", columns="bar", values=["baz", "zoo"]),
          check_dtype=False,
      )
  
imports: import re
  from itertools import chain
  import numpy
  import pandas
  import pytest
  import cudf
  from cudf import melt
  from cudf.core.buffer.spill_manager import get_global_manager
  from cudf.testing._utils import ALL_TYPES, DATETIME_TYPES, NUMERIC_TYPES, assert_eq
label_desc: Use image node_id 16 for calling a global function with example usage: test_pivot_multi_values() without return types