code: def test_complex_df():
      complex_df = pd.DataFrame(
          {
              "src": [0, 1, 2, 3],
              "dst": [1, 2, 3, 0],
              "colors": [1, 1, 2, 2],
              "bool": [True, False, True, True],
              "char": ["a", "b", "c", "d"],
              "str": ["a", "b", "c", "d"],
              "ustr": ["a", "b", "c", "d"],
              "emoji": ["😋", "😋😋", "😋", "😋"],
              "int": [0, 1, 2, 3],
              "num": [0.5, 1.5, 2.5, 3.5],
              "date_str": [
                  "2018-01-01 00:00:00",
                  "2018-01-02 00:00:00",
                  "2018-01-03 00:00:00",
                  "2018-01-05 00:00:00",
              ],
              "date": [
                  dt.datetime(2018, 1, 1),
                  dt.datetime(2018, 1, 1),
                  dt.datetime(2018, 1, 1),
                  dt.datetime(2018, 1, 1),
              ],
              "time": [
                  pd.Timestamp("2018-01-05"),
                  pd.Timestamp("2018-01-05"),
                  pd.Timestamp("2018-01-05"),
                  pd.Timestamp("2018-01-05"),
              ],
          }
      )
  
      for c in complex_df.columns:
          try:
              complex_df[c + "_cat"] = complex_df[c].astype("category")
          except Exception:
              # lists aren't categorical
              # print('could not make categorical', c)
              pass
  
      complex_df = cudf.DataFrame.from_pandas(complex_df)
  
      cugraph.hypergraph(complex_df)
  
imports: import datetime
  import pandas
  import pytest
  import cudf
  from cudf.testing.testing import assert_frame_equal
  import cugraph
label_desc: Use image node_id 1 for calling a global function with example usage: test_complex_df() without return types