code: def test_compare_df_two_metrics(metrics):
      expected = pd.DataFrame(
          {
              1: [0.1, 0.2],
              2: [0.15, 0.25],
              "diff": [0.04999999999999999, 0.04999999999999999],
              "diff_relative": [
                  0.33333333333333326,
                  0.19999999999999996,
              ],
              "ratio": [1.4999999999999998, 1.25],
          }
      )
  
      out = nbcollection.compare_df(
          tables=metrics[:2], ids=[1, 2], scores_arg=None
      )
  
      np.testing.assert_allclose(out.data, expected)
      assert list(out.data.columns) == list(expected.columns)
      assert out.data.index.name == expected.index.name
  
imports: import pytest
  import pandas
  import numpy
  from sklearn_evaluation import NotebookCollection
  from sklearn_evaluation.nb import NotebookCollection
  from IPython.display import HTML
label_desc: Use image node_id 12 for calling a global function with example usage: test_compare_df_two_metrics(metrics) without return types