code: def _return_tags():
      return {
          "preserves_dtype": [],
          "_xfail_checks": {
              # Complex data in math terms, are values like 4i (imaginary numbers
              # so to speak). I've never seen such a thing in the dfs I've
              # worked with, so I don't think we need this test.
              "check_complex_data": "Test not needed.",
              # check that estimators treat dtype object as numeric if possible
              "check_dtype_object": "Feature-engine transformers use dtypes to select "
              "between numerical and categorical variables. Feature-engine trusts the "
              "user casts the variables appropriately",
              # Test fails because FE does not like the sklearn class _NotAnArray
              # The test aims to check that the check_X_y function from sklearn is
              # working, but we do not use that check, because we work with dfs.
              "check_transformer_data_not_an_array": "Ok to fail",
              # TODO: we probably need the test below!!
              "check_methods_sample_order_invariance": "Test does not work on dataframes",
              # TODO: we probably need the test below!!
              # the test below tests that a second fit overrides a first fit.
              # the problem is that the test does not work with pandas df.
              "check_fit_idempotent": "Test does not work on dataframes.",
              "check_fit2d_predict1d": "Test not relevant, Feature-engine transformers "
              "only work with dataframes.",
          },
      }
  
label_desc: Use image node_id 1 for calling a global function with example usage: _return_tags() and returns: dict