code: def util_generate_second_similar_dataframe_and_expected():
      np.random.seed(42)
      df, _ = util_generate_dataframe_and_expected()
      df2 = df.copy()
      df2["x2"] = df["x2"] + 0.5 * df["x1"]
      df2["x3"] = 0.3 * df["x3"] + df["label"]
  
      return (
          df,
          df2,
          {
              "x1": close_to(0, 0.1),
              "x2": close_to(0.3, 0.1),
              "x3": close_to(-0.54, 0.1),
              "x4": close_to(0, 0.1),
              "x5": close_to(0, 0.1),
          },
      )
  
imports: import numpy
  import pandas
  from hamcrest import assert_that, calling, close_to, equal_to, greater_than, has_entries, has_length, raises
  from deepchecks.core.errors import DatasetValidationError, DeepchecksNotSupportedError, DeepchecksValueError
  from deepchecks.tabular.checks.data_integrity import FeatureLabelCorrelation
  from deepchecks.tabular.checks.train_test_validation import FeatureLabelCorrelationChange
  from deepchecks.tabular.dataset import Dataset
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 2 for calling a global function with example usage: util_generate_second_similar_dataframe_and_expected() and returns: df,  df2,  dict