code: def test_df_values(self):
      est1 = dpp.MinMaxScaler()
      est2 = dpp.MinMaxScaler()
  
      result_ar = est1.fit_transform(X)
      result_df = est2.fit_transform(df)
  
      for attr in [
          "data_min_",
          "data_max_",
          "data_range_",
          "scale_",
          "min_",
      ]:
          assert_eq_ar(getattr(est1, attr), getattr(est2, attr).values)
  
      assert_eq_ar(est1.transform(X), est2.transform(df).values)
  
      if hasattr(result_df, "values"):
          result_df = result_df.values
      assert_eq_ar(result_ar, result_df)
  
imports: from copy import copy
  import dask
  import dask.array
  import dask.dataframe
  import numpy
  import pandas
  import pandas.testing
  import pytest
  import sklearn.preprocessing
  from dask import compute
  from dask.array.utils import assert_eq
  from dask.dataframe.utils import assert_eq
  from pandas.api.types import is_categorical_dtype, is_object_dtype
  from sklearn.exceptions import NotFittedError
  import dask_ml.preprocessing
  from dask_ml.datasets import make_classification
  from dask_ml.utils import assert_estimator_equal
label_desc: Use image node_id 4 for calling the TestMinMaxScaler obj's underlying member method code with example usage: obj.test_df_values() without return types