code: def test_df_column_slice(self):
      mask = ["3", "4"]
      mask_ix = [mask.index(x) for x in mask]
      a = dpp.MinMaxScaler(columns=mask)
      b = spp.MinMaxScaler()
  
      dfa = a.fit_transform(df2)
      mxb = b.fit_transform(df2.compute())
  
      assert isinstance(dfa, dd.DataFrame)
      assert_eq_ar(dfa[mask].values, mxb[:, mask_ix])
      assert_eq_df(dfa.drop(mask, axis=1), df2.drop(mask, axis=1))
  
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 5 for calling the TestMinMaxScaler obj's underlying member method code with example usage: obj.test_df_column_slice() without return types