code: def test_nan(self, pandas_df):
      pandas_df = pandas_df.copy()
      pandas_df.iloc[0] = np.nan
      dask_nan_df = dd.from_pandas(pandas_df, npartitions=5)
      a = dpp.StandardScaler()
      a.fit(dask_nan_df.values)
      assert np.isnan(a.mean_).sum() == 0
      assert np.isnan(a.var_).sum() == 0
  
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 TestStandardScaler obj's underlying member method code with example usage: obj.test_nan(pandas_df) without return types