code: def make_column_transformer(*transformers, **kwargs):
      # This is identical to scikit-learn's. We're just using our
      # ColumnTransformer instead.
      n_jobs = kwargs.pop("n_jobs", 1)
      remainder = kwargs.pop("remainder", "drop")
      preserve_dataframe = kwargs.pop("preserve_dataframe", True)
      if kwargs:
          raise TypeError(
              'Unknown keyword arguments: "{}"'.format(
                  list(kwargs.keys())[0]
              )
          )
      transformer_list = _get_transformer_list(transformers)
      return ColumnTransformer(
          transformer_list,
          n_jobs=n_jobs,
          remainder=remainder,
          preserve_dataframe=preserve_dataframe,
      )
  
file_path: dask-ml/dask_ml/compose/_column_transformer.py
imports: import warnings
  import dask.array
  import dask.dataframe
  import numpy
  import pandas
  import sklearn.compose
  from scipy import sparse
  from sklearn.compose._column_transformer import _get_transformer_list
label_desc: Use image node_id 1 for calling a global function with example usage: make_column_transformer() and returns: ColumnTransformer