class_docstr: Wrapper class for estimators from the EconML library.
  
  Supports additional parameters as listed below. For init and fit
  parameters of each estimator, refer to the EconML docs.
code: def apply_multitreatment(
      self, df: pd.DataFrame, fun: Callable, *args, **kwargs
  ):
      ests = []
      assert not isinstance(self._treatment_value, str)
      assert is_sequence(self._treatment_value)
  
      if df is None:
          filtered_df = None
      else:
          filtered_df = df.values
      for tv in self._treatment_value:
          ests.append(
              fun(
                  filtered_df,
                  T0=self._control_value,
                  T1=tv,
                  *args,
                  **kwargs,
              )
          )
      est = np.stack(ests, axis=1)
      return est
  
imports: import inspect
  from importlib import import_module
  from typing import Any, Callable, List, Optional, Protocol, Union
  from warnings import warn
  import numpy
  import pandas
  from numpy.distutils.misc_util import is_sequence
  from dowhy.causal_estimator import CausalEstimate, CausalEstimator
  from dowhy.causal_identifier import IdentifiedEstimand
  from dowhy.utils.api import parse_state
label_desc: Use image node_id 9 for calling the Econml obj's underlying member method code with example usage: obj.apply_multitreatment(df, fun) and returns: est