class_docstr: Mixin class with utilities for by-column applicates.
docstr: Apply self.methodname to kwargs by column, then column-concatenate.
  
  Parameters
  ----------
  methodname : str, one of the methods of self
      assumed to take kwargs and return pd.DataFrame
  col_multiindex : bool, optional, default=False
      if True, will add an additional column multiindex at top, entries = index
  
  Returns
  -------
  y_pred : pd.DataFrame
      result of [f.methodname(**kwargs) for _, f, _ in self.forecsaters_]
      column-concatenated with keys being the variable names last seen in y
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code: def _by_column(self, methodname, **kwargs):
      """Apply self.methodname to kwargs by column, then column-concatenate.
  
      Parameters
      ----------
      methodname : str, one of the methods of self
          assumed to take kwargs and return pd.DataFrame
      col_multiindex : bool, optional, default=False
          if True, will add an additional column multiindex at top, entries = index
  
      Returns
      -------
      y_pred : pd.DataFrame
          result of [f.methodname(**kwargs) for _, f, _ in self.forecsaters_]
          column-concatenated with keys being the variable names last seen in y
      """
      # get col_multiindex arg from kwargs
      col_multiindex = kwargs.pop("col_multiindex", False)
  
      y_preds = []
      keys = []
      for _, est, index in getattr(self, self._steps_fitted_attr):
          y_preds += [getattr(est, methodname)(**kwargs)]
          keys += [index]
  
      keys = self._get_indices(self._y, keys)
  
      if col_multiindex:
          y_pred = pd.concat(y_preds, axis=1, keys=keys)
      else:
          y_pred = pd.concat(y_preds, axis=1)
      return y_pred
  
imports: from inspect import isclass
  import numpy
  import pandas
  from sktime.base import BaseEstimator
label_desc: Use image node_id 3 for calling the _ColumnEstimator obj's underlying member method code with example usage: obj._by_column(methodname) and returns: y_pred