class_docstr: Object for selecting specific columns from a data set.
  
  Parameters
  ----------
  cols : array-like (default: None)
      A list specifying the feature indices to be selected. For example,
      [1, 4, 5] to select the 2nd, 5th, and 6th feature columns, and
      ['A','C','D'] to select the name of feature columns A, C and D.
      If None, returns all columns in the array.
  
  drop_axis : bool (default=False)
      Drops last axis if True and the only one column is selected. This
      is useful, e.g., when the ColumnSelector is used for selecting
      only one column and the resulting array should be fed to e.g.,
      a scikit-learn column selector. E.g., instead of returning an
      array with shape (n_samples, 1), drop_axis=True will return an
      aray with shape (n_samples,).
  
  Examples
  -----------
  For usage examples, please see
  https://rasbt.github.io/mlxtend/user_guide/feature_selection/ColumnSelector/
code: def __init__(self, cols=None, drop_axis=False):
      self.cols = cols
      self.drop_axis = drop_axis
  
imports: import numpy
  from sklearn.base import BaseEstimator
label_desc: Use image node_id 1 to create a new ColumnSelector object from inherited base classes: BaseEstimator with example: obj = ColumnSelector(cols, drop_axis)