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/
docstr: Mock method. Does nothing.
  
  Parameters
  ----------
  X : {array-like, sparse matrix}, shape = [n_samples, n_features]
      Training vectors, where n_samples is the number of samples and
      n_features is the number of features.
  y : array-like, shape = [n_samples] (default: None)
  
  Returns
  ---------
  self
docstr_tok: ["Mock","method",".","Does","nothing",".","Parameters","--","--","--","--","--","X",":","{","array-like",",","sparse","matrix","}",",","shape","=","[","n_samples",",","n_features","]","Training","vectors",",","where","n_samples","is","the","number","of","samples","and","n_features","is","the","number","of","features",".","y",":","array-like",",","shape","=","[","n_samples","]","(","default",":","None",")","Returns","--","--","--","--","-","self"]
code: def fit(self, X, y=None):
      """Mock method. Does nothing.
  
      Parameters
      ----------
      X : {array-like, sparse matrix}, shape = [n_samples, n_features]
          Training vectors, where n_samples is the number of samples and
          n_features is the number of features.
      y : array-like, shape = [n_samples] (default: None)
  
      Returns
      ---------
      self
  
      """
      return self
  
imports: import numpy
  from sklearn.base import BaseEstimator
label_desc: Use image node_id 4 for calling the ColumnSelector obj's underlying member method code with example usage: obj.fit(X, y) and returns: self