class_docstr: StringEncoder transform.
  The transform will cast everything to a
  string and the inverse transform will cast to the type defined in dtype.
class_docstr_tok: ["StringEncoder","transform",".","The","transform","will","cast","everything","to","a","string","and","the","inverse","transform","will","cast","to","the","type","defined","in","dtype","."]
docstr: Transform an array of categories to a string encoded representation.
  
  Parameters
  ----------
  X : array-like, shape=(n_samples,)
      List of categories.
  
  Returns
  -------
  Xt : array-like, shape=(n_samples,)
      The string encoded categories.
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code: def transform(self, X):
      """Transform an array of categories to a string encoded representation.
  
      Parameters
      ----------
      X : array-like, shape=(n_samples,)
          List of categories.
  
      Returns
      -------
      Xt : array-like, shape=(n_samples,)
          The string encoded categories.
      """
      return [str(x) for x in X]
  
imports: from __future__ import division
  import numpy
  from sklearn.preprocessing import LabelBinarizer
  from sklearn.utils import column_or_1d
label_desc: Use image node_id 3 for calling the StringEncoder obj's underlying member method code with example usage: obj.transform(X) and returns: unknown