class_docstr: LabelEncoder wrapper with TransformerMixin. Allows LabelEncoder
  to work with a Pipeline.
class_docstr_tok: ["LabelEncoder","wrapper","with","TransformerMixin",".","Allows","LabelEncoder","to","work","with","a","Pipeline","."]
docstr: Transform the label encoder 
docstr_tok: ["Transform","the","label","encoder"]
code: def transform(self, X, y=None):
      """Transform the label encoder"""
      return np.array([[x] for x in self.le.transform(X)])
  
imports: import warnings
  import pandas
  import numpy
  from scipy import sparse
  from sklearn.base import BaseEstimator, TransformerMixin
  from sklearn.preprocessing import MultiLabelBinarizer, FunctionTransformer, LabelEncoder, normalize
  from sklearn.feature_extraction.text import HashingVectorizer
  from sklearn import feature_selection
label_desc: Use image node_id 2 for calling the LabelEncoderPipe obj's underlying member method code with example usage: obj.transform(X, y) and returns: np