class_docstr: One-Hot-Encoder that groups infrequent values into one dummy variable.
  
  Code from https://github.com/jeongyoonlee/Kaggler/blob/master/kaggler/preprocessing/data.py
  
  Attributes:
      min_obs (int): minimum number of observation to create a dummy variable
      label_encoders (list of (dict, int)): label encoders and their maximums
                                            for columns
code: def fit(self, X, y=None):
      self.label_encoder.fit(X)
  
      return self
  
imports: import logging
  import numpy
  import pandas
  from scipy import sparse
  from sklearn import base
label_desc: Use image node_id 4 for calling the OneHotEncoder obj's underlying member method code with example usage: obj.fit(X, y) and returns: self