code: def _fit(self, X, y=None, **kwargs):
      self.ordinal_encoder = OrdinalEncoder(
          verbose=self.verbose,
          cols=self.cols,
          handle_unknown="value",
          handle_missing="value",
      )
      self.ordinal_encoder = self.ordinal_encoder.fit(X)
      X_ordinal = self.ordinal_encoder.transform(X)
  
      self._check_set_create_dict_attrs()
      self._fit_count_encode(X_ordinal, y)
      return self
  
file_path: category_encoders/category_encoders/count.py
imports: import numpy
  import pandas
  import category_encoders.utils
  from category_encoders.ordinal import OrdinalEncoder
  from copy import copy
label_desc: Use image node_id 2 for calling the CountEncoder obj's underlying member method code with example usage: obj._fit(X, y) and returns: self