class_docstr: Base class for encoders that includes the code to categorize and
  transform the input features.
code: def _get_feature(self, X, feature_idx):
      if hasattr(X, "iloc"):
          # pandas dataframes
          return X.iloc[:, feature_idx]
      # numpy arrays, sparse arrays
      return X[:, feature_idx]
  
imports: import copy
  from numbers import Integral
  import numpy
  from scipy import sparse
  from sklearn.base import BaseEstimator, TransformerMixin
  from sklearn.utils import check_array
  from sklearn.utils.validation import check_is_fitted
  from autogluon.features.generators import LabelEncoderFeatureGenerator
label_desc: Use image node_id 2 for calling the _BaseEncoder obj's underlying member method code with example usage: obj._get_feature(X, feature_idx) and returns: X, X