class_docstr: Transformers that may update their params, like ARIMAs
docstr: Update the params and return the transformed arrays
  
  Parameters
  ----------
  y : array-like or None, shape=(n_samples,)
      The endogenous (time-series) array.
  
  X : array-like or None, shape=(n_samples, n_features)
      The exogenous array of additional covariates.
  
  **kwargs : keyword args
      Keyword arguments required by the transform function.
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code: def update_and_transform(self, y, X=None, **kwargs):
      """Update the params and return the transformed arrays
  
      Parameters
      ----------
      y : array-like or None, shape=(n_samples,)
          The endogenous (time-series) array.
  
      X : array-like or None, shape=(n_samples, n_features)
          The exogenous array of additional covariates.
  
      **kwargs : keyword args
          Keyword arguments required by the transform function.
      """
  
file_path: pmdarima/pmdarima/preprocessing/base.py
imports: from sklearn.base import BaseEstimator, TransformerMixin
  import abc
  from ..compat.numpy import DTYPE
  from ..utils import check_exog, check_endog
label_desc: Use image node_id 2 for calling the UpdatableMixin obj's underlying member method code with example usage: obj.update_and_transform(y, X) without return types