class_docstr: Standardize an H2OFrame by demeaning and scaling each column.
  
  The default scaling will result in an H2OFrame with columns
  having zero mean and unit variance. Users may specify the
  centering and scaling values used in the standardization of
  the H2OFrame.
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docstr: :param center: A boolean or list of numbers. If True, then columns will be demeaned before scaling.
      If False, then columns will not be demeaned before scaling.
      If centers is an array of numbers, then len(centers) must match the number of
      columns in the dataset. Each value is removed from the respective column
      before scaling.
  :param scale: A boolean or list of numbers. If True, then columns will be scaled by the column's standard
      deviation. If False, then columns will not be scaled. If scales is an array, then len(scales) must match
      the number of columns in the dataset. Each column is scaled by the respective value in this array.
  :returns: An instance of H2OScaler.
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code: def __init__(self, center=True, scale=True):
      """
      :param center: A boolean or list of numbers. If True, then columns will be demeaned before scaling.
          If False, then columns will not be demeaned before scaling.
          If centers is an array of numbers, then len(centers) must match the number of
          columns in the dataset. Each value is removed from the respective column
          before scaling.
      :param scale: A boolean or list of numbers. If True, then columns will be scaled by the column's standard
          deviation. If False, then columns will not be scaled. If scales is an array, then len(scales) must match
          the number of columns in the dataset. Each column is scaled by the respective value in this array.
      :returns: An instance of H2OScaler.
      """
      self.parms = locals()
      self.parms = {k: v for k, v in self.parms.items() if k != "self"}
      if center is None or scale is None:
          raise ValueError("centers and scales must not be None.")
      self._means = None
      self._stds = None
  
imports: import warnings
  from .transform_base import H2OTransformer
label_desc: Use image node_id 1 to create a new H2OScaler object from inherited base classes: H2OTransformer with example: obj = H2OScaler(center, scale)