class_docstr: Divisive scaling on the value axis after aggregating within groups.
  
  Parameters
  ----------
  func : str or callable
      Function called on each group to define the comparison value.
  where : str
      Query string defining the subset used to define the comparison values.
  by : list of variables
      Variables used to define aggregation groups.
  percent : bool
      If True, multiply the result by 100.
  
  Examples
  --------
  .. include:: ../docstrings/objects.Norm.rst
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code: def __call__(
      self,
      data: DataFrame,
      groupby: GroupBy,
      orient: str,
      scales: dict[str, Scale],
  ) -> DataFrame:
      other = {"x": "y", "y": "x"}[orient]
      return groupby.apply(data, self._norm, other)
  
imports: from __future__ import annotations
  from dataclasses import dataclass
  from typing import ClassVar, Callable, Optional, Union, cast
  import numpy
  from pandas import DataFrame
  from seaborn._core.groupby import GroupBy
  from seaborn._core.scales import Scale
  from seaborn._core.typing import Default
label_desc: Use image node_id 2 for calling the Norm obj's underlying member method code with example usage: obj.__call__(data, groupby, orient, scales) and returns: groupby