class_docstr: The ReciprocalTransformer() applies the reciprocal transformation 1 / x
  to numerical variables.
  
  The ReciprocalTransformer() only works with numerical variables with non-zero
  values. If a variable contains the value 0, the transformer will raise an error.
  
  A list of variables can be passed as an argument. Alternatively, the
  transformer will automatically select and transform all numerical
  variables.
  
  More details in the :ref:`User Guide <reciprocal>`.
  
  Parameters
  ----------
  {variables}
  
  Attributes
  ----------
  {variables_}
  
  {feature_names_in_}
  
  {n_features_in_}
  
  Methods
  -------
  {fit}
  
  {fit_transform}
  
  {inverse_transform}
  
  transform:
      Apply the reciprocal 1 / x transformation.
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code: def __init__(
      self,
      variables: Union[None, int, str, List[Union[str, int]]] = None,
  ) -> None:
      self.variables = _check_init_parameter_variables(variables)
  
file_path: feature_engine/feature_engine/transformation/reciprocal.py
imports: from typing import List, Optional, Union
  import numpy
  import pandas
  from feature_engine._base_transformers.base_numerical import BaseNumericalTransformer
  from feature_engine._docstrings.fit_attributes import _feature_names_in_docstring, _n_features_in_docstring, _variables_attribute_docstring
  from feature_engine._docstrings.init_parameters import _variables_numerical_docstring
  from feature_engine._docstrings.methods import _fit_not_learn_docstring, _fit_transform_docstring, _inverse_transform_docstring
  from feature_engine._docstrings.substitute import Substitution
  from feature_engine._variable_handling.init_parameter_checks import _check_init_parameter_variables
  from feature_engine.tags import _return_tags
label_desc: Use image node_id 1 to create a new ReciprocalTransformer object from inherited base classes: BaseNumericalTransformer with example: obj = ReciprocalTransformer(variables)