code: def parallel_coordinates(
      experiment, with_evc_tree=True, order=None, **kwargs
  ):
      """
      Make a Parallel Coordinates Plot to visualize the effect of the hyperparameters
      on the objective.
  
      Parameters
      ----------
      experiment: ExperimentClient or Experiment
          The orion object containing the experiment data
  
      with_evc_tree: bool, optional
          Fetch all trials from the EVC tree.
          Default: True
  
      order: list of str or None
          Indicates the order of columns in the parallel coordinate plot. By default
          the columns are sorted alphabetically with the exception of the first column
          which is reserved for a fidelity dimension is there is one in the search space.
  
      kwargs: dict
          All other plotting keyword arguments to be passed to
          :plotly:`express.line`.
  
      Returns
      -------
      plotly.graph_objects.Figure
  
      Raises
      ------
      ValueError
          If no experiment is provided.
  
      """
      return backend.parallel_coordinates(
          experiment, with_evc_tree=with_evc_tree, order=order, **kwargs
      )
  
file_path: orion/src/orion/plotting/base.py
imports: import orion.plotting.backend_plotly
label_desc: Use image node_id 2 for calling a global function with example usage: parallel_coordinates(experiment, with_evc_tree, order) and returns: backend