code: def rankings(
      experiments, with_evc_tree=True, order_by="suggested", **kwargs
  ):
      """
      Make a plot to visually compare the ranking of different hyper-optimization processes.
  
      The x-axis contain the trials and the y-axis their respective ranking.
  
      4 formats are supported for the experiments:
  
          1. List of experiments. The names of the experiments will be used for the figure labels.
          2. Dictionary of experiments. The keys of the dictionary will be used for the figure labels.
          3. List of dictionary of experiments. The keys of the dictionary will be used for the figure \
          labels. The ranking will be averaged across the dictionaries.
          4. Dictionary of list of experiments. The keys of the dictionary will be used for the figure \
          labels. A dictionary of experiments will be build grouping the i-th experiments of each \
          list to result in a list of dictionary of experiments. Behavior will be same as format 3.
  
      Parameters
      ----------
      experiments: list or dict
          List or dictionary of experiments.
  
      with_evc_tree: bool, optional
          Fetch all trials from the EVC tree.
          Default: True
  
      order_by: str
          Indicates how the trials should be ordered. Acceptable options are below.
          See attributes of ``Trial`` for more details.
  
          * 'suggested': Sort by trial suggested time (default).
          * 'reserved': Sort by trial reserved time.
          * 'completed': Sort by trial completed time.
  
      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 or order_by is invalid.
  
      """
      return backend.rankings(
          experiments,
          with_evc_tree=with_evc_tree,
          order_by=order_by,
          **kwargs,
      )
  
file_path: orion/src/orion/plotting/base.py
imports: import orion.plotting.backend_plotly
label_desc: Use image node_id 4 for calling a global function with example usage: rankings(experiments, with_evc_tree, order_by) and returns: backend