class_docstr: Used to display various kinds of plots (matplotlib, plotly, or bokeh are supported).
  Preprocessing: this component does *not* accept input.
  Postprocessing: expects either a {matplotlib.figure.Figure}, a {plotly.graph_objects._figure.Figure}, or a {dict} corresponding to a bokeh plot (json_item format)
  
  Demos: altair_plot, outbreak_forecast, blocks_kinematics, stock_forecast, map_airbnb
  Guides: plot-component-for-maps
code: def get_config(self):
      try:
          import bokeh  # type: ignore
  
          bokeh_version = bokeh.__version__
      except ImportError:
          bokeh_version = None
  
      config = super().get_config()
      config["bokeh_version"] = bokeh_version
      return config
  
imports: from __future__ import annotations
  import json
  from types import ModuleType
  from typing import Any, Callable, Literal
  import altair
  import pandas
  from gradio_client.documentation import document, set_documentation_group
  from gradio import processing_utils
  from gradio.components.base import Component
  from gradio.data_classes import GradioModel
  from gradio.events import Events
label_desc: Use image node_id 2 for calling the Plot obj's underlying member method code with example usage: obj.get_config() and returns: config