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 postprocess(self, value) -> PlotData | None:
      import matplotlib.figure
  
      if value is None:
          return None
      if isinstance(value, (ModuleType, matplotlib.figure.Figure)):  # type: ignore
          dtype = "matplotlib"
          out_y = processing_utils.encode_plot_to_base64(value)
      elif "bokeh" in value.__module__:
          dtype = "bokeh"
          from bokeh.embed import json_item  # type: ignore
  
          out_y = json.dumps(json_item(value))
      else:
          is_altair = "altair" in value.__module__
          dtype = "altair" if is_altair else "plotly"
          out_y = value.to_json()
      return PlotData(type=dtype, plot=out_y)
  
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 5 for calling the Plot obj's underlying member method code with example usage: obj.postprocess(value) and returns: PlotData, None