class_docstr: Class that takes care of converting unspecified data blob
  (Dict or List[Dict]) into datapoints (List[Dict]).
  If some properties that are required by Template class are missing
  ('x', 'y') it will attempt to fill in the blanks.
class_docstr_tok: ["Class","that","takes","care","of","converting","unspecified","data","blob","(","Dict","or","List","[","Dict","]",")","into","datapoints","(","List","[","Dict","]",")",".","If","some","properties","that","are","required","by","Template","class","are","missing","(","'","x","'",",","'","y","'",")","it","will","attempt","to","fill","in","the","blanks","."]
code: def __init__(
      self,
      plot_id: str,
      data: Optional[Dict] = None,
      properties: Optional[Dict] = None,
  ):
      super().__init__(plot_id, data, properties)
      self.plot_id = plot_id
  
imports: import os
  from typing import Any, Dict, Iterable, List, Optional, Tuple, Union
  from funcy import first, last
  from dvc.exceptions import DvcException
  from dvc.render import FIELD, FILENAME, INDEX, REVISION
  from .None import Converter
label_desc: Use image node_id 1 to create a new VegaConverter object from inherited base classes: Converter with example: obj = VegaConverter(plot_id, data, properties)