class_docstr: Abstract interface for data aggregation functionality for plotly figures.
class_docstr_tok: ["Abstract","interface","for","data","aggregation","functionality","for","plotly","figures","."]
docstr: Convert the `add_trace` kwargs to the `add_traces` kwargs.
docstr_tok: ["Convert","the","`","add_trace","`","kwargs","to","the","`","add_traces","`","kwargs","."]
code: def _add_trace_to_add_traces_kwargs(kwargs: dict) -> dict:
      """Convert the `add_trace` kwargs to the `add_traces` kwargs."""
      # The keywords that need to be converted to a list
      convert_keywords = ["row", "col", "secondary_y"]
  
      updated_kwargs = (
          {}
      )  # The updated kwargs (from `add_trace` to `add_traces`)
      for keyword in convert_keywords:
          value = kwargs.pop(keyword, None)
          if value is not None:
              updated_kwargs[f"{keyword}s"] = [value]
          else:
              updated_kwargs[f"{keyword}s"] = None
  
      return {**kwargs, **updated_kwargs}
  
imports: from __future__ import annotations
  import itertools
  import re
  from abc import ABC
  from collections import namedtuple
  from copy import copy
  from typing import Dict, Iterable, List, Optional, Tuple, Union
  from uuid import uuid4
  import dash
  import numpy
  import pandas
  import plotly.graph_objects
  from pandas.io.json._normalize import nested_to_record
  from plotly.basedatatypes import BaseFigure, BaseTraceType
  from ..aggregation import AbstractAggregator, MedDiffGapHandler, MinMaxLTTB
  from ..aggregation.aggregation_interface import DataPointSelector
  from ..aggregation.gap_handler_interface import AbstractGapHandler
  from ..aggregation.plotly_aggregator_parser import PlotlyAggregatorParser
  from .utils import round_number_str, round_td_str
label_desc: Use image node_id 13 for calling the AbstractFigureAggregator obj's underlying member method code with example usage: obj._add_trace_to_add_traces_kwargs(kwargs) and returns: dict