code: def process_dataframe_timeline(args):
      """
      Massage input for bar traces for px.timeline()
      """
      args["is_timeline"] = True
      if args["x_start"] is None or args["x_end"] is None:
          raise ValueError("Both x_start and x_end are required")
  
      try:
          x_start = pd.to_datetime(args["data_frame"][args["x_start"]])
          x_end = pd.to_datetime(args["data_frame"][args["x_end"]])
      except (ValueError, TypeError):
          raise TypeError(
              "Both x_start and x_end must refer to data convertible to datetimes."
          )
  
      # note that we are not adding any columns to the data frame here, so no risk of overwrite
      args["data_frame"][args["x_end"]] = (x_end - x_start).astype(
          "timedelta64[ns]"
      ) / np.timedelta64(1, "ms")
      args["x"] = args["x_end"]
      del args["x_end"]
      args["base"] = args["x_start"]
      del args["x_start"]
      return args
  
imports: import plotly.graph_objs
  import plotly.io
  from collections import namedtuple, OrderedDict
  from ._special_inputs import IdentityMap, Constant, Range
  from .trendline_functions import ols, lowess, rolling, expanding, ewm
  from _plotly_utils.basevalidators import ColorscaleValidator
  from plotly.colors import qualitative, sequential
  import math
  from packaging import version
  import pandas
  import numpy
  from plotly._subplots import make_subplots, _set_trace_grid_reference, _subplot_type_for_trace_type
label_desc: Use image node_id 33 for calling a global function with example usage: process_dataframe_timeline(args) and returns: args