docs: def _plot_ts_cols(ts):
      """
      Get variable + values vs year, age, depth (whichever are available)
      :param dict ts: TimeSeries dictionary
      :return dict: Key: variableName, Value: Panda Series object
      """
      logger_dataframes.info("enter get_ts_cols()")
      d = {}
  
      # Not entirely necessary, but this will make the column headers look nicer for the data frame
      # The column header will be in format "variableName (units)"
      try:
          units = " (" + ts["paleoData_units"] + ")"
      except KeyError as e:
          units = ""
          logger_dataframes.warn("get_ts_cols: KeyError: paleoData_units not found, {}".format(e))
      try:
          d[ts["paleoData_variableName"] + units] = ts["paleoData_values"]
      except KeyError as e:
          logger_dataframes.warn("get_ts_cols: KeyError: variableName or values not found, {}".format(e))
  
      # Start looking for age, year, depth columns
      for k, v in ts.items():
          if re_pandas_x_num.match(k):
              try:
                  units = " (" + ts[k + "Units"] + ")"
                  d[k + units] = v
              except KeyError as e:
                  logger_dataframes.warn("get_ts_cols: KeyError: Special column units, {}, {}".format(k, e))
      logger_dataframes.info("exit get_ts_cols: found {}".format(len(d)))
      return d