code: def expected_bar_value_with_holes(
      asset_id, date, colname, holes, missing_value
  ):
      # Explicit holes are filled with the missing value.
      if asset_id in holes and date in holes[asset_id]:
          return missing_value
  
      return expected_bar_value(asset_id, date, colname)
  
imports: from interface import implements
  from numpy import arange, array, eye, float64, full, iinfo, nan, uint32
  from numpy.random import RandomState
  from pandas import DataFrame, Timestamp
  from six import iteritems
  from sqlite3 import connect
  from .base import PipelineLoader
  from .frame import DataFrameLoader
  from zipline.data.adjustments import SQLiteAdjustmentReader, SQLiteAdjustmentWriter
  from zipline.data.bcolz_daily_bars import US_EQUITY_PRICING_BCOLZ_COLUMNS
  from zipline.utils.numpy_utils import bool_dtype, datetime64ns_dtype, float64_dtype, int64_dtype, object_dtype
label_desc: Use image node_id 6 for calling a global function with example usage: expected_bar_value_with_holes(asset_id, date, colname, holes, missing_value) and returns: expected_bar_value, missing_value