old_contents: """sum operation
  """
  import pandas as pd
  import math
  
  SAMPLE = 10
  
  def execute(options, id_columns, value_columns):
  	'''
  		id_columns - a dictionary mapping names (strings) to numpy arrays
  		value_columns - a dictionary mapping names (strings) to numpy arrays
  
  	'''
  
  	columns = id_columns.copy()
  	columns.update(value_columns)
  
  	frame = pd.DataFrame(columns)
  
  	id_name = "id_0"
  	value_name = "value_0"
  
  	# create a subset of the column values
  	column = id_columns[id_name]
  	uniques = set(column[:SAMPLE])
  	l = int(math.ceil(len(uniques)/2.0))
  	subset = sorted(list(uniques))[:l]
  	print(subset)
  
  	#frame.loc[frame[id_name] == 1, value_name].sum()
  	v = frame.loc[frame[id_name].isin(subset), value_name].sum()
  
  	return v.item() # convert from numpy type to python type
  
new_contents: """sum operation
  """
  import pandas as pd
  import math
  
  SAMPLE = 10
  
  def execute(options, id_columns, value_columns):
  	'''
  		id_columns - a dictionary mapping names (strings) to numpy arrays
  		value_columns - a dictionary mapping names (strings) to numpy arrays
  
  	'''
  
  	columns = id_columns.copy()
  	columns.update(value_columns)
  
  	frame = pd.DataFrame(columns)
  
  	id_name = "id_0"
  	value_name = "value_0"
  
  	# create a subset of the column values
  	column = id_columns[id_name]
  	uniques = set(column[:SAMPLE])
  	l = int(math.ceil(len(uniques)/2.0))
  	subset = sorted(list(uniques))[:l]
  
  	#frame.loc[frame[id_name] == 1, value_name].sum()
  	v = frame.loc[frame[id_name].isin(subset), value_name].sum()
  
  	return v.item() # convert from numpy type to python type
  
subject: remove debugging from where.in sum data generation