code: def _execute_cumsum(cls, op: "DataFrameEwmAgg", in_data):
      exec_cache = cls._exec_cache[op.key]
      cache_key = ("cumsum", id(in_data))
      summary = None
  
      try:
          result = exec_cache[cache_key]
      except KeyError:
          min_periods = 1 if op.min_periods > 0 else 0
  
          try:
              data = in_data.ewm(
                  alpha=op.alpha,
                  ignore_na=op.alpha_ignore_na,
                  adjust=op.adjust,
                  min_periods=min_periods,
              ).mean()
          except ValueError:
              in_data = in_data.copy()
              data = in_data.ewm(
                  alpha=op.alpha,
                  ignore_na=op.alpha_ignore_na,
                  adjust=op.adjust,
                  min_periods=min_periods,
              ).mean()
  
          alpha_sum, _ = op._execute_cum_alpha_coeff(
              op, in_data, 1, final=False
          )
          result = exec_cache[cache_key] = data * alpha_sum
  
      if op.output_agg:
          summary = result.ffill()[-1:]
      return result, summary
  
imports: from collections import namedtuple
  import numpy
  import pandas
  from ....None import opcodes
  from ....serialization.serializables import BoolField, Float64Field
  from ..aggregation import BaseDataFrameExpandingAgg
label_desc: Use image node_id 9 for calling the DataFrameEwmAgg obj's underlying member method code with example usage: obj._execute_cumsum(cls, op, in_data) and returns: result,  summary