code: def apply_broadcast(self, target):
      result_values = np.empty_like(target.values)
  
      # axis which we want to compare compliance
      result_compare = target.shape[0]
  
      for i, col in enumerate(target.columns):
          res = self.f(target[col])
          ares = np.asarray(res).ndim
  
          # must be a scalar or 1d
          if ares > 1:
              raise ValueError("too many dims to broadcast")
          elif ares == 1:
              # must match return dim
              if result_compare != len(res):
                  raise ValueError("cannot broadcast result")
  
          result_values[:, i] = res
  
      # we *always* preserve the original index / columns
      result = self.obj._constructor(
          result_values, index=target.index, columns=target.columns
      )
      return result
  
imports: import warnings
  import numpy
  from pandas._libs import reduction
  import pandas.compat
  from pandas.util._decorators import cache_readonly
  from pandas.core.dtypes.common import is_dict_like, is_extension_type, is_list_like, is_sequence
  from pandas.core.dtypes.generic import ABCSeries
  from pandas.io.formats.printing import pprint_thing
label_desc: Use image node_id 10 for calling the FrameApply obj's underlying member method code with example usage: obj.apply_broadcast(target) and returns: result