code: def evaluate(self, verbose=True, passes=None):
          
          if self.is_pivot:
              index, pivot, columns = LazyOpResult(
                  self.expr,
                  self.weld_type,
                  0
              ).evaluate(verbose=verbose, passes=passes)
              df_dict = {}
              for i, column_name in enumerate(columns):
                  df_dict[column_name] = pivot[i]
              return DataFrameWeld(pd.DataFrame(df_dict, index=index))
          else:
              df = pd.DataFrame(columns=[])
              weldvec_type_list = []
              for type in self.column_types:
                  weldvec_type_list.append(WeldVec(type))
  
              columns = LazyOpResult(
                  grizzly_impl.unzip_columns(
                      self.expr,
                      self.column_types
                  ),
                  WeldStruct(weldvec_type_list),
                  0
              ).evaluate(verbose=verbose, passes=passes)
  
              for i, column_name in enumerate(self.column_names):
                  df[column_name] = columns[i]
  
              return DataFrameWeld(df)
docs: Summary
  
          Returns:
              TYPE: Description