code: def parse_record_static(self, raw):
          
          # Parsing status
          status = self.status(raw)
  
          # Testing if no errors
          if status['StatusType'] != 'Connected':
              if self.raise_on_error:
                  raise DatastreamException('%s (error %i): %s --> "%s"' %
                                            (status['StatusType'], status['StatusCode'],
                                             status['StatusMessage'], status['Request']))
              else:
                  self._test_status_and_warn()
                  return pd.DataFrame(), {}
  
          # Convert record to dict
          record = self.extract_data(raw)
  
          try:
              error = record['INSTERROR']
              if self.raise_on_error:
                  raise DatastreamException('Error: %s --> "%s"' %
                                            (error, status['Request']))
              else:
                  self.last_status['StatusMessage'] = error
                  self.last_status['StatusType'] = 'INSTERROR'
                  self._test_status_and_warn()
                  return pd.DataFrame(), {'Status': error, 'Date': None}
          except KeyError:
              metadata = {'Status': 'OK', 'Date': ''}
  
          # All fields that are available
          fields = [x for x in record if '_' not in x]
          metadata['Date'] = record['DATE']
          fields.remove('DATE')
  
          # Number of elements
          num = len([x[0] for x in record if 'SYMBOL' in x])
  
          # field naming 'CCY', 'CCY_2', 'CCY_3', ...
          fld_name = lambda field, indx: field if indx == 0 else field + '_%i' % (indx + 1)
  
          # Construct pd.DataFrame
          res = pd.DataFrame({fld: [record[fld_name(fld, ind)]
                                    if fld_name(fld, ind) in record else ''
                                    for ind in range(num)]
                              for fld in fields})
          return res, metadata
docs: Parse raw data (that is retrieved by static request) and return pandas.DataFrame.
             Returns tuple (data, metadata)
  
             data - pandas.DataFrame with retrieved data.
             metadata - pandas.DataFrame with info about symbol, currency, frequency,
                        displayname and status of given request