code: def _normalize(self, name, columns, points):
          
  
          for i, _ in enumerate(points):
              # Supported type:
              # https://docs.influxdata.com/influxdb/v1.5/write_protocols/line_protocol_reference/
              if points[i] is None:
                  # Ignore points with None value
                  del(points[i])
                  del(columns[i])
                  continue
              try:
                  points[i] = float(points[i])
              except (TypeError, ValueError):
                  pass
              else:
                  continue
              try:
                  points[i] = str(points[i])
              except (TypeError, ValueError):
                  pass
              else:
                  continue
  
          return [{'measurement': name,
                   'tags': self.parse_tags(self.tags),
                   'fields': dict(zip(columns, points))}]
docs: Normalize data for the InfluxDB's data model.