code: def write_points(self, data, *args, **kwargs):
          
          batch_size = kwargs.get('batch_size')
          time_precision = kwargs.get('time_precision', 's')
          if batch_size:
              kwargs.pop('batch_size')  # don't hand over to InfluxDBClient
              for key, data_frame in data.items():
                  number_batches = int(math.ceil(
                      len(data_frame) / float(batch_size)))
                  for batch in range(number_batches):
                      start_index = batch * batch_size
                      end_index = (batch + 1) * batch_size
                      outdata = [
                          self._convert_dataframe_to_json(
                              name=key,
                              dataframe=data_frame
                              .iloc[start_index:end_index].copy(),
                              time_precision=time_precision)]
                      InfluxDBClient.write_points(self, outdata, *args, **kwargs)
              return True
  
          outdata = [
              self._convert_dataframe_to_json(name=key, dataframe=dataframe,
                                              time_precision=time_precision)
              for key, dataframe in data.items()]
          return InfluxDBClient.write_points(self, outdata, *args, **kwargs)
docs: Write to multiple time series names.
  
          :param data: A dictionary mapping series names to pandas DataFrames
          :param time_precision: [Optional, default 's'] Either 's', 'm', 'ms'
              or 'u'.
          :param batch_size: [Optional] Value to write the points in batches
              instead of all at one time. Useful for when doing data dumps from
              one database to another or when doing a massive write operation
          :type batch_size: int