code: def aggregate_values_over_time(self, metric_store, data, groupby_name, column_name, aggregate_timestamp):
      
      # To add overall_summary one
      if self.groupby:
        metric_data = reduce(defaultdict.__getitem__, [column_name, 'Overall_summary', aggregate_timestamp], metric_store)
        metric_data.append(float(data))
      metric_data = reduce(defaultdict.__getitem__, [column_name, groupby_name, aggregate_timestamp], metric_store)
      metric_data.append(float(data))
      return None
docs: Organize and store the data from the log line into the metric store by metric type, transaction, timestamp
  
      :param dict metric_store: The metric store used to store all the parsed log data
      :param string data: column data in the log line
      :param string groupby_name: the group that the data belongs to
      :param string column_name: the column name of the data
      :param string aggregate_timestamp: timestamp used for storing the raw data. This accounts for aggregation time period
      :return: None