code: def get_stop_count_data(self, start_ut, end_ut):
          
          # TODO! this function could perhaps be made a single sql query now with the new tables?
          trips_df = self.get_tripIs_active_in_range(start_ut, end_ut)
          # stop_I -> count, lat, lon, name
          stop_counts = Counter()
  
          # loop over all trips:
          for row in trips_df.itertuples():
              # get stop_data and store it:
              stops_seq = self.get_trip_stop_time_data(row.trip_I, row.day_start_ut)
              for stop_time_row in stops_seq.itertuples(index=False):
                  if (stop_time_row.dep_time_ut >= start_ut) and (stop_time_row.dep_time_ut <= end_ut):
                      stop_counts[stop_time_row.stop_I] += 1
  
          all_stop_data = self.stops()
          counts = [stop_counts[stop_I] for stop_I in all_stop_data["stop_I"].values]
  
          all_stop_data.loc[:, "count"] = pd.Series(counts, index=all_stop_data.index)
          return all_stop_data
docs: Get stop count data.
  
          Parameters
          ----------
          start_ut : int
              start time in unixtime
          end_ut : int
              end time in unixtime
  
          Returns
          -------
          stopData : pandas.DataFrame
              each row in the stopData dataFrame is a dictionary with the following elements
                  stop_I, count, lat, lon, name
              with data types
                  (int, int, float, float, str)