code: def load_flights():
      
      tbl_name = 'flights'
      data = get_example_data('flight_data.csv.gz', make_bytes=True)
      pdf = pd.read_csv(data, encoding='latin-1')
  
      # Loading airports info to join and get lat/long
      airports_bytes = get_example_data('airports.csv.gz', make_bytes=True)
      airports = pd.read_csv(airports_bytes, encoding='latin-1')
      airports = airports.set_index('IATA_CODE')
  
      pdf['ds'] = pdf.YEAR.map(str) + '-0' + pdf.MONTH.map(str) + '-0' + pdf.DAY.map(str)
      pdf.ds = pd.to_datetime(pdf.ds)
      del pdf['YEAR']
      del pdf['MONTH']
      del pdf['DAY']
  
      pdf = pdf.join(airports, on='ORIGIN_AIRPORT', rsuffix='_ORIG')
      pdf = pdf.join(airports, on='DESTINATION_AIRPORT', rsuffix='_DEST')
      pdf.to_sql(
          tbl_name,
          db.engine,
          if_exists='replace',
          chunksize=500,
          dtype={
              'ds': DateTime,
          },
          index=False)
      tbl = db.session.query(TBL).filter_by(table_name=tbl_name).first()
      if not tbl:
          tbl = TBL(table_name=tbl_name)
      tbl.description = 'Random set of flights in the US'
      tbl.database = utils.get_or_create_main_db()
      db.session.merge(tbl)
      db.session.commit()
      tbl.fetch_metadata()
      print('Done loading table!')
docs: Loading random time series data from a zip file in the repo