code: def load_random_time_series_data():
      
      data = get_example_data('random_time_series.json.gz')
      pdf = pd.read_json(data)
      pdf.ds = pd.to_datetime(pdf.ds, unit='s')
      pdf.to_sql(
          'random_time_series',
          db.engine,
          if_exists='replace',
          chunksize=500,
          dtype={
              'ds': DateTime,
          },
          index=False)
      print('Done loading table!')
      print('-' * 80)
  
      print('Creating table [random_time_series] reference')
      obj = db.session.query(TBL).filter_by(table_name='random_time_series').first()
      if not obj:
          obj = TBL(table_name='random_time_series')
      obj.main_dttm_col = 'ds'
      obj.database = utils.get_or_create_main_db()
      db.session.merge(obj)
      db.session.commit()
      obj.fetch_metadata()
      tbl = obj
  
      slice_data = {
          'granularity_sqla': 'day',
          'row_limit': config.get('ROW_LIMIT'),
          'since': '1 year ago',
          'until': 'now',
          'metric': 'count',
          'where': '',
          'viz_type': 'cal_heatmap',
          'domain_granularity': 'month',
          'subdomain_granularity': 'day',
      }
  
      print('Creating a slice')
      slc = Slice(
          slice_name='Calendar Heatmap',
          viz_type='cal_heatmap',
          datasource_type='table',
          datasource_id=tbl.id,
          params=get_slice_json(slice_data),
      )
      merge_slice(slc)
docs: Loading random time series data from a zip file in the repo