code: def _sample_cell(args, cell_body):
    
  
    env = datalab.utils.commands.notebook_environment()
    query = None
    table = None
    view = None
  
    if args['query']:
      query = _get_query_argument(args, cell_body, env)
    elif args['table']:
      table = _get_table(args['table'])
    elif args['view']:
      view = datalab.utils.commands.get_notebook_item(args['view'])
      if not isinstance(view, datalab.bigquery.View):
        raise Exception('%s is not a view' % args['view'])
    else:
      query = datalab.bigquery.Query(cell_body, values=env)
  
    count = args['count']
    method = args['method']
    if method == 'random':
      sampling = datalab.bigquery.Sampling.random(percent=args['percent'], count=count)
    elif method == 'hashed':
      sampling = datalab.bigquery.Sampling.hashed(field_name=args['field'], percent=args['percent'],
                                                  count=count)
    elif method == 'sorted':
      ascending = args['order'] == 'ascending'
      sampling = datalab.bigquery.Sampling.sorted(args['field'],
                                                  ascending=ascending,
                                                  count=count)
    elif method == 'limit':
      sampling = datalab.bigquery.Sampling.default(count=count)
    else:
      sampling = datalab.bigquery.Sampling.default(count=count)
  
    if query:
      results = query.sample(sampling=sampling, dialect=args['dialect'], billing_tier=args['billing'])
    elif view:
      results = view.sample(sampling=sampling)
    else:
      results = table.sample(sampling=sampling)
    if args['verbose']:
      print(results.sql)
    if args['profile']:
      return datalab.utils.commands.profile_df(results.to_dataframe())
    else:
      return results
docs: Implements the bigquery sample cell magic for ipython notebooks.
  
    Args:
      args: the optional arguments following '%%bigquery sample'.
      cell_body: optional contents of the cell interpreted as SQL, YAML or JSON.
    Returns:
      The results of executing the sampling query, or a profile of the sample data.