_csv.py 文件源码

def _view(args, cell):
  csv = datalab.data.Csv(args['input'])
  num_lines = int(args['count'] or 5)
  headers = None
  if cell:
    ipy = IPython.get_ipython()
    config = _utils.parse_config(cell, ipy.user_ns)
    if 'columns' in config:
      headers = [e.strip() for e in config['columns'].split(',')]
  df = pd.DataFrame(csv.browse(num_lines, headers))
  if args['profile']:
    # TODO(gram): We need to generate a schema and type-convert the columns before this
    # will be useful for CSV
    return _utils.profile_df(df)
  else:
    return IPython.core.display.HTML(df.to_html(index=False))