code: def read_sas(
      filepath_or_buffer,
      format=None,
      index=None,
      encoding=None,
      chunksize=None,
      iterator=False,
  ):
      """
      Read SAS files stored as either XPORT or SAS7BDAT format files.
  
      Parameters
      ----------
      filepath_or_buffer : string or file-like object
          Path to the SAS file.
      format : string {'xport', 'sas7bdat'} or None
          If None, file format is inferred from file extension. If 'xport' or
          'sas7bdat', uses the corresponding format.
      index : identifier of index column, defaults to None
          Identifier of column that should be used as index of the DataFrame.
      encoding : string, default is None
          Encoding for text data.  If None, text data are stored as raw bytes.
      chunksize : int
          Read file `chunksize` lines at a time, returns iterator.
      iterator : bool, defaults to False
          If True, returns an iterator for reading the file incrementally.
  
      Returns
      -------
      DataFrame if iterator=False and chunksize=None, else SAS7BDATReader
      or XportReader
      """
      if format is None:
          buffer_error_msg = (
              "If this is a buffer object rather "
              "than a string name, you must specify "
              "a format string"
          )
          filepath_or_buffer = _stringify_path(filepath_or_buffer)
          if not isinstance(filepath_or_buffer, compat.string_types):
              raise ValueError(buffer_error_msg)
          fname = filepath_or_buffer.lower()
          if fname.endswith(".xpt"):
              format = "xport"
          elif fname.endswith(".sas7bdat"):
              format = "sas7bdat"
          else:
              raise ValueError("unable to infer format of SAS file")
  
      if format.lower() == "xport":
          from pandas.io.sas.sas_xport import XportReader
  
          reader = XportReader(
              filepath_or_buffer,
              index=index,
              encoding=encoding,
              chunksize=chunksize,
          )
      elif format.lower() == "sas7bdat":
          from pandas.io.sas.sas7bdat import SAS7BDATReader
  
          reader = SAS7BDATReader(
              filepath_or_buffer,
              index=index,
              encoding=encoding,
              chunksize=chunksize,
          )
      else:
          raise ValueError("unknown SAS format")
  
      if iterator or chunksize:
          return reader
  
      data = reader.read()
      reader.close()
      return data
  
label_desc: Use image node_id 1 for calling a global function with example usage: read_sas(filepath_or_buffer, format, index, encoding, chunksize, iterator) and returns: data, reader