# pandas.read_sas

`pandas.``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 : str, path object or file-like object

  > Any valid string path is acceptable. The string could be a URL. Valid URL schemes include http, ftp, s3, and file. For file URLs, a host is expected. A local file could be: `file://localhost/path/to/table.sas`.

  > If you want to pass in a path object, pandas accepts any `os.PathLike`.

  > By file-like object, we refer to objects with a `read()` method, such as a file handler (e.g. via builtin `open` function) or `StringIO`.

  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

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