Read SAS files stored as either XPORT or SAS7BDAT format files.
Parameters : filepath_or_buffer str, path object, or file-like object
String, path object (implementing os.PathLike[str] ), or file-like object implementing a binary read() function. 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.sas7bdat .
format str 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 str, 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.
compression str or dict, default ‘infer’
For on-the-fly decompression of on-disk data. If ‘infer’ and ‘filepath_or_buffer’ is path-like, then detect compression from the following extensions: ‘.gz’, ‘.bz2’, ‘.zip’, ‘.xz’, ‘.zst’, ‘.tar’, ‘.tar.gz’, ‘.tar.xz’ or ‘.tar.bz2’ (otherwise no compression). If using ‘zip’ or ‘tar’, the ZIP file must contain only one data file to be read in. Set to None for no decompression. Can also be a dict with key 'method' set to one of < 'zip' , 'gzip' , 'bz2' , 'zstd' , 'xz' , 'tar' >and other key-value pairs are forwarded to zipfile.ZipFile , gzip.GzipFile , bz2.BZ2File , zstandard.ZstdDecompressor , lzma.LZMAFile or tarfile.TarFile , respectively. As an example, the following could be passed for Zstandard decompression using a custom compression dictionary: compression= .
New in version 1.5.0: Added support for .tar files.
Returns : DataFrame if iterator=False and chunksize=None, else SAS7BDATReader or XportReader>>> df = pd.read_sas("sas_data.sas7bdat")