pandas.read_sas#
- pandas.read_sas(filepath_or_buffer, *, format=None, index=None, encoding=None, chunksize=None, iterator=False, compression='infer')[source]#
- Read SAS files stored as either XPORT or SAS7BDAT format files. - Parameters:
- filepath_or_bufferstr, 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.
- formatstr {‘xport’, ‘sas7bdat’} or None
- If None, file format is inferred from file extension. If ‘xport’ or ‘sas7bdat’, uses the corresponding format. 
- indexidentifier of index column, defaults to None
- Identifier of column that should be used as index of the DataFrame. 
- encodingstr, default is None
- Encoding for text data. If None, text data are stored as raw bytes. 
- chunksizeint
- Read file chunksize lines at a time, returns iterator. - Changed in version 1.2: - TextFileReaderis a context manager.
- iteratorbool, defaults to False
- If True, returns an iterator for reading the file incrementally. - Changed in version 1.2: - TextFileReaderis a context manager.
- compressionstr 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 - Nonefor 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.LZMAFileor- tarfile.TarFile, respectively. As an example, the following could be passed for Zstandard decompression using a custom compression dictionary:- compression={'method': 'zstd', 'dict_data': my_compression_dict}.- New in version 1.5.0: Added support for .tar files. 
 
- Returns:
- DataFrame if iterator=False and chunksize=None, else SAS7BDATReader
- or XportReader
 
 - Examples - >>> df = pd.read_sas("sas_data.sas7bdat")