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 binaryread()
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:
TextFileReader
is a context manager.- iteratorbool, defaults to False
If True, returns an iterator for reading the file incrementally.
Changed in version 1.2:
TextFileReader
is 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
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 tozipfile.ZipFile
,gzip.GzipFile
,bz2.BZ2File
,zstandard.ZstdDecompressor
,lzma.LZMAFile
ortarfile.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")