pandas.read_sas — pandas 3.0.1 documentation (original) (raw)
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.
iteratorbool, defaults to False
If True, returns an iterator for reading the file incrementally.
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). 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.ZstdCompressor,lzma.LZMAFile or tarfile.TarFile, respectively. As an example, the following could be passed for faster compression and to create a reproducible gzip archive:compression={'method': 'gzip', 'compresslevel': 1, 'mtime': 1}.
Returns:
DataFrame, SAS7BDATReader, or XportReader
DataFrame if iterator=False and chunksize=None, else SAS7BDATReader or XportReader, file format is inferred from file extension.
See also
Read a comma-separated values (csv) file into a DataFrame.
Read an Excel file into a pandas DataFrame.
Read an SPSS file into a pandas DataFrame.
Load an ORC object into a pandas DataFrame.
Load a feather-format object into a pandas DataFrame.
Examples
df = pd.read_sas("sas_data.sas7bdat")