modin.pandas.read_sas

modin.pandas.read_sas(filepath_or_buffer, *, format: str | None = None, index: Hashable | None = None, encoding: str | None = None, chunksize: int | None = None, iterator: bool = False, compression: CompressionOptions = 'infer') → pd.DataFrame[source] (https://github.com/snowflakedb/snowpark-python/blob/v1.26.0/snowpark-python/src/snowflake/snowpark/modin/plugin/extensions/io_overrides.py#L304-L322)

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 {‘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 (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={‘method’: ‘zstd’, ‘dict_data’: my_compression_dict}.

Returns:

  • DataFrame if iterator=False and chunksize=None, else SAS7BDATReader

  • or XportReader

Examples

>>> df = pd.read_sas("sas_data.sas7bdat")
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