w:iSrSSKJr SSKJrJr SSKJrJr SSK J r SSK J r SSK Jr \(aSSKJr SS KJr SS KJrJrJrJr SS KJr "S S \5r\SSSSSSS.SSjj5r\SSSSSSS.SSjj5r\ "\ SS-S9SSSSSSS.SSjj5rg)z# Read SAS sas7bdat or xport files. ) annotations)ABCabstractmethod) TYPE_CHECKINGoverload)doc) _shared_docs)stringify_path)Hashable) TracebackType)CompressionOptionsFilePath ReadBufferSelf) DataFramech\rSrSrSr\S S Sjj5r\S Sj5rS SjrS Sjr Sr g) ReaderBase#z6 Protocol for XportReader and SAS7BDATReader classes. NcgN)selfnrowss Z/srv/projetos/modelo_ml_acdoc/venv/lib/python3.13/site-packages/pandas/io/sas/sasreader.pyreadReaderBase.read( cgrrrs rcloseReaderBase.close,rrcU$rrr s r __enter__ReaderBase.__enter__0s rc$UR5 gr)r!)rexc_type exc_value tracebacks r__exit__ReaderBase.__exit__3s rrr)r int | Nonereturnr)r-None)r-r)r'ztype[BaseException] | Noner(zBaseException | Noner)zTracebackType | Noner-r.) __name__ __module__ __qualname____firstlineno____doc__rrr!r$r*__static_attributes__rrrrr#s_    ,((   rr.)formatindexencoding chunksizeiterator compressionfilepath_or_buffercgrrr;r5r6r7r8r9r:s rread_sasr><rcgrrr=s rr>r>Jr?rdecompression_options)rANFinfercUcfSn[U5n[U[5(d [U5eUR 5nSU;aSnO SU;aSnO[S[ U535eUR 5S:XaSS KJn U "UUUUUS 9n O0UR 5S:XaSS KJ n U "UUUUUS 9n O [S 5eU(dU(aU $U  U R5sSSS5 $!,(df  g=f) a 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. {decompression_options} Returns ------- DataFrame if iterator=False and chunksize=None, else SAS7BDATReader or XportReader Examples -------- >>> df = pd.read_sas("sas_data.sas7bdat") # doctest: +SKIP NzVIf this is a buffer object rather than a string name, you must specify a format stringz.xptxportz .sas7bdatsas7bdatz2unable to infer format of SAS file from filename: r) XportReader)r6r7r8r:)SAS7BDATReaderzunknown SAS format) r isinstancestr ValueErrorlowerreprpandas.io.sas.sas_xportrFpandas.io.sas.sas7bdatrGr) r;r5r6r7r8r9r:buffer_error_msgfnamerFreaderrGs rr>r>XsX~ C ,,>?,c22-. ."((* U?F E !FDT%[MR  ||~ 7 #   : %9 #  -..9 {{} s C++ C9)r;FilePath | ReadBuffer[bytes]r5 str | Noner6Hashable | Noner7rSr8intr9boolr:r r-r)r;rRr5rSr6rTr7rSr8r.r9rVr:r r-DataFrame | ReaderBase)r;rRr5rSr6rTr7rSr8r,r9rVr:r r-rW)r3 __future__rabcrrtypingrrpandas.util._decoratorsrpandas.core.shared_docsr pandas.io.commonr collections.abcr typesr pandas._typingr rrrpandasrrr>rrrrbs# (0+(#!2  &) 4          $      &) 4          $    <(?@CWWX! &-Y4Y Y  Y  Y  YY$YYYYr