A>iSrSSKJr SSKJr SSKJr SSKrSSKJ r SSK J r SSK J r SS KJr SS KJr SS KJrJr \(aSS KJr \ "S 5S\ R.4SSjj5rSSSjjrg)zio on the clipboard) annotations)StringIO) TYPE_CHECKINGN)lib) set_module)find_stack_level)check_dtype_backend) ABCDataFrame) get_optionoption_context) DtypeBackendpandasz\s+c BURSS5nUb/UR5RSS5S:wa [S5e[ U5 SS KJn SS KJn U"5nURURS5=(d [S 55nUSS RS 5SSSSnUVs1sH"oRS5RS5iM$ n n[!U5S:a|[!U 5S:XamU R5S:waYSn[!US5[!USRS55- n U S:wa$UR#S[%['U 555 O%[)U[*5(d[-SU<S35e[!U5S:aURS5cSUS'OA[!U5S:a2URS5S:Xa[.R0"S[35S9 U"[5U54XS.UD6$![a GNf=fs snf)aN Read text from clipboard and pass to :func:`~pandas.read_csv`. Parses clipboard contents similar to how CSV files are parsed using :func:`~pandas.read_csv`. Parameters ---------- sep : str, default '\\s+' A string or regex delimiter. The default of ``'\\s+'`` denotes one or more whitespace characters. dtype_backend : {'numpy_nullable', 'pyarrow'} Back-end data type applied to the resultant :class:`DataFrame` (still experimental). If not specified, the default behavior is to not use nullable data types. If specified, the behavior is as follows: * ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame` * ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype` :class:`DataFrame` .. versionadded:: 2.0 **kwargs See :func:`~pandas.read_csv` for the full argument list. Returns ------- DataFrame A parsed :class:`~pandas.DataFrame` object. See Also -------- DataFrame.to_clipboard : Copy object to the system clipboard. read_csv : Read a comma-separated values (csv) file into DataFrame. read_fwf : Read a table of fixed-width formatted lines into DataFrame. Examples -------- >>> df = pd.DataFrame([[1, 2, 3], [4, 5, 6]], columns=["A", "B", "C"]) >>> df.to_clipboard() # doctest: +SKIP >>> pd.read_clipboard() # doctest: +SKIP A B C 0 1 2 3 1 4 5 6 encodingutf-8N-utf8z3reading from clipboard only supports utf-8 encodingr) clipboard_get)read_csvzdisplay.encodingi'   z index_colzsep=z must be a stringenginepythonczIread_clipboard with regex separator does not work properly with c engine. stacklevel)sep dtype_backend)poplowerreplaceNotImplementedErrorr pandas.io.clipboardrpandas.io.parsersrdecodegetr AttributeErrorsplitlstripcountlen setdefaultlistrange isinstancestr ValueErrorwarningswarnrr) r#r$kwargsrrrtextlinesxcounts index_lengths S/var/www/html/land-tabula/venv/lib/python3.13/site-packages/pandas/io/clipboards.pyread_clipboardrAsjzz*g.H 0 8 8b AV K!"WXX &1* ?D {{6::j1SZ@R5ST %L  t $Sb )#2 .E27 7Ahhsm!!$'F 7 5zA~#f+*vzz|q/@58}s58??5+A'BB 1    k4l0C+D E S ! !DC6!2344 3x!| 8,4#x SA&**X.#5 W') HTN S SF SSK    8s$2H 4)H HHc URSS5nUb/UR5RSS5S:wa [S5eSS KJn UcS nU(a?UcS n[ 5nUR"U4USS .UD6 UR5nU"U5 gUb[R"S[5S9 [U[5(a([SS5 UR "S0UD6nSSS5 O [#U5nU"W5 g![a [R"S [5S9 Nzf=f!,(df  ND=f)ab Attempt to write text representation of object to the system clipboard The clipboard can be then pasted into Excel for example. Parameters ---------- obj : the object to write to the clipboard excel : bool, defaults to True if True, use the provided separator, writing in a csv format for allowing easy pasting into excel. if False, write a string representation of the object to the clipboard sep : optional, defaults to tab other keywords are passed to to_csv Notes ----- Requirements for your platform - Linux: xclip, or xsel (with PyQt4 modules) - Windows: - OS X: rrNrrrz&clipboard only supports utf-8 encodingr) clipboard_setTr)r#rzAto_clipboard in excel mode requires a single character separator.r!z7to_clipboard with excel=False ignores the sep argument.zdisplay.max_colwidth)r%r&r'r7r)rCrto_csvgetvalue TypeErrorr8r9rr5r r to_stringr6) objexcelr#r:rrCbufr;objstrs r@ to_clipboardrMs*2zz*g.H 0 8 8b AV KABB1 }  {*C JJs @g @ @<<>D $    E') #|$$ 2D 9]],V,F: 9S&#  MMS+-  : 9s=DD4'D10D14 E)r#r6r$zDtypeBackend | lib.NoDefault)TN)rJz bool | Noner#z str | NonereturnNone)__doc__ __future__riortypingrr8 pandas._libsrpandas.util._decoratorsrpandas.util._exceptionsrpandas.util._validatorsr pandas.core.dtypes.genericr rr r pandas._typingr no_defaultrArMrDr@r\s" .473 + H25..jT jT/jTjT\7;AA)3A Ar[