]j^FSrSSKJr SSKrSSKJrJr SSKJrJ r J r J r J r J r SSKrSSKJr SSKrSSKrSSKJrJrJrJrJrJr SSKrSSKJr SS KJr SS K J!r!J"r" SS K#J$r$J%r%J&r&J'r'J(r( SS K)J*r* SS K+J,r, \(aSSK-J.r.J/r/J0r0J1r1J2r2J3r3 SSK4J5r5 Sr6Sr7SASjr8Sr9Sr:SBSjr;SBSjrSCSjr?\SDSESjj5r@\SDSFSjj5r@SGSFSjjr@SGSHSjjrASrBSISjrCSBS jrDSBS!jrESJS"jrFSKS#jrGS$rHS%rIS&rJ\SLS'j5rK\SMS(j5rKSGSNS)jjrK\"S*5rL\SOS+j5rM\SPS,j5rMSQS-jrMS.rNSRS/jrO\RSSSTS0jj5rQSUS1jrR0\RS2_\RS3_\RS4_\RS5_\RS6_\RS2_\RS2_\RS7_\RS7_\RS8_\RS8_\RS9_\RS9_\RS:_\RS:_\RS;_\RS;_\RS3\RS3\RS4\RS4\RS<\RS<\RS=\RS=0EriSVS>jrjSWS?jrkS@rlg)Xzh Misc tools for implementing data structures Note: pandas.core.common is *not* part of the public API. ) annotationsN)abc defaultdict)Callable Collection GeneratorHashableIterableSequence)partial) TYPE_CHECKINGAny ConcatenateTypeVarcastoverload)lib)'construct_1d_object_array_from_listlike) is_bool_dtype is_integer)ABCExtensionArrayABCIndex ABCMultiIndexABCNumpyExtensionArray ABCSeries)iterable_not_string) Expression) AnyArrayLike ArrayLikeNpDtypeP RandomStateT)Indexc#t# UH,n[U5(a[U5ShvN M(Uv M. gN7f)z Flatten an arbitrarily nested sequence. Parameters ---------- line : sequence The non string sequence to flatten Notes ----- This doesn't consider strings sequences. Returns ------- flattened : generator N)rflatten)lineelements O/home/mande/repo/quber/.venv/lib/python3.13/site-packages/pandas/core/common.pyr&r&Ds2" w ' 'w' ' 'M  's $868cUSRnUSSHnURU:waSn U$M U$![a Sn U$f=f)Nr)name ValueError)objsr,objs r)consensus_name_attrr0\si 7<not_none..s 34CCC4s rKargss r)not_nonerSs 44 33rBc&[SU55$)z7 Returns a boolean indicating if any argument is None. c3(# UHoSLv M g7frJrKrLs r)rOany_none..+dsd{danyrQs r)any_noner[ +d+ ++rBc&[SU55$)z9 Returns a boolean indicating if all arguments are None. c3(# UHoSLv M g7frJrKrLs r)rOall_none..rWrXallrQs r)all_nonerbr\rBc&[SU55$)z; Returns a boolean indicating if any argument is not None. c3(# UHoSLv M g7frJrKrLs r)rOany_not_none../$3$$rXrYrQs r) any_not_nonerg /$/ //rBc&[SU55$)z= Returns a boolean indicating if all arguments are not None. c3(# UHoSLv M g7frJrKrLs r)rOall_not_none..rfrXr`rQs r) all_not_nonerlrhrBc&[SU55$)z3 Returns the count of arguments that are not None. c3(# UHoSLv M g7frJrK)rMxs r)rO!count_not_none..s+d}drX)sumrQs r)count_not_nonerrr\rBcgrJrKvaluesr6s r)asarray_tuplesafervsrBcgrJrKrts r)rvrvsSVrBc[U[[45(d[US5(d [U5nOB[U[5(a UR $[U[ 5(a UR $[U[5(a%U[R[4;a [U5$[R"XS9n[URR[ 5(a[R"U[S9nUR"S:Xa&UVs/sHn[U5PM nn[U5nU$![a [U5s$f=fs snf)N __array__r6)r3r:tuplehasattrr_valuesrr4r7objectrr8r- issubclassr6r<strndim)rur6resultros r)rvrvs ve} - -1M1Mf FH % %~~ FI & &~~&$Ebjj&-A$A6v>>?F0&,,##S))F&1 {{a$*+Fq%(F+8@ M ? 7v>> ?,s6E EEEc[U[[45(aU/n[U[[R 45(d [U5n[XS9nU$![ a U/nNf=f)z Transform label or iterable of labels to array, for use in Index. Parameters ---------- dtype : dtype If specified, use as dtype of the resulting array, otherwise infer. Returns ------- array rz)r3rr|r:r4r5 TypeErrorrv)labelsr6rlabelss r)index_labels_to_arrayrsi&3,'' ftRZZ0 1 1 &\F 4G N  XF s A A+*A+cHUb[U[[45(dU/$U$rJ)r3r|r:r/s r)maybe_make_listr+s# z#t}==u JrBc[U[R5(a*[U[R5(d [ U5$[ [ U5nU$)z: If obj is Iterable but not list-like, consume into list. )r3rr Sizedr:rrrs r)maybe_iterable_to_listr1s@#s||$$ZSYY-G-GCy z3 C JrBc[U[5=(a8 URSL=(a# URSL=(a URSL$)z We have a null slice. Nr3slicestartstopsteprs r) is_null_slicer;sH 3  II   HH   HH  rBc[U[5=(aC URSL=(a. URSL=(a URUR:H$)z6 We have an empty slice, e.g. no values are selected. N)r3rrrrs r)is_empty_slicerGsL 3 " IIT ! " HHD  " II ! rBc#p# UH,n[U[5=(a [U5(+v M. g7f)z3 Find non-trivial slices in "line": yields a bool. 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Returns ------- mapping : a collections.abc.Mapping subclass or other constructor a callable object that can accept an iterator to create the desired Mapping. See Also -------- DataFrame.to_dict Series.to_dict zunsupported type: z/to_dict() only accepts initialized defaultdicts) inspectisclassr3rr default_factoryr<rrMappingr)intos r)standardize_mappingrsy* ??4 dK ( (;(<(<= =Dz dCKK ( (,TF344 {IJJ KrBcgrJrKstates r) random_statersEHrBcgrJrKrs r)rrs rBc[U5(d9[U[R[RR 45(a[RR U5$[U[RR 5(aU$[U[RR5(aU$Uc[R$[S5e)a9 Helper function for processing random_state arguments. Parameters ---------- state : int, array-like, BitGenerator, Generator, np.random.RandomState, None. If receives an int, array-like, or BitGenerator, passes to np.random.RandomState() as seed. If receives an np.random RandomState or Generator, just returns that unchanged. If receives `None`, returns np.random. If receives anything else, raises an informative ValueError. Default None. Returns ------- np.random.RandomState or np.random.Generator. If state is None, returns np.random zdrandom_state must be an integer, array-like, a BitGenerator, Generator, a numpy RandomState, or None) rr3r4r5random BitGeneratorr"rr-rs r)rrs(%Jurzz299;Q;Q.RSSyy$$U++ E29900 1 1 E299.. / / yy +  rB_TcgrJrKr/rrRrs r)piper rBcgrJrKrs r)rrrrBc[U[5(a%UupEXS;aUS3n[U5eXU'U"U0UD6$U"U/UQ70UD6$)a# Apply a function ``func`` to object ``obj`` either by passing obj as the first argument to the function or, in the case that the func is a tuple, interpret the first element of the tuple as a function and pass the obj to that function as a keyword argument whose key is the value of the second element of the tuple. Parameters ---------- func : callable or tuple of (callable, str) Function to apply to this object or, alternatively, a ``(callable, data_keyword)`` tuple where ``data_keyword`` is a string indicating the keyword of ``callable`` that expects the object. *args : iterable, optional Positional arguments passed into ``func``. **kwargs : dict, optional A dictionary of keyword arguments passed into ``func``. Returns ------- object : the return type of ``func``. z/ is both the pipe target and a keyword argument)r3r|r-)r/rrRrfunc_targetmsgs r)rrsa:$   HKLCS/ !vd%f%%C)$)&))rBcb^U4Sjn[T[R[45(aU$T$)zj Returns a function that will map names/labels, dependent if mapper is a dict, Series or just a function. c>UT;aTU$U$rJrK)romappers r)fget_rename_function..fs ;!9 HrB)r3rrr)rrs` r)get_rename_functionrs*  6CKK#;<<1H&HrBc[U[[R[[ [ 45(aU$[U[R5(a [U[5(d [U5$U/$)z Convert list-like or scalar input to list-like. List, numpy and pandas array-like inputs are returned unmodified whereas others are converted to list. ) r3r:r4r5rrrrr r)rus r)convert_to_list_liker&sT&4XyBSTUU FCLL ) )*VS2I2IF| 8OrBc## U(a[X5n[XU5 Uv U(a [XW5 gg!U(a [XW5 ff=f7f)a Temporarily set attribute on an object. Parameters ---------- obj : object Object whose attribute will be modified. attr : str Attribute to modify. value : Any Value to temporarily set attribute to. condition : bool, default True Whether to set the attribute. Provided in order to not have to conditionally use this context manager. Yields ------ object : obj with modified attribute. N)getattrsetattr)r/attrvalue condition old_values r) temp_setattrr5sL*C& 5!*  Cy ) 9 Cy ) sA;AAAc|[U5[U5:wa$[S[U5S[U5S35eg)z; Check the length of data matches the length of the index. zLength of values (z") does not match length of index ()N)r;r-)dataindexs r)require_length_matchrTsI 4yCJ D {E |1   rBrqmaxminrarZmeanprodstdvarmediancumprodcumsumc,[RU5$)z@ if we define an internal function for this argument, return it ) _cython_tableget)rNs r)get_cython_funcr~s   S !!rBc^[U5VVs/sHupUcSU3OUPM snn$s snnf)z If a name is missing then replace it by level_n, where n is the count Parameters ---------- names : list-like list of column names or None values. Returns ------- list list of column names with the None values replaced. level_) enumerate)namesir,s r)fill_missing_namesrs6CLEBR SBRwqDLfQCLd 2BR SS Ss)c~[R"S5nURR5H nX LdM g g)aQ Helper function used in detecting chained assignment. If the pandas object (DataFrame/Series) is a local variable in the caller's frame, it should not be a case of chained assignment or method call. For example: def test(): df = pd.DataFrame(...) df["a"] = 1 # not chained assignment Inside ``df.__setitem__``, we call this function to check whether `df` (`self`) is a local variable in `test` frame (the frame calling setitem). If so, we know it is not a case of chained assignment (even when the refcount of `df` is below the threshold due to optimization of local variables). r{TF)sys _getframef_localsru)r/framevs r)is_local_in_caller_framers6& MM! E ^^ " " $ 8% rB)r>rreturnbool)rr)rint).)ruzArrayLike | list | tuple | zipr6NpDtype | Noner np.ndarray)rur r6rrrrJ)rznp.ndarray | Iterabler6rrr)r/zIterable[T] | TrzCollection[T] | T)r'z abc.Iterablerzabc.Generator[bool, None, None])r'rrr)rnp.random.Generatorrr)rzHint | np.ndarray | np.random.BitGenerator | np.random.RandomState | Nonerznp.random.RandomState)rzRandomState | None) r/rrzCallable[Concatenate[_T, P], T]rRzP.argsrzP.kwargsrr#) r/rrztuple[Callable[..., T], str]rRrrrrr#) r/rrz>Callable[Concatenate[_T, P], T] | tuple[Callable[..., T], str]rRrrrrr#)ruz"Hashable | Iterable | AnyArrayLikerzlist | AnyArrayLike)T)rrrrrzGenerator[None])rr$rNone)rNrrz str | None)rzSequence[Hashable | None]rzlist[Hashable])m__doc__ __future__rbuiltins collectionsrrcollections.abcrrrr r r contextlib functoolsr rrtypingr rrrrrnumpyr4 pandas._libsrpandas.core.dtypes.castrpandas.core.dtypes.commonrrpandas.core.dtypes.genericrrrrrpandas.core.dtypes.inferencerpandas.core.colrpandas._typingrrr r!r"r#pandasr$r&r0rArGrSr[rbrgrlrrrvrrrrrrrrrrrrrrrcontextmanagerrrrqrrrarZnansumrnanmeanrnanprodrnanstdrnanvarr nanmediannanmaxnanminr nancumprodr nancumsumrrrrrKrBr)rs # K=&0 5p,4,,00, DG *3A  V V@<@ !*8:   < "&@ H H  S     F T]   )            &         &* &* H&* &* &*  &*R I  .   **<   LL% LL% LL%FFE  FFE  FFE IIuGGVJJGGVJJFFEIIuFFEIIu IIx!"LL(#$FFEIIuFFEIIuJJ MM9IIxLL(3 :"T"rB