Mh>(SrSSKJr SSKJrJr SSKrSSKJ r SSK J r J r J r JrJr SSKJr SSKJrJr \(aSS KJr SS KJr SS KJr SS jrSS jrSSjrSSjrSSjrSSjr SSSjjr!SS Sjjr"S!Sjr#Sr$S"Sjr%S#Sjr&S$Sjr'g)%z$ Low-dependency indexing utilities. ) annotations) TYPE_CHECKINGAnyN)lib) is_array_like is_bool_dtype is_integeris_integer_dtype is_list_like)ExtensionDtype)ABCIndex ABCSeries) AnyArrayLike) DataFrame)Indexc[R"UR5=(aG [R"UR5=(a [R"UR5$)z Check if a slice object can be interpreted as a positional indexer. Parameters ---------- slc : slice Returns ------- bool Notes ----- A valid positional slice may also be interpreted as a label-based slice depending on the index being sliced. )ris_int_or_nonestartstopstep)slcs L/var/www/html/env/lib/python3.13/site-packages/pandas/core/indexers/utils.pyis_valid_positional_slicer&sI$ 399% )   sxx ( )   sxx (c[U5=(a- [U[5=(a [U5[L(+$)z| Check if we have a list-like indexer that is *not* a NamedTuple. Parameters ---------- key : object Returns ------- bool )r isinstancetupletype)keys ris_list_like_indexerr >s-   Xje&<&WcRWAW!XXrcUS:Xa[U5(ag[U[5(a![U5U:Xa[ SU55$g)z Return True if we are all scalar indexers. Parameters ---------- indexer : object ndim : int Number of dimensions in the object being indexed. Returns ------- bool Tc38# UHn[U5v M g7fN)r ).0xs r $is_scalar_indexer..`s2'Q:a=='sF)r rrlenall)indexerndims ris_scalar_indexerr-NsD qyZ(('5!!c'ld&:2'222 rc[U5(a[U5(dg[U[5(dU4n[ SU55$)zb Check if we have an empty indexer. Parameters ---------- indexer : object Returns ------- bool Tc3# UH4n[U[R5=(a [U5S:Hv M6 g7f)rN)rnpndarrayr))r%idxs rr'#is_empty_indexer..ts+Pz#rzz*)r r)rrany)r+s ris_empty_indexerr5ds?GS\\ gu % %* PP PPrcSn[U[R[45(a[ U5(a[ U5[ U5:waUR S:Xa[U[5(a[R"U5n[U[R5(a;UR[R:XaUR5[ U5:Xd [S5e[ U5(dSnU$[U[5(aU[ U5(aE[ U5[X5:waUR S:Xa [S5e[ U5(dSnU$)a6 Validate that value and indexer are the same length. An special-case is allowed for when the indexer is a boolean array and the number of true values equals the length of ``value``. In this case, no exception is raised. Parameters ---------- indexer : sequence Key for the setitem. value : array-like Value for the setitem. values : array-like Values being set into. Returns ------- bool Whether this is an empty listlike setting which is a no-op. Raises ------ ValueError When the indexer is an ndarray or list and the lengths don't match. Fr"zKcannot set using a list-like indexer with a different length than the valueTzGcannot set using a slice indexer with a different length than the value)rr0r1listr r)r,arraydtypebool_sum ValueErrorslicelength_of_indexer)r+valuevaluesno_ops rcheck_setitem_lengthsrB{s6 E'BJJ-..   7|s5z)fkkQ.>gt,, hhw/Gw 33 1 U3$Aw<< L GU # #   5z.w??FKKSTDT 6u:: Lrc[U5(aHUR5nUS:aSUS3n[U5eUR5nXA:a [ S5egg)a Perform bounds-checking for an indexer. -1 is allowed for indicating missing values. Parameters ---------- indices : ndarray n : int Length of the array being indexed. Raises ------ ValueError Examples -------- >>> validate_indices(np.array([1, 2]), 3) # OK >>> validate_indices(np.array([1, -2]), 3) Traceback (most recent call last): ... ValueError: negative dimensions are not allowed >>> validate_indices(np.array([1, 2, 3]), 3) Traceback (most recent call last): ... IndexError: indices are out-of-bounds >>> validate_indices(np.array([-1, -1]), 0) # OK >>> validate_indices(np.array([0, 1]), 0) Traceback (most recent call last): ... IndexError: indices are out-of-bounds z-'indices' contains values less than allowed (z < -1)indices are out-of-boundsN)r)minr<max IndexError)indicesnmin_idxmsgmax_idxs rvalidate_indicesrNs^J 7||++- R<A'&QCS/ !++- <89 9 rc[U[5(aH[R"U5n[ U5S:Xa#[R "S[R S9$US:nUR5(aUR5nX==U- ss'U(a*X:US:-nUR5(a [S5eU$)a Attempt to convert indices into valid, positive indices. If we have negative indices, translate to positive here. If we have indices that are out-of-bounds, raise an IndexError. Parameters ---------- indices : array-like Array of indices that we are to convert. n : int Number of elements in the array that we are indexing. verify : bool, default True Check that all entries are between 0 and n - 1, inclusive. Returns ------- array-like An array-like of positive indices that correspond to the ones that were passed in initially to this function. Raises ------ IndexError One of the converted indices either exceeded the number of, elements (specified by `n`), or was still negative. rr9rE) rr7r0r8r)emptyintpr4copyrH)rIrJverifymasks rmaybe_convert_indicesrVs8'4  ((7# w<1 88ARWW- - Q;D xxzz,,.    1- 88::89 9 NrcUb[U[5(ay[U5nURnURnUR nUcSnO US:aX2- nUbXB:aUnO US:aXB- nUcSnOUS:a US-US-pCU*nXC- U-S- U-$[U[ [[R[45(aZ[U[5(a[R"U5nUR[:XaUR5$[U5$[U[5(a&URUR- UR -$[!U5(dg[#S5e)zD Return the expected length of target[indexer] Returns ------- int rr"z%cannot find the length of the indexer)rr=r)rrrrr r0r1r7r8r9boolr;ranger AssertionError)r+target target_lenrrrs rr>r>"sIj%88[  |||| =E QY  E <4,D AX  D <D AX(EAI45D t#a'D00 Gi2::tD E E gt $ $hhw'G ==D ;;= 7| GU # # w}},== !' * * @ AArcN[R"U5S:a [S5eg)z Helper function to disallow multi-dimensional indexing on 1D Series/Index. GH#27125 indexer like idx[:, None] expands dim, but we cannot do that and keep an index, so we used to return ndarray, which was deprecated in GH#30588. r"zzMulti-dimensional indexing (e.g. `obj[:, None]`) is no longer supported. Convert to a numpy array before indexing instead.N)r0r,r<)results rdisallow_ndim_indexingr_Ls, wwv K  rc[U5S:Xa=[US[5(a%[U[5(a [ S5eUS$U$)z} If we have a length-1 tuple/list that contains a slice, unpack to just the slice. Notes ----- The list case is deprecated. r"rzYIndexing with a single-item list containing a slice is not allowed. Pass a tuple instead.)r)rr=r7r<)tups r unpack_1tuplerb[sP 3x1}CFE22 c4 >  1v JrcUR(a.[UR5[U5:wa [S5eg[UR U5S5[UR5:wa [S5eg)a Checks if a key used as indexer has the same length as the columns it is associated with. Parameters ---------- columns : Index The columns of the DataFrame to index. key : A list-like of keys to index with. value : DataFrame The value to set for the keys. Raises ------ ValueError: If the length of key is not equal to the number of columns in value or if the number of columns referenced by key is not equal to number of columns. z"Columns must be same length as keyrN) is_uniquer)columnsr<get_indexer_non_unique)rerr?s rcheck_key_lengthrgssm" u}} S )AB B * w--c215 6#emm:L LAB B Mrc[U5S:a#US[LaUSSnOUS[LaUSSn[U5S:a [S5eUSnU$)z' Possibly unpack arr[..., n] to arr[n] r"rNrDztoo many indices for array.)r)EllipsisrH)items runpack_tuple_and_ellipsesrksb 4y1} 7h 8D "X !9D 4y1}677 7D KrcSSKJn [U5(a[U[5(aU$OU$[ U5(d:U"U5n[ U5S:Xa#[R"/[RS9nURn[U5(a[U[5(aUR[SS9nO[R"U[S9n[ U5[ U5:wa#[S[ U5S[ U535eU$[!U5(a&[R"U[RS9nU$[S 5e!["an[#S5UeS nAff=f) a Check if `indexer` is a valid array indexer for `array`. For a boolean mask, `array` and `indexer` are checked to have the same length. The dtype is validated, and if it is an integer or boolean ExtensionArray, it is checked if there are missing values present, and it is converted to the appropriate numpy array. Other dtypes will raise an error. Non-array indexers (integer, slice, Ellipsis, tuples, ..) are passed through as is. Parameters ---------- array : array-like The array that is being indexed (only used for the length). indexer : array-like or list-like The array-like that's used to index. List-like input that is not yet a numpy array or an ExtensionArray is converted to one. Other input types are passed through as is. Returns ------- numpy.ndarray The validated indexer as a numpy array that can be used to index. Raises ------ IndexError When the lengths don't match. ValueError When `indexer` cannot be converted to a numpy ndarray to index (e.g. presence of missing values). See Also -------- api.types.is_bool_dtype : Check if `key` is of boolean dtype. Examples -------- When checking a boolean mask, a boolean ndarray is returned when the arguments are all valid. >>> mask = pd.array([True, False]) >>> arr = pd.array([1, 2]) >>> pd.api.indexers.check_array_indexer(arr, mask) array([ True, False]) An IndexError is raised when the lengths don't match. >>> mask = pd.array([True, False, True]) >>> pd.api.indexers.check_array_indexer(arr, mask) Traceback (most recent call last): ... IndexError: Boolean index has wrong length: 3 instead of 2. NA values in a boolean array are treated as False. >>> mask = pd.array([True, pd.NA]) >>> pd.api.indexers.check_array_indexer(arr, mask) array([ True, False]) A numpy boolean mask will get passed through (if the length is correct): >>> mask = np.array([True, False]) >>> pd.api.indexers.check_array_indexer(arr, mask) array([ True, False]) Similarly for integer indexers, an integer ndarray is returned when it is a valid indexer, otherwise an error is (for integer indexers, a matching length is not required): >>> indexer = pd.array([0, 2], dtype="Int64") >>> arr = pd.array([1, 2, 3]) >>> pd.api.indexers.check_array_indexer(arr, indexer) array([0, 2]) >>> indexer = pd.array([0, pd.NA], dtype="Int64") >>> pd.api.indexers.check_array_indexer(arr, indexer) Traceback (most recent call last): ... ValueError: Cannot index with an integer indexer containing NA values For non-integer/boolean dtypes, an appropriate error is raised: >>> indexer = np.array([0., 2.], dtype="float64") >>> pd.api.indexers.check_array_indexer(arr, indexer) Traceback (most recent call last): ... IndexError: arrays used as indices must be of integer or boolean type r)r8rPF)r9na_valuez Boolean index has wrong length: z instead of z9Cannot index with an integer indexer containing NA valuesNz9arrays used as indices must be of integer or boolean type)pandas.core.constructionr8r rrrr)r0rRr9rr to_numpyrXasarrayrHr r<)r8r+pd_arrayr9errs rcheck_array_indexerrssVx; G gu % %N &  ! !7# w<1 hhr1G MMEU e^ , ,&&TE&BGjj5G w<3u: %2w<. SZL:  & N %  jj8G NTUU  K  s)#E E4# E//E4)rr=returnrX)rtrX)r,intrtrX)rI np.ndarrayrJrurtNone)T)rJrurTrXrtrvr$)rtru)rtrw)rerr?rrtrw)rjr)r8rr+rrtr)(__doc__ __future__rtypingrrnumpyr0 pandas._libsrpandas.core.dtypes.commonrrr r r pandas.core.dtypes.dtypesr pandas.core.dtypes.genericr rpandas._typingrpandas.core.framerpandas.core.indexes.baserrr r-r5rBrNrVr>r_rbrgrkrsrrrs# 5 ++. 0 Y ,Q.=@-:h,f'BT  0C4,Fr