Ë
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nñúhÅ> ã ó d Z ddlmZ ddlmZmZ ddlZddlm Z ddl
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m Z m Z m Z mZmZ ddlmZ ddlmZmZ erdd lmZ dd
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lmZ dd lmZ dd Zdd Z ddZ ddZ ddZ d dZ d d dZ!d d dZ"d!dZ#d Z$d"dZ%d#dZ&d$dZ'y)%z$
|
Low-dependency indexing utilities.
|
é )Ú annotations)Ú TYPE_CHECKINGÚAnyN)Úlib)Ú is_array_likeÚ is_bool_dtypeÚ
|
is_integerÚis_integer_dtypeÚ is_list_like)ÚExtensionDtype)ÚABCIndexÚ ABCSeries)Ú AnyArrayLike)Ú DataFrame)ÚIndexc óÄ t j | j « xr@ t j | j « xr t j | j « S )a(
|
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.
|
)r Úis_int_or_noneÚstartÚstopÚstep)Úslcs úMH:\Change_password\venv_build\Lib\site-packages\pandas/core/indexers/utils.pyÚis_valid_positional_slicer & sI ô$ ×Ñ399Ó%ò )Ü × Ñ sxxÓ (ò )ä × Ñ sxxÓ (ðó c ód t | « xr$ t | t « xr t | « t u S )z
|
Check if we have a list-like indexer that is *not* a NamedTuple.
|
|
Parameters
|
----------
|
key : object
|
|
Returns
|
-------
|
bool
|
)r Ú
|
isinstanceÚtupleÚtype)Úkeys r Úis_list_like_indexerr > s- ô Ó Ò X¤j°´eÓ&<Ò&WÄÀcÃÔRWÐAWÐ!XÐXr c ó |dk( r t | « ryt | t « r t | « |k( rt d | D « « S y)zÓ
|
Return True if we are all scalar indexers.
|
|
Parameters
|
----------
|
indexer : object
|
ndim : int
|
Number of dimensions in the object being indexed.
|
|
Returns
|
-------
|
bool
|
é Tc 3 ó2 K | ] }t |« y w©N)r )Ú.0Úxs r ú <genexpr>z$is_scalar_indexer.<locals>.<genexpr>` s è ø Ò2 Q:a=Ñ2ùs F)r r r ÚlenÚall)ÚindexerÚndims r Úis_scalar_indexerr, N s> ð qyZ Ô(àÜ'5Ô!¤c¨'£l°dÒ&:ÜÑ2¨'Ô2Ó2Ð2Ø r c óz t | « r t | « syt | t « s| f} t d | D « « S )z
|
Check if we have an empty indexer.
|
|
Parameters
|
----------
|
indexer : object
|
|
Returns
|
-------
|
bool
|
Tc 3 óp K | ]. }t |t j « xr t |« d k( 0 yw)r N)r ÚnpÚndarrayr( )r% Úidxs r r' z#is_empty_indexer.<locals>.<genexpr>t s+ è ø ÒPÀz#rzzÓ*Ò<¬s°3«x¸1©}Ó<ÑPùs 46)r r( r r Úany)r* s r Úis_empty_indexerr3 d s7 ô GÔ ¤S¨¤\ØÜ guÔ %Ø*Ü ÑPÈÔPÓ PÐPr c ó d}t | t j t f« rÃt |« r¶t | « t |« k7 r|j dk( rt | t « rt j | « } t | t j « r9| j t j k( r | j « t |« k( s t d« t | « sd}|S t | t « rJt |« r?t |« t | |« k7 r|j dk( r t d« t |« sd}|S )a
|
Validate that value and indexer are the same length.
|
|
An special-case is allowed for when the indexer is a boolean array
|
and the number of true values equals the length of ``value``. In
|
this case, no exception is raised.
|
|
Parameters
|
----------
|
indexer : sequence
|
Key for the setitem.
|
value : array-like
|
Value for the setitem.
|
values : array-like
|
Values being set into.
|
|
Returns
|
-------
|
bool
|
Whether this is an empty listlike setting which is a no-op.
|
|
Raises
|
------
|
ValueError
|
When the indexer is an ndarray or list and the lengths don't match.
|
Fr" zKcannot set using a list-like indexer with a different length than the valueTzGcannot set using a slice indexer with a different length than the value)r r/ r0 Úlistr r( r+ ÚarrayÚdtypeÚbool_ÚsumÚ
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ValueErrorÚsliceÚlength_of_indexer)r* ÚvalueÚvaluesÚno_ops r Úcheck_setitem_lengthsr@ { s
|
ð6 Eä'BJJ¬Ð-Ô.ô Ô Ü7|s 5zÒ)¨f¯k©k¸QÒ.>ä g¤tÔ,Ü hh wÓ /Gä w¬¯
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©
|
Ô3Ø ¬¯©Ò1Ø ¬¨U«Ò3ä$ðAóð ô w<Ø ð Lô
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GUÔ #Ü Ô Ü5zÔ .¨w¸Ó ?Ò?ÀFÇKÁKÐSTÒDTä ð6óð ô u:Ø à Lr c ó¨ t | « rG| j « }|dk rd| d}t |« | j « }||k\ r t d« yy)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
|
éÿÿÿÿz-'indices' contains values less than allowed (z < -1)úindices are out-of-boundsN)r( Úminr: ÚmaxÚ
|
IndexError)ÚindicesÚnÚmin_idxÚmsgÚmax_idxs r Úvalidate_indicesrL » s^ ôJ 7|Ø++-Ø R<ØAÀ'ÀÈ&ÐQCÜ S/Ð !à++-Ø a<Ü Ð 8Ó9Ð 9ð ð r c ój t | t « rHt j | « } t | « dk( r%t j
|
dt j ¬« S | dk }|j « r | j « } | |xx |z cc< |r&| |k\ | dk z }|j « r t d« | S )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.
|
r ©r7 rC )
|
r r5 r/ r6 r( ÚemptyÚintpr2 ÚcopyrF )rG rH ÚverifyÚmasks r Úmaybe_convert_indicesrT ï s ô8 '4Ô Ü((7Ó#Ü w<1Ò ô 88A¤R§W¡WÔ-Ð -à Q;DØ xxzØ,,.Ø Ñ á Ø1 ¨1¡Ñ-Ø 88:Ü Ð 8Ó9Ð 9Ø Nr c ó¨ |t | t « rwt |« }| j }| j }| j
|
}|d}n
|
|dk r||z }|||kD r|}n
|
|dk r||z }|d}n|dk r |dz |dz }}| }||z
|
|z dz
|
|z S t | t t t j t f« rSt | t « rt j | « } | j t k( r| j « S t | « S t | t « r&| j | j z
|
| j
|
z S t! | « syt# d« )zX
|
Return the expected length of target[indexer]
|
|
Returns
|
-------
|
int
|
r r" z%cannot find the length of the indexer)r r; r( r r r r r r/ r0 r5 r6 r7 Úboolr9 Úranger ÚAssertionError)r* ÚtargetÚ
|
target_lenr r r s r r< r< " sD ð Ðj¨´%Ô 8Ü[
|
Ø Ø||Ø||Ø =ØEØ QYØ ZÑ EØ <4 *Ò,Ø DØ AXØ JÑ DØ <ØDØ AXØ ( E¨A¡I4EØ5DØu tÑ# aÑ'¨DÑ0Ð0Ü Gi¬´2·:±:¼tÐ DÔ EÜ gtÔ $ÜhhwÓ'Gà ==DÒ à;;=Ð Ü7|ÐÜ GUÔ #Ø w}}Ñ,°· ± Ñ=Ð=Ü ! 'Ô *ØÜ
|
Ð@Ó
|
AÐAr c óJ t j | « dkD r t d« y)zú
|
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)r/ r+ r: )Úresults r Údisallow_ndim_indexingr] L s, ô
|
wwvÒÜð Kó
|
ð
|
ð r c ó t | « dk( r3t | d t « r t | t « r t d« | d S | S )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" r zYIndexing with a single-item list containing a slice is not allowed. Pass a tuple instead.)r( r r; r5 r: )Útups r Ú unpack_1tupler` [ sJ ô 3x1} C¨¡F¬EÔ2ô c4Ô ä ð>óð ð
|
1v Ø Jr c óò | j r-t |j « t |« k7 r t d« yt | j |« d « t |j « k7 r t d« y)aÿ
|
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 keyr N)Ú is_uniquer( Úcolumnsr: Úget_indexer_non_unique)rc r r= s r Úcheck_key_lengthre s sm ð" ×ÒÜ u}}Ó ¤ S£Ò )Ü Ð AÓBÐ Bð *ô w×-Ñ-¨cÓ2°1Ñ5Ó 6¼#¸e¿m¹mÓ:LÒ LÜ Ð AÓBÐ Bð Mr c ó t | « dkD r!| d t u r| dd } n| d t u r| dd } t | « dkD r t d« | d } | S )z/
|
Possibly unpack arr[..., n] to arr[n]
|
r" r NrB ztoo many indices for array.)r( ÚEllipsisrF )Úitems r Úunpack_tuple_and_ellipsesri sb ô 4y1}à 7hÑ Ø8DØ "XÑ !Ø9Dä
|
4y1}ÜÐ6Ó7Ð7à 7DØ Kr c óº ddl m} t |« rt |t « r|S |S t |« s; ||« }t |« dk( r%t j g t j ¬« }|j }t |« rt |t « r|j t d¬« }nt j |t ¬« }t |« t | « k7 r#t dt |« dt | « « |S t! |« r( t j |t j ¬« }|S t d
|
« # t" $ r}t# d« |d }~ww xY w) aë
|
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 )r6 rN F)r7 Úna_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)Úpandas.core.constructionr6 r r r r r( r/ rP r7 r r Úto_numpyrV ÚasarrayrF r
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r Úpandas.core.dtypes.dtypesr Úpandas.core.dtypes.genericr r Úpandas._typingr Úpandas.core.framer Úpandas.core.indexes.baser r r r, r3 r@ rL rT r< r] r` re ri rq © r r ú<module>r s ðñõ #÷ó
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