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B �5�g�@ � @ s\ d Z ddlmZ ddlmZ ddlZddlZddlm Z m Z m Z ddl m Z mZmZmZmZmZ ddlmZmZ er�ddlmZ dd lmZ d d d �d d�Zd d�dd�Zdd d�dd�Z dd d�dd�Z d d�dd�Z ddd d �d d �Z d:dd d!�d"d#�Z d$d$d d%�d&d'�Z!d;dd�d(d)�Z"d<dd+�d,d-�Z#d.d/� Z$d0d1d2�d3d4�Z%d5d6d6d7�d8d9�Z&dS )=z$ Low-dependency indexing utilities. � )� annotations)� TYPE_CHECKINGN)�Any� AnyArrayLike� ArrayLike)� is_array_like� is_bool_dtype�is_extension_array_dtype� is_integer�is_integer_dtype� is_list_like)�ABCIndex� ABCSeries)� DataFrame)�Index�slice�bool)�slc�returnc C s& dd� }|| j �o$|| j�o$|| 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. c S s | d kpt | �S )N)r )�val� r �J/home/digitalm-up/venv/lib/python3.7/site-packages/pandas/core/indexers.py�is_int_or_none8 s z1is_valid_positional_slice.<locals>.is_int_or_none)�start�stop�step)r r r r r �is_valid_positional_slice& s r )r c C s t | �o t| t�o t| �tk S )z� Check if we have a list-like indexer that is *not* a NamedTuple. Parameters ---------- key : object Returns ------- bool )r � isinstance�tuple�type)�keyr r r �is_list_like_indexerB s r! �int)�ndimr c C s@ |dkrt | �rdS t| t�r<t| �|kr<tdd� | D ��S dS )z� Return True if we are all scalar indexers. Parameters ---------- indexer : object ndim : int Number of dimensions in the object being indexed. Returns ------- bool � Tc s s@ | ]8}t |�p6t|tj�o6|jt|� ko2d kn V qdS )r$ N)r r �np�ndarrayr# �len)�.0�xr r r � <genexpr>e s z$is_scalar_indexer.<locals>.<genexpr>F)r r r r' �all)�indexerr# r r r �is_scalar_indexerR s r- z np.ndarray)� arr_valuer c C sD t | �rt| �sdS |jdkr@t| t�s.| f} tdd� | D ��S dS )z� Check if we have an empty indexer. Parameters ---------- indexer : object arr_value : np.ndarray Returns ------- bool Tr$ c s s& | ] }t |tj�o t|�d kV qdS )r N)r r% r& r' )r( �idxr r r r* } s z#is_empty_indexer.<locals>.<genexpr>F)r r' r# r r �any)r, r. r r r �is_empty_indexerk s r1 c C s� d}t | tjtf�r�t|�r�t| �t|�kr~|jdkr~t | t�rJt�| �} t | tj�rv| jtj krvt| | �t|�ks~t d��t| �s�d}nBt | t �r�t|�r�t|�t | |�kr�|jdkr�t d��t|�s�d}|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% r& �listr r' r# �array�dtypeZbool_� ValueErrorr �length_of_indexer)r, �value�valuesZno_opr r r �check_setitem_lengths� s* r9 �None)�indices�nr c C sH t | �rD| �� }|dk r,d|� d�}t|��| �� }||krDtd��dS )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)zindices are out-of-boundsN)r' �minr5 �max� IndexError)r; r< �min_idx�msgZmax_idxr r r �validate_indices� s % rC T)r< �verifyc C s� t | t�r0t�| �} t| �dkr0tjdtjd�S | dk }|�� rX| �� } | | |7 < |r|| |k| dk B }|�� 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 )r4 zindices are out-of-bounds) r r2 r% r3 r' �empty�intpr0 �copyr@ )r; r< rD �maskr r r �maybe_convert_indices� s rI r )�targetr7 r c C s< t |j�dko:t | j�dko:|jd | jd ko:|j| jkS )z� Is setting this value into this target overwriting the entire column? Parameters ---------- target : np.ndarray or ExtensionArray value : np.ndarray or ExtensionArray Returns ------- bool r )r' �shape�size)rJ r7 r r r �is_exact_shape_match, s rM c C s, |dk r�t | t�r�t|�}| j}| j}| j}|dkr:d}n|dk rJ||7 }|dksZ||kr`|}n|dk rp||7 }|dkr~d}n |dk r�|d |d }}| }|| | d | S t | tttj t f�r�t | t �r�t� | �} | j t kr�| �� S t| �S t | t��r| j| j | j S t| ��s dS td��dS )zX Return the expected length of target[indexer] Returns ------- int Nr r$ z%cannot find the length of the indexer)r r r' r r r r r r% r& r2 r3 r4 r �sum�ranger! �AssertionError)r, rJ Z target_lenr r r r r r r6 A s< r6 � )� stacklevelc C s" t �| �dkr tjdt|d� dS )a# Helper function to raise the deprecation warning for 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 currently return ndarray, which is deprecated (Deprecation GH#30588). r$ z�Support for multi-dimensional indexing (e.g. `obj[:, None]`) is deprecated and will be removed in a future version. Convert to a numpy array before indexing instead.)rR N)r% r# �warnings�warn� FutureWarning)�resultrR r r r �deprecate_ndim_indexingk s rW c C s@ t | �dkr<t| d t�r<t| t�r4tjdtdd� | 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 z|Indexing with a single-item list containing a slice is deprecated and will raise in a future version. Pass a tuple instead.rQ )rR )r' r r r2 rS rT rU )�tupr r r � unpack_1tuple~ s rY r r )�columnsr7 c C sJ | j r"t|j�t|�krFtd��n$t| �|�d �t|j�krFtd��dS )a� Checks if a key used as indexer has the same length as the columns it is associated with. Parameters ---------- columns : Index The columns of the DataFrame to index. key : A list-like of keys to index with. value : DataFrame The value to set for the keys. Raises ------ ValueError: If the length of key is not equal to the number of columns in value or if the number of columns referenced by key is not equal to number of columns. z"Columns must be same length as keyr N)Z is_uniquer' rZ r5 Zget_indexer_non_unique)rZ r r7 r r r �check_key_length� s r[ r r )r3 r, r c C s ddl m} t|�r$t|t�r(|S n|S t|�sT||�}t|�dkrTtjg tjd�}|j }t |�r�t |�rz|j t dd�}ntj|t d�}t|�t| �kr�tdt|�� dt| �� ���nXt|��rytj|tjd�}W n. tk �r } ztd�|�W d d }~X Y nX ntd ��|S ) 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. .. versionadded:: 1.0.0 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 )r3 )r4 F)r4 Zna_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)Zpandas.core.constructionr3 r r r r r' r% rF r4 r r Zto_numpyr Zasarrayr@ r r5 )r3 r, Zpd_arrayr4 �errr r r �check_array_indexer� s4 ^ r] )T)N)rQ )'�__doc__� __future__r �typingr rS �numpyr% Zpandas._typingr r r Zpandas.core.dtypes.commonr r r r r r Zpandas.core.dtypes.genericr r Zpandas.core.framer Zpandas.core.indexes.baser r r! r- r1 r9 rC rI rM r6 rW rY r[ r] r r r r �<module> s. @43*
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