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B �5�g] � @ s d dl mZ d dlZd dlmZ d dlZd dlZd dlm Z m Z d dl m Z mZmZ d dlmZ d dlmZmZmZmZmZmZmZ d dlm Z m Z d d l m Z d d l m!Z! d d l"m#Z#m$Z$ er�d dl%Z%e G d d � d e$��Z&dddd�dd�Z'G dd� de#�Z(dS )� )� annotationsN)� TYPE_CHECKING)�lib�missing)� ArrayLike�Dtype�type_t)�function)� is_bool_dtype�is_float�is_float_dtype�is_integer_dtype� is_list_like�is_numeric_dtype� pandas_dtype)�ExtensionDtype�register_extension_dtype)�isna)�ops)�BaseMaskedArray�BaseMaskedDtypec @ s� e Zd ZdZdZedd�dd��Zedd�dd ��Zed d�d d ��Ze d d�dd��Z dd�dd�Z edd�dd��Z edd�dd��Z ddd�dd�Zd S ) � BooleanDtypeaf Extension dtype for boolean data. .. versionadded:: 1.0.0 .. warning:: BooleanDtype is considered experimental. The implementation and parts of the API may change without warning. Attributes ---------- None Methods ------- None Examples -------- >>> pd.BooleanDtype() BooleanDtype �boolean�type)�returnc C s t jS )N)�np�bool_)�self� r �P/home/digitalm-up/venv/lib/python3.7/site-packages/pandas/core/arrays/boolean.pyr K s zBooleanDtype.type�strc C s dS )N�br )r r r r �kindO s zBooleanDtype.kindznp.dtypec C s t �d�S )N�bool)r �dtype)r r r r � numpy_dtypeS s zBooleanDtype.numpy_dtypeztype_t[BooleanArray]c C s t S )zq Return the array type associated with this dtype. Returns ------- type )� BooleanArray)�clsr r r �construct_array_typeW s z!BooleanDtype.construct_array_typec C s dS )Nr r )r r r r �__repr__b s zBooleanDtype.__repr__r# c C s dS )NTr )r r r r � _is_booleane s zBooleanDtype._is_booleanc C s dS )NTr )r r r r � _is_numerici s zBooleanDtype._is_numericz$pyarrow.Array | pyarrow.ChunkedArrayr& )�arrayr c C s" ddl }|j|�� kr(td|j� d���t||j�r<|g}n|j}g }x�|D ]�}|�� }|jj |jt |�d|d g|j d�j dd�}|j dkr�|jj |jt |�d|d g|j d�j dd�}| }ntjt |�td �}t||�} |�| � qLW |�sttjg tjd �tjg tjd ��S t�|�S dS ) zI Construct BooleanArray from pyarrow Array/ChunkedArray. r Nz$Expected array of boolean type, got z instead� )�offsetF)Zzero_copy_only)r$ )�pyarrowr r � TypeError� isinstanceZArray�chunksZbuffersr& Z from_buffers�lenr. �to_numpyZ null_countr �zerosr# �appendr, Z_concat_same_type) r r, r/ r2 �resultsZarrZbuflist�data�maskZbool_arrr r r �__from_arrow__m s0 zBooleanDtype.__from_arrow__N)�__name__� __module__� __qualname__�__doc__�name�propertyr r" r% � classmethodr( r) r* r+ r: r r r r r - s r Fr# z tuple[np.ndarray, np.ndarray])�copyr c C sN t | t�rD|dk rtd��| j| j } }|r<| �� } |�� }| |fS d}t | tj�rp| jtj krp|rl| �� } �nt | tj�r�t | j�r�t | �}tj t | �td�}| | �t�|| < t�|| �| j�| | k�s�td��|} n�tj| td�}tj|dd�}d}|d| k�r td��t |�}tj t | �td�} || �t�| | < ||k�r�t�| | �t�|| �t�k��s�td��|dk�r�|dk�r�tj t | �td�}np|dk�r�|}n`t |tj��r�|jtj k�r�|dk �r�||B }n|�r |�� }n tj|td�}|dk �r ||B }| jd k�r2td ��|jd k�rFtd ��| |fS ) a Coerce the input values array to numpy arrays with a mask. Parameters ---------- values : 1D list-like mask : bool 1D array, optional copy : bool, default False if True, copy the input Returns ------- tuple of (values, mask) Nz'cannot pass mask for BooleanArray input)r$ z Need to pass bool-like valuesT)�skipna)Zfloating�integerzmixed-integer-float)r �emptyr- z values must be a 1D list-likezmask must be a 1D list-like)r1 r& � ValueError�_data�_maskrB r �ndarrayr$ r r r r5 r3 r# �astype�allr0 �asarray�objectr Z infer_dtype�floatr, �ndim)�valuesr9 rB Z mask_valuesZ values_boolZ values_objectZinferred_dtypeZ integer_liker r r �coerce_to_array� sd rQ c s` e Zd ZdZdZdddddhZdd d d d hZdBd d dd�� fdd� Zedd�dd��Z e ddd�ddd d�dd��Z e ddddd �d ddd d d d �d d!��Z e jejee jfZd"d#d$�d%d&�Zd'd�d(d)�ZdCdd+d,�� fd-d.� Zd d�d/d0�Zd*d1�dd1�d2d3�Zd*d1�dd1�d4d5�Zd6d7� Zd8d9� Zd:d;� Z d*d1�d#dd<�� fd=d>�Z d#d?�d@dA�Z � Z S )Dr& aZ Array of boolean (True/False) data with missing values. This is a pandas Extension array for boolean data, under the hood represented by 2 numpy arrays: a boolean array with the data and a boolean array with the mask (True indicating missing). BooleanArray implements Kleene logic (sometimes called three-value logic) for logical operations. See :ref:`boolean.kleene` for more. To construct an BooleanArray from generic array-like input, use :func:`pandas.array` specifying ``dtype="boolean"`` (see examples below). .. versionadded:: 1.0.0 .. warning:: BooleanArray is considered experimental. The implementation and parts of the API may change without warning. Parameters ---------- values : numpy.ndarray A 1-d boolean-dtype array with the data. mask : numpy.ndarray A 1-d boolean-dtype array indicating missing values (True indicates missing). copy : bool, default False Whether to copy the `values` and `mask` arrays. Attributes ---------- None Methods ------- None Returns ------- BooleanArray Examples -------- Create an BooleanArray with :func:`pandas.array`: >>> pd.array([True, False, None], dtype="boolean") <BooleanArray> [True, False, <NA>] Length: 3, dtype: boolean F�True�TRUE�true�1z1.0�False�FALSE�false�0z0.0z np.ndarrayr# )rP r9 rB c s> t |tj�r|jtjks td��t� | _t� j |||d� d S )NzIvalues should be boolean numpy array. Use the 'pd.array' function instead)rB ) r1 r rI r$ r r0 r �_dtype�super�__init__)r rP r9 rB )� __class__r r r\ ) s zBooleanArray.__init__r )r c C s | j S )N)rZ )r r r r r$ 2 s zBooleanArray.dtypeN)r$ rB z Dtype | None)r$ rB r c C s* |r|dkst �t||d�\}}t||�S )Nr )rB )�AssertionErrorrQ r& )r' �scalarsr$ rB rP r9 r r r �_from_sequence6 s zBooleanArray._from_sequence)r$ rB � true_values� false_valuesz list[str]zlist[str] | None)�stringsr$ rB ra rb r c sP | j �|p g ��| j�|p g �� � �fdd���fdd�|D �}| j|||d�S )Nc s6 t | �r | S | �krdS | � kr$dS t| � d���d S )NTFz cannot be cast to bool)r rF )�s)�false_values_union�true_values_unionr r � map_stringL s z:BooleanArray._from_sequence_of_strings.<locals>.map_stringc s g | ] }� |��qS r r )�.0�x)rg r r � <listcomp>V s z:BooleanArray._from_sequence_of_strings.<locals>.<listcomp>)r$ rB )� _TRUE_VALUES�union� _FALSE_VALUESr` )r' rc r$ rB ra rb r_ r )re rg rf r �_from_sequence_of_strings? s z&BooleanArray._from_sequence_of_stringsznp.ufuncr )�ufunc�methodc s |dkrt d��|�dd�}x&|| D ]}t|| jtf �s&tS q&W tj| ||f|�|�}|tk rf|S tj t | �t d�� g }x8|D ]0}t|t�r�� |j O � |� |j� q�|� |� q�W � fdd��t||�||�}t|t�r�t�fdd �|D �� n�|�S d S ) N�reducez%The 'reduce' method is not supported.�outr )r$ c s* t | j�r � �� }t| |�S tj| � < | S )N)r r$ rB r& r �nan)ri �m)r9 r r � reconstructw s z1BooleanArray.__array_ufunc__.<locals>.reconstructc 3 s | ]}� |�V qd S )Nr )rh ri )ru r r � <genexpr>� s z/BooleanArray.__array_ufunc__.<locals>.<genexpr>)�NotImplementedError�getr1 �_HANDLED_TYPESr& �NotImplementedr Z!maybe_dispatch_ufunc_to_dunder_opr r5 r3 r# rH r6 rG �getattr�tuple) r ro rp �inputs�kwargsrr ri �resultZinputs2r )r9 ru r �__array_ufunc__[ s, z BooleanArray.__array_ufunc__z tuple[np.ndarray, np.ndarray]c C s t |�S )N)rQ )r �valuer r r �_coerce_to_array� s z BooleanArray._coerce_to_arrayTr )rB r c s� t |�}t|t�r t� �||�S t|�rH| jr8td��n| jj||d�S t |�r^| jr^td��| j }t |�rrt j }| j||dd�S )a� Cast to a NumPy array or ExtensionArray with 'dtype'. Parameters ---------- dtype : str or dtype Typecode or data-type to which the array is cast. copy : bool, default True Whether to copy the data, even if not necessary. If False, a copy is made only if the old dtype does not match the new dtype. Returns ------- ndarray or ExtensionArray NumPy ndarray, BooleanArray or IntegerArray with 'dtype' for its dtype. Raises ------ TypeError if incompatible type with an BooleanDtype, equivalent of same_kind casting z cannot convert float NaN to bool)rB z cannot convert NA to integerF)r$ �na_valuerB )r r1 r r[ rJ r Z_hasnarF rG r Z _na_valuer r rs r4 )r r$ rB r� )r] r r rJ � s zBooleanArray.astypec C s | j �� }d|| j< |S )a= Return values for sorting. Returns ------- ndarray The transformed values should maintain the ordering between values within the array. See Also -------- ExtensionArray.argsort : Return the indices that would sort this array. ���)rG rB rH )r r8 r r r �_values_for_argsort� s z BooleanArray._values_for_argsort)rC c K sl |� dd� t�d|� | j�� }t�|| jd� |�� }|rB|S |s\t | �dks\| j�� s`|S | j j S dS )a8 Return whether any element is True. Returns False unless there is at least one element that is True. By default, NAs are skipped. If ``skipna=False`` is specified and missing values are present, similar :ref:`Kleene logic <boolean.kleene>` is used as for logical operations. Parameters ---------- skipna : bool, default True Exclude NA values. If the entire array is NA and `skipna` is True, then the result will be False, as for an empty array. If `skipna` is False, the result will still be True if there is at least one element that is True, otherwise NA will be returned if there are NA's present. **kwargs : any, default None Additional keywords have no effect but might be accepted for compatibility with NumPy. Returns ------- bool or :attr:`pandas.NA` See Also -------- numpy.any : Numpy version of this method. BooleanArray.all : Return whether all elements are True. Examples -------- The result indicates whether any element is True (and by default skips NAs): >>> pd.array([True, False, True]).any() True >>> pd.array([True, False, pd.NA]).any() True >>> pd.array([False, False, pd.NA]).any() False >>> pd.array([], dtype="boolean").any() False >>> pd.array([pd.NA], dtype="boolean").any() False With ``skipna=False``, the result can be NA if this is logically required (whether ``pd.NA`` is True or False influences the result): >>> pd.array([True, False, pd.NA]).any(skipna=False) True >>> pd.array([False, False, pd.NA]).any(skipna=False) <NA> �axisNr Fr ) �pop�nvZ validate_anyrG rB r �putmaskrH �anyr3 r$ r� )r rC r~ rP r r r r r� � s 6 zBooleanArray.anyc K sl |� dd� t�d|� | j�� }t�|| jd� |�� }|rB|S |r\t | �dks\| j� � s`|S | j j S dS )a� Return whether all elements are True. Returns True unless there is at least one element that is False. By default, NAs are skipped. If ``skipna=False`` is specified and missing values are present, similar :ref:`Kleene logic <boolean.kleene>` is used as for logical operations. Parameters ---------- skipna : bool, default True Exclude NA values. If the entire array is NA and `skipna` is True, then the result will be True, as for an empty array. If `skipna` is False, the result will still be False if there is at least one element that is False, otherwise NA will be returned if there are NA's present. **kwargs : any, default None Additional keywords have no effect but might be accepted for compatibility with NumPy. Returns ------- bool or :attr:`pandas.NA` See Also -------- numpy.all : Numpy version of this method. BooleanArray.any : Return whether any element is True. Examples -------- The result indicates whether any element is True (and by default skips NAs): >>> pd.array([True, True, pd.NA]).all() True >>> pd.array([True, False, pd.NA]).all() False >>> pd.array([], dtype="boolean").all() True >>> pd.array([pd.NA], dtype="boolean").all() True With ``skipna=False``, the result can be NA if this is logically required (whether ``pd.NA`` is True or False influences the result): >>> pd.array([True, True, pd.NA]).all(skipna=False) <NA> >>> pd.array([True, False, pd.NA]).all(skipna=False) False r� Nr Tr ) r� r� Z validate_allrG rB r r� rH rK r3 r� r$ r� )r rC r~ rP r r r r rK s 4 zBooleanArray.allc C sJ |j dkst�t|t�}t�|�}d }|r:|j|j }}nNt|�rtt j |dd�}|j dkrbt d��t |dd�\}}nt|t j�r�|�� }|r�|tjk r�t�|�s�tdt|�j � d ���|s�t| �t|�kr�td ��|j d kr�t�| j|| j|�\}}nJ|j d k�r t�| j|| j|�\}}n$|j d k�r@t�| j|| j|�\}}t||�S )N> �or_�rand_�xor�ror_�rxor�and_r# )r$ r- z(can only perform ops with 1-d structuresF)rB z+'other' should be pandas.NA or a bool. Got z instead.z Lengths must match to compare> r� r� > r� r� > r� r� )r; r^ r1 r& r Z is_scalarrG rH r r rL rO rw rQ r �item� libmissing�NAZis_boolr0 r r3 rF r Z kleene_orZ kleene_andZ kleene_xor)r �other�opZother_is_booleanarrayZother_is_scalarr9 r r r r �_logical_methodT s2 z BooleanArray._logical_methodc C s ddl m}m} t|||f�r"tS d }t|t�r@|j|j }}n<t|�r|t � |�}|j dkrdt d��t | �t |�kr|td��|tjkr�t �| j�}t �| j�}ndt�� �8 t�ddt� t jdd�� || j|�}W d Q R X W d Q R X |d kr�| j�� }n | j|B }t||d d �S ) Nr )� FloatingArray� IntegerArrayr- z(can only perform ops with 1-d structuresz Lengths must match to compare�ignoreZ elementwise)rK F)rB )Z pandas.arraysr� r� r1 rz r& rG rH r r rL rO rw r3 rF r� r� Z zeros_likeZ ones_like�warnings�catch_warnings�filterwarnings� FutureWarning�errstaterB )r r� r� r� r� r9 r r r r � _cmp_methody s. zBooleanArray._cmp_methodc C s@ d }|j }t|t�r$|j|j }}n<t|�r`t�|�}|jdkrHt d��t | �t |�kr`t d��|d kr�| j}|t j kr�|dO }n | j|B }|t j kr�|dkr�d}nd}tjt | j�|d�}n@|d kr�t|tj�r�t|�}tjd d �� || j|�}W d Q R X |d k�r0|\}}| �|||d �| �|||d�fS | �||||�S )Nr- z(can only perform ops with 1-d structureszLengths must matchT> �mod�pow�floordiv�rpow�rmod� rfloordivZint8r# )r$ > r� r� r� )rK �divmodr� r� )r; r1 r& rG rH r r rL rO rw r3 rF r� r� r5 r r# r� �_maybe_mask_result) r r� r� r9 �op_namer$ r �divr� r r r � _arith_method� s: zBooleanArray._arith_method)r? rC c s8 |dkr t | |�f d|i|��S t� j|fd|i|��S )N> rK r� rC )r{ r[ �_reduce)r r? rC r~ )r] r r r� � s zBooleanArray._reduce)r� c C s| t |�st|�s|dkr2ddlm} |||dd�S t|�rHt||dd�S t|�rjddlm} |||dd�S tj ||< |S dS )z� Parameters ---------- result : array-like mask : array-like bool other : scalar or array-like op_name : str )Zrtruediv�truedivr )r� F)rB )r� N) r r Zpandas.core.arraysr� r r& r r� r rs )r r r9 r� r� r� r� r r r r� � s z BooleanArray._maybe_mask_result)F)T) r; r< r= r> Z_internal_fill_valuerk rm r\ r@ r$ rA r` rn r rI �numbers�Numberr# r ry r� r� rJ r� r� rK r� r� r� r� r� � __classcell__r r )r] r r& � s2 4 -0DC%*1r& )NF))� __future__r r� �typingr r� �numpyr Z pandas._libsr r r� Zpandas._typingr r r Zpandas.compat.numpyr r� Zpandas.core.dtypes.commonr r r r r r r Zpandas.core.dtypes.dtypesr r Zpandas.core.dtypes.missingr Z pandas.corer Zpandas.core.arrays.maskedr r r/ r rQ r& r r r r �<module> s$ $ jV
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