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For example we have Int8Dtype to represent signed int 8s. The attributes name & type are set when these subclasses are created. �str)�returnc C s$ | j r dnd}|� dd| j � d�S )N�U� �Int� zDtype())�is_unsigned_integer�itemsize)�self�sign� r' �P/home/digitalm-up/venv/lib/python3.7/site-packages/pandas/core/arrays/integer.py�__repr__: s z_IntegerDtype.__repr__�boolc C s | j dkS )N�i)�kind)r% r' r' r( �is_signed_integer> s z _IntegerDtype.is_signed_integerc C s | j dkS )N�u)r, )r% r' r' r( r# B s z!_IntegerDtype.is_unsigned_integerc C s dS )NTr' )r% r' r' r( � _is_numericF s z_IntegerDtype._is_numericztype[IntegerArray]c C s t S )zq Return the array type associated with this dtype. Returns ------- type )� IntegerArray)�clsr' r' r( �construct_array_typeJ s z"_IntegerDtype.construct_array_typezlist[DtypeObj]zDtypeObj | None)�dtypesr c C sp t dd� |D ��sd S t�dd� |D �g �}t�|tj�rFtt|� S t�|tj�rlddlm } |t|� S d S )Nc s s@ | ]8}t |t�p6t |tj�o6t�|tj�p6t�|tj�V qd S )N)� isinstancer �np�dtype� issubdtype�numberZbool_)�.0�tr' r' r( � <genexpr>X s z2_IntegerDtype._get_common_dtype.<locals>.<genexpr>c S s g | ]}t |t�r|jn|�qS r' )r4 r � numpy_dtype)r9 r: r' r' r( � <listcomp>f s z3_IntegerDtype._get_common_dtype.<locals>.<listcomp>r )�FLOAT_STR_TO_DTYPE) �allr5 Zfind_common_typer7 �integer�INT_STR_TO_DTYPEr �floatingZpandas.core.arrays.floatingr> )r% r3 Znp_dtyper> r' r' r( �_get_common_dtypeU s z _IntegerDtype._get_common_dtypeN) �__name__� __module__� __qualname__�__doc__r) r r- r# �propertyr/ � classmethodr2 rC r' r' r' r( r 0 s r r* )�copyc C st y| j |d|d�S tk rn } z@| j ||d�}|| k�� r@|S td| j� dt�|�� ��|�W dd}~X Y nX dS )z} Safely cast the values to the dtype if they are equivalent, meaning floats must be equivalent to the ints. �safe)ZcastingrJ )rJ z"cannot safely cast non-equivalent z to N)�astype� TypeErrorr? r6 r5 )�valuesr6 rJ �errZcastedr' r' r( � safe_castv s rP Fz tuple[np.ndarray, np.ndarray])rJ r c C sT |dkr"t | d�r"t| j�r"| j}|dk r�t|t�rP|�d�sH|�d�rP|�� }tt|�t �s�yt tt �|�� }W n2 t k r� } zt d|� ��|�W dd}~X Y nX t| t�r�| j| j } }|dk r�| j|jdd�} |r�| �� } |�� }| |fS t j| |d�} t| ��r\tj| dd �}|d k�r@t �t| ��} | �t j� n|d k�r�t | j� d ���nJt | ��r�t|��r�t j| t |d �} n$t| ��s�t | ��s�t | j� d ���|dk�r�t | �}nt|�t| �k�s�t!�| j"dk�s�t d��|j"dk�s�t d��|dk�rt �d�}n|j}|�#� �r>| �� } d| |< t$| |dd�} nt$| |dd�} | |fS )a- Coerce the input values array to numpy arrays with a mask Parameters ---------- values : 1D list-like dtype : integer dtype mask : bool 1D array, optional copy : bool, default False if True, copy the input Returns ------- tuple of (values, mask) Nr6 r! ZUIntzinvalid dtype specified F)rJ T)�skipna�empty)rB r@ z mixed-integerz integer-nazmixed-integer-floatz' cannot be converted to an IntegerDtype)r6 rJ � z values must be a 1D list-likezmask must be a 1D list-like�int64)%�hasattrr r6 r4 r � startswith�lower� issubclass�typer rA r5 �KeyError� ValueErrorr0 �_data�_maskrL r< rJ �arrayr r Z infer_dtyperR �len�fill�nanrM r �intr r �AssertionError�ndim�anyrP )rN r6 �maskrJ rO Z inferred_typer' r' r( �coerce_to_array� s` " rg c s e Zd ZdZdZedd�dd��Zd0ddd d �� fd d � Zed dd�dd d d�dd��Z ed dd�dd d d�dd��Z dd�dd�Z d1d dd�� fdd � Z dd�d d �Z d d � Zdd!d"�� fd#d$� Zdd!d"�� fd%d&� Zdd'�� fd(d)� Zdd'�� fd*d+� Zd,d-�d.d/�Z� ZS )2r0 a> Array of integer (optional missing) values. .. versionchanged:: 1.0.0 Now uses :attr:`pandas.NA` as the missing value rather than :attr:`numpy.nan`. .. warning:: IntegerArray is currently experimental, and its API or internal implementation may change without warning. We represent an IntegerArray with 2 numpy arrays: - data: contains a numpy integer array of the appropriate dtype - mask: a boolean array holding a mask on the data, True is missing To construct an IntegerArray from generic array-like input, use :func:`pandas.array` with one of the integer dtypes (see examples). See :ref:`integer_na` for more. Parameters ---------- values : numpy.ndarray A 1-d integer-dtype array. mask : numpy.ndarray A 1-d boolean-dtype array indicating missing values. copy : bool, default False Whether to copy the `values` and `mask`. Attributes ---------- None Methods ------- None Returns ------- IntegerArray Examples -------- Create an IntegerArray with :func:`pandas.array`. >>> int_array = pd.array([1, None, 3], dtype=pd.Int32Dtype()) >>> int_array <IntegerArray> [1, <NA>, 3] Length: 3, dtype: Int32 String aliases for the dtypes are also available. They are capitalized. >>> pd.array([1, None, 3], dtype='Int32') <IntegerArray> [1, <NA>, 3] Length: 3, dtype: Int32 >>> pd.array([1, None, 3], dtype='UInt16') <IntegerArray> [1, <NA>, 3] Length: 3, dtype: UInt16 rS r )r c C s t t| jj� S )N)rA r r\ r6 )r% r' r' r( r6 3 s zIntegerArray.dtypeFz np.ndarrayr* )rN rf rJ c s6 t |tj�r|jjdks td��t� j|||d� d S )N)r+ r. zIvalues should be integer numpy array. Use the 'pd.array' function instead)rJ )r4 r5 Zndarrayr6 r, rM �super�__init__)r% rN rf rJ )� __class__r' r( ri 7 s zIntegerArray.__init__N)r6 rJ z Dtype | None)r6 rJ r c C s t |||d�\}}t||�S )N)r6 rJ )rg r0 )r1 �scalarsr6 rJ rN rf r' r' r( �_from_sequence? s zIntegerArray._from_sequencec C s t |dd�}| j|||d�S )N�raise)�errors)r6 rJ )r rl )r1 �stringsr6 rJ rk r' r' r( �_from_sequence_of_stringsF s z&IntegerArray._from_sequence_of_stringsz tuple[np.ndarray, np.ndarray]c C s t || jd�S )N)r6 )rg r6 )r% �valuer' r' r( �_coerce_to_arrayM s z IntegerArray._coerce_to_arrayTr )rJ r c s\ t |�}t|t�r"t� j||d�S t|�r2tj}nt|�rFt� d�}nt 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 IntegerDtype, equivalent of same_kind casting )rJ ZNaTF)r6 �na_valuerJ ) r r4 r rh rL r r5 ra r Z datetime64r Z no_defaultZto_numpy)r% r6 rJ rs )rj r' r( rL P s zIntegerArray.astypec C s* | j �� }| j�� r&|�� 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. rS )r\ rJ r] re �min)r% �datar' r' r( �_values_for_argsortz s z IntegerArray._values_for_argsortc C s. ddl m} d }t|t�r*|j|j }}n<t|�rft�|�}|j dkrNt d��t | �t |�krft d��|t jkr�tj| jjdd�}tj| jjdd�}nnt�� �` t�dd t� tjdd ��$ t| jd |j� d ��}||�}W d Q R X |tkr�t| j||�}W d Q R X |d k�r| j�� }n | j|B }|||�S ) Nr )� BooleanArrayrS z(can only perform ops with 1-d structuresz Lengths must match to comparer* )r6 �ignoreZ elementwise)r? �__) �pandas.core.arraysrw r4 r r\ r] r r5 Zasarrayrd �NotImplementedErrorr_ r[ � libmissingZNAZzeros�shapeZones�warnings�catch_warnings�filterwarnings� FutureWarningZerrstate�getattrrD �NotImplementedr rJ )r% �other�oprw rf �result�methodr' r' r( � _cmp_method� s0 zIntegerArray._cmp_methodr )rQ � min_countc s t �d|� t� jd||d�S )Nr' �sum)rQ r� )�nvZ validate_sumrh �_reduce)r% rQ r� �kwargs)rj r' r( r� � s zIntegerArray.sumc s t �d|� t� jd||d�S )Nr' �prod)rQ r� )r� Z validate_prodrh r� )r% rQ r� r� )rj r' r( r� � s zIntegerArray.prod)rQ c s t �d|� t� jd|d�S )Nr' rt )rQ )r� Z validate_minrh r� )r% rQ r� )rj r' r( rt � s zIntegerArray.minc s t �d|� t� jd|d�S )Nr' �max)rQ )r� Z validate_maxrh r� )r% rQ r� )rj r' r( r� � s zIntegerArray.maxr )�op_namec C sl t |�st|�s|dkr2ddlm} |||dd�S |jdkrZddlm} t||< |�|�S t| �||dd�S )z� Parameters ---------- result : array-like mask : array-like bool other : scalar or array-like op_name : str )Zrtruediv�truedivr )� FloatingArrayF)rJ ztimedelta64[ns])�TimedeltaArray) r r rz r� r6 r� r Z _simple_newrY )r% r� rf r� r� r� r� r' r' r( �_maybe_mask_result� s z IntegerArray._maybe_mask_result)F)T)rD rE rF rG Z_internal_fill_valuer r6 ri rI rl rp rr rL rv r� r� r� rt r� r� � __classcell__r' r' )rj r( r0 � s" B *-r0 z� An ExtensionDtype for {dtype} integer data. .. versionchanged:: 1.0.0 Now uses :attr:`pandas.NA` as its missing value, rather than :attr:`numpy.nan`. Attributes ---------- None Methods ------- None c @ s" e Zd ZejZdZejdd�Z dS )� Int8DtypeZInt8�int8)r6 N) rD rE rF r5 r� rY �name�_dtype_docstring�formatrG r' r' r' r( r� � s r� c @ s" e Zd ZejZdZejdd�Z dS )� Int16DtypeZInt16�int16)r6 N) rD rE rF r5 r� rY r� r� r� rG r' r' r' r( r� s r� c @ s" e Zd ZejZdZejdd�Z dS )� Int32DtypeZInt32�int32)r6 N) rD rE rF r5 r� rY r� r� r� rG r' r' r' r( r� s r� c @ s" e Zd ZejZdZejdd�Z dS )� Int64DtypeZInt64rT )r6 N) rD rE rF r5 rT rY r� r� r� rG r' r' r' r( r� s r� c @ s" e Zd ZejZdZejdd�Z dS )� UInt8DtypeZUInt8�uint8)r6 N) rD rE rF r5 r� rY r� r� r� rG r' r' r' r( r� s r� c @ s" e Zd ZejZdZejdd�Z dS )� UInt16DtypeZUInt16�uint16)r6 N) rD rE rF r5 r� rY r� r� r� rG r' r' r' r( r� s r� c @ s" e Zd ZejZdZejdd�Z dS )� UInt32DtypeZUInt32�uint32)r6 N) rD rE rF r5 r� rY r� r� r� rG r' r' r' r( r� $ s r� c @ s" e Zd ZejZdZejdd�Z dS )� UInt64DtypeZUInt64�uint64)r6 N) rD rE rF r5 r� rY r� r� r� rG r' r' r' r( r� + s r� )r� r� r� rT r� r� r� r� zdict[str, _IntegerDtype]rA )NF):� __future__r r~ �numpyr5 Z pandas._libsr r r r| Zpandas._typingr r r Zpandas.compat.numpyr r� Zpandas.util._decoratorsr Zpandas.core.dtypes.baser r Zpandas.core.dtypes.commonr r r r r r r r Zpandas.core.dtypes.missingr Zpandas.core.arrays.maskedr r Zpandas.core.arrays.numericr r Zpandas.core.opsr Zpandas.core.tools.numericr r rP rg r0 r� r� r� r� r� r� r� r� r� rA �__annotations__r' r' r' r( �<module> sZ ( Fa
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