o
    ŀgF                     @  s  U d dl mZ d dlmZ d dlZd dlmZ d dlm	Z	 d dl
mZmZ G dd deZG d	d
 d
eZdZeG dd deZeG dd deZeG dd deZeG dd deZeG dd deZeG dd deZeG dd deZeG dd deZeeje eeje eeje eeje eeje eeje eeje eej e iZ!de"d< dS )    )annotations)ClassVarN)register_extension_dtype)is_integer_dtype)NumericArrayNumericDtypec                   @  sJ   e Zd ZdZeejZeZ	e
dddZe
dddZe
dddZdS )IntegerDtypea'  
    An ExtensionDtype to hold a single size & kind of integer dtype.

    These specific implementations are subclasses of the non-public
    IntegerDtype. For example, we have Int8Dtype to represent signed int 8s.

    The attributes name & type are set when these subclasses are created.
    returntype[IntegerArray]c                 C     t S )zq
        Return the array type associated with this dtype.

        Returns
        -------
        type
        )IntegerArraycls r   N/var/www/html/myenv/lib/python3.10/site-packages/pandas/core/arrays/integer.pyconstruct_array_type   s   	z!IntegerDtype.construct_array_typedict[np.dtype, IntegerDtype]c                 C  r   )N)NUMPY_INT_TO_DTYPEr   r   r   r   _get_dtype_mapping(   s   zIntegerDtype._get_dtype_mappingvalues
np.ndarraydtypenp.dtypecopyboolc              
   C  st   z	|j |d|dW S  ty9 } z$|j ||d}||k r&|W  Y d}~S td|j dt| |d}~ww )z
        Safely cast the values to the given dtype.

        "safe" in this context means the casting is lossless. e.g. if 'values'
        has a floating dtype, each value must be an integer.
        safe)castingr   )r   Nz"cannot safely cast non-equivalent z to )astype	TypeErrorallr   np)r   r   r   r   errcastedr   r   r   
_safe_cast,   s   zIntegerDtype._safe_castN)r	   r
   )r	   r   )r   r   r   r   r   r   r	   r   )__name__
__module____qualname____doc__r    r   int64_default_np_dtyper   _checkerclassmethodr   r   r#   r   r   r   r   r      s    	
r   c                   @  s    e Zd ZdZeZdZdZdZdS )r   a  
    Array of integer (optional missing) values.

    Uses :attr:`pandas.NA` as the missing value.

    .. 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
       r   N)	r$   r%   r&   r'   r   
_dtype_cls_internal_fill_value_truthy_value_falsey_valuer   r   r   r   r   @   s    @r   a  
An ExtensionDtype for {dtype} integer data.

Uses :attr:`pandas.NA` as its missing value, rather than :attr:`numpy.nan`.

Attributes
----------
None

Methods
-------
None

Examples
--------
For Int8Dtype:

>>> ser = pd.Series([2, pd.NA], dtype=pd.Int8Dtype())
>>> ser.dtype
Int8Dtype()

For Int16Dtype:

>>> ser = pd.Series([2, pd.NA], dtype=pd.Int16Dtype())
>>> ser.dtype
Int16Dtype()

For Int32Dtype:

>>> ser = pd.Series([2, pd.NA], dtype=pd.Int32Dtype())
>>> ser.dtype
Int32Dtype()

For Int64Dtype:

>>> ser = pd.Series([2, pd.NA], dtype=pd.Int64Dtype())
>>> ser.dtype
Int64Dtype()

For UInt8Dtype:

>>> ser = pd.Series([2, pd.NA], dtype=pd.UInt8Dtype())
>>> ser.dtype
UInt8Dtype()

For UInt16Dtype:

>>> ser = pd.Series([2, pd.NA], dtype=pd.UInt16Dtype())
>>> ser.dtype
UInt16Dtype()

For UInt32Dtype:

>>> ser = pd.Series([2, pd.NA], dtype=pd.UInt32Dtype())
>>> ser.dtype
UInt32Dtype()

For UInt64Dtype:

>>> ser = pd.Series([2, pd.NA], dtype=pd.UInt64Dtype())
>>> ser.dtype
UInt64Dtype()
c                   @  ,   e Zd ZU ejZdZded< ej	ddZ
dS )	Int8DtypeInt8ClassVar[str]nameint8r   N)r$   r%   r&   r    r6   typer5   __annotations___dtype_docstringformatr'   r   r   r   r   r2         
 r2   c                   @  r1   )
Int16DtypeInt16r4   r5   int16r7   N)r$   r%   r&   r    r?   r8   r5   r9   r:   r;   r'   r   r   r   r   r=      r<   r=   c                   @  r1   )
Int32DtypeInt32r4   r5   int32r7   N)r$   r%   r&   r    rB   r8   r5   r9   r:   r;   r'   r   r   r   r   r@      r<   r@   c                   @  r1   )
Int64DtypeInt64r4   r5   r(   r7   N)r$   r%   r&   r    r(   r8   r5   r9   r:   r;   r'   r   r   r   r   rC      r<   rC   c                   @  r1   )
UInt8DtypeUInt8r4   r5   uint8r7   N)r$   r%   r&   r    rG   r8   r5   r9   r:   r;   r'   r   r   r   r   rE      r<   rE   c                   @  r1   )UInt16DtypeUInt16r4   r5   uint16r7   N)r$   r%   r&   r    rJ   r8   r5   r9   r:   r;   r'   r   r   r   r   rH      r<   rH   c                   @  r1   )UInt32DtypeUInt32r4   r5   uint32r7   N)r$   r%   r&   r    rM   r8   r5   r9   r:   r;   r'   r   r   r   r   rK      r<   rK   c                   @  r1   )UInt64DtypeUInt64r4   r5   uint64r7   N)r$   r%   r&   r    rP   r8   r5   r9   r:   r;   r'   r   r   r   r   rN      r<   rN   r   r   )#
__future__r   typingr   numpyr    pandas.core.dtypes.baser   pandas.core.dtypes.commonr   pandas.core.arrays.numericr   r   r   r   r:   r2   r=   r@   rC   rE   rH   rK   rN   r   r6   r?   rB   r(   rG   rJ   rM   rP   r   r9   r   r   r   r   <module>   sD    0LC