`Vg UddlmZddlZddlmZddlmZddlm Z m Z Gdde Z Gdd e Z d Z eGd d e ZeGd de ZeGdde ZeGdde ZeGdde ZeGdde ZeGdde ZeGdde ZeeeeeeeedZded<y)) annotationsN)register_extension_dtype)is_integer_dtype) NumericArray NumericDtypeceZdZdZej ej ZeZ e ddZ e dZ e ddZ y) 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. ctS)zq Return the array type associated with this dtype. Returns ------- type ) IntegerArrayclss [/var/www/html/hubwallet-dev/venv/lib/python3.12/site-packages/pandas/core/arrays/integer.pyconstruct_array_typez!IntegerDtype.construct_array_types ctS)N)INT_STR_TO_DTYPEr s r_str_to_dtype_mappingz"IntegerDtype._str_to_dtype_mapping&src  |j|d|S#t$ra}|j||}||k(jr|cYd}~Std|jdt j||d}~wwxYw)z Safely cast the values to the given dtype. "safe" in this context means the casting is lossless. e.g. if 'values' has a floating dtype, each value must be an integer. safe)castingcopy)rNz"cannot safely cast non-equivalent z to )astype TypeErroralldtypenp)r valuesrrerrcasteds r _safe_castzIntegerDtype._safe_cast*s ==T=B B ]]5t]4F& %%' 4V\\N$rxxPUFWX   s  B'A;B /A;;BN)returnztype[IntegerArray])r np.ndarrayrznp.dtyperboolr!r")__name__ __module__ __qualname____doc__rrint64_default_np_dtyper_checker classmethodrrr rrr r s]!*H  rr c eZdZdZeZdZdZdZy)r 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 [1, , 3] Length: 3, dtype: Int32 String aliases for the dtypes are also available. They are capitalized. >>> pd.array([1, None, 3], dtype='Int32') [1, , 3] Length: 3, dtype: Int32 >>> pd.array([1, None, 3], dtype='UInt16') [1, , 3] Length: 3, dtype: UInt16 rN) r$r%r&r'r _dtype_cls_internal_fill_value _truthy_value _falsey_valuer,rrr r >s"AFJMMrr z An ExtensionDtype for {dtype} integer data. .. versionchanged:: 1.0.0 Now uses :attr:`pandas.NA` as its missing value, rather than :attr:`numpy.nan`. Attributes ---------- None Methods ------- None cLeZdZejZdZejdZ y) Int8DtypeInt8int8rN) r$r%r&rr6typename_dtype_docstringformatr'r,rrr4r4s# 77D D%%F%3Grr4cLeZdZejZdZejdZ y) Int16DtypeInt16int16r7N) r$r%r&rr?r8r9r:r;r'r,rrr=r=# 88D D%%G%4Grr=cLeZdZejZdZejdZ y) Int32DtypeInt32int32r7N) r$r%r&rrDr8r9r:r;r'r,rrrBrBr@rrBcLeZdZejZdZejdZ y) Int64DtypeInt64r(r7N) r$r%r&rr(r8r9r:r;r'r,rrrFrFr@rrFcLeZdZejZdZejdZ y) UInt8DtypeUInt8uint8r7N) r$r%r&rrKr8r9r:r;r'r,rrrIrIr@rrIcLeZdZejZdZejdZ y) UInt16DtypeUInt16uint16r7N) r$r%r&rrOr8r9r:r;r'r,rrrMrM# 99D D%%H%5GrrMcLeZdZejZdZejdZ y) UInt32DtypeUInt32uint32r7N) r$r%r&rrTr8r9r:r;r'r,rrrRrRrPrrRcLeZdZejZdZejdZ y) UInt64DtypeUInt64uint64r7N) r$r%r&rrXr8r9r:r;r'r,rrrVrVrPrrV)r6r?rDr(rKrOrTrXzdict[str, IntegerDtype]r) __future__rnumpyrpandas.core.dtypes.baserpandas.core.dtypes.commonrpandas.core.arrays.numericrrr r r:r4r=rBrFrIrMrRrVr__annotations__r,rrr_sL"<6 -<-`J<JZ(4 44 555 555 555 555 6,66 6,66 6,66 K \ \ \ \mmm -) r