OwgPUddlmZddlmZddlZddlmZddlm Z ddl m Z m Z Gdde Z Gd d e Zd ZeGd d e ZeGdde Zej$ej&eej$ej(eiZded<y)) annotations)ClassVarN)register_extension_dtype)is_float_dtype) NumericArray NumericDtypeceZdZdZej ej ZeZ e ddZ e ddZ e ddZ y) FloatingDtypea An ExtensionDtype to hold a single size of floating dtype. These specific implementations are subclasses of the non-public FloatingDtype. For example we have Float32Dtype to represent float32. The attributes name & type are set when these subclasses are created. ctS)zq Return the array type associated with this dtype. Returns ------- type ) FloatingArrayclss R/var/www/horilla/myenv/lib/python3.12/site-packages/pandas/core/arrays/floating.pyconstruct_array_typez"FloatingDtype.construct_array_types ctS)N)NUMPY_FLOAT_TO_DTYPEr s r_get_dtype_mappingz FloatingDtype._get_dtype_mapping(s##rc(|j||S)z{ Safely cast the values to the given dtype. "safe" in this context means the casting is lossless. )copy)astype)rvaluesdtypers r _safe_castzFloatingDtype._safe_cast,s}}U}..rN)returnztype[FloatingArray])rdict[np.dtype, FloatingDtype])r np.ndarrayrznp.dtyperboolrr)__name__ __module__ __qualname____doc__nprfloat64_default_np_dtyper_checker classmethodrrrrrr r s]!,H$$//rr c4eZdZdZeZejZdZ dZ y)r a Array of floating (optional missing) values. .. warning:: FloatingArray is currently experimental, and its API or internal implementation may change without warning. Especially the behaviour regarding NaN (distinct from NA missing values) is subject to change. We represent a FloatingArray with 2 numpy arrays: - data: contains a numpy float array of the appropriate dtype - mask: a boolean array holding a mask on the data, True is missing To construct an FloatingArray from generic array-like input, use :func:`pandas.array` with one of the float dtypes (see examples). See :ref:`integer_na` for more. Parameters ---------- values : numpy.ndarray A 1-d float-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 ------- FloatingArray Examples -------- Create an FloatingArray with :func:`pandas.array`: >>> pd.array([0.1, None, 0.3], dtype=pd.Float32Dtype()) [0.1, , 0.3] Length: 3, dtype: Float32 String aliases for the dtypes are also available. They are capitalized. >>> pd.array([0.1, None, 0.3], dtype="Float32") [0.1, , 0.3] Length: 3, dtype: Float32 g?gN) rr r!r"r _dtype_clsr#nan_internal_fill_value _truthy_value _falsey_valuer(rrr r 8s'7rJ66MMrr az An ExtensionDtype for {dtype} data. This dtype uses ``pd.NA`` as missing value indicator. Attributes ---------- None Methods ------- None Examples -------- For Float32Dtype: >>> ser = pd.Series([2.25, pd.NA], dtype=pd.Float32Dtype()) >>> ser.dtype Float32Dtype() For Float64Dtype: >>> ser = pd.Series([2.25, pd.NA], dtype=pd.Float64Dtype()) >>> ser.dtype Float64Dtype() cXeZdZUejZdZded<ejdZ y) Float32DtypeFloat32 ClassVar[str]namefloat32rN) rr r!r#r4typer3__annotations___dtype_docstringformatr"r(rrr0r0( ::D#D-#%%I%6Grr0cXeZdZUejZdZded<ejdZ y) Float64DtypeFloat64r2r3r$r5N) rr r!r#r$r6r3r7r8r9r"r(rrr<r<r:rr<rr) __future__rtypingrnumpyr#pandas.core.dtypes.baserpandas.core.dtypes.commonrpandas.core.arrays.numericrrr r r8r0r<rr4r$rr7r(rrrDs"<4 %/L%/PBLBJ>7=77 7=77 BHHRZZ,. BHHRZZ,.73r