E gfUddlmZddlmZddlZddlmZddlm Z ddl m Z m Z Gdde Z Gd d e Zd ZeGd d e ZeGdde ZejejeejejeiZded<dS)) annotations)ClassVarN)register_extension_dtype)is_float_dtype) NumericArray NumericDtypeceZdZdZejejZeZ e ddZ e ddZ e dd Z dS) 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. returntype[FloatingArray]ctS)zq Return the array type associated with this dtype. Returns ------- type ) FloatingArrayclss P/var/www/sysmax/venv/lib/python3.11/site-packages/pandas/core/arrays/floating.pyconstruct_array_typez"FloatingDtype.construct_array_types dict[np.dtype, FloatingDtype]ctS)N)NUMPY_FLOAT_TO_DTYPErs r_get_dtype_mappingz FloatingDtype._get_dtype_mapping(s##rvalues np.ndarraydtypenp.dtypecopyboolc0|||S)z{ Safely cast the values to the given dtype. "safe" in this context means the casting is lossless. )r)astype)rrrrs r _safe_castzFloatingDtype._safe_cast,s}}U}...rN)r r )r r)rrrrrrr r)__name__ __module__ __qualname____doc__nprfloat64_default_np_dtyper_checker classmethodrrr rrr r s!,,H[$$$[$///[///rr c,eZdZdZeZejZdZ dZ dS)ra Array of floating (optional missing) values. .. warning:: FloatingArray is currently experimental, and its API or internal implementation may change without warning. Especially the behaviour regarding NaN (distinct from NA missing values) is subject to change. We represent a FloatingArray with 2 numpy arrays: - data: contains a numpy float array of the appropriate dtype - mask: a boolean array holding a mask on the data, True is missing To construct an FloatingArray from generic array-like input, use :func:`pandas.array` with one of the float dtypes (see examples). See :ref:`integer_na` for more. Parameters ---------- values : numpy.ndarray A 1-d float-dtype array. mask : numpy.ndarray A 1-d boolean-dtype array indicating missing values. copy : bool, default False Whether to copy the `values` and `mask`. Attributes ---------- None Methods ------- None Returns ------- FloatingArray Examples -------- Create an FloatingArray with :func:`pandas.array`: >>> pd.array([0.1, None, 0.3], dtype=pd.Float32Dtype()) [0.1, , 0.3] Length: 3, dtype: Float32 String aliases for the dtypes are also available. They are capitalized. >>> pd.array([0.1, None, 0.3], dtype="Float32") [0.1, , 0.3] Length: 3, dtype: Float32 g?gN) r!r"r#r$r _dtype_clsr%nan_internal_fill_value _truthy_value _falsey_valuer*rrrr8s677rJ6MMMMrraz 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<e dZ dS) Float32DtypeFloat32 ClassVar[str]namefloat32rN) r!r"r#r%r6typer5__annotations___dtype_docstringformatr$r*rrr2r2> :D#D####%%I%66GGGrr2cXeZdZUejZdZded<e dZ dS) Float64DtypeFloat64r4r5r&r7N) r!r"r#r%r&r8r5r9r:r;r$r*rrr>r>r<rr>rr) __future__rtypingrnumpyr%pandas.core.dtypes.baserpandas.core.dtypes.commonrpandas.core.arrays.numericrrr rr:r2r>rr6r&rr9r*rrrFs"""""""<<<<<<444444 %/%/%/%/%/L%/%/%/PBBBBBLBBBJ>77777=777 77777=777 BHRZ,,.. BHRZ,,..7r