Ij%SSKJr SSKJrJrJr SSKrSSKJ r SSK J r SSK J r SSKJrJr \(aSSKJr "S S \5r\ "S 5"S S \55rSr\ \ "S5"SS\555r\ \ "S5"SS\555r\R0"\R25\"5\R0"\R45\"50rS\S'g)) annotations) TYPE_CHECKINGAnyClassVarN) set_module)register_extension_dtype)is_float_dtype) NumericArray NumericDtype)Callablec\rSrSr%Sr\R r\R"\R5r \ r S\ S'S Sjr\S Sj5r\S Sj5rSrg ) 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. zCallable[[Any], bool]_checkerc[$)zI Return the array type associated with this dtype. Returns ------- type ) FloatingArray)selfs l/root/GenerationalWealth/GenerationalWealth/venv/lib/python3.13/site-packages/pandas/core/arrays/floating.pyconstruct_array_type"FloatingDtype.construct_array_type(s c[$)N)NUMPY_FLOAT_TO_DTYPE)clss r_get_dtype_mapping FloatingDtype._get_dtype_mapping2s##rc URX#S9$)zc Safely cast the values to the given dtype. "safe" in this context means the casting is lossless. )copy)astype)rvaluesdtypers r _safe_castFloatingDtype._safe_cast6s}}U}..rN)returnztype[FloatingArray])r%dict[np.dtype, FloatingDtype])r np.ndarrayr!znp.dtyperboolr%r')__name__ __module__ __qualname____firstlineno____doc__npnan_internal_fill_valuer!float64_default_np_dtyper r__annotations__r classmethodrr"__static_attributes__r$rrrrs^66,&4H#4$$//rrz pandas.arraysc\rSrSrSr\rSrg)rBa* 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 a 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 See Also -------- array : Create an array. Float32Dtype : Float32 dtype for FloatingArray. Float64Dtype : Float64 dtype for FloatingArray. Series : One-dimensional labeled array capable of holding data. DataFrame : Two-dimensional, size-mutable, potentially heterogeneous tabular data. Examples -------- Create a 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 r$N)r)r*r+r,r-r _dtype_clsr5r$rrrrBs?BJrra` An ExtensionDtype for {dtype} data. This dtype uses ``pd.NA`` as missing value indicator. Attributes ---------- None Methods ------- None See Also -------- CategoricalDtype : Type for categorical data with the categories and orderedness. IntegerDtype : An ExtensionDtype to hold a single size & kind of integer dtype. StringDtype : An ExtensionDtype for string data. 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() pandascZ\rSrSr%\R rSrS\S'\ RSS9r Sr g) Float32DtypeFloat32 ClassVar[str]namefloat32r!r$N) r)r*r+r,r.r@typer?r3_dtype_docstringformatr-r5r$rrr;r;* ::D#D-#%%I%6Grr;cZ\rSrSr%\R rSrS\S'\ RSS9r Sr g) Float64DtypeFloat64r>r?r1rAr$N) r)r*r+r,r.r1rBr?r3rCrDr-r5r$rrrGrGrErrGr&r) __future__rtypingrrrnumpyr.pandas.util._decoratorsrpandas.core.dtypes.baserpandas.core.dtypes.commonr pandas.core.arrays.numericr r collections.abcr rrrCr;rGr!r@r1rr3r$rrrRs" .<4 (&/L&/R OBLBBJ J H7=77  H7=77HHRZZ,.HHRZZ,.73r