U c@sddlmZddlZddlmZddlmZddlm Z m Z Gddde Z Gdd d e Z d Z eGd d d e ZeGd dde ZeedZdS)) annotationsN)is_float_dtype)register_extension_dtype) NumericArray NumericDtypec@sVeZdZdZeejZeZ e ddddZ e ddZ e dd d dd d d 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. ztype[FloatingArray])returncCstS)zq Return the array type associated with this dtype. Returns ------- type ) FloatingArrayclsr ?/tmp/pip-unpacked-wheel-g7fro6k3/pandas/core/arrays/floating.pyconstruct_array_types z"FloatingDtype.construct_array_typecCstS)N)FLOAT_STR_TO_DTYPEr r r r _str_to_dtype_mapping&sz#FloatingDtype._str_to_dtype_mappingz np.ndarrayznp.dtypebool)valuesdtypecopyrcCs|j||dS)z{ Safely cast the values to the given dtype. "safe" in this context means the casting is lossless. )r)Zastype)r rrrr r r _safe_cast*s zFloatingDtype._safe_castN)__name__ __module__ __qualname____doc__nprfloat64Z_default_np_dtyperZ_checker classmethodrrrr r r r rs   rc@s"eZdZdZeZejZdZ dZ dS)r a Array of floating (optional missing) values. .. versionadded:: 1.2.0 .. 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) rrrrrZ _dtype_clsrnanZ_internal_fill_valueZ _truthy_valueZ _falsey_valuer r r r r 6s ;r z An ExtensionDtype for {dtype} data. This dtype uses ``pd.NA`` as missing value indicator. Attributes ---------- None Methods ------- None c@s"eZdZejZdZejddZ dS) Float32DtypeZFloat32float32rN) rrrrrtypename_dtype_docstringformatrr r r r rsrc@s"eZdZejZdZejddZ dS) Float64DtypeZFloat64rr N) rrrrrr!r"r#r$rr r r r r%sr%)rr) __future__rZnumpyrZpandas.core.dtypes.commonrZpandas.core.dtypes.dtypesrZpandas.core.arrays.numericrrrr r#rr%rr r r r s   (E