U f/e3@s8ddlmZddlZddlZddlmZmZddl m Z m Z ddl m ZddlmZddlmZddlmZmZmZmZmZmZmZdd lmZmZdd lmZdd l m!Z!m"Z"dd l#m$Z$dd l%m&Z&Gddde"Z'ddddddZ(Gddde!Z)dZ*eGddde'Z+eGddde'Z,e+e,dZ-dS)) annotationsN)libmissing) ArrayLikeDtypeObj)function)cache_readonly)astype_nansafe) is_bool_dtypeis_datetime64_dtypeis_float_dtypeis_integer_dtype is_list_likeis_object_dtype pandas_dtype)ExtensionDtyperegister_extension_dtype)isna) NumericArray NumericDtype)invalid_comparison) to_numericc@sReZdZdZddddZeddddZed dd d Zd d dddZ 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. strreturncCs |jdS)NzDtype())nameselfr?/tmp/pip-unpacked-wheel-tiezk1ph/pandas/core/arrays/floating.py__repr__4szFloatingDtype.__repr__boolcCsdS)NTrrrrr _is_numeric7szFloatingDtype._is_numericztype[FloatingArray]cCstS)zq Return the array type associated with this dtype. Returns ------- type ) FloatingArray)clsrrr construct_array_type;s z"FloatingDtype.construct_array_typezlist[DtypeObj]zDtypeObj | None)dtypesrcCsJtdd|DsdStdd|Dg}t|tjrFtt|SdS)Ncss|]}t|tVqdSN) isinstancer.0trrr Hsz2FloatingDtype._get_common_dtype..cSsg|] }|jqSr) numpy_dtyper*rrr Msz3FloatingDtype._get_common_dtype..)allnpZfind_common_typeZ issubdtypefloatingFLOAT_STR_TO_DTYPEr)rr'Znp_dtyperrr _get_common_dtypeFs  zFloatingDtype._get_common_dtypeN) __name__ __module__ __qualname____doc__r!propertyr# classmethodr&r4rrrr r*s  rFr"tuple[np.ndarray, np.ndarray]copyrc CsL|dkr"t|dr"t|jr"|j}|dk rt|trF|drF|}tt|t szt tt |}Wn2t k r}zt d||W5d}~XYnXt|tr|j|j}}|dk r|j|jdd}|r|}|}||fSt j||d}t|rRtj|dd}|d kr6t t|}|t jn|d krt|jd nJt|rxt|rxt j|t|d }n$t|st|st|jd |dkrt |}nt|t|kst!|j"d kstd|j"d kstd|dkrt d}n|j}|#r6|}t j||<|j|dd}n|j|dd}||fS)a, Coerce the input values array to numpy arrays with a mask. Parameters ---------- values : 1D list-like dtype : float dtype mask : bool 1D array, optional copy : bool, default False if True, copy the input Returns ------- tuple of (values, mask) NdtypeZFloatzinvalid dtype specified Fr=Tskipnaempty)r2integerz mixed-integerz integer-nazmixed-integer-floatz' cannot be converted to a FloatingDtyper>r=zvalues must be a 1D list-likezmask must be a 1D list-likefloat64)$hasattrr r>r)r startswithlower issubclasstyperr3r1KeyError ValueErrorr$_data_maskastyper.r=arrayrrZ infer_dtyperBlenfillnan TypeErrorr floatr rAssertionErrorndimany)valuesr>maskr=errZ inferred_typerrr coerce_to_arrayUs^ "            r]cseZdZdZdZeddddZd.ddd d fd d Zed ddd ddddZ ed ddd ddddZ ddddZ d/d ddfdd Z ddddZ ddZddd fd!d" Zddd fd#d$ Zdd%fd&d' Zdd%fd(d) Zd*d+d,d-ZZS)0r$a Array of floating (optional missing) values. .. versionadded:: 1.2.0 .. warning:: FloatingArray is currently experimental, and its API or internal implementation may change without warning. Especially the behaviour regarding NaN (distinct from NA missing values) is subject to change. We represent a FloatingArray with 2 numpy arrays: - data: contains a numpy float array of the appropriate dtype - mask: a boolean array holding a mask on the data, True is missing To construct an FloatingArray from generic array-like input, use :func:`pandas.array` with one of the float dtypes (see examples). See :ref:`integer_na` for more. Parameters ---------- values : numpy.ndarray A 1-d float-dtype array. mask : numpy.ndarray A 1-d boolean-dtype array indicating missing values. copy : bool, default False Whether to copy the `values` and `mask`. Attributes ---------- None Methods ------- None Returns ------- FloatingArray Examples -------- Create an FloatingArray with :func:`pandas.array`: >>> pd.array([0.1, None, 0.3], dtype=pd.Float32Dtype()) [0.1, , 0.3] Length: 3, dtype: Float32 String aliases for the dtypes are also available. They are capitalized. >>> pd.array([0.1, None, 0.3], dtype="Float32") [0.1, , 0.3] Length: 3, dtype: Float32 grrcCstt|jjSr()r3rrNr>rrrr r>szFloatingArray.dtypeFz np.ndarrayr")rZr[r=cs6t|tjr|jjdks tdtj|||ddS)NfzJvalues should be floating numpy array. Use the 'pd.array' function insteadr?)r)r1Zndarrayr>kindrUsuper__init__)rrZr[r= __class__rr ras zFloatingArray.__init__NrDr<cCst|||d\}}t||S)NrD)r]r$)r%scalarsr>r=rZr[rrr _from_sequenceszFloatingArray._from_sequencecCst|dd}|j|||dS)Nraise)errorsrD)rre)r%stringsr>r=rdrrr _from_sequence_of_stringss z'FloatingArray._from_sequence_of_stringsr;cCst||jdS)Nr>)r]r>)rvaluerrr _coerce_to_arrayszFloatingArray._coerce_to_arrayTrcstt|}t|tr"tj||dSt|r6dtji}nt|rNdt di}ni}|j fd|i|}t ||ddS)a Cast to a NumPy array or ExtensionArray with 'dtype'. Parameters ---------- dtype : str or dtype Typecode or data-type to which the array is cast. copy : bool, default True Whether to copy the data, even if not necessary. If False, a copy is made only if the old dtype does not match the new dtype. Returns ------- ndarray or ExtensionArray NumPy ndarray, or BooleanArray, IntegerArray or FloatingArray with 'dtype' for its dtype. 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This dtype uses ``pd.NA`` as missing value indicator. Attributes ---------- None Methods ------- None c@s"eZdZejZdZejddZ dS) Float32DtypeZFloat32float32rjN) r5r6r7r1rrKr_dtype_docstringformatr8rrrr rsrc@s"eZdZejZdZejddZ dS) Float64DtypeZFloat64rFrjN) r5r6r7r1rFrKrrrr8rrrr rsr)rrF)NNF). __future__rrxZnumpyr1Z pandas._libsrrruZpandas._typingrrZpandas.compat.numpyrrZpandas.util._decoratorsrZpandas.core.dtypes.castr Zpandas.core.dtypes.commonr r r r rrrZpandas.core.dtypes.dtypesrrZpandas.core.dtypes.missingrZpandas.core.arrays.numericrrZpandas.core.opsrZpandas.core.tools.numericrrr]r$rrrr3rrrr s8    $    ,ab