B W0d]@sddlmZddlZddlmZddlZddlZddlm Z m Z ddl m Z mZmZddlmZddlmZmZmZmZmZmZmZddlmZmZdd lmZdd l m!Z!dd l"m#Z#m$Z$erddl%Z%eGd d d e$Z&ddddddZ'Gddde#Z(dS)) annotationsN) TYPE_CHECKING)libmissing) ArrayLikeDtypetype_t)function) is_bool_dtypeis_floatis_float_dtypeis_integer_dtype is_list_likeis_numeric_dtype pandas_dtype)ExtensionDtyperegister_extension_dtype)isna)ops)BaseMaskedArrayBaseMaskedDtypec@seZdZdZdZeddddZedddd Zed dd d Ze d dddZ ddddZ eddddZ eddddZ dddddZdS) BooleanDtypeaf Extension dtype for boolean data. .. versionadded:: 1.0.0 .. warning:: BooleanDtype is considered experimental. The implementation and parts of the API may change without warning. Attributes ---------- None Methods ------- None Examples -------- >>> pd.BooleanDtype() BooleanDtype booleantype)returncCstjS)N)npbool_)selfrL/var/www/html/venv/lib/python3.7/site-packages/pandas/core/arrays/boolean.pyrKszBooleanDtype.typestrcCsdS)Nbr)rrrrkindOszBooleanDtype.kindznp.dtypecCs tdS)Nbool)rdtype)rrrr numpy_dtypeSszBooleanDtype.numpy_dtypeztype_t[BooleanArray]cCstS)zq Return the array type associated with this dtype. Returns ------- type ) BooleanArray)clsrrrconstruct_array_typeWs z!BooleanDtype.construct_array_typecCsdS)Nrr)rrrr__repr__bszBooleanDtype.__repr__r#cCsdS)NTr)rrrr _is_booleaneszBooleanDtype._is_booleancCsdS)NTr)rrrr _is_numericiszBooleanDtype._is_numericz$pyarrow.Array | pyarrow.ChunkedArrayr&)arrayrc Cs"ddl}|j|kr(td|jdt||jr<|g}n|j}g}x|D]}|}|jj |jt |d|dg|j dj dd}|j dkr|jj |jt |d|dg|j dj dd}|}ntjt |td }t||} || qLW|sttjgtjd tjgtjd St|SdS) zI Construct BooleanArray from pyarrow Array/ChunkedArray. rNz$Expected array of boolean type, got z instead)offsetF)Zzero_copy_only)r$)pyarrowrr TypeError isinstanceZArraychunksZbuffersr&Z from_bufferslenr.to_numpyZ null_countrzerosr#appendr,Z_concat_same_type) rr,r/r2resultsZarrZbuflistdatamaskZbool_arrrrr__from_arrow__ms0     zBooleanDtype.__from_arrow__N)__name__ __module__ __qualname____doc__namepropertyrr"r% classmethodr(r)r*r+r:rrrrr-s rFr#ztuple[np.ndarray, np.ndarray])copyrcCsNt|trD|dk rtd|j|j}}|r<|}|}||fSd}t|tjrp|jtj krp|rl|}nt|tjrt |jrt |}tj t |td}||t||<t|||j||kstd|}ntj|td}tj|dd}d}|d|krtdt |}tj t |td}||t||<||krt||t||tkstd|dkr|dkrtj t |td}np|dkr|}n`t|tjr|jtj kr|dk r||B}n|r|}n tj|td}|dk r||B}|jd kr2td |jd krFtd ||fS) a Coerce the input values array to numpy arrays with a mask. Parameters ---------- values : 1D list-like mask : bool 1D array, optional copy : bool, default False if True, copy the input Returns ------- tuple of (values, mask) Nz'cannot pass mask for BooleanArray input)r$zNeed to pass bool-like valuesT)skipna)Zfloatingintegerzmixed-integer-float)remptyr-zvalues must be a 1D list-likezmask must be a 1D list-like)r1r& ValueError_data_maskrBrndarrayr$rrrr5r3r#astypeallr0asarrayobjectrZ infer_dtypefloatr,ndim)valuesr9rBZ mask_valuesZ values_boolZ values_objectZinferred_dtypeZ integer_likerrrcoerce_to_arraysd          rQc s`eZdZdZdZdddddhZdd d d d hZdBd d ddfdd ZeddddZ e dddddddddZ e ddddddddddddd d!Z e jejee jfZd"d#d$d%d&Zd'dd(d)ZdCdd+d,fd-d. Zd dd/d0Zd*d1dd1d2d3Zd*d1dd1d4d5Zd6d7Zd8d9Zd:d;Zd*d1d#dd<fd=d>Zd#d?d@dAZZS)Dr&aZ Array of boolean (True/False) data with missing values. This is a pandas Extension array for boolean data, under the hood represented by 2 numpy arrays: a boolean array with the data and a boolean array with the mask (True indicating missing). BooleanArray implements Kleene logic (sometimes called three-value logic) for logical operations. See :ref:`boolean.kleene` for more. To construct an BooleanArray from generic array-like input, use :func:`pandas.array` specifying ``dtype="boolean"`` (see examples below). .. versionadded:: 1.0.0 .. warning:: BooleanArray is considered experimental. The implementation and parts of the API may change without warning. Parameters ---------- values : numpy.ndarray A 1-d boolean-dtype array with the data. mask : numpy.ndarray A 1-d boolean-dtype array indicating missing values (True indicates missing). copy : bool, default False Whether to copy the `values` and `mask` arrays. Attributes ---------- None Methods ------- None Returns ------- BooleanArray Examples -------- Create an BooleanArray with :func:`pandas.array`: >>> pd.array([True, False, None], dtype="boolean") [True, False, ] Length: 3, dtype: boolean FTrueTRUEtrue1z1.0FalseFALSEfalse0z0.0z np.ndarrayr#)rPr9rBcs>t|tjr|jtjks tdt|_tj |||ddS)NzIvalues should be boolean numpy array. Use the 'pd.array' function instead)rB) r1rrIr$rr0r_dtypesuper__init__)rrPr9rB) __class__rrr\)s zBooleanArray.__init__r)rcCs|jS)N)rZ)rrrrr$2szBooleanArray.dtypeN)r$rBz Dtype | None)r$rBrcCs*|r|dkstt||d\}}t||S)Nr)rB)AssertionErrorrQr&)r'scalarsr$rBrPr9rrr_from_sequence6s zBooleanArray._from_sequence)r$rB true_values false_valuesz list[str]zlist[str] | None)stringsr$rBrarbrcsP|j|p g|j|pgfddfdd|D}|j|||dS)Ncs6t|r |S|krdS|kr$dSt|ddS)NTFz cannot be cast to bool)rrF)s)false_values_uniontrue_values_unionrr map_stringLsz:BooleanArray._from_sequence_of_strings..map_stringcsg|] }|qSrr).0x)rgrr Vsz:BooleanArray._from_sequence_of_strings..)r$rB) _TRUE_VALUESunion _FALSE_VALUESr`)r'rcr$rBrarbr_r)rergrfr_from_sequence_of_strings?s  z&BooleanArray._from_sequence_of_stringsznp.ufuncr )ufuncmethodc s|dkrtd|dd}x&||D]}t||jtfs&tSq&Wtj|||f||}|tk rf|Stj t |t dg}x8|D]0}t|tr|j O| |jq| |qWfddt||||}t|trtfdd |Dn|SdS) Nreducez%The 'reduce' method is not supported.outr)r$cs*t|jr}t||Stj|<|S)N)r r$rBr&rnan)rim)r9rr reconstructws    z1BooleanArray.__array_ufunc__..reconstructc3s|]}|VqdS)Nr)rhri)rurr sz/BooleanArray.__array_ufunc__..)NotImplementedErrorgetr1_HANDLED_TYPESr&NotImplementedrZ!maybe_dispatch_ufunc_to_dunder_oprr5r3r#rHr6rGgetattrtuple) rrorpinputskwargsrrriresultZinputs2r)r9rur__array_ufunc__[s,      zBooleanArray.__array_ufunc__ztuple[np.ndarray, np.ndarray]cCst|S)N)rQ)rvaluerrr_coerce_to_arrayszBooleanArray._coerce_to_arrayTr)rBrcst|}t|tr t||St|rH|jr8tdn|jj||dSt |r^|jr^td|j }t |rrt j }|j||ddS)a Cast to a NumPy array or ExtensionArray with 'dtype'. Parameters ---------- dtype : str or dtype Typecode or data-type to which the array is cast. copy : bool, default True Whether to copy the data, even if not necessary. If False, a copy is made only if the old dtype does not match the new dtype. Returns ------- ndarray or ExtensionArray NumPy ndarray, BooleanArray or IntegerArray with 'dtype' for its dtype. Raises ------ TypeError if incompatible type with an BooleanDtype, equivalent of same_kind casting z cannot convert float NaN to bool)rBzcannot convert NA to integerF)r$na_valuerB)rr1rr[rJr Z_hasnarFrGr Z _na_valuer rrsr4)rr$rBr)r]rrrJs  zBooleanArray.astypecCs|j}d||j<|S)a= Return values for sorting. Returns ------- ndarray The transformed values should maintain the ordering between values within the array. See Also -------- ExtensionArray.argsort : Return the indices that would sort this array. )rGrBrH)rr8rrr_values_for_argsorts  z BooleanArray._values_for_argsort)rCcKsl|ddtd||j}t||jd|}|rB|S|s\t |dks\|js`|S|j j SdS)a8 Return whether any element is True. Returns False unless there is at least one element that is True. By default, NAs are skipped. If ``skipna=False`` is specified and missing values are present, similar :ref:`Kleene logic ` is used as for logical operations. Parameters ---------- skipna : bool, default True Exclude NA values. If the entire array is NA and `skipna` is True, then the result will be False, as for an empty array. If `skipna` is False, the result will still be True if there is at least one element that is True, otherwise NA will be returned if there are NA's present. **kwargs : any, default None Additional keywords have no effect but might be accepted for compatibility with NumPy. Returns ------- bool or :attr:`pandas.NA` See Also -------- numpy.any : Numpy version of this method. BooleanArray.all : Return whether all elements are True. Examples -------- The result indicates whether any element is True (and by default skips NAs): >>> pd.array([True, False, True]).any() True >>> pd.array([True, False, pd.NA]).any() True >>> pd.array([False, False, pd.NA]).any() False >>> pd.array([], dtype="boolean").any() False >>> pd.array([pd.NA], dtype="boolean").any() False With ``skipna=False``, the result can be NA if this is logically required (whether ``pd.NA`` is True or False influences the result): >>> pd.array([True, False, pd.NA]).any(skipna=False) True >>> pd.array([False, False, pd.NA]).any(skipna=False) axisNrFr) popnvZ validate_anyrGrBrputmaskrHanyr3r$r)rrCr~rPrrrrrs6   zBooleanArray.anycKsl|ddtd||j}t||jd|}|rB|S|r\t |dks\|j s`|S|j j SdS)a Return whether all elements are True. Returns True unless there is at least one element that is False. By default, NAs are skipped. If ``skipna=False`` is specified and missing values are present, similar :ref:`Kleene logic ` is used as for logical operations. Parameters ---------- skipna : bool, default True Exclude NA values. If the entire array is NA and `skipna` is True, then the result will be True, as for an empty array. If `skipna` is False, the result will still be False if there is at least one element that is False, otherwise NA will be returned if there are NA's present. **kwargs : any, default None Additional keywords have no effect but might be accepted for compatibility with NumPy. Returns ------- bool or :attr:`pandas.NA` See Also -------- numpy.all : Numpy version of this method. BooleanArray.any : Return whether any element is True. Examples -------- The result indicates whether any element is True (and by default skips NAs): >>> pd.array([True, True, pd.NA]).all() True >>> pd.array([True, False, pd.NA]).all() False >>> pd.array([], dtype="boolean").all() True >>> pd.array([pd.NA], dtype="boolean").all() True With ``skipna=False``, the result can be NA if this is logically required (whether ``pd.NA`` is True or False influences the result): >>> pd.array([True, True, pd.NA]).all(skipna=False) >>> pd.array([True, False, pd.NA]).all(skipna=False) False rNrTr) rrZ validate_allrGrBrrrHrKr3rr$r)rrCr~rPrrrrrKs4   zBooleanArray.allcCsJ|jdkstt|t}t|}d}|r:|j|j}}nNt|rtt j |dd}|j dkrbt dt |dd\}}nt|t jr|}|r|tjk rt|stdt|jd |st|t|krtd |jd krt|j||j|\}}nJ|jd krt|j||j|\}}n$|jd kr@t|j||j|\}}t||S)N>or_rxorxorrand_and_ror_r#)r$r-z(can only perform ops with 1-d structuresF)rBz+'other' should be pandas.NA or a bool. Got z instead.zLengths must match to compare>rr>rr>rr)r;r^r1r&rZ is_scalarrGrHrrrLrOrwrQritem libmissingNAZis_boolr0rr3rFrZ kleene_orZ kleene_andZ kleene_xor)rotheropZother_is_booleanarrayZother_is_scalarr9rrrr_logical_methodTs2       zBooleanArray._logical_methodc Csddlm}m}t|||fr"tSd}t|tr@|j|j}}npow rfloordivrpowfloordivrmodmodZint8r#)r$>rrr)rKdivmodrr)r;r1r&rGrHrrrLrOrwr3rFrrr5rr#r_maybe_mask_result) rrrr9op_namer$rdivrrrr _arith_methods:        zBooleanArray._arith_method)r?rCc s8|dkr t||fd|i|Stj|fd|i|S)N>rrKrC)r{r[_reduce)rr?rCr~)r]rrrszBooleanArray._reduce)rcCs|t|st|s|dkr2ddlm}|||ddSt|rHt||ddSt|rjddlm}|||ddStj ||<|SdS)z Parameters ---------- result : array-like mask : array-like bool other : scalar or array-like op_name : str )Zrtruedivtruedivr)rF)rB)rN) r r Zpandas.core.arraysrr r&r rrrs)rrr9rrrrrrrrs    zBooleanArray._maybe_mask_result)F)T) r;r<r=r>Z_internal_fill_valuerkrmr\r@r$rAr`rnrrInumbersNumberr#rryrrrJrrrKrrrrr __classcell__rr)r]rr&s24  -0DC%*1r&)NF)) __future__rrtypingrrnumpyrZ pandas._libsrrrZpandas._typingrrrZpandas.compat.numpyr rZpandas.core.dtypes.commonr r r r rrrZpandas.core.dtypes.dtypesrrZpandas.core.dtypes.missingrZ pandas.corerZpandas.core.arrays.maskedrrr/rrQr&rrrrs$   $    jV