+
    ÏÜ³j¬E  ã                  óö   € R t ^ RIHt ^ RIt^ RIHt ^ RIt^ RIH	t	 ^ RI
Ht ^ RIHt ^ RIHt ^ RIHt ^ R	IHt ^ R
IHt RRRRRRRR/t ! R R4      tR R ltR R ltR R ltR R ltR R ltR R  ltR# )!zn
Methods that can be shared by many array-like classes or subclasses:
    Series
    Index
    ExtensionArray
)ÚannotationsN)ÚAny)Úlib)Ú!maybe_dispatch_ufunc_to_dunder_op)Úmaybe_unbox_numpy_scalar)Ú
ABCNDFrame)Ú	roperator©Úextract_array)Úunpack_zerodim_and_deferÚmaximumÚmaxÚminimumÚminÚaddÚsumÚmultiplyÚprodc                  ó8  € ] tR t^!tR t]! R4      R 4       t]! R4      R 4       t]! R4      R 4       t]! R4      R	 4       t	]! R
4      R 4       t
]! R4      R 4       tR t]! R4      R 4       t]! R4      R 4       t]! R4      R 4       t]! R4      R 4       t]! R4      R 4       t]! R4      R 4       tR t]! R4      R 4       t]! R4      R 4       t]! R 4      R! 4       t]! R"4      R# 4       t]! R$4      R% 4       t]! R&4      R' 4       t]! R(4      R) 4       t]! R*4      R+ 4       t]! R,4      R- 4       t]! R.4      R/ 4       t]! R04      R1 4       t]! R24      R3 4       t]! R44      R5 4       t ]! R64      R7 4       t!]! R84      R9 4       t"]! R:4      R; 4       t#R<t$R=# )>ÚOpsMixinc                	ó   € \         # ©N©ÚNotImplemented©ÚselfÚotherÚops   &&&ÚV/home/luca/screen-checking/.venv/lib/python3.14/site-packages/pandas/core/arraylike.pyÚ_cmp_methodÚOpsMixin._cmp_method%   ó   € ÜÐó    Ú__eq__c                	óB   € V P                  V\        P                  4      # r   )r   ÚoperatorÚeq©r   r   s   &&r   r#   ÚOpsMixin.__eq__(   ó   € à×Ñ ¤x§{¡{Ó3Ð3r"   Ú__ne__c                	óB   € V P                  V\        P                  4      # r   )r   r%   Úner'   s   &&r   r*   ÚOpsMixin.__ne__,   r)   r"   Ú__lt__c                	óB   € V P                  V\        P                  4      # r   )r   r%   Últr'   s   &&r   r.   ÚOpsMixin.__lt__0   r)   r"   Ú__le__c                	óB   € V P                  V\        P                  4      # r   )r   r%   Úler'   s   &&r   r2   ÚOpsMixin.__le__4   r)   r"   Ú__gt__c                	óB   € V P                  V\        P                  4      # r   )r   r%   Úgtr'   s   &&r   r6   ÚOpsMixin.__gt__8   r)   r"   Ú__ge__c                	óB   € V P                  V\        P                  4      # r   )r   r%   Úger'   s   &&r   r:   ÚOpsMixin.__ge__<   r)   r"   c                	ó   € \         # r   r   r   s   &&&r   Ú_logical_methodÚOpsMixin._logical_methodC   r!   r"   Ú__and__c                	óB   € V P                  V\        P                  4      # r   )r?   r%   Úand_r'   s   &&r   rA   ÚOpsMixin.__and__F   s   € à×#Ñ# E¬8¯=©=Ó9Ð9r"   Ú__rand__c                	óB   € V P                  V\        P                  4      # r   )r?   r   Úrand_r'   s   &&r   rE   ÚOpsMixin.__rand__J   s   € à×#Ñ# E¬9¯?©?Ó;Ð;r"   Ú__or__c                	óB   € V P                  V\        P                  4      # r   )r?   r%   Úor_r'   s   &&r   rI   ÚOpsMixin.__or__N   ó   € à×#Ñ# E¬8¯<©<Ó8Ð8r"   Ú__ror__c                	óB   € V P                  V\        P                  4      # r   )r?   r   Úror_r'   s   &&r   rN   ÚOpsMixin.__ror__R   ó   € à×#Ñ# E¬9¯>©>Ó:Ð:r"   Ú__xor__c                	óB   € V P                  V\        P                  4      # r   )r?   r%   Úxorr'   s   &&r   rS   ÚOpsMixin.__xor__V   rM   r"   Ú__rxor__c                	óB   € V P                  V\        P                  4      # r   )r?   r   Úrxorr'   s   &&r   rW   ÚOpsMixin.__rxor__Z   rR   r"   c                	ó   € \         # r   r   r   s   &&&r   Ú_arith_methodÚOpsMixin._arith_methoda   r!   r"   Ú__add__c                óB   € V P                  V\        P                  4      # )a	  
Get Addition of DataFrame and other, column-wise.

Equivalent to ``DataFrame.add(other)``.

Parameters
----------
other : scalar, sequence, Series, dict or DataFrame
    Object to be added to the DataFrame.

Returns
-------
DataFrame
    The result of adding ``other`` to DataFrame.

See Also
--------
DataFrame.add : Add a DataFrame and another object, with option for index-
    or column-oriented addition.

Examples
--------
>>> df = pd.DataFrame(
...     {"height": [1.5, 2.6], "weight": [500, 800]}, index=["elk", "moose"]
... )
>>> df
       height  weight
elk       1.5     500
moose     2.6     800

Adding a scalar affects all rows and columns.

>>> df[["height", "weight"]] + 1.5
       height  weight
elk       3.0   501.5
moose     4.1   801.5

Each element of a list is added to a column of the DataFrame, in order.

>>> df[["height", "weight"]] + [0.5, 1.5]
       height  weight
elk       2.0   501.5
moose     3.1   801.5

Keys of a dictionary are aligned to the DataFrame, based on column names;
each value in the dictionary is added to the corresponding column.

>>> df[["height", "weight"]] + {"height": 0.5, "weight": 1.5}
       height  weight
elk       2.0   501.5
moose     3.1   801.5

When `other` is a :class:`Series`, the index of `other` is aligned with the
columns of the DataFrame.

>>> s1 = pd.Series([0.5, 1.5], index=["weight", "height"])
>>> df[["height", "weight"]] + s1
       height  weight
elk       3.0   500.5
moose     4.1   800.5

Even when the index of `other` is the same as the index of the DataFrame,
the :class:`Series` will not be reoriented. If index-wise alignment is desired,
:meth:`DataFrame.add` should be used with `axis='index'`.

>>> s2 = pd.Series([0.5, 1.5], index=["elk", "moose"])
>>> df[["height", "weight"]] + s2
       elk  height  moose  weight
elk    NaN     NaN    NaN     NaN
moose  NaN     NaN    NaN     NaN

>>> df[["height", "weight"]].add(s2, axis="index")
       height  weight
elk       2.0   500.5
moose     4.1   801.5

When `other` is a :class:`DataFrame`, both columns names and the
index are aligned.

>>> other = pd.DataFrame(
...     {"height": [0.2, 0.4, 0.6]}, index=["elk", "moose", "deer"]
... )
>>> df[["height", "weight"]] + other
       height  weight
deer      NaN     NaN
elk       1.7     NaN
moose     3.0     NaN
)r\   r%   r   r'   s   &&r   r^   ÚOpsMixin.__add__d   s   € ðt ×!Ñ! %¬¯©Ó6Ð6r"   Ú__radd__c                	óB   € V P                  V\        P                  4      # r   )r\   r   Úraddr'   s   &&r   ra   ÚOpsMixin.__radd__À   ó   € à×!Ñ! %¬¯©Ó8Ð8r"   Ú__sub__c                	óB   € V P                  V\        P                  4      # r   )r\   r%   Úsubr'   s   &&r   rf   ÚOpsMixin.__sub__Ä   ó   € à×!Ñ! %¬¯©Ó6Ð6r"   Ú__rsub__c                	óB   € V P                  V\        P                  4      # r   )r\   r   Úrsubr'   s   &&r   rk   ÚOpsMixin.__rsub__È   re   r"   Ú__mul__c                	óB   € V P                  V\        P                  4      # r   )r\   r%   Úmulr'   s   &&r   ro   ÚOpsMixin.__mul__Ì   rj   r"   Ú__rmul__c                	óB   € V P                  V\        P                  4      # r   )r\   r   Úrmulr'   s   &&r   rs   ÚOpsMixin.__rmul__Ð   re   r"   Ú__truediv__c                	óB   € V P                  V\        P                  4      # r   )r\   r%   Útruedivr'   s   &&r   rw   ÚOpsMixin.__truediv__Ô   s   € à×!Ñ! %¬×)9Ñ)9Ó:Ð:r"   Ú__rtruediv__c                	óB   € V P                  V\        P                  4      # r   )r\   r   Úrtruedivr'   s   &&r   r{   ÚOpsMixin.__rtruediv__Ø   s   € à×!Ñ! %¬×);Ñ);Ó<Ð<r"   Ú__floordiv__c                	óB   € V P                  V\        P                  4      # r   )r\   r%   Úfloordivr'   s   &&r   r   ÚOpsMixin.__floordiv__Ü   s   € à×!Ñ! %¬×):Ñ):Ó;Ð;r"   Ú__rfloordivc                	óB   € V P                  V\        P                  4      # r   )r\   r   Ú	rfloordivr'   s   &&r   Ú__rfloordiv__ÚOpsMixin.__rfloordiv__à   s   € à×!Ñ! %¬×)<Ñ)<Ó=Ð=r"   Ú__mod__c                	óB   € V P                  V\        P                  4      # r   )r\   r%   Úmodr'   s   &&r   rˆ   ÚOpsMixin.__mod__ä   rj   r"   Ú__rmod__c                	óB   € V P                  V\        P                  4      # r   )r\   r   Úrmodr'   s   &&r   rŒ   ÚOpsMixin.__rmod__è   re   r"   Ú
__divmod__c                	ó.   € V P                  V\        4      # r   )r\   Údivmodr'   s   &&r   r�   ÚOpsMixin.__divmod__ì   s   € à×!Ñ! %¬Ó0Ð0r"   Ú__rdivmod__c                	óB   € V P                  V\        P                  4      # r   )r\   r   Úrdivmodr'   s   &&r   r”   ÚOpsMixin.__rdivmod__ð   s   € à×!Ñ! %¬×):Ñ):Ó;Ð;r"   Ú__pow__c                	óB   € V P                  V\        P                  4      # r   )r\   r%   Úpowr'   s   &&r   r˜   ÚOpsMixin.__pow__ô   rj   r"   Ú__rpow__c                	óB   € V P                  V\        P                  4      # r   )r\   r   Úrpowr'   s   &&r   rœ   ÚOpsMixin.__rpow__ø   re   r"   © N)%Ú__name__Ú
__module__Ú__qualname__Ú__firstlineno__r   r   r#   r*   r.   r2   r6   r:   r?   rA   rE   rI   rN   rS   rW   r\   r^   ra   rf   rk   ro   rs   rw   r{   r   r†   rˆ   rŒ   r�   r”   r˜   rœ   Ú__static_attributes__r    r"   r   r   r   !   sÐ  † òñ ˜hÓ'ñ4ó (ð4ñ ˜hÓ'ñ4ó (ð4ñ ˜hÓ'ñ4ó (ð4ñ ˜hÓ'ñ4ó (ð4ñ ˜hÓ'ñ4ó (ð4ñ ˜hÓ'ñ4ó (ð4òñ ˜iÓ(ñ:ó )ð:ñ ˜jÓ)ñ<ó *ð<ñ ˜hÓ'ñ9ó (ð9ñ ˜iÓ(ñ;ó )ð;ñ ˜iÓ(ñ9ó )ð9ñ ˜jÓ)ñ;ó *ð;òñ ˜iÓ(ñY7ó )ðY7ñv ˜jÓ)ñ9ó *ð9ñ ˜iÓ(ñ7ó )ð7ñ ˜jÓ)ñ9ó *ð9ñ ˜iÓ(ñ7ó )ð7ñ ˜jÓ)ñ9ó *ð9ñ ˜mÓ,ñ;ó -ð;ñ ˜nÓ-ñ=ó .ð=ñ ˜nÓ-ñ<ó .ð<ñ ˜mÓ,ñ>ó -ð>ñ ˜iÓ(ñ7ó )ð7ñ ˜jÓ)ñ9ó *ð9ñ ˜lÓ+ñ1ó ,ð1ñ ˜mÓ,ñ<ó -ð<ñ ˜iÓ(ñ7ó )ð7ñ ˜jÓ)ñ9ó *ô9r"   r   c               ó(   € V ^8„  d   QhRRRRRRRR/# )é   Úufuncúnp.ufuncÚmethodÚstrÚinputsr   Úkwargsr    )Úformats   "r   Ú__annotate__r¯     s.   € ÷ `ñ `˜Xð `¨sð `¸Sð `ÈCñ `r"   c           	     óP	  a aaaaaaaa€ ^ RI HpHp ^ RIHo ^ RIHo \        S 4      p\        R/ VB p\        S SS.VO5/ VB pV\        Jd   V# \        P                  P                  VP                  3p	V F—  p
\        V
R4      ;'       d    V
P                  S P                  8„  p\        V
R4      ;'       d<    \        V
4      P                  V	9  ;'       d    \!        V
S P"                  4      '       * pV'       g   V'       g   K‘  \        u # 	  \$        ;QJ d    . R V 4       F  NK  	  5M! R V 4       4      p\'        W=RR7       UUu. uF  w  rï\)        VS4      '       g   K  VNK  	  uppo\+        S4      ^8”  Ed   \-        V4      p\+        V4      ^8”  d(   WV0P/                  V4      '       d   \1        R	S R
24      hS P2                  pSR,           FE  p\5        \'        VVP2                  RR7      4       F  w  pw  ppVP7                  V4      VV&   K  	  KG  	  \9        \'        S P:                  VRR7      4      o\$        ;QJ d#    . VV3R l\'        W=RR7       4       F  NK  	  5M! VV3R l\'        W=RR7       4       4      pM+\9        \'        S P:                  S P2                  RR7      4      oS P<                  ^8X  dW   V Uu0 uF#  p\        VR4      '       g   K  VP>                  kK%  	  pp\+        V4      ^8X  d   VPA                  4       MRpRV/oM/ oVV3R lpVVVVVV 3R loRV9   d   \C        S SS.VO5/ VB pV! V4      # SR8X  d   \E        S SS.VO5/ VB pV\        Jd   V# S P<                  ^8”  da   \+        V4      ^8”  g   SPF                  ^8”  d@   \$        ;QJ d    . R V 4       F  NK  	  5M! R V 4       4      p\I        SS4      ! V/ VB pM¦S P<                  ^8X  d@   \$        ;QJ d    . R V 4       F  NK  	  5M! R V 4       4      p\I        SS4      ! V/ VB pMVSR8X  d8   V'       g0   V^ ,          PJ                  pVPM                  \I        SS4      4      pM\O        V^ ,          SS.VO5/ VB pV! V4      pV# u uppi u upi )z„
Compatibility with numpy ufuncs.

See also
--------
numpy.org/doc/stable/reference/arrays.classes.html#numpy.class.__array_ufunc__
)Ú	DataFrameÚSeries)ÚNDFrame)ÚBlockManagerÚ__array_priority__Ú__array_ufunc__c              3  ó8   "  € T F  p\        V4      x € K  	  R # 5ir   )Útype©Ú.0Úxs   & r   Ú	<genexpr>Úarray_ufunc.<locals>.<genexpr>-  s   é € Ð*¡6˜a”$�q—'�'£6ùs   ‚T©ÚstrictzCannot apply ufunc z& to mixed DataFrame and Series inputs.:é   NNc              3  ót   <"  € T F-  w  r\        VS4      '       d   VP                  ! R/ SB MTx € K/  	  R # 5i)Nr    )Ú
issubclassÚreindex)rº   r»   Útr³   Úreconstruct_axess   &  €€r   r¼   r½   G  s8   øé € ð 
á7‘�ô .8¸¸7×-CÒ-CˆA�IŠIÑ)Ð(Ò)ÈÔJÛ7ùs   ƒ58ÚnameNc                óš   <€ SP                   ^8”  d3   \        ;QJ d    . V3R lV  4       F  NK  	  5# ! V3R lV  4       4      # S! V 4      # )rÀ   c              3  ó4   <"  € T F  pS! V4      x € K  	  R # 5ir   r    )rº   r»   Ú_reconstructs   & €r   r¼   Ú3array_ufunc.<locals>.reconstruct.<locals>.<genexpr>X  s   øé € Ð9±&¨Q™ aŸ˜³&ùs   ƒ)ÚnoutÚtuple)ÚresultrÉ   r¨   s   &€€r   ÚreconstructÚ array_ufunc.<locals>.reconstructU  s;   ø€ Ø�:‰:˜Œ>ç”5Ô9±&Ó9—5Ð9�5Ô9±&Ó9Ó9Ð9á˜FÓ#Ð#r"   c                ój  <€ \         P                  ! V 4      '       d   V # V P                  SP                  8w  d   SR 8X  d   \        hV # \	        V S4      '       d   SP                  W P                  R7      p MSP                  ! V 3/ SBSBRR/B p \        S4      ^8X  d   V P                  S4      p V # )Úouter)ÚaxesÚcopyF)
r   Ú	is_scalarÚndimÚNotImplementedErrorÚ
isinstanceÚ_constructor_from_mgrrÒ   Ú_constructorÚlenÚ__finalize__)rÍ   r´   Ú	alignablerª   rÅ   Úreconstruct_kwargsr   s   &€€€€€€r   rÉ   Ú!array_ufunc.<locals>._reconstruct\  s®   ø€ Ü�=Š=˜× Ò ØˆMà�;‰;˜$Ÿ)™)Ô#Ø˜Ô Ü)Ð)ØˆMÜ�f˜l×+Ò+à×/Ñ/°¿[¹[Ð/ÓI‰Fð ×&Ò&ØñØ*ðØ.@ñØGLòˆFô ˆy‹>˜QÔØ×(Ñ(¨Ó.ˆFØˆr"   ÚoutÚreducec              3  óN   "  € T F  p\         P                  ! V4      x € K  	  R # 5ir   )ÚnpÚasarrayr¹   s   & r   r¼   r½   ‹  s   é € Ð5©f¨”r—z’z !—}�}«fùs   ‚#%c              3  ó<   "  € T F  p\        VR R7      x € K  	  R# 5i)T)Úextract_numpyNr	   r¹   s   & r   r¼   r½   ‘  s   é € ÐLÁVÀ”} Q°d×;Ñ;ÃVùs   ‚Ú__call__r    )(Úpandas.core.framer±   r²   Úpandas.core.genericr³   Úpandas.core.internalsr´   r¸   Ú_standardize_out_kwargr   r   râ   Úndarrayr¶   Úhasattrrµ   r×   Ú_HANDLED_TYPESrÌ   ÚziprÂ   rÚ   ÚsetÚissubsetrÖ   rÒ   Ú	enumerateÚunionÚdictÚ_AXIS_ORDERSrÕ   rÆ   ÚpopÚdispatch_ufunc_with_outÚdispatch_reduction_ufuncrË   ÚgetattrÚ_mgrÚapplyÚdefault_array_ufunc) r   r¨   rª   r¬   r­   r±   r²   ÚclsrÍ   Úno_deferÚitemÚhigher_priorityÚhas_array_ufuncÚtypesr»   rÄ   Ú	set_typesrÒ   ÚobjÚiÚax1Úax2ÚnamesrÆ   rÎ   Úmgrr´   r³   rÉ   rÜ   rÅ   rÝ   s    fff*,                     @@@@@@r   Úarray_ufuncr	    s*  ÿø€ ÷õ ,Ý2ä
ˆt‹*€Cä#Ñ- fÑ-€Fô /¨t°U¸FÐVÀVÒVÈvÑV€FØ”^Ó#Øˆô 	�
‰
×"Ñ"Ø×Ñð€Hó
 ˆä�DÐ.Ó/÷ Bð BØ×'Ñ'¨$×*AÑ*AÑAð 	ô
 �DÐ+Ó,÷ :ð :Ü�T“
×*Ñ*°(Ñ:÷:ð :ä˜t T×%8Ñ%8Ó9Ô9ð 	÷
 Ÿo™oÜ!Ò!ñ ÷ ŒEÑ*¡6Ó*�E‰EÑ*¡6Ó*Ó*€Eä˜&°Õ5ôÙ5‰dˆa¼ÀAÀw×9O�ˆÑ5ò€Iô ˆ9ƒ~˜Õô
 ˜“Jˆ	Üˆy‹>˜AÔ 9Ð"5×">Ñ">¸y×"IÒ"Iô &Ø% e WÐ,RÐSóð ð �y‰yˆØ˜R—=�=ˆCô "+¬3¨t°S·X±XÀdÔ+KÖ!L‘�‘:�C˜ØŸ)™) C›.��Q“ó "Mñ !ô  ¤ D×$5Ñ$5°tÀDÔ IÓJÐß”õ 
ä˜F°$Õ7ó
—‘õ 
ä˜F°$Õ7ó
ó 
‰ô
  ¤ D×$5Ñ$5°t·y±yÈÔ NÓOÐà‡y�y�A„~Ù!'Ó>¡˜A¬7°1°f×+=”�—”¡ˆÐ>Ü! %›j¨Aœoˆu�y‰yŒ{°4ˆØ$ d˜^ÑàÐö$÷ò ð0 �„ä(¨¨u°fÐP¸vÒPÈÑPˆÙ˜6Ó"Ð"à�Ôä)¨$°°vÐQÀÒQÈ&ÑQˆØœÓ'ØˆMð
 ‡y�y�1„}œ#˜f›+¨œ/¨U¯Z©Z¸!¬^÷ ”Ñ5©fÓ5—‘Ñ5©fÓ5Ó5ˆô ˜ Ô'¨Ð:°6Ñ:‰Ø	�‰�aŒç”ÑLÁVÓL—‘ÑLÁVÓLÓLˆÜ˜ Ô'¨Ð:°6Ñ:‰à	�:Ô	§fð �Q�i�n‰nˆØ—‘œ7 5¨&Ó1Ó2‰ô % V¨A¥Y°°vÐQÀÒQÈ&ÑQˆñ ˜Ó €FØ€MùógùòB ?s   ÅRÅ+RËR#Ë+R#c               ó   € V ^8„  d   QhRR/# )r§   Úreturnró   r    )r®   s   "r   r¯   r¯   ¤  s   € ÷ ñ ¨ñ r"   c                 ó‚   € RV 9  d8   RV 9   d1   RV 9   d*   V P                  R4      pV P                  R4      pW3pW0R&   V # )z¢
If kwargs contain "out1" and "out2", replace that with a tuple "out"

np.divmod, np.modf, np.frexp can have either `out=(out1, out2)` or
`out1=out1, out2=out2)`
rß   Úout1Úout2)rõ   )r­   r  r  rß   s   ,   r   rê   rê   ¤  sI   € ð �FÔ˜v¨Ô/°F¸fÔ4DØ�z‰z˜&Ó!ˆØ�z‰z˜&Ó!ˆØˆlˆØˆu‰Ø€Mr"   c               ó    € V ^8„  d   QhRRRR/# ©r§   r¨   r©   rª   r«   r    )r®   s   "r   r¯   r¯   ³  s   € ÷  ñ  ¨ð  ¸3ñ  r"   c                óð  € VP                  R4      pVP                  RR4      p\        W4      ! V/ VB pV\        J d   \        # \        V\        4      '       dZ   \        V\        4      '       d   \        V4      \        V4      8w  d   \        h\        WWRR7       F  w  r‰\        W‰V4       K  	  V# \        V\        4      '       d!   \        V4      ^8X  d   V^ ,          pM\        h\        WWV4       V# )zn
If we have an `out` keyword, then call the ufunc without `out` and then
set the result into the given `out`.
rß   ÚwhereNTr¾   )	rõ   rø   r   r×   rÌ   rÚ   rÖ   rî   Ú_assign_where)
r   r¨   rª   r¬   r­   rß   r  rÍ   ÚarrÚress
   &&&*,     r   rö   rö   ³  sÍ   € ð �*‰*�UÓ
€CØ�J‰J�w Ó%€Eä�UÔ# VÐ6¨vÑ6€Fà”ÓÜÐä�&œ%× Ò ä˜#œu×%Ò%¬¨S«´S¸³[Ô)@Ü%Ð%ä˜C°×5‰HˆCÜ˜# EÖ*ñ 6ð ˆ
ä�#”u×ÒÜˆs‹8�qŒ=Ø�a•&‰Cä%Ð%ä�#˜uÔ%Ø€Jr"   c               ó   € V ^8„  d   QhRR/# )r§   r  ÚNoner    )r®   s   "r   r¯   r¯   Ö  s   € ÷ 'ñ '¨ñ 'r"   c                óH   € Vf   WR&   R# \         P                  ! WV4       R# )zN
Set a ufunc result into 'out', masking with a 'where' argument if necessary.
N:NNN)râ   Úputmask)rß   rÍ   r  s   &&&r   r  r  Ö  s   € ð ‚}àˆA‹ä
�
Š
�3˜vÖ&r"   c               ó    € V ^8„  d   QhRRRR/# r  r    )r®   s   "r   r¯   r¯   á  s   € ÷ 9ñ 9 Xð 9°sñ 9r"   c                ó  a € \         ;QJ d    V 3R lV 4       F  '       g   K   RM	  RM! V 3R lV 4       4      '       g   \        hV Uu. uF   qUS Jd   TM\        P                  ! V4      NK"  	  pp\	        W4      ! V/ VB # u upi )z‰
Fallback to the behavior we would get if we did not define __array_ufunc__.

Notes
-----
We are assuming that `self` is among `inputs`.
c              3  ó*   <"  € T F  qSJ x € K
  	  R # 5ir   r    )rº   r»   r   s   & €r   r¼   Ú&default_array_ufunc.<locals>.<genexpr>é  s   øé € Ð)¡&˜Q�D�y£&ùs   ƒTF)ÚanyrÖ   râ   rã   rø   )r   r¨   rª   r¬   r­   r»   Ú
new_inputss   f&&*,  r   rû   rû   á  sl   ø€ ÷ ‹3Ô)¡&Ó)�3�3Š3Ô)¡&Ó)×)Ò)Ü!Ð!áAGÓHÁ¸A “}‘!¬"¯*ª*°Q«-Ò7Á€JÐHä�5Ô! :Ð8°Ñ8Ð8ùò Is   Á&Bc               ó    € V ^8„  d   QhRRRR/# r  r    )r®   s   "r   r¯   r¯   ñ  s   € ÷ %ñ %¨(ð %¸Cñ %r"   c                óœ  € VR8X  g   Q h\        V4      ^8w  g   V^ ,          V Jd   \        # VP                  \        9  d   \        # \        VP                  ,          p\	        W4      '       g   \        # V P
                  ^8”  d(   \        V \        4      '       d   RVR&   RV9  d   ^ VR&   \        W4      ! RRR/VB p\        V4      pV# )z8
Dispatch ufunc reductions to self's reduction methods.
rà   FÚnumeric_onlyÚaxisÚskipnar    )
rÚ   r   r¡   ÚREDUCTION_ALIASESrì   rÕ   r×   r   rø   r   )r   r¨   rª   r¬   r­   Úmethod_namerÍ   s   &&&*,  r   r÷   r÷   ñ  sÀ   € ð �XÔÐÐä
ˆ6ƒ{�aÔ˜6 !�9¨DÓ0ÜÐà‡~�~Ô.Ô.ÜÐä# E§N¡NÕ3€Kô �4×%Ò%ÜÐà‡y�y�1„}Ü�dœJ×'Ò'à%*ˆF�>Ñ"à˜Ôð ˆF�6‰Nô �TÔ'Ñ?¨uÐ?¸Ñ?€FÜ% fÓ-€FØ€Mr"   )Ú__doc__Ú
__future__r   r%   Útypingr   Únumpyrâ   Úpandas._libsr   Úpandas._libs.ops_dispatchr   Úpandas.core.dtypes.castr   Úpandas.core.dtypes.genericr   Úpandas.corer   Úpandas.core.constructionr
   Úpandas.core.ops.commonr   r%  r   r	  rê   rö   r  rû   r÷   r    r"   r   Ú<module>r2     sy   ðñõ #ã Ý ã å Ý Gå <Ý 1å !Ý 2Ý ;ð ˆuØˆuØ	ˆ5Ø�ð	Ð ÷Y9ñ Y9õ@`õFõ õF'õ9÷ %r"   