+
    ŜiE                        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
)annotationsN)Any)lib)!maybe_dispatch_ufunc_to_dunder_op)maybe_unbox_numpy_scalar)
ABCNDFrame)	roperatorextract_array)unpack_zerodim_and_defermaximummaxminimumminaddsummultiplyprodc                  8   ] 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=# )>OpsMixinc                	    \         # NNotImplementedselfotherops   &&&^/Users/mibo/.openclaw/workspace/.venv-ak/lib/python3.14/site-packages/pandas/core/arraylike.py_cmp_methodOpsMixin._cmp_method%           __eq__c                	B    V P                  V\        P                  4      # r   )r   operatoreqr   r   s   &&r   r#   OpsMixin.__eq__(       x{{33r"   __ne__c                	B    V P                  V\        P                  4      # r   )r   r%   ner'   s   &&r   r*   OpsMixin.__ne__,   r)   r"   __lt__c                	B    V P                  V\        P                  4      # r   )r   r%   ltr'   s   &&r   r.   OpsMixin.__lt__0   r)   r"   __le__c                	B    V P                  V\        P                  4      # r   )r   r%   ler'   s   &&r   r2   OpsMixin.__le__4   r)   r"   __gt__c                	B    V P                  V\        P                  4      # r   )r   r%   gtr'   s   &&r   r6   OpsMixin.__gt__8   r)   r"   __ge__c                	B    V P                  V\        P                  4      # r   )r   r%   ger'   s   &&r   r:   OpsMixin.__ge__<   r)   r"   c                	    \         # r   r   r   s   &&&r   _logical_methodOpsMixin._logical_methodC   r!   r"   __and__c                	B    V P                  V\        P                  4      # r   )r?   r%   and_r'   s   &&r   rA   OpsMixin.__and__F   s    ##E8==99r"   __rand__c                	B    V P                  V\        P                  4      # r   )r?   r   rand_r'   s   &&r   rE   OpsMixin.__rand__J   s    ##E9??;;r"   __or__c                	B    V P                  V\        P                  4      # r   )r?   r%   or_r'   s   &&r   rI   OpsMixin.__or__N       ##E8<<88r"   __ror__c                	B    V P                  V\        P                  4      # r   )r?   r   ror_r'   s   &&r   rN   OpsMixin.__ror__R       ##E9>>::r"   __xor__c                	B    V P                  V\        P                  4      # r   )r?   r%   xorr'   s   &&r   rS   OpsMixin.__xor__V   rM   r"   __rxor__c                	B    V P                  V\        P                  4      # r   )r?   r   rxorr'   s   &&r   rW   OpsMixin.__rxor__Z   rR   r"   c                	    \         # r   r   r   s   &&&r   _arith_methodOpsMixin._arith_methoda   r!   r"   __add__c                B    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^   OpsMixin.__add__d   s    t !!%66r"   __radd__c                	B    V P                  V\        P                  4      # r   )r\   r   raddr'   s   &&r   ra   OpsMixin.__radd__       !!%88r"   __sub__c                	B    V P                  V\        P                  4      # r   )r\   r%   subr'   s   &&r   rf   OpsMixin.__sub__       !!%66r"   __rsub__c                	B    V P                  V\        P                  4      # r   )r\   r   rsubr'   s   &&r   rk   OpsMixin.__rsub__   re   r"   __mul__c                	B    V P                  V\        P                  4      # r   )r\   r%   mulr'   s   &&r   ro   OpsMixin.__mul__   rj   r"   __rmul__c                	B    V P                  V\        P                  4      # r   )r\   r   rmulr'   s   &&r   rs   OpsMixin.__rmul__   re   r"   __truediv__c                	B    V P                  V\        P                  4      # r   )r\   r%   truedivr'   s   &&r   rw   OpsMixin.__truediv__   s    !!%)9)9::r"   __rtruediv__c                	B    V P                  V\        P                  4      # r   )r\   r   rtruedivr'   s   &&r   r{   OpsMixin.__rtruediv__   s    !!%););<<r"   __floordiv__c                	B    V P                  V\        P                  4      # r   )r\   r%   floordivr'   s   &&r   r   OpsMixin.__floordiv__   s    !!%):):;;r"   __rfloordivc                	B    V P                  V\        P                  4      # r   )r\   r   	rfloordivr'   s   &&r   __rfloordiv__OpsMixin.__rfloordiv__   s    !!%)<)<==r"   __mod__c                	B    V P                  V\        P                  4      # r   )r\   r%   modr'   s   &&r   r   OpsMixin.__mod__   rj   r"   __rmod__c                	B    V P                  V\        P                  4      # r   )r\   r   rmodr'   s   &&r   r   OpsMixin.__rmod__   re   r"   
__divmod__c                	.    V P                  V\        4      # r   )r\   divmodr'   s   &&r   r   OpsMixin.__divmod__   s    !!%00r"   __rdivmod__c                	B    V P                  V\        P                  4      # r   )r\   r   rdivmodr'   s   &&r   r   OpsMixin.__rdivmod__   s    !!%):):;;r"   __pow__c                	B    V P                  V\        P                  4      # r   )r\   r%   powr'   s   &&r   r   OpsMixin.__pow__   rj   r"   __rpow__c                	B    V P                  V\        P                  4      # r   )r\   r   rpowr'   s   &&r   r   OpsMixin.__rpow__   re   r"    N)%__name__
__module____qualname____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   r   r   r   r   r   r   __static_attributes__r   r"   r   r   r   !   s    h'4 (4 h'4 (4 h'4 (4 h'4 (4 h'4 (4 h'4 (4 i(: ): j)< *< h'9 (9 i(; ); i(9 )9 j); *; i(Y7 )Y7v j)9 *9 i(7 )7 j)9 *9 i(7 )7 j)9 *9 m,; -; n-= .= n-< .< m,> -> i(7 )7 j)9 *9 l+1 ,1 m,< -< i(7 )7 j)9 *9r"   r   c               (    V ^8  d   QhRRRRRRRR/# )   ufuncnp.ufuncmethodstrinputsr   kwargsr   )formats   "r   __annotate__r     s.     ` `X `s `S `C `r"   c           	     P	  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  r\)        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MS 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__
)	DataFrameSeries)NDFrame)BlockManager__array_priority____array_ufunc__c              3  8   "   T F  p\        V4      x  K  	  R # 5ir   )type.0xs   & r   	<genexpr>array_ufunc.<locals>.<genexpr>-  s     *6a$q''6s   TstrictzCannot apply ufunc z& to mixed DataFrame and Series inputs.:   NNc              3  t   <"   T F-  w  r\        VS4      '       d   VP                  ! R/ SB MTx  K/  	  R # 5i)Nr   )
issubclassreindex)r   r   tr   reconstruct_axess   &  r   r   r   G  s8      
7 .87-C-CAII)()J7s   58nameNc                   < SP                   ^8  d3   \        ;QJ d    . V3R lV  4       F  NK  	  5# ! V3R lV  4       4      # S! V 4      # )r   c              3  4   <"   T F  pS! V4      x  K  	  R # 5ir   r   )r   r   _reconstructs   & r   r   3array_ufunc.<locals>.reconstruct.<locals>.<genexpr>X  s     9&Qa&s   )nouttuple)resultr   r   s   &r   reconstruct array_ufunc.<locals>.reconstructU  s;    ::>59&95959&999F##r"   c                j  < \         P                  ! V 4      '       d   V # V P                  SP                  8w  d   SR 8X  d   \        hV # \	        V S4      '       d   SP                  W P                  R7      p MSP                  ! V 3/ SBSBRR/B p \        S4      ^8X  d   V P                  S4      p V # )outer)axescopyF)
r   	is_scalarndimNotImplementedError
isinstance_constructor_from_mgrr   _constructorlen__finalize__)r   r   	alignabler   r   reconstruct_kwargsr   s   &r   r   !array_ufunc.<locals>._reconstruct\  s    ==  M;;$))# ))Mfl++//[[/IF &&*.@GLF y>Q((.Fr"   outreducec              3  N   "   T F  p\         P                  ! V4      x  K  	  R # 5ir   )npasarrayr   s   & r   r   r     s     5frzz!}}fs   #%c              3  <   "   T F  p\        VR R7      x  K  	  R# 5i)T)extract_numpyNr	   r   s   & r   r   r     s     LV}Qd;;Vs   __call__r   )(pandas.core.framer   r   pandas.core.genericr   pandas.core.internalsr   r   _standardize_out_kwargr   r   r   ndarrayr   hasattrr   r   _HANDLED_TYPESr   zipr   r   setissubsetr   r   	enumerateuniondict_AXIS_ORDERSr   r   popdispatch_ufunc_with_outdispatch_reduction_ufuncr   getattr_mgrapplydefault_array_ufunc) r   r   r   r   r   r   r   clsr   no_deferitemhigher_priorityhas_array_ufunctypesr   r   	set_typesr   objiax1ax2namesr   r   mgrr   r   r   r   r   r   s    fff*,                     @@@@@@r   array_ufuncr	    s*    ,2
t*C#-f-F /tUFVVVvVF^# 	

""H
 D./ B B''$*A*AA 	
 D+, : :T
**(:: :tT%8%899 	
 oo!!  E*6*EE*6**E&55daAw9O5I 9~
 J	y>A9"5">">y"I"I &%eW,RS  yyR==C "+3tSXXd+K!L:C))C.Q "M !  D$5$5tD IJ 
F$7
 
F$7
 

  D$5$5tyy NOyyA~!'>A71f+=>!%jAouyy{4$d^$ 0 (ufPvPP6"")$vQQ&Q'M
 yy1}#f+/UZZ!^ 5f55f55 ':6:	aLVLLVLL':6:	:	f Qinn75&12 %VAYvQQ&Q  FMgB ?s   R+RR#+R#c                   V ^8  d   QhRR/# )r   returnr   r   )r   s   "r   r   r     s       r"   c                     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)`
r   out1out2)r   )r   r  r  r   s   ,   r   r   r     sI     Fv/Ff4Dzz&!zz&!luMr"   c                    V ^8  d   QhRRRR/# r   r   r   r   r   r   )r   s   "r   r   r     s          3  r"   c                   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\        WV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`.
r   whereNTr   )	r   r   r   r   r   r   r   r   _assign_where)
r   r   r   r   r   r   r  r   arrress
   &&&*,     r   r   r     s     **U
CJJw%EU#V6v6F&%  #u%%SS[)@%%C5HC#E* 6 
#us8q=a&C%%#u%Jr"   c                   V ^8  d   QhRR/# )r   r  Noner   )r   s   "r   r   r     s     ' ' 'r"   c                H    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)r   putmask)r   r   r  s   &&&r   r  r    s     }A


3v&r"   c                    V ^8  d   QhRRRR/# r  r   )r   s   "r   r   r     s     9 9X 9s 9r"   c                  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  *   <"   T F  qSJ x  K
  	  R # 5ir   r   )r   r   r   s   & r   r   &default_array_ufunc.<locals>.<genexpr>  s     )&QDy&s   TF)anyr   r   r   r   )r   r   r   r   r   r   
new_inputss   f&&*,  r   r   r     sl     3)&)333)&)))!!AGHA}!"**Q-7JH5!:888 Is   &Bc                    V ^8  d   QhRRRR/# r  r   )r   s   "r   r   r     s     % %( %C %r"   c                   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.
r   Fnumeric_onlyaxisskipnar   )
r   r   r   REDUCTION_ALIASESr   r   r   r   r   r   )r   r   r   r   r   method_namer   s   &&&*,  r   r   r     s     X
6{a6!9D0~~..#ENN3K 4%%yy1}dJ''%*F>" F6N T'?u??F%f-FMr"   )__doc__
__future__r   r%   typingr   numpyr   pandas._libsr   pandas._libs.ops_dispatchr   pandas.core.dtypes.castr   pandas.core.dtypes.genericr   pandas.corer   pandas.core.constructionr
   pandas.core.ops.commonr   r%  r   r	  r   r   r  r   r   r   r"   r   <module>r2     sy    #     G < 1 ! 2 ; uu	5	 Y9 Y9@`F F'9 %r"   