*jdZddlmZddlmZddlZddlZddlm Z m Z ddl m Z erddlmZddlmZmZd dde j&d  dd Zd dde j&d  dd Zd ddd  ddZd dd ddZd dd ddZd dd ddZd dd ddZd ddd ddZd ddd ddZy)zb masked_reductions.py is for reduction algorithms using a mask-based approach for missing values. ) annotations) TYPE_CHECKINGN)libmissing)check_below_min_count)Callable)AxisIntnptT)skipna min_countaxisinitialc B|tjur||d<|sB|jst|jd|rt j S||fd|i|St|j||r!||jdk(rt j S||f||d|S)a Sum, mean or product for 1D masked array. Parameters ---------- func : np.sum or np.prod values : np.ndarray Numpy array with the values (can be of any dtype that support the operation). mask : np.ndarray[bool] Boolean numpy array (True values indicate missing values). skipna : bool, default True Whether to skip NA. min_count : int, default 0 The required number of valid values to perform the operation. If fewer than ``min_count`` non-NA values are present the result will be NA. axis : int, optional, default None initial : scalar, optional Starting value for the reduction. NumPy has a default value for most data types, but for object-dtype arrays we need to specify it explicitly rNr )wherer )r no_defaultanyrshape libmissingNAndim)funcvaluesmaskr r r rkwargss KC:\FundamentalWorkbench\vendor\pandas\core\array_algos\masked_reductions.py _reductionsrs@cnn$#y  88:.v||T9M== 4T4V4 4 tY ? LFKK1,== F=4%d=f==c Bttj||||||S)Nrrr r r r)rnpsumr s rr"r"Ns*     r)r r r c@ttj|||||S)Nrrr r r )rr!prodr$s rr%r%bs#  T&ITX r)r r c|s6|js |jstjS|||S||}|jr |||StjS)a Reduction for 1D masked array. Parameters ---------- func : np.min or np.max values : np.ndarray Numpy array with the values (can be of any dtype that support the operation). mask : np.ndarray[bool] Boolean numpy array (True values indicate missing values). skipna : bool, default True Whether to skip NA. axis : int, optional, default None )r )rsizerr)rrrr r subsets r_minmaxr)osX.  88:V[[== T* * ;;T* *== rc>ttj||||SNrrr r )r)r!minr,s rr-r- 266&tF NNrc>ttj||||Sr+)r)r!maxr,s rr0r0r.rc|jr|jrtjSt t j ||||Sr+)r'allrrrr!meanr,s rr3r3s4 ;;$((*}} rwwvDd SSrr)r r ddofc  |jr|jrtjSt j 5t j dtttj|||||cdddS#1swYyxYwNignorerrr r r4) r'r2rrwarningscatch_warnings simplefilterRuntimeWarningrr!varr8s rr=r=^ ;;$((*}}  "h7 FF6V$T  # " " 9BB c  |jr|jrtjSt j 5t j dtttj|||||cdddS#1swYyxYwr6) r'r2rrr9r:r;r<rr!stdr8s rrArAr>r?)rrr np.ndarrayrnpt.NDArray[np.bool_]r boolr intr AxisInt | Nonerobject | lib.NoDefault) rrBrrCr rDr rEr rFrrG) rrBrrCr rDr rEr rF) rrrrBrrCr rDr rF)rrBrrCr rDr rF) rrBrrCr rDr rFr4rE)__doc__ __future__rtypingrr9numpyr! pandas._libsrrrpandas.core.nanopsrcollections.abcrpandas._typingr r rrr"r%r)r-r0r3r=rArrrQsn #  5(&)nn.> .> .> .>  .>  .> .>$.>j&)nn        $0           $ #! #! #! #!  #!  #!T O O O  O  O O O O  O  O T  T  T  T  T            ,           r