a 鴫j7@svdZddlmZddlmZmZddlmZmZddl Z ddl m Z ddl mZmZedeeZed eedZd d d d Zd d ddZd d ddZd d ddZd d ddZd d ddZd>d dddd dddZd?ddd d!Zd"d#d$d%d&Zeddd'd(d)Zed*d+d'd,d)Zd-d.d'd/d)Zd0d1d2d3d4Zd0d1d5d6d7Zd8d8d8d9d:d;Z d d d|dur>||}nR|durx|durx|rt|ttfrtdt|jdn|dur|durtd||fS)a$ Validate the keyword arguments to 'fillna'. This checks that exactly one of 'value' and 'method' is specified. If 'method' is specified, this validates that it's a valid method. Parameters ---------- value, method : object The 'value' and 'method' keyword arguments for 'fillna'. validate_scalar_dict_value : bool, default True Whether to validate that 'value' is a scalar or dict. Specifically, validate that it is not a list or tuple. Returns ------- value, method : object r)clean_fill_methodNz(Must specify a fill 'value' or 'method'.z>"value" parameter must be a scalar or dict, but you passed a ""z)Cannot specify both 'value' and 'method'.) Zpandas.core.missingr?rr9listr.rr;r<)r4methodr>r?rrrvalidate_fillna_kwargss  rCzfloat | Iterable[float]z np.ndarray)qr cCsVt|}d}|jdkr8d|kr,dksRnt|ntdd|DsRt||S)a Validate percentiles (used by describe and quantile). This function checks if the given float or iterable of floats is a valid percentile otherwise raises a ValueError. Parameters ---------- q: float or iterable of floats A single percentile or an iterable of percentiles. Returns ------- ndarray An ndarray of the percentiles if valid. Raises ------ ValueError if percentiles are not in given interval([0, 1]). z0percentiles should all be in the interval [0, 1]rrcss&|]}d|kodknVqdS)rrNr).0qsrrr Sz&validate_percentile..)npZasarrayndimrall)rDZq_arrmsgrrrvalidate_percentile6s   rM) ascendingr cCsdSNrrNrrrvalidate_ascendingXsrQzSequence[BoolishT]zlist[BoolishT]cCsdSrOrrPrrrrQ]szbool | int | Sequence[BoolishT]zbool | int | list[BoolishT]cs8dddt|ts&t|dfiSfdd|DS)z8Validate ``ascending`` kwargs for ``sort_index`` method.FT)r6r7rNcsg|]}t|dfiqSrP)r=)rEitemr#rr jrHz&validate_ascending..)r9rr=rPrrSrrQbs  z str | Noneztuple[bool, bool])closedr cCsFd}d}|durd}d}n$|dkr(d}n|dkr6d}ntd||fS)a% Check that the `closed` argument is among [None, "left", "right"] Parameters ---------- closed : {None, "left", "right"} Returns ------- left_closed : bool right_closed : bool Raises ------ ValueError : if argument is not among valid values FNTleftrightz/Closed has to be either 'left', 'right' or None)r)rUZ left_closedZ right_closedrrrvalidate_endpointsmsrX) inclusiver cCs6d}t|tr"ddddd|}|dur2td|S)aD Check that the `inclusive` argument is among {"both", "neither", "left", "right"}. Parameters ---------- inclusive : {"both", "neither", "left", "right"} Returns ------- left_right_inclusive : tuple[bool, bool] Raises ------ ValueError : if argument is not among valid values N)TT)TF)FT)FF)ZbothrVrWZneitherz?Inclusive has to be either 'both', 'neither', 'left' or 'right')r9r2getr)rYZleft_right_inclusiverrrvalidate_inclusives r[r:)loclengthr cCsZt|std|d||dkr,||7}d|kr@|ksVntd|d||S)z Check that we have an integer between -length and length, inclusive. Standardize negative loc to within [0, length]. The exceptions we raise on failure match np.insert. z loc must be an integer between -z and r)r r IndexError)r\r]rrrvalidate_insert_locsr_cCs&|tjur"|dvr"td|ddS)N)Znumpy_nullableZpyarrowzdtype_backend z= is invalid, only 'numpy_nullable' and 'pyarrow' are allowed.)rZ no_defaultr)Z dtype_backendrrrcheck_dtype_backends   r`)TF)T)"__doc__ __future__rcollections.abcrrtypingrrnumpyrIZ pandas._libsrZpandas.core.dtypes.commonrr r3r:r r rr r$r*r-r1r=rCrMrQrXr[r_r`rrrrs8   &) =-'" !"