ttjUdZddlmZddlmZddlmZmZmZm Z m Z ddl Z ddl mZddlmZmZmZddlmZmZmZmZmZdd lmZdd lmZdd lmZmZm Z m!Z!m"Z"dd l#m$Z$m%Z%m&Z&dd l'm(Z(m)Z)m*Z*erddl+m,Z,ddlm-Z-ddl.m/Z/edZ0de1d<d|dZ2d}dZ3e ddd~d$Z4e dd(Z4d)ddd+Z4gd,Z5gd-Z6dd1Z7dd5Z8dd8Z9dd<Z:dd?Z;dd@Z< dddKZ=ddLZ> dddQZ? dddUZ@ ddd[ZA ddd\ZB dddaZC ddddZD dddfZEddiZFeF dddkZGeF dddlZHeF dddmZIeF dddnZJddpZKddqZLeGeHdrZMddduZNddwZOdd{ZPdS)z$ Routines for filling missing data. ) annotations)wraps) TYPE_CHECKINGAnyLiteralcastoverloadN) is_nan_na)NaTalgoslib) ArrayLikeAxisIntF ReindexMethodnpt)import_optional_dependency)infer_dtype_from) is_array_like is_bool_dtypeis_numeric_dtypeis_object_dtypeneeds_i8_conversion) ArrowDtypeBaseMaskedDtypeDatetimeTZDtype)is_valid_na_for_dtypeisnana_value_for_dtype)Callable) TypeAlias)Index) not-a-knotclampednaturalperiodicr!_CubicBCmasknpt.NDArray[np.bool_]lengthintct|r=t||kr"tdt|d|||}|S)zJ Validate the size of the values passed to ExtensionArray.fillna. z'Length of 'value' does not match. Got (z ) expected )rlen ValueError)valuer(r*s Q/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/pandas/core/missing.pycheck_value_sizer1>skU u::  &#e**&&#&& d  Larrrreturnct|\}}t|jttfrt j|rtj|rts|jj dkrt|jtr1tj|j | z}|Sddl m}||jd}|S|jj dvr"tj|jt*}|St|rt|Stj|jt*}t-|jr)t/|jst j|rnt/|jr$t-|rt j|snt-|jrt|t2rnrt5|jr t|}|||k||<n>||k}t|tjs|t*d}|}|S)a? Return a masking array of same size/shape as arr with entries equaling value set to True. Parameters ---------- arr : ArrayLike value : scalar-like Caller has ensured `not is_list_like(value)` and that it can be held by `arr`. Returns ------- np.ndarray[bool] frNFiudtype)r9na_value)r isinstancer9rrr is_floatnpisnanr kind_datarpyarrow.computecomputeis_nan _pa_array fill_nullto_numpyzerosshapeboolrris_boolstrrndarray)r3r/r9r(pcarr_masknew_masks r0 mask_missingrPMs` $E**LE5 39 ;<< L   HUOO  9>S #)_55 x **chhjj[8 -,,,,,yy//99%@@IIKK Y^t # #8CIT222DK E{{Cyy 8CIT * * *D##ci(( K   ci  %5e%<%<EH[QVEWEW #) $ $E3)?)?  # # II:X%/X%<(BJ// E((te(DDH Kr2. allow_nearestmethod,Literal['ffill', 'pad', 'bfill', 'backfill']rRLiteral[False]Literal['pad', 'backfill']cdSNrSrRs r0clean_fill_methodr[s "%r27Literal['ffill', 'pad', 'bfill', 'backfill', 'nearest'] Literal[True]%Literal['pad', 'backfill', 'nearest']cdSrXrYrZs r0r[r[s -0Cr2FrIct|tr%|}|dkrd}n|dkrd}ddg}d}|r|dd}||vrt d|d ||S) Nffillpadbfillbackfillzpad (ffill) or backfill (bfill)nearestz(pad (ffill), backfill (bfill) or nearestzInvalid fill method. Expecting z. Got )r;rKlowerappendr.)rSrR valid_methods expectings r0r[r[s &#  W  FF w  FJ'M1I?Y'''>  ]""T9TTFTTUUU Mr2)lineartimeindexvalues)rezeroslinear quadraticcubic barycentrickroghspline polynomialfrom_derivativespiecewise_polynomialpchipakima cubicsplinerKrlr"c |d}|dvr|tdttz}||vrtd|d|d|dvr|jst|d|S) Norder)rtruz7You must specify the order of the spline or polynomial.zmethod must be one of z. Got 'z ' instead.)rsrwrxz4 interpolation requires that the index be monotonic.)getr. NP_METHODS SP_METHODSis_monotonic_increasing)rSrlkwargsr|valids r0clean_interp_methodrs JJw  E )))emRSSS  #E UR%RRRRRSSS ;;;, OOO  Mr2howis_valid int | NonecH|dvsJt|dkrdS|jdkr|d}|dkr|dd}n6|dkr0t|dz |ddd z }||}|sdS|S) a+ Retrieves the positional index of the first valid value. Parameters ---------- how : {'first', 'last'} Use this parameter to change between the first or last valid index. is_valid: np.ndarray Mask to find na_values. Returns ------- int or None )firstlastrNaxisrr)r-ndimanyargmax)rridxpos chk_notnas r0find_valid_indexrs # # # # # 8}}t}<rkrlrmremMz9Index column must be numeric or datetime type when using z_ method other than linear. Try setting a numeric or datetime index column before interpolating. Can not interpolate with method=rzkInterpolation with NaNs in the index has not been implemented. Try filling those NaNs before interpolating.)pandasrr-rr9r;rr is_np_dtyper~rr.rrNotImplementedError)rSrlrmethodsis_numeric_or_datetimers r0get_interp_indexrHs %%%%%% 3u::&&888 U[ ) ) 2%+77 2u{D11  Z' U??W$$-C$ %#%%%IIIIJJ J E{{ ! /   Lr2rjrdata np.ndarrayrrlimit fill_value Any | NoneNonec  t|fi t|jrt|jddkr%t |jst ddt t| tj dt| d   fd } tj | ||dS)z Column-wise application of _interpolate_1d. Notes ----- Alters 'data' in-place. The signature does differ from _interpolate_1d because it only includes what is needed for Block.interpolate. F)compatrkzStime-weighted interpolation only works on Series or DataFrames with a DatetimeIndexrmN)nobsryvaluesrr4rc 4td|dd dS)NF) indicesrrSrrrr bounds_errorr(rY)_interpolate_1d) rrrrrlimit_area_validatedrr(rSs r0funcz$interpolate_2d_inplace..funcsP  ++!  r2)rrr4r) rrr9rrr.rrr validate_limit_index_to_interp_indicesr=apply_along_axis) rrlrrSrrrrr(rrrrs ``` ``` @@r0interpolate_2d_inplacerks'.00000Z44B' 5AAA  "5;//    .??O.z::  d% 8 8 8E&uf55G             dD)))))r2c.|j}t|jr|d}|dkr|}t t j|}nAt j|}|dvr)|jt jkrtj |}|S)zE Convert Index to ndarray of indices to pass to NumPy/SciPy. i8rj)rmrl) _valuesrr9viewrr=rLasarrayobject_r maybe_convert_objects)rlrSxarrindss r0rrs =D4:&&yy BJ%%z$ ( ( (zRZ''066 Kr2rrrr|c  ,| | } nt|} | } | sdS| rdStj| } t d| }|d}tj|}t d| }|t|}tjd|zt| }|dkr%tj|t| |d}nN|dkr%tj|t| d|}n#tj t| ||}|d kr+tj||}tj||}nI|d krCtj | |d }tj ||d }tj||}|j j d v}|r|d}|tvrRtj|| }tj|| || ||| ||| <n)t%|| || || f||||d| || <| d| dd<d | |<n!|rt&j||<ntj||<dS)a Logic for the 1-d interpolation. The input indices and yvalues will each be 1-d arrays of the same length. Bounds_error is currently hardcoded to False since non-scipy ones don't take it as an argument. Notes ----- Fills 'yvalues' in-place. Nr)rrrrrrrrrT assume_uniquerr)rSrrr|F)rrallr= flatnonzeroraranger-union1d _interp_limitunique setdiff1dr9r?rr~argsortinterp_interpolate_scipy_wrapperr r/nan)rrrSrrrrrr|r(rinvalidrall_nansfirst_valid_index start_nanslast_valid_indexend_nans preserve_nansmid_nansis_datetimelikeindexers r0rrs0 w-- HE 99;; yy{{~g&&H(WuEEE ,--J'FUCCCw<<y--s5zz::H)## :}WeQ/O/OPP J & & 8]7Au-M-MNN  -"F"FGG X =*==  =(;; y <*DIII<($GGG =(;; m(D0O%,,t$$ *WU^,,9 G genW5wu~g7N  6 EN EN G   !%       QQQ"] (!$ !#  Fr2xynew_xc |d}td|ddlm} tj|}| j| jtttt| j d} gd} || vr1|dkr|} n|} | ||| || } | |}n|d krDt|s|dkrtd || j||fd |i|} | |}n|jjs|}|jjs|}|jjs|}| |d } | td|d|dd | |||fi|}|S)z Passed off to scipy.interpolate.interp1d. method is scipy's kind. Returns an array interpolated at new_x. Add any new methods to the list in _clean_interp_method. z interpolation requires SciPy.scipy)extrar interpolate)rrrsrvrwrzryrx)rernrorprqruru)r?rrrtz;order needs to be specified and greater than 0; got order: kNrrdowncast)rrrr=rbarycentric_interpolatekrogh_interpolate_from_derivatives_cubicspline_interpolate_akima_interpolatepchip_interpolateinterp1drr.UnivariateSplineflags writeablecopyr}pop)rrrrSrrr|rrr alt_methodsinterp1d_methodsr?terpnew_ys r0rr1s 5 5 5Ewe4444!!!!!! Ju  E#:.- 1/#.99K!!! \ ! !DDD## qt $  U  8   ;; 5A::UeUU ,{+AqDDEDVDDU w  Aw  A{$ !JJLLEvt,, <IIIIJJ J  :t$$$Q5++F++ Lr2xiyiderint | list[int] | None extrapolatecddlm}|jj}|||dd||}||S)a Convenience function for interpolate.BPoly.from_derivatives. Construct a piecewise polynomial in the Bernstein basis, compatible with the specified values and derivatives at breakpoints. Parameters ---------- xi : array-like sorted 1D array of x-coordinates yi : array-like or list of array-likes yi[i][j] is the j-th derivative known at xi[i] order: None or int or array-like of ints. Default: None. Specifies the degree of local polynomials. If not None, some derivatives are ignored. der : int or list How many derivatives to extract; None for all potentially nonzero derivatives (that is a number equal to the number of points), or a list of derivatives to extract. This number includes the function value as 0th derivative. extrapolate : bool, optional Whether to extrapolate to ouf-of-bounds points based on first and last intervals, or to return NaNs. Default: True. See Also -------- scipy.interpolate.BPoly.from_derivatives Returns ------- y : scalar or array-like The result, of length R or length M or M by R. rrrr)ordersr )rrBPolyrvreshape) rrrr|rr rrSms r0rr~sWR"!!!!!  /Fr2::b!$$U LLLA 1Q44Kr2cXddlm}||||}|||S)a Convenience function for akima interpolation. xi and yi are arrays of values used to approximate some function f, with ``yi = f(xi)``. See `Akima1DInterpolator` for details. Parameters ---------- xi : np.ndarray A sorted list of x-coordinates, of length N. yi : np.ndarray A 1-D array of real values. `yi`'s length along the interpolation axis must be equal to the length of `xi`. If N-D array, use axis parameter to select correct axis. x : np.ndarray Of length M. der : int, optional How many derivatives to extract. This number includes the function value as 0th derivative. axis : int, optional Axis in the yi array corresponding to the x-coordinate values. See Also -------- scipy.interpolate.Akima1DInterpolator Returns ------- y : scalar or array-like The result, of length R or length M or M by R, rrr)nu)rrAkima1DInterpolator)rrrrrrPs r0rrsCP"!!!!!''BT'::A 1Q3<<<r2r#bc_type_CubicBC | tuple[Any, Any]!Literal['periodic'] | bool | NonecXddlm}||||||}||S)ag Convenience function for cubic spline data interpolator. See `scipy.interpolate.CubicSpline` for details. Parameters ---------- xi : np.ndarray, shape (n,) 1-d array containing values of the independent variable. Values must be real, finite and in strictly increasing order. yi : np.ndarray Array containing values of the dependent variable. It can have arbitrary number of dimensions, but the length along ``axis`` (see below) must match the length of ``x``. Values must be finite. x : np.ndarray, shape (m,) axis : int, optional Axis along which `y` is assumed to be varying. Meaning that for ``x[i]`` the corresponding values are ``np.take(y, i, axis=axis)``. Default is 0. bc_type : string or 2-tuple, optional Boundary condition type. Two additional equations, given by the boundary conditions, are required to determine all coefficients of polynomials on each segment [2]_. If `bc_type` is a string, then the specified condition will be applied at both ends of a spline. Available conditions are: * 'not-a-knot' (default): The first and second segment at a curve end are the same polynomial. It is a good default when there is no information on boundary conditions. * 'periodic': The interpolated functions is assumed to be periodic of period ``x[-1] - x[0]``. The first and last value of `y` must be identical: ``y[0] == y[-1]``. This boundary condition will result in ``y'[0] == y'[-1]`` and ``y''[0] == y''[-1]``. * 'clamped': The first derivative at curves ends are zero. Assuming a 1D `y`, ``bc_type=((1, 0.0), (1, 0.0))`` is the same condition. * 'natural': The second derivative at curve ends are zero. Assuming a 1D `y`, ``bc_type=((2, 0.0), (2, 0.0))`` is the same condition. If `bc_type` is a 2-tuple, the first and the second value will be applied at the curve start and end respectively. The tuple values can be one of the previously mentioned strings (except 'periodic') or a tuple `(order, deriv_values)` allowing to specify arbitrary derivatives at curve ends: * `order`: the derivative order, 1 or 2. * `deriv_value`: array-like containing derivative values, shape must be the same as `y`, excluding ``axis`` dimension. For example, if `y` is 1D, then `deriv_value` must be a scalar. If `y` is 3D with the shape (n0, n1, n2) and axis=2, then `deriv_value` must be 2D and have the shape (n0, n1). extrapolate : {bool, 'periodic', None}, optional If bool, determines whether to extrapolate to out-of-bounds points based on first and last intervals, or to return NaNs. If 'periodic', periodic extrapolation is used. If None (default), ``extrapolate`` is set to 'periodic' for ``bc_type='periodic'`` and to True otherwise. See Also -------- scipy.interpolate.CubicHermiteSpline Returns ------- y : scalar or array-like The result, of shape (m,) References ---------- .. [1] `Cubic Spline Interpolation `_ on Wikiversity. .. [2] Carl de Boor, "A Practical Guide to Splines", Springer-Verlag, 1978. rr)rrr )rr CubicSpline)rrrrrr rrs r0rrsKZ"!!!!! BT7    A 1Q44Kr2rbrmc |dkrdnd}|jdkr3|dkrtd|dg|jR}t |}||}t |d}||||d S) a Perform an actual interpolation of values, values will be make 2-d if needed fills inplace, returns the result. Parameters ---------- values: np.ndarray Input array. method: str, default "pad" Interpolation method. Could be "bfill" or "pad" axis: 0 or 1 Interpolation axis limit: int, optional Index limit on interpolation. limit_area: str, optional Limit area for interpolation. Can be "inside" or "outside" Notes ----- Modifies values in-place. rc|SrXrYrs r0z)pad_or_backfill_inplace..Qsr2c|jSrX)Trs r0rz)pad_or_backfill_inplace..Qsr2rz1cannot interpolate on an ndim == 1 with axis != 0r)r)rrN)rAssertionErrorr rHr[ get_fill_func)rmrSrrrtransftvaluesrs r0pad_or_backfill_inplacer"5s8#aiikkkmmF{a 199 !TUU U 2V\ 2 233 v & &FfVnnG a ( ( (DD*555555r2npt.NDArray[np.bool_] | Nonec(|t|}|SrX)r)rmr(s r0 _fillna_prepr%as  |F|| Kr2rrclt ddfd }tt|S) z> Wrapper to handle datetime64 and timedelta64 dtypes. Nrrrrct|jrR|t|}|d|||\}}||j|fS||||S)Nr)rrr()rr9rr)rmrrr(resultrs r0new_funcz&_datetimelike_compat..new_funcqs v| , , 3|F||4 D!!:DLFD;;v|,,d2 2tF%JTJJJJr2NNN)rrrr)rrr)rr)s` r0_datetimelike_compatr+ls\  4[[!:>  KKKKKK[K$ 8  r2(tuple[np.ndarray, npt.NDArray[np.bool_]]ct||}|$|st||tj|||||fSN)r)r%r_fill_limit_area_1dr pad_inplacermrrr(s r0_pad_1dr2sX  % %DdhhjjD*--- fd%0000 4<r2ct||}|$|st||tj|||||fSr.)r%rr/r backfill_inplacer1s r0 _backfill_1dr5sX  % %DdhhjjD*--- 64u5555 4<r2ct||}|t|||jrtj|||||fSr.)r%_fill_limit_area_2dsizer pad_2d_inplacer1s r0_pad_2dr:sU  % %DD*--- {8 VT7777 4<r2ct||}|t|||jrtj|||n ||fSr.)r%r7r8r backfill_2d_inplacer1s r0 _backfill_2dr=s]  % %DD*--- {  !&$e<<<<< 4<r2Literal['outside', 'inside']c|}|}t||dddz dz }|dkrd|d|<d||dzd<dS|dkr d||dz|<dSdS)aPrepare 1d mask for ffill/bfill with limit_area. Caller is responsible for checking at least one value of mask is False. When called, mask will no longer faithfully represent when the corresponding are NA or not. Parameters ---------- mask : np.ndarray[bool, ndim=1] Mask representing NA values when filling. limit_area : { "outside", "inside" } Whether to limit filling to outside or inside the outer most non-NA value. NrrrFr)rr-)r(rneg_maskrrs r0r/r/s uH OO  E x==8DDbD>0022 2Q 6DXVeV  TAXZZ y !&UQY  ! r2c|j}|dkrVtj|dtj|dddddddz}nWtj|dtj|dddddddz}d||j<dS)aPrepare 2d mask for ffill/bfill with limit_area. When called, mask will no longer faithfully represent when the corresponding are NA or not. Parameters ---------- mask : np.ndarray[bool, ndim=1] Mask representing NA values when filling. limit_area : { "outside", "inside" } Whether to limit filling to outside or inside the outer most non-NA value. rrrNrF)rr=maximum accumulate)r(rr@la_masks r0r7r7swHY J ! !( ! 3 3j##HTTrTN#;;DDbDA B Z " "8! " 4 4 4z$$Xddd^!$<.inner5sE1q5!!6';;GUQYOOSSTUVVj HX  q !E ) Hw{{++3355: ; ;A >   r2NrFrrr)rr+)r-r=arrayint64rR intersect1d)rrKrLf_idxb_idxrrWrVs @r0rrsB G A HRrx ( ( (E HRrx ( ( (EM q==HW%%a(E!MME'8,,E q==LEEE'$$B$-:::E1}} >%m D D DDr2)r(r)r*r+)r3rr4r))rSrTrRrUr4rV)rSr\rRr]r4r^)rSr\rRrIr4r^)rSrKrlr"r4rK)rrKrr)r4r)rrKr4r)rrr4r)rrrSrKr4r)rlr"r4r")rjNrNNN)rrrlr"rrrSrKrrrrKrrrrr4r)rlr"rSrKr4r)rjNrNNFNN)rrrrrSrKrrrrKrrrrrrIr|rr4r)NFN) rrrrrrrSrKrrI)NrF) rrrrrrrrr rI)rr) rrrrrrrr+rr)rr#N)rrrrrrrrrrr rr4r)rbrNN) rmrrSrVrrrrrrr4rrX)r(r#r4r))rrr4rr*) rmrrrrrr(r#r4r,)rrrrr(r#)r(r)rr>r4r)r)rr+)r4rH)rr)rKrrLrr4r)Q__doc__ __future__r functoolsrtypingrrrrr numpyr=pandas._configr pandas._libsr r r pandas._typingrrrrrpandas.compat._optionalrpandas.core.dtypes.castrpandas.core.dtypes.commonrrrrrpandas.core.dtypes.dtypesrrrpandas.core.dtypes.missingrrrcollections.abcr r!rr"r'__annotations__r1rPr[r~rrrrrrrrrrrrrrr"r%r+r2r5r:r=r/r7rGrrJrrYr2r0rls9#"""""$$$$$$ ?>>>>>444444  R((((((      !"PQHQQQQ    LLLL^ %(%%%%% % 000 0 43 2 2  $&$$$$N        *    N$!! =*=*=*=*=*@2$6:! m m m m m j JJJJJb "# /////l ,,,,,f*659 SSSSSp*/6: )6)6)6)6)6Z2666:)-     6:)-     6:)-     6:)- $''''4> \:: >>>>>9999 @E@E@E@E@E@Er2