o d8y@sPdZddlmZddlmZmZddlmZmZm Z ddl Z ddl m Z mZmZddlmZmZmZmZmZddlmZdd lmZdd lmZmZmZmZdd lm Z m!Z!m"Z"er`dd l#m$Z$dyddZ%dzddZ&d{d|ddZ'gdZ(gd Z)d}d$d%Z*d~d)d*Z+ +    ,    ddd:d;Z, <  ,  ddd=d>Z-dd?d@Z. <  ,    dddEdFZ/   dddGdHZ0 dddLdMZ1dddNdOZ2  P dddSdTZ3ddVdWZ4 +   dddYdZZ5 ddd\d]Z6dd`daZ7e7  dddcddZ8e7  dddedfZ9e7dddgdhZ:e7dddidjZ;e8e9dkZddsdtZ?ddwdxZ@dS)z$ Routines for filling missing data. ) annotations)partialwraps) TYPE_CHECKINGAnycastN)NaTalgoslib) ArrayLikeAxisAxisIntFnpt)import_optional_dependency)infer_dtype_from) is_array_likeis_numeric_v_string_likeis_object_dtypeneeds_i8_conversion)is_valid_na_for_dtypeisnana_value_for_dtype)Indexmasknpt.NDArray[np.bool_]lengthintcCs8t|rt||krtdt|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)valuerrr!X/var/www/html/visualizacion-main/env/lib/python3.10/site-packages/pandas/core/missing.pycheck_value_size1s  r#arrr returnc Cst|\}}tj||d}d}t|rd}t|}t|}||}tj|jtd}|D]1}t||r5q-|rItj|jtj d} |||k| |<n||k} t | tj sZ| j tdd} || O}q-| ri|t|O}|S)a  Return a masking array of same size/shape as arr with entries equaling any member of values_to_mask set to True Parameters ---------- arr : ArrayLike values_to_mask: list, tuple, or scalar Returns ------- np.ndarray[bool] )dtypeFT)r&na_value)rnparrayrrzerosshapeboolrbool_ isinstancendarrayto_numpyany) r$values_to_maskr& potential_naarr_maskna_masknonnarxnew_maskr!r!r" mask_missing@s,       r9Fmethod str | None allow_nearestr,cCsv|dvrdSt|tr|}|dkrd}n|dkrd}ddg}d}|r+|dd}||vr9td |d ||S) N)Nasfreqffillpadbfillbackfillzpad (ffill) or backfill (bfill)nearestz(pad (ffill), backfill (bfill) or nearestzInvalid fill method. Expecting z. Got )r.strlowerappendr)r:r< valid_methods expectingr!r!r"clean_fill_methodys   rH)lineartimeindexvalues)rBzeroslinear quadraticcubic barycentrickroghspline polynomialfrom_derivativespiecewise_polynomialpchipakima cubicsplinerCrKrcKsh|d}|dvr|durtdtt}||vr$td|d|d|dvr2|js2t|d|S) Norder)rSrTz7You must specify the order of the spline or polynomial.zmethod must be one of z. Got 'z ' instead.)rRrVrWz4 interpolation requires that the index be monotonic.)getr NP_METHODS SP_METHODSis_monotonic_increasing)r:rKkwargsrZvalidr!r!r"clean_interp_methods rahowis_valid int | NonecCs|dvsJt|dkrdS|jdkr|jdd}|dkr&|dd}n|dkr9t|d|ddd }||}|sAdS|S) aG Retrieves the index of the first valid value. Parameters ---------- values : ndarray or ExtensionArray 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 )firstlastrNaxisrerf)rndimr1argmax)rLrbrcidxpos chk_notnar!r!r"find_valid_indexs    rpr?forwarddata np.ndarrayrjr Index | Nonelimitlimit_direction limit_area fill_value Any | NonecoercedowncastNonec Kszt|} Wn tyd} Ynw| dur)|durtdt|| |||ddS|dus/Jtd||||||||d| dS)z Wrapper to dispatch to either interpolate_2d or _interpolate_2d_with_fill. Notes ----- Alters 'data' in-place. Nz&Cannot pass both fill_value and method)r:rjrurw)rrrKrjr:rurvrwrxr!)rHrinterpolate_2d_interpolate_2d_with_fill) rrr:rjrKrurvrwrxrzr{r_mr!r!r"interpolate_array_2ds8    rrIc  st|fit|jrt|jdddkr%t|js#tddgd} | vr.func)rrsr%r|) rarr&rrrrDr validate_limit_index_to_interp_indicesr(apply_along_axis) rrrKrjr:rurvrwrxr_valid_limit_directionsvalid_limit_areasrr!rr"r~s@   r~cCsb|j}t|jr |d}|dkr|}ttj|}|St|}|dvr/|jtjkr/t |}|S)zE Convert Index to ndarray of indices to pass to NumPy/SciPy. i8rI)rLrK) _valuesrr&viewrr(r/asarrayobject_r maybe_convert_objects)rKr:xarrindsr!r!r"rjs      rrrrrZc Kst|} | } | s dS| rdStt| } t|d| d} | dur'd} tt| }t|d| d}|dur`_ on Wikiversity. .. [2] Carl de Boor, "A Practical Guide to Splines", Springer-Verlag, 1978. rr)rjrr)rr CubicSpline)rrr7rjrrrrr!r!r"rs M rrLcCst|}|}|sTt|d|d}|durd}t|d|d}|dur't|}t|||d|dkr;d|||d <n|d krMd|d|<||d d<tj||<dSdS) a Apply interpolation and limit_area logic to values along a to-be-specified axis. Parameters ---------- values: np.ndarray Input array. method: str Interpolation method. Could be "bfill" or "pad" limit: int, optional Index limit on interpolation. limit_area: str Limit area for interpolation. Can be "inside" or "outside" Notes ----- Modifies values in-place. rerNrrf)r:rurFrhr)rrrprr}r(r)rLr:rurwrrcrerfr!r!r"_interpolate_with_limit_areas(rr cCs|durttt|||d||dS|dkrddndd}|jdkr6|dkr,td|td |j}t |}||}|d krJt ||d dSt ||d dS) 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. N)r:rurwrcSs|SNr!r7r!r!r"Isz interpolate_2d..cSs|jSr)Trr!r!r"rIsrhz0cannot interpolate on a ndim == 1 with axis != 0rhr?ru) r(rrrrlAssertionErrorrtupler+rH_pad_2d _backfill_2d)rLr:rjrurwtransftvaluesr!r!r"r}s0    r}npt.NDArray[np.bool_] | NonecCs |durt|}|tj}|Sr)rrr(uint8)rLrr!r!r" _fillna_prep]s rrrcs tdfdd }tt|S)z> Wrapper to handle datetime64 and timedelta64 dtypes. NcsPt|jr!|dur t|}|d||d\}}||j|fS|||dS)Nr)rur)rr&rr)rLrurresultrr!r"new_funcns z&_datetimelike_compat..new_funcNN)rrr)rrr!rr"_datetimelike_compatis r(tuple[np.ndarray, npt.NDArray[np.bool_]]cC"t||}tj|||d||fSNr)rr pad_inplacerLrurr!r!r"_pad_1d} rcCrr)rr backfill_inplacerr!r!r" _backfill_1drrcC8t||}t|jrtj|||d||fS ||fSr)rr(rr+r pad_2d_inplacerr!r!r"r  rcCrr)rr(rr+r backfill_2d_inplacerr!r!r"rrrr?rArhrlcCs&t|}|dkr t|Sttd|S)Nrhr)rH _fill_methodsrr)r:rlr!r!r" get_fill_funcsrcCs t|ddS)NT)r<)rH)r:r!r!r"clean_reindex_fill_methods rrcst|t}t}fdd}|dur'|dkr"tt|d}n|||}|durN|dkr1|St||ddd|}tdt|}|dkrN|S||@S)ak Get indexers of values that won't be filled because they exceed the limits. Parameters ---------- invalid : np.ndarray[bool] fw_limit : int or None forward limit to index bw_limit : int or None backward limit to index Returns ------- set of indexers Notes ----- This is equivalent to the more readable, but slower .. code-block:: python def _interp_limit(invalid, fw_limit, bw_limit): for x in np.where(invalid)[0]: if invalid[max(0, x - fw_limit):x + bw_limit + 1].all(): yield x cs`t|}t||dd}tt|d|tt|d|ddkdB}|S)Nrhr)min_rolling_windowrrr(wherecumsum)rruwindowedidxNr!r"inners "z_interp_limit..innerNrrkrh)rrr(rlistr)rfw_limitbw_limitf_idxb_idxr b_idx_invr!rr"rs   rawindowcCsJ|jdd|jd|d|f}|j|jdf}tjjj|||dS)z [True, True, False, True, False], 2 -> [ [True, True], [True, False], [False, True], [True, False], ] Nrkrh)r+strides)r+rr(r stride_tricks as_strided)rrr+rr!r!r"rs$ r)rrrr)r$r r%r)F)r:r;r<r,)r:rCrKrr%rC)rbrCrcrr%rd) r?rNNrqNNFN)rrrsr:rCrjr rKrtrurdrvrCrwr;rxryrzr,r{r;r%r|)rINrqNN)rrrsrKrrjr r:rCrurdrvrCrwr;rxryr%r|)rKrr:rCr%rs)rINrqNNFN)rrsrrsr:r;rurdrvrCrwr;rxryrr,rZrdr%r|)NFN)rr,)NrF)rrrr,)rr)rrrjr )rrN)rjr rr) rLrsr:rCrurdrwr;r%r|)r?rNN) rLrsr:rCrjr rurdrwr;r%r|r)rrr%r)rrr%rr)rLrsrurdrrr%r)rLrsrr)rrr)rlr)r%r;)rr)rrrrr%r)A__doc__ __future__r functoolsrrtypingrrrnumpyr( pandas._libsrr r pandas._typingr r r rrpandas.compat._optionalrpandas.core.dtypes.castrpandas.core.dtypes.commonrrrrpandas.core.dtypes.missingrrrpandasrr#r9rHr\r]rarprr~rrrrrrrr}rrrrrrrrrrrr!r!r!r"s       9  + 9 R q N -/ V1 H       ?